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Articles 5821 - 5850 of 40942

Full-Text Articles in Engineering

Development Of Halalan Tayyiban Plant-Based Cheese Formulations, Hasna B. Mazalana, Mas M. Rambli, Syazana A. Lim, Beston F. Nore Jan 2024

Development Of Halalan Tayyiban Plant-Based Cheese Formulations, Hasna B. Mazalana, Mas M. Rambli, Syazana A. Lim, Beston F. Nore

ASEAN Journal on Science and Technology for Development

The worldwide cheese production is dominated by animal milk sources with various industrial procedures, including animal rennet. There is a need to diversify the animal-based dairy products into plant-based one, not only to nurture the halalan tayyiban concept for Muslims, but also to accommodate the dietary restriction of some consumers. The objective of this work is to formulate a cheese type derived from plant-based milk with permissible ingredients to create a product for Muslim and non-Muslim consumers. In this study, we explored the use of conventional and non-conventional cheese-making procedures. A total of four experimental formulations (EF1-4) combinations were conducted …

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Unveiling The Antioxidant Properties Of Stenochlaena Palustris And Diplazium Esculentum Through Time-Dependent Analysis, Nurnajiihah A. Samad, Hasna B. Mazalan, Hazimah Sharifulazar, Aida M. Basri, Masayoshi Arai Jan 2024

Unveiling The Antioxidant Properties Of Stenochlaena Palustris And Diplazium Esculentum Through Time-Dependent Analysis, Nurnajiihah A. Samad, Hasna B. Mazalan, Hazimah Sharifulazar, Aida M. Basri, Masayoshi Arai

ASEAN Journal on Science and Technology for Development

Medicinal plants are generally known for its health benefits and there has been ongoing research to gather evidence on potential plants that could exhibit antioxidant activities. In this study, we explored underutilised local medicinal plants which are Stenochlaena palustris and Diplazium esculentum, locally known as ‘Lemiding’ and ‘Pakis’, respectively. The aim was to determine the effect of extraction time on phytochemical contents, antioxidant activities and total phenolic content (TPC) of the two plant species. Maceration method was used to extract the compounds from leaves of the plant in distilled water at different durations of extraction i.e. 2 hours, 4 hours, …

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Nanocellulose Synthesized From Sugarcane Bagasse (S. Officinarum) Via Alkaline-Mechanical Process And Its Characterization, Wafiqah Daim, Hiroshi Uyama, Syazana Abdullah Lim Jan 2024

Nanocellulose Synthesized From Sugarcane Bagasse (S. Officinarum) Via Alkaline-Mechanical Process And Its Characterization, Wafiqah Daim, Hiroshi Uyama, Syazana Abdullah Lim

ASEAN Journal on Science and Technology for Development

Nanocellulose is one of many promising materials that have garnered the attention of researchers and industries. In this study, sugarcane bagasse (S. officinarum) was used to synthesize cellulose nanofiber (SB-CNF) via an alkaline-mechanical process. A comprehensive characterization of SB-CNF was conducted to explore its morphology via scanning electron microscopy (SEM) and dynamic force microscopy (DFM), assess its functional groups using Fourier transform infrared spectroscopy (FT-IR), analyze its thermal properties through thermogravimetric analysis (TGA), and lastly, evaluate light absorbance and transmittance using a UV-VIS spectrophotometer. Our findings revealed that SB-CNF resulted in a highly intertwined nanofiber structure within a nano-scale dimension. …

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Innovative Approaches And Challenges In Brunei's Agricultural Management, Nuramalina Manshor, Ulaganathan Subramanian Jan 2024

Innovative Approaches And Challenges In Brunei's Agricultural Management, Nuramalina Manshor, Ulaganathan Subramanian

ASEAN Journal on Science and Technology for Development

The management and development in agriculture attract agricultural economic science for the pricing, business, farm policy, and financial knowledge. It conjointly draws on plant and animal sciences for soil, seed and fertilizer information, weed control, insect management, and rationing and breeding; agricultural engineering knowledge for farmhouses, vehicles, irrigation, field drying, drainage, and management of erosions; and data on human behavior in Science and Social Science.

