Does increased hydrochemical model complexity decrease robustness?

The aim of this study was, within a sensitivity analysis framework, to determine if additional model complexity gives a better capability to model the hydrology and nitrogen dynamics of a small Mediterranean forested catchment or if the additional parameters cause over-fitting. Three nitrogen-models of varying hydrological complexity were considered. For each model, general sensitivity analysis (GSA) and Generalized Likelihood Uncertainty Estimation (GLUE) were applied, each based on 100,000 Monte Carlo simulations. The results highlighted the most complex structure as the most appropriate, providing the best representation of the non-linear patterns observed in the flow and streamwater nitrate concentrations between 1999 and 2002. Its 5% and 95% GLUE bounds, obtained considering a multi-objective approach, provide the narrowest band for streamwater nitrogen, which suggests increased model robustness, though all models exhibit periods of inconsistent good and poor fits between simulated outcomes and observed data. The results confirm the importance of the riparian zone in controlling the short-term (daily) streamwater nitrogen dynamics in this catchment but not the overall flux of nitrogen from the catchment. It was also shown that as the complexity of a hydrological model increases over-parameterisation occurs, but the converse is true for a water quality model where additional process representation leads to additional acceptable model simulations. Water quality data help constrain the hydrological representation in process-based models. Increased complexity was justifiable for modelling river-system hydrochemistry. Increased complexity was justifiable for modelling river-system hydrochemistry.

Adaptive noise cancellation with fast tunable RBF network

This paper describes a novel adaptive noise cancellation system with fast tunable radial basis function (RBF). The weight coefficients of the RBF network are adapted by the multi-innovation recursive least square (MRLS) algorithm. If the RBF network performs poorly despite of the weight adaptation, an insignificant node with little contribution to the overall performance is replaced with a new node without changing the model size. Otherwise, the RBF network structure remains unchanged and only the weight vector is adapted. The simulation results show that the proposed approach can well cancel the noise in both stationary and nonstationary ANC systems.

Agency of Noise

Agency of Noise is a network of artists, musicians and academics from across the UK whose work is concerned with noise. The website offers a site for the development of online profiles for its members, the publication of works by members and the promotion and documentation of events hosted by the network. It also provides related links and references. The platform has developed from participation at national network events and conferences including Noise Vs Culture, University of Kent (2012); Liveness, University of Bournemouth (2012); Noise, Affect Politics, University of Salford (2010); and a research residency at The Banff Centre, Banff, Canada (2009).

The Prophetic Sound: a day and night of noise cabaret(symposium of talks and live performances)

'The Prophetic Sound: a day and night of noise cabaret' is the first event hosted by Agency of Noise. This all day event brought together artists and academics whose subject of focus is noise (in creative practice). Artists from across the UK were invited to consider a future post-digital era in which everything with a microchip has malfunctioned, as a thought exercise and starting point for response through sound. In response to Jacques Attali’s claim that music is prophecy, The Prophetic Sound asks us to consider if noise can communicate in an unbridled, unfiltered, way that is somehow not culturally coded -before it becomes sound that is recognised, refined, manipulated and exploited for musical or other cultured purpose. Featuring students from Reading, Brighton, LCC and Goldsmiths alongside more established artists and academics from across the UK, this event brings into focus locations where pattern, timbre, pitch, organisation and sequencing of sounds become distinguishable from noise and asks us to consider, through diversion within such locations, new origins for future communication systems. The Prophetic Sound included talks, films, presentations and performances from: Ryo Ikeshiro / Inigo Wilkins / Neal Spowage / Dane Sutherland / Poulomi Desai / Benedict Drew / AAS / Polly Fibre / Steven Dickie As part of The Prophetic Sound, POLLYFIBRE (Ellison, C.) performed LIVE RECORDING with Amplified Scissors. This industrial activity by POLLYFIBRE short-circuits the complicated chain that is music production. The distinctive roles of consumer, producer, composer, and performer collapse in a series of live ‘cuts’ where vinyl discs are produced with amplified scissors. Production happens through action and action becomes production. A limited edition of 9 flexi discs were produced and available for special collectors at the event.

