997 resultados para Hoftheater (Karlsruhe, Germany)


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The second European Zebrafish Principal Investigator (PI) Meeting was held in March, 2012, in Karlsruhe, Germany. It brought together PIs from all over Europe who work with fish models such as zebrafish and medaka to discuss their latest results, as well as to resolve strategic issues faced by this research community. Scientific discussion ranged from the development of new technologies for working with fish models to progress in various fields of research such as injury and repair, disease models, and cell polarity and dynamics. This meeting also marked the establishment of the European Zebrafish Resource Centre (EZRC) at Karlsruhe that in the future will serve as an important focus and community resource for zebrafish- and medaka-based research.

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Construction and demolition (C&D) waste occupies the largest share of overall waste generation in many countries. However, waste management practices and outcomes may differ between countries. For instance, in Australia, C&D waste recovery is continuously improving during the last years but the amount of C&D waste increases every year, as there has been little improvement in waste avoidance and minimization. In contrast, in Germany, waste generation remains constant over many years despite the continuous economic growth. The waste recycling rate in Germany is one of the highest in the world. However, most waste recycled is from demolition work rather than from waste generated during new construction. In addition, specific laws need to be developed to further reduce landfill of non-recycled waste. Despite of the differences, C&D waste generation and recovery in both countries depend on the effectiveness of the statutory framework, which regulates their waste management practices. This is an issue in other parts of the world as well. Therefore countries can learn from each other to improve their current statutory framework for C&D waste management. By taking Germany and Australia as an example, possible measures to improve current practices of C&D waste management through better statutory tools are identified in this paper. After providing an overview of the statutory framework of both countries and their status in waste generation and recovery, a SWOT analysis is conducted to identify strengths, weaknesses, opportunities and threats of the statutory tools. Recommendations to improve the current statutory frameworks, in order to achieve less waste generation and more waste recovery in the construction industry are provided for the German and Australian government and they can also be transferred to other countries.

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Widespread flooding in June 2013 caused damage costs of €6 to 8 billion in Germany, and awoke many memories of the floods in August 2002, which resulted in total damage of €11.6 billion and hence was the most expensive natural hazard event in Germany up to now. The event of 2002 does, however, also mark a reorientation toward an integrated flood risk management system in Germany. Therefore, the flood of 2013 offered the opportunity to review how the measures that politics, administration, and civil society have implemented since 2002 helped to cope with the flood and what still needs to be done to achieve effective and more integrated flood risk management. The review highlights considerable improvements on many levels, in particular (1) an increased consideration of flood hazards in spatial planning and urban development, (2) comprehensive property-level mitigation and preparedness measures, (3) more effective flood warnings and improved coordination of disaster response, and (4) a more targeted maintenance of flood defense systems. In 2013, this led to more effective flood management and to a reduction of damage. Nevertheless, important aspects remain unclear and need to be clarified. This particularly holds for balanced and coordinated strategies for reducing and overcoming the impacts of flooding in large catchments, cross-border and interdisciplinary cooperation, the role of the general public in the different phases of flood risk management, as well as a transparent risk transfer system. Recurring flood events reveal that flood risk management is a continuous task. Hence, risk drivers, such as climate change, land-use changes, economic developments, or demographic change and the resultant risks must be investigated at regular intervals, and risk reduction strategies and processes must be reassessed as well as adapted and implemented in a dialogue with all stakeholders.

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Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Although these models provide information at a unprecedented resolutions and have proven to increase accuracy and effectiveness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles. For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current velocity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.

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Exploiting wind-energy is one possible way to extend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

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In a globalised world, it makes sense to examine our demands on the landscape through the wide-angle lens of ecological footprint analysis. However, the important impetus towards a more localised societal system suggests a review of this approach and a return to its origins in carrying capacity assessment. The determination of whether we live within or beyond our carrying capacity is entirely scalar, with national, regional and local assessments dependent not only on the choices of the population but the capability of a landscape - at scale. The Carrying Capacity Dashboard, an openly accessible online modelling interface, has been developed for Australian conditions, facilitating analysis at various scales. Like ecological footprint analysis it allows users to test a variety of societal behaviours such as diet, consumption patterns, farming systems and ecological protection practices; but unlike the footprint approach, the results are uniquely tailored to place. This paper examines population estimates generated by the Carrying Capacity Dashboard. It compares results in various scales of analysis, from national to local. It examines the key behavioural choices influencing Australian carrying capacity estimates. For instance, the assumption that the consumption of red meat automatically lowers carrying capacity is examined and in some cases, debunked. Lastly, it examines the implications of implementing carrying capacity assessment globally, but not through a wide angle lens; rather, by examining the landscape one locality at a time.

