Engineering Commons^™

Synthesis, Characterization, Spectroscopic, And Mesomorphic Studies Of New Schiff Base Ligands And Titanium, Cobalt, Nickel And Copper Metal Centers, Raj K. Gurung

Chemistry & Biochemistry Theses & Dissertations

Transition metal complexes with Schiff base ligands offer a wide application in the field of development of catalysis and material. The straightforward synthesis allowed the structural modification and helped to optimize in various application of such complexes. Titanium-containing complexes have been reported to be important for their catalytic and material applications through the coordination of a tetradentate Schiff base ligand, viz. N, N’-ethylene bis(salicylideneiminate) dianion (salen). Studies reporting the characterization of achiral titanium(IV) salen complexes are scarce due to their intricate nature. Such complexes would be comparatively less expensive and easier to prepare synthetically and thus could represent an …

Onboard Autonomous Controllability Assessment For Fixed Wing Suavs, Brian Edward Duvall

Mechanical & Aerospace Engineering Theses & Dissertations

Traditionally fixed-wing small Unmanned Arial Vehicles (sUAV) are flown while in direct line of sight with commands from a remote operator. However, this is changing with the increased popularity and ready availability of low-cost flight controllers. Flight controllers provide fixed-wing sUAVs with functions that either minimize or eliminate the need for a remote operator. Since the remote operator is no longer controlling the sUAV, it is impossible to determine if the fixed-wing sUAV has proper control authority. In this work, a controllability detection system was designed, built, and flight-tested using COTS hardware. The method features in-situ measurement and analysis of …

Enhanced Traffic Incident Analysis With Advanced Machine Learning Algorithms, Zhenyu Wang

Computational Modeling & Simulation Engineering Theses & Dissertations

Traffic incident analysis is a crucial task in traffic management centers (TMCs) that typically manage many highways with limited staff and resources. An effective automatic incident analysis approach that can report abnormal events timely and accurately will benefit TMCs in optimizing the use of limited incident response and management resources. During the past decades, significant efforts have been made by researchers towards the development of data-driven approaches for incident analysis. Nevertheless, many developed approaches have shown limited success in the field. This is largely attributed to the long detection time (i.e., waiting for overwhelmed upstream detection stations; meanwhile, downstream stations …

Conical Orbital Mechanics: A Rework Of Classic Orbit Transfer Mechanics, Cian Anthony Branco

Mechanical & Aerospace Engineering Theses & Dissertations

Simple orbital maneuvers obeying Kepler’s Laws, when taken with respect to Newton’s framework, require considerable time and effort to interpret and understand. Instead of a purely mathematical approach relying on the governing relations, a graphical geometric conceptual representation provides a useful alternative to the physical realities of orbits. Conic sections utilized within the full scope of a modified cone (frustum) were employed to demonstrate and develop a geometric approach to elliptical orbit transformations. The geometric model in-question utilizes the rotation of a plane intersecting the orbital frustum at some angle β (and the change in this angle) in a novel …

Parallelization Of The Advancing Front Local Reconnection Mesh Generation Software Using A Pseudo-Constrained Parallel Data Refinement Method, Kevin Mark Garner Jr.

Computer Science Theses & Dissertations

Preliminary results of a long-term project entailing the parallelization of an industrial strength sequential mesh generator, called Advancing Front Local Reconnection (AFLR), are presented. AFLR has been under development for the last 25 years at the NSF/ERC center at Mississippi State University. The parallel procedure that is presented is called Pseudo-constrained (PsC) Parallel Data Refinement (PDR) and consists of the following steps: (i) use an octree data-decomposition scheme to divide the original geometry into subdomains (octree leaves), (ii) refine each subdomain with the proper adjustments of its neighbors using the given refinement code, and (iii) combine all subdomain data into …

Gaining Insight Into Solar Photovoltaic Power Generation Forecasting Utilizing Explainable Artificial Intelligence Tools, Murat Kuzlu, Umit Cali, Vinayak Sharma, Özgür Güler

Engineering Technology Faculty Publications

Over the last two decades, Artificial Intelligence (AI) approaches have been applied to various applications of the smart grid, such as demand response, predictive maintenance, and load forecasting. However, AI is still considered to be a ‘‘black-box’’ due to its lack of explainability and transparency, especially for something like solar photovoltaic (PV) forecasts that involves many parameters. Explainable Artificial Intelligence (XAI) has become an emerging research field in the smart grid domain since it addresses this gap and helps understand why the AI system made a forecast decision. This article presents several use cases of solar PV energy forecasting using …

