Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Series

Physical Sciences and Mathematics

Institution
Keyword
Publication Year
Publication
File Type

Articles 1 - 30 of 15382

Full-Text Articles in Engineering

Tribocorrosion And Metal Release From Austenitic Stainless Steels 304 And 201 In Simulated Cassava Food Contact, Robert Addai, Temitope E. Olowoyo, Thalia E. Standish, Jeffrey Daniel Henderson, Ubong Eduok, Yolanda Hedberg Jul 2024

Tribocorrosion And Metal Release From Austenitic Stainless Steels 304 And 201 In Simulated Cassava Food Contact, Robert Addai, Temitope E. Olowoyo, Thalia E. Standish, Jeffrey Daniel Henderson, Ubong Eduok, Yolanda Hedberg

Chemistry Publications

Cassava is the third most significant calorie source in the tropics. Its processing has changed from traditional methods to stainless steel processing machines. This study investigated the influence of cassava on metal release from two common stainless steels, ASTM 304 and 201, with and without friction, and on tribocorrosion (multianalytically) of 304. Cassava was relatively corrosive and hindered repassivation of the surface oxide of stainless steel, but it also acted as a lubricant against mechanical friction. The combined action of friction and cassava caused a significant increase in iron, chromium, nickel, and manganese release from the stainless steels (30–35- fold …


Understanding The Impact Of Microplastic Contamination On Soil Quality And Eco-Toxicological Risks In Horticulture: A Comprehensive Review, N. P. Gayathri, Geena Prasad, Vaishna Prabhakaran, Vishnu Priya Jun 2024

Understanding The Impact Of Microplastic Contamination On Soil Quality And Eco-Toxicological Risks In Horticulture: A Comprehensive Review, N. P. Gayathri, Geena Prasad, Vaishna Prabhakaran, Vishnu Priya

Research outputs 2022 to 2026

The horticulture sector, essential for global food production, confronts significant challenges with prevalent pollutants, mainly microplastics. The presence of microplastics in the food chain has induced physiological stress and a multifactorial food safety concern. The complexity of the problem, arising from intricate interactions among microplastics, organisms, and ecosystems, poses a substantial challenge to food safety, necessitating an immediate strategic perspective due to the associated risks to human health and eco-toxicology. Significant knowledge gaps persist regarding their impact on terrestrial ecosystems, especially in horticulture. This study addresses the urgent need to comprehend the implications of microplastics on soil health, eco-toxicological risks, …


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 May 2024

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 …


Data Engineering: Building Software Efficiency In Medium To Large Organizations, Alessandro De La Torre Apr 2024

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.


Microplastics Fouling Mitigation In Forward Osmosis Membranes By The Molecular Assembly Of Sulfobetaine Zwitterion, Javad Farahbakhsh, Mitra Golgoli, Mehdi Khiadani, Amir Razmjou, Masoumeh Zargar Apr 2024

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 Apr 2024

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 Apr 2024

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 …


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 Apr 2024

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, …


Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy Apr 2024

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 …


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 Mar 2024

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 (Hf1−xZrxO2) 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 Hf1−xZrxO2 require further investigation. In this paper, we present a statistical study and a model that relates Zr concentration (x), film thickness (tf), and annealing temperature (Ta) with the remanent polarization (Pr) in tungsten (W)-capped Hf1−xZrxO2. …


Lrs: Enhancing Adversarial Transferability Through Lipschitz Regularized Surrogate, Tao Wu, Tony Tie Luo, Donald C. Wunsch Mar 2024

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 …


Cr-Sam: Curvature Regularized Sharpness-Aware Minimization, Tao Wu, Tony Tie Luo, Donald C. Wunsch Mar 2024

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, …


Will Saf Turbocharge The Corn Ethanol Market?, Richard Perrin, Lilyan Fulginiti, Felipe Miranda De Souza Almeida Mar 2024

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 Mar 2024

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, KFE8L and KFE8D, 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 Mar 2024

