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Articles 541 - 570 of 4692

Full-Text Articles in Engineering

Automated Flood Depth Estimation On Roadways, Kwame Ampofo, Megan A. Witherow, Alex Glandon, Monibor Rahman, Ahmed Temtam, Mecit Cetin, Khan M. Iftekharuddin Jan 2024

Automated Flood Depth Estimation On Roadways, Kwame Ampofo, Megan A. Witherow, Alex Glandon, Monibor Rahman, Ahmed Temtam, Mecit Cetin, Khan M. Iftekharuddin

Civil & Environmental Engineering Faculty Publications

Recurrent nuisance flooding is common across many parts of the globe and causes extensive challenges for drivers on the roadways. The prevailing monitoring methods for roadway flooding are costly and not automated or effective. The ubiquity of visual data from cameras and advancements in computing such as deep learning may offer cost-effective methods for automated flood depth estimation on roadways based on reference objects such as cars. However, flood depth estimation faces challenges due to the limited amount of data annotated with water levels and diverse scenes showing reference objects at various scales and perspectives. This study proposes a novel …

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Methods That Support The Validation Of Agent-Based Models: An Overview And Discussion, Andrew Collins, Matthew Koehler, Christopher Lynch Jan 2024

Methods That Support The Validation Of Agent-Based Models: An Overview And Discussion, Andrew Collins, Matthew Koehler, Christopher Lynch

Engineering Management & Systems Engineering Faculty Publications

Validation is the process of determining if a model adequately represents the system under study for the model’s intended purpose. Validation is a critical component in building the credibility of a simulation model with its end-users. Effectively conducting validation can be a daunting task for both novice and experienced simulation developers. Further compounding the difficult task of conducting validation is that there is no universally accepted approach for assessing a simulation. These challenges are particularly relevant to the paradigm of Agent-Based Modeling and Simulation (ABMS) because of the complexity found in these models’ mechanisms and in the real-world situations they …

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Abmscore: A Heuristic Algorithm For Forming Strategic Coalitions In Agent-Based Simulation, Andrew J. Collins, Gayane Grigoryan Jan 2024

Abmscore: A Heuristic Algorithm For Forming Strategic Coalitions In Agent-Based Simulation, Andrew J. Collins, Gayane Grigoryan

Engineering Management & Systems Engineering Faculty Publications

Integrating human behavior into agent-based models has been challenging due to its diversity. An example is strategic coalition formation, which occurs when an individual decides to collaborate with others because it strategically benefits them, thereby increasing the expected utility of the situation. An algorithm called ABMSCORE was developed to help model strategic coalition formation in agent-based models. The ABMSCORE algorithm employs hedonic games from cooperative game theory and has been applied to various situations, including refugee egress and smallholder farming cooperatives. This paper discusses ABMSCORE, including its mechanism, requirements, limitations, and application. To demonstrate the potential of ABMSCORE, a new …

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B(C₆F₅)₃ Co-Catalyst Promotes Unconventional Halide Abstraction From Grubbs I To Enhance Reactivity And Limit Decomposition, Austin W. Medley, Diya Patel, Calvin Utne, Trandon A. Bender Jan 2024

B(C₆F₅)₃ Co-Catalyst Promotes Unconventional Halide Abstraction From Grubbs I To Enhance Reactivity And Limit Decomposition, Austin W. Medley, Diya Patel, Calvin Utne, Trandon A. Bender

Chemistry & Biochemistry Faculty Publications

Ruthenium based Grubbs metathesis has become a commonplace reaction for synthetic chemists. Development of new generations of catalysts evolving from Grubbs I (GI) have led to greater stability, functional group compatibility, and superior reactivities. However, these advancements lead to increased costs. To this end, we report here how the addition of the commercially available tris(pentafluorophenyl)borane Lewis acid, which has become a common place catalyst in its own right, leads to enhanced reactivity of GI. Moreover, the increased reactivity arises via halide abstraction rather than traditional phosphine dissociation, providing ring-opening metathesis polymerization products that are divergent from those synthesized without the …

