On The Homology Spectral Sequence For Topological Hochschild Homology

Marcel Bokstedt has computed the homotopy type of the topological Hochschild homology of Z/p using his definition of topological Hochschild homology for a functor with smash product. Here we show that easy conceptual proofs of his main technical result of are possible in the context of the homotopy theory of S-algebras as introduced by Elmendorf, Kriz, Mandell and May. We give algebraic arguments based on naturality properties of the topological Hochschild homology spectral sequence. In the process we demonstrate the utility of the unstable \u27\u27lower\u27\u27 notation for the Dyer-Lashof algebra

Coherence-Induced Bias Reduction in Synthetic Aperture Sonar Along-Track Micronavigation

Subwavelength motion estimation is vital for the production of focused synthetic aperture sonar (SAS) imagery. The required precision is obtainable from the sonar data itself through a process termed micronavigation. Along-track micronavigation is achieved by a similar technique to that used in correlation velocity logs (CVLs), where sparse estimates of the spatial coherence function are interpolated to estimate the location of the peak coherence and hence estimate the interping vehicle motion. However, along-track micronavigation estimates made using this technique are biased, which limits the utility of these measurements for long-term navigation of autonomous underwater vehicles (AUVs). Three sources of along-track motion estimation bias are considered in this article. First, imperfect temporal registration between the signals results in coherence estimates that are negatively biased as a function of the temporal offset. Second, the sparse estimates of the spatial coherence function are obtained by cross-correlation of complex baseband signals, a process which is known to result in positively biased coherence estimates, especially when the true coherence is low. Finally, mismatches between the underlying spatial coherence function and the interpolation kernel used to estimate the peak coherence location also result in along-track micronavigation bias. In this article, we describe and evaluate three methods for reducing along-track micronavigation bias. We introduce a temporal registration of the signals before coherence estimation, which reduces the impact of negative coherence bias due to temporal offsets. The remaining coherence estimation bias is reduced by combining multiple coherence estimates in a Bayesian coherence estimator. Additionally, an improved interpolation kernel is derived with a significantly improved fit compared to the current gold standard Gaussian interpolation kernel. The improvements in along-track micronavigation accuracy are demonstrated using two simulated data sets, which both allow comparison with ground truth. The first involves direct simulation of the spatial coherence from a given interping geometry using the pulse-echo formulation of the van Cittert-Zernike theorem, while the second involves simulation of raw sonar echo data using a point-scatterer model. Using these simulations, a reduction in along-track micronavigation bias of 48.5%-99.5% is demonstrated, with reductions in along-track micronavigation error standard deviation of up to 34%. This improvement expands the potential for SAS-equipped AUVs to reduce their long-term navigation drift, facilitating longer underwater transits, improved target localization, and reduced track misalignment in repeat-pass operations.</p

Electrophoresis of colloidal dispersions in the low-salt regime

We study the electrophoretic mobility of spherical charged colloids in a low-salt suspension as a function of the colloidal concentration. Using an effective particle charge and a reduced screening parameter, we map the data for systems with different particle charges and sizes, including numerical simulation data with full electrostatics and hydrodynamics and experimental data for latex dispersions, on a single master curve. We observe two different volume fraction-dependent regimes for the electrophoretic mobility that can be explained in terms of the static properties of the ionic double layer.Comment: Substantially revised versio

Model-based 3D micro-navigation and bathymetry estimation for interferometric synthetic aperture sonar

Sub-wavelength navigation information is vital for the formation of all synthetic aperture sonar (SAS) data products. This challenging requirement can be achieved using the redundant phase centre (RPC) or displaced phase centre antenna (DPCA) micro-navigation algorithm, which uses cross-correlation of signals with inter-ping coherence to estimate time delays and hence make navigation estimates. In this paper a new approach to micro- navigation for interferometric synthetic aperture sonar is introduced. The algorithm makes 3D vehicle position estimates for each sonar ping by making use of time delays measured between all possible pairs of redundant phase centre arrays, using both interferometric arrays on each side of the vehicle. Simultaneous estimation of coarse bathymetry allows the SAS images to be projected onto ground-range. The method is based on non-linear minimization of the difference in modelled and measured time delays and surges between redundant phase centre arrays. The approach is demonstrated using data collected by the CMRE MUSCLE AUV using its 270-330 kHz SAS during the MANEX’14 experiment. SAS images have been projected onto the coarsely estimated bathymetry, and interferograms have been formed. The coarse bathymetry estimate and vehicle navigation estimate are validated by the quality of the image focussing and the near-zero phase of the interferogram. The method has the potential to improve through-the-sensor navigation aiding and to increase the accuracy of single-pass bathymetry estimation. Future development of the algorithm for repeat-pass operation has the potential to enable repeat-pass track registration in three dimensions. The method is therefore an important step towards improved coherent change detection and high resolution bathymetry estimation

