Engineering Commons^™

Nonlinear Observers For Burning Zone Temperatures And Torque Estimation Of The Rotary Cement Kiln., Bhagyashri Aditya Bhagwat

Electronic Theses and Dissertations

Due to consistent expansion in the infrastructure and housing sectors worldwide have given a new way for the rapid growth of global cement market. Increased global demand for the cement production makes the attractive research topic which can lead to the quality and overall efficiency of the product. Measurement of the temperature in the burning zone is vital to maintain product quality and kiln efficiency in the cement industry. Often the BZT is un-measurable due to internal kiln conditions, dusty environment, extreme heat, harshness for example and this leads to kiln not being driven as efficient as possible. Multi-physics tools …

Design, Evaluation, And Control Of Nexus: A Multiscale Additive Manufacturing Platform With Integrated 3d Printing And Robotic Assembly., Danming Wei

Electronic Theses and Dissertations

Additive manufacturing (AM) technology is an emerging approach to creating three-dimensional (3D) objects and has seen numerous applications in medical implants, transportation, aerospace, energy, consumer products, etc. Compared with manufacturing by forming and machining, additive manufacturing techniques provide more rapid, economical, efficient, reliable, and complex manufacturing processes. However, additive manufacturing also has limitations on print strength and dimensional tolerance, while traditional additive manufacturing hardware platforms for 3D printing have limited flexibility. In particular, part geometry and materials are limited to most 3D printing hardware. In addition, for multiscale and complex products, samples must be printed, fabricated, and transferred among different …

Low Cost And Reliable Wireless Sensor Networks For Environmental Monitoring, Sonia Naderi

Electronic Theses and Dissertations

This thesis utilizes wireless sensor network systems to learn of changes in wireless network performance and environment, establishing power efficient systems that are low cost and are able to perform large scale monitoring. The proposed system was built at the University of Maine’s Wireless Sensor Networks (WiSe-Net) laboratory in collaboration with University of New Hampshire and University of Vermont researchers. The system was configured to perform soil moisture measurement with provision to include other sensor types at later stages in collaboration with Alabama A & M University. In the research associated with this thesis, a general relay energy assisted scenario …

Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt

Electronic Theses and Dissertations

Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication enable the sharing, in real time, of vehicular locations and speeds with other vehicles, traffic signals, and traffic control centers. This shared information can help traffic to better traverse intersections, road segments, and congested neighborhoods, thereby reducing travel times, increasing driver safety, generating data for traffic planning, and reducing vehicular pollution. This study, which focuses on vehicular pollution, used an analysis of data from NREL, BTS, and the EPA to determine that the widespread use of V2V-based truck platooning—the convoying of trucks in close proximity to one another so as to reduce air drag …

Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche

Electronic Theses and Dissertations

The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …

Design, Implementation, And Test Of Spacecraft Antennae And A Ground Station For Mesat1, Travis Russell

Electronic Theses and Dissertations

MESAT1 is a CubeSat that was proposed by the University of Maine in response to NASA's CubeSat Launch Initiative, and in early 2020 was selected by NASA to be launched into a Low Earth Orbit (LEO) in June of 2022. The satellite will carry four low-cost complementary metal–oxide–semiconductor (CMOS) cameras which serve as sensing instruments for three science missions proposed by K-12 schools in Maine. The cameras will periodically take pictures of Earth to analyze water turbidity, identify urban heat islands, and predict harmful algal blooms. The multi-spectral image data is packed into frames and downlinked as Binary Phase-Shift Keying …

Automatic Testing Of Organic Strain Gauge Tactile Sensors., Brian P. Goulet

Electronic Theses and Dissertations

Human-Robot Interaction is a developing field of science, that is posed to augment everything we do in life. Skin sensors that can detect touch, temperature, distance, and other physical interaction parameters at the human-robot interface are very important to enhancing the collaboration between humans and machines. As such, these sensors must be efficiently tested and characterized to give accurate feedback from the sensor to the robot. The objective of this work is to create a diversified software testing suite that removes as much human intervention as possible. The tests and methodology discussed here provide multiple realistic scenarios that the sensors …

Hardware Design And Implementation Of Genesio-Tesi Chaotic System, Manya Mehta

Electronic Theses and Dissertations

This work presents digital implementation of integer and fractional order Genesio-Tesi chaotic system. In the proposed work, digital hardware design of the model is realized. The model is first validated through software simulations and then translated into Verilog code. Each coefficient is represented through signed 2’s complement fixed point representation. A methodology has been developed to construct integer and fractional order Genesio-Tesi system. Statistical analysis like Maximum Lyapunov Exponent and autocorrelation are employed to quantify the chaotic behavior of the system. Chaotic characteristics have been analyzed by plotting graphs for different set of initial conditions thereby verifying the sensitivity of …

