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2022

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Articles 74041 - 74070 of 74074

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Chimeranet: U-Net For Hair Detection In Dermoscopic Skin Lesion Images, Norsang Lama, Reda Kasmi, Jason R. Hagerty, R. Joe Stanley, Reagan Harris Young, Jessica Miinch, Januka Nepal, Anand Nambisan, William V. Stoecker Jan 2022

Chimeranet: U-Net For Hair Detection In Dermoscopic Skin Lesion Images, Norsang Lama, Reda Kasmi, Jason R. Hagerty, R. Joe Stanley, Reagan Harris Young, Jessica Miinch, Januka Nepal, Anand Nambisan, William V. Stoecker

Electrical and Computer Engineering Faculty Research & Creative Works

Hair and ruler mark structures in dermoscopic images are an obstacle preventing accurate image segmentation and detection of critical network features. Recognition and removal of hairs from images can be challenging, especially for hairs that are thin, overlapping, faded, or of similar color as skin or overlaid on a textured lesion. This paper proposes a novel deep learning (DL) technique to detect hair and ruler marks in skin lesion images. Our proposed ChimeraNet is an encoder-decoder architecture that employs pretrained EfficientNet in the encoder and squeeze-and-excitation residual (SERes) structures in the decoder. We applied this approach at multiple image sizes …

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A Dnn-Ensemble Method For Error Reduction And Training Data Selection In Dnn Based Modeling, Ling Zhang, Da Li, Jiayi He, Bhyrav Mutnury, Bo Pu, Xiao Ding Cai, Chulsoon Hwang, Jun Fan, James L. Drewniak, Er Ping Li Jan 2022

A Dnn-Ensemble Method For Error Reduction And Training Data Selection In Dnn Based Modeling, Ling Zhang, Da Li, Jiayi He, Bhyrav Mutnury, Bo Pu, Xiao Ding Cai, Chulsoon Hwang, Jun Fan, James L. Drewniak, Er Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

Deep neural networks (DNNs) have been widely adopted in modeling electromagnetic compatibility (EMC) problems, but the training data acquisition is usually time-consuming through various simulators. This paper presents a powerful approach using an ensemble of DNN s to effectively reduce the training data size in DNN-based modeling problems. A batch of training data with the largest uncertainties is selected using active learning through the variance among the ensemble of DNNs. Subsequently, a greedy sampling algorithm is applied to select a data subset using diversity. Thus, the proposed method can achieve both uncertainty and diversity in data selection. By averaging the …

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Peec-Based On-Chip Pdn Impedance Modeling Using Layered Green's Function, Chaofeng Li, Biyao Zhao, Bo Pu, Xu Wang, Donghyun Kim, Jun Fan Jan 2022

Peec-Based On-Chip Pdn Impedance Modeling Using Layered Green's Function, Chaofeng Li, Biyao Zhao, Bo Pu, Xu Wang, Donghyun Kim, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents an impedance model of on-chip power distribution network (PDN), which is an efficient criterion for estimating simultaneous switching noises (SSNs) on 3-D integrated circuit (IC). The impedance of on-chip PDN, including the effect of silicon substrate, is accurately modeled based on partial element equivalent circuit (PEEC) and layered Green's function (LGF). The equivalent circuit model of PDN is extracted based on the physical dimensions and electrical material characteristic of PDN at first. And then the LGF is used to consider the effect of silicon substrate for improving the accuracy of on-chip PDN impedance model. The effectiveness of …

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A Methodical Approach For Pcb Pdn Decoupling Minimizing Overdesign With Genetic Algorithm Optimization, F. De Paulis, Y. Ding, M. Cocchini, Chulsoon Hwang, S. Connor, M. Doyle, S. Scearce, W. D. Becker, Albert E. Ruehli, James L. Drewniak Jan 2022

A Methodical Approach For Pcb Pdn Decoupling Minimizing Overdesign With Genetic Algorithm Optimization, F. De Paulis, Y. Ding, M. Cocchini, Chulsoon Hwang, S. Connor, M. Doyle, S. Scearce, W. D. Becker, Albert E. Ruehli, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

