Digital Commons Network^™

Trust Model Measurements For The Energy Grid Of Things, N. Sonali Fernando, John M. Acken, Robert Bass

Electrical and Computer Engineering Faculty Publications and Presentations

Information security is essential for the reliable operation of an Energy Grid of Things (EGoT). In addition to basic information security protocols as defined by published standards, there is a need for a monitoring function that measures the trustworthiness of the various actors participating in an EGoT. We describe in this paper the implementation and evaluation of a Distributed Trust Model that was developed specifically for monitoring communication within an EGoT. We then show how the model parameters are set using statistical measures for hypothesis testing.

Meso-Scale Seabed Quantification With Geoacoustic Inversion, Tim Sonnemann, Jan Dettmer, Charles W. Holland, Stan E. Dosso

Electrical and Computer Engineering Faculty Publications and Presentations

Abstract Knowledge of sub-seabed geoacoustic properties, for example depth dependent sound speed and porosity, is of importance for a variety of applications. Here, we present a semi-automated geoacoustic inversion method for autonomous underwater vehicle data that objectively adapts model inference to seabed structure. Through parallelized trans-dimensional Bayesian inference, we infer seabed properties along a 12 km survey track on the scale of about 10 cm and 50 m in the vertical and horizontal, respectively. The inferred seabed properties include sound speed, attenuation, density, and porosity as a function of depth from acoustic reflection coefficient data. Parameter uncertainties are quantified, and …

An Introduction To Nanomaterials For Nanopackaging, James E. Morris

Electrical and Computer Engineering Faculty Publications and Presentations

The multiple purposes of an electronics “package” include the provision of mechanical support to the silicon chip, for example, and protection from the environment, the delivery of power in and the facilitation of heat out, and the reliable input and output of information signals, whether electrical or optical. In the age of heterogeneous integration, this includes the internal conversion of signal modes between multiple technologies within the package, while maintaining the traditional requirement of reliable information transmission between packages, e.g., on a traditional circuit board. This article presents some selected examples of nanopackaging, i.e., the application of nanotechnologies, (nanoparticles, carbon …

Recent Progress And Challenges Of Implantable Biodegradable Biosensors, Fahmida Alam, Md Ashfaq Ahmed, Ahmed Hasnain Jalal, Ishrak Siddiquee, Rabeya Zinnat Adury, G M Mehedi Hossain, Nezih Pala

Electrical and Computer Engineering Faculty Publications and Presentations

Implantable biosensors have evolved to the cutting-edge technology of personalized health care and provide promise for future directions in precision medicine. This is the reason why these devices stand to revolutionize our approach to health and disease management and offer insights into our bodily functions in ways that have never been possible before. This review article tries to delve into the important developments, new materials, and multifarious applications of these biosensors, along with a frank discussion on the challenges that the devices will face in their clinical deployment. In addition, techniques that have been employed for the improvement of the …

Investigating Customer Churn In Banking: A Machine Learning Approach And Visualization App For Data Science And Management, Pahul Preet Singh, Fahim Islam Anik, Rahul Senapati, Arnav Sinha, Nazmus Sakib, Eklas Hossain

Electrical and Computer Engineering Faculty Publications and Presentations

Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and, after that, end their connection with the bank. Therefore, customer retention is essential in today’s extremely competitive banking market. Additionally, having a solid customer base helps attract new consumers by fostering confidence and a referral from a current clientele. These factors make reducing client attrition a crucial step that banks must pursue. In our research, we aim to examine bank data and forecast which users will most likely discontinue using the bank’s services and become paying customers. …

Source Level Of Wind-Generated Ambient Sound In The Oceana, N. Ross Chapman, Michael Ainslie, Martin Siderius

Electrical and Computer Engineering Faculty Publications and Presentations

Inference of source levels for ambient ocean sound from local wind at the sea surface requires an assumption about the nature of the sound source. Depending upon the assumptions made about the nature of the sound source, whether monopole or dipole distributions, the estimated source levels from different research groups are different by several decibels over the frequency band 10–350 Hz. This paper revisits the research issues of source level of local wind-generated sound and shows that the differences in estimated source levels can be understood through a simple analysis of the source assumptions.

Energy-Efficient Neuromorphic Architectures For Nuclear Radiation Detection Applications, Jorge I. Canales-Verdial, Jamison R. Wagner, Landon A. Schmucker, Mark Wetzel, Nathan J. Withers, Philippe Erol Proctor, Christof Teuscher, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

A comprehensive analysis and simulation of two memristor-based neuromorphic architectures for nuclear radiation detection is presented. Both scalable architectures retrofit a locally competitive algorithm to solve overcomplete sparse approximation problems by harnessing memristor crossbar execution of vector–matrix multiplications. The proposed systems demonstrate excellent accuracy and throughput while consuming minimal energy for radionuclide detection. To ensure that the simulation results of our proposed hardware are realistic, the memristor parameters are chosen from our own fabricated memristor devices. Based on these results, we conclude that memristor-based computing is the preeminent technology for a radiation detection platform.

