Physical Sciences and Mathematics Commons^™

Coastal Flooding And Housing Market Liquidity: Policy Implications For Eastern U. S. Communities, Wai Yan Siu, Rex Sitti

ODU Articles

Coastal flooding poses an escalating threat to communities across the U.S East Coast, where rising sea levels and intensifying storms increasingly overwhelm existing infrastructure and natural defenses. These events generate complex economic consequences that extend beyond immediate property damage to affect community stability and long-term development patterns. The real estate industry in particular, faces increasing levels of flood risk. Existing research on climate risk and real estate markets focuses predominantly on price capitalization effects, overlooking the critical dimension of housing market liquidity. This study examines the causal impact of coastal flooding on days-on-market (DOM), a metric of liquidity in the …

Landslide At River's Edge: Alum Bluff, Apalachicola River, Florida, Joann Mossa, Yin-Hsuen Chen

Center for Geospatial Science, Education & Analytics Faculty Publications

When rivers impinge on the steep bluffs of valley walls, dynamic changes stem from a combination of fluvial and mass wasting processes. This study identifies the geomorphic changes, drivers, and timing of a landslide adjacent to the Apalachicola River at Alum Bluff, the tallest natural geological exposure in Florida at similar to 40 m, comprising horizontal sediments of mixed lithology. We used hydrographic surveys from 1960 and 2010, two sets of LiDAR from 2007 and 2018, historical aerial, drone, and ground photography, and satellite imagery to interpret changes at this bluff and river bottom. Evidence of slope failure includes a …

Drone-Based Medication Delivery For Rural, Flood-Prone Coastal Cities, Yin-Hsuen Chen, Amro M. El-Adle, Kevin J. O'Brien, Taylor Wentworth, Heather G. Richter

Center for Geospatial Science, Education & Analytics Faculty Publications

Access to healthcare remains a critical challenge for rural populations, particularly in flood-prone coastal communities where transportation barriers limit access to essential medical services. This study evaluates the effectiveness of drone-based medication delivery in improving healthcare accessibility for vulnerable populations on Virginia’s Eastern Shore. Compared to traditional personal vehicle travel, drone delivery reduced trip times from up to 50 minutes to under 10 minutes for more than 80% of the population, including elderly patients. Using publicly available datasets, we developed two transportation vulnerability indices that incorporate age, travel time, and flood risk to prioritize patients for drone-based pharmaceutical delivery. These …

Restored Wetlands Show Rapid Vegetation Recovery And Substantial Surface-Water Expansion, Thilina D. Surasinghe, Yin-Hsuen Chen, Kunwar K. Singh

Center for Geospatial Science, Education & Analytics Faculty Publications

Ecological restoration is essential for improving the ecological integrity of degraded ecosystems to enhance ecosystem services and biodiversity. In this study, we assessed the effectiveness of wetland restoration on retired cranberry farms by analyzing vegetation recovery and surface-water dynamics using the enhanced vegetation index (EVI) and normalized difference water index (NDWI) derived from Sentinel-2 satellite imagery. To quantify temporal dynamics of both vegetation recovery and surface-water cover, we identified the spectral distinctions among restored wetland plant communities. Our results indicated the emergence of distinct plant communities upon restoration. Restored wetlands in general showed significant and progressive vegetation recovery and expanding …

Fabrication Of Thylakoid Membrane-Based Photo-Bioelectrochemical Bioanode For Self-Powered Light-Driven Electronics, Amit Sarode, Gymama Slaughter

Center for Bioelectronics Publications

The transition toward sustainable and decentralized energy solutions necessitates the development of innovative bioelectronic systems capable of harvesting and converting renewable energy. Here, we present a novel photo-bioelectrochemical fuel cell architecture based on a biohybrid anode integrating laser-induced graphene (LIG), poly(3,4-ethylenedioxythiophene) (PEDOT), and isolated thylakoid membranes. LIG provided a porous, conductive scaffold, while PEDOT enhanced electrode compatibility, electrical conductivity, and operational stability. Compared to MXene-based systems that involve complex, multi-step synthesis, PEDOT offers a cost-effective and scalable alternative for bioelectrode fabrication. Thylakoid membranes were immobilized onto the PEDOT-modified LIG surface to enable light-driven electron generation. Electrochemical characterization revealed enhanced redox …

