The limited streamer tube system of H1

1992 ◽  
Author(s):  
Joerg Tutas
Keyword(s):  
Tube System ◽  
Streamer Tube

scholarly journals Some Properties of the Streamer Tube System of the CHARM Neutrino Detector

1983 ◽  
Vol 30 (1) ◽  
pp. 122-124 ◽  
Author(s):  
F. Bergsma ◽  
J. Dorenbosch ◽  
M. Jonker ◽  
C. Nieuwenhuis ◽  
F. Udo ◽  
...  
Keyword(s):  
Neutrino Detector ◽  
Tube System ◽  
Streamer Tube

Monopole trigger for the streamer tube system in macro

1988 ◽  
Vol 263 (1) ◽  
pp. 249-254 ◽  
Author(s):  
G. Auriemma ◽  
G. Battistoni ◽  
E. Lamanna ◽  
S. Petrera ◽  
G. Piccinelli ◽  
...  
Keyword(s):  
Tube System ◽  
Streamer Tube

Performance of the MACRO streamer tube system in the search for magnetic monopoles

1995 ◽  
Vol 4 (1) ◽  
pp. 33-43 ◽  
Author(s):  
M. Ambrosio ◽  
R. Antolini ◽  
G. Auriemma ◽  
R. Baker ◽  
A. Baldini ◽  
...  
Keyword(s):  
Magnetic Monopoles ◽  
Tube System ◽  
Streamer Tube

scholarly journals The limited streamer tube system of the charm collaboration

1983 ◽  
Vol 215 (3) ◽  
pp. 361-368 ◽  
Author(s):  
M. Jonker ◽  
F. Udo ◽  
U. Amaldi ◽  
R. Donnet ◽  
W. Flegel ◽  
...  
Keyword(s):  
Tube System ◽  
Streamer Tube

scholarly journals A Novel Method for the Complex Tube System Reconstruction and Measurement

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2207
Author(s):  
Xiang Guo ◽  
Xin Su ◽  
Yingtao Yuan ◽  
Tao Suo ◽  
Yan Liu
Keyword(s):  
Neural Network ◽  
Minimum Distance ◽  
Technical Difficulty ◽  
Industry Structure ◽  
Tube System ◽  
Simulation Experiments ◽  
Pipe System ◽  
System Reconstruction ◽  
Novel Method ◽  
Assembly Error

Pipe structures are at the base of the entire industry. In the industry structure, heat and vibration are transmitted in each pipe. The minimum distance between each pipe is significant to the security. The assembly error and the deformation of the pipeline positions after multiple runs are significant problems. The reconstruction of the multi-pipe system is a critical technical difficulty in the complex tube system. In this paper, a new method for the multi-pipes structure inspection is presented. Images of the tube system are acquired from several positions. The photogrammetry technology calculates positions, and the necessary coordination of the structure is reconstructed. A convolution neural network is utilized to detect edges of tube-features. The new algorithm for tube identification and reconstruction is presented to extract the tube feature in the image and reconstruct the 3D parameters of all tubes in a multi-pipes structure. The accuracy of the algorithm is verified by simulation experiments. An actual engine of the aircraft is measured to verify the proposed method.

Requiem for the STAT Test: Automation and Point of Care Testing

2019 ◽  
Author(s):  
Gurmukh Singh ◽  
Natasha M Savage ◽  
Brandy Gunsolus ◽  
Kellie A Foss
Keyword(s):  
Point Of Care ◽  
Turnaround Time ◽  
Test Automation ◽  
Test Results ◽  
Point Of Care Testing ◽  
Tube System ◽  
Front End ◽  
Laboratory Test Results ◽  
Batch Testing ◽  
Pneumatic Tube System

Abstract Objective Quick turnaround of laboratory test results is needed for medical and administrative reasons. Historically, laboratory tests have been requested as routine or STAT. With a few exceptions, a total turnaround time of 90 minutes has been the usually acceptable turnaround time for STAT tests. Methods We implemented front-end automation and autoverification and eliminated batch testing for routine tests. We instituted on-site intraoperative testing for selected analytes and employed point of care (POC) testing judiciously. The pneumatic tube system for specimen transport was expanded. Results The in-laboratory turnaround time was reduced to 45 minutes for more than 90% of tests that could reasonably be ordered STAT. With rare exceptions, the laboratory no longer differentiates between routine and STAT testing. Having a single queue for all tests has improved the efficiency of the laboratory. Conclusion It has been recognized in manufacturing that batch processing and having multiple queues for products are inefficient. The same principles were applied to laboratory testing, which resulted in improvement in operational efficiency and elimination of STAT tests. We propose that the target for in-laboratory turnaround time for STAT tests, if not all tests, be 45 minutes or less for more than 90% of specimens.

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