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Full-Text Articles in Electrical and Electronics

Transfer-To-Transfer Learning Approach For Computer Aided Detection Of Covid-19 In Chest Radiographs, Barath Narayanan Narayanan, Russell C. Hardie, Vignesh Krishnaraja, Christina Karam, Venkata Salini Priyamvada Davuluru Dec 2020

Transfer-To-Transfer Learning Approach For Computer Aided Detection Of Covid-19 In Chest Radiographs, Barath Narayanan Narayanan, Russell C. Hardie, Vignesh Krishnaraja, Christina Karam, Venkata Salini Priyamvada Davuluru

Electrical and Computer Engineering Faculty Publications

The coronavirus disease 2019 (COVID-19) global pandemic has severely impacted lives across the globe. Respiratory disorders in COVID-19 patients are caused by lung opacities similar to viral pneumonia. A Computer-Aided Detection (CAD) system for the detection of COVID-19 using chest radiographs would provide a second opinion for radiologists. For this research, we utilize publicly available datasets that have been marked by radiologists into two-classes (COVID-19 and non-COVID-19). We address the class imbalance problem associated with the training dataset by proposing a novel transfer-to-transfer learning approach, where we break a highly imbalanced training dataset into a group of balanced mini-sets and …


Novel Memristor Based True Random Number Generator, Scott Stoller Dec 2020

Novel Memristor Based True Random Number Generator, Scott Stoller

Boise State University Theses and Dissertations

Random numbers are an important, but often overlooked part of the modern computing environment. They are used everywhere around us for a variety of purposes, from simple decision making in video games such as a coin toss, to securing financial transactions and encrypting confidential communications. They are even useful for gambling and the lottery.

Random numbers are generated in many ways. Pseudo random number generators (PRNGs) generate numbers based on a formula. True random number generators (TRNGs) capture entropy from the environment to generate randomness. As our society and our devices become more connected in the digital world, it is …


Design Of A Single-Carrier Pulse Width Modulation With Submodule Fault-Tolerant Capability For Modular Multilevel Converter, Tuanku Badzlin Hashfi Nov 2020

Design Of A Single-Carrier Pulse Width Modulation With Submodule Fault-Tolerant Capability For Modular Multilevel Converter, Tuanku Badzlin Hashfi

Student Works (2020-2029)

Multilevel converters are attracting a lot of attention and becoming one of the energy conversion choices for new topologies and control in industry applications and research fields. Modular multilevel converters (MMCs) are considered very promising among converter topologies for future medium-voltage and high-power applications compared to NPC, FC and CHB topologies. The improved phase disposition pulse width modulation (PDPWM) technique control for MMCs, which has a fault-tolerant capability, is presented. This study presents two methods to distribute pulses into submodules (SMs) by using PDPWM which has drawback to distribute the power equally among the submodules (SMs). First method, this study …


Optimal Distribution System Reconfiguration Incorporating Dg And Variable Load Profile Using Artificial Neural Network, Hesham Hanie Youssef Nov 2020

Optimal Distribution System Reconfiguration Incorporating Dg And Variable Load Profile Using Artificial Neural Network, Hesham Hanie Youssef

Student Works (2020-2029)

Optimal network reconfiguration is a common method used in distribution systems to ensure minimum power losses are always attained. This is very important task for achieving cost effective operation. Due to varying load demands, conventional network reconfiguration techniques have to be repeated whenever system loading changes to find a new configuration that has minimum power losses. This task is time consuming and ineffective approach for a real time application. Therefore, this research proposes an Artificial Neural Network (ANN) technique for optimal distribution network reconfiguration to overcome long processing time, mainly in load variation case. The proposed method involves; (1) Implement …


Optimized Transconductance Designs To Enhance The Linearity Performance Of Rf Front-End Receiver Circuits In 130 Nm Cmos Technology, Nandini Vitee Sep 2020

Optimized Transconductance Designs To Enhance The Linearity Performance Of Rf Front-End Receiver Circuits In 130 Nm Cmos Technology, Nandini Vitee

Student Works (2020-2029)

Highly linear front-end circuits are greatly desired for wireless receivers to improve the dynamic range. However, intermodulation distortions caused by the non-linear transconductor current limits the linearity of the front-end receiver circuit in CMOS technologies. In addition to the inherent nonlinear effect, the downscaling of CMOS further exacerbates the linearity of the circuit due to lower voltage headroom and high-field mobility. Thus, it is essential to develop effective circuit techniques that can aid linearity enhancement without jeopardizing other preferred performances such as low noise, high conversion gain, and low-power consumption. In this thesis, two different high linear transconductors are presented …


