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2023

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Esd Events To Wearable Medical Devices In Healthcare Environments—Part 1: Current Measurements, Mehdi Kohani, Javad Meiguni, David J. Pommerenke, Michael G. Pecht Jan 2023

Esd Events To Wearable Medical Devices In Healthcare Environments—Part 1: Current Measurements, Mehdi Kohani, Javad Meiguni, David J. Pommerenke, Michael G. Pecht

Electrical and Computer Engineering Faculty Research & Creative Works

Wearable medical devices are widely used for monitoring and treatment of patients. Electrostatic discharge can render these devices unreliable and cause a temporary or permanent disturbance in their operation. In a healthcare environment, severe electrostatic discharge (ESD) can occur while a patient, lying down or sitting on a hospital bed with a wearable device, discharges the device via a grounded bedframe. To protect the devices from ESD damage, the worst-case discharge conditions in the usage environment need to be identified. Previous studies by authors revealed that such events could be more severe than the conventional human metal model (HMM). However, …

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Virtual Synchronous Generator Control Using Twin Delayed Deep Deterministic Policy Gradient Method, Oroghene Oboreh-Snapps, Buxin She, Shah Fahad, Haotian Chen, Jonathan W. Kimball, Fangxing Li, Hantao Cui, Rui Bo Jan 2023

Virtual Synchronous Generator Control Using Twin Delayed Deep Deterministic Policy Gradient Method, Oroghene Oboreh-Snapps, Buxin She, Shah Fahad, Haotian Chen, Jonathan W. Kimball, Fangxing Li, Hantao Cui, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a data-driven approach that adaptively tunes the parameters of a virtual synchronous generator to achieve optimal frequency response against disturbances. In the proposed approach, the control variables, namely, the virtual moment of inertia and damping factor, are transformed into actions of a reinforcement learning agent. Different from the state-of-the-art methods, the proposed study introduces the settling time parameter as one of the observations in addition to the frequency and rate of change of frequency (RoCoF). In the reward function, preset indices are considered to simultaneously ensure bounded frequency deviation, low RoCoF, fast response, and quick settling time. …

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A Physics-Based Model For Snapback-Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, Daryl G. Beetner Jan 2023

A Physics-Based Model For Snapback-Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

A simplified physical-based model for deep-snapback transient voltage suppressors (TVS) is developed in this article. While based on physics, the number of parameters and components is minimized, so the model can be tuned easily from available measurements of the packaged TVS. SPICE convergence issues seen in previous snapback device models are eliminated by adding nonlinear damping components to the model. No convergence issues were seen among any of the simulations performed for this study, which includes transmission-line pulse tests with multiple levels and rise times. The proposed model was used to represent two different TVS devices and was validated in …

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Enhancing Near-Field Wireless Localization With Lidar-Assisted Ris In Multipath Environments, Omar Rinch, Ahmed Elzanaty, Ahmad Alsharoa Jan 2023

Enhancing Near-Field Wireless Localization With Lidar-Assisted Ris In Multipath Environments, Omar Rinch, Ahmed Elzanaty, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

In Next-Generation Wireless Networks that Adopt Millimeter-Waves and Large RIS, the User is Expected to Be in the Near-Field Region, Where the Widely Adopted Far-Field Algorithms based on Far-Field Can Yield Low Positioning Accuracy. Also, the Localization of UE Becomes More Challenging in Multipath Environments. in This Paper, We Propose a Localization Algorithm for a UE in the Near-Field of a RIS in Multipath Environments. the Proposed Scheme Utilizes a LiDAR to Assist the UE Positioning by Providing Geometric Information About Some of the Scatterers in the Environment. This Information is Fed to a Sparse Recovery Algorithm to Improve the …

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Guest Editorial Special Section On The 2022 Ieee International Instrumentation And Measurement Technology Conference, Sergio Rapuano, Kristen M. Donnell, Pawel Niewczas Jan 2023

Guest Editorial Special Section On The 2022 Ieee International Instrumentation And Measurement Technology Conference, Sergio Rapuano, Kristen M. Donnell, Pawel Niewczas

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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A Statistical Shmoo For A Decision Feedback Equalizer (Dfe), Junyong Park, Donghyun Kim Jan 2023

