5,476 research outputs found
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
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An investigation into the cultural and legal factors influencing the differential prosecution rate for female genital mutilation in England and France
Female Genital Mutilation (FGM) is a problem that both England and France face. Both countries agree that FGM is a criminal offence and that it constitutes child abuse. Accordingly, each nation has taken its own distinct measures in law and policy against the practice. These approaches have produced significantly divergent outcomes, particularly in the prosecution rates of offenders, with France leading in that regard.
This thesis seeks to understand why criminal justice outcomes differ so significantly between the two nations, despite many parallels between the historical and contemporary contexts of these two Western European neighbours. In order to do this, it seeks to explore the overarching, systemic forces at play within both paradigms, what the author has termed âthe Mediumâ. Furthermore, given that FGM within both France and England is a product of migrant communities having transported cultural practices into their new context, particular attention is paid to approaches to multiculturalism as a key aspect of the Medium for the purposes of this study. However, alongside this examination of the Medium, the study also explores the role of individual activism, and the agency of particular campaigners, termed âthe Human Catalystâ. It addresses the complex interplay between the Medium and the Human Catalyst, as a means of understanding their combined influence on the divergent pictures in respect of prosecuting FGM
Thomas Hobbes and the phenomena of civil war: A textual exposition of Hobbesâs commitment to the empirical and historical existence of the state of nature.
Did Thomas Hobbes consider his conception of the state of nature to be based within any empirically verifiable reality?
The foundational predicates of this thesis can be reduced to two fundamental points:
1. That Hobbesâs belief in the existence in the state of nature was sincere.
2. The most pertinent empirical basis for the state of nature expressed by Hobbes was civil war, specifically, the English Civil War Period.
The analytical trajectory of the thesis will endeavour, whenever possible, to pursue channels of inquiry which correspond to the two key predicates adumbrated above.
The format has been styled as a âtextual expositionâ because the method endorsed will seek to expose Hobbesâs commitment to the existence of the state of nature from the words that he himself had written. Whether they be elements of his renowned philosophical system, or written material situated outside the terminus of his political science. Such as his correspondence, or lesser-known publications.
Secondary material written about Hobbesâs state of nature, and the judgments of such authors as created them will of course be consulted at various points. However, to the primary material, containing Hobbesâs own judgments on the state of nature and its relationship with civil war, is accorded the greater responsibility for validating the premises of this thesis
Measuring the Severity of Depression from Text using Graph Representation Learning
The common practice of psychology in measuring the severity of a patient's depressive symptoms is based on an interactive conversation between a clinician and the patient. In this dissertation, we focus on predicting a score representing the severity of depression from such a text. We first present a generic graph neural network (GNN) to automatically rate severity using patient transcripts. We also test a few sequence-based deep models in the same task. We then propose a novel form for node attributes within a GNN-based model that captures node-specific embedding for every word in the vocabulary. This provides a global representation of each node, coupled with node-level updates according to associations between words in a transcript. Furthermore, we evaluate the performance of our GNN-based model on a Twitter sentiment dataset to classify three different sentiments and on Alzheimer's data to differentiate Alzheimerâs disease from healthy individuals respectively. In addition to applying the GNN model to learn a prediction model from the text, we provide post-hoc explanations of the model's decisions for all three tasks using the model's gradients
Embedding Based Link Prediction for Knowledge Graph Completion
Knowledge Graphs (KGs) are the most widely used representation of structured information about a particular domain consisting of billions of facts in the form of entities (nodes) and relations (edges) between them. Besides, the KGs also encapsulate the semantic type information of the entities. The last two decades have witnessed a constant growth of KGs in various domains such as government, scholarly data, biomedical domains, etc. KGs have been used in Machine Learning based applications such as entity linking, question answering, recommender systems, etc. Open KGs are mostly heuristically created, automatically generated from heterogeneous resources such as text, images, etc., or are human-curated. However, these KGs are often incomplete, i.e., there are missing links between the entities and missing links between the entities and their corresponding entity types. This thesis focuses on addressing these two challenges of link prediction for Knowledge Graph Completion (KGC):
\textbf{(i)} General Link Prediction in KGs that include head and tail prediction, triple classification, and
\textbf{(ii)} Entity Type Prediction.
Most of the graph mining algorithms are proven to be of high complexity, deterring their usage in KG-based applications. In recent years, KG embeddings have been trained to represent the entities and relations in the KG in a low-dimensional vector space preserving the graph structure. In most published works such as the translational models, convolutional models, semantic matching, etc., the triple information is used to generate the latent representation of the entities and relations.