Electron Trajectories And Critical Current In A Two-Dimensional Planar Magnetically Insulated Crossed-Field Gap, Xiaojun Zhu, Jack K. Wright, N. R. Sree Harsha, Jim Browning, Allen L. Garner

Electrical and Computer Engineering Faculty Publications and Presentations

The critical current in a one-dimensional (1D) crossed-field gap is defined by the transition from a cycloidal flow to a near-Brillouin (nB) state characterized by electron flow orthogonal to both the electric and magnetic fields and uniform virtual cathode formation. Motivated by recent studies on space-charge-limited current in non-magnetic diodes, we assess the meaning of critical current in a magentically insulated two-dimensional (2D) planar crossed-field geometry. Particle-in-cell (PIC) simulations demonstrate that binary behavior between a laminar and turbulent state does not occur in 2D because the virtual cathode is nonuniform. Rather than a distinct nB state above the critical current …

Implementation Profile: Modeling Environment (Doe-Psu-0000922-3), Sean Keene, Midrar Adham, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

This implementation profile provides the scope, background, and requirements necessary to implement a Modeling Environment (ME) to test a Distributed Energy Resource (DER) Management System (DERMS). A DERMS is used by an aggregator to dispatch large numbers of DERs in order to provide grid services to a Grid Operator. The ME addresses scalability issues inherent to Hardware-in-the-Loop DERMS simulation; a large number of assets are needed in order to observe effects on the grid from deployment and dispatch of DERs.

H-Nobs: Achieving Certified Fairness And Robustness In Distributed Learning On Heterogeneous Datasets, Guanqiang Zhou, Ping Xu, Yue Wang, Zhi Tian

Electrical and Computer Engineering Faculty Publications and Presentations

Fairness and robustness are two important goals in the design of modern distributed learning systems. Despite a few prior works attempting to achieve both fairness and robustness, some key aspects of this direction remain underexplored. In this paper, we try to answer three largely unnoticed and unaddressed questions that are of paramount significance to this topic: (i) What makes jointly satisfying fairness and robustness difficult? (ii) Is it possible to establish theoretical guarantee for the dual property of fairness and robustness? (iii) How much does fairness have to sacrifice at the expense of robustness being incorporated into the system? To …

Robust Denoising And Densenet Classification Framework For Plant Disease Detection, Kevin Zhou, Dimah Dera

Electrical and Computer Engineering Faculty Publications and Presentations

Plant disease is one of many obstacles encountered in the field of agriculture. Machine learning models have been used to classify and detect diseases among plants by analyzing and extracting features from plant images. However, a common problem for many models is that they are trained on clean laboratory images and do not exemplify real conditions where noise can be present. In addition, the emergence of adversarial noise that can mislead models into wrong predictions poses a severe challenge to developing preserved models against noisy environments. In this paper, we propose an end-to-end robust plant disease detection framework that combines …

Moisture-Controlled Triboelectrification During Coffee Grinding, Joshua Méndez Harper, Yong-Hyun Kim, Robin E. Bumbaugh, Connor S. Mcdonald, Christopher H. Hendon, Elana J. Cope, Leif E. Lindberg, Justin Pham, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

Triboelectrification is the physical process where materials acquire surface charge from frictional interactions at their interfaces.The magnitude of charge depends on the interfacial material composition and can be harnessed in emergent technologies for energy generation.

The mechanism of electrostatic accumulation is complex and is further obscured in granular materials where collisions are sufficiently energetic to cause fracturing. In this “fractoelectric” regime, crack initiation and propagation are thought to charge particles through transfer of electrons and/or ions at the hot crack interface.

Whether a material’s charging is dominated by tribo- or fractoelectrification, fracture-generated granular flows often comprise particles whose surface charge …

Analyzing Frequency Event Detection Algorithm Performance Using Different Denoising Methods, Hussain A. Alghamdi, Midrar Adham, Robert Bass

Electrical and Computer Engineering Faculty Publications and Presentations

Maintaining grid frequency at its nominal value is crucial for power system stability and supply-demand balance. Swift and accurate detection of frequency events is vital for providing primary frequency response support. Frequency event detection algorithms often rely on Phasor Measurement Unit data, which may contain noise. Implementing a denoising preprocessing step enhances detection precision and accuracy. In previous works, a frequency event detection algorithm based on wavelet transform was developed, which uses discrete wavelet transform (DWT) for denoising purposes. In this paper, several denoising techniques are considered as potential replacements for the current DWT method. This research investigates and compares …

Advancements In Adsorption Based Carbon Dioxide Capture Technologies- A Comprehensive Review, Arnob Das, Susmita Datta Peu, Md Sanowar Hossain, Md Mahafujul Alam Nahid, Fazlur Rahman Bin Karim, Hribhu Chowdhury, Mahmudul Hasan Porag, Debo Brata Paul Argha, Sabhasachi Saha, Abu Reza Md Towfiqul Islam

