Engineering Commons^™

Bio-Inspired Learning And Hardware Acceleration With Emerging Memories, Shruti R. Kulkarni

Dissertations

Machine Learning has permeated many aspects of engineering, ranging from the Internet of Things (IoT) applications to big data analytics. While computing resources available to implement these algorithms have become more powerful, both in terms of the complexity of problems that can be solved and the overall computing speed, the huge energy costs involved remains a significant challenge. The human brain, which has evolved over millions of years, is widely accepted as the most efficient control and cognitive processing platform. Neuro-biological studies have established that information processing in the human brain relies on impulse like signals emitted by neurons called …

Study And Modelling Of Lithium Ion Cell With Accurate Soc Measurement Algorithm Using Kalman Filter For Electric Vehicles, Kasthuriramanan Mahendravadi Sivaguru

Theses

Lithium Ion cells are preferred over lead acid cells for electric vehicles due to their energy density, higher discharge current and size. The cost of lithium ion cells is scaling down compared to ten years earlier, but as their performance characteristics increase, the need for safety and accurate modelling also increases.

The absence of a generic cell model is associated to the different makes of cells and different chemistries of Lithium ion cells behave differently under the testing conditions required for every unique application. The focus of this thesis will be on how to provide intelligence to the battery management …

Magnetic Field Effects On Lithium Ion Batteries, Kevin Mahon

Theses

The Nobel Prize in Chemistry 2019 was just recently awarded to John B. Goodenough, M. Stanley Whittingham, and Akira Yoshino for the development of lithium-ion batteries. Lithium-ion batteries have seen use in many different industries and applications such as in portable devices, power grids, and electric vehicles. As lithium-ion batteries become more commonplace they will need to be modeled more extensively. The magnetic field effect on lithium-ion batteries has not been studied significantly since they were first discovered.

Modeling these batteries is still difficult because of the many complexities of the operation of a battery. Lithium-ion batteries are commonly modeled …

Technology-Dependent Quantum Logic Synthesis And Compilation, Kaitlin Smith

Electrical Engineering Theses and Dissertations

The models and rules of quantum computation and quantum information processing (QIP) differ greatly from those that govern classical computation, and these differences have caused the implementation of quantum processing devices with a variety of new technologies. Many platforms have been developed in parallel, but at the time of writing, one method of quantum computing has not shown to be superior to the rest. Because of the variation that exists between quantum platforms, even between those of the same technology, there must be a way to automatically synthesize technology-independent quantum designs into forms that are capable of physical realization on …

Reducing The Production Cost Of Semiconductor Chips Using (Parallel And Concurrent) Testing And Real-Time Monitoring, Qutaiba Khasawneh

Electrical Engineering Theses and Dissertations

Consumer electronics changed the semiconductor industry by developing many new challenges for consumer products. One of the main challenges in the consumer product is that it propelled the volume of production to massive production, e.g. hundreds of millions of cell phones are produced yearly. Combined with the overproduction of consumer products, price pressure is another challenge for consumer products. Many of the new techniques used in the design and fabrication enabled the integration of more devices in the same chips. This reduced the cost of the chips, lowered the power consumption, increased the circuit operation speed, enabled more reliable implementation, …

Design And Implementation Of Anomaly Detections For User Authentication Framework, Iman Abu Sulayman

Electronic Thesis and Dissertation Repository

Anomaly detection is quickly becoming a very significant tool for a variety of applications such as intrusion detection, fraud detection, fault detection, system health monitoring, and event detection in IoT devices. An application that lacks a strong implementation for anomaly detection is user trait modeling for user authentication purposes. User trait models expose up-to-date representation of the user so that changes in their interests, their learning progress or interactions with the system are noticed and interpreted. The reason behind the lack of adoption in user trait modeling arises from the need of a continuous flow of high-volume data, that is …

