The role of conceptual models in formal software training

Author(s):  
Conrad Shayo ◽  
Lorne Olfman
2021 ◽  
Author(s):  
Hamish Johnson ◽  
Jean-Christophe Comte ◽  
Ulrich Ofterdinger ◽  
Rachel Cassidy ◽  
Mads Troldborg

<p>The environmental fate and transport of nitrogen and phosphorus nutrient species leached from agroecosystems are largely influenced by the hydrogeological setting, which dictates the distribution of groundwater flow pathways, residence times, and physio-chemical properties of the subsurface. Traditional conceptual models tend to oversimplify these relationships, and their application towards river catchment nutrient management promotes insufficient characterisation of hydrogeological heterogeneity, which is subsequently not accounted for. Until recently, very little hydrogeological information and conceptual understanding existed for groundwater systems within the postglacial basement terranes of Scotland and Northern Ireland, due to an abundance of surface water resources and prevalence of poorly productive bedrock aquifers. Recent research has demonstrated the role of geological heterogeneity in determining the contaminant transport behaviour of these hard-rock aquifers, where the presence of weathering and fracturing can potentially result in the rapid delivery of nutrients to rural water supplies and groundwater-dependent ecosystems.</p><p>We aim to further elucidate the role of hydrogeological setting in river catchment nutrient dynamics to improve agricultural sustainability in geologically heterogeneous agricultural regions. This will be achieved by developing conceptual models of nutrient fate and transport for two contrasting agricultural river catchments. Here, we present preliminary conceptual models based on a literature review of groundwater systems within the same geological terranes, analysis of hydrochemical monitoring data, and accounting for catchment-specific features through desk studies of geological and airborne geophysical surveys.</p><p>The River Ythan is a groundwater-dominated lowland catchment within Scotland’s arable belt, designated a Nitrate Vulnerable Zone due to the eutrophication of its estuary. This catchment is geologically complex, with a variably metamorphosed and sheared Precambrian basement with igneous intrusions ranging from ultrabasic rocks to granite. This complexity is enhanced by the significant preservation of Tertiary weathering profiles and an extensive but discontinuous cover of glacial deposits derived from the saprolites. The superficial deposits create a shallow aquifer system characterized by oxic, well-mixed groundwaters with high nitrate concentrations. The bedrock groundwater bodies feature lower nitrate concentrations with variable denitrification rates, resulting from the relationships between lithology, tectonics, and weathering.</p><p>Two upland headwater sub-catchments of the Upper Bann River (Co. Down, Northern Ireland) drain either side of the contact between a granodiorite laccolith and Lower Palaeozoic metasedimentary rocks within an elevated drumlinoid landscape. Here, diffuse phosphorus exports to surface waters have not experienced the same extent of decline observed in storm runoff phosphorus following the implementation of nutrient management policies. Anoxic groundwaters favourable for denitrification may result in the release of previously adsorbed (legacy) phosphorus following the reductive dissolution of Fe (hydr)oxides. These conditions are generated by (a) confinement by thick, drumlinised clayey tills; and (b) bedrock structures promoting deep groundwater flow.</p><p>The site-specific conceptual models will be further developed through multi-scale geophysical characterisation of hydrogeological heterogeneity and constrained by the catchment-scale distribution of residence times derived from stable (<sup>2</sup>H, <sup>18</sup>O) and radioactive (<sup>3</sup>H) isotope compositions of groundwaters. These refined conceptual models can guide the development of numerical groundwater models and spatially targeted nutrient management.</p>


2017 ◽  
Vol 9 (1) ◽  
pp. 1 ◽  
Author(s):  
Nawras M. Nusairat ◽  
Abdel Hakim O. Akhorshaideh ◽  
Tahir Rashid ◽  
Sunil Sahadev ◽  
Grazyna Rembielak

This paper investigates the effect of social cues in a mall’s shopping environment on customer behavior. Two competing mediation scenarios are assessed: emotion-cognition and cognition-emotion in a stimulus-organism-response (SOR)-based framework. Although the role of social cues in driving customer behavior in shopping contexts is largely addressed in the extant literature, the mechanism of the effect is still under-researched area and this study is an attempt to fill this gap.The conceptual model is validated through a questionnaire survey of 1028 shopping mall customers from three cities in Jordan. Two different conceptual models are tested. The analysis reveals that the cognition-emotion mediated model is more robust in predicting the effect of social cues than emotion-cognition mediated model. The findings indicate that a) social cues have a significant positive effect on customers’ emotion of pleasure; cognition; and behavioral response; and b) only pleasure and cognition mediate the effect of social cues on customers’ behavioral response.Theoretically, this study provides a comprehensive understanding of the mechanism by which customers’ emotions and cognition mediate the effect of social cues on customer behavior; and practically, it asserts the significance of social cues as a marketing tool. 