Fault-Tolerant Capability Of Star Connected Symmetrical Six-Phase Induction Machine With Single And Two Isolated Neutrals, Wan Noraishah Wan Abdul Munim Aug 2020

Fault-Tolerant Capability Of Star Connected Symmetrical Six-Phase Induction Machine With Single And Two Isolated Neutrals, Wan Noraishah Wan Abdul Munim

Student Works (2020-2029)

Traditionally, electrical machines have been designed to operate with single- or three phase power supplies. In the early stage of power electronics development, three-phase machine suffers problems such as high torque ripple due to low order harmonics during six-step switching and limited current handling capacity of the power switches. This has motivated the use of multiphase machines which is capable of mitigating the aforementioned issues. The revival of multiphase machine research is mainly motivated by the need for more reliable drive systems. The vector space decomposition (VSD) model is used for a healthy multiphase machine as the basis for control …


A 2.56 Gbps Serial Wireline Transceiver That Supports An Auxiliary Channel And A Hybrid Line Driver To Compensate Large Channel Loss, Xiaoran Wang Aug 2020

A 2.56 Gbps Serial Wireline Transceiver That Supports An Auxiliary Channel And A Hybrid Line Driver To Compensate Large Channel Loss, Xiaoran Wang

Electrical Engineering Theses and Dissertations

Serial transceiver links are widely used for high-speed point-to-point communications. This dissertation describes two transceiver link designs for two different applications.

In serial wireline communications, security is an increasingly important factor to concern. Securing an information processing system at the application and system software layers is regarded as a necessary but incomplete defense against the cyber security threats. In this dissertation, an asynchronous serial transceiver that is capable of transmitting and receiving an auxiliary data stream concurrently with the primary data stream is described. The transceiver instantiates the auxiliary data stream by modulating the phase of the primary data without …


Polyone Smartphone, Joshua Zalmanowitz, Chi Nguyen, Gerome Cacho, Chris Lim Jun 2020

Polyone Smartphone, Joshua Zalmanowitz, Chi Nguyen, Gerome Cacho, Chris Lim

Electrical Engineering

The Poly One Smartphone is a student designed smartphone built to explore the implementation of 5G, provide a hardware solution to ensure personal information security and privacy, and provide longer battery life. The key features of this smartphone include but are not limited to a main cpu, some form of network connectivity in the form of Wi-fi or Cellular Data, calling functionality, a rechargeable battery that works with common power connection protocols, and compatibility with popular applications.


Design And Development Of Laboratory Single-Axis Pv Module Tracker, Helen A. Rice, Delaney Berger, Avishek Maitra Jun 2020

Design And Development Of Laboratory Single-Axis Pv Module Tracker, Helen A. Rice, Delaney Berger, Avishek Maitra

Electrical Engineering

Solar energy is an integral part of the renewable energy industry. Advanced solar farms actively track solar movement and update solar panel angles to maximize the system’s output power. Cal Poly boasts its own Solar Farm that features a single-axis tracking system. Single-axis tracking aims to get panels as close to perpendicular as possible given the panel arrangements and given the time of year. Single-axis tracking is a more robust measurement and tracking option. Single-axis tracking systems usually only have East-West panel arc movement, following the sun’s rotation. Dual-axis trackers have both East-West and North-South panel arc movements. Dual-axis systems …


Dc Treasure Box, Michael A. Derrenbacher Jun 2020

Dc Treasure Box, Michael A. Derrenbacher

Electrical Engineering

An all in one DC resource would enable electronics students to prototype circuits for labs and projects without the need for the lab equipment present on campus. The labs on campus can be physically far, closed, or overcrowded, preventing students from accessing the equipment. Roughly 75% of upper division electrical engineering students do not own power supplies, with even fewer students owning a source measurement unit (SMU). There is a significant need for a product capable of providing standard lab equipment functionality. The functionally this project provides are positive and negative DC power supplies, 4-Quadrant SMU, analog inputs and outputs, …


Wildland Fire Location Management System (Wflms), Robert G. Goldie, Jack A. Gallegos Jun 2020

Wildland Fire Location Management System (Wflms), Robert G. Goldie, Jack A. Gallegos

Electrical Engineering

Wildland firefighters work in complex, dangerous environments where effective communication is key to developing situational awareness. Currently, the only communication firefighters have is with Very High Frequency (VHF) 160 MHz band analog radios. While digital radio protocols could potentially allow location data and commands to be sent to field crews, the technology is primarily for voice communication. This project presents a new system that frees up voice channels and uses LoRa transceivers for robust communication. The system allows for emergency and location reports to be sent to a dispatcher via an airborne repeater. The entire system is software-defined, so it …


