Influence of diurnal and seasonal temperature variations on the detection of corrosion in reinforced concrete by acoustic emission

Chloride rich reinforced concrete prisms were coupled to chloride-free prisms and exposed to diurnal and seasonal temperature cycles typical of those found in the UK. Acoustic emissions (AE) and galvanic currents were continuously monitored and correlated with ambient temperature. AE and galvanic currents were found to emulate the evolution of temperature in the diurnal cycles, although no specific relationship between AE and galvanic current could be obtained. The influence of seasonal variations in galvanic current had no obvious influence on AE Energy per second over the range of corrosion rates studied. The findings suggest that AE is more sensitive to short term (diurnal) changes in corrosion rates than the longer (seasonal) effects. It was hypothesised that this is due to transitory changes in the internal microclimate of the concrete.     

Evolution-in-materio: solving computational problems using carbon nanotube–polymer composites

Evolution-in-materio uses evolutionary algorithms to exploit properties of materials to solve computational problems without requiring a detailed understanding of such properties. We show that using a purpose-built hardware platform called Mecobo, it is possible to solve computational problems by evolving voltages and signals applied to an electrode array covered with a carbon nanotube–polymer composite. We demonstrate for the first time that this methodology can be applied to function optimization and also to the tone discriminator problem (TDP). For function optimization, we evaluate the approach on a suite of optimization benchmarks and obtain results that in some cases come very close to the global optimum or are comparable with those obtained using well-known software-based evolutionary approach. We also obtain good results in comparison with prior work on the tone discriminator problem. In the case of the TDP we also investigated the relative merits of different mixtures of materials and organizations of electrode array.     

Hierarchical classification in text mining for sentiment analysis of online news

Sentiment analysis in text mining is a challenging task. Sentiment is subtly reflected by the tone and affective content of a writer’s words. Conventional text mining techniques, which are based on keyword frequencies, usually run short of accurately detecting such subjective information implied in the text. In this paper, we evaluate several popular classification algorithms, along with three filtering schemes. The filtering schemes progressively shrink the original dataset with respect to the contextual polarity and frequent terms of a document. We call this approach “hierarchical classification”. The effects of the approach in different combination of classification algorithms and filtering schemes are discussed over three sets of controversial online news articles where binary and multi-class classifications are applied. Meanwhile we use two methods to test this hierarchical classification model, and also have a comparison of the two methods.     

Experimental study of stable surfaces for anti-slug control in multi-phase flow

Severe slugging flow is always challenging in oil & gas production, especially for the current offshore based production. The slugging flow can cause a lot of problems, such as those relevant to production safety, fatigue as well as capability. As one typical phenomenon in multi-phase flow dynamics, the slug can be avoided or eliminated by proper facility design or control of operational conditions. Based on a testing facility which can emulate a pipeline-riser or a gas-lifted production well in a scaled-down manner, this paper experimentally studies the correlations of key operational parameters with severe slugging flows. These correlations are reflected through an obtained stable surface in the parameter space, which is a natural extension of the bifurcation plot. The maximal production opportunity without compromising the stability is also studied. Relevant studies have already showed that the capability, performance and efficiency of anti-slug control can be dramatically improved if these stable surfaces can be experimentally determined beforehand. The paper concludes that obtaining the stable surface on the new developed map can significantly improve the production rate in a control scheme. Even though the production rate can be further improved by moving the stable surface using advanced control strategies, the constant inputs can in some cases be preferable due to the easier implementation.     

Physically Meaningful Rendering using Tristimulus Colours

In photorealistic image synthesis the radiative transfer equation is often not solved by simulating every wavelength of light, but instead by computing tristimulus transport, for instance using sRGB primaries as a basis. This choice is convenient, because input texture data is usually stored in RGB colour spaces. However, there are problems with this approach which are often overlooked or ignored. By comparing to spectral reference renderings, we show how rendering in tristimulus colour spaces introduces colour shifts in indirect light, violation of energy conservation, and unexpected behaviour in participating media. Furthermore, we introduce a fast method to compute spectra from almost any given XYZ input colour. It creates spectra that match the input colour precisely. Additionally, like in natural reflectance spectra, their energy is smoothly distributed over wide wavelength bands. This method is both useful to upsample RGB input data when spectral transport is used and as an intermediate step for corrected tristimulus‐based transport. Finally, we show how energy conservation can be enforced in RGB by mapping colours to valid reflectances.     