2020 ◽  
Vol 77 (11) ◽  
pp. 3661-3681 ◽  
Author(s):  
John M. Peters ◽  
Hugh Morrison ◽  
Adam C. Varble ◽  
Walter M. Hannah ◽  
Scott E. Giangrande

AbstractResearch has suggested that the structure of deep convection often consists of a series of rising thermals, or “thermal chain,” which contrasts with existing conceptual models that are used to construct cumulus parameterizations. Simplified theoretical expressions for updraft properties obtained in Part I of this study are used to develop a hypothesis explaining why this structure occurs. In this hypothesis, cumulus updraft structure is strongly influenced by organized entrainment below the updraft’s vertical velocity maximum. In a dry environment, this enhanced entrainment can locally reduce condensation rates and increase evaporation, thus eroding buoyancy. For moderate-to-large initial cloud radius R, this breaks up the updraft into a succession of discrete pulses of rising motion (i.e., a thermal chain). For small R, this leads to the structure of a single, isolated rising thermal. In contrast, moist environments are hypothesized to favor plume-like updrafts for moderate-to-large R. In a series of axisymmetric numerical cloud simulations, R and environmental relative humidity (RH) are systematically varied to test this hypothesis. Vertical profiles of fractional entrainment rate, passive tracer concentration, buoyancy, and vertical velocity from these runs agree well with vertical profiles calculated from the theoretical expressions in Part I. Analysis of the simulations supports the hypothesized dependency of updraft structure on R and RH, that is, whether it consists of an isolated thermal, a thermal chain, or a plume, and the role of organized entrainment in driving this dependency. Additional three-dimensional (3D) turbulent cloud simulations are analyzed, and the behavior of these 3D runs is qualitatively consistent with the theoretical expressions and axisymmetric simulations.


2020 ◽  
Author(s):  
András Bárdossy ◽  
Chris Kilsby ◽  
Faizan Anwar ◽  
Ning Wang

<p>Rainfall-runoff models produce outputs which differ from observations due to uncertainties in process description, process parametrization, uncertainties in observations and changing spatio-temporal variability of input and state variables. Traditionally, attention has been focused mostly on process parameters to quantify runoff uncertainty using e.g. GLUE.</p><p>Here we have focused on the role of precipitation uncertainty relating to discharge. For this purpose, we used an inverse model approach. We generated time series of daily precipitation with high spatial resolution  using a modified version of Random Mixing and the Shannon-Whittaker interpolation to improve simulated runoff using the SHETRAN (physically-based) and HBV (conceptual) models, both spatially distributed for various sub-catchments of the Neckar River in Germany.  HBV was initially calibrated using interpolated precipitation, while SHETRAN uses pre-defined parameters. The modelling goal was to find a spatio-temporal series of precipitation which improved the predicted runoff,  under the constraints that the precipitation values be the same at the measurement locations and share their spatial variability with the observations at a given step. Care was taken to select subsequent days for improvement such that the previously improved step considered the effect of the previous steps.</p><p>We asked the questions: i) does improving precipitation inputs for one sub-catchment bring runoff improvement for the others? ii) Can the improved precipitation using SHETRAN be used for HBV and still get runoff improvements as compared to the interpolated precipitation and vice versa?</p><p>Results showed that overall runoff errors were reduced by 40 to 50% for all sub-catchments. For the peaks, a reduction of 70 to 90% was observed. As compared with the interpolated fields, new fields showed similar overall distribution but different details at finer spatial scales. Swapping improved precipitations between SHETRAN and HBV showed improvement as compared with the discharge from interpolated precipitation.</p>


1993 ◽  
Vol 26 (4) ◽  
pp. 105-108
Author(s):  
Ewart R Carson

Computational modelling is becoming of increasing importance in assisting with, and enhancing, the processes of decision-making in clinical medicine and in health care delivery, processes which depend upon the effective interpretation of data yielded by measurement practice. Using conceptual models of health care delivery, a framework can be established within which the role of specific computational modelling paradigms can be clearly identified. Some of the methodological issues which underpin computer modelling are considered across the range of realizations (mathematical, logical, statistical and graphical) that find application in the clinical and health care domains. Examples are given of both quantitative modelling and qualitative model-based reasoning as important adjuncts to measurement practice.


2002 ◽  
Vol 55 (10) ◽  
pp. 1227-1250 ◽  
Author(s):  
Nicolay Am Worren ◽  
Karl Moore ◽  
Richard Elliott

In this article we discuss the characteristics of knowledge that lead to practical utility. We first review previous efforts at identifying the characteristics of useful knowledge. These contributions are grouped into three perspectives according to which representational mode they imply: propositional, narrative, or visual. We develop a framework for pragmatic validity that encompasses knowledge represented in all three modes. However, we also note an over-reliance on the propositional mode in academia, which contrasts with a preference for narrative and visual knowledge among practitioners. Explicit and propositional knowledge are key criteria for achieving scientific validity, but more ambiguous knowledge serves important functions in organizational life and may thus possess pragmatic validity. We highlight the role of conceptual models expressed in a visual format, a representational mode that has received little attention in the literature. We end with suggestions for further research that may extend the notion of pragmatic validity and lead to a more refined framework for the development of useful knowledge.


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