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Role Of Nitrogenous Functional Group Identity In Accelerating 1,2,3- Trichloropropane Degradation By Pyrogenic Carbonaceous Matter (Pcm) And Sulfide Using Pcm-Like Polymers, Han Cao, Jingdong Mao, Paul G. Tratnyek, Wenqing Xu Jan 2024

Role Of Nitrogenous Functional Group Identity In Accelerating 1,2,3- Trichloropropane Degradation By Pyrogenic Carbonaceous Matter (Pcm) And Sulfide Using Pcm-Like Polymers, Han Cao, Jingdong Mao, Paul G. Tratnyek, Wenqing Xu

Chemistry & Biochemistry Faculty Publications

Groundwater contamination by 1,2,3-trichloropropane (TCP) poses a unique challenge due to its human toxicity and recalcitrance to degradation. Previous work suggests that nitrogenous functional groups of pyrogenic carbonaceous matter (PCM), such as biochar, are important in accelerating contaminant dechlorination by sulfide. However, the reaction mechanism is unclear due, in part, to PCM's structural complexity. Herein, PCM-like polymers (PLPs) with controlled placement of nitrogenous functional groups [i.e., quaternary ammonium (QA), pyridine, and pyridinium cations (py+)] were employed as model systems to investigate PCM-enhanced TCP degradation by sulfide. Our results suggest that both PLP-QA and PLP-py+ were highly effective …

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Type-B Energetic Processes: Their Identification And Implications, James Weifu Lee Jan 2024

Type-B Energetic Processes: Their Identification And Implications, James Weifu Lee

Chemistry & Biochemistry Faculty Publications

We have now identified two thermodynamically distinct types (A and B) of energetic processes naturally occurring on Earth. Type-A energy processes, such as classical heat engines, apparently well follow the second law of thermodynamics; Type-B energy processes, such as the newly discovered thermotrophic function that isothermally utilizes environmental heat energy to perform useful work in driving ATP synthesis, follow the first law of thermodynamics (conservation of mass and energy) but do not have to be constrained by the second law, owing to their special asymmetric functions. Several Type-B energy processes such as asymmetric function-gated isothermal electricity production and epicatalysis have …

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Examining The Effectiveness Of Oiled Ballast Water Treatment Processes: Insights Into Hydrocarbon Oxidation Product Formation And Environmental Implications, Maxwell L. Harsha, Danielle E. Verna, Yanila Salas-Ortiz, Eduardo Osborn, Eduardo Turcios Valle, Aleksandar I. Goranov, Patrick G. Hatcher, Ana M. Aguilar-Islas, Patrick L. Tomco, David C. Podgorski Jan 2024

Examining The Effectiveness Of Oiled Ballast Water Treatment Processes: Insights Into Hydrocarbon Oxidation Product Formation And Environmental Implications, Maxwell L. Harsha, Danielle E. Verna, Yanila Salas-Ortiz, Eduardo Osborn, Eduardo Turcios Valle, Aleksandar I. Goranov, Patrick G. Hatcher, Ana M. Aguilar-Islas, Patrick L. Tomco, David C. Podgorski

Chemistry & Biochemistry Faculty Publications

Ballast water released from ships into coastal environments has been identified as a mechanism that introduces contaminants of concern into coastal ecosystems. This study investigates the treatment processes employed at a ballast water treatment facility in Valdez, Alaska, that remove hydrocarbons from unsegregated ballast water. Specifically, the aim is to quantify and characterize hydrocarbons of emerging concern, known as dissolved hydrocarbon oxidation products (HOPs) and heavy metals (HMs), throughout the treatment process. Specialized analytical techniques were employed, such as non-volatile dissolved organic carbon analysis, fluorescence spectroscopy, Fourier transform-ion cyclotron resonance-mass spectrometry, and inductively coupled plasma triple quadrupole mass spectrometry. Results …

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Digitalization Of Railway Transportation Through Ai-Powered Services: Digital Twin Trains, Salih Sarp, Murat Kuzlu, Vukica Jovanovic, Zekeriya Polat, Ozgur Guler Jan 2024