Raysun's Infrared Raisin Dryer, Lucas Kensinger, Saraith Aispuro, Joe Vanacore Jun 2020

Raysun's Infrared Raisin Dryer, Lucas Kensinger, Saraith Aispuro, Joe Vanacore

General Engineering

The RaySuns senior project team was tasked with lowering the drying costs of raisins for River Ranch Raisins. In doing so, we explored several options for cutting costs: utilizing automation and exploring new drying technologies were our primary focus. We eventually planned a modular infrared heating mechanism which would be easy to automate in future projects. After manufacturing and testing an infrared heating mechanism, it was found that infrared drying could significantly cut costs versus the previous natural gas fired dryer tunnels while leaving room for automation. The infrared dryer was also shown to have the potential to create high-quality …


Electrical Measurement Of Sram Cell Variation And Sensitivity To Singe-Event Upsets By Low-Energy Protons, James M. Cannon May 2020

Electrical Measurement Of Sram Cell Variation And Sensitivity To Singe-Event Upsets By Low-Energy Protons, James M. Cannon

Macalester Journal of Physics and Astronomy

With the rise of the transistor in the 1970s, electronics shifted from analog circuitry, where values are stored on a continuum, to digital, in which ones and zeros are the law of the land. Transistors, as a class circuit element, can be affected by radiation and cosmic rays which then cause temporary or permanent failures, depending on the specifics of the situation. On Earth, this poses little risk with all electronics shielded by the magnetosphere, however for space bound electronics, the risks from these extraterrestrial particles are not so negligible. The first step in designing a mission to be able …


Low-Cost Test And Characterization Platform For Memristors, Lyle Jones May 2020

Low-Cost Test And Characterization Platform For Memristors, Lyle Jones

Boise State University Theses and Dissertations

The electrical Testing and Characterization of the devices built under research conditions on silicon wafers, diced wafers, or package parts have hampered research since the beginning of integrated circuits. The challenges of performing electrical characterization on devices are to acquire useful and accurate data, the ease of use of the test platform, the portability of the test equipment, the ability to automate quickly, to allow modifications to the platform, the ability to change the configuration of the Device Under Test (DUT) or the Memristor Based Design (MBD), and to do this within budget. The devices that this research is focused …


Ensemble Malware Classification System Using Deep Neural Networks, Barath Narayanan Narayanan, Venkata Salini Priyamvada Davuluru Apr 2020

Ensemble Malware Classification System Using Deep Neural Networks, Barath Narayanan Narayanan, Venkata Salini Priyamvada Davuluru

Electrical and Computer Engineering Faculty Publications

With the advancement of technology, there is a growing need of classifying malware programs that could potentially harm any computer system and/or smaller devices. In this research, an ensemble classification system comprising convolutional and recurrent neural networks is proposed to distinguish malware programs. Microsoft's Malware Classification Challenge (BIG 2015) dataset with nine distinct classes is utilized for this study. This dataset contains an assembly file and a compiled file for each malware program. Compiled files are visualized as images and are classified using Convolutional Neural Networks (CNNs). Assembly files consist of machine language opcodes that are distinguished among classes using …


Dual-Axis Solar Tracker, Bryan Kennedy Jan 2020

Dual-Axis Solar Tracker, Bryan Kennedy

All Undergraduate Projects

Renewable energies, and fuels that are not fossil fuel-based, are one of the prolific topics of debate in modern society. With climate change now becoming a primary focus for scientists and innovators of today, one of the areas for the largest amount of potential and growth is that of the capturing and utilization of Solar Energy. This method involves using a mechanical system to track the progression of the sun as it traverses the sky throughout the day. A dual-axis solar tracker such as the one designed and built for this project, can follow the sun both azimuthally and in …


Ensemble Lung Segmentation System Using Deep Neural Networks, Redha A. Ali, Russell C. Hardie, Hussin K. Ragb Jan 2020

Ensemble Lung Segmentation System Using Deep Neural Networks, Redha A. Ali, Russell C. Hardie, Hussin K. Ragb

Electrical and Computer Engineering Faculty Publications

Lung segmentation is a significant step in developing computer-aided diagnosis (CAD) using Chest Radiographs (CRs). CRs are used for diagnosis of the 2019 novel coronavirus disease (COVID-19), lung cancer, tuberculosis, and pneumonia. Hence, developing a Computer-Aided Detection (CAD) system would provide a second opinion to help radiologists in the reading process, increase objectivity, and reduce the workload. In this paper, we present the implementation of our ensemble deep learning model for lung segmentation. This model is based on the original DeepLabV3+, which is the extended model of DeepLabV3. Our model utilizes various architectures as a backbone of DeepLabV3+, such as …


