977 resultados para GPS denied environments


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In many prediction problems, including those that arise in computer security and computational finance, the process generating the data is best modelled as an adversary with whom the predictor competes. Even decision problems that are not inherently adversarial can be usefully modeled in this way, since the assumptions are sufficiently weak that effective prediction strategies for adversarial settings are very widely applicable.

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The problem of decision making in an uncertain environment arises in many diverse contexts: deciding whether to keep a hard drive spinning in a net-book; choosing which advertisement to post to a Web site visitor; choosing how many newspapers to order so as to maximize profits; or choosing a route to recommend to a driver given limited and possibly out-of-date information about traffic conditions. All are sequential decision problems, since earlier decisions affect subsequent performance; all require adaptive approaches, since they involve significant uncertainty. The key issue in effectively solving problems like these is known as the exploration/exploitation trade-off: If I am at a cross-roads, when should I go in the most advantageous direction among those that I have already explored, and when should I strike out in a new direction, in the hopes I will discover something better?

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The performance of automatic speech recognition systems deteriorates in the presence of noise. One known solution is to incorporate video information with an existing acoustic speech recognition system. We investigate the performance of the individual acoustic and visual sub-systems and then examine different ways in which the integration of the two systems may be performed. The system is to be implemented in real time on a Texas Instruments' TMS320C80 DSP.

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In dynamic and uncertain environments such as healthcare, where the needs of security and information availability are difficult to balance, an access control approach based on a static policy will be suboptimal regardless of how comprehensive it is. The uncertainty stems from the unpredictability of users’ operational needs as well as their private incentives to misuse permissions. In Role Based Access Control (RBAC), a user’s legitimate access request may be denied because its need has not been anticipated by the security administrator. Alternatively, even when the policy is correctly specified an authorised user may accidentally or intentionally misuse the granted permission. This paper introduces a novel approach to access control under uncertainty and presents it in the context of RBAC. By taking insights from the field of economics, in particular the insurance literature, we propose a formal model where the value of resources are explicitly defined and an RBAC policy (entailing those predictable access needs) is only used as a reference point to determine the price each user has to pay for access, as opposed to representing hard and fast rules that are always rigidly applied.

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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.

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Probabilistic topic models have recently been used for activity analysis in video processing, due to their strong capacity to model both local activities and interactions in crowded scenes. In those applications, a video sequence is divided into a collection of uniform non-overlaping video clips, and the high dimensional continuous inputs are quantized into a bag of discrete visual words. The hard division of video clips, and hard assignment of visual words leads to problems when an activity is split over multiple clips, or the most appropriate visual word for quantization is unclear. In this paper, we propose a novel algorithm, which makes use of a soft histogram technique to compensate for the loss of information in the quantization process; and a soft cut technique in the temporal domain to overcome problems caused by separating an activity into two video clips. In the detection process, we also apply a soft decision strategy to detect unusual events.We show that the proposed soft decision approach outperforms its hard decision counterpart in both local and global activity modelling.

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In this paper, we present a method for the recovery of position and absolute attitude (including pitch, roll and yaw) using a novel fusion of monocular Visual Odometry and GPS measurements in a similar manner to a classic loosely-coupled GPS/INS error state navigation filter. The proposed filter does not require additional restrictions or assumptions such as platform-specific dynamics, map-matching, feature-tracking, visual loop-closing, gravity vector or additional sensors such as an IMU or magnetic compass. An observability analysis of the proposed filter is performed, showing that the scale factor, position and attitude errors are fully observable under acceleration that is non-parallel to velocity vector in the navigation frame. The observability properties of the proposed filter are demonstrated using numerical simulations. We conclude the article with an implementation of the proposed filter using real flight data collected from a Cessna 172 equipped with a downwards-looking camera and GPS, showing the feasibility of the algorithm in real-world conditions.

