Computer Engineering Commons^™

Experimental Study Of Linux Flightsize Estimation, Mingrui Zhang

School of Computing: Dissertations, Theses, and Student Research

Transmission Control Protocol (TCP) is a fundamental Internet protocol responsible for controlling and coordinating the Internet traffic. As a result, TCP significantly influences the overall performance and stability of the Internet. One critical information required by a TCP connection to make decisions is FlightSize, which is the total amount of outstanding data contributed by the connection to the Internet. The FlightSize information is used by a TCP connection to determine its future sending rate and also avoid traffic congestion and collapse in the Internet. Consequently, an inaccurate estimation of FlightSize can result in degraded performance and instability of the Internet. …

A Unified Switched Nonlinear Dynamic Model Of An Electric Vehicle For Performance Evaluation, Dibyendu Khan, Kuntal Mandal, Anjan Kumar Ray, Abdelali El Aroudi

Department of Electrical and Computer Engineering: Faculty Publications

The advanced modeling and estimation of overall system dynamics play a vital role in electric vehicles (EVs), as the selection of components in the powertrain and prediction of performance are the key market qualifiers. The state-space averaged model and small-signal transfer function model are useful for assessing long-term behavior in system-level analysis and for designing the controller parameters, respectively. Both models take less computation time but ignore the high-frequency switching dynamics. Therefore, these two models could be impractical for the development and testing of EV prototypes. On the other hand, the multi-domain model in available simulation tools gives in-depth information …

An Ai-Based Intervention For Improving Undergraduate Stem Learning, Mohammad Rashedul Hasan, Bilal Khan

Department of Electrical and Computer Engineering: Faculty Publications

We present results from a small-scale randomized controlled trial that evaluates the impact of just-in-time interventions on the academic outcomes of N = 65 undergraduate students in a STEM course. Intervention messaging content was based on machine learning forecasting models of data collected from 537 students in the same course over the preceding 3 years. Trial results show that the intervention produced a statistically significant increase in the proportion of students that achieved a passing grade. The outcomes point to the potential and promise of just-in-time interventions for STEM learning and the need for larger fully-powered randomized controlled trials.

Generation Of Vector Vortex Wave Modes In Cylindrical Waveguides, Md Khadimul Islam, Pawan Gaire, Arjuna Madanayake, Shubhendu Bhardwaj

Department of Electrical and Computer Engineering: Faculty Publications

In this paper, we propose a method to generate Vector Vortex Modes (VVM) inside a metallic cylindrical waveguide at microwave frequencies and demonstrate the experimental validation of the concept. Vector vortex modes of EM waves can carry both spin and orbital angular momentum as they propagate within a tubular medium. The existence of such waves in tubular media can be beneficial to wireless communication in such structures. These waves can carry different orbital angular momentum and spin angular momentum, and therefore, they feature the ability to carry multiple orthogonal modes at the same frequency due to spatial structure of the …

A Flexible Ot Testbed For Evaluating On-Device Implementations Of Iec-61850 Goose, Matthew Boeding, Michael Hempel, Hamid Sharif, Juan Lopez Jr., Kalyan Perumalla

Department of Electrical and Computer Engineering: Faculty Publications

The growing convergence of Information Technology and Operational Technology has enhanced communication and visibility across power grids. This, coupled with the growing use of Distributed Energy Resources in power grids, has enhanced the grid capabilities while also creating a larger attack surface for malicious actors. A common protocol vulnerable to these attacks is the IEC-61850 GOOSE protocol due to its low-latency requirements, multicast packet delivery method, and lack of encryption. In this paper, we evaluate the security implications of different hardware implementations of this protocol by contrasting device response and recovery of two commercial off-the-shelf Intelligent Electronic Devices from separate …

Cometrics: A New Software Tool For Behavior‑Analytic Clinicians And Machine Learning Researchers, Walker S. Arce, Seth G. Walker, Morgan L. Hurtz

Department of Electrical and Computer Engineering: Faculty Publications

Cometrics is a Microsoft Windows compatible clinical tool for the collection and recording of frequency- and duration-based target behaviors, physiological signals, and video data. This software package is designed to record in-vivo observational and physiological data. In addition, we have included features that allow observers to capture video from real-time camera feeds and import saved video for retroactive data collection. By using Microsoft Excel-based spreadsheets, also called keystroke files, assessment and treatment sessions are exported into a single document using the click of a button. Integrated interobserver agreement metrics allow comparisons across primary and reliability observers, with the output exported …

Guest Editorial: Special Issue On Green Iot For Future Space–Air–Ground–Ocean-Integrated Networks And Applications, Bo Rong, Mohamed Cheriet, Jon Montalban, Lei Shu, Yi Qian

