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Smart Adaptive Beam-Forming Antenna Design For Next Generation Communication Systems, Ahmed Umar Kausar 2018 Boise State University

Smart Adaptive Beam-Forming Antenna Design For Next Generation Communication Systems, Ahmed Umar Kausar

Boise State University Theses and Dissertations

Adaptive beamforming antennas open a new venue for research to achieve high data rates. Such antennas are of interest at higher frequencies, especially at millimeter-waves. Millimeter-wave band ranges from 30 GHz - 300 GHz. There is an ample bandwidth available in this spectrum. However, due to the significant path loss at high frequencies, there is a need for better error correction schemes and adaptive beam-forming antennas for this frequency band.

The goal of our research is to design a novel adaptive beamforming smart antenna that is low cost, compact, power-efficient and less complex. Based on our recently awarded US patent, …


Micron/Nano Structure Creation Through Dual Pulse Femtosecond Laser Surface Processing, Nicholas Roth 2018 University of Nebraska-Lincoln

Micron/Nano Structure Creation Through Dual Pulse Femtosecond Laser Surface Processing, Nicholas Roth

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A new technique has been developed for creating multiscale micro/nanoscale surfaces on metals. This technique is based on past work in femtosecond laser surface processing (FLSP) and dual pulse laser induced breakdown spectroscopy (LIBS). Using a femtosecond laser, pulse pairs were created with varying pulse separations between 0 ps to 500 ps. The creation of surface structures with dual pulse FLSP was studied on Ag, Cu, Ti, Al, Ni, and 304 stainless steel in relation to pulse separation.

Using dual pulse FLSP micro/nano structures have been created for the first time on silver. The silver structures are multiscale in nature …


Iris Biometric Identification Using Artificial Neural Networks, Kevin Joseph Haskett 2018 California Polytechnic State University, San Luis Obispo

Iris Biometric Identification Using Artificial Neural Networks, Kevin Joseph Haskett

Master's Theses

A biometric method is a more secure way of personal identification than passwords. This thesis examines the iris as a personal identifier with the use of neural networks as the classifier. A comparison of different feature extraction methods that include the Fourier transform, discrete cosine transform, the eigen analysis method, and the wavelet transform, is performed. The robustness of each method, with respect to distortion and noise, is also studied.


Cmos Radioactive Isotope Identification With Multichannel Analyzer And Embedded Neural Network, Samuel Murray 2018 University of Nebraska-Lincoln

Cmos Radioactive Isotope Identification With Multichannel Analyzer And Embedded Neural Network, Samuel Murray

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A radiation detection and identification system is designed and implemented to perform gamma ray spectroscopy on radioactive sources and identify which isotopes are present in the sources. A multichannel analyzer is implemented on an ASIC to process the signal produced from gamma rays detected by a scintillator and photomultiplier tube and to quantize the gamma ray energies to build a histogram. A fast, low memory embedded neural network is implemented on a microcontroller ASIC to identify the isotopes present in the gamma ray histogram produced by the multichannel analyzer in real time.

Advisors: Sina Balkir and Michael W. Hoffman


Multiuser Coding And Signal Processing In A Low Power Sensor Network, Dongqi Lai 2018 University of Nebraska-Lincoln

Multiuser Coding And Signal Processing In A Low Power Sensor Network, Dongqi Lai

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Backscatter communication system is a wireless communication system that is used by both academic community and industry circles in recent years. This communication system only requires ultra-low power usage and simple design of the sensors. This project is using backscatter communication system to transmit data with backscatter tags. The method we used is semi-passive backscatter communication. This project focuses on transmitting signals with multiple sensors so there is a problem about distinguishing the signal reflected by different nodes. We modulated the transmitting digital signal with Walsh function to solve the problem of separating the signals between different nodes. By using …


Implementation Of Vision Processing Tasks On A Smart Camera Platform Using Neighborhood Processors, Dingyi Hong 2018 University of Nebraska-Lincoln

Implementation Of Vision Processing Tasks On A Smart Camera Platform Using Neighborhood Processors, Dingyi Hong

