scholarly journals DARHT Multi-intelligence Seismic and Acoustic Data Analysis

2016 ◽  
Author(s):  
Garrison Nicole Stevens ◽  
Kendra Lu Van Buren ◽  
Francois M. Hemez
Keyword(s):  
Data Analysis ◽  
Acoustic Data

Novel software for deep-learning based acoustic data analysis

2021 ◽  
Vol 150 (4) ◽  
pp. A164-A164
Author(s):  
Fabio Frazao ◽  
Steven Bergner ◽  
Mike Dowd ◽  
Ruth Joy ◽  
Oliver S. Kirsebom ◽  
...  
Keyword(s):  
Deep Learning ◽  
Data Analysis ◽  
Acoustic Data

Acoustic data analysis for underwater archaeological sites detection and mapping by means of autonomous underwater vehicles

2015 ◽  
Author(s):  
Benedetto Allotta ◽  
Riccardo Costanzi ◽  
Alessandro Ridolfi ◽  
Maria Antonietta Pascali ◽  
Marco Reggiannini ◽  
...  
Keyword(s):  
Data Analysis ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Archaeological Sites ◽  
Acoustic Data

The Acoustical Presentation of Technical Information

1992 ◽  
Vol 22 (1) ◽  
pp. 39-52 ◽  
Author(s):  
George A. Barnett
Keyword(s):  
Data Analysis ◽  
Television Viewing ◽  
Technical Information ◽  
Acoustic Data ◽  
Acoustic Information ◽  
Potential Benefits ◽  
Scientists And Engineers

This article advocates listening to technical information in much the same way as scientists and engineers currently look at graphics in order to gain an understanding of the relations among variables. It specifies a number of potential benefits of this approach. 1) The ability to hear data may contribute to the greater understanding of the relationships that lie within data. This may lead to alternative theoretical interpretations and explanations. 2) Listening to the data may produce a greater long-term understanding. 3) It will facilitate the understanding of technical information by individuals whose dominant learning modality is acoustic rather than visual. 4) Acoustic data analysis is ideally suited for the analysis of processual data. The article provides a demonstration of the presentation of acoustic information with data on the frequency of television viewing, 1950–1988.

Preliminary acoustic data analysis from Littoral Acoustic Demonstration Center 2007 (LADC07) passive acoustic experiment

2007 ◽  
Vol 122 (5) ◽  
pp. 3002
Author(s):  
Natalia A. Sidorovskaia ◽  
George E. Ioup ◽  
Juliette W. Ioup ◽  
Arslan M. Tashmukhambetov ◽  
Grayson H. Rayborn ◽  
...  
Keyword(s):  
Data Analysis ◽  
Acoustic Data ◽  
Passive Acoustic

scholarly journals Stridulations of Melolontha spp. larvae open up new possibilities for species-specific pest monitoring in soils

2019 ◽  
Author(s):  
Carolyn-Monika Görres ◽  
David Chesmore
Keyword(s):  
Data Analysis ◽  
Analysis Method ◽  
White Grub ◽  
Acoustic Data ◽  
Non Invasive ◽  
Pest Monitoring ◽  
Melolontha Melolontha ◽  
Data Analysis Method ◽  
Species Specific ◽  
First Time

AbstractRoot-feeding Scarabaeidae larvae can pose a serious threat to agricultural and forest ecosystems, but many details of larval ecology are still unknown. We developed an acoustic data analysis method for gaining new insights into larval ecology. In a laboratory study, third instar larvae of Melolontha melolontha (n=38) and M. hippocastani (n=15) kept in soil-filled containers were acoustically monitored for 5 min each, resulting in the first known stridulation recordings for each species. Subsequent continuous monitoring of three M. hippocastani larvae over several hours showed that a single larva could stridulate more than 70 times per hour, and stridulation rates increased drastically with increasing larval abundance. The new fractal dimension-based data analysis method automatically detected audio sections with stridulations and provided a semi-quantitative estimate of stridulation activity. It is the first data analysis method specifically targeting Scarabaeidae larvae stridulations in soils, enabling for the first time non-invasive species-specific pest monitoring.Key messageRoot-feeding scarab beetle larvae, known as white grubs, can be serious agricultural and forest pests.White grub infestation monitoring is difficult due to their cryptic lifestyle, but detailed monitoring data is essential for effective pest control.We present the first acoustic data analysis routine targeting stridulations, using Melolontha melolontha and M. hippocastani as model organisms.This new method provides for the first time the basis for the development of tools for non-invasive, species-specific, and rapid white grub monitoring in soils.

scholarly journals Experimental Acoustic Data Analysis for Fish Detection using an Active Ultrasound System

2019 ◽  
Author(s):  
Gabriel Vasile ◽  
Alexandre Girard ◽  
Guy d'Urso ◽  
Eric de Oliveira ◽  
Franck Hieramente ◽  
...  
Keyword(s):  
Data Analysis ◽  
Acoustic Data ◽  
Fish Detection ◽  
Ultrasound System

Scaling Acoustic Data Analysis through Collaboration and Automation

2010 ◽  
Author(s):  
Jason Wimmer ◽  
Michael Towsey ◽  
Birgit Planitz ◽  
Paul Roe ◽  
Ian Williamson
Keyword(s):  
Data Analysis ◽  
Acoustic Data
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