Heterogeneous Collaborative Mapping For Autonomous Mobile Systems, Sooraj Sunil

Electronic Theses and Dissertations

An accurate map of the environment is essential for autonomous robot navigation. During collaborative simultaneous localization and mapping, the individual robots usually represent the environment as probabilistic occupancy grid maps. These maps can be exchanged among robots and fused to reduce the overall exploration time, which is the main advantage of the collaborative systems. Such fusion is challenging due to the unknown initial correspondence problem. This thesis presents a novel feature-based map fusion approach through detecting, describing, and matching geometrically consistent features present in the overlapping region between the maps. The main drawback of usual feature-based approaches is the incapability …

High-Performance Gallium Nitride Switching Semiconductor Based Pmsm Drive For Ev Applications, Jiangobo Tian

Electronic Theses and Dissertations

This thesis explores the techniques of characterization and applications of gallium nitride (GaN) semiconductor switching devices in power conversion areas, especially permanent magnet synchronous motor (PMSM) based electric vehicle (EV) traction drives to achieve improved system performances.

At first, an investigation has been conducted to report the progresses of wide bandgap (WBG), especially GaN devices in power conversion applications. Based on the motivations to bridge the knowledge gap, the switching transient performance of enhancement–mode gallium nitride high–electron–mobility transistor (eGaN HEMT) and its impaction on switching energy loss have been chosen to start the research due to its technical challenges. Based …

Different Implementation Methods Of Tanh On Fpgas For Neural Networks Application, Samira Soaryaasa

Electronic Theses and Dissertations

Artificial neural networks (ANN) consist of a layered network of the neurons which compute the weighted sum of multiple inputs and pass it through a non-linear activation function (AF). A major difficulty is faced in the implementation of AF, which is usually hyperbolic tangent (Tanh) function. Tanh consists of exponential and division terms which makes its accurate implementation very difficult. Tanh is the most suitable for back propagation learning algorithm because it is differentiable. Previous studies have shown that the accuracy of the AF impacts the performance and the size of the whole neural networks (NNs). AFs are important elements …

Robot Learning From Human Observation Using Deep Neural Networks, Michael Elachkar

Electronic Theses and Dissertations

Industrial robots have gained traction in the last twenty years and have become an integral component in any sector empowering automation. Specifically, the automotive industry implements a wide range of industrial robots in a multitude of assembly lines worldwide. These robots perform tasks with the utmost level of repeatability and incomparable speed. It is that speed and consistency that has always made the robotic task an upgrade over the same task completed by a human. The cost savings is a great return on investment causing corporations to automate and deploy robotic solutions wherever feasible.

The cost to commission and set …

Classification Of Electropherograms Using Machine Learning For Parkinson’S Disease, Soroush Dehghan

Electronic Theses and Dissertations

Parkinson’s disease (PD) is a neurodegenerative movement disorder that progresses gradually over time. The onset of symptoms in people who are suffering from PD can vary from case to case, and it depends on the progression of the disease in each patient. The PD symptoms gradually develop and exacerbate the patient’s movements throughout time. An early diagnosis of PD could improve the outcomes of treatments and could potentially delay the progression of this disorder and that makes discovering a new diagnostic method valuable. In this study, I investigate the feasibility of using a machine learning (ML) approach to classify PD …

Data-Enabled Distribution Grid Management, Zohreh Sadat Hosseini

Electronic Theses and Dissertations

In 2020, U.S. electric utilities installed more than 94 million advanced meters, which brought the percentage of residential customers equipped with smart meters to 75%. This significant investment allows collecting extensive customer data at the distribution level, however, the data are not currently leveraged effectively to help with system operations. This dissertation aims to use the smart meters’ data to improve the grid’s reliability, stability, and controllability by solving two of the most challenging problems at the distribution level, namely distribution network phase identification and outage identification.

Distribution networks have typically been the least observable and most dynamic and locally …

Learning Approach For Fast Approximate Matrix Factorizations, Haiyan Yu

Electronic Theses and Dissertations

Efficiently computing an (approximate) orthonormal basis and low-rank approximation for the input data X plays a crucial role in data analysis. One of the most efficient algorithms for such tasks is the randomized algorithm, which proceeds by computing a projection XA with a random projection matrix A of much smaller size, and then computing the orthonormal basis as well as low-rank factorizations of the tall matrix XA. While a random matrix A is the de facto choice, in this work, we improve upon its performance by utilizing a learning approach to find an adaptive projection matrix A from a set …

Efficient Numerical Optimization For Parallel Dynamic Optimal Power Flow Simulation Using Network Geometry, Rylee Sundermann