An optimization routine is applied for the decoupling capacitor placement on Power Distribution Networks to identify the limit beyond which the placement of additional decaps is no longer effective, thus leading to wasting layout area and components, and to a cost increase. A specific test example from a real design is used together with the required target impedance and frequency band of interest for the PDN design. The effectiveness of the decap placement while selecting different layers of the stack-up, and while moving the upper limit of the PDN design band is analyzed. Such analysis leads to helpful insights based …

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Incremental Cluster Validity Index-Guided Online Learning For Performance And Robustness To Presentation Order, Leonardo Enzo Brito Da Silva, Nagasharath Rayapati, Donald C. Wunsch Jan 2022

Incremental Cluster Validity Index-Guided Online Learning For Performance And Robustness To Presentation Order, Leonardo Enzo Brito Da Silva, Nagasharath Rayapati, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In streaming data applications, the incoming samples are processed and discarded, and therefore, intelligent decision-making is crucial for the performance of lifelong learning systems. In addition, the order in which the samples arrive may heavily affect the performance of incremental learners. The recently introduced incremental cluster validity indices (iCVIs) provide valuable aid in addressing such class of problems. Their primary use case has been cluster quality monitoring; nonetheless, they have been recently integrated in a streaming clustering method. In this context, the work presented, here, introduces the first adaptive resonance theory (ART)-based model that uses iCVIs for unsupervised and semi-supervised …

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Concurrent Learning-Based Neuro-Adaptive Robust Tracking Control Of Wheeled Mobile Robot: An Event-Triggered Design, Krishanu Nath, Manas Kumar Bera, Sarangapani Jagannathan Jan 2022

Concurrent Learning-Based Neuro-Adaptive Robust Tracking Control Of Wheeled Mobile Robot: An Event-Triggered Design, Krishanu Nath, Manas Kumar Bera, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an event-based neuro-adaptive robust tracking controller for a perturbed and networked differential drive mobile robot (DMR) is designed with concurrent learning. A radial basis function neural network, which approximates an unknown perturbation, is used to design an adaptive sliding mode controller (SMC). The RBFNN weights and SMC parameters are estimated online using an adaptive tuning law to ensure performance with reduced chattering. To improve the convergence of RBFNN weight estimation error, a concurrent learning-based adaptive law is derived, which uses measured online and recorded data. Further, a suitable triggering condition is designed to achieve a reduced number …

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An Energy-Efficient Internet Of Things Relaying System For Delay-Constrained Applications, Abdullah M. Almasoud, Ahmad Alsharoa, Daji Qiao, Ahmed E. Kamal Jan 2022

An Energy-Efficient Internet Of Things Relaying System For Delay-Constrained Applications, Abdullah M. Almasoud, Ahmad Alsharoa, Daji Qiao, Ahmed E. Kamal

Electrical and Computer Engineering Faculty Research & Creative Works

The emerging Internet-of-things (IoT) systems contain a large number of small wireless devices with limited energy, communication, and computational capabilities. In such systems, a helping station located between the IoT devices and backhaul servers can be deployed to broadcast the IoT devices to the backhaul networks. This paper investigates a hybrid energy-efficient framework using multiple energy harvested relays with data buffering capabilities. The relays are powered by a hybrid energy supply consisting of a traditional electric grid and renewable energy grid. We propose an energy efficient novel approach aiming to support the wireless uplink transmission from IoT devices to backhaul …

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Pulsed-Active Microwave Thermography, Logan M. Wilcox, Mathias Bonmarin, Kristen M. Donnell Jan 2022

Pulsed-Active Microwave Thermography, Logan M. Wilcox, Mathias Bonmarin, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a thermographic nondestructive testing and evaluation technique that utilizes an electromagnetic-based excitation with a subsequent infrared measurement of the surface thermal profile of the material or structure of interest. AMT has been successfully applied to several aerospace and civil infrastructure applications. This work seeks to expand the performance of AMT by incorporating a signal processing technique common to traditional (flash-lamp) thermography, referred to as pulsed thermography (PT). PT operates on the premise of a pulsed excitation, as opposed to a constant or step excitation (ST) over a given time-period that is typical to traditional active …

