Acoustic power measurements of oscillating flames

The acoustic power of an oscillating flame is measured. A turbulent premixed propane/air flame is situated near a pressure antinode of a standing wave in a laboratory combustion chamber. This standing wave is generated by a piston. The fluctuating heat release of the flame will supply acoustic power to the standing wave as postulated by Rayleigh. This flame acoustic power is obtained by setting up a power balance of the whole combustion chamber.\ud \ud Experiments proved that it is possible to measure quantitatively the acoustic power and the frequency change as a function of relevant parameters. This frequency change is a second phenomenon described by Rayleigh. The acoustic power of the flame as a function of the amplitude of the fluctuating component of the mixture flow velocity at different frequencies can be measured.\ud \ud Measurement techniques are described and results for frequencies ranging from 3 to 120 Hz are given

Approximation of high quantiles from intermediate quantiles

Motivated by applications requiring quantile estimates for very small probabilities of exceedance, this article addresses estimation of high quantiles for probabilities bounded by powers of sample size with exponents below -1. As regularity assumption, an alternative to the Generalised Pareto tail limit is explored for this purpose. Motivation for the alternative regularity assumption is provided, and it is shown to be equivalent to a limit relation for the logarithm of survival function, the log-GW tail limit, which generalises the GW (Generalised Weibull) tail limit, a generalisation of the Weibull tail limit. The domain of attraction is described, and convergence results are presented for quantile approximation and for a simple quantile estimator based on the log-GW tail. Simulations are presented, and advantages and limitations of log-GW-based estimation of high quantiles are indicated

Interdisciplinary perspectives on aid and local ownership in projects

development projects;development aid;organization theory;local level;aid institutions;intercultural communication;project implementation

Garuda 5 (khyung lnga): Ecologies of Potency and the Poison-Medicine Spectrum of Sowa Rigpa’s Renowned ‘Black Aconite’ Formula

This article focuses on ethnographic work conducted at the Men-Tsee-Khang (Dharamsala, India) on Garuda 5 (khyung lnga), a commonly prescribed Tibetan medical formula. This medicine’s efficacy as a painkiller and activity against infection and inflammation is largely due to a particularly powerful plant, known as ‘virulent poison’ (btsan dug) as well as ‘the great medicine’ (sman chen), and identified as a subset of Aconitum species. Its effects, however, are potentially dangerous or even deadly. How can these poisonous plants be used in medicine and, conversely, when does a medicine become a poison? How can ostensibly the same substance be both harmful and helpful? The explanation requires a more nuanced picture than mere dose dependency. Attending to the broader ‘ecologies of potency’ in which these substances are locally enmeshed, in line with Sienna Craig’s Efficacy and the Social Ecologies of Tibetan Medicine (2012), provides fertile ground to better understand the effects of Garuda 5 and how potency is developed and directed in practice. I aim to unpack the spectrum between sman (medicine) and dug (poison) in Sowa Rigpa by elucidating some of the multiple dimensions which determine the activity of Garuda 5 as it is formulated and prescribed in India. I thus embrace the full spectrum of potency— the ‘good’ and the ‘bad,’ the ‘wanted’ and the ‘unwanted’—without presuming the universal validity of biomedical notions of toxicity and side effects

A machine learning approach to voice separation in lute tablature

[TODO] Add abstract here

Deep neural networks with voice entry estimation heuristics for voice separation in symbolic music representations

In this study we explore the use of deep feedforward neural networks for voice separation in symbolic music representations. We experiment with different network architectures, varying the number and size of the hidden layers, and with dropout. We integrate two voice entry estimation heuristics that estimate the entry points of the individual voices in the polyphonic fabric into the models. These heuristics serve to reduce error propagation at the beginning of a piece, which, as we have shown in previous work, can seriously hamper model performance. The models are evaluated on the 48 fugues from Johann Sebastian Bach’s The Well-Tempered Clavier and his 30 inventions—a dataset that we curated and make publicly available. We find that a model with two hidden layers yields the best results. Using more layers does not lead to a significant performance improvement. Furthermore, we find that our voice entry estimation heuristics are highly effective in the reduction of error propagation, improving performance significantly. Our best-performing model outperforms our previous models, where the difference is significant, and, depending on the evaluation metric, performs close to or better than the reported state of the art

Simulating Wde-area Replication

We describe our experiences with simulating replication algorithms for use in far flung distributed systems. The algorithms under scrutiny mimic epidemics. Epidemic algorithms seem to scale and adapt to change (such as varying replica sets) well. The loose consistency guarantees they make seem more useful in applications where availability strongly outweighs correctness; e.g., distributed name service