Digital Commons Network^™

Correction: Advancing Cislunar Space Domain Awareness Through Robust Optimization Framework For Optical Sensors-Based Autonomous Satellite Systems (American Institute Of Aeronautics And Astronautics Inc, Aiaa), Smriti Nandan Paul, Siwei Fan, Igor Panfil

Mechanical and Aerospace Engineering Faculty Research & Creative Works

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High-Order Dynamic Mode Decomposition For Multidimensional Harmonic Retrieval, Yanming Zhang, Steven Gao, Lijun Jiang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Estimating channel parameters such as azimuth, elevation, Doppler shift, and delay is a key challenge in wireless communication, often formulated as a multidimensional harmonic retrieval (MHR) problem. To address this, we propose a high-order dynamic mode decomposition (HODMD) framework for robust frequency estimation from high-dimensional signals in noisy environments. The HODMD approach combines high-order singular value decomposition (HOSVD) to decompose tensor data into a core tensor and mode matrices, with dynamic mode decomposition (DMD) to extract frequencies from the imaginary parts of the DMD eigenvalues. Simulation examples validate the effectiveness of the proposed method, demonstrating its efficiency in solving MHR …

Performance Evaluation And Multiphysics Process Modeling Of Carbon Fiber Reinforced Thermoset Composites Using Microwave And Autoclave, Nayan Pundhir, Patrick Schwartzkopf, K. Chandrashekhara, Logan Wilcox, Kristen M. Donnell, Jim Lua, Rui Li

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this study, IM7/Cycom 5320-1 unidirectional prepreg has been utilized to manufacture 16-layer laminated composites: a symmetric cross-ply ([0°/90°]4s) and a quasi-isotropic ([45°/90°/−45°/0°]2s) configuration. Microwave and autoclave curing processes have been employed to manufacture the laminated composites. The manufactured composite cure was assessed using differential scanning calorimetry (DSC). The quality and porosity of the microwave-cured parts were juxtaposed to those of autoclave-cured parts through optical microscopy and micro-computed tomography (micro-CT) scanning. Mechanical characterization of the microwave-cured panels was conducted using uniaxial tensile and flexural tests, with results juxtaposed to autoclave-cured samples. Experimental characterization revealed that the microwave-cured parts exhibited nearly …

A Low-Frequency-Stable Higher-Order Isogeometric Discretization Of The Augmented Electric Field Integral Equation, Maximilian Nolte, Riccardo Torchio, Sebastian Schöps, Jürgen Dölz, Felix Wolf, Albert E. Ruehli

Electrical and Computer Engineering Faculty Research & Creative Works

This contribution investigates the connection between Iso geometric analysis (IGA) and integral equation (IE) methods for full-wave electromagnetic problems up to the low-frequency limit. The proposed spline-based IE method allows for an exact representation of the model geometry described in terms of nonuniform rational B-splines (NURBS) without meshing. This is particularly useful when high accuracy is required or when meshing is cumbersome, for instance, during the optimization of electric components. The augmented electric field IE (EFIE) is adopted, and the deflation method is applied, so the low-frequency breakdown is avoided. The extension to higher-order basis functions is analyzed and the …

Cognitive Fatigue Detection Using Photoplethysmography (Ppg) And Reaction Time Data, Anhar Sami Mohammed, Prajoy Podder, Maciej Jan Zawodniok, Cihan Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a framework for real-time cognitive fatigue detection among shift workers using an integrated approach that combines photoplethysmography (PPG) data and reaction time analysis with advanced deep learning models, including Long Short-Term Memory (LSTM) networks and Feedforward Neural Networks (FNNs). The system leverages heart rate variability (HRV) and reaction time data to identify fatigue indicators. The results demonstrate significant performance, with the first FNN model achieving a test accuracy of 98.94% and a loss of 0.2928, while the second FNN model achieved the same accuracy with a slightly higher loss of 0.3089. The LSTM model, designed for sequential …