Objective Estimation Of Tracheoesophageal Speech Quality, Yousef S Ettomi Ali

Electronic Thesis and Dissertation Repository

Speech quality estimation for pathological voices is becoming an increasingly important research topic. The assessment of the quality and the degree of severity of a disordered speech is important to the clinical treatment and rehabilitation of patients. In particular, patients who have undergone total laryngectomy (larynx removal) produce Tracheoesophageal (TE) speech. In this thesis, we study the problem of TE speech quality estimation using advanced signal processing approaches. Since it is not possible to have a reference (clean) signal corresponding to a given TE speech (disordered) signal, we investigate in particular the non-intrusive techniques (also called single-ended or blind approaches) …

Neural Network In Hardware, Jiong Si

UNLV Theses, Dissertations, Professional Papers, and Capstones

This dissertation describes the implementation of several neural networks built on a field programmable gate array (FPGA) and used to recognize a handwritten digit dataset – the Modified National Institute of Standards and Technology (MNIST) database. A novel hardwarefriendly activation function called the dynamic ReLU (D-ReLU) function is proposed. This activation function can decrease chip area and power of neural networks when compared to traditional activation functions at no cost to prediction accuracy.

The implementations of three neural networks on FPGA are presented: 2-layer online training fully-connected neural network, 3-layer offline training fully-connected neural network, and two solutions of Super-Skinny …

High-Speed Radhard Mega-Pixel Cis Camera For High-Energy Physics, Wenlan Wu

UNLV Theses, Dissertations, Professional Papers, and Capstones

This dissertation describes the schematic design, physical layout implementation, system-level hardware with FPGA firmware design, and testing of a camera-on-a-chip with a novel high-speed CMOS image sensor (CIS) architecture developed for a mega-pixel array. The novel features of the design include an innovative quadruple column-parallel readout (QCPRO) scheme with rolling shutter that increases pixel rate, its ability to program the frame rate and to tolerate Total Ionizing Dose effects (TID). Two versions of the architecture, a small (128 x 1,024 pixels) and large (768 x 1,024 pixels) version were designed and fabricated with a custom layout that does not include …

Kernel Methods For Graph-Structured Data Analysis, Zhen Zhang

McKelvey School of Engineering Theses & Dissertations

Structured data modeled as graphs arise in many application domains, such as computer vision, bioinformatics, and sociology. In this dissertation, we focus on three important topics in graph-structured data analysis: graph comparison, graph embeddings, and graph matching, for all of which we propose effective algorithms by making use of kernel functions and the corresponding reproducing kernel Hilbert spaces.For the first topic, we develop effective graph kernels, named as "RetGK," for quantitatively measuring the similarities between graphs. Graph kernels, which are positive definite functions on graphs, are powerful similarity measures, in the sense that they make various kernel-based learning algorithms, for …

Instrumentation For Dynamic Nuclear Polarization And Application Of Electron Decoupling For Electron Relaxation Measurement, Nicholas Howard Alaniva

Arts & Sciences Electronic Theses and Dissertations

Dynamic nuclear polarization nuclear magnetic resonance (DNP NMR) exploits internal electron spin and nuclear spin interactions to increase sensitivity and uncover valuable information regarding structure and dynamics of a system. To manipulate these interactions, instrumentation is developed to combine high-power microwave and radiofrequency irradiation with the ability to spin samples at the magic angle (MAS) at temperatures from 90 K to 4.2 K. Electron decoupling uses frequency-modulated microwaves to mitigate the electron-nuclear dipolar interaction, improving signal intensity and resolution in DNP NMR experiments. Electron decoupling is combined with short DNP periods to encode electron spin information in polarized nuclear signal. …

On Action Quality Assessment, Paritosh Parmar

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this dissertation, we tackle the task of quantifying the quality of actions, i.e., how well an

action was performed using computer vision. Existing methods used human body pose-based features to express the quality contained in an action sample. Human body pose estimation in actions such as sports actions, like diving and gymnastic vault, is particularly challenging, since the athletes undergo convoluted transformations while performing their routines. Moreover, pose-based features do not take into account visual cues such as water splash in diving. Visual cues are taken into account by human judges. In our first work, we show that using …

A Highly-Sensitive Global-Shutter Cmos Image Sensor With On-Chip Memory For Hundreds Of Kilo-Frames Per Second Scientific Experiments, Konstantinos Moutafis

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this work, a highly-sensitive global-shutter CMOS image sensor with on-chip memory that can capture up to 16 frames at speeds higher than 200kfps is presented. The sensor fabricated and tested is a 100 x 100 pixel sensor, and was designed to be expandable to a 1000 x 1000 pixel sensor using the same building blocks and similar architecture.

