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Full-Text Articles in Engineering

Black Beyond Measure: An Antideficit Exploration Of Cultural Capital Within A National Society Of Black Engineers (Nsbe) Chapter At A Predominantly White Institution (Pwi), Rhonda Harley May 2022

Black Beyond Measure: An Antideficit Exploration Of Cultural Capital Within A National Society Of Black Engineers (Nsbe) Chapter At A Predominantly White Institution (Pwi), Rhonda Harley

Dissertations

Historically, Black students have been excluded from Predominately White institutions (PWI) longer than welcomed to attend and matriculate (Harper et al., 2009). Due to this lack of inclusion, African American students' educational experiences often center on academic disparities, inequality of opportunity, and under-preparedness in career planning within the American education system. While there has been a fair amount of research on the lack of representation of Black students in the engineering disciplines, the heavy focus on quantitative data offers little insight into the unique ways students succeed and overcome institutional and systemic barriers in pursuit of their degree. Undergraduate experiences ...


An Analysis On Network Flow-Based Iot Botnet Detection Using Weka, Cian Porteous Jan 2022

An Analysis On Network Flow-Based Iot Botnet Detection Using Weka, Cian Porteous

Dissertations

Botnets pose a significant and growing risk to modern networks. Detection of botnets remains an important area of open research in order to prevent the proliferation of botnets and to mitigate the damage that can be caused by botnets that have already been established. Botnet detection can be broadly categorised into two main categories: signature-based detection and anomaly-based detection. This paper sets out to measure the accuracy, false-positive rate, and false-negative rate of four algorithms that are available in Weka for anomaly-based detection of a dataset of HTTP and IRC botnet data. The algorithms that were selected to detect botnets ...


Dark Patterns: Effect On Overall User Experience And Site Revisitation, Deon Soul Calawen Jan 2022

Dark Patterns: Effect On Overall User Experience And Site Revisitation, Deon Soul Calawen

Dissertations

Dark patterns are user interfaces purposefully designed to manipulate users into doing something they might not otherwise do for the benefit of an online service. This study investigates the impact of dark patterns on overall user experience and site revisitation in the context of airline websites. In order to assess potential dark pattern effects, two versions of the same airline website were compared: a dark version containing dark pattern elements and a bright version free of manipulative interfaces. User experience for both websites were assessed quantitatively through a survey containing a User Experience Questionnaire (UEQ) and a System Usability Scale ...


Measuring And Comparing Social Bias In Static And Contextual Word Embeddings, Alan Cueva Mora Jan 2022

Measuring And Comparing Social Bias In Static And Contextual Word Embeddings, Alan Cueva Mora

Dissertations

Word embeddings have been considered one of the biggest breakthroughs of deep learning for natural language processing. They are learned numerical vector representations of words where similar words have similar representations. Contextual word embeddings are the promising second-generation of word embeddings assigning a representation to a word based on its context. This can result in different representations for the same word depending on the context (e.g. river bank and commercial bank). There is evidence of social bias (human-like implicit biases based on gender, race, and other social constructs) in word embeddings. While detecting bias in static (classical or non-contextual ...


Evaluating The Performance Of Vision Transformer Architecture For Deepfake Image Classification, Devesan Govindasamy Jan 2022

Evaluating The Performance Of Vision Transformer Architecture For Deepfake Image Classification, Devesan Govindasamy

Dissertations

Deepfake classification has seen some impressive results lately, with the experimentation of various deep learning methodologies, researchers were able to design some state-of-the art techniques. This study attempts to use an existing technology “Transformers” in the field of Natural Language Processing (NLP) which has been a de-facto standard in text processing for the purposes of Computer Vision. Transformers use a mechanism called “self-attention”, which is different from CNN and LSTM. This study uses a novel technique that considers images as 16x16 words (Dosovitskiy et al., 2021) to train a deep neural network with “self-attention” blocks to detect deepfakes. It creates ...


