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Electrical and Computer Engineering Faculty Publications

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Articles 121 - 150 of 691

Full-Text Articles in Electrical and Computer Engineering

Electromagnetic Pollution Alert: Microwave Radiation And Absorption In Human Organs And Tissues, Nantakan Wongkasem Feb 2021

Electromagnetic Pollution Alert: Microwave Radiation And Absorption In Human Organs And Tissues, Nantakan Wongkasem

Electrical and Computer Engineering Faculty Publications

Electromagnetic radiation from communication and electronic devices, networks, systems and base stations has drawn concern due to excessive global usage with increasing power and operating frequency level. Numerous previous researches only focus on how the radiation from certain frequency ranges of particular devices could harm specific human organs and tissues, resulting in distinct symptoms. In this research, electromagnetic propagation and properties in fourteen human organs and tissues were analyzed and investigated based on the organs and tissues’ electromagnetic and mechanical parameters, and chemical composition. Counting the organs and tissues as electromagnetic materials, their permittivity and conductivity, computed by a 4-Cole-Cole …

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An Ultrabroadband 3d Achromatic Metalens, Fatih Balli, Mansoor A. Sultan, Aytekin Ozdemir, J. Todd Hastings Jan 2021

An Ultrabroadband 3d Achromatic Metalens, Fatih Balli, Mansoor A. Sultan, Aytekin Ozdemir, J. Todd Hastings

Electrical and Computer Engineering Faculty Publications

We design and fabricate ultra-broadband achromatic metalenses operating from the visible into the short-wave infrared, 450–1700 nm, with diffraction-limited performance. A hybrid 3D architecture, which combines nanoholes with a phase plate, allows realization in low refractive index materials. As a result, two-photon lithography can be used for prototyping while molding can be used for mass production. Experimentally, a 0.27 numerical aperture (NA) metalens exhibits 60% average focusing efficiency and 6% maximum focal length error over the entire bandwidth. In addition, a 200 μm diameter, 0.04 NA metalens was used to demonstrate achromatic imaging over the same broad spectral range. These …

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Study Of Renewable Energy Penetration On A Benchmark Generation And Transmission System, Oluwaseun M. Akeyo, Aron Patrick, Dan M. Ionel Jan 2021

Study Of Renewable Energy Penetration On A Benchmark Generation And Transmission System, Oluwaseun M. Akeyo, Aron Patrick, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

Significant changes in conventional generator operation and transmission system planning will be required to accommodate increasing solar photovoltaic (PV) penetration. There is a limit to the maximum amount of solar that can be connected in a service area without the need for significant upgrades to the existing generation and transmission infrastructure. This study proposes a framework for analyzing the impact of increasing solar penetration on generation and transmission networks while considering the responses of conventional generators to changes in solar PV output power. Contrary to traditional approaches in which it is assumed that generation can always match demand, this framework …

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Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar, Nina M. Singer, Vijayan K. Asari Jan 2021

Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar, Nina M. Singer, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

We present DALES Objects, a large-scale instance segmentation benchmark dataset for aerial lidar. DALES Objects contains close to half a billion hand-labeled points, including semantic and instance segmentation labels. DALES Objects is an extension of the DALES (Varney et al., 2020) dataset, adding additional intensity and instance segmentation annotation. This paper provides an overview of the data collection, preprocessing, hand-labeling strategy, and final data format. We propose relevant evaluation metrics and provide insights into potential challenges when evaluating this benchmark dataset. Finally, we provide information about how researchers can access the dataset for their use at go.udayton.edu/dales3d.

