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Articles 1 - 30 of 30
Full-Text Articles in Engineering
Design And Development Of A Comprehensive And Interactive Diabetic Parameter Monitoring System - Betictrack, Nusrat Chowdhury
Design And Development Of A Comprehensive And Interactive Diabetic Parameter Monitoring System - Betictrack, Nusrat Chowdhury
Electronic Theses and Dissertations
A novel, interactive Android app has been developed that monitors the health of type 2 diabetic patients in real-time, providing patients and their physicians with real-time feedback on all relevant parameters of diabetes. The app includes modules for recording carbohydrate intake and blood glucose; for reminding patients about the need to take medications on schedule; and for tracking physical activity, using movement data via Bluetooth from a pair of wearable insole devices. Two machine learning models were developed to detect seven physical activities: sitting, standing, walking, running, stair ascent, stair descent and use of elliptical trainers. The SVM and decision …
Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui
Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui
Electronic Theses and Dissertations
This dissertation describes progress in the state-of-the-art for developing and deploying formally verified cyber security devices in industrial control networks. It begins by detailing the unique struggles that are faced in industrial control networks and why concepts and technologies developed for securing traditional networks might not be appropriate. It uses these unique struggles and examples of contemporary cyber-attacks targeting control systems to argue that progress in securing control systems is best met with formal verification of systems, their specifications, and their security properties. This dissertation then presents a development process and identifies two technologies, TLA+ and seL4, that can be …
Cognitive Satellite Communications And Representation Learning For Streaming And Complex Graphs., Wenqi Liu
Cognitive Satellite Communications And Representation Learning For Streaming And Complex Graphs., Wenqi Liu
Electronic Theses and Dissertations
This dissertation includes two topics. The first topic studies a promising dynamic spectrum access algorithm (DSA) that improves the throughput of satellite communication (SATCOM) under the uncertainty. The other topic investigates distributed representation learning for streaming and complex networks. DSA allows a secondary user to access the spectrum that are not occupied by primary users. However, uncertainty in SATCOM causes more spectrum sensing errors. In this dissertation, the uncertainty has been addressed by formulating a DSA decision-making process as a Partially Observable Markov Decision Process (POMDP) model to optimally determine which channels to sense and access. Large-scale networks have attracted …
An Explainable Recommender System Based On Semantically-Aware Matrix Factorization., Mohammed Sanad Alshammari
An Explainable Recommender System Based On Semantically-Aware Matrix Factorization., Mohammed Sanad Alshammari
Electronic Theses and Dissertations
Collaborative Filtering techniques provide the ability to handle big and sparse data to predict the ratings for unseen items with high accuracy. Matrix factorization is an accurate collaborative filtering method used to predict user preferences. However, it is a black box system that recommends items to users without being able to explain why. This is due to the type of information these systems use to build models. Although rich in information, user ratings do not adequately satisfy the need for explanation in certain domains. White box systems, in contrast, can, by nature, easily generate explanations. However, their predictions are less …
Heterogeneous Reconfigurable Fabrics For In-Circuit Training And Evaluation Of Neuromorphic Architectures, Ramtin Mohammadizand
Heterogeneous Reconfigurable Fabrics For In-Circuit Training And Evaluation Of Neuromorphic Architectures, Ramtin Mohammadizand
Electronic Theses and Dissertations
A heterogeneous device technology reconfigurable logic fabric is proposed which leverages the cooperating advantages of distinct magnetic random access memory (MRAM)-based look-up tables (LUTs) to realize sequential logic circuits, along with conventional SRAM-based LUTs to realize combinational logic paths. The resulting Hybrid Spin/Charge FPGA (HSC-FPGA) using magnetic tunnel junction (MTJ) devices within this topology demonstrates commensurate reductions in area and power consumption over fabrics having LUTs constructed with either individual technology alone. Herein, a hierarchical top-down design approach is used to develop the HSCFPGA starting from the configurable logic block (CLB) and slice structures down to LUT circuits and the …