Corrections To ‘‘Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping’’, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel Jan 2020

Corrections To ‘‘Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping’’, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel

Electrical and Computer Engineering Faculty Publications

In the above article [1], Figure 2 was incorrect. Unfortunately, we mixed the color label of "CONV $\to $ BN $\to $ ReLu" and "Unpooling" in the CNN structure section of Figure 2. The color label of "CONV $\to $ BN $\to $ ReLu" should be orange while the color label of "Unpooling" should be green. Also, the word "Decoder" is misspelled. That same figure with the same error is also used for the graphic abstract. The corrected figure is given here. None of the sections in the figure is modified. The only change is in the color label of …


Design, Construction, And Characterization Of A Combined Mini-Co₂/Voc Sensor And Gas Chromatograph For Field Research, Rishi Basdeo, Michael Hampton Jan 2020

Design, Construction, And Characterization Of A Combined Mini-Co₂/Voc Sensor And Gas Chromatograph For Field Research, Rishi Basdeo, Michael Hampton

Digital Repository: Showcase of Undergraduate Research Excellence

No abstract provided.


Ev Charging Behavior Analysis Using Hybrid Intelligence For 5g Smart Grid, Yi Shen, Wei Fang, Feng Ye, Michel Kadoch Jan 2020

Ev Charging Behavior Analysis Using Hybrid Intelligence For 5g Smart Grid, Yi Shen, Wei Fang, Feng Ye, Michel Kadoch

Electrical and Computer Engineering Faculty Publications

With the development of the Internet of Things (IoT) and the widespread use of electric vehicles (EV), vehicle-to-grid (V2G) has sparked considerable discussion as an energy-management technology. Due to the inherently high maneuverability of EVs, V2G systems must provide on-demand service for EVs. Therefore, in this work, we propose a hybrid computing architecture based on fog and cloud with applications in 5G-based V2G networks. This architecture allows the bi-directional flow of power and information between schedulable EVs and smart grids (SGs) to improve the quality of service and cost-effectiveness of energy service providers. However, it is very important to select …


Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel Jan 2020

Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel

Electrical and Computer Engineering Faculty Publications

Rising global temperatures over the past decades is directly affecting glacier dynamics. To understand glacier fluctuations and document regional glacier-state trends, glacier-boundary detection is necessary. Debris-covered glacier (DCG) mapping, however, is notoriously difficult using conventional geospatial technology methods. Therefore, in this research for automated DCG mapping, we evaluate the utility of a convolutional neural network (CNN), which is a deep learning feed-forward neural network. The CNN inputs include Landsat satellite images, an Advanced Land Observation Satellite (ALOS) digital elevation model (DEM) and DEM-derived land-surface parameters. Our CNN based deep-learning approach named GlacierNet was designed by appropriately choosing the type, number …


Mitosisnet: End-To-End Mitotic Cell Detection By Multi-Task Learning, Md Zahangir Alom, Theus Aspiras, Tarek M. Taha, Tj Bowen, Vijayan K. Asari Jan 2020

Mitosisnet: End-To-End Mitotic Cell Detection By Multi-Task Learning, Md Zahangir Alom, Theus Aspiras, Tarek M. Taha, Tj Bowen, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Mitotic cell detection is one of the challenging problems in the field of computational pathology. Currently, mitotic cell detection and counting are one of the strongest prognostic markers for breast cancer diagnosis. The clinical visual inspection on histology slides is tedious, error prone, and time consuming for the pathologist. Thus, automatic mitotic cell detection approaches are highly demanded in clinical practice. In this paper, we propose an end-to-end multi-task learning system for mitosis detection from pathological images which is named"MitosisNet". MitosisNet consist of segmentation, detection, and classification models where the segmentation, and detection models are used for mitosis reference region …


Performance Enhancement And Characterization Of An Electromagnetic Railgun, Paul M. Gilles Dec 2019

Performance Enhancement And Characterization Of An Electromagnetic Railgun, Paul M. Gilles

Master's Theses

Collision with orbital debris poses a serious threat to spacecraft and astronauts. Hypervelocity impacts resulting from collisions mean that objects with a mass less than 1g can cause mission-ending damage to spacecraft. A means of shielding spacecraft against collisions is necessary. A means of testing candidate shielding methods for their efficacy in mitigating hypervelocity impacts is therefore also necessary. Cal Poly’s Electromagnetic Railgun was designed with the goal of creating a laboratory system capable of simulating hypervelocity (≥ 3 km/s) impacts. Due to several factors, the system was not previously capable of high-velocity (≥ 1 km/s) tests. A deficient projectile …


