Engineering Commons^™

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 …

Data-Driven Distributed Modeling, Operation, And Control Of Electric Power Distribution Systems, Hasala Dharmawardena

All Dissertations

The power distribution system is disorderly in design and implementation, chaotic in operation, large in scale, and complex in every way possible. Therefore, modeling, operating, and controlling the distribution system is incredibly challenging. It is required to find solutions to the multitude of challenges facing the distribution grid to transition towards a just and sustainable energy future for our society. The key to addressing distribution system challenges lies in unlocking the full potential of the distribution grid. The work in this dissertation is focused on finding methods to operate the distribution system in a reliable, cost-effective, and just manner.

In …

System Identification Of Linear And Non-Linear Dynamical Systems Using Semi-Definite Programming Via Penalized Parabolic Relaxation Method, Adnan Nasir

Electrical Engineering Dissertations - Archive

This document is prepared to highlight the difference between two very important fields in the realm of Convex Optimization, Machine Learning, Artificial Intelligence and many such sprouting advance fields currently impacting the whole world. The main aim of the recent SDP algorithms is to relax the NP-Hard Convex optimization problems and transform them into amenable jobs without strong theoretical guarantees, but these algorithms tends to approximate the practical in demand applications in many of the aforementioned fields. Moreover, The lack of theoretical guarantee makes the SDP relaxation in-exact and unoptimizable in finite duration. The actual world applications most of the …

Embedding A Grid Of Load Cells Into A Dining Table For Automatic Monitoring And Detection Of Eating Events, Mohammad Mayyan

All Dissertations

This dissertation describes a “smart dining table” that can detect and measure consumption events. This work is motivated by the growing problem of obesity, which is a global problem and an epidemic in the United States and Europe. Chapter 1 gives a background on the economic burden of obesity and its comorbidities. For the assessment of obesity, we briefly describe the classic dietary assessment tools and discuss their drawback and the necessity of using more objective, accurate, low-cost, and in-situ automatic dietary assessment tools. We explain in short various technologies used for automatic dietary assessment such as acoustic-, motion-, or …

Hierarchical And Distributed Architecture For Large-Scale Residential Demand Response Management, Pramod Herath Mudiyanselage

All Dissertations

The implementation of smart grid brings several challenges to the power system. The ‘prosumer’ concept, proposed by the smart grid, allows small-scale ‘nano-grids’ to buy or sell electric power at their own discretion. One major problem in integrating prosumers is that they tend to follow the same pattern of generation and consumption, which is un-optimal for grid operations. One tool to optimize grid operations is demand response (DR). DR attempts to optimize by altering the power consumption patterns. DR is an integrated tool of the smart grid. FERC Order No. 2222 caters for distributed energy resources, including demand response resources, …

Towards A Low-Cost Solution For Gait Analysis Using Millimeter Wave Sensor And Machine Learning, Mubarak A. Alanazi, Abdullah K. Alhazmi, Osama Alsattam, Kara Gnau, Meghan Brown, Shannon Thiel, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Human Activity Recognition (HAR) that includes gait analysis may be useful for various rehabilitation and telemonitoring applications. Current gait analysis methods, such as wearables or cameras, have privacy and operational constraints, especially when used with older adults. Millimeter-Wave (MMW) radar is a promising solution for gait applications because of its low-cost, better privacy, and resilience to ambient light and climate conditions. This paper presents a novel human gait analysis method that combines the micro-Doppler spectrogram and skeletal pose estimation using MMW radar for HAR. In our approach, we used the Texas Instruments IWR6843ISK-ODS MMW radar to obtain the micro-Doppler spectrogram …

Glaciernet2: A Hybrid Multi-Model Learning Architecture For Alpine Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Michael P. Bishop, Jeffrey S. Kargel, Theus Aspiras

Electrical and Computer Engineering Faculty Publications

In recent decades, climate change has significantly affected glacier dynamics, resulting in mass loss and an increased risk of glacier-related hazards including supraglacial and proglacial lake development, as well as catastrophic outburst flooding. Rapidly changing conditions dictate the need for continuous and detailed ob-servations and analysis of climate-glacier dynamics. Thematic and quantitative information regarding glacier geometry is fundamental for understanding climate forcing and the sensitivity of glaciers to climate change, however, accurately mapping debris-cover glaciers (DCGs) is notoriously difficult based upon the use of spectral information and conventional machine-learning techniques. The objective of this research is to improve upon an …

