MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL.

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I n this paper we present results of the application of a Si"1taneous Localisation nnfl Map building ( S L A M ) algorithm to estimate the motion of a submersible vehacle. Scans obtained from an on-board sonar are processed to extract stable point features environment. These point features are then used d up a map of the environment while simultaneously providing estimates of the vehicle location. Results are shown from deployment in a swimming pool at the University of Sydney as well as from field trials in a natural environment along Sydney's coast. This work represents the first instance of a deployable underwater implementation of the SLAM algorithm. 0-7803-5886-4/00/$1 O.OO@ 2000 IEEE

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Abstract-This paper presents an automated approach to correcting for colour inconsistency in underwater images collected from multiple perspectives during the construction of 3D structure-from-motion models. When capturing images underwater, the water column imposes several effects on images that are negligible in air such as colour-dependant attenuation and lighting patterns. These effects cause problems for human interpretation of images and also confound computer-based techniques for clustering and classification. Our approach exploits the 3D structure of the scene generated using structure-from-motion and photogrammetry techniques accounting for distance-based attenuation, vignetting and lighting pattern, and improves the consistency of photo-textured 3D models. Results are presented using imagery collected in two different underwater environments using an Autonomous Underwater Vehicle (AUV).

Background Background: Computer vision can measure movement from video without the time and access limitations of hospital accelerometry/electromyography or the requirement to hold or strap a smartphone accelerometer. Objective Objective: To compare computer vision measurement of hand tremor frequency from smartphone video with a gold standard measure accelerometer. Methods Methods: A total of 37 smartphone videos of hands, at rest and in posture, were recorded from 15 participants with tremor diagnoses (9 Parkinson's disease, 5 essential tremor, 1 functional tremor). Video pixel movement was measured using the computing technique of optical flow, with contemporaneous accelerometer recording. Fast Fourier transform and Bland-Altman analysis were applied. Tremor amplitude was scored by 2 clinicians. Results Results: Bland-Altman analysis of dominant tremor frequency from smartphone video compared with accelerometer showed excellent agreement: 95% limits of agreement −0.38 Hz to +0.35 Hz. In 36 of 37 videos (97%), there was <0.5 Hz difference between computer vision and accelerometer measurement. There was no significant correlation between the level of agreement and tremor amplitude. Conclusion Conclusion: The study suggests a potential new, contactless point-and-press measure of tremor frequency within standard clinical settings, research studies, or telemedicine.

This paper describes a two week deployment of the Autonomous Underwater Vehicle (AUV) Sirius on the Tasman Peninsula in SE Tasmania and in the Huon Marine Protected Area (MPA) to the South West of Hobart. The objective of the deployments described in this work were to document biological assemblages associated with rocky reef systems in shelf waters beyond normal diving depths. At each location, multiple reefs were surveyed at a range of depths from approximately 50 m to 100 m depth. We illustrate how the AUV based imaging complements benthic habitat assessments to be made based on the ship-borne swath bathymetry. Over the course of the 10 days of operation, 19 dives were undertaken with the AUV covering in excess of 70 linear kilometers of survey and returning nearly 160,000 geo-referenced high resolution stereo image pairs. These are now being analysed to describe the distribution of benthic habitats in more detail.

The significance of submerged fossil coral reefs as important archives of abrupt global sea level rise and climate change has been confirmed by investigations in the Caribbean [Fairbanks, 1989] and the Indo‐ Pacific (see Montaggioni [2005] for a summary) and by recent Integrated Ocean Drilling Program (IODP) activities in Tahiti [Camoin et al., 2007]. Similar submerged (40–130 meters) reef structures are preserved along the margin of the Great Barrier Reef (GBR), but they have not yet been systematically studied. The submerged reefs have the potential to provide critical new information about the nature of past global sea level and climate variability and about the response of the GBR to these past and perhaps future environmental changes [Beaman et al., 2008]. Equally important for GBR Marine Park managers is information about the role of the reefs as habitats and substrates for modern biological communities.