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Direct Blue 86 Textile Dye Removal From Aqueous Solution Using Rice Husk-Based Adsorbent, M. Zulbahari M. Zua, Muhammad Raza Ul Mustafa, Mohamed Hasnain Isa, Teh Sabariah Binti Abd Manan, Naimah Ibrahim, Rozeana Hj Md Juani, Wida Susanty Hj Suhaili, Asmaal Muizz Sallehhin Bin Hj Mohammad Sultan, Zuliana Binti Hj Nayan Jan 2024

Direct Blue 86 Textile Dye Removal From Aqueous Solution Using Rice Husk-Based Adsorbent, M. Zulbahari M. Zua, Muhammad Raza Ul Mustafa, Mohamed Hasnain Isa, Teh Sabariah Binti Abd Manan, Naimah Ibrahim, Rozeana Hj Md Juani, Wida Susanty Hj Suhaili, Asmaal Muizz Sallehhin Bin Hj Mohammad Sultan, Zuliana Binti Hj Nayan

ASEAN Journal on Science and Technology for Development

Adsorption by activated carbon is an effective method of dye removal. However, due to high production and regeneration costs of activated carbon, various studies on low-cost adsorbents have been conducted. Agricultural waste such as rice husk (RH) is seen to be a good adsorbent for dye removal. Moreover, rice husk is readily available. In this study, rice husk-based adsorbents were prepared by chemical and thermal treatments. Standard curve (colour vs absorbance) for Direct Blue 86 (DB 86) was prepared to determine the concentration of dye before and after adsorption. The adsorption potential of the adsorbent for textile dye DB 86 …

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The Conceptual Review On The Effect Of Corporate Governance Monitoring Mechanisms On Tax Avoidance, Eveana Mosuin, Nor Balkish Zakaria, Yvonne Joseph Ason Jan 2024

The Conceptual Review On The Effect Of Corporate Governance Monitoring Mechanisms On Tax Avoidance, Eveana Mosuin, Nor Balkish Zakaria, Yvonne Joseph Ason

ASEAN Journal on Science and Technology for Development

Taxes are the primary source of revenue for many nations in order to increase budget revenues and fund national development. Taxation serves multiple purposes because it can positively impact a nation's investment, education, social and economic development. However, tax authorities require assistance with the issue of tax non-compliance, which impedes tax administration and collection. One of the categories of tax non-compliance is tax avoidance, which is one of the company's strategies for legally reducing its tax burden by exploiting loopholes in tax regulations to minimise tax liability. Tax avoidance is when a company follows a particular tax strategy in the …

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The Contribution Of Outcome Expectation In Water Saving Among Malaysians For Sustainable Living Standard, Ganesh. R, Vxynette Fiorna, Ammar Abdulaziz Al-Talib, Haslinda. A, Elango Natarajan Jan 2024

The Contribution Of Outcome Expectation In Water Saving Among Malaysians For Sustainable Living Standard, Ganesh. R, Vxynette Fiorna, Ammar Abdulaziz Al-Talib, Haslinda. A, Elango Natarajan

ASEAN Journal on Science and Technology for Development

Saving water is an essential component of a higher level of living for each individual in any Nation. The current and next generation will be greatly impacted by attitudes and emotional aspects of social cognitive behaviour. This empirical investigation was carried out in Malaysia. To determine their attitude and behaviour, a convenience sampling method was applied to a sample size of 265 individuals. It was discovered that outcome expectancy significantly improves water saving. Observed self-efficacy, personal elements, and environmental elements all impacted the outcome expectancy. The model evaluation showed that the adjusted R2 was 0.78, or about 78% of the …

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In Vivo Measurement Of Nadh Fluorescence Lifetime In Skeletal Muscle Via Fiber-Coupled Time-Correlated Single Photon Counting, Kathryn M. Priest, Jacob V. Schluns, Nathania Nischal, Colton L. Gattis, Jeffery C. Wolchok, Timothy J. Muldoon Jan 2024

In Vivo Measurement Of Nadh Fluorescence Lifetime In Skeletal Muscle Via Fiber-Coupled Time-Correlated Single Photon Counting, Kathryn M. Priest, Jacob V. Schluns, Nathania Nischal, Colton L. Gattis, Jeffery C. Wolchok, Timothy J. Muldoon

Biomedical Engineering Faculty Publications and Presentations

Nicotinamide adenine dinucleotide (NADH) is a cofactor that serves to shuttle electrons during metabolic processes such as glycolysis, the tricarboxylic acid cycle, and oxidative phosphorylation (OXPHOS). NADH is autofluorescent, and its fluorescence lifetime can be used to infer metabolic dynamics in living cells. Fiber-coupled time-correlated single photon counting (TCSPC) equipped with an implantable needle probe can be used to measure NADH lifetime in vivo, enabling investigation of changing metabolic demand during muscle contraction or tissue regeneration. This study illustrates a proof of concept for point-based, minimally-invasive NADH fluorescence lifetime measurement in vivo. Volumetric muscle loss (VML) injuries were …