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Generation Expansion Planning Considering Discrete Storage Model And Renewable Energy Uncertainty: A Bi-Interval Optimization Approach, Siyuan Wang, Guangchao Geng, Qy Jiang, Rui Bo Jan 2022

Generation Expansion Planning Considering Discrete Storage Model And Renewable Energy Uncertainty: A Bi-Interval Optimization Approach, Siyuan Wang, Guangchao Geng, Qy Jiang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Both discrete storage model (DSM) and continuous storage model (CSM) have been used in the power system planning literature. In this work, we conduct a sizing-error analysis for the use of CSM in generation expansion planning (GEP), which shows more reasonable storage sizing decisions are offered by the DSM in comparison to the CSM. However, when the DSM is considered in the context of interval optimization, the discrete status variables in mutually exclusive constraints and the strong temporal coupling in state-of-charge (SOC) constraints create significant challenges. To tackle this, a tailored interval optimization approach is proposed to consider both DSM …

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A New Discontinuous Conduction Mode In A Transformer Coupled High Gain Dc-Dc Converter, Kartikeya J.P. Veeramraju, Jacob Eisen, Joshua L. Rovey, Jonathan W. Kimball Jan 2022

A New Discontinuous Conduction Mode In A Transformer Coupled High Gain Dc-Dc Converter, Kartikeya J.P. Veeramraju, Jacob Eisen, Joshua L. Rovey, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

Electrospray space propulsion thrusters often employ transformer coupled high gain dc-dc converters. These thrusters have a unique load resistance profile that can vary dramatically during operation. Transformer coupled high gain dc-dc converters working in very low power modes can enter a unique discontinuous conduction mode (DCM) caused by a coupling effect between the boost and magnetization inductors in the converter. The transformer magnetization current prevents the boost inductors from discharging properly, which causes premature loss of boost action and higher than expected boost inductor voltages. This mechanism generates abnormally high voltages on the converter's output side, leading to converter and …

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Optimal Adaptive Output Regulation Of Uncertain Nonlinear Discrete-Time Systems Using Lifelong Concurrent Learning, R. Moghadam, B. Farzanegan, S.(Sarangapani) Jagannathan, P. Natarajan Jan 2022

Optimal Adaptive Output Regulation Of Uncertain Nonlinear Discrete-Time Systems Using Lifelong Concurrent Learning, R. Moghadam, B. Farzanegan, S.(Sarangapani) Jagannathan, P. Natarajan

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Addresses Neural Network (NN) based Optimal Adaptive Regulation of Uncertain Nonlinear Discrete-Time Systems in Affine Form using Output Feedback Via Lifelong Concurrent Learning. First, an Adaptive NN Observer is Introduced to Estimate Both the State Vector and Control Coefficient Matrix, and its NN Weights Are Adjusted using Both Output Error and Concurrent Learning Term to Relax the Persistency Excitation (PE) Condition. Next, by Utilizing an Actor-Critic Framework for Estimating the Value Functional and Control Policy, the Critic Network Weights Are Tuned Via Both Temporal Different Error and Concurrent Learning Schemes through a Replay Buffer. the Actor NN Weights …

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Review Of Fiber Optic Displacement Sensors, Chen Zhu, Yiyang Zhuang, Bo Liu, Jie Huang Jan 2022

Review Of Fiber Optic Displacement Sensors, Chen Zhu, Yiyang Zhuang, Bo Liu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Displacement Measurements Are of Significant Importance in a Variety of Critical Scientific and Engineering Fields, Such as Gravitational Wave Detection, Geophysical Research, and Manufacturing Industries. Due to the Inherent Advantages Such as Compactness, High Sensitivity, and Immunity to Electromagnetic Interference, in Recent Years, Fiber Optic Sensors Have Been Widely Used in an Expansive Range of Sensing Applications, Ranging from Infrastructural Health Monitoring to Chemical and Biological Sensing. of Particular Interest Here, Fiber Optic Displacement Sensors Have Gained Wide Interest and Have Evolved from Basic Intensity Modulation-Based Configurations to More Advanced Structures, Such as Fiber Bragg Grating (FBG)-Based and Interferometric Configurations. …

