Visual Sensing For Comprehensive Granular Traffic Data Collection In Support Of Intelligent Transportation Applications, Linjun Lu

Graduate Theses, Dissertations, and Problem Reports (ETD)

Comprehensive granular traffic data collection has been identified as one of the most essential tasks in the development of intelligent transportation systems (ITS). With the recent advances in electro-optical sensors and computational capacities, machine vision is regarded as cost-efficient for traffic data collection. However, the existing vision-based methods are only applicable for collecting limited types of traffic data, and a unified method allowing for comprehensive traffic data collection is still missing in the existing literature. Moreover, there are still challenges that exist for the use of the existing vision-based methods in real settings, including low accuracy and compromised applicability due …

Development Of Machine Learning Based Approach To Predict Fuel Consumption And Maintenance Cost Of Heavy-Duty Vehicles Using Diesel And Alternative Fuels, Sasanka Katreddi

Graduate Theses, Dissertations, and Problem Reports (ETD)

One of the major contributors of human-made greenhouse gases (GHG) namely carbon dioxide (CO2), methane (CH4), and nitrous oxide (NOX) in the transportation sector and heavy-duty vehicles (HDV) contributing to about 27% of the overall fraction. In addition to the rapid increase in global temperature, airborne pollutants from diesel vehicles also present a risk to human health. Even a small improvement that could potentially drive energy savings to the century-old mature diesel technology could yield a significant impact on minimizing greenhouse gas emissions. With the increasing focus on reducing emissions and operating costs, there is a need for efficient and …

Selective Recovery Of Rare Earth Elements From Acid Mine Drainage Treatment Byproduct, Zeynep Cicek

Graduate Theses, Dissertations, and Problem Reports (ETD)

Rare earth elements (REEs) are critical in emerging clean energy, advanced technologies, and military defense applications due to their unique physical, chemical, optical, and luminescent properties. Given the potential supply chain restrictions imposed by one country's dominance in the global REE market and the consistently growing demand for REEs, developing the US domestic REE supply chain is imperative. Thus, alternative sources are crucial to supply the demand and prevent interruption in manufacturing products that consume REEs. Concurrently, acid mine drainage (AMD) is a long-standing and widespread global challenge the mining industry encounters. AMD is generated in large volumes and continuously …

Nonlinear Dynamic Analysis And Control Of Chemical Processes Using Dynamic Operability, San Quan Dinh

Graduate Theses, Dissertations, and Problem Reports (ETD)

Nonlinear dynamic analysis serves an increasingly important role in process systems engineering research. Understanding the nonlinear dynamics from the mathematical model of a process helps to find the boundaries of all achievable process conditions and identify the system instabilities. The information on such boundaries is beneficial for optimizing the design and formulating a control structure. However, a systematic approach to analyzing nonlinear dynamics of chemical processes considering such boundaries in a quantifiable and adaptable way is yet to exist in the literature. The primary aim of this work is to formulate theoretical concepts for dynamic operability, as well as develop …

Dynamic Modeling, Data Reconciliation, Parameter Estimation, And Health Monitoring Of A Supercritical Power Plant, Katherine Grace Hedrick

Graduate Theses, Dissertations, and Problem Reports (ETD)

With the introduction of a larger portion of renewable sources of power coming onto the U.S. power grid in recent decades, the operational strategy of coal-fired power plants has changed significantly to focus more on flexibility in response to the changing energy market. This has naturally led to different operational challenges. Many of these challenges are focused on the boilers within these plants, as they are producing more emissions and experiencing increased damage during load-following, which in turn leads to increased costs from penalties for not achieving emission standards or maintenance costs as boilers accumulate damage from the cycling behavior. …

Optimal Path Planning For Aerial Robots Using Genetic Algorithm, Anna Puigvert I Juan

Graduate Theses, Dissertations, and Problem Reports (ETD)

This thesis presents a path optimization solution for a robot in two different constrained 3-dimensional (3D) environments. The robot is required to travel from its current position to a goal position following minimum cost paths (optimal paths). The first environment has 3D obstacles that interfere with the robot’s path. The path cost for this environment accounts for the minimum distance traveled by the robot from the start to the goal position while avoiding obstacles. The second environment is the atmosphere of Venus, specifically a flyable region of this atmosphere with characteristics similar to Earth’s. This environment has strong westward winds …

Computational Mechanisms Of Face Perception, Jinge Wang

Graduate Theses, Dissertations, and Problem Reports (ETD)