Spatiotemporal Patterns Of Desertification Sensitivity And Influencing Factors Across The Western Inner Mongolia Plateau, China, Yang Chen, Long Ma, Xixi Wang, Tingxi Liu, Zixu Qiao

Civil & Environmental Engineering Faculty Publications

Desertification remains a critical global ecological and environmental challenge that threatens sustainable development. Although our understanding of desertification dynamics and their underlying drivers has improved, continued research is needed due to the region-specific nature of these processes. This study focuses on the Western Inner Mongolia Plateau in China as a case study to examine the evolution of desertification and its driving factors using a multifaceted approach, including the Mediterranean Desertification and Land Use (MEDALUS) model. Results show that the desertification sensitivity index (DSI) across the plateau ranged from 1.12 in prairie regions to 1.87 in desert areas, with a spatial …

A Global Application Programming Interface-Enabled Earthquake Ground Motion Relational Database For Engineering Applications, Tristan E. Buckreis, Chukwuebuka C. Nweke, Pengfei Wang, Scott J. Brandenberg, Maria E. Ramos-Sepúlveda, Rashid Shams, Shako Mohammed, Renmin Pretell, Silvia Mazzoni, Paolo Zimmaro, Jonathan P. Steward

Civil & Environmental Engineering Faculty Publications

We present a application programming interface (API)-enabled relational database of global earthquake ground motion intensity measures, associated metadata, and processed time-series data. Raw ground motion records were processed by the authors using either manual or semi-automated processing procedures, and every processed record has passed a quality review by a trained analyst. Computed intensity measures include peak acceleration and velocity, pseudo-spectral acceleration response spectra, cumulative absolute velocity, Arias Intensity, and Fourier amplitude spectra. The processed time-series data, associated metadata, and ground motion intensity measures were organized into a web-served relational database consisting of 32 tables connected by primary/foreign key pairs. Ground …

Laboratory Investigation Of Shape And Initial Orientation Effects On Surf Zone Object Migration, Temitope E. Idowu, Jack A. Puleo

Civil & Environmental Engineering Faculty Publications

Discarded objects like munitions in marine environments pose public safety risks. The behavior of various density objects deployed at four cross-shore positions in the surf zone of a large-scale 120 m x 5 m x 5 m wave flume were observed under different forcing conditions. Net migration was predominantly directed offshore, with approximately 70 % offshore migration observed near the outer surf zone. Density, shape, and initial orientation were identified as important to object behavior, with density acting as the dominant driver in 67 % of the object pairing scenarios. The influence of shape and initial orientation on net migration …

Empirical Vulnerability Function Development Based On The Damage Caused By The 2014 Chiang Rai Earthquake, Thailand, Patcharavadee Hong, Masashi Matsuoka

Institute for Innovation & Entrepreneurship Publications

Seismic hazards in Thailand are frequently overlooked in disaster management planning, leading to insufficient research and significant economic losses during earthquake events. The 2014 Chiang Rai earthquake exposed critical vulnerabilities in Thailand's building practices due to widespread non-compliance with building codes and limited preparedness. This exposure prompted the development of empirical vulnerability functions using loss data from 15,031 damaged residences. The study analyzed government compensation records, which were standardized using replacement cost metrics. Three distinct models were developed through probabilistic and possibilistic modeling approaches. Residual analysis demonstrated the superior performance of the possibilistic approach, with the Possibilistic-based Vulnerability Function achieving …

Wasting Disease Of A Marine Foundation Species Links Community Interactions To Disease Dynamics, Lillian R. Aoki, Olivia J. Graham, Reyn M. Yoshioka, Rebecca Maher, Lindsay Alma, Eileen E. Hofmann, Colleen A. Burge, Drew Harvell, Maya L. Groner

CCPO Publications

Infectious disease plays a key role in shaping marine communities, including in seagrass meadows, which form biodiverse coastal habitats. Eelgrass (Zostera marina) is the most widespread seagrass species and is susceptible to seagrass wasting disease, caused by the protist Labyrinthula zosterae. As a foundation species, eelgrass strongly influences ecosystem structure, function and services; recent work has begun to explore the links between critical community interactions and seagrass wasting disease. Here, we highlight recent advances about how the eelgrass community regulates and responds to seagrass wasting disease, from the microbiome to herbivores and filter feeders. We further show …

