Engineering Commons^™

Plasma-Based Water Purification For Crewed Space Missions: Laboratory Experimental Comparisons For On-Board Applicability, Ryan P. Gott, Sydney D. Miller, Josie C. Hodges, Kunning G. Xu

PRC-Affiliated Research

Low-temperature, atmospheric pressure plasma presents a new, inexpensive, and environmentally friendly method of water purification. For long duration crewed space missions, a novel water purification system that does not rely on consumable filters and chemicals would be desirable. Plasma systems provide a viable option for these missions, but their operation and designs need to be optimized and compared to existing technology. For this application, gas and power usage are key limiting factors. In this work, water contaminated with methylene blue is purified with plasma. The rate of purification, gas flow usage, and power consumption are compared for multiple devices. A …

Characterization Of Wide-Bandgap Sic Field Effect Transistors And Their Active Gate Driving Circuit In High Power Applications, Arijit Sengupta

Legacy Theses & Dissertations (2009 - 2024)

Silicon Carbide (SiC) devices are slowly becoming one of the most reliable choices for high power density, high switching frequency applications with higher efficiency than Gallium Nitride (GaN) and Silicon (Si) devices. For a wide range of applications, such as Electric Motor Drives, Switching Power Supplies, and Renewable Energy Circuits, SiC devices are being tested and are found to yield prominent results.In this research, the characterization of two similarly rated commercially available SiC devices - a trench Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) and a cascoded Junction Field Effect Transistor (JFET) are done. It is followed by a comparative analysis of both …

Learning And Exploiting Shaped Reward Models For Large Scale Multiagent Rl, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Many real world systems involve interaction among large number of agents to achieve a common goal, for example, air traffic control. Several model-free RL algorithms have been proposed for such settings. A key limitation is that the empirical reward signal in model-free case is not very effective in addressing the multiagent credit assignment problem, which determines an agent's contribution to the team's success. This results in lower solution quality and high sample complexity. To address this, we contribute (a) an approach to learn a differentiable reward model for both continuous and discrete action setting by exploiting the collective nature of …

Vehicle Routing: Review Of Benchmark Datasets, Aldy Gunawan, Graham Kendall, Barry Mccollum, Hsin-Vonn Seow, Lai Soon Lee

Research Collection School Of Computing and Information Systems

The Vehicle Routing Problem (VRP) was formally presented to the scientific literature in 1959 by Dantzig and Ramser (DOI:10.1287/mnsc.6.1.80). Sixty years on, the problem is still heavily researched, with hundreds of papers having been published addressing this problem and the many variants that now exist. Many datasets have been proposed to enable researchers to compare their algorithms using the same problem instances where either the best known solution is known or, in some cases, the optimal solution is known. In this survey paper, we provide a list of Vehicle Routing Problem datasets, categorized to enable researchers to have easy access …

Learning And Exploiting Shaped Reward Models For Large Scale Multiagent Rl, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Many real world systems involve interaction among large number of agents to achieve a common goal, for example, air traffic control. Several model-free RL algorithms have been proposed for such settings. A key limitation is that the empirical reward signal in model-free case is not very effective in addressing the multiagent credit assignment problem, which determines an agent's contribution to the team's success. This results in lower solution quality and high sample complexity. To address this, we contribute (a) an approach to learn a differentiable reward model for both continuous and discrete action setting by exploiting the collective nature of …

Thunderrw: An In-Memory Graph Random Walk Engine, Shixuan Sun, Yuhang Chen, Shengliang Lu, Bingsheng He, Yuchen Li

Research Collection School Of Computing and Information Systems

As random walk is a powerful tool in many graph processing, mining and learning applications, this paper proposes an efficient inmemory random walk engine named ThunderRW. Compared with existing parallel systems on improving the performance of a single graph operation, ThunderRW supports massive parallel random walks. The core design of ThunderRW is motivated by our profiling results: common RW algorithms have as high as 73.1% CPU pipeline slots stalled due to irregular memory access, which suffers significantly more memory stalls than the conventional graph workloads such as BFS and SSSP. To improve the memory efficiency, we first design a generic …