The intertwined history of artificial intelligence and neuroscience has significantly impacted their development, with AI arising from and evolving alongside neuroscience. The remarkable performance of deep learning has inspired neuroscientists to investigate and utilize artificial neural networks as computational models to address biological issues. Studying the brain and its operational mechanisms can greatly enhance our understanding of neural networks, which has crucial implications for developing efficient AI algorithms. Many of the advanced perceptual and cognitive skills of biological systems are now possible to achieve through artificial intelligence systems, which is transforming our knowledge of brain function. Thus, the need for …

Optimizing Sample Collection And Data Interpretation For Effective Wastewater-Based Epidemiology In Combined Sewer Systems, Christopher Allen Anderson

Graduate Theses, Dissertations, and Problem Reports (ETD)

COVID-19 has spurred growth in the science surrounding wastewater-based epidemiology (WBE) pertaining to the detection of severe acute respiratory virus 2 (SARS-CoV-2) in waste streams as an early warning signal for public health. However, the highly variable wastewater environment has made it difficult to standardize an approach for sampling and analysis, especially in locations using combined sewer infrastructure. This study addresses knowledge gaps of WBE via three specific aims: (1) to compare diurnal fluctuations of SARS-CoV-2 and the human fecal indicator, pepper mild mottle virus (PMMoV) in wastewater treatment plant (WWTP) influent samples collected during dry versus wet weather conditions; …

Structural Health Monitoring Using Machine Learning And Synthetic Data, Michail Tzimas

Graduate Theses, Dissertations, and Problem Reports (ETD)

Structural health monitoring spans many decades of research across multiple engineering fields. However, typical monitoring processes for damage detection of complex structures usually prohibit real-time or fast detection of debilitating damage to the structure. One of the major issues of real-time detection of damage is the enormity of data that needs to be processed, which is worsened by the relative inability of fast relaying of data to structural engineers. With the rapid advancement of Machine Learning, both issues can be overcome, and detection of failure is achieved with non-invasive techniques. This dissertation explores the applicability of Machine Learning as a …

Comparative Analysis Of Artificial Intelligence And Numerical Reservoir Simulation In Marcellus Shale Wells, Arya Maher Sattari

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation addresses the limitations of conventional numerical reservoir simulation techniques in the context of unconventional shale plays and proposes the use of data-driven artificial intelligence (AI) models as a promising alternative. Traditional methods, while providing valuable insights, often rely on simplifying assumptions and are constrained by time, resources, and data quality. The research leverages AI models to handle the complexities of shale behavior more effectively, facilitating accurate predictions and optimizations with less resource expenditure.

Two specific methodologies are investigated for this purpose: traditional numerical reservoir simulations using Computer Modelling Group's GEM reservoir simulation software, and an AI-based Shale Analytics …

Probabilistic Short Term Solar Driver Forecasting With Neural Network Ensembles, Joshua Daniell

Graduate Theses, Dissertations, and Problem Reports (ETD)

Commonly utilized space weather indices and proxies drive predictive models for thermosphere density, directly impacting objects in low-Earth orbit (LEO) by influencing atmospheric drag forces. A set of solar proxies and indices (drivers), F_10.7, S_10.7, M_10.7, and Y_10.7, are created from a mixture of ground based radio observations and satellite instrument data. These solar drivers represent heating in various levels of the thermosphere and are used as inputs by the JB2008 empirical thermosphere density model. The United States Air Force (USAF) operational High Accuracy Satellite Drag Model (HASDM) relies on JB2008, and …

Evaluation Of Changes In Cellular Behavior Upon Exposure To Selected Analytes Used In Synthetic Applications, Olivia L. Rose

Graduate Theses, Dissertations, and Problem Reports (ETD)

Metal-organic frameworks (MOFs) are organic crystalline hybrids that have been used for a variety of applications from catalysis to gas storage and drug delivery. Studies have shown that generally, while such frameworks are more biocompatible than similar aspect ratio nanostructures, they are also more prone to transformation and disintegration due to their flexible and fragile nature as resulted from the structure assembly and implemented structure-function relationships. With extensive previous literature showing that materials with nano dimensions such as carbon nanotubes, quantum dots and other nanomaterials have unique physicochemical properties that lead to increased biosystems’ reactivity. With increasing concerns regarding adverse …

Leveraging Data Science To Promote Sustainable Resource Recovery From Organic Waste Streams In Rural Regions, Mohammed Tamim Zaki

Graduate Theses, Dissertations, and Problem Reports (ETD)

Conventional organic waste management practices such as landfilling contribute to global warming and degrade environmental and human health. Alternatively, organic waste can be treated to recover energy, nutrients, and carbon through resource recovery technologies. Data science could benefit such technologies by improving their efficiency through data-driven process modeling along with reducing environmental and economic burdens via life cycle assessment (LCA) and techno-economic analysis (TEA), respectively.

