Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

Intelligent agents and distributed models for cooperative task support

Purpose – To describe some research done, as part of an EPSRC funded project, to assist engineers working together on collaborative tasks. Design/methodology/approach – Distributed finite state modelling and agent techniques are used successfully in a new hybrid self-organising decision making system applied to collaborative work support. For the particular application, analysis of the tasks involved has been performed and these tasks are modelled. The system then employs a novel generic agent model, where task and domain knowledge are isolated from the support system, which provides relevant information to the engineers. Findings – The method is applied in the despatch of transmission commands within the control room of The National Grid Company Plc (NGC) – tasks are completed significantly faster when the system is utilised. Research limitations/implications – The paper describes a generic approach and it would be interesting to investigate how well it works in other applications. Practical implications – Although only one application has been studied, the methodology could equally be applied to a general class of cooperative work environments. Originality/value – One key part of the work is the novel generic agent model that enables the task and domain knowledge, which are application specific, to be isolated from the support system, and hence allows the method to be applied in other domains.

Action observation and robotic agents: learning and anthropomorphism

The ‘action observation network’ (AON), which is thought to translate observed actions into motor codes required for their execution, is biologically tuned: it responds more to observation of human, than non-human, movement. This biological specificity has been taken to support the hypothesis that the AON underlies various social functions, such as theory of mind and action understanding, and that, when it is active during observation of non-human agents like humanoid robots, it is a sign of ascription of human mental states to these agents. This review will outline evidence for biological tuning in the AON, examining the features which generate it, and concluding that there is evidence for tuning to both the form and kinematic profile of observed movements, and little evidence for tuning to belief about stimulus identity. It will propose that a likely reason for biological tuning is that human actions, relative to non-biological movements, have been observed more frequently while executing corresponding actions. If the associative hypothesis of the AON is correct, and the network indeed supports social functioning, sensorimotor experience with non-human agents may help us to predict, and therefore interpret, their movements.

Secondary structure prediction with support vector machines

Motivation: A new method that uses support vector machines (SVMs) to predict protein secondary structure is described and evaluated. The study is designed to develop a reliable prediction method using an alternative technique and to investigate the applicability of SVMs to this type of bioinformatics problem. Methods: Binary SVMs are trained to discriminate between two structural classes. The binary classifiers are combined in several ways to predict multi-class secondary structure. Results: The average three-state prediction accuracy per protein (Q3) is estimated by cross-validation to be 77.07 ± 0.26% with a segment overlap (Sov) score of 73.32 ± 0.39%. The SVM performs similarly to the 'state-of-the-art' PSIPRED prediction method on a non-homologous test set of 121 proteins despite being trained on substantially fewer examples. A simple consensus of the SVM, PSIPRED and PROFsec achieves significantly higher prediction accuracy than the individual methods. Availability: The SVM classifier is available from the authors. Work is in progress to make the method available on-line and to integrate the SVM predictions into the PSIPRED server.

Children with Special Educational Needs as film makers: Using digital video to support Understandings of Narrative

The literature has identified issues around transitions among phases for all pupils (Cocklin, 1999) including pupils with special educational needs (SEN) (Morgan 1999, Maras and Aveling 2006). These issues include pupils’ uncertainties and worries about building size and spatial orientation, exposure to a range of teaching styles, relationships with peers and older pupils as well as parents’ difficulties in establishing effective communications with prospective secondary schools. Research has also identified that interventions to facilitate these educational transitions should consider managerial support, social and personal familiarisation with the new setting as well as personalised learning strategies (BECTA 2004). However, the role that digital technologies can play in supporting these strategies or facilitating the role of the professionals such as SENCos and heads of departments involved in supporting effective transitions for pupils with SEN has not been widely discussed. Uses of ICT include passing references of student-produced media presentations (Higgins 1993) and use of photographs of activities attached to a timetable to support familiarisation with the secondary curriculum for pupils with autism (Cumine et al. 1998).

Exploring business and IT alignment mechanisms: toward a learning perspective

Numerous studies have attempted to develop strategic alignment mechanisms. The strategic alignment mechanism is broken down into two categories namely: strategy process and strategy content. Our review shows that alignment research has been carried out in isolation. We see this as having had the effect of limiting the extent to which executives can understand elements of performance. We confer with a number of researchers in postulating that using a mechanism such as multilevel learning to combine strategy content and strategy process under one metaphor can greatly facilitate, through exploration and exploitation, the understanding not only of human interactions within a firm, but also of the interaction existent between a firm and its environment. The findings in this study further support the idea of integrating strategy process and content to have a better understating of alignment maturity and impact on business performance. It also elaborates the affect of misalignment in companies on performance.