Value-Of-Information Based Data Collection In Underwater Sensor Networks, Fahad Khan
Value-Of-Information Based Data Collection In Underwater Sensor Networks, Fahad Khan
Electronic Theses and Dissertations
Underwater sensor networks are deployed in marine environments, presenting specific challenges compared to sensor networks deployed in terrestrial settings. Among the major issues that underwater sensor networks face is communication medium limitations that result in low bandwidth and long latency. This creates problems when these networks need to transmit large amounts of data over long distances. A possible solution to address this issue is to use mobile sinks such as autonomous underwater vehicles (AUVs) to offload these large quantities of data. Such mobile sinks are called data mules. Often it is the case that a sensor network is deployed to …
Leveraging The Intrinsic Switching Behaviors Of Spintronic Devices For Digital And Neuromorphic Circuits, Steven Pyle
Leveraging The Intrinsic Switching Behaviors Of Spintronic Devices For Digital And Neuromorphic Circuits, Steven Pyle
Electronic Theses and Dissertations
With semiconductor technology scaling approaching atomic limits, novel approaches utilizing new memory and computation elements are sought in order to realize increased density, enhanced functionality, and new computational paradigms. Spintronic devices offer intriguing avenues to improve digital circuits by leveraging non-volatility to reduce static power dissipation and vertical integration for increased density. Novel hybrid spintronic-CMOS digital circuits are developed herein that illustrate enhanced functionality at reduced static power consumption and area cost. The developed spin-CMOS D Flip-Flop offers improved power-gating strategies by achieving instant store/restore capabilities while using 10 fewer transistors than typical CMOS-only implementations. The spin-CMOS Muller C-Element developed …
Normally-Off Computing Design Methodology Using Spintronics: From Devices To Architectures, Arman Roohi
Normally-Off Computing Design Methodology Using Spintronics: From Devices To Architectures, Arman Roohi
Electronic Theses and Dissertations
Energy-harvesting-powered computing offers intriguing and vast opportunities to dramatically transform the landscape of Internet of Things (IoT) devices and wireless sensor networks by utilizing ambient sources of light, thermal, kinetic, and electromagnetic energy to achieve battery-free computing. In order to operate within the restricted energy capacity and intermittency profile of battery-free operation, it is proposed to innovate Elastic Intermittent Computation (EIC) as a new duty-cycle-variable computing approach leveraging the non-volatility inherent in post-CMOS switching devices. The foundations of EIC will be advanced from the ground up by extending Spin Hall Effect Magnetic Tunnel Junction (SHE-MTJ) device models to realize SHE-MTJ-based …
Segmentation And Classification Of Lung Nodules From Thoracic Ct Scans : Methods Based On Dictionary Learning And Deep Convolutional Neural Networks., Mohammad Mehdi Farhangi
Segmentation And Classification Of Lung Nodules From Thoracic Ct Scans : Methods Based On Dictionary Learning And Deep Convolutional Neural Networks., Mohammad Mehdi Farhangi
Electronic Theses and Dissertations
Lung cancer is a leading cause of cancer death in the world. Key to survival of patients is early diagnosis. Studies have demonstrated that screening high risk patients with Low-dose Computed Tomography (CT) is invaluable for reducing morbidity and mortality. Computer Aided Diagnosis (CADx) systems can assist radiologists and care providers in reading and analyzing lung CT images to segment, classify, and keep track of nodules for signs of cancer. In this thesis, we propose a CADx system for this purpose. To predict lung nodule malignancy, we propose a new deep learning framework that combines Convolutional Neural Networks (CNN) and …
An Explainable Sequence-Based Deep Learning Predictor With Applications To Song Recommendation And Text Classification., Khalil Damak
An Explainable Sequence-Based Deep Learning Predictor With Applications To Song Recommendation And Text Classification., Khalil Damak
Electronic Theses and Dissertations
