852 resultados para Literacy Content Knowledge


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There are still major challenges in the area of automatic indexing and retrieval of digital data. The main problem arises from the ever increasing mass of digital media and the lack of efficient methods for indexing and retrieval of such data based on the semantic content rather than keywords. To enable intelligent web interactions or even web filtering, we need to be capable of interpreting the information base in an intelligent manner. Research has been ongoing for a few years in the field of ontological engineering with the aim of using ontologies to add knowledge to information. In this paper we describe the architecture of a system designed to automatically and intelligently index huge repositories of special effects video clips, based on their semantic content, using a network of scalable ontologies to enable intelligent retrieval.

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Information provision to address the changing requirements can be best supported by content management. The Current information technology enables information to be stored and provided from various distributed sources. To identify and retrieve relevant information requires effective mechanisms for information discovery and assembly. This paper presents a method, which enables the design of such mechanisms, with a set of techniques for articulating and profiling users' requirements, formulating information provision specifications, realising management of information content in repositories, and facilitating response to the user's requirements dynamically during the process of knowledge construction. These functions are represented in an ontology which integrates the capability of the mechanisms. The ontological modelling in this paper has adopted semiotics principles with embedded norms to ensure coherent course of actions represented in these mechanisms. (C) 2008 Elsevier B.V. All rights reserved.

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The quality of information provision influences considerably knowledge construction driven by individual users’ needs. In the design of information systems for e-learning, personal information requirements should be incorporated to determine a selection of suitable learning content, instructive sequencing for learning content, and effective presentation of learning content. This is considered as an important part of instructional design for a personalised information package. The current research reveals that there is a lack of means by which individual users’ information requirements can be effectively incorporated to support personal knowledge construction. This paper presents a method which enables an articulation of users’ requirements based on the rooted learning theories and requirements engineering paradigms. The user’s information requirements can be systematically encapsulated in a user profile (i.e. user requirements space), and further transformed onto instructional design specifications (i.e. information space). These two spaces allow the discovering of information requirements patterns for self-maintaining and self-adapting personalisation that enhance experience in the knowledge construction process.

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A novel framework referred to as collaterally confirmed labelling (CCL) is proposed, aiming at localising the visual semantics to regions of interest in images with textual keywords. Both the primary image and collateral textual modalities are exploited in a mutually co-referencing and complementary fashion. The collateral content and context-based knowledge is used to bias the mapping from the low-level region-based visual primitives to the high-level visual concepts defined in a visual vocabulary. We introduce the notion of collateral context, which is represented as a co-occurrence matrix of the visual keywords. A collaborative mapping scheme is devised using statistical methods like Gaussian distribution or Euclidean distance together with collateral content and context-driven inference mechanism. We introduce a novel high-level visual content descriptor that is devised for performing semantic-based image classification and retrieval. The proposed image feature vector model is fundamentally underpinned by the CCL framework. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval, respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicate that the proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models. (C) 2007 Elsevier B.V. All rights reserved.

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In this paper, we introduce a novel high-level visual content descriptor devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt for bridging the so called "semantic gap". The proposed image feature vector model is fundamentally underpinned by an automatic image labelling framework, called Collaterally Cued Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts accompanying the images with the state-of-the-art low-level visual feature extraction techniques for automatically assigning textual keywords to image regions. A subset of the Corel image collection was used for evaluating the proposed method. The experimental results indicate that our semantic-level visual content descriptors outperform both conventional visual and textual image feature models.

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Data on the potential health benefits of dietary flavanols and procyanidins, especially in the context of cardiovascular health, are considerable and continue to accumulate. Significant progress has been made in flavanol analytics and the creation of phytonutrient-content food databases, and novel data emanated from epidemiological investigations as well as dietary intervention studies. However, a comprehensive understanding of the pharmacological properties of flavanols and procyanidins, including their precise mechanisms of action in vivo, and a conclusive, consensus-based accreditation of a causal relationship between intake and health benefits in the context of primary and secondary cardiovascular disease prevention is still outstanding. Thus, the objective of this review is to identify and discuss key questions and gaps that will need to be addressed in order to conclusively demonstrate whether or not dietary flavanols and procyanidins have a role in preventing, delaying the onset of, or treating cardiovascular diseases, and thus improving human life expectancy and quality of life.

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The recent increase in short messaging system (SMS) text messaging, often using abbreviated, non-conventional ‘textisms’ (e.g. ‘2nite’), in school-aged children has raised fears of negative consequences of such technology for literacy. The current research used a paradigm developed by Dixon and Kaminska, who showed that exposure to phonetically plausible misspellings (e.g. ‘recieve’) negatively affected subsequent spelling performance, though this was true only with adults, not children. The current research extends this work to directly investigate the effects of exposure to textisms, misspellings and correctly spelledwords on adults’ spelling. Spelling of a set of key words was assessed both before and after an exposure phase where participants read the same key words, presented either as textisms (e.g. ‘2nite’), correctly spelled (e.g. ‘tonight’) or misspelled (e.g. 'tonite’)words. Analysis showed that scores decreased from pre- to post-test following exposure to misspellings, whereas performance improved following exposure to correctly spelled words and, interestingly, to textisms. Data suggest that exposure to textisms, unlike misspellings, had a positive effect on adults’ spelling. These findings are interpreted in light of other recent research suggesting a positive relationship between texting and some literacy measures in school-aged children.

