Analysis of physiological signals using machine learning methods

Technological advances in data collection enable scientists to suggest novel approaches, such as Machine Learning algorithms, to process and make sense of this information. However, during this process of collection, data loss and damage can occur for reasons such as faulty device sensors or miscommunication. In the context of time-series data such as multi-channel bio-signals, there is a possibility of losing a whole channel. In such cases, existing research suggests imputing the missing parts when the majority of data is available. One way of understanding and classifying complex signals is by using deep neural networks. The hyper-parameters of such models have been optimised using the process of back propagation. Over time, improvements have been suggested to enhance this algorithm. However, an essential drawback of the back propagation can be the sensitivity to noisy data. This thesis proposes two novel approaches to address the missing data challenge and back propagation drawbacks: First, suggesting a gradient-free model in order to discover the optimal hyper-parameters of a deep neural network. The complexity of deep networks and high-dimensional optimisation parameters presents challenges to find a suitable network structure and hyper-parameter configuration. This thesis proposes the use of a minimalist swarm optimiser, Dispersive Flies Optimisation(DFO), to enable the selected model to achieve better results in comparison with the traditional back propagation algorithm in certain conditions such as limited number of training samples. The DFO algorithm offers a robust search process for finding and determining the hyper-parameter configurations. Second, imputing whole missing bio-signals within a multi-channel sample. This approach comprises two experiments, namely the two-signal and five-signal imputation models. The first experiment attempts to implement and evaluate the performance of a model mapping bio-signals from A toB and vice versa. Conceptually, this is an extension to transfer learning using CycleGenerative Adversarial Networks (CycleGANs). The second experiment attempts to suggest a mechanism imputing missing signals in instances where multiple data channels are available for each sample. The capability to map to a target signal through multiple source domains achieves a more accurate estimate for the target domain. The results of the experiments performed indicate that in certain circumstances, such as having a limited number of samples, finding the optimal hyper-parameters of a neural network using gradient-free algorithms outperforms traditional gradient-based algorithms, leading to more accurate classification results. In addition, Generative Adversarial Networks could be used to impute the missing data channels in multi-channel bio-signals, and the generated data used for further analysis and classification tasks

Assessment of Biodegradable Magnesium Alloys for Enhanced Mechanical and Biocompatible Properties

Biomaterials have been used for more than a century in the human body to improve body functions and replace damaged tissues. Currently approved and commonly used metallic biomaterials such as, stainless steel, titanium, cobalt chromium and other alloys have been found to have adverse effects leading in some cases, to mechanical failure and rejection of the implant. The physical or chemical nature of the degradation products of some implants initiates an adverse foreign body reaction in the tissue. Some metallic implants remain as permanent fixtures, whereas others such as plates, screws and pins used to secure serious fractures are removed by a second surgical procedure after the tissue has healed sufficiently. However, repeat surgical procedures increase the cost of health care and the possibility of patient morbidity. This study focuses on the development of magnesium based biodegradable alloys/metal matrix composites (MMCs) for orthopedic and cardiovascular applications. The Mg alloys/MMCs possessed good mechanical properties and biocompatible properties. Nine different compositions of Mg alloys/MMCs were manufactured and surface treated. Their degradation behavior, ion leaching, wettability, morphology, cytotoxicity and mechanical properties were determined. Alloying with Zn, Ca, HA and Gd and surface treatment resulted in improved mechanical properties, corrosion resistance, reduced cytotoxicity, lower pH and hydrogen evolution. Anodization resulted in the formation of a distinct oxide layer (thickness 5-10 μm) as compared with that produced on mechanically polished samples (~20-50 nm) under ambient conditions. It is envisaged that the findings of this research will introduce a new class of Mg based biodegradable alloys/MMCs and the emergence of innovative cardiovascular and orthopedic implant devices

Temples for Tomorrow: The Journal Fire!! and African American Modernism During the Harlem Renaissance

This dissertation explores the one-issue Fire!! created, edited, and published by Wallace Thurman, Zora Neale Hurston, Langston Hughes, Gwendolyn Bennett, Aaron Douglas, and Richard Bruce Nugent in 1926 - during the height of the Harlem Renaissance. By giving a close examination of the short stories, plays, poems, editorials, and illustrations included in the journal, I examine the editorial and aesthetic choices of the younger generation of artists and their collective effort to broaden the perspectives and representations of African Americans in art and in culture. By publishing a journal outside of the constraints of the race leaders social science journals and outside of the white patrons expectations, these artists were generating texts that conformed to an understanding of culture - more to the proletariat, lower classes, and less to the social uplift mantra of the era. In this journal multiple representations are given from a narrative of an unapologetic and unregenerate prostitute to self-hatred and colorism among African American women, to even the first explicitly homoerotic narrative published by an African American author. The goal of this journal was to burn up the old conventions, escape the strict and narrow creative options of either the pure or the primitive, and create art that reflected the lives these artists new were viable possibilities within African American culture.The works of these authors contained in this journal represent the creative approaches that many of these authors continued even after the height of the movement, and most of these editor-authors even reflect back to the publication of Fire!! in other works produced after the climax of the Harlem Renaissance. For instance, both Thurman and Nugent reflect back to the summer of 1926 in their respective novels Infants in the Spring and Gentlemens Jigger. However, Hughes, Hurston, Douglas, and Bennett do a similar thing with later publications. Each chapter in this study discusses a different author and contributor. My method, a combination of biography and close reading, allows me to examine the journal in ways not often fully discussed in other scholarship. This approach reveals the historical currency and literary consistency of each author. Organized in conjunction with the order of the journal, the chapters of this study tell of the many and often contested versions of modern African American literary production