956 resultados para environmental modeling
Resumo:
The uptake of sustainability initiatives in early childhood education curricula continues to gain momentum in Australia and internationally. Growing awareness about the fragility of natural environments in local and global contexts, along with prioritising sustainability in educational policy, has resulted in more broad-scale responses to sustainability in early years settings. To address issues of sustainability, many childcare centres and schools focus on environmental initiatives such as garden projects, recycling and water conservation. While important, such initiatives respond to just one dimension of sustainability. With expanding focus on sustainability initiatives in early childhood education, it is timely to consider why the environmental dimension receives the most attention and what this means for social, political and economic areas of concern.
Resumo:
We contribute an empirically derived noise model for the Kinect sensor. We systematically measure both lateral and axial noise distributions, as a function of both distance and angle of the Kinect to an observed surface. The derived noise model can be used to filter Kinect depth maps for a variety of applications. Our second contribution applies our derived noise model to the KinectFusion system to extend filtering, volumetric fusion, and pose estimation within the pipeline. Qualitative results show our method allows reconstruction of finer details and the ability to reconstruct smaller objects and thinner surfaces. Quantitative results also show our method improves pose estimation accuracy. © 2012 IEEE.
Resumo:
In the commercial food industry, demonstration of microbiological safety and thermal process equivalence often involves a mathematical framework that assumes log-linear inactivation kinetics and invokes concepts of decimal reduction time (DT), z values, and accumulated lethality. However, many microbes, particularly spores, exhibit inactivation kinetics that are not log linear. This has led to alternative modeling approaches, such as the biphasic and Weibull models, that relax strong log-linear assumptions. Using a statistical framework, we developed a novel log-quadratic model, which approximates the biphasic and Weibull models and provides additional physiological interpretability. As a statistical linear model, the log-quadratic model is relatively simple to fit and straightforwardly provides confidence intervals for its fitted values. It allows a DT-like value to be derived, even from data that exhibit obvious "tailing." We also showed how existing models of non-log-linear microbial inactivation, such as the Weibull model, can fit into a statistical linear model framework that dramatically simplifies their solution. We applied the log-quadratic model to thermal inactivation data for the spore-forming bacterium Clostridium botulinum and evaluated its merits compared with those of popular previously described approaches. The log-quadratic model was used as the basis of a secondary model that can capture the dependence of microbial inactivation kinetics on temperature. This model, in turn, was linked to models of spore inactivation of Sapru et al. and Rodriguez et al. that posit different physiological states for spores within a population. We believe that the log-quadratic model provides a useful framework in which to test vitalistic and mechanistic hypotheses of inactivation by thermal and other processes. Copyright © 2009, American Society for Microbiology. All Rights Reserved.
Resumo:
Significance of colour schemes in appraisal of the urban aesthetic has been traditionally recognised by design professionals. However, the proven psychological and emotional impacts of urban colour remain overlooked in design thinking. This paper argues that health-conscious approach to environmental colour design requires consideration of phenomenological human needs in addition to aesthetic and stylistic preferences of a designer. A body of knowledge accumulated in environmental colour psychology provides a foundation for a shift in the environmental colour design. Though, some architectural critics suggest that design professionals have little understanding of how different aspects of colour psychology can be integrated in design process. Lack of an explicit design methodology has been described as a main constraint to applicability of the related knowledge in design process. Understanding the notion of environmental colour is essential in developing health-conscious approach to environmental colour design. Therefore, this paper is primarily focused on conceptualisation of environmental colour and experiential environmental colour design. Additionally, a role of environmental colour design in the delivery of health-enhancing environments and balanced sensorial experiences is briefly discussed.
Resumo:
This paper proposes a linear large signal state-space model for a phase controlled CLC (Capacitor Inductor Capacitor) Resonant Dual Active Bridge (RDAB). The proposed model is useful for fast simulation and for the estimation of state variables under large signal variation. The model is also useful for control design because the slow changing dynamics of the dq variables are relatively easy to control. Simulation results of the proposed model are presented and compared to the simulated circuit model to demonstrate the proposed model's accuracy. This proposed model was used for the design of a Proportional-Integral (PI) controller and it has been implemented in the circuit simulation to show the proposed models usefulness in control design.
Resumo:
Steel hollow sections used in structures such as bridges, buildings and space structures involve different strengthening techniques according to their structural purpose and shape of the structural member. One such technique is external bonding of CFRP sheets to steel tubes. The performance of CFRP strengthening for steel structures has been proven under static loading while limited studies have been conducted on their behaviour under impact loading. In this study, a comprehensive numerical investigation is carried out to evaluate the response of CFRP strengthened steel tubes under dynamic axial impact loading. Impact force, axial deformation impact velocities are studied. The results of the numerical investigations are validated by experimental results. Based on the developed finite element (FE) model several output parameters are discussed. The results show that CFRP wrapping is an effective strengthening technique to increase the axial dynamic load bearing capacity by increasing the stiffness of the steel tube.
Resumo:
Process modeling – the design and use of graphical documentations of an organization’s business processes – is a key method to document and use information about the operations of businesses. Still, despite current interest in process modeling, this research area faces essential challenges. Key unanswered questions concern the impact of process modeling in organizational practice, and the mechanisms through which impacts are developed. To answer these questions and to provide a better understanding of process modeling impact, I turn to the concept of affordances. Affordances describe the possibilities for goal-oriented action that a technical object offers to a user. This notion has received growing attention from IS researchers. The purpose of my research is to further develop the IS discipline’s understanding of affordances and impacts from information objects, such as process models used by analysts for information systems analysis and design. Specifically, I seek to extend existing theory on the emergence, perception and actualization of affordances. I develop a research model that describes the process by which affordances emerge between an individual and an object, how affordances are perceived, and how they are actualized by the individual. The proposed model also explains the role of available information for the individual, and the influence of perceived actualization effort. I operationalize and test this research model empirically, using a full-cycle, mixed methods study consisting of case study and experiment.