Department of Electrical and Computer Engineering: Faculty Publications

The Internet of Things (IoT) plays a critical role in enabling the seamless integration of disparate devices. Future IoT will rapidly expand its coverage to offer future worldwide omnipresent applications and services by merging communications in diverse spatial domains to build the space–air–ground–ocean-integrated network (SAGOI-Net). SAGOI-Net will include a significant number of battery-powered network nodes, such as satellites, unmanned vehicles, and underwater devices, due to the extremely vast geographic reach and dynamics in free space. Given the battery limitations, high-energy-efficiency communications and networking will be critical to the future system. Green SAGOI-Net seeks to not only bring ubiquitous connectivity to …

A Novel Graph Neural Network-Based Framework For Automatic Modulation Classification In Mobile Environments, Pejman Ghasemzadeh

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

Automatic modulation classification (AMC) refers to a signal processing procedure through which the modulation type and order of an observed signal are identified without any prior information about the communications setup. AMC has been recognized as one of the essential measures in various communications research fields such as intelligent modem design, spectrum sensing and management, and threat detection. The research literature in AMC is limited to accounting only for the noise that affects the received signal, which makes their models applicable for stationary environments. However, a more practical and real-world application of AMC can be found in mobile environments where …

Modern Practices For Responsive Web Design And Web Accessibility, Keyaun Washington

Honors Program: Senior Projects (Public)

Responsive web design and web accessibility play crucial roles in ensuring an optimal user experience on the web. By designing websites with responsiveness and accessibility in mind, more opportunities are opened up for a wider audience to access and interact with our content. Through modern practices, responsive web design allows websites to reach several different devices ranging from compact smartwatches to expansive television screens. Designing for accessibility provides accommodations for individuals with impairments while also providing benefits for individuals without impairments. However, designing for responsiveness and accessibility can present challenges; a poor attempt at providing accessibility features can worsen a …

Unobtrusive Data Collection In Clinical Settings For Advanced Patient Monitoring And Machine Learning, Walker Arce

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

When applying machine learning to clinical practice, a major hurdle that will be encountered is the lack of available data. While the data collected in clinical therapies is suitable for the types of analysis that are needed to measure and track clinical outcomes, it may not be suitable for other types of analysis. For instance, video data may have poor alignment with behavioral data, making it impossible to extract the videos frames that directly correlate with the observed behavior. Alternatively, clinicians may be exploring new data modalities, such as physiological signal collection, to research methods of improving clinical outcomes that …

Anticancer Activities Of Tetra-, Penta-, And Hexacyclic Phenothiazines Modified With Quinoline Moiety., Małgorzata Jel, Beata Morak-Młodawska, Rafał Korlacki

Department of Electrical and Computer Engineering: Faculty Publications

The quinoline molecule is a chemical motif showing a highly promising pharmacological potential. Its numerous derivatives introduced into medicine revolutionized in the treatment of many entities of disease. The presence of the quinoline system in the structure of phenothiazines made it possible to obtain new aza- and diazaphenothiazine derivatives that show promising anticancer potential. The aza-analogs of the phenothiazines are structurally modified phenothiazines by the substitution of one or both benzene rings in the phenothiazine ring system with various azine rings. This approach to the strategy of obtaining new substances with biological potential can be classified as molecular hybridization methods …

Modeling And Visualization Of Competing Escalation Dynamics: A Multilayer Multiagent Network Approach, Josh Allen

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

Recent advances in military technology, such as hypersonic missiles, which can travel at more than five times the speed of sound and descend quickly into the atmosphere, give world nuclear superpowers a new edge. These advances up the game for nuclear superpowers with an extremely rapid, intense burst of military striking capability to secure upfront gains before encountering potentially overwhelming military confrontation. However, this so-called fait accompli has not been systematically studied by the United States in the perspective of the escalation philosophies of nuclear power competitors, or the mathematical modeling and visualization of multi-modal escalation dynamics. This gap may …

Leveraging Aruco Fiducial Marker System For Bridge Displacement Estimation Using Unmanned Aerial Vehicles, Mohamed Aly

School of Computing: Dissertations, Theses, and Student Research

The use of unmanned aerial vehicles (UAVs) in construction sites has been widely growing for surveying and inspection purposes. Their mobility and agility have enabled engineers to use UAVs in Structural Health Monitoring (SHM) applications to overcome the limitations of traditional approaches that require labor-intensive installation, extended time, and long-term maintenance. One of the critical applications of SHM is measuring bridge deflections during the bridge operation period. Due to the complex remote sites of bridges, remote sensing techniques, such as camera-equipped drones, can facilitate measuring bridge deflections. This work takes a step to build a pipeline using the state-of-the-art computer …

Sim-To-Real Reinforcement Learning Framework For Autonomous Aerial Leaf Sampling, Ashraful Islam

School of Computing: Dissertations, Theses, and Student Research

Using unmanned aerial systems (UAS) for leaf sampling is contributing to a better understanding of the influence of climate change on plant species, and the dynamics of forest ecology by studying hard-to-reach tree canopies. Currently, multiple skilled operators are required for UAS maneuvering and using the leaf sampling tool. This often limits sampling to only the canopy top or periphery. Sim-to-real reinforcement learning (RL) can be leveraged to tackle challenges in the autonomous operation of aerial leaf sampling in the changing environment of a tree canopy. However, trans- ferring an RL controller that is learned in simulation to real UAS …