Machine Learning Techniques For Network Analysis, Irfan Lateef Dec 2021

Machine Learning Techniques For Network Analysis, Irfan Lateef

Dissertations

The network's size and the traffic on it are both increasing exponentially, making it difficult to look at its behavior holistically and address challenges by looking at link level behavior. It is possible that there are casual relationships between links of a network that are not directly connected and which may not be obvious to observe. The goal of this dissertation is to study and characterize the behavior of the entire network by using eigensubspace based techniques and apply them to network traffic engineering applications.

A new method that uses the joint time-frequency interpretation of eigensubspace representation for network ...


Statistics-Based Anomaly Detection And Correction Method For Amazon Customer Reviews, Ishani Chatterjee Dec 2021

Statistics-Based Anomaly Detection And Correction Method For Amazon Customer Reviews, Ishani Chatterjee

Dissertations

People nowadays use the Internet to project their assessments, impressions, ideas, and observations about various subjects or products on numerous social networking sites. These sites serve as a great source of gathering information for data analytics, sentiment analysis, natural language processing, etc. The most critical challenge is interpreting this data and capturing the sentiment behind these expressions. Sentiment analysis is analyzing, processing, concluding, and inferencing subjective texts with the views. Companies use sentiment analysis to understand public opinions, perform market research, analyze brand reputation, recognize customer experiences, and study social media influence. According to the different needs for aspect granularity ...


Hydrophobically Modified Isosorbide Dimethacrylates As Biomaterials For Bisphenol A Free Dental Fillings, Bilal Marie Dec 2021

Hydrophobically Modified Isosorbide Dimethacrylates As Biomaterials For Bisphenol A Free Dental Fillings, Bilal Marie

Dissertations

Amalgam and Bisphenol A glycerolate dimethacrylate (BisGMA) are the main dental filling materials in use today. Because of the negative perception of amalgam and its lower esthetic appeal, as well as the desire to replace the endocrine disruptor Bisphenol A, which is the building block of BisGMA, there has been a critical need to search for safer alternatives to these dental filling materials.

Isosorbide is a sugar-based molecule generally recognized as safe. It has been extensively studied as a replacement to the Bisphenol A core in various materials. However, isosorbide is extremely hygroscopic, and water uptake in dental fillings causes ...


Coherent Control Of Dispersive Waves, Jimmie Adriazola Dec 2021

Coherent Control Of Dispersive Waves, Jimmie Adriazola

Dissertations

This dissertation addresses some of the various issues which can arise when posing and solving optimization problems constrained by dispersive physics. Considered here are four technologically relevant experiments, each having their own unique challenges and physical settings including ultra-cold quantum fluids trapped by an external field, paraxial light propagation through a gradient index of refraction, light propagation in periodic photonic crystals, and surface gravity water waves over shallow and variable seabeds. In each of these settings, the physics can be modeled by dispersive wave equations, and the technological objective is to design the external trapping fields or propagation media such ...


A Vacuum-Driven Distillation Technology Of Aqueous Solutions And Mixtures, Guo Guangyu Dec 2021

A Vacuum-Driven Distillation Technology Of Aqueous Solutions And Mixtures, Guo Guangyu

Dissertations

Distillation of aqueous solutions and aqueous mixtures has vast industrial applications, including desalination, wastewater treatment, and fruit juice concentration. Currently, two major distillation technologies are adopted in the industry, membrane separation and thermal distillation. However, both of them face certain inevitable drawbacks. Membrane separation has disadvantages as relying on high-grade energy, requiring membrane, fouling problem, narrow treatment range, limited scalability, and vibrating and noisy operating conditions. Traditional thermal distillation technologies can avoid above concerns but has other shortcomings, such as relatively low energy efficiency and yield rate, complicated and bulky system structure, and scaling problem.

This project proposes an innovative ...


