This thesis investigates the concept of the symbolic form of architecture. It first focuses on the philosophical foundations for this concept in the works of Ernst Cassirer, Immanuel Kant, Conrad Fiedler, and Theodor Adorno. Then, the development of the modern perception of form in architectural theoreticians, where "modern" architectural theory evolved from an analogical state into a symbolic state, is examined: Karl Bötticher's concept of a Junktur and his attempt to transcend the presumed dichotomy in architecture between ornamentation and form is discussed; Gottfried Semper's concept of style and Alois Riegl's concept of motif are presented as reactions against what they saw as the mechanistic reliance on structure as definitive of form in architecture; Louis Sullivan's ornamentation is discussed as an attempt to integrate structure and ornamentation into a morphological whole; Otto Wagner's attempt to purge architecture from analogical responses through a strictly constructional basis for ornamentation is presented; and Adolf Loos' dismissal of decorative ornamentation, since it is an impediment towards true aesthetic judgment, is examined. Finally, a critical review of the symbolist movement in architecture, art, and literature is presented as a movement diametric to the symbolic development in architecture, since it glorified the analogical, and frequently the mimetic. The origins for how the symbolist movement became a denial of clarity center on Emanuel Swedenborg's concept of symbols, and how it was misinterpreted by the symbolists. / Master of Architecture

The Fourier transform is one of the most useful tools in science and engineering and can be expanded to multi-dimensions and curvilinear coordinates. Multidimensional Fourier transforms are widely used in image processing, tomographic reconstructions and in fact any application that requires a multidimensional convolution. By examining a function in the frequency domain, additional information and insights may be obtained. In this thesis, the development of a symbolic computer algebra toolbox to compute two dimensional Fourier transforms in polar coordinates is discussed. Among the many operations implemented in this toolbox are different types of convolutions and procedures that allow for managing the toolbox effectively. The implementation of the two dimensional Fourier transform in polar coordinates within the toolbox is shown to be a combination of two significantly simpler transforms. The toolbox is also tested throughout the thesis to verify its capabilities.

The Fourier transform is one of the most useful tools in science and engineering and can be expanded to multi-dimensions and curvilinear coordinates. Multidimensional Fourier transforms are widely used in image processing, tomographic reconstructions and in fact any application that requires a multidimensional convolution. By examining a function in the frequency domain, additional information and insights may be obtained. In this thesis, the development of a symbolic computer algebra toolbox to compute two dimensional Fourier transforms in polar coordinates is discussed. Among the many operations implemented in this toolbox are different types of convolutions and procedures that allow for managing the toolbox effectively. The implementation of the two dimensional Fourier transform in polar coordinates within the toolbox is shown to be a combination of two significantly simpler transforms. The toolbox is also tested throughout the thesis to verify its capabilities.

The Fourier transform is one of the most useful tools in science and engineering and can be expanded to multi-dimensions and curvilinear coordinates. Multidimensional Fourier transforms are widely used in image processing, tomographic reconstructions and in fact any application that requires a multidimensional convolution. By examining a function in the frequency domain, additional information and insights may be obtained. In this thesis, the development of a symbolic computer algebra toolbox to compute two dimensional Fourier transforms in polar coordinates is discussed. Among the many operations implemented in this toolbox are different types of convolutions and procedures that allow for managing the toolbox effectively. The implementation of the two dimensional Fourier transform in polar coordinates within the toolbox is shown to be a combination of two significantly simpler transforms. The toolbox is also tested throughout the thesis to verify its capabilities.

The Fourier transform is one of the most useful tools in science and engineering and can be expanded to multi-dimensions and curvilinear coordinates. Multidimensional Fourier transforms are widely used in image processing, tomographic reconstructions and in fact any application that requires a multidimensional convolution. By examining a function in the frequency domain, additional information and insights may be obtained. In this thesis, the development of a symbolic computer algebra toolbox to compute two dimensional Fourier transforms in polar coordinates is discussed. Among the many operations implemented in this toolbox are different types of convolutions and procedures that allow for managing the toolbox effectively. The implementation of the two dimensional Fourier transform in polar coordinates within the toolbox is shown to be a combination of two significantly simpler transforms. The toolbox is also tested throughout the thesis to verify its capabilities.

No description available.