A Statistical Shmoo For A Decision Feedback Equalizer (Dfe), Junyong Park, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes a statistical shmoo for a Decision Feedback Equalizer (DFE). A statistical shmoo shows a Bit-Error Rate (BER) distribution of a system depending on conditions such as a threshold voltage and sampling time. The previous statistical eye diagram can be converted to a statistical shmoo except for the case of a DFE. In the shmoo, rows and columns represent different threshold voltages and sampling times, respectively. Thus, the DFE operation also depends on each row and column. Furthermore, a DFE may have error propagations because of substantial noise. Therefore, this article proposes a statistical shmoo for an ideal …

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Accelerated Statistical Eye Diagram Estimation Method For Efficient Signal Integrity Analysis, Junyong Park, Youngwoo Kim, Donghyun Kim Jan 2023

Accelerated Statistical Eye Diagram Estimation Method For Efficient Signal Integrity Analysis, Junyong Park, Youngwoo Kim, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes an accelerated statistical eye diagram estimation method for efficient signal integrity (SI) analysis. An eye diagram is a critical metric in the SI analysis, however obtaining an eye diagram is time-consuming in simulation. The required time might be a few weeks depending on the complexity. Because the eye diagram is obtained by superposition of the received waveforms. Statistical eye diagram estimation methods were proposed to make the eye diagram acquisition efficient, however, it still has a limited improvement due to a large number of convolution operations. To address this limitation, the proposed method includes two approaches: (i) …

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Implementing The Fast Full-Wave Electromagnetic Forward Solver Using The Deep Convolutional Encoder-Decoder Architecture, He Ming Yao, Lijun Jiang, Michael Ng Jan 2023

Implementing The Fast Full-Wave Electromagnetic Forward Solver Using The Deep Convolutional Encoder-Decoder Architecture, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

In this communication, a novel deep learning (DL)-based solver is proposed for the electromagnetic forward (EMF) process. It is based on the complex-valued deep convolutional neural networks (DConvNets) comprising an encoder network and a corresponding decoder network with pixel-wise regression layer. The encoder network takes the incident EM wave and the contrast (permittivity) distribution of the object as the input. It channels the processed data into the corresponding decoder network to predict the total EM field due to the scatter of the input incident EM wave. The training of the proposed DConvNets is done using the simple synthetic dataset. Due …

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Detection Of Surface Cracks In Metals Using Microwave And Millimeter-Wave Nondestructive Testing Techniques-A Review, Mohamed A. Abou-Khousa, Mohammed Saif Ur Rahman, Kristen M. Donnell, Mohammad Tayeb Al (Tayeb) (Al) Qaseer Jan 2023

Detection Of Surface Cracks In Metals Using Microwave And Millimeter-Wave Nondestructive Testing Techniques-A Review, Mohamed A. Abou-Khousa, Mohammed Saif Ur Rahman, Kristen M. Donnell, Mohammad Tayeb Al (Tayeb) (Al) Qaseer

Electrical and Computer Engineering Faculty Research & Creative Works

Integrity Assessment of Metallic Structures Requires Inspection Tools Capable of Detecting and Evaluating Cracks Reliably. to This End, Many Microwave and Millimeter-Wave Nondestructive Testing and Evaluation (NDT&E) Methods Have Been Developed and Applied Successfully in the Past. Detection of Fatigue Cracks with Widths Less Than 5 Μ M using Noncontact Microwave-Based Inspection Methods Was Demonstrated in the 1970s. Since their Introduction, These Methods Have Evolved Considerably Toward Enhancing the Detection Sensitivity and Resolution. Undertaking Key Application Challenges Has Attracted Considerable Attention in the Past Three Decades and Led to the Development of the Near-Field Techniques for Crack Detection. to Address …

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A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi Jan 2023

A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi

Electrical and Computer Engineering Faculty Research & Creative Works

According to the Third Generation Partnership Project Specification, a Period of 8-12.8 H is Required to Evaluate the Multiple-Input-Multiple-Output (MIMO) Performance of a Wireless Terminal for a Single Frequency Point and Channel Model Combination. the Following Article Proposes a Semi-Simulation, Semi-Measurement-Based MIMO throughput Modeling Scheme Which Can Reduce the 8-12.8-H Measurement Time to 40-60 Min, Corresponding to More Than a Ten Times Improvement of the Test Efficiency, Without Loss of the Test Accuracy.

