202 resultados para Mandibular advancement


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Many education providers grapple with “where” to host their online education community. While many have invested significant funding and time into developing a user specific solution, others are using alternative open source software solutions that provide a just in time response. This research paper reports on the importance of the engagement of an online community within an open source learning management system, presents the key aspects of communication occurring and romanticizes the notion that a user specific solution is not a necessary consideration.

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With a significant investment in digital technologies in Australian schools, the effective integration of such technology into teaching and learning is paramount. A growing body of evidence indicates that ICT professional learning is integral to the transformation of pedagogy that will improve student learning outcomes. The question arises as to how professional learning is planned and delivered within schools to ensure that all needs are being met. The purpose of this paper is to report on the research findings of a study into professional learning and ICT integration. The TPACK conceptual framework underpins the analyses of the data and brings forth the importance of technological and pedagogical knowledge. Six key categories will be discussed and the implication for practice will be considered.

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The problem of unsupervised anomaly detection arises in a wide variety of practical applications. While one-class support vector machines have demonstrated their effectiveness as an anomaly detection technique, their ability to model large datasets is limited due to their memory and time complexity for training. To address this issue for supervised learning of kernel machines, there has been growing interest in random projection methods as an alternative to the computationally expensive problems of kernel matrix construction and sup-port vector optimisation. In this paper we leverage the theory of nonlinear random projections and propose the Randomised One-class SVM (R1SVM), which is an efficient and scalable anomaly detection technique that can be trained on large-scale datasets. Our empirical analysis on several real-life and synthetic datasets shows that our randomised 1SVM algorithm achieves comparable or better accuracy to deep auto encoder and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

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This commentary was stimulated by Yeping Li's first editorial (2014) citing one of the journal's goals as adding multidisciplinary perspectives to current studies of single disciplines comprising the focus of other journals. In this commentary I argue for a greater focus on STEM integration, with a more equitable representation of the four disciplines in studies purporting to advance STEM learning. The STEM acronym is often used in reference to just one of the disciplines, commonly science. Although the integration of STEM disciplines is increasingly advocated in the literature, studies that address multiple disciplines appear scant with mixed findings and inadequate directions for STEM advancement. Perspectives on how discipline integration can be achieved are varied, with reference to multidisciplinary, interdisciplinary, and transdisciplinary approaches adding to the debates. Such approaches include core concepts and skills being taught separately in each discipline but housed within a common theme; the introduction of closely linked concepts and skills from two or more disciplines with the aim of deepening understanding and skills; and the adoption of a transdisciplinary approach, where knowledge and skills from two or more disciplines are applied to real-world problems and projects with the aim of shaping the total learning experience. Research that targets STEM integration is an embryonic field with respect to advancing curriculum development and various student outcomes. For example, we still need more studies on how student learning outcomes arise not only from different forms of STEM integration but also from the particular disciplines that are being integrated. As noted in this commentary, it seems that mathematics learning benefits less than the other disciplines in programs claiming to focus on STEM integration. Factors contributing to this finding warrant more scrutiny. Likewise, learning outcomes for engineering within K-12 integrated STEM programs appear under-researched. This commentary advocates a greater focus on these two disciplines within integrated STEM education research. Drawing on recommendations from the literature, suggestions are offered for addressing the challenges of integrating multiple disciplines faced by the STEM community.

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Jarvis et al. (Research Articles, 12 December 2014, p. 1320) presented molecular clock analyses that suggested that most modern bird orders diverged just after the mass extinction event at the Cretaceous-Paleogene boundary (about 66 million years ago). We demonstrate that this conclusion results from the use of a single inappropriate maximum bound, which effectively precludes the Cretaceous diversification overwhelmingly supported by previous molecular studies.

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The Australasian Society for Computers in Learning in Tertiary Education (ascilite) has recently completed research to inform development of the ALTC Exchange, a new online service for learning and teaching in Australia. The research investigated resource identification and contribution, engagement with the repository and user community, and associated peer review and commentary processes. This article focuses on the data obtained and recommendations developed for engagement of potential end users. It reports a literature review and findings, including an international perspective on the ALTC Exchange, with specific focus on prospective user needs, contexts of use and policies necessary to facilitate engagement of the higher education sector with the ALTC Exchange

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In September, the United Nations General Assembly adopted Sustainable Development Goals (SDGs), to be met by the year 2030. These important goals range from poverty eradication and improvements in education and health to the protection of global assets, including the oceans and a stable climate. Unfortunately, neither the SDGs nor their background documents explain how governments should judge whether the development programs they undertake to meet the goals are sustainable.