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Optimal Onsite Microgrid Design For Net-Zero Energy Operation In Manufacturing Industry, Md Monirul Islam, Mostafizur Rahman, Farzin Heidari, Vinayaka Gude Jan 2021

Optimal Onsite Microgrid Design For Net-Zero Energy Operation In Manufacturing Industry, Md Monirul Islam, Mostafizur Rahman, Farzin Heidari, Vinayaka Gude

Electrical and Computer Engineering Faculty Publications

Developing an economic net-zero energy infrastructure for the manufacturing industry can play a critical role to achieve the goal of affordable, reliable, and sustainable clean energy paradigm for the next generation. However, it is quite challenging to develop such an infrastructure due to the uncertain demand of the manufacturing system, intermittent electricity generation from the renewable sources, time of use (TOU) pricing of electricity, and integrated operational planning for the long-term planning horizon. In this paper, a mixed-integer non-linear programming (MINLP) model is developed to economically design an onsite microgrid system considering the critical conditions and achieve a net-zero energy …

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Metal Discovery By Highly Sensitive Microwave Multi-Band Metamaterial-Inspired Sensors, Ghaleb Al-Duhni, Nantakan Wongkasem Jan 2021

Metal Discovery By Highly Sensitive Microwave Multi-Band Metamaterial-Inspired Sensors, Ghaleb Al-Duhni, Nantakan Wongkasem

Electrical and Computer Engineering Faculty Publications

A simple, compact, contactless, and high sensitivity metamaterial-inspired sensor has been developed to detect and classify precious transition metals in the S- and C-band regime, using reflection coefficients. A multi-band metamaterial, quadruple concentric circular split ring resonator, is specifically designed as a sensing enhancer, where the additional bands can effectively trigger the electromagnetic properties, as well as enhance the differentiation between the testing metal samples. The proposed sensor was tested on precious transition metals, silver, platinum, and gold thin slabs of various thicknesses, from 0.5 µm to 3 mm. Five resonances were established in the frequency range of 2–8 GHz. …

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Fifnet: A Convolutional Neural Network For Motion-Based Multiframe Super-Resolution Using Fusion Of Interpolated Frames, Hamed Elwarfalli, Russell C. Hardie Jan 2021

Fifnet: A Convolutional Neural Network For Motion-Based Multiframe Super-Resolution Using Fusion Of Interpolated Frames, Hamed Elwarfalli, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

We present a novel motion-based multiframe image super-resolution (SR) algorithm using a convolutional neural network (CNN) that fuses multiple interpolated input frames to produce an SR output. We refer to the proposed CNN and associated preprocessing as the Fusion of Interpolated Frames Network (FIFNET). We believe this is the first such CNN approach in the literature to perform motion-based multiframe SR by fusing multiple input frames in a single network. We study the FIFNET using translational interframe motion with both fixed and random frame shifts. The input to the network is a sequence of interpolated and aligned frames. One key …

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Ieee Access Special Section Editorial: Trends And Advances In Bio-Inspired Image-Based Deep Learning Methodologies And Applications, Peter Peer, Carlos M. Travieso-Gonzalez, Vijayan K. Asari, Malay Kishore Dutta Jan 2021

Ieee Access Special Section Editorial: Trends And Advances In Bio-Inspired Image-Based Deep Learning Methodologies And Applications, Peter Peer, Carlos M. Travieso-Gonzalez, Vijayan K. Asari, Malay Kishore Dutta

Electrical and Computer Engineering Faculty Publications

Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency. Designing technological solutions based on biological inspiration has become a cornerstone of research in a variety of areas ranging from control theory and optimization to computer vision, machine learning, and artificial intelligence. Especially in the latter few areas, biologically relevant solutions are becoming increasingly important as we look for new ways to make artificial systems more efficient, intelligent, and overall effective.