Context-Aware Outstanding Fact Mining From Knowledge Graphs, Yueji Yang, Yuchen Li, Panagiotis Karras, Anthony Tung

Research Collection School Of Computing and Information Systems

An Outstanding Fact (OF) is an attribute that makes a target entity stand out from its peers. The mining of OFs has important applications, especially in Computational Journalism, such as news promotion, fact-checking, and news story finding. However, existing approaches to OF mining: (i) disregard the context in which the target entity appears, hence may report facts irrelevant to that context; and (ii) require relational data, which are often unavailable or incomplete in many application domains. In this paper, we introduce the novel problem of mining Contextaware Outstanding Facts (COFs) for a target entity under a given context specified by …

Automated Taxi Queue Management At High-Demand Venues, Mengyu Ji, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

In this paper, we seek to identify an effective management policy that could reduce supply-demand gaps at taxi queues serving high-density locations where demand surges frequently happen. Unlike current industry practice, which relies on broadcasting to attract taxis to come and serve the queue, we propose more proactive and adaptive approaches to handle demand surges. Our design objective is to reduce the cumulative supply-demand gaps as much as we could by sending notifications to individual taxis. To address this problem, we first propose a highly effective passenger demand prediction system that is based on the real-time flight arrival information. By …

A Lagrangian Column Generation Approach For The Probabilistic Crowdsourced Logistics Planning, Chung-Kyun Han, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

In recent years we have increasingly seen the movement for the retail industry to move their operations online. Along the process, it has created brand new patterns for the fulfillment service, and the logistics service providers serving these retailers have no choice but to adapt. The most challenging issues faced by all logistics service providers are the highly fluctuating demands and the shortening response times. All these challenges imply that maintaining a fixed fleet will either be too costly or insufficient. One potential solution is to tap into the crowdsourced workforce. However, existing industry practices of relying on human planners …

Estimating Homophily In Social Networks Using Dyadic Predictions, George Berry, Antonio Sirianni, Ingmar Weber, Jisun An, Michael Macy

Research Collection School Of Computing and Information Systems

Predictions of node categories are commonly used to estimate homophily and other relational properties in networks. However, little is known about the validity of using predictions for this task. We show that estimating homophily in a network is a problem of predicting categories of dyads (edges) in the graph. Homophily estimates are unbiased when predictions of dyad categories are unbiased. Node-level prediction models, such as the use of names to classify ethnicity or gender, do not generally produce unbiased predictions of dyad categories and therefore produce biased homophily estimates. Bias comes from three sources: sampling bias, correlation between model errors …

A Manufacturing-To-Response Pathway For Formed Carbon Fiber Reinforced Polymer Composite Structures, Madhura Limaye

All Theses

Over the past decade, there has been an increased adoption of thermoplastic and thermoset based continuous carbon fiber reinforced polymer (CFRP) composites for structural applications in several industries. Among the different manufacturing methods, thermoforming process for thermoplastic based continuous CFRP’s offer a major advantage in reducing cycle times for large scale productions. Similarly, out-of-autoclave curing process for thermoset based continuous CFRP’s using heated tooling enables production of large composite structures. However, these manufacturing processes can have a significant impact on the structural performance of parts by inducing undesirable effects. These effects include inhomogeneous fiber orientations, thickness variations, and residual stresses …

Fast Magnetic Resonance Image Reconstruction With Deep Learning Using An Efficientnet Encoder, Tahsin Rahman

Open Access Theses & Dissertations

This thesis aims to develop an efficient, deep network based method for Magnetic Resonance Imaging (MRI) acceleration through undersampled MR image reconstruction. Deep Neural Networks, particularly Deep Convolutional Networks, have been demonstrated to be highly effective in a wide variety of computer vision tasks, including MRI reconstruction. However, modern highly efficient encoder structures, such as the EfficientNet can potentially reduce reconstruction times further while improving reconstruction quality. To that end, we have developed a multi-channel U-Net MRI reconstruction network which uses an EfficientNet encoder and a custom asymmetric. The network was trained and tested using 5x undersampled multi-channel brain MR …

