Digital Commons Network^™

Mobilizing Feminist Politics In Yugoslavia: Sanja Iveković And Vlasta Delimar’S Performance Art., Candyce Sturgeon

Electronic Theses and Dissertations

This thesis examines the radical performance works of Yugoslavian artists Sanja Iveković and Vlasta Delimar. Three performances by each artist are analyzed and juxtaposed with one another. These performances include Triangle, 1979, He is Looking at Me all the Time, 1979, and Nessie, 1981 performed by Sanja Iveković along with This was Me in 1980 when Comrade Tito Died, 1980, Visual Orgasm, 1981, and Tied to a Tree, 1985 performed by Vlasta Delimar. Throughout the paper I argue that these performances by Iveković and Delimar, along with their differing stances on feminism, create a multifaceted …

Imperial Nostalgia: The War For The Kievan Rus Legacy., Jacob Wolfe

Electronic Theses and Dissertations

This thesis explores the deep-seated historical, cultural, and religious narratives fueling the modern conflict between Russia and Ukraine. Central to this dispute is the legacy of the Kievan Rus, a medieval East Slavic state. The research examines historical claims over the Kievan Rus legacy, Russia's perception as the heir to the Eastern Orthodox Church, and the impact of the Soviet Union's dissolution. It also delves into the Varangian Guard's role in establishing Kievan Rus-Byzantine relations, the mistrust instilled by the Crusades, and the shared linguistic and cultural influences between Russia and Ukraine. Additionally, the thesis analyzes the Normanist Controversy, Russian …

Bayesian Approaches In Multi-State Markov Models And High Dimensional Time-To-Event Data., Yuchen Han

Electronic Theses and Dissertations

This dissertation consists of two projects. The first one involves nonparametric methods on Continuous Time Markov Chains (CTMCs). The second one is centered around Bayesian shrinkage models for detecting prognostic and predictive biomarkers in high-dimensional clinical data. Both these projects build on methods from across the frequentist and Bayesian paradigm to offer novel solutions. In the first project, we aim to model the nonlinear effects of continuous variables within multistate framework in a non-parametrically by appealing to the rich mathematical framework of Reproducing Kernel Hilbert Spaces (RKHS). Then we adapted the classical Representer Theorem to penalized (squared norm) log-likelihood which …

Health Professions Education And Critical Action Engagement: A Mixed Method Analysis., Leonda Richardson

Electronic Theses and Dissertations

Poorer health outcomes disproportionately impact racial/ethnically minoritized (e.g., Black Indigenous People of Color, or BIPOC) populations in the U.S. One plausible reason for the persistence of poorer health outcomes among this population is the teaching of racialized curricular content within academic health professions programs. This includes the absence of appropriate context through explicit socio-political curricular content (SPC) and critical pedagogy (i.e., social and structural determinants of health, history of racism in health care, social justice concepts; dialogue and reflective writing). Racialized curriculum is thought to initiate and/or exacerbate existing racial biases, cultural incompetence, and perpetuate dominant medical ideologies and myths …

Figure Worlds: An Analysis Of The Untold Stories Of Female Teachers Of Color., Anetria B. Swanson

Electronic Theses and Dissertations

This dissertation explores the lived experiences of Black female teachers in a large urban school district, focusing on how these experiences shape their identities, influence their professional practices, and affect their retention in the profession. Despite the growing recognition of the importance of teacher diversity, Black female teachers often encounter unique challenges, including systemic racism, microaggressions, and a lack of support and resources. Through a narrative inquiry approach, this study amplifies the voices of nine Black female teachers, uncovering their stories and the complexities of their professional lives. Guided by Critical Race Theory and the concept of figured worlds, this …

Understanding Barriers To Effective And Equitable Covid-19 Response Through The Evaluation Of Essential Needs Program In Jefferson County, Ky., Haritha Pallam

Electronic Theses and Dissertations

This study utilized a multi-method study approach to assess the effectiveness of the Essential Needs Program (ENP), aimed at aiding priority groups in successfully completing isolation or quarantine (I/Q) during the COVID-19 pandemic. It commences with an overview of the COVID-19 pandemic's history and the role of ENP as a local emergency response strategy to mitigate community spread. Chaos and systems theories were employed to comprehensively understand disaster phenomena and factors influencing individual adoption of protective measures during the pandemic. Additionally, institutional decision-making models and implementation science were utilized to elucidate how public health stakeholders coordinated ENP services provision and …

