17 resultados para Multiple subspace learning


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Traditional dictionary learning algorithms are used for finding a sparse representation on high dimensional data by transforming samples into a one-dimensional (1D) vector. This 1D model loses the inherent spatial structure property of data. An alternative solution is to employ Tensor Decomposition for dictionary learning on their original structural form —a tensor— by learning multiple dictionaries along each mode and the corresponding sparse representation in respect to the Kronecker product of these dictionaries. To learn tensor dictionaries along each mode, all the existing methods update each dictionary iteratively in an alternating manner. Because atoms from each mode dictionary jointly make contributions to the sparsity of tensor, existing works ignore atoms correlations between different mode dictionaries by treating each mode dictionary independently. In this paper, we propose a joint multiple dictionary learning method for tensor sparse coding, which explores atom correlations for sparse representation and updates multiple atoms from each mode dictionary simultaneously. In this algorithm, the Frequent-Pattern Tree (FP-tree) mining algorithm is employed to exploit frequent atom patterns in the sparse representation. Inspired by the idea of K-SVD, we develop a new dictionary update method that jointly updates elements in each pattern. Experimental results demonstrate our method outperforms other tensor based dictionary learning algorithms.

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The close relationship between children’s vocabulary size and their later academic success has led researchers to explore how vocabulary development might be promoted during the early school years. We describe a study that explored the effectiveness of naturalistic classroom storytelling as an instrument for teaching new vocabulary to six- to nine-year-old children. We examined whether learning was facilitated by encountering new words in single versus multiple story contexts, or by the provision of age-appropriate definitions of words as they were encountered. Results showed that encountering words in stories on three occasions led to significant gains in word knowledge in children of all ages and abilities, and that learning was further enhanced across the board when teachers elaborated on the new words’ meanings by providing dictionary definitions. Our findings clarify how classroom storytelling activities can be a highly effective means of promoting vocabulary development.

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Research is described that sought to understand how senior managers within regional contracting firms conceptualize and enact competitiveness. Existing formal discourses of construction competitiveness include the discourse of 'best practice' and the various theories of competitiveness as routinely mobilized within the academic literature. Such discourses consistently underplay the influence of contextual factors in shaping how competitiveness is enacted. An alternative discourse of competitiveness is outlined based on the concepts of localized learning and embeddedness. Two case studies of regional construction firms provide new insights into the emergent discourses of construction competitiveness. The empirical findings resonate strongly with the concepts of localized learning and embeddedness. The case studies illustrate the importance of de-centralized structures which enable multiple business units to become embedded within localized markets. A significant degree of autonomy is essential to facilitate localized entrepreneurial behaviour. In essence, sustained competitiveness was found to depend upon the extent to which de-centralized business units enact ongoing processes of localized learning. Once local business units have become embedded within localized markets the essential challenge is how to encourage continued entrepreneurial behaviour while maintaining a degree of centralized control and coordination. Of key importance is the recognition that the capabilities that make companies competitive transcend organizational boundaries such that they become situated within complex networks of relational ties.

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The tides of globalization and the unsteady surges and distortions in the evolution of the European Union are causing identities and cultures to be in a state of flux. Education is used by politicians as a major lever for political and social change through micro-management, but it is a crude tool. There can, however, be opportunities within educational experience for individual learners to gain strong, reflexive, multiple identities and multiple citizenship through the engagement of their creative energies. It has been argued that the twenty-first century needs a new kind of creativity characterized by unselfishness, caring and compassion—still involving monetary wealth, but resulting in a healthy planet and healthy people. Creativity and its economically derived relation, innovation, have become `buzz words' of our times. They are often misconstrued, misunderstood and plainly misused within educational conversations. The small-scale pan-European research study upon which this article is founded discovered that more emphasis needs to be placed on creative leadership, empowering teachers and learners, reducing pupils' fear of school, balancing teaching approaches, and ensuring that the curriculum and assessment are responsive to the needs of individual learners. These factors are key to building strong educational provision that harnesses the creative potential of learners, teachers and other stakeholders, values what it is to be human and creates a foundation upon which to build strong, morally based, consistent, participative democracies.

