Digital Commons Network^™

Aiw26s: Machine Learning Of Structured Data, Moumita Saha

Paul English Applied Artificial Intelligence (AI) Institute Publications

This workshop introduces the fundamentals of machine learning for structured data, focusing on tabular datasets and real-world applications. Participants explore key concepts such as data types, data preprocessing, feature engineering, and supervised learning methods. The session covers commonly used models, including linear regression, logistic regression, decision trees, and neural networks, along with evaluation metrics such as RMSE, accuracy, and confusion matrices. By the end of the workshop, participants will have gained a practical understanding of how to build, interpret, and evaluate machine learning models for structured data.

An Integrated Bayesian Network-Based Zero Trust Model To Quantify Cyber Risk In Small-Medium Businesses, Ahmed Abdelmagid

Engineering Management & Systems Engineering Theses & Dissertations

Small-medium businesses (SMBs) play a pivotal role in the worldwide economy as they constitute the most considerable portion of businesses in developed countries like the UK and the US. As such, SMBs are likely targets of cybercrimes by malicious agents because of their vulnerable IT systems. The digital infrastructure of SMBs is more likely to be hit by cyberattacks than large businesses due to many factors that facilitate hackers’ missions. These factors include a limited financial budget devoted to cybersecurity, a lack of knowledge, an underrating of how dangerous cyber threats are, and a shortage of IT expertise. The enormous …

Shadowrunning The Human: Harebrained Schemes' Shadowrun Series And Transhumanism, Alexander P. Orelup

English Theses & Dissertations

I argue that Harebrained Schemes’ video game series Shadowrun critiques transhumanism in three distinct yet related ways: in terms of religion, political control, and identity capitalism. In doing so, Shadowrun attempts to counter claims that video games are an inherently transhumanist medium and provides an opportunity for players to resist a potential transhuman future. This further elucidates the trends and perceptions of transhumanism within American culture around the time period. I utilize a variety of methodologies in my argument, ranging from cultural studies, narratology, ludology, and close reading in order to grasp all of the audio-visual and gameplay elements that …

Workforce Resilience In Public Transportation Agencies, Kristal D. Metro

Civil Engineering ETDs

A strong, resilient public workforce is necessary to keep the United States’ infrastructure system running smoothly. Across the public sector, hiring is lagging behind increasing retirement rates, leaving public agencies facing the loss of institutional knowledge at unprecedented levels. Combined with above-average retirement rates, low unemployment rates, and below-average salaries, workforce shortages are expected to become critical, putting the resilience of the public transportation workforce, and by extension, the United States public infrastructure and services at risk. The purpose of this research is to determine the best practices for recruiting and retaining employees at public transportation agencies, thereby positively influencing …

Comparative Kinetic And Thermal Characterization Of A Full-Length And Truncated Variant Of Endo-Β-1,4-Glucanase From Bacillus Subtilis, Cara Giordano

Bioengineering Master's Theses

The enzyme Endo-β-1,4-Glucanase from Bacillus subtilis, commonly known as BsCel5A, catalyzes the hydrolysis of β-1,4-glycosidic bonds in cellulose aiding in biomass deconstruction and its conversion into fermentable sugars. Efficient, thermostable cellulases are critical for reducing the cost and energy demands of lignocellulosic bioprocessing. Unfortunately, many naturally occurring enzymes are limited by activity rate and stability in bioprecessing conditions, especially high temperatures. In this study, we compared the catalytic and thermal properties of wild-type BsCel5A (BsCel5A‑WT) and a truncated catalytic core variant (BsCel5A‑CC) to evaluate their efficiency and thermostability. The catalytic and thermal properties were investigated through the hydrolysis of …

Life Cycle Costing Of Modular Timber Residential Construction, Logan Micah Hammel

Construction Management

This study examines the economic feasibility of modular residential construction using life-cycle costing (LCC) and life-cycle assessment (LCA) approaches to assess the sustainability and maintenance costs of modular construction. Using the structures and documents from the Gateway Decathlon project as the subject, we applied LCC formulas and programs to assess their economic performance. These calculations were conducted manually in Excel and modeled using the OpenLCA platform to compare traditional and software-based approaches. The study aims to identify cost drivers across building scopes, such as building materials and electrical and mechanical systems, and to evaluate how modular construction performs over its …

