The ethics, aesthetics and practical politics of ownership in co-creative media

What is ‘best practice’ when it comes to managing intellectual property rights in participatory media content? As commercial media and entertainment business models have increasingly come to rely upon the networked productivity of end-users (Banks and Humphreys 2008) this question has been framed as a problem of creative labour made all the more precarious by changing employment patterns and work cultures of knowledge-intensive societies and globalising economies (Banks, Gill and Taylor 2014). This paper considers how the problems of ownership are addressed in non-commercial, community-based arts and media contexts. Problems of labour are also manifest in these contexts (for example, reliance on volunteer labour and uncertain economic reward for creative excellence). Nonetheless, managing intellectual property rights in collaborative creative works that are created in community media and arts contexts is no less challenging or complex than in commercial contexts. This paper takes as its focus a particular participatory media practice known as ‘digital storytelling’. The digital storytelling method, formalised by the Centre for Digital Storytelling (CDS) from the mid-1990s, has been internationally adopted and adapted for use in an open-ended variety of community arts, education, health and allied services settings (Hartley and McWilliam 2009; Lambert 2013; Lundby 2008; Thumin 2012). It provides a useful point of departure for thinking about a range of collaborative media production practices that seek to address participation ‘gaps’ (Jenkins 2006). However the outputs of these activities, including digital stories, cannot be fully understood or accurately described as user-generated content. For this reason, digital storytelling is taken here to belong to a category of participatory media activity that has been described as ‘co-creative’ media (Spurgeon 2013) in order to improve understanding of the conditions of mediated and mediatized participation (Couldry 2008). This paper reports on a survey of the actual copyrighting practices of cultural institutions and community-based media arts practitioners that work with digital storytelling and similar participatory content creation methods. This survey finds that although there is a preference for Creative Commons licensing a great variety of approaches are taken to managing intellectual property rights in co-creative media. These range from the use of Creative Commons licences (for example, Lambert 2013, p.193) to retention of full copyrights by storytellers, to retention of certain rights by facilitating organisations (for example, broadcast rights by community radio stations and public service broadcasters), and a range of other shared rights arrangements between professional creative practitioners, the individual storytellers and communities with which they collaborate, media outlets, exhibitors and funders. This paper also considers how aesthetic and ethical considerations shape responses to questions of intellectual property rights in community media arts contexts. For example, embedded in the CDS digital storytelling method is ‘a critique of power and the numerous ways that rank is unconsciously expressed in engagements between classes, races and gender’ (Lambert 117). The CDS method privileges the interests of the storyteller and, through a transformative workshop process, aims to generate original individual stories that, in turn, reflect self-awareness of ‘how much the way we live is scripted by history, by social and cultural norms, by our own unique journey through a contradictory, and at times hostile, world’ (Lambert 118). Such a critical approach is characteristic of co-creative media practices. It extends to a heightened awareness of the risks of ‘story theft’ and the challenges of ownership and informs ideas of ‘best practice’ amongst creative practitioners, teaching artists and community media producers, along with commitments to achieving equitable solutions for all participants in co-creative media practice (for example, Lyons-Reid and Kuddell nd.). Yet, there is surprisingly little written about the challenges of managing intellectual property produced in co-creative media activities. A dialogic sense of ownership in stories has been identified as an indicator of successful digital storytelling practice (Hayes and Matusov 2005) and is helpful to grounding the more abstract claims of empowerment for social participation that are associated with co-creative methods. Contrary to the ‘change from below’ philosophy that underpins much thinking about co-creative media, however, discussions of intellectual property usually focus on how methods such as digital storytelling contribute to the formation of copyright law-compliant subjects, particularly when used in educational settings (for example, Ohler nd.). This also exposes the reliance of co-creative methods on the creative assets storytellers (rather than on the copyrighted materials of the media cultures of storytellers) as a pragmatic response to the constraints that intellectual property right laws impose on the entire category of participatory media. At the level of practical politics, it also becomes apparent that co-creative media practitioners and storytellers located in copyright jurisdictions governed by ‘fair use’ principles have much greater creative flexibility than those located in jurisdictions governed by ‘fair dealing’ principles.