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Conditional Generative Adversarial Network Demosaicing Strategy For Division Of Focal Plane Polarimeters, Garrett Sargent, Bradley M. Ratliff, Vijayan K. Asari Dec 2020

Conditional Generative Adversarial Network Demosaicing Strategy For Division Of Focal Plane Polarimeters, Garrett Sargent, Bradley M. Ratliff, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Division of focal plane (DoFP), or integrated microgrid polarimeters, typically consist of a 2 × 2 mosaic of linear polarization filters overlaid upon a focal plane array sensor and obtain temporally synchronized polarized intensity measurements across a scene, similar in concept to a Bayer color filter array camera. However, the resulting estimated polarimetric images suffer a loss in resolution and can be plagued by aliasing due to the spatially-modulated microgrid measurement strategy. Demosaicing strategies have been proposed that attempt to minimize these effects, but result in some level of residual artifacts. In this work we propose a conditional generative adversarial …

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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 …

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Parameter Identification For Cells, Modules, Racks, And Battery For Utility-Scale Energy Storage Systems, Oluwaseun M. Akeyo, Vandana Rallabandi, Nicholas Jewell, Aron Patrick, Dan M. Ionel Nov 2020

Parameter Identification For Cells, Modules, Racks, And Battery For Utility-Scale Energy Storage Systems, Oluwaseun M. Akeyo, Vandana Rallabandi, Nicholas Jewell, Aron Patrick, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

The equivalent circuit model for utility-scale battery energy storage systems (BESS) is beneficial for multiple applications including performance evaluation, safety assessments, and the development of accurate models for simulation studies. This paper evaluates and compares the performance of utility-scale equivalent circuit models developed at multiple sub-component levels, i.e. at the rack, module, and cell levels. This type of modeling is used to demonstrate that the equivalent circuit model for a reference cell, module, or rack of a BESS can be scaled to represent the entire battery system provided that the battery management system (BMS) is active and functional. Contrary to …

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Cost Minimization Of Battery-Supercapacitor Hybrid Energy Storage For Hourly Dispatching Wind-Solar Hybrid Power System, Pranoy Roy, Jiangbiao He, Yuan Liao Nov 2020

Cost Minimization Of Battery-Supercapacitor Hybrid Energy Storage For Hourly Dispatching Wind-Solar Hybrid Power System, Pranoy Roy, Jiangbiao He, Yuan Liao

Electrical and Computer Engineering Faculty Publications

This study demonstrates a dispatching scheme of wind-solar hybrid power system (WSHPS) for a one-hour dispatching period for an entire day utilizing battery and supercapacitor hybrid energy storage subsystem (HESS). A frequency management approach is deployed to extend the longevity of the batteries through extensively utilizing the high energy density property of batteries and the high power density property of supercapacitors in the HESS framework. A low-pass filter (LPF) is employed to decouple the power between a battery and a supercapacitor (SC). The cost optimization of the HESS is computed based on the time constant of the LPF through extensive …

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Challenges And Opportunities In Near-Threshold Dnn Accelerators Around Timing Errors, Pramesh Pandey, Noel Daniel Gundi, Prabal Basu, Tahmoures Shabanian, Mitchell Craig Patrick, Koushik Chakraborty, Sanghamitra Roy Oct 2020

Challenges And Opportunities In Near-Threshold Dnn Accelerators Around Timing Errors, Pramesh Pandey, Noel Daniel Gundi, Prabal Basu, Tahmoures Shabanian, Mitchell Craig Patrick, Koushik Chakraborty, Sanghamitra Roy

Electrical and Computer Engineering Faculty Publications

AI evolution is accelerating and Deep Neural Network (DNN) inference accelerators are at the forefront of ad hoc architectures that are evolving to support the immense throughput required for AI computation. However, much more energy efficient design paradigms are inevitable to realize the complete potential of AI evolution and curtail energy consumption. The Near-Threshold Computing (NTC) design paradigm can serve as the best candidate for providing the required energy efficiency. However, NTC operation is plagued with ample performance and reliability concerns arising from the timing errors. In this paper, we dive deep into DNN architecture to uncover some unique challenges …

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Research And Simulation Of Dc Microgrid Three-Phase Ac-Dc Converter Control Strategy Based On Double Loop, Boning Wu, Zhiqiang Gao, Xuesong Zhou, Youjie Ma, Chenglong Wang Oct 2020