Digitalization Of Railway Transportation Through Ai-Powered Services: Digital Twin Trains, Salih Sarp, Murat Kuzlu, Vukica Jovanovic, Zekeriya Polat, Ozgur Guler

Engineering Technology Faculty Publications

Digitalization is a key concept that transformed the various industries through technologies like Internet of Things (IoT), Artificial Intelligence (AI), and Digital Twin (DT). Although innovations provided by the advancement of digitalization have paved the way for more efficient operations and products for transportation, the rail transportation sector struggles to keep up with the rest of the transportation industry, since trains are designed to last for decades, and the insufficient infrastructure investment leads to multiple railroad derailments across the globe. Therefore, the primary aim is to transform current railway systems into human-centric, adaptable, sustainable and future-proof networks, aligning with Industry …

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Nano-Pulse Treatment Overcomes The Immunosuppressive Tumor Microenvironment To Elicit In Situ Vaccination Protection Against Breast Cancer, Anthony Nanajian, Megan Scott, Niculina I. Burcus, Brittney L. Ruedlinger, Edwin A. Oshin, Stephen J. Beebe, Siqi Guo Jan 2024

Nano-Pulse Treatment Overcomes The Immunosuppressive Tumor Microenvironment To Elicit In Situ Vaccination Protection Against Breast Cancer, Anthony Nanajian, Megan Scott, Niculina I. Burcus, Brittney L. Ruedlinger, Edwin A. Oshin, Stephen J. Beebe, Siqi Guo

Bioelectrics Publications

We previously reported that nano-pulse treatment (NPT), a pulsed power technology, resulted in 4T1-luc mammary tumor elimination and a strong in situ vaccination, thereby completely protecting tumor-free animals against a second live tumor challenge. The mechanism whereby NPT mounts effective antitumor immune responses in the 4T1 breast cancer predominantly immunosuppressive tumor microenvironment (TME) remains unanswered. In this study, orthotopic 4T1 mouse breast tumors were treated with NPT (100 ns, 50 kV/cm, 1000 pulses, 3 Hz). Blood, spleen, draining lymph nodes, and tumors were harvested at 4-h, 8-h, 1-day, 3-day, 7-day, and 3-month post-treatment intervals for the analysis of frequencies, death, …

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Teaching Analytics Online: A Self-Study Of Professional Practice, Andrew J. Collins, Brandon Butler, James F. Leathrum Jr., Christopher J. Lynch Jan 2024

Teaching Analytics Online: A Self-Study Of Professional Practice, Andrew J. Collins, Brandon Butler, James F. Leathrum Jr., Christopher J. Lynch

Engineering Management & Systems Engineering Faculty Publications

As the COVID-19 pandemic caused severe disruption to education enterprises throughout the world, the main response by educational institutions was to move to online learning environments. The purpose of this study was to understand better how instructors could improve online learning for a professional-level week-long short course in a highly technical area (data analytics), which had, pre-COVID, been a hands-on computer, laboratory-based learning experience. The authors used self-study of professional practice to elicit and understand the major issues and concerns of the transition to an online learning environment. Under the guidance of a colleague in teacher education, three course instructors …

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Urban Flood Extent Segmentation And Evaluation From Real-World Surveillance Camera Images Using Deep Convolutional Neural Network, Yidi Wang, Yawen Shen, Behrouz Salahshour, Mecit Cetin, Khan Iftekharuddin, Navid Tahvildari, Guoping Huang, Devin K. Harris, Kwame Ampofo, Jonathan L. Goodall Jan 2024

Urban Flood Extent Segmentation And Evaluation From Real-World Surveillance Camera Images Using Deep Convolutional Neural Network, Yidi Wang, Yawen Shen, Behrouz Salahshour, Mecit Cetin, Khan Iftekharuddin, Navid Tahvildari, Guoping Huang, Devin K. Harris, Kwame Ampofo, Jonathan L. Goodall