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Literacy as a social practice is integrally linked with social, economic and political institutions and processes. As such, it has a material base which is fundamentally constituted in power relations. Literacy is therefore interwoven with the text and context of everyday living in which multi-levelled meanings are organically produced at both individual and societal level. This paper argues that if language thus mediates social reality, then it follows that literacy defined as a social practice cannot really be addressed as a reified, neutral activity but that it should take account of the social, cultural and political processes in which literacy practices are embedded. Drawing on the work of key writers within the field, the paper foregrounds the primary role of the state in defining the forms and levels of literacy required and made available at particular moments within society. In a case-study of the social construction of literacy meanings in pre-revolutionary Iran, it explores the view that the discourse about societal literacy levels has historically constituted a key terrain in which the struggle for control over meaning has taken place. This struggle, it is argued, sets the interests of the state to maintain ideological and political control over the production of knowledge within the culture and society over and against the needs identified by the individual for personal development, empowerment and liberation. In an overall sense, the paper examines existing theoretical perspectives on societal literacy programmes in terms of the scope that they provide for analyses that encompass the multi-levelled power relations that shape and influence dominant discourses on the relative value of literacy for both the individual and society

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Recent national developments in the teaching of literacy in the early years in the UK mean that teachers need to have explicit fluent knowledge of the sound structure of the language and its relationship to orthography in order to teach reading effectively. In this study, a group of 38 graduate trainee primary teachers were given a pencil and paper test of phonological awareness as part of a course on teaching literacy. Results from the pencil and paper test were used as the basis of teaching about the sound structure of words. The test was repeated six months later. The results showed that they did not use a consistent system for segmenting words into component sounds. Though there was substantial improvement on second testing, many trainees still did not show evidence that they had yet developed sufficient insights into the sound structure of words to be able to teach children about phonemes with certainty. It is argued that student teachers need substantial explicit training and practice in manipulating the sound structure of words to enable them to teach this aspect of language confidently.

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Clinical pathways have been adopted for various diseases in clinical departments for quality improvement as a result of standardization of medical activities in treatment process. Using knowledge-based decision support on the basis of clinical pathways is a promising strategy to improve medical quality effectively. However, the clinical pathway knowledge has not been fully integrated into treatment process and thus cannot provide comprehensive support to the actual work practice. Therefore this paper proposes a knowledgebased clinical pathway management method which contributes to make use of clinical knowledge to support and optimize medical practice. We have developed a knowledgebased clinical pathway management system to demonstrate how the clinical pathway knowledge comprehensively supports the treatment process. The experiences from the use of this system show that the treatment quality can be effectively improved by the extracted and classified clinical pathway knowledge, seamless integration of patient-specific clinical pathway recommendations with medical tasks and the evaluating pathway deviations for optimization.

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The rising share of intangibles in economies worldwide highlights the crucial role of knowledge-intensive and creative industries in current and future wealth generation. The recognition of this trend has led to intense competition in these industries. At the micro-level, firms from both advanced and emerging economies are globally dispersing their value chains to control costs and leverage capabilities. The geography of innovation is the outcome of a dynamic process whereby firms from emerging economies strive to catch-up with advanced economy competitors, creating strong pressures for continued innovation. However, two distinct strategies can be discerned with regard to the control of the value chain. A vertical integration strategy emphasizes taking advantage of ‘linkage economies’ whereby controlling multiple value chain activities enhances the efficiency and effectiveness of each one of them. In contrast, a specialization strategy focuses on identifying and controlling the creative heart of the value chain, while outsourcing all other activities. The global mobile handset industry is used as the template to illustrate the theory.

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The aetiology of breast cancer is multifactorial. While there are known genetic predispositions to the disease it is probable that environmental factors are also involved. Recent research has demonstrated a regionally specific distribution of aluminium in breast tissue mastectomies while other work has suggested mechanisms whereby breast tissue aluminium might contribute towards the aetiology of breast cancer. We have looked to develop microwave digestion combined with a new form of graphite furnace atomic absorption spectrometry as a precise, accurate and reproducible method for the measurement of aluminium in breast tissue biopsies. We have used this method to test the thesis that there is a regional distribution of aluminium across the breast in women with breast cancer. Microwave digestion of whole breast tissue samples resulted in clear homogenous digests perfectly suitable for the determination of aluminium by graphite furnace atomic absorption spectrometry. The instrument detection limit for the method was 0.48 μg/L. Method blanks were used to estimate background levels of contamination of 14.80 μg/L. The mean concentration of aluminium across all tissues was 0.39 μg Al/g tissue dry wt. There were no statistically significant regionally specific differences in the content of aluminium. We have developed a robust method for the precise and accurate measurement of aluminium in human breast tissue. There are very few such data currently available in the scientific literature and they will add substantially to our understanding of any putative role of aluminium in breast cancer. While we did not observe any statistically significant differences in aluminium content across the breast it has to be emphasised that herein we measured whole breast tissue and not defatted tissue where such a distribution was previously noted. We are very confident that the method developed herein could now be used to provide accurate and reproducible data on the aluminium content in defatted tissue and oil from such tissues and thereby contribute towards our knowledge on aluminium and any role in breast cancer.

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In order to overcome divergence of estimation with the same data, the proposed digital costing process adopts an integrated design of information system to design the process knowledge and costing system together. By employing and extending a widely used international standard, industry foundation classes, the system can provide an integrated process which can harvest information and knowledge of current quantity surveying practice of costing method and data. Knowledge of quantification is encoded from literatures, motivation case and standards. It can reduce the time consumption of current manual practice. The further development will represent the pricing process in a Bayesian Network based knowledge representation approach. The hybrid types of knowledge representation can produce a reliable estimation for construction project. In a practical term, the knowledge management of quantity surveying can improve the system of construction estimation. The theoretical significance of this study lies in the fact that its content and conclusion make it possible to develop an automatic estimation system based on hybrid knowledge representation approach.