Public announcement of theses and dissertations
UMass Dartmouth Graduate Studies requires all thesis and dissertation defenses to be publicly announced to the community, via UMassD Announce, a minimum of two weeks prior to the defense date.
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Upcoming Defenses
Please scroll to the right to view all information related to defense submissions.
| Title | Date | Start Time | Location | Advisor(s) | Committee Members | Abstract | Contact | |||
| ELEC Doctor of Philosophy Dissertation Defense by Charles Montes - ECE | Friday, May 09, 2025 | 10am | Charlton College of Business (CCB), Room 115; Zoom Link: https://umassd.zoom.us/j/99223130208 Meeting ID: 992 2313 0208 Passcode: 768938 | Dr. Ruolin Zhou, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth | Dr. Lance Fiondella, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Alfa Heryudono, Associate Professor, Department of Mathematics, UMASS Dartmouth; Dr. Eugene Chabot, Engineer, Naval Undersea Warfare Center (NUWC) | Topic: Machine Learning Optimization for Dynamic Spectrum Awareness Abstract: This dissertation proposes a machine learning-based approach focused on improving dynamic spectrum awareness in wireless communications. The approach is comprised of four main components: network optimization with genetic algorithm convolutional neural networks (GACNN), which focuses on optimizing neural network architectures for specific tasks to reduce the complexity and cost of the network optimization process; unsupervised prototype learning, which uses hierarchical clustering and a prototype-based learning objective to estimate signal-to-noise ratio (SNR) regions and perform modulation classification to improve the classification accuracy and the identification of new signal classes; deep neural network explainable AI (DNN XAI), which increases the transparency and interpretability of machine learning models in deep neural networks to ensure compliance with spectrum regulatory standards; and lastly, incremental learning class representation drift, which evaluates the performance of incremental learning methods in baseband modulation classification to establish a continuous learning process that adapts to dynamic environments. By addressing gaps in current spectrum management techniques, these components can improve spectrum utilization, increase machine learning-based communication interpretability, and provide an informed model for future spectrum management strategies. NOTE: All ECE Graduate Students are ENCOURAGED to attend. All interested parties are invited to attend. Open to the public. *For further information, please contact Dr. Ruolin Zhou via email at ruolin.zhou@umassd.edu. | ruolin.zhou@umassd.edu | |||
| Doctoral Dissertation Defense by Eleanor DiNuzzo: The impacts of a non-native predator on a resident trophic cascade | Friday, May 09, 2025 | 10am | SENG 115 | Dr. Michael Sheriff and Dr. Sarah Donelan, Biology Department, UMass Dartmouth | Dr. Nancy O'Connor, Biology Department, UMass Dartmouth; Dr. Diego Bernal, Biology Department, UMass Dartmouth; Dr. David Kimbro, Marine and Environmental Sciences Department, Northeastern University | Predators are important drivers of community dynamics and composition, exerting a strong influence on species in lower trophic levels. Predators influence prey by either directly consuming them or scaring them (i.e., predation risk effects), both of which can scale up to have population-level consequences. Thus, examining predator-prey dynamics is a crucial piece to comprehend how communities function. As the introductions of non-native species are accelerating worldwide though, existing predator-prey dynamics are becoming increasingly difficult to predict and examine. Previous work shows that examining the impact of non-native species in the context of a multi-species food chain, such as trophic cascades, can improve our understanding of the impact non-natives have and that exploring the multiple different trophic links non-native species has is crucial to assess their impact communities instead of singular dyadic interactions. However, most studies do not account for the traits of non-native species, such as changing body size, that may change over time and result in dynamic, complex interactions between non-native and resident predators that have previously not been accounted for. Thus, for my dissertation, I investigated how a non-native predator at two different stages of ontogeny disrupts a resident trophic cascade via 1) nonconsumptive effects and 2) consumptive effects, and 3) if the non-consumptive effects differ between intraspecific and interspecific predator interactions using a well-known rocky intertidal system. This system consists of the predatory green crab, Carcinus maenas, its prey the dogwhelk snail, Nucella lapillus, the basal resource the blue mussel, Mytilus