Civil & Environmental Engineering Faculty Publications

This study explores the use of Deep Convolutional Neural Network (DCNN) for semantic segmentation of flood images. Imagery datasets of urban flooding were used to train two DCNN-based models, and camera images were used to test the application of the models with real-world data. Validation results show that both models extracted flood extent with a mean F1-score over 0.9. The factors that affected the performance included still water surface with specular reflection, wet road surface, and low illumination. In testing, reduced visibility during a storm and raindrops on surveillance cameras were major problems that affected the segmentation of flood extent. …

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Advanced Nested Coaxial Thin-Film Zno Nanostructures Synthesized By Atomic Layer Deposition For Improved Sensing Performance, Pengtao Lin, Lari S. Zhang, Kai Zhang, Helmut Baumgart Jan 2024

Advanced Nested Coaxial Thin-Film Zno Nanostructures Synthesized By Atomic Layer Deposition For Improved Sensing Performance, Pengtao Lin, Lari S. Zhang, Kai Zhang, Helmut Baumgart

Electrical & Computer Engineering Faculty Publications

We report a new synthesis method for multiple-walled nested thin-film nanostructures by combining hydrothermal growth methods with atomic layer deposition (ALD) thin-film technology and sacrificial films, thereby increasing the surface-to-volume ratio to improve the sensing performance of novel ZnO gas sensors. Single-crystal ZnO nanorods serve as the core of the nanostructure assembly and were synthesized hydrothermally on fine-grained ALD ZnO seed films. Subsequently, the ZnO core nanotubes were coated with alternating sacrificial coaxial 3D wrap-around ALD Al2O3 films and ALD ZnO films. Basically, the center nanorod was coated with an ALD 3D wrap-around Al₂O₃ sacrificial layer to realize a nested …

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A Generative Approach For Document Enhancement With Small Unpaired Data, Mohammad Shahab Uddin, Wael Khallouli, Andres Sousa-Poza, Samuel Kovacic, Jiang Li Jan 2024

A Generative Approach For Document Enhancement With Small Unpaired Data, Mohammad Shahab Uddin, Wael Khallouli, Andres Sousa-Poza, Samuel Kovacic, Jiang Li

Engineering Management & Systems Engineering Faculty Publications

Shipbuilding drawings, crafted manually before the digital era, are vital for historical reference and technical insight. However, their digital versions, stored as scanned PDFs, often contain significant noise, making them unsuitable for use in modern CAD software like AutoCAD. Traditional denoising techniques struggle with the diverse and intense noise found in these documents, which also does not adhere to standard noise models. In this paper, we propose an innovative generative approach tailored for document enhancement, particularly focusing on shipbuilding drawings. For a small, unpaired dataset of clean and noisy shipbuilding drawing documents, we first learn to generate the noise in …

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Rf And Mechanical Design Of A 915 Mhz Srf Cavity For Conduction-Cooled Cryomodules, G. Ciovati, A. Castilla-Loeza, G. Cheng, J. Henry, J. Rathke, J. Vennekate, K. Harding, T. Schultheiss, J. Lewis Jan 2024

Rf And Mechanical Design Of A 915 Mhz Srf Cavity For Conduction-Cooled Cryomodules, G. Ciovati, A. Castilla-Loeza, G. Cheng, J. Henry, J. Rathke, J. Vennekate, K. Harding, T. Schultheiss, J. Lewis

Physics Faculty Publications

Conduction-cooled SRF niobium cavities are being developed for use in compact, continuous-wave electron linear accelerators for a variety of industrial applications. A 915 MHz two-cell cavity has been designed to achieve an energy gain of 3.5 MeV. The design of the cell shape aims at minimizing the peak surface magnetic field. Field flatness is achieved by adjusting the length of the outer end half-cells. The higher-order mode analysis shows that absorbers are not required for a moderate beam current of 5 mA. One of the beam tubes has two side-ports for insertion of coaxial fundamental power couplers. The mechanical design …

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The Discharge-Induced Polarity-Dependent Propagation Characteristics Of A Strong Shock Wave, Anna Markhotok Jan 2024