A fast two-grid and finite section method for a class of integral equations on the real line with application to an acoustic scattering problem in the half-plane

We consider the numerical treatment of second kind integral equations on the real line of the form ∅(s) = ∫_(-∞)^(+∞)▒〖κ(s-t)z(t)ϕ(t)dt,s=R〗 (abbreviated ϕ= ψ+K_z ϕ) in which K ϵ L_1 (R), z ϵ L_∞ (R) and ψ ϵ BC(R), the space of bounded continuous functions on R, are assumed known and ϕ ϵ BC(R) is to be determined. We first derive sharp error estimates for the finite section approximation (reducing the range of integration to [-A, A]) via bounds on (1-K_z )^(-1)as an operator on spaces of weighted continuous functions. Numerical solution by a simple discrete collocation method on a uniform grid on R is then analysed: in the case when z is compactly supported this leads to a coefficient matrix which allows a rapid matrix-vector multiply via the FFT. To utilise this possibility we propose a modified two-grid iteration, a feature of which is that the coarse grid matrix is approximated by a banded matrix, and analyse convergence and computational cost. In cases where z is not compactly supported a combined finite section and two-grid algorithm can be applied and we extend the analysis to this case. As an application we consider acoustic scattering in the half-plane with a Robin or impedance boundary condition which we formulate as a boundary integral equation of the class studied. Our final result is that if z (related to the boundary impedance in the application) takes values in an appropriate compact subset Q of the complex plane, then the difference between ϕ(s)and its finite section approximation computed numerically using the iterative scheme proposed is ≤C_1 [kh log⁡〖(1⁄kh)+(1-Θ)^((-1)⁄2) (kA)^((-1)⁄2) 〗 ] in the interval [-ΘA,ΘA](Θ<1) for kh sufficiently small, where k is the wavenumber and h the grid spacing. Moreover this numerical approximation can be computed in ≤C_2 N log⁡N operations, where N = 2A/h is the number of degrees of freedom. The values of the constants C1 and C2 depend only on the set Q and not on the wavenumber k or the support of z.

Implicit learning and imperceptible influence: Syncretic literacy of multilingual Chinese children.

This article reports on an ethnographic study involving the literacy practices of two multilingual Chinese children from two similar yet different cultural and linguistic contexts: Montreal and Singapore. Using syncretism as a theoretical tool, this inquiry examines how family environment and support facilitate children’s process of becoming literate in multiple languages. Informed by sociocultural theory, the inquiry looks in particular at the role of grandparents in the syncretic literacy practices of children. Through comparative analysis, the study reveals similarities and differences that, when considered together, contribute to our understanding of multilingual children’s creative forms of learning with regard to their rich literacy resources in multiple languages, the imperceptible influences of mediators, various learning styles and syncretic literacy practices.

Blended learning in distance education: Sri Lankan perspective

The purpose of this paper is to explore the implementation of online learning in distance educational delivery at Yellow Fields University (pseudonymous) in Sri Lanka. The implementation of online distance education at the University included the use of blended learning. The policy initiative to introduce online for distance education in Sri Lanka was guided by the expectation of cost reduction and the implementation was financed under the Distance Education Modernization Project. The paper presents one case study of a larger multiple case study research that employed an ethnographic research approach in investigating the impact of ICT on distance education in Sri Lanka. Documents, questionnaires and qualitative interviews were used for data collection. There was a significant positive relationship between ownership of computers and students’ ability to use computer for word processing, emailing and Web searching. The lack of access to computers and the Internet, the lack of infrastructure, low levels of computer literacy, the lack of local language content, and the lack of formal student support services at the University were found to be major barriers to implementing compulsory online activities at the University

Once upon a time, there was a fabulous funambulist: What children learn about the “high-level” vocabulary they encounter while listening to stories

Previous research has shown that listening to stories supports vocabulary growth in preschool and school-aged children and that lexical entries for even very difficult or rare words can be established if these are defined when they are first introduced. However, little is known about the nature of the lexical representations children form for the words they encounter while listening to stories, or whether these are sufficiently robust to support the child’s own use of such ‘high-level’ vocabulary. This study explored these questions by administering multiple assessments of children’s knowledge about a set of newly-acquired vocabulary. Four- and 6-year-old children were introduced to nine difficult new words (including nouns, verbs and adjectives) through three exposures to a story read by their class teacher. The story included a definition of each new word at its first encounter. Learning of the target vocabulary was assessed by means of two tests of semantic understanding – a forced choice picture-selection task and a definition production task – and a grammaticality judgment task, which asked children to choose between a syntactically-appropriate and syntactically-inappropriate usage of the word. Children in both age groups selected the correct pictorial representation and provided an appropriate definition for the target words in all three word classes significantly more often than they did for a matched set of non-exposed control words. However, only the older group was able to identify the syntactically-appropriate sentence frames in the grammaticality judgment task. Further analyses elucidate some of the components of the lexical representations children lay down when they hear difficult new vocabulary in stories and how different tests of word knowledge might overlap in their assessment of these components.

