Engineering Commons^™

Extended Time, Elevated Expectations: The Unappreciated Downsides Of Pausing The Tenure Clock, Maria A. Holland, Katharina Maisel, Carolyn B. Ibberson, Laura K. Wiley, David C. Burnett, Emily M. Mace, Mary Williard Elting

Electrical and Computer Engineering Faculty Publications and Presentations

In 1971, Stanford became the first university to introduce tenure clock extensions in academia for new mothers. The American Association of University Professors (AAUP) began recommending such policies a few years later, and in 2001, modified their recommendation to include primary or coequal caregivers, following either the birth or adoption of a child (1). By 2004, 43% of 255 surveyed institutions had formal clock-stop policies...

Cybersecurity, Image-Based Control, And Process Design And Instrumentation Selection, Dominic Messina, Akkarakaran Francis Leonard, Ryan Hightower, Kip Nieman, Renee O'Neill, Paloma Beacham, Katie Tyrrell, Muhammad Adnan, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Within an Industry 4.0 framework, a variety of new considerations are of increasing importance, such as securing processes against cyberattacks on the control systems or utilizing advances in image processing for image-based control. These new technologies impact relationships between process design and control. In this work, we discuss some of these potential relationships, beginning with a discussion of side channel attacks and what they suggest about ways of evaluating plant design and instrumentation selection, along with controller and security schemes, particularly as more data is collected and there is a move toward an industrial Internet of Things. Next, we highlight …

Perovskites Informatics: Studying The Impact Of Thicknesses, Doping, And Defects On The Perovskite Solar Cell Efficiency Using A Machine Learning Algorithm, Zahraa Ismail, Eman Sawires, Fathy Amer, Sameh O. Abdellatif

Electrical Engineering

No abstract provided.

Breaking The Causality Limit For Broadband Acoustic Absorption Using A Noncausal Active Absorber, Kangkang Wang, Sipei Zhao, Chen Shen, Haishan Zou, Jing Lu, Andrea Alu

Henry M. Rowan College of Engineering Departmental Research

The principle of causality imposes a constraint between the thickness and bandwidth of absorbers. This trade-off applies to any linear, time-invariant, passive system, limiting the development of broadband-absorbing materials that demand a thin profile for sound, light, and radio waves. Here, we demonstrate a strategy to overcome this constraint in acoustics using a noncausal active absorber whose response is controlled over time. A theoretical framework is established, which sets a relation among minimum thickness, bandwidth, and a priori information about the incident signal, representing a relaxed physical bound for noncausal absorbers. We design an absorber based on this principle and …

Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy

Publications

Although Artificial Intelligence technology has proven effective in providing healthcare assistance by analyzing health data, it still falls short in supporting decision-making. This deficiency largely stems from the predominance of opaque neural networks, particularly in mental health care AI applications, which raise concerns about their unpredictable and unverifiable nature. This skepticism hinders the transition from information support to decision support. This presentation will explore neurosymbolic approaches that combine neural networks with symbolic control and verification mechanisms. These approaches aim to unlock AI’s full potential by enhancing information analysis and decision-making support for healthcare assistance.

A Measure Of Interactive Complexity In Network Models, Will Deter

Northeast Journal of Complex Systems (NEJCS)

This work presents an innovative approach to understanding and measuring complexity in network models. We revisit several classic characterizations of complexity and propose a novel measure that represents complexity as an interactive process. This measure incorporates transfer entropy and Jensen-Shannon divergence to quantify both the information transfer within a system and the dynamism of its constituents’ state changes. To validate our measure, we apply it to several well-known simulation models implemented in Python, including: two models of residential segregation, Conway’s Game of Life, and the Susceptible-Infected-Susceptible (SIS) model. Our results reveal varied trajectories of complexity, demonstrating the efficacy and sensitivity …

Feasibility Study Of Using Energy Extracted From The Process Of Electrochemically Consumed Of Al 2024 For Powering Daily Used Electric Car, Yanuar Mohamad Marda, Rini Riastuti, Muhammad Hamka Ibrahim