Streaming applications are now the predominant tools for listening to music. What makes the success of such software is the availability of songs and especially their ability to provide users with relevant personalized recommendations. State of the art music recommender systems mainly rely on either Matrix factorization-based collaborative filtering approaches or deep learning architectures. Deep learning models usually use metadata for content-based filtering or predict the next user interaction (listening to a song) using a memory-based deep learning structure that learns from temporal sequences of user actions. Despite advances in deep learning models for song recommendation systems, none has taken …
Automated Synthesis Of Unconventional Computing Systems, Amad Ul Hassen
Automated Synthesis Of Unconventional Computing Systems, Amad Ul Hassen
Electronic Theses and Dissertations
Despite decades of advancements, modern computing systems which are based on the von Neumann architecture still carry its shortcomings. Moore's law, which had substantially masked the effects of the inherent memory-processor bottleneck of the von Neumann architecture, has slowed down due to transistor dimensions nearing atomic sizes. On the other hand, modern computational requirements, driven by machine learning, pattern recognition, artificial intelligence, data mining, and IoT, are growing at the fastest pace ever. By their inherent nature, these applications are particularly affected by communication-bottlenecks, because processing them requires a large number of simple operations involving data retrieval and storage. The …
Development Of Enhanced Weed Detection System With Adaptive Thresholding, K-Means And Support Vector Machine, Dheeman Saha
Development Of Enhanced Weed Detection System With Adaptive Thresholding, K-Means And Support Vector Machine, Dheeman Saha
Electronic Theses and Dissertations
This paper proposes a sophisticated classification process to segment the leaves of carrots from weeds (mostly Chamomile). In the early stages, of the plants’ development, both weeds and carrot leaves are intermixed with each other and have similar color texture. This makes it difficult to identify without the help of the domain experts. Therefore, it is essential to remove the weed regions so that the carrot plants can grow without any interruptions. The process of identifying the weeds become more challenging when both plant and weed regions overlap (inter-leaves). The proposed system addresses this problem by creating a sophisticated means …
Scalable Map Information Dissemination For Connected And Automated Vehicle Systems, S. M. Osman Gani
Scalable Map Information Dissemination For Connected And Automated Vehicle Systems, S. M. Osman Gani
Electronic Theses and Dissertations
Situational awareness in connected and automated vehicle (CAV) systems becomes particularly challenging in the presence of non-line of sight objects and/or objects beyond the sensing range of local onboard sensors. Despite the fact that fully autonomous driving requires the use of multiple redundant sensor systems, primarily including camera, radar, and LiDAR, the non-line of sight object detection problem still persists due to the inherent limitations of those sensing techniques. To tackle this challenge, the inter-vehicle communication system is envisioned that allows vehicles to exchange self-status updates aiming to extend their effective field of view and thus compensate for the limitations …
Development Of Semantic Scene Conversion Model For Image-Based Localization At Night, Dongyoun Kim
Development Of Semantic Scene Conversion Model For Image-Based Localization At Night, Dongyoun Kim
Electronic Theses and Dissertations
Developing an autonomous vehicle navigation system invariant to illumination change is one of the biggest challenges in vision-based localization field due to the fact that the appearance of an image becomes inconsistent under different light conditions even with the same location. In particular, the night scene images have greatest change in appearance compared to the according day scenes. Moreover, the night images do not have enough information in Image-based localization. To deal with illumination change, image conversion methods have been researched. However, these methods could lose the detail of objects and add fake objects into the output images. In this …
A Policy Mechanism For Federal Recommendation Of Security Standards For Mobile Devices That Conduct Transactions, Ariel Huckabay
A Policy Mechanism For Federal Recommendation Of Security Standards For Mobile Devices That Conduct Transactions, Ariel Huckabay
Electronic Theses and Dissertations
The proliferation of mobile devices in the BRIC countries has prompted them to develop policies to manage the security of these devices. In China, mobile devices are a primary tool for payments. As a result, China instituted in 2017 a cyber security policy that applies to mobile devices giving China broad authority to manage cyber threats. The United States has a similar need for a cyber policy. Mobile devices are likely to become a primary payment tool in the United States soon. DHS has also identified a need for more effective security policy in mobile devices for government operations. This …