Exploratory Analysis Of Machine Learning For Images: Methods And Applications, Meenu Ajith

Electrical and Computer Engineering ETDs

This research focuses on implementing four different applications of machine learning on images. The various categories of digital images considered for these applications are grayscale, RGB, and infra-red images. The first framework uses an unsupervised learning strategy for detecting fire and smoke from an infra-red image dataset. This problem was solved using a classical machine learning algorithm since the dataset was small and unlabeled. Next, a semi-supervised deep learning model was used for facial expression recognition. Here we detect emotions from a moderately large dataset containing labeled and unlabeled grayscale images. The third application focused on single image superresolution, which …

Sub-Bandgap Photon-Assisted Electron Trapping And Detrapping In Algan/Gan Heterostructure Field-Effect Transistors, Andrew Gunn

All Theses

We have investigated photon-assisted trapping and detrapping of electrons injected from the gate under negative bias in a heterostructure field-effect transistor (HFET). The electron injection rate from the gate was found to be dramatically affected by sub-bandgap laser illumination. The trapped electrons reduced the two-dimensional electron gas (2DEG) density at the AlGaN/GaN heterointerface but could also be emitted from their trap states by sub-bandgap photons, leading to a recovery of 2DEG density. The trapping and detrapping dynamics were found to be strongly dependent on the wavelength and focal position of the laser, as well as the gate bias stress time …

Femtosecond Laser Surface Processing To Create Self-Organized Micro- And Nano-Scale Features On Composite And Ceramic Materials, Nate Koeppe

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

Femtosecond laser surface processing (FLSP) is applied to a range of materials in this thesis. The materials studied were a carbon fiber reinforced polymer (CFRP), a thermosetting polymer, silicon nitride (Si₃N₄), and ceramic alumina. The CFRP is a composite material consisting of a thermosetting polymer and carbon fibers. The CFRP are referred to as a composite and the thermosetting polymer is referred to as a resin in this thesis. Alumina can exist in many different forms. The alumina used is 0.5 mm thick nonporous alumina sheets purchased from McMaster-Carr, and will be referred to as alumina …

Act5 Eit System : A Multiple-Source Electrical Impedance Tomography System, Omid Rajabi Shishvan

Legacy Theses & Dissertations (2009 - 2024)

This dissertation describes the design and implementation of Adaptive Current Tomograph 5 (ACT5) with a focus on the digital processing and data ow in the instrument. ACT5 is an electrical impedance tomography (EIT) instrument that produces images of the complex impedivity distribution within the body by injecting currents through and measuring voltages on electrodes applied to the skin. ACT5 is a parallel-drive EIT system with a dedicated current source for each electrode, capable of driving all electrodes simultaneously and measuring the induced voltages on them. It can support up to 48 electrodes with a frequency range of 5 kHz to …

Design And Implementation Of A Novel Eit/Ecg System With An Adaptive Current Source Act-5 / Narrative Competence And Cognitive Mapping As A Culturally Sustaining Pedagogy In The Education Of Emergent Bilinguals, Ahmed Abdelwahab

Legacy Theses & Dissertations (2009 - 2024)

Electrical Impedance Tomography (EIT) is a promising medical imaging technique used to detect the body's internal electrical characteristics based on electrical measurements made on its surface. EIT systems, particularly those that use parallel, multiple source architectures, require current sources with very high output impedance. This is a usual challenge for EIT as the practical current sources come with finite output impedance, which is highly degraded as the operation frequency gets wider. To overcome this challenge and maintain the high output impedance requirement, sources often use complex analog circuits which require manual or electronically-controlled adjustments.