A critical review of 616 peer-reviewed articles published during 2002–2022 was conducted on the use of data science methods in resource recovery from organic waste. Although applications of machine learning (ML) methods have drastically increased …

Microwave-Assisted Ammonia Synthesis Over Cs-Ru/Ceo2 Catalyst, Alazar Kesete Araia

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ammonia synthesis is one of the greatest innovations of the 20^th century with extensive applications from fertilizers to intermediates for nitrogen-containing chemicals and pharmaceuticals. Annually, more than 242 million tons of ammonia is produced globally, supporting approximately 27% of the world’s population. One of the fast-growing applications for ammonia is as H₂ energy carrier due to its high energy storage capacity, considered to be a decarbonized energy source. The low volumetric energy density and incompressibility makes Hydrogen a non-preferable energy carrier; an alternative carrier becomes a requirement. Ammonia possesses unique property as an energy-dense carrier to store and …

Energy Content Of Grasshoppers (Orthoptera: Acrididae) In The Diet Of Scaled Quail (Callipepla Squamata) In Southeastern New Mexico, J.L. Hunt, M.E. Grilliot, T.L. Best, C.M. Wilkerson, A.F. Huitt

Journal of the Arkansas Academy of Science

Grasshoppers (Orthoptera: Acrididae) are common insects that are important food items for many kinds of wildlife, including many species of upland game birds such as scaled quail (Callipepla squamata). We analyzed the energy content of grasshoppers obtained from the crops of scaled quail collected from plainsmesa sand-scrub in Lea and Eddy counties, New Mexico. Grasshoppers were removed from crops and dried for 48 hours at 60°C to remove moisture and standardize masses. Grasshoppers were then pulverized and analyzed for gross caloric value (i.e., energy content) in an oxygen bomb calorimeter. Energy content of grasshoppers from New Mexico averaged 19.2 J/kg …

Deep Face Morph Detection Based On Wavelet Decomposition, Poorya Aghdaie

Graduate Theses, Dissertations, and Problem Reports (ETD)

Morphed face images are maliciously used by criminals to circumvent the official process for receiving a passport where a look-alike accomplice embarks on requesting a passport. Morphed images are either synthesized by alpha-blending or generative networks such as Generative Adversarial Networks (GAN). Detecting morphed images is one of the fundamental problems associated with border control scenarios. Deep Neural Networks (DNN) have emerged as a promising solution for a myriad of applications such as face recognition, face verification, fake image detection, and so forth. The Biometrics communities have leveraged DNN to tackle fundamental problems such as morphed face detection. In this …

Modular Product Architecture For Sustainable Flexible Manufacturing In Industry 4.0: The Case Of 3d Printer And Electric Toothbrush, Tufail Habib, Muhammad Omair, Muhammad Salman Habib, Muhammad Zeeshan Zahir, Sikandar Bilal Khattak, Se-Jin Yook, Muhammad Aamir, Rehman Akhtar

Research outputs 2022 to 2026

Integrating sustainability, a flexible manufacturing system, and Industry 4.0 resolves the issues of fluctuating market demand arising from customization requirements. Modular products allow flexibility to adapt to changing requirements and optimize resource utilization. In this study, a method was proposed and applied to two products, i.e., a 3D printer and an electric toothbrush featuring modular architecture, multiple product versions, and customization, to contribute to the development of sustainable flexible manufacturing systems. From the results of the two case studies nine modules were identified that contain specific functions and related interface information. From these modules, one platform was developed that comprises …

A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung

Research outputs 2022 to 2026

The concept of Acoustic Source Identification (ASI), which refers to the process of identifying noise sources has attracted increasing attention in recent years. The ASI technology can be used for surveillance, monitoring, and maintenance applications in a wide range of sectors, such as defence, manufacturing, healthcare, and agriculture. Acoustic signature analysis and pattern recognition remain the core technologies for noise source identification. Manual identification of acoustic signatures, however, has become increasingly challenging as dataset sizes grow. As a result, the use of Artificial Intelligence (AI) techniques for identifying noise sources has become increasingly relevant and useful. In this paper, we …

The Compressive Strength And Microstructure Of Alkali-Activated Mortars Utilizing By-Product-Based Binary-Blended Precursors, Otman M. M. Elbasir, Megat A. M. Johari, Zainal A. Ahmad, Nuha S. Mashaan, Abdalrhman Milad