Noise propagation from a cutting of arbitrary cross-section and impedance

A boundary integral equation is described for the prediction of acoustic propagation from a monofrequency coherent line source in a cutting with impedance boundary conditions onto surrounding flat impedance ground. The problem is stated as a boundary value problem for the Helmholtz equation and is subsequently reformulated as a system of boundary integral equations via Green's theorem. It is shown that the integral equation formulation has a unique solution at all wavenumbers. The numerical solution of the coupled boundary integral equations by a simple boundary element method is then described. The convergence of the numerical scheme is demonstrated experimentally. Predictions of A-weighted excess attenuation for a traffic noise spectrum are made illustrating the effects of varying the depth of the cutting and the absorbency of the surrounding ground surface.

The combined effects of porous asphalt surfacing and barriers on traffic noise

There is considerable interest in the use of porous asphalt (PA) surfacing on highways since physical and subjective assessments of noise have indicated a significant advantage over conventional non-porous surfaces such as hot rolled asphalt (HRA) used widely for motorway surfacing in the UK. However, it was not known whether the benefit of the PA surface was affected by the presence of roadside barriers. Noise predictions have been made using the Boundary Element Method (BEM) approach to determine the extent to which the noise reducing benefits of PA could be added to the screening effects of noise barriers in order to obtain the overall reduction in noise levels

Influence of shape and absorbing surface: a numerical study of railway noise barriers

Results are presented of a study of a performance of various track-side railway noise barriers, determined by using a two- dimensional numerical boundary element model. The basic model uses monopole sources and has been adapted to allow the sources to exhibit dipole-type radiation characteristics. A comparison of boundary element predictions of the performance of simple barriers and vehicle shapes is made with results obtained by using the standard U.K. prediction method. The results obtained from the numerical model indicate that modifying the source to exhibit dipole characteristics becomes more significant as the height of the barrier increases, and suggest that for any particular shape, absorbent barriers provide much better screening efficiency than the rigid equivalent. The cross-section of the rolling stock significantly affects the performance of rigid barriers. If the position of the upper edge is fixed, the results suggest that simple absorptive barriers provide more effective screening than tilted barriers. The addition of multiple edges to a barrier provides additional insertion loss without any increase in barrier height.

Multiple-edge noise barriers

A numerical model using boundary element techniques is discussed which enables the insertion loss for various noise barriers of complex profile and surface cover to be calculated. The model is applied to single-foundation noise barriers to which additional side-panels are added to create fork-like profiles. Spectra of insertion loss and mean insertion loss results over a range of receiver positions for a broadband source are presented. It is concluded that ‘multiple-edged’ barriers show a significant increase in acoustic-efficiency over a simple vertical screen. Adding lightweight side-panels would be a relatively inexpensive measure, and one which could be applied to barriers already in existence. This type of barrier would also allow the height of the construction to be kept to a minimum.

Random Prism: a noise-tolerant alternative to Random Forests

Ensemble learning can be used to increase the overall classification accuracy of a classifier by generating multiple base classifiers and combining their classification results. A frequently used family of base classifiers for ensemble learning are decision trees. However, alternative approaches can potentially be used, such as the Prism family of algorithms that also induces classification rules. Compared with decision trees, Prism algorithms generate modular classification rules that cannot necessarily be represented in the form of a decision tree. Prism algorithms produce a similar classification accuracy compared with decision trees. However, in some cases, for example, if there is noise in the training and test data, Prism algorithms can outperform decision trees by achieving a higher classification accuracy. However, Prism still tends to overfit on noisy data; hence, ensemble learners have been adopted in this work to reduce the overfitting. This paper describes the development of an ensemble learner using a member of the Prism family as the base classifier to reduce the overfitting of Prism algorithms on noisy datasets. The developed ensemble classifier is compared with a stand-alone Prism classifier in terms of classification accuracy and resistance to noise.