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The neuroprotective actions of dietary flavonoids involve a number of effects within the brain, including a potential to protect neurons against injury induced by neurotoxins, an ability to suppress neuroinflammation, and the potential to promote memory, learning and cognitive function. This multiplicity of effects appears to be underpinned by two processes. Firstly, they interact with important neuronal signalling cascades leading to an inhibition of apoptosis triggered by neurotoxic species and to a promotion of neuronal survival and differentiation. These interactions include selective actions on a number of protein kinase and lipid kinase signalling cascades, most notably the PI3K/Akt and MAP kinase pathways which regulate pro-survival transcription factors and gene expression. Secondly, they induce peripheral and cerebral vascular blood flow in a manner which may lead to the induction of angiogenesis, and new nerve cell growth in the hippocampus. Therefore, the consumption of flavonoid-rich foods, such as berries and cocoa, throughout life holds a potential to limit the neurodegeneration associated with a variety of neurological disorders and to prevent or reverse normal or abnormal deteriorations in cognitive performance.

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We investigated infants' sensitivity to spatiotemporal structure. In Experiment 1, circles appeared in a statistically defined spatial pattern. At test 11-month-olds, but not 8-month-olds, looked longer at a novel spatial sequence. Experiment 2 presented different color/shape stimuli, but only the location sequence was violated during test; 8-month-olds preferred the novel spatial structure, but 5-month-olds did not. In Experiment 3, the locations but not color/shape pairings were constant at test; 5-month-olds showed a novelty preference. Experiment 4 examined "online learning": We recorded eye movements of 8-month-olds watching a spatiotemporal sequence. Saccade latencies to predictable locations decreased. We argue that temporal order statistics involving informative spatial relations become available to infants during the first year after birth, assisted by multiple cues.

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This work compares classification results of lactose, mandelic acid and dl-mandelic acid, obtained on the basis of their respective THz transients. The performance of three different pre-processing algorithms applied to the time-domain signatures obtained using a THz-transient spectrometer are contrasted by evaluating the classifier performance. A range of amplitudes of zero-mean white Gaussian noise are used to artificially degrade the signal-to-noise ratio of the time-domain signatures to generate the data sets that are presented to the classifier for both learning and validation purposes. This gradual degradation of interferograms by increasing the noise level is equivalent to performing measurements assuming a reduced integration time. Three signal processing algorithms were adopted for the evaluation of the complex insertion loss function of the samples under study; a) standard evaluation by ratioing the sample with the background spectra, b) a subspace identification algorithm and c) a novel wavelet-packet identification procedure. Within class and between class dispersion metrics are adopted for the three data sets. A discrimination metric evaluates how well the three classes can be distinguished within the frequency range 0. 1 - 1.0 THz using the above algorithms.

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This paper presents a novel intelligent multiple-controller framework incorporating a fuzzy-logic-based switching and tuning supervisor along with a generalised learning model (GLM) for an autonomous cruise control application. The proposed methodology combines the benefits of a conventional proportional-integral-derivative (PID) controller, and a PID structure-based (simultaneous) zero and pole placement controller. The switching decision between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using a fuzzy-logic-based supervisor, operating at the highest level of the system. The supervisor is also employed to adaptively tune the parameters of the multiple controllers in order to achieve the desired closed-loop system performance. The intelligent multiple-controller framework is applied to the autonomous cruise control problem in order to maintain a desired vehicle speed by controlling the throttle plate angle in an electronic throttle control (ETC) system. Sample simulation results using a validated nonlinear vehicle model are used to demonstrate the effectiveness of the multiple-controller with respect to adaptively tracking the desired vehicle speed changes and achieving the desired speed of response, whilst penalising excessive control action. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

