Investigation of electro-optical techniques for controlling the direction of a laser beam. Part one - Beam deflector devices. Part two - Beam deflector systems Interim report

Piezoelectrically powered laser beam waveguide for electro-optical acquisition and trackin

Exploratory studies of liquid behavior in randomly excited tanks - Lateral excitation

Fluid behavior in unbaffled circular cylindrical tank under relatively low frequency random lateral excitatio

Analytical study of the feasibility of a pneumatic neutron flux detector

Pneumatic thermal neutron flux detector feasibility stud

Operational application of a universal turbulence measuring system Final report

Aeronautical turbulence measuring apparatus - gust loadin

Joint Frequency and Image Space Learning for Fourier Imaging

We demonstrate that neural network layers that explicitly combine frequency and image feature representations are a versatile building block for analysis of imaging data acquired in the frequency space. Our work is motivated by the challenges arising in MRI acquisition where the signal is a corrupted Fourier transform of the desired image. The joint learning schemes proposed and analyzed in this paper enable both correction of artifacts native to the frequency space and manipulation of image space representations to reconstruct coherent image structures. This is in contrast to most current deep learning approaches for image reconstruction that apply learned data manipulations solely in the frequency space or solely in the image space. We demonstrate the advantages of joint convolutional learning on three diverse tasks: image reconstruction from undersampled acquisitions, motion correction, and image denoising in brain and knee MRI. We further demonstrate advantages of the joint learning approaches across training schemes using a wide variety of loss functions. Unlike purely image based and purely frequency based architectures, the joint models produce consistently high quality output images across all tasks and datasets. Joint image and frequency space feature representations promise to significantly improve modeling and reconstruction of images acquired in the frequency space. Our code is available at https://github.com/nalinimsingh/interlacer.Comment: 16 pages, 13 figures, image reconstruction, motion correction, denoising, magnetic resonance imaging, deep learnin

Multiple intensity reference interferometry for the correction of sub-fringe displacement non-linearities

Displacement measuring interferometers, commonly employed for traceable measurements at the nanoscale, suffer from non-linearities in the measured displacement that limit the achievable measurement uncertainty for microscopic displacements. Two closely related novel non-linearity correction methodologies are presented here that allow for the correction of non-linearities in cases where the displacement covers much less than a full optical fringe. Both corrections have been shown, under ideal conditions, to be capable of reducing all residual non-linearity harmonics to below the 10 pm level.Engineering and Physical Sciences Research Council (EPSRC) EP/R511894/1 (Project 2199198). Department for Business, Energy and Industrial Strategy; Royal Academy of Engineering Research Fellowship F\201718\174

Introduction to the derivation of mission requirements profiles for system elements

Development of mission requirement profile for subsystem components from overall system profil

Static and dynamic properties of synaptic transmission at the cyto-neural junction of frog labyrinth posterior canal

The properties of synaptic transmission have been studied at the cyto-neural junction of the frog labyrinth posterior canal by examining excitatory postsynaptic potential (EPSP) activity recorded intraaxonally from the afferent nerve after abolishing spike firing by tetrodotoxin. The waveform, amplitude, and rate of occurrence of the EPSPs have been evaluated by means of a procedure of fluctuation analysis devised to continuously monitor these parameters, at rest as well as during stimulation of the semicircular canal by sinusoidal rotation at 0.1 Hz, with peak accelerations ranging from 8 to 87 deg.s-2. Responses to excitatory and inhibitory accelerations were quantified in terms of maximum and minimum EPSP rates, respectively, as well as total numbers of EPSPs occurring during the excitatory and inhibitory half cycles. Excitatory responses were systematically larger than inhibitory ones (asymmetry). Excitatory responses were linearly related either to peak acceleration or to its logarithm, and the same occurred for inhibitory responses. In all units examined, the asymmetry of the response yielded nonlinear two-sided input-output intensity functions. Silencing of EPSPs during inhibition (rectification) was never observed. Comparison of activity during the first cycle of rotation with the average response over several cycles indicated that variable degrees of adaptation (up to 48%) characterize the excitatory response, whereas no consistent adaptation was observed in the inhibitory response. All fibers appeared to give responses nearly in phase with angular velocity, at 0.1 Hz, although the peak rates generally anticipated by a few degrees the peak angular velocity. From the data presented it appears that asymmetry, adaptation, and at least part of the phase lead in afferent nerve response are of presynaptic origin, whereas rectification and possible further phase lead arise at the encoder. To confirm these conclusions a simultaneous though limited study of spike firing and EPSP activity has been attempted in a few fibers

Inertial gyroscope system application considerations

Criteria for designing inertial gyroscope system