Digital Commons Network^™

Calculation Of Aquifer Transmissivity From Borehole Resistance Measurements And Pumping Test Results, Fen-Rong Yang, Chien-Wei Huang, Tien-Kuen Huang

Journal of Marine Science and Technology–Taiwan

Transmissivity is a crucial hydrogeological parameter for evaluating groundwater resources. This parameter is conventionally evaluated using pumping tests; however, these tests are costly and can be conducted at few sites. Many researchers have used ground resistance and pumping test data to estimate various hydrogeological parameters. In this study, borehole resistance survey and pumping test data collected by the Taiwan Groundwater Monitoring Network were used to establish the relationship between transmissivity and formation factor for aquifers in the Zhuoshui River alluvial fan. This relationship was then used to estimate the water output of the aforementioned aquifers in a cost-effective manner from …

A Neural Network-Based Sliding Mode Adaptive Control System For Unmanned Surface Vehicles, Sun Qiaomei, An Liang, Jiang Linglin

Journal of Marine Science and Technology–Taiwan

Over the past decades, numerous studies have explored the use of autonomous unmanned surface vehicles (USVs). Successful USV operation requires a robust tracking control system to perform a range of tasks. However, USV dynamics are uncertain, time-varying, and nonlinear. This paper presents a neural network-based sliding mode adaptive control (NNSMAC) system to enhance USV tracking performance. Trajectories were generated using spline and polynomial interpolation based on a set of N predefined waypoints. Simulation results show that the proposed method outperforms traditional sliding mode control in error reduction, enabling more effective tracking.

A Limb-Speed-Driven Locomotor Control System And Its Ability To Adapt, Emily Marie Herrick

Graduate Theses, Dissertations, and Problem Reports (ETD)

Despite how simple walking may seem, the locomotor control system is structurally and functionally complex. Its hierarchical organization of supraspinal and spinal networks with forward and feedback pathways has many interactions at multiple levels that are dependent on the dynamics of a high-dimensional musculoskeletal system. Having a comprehensive understanding of sensorimotor integration within a healthy locomotor control system is crucial for understanding changes to the system due to age or neurologic disease and developing effective technologies to recover mobility in those populations. In this dissertation, we address persistent gaps in knowledge pertaining to how the nervous system controls locomotion.

In …

Rare Earth Element Recovery From Acid Mine Drainage Using Ion Exchange And Selective Precipitation Processes, Paubla Andrea Gallego Lopez

Graduate Theses, Dissertations, and Problem Reports (ETD)

Rare earth elements (REEs) are used in high-tech applications due to their electromagnetic and optical properties. As global demand for REEs surges, the limitation of primary mineral deposits has increased interest in alternative sources. One such source is acid mine drainage (AMD), which, although typically low in REE concentration, offers a promising avenue for recovery. Among the emerging recovery methods, ion exchange has shown promise due to its effectiveness at low concentrations and lower operational cost than conventional techniques such as acid leaching and solvent extraction.

This research focused on developing a recovery process by combining ion exchange with selective …

Using Data Science And Sustainability Assessment Tools To Evaluate Wastewater Treatment Technologies, Haidar Shakuir Aldaach

Graduate Theses, Dissertations, and Problem Reports (ETD)

Wastewater management in small communities has faced numerous challenges in recent years, including population growth, limited budgets for operation and maintenance, and stringent effluent standards required by environmental regulations. These challenges motivate enhancing wastewater treatment processes to protect water quality. Wastewater treatment performance can be improved in small towns and rural regions by implementing data-driven strategies. Data science, life cycle assessment (LCA), and life cycle cost analysis (LCCA) are three data-driven decision-making tools that require data collection, modeling, computational models, and statistical analysis that could be utilized to improve wastewater treatment efficiencies. In this study, these three tools were adopted …

Evaluation Of Small Unmanned Tailsitter Hybrid Air Vehicles Via Full Flight Simulation, Andrew Spencer Winters