High-Density Parking For Autonomous Vehicles., Parag J. Siddique

Electronic Theses and Dissertations

In a common parking lot, much of the space is devoted to lanes. Lanes must not be blocked for one simple reason: a blocked car might need to leave before the car that blocks it. However, the advent of autonomous vehicles gives us an opportunity to overcome this constraint, and to achieve a higher storage capacity of cars. Taking advantage of self-parking and intelligent communication systems of autonomous vehicles, we propose puzzle-based parking, a high-density design for a parking lot. We introduce a novel method of vehicle parking, which leads to maximum parking density. We then propose a heuristic method …

Signal Fingerprinting And Machine Learning Framework For Uav Detection And Identification., Olusiji Oloruntobi Medaiyese

Electronic Theses and Dissertations

Advancement in technology has led to creative and innovative inventions. One such invention includes unmanned aerial vehicles (UAVs). UAVs (also known as drones) are now an intrinsic part of our society because their application is becoming ubiquitous in every industry ranging from transportation and logistics to environmental monitoring among others. With the numerous benign applications of UAVs, their emergence has added a new dimension to privacy and security issues. There are little or no strict regulations on the people that can purchase or own a UAV. For this reason, nefarious actors can take advantage of these aircraft to intrude into …

Rapid Annealing Of Perovskite Solar Cell Thin Film Materials Through Intense Pulse Light., Amir Hossein Ghahremani

Electronic Theses and Dissertations

Perovskite solar cells (PSCs) have garnered a great attention due to their rapid efficiency improvement using cheap and solution processable materials that can be adapted for scalable high-speed automated manufacturing. Thin film perovskite photovoltaics (PVs) are typically fabricated in an inert environment, such as nitrogen glovebox, through a set of deposition and annealing steps, each playing a significant role on the power conversion efficiency (PCE), reproducibility, and stability of devices. However, atmospheric processing of PSCs would achieve lucrative commercialization. Therefore, it is necessary to utilize materials and methods that enable successful fabrication of efficient PSCs in the ambient environment. The …

Biometric Features Modeling To Measure Students Engagement., Islam Mohamed Ahmed Mohamed Mahmoud Alkabbany

Electronic Theses and Dissertations

The ability to measure students’ engagement in an educational setting may improve student retention and academic success, revealing which students are disinterested, or which segments of a lesson are causing difficulties. This ability will facilitate timely intervention in both the learning and the teaching process in a variety of classroom settings. In this dissertation, an automatic students engagement measure is proposed through investigating three main engagement components of the engagement: the behavioural engagement, the emotional engagement and the cognitive engagement. The main goal of the proposed technology is to provide the instructors with a tool that could help them estimating …

Cosine-Based Explainable Matrix Factorization For Collaborative Filtering Recommendation., Pegah Sagheb Haghighi

Electronic Theses and Dissertations

Recent years saw an explosive growth in the amount of digital information and the number of users who interact with this information through various platforms, ranging from web services to mobile applications and smart devices. This increase in information and users has naturally led to information overload which inherently limits the capacity of users to discover and find their needs among the staggering array of options available at any given time, the majority of which they may never become aware of. Online services have handled this information overload by using algorithmic filtering tools that can suggest relevant and personalized information …

Motion And Emotion Estimation For Robotic Autism Intervention., Jacob M Berdichevsky

Electronic Theses and Dissertations

Robots have recently emerged as a novel approach to treating autism spectrum disorder (ASD). A robot can be programmed to interact with children with ASD in order to reinforce positive social skills in a non-threatening environment. In prior work, robots were employed in interaction sessions with ASD children, but their sensory and learning abilities were limited, while a human therapist was heavily involved in “puppeteering” the robot. The objective of this work is to create the next-generation autism robot that includes several new interactive and decision-making capabilities that are not found in prior technology. Two of the main features that …

Variable Autonomy Assignment Algorithms For Human-Robot Interactions., Christopher Kevin Robinson