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Two applications of vision processing on a smart camera platform using neighborhood processors are presented. A smart camera application of real-time trajectory calculation for tracking objects and predicting their path of motion by using a single intelligent camera or a dual camera system are designed, simulated and implemented. Another application of object recognition with a key points algorithm for detecting simple shaped objects and locating the camera position within a 3-D coordinate system via imaging by using artificial neural network is applied to provide quick and accurate processing on a neighborhood-level parallel processor or other limited vision chip. For all …


Multiple-Change-Point Modeling And Exact Bayesian Inference Of Degradation Signal For Prognostic Improvement, Yuxin Wen, Jianguo Wu, Qiang Matthew Zhou, Tzu-Liang Bill Tseng 2018 Chapman University

Multiple-Change-Point Modeling And Exact Bayesian Inference Of Degradation Signal For Prognostic Improvement, Yuxin Wen, Jianguo Wu, Qiang Matthew Zhou, Tzu-Liang Bill Tseng

Engineering Faculty Articles and Research

Prognostics play an increasingly important role in modern engineering systems for smart maintenance decision-making. In parametric regression-based approaches, the parametric models are often too rigid to model degradation signals in many applications. In this paper, we propose a Bayesian multiple-change-point (CP) modeling framework to better capture the degradation path and improve the prognostics. At the offline modeling stage, a novel stochastic process is proposed to model the joint prior of CPs and positions. All hyperparameters are estimated through an empirical two-stage process. At the online monitoring and remaining useful life (RUL) prediction stage, a recursive updating algorithm is developed to …


Portable High-Definition Audio Spectrum Analyzer, Alex Zahn, Jamie Corr 2018 California Polytechnic State University, San Luis Obispo

Portable High-Definition Audio Spectrum Analyzer, Alex Zahn, Jamie Corr

Electrical Engineering

The Portable High-definition Audio Spectrum Analyzer (PHASA) allows the user to visualize the audio frequency spectrum of an incoming line-level stereo audio signal. Upon pressing the touch screen spectrum graph, the PHASA displays the corresponding frequency and volume levels as well as crosshairs at the touched location. The PHASA features multiple left/right channel display modes— Left channel only, right channel only, both channels simultaneously, and the average between the two channels. The PHASA features multiple resolution display modes (standard-resolution and high-resolution) and multiple dynamics display modes (standard dynamics, averaging, and peak/hold). The PHASA accepts input audio via a 1/4" TRS …


Electric Upgrades - Supercapacitor Electric Bicycle, John Chen, Wilson Fletcher, Spencer Esparza 2018 California Polytechnic State University, San Luis Obispo

Electric Upgrades - Supercapacitor Electric Bicycle, John Chen, Wilson Fletcher, Spencer Esparza

Electrical Engineering

Supercapacitors provide high current capabilities compared to conventional lithium-ion batteries, allowing for fast charging and discharging of electrical energy. This project seeks to test the benefits of supercapacitors in an electric bicycle unit in order to gain higher regenerative energy. The main components of the bicycle are its regenerative motor, supercapacitor array, and motor controller. Developing the project will provide data on the feasibility of using alternative battery storage and charging.


Towards A Strawberry Harvest Prediction System Using Computer Vision And Pattern Recognition, Andreas M. Apitz 2018 California Polytechnic State University, San Luis Obispo

Towards A Strawberry Harvest Prediction System Using Computer Vision And Pattern Recognition, Andreas M. Apitz

Master's Theses

Farmers require advance notice when a harvest is approaching, so they can allocate resources and hire workers as efficiently as possible. Existing methods are subjective and labor intensive, and require the expertise of a professional forecaster. Cal Poly’s EE department has been collaborating with the Cal Poly Strawberry Center to investigate the potential in using digital imaging processing to predict harvests more reliably. This paper shows the progress of that ongoing project, as well as what aspects could still be improved. Three main blocks comprise this system: data acquisition, which obtains and catalogues images of the strawberry plants; computer vision, …


Developing, Evaluating, And Demonstrating An Open Source Gateway And Mobile Application For The Smartfarm Decision Support System, Caleb D. Fink 2018 California Polytechnic State University, San Luis Obispo