Agent-Based Modelling Of Values: The Case Of Value Sensitive Design For Refugee Logistics, Christine Boshuijzen-Van Burken, Ross J. Gore, Frank Dignum, Lamber Royakkers, Phillip Wozny, F. Leron Shults

VMASC Publications

We have used value sensitive design as a method to develop an agent-based model of values in humanitarian logistics for refugees. Schwartz’s theory of universal values is implemented in the model in such a way that agents can make value trade-offs, which are operationalized into a measure of refugee wellbeing and a measure of public opinion about how the refugee logistics is being handled. By trying out different ‘value scenarios’, stakeholders who are responsible for, or involved in refugee logistics can have insights into the effects of various value choices. The model is visualized and made usable as a platform …

Snitch Application: Addressing Cyber Trust In Future Living Spaces, Russell Moore

Cybersecurity Undergraduate Research Showcase

The future of smart homes is filled with excitement and ample opportunity to live in an environment that features extraordinary convenience and energy efficiency. Devices such as Amazon Alexa and Roku Smart TV’s feature voice interaction options that provide the user with enhanced functionality. While voice-activated devices are accommodating, it is imperative to acknowledge how they work on the backend. The problem is that these devices collect and share a large amount of data from users who are oftentimes unaware that it’s even happening. The Snitch App is being developed in order to inform the user of what exactly is …

Cyber-Assets At Risk (Car): Monetary Impact Of Personally Identifiable Information Data Breaches On Companies, Omer Ilker Poyraz

Engineering Management & Systems Engineering Theses & Dissertations

Cyber-systems provide convenience, ubiquity, economic advantage, and higher efficiency to both individuals and organizations. However, vulnerabilities of the cyber domain also offer malicious actors with the opportunities to compromise the most sensitive information. Recent cybersecurity incidents show that a group of hackers can cause a massive data breach, resulting in companies losing competitive advantage, reputation, and money. Governments have since taken some actions in protecting individuals and companies from such crime by authorizing federal agencies and developing regulations. To protect the public from losing their most sensitive records, governments have also been compelling companies to follow cybersecurity regulations. If companies …

Secure Mobile Computing By Using Convolutional And Capsule Deep Neural Networks, Rui Ning

Electrical & Computer Engineering Theses & Dissertations

Mobile devices are becoming smarter to satisfy modern user's increasing needs better, which is achieved by equipping divers of sensors and integrating the most cutting-edge Deep Learning (DL) techniques. As a sophisticated system, it is often vulnerable to multiple attacks (side-channel attacks, neural backdoor, etc.). This dissertation proposes solutions to maintain the cyber-hygiene of the DL-Based smartphone system by exploring possible vulnerabilities and developing countermeasures.

First, I actively explore possible vulnerabilities on the DL-Based smartphone system to develop proactive defense mechanisms. I discover a new side-channel attack on smartphones using the unrestricted magnetic sensor data. I demonstrate that attackers can …

Towards Dynamic Vehicular Clouds, Aida Ghazizadeh

Computer Science Theses & Dissertations

Motivated by the success of the conventional cloud computing, Vehicular Clouds were introduced as a group of vehicles whose corporate computing, sensing, communication, and physical resources can be coordinated and dynamically allocated to authorized users. One of the attributes that set Vehicular Clouds apart from conventional clouds is resource volatility. As vehicles enter and leave the cloud, new computing resources become available while others depart, creating a volatile environment where the task of reasoning about fundamental performance metrics becomes very challenging. The goal of this thesis is to design an architecture and model for a dynamic Vehicular Cloud built on …

Deep Learning For Remote Sensing Image Processing, Yan Lu

Computational Modeling & Simulation Engineering Theses & Dissertations

Remote sensing images have many applications such as ground object detection, environmental change monitoring, urban growth monitoring and natural disaster damage assessment. As of 2019, there were roughly 700 satellites listing “earth observation” as their primary application. Both spatial and temporal resolutions of satellite images have improved consistently in recent years and provided opportunities in resolving fine details on the Earth's surface. In the past decade, deep learning techniques have revolutionized many applications in the field of computer vision but have not fully been explored in remote sensing image processing. In this dissertation, several state-of-the-art deep learning models have been …

