Engineering Commons^™

Quantum Algorithms For Unate And Binate Covering Problems With Application To Finite State Machine Minimization, Abdirahman Alasow, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Covering problems find applications in many areas of computer science and engineering, such that numerous combinatorial problems can be formulated as covering problems. Combinatorial optimization problems are generally NPhard problems that require an extensive search to find the optimal solution. Exploiting the benefits of quantum computing, we present a quantum oracle design for covering problems, taking advantage of Grover’s search algorithm to achieve quadratic speedup. This paper also discusses applications of the quantum counter in unate covering problems and binate covering problems with some important practical applications, such as finding prime implicants of a Boolean function, implication graphs, and minimization …

Chemical Strategies To Mitigate Electrostatic Charging During Coffee Grinding, Joshua Méndez Harper, Christopher H. Hendon

Electrical and Computer Engineering Faculty Publications and Presentations

The process of grinding coffee generates particles with high levels of electrostatic charge, causing a number of detrimental effects including clumping, particle dispersal, and spark discharge. At the brewing level, electrostatic aggregation between particles affects liquid-solid accessibility, leading to variable extraction quality. In this study, we quantify the effectiveness of four charge mitigation strategies. Our data suggests that adding small amounts of water to whole beans pre-grinding, or bombarding the grounds with ions produced from a high-voltage ionizer, are capable of de-electrifying the granular flows. While these techniques helped reduce visible mess, only the static reduction through water inclusion was …

Quantitative Gait And Balance Outcomes For Ataxia Trials: Consensus Recommendations By The Ataxia Global Initiative Working Group On Digital-Motor Biomarkers, Winfried Ilg, Sarah Milne, Tanja Schmitz-Hübsch, Lisa Alcock, Lukas Beichert, Enrico Bertini, Helen Dawes, Christopher M. Gomez, James Mcnames, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

With disease-modifying drugs on the horizon for degenerative ataxias, ecologically valid, finely granulated, digital health measures are highly warranted to augment clinical and patient-reported outcome measures. Gait and balance disturbances most often present as the first signs of degenerative cerebellar ataxia and are the most reported disabling features in disease progression. Thus, digital gait and balance measures constitute promising and relevant performance outcomes for clinical trials.

This narrative review with embedded consensus will describe evidence for the sensitivity of digital gait and balance measures for evaluating ataxia severity and progression, propose a consensus protocol for establishing gait and balance metrics …

Optimally Distributed Receiver Placements Versus An Environmentally Aware Source: New England Shelf Break Acoustics Signals And Noise Experiment, William K. Stevens, Martin Siderius, Matthew J. Carrier, Drew Wendeborn

Electrical and Computer Engineering Faculty Publications and Presentations

This article describes the results of the Spring of 2021 New England Shelf Break Acoustics (NESBA) Signals and Noise experiment as they pertain to the optimization of a field of passive receivers versus an environmentally aware source with end-state goals. A discrete optimization has been designed and used to demonstrate providing an acoustic system operator with actionable guidance relating to optimally distributed receiver locations and depths and likely mean source detection times and associated uncertainties as a function of source and receiver levels of environmental awareness. The uncertainties considered here are those due to the imperfect spatial and temporal sensing …

Modeling And Validating Temporal Rules With Semantic Petri Net For Digital Twins, Han Liu, Xiaoyu Song, Ge Gao, Hehua Zhang, Yu-Shen Liu, Ming Gu

Electrical and Computer Engineering Faculty Publications and Presentations

Semantic rule checking on RDFS/OWL data has been widely used in the construction industry. At present, semantic rule checking is mainly performed on static models. There are still challenges in integrating temporal models and semantic models for combined rule checking. In this paper, Semantic Petri-Net (SPN) is proposed as a novel temporal modeling and validating method, which implements the states and transitions of the Colored Petri-Net directly based on RDFS and SPARQL, and realizes two-way sharing of knowledge between domain semantic webs and temporal models in the runtime. Several cases are provided to demonstrate the possible applications in digital twins …

Lift Force Analysis For An Electrodynamic Wheel Maglev Vehicle, Colton W. Bruce, Jonathan Bird, Matthew K. Grubbs

Electrical and Computer Engineering Faculty Publications and Presentations

This paper used an analytic based 3-D second order vector potential model to study the vertical dynamic force ripple and dynamic airgap height change when using a one pole-pair electrodynamic wheel (EDW) maglev vehicle. A one-pole pair EDW creates the lowest lift specific power; however transient finite element analysis (FEA) also shows that the one pole-pair EDW will create a large oscillating vertical force when maintaining a static airgap height. A dynamically coupled eddy current model was used to confirm that when the airgap length is allowed to change with time then an increase in vertical airgap creates a large …

Distributed Deep Learning Optimization Of Heat Equation Inverse Problem Solvers, Zhuowei Wang, Le Yang, Haoran Lin, Genping Zhao, Zixuan Liu, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

