304 resultados para Outdoor furniture.


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Curriculum demands continue to increase on school education systems with teachers at the forefront of implementing syllabus requirements. Education is reported frequently as a solution to most societal problems and, as a result of the world’s information explosion, teachers are expected to cover more and more within teaching programs. How can teachers combine subjects in order to capitalise on the competing educational agendas within school timeframes? Fusing curricula requires the bonding of standards from two or more syllabuses. Both technology and ICT complement the learning of science. This study analyses selected examples of preservice teachers’ overviews for fusing science, technology and ICT. These program overviews focused on primary students and the achievement of two standards (one from science and one from either technology or ICT). These primary preservice teachers’ fused-curricula overviews included scientific concepts and related technology and/or ICT skills and knowledge. Findings indicated a range of innovative curriculum plans for teaching primary science through technology and ICT, demonstrating that these subjects can form cohesive links towards achieving the respective learning standards. Teachers can work more astutely by fusing curricula; however further professional development may be required to advance thinking about these processes. Bonding subjects through their learning standards can extend beyond previous integration or thematic work where standards may not have been assessed. Education systems need to articulate through syllabus documents how effective fusing of curricula can be achieved. It appears that education is a key avenue for addressing societal needs, problems and issues. Education is promoted as a universal solution, which has resulted in curriculum overload (Dare, Durand, Moeller, & Washington, 1997; Vinson, 2001). Societal and curriculum demands have placed added pressure on teachers with many extenuating education issues increasing teachers’ workloads (Mobilise for Public Education, 2002). For example, as Australia has weather conducive for outdoor activities, social problems and issues arise that are reported through the media calling for action; consequently schools have been involved in swimming programs, road and bicycle safety programs, and a wide range of activities that had been considered a parental responsibility in the past. Teachers are expected to plan, implement and assess these extra-curricula activities within their already overcrowded timetables. At the same stage, key learning areas (KLAs) such as science and technology are mandatory requirements within all Australian education systems. These systems have syllabuses outlining levels of content and the anticipated learning outcomes (also known as standards, essential learnings, and frameworks). Time allocated for teaching science in obviously an issue. In 2001, it was estimated that on average the time spent in teaching science in Australian Primary Schools was almost an hour per week (Goodrum, Hackling, & Rennie, 2001). More recently, a study undertaken in the U.S. reported a similar finding. More than 80% of the teachers in K-5 classrooms spent less than an hour teaching science (Dorph, Goldstein, Lee, et al., 2007). More importantly, 16% did not spend teaching science in their classrooms. Teachers need to learn to work smarter by optimising the use of their in-class time. Integration is proposed as one of the ways to address the issue of curriculum overload (Venville & Dawson, 2005; Vogler, 2003). Even though there may be a lack of definition for integration (Hurley, 2001), curriculum integration aims at covering key concepts in two or more subject areas within the same lesson (Buxton & Whatley, 2002). This implies covering the curriculum in less time than if the subjects were taught separately; therefore teachers should have more time to cover other educational issues. Expectedly, the reality can be decidedly different (e.g., Brophy & Alleman, 1991; Venville & Dawson, 2005). Nevertheless, teachers report that students expand their knowledge and skills as a result of subject integration (James, Lamb, Householder, & Bailey, 2000). There seems to be considerable value for integrating science with other KLAs besides aiming to address teaching workloads. Over two decades ago, Cohen and Staley (1982) claimed that integration can bring a subject into the primary curriculum that may be otherwise left out. Integrating science education aims to develop a more holistic perspective. Indeed, life is not neat components of stand-alone subjects; life integrates subject content in numerous ways, and curriculum integration can assist students to make these real-life connections (Burnett & Wichman, 1997). Science integration can provide the scope for real-life learning and the possibility of targeting students’ learning styles more effectively by providing more than one perspective (Hudson & Hudson, 2001). To illustrate, technology is essential to science education (Blueford & Rosenbloom, 2003; Board of Studies, 1999; Penick, 2002), and constructing technology immediately evokes a social purpose for such construction (Marker, 1992). For example, building a model windmill requires science and technology (Zubrowski, 2002) but has a key focus on sustainability and the social sciences. Science has the potential to be integrated with all KLAs (e.g., Cohen & Staley, 1982; Dobbs, 1995; James et al., 2000). Yet, “integration” appears to be a confusing term. Integration has an educational meaning focused on special education students being assimilated into mainstream classrooms. The word integration was used in the late seventies and generally focused around thematic approaches for teaching. For instance, a science theme about flight only has to have a student drawing a picture of plane to show integration; it did not connect the anticipated outcomes from science and art. The term “fusing curricula” presents a seamless bonding between two subjects; hence standards (or outcomes) need to be linked from both subjects. This also goes beyond just embedding one subject within another. Embedding implies that one subject is dominant, while fusing curricula proposes an equal mix of learning within both subject areas. Primary education in Queensland has eight KLAs, each with its established content and each with a proposed structure for levels of learning. Primary teachers attempt to cover these syllabus requirements across the eight KLAs in less than five hours a day, and between many of the extra-curricula activities occurring throughout a school year (e.g., Easter activities, Education Week, concerts, excursions, performances). In Australia, education systems have developed standards for all KLAs (e.g., Education Queensland, NSW Department of Education and Training, Victorian Education) usually designated by a code. In the late 1990’s (in Queensland), “core learning outcomes” for strands across all KLA’s. For example, LL2.1 for the Queensland Education science syllabus means Life and Living at Level 2 standard number 1. Thus, a teacher’s planning requires the inclusion of standards as indicated by the presiding syllabus. More recently, the core learning outcomes were replaced by “essential learnings”. They specify “what students should be taught and what is important for students to have opportunities to know, understand and be able to do” (Queensland Studies Authority, 2009, para. 1). Fusing science education with other KLAs may facilitate more efficient use of time and resources; however this type of planning needs to combine standards from two syllabuses. To further assist in facilitating sound pedagogical practices, there are models proposed for learning science, technology and other KLAs such as Bloom’s Taxonomy (Bloom, 1956), Productive Pedagogies (Education Queensland, 2004), de Bono’s Six Hats (de Bono, 1985), and Gardner’s Multiple Intelligences (Gardner, 1999) that imply, warrant, or necessitate fused curricula. Bybee’s 5 Es, for example, has five levels of learning (engage, explore, explain, elaborate, and evaluate; Bybee, 1997) can have the potential for fusing science and ICT standards.