Phase wrap error correction by random sample consensus with application to synthetic aperture sonar micro-navigation

Accurate time delay estimation between signals is crucial for coherent imaging systems such as synthetic aperture sonar (SAS) and synthetic aperture radar (SAR). In such systems, time delay estimates resulting from the cross-correlation of complex signals are commonly used to generate navigation and scene height measurements. In the presence of noise, the time delay estimates can be ambiguous, containing errors corresponding to an integer number of phase wraps. These ambiguities cause navigation and bathymetry errors and reduce the quality of synthetic aperture imagery. In this article, an algorithm is introduced for the detection and correction of phase wrap errors. The random sample consensus (RANSAC) algorithm is used to fit 1-D and 2-D models to the ambiguous time delay estimates made in the time delay estimation step of redundant phase center (RPC) micronavigation. Phase wrap errors are then corrected by recalculating the phase wrap number using the best-fitting model. The approach is demonstrated using the data collected by the 270&amp;#x2013;330 kHz SAS of the NATO Centre for Maritime Research and Experimentation Minehunting unmanned underwater vehicle for Shallow water Covert Littoral Expeditions. Systems with lower fractional bandwidth were emulated by windowing the bandwidth of the signals to increase the occurrence of phase wrap errors. The time delay estimates were refined using both the RANSAC algorithms using 1-D and 2-D models and the commonly used branch-cuts method. Following qualitative assessment of the smoothness of the full-bandwidth time delay estimates after application of these three methods, the results from the 2-D RANSAC method were chosen as the reference time delay estimates. Comparison with the reference estimates shows that the 1-D and 2-D RANSAC methods outperform the branch-cuts method, with improvements of 29&amp;#x0025;&amp;#x2013;125&amp;#x0025; and 30&amp;#x0025;&amp;#x2013;150&amp;#x0025;, respectively, compared to 16&amp;#x0025;&amp;#x2013;134&amp;#x0025; for the branch-cuts method for this data set.</p

Fourier-Domain Wavefield Rendering for Rapid Simulation of Synthetic Aperture Sonar Data

This paper introduces a new method for simulating synthetic aperture sonar (SAS) raw coherent echo data that is orders of magnitude faster than the commonly used point and facet diffraction models. The new approach uses Fourier wavefield generation and propagation in combination with a highly optimised optical rendering engine. It has been shown to produce a quantifiably similar quality of data and data products (i.e., images and spectra) to a point-diffraction model, capturing the important coherent wave physics (including diffraction, speckle, aspect-dependence, and layover) as well as effects of the SAS processing chain (including image focusing errors and artefacts). This new simulation capability may be an enabler for augmenting data sets with physically accurate and diverse synthetic data for robust machine learning

Phase wrap error correction by random sample consensus with application to synthetic aperture sonar micro-navigation

Accurate time delay estimation between signals is crucial for coherent imaging systems such as synthetic aperture sonar (SAS) and synthetic aperture radar (SAR). In such systems, time delay estimates resulting from the cross-correlation of complex signals are commonly used to generate navigation and scene height measurements. In the presence of noise, the time delay estimates can be ambiguous, containing errors corresponding to an integer number of phase wraps. These ambiguities cause navigation and bathymetry errors and reduce the quality of synthetic aperture imagery. In this article, an algorithm is introduced for the detection and correction of phase wrap errors. The random sample consensus (RANSAC) algorithm is used to fit 1-D and 2-D models to the ambiguous time delay estimates made in the time delay estimation step of redundant phase center (RPC) micronavigation. Phase wrap errors are then corrected by recalculating the phase wrap number using the best-fitting model. The approach is demonstrated using the data collected by the 270&amp;#x2013;330 kHz SAS of the NATO Centre for Maritime Research and Experimentation Minehunting unmanned underwater vehicle for Shallow water Covert Littoral Expeditions. Systems with lower fractional bandwidth were emulated by windowing the bandwidth of the signals to increase the occurrence of phase wrap errors. The time delay estimates were refined using both the RANSAC algorithms using 1-D and 2-D models and the commonly used branch-cuts method. Following qualitative assessment of the smoothness of the full-bandwidth time delay estimates after application of these three methods, the results from the 2-D RANSAC method were chosen as the reference time delay estimates. Comparison with the reference estimates shows that the 1-D and 2-D RANSAC methods outperform the branch-cuts method, with improvements of 29&amp;#x0025;&amp;#x2013;125&amp;#x0025; and 30&amp;#x0025;&amp;#x2013;150&amp;#x0025;, respectively, compared to 16&amp;#x0025;&amp;#x2013;134&amp;#x0025; for the branch-cuts method for this data set.</p