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Temperature-Insensitive Inclinometer Based On Transmission Line Fabry-Perot Resonators, Jing Guo, Chen Zhu, Yan Tang, Jie Huang Jan 2022

Temperature-Insensitive Inclinometer Based On Transmission Line Fabry-Perot Resonators, Jing Guo, Chen Zhu, Yan Tang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This Article Reports a Novel Self-Compensated Inclinometer with a Wide Dynamic Range and High Measurement Resolution based on Two Hollow Coaxial Cable Fabry-Perot Resonators (HCC-FPRs). the HCC-FPR is Formed between a Metal Post that Shorts the Inner Conductor and the Outer Conductor of the HCC and the Water Level Inside the HCC. Changes in Tilt Angles Result in Variations of the Water Level in the HCC, Leading to Changes in the Cavity Length of the HCC-FPR. by Tracking the Shift of the Resonance Wavelength of the HCC-FPR, a Single HCC-FPR Can Be Used as a Sensor Device for Tilt Measurements. …

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Cmn 3982, Clas Jan 2022

Cmn 3982, Clas

Executive Actions

No abstract provided.

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Cmn 4450 & Cmn 4750, Clas Jan 2022

Cmn 4450 & Cmn 4750, Clas

Executive Actions

No abstract provided.

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Hcm 4950, Clas Jan 2022

Hcm 4950, Clas

Executive Actions

No abstract provided.

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Jou 4401, Clas Jan 2022

Jou 4401, Clas

Executive Actions

No abstract provided.

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Prediction Of Formation Conditions Of Gas Hydrates Using Machine Learning And Genetic Programming, Anupama Kumari, Mukund Madhaw, Vishnu S. Pendyala Jan 2022

Prediction Of Formation Conditions Of Gas Hydrates Using Machine Learning And Genetic Programming, Anupama Kumari, Mukund Madhaw, Vishnu S. Pendyala

Faculty Research, Scholarly, and Creative Activity

The formation of gas hydrates in the pipelines of oil, gas, chemical, and other industries has been a significant problem for many years because the formation of gas hydrates may block the pipelines. Hence, the knowledge of the phase equilibrium conditions of gas hydrate became necessary for the economic and safe working of oil, gas, chemical industries. Various thermodynamic approaches with various mathematical techniques are available for the prediction of formation conditions of gas hydrates. In this chapter, the authors have discussed the least square support vector machine and artificial neural network models for the prediction of stability conditions of …

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3d-Printed Gelatin-Alginate Hydrogel Dressings For Burn Wound Healing: A Comprehensive Study, Fateme Fayyazbakhsh, Michael J. Khayat, Ming-Chuan Leu Jan 2022

3d-Printed Gelatin-Alginate Hydrogel Dressings For Burn Wound Healing: A Comprehensive Study, Fateme Fayyazbakhsh, Michael J. Khayat, Ming-Chuan Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Burn Wound Treatment is Still a Clinical Challenge Due to the Severity of Tissue Damage and Dehydration. among Various Wound Dressings, Hydrogel Materials Have Gained Significant Attention for Burn Wound Treatment in Clinical Practice Due to their Soothing and Moisturizing Activity. in This Study, 3D-Printed Dressings Were Fabricated using Clinically Relevant Hydrogels for Deep Partial-Thickness Burn (PTB) Wounds. Different Ratios of Gelatin and Alginate Mixture Were 3D-Printed and Examined in Terms of Rheological Behavior, Shear Thinning Behavior, Mechanical Properties, Degradation Rate, and Hydration Activity to Tune the Hydrogel Composition for Best Functionality. the Cell-Laden Dressings Were Bioprinted to Evaluate the …

