Homogeneous vector capsules and their application to sufficient and complete data

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonCapsules (vector-valued neurons) have recently become a more active area of research in neural networks. However, existing formulations have several drawbacks including the large number of trainable parameters that they require as well as the reliance on routing mechanisms between layers of capsules. The primary aim of this project is to demonstrate the benefits of a new formulation of capsules called Homogeneous Vector Capsules (HVCs) that overcome these drawbacks. Using HVCs, new state-of-the-art accuracies for the MNIST dataset are established for multiple individual models as well as multiple ensembles. This work additionally presents a dataset consisting of high-resolution images of 13 micro-PCBs captured in various rotations and perspectives relative to the camera, with each sample labeled for PCB type, rotation category, and perspective categories. Experiments performed and elucidated in this work examine classification accuracy of rotations and perspectives that were not trained on as well as the ability to artificially generate missing rotations and perspectives during training. The results of these experiments include showing that using HVCs is superior to using fully connected layers. This work also showed that certain training samples are more informative of class membership than others. These samples can be identified prior to training by analyzing their position in reduced dimensional space relative to the classes’ centroids in that space. And a definition and calculation both for class density and dataset completeness based on the distribution of data in the reduced dimensional space has been put forth. Experimentation using the dataset completeness calculation shows that those datasets that meet a certain completeness threshold can be trained on a subset of the total dataset, based on each class’s density, while improving upon or maintaining validation accuracy

Hormonal Signal Amplification Mediates Environmental Conditions during Development and Controls an Irreversible Commitment to Adulthood

Many animals can choose between different developmental fates to maximize fitness. Despite the complexity of environmental cues and life history, different developmental fates are executed in a robust fashion. The nematode Caenorhabditis elegans serves as a powerful model to examine this phenomenon because it can adopt one of two developmental fates (adulthood or diapause) depending on environmental conditions. The steroid hormone dafachronic acid (DA) directs development to adulthood by regulating the transcriptional activity of the nuclear hormone receptor DAF-12. The known role of DA suggests that it may be the molecular mediator of environmental condition effects on the developmental fate decision, although the mechanism is yet unknown. We used a combination of physiological and molecular biology techniques to demonstrate that commitment to reproductive adult development occurs when DA levels, produced in the neuroendocrine XXX cells, exceed a threshold. Furthermore, imaging and cell ablation experiments demonstrate that the XXX cells act as a source of DA, which, upon commitment to adult development, is amplified and propagated in the epidermis in a DAF-12 dependent manner. This positive feedback loop increases DA levels and drives adult programs in the gonad and epidermis, thus conferring the irreversibility of the decision. We show that the positive feedback loop canalizes development by ensuring that sufficient amounts of DA are dispersed throughout the body and serves as a robust fate-locking mechanism to enforce an organism-wide binary decision, despite noisy and complex environmental cues. These mechanisms are not only relevant to C. elegans but may be extended to other hormonal-based decision-making mechanisms in insects and mammals

Firefly: The Case for a Holistic Understanding of the Global Structure and Dynamics of the Sun and the Heliosphere

This white paper is on the HMCS Firefly mission concept study. Firefly focuses on the global structure and dynamics of the Sun's interior, the generation of solar magnetic fields, the deciphering of the solar cycle, the conditions leading to the explosive activity, and the structure and dynamics of the corona as it drives the heliosphere