Journal of Materials Exploration and Findings

Usage of green energy for transportation has become important due to the contribution of transportation activity to climate change. Electrochemical energy has been used as a source of green energy. The objective of this work is to evaluate sufficiency of energy provided by electrochemically consumed Al 2024 for supplying energy to daily used PHEV electric car. Study of previous articles, observation of typical amount of energy required, electrochemical galvanic cell experiments, and simple calculations have been conducted to determine produced energy feasibility. Electrical energy produced by consuming 340 gr of Al 2024 in galvanic cells has the total lifetime of …

Degradation Study Of Single Crystal Barium Titanate Capacitors Under Harsh Environment, Menglin Wang

Electrical Engineering Theses and Dissertations

Capacitors are critical for voltage source converter functionality. DC-link capacitors are known to have reliability issues. Resistance degradation at high temperatures is one of the primary failure modes in capacitors. The overall goal of this program is to improve the understanding of high voltage breakdown and resistance degradation in high dielectric constant inorganic ceramic capacitors, using single crystal BaTiO₃ as a model system to understand the impact and control of oxygen vacancy migration to maximize the long-term reliability of high voltage inorganic multi-layer ceramic capacitors, which allows higher frequency operation, reducing the size and cost of passive components in …

Empty State Electronics, Reza Farsad Asadi

Electrical Engineering Theses and Dissertations

Field emitter arrays (FEAs) have the potential to operate at high frequencies and withstand harsh environments, such as radiation and high temperatures. However, they are sensitive to gaseous environments. This study examines the impact of different gas environments on silicon (Si) and gallium nitride (GaN) FEAs. To investigate the failure mechanisms, a vacuum system was designed and fabricated to monitor emission uniformity using a phosphor screen. Additionally, a vacuum system was created to introduce high-purity gases into the chamber while operating the devices. The results indicate that both types of FEAs are susceptible to oxidizing environments. Argon (Ar) did not …

Development Of A Nephelometer For Characterization Of Calcium Oxalate Crystal Concentrations Within Solution, Conrad Small

Electrical Engineering Theses and Dissertations

The prevalence of kidney stones has been steadily increasing over the last 30 years, affecting both men and women across all age groups. This rise is largely attributed to lifestyle changes associated with technological advancements, such as more sedentary lifestyles, dietary shifts towards more processed foods, and an increased incidence of metabolic diseases like diabetes. Despite the growing prevalence of kidney stones, the methods for early detection have remained relatively unchanged. Current testing involves collecting urine samples over a 24-hour period and sending them to a lab for microscopic and dipstick analysis. This process provides a comprehensive overview of urine …

Enhancing Fundraising Strategies In Higher Education Through Machine Learning, Laith Alatwah

Electrical Engineering Theses

This thesis presents a comprehensive application of machine learning techniques, namely Fine Gaussian SVM and RUS Boosted Trees, to enhance fundraising strategies in higher education institutions. Analyzing a rich dataset from Blackbaud Raiser's Edge NXT, spanning 2012 to 2022, the study focuses on donor profiles, including demographics, donation history, and engagement patterns. Key demographic insights include the increasing engagement of younger donors (20-29 age group) and significant contributions from older donors (70-99 age group). Geographical trends are also examined, revealing distinct patterns based on donors' city, state, and ZIP code. The Fine Gaussian SVM model demonstrates moderate discriminatory power, with …

Assessment Of Economic Viability Of Direct Current Fast Charging Infrastructure Investments For Electric Vehicles In The United States, Daniel Bernal, Adeeba A. Raheem, Sundeep Inti, Hongjie Wang

Electrical and Computer Engineering Faculty Publications

As the global transportation sector increasingly adopts electric vehicles, the demand for advanced and accessible charging infrastructure is rising. In addition to at-home electric vehicle (EV) charging, there is a growing need for the swift development of commercial direct current fast charging (DCFC) stations to meet on-the-go EV charging demands. While government funds are available to support the expansion of the EV charging network in the United States, the establishment of a robust nationwide EV charging infrastructure requires significant private sector investment. This study was conducted to assess the economic feasibility of various business models for fast charging stations in …

Design Of A Portable Fast Scan Cyclic Voltammetry Device Utilizing Pulse Width Modulation For Waveform Generation, Nora Szymkowski