Research And Simulation Of Dc Microgrid Three-Phase Ac-Dc Converter Control Strategy Based On Double Loop, Boning Wu, Zhiqiang Gao, Xuesong Zhou, Youjie Ma, Chenglong Wang

Electrical and Computer Engineering Faculty Publications

The new voltage and current double loop control strategy is proposed to solve the DC microgrid bus voltage fluctuation caused by loads fluctuation, parameters perturbation and unbalanced three-phase power supply. Firstly, the dq axis mathematical model of three-phase AC-DC bidirectional converter in DC microgrid is analyzed and established, and then the controllers are designed according to the dq axis mathematical model. The outer loop is a voltage loop based on variable gain linear extended state observer (VGLESO) and sliding mode theory. VGLESO can not only effectively overcome the problem of peak output of traditional high-gain LESO in the initial stage …

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Titan: Uncovering The Paradigm Shift In Security Vulnerability At Near-Threshold Computing, Prabal Basu, Pramesh Pandey, Aatreyi Bal, Chidhambaranathan Rajamanikkam, Koushik Chakraborty, Sanghamitra Roy Oct 2020

Titan: Uncovering The Paradigm Shift In Security Vulnerability At Near-Threshold Computing, Prabal Basu, Pramesh Pandey, Aatreyi Bal, Chidhambaranathan Rajamanikkam, Koushik Chakraborty, Sanghamitra Roy

Electrical and Computer Engineering Faculty Publications

In this paper, we investigate the emerging security threats at Near-Threshold Computing (NTC) that are poised to jeopardize the trustworthy operation of future low-power electronic devices. A substantial research effort over the last decade has bolstered energy efficient operation in low-power computing. However, innovation in low-power security has received only marginal attention, thwarting a ubiquitous adoption of critical Internet of Things applications, such as wearable gadgets. Using a cross-layer methodology, we demonstrate that the timing fault vulnerability of a circuit rapidly increases as the operating conditions of the transistor devices shift from super-threshold to near-threshold values. Exploiting this vulnerability, we …

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Combined Numerical And Experimental Determination Of Ball Bearing Capacitances For Bearing Current Prediction, Peng Han, Greg Heins, Dean Patterson, Mark Theile, Dan M. Ionel Oct 2020

Combined Numerical And Experimental Determination Of Ball Bearing Capacitances For Bearing Current Prediction, Peng Han, Greg Heins, Dean Patterson, Mark Theile, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

High-frequency voltages across the steel ball bearings and the corresponding currents can cause premature bearing failures in electric machines driven by PWM converters. The bearing voltage, one of the most commonly-used failure indicators, depends heavily on the bearing capacitance. This paper presents a combined numerical and experimental approach for the calculation of ball bearing capacitances to address the uncertainty introduced by lubricant property, lubrication status and other metal parts, such as seals and ball retainers. Based on the obtained capacitance breakdown, the influences of temperature, speed and bearing load (radial, axial or combined) on the capacitance are studied. Measurements and …

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Design Optimization Of Coreless Axial-Flux Pm Machines With Litz Wire And Pcb Stator Windings, Murat G. Kesgin, Peng Han, Narges Taran, Damien Lawhorn, Donovin Lewis, Dan M. Ionel Oct 2020

Design Optimization Of Coreless Axial-Flux Pm Machines With Litz Wire And Pcb Stator Windings, Murat G. Kesgin, Peng Han, Narges Taran, Damien Lawhorn, Donovin Lewis, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

Coreless axial-flux permanent-magnet (AFPM) machines may be attractive options for high-speed and high-power-density applications due to the elimination of core losses. In order to make full use of the advantages offered by these machines and avoid excessive eddy current losses in windings, advanced technologies for winding conductors need to be employed to suppress the eddy effect, such as the Litz wire and printed circuit board (PCB). In this paper, the best practices for designing Litz wire/PCB windings are discussed and a brief survey of state of the art PCB winding technology is provided. Three coreless AFPM machines are mainly considered. …