Electronic Theses and Dissertations

As robotic agents become increasingly present in human environments, task completion rates during human-robot interaction has grown into an increasingly important topic of research. Safe collaborative robots executing tasks under human supervision often augment their perception and planning capabilities through traded or shared control schemes. However, such systems are often proscribed only at the most abstract level, with the meticulous details of implementation left to the designer's prerogative. Without a rigorous structure for implementing controls, the work of design is frequently left to ad hoc mechanism with only bespoke guarantees of systematic efficacy, if any such proof is forthcoming at …

Multilateration Index., Chip Lynch

Electronic Theses and Dissertations

We present an alternative method for pre-processing and storing point data, particularly for Geospatial points, by storing multilateration distances to fixed points rather than coordinates such as Latitude and Longitude. We explore the use of this data to improve query performance for some distance related queries such as nearest neighbor and query-within-radius (i.e. “find all points in a set P within distance d of query point q”). Further, we discuss the problem of “Network Adequacy” common to medical and communications businesses, to analyze questions such as “are at least 90% of patients living within 50 miles of a covered emergency …

Linking Social Media, Medical Literature, And Clinical Notes Using Deep Learning., Mohsen Asghari

Electronic Theses and Dissertations

Researchers analyze data, information, and knowledge through many sources, formats, and methods. The dominant data format includes text and images. In the healthcare industry, professionals generate a large quantity of unstructured data. The complexity of this data and the lack of computational power causes delays in analysis. However, with emerging deep learning algorithms and access to computational powers such as graphics processing unit (GPU) and tensor processing units (TPUs), processing text and images is becoming more accessible. Deep learning algorithms achieve remarkable results in natural language processing (NLP) and computer vision. In this study, we focus on NLP in the …

Aggregation Dynamics Of Bulk Nanoparticle Haloing Systems And The Influence Of Non-Ambient Temperatures., Marzieh Moradi

Electronic Theses and Dissertations

One of the methods of assembling colloids into 3D crystal structures is through the use of nanoparticle haloing. Nanoparticle haloing is a stabilization mechanism in binary particle suspensions possessing both a size and charge asymmetry, with which the nanoparticles aid in the bulk suspension’s stability. By altering the volume fractions of nanoparticles, it is possible to control the effective repulsion between the microparticles. Understanding the colloidal interactions and aggregate crystallinity as a function of nanoparticle concentration, temperature, and time are key challenges in developing future materials and designing crystalized 3D colloidal systems. In this study, we investigated the effect of …

In Vitro Osteogenic Performance Of Two Novel Strontium And Zinc-Containing Glass Polyalkenoate Cements, Daniella Marx, Alireza Rahimnejad Yazdi, Marcello Papini, Mark R. Towler

Chemical and Biochemical Engineering Faculty Research & Creative Works

Glass polyalkenoate cements (GPCs) are under investigation as potential bone adhesives, as they may provide an alternative to polymethylmethacrylate-based cements. GPCs containing strontium (Sr) and zinc (Zn) in place of aluminum (Al) are of particular interest because these ions are known stimulators of osteoprogenitor differentiation. GPCs have been manufactured from a novel bioactive glass (SiO2:0.48, ZnO:0.36, CaO:0.12, SrO:0.04) in the past, but, while such materials have been assessed for their influence on viability, their influence on osteogenic function has not been investigated until now. For this study, two GPCs were formulated from the same glass precursor evaluated in previous studies. …

Development Of Tractor Instrumentation System: Hydraulics, And Controller Area Network (Can) Data Analysis Of Agricultural Machinery, Chee Town Liew

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

The tractor is a very important piece of machinery in agriculture, and it has been evolving and progressing over the years with improved and increasingly complex functionality. Controller Area Network (CAN) has been incorporated into tractors and other machinery with SAE J1939 and ISO 11783 standards, serving as the communication bus for various on-board electronic controller units (ECUs), and carries various machine operation data that can be used for analyzing machine performance. Investigation of data extraction from CAN messages was conducted by examining the SAE J1939 and ISO 11783 standards. A case study on CAN bus data analysis for a …

Tractor Instrumentation System: Hitch And Pto, And Row Crop Tractor Electrification Considerations, Andrew Donesky

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Power sources used for vehicles are advancing at a fast pace. Electric batteries are becoming more power dense, thus allowing them to be used with electric motors in place of a diesel or gas powered systems. There are several ways that energy use and storage size can be computed for agricultural field operations, such as planting, using theoretical predictions, gathering engine load data from tractor’s Controller Area Network (CAN) bus, or integrating the CAN data to determine the actual power used by implements.