Protection Of High-Voltage Transformer Bushings And Other Brittle Structures Against Impact, Christine Nichole Henderson
Protection Of High-Voltage Transformer Bushings And Other Brittle Structures Against Impact, Christine Nichole Henderson
Electronic Theses and Dissertations
This dissertation contributes unique approaches to improve the fundamental understanding of the impact behavior of porcelain high-voltage (HV) transformer bushings under high-velocity impact, with a focus on their protection with feasible methods which could be quickly applied in service to prevent vandalism and other undesirable impact situations. The bushings are brittle and pressurized; prone to explosive damage when hit by a high-velocity projectile. Damaged bushings can destroy transformers and entire substations in complex fashions. This can put the power grid at risk for cascading failures and electrical blackouts, affecting consumers. Therefore, suggesting practical approaches which could be used to protect …
Optimal Design And Planning Of Hybrid Ac/Dc Microgrid, Hossein Lotfi
Optimal Design And Planning Of Hybrid Ac/Dc Microgrid, Hossein Lotfi
Electronic Theses and Dissertations
The traditional approach for microgrid design and deployment has been mainly focused on AC systems. DC microgrids, however, are gaining attention due to numerous advantages they provide over AC microgrids, such as removing the need for synchronization and frequency adjustment as well as appropriateness in supporting DC loads and distributed energy resources (DERs). Moreover, considering that both AC and DC DERs are utilized in microgrids, hybrid microgrids would provide viable and economic solutions as they can potentially eliminate the need for AC-to-DC or DC-to-AC voltage conversions. This dissertation focuses on a hybrid microgrid planning model with the objective of minimizing …
Application Of Microgrids In Supporting The Utility Grid, Alireza Majzoobi
Application Of Microgrids In Supporting The Utility Grid, Alireza Majzoobi
Electronic Theses and Dissertations
Distributed renewable energy resources have attracted significant attention in recent years due to the falling cost of the renewable energy technology, extensive federal and state incentives, and the application in improving load-point reliability. This growing proliferation, however, is changing the traditional consumption load curves by adding considerable levels of variability and further challenging the electricity supply-demand balance. In this dissertation, the application of microgrids in effectively capturing the distribution network net load variability, caused primarily by the prosumers, is investigated. Microgrids provide a viable and localized solution to this challenge while removing the need for costly investments by the electric …
3d Formation Control In Multi-Robot Teams Using Artificial Potential Fields, Sanjana Reddy Mohan
3d Formation Control In Multi-Robot Teams Using Artificial Potential Fields, Sanjana Reddy Mohan
Electronic Theses and Dissertations
Multi-robot teams find applications in emergency response, search and rescue operations, convoy support and many more. Teams of autonomous aerial vehicles can also be used to protect a cargo of airplanes by surrounding them in some geometric shape. This research develops a control algorithm to attract UAVs to one or a set of bounded geometric shapes while avoiding collisions, re-configuring in the event of departure or addition of UAVs and maneuvering in mission space while retaining the configuration. Using potential field theory, weighted vector fields are described to attract UAVs to a desired formation. In order to achieve this, three …
Improvements Of And Extensions To Fsmweb: Testing Mobile Apps, Ahmed Fawzi Al Haddad
Improvements Of And Extensions To Fsmweb: Testing Mobile Apps, Ahmed Fawzi Al Haddad
Electronic Theses and Dissertations
A mobile application is a software program that runs on mobile device. In 2017, 178.1 billion mobile apps downloaded and the number is expected to grow to 258.2 billion app downloads in 2022 [19]. The number of app downloads poses a challenge for mobile application testers to find the right approach to test apps. This dissertation extends the FSMWeb approach for testing web applications [50] to test mobile applications (FSMApp). During the process of analyzing FSMWeb how it could be extended to test Mobile Apps, a number of shortcomings were detected which we improved upon. We discuss these first. We …