A Non-Destructive And Simple Setup Method For Dielectric Liquid Characterization In A Wide Frequency Range With Djordjevic-Sarkar Model, Reza Vahdani, Reza Asadi, Seyedmehdi Mousavi, Xiaoning Ye, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces a non-destructive and simple setup method for characterizing dielectric liquids over a broad frequency range (up to 30 GHz) using the Djordjevic-Sarkar model. By employing a differential microstrip line and comparing scattering parameters in air-filled and liquid-immersed scenarios, the proposed method achieves precise dielectric constant (DK) and dissipation factor (Df) extraction. 2 Liquid samples (PAO4 and DC-15) were tested using this method. Validation against the cavity resonance method demonstrates a strong agreement for the extracted DK values, with a relative error of less than 1.5 %, indicating high accuracy. However, the method is less sensitive to Df, …

Data Representation And Preprocessing Effects On S-Parameter Modeling Of High-Speed Channels Using Machine Learning, Hyunwook Park, Davit Kharshiladze, Yifan Ding, Ling Zhang, Natalia Bondarenko, Hanqin Ye, Kaushal Sanjay Mhalgi, Brice Achkir, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the effects of data representations and preprocessing on machine learning based S-parameter modeling of high-speed channels are investigated. Using a transformer network as a base model, two S-parameter representations in real/imaginary and magnitude/phase are compared and studied. Considering S-parameter data distributions, various preprocessing techniques including MinMax normalization, standardization, robust scaling, power transformation, and quantile transformation are compared and analyzed to improve accuracy. Moreover, the accuracy results are compared depending on the electrical length of target channels.

The Role Of Team Compassion In Mitigating The Impact Of Hierarchical Bullying, Ben Farr-Wharton, Ace V. Simpson, Yvonne Brunetto, Tim Bentley

Research outputs 2022 to 2026

Hierarchical bullying in public healthcare organizations is an entrenched negative behaviour that results in a range of adverse outcomes for staff, including diminished wellbeing. This study integrates social exchange and conservation of resources theories as a lens for formulating hypotheses and employs multilevel statistical modelling to examine whether team-level compassion moderates the impact of hierarchical bullying on wellbeing. Using multilevel statistical modelling, the study analysed cross-sectional data from 632 healthcare workers nested within 48 teams in a single public health district in Australia. The findings indicate that work teams with higher levels of team compassion can mitigate the negative effects …

Neuron Semantic-Guided Test Generation For Deep Neural Networks Fuzzing, Li Huang, Weifeng Sun, Meng Yan, Zhongxin Liu, Yan Lei, David Lo

Research Collection School Of Computing and Information Systems

In recent years, significant progress has been made in testing methods for deep neural networks (DNNs) to ensure their correctness and robustness. Coverage-guided criteria, such as neuron-wise, layer-wise, and path-/trace-wise, have been proposed for DNN fuzzing. However, existing coverage-based criteria encounter performance bottlenecks for several reasons: Testing Adequacy: Partial neural coverage criteria have been observed to achieve full coverage using only a small number of test inputs. In this case, increasing the number of test inputs does not consistently improve the quality of models. Interpretability: The current coverage criteria lack interpretability. Consequently, testers are unable to identify and understand which …

Processing Of Verbal Versus Adjectival Agreement: Implications For Syntax And Psycholinguistics, Zuzanna Fuchs, Olga Parshina, Irina A. Sekerina, Maria Polinsky

Publications and Research

Linguistic theories distinguish between external and internal agreement (e.g., noun-verb agreement vs. noun-modifier agreement, the latter also known as concord) and model them using different mechanisms. While this distinction has garnered considerable attention in syntactic theory, it remains largely unexplored in experimental work. In an effort to address this gap, we conducted two studies of external/internal agreement in Russian using self-paced reading and eye-tracking while reading. We measured the response to violations generated when native speakers encounter a noun that mismatches the features on an earlier element inflected for agreement (verb, modifying adjective, and predicative adjective). Both experimental studies found …