edulis, and the recently invaded predator the Asian shore crab, Hemigrapsus sanguineus. I ran a series of three laboratory mesocosm experiments and found that 1) Hemigrapsus had significant non-consumptive effects resulting in increased refuge use and reduced foraging and growth in Nucella, and that when both predators were together Nucella had weaker risk responses than expected regardless of Hemigrapsus body size. 2) Hemigrapsus had risk reducing emergent multiple predator effects on shared prey mortality, but those effects varied in some contexts depending on Hemigrapsus body size and the presence of alternate prey. 3) The type of refuge Nucella used differed between the intraspecific and interspecific predator interactions between Hemigrapsus and Carcinus, but not Nucella foraging or tissue growth. This work highlights the importance of accounting for multi-species interactions to provide a more comprehensive picture of non-native species impacts on resident species interactions and communities. | msheriff@umassd.edu | |||
| ELE Master of Science Thesis Defense by Clivens Joseph - ECE | Monday, May 12, 2025 | 10am | Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A / Zoom Link: https://umassd.zoom.us/j/94272084550 Meeting ID: 942 7208 4550 Passcode: 244930 | Dr. Ana Doblas, Assistant Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth | Dr. John R. Bucks, Chancellor Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Zheng Chen, Associate Professor, Mathematics Department, UMASS Dartmouth | Topic: Decoupling Refractive Index and Thickness in Biological and Non-Biological Samples using Digital Holographic Microscopy Abstract: Quantitative Phase Imaging (QPI) provides valuable insights into the morphological and chemical properties of biological systems. Among the different QPI methods, Digital Holographic Microscopy (DHM) is one of the most promising because of its high spatial resolution and sensitivity, allowing for the reconstruction of two-dimensional (2D) phase distributions in a single shot (i.e., a single recorded image is required). These 2D phase distributions encode critical information about a sample’s refractive index (RI) and thickness, which are vital parameters for studying cellular structures and dynamics. However, interpreting DHM phase measurements poses a significant challenge due to the intrinsic coupling between the sample’s refractive index (RI) and thickness (t). This coupling complicates the accurate retrieval of both parameters, limiting the potential of DHM in advancing biological research and enhancing the precision of cellular diagnostics. This Master’s Thesis is focused on the investigation of a mathematical framework designed to accurately estimate both the refractive index and thickness of a sample using 2D DHM phase data by leveraging the wavelength dependence of the sample’s refractive index using Cauchy’s equation. The proposed computational framework decouples the RI and thickness distributions from reconstructed DHM phase measurements by minimizing the error between the theoretical and measured phase data. The performance of the proposed method has been demonstrated using both simulated and experimental datasets. In addition, the performance of the proposed method has also been compared with the Spherical Phase-based Holistic INdex-thickness eXtraction (SPHINX) approach, which assumes that the sample is spherical and estimates its thickness from a fitting of the 2D sample’s morphology. The results show that the proposed approach achieves very low error, in some cases even with the presence of noise. Additionally, the CIPHER method outperforms the SPHINX approach because of lower error percentage. The main advantages of the proposed approach are: (1) it does not include any change of the experimental DHM system, (2) it requires fewer input images or data, reducing the acquisition time required for measurements, and (3) it eliminates the need for prior assumptions regarding the sample’s morphology or the surrounding medium, making it a versatile tool for a wide range of applications. We believe that this framework can be transformative in biomedical research, improving our understanding of biological systems. NOTE: All ECE Graduate Students are ENCOURAGED to attend. All interested parties are invited to attend. Open to the public. *For further information, please contact Dr. Ana Doblas email at adoblas@umassd.edu | adoblas@umassd.edu | |||
| Optimization of production scheduling using Linear Programming | Wednesday, May 14, 2025 | 10am | contact mrahman15@umassd.edu for the Zoom link | Effective production planning is critical in die-casting production to maximize the utilization of resources, minimize costs, and satisfy customer demand... | scunha@umassd.edu | |||||