Deep Learning Based Localization Of Zigbee Interference Sources Using Channel State Information, Dylan Kensler

All Theses

As the field of Internet of Things (IoT) continues to grow, a variety of wireless signals fill the ambient wireless environment. These signals are used for communication, however, recently wireless sensing has been studied, in which these signals can be used to gather information about the surrounding space. With the development of 802.11n, a newer standard of WiFi, more complex information is available about the environment a signal propagates through. This information called Channel State Information (CSI) can be used in wireless sensing. With the help of Deep Learning, this work attempts to generate a fingerprinting technique for localizing a …

Arrayed Waveguide Lens For Beam Steering, Mostafa Honari-Latifpour, Ali Binaie, Mohammad Amin Eftekhar, Nicholas Madamopoulos, Mohammad-Ali Miri

Publications and Research

Integrated planar lenses are critical components for analog optical information processing that enable a wide range of applications including beam steering. Conventional planar lenses require gradient index control which makes their on-chip realization challenging. Here, we introduce a new approach for beam steering by designing an array of coupled waveguides with segmented tails that allow for simultaneously achieving planar lensing and off-chip radiation. The proposed arrayed waveguide lens is built on engineering the evanescent coupling between adjacent channels to realize a photonic lattice with an equi-distant ladder of propagation constants that emulates the continuous parabolic index profile. Through coupled-mode analysis …

Source Reconstruction Of Electronic Circuits In Shielding Enclosures Based On Numerical Green's Function And Application In Electromagnetic Interference Estimation, Zi An Wang, Zhi Fei Xiao, Jun Fa Mao, Li (Lijun) Jun Jiang, Hakan Bagci, Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

In this work, to characterize the radiated emission from electronic circuits in shielding enclosure, an improved electric dipole-based source reconstruction method (SRM) is developed. Moreover, by resorting to this reconstructed equivalent source, the estimation of electromagnetic interference (EMI) between different circuit modules in the enclosure can be conveniently and accurately evaluated. Different from the free-space SRM, the equivalent dipoles of the proposed SRM are directly placed over the shielding box enclosed circuit board, and the numerical Green's function (NGF) is developed to bridge the connection between the equivalent dipoles and the planar scanned magnetic near-field. With the NGF strategy, the …

A Millimeter-Wave Frequency-Reconfigurable Fabry-Pérot Cavity Antenna, Min Li, Muhammad Yasir Jamal, Xiaoqiang Li, Kwan Lawrence Yeung, Lijun Jiang, Tatsuo Itoh, Ross Murch

Electrical and Computer Engineering Faculty Research & Creative Works

This letter introduces a method for implementing a frequency-reconfigurable Fabry-Pérot cavity (FPC) antenna utilizing polarization standing waves (PSWs). The PSW is supported by two metasurfaces (MSs) at cavity ends. The resonant condition allows the antenna to have frequency-reconfigurable characteristic by mechanically rotating the top MS around the center and relative to the bottom MS, without adjusting the physical dimension. The antenna is prototyped at 60 GHz for millimeter-wave applications. Simulated and measured results demonstrate that a tunable frequency range of 60.8-66.2 GHz with a maximum boresight gain of around 22.2 dBi can be attained, verifying the antenna concept.

Controller Platform Design And Demonstration For An Electric Aircraft Propulsion Driv, Rosten Sweeting

Graduate Theses and Dissertations

With the growth in the aerospace industry there has been a trend to optimize the performance of an aircraft by reducing fuel consumption and operational cost. Recent advancements in the field of power electronics have pushed towards the concepts of hybrid electric aircraft also known as more electrical aircrafts. In this work, a custom controller board for an electric aircraft propulsion drive was designed to drive a permanent magnet synchronous motor. Design of the controller board required knowledge of the topology selection and power module selections. Simulations of the system were performed using MATLAB/Simulink to analyze the overall performance of …

Materials Design For Energy Applications Using Ab- Initio Calculations, Hind Hemaidee Alqurashi

Graduate Theses and Dissertations

The structural, dynamical, electronic, and thermoelectric properties of rock-salt and wurtzite Cd1-xZnxO alloys, VTiRhZ (Al, Ga, In, Si, Ge, Sn) and ZrTiRhZ (Ge, Sn) quaternary Heusler alloys (QHAs) were investigated using density functional theory (DFT) and semi-classical Boltzmann transport theory. From these calculations, the alloys were identified as potential materials for future thermoelectric applications. Furthermore, the magnetic and spin-polarization properties of these QHAs were investigated. The total magnetic moments were found to be integer values for all QHAs. In addition, all studied QHAs except VTiRhAl possess a half-metallic behavior with a 100% spin-polarization. The half-metallic ferromagnetic behavior makes them promising …