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Just Go To The Office! An Intersectional Exploration Of The Role Of Race And Gender In Discipline Referral Reasons, Kamilah B. Legette, Yoli Anyon Jan 2023

Just Go To The Office! An Intersectional Exploration Of The Role Of Race And Gender In Discipline Referral Reasons, Kamilah B. Legette, Yoli Anyon

Faculty Research, Scholarly, and Creative Activity

Educators’ differential selection of Black and Latine students for office discipline referrals is a significant driver of inequity in exclusionary outcomes. Using demographic data and discipline records for all students in one large urban school district, we use descriptive statistics and multilevel regression models to consider whether referral reasons are racialized and if these patterns intersect with gender. Our analyses indicate that educators are consistently more likely to refer Black students than White students to the office for several subjective reasons, including habitual disruption, that are purportedly race-neutral but privilege Whiteness. They are less likely to make referrals for Black …

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Swayed Pines Festival, 1974-2000: Community Building Through Music, Crafts, Food & Fun [2023], Peggy L. Roske Jan 2023

Swayed Pines Festival, 1974-2000: Community Building Through Music, Crafts, Food & Fun [2023], Peggy L. Roske

Archives History Lessons

The Swayed Pines Festival was a community event held at Saint John’s every spring for 27 years. Folk music, a fiddling contest, crafts, food, workshops, art and concerts brought thousands to campus.

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Ghost Stories, Peggy L. Roske Jan 2023

Ghost Stories, Peggy L. Roske

Archives History Lessons

A compilation of what is known, rumored or fabricated about ghosts at Saint John’s and Saint Ben’s and the basis some of the ghost stories have in historical facts.

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Shifting Mediates Gendered Racial Microaggressions And Perceived Racism Among Asian American Women, Glenn Gamst, Christine Ma-Kellams, Lawrence S. Meyers, Leticia Arellano-Morales Jan 2023

Shifting Mediates Gendered Racial Microaggressions And Perceived Racism Among Asian American Women, Glenn Gamst, Christine Ma-Kellams, Lawrence S. Meyers, Leticia Arellano-Morales

Faculty Research, Scholarly, and Creative Activity

Introduction: Microaggressive attacks on Asian American women increased during the COVID-19 pandemic. The present study tested whether Asian American women's shifting, a coping strategy employed by some women of color to alter their self-presentation in response to perceived racism, mediated the association between gendered racial microaggressions and self-perceived subtle and blatant racism. Methods: A convenience sample of 253 Asian American adult women completed the gendered racial microaggressions scale for Asian American women (GRMSAAW), the Asian American women's shifting scale (AsAWSS), and the subtle and blatant racism scale for Asian American college students (SABR-A2). Results: Results from a structural equation model …

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2023 Silicon Valley Pain Index, Scott Myers-Lipton, William Armaline Jan 2023

2023 Silicon Valley Pain Index, Scott Myers-Lipton, William Armaline

Faculty Research, Scholarly, and Creative Activity

No abstract provided.

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Boycotting Vs. Canceling: Exploring Consumer Activism Against Corporations, Erica Buchman Jan 2023

Boycotting Vs. Canceling: Exploring Consumer Activism Against Corporations, Erica Buchman

Student Theses and Dissertations

The purpose of this thesis is to establish the difference between boycotting and canceling a corporation and what compels consumers to act. Consumer activism attempts to hold companies to account when a line, be it arbitrary or rational, is crossed, and these attempts are not always successful. However, when enough social pressure is exerted on a company via boycotting, depending on the wrongful act committed, accountability and change can be possible. I want to determine what some of the factors are that could compel customers to engage in consumer activism or boycott against a corporation and whether a corporation that …

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Les Risques De Vibrations Mains-Bras Dans Le Secteur Minier, Sachez Les Identifier Et Les Réduire!, Isabelle Maguire, Laurent Giraud Jan 2023

Les Risques De Vibrations Mains-Bras Dans Le Secteur Minier, Sachez Les Identifier Et Les Réduire!, Isabelle Maguire, Laurent Giraud

Fiches

No abstract provided.

