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Modeling
Kinds of Modeling Terms modified by Modeling Selected AbstractsFROM DISCRETE-TIME MODELS TO CONTINUOUS-TIME, ASYNCHRONOUS MODELING OF FINANCIAL MARKETSCOMPUTATIONAL INTELLIGENCE, Issue 