The Cliché as Critique and Complaint

The cliché is a peripheral term in our critical vocabulary. Reviewers, critics, and editors speak of clichés, but dictionaries of critical terms rarely provide entries on the word. This paper asks whether pointing out clichés represents a form of critique or whether it is just quibbling, and how we draw the line between scrutiny and pedantry.

Rhetoric, Roman Values, and the Fall of the Republic in Cicero's Reception of Plato

This dissertation seeks to identify what makes Cicero’s approach to politics unique. The author's methodology is to turn to Cicero’s unique interpretation of Plato as the crux of what made his thinking neither Stoic nor Aristotelian nor even Platonic (at least, in the usual sense of the word) but Ciceronian. As the author demonstrates in his reading of Cicero’s correspondences and dialogues during the downward spiral of a decade that ended in the fall of the Republic (that is, from Cicero’s return from exile in 57 BC to Caesar’s crossing of the Rubicon in 49 BC), it is through Cicero's reading of Plato that the former develops his characteristically Ciceronian approach to politics—that is, his appreciation for the tension between the political ideal on the one hand and the reality of human nature on the other as well as the need for rhetoric to fuse a practicable compromise between the two. This triangulation of political ideal, human nature, and rhetoric is developed by Cicero through his dialogues "de Oratore," "de Re publica," and "de Legibus."

Detection and Classification of Whale Acoustic Signals

This dissertation focuses on two vital challenges in relation to whale acoustic signals: detection and classification.

In detection, we evaluated the influence of the uncertain ocean environment on the spectrogram-based detector, and derived the likelihood ratio of the proposed Short Time Fourier Transform detector. Experimental results showed that the proposed detector outperforms detectors based on the spectrogram. The proposed detector is more sensitive to environmental changes because it includes phase information.

In classification, our focus is on finding a robust and sparse representation of whale vocalizations. Because whale vocalizations can be modeled as polynomial phase signals, we can represent the whale calls by their polynomial phase coefficients. In this dissertation, we used the Weyl transform to capture chirp rate information, and used a two dimensional feature set to represent whale vocalizations globally. Experimental results showed that our Weyl feature set outperforms chirplet coefficients and MFCC (Mel Frequency Cepstral Coefficients) when applied to our collected data.

Since whale vocalizations can be represented by polynomial phase coefficients, it is plausible that the signals lie on a manifold parameterized by these coefficients. We also studied the intrinsic structure of high dimensional whale data by exploiting its geometry. Experimental results showed that nonlinear mappings such as Laplacian Eigenmap and ISOMAP outperform linear mappings such as PCA and MDS, suggesting that the whale acoustic data is nonlinear.

We also explored deep learning algorithms on whale acoustic data. We built each layer as convolutions with either a PCA filter bank (PCANet) or a DCT filter bank (DCTNet). With the DCT filter bank, each layer has different a time-frequency scale representation, and from this, one can extract different physical information. Experimental results showed that our PCANet and DCTNet achieve high classification rate on the whale vocalization data set. The word error rate of the DCTNet feature is similar to the MFSC in speech recognition tasks, suggesting that the convolutional network is able to reveal acoustic content of speech signals.