Electrical and Computer Engineering Faculty Publications and Presentations

The significant increase in energy consumption has facilitated a rapid increase in offensive greenhouse gas (GHG) and CO2 emissions. The consequences of such emissions are one of the most pivotal concerns of environmental scientists. To protect the environment, they are conducting the necessary research to protect the environment from the greenhouse effect. Among the different sources of CO2 emission, power plants contribute the largest amount of CO2 and as the number of power plants around the world is rising gradually due to increasing energy demand, the amount of CO2 emission is also rising subsequently. Researchers have developed different potential technologies …

Material And Physical Reservoir Computing For Beyond Cmos Electronics: Quo Vadis?, Christof Teuscher

Electrical and Computer Engineering Faculty Publications and Presentations

Traditional computing is based on an engineering approach that imposes logical states and a computational model upon a physical substrate. Physical or material computing, on the other hand, harnesses and exploits the inherent, naturally-occurring properties of a physical substrate to perform a computation. To do so, reservoir computing is often used as a computing paradigm. In this review and position paper, we take stock of where the field currently stands, delineate opportunities and challenges for future research, and outline steps on how to get material reservoir to the next level. The findings are relevant for beyond CMOS and beyond von …

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 …

Generation Of Dna Oligomers With Similar Chemical Kinetics Via In-Silico Optimization, Michael Tobiason, Bernard Yurke, William L. Hughes

Electrical and Computer Engineering Faculty Publications and Presentations

Networks of interacting DNA oligomers are useful for applications such as biomarker detection, targeted drug delivery, information storage, and photonic information processing. However, differences in the chemical kinetics of hybridization reactions, referred to as kinetic dispersion, can be problematic for some applications. Here, it is found that limiting unnecessary stretches of Watson-Crick base pairing, referred to as unnecessary duplexes, can yield exceptionally low kinetic dispersions. Hybridization kinetics can be affected by unnecessary intra-oligomer duplexes containing only 2 base-pairs, and such duplexes explain up to 94% of previously reported kinetic dispersion. As a general design rule, it is recommended that unnecessary …

Depth And Frequency Dependence Of Geoacoustic Properties On The New England Mud Patch From Reflection Coefficient Inversion, Jiang Yong-Min, Charles W. Holland, Stan E. Dosso, Jan Dettmer

Electrical and Computer Engineering Faculty Publications and Presentations

Muddy sediments cover significant portions of continental shelves, but their physical properties remain poorly understood compared to sandy sediments. This paper presents a generally applicable model for sediment-column structure and variability on the New England Mud Patch (NEMP), based on trans-dimensional Bayesian inversion of wide-angle, broadband reflection-coefficient data in this work and in two previously published reflection-coefficient inversions at different sites on the NEMP. The data considered here include higher frequencies and larger bandwidth and cover lower reflection grazing angles than the previous studies, hence, resulting in geoacoustic profiles with significantly better structural resolution and smaller uncertainties. The general sediment-column …

Qc-Odkla: Quantized And Communication-Censored Online Decentralized Kernel Learning Via Linearized Admm, Ping Xu, Yue Wang, Xiang Chen, Zhi Tian

Electrical and Computer Engineering Faculty Publications and Presentations

This article focuses on online kernel learning over a decentralized network. Each agent in the network receives online streaming data and collaboratively learns a globally optimal nonlinear prediction function in the reproducing kernel Hilbert space (RKHS). To overcome the curse of dimensionality issue in traditional online kernel learning, we utilize random feature (RF) mapping to convert the nonparametric kernel learning problem into a fixed-length parametric one in the RF space. We then propose a novel learning framework, named online decentralized kernel learning via linearized ADMM (ODKLA), to efficiently solve the online decentralized kernel learning problem. To enhance communication efficiency, we …

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 …

Experimental Evaluation Of Smart Electric Meters’ Resilience Under Cyber Security Attacks, Harsh Kumar, Oscar A. Alvarez, Sanjeev Kumar

Electrical and Computer Engineering Faculty Publications and Presentations

For the first time, commercial grade smart meters have been subjected to cyber security attacks to understand their operation and security resilience under different attack scenarios. Cyber security is a matter of top concern for utility companies installing smart meters for remote collection of power usage data from customer premises. Keeping power-usage data secure and to maintain system’s resiliency under cyber security attacks is very important. In Smart electric grids, the power usage data from smart meters are periodically reported to the utility company. Reporting and remote monitoring of power usage data requires the use of data network protocols, which …

Participation Of Electric Vehicle Aggregators In Wholesale Electricity Markets: Recent Works And Future Directions, Saeed Salimi Amiri, Fazlur Rahman Bin Karim, Pedro Cesar Lopes Gerum

Electrical and Computer Engineering Faculty Publications and Presentations

Electric Vehicles are key to reducing carbon emissions while bringing a revolution to the transportation sector. With the massive increase of EVs in road networks and the growing demand for charging services, the electric power grid faces enormous system reliability and operation stability challenges. Demand and supply disparities create inconsistency in the smooth delivery of electrical power. As a potential solution, EVs and their charging infrastructure can be aggregated to prevent the unwanted effects on power systems and also facilitate ancillary services to the power grid. When not need for transportation purposes, EVs can leverage their batteries for power grid …

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 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 …

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 …