Research outputs 2022 to 2026

Researchers have investigated the feasibility of using ultrafine palm oil fuel ash (u-POFA) as a cement replacement material because of its potential to reduce the environmental impact of concrete production. u-POFA, a by-product of palm oil fuel combustion, is a suitable replacement for Portland cement in concrete mixes because of its sustainability and cost-effectiveness. This study investigated the microstructural and compressive strengths of alkali-activated mortars (AAMs) based on fly ash (FA) and granulated blast-furnace slag (GBFS) being added with varying percentages of u-POFA. The mixture samples were prepared in eighteen mortars using sodium metasilicate (Na2SiO3) as the source material and …

Enhancing Professional Skills Among Engineering Students By Interdisciplinary International Collaboration, Thomas Mejtoft, Helen Cripps, Melissa Fong-Emmerson, Christopher Blöcker

Research outputs 2022 to 2026

Providing necessary knowledge and skills for engineering students to become successful professionals is a tricky task. Besides disciplinary knowledge, e.g., communication skills, ability to work in teams, and international experience are often mentioned as important. Regarding internationalization, most engineering programs in Sweden rely on either student exchange or low-level internationalization-at-home, such as international literature and lecturers. This paper explores sustainable international experiences for students on their home turf provided through an international interdisciplinary collaboration where engineering students in Sweden and marketing students in Australia work together on a project. The setup simulates a consultancy firm with development and marketing offices …

Metal-Organic Framework-Based Biosensing Platforms For The Sensitive Determination Of Trace Elements And Heavy Metals: A Comprehensive Review, Hessamaddin Sohrabi, Shahin Ghasemzadeh, Sama Shakib, Mir Reza Majidi, Amir Razmjou, Yeojoon Yoon, Alireza Khataee

Research outputs 2022 to 2026

Heavy metals in food and water sources are potentially harmful to humans. Determination of these pollutants is critical for improving safety. Effective recognition systems are a contemporary challenge; several novel technologies for the quick, easy, selective, and sensitive determination of these compounds are in demand. Metal-organic framework (MOF)-based sensors and biosensors have crucial applications in identifying these potentially harmful substances. Here, we review electrochemical and optical biosensors for in situ sensing that are sensitive and cost effective, with a simple protocol and wide linear range. Despite the abundance of articles in this field, we assessed and checked out various basic …

Nanoscale Oxygenous Heterogeneity In Fepc Glass For Highly Efficient And Reusable Catalytic Performance, Qi Chen, Lingyu Guo, Haoxiang Di, Zhigang Qi, Zhaoxuan Wang, Ziqi Song, Laichang Zhang, Lina Hu, Weimin Wang

Research outputs 2022 to 2026

Metallic glass, with its unique disordered atomic structure and high density of low-coordination sites, is regarded as the most competitive new catalyst for environmental catalysis. However, the efficiency and stability of metallic glass catalysts are often affected by their atomic configuration. Thus, the design and regulation of the nanoscale structure of metallic glasses to improve their catalytic efficiency and stability remains a challenge. Herein, a non-noble component, Fe75P15C10 amorphous ribbon, is used as a precursor to fabricate a hierarchical gradient catalyst with nanoscale heterogeneous and oxygenous amorphous structure by simple annealing and acid-immersing. The resulting catalyst offers an ultrahigh catalytic …

Uncertainties In Wave-Driven Longshore Sediment Transport Projections Presented By A Dynamic Cmip6-Based Ensemble, Amin Reza Zarifsanayei, José A.A. Antolínez, Nick Cartwright, Amir Etemad-Shahidi, Darrell Strauss, Gil Lemos, Alvaro Semedo, Rajesh Kumar, Mikhail Dobrynin, Adem Akpinar

Research outputs 2022 to 2026

In this study four experiments were conducted to investigate uncertainty in future longshore sediment transport (LST) projections due to: working with continuous time series of CSIRO CMIP6-driven waves (experiment #1) or sliced time series of waves from CSIRO-CMIP6-Ws and CSIRO-CMIP5-Ws (experiment #2); different wave-model-parametrization pairs to generate wave projections (experiment #3); and the inclusion/exclusion of sea level rise (SLR) for wave transformation (experiment #4). For each experiment, a weighted ensemble consisting of offshore wave forcing conditions, a surrogate model for nearshore wave transformation and eight LST models was used. The results of experiment # 1 indicated that the annual LST …

Influence Of Soil Fabric On Dynamic Properties Of Sand: An Experimental Study, Arpit Jain, Satyendra Mittal, Sanjay K. Shukla

