858 resultados para Hydrologic Modeling Processes and River Flows
Resumo:
Creative processes, for instance, the development of visual effects or computer games, increasingly become part of the agenda of information systems researchers and practitioners. Such processes get their managerial challenges from the fact that they comprise both well-structured, transactional parts and creative parts. The latter can often not be precisely specified in terms of control flow, required resources, and outcome. The processes’ high uncertainty sets boundaries for the application of traditional business process management concepts, such as process automation, process modeling, process performance measurement, and risk management. Organizations must thus exercise caution when it comes to managing creative processes and supporting these with information technology. This, in turn, requires a profound understanding of the concept of creativity in business processes. In response to this, the present paper introduces a framework for conceptualizing creativity within business processes. The conceptual framework describes three types of uncertainty and constraints as well as the interrelationships among these. The study is grounded in the findings from three case studies that were conducted in the film and visual effects industry. Moreover, we provide initial evidence for the framework’s validity beyond this narrow focus. The framework is intended to serve as a sensitizing device that can guide further information systems research on creativity-related phenomena.
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On the microscale, migration, proliferation and death are crucial in the development, homeostasis and repair of an organism; on the macroscale, such effects are important in the sustainability of a population in its environment. Dependent on the relative rates of migration, proliferation and death, spatial heterogeneity may arise within an initially uniform field; this leads to the formation of spatial correlations and can have a negative impact upon population growth. Usually, such effects are neglected in modeling studies and simple phenomenological descriptions, such as the logistic model, are used to model population growth. In this work we outline some methods for analyzing exclusion processes which include agent proliferation, death and motility in two and three spatial dimensions with spatially homogeneous initial conditions. The mean-field description for these types of processes is of logistic form; we show that, under certain parameter conditions, such systems may display large deviations from the mean field, and suggest computationally tractable methods to correct the logistic-type description.
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With the advent of live cell imaging microscopy, new types of mathematical analyses and measurements are possible. Many of the real-time movies of cellular processes are visually very compelling, but elementary analysis of changes over time of quantities such as surface area and volume often show that there is more to the data than meets the eye. This unit outlines a geometric modeling methodology and applies it to tubulation of vesicles during endocytosis. Using these principles, it has been possible to build better qualitative and quantitative understandings of the systems observed, as well as to make predictions about quantities such as ligand or solute concentration, vesicle pH, and membrane trafficked. The purpose is to outline a methodology for analyzing real-time movies that has led to a greater appreciation of the changes that are occurring during the time frame of the real-time video microscopy and how additional quantitative measurements allow for further hypotheses to be generated and tested.
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In this reflection on research processes a humanities researcher begins to ask questions about the cultural materialist dimensions of research activities. At the center of this exploration are questions relating to the ways in which personal histories and experiences inform particular research processes and the ways in which a researcher's habits of collecting and working with data are regulated by cultural and social practice. The reflection on personal research processes is located in terms of the ethics work of Michel Foucault that provides reminders about the role of modern bureaucracy in governing what appear to be personal processes.
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Business process modeling as a practice and research field has received great attention in recent years. However, while related artifacts such as models, tools or grammars have substantially matured, comparatively little is known about the activities that are conducted as part of the actual act of process modeling. Especially the key role of the modeling facilitator has not been researched to date. In this paper, we propose a new theory-grounded, conceptual framework describing four facets (the driving engineer, the driving artist, the catalyzing engineer, and the catalyzing artist) that can be used by a facilitator. These facets with behavioral styles have been empirically explored via in-depth interviews and additional questionnaires with experienced process analysts. We develop a proposal for an emerging theory for describing, investigating, and explaining different behaviors associated with Business Process Modeling Facilitation. This theory is an important sensitizing vehicle for examining processes and outcomes from process modeling endeavors.
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Ocean processes are complex and have high variability in both time and space. Thus, ocean scientists must collect data over long time periods to obtain a synoptic view of ocean processes and resolve their spatiotemporal variability. One way to perform these persistent observations is to utilise an autonomous vehicle that can remain on deployment for long time periods. However, such vehicles are generally underactuated and slow moving. A challenge for persistent monitoring with these vehicles is dealing with currents while executing a prescribed path or mission. Here we present a path planning method for persistent monitoring that exploits ocean currents to increase navigational accuracy and reduce energy consumption.
