Engineering Commons^™

Multistage Integrated Systems For Wastewater Treatment And Resource Recovery: A Systematic Process Design Framework, Mahsa Golmohammadi, Ensiyeh Taheri, Ratish Ramyad Permala, Sebastien Allard, Mehdi Khiadani, Amir Razmjou

Research outputs 2022 to 2026

The wastewater treatment paradigm is shifting from pollutant removal toward integrated systems that simultaneously achieve contaminant treatment and resource recovery. Despite extensive literature on individual technologies, systematic frameworks for designing multistage integrated wastewater treatment and resource recovery systems remain notably absent. This review addresses this gap by developing a comprehensive decision framework that guides designers from influent characterization through technology selection across pretreatment, main process, and post-treatment stages. The framework accommodates diverse integration strategies, ranging from fully unified treatment processes to stage-specific configurations where each treatment stage employs technologies tailored to its designated function. Rather than optimizing for a single …

Optimizing Few-Shot Learning In Pruned Large Language Models With Task-Specific Prompts, Danyal Aftab

Dissertations

Few-shot learning enables large language models to efficiently perform tasks given only a limited number of labeled examples. However, training these models entirely from scratch requires substantial computational resources, making it challenging for many organizations to fully leverage their potential. This thesis explores how structured pruning, task-specific prompting, and parameter-efficient fine-tuning can be combined to preserve few-shot learning capabilities in compressed LLMs, while also extending their utility to real-world recommendation systems.

In this research, we propose the Tailored LLM framework, which first reduces model size through structured pruning and then enhances few-shot learning performance using carefully designed prompts. We experiment …

Secure And Compassionate Dementia Care: Non-Intrusive Remote Monitoring Of Falls, Wandering, And Agitation, Awan-Ur- Rahman

Master's Theses

Alzheimer’s disease and related dementias (ADRD) present significant safety challenges, as affected individuals may experience falls, wandering, agitation, and a progressive decline in independence. Although continuous monitoring can enable timely intervention, many existing systems rely on cameras or wearable devices, which may introduce concerns related to privacy, comfort, and sustained use. This thesis explores privacy-preserving and non-intrusive remote monitoring through two complementary studies. The first study presents an ambient Wi-Fi channel state information framework for recognizing agitation and eight daily activities. The proposed approach translates behavioral and physiological markers commonly captured by wearable sensors into the Wi-Fi sensing domain. The …

Constructing Female High School Students’ Stem Self-Efficacy: The Role Of High School Stem Research Experiences, Hyunjin Son

Dissertations

In the U.S., nearly a quarter of the workforce is employed in Science, Technology, Engineering, and Mathematics (STEM) occupations. However, the STEM workforce lacks diversity, limiting perspectives to address real-world problems facing society. While many factors influence decisions to pursue STEM majors in college and enter the STEM workforce, one factor commonly associated with performance and persistence in STEM is STEM self-efficacy. Independent research experiences have been shown to increase conceptual understanding and confidence in STEM, leading to STEM degrees and careers. As high school co-curricular STEM research opportunities become more common, the effects of such experiences on students’ STEM …

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Prompt-Driven Tabletop Robotic Manipulation With A Structured Llm Interface And Visual Verification, Tomas Franco

Master's Theses

Creating a tabletop robotic manipulation system that connects language goals to robot actions is a challenging problem. Large language models can interpret mission objectives and reason through actions, but when placed directly in control of hardware they can produce hallucinated commands that result in unsafe behavior without the proper safeguards.

