Broadband acoustic invisibility and illusions

Rendering objects invisible to impinging acoustic waves (cloaking) and creating acoustic illusions (holography) has been attempted using active and passive approaches. While most passive methods are inflexible and applicable only to narrow frequency bands, active approaches attempt to respond dynamically, interfering with broadband incident or scattered wavefields by emitting secondary waves. Without prior knowledge of the primary wavefield, the signals for the secondary sources need to be estimated and adapted in real time. This has thus far impeded active cloaking and holography for broadband wavefields. We present experimental results of active acoustic cloaking and holography without prior knowledge of the wavefield so that objects remain invisible and illusions intact even for broadband moving sources. This opens previously inaccessible research directions and facilitates practical applications including architectural acoustics, education, and stealth

Compensating for source directivity in immersive wave experimentation

ISSN:0001-4966ISSN:1520-852

Binary classification of spoken words with passive elastic metastructures

Many electronic devices spend most of their time waiting for a wake-up event: pacemakers waiting for an anomalous heartbeat, security systems on alert to detect an intruder, smartphones listening for the user to say a wake-up phrase. These devices continuously convert physical signals into electrical currents that are then analyzed on a digital computer -- leading to power consumption even when no event is taking place. Solving this problem requires the ability to passively distinguish relevant from irrelevant events (e.g. tell a wake-up phrase from a regular conversation). Here, we experimentally demonstrate an elastic metastructure, consisting of a network of coupled silicon resonators, that passively discriminates between pairs of spoken words -- solving the wake-up problem for scenarios where only two classes of events are possible. This passive speech recognition is demonstrated on a dataset from speakers with significant gender and accent diversity. The geometry of the metastructure is determined during the design process, in which the network of resonators ('mechanical neurones') learns to selectively respond to spoken words. Training is facilitated by a machine learning model that reduces the number of computationally expensive three-dimensional elastic wave simulations. By embedding event detection in the structural dynamics, mechanical neural networks thus enable novel classes of always-on smart devices with no standby power consumption.Comment: 13 pages, 9 figure

Statistical analysis of arthroplasty data: II. Guidelines

It is envisaged that guidelines for statistical analysis and presentation of results will improve the quality and value of research. The Nordic Arthroplasty Register Association (NARA) has therefore developed guidelines for the statistical analysis of arthroplasty register data. The guidelines are divided into two parts, one with an introduction and a discussion of the background to the guidelines (Ranstam et al. 2011a, see pages x-y in this issue), and this one with a more technical statistical discussion on how specific problems can be handled. This second part contains (1) recommendations for the interpretation of methods used to calculate survival, (2) recommendations on howto deal with bilateral observations, and (3) a discussion of problems and pitfalls associated with analysis of factors that influence survival or comparisons between outcomes extracted from different hospitals

Optimal finite-difference operators for arbitrarily sampled data

We have developed a general method to obtain the equiripple and the least-squares finite-difference (FD) operator weights to compute arbitrary-order derivatives from arbitrary sample locations. The method is based on the complex-valued Remez exchange algorithm applied to three cost functions: the total error, the relative error, and the group-velocity error. We evaluate the method on three acoustic FD modeling examples. In the first example, we assess the accuracy obtained with the optimal coefficients when propagating acoustic waves through a medium. In the second example, we propagate a wave through an irregular grid. In the final example, we position a source and receiver at arbitrary locations in-between the modeling grid points. In the examples using regular grids, the equiripple solution to the relative cost function performs best. It obtains marginally (4%–10%) better results compared to the second-best option, the least-squares solution for the relative cost function. The least-squares solution for the relative error produced the only stable and accurate results also in the example of modeling on an irregular grid