| Are Metaphors Linked to How We Conceptualize Happiness? Evidence from English and Portuguese Speakers; Masters Thesis Defense by Jamie Phillips | Thursday, May 15, 2025 | 1pm | Library 314 | Mary Kayyal | Trina Kershaw; Heloisa Alves | Are Metaphors Linked to How We Conceptualize Happiness?: Evidence from English and Portuguese Speakers According to Conceptual Metaphor Theory, much of spoken language is figurative. Thus, by studying how a domain (e.g., emotion) is figuratively described, we can better understand how that domain is conceptualized. The current study examined the degree to which metaphors for happiness across languages reflect the assertions of Conceptual Metaphor Theory. Via an online survey, speakers of English (n=29) and Portuguese (n=14) rated each of 12 metaphors on valence, arousal, and the degree to which they relate to 11 different conceptual categories (e.g., Psychological Reaction, Life Event, etc.). All conceptual categories were selected at high rates, but the Portuguese-speaking group displayed more variability. No metaphor had a dominant category (i.e., rated significantly higher than others); this was true for both language groups. Within each language, metaphors varied on valence and arousal, indicating that different metaphors communicated different information about the structure of happiness. This means that, while metaphors communicate detailed information about emotional sensations, the way the metaphors describe variations in emotion sensation varies between languages. Multidimensional scaling analyses examined the relationships among the conceptual categories and, separately, metaphors, for each language group. For conceptual categories, both English- and Portuguese-speakers shared the first dimension, but differed on the second dimension. For metaphors, English- and Portuguese-speakers did not share either of the two dimensions. These findings suggest that the conceptualization of happiness is fluid, varying by the metaphor used to describe it and the language in which that metaphor exists. | jphillips@umassd.edu | |||
| MNE/ISE MS Project Presentation by Mr. Emmanuel Amaechi | Friday, May 16, 2025 | 10:00 a.m. | Zoom (contact scunha@umassd.edu for the link and passcode) | Dr. Wenzhen Huang, Professor, Department of Mechanical Engineering, UMD | Dr. Ana Doblas, Assistant Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Paul J. Gendron, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth | Comparative Analysis of Customers Segmentation in Marketing Campaign evaluates and compares various unsupervised clustering algorithms applied to customer segmentation in marketing campaigns. The objective is to... | whuang@umassd.edu | |||
| ELE Master of Science Thesis Defense by Christopher J. Brunette - ECE | Friday, May 16, 2025 | 11am | Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A / Zoom Link: https://umassd.zoom.us/j/89322289227 Meeting ID: 893 2228 9227 | Dr. Dayalan P. Kasilingam, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth | Dr. Ana Doblas, Assistant Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Paul J. Gendron, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth | Topic: Reduced Runtime Complexity for Circular/Hankel Hadamard Matrix Multiplication Applied to the Spectral Projection Model for Electromagnetic Scattering Abstract: Electromagnetic scattering for various geometrical constructs is often modeled with the aid of specialized electromagnetic simulation software. Currently, the Method of Moments (MoM) is one of the most used methods for analysis of scattering. However, this method has a more computationally efficient alternative known as the Spectral Projection Model (SPM). The SPM takes the kernel for the Electric Field Integral Equation (EFIE) and decomposes it into a projection of the spectral signature of a source point onto an observation point. This is possible using Graf's Addition Theorem (GAT) for the Bessel and Hankel functions. Showing that GAT can be represented as a Hadamard product in the Fourier domain requires the computation of the inverse of the Circular/Hankel Hadamard Product (CHHP) for elliptical cross sections. In MATLAB, an algorithmic approach is employed to compute the inverse of each submatrix and construct the inverse based on these submatrices. This approach yields an inversion time complexity of O(N²·⁷⁵) as an alternative to the O(N³) time complexity of a standard matrix inversion. Note: All ECE Graduate Students are ENCOURAGED to attend. All interested parties are invited to attend. Open to the public. *For further information, please contact Dr. Dayalan Kasilingam email at dkasilingam@umassd.edu | dkasilingam@umassd.edu | |||
| Application of Lean Thinking Principles to Improve Efficiency and Reduce Waste in a Quality Control Lab | Monday, May 19, 2025 | 10:30am | contact scunha@umassd.edu for link | Quality Control (QC) laboratories play a vital role in ensuring high manufacturing standards... | scunha@umassd.edu | |||||
