Characterization of the envelope protecting an acoustic detection system

1987 ◽  
Vol 82 (S1) ◽  
pp. S39-S39
Author(s):  
D. Vaucher De La Croix ◽  
M. Lathuilière ◽  
L. Périer
Keyword(s):  
Detection System ◽  
Acoustic Detection

Mass Spectrometry and Integrated Virus Detection System Characterization of MS2 Bacteriophage

2005 ◽  
Author(s):  
Rabih E. Jabbour ◽  
Deborah Kuzmanovic ◽  
Patrick E. McCubbin ◽  
Ilya Elashvili ◽  
Charles H. Wick
Keyword(s):  
Mass Spectrometry ◽  
Detection System ◽  
Virus Detection ◽  
Ms2 Bacteriophage ◽  
System Characterization

Integrated Virus Detection System Characterization of MS2 and TBSV After Pulsed Lamp Exposure

2010 ◽  
Author(s):  
Charles H. Wick ◽  
Stephen Wengraitis ◽  
Patrick E. McCubbin
Keyword(s):  
Detection System ◽  
Virus Detection ◽  
System Characterization

scholarly journals Development and Evaluation of Real-time Acoustic Detection System of Harmful Red-tide Using Ultrasonic Sound

2013 ◽  
Vol 35 (1) ◽  
pp. 15-26 ◽  
Author(s):  
Donhyug Kang ◽  
Seonho Lim ◽  
Hyungbeen Lee ◽  
Jaewon Doh ◽  
Youn-Ho Lee ◽  
...  
Keyword(s):  
Real Time ◽  
Detection System ◽  
Red Tide ◽  
Acoustic Detection ◽  
Ultrasonic Sound

Acoustic Detection of Distressed Freight Car Roller Bearings

2007 ◽  
Author(s):  
Gerald B. Anderson
Keyword(s):  
High Risk ◽  
North America ◽  
Detection System ◽  
Roller Bearing ◽  
Acoustic Emissions ◽  
Basic Research ◽  
Acoustic Detection ◽  
Internal Damage ◽  
Increased Risk ◽  
Freight Car

Trackside Acoustic Detection System (TADS®) development spearheaded implementation of an acoustic freight car roller bearing detector whose purpose is to prevent in-service bearing failures (burned off journals and hot bearing detector train stops). The means of accomplishing this goal is by providing the user with a warning of internal bearing defects or degradation with component involvement and severity information. The Transportation Technology Center, Inc. (TTCI) began the TADS® development process in 1994 with basic research into bearing defect acoustic emissions. Subsequently, TTCI conducted prototype testing on a North American railroad, constructed and installed of several international beta test systems, and finally has sold production systems in North America and internationally. There are currently about 40 TADS® sites in operation world-wide with 2.0 or more systems scheduled for installation in 2007. The original mission for TADS® in North America was an early warning of bearing degradation to allow for scheduled maintenance, but after initial evaluation, this mission enlarged to include notification of potentially high risk bearings. The high risk bearing is defined as one with fairly large areas of internal damage and at an increased risk of overheating or failing in service. The high risk bearing has a different acoustic signature, dissimilar to that of smaller defects. This paper will outline the change in mission for this detector and describe the development of an improved capability for detecting these high risk bearings.

scholarly journals Production and Characterization of Two Monoclonal Antibodies Specific for Plasmopara halstedii

2000 ◽  
Vol 66 (8) ◽  
pp. 3277-3282 ◽  
Author(s):  
S. Bouterige ◽  
R. Robert ◽  
J. P. Bouchara ◽  
A. Marot-Leblond ◽  
V. Molinero ◽  
...  
Keyword(s):  
Monoclonal Antibodies ◽  
Detection System ◽  
Sandwich Elisa ◽  
Plasmopara Viticola ◽  
Enzyme Linked Immunosorbent Assay ◽  
Plasmopara Halstedii ◽  
Race 1 ◽  
Molecular Masses ◽  
Fungal Antigens

ABSTRACT Sunflower downy mildew, caused by the fungus Plasmopara halstedii, is a potentially devastating disease. We produced two monoclonal antibodies (MAbs) (12C9 and 18E2) by immunizing mice with a partially purified extract of P. halstedii race 1. Both MAbs detected in enzyme-linked immunosorbent assay (ELISA) all races ofP. halstedii present in France. No cross-reactions were observed with Plasmopara viticola or with other fungi commonly associated with sunflowers. Both MAbs recognized the same three fungal antigens with molecular masses of 68, 140, and 192 kDa. However, the epitopes on the fungal antigens were distinct and repetitive. Seed homogenates from infected plants were incubated in wells coated with MAb 18E2. This resulted in the trapping of P. halstedii antigens that were identified with biotinylated MAb 12C9. No reactions were seen with seed homogenates from healthy plants. Thus, our results suggest that these MAbs might be used to develop a sandwich ELISA detection system for P. halstedii in infected seeds.

High bandwidth airborne acoustic detection system (HBADS) for circular synthetic aperture acoustic imaging of canonical ground targets

2019 ◽  
Vol 146 (4) ◽  
pp. 3079-3079
Author(s):  
Steven S. Bishop ◽  
Timothy R. Moore ◽  
Peter Gugino ◽  
Brett Smith ◽  
Kathryn P. Kirkwood ◽  
...  
Keyword(s):  
Detection System ◽  
Acoustic Imaging ◽  
Synthetic Aperture ◽  
Acoustic Detection ◽  
High Bandwidth

scholarly journals Nighttime Fire/Smoke Detection System Based on a Support Vector Machine

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Chao-Ching Ho
Keyword(s):  
Support Vector Machine ◽  
Detection System ◽  
Time Algorithm ◽  
Detection Methods ◽  
Support Vector ◽  
Smoke Detection ◽  
Fire Smoke ◽  
Large Fires ◽  
Monitoring Zone

Currently, video surveillance-based early fire smoke detection is crucial to the prevention of large fires and the protection of life and goods. To overcome the nighttime limitations of video smoke detection methods, a laser light can be projected into the monitored field of view, and the returning projected light section image can be analyzed to detect fire and/or smoke. If smoke appears within the monitoring zone created from the diffusion or scattering of light in the projected path, the camera sensor receives a corresponding signal. The successive processing steps of the proposed real-time algorithm use the spectral, diffusing, and scattering characteristics of the smoke-filled regions in the image sequences to register the position of possible smoke in a video. Characterization of smoke is carried out by a nonlinear classification method using a support vector machine, and this is applied to identify the potential fire/smoke location. Experimental results in a variety of nighttime conditions demonstrate that the proposed fire/smoke detection method can successfully and reliably detect fires by identifying the location of smoke.

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