The Best Way to Locate a Purpose in Sport: In Defence of a Distinction for Aesthetics?

The paper highlights the centrality of some concepts from philosophy of sport for philosophical aesthetics. Once Best (BJA, 1974) conclusively answered negatively the fundamental question, ‘Can any sport form be an artform’, what further issues remained at the intersection of these parts of philosophy? Recent work revitalizing this interface, especially Mumford’s Watching Sport (2012), contested Best’s fundamental distinction between purposive and aesthetic sports, and insisted that purist viewers are taking an aesthetic interest in sporting events. Here, we defend Best’s conception against considerations Mumford hoped would bring the aesthetics of art and sport closer together, thereby elaborating the aesthetics of sport. But, against Mumford’s resolutely psychological conception of an aim, we follow Best to defend the centrality, for purposive sports, of the means/ends contrast remains, even when taking an aesthetic interest in such sports. We conclude with general speculations about the potential future of the discussions originated here

Assessing movements of three buoy line types using DSTmilli Loggers: Implications for entanglements of bottlenose dolphins in the crab pot fishery

A study was conducted in October 2006 in the Charleston, South Carolina area to test the movements of three different buoy line types to determine which produced a preferred profile that could reduce the risk of dolphin entanglement. Tests on diamond-braided nylon commonly used in the crab pot fishery were compared with stiffened line of Esterpro and calf types in both shallow and deep water environments using DSTmilli data loggers. Loggers were placed at intervals along the lines to record depth, and thus movements, over a 24 hour period. Three observers viewed video animations and charts created for each of the six trial days from the collected logger data and provided their opinions on the most desirable line type that fit set criteria. A quantitative analysis (ANCOVA) of the data was conducted taking into consideration daily tidal fluctuations and logger movements. Loggers tracking the tides had an r2 value approaching 1.00 and produced little movement other than with the tides. Conversely, r2 values approaching 0.00 were less affected by tidal movement and influenced by currents that cause more erratic movement. Results from this study showed that stiffened line, in particular the medium lay Esterpro type, produced the more desirable profiles that could reduce risk of dolphin entanglement. Combining the observer’s results with the ANCOVA results, Esterpro was chosen nearly 60% of the time as opposed to the nylon line which was only chosen 10% of the time. ANCOVA results showed that the stiffened lines performed better in both the shallow and deep water environments, while the nylon line only performed better during one trial in a deep water set, most probably due to the increased current velocities experienced that day. (58pp.)(PDF contains 68 pages

A GIS analysis of coastal development and trends in bottlenose dolphin strandings in Charleston, SC: implications for coastal marine spatial planning

Bottlenose dolphins (Tursiops truncatus) inhabit estuarine waters near Charleston, South Carolina (SC) feeding, nursing and socializing. While in these waters, dolphins are exposed to multiple direct and indirect threats such as anthropogenic impacts (egs. harassment with boat traffic and entanglements in fishing gear) and environmental degradation. Bottlenose dolphins are protected under the Marine Mammal Protection Act of 1972. Over the years, the percentage of strandings in the estuaries has increased in South Carolina and, specifically, recent stranding data shows an increase in strandings occurring in Charleston, SC near areas of residential development. During the same timeframe, Charleston experienced a shift in human population towards the coastline. These two trends, rise in estuarine dolphin strandings and shift in human population, have raised questions on whether the increase in strandings is a result of more detectable strandings being reported, or a true increase in stranding events. Using GIS, the trends in strandings were compared to residential growth, boat permits, fishing permits, and dock permits in Charleston County from 1994-2009. A simple linear regression analysis was performed to determine if there were any significant relationships between strandings, boat permits, commercial fishing permits, and crabpot permits. The results of this analysis show the stranding trend moves toward Charleston Harbor and adjacent rivers over time which suggests the increase in strandings is related to the strandings becoming more detectable. The statistical analysis shows that the factors that cause human interaction strandings such as boats, commercial fishing, and crabpot line entanglements are not significantly related to strandings further supporting the hypothesis that the increase in strandings are due to increased observations on the water as human coastal population increases and are not a natural phenomenon. This study has local and potentially regional marine spatial planning implications to protect coastal natural resources, such as the bottlenose dolphin, while balancing coastal development

Stacked Convolutional and Recurrent Neural Networks for Bird Audio Detection

This paper studies the detection of bird calls in audio segments using stacked convolutional and recurrent neural networks. Data augmentation by blocks mixing and domain adaptation using a novel method of test mixing are proposed and evaluated in regard to making the method robust to unseen data. The contributions of two kinds of acoustic features (dominant frequency and log mel-band energy) and their combinations are studied in the context of bird audio detection. Our best achieved AUC measure on five cross-validations of the development data is 95.5% and 88.1% on the unseen evaluation data.Comment: Accepted for European Signal Processing Conference 201

Relative Comparison Kernel Learning with Auxiliary Kernels

In this work we consider the problem of learning a positive semidefinite kernel matrix from relative comparisons of the form: "object A is more similar to object B than it is to C", where comparisons are given by humans. Existing solutions to this problem assume many comparisons are provided to learn a high quality kernel. However, this can be considered unrealistic for many real-world tasks since relative assessments require human input, which is often costly or difficult to obtain. Because of this, only a limited number of these comparisons may be provided. In this work, we explore methods for aiding the process of learning a kernel with the help of auxiliary kernels built from more easily extractable information regarding the relationships among objects. We propose a new kernel learning approach in which the target kernel is defined as a conic combination of auxiliary kernels and a kernel whose elements are learned directly. We formulate a convex optimization to solve for this target kernel that adds only minor overhead to methods that use no auxiliary information. Empirical results show that in the presence of few training relative comparisons, our method can learn kernels that generalize to more out-of-sample comparisons than methods that do not utilize auxiliary information, as well as similar methods that learn metrics over objects