Engineering Commons^™

Standardization Roadmap For Unmanned Aircraft Systems, Version 2.0, Kristine Kiernan, Robert Joslin, John Robbins

Publications

This Standardization Roadmap for Unmanned Aircraft Systems, Version 2.0 (“roadmap”) is an update to version 1.0 of this document published in December 2018. It identifies existing standards and standards in development, assesses gaps, and makes recommendations for priority areas where there is a perceived need for additional standardization and/or pre-standardization R&D.

The roadmap has examined 78 issue areas, identified a total of 71 open gaps and corresponding recommendations across the topical areas of airworthiness; flight operations (both general concerns and application-specific ones including critical infrastructure inspections, commercial services, and public safety operations); and personnel training, qualifications, and certification. Of that …

The Use Of Polyvinyldene Fluoride (Pvdf) Films For Pressure Measurement, Patrick Smith

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

Plasma Jet Flow Characterization Via Computational Modeling, Declan Brick

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

Role Of The Adhesion Torque On Spiky Particles Deposition, Kailian Davis

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

An Electrostatic Field Detector For Pulsed Power Safety, Bailey Gregory

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

Applications Of Cloud-Based Quantum Computers With Cognitive Computing Algorithms In Automated, Evidence-Based Virginia Geriatric Healthcare, Henry Childs

AUCTUS: The Journal of Undergraduate Research and Creative Scholarship

Quantum computers have recently headlined IBM’s next generation of products promoting computational evolution. After the successful release of the cloud-streaming quantum computer IBM Watson Q, the company has released projections for future development of quantum devices. Because of the incredible processing power of these machines and the expected integration into everyday life in the near future, what implications can this have in the healthcare field?

I am studying cloud-based quantum computers with natural language processing (NLP) algorithms and patient health record data because I want to understand automated, evidenced-based co-optimized treatment of home-bound geriatric patients in order to help my …

Recommended Training Practices To Prepare Pilots To Cope With Information Conflicts, Meredith Carroll, Paige Sanchez, Donna Wilt

Aeronautics Faculty Publications

As the next generation of flight deck information systems are being utilized on the flight deck, pilots now have greater amounts of information at their fingertips. Information that was typically available only from certified information sources in aircraft panels, is now being provided by a range of sources, both within the panel and on Electronic Flight Bags (EFBs). Although redundant sources of information provide pilots a means by which to crosscheck and hone in on ground truth, they also introduce the potential for pilots encountering conflicting information. As conflicting information can have negative effects on decision making, there is a …

Pilot Selection Research Gaps: What We Do And Don't Know About "The Right Stuff", Thomas C. Scott, Meredith Carroll

Aeronautics Faculty Publications

Ever since the commencement of high-powered flight, pilot selection has been a crucial process within military, general, and commercial aviation. Through effective pilot selection, individuals with the necessary aptitudes, or "the right stuff" to get through a training program and successfully perform the job, can be chosen. There is a range of different aptitudes that have been shown through research to correlate with effective pilot performance. However, there is currently not a comprehensive understanding of the aptitudes, including both cognitive abilities and psychological attributes, necessary not only for effective pilot performance but also for a successful career as an aviator. …

Examination Of The Impact Of Various Training Approaches On Different Uas Operator Populations, Summer Rebensky, Meredith Carroll, Maria Chaparro

Aeronautics Faculty Publications

In recent years, the UAS industry has extended beyond military and recreational use and is now positioned to become a major portion of the aviation industry. As we move toward UAS integration into the national airspace system, UAS operators need effective training to ensure safe operation. Training UAS operators in an engaging way is important to ensure the best performance and transfer of training. Training methods that elicit high levels of learner engagement have been shown to improve knowledge gains, performance, and therefore such training techniques provide an opportunity for improving UAS training effectiveness and transfer. The growth of the …

Examining Pilot Response To Cybersecurity Events On The Flight Deck, Meredith Carroll, Summer Rebensky, Paige Sanchez

Aeronautics Faculty Publications

Cybersecurity is a growing concern in the aviation industry. In general, cybersecurity research has typically focused on providing technical solutions such as hardening networks and improving computer systems, with little focus on the human operator. Human operators, such as pilots, are often the last line of defense; however, it is currently unclear whether pilots can recognize cybersecurity vulnerabilities, detect when a system is being compromised, and respond appropriately to a cybersecurity event. A review of literature revealed three key stages in cybersecurity response decision process (susceptibility, detection, and response) that are influenced by eight separate factors (perceived susceptibility, perceived safeguard …

