Treasures @ UT Dallas

Welcome to Treasures @ UT Dallas Institutional Repository, established in 2010. Treasures is a resource for our community to showcase, organize, share, and preserve research and scholarship in an Open Access repository.


Recent Submissions

Non-resilience of Resilient Distributed Consensus in Multi-agent Systems
(August 2023) Khalyavin, Leon Sergey 2001-; Abbas, Waseem; Yurkovich, Stephen; Ruths, Justin
This thesis explores the resilient distributed consensus in networks that lack the necessary structural robustness to achieve consensus in the presence of malicious agents. While exist- ing solutions provide robustness conditions for consensus among normal agents, they fail to evaluate network performance comprehensively when the graph’s robustness is insufficient. To address this limitation, we introduce the concept of non-convergent nodes, representing agents unable to attain consensus with any arbitrary agent due to malicious agents in the network. This notion allows us to classify graphs based on their robustness levels and assess partial performance. This study initially establishes the (r, s)-robustness of commonly en- countered graphs, such as complete, complete bipartite, 1-D distance, and circulant graphs. Our approach facilitates easier identification of robustness and enables us to gain insights into the behavior of non-convergent nodes. By understanding the dynamics of these non- convergent nodes, we can establish more relaxed conditions for converging subgraphs, which are the subgraphs that are guaranteed to converge. This knowledge enhances our under- standing of resilient algorithms and their behavior in practical scenarios. Furthermore, we present graphs with given robustness levels, including (F + 1, 1), (F, F ), and (F + 1, F ) ro- bustness, and determine the maximal number of non-convergent nodes associated with each graph. This quantification of non-resilience sheds light on the impact of graph robustness on the network’s ability to achieve consensus. Surprisingly, we find that graphs with the same structural robustness may exhibit varying degrees of non-resilience, leading to different network performance outcomes. Through numerical evaluations, we demonstrate that our approach provides a comprehensive resilience perspective beyond the conventional binary view of success or failure in the face of malicious agents. By quantifying network perfor- mance under sub-optimal robustness conditions and identifying converging subgraphs, our study opens up new possibilities for designing more resilient consensus algorithms.
Multilingual Extractive Question Answering With Conflibert for Political and Social Science Studies
(August 2023) Whitehead, Parker Madden 2001-; Khan, Latifur; Gogate, Vibhav; Mazidi, Karen
Political conflict and violence have emerged as prominent concerns for political scientists in both academia and policy circles. The overwhelming influx of complex and dense news makes it increasingly challenging to effectively monitor and analyze political events. To address this challenge and contribute to the advancement of conflict research, we propose the introduction of ConfliBERT English and ConfliBERT Spanish. These two domain-specific pre-trained language models are specifically designed for the analysis of political conflict and violence, and have undergone fine-tuning to excel in extractive question answering tasks, which are not susceptible to hallucination. The pre-training of our ConfliBERT models utilized our comprehensive conflict-specific corpus from diverse sources. In order to evaluate the performance of ConfliBERT for extractive question-answering, We performed fine-tuning on SQuAD v1.1 and NewsQA, two large question-answering datasets. Additionally, we created ConfliQA English and Spanish, two crowd-sourced evaluation datasets for conflict- domain extractive QA. Through extensive experimentation and evaluation on all versions of ConfliBERT English and Spanish, we proved that ConfliBERT English outperforms in analyzing political texts compared to BERT English baseline models, and provided detailed insight into further developing ConfliBERT for low-resource languages.
Automated extraction of data constraints from software documentation
(August 2023) Zhou, Ying 1998-; Marcus, Andrian; Wei, Shiyi; Chung, Lawrence
Data constraints encompass crucial business rules that specify the values allowed or required for the data utilized within a software system. These constraints are typically described in textual software artifacts (e.g., requirements and design documents, or user manuals). Previous research on data constraints in software focused on studying their implementation in the code for identifying inconsistencies or to support their traceability. This thesis contribute to the existing knowledge by studying 548 data constraints described in the documentation of nine systems. We identified and documented 15 linguistic discourse patterns employed by stakeholders to describe data constraints in natural language. In a comprehensive extensive study, we explore the use of the discourse patterns we discovered, along with linguistic elements, the operands of the data constraints and their types, as features for automatically classifying sentence fragments as data constraint descriptions. The best combination of features and learner achieves 70.87% precision and 59.73% recall (64.76% F1). The discoveries made in this thesis represent a significant advancement in the automated identification and extraction of data constraints from natural language text, which in turn is essential for enabling the automation of traceability to code and facilitating test generation associated with these constraints.
Study of Wall Turbulence Response to Large-scale Homogeneous and Heterogeneous Surfaces
(August 2023) Zheng, Yiran; Anderson, William; Ferruzzi, Jacopo; Iungo, Giacomo Valerio; Jin, Yaqing; Hassanipour, Fatemeh