The Discharge-Induced Polarity-Dependent Propagation Characteristics Of A Strong Shock Wave, Anna Markhotok

Physics Faculty Publications

The specifics of a shock wave propagation down a positive column of a DC discharge in molecular chemically inert gases has been investigated. It was shown that axial gradients caused by the imbalance in the charged particle momentum transfer to the gas molecules can be a reason for the shock velocity dependence on the electric field direction. In pure nitrogen gas, the calculated shock velocity difference of up to 13.5% is in good agreement with the 12% value obtained in the experiment. A returning gas flow organizing in the discharge as a possible mechanism for an extended shock structure and …

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Particle Accelerator Spin-Transparent Storage Rings For Beyond State-Of-The-Art Science, R. Suleiman, Y. Derbenev, M. Grau, V. Morozov Jan 2024

Particle Accelerator Spin-Transparent Storage Rings For Beyond State-Of-The-Art Science, R. Suleiman, Y. Derbenev, M. Grau, V. Morozov

Physics Faculty Publications

We will describe spin-transparent storage rings that exhibit spin-coherence times of several hours and store a large number of particles and their use in novel applications. For example, these rings can be used to directly measure the electric dipole moment of the electron, relevant to CP violation and matter-antimatter asymmetry in the universe, and to search for dark energy and ultra-light dark matter*. These rings can also serve as a compelling platform for quantum computing. In this presentation, we will describe how spin-transparent rings can be used in conjunction with ion traps to enhance scalability and increase quantum coherence times …

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Conflict Profiles And Team Outcomes In Cross-Disciplinary Teams: An Integrated Latent Profile Analysis And Natural Language Processing Approach, Francisco Cima, Pilar Pazos Jan 2024

Conflict Profiles And Team Outcomes In Cross-Disciplinary Teams: An Integrated Latent Profile Analysis And Natural Language Processing Approach, Francisco Cima, Pilar Pazos

Engineering Management & Systems Engineering Faculty Publications

Team conflict is a naturally emerging phenomenon resulting from individuals' interactions during project execution. Cross-disciplinary teams can experience higher levels of conflict than single-discipline teams because of the increased diversity of knowledge and perspectives. Research has shown that team conflict can emerge from different types of disagreements (cognitive and interpersonal), which have different implications for team functioning. Past empirical research has focused on the impact of both conflict types independent from each other while overlooking their combined effects. This work examines the conflict profiles resulting from the combined levels of interpersonal and cognitive disagreements and their association with team outcomes. …

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Advancing Household Robotics: Deep Interactive Reinforcement Learning For Efficient Training And Enhanced Performance, Arpita Soni, Sujatha Alla, Suresh Dodda, Hemanth Volikatla Jan 2024

Advancing Household Robotics: Deep Interactive Reinforcement Learning For Efficient Training And Enhanced Performance, Arpita Soni, Sujatha Alla, Suresh Dodda, Hemanth Volikatla

Engineering Management & Systems Engineering Faculty Publications

The market for domestic robots—made to perform household chore, is growing as these robots relieve people of everyday responsibilities. Domestic robots are generally welcomed for their role in easing human labour, in contrast to industrial robots, which are frequently criticised for displacing human workers. But before these robots can carry out domestic chores, they need to become proficient in a number of minor activities, such as recognizing their surroundings, making decisions, and picking up on human behaviours. Reinforcement learning, or RL, has emerged as a key robotics technology that enables robots to interact with their environment and learn how to …

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Improving Neuropathological Analysis With Aβgan: Addressing Morphology Imbalance For Efficient Alzheimer's Disease Diagnosis, Sujatha Alla, Prasanthi Chidipudi, Nagesh Bheesetty, Vedvikash Reddy Velur, Joshit Mohanty, Puneeth Bheesetty, Marisha Jmukhadze, Narendra Lakshmana Gowda, Sai Gireesh Komaragiri Jan 2024