Human Supremacy As Posthuman Risk, Daniel Estrada

The Journal of Sociotechnical Critique

Human supremacy is the widely held view that human interests ought to be privileged over other interests as a matter of ethics and public policy. Posthumanism is the historical situation characterized by a critical reevaluation of anthropocentrist theory and practice. This paper draws on animal studies, critical posthumanism, and the critique of ideal theory in Charles Mills and Serene Khader to address the appeal to human supremacist rhetoric in AI ethics and policy discussions, particularly in the work of Joanna Bryson. This analysis identifies a specific risk posed by human supremacist policy in a posthuman context, namely the classification of …

Human Behavior Is A Significant Flaw In Maintaining Cyber Security, Elizabeth Jackson

Cybersecurity Undergraduate Research Showcase

Human behavior and data security utilization must be intertwined; in order to mitigate the negative effects of cyber attacks. No consumer wants their data hacked, breached, stolen, shared or wiped out. It is imperative to survey the type of education is needed to keep users safe and interested in securing their data. This can be done by simply seeking out the consumer's view of data security. The information obtained would allow the cybersecurity community to offer a simple way for consumers to protect their mobile data. There is a constant interaction between human behavior and the need for increased data …

Three-Event Energy Detection With Adaptive Threshold For Spectrum Sensing In Cognitive Radio Systems, Alexandru Martian, Mahmood Jalal Ahmad Al Sammarraie, Calin Vladeanu, Dimitrie Popescu

Electrical & Computer Engineering Faculty Publications

Implementation of dynamic spectrum access (DSA) in cognitive radio (CR) systems requires the unlicensed secondary users (SU) to implement spectrum sensing to monitor the activity of the licensed primary users (PU). Energy detection (ED) is one of the most widely used methods for spectrum sensing in CR systems, and in this paper we present a novel ED algorithm with an adaptive sensing threshold. The three-event ED (3EED) algorithm for spectrum sensing is considered for which an accurate approximation of the optimal decision threshold that minimizes the decision error probability (DEP) is found using Newton’s method with forced convergence in one …

Virginia Digital Shipbuilding Program (Vdsp): Building An Agile Modern Workforce To Improve Performance In The Shipbuilding And Ship Repair Industry, Joseph Peter Kosteczko, Katherine Smith, Jessica Johnson, Rafael Diaz

VMASC Publications

Industry 4.0 is the latest stage in the Industrial Revolution and is reflected in the digital transformation and use of emergent technologies including the Internet of Things, Big Data, Robotic automation of processes, 3D printing and additive manufacturing, drones and Artificial Intelligence (AI) in the manufacturing industry. The implementation of these technologies in the Shipbuilding and Ship Repair Industry is currently in a nascent stage. Considering this, there is huge potential to increase cost savings, decrease production timelines, and drive down inefficiencies in Lifecyle management of ships. However, the implementation of these Industry 4.0 technologies is hindered by a noticeable …

What Do Undergraduate Engineering Students And Preservice Teachers Learn By Collaborating And Teaching Engineering And Coding Through Robotics?, Jennifer Jill Kidd, Krishnanand Kaipa, Samuel J. Jacks, Stacie I. Ringleb, Pilar Pazos, Kristie Gutierrez, Orlando M. Ayala, Lillian Maria De Souza Almeida

Teaching & Learning Faculty Publications

This research paper presents preliminary results of an NSF-supported interdisciplinary collaboration between undergraduate engineering students and preservice teachers. The fields of engineering and elementary education share similar challenges when it comes to preparing undergraduate students for the new demands they will encounter in their profession. Engineering students need interprofessional skills that will help them value and negotiate the contributions of various disciplines while working on problems that require a multidisciplinary approach. Increasingly, the solutions to today's complex problems must integrate knowledge and practices from multiple disciplines and engineers must be able to recognize when expertise from outside their field can …

Work-In-Progress: Augmented Reality System For Vehicle Health Diagnostics And Maintenance, Yuzhong Shen, Anthony W. Dean, Rafael Landaeta

Electrical & Computer Engineering Faculty Publications

This paper discusses undergraduate research to develop an augmented reality (AR) system for diagnostics and maintenance of the Joint Light Tactical Vehicle (JLTV) employed by U.S. Army and U.S. Marine Corps. The JLTV’s diagnostic information will be accessed by attaching a Bluetooth adaptor (Ford Reference Vehicle Interface) to JLTV’s On-board diagnostics (OBD) system. The proposed AR system will be developed for mobile devices (Android and iOS tablets and phones) and it communicates with the JLTV’s OBD via Bluetooth. The AR application will contain a simplistic user interface that reads diagnostic data from the JLTV, shows vehicle sensors, and allows users …