Fully-rough wall-sheared turbulence consists of an inner and outer layer, each with its own distinct characteristics. The inner layer is composed of sinuous structures sustained by an autonomous cycle, while the outer layer boasts inclined parcels of relative momentum deficit and excess. The stair-case pattern of successive uniform momentum zones (UMZs) necessitates the existence of an interfacial shear layer of abrupt velocity change on the wall- normal direction. This phenomenon has been established in prior research and highlights the importance of understanding the structure and behavior of fully-rough wall-sheared turbulence. A conditional sampling procedure has been leveraged in the LES statistics of fully rough channel flow to generalize the positions of UMZs, which prevail where sublayer interactions create large-scale and arbitrary momentum excesses or deficits. By observing the distribution of the interfacial shear layer during different conditions when fast or slow parcels of fluid pass the sampling location, gained are the insight into the flow structures and their interactions within the roughness sublayer. These observations are consistent with previous studies and provide a new perspective on the structure of fully-rough wall-sheared turbulence. The relationship between wall roughness obliquity and the flow regime of the fully-rough wall-sheared turbulence has been investigated through parametric assessments. This research estimates between the flow pattern of the internal boundary layer (IBL) when there is large- scale orthogonal roughness heterogeneity, and the secondary flow of the second kind, i.e., the counter-rotating secondary cells, under the circumstance of the heterogeneity parallel to the streamwise direction. Of particular interest is the transition at the obliquity angle, 22π/56, where a critical obliquity is observed and the sheltering area abruptly changes. These findings provide valuable insights into the behavior of fully-rough wall-sheared turbulence and can be used to improve future turbulence models. Additional research has found that the radial spacing between roughness elements in fully- rough wall-sheared turbulence is a crucial factor in determining the critical obliquity of the wall roughness heterogeneity. By adjusting the radial spacing between adjacent roughness blocks in a row, it is possible to shift the critical obliquity in a predictable way. This theory was discovered by studying turbulent channel flow cases of rows of roughness blocks with different oblique angles and radial spacing. The predictable influence of radial spacing on critical obliquity further highlights the interplay between successive element sheltering, the flow patterns of IBL, and secondary cells, which are all key factors that determine the structure and behavior of turbulence in fully-rough wall-sheared flows, and further to contribute to refining turbulence models and improving the understanding of fully-rough wall-sheared turbulence.
Hemodynamic Response Variability and its Relationship to the BOLD signal in Younger and Older Adults
(August 2023) Taylor, Mackenzie Breann 1996-; Rypma, Bart; Rennaker, Robert; Spence, Jeffrey S.; Seaman, Kendra; Krawczyk, Daniel
Studies have shown age-related differences in blood-oxygen-level-dependent signal (BOLD) variability, specifically amplitude variability. However, results have been mixed. Little remains known about the sources contributing to this variability. Identifying these sources would have implications for underlying mechanisms contributing to BOLD measurement. Changes in BOLD yield a characteristic hemodynamic response function (HRF) that reflects a combination of blood flow and oxygenation changes that follow neural activity. In healthy aging, multiple components of the HRF (e.g., time-to-peak, rise slope, peak amplitude, full-width half-maximum, peak-to- trough, time-to-trough, fall slope, and trough amplitude) are susceptible to the mediating effects of age-related cerebrovascular alterations and underlying processes. Additionally, several studies have demonstrated that neuro-vascular coupling (NVC) differences in older adults are mirrored in HRF differences. To further explore these phenomena, the current study utilized the publicly available Cambridge Center for Aging and Neuroscience (CamCAN) dataset to estimate HRF variability in a visual-auditory task in 80 younger (18-30 years old; 44 Female/36 Male) and 212 older adults (54-74 years old; 100 Female/112 Male). The proposed study was carried out according to three aims: (1) examine intra-individual HRF variability in younger and older adults, (2) examine inter-individual HRF variability in younger and older adults, and (3) determine the relationship between HRF variability and cognitive performance in younger and older adults. Linear mixed models were used to assess individual and age-related differences in HRF features. I hypothesized that individuals, regardless of age, would have increased HRF variability in higher frequency task conditions compared to lower frequency conditions. For age- related differences, I hypothesized that older adults would have increased HRF feature variability, and that their HRF variability would be inversely related to canonical-derived BOLD voxel extent. Finally, I hypothesized that there would be an interaction between HRF variability, age, and cognitive performance such that low-performing older adults would have increased HRF variability compared to high-performing older and younger adults. For group differences in HRF feature variability, I found that increased/decreased HRF feature variability was associated with increasing auditory frequencies depending on the region examined. For group differences in mean HRF features, I found that increased mean HRF features were associated with increasing auditory frequencies, with the exception of fall slope which exhibited an inverse relationship. Older adults had increased HRF feature variability and mean HRF features, primarily in the precentral and temporal ROIs, compared to younger adults. Older adults’ increased voxel extent was associated with decreased variance of their rise slopes, full-width half-maxima, peak-to- troughs, and time-to-troughs. Finally, younger adults exhibited a significant relationship between their reaction times and mean HRF features in the highest frequency condition while the older adults did not. My results showed that HRF feature variability exhibits region- and task- dependent differences that need to be accounted for when performing age-group comparisons, the latter-half of the HRF evolution and underlying mechanisms are potential sources of additional variability in older adults, and the difference between HRF features in the precentral cortex and other sensory cortices may serve a mediatory role between age and processing speed ability. This study assessed features of BOLD HRF shape as a proxy of NVC to identify potential sources of altered age-related variability and their relationships to behavior.