Fusing data-mining and knowledge elicitation for the supervisory control of an aluminium plate mill

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process.

Changing Standards? Children's awareness and knowledge of features of written standard English at ages 10-11

This paper reports the findings of a small-scale research project, which investigated the levels of awareness and knowledge of written standard English of 10- and 11-year-old children in two English primary schools over a six-year period, coinciding with the implementation in the schools of the National Literacy Strategy (NLS). A questionnaire was used to provide quantitative and qualitative data relating to: features of writing which were recognised as standard or non-standard; children's understanding of technical terminology; variations between boys' and girls' performance; and the impact of the NLS over time. The findings reveal variations in levels of recognition of different non-standard features, differences between girls' and boys' recognition, possible examples of language change, but no evidence of a positive impact of the NLS. The implications of these findings are discussed both in terms of changes in educational standards and changes to standard English.

Changing standards revisited: children’s awareness and knowledge of features of written standard English at ages 10-11

This paper reports the findings of a small-scale research project which investigated the levels of awareness and knowledge of written standard English of 10 and 11 year old children in two English primary schools. The project involved repeating in 2010 a written questionnaire previously used with children in the same schools in three separate surveys in 1999, 2002 and 2005. Data from the latest survey are compared to those from the previous three. The analysis seeks to identify any changes over time in children’s ability to recognise non-standard forms and supply standard English alternatives, as well as their ability to use technical terms related to language variation. Differences between the performance of boys and girls and that of the two schools are also analysed. The paper concludes that the socio-economic context of the schools may be a more important factor than gender in variations over time identified in the data.

Homogeneous and heterogeneous distributed classification for pocket data mining

Pocket Data Mining (PDM) describes the full process of analysing data streams in mobile ad hoc distributed environments. Advances in mobile devices like smart phones and tablet computers have made it possible for a wide range of applications to run in such an environment. In this paper, we propose the adoption of data stream classification techniques for PDM. Evident by a thorough experimental study, it has been proved that running heterogeneous/different, or homogeneous/similar data stream classification techniques over vertically partitioned data (data partitioned according to the feature space) results in comparable performance to batch and centralised learning techniques.

Interface vulnerability and knowledge of the subjunctive/indicative distinction with negated epistemic predicates in L2 Spanish.

Much recent research in SLA is guided by the hypothesis of L2 interface vulnerability (see Sorace 2005). This study contributes to this general project by examining the acquisition of two classes of subjunctive complement clauses in L2 Spanish: subjunctive complements of volitional predicates (purely syntactic) and subjunctive vs. indicative complements with negated epistemic matrix predicates, where the mood distinction is discourse dependent (thus involving the syntax-discourse interface). We provide an analysis of the volitional subjunctive in English and Spanish, suggesting that English learners of L2 Spanish need to access the functional projection Mood P and an uninterpretable modal feature on the Force head available to them from their formal English register grammar, and simultaneously must unacquire the structure of English for-to clauses. For negated epistemic predicates, our analysis maintains that they need to revalue the modal feature on the Force head from uninterpretable to interpretable, within the L2 grammar.With others (e.g. Borgonovo & Prévost 2003; Borgonovo, Bruhn de Garavito & Prévost 2005) and in line with Sorace's (2000, 2003, 2005) notion of interface vulnerability, we maintain that the latter case is more difficult for L2 learners, which is borne out in the data we present. However, the data also show that the indicative/subjunctive distinction with negated epistemics can be acquired by advanced stages of acquisition, questioning the notion of obligatory residual optionality for all properties which require the integration of syntactic and discourse information.