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Satellite Drag Coefficient Modeling For Thermosphere Science And Mission Operations, Piyush M. Mehta, Smriti N. Paul, Nicholas H. Crisp, Philip L. Sheridan, Christian Siemes, Günther March, Sean Bruinsma Jan 2022

Satellite Drag Coefficient Modeling For Thermosphere Science And Mission Operations, Piyush M. Mehta, Smriti N. Paul, Nicholas H. Crisp, Philip L. Sheridan, Christian Siemes, Günther March, Sean Bruinsma

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Satellite drag modeling remains the largest source of uncertainty affecting space operations in low Earth orbit. The uncertainty stems from inaccurate models for mass density and drag coefficient. Drag coefficient modeling also impacts scientific knowledge on the physics and dynamics of the upper atmosphere through the estimation of high-fidelity mass density from measurements of acceleration on-board satellites. Efforts over the last decade have pushed drag coefficient modeling in the right direction, however, have resulted in multiple methods and tools. We provide a comprehensive review of the drag coefficient modeling methods and tools. Current scale differences between thermospheric data sets mostly …

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Effects Of Wheel Rotation On Long-Period Wake Dynamics Of The Drivaer Fastback Model, Matthew Aultman, Rodrigo Auza-Gutierrez, Kevin Disotell, Lian Duan Jan 2022

Effects Of Wheel Rotation On Long-Period Wake Dynamics Of The Drivaer Fastback Model, Matthew Aultman, Rodrigo Auza-Gutierrez, Kevin Disotell, Lian Duan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Lattice Boltzmann method (LBM) simulations were performed to capture the long-period dynamics within the wake of a realistic DrivAer fastback model with stationary and rotating wheels. The simulations showed that the wake developed as a low-pressure torus regardless of whether the wheels were rotating. This torus shrank in size on the base in the case of rotating wheels, leading to a reduction in the low-pressure footprint on the base, and consequently a 7% decrease in the total vehicle drag in comparison to the stationary wheels case. Furthermore, the lateral vortex shedding experienced a long-period switching associated with the bi-stability in …

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Discrimination Experiences During Covid-19 Among A National, Multi-Lingual, Community-Based Sample Of Asian Americans And Pacific Islanders: Compass Findings, Van M. Ta Park, Marcelle M. Dougan, Oanh L. Meyer, Bora Nam, Marian Tzuang, Linda G. Park, Quyen Vuong, Joon Bang, Janice Y. Tsoh Jan 2022

Discrimination Experiences During Covid-19 Among A National, Multi-Lingual, Community-Based Sample Of Asian Americans And Pacific Islanders: Compass Findings, Van M. Ta Park, Marcelle M. Dougan, Oanh L. Meyer, Bora Nam, Marian Tzuang, Linda G. Park, Quyen Vuong, Joon Bang, Janice Y. Tsoh

Faculty Research, Scholarly, and Creative Activity

Reports of escalated discrimination among Asian Americans and Pacific Islanders (AAPIs) due to COVID-19 are alarming, making this a public health priority. However, there are limited empirical studies on the scope and impact of COVID-19-related discrimination among AAPIs. Using the COVID-19 Effects on the Mental and Physical Health of AAPI Survey Study (COMPASS) data (N = 4971; survey period: October 2020–February 2021), which is a U.S.-wide multi-lingual survey, we examined the prevalence of, and factors associated with discrimination experiences attributable to being an AAPI during the COVID-19 pandemic. Overall, 60.7% reported experiencing discrimination; the group prevalence ranged from 80.0% (Hmong) …

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Efficient Routing Protection Algorithm Based On Optimized Network Topology, Haijun Geng, Zikun Jin, Jiangyuan Yao, Han Zhang, Zhiguo Hu, Bo Yang, Yingije Guo, Wei Wang, Qidong Zhang, Guoao Duan Jan 2022

Efficient Routing Protection Algorithm Based On Optimized Network Topology, Haijun Geng, Zikun Jin, Jiangyuan Yao, Han Zhang, Zhiguo Hu, Bo Yang, Yingije Guo, Wei Wang, Qidong Zhang, Guoao Duan