This thesis presents a constrained LLM-guided manipulation system built around the Quanser Qarm, a four degree of freedom manipulator with a mounted Realsense RGB-D camera and a gripper with readable current. Every decision made by the LLM planner is routed through a gated command interface that restricts the model to …

Hardware-In-The-Loop Evaluation Of Sensor-Source Selection For Prosthetic Locomotion Intent Recognition, Victoria Asencio-Clemens

Master's Theses

Active lower-limb prostheses use intent-recognition systems to identify a user’s locomotion mode and select an appropriate control strategy, but sensor configurations that perform well offline may be unsuitable for resource-constrained embedded hardware. Existing sensor-selection methods generally prioritize classification accuracy without directly accounting for processing latency, memory usage, or other hardware-dependent requirements. To address this limitation, this thesis develops a hardware-in-the-loop source-selection framework for embedded classification of level walking, ramp ascent, ramp descent, stair ascent, and stair descent using multimodal biomechanical data from transtibial amputee participants. Subject-specific linear support vector machine classifiers were evaluated using trial-held-out validation, and candidate configurations from …

Predicting Student Belonging In Computing Education: A Multimodal Machine Learning Approach Using Eeg And Survey Data, Hannah Moshtaghi

Master's Theses

Measuring students’ sense of belonging, characterized by feelings of acceptance, inclusion, and encouragement from teachers, remains a significant challenge in computing education. Prior research has associated this multidimensional construct with positive academic outcomes and has identified instructors’ growth- and fixed-mindset messaging as a potential influence. However, belonging is a complex and deeply personal experience that is difficult to capture through direct observation alone. Current measurement methods rely on self-report surveys, which may not capture every aspect of an experience that can also involve emotional and cognitive responses.

This thesis investigates whether combining EEG data recorded during a belonging questionnaire with …

A Maintainable Extensible And Performant Compiler Toolchain For The Trustguard Architecture, Ethan N. Emery

Master's Theses

TrustGuard is a hardware architecture implementing a CAVO (Containment Architecture with Verified Output) model, which provides security guarantees by bootstrapping trust of a system to a hardware component known as the Sentry. Rather than verifying an entire system, TrustGuard re-executes trusted computation on the Sentry and validates the host system's execution before allowing values to pass to the outside world, thereby containing the effects of erroneous computation. Implementing this architecture in practice without hardware modifications to a host CPU requires a compiler toolchain capable of automatically generating instrumented binaries for both the untrusted host and the trusted Sentry from C …

Synthesis And Characterization Of Carbon Quantum Dots And Gold Nanoparticles For Norovirus Biosensing Applications In Water Systems, Breanne Evans

Master's Theses

Rapid, reliable detection of viral pathogens remains a significant challenge across water-treatment and environmental monitoring systems, including drinking-water, wastewater, water reuse, and environmental surveillance applications. Waterborne viral contamination can pose substantial public-health risks, making early detection essential for protecting water quality and responding quickly to treatment failures or contamination events. Direct potable reuse (DPR) is one particularly demanding example because it requires continuous verification of treatment performance and the broader need for rapid virus monitoring extends across many water-treatment and environmental surveillance applications. Norovirus is a priority target because of its widespread occurrence in wastewater, environmental persistence, and exceptionally low …

Understanding The Correlation Between Prediction Performance And Trust In Ai Through Scenario-Based Tasks, Likhitha Kammara

Theses and Dissertations

Trust in artificial intelligence is commonly assessed through self-reported scales or behavioral reliance, yet behavioral reliance is retrospective and can only be observed after a decision has already been made. This thesis examines whether prediction accuracy — a user's ability to predict what an AI system will recommend before its output is revealed — can serve as a prospective correlate of trust in the same empirical sense as behavioral reliance. The study was conducted in two phases using scenario-based AI decision tasks across disaster response, healthcare, and infrastructure restoration contexts, employing a between-group design in which participants either predicted AI …

Review: Mechanics Of Mycelium Materials, Md Anwar Sadat Anik, Ehsanul Azim, Gerardo I. Zapata, Mohammad R. Islam