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In a study aimed at better understanding how staff and students adapt to new blended studio learning environments (BSLE’s), a group of 165 second year architecture students at a large school of architecture in Australia were separated into two different design studio learning environments. 70% of students were allocated to a traditional studio design learning environment (TSLE) and 30% to a new, high technology embedded, prototype digital learning laboratory. The digital learning laboratory was purpose designed for the case-study users, adapted Student-Centred Active Learning Environment for Undergraduate Programs (SCALE-UP) principles, and built as part of a larger university research project. The architecture students attended the same lectures, followed the same studio curriculum and completed the same pieces of assessment; the only major differences were the teaching staff and physical environment within which the studios were conducted. At the end of the semester, the staff and students were asked to complete a questionnaire about their experiences and preferences within the two respective learning environments. Following this, participants were invited to participate in focus groups, where a synergistic approach was effected. Using a dual method qualitative approach, the questionnaire and survey data were coded and extrapolated using both thematic analysis and grounded theory methodology. The results from these two different approaches were compared, contrasted and finally merged, to reveal six distinct emerging themes, which were instrumental in offering resistance or influencing adaptation to, the new BLSE. This paper reports on the study, discusses the major contributors to negative resistance and proposes points for consideration, when transitioning from a TSLE to a BLSE.

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Although, transportation disadvantage or imbalance between travel needs and supply of transportation system is a great harm to knowledge based environments, quantification and objectively measuring the state of transportation disadvantaged remain to be a great challenge for researcher due to its ambiguity. This poses questions of whether the current indicators are accurately linked with transportation disadvantages and the effectiveness of the current policies. Using current indicators of transportation disadvantages, the state of transportation disadvantage is often exaggerated due to limited afford has been put forward to provide clear assessment on the existed relationship between transportation disadvantage indicators with travel performance or capability. This paper proposes a structural equation model of transportation disadvantage using household variables gained from the 2006-2008 South-East Queensland Travel Survey (SEQTS). The underlying relationships between social economics and demographic characteristics of household with travel performance are modelled using a latent variable approach. The final model has been able to fit the data gathered from SEQTS and explained established links between key household factors with travel capability and determined key indicator of travel capability. The model recognises that travel capability is directly influenced by household factors; vehicle ratio, license possession, retirees and pensioners.

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This key planning textbook on designing healthy and sustainable communities informs planners about community life and the processes of planning and equips them with the essential knowledge and skills they need to organise change and improve the quality of urban living. The author examines the impacts of social and economic change on community life and organization and explores ways in which these changes can be planned and managed. Community planning is presented as a means to balance and integrate beneficial change with the maintenance of valued cultural traditions and life styles. This involves bringing together fields of study and practice including urban and regional planning, design, communication, housing, community organization, employment, transport, and governance. Links drawn between personal values, human activities, physical spaces and societal governance assist this process of synthesis. Establishing a common vocabulary to discuss planning - for urban and regional planners, including health planners; and open space planners - enables both students and practitioners to work with each other and with those for whom they provide services to create stronger, healthier and more sustainable communities. The aims and roles of community planning are explored and the key planning operations are explained, including the phases and applications of community planning method; the planning and location of community facilities; the roles of design in shaping responsive community spaces; and the capacity of different types of community governance to improve the relations between citizens and societies. The book is organized into two main parts: after the first three chapters have established the interests and scope of community planning, the next six each moves from an account of issues and theoretical concerns, through a review of case studies, to summaries of leading practice. This positive approach is intended to encourage readers to develop their own capacities for effective participation and action. The concluding chapter draws together the contributions of preceding ones to demonstrate the integrity of the community planning process

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Many of the teaching elements in Civil and Environmental Engineering and Spatial Science/Surveying are strongly related to multidisciplinary real-world situations. Professionals in each discipline commonly work collaboratively, knowing each other’s professional and technical limitations and requirements. Replication of such real-world situations allows students to gain an insight and acquire knowledge of professional practice for both civil engineering and spatial science disciplines. However, replication of an authentic design project is not always possible in a single unit basis where empirical project situations are often created with controlled sets of constraints, inputs and outputs. A cross-disciplinary design-based project that is designed to promote active student learning, engagement and professional integration would be the preferred option. The central aim of this collaborative project was to create positive and inclusive environments to promote engaging learning opportunities that cater for a range of learning styles with a two-way linkage involving third-year civil engineering and spatial science (surveying) students. This paper describes the cross-disciplinary project developed and delivered in 2010 and 2011. A survey was conducted at completion of the project to assess the degree of improvement in student engagement and their learning experiences. Improvements were assessed in a range of dimensions including student motivation, learning by cross-disciplinary collaboration and learning by authentic design project experiences. In this specific cross-disciplinary linkage project, the study findings showed that teaching approaches utilised have been effective in promoting active student learning and increasing engagement.