Developing, Evaluating, And Demonstrating An Open Source Gateway And Mobile Application For The Smartfarm Decision Support System, Caleb D. Fink

Master's Theses

The purpose of this research is to design, develop, evaluate, and demonstrate an open source gateway and mobile application for the SmartFarm open source decision support system to improve agricultural stewardship, environmental conservation, and provide farmers with a system that they own. There are very limited options for an open source gateway for collecting data on the farm. The options available are: expensive, require professional maintenance, are not portable between systems, improvements are made only by the manufacturer, limited in customization options, difficult to operate, and data is owned by the company rather than the farmer. The gateway is designed …


Lionfish Detection System, Carmelo Furlan, Andrew Boniface 2018 California Polytechnic State University, San Luis Obispo

Lionfish Detection System, Carmelo Furlan, Andrew Boniface

Computer Engineering

Deep neural networks have proven to be an effective method in classification of images. The ability to recognize objects has opened the door for many new systems which use image classification to solve challenging problems where conventional image classification would be inadequate. We trained a large, deep convolutional neural network to identify lionfish from other species that might be found in the same habitats. Google’s Inception framework served as a powerful platform for our fish recognition system. By using transfer learning, we were able to obtain exceptional results for the classification of different species of fish. The convolutional neural network …


Range Information Characterization Of The Hokuyo Ust-20lx Lidar Sensor, Matthew A. Cooper, John F. Raquet, Rick Patton 2018 Air Force Institute of Technology

Range Information Characterization Of The Hokuyo Ust-20lx Lidar Sensor, Matthew A. Cooper, John F. Raquet, Rick Patton

Faculty Publications

This paper presents a study on the data measurements that the Hokuyo UST-20LX Laser Rangefinder produces, which compiles into an overall characterization of the LiDAR sensor relative to indoor environments. The range measurements, beam divergence, angular resolution, error effect due to some common painted and wooden surfaces, and the error due to target surface orientation are analyzed. It was shown that using a statistical average of sensor measurements provides a more accurate range measurement. It was also shown that the major source of errors for the Hokuyo UST-20LX sensor was caused by something that will be referred to as “mixed …


Multi-Label Latent Spaces With Semi-Supervised Deep Generative Models, Rastin Rastgoufard 2018 University of New Orleans

Multi-Label Latent Spaces With Semi-Supervised Deep Generative Models, Rastin Rastgoufard

LSU New Orleans Theses and Dissertations

Expert labeling, tagging, and assessment are far more costly than the processes of collecting raw data. Generative modeling is a very powerful tool to tackle this real-world problem. It is shown here how these models can be used to allow for semi-supervised learning that performs very well in label-deficient conditions.

The foundation for the work in this dissertation is built upon visualizing generative models' latent spaces to gain deeper understanding of data, analyze faults, and propose solutions. A number of novel ideas and approaches are presented to improve single-label classification. This dissertation's main focus is on extending semi-supervised Deep Generative …


Design Of A Distributed Real-Time E-Health Cyber Ecosystem With Collective Actions: Diagnosis, Dynamic Queueing, And Decision Making, Yanlin Zhou 2018 University of Nebraska-Lincoln

Design Of A Distributed Real-Time E-Health Cyber Ecosystem With Collective Actions: Diagnosis, Dynamic Queueing, And Decision Making, Yanlin Zhou

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

In this thesis, we develop a framework for E-health Cyber Ecosystems, and look into different involved actors. The three interested parties in the ecosystem including patients, doctors, and healthcare providers are discussed in 3 different phases. In Phase 1, machine-learning based modeling and simulation analysis is performed to remotely predict a patient's risk level of having heart diseases in real time. In Phase 2, an online dynamic queueing model is devised to pair doctors with patients having high risk levels (diagnosed in Phase 1) to confirm the risk, and provide help. In Phase 3, a decision making paradigm is proposed …


Density And Velocity Measurement Of Ari And Arii Using Laser Induced Fluorescence (Lif) In A Large-Scale Helicon Plasma, Ralph F. Kelly 2018 University of New Mexico