| MNE/ISE MS Project Presentation by Mr. Amey Sawargaonkar | Tuesday, May 20, 2025 | 2pm | Zoom (contact scunha@umassd.edu for the link and passcode) | Dr. Md Habibor Rahman, Assistant Professor, Mechanical Engineering, UMass Dartmouth | Dr. Satyanarayana Parayitam, Professor, Management and Marketing, UMass Dartmouth -and- Dr. Wenzhen Huang, Professor, Mechanical Engineering, UMass Dartmouth | TOPIC: An Integrated Approach to Accelerated and Cost-Effective HEV Manufacturing: Leveraging Systems Engineering, Logistics Optimization, and Engineering Design ABSTRACT: In response to the global demand for sustainable mobility solutions, Hybrid Electric Vehicles (HEVs) represent a critical transition point in the automotive industry. This project presents a formal, multidisciplinary investigation into HEVs and proposes a cost-effective and accelerated approach to the development and deployment of HEVs, combining engineering design, economic analysis, systems engineering, supply chain management, logistics modeling and data visualization to propose innovative, data-driven strategies for scalable vehicle production... | mrahman15@umassd.edu | |||
| DFO MS Thesis Defense "Impacts to stock abundance indices due to offshore wind development-driven changes to fishery-independent survey effort" presented by Angelia Miller on May 20th | Tuesday, May 20, 2025 | 1:30pm | SMAST East 101-103 | Dr. Gavin Fay (University of Massachusetts Dartmouth) | Dr. Steven X. Cadrin (University of Massachusetts Dartmouth), and Dr. Catherine Foley (NOAA NEFSC) | Offshore wind energy development is occurring throughout the Northeast Large Marine Ecosystem and will interact with many marine use sectors, including fisheries. Wind areas overlap spatially with the footprint of the National Marine Fisheries Service (NMFS) Northeast Fisheries Science Center (NEFSC) multispecies bottom trawl survey, which has been conducted since the 1960s, and whose data are relied upon for the assessment and management of many fisheries stocks in the Northeast U.S. This fishery-independent survey is confronted by potential preclusion of trawl sampling efforts due to the spatial conflict arising from offshore wind energy development. My thesis aims to quantify the impacts of preclusion to monitoring and operations and understand changes to species distributions and abundances within wind areas, which could jointly affect downstream data products, such as stock abundance indices, and fisheries management advice. The first phase of my study serves as a proxy for expected losses for comparison to my species distribution modeling and suggests that, when accounting for reduced trawl samples, annual estimates of relative abundance are lower than those calculated when including all samples. Additionally, when compared to a random, null model of effort reduction, preclusion of wind areas resulted in lower abundance estimates. Applying summer flounder (Paralichthys dentatus) and Atlantic mackerel (Scomber scombrus) as two case study species, I fit a spatiotemporal generalized linear mixed effects model (GLMM), generate simulated survey data, and calculate indices of abundance and population trends to compare survey outcomes with and without trawl samples inside proposed wind development areas in the second phase of my study. I employed the species distribution operating model to examine changes in fish density under assumed changes in species productivity, and to survey catch rates, as a function of offshore wind development. I found that the loss of samples inside wind areas has a substantial impact on estimates of abundance indices and population trends. This study contributes directly to implementation of the Federal Survey Mitigation Strategy for the Northeast U.S. Region (Action 3.2.2) as a part of the Survey Simulation Evaluation and Experimentation Project, which aims to assess potential impacts to the bottom trawl survey operations and data products and identify mitigation strategies to maintain data integrity. Furthermore, this study contributes to the current knowledge surrounding the impacts that offshore wind energy development can have on fishery-independent surveys, which globally is scarce. | c.rumbut@umassd.edu | |||