Graduate Theses, Dissertations, and Problem Reports (ETD)

Small Unmanned Aerial Vehicles have exploded in popularity in the past 15 years among researchers and for industrial uses such as agriculture, search and rescue, and infrastructure inspection. Fixed wing and multirotor designs present two major paths that can be taken with these technologies. Fixed wing platforms have superior aerodynamic efficiency but require large areas for takeoff/landing and cannot hold a constant position in space, limiting their use. Multirotor configurations offer a more versatile platform that can maneuver in 3 dimensions independently but lack the endurance of fixed wing vehicles. This thesis analyses a quadrotor biplane and a variable wingspan …

Evaluation Of Practical Methods To Determine If A Karst Creek Is Gaining Or Losing: Case Study Of Leith Creek, Elizabeth Jones

Graduate Theses/Dissertations

Karst landscapes are abundant in Missouri, with features such as caves, springs, and sinkholes that form through the dissolution of limestone. Leith Creek is a small stream in Polk County, Missouri fed by two springs and the shallow unconfined Springfield Plateau aquifer, a highly karstified aquifer which is made up of limestone and minor interbedded shale-mudstone units. To determine if Leith Creek is gaining or losing, stream flow, water chemistry and temperature sensors were monitored. Stream flow results required multiple visits to take measurements while temperature sensors required two visits, one to install the dataloggers and another to remove the …

Extraction And Separation Of Metal Cations From Synthetic Acidic Solutions Using Emulsion Liquid Membrane, Nouhaila Filali

Masters Theses

The work is organized into two main papers supported by experimental and comparative studies using Emulsion Liquid Membrane (ELM) systems. The first paper explores the individual extraction of heavy metals (Cd, Cr, As, Ni) from synthetic phosphoric acid using Alamine 336 and D2EHPA as carriers. Alamine 336 achieved the highest extraction efficiency (>90%) and stability, offering a promising route to reduce toxic impurities in fertilizer-grade acid. The second paper examines the selective separation of Ni2+ and Co2+ from various acidic solutions using the ELM configuration. Systematic variation of carriers, stripping agent and feed acidity, clarified transport mechanisms and stability, …

Mitigation Of Antibiotic Resistance Using Ultraviolet Light-Emitting Diodes For Water Treatment, Nicole Heyniger, Patrick J. Mcnamara, Anthony D. Kappell, Brandon Schultz, Troy Skwor, Brooke K. Mayer

Civil and Environmental Engineering Faculty Research and Publications

The presence of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the environment is a growing issue, which has been exacerbated by the overuse and misuse of antibiotics in health care and agricultural systems. One means of mitigating antibiotic resistance is through drinking water and wastewater treatment, specifically during disinfection processes. Ultraviolet light-emitting diodes (UV-LEDs) are an emerging disinfection technology featuring adjustable peak wavelength emissions. We assessed the use of UV-LED for treating waterborne ARB (Escherichia coli and Aeromonas hydrophila) and ARGs (intracellular and extracellular) compared to conventional low-pressure UV (LP-UV). Overall, less efficient reduction (bacterial inactivation and/or gene …

Foreign Object Detection System Development Using Edge Devices Integrated With Quadcopter Autonomous Tracking, Chi-Chia Huang, Ching-Hung Lee

Journal of Marine Science and Technology–Taiwan

This study proposes an all-weather autonomous foreign-object detection system capable of operating in low-light environments. We used a highly mobile quadcopter equipped with an edge-computing device as the inspection platform. On the software side, we integrated a low-light image enhancement model, a path-tracking algorithm, and a foreign object detection model to achieve rapid object detection. A lightweight, low-light image-enhancement model reduces the need for additional lighting equipment, thereby enabling reliable detection under low-light conditions. The path-tracking algorithm integrates a lightweight semantic segmentation model with traditional image-processing techniques to establish flight paths efficiently and reliably. The foreign-object detection component employs state-of-the-art …

