Institution
Defence Science and Technology Laboratory
Government•Salisbury, United Kingdom•
About: Defence Science and Technology Laboratory is a government organization based out in Salisbury, United Kingdom. It is known for research contribution in the topics: Burkholderia pseudomallei & Francisella tularensis. The organization has 926 authors who have published 1242 publications receiving 30091 citations. The organization is also known as: Dstl & [dstl].
Papers published on a yearly basis
Papers
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TL;DR: In this article, the tensile response of PMMA, Kevlar and Dyneema yarns was measured at strain rates ranging from 10−4 to 323 s−1.
6 citations
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TL;DR: Windscreen scatter measurements were taken, showing that windscreen scatter is similar in magnitude to scatter from the human eye, and a model based on this analysis has been shown to be a useful tool to predict the impact of windscreens on laser eye dazzle.
Abstract: This study investigates the extent to which a windscreen affects the severity of laser eye dazzle (disability glare produced by a laser) experienced by a human observer. Windscreen scatter measurements were taken for a range of windscreens in a variety of conditions, showing that windscreen scatter is similar in magnitude to scatter from the human eye. Human subject experiments verified that obscuration angles caused by laser eye dazzle could be increased by the presence of a windscreen when comparing a dirty automobile windscreen to an eye-only condition with a 532-nm laser exposure. However, a light aircraft windscreen with lower scatter did not exhibit increased obscuration angles at 532 nm, and neither windscreen exhibited an increase at 635 nm. A theoretical analysis of laser eye dazzle, using measured windscreen scatter functions, has provided insight into the delicate interplay between scatter, transmission and the angular extent of dazzle. A model based on this analysis has been shown to be a useful tool to predict the impact of windscreens on laser eye dazzle, with the goal of informing future updates to the authors' laser eye dazzle safety framework.
6 citations
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TL;DR: The overall system can be resilient to some adversarial examples thanks to the existence of other components, and the overall system presents an extra level of uncertainty which cannot be determined by analysing the deep learning components only, suggesting the need for novel verification and validation methods for learning-enabled systems.
Abstract: This paper studies the reliability of a real-world learning-enabled system, which conducts dynamic vehicle tracking based on a high-resolution wide-area motion imagery input. The system consists of multiple neural network components -- to process the imagery inputs -- and multiple symbolic (Kalman filter) components -- to analyse the processed information for vehicle tracking. It is known that neural networks suffer from adversarial examples, which make them lack robustness. However, it is unclear if and how the adversarial examples over learning components can affect the overall system-level reliability. By integrating a coverage-guided neural network testing tool, DeepConcolic, with the vehicle tracking system, we found that (1) the overall system can be resilient to some adversarial examples thanks to the existence of other components, and (2) the overall system presents an extra level of uncertainty which cannot be determined by analysing the deep learning components only. This research suggests the need for novel verification and validation methods for learning-enabled systems.
6 citations
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TL;DR: The history of development and mechanism of action of some sensory irritants is discussed here in relation to recent advice from the Scientific Advisory Board (SAB) of the Organisation for the Prohibition of Chemical Weapons (OPCW) on chemicals that conform to the definition of a riot control agent (RCA) under the Chemical Weapons Convention.
Abstract: Abstract Pain! Most humans feel it throughout their lives. The molecular mechanisms underlying the phenomenon are still poorly understood. This is especially true of pain triggered in response to molecules of a certain shape and reactivity present in the environment. Such molecules can interact with the sensory nerve endings of the eyes, nose, throat and lungs to cause irritation that can range from mild to severe. The ability to alert to the presence of such potentially harmful substances has been termed the ‘common chemical sense’ and is thought to be distinct from the senses of smell or taste, which are presumed to have evolved later. Barbecue a burger excessively and you self-experiment. Fatty acids present in the meat break off their glycerol anchor under the thermal stress. The glycerol loses two molecules of water and forms acrolein, whose assault on the eyes is partly responsible for the tears elicited by smoke. Yet the smell and taste of the burger are different experiences. It was this eye-watering character of acrolein that prompted its use as a warfare agent during World War I. It was one of several ‘lachrymators’ deployed to harass, and the forerunner of safer chemicals, such as ‘tear gas’ CS, developed for riot control. The history of development and mechanism of action of some sensory irritants is discussed here in relation to recent advice from the Scientific Advisory Board (SAB) of the Organisation for the Prohibition of Chemical Weapons (OPCW) on chemicals that conform to the definition of a riot control agent (RCA) under the Chemical Weapons Convention.
6 citations
Authors
Showing all 928 results
Name | H-index | Papers | Citations |
---|---|---|---|
Richard W. Titball | 79 | 410 | 22484 |
Andrew D. Griffiths | 72 | 152 | 37590 |
Alan D.T. Barrett | 71 | 341 | 17136 |
Jim Haywood | 67 | 213 | 20503 |
Philip N. Bartlett | 58 | 293 | 12798 |
Alan C. Newell | 58 | 209 | 17820 |
David A. Rand | 57 | 223 | 12157 |
Michael P. O'Donnell | 49 | 301 | 8762 |
James Hill | 47 | 216 | 6837 |
Franz Worek | 46 | 262 | 8754 |
Petra C. F. Oyston | 45 | 127 | 7155 |
K. Ravi Acharya | 45 | 161 | 7405 |
Horst Thiermann | 43 | 298 | 7091 |
Leigh T. Canham | 42 | 160 | 18268 |
Mark J. Midwinter | 39 | 180 | 5330 |