| Drug-Elusive Thermoresponsive Hydrogel Wound Dressing | Monday, May 19, 2025 | 10am | TEX 219 | Profs. Qinguo Fan and Tracie Ferreira | Drs. Christopher Brigham and Laura Hanzly | Two important aspects of wound healing are maintaining a clean, moist wound environment, and preventing infection. An effective wound dressing protects the wound from external debris, helps maintain a healthy wound environment, and does not damage the tissue. Hydrogels are a commonly used wound dressing material due to their nonadherent nature, biocompatibility, swellability, similarity in mechanical strength to skin, and tunability of properties. These properties can be affected by phase changes, or conformation of the polymer components of the hydrogel in response to stimuli such as pH or temperature. Additionally, antibacterial agents can be incorporated into the hydrogel to prevent or treat bacterial infection. We developed a thermoresponsive PNIPAM and chitosan bicomponent hydrogel that is able to undergo phase transition when the skin temperature changes between the normal skin and injured skin, as well as display drug elution at those temperatures. We also tested the hydrogel’s biodegradability, swelling ratio, and mechanical strength. This hydrogel has the capability of being used as a thermoresponsive antibacterial wound dressing material. | qfan@umassd.edu | |||
| "Targeting Copper-Mediated Aβ Neurotoxicity, Tau Phosphorylation and Oxidative Stress in Alzheimer’s Disease Using Cranberry-Derived Polyphenols" by Sarah Auguste McCaulley | Wednesday, May 21, 2025 | 1:00pm | Join Zoom Meeting: https://umassd.zoom.us/j/96549246129?pwd=Zp8S78A354o695z9agxvS0febTLr9E.1; Meeting ID: 965 4924 6129; Passcode: 082135 | Dr. Maolin Guo, Chemistry & Biochemistry Department | Dr. Catherine Neto, Chemistry& Biochemistry Department; Dr. Shuowei Cai, Chemistry & Biochemistry Department; Dr. Isabelle Phillip, Siemens Healthineers | Copper has been linked to the pathogenesis of Alzheimer’s Disease (AD) as it binds to amyloid beta (Aβ) and tau, impacting their aggregation and generating reactive oxygen species (ROS). Metal chelation therapy has emerged as a potential treatment strategy for amyloid diseases like AD. Flavonoids including polyphenols in cranberries chelate metals and have shown neuroprotective effects in AD, however, their mechanisms of action remain poorly understood. This study will investigate the effects of cranberry extracts, subfractions and polyphenols—including quercetin and its metabolites isorhamnetin and tamarixetin—on copper-mediated Aβ/tau-induced oxidative stress, Aβ neurotoxicity, and tau phosphorylation with the following specific aims: 1) Assess cranberry's ability to attenuate copper mediated Aβ/tau induced ROS; 2) Investigate the impact of cranberries/copper on the formation of α sheet structure in Aβ/tau; 3) Evaluate the impact of cranberries/copper on the formation of Aβ oligomers; 4) Evaluate the impact of cranberries on copper induced tau phosphorylation. Cranberry’s impact on SH-SY5Y neuroblastoma cell viability will be assessed using an MTT assay prior to evaluating its ability to reduce copper mediated Aβ and tau induced ROS by confocal microscopy. The effects on α sheet structure in Aβ and tau will be examined via CD and FTIR spectroscopy. Aβ oligomers will be analyzed by developing a Homebrew Custom Simoa assay with an α sheet peptide or a monoclonal antibody and by developing a confocal microscopy method using a fluorescent α-sheet peptide. Cranberry’s effects on copper-induced tau phosphorylation will be evaluated using commercially available Simoa® and Atellica® IM immunoassays. These studies will contribute to a better understanding of the mechanisms of action of copper's role in AD and cranberry polyphenols’ neuroprotective effects, providing valuable insight for the development of therapeutics targeting metal-chelation oxidative stress, Aβ neurotoxicity, and tau phosphorylation in AD. | rwhite@umassd.edu | |||
| CPE Master of Science Thesis Defense by Brendan C Thibault - ECE | Friday, May 23, 2025 | 1pm | Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A / Zoom Link: https://umassd.zoom.us/j/91704072785 Meeting ID: 917 0407 2785 Passcode: 603590 | Dr. Lance Fiondella, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth | Dr. Hong Liu, Commonwealth Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Ruolin Zhou, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Gokhan Kul, Assistant Professor, Department of Computer & Information Science, UMASS Dartmouth | Topic: Enhancing Static Code Analysis in Reverse Engineering Using Retrieval-Augmented Generation and Large Language Models Abstract: This thesis explores the application of Large Language Models, (LLMs), in a reverse engineering context to perform accurate static analysis of disassembled and decompiled code. A novel approach was taken using Retrieval-Augmented Generation (RAG) to enhance the model’s output with relevant contextual metadata, improving the accuracy and relevance of the generated documentation. This methodology was implemented within an Artificial Intelligence, (AI), enabled reverse engineering platform that enables users to perform static analysis and includes features such as a linear disassembly view, graph-based navigation, and AI-driven code summaries, among others. Several leading AI models are integrated into the tool, providing users with a flexible range of analysis options. The results show that a RAG-based approach outperforms traditional methods of AI-assisted reverse engineering. This research demonstrates significant performance and accuracy improvements using an AI-enabled framework, and highlights the potential of integrating LLMs into reverse engineering workflows. NOTE: All ECE Graduate Students are ENCOURAGED to attend. All interested parties are invited to attend. Open to the public. *For further information, please contact Dr. Lance Fiondella email at lfiondella@umassd.edu | lfiondella@umassd.edu | |||