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Robust Learning Via Ensemble Density Propagation In Deep Neural Networks, Giuseppina Carannante, Dimah Dera, Ghulam Rasool, Nidhal Carla Bouaynaya, Lyudmila Mihaylova Oct 2020

Robust Learning Via Ensemble Density Propagation In Deep Neural Networks, Giuseppina Carannante, Dimah Dera, Ghulam Rasool, Nidhal Carla Bouaynaya, Lyudmila Mihaylova

Electrical and Computer Engineering Faculty Publications

Learning in uncertain, noisy, or adversarial environments is a challenging task for deep neural networks (DNNs). We propose a new theoretically grounded and efficient approach for robust learning that builds upon Bayesian estimation and Variational Inference. We formulate the problem of density propagation through layers of a DNN and solve it using an Ensemble Density Propagation (EnDP) scheme. The EnDP approach allows us to propagate moments of the variational probability distribution across the layers of a Bayesian DNN, enabling the estimation of the mean and covariance of the predictive distribution at the output of the model. Our experiments using MNIST …

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A Hybrid Achromatic Metalens, Fatih Balli, Mansoor A. Sultan, Sarah K. Lami, J. Todd Hastings Aug 2020

A Hybrid Achromatic Metalens, Fatih Balli, Mansoor A. Sultan, Sarah K. Lami, J. Todd Hastings

Electrical and Computer Engineering Faculty Publications

Metalenses, ultra-thin optical elements that focus light using subwavelength structures, have been the subject of a number of recent investigations. Compared to their refractive counterparts, metalenses offer reduced size and weight, and new functionality such as polarization control. However, metalenses that correct chromatic aberration also suffer from markedly reduced focusing efficiency. Here we introduce a Hybrid Achromatic Metalens (HAML) that overcomes this trade-off and offers improved focusing efficiency over a broad wavelength range from 1000-1800 nm. HAMLs can be designed by combining recursive ray-tracing and simulated phase libraries rather than computationally intensive global search algorithms. Moreover, HAMLs can be fabricated …

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Greentpu: Predictive Design Paradigm For Improving Timing Error Resilience Of A Near-Threshold Tensor Processing Unit, Pramesh Pandey, Prabal Basu, Koushik Chakraborty, Sanghamitra Roy Jul 2020

Greentpu: Predictive Design Paradigm For Improving Timing Error Resilience Of A Near-Threshold Tensor Processing Unit, Pramesh Pandey, Prabal Basu, Koushik Chakraborty, Sanghamitra Roy

Electrical and Computer Engineering Faculty Publications

The emergence of hardware accelerators has brought about several orders of magnitude improvement in the speed of the deep neural-network (DNN) inference. Among such DNN accelerators, the Google tensor processing unit (TPU) has transpired to be the best-in-class, offering more than 15\times speedup over the contemporary GPUs. However, the rapid growth in several DNN workloads conspires to escalate the energy consumptions of the TPU-based data-centers. In order to restrict the energy consumption of TPUs, we propose GreenTPU - a low-power near-threshold (NTC) TPU design paradigm. To ensure a high inference accuracy at a low-voltage operation, GreenTPU identifies the patterns in …

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Experience Of Teaching Introduction To Electrical Engineering With An Online Platform, Junfei Li, Jaime Ramos-Salas, Cara Li Jul 2020

Experience Of Teaching Introduction To Electrical Engineering With An Online Platform, Junfei Li, Jaime Ramos-Salas, Cara Li

Electrical and Computer Engineering Faculty Publications

To engage engineering students in their field of studies, it is essential for the students to take major courses as early as possible. However, first year EE major students in our institution don’t have many options as almost all major courses need physics and math courses as prerequisites. For most of our students, the Introduction to Electrical Engineering is available to them as the only Electrical Engineering course during their first semester in college. It is offered to introduce the students to such topics as electrical circuits, digital logic, and robotics. In addition to learning fundamental topics, the students are …