Mechanical Engineering Faculty Publications

The biological growth of fungal root structure, called mycelium, can be engineered to develop innovative fibrous and biocomposite materials. Mycelium materials have potential as sustainable alternatives to petroleum-derived materials for load-bearing applications. To realize this potential, there is an increasing effort dedicated to understanding the mechanics of mycelium materials. This work presents a systematic review of our current understanding of the mechanics of mycelium materials with a specific focus on structure–property relationships. The review first explores how the mycelium’s fiber network structure varies depending on whether it is grown as a two-dimensional (2D) membrane, a cellular foam, or as a …

Automated Battery Management Systems For Electric Vehicles, Woonki Na, Yuanyuan Xie

Mineta Transportation Institute

Electric vehicle (EV) safety, efficiency, and lifetime are strongly influenced by how well battery cells are managed, and as EV adoption accelerates, improving battery performance has become critical to vehicle reliability, cost, and public trust. This report conducts a field study on the core technologies and challenges in Battery Management Systems (BMS), focusing on the classification of BMS circuit topologies (design/structures) and systematically reviewing different topologies of active cell balancing circuits (systems that move energy from stronger battery cells to weaker ones). The study provides a detailed analysis of the working principles, advantages, and disadvantages of various active balancing circuit …

Morphological Determinants Of Multiple Courtyard Configurations In Contemporary Urban Housing: A Quantitative Analysis Of Plot Area And Frontage Width, Maha Khalaf Hammad, Hasan Abdulrazzaq Hasan

AUIQ Technical Engineering Science

In modern cities with small plots and narrow frontages, courtyard-based housing has come back as a flexible way to use space. This study seeks to quantitatively examine the impact of residential plot area and frontage width on the diversity and functional distribution of courtyards in modern urban housing. A quantitative morphological approach was used by looking at the shapes of 121 modern residential plans that included internal courtyards. Using AutoCAD, we got spatial data, and then we used Microsoft Excel to look at the relationships between plot morphology, courtyard number, area, and functional role. The results show that the courtyard …

Integrating Ai-Based Electricity Demand Forecasting With Solar Grid Planning To Enhance Sustainability And Reliability, Anas Thamer Mustafa, Omar Sharaf Al-Deen Al-Yozbaky

AUIQ Technical Engineering Science

Proper electricity-demand forecasting is essential for reliable power-system planning, particularly in urban networks facing rapid demand growth and transformer overloading. However, many previous studies have treated load forecasting and renewable-energy integration as separate tasks, which limits their usefulness for practical planning. This study develops an integrated forecasting–planning framework that links AI-based electricity-demand forecasting with photovoltaic (PV) system design and transformer-loading assessment. The framework is applied to real daily data from the Al-Intisar 132/33 kV substation in Mosul, Iraq, covering electrical load, temperature, population, and date-related variables for the period 2022–2024. Fourteen forecasting models from four methodological categories were evaluated: machine-learning …

Evaluating Machine Learning Models On Classification Of Novel Cyber Attacks In The Healthcare Domain, Promise Ehimen

Dissertations, Theses, and Projects

The increasing adoption of the Internet of Medical Things (IoMT) has improved healthcare delivery through connected medical devices while simultaneously expanding the cybersecurity risks facing healthcare organizations. Although machine learning based intrusion detection systems have demonstrated high detection accuracy, their ability to respond reliably to previously unseen cyberattacks remains uncertain. This study investigated how a Neural Network model and a Logistic Regression model classified novel cyberattacks within the IoMT environment. The Neural Network and Logistic Regression models were both trained and tested using a subset of the CICIoMT2024 benchmark dataset. The Neural Network achieved 99.82% test accuracy and a 0.94 …

Radiation Testing And Failure Analysis Of A Complex Heterogeneous Soc, Garrett Smith

Theses and Dissertations

Heterogeneous System on Chips (SoCs) provide a robust platform that can flexibly handle different applications. Their small form factor and low power consumption for their performance have made SoCs an attractive option for space applications. However, SoCs are sensitive to the ionizing radiation found in space. We need to understand how an SoC will behave in the high radiation found in space. This requires us to perform radiation testing of the SoCs on Earth to understand their behavior. The radiation testing and analysis of a heterogeneous SoC is complex as it contains multiple different processing cores, memories, and other system …