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Foraging Economies: A Market Based Methodology For Robotic Swarm Foraging, John A. Little Jan 2024

Foraging Economies: A Market Based Methodology For Robotic Swarm Foraging, John A. Little

Graduate Theses, Dissertations, and Problem Reports (ETD)

Swarm robotics involves coordinating large groups of autonomous agents to accomplish complex tasks through decentralized, adaptive behaviors, providing a robust and scalable approach suited to dynamic and unpredictable environments. While traditional swarm models frequently draw inspiration from biological systems such as ant colonies or bee foraging, other approaches use techniques from physics, control theory, and economics to achieve effective coordination. This study distinguishes itself by applying economic principles—specifically, market-driven mechanisms like auctions, utility functions based on opportunity cost, and supply-demand dynamics based on fluctuating resource values at a central base—to improve task allocation within a swarm foraging context. This approach …

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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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Implementing Unmanned Aerial Vehicles To Collect Human Gait Data At Distance And Altitude For Identification And Re-Identification, Donn E. Bartram Jan 2024

Implementing Unmanned Aerial Vehicles To Collect Human Gait Data At Distance And Altitude For Identification And Re-Identification, Donn E. Bartram

Graduate Theses, Dissertations, and Problem Reports (ETD)

Gait patterns are a class of biometric information pertaining to the way a person moves and poses. Gait information is unique to each person and can be used to identify and reidentify people. Historically, this task has been achieved through the use of multiple ground-based imaging sensors. However, as Unmanned Aerial Vehicles (UAVs) advance, they present the opportunity to evolve the process of persons identification and re-identification. Collecting human gait data using UAVs at distances ranging from 20m to 500m and altitudes ranging from 0m to 120m is a challenging task. The current biometric data collection methods, primarily designed for …

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Virtual Reality & Pilot Training: Existing Technologies, Challenges & Opportunities, Tim Marron, Niall Dungan, Brian Mac Namee, Anna Donnla O'Hagan Jan 2024

Virtual Reality & Pilot Training: Existing Technologies, Challenges & Opportunities, Tim Marron, Niall Dungan, Brian Mac Namee, Anna Donnla O'Hagan

Journal of Aviation/Aerospace Education & Research

The introduction of virtual reality (VR) to flying training has recently gained much attention, with numerous VR companies, such as Loft Dynamics and VRpilot, looking to enhance the training process. Such a considerable change to how pilots are trained is a subject that warrants careful consideration. Examining the effect that VR has on learning in other areas gives us an idea of how VR can be suitably applied to flying training. Some of the benefits offered by VR include increased safety, decreased costs, and increased environmental sustainability. Nevertheless, some challenges ahead for developers to consider are negative transfer of learning, …

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Application Of Density Altitude Climatology To General Aviation Impacts, Thomas A. Guinn, Daniel J. Halperin, Sarah Strazzo Jan 2024

Application Of Density Altitude Climatology To General Aviation Impacts, Thomas A. Guinn, Daniel J. Halperin, Sarah Strazzo

Journal of Aviation/Aerospace Education & Research

Density altitude (DA) plays a key role in flight safety because it helps pilots anticipate poor aircraft performance when temperatures are warmer than standard. In this study, a 30-year climatology of DA for the conterminous United States was created using the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate (ERA5) dataset was applied to four separate DA-based, aircraft-performance, rules-of-thumb for general aviation (GA) flight. The goal was to demonstrate a technique to create educational visualization tools showing the variation of operational flight impacts with both month and location. Four such parameters were chosen to show …

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Machine Learning - Hail Awareness Spatial Analysis Toolkit (Hasat), Haoruo Fu, Joseph P. Hupy, Chien-Tsung Lu, Zhenglei Ji Jan 2024

Machine Learning - Hail Awareness Spatial Analysis Toolkit (Hasat), Haoruo Fu, Joseph P. Hupy, Chien-Tsung Lu, Zhenglei Ji

Journal of Aviation/Aerospace Education & Research

The National Airspace System (NAS) is a sophisticated network of air traffic control, navigation, and communication systems that play a critical role in ensuring the safe and efficient flow of air traffic across the United States. However, the occurrence of severe weather conditions, particularly hailstorms, poses a significant threat to flight safety within the NAS. To mitigate the risks associated with hail, aviation organizations have implemented a range of safety measures. This study utilized Esri’s ArcGIS as a mapping software to conduct a geospatial analysis of the impact of severe weather, particularly hail, on the NAS. The Hail Awareness Spatial …