Improving Neuropathological Analysis With Aβgan: Addressing Morphology Imbalance For Efficient Alzheimer's Disease Diagnosis, Sujatha Alla, Prasanthi Chidipudi, Nagesh Bheesetty, Vedvikash Reddy Velur, Joshit Mohanty, Puneeth Bheesetty, Marisha Jmukhadze, Narendra Lakshmana Gowda, Sai Gireesh Komaragiri

Engineering Management & Systems Engineering Faculty Publications

Histopathologists are experiencing a digital revolution in their field thanks to the digitization of Whole Slide Images (WSIs), which are microscope slides of tissue that can measure gigapixels in size. With so much high resolution data at their disposal, computer vision techniques can now be used to automate laboratory processes, create visual standards, and increase analysis throughput, all of which reduce the workload of pathologists [1]. The "gold" standard in neuropathology, particularly for Alzheimer's Disease- is pathological diagnosis made by looking at White Matter Inclusions (WSIs) in brain tissue. Semi-quantitative scoring in accordance with the standards established by the Consortium …

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Advancements And Challenges In Additively Manufactured Functionally Graded Materials: A Comprehensive Review, Suhas Alkunte, Ismail Fidan, Vivekanand Naikwadi, Shamil Gudavasov, Mohammad Alshaikh Ali, Mushfig Mahmudov, Seymur Hasanov, Muralimohan Cheepu Jan 2024

Advancements And Challenges In Additively Manufactured Functionally Graded Materials: A Comprehensive Review, Suhas Alkunte, Ismail Fidan, Vivekanand Naikwadi, Shamil Gudavasov, Mohammad Alshaikh Ali, Mushfig Mahmudov, Seymur Hasanov, Muralimohan Cheepu

Engineering Technology Faculty Publications

This paper thoroughly examines the advancements and challenges in the field of additively manufactured Functionally Graded Materials (FGMs). It delves into conceptual approaches for FGM design, various manufacturing techniques, and the materials employed in their fabrication using additive manufacturing (AM) technologies. This paper explores the applications of FGMs in diverse fields, including structural engineering, automotive, biomedical engineering, soft robotics, electronics, 4D printing, and metamaterials. Critical issues and challenges associated with FGMs are meticulously analyzed, addressing concerns related to production and performance. Moreover, this paper forecasts future trends in FGM development, highlighting potential impacts on diverse industries. The concluding section summarizes …

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Energy Efficiency In Additive Manufacturing: Condensed Review, Ismail Fidan, Vivekanand Naikwadi, Suhas Alkunte, Roshan Mishra, Khalid Tantawi Jan 2024

Energy Efficiency In Additive Manufacturing: Condensed Review, Ismail Fidan, Vivekanand Naikwadi, Suhas Alkunte, Roshan Mishra, Khalid Tantawi

Engineering Technology Faculty Publications

Today, it is significant that the use of additive manufacturing (AM) has growing in almost every aspect of the daily life. A high number of sectors are adapting and implementing this revolutionary production technology in their domain to increase production volumes, reduce the cost of production, fabricate light weight and complex parts in a short period of time, and respond to the manufacturing needs of customers. It is clear that the AM technologies consume energy to complete the production tasks of each part. Therefore, it is imperative to know the impact of energy efficiency in order to economically and properly …

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Ground Tire Rubber As A Sustainable Additive: Transforming Desert Sand Behavior, Nabil Ismael, Dalya Ismael, Asmaa Al-Ahmad Jan 2024

Ground Tire Rubber As A Sustainable Additive: Transforming Desert Sand Behavior, Nabil Ismael, Dalya Ismael, Asmaa Al-Ahmad

Engineering Technology Faculty Publications

Managing waste tires presents a significant challenge globally, particularly in regions experiencing high temperatures and shortage of landfill sites. This issue is affecting countries like Kuwait, where the abundance of waste tires is a major source of environmental and safety risks, particularly during the intensely hot summer months. This extreme heat has sparked numerous fires, leading to substantial air pollution due to thick black smoke. Given the limited disposal options, recycling waste tires and finding practical applications for ground tire rubber (GTR) is essential. To address the challenge, a comprehensive laboratory testing program was conducted, using locally produced rubber aggregates …