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2+1 Roadway Design Guidance Update, Jeff Jasper, Jeff Wolfe, Robin Baskette, Paul Ross, Chris Van Dyke Jan 2023

2+1 Roadway Design Guidance Update, Jeff Jasper, Jeff Wolfe, Robin Baskette, Paul Ross, Chris Van Dyke

Kentucky Transportation Center Research Report

The frequency and severity of crashes on rural two-lane roadways have increased in the US relative to other road types. This trend can be explained by the growing number of vehicles, higher speeds, narrow shoulders, and vehicle mixes. One solution for improving traffic flow and safety outcomes on rural two-lane roadways is to adopt a 2+1 design, which confers the benefits of four-lane highways but at a lower cost. Transportation agencies throughout Europe — and increasingly the US — have seen good results from 2+1 layouts. Crash data from Sweden, Germany, Finland, and Denmark reveal better safety outcomes following the …

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Pedestrian And Bicycle Improvement Scoring Method For Shift–2024, Nikiforos Stamatiadis, Daria Korostina, Teng Wang, Reginald Souleyrette Jan 2023

Pedestrian And Bicycle Improvement Scoring Method For Shift–2024, Nikiforos Stamatiadis, Daria Korostina, Teng Wang, Reginald Souleyrette

Kentucky Transportation Center Research Report

State transportation agencies have limited funding to deliver multimodal transportation programs that address the needs of all users. To allocate project funding in an impartial and objective manner, many agencies have adopted data-driven scoring systems that are used to evaluate the merits of proposed capital improvement projects. The Kentucky Transportation Cabinet introduced the Strategic Highway Investment Formula for Tomorrow (SHIFT) for this purpose. Until now SHIFT, has evaluated projects based five core variables — congestion, safety, benefit-cost ratio, asset management, economic growth. To address local needs, SHIFT has also allocated points that Area Development Districts, metropolitan planning organizations, and Cabinet …

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View Synthesis With Scene Recognition For Cross-View Image Localization, Uddom Lee, Peng Jiang, Hongyi Wu, Chunsheng Xin Jan 2023

View Synthesis With Scene Recognition For Cross-View Image Localization, Uddom Lee, Peng Jiang, Hongyi Wu, Chunsheng Xin

Electrical & Computer Engineering Faculty Publications

Image-based localization has been widely used for autonomous vehicles, robotics, augmented reality, etc., and this is carried out by matching a query image taken from a cell phone or vehicle dashcam to a large scale of geo-tagged reference images, such as satellite/aerial images or Google Street Views. However, the problem remains challenging due to the inconsistency between the query images and the large-scale reference datasets regarding various light and weather conditions. To tackle this issue, this work proposes a novel view synthesis framework equipped with deep generative models, which can merge the unique features from the outdated reference dataset with …

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Security Of Internet Of Things (Iot) Using Federated Learning And Deep Learning — Recent Advancements, Issues And Prospects, Vinay Gugueoth, Sunitha Safavat, Sachin Shetty Jan 2023

Security Of Internet Of Things (Iot) Using Federated Learning And Deep Learning — Recent Advancements, Issues And Prospects, Vinay Gugueoth, Sunitha Safavat, Sachin Shetty

Electrical & Computer Engineering Faculty Publications

There is a great demand for an efficient security framework which can secure IoT systems from potential adversarial attacks. However, it is challenging to design a suitable security model for IoT considering the dynamic and distributed nature of IoT. This motivates the researchers to focus more on investigating the role of machine learning (ML) in the designing of security models. A brief analysis of different ML algorithms for IoT security is discussed along with the advantages and limitations of ML algorithms. Existing studies state that ML algorithms suffer from the problem of high computational overhead and risk of privacy leakage. …

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Toward Real-Time, Robust Wearable Sensor Fall Detection Using Deep Learning Methods: A Feasibility Study, Haben Yhdego, Christopher Paolini, Michel Audette Jan 2023

Toward Real-Time, Robust Wearable Sensor Fall Detection Using Deep Learning Methods: A Feasibility Study, Haben Yhdego, Christopher Paolini, Michel Audette

