A Patient-Specific Algorithm For Lung Segmentation In Chest Radiographs,
2022
University of Dayton
A Patient-Specific Algorithm For Lung Segmentation In Chest Radiographs, Manawaduge Supun De Silva, Barath Narayanan Narayanan, Russell C. Hardie
Electrical and Computer Engineering Faculty Publications
Lung segmentation plays an important role in computer-aided detection and diagnosis using chest radiographs (CRs). Currently, the U-Net and DeepLabv3+ convolutional neural network architectures are widely used to perform CR lung segmentation. To boost performance, ensemble methods are often used, whereby probability map outputs from several networks operating on the same input image are averaged. However, not all networks perform adequately for any specific patient image, even if the average network performance is good. To address this, we present a novel multi-network ensemble method that employs a selector network. The selector network evaluates the segmentation outputs from several networks; on …
Compilation Optimizations To Enhance Resilience Of Big Data Programs And Quantum Processors,
2022
Louisiana State University and Agricultural and Mechanical College
Compilation Optimizations To Enhance Resilience Of Big Data Programs And Quantum Processors, Travis D. Lecompte
LSU Doctoral Dissertations
Modern computers can experience a variety of transient errors due to the surrounding environment, known as soft faults. Although the frequency of these faults is low enough to not be noticeable on personal computers, they become a considerable concern during large-scale distributed computations or systems in more vulnerable environments like satellites. These faults occur as a bit flip of some value in a register, operation, or memory during execution. They surface as either program crashes, hangs, or silent data corruption (SDC), each of which can waste time, money, and resources. Hardware methods, such as shielding or error correcting memory (ECM), …
Spam Detection Using Machine Learning And Deep Learning,
2022
Louisiana State University and Agricultural and Mechanical College
Spam Detection Using Machine Learning And Deep Learning, Olubodunde Agboola
LSU Doctoral Dissertations
Text messages are essential these days; however, spam texts have contributed negatively to the success of this communication mode. The compromised authenticity of such messages has given rise to several security breaches. Using spam messages, malicious links have been sent to either harm the system or obtain information detrimental to the user. Spam SMS messages as well as emails have been used as media for attacks such as masquerading and smishing ( a phishing attack through text messaging), and this has threatened both the user and service providers. Therefore, given the waves of attacks, the need to identify and remove …
Ethics In Engineering Education: Is Abet Enough?,
2022
Purdue University
Ethics In Engineering Education: Is Abet Enough?, Alyssa Delouise
The Journal of Purdue Undergraduate Research
No abstract provided.
The Design Of A Point Of Care Fet Biosensor To Detect And Screen Covid-19,
2022
United Arab Emirates University
The Design Of A Point Of Care Fet Biosensor To Detect And Screen Covid-19, Nisreen Amer Mohammad Alnaji
Theses
This work proposes and demonstrates a biosensor with reduced Graphene Oxide (rGO) based Field Effect Transistor (FET) for rapid and selective detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The main objective of this thesis is to detect the SARS-CoV-2 spike protein antigen on spot selectively and rapidly. The rGO channel is coated with the spike protein antibodies to achieve selectivity. Moreover, the biosensing performance and specificity are governed by decorating the sensor’s channel with Metal Nanoparticles (MNPs) such as, copper, and silver. The designed sensor successfully detects the SARS-CoV-2 spike protein and shows singular electrical behavior for detection. …
Wireless Coupled Feed Structure For Additively Manufactured Conformal Antennas,
2022
Embry-Riddle Aeronautical University
Wireless Coupled Feed Structure For Additively Manufactured Conformal Antennas, Blake Roberts
Doctoral Dissertations and Master's Theses
Due to advancements in additive manufacturing, it is possible to create electromagnetic devices that can be conformally printed directly onto 3D surfaces using conductive inks and dielectric pastes. Instance, the traditional antenna radomes that had the purpose of protecting the antenna on its inside can now become the antenna itself. With the components on the surface of the structure, instead of inside if it, a direct feed line would require cutting through dielectric layers and creating a direct electrical connection, also called vertical interconnect access (VIA). Such interconnects are frequent sources of failures, especially in applications that are subject to …