Review of monitoring tools for e-learning platforms

The advancement of e-learning technologies has made it viable for developments in education and technology to be combined in order to fulfil educational needs worldwide. E-learning consists of informal learning approaches and emerging technologies to support the delivery of learning skills, materials, collaboration and knowledge sharing. E-learning is a holistic approach that covers a wide range of courses, technologies and infrastructures to provide an effective learning environment. The Learning Management System (LMS) is the core of the entire e-learning process along with technology, content, and services. This paper investigates the role of model-driven personalisation support modalities in providing enhanced levels of learning and trusted assimilation in an e-learning delivery context. We present an analysis of the impact of an integrated learning path that an e-learning system may employ to track activities and evaluate the performance of learners.

Teaching and learning Chinese: heritage language classroom discourse in Montreal

This paper explores issues of teaching and learning Chinese as a heritage language in a Chinese heritage language school, the Zhonguo Saturday School, in Montreal, Quebec. With a student population of more than 1000, this school is the largest of the eight Chinese Heritage Language schools in Montreal. Students participating in this study were from seven different classes (grade K, two, three, four, five, six, and special class), their ages ranging from 4 to 13 years. The study took place over a period of two years between 2000 and 2002. Focusing on primary level classroom discourse and drawing on the works of Vygotsky and Bakhtin, I examine how teachers and students use language to communicate, and how their communication mediates teaching, learning and heritage language acquisition. Data sources include classroom observations, interviews with students and their teachers, students’ writings, and video and audio taping of classroom activities. Implications for heritage language development and maintenance are discussed with reference to the findings of this study.

Assessment for Learning in teaching English to Young Learners: teachers’ understanding, classroom practice and impact on interactions

It has been suggested that Assessment for Learning (AfL) plays a significant role in enhancing teaching and learning in mainstream educational contexts. However, little empirical evidence can support these claims. As AfL has been shown to be enacted predominantly through interactions in primary classes, there is a need to understand if it is appropriate, whether it can be efficiently used in teaching English to Young Learners (TEYL) and how it can facilitate learning in such a context. This emerging research focus gains currency especially in the light of SLA research, which suggests the important role of interactions in foreign language learning. This mixed-method, descriptive and exploratory study aims to investigate how teachers of learners aged 7-11 understand AfL; how they implement it; and the impact that such implementation could have on interactions which occur during lessons. The data were collected through lesson observations, scrutiny of school documents, semi-structured interviews and a focus group interview with teachers. The findings indicate that fitness for purpose guides the implementation of AfL in TEYL classrooms. Significantly, the study has revealed differences in the implementation of AfL between classes of 7-9 and 10-11 year olds within each of the three purposes (setting objectives and expectations; monitoring performance; and checking achievement) identified through the data. Another important finding of this study is the empirical evidence suggesting that the use of AfL could facilitate creating conditions conducive to learning in TEYL classes during collaborative and expert/novice interactions. The findings suggest that teachers’ understanding of AfL is largely aligned with the theoretical frameworks (Black & Wiliam, 2009; Swaffield, 2011) already available. However, they also demonstrate that there are TEYL specific characteristics. This research has important pedagogical implications and indicates a number of areas for further research.

Linking classroom learning and research to advance ideas about social-ecological resilience

There is an increasing demand in higher education institutions for training in complex environmental problems. Such training requires a careful mix of conventional methods and innovative solutions, a task not always easy to accomplish. In this paper we review literature on this theme, highlight relevant advances in the pedagogical literature, and report on some examples resulting from our recent efforts to teach complex environmental issues. The examples range from full credit courses in sustainable development and research methods to project-based and in-class activity units. A consensus from the literature is that lectures are not sufficient to fully engage students in these issues. A conclusion from the review of examples is that problem-based and project-based, e.g., through case studies, experiential learning opportunities, or real-world applications, learning offers much promise. This could greatly be facilitated by online hubs through which teachers, students, and other members of the practitioner and academic community share experiences in teaching and research, the way that we have done here.