The heart of the sensor is the pixel. The pixel consists of 11 transistors (11T) and 2 MOSFET capacitors. A 6T front-end is followed by a Correlated Double Sampling (CDS) circuitry that includes 2 capacitors and a reset switch. The 4T …

Leveraging Cloud-Based Nfv And Sdn Platform Towards Quality-Driven Next-Generation Mobile Networks, Hassan Hawilo

Electronic Thesis and Dissertation Repository

Network virtualization has become a key approach for Network Service Providers (NSPs) to mitigate the challenge of the continually increasing demands for network services. Tightly coupled with their software components, legacy network devices are difficult to upgrade or modify to meet the dynamically changing end-user needs. To virtualize their infrastructure and mitigate those challenges, NSPs have started to adopt Software Defined Networking (SDN) and Network Function Virtualization (NFV). To this end, this thesis addresses the challenges faced on the road of transforming the legacy networking infrastructure to a more dynamic and agile virtualized environment to meet the rapidly increasing demand …

An Application Of Deep Learning Models To Automate Food Waste Classification, Alejandro Zachary Espinoza

Dissertations and Theses

Food wastage is a problem that affects all demographics and regions of the world. Each year, approximately one-third of food produced for human consumption is thrown away. In an effort to track and reduce food waste in the commercial sector, some companies utilize third party devices which collect data to analyze individual contributions to the global problem. These devices track the type of food wasted (such as vegetables, fruit, boneless chicken, pasta) along with the weight. Some devices also allow the user to leave the food in a kitchen container while it is weighed, so the container weight must also …

Cluster-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian

Electronic Thesis and Dissertation Repository

Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building/group to predict future consumption for that same building/group. With hundreds of thousands of smart meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Cluster-Based Chained Transfer Learning (CBCTL), an approach for building neural network-based models for many meters by taking advantage of already trained models through …

Hf Iq Mixer Vfo Temperature Compensation And Drive Level Optimization For Opposite Sideband Suppression, Katlin Anne-Rostomyan Dahn

Dissertations and Theses

An amateur radio 40m band temperature compensated variable frequency oscillator (VFO) with drive-level optimized for opposite sideband suppression for use as the local oscillator (LO) of a high frequency (HF) IQ image reject mixer is considered in this work. The first problem of this thesis was the discovery of the HF IQ mixer's opposite sideband suppression dependence on LO drive-level. As a solution to this problem, the author built a fixed drive-level VFO for the optimal opposite sideband suppression. This then led to the second problem of this thesis; the discovery by this author of the well-known problem of VFO …

A Wearable Mechatronic Device For Hand Tremor Monitoring And Suppression: Development And Evaluation, Yue Zhou

Electronic Thesis and Dissertation Repository

Tremor, one of the most disabling symptoms of Parkinson's disease (PD), significantly affects the quality of life of the individuals who suffer from it. These people live with difficulties with fine motor tasks, such as eating and writing, and suffer from social embarrassment. Traditional medicines are often ineffective, and surgery is highly invasive and risky. The emergence of wearable technology facilitates an externally worn mechatronic tremor suppression device as a potential alternative approach for tremor management. However, no device has been developed for the suppression of finger tremor that has been validated on a human.