Automatic Detection Of Learner Engagement Using Machine Learning And Wearable Sensors, Meredith Carroll, Mitchell Ruble, Mark Dranias, Summer Rebensky, Maria Chaparro, Joanna Chiang, Brent Winslow

Aeronautics Faculty Publications

Training can now be delivered on a large scale through mobile and web-based platforms in which the learner is often distanced from the instructor and their peers. In order to optimize learner engagement and maximize learning in these contexts, instructional content and strategies must be engaging. Key to the de-velopment and study of such content and strategies, and adaptation of instruc-tional techniques when learners become disengaged, is the ability to objec-tively assess engagement in real-time. Previous self-reported metrics, or expen-sive EEG-based engagement measures are not appropriate for large-scale plat-forms due to their complexity and cost. Here we describe the development …

Impact Of The Arrival Distribution Of Primary User Traffic In Dynamic Spectrum Access, Jun Peng

Electrical and Computer Engineering Faculty Publications

In dynamic spectrum access (DSA) a primary user shares the spectrum with one or more secondary users, with or without the primary user knowing the existence of the secondary users and offering assistance to the secondary users. When the primary user is inactive in the channel, the secondary users use the spectrum for data communication. When the primary user becomes active, the secondary users back off to return the spectrum back to the primary user. It is therefore that an arrival of the primary user traffic interrupts the ongoing communication among the secondary users. The arrivals of the primary user …

Improving Students’ Learning And Performance Using Mock Tests In Engineering Classes, Mohammad R. Hossan, Nazmul Islam

Electrical and Computer Engineering Faculty Publications

Class performance and classroom environment have a direct impact on students’ learning and long-term retention of key engineering concepts. In addition, class performance is critical for preserving students’ interest and continuous engagement. However, engineering classes are widely rated as boring and monotonous by students due to one-way lectures and lack of application of active learning techniques. In this study, we employed mock tests as an active learning technique to empower students on their own learning through identification of conceptual weakness, reinforcement of understanding and hence, to improve their overall learning and class performance in two different engineering classes at two …

A Novel S-Box-Based Postprocessing Method For True Random Number Generation, Erdi̇nç Avaroğlu, Taner Tuncer

Turkish Journal of Electrical Engineering and Computer Sciences

The quality of randomness in numbers generated by true random number generators (TRNGs) depends on the source of entropy. However, in TRNGs, sources of entropy are affected by environmental changes and this creates a correlation between the generated bit sequences. Postprocessing is required to remove the problem created by this correlation in TRNGs. In this study, an S-box-based postprocessing structure is proposed as an alternative to the postprocessing structures seen in the published literature. A ring oscillator (RO)-based TRNG is used to demonstrate the use of an S-box for postprocessing and the removal of correlations between number sequences. The statistical …

Harmonic Effects Optimization At A System Level Using A Harmonic Power Flowcontroller, Reza Mehri, Hossein Mokhtari

Turkish Journal of Electrical Engineering and Computer Sciences

Increase of nonlinear loads in industries has resulted in high levels of harmonic currents and consequently harmonic voltages in power networks. Harmonics have several negative effects such as higher energy losses and equipment life reduction. To reduce the levels of harmonics in power networks, different methods of harmonic suppression have been employed. The basic idea in all of these methods is to prevent harmonics from flowing into a power network at customer sides and the point of common coupling (PCC). Due to the costs, none of the existing mitigating methods result in a harmonic-free power system. The remaining harmonic currents, …

Sla-Aware Routing Strategy For Multi-Tenant Software-Defined Networks, Ali Malik, Ruairí De Fréin

Conference papers

A crucial requirement for the network service provider is to satisfy the Service Level Agreements (SLA) that it has made with its customers. Coexisting network tenants may have agreed different SLAs, and thus, the service provider must be able to provide QoS differentiation in order to meet his contractual commitments. Current one-size-fits-all routing models are not appropriate for all network tenants if their individual SLA requirements are to be efficiently met. We propose a SDN-based multi-cost routing approach which allocates network resources based on a portfolio of tenant SLA, which achieves the goal of accommodating multiple tenants, given their SLAs. …

A Statistically Significant Test To Evaluate The Order Or Disorder For A Binary String Of A Finite Length, Jonathan Blackledge, N. Mosola