Dirges Of Hope, Manasseh Azure Awuni

Department of English: Dissertations, Theses, and Student Research

Among the varied themes that African fiction explores, politics and governance remain the most dominant across generations. Writing under oppressive and exploitative colonial administrations, the first generation of African storytellers used fiction to highlight the injustice of colonial rule. With fidelity to the African proverb that says the tales of hunting will always glorify the hunter until the lion learns to tell its own stories, African writers also used fiction to push back against one-sided, toxic narratives about the continent. After independence, when rulers of the new republics continued the colonial legacies of oppression, inflicting untold hardships on their citizens, …

Sustainability In Concrete: Decision-Makers, Dismissal Points, And A Framework For Implementation, Max Dennison

Construction Management

Concrete is essential to modern infrastructure, but is also one of the largest sources of embodied carbon, with cement production alone responsible for a significant share of global CO₂ emissions. Although low-carbon and otherwise “sustainable” concrete technologies are growing, their use in everyday projects remains limited. This research investigates why sustainable concrete options are most often dismissed during the project lifecycle, who drives these decisions, and what conditions are needed to enable broader adoption. Using a combination of literature review and semi-structured interviews with professionals in contracting, life-cycle assessment, sustainability consulting, and materials production, the study maps decision points from …

Semat: Semantic Enhanced Natural Image Interactive Matting, Ruihao Xia, Yu Liang, Peng-Tao Jiang, Hao Zhang, Qianru Sun, Yang Tang, Bo Li, Pan Zhou

Research Collection School Of Computing and Information Systems

Recent approaches attempt to adapt powerful interactive segmentation models, such as SAM, to interactive matting and fine-tune the models based on synthetic matting datasets. However, models trained on synthetic data fail to generalize to complex and occlusion scenes. We address this challenge by proposing a new matting dataset based on the COCO dataset, namely COCO-Matting. It selects real-world complex images from COCO and converts semantic segmentation masks to matting labels. The built COCO-Matting comprises an extensive collection of 36,980 human instance-level alpha mattes in complex natural scenarios. Furthermore, existing SAM-based matting methods extract intermediate features and masks from a frozen …

Bridging Bug Localization And Issue Fixing: A Hierarchical Localization Framework Leveraging Large Language Models, Jianming Chang, Xin Zhou, Lulu Wang, David Lo, Bixin Li

Research Collection School Of Computing and Information Systems

Automated issue fixing is a critical task in software debugging and has recently garnered significant attention from academia and industry. However, existing fixing techniques predominantly focus on the repair phase, often overlooking the importance of improving the preceding bug localization phase. As a foundational step in issue fixing, bug localization plays a pivotal role in determining the overall effectiveness of the entire process. To enhance the precision of issue fixing by accurately identifying bug locations in large-scale projects, this paper presents BugCerberus, the first hierarchical bug localization framework powered by three customized large language models. First, BugCerberus analyzes intermediate representations …

Evolution Of Antibiotic Responses During Chronic P. Aeruginosa Infections In The Human Lung, David Frank Ritz

Dartmouth College Ph.D Dissertations

Typical antibiotic susceptibility testing (AST) of microbial samples is performed in homogeneous cultures in batch environments, which does not account for the highly heterogeneous and dynamic nature of antibiotic responses. The most common mutation found in P. aeruginosa lineages evolved during chronic cystic fibrosis infections in the human lung, a loss of function of repressor MexZ, increases basal levels of multidrug efflux MexXY, but does not increase resistance by traditional minimal inhibitory concentration (MIC) assays. Here, we use single cell microfluidics to show that P. aeruginosa’s response to aminoglycosides is highly heterogeneous, with only a subpopulation of cells surviving exposure. …

Behavioral-Centric Team Evaluation Via Consistent Rewards, Clement Kudakwashe Nyanhongo

Dartmouth College Ph.D Dissertations

Across human domains ranging from sports to business and organizational settings, complex tasks are often solved by teams rather than individuals, leveraging benefits such as interaction, mutual support, complementary skills, cohesion, and task allocation. Evaluating team effectiveness, however, is inherently challenging due to the subjectivity of many existing techniques and the limitations of outcome-driven metrics that primarily focus on performance scores while overlooking the team processes that generated the scores. To address these challenges, this dissertation proposes a behavioral-centric, end-to-end framework for team evaluation grounded in reward functions that model sequential team behavior. Reward functions offer compact and interpretable representations …

Advancement And Characterization Of Next-Generation Solid-State Photon-Counting Image Sensors For Astrophysics Applications, Nicholas R. Shade