Electrical & Computer Engineering Faculty Publications

Real-time fall detection using a wearable sensor remains a challenging problem due to high gait variability. Furthermore, finding the type of sensor to use and the optimal location of the sensors are also essential factors for real-time fall-detection systems. This work presents real-time fall-detection methods using deep learning models. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. First, we developed and compared different data-segmentation techniques for sliding windows. Next, we implemented various techniques to balance the datasets because collecting fall datasets in the real-time setting has …

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Opioid Use Disorder Prediction Using Machine Learning Of Fmri Data, A. Temtam, Liangsuo Ma, F. Gerard Moeller, M. S. Sadique, K. M. Iftekharuddin, Khan M. Iftekharuddin (Ed.), Weijie Chen (Ed.) Jan 2023

Opioid Use Disorder Prediction Using Machine Learning Of Fmri Data, A. Temtam, Liangsuo Ma, F. Gerard Moeller, M. S. Sadique, K. M. Iftekharuddin, Khan M. Iftekharuddin (Ed.), Weijie Chen (Ed.)

Electrical & Computer Engineering Faculty Publications

According to the Centers for Disease Control and Prevention (CDC) more than 932,000 people in the US have died since 1999 from a drug overdose. Just about 75% of drug overdose deaths in 2020 involved Opioid, which suggests that the US is in an Opioid overdose epidemic. Identifying individuals likely to develop Opioid use disorder (OUD) can help public health in planning effective prevention, intervention, drug overdose and recovery policies. Further, a better understanding of prediction of overdose leading to the neurobiology of OUD may lead to new therapeutics. In recent years, very limited work has been done using statistical …

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Transfer Learning Using Infrared And Optical Full Motion Video Data For Gender Classification, Alexander M. Glandon, Joe Zalameda, Khan M. Iftekharuddin, Gabor F. Fulop (Ed.), David Z. Ting (Ed.), Lucy L. Zheng (Ed.) Jan 2023

Transfer Learning Using Infrared And Optical Full Motion Video Data For Gender Classification, Alexander M. Glandon, Joe Zalameda, Khan M. Iftekharuddin, Gabor F. Fulop (Ed.), David Z. Ting (Ed.), Lucy L. Zheng (Ed.)

Electrical & Computer Engineering Faculty Publications

This work is a review and extension of our ongoing research in human recognition analysis using multimodality motion sensor data. We review our work on hand crafted feature engineering for motion capture skeleton (MoCap) data, from the Air Force Research Lab for human gender followed by depth scan based skeleton extraction using LIDAR data from the Army Night Vision Lab for person identification. We then build on these works to demonstrate a transfer learning sensor fusion approach for using the larger MoCap and smaller LIDAR data for gender classification.

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Ict Security Tools And Techniques Among Higher Education Institutions: A Critical Review, Miko Nuñez, Xavier-Lewis Palmer, Lucas Potter, Chris Jordan Aliac, Lemuel Clark Velasco Jan 2023

Ict Security Tools And Techniques Among Higher Education Institutions: A Critical Review, Miko Nuñez, Xavier-Lewis Palmer, Lucas Potter, Chris Jordan Aliac, Lemuel Clark Velasco

Electrical & Computer Engineering Faculty Publications

Higher education institutions (HEIs) are increasingly relying on digital technologies for classroom and organizational management, but this puts them at higher risk for information and communication (ICT security attacks. Recent studies show that HEIs have experienced more security breaches in ICT security composed of both cybersecurity an information security. A literature review was conducted to identify common ICT security practices in HEIs over the last decade. 11 journal articles were profiled and analyzed, revealing threats to HEIs’ security and protective measures in terms of organizational security, technological security, physical security, and standards and frameworks. Security tools and techniques were grouped …

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Technology Adoption Of Computer-Aided Instruction In Healthcare: A Structured Review, Queenie Kate Cabanilla, Frevy Teofilo-Orencia, Rentor Cafino, Armando T. Isla Jr., Jehan Grace Maglaya, Xavier-Lewis Palmer, Lucas Potter, Dave E. Marcial, Lemuel Clark Velasco Jan 2023