It has been reported in …

Image Restoration Using Automatic Damaged Regions Detection And Machine Learning-Based Inpainting Technique, Chloe Martin-King

Computational and Data Sciences (PhD) Dissertations

In this dissertation we propose two novel image restoration schemes. The first pertains to automatic detection of damaged regions in old photographs and digital images of cracked paintings. In cases when inpainting mask generation cannot be completely automatic, our detection algorithm facilitates precise mask creation, particularly useful for images containing damage that is tedious to annotate or difficult to geometrically define. The main contribution of this dissertation is the development and utilization of a new inpainting technique, region hiding, to repair a single image by training a convolutional neural network on various transformations of that image. Region hiding is also …

Critical Radius Of Insulation, Maria N. Ambrose, Samuel J. Sayre, Travis W. Martin, Matt T. Sterling

Mechanical Engineering

The critical radius of insulation is a counterintuitive concept within the study of heat transfer. The theory states that adding insulation to a cylindrical or spherical object will increase the rate of heat loss rather than decrease it, if the radius (thickness) of the insulation is at its “critical” value. The Critical Radius of Insulation Senior Project is designed to demonstrate this phenomenon to Heat Transfer students via a portable apparatus. The concept will be demonstrated with a cylindrical object which is heated by way of a separate voltage source. Thermocouples will display the temperature of the cylinder while insulation …

Intracellular Electrometer, Lucas M. Essenburg

Masters Theses

The Western Michigan University Neurobiology Engineering Laboratory conducts re- search in energy-efficient electrical stimulation of biological neurons. Experimental work re- quires an intracellular electrometer to inject nanoamp-level currents into a biological neuron and to measure its membrane voltage response. In order to fully understand the generation of such minute currents, an `in-house' electrometer was designed, constructed, and validated. This required exploration of various design trade-offs including precision of generated nanoamp-level currents vs. susceptibility to noise, portability vs. functionality, and cost vs. functionality. The electrometer was successfully used to stimulate and measure responses of neurons from the medicinal leech Hirudo verbana …

Portable Electrochemical System For Flexible Hybrid Electronics, Anthony Joseph Hanson

Masters Theses

This work focuses on the fabrication and design of a portable electrochemical sensing system for flexible hybrid electronic (FHE) sensors. A three-electrode chemical sensor was fabricated using copper tape on polyethylene terephthalate (PET) substrate, using laser etching process. An electronic circuit was designed to measure the sensor response through electrochemical techniques to detect different concentrations of glucose. The device was calibrated to give the user a concentration value in 5 seconds. The system was also designed to preform tests such as cyclic voltammogram and chronoamperogram for various chemicals. A Bluetooth Low Energy module was used to wirelessly transmit the results …

A Comparative Study On The Stability And Degradation Of Perovskite Solar Cells, Jyotiska Chakraborty

Masters Theses

This study aims to investigate the environmental factors that affect the performance and longterm stability of the perovskite solar cells (PSCs). PSCs are based on organo-metallic halides (perovskites) that act as a light-sensitive compound that produces excitons when placed under the light. However, PSCs have a limited operating lifetime due to the degradation of the perovskite layer. There are many factors like moisture, UV light, and temperature that lead to the degradation of the perovskite layer. From the literature review, it was found that the PSCs do not degrade with the presence of oxygen in a dry and dark environment. …

Load Flow Analysis Of 138/69kv Substation Using Electrical Transient & Analysis Program (Etap), Vanessa Abadia Gomez

Electrical Engineering Undergraduate Honors Theses

This paper examines the load flow analysis of a high-voltage substation using ETAP, and explores options for improving the voltage profile of the system. This study yields critical information about the system, such as the voltage drop at each feeder, the voltage at each bus, as well as real and reactive power losses at the different branches and feeders. In this power flow examination, the system’s performance is evaluated for different operating conditions, so that control measurements can be applied if necessary. The experimental results are used for proposing a plan of using fixed and switched shunt capacitor banks to …

Single Photon Avalanche Diode (Spad) Array Quenching And A Novel Quantum Random Number Generator (Qrng), Mano Rahul Kumar Pakalapati