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Low-Resource Automatic Speech Recognition Domain Adaptation – A Case-Study In Aviation Maintenance, Nadine Amin, Tracy L. Yother, Julia Rayz Jan 2024

Low-Resource Automatic Speech Recognition Domain Adaptation – A Case-Study In Aviation Maintenance, Nadine Amin, Tracy L. Yother, Julia Rayz

Journal of Aviation/Aerospace Education & Research

With timeliness and efficiency being critical in the aviation maintenance industry, the need has been growing for smart technological solutions that optimize and streamline the different underlying tasks (Bergkvist & Sabbagh, 2021). One such task is the technical documentation of the performed maintenance operations (Chandola et al., 2022). Instead of manual documentation, voice tools that transcribe spoken logbook entries allow technicians to document their work right away in a hands-free and time efficient manner. However, an accurate automatic speech recognition (ASR) model requires large training corpora (Siyaev & Jo, 2021a), which are lacking in the domain of aviation maintenance. In …

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An Enhanced Deep Autoencoder For Flight Delay Prediction, Desmond B. Bisandu, Dan Andrei Soviani-Sitoiu, Irene Moulitsas Jan 2024

An Enhanced Deep Autoencoder For Flight Delay Prediction, Desmond B. Bisandu, Dan Andrei Soviani-Sitoiu, Irene Moulitsas

Journal of Aviation/Aerospace Education & Research

Accurate and timely flight delay prediction cannot be overemphasized because of the ever-increasing demand for air travel and its importance in deploying intelligent transportation systems. Nonetheless, there has not been a universal solution to the problem, as more intelligent flight decision systems are required for the aviation industry's future growth. Existing flight delay classification and prediction approaches are mainly shallow traffic models and do not satisfy many applications in the real world. Our motivation to rethink the deep architecture model for predicting flight delays emanates from the problem. In this research, we proposed a technique that modified stacked autoencoder architecture …

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Adversarial Transferability And Generalization In Robust Deep Learning, Tao Wu Jan 2024

Adversarial Transferability And Generalization In Robust Deep Learning, Tao Wu

Doctoral Dissertations

Despite its remarkable achievements across a multitude of benchmark tasks, deep learning (DL) models exhibit significant fragility to adversarial examples, i.e., subtle modifications applied to inputs during testing yet effective in misleading DL models. These meticulously crafted perturbations possess the remarkable property of transferability: an adversarial example that effectively fools one model often retains its effectiveness against another model, even if the two models were trained independently. This research delves into the characteristics influencing the transferability of adversarial examples from three distinct and complementary perspectives: data, model, and optimization. Firstly, from the data perspective, we propose a new method of …

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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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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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Small-Strain Site Response Of Soft Soils In The Sacramento-San Joaquin Delta Region Of California Conditioned On Vₛ₃₀ And Mhvsr, Tristan E. Buckreis, Jonathan P. Stewart, Scott J. Brandenberg, Pengfei Wang Jan 2024

Small-Strain Site Response Of Soft Soils In The Sacramento-San Joaquin Delta Region Of California Conditioned On Vₛ₃₀ And Mhvsr, Tristan E. Buckreis, Jonathan P. Stewart, Scott J. Brandenberg, Pengfei Wang

Civil & Environmental Engineering Faculty Publications

Sites located in the Sacramento-San Joaquin Delta region of California typically have peaty-organic soils near the ground surface, which are characteristically soft, with shear wave velocities as low as 30 m/s. These unusually soft geotechnical conditions, which are outside the range of applicability of existing ergodic site amplification models, can be anticipated to produce significant site effects during earthquake shaking. We evaluate site response for 36 seismic stations in the Delta region using non-ergodic methods with low-amplitude ground motion data. We model first-order site effects using a period-dependent relation conditioned on the 30 m time-averaged shear wave velocity (V …

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Investigating The Viability Of Low Frequency Mhvsr Estimates Using Deep Shear Wave Velocity Profile, T. Mai, C. C. Nweke, P. Wang, F. J. Ornelas Jan 2024

Investigating The Viability Of Low Frequency Mhvsr Estimates Using Deep Shear Wave Velocity Profile, T. Mai, C. C. Nweke, P. Wang, F. J. Ornelas