Systematic Review Of The Institutionalization Of Service Learning In Higher Education, Wilmer Hernan Cruz Gutierrez

ASEAN Journal of Community Engagement

An increasing number of universities are integrating service-learning (SL) to fulfill their social mission. However, sustainable institutionalization of SL remains a persistent challenge. This study identifies and analyzes the factors, actors, and strategies that drive and inhibit SL institutionalization in higher education. Using the PRISMA 2020 guidelines, a systematic literature review analyzed 52 documents from seven academic databases (including WoS, Scopus, and ERIC). The findings were grouped into three sections: cultural (integration into institutional values/missions), process (articulation within teaching, research, and outreach), and structural dimensions (dedicated support entities). The results obtained reveal a reciprocal relationship where cultural alignment enables processual …

Digraphicsoft Sets And Bidigraphicsoft Sets: Directed And Bidirected Extensions Of Graphicsoft Modeling, Takaaki Fujita, Ajoy Kanti Das, Suman Das, Sankar Prasad Mondal, Volkan Duran, Mithun Datta

Neutrosophic Systems with Applications

Uncertainty has been modeled through a wide variety of mathematical frameworks, including fuzzy sets, neutrosophic sets, rough sets, and plithogenic sets. Among these approaches, soft sets offer a parameterized representation of uncertain information and have inspired numerous extensions, such as multisoft sets, double-framed soft sets, hypersoft sets, SuperHyperSoft sets, TreeSoft sets, ForestSoft sets, IndetermSoft sets, and IndetermHyperSoft sets.
This paper focuses on GraphicSoft Sets, which extend the classical soft-set framework by assigning a subset of the universe to each subgraph of an attribute graph. In this way, relationships among attributes are incorporated directly into the parameterized model. Building on …

Foundations Of Neutrosophic N-Semirings Theory And Structural Properties, Raja Muhammad Hashim, Muhammad Gulistan, Muhammad Shahzad

Neutrosophic Systems with Applications

In this paper the concept of neutrosophic n-semirings (S∪ I, ∗ ₁, ∗ _2, ∗ ₃,..., ∗ _n, ∗ _n+1) has been introduced. The substructure of n-semirings (S∪ I, ∗ ₁, ∗ _2, ∗ ₃,..., ∗ _n, ∗ _n+1) has been defined and some useful results have been proved. Moreover, in order to familiarize the readers with these concepts some worthy examples have been coined. The left, right and two sided ideals of neutrosophic n-semirings have been paid a special heed. Finally we have turned our discussion towards the compatible and congruence …

A Fuzzy–Neutrosophic Suitability Index For Selecting An Appropriate Reasoning Model Under Vagueness, Incompleteness, And Conflict, Nada A. Nabeeh, Ahmed Samy

Neutrosophic Systems with Applications

Fuzzy reasoning and neutrosophic reasoning are both used to handle uncertainty, but they are not intended for the same uncertainty structure. Fuzzy reasoning is suitable when uncertainty appears mainly as gradual vagueness, where a value may belong to a concept such as ``high risk'' or ``good performance'' to a certain degree. In this case, a membership value is often sufficient. Neutrosophic reasoning is more suitable when the problem also contains incomplete information, undecided evidence, or conflict between sources. In such cases, one membership degree may be too limited because it cannot represent support, rejection, and indeterminacy separately. This study introduces …

Evaluating Generative Ai-Based User Interfaces Using An Integrated Neutrosophic Multi-Criteria Decision-Making Framework, Nada Mohamed, Alshaimaa A. Tantawy