Dartmouth College Ph.D Dissertations

Astronomers’ pursuit of detecting light from increasingly faint and distant objects in the expanse of space necessitates continuous improvement in signal-to-noise ratio of camera technology. Recent advancements in solid-state detector technologies have enabled the determination of photon-number, including single photon events, enabling observations at the fundamental limits of physics. These developments are instrumental not only for standard two-dimensional imaging but also for advanced spectroscopy, which increasingly drives future astrophysical applications. This thesis presents an evaluation of three next-generation silicon-based detectors capable of photon-counting with deep-sub-electron input-referred read noise: the electron-multiplying charge-coupled device (EMCCD), the single-photon avalanche diode (SPAD), and the …

Hybrid Portfolio Optimization With Pca, Clustering, And The Barzilai-Borwein Method, Shin Chiew Kai, Yeing Pan Wei, Seng Sim Hong, Hou Chin Jia, Jia Lee Yap

Malaysian Journal of Computing (MJoC)

Portfolio optimization aims to balance risk and return by identifying an effective mix of assets. In this study, we integrate principal component analysis (PCA) and hierarchical clustering for stock selection with the Barzilai–Borwein (BB) gradient method for portfolio optimization. Forty-eight U.S. stocks from the Kaggle fundamental stock dataset were initially collected, and 42 stocks were retained after preprocessing. Financial ratios from 2006 and adjusted closing prices from 2016–2017 were analysed, with one representative stock from each cluster selected using the Sharpe ratio. The BB method was then applied to determine optimal weights, ensuring full capital allocation without short selling. Among …

Influence Of Coriolis Force On Controlled Double-Diffusive Marangoni Convection In Nanofluid Layers, Izzati Khalidah Khalid, Ahmad Syukri Mohd Shukor, Mohd Rijal Ilias, Nurul Hafizah Zainal Abidin, Bekzodjon Fayziev

Malaysian Journal of Computing (MJoC)

Controlled double-diffusive Marangoni convection in a rotating nanofluid layer, heated from below, is studied. Various types of lower-upper boundary conditions, including free-free and rigid-free, are considered. The nanofluids model incorporates the mechanisms of Brownian motion and thermophoresis in nanofluids. The stability of the nanofluids model is analysed using a linear stability analysis based on the normal mode technique. The eigenvalue problem is numerically solved using the Galerkin technique and computational simulations are carried out using Maple software. The influences of several parameters are examined and presented graphically, including modified diffusivity ratio, nanoparticles concentration, solutal Rayleigh number and Soret effects. These …

Uncovering Ethical Values In Information Systems Development Methodologies, Zahidah Zulkifli, Noor Hayani Abd Rahim, Tahmid Alam, Fakhrul Hazman Yusoff, Mohammad Masudur Rahman

Malaysian Journal of Computing (MJoC)

Information system development involves a lot of tools, infrastructures, and humans. The many phases in system development need humans to interact and work with each other to obtain the goal: to complete information system development. These interactions of humans require the right ethics to ensure that the information system development can be successful. For example, ethical leadership is a vital component in determining the success of any project related to information system development in organizations. The aim of this study is to identify the ethical values which are important in information system development methodology phases. This systematic literature review (SLR) …

Textual Adversarial Example Generation Using Bigram Unigram-Semantic Preservation Optimization Algorithm, Noor Adam Noor Azmi, Haslizatul Fairuz Mohamed Hanum

Malaysian Journal of Computing (MJoC)

The vulnerability of Natural Language Processing (NLP) models to adversarial attacks remains a critical challenge in the field of cybersecurity and AI robustness. While deep learning models have achieved high performance in sentiment analysis, they are susceptible to subtle input perturbations that induce misclassification. This study presents the design and practical implementation of a web-based system (Proof of Concept) that automates the generation of textual adversarial examples using the Bigram Unigram-Semantic Preservation Optimization (BU-SPOF) algorithm. Rather than proposing a novel attack algorithm, our primary contribution is the architectural integration of a dual-source candidate generation strategy (WordNet and OpenHowNet) and a …

Lru Caching Policy Based On Naïve Bayes Ml Algorithm In Collaborative Peer-To-Peer Systems For Network Bandwidth Utilization, Waheed Yasin

Malaysian Journal of Computing (MJoC)

Web caching offers several advantages, such as increasing cache hit rates, lowering the workload on origin servers, and minimizing network traffic. Nevertheless, limited cache capacity poses a major challenge in web caching systems. Moreover, repeatedly fetching same media objects from origin servers leads to unnecessary bandwidth consumption. Furthermore, traditional caching policies, including Least Recently Used (LRU), are vulnerable to cache pollution. This study introduces a collaborative caching policy based on the Naïve Bayes (NB) Machine Learning (ML) algorithm. The proposed policy exploits structured peer-to-peer architectures, allowing cache contents to be shared among peers to improve the efficiency of LRU web …