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Though stadium style seating in large lecture theatres may suggest otherwise, effective teaching and learning is a not a spectator sport. A challenge in creating effective learning environments in both physical and virtual spaces is to provide optimal opportunity for student engagement in active learning. Queensland University of Technology (QUT) has developed the Open Web Lecture (OWL), a new web-based student response application, which seamlessly integrates a virtual learning environment within the physical learning space. The result is a blended learning experience; a fluid collaboration between academic and students connected to OWL via the University’s Wi-Fi using their own laptop or mobile web device. QUT is currently piloting the OWL application to encourage student engagement. OWL offers opportunities for participants to: • Post comments and questions • Reply to comments
 • "Like" comments
 • Poll students and review data • Review archived sessions. Many of these features instinctively appeal to student users of social networking media, yet avail the academic of control within the University network. Student privacy is respected through a system of preserving peer-peer anonymity, a functionality that seeks to address a traditional reluctance to speak up in large classes. The pilot is establishing OWL as an opportunity for engaging students in active learning opportunities by enabling • virtual learning in physical spaces for large group lectures, seminar groups, workshops and conferences • live collaborative technology connecting students and the academic via the wireless network using their own laptop or mobile device • an non- intimidating environment in which to ask questions • promotion of a sense of community • instant feedback • problem based learning. The student and academic response to OWL has been overwhelmingly positive, crediting OWL as an easy to use application, which creates effective learning opportunities though interactivity and immediate feedback. This poster and accompanying online presentation of the technology will demonstrate how OWL offers new possibilities for active learning in physical spaces by: • providing increased opportunity for student engagement • supporting a range of learners and learning activities • fostering blended learning experiences. The presentation will feature visual displays of the technology, its various interfaces and feedback including clips from interviews with students and academics participating in the early stages of the pilot.

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In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountain biking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.

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Virtual environments can provide, through digital games and online social interfaces, extremely exciting forms of interactive entertainment. Because of their capability in displaying and manipulating information in natural and intuitive ways, such environments have found extensive applications in decision support, education and training in the health and science domains amongst others. Currently, the burden of validating both the interactive functionality and visual consistency of a virtual environment content is entirely carried out by developers and play-testers. While considerable research has been conducted in assisting the design of virtual world content and mechanics, to date, only limited contributions have been made regarding the automatic testing of the underpinning graphics software and hardware. The aim of this thesis is to determine whether the correctness of the images generated by a virtual environment can be quantitatively defined, and automatically measured, in order to facilitate the validation of the content. In an attempt to provide an environment-independent definition of visual consistency, a number of classification approaches were developed. First, a novel model-based object description was proposed in order to enable reasoning about the color and geometry change of virtual entities during a play-session. From such an analysis, two view-based connectionist approaches were developed to map from geometry and color spaces to a single, environment-independent, geometric transformation space; we used such a mapping to predict the correct visualization of the scene. Finally, an appearance-based aliasing detector was developed to show how incorrectness too, can be quantified for debugging purposes. Since computer games heavily rely on the use of highly complex and interactive virtual worlds, they provide an excellent test bed against which to develop, calibrate and validate our techniques. Experiments were conducted on a game engine and other virtual worlds prototypes to determine the applicability and effectiveness of our algorithms. The results show that quantifying visual correctness in virtual scenes is a feasible enterprise, and that effective automatic bug detection can be performed through the techniques we have developed. We expect these techniques to find application in large 3D games and virtual world studios that require a scalable solution to testing their virtual world software and digital content.