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The Gridded Retarding Ion Drift Sensor For The Petitsat Cubesat Mission, Ryan L. Davidson, B. Oborn, E. F. Robertson, S. Noel, G. D. Earle, J. Green, J. Kramer Jun 2020

The Gridded Retarding Ion Drift Sensor For The Petitsat Cubesat Mission, Ryan L. Davidson, B. Oborn, E. F. Robertson, S. Noel, G. D. Earle, J. Green, J. Kramer

Electrical and Computer Engineering Faculty Publications

The Gridded Retarding Ion Drift Sensor (GRIDS) is a small sensor that will fly on the 6 U petitSat CubeSat. It is designed to measure the three-dimensional plasma drift velocity vector in the Earth’s ionosphere. The GRIDS also supplies information about the ion temperature, ion density, and the ratio of light to heavy ions present in the ionospheric plasma. It utilizes well-proven techniques that have been successfully validated by similar instruments on larger satellite missions while meeting CubeSat-compatible requirements for low mass, size, and power consumption. GRIDS performs the functions of a Retarding Potential Analyzer (RPA) and an Ion Drift …

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A Real-Time Attendance System Using Deep-Learning Face Recognition, Weidong Kuang, Abhijit Baul Jun 2020

A Real-Time Attendance System Using Deep-Learning Face Recognition, Weidong Kuang, Abhijit Baul

Electrical and Computer Engineering Faculty Publications

A real-time attendance system using deep learning face recognition abstract: Attendance check plays an important role in classroom management. Checking attendance by calling names or passing around a sign-in sheet is time-consuming, and especially the latter is open to easy fraud. This paper presents the detailed implementation of a real-time attendance check system based on face recognition and its results. To recognize a student’s face, the system must first take and save a picture of the student as a reference in a database. During the attendance check, the web camera takes face pictures for a student to be recognized, and …

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Effectiveness Of Using Myfpga Platform For Teaching Digital Logic, Junfei Li, Cara Li, Jae Sok Son, Weidong Kuang, Edgar Gil Jun 2020

Effectiveness Of Using Myfpga Platform For Teaching Digital Logic, Junfei Li, Cara Li, Jae Sok Son, Weidong Kuang, Edgar Gil

Electrical and Computer Engineering Faculty Publications

Accompanying electric circuits and computer programming, digital logic is deemed one of the most essential parts of any Electrical and Computer Engineering curriculum, so student success in the course is critical. Furthermore, research shows that the academic performance of students is heavily dependent upon student engagement, which is believed to increase with classroom strategies such as flipped-classrooms, cooperative learning, project-based learning, and virtual labs. The University of Texas Rio Grande Valley (UTRGV) is a Hispanic serving institution with distributive campuses, where many of the students work part-time. With consideration of the special needs of our students and the latest developments …

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Estimation Of Autoregressive Parameters From Noisy Observations Using Iterated Covariance Updates, Todd K. Moon, Jacob H. Gunther May 2020

Estimation Of Autoregressive Parameters From Noisy Observations Using Iterated Covariance Updates, Todd K. Moon, Jacob H. Gunther

Electrical and Computer Engineering Faculty Publications

Estimating the parameters of the autoregressive (AR) random process is a problem that has been well-studied. In many applications, only noisy measurements of AR process are available. The effect of the additive noise is that the system can be modeled as an AR model with colored noise, even when the measurement noise is white, where the correlation matrix depends on the AR parameters. Because of the correlation, it is expedient to compute using multiple stacked observations. Performing a weighted least-squares estimation of the AR parameters using an inverse covariance weighting can provide significantly better parameter estimates, with improvement increasing with …