Research outputs 2022 to 2026

Natural field sites originate under the action of external sources such as rivers, wind, or marine environments. These sources are responsible for constituting a variety of soil fabrics, which ultimately modify the deformation characteristics. Additionally, the dynamic properties of a site present the characterization of a region and have been profusely utilized by field engineers and researchers. In the present study, the dynamic properties of soil specimens have been evaluated for specimen preparation techniques, namely, air pluviation (AP) and water sedimentation (WS). The cyclic triaxial tests were conducted on the strain-controlled consolidated undrained specimens at a frequency of 0.1 Hz. …

Thermal Curing Effects On Alkali-Activated Treated Soils With Palm Oil Fuel Ash, Lokmane Abdeldjouad, Wisam Dheyab, Yaser Gamil, Afshin Asadi, Sanjay K. Shukla

Research outputs 2022 to 2026

Regarding the significance of binder quantity, alkali activator molarities, and thermal curing, this work was utilized to geopolymerize with a potassium-based alkaline activator to strengthen soils. Five different molarities of palm oil fuel ash (POFA) in four different amounts were utilized to activate the clayey soil. POFA admixtures have been used to test soils. The results showed that for mixtures with 10 and 12.5 molarities, the unconfined compressive strength (UCS) with 15 % and 20 % of POFA was stronger. Comparing the strengths of the blends with various POFA amounts and concentration molarities allowed for this determination. To increase the …

Influence Of Surface Cracking, Anchor Head Profile, And Anchor Head Size On Cast-In Headed Anchors In Geopolymer Concrete, Trijon Karmokar, Alireza Moyheddin

Research outputs 2022 to 2026

In this study, the concrete cone capacity, concrete cone angle, and load–displacement response of cast-in headed anchors in geopolymer concrete are explored using numerical analyses. The concrete damaged plasticity (CDP) model in ABAQUS is used to simulate the behavior of concrete substrates. The tensile behavior of anchors in geopolymer concrete is compared with that in normal concrete as well as that predicted by the linear fracture mechanics (LFM) and concrete capacity design (CCD) models. The results show that the capacity of the anchors in geopolymer concrete is 30%–40% lower than that in normal concrete. The results also indicate that the …

Experimental Assessment Of Hole Quality And Tool Condition In The Machining Of An Aerospace Alloy, Muhammad Aamir, Aamer Sharif, Muhammad Z. Zahir, Khaled Giasin, Majid Tolouei-Rad

Research outputs 2022 to 2026

This paper deals with an experimental investigation of hole quality in Al2024-T3, which is one of the aerospace alloys used in aircraft fuselage skin due to its high level of resistance to fatigue crack propagation. The experiments are conducted with 6 mm uncoated carbide and HSS drill bits using a CNC machine under dry conditions and different drilling parameters. The characteristics of the hole quality are investigated in terms of its perpendicularity, cylindricity, circularity and hole size. An ANOVA (analysis of variance) and Pareto charts are used to analyze the effects of the drilling parameters on the hole quality. The …

Fem Eem Dataset: Optimising Retrofitted Insulation For Irish Residential Building Walls, Rakshit D. Muddu, Aimee Byrne, Anthony Robinson Dr.

Datasets

A large number of combinations of Irish wall types, insulation materials, and heating fuel types were produced to compare the multiple variables which influence Optimal Insulation Thickness values. The total cost (TC) and carbon emission (CE) at optimum insulation thickness (OIT) for all combinations of insulation material and three types of fuel are considered. The dataset presents OIT for solid wall, cavity wall and cavity block wall types located in Monaghan, Dublin, and Kerry.

Exploring The Impact Of Noise And Degradations On Heart Sound Classification Models, Davoud Shariat Panah, Andrew Hines, Susan Mckeever

Articles

The development of data-driven heart sound classification models has been an active area of research in recent years. To develop such data-driven models in the first place, heart sound signals need to be captured using a signal acquisition device. However, it is almost impossible to capture noise-free heart sound signals due to the presence of internal and external noises in most situations. Such noises and degradations in heart sound signals can potentially reduce the accuracy of data-driven classification models. Although different techniques have been proposed in the literature to address the noise issue, how and to what extent different noise …

Comparing Poor And Favorable Outcome Prediction With Machine Learning After Mechanical Thrombectomy In Acute Ischemic Stroke, Matthias A. Mutke, Vince I. Madai, Adam Hilbert, Esra Zihni, Arne Potreck, Charlotte S. Weyland, Markus A. Mohlenbruch, Sabine Heiland, Peter A. Ringleb, Simon Nagel, Martin Beendszus, Dietmar Frey

Articles

Outcome prediction after mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) and large vessel occlusion (LVO) is commonly performed by focusing on favorable outcome (modified Rankin Scale, mRS 0–2) after 3 months but poor outcome representing severe disability and mortality (mRS 5 and 6) might be of equal importance for clinical decision-making.