Dissertations / Theses on the topic 'Theory and criticism not elsewhere classified'

This thesis uses cultural studies approaches to ask in what ways can intersubjective art act on the disparities brought about by late capitalism through the auspices of cosmopolitanism? How do the same processes that oppress others allow the artist to be mobile and self-reflexive while accruing and deploying a broad range of knowledges and competencies? The answer is paradoxical: those oppressed by the processes of late capitalism become the focus, theme, and content of the intersubjective artwork while the artists benefit from a system they seek to problematise and critique. Three case study chapters highlight these complex and disconcerting politics.

This thesis studies the theory of stochastic adaptive computation based on neural networks. A mathematical theory of computation is developed in the framework of information geometry, which generalises Turing machine (TM) computation in three aspects - It can be continuous, stochastic and adaptive - and retains the TM computation as a subclass called "data processing". The concepts of Boltzmann distribution, Gibbs sampler and simulated annealing are formally defined and their interrelationships are studied. The concept of "trainable information processor" (TIP) - parameterised stochastic mapping with a rule to change the parameters - is introduced as an abstraction of neural network models. A mathematical theory of the class of homogeneous semilinear neural networks is developed, which includes most of the commonly studied NN models such as back propagation NN, Boltzmann machine and Hopfield net, and a general scheme is developed to classify the structures, dynamics and learning rules. All the previously known general learning rules are based on gradient following (GF), which are susceptible to local optima in weight space. Contrary to the widely held belief that this is rarely a problem in practice, numerical experiments show that for most non-trivial learning tasks GF learning never converges to a global optimum. To overcome the local optima, simulated annealing is introduced into the learning rule, so that the network retains adequate amount of "global search" in the learning process. Extensive numerical experiments confirm that the network always converges to a global optimum in the weight space. The resulting learning rule is also easier to be implemented and more biologically plausible than back propagation and Boltzmann machine learning rules: Only a scalar needs to be back-propagated for the whole network. Various connectionist models have been proposed in the literature for solving various instances of problems, without a general method by which their merits can be combined. Instead of proposing yet another model, we try to build a modular structure in which each module is basically a TIP. As an extension of simulated annealing to temporal problems, we generalise the theory of dynamic programming and Markov decision process to allow adaptive learning, resulting in a computational system called a "basic adaptive computer", which has the advantage over earlier reinforcement learning systems, such as Sutton's "Dyna", in that it can adapt in a combinatorial environment and still converge to a global optimum. The theories are developed with a universal normalisation scheme for all the learning parameters so that the learning system can be built without prior knowledge of the problems it is to solve.

The International Safety Management (ISM) Code was introduced in 1998 in response to a number of high-profile maritime disasters, with the aim of establishing minimum standards for the safe operation of ships and creating an enhanced safety culture. It was the first piece of legislation introduced by the International Maritime Organisation that demanded a change in the behaviour and attitude of the international maritime community. Whilst there is no doubt that the ISM Code has been successful at improving maritime safety, there is now an increasing problem with complacency. The aim of this thesis is to consider how complacency with the ISM Code in the UK can be tackled by using reformed corporate manslaughter legislation. This thesis adopts a Safety Culture Theory approach and uses a multi-model research design methodology; a doctrinal model and a socio-legal model. The thesis hypothesis and the author's proposed corporate manslaughter reforms are tested through case studies and a survey. The thesis proposes the introduction of secondary individual liability for corporate manslaughter, in addition to existing primary corporate liability. If the proposed provisions were to be implemented, a gap in the law would be filled and, for the maritime industry, both the ship company and its corporate individuals would be held accountable for deaths at sea that are attributable to non-implementation of the ISM Code. It is suggested that this would deter further ISM complacency and so encourage the ISM Code’s intended safety culture. This thesis contributes to the intellectual advancement of the significant and developing interplay between criminal and maritime law, by adding to the scholarly understanding of the safety culture operating within the international maritime community, and examining how corporate manslaughter legislation could be used to improve implementation of the ISM Code. It offers sound research for consideration by legal researchers and scholars, and also by those working within the field of maritime safety regulation.

This dissertation argues for the value of the concept of systemic reflexivity in sense making, orientation and action in systemic practice, and in organisational practice in particular. The concept emerges as a theme through the development of two specific strands of published work from 1992 to 2013, that of Coordinated Management of Meaning Theory (CMM) and Appreciative Inquiry (AI). Both lines of inquiry highlight the moral dimension of practitioners’ conceptualisation and practice. Systemic reflexivity alerts us to the opportunities and constraints system participants make for the system in focus, facilitating exploration of a system’s coherence, through a detailed framework for systemic thinking which links patterns of communication to their narratives of influence and narrative consequences. It provides the conditions for enabling individual and collective responsibility for the ways that communication shapes our social worlds. The concept is illustrated in practice through a range of case studies within the published works.