Higher order spectra based support vector machine for arrhythmia classification

Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. HRV analysis is an important tool to observe the heart’s ability to respond to normal regulatory impulses that affect its rhythm. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. A computer-based arrhythmia detection system of cardiac states is very useful in diagnostics and disease management. In this work, we studied the identification of the HRV signals using features derived from HOS. These features were fed to the support vector machine (SVM) for classification. Our proposed system can classify the normal and other four classes of arrhythmia with an average accuracy of more than 85%.

A new approach to spatial data interpolation using higher-order statistics

Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use first- and second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental phenomena tend to be very complex, presenting non-Gaussian distribution and/or non-linear inter-variable relationship. This paper proposes a new approach to the interpolation of spatial data, which can be applied with great flexibility. Suitable cross-variable higher-order spatial statistics are developed to measure the spatial relationship between the random variable at an unsampled location and those in its neighbourhood. Given the computed cross-variable higher-order spatial statistics, the conditional probability density function (CPDF) is approximated via polynomial expansions, which is then utilized to determine the interpolated value at the unsampled location as an expectation. In addition, the uncertainty associated with the interpolation is quantified by constructing prediction intervals of interpolated values. The proposed method is applied to a mineral deposit dataset, and the results demonstrate that it outperforms kriging methods in uncertainty quantification. The introduction of the cross-variable higher-order spatial statistics noticeably improves the quality of the interpolation since it enriches the information that can be extracted from the observed data, and this benefit is substantial when working with data that are sparse or have non-trivial dependence structures.

Using upper bounds on attainable discrimination to select discrete valued features

Selection of features that will permit accurate pattern classification is a difficult task. However, if a particular data set is represented by discrete valued features, it becomes possible to determine empirically the contribution that each feature makes to the discrimination between classes. This paper extends the discrimination bound method so that both the maximum and average discrimination expected on unseen test data can be estimated. These estimation techniques are the basis of a backwards elimination algorithm that can be use to rank features in order of their discriminative power. Two problems are used to demonstrate this feature selection process: classification of the Mushroom Database, and a real-world, pregnancy related medical risk prediction task - assessment of risk of perinatal death.

Compensation for higher order mode coupling between inclined coupling slots and radiating slots in planar slotted waveguide arrays

Summary form only given. Geometric simplicity, efficiency and polarization purity make slot antenna arrays ideal solutions for many radar, communications and navigation applications, especially when high power, light weight and limited scan volume are priorities. Resonant arrays of longitudinal slots have a slot spacing of one-half guide wavelength at the design frequency, so that the slots are located at the standing wave peaks. Planar arrays are implemented using a number of rectangular waveguides (branch line guides), arranged side-by-side, while waveguides main lines located behind and at right angles to the branch lines excite the radiating waveguides via centered-inclined coupling slots. Planar slotted waveguide arrays radiate broadside beams and all radiators are designed to be in phase.

Straightforward biodegradable nanoparticle generation through megahertz-order ultrasonic atomization

Simple and reliable formation of biodegradable nanoparticles formed from poly-ε-caprolactone was achieved using 1.645 MHz piston atomization of a source fluid of 0.5% w/v of the polymer dissolved in acetone; the particles were allowed to descend under gravity in air 8 cm into a 1 mM solution of sodium dodecyl sulfate. After centrifugation to remove surface agglomerations, a symmetric monodisperse distribution of particles φ 186 nm (SD=5.7, n=6) was obtained with a yield of 65.2%. © 2006 American Institute of Physics.

A Fixed Order Model Matching Approach for the Design of Robust Power System Oscillation Damper

This book focuses on how evolutionary computing techniques benefit engineering research and development tasks by converting practical problems of growing complexities into simple formulations, thus largely reducing development efforts. This book begins with an overview of the optimization theory and modern evolutionary computing techniques, and goes on to cover specific applications of evolutionary computing to power system optimization and control problems.

Second-order quantile methods for experts and combinatorial games

We aim to design strategies for sequential decision making that adjust to the difficulty of the learning problem. We study this question both in the setting of prediction with expert advice, and for more general combinatorial decision tasks. We are not satisfied with just guaranteeing minimax regret rates, but we want our algorithms to perform significantly better on easy data. Two popular ways to formalize such adaptivity are second-order regret bounds and quantile bounds. The underlying notions of 'easy data', which may be paraphrased as "the learning problem has small variance" and "multiple decisions are useful", are synergetic. But even though there are sophisticated algorithms that exploit one of the two, no existing algorithm is able to adapt to both. In this paper we outline a new method for obtaining such adaptive algorithms, based on a potential function that aggregates a range of learning rates (which are essential tuning parameters). By choosing the right prior we construct efficient algorithms and show that they reap both benefits by proving the first bounds that are both second-order and incorporate quantiles.