Surface Currents In The Mid-Atlantic Bight: The Role Of The Gulf Stream Versus Wind, Tal Ezer

CCPO Publications

Surface currents of the Mid-Atlantic Bight (MAB) were studied using high frequency radar (HFR) observations at 6 km resolution during a five-year period (2020-2024). The study's focus on the role of the Gulf Stream (GS) contrasts with most past studies that focused on the seasonal wind-driven currents. Empirical Orthogonal Function (EOF) analyses of the daily HFR currents were conducted with and without the GS, revealing modes of current variability linked to the seasonal wind pattern and storms versus modes linked to GS variability. The remote impact of the GS on coastal currents is complex, with different impacts seen on different …

Comparing Surface Currents Near The Mouth Of Three Bays Along The U.S. East Coast: Chesapeake Bay, Delaware Bay, And New York Bay, Tal Ezer, Teresa Updyke

CCPO Publications

Monthly surface currents at 2 km resolution near the mouths of three U.S. east coast bays were obtained from high-frequency radars (Coastal Ocean Dynamics Application Radar, CODAR) during 2012–2024. The currents near these bays, the Chesapeake Bay (CB), the Delaware Bay (DB) and the New York Bay (NB) were analyzed to infer similarity and differences, as well as potential common forcing from regional and basin-scale factors. The contribution to flow variability from local and remote forcing is evaluated by comparing surface currents with (a) river discharges into each bay, (b) with local and regional winds, and (c) with the North …

Preparing The Built Environment In Grenada For Future Sea Level Rise And Extreme Precipitation Events, Rocco D. Boyd, Meagan P. Duncan, Alivia D. Markham, Adelle K. Novak, Blaizen B. Bloom, Ashawne Edwards, Jai S. Lewis, Hans-Peter Plag

CCPO Publications

[Introduction] Communities across the globe are being affected by climate change in numerous ways. However, those most often affected, especially by sea level rise, are those small island nations that are pressed for space already; this includes the island of Grenada. Grenada is located in the southern portion of the Caribbean and is bordered by the Caribbean Sea (West) and the Atlantic Ocean (East). The planning and development authority (PDA) has been identified as the main stakeholder involved in this case study, but recommendations will be made to all parties involved to best accomplish our mission.

Key stakeholders were initially …

Multi-Model Estimate Of Antarctic Ice-Shelf Basal Mass Budget And Ocean Drivers, Benjamin K. Galton-Fenzi, Richard Porter-Smith, Sue Cook, Eva Cougnon, David E. Gwyther, Wilma G. C. Huneke, Madelaine G. Rosevear, Xylar Asay-Davis, Fabio Boeira Dias, Michael S. Dinniman, David Holland, Kazuya Kusahara, Kaitlin A. Naughten, Keith W. Nicholls, Charles Pelletier, Ole Richter, Hélène Seroussi, Ralph Timmerman

CCPO Publications

Societal adaptation to rising sea levels requires robust projections of the Antarctic Ice Sheet's retreat, particularly due to ocean-driven basal melting of its fringing ice shelves. Recent advances in ocean models that simulate ice-shelf melting offer an opportunity to reduce uncertainties in ice–ocean interactions. Here, we compare several community-contributed, circum-Antarctic ocean simulations to highlight inter-model differences, evaluate agreement with satellite-derived melt rates, and examine underlying physical processes. All but one simulation use a melting formulation depending on both thermal driving (T^⋆) and friction velocity (u^⋆), which together represent the thermal and ocean current forcings at the …

Improving Understanding And Connections For Preparedness, Mitigation, Response, And Recovery For Tornado And Straight-Line Wind Events In Virginia: Summary Of The Inaugural Virginia Tornado And Straight-Line Wind Summit, Wie Yusuf, Monica Arul, Joshua Behr, Kaleen Lawsure, An Huy Pham, Henry Attivor

School of Public Service Faculty Publications

Background

The Virginia Tornado and Straight-Line Wind Summit, the first of its kind in the Commonwealth, was held on October 15, 2025 in Isle of Wight County, Virginia. The Summit had several goals, including:

• Understanding Virginia’s wind risk and learning the science behind it.
• Hearing lessons learned from emergency managers who have experienced extreme wind events.
• Learning about practical steps to prepare, mitigate, and respond to severe wind events.
• Learning best practices for timely and actionable communication with the public before and after events.
• Strengthening interagency coordination and connecting with others to share resources, align priorities, and coordinate resilience planning. …

Ai-Generated Messaging For Life Events Using Structured Prompts: A Comparative Study Of Gpt With Human Experts And Machine Learning, Christopher Lynch, Erik Jensen, Ross Gore, Virginia Zamponi, Kevin O'Brien, Brandon Feldhaus, Katherine Smith, Joseph Martínez, Madison H. Munro, Timur E. Ozkose, Tugce B. Gundogdu, Ann Marie Reinhold, Hamdi Kavak, Barry Ezell

VMASC Publications

Large Language Models (LLMs) play an increasingly integrated and pivotal role in generating diverse types of texts, such as social media messages, emails, narratives, and technical reports, among other textual communication forms. As AI-generated messaging filters into human communication, a systematic exploration of their effectiveness for mimicking human-like communication of life events is needed. In this study, we employ a zero-shot structured narrative prompt to generate 24,000 life event messages for birth, death, hiring, and firing events using OpenAI's GPT-4. From this dataset, we manually classify 2880 messages and evaluate their validity in conveying these life events through the form …

Advances In Bacterial Cellulose-Based Scaffolds For Tissue Engineering: Review, Rewati Raman Ujjwal, Gymama Slaughter

Center for Bioelectronics Publications

Bacterial cellulose (BC) has emerged as a highly versatile and promising biomaterial in tissue engineering, with potential applications across skin, bone, cartilage, and vascular regeneration. Its exceptional properties like high mechanical strength, superior biocompatibility, excellent moisture retention, and inherent ability to support cell adhesion and proliferation, make BC particularly effective for wound healing and skin regeneration. These attributes accelerate tissue repair and foster new tissue formation, highlighting its value in skin-related applications. Additionally, BC's capacity to support osteogenic differentiation, combined with its mechanical robustness, positions it as a strong candidate for bone tissue engineering, facilitating regeneration and repair. Recent advancements …

Evaluating The Long-Term Effectiveness Of Marsh Terracing For Conservation With Integrated Geospatial And Wetland Simulation Modeling, Nick Carpenter, Laura Costadone, Thomas R. Allen

ODU Articles

Coastal marshes provide essential ecosystem services, yet they are vulnerable to anthropogenic stressors and climate change, particularly sea level rise (SLR). Restoration approaches like marsh terracing have emerged as nature-based strategies to enhance resilience and reduce habitat loss. This study applies the Sea Level Affecting Marshes Model (SLAMM) to assess the potential of marsh terraces to mitigate future losses, while also examining the model’s limitations, including its assumptions and capacity to reflect complex marsh processes. A geospatial approach was used to generate 3D representations of terraces through morphostatic modeling within digital elevation models (DEMs). Under a no-restoration scenario, SLAMM projections …

Qos-Aware Link Adaptation For Beyond 5g Networks: A Deep Reinforcement Learning Approach, Ali Parsa, Neda Moghim, Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Modern wireless communication systems face increasingly complex challenges due to rapidly changing channel conditions and the growing diversity of application-specific Quality of Service (QoS) requirements. Traditional link adaptation mechanisms primarily aim to maximize throughput and often lack the flexibility to support emerging applications, such as Extended Reality (XR) and Virtual Reality (VR), which demand simultaneous guarantees for high data rates, ultra low latency, and high reliability. These stringent and multidimensional QoS needs call for more intelligent and adaptive solutions. In this paper, we propose QDRLLA (QoS-aware Deep Reinforcement Learning-based Link Adaptation), a novel framework that employs deep reinforcement learning to …

A Trust-By-Learning Framework For Secure 6g Wireless Networks Under Native Generative Ai Attacks, Md Shirajum Munir, Sravanthi Proddatoori, Manjushree Muralidhara, Trinidad Mario Dena, Walid Saad, Zhu Han, Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Sixth-generation (6G) wireless networks will become vulnerable due to native generative AI (GenAI)-driven intelligent poisoning attacks in both the radio unit and the core network. In particular, network parameters and metrics in cross-layer design pose fundamentally uncertain conditions and can be compromised through the native GenAI mechanism, which leverages data augmentation and reconstruction capabilities. This work investigates the capabilities of native GenAI to create novel poisoning attacks in wireless networks, while investigating their impact through uncertainty-informed root analysis. Then, detected attacks are mitigated by developing a trustworthy service aggregation in the wireless network. First, a joint decision problem is formulated …