Masters Theses

Fast Scan Cyclic Voltammetry (FSCV) is a widely used electrochemical technique for real-time measurement of the brain’s chemical messengers, including the molecule dopamine, with high temporal resolution. Currently the financial burden of performing FSCV is quite high, ranging from $8,000 to $20,000+ making the barrier to entry nearly insurmountable for laboratories and classrooms at small institutions. The purpose of this project was to develop a Do-It-Yourself (DIY), portable, and cost-effective FSCV system for use in laboratory and classroom settings. The project aimed to create a compact and cost-effective system that could be used by researchers and educators to study dopamine …

Multivariate Analysis Of The Temporal And Spatial Correlations Of The Global Human Rights Dataset, Amanda Goodrick, Skip Mark, Mikhail G. Filippov, David Cingranelli, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

We propose an extension of a previously proposed method for lead-lag analysis of multivariate time series to include the analysis of spatial correlations. We applied the extended spatial and temporal method to CIRIGHTS, a large global human rights dataset, in order to determine the most influential and most influenced indicators of human rights, freedoms, and atrocities over time. We consider four target countries, each from a different continent. The previously proposed method used a weighted directed network with several lags of each variable as nodes and with edges weighted by transfer entropy. In this study, that method is extended to …

Evaluating The Role Of Data Enrichment Approaches Towards Rare Event Analysis In Manufacturing, Chathurangi Shyalika, Ruwan Wickramarachchi, Fadi El Kalach, Ramy Harik, Amit P. Sheth

Publications

Rare events are occurrences that take place with a significantly lower frequency than more common, regular events. These events can be categorized into distinct categories, from frequently rare to extremely rare, based on factors like the distribution of data and significant differences in rarity levels. In manufacturing domains, predicting such events is particularly important, as they lead to unplanned downtime, a shortening of equipment lifespans, and high energy consumption. Usually, the rarity of events is inversely correlated with the maturity of a manufacturing industry. Typically, the rarity of events affects the multivariate data generated within a manufacturing process to be …

Evaluation Of The Alveolar Crest And Cemento-Enamel Junction In Periodontitis Using Object Detection On Periapical Radiographs, Tai Jung Lin, Yi Cheng Mao, Yuan Jin Lin, Chin Hao Liang, Yi Qing He, Yun Chen Hsu, Shih Lun Chen, Tsung Yi Chen, Chiung An Chen, Kuo Chen Li, Patricia Angela R. Abu

Ateneo Laboratory for Intelligent Visual Environments

The severity of periodontitis can be analyzed by calculating the loss of alveolar crest (ALC) level and the level of bone loss between the tooth’s bone and the cemento-enamel junction (CEJ). However, dentists need to manually mark symptoms on periapical radiographs (PAs) to assess bone loss, a process that is both time-consuming and prone to errors. This study proposes the following new method that contributes to the evaluation of disease and reduces errors. Firstly, innovative periodontitis image enhancement methods are employed to improve PA image quality. Subsequently, single teeth can be accurately extracted from PA images by object detection with …

Reinforcement Learning Assisted Communication Resources Optimization In Advanced Air Mobility., Ruixuan Han

Electronic Theses and Dissertations

Advanced air mobility (AAM), which envisages a safe and efficient aviation transportation system, has drawn significant attention to support the increasing mobility demand in metropolitan areas. Communication services for AAM aerial vehicles (AVs) are crucial for ensuring flight safety. This dissertation explores three research topics on communication resource allocation problems in AAM applications. The first topic, addressed in Chapter II, investigates the joint velocity selection and spectrum allocation problem for AAM applications to enhance spectrum utilization efficiency (SUE). In the AAM scenario, multiple AVs travel along predefined paths for passenger and cargo deliveries. Given that AAM aims to provide fast …

Deep Reinforcement Learning-Based Dynamic Routing And Spectrum Access In Aeronautical Networks., Zhe Wang

Electronic Theses and Dissertations

As the airspace is experiencing an increasing number of aircraft, spectrum sharing among Air Vehicles (AVs) and Terrestrial Users (TUs) emerges as a compelling solution to improve spectrum utilization efficiency. I investigated three types of aeronautical communication including the single-hop Air-Air Communication Network (AACN), the multi-hop Air-Air Ad-hoc Network (AAAN), and the Aerial and Terrestrial Hybrid Network (ATHN). I assume a spectrum-limited scenario through all communication networks. Thus, the number of communication pairs is greater than that of the available channels, resulting in co-channel interference due to the reuse of the same channel among communication links. In a single-hop AACN, …