In this work methods for performing time series prediction on complex real world time series are examined. In particular series exhibiting non-linear or chaotic behaviour are selected for analysis. A range of methodologies based on Takens' embedding theorem are considered and compared with more conventional methods. A novel combination of methods for determining the optimal embedding parameters are employed and tried out with multivariate financial time series data and with a complex series derived from an experiment in biotechnology. The results show that this combination of techniques provide accurate results while improving dramatically the time required to produce predictions and analyses, and eliminating a range of parameters that had hitherto been fixed empirically. The architecture and methodology of the prediction software developed is described along with design decisions and their justification. Sensitivity analyses are employed to justify the use of this combination of methods, and comparisons are made with more conventional predictive techniques and trivial predictors showing the superiority of the results generated by the work detailed in this thesis.

This thesis identifies and characterises a minimal aesthetic evident in a strand of fashion emerging in New York and Paris from 1964 onwards. It examines the way in which a minimal aesthetic has been applied to the practice of fashion design and retail architecture, specifically in a high-fashion context. The research establishes that the earliest manifestation of a minimal aesthetic in fashion design, took place in 1964, in the work of the French fashion designer André Courrèges. Designers who later adopted similar principles include Jil Sander (1968), Calvin Klein (1968), Zoran Ladricorbic (1976), Donna Karan (1984), Helmut Lang (1986) and Narciso Rodriguez (1997), among others. The study identifies the origins of the principles of a minimal aesthetic and examines them through two distinct case studies that consider the practice of designers Donna Karan and Helmut Lang, both of whose work emerged during the 1980s. The investigation re-evaluates the significance of Minimalism in fashion history. It challenges accepted views of Minimalism in fashion as merely a trend of the mid-1990s, or as a local phenomenon. The thesis maintains that these principles find expression in the designers’ work, in the architecture of the flagship stores and in the inter-relationship between the two. Additionally, it investigates the meanings that these products convey to the consumer. Through an evaluation of the retail architecture, it establishes parallels between the principles of this aesthetic and earlier elements of a post-war Modernist architecture. The study of the dynamic inter-relationship between elements of fashion design and those of architecture focuses on the definition of a minimal aesthetic. Furthermore, these claims are contextualized within other fields such as material culture, cultural and historical studies and sociology. The thesis employs a qualitative methodology comprising empirical research based on case studies and object-based analysis, all of which draw upon theory that addresses the means of interpretation. The study has developed through an analysis of dress and the retail architecture associated with the case study designers’ work. Through empirical research, the research shows how contemporary attitudes, practices and theories have emerged which are essential for the analysis of dress and the spaces it inhabits. The primary sources, garments from the collections of André Courrèges, Donna Karan and Helmut Lang held at key international costume archives at the Victoria & Albert Museum, London and the Fashion Institute of Technology and the Metropolitan Museum of Art, New York, are discussed in relation to other archival and published sources.

One of the most important advances in modern theoretical surface science and catalysis research has been the advent of Ab-Initio Density Functional Theory (DFT). Based on the electronic structure formulation of Pierre Hohenberg, Walter Kohn and Lu Jeu Sham, DFT has revolutionized theoretical research in heterogeneous catalysis, electrocatalysis, batteries, as well as homogeneous catalysis using first-principles electronic structure simulations. Combined with statistical mechanics, kinetic theory, and experimental inputs, DFT provides a powerful technique for investigating surface structure, reaction mechanisms, understanding underlying reactivity trends, and using them for rational and predictive design of materials for various catalytic chemistries, including those that can propel us towards a clean energy future – for example water gas shift (WGS), methanol synthesis, oxidation reactions, CO2 electroreduction, among many others. Fueled by advances in supercomputing facilities, numerous early and current DFT studies have been primarily focused on idealized simulations aimed at obtaining qualitative insights into experimental observations. However, as the immense potential of DFT has been unfolding, the demand for closer representation of realistic catalytic situations have rapidly emerged, and with it, the recognition of the need to reduce the disparity between theoretical DFT structures and real catalytic environments. Bridging this ‘materials gap’ necessitates using more rigorous catalyst structures in DFT calculations that can capture realistic experimental geometries, while at the same time, are creatively simplified to be computationally tractable. This thesis is a compilation of several projects on metals and metal/oxide systems that have been undertaken using DFT, in collaboration with experimental colleagues, with the goal of addressing some of the challenges in heterogeneous catalysis, while decreasing the ‘materials gap’ between theory and experiments.

