Engineering Commons^™

Aligning Human And Computational Coherence Evaluations, Jia Peng Lim, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Automated coherence metrics constitute an efficient and popular way to evaluate topic models. Previous work presents a mixed picture of their presumed correlation with human judgment. This work proposes a novel sampling approach to mining topic representations at a large scale while seeking to mitigate bias from sampling, enabling the investigation of widely used automated coherence metrics via large corpora. Additionally, this article proposes a novel user study design, an amalgamation of different proxy tasks, to derive a finer insight into the human decision-making processes. This design subsumes the purpose of simple rating and outlier-detection user studies. Similar to the …

Enhancing Multi-Agent System Testing With Diversity-Guided Exploration And Adaptive Critical State Exploitation, Xuyan Ma, Yawen Wang, Junjie Wang, Xiaofei Xie

Research Collection School Of Computing and Information Systems

Multi-agent systems (MASs) have achieved remarkable success in multi-robot control, intelligent transportation, and multiplayer games, etc. Thorough testing for MAS is urgently needed to ensure its robustness in the face of constantly changing and unexpected scenarios. Existing methods mainly focus on single-agent system testing and cannot be directly applied to MAS testing due to the complexity of MAS. To our best knowledge, there are fewer studies on MAS testing. While several studies have focused on adversarial attacks on MASs, they primarily target failure detection from an attack perspective, i.e., discovering failure scenarios, while ignoring the diversity of scenarios. In this …

Bugs In Pods: Understanding Bugs In Container Runtime Systems, Jiongchi Yu, Xiaofei Xie, Ceng Zhang, Sen Chen

Research Collection School Of Computing and Information Systems

Container Runtime Systems (CRSs), which form the foundational infrastructure of container clouds, are critically important due to their impact on the quality of container cloud implementations. However, a comprehensive understanding of the quality issues present in CRS implementations remains lacking. To bridge this gap, we conduct the first comprehensive empirical study of CRS bugs. Specifically, we gather 429 bugs from 8,271 commits across dominant CRS projects, including runc, gvisor, containerd, and cri-o. Through manual analysis, we develop taxonomies of CRS bug symptoms and root causes, comprising 16 and 13 categories, respectively. Furthermore, we evaluate the capability of popular testing approaches, …

Comparison Of Evolutionary Algorithms: A Case Study On The Multi-Objective Carbon-Aware Mine Planning, Nurul Asyikeen Binte Azhar, Aldy Gunawan, Shih-Fen Cheng, Erwin Leonardi

Research Collection School Of Computing and Information Systems

The NP-hard precedence-constrained production scheduling problem (PCPSP) for mine planning chooses the ordered removal of materials from the mine pit and the next processing steps based on resource, geological, and geometrical constraints. Traditionally, it prioritizes the net present value (NPV) of profits across the lifespan of the mine. Yet, the growing shift in environmental concerns also requires shifts to more carbon-aware practices. In this paper, we use the enhanced multi-objective version of the generic PCPSP formulation by adding the NPV of carbon costs as another objective. We then compare how the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Pareto …

Quantum Relaxation For Solving Multiple Knapsack Problems, Monit Sharma, Jin Yan, Hoong Chuin Lau, Rudy Raymond

Research Collection School Of Computing and Information Systems

Combinatorial problems are a common challenge in business, requiring finding optimal solutions under specified constraints. While significant progress has been made with variational approaches such as QAOA, most problems addressed are unconstrained (such as Max-Cut). In this study, we investigate a hybrid quantum-classical method for constrained optimization problems, particularly those with knapsack constraints that occur frequently in financial and supply chain applications. Our proposed method relies firstly on relaxations to local quantum Hamiltonians, defined through commutative maps. Drawing inspiration from quantum random access code (QRAC) concepts, particularly Quantum Random Access Optimizer (QRAO), we explore QRAO's potential in solving large constrained …

Two-Dimensional Quantum Material Identification Via Self-Attention And Soft-Labeling In Deep Learning, Xuan Bac Nguyen, Apoorva Bisht, Benjamin Thompson, Hugh O.H. Churchill, Khoa Luu, Samee U. Khan

Electrical Engineering and Computer Science Faculty Publications and Presentations

Detecting two-dimensional (2D) materials in silicon chips presents a significant challenge in the field of quantum machines due to the difficulty of data collection. Specifically, among thousands of flakes, not all flakes are useful or well-annotated, resulting in noisy and hard samples within the dataset, which challenges the deep neural network (DNN) to learn. To address this problem, we propose a novel method for identifying quantum 2D flakes even when there is a high rate of missing annotations in the input images. In particular, we first propose a new mechanism for automatically detecting false negative flakes that are missing annotations. …