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Immersive Visualization In Infrastructure Planning: Enhancing Long-Term Resilience And Sustainability, Dalya Ismael Jan 2024

Immersive Visualization In Infrastructure Planning: Enhancing Long-Term Resilience And Sustainability, Dalya Ismael

Engineering Technology Faculty Publications

Infrastructure decisions today significantly impact future generations' quality of life, especially as severe storms and rising sea levels increasingly threaten communities across the United States. Decision-makers at all levels, including those involved in disaster prevention and response, must address climate change. However, those in infrastructure design and construction often prioritize immediate gains over long-term resilience. Engineering teams typically employ decision tools to manage complexity, but these methods may not highlight the long-term consequences of their choices. This study tests whether integrating Virtual Reality (VR) technology with engineering decision-making tools, can enhance engineers’ ability to visualize the future impacts of their …

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Uncertainty Quantification In Large Language Models Through Convex Hull Analysis, Ferhat Ozgur Catak, Murat Kuzlu Jan 2024

Uncertainty Quantification In Large Language Models Through Convex Hull Analysis, Ferhat Ozgur Catak, Murat Kuzlu

Engineering Technology Faculty Publications

Uncertainty quantification approaches have been more critical in large language models (LLMs), particularly high-risk applications requiring reliable outputs. However, traditional methods for uncertainty quantification, such as probabilistic models and ensemble techniques, face challenges when applied to the complex and high-dimensional nature of LLM-generated outputs. This study proposes a novel geometric approach to uncertainty quantification using convex hull analysis. The proposed method leverages the spatial properties of response embeddings to measure the dispersion and variability of model outputs. The prompts are categorized into three types, i.e., ’easy’, ’moderate’, and ’confusing’, to generate multiple responses using different LLMs at varying temperature settings. …

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Long-Term Impact Of A Semester-Long Multidisciplinary Service-Learning Assignment In A Fluid Mechanics Course, Orlando M. Ayala, Kristie Gutierrez, Isaac Koduah Kumi, Francisco Cima, Stacie I. Ringleb, Krishnanand Kaipa, Danielle M. Rhemer, Pilar Pazos, Jennifer Jill Kidd Jan 2024

Long-Term Impact Of A Semester-Long Multidisciplinary Service-Learning Assignment In A Fluid Mechanics Course, Orlando M. Ayala, Kristie Gutierrez, Isaac Koduah Kumi, Francisco Cima, Stacie I. Ringleb, Krishnanand Kaipa, Danielle M. Rhemer, Pilar Pazos, Jennifer Jill Kidd

Engineering Technology Faculty Publications

Seventy-three students who enrolled in a senior-year level fluid mechanics course during spring semesters from 2019-2023 were asked about their perceptions on the impact in their professional preparation of a semester-long multidisciplinary service-learning assignment. This paper aims to evaluate their current perceived impact of the assignment (long-term impact) and whether it might have changed from when they took the course (short-term impact). The project tested their creativity, knowledge of fluid mechanics concepts, and skills to work with people from other disciplines. They were told that they were working for a hypothetical company, “Engineering is for all,” and were assigned to …

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Federated Learning: Overview, Strategies, Applications, Tools And Future Directions, Betul Yurdem, Murat Kuzlu, Mehmet Kemal Gullu, Maliha Tabassum Jan 2024

Federated Learning: Overview, Strategies, Applications, Tools And Future Directions, Betul Yurdem, Murat Kuzlu, Mehmet Kemal Gullu, Maliha Tabassum

Engineering Technology Faculty Publications

Federated learning (FL) is a distributed machine learning process, which allows multiple nodes to work together to train a shared model without exchanging raw data. It offers several key advantages, such as data privacy, security, efficiency, and scalability, by keeping data local and only exchanging model updates through the communication network. This review paper provides a comprehensive overview of federated learning, including its principles, strategies, applications, and tools along with opportunities, challenges, and future research directions. The findings of this paper emphasize that federated learning strategies can significantly help overcome privacy and confidentiality concerns, particularly for high-risk applications.