Examining Non-Traditional Online Learners' Ownership Of Learning In The Context Of Chatgpt-Facilitated Design, Mohan Yang, Tian Luo, Kristin Herman, Belle Li, Shanan Chappell Moots, Noah Glaser, Shiyan Jiang

STEMPS Faculty Publications

Generative artificial intelligence (GenAI) offers potential solutions to educational challenges by personalizing learning experiences for diverse learners. However, it also introduces complexities around issues of ownership of learning. As an indicator of empowered learning, ownership is a multifaceted but underexplored concept. In this study, the authors adopted a mixed-methods multiple-case study design to explore non-traditional online students’ perceived ownership of learning when using ChatGPT for instructional design. The authors adopted the psychology ownership construct consisting of self-efficacy, accountability, belongingness, and self-identity as the theoretical framework. Findings revealed students’ prior AI experiences and educational levels played a significant role in their …

Socially Shared Regulation Of Learning And Artificial Intelligence: Opportunities To Support Socially Shared Regulation, Jinhee Kim, Rita Detrick, Seongryeong Yu, Yukyeong Song, Linda Bol, Na Li

STEMPS Faculty Publications

Supporting learners in achieving high-level socially shared regulation of learning (SSRL) in the online collaborative learning (OCL) context presents challenges that the utilization of artificial intelligence (AI) technologies may help solve. However, the effective uses of AI to support multifaceted areas (cognition, metacognition, and motivation) and phases (forethought, performance, and reflection) of SSRL remain elusive. Furthermore, research on developing an educational AI and what pedagogical attributes and elements are required for AI to support students' SSRL effectively is limited. This study, therefore, aims to investigate students' perceptions of AI applications in enhancing SSRL and to explore the essential pedagogical elements …

Leveraging Custom Gpts For Formative Assessment And Feedback, Nari Kim, Jason Vickers, Shaimaa Alyehaibi, Chikezie Ozuzu, Xinyue Ren, Suhasini Kotcherlakota

STEMPS Faculty Publications

As artificial intelligence (AI) advances, the use of custom generative pre-trained transformers (Custom GPTs) in formative assessments opens new opportunities for improving student learning and engagement. Custom GPTs increase cognitive and emotional engagement by providing timely, context-sensitive, and tailored responses based on unique learner profiles. This paper aims to investigate how custom GPT-driven formative feedback can enhance individualized learning experiences and improve student performance. This paper will discuss the promise of this AI tool, the challenges associated with its application, and recommendations for educators and academics looking to use these technologies for formative assessments.

The Integration Of Artificial Intelligence And Ontologies: Transformations In Knowledge Representation And Application, Grazia Serratore, Julaine Clunis

STEMPS Faculty Publications

Artificial Intelligence (AI) is reshaping the landscape of knowledge representation. There is an increasingly strong bidirectional relationship, between AI techniques and ontologies. AI techniques revolutionized traditional, manual ontology development and contribute to automated ontology construction, while ontologies enhance the performance of AI systems and their semantic accuracy. Through a comprehensive review of current literature, this paper aims to examine: i) how Machine Learning (ML) techniques contribute to the automated construction, refinement, and validation of ontologies; ii) the most widely used and effective ML approaches for ontology construction; iii) how domain-specific requirements influence the selection and adaptation of AI techniques for …

Exploring The Impact Of Generative Ai Chatgpt On Critical Thinking In Higher Education: Passive Ai-Directed Use Or Human-Ai Supported Collaboration?, Nesma Ragab Nasr, Chih-Hsiung Tu, Jennifer Werner, Tonia Bauer, Cherng-Jyh Yen, Laura Sujo-Montes