Ten Years As Boundary Object: The Search For Identity And Belonging As 'Hongkongers', John Lowe, Darlene Machell Espena, George Wong

Research Collection College of Integrative Studies

This article examines the complex process of symbolic boundary-making of ‘Hongkonger’ cultural identities through the lens of the controversial 2015 film Ten Years, which is a celebrated omnibus production comprised of five short segments that picture a dystopic end to Hong Kong’s cherished way of life in the year 2025. The article is premised on an interdisciplinary approach engaging with cultural studies and film studies. On one hand, it explores how Ten Years functioned as a boundary object, a vast terrain within which cultural identities of what it means to be a Hongkonger are constructed, banished, imagined, and performed under …

Mobilizing Online, Marching Offline: Familias Unidas Por Nuestros Desaparecidos’ Strategic Use Of Social Media, Iara Gonzalez Ascencio

International Studies (MA) Theses

How do civilian women strategically steer their nonviolent social movements in reaction to the terrifying phenomena of forced disappearances under narco-violence? As a form of resistance, civilian women in Mexico have organized and joined groups to locate their missing family members and friends in response to risks posed by the pervasiveness of drug-related violence and the absence of official security services. Existing studies explore the role of women in peacebuilding initiatives to resist violence and obtain social change in Latin American countries. Still, there is limited research on the role of digital feminism in marginalized local collective groups, particularly under …

Visible But Invisible: Chinese International Students’ Experience Of The Covid-19 Pandemic And Academic Institutions’ Support

Journal of Comparative & International Higher Education

No abstract provided.

Cybersecurity In Education, Rahima Shelim

Theses, Dissertations and Culminating Projects

Cybersecurity is becoming increasingly important as we rely more on digital devices and programs to conduct our daily lives, including the transfer and storage of personal information. According to research, one of the most critical stages in improving cybersecurity is to implement an effective security awareness program. In this work, we seek to understand the existing level of security knowledge among college students, industry professionals and create a module to help raise the awareness. Our module's primary elements are interaction and the display of alarming effects of reckless cyber behaviors among common Internet/technology users. This report presents a simple systematic …

Measuring Listening Effort In Bilingual Listeners For Speech Perception In Noise, Sita Carraturo

Arts & Sciences Graduate Student Theses and Dissertations

Noise is a common impedance to easy and accurate speech understanding. In the presence of noise, speech processing mechanisms proceed with partial or ambiguous inputs, and listeners will engage additional cognitive resources to make sense of what they hear. The extent to which this is situation is affected by diminished exposure to a language is an understudied question, but one that is relevant to bilingual listeners. By virtue of using two or more languages, bilinguals have less exposure to any one language than monolinguals of that language do. This, in turn, may make language processing more effortful for them, particularly …

Teachers’ Self-Reported Practices Of Teaching Academic Writing In Pakistani Universities, Hafiz Yar

Language, Literacy, and Sociocultural Studies ETDs

This study has explored teachers’ self-reported practices of teaching academic writing in Pakistani universities. The English language based developmental literacy courses in Pakistani undergraduate degrees are offered as part of the curricula rather than through specialized language centers. The three-course progression of developmental English literacy in Pakistani undergraduate curricula aims to develop academic writing proficiency besides effective business communication and technical report writing skills.

This study has used generic qualitative research methodology (Caelli et al., 2003; Kahlke, 2014; Kostere & Kostere, 2021), snowball sampling for participant recruitment, and a combination of survey and one-to-one semi structured interviews for data collection. …

Interpretable Tensor Fusion, Saurabh Varshneya, Antoine Ledent, Philipp Liznerski, Andriy Balinskyy, Purvanshi Mehta, Waleed Mustafa, Marius Kloft

Research Collection School Of Computing and Information Systems

Conventional machine learning methods are predominantly designed to predict outcomes based on a single data type. However, practical applications may encompass data of diverse types, such as text, images, and audio. We introduce interpretable tensor fusion (InTense), a multimodal learning method training a neural network to simultaneously learn multiple data representations and their interpretable fusion. InTense can separately capture both linear combinations and multiplicative interactions of the data types, thereby disentangling higher-order interactions from the individual effects of each modality. InTense provides interpretability out of the box by assigning relevance scores to modalities and their associations, respectively. The approach is …

