Methods for Data-centric Small Satellite Anomaly Detection and Fault Prediction

Autonomy can increase reaction speed, flexibility, and accuracy of satellite operations, especially in uncertain environments caused by delayed communication and/or adversarial conditions. An increased focus on small satellites makes the development of satellite autonomy even more salient, given fewer operators per satellite. Anomaly detection automates satellite health monitoring, ensuring it functions as designed. This is typically achieved using various forms of recurrent neural networks (RNN). While many of these model-based works show promise, a majority use simulated data or assume lossless communication. In contrast, raw satellite telemetry often has dropped packets, sampling frequency mismatches, noise from electrical systems and radiation, and a lack of clear labels for training. This work demonstrates how data-centric artificial intelligence (AI) can be utilized in satellite autonomy, using telemetry from the Very Low Frequency Propagation Mapper (VPM) small satellite flown by the Air Force Research Lab Space Vehicle Directorate in 2020. We introduce simple, but effective, tools for extracting fault labels from system parameters, resampling outliers to a common, uniform timeline, and evaluating outlier fault predictability. Results find that detected outliers were able to predict faults 1-10 minutes before they occurred with high accuracy

Welsh svarabhakti as stem allomorphy

In this paper I propose an analysis of the repairs of sonority sequencing violations in South Welsh in terms of a non-phonological process of stem allomorphy. As documented by Hannahs (2009), modern Welsh uses a variety of strategies to avoid word-final rising-sonority consonant clusters, depending in part on the number of syllables in the word. In particular, while some lexical items epenthesise a copy of the rightmost underlying vowel in the word, others delete one of the consonants in a cluster. In this paper, I argue that at least the deletion is not a live phonological process, and suggest viewing it as an instance of stem allomorphy in a stratal OT framework (Bermúdez-Otero 2013). This accounts for the lexical specificity of the pattern,which has been understated in the literature, and for the fact that cyclic misapplication of deletion and diachronic change are constrained by part-of-speech boundaries

Norepinephrine-mediated emotional arousal facilitates subsequent pattern separation

Pattern separation, the process by which similar experiences can be stored as distinct memories, has been ascribed to the dentate gyrus (DG) of the hippocampus. The DG is the target of noradrenergic modulation directly and indirectly via the basolateral amygdala. We tested the hypothesis that noradrenergic activation (tested using salivary alpha-amylase) potentiates DG function, enhancing pattern separation, by showing participants fearful stimuli in a pre-training task and then testing their capacity for pattern separation in a later test. Consistent with our hypothesis, we found that increased levels of salivary alphaamylase were positively correlated with enhanced pattern separation performance even after accounting for general enhancements in recognition