Nanosecond response 'gasket-type' magnetic loop current monitor for relativistic electron beam current measurements

A fast response magnetic loop current monitor has been developed to measure relativistic electron beam return currents. The monitor has a rise time of about a nanosecond and a high degree of symmetry with moderate sensitivity, variable from about 1 to 10 V/kA. This simple monitor, with a thickness of 0.254 mm or less, is thin enough to be placed between segments of return current path in the diode or drift tube regions, is insensitive to flashover, beam and plasma bombardment, and radiation effects, and measures net current, thus offering some advantages over conventional magnetic probes, since the main components are outside of the vacuum region. Design criteria, an equivalent circuit analysis, and typical calibration waveforms are presented. Experimental current measurements for a pinched electron beam diode configuration using both conventional magnetic probes and 'gasket-type'current monitors with the FX-75 relativistic electron beam accelerator are presented.     

The effects of foveal load and visual context on peripheral letter recognition

Peripheral letter recognition was examined by presenting subjects with a letter triad centered 7.16 degrees to the right of fixation. At the same time, a single letter was presented at the point of fixation that was either the same as one of the letters in the triad or different from any of the triad letters. On other trials, no letter was presented at the point of fixation. Results supported and extended previous foveal load research. The disruptive effect of foveal load does not depend solely on the presence or absence of a foveal stimulus. Recognition of the first letter in non-words was disrupted when a foveal letter was presented that was different from the peripheral letter. Recognition of the middle letter for both words and non-words was disrupted when a foveal letter was presented that was the same as the middle letter. A significant interaction between foveal letter and triad type was also found. No evidence was found to suggest that recognition of a peripheral letter is significantly better when that same letter is also present at the point of fixation.     

Bit-to-bit error dependence in slotted DS/SSMA packet systems withrandom signature sequences

A technique is developed to find an accurate approximation to the probability of data bit error and the probability of packet success in a direct-sequence spread-spectrum multiple-access (DS/SSMA) packet radio system with random signature sequences. An improved Gaussian approximation to the probability of data bit error is performed. Packet performance is analyzed by using the theory of moment spaces to gain insight into the effect of bit-to-bit error dependence caused by interfering signal relative delays and phases which are assumed constant over the duration of a desired packet. Numerical results show that if no error control exists in the desired packet or if block error control is used when multiple-access interference is high, the error dependence increases the average probability of packet success beyond that predicted by models which use independent bit errors. However, when block error control is used and the multiple-access interference is low, the bit error dependencies cause a reduction in packet error performance     

Fusion of Data and Knowledge for Safe UAV Landing

Autonomous Unmanned Aerial Vehicles (UAVs) have the potential to significantly improve current working practices for a variety of applications including aerial surveillance and search-and-rescue. However before UAVs can be widely integrated into civilian airspace there are a number of technical challenges which must be overcome including provision of an autonomous method of landing which would be executed in the event of an emergency. A fundamental component of autonomous landing is safe landing zone detection of which terrain classification is a major constituent. Presented in this paper is an extension of the Multi-Modal Expectation Maximization algorithm which combines data in the form of multiple images of the same scene, with knowledge in the form of historic training data and Ordnance Survey map information to compute updated class parameters. These updated parameters are subsequently used to classify the terrain of an area based on the pixel data contained within the images. An image''s contribution to the classification of an area is then apportioned according to its coverage of that area. Preliminary results are presented based on aerial imagery of the Antrim Plateau region in Northern Ireland which indicates potential in the approach used.