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Articles 1 - 30 of 296
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Trust Model Measurements For The Energy Grid Of Things, N. Sonali Fernando, John M. Acken, Robert Bass
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
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
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 …
Source Level Of Wind-Generated Ambient Sound In The Oceana, N. Ross Chapman, Michael Ainslie, Martin Siderius
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
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.
Implementation Profile: Modeling Environment (Doe-Psu-0000922-3), Sean Keene, Midrar Adham, Robert B. Bass
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.
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
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
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 …
Quantum Algorithms For Unate And Binate Covering Problems With Application To Finite State Machine Minimization, Abdirahman Alasow, Marek Perkowski
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 …
Material And Physical Reservoir Computing For Beyond Cmos Electronics: Quo Vadis?, Christof Teuscher
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 …
Chemical Strategies To Mitigate Electrostatic Charging During Coffee Grinding, Joshua Méndez Harper, Christopher H. Hendon
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 …
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
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 …
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
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
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 …
Distributed Deep Learning Optimization Of Heat Equation Inverse Problem Solvers, Zhuowei Wang, Le Yang, Haoran Lin, Genping Zhao, Zixuan Liu, Xiaoyu Song
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 …
Lift Force Analysis For An Electrodynamic Wheel Maglev Vehicle, Colton W. Bruce, Jonathan Bird, Matthew K. Grubbs
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 …
An Examination Of The Stiffness Terms Needed To Model The Dynamics Of An Eddy Current Based Maglev Vehicle, Colton W. Bruce, Jonathan Bird
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
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
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
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 …
Trust Model System For The Energy Grid Of Things Network Communications, Narmada Sonali Fernando, Zhongkai Zheng, John M. Acken, Robert B. Bass
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
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
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
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
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 …
Implications Of Physical Fault Injections On Single Chip Motes, Sara Faour, Mališa Vučinić, Filip Maksimovic, David Burnett, Paul Muhlethaler, Thomas Watteyne, Kristofer Pister
Implications Of Physical Fault Injections On Single Chip Motes, Sara Faour, Mališa Vučinić, Filip Maksimovic, David Burnett, Paul Muhlethaler, Thomas Watteyne, Kristofer Pister
Electrical and Computer Engineering Faculty Publications and Presentations
Single-chip motes are wireless sensor nodes that integrate computation, communication, power and sensing on a single chip. We consider the security threats these novel devices are subject to when employed in safety-critical applications. Fault injection attacks are a prominent form of physical attacks that pose a threat to the normal and secure functioning of targeted devices, potentially compromising their intended behavior. These attacks have been studied mainly on commercial off-the-shelf devices which rely on external components such as crystal oscillators and passives. Such external components are absent from single-chip motes, resulting in a uniquely different attack surface compared to commercial …
Feasibility Of Tracking Human Kinematics With Simultaneous Localization And Mapping (Slam), Sepehr Laal, Paul Vasilyev, Sean Pearson, Mateo Aboy, James Mcnames
Feasibility Of Tracking Human Kinematics With Simultaneous Localization And Mapping (Slam), Sepehr Laal, Paul Vasilyev, Sean Pearson, Mateo Aboy, James Mcnames
Electrical and Computer Engineering Faculty Publications and Presentations
We evaluated a new wearable technology that fuses inertial sensors and cameras for tracking human kinematics. These devices use on-board simultaneous localization and mapping (SLAM) algorithms to localize the camera within the environment. Significance of this technology is in its potential to overcome many of the limitations of the other dominant technologies. Our results demonstrate this system often attains an estimated orientation error of less than 1o and a position error of less than 4 cm as compared to a robotic arm. This demonstrates that SLAM’s accuracy is adequate for many practical applications for tracking human kinematics.
Cocm: Co-Occurrence-Based Consistency Matching In Domain-Adaptive Segmentation, Siyu Zhu, Yingjie Tian, Fenfen Zhou, Kunlong Bai, Xiaoyu Song
Cocm: Co-Occurrence-Based Consistency Matching In Domain-Adaptive Segmentation, Siyu Zhu, Yingjie Tian, Fenfen Zhou, Kunlong Bai, Xiaoyu Song
Electrical and Computer Engineering Faculty Publications and Presentations
This paper focuses on domain adaptation in a semantic segmentation task. Traditional methods regard the source domain and the target domain as a whole, and the image matching is determined by random seeds, leading to a low degree of consistency matching between domains and interfering with the reduction in the domain gap. Therefore, we designed a two-step, three-level cascaded domain consistency matching strategy—co-occurrence-based consistency matching (COCM)—in which the two steps are: Step 1, in which we design a matching strategy from the perspective of category existence and filter the sub-image set with the highest degree of matching from the image …
Real-Time Joint Ocean Acoustics And Circulation Modeling In The 2021 New England Shelf Break Acoustics Experiment (L), Brendan J. Decourcy, Ying-Tsong Lin, Weifeng Gordon Zhang, Emma Reeves Ozanich, Natalie Kukshtel, Martin Siderius, Glen Gawarkiewicz, Jacob Forsyth
Real-Time Joint Ocean Acoustics And Circulation Modeling In The 2021 New England Shelf Break Acoustics Experiment (L), Brendan J. Decourcy, Ying-Tsong Lin, Weifeng Gordon Zhang, Emma Reeves Ozanich, Natalie Kukshtel, Martin Siderius, Glen Gawarkiewicz, Jacob Forsyth
Electrical and Computer Engineering Faculty Publications and Presentations
During the spring of 2021, a coordinated multi-vessel effort was organized to study physical oceanography, marine geology and biology, and acoustics on the northeast United States continental shelf, as part of the New England Shelf Break Acoustics (NESBA) experiment. One scientific goal was to establish a real-time numerical model aboard the research vessel with high spatial and temporal resolution to predict the oceanography and sound propagation within the NESBA study area. The real-time forecast model performance and challenges are reported in this letter without adjustment or re-simulation after the cruise. Future research directions for post-experiment studies are also suggested.
Selected Topics Of The Past Thirty Years In Ocean Acoustics, Michael D. Collins, Altan Turgut, Michael J. Buckingham, Peter Gerstoft, Martin Siderius
Selected Topics Of The Past Thirty Years In Ocean Acoustics, Michael D. Collins, Altan Turgut, Michael J. Buckingham, Peter Gerstoft, Martin Siderius
Electrical and Computer Engineering Faculty Publications and Presentations
This paper reviews some of the highlights of selected topics in ocean acoustics during the thirty years that have passed since the founding of the Journal of Theoretical and Computational Acoustics. Advances in computational methods and computers helped to make computational ocean acoustics a vibrant area of research during that period. The parabolic equation method provides an unrivaled combination of accuracy and efficiency for propagation problems in which the bathymetry, sound speed, and other environmental parameters vary in the horizontal directions. The extension of this approach to cases involving layers that support shear waves has been an active area …