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 …


Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor Mar 2024

Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor

Faculty Publications

Once realized, autonomous aerial refueling will revolutionize unmanned aviation by removing current range and endurance limitations. Previous attempts at establishing vision-based solutions have come close but rely heavily on near perfect extrinsic camera calibrations that often change midflight. In this paper, we propose dual object detection, a technique that overcomes such requirement by transforming aerial refueling imagery directly into receiver aircraft reference frame probe-to-drogue vectors regardless of camera position and orientation. These vectors are precisely what autonomous agents need to successfully maneuver the tanker and receiver aircraft in synchronous flight during refueling operations. Our method follows a common 4-stage process …


Adsorption Of Crystal Violet Dye From Synthetic Wastewater By Ball-Milled Royal Palm Leaf Sheath, Neloy Sen, Nawrin Rahman Shefa, Kismot Reza, Sk Md Ali Zaker Shawon, Md. Wasikur Rahman Mar 2024

Adsorption Of Crystal Violet Dye From Synthetic Wastewater By Ball-Milled Royal Palm Leaf Sheath, Neloy Sen, Nawrin Rahman Shefa, Kismot Reza, Sk Md Ali Zaker Shawon, Md. Wasikur Rahman

Physics and Astronomy Faculty Publications and Presentations

The current study shows that using a batch approach to remove crystal violet dye from synthetic wastewater is feasible when using royal palm leaf sheath powder as an adsorbent. In order to investigate the effects of many parameters, including starting concentration, pH effect, dye concentration, adsorbent dose, contact time, and temperature, experiments were carried out under various operating conditions. Maximum removal was obtained at pH 6 and at a concentration of 100 ppm, which are considered as ideal values. The influence of pH and dye concentration was shown to be substantial. Langmuir, Freundlich, and Temkin isotherm models were fitted to …


Analyzing Biomedical Datasets With Symbolic Tree Adaptive Resonance Theory, Sasha Petrenko, Daniel B. Hier, Mary A. Bone, Tayo Obafemi-Ajayi, Erik J. Timpson, William E. Marsh, Michael Speight, Donald C. Wunsch Mar 2024

Analyzing Biomedical Datasets With Symbolic Tree Adaptive Resonance Theory, Sasha Petrenko, Daniel B. Hier, Mary A. Bone, Tayo Obafemi-Ajayi, Erik J. Timpson, William E. Marsh, Michael Speight, Donald C. Wunsch

Chemistry Faculty Research & Creative Works

Biomedical Datasets Distill Many Mechanisms Of Human Diseases, Linking Diseases To Genes And Phenotypes (Signs And Symptoms Of Disease), Genetic Mutations To Altered Protein Structures, And Altered Proteins To Changes In Molecular Functions And Biological Processes. It Is Desirable To Gain New Insights From These Data, Especially With Regard To The Uncovering Of Hierarchical Structures Relating Disease Variants. However, Analysis To This End Has Proven Difficult Due To The Complexity Of The Connections Between Multi-Categorical Symbolic Data. This Article Proposes Symbolic Tree Adaptive Resonance Theory (START), With Additional Supervised, Dual-Vigilance (DV-START), And Distributed Dual-Vigilance (DDV-START) Formulations, For The Clustering Of …


Continual Online Learning-Based Optimal Tracking Control Of Nonlinear Strict-Feedback Systems: Application To Unmanned Aerial Vehicles, Irfan Ganie, Sarangapani Jagannathan Mar 2024

Continual Online Learning-Based Optimal Tracking Control Of Nonlinear Strict-Feedback Systems: Application To Unmanned Aerial Vehicles, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

A novel optimal trajectory tracking scheme is introduced for nonlinear continuous-time systems in strict feedback form with uncertain dynamics by using neural networks (NNs). The method employs an actor-critic-based NN back-stepping technique for minimizing a discounted value function along with an identifier to approximate unknown system dynamics that are expressed in augmented form. Novel online weight update laws for the actor and critic NNs are derived by using both the NN identifier and Hamilton-Jacobi-Bellman residual error. A new continual lifelong learning technique utilizing the Fisher Information Matrix via Hamilton-Jacobi-Bellman residual error is introduced to obtain the significance of weights in …