Altered Cortical Activity During A Finger Tap In People With Stroke, Priya Balasubramanian, Roxanne P. Deleon, Dylan B. Snyder, Scott A. Beardsley, Allison S. Hyngstrom, Brian D. Schmit

Biomedical Engineering Faculty Research and Publications

This study describes electroencephalography (EEG) measurements during a simple finger movement in people with stroke to understand how temporal patterns of cortical activation and network connectivity align with prolonged muscle contraction at the end of a task. We investigated changes in the EEG temporal patterns in the beta band (13–26 Hz) of people with chronic stroke (N = 10, 7 F/3 M) and controls (N = 10, 7 F/3 M), during and after a cued movement of the index finger. We quantified the change in beta band EEG power relative to baseline as activation at each electrode and …

Validation Of Mobile Devices In Arbitrary Locations Against Force Plate Standard For Balance Assessment, German J. Ellsworth

Master's Theses

With balance assessment being essential to the prediction of fall risk and detection and assessment of motor disorders, increasing clinical accessibility to objective balance metrics is essential. Work has been done validating center of mass (COM) acceleration metrics against well regarded force plate center of pressure (COP) position standards for mobile device data acquisition systems, but most research is restricted to devices being close to the COM or strapped in a harness configuration. Through the use of rigid body kinematics and the inverted pendulum model, this study develops novel methodology for calculating COM acceleration using mobile devices in arbitrary positions, …

A Data-Driven Framework For Analyzing And Predicting Social Media Engagement During Rumor Propagation, Joseph E. Faza

Master's Theses

The spread of rumors on social media has become a significant concern, as platforms like X (formerly known as Twitter) enable rapid dissemination of unverified information. These rumors can shape public perception and behavior, making it crucial to understand the dynamics of their spread. The main objective of this study is to explore how users interact with rumor-related tweets and identify key factors that predict tweet engagement. By analyzing tweets from seven different rumor events, this research aims to uncover patterns in user engagement and provide insights into the spread of misinformation. The study utilized a dataset of tweets from …

Assessment Of Dune Change Using Historical Aerial And Satellite Photos, Topographic Surveys, And Wave Data At Toro Creek Beach, Owen D. Emerson

Master's Theses

Coastal sand dunes play an important role in the littoral processes of California’s coastline. Functioning as both source and sink for sand, these dunes often protect coastal infrastructure and provide a buffer between anthropogenic development and coastal forces. At Toro Creek Beach, north of Morro Bay California, recent extreme winter storms have raised concerns about the erosion of the sand dunes that front California State Highway 1. This thesis attempts to characterize the historical growth and recession patterns of the Toro Creek dunes since 1977, the dune movement over the 2023-2024 winter seasons, the wave forcings behind recent high erosion …

Seal Counting On Our Plages (S.C.O.O.P.), Kaanan Kharwa

Master's Theses

The Vertebrate Integrative Physiology (VIP) lab monitors the population of northern elephant seals at the largest mainland breeding colony, located at Piedras Blancas (San Simeon, CA). As the population expands, more human-seal interactions and conflicts over land use occur. The VIP lab's work informs California State Parks and helps with the management of the rookery. Currently, members of the VIP lab fly a drone over the beaches, capture multiple images, and manually count the seals, which takes around 14 to 21 hours of analysis per survey. Machine learning methods such as Convolutional Neural Networks (CNN) and Region-based Convolutional Neural Networks …

Investigating The Neurovascular Correlates Of Cognitive Function In Individuals With Spinal Cord Injury Using Functional Near-Infrared Spectroscopy, Donna Yali Chen

Dissertations

Individuals with spinal cord injury (SCI) have a 13 times greater risk of cognitive impairment than able-bodied individuals and commonly report symptoms of depression and anxiety. The reports of cognitive impairment in individuals with SCI are independent of concomitant brain injury. Although the direct cause of cognitive impairment in individuals with SCI is unknown, key contributors may include comorbid depression, chronic pain, anxiety, fatigue, brain injury, or cardiovascular dysfunction. Previous studies have focused on SCI at the level of the spinal cord but have under-investigated the supraspinal levels. Due to the lack of neuroimaging studies on SCI rehabilitation, it is …

