Nonlinear identification using orthogonal forward regression with nested optimal regularization

An efficient data based-modeling algorithm for nonlinear system identification is introduced for radial basis function (RBF) neural networks with the aim of maximizing generalization capability based on the concept of leave-one-out (LOO) cross validation. Each of the RBF kernels has its own kernel width parameter and the basic idea is to optimize the multiple pairs of regularization parameters and kernel widths, each of which is associated with a kernel, one at a time within the orthogonal forward regression (OFR) procedure. Thus, each OFR step consists of one model term selection based on the LOO mean square error (LOOMSE), followed by the optimization of the associated kernel width and regularization parameter, also based on the LOOMSE. Since like our previous state-of-the-art local regularization assisted orthogonal least squares (LROLS) algorithm, the same LOOMSE is adopted for model selection, our proposed new OFR algorithm is also capable of producing a very sparse RBF model with excellent generalization performance. Unlike our previous LROLS algorithm which requires an additional iterative loop to optimize the regularization parameters as well as an additional procedure to optimize the kernel width, the proposed new OFR algorithm optimizes both the kernel widths and regularization parameters within the single OFR procedure, and consequently the required computational complexity is dramatically reduced. Nonlinear system identification examples are included to demonstrate the effectiveness of this new approach in comparison to the well-known approaches of support vector machine and least absolute shrinkage and selection operator as well as the LROLS algorithm.

Looking back, moving forward: drama, disability and social justice

The aim of this chapter is to briefly outline how disability has been represented in theatre, what access disabled people have had to drama and theatre in the past, and what might be achieved in the pursuit of social justice with young people in relation to awareness of and provision for disability. It will focus in particular on how disability has been addressed in drama education and what assumptions have been made regarding drama and disability in education. In considering such issues one might perceive manifestations of what Freebody and Finneran (2013) recognise as an overlapping and ‘somewhat artificially created dichotomy between drama for social justice and drama about social justice.’ This chapter will examine some examples of how drama has been used to give students in mainstream schools insights into disability, and the philosophy that underpins the drama curriculum of one special school where the focus is on drama as social justice: the argument being that in some cases simply doing drama is, in effect, a manifestation of social justice. Finally, some of the progress made in recent years regarding access and engagement will be addressed through specific reference to the authors’ on-going work into ‘performing social research’ (Shah, 2013) and how theatres are increasingly attempting to give more access to disabled young people and their families by offering ‘relaxed performances.’

One step forward, and two steps back: women and career progression in academia during times of uncertainty

While there is an extensive and still growing body of literature on women in academia and the challenges they encounter in career progression, there is little research on their experience specifically within a business school setting. In this study, we attempt to address this gap and examine the experiences and career development of female academics in a business school and how these are impacted by downsizing programmes. To this end, an exploratory case study is conducted. The findings of this study show that female business school academics experience numerous challenges in terms of promotion and development, networking, and the multiple and conflicting demands placed upon them. As a result, the lack of visibility seems to be a pertinent issue in terms of their career progression. Our data also demonstrates that that, paradoxically, during periods of downsizing women become more visible and thus vulnerable to layoffs as a consequence of the challenges and pressures created in their environment during this process. In this paper, we argue that this heightened visibility, and being subject to possible layoffs, further reproduces inequality regimes in academia.

Electricity derivatives pricing with forward-looking information

In order to increase overall transparency on key operational information, power transmission system operators publish an increasing amount of fundamental data, including forecasts of electricity demand and available capacity. We employ a fundamental model for electricity prices which lends itself well to integrating such forecasts, while retaining ease of implementation and tractability to allow for analytic derivatives pricing formulae. In an extensive futures pricing study, the pricing performance of our model is shown to further improve based on the inclusion of electricity demand and capacity forecasts, thus confirming the general importance of forward-looking information for electricity derivatives pricing. However, we also find that the usefulness of integrating forecast data into the pricing approach is primarily limited to those periods during which electricity prices are highly sensitive to demand or available capacity, whereas the impact is less visible when fuel prices are the primary underlying driver to prices instead.

The EarthCARE satellite: the next step forward in global measurements of clouds, aerosols, precipitation, and radiation

The collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s cloud profiling radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle, and raindrop fall speeds. EarthCARE’s 355-nm high-spectral-resolution lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The multispectral imager will provide a context for, and the ability to construct, the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross section. The consistency of the retrievals will be assessed to within a target of ±10 W m–2 on the (10 km)2 scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.