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The evaluation of EU policy in the area of rural land use management often encounters problems of multiple and poorly articulated objectives. Agri-environmental policy has a range of aims, including natural resource protection, biodiversity conservation and the protection and enhancement of landscape quality. Forestry policy, in addition to production and environmental objectives, increasingly has social aims, including enhancement of human health and wellbeing, lifelong learning, and the cultural and amenity value of the landscape. Many of these aims are intangible, making them hard to define and quantify. This article describes two approaches for dealing with such situations, both of which rely on substantial participation by stakeholders. The first is the Agri-Environment Footprint Index, a form of multi-criteria participatory approach. The other, applied here to forestry, has been the development of ‘multi-purpose’ approaches to evaluation, which respond to the diverse needs of stakeholders through the use of mixed methods and a broad suite of indicators, selected through a participatory process. Each makes use of case studies and involves stakeholders in the evaluation process, thereby enhancing their commitment to the programmes and increasing their sustainability. Both also demonstrate more ‘holistic’ approaches to evaluation than the formal methods prescribed in the EU Common Monitoring and Evaluation Framework.

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This article investigates the nature of enterprise pedagogy in music. It presents the results of a research project that applied the practices of enterprise learning developed in the post-compulsory music curriculum in England to the teaching of the National Curriculum for music for 11-to-14-year-olds. In doing so, the article explores the nature of enterprise learning and the nature of pedagogy, in order to consider whether enterprise pedagogy offers an effective way to teach the National Curriculum. Enterprise pedagogy was found to have a positive effect on the motivation of students and on the potential to match learning to the needs of students of different abilities. Crucially, it was found that, to be effective, not only did the teacher’s practice need to be congruent with the beliefs and theories on which it rests, but that the students also needed to share in these underlying assumptions through their learning. The study has implications for the way in which teachers work multiple pedagogies in the process of developing their pedagogical identity.

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Explanations of the marked individual differences in elementary school mathematical achievement and mathematical learning disability (MLD or dyscalculia) have involved domain-general factors (working memory, reasoning, processing speed and oral language) and numerical factors that include single-digit processing efficiency and multi-digit skills such as number system knowledge and estimation. This study of third graders (N = 258) finds both domain-general and numerical factors contribute independently to explaining variation in three significant arithmetic skills: basic calculation fluency, written multi-digit computation, and arithmetic word problems. Estimation accuracy and number system knowledge show the strongest associations with every skill and their contributions are both independent of each other and other factors. Different domain-general factors independently account for variation in each skill. Numeral comparison, a single digit processing skill, uniquely accounts for variation in basic calculation. Subsamples of children with MLD (at or below 10th percentile, n = 29) are compared with low achievement (LA, 11th to 25th percentiles, n = 42) and typical achievement (above 25th percentile, n = 187). Examination of these and subsets with persistent difficulties supports a multiple deficits view of number difficulties: most children with number difficulties exhibit deficits in both domain-general and numerical factors. The only factor deficit common to all persistent MLD children is in multi-digit skills. These findings indicate that many factors matter but multi-digit skills matter most in third grade mathematical achievement.

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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.

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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

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We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

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This article focuses on the identity accounts of a group of Chinese children who attend a heritage language school. Bakhtin’s concepts of ideological becoming, and authoritative and internally persuasive discourse, frame our exploration. Taking a dialogic view of language and learning raises questions about schools as socializing spaces and ideological environments. The children in this inquiry articulate their own ideological patterns of alignment. Those patterns, and the children's code switching, seem mostly determined by their socialization, language affiliations, friendship patterns, family situations, and legal access to particular schools. Five patterns of ideological becoming are presented. The children’s articulated preferences indicate that they assert their own ideological stances towards prevailing authoritative discourses, give voice to their own sense of agency and internally persuasive discourses, and respond to the ideological resources that mediate their linguistic repertoires.