Experimental And Computational Studies Of Functionalized Carbon Nanotubes For Use In Energy Storage Devices And Membranes, Emine S. Karaman Dec 2021

Experimental And Computational Studies Of Functionalized Carbon Nanotubes For Use In Energy Storage Devices And Membranes, Emine S. Karaman

Dissertations

Electrolytes with good interfacial stability are a crucial component of any electrochemical device. The development of novel gel polymer electrolytes (GEs) with good interface stability and better manufacturability is important for the development of the next generation electrochemical devices. Gel electrolytes are hybrid electrolyte materials, combining benefits of both liquid and solid systems. Compared with liquid and solid electrolytes, GEs open new design opportunities and do not require rigorous encapsulation methods. In this dissertation, studies on functionalized carbon nanotubes (fCNTs) and graphene oxide (GO) doped polyvinyl alcohol (PVA) based gel electrolytes (GEs) are reported. The ionic conductivity and mechanical strength ...


Electro-Chemo-Mechanics Of The Interfaces In 2d-3d Heterostructure Electrodes, Vidushi Sharma Dec 2021

Electro-Chemo-Mechanics Of The Interfaces In 2d-3d Heterostructure Electrodes, Vidushi Sharma

Dissertations

Unique heterostructure electrodes comprising two-dimensional (2D) materials and bulk three dimensional (3D) high-performance active electrodes are recently synthesized and experimentally tested for their electrochemical performance in metal-ion batteries. Such electrodes exhibit long cycle life while they also retain high-capacity inherent to the active electrode. The role of 2D material is to provide a supportive mesh that allows buffer space for volume expansions upon ion intercalation in the active material and establishes a continuous electronic contact. Therefore, the binding strength between both materials is crucial for the success of such electrodes. Furthermore, battery cycles may bring about phase transformations in the ...


Crash Injury Severity Prediction With Artificial Neural Networks, Rima Abisaad Dec 2021

Crash Injury Severity Prediction With Artificial Neural Networks, Rima Abisaad

Dissertations

Motor vehicle crashes are one of our nation's most serious social, economic and health issues. They are the leading cause of death among children and young adults, killing approximately 1.35 million people each year. Providing a safe and efficient transportation system is the primary goal of transportation engineering and planning. To help reduce traffic fatalities and injuries on roadways, crash prediction models are used to forecast the injury severity of potential crashes and apply precautionary countermeasures accordingly. Most of these models are reactive as they use historical crash data to categorize crash-related factors. Recently, advancements have been made ...


A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko Dec 2021

A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko

Dissertations

To repair an incorrect program does not mean to make it correct; it only means to make it more-correct, in some sense, than it is. In the absence of a concept of relative correctness, i.e. the property of a program to be more-correct than another with respect to a specification, the discipline of program repair has resorted to various approximations of absolute (traditional) correctness, with varying degrees of success. This shortcoming is concealed by the fact that most program repair tools are tested on basic cases, whence making them absolutely correct is not clearly distinguishable from making them relatively ...


On Resource-Efficiency And Performance Optimization In Big Data Computing And Networking Using Machine Learning, Wuji Liu Dec 2021

On Resource-Efficiency And Performance Optimization In Big Data Computing And Networking Using Machine Learning, Wuji Liu

Dissertations

Due to the rapid transition from traditional experiment-based approaches to large-scale, computational intensive simulations, next-generation scientific applications typically involve complex numerical modeling and extreme-scale simulations. Such model-based simulations oftentimes generate colossal amounts of data, which must be transferred over high-performance network (HPN) infrastructures to remote sites and analyzed against experimental or observation data on high-performance computing (HPC) facility. Optimizing the performance of both data transfer in HPN and simulation-based model development on HPC is critical to enabling and accelerating knowledge discovery and scientific innovation. However, such processes generally involve an enormous set of attributes including domain-specific model parameters, network transport ...