Density And Velocity Measurement Of Ari And Arii Using Laser Induced Fluorescence (Lif) In A Large-Scale Helicon Plasma, Ralph F. Kelly

Electrical and Computer Engineering ETDs

Helicon plasma sources are widely used in basic plasma science, as well as for materials processing. These plasmas typically operate at high gas fill pressure, and therefore have significant densities of neutral particles. However, the role of neutrals in the overall plasma dynamics, such as ion flows, remains poorly understood. There are at least two possible mechanisms for neutrals to influence ion flows. One is an FxB drift, where F is the force exerted on ions by neutrals through collisions. The second is through Pedersen conductivity which is dependent on the ratio of the ion cyclotron frequency, ω …


Command Validation For Cybersecure Power Router, Isaac M. Kroger 2018 University of Arkansas, Fayetteville

Command Validation For Cybersecure Power Router, Isaac M. Kroger

Electrical Engineering Undergraduate Honors Theses

For grid-connected homes equipped with solar panels, power electronics are necessary to manage and convert power between the solar panels, battery storage, grid, and residential load. A power router can be used to manage these power electronics and govern power generation, storage, and distribution within the household. This level of control makes power routers that do not employ cybersecurity a target for external attacks. The use of command validation is an effective way to prevent unauthorized commands from maliciously altering the state of a home’s power router. The purpose of this thesis is to describe the development of the command …


Experimental And Model-Based Terahertz Imaging And Spectroscopy For Mice, Human, And Phantom Breast Cancer Tissues, Tyler Bowman 2018 University of Arkansas, Fayetteville

Experimental And Model-Based Terahertz Imaging And Spectroscopy For Mice, Human, And Phantom Breast Cancer Tissues, Tyler Bowman

Graduate Theses and Dissertations

The goal of this work is to investigate terahertz technology for assessing the surgical margins of breast tumors through electromagnetic modeling and terahertz experiments. The measurements were conducted using a pulsed terahertz system that provides time and frequency domain signals. Three types of breast tissues were investigated in this work. The first was formalin-fixed, paraffin-embedded tissues from human infiltrating ductal and lobular carcinomas. The second was human tumors excised within 24-hours of lumpectomy or mastectomy surgeries. The third was xenograft and transgenic mice breast cancer tumors grown in a controlled laboratory environment to achieve more data for statistical analysis.

Experimental …


Real-Time Streaming Video And Image Processing On Inexpensive Hardware With Low Latency, Richard L. Gregg 2018 University of Nebraska-Lincoln

Real-Time Streaming Video And Image Processing On Inexpensive Hardware With Low Latency, Richard L. Gregg

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The use of resource constrained inexpensive hardware places restrictions on the design of streaming video and image processing system performance. In order to achieve acceptable frame-per-second (fps) performance with low latency, it is important to understand the response time requirements that the system needs to meet. For humans to be able to process and react to an image there should not be more than a 100ms delay between the time a camera captures an image and subsequently displays that image to the user.

In order to accomplish this goal, several design considerations need to be taken into account that limit …


Degradation Modeling And Rul Prediction Using Wiener Process Subject To Multiple Change Points And Unit Heterogeneity, Yuxin Wen, Jianguo Wu, Devashish Das, Tzu-Liang Bill Tseng 2018 Chapman University

Degradation Modeling And Rul Prediction Using Wiener Process Subject To Multiple Change Points And Unit Heterogeneity, Yuxin Wen, Jianguo Wu, Devashish Das, Tzu-Liang Bill Tseng

Engineering Faculty Articles and Research

Degradation modeling is critical for health condition monitoring and remaining useful life prediction (RUL). The prognostic accuracy highly depends on the capability of modeling the evolution of degradation signals. In many practical applications, however, the degradation signals show multiple phases, where the conventional degradation models are often inadequate. To better characterize the degradation signals of multiple-phase characteristics, we propose a multiple change-point Wiener process as a degradation model. To take into account the between-unit heterogeneity, a fully Bayesian approach is developed where all model parameters are assumed random. At the offline stage, an empirical two-stage process is proposed for model …


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