Sibo : A Simple Booster For Parameter-Efficient Fine-Tuning, Zhihao Wen, Jie Zhang, Yuan Fang

Research Collection School Of Computing and Information Systems

Fine-tuning all parameters of large language models (LLMs) necessitates substantial computational power and extended time. Latest advancements in parameter-efficient fine-tuning (PEFT) techniques, such as Adapter tuning and LoRA, allow for adjustments to only a minor fraction of the parameters of these LLMs. Concurrently, it has been noted that the issue of over-smoothing diminishes the effectiveness of these Transformer-based LLMs, resulting in suboptimal performances in downstream tasks. In this paper, we present SIBO, which is a SImple BOoster to enhance PEFT, by injecting an initial residual. SIBO is straightforward and readily extensible to a range of state-of-the-art PEFT techniques to alleviate …

Planning Like Human : A Dual-Process Framework For Dialogue Planning, Tao He, Lizi Liao, Yixin Cao, Yuanxing Liu, Ming Liu, Zerui Chen, Bing Qin

Research Collection School Of Computing and Information Systems

In proactive dialogue, the challenge lies not just in generating responses but in steering conversations toward predetermined goals, a task where Large Language Models (LLMs) typically struggle due to their reactive nature. Traditional approaches to enhance dialogue planning in LLMs, ranging from elaborate prompt engineering to the integration of policy networks, either face efficiency issues or deliver suboptimal performance. Inspired by the dual-process theory in psychology, which identifies two distinct modes of thinking—intuitive (fast) and analytical (slow), we propose the Dual-Process Dialogue Planning (DPDP) framework. DPDP embodies this theory through two complementary planning systems: an instinctive policy model for familiar …

Analyzing Temporal Complex Events With Large Language Models? A Benchmark Towards Temporal, Long Context Understanding, Zhihan Zhang, Yixin Cao, Chenchen Ye, Ma. Yunshan, Lizi Liao, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The digital landscape is rapidly evolving with an ever-increasing volume of online news, emphasizing the need for swift and precise analysis of complex events.We refer to the complex events composed of many news articles over an extended period as Temporal Complex Event (TCE). This paper proposes a novel approach using Large Language Models (LLMs) to systematically extract and analyze the event chain within TCE, characterized by their key points and timestamps. We establish a benchmark, named TCELongBench, to evaluate the proficiency of LLMs in handling temporal dynamics and understanding extensive text. This benchmark encompasses three distinct tasks - reading comprehension, …

Synergizing Large Language Models And Pre-Trained Smaller Models For Conversational Intent Discovery, Jinggui Liang, Lizi Liao, Hao Fei, Jing Jiang

Research Collection School Of Computing and Information Systems

In Conversational Intent Discovery (CID), Small Language Models (SLMs) struggle with overfitting to familiar intents and fail to label newly discovered ones. This issue stems from their limited grasp of semantic nuances and their intrinsically discriminative framework. Therefore, we propose Synergizing Large Language Models (LLMs) with pre-trained SLMs for CID (SynCID). It harnesses the profound semantic comprehension of LLMs alongside the operational agility of SLMs. By utilizing LLMs to refine both utterances and existing intent labels, SynCID significantly enhances the semantic depth, subsequently realigning these enriched descriptors within the SLMs’ feature space to correct cluster distortion and promote robust learning …

A Survey On Neural Question Generation : Methods, Applications, And Prospects, Shasha Guo, Lizi Liao, Cuiping Li, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

In this survey, we present a detailed examination of the advancements in Neural Question Generation (NQG), a field leveraging neural network techniques to generate relevant questions from diverse inputs like knowledge bases, texts, and images. The survey begins with an overview of NQG’s background, encompassing the task’s problem formulation, prevalent benchmark datasets, established evaluation metrics, and notable applications. It then methodically classifies NQG approaches into three predominant categories: structured NQG, which utilizes organized data sources, unstructured NQG, focusing on more loosely structured inputs like texts or visual content, and hybrid NQG, drawing on diverse input modalities. This classification is followed …

Speaker Verification In Agent-Generated Conversations, Yizhe Yang, Palakorn Achananuparp, Heyan Huang, Jing Jiang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

The recent success of large language models (LLMs) has attracted widespread interest to develop role-playing conversational agents personalized to the characteristics and styles of different speakers to enhance their abilities to perform both general and special purpose dialogue tasks. However, the ability to personalize the generated utterances to speakers, whether conducted by human or LLM, has not been well studied. To bridge this gap, our study introduces a novel evaluation challenge: speaker verification in agent-generated conversations, which aimed to verify whether two sets of utterances originate from the same speaker. To this end, we assemble a large dataset collection encompassing …

