955 resultados para mental model development


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The overall goal of the MARine and Estuarine goal Setting (MARES) project for South Florida is “to reach a science-based consensus about the defining characteristics and fundamental regulating processes of a South Florida coastal marine ecosystem that is both sustainable and capable of providing the diverse ecosystem services upon which our society depends.” Through participation in a systematic process of reaching such a consensus, science can contribute more directly and effectively to the critical decisions being made by both policy makers and by natural resource and environmental management agencies. The document that follows briefly describes the MARES project and this systematic process. It then describes in considerable detail the resulting output from the first two steps in the process, the development of conceptual diagrams and an Integrated Conceptual Ecosystem Model (ICEM) for the first subregion to be addressed by MARES, the Florida Keys/Dry Tortugas (FK/DT). What follows with regard to the FK/DT is the input received from more than 60 scientists, agency resource managers, and representatives of environmental organizations beginning with a workshop held December 9-10, 2009 at Florida International University in Miami, Florida.

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The overall goal of the MARES (MARine and Estuarine goal Setting) project for South Florida is “to reach a science-based consensus about the defining characteristics and fundamental regulating processes of a South Florida coastal marine ecosystem that is both sustainable and capable of providing the diverse ecosystem services upon which our society depends.” Through participation in a systematic process of reaching such a consensus, science can contribute more directly and effectively to the critical decisions being made both by policy makers and by natural resource and environmental management agencies. The document that follows briefly describes MARES overall and this systematic process. It then describes in considerable detail the resulting output from the first step in the process, the development of an Integrated Conceptual Ecosystem Model (ICEM) for the third subregion to be addressed by MARES, the Southeast Florida Coast (SEFC). What follows with regard to the SEFC relies upon the input received from more than 60 scientists, agency resource managers, and representatives of environmental organizations during workshops held throughout 2009–2012 in South Florida.

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The overall goal of the MARine and Estuarine goal Setting (MARES) project for South Florida is “to reach a science-based consensus about the defining characteristics and fundamental regulating processes of a South Florida coastal marine ecosystem that is both sustainable and capable of providing the diverse ecosystem services upon which our society depends.” Through participation in a systematic process of reaching such a consensus, science can contribute more directly and effectively to the critical decisions being made by both policy makers and by natural resource and environmental management agencies. The document that follows briefly describes the MARES project and this systematic process. It then describes in considerable detail the resulting output from the first two steps in the process, the development of conceptual diagrams and an Integrated Conceptual Ecosystem Model (ICEM) for the second subregion to be addressed by MARES, the Southwest Florida Shelf (SWFS). What follows with regard to the SWFS is the input received from more than 60 scientists, agency resource managers, and representatives of environmental organizations beginning with a workshop held August 19-20, 2010 at Florida Gulf Coast University in Fort Myers, Florida.

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Several agencies in the United Kingdom have interest in the water quality of old navigational canals that have fallen into disuse after the decline of commercial canal transportation. The interested agencies desired a model to predict the water quantity and quality of inland navigational canals in order to evaluate management options to address the issues in the natural streams to which they discharge. Inland navigational canals have unique drivers of their hydrology and water quality compared to either natural streams, irrigation canals, or larger navigational canals connected to seas or oceans. Water in an inland canal is typically sourced from a reservoir and artificially pumped to a summit reach; its movement downhill is controlled by the activity of boats and overflow weirs. Stagnant impoundments between locks, which might normally be expected to result in a decrease in the concentration of sediment-associated pollutants, actually have surprisingly high levels of sediment due to boat traffic. Algal growth in the stagnant reach can be high. This paper describes a canal model developed to simulate hydrology and water quality in inland navigational canals. This model was successfully applied to the Kennet and Avon Canal to predict hydrology, sediment generation and transport, and algal growth and transport. The model is responsive to external influences such as sunlight, temperature, nutrient concentrations, boat traffic, and runoff from the contributing catchment area.