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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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In recent years there has been widespread interest in patterns, perhaps provoked by a realisation that they constitute a fundamental brain activity and underpin many artificial intelligence systems. Theorised concepts of spatial patterns including scale, proportion, and symmetry, as well as social and psychological understandings are being revived through digital/parametric means of visualisation and production. The effect of pattern as an ornamental device has also changed from applied styling to mediated dynamic effect. The interior has also seen patterned motifs applied to wall coverings, linen, furniture and artefacts with the effect of enhancing aesthetic appreciation, or in some cases causing psychological and/or perceptual distress (Rodemann 1999). ----- ----- While much of this work concerns a repeating array of surface treatment, Philip Ball’s The Self- Made Tapestry: Pattern Formation in Nature (1999) suggests a number of ways that patterns are present at the macro and micro level, both in their formation and disposition. Unlike the conventional notion of a pattern being the regular repetition of a motif (geometrical or pictorial) he suggests that in nature they are not necessarily restricted to a repeating array of identical units, but also include those that are similar rather than identical (Ball 1999, 9). From his observations Ball argues that they need not necessarily all be the same size, but do share similar features that we recognise as typical. Examples include self-organized patterns on a grand scale such as sand dunes, or fractal networks caused by rivers on hills and mountains, through to patterns of flow observed in both scientific experiments and the drawings of Leonardo da Vinci.

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This paper presents a framework for performing real-time recursive estimation of landmarks’ visual appearance. Imaging data in its original high dimensional space is probabilistically mapped to a compressed low dimensional space through the definition of likelihood functions. The likelihoods are subsequently fused with prior information using a Bayesian update. This process produces a probabilistic estimate of the low dimensional representation of the landmark visual appearance. The overall filtering provides information complementary to the conventional position estimates which is used to enhance data association. In addition to robotics observations, the filter integrates human observations in the appearance estimates. The appearance tracks as computed by the filter allow landmark classification. The set of labels involved in the classification task is thought of as an observation space where human observations are made by selecting a label. The low dimensional appearance estimates returned by the filter allow for low cost communication in low bandwidth sensor networks. Deployment of the filter in such a network is demonstrated in an outdoor mapping application involving a human operator, a ground and an air vehicle.