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Four Decades Of Distance Learning Instruction In An Electrical Engineering Technology Program, Otilia Popescu, Isaac L. Flory Iv, John R. Hackworth, Murat Kuzlu Jan 2024

Four Decades Of Distance Learning Instruction In An Electrical Engineering Technology Program, Otilia Popescu, Isaac L. Flory Iv, John R. Hackworth, Murat Kuzlu

Engineering Technology Faculty Publications

Online instruction is no longer a new or seldom used modality. It has grown over the last few decades, reaching a pinnacle during the recent pandemic. Different institutions and different programs chose different approaches for the online delivery of courses, adopting either synchronous or asynchronous deliveries for online students, and hybrid delivery for mixed groups of campus and online students attending the classes in a live or synchronous manner. This paper’s main goal is to present the history of over 40 years of distance learning in an Electrical Engineering Technology program and how the delivery mode progressed over time. While …

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Advancing The Manufacturing Engineering Technology Pathway: Innovating And Developing The Curriculum (Courses And Labs) From Associate To Bachelor's Level, Afi Anuar, Vukica Jovanovic, Nathan Luetke, Hamid Eisazadeh, Isaac Flory Iv, Mileta Tomović, Anthony W. Dean Jan 2024

Advancing The Manufacturing Engineering Technology Pathway: Innovating And Developing The Curriculum (Courses And Labs) From Associate To Bachelor's Level, Afi Anuar, Vukica Jovanovic, Nathan Luetke, Hamid Eisazadeh, Isaac Flory Iv, Mileta Tomović, Anthony W. Dean

Engineering Technology Faculty Publications

The southeastern region of Virginia, specifically Hampton Roads, has a diverse manufacturing landscape encompassing a range of enterprises, from small businesses to large corporations. This sector includes shipbuilding, construction machinery, aeronautics, and food processing. However, both the region and the broader state of Virginia are struggling with a skilled labor shortage that fails to meet the demands of these manufacturing enterprises. This paper aims to provide insights into the recently established Manufacturing Engineering Technology (MFET) program at Old Dominion University, located in Norfolk, Virginia. The MFET program features a comprehensive curriculum, encompassing the development of new courses and the establishment …

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A Project-Based Learning Activity For An Engineering Technology Heat Transfer Course To Design A Shell-And-Tube Heat Exchanger, Nathan Luetke, Orlando Ayala Jan 2024

A Project-Based Learning Activity For An Engineering Technology Heat Transfer Course To Design A Shell-And-Tube Heat Exchanger, Nathan Luetke, Orlando Ayala

Engineering Technology Faculty Publications

Thermofluids courses demand a strong grasp of mathematics and employ physics extensively to describe physical systems. Heat transfer, in particular, presents challenging topics, which can be even more daunting for engineering technology students. In this paper, we present the implementation of a project-based learning activity in the engineering technology heat transfer course. The students' task involves designing a shell-and-tube heat exchanger to meet specific minimum requirements. The objective is to provide students with a real-world assignment that enhances their heat transfer calculation skills. To accommodate instructors' busy schedules, we have developed an assignment that is user friendly. Detailed instructor guides …

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Latent Space Dynamics Learning For Stiff Collisional-Radiative Models, Xuping Xie, Qi Tang, Xianzhu Tang Jan 2024

Latent Space Dynamics Learning For Stiff Collisional-Radiative Models, Xuping Xie, Qi Tang, Xianzhu Tang

Mathematics & Statistics Faculty Publications

In this work, we propose a data-driven method to discover the latent space and learn the corresponding latent dynamics for a collisional-radiative (CR) model in radiative plasma simulations. The CR model, consisting of high-dimensional stiff ordinary differential equations, must be solved at each grid point in the configuration space, leading to significant computational costs in plasma simulations. Our method employs a physics-assisted autoencoder to extract a low-dimensional latent representation of the original CR system. A flow map neural network is then used to learn the latent dynamics. Once trained, the reduced surrogate model predicts the entire latent dynamics given only …

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