Field Research Report: Results From The Enreec Vri Field For The 2021, 2022, And 2023 Crop Seasons, Derek M. Heeren, Ali T. Mohammed, Eric Wilkening, Christopher M. U. Neale, Alan L. Boldt, Ankit Chandra, Precious Nneka Amori, Ivo Z. Goncalves, Yeyin Shi, Guillermo R. Balboa Mar 2024

Field Research Report: Results From The Enreec Vri Field For The 2021, 2022, And 2023 Crop Seasons, Derek M. Heeren, Ali T. Mohammed, Eric Wilkening, Christopher M. U. Neale, Alan L. Boldt, Ankit Chandra, Precious Nneka Amori, Ivo Z. Goncalves, Yeyin Shi, Guillermo R. Balboa

Department of Biological Systems Engineering: Conference Presentations and White Papers

Long-term irrigation management research has been conducted from 2014 to 2023 for corn and soybean at the Eastern Nebraska Research, Extension, and Education Center (ENREEC) Variable Rate Irrigation (VRI) Field located in subhumid east-central Nebraska (in the Lower Platte North Natural Resources District). The objective of this report was to present the overall results from the VRI Field for 2021 to 2023. Across the three growing seasons, there were the following irrigation treatments: Best Management Practice (BMP), 50% BMP, 125% BMP, rainfed, Spatial ET Modeling Interface (SETMI), SDD1, SDD2, machine-learning-based Cyber-Physical System (CPS), a student team recommended rate, and industry …


T-Pickseer: Visual Analysis Of Taxi Pick-Up Point Selection Behavior, Shuxian Gu, Yemo Dai, Zezheng Feng, Yong Wang, Haipeng Zeng Mar 2024

T-Pickseer: Visual Analysis Of Taxi Pick-Up Point Selection Behavior, Shuxian Gu, Yemo Dai, Zezheng Feng, Yong Wang, Haipeng Zeng

Research Collection School Of Computing and Information Systems

Taxi drivers often take much time to navigate the streets to look for passengers, which leads to high vacancy rates and wasted resources. Empty taxi cruising remains a big concern for taxi companies. Analyzing the pick-up point selection behavior can solve this problem effectively, providing suggestions for taxi management and dispatch. Many studies have been devoted to analyzing and recommending hotspot regions of pick-up points, which can make it easier for drivers to pick-up passengers. However, the selection of pick-up points is complex and affected by multiple factors, such as convenience and traffic management. Most existing approaches cannot produce satisfactory …


A Bayesian Approach For Lifetime Modeling And Prediction With Multi-Type Group-Shared Missing Covariates, Hao Zeng, Xuxue Sun, Kuo Wang, Yuxin Wen, Wujun Si, Mingyang Li Feb 2024

A Bayesian Approach For Lifetime Modeling And Prediction With Multi-Type Group-Shared Missing Covariates, Hao Zeng, Xuxue Sun, Kuo Wang, Yuxin Wen, Wujun Si, Mingyang Li

Engineering Faculty Articles and Research

In the field of reliability engineering, covariate information shared among product units within a specific group (e.g., a manufacturing batch, an operating region), such as operating conditions and design settings, exerts substantial influence on product lifetime prediction. The covariates shared within each group may be missing due to sensing limitations and data privacy issues. The missing covariates shared within the same group commonly encompass a variety of attribute types, such as discrete types, continuous types, or mixed types. Existing studies have mainly considered single-type missing covariates at the individual level, and they have failed to thoroughly investigate the influence of …


The Behavior Of ½⟨111⟩ Screw Dislocations In W–Mo Alloys Analyzed Through Atomistic Simulations, Lucas A. Heaton, Kevin Chu, Adib J. Samin Feb 2024

The Behavior Of ½⟨111⟩ Screw Dislocations In W–Mo Alloys Analyzed Through Atomistic Simulations, Lucas A. Heaton, Kevin Chu, Adib J. Samin

Faculty Publications

Analyzing plastic flow in refractory alloys is relevant to many different commercial and technological applications. In this study, screw dislocation statics and dynamics were studied for various compositions of the body-centered cubic binary alloy tungsten–molybdenum (W–Mo). The core structure did not appear to change for different alloy compositions, consistent with the literature. The pure tungsten and pure molybdenum samples had the lowest plastic flow, while the highest dislocation velocities were observed for equiatomic, W0.5Mo0.5 alloys. In general, dislocation velocities were found to largely align with a well-established dislocation mobility phenomenological model supporting two discrete dislocation mobility regimes, …