Civil & Environmental Engineering Faculty Publications

Site response describes the alterations of seismic energy due to its interaction with subsurface geological interfaces and structures, which is usually estimated by one dimensional (1D) ground response analysis (GRA). However, 1D GRA requires subsurface information (e.g., shear wave velocity profile), which makes it not widely applicable, particularly for the sites where subsurface information is unavailable. Alternatively, the microtremor horizontal-to-vertical spectral ratio (mHVSR) from three-component recordings of ambient noise on the ground surface is easily measured and is believed to have the potential for site response prediction (the peaks in mHVSR are strongly associated with the site resonant frequencies). However,the …

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Contribution Of High Turbidity To Tidal Dynamics In A Curved Channel In Zhoushan Islands, China, Li Li, Fangzhou Shen, Zhiguo He, Gangfeng Ma, Jiachen Wang, Kailong Huangfu Jan 2024

Contribution Of High Turbidity To Tidal Dynamics In A Curved Channel In Zhoushan Islands, China, Li Li, Fangzhou Shen, Zhiguo He, Gangfeng Ma, Jiachen Wang, Kailong Huangfu

Civil & Environmental Engineering Faculty Publications

The curved tidal channel, Luotou Deep-water Navigational Channel, is the main channel of the Ningbo Zhoushan Port, which is ranked first in the world. Tidal dynamics in the channel are spatially and temporally asymmetric. In this study, the three-dimensional tidal dynamics in the channel were analyzed using field data and simulated using FVCOM. The results show that the tides in the channel flood/ebb along the northern/southern bank near the bottom/surface layer and these asymmetries are due to the imbalanced Coriolis force, centrifugal force, sea-level gradient, and density gradient. Residual current velocity peaks (0.7 m/s) in the middle of the channel …

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Electrospun Pt-Tio₂ Nanofibers Doped With Hpa For Catalytic Hydrodeoxygenation, Amos Taiswa, Randy L. Maglinao, Jessica M. Andriolo, Sandeep Kumar, Jack L. Skinner Jan 2024

Electrospun Pt-Tio₂ Nanofibers Doped With Hpa For Catalytic Hydrodeoxygenation, Amos Taiswa, Randy L. Maglinao, Jessica M. Andriolo, Sandeep Kumar, Jack L. Skinner

Civil & Environmental Engineering Faculty Publications

Electrospinning is utilized to fabricate catalytic nanofiber scaffold for biocrude upgrading in hydrodeoxygenation (HDO) following computational studies suggesting the need for nano-catalysts for efficient HDO conversion and selectivity. Here, Pt-TiO2 nanofibers are fabricated through electrospinning, followed by wet impregnation with a heteropoly acid (HPA), tungstosilicic acid. Intensive heat treatments were incorporated during and after processes to obtain a HPA doped Pt-TiO2 nano-catalyst. Catalytic HDO was performed in a batch reactor with phenol as the raw biocrude dissolved in hexadecane. The HPA doped Pt-TiO2 catalyst demonstrated promising HDO performance of 37.2% conversion and a 78.9% selectivity to oxygen …

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Modeling Coupled Driving Behavior During Lane Change: A Multi-Agent Transformer Reinforcement Learning Approach, Hongyu Guo, Mehdi Keyvan-Ekbatani, Kun Xie Jan 2024

Modeling Coupled Driving Behavior During Lane Change: A Multi-Agent Transformer Reinforcement Learning Approach, Hongyu Guo, Mehdi Keyvan-Ekbatani, Kun Xie

Civil & Environmental Engineering Faculty Publications

In a lane change (LC) scenario, the lane change vehicle interacts with surrounding vehicles. The interactions not only affect their driving behaviors but also influence the traffic flow. This study aims to model the coupled behavior of the lane changer and the follower in the target lane during LC. Large-scale real-world connected vehicle (CV) data from the Safety Pilot Model Deployment (SPMD) program are used to extract LCs and study vehicle interactions. A multi-agent Transformer-based deep deterministic policy gradient (MA-TDDPG) method is proposed to model the coupled behaviors during LC. The multi-agent framework can handle the multiple agents’ behaviors with …

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A General Framework For Modeling Subregional Path Effects, T. E. Buckreis, P. Wang, S. J. Brandenberg, J. P. Stewart Jan 2024

A General Framework For Modeling Subregional Path Effects, T. E. Buckreis, P. Wang, S. J. Brandenberg, J. P. Stewart

