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Real-Time Anomaly Detection in OT Networks Using GRU-Based Autoencoders
Get PDFOperational Technology (OT) networks, particularly those used in critical infrastructure, face increasing cyber threats that target network-level protocols and behaviors. While most anomaly detection research for OT systems has traditionally relied on sensor data, this thesis explores the viability of detecting malicious activity directly from network telemetry. We propose a sequence-to-sequence autoencoder model based on Gated Recurrent Units (GRUs) with multilevel attention, trained to reconstruct normal patterns of packet-level communication extracted from raw PCAP data. The developed feature engineering pipeline integrates general networking attributes such as IP and MAC addresses, ports, and transport protocols with OT-specific protocol information from Modbus and DNP3. In the first-ever machine learning–based analysis of a recently released OT dataset, models were trained and evaluated at varying sequence lengths (25, 50, and 100 packets) to determine optimal performance trade-offs. Only the model trained on 100- packet sequences (Seq100) yielded meaningful detection performance, achieving approximately 81% precision in a partially labeled scenario and identifying half of the known attacker network artifacts within the dataset. Temporal visualization of reconstruction errors indicated alignment with known attack periods. In contrast, per-feature error analysis highlighted that high-cardinality fields such as ports and application protocols contributed most significantly to anomaly detection. To evaluate practical applicability, the Seq100 model was quantized, exported to ONNX, and deployed on an AMD Neural Processing Unit (NPU) and an NVIDIA V100 GPU. With a mean inference time of just 5.6 milliseconds on the NPU, the model demonstrated strong real-time feasibility in resource-constrained environments. This thesis establishes a foundation for deploying interpretable, real-time anomaly detection systems based on unsupervised deep learning techniques in OT networks, demonstrating both strong detection capability and practical inference efficiency
Thermal Design and Control of a PCB-based Solid-State Gas Generator (SSGG) Heater for Space Applications
Get PDFThis thesis presents the development and experimental validation of a compact, solid-state gas generator (SSGG) heater integrated into a printed circuit board (PCB) for use in satellite deorbiting systems. Designed for CubeSat-class spacecraft, the system produces gas via the thermal decomposition of sodium azide (NaN₃). The project emphasizes minimal mass, low power consumption, and mechanical simplicity – key constraints for modern space missions. The heater system relies on Joule heating through patterned copper coils embedded within the PCB structure. NaN₃ is deposited into wells drilled into the board surface, where localized heating initiates its decomposition near 300°C. A range of PCB configurations were designed and fabricated to assess the influence of geometric and electrical parameters on thermal performance. Experimental testing revealed that higher initial coil resistance correlates strongly with improved thermal localization and efficiency. Coils placed within inner copper layers offered greater thermal retention and structural robustness, while strategic reductions in copper area around the wells enhanced heat focus. These findings guided the development of a final 6-layer modular design capable of achieving the desired decomposition temperature reliably and repeatably. The result is a 4x4 array of compact heating elements, each functioning independently but integrated into a unified architecture scalable to different mission sizes. Additional features, such as edge-mounted diodes and automated data acquisition, support precise control and monitoring during operation. Testing conducted in Earth conditions confirmed the system’s ability to reach decomposition temperatures, with improved efficiency anticipated in the vacuum of space due to reduced convective losses. This design provides a lightweight, manufacturable solution for small satellite missions and a foundation for future gas-based deorbiting technologies
The Future of Fashion: A Systematic Literature Review on Consumer Willingness to Pay for Green Apparel
Get PDFIn recent years, consumers have become highly aware of the environmental impact of their purchases, specifically of apparel products. Accordingly, apparel brands have increasingly focused on enhancing the sustainability of their product offerings to attract environmentally conscious consumers and elevate their brand image (Dangelico et al., 2022). Furthermore, most sustainably produced products are priced higher for consumers compared to standard alternatives (Elmanadily & El-Deeb, 2022). Research has shown that consumers can accept higher prices for products that do less harm to the environment (Gomes et al., 2023), but it has yet to be determined in which cases this is consistently true.