STEMPS Faculty Publications

Generative AI is weaving into the fabric of many human aspects through its transformative power to mimic human-generated content. It is not a mere technology; it functions as a generative virtual assistant, raising concerns about its impact on cognition and critical thinking. This mixed-methods study investigates how GenAI ChatGPT affects critical thinking across cognitive presence (CP) phases. Forty students from a four-year university in the southwestern United States completed a survey; six provided their ChatGPT scripts, and two engaged in semi-structured interviews. Students’ self-reported survey responses suggested that GenAI ChatGPT improved triggering events (M = 3.60), exploration (M = 3.70), …

Designing Ai-Powered Learning: Adult Learners' Expectations For Curriculum And Human-Ai Interaction, Jinhee Kim, Seongryeong Yu, Rita Detrick, Xi Lin, Na Li

STEMPS Faculty Publications

Despite the potential benefits offered by GenAI technologies to provide innovative solutions to address distinct challenges faced by working adult learners (ALs) in higher education and beyond, there is limited understanding of how best to structure AI-powered learning for this population while ensuring their distinct needs and perspectives are considered. Hence, this study aimed to determine what curriculum and student-AI interaction would be required by situating ALs’ views. Through analyzing 48 e-portfolios and in-depth interviews with 20 ALs from diverse educational and professional backgrounds, the study found that ALs perceived content mastery and developing a lifelong habit of learning as …

Artificial Intelligence In Cancer-Related Malnutrition And Cachexia: A Transformative Tool In Clinical Nutrition, Salvatore Carbone

EVMS School of Health Professions Faculty Publications

[Introduction] Malnutrition and cachexia are common complications in cancer patients, and they negatively influence prognosis, treatment efficacy, and tolerability as well as quality of life [[1], [2], [3]]. Accurately identifying and effectively managing malnutrition and cachexia in this population remains a clinical challenge. Conventional validated screening tools may lack the sensitivity and specificity required for early detection and personalized intervention in diverse cancer types and treatment settings [4,5]. Over the last decade, the use of artificial intelligence (AI), including machine learning (ML) and deep learning (DL) strategies, has shown promising results in clinical nutrition, with the potential to revolutionize nutritional …

Automation To Autonomy: Temporal Dynamics Of Trust And Visual Attention Allocation Did Not Evolve, Tetsuya Sato, Eric Chancey, Yusuke Yamani

Psychology Faculty Publications

Emerging work environments are expected to implement autonomy that performs various functions without human input. Previous works has shown that trust in automation is negatively correlated with visual attention allocation, indicating that trust is a dynamic construct. Moreover, trust in automation and trust in autonomy appears to evolve in similar ways. However, recent work has demonstrated differences between trust in automation and trust in autonomy within Kaber’s (2018) theoretical framework (Sato et al., 2023b). Yet, it is uncertain whether the development of trust and visual attention allocation differs between automation and autonomy. The present study examined the temporal dynamics of …

Analyzing Visual Attention In Virtual Crime Scene Investigations Using Eye-Tracking And Vr: Insights For Cognitive Modeling, Wen-Chao Yang, Chih-Hung Shih, Jiajun Jiang, Sergio Pallas Enguita, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

Understanding human perceptual strategies in high-stakes environments, such as crime scene investigations, is essential for developing cognitive models that reflect expert decision-making. This study presents an immersive experimental framework that utilizes virtual reality (VR) and eye-tracking technologies to capture and analyze visual attention during simulated forensic tasks. A 360° panoramic crime scene, constructed using the Nikon KeyMission 360 camera, was integrated into a VR system with HTC Vive and Tobii Pro eye-tracking components. A total of 46 undergraduate students aged 19 to 24–23, from the National University of Singapore in Singapore and 23 from the Central Police University in Taiwan—participated …

Flux-Weakening Control Methods For Permanent Magnet Synchronous Machines In Electric Vehicles At High Speed, Samer Alwaqfi, Mohamad Alzayed, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Permanent magnet synchronous motors (PMSMs) are widely favored by manufacturers for use in electric vehicles (EVs) because of their many benefits, which include high power density at high speeds, ruggedness, potential for high efficiency, and reduced control complexity. However, since the Back Electromotive Force (EMF) increases proportionally with the motor’s rotational speed, it must be carefully controlled at high speeds. Flux-weakening (FW) control is required to avoid excessive electromagnetic flux beyond the power source and inverter’s voltage restrictions. This paper aims to compare various FW control strategies and analyze their effectiveness in maximizing the speed of PMSMs in EV applications …