Iii-Nitride Nanostructures: Photonics And Memory Device Applications, Barsha Jain Dec 2021

Iii-Nitride Nanostructures: Photonics And Memory Device Applications, Barsha Jain

Dissertations

III-nitride materials are extensively studied for various applications. Particularly, III-nitride-based light-emitting diodes (LEDs) have become the major component of the current solid-state lighting (SSL) technology. Current III-nitride-based phosphor-free white color LEDs (White LEDs) require an electron blocking layer (EBL) between the device active region and p-GaN to control the electron overflow from the active region, which has been identified as one of the primary reasons to adversely affect the hole injection process. In this dissertation, the effect of electronically coupled quantum well (QW) is investigated to reduce electron overflow in the InGaN/GaN dot-in-a-wire phosphor-free white LEDs and to improve ...


The Integration Of Art: A Multiple Case Study Of Science, Technology, Engineering, Art, And Math (Steam) Schools In Three Schools In Southern California, Reyna Esther Smith Dec 2021

The Integration Of Art: A Multiple Case Study Of Science, Technology, Engineering, Art, And Math (Steam) Schools In Three Schools In Southern California, Reyna Esther Smith

Dissertations

Purpose: The purpose of this qualitative multi-case study was to describe and analyze how schools that implement a STEAM program include the arts in their integrated program. The study focused on 3 K-12 schools in Southern California that are located in the Antelope Valley high desert region of the state. This multi-case study analyzed an elementary school, a middle school, and a high school that are in different districts in the area.

Methodology: This multi-case study used qualitative data to analyze the research questions regarding art infusion in STEAM programs and teacher and leader perspectives. Drawing from interviews of teachers ...


Optimizing Vaccine Supply Chains With Drones In Less-Developed Regions: Multimodal Vaccine Distribution In Vanuatu, Deng Pan Nov 2021

Optimizing Vaccine Supply Chains With Drones In Less-Developed Regions: Multimodal Vaccine Distribution In Vanuatu, Deng Pan

Dissertations

In recent years, many less-developed countries (LDCs) have been exploring new opportunities provided by drones, such as the capability to deliver items with minimal infrastructure, fast speed, and relatively low cost, especially for high value-added products such as lifesaving medical products and vaccines. This dissertation optimizes the delivery network and operations for routine childhood vaccines in LDCs. It analyzes two important problems using mathematical programming, with an application in the South Pacific nation of Vanuatu. The first problem is to optimize the nation-wide multi-modal vaccine supply chain with drones to deliver vaccines from the national depot to all health zones ...


Development Of Sensor, Sensory System And Signal Processing Algorithm For Intelligent Sensing Applications, Xingzhe Zhang Nov 2021

Development Of Sensor, Sensory System And Signal Processing Algorithm For Intelligent Sensing Applications, Xingzhe Zhang

Dissertations

Sensors have been receiving significant attention in the last decade and the demand for sensory systems has increased in recent years due to the rapid growth in the field of artificial intelligence (AI). Sensors can improve people’s awareness by providing them with real-time information on the environment and their immediate health conditions. This dissertation presents the fulfilment of three main projects and focuses on the development of a sensor, a sensory system, and a sensor signal recognition system for AI applications by employing printed electronics, analog circuit design, and digital signal processing techniques.

In the first project, a multi-channel ...


Impact Of Exposure On Thin Epoxy Overlay Performance, Abul Fazal Mazumder Nov 2021

Impact Of Exposure On Thin Epoxy Overlay Performance, Abul Fazal Mazumder

Dissertations

Thin epoxy overlays are used for improving the condition and extending the service life of bridge decks. The tensile bond pull-off strength, evaluated as per the ASTM C1583, is used as the performance indicator. A failure in the substrate with a tensile strength of 250 psi or greater is considered acceptable. However, the performance evaluated on in-service bridge decks shows inconsistent results. Laboratory studies by several researchers documented a distinct performance difference when the overlays are exposed to room temperatures in comparison to elevated temperatures. However, the most influential parameters such as concrete surface profile, thermal compatibility between overlay and ...


Infrastructure Risk Reduction: The Case Of Drinking Water Emergencies, Mark Paine Oct 2021

Infrastructure Risk Reduction: The Case Of Drinking Water Emergencies, Mark Paine

Dissertations

Public water systems are an integral part of community infrastructure. Drinking water contamination or service disruptions have the potential to cause economic losses, limit fire suppression capability, and result in human illnesses. Until 2016, the United States federal government had not issued a disaster declaration due to contaminated water. The first federal drinking water disaster declaration due to contaminated water serves as a sentinel event demonstrating the need to increase focus on public water systems during all phases of emergency management: mitigation, preparation, response, and recovery. Previous studies evaluating risks to vulnerable populations associated with drinking water primarily utilized qualitative ...


Modeling And Design Optimization For Membrane Filters, Yixuan Sun Aug 2021

Modeling And Design Optimization For Membrane Filters, Yixuan Sun

Dissertations

Membrane filtration is widely used in many applications, ranging from industrial processes to everyday living activities. With growing interest from both industrial and academic sectors in understanding the various types of filtration processes in use, and in improving filter performance, the past few decades have seen significant research activity in this area. Experimental studies can be very valuable, but are expensive and time-consuming, therefore theoretical studies offer potential as a cost-effective and predictive way to improve on current filter designs. In this work, mathematical models, derived from first principles and simplified using asymptotic analysis, are proposed for: (1) pleated membrane ...


Data-Driven Learning For Robot Physical Intelligence, Leidi Zhao Aug 2021

Data-Driven Learning For Robot Physical Intelligence, Leidi Zhao

Dissertations

The physical intelligence, which emphasizes physical capabilities such as dexterous manipulation and dynamic mobility, is essential for robots to physically coexist with humans. Much research on robot physical intelligence has achieved success on hyper robot motor capabilities, but mostly through heavily case-specific engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous manner, robot learning from human demonstration (LfD) has achieved great progress, but still has limitations handling dynamic skills and compound actions. In this dissertation, a composite learning scheme which goes beyond LfD and integrates robot learning from human definition, demonstration, and evaluation is proposed. This method tackles ...


Shale Softening Based On Pore Network And Laboratory Investigations, Di Zhang Aug 2021

Shale Softening Based On Pore Network And Laboratory Investigations, Di Zhang

Dissertations

This dissertation consists of two major parts: Firstly, experimental investigation of four major shale softening mechanisms and quantifications of structural parameters. Secondly, numerical simulations of nano-scale flow behaviors using the previous experiments determined parameters based on modified pore network modeling.

Hydraulic fracturing is widely applied to economical gas production from shale reservoirs. Still, the gradual swelling of the clay micro/nano-pores due to retained fluid from hydraulic fracturing causes a gradual reduction of gas production. Four different gas-bearing shale samples are investigated to quantify the expected shale swelling due to hydraulic fracturing. These shale samples are subject to heated deionized ...


Short-Term Crash Risk Prediction Considering Proactive, Reactive, And Driver Behavior Factors, Sina Darban Khales Aug 2021

Short-Term Crash Risk Prediction Considering Proactive, Reactive, And Driver Behavior Factors, Sina Darban Khales

Dissertations

Providing a safe and efficient transportation system is the primary goal of transportation engineering and planning. Highway crashes are among the most significant challenges to achieving this goal. They result in significant societal toll reflected in numerous fatalities, personal injuries, property damage, and traffic congestion. To that end, much attention has been given to predictive models of crash occurrence and severity. Most of these models are reactive: they use the data about crashes that have occurred in the past to identify the significant crash factors, crash hot-spots and crash-prone roadway locations, analyze and select the most effective countermeasures for reducing ...


Colloidal Quantum Dot (Cqd) Based Mid-Wavelength Infrared Optoelectronics, Shihab Bin Hafiz Aug 2021

Colloidal Quantum Dot (Cqd) Based Mid-Wavelength Infrared Optoelectronics, Shihab Bin Hafiz

Dissertations

Colloidal quantum dot (CQD) photodetectors are a rapidly emerging technology with a potential to significantly impact today’s infrared sensing and imaging technologies. To date, CQD photodetector research is primarily focused on lead-chalcogenide semiconductor CQDs which have spectral response fundamentally limited by the bulk bandgap of the constituent material, confining their applications to near-infrared (NIR, 0.7-1.0 um) and short-wavelength infrared (SWIR, 1-2.5 um) spectral regions. The overall goal of this dissertation is to investigate a new generation of CQD materials and devices that advances the current CQD photodetector research toward the technologically important thermal infrared region of ...


Feedstock Powders For Reactive Structural Materials, Daniel Hastings Aug 2021

Feedstock Powders For Reactive Structural Materials, Daniel Hastings

Dissertations

Metals as fuels have higher energy density per unit mass or volume compared to any hydrocarbon. At the same time, metals are common structural materials. Exploring metals as reactive structural materials may combine their high energy density with attractive mechanical properties. Preparing such materials, however, is challenging. Requirements that need to be met for applications include density, strength, and stability enabling the component to sustain the structure during its desired operation; added requirements are the amount and rate of the energy release upon impact or shock. Powder technology and additive manufacturing are approaches considered for design of reactive structural materials ...


Multi-Stage Stochastic Optimization And Reinforcement Learning For Forestry Epidemic And Covid-19 Control Planning, Sabah Bushaj Aug 2021

Multi-Stage Stochastic Optimization And Reinforcement Learning For Forestry Epidemic And Covid-19 Control Planning, Sabah Bushaj

Dissertations

This dissertation focuses on developing new modeling and solution approaches based on multi-stage stochastic programming and reinforcement learning for tackling biological invasions in forests and human populations. Emerald Ash Borer (EAB) is the nemesis of ash trees. This research introduces a multi-stage stochastic mixed-integer programming model to assist forest agencies in managing emerald ash borer insects throughout the U.S. and maximize the public benets of preserving healthy ash trees. This work is then extended to present the first risk-averse multi-stage stochastic mixed-integer program in the invasive species management literature to account for extreme events. Significant computational achievements are obtained ...


Gradient Free Sign Activation Zero One Loss Neural Networks For Adversarially Robust Classification, Yunzhe Xue Aug 2021

Gradient Free Sign Activation Zero One Loss Neural Networks For Adversarially Robust Classification, Yunzhe Xue

Dissertations

The zero-one loss function is less sensitive to outliers than convex surrogate losses such as hinge and cross-entropy. However, as a non-convex function, it has a large number of local minima, andits undifferentiable attribute makes it impossible to use backpropagation, a method widely used in training current state-of-the-art neural networks. When zero-one loss is applied to deep neural networks, the entire training process becomes challenging. On the other hand, a massive non-unique solution probably also brings different decision boundaries when optimizing zero-one loss, making it possible to fight against transferable adversarial examples, which is a common weakness in deep learning ...


Stochastic Programming And Agent-Based Simulation Approaches For Epidemics Control And Logistics Planning, Xuecheng Yin Aug 2021

Stochastic Programming And Agent-Based Simulation Approaches For Epidemics Control And Logistics Planning, Xuecheng Yin

Dissertations

This dissertation addresses the resource allocation challenges of fighting against infectious disease outbreaks. The goal of this dissertation is to formulate multi-stage stochastic programming and agent-based models to address the limitations of former literature in optimizing resource allocation for preventing and controlling epidemics and pandemics. In the first study, a multi-stage stochastic programming compartmental model is presented to integrate the uncertain disease progression and the logistics of resource allocation to control a highly contagious infectious disease. The proposed multi-stage stochastic program, which involves various disease growth scenarios, optimizes the distribution of treatment centers and resources while minimizing the total expected ...