Health in Brazil 6 Health conditions and health-policy innovations in Brazil: the way forward

Brazil is a large complex country that is undergoing rapid economic, social, and environmental change In this Series of six articles, we have reported important improvements in health status and life expectancy, which can be ascribed largely to progress in social determinants of health and to implementation of a comprehensive national health system with strong social participation. Many challenges remain, however. Socioeconomic and regional disparities are still unacceptably large, reflecting the fact that much progress is still needed to improve basic living conditions for a large proportion of the population. New health problems arise as a result of urbanisation and social and environmental change, and some old health issues remain unabated. Administration of a complex, decentralised public-health system, in which a large share of services is contracted out to the private sector, together with many private insurance providers, inevitably causes conflict and contradiction. The challenge is ultimately political, and we conclude with a call for action that requires continuous engagement by Brazilian society as a whole in securing the right to health for all Brazilian people.

Looking for intrinsic charm in the forward region at BNL RHIC and CERN LHC

The complete understanding of the basic constituents of hadrons and the hadronic dynamics at high energies are two of the main challenges for the theory of strong interactions. In particular, the existence of intrinsic heavy quark components in the hadron wave function must be confirmed (or disproved). In this paper we propose a new mechanism for the production of D-mesons at forward rapidities based on the Color Glass Condensate (CGC) formalism and demonstrate that the resulting transverse momentum spectra are strongly dependent on the behavior of the charm distribution at large Bjorken x. Our results show clearly that the hypothesis of intrinsic charm can be tested in pp and p(d)A collisions at RHIC and LHC. (C) 2010 Elsevier B.V. All rights reserved.

Center of mass energy and system-size dependence of photon production at forward rapidity at RHIC

We present the multiplicity and pseudorapidity distributions of photons produced in Au + Au and Cu + Cu collisions at root(s)NN = 62.4 and 200 GeV. The photons are measured in the region -3.7 < eta < -2.3 using the photon Multiplicity detector in the STAR experiment at RHIC. The number of photons produced per average number of participating nucleon pairs increases with the beam energy and is independent of (lie collision centrality. For collisions with similar average numbers of participating nucleons the photon multiplicities are observed to be similar for An + Au and Cu + Cu collisions at a given beam energy. The ratios of the number of charged particles to photons in the measured pseudorapidity range are found to be 1.4 +/- 0.1 and 1.2 +/- 0.1 for root(s)NN = 62.4 and 200 GeV, respectively. The energy dependence of this ratio could reflect varying contributions from baryons to charged particles, while mesons are the dominant contributors to photon production in the given kinematic region. The photon pseudorapidity distributions normalized by average number of participating nucleon pairs, when plotted as a function of eta-Y(beam), are found to follow a longitudinal scaling independent of centrality and colliding ion species at both beam energies. (C) 2009 Elsevier B.V. All rights reserved.

The influence of ARIMA-GARCH parameters in feed forward neural networks prediction

The objective of this article is to find out the influence of the parameters of the ARIMA-GARCH models in the prediction of artificial neural networks (ANN) of the feed forward type, trained with the Levenberg-Marquardt algorithm, through Monte Carlo simulations. The paper presents a study of the relationship between ANN performance and ARIMA-GARCH model parameters, i.e. the fact that depending on the stationarity and other parameters of the time series, the ANN structure should be selected differently. Neural networks have been widely used to predict time series and their capacity for dealing with non-linearities is a normally outstanding advantage. However, the values of the parameters of the models of generalized autoregressive conditional heteroscedasticity have an influence on ANN prediction performance. The combination of the values of the GARCH parameters with the ARIMA autoregressive terms also implies in ANN performance variation. Combining the parameters of the ARIMA-GARCH models and changing the ANN`s topologies, we used the Theil inequality coefficient to measure the prediction of the feed forward ANN.

The forward- and the equity-premium puzzles: two symptoms of the same illness?

In this paper we revisit the relationship between the equity and the forward premium puzzles. We construct return-based stochastic discount factors under very mild assumptions and check whether they price correctly the equity and the foreign currency risk premia. We avoid log-linearizations by using moments restrictions associated with euler equations to test the capacity of our return-based stochastic discount factors to price returns on the relevant assets. Our main finding is that a pricing kernel constructed only using information on American domestic assets accounts for both domestic and international stylized facts that escape consumption based models. In particular, we fail to reject the null hypothesis that the foreign currency risk premium has zero price when the instrument is the own current value of the forward premium.