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Nha Trang Bay (NTB) is located on the Central Vietnam coast, western South China Sea. Recent coastal development of Nha Trang City has raised public concern over an increasing level of pollution within the bay and degradation of nearby coral reefs. In this study, multiple proxies (e.g., trace metals, rare earth elements (REEs), and Y/Ho) recorded in a massive Porites lutea coral colony were used to reconstruct changes in seawater conditions in the NTB from 1995 to 2009. A 14-year record of REEs and other trace metals revealed that the concentrations of terrestrial trace metals have increased dramatically in response to an increase in coastal development projects such as road, port, and resort constructions, port and river dredging, and dumping activities since 2000. The effects of such developmental processes are also evident in changes in REE patterns and Y/Ho ratios through time, suggesting that both parameters are critical proxies for marine pollution.
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Sugarcane bagasse is an abundant and sustainable resource, generated as a by-product of sugarcane milling. The cellulosic material within bagasse can be broken down into glucose molecules and fermented to produce ethanol, making it a promising feedstock for biofuel production. Mild acid pretreatment hydrolyses the hemicellulosic component of biomass, thus allowing enzymes greater access to the cellulosic substrate during saccharification. A particle-scale mathematical model describing the mild acid pretreatment of sugarcane bagasse has been developed, using a volume averaged framework. Discrete population-balance equations are used to characterise the polymer degradation kinetics, and diffusive effects account for mass transport within the cell wall of the bagasse. As the fibrous material hydrolyses over time, variations in the porosity of the cell wall and the downstream effects on the reaction kinetics are accounted for using conservation of volume arguments. Non-dimensionalization of the model equations reduces the number of parameters in the system to a set of four dimensionless ratios that compare the timescales of different reaction and diffusion events. Theoretical yield curves are compared to macroscopic experimental observations from the literature and inferences are made as to constraints on these “unknown” parameters. These results enable connections to be made between experimental data and the underlying thermodynamics of acid pretreatment. Consequently, the results suggest that data-fitting techniques used to obtain kinetic parameters should be carefully applied, with prudent consideration given to the chemical and physiological processes being modeled.
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Osmotic treatments are often applied prior to convective drying of foods to impart sensory appeal aspects. During this process a multicomponent mass flow, composed mainly of water and osmotic agent, takes place. In this work, a heat and mass transfer model for the osmo-convective drying of yacon was developed and solved by the Finite Element Method using COMSOL Multiphysics®, considering a 2-D axisymmetric geometry and moisture dependent thermophysical properties. Yacon slices were osmotically dehydrated for 2 hours in a solution of sucralose and then dried in a tray dryer for 3 hours. The model was validated by experimental data of temperature, moisture content and sucralose uptake (R²> 0.90).
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Mosquito-borne diseases pose some of the greatest challenges in public health, especially in tropical and sub-tropical regions of theworld. Efforts to control these diseases have been underpinned by a theoretical framework developed for malaria by Ross and Macdonald, including models, metrics for measuring transmission, and theory of control that identifies key vulnerabilities in the transmission cycle. That framework, especially Macdonald’s formula for R0 and its entomological derivative, vectorial capacity, are nowused to study dynamics and design interventions for many mosquito-borne diseases. A systematic review of 388 models published between 1970 and 2010 found that the vast majority adopted the Ross–Macdonald assumption of homogeneous transmission in a well-mixed population. Studies comparing models and data question these assumptions and point to the capacity to model heterogeneous, focal transmission as the most important but relatively unexplored component in current theory. Fine-scale heterogeneity causes transmission dynamics to be nonlinear, and poses problems for modeling, epidemiology and measurement. Novel mathematical approaches show how heterogeneity arises from the biology and the landscape on which the processes of mosquito biting and pathogen transmission unfold. Emerging theory focuses attention on the ecological and social context formosquito blood feeding, themovement of both hosts and mosquitoes, and the relevant spatial scales for measuring transmission and for modeling dynamics and control.