Brain-Inspired Continual Learning: Robust Feature Distillation And Re-Consolidation For Class Incremental Learning, Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool Feb 2024

Brain-Inspired Continual Learning: Robust Feature Distillation And Re-Consolidation For Class Incremental Learning, Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool

Henry M. Rowan College of Engineering Faculty Scholarship

Artificial intelligence and neuroscience have a long and intertwined history. Advancements in neuroscience research have significantly influenced the development of artificial intelligence systems that have the potential to retain knowledge akin to humans. Building upon foundational insights from neuroscience and existing research in adversarial and continual learning fields, we introduce a novel framework that comprises two key concepts: feature distillation and re-consolidation. The framework distills continual learning (CL) robust features and rehearses them while learning the next task, aiming to replicate the mammalian brain's process of consolidating memories through rehearsing the distilled version of the waking experiences. Furthermore, the proposed …


Ai-Based Investigation And Mitigation Of Rain Effect On Channel Performance With Aid Of A Novel 3d Slot Array Antenna Design For High Throughput Satellite System, Ali M. Al-Saegh, Fatma Taher, Taha A. Elwi, Mohammad Alibakhshikenari, Bal S. Virdee, Osama Abdullah, Salahuddin Khan, Patrizia Livreri, Abdulmajeed Al-Jumaily, Mohamed Fathy Abo Sree, Arkan Mousa Majeed, Lida Kouhalvandi, Zaid A. Abdul Hassain, Giovanni Pau Feb 2024

Ai-Based Investigation And Mitigation Of Rain Effect On Channel Performance With Aid Of A Novel 3d Slot Array Antenna Design For High Throughput Satellite System, Ali M. Al-Saegh, Fatma Taher, Taha A. Elwi, Mohammad Alibakhshikenari, Bal S. Virdee, Osama Abdullah, Salahuddin Khan, Patrizia Livreri, Abdulmajeed Al-Jumaily, Mohamed Fathy Abo Sree, Arkan Mousa Majeed, Lida Kouhalvandi, Zaid A. Abdul Hassain, Giovanni Pau

All Works

Rain attenuation poses a significant challenge for high-throughput communication systems. In response, this paper introduces an artificial intelligence (AI) model designed for predicting and mitigating rain-induced impairments in high-throughput satellite (HTS) to land channels. The model is based on three AI algorithms developed using 3D antenna design to characterize, analyze, and mitigate rain-induced attenuation, optimizing channel quality specifically in the United Arab Emirates (UAE). The study evaluates various parameters, including rain-specific attenuation, effective slant path through rain, rain-induced attenuation, signal carrier-to-noise ratio, and symbol error rate, for five conventional modulation schemes: Quadrature Phase-Shift Keying (QPSK), 8-Phase Shift Keying (8-PSK), 16-Quadrature …


Pisa Printing Microneedles With Controllable Aqueous Dissolution Kinetics, Aaron Priester, Jimmy Yeng, Yuwei Zhang, Krista Hilmas, Risheng Wang, Anthony J. Convertine Feb 2024

Pisa Printing Microneedles With Controllable Aqueous Dissolution Kinetics, Aaron Priester, Jimmy Yeng, Yuwei Zhang, Krista Hilmas, Risheng Wang, Anthony J. Convertine

Chemistry Faculty Research & Creative Works

This study focused on the development of high-resolution polymeric structures using polymer-induced self-assembly (PISA) printing with commercially available digital light-processing (DLP) printers. Significantly, soluble solids could be 3D-printed using this methodology with controllable aqueous dissolution rates. This was achieved using a highly branched macrochain transfer agent (macro-CTA) containing multiple covalently attached CTA groups. In this work, the use of acrylamide as the self-assembling monomer in isopropyl alcohol was explored with the addition of N-(butoxymethyl)acrylamide to modulate the aqueous dissolution kinetics. PISA-printed microneedles were observed to have feature sizes as small as 27 μm, which was close to the resolution limit …