Development And Processing Of Shape Memory Polymer Composites (Smpcs) For Application In Structural Robotics And Robotic Sensors., Kavish Sudan

Electronic Theses and Dissertations

Shape Memory Polymers (SMPs) have attracted significant attention since their introduction in the 1980s due to their remarkable ability to regain their original shape from a temporarily deformed state when exposed to an external stimulus, typically heat. This shape memory effect, driven by thermal transitions such as the glass transition temperature (T_g) or melting temperature (T_m), has made SMPs highly attractive for applications in soft robotics, aerospace, and biomedical devices. However, SMPs face challenges such as limited mechanical strength, thermal stability, and electrical conductivity, which hinder their broader adoption in advanced applications. To address these challenges, …

Fault Detection And Location In Renewable-Fed Distribution Systems Using Low Voltage Sensors, Bushra Farhat

All Theses

The penetration of Distributed Energy Resources (DERs) into the Electric Power System (EPS) is increasing. These (DERs) are mostly inverter-based resources (IBRs) that are integrated into (EPS) at the distribution level. Therefore, it has become necessary to leverage the integration of (IBRs) for both commercial and residential distribution systems through the deployment of Microgrid (MG). However, existing distribution systems that use fuses for sensing and isolating faults are not equipped to handle protection of microgrids where fault currents are fed from multiple sources and can flow downstream or upstream. Bulk of the protection schemes proposed in literature are heavily dependent …

Using Efficient Vision Transformers To Improve Perception Systems In Autonomous Off-Road Vehicles, Adam S. Pickeral

All Theses

The development of autonomous vehicles has become one of the greatest research endeavors in recent years. These vehicles rely on many complex systems working in tandem to make decisions. For practical use and safety reasons, these systems must not only be accurate, but also be quick to make decisions. In Autonomous Vehicle research, the environment perception system is one of the key com- ponents of development. The environment perception system allows the vehicle to understand its surroundings using cameras, light detection and ranging (LiDAR), and other sensor systems or modalities. Deep learning computer vision algorithms have shown to be the …

Applying Circuit Theory To Describe Changes In Structural Landscape Connectivity In Response To Wildfire, Christian Ross Nielsen

School of Natural Resources: Dissertations, Theses, and Student Research

Understanding and conserving ecological connectivity is critical to the preservation of vulnerable landscapes. Circuit theory, in which landscapes are imagined as circuit boards with varying resistances to the flow of current, is being increasingly used to model spatially explicit connectivity of landscapes and to inform land management and conservation decision-making. Utilizing continuous, quantitative estimates of percent cover by five land cover functional groups to create a conductance surface, this study expanded upon an established application of circuit theory that used the open-source software Circuitscape to model species-agnostic, omnidirectional connectivity. This model was automated using Python to create time-series connectivity maps …

Power Controller For Insulated Solar Electric Cooker, Ryan Koshy, Justin Tae-Hoon Kim

Electrical Engineering

Insulated Solar Electric Cookers, or ISECookers, are devices created to aid those in impoverished regions improve safety, sustainability, and quality of life regarding their cooking practices. ISECookers present an alternative to traditional biofuel/biomass energy sources and provide a closed-loop, self-sustaining system that can be used in a variety of environments. These devices present solutions to widespread issues such as pollution, deforestation, and hazardous emissions as a result of traditional cooking in developing regions around the world. A notable obstacle of these devices is power delivery. Given the varying conditions experienced by a solar panel (inclement weather, irradiance irregularities, etc.), it …

Image Processing Techniques For Water Droplet Penetration Time And Contact Angle Estimation, Sai Balaji Jai Kumar

UNLV Theses, Dissertations, Professional Papers, and Capstones

Water droplet behavior on soil surfaces plays a critical role in numerous environmental processes, including soil erosion, hydrological dynamics, and ecosystem health. Accurate characterization of soil water repellency, quantified by parameters such as water droplet penetration time (WDPT) and contact angles (WDCA), is essential for informed decision-making in agricultural management, forestry practices, and land-use planning. Despite the significance of these parameters, challenges exist in reliably estimating them due to the complex and dynamic nature of soil-water interactions. This thesis address challenges in estimating WDPT and WDCA, by leveraging state-of-the-art image processing techniques and machine learning algorithms. The research focuses on …