Soft-Error Resilience Framework For Reliable And Energy-Efficient Cmos Logic And Spintronic Memory Architectures, Faris Alghareb
Soft-Error Resilience Framework For Reliable And Energy-Efficient Cmos Logic And Spintronic Memory Architectures, Faris Alghareb
Electronic Theses and Dissertations
The revolution in chip manufacturing processes spanning five decades has proliferated high performance and energy-efficient nano-electronic devices across all aspects of daily life. In recent years, CMOS technology scaling has realized billions of transistors within large-scale VLSI chips to elevate performance. However, these advancements have also continually augmented the impact of Single-Event Transient (SET) and Single-Event Upset (SEU) occurrences which precipitate a range of Soft-Error (SE) dependability issues. Consequently, soft-error mitigation techniques have become essential to improve systems' reliability. Herein, first, we proposed optimized soft-error resilience designs to improve robustness of sub-micron computing systems. The proposed approaches were developed to …
Simulation, Analysis, And Optimization Of Heterogeneous Cpu-Gpu Systems, Christopher Giles
Simulation, Analysis, And Optimization Of Heterogeneous Cpu-Gpu Systems, Christopher Giles
Electronic Theses and Dissertations
With the computing industry's recent adoption of the Heterogeneous System Architecture (HSA) standard, we have seen a rapid change in heterogeneous CPU-GPU processor designs. State-of-the-art heterogeneous CPU-GPU processors tightly integrate multicore CPUs and multi-compute unit GPUs together on a single die. This brings the MIMD processing capabilities of the CPU and the SIMD processing capabilities of the GPU together into a single cohesive package with new HSA features comprising better programmability, coherency between the CPU and GPU, shared Last Level Cache (LLC), and shared virtual memory address spaces. These advancements can potentially bring marked gains in heterogeneous processor performance and …
Guided Autonomy For Quadcopter Photography, Saif Alabachi
Guided Autonomy For Quadcopter Photography, Saif Alabachi
Electronic Theses and Dissertations
Photographing small objects with a quadcopter is non-trivial to perform with many common user interfaces, especially when it requires maneuvering an Unmanned Aerial Vehicle (C) to difficult angles in order to shoot high perspectives. The aim of this research is to employ machine learning to support better user interfaces for quadcopter photography. Human Robot Interaction (HRI) is supported by visual servoing, a specialized vision system for real-time object detection, and control policies acquired through reinforcement learning (RL). Two investigations of guided autonomy were conducted. In the first, the user directed the quadcopter with a sketch based interface, and periods of …
Rethinking Routing And Peering In The Era Of Vertical Integration Of Network Functions, Prasun Kanti Dey
Rethinking Routing And Peering In The Era Of Vertical Integration Of Network Functions, Prasun Kanti Dey
Electronic Theses and Dissertations
Content providers typically control the digital content consumption services and are getting the most revenue by implementing an "all-you-can-eat" model via subscription or hyper-targeted advertisements. Revamping the existing Internet architecture and design, a vertical integration where a content provider and access ISP will act as unibody in a sugarcane form seems to be the recent trend. As this vertical integration trend is emerging in the ISP market, it is questionable if existing routing architecture will suffice in terms of sustainable economics, peering, and scalability. It is expected that the current routing will need careful modifications and smart innovations to ensure …
Improvement Of Data-Intensive Applications Running On Cloud Computing Clusters, Ibrahim Adel Ibrahim
Improvement Of Data-Intensive Applications Running On Cloud Computing Clusters, Ibrahim Adel Ibrahim
Electronic Theses and Dissertations
MapReduce, designed by Google, is widely used as the most popular distributed programming model in cloud environments. Hadoop, an open-source implementation of MapReduce, is a data management framework on large cluster of commodity machines to handle data-intensive applications. Many famous enterprises including Facebook, Twitter, and Adobe have been using Hadoop for their data-intensive processing needs. Task stragglers in MapReduce jobs dramatically impede job execution on massive datasets in cloud computing systems. This impedance is due to the uneven distribution of input data and computation load among cluster nodes, heterogeneous data nodes, data skew in reduce phase, resource contention situations, and …