Endodontic Management Of Dens Invaginatus Using Dynamic Navigation System In Pediatric Patient: A Case Report, Ayesha Fathima, Sahana Selvaganesh, Ganesh Jeevanandan, Pradeep Solete, Prabahdevi Maganur, Ather Syed Ahmed, Satish Vishwanathaiah

International Arab Journal of Dentistry

Dens invaginatus, also known as dens in dente, is a dental anomaly resulting from infolding the enamel organ into the dental papilla. Dynamic Navigation Systems (DNS) like Navident, offer real-time guidance during endodontic procedures, proving especially useful in complex cases, such as calcified canals or pulp obliteration. This case report presents a 13-year-old female, who reported the chief complaint of continuous pain in the upper left front tooth region. Based on the clinical and radiographical findings, a diagnosis of pulp necrosis and chronic periapical abscess in relation to maxillary canine (23) was established with dens invaginated palatal canal ( Oehler’s …

Receptiveness Of The Kindytxt Universal Early Literacy Texting Program By Parents From Low, Medium, And High Socioeconomic Communities, Susan M. Hill, Caroline Barratt-Pugh, Nicola F. Johnson, Lennie Barblett

Research outputs 2022 to 2026

The home literacy environment (HLE) plays an important role in children’s early literacy learning. Texting programs are an increasing feature of family literacy interventions that support parent engagement in their children’s learning. Unlike face-to-face interventions, texting programs can offer sustained parental support at low cost and large scale. Messages can be translated into other languages, saved and shared, thus potentially widening the influence on children’s HLEs. Most early literacy texting programs target families from disadvantaged communities, yet research suggests all families may benefit from guidance on supporting their children’s early literacy. This study examined the receptiveness of a universal early …

From ‘Raise The Age’ To ‘Raise The Awareness’: How Knowledge Affects Public Opinion Of The Minimum Age Of Criminal Responsibility In Western Australia, Suzanne Rock, Natalie Gately, Piero Moraro, James L. Finney

Research outputs 2022 to 2026

The minimum age of criminal responsibility (MACR) in Western Australia is 10 years old. While the negative impacts of early contact with justice systems have been well-documented and have resulted in calls to raise the age, research had not examined the public views of MACR in Western Australia. This article presents a novel examination of the knowledge and perceptions of the MACR with a sample of the West Australian public (n = 69). Findings from the semi-structured interviews revealed low levels of knowledge about the MACR, some reacted with surprise when provided with the information. Participants’ views shifted in that …

Identifying Potential Risk Areas Close To The Oil And Gas Pipelines Due To Subsidence In Qazvin Plain, Mahmoud Rajabi, Sanaz Vajedian, Ryan Smith, Neil Grigg, Hossein Nahavandchi, Mehdi Goli

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Surface displacement caused by natural and anthropogenic activities poses a significant risk to subsurface pipelines, particularly in areas experiencing subsidence. Stress and strain induced by deformation can lead to pipeline buckling and potential vulnerability. This study applies a multidisciplinary approach integrating interferometric synthetic aperture radar (InSAR) deformation analysis, well data, and geological context to assess the risk to oil and gas pipelines in Iran's Qazvin plain. The focus is on evaluating the impact of an unconfined aquifer, which has a lower risk of subsidence compared to a confined aquifer, on pipeline infrastructure. We analyzed multitemporal Sentinel-1 data collected between 2014 …

Leveraging Intrinsic Properties For Classification Of Coal Seams Towards Spontaneous Combustion Proclivity And Predicting Susceptibility Using Machine Learning: Smart And Sustainable Mining Approach, Siddhartha Agarwal, Pradeep K. Gautam, Yuhao Zou, Rishabh Dwivedi, Durga C. Panigrahi, Cihan H. Dagli, A. Singh

