980 resultados para CONTEXTUAL KNOWLEDGE


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To date, automatic recognition of semantic information such as salient objects and mid-level concepts from images is a challenging task. Since real-world objects tend to exist in a context within their environment, the computer vision researchers have increasingly incorporated contextual information for improving object recognition. In this paper, we present a method to build a visual contextual ontology from salient objects descriptions for image annotation. The ontologies include not only partOf/kindOf relations, but also spatial and co-occurrence relations. A two-step image annotation algorithm is also proposed based on ontology relations and probabilistic inference. Different from most of the existing work, we specially exploit how to combine representation of ontology, contextual knowledge and probabilistic inference. The experiments show that image annotation results are improved in the LabelMe dataset.

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One method of addressing the shortage of science and mathematics teachers is to train scientists and other science-related professionals to become teachers. Advocates argue that as discipline experts these career changers can relate the subject matter knowledge to various contexts and applications in teaching. In this paper, through interviews and classroom observations with a former scientist and her students, we examine how one career changer used her expertise in microbiology to teach microscopy. These data provided the basis for a description of the teacher’s instruction which was then analysed for components of domain knowledge for teaching. Consistent with the literature, the findings revealed that this career changer needed to develop her pedagogical knowledge. However, an interesting finding was that the teacher’s subject matter as a science teacher differed substantively from her knowledge as a scientist. This finding challenges the assumption that subject matter is readily transferable across professions and provides insight into how to better prepare and support career changers to transition from scientist to science teacher.

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Competitive advantage in a knowledge economy is dependent on the ability to innovate and create new knowledge products and services, and to find innovative applications for them. Higher education institutions in Asia and the Pacific, modelled on industrial age thinking that demands excellence in routinized capacities, lack the ability to innovate and create new knowledge enterprises. The transition to a knowledge economy is affecting the purpose, content, pedagogy, and methodologies of higher education. Nontraditional stakeholders such as professional bodies, industry experts, think tanks, research institutes, and field experts/practitioners are now involved not only in planning but in providing higher education services. The traditional model of “knowledge versus skills” is no longer relevant. Higher education programs must consider lived experiences, contextual knowledge, and indigenous knowledge.

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This article investigates how teachers in religious education (RE) think and act as professionals while working with differences in religious and philosophy of life experiences and beliefs in class and trying to do this in respectful and inclusive ways. It analyses data from two research projects that were carried out in lower secondary school in Norway. The main research question is: What is the relationship between teachers’ contextual knowledge and knowledge of the child and how do these two dimensions of professional knowledge interact when religious education teachers try to strike a good balance between inclusion and productive learning in their teaching practice? The data analysed were drawn from three different data sets featuring three Norwegian religious education-teachers. The research was part of the EU-funded "REDCo"-project and the "Religious education and diversity" - project ["ROM"] funded by the Norwegian Research Council. The interviewees emphasized the potential of the religious education subject to contribute to a wider tolerance for difference and to support individual students in their identity management. The analysis shows, however, that considerable contextual awareness - of the classroom and of the local community - is needed to realize this potential. It also shows the importance of interpersonal knowledge between the teacher and each student if contextual awareness is to be effective in terms of inclusion, participation, wellbeing and good learning outcomes for all students.

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Image annotation is a significant step towards semantic based image retrieval. Ontology is a popular approach for semantic representation and has been intensively studied for multimedia analysis. However, relations among concepts are seldom used to extract higher-level semantics. Moreover, the ontology inference is often crisp. This paper aims to enable sophisticated semantic querying of images, and thus contributes to 1) an ontology framework to contain both visual and contextual knowledge, and 2) a probabilistic inference approach to reason the high-level concepts based on different sources of information. The experiment on a natural scene database from LabelMe database shows encouraging results.