A Micromagnetic Study Of Skyrmions In Thin-Film Multilayered Ferromagnetic Materials, Nicholas J. Dubicki

Dissertations

Magnetic skyrmions are topologically protected, localized, nanoscale spin textures in non-centrosymmetric thin ferromagnetic materials and heterostructures. At present they are of great interest to physicists for potential applications in information technology due to their particle-like properties and stability. In a system of multiple thin ferromagnetic layers, the stray field interaction was typically treated with various simplifications and approximations. It is shown that extensive analysis of the micromagnetic equations leads to an exact representation of the stray field interaction energy in the form of layer interaction kernels, a so-called 'finite thickness' representation. This formulation reveals the competition between perpendicular magnetic anisotropy …

Federated Learning Systems For Mobile Sensing Data, Xiaopeng Jiang

Dissertations

Federated Learning (FL) has emerged as a new distributed Deep Learning (DL) paradigm that enables privacy-aware training and inference on mobile devices with help from the cloud. This dissertation presents a comprehensive exploration of FL with mobile sensing data, covering systems, applications, and optimizations.

First, a mobile-cloud FL system, FLSys, is designed to balance model performance with resource consumption, tolerate communication failures, and achieve scalability. In FLSys, different DL models with different FL aggregation methods can be trained and accessed concurrently by different apps. In addition, FLSys provides advanced privacy-preserving mechanisms and a common API for third-party app developers to …

Data Driven Decision Making For Sustainable Planning And Operations Of Large Scale Networks, Bahareh Kargar

Dissertations

This dissertation explores data-driven decision-making networks, focusing on sustainable planning and operations for large-scale systems such as healthcare supply chains and power systems. One significant application in healthcare is the optimization of vaccine supply chains. An agent-based simulation-optimization modeling framework is developed to enhance the efficiency and sustainability of vaccine distribution. First, an agent-based epidemiological model of COVID-19 is extended to capture disease transmission dynamics and forecast the number of susceptible individuals and infections. Then, a sustainable vaccine supply chain considering the impacts of greenhouse gases is developed and integrated with the simulation model to minimize total costs and environmental …

Electrified Membrane For Water Treatment And Resource Recovery: Advancing Multiscale Strategies In Gas-Involving Reactions, Jianan Gao

Dissertations

Multifunctional, modular, and scalable water treatment technologies that operate without chemical additives are crucial for addressing global water pollution challenges. While traditional membrane-based separation processes are crucial for ensuring clean water supplies, they primarily focus on pollutant removal rather than on the upcycling of pollutants into valuable resources. Electrified membrane filtration presents a robust alternative, utilizing minimal or no chemical additives and harnessing electrical power to directly reduce contaminants or produce reactive oxidants or reductants on-site.

This dissertation is dedicated to the development of innovative electrochemically reactive membranes designed to address three major challenges: (1) the engineering of electrocatalysts with …

Microwave Catalysis-Enabled Membrane Processes For Microbial Inactivation, Fangzhou Liu

Dissertations

The COVID-19 pandemic has highlighted the urgent need for advanced technologies to combat virus transmission. Traditional membrane filtration technologies primarily serve as physical barriers, capturing pollutants but failing to inactivate microbial agents such as bacteria and viruses. These membranes typically target larger particles but are ineffective against sub-micrometer viral particles. Thus, there's a critical demand for membrane filtration processes that combine robust filtration with antifouling and reaction -enabled functions for efficient pathogen disinfection. This research explores a novel microwave-assisted membrane filtration process incorporating catalytic reactions to enhance microbial disinfection and prevent membrane fouling, offering a groundbreaking solution to global challenges …

Estimation Of Spo2 Levels And Heart Rate From Ppg Signals In The Presence Of Motion Artifacts, Chizhong Wang

Dissertations

In the rapidly advancing world of health technology, wearable devices are at the forefront, fundamentally changing how individuals monitor their health. The key to this transformation is photoplethysmography (PPG), a non-invasive optical method that measures blood flow variations through the skin by detecting changes in light absorption with each heartbeat. This capability makes PPG essential for monitoring vital signs such as heart rate and blood oxygen saturation(SpO₂). Furthermore, the utility of PPG signals has been extended beyond traditional health metrics to include human activity classification, offering a holistic perspective on an individual's physical health and activity levels, in …

Order-Picking Strategies And Efficiency Models For The Fulfillment Of Multi-Line E-Commerce Grocery Orders, Zijia Wang