The inversion problem of partial differential equation plays a crucial role in cyber-physical systems applications. This paper presents a novel deep learning optimization approach to constructing a solver of heat equation inversion. To improve the computational efficiency in large-scale industrial applications, data and model parallelisms are incorporated on a platform of multiple GPUs. The advanced Ring-AllReduce architecture is harnessed to achieve an acceleration ratio of 3.46. Then a new multi-GPUs distributed optimization method GradReduce is proposed based on Ring-AllReduce architecture. This method optimizes the original data communication mechanism based on mechanical time and frequency by introducing the gradient transmission scheme …

Residual Vulnerabilities To Power Side Channel Attacks Of Lightweight Ciphers Cryptography Competition Finalists, Aurelien Mozipo, John M. Acken

Electrical and Computer Engineering Faculty Publications and Presentations

The protection of communications between Internet of Things (IoT) devices is of great concern because the information exchanged contains vital sensitive data. Malicious agents seek to exploit those data to extract secret information about the owners or the system. Power side channel attacks are of great concern on these devices because their power consumption unintentionally leaks information correlatable to the device's secret data. Several studies have demonstrated the effectiveness of authenticated encryption with advanced data, in protecting communications with these devices. A comprehensive evaluation of the seven (out of 10) algorithm finalists of the National Institute of Standards and Technology …

An Examination Of The Stiffness Terms Needed To Model The Dynamics Of An Eddy Current Based Maglev Vehicle, Colton W. Bruce, Jonathan Bird

Electrical and Computer Engineering Faculty Publications and Presentations

This paper re-examines the basis for each eddy current stiffness term computed from prior published steady-state eddy current models. The paper corrects prior analysis work by confirming, through the use of 2-D and 3-D dynamic finite element analysis modelling, that when a magnetic source is moving over an infinite-wide and infinite-long conductive sheet guideway the steady-state lateral and translational stiffness terms will be zero and only the vertical coupled stiffness terms need to be modelled. Using these observations, a much simplified 6 degrees-of-freedom (DoF) linearized eddy current dynamic force model can be used to compute the steady-state force changes in …

A Pwm Method For Reducing Dv/Dt And Switching Losses In Two-Stage Power Converters, Mahima Gupta, Abhijeet Prem

Electrical and Computer Engineering Faculty Publications and Presentations

Today's semiconductor devices are accompanied by high switching frequencies (> kilo-hertz) and small transition times (< micro-seconds). Such fast transition times are accompanied by undesirable effects such as voltage overshoots at the load terminals, ground leakage currents, wide-band electromagnetic noise, etc. With the advent of wide band-gap devices, several applications are moving towards higher switching frequency operation with at-least an order of magnitude reduction in transition times. While these characteristics are considered necessary to break the next-generation barriers in power density, efficiency and applicability, the undesirable effects due to faster transitions are expected to present obstacles. This work proposes a PWM approach to modify the shape of the switching voltages to overcome the disadvantages of the fast transition times without any increase in switching losses. In fact, several of the switching transitions feature ZVS operation, resulting in reduced switching losses. The paper discusses the analytical details of the approach using a simple DC-DC boost-buck converter and extends it to a DC to three-phase AC converter using the principles of space vector modulation. The paper presents detailed simulation and comparative results in terms of voltage over-shoots over long cables, loss calculations and electromagnetic noise. Results from a laboratory-scale working prototype confirm the benefits of the proposed approach in terms of EMI and loss reduction.

When Less Is More: How Increasing The Complexity Of Machine Learning Strategies For Geothermal Energy Assessments May Not Lead Toward Better Estimates, Stanley P. Mordensky, John Lipor, Jacob Deangelo, Erick R. Burns, Cary R. Lindsey

Electrical and Computer Engineering Faculty Publications and Presentations

Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates.

Our study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. We present and compare nine favorability maps for geothermal resources in the …

The Networked Nitrous Node: A Low-Power Field-Deployable Cots-Based N2o Gas Sensor Platform, Ronaldo Leon, Wenyu Bi, Eyal Eynis, Travis Johnson, Wei Yan, David C. Burnett, John M. Acken

Electrical and Computer Engineering Faculty Publications and Presentations

We present a wireless nitrous oxide (N 2 O) gas sensor system consisting of a commercial high-current infrared N 2 O sensor wrapped in a “smart” sensor framework to make it suitable for battery-powered deployment. This framework consists of wireless mesh networking, data storage, additional environmental sensors, and a gas sensor power control circuit managed by a central microcontroller. The N 2 O sensor is the first order consumer of power and sampling N 2 O at approximately ten minute intervals yields an estimated system lifetime of 63 days when using four 18650 Li-ion batteries. The node stores data locally …