Extraterrestrial Life: The Possibility Of A Human-Alien Interaction, Ariana M. Piscoya Feb 2024

Extraterrestrial Life: The Possibility Of A Human-Alien Interaction, Ariana M. Piscoya

CAFE Symposium 2024

We all have heard of at least one case where someone assured having seen a flying extraterrestrial object. There are thousands of thousands of videos we can find online that “prove” the existence of aliens. In the hypothetical case where aliens are really out there, why haven't we been able to talk to them and look at them face-to-face? A human-extraterrestrial interaction has not yet been achieved for two reasons. First, alien energy is much more powerful than that of humans, so it would require thousands of thousands of years for the human race to develop a technology able to …


Emoji Use In Social Media Posts: Relationships With Personality Traits And Word Usage, Shelia Kennison, Kameryn Fritz, Maria Andrea Hurtado Morales, Eric Chan-Tin Feb 2024

Emoji Use In Social Media Posts: Relationships With Personality Traits And Word Usage, Shelia Kennison, Kameryn Fritz, Maria Andrea Hurtado Morales, Eric Chan-Tin

Computer Science: Faculty Publications and Other Works

Prior research has demonstrated relationships between personality traits of social media users and the language used in their posts. Few studies have examined whether there are relationships between personality traits of users and how they use emojis in their social media posts. Emojis are digital pictographs used to express ideas and emotions. There are thousands of emojis, which depict faces with expressions, objects, animals, and activities. We conducted a study with two samples (n = 76 and n = 245) in which we examined how emoji use on X (formerly Twitter) related to users’ personality traits and language use …


Maximizing Charge Dynamics In Znin2s4/Cn Van Der Waals Heterojunction For Optimal Hydrogen Production From Photoreforming Of Glucose, Jinqiang Zhang, Xinyuan Xu, Lei Shi, Huayang Zhang, Shaobin Wang, Hongqi Sun Feb 2024

Maximizing Charge Dynamics In Znin2s4/Cn Van Der Waals Heterojunction For Optimal Hydrogen Production From Photoreforming Of Glucose, Jinqiang Zhang, Xinyuan Xu, Lei Shi, Huayang Zhang, Shaobin Wang, Hongqi Sun

Research outputs 2022 to 2026

Biomass photoreforming stands out as a promising avenue for green hydrogen, leveraging solar energy for the generation and transformation of clean and renewable energy resources. The pursuit of efficient photocatalysts is motivated by the unsatisfied hydrogen evolution performance arising from the complex and stubborn structure of biomass. Herein, we loaded 2-dimensional (2D) ZnIn2S4 onto 2D carbon nitride nanosheets, resulting in the formation of Van der Waals (VDW) heterojunctions (ZIS/CN). Band structure and morphology of CN were rationally tailored through precursor engineering to effectively magnify interfacial internal electric field and minimize diffusion pathway within the VDW heterostructure, realizing optimal charge dynamics …


Residual Optical Absorption From Native Defects In Cdsip2 Crystals, Timothy D. Gustafson, Nancy C. Giles, Elizabeth M. Scherrer, Kevin T. Zawilski, Peter G. Schunemann, Kent L. Averett, Jonathan E. Slagle, Larry E. Halliburton Feb 2024

Residual Optical Absorption From Native Defects In Cdsip2 Crystals, Timothy D. Gustafson, Nancy C. Giles, Elizabeth M. Scherrer, Kevin T. Zawilski, Peter G. Schunemann, Kent L. Averett, Jonathan E. Slagle, Larry E. Halliburton

Faculty Publications

CdSiP2 crystals are used in optical parametric oscillators to produce tunable output in the mid-infrared. As expected, the performance of the OPOs is adversely affected by residual optical absorption from native defects that are unintentionally present in the crystals. Electron paramagnetic resonance (EPR) identifies these native defects. Singly ionized silicon vacancies (V-Si) are responsible for broad optical absorption bands peaking near 800, 1033, and 1907 nm. A fourth absorption band, peaking near 630 nm, does not involve silicon vacancies. Exposure to 1064 nm light when the temperature of the CdSiP2 crystal is near 80K converts …