This thesis discusses occupancy grid map, collision avoidance system and belief theory, and propose some of the latest and the most effective method such as predictive occupancy grid map, risk evaluation model and OGM role in the belief function theory with the approach of decision uncertainty according to the environment perception with the degree of belief in the driving command acceptability. Finally, how the proposed models mitigate or prevent the occurrence of the collision.

This creative non-thesis project includes three theories from communication studies. Uncertainty Reduction Theory, Cultivation Theory, and Cognitive Dissonance Theory. Each theoretical framework also includes a script written with the intent of filming in the future. Those videos could be shown in communication classes. These three theories cover a breadth of knowledge in the field as they pertain to interpersonal communication, media studies, and persuasion.

Stakeholders involved in debates around climate-energy policy shape public conversations through different “frames”: message units that strategically emphasize particular aspects of an issue while downplaying others. I investigate the presence of frames within climate change discourse and their political influence in the creation of climate-energy policies. Findings suggest that science frames may play a limited role when it comes to the development of actual climate policy at the state level, and importantly, that the strategic use of issue frames was able to level the playing field between environmental advocates and historically dominant industry actors. This work thus contributes to ongoing debates in the climate change framing literature by considering the “real world” of political communication coupled with an on-the-ground policy conflict.

In recent years, there has been an increase in environmental awareness in the United States leading to steady growth in environmentally conscious consumerism. These changes have come in response to issues such as the energy crisis, climate change, exponential population growth, and rapid urbanization. This fact is further supported by environmental campaigns and the green movement. Looking to the future of green home marketing, understanding the green consumer behavior of Generation Z (GenZ) is important for environmental and business reasons. The purpose of this research is to better understand the perception of GenZ on Green Homes (GHs). The study uses the lenses of dual inheritance and normative motivation theory to explain the influence of benefits and norms related to environmentalism and sustainability on GenZ consumers’ green behavior. This study seeks to evaluate 1) GenZ’s preferences related to Green Home Features (GHFs), 3) the extent of the influence of certain barriers on the adoption of GHFs, and 3) the types of motivation (intrinsic, instrumental and non-normative) influencing GenZ towards green home consumerism. Data was collected using an online survey questionnaire exclusively at Purdue University during March – April of 2021 (IRB 2020-1414). One hundred sixteen GenZ participants responded to the survey.The findings show that these GenZ consumers prefer a certain type of GHFs over others. Additionally, based on descriptive tests of GHFs, energy-related features were the most prized features, while the least preferred was water-efficient features. Descriptive tests on barriers suggest that GenZ consumers perceive the lack of choice in selecting GHFs in their homes to be a top barrier, followed by a lack of information and the perceived effort to analyze GHFs. Inferential tests for the same indicated that GenZ consumers perceive these barriers differently. Lastly, for GenZ consumers, intrinsic and non-normative motivations significantly affect their willingness to buy GHs. The findings concur with previous studies on green consumer behavior, yet they provide a new benchmark for understanding GenZ consumer behavior on GHs and an updated view of what GHFs they prefer. This research can be used by home marketers and policy makers to study future home trends, attract more potential homeowners to GHs, and help create a sustainable environment for future generations.

Misunderstanding or misinterpreting specific animal behavior and welfare terminology, as well as principles of learning theory, may influence an individual’s perceptions of horse behavior. This error could potentially result in unnecessary applications of horse training principles and/or human interventions, which could potentially worsen the behavior or situation, leading to unnecessary welfare problems.

The purpose of this dissertation was to explore interpretations and understandings of specific animal behavior and welfare terminology, and learning theory principles, as applied to horses, among adults within the horse industry. Chapters 1 and 2 introduced, summarized, and linked the connection between horse behavior, horse welfare, learning theory, and schema theory. Chapter 3 and Chapter 4 each pilot-tested an online survey that was completed at the convenience of each participant to explore these interpretations and understandings. Chapter 3 (n = 46) utilized a survey containing general demographic questions, psychographic questions related to horse industry involvement, five videos of horse-human interactions (each with corresponding heart rate, HR, data), and 11 learning theory scenarios. Chapter 4 (n = 21) used a survey containing general demographic questions and five videos of various human-horse interactions, including the same five videos with horse HR information included. Using results from Chapter 3 and Chapter 4, further investigation of how individuals interpret and understand specific animal behavior and welfare terminology, and learning theory principles, as applied to horses was explored across a larger sample of adults within the horse industry. Chapter 5 (n = 1,145) utilized the same survey instrument as Chapter 3 among a more robust sample of adults within the horse industry.

