670 resultados para Light Design
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In the design studio learning environment, traditional student and staff expectations are of close contact teaching and learning. In recent years at QUT students have experienced reduced personal staff attention, and have increasingly felt “anonymous” and correspondingly disengaged, to the detriment of quality learning (Carbone 1998: 8; Biggs 2003). Concurrently, there has been a necessary increase in teaching by sessional staff at QUT with varied levels of experience and assurance. This paper outlines the first iteration of an action research project exploring whether changing the current QUT design studio student and staff relationships may lead to more engaged, dynamic learning environments. “Engagement” is understood as a primarily emotional, rather than operational student concern (Solomonides and Martin 2008; Austerlitz and Aravot 2007). The project inverted the standard QUT design studio teaching structure, and evaluated the new structure and activation of student engagement across four identified markers: attendance, participation, learning and performance (ACER 2009; NSSE 2005; Chapman 2003). Student and staff surveys and focus groups, corporate data, and informal feedback informed these evaluations. Overall, the results support the premise that when students and staff feel part of a reasonably-sized studio class with a dedicated lecturer and self-selected project, the majority are inclined to value these relationships, to feel actively engaged, and to experience some improvement in their learning and teaching performances.
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This action research examines the enhancement of visual communication within the architectural design studio through physical model making. „It is through physical model making that designers explore their conceptual ideas and develop the creation and understanding of space,‟ (Salama & Wilkinson 2007:126). This research supplements Crowther‟s findings extending the understanding of visual dialogue to include physical models. „Architecture Design 8‟ is the final core design unit at QUT in the fourth year of the Bachelor of Design Architecture. At this stage it is essential that students have the ability to communicate their ideas in a comprehensive manner, relying on a combination of skill sets including drawing, physical model making, and computer modeling. Observations within this research indicates that students did not integrate the combination of the skill sets in the design process through the first half of the semester by focusing primarily on drawing and computer modeling. The challenge was to promote deeper learning through physical model making. This research addresses one of the primary reasons for the lack of physical model making, which was the limited assessment emphasis on the physical models. The unit was modified midway through the semester to better correlate the lecture theory with studio activities by incorporating a series of model making exercises conducted during the studio time. The outcome of each exercise was assessed. Tutors were surveyed regarding the model making activities and a focus group was conducted to obtain formal feedback from students. Students and tutors recognised the added value in communicating design ideas through physical forms and model making. The studio environment was invigorated by the enhanced learning outcomes of the students who participated in the model making exercises. The conclusions of this research will guide the structure of the upcoming iteration of the fourth year design unit.
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The aim of this paper is to aid researchers in selecting appropriate qualitative methods in order to develop and improve future studies in the field of emotional design. These include observations, think-aloud protocols, questionnaires, diaries and interviews. Based on the authors’ experiences, it is proposed that the methods under review can be successfully used for collecting data on emotional responses to evaluate user product relationships. This paper reviews the methods; discusses the suitability, advantages and challenges in relation to design and emotion studies. Furthermore, the paper outlines the potential impact of technology on the application of these methods, discusses the implications of these methods for emotion research and concludes with recommendations for future work in this area.
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We aim to demonstrate unaided visual 3D pose estimation and map reconstruction using both monocular and stereo vision techniques. To date, our work has focused on collecting data from Unmanned Aerial Vehicles, which generates a number of significant issues specific to the application. Such issues include scene reconstruction degeneracy from planar data, poor structure initialisation for monocular schemes and difficult 3D reconstruction due to high feature covariance. Most modern Visual Odometry (VO) and related SLAM systems make use of a number of sensors to inform pose and map generation, including laser range-finders, radar, inertial units and vision [1]. By fusing sensor inputs, the advantages and deficiencies of each sensor type can be handled in an efficient manner. However, many of these sensors are costly and each adds to the complexity of such robotic systems. With continual advances in the abilities, small size, passivity and low cost of visual sensors along with the dense, information rich data that they provide our research focuses on the use of unaided vision to generate pose estimates and maps from robotic platforms. We propose that highly accurate (�5cm) dense 3D reconstructions of large scale environments can be obtained in addition to the localisation of the platform described in other work [2]. Using images taken from cameras, our algorithm simultaneously generates an initial visual odometry estimate and scene reconstruction from visible features, then passes this estimate to a bundle-adjustment routine to optimise the solution. From this optimised scene structure and the original images, we aim to create a detailed, textured reconstruction of the scene. By applying such techniques to a unique airborne scenario, we hope to expose new robotic applications of SLAM techniques. The ability to obtain highly accurate 3D measurements of an environment at a low cost is critical in a number of agricultural and urban monitoring situations. We focus on cameras as such sensors are small, cheap and light-weight and can therefore be deployed in smaller aerial vehicles. This, coupled with the ability of small aerial vehicles to fly near to the ground in a controlled fashion, will assist in increasing the effective resolution of the reconstructed maps.
