Atlantic Universities Geoscience Conference 2015: 65th Annual Conference, October 22-24, 2015

White, C Michael

doi:10.4138/atlgeol.2015.015

Cited by 2 publications

(3 citation statements)

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“…Environmental data representing surficial properties include fine-scale bathymetry, backscatter intensity at 400 kHz [21], and sediment roughness power spectra [22]. Subbottom measurements include chirp surveys and cores [23], sediment sound speed and attenuation [24], and cone penetrometer measurements [34]. The single path backscatter [19] measures the combined effects of both surficial and subbottom properties of the seabed.…”

Section: A Measurements Of Bottom Properties For Understanding Category I Rl Fluctuationsmentioning

confidence: 99%

“…Although uncalibrated in absolute level, the variation in volume backscatter intensity is about 6 dB from the sand ridges to the swale valleys. In addition, subbottom chirp profiling and free-falling cone penetrometer data, collected by Defense Research and Development Canada (DRDC), Ottawa, ON, Canada, are also available along the main reverberation track [34].…”

Section: A Measurements Of Bottom Properties For Understanding Category I Rl Fluctuationsmentioning

confidence: 99%

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Overview of Midfrequency Reverberation Data Acquired During the Target and Reverberation Experiment 2013

Yang

Tang

Hefner

et al. 2018

IEEE J. Oceanic Eng.

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The Target and Reverberation EXperiment 2013 (TREX13) included a comprehensive reverberation field project in the frequency band of 2-10 kHz, and was carried out off the coast of Panama City, FL, USA, from April 21 to May 17, 2013. A spatially fixed transmit and receive acoustic system was used to measure reverberation over time under diverse environmental conditions, allowing study of reverberation level (RL) dependence on bottom composition, sea surface conditions, and water column properties.Extensive in situ measurements, including a multibeam bathymetric survey, chirp sonar subbottom profiling, gravity/diver cores, sediment sound speed and attenuation, interface roughness, windgenerated sea surface waves, and water column properties, were made to support studies of environmental effects on RL. Beamformed RL data are categorized to facilitate studies emphasizing physical mechanisms of 1) bottom reverberation; 2) sea surface impact; and 3) biological impact. This paper is an overview of RL over the entire sea trial, intending to summarize major observations and provide both a road map and suitable data sets for follow-up efforts on model/data comparisons. Emphasis is placed on the dependence of RL on local geoacoustic properties and sea surface conditions.

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Section: A Measurements Of Bottom Properties For Understanding Category I Rl Fluctuationsmentioning

confidence: 99%

Section: A Measurements Of Bottom Properties For Understanding Category I Rl Fluctuationsmentioning

confidence: 99%

Overview of Midfrequency Reverberation Data Acquired During the Target and Reverberation Experiment 2013

Yang

Tang

Hefner

et al. 2018

IEEE J. Oceanic Eng.

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“…Nevertheless, the interest of dark side research in algorithmic management remains in its infancy relative to the wide coverage of this phenomenon in the popular press (e.g. Hill, 2015; O’Connor, 2016; Porter, 2015; Scheiber, 2017; White, 2015).…”

Section: The Dark Side Of Digital Controlmentioning

confidence: 99%

Who is pulling the strings in the platform economy? Accounting for the dark and unexpected sides of algorithmic control

Pignot

2021

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This paper aims to address the dark side perspective on digital control and surveillance by emphasizing the affective grip of ideological control, namely the process that silently ensures the subjugation of digital labour, and which keeps the ‘unexpectedness’ of algorithmic practices at bay: that is, the propensity of users to contest digital prescriptions. In particular, the theoretical contribution of this paper is to combine Labour Process with psychoanalytically-informed, post-structuralist theory, in order to connect to, and further our understanding of, how and why digital workers assent to, or oppose, the interpellations of algorithmic ideology at work. To illustrate the operation of affective control in the Platform Economy, the emblematic example of ride-hailing platforms, such as Uber, and their algorithmic management, is revisited. Thus, the empirical section describes the way drivers are glued to the algorithm (e.g. for one more fare, or for the next surge pricing) in a way that prevents them, although not always, from considering genuine resistance to management. Finally, the paper discusses the central place of ideological fantasy and cynical enjoyment in the Platform Economy, as well as the ethical implications of the study.

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Atlantic Universities Geoscience Conference 2015: 65th Annual Conference, October 22-24, 2015

Cited by 2 publications

References 0 publications

Overview of Midfrequency Reverberation Data Acquired During the Target and Reverberation Experiment 2013

Overview of Midfrequency Reverberation Data Acquired During the Target and Reverberation Experiment 2013

Who is pulling the strings in the platform economy? Accounting for the dark and unexpected sides of algorithmic control

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