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With regard to the long-standing problem of the semantic gap between low-level image features and high-level human knowledge, the image retrieval community has recently shifted its emphasis from low-level features analysis to high-level image semantics extrac- tion. User studies reveal that users tend to seek information using high-level semantics. Therefore, image semantics extraction is of great importance to content-based image retrieval because it allows the users to freely express what images they want. Semantic content annotation is the basis for semantic content retrieval. The aim of image anno- tation is to automatically obtain keywords that can be used to represent the content of images. The major research challenges in image semantic annotation are: what is the basic unit of semantic representation? how can the semantic unit be linked to high-level image knowledge? how can the contextual information be stored and utilized for image annotation? In this thesis, the Semantic Web technology (i.e. ontology) is introduced to the image semantic annotation problem. Semantic Web, the next generation web, aims at mak- ing the content of whatever type of media not only understandable to humans but also to machines. Due to the large amounts of multimedia data prevalent on the Web, re- searchers and industries are beginning to pay more attention to the Multimedia Semantic Web. The Semantic Web technology provides a new opportunity for multimedia-based applications, but the research in this area is still in its infancy. Whether ontology can be used to improve image annotation and how to best use ontology in semantic repre- sentation and extraction is still a worth-while investigation. This thesis deals with the problem of image semantic annotation using ontology and machine learning techniques in four phases as below. 1) Salient object extraction. A salient object servers as the basic unit in image semantic extraction as it captures the common visual property of the objects. Image segmen- tation is often used as the �rst step for detecting salient objects, but most segmenta- tion algorithms often fail to generate meaningful regions due to over-segmentation and under-segmentation. We develop a new salient object detection algorithm by combining multiple homogeneity criteria in a region merging framework. 2) Ontology construction. Since real-world objects tend to exist in a context within their environment, contextual information has been increasingly used for improving object recognition. In the ontology construction phase, visual-contextual ontologies are built from a large set of fully segmented and annotated images. The ontologies are composed of several types of concepts (i.e. mid-level and high-level concepts), and domain contextual knowledge. The visual-contextual ontologies stand as a user-friendly interface between low-level features and high-level concepts. 3) Image objects annotation. In this phase, each object is labelled with a mid-level concept in ontologies. First, a set of candidate labels are obtained by training Support Vectors Machines with features extracted from salient objects. After that, contextual knowledge contained in ontologies is used to obtain the �nal labels by removing the ambiguity concepts. 4) Scene semantic annotation. The scene semantic extraction phase is to get the scene type by using both mid-level concepts and domain contextual knowledge in ontologies. Domain contextual knowledge is used to create scene con�guration that describes which objects co-exist with which scene type more frequently. The scene con�guration is represented in a probabilistic graph model, and probabilistic inference is employed to calculate the scene type given an annotated image. To evaluate the proposed methods, a series of experiments have been conducted in a large set of fully annotated outdoor scene images. These include a subset of the Corel database, a subset of the LabelMe dataset, the evaluation dataset of localized semantics in images, the spatial context evaluation dataset, and the segmented and annotated IAPR TC-12 benchmark.

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Although safety statistics indicate that road crashes are the most common form of work-related fatalities, many organizations fail to treat company vehicles in the same manner as other physical safety hazards within the workplace. Traditionally, work-related road safety has targeted primarily driver-related issues and not adequately addressed organizational processes, such as the organizations’ safety system and risk management processes and practice. This inadequacy generally stems from a lack of specific contextual knowledge and basic requirements to improve work-related road safety, including the supporting systems to ensure any intervention strategy or initiative’s ongoing effectiveness. Therefore, informed by previous research and based on a case study methodology, the Organizational Work-Related Road Safety Situational Analysis was developed to assess organizations’ current work-related road safety system, including policy, procedures, processes and practice. The situational analysis tool is similar to a safety audit however is more comprehensive in detail, application and provides sufficient evidence to enable organizations to mitigate and manage their work-related road safety risks. In addition, data collected from this process assists organizations in making informed decisions regarding intervention strategy design, development, implementation and ongoing effectiveness. This paper reports on the effectiveness of the situational analysis tool to assess WRRS systems across five differing and diverse organizations; including gas exploration and mining, state government, local government, and not for profit/philanthropy. The outcomes of this project identified considerable differences in the degree by which the organizations’ addressed work-related road safety across their vehicle fleet operations and provides guidelines for improving organizations’ work-related road safety systems.

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Undergraduate medical imaging students at an urban Australian university attend their first clinical placement towards the end of Semester two in their first year. While they often have a great deal of contextual knowledge and targeted theoretical learning prior to their first clinical placement, many of them are unfamiliar with the dynamics of a hospital environment. With the increase in online communication platforms, there was a concern that face-to-face clinical communication skills were becoming a source of anxiety for students, especially prior to their first clinical placements. Given the impact of anxiety on communication, reducing communication-related apprehension was considered a programme priority. A pilot series of scenario-based tutorials was implemented in the general radiography unit for the first year students.

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This paper describes the implementation of the recommendations of a series of research projects, within an undergraduate dance teacher-training course, into the training of collaborative, empathetic, ethical and creative dance teachers. Banks’s Dimensions for Multicultural Education (Banks, 1993) was used as a lens to analyze the design and delivery of cultural dance activities within a university dance-teaching unit, implemented in Australia and Timor Leste, and to reflect on the adaptability of the Performance in Context Model (Stevens & Huddy, in press) across different cultural contexts. Content and contextual knowledge, transformational learning pedagogy, teaching for equity and empathy development were explored through a culturally responsive teaching and learning unit, supported by critical analysis and reflection. This analysis identified a number of key understandings in relation to the design and delivery of cultural dance activities.