Neutrosophic Systems with Applications

User Interface (UI) design can be seen as an essential aspect of human-computer interaction (HCI) and makes communication easier between people and technology. In today's digital economy, interface quality has become one of the most important business concerns, since it has a direct impact on customer satisfaction and retention while affecting revenue. Although creating user-centered and accessible interfaces is crucial, doing so is a difficult and time-consuming process, which leads to burnout for many usability professionals. Although conventional artificial intelligence (AI) was utilized for design assessment and automation, the arrival of generative AI technology has created new possibilities for automated …

Neutrosophic Time-Truncated Acceptance Sampling Plans Based On The Exponentiated Weibull Distribution For Reliability Applications, Divya P.R., Preethi John

Neutrosophic Systems with Applications

Classical acceptance sampling plans require precisely specified parameter values, an assumption routinely violated by measurement uncertainty and gauge imprecision in practice. This article develops Neutrosophic Time-Truncated Acceptance Sampling Plans (N-TTASP) for the Exponentiated Weibull (EW) distribution by representing the scale parameter as a neutrosophic interval. The neutrosophic sample size n_N ∈ [n_L, n_U] and acceptance number c_N ∈ [c_L, c_U] are obtained by minimizing n_U subject to dual producer and consumer risk constraints on the neutrosophic Operating Characteristic interval. A new indeterminacy ratio η is introduced as a …

Enhanced Transdermal Immunization Via Solid-In-Oil Nanodispersions Incorporating Dendritic Cell-Targeting Peptide, Md Samiul Islam, Md. Shahin Ekka Sarker, Yoshirou Kawaguchi, Rie Wakabayashi, Noriho Kamiya, Muhammad Moniruzzaman, Masahiro Goto

Publications and Research

Transdermal immunization represents a promising needle-free alternative to conventional vaccination. However, efficient antigen delivery and robust immune activation remain major challenges. In this study, a solid-in-oil (S/O) nanodispersion system comprising a dendritic cell-targeting peptide (HR8), ovalbumin (OVA), and an adjuvant was developed for transdermal immunization. The HR8 peptide along with OVA was successfully incorporated into an S/O nanodispersion with an optimal hydrodynamic diameter of particles (< 200 nm) and exhibited stable physical properties for up to 90 days. In vitro and in vivo studies demonstrated enhanced antigen delivery with insignificant skin irritation in C57BL/6N mice. Moreover, in vivo transdermal immunization studies demonstrated that the addition of the HR8 peptide enhanced OVA-specific IgG responses (~1.5-fold). Notably, the HR8 peptide also promoted an approximately 2.5-fold increase in IgG2c levels, suggesting a shift toward a more T helper type 1-biased immune response, as reflected by an increased IgG2c/IgG1 ratio. Overall, these findings demonstrate that the incorporation of HR8 peptide into an S/O nanodispersion enables efficient transdermal antigen delivery and improved immunogenicity, highlighting its potential as a simple, non-invasive, and patient-friendly immunization strategy.

Thermal Degradation Analysis Of Bagasse Fibers From Sugarcane Waste, Rashmitha Suresh, Faisal Al Nasser

Journal of Mechanical Engineering Science and Technology (JMEST)

Sugarcane is one of the important commodities in the industry where bagasse fiber as waste is abundantly available.   Sugarcane bagasse fiber has high cellulose, a key element in the utilization of bagasse. Chemical pretreatment is important to prepare the natural fiber before used as composite reinforcement. The purpose of the study is to analyze the thermal degradation of bagasse fiber after being treated using NaOH and TEMPO solution. The manufacturing method was carried out by a series of washing bagasse with distilled water and NaOH solution, subsequently soaking it in 6% NaOH and 2,2,6,6-tetramethylpiperidine-l-oxyl (TEMPO) solution, and conducted oven-dried. Thermogravimetric …

Powered Parachute Vehicle For Crew Transportation On Mars, Louis J. Spier

Beyond: Undergraduate Research Journal

To support possible future human presence on Mars where bases are likely to be spread apart, aerial vehicles could be used to transport crew and cargo between them. Designing and operating such a vehicle is very challenging because of the low atmospheric density on Mars compared to Earth, the logistics involved with transporting it to Mars, and the infrastructure necessary to operate it. This study discusses the problems involved with designing, building, and operating fixed-wing and powered parachute aircraft on Mars and presents a concept involving a powered parachute vehicle utilizing an inflatable parachute wing that can be packed together …