Size-Dependent Inhibitory Effects Of Antibiotic Nanocarriers On Filamentation Of E. Coli, Preeyaporn Songkiatisak, Feng Ding, Pavan Kumar Cherukuri, Xiao-Hong Nancy Xu

Chemistry & Biochemistry Faculty Publications

Multidrug membrane transporters exist in both prokaryotic and eukaryotic cells and cause multidrug resistance (MDR), which results in an urgent need for new and more effective therapeutic agents. In this study, we used three different sized antibiotic nanocarriers to study their mode of action and their size-dependent inhibitory effects against Escherichia coli (E. coli). Antibiotic nanocarriers (AgMUNH–Oflx NPs) with 8.6 × 10², 9.4 × 10³ and 6.5 × 10⁵ Oflx molecules per nanoparticle (NP) were prepared by functionalizing Ag NPs (2.4 ± 0.7, 13.0 ± 3.1 and 92.6 ± 4.4 nm) with a monolayer …

Probing Nanoelectroporation And Resealing Of The Cell Membrane By The Entry Of Ca2+ And Ba2+ Ions, Wenfei Bo, Mantas Silkunas, Uma Mangalanathan, Vitalij Novickij, Maura Casciola, Iurii Semenov, Shu Xiao, Olga N. Pakhomova, Andrei G. Pakhomov

Bioelectrics Publications

The principal bioeffect of the nanosecond pulsed electric field (nsPEF) is a lasting cell membrane permeabilization, which is often attributed to the formation of nanometer-sized pores. Such pores may be too small for detection by the uptake of fluorescent dyes. We tested if Ca²⁺, Cd²⁺, Zn²⁺, and Ba²⁺ ions can be used as nanoporation markers. Time-lapse imaging was performed in CHO, BPAE, and HEK cells loaded with Fluo-4, Calbryte, or Fluo-8 dyes. Ca²⁺ and Ba²⁺ did not change fluorescence in intact cells, whereas their entry after nsPEF increased fluorescence within <1 ms. The threshold for one 300-ns pulse was at 1.5–2 kV/cm, much lower than >7 …

Truck Trailer Classification Using Side-Fire Light Detection And Ranging (Lidar) Data, Olcay Sahin

Civil & Environmental Engineering Theses & Dissertations

Classification of vehicles into distinct groups is critical for many applications, including freight and commodity flow modeling, pavement management and design, tolling, air quality monitoring, and intelligent transportation systems. The Federal Highway Administration (FHWA) developed a standardized 13-category vehicle classification ruleset, which meets the needs of many traffic data user applications. However, some applications need high-resolution data for modeling and analysis. For example, the type of commodity being carried must be known in the freight modeling framework. Unfortunately, this information is not available at the state or metropolitan level, or it is expensive to obtain from current resources.

Nevertheless, using …

Deep Cellular Recurrent Neural Architecture For Efficient Multidimensional Time-Series Data Processing, Lasitha S. Vidyaratne

Electrical & Computer Engineering Theses & Dissertations

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in …

Investigating The Feasibility And Stability For Modeling Acoustic Wave Scattering Using A Time-Domain Boundary Integral Equation With Impedance Boundary Condition, Michelle E. Rodio

Mathematics & Statistics Theses & Dissertations

Reducing aircraft noise is a major objective in the field of computational aeroacoustics. When designing next generation quiet and environmentally friendly aircraft, it is important to be able to accurately and efficiently predict the acoustic scattering by an aircraft body from a given noise source. Acoustic liners are an effective tool for aircraft noise reduction and are characterized by a frequency-dependent impedance. Converted into the time-domain using Fourier transforms, an impedance boundary condition can be used to simulate the acoustic wave scattering by geometric bodies treated with acoustic liners

This work considers using either an impedance or an admittance (inverse …

Rotorcraft Blade Angle Calibration Methods, Brian David Calvert Jr.