Residential Electricity Management And Protection System, Ejimonu Kosisochukwu Gabriel Aug 2019

Residential Electricity Management And Protection System, Ejimonu Kosisochukwu Gabriel

Journal of International Technology and Information Management

The Residential Electricity Monitoring System is an electricity meter connected to the Internet to provide real time data on the power system in your home. The REMS is designed to replace the distribution board allowing it to conduct a series of tests on the quality of the electricity supply to your home/facility and, within your home detect basic wiring faults and allow owners and service providers to identify potential problems with the electrical systems.

The electrical monitoring system finally puts proper electrical control into the hands of the home owner by providing him with the ability to control power distribution …


Characterization Of High Temperature Optocoupler For Power Electronic Systems, David Gonzalez May 2019

Characterization Of High Temperature Optocoupler For Power Electronic Systems, David Gonzalez

Electrical Engineering Undergraduate Honors Theses

High-temperature devices have been rapidly increas due to the implementation of new technologies like silicon carbide, high-temperature ceramic, and others. Functionality under elevated temperatures can reduce signal integrity reducing the reliability of power electronic systems. This study presents an ongoing research effort to develop a high-temperature package for optocouplers to operate at higher temperature compared with commercial devices. Low temperature co-fired ceramic (LTCC) was used as the substrate. Bare die commercial LED and photodetectors were attached to the substrate and tested for functionality. Preliminary results show enhanced performance at elevated temperatures compared to a commercial optocoupler device.


Designing A Robotic Platform For Investigating Swarm Robotics, Jonathan Gray Apr 2019

Designing A Robotic Platform For Investigating Swarm Robotics, Jonathan Gray

Senior Honors Theses

This paper documents the design and subsequent construction of a low-cost, flexible robotic platform for swarm robotics research, and the selection of appropriate swarm algorithms for the implementation of a swarm focused predominantly on target location. The design described herein is intended to allow for the construction of robots large enough to meaningfully interact with their environment while maintaining a low per-robot cost of materials and a low assembly time. The design process is separated into three stages: mechanical design, electrical design, and software design. All major design components are described in detail under the appropriate design section. The BOM …


Ent1201 Introduction To Electricity For Live Entertainment Syllabus, Miguel A. Valderrama Apr 2019

Ent1201 Introduction To Electricity For Live Entertainment Syllabus, Miguel A. Valderrama

Open Educational Resources

No abstract provided.


A State-Of-The-Art Survey On Deep Learning Theory And Architectures, Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari Mar 2019

A State-Of-The-Art Survey On Deep Learning Theory And Architectures, Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some new areas that present more opportunities. Different methods have been proposed based on different categories of learning, including supervised, semi-supervised, and un-supervised learning. Experimental results show state-of-the-art performance using deep learning when compared to traditional machine learning approaches in the fields of image processing, computer vision, speech recognition, machine translation, art, medical imaging, medical information processing, robotics and control, bioinformatics, natural language …


Development Of A Myoelectric Detection Circuit Platform For Computer Interface Applications, Nickolas Andrew Butler Mar 2019

Development Of A Myoelectric Detection Circuit Platform For Computer Interface Applications, Nickolas Andrew Butler

Master's Theses

Personal computers and portable electronics continue to rapidly advance and integrate into our lives as tools that facilitate efficient communication and interaction with the outside world. Now with a multitude of different devices available, personal computers are accessible to a wider audience than ever before. To continue to expand and reach new users, novel user interface technologies have been developed, such as touch input and gyroscopic motion, in which enhanced control fidelity can be achieved. For users with limited-to-no use of their hands, or for those who seek additional means to intuitively use and command a computer, novel sensory systems …


Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization, Theus Aspiras, Ruixu Liu, Vijayan K. Asari Jan 2019

Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization, Theus Aspiras, Ruixu Liu, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Given that there are numerous amounts of unlabeled data available for usage in training neural networks, it is desirable to implement a neural network architecture and training paradigm to maximize the ability of the latent space representation. Through multiple perspectives of the latent space using adversarial learning and autoencoding, data requirements can be reduced, which improves learning ability across domains. The entire goal of the proposed work is not to train exhaustively, but to train with multiperspectivity. We propose a new neural network architecture called Active Recall Network (ARN) for learning with less labels by optimizing the latent space. This …