Occlusion Modeling for Coherent Echo Data Simulation:A Comparison Between Ray-Tracing and Convex-Hull Methods

The ability to simulate realistic coherent datasets for synthetic aperture imaging systems is crucial for the design, development and evaluation of the sensors and their signal processing pipelines, machine learning algorithms and autonomy systems. In the case of synthetic aperture sonar (SAS), collecting experimental data is expensive and it is rarely possible to obtain ground truth of the sensor’s path, the speed of sound in the medium, and the geometry of the imaged scene. Simulating sonar echo data allows signal processing algorithms to be tested with known ground truth, enabling rapid and inexpensive development and evaluation of signal processing algorithms. The de-facto standard for simulating conventional high-frequency (i.e., &gt; 100 kHz) SAS echo data from an arbitrary sensor, path and scene is to use a point-based or facet-based diffraction model. A crucial part of this process is acoustic occlusion modeling. This article describes a SAS simulation pipeline and compares implementations of two occlusion methods; ray-tracing, and a newer approximate method based on finding the convex hull of a transformed point cloud. The full capability of the simulation pipeline is demonstrated using an example scene based on a high-resolution 3D model of the SS Thistlegorm shipwreck which was obtained using photogrammetry. The 3D model spans a volume of 220 × 130 × 25 m and is comprised of over 30 million facets that are decomposed into a cloud of almost 1 billion points. The convex-hull occlusion model was found to result in simulated SAS imagery that is qualitatively indistinguishable from the ray-tracing approach and quantitatively very similar, demonstrating that use of this alternative method has potential to improve speed while retaining high fidelity of simulation.The convex-hull approach was found to be up to 4 times faster in a fair speed comparison with serial and parallel CPU implementations for both methods, with the largest performance increase for wide-beam systems. The fastest occlusion modeling algorithm was found to be GPU-accelerated ray-tracing over the majority of scene scales tested, which was found to be up to 2 times faster than the parallel CPU convex-hull implementation. Although GPU implementations of convex hull algorithms are not currently readily available, future development of GPU-accelerated convex-hull finding could make the new approach much more viable. However, in the meantime, ray-tracing is still preferable, since it has higher accuracy and can leverage existing implementations for high performance computing architectures for better performance

Strain Modulations as a Mechanism to Reduce Stress Relaxation in Laryngeal Tissues

Vocal fold tissues in animal and human species undergo deformation processes at several types of loading rates: a slow strain involved in vocal fold posturing (on the order of 1 Hz or so), cyclic and faster posturing often found in speech tasks or vocal embellishment (1–10 Hz), and shear strain associated with vocal fold vibration during phonation (100 Hz and higher). Relevant to these deformation patterns are the viscous properties of laryngeal tissues, which exhibit non-linear stress relaxation and recovery. In the current study, a large strain time-dependent constitutive model of human vocal fold tissue is used to investigate effects of phonatory posturing cyclic strain in the range of 1 Hz to 10 Hz. Tissue data for two subjects are considered and used to contrast the potential effects of age. Results suggest that modulation frequency and extent (amplitude), as well as the amount of vocal fold overall strain, all affect the change in stress relaxation with modulation added. Generally, the vocal fold cover reduces the rate of relaxation while the opposite is true for the vocal ligament. Further, higher modulation frequencies appear to reduce the rate of relaxation, primarily affecting the ligament. The potential benefits of cyclic strain, often found in vibrato (around 5 Hz modulation) and intonational inflection, are discussed in terms of vocal effort and vocal pitch maintenance. Additionally, elderly tissue appears to not exhibit these benefits to modulation. The exacerbating effect such modulations may have on certain voice disorders, such as muscle tension dysphonia, are explored

Arts Education Academics’ Perceptions of eLearning & Teaching in Australian Early Childhood and Primary ITE Degrees

This article presents the findings of an investigation of eLearning & teaching in Arts education in Australian Initial Teacher Education (ITE) degrees. This project used survey and interviews to collect data from academics in 16 universities in 5 Australian states regarding their experiences of eLearning and Arts education. A rigorous and comprehensive thematic, inductive approach to the analysis of data revealed four main themes: congruence and incongruence of eLearning in Arts education with academic identity, dissonance between eLearning and the nature of Arts education, negatively perceived reasons for teaching Arts education in an eLearning mode, and some expressions of positive experiences in this space. These themes revealed a divided, unsettled and challenging space with pockets of acceptance, but characterised by epistemological and pedagogical questions, doubts and uneasiness