379 resultados para Intelligent Environments


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Ocean processes are dynamic, complex, and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high-value data. More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path, while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long-term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show significant improvements in data resolution and path reliability compared to previously executed sampling paths used in the respective regions.

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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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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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This paper defines and discusses two contrasting approaches to designing game environments. The first, referred to as scripting, requires developers to anticipate, hand-craft and script specific game objects, events and player interactions. The second, known as emergence, involves defining general, global rules that interact to give rise to emergent gameplay. Each of these approaches is defined, discussed and analyzed with respect to the considerations and affects for game developers and game players. Subsequently, various techniques for implementing these design approaches are identified and discussed. It is concluded that scripting and emergence are two extremes of the same continuum, neither of which are ideal for game development. Rather, there needs to be a compromise in which the boundaries of action (such as story and game objectives) can be hardcoded and non-scripted behavior (such as interactions and strategies) are able to emerge within these boundaries.

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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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On obstacle-cluttered construction sites where heavy equipment is in use, safety issues are of major concern. The main objective of this paper is to develop a framework with algorithms for obstacle avoidance and path planning based on real-time three-dimensional job site models to improve safety during equipment operation. These algorithms have the potential to prevent collisions between heavy equipment vehicles and other on-site objects. In this study, algorithms were developed for image data acquisition, real-time 3D spatial modeling, obstacle avoidance, and shortest path finding and were all integrated to construct a comprehensive collision-free path. Preliminary research results show that the proposed approach is feasible and has the potential to be used as an active safety feature for heavy equipment.

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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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Many modern business environments employ software to automate the delivery of workflows; whereas, workflow design and generation remains a laborious technical task for domain specialists. Several differ- ent approaches have been proposed for deriving workflow models. Some approaches rely on process data mining approaches, whereas others have proposed derivations of workflow models from operational struc- tures, domain specific knowledge or workflow model compositions from knowledge-bases. Many approaches draw on principles from automatic planning, but conceptual in context and lack mathematical justification. In this paper we present a mathematical framework for deducing tasks in workflow models from plans in mechanistic or strongly controlled work environments, with a focus around automatic plan generations. In addition, we prove an associative composition operator that permits crisp hierarchical task compositions for workflow models through a set of mathematical deduction rules. The result is a logical framework that can be used to prove tasks in workflow hierarchies from operational information about work processes and machine configurations in controlled or mechanistic work environments.