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Human spatial environments must adapt to climate change. Spatial planning is central to climate change adaptation and potentially well suited to the task, however neoliberal influences and trends threaten this capacity. This paper explores the potential interaction of emerging research areas, the first of which pursues climate change adaptation through spatial planning and the second of which has observed the neoliberalisation of urban planning, The potential capacity and form of spatial adaptation within the context a planning environment influenced by neoliberal principles is evaluated. This influence relates to the themes of spatial scale, temporal scale, responsibility for action, strategies and mechanisms, accrual of benefits, negotiation of priorities and approach to uncertainty. This paper presents a conceptual framework of the influence of neoliberalism on spatial adaptation and presents examples of this approach in documents which underpin adaptation in Australia. It identifies the potential characteristics and the challenges and opportunities of spatial adaptation under a neoliberal frame. The neoliberal frame does not entirely preclude spatial adaptation but significantly influence its form. Neoliberal approaches involve individual action in response to private incentives and near term impacts while collective action, regulatory mechanisms and long term planning is approached cautiously. Challenges concern the degree to which collective action and a long term orientation are necessary, how individual adaptation relates to collective vulnerability and the prioritisation of adaptation by markets. Opportunities might involve the operability of individual and local adaptation, the existence of private incentives to adapt and the potential to align adaptation with entrepreneurial projects.

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Urban design that harnesses natural features (such as green roofs and green walls) to improve design outcomes is gaining significant interest, particularly as there is growing evidence of links between human health and wellbeing, and contact with nature. The use of such natural features can provide many significant benefits, such as reduced urban heat island effects, reduced peak energy demand for building cooling, enhanced stormwater attenuation and management, and reduced air pollution and greenhouse gas emissions. The principle of harnessing natural features as functional design elements, particularly in buildings, is becoming known as ‘biophilic urbanism’. Given the potential for global application and benefits for cities from biophilic urbanism, and the growing number of successful examples of this, it is timely to develop enabling policies that help overcome current barriers to implementation. This paper describes a basis for inquiry into policy considerations related to increasing the application of biophilic urbanism. The paper draws on research undertaken as part of the Sustainable Built Environment National Research Centre (SBEnrc) In Australia in partnership with the Western Australian Department of Finance, Parsons Brinckerhoff, Green Roofs Australasia, and Townsville City Council (CitySolar Program). The paper discusses the emergence of a qualitative, mixed-method approach that combines an extensive literature review, stakeholder workshops and interviews, and a detailed study of leading case studies. It highlights the importance of experiential and contextual learnings to inform biophilic urbanism and provides a structure to distil such learnings to benefit other applications.

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Modern mobile computing devices are versatile, but bring the burden of constant settings adjustment according to the current conditions of the environment. While until today, this task has to be accomplished by the human user, the variety of sensors usually deployed in such a handset provides enough data for autonomous self-configuration by a learning, adaptive system. However, this data is not fully available at certain points in time, or can contain false values. Handling potentially incomplete sensor data to detect context changes without a semantic layer represents a scientific challenge which we address with our approach. A novel machine learning technique is presented - the Missing-Values-SOM - which solves this problem by predicting setting adjustments based on context information. Our method is centered around a self-organizing map, extending it to provide a means of handling missing values. We demonstrate the performance of our approach on mobile context snapshots, as well as on classical machine learning datasets.

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This paper presents an Image Based Visual Servo control design for Fixed Wing Unmanned Aerial Vehicles tracking locally linear infrastructure in the presence of wind using a body fixed imaging sensor. Visual servoing offers improved data collection by posing the tracking task as one of controlling a feature as viewed by the inspection sensor, although is complicated by the introduction of wind as aircraft heading and course angle no longer align. In this work it is shown that the effects of wind alter the desired line angle required for continuous tracking to equal the wind correction angle as would be calculated to set a desired course. A control solution is then sort by linearizing the interaction matrix about the new feature pose such that kinematics of the feature can be augmented with the lateral dynamics of the aircraft, from which a state feedback control design is developed. Simulation results are presented comparing no compensation, integral control and the proposed controller using the wind correction angle, followed by an assessment of response to atmospheric disturbances in the form of turbulence and wind gusts

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This paper addresses the problem of automatically estimating the relative pose between a push-broom LIDAR and a camera without the need for artificial calibration targets or other human intervention. Further we do not require the sensors to have an overlapping field of view, it is enough that they observe the same scene but at different times from a moving platform. Matching between sensor modalities is achieved without feature extraction. We present results from field trials which suggest that this new approach achieves an extrinsic calibration accuracy of millimeters in translation and deci-degrees in rotation.

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The building sector is the dominant consumer of energy and therefore a major contributor to anthropomorphic climate change. The rapid generation of photorealistic, 3D environment models with incorporated surface temperature data has the potential to improve thermographic monitoring of building energy efficiency. In pursuit of this goal, we propose a system which combines a range sensor with a thermal-infrared camera. Our proposed system can generate dense 3D models of environments with both appearance and temperature information, and is the first such system to be developed using a low-cost RGB-D camera. The proposed pipeline processes depth maps successively, forming an ongoing pose estimate of the depth camera and optimizing a voxel occupancy map. Voxels are assigned 4 channels representing estimates of their true RGB and thermal-infrared intensity values. Poses corresponding to each RGB and thermal-infrared image are estimated through a combination of timestamp-based interpolation and a pre-determined knowledge of the extrinsic calibration of the system. Raycasting is then used to color the voxels to represent both visual appearance using RGB, and an estimate of the surface temperature. The output of the system is a dense 3D model which can simultaneously represent both RGB and thermal-infrared data using one of two alternative representation schemes. Experimental results demonstrate that the system is capable of accurately mapping difficult environments, even in complete darkness.