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Tesis con Mención de Doctor Internacional

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No âmbito do ensino-aprendizagem de línguas adicionais, pesquisas acerca do desenvolvimento da oralidade têm demonstrado que se trata de um fenômeno multidimensional. Nakatani (2010) mostrou que o domínio de estratégias comunicacionais são indicadores de desempenho linguístico e se relacionam com a proficiência do aprendiz; Kang, Rubin e Pickering (2010) observaram que os traços fonológicos afetam a percepção sobre inteligibilidade e proficiência; Hewitt e Stephenson (2011), e Ahmadian (2012) indicaram que as condições psicológicas individuais interferem na qualidade da produção oral. Escribano (2004) sugeriu que a referência contextual é essencial na construção de sentido; Gao (2011) apontou os benefícios do ensino baseado na construção do sentido, a partir de metáforas conceptuais (LAKOFF e JOHNSON, 1980), codificação dupla (CLARK e PAIVIO, 1991) e esquemas imagéticos (LAKOFF, 1987); e Ellis e Ferreira-Junior (2009) demonstraram que as construções exibem efeitos de recência e priming, afetando o uso da linguagem dos parceiros interacionais. Tais estudos apontam para a natureza complexa da aquisição de L2, mas o fazem dentro do paradigma experimental da psicolinguística. Já Larsen-Freeman (2006), demonstra que a fluência, a precisão e a complexidade desenvolvem-se com o tempo, com alto grau de variabilidade, dentro do paradigma da Teoria da Complexidade. Em viés semelhante, Paiva (2011) observa que os sistemas de Aquisição de Segunda Língua (ASL) são auto-organizáveis. Esses trabalhos, no entanto, não abordaram aprendizes de L2 com proficiência inicial, como pretendo fazer aqui. Tendo como referenciais teóricos a Teoria da Complexidade e a Linguística Cognitiva, o presente trabalho apresenta um estudo de caso, qualitativo-interpretativista, com nuances quantitativos, que discute os processos de adaptação que emergiram na expressão oral de um grupo de aprendizes iniciantes de inglês como língua adicional no contexto vocacional. Parte do entendimento de que na sala de aula vários (sub)sistemas complexos coocorrem, covariando e coadaptando-se em diferentes níveis. A investigação contou com dados transcritos de três avaliações coletados ao longo de 28 horas de aula, no domínio ENTREVISTA DE EMPREGO. Após observar a produção oral das aprendizes, criei uma taxonomia para categorizar as adaptações que ocorreram na sintaxe, semântica, fonologia e pragmática da língua-alvo. Posteriormente organizei as categorias em níveis de prototipicidade (ROSCH et al, 1976) de acordo com as adaptações mais frequentes. Finalmente, avaliei a inteligibilidade de cada elocução, classificando-as em três níveis. A partir desses dados, descrevi como a prática oral dessas participantes emergiu e se desenvolveu ao longo das 28 horas. Os achados comprovam uma das premissas da Linguística Cognitiva ao mostrarem que os níveis de descrição linguística funcionam conjuntamente em prol do sucesso comunicacional. Além disso, demonstram que a função do professor, como discutem LARSEN-FREEMAN e CAMERON (2008), não é gerar uniformidade, mas sim oportunizar vivências que estabeleçam continuidade entre o mundo, o corpo e a mente

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We report on a study of how people look for information within email, files, and the Web. When locating a document or searching for a specific answer, people relied on their contextual knowledge of their information target to help them find it, often associating the target with a specific document. They appeared to prefer to use this contextual information as a guide in navigating locally in small steps to the desired document rather than directly jumping to their target. We found this behavior was especially true for people with unstructured information organization. We discuss the implications of our findings for the design of personal information management tools.

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Zinkin's lucid challenge to Jung makes perfect sense. Indeed, it is the implications of this `making sense' that this paper addresses. For Zinkin's characterization of the `self' takes it as a `concept' requiring coherence; a variety of abstract non-contextual knowledge that itself has a mythical heritage. Moreover, Zinkin's refinement of Jung seeks to make his work fit for the scientific paradigm of modernity. In turn, modernity's paradigm owes much to Newton's notion of knowledge via reductionism. Here knowledge or investigation is divided up into the smallest possible units with the aim of eventually putting it all together into `one' picture of scientific truth. Unfortunately, `reductionism' does not do justice to the resonant possibilities of Jung's writing. These look forward to a new scientific paradigm of the twenty-first century, of the interactive `field', emergence and complexity theory. The paper works paradoxically by discovering Zinkin's `intersubjective self' after all, in two undervalued narratives by Jung, his doctoral thesis and a short late ghost story. However, in the ambivalences and radical fictional experimentation of these fascinating texts can be discerned an-Other self, one both created and found. [From the Publisher]