Numerical algorithms for time-fractional subdiffusion equation with second-order accuracy

This article aims to fill in the gap of the second-order accurate schemes for the time-fractional subdiffusion equation with unconditional stability. Two fully discrete schemes are first proposed for the time-fractional subdiffusion equation with space discretized by finite element and time discretized by the fractional linear multistep methods. These two methods are unconditionally stable with maximum global convergence order of $O(\tau+h^{r+1})$ in the $L^2$ norm, where $\tau$ and $h$ are the step sizes in time and space, respectively, and $r$ is the degree of the piecewise polynomial space. The average convergence rates for the two methods in time are also investigated, which shows that the average convergence rates of the two methods are $O(\tau^{1.5}+h^{r+1})$. Furthermore, two improved algorithms are constrcted, they are also unconditionally stable and convergent of order $O(\tau^2+h^{r+1})$. Numerical examples are provided to verify the theoretical analysis. The comparisons between the present algorithms and the existing ones are included, which show that our numerical algorithms exhibit better performances than the known ones.

High order unconditionally stable difference schemes for the Riesz space-fractional telegraph equation

In this paper, a class of unconditionally stable difference schemes based on the Pad´e approximation is presented for the Riesz space-fractional telegraph equation. Firstly, we introduce a new variable to transform the original dfferential equation to an equivalent differential equation system. Then, we apply a second order fractional central difference scheme to discretise the Riesz space-fractional operator. Finally, we use (1, 1), (2, 2) and (3, 3) Pad´e approximations to give a fully discrete difference scheme for the resulting linear system of ordinary differential equations. Matrix analysis is used to show the unconditional stability of the proposed algorithms. Two examples with known exact solutions are chosen to assess the proposed difference schemes. Numerical results demonstrate that these schemes provide accurate and efficient methods for solving a space-fractional hyperbolic equation.

Numerical analysis for the time distributed-order and Riesz space fractional diffusions on bounded domains

Subdiffusion equations with distributed-order fractional derivatives describe some important physical phenomena. In this paper, we consider the time distributed-order and Riesz space fractional diffusions on bounded domains with Dirichlet boundary conditions. Here, the time derivative is defined as the distributed-order fractional derivative in the Caputo sense, and the space derivative is defined as the Riesz fractional derivative. First, we discretize the integral term in the time distributed-order and Riesz space fractional diffusions using numerical approximation. Then the given equation can be written as a multi-term time–space fractional diffusion. Secondly, we propose an implicit difference method for the multi-term time–space fractional diffusion. Thirdly, using mathematical induction, we prove the implicit difference method is unconditionally stable and convergent. Also, the solvability for our method is discussed. Finally, two numerical examples are given to show that the numerical results are in good agreement with our theoretical analysis.

A Novel High Order Space-Time Spectral Method for the Time Fractional Fokker--Planck Equation

The fractional Fokker-Planck equation is an important physical model for simulating anomalous diffusions with external forces. Because of the non-local property of the fractional derivative an interesting problem is to explore high accuracy numerical methods for fractional differential equations. In this paper, a space-time spectral method is presented for the numerical solution of the time fractional Fokker-Planck initial-boundary value problem. The proposed method employs the Jacobi polynomials for the temporal discretization and Fourier-like basis functions for the spatial discretization. Due to the diagonalizable trait of the Fourier-like basis functions, this leads to a reduced representation of the inner product in the Galerkin analysis. We prove that the time fractional Fokker-Planck equation attains the same approximation order as the time fractional diffusion equation developed in [23] by using the present method. That indicates an exponential decay may be achieved if the exact solution is sufficiently smooth. Finally, some numerical results are given to demonstrate the high order accuracy and efficiency of the new numerical scheme. The results show that the errors of the numerical solutions obtained by the space-time spectral method decay exponentially.