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Hydraulic conductivity (K) fields are used to parameterize groundwater flow and transport models. Numerical simulations require a detailed representation of the K field, synthesized to interpolate between available data. Several recent studies introduced high-resolution K data (HRK) at the Macro Dispersion Experiment (MADE) site, and used ground-penetrating radar (GPR) to delineate the main structural features of the aquifer. This paper describes a statistical analysis of these data, and the implications for K field modeling in alluvial aquifers. Two striking observations have emerged from this analysis. The first is that a simple fractional difference filter can have a profound effect on data histograms, organizing non-Gaussian ln K data into a coherent distribution. The second is that using GPR facies allows us to reproduce the significantly non-Gaussian shape seen in real HRK data profiles, using a simulated Gaussian ln K field in each facies. This illuminates a current controversy in the literature, between those who favor Gaussian ln K models, and those who observe non-Gaussian ln K fields. Both camps are correct, but at different scales.
Resumo:
Magnetic properties of soils have been highlighted as a primary detrimental environmental effect on the performance of geophysical systems for detection of unexploded ordnance (UXO) and mine targets. A recent workshop at Cranfield University, U.K., aimed to identify knowledge gaps related to soil magnetism. Eight invited speakers from multidisciplinary areas provided briefings on state‐of‐the‐art research linked to soil magnetism and geophysical sensing. Contributions from other participants provided additional insights from a range of disciplines through case studies and applications. The workshop included break‐out sessions to identify current gaps in knowledge and to determine priority areas for investment in research to further developments in UXO and mine detection in magnetic soil environments. Key recommendations for future research investments have been grouped in categories including soils, theory and modeling, instrumentation, and communication.
Resumo:
For decades, social scientists have searched for factors that shape pro-environmental behaviour. However, only a few studies have investigated the causes and consequences of participation in environmental organizations. This book fills the gap by analysing in detail the determinants of environmental participation and its consequences in different parts of the world. Benno Torgler, María A. García-Valinas and Alison Macintyre seek the answer to several questions regarding who is working towards positive outcomes for our environment, what sort of social and institutional context will assist voluntary participation, what sort of attitudes are related to positive environmental behavior, and which countries are active on the intergovernmental stage. By focusing on voluntary participation in environmental organizations, we are able to determine the level of willingness to work towards a solution for environmental problems. This allows an insight into the motivations and attitudes of individuals and nations and how these factors can affect environmental cooperation. Participation in Environmental Organizations sheds light on who is liable to participate and will help to see whose priorities and values are forwarded through voluntary activities and to what extent voluntary participation can become representative. Thus, the book provides a unique examination of citizens’ willingness to participate in environmental organizations. The book will be of interest to Economics students and researchers alike who seek a deeper understanding of the theory and practice of environmental participation.
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This paper addresses research from a three-year longitudinal study that engaged children in data modeling experiences from the beginning school year through to third year (6-8 years). A data modeling approach to statistical development differs in several ways from what is typically done in early classroom experiences with data. In particular, data modeling immerses children in problems that evolve from their own questions and reasoning, with core statistical foundations established early. These foundations include a focus on posing and refining statistical questions within and across contexts, structuring and representing data, making informal inferences, and developing conceptual, representational, and metarepresentational competence. Examples are presented of how young learners developed and sustained informal inferential reasoning and metarepresentational competence across the study to become “sophisticated statisticians”.
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Previous attempts to determine the degree to which exposure to environmental factors contribute to noncommunicable diseases (NCDs) have been very conservative and have significantly underestimated the actual contribution of the environment for at least two reasons. Firstly, most previous reports have excluded the contribution of lifestyle behavioral risk factors, but these usually involve significant exposure to environmental chemicals that increase risk of disease. Secondly, early life exposure to chemical contaminants is now clearly associated with an elevated risk of several diseases later in life, but these connections are often difficult to discern. This is especially true for asthma and neurodevelopmental conditions, but there is also a major contribution to the development of obesity and chronic diseases. Most cancers are caused by environmental exposures in genetically susceptible individuals. In addition, new information shows significant associations between cardiovascular diseases and diabetes and exposure to environmental chemicals present in air, food, and water. These relationships likely reflect the combination of epigenetic effects and gene induction. Environmental factors contribute significantly more to NCDs than previous reports have suggested. Prevention needs to shift focus from individual responsibility to societal responsibility and an understanding that effective prevention of NCDs ultimately relies on improved environmental management to reduce exposure to modifiable risks.
Resumo:
Although the effect of adverse environments on the well-being of children is an important global health issue, it remains underrecognized in health care and underconsidered in terms of both research and public policy. Children have developmentally distinct patterns of environmental exposure and susceptibilities that increase their risk of disease. Young children, especially those who are impoverished, have disproportionately heavier exposures to environmental threats in a given environment. They also have decreased metabolic capacity to detoxify and eliminate contaminants. Furthermore, rapid growth and development before and after birth and the continuing growth and postnatal maturation of the respiratory, immune, and neurological systems, in particular, make them increasingly vulnerable to environmental threats...