Across all three studies, the main results suggest that although participants demonstrated a high level of agreement between each other when identifying fear, stress, and reactivity to describe a horse’s behavior, participants could not correctly define fear, stress, reactivity, or principles of learning theory, as related to horses. They also could not connect these states to an important physiological factor, i.e., HR, when identifying these states. Results across all three studies suggest that most participant demographics (such as age, gender, or race) did not influence participants’ abilities to correctly identify or define fear, stress, reactivity, or learning theory principles. Similarly, results from Chapters 3 and 5 suggest that most participant psychographics, such as horse ownership, or level of involvement with horses, did not affect ability to correctly identify key horse behaviors related to fear, stress, and reactivity, or understanding of learning theory principles, or ability to correctly define these states and principles.

Overall, this dissertation identified the need for additional education when it comes to clearly defining specific states such as fear, stress, and reactivity for individuals across the horse industry. Additional psychographic factors, such as an individual’s specific role or niche in the industry, or an individuals’ overall view of horses, should be further explored.

The recent surge in shale gas production led to increases in alkane resources across the United States. One promising approach to convert the alkanes to higher value products is through dehydrogenation and oligomerization processes. This conversion to alkenes, if done in small modular units near the shale wells further aids in the ease of transportation and distribution of the final products. However, having highly selective processes is a major hindrance to improve the economic feasibility of the modular processes. Theoretical studies are of great significance to analyze detailed reaction mechanisms and identify the reaction pathways that leads to unselective product formations. These studies further enable the search for selective catalysts for any given chemistry based on descriptor analysis. Therefore, in this work Density Function Theory and Ab-initio Molecular Dynamics methods are used in conjunction with microkinetic modeling analyses to investigate the complex reaction networks involved in the shale gas conversion. Specifically, the work focuses on propane dehydrogenation (PDH) on alloy surfaces along with ethylene oligomerization on zeolite catalysts.

A major part of thesis is focused on finding selective and stable alloy catalysts for PDH chemistry. The initial work focused on understanding the selectivity, activity, and stability differences between 1:1 intermetallic alloys (PdIn) and the pure metal surfaces. This combined experimental and computational study shed light on the important role of step surfaces in understanding the activity trends across alloys. Through a detailed microkinetic analysis and simplified rate expression analysis, a novel selectivity descriptor in terms of effective barriers for propane C-H bond breaking and propyne C-C bond breaking was derived for propylene formation. This newly proposed descriptor showed greater fidelity for predicting the trends in experimental selectivities for a small set of Pd alloys than the previously proposed selectivity descriptors. Building upon these insights, a high throughput screening framework using graph-theory algorithms and python-based databasing has been developed to identify trends across a larger set of alloy combinations. The framework helped us identify a novel set of alloys that have not been explored until now for this chemistry. These alloy combinations were then experimentally tested and shown to have high selectivities for propylene formation and along with stabilities close to benchmark Pt-Sn catalysts. Detailed transition state analysis on terraces shows that the undesired C-C bond breaking pathways involves larger surface atom ensembles (4-5 atoms) while the C-H bond breaking involves smaller surface atom ensembles (1-2 atoms). This led to the conclusion that the site-isolation of active metal atoms is important to increase the selectivities for propylene formation. More importantly the combination of detailed mechanistic and screening studies using graph-theory methods shows a generalized framework towards finding new catalysts spaces for complex chemistries.

The work on ethylene oligomerization on the other hand is focused on understanding the role of mobility of active Ni species in the zeolites towards isomerization and deactivation reaction mechanisms. For this specific project, we have used state-of-the-art AIMD methods, including potential of mean force calculations, for accurate estimation of free energies for the reaction intermediates and transition states. The thermodynamic and kinetic analyses show that the reaction pathways involving mobile intermediates have the highest rates towards butene formations even under pressures lower than 1 bar. Further the isomerization step is found to be feasible on Ni-ethyl complex in agreement with experiments. Finally, the mobile complexes were shown to dimerize through alkyl bridged complexes and the generated complex has higher barriers for C-C bond formation than the isolated complex indicating that these are likely pathways for catalyst deactivation. This mechanistic understanding paves the way for fine-tuning the reaction conditions as well as ways in which the active site can be speciated inside the zeolitic frameworks to increase the selectivity towards 1-butene and reduce deactivation.

In the need of computational tools for epsilon-multiplicity, we provide a criterion for a module with a rank E inside a free module F to have rational epsilon-multiplicity in terms of the finite generation of the saturation Rees algebra of E. In this case, the multiplicity can be related to a Hilbert multiplicity of certain graded algebra. A particular example of this situation is provided: it is shown that the epsilon-multiplicity of monomial modules is Noetherian. Numerical evidence is provided that leads to a conjecture formula for the epsilon-multiplicity of certain monomial curves in the 3-affine space.