Optimization Of Underactuated Ship Sliding Mode Controller Based On The Ddpg Algorithm, Lin Ma, Mingzhe Qi, Shicai Chen, Hongwei Bian, Jian Zhang

Journal of Marine Science and Technology–Taiwan

Due to the development of ship intelligence, the demand for precise controllers is increasing day by day. In traditional design, the trial-and-error method often leads to the use of inaccurate controller parameters, causing oscillations when environmental disturbances are present. To address these issues, this study introduces deep learning to optimize the controller parameters, particularly those used for sliding mode controllers in underactuated ships. We adopt the Deep Deterministic Policy Gradient (DDPG) algorithm based on the Actor Critic framework. By freely setting the reward function to match the control objective, the trained model can output more accurate controller parameters, with the …

An Optimization Model For Supporting Bunkering Decisions In Bulk Shipping, Chung-Cheng Lu, Hui-Chieh Li, Hung-Yu Chen

Journal of Marine Science and Technology–Taiwan

This study addresses a bunkering optimization problem for bulk shipping carriers that explores route deviation to find optimal bunkering locations and amounts. A mixed integer linear programming (MILP) model is developed to determine optimal bunkering decisions that minimize total operating costs, including total daily operating costs, bunkering costs, port charges and surcharges, while observing time window constraints at loading/unloading ports. The proposed model is evaluated using instances generated from real data provided by H company with its operational headquarters in Taipei, Taiwan, which operates a fleet of handysize ships in East and South Asia. The results indicate that optimization models …

Assessment Of Coastal Navigation Safety: A Case Study Of Boka Bay With Stakeholder Perspectives, Ivan Mraković, Rino Bošnjak

Journal of Marine Science and Technology–Taiwan

The navigational safety of Boka Bay, i.e., a critical maritime area along the Adriatic coast, is of great importance owing to its ecological sensitivity, diverse marine traffic, and significant economic activity. This study provides a comprehensive assessment by analyzing the perspectives of various stakeholders, including seafarers, local pilots, skippers, regulatory authorities, and others engaged in maritime activities within the bay. Using a structured questionnaire survey, both quantitative and qualitative data were collected in formats such as descriptive responses, Yes/No choices, and Likert scale ratings, ensuring a well-rounded understanding of navigational practices and challenges. The data were analyzed using descriptive statistics, …

A Hybrid Model To Assess Commercial Port Resilience In Taiwan, Po-Hsing Tseng, James J.H. Liou

Journal of Marine Science and Technology–Taiwan

Since 2021, international commercial ports have faced unprecedented challenges (e.g., COVID-19 pandemic, Suez Canal congestion), impacting daily life, work, human well-being, properties, the environment, and socio-economic activities. The adaptation capability resilience of international commercial ports to respond to external changes has become crucial. This study develops an expert knowledge-based hybrid multi-criteria decision-making model integrating Best-Worst Method (BWM), Rough Dombi Aggregator, and Combined Compromise Solution (CoCoSo) to evaluate port resilience capabilities, using Taiwan's international commercial ports as a case study. We propose four evaluation dimensions encompassing 13 indicators: detection capability, resistance capability, resource integration capability, and recovery capability. The BWM determined …

Nutrient Transport By Overland Sheet Flow On Sites Containing Swine Slurry, John E. Gilley

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Nutrients in agricultural runoff may cause offsite environmental impacts. The objective of this investigation was to examine nutrient transport by overland sheet flow on sites containing swine slurry. Data examined in this study was collected during field rainfall simulation tests conducted on cropland sites in southeast Nebraska, USA. Inflow was added to the top of experimental plots in four successive increments to simulate runoff rates occurring at greater downslope distances. Runoff rates on the experimental sites ranged from 2.3 to 21.2 L min⁻¹ and maximum equivalent downslope distances varied from 5 to 108 m. Phosphorus (P) and nitrogen (N) …