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Purpose: In the global knowledge economy, investment in knowledge-intensive industries and information and communication technology (ICT) infrastructures are seen as significant factors in improving the overall socio-economic fabric of cities. Consequently knowledge-based urban development (KBUD) has become a new paradigm in urban planning and development, for increasing the welfare and competitiveness of cities and regions. The paper discusses the critical connections between KBUD strategies and knowledge-intensive industries and ICT infrastructures. In particular, it investigates the application of the knowledge-based urban development concept by discussing one of South East Asia’s large scale manifestations of KBUD; Malaysia’s Multimedia Super Corridor. ----- ----- Design/methodology/approach: The paper provides a review of the KBUD concept and develops a knowledge-based urban development assessment framework to provide a clearer understanding of development and evolution of KBUD manifestations. Subsequently the paper investigates the implementation of the KBUD concept within the Malaysian context, and particularly the Multimedia Super Corridor (MSC). ----- ----- Originality/value: The paper, with its KBUD assessment framework, scrutinises Malaysia’s experince; providing an overview of the MSC project and discussion of the case findings. The development and evolution of the MSC is viewed with regard to KBUD policy implementation, infrastructural implications, and the agencies involved in the development and management of the MSC. ----- ----- Practical implications: The emergence of the knowledge economy, together with the issues of globalisation and rapid urbanisation, have created an urgent need for urban planners to explore new ways of strategising planning and development that encompasses the needs and requirements of the knowledge economy and society. In light of the literature and MSC case findings, the paper provides generic recommendations, on the orchestration of knowledge-based urban development, for other cities and regions seeking to transform to the knowledge economy.
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Water Sensitive Urban Design (WSUD) practices such as wetlands, bioretention systems and swales are widely implemented in Australia’s urban areas for the mitigation of stormwater pollution and to enhance its reuse potential. In-depth research undertaken has confirmed that these systems do not always perform according to design expectations due to a diversity of reasons. To deliver anticipated benefits, it is critical that they are designed in conformity with catchment and rainfall characteristics and pollutant processes. This in turn entails an in-depth understanding of key pollutant processes. This paper presents the outcomes of extensive research investigations on pollutant characterisation and stormwater pollutant processes on urban catchment surfaces. Outcomes from the research studies revealed the complexities in physical and chemical characteristics of pollutants originating from urban catchments which are strongly influenced by rainfall and catchment characteristics. Based on the research outcomes, recommendations are provided to enhance stormwater treatment performance and to enhance its reuse potential.
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Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceano- graphic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to manoeuvre through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.
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In this paper, we present a control strategy design technique for an autonomous underwater vehicle based on solutions to the motion planning problem derived from differential geometric methods. The motion planning problem is motivated by the practical application of surveying the hull of a ship for implications of harbor and port security. In recent years, engineers and researchers have been collaborating on automating ship hull inspections by employing autonomous vehicles. Despite the progresses made, human intervention is still necessary at this stage. To increase the functionality of these autonomous systems, we focus on developing model-based control strategies for the survey missions around challenging regions, such as the bulbous bow region of a ship. Recent advances in differential geometry have given rise to the field of geometric control theory. This has proven to be an effective framework for control strategy design for mechanical systems, and has recently been extended to applications for underwater vehicles. Advantages of geometric control theory include the exploitation of symmetries and nonlinearities inherent to the system. Here, we examine the posed inspection problem from a path planning viewpoint, applying recently developed techniques from the field of differential geometric control theory to design the control strategies that steer the vehicle along the prescribed path. Three potential scenarios for surveying a ship?s bulbous bow region are motivated for path planning applications. For each scenario, we compute the control strategy and implement it onto a test-bed vehicle. Experimental results are analyzed and compared with theoretical predictions.