Spatial Analysis Of The Environmental And Climatic Explanatory Relationship Of Photovoltaic Potential For Sustainable Shrimp Farming, Dyah Lestari Widaningrum, Roikhanatun Nafi'ah, Religiana Hendarti, Alexandra Catherine Djunaedi, Evaristus Didik Madyatmadja

Journal of Environmental Science and Sustainable Development

Sustainable shrimp aquaculture requires reliable and affordable energy, particularly for coastal pond aeration. However, identifying suitable locations for photovoltaic (PV) deployment remains challenging because ground-based solar-resource measurement is expensive, spatially limited, and difficult to maintain across large coastal regions. This study develops a village-level spatial framework to evaluate PV potential for shrimp aquaculture using open geospatial datasets. The analysis covered villages across Central Java, Special Region of Yogyakarta, and East Java. PV power potential (PVout), Global Horizontal Irradiation (GHI), and Direct Normal Irradiation (DNI) were obtained from the Global Solar Atlas; land surface temperature (LST) and precipitation were derived from …

Emergent De Sitter Expansion And Closed Topology From The Cosmic Fabric Model As An Open Thermodynamic System: Resolving The Negative Bulk Modulus Paradox, T G. Tenev, C B. Ward, T F. Tenev, M F. Horstemeyer

Faculty Publications and Presentations

The Cosmic Fabric Model establishes a continuum-mechanics isomorphism to General Relativity by representing physical space as an elastic three-dimensional hyperplate embedded in a four-dimensional spatial bulk. Reproducing vacuum kinematics requires a vanishing P-wave modulus, which in turn implies a negative bulk modulus—an apparent thermodynamic instability in a closed system. This paradox is resolved by recasting the framework as an open system: the instability is not pathological but instead drives cosmic expansion. In this interpretation, the observable universe is a lower-energy solid formed through continuous solidification from a higher-dimensional precursor fluid. Using multiplicative kinematics from finite-growth mechanics, the model shows that …

Ascc-M Based Transformational Education Model For Enhancing Carbon Literacy And Agroecological Resilience Among Rural Farmers, Alya Dwi Arianty, Fitria Fatichatul Hidayah, Eny Winaryati, Rica Mae Badilla Guarin

Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktek dalam Bidang Pendidikan dan Ilmu Geografi

Climate change has become a major ecological and social challenge affecting food security and agricultural sustainability worldwide. The agricultural sector significantly contributes to carbon emissions through fertilizer use and land conversion, particularly in developing countries. This study aims to conceptualize a place-based, technology-enhanced Transformational Education Model grounded in Agro-Smart Carbon Capture Microbiome (ASCC-M) technology, designed to strengthen rural farmers' carbon literacy and agroecological resilience while advancing geography education through deeper understanding of human–environment interactions, spatial agricultural processes, and climate-related dynamics within real rural landscapes. The research employed conceptual design through systematic literature review and model development, integrating theories of transformative …

Modeling Of Air-Water Filled Rubber Dam Under Hydrostatic Conditions, Qusay Khaleel, Thair Khayyun, Khudhayer Abdullah

Engineering and Technology Journal

Inflatable dams, also called rubber dams, are flexible cylindrical inflatable and deflatable structures attached to a rigid base; these dams are basically cylindrical tubes made of rubberized material and inflated by air, water, or a combination of the two. In this paper, the air/water inflatable dam was studied and analyzed numerically using ANSYS software. The 3-parameter Mooney-Rivlin Model was used to model the rubber material of the dam. At first, a physical model from literature was used to calibrate the results of the ANSYS software, and then a new model was analyzed with different dimensions and conditions. Thirty-six simulations were …