An Ultrafine-Resolution Numerical Investigation Of The Influence Of Terrain On Tornado Behavior, Jiamin Dang, Jana Houser, Leigh Orf, Peng Yue, Guirong Yan

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study investigates the effects of idealized and realistic terrain on tornado characteristics and behavior. It uses a novel simulation approach, nesting a high-fidelity, ultrafine-resolution, tornado-scale, engineering large-eddy simulation (LES) within a Cloud Model 1 (CM1) simulation of a tornadic supercell. We analyze the effects of terrain on the tornado's central pressure, horizontal and vertical velocities, vortex shape, and path. Seven idealized terrain configurations are used including 1) a control run with flat ground, 2) and 3) an idealized hill with steep and gradual slopes having the height of 25.4 m, 4) and 5) an idealized escarpment with steep and …

Determinants Of Future Suas Adoption: An Empirical Analysis Of Organizational And Behavioral Factors Within The Commercial Aviation Maintenance Enterprise, Jordan Baus

Doctoral Dissertations and Master's Theses

The adoption of small Uncrewed Aircraft Systems (sUAS) represents a significant technological shift within the commercial aviation maintenance enterprise, offering the potential to improve inspection accuracy, enhance operational efficiency, and reduce maintenance-related risk. Despite these anticipated benefits, adoption intentions remain vague, influenced by a complex interplay of organizational structures, behavioral factors, and workforce perceptions. Limited empirical research has examined how these dynamics shape the willingness to adopt sUAS within highly regulated and institutionalized aviation maintenance environments. This study investigates the determinants of future sUAS adoption through an extension of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT …

Instrumentation And Control Of A Novel Device To Simulate A Hypersonic Environment, Andrew Marcello

Doctoral Dissertations and Master's Theses

The hypersonic flow regime poses several challenges regarding the design of hypersonic vehicles. Among them is the massive energy and economic expense associated with ground- testing evaluation of material responses within this extreme environment. In order to provide a low-cost, rapid option for preliminary material analysis within hypersonic applications, a novel device is under production to replicate this environment on the surface of these materials. This device has been designed to work in conjunction with Argonne National Laboratory (ANL) Advanced Photo Source (APS) synchrotron, to allow for in-situ characterization of ablation and oxidation on the sample surface.

To achieve this, …

Scenarioxp: A Complete Scenario-Based Testing Framework For The Exploration And Exploitation Of Autonomous Vehicle Validation Scenarios, Quentin Goss

Doctoral Dissertations and Master's Theses

Today is an age of exciting emerging technology where cutting-edge research in autonomous vehicles (AVs) reduces the active human participation in driving and extends awareness beyond human limitations of perception and reaction, improving driving safety and quality of the user experience as a result. The ever-increasing complexity of these autonomous systems poses many challenges towards the validation and verification (V\&V) of these complex systems under time and resource constraints, as the use of artificial intelligence and also the intricacy of the operating environment means that these systems are also black-box and non-deterministic. Scenario-based V\&V testing of such systems, which involves …

Insect Inspired Behavioral Strategies For Improving Multi-Agent System Resilience In The Presence Of Contagious Faults, James E. Hand

Doctoral Dissertations and Master's Theses

As Multi-Agent Systems (MASs) become increasingly involved in every aspect of everyday life the need to maintain reliability and resilience within these systems grows. However, in equal measure bad actors wishing to maliciously control or alter these systems are growing in both scale and capability. Thus, there is a present need for control schemes and agent behaviors that provide security against these threats while also avoiding large degradation in system performance as a tradeoff. Current research has covered a wide breadth of avenues and strategies that provide measurable resilience to faulted agents. However, these strategies often require group consensus, specialized …

Enhancing Undergraduate Learning In Physics: The Effects Of Ai-Assisted And Ai-Guided Instruction On Knowledge, Self-Efficacy, And Satisfaction, Stephen Woods

Doctoral Dissertations and Master's Theses

Generative artificial intelligence (AI) tools such as large language models are increasingly used for self-directed learning, yet there is limited experimental evidence on whether they improve learning outcomes and whether theory-informed guidance adds value beyond AI use alone. Prior literature suggests that effective learning depends not only on access to information, but also on how instruction supports attention, working memory, long-term memory, and cognitive load, while also fostering motivational processes such as self-efficacy. Individual differences such as Need for Cognition may also shape how learners engage with cognitively demanding instructional tools such as AI.