| ELE Master of Science Thesis Defense by Garret Magalhaes - ECE | Friday, May 23, 2025 | 10am | Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A / Zoom Link: https://umassd.zoom.us/j/96767453993 Meeting ID: 967 6745 3993 Passcode: 668490 | Dr. Ruolin Zhou, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth | Dr. Dayalan P. Kasilingam, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. William P. Craig, Technical Project Mgr., Undersea Warfare Electromagnetic Systems Dept., Naval Undersea Warfare Center (NUWC) | Topic: FPGA-Accelerated RF Environment Emulation: Design, Implementation, and Performance Evaluation Abstract: With the rise of wireless communication systems comes the demand for testing Radio Frequency (RF) systems in real environments. This research applies Field-Programmable Gate Array (FPGA) technology to create a high-fidelity, reconfigurable RF environment framework for efficient and accurate wireless system testing. The comprehensive testbed features multiple modulation schemes including Amplitude Modulation (AM), Frequency Modulation (FM), Binary Phase-Shift Keying (BPSK) for Global Positioning Systems (GPS) spoofing, Orthogonal Frequency-Division Multiplexing with Quadrature Phase-Shift Keying (OFDM-QPSK), and Automatic Dependent Surveillance-Broadcast (ADS-B) transmission. FPGAs offer ad-vantages over Central Processing Unit (CPU) and Graphics Processing Unit (GPU) approaches due to deterministic timing, customizable hardware parallelism, and direct digital signal processing without operating system overhead. The implementation used MATLAB for signal generation, processing algorithm design, and system validation. For each modulation scheme (except ADS-B), dedicated transmitter and receiver configurations were developed on the USRP X300 platform. Performance evaluation through real-time analysis of time and frequency domain plots confirmed that signal processing and transmission occurred with expected characteristics and timing precision. Results demonstrate FPGA acceleration’s effectiveness in handling computational demands of real-time RF environment emulation while maintaining signal fidelity. This work contributes to transferring theoretical RF system design to practical implementation by providing a framework for creating and testing wireless communication systems in realistic scenarios. Note: All ECE Graduate Students are ENCOURAGED to attend. All interested parties are invited to attend. Open to the public. *For further information, please contact Dr. Ruolin Zhou email at rzhou1@umassd.edu | rzhou1@umassd.edu | |||
| Emotional Storytelling as a Window to Context-Incongruent Anger and Externalizing Behaviors; Master’s Thesis Defense by Emily Jeanne King | Wednesday, May 21, 2025 | 2pm | Library 314 and via zoom at https://umassd.zoom.us/j/92345608298?pwd=74JTjGWu3TtVJdTLJ6GdsnC0HKK0pc.1 | Robin Arkerson | Judith Sims-Knight; Mary Kayyal | This study addressed emotional factors that are relevant for children’s social and emotional well-being. For those that may have deficits or biases in identifying and reacting to the emotions of others, especially when it results in an unexpected emotion expression for a given context, maladaptive interpersonal skills may emerge that can impact emotional competence. The present study investigated the relationship between emotion processing, context-incongruent (CI) anger, and externalizing behavior in four-and-five-year-old preschoolers (n = 74). Measures included parent report and behavioral measures of CI anger, behavioral measures of context-congruent (CC) anger, anger perception bias, anger narrative bias, and parent and teacher report of externalizing behaviors. The findings of the study replicated associations between CI anger and externalizing behavior, as well as provided novel findings supporting a specific anger bias affecting storytelling narratives called anger narrative bias. Children with greater parent-reported CI anger had greater parent-reported externalizing behavior. Greater levels of CI anger during a positive game tended to relate to higher anger narrative during non-anger pictures in the storybook, but did not relate to congruent anger narrative during anger pictures in the storybook. Anger narrative bias also predicted externalizing behavior for children with high CI anger, but unexpectedly this association trended in a negative direction. These findings suggest that anger narrative bias should be researched further to help find interventions to mitigate the negative social consequences biased emotion processing has on children, as well as providing aspects of emotion processing in everyday life that may be relevant for CI anger. | rlocke@umassd.edu | |||