Dissertations

The fulfillment process for Buy Online Pickup from Store grocery orders (BOPS-Grocery) is particularly challenging, given the large item count per order and the low-profit margins. This research investigates the BOPS-Grocery model and pursues the following objectives: (i) Defining and specifying the BOPS-Grocery fulfillment process. Differentiating the process from classical warehouse order picking., identifying performance objectives, and characterizing design options and facility layout. (ii) Modelling and developing order picking algorithms specific to the straight aisle section. Formulated as an order hatching problem with picker movement minimization. No order splitting, and (iii) modeling and developing order picking algorithms specific to the …

Collision Dynamics Of Compound Droplets In Microchannels: A Combined Numerical And Data-Driven Study, S M Abdullah Al Mamun

Dissertations

Understanding and predicting the hydrodynamic interactions of micron-scale droplets is crucial in a wide range of industrial and real-life applications, including microfluidics, pharmaceutics, drug delivery, food science, and enhanced oil recovery. These multi-phase and multi-scale phenomena are further complicated by the presence of core droplets of an immiscible fluid within shell droplets, known as compound droplets. The collisions and interactions of droplets in emulsions are influenced by various physical and geometric parameters, leading to distinct rheological and dynamic responses. This research employs numerical methods for a systematic parametric study of both simple and compound droplet pair collisions under confined shear …

Modular Reconfigurable Rotary Style Soft Pneumatic Actuators, Nicholas Pagliocca, Aatish Gupta, Joshua Knospler, Nand K. Singh, Mitja Trkov

Henry M. Rowan College of Engineering Departmental Research

Modular soft robots have the advantage in their ability to be reconfigured and change their morphology on-demand according to a specified task. The actuator design and particularly the inter-unit connectivity strength commonly govern the usability and functionality of these modular robots and their applications. In this paper, we present development of reconfigurable modular rotary soft actuators that allow the construction of highly versatile soft robotic actuators and systems. These pneumatically driven modular actuators are composed of an inner balloon and a flexible arched reinforcement structure to produce a rotary motion. They serve as building blocks which may be combined in …

Faculty Perspectives On Research Mentoring Across A Multi-Level Statewide Lsamp Alliance, Tokesha Warner, Shaniqua Nixon, Terrance Mcneil, Denise Green, John T. Robinson

The Journal of the Research Association of Minority Professors

In this, mixed-method exploratory sequential design study, we examined a multi-level state-wide mentoring program for underrepresented students in science, technology, engineering, and mathematics (STEM). This study examined faculty perspectives on the factors involved in, and the impact of, mentoring minoritized students at the critical retention-to-graduation stage. Between 2020 and 2022, an online survey and two rounds of focus group interviews were conducted with faculty members at participating institutions. Data were analyzed using an iterative, thematic coding method. Analysis of the comments from faculty focus groups and a faculty survey revealed eleven themes that codified the faculty member’s perspectives on mentoring. …

Investigations On Structure-Related Properties Of Organic Inorganic Hybrid Materials For Multifunction, Anu Ranjani E Ms

Theses and Dissertations

Two-dimensional (2D) hybrid halide perovskites have become a versatile material in diverse applications like optoelectronics, lighting and display, magnetism, etc. These materials are often termed as layered hybrid halide perovskites (LHHPs) due to their unique structure with alternate organic and inorganic layers. The presence of insulating organic layers separates the inorganic perovskite slabs, creating a quantum-confined architectural configuration. This unique configuration endows these materials with a spectrum of distinctive functionalities, encompassing photovoltaics, lighting and displays, second harmonic generation, optical limiting, ferroelectricity, and ferromagnetism. The exceptional attribute is that a single LHHP can respond autonomously to external stimuli, such as changes …

Enhancing Security And Privacy For Smarter Environment Through A Robust Cyber-Physical System Framework, Ramya S

Theses and Dissertations

As digital computing paradigm and practices have emerged in disciplines, devices with processors and sensors were rudimentary, performing independent tasks with limited power. The first computer processors were slow, bulky and consuming high energy, as sensors in thermometers and pressure gauges provide original, independent measurements without effective communication, 1999. It often required powerful, energy-efficient processors and advanced sensors to enable seamless communication and sophisticated data processing.