Future Proof: The Transition to Digital at IFI Archive

Informed by research over the past two years and the work of colleagues in peer institutions, the IFI Irish Film Archive developed a six-year Digital Preservation and Access strategy which launched in 2014. Fundamental to this Strategy was the design and installation of digital archive tools for long term preservation and the redesign of workflow practices to facilitate accession and management of high resolution digital film and broadcast assets and associated metadata. This article outlines the steps taken and standards applied in developing a future proof digital audiovisual archive.     

The structure and content of programming knowledge: Disentangling training and language effects in theories of skill development

This article reviews the extensive literature emerging from studies concerned with skill acquisition and the development of knowledge representation in programming. In particular, it focuses upon theories of program comprehension that suggest programming knowledge can be described in terms of stereotypical knowledge structures that can in some way capture programming expertise independently of the programming language used and in isolation from a programmer's specific training experience. An attempt is made to demonstrate why existing views are inappropriate. On the one hand, programs are represented in terms of a variety of formal notations ranging from the quasi‐mathematical to the near textual. It is argued that different languages may lead to different forms of knowledge representation, perhaps emphasizing certain structures at the expense of others or facilitating particular strategies. On the other hand, programmers are typically taught problem‐solving techniques that suggest a strict approach to problem decomposition. Hence, it seems likely that another factor that may mediate the development of knowledge representation, and that has not received significant attention elsewhere, is related to the training experience that programmers typically encounter. In this article, recent empirical studies that have addressed these issues are reviewed, and the implications of these studies for theories of skill acquisition and for knowledge representation are discussed. In conclusion, a more extensive account of knowledge representation in programming is presented that emphasizes training effects and the role played by specific language features in the development of knowledge representation within the programming domain.     

Twenty years of artificial life art

This essay begins with discussion of four relatively recent works which are representative of major themes and preoccupations in Artificial Life Art: ‘Propagaciones’ by Leo Nuñez; ‘Sniff’ by Karolina Sobecka and Jim George; ‘Universal Whistling Machine’ by Marc Boehlen; and ‘Performative Ecologies’ by Ruari Glynn. This essay is an attempt to contextualise these works by providing an overview of the history and forms of Artificial Life Art as it has developed over two decades, along with some background in the ideas of the Artificial Life movement of the late 1980s and 1990s.1 A more extensive study of the theoretical history of Artificial Life can be found in my paper ‘Artificial Life Art—A Primer’, in the Proceedings of DAC09 and also at http://www.ace.uci.edu/Penny. Excerpts from that essay are included here.      

Using space windowing for a preliminary analysis of complex time data in human component system studies. Examples with eye-tracking in advertising and car/head movements in driving

Empirical studies of human systems often involve recording multidimensional signals because the system components may require physical measurements (e.g., temperature, pressure, body movements and/or movements in the environment) and physiological measurements (e.g., electromyography or electrocardiography). Analysis of such data becomes complex if both the multifactor aspect and the multivariate aspect are retained. Three examples are used to illustrate the role of fuzzy space windowing and the large number of data analysis paths. The first example is a classic simulated data set found in the literature, which we use to compare several data analysis paths generated with principal component analysis and multiple correspondence analysis with crisp and fuzzy windowing. The second example involves eye-tracking data based on advertising, with a focus on the case of one category variable, but with the possibility of several space windowing models and time entities. The third example concerns car and head movement data from a driving vigilance study, with a focus on the case involving several quantitative variables. The notions of analysis path multiplicity and information are discussed both from a general perspective and in terms of our two real examples.