The present study examined how different …

Ellie - Exteroceptive Light Locomotion In Eukaryote-Fungi, Brandon Etwarroo

Doctoral Dissertations and Master's Theses

Over the past decade, fungal research and its technological applications have expanded across multiple disciplines, including the emerging field of biohybrid systems. This thesis develops and evaluates a wireless, untethered mobile robot controlled by the action potential-like activity generated by Pleurotus ostreatus sporocarps under red, green, and blue optical stimulation. Light is applied to the sporocarps, the resulting electrical responses are recorded, and these signals are transmitted wirelessly to actuate the mobile robot. Both the action potential-like activity patterns and the robot’s movement trajectories were analyzed. The results demonstrate that wireless robotic control mediated by fungal electrophysiology is feasible. Overall, …

Effect Of Nozzle Pressure Ratio On Thrust And Flow Behavior In A Supersonic De Laval Nozzle, Esha Jain

Doctoral Dissertations and Master's Theses

Supersonic nozzles operate across a range of flow regimes. While an ideally expanded condition yields optimal thrust, practical propulsion systems rarely operate at this design point due to variations in altitude and engine operating conditions. As a result, nozzles frequently operate in off-design conditions. In overexpanded regime, where the exit pressure is lower than the ambient pressure, shock-induced separation may occur within the divergent section of the nozzle, potentially degrading nozzle performance. Understanding the aerodynamic behavior of nozzles operating under off-design conditions is therefore important for improving propulsion system performance and stability. In particular, direct thrust measurements provide a key …

Intelligent Flight Control Systems Using Adaptive Deep Neural Networks And Concurrent Learning-Based Design Methods, Maddox C. Morrison

Doctoral Dissertations and Master's Theses

This thesis investigates deep neural network (DNN)-based adaptive control strategies for unmanned aerial vehicles (UAVs) operating under aerodynamic uncertainty and complex actuator dynamics.

The first contribution presents a control strategy employing a concurrent learning (CL)-based DNN training algorithm, which combines online adaptive DNN weight adaptation with offline batch-like training updates using a recorded data stack. The analysis focuses on the closed-loop performance improvements resulting from the use of optimum CL data-selection algorithms, which ensure that the recorded data stack maintains sufficient data diversity to provide a statistically meaningful representation of the operating conditions using a reduced data set. Specifically, this …

Study Of Output And Behavior Of Llms Using Confidence Framing In Prompt Engineering, Micah Parrilla

Doctoral Dissertations and Master's Theses

While prompt engineering is pivotal for shaping Large Language Model (LLM) outputs, the impact of confidence framing on behavioral calibration remains underexplored. This study investigates the ways in which psychological framing, utilizing techniques such as capability praise, role amplification, and doubt induction, affects linguistic tone, objective accuracy, and internal calibration. A 1,080-trial experimental matrix evaluated six diverse models across factual, logical, coding, and cyber security domains. Analysis using the Kruskal-Wallis H-test revealed highly significant behavioral shifts across all measured dimensions, providing conclusive evidence that the applied frames exert a substantial influence on model performance.

The findings identify a distinct cognitive …

Low-Complexity Structured Neural Networks And Their Usage In Image And Signal Processing, Adam Kuzmicki

Doctoral Dissertations and Master's Theses

Conventional neural networks face significant challenges due to high computational costs, large parameter counts, and reliance on backpropagation, which restricts their application in resource-constrained and real-time settings. To address these challenges, this thesis proposes three structured neural network (NN) architectures grounded in the theories of sparse and self-contained factorizations of transforms, with applications to image compression, reconstruction, classification, encryption, and also adaptive wideband multi-beam beamforming. The first neural network architecture, named DCTrix-Net, replaces conventional spatial con- volution with highly sparse factorization of the discrete Cosine transform (DCT) complemented by Toeplitz-structured weight initialization, achieving at least 97% FLOP reduction over CNNs, …

Additive Manufacturing Of Ti-Ni Based Ternary Shape Memory Alloys, Yitao Chen, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Metal additive manufacturing has become a powerful tool to develop customized metal alloys and to discover more advanced properties for novel extended applications. Ti-Ni based shape memory alloy is a group of intriguing smart functional materials, and adding a small amount of a third element can promote and induce more attractive functions. Due to the difficulty in traditional processing and the unique feature of material flexibility of in-situ alloying in additive manufacturing processes, not only Ti-Ni binary shape memory alloys but also Ti-Ni-X ternary shape memory alloys can be developed, manufactured, and investigated in-depth by additive manufacturing. This paper provides …