Artificial Intelligence And Seeing The Invisible In Arts - From The Wane Of Axiality And Symmetry To The Wax Of Invisibility And Emptiness, M. Samir Abou El-Seoud

Computer Science

Function has been always an important driver in architectural design. It is the request to generate form directly from purpose and utility. In 1896, Louis Sullivan projected that ‘form follows function’ and that the beauty of a building derives directly from its function and not from references of the built heritage. The assumption was that beauty would naturally derive from design once functional requirements are met. Thus, fitness for purpose equals beauty. In 1908, Adolf Loos even went so far as to ask for the total abandonment of decoration. In 1947, Mies van der Rohe made his paradigm shift, function …

Leaf-Based Varietal Categorization Of Sweetpotato (Ipomoea Batatas L. Lam.), A Potentially Healthful Vegetable, Using Image Processing And K-Means Clustering, Shahidul Islam, Md Towfiqur Rahman, Md Hamidul Rahman, Abdul Momin

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Sweetpotato (Ipomoea batatas Lam) leaves contain higher concentrations of phenolic compounds, flavonoids, and carotenoids that are remarkable in health promotion. However, the nutrient content in sweetpotato leaves varies from variety to variety, and leaf shape and color are the key identifying factors for the varietal classification of sweetpotatoes. So, detecting sweetpotato leaves is essential for the in-situ identification of sweetpotato varieties and for developing intelligent agricultural systems. This study aimed to create a leaf-shape-based varietal classification technique for sweetpotato using image processing techniques coupled with a K-means clustering algorithm. 38 leaf images (RGB) of two sweetpotato cultivars were collected …

Improvement Of Cellular Pattern Organization And Clarity Through Centrifugal Force, Lauren E. Mehanna, James D. Boyd, Shelley Remus-Williams, Nicole M. Racca, Dawson P. Spraggins, Martha E. Grady, Brad J. Berron

Chemical and Materials Engineering Faculty Publications

Rapid and strategic cell placement is necessary for high throughput tissue fabrication. Current adhesive cell patterning systems rely on fluidic shear flow to remove cells outside of the patterned regions, but limitations in washing complexity and uniformity prevent adhesive patterns from being widely applied. Centrifugation is commonly used to study the adhesive strength of cells to various substrates; however, the approach has not been applied to selective cell adhesion systems to create highly organized cell patterns. This study shows centrifugation as a promising method to wash cellular patterns after selective binding of cells to the surface has taken place. After …

Nanotube Spectral Fingerprinting And Machine Learning For Optimized Bioimaging/Sensing And Disease Detection Applications In Als, Rodrigo Monroy Lopez

Open Access Master's Theses

Single-walled carbon nanotubes (SWCNTs) possess unique physicochemical and optical properties that make them ideal candidates for biomedical imaging, biosensing, and disease diagnostics. This thesis explores the potential of SWCNT-based spectral fingerprinting combined with ML (Machine Learning) algorithms to optimize bioimaging, disease detection and prediction, with a specific focus on differentiating between healthy and amyotrophic lateral sclerosis (ALS) lymphoblastic patient samples. By functionalizing SWCNTs with single-stranded DNA, we enhance their stability and target specificity, enabling their application in serum patient samples.

A comprehensive spectral analysis of DNA-SWCNTs was conducted using near-infrared fluorescence spectroscopy and other characterization techniques, including UV-Vis-absorption spectroscopy. The …

The Coral Carousel: A Device And Method For In-Situ Propagation Of Deep-Sea Corals, Gregory Bales

Open Access Master's Theses

The research described herein covers the development of a tool station for performing in-situ propagation of corals using a work class ROV. This includes a system for manipulating coral fragments and affixing them to a cement base plug. To validate this tool station, testing was performed both in the lab as well as at depth in the Gulf of Mexico. As restoration of shallow-water corals has grown in popularity, many techniques have been developed for propagation. However, it is difficult or inappropriate to directly apply these techniques to deep-sea corals. While some forms of diving are capable of approaching the …