Mechanical & Aerospace Engineering Theses & Dissertations

The most vital system of a rotorcraft is the rotor system due to its effects on the overall flight quality of the vehicle. Therefore, it is of importance to be able to accurately determine blade position during flight so that fine adjustments can be made to ensure a safe and efficient flight. In this study, a current calibration method focusing on the pitch, flap, and lead-lag blade angles is analyzed and found to have larger than acceptable error associated with the sensor calibrations. A literature review is conducted which reveals four novel methods that can potentially increase the accuracy of …

Lignin: A Likely Precursor Of A Significant Fraction Of Humic Substances Via Oxidative Transformations, Seyyedhadi Khatami

Chemistry & Biochemistry Theses & Dissertations

Lignin is a major component of decaying terrestrial vegetation in soils and has been arguably reported to contribute substantially to the formation of soil carbon humus, and natural dissolved organic matter (DOM). To better understand the process by which this humification occurs, lignin and lignin-derived monomers were subjected to both biotic and abiotic oxidation processes. Two well-known oxidative transformation strategies were employed. The first involved the fungal degradation of brown-rot degraded wood subjected to a white-rot fungus (Phanerochaete chrysosporium) whose enzymes are particularly effective in lignin degradation via enzymatic oxidation. This enzymatic attack was monitored by ultrahigh resolution …

In-Situ Gold-Ceria Nanoparticles: Superior Optical Fluorescence Quenching Sensor For Dissolved Oxygen, Nader Shehata, Ishac Kandas, Effat Samir

Electrical & Computer Engineering Faculty Publications

Cerium oxide (ceria) nanoparticles (NPs) have been proved to be an efficient optical fluorescent material through generating visible emission (~530 nm) under violet excitation. This feature allowed ceria NPs to be used as an optical sensor via the fluorescence quenching Technique. In this paper, the impact of in-situ embedded gold nanoparticles (Au NPs) inside ceria nanoparticles was studied. Then, gold–ceria NPs were used for sensing dissolved oxygen (DO) in aqueous media. It was observed that both fluorescence intensity and lifetime were changed due to increased concentration of DO. Added gold was found to enhance the sensitivity of ceria to DO …

A Blockchain Simulator For Evaluating Consensus Algorithms In Diverse Networking Environments, Peter Foytik, Sachin Shetty, Sarada Prasad Gochhayat, Eranga Herath, Deepak Tosh, Laurent Njilla

VMASC Publications

The massive scale, heterogeneity and distributed nature of Internet-of-Things (IoT) presents challenges in realizing a practical and effective security solution. Blockchain empowered platforms and technologies have been proposed to address aspects of this challenge. In order to realize a practical Blockchain deployment for IoT, there is a need for a testing and evaluation platform to evaluate performance and security of Blockchain applications and systems. In this paper, we present a Blockchain simulator that evaluates the consensus algorithms in a realistic and configurable network environment. Though, there are several Blockchain evaluation platforms, they are either wedded to a specific consensus protocol …

Measuring Decentrality In Blockchain Based Systems, Sarada Prasad Gochhayat, Sachin Shetty, Ravi Mukkamala, Peter Foytik, Georges A. Kamhoua, Laurent Njilla

VMASC Publications

Blockchain promises to provide a distributed and decentralized means of trust among untrusted users. However, in recent years, a shift from decentrality to centrality has been observed in the most accepted Blockchain system, i.e., Bitcoin. This shift has motivated researchers to identify the cause of decentrality, quantify decentrality and analyze the impact of decentrality. In this work, we take a holistic approach to identify and quantify decentrality in Blockchain based systems. First, we identify the emergence of centrality in three layers of Blockchain based systems, namely governance layer, network layer and storage layer. Then, we quantify decentrality in these layers …

The Artificial University: Decision Support For Universities In The Covid-19 Era, Wesley J. Wildman, Saikou Y. Diallo, George Hodulik, Andrew Page, Andreas Tolk, Neha Gondal

VMASC Publications

Operating universities under pandemic conditions is a complex undertaking. The Artificial University (TAU) responds to this need. TAU is a configurable, open-source computer simulation of a university using a contact network based on publicly available information about university classes, residences, and activities. This study evaluates health outcomes for an array of interventions and testing protocols in an artificial university of 6,500 students, faculty, and staff. Findings suggest that physical distancing and centralized contact tracing are most effective at reducing infections, but there is a tipping point for compliance below which physical distancing is less effective. If student compliance is anything …

A Saliency-Driven Video Magnifier For People With Low Vision, Ali Selman Aydin, Shirin Feiz, Iv Ramakrishnan, Vikas Ashok

Computer Science Faculty Publications

Consuming video content poses significant challenges for many screen magnifier users, which is the “go to” assistive technology for people with low vision. While screen magnifier software could be used to achieve a zoom factor that would make the content of the video visible to low-vision users, it is oftentimes a major challenge for these users to navigate through videos. Towards making videos more accessible for low-vision users, we have developed the SViM video magnifier system [6]. Specifically, SViM consists of three different magnifier interfaces with easy-to-use means of interactions. All three interfaces are driven by visual saliency as a …