Electronic Theses and Dissertations

In this work, we present a parallel method for accelerating the multi-period dynamic optimal power flow (DOPF). Our approach involves a distributed-memory parallelization of DOPF time-steps, use of a newly developed parallel primal-dual interior point method, and an iterative Krylov subspace linear solver with a block-Jacobi preconditioning scheme. The parallel primal-dual interior point method has been implemented and distributed in the open-source PETSc library and is currently available. We present the formulation of the DOPF problem, the developed primal dual interior point method solver, the parallel implementation, and results on various multi-core machines. We demonstrate the effectiveness our proposed block-Jacobi …

Study On Performance Of Pruned Cnn-Based Classification Models, Mengling Deng

Electronic Theses and Dissertations

Convolutional Neural Network (CNN) is a neural network developed for processing image data. CNNs have been studied extensively and have been used in numerous computer vision tasks such as image classification and segmentation, object detection and recognition, etc. [1] Although, the CNNs-based approaches showed humanlevel performances in these tasks [2], they require heavy computation in both training and inference stages, and the models consist of millions of parameters. This hinders the development and deployment of CNN-based models for real world applications. Neural Network Pruning and Compression techniques have been proposed [3, 4] to reduce the computation complexity of trained CNNs …

Superhalogen-Based Li-Rich Anti-Perovskite Superionic Conductors, Md Mominul Islam

Electronic Theses and Dissertations

Solid-state batteries are being widely explored to meet next-generation energy storage demand with a great potentiality of achieving high energy and power densities at All-solidstate Lithium-ion batteries (LIBs). In recent years, electronically inverted lithium-rich antiperovskite (LiRAP) solid electrolytes with the formula Li3OX, where X is a halogen or mixture of halogens have appeared as a prospective alternative of the commercially available flammable and corrosive organic liquid electrolytes because of their high ionic conductivity, structural variety, and wide electrochemical window. Here, For the first time, we have successfully formulated and synthesized a completely new class of super halogen based double anti-perovskite …

Artificial Solid Electrolyte Interface With Superhalogen-Based Double Antiperovskite Li6os(Bh4)2 Materials For Dentrite-Free And Stable Lithium Metal Batteries, Gazi Mahfujul Alam

Electronic Theses and Dissertations

Lithium ion batteries -- Materials.
Electrolytes.
Solid state batteries.

Sentiment Without Sentiment Analysis: Using The Recommendation Outcome Of Steam Game Reviews As Sentiment Predictor, Anqi Zhang

Electronic Theses and Dissertations

This paper presents and explores a novel way to determine the sentiment of a Steam game review based on the predicted recommendation of the review, testing different regression models on a combination of Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA) features. A dataset of Steam game reviews extracted from the Programming games genre consisting of 21 games along with other significant features such as the number of helpful likes on the recommendation, number of hours played, and others. Based on the features, they are grouped into three datasets: 1) either having keyword features only, 2) keyword features …

Relative Radiometric Correction Of Pushbroom Satellites Using The Yaw Maneuver, Christopher Begeman

Electronic Theses and Dissertations

Earth imaging satellites commonly acquire multispectral imagery using linear array detectors formatted as a pushbroom scanner. Landsat 8, a well-known example, uses pushbroom scanning and thus has 73,000 individual detectors. These 73,000 detectors are split among 14 different focal plane modules (FPM), and each detector and FPM exhibit unique behavior when monitoring a uniform radiance value. To correct for each detectors differences in sensor measurement a novel technique of relative gain estimation that employs an optimized modified Signal-to-Noise Ratio through a 90˚ yaw maneuver, also known as side slither, is presented that allows for both FPM and detector level relative …

Using Long Short-Term Memory Networks To Make And Train Neural Network Based Pseudo Random Number Generator, Aditya Harshvardhan

Electronic Theses and Dissertations

Neural Networks have been used in many decision-making models and been employed in computer vision, and natural language processing. Several works have also used Neural Networks for developing Pseudo-Random Number Generators [2, 4, 5, 7, 8]. However, despite great performance in the National Institute of Standards and Technology (NIST) statistical test suite for randomness, they fail to discuss how the complexity of a neural network affects such statistical results. This work introduces: 1) a series of new Long Short- Term Memory Network (LSTM) based and Fully Connected Neural Network (FCNN – baseline [2] + variations) Pseudo Random Number Generators (PRNG) …

Optimization Based Parameter And State Estimation Framework For Remote Microgrid Frequency Dynamics Modeling Using Probing Signals From Energy Storage Systems, Manisha Rauniyar

Electronic Theses and Dissertations

The primary aim of this thesis is to deliver an efficient design and selection of probing signal needed to estimate state and parameters representing the power system frequency dynamics with the proposed estimation technique in real-time with minimum computational time and cost. These test cases are designed for power system researchers that need to estimate and control analysis at the remote microgrid level. Case studies are presented that can be simulated at the transmission and distribution level in power grids, and in remote isolated microgrids where the independent system operator (ISO) has control. Increasing utilization of renewable energy sources and …