| CPE Master of Science Thesis Defense and ELEC Research Component of PhD Qualifier Exam by Eric N. Savage - ECE | Friday, May 23, 2025 | 8am | Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A / Zoom Link: https://umassd.zoom.us/j/95401845978 Meeting ID: 954 0184 5978 Passcode: 576893 | Dr. Ruolin Zhou, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth | Dr. Hong Liu, Commonwealth Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Lance Fiondella, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth | Topic: Profiling Attacker Behavior in Honeypot Deception: A Comparative Analysis of Varying Cyber Deception Levels Abstract: As cyber threats continue to rise and grow more sophisticated, organizations must find new ways to understand and counteract attacker behavior. This thesis compares attacker actions across three setups—a machine with no deception, a low-interaction honeypot, and a high-interaction honeypot—by recording activity over several weeks and building per-IP attacker profiles. We identify clear differences in behavior across these environments and, based on our observations, propose new honeypot design strategies that enhance intelligence gathering and illuminate attacker motives. Finally, we explore how integrating these deception tools into Zero Trust networks can help organizations remain resilient against future attacks. NOTE: All ECE Graduate Students are ENCOURAGED to attend. All interested parties are invited to attend. Open to the public. *For further information, please contact Dr. Ruolin Zhou email at rzhou1@umassd.edu | rzhou1@umassd.edu | |||
| BMEBT MS Thesis Defense by Andrew Medeiros | Wednesday, May 28, 2025 | 10am | TEX 219 | Lamya Karim | Tracie Ferreira, Laura Hanzly | Type 2 diabetes mellitus (T2DM) is associated with elevated fracture risk despite normal bone mineral density (BMD), suggesting deficits in bone quality. Advanced glycation end-products (AGEs), formed under chronic hyperglycemia, alter collagen cross-linking and osteocyte signaling, impairing bone remodeling. Irisin, a myokine secreted after exercise, may counteract these effects by improving glucose metabolism and promoting osteoblast activity, but its role in osteocyte function remains unknown. This study investigates how hyperglycemia and AGEs influence osteocyte behavior and tests irisin’s potential to mitigate these effects. Using the mature osteocyte cell line Ocy454, we assess both cell viability under no-sugar, high-sugar, and irisin-treated high-sugar conditions, and gene/protein expression of key bone remodeling markers (RANKL, OPG, SOST, TNF-α, IL-6, and RAGE). We hypothesize that high glucose will reduce osteocyte viability and upregulate pro-resorptive signals, while irisin will restore viability and promote pro-formative pathways. By linking AGE-driven osteocyte dysfunction to irisin’s therapeutic potential, this work may inform novel strategies to improve bone quality in T2DM, addressing a critical gap in diabetic bone pathology. | lkarim@umassd.edu | |||
| DFO PhD Dissertation Defense presented by Nicholas M. Calabrese on May 28th | Wednesday, May 28, 2025 | 1pm | SMAST East 101-103 and zoom https://umassd.zoom.us/j/92695694559 | Dr. Kevin Stokesbury | Steven X. Cadrin (UMass Dartmouth), Pingguo He (UMass Dartmouth), Michael J.W. Stokesbury (Acadia University), and Anna Mercer (NOAA Federal) | The School for Marine Science and Technology (SMAST) video trawl survey employs cameras mounted in the open codend of a trawl to identify and numerate groundfish. This minimally invasive survey technology has been used for semi-annual surveys of Atlantic Cod (Gadus morhua) in the Western Gulf of Maine since 2020. Accurate estimates of absolute abundance from the video trawl survey required estimates of catchability, efficiency, and fish length. This project aimed to address these requirements through three experiments and evaluate sampling methodology in a fourth experiment. First, a passive integrated transponder (PIT) tag detection system was developed, tested, and installed in the codend of the net. The custom-designed PIT tag detection system achieved an efficiency of 79%, with detection rates influenced by tag orientation and group size. Then, a mark-recapture experiment to estimate the efficiency and catchability of Atlantic cod was conducted using this system. A Petersen mark-recapture model, based on 1,094 tagged fish and six recaptures, accounting for both discard mortality and reader efficiency, yielded a doorspread efficiency of 12% and a catchability coefficient of 0.0024 per hour of towing. Next, the accuracy of length measurements