In this dissertation, it is argued that contextual information about the entities obtained from the random walks, and textual entity descriptions, are the keys to improving the latent representation of the entities for KGC. The experimental results show that the knowledge obtained from the context of the entities supports the hypothesis. Several methods have been proposed for KGC and their effectiveness is shown empirically in this thesis. Firstly, a novel multi-hop attentive KG embedding model MADLINK is proposed for Link Prediction. It considers the contextual information of the entities by using random walks as well as textual entity descriptions of the entities. Secondly, a novel architecture exploiting the information contained in a pre-trained contextual Neural Language Model (NLM) is proposed for Triple Classification. Thirdly, the limitations of the current state-of-the-art (SoTA) entity type prediction models have been analysed and a novel entity typing model CAT2Type is proposed that exploits the Wikipedia Categories which is one of the most under-treated features of the KGs. This model can also be used to predict missing types of unseen entities i.e., the newly added entities in the KG.
Finally, another novel architecture GRAND is proposed to predict the missing entity types in KGs using multi-label, multi-class, and hierarchical classification by leveraging different strategic graph walks in the KGs. The extensive experiments and ablation studies show that all the proposed models outperform the current SoTA models and set new baselines for KGC.
The proposed models establish that the NLMs and the contextual information of the entities in the KGs together with the different neural network architectures benefit KGC. The promising results and observations open up interesting scopes for future research involving exploiting the proposed models in domain-specific KGs such as scholarly data, biomedical data, etc. Furthermore, the link prediction model can be exploited as a base model for the entity alignment task as it considers the neighbourhood information of the entities
International Academic Symposium of Social Science 2022
This conference proceedings gathers work and research presented at the International Academic Symposium of Social Science 2022 (IASSC2022) held on July 3, 2022, in Kota Bharu, Kelantan, Malaysia. The conference was jointly organized by the Faculty of Information Management of Universiti Teknologi MARA Kelantan Branch, Malaysia; University of Malaya, Malaysia; Universitas Pembangunan Nasional Veteran Jakarta, Indonesia; Universitas Ngudi Waluyo, Indonesia; Camarines Sur Polytechnic Colleges, Philippines; and UCSI University, Malaysia. Featuring experienced keynote speakers from Malaysia, Australia, and England, this proceeding provides an opportunity for researchers, postgraduate students, and industry practitioners to gain knowledge and understanding of advanced topics concerning digital transformations in the perspective of the social sciences and information systems, focusing on issues, challenges, impacts, and theoretical foundations. This conference proceedings will assist in shaping the future of the academy and industry by compiling state-of-the-art works and future trends in the digital transformation of the social sciences and the field of information systems. It is also considered an interactive platform that enables academicians, practitioners and students from various institutions and industries to collaborate
Accounting in action in the New Zealand health reform process: an analysis informed by a specific case study of a major health provider
This thesis constitutes an empirical study of accounting in action, focussing attention on patient based cost systems. The thesis contributes an in depth understanding of the mobilisation of casemix and related information systems at a large regional hospital, Health Waikato (HW), in the centre of the North Island of New Zealand. The field research consisted of primarily unstructured and semi-structured interviews and documentary analysis. I present the research in the later part of the thesis from a constructionist, interpretive perspective. This consists of richly descriptive case studies of aspects of the change process as it has impacted upon the research site. The themes of the analysis are related, at the macro level, to the resurrection of neoclassical economics policies and the relative ascendancy of free market solutions. The process through which areas of knowledge and in this case particularly public policy become problematised is explicated.
My research attempts to describe the experiences and perceptions of medical and managerial\financial staff at a work unit level within a single hospital. A part of this process has involved investigation of the implementation of traditional accounting technologies in unfamiliar environments. The research is primarily concerned to elaborate upon the social context of accounting systems implementation using theoretical insights derived from Latour (particularly: 1987, 1993). The research has sought to explicate the change process as a process of translation. Traditional accounting techniques have been explicated as âblack boxâ technology with which the organisation has been redefined in economic terms.
In the study, the power of accounting in the translation and inscription of data (the fabrication of accounting systems per Preston et al, 1992), is central to understanding the role of accounting systems as technology. Drawing from the work of Latour helps to provide a frame of reference to allow an assimilation of disparate changes and influences as they have come to affect the health sector at a national level, within New Zealand, and also at an organisational level, within a large regional health provider. The research contributes in explicating the relevance of Latourâs rules of method, and underlying theoretical framework for an organisational analysis focusing upon accounting. Latour uses a very general conception of technology which encompasses anything emerging from what he terms the process of âtranslationâ. In this context Latour uses the term to refer to the production or âfabricationâ of âquasi-objectsâ. This is most easily seen as consisting of the physical objects which âpopulate our western societiesâ, but for Latour also includes inscriptions and âfacts/artefactsâ. I regard accounting and information systems as consisting of mixtures (or perhaps âcollectivesâ) of technological quasi-objects in this very general sense.