Engineering Management and Systems Engineering Faculty Research & Creative Works

Mine fires and other hazards caused by spontaneous coal combustion are a pervasive and longstanding issue in Jharia coalfields, India. This study proposes a novel approach to classify coal seams based on their propensity to spontaneous combustion using the intrinsic properties of 30 coal samples from different seams. This method eliminates the need for expensive and time-consuming experimental determinations of susceptibility indices (SI) such as crossing point temperature (CPT), critical air blast (CAB), and differential thermal analysis (DTA). All clustering models, viz. hierarchical, k-means, and multidimensional scaling, aptly classify coal seams into three categories: highly risky, medium risky, and low …

Data Management In Large-Scale Studies: A Handbook For Researchers, Sadia Muzaffar Bhutta, Aisha Naz Ansari, Sohail Ahmad, Wadhwani Nimarta

Institute for Educational Development Pakistan (IED-PK) Archives

This handbook presents insights and experiences on managing largescale data, shared by team members who contributed to six large-scale studies, including the AKU-IED Impact Study, EGRI-QEP, SMILO1, TCFSMILO, SMILO2, and PPP study. All these projects were funded by different organisations. We extend our gratitude to all research team members for their valuable experiential contributions to this handbook.

Encapsulating Student Perspectives: Investigating Students’ Voice In Urban Secondary Education, Treyvon L. Harlin

Wayne State University Dissertations

ABSTRACTEncapsulating Student Perspectives: Investigating Students’ Voice in Urban Secondary Education by Treyvon L. Harlin February 2025 Advisor: Ben Pogodzinski, Ph.D. Major: Educational Leadership and Policy Studies Degree: Doctor of Philosophy The research in this dissertation focuses on the implication of student voice in historically marginalized secondary schools throughout the metropolitan area of Detroit, Michigan. Research initiatives conducted by Delpit (2006), Holmes & Crossley (2004), and Levitan (2018) have shown that students, especially those of marginalized populations, must have a sense of safety, feel valued and that their opinions matter to have buy-in with academic objectives and a school’s vision. Unfortunately, …

Usability Testing Of A Bystander Bullying Intervention For Rural Middle Schools: Mixed Methods Study, Aidan Midgett, Diana M. Doumas, Claudia Peralta, Matthew Peck, Blaine Reilly, K.B. Butler

Counseling, Leadership, and Research Methods Faculty Publications and Presentations

Background: Targets of bullying are at high risk of negative socioemotional outcomes. Bullying programming in rural schools is important as bullying is more prevalent in those schools compared to urban schools. Comprehensive, school-wide bullying programs require resources that create significant barriers to implementation for rural schools. Because technology-based programs can reduce implementation barriers, the development of a technology-based program increases access to bullying prevention in rural settings. Objective: We aimed to conduct usability testing of a bystander bullying intervention (STAC-T). We assessed usability and acceptability of the STAC-T application and differences in usability between school personnel and students. We were …

Police Records And Rural Crime In 1940s Ireland: The Challenges Of Using Historical Documents As Primary Sources In Sociological Research, Clay Darcy

Research Outputs: 2025-Present

No abstract provided.

Legalist Realism, Mark A. Drumbl

FIU Law Review

This article explores the scholarly footprint of Professor Megan Fairlie. This is a footprint of 'legalist realism'. Professor Fairlie was greatly concerned with legalism, in other words, the centrality of due process, the rights of the defendant, and human dignity in trials of individuals accused of the most heinous crimes. She was committed to put the law in international criminal law. And her view was one of realism, notably, that the structure of international institutions must be mindful of power politics, and expectations and ambitions ought to recognize the limitations and possibilities of politics in order to retain legitimacy and …

Beyond Policy: Overcoming Challenges In Prosecuting Gender Persecution At The International Criminal Court, Yvonne M. Dutton, Milena Sterio

FIU Law Review

No abstract provided.