A Heuristic Approach To Operations And Control Of Btm-Ders For Bill Management And Grid Services, Md Arshad Rashid Shaon

UNLV Theses, Dissertations, Professional Papers, and Capstones

Behind-The-Meter (BTM) distributed energy resources (DERs) have emerged as a critical and transformative force within the energy sector. These decentralized energy assets, which include solar photovoltaic (PV) systems, battery energy storage systems (BESS), and thermostatically controlled loads (TCLs), are increasingly essential for empowering customers by granting them greater control over their energy production and consumption, thereby reducing reliance on centralized power sources. Additionally, they have the potential to play a pivotal role in enhancing grid resilience by providing grid services. This study investigates the management of customer electricity bills and grid services through the integration of various BTM-DERs, particularly solar …

Gps-Denied Navigation Using Location Estimation And Texel Image Correction, Nikolas I. Jensen

All Graduate Theses and Dissertations, Fall 2023 to Present

In recent years, the use of small drones, also categorized as small Unmanned Aerial Vehicles (sUAV), has surged. They are used for tasks like surveying land, collecting data from a distance, and performing maneuvers for military operations. These drones are popular because they are affordable, small, easy to use, and can navigate well in complex areas. These factors make them a cheap and quick option for tasks like surveying and surveillance when compared to traditional methods.

This thesis introduces a system that uses algorithms to figure out where the drone is. Typically, this relies on sensors and GPS, but GPS …

Federated Learning In Wireless Networks, Xiang Ma

All Graduate Theses and Dissertations, Fall 2023 to Present

Artificial intelligence (AI) is transitioning from a long development period into reality. Notable instances like AlphaGo, Tesla’s self-driving cars, and the recent innovation of ChatGPT stand as widely recognized exemplars of AI applications. These examples collectively enhance the quality of human life. An increasing number of AI applications are expected to integrate seamlessly into our daily lives, further enriching our experiences.

Although AI has demonstrated remarkable performance, it is accompanied by numerous challenges. At the forefront of AI’s advancement lies machine learning (ML), a cutting-edge technique that acquires knowledge by emulating the human brain’s cognitive processes. Like humans, ML requires …

Ensemble Machine Learning At The Edge Using The Codec Classifier Structure And Weak Learners Guided By Mutual Information, Aj Beckwith

All Graduate Theses and Dissertations, Fall 2023 to Present

The Codec Classifier is a low-computation, low-memory tree ensemble method that dramatically improves feasibility of image classification on resource-constrained edge devices. It achieves advantages over other tree ensemble methods due the separation of encoder and decoder tasks in the classifier. The encoder partitions feature space, and the decoder labels the regions in the partition. This functional separation of tasks enables the encoder design (partitioning) to be guided by maximizing the mutual information (MI) between class labels and the features (i.e. the encoded representation of the data) without regard to the error performance of the classifier. Experiments show maximizing MI leads …

A Position Allocation Approach To The Battery Electric Bus Charging Problem, Alexander Brown

All Graduate Theses and Dissertations, Fall 2023 to Present

With an increasing adoption of Battery Electric Bus (BEB) fleets, developing a reliable charging schedule is vital to a successful migration from their fossil fuel counterparts. In this work, a BEB charging scheduling framework that considers fixed route schedules, multiple charger types, and battery dynamics is modeled as a Mixed Integer Linear Program (MILP). The MILP is modeled after the Berth Allocation Problem (BAP) in a modified form known as the Position Allocation Problem (PAP). The optimization coordinates BEB charging to ensure that each vehicle remains above a specified charge percentage. The model also minimizes the total number of chargers …

Anomaly Detection On Wind Turbine Blades Using Aerial Imaging, Image Processing, And Deep Learning, Bridger Kohl Altice

All Graduate Theses and Dissertations, Fall 2023 to Present

In reaction to rising global temperatures and carbon dioxide emissions, many countries are looking to use energy sources other than fossil fuels. One such source of energy is wind energy, which can be harvested by wind turbines. By rotating at high speeds, the blades of these large turbines are able to convert wind energy to kinetic energy, which is then converted to electricity usable by the power grid. Traditional methods for inspecting these turbines for damages are expensive, unsafe, and susceptible to human error. These turbines are so tall and so large that inspectors run the risk of falling from …