These devices, since smart home systems to industrial automation tools, which continuously collect, analyse and share data via the internet, facilitating if real-time management, predictive maintenance, and improved seamless experience are used, transforming everyday …

Deep Learning Technique For The Classification Of Stress Among The Students Using Physiological Biomarkers With A Hybrid Feature Approach, Rajendran Vg

Theses and Dissertations

Adolescence is a crucial part in life, and the presence of stress, anxiety, depression, and health issues during this stage is a great concern. This research aims to analyze and predict the cognitive stress in students during the examination period using EEG biomarkers. In this study, raw EEG data is acquired under two different experimental conditions, before and after examination, from 14 subjects with an eight-channel Enobio device. After preprocessing of the EEG signal, the brain rhythms such as theta, alpha, and beta sub-band energies and EEG band ratios such as neural activity, heart rate, arousal index, vigilance index and …

Ai In Healthcare: Early Diagnosis Of Skin Cancer Using Medical Image Processing And Deep Neural Networks, Nirmala V

Theses and Dissertations

Several cancer types are commonly prevalent, and skin cancer is one among them, becoming even more widespread worldwide in the last few decades. To diagnose skin cancer at an early stage and obtain appropriate therapy to treat it, there is a demand to know more about the disease’s characteristics or severity. Skin cancer is caused mainly by various reasons, including damage of the sun or tanning beds by ultraviolet light exposure.

Failing to treat skin cancer might substantially impair an individual’s quality of life as the victim. They likely to experience physical issues linked with the deformities caused by psychological …

Effect Of Gas Tungsten Arc Welding Process Variants On The Microstructure And Properties Of Az31b Magnesium Alloy And 304hcu Austenitic Stainless Steel Welds, Srinivasan S

Theses and Dissertations

The automotive and aero sectors seek materials with high specific strength & specific stiffness for enhanced efficiency / emission control. Mg alloys, known for their low density, are used in the as-cast, and wrought forms, depending on the service requirements, and are predominantly used for non-loaded structural parts in varied engineering applications. Welding Mg alloys is of great interest to industry, not only for the fabrication of components but for the repair welding of casting as well. There has been considerable research in the fusion & solid-state welding of Mg alloys. Gas tungsten arc welding (GTAW) has often been preferred …

Investigation On Production, Kinetic Modelling, Downstream Processing, And Characterization Of Microbial Dextran Using Sucrose-Rich Alternate Feedstocks, Sameeha Syed Ar

Theses and Dissertations

Microbial exopolysaccharides (EPS) synthesized by microorganisms have a wide range of applications from thickener agents in the field of food to formulations in the field of pharmaceuticals. Owing to their rheological, structural, and physicochemical characteristics in addition to its biodegradability, low antigenicity, antioxidant activities, etc., several EPS have gained research focus in recent years. Dextran is one such example of EPS, which is synthesized by lactic acid bacteria (LAB). However, its production is limited to utilization of sucrose medium with a yield of 0.3-0.4 g dextran/ g sucrose. Hence, this thesis work focuses on dextran production using sucrose-rich alternate feedstocks …

Experimental Investigation And Evaluation Of Mechanical Properties And Microstructural Characterization On Chromium Molybdenum Steel Processed Through Laser Based Welding, Rakesh S

Theses and Dissertations

Creep Strength Enhanced Ferritic (CSEF) martensitic modified 9Cr-1Mo (P91) steel is extensively employed in fast breeder nuclear reactors and thermal power plants owing to its superior resistance to thermal fatigue and oxidation corrosion compared with other low-alloy steels. Despite its excellent high-temperature performance, the weldability of this steel remains a critical concern.

Conventional arc welding processes generate excessive heat input and complex thermal cycles, resulting in heterogeneous microstructures, retention of δ-ferrite, and subsequent degradation in service life. In contrast, high energy density beam welding techniques such as laser and electron beam welding offer precise thermal control and minimal heat-affected zones …

Remote Sensing Assessment Of Ionospheric Total Electron Content Over Thanjavur Gps Station Geomagnetic 2.91 N 152.22 E, Veera Kumar Maheswaran

Theses and Dissertations

A Global Positioning System (GPS) station for ionosphere studies was established during December 2019 in Thanjavur (Geographic 10.72◦ E, 79.01◦ N, Geomagnetic 2.91◦ N, 152.22◦ E). The study involved analysing Total Electron Content (TEC) data and correcting biases to estimate Slant Total Electron Content (STEC). STEC was then converted to Vertical Total Electron Content (VTEC), useful for space weather, navigation, surveying, and environmental monitoring.

During the course of our study, this Thanjavur station witnessed a Annular Solar eclipse of Dec-26, 2019. The Solar eclipses can impact ionospheric conditions, causing VTEC depletion. This study shows how the near-earth environment changes during …