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This paper presents a robust place recognition algorithm for mobile robots. The framework proposed combines nonlinear dimensionality reduction, nonlinear regression under noise, and variational Bayesian learning to create consistent probabilistic representations of places from images. These generative models are learnt from a few images and used for multi-class place recognition where classification is computed from a set of feature-vectors. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions and blurring. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.

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This paper describes a novel probabilistic approach to incorporating odometric information into appearance-based SLAM systems, without performing metric map construction or calculating relative feature geometry. The proposed system, dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM), represents location as a probability distribution along a trajectory, and represents appearance continuously over the trajectory rather than at discrete locations. The distribution is evaluated using a Rao-Blackwellised particle filter, which weights particles based on local appearance and odometric similarity and explicitly models both the likelihood of revisiting previous locations and visiting new locations. A modified resampling scheme counters particle deprivation and allows loop closure updates to be performed in constant time regardless of map size. We compare the performance of CAT-SLAM to FAB-MAP (an appearance-only SLAM algorithm) in an outdoor environment, demonstrating a threefold increase in the number of correct loop closures detected by CAT-SLAM.

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Subtropical Design in South East Queensland provides a direct link between climatic design, applied urban design and sustainable planning policy. The role that character and identity of a place plays in achieving environmental sustainability is explained. Values of local distinctiveness to do with climate, landscape and culture are identified and the environmental, social and economic benefits of applying subtropical design principles to planning are described. The handbook provides planners and urban designers with an understanding of how subtropical design principles apply within the different contexts of urban planning including the entire spectrum of urban scales from the regional scale, to the city, neighbourhood, street, individual building or site. Twelve interactive principles, and interrelated strategies, drawn predominantly from the body of knowledge of landscape architecture, architectural science and urban design are described in detail in text, and richly illustrated with diagrams and photographs.

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Given today's focus on the state of the environment and the developing role of corporate social leadership in could be argued that there is a need for the development of successful business leaders who have a positive relationship to the natural world. Gifford (2007) argued that any real change in sustainable practice will most likely happen at an individual level, through changes in attitudes and everyday behaviour. For this change to happen, an individual will need to feel connected to the natural world (Dunbar, 2004; Schroll, 2007). Roszak (1992) developed the notion of ecopsychology specifically to explore this relationship and suggest new ways to generate greater environmental awareness as well as ameliorate psychological problems caused or exacerbated by widespread alienation from nature. From this perspective it seems imperative that we develop people centred leader’s who feel connected to the natural world whilst demonstrating solid performance, as measured by organisational and social indicators. This paper presents information from an International research project that might add further insights into the role outdoor education plays in the development of generic leaders who have a positive relationship to the natural world. Three questionnaires, an established measurement of generic transformational leadership (MLQ) and two established measurement of attitudes to and feelings about the natural world (the New Ecological Paradigm Scale and the Connectedness to Nature Scale), were administered to 214 (males, n=138 and females, n=76) International outdoor leaders with the implicit aim of assessing the nexus of transformational leadership theory and adventure based leadership development. The large and diverse cohort of participants has provided ground-breaking insights into transformational and ecological leadership styles. This paper outlines a descriptive analysis of findings and offers valuable information for those involved in training leaders. Throughout this presentation participants will be encouraged to contextualise the information for their specific circumstance.

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In this paper we present an account of children's interactions with a mobile technology prototype within a school context. The Noise Detectives trial was conducted in a school setting with the aim of better understanding the role of mobile technology as a mediator within science learning activities. Over eighty children, aged between ten and twelve, completed an outdoor data gathering activity using a mobile learning prototype that included paper and digital components. They measured and recorded noise levels at a range of locations throughout the schools. We analyzed the activity to determine how the components of the prototype were integrated into the learning activity, and to identify differences in behavior that resulted from using these components. We present design implications that resulted from observed differences in prototype use and appropriation.