Peaking Today, Taking It Easy Tomorrow: Daily Performance Dynamics Of Working Long Hours, Lieke L. Ten Brummelhuis, Charles Calderwood, Christopher C. Rosen, Alison S. Gabriel

Management Faculty Publications and Presentations

Underlying the “ideal worker” image that pervades many organizational cultures is the assumption that working longer hours equates to higher performance, despite recovery research that suggests that long work hours might actually impair future work performance. In an effort to reconcile these differences in how long work hours are thought to relate to job performance, we develop and test a conceptual model in which daily boosts in same-day performance associated with working longer hours could be offset by lower next-day performance. More specifically, we examine if working a longer day than usual reduces sleep, which has the potential to diminish …

A Case Study Using The Transparency Framework And Artificial Intelligence To Promote Effective Writing And Student Success In A Writing-Intensive Course, Elizabeth A. Brown, Maria Kronenburg, Ashlee Steeley, Diana Tagbor

Health Behavior, Policy & Management Faculty Publications

Program evaluation data suggest that undergraduate students struggle with writing in a clear and concise manner and appropriately citing. Faculty implemented the plan-do study-act cycle to pilot the Transparency in Learning and Teaching (TILT) project framework and to explore the use of artificial intelligence (AI) and discuss approaches to using AI, along with the TILT framework, in a writing-intensive course to identify the pros and cons of using ChatGPT in an online classroom. The TILT framework reinforces adult learning by helping students clearly understand the assignment's purpose and establish a clear relationship between assignment and students' professional lives. Faculty encouraged …

Examining Low-Income Caregivers' Knowledge And Comprehension Of The Dental Caries Process, Melissa Sullivan, Denise C. Mckinney, Deanne Shuman, Qi Zhang

Dental Hygiene Faculty Publications

Purpose Dental caries among young children remains a public health concern in the United States (US). Children of caregivers with low oral health literacy (OHL) tend to have greater unmet dental needs and poorer oral health status. The purpose of this study was to examine the understanding of pediatric dental terms associated with the dental caries process among low-income caregivers.

Methods This study included 14 caregivers with children enrolled in a Special Supplemental Nutrition Program for Women, Infants and Children (WIC) in the Southeastern US. Through structured phone interviews, the validated Oral Health Literacy Inventory for Parents (OH-LIP) was used …

Nesting Population Trend Of The Leatherback Sea Turtle In Bocas Del Toro Province And Comarca Ngäbe-Buglé, Panama For The Period 2002–2022, Sonia Gutiérrez Parejo, Susan E. Piacenza, Raúl García, Cristina Ordóñez, Roldán A. Valverde

School of Earth, Environmental, & Marine Sciences Faculty Publications

Sea turtle biologists have made sustained efforts to understand the global status of leatherback sea turtle populations. However, despite progress in assessments, demographics, and ecology, key uncertainties persist in tracking leatherback population trends. Trend analyses have historically focused on nesting beaches, with nest counts providing a widely used index for population abundance. Here, we analysed 20 years of annual nest abundance at four main nesting beaches (Soropta, Bluff, Playa Larga and Chiriquí) in Bocas del Toro province and the Comarca Ngäbe-Buglé, Panama, which constitute the largest nesting leatherback sea turtle population in Central America. We conducted daily nest counts during …

Infants’ Resting-State Functional Connectivity And Event-Related Potentials: A Multimodal Approach To Investigating The Neural Basis Of Infant Novelty Detection, Dana Kanel, Santiago Morales, Kathryn Altman, John E. Richards, Anderson M. Winkler, Daniel Samuel Pine, Nathan A. Fox, Courtney A. Filippi

