977 resultados para Outdoor cooking.


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This work investigates the computer modelling of the photochemical formation of smog products such as ozone and aerosol, in a system containing toluene, NOx and water vapour. In particular, the problem of modelling this process in the Commonwealth Scientific and Industrial Research Organization (CSIRO) smog chambers, which utilize outdoor exposure, is addressed. The primary requirement for such modelling is a knowledge of the photolytic rate coefficients. Photolytic rate coefficients of species other than N02 are often related to JNo2 (rate coefficient for the photolysis ofN02) by a simple factor, but for outdoor chambers, this method is prone to error as the diurnal profiles may not be similar in shape. Three methods for the calculation of diurnal JNo2 are investigated. The most suitable method for incorporation into a general model, is found to be one which determines the photolytic rate coefficients for N02, as well as several other species, from actinic flux, absorption cross section and quantum yields. A computer model was developed, based on this method, to calculate in-chamber photolysis rate coefficients for the CSIRO smog chambers, in which ex-chamber rate coefficients are adjusted by accounting for variation in light intensity by transmittance through the Teflon walls, albedo from the chamber floor and radiation attenuation due to clouds. The photochemical formation of secondary aerosol is investigated in a series of toluene-NOx experiments, which were performed in the CSIRO smog chambers. Three stages of aerosol formation, in plots of total particulate volume versus time, are identified: a delay period in which no significant mass of aerosol is formed, a regime of rapid aerosol formation (regime 1) and a second regime of slowed aerosol formation (regime 2). Two models are presented which were developed from the experimental data. One model is empirically based on observations of discrete stages of aerosol formation and readily allows aerosol growth profiles to be calculated. The second model is based on an adaptation of published toluene photooxidation mechanisms and provides some chemical information about the oxidation products. Both models compare favorably against the experimental data. The gross effects of precursor concentrations (toluene, NOx and H20) and ambient conditions (temperature, photolysis rate) on the formation of secondary aerosol are also investigated, primarily using the mechanism model. An increase in [NOx]o results in increased delay time, rate of aerosol formation in regime 1 and volume of aerosol formed in regime 1. This is due to increased formation of dinitrocresol and furanone products. An increase in toluene results in a decrease in the delay time and an increase in the rate of aerosol formation in regime 1, due to enhanced reactivity from the toluene products, such as the radicals from the photolysis of benzaldehyde. Water vapor has very little effect on the formation of aerosol volume, except that rates are slightly increased due to more OH radicals from reaction with 0(1D) from ozone photolysis. Increased temperature results in increased volume of aerosol formed in regime 1 (increased dinitrocresol formation), while increased photolysis rate results in increased rate of aerosol formation in regime 1. Both the rate and volume of aerosol formed in regime 2 are increased by increased temperature or photolysis rate. Both models indicate that the yield of secondary particulates from hydrocarbons (mass concentration aerosol formed/mass concentration hydrocarbon precursor) is proportional to the ratio [NOx]0/[hydrocarbon]0

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Probabilistic robot mapping techniques can produce high resolution, accurate maps of large indoor and outdoor environments. However, much less progress has been made towards robots using these maps to perform useful functions such as efficient navigation. This paper describes a pragmatic approach to mapping system development that considers not only the map but also the navigation functionality that the map must provide. We pursue this approach within a bio-inspired mapping context, and use esults from robot experiments in indoor and outdoor environments to demonstrate its validity. The research attempts to stimulate new research directions in the field of robot mapping with a proposal for a new approach that has the potential to lead to more complete mapping and navigation systems.