A Novel Deep Learning, Camera, And Sensorbased System For Enforcing Hand Hygiene Compliance In Healthcare Facilities, Samyak Shrimali, Christof Teuscher

Electrical and Computer Engineering Faculty Publications and Presentations

Hospital-acquired infections are a major cause of death worldwide, and poor hand hygiene compliance is a primary reason for their spread. This paper proposes an artificial intelligence, microcontroller, and sensor-based system that monitors and improves staff hand hygiene compliance at various critical points in a hospital. The system uses a Convolutional Neural Network (CNN) to detect and track if staff have followed the WHO hand rub/hand wash guidelines at alcohol dispensers, hospital sinks, and patient beds. The system also uses RFID tags, vibration motors, LEDs, and a central server to identify staff, alert them of their cleaning requirements, monitor their …

Detecting Fast Frequency Events In Power System: Development And Comparison Of Two Methods, Hussain A. Alghamdi, Midrar Adham, Umar Farooq, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

In power systems, frequency deviation from nominal value can occur due to reasons such as loss of generation, loss of load, or major faults in the grid. Such frequency fluctuations can lead to serious subsequent outages and damages to both end-user and utility equipment. Therefore, a proper frequency deviation detection methodology must be in place to effectively identify frequency events in a timely manner. This manuscript provides a comparative analysis between two frequency deviation detection algorithms. One is based on signal processing and statistical analysis. The other is a regression-based algorithm. Both of these algorithms have multiple adjustable parameters, making …

Trust Model System For The Energy Grid Of Things Network Communications, Narmada Sonali Fernando, Zhongkai Zheng, John M. Acken, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

Network communication is crucial in the Energy Grid of Things (EGoT). Without a network connection, the energy grid becomes just a power grid where the energy resources are available to the customer uni-directionally. A mechanism to analyze and optimize the energy usage of the grid can only happen through a medium, a communications network, that enables information exchange between the grid participants and the service provider. Security implementers of EGoT network communication take extraordinary measures to ensure the safety of the energy grid, a critical infrastructure, as well as the safety and privacy of the grid participants. With the dynamic …

Quantum Algorithm For Mining Frequent Patterns For Association Rule Mining, Abdirahman Alasow, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Maximum frequent pattern generation from a large database of transactions and items for association rule mining is an important research topic in data mining. Association rule mining aims to discover interesting correlations, frequent patterns, associations, or causal structures between items hidden in a large database. By exploiting quantum computing, we propose an efficient quantum search algorithm design to discover the maximum frequent patterns. We modified Grover’s search algorithm so that a subspace of arbitrary symmetric states is used instead of the whole search space. We presented a novel quantum oracle design that employs a quantum counter to count the maximum …

Gait And Turning Characteristics From Daily Life Increase Ability To Predict Future Falls In People With Parkinson’S Disease, Vrutangkumar Shah, Adam Jagodinsky, James Mcnames, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

Objectives: To investigate if digital measures of gait (walking and turning) collected passively over a week of daily activities in people with Parkinson’s disease (PD) increases the discriminative ability to predict future falls compared to fall history alone. Methods: We recruited 34 individuals with PD (17 with history of falls and 17 non-fallers), age: 68 ± 6 years, MDS-UPDRS III ON: 31 ± 9. Participants were classified as fallers (at least one fall) or non-fallers based on self-reported falls in past 6 months. Eighty digital measures of gait were derived from 3 inertial sensors (Opal® V2 System) placed on the …

A Representation For Many Player Generalized Divide The Dollar Games, Garrison Greenwood, Daniel Ashlock

Electrical and Computer Engineering Faculty Publications and Presentations

Divide the dollar is a simplified version of a two player bargaining problem game devised by John Nash. The generalized divide the dollar game has n > 2 players. Evolutionary algorithms can be used to evolve individual players for this generalized game but representation—i.e., a genome plus a move or search operator(s)—must be carefully chosen since it affects the search process. This paper proposes an entirely new representation called a demand matrix. Each individual in the evolving population now represents a collection of n players rather than just an individual player. Players use previous outcomes to decide their choices (bids) in …

Opal Actigraphy (Activity And Sleep) Measures Compared To Actigraph: A Validation Study, Vrutangkumar Shah, Barbara H. Brumbach, Sean Pearson, Paul Vasilyev, James Mcnames, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

Physical activity and sleep monitoring in daily life provide vital information to track health status and physical fitness. The aim of this study was to establish concurrent validity for the new Opal Actigraphy solution in relation to the widely used ActiGraph GT9X for measuring physical activity from accelerometry epic counts (sedentary to vigorous levels) and sleep periods in daily life. Twenty participants (age 56 + 22 years) wore two wearable devices on each wrist for 7 days and nights, recording 3-D accelerations at 30 Hz. Bland–Altman plots and intraclass correlation coefficients (ICCs) assessed validity (agreement) and test–retest reliability between ActiGraph …