Civil & Environmental Engineering Faculty Publications

Next Generation Attenuation (NGA) West2 ground motion models (GMMs) include regional path adjustments for broad jurisdictional regions, which necessarily averages spatially variable path effects within those regions. We extend that framework to account for systematic variations in attenuation within subregions defined in consideration of geologic differences. In recent years, cell-based methods which systematically account for spatial variations by summing the attenuation effects over a fine discretization of uniform-rectangular cells (e.g., Dawood and Rodriquez-Marek 2013; Kuehn et al. 2019) have been shown to be an effective alternative to regionalization and a step towards modelling non-ergodic path effects. The main drawbacks of …

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Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman Jan 2024

Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman

College of Graduate Studies: Theses & Dissertations

Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …

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Machine Learning Based Three-Limb Core-Type Transformer Core Aspect Ratios Identification, Ananta Bijoy Bhadra Jan 2024

Machine Learning Based Three-Limb Core-Type Transformer Core Aspect Ratios Identification, Ananta Bijoy Bhadra

College of Graduate Studies: Theses & Dissertations

Power transformers are considered one of the key elements of electric grids. Transient studies include transformer transient analysis which is required for the continuous power supply. However, to perform the transient analysis, the details of the internal structure of the transformer are required which are unobtainable and considered as confidential information. Therefore, the application of topological-based transformer models is limited although the models can accurately represent the transformers. To address this concern, a novel approach utilizing Machine Learning (ML) to identify the core aspect ratios of the three-limb core-type transformer is introduced. The proposed approach, using only the voltage and …

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Numerical Modeling Of Thermal Runaway In Lithium-Ion Batteries Using Decomposition Kinetics And Inter-Cell Contact Resistance, Shehzad Khan Jan 2024

Numerical Modeling Of Thermal Runaway In Lithium-Ion Batteries Using Decomposition Kinetics And Inter-Cell Contact Resistance, Shehzad Khan

College of Graduate Studies: Theses & Dissertations

Lithium-ion batteries (LIBs) are central in numerous high-demand applications due to their high energy density and prolonged cycle life. Despite these advantages, their susceptibility to thermal runaway (TR) poses a significant safety risk, with the potential for catastrophic failures. This study focuses on the thermal behavior of prismatic lithium-ion cells, using a finite volume-based partial differential equation (PDE) solver developed in MATLAB and JULIA to model TR behavior. This solver accurately simulates transient behaviors, convection, diffusion, and source terms across various coordinate systems. By engaging in a series of increasing complex case studies, this research aims to identify the critical …

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A Survey On Few-Shot Class-Incremental Learning, Songsong Tian, Lusi Li, Weijun Li, Hang Ran, Xin Ning, Prayag Tiwari Jan 2024

A Survey On Few-Shot Class-Incremental Learning, Songsong Tian, Lusi Li, Weijun Li, Hang Ran, Xin Ning, Prayag Tiwari

Computer Science Faculty Publications

Large deep learning models are impressive, but they struggle when real-time data is not available. Few-shot class-incremental learning (FSCIL) poses a significant challenge for deep neural networks to learn new tasks from just a few labeled samples without forgetting the previously learned ones. This setup can easily leads to catastrophic forgetting and overfitting problems, severely affecting model performance. Studying FSCIL helps overcome deep learning model limitations on data volume and acquisition time, while improving practicality and adaptability of machine learning models. This paper provides a comprehensive survey on FSCIL. Unlike previous surveys, we aim to synthesize few-shot learning and incremental …

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Triphlapan: Predicting Hla Molecules Binding Peptides Based On Triple Coding Matrix And Transfer Learning, Meng Wang, Chuqi Lei, Jianxin Wang, Yaohang Li, Min Li Jan 2024

Triphlapan: Predicting Hla Molecules Binding Peptides Based On Triple Coding Matrix And Transfer Learning, Meng Wang, Chuqi Lei, Jianxin Wang, Yaohang Li, Min Li

Computer Science Faculty Publications

Human leukocyte antigen (HLA) recognizes foreign threats and triggers immune responses by presenting peptides to T cells. Computationally modeling the binding patterns between peptide and HLA is very important for the development of tumor vaccines. However, it is still a big challenge to accurately predict HLA molecules binding peptides. In this paper, we develop a new model TripHLApan for predicting HLA molecules binding peptides by integrating triple coding matrix, BiGRU + Attention models, and transfer learning strategy. We have found the main interaction site regions between HLA molecules and peptides, as well as the correlation between HLA encoding and binding …

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