Unconditional-To-Conditional Transfer And Optimization For Web-Based Skybox Gan, Crystal Kwong

Master's Projects

Generative adversarial networks (GANs) are known for their ability to generate high quality
images mimicking real life or even particular art styles. Yet for all their capability, casually
training a GAN on an average machine can be infeasible as GANs require an enormous amount
of time and data to train. Even with a trained GAN, model inference demands heavy
computations, making GANs difficult to deploy on applications. To address these limitations,
techniques such as transfer learning and quantization have been leveraged to speed up training of
GANs and lighten computational cost of GAN inference. This project aims to use such …

Annotated 3d Point Cloud Dataset For Traffic Management In Simulated Urban Intersections, Elham Binshaflout, Chaima Zaghouani, Nawfal Guefrachi, Charalampos Antoniadis, Hakim Ghazzai, Ahmad Alsharoa, Gianluca Setti

Electrical and Computer Engineering Faculty Research & Creative Works

Ensuring accurate traffic perception and road safety in complex urban environments remains a significant challenge. Advanced traffic monitoring increasingly relies on deep learning, which requires large data volumes. However, existing datasets are often limited to CCTV video footage or focus on dynamic scenarios captured by sensors mounted on ego vehicles. This narrow perspective reduces the effectiveness of comprehensive traffic monitoring, particularly for LiDAR sensors, which typically capture only the vehicle's viewpoint and miss critical areas such as intersections and pedestrian crossings. To address these limitations, we propose a holistic strategy for rapid data collection in urban settings using simulated 3D …

Effects Of Chain Length, Saturation, And Bases On Saponification, Sarah Fenik

Williams Honors College, Honors Research Projects

This project will analyze the effects of chain length and saturation of fatty acids on saponification processes, as well as the effects of the base used in the reaction. Stearic acid, lauric acid, and oleic acid will be used for the fatty acid comparisons, and sodium hydroxide and potassium hydroxide will be used for the base comparisons. Stearic acid is considered a long chain fatty acid, while lauric acid is considered a short chain fatty acid. Oleic acid is a monounsaturated fatty acid. Five soap products are be made: sodium stearate, sodium laurate, sodium oleate, potassium stearate, and potassium oleate. …

The Current State Of Dimensioning And Tolerancing Pedagogy In United States Post-Secondary Engineering And Engineering Technology Programs, Jaime Berez, Rustin Webster, Rudy Ottway

School of Engineering Technology Faculty Publications

Dimensioning and tolerancing (D&T) is understood to be a crucial element of the engineering product lifecycle and has been documented as an important skill for various careers, e.g., engineering, design, manufacturing, and metrology. Even so, there is a widely perceived skills gap in today's workforce. In response to this perceived misalignment between employer expectations and student preparation, a survey of post-secondary engineering and engineering technology (ET) degree programs in the United States was conducted to quantitatively characterize the current state of D&T pedagogy. Respondents (n = 67) who identified as being the instructor-of-record for a course(s) that required students to …

Automatic Cat Caretaker, Connor Mcclenathan, Ryan Anderson, Andrew Tate

Williams Honors College, Honors Research Projects

This project will involve developing and constructing a self-cleaning litter box with feeding and watering functions attached. The machine will have a user interface for setting both the feeding and watering times, as well as how much to fill the food and water bowls at the same time. The project will involve the use of motors for the cleaning, feeding, and watering functions, sensors to detect when to perform those functions, and a microcontroller to process all the data and to tell the motors when to perform their respective functions. This project's goal is to make the task of caring …

Neurotensin Regulates Primate Ovulation Via Multiple Neurotensin Receptors, Andrew C. Pearson, Jessica S. Miller, Hannah J. Jensen, Ketan Shrestha, Thomas E. Curry Jr., Diane M. Duffy