Are informed citizens more trusting? Transparency of performance data and trust towards a British police force

In Britain, substantial cuts in police budgets alongside controversial handling of incidents such as politically sensitive enquiries, public disorder and relations with the media have recently triggered much debate about public knowledge and trust in the police. To date, however, little academic research has investigated how knowledge of police performance impacts citizens’ trust. We address this long-standing lacuna by exploring citizens’ trust before and after exposure to real performance data in the context of a British police force. The results reveal that being informed of performance data affects citizens’ trust significantly. Furthermore, direction and degree of change in trust are related to variations across the different elements of the reported performance criteria. Interestingly, the volatility of citizens’ trust is related to initial performance perceptions (such that citizens with low initial perceptions of police performance react more significantly to evidence of both good and bad performance than citizens with high initial perceptions), and citizens’ intentions to support the police do not always correlate with their cognitive and affective trust towards the police. In discussing our findings, we explore the implications of how being transparent with performance data can both hinder and be helpful in developing citizens’ trust towards a public organisation such as the police. From our study, we pose a number of ethical challenges that practitioners face when deciding what data to highlight, to whom, and for what purpose.

Assessing species’ habitat associations from occurrence records, standardised monitoring data and expert opinion: a test with British butterflies

Accurate knowledge of species’ habitat associations is important for conservation planning and policy. Assessing habitat associations is a vital precursor to selecting appropriate indicator species for prioritising sites for conservation or assessing trends in habitat quality. However, much existing knowledge is based on qualitative expert opinion or local scale studies, and may not remain accurate across different spatial scales or geographic locations. Data from biological recording schemes have the potential to provide objective measures of habitat association, with the ability to account for spatial variation. We used data on 50 British butterfly species as a test case to investigate the correspondence of data-derived measures of habitat association with expert opinion, from two different butterfly recording schemes. One scheme collected large quantities of occurrence data (c. 3 million records) and the other, lower quantities of standardised monitoring data (c. 1400 sites). We used general linear mixed effects models to derive scores of association with broad-leaf woodland for both datasets and compared them with scores canvassed from experts. Scores derived from occurrence and abundance data both showed strongly positive correlations with expert opinion. However, only for occurrence data did these fell within the range of correlations between experts. Data-derived scores showed regional spatial variation in the strength of butterfly associations with broad-leaf woodland, with a significant latitudinal trend in 26% of species. Sub-sampling of the data suggested a mean sample size of 5000 occurrence records per species to gain an accurate estimation of habitat association, although habitat specialists are likely to be readily detected using several hundred records. Occurrence data from recording schemes can thus provide easily obtained, objective, quantitative measures of habitat association.

Serving GODAE Data and Products to the Ocean Community

The Global Ocean Data Assimilation Experiment (GODAE [http:// www.godae.org]) has spanned a decade of rapid technological development. The ever-increasing volume and diversity of oceanographic data produced by in situ instruments, remote-sensing platforms, and computer simulations have driven the development of a number of innovative technologies that are essential for connecting scientists with the data that they need. This paper gives an overview of the technologies that have been developed and applied in the course of GODAE, which now provide users of oceanographic data with the capability to discover, evaluate, visualize, download, and analyze data from all over the world. The key to this capability is the ability to reduce the inherent complexity of oceanographic data by providing a consistent, harmonized view of the various data products. The challenges of data serving have been addressed over the last 10 years through the cooperative skills and energies of many individuals.

Monitoring changes in precipitation and radiative energy using satellite data and climate models

Current changes in the tropical hydrological cycle, including water vapour and precipitation, are presented over the period 1979-2008 based on a diverse suite of observational datasets and atmosphere-only climate models. Models capture the observed variability in tropical moisture while reanalyses cannot. Observed variability in precipitation is highly dependent upon the satellite instruments employed and only cursory agreement with model simulations, primarily relating to the interannual variability associated with the El Niño Southern Oscillation. All datasets display a positive relationship between precipitation and surface temperature but with a large spread. The tendency for wet, ascending regions to become wetter at the expense of dry, descending regimes is in general reproduced. Finally, the frequency of extreme precipitation is shown to rise with warming in the observations and for the model ensemble mean but with large spread in the model simulations. The influence of the Earth’s radiative energy balance in relation to changes in the tropical water cycle are discussed

Chess endgames: 6-man data and strategy

While Nalimov’s endgame tables for Western Chess are the most used today, their Depth-to-Mate metric is not the most efficient or effective in use. The authors have developed and used new programs to create tables to alternative metrics and recommend better strategies for endgame play.