A Critical Study On The Effect Of Dimensionality Reduction On Intrusion Detection In Water Storage Critical Infrastructure, Ranim Aljoudi

Electronic Theses and Dissertations

Supervisory control and data acquisition (SCADA) systems are often imperiled bycyber-attacks, which can often be detected using intrusion detection system (IDSs).However, the performance and efficiency of IDSs can be affected by several factors,including the quality of data, curse of dimensionality of the data, and computationalcost. Feature reduction techniques can overcome most of these challenges by eliminatingthe redundant and non-informative features, thereby increasing the detectionaccuracy. This study aims to shows the importance of feature reduction on the intrusiondetection performance. To do this, a multi-modular IDS is designed that isconnected to the SCADA system of a water storage tank. A comparative study …

Cognitive Load Estimation Using Heart Rate Variability Measures For Driver Monitoring Systems, Safoura Kavousi

Electronic Theses and Dissertations

The society of automotive engineers define six levels of automation in vehicles from Level-0 (no automation) to Level-5 (full automation). Until the Level-5 automation is achieved, driver monitoring systems play a major role in road safety in partially automated vehicles. A driver monitoring system uses sensors to extract various psychophysiological measurements from the driver in order to monitor their readiness to safely operate the vehicle. Some driver monitoring systems use webcam type cameras to extract various features related to the alertness of the driver, such as, head-pose patterns, eye-closing patterns, and facial features. The use of physiological features such as …

Utilization Of Fringing Fields For Improved Impedance-Based Gas Detector Sensitivity, Calvin Love

Electronic Theses and Dissertations

The agriculture industry in its current form is under considerable threat due to rapidly changing climate conditions and severe weather brought upon by global warming. This global food production crisis has prompted a growing affluence towards greenhouse farming which is reported to increase the per acre yield by up to 15 times when compared to traditional open-air farming. The increase in crop production capacity is attributed in part to the controlled environmental conditions which is made possible through the implementation of gas sensing technologies. All gas sensing technologies implement a sensing material which acts as the chemical interface between the …

Landmark Identification Using Gpu For Autonomous Unmanned Aerial Vehicle In Gps Denied Navigation, Manikya Ravi Goteti

Electronic Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) depend on Global Position System (GPS) for determining their own location during navigation. In GPS-denied environments, a UAV needs to make use of alternative strategies for location estimation. Computer vision and machine learning algorithms can be used to detect common landmarks such as buildings, trees, and road intersections from aerial views. Landmark detection in combination with geotagging can be utilized for UAV self-localization. Graphical Processing Units (GPUs) such as Nvidia's Jetson have shown great promise for accelerating computationally intensive computer vision and machine learning algorithms. This thesis presents a novel method for an optimized GPU implementation …

Automated Generation Of Autosar Compliant Runtime Environment Configurations, Shawn Smith

Electronic Theses and Dissertations

Automotive Open System Architecture (AUTOSAR) is a system-level standard that is used worldwide by automotive companies and their suppliers to develop the standardized software development framework for automobiles. A Runtime Environment (RTE) is essential for any AUTOSAR software architecture. The information to configure the Runtime Environment (RTE) is given in an AUTOSAR Extensible Markup Language (ARXML) file. Currently, these ARXML files are interpreted by the developer to manually create each configuration. One may understand that this is a huge bottleneck in the design flow of software because of the following drawbacks. The first drawback is the cost and time spent …

Investigation Of Fluid Loading Effects On Cmut Arrays For Cardiac Imaging, Thasnim Mohammed

Electronic Theses and Dissertations

This thesis presents a method to minimize the resonant frequency drift of Capacitive Micromachined Ultrasonic Transducers (CMUTs) due to fluid loading. A unified mathematical model for the resonant frequency of a CMUT that includes the electrostatic spring softening effect and the fluid loading effect due to the coupled fluidic layer has been developed that provides the basis of the proposed approach. The minimization method involves dynamic adjustment of the DC bias voltage to modify the electrostatic spring softening parameter to offset the effects of fluid loading. Analytical and COMSOL based 3D Finite Element Analysis (FEA) results show that the drift …

Design, Analysis And Fabrication Of Capacitive Micromachined Resonator – Based Mass Sensors, Muhammed Umair Nathani

Electronic Theses and Dissertations

A challenge in greenhouses is the presence of various pests, virus, and bacteria. Although many pest management strategies are available, however, they all depend on visually identifying these invasive forces when they have eradicated the crop. To avoid the impacts on the agricultural sector due to such pests, early detection is required. Therefore, in this thesis MEMS-based capacitive mass resonators are proposed for early detection of such invasive forces through identifying their released volatile organic compounds (VOCs). In this work, multiple moving membrane capacitive micromachined ultrasonic transducer (M3-CMUT) as a mass sensor is proposed due to its advantages shared with …