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Hybrid Machine Learning Architecture For Automated Detection And Grading Of Retinal Images For Diabetic Retinopathy, Barath Narayanan, Barath Narayanan, Russell C. Hardie, Manawaduge Supun De Silva, Nathaniel K. Kueterman May 2020

Hybrid Machine Learning Architecture For Automated Detection And Grading Of Retinal Images For Diabetic Retinopathy, Barath Narayanan, Barath Narayanan, Russell C. Hardie, Manawaduge Supun De Silva, Nathaniel K. Kueterman

Electrical and Computer Engineering Faculty Publications

Purpose: Diabetic retinopathy is the leading cause of blindness, affecting over 93 million people. An automated clinical retinal screening process would be highly beneficial and provide a valuable second opinion for doctors worldwide. A computer-aided system to detect and grade the retinal images would enhance the workflow of endocrinologists. Approach: For this research, we make use of a publicly available dataset comprised of 3662 images. We present a hybrid machine learning architecture to detect and grade the level of diabetic retinopathy (DR) severity. We also present and compare simple transfer learning-based approaches using established networks such as AlexNet, VGG16, ResNet, …

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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 …

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Symmetry Versus Balance In Balancing Networks For Dipolar Antennas, James Mclean, Heinrich D. Foltz Apr 2020

Symmetry Versus Balance In Balancing Networks For Dipolar Antennas, James Mclean, Heinrich D. Foltz

Electrical and Computer Engineering Faculty Publications

Imperfect balancing networks (baluns) have been identified as a source of error in emission and site attenuation measurements. For this reason performance tests have been developed to characterize the symmetry of baluns. We draw a distinction between symmetry and balance as they relate to baluns and describe both quantitatively in terms of 3-port network parameters. It is shown that a symmetric balun alone does not necessarily eliminate common-mode (CM) current on the feed transmission line. Common-mode current on the feed transmission line is minimized by use of a current balun. However, for a given implementation such as a transmissionline transformer, …

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Reducing Road Wear While Ensuring Comfort And Charging Constraints For Dynamically Charged Passenger Vehicles Through Noise-Shaped Path Variations, Clint Jay Ferrin, Randall Christensen Mar 2020

Reducing Road Wear While Ensuring Comfort And Charging Constraints For Dynamically Charged Passenger Vehicles Through Noise-Shaped Path Variations, Clint Jay Ferrin, Randall Christensen

Electrical and Computer Engineering Faculty Publications

Dynamically charged vehicles suffer from power loss during wireless power transfer due to receiver and transmitter coil misalignment while driving. Autonomous, dynamically charged vehicles can maximize wireless power transfer by minimizing the misalignment, but the repeated high-precision driving increases road wear. To avoid unnecessary road wear and rutting, a noise shaping filter is proposed that adds variability to a vehicle's trajectory that complies with passenger acceleration and position constraints. However, introducing variability into an optimal charging path also risks depleting battery life prior to destination arrival. Therefore, a path planner is proposed that guarantees average charge within a specified probability …

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A Compendium Of Single Cell Analysis In Aging And Disease, Uday Chintapula, Samir M. Iqbal, Young-Tae Kim Mar 2020

A Compendium Of Single Cell Analysis In Aging And Disease, Uday Chintapula, Samir M. Iqbal, Young-Tae Kim

Electrical and Computer Engineering Faculty Publications

Cell is the fundamental structural and functional unit of complex multicellular organisms. Conventional methods which involve average analysis of cells in bulk populations can undermine physiologically significant cell populations, whereas analysis of cells at a single cell level may reveal unique biomarkers and other mechanisms that govern the genotype and phenotype in various physiological processes in presumed homogenous cell populations. Cellular abnormalities such as irregularities in cellular mechanisms have been linked to human aging and other major diseases including neurodegenerative, vascular, autoimmune, and cancer. Aging is a functional decline associated with various diseases in an organism, majorly arising from cellular …

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