Study Of Lipophilicity And Adme Properties Of 1,9-Diazaphenothiazines With Anticancer Action, Beata Morak-Młodawska, Małgorzata Jeleń, Emilia Martula, Rafał Korlacki

Department of Electrical and Computer Engineering: Faculty Publications

Lipophilicity is one of the key properties of a potential drug that determines the solubility, the ability to penetrate through cell barriers, and transport to the molecular target. It affects pharmacokinetic processes such as adsorption, distribution, metabolism, excretion (ADME). The 10-substituted 1,9-diazaphenothiazines show promising if not impressive in vitro anticancer potential, which is associated with the activation of the mitochondrial apoptosis pathway connected with to induction BAX, forming a channel in MOMP and releasing cytochrome c for the activation of caspases 9 and 3. In this publication, the lipophilicity of previously obtained 1,9-diazaphenothiazines was determined theoretically using various computer programs …

Study Of Lipophilicity And Adme Properties Of 1,9-Diazaphenothiazines With Anticancer Action, Beata Morak-Młodawska, Małgorzata Jeleń, Emilia Martula, Rafał Korlacki

Department of Electrical and Computer Engineering: Faculty Publications

Lipophilicity is one of the key properties of a potential drug that determines the solubility, the ability to penetrate through cell barriers, and transport to the molecular target. It affects pharmacokinetic processes such as adsorption, distribution, metabolism, excretion (ADME). The 10-substituted 1,9-diazaphenothiazines show promising if not impressive in vitro anticancer potential, which is associated with the activation of the mitochondrial apoptosis pathway connected with to induction BAX, forming a channel in MOMP and releasing cytochrome c for the activation of caspases 9 and 3. In this publication, the lipophilicity of previously obtained 1,9-diazaphenothiazines was determined theoretically using various computer programs …

Artificial Neural Network-Based Prediction Assessment Of Wire Electric Discharge Machining Parameters For Smart Manufacturing, Itagi Vijayakumar Manoj, Sannayellappa Narendranath, Peter Madindwa Mashinini, Hargovind Soni, Shanay Rab, Shadab Ahmad, Ahatsham Hayat

Department of Electrical and Computer Engineering: Faculty Publications

Artificial intelligence (AI), robotics, cybersecurity, the Industrial Internet of Things, and blockchain are some of the technologies and solutions that are combined to produce “smart manufacturing,” which is used to optimize manufacturing processes by creating and/or accepting data. In manufacturing, spark erosion technique such as wire electric discharge machining (WEDM) is a process that machines different hard-to-cut alloys. It is regarded as the solution for cutting intricate parts and materials that are resistant to conventional machining techniques or are required by design. In the present study, holes of different radii, i.e. 1, 3, and 5mm, have been cut on Nickelvac-HX. …

Deep Reinforcement Learning For Articulatory Synthesis In A Vowel-To-Vowel Imitation Task, Denis Shitov, Elena Pirogova, Tadeusz A. Wysocki, Margaret Lech

Department of Electrical and Computer Engineering: Faculty Publications

Articulatory synthesis is one of the approaches used for modeling human speech production. In this study, we propose a model-based algorithm for learning the policy to control the vocal tract of the articulatory synthesizer in a vowel-to-vowel imitation task. Our method does not require external training data, since the policy is learned through interactions with the vocal tract model. To improve the sample efficiency of the learning, we trained the model of speech production dynamics simultaneously with the policy. The policy was trained in a supervised way using predictions of the model of speech production dynamics. To stabilize the training, …

A Highly Efficient Broadband Multi-Functional Metaplate, Azhar Javed Satti, Muhammad Ashar Naveed, Isma Javed, Nasir Mahmood, Muhammad Zubair, Muhammad Qasim Mehmood, Yehia Massoud

Department of Electrical and Computer Engineering: Faculty Publications

Due to the considerable potential of ultra-compact and highly integrated meta-optics, multi-functional metasurfaces have attracted great attention. The mergence of nanoimprinting and holography is one of the fascinating study areas for image display and information masking in meta-devices. However, existing methods rely on layering and enclosing, where many resonators combine various functions effectively at the expense of efficiency, design complication, and complex fabrication. To overcome these limitations, a novel technique for a tri-operational metasurface has been suggested by merging PB phase-based helicity-multiplexing and Malus's law of intensity modulation. To the best of our knowledge, this technique resolves the extreme-mapping issue …

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 …

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 …

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 …

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 …

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 …

Computer Engineering Education, Marilyn Wolf

School of Computing: Conference and Workshop Papers

Computer engineering is a rapidly evolving discipline. How should we teach it to our students?

This virtual roundtable on computer engineering education was conducted in summer 2022 over a combination of email and virtual meetings. The panel considered what topics are of importance to the computer engineering curriculum, what distinguishes computer engineering from related disciplines, and how computer engineering concepts should be taught.