Larp: Language Audio Relational Pre‑Training For Cold‑Start Playlist Continuation, Rebecca Salganik, Xiaohao Liu, Yunshan Ma, Jian Kang, Tat‑Seng Chua

Research Collection School Of Computing and Information Systems

As online music consumption increasingly shifts towards playlist-based listening, the task of playlist continuation, in which an algorithm suggests songs to extend a playlist in a personalized and musically cohesive manner, has become vital to the success of music streaming services. Currently, many existing playlist continuation approaches rely on collaborative filtering methods to perform their recommendations. However, such methods will struggle to recommend songs that lack interaction data, an issue known as the cold-start problem. Current approaches to this challenge design complex mechanisms for extracting relational signals from sparse collaborative signals and integrating them into content representations. However, these approaches …

Nonfactoid Question Answering As Query-Focused Summarization With Graph-Enhanced Multihop Inference, Yang Deng, Wenxuan Zhang, Weiwen Xu, Ying Shen, Wai Lam

Research Collection School Of Computing and Information Systems

Nonfactoid question answering (QA) is one of the most extensive yet challenging applications and research areas in natural language processing (NLP). Existing methods fall short of handling the long-distance and complex semantic relations between the question and the document sentences. In this work, we propose a novel query-focused summarization method, namely a graph-enhanced multihop query-focused summarizer (GMQS), to tackle the nonfactoid QA problem. Specifically, we leverage graph-enhanced reasoning techniques to elaborate the multihop inference process in nonfactoid QA. Three types of graphs with different semantic relations, namely semantic relevance, topical coherence, and coreference linking, are constructed for explicitly capturing the …

A New Approach Of Tree Soft Set With Mcdm Technique For Leadership In International Climate Policy: Measuring Renewable Energy Sources And Policies, Nouran Ajabnoor

Neutrosophic Sets and Systems

Green technological progress can be achieved by mitigation efforts of leadership in climate policy. Renewable energies need to develop technological innovations for more competitive advantages. This study proposed a decision-making methodology for evaluating renewable energy sources under leadership in international climate policy. This study used the multi-criteria decision-making methodology to deal with conflicting criteria in the decision-making problem. The evaluation is based on the distance from the average solution (EDAS) method, which ranks the alternatives. The criteria weights are computed by using the average method. The neutrosophic set deals with uncertainty and vague information in the evaluation process. The neutrosophic …

On The Multi-Turn Instruction Following For Conversational Web Agents, Yang Deng, Xuan Zhang, Wenxuan Zhang, Yifei Yuan, See-Kiong Ng, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Web agents powered by Large Language Models (LLMs) have demonstrated remarkable abilities in planning and executing multi-step interactions within complex web-based environments, fulfilling a wide range of web navigation tasks. Despite these advancements, the potential for LLM-powered agents to effectively engage with sequential user instructions in real-world scenarios has not been fully explored. In this work, we introduce a new task of Conversational Web Navigation, which necessitates sophisticated interactions that span multiple turns with both the users and the environment, supported by a specially developed dataset named Multi-Turn Mind2Web (MT-Mind2Web). To tackle the limited context length of LLMs and the …

Clamber: A Benchmark Of Identifying And Clarifying Ambiguous Information Needs In Large Language Models, Tong Zhang, Peixin Qin, Yang Deng, Chen Huang, Wenqiang Lei, Junhong Liu, Dingnan Jin, Hongru Liang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly used to meet user information needs, but their effectiveness in dealing with user queries that contain various types of ambiguity remains unknown, ultimately risking user trust and satisfaction. To this end, we introduce CLAMBER, a benchmark for evaluating LLMs using a well-organized taxonomy. Building upon the taxonomy, we construct 12K high-quality data to assess the strengths, weaknesses, and potential risks of various off-the-shelf LLMs.Our findings indicate the limited practical utility of current LLMs in identifying and clarifying ambiguous user queries, even enhanced by chain-of-thought (CoT) and few-shot prompting. These techniques may result in overconfidence …

Examining Novice Teacher’S Perspectives On Mentoring Programs And Their Influence On Attrition, Lakeisha Ector