Theses and Dissertations

Single Photon Avalanche Diodes, SPADs is a single-photon sensitive light detector with capabilities of pico-second timing resolutions and offer potential for enhancing various fields of science to evolve into quantum-age. SPAD has applications ranging from quantum computing, cryptography (QKD) to applications in medicine such as neural imaging and Single Photon Emission Computed Tomography (SPECT). SPAD arrays are gaining popularity as they enable for parallel photon detection and 3D imaging. To account for the process tolerances and aging, each SPAD-pixel needs a tunable quenching circuit in the frontend for post-fabrication fine-tuning, this research work presents a novel Dual Triggered Tunable Active …

Radio Direction Finding Using Pseudo-Doppler For Uav-Based Animal Tracking, Anup Karki

Masters Theses

Radio Direction Finding (RDF) is commonly used for low cost tracking and navigation systems. However, for a low cost application and mobility, the design constraints are highly limited. Pseudo Doppler (PD) can improve RDF capabilities without being cost prohibitive. This work entails the analysis of PD RDF and its potential use for Unmanned Aerial Vehicles (UAV) that are currently employed in wildlife research animal tracking. PD is based on the doppler effect or doppler shift. The doppler effect works like a frequency modulator that increases or decreases the observed frequency depending on whether a signal source is approaching or receding …

Assessment Of Sensory Abnormalities In Children With Asd Using Virtual Reality, Ankit Koirala

Theses and Dissertations

Sensory abnormality is one of the important characteristics of Autism Spectrum Disorder(ASD). A large number of studies suggest a strong connection between sensory abnormalities and ASD. Therefore, it is important to assess sensory abnormalities for diagnosis and intervention of ASD. In this thesis study, we aim to develop a virtual reality system that can measure sensory abnormalities in adolescents with ASD. Sensory abnormalities can affect all five senses: touch, vision, smell, taste and auditory. However, in this study, we focus on assessing sensory abnormality in vision and touch sensory processing. Twelve adolescents with ASD and 12 typically developing (TD) adolescents …

Optimal Reactive Power Dispatch Using Tlbo For Modelling And Powerworld For Validation, Nneka Nwosu

Culminating Projects in Electrical Engineering

This research presents a Teaching Learning Based Optimization (TLBO) algorithm to solve Optimal Reactive Power Dispatch (ORPD) problem. The primary objective of this paper is to minimize the active power transmission losses by the optimal settings of the control variables within their limits and avoiding violations on the constraints. TLBO is a population- based algorithm and requires few algorithm specifications to compute making it a recommended option to solve various degrees of optimization problems. The TLBO algorithm was implemented using MATLAB programming and by incorporating MATPOWER, the algorithm was tested on IEEE 30-bus test system to solve the ORPD problem. …

Dual-Task Multimodal Web Browsing In Semi-Autonomous Vehicles, Jarrett William Clark

Theses and Dissertations

Drivers should remain alert when operating semi-autonomous vehicles as human intervention is required when the automated systems fail, or an unusual situation is encountered. However, drivers do not always focus solely on the road and sometimes divert their attention to look at cell phones, laptops, tablet computers, or in-dash infotainment systems. In this research, software was created to enable operators of a simulated self-driving car to browse the Human-Centered Design Institute (HCDI) website using multimodal interaction. The software used synthesized speech to read the website aloud and visually highlighted the content on the screen as it was read. Web analytics …

Resource Allocation And Task Scheduling Optimization In Cloud-Based Content Delivery Networks With Edge Computing, Yang Peng

Operations Research and Engineering Management Theses and Dissertations

The extensive growth in adoption of mobile devices pushes global Internet protocol (IP) traffic to grow and content delivery network (CDN) will carry 72 percent of total Internet traffic by 2022, up from 56 percent in 2017. In this praxis, Interconnected Cache Edge (ICE) based on different public cloud infrastructures with multiple edge computing sites is considered to help CDN service providers (SPs) to maximize their operational profit. The problem of resource allocation and performance optimization is studied in order to maximize the cache hit ratio with available CDN capacity.

The considered problem is formulated as a multi-stage stochastic linear …