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The broad research questions of the book are: How can successful, interdisciplinary collaboration contribute to research innovation through Practice-led research? What contributes to the design, production and curation of successful new media art? What are the implications of exhibiting it across dual sites for artists, curators and participant audiences? Is it possible to create an 'intimate transaction' between people who are separated by vast distances but joined by interfaces and distributed networks? Centred on a new media work of the same name by the Transmute Collective (led by Keith Armstrong), this book provides insights from multidisciplinary perspectives. Visual, sound and performance artists, furniture designers, spatial architects, technology systems designers, and curators who collaborated in the production of Intimate Transactions discuss their design philosophies, working processes and resolution of this major new media work. Analytical and philosophical essays by international writers complement these writings on production. They consider how new media art, like Intimate Transactions, challenges traditional understandings of art, curatorial installation and exhibition experience because of the need to take into account interaction, the reconfiguration of space, co-presence, performativity and inter-site collaboration.

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Inadequate air quality and the inhalation of airborne pollutants pose many risks to human health and wellbeing, and are listed among the top environmental risks worldwide. The importance of outdoor air quality was recognised in the 1950s and indoor air quality emerged as an issue some time later and was soon recognised as having an equal, if not greater importance than outdoor air quality. Identification of ambient air pollution as a health hazard was followed by steps, undertaken by a broad range of national and international professional and government organisations, aimed at reduction or elimination of the hazard. However, the process of achieving better air quality is still in progress. The last 10 years or so have seen an unprecedented increase in the interest in, and attention to, airborne particles, with a special focus on their finer size fractions, including ultrafine (< 0.1 m) and their subset, nano particles (< 0.05 m). This paper discusses the current status of scientific knowledge on the links between air quality and health, with a particular focus on airborne particulate matter, and the directions taken by national and international bodies to improve air quality.

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In this paper we describe a body of work aimed at extending the reach of mobile navigation and mapping. We describe how running topological and metric mapping and pose estimation processes concurrently, using vision and laser ranging, has produced a full six-degree-of-freedom outdoor navigation system. It is capable of producing intricate three-dimensional maps over many kilometers and in real time. We consider issues concerning the intrinsic quality of the built maps and describe our progress towards adding semantic labels to maps via scene de-construction and labeling. We show how our choices of representation, inference methods and use of both topological and metric techniques naturally allow us to fuse maps built from multiple sessions with no need for manual frame alignment or data association.

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As global warming entails new conditions for the built environment, the thermal and energy performance of existing buildings, which are designed based on current weather data, may become unclear and remain a great concern. Through building computer simulation and qualitative analysis of the weighted factor for the outdoor temperature impact on building energy and thermal performance, this paper investigates the sensitivity of different office building zoning to the potential global warming. A standard office building type is examined for all eight capital cities in Australia. Results show that comparing the middle and top floors, except for cool climate (i.e. Hobart), the ground floor appears to be the most sensitive to the effect of global warming and has the highest tendency for a overheating problem. From the analysis of the responses of different zone orientations to the outdoor air temperature increase, it is also found that there are widely varied responses between zone orientations, with South zone (in the southern hemisphere) being the most sensitive. With an increased external air temperature, the variation between different floors or zone orientations will become more significant, up to 53 percent increase of overheating hours in Darwin and 47 percent increase of cooling load in Hobart.

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Micro aerial vehicles (MAVs) are a rapidly growing area of research and development in robotics. For autonomous robot operations, localization has typically been calculated using GPS, external camera arrays, or onboard range or vision sensing. In cluttered indoor or outdoor environments, onboard sensing is the only viable option. In this paper we present an appearance-based approach to visual SLAM on a flying MAV using only low quality vision. Our approach consists of a visual place recognition algorithm that operates on 1000 pixel images, a lightweight visual odometry algorithm, and a visual expectation algorithm that improves the recall of place sequences and the precision with which they are recalled as the robot flies along a similar path. Using data gathered from outdoor datasets, we show that the system is able to perform visual recognition with low quality, intermittent visual sensory data. By combining the visual algorithms with the RatSLAM system, we also demonstrate how the algorithms enable successful SLAM.