Dissertations

This qualitative study examines the perspectives of novice teachers on mentoring programs and their influence on attrition. Mentoring programs present opportunities for skilled educators to teach, sponsor, encourage and advise novices, improving their personal and professional development. The research determines whether mentoring and induction programs strengthen teacher efficacy and their influence on attrition rates. The study is rooted in constructivism, which seeks to develop an understanding and knowledge of individuals through their experiences and reflection. The research employs an inductive and deductive approach, facilitating pattern and theme identification. The study involves nine participants – novice teachers – from Martin-Ellison County …

Religious Motives In Ukrainian Folklore: Linguistic Analysis, Olena Svysiuk, Zoya Biloshytska

Occasional Papers on Religion in Eastern Europe

The paper explores the profound influence of religious motifs on the national identity of Ukrainians, emphasizing their impact on cultural, social, and spiritual dimensions. The enduring significance of religion in shaping cultural and societal development is highlighted, with particular attention to the intricate interplay of religious and national themes throughout Ukrainian history. In the context of contemporary globalization, the study underscores the critical role of religious elements in folklore, art, and literature as custodians of cultural memory and transmitters of traditional values. Ukrainian folklore, especially rich in religious themes, serves as a vital means of preserving national ideals and ethical …

Review Of Aleksandra Djurić-Milovanović'S, “The Untold Journey Of The Nazarene Emigration From Yugoslavia To North America“, Marko Galić

Occasional Papers on Religion in Eastern Europe

A review of Aleksandra Djurić-Milovanović, “The Untold Journey of the Nazarene Emigration from Yugoslavia to North America“ Lexington Books, 2024, 158 pp.

ISBN: 978-1-66692-276-9

Utilizing New Temporal Complex Neutrosophic Aczel-Alsina Aggregation Operators For Multi-Criteria Decision Making: An Application To Tourist Destination Selection, Le Mai Trang, Nguyen Tho Thong, Nguyen Thi Lan Nhi

Neutrosophic Sets and Systems

The Temporal Complex Neutrosophic Set (TCNS) is a powerful extension of the Neutrosophic theory, and TCNS has added advantage to represents uncertain, indeterminate, inconsistent and time related factors. In the literature TCNS has been used for multi-criteria decision-making problems, especially in the time-aware systems. In order to tackle effectively decision-making problems in the TCNS environment effectively, it is crucial to make suite aggregation operators that enable decision makers to process preferences in a nuanced manner. In this paper, we introduce novel TCNS aggregation operators based on Aczel and Alsina t-norm and t-conorm using Aczel-Alsina operations, and we propose a multi-criteria …

Magdm Technique Based On Linguistic Neutrosophic Tangent Dombi Aggregation Operators And Its Application In Selecting New Energy Design Schemes, Lu Niu, Jun Ye

Neutrosophic Sets and Systems

In linguistic decision theory, multi-attribute group decision-making (MAGDM) of linguistic neutrosophic numbers (LNNs) is one of the crucial research topics. Existing LNN aggregation algorithms do not consider trigonometric periodicity. In this case, they cannot perform MAGDM problems including periodic/multitemporal applications in LNN scenarios. To fill this gap, this article aims to present a MAGDM technique using the LNN tangent Dombi aggregation operators (TDAOs) for addressing MAGDM issues including multitemporal/periodic applications in LNN scenarios. First, we present the linguistic tangent Dombi t-norm and t-conorm and the LNN tangent Dombi operation laws. Second, we propose the LNN tangent Dombi weighted average and …

Trf-Bwm-Neutrosophic-Topsis Strategy Under Svns Environment Approach And Its Application To Select The Most Effective Water Quality Parameter Of Aquaponic System, Pragnaleena Debroy, Priyanka Majumder, Surapati Pramanik, Lalu Seban

Neutrosophic Sets and Systems

The rapid emergence of aquaponics presents a promising solution for food production in arid regions, heavily reliant on maintaining optimal water quality parameters for overall success. However, monitoring and controlling these parameters can be complex and costly, involving numerous sensors and actuators. Focusing on the most significant parameter for fish growth could alleviate some of this complexity and promote sustainability by ensuring a balanced system. This study introduces a novel fuzzy-based Multiple Criteria Decision Making (MCDM) methodology, combining Trapezoidal Fuzzy with the Best Worst Method (BWM) and Neutrosophic-TOPSIS strategy, to identify the primary water quality parameters impacting fish growth. Through …