Context-Centric Affect Recognition From Paralinguistic Features Of Speech, Andreas Marpaung
Context-Centric Affect Recognition From Paralinguistic Features Of Speech, Andreas Marpaung
Electronic Theses and Dissertations
As the field of affect recognition has progressed, many researchers have shifted from having unimodal approaches to multimodal ones. In particular, the trends in paralinguistic speech affect recognition domain have been to integrate other modalities such as facial expression, body posture, gait, and linguistic speech. Our work focuses on integrating contextual knowledge into paralinguistic speech affect recognition. We hypothesize that a framework to recognize affect through paralinguistic features of speech can improve its performance by integrating relevant contextual knowledge. This dissertation describes our research to integrate contextual knowledge into the paralinguistic affect recognition process from acoustic features of speech. We …
Instance Segmentation And Object Detection In Road Scenes Using Inverse Perspective Mapping Of 3d Point Clouds And 2d Images, Chungyup Lee
Instance Segmentation And Object Detection In Road Scenes Using Inverse Perspective Mapping Of 3d Point Clouds And 2d Images, Chungyup Lee
Electronic Theses and Dissertations
The instance segmentation and object detection are important tasks in smart car applications. Recently, a variety of neural network-based approaches have been proposed. One of the challenges is that there are various scales of objects in a scene, and it requires the neural network to have a large receptive field to deal with the scale variations. In other words, the neural network must have deep architectures which slow down computation. In smart car applications, the accuracy of detection and segmentation of vehicle and pedestrian is hugely critical. Besides, 2D images do not have distance information but enough visual appearance. On …
Eaglebot: A Chatbot Based Multi-Tier Question Answering System For Retrieving Answers From Heterogeneous Sources Using Bert, Muhammad Rana
Eaglebot: A Chatbot Based Multi-Tier Question Answering System For Retrieving Answers From Heterogeneous Sources Using Bert, Muhammad Rana
Electronic Theses and Dissertations
This paper proposes to tackle Question Answering on a specific domain by developing a multi-tier system using three different types of data storage for storing answers. For testing our system on University domain we have used extracted data from Georgia Southern University website. For the task of faster retrieval we have divided our answer data sources into three distinct types and utilized Dialogflow's Natural Language Understanding engine for route selection. We compared different word and sentence embedding techniques for making a semantic question search engine and BERT sentence embedding gave us the best result and for extracting answer from a …
Building A Classification Model Using Affinity Propagation, Christopher R. Klecker
Building A Classification Model Using Affinity Propagation, Christopher R. Klecker
Electronic Theses and Dissertations
Regular classification of data includes a training set and test set. For example for Naïve Bayes, Artificial Neural Networks, and Support Vector Machines, each classifier employs the whole training set to train itself. This thesis will explore the possibility of using a condensed form of the training set in order to get a comparable classification accuracy. The technique explored in this thesis will use a clustering algorithm to explore with data records can be labeled as exemplar, or a quality of multiple records. For example, is it possible to compress say 50 records into one single record? Can a single …
Hydrogen Fuel Cell Gasket Handling And Sorting With Machine Vision Integrated Dual Arm Robot, Devin C. Fowler
Hydrogen Fuel Cell Gasket Handling And Sorting With Machine Vision Integrated Dual Arm Robot, Devin C. Fowler
Electronic Theses and Dissertations
Recently demonstrated robotic assembling technologies for fuel cell stacks used fuel cell components manually pre-arranged in stacks (presenters), all oriented in the same position. Identifying the original orientation of fuel cell components and loading them in stacks for a subsequent automated assembly process is a difficult, repetitive work cycle which if done manually, deceives the advantages offered by automated fabrication technologies of fuel cell components and by robotic assembly processes. We present an innovative robotic technology which enables the integration of automated fabrication processes of fuel cell components with robotic assembly of fuel cell stacks into a fully automated fuel …