Willingness to pay (WTP) is an economic concept defining the amount of money an individual is willing to forgo to obtain a product or gain a higher degree of a particular attribute (Narayanan & Singh, 2023), making it a valuable measure for evaluating consumers’ assessment of green product attributes. The purpose of this study is to develop an integrative framework of consumers’ willingness to pay (WTP) more for environmentally friendly apparel products through conducting a systematic literature review (SLR). Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to locate and extract relevant articles, this study systematically reviews the pertinent literature. The findings are enriched through the application of the Theories-Characteristics-Contexts-Methods (TCCM) framework.
Guided by the research questions, this systematic review first analyzes the definitions of green apparel across the retained articles. A key finding of this review is regarding the absence of a unifying definition for classifying green products. Varying definitions of green apparel are shown to be a significant barrier for both consumer behavior research and consumer education. Second, this review identifies patterns across WTP measures in research. The findings demonstrate that there are several barriers leading to a lack of comparability of measures across WTP research. Suggestions for addressing this barrier are provided. Third, this review presents theories, contexts, characteristics, and methods (TCCM) that have been utilized in green apparel WTP research. Patterns highlighted through the application of the TCCM framework provide an overview of the present standing of the research domain. Fourth, this review analyzes outcomes associated with green apparel attributes. Interestingly, other product and respondent characteristics were shown to influence WTP more significantly than specific green attributes in and of themselves. Fifth, the influence of sociodemographic characteristics on WTP is evaluated. Lastly, this study provides future research directions.
In conclusion, the studies in the review agree that consumers are generally willing to pay a premium for green attributes in apparel, though the amount varies based on many considerations. The amount of premium consumers are WTP has been shown to be impacted by green attribute type, other product attributes, labeling or information provided about the green product, and individual consumers’ values and attitudes. Research concludes that translating consumers’ expressed WTP into actual purchasing behavior is a leading issue in the domain. Furthermore, the formulation and adoption of a universal definition of green apparel could significantly positively impact future research on the topic
Development of a Degradation Methodology for Introducing Thermal Performance Deterioration of TIMs to Quantify Reliability Metrics of Electronic Packages
No full textPower densities of electronic devices, specifically, integrated circuits (ICs) or chips, continue to rise significantly, generating considerable amounts of heat. These thermal load increases are detrimental to the performance and service life of chips within central processing units (CPUs) and graphics processing units (GPUs). These microprocessors are encompassed in electronic packages that provide several vital roles, most importantly heat removal. This is achieved by utilizing integrated heat spreaders and heat sinks that interact with various cooling architectures. However, surface deformities between components heavily limit the contact area for adequate heat transfer from the package. Thermal interface materials (TIMs) are incorporated into these high contact resistance regions, replacing non-conductive air gaps with conductive material that can conform to surface disparities. This improves the conduction thermal pathway and decreases abrupt temperature rises. However, TIMs experience extremely hostile conditions during their service life, deteriorating the thermal performance immensely and putting sensitive components at risk of failure. Numerous degradation trends have been observed in literature across a variety of TIMs, but only a handful of attempts at characterizing TIM degradation into predictive empirical models of thermal resistance. Furthermore, these predictive models were only subjected to thermal aging conditions or humidity stresses, with no models pertaining to stress conditions exhibited by processors. Additionally, the influence of TIM degradation on package reliability has not been explored in literature, potentially leading to overestimates of device lifetimes. In this thesis, a commercial TIM is subjected to power cycling conditions to replicate the thermo-mechanical stress conditions of a processor using a temperature difference (ΔT) of 75 °C and 85 °C, respectively. Quantifying the thermal resistance of the TIM was completed using a thermal circuit analysis and verified using steady-state thermal ANSYS simulations. Temperatures were measured using a thermocouple integrated into the heater placed on the TIM and an infrared camera that measured the temperature of the substrate underneath the TIM, with the substrate’s thermal resistance being accounted for in the thermal circuit analysis. The different stress conditions were plotted to analyze the degradation trends and develop a novel mathematical model to predict the thermal resistance of the TIM under power cycling conditions. Next, a methodology was established to examine the impacts of TIM degradation on the chip, specifically, its reliability, prognostics, and performance. The degradation models ascribed from literature were leveraged to emulate TIM degradation behaviors and applied to an electronic package frequently employed in server racks to develop critical relationships between electronic packages and TIM degradation