derived from an off-the-shelf stereoscopic camera mounted within the trawl was assessed. This camera produced inaccurate length measurements, however, these findings helped inform the design of a custom imaging system. Finally, optical data from the survey were used to evaluate the effects of sampling design, tow duration, and sampling intensity on the variance of population estimates through a novel analytical approach. Stratified random sampling produced more precise biomass estimates than simple random sampling. In addition, CPUE mean, and variance increased with shorter tow durations. A 30-minute tow duration minimized within-tow variability and yielded the most precise abundance estimates, although this analysis lacked factors such as fish size and logistical constraints. Collectively, this research advances fisheries-independent survey methodology by addressing key limitations of new approaches. | c.rumbut@umassd.edu | |||
| The Triad Bonding in the NICU Model from the NICU Nurse's Perspective | Thursday, May 29, 2025 | 1pm | Library 314/ZOOM | June Andrews Horowitz, PhD, RN, PMHCNS-BC, FAAN | Jennifer Mammen, PhD, RN & Dorothy Vitner, PhD, RN, FAAN | Abstract Background: When an infant is admitted into the neonatal intensive care unit (NICU) a physical barrier to maternal-infant bonding is created (Hill & Flanagan, 20202). The repercussions of this event lead to negative developmental outcomes for infants (Hill & Flanagan, 20202). Currently, there is a limited understanding of the phenomenon of nurse-infant bonding in the NICU. Purpose: The purpose of this study was to understand the bonding relationship between nurses and the infants they care for in the NICU setting, as well as how the NICU nurses might facilitate bonding to family members within a family-centered care model. The outcomes of nurse-infant bonding for the nurse, infant, and family were explored. Method: The study used an interpretive descriptive qualitative approach by collecting personal descriptions via individual interviews. Repeated reflexive thematic analysis was completed as outlined by Braun and Clarke (2022) to inform the creation of a conceptual model. Results: The themes informed the creation of the Triad Bonding in the NICU model. The emotional impact “love” has on forming a bond between the NICU nurses, infants, and parents was described with identification of facilitating characteristics. Barriers to bonding among the triad were described. Potential outcomes of the bond were expressed by participants as rewarding or challenging. Within the triad relationship, nurses had the opportunity to enhance the connection between parents and infants by acting as a “bridge” between the two. Conclusion: This study described the unique emotional process NICU nurses experience when bonding with infants and parents. The knowledge of these bonds aims to close the gap within the literature regarding the phenomenon of triad bonding in the NICU. Comprehension of the facilitating interventions and barriers will allow nurses to connect better with infants and parents. Educating nurses about the model may help to alleviate emotional distress of families and improve understanding of the unique experience in the NICU. | dhoffman@umassd.edu | |||
| EAS Doctoral Proposal Defense by Guancheng Zhou | Friday, May 30, 2025 | 10am | Zoom | Dr. Donghui Yan, Department of Mathematics | Dr. Haiping Xu, Department of Computer& Information Science Dr. Hongkang Xu, Department of Accounting & Finance Dr. Long Jiao, Department of Computer & Information Science | A number of machine learning algorithms have delivered superior empirical performance. However, the understanding of their mechanisms has been hampered by the black-box nature of the algorithms. In this proposal, we approach the problem from two different lens. One is visualization, with a data-driven geometry following kernel—the rpf-kernel, which can extract complex and highly nonlinear patterns beyond the usual principal component analysis. The other is the diagnosis perspective. Specifically, we perform a diagnostic analysis to data points under a given algorithm and hope to use this as a proxy to understand the algorithm. Random Forests classification is used as an example algorithm for our study. We borrow two metrics, leverage and influence, from statistics regression to measure the importance of data points, while extending their definition to a small neighborhood of data points. Also studied is a related issue fairness—whether the algorithm delivers a response that is fair in terms of some given metric, for example the gender of the associated subjects. K-means clustering is studied, and a computational efficient post-algorithm adjustment method is proposed. Experiments show that the proposed method is effective in improving the fairness while maintaining the clustering performance. | dyan@umassd.edu |