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Multivariate predictive models are widely used tools for assessment of aquatic ecosystem health and models have been successfully developed for the prediction and assessment of aquatic macroinvertebrates, diatoms, local stream habitat features and fish. We evaluated the ability of a modelling method based on the River InVertebrate Prediction and Classification System (RIVPACS) to accurately predict freshwater fish assemblage composition and assess aquatic ecosystem health in rivers and streams of south-eastern Queensland, Australia. The predictive model was developed, validated and tested in a region of comparatively high environmental variability due to the unpredictable nature of rainfall and river discharge. The model was concluded to provide sufficiently accurate and precise predictions of species composition and was sensitive enough to distinguish test sites impacted by several common types of human disturbance (particularly impacts associated with catchment land use and associated local riparian, in-stream habitat and water quality degradation). The total number of fish species available for prediction was low in comparison to similar applications of multivariate predictive models based on other indicator groups, yet the accuracy and precision of our model was comparable to outcomes from such studies. In addition, our model developed for sites sampled on one occasion and in one season only (winter), was able to accurately predict fish assemblage composition at sites sampled during other seasons and years, provided that they were not subject to unusually extreme environmental conditions (e.g. extended periods of low flow that restricted fish movement or resulted in habitat desiccation and local fish extinctions).
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Plasma sheath, nanostructure growth, and thermal models are used to describe carbon nanofiber (CNF) growth and heating in a low-temperature plasma. It is found that when the H2 partial pressure is increased, H atom recombination and H ion neutralization are the main mechanisms responsible for energy release on the catalyst surface. Numerical results also show that process parameters such as the substrate potential, electron temperature and number density mainly affect the CNF growth rate and plasma heating at low catalyst temperatures. In contrast, gas pressure, ion temperature, and the C2H2:H2 supply ratio affect the CNF growth at all temperatures. It is shown that plasma-related processes substantially increase the catalyst particle temperature, in comparison to the substrate and the substrate-holding platform temperatures.
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In this paper, a novel data-driven approach to monitoring of systems operating under variable operating conditions is described. The method is based on characterizing the degradation process via a set of operation-specific hidden Markov models (HMMs), whose hidden states represent the unobservable degradation states of the monitored system while its observable symbols represent the sensor readings. Using the HMM framework, modeling, identification and monitoring methods are detailed that allow one to identify a HMM of degradation for each operation from mixed-operation data and perform operation-specific monitoring of the system. Using a large data set provided by a major manufacturer, the new methods are applied to a semiconductor manufacturing process running multiple operations in a production environment.
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The effects of a range of different sublethal salinities were assessed on physiological processes and growth performance in the freshwater ‘tra’ catfish (Pangasianodon hypophthalmus) juveniles over an 8-week experiment. Fish were distributed randomly among 6 salinity treatments [2, 6, 10, 14 and 18 g/L of salinity and a control (0 g/L)] with a subsequent 13-day period of acclimation. Low salinity conditions from 2 to 10 g/L provided optimal conditions with high survival and good growth performance, while 0 g/L and salinities[14 g/L gave poorer survival rates (p\0.05). Salinity levels from freshwater to 10 g/L did not have any negative effects on fish weight gain, daily weight gain, or specific growth rate. Food conversion ratio, however, was lowest in the control treatment (p\0.05) and highest at the maximum salinities tested (18 g/L treatment). Cortisol levels were elevated in the 14 and 18 g/L treatments after 6 h and reached a peak after 24-h exposure, and this also led to increases in plasma glucose concentration. After 14 days, surviving fish in all treatments appeared to have acclimated to their respective conditions with cortisol levels remaining under 5 ng/ mL with glucose concentrations stable. Tra catfish do not appear to be efficient osmoregulators when salinity levels exceed 10 g/L, and at raised salinity levels, growth performance is compromised. In general, results of this study confirm that providing culture environments in the Mekong River Basin do not exceed 10 g/L salinity and that cultured tra catfish can continue to perform well.