Constraint-Aware, Scalable, And Efficient Algorithms For Multi-Chip Power Module Layout Optimization, Imam Al Razi

Graduate Theses and Dissertations

Moving towards an electrified world requires ultra high-density power converters. Electric vehicles, electrified aerospace, data centers, etc. are just a few fields among wide application areas of power electronic systems, where high-density power converters are essential. As a critical part of these power converters, power semiconductor modules and their layout optimization has been identified as a crucial step in achieving the maximum performance and density for wide bandgap technologies (i.e., GaN and SiC). New packaging technologies are also introduced to produce reliable and efficient multichip power module (MCPM) designs to push the current limits. The complexity of the emerging MCPM …

A Memory-Centric Customizable Domain-Specific Fpga Overlay For Accelerating Machine Learning Applications, Atiyehsadat Panahi

Graduate Theses and Dissertations

Low latency inferencing is of paramount importance to a wide range of real time and userfacing Machine Learning (ML) applications. Field Programmable Gate Arrays (FPGAs) offer unique advantages in delivering low latency as well as energy efficient accelertors for low latency inferencing. Unfortunately, creating machine learning accelerators in FPGAs is not easy, requiring the use of vendor specific CAD tools and low level digital and hardware microarchitecture design knowledge that the majority of ML researchers do not possess. The continued refinement of High Level Synthesis (HLS) tools can reduce but not eliminate the need for hardware-specific design knowledge. The designs …

Evaluation Of Single Phase Smart Pv Inverter Functions In Unbalanced Residential Distribution Systems, Darren Symonette

Graduate Theses and Dissertations

In the United States, smart PV inverters integrated with residential distribution systems are becoming a more common occurrence. With integration of smart PV inverters, power utilities are experiencing an increase of number of operations with regards to switched capacitor banks, voltage regulators and on load tap changers. These increases can lead to excess wear and tear on the devices causing power utilities to perform unwanted replacement and maintenance. However, smart PV inverters when controlled under specific functions can enable these inverters to provide reactive power and voltage control which in turn lowers the number of operations for switched capacitor banks, …

Z-Source-Based High Step-Up Dc-Dc Converters For Photovoltaic Applications, Ramin Rahimi, Saeed Habibi, Mehdi Ferdowsi, Pourya Shamsi

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes three high step-up Z-source (ZS)-based dc-dc converters by integrating the conventional ZS network with switched-capacitor (SC) cells. The proposed converters offer a simple structure with a smooth input current, a high-voltage gain, and low voltage stress on the semiconductor devices. In addition, the proposed converters, unlike some existing ZS-based topologies in the literature, do not impose any limitation on the duty cycle of the power switch. These characteristics make the proposed converters excellent candidates to interface a low-voltage solar photovoltaic (PV) panel with a high-voltage dc bus in PV applications. Among the proposed three converters, the operating …

Gp-K: A Probabilistic Method For Hourly Day-Ahead Power Load Forecasting, Miguel A. Hombrados-Herrera

Electrical and Computer Engineering ETDs

The elevated costs that incur power grid stakeholders due to forecasting errors in power load demand have created the need for forecasting methods that provide accurate predictions and allow for assessing the reliability of their predictions. This thesis proposes a probabilistic forecasting method for multi-step ahead forecasting.

In particular, it presents a probabilistic method to perform a 24-hours-ahead power load forecasting that arises as the combination of Gaussian Process regressors with NMF (nonnegative matrix factorization) and integrates the advantages of both methods. Instead of training 24 independent processes for each hour of the predicted day, this work proposes to factorize …

Ternary Logic Design In Topological Quantum Computing, Muhammad Ilyas, Shawn Cui, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

A quantum computer can perform exponentially faster than its classical counterpart. It works on the principle of superposition. But due to the decoherence effect, the superposition of a quantum state gets destroyed by the interaction with the environment. It is a real challenge to completely isolate a quantum system to make it free of decoherence. This problem can be circumvented by the use of topological quantum phases of matter. These phases have quasiparticles excitations called anyons. The anyons are charge-flux composites and show exotic fractional statistics. When the order of exchange matters, then the anyons are called non-Abelian anyons. Majorana …