The focus of the research has been upon the identification of problems, the choice of accounting techniques and their implementation. Together with other devices the use of accounting techniques may be seen as a central part of the process through which change is made acceptable within the organisation. Supporters are enrolled into the change process in part by being exposed to the accounting inscriptions which are used to represent the cost and profit ârealityâ of their unit and the whole organisation. The research process has involved detailed investigation on a case by case basis to enable a thorough description of the accounting techniques being put in place.
The title of the thesis is based on Latour (1987) "Science in Action". Conventions developed in Actor Network Theory might suggest my title would be better understood as "Accounting as Actant" but it seems to me that Latour was clearly aware of this same point when he chose this title for his book
Say That Again: The role of multimodal redundancy in communication and context
With several modes of expression, such as facial expressions, body language, and speech working together to convey meaning, social communication is rich in redundancy. While typically relegated to signal preservation, this study investigates the role of cross-modal redundancies in establishing performance context, focusing on unaided, solo performances. Drawing on information theory, I operationalize redundancy as predictability and use an array of machine learning models to featurize speakers\u27 facial expressions, body poses, movement speeds, acoustic features, and spoken language from 24 TEDTalks and 16 episodes of Comedy Central Stand-Up Presents. This analysis demonstrates that it is possible to distinguish between these performance types based on cross-modal predictions, while also highlighting the significant amount of prediction supported by the signalsâ synchrony across modalities. Further research is needed to unravel the complexities of redundancy\u27s place in social communication, paving the way for more effective and engaging communication strategies
Prompt Injection attack against LLM-integrated Applications
Large Language Models (LLMs), renowned for their superior proficiency in
language comprehension and generation, stimulate a vibrant ecosystem of
applications around them. However, their extensive assimilation into various
services introduces significant security risks. This study deconstructs the
complexities and implications of prompt injection attacks on actual
LLM-integrated applications. Initially, we conduct an exploratory analysis on
ten commercial applications, highlighting the constraints of current attack
strategies in practice. Prompted by these limitations, we subsequently
formulate HouYi, a novel black-box prompt injection attack technique, which
draws inspiration from traditional web injection attacks. HouYi is
compartmentalized into three crucial elements: a seamlessly-incorporated
pre-constructed prompt, an injection prompt inducing context partition, and a
malicious payload designed to fulfill the attack objectives. Leveraging HouYi,
we unveil previously unknown and severe attack outcomes, such as unrestricted
arbitrary LLM usage and uncomplicated application prompt theft. We deploy HouYi
on 36 actual LLM-integrated applications and discern 31 applications
susceptible to prompt injection. 10 vendors have validated our discoveries,
including Notion, which has the potential to impact millions of users. Our
investigation illuminates both the possible risks of prompt injection attacks
and the possible tactics for mitigation
Ludology as a theoretical lens for interactive works: Demonstrating the theoretical gaps in copyright analysis of interactive works
This research argues that without the appropriate category or lexicon to address interactive creations and with their assessment by analogy, interactive creations are improperly protected by copyright. They are over-under protected, their infringement decisions incoherent, inconsistent, and are protected in ways which entirely overlook their distinct and unique characteristics as an expressive medium. Drawing the boundaries of protection already proves difficult for copyright, owing to flaws and shortcomings with its principles and subject matter categorization. Which in part is why copyright struggles to protect interactive creations. However, it is contended that interactive creations present further difficulties which emerge by virtue of their interactivity. It is argued that this interactivity leads them to present significant practical and conceptual questions which copyright is ill equipped to answer. And whilst the existing academic commentary does highlight the challenges facing interactive creations, it does not do so in a way that meaningfully or specifically addresses interactive creations as a distinct medium, nor does it consider their unique qualities. To that end, this thesis argues that video game scholarship presents a helpful foundation for understanding how a more accurate ontology for interactive works might be constructed. It is contended that video game studies and ludology, can provide insights on what these neglected qualities are, as well as potential frameworks and vocabulary for more appropriately understanding and structuring these concepts. Arguing that ludology and the concepts proposed by the ludologist Frasca provide a clearer analytical lens for assessing the distinct and novel expressive capabilities of the medium. Concluding that copyright must re-evaluate its scope and purpose to better accommodate the subject matter it seeks to protect
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