While measuring data from the CAN bus is a great way to capture actual tractor use information, …

Adaptive Activations And Shift Invariance In Shallow Convolutional Neural Networks, Chinmay Appa Rane

Electrical Engineering Dissertations - Archive

Deep learning training training algorithms are a huge success in recent years in many fields including speech, text,image video etc. Deeper and deeper layers are proposed with huge success with resnet structures having around 152 layers. Shallow convolution neural networks(CNN's) are still an active research, where some phenomena are still unexplanined. CNN's are assumed to be invariant to shift due to its architecture, but recent studies have shown other wise. Apart from shift invariance, activation functions used in the network are of utmost importance, as they provide non linearity to the networks. Relu's are the most commonly used activation function. …

New Infeed Correction Methods For Distance Protection In Distribution Systems, Fahd Hariri, Mariesa Crow

Electrical and Computer Engineering Faculty Research & Creative Works

The reliability and security of power systems may be jeopardized by the increase in the amounts of renewable generation and the uncertainties produced by these devices. In particular, the protection schemes of traditional power systems have been challenged by the integration of distributed generation (DG) resources. Distance relays (DRs), which have been mainly employed to protect transmission systems, are increasingly proposed as one of the solutions to protect distribution systems with a heavy penetration of DGs. However, conventional distance protection faces several drawbacks that might lead to maloperation. One of those challenges is the "infeed effect", which causes the impedance …

The Development Of Micro-Gas Chromatography System With Integrated Photonic Crystal Sensors, Priyanka Biswas

Electrical Engineering Dissertations - Archive

Miniaturization of gas chromatography (GC) systems have made it possible to utilize the analytical technique in on-site applications without having to compromise data reliability offered by the conventional benchtop GC. Various types of miniaturized microsensors and nanosensors have been developed for a micro-gas chromatography (µGC) system. However, integration of an appropriate detector in µGC systems still face significant challenge. We present a solution to the problem through integration of µGC with photonic crystal slab (PCS) sensors using transfer printing technology. This integration offers an opportunity to utilize the advantages of optical sensors such as high sensitivity, immunity to electromagnetic interference, …

Object Classication, Detection And State Estimation Using Yolo V3 Deep Neural Network And Sensor Fusion Of Stereo Camera And Lidar, Kamalkumar Bharatkumar Mehta

Mechanical and Aerospace Engineering Theses - Archive

Real-time object classification, localization, and detection with region-based convolution neural network (R-CNN) require high computational power, or it consumes a tremendous amount of time with the use of the available onboard computer system. Therefore, either of those ways is not practical in real-time object detection. In contrast, the YOLO-v3 network, which stands for you only look once, that uses the YOLO algorithm seems to be practical in live object classification, localization, and detection, since the YOLO algorithm seems to work faster than the sliding window algorithm used by R-CNN. Sensor fusion in this context requires estimation and association of information …

Development Of Eam And Rf-Meam Interatomic Potential For Zirconium Diboride, Bikash Timalsina

Graduate Theses/Dissertations

Embedded Atom Method (EAM) and Modified-EAM (MEAM) interatomic potentials were developed for zirconium diboride (ZrB₂). The EAM and “Reference Free” (RF) version of the Modified Embedded Atom Method (RFMEAM) potentials have been fitted by utilizing Density Functional Theory (DFT)-based datasets including lattice deformations and high-temperature ab-initio molecular dynamics (AIMD) simulation results. The occupancies of phonons for acoustic phonon modes from the density functional theory calculation shows that these modes of vibration, mostly due to heavier mass element (Zr), which occur below 8.711 THz, while a slight underestimation to that of DFT calculation predicted by EAM below 8.439 THz …