In the past decade, reinforcement learning (RL) has achieved breakthroughs across various domains, from surpassing human performance in strategy games to enhancing the training of large language models (LLMs) with human feedback. However, RL has yet to gain widespread adoption in mission-critical fields such as healthcare and autonomous vehicles. This is primarily attributed to the inherent lack of trust, explainability, and generalizability of neural networks in deep reinforcement learning (DRL) agents. While neural DRL agents leverage the power of neural networks to solve specific tasks robustly and efficiently, this often comes at the cost of explainability and generalizability. In contrast, pure symbolic agents maintain explainability and trust but often underperform in high-dimensional data. In this work, we developed a method to distill explainable and trustworthy agents using neuro-symbolic AI. Neuro-symbolic distillation combines the strengths of symbolic reasoning and neural networks, creating a hybrid framework that leverages the structured knowledge representation of symbolic systems alongside the learning capabilities of neural networks. The key steps of neuro-symbolic distillation involve training traditional DRL agents, followed by extracting, selecting, and distilling their learned policies into symbolic forms using symbolic regression and tree-based models. These symbolic representations are then employed instead of the neural agents to make interpretable decisions with comparable accuracy. The approach is validated through experiments on Lunar Lander and Pong, demonstrating that symbolic representations can effectively replace neural agents while enhancing transparency and trustworthiness. Our findings suggest that this approach mitigates the black-box nature of neural networks, providing a pathway toward more transparent and trustworthy AI systems. The implications of this research are significant for fields requiring both high performance and explainability, such as autonomous systems, healthcare, and financial modeling.

This thesis is a part of an ongoing research project at Link ̈oping University. The goal of the thesis work is to design and implement a prototype for a symbolic execution system that scales well with larger programs and is capable of performing symbolic execution on machine code. For this reason we have analyzed the current state of symbolic executors that are able to perform symbolic execution on machine code to see if we could use that implementation as base for our prototype. We wanted to know if any of the existing systems scaled well with large software. We found that neither of the existing systems worked well with the real life software in our evaluation. Furthermore, even if it would have been possible to fix one of the existing systems, the time required to figure out the faults in their implementation would most likely have been too great. For this reason we decided to create an implementation of our own from scratch. However, we did note that some approaches in the existing systems seemed to work better with large software. Specifically saving as little state as possible about the program seemed favorable. Armed with the knowledge gained from the analysis, we managed to implement a system that compared quite well with the existing systems. Our system was able to execute all the real-life programs used in our tests, but unfortunately had some issues with high memory usage for certain programs. In order to lessen the problem with high memory usage, we present and discuss several potential ways to mitigate this issue.

No description available.

It is known that the educational and social development of all children and young people are affected by the quality of communication within the family and by participation in social life and in activities outwith school. Although deaf children tend to under-achieve educationally and to experience marginalisation within mainstream groups, relatively little research has been located within family and out-of-school domains. This thesis interrogates data which were collected as part of a national questionnaire-based survey of parents of deaf children in Scotland. Quantitative and qualitative analyses of responses to closed and open questions illuminate parental perspectives on the extent to which deafness-related issues influenced: the quality of communication between their deaf children and family members; levels of friendships with both deaf and hearing peers; the amount and nature of their children’s participation in cultural and structured social activities; and parental facilitation of their adolescent deaf children’s independence. Although the majority of respondents indicated no, or minimal, disadvantages, a sizeable minority reported specific linguistic and social barriers which influenced key relationships and, in the case of activities, precipitated marginalising experiences. Whilst some clear patterns are revealed, such as a correlation with level of hearing loss and, in terms of parent/child quality of communication, with the hearing status of parents, there was a persistent level of unexplained diversity among those experiencing linguistic barriers. Limitations to the data restrict the generalisability of findings, although these have import in themselves. In addition, new knowledge is derived from the application of symbolic capital as a heuristic lens. Evidence of the diversity of family communication and ‘visitorship’ experiences are viewed in the context of linguistic access strategy choices emanating from the complexity of each deaf child’s habitus. Indications of differences between children of deaf and hearing parents, in terms of the balance of linguistic benefits and disadvantages, are considered in the context of social and cultural capital which is accumulated through access to alternative deaf and hearing networks. It is posited that, in order for deaf children to be enabled to realise their highly individual linguistic potential, and to optimise their accumulation of cultural and social capital, there is a need to address the imbalance within the linguistic spectrum of assessments and resources provided by specialist educational services. It is further argued that this should be within the context of a positive conceptualisation of deafness, and a holistic approach to assessment and service provision.