School of Medicine Publications

Individual differences in how the brain responds to novelty are present from infancy. A common method of studying novelty processing is through event-related potentials (ERPs). While ERPs possess millisecond precision, spatial resolution remains poor, especially in infancy. This study aimed to balance spatial and temporal precision by combining ERP data with functional magnetic resonance imaging (fMRI) data. Twenty-nine infants (15 female) underwent resting-state fMRI (Mage = 4.73 months) and electroencephalography (EEG) during a three-stimulus auditory oddball task (Mage = 5.19 months). The mismatch response (MMR) and P3 were computed from ERP data, and resting-state functional connectivity …

Forecasting Covid-19 Cases, Hospital Admissions, And Deaths Based On Wastewater Sars-Cov-2 Surveillance Using Gaussian Copula Time Series Marginal Regression Model, Hueiwang Anna Jeng, Norou Diawara, Cynthia Jackson, Rekha Singh, Kyle Curtis, Raul Gonzalez, David Jurgens, Sasanka Adikari

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Modeling efforts are needed to predict trends in COVID-19 cases and related health outcomes, aiding in the development of management strategies and adaptation measures. This study was conducted to assess whether the SARS-CoV-2 viral load in wastewater could serve as a predictor for forecasting COVID-19 cases, hospitalizations, and deaths using copula-based time series modeling. SARS-CoV-2 RNA load in wastewater in Chesapeake, VA, was measured using the RT-qPCR method. A Gaussian copula time series (CTS) marginal regression model, incorporating an autoregressive moving average model and Gaussian copula function, was used as a forecasting model. Wastewater SARS-CoV-2 viral loads were correlated with …

Machine Learning Models For Pancreatic Cancer Survival Prediction: A Multi-Model Analysis Across Stages And Treatments Using The Surveillance, Epidemiology, And End Results (Seer) Database, Aditya Chakraborty, Mohan D. Pant

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background: Pancreatic cancer is among the most lethal malignancies, with poor prognosis and limited survival despite treatment advances. Accurate survival modeling is critical for prognostication and clinical decision-making. This study had three primary aims: (1) to determine the best-fitting survival distribution among patients diagnosed and deceased from pancreatic cancer across stages and treatment types; (2) to construct and compare predictive risk classification models; and (3) to evaluate survival probabilities using parametric, semi-parametric, non-parametric, machine learning, and deep learning methods for Stage IV patients receiving both chemotherapy and radiation. Methods: Using data from the SEER database, parametric models (Generalized Extreme Value, …

Engineering Ethics Education Bingo 1.0, Shannon Chance, Mike Murphy, Celina P. Leão, M. Tobosaru, Mary Nolan

Research Outputs: 2025-Present

This paper introduces Engineering Ethics Education (EEE) Bingo 1.0, an active learning tool designed to support ethics education among engineering educators. Drawing inspiration from game-based learning, EEE Bingo provides a playful yet purposeful framework for exploring diverse pedagogical approaches in engineering ethics. The game stimulates discussion and reflection on the alignment between ethical issues and suitable teaching methods, promoting greater pedagogical awareness and collaboration. This paper outlines the motivation behind the game, its structure and rules, and illustrative examples. EEE Bingo encourages critical engagement with teaching strategies, reinforcing the importance of contextualized, interdisciplinary, and reflective ethics education.

Accreditation Considerations In Engineering Ethics Education: Bridging Global Standards And Local Practices: Bridging Global Standards And Local Practices, Louise O'Gorman, Alison Gwynne-Evan, Leah Ridgeway, Marek Rebow, Shannon Chance

Research Outputs: 2025-Present

Accreditation can drive curricular innovation and change in engineering and can have a role in encouraging students' development of ethics-related competencies. Despite engineering educators' competence in the technical aspects of design and research, there can be an element of discomfort in planning and delivering lessons relating to ethics that span social justice, diversity and inclusion, environmental sustainability, and ethical theories. Because engineering accreditation can encourage and/or require the inclusion of ethical content in accredited engineering courses, the recently published Routledge Handbook of Engineering Ethics Education dedicated an entire section to the topic. This paper critically assesses the handbook's accreditation section …