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Designing trajectories for a submerged rigid body motivates this paper. Two approaches are addressed: the time optimal approach and the motion planning ap- proach using concatenation of kinematic motions. We focus on the structure of singular extremals and their relation to the existence of rank-one kinematic reduc- tions; thereby linking the optimization problem to the inherent geometric frame- work. Using these kinematic reductions, we provide a solution to the motion plan- ning problem in the under-actuated scenario, or equivalently, in the case of actuator failures. We finish the paper comparing a time optimal trajectory to one formed by concatenation of pure motions.
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Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.
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Harmful Algal Blooms (HABs) have become an important environmental concern along the western coast of the United States. Toxic and noxious blooms adversely impact the economies of coastal communities in the region, pose risks to human health, and cause mortality events that have resulted in the deaths of thousands of fish, marine mammals and seabirds. One goal of field-based research efforts on this topic is the development of predictive models of HABs that would enable rapid response, mitigation and ultimately prevention of these events. In turn, these objectives are predicated on understanding the environmental conditions that stimulate these transient phenomena. An embedded sensor network (Fig. 1), under development in the San Pedro Shelf region off the Southern California coast, is providing tools for acquiring chemical, physical and biological data at high temporal and spatial resolution to help document the emergence and persistence of HAB events, supporting the design and testing of predictive models, and providing contextual information for experimental studies designed to reveal the environmental conditions promoting HABs. The sensor platforms contained within this network include pier-based sensor arrays, ocean moorings, HF radar stations, along with mobile sensor nodes in the form of surface and subsurface autonomous vehicles. FreewaveTM radio modems facilitate network communication and form a minimally-intrusive, wireless communication infrastructure throughout the Southern California coastal region, allowing rapid and cost-effective data transfer. An emerging focus of this project is the incorporation of a predictive ocean model that assimilates near-real time, in situ data from deployed Autonomous Underwater Vehicles (AUVs). The model then assimilates the data to increase the skill of both nowcasts and forecasts, thus providing insight into bloom initiation as well as the movement of blooms or other oceanic features of interest (e.g., thermoclines, fronts, river discharge, etc.). From these predictions, deployed mobile sensors can be tasked to track a designated feature. This focus has led to the creation of a technology chain in which algorithms are being implemented for the innovative trajectory design for AUVs. Such intelligent mission planning is required to maneuver a vehicle to precise depths and locations that are the sites of active blooms, or physical/chemical features that might be sources of bloom initiation or persistence. The embedded network yields high-resolution, temporal and spatial measurements of pertinent environmental parameters and resulting biology (see Fig. 1). Supplementing this with ocean current information and remotely sensed imagery and meteorological data, we obtain a comprehensive foundation for developing a fundamental understanding of HAB events. This then directs labor- intensive and costly sampling efforts and analyses. Additionally, we provide coastal municipalities, managers and state agencies with detailed information to aid their efforts in providing responsible environmental stewardship of their coastal waters.
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This paper discusses control strategies adapted for practical implementation and efficient motion of underwater vehicles. These trajectories are piecewise constant thrust arcs with few actuator switchings. We provide the numerical algorithm which computes the time efficient trajectories parameterized by the switching times. We discuss both the theoretical analysis and experimental implementation results.
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One of the major challenges in the design of social technologies is the evaluation of their qualities of use and how they are appropriated over time. While the field of HCI abounds in short-term exploratory design and studies of use, relatively little attention has focused on the continuous development of prototypes longitudinally and studies of their emergent use. We ground the exploration and analysis of use in the everyday world, embracing contingency and open-ended use, through the use of a continuously-available exploratory prototype. Through examining use longitudinally, clearer insight can be gained of realistic, non-novelty usage and appropriation into everyday use. This paper sketches out a framework for design that puts a premium on immediate use and evolving the design in response to use and user feedback. While such design practices with continuously developing systems are common in the design of social technologies, they are little documented. We describe our approach and reflect upon its key characteristics, based on our experiences from two case studies. We also present five major patterns of long-term usage which we found useful for design.