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The movement of chemicals through soil to groundwater is a major cause of degradation of water resources. In many cases, serious human and stock health implications are associated with this form of pollution. The study of the effects of different factors involved in transport phenomena can provide valuable information to find the best remediation approaches. Numerical models are increasingly being used for predicting or analyzing solute transport processes in soils and groundwater. This article presents the development of a stochastic finite element model for the simulation of contaminant transport through soils with the main focus being on the incorporation of the effects of soil heterogeneity in the model. The governing equations of contaminant transport are presented. The mathematical framework and the numerical implementation of the model are described. The comparison of the results obtained from the developed stochastic model with those obtained from a deterministic method and some experimental results shows that the stochastic model is capable of predicting the transport of solutes in unsaturated soil with higher accuracy than deterministic one. The importance of the consideration of the effects of soil heterogeneity on contaminant fate is highlighted through a sensitivity analysis regarding the variance of saturated hydraulic conductivity as an index of soil heterogeneity. © 2011 John Wiley & Sons, Ltd.

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This paper presents a comparison between theoretical predictions and experimental results from a pin-on-disc test rig exploring friction-induced vibration. The model is based on a linear stability analysis of two systems coupled by sliding contact at a single point. Predictions are compared with a large volume of measured squeal initiations that have been post-processed to extract growth rates and frequencies at the onset of squeal. Initial tests reveal the importance of including both finite contact stiffness and a velocity-dependent dynamic model for friction, giving predictions that accounted for nearly all major clusters of squeal initiations from 0 to 5 kHz. However, a large number of initiations occurred at disc mode frequencies that were not predicted with the same parameters. These frequencies proved remarkably difficult to destabilise, requiring an implausibly high coefficient of friction. An attempt has been made to estimate the dynamic friction behaviour directly from the squeal initiation data, revealing complex-valued frequency-dependent parameters for a new model of linearised dynamic friction. These new parameters readily destabilised the disc modes and provided a consistent model that could account for virtually all initiations from 0 to 15 kHz. The results suggest that instability thresholds for a wide range of squeal-type behaviour can be predicted, but they highlight the central importance of a correct understanding and accurate description of dynamic friction at the sliding interface. © 2013 Elsevier Ltd. All rights reserved.

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This paper presents ongoing work on data collection and collation from a large number of laboratory cement-stabilization projects worldwide. The aim is to employ Artificial Neural Networks (ANN) to establish relationships between variables, which define the properties of cement-stabilized soils, and the two parameters determined by the Unconfined Compression Test, the Unconfined Compressive Strength (UCS), and stiffness, using E50 calculated from UCS results. Bayesian predictive neural network models are developed to predict the UCS values of cement-stabilized inorganic clays/silts, as well as sands as a function of selected soil mix variables, such as grain size distribution, water content, cement content and curing time. A model which can predict the stiffness values of cement-stabilized clays/silts is also developed and compared to the UCS model. The UCS model results emulate known trends better and provide more accurate estimates than the results from the E50 stiffness model. © 2013 American Society of Civil Engineers.

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Lovastatin biosynthesis depends on the relative concentrations of dissolved oxygen and the carbon and nitrogen resources. An elucidation of the underlying relationship would facilitate the derivation of a controller for the improvement of lovastatin yield in bioprocesses. To achieve this goal, batch submerged cultivation experiments of lovastatin production by Aspergillus flavipus BICC 5174, using both lactose and glucose as carbon sources, were performed in a 7 liter bioreactor and the data used to determine how the relative concentrations of lactose, glucose, glutamine and oxygen affected lovastatin yield. A model was developed based on these results and its prediction was validated using an independent set of batch data obtained from a 15-liter bioreactor using five statistical measures, including the Willmott index of agreement. A nonlinear controller was designed considering that dissolved oxygen and lactose concentrations could be measured online, and using the lactose feed rate and airflow rate as process inputs. Simulation experiments were performed to demonstrate that a practical implementation of the nonlinear controller would result in satisfactory outcomes. This is the first model that correlates lovastatin biosynthesis to carbon-nitrogen proportion and possesses a structure suitable for implementing a strategy for controlling lovastatin production.

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Research on business model development has focused on the relationships between elements of value conceptualization and organization having a linear sequence in which business models are first designed and then implemented. Another stream of research points to business model development with these elements interacting in a cyclical manner. There is a need to improve our understanding of the connective mechanisms and dynamics involved in business model development, particularly from the challenging perspective of commercializing innovations. The aim of this paper was to explore business model development during the commercialization of innovations through a case-based qualitative study. This study found from four case studies that specific elements of business model development, representative of the conceptualization of value and organizing for value creation, integrate in a dynamic and cyclical process in the commercialization of technology innovations. The study provides empirical evidence that adds new insights to literature on sequential and more interactive processes of business model development. It also contributes to literature on business model development and particularly how it relates to the commercialization of innovations.