Polynomial-based noise variance estimation for MIMO-SCBT systems

In this paper, we present a polynomial-based noise variance estimator for multiple-input multiple-output single-carrier block transmission (MIMO-SCBT) systems. It is shown that the optimal pilots for noise variance estimation satisfy the same condition as that for channel estimation. Theoretical analysis indicates that the proposed estimator is statistically more efficient than the conventional sum of squared residuals (SSR) based estimator. Furthermore, we obtain an efficient implementation of the estimator by exploiting its special structure. Numerical results confirm our theoretical analysis.

Squirmish at the Oasis: an evening of performance and rant hosted by Agency of Noise at the Kinsgate Workshsops Trust in affiliation with Camden Arts Centre

Squirmish at the Oasis takes its name from Luigi Russolo's fourth noise network 'Skirmish at the Oasis' performed in Milan in 1913. 100 years on the Agency of Noise contemplate changes in technology and the culture industry that provoke new questions around the deliberate use of noise within music and art. Through live acts of enquiry and experimentation five artists unravel paradoxes associated with the use of noise in art, music and the gallery space. The works challenge tensions, contradictions and possible oxymorons that emerge through the use and acceptance of noise within an artistic framework. Featuring: DAISY DIXON / GRAHAM DUNNING / POLLYFIBRE / DANE SUTHERLAND / MARNIE WATTS

Effects of noise and by-catch on a Danish harbour porpoise population

Ships and wind turbines generate noise, which can have a negative impact on marine mammal populations by scaring animals away. Effective modelling of how this affects the populations has to take account of the location and timing of disturbances. Here we construct an individual-based model of harbour porpoises in the Inner Danish Waters. Individuals have their own energy budgets constructed using established principles of physiological ecology. Data are lacking on the spatial distribution of food which is instead inferred from knowledge of time-varying porpoise distributions. The model produces plausible patterns of population dynamics and matches well the age distribution of porpoises caught in by-catch. It estimates the effect of existing wind farms as a 10% reduction in population size when food recovers fast (after two days). Proposed new wind farms and ships do not result in further population declines. The population is however sensitive to variations in mortality resulting from by-catch and to the speed at which food recovers after being depleted. If food recovers slowly the effect of wind turbines becomes negligible, whereas ships are estimated to have a significant negative impact on the population. Annual by-catch rates ≥10% lead to monotonously decreasing populations and to extinction, and even the estimated by-catch rate from the adjacent area (approximately 4.1%) has a strong impact on the population. This suggests that conservation efforts should be more focused on reducing by-catch in commercial gillnet fisheries than on limiting the amount of anthropogenic noise. Individual-based models are unique in their ability to take account of the location and timing of disturbances and to show their likely effects on populations. The models also identify deficiencies in the existing database and can be used to set priorities for future field research.

Reducing noise associated with the Monte Carlo Independent Column Approximation for weather forecasting models

The Monte Carlo Independent Column Approximation (McICA) is a flexible method for representing subgrid-scale cloud inhomogeneity in radiative transfer schemes. It does, however, introduce conditional random errors but these have been shown to have little effect on climate simulations, where spatial and temporal scales of interest are large enough for effects of noise to be averaged out. This article considers the effect of McICA noise on a numerical weather prediction (NWP) model, where the time and spatial scales of interest are much closer to those at which the errors manifest themselves; this, as we show, means that noise is more significant. We suggest methods for efficiently reducing the magnitude of McICA noise and test these methods in a global NWP version of the UK Met Office Unified Model (MetUM). The resultant errors are put into context by comparison with errors due to the widely used assumption of maximum-random-overlap of plane-parallel homogeneous cloud. For a simple implementation of the McICA scheme, forecasts of near-surface temperature are found to be worse than those obtained using the plane-parallel, maximum-random-overlap representation of clouds. However, by applying the methods suggested in this article, we can reduce noise enough to give forecasts of near-surface temperature that are an improvement on the plane-parallel maximum-random-overlap forecasts. We conclude that the McICA scheme can be used to improve the representation of clouds in NWP models, with the provision that the associated noise is sufficiently small.