Department of Biomedical and Translational Sciences Faculty Publications

Neurotensin (NTS), a small neuropeptide, was recently established as a key paracrine mediator of ovulation. NTS mRNA is highly expressed by granulosa cells in response to the luteinizing hormone (LH) surge, and multiple NTS receptors are expressed by cells of the ovulatory follicle. To identify the role of NTS receptors NTSR1 and SORT1 in ovulation in vivo, the dominant follicle of cynomolgus macaques (Macaca fascicularis) was injected with either vehicle control, the general NTS receptor antagonist SR142948, the NTSR1-selective antagonist SR48692, or the SORT1-selective antagonist AF38469. Human chorionic gonadotropin (hCG) was then administered to initiate ovulatory events. …

Design Of An Improved Robust Fractional-Order Pid Controller For Buck–Boost Converter Using Snake Optimization Algorithm, Seyyed Morteza Ghamari, Hasan Molaee, Mehrdad Ghahramani, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

With the increasing complexity of modern power systems, effective control of DC–DC converters has become crucial to ensure stability and efficiency. This paper focuses on optimizing the parameters of a known fractional-order proportional–integral–derivative (FOPID) controller for the control of a DC–DC buck–boost converter. The control of a DC–DC buck–boost converter is achieved using aFOPID approach. The gains of this technique have been enhanced utilizing the snake optimization (SO) algorithm. This converter exhibits unfavourable behaviour due to its non-minimum structure, necessitating a well-regulated controller to guarantee stability. The fractional concept is suggested here to enhance the dynamics of the classical PID …

Techno-Economic And Eco-Friendly Msw-Based Strategy To Reduce The Impact Of Rajshahi City Electric Vehicle Power Outage In Bangladesh, Shah Tanvir Alam Rimon, Md Shahriar Mohtasim, Md Golam Kibria, Mim Mashrur Ahmed, Barun K. Das

Research outputs 2022 to 2026

Population growth, economic expansion, urbanization, and evolving consumer habits are driving a significant increase in municipal solid waste generation, placing Bangladesh under immense societal pressure to manage and dispose of this waste effectively. Numerous studies have examined municipal solid waste management practices in Bangladesh, yet the potential for utilizing the generated energy to charge electric vehicles (EVs) remains unexplored. Therefore, in this study, waste-to-energy technologies such as landfill gas recovery (LGR), incineration (INC) and anaerobic digestion (AD) were assessed for energy recovery, economic feasibility, and global warming potential in Rajshahi City Corporation, Bangladesh, to meet the extra electricity demand imposed …

Joint Channel Allocation And Power Control For Mission-Critical Applications In Sustainable Underwater Acoustic Networks, Sadaf Vahabli, Iftekhar Ahmad, Quoc Viet Phung, Daryoush Habibi

Research outputs 2022 to 2026

Underwater Acoustic Networks (UANs) are gaining popularity for underwater communication due to their long-range capabilities. However, they experience significant challenges, including limited bandwidth and spectrum overlap with marine mammal vocalizations, which raises concerns about the sustainable and ethical use of underwater acoustic resources. This study proposes an eco-friendly approach that integrates joint channel allocation and power control to minimize harmful interference with marine life while ensuring reliable communication for mission-critical applications, such as diver safety. To balance marine protection and communication reliability, this work introduces a strategy for intelligent spectrum management, where nodes first sense the acoustic spectrum to detect …

Optimized Vgg16 For Multi-Class Classification Of Alzheimer's Disease, Amira M. Basuoni, Hussein Seleem, Amira S. Ashour

Mansoura Engineering Journal

Alzheimer’s disease (AD) is a severe neurological disorder that leads to memory loss and other cognitive impairments, ultimately resulting in death. With the advancement of deep learning, several researchers implemented a deep learning (DL)-based classification system for diagnosing such disease. However, determining the proper setting of the parameters, like learning rate and the number of dense units in the classification model is essential to achieve the best performance. Although manual tuning and grid search methods may be used, they are often time-consuming and cannot achieve the optimal model’s design. Accordingly, this paper proposed an improved model of the Visual Geometry …