Faculty Research, Scholarly, and Creative Activity

Network failures are unavoidable and occur frequently. When the network fails, intra-domain routing protocols deploying on the Internet need to undergo a long convergence process. During this period, a large number of messages are discarded, which results in a decline in the user experience and severely affects the quality of service of Internet Service Providers (ISP). Therefore, improving the availability of intra-domain routing is a trending research question to be solved. Industry usually employs routing protection algorithms to improve intra-domain routing availability. However, existing routing protection schemes compute as many backup paths as possible to reduce message loss due to …

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Commuter Mobility Patterns In Social Media: Correlating Twitter And Lodes Data, Andreas Petutschnig, Jochen Albrecht, Bernd Resch, Laxmi Ramasubramanian, Aleisha Wright Jan 2022

Commuter Mobility Patterns In Social Media: Correlating Twitter And Lodes Data, Andreas Petutschnig, Jochen Albrecht, Bernd Resch, Laxmi Ramasubramanian, Aleisha Wright

Faculty Research, Scholarly, and Creative Activity

The Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) are an important city planning resource in the USA. However, curating these statistics is resource-intensive, and their accuracy deteriorates when changes in population and urban structures lead to shifts in commuter patterns. Our study area is the San Francisco Bay area, and it has seen rapid population growth over the past years, which makes frequent updates to LODES or the availability of an appropriate substitute desirable. In this paper, we derive mobility flows from a set of over 40 million georeferenced tweets of the study area and compare them with LODES data. …

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Blackcurrants: A Nutrient-Rich Source For The Development Of Functional Foods For Improved Athletic Performance, Ali Ali Redha, Shahida Anusha Siddiqui, Reza Zare, Daniele Spadaccini, Silvia Guazzotti, Xi Feng, Nur Alim Bahmid, Yuan Seng Wu, Fathima Zahraa Ozeer, Rotimi E. Aluko Jan 2022

Blackcurrants: A Nutrient-Rich Source For The Development Of Functional Foods For Improved Athletic Performance, Ali Ali Redha, Shahida Anusha Siddiqui, Reza Zare, Daniele Spadaccini, Silvia Guazzotti, Xi Feng, Nur Alim Bahmid, Yuan Seng Wu, Fathima Zahraa Ozeer, Rotimi E. Aluko

Faculty Research, Scholarly, and Creative Activity

Blackcurrants are nutrient-rich fruits with a significant amount of bioactive compounds including vitamin C and polyphenols, especially anthocyanins. The high phytochemical content of blackcurrants promotes this fruit to become a valuable functional food ingredient with varying health-promoting activities targeting different consumers including athletes. Athletes experience oxidative stress during intense exercise, which can result in inflammation and reduced exercise performance. Antioxidants such as vitamin C and polyphenols can restore the regular oxidative status of the body. Blackcurrant supplementation has shown potential ergogenic activity to improve athlete performance during high-intensity training. Clinical trials have evaluated the effectiveness of blackcurrant supplementation on exercise …

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Characterizing The Feedback That Learning Assistants Give To Faculty, Sadhana Indukuri, Gina M. Quan Jan 2022

Characterizing The Feedback That Learning Assistants Give To Faculty, Sadhana Indukuri, Gina M. Quan

Faculty Research, Scholarly, and Creative Activity

Learning assistants are undergraduate peer educators that help facilitate learning in a university classroom environment. Jardine (2019) found that learning assistant feedback to faculty roughly fell into three categories: course logistics, student behavior, and student understanding. We built from this previous work by further characterizing the feedback given to faculty by learning assistants and found the following categories: student experience, classroom content, classroom structure, accessibility, empathy, and broad feedback. Using interview data with learning assistants and faculty working with learning assistants, we created a preliminary framework for the types of feedback and examples by learning assistants. This framework may be …

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Sieve Or Shield? High Tech Firms And Entrepreneurs And The Impacts Of Covid 19 On North American Border Regions, Kathrine Eileen Richardson, Francesco Cappellano Jan 2022