Using Scaffolding, Gamification, and Self Awareness to Create Responsive UX/UI in CAD Software to Nurture Metacognition in Novice Users
Get PDFComputer-aided Design (CAD) software represents a significant shift from manual and analog design processes to digital workflows, offering substantial utility, accuracy, and productivity benefits. However, CAD software often presents a steep learning curve, particularly for novice users who are new to the software or possess only basic knowledge. Traditional CAD curricula have predominantly focused on technical problem-solving—teaching tools and systems—while often neglecting strategic knowledge that encompasses reflection, planning, and refining, which are essential components of metacognition. Metacognition is crucial for transforming novices into experts who use fewer and more complex commands, employ sophisticated planning, and achieve their goals more efficiently.
This research’s conceptual framework is based on Scaffolding, Gamification, and Self-Awareness theories to realign the learning continuum toward nurturing metacognition through a Responsive User Experience (UX) and User Interface (UI). The framework comprises three interconnected components: Accessibility, Customization, and Awareness. Accessibility reduces cognitive load by removing barriers to understanding, making it easier for novice users to grasp complex concepts and tools. Customization enhances engagement by tailoring user interfaces to individual needs and preferences, making the learning experience more engaging and motivating. Scaffolding Theory supports breaking complex tasks into manageable steps with guided assistance, feedback, instruction, and guidance. Gamification drives behavioral feedback loops through human-computer interactions, enhancing engagement and motivation. Self-awareness theory, particularly Feuerstein’s Mediated Learning Experience (MLE), addresses gaps in metacognition by fostering informed, mindful decision-making. This framework aims to create a collaborative learning environment where teachers, students, and software interact seamlessly to transform novices into experts. Primary research focused on a lesson and a workshop with novice users utilizing UX/UI modifications to existing CAD programs to test theory efficacy. The research was used to develop a toolkit for educators to redesign arts curricula using innovative UX/UI modifications, thereby enhancing learning outcomes with 3D CAD software and 3D printing. This toolkit will be implemented during the University of Arkansas, School of Art’s first annual Arkansas Art Educator ArtLab in June, 2025
Development and Investigation of a Novel Near-Wall Methodology for Large-Eddy Simulation Based on Dynamic Hybrid RANS-LES
Get PDFThe use of computational fluid dynamics (CFD) to test engineering designs with reduced cost and time compared to physical testing has become increasingly common in a range of industries and research fields. While numerical methods exist that can accurately solve the equations that govern the flow of fluids, these methods are computationally expensive for practical engineering problems due to the large amount of computational power needed to resolve the fluid flow over the entire range of length and time scales. Several different approaches have been introduced to address this computational cost issue, namely Reynolds-averaged Navier-Stokes (RANS) modeling and scale resolving methods. Reynolds averaging is the least computationally expensive approach, however due to assumptions made in the formulations this method also tends to be the least physically accurate as it only solves for the mean flow field. Scale resolving approaches such as Large-Eddy simulation (LES) provide more accurate results by resolving the large turbulent eddies primarily responsible for momentum and energy transfer. In free shear flows the grid resolution requirements for LES models are comparable in size to that of RANS models. However, for LES to produce accurate results for wall bounded flows by resolving even the largest eddy present in the boundary layer, the computational grid must be significantly more refined than that of RANS simulations. Hence, fully resolved LES for wall-bounded flows remain computationally expensive and are rarely used for simulation of practical engineering problems. There have been several different methods presented to mitigate the cost of modeling in the near wall region while still providing results that are comparable to fully resolving the eddies in this region.