Conference papers

—This paper addresses a basic problem in regard to the analysis of a finite binary string or bit stream (of compact support), namely, how to tell whether the string is representative of non-random or intelligible information (involving some form of periodicity, for example), whether it is the product of an entirely random process or whether it is something in between thetwo.Thisproblemhasapplicationsthatincludecryptanalysis, quantitative finance, machine learning, artificial intelligence and other forms of signal and image processing involving the general problem of how to distinguishing real noise from information embedded in noise, for example. After providing a short introductiontotheproblem,wefocusontheapplicationofinformation entropy for solving …

Digital Image Exchange Using A No-Key(S) Protocol With Phase-Only Encryption,, Jonathan Blackledge, N. Mosola

Conference papers

This paper considers an algorithm for transferring a digital image over an open network using a No-key(s) Protocol or Three-Way Pass and phase-only encryption/decryption. After providing a short study on the theoretical background to the method, an algorithm is presented on a step-by-step basis. Cryptanalysis is undertaken for the three intercept and single intercept cases, when it is assumed that the encrypted data is intercepted in its entirety for each pass or for any single pass, respectively. The algorithm focuses on the exchange of a JPEG image although in principle, the approach is independent of the format of the image …

Deep Learning Towards Intelligent Vehicle Fault Diagnosis, Mohammed Al-Zeyadi, Javier Andreu-Perez, Hani Hagras, Chris Royce, Darren Smith, Piotr Rzonsowski, Ali Malik

Conference papers

Recently, the rapid development of automotive industries has given rise to large multidimensional datasets both in the production sites and after-sale services. Fault diagnostic systems are one of the services that the automotive industries provide. As a consequence of the rapid development of cars features, traditional rule-based diagnostic systems became very limited. Therefore, more sophisticated AI approaches need to be investigated towards more efficient solutions. In this paper, we focus on utilising deep learning so as to build a diagnostic system that is able to estimate the required services in an efficient and effective way. We propose a new model, …

Active Learning For Auditory Hierarchy, William Coleman, Sarah Jane Delany, Charlie Cullen, Ming Yan

Conference papers

Much audio content today is rendered as a static stereo mix: fundamentally a fixed single entity. Object-based audio envisages the delivery of sound content using a collection of individual sound ‘objects’ controlled by accompanying metadata. This offers potential for audio to be delivered in a dynamic manner providing enhanced audio for consumers. One example of such treatment is the concept of applying varying levels of data compression to sound objects thereby reducing the volume of data to be transmitted in limited bandwidth situations. This application motivates the ability to accurately classify objects in terms of their ‘hierarchy’. That is, whether …

Meaningful Age-Friendly Design. Case Studies On Enabling Assistive Technology., Matteo Zallio, Damon Berry, Larry J. Leifer

Conference papers

The world population is steadily ageing and the World Health Organization recently stated that 8.5 percent of people worldwide are aged 65 and over. This cohort is projected to account for 1.6 billion people by 2050. Assistive Technology has been developed over previous decades with a particular aim to support people with disabilities. With the evolution of the market and the introduction of wearable technologies and IoT-based (Internet of Things) appliances, Assistive Technology has been influenced by the discipline of Age-Friendly Design, which has been applied to meaningfully improve the autonomy of a larger segment of the population, including older …

Modern Techniques For Discovering Digital Steganography, Michael Hegarty, Anthony Keane

Conference papers

Digital steganography can be difficult to detect and as such is an ideal way of engaging in covert communications across the Internet. This research paper is a work-in-progress report on instances of steganography that were identified on websites on the Internet including some from the DarkWeb using the application of new methods of deep learning algorithms. This approach to the identification of Least Significant Bit (LSB) Steganography using Convolutional Neural Networks (CNN) has demonstrated some efficiency for image classification. The CNN algorithm was trained using datasets of images with known steganography and then applied to datasets with images to identify …

Evaluating The Impact Of Defeasible Argumentation As A Modelling Technique For Reasoning Under Uncertainty, Lucas Rizzo

Doctoral

Limited work exists for the comparison across distinct knowledge-based approaches in Artificial Intelligence (AI) for non-monotonic reasoning, and in particular for the examination of their inferential and explanatory capacity. Non-monotonicity, or defeasibility, allows the retraction of a conclusion in the light of new information. It is a similar pattern to human reasoning, which draws conclusions in the absence of information, but allows them to be corrected once new pieces of evidence arise. Thus, this thesis focuses on a comparison of three approaches in AI for implementation of non-monotonic reasoning models of inference, namely: expert systems, fuzzy reasoning and defeasible argumentation. …

Metal Filled Carbon Nanotubes In Radiation Therapy : Dose Enhancement Effect, Sarah Ashmeg

Legacy Theses & Dissertations (2009 - 2024)

In this work, the radiation dose enhancement is studied using a novel method and material that has not been widely investigated, at the time of this publication. Radiation dose enhancement is a useful technique in the field of radiation therapy, especially when dealing with radioresistant cells. Ideally, it increases the dose to the desired site with no additional damage to organs at risk.