Hybrid Smart Transformer For Enhanced Power System Protection Against Dc With Advanced Grid Support, Moazzam Nazir

All Dissertations

The traditional grid is rapidly transforming into smart substations and grid assets incorporating advanced control equipment with enhanced functionalities and rapid self-healing features. The most important and strategic equipment in the substation is the transformer and is expected to perform a variety of functions beyond mere voltage conversion and isolation. While the concept of smart solid-state transformers (SSTs) is being widely recognized, their respective lifetime and reliability raise concerns, thus hampering the complete replacement of traditional transformers with SSTs. Under this scenario, introducing smart features in conventional transformers utilizing simple, cost-effective, and easy to install modules is a highly desired …

A Novel Testbed For Evaluation Of Operational Technology Communications Protocols And Their On-Device Implementations, Matthew Boeding

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

Operational Technology (OT) and Infrastructure Technology (IT) systems are converging with the rapid addition of centralized remote management in OT systems. Previously air-gapped systems are now interconnected through the internet with application-specific protocols. This has led to systems that had limited access points being remotely accessible. In different OT sectors, legacy protocols previously transmitted over serial communication were updated to allow internet communication with legacy devices. New protocols such as IEC-61850 were also introduced for monitoring of different OT resources. The IEC-61850 standard’s Generic Object Oriented Substation Event (GOOSE) protocol outlines the representation and communication of a variety of different …

Physical Implementation And Testing Of A Transmission Line Fault Location Algorithm, Shadi Mohammad Alshagarin

Masters Theses

Fault detection and location is crucial in any power system. In order to improve system reliability, reduce outage time and speed-up system restoration from a fault, fault detection and location must be prompt and accurate. Traditional methods of pinpointing faults can be complex, costly, unreliable, and can even result in unacceptably large fault.

This thesis aims to develop and evaluate a physical proof-of-concept for transmission line fault location technology based on a novel methodology with high accuracy and unique visualization capabilities. The proposed prototype utilizes the open-source tools Raspberry Pi 4 and Python computer language. This prototype model is intended …

Seamless Transition Of A Microgrid Between Grid-Connected And Islanded Mode, Julie B. Matarweh

Boise State University Theses and Dissertations

This thesis focuses on improving the behavior of inverters during transition periods from islanded mode to grid-connected mode (GC) and vice-versa. A systematic approach is presented to add smart features to inverters to enhance their capability to cope with sudden changes in the power system.

The importance of microgrids lies in their ability to provide a stable and reliable source of power for critical loads in the presence of faults. For this purpose, a design is proposed consisting of a distributed energy resource (DER), battery energy storage system (BESS) and a load connected through a bypass switch with the main …

Data-Driven Passivity-Based Control Of Underactuated Robotic Systems, Wankun Sirichotiyakul

Boise State University Theses and Dissertations

Classical control strategies for robotic systems are based on the idea that feedback control can be used to override the natural dynamics of the machines. Passivity-based control (Pbc) is a branch of nonlinear control theory that follows a similar approach, where the natural dynamics is modified based on the overall energy of the system. This method involves transforming a nonlinear control system, through a suitable control input, into another fictitious system that has desirable stability characteristics. The majority of Pbc techniques require the discovery of a reasonable storage function, which acts as a Lyapunov function candidate that can be …

Process-Property Linkages Construction For Inkjet Printing With Machine Learning, Fataneh Jenabi

Boise State University Theses and Dissertations

Printed electronics are emerging technologies that can potentially revolutionize the manufacturing of electronic devices. One promising technology for printed electronics is inkjet printing. Inkjet printing offers both low-cost processing and high resolution. Being a subset of additive manufacturing, inkjet printing minimizes waste and is compatible with a wide range of inks. However, inkjet printing of electronic devices is still in its infancy. One major challenge for inkjet printing is the complexity of the process optimization and uncertain high throughput production. To achieve a high-quality print, there is a complex parameter space of materials and processing parameters that needs to be …