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This thesis addresses the problem of detecting and describing the same scene points in different wide-angle images taken by the same camera at different viewpoints. This is a core competency of many vision-based localisation tasks including visual odometry and visual place recognition. Wide-angle cameras have a large field of view that can exceed a full hemisphere, and the images they produce contain severe radial distortion. When compared to traditional narrow field of view perspective cameras, more accurate estimates of camera egomotion can be found using the images obtained with wide-angle cameras. The ability to accurately estimate camera egomotion is a fundamental primitive of visual odometry, and this is one of the reasons for the increased popularity in the use of wide-angle cameras for this task. Their large field of view also enables them to capture images of the same regions in a scene taken at very different viewpoints, and this makes them suited for visual place recognition. However, the ability to estimate the camera egomotion and recognise the same scene in two different images is dependent on the ability to reliably detect and describe the same scene points, or ‘keypoints’, in the images. Most algorithms used for this purpose are designed almost exclusively for perspective images. Applying algorithms designed for perspective images directly to wide-angle images is problematic as no account is made for the image distortion. The primary contribution of this thesis is the development of two novel keypoint detectors, and a method of keypoint description, designed for wide-angle images. Both reformulate the Scale- Invariant Feature Transform (SIFT) as an image processing operation on the sphere. As the image captured by any central projection wide-angle camera can be mapped to the sphere, applying these variants to an image on the sphere enables keypoints to be detected in a manner that is invariant to image distortion. Each of the variants is required to find the scale-space representation of an image on the sphere, and they differ in the approaches they used to do this. Extensive experiments using real and synthetically generated wide-angle images are used to validate the two new keypoint detectors and the method of keypoint description. The best of these two new keypoint detectors is applied to vision based localisation tasks including visual odometry and visual place recognition using outdoor wide-angle image sequences. As part of this work, the effect of keypoint coordinate selection on the accuracy of egomotion estimates using the Direct Linear Transform (DLT) is investigated, and a simple weighting scheme is proposed which attempts to account for the uncertainty of keypoint positions during detection. A word reliability metric is also developed for use within a visual ‘bag of words’ approach to place recognition.

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We alternately measured on-road and in-vehicle ultrafine (<100 nm) particle (UFP) concentration for 5 passenger vehicles that comprised an age range of 18 years. A range of cabin ventilation settings were assessed during 301 trips through a 4 km road tunnel in Sydney, Australia. Outdoor airflow(ventilation) rates under these settings were quantified on open roads using tracer gas techniques. Significant variability in tunnel trip average median in-cabin/on-road (I/O) UFP ratios was observed (0.08 to ∼1.0). Based on data spanning all test automobiles and ventilation settings, a positive linear relationship was found between outdoor air flow rate and I/O ratio, with the former accounting for a substantial proportion of variation in the latter (R2 ) 0.81). UFP concentrations recorded in cabin during tunnel travel were significantly higher than those reported by comparable studies performed on open roadways. A simple mathematical model afforded the ability to predict tunnel trip average in-cabin UFP concentrations with good accuracy. Our data indicate that under certain conditions, in-cabin UFP exposures incurred during tunnel travel may contribute significantly to daily exposure. The UFP exposure of automobile occupants appears strongly related to their choice of ventilation setting and vehicle.

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The aim of this work was to quantify exposure to particles emitted by wood-fired ovens in pizzerias. Overall, 15 microenvironments were chosen and analyzed in a 14-month experimental campaign. Particle number concentration and distribution were measured simultaneously using a Condensation Particle Counter (CPC), a Scanning Mobility Particle Sizer (SMPS), an Aerodynamic Particle Sizer (APS). The surface area and mass distributions and concentrations, as well as the estimation of lung deposition surface area and PM1 were evaluated using the SMPS-APS system with dosimetric models, by taking into account the presence of aggregates on the basis of the Idealized Aggregate (IA) theory. The fraction of inhaled particles deposited in the respiratory system and different fractions of particulate matter were also measured by means of a Nanoparticle Surface Area Monitor (NSAM) and a photometer (DustTrak DRX), respectively. In this way, supplementary data were obtained during the monitoring of trends inside the pizzerias. We found that surface area and PM1 particle concentrations in pizzerias can be very high, especially when compared to other critical microenvironments, such as the transport hubs. During pizza cooking under normal ventilation conditions, concentrations were found up to 74, 70 and 23 times higher than background levels for number, surface area and PM1, respectively. A key parameter is the oven shape factor, defined as the ratio between the size of the face opening in respect

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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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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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This chapter considers the complex literate repertoires of 21st century children in multicultural primary classrooms in Adelaide South Australia. It draws on the curricular and pedagogical work of two experienced primary school teachers who explore culture, race and class, by positioning children as textual producers across a variety of media. In particular we discuss two child-authored texts – A is for Arndale – a local alphabet book co-authored by children aged between eight and ten, and – Cooking Afghani Style - a magazine style film produced by a multi-aged class of children (aged eight to thirteen) recently arrived in Australia. In the process of making these texts, primary children engaged in reading as a cultural practice – re-reading and re-writing their neighbourhoods and identities (both individual and collective). This involved frequent excursions to local key sites, both familiar and unfamiliar to the children. They investigated how diverse children experienced and lived their lives in particular places within changing communities.

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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.