Technology Adoption Of Computer-Aided Instruction In Healthcare: A Structured Review, Queenie Kate Cabanilla, Frevy Teofilo-Orencia, Rentor Cafino, Armando T. Isla Jr., Jehan Grace Maglaya, Xavier-Lewis Palmer, Lucas Potter, Dave E. Marcial, Lemuel Clark Velasco

Electrical & Computer Engineering Faculty Publications

Computer-Aided Instruction (CAI) is one of the interactive teaching methods that electronically presents instructional resources and enhances learner performance. In health settings, using CAI is one of the important ways to improve learners' knowledge and usefulness in their healthcare specialization yet there is still a lack of research that offers a comprehensive synthesis of investigating into the adoption of CAI in healthcare. This research aims to provide a comprehensive review of related literatures on the enablers and barriers for technology adoption of CAI in healthcare. 31 journals were analyzed and revealed that several studies were utilizing the Unified Theory of …

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Comparison Of Machine Learning Methods For Classification Of Alexithymia In Individuals With And Without Autism From Eye-Tracking Data, Furkan Iigin, Megan A. Witherow, Khan M. Iftekharuddin Jan 2023

Comparison Of Machine Learning Methods For Classification Of Alexithymia In Individuals With And Without Autism From Eye-Tracking Data, Furkan Iigin, Megan A. Witherow, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Alexithymia describes a psychological state where individuals struggle with feeling and expressing their emotions. Individuals with alexithymia may also have a more difficult time understanding the emotions of others and may express atypical attention to the eyes when recognizing emotions. This is known to affect individuals with Autism Spectrum Disorder (ASD) differently than neurotypical (NT) individuals. Using a public data set of eye-tracking data from seventy individuals with and without autism who have been assessed for alexithymia, we train multiple traditional machine learning models for alexithymia classification including support vector machines, logistic regression, decision trees, random forest, and multilayer perceptron. …

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Special Section Editorial: Artificial Intelligence For Medical Imaging In Clinical Practice, Claudia Mello-Thoms, Karen Drukker, Sian Taylor-Phillips, Khan Iftekharuddin, Marios Gavrielides Jan 2023

Special Section Editorial: Artificial Intelligence For Medical Imaging In Clinical Practice, Claudia Mello-Thoms, Karen Drukker, Sian Taylor-Phillips, Khan Iftekharuddin, Marios Gavrielides

Electrical & Computer Engineering Faculty Publications

This editorial introduces the JMI Special Section on Artificial Intelligence for Medical Imaging in Clinical Practice.

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Social-Engineering, Bio-Economies, And Nation-State Ontological Security: A Commentary, Brandon Griffin, Keitavius Alexander, Xavier-Lewis Palmer, Lucas Potter Jan 2023

Social-Engineering, Bio-Economies, And Nation-State Ontological Security: A Commentary, Brandon Griffin, Keitavius Alexander, Xavier-Lewis Palmer, Lucas Potter

Electrical & Computer Engineering Faculty Publications

Biocybersecurity is an evolving discipline that aims to identify the gaps and risks associated with the convergence of Biology (the science of life and living organisms) and cybersecurity (the science, study, and theory of cyberspace and cybernetics) to protect the bioeconomy. The biological industries’ increased reliance on digitization, automation, and computing power has resulted in benefits for the scientific community, it has simultaneously multiplied the risk factors associated with industrial espionage and the protection of data both commercial and proprietary. The sensitive and potentially destructive power of this data and its access inherently poses a risk to the national and …

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Implications Of Cyberbiosecurity In Advanced Agriculture, Simone Stephen, Keitavius Alexander, Lucas Potter, Xavier-Lewis Palmer Jan 2023

Implications Of Cyberbiosecurity In Advanced Agriculture, Simone Stephen, Keitavius Alexander, Lucas Potter, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

The world is currently undergoing a rapid digital transformation sometimes referred to as the fourth industrial revolution. During this transformation, it is increasingly clear that many scientific fields are not prepared for this change. One specific area is agriculture. As the sector which creates global food supply, this critical infrastructure requires detailed assessment and research via newly developed technologies (Millett et al, 2019; Peccoud et al, 2018) . Despite its fundamental significance to modern civilization, many aspects of industrial agriculture have not yet adapted to the digital world. This is evident in the many vulnerabilities currently present within agricultural systems, …

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