Digital recording of performing arts: formats and conversion

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Recovery of critically endangered Nassau grouper (Epinephelus striatus) in the Cayman Islands following targeted conservation actions.

Many large-bodied marine fishes that form spawning aggregations, such as the Nassau grouper (Epinephelus striatus), have suffered regional overfishing due to exploitation during spawning. In response, marine resource managers in many locations have established marine protected areas or seasonal closures to recover these overfished stocks. The challenge in assessing management effectiveness lies largely in the development of accurate estimates to track stock size through time. For the past 15 y, the Cayman Islands government has taken a series of management actions aimed at recovering collapsed stocks of Nassau grouper. Importantly, the government also partnered with academic and nonprofit organizations to establish a research and monitoring program (Grouper Moon) aimed at documenting the impacts of conservation action. Here, we develop an integrated population model of 2 Cayman Nassau grouper stocks based on both diver-collected mark-resight observations and video censuses. Using both data types across multiple years, we fit parameters for a state-space model for population growth. We show that over the last 15 y the Nassau grouper population on Little Cayman has more than tripled in response to conservation efforts. Census data from Cayman Brac, while more sparse, show a similar pattern. These findings demonstrate that spatial and seasonal closures aimed at rebuilding aggregation-based fisheries can foster conservation success

Sample-level CNN Architectures for Music Auto-tagging Using Raw Waveforms

Recent work has shown that the end-to-end approach using convolutional neural network (CNN) is effective in various types of machine learning tasks. For audio signals, the approach takes raw waveforms as input using an 1-D convolution layer. In this paper, we improve the 1-D CNN architecture for music auto-tagging by adopting building blocks from state-of-the-art image classification models, ResNets and SENets, and adding multi-level feature aggregation to it. We compare different combinations of the modules in building CNN architectures. The results show that they achieve significant improvements over previous state-of-the-art models on the MagnaTagATune dataset and comparable results on Million Song Dataset. Furthermore, we analyze and visualize our model to show how the 1-D CNN operates.Comment: Accepted for publication at ICASSP 201

A video method for quantifying size distribution, density, and three-dimensional spatial structure of reef fish spawning aggregations

There is a clear need to develop fisheries independent methods to quantify individual sizes, density, and three dimensional characteristics of reef fish spawning aggregations for use in population assessments and to provide critical baseline data on reproductive life history of exploited populations. We designed, constructed, calibrated, and applied an underwater stereo-video system to estimate individual sizes and three dimensional (3D) positions of Nassau grouper (Epinephelus striatus) at a spawning aggregation site located on a reef promontory on the western edge of Little Cayman Island, Cayman Islands, BWI, on 23 January 2003. The system consists of two free-running camcorders mounted on a meter-long bar and supported by a SCUBA diver. Paired video “stills” were captured, and nose and tail of individual fish observed in the field of view of both cameras were digitized using image analysis software. Conversion of these two dimensional screen coordinates to 3D coordinates was achieved through a matrix inversion algorithm and calibration data. Our estimate of mean total length (58.5 cm, n = 29) was in close agreement with estimated lengths from a hydroacoustic survey and from direct measures of fish size using visual census techniques. We discovered a possible bias in length measures using the video method, most likely arising from some fish orientations that were not perpendicular with respect to the optical axis of the camera system. We observed 40 individuals occupying a volume of 33.3 m3, resulting in a concentration of 1.2 individuals m–3 with a mean (SD) nearest neighbor distance of 70.0 (29.7) cm. We promote the use of roving diver stereo-videography as a method to assess the size distribution, density, and 3D spatial structure of fish spawning aggregations

Social Media for Cities, Counties and Communities

Social media (i.e., Twitter, Facebook, Flickr, YouTube) and other tools and services with user- generated content have made a staggering amount of information (and misinformation) available. Some government officials seek to leverage these resources to improve services and communication with citizens, especially during crises and emergencies. Yet, the sheer volume of social data streams generates substantial noise that must be filtered. Potential exists to rapidly identify issues of concern for emergency management by detecting meaningful patterns or trends in the stream of messages and information flow. Similarly, monitoring these patterns and themes over time could provide officials with insights into the perceptions and mood of the community that cannot be collected through traditional methods (e.g., phone or mail surveys) due to their substantive costs, especially in light of reduced and shrinking budgets of governments at all levels. We conducted a pilot study in 2010 with government officials in Arlington, Virginia (and to a lesser extent representatives of groups from Alexandria and Fairfax, Virginia) with a view to contributing to a general understanding of the use of social media by government officials as well as community organizations, businesses and the public. We were especially interested in gaining greater insight into social media use in crisis situations (whether severe or fairly routine crises, such as traffic or weather disruptions)