Towards Machine Learning In Chemical Sensing : Milk Differentiation And Quality Control Through Two-Dimensional Nano-Sensor Array, Yu Sheng Chen

Legacy Theses & Dissertations (2009 - 2024)

Herein, we developed a novel artificial tongue using machine learning and 12 nanoassemblies (2D-NAs) to identify and analyzed different kinds of milk beverages for quality control. This biomimetic sensor array was trained to “taste” different milk types as an “artificial tongue” which is the first time we demonstrated that this sensor array can be implemented to complex systems. Two-dimensional nanoparticles (2D-nps) and nine fluorescently labeled single stranded oligonucleotides (ssDNA) with different length and nucleobases were assembled to create 12 2D-NAs. The artificial tongue was deployed to identify and analyze five milk types. All five milk types were discriminated with 95% …

Using Systems Archetypes And Generic Structures To Support Water Resource Management Studies : The Case Of Cropping Pattern Change In New Mexico State, Babak Bahaddin

Legacy Theses & Dissertations (2009 - 2024)

A wide range of managerial problems are similar in nature, and yet they continuously appear in different forms and in different geographical locations. Compared to other sciences, it seems that in the field of management, managers have a hard time facing these similar problems. Part of this issues is caused by the extreme complexity of the systems and another part is caused by the lack of a universal language with which managers can communicate their lessons. This dissertation offers a set of tools that have been previously manufactured in systems science, and more specifically in System Dynamics.

Increasing Performance Of Classifiers For Ssvep-Based Brain-Computer Interfaces Using Extension Methods, Ethan Douglas Webster

Legacy Theses & Dissertations (2009 - 2024)

Brain-computer interfaces (BCI) provide an alternative communication method that does not require standard physical mediums (speech, typing, etc.). These systems have been implemented to provide additional communication and control options for people with certain motor disabilities. Classification is an important part of BCI systems and consists of inferring user commands from brain activity. Supervised classification methods often achieve higher accuracy, but unsupervised classification methods are useful when training is not practical for the user. This thesis focuses on unsupervised classification algorithms used for a BCI speller application and presents extensions for two existing classifiers that improve classification accuracy and thus …

The Brain's Large-Scale Electrophysiological Signals : Fundamental Attributes And Neurosurgical Applications, Mohammad Amin N/A Nourmohammadi

Legacy Theses & Dissertations (2009 - 2024)

Brain’s electrophysiological signals are most certainly the ultimate source for studying the sophisticated neural network inside our cranium. The unparalleled complexity of these biosignalsis the quintessential manifestation of their underlying complicated neurophysiological processes. Studying brain signals on the cellular level provides valuable information regarding the brain’s electrophysiology on the small-scale. However, it is the remarkable network in the large-scale that gives rise to the brain’s extraordinary attributes and exceptional capabilities—perception, cognition, computation, and consciousness are all the emergent byproducts of the dynamic neuronal interactions on the network level. In this sense, the large-scale electrophysiological signals, recorded from the surface of …

Sequentially-Closed And Forward-Closed String Rewriting Systems, Yu Zhang

Legacy Theses & Dissertations (2009 - 2024)

In this dissertation we introduce the new concept of sequentially-closed string rewriting systems which generalizes forward-closed string rewriting systems and monadic string rewriting systems. We also investigate subclasses and properties of finite and regular sequentially-closed systems and forward-closed systems.

Statistical Methods To Unravel Cortical Mechanism Of Perception And Response To Auditory Stimuli, Ladan Moheimanian

Legacy Theses & Dissertations (2009 - 2024)

Behavioral responses to auditory stimuli have a critical role in our daily activities. The perception of these stimuli and the generation of appropriate behavioral responses requires the interaction of thousands of neurons in the auditory-motor pathways in the brain. Despite their importance, still many neuroscientific questions about these interactions are remained to be answered. This may result from the limitations of brain recordings as well as statistical methods to analyze brain recordings. In this dissertation, I investigated underlying mechanisms that govern these neural interactions in the auditory-motor pathways using novel statistical techniques applied to the brain recordings from the surface …