Sieve Or Shield? High Tech Firms And Entrepreneurs And The Impacts Of Covid 19 On North American Border Regions, Kathrine Eileen Richardson, Francesco Cappellano

Faculty Research, Scholarly, and Creative Activity

This study examines the role of international borders in the era of the Covid-19 pandemic, which led to unprecedented national decisions to close borders in order to contain the domestic contagion. The idea that borders act as shields conflicts with the needs of cross-border regions, as they rely on networks straddling the borders for goods and services’ provisions. This paper explores different approaches at individual, local, and regional policy levels used to counterbalance such impacts. As evidenced by North American border closures to most non-citizens seeking entry (shield effects), it is important to understand how professionals, firms, and their networks …

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Design, Construction And Operation Of The Protodune-Sp Liquid Argon Tpc, A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, D. Adams, M. Adinolfi, A. Aduszkiewicz, J. Aguilar, Z. Ahmad, J. Ahmed, B. Ali-Mohammadzadeh, T. Alion, K. Allison, S. Alonso Monsalve, M. Alrashed, Athanasios Hatzikoutelis, For Full Author List, See Comments Below Jan 2022

Design, Construction And Operation Of The Protodune-Sp Liquid Argon Tpc, A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, D. Adams, M. Adinolfi, A. Aduszkiewicz, J. Aguilar, Z. Ahmad, J. Ahmed, B. Ali-Mohammadzadeh, T. Alion, K. Allison, S. Alonso Monsalve, M. Alrashed, Athanasios Hatzikoutelis, For Full Author List, See Comments Below

Faculty Research, Scholarly, and Creative Activity

The ProtoDUNE-SP detector is a single-phase liquid argon time projection chamber (LArTPC) that was constructed and operated in the CERN North Area at the end of the H4 beamline. This detector is a prototype for the first far detector module of the Deep Underground Neutrino Experiment (DUNE), which will be constructed at the Sandford Underground Research Facility (SURF) in Lead, South Dakota, U.S.A. The ProtoDUNE-SP detector incorporates full-size components as designed for DUNE and has an active volume of 7 × 6 × 7.2 m3. The H4 beam delivers incident particles with well-measured momenta and high-purity particle identification. ProtoDUNE-SP's successful …

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Visual Task Classification Using Classic Machine Learning And Cnns, Devangi Vilas Chinchankarame, Noha Elfiky, Nada Attar Jan 2022

Visual Task Classification Using Classic Machine Learning And Cnns, Devangi Vilas Chinchankarame, Noha Elfiky, Nada Attar

Faculty Research, Scholarly, and Creative Activity

Our eyes actively perform tasks including, but not limited to, searching, comparing, and counting. This includes tasks in front of a computer, whether it be trivial activities like reading email, or video gaming, or more serious activities like drone management, or flight simulation. Understanding what type of visual task is being performed is important to develop intelligent user interfaces. In this work, we investigated standard machine and deep learning methods to identify the task type using eye-tracking data-including both raw numerical data and the visual representations of the user gaze scan paths and pupil size. To this end, we experimented …

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Leveraging Initial Cognitive Load To Predict User Response To Complex Visual Tasks, Reem Albaghli, Yaman Jandali, Sarah Almahmid, Nada Attar Jan 2022

Leveraging Initial Cognitive Load To Predict User Response To Complex Visual Tasks, Reem Albaghli, Yaman Jandali, Sarah Almahmid, Nada Attar

Faculty Research, Scholarly, and Creative Activity

In this study, we were able to show how cognitive load measurement during the initiation of a complex visual task can predict user response. We measured cognitive load using pupil size and microsaccade rate. The initial phase of task was defined as the first 25 percent of the trial Reaction Time (RT), which was variable up to 50 seconds. The complex visual task entailed a set of twelve words that could be grouped based into 1, 2, or 3 categories or sets, e.g., the words bed, pillow, headboard, etc. can be grouped into a single set that is bedroom. We …

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