The present work presents a new approach for wall modeling in large-eddy simulation. The wall mean resolved LES method (WMRLES) utilizes the dynamic hybrid RANS-LES (DHRL) framework to solve a RANS model in the near wall region and transition to LES further from the wall. This approach differs from other hybrid RANS-LES methods. The choice of RANS model differs as a zero-equation mixing length model is used. This does not require the solution of additional transport equations, significantly reducing computational cost. Since the transition between RANS and LES modes is affected by a physics-based blending function which is computed locally in the flow domain, prior knowledge of the flow is not required to denote RANS and LES regions prior to the simulation. Finally, WMRLES does not require the use of analytical or numerical wall functions, which are limited in their flexibility and universality for numerical simulations. The new modeling approach is developed, presented, and applied to two separate classes of problem: an attached boundary layer case represented by a fully developed channel flow and a separated shear layer case represented by a two-dimensional channel with periodic restrictions. Results are compared to available direct numerical simulation data and other wall modeling methods. The new method is found to produce results comparable to the full dynamic hybrid RANS-LES method in terms of accuracy, while using a simpler and more computationally efficient implementation
Understanding and Redesigning Membrane-based Unit Operations for Bioseparations
No full textThe biopharmaceutical industry has developed dramatically in the past decades, alleviating and curing numerous diseases that are not curable with traditional therapies. However, producing biopharmaceuticals is a challenging, complex, and expensive process. Membrane-based technologies have been widely used in biopharmaceutical production, especially downstream processing steps, including clarification, polishing, and other unit operations.
Our research interests focus on the production of two major biopharmaceutical categories: monoclonal antibodies (mAbs) and adeno-associated virus (AAV) vectors. Monoclonal antibodies are the largest class of approved biopharmaceuticals, with more than 130 mAb-based therapies having received regulatory approval in the United States or the European Union. In contrast, AAV-based gene therapy is an emerging but rapidly evolving field. Although there are only five FDA-approved treatments as of June 2024, AAV has attracted considerable research interest due to its potential for gene delivery. Currently, hundreds of AAV-based gene therapies are in various stages of clinical trials.
This study explored the application of membrane technologies for both clarification and polishing steps in producing mAb and AAV capsids. The investigation was divided into four key areas. Firstly, foulants associated with ATF membrane filters employed in mAb production using a perfusion cell culture system were analyzed. Secondly, the removal of mAb aggregates was investigated using environmentally responsive HIC membranes. Thirdly, the clarification of HEK cell lysate for AAV production was achieved using BioOptimal membrane filters in TFF and diafiltration mode to enhance AAV recovery. Finally, the separation of empty and full AAV capsids was examined by applying multimodal AEX membranes
Physiological and Molecular Responses of Diverse Rice Genotypes under Drought Stress
Get PDFClimate change-induced drought stress is a significant constraint on global rice (Oryza sativa L.) production, threatening food security. This study evaluated the drought resilience of 15 diverse rice genotypes from the USDA mini-core collection under field, greenhouse, and osmotic stress conditions. Field trials assessed reproductive-stage drought tolerance based on panicle length (PL), number of spikelets per panicle (NSP), and spikelet sterility (SS). Greenhouse experiments examined moisture retention at the vegetative stage. Significant genotypic variation was observed, with genotypes 310724, 310779, 311181, 311603, 311793, and Vandana exhibiting drought tolerance through stable PL and SS. Additionally, genotypes 310100, 310428, 311255, N22, and Bengal demonstrated superior moisture retention. The study emphasizes selecting genotypes with stable performance to enhance drought tolerance, with 310779 and N22 standing out for their low spikelet sterility and strong drought resilience. In contrast, genotypes like 311111, 311140, 311180, and KB showed heightened sensitivity to drought, with reduced panicle length, fewer spikelets, and increased sterility, making them less suitable for drought-prone environments.