A Roller Coaster For The Mind: Virtual Reality Sickness Modes, Metrics, And Mitigation,
2022
University of Louisville
A Roller Coaster For The Mind: Virtual Reality Sickness Modes, Metrics, And Mitigation, Dalton C. Sparks
The Cardinal Edge
Understanding and preventing virtual reality sickness(VRS), or cybersickness, is vital in removing barriers for the technology's adoption. Thus, this article aims to synthesize a variety of academic sources to demonstrate the modes by which VRS occurs, the metrics by which it is judged, and the methods to mitigate it. The predominant theories on the biological origins of VRS are discussed, as well as the individual factors which increase the likelihood of a user developing VRS. Moreover, subjective and physiological measurements of VRS are discussed in addition to the development of a predictive model and conceptual framework. Finally, several methodologies of …
Development Of The Subwave Rov And Neural-Inertial Positioning System,
2022
Mississippi State University
Development Of The Subwave Rov And Neural-Inertial Positioning System, Jason Farmer
Theses and Dissertations
This report documents the development of the Subwave, a remotely-operated underwater vehicle (ROV), and an artificial neural network based inertial positioning system. The Subwave uses the open-source ArduSub software framework, commercial-off-the-shelf hardware components, and several custom systems. It is designed as a platform for researching autonomous underwater vehicles (AUVs). The first step for an AUV is navigating waypoints, which requires the AUV to know its global position. Since global navigation satellite systems (GNSSs) are denied underwater, the available underwater positioning systems were surveyed and determined that all the available systems were too large and expensive for the Subwave. It was …
Evaluating Serverless Computing,
2022
Louisiana State University and Agricultural and Mechanical College
Evaluating Serverless Computing, Charitra Maharjan
LSU Master's Theses
Function as a Service (FaaS) is gaining admiration because of its way of deploying the computations to serverless backends in the different clouds. It transfers the complexity of provisioning and allocating the necessary resources for an application to the cloud providers. The cloud providers also give an illusion of always availability of resources to the users. Among the cloud providers, AWS serverless platform offers a new paradigm for developing cloud applications without worrying about the underlying hardware infrastructure. It manages not only the resource provisioning and scaling of an application but also provides an opportunity to reimagine the cloud infrastructure …
Towards A Low-Cost Solution For Gait Analysis Using Millimeter Wave Sensor And Machine Learning,
2022
University of Dayton
Towards A Low-Cost Solution For Gait Analysis Using Millimeter Wave Sensor And Machine Learning, Mubarak A. Alanazi, Abdullah K. Alhazmi, Osama Alsattam, Kara Gnau, Meghan Brown, Shannon Thiel, Kurt Jackson, Vamsy P. Chodavarapu
Electrical and Computer Engineering Faculty Publications
Human Activity Recognition (HAR) that includes gait analysis may be useful for various rehabilitation and telemonitoring applications. Current gait analysis methods, such as wearables or cameras, have privacy and operational constraints, especially when used with older adults. Millimeter-Wave (MMW) radar is a promising solution for gait applications because of its low-cost, better privacy, and resilience to ambient light and climate conditions. This paper presents a novel human gait analysis method that combines the micro-Doppler spectrogram and skeletal pose estimation using MMW radar for HAR. In our approach, we used the Texas Instruments IWR6843ISK-ODS MMW radar to obtain the micro-Doppler spectrogram …
Glaciernet2: A Hybrid Multi-Model Learning Architecture For Alpine Glacier Mapping,
2022
University of Dayton
Glaciernet2: A Hybrid Multi-Model Learning Architecture For Alpine Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Michael P. Bishop, Jeffrey S. Kargel, Theus Aspiras
Electrical and Computer Engineering Faculty Publications
In recent decades, climate change has significantly affected glacier dynamics, resulting in mass loss and an increased risk of glacier-related hazards including supraglacial and proglacial lake development, as well as catastrophic outburst flooding. Rapidly changing conditions dictate the need for continuous and detailed ob-servations and analysis of climate-glacier dynamics. Thematic and quantitative information regarding glacier geometry is fundamental for understanding climate forcing and the sensitivity of glaciers to climate change, however, accurately mapping debris-cover glaciers (DCGs) is notoriously difficult based upon the use of spectral information and conventional machine-learning techniques. The objective of this research is to improve upon an …
Exploratory Analysis Of Machine Learning For Images: Methods And Applications,
2022
University of New Mexico - Main Campus
Exploratory Analysis Of Machine Learning For Images: Methods And Applications, Meenu Ajith
Electrical and Computer Engineering ETDs
This research focuses on implementing four different applications of machine learning on images. The various categories of digital images considered for these applications are grayscale, RGB, and infra-red images. The first framework uses an unsupervised learning strategy for detecting fire and smoke from an infra-red image dataset. This problem was solved using a classical machine learning algorithm since the dataset was small and unlabeled. Next, a semi-supervised deep learning model was used for facial expression recognition. Here we detect emotions from a moderately large dataset containing labeled and unlabeled grayscale images. The third application focused on single image superresolution, which …
Femtosecond Laser Surface Processing To Create Self-Organized Micro- And Nano-Scale Features On Composite And Ceramic Materials,
2022
University of Nebraska-Lincoln
Femtosecond Laser Surface Processing To Create Self-Organized Micro- And Nano-Scale Features On Composite And Ceramic Materials, Nate Koeppe
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Femtosecond laser surface processing (FLSP) is applied to a range of materials in this thesis. The materials studied were a carbon fiber reinforced polymer (CFRP), a thermosetting polymer, silicon nitride (Si3N4), and ceramic alumina. The CFRP is a composite material consisting of a thermosetting polymer and carbon fibers. The CFRP are referred to as a composite and the thermosetting polymer is referred to as a resin in this thesis. Alumina can exist in many different forms. The alumina used is 0.5 mm thick nonporous alumina sheets purchased from McMaster-Carr, and will be referred to as alumina …
A Novel Testbed For Evaluation Of Operational Technology Communications Protocols And Their On-Device Implementations,
2022
University of Nebraska-Lincoln
A Novel Testbed For Evaluation Of Operational Technology Communications Protocols And Their On-Device Implementations, Matthew Boeding
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Operational Technology (OT) and Infrastructure Technology (IT) systems are converging with the rapid addition of centralized remote management in OT systems. Previously air-gapped systems are now interconnected through the internet with application-specific protocols. This has led to systems that had limited access points being remotely accessible. In different OT sectors, legacy protocols previously transmitted over serial communication were updated to allow internet communication with legacy devices. New protocols such as IEC-61850 were also introduced for monitoring of different OT resources. The IEC-61850 standard’s Generic Object Oriented Substation Event (GOOSE) protocol outlines the representation and communication of a variety of different …
Combinatorial Cnn Meta-Structures In Deep Learning Applications,
2022
University of New Mexico - Main Campus
Combinatorial Cnn Meta-Structures In Deep Learning Applications, Aswathy Rajendra Kurup
Electrical and Computer Engineering ETDs
The study aims in applying combinatorial structures motivated from the basic CNN in various applications. Convolutional neural networks (CNNs) have grown to be very popular in the field of deep learning. The ability of such networks to learn both Spatial and temporal characteristics in the data have helped in deploying them in various fields. Through this research we explore different kinds of CNN-derived architectures and how these structures can be trained and setup in combinatorial environment to solve problems in deep learning applications. First, we introduce the basic idea of a deep learning meta-structures which is used in the application …
Classifying Toe Walking Gait Patterns Among Children Diagnosed With Idiopathic Toe Walking Using Wearable Sensors And Machine Learning Algorithms,
2022
Chapman University
Classifying Toe Walking Gait Patterns Among Children Diagnosed With Idiopathic Toe Walking Using Wearable Sensors And Machine Learning Algorithms, Rahul Soangra, Yuxin Wen, Hualin Yang, Marybeth Grant-Beuttler
Physical Therapy Faculty Articles and Research
Idiopathic toe walking (ITW) is a gait abnormality in which children’s toes touch at initial contact and demonstrate limited or no heel contact throughout the gait cycle. Toe walking results in poor balance, increased risk of falling, and developmental delays among children. Identifying toe walking steps during walking can facilitate targeted intervention among children diagnosed with ITW. With recent advances in wearable sensing, communication technologies, and machine learning, new avenues of managing toe walking behavior among children are feasible. In this study, we investigate the capabilities of Machine Learning (ML) algorithms in identifying initial foot contact (heel strike versus toe …
One-Bit Algorithm Considerations For Sparse Pmcw Radar,
2022
University of Nebraska-Lincoln
One-Bit Algorithm Considerations For Sparse Pmcw Radar, Ethan Triplett
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Phase Modulated Continuous Wave (PMCW) radar an emerging technology for autonomous cars. It is more flexible than the current frequency modulated systems, offering better detection resolution, interference mitigation, and future development opportunities. The issue preventing PMCW adoption is the need for high sample-rate analog to digital converters (ADCs). Due to device limits, a large increase in cost and power consumption occurs for every added resolution bit for a given sampling rate. This thesis explores radar detection techniques for few-bit and 1-bit ADC measurements. 1-bit quantization typically results in poor amplitude estimation, which can limit detections if the target signals are …
Modeling And Analysis Of A 12kw Solar-Wind Hybrid Renewable Energy System,
2022
University of Nebraska-Lincoln
Modeling And Analysis Of A 12kw Solar-Wind Hybrid Renewable Energy System, Ekaterina Muravleva
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
The increase in rate of depletion of natural resources in the last decade as well as the increased global focus on climate change has made the transition to renewable resources of energy a priority for various countries and organizations across the globe. The sporadic nature of energy generated by photovoltaic systems and wind energy conversion systems has led to an increased utilization of more reliable hybrid renewable energy systems. A combination of both solar and wind energy-based power generations systems reduces the impact of seasonal variation on the amount of power generated and therefore, can be used under varying weather …
A Comparison Of Correlation-Agnostic Techniques For Magnetic Navigation,
2022
Air Force Institute of Technology
A Comparison Of Correlation-Agnostic Techniques For Magnetic Navigation, Clark N. Taylor, Josh Hiatt
Faculty Publications
Navigation using a Global Navigation Satellite System (GNSS) is common for autonomous vehicles (ground or air). Unfortunately, GNSS-based navigation solutions are often susceptible to jamming, interference, and a limited number of satellites. A proposed technique to aid in navigation when a GNSS-based system fails is magnetic navigation - navigation using the Earth's magnetic anomaly field. This solution comes with its own set of problems including the need for quality magnetic maps in every area in which magnetic navigation will be used. Many of the currently available magnetic maps are generated from a combination of dated magnetic surveys, resulting in maps …
Imnets: Deep Learning Using An Incremental Modular Network Synthesis Approach For Medical Imaging Applications,
2022
University of Dayton
Imnets: Deep Learning Using An Incremental Modular Network Synthesis Approach For Medical Imaging Applications, Redha A. Ali, Russell C. Hardie, Barath Narayanan Narayanan, Temesguen Messay
Electrical and Computer Engineering Faculty Publications
Deep learning approaches play a crucial role in computer-aided diagnosis systems to support clinical decision-making. However, developing such automated solutions is challenging due to the limited availability of annotated medical data. In this study, we proposed a novel and computationally efficient deep learning approach to leverage small data for learning generalizable and domain invariant representations in different medical imaging applications such as malaria, diabetic retinopathy, and tuberculosis. We refer to our approach as Incremental Modular Network Synthesis (IMNS), and the resulting CNNs as Incremental Modular Networks (IMNets). Our IMNS approach is to use small network modules that we call SubNets …