Under polyethylene glycol (PEG)-induced osmotic stress, Vandana, 301418, and 311140 exhibited strong tolerance, while 310428, 310724, 311111, 311180, 310779, and 311181 were sensitive. Drought-resistant genotypes exhibited increased root traits, including root length (RL), root-to-shoot ratio (RSR), total root number (TRN), and dry root weight (DRN). Further, drought-resistant genotypes Vandana, N22, 311255 and 311181 displayed an ABA-sensitive phenotype at early growth stages, with ABA-mediated signaling influencing osmotic stress tolerance. RT-qPCR analysis revealed increased ZIP gene expression in drought-tolerant genotypes following ABA application.
These findings underscore the importance of stress-specific evaluations in identifying drought-tolerant genotypes. However, genotypes such as Vandana, N22, and 311255 emerged as promising candidates for breeding programs aimed at improving drought resilience in rice. The study provides valuable insights for developing climate-resilient rice varieties, integrating physiological, morphological, and genetic approaches to enhance adaptation to water-limited conditions. Keywords: Drought tolerance, Oryza sativa, spikelet sterility, ABA signaling, ZIP gene, root phenotyping, PEG stress
Perceiving School Success: A Phenomenological Study of Asian Indian Parents
Get PDFThis phenomenological qualitative study aimed to explore how Asian Indian parents at East Ridge Elementary School perceived student success. The research sought to understand their experiences, their views on student success, and the factors they perceived as supports or barriers to achieving that success. Interviews with 14 Asian Indian families revealed four major themes: Positive School Experiences, Academic Programming, Holistic View of Education, and Parental Engagement. While communication emerged as a central element, it was not categorized as a theme but rather as a supporting factor. The study found that parents expressed satisfaction with the school’s cultural inclusivity and sense of community, though they identified areas for improvement in academic programming, particularly in curriculum clarity and opportunities for parental engagement. A secondary objective of the study was to explore differences among families with children receiving English Language services. The findings indicated that although academic success was a common priority, families in this subgroup faced distinct challenges, particularly related to language acquisition. Based on these findings, several practical recommendations were made, such as improving communication about the curriculum, expanding extracurricular opportunities, and strengthening parental involvement. The study also highlighted the importance of measuring student success beyond traditional academic assessments and suggested avenues for future research on effective communication strategies and cultural integration efforts. These recommendations have the potential to strengthen school-family partnerships and improve the educational experience for Asian Indian students and their families
Exploring the Role of Influencer Marketing in the Animal Health Industry: A Content Analysis of Strategies and Impact
Get PDFA review of literature revealed a lack of peer-reviewed research on influencer marketing within the animal health and nutrition industry, specifically within the livestock sector. This study aimed to address this gap by analyzing how animal health and nutrition companies of different sizes utilized influencer marketing and how consumers interacted with content tailored to influencer marketing. A content analysis was conducted. This study collected and analyzed social media influencer posts from eight North American animal health and nutrition companies, three small, three medium, and two large, between January 2023 and December 2024. Influencer content included posts by individuals, partner organizations, or livestock that promoted company products or services. The posts were coded and analyzed to determine strategy types, engagement metrics, and social media marketing differences by company size.
The findings revealed while all companies used influencer marketing, larger companies focused on professional partnerships and educational content, while smaller companies relied on personalized influencer connections. Consumer engagement varies by format and tone of content, with visual storytelling and scientific credibility influencing post-interaction. Limitations included platform restrictions with the potential to remove negative comments and the exclusion of TikTok data due to university policy. This study highlights the need for further research into agricultural influencer marketing and provides insights for companies aiming to build more effective digital strategies tailored to livestock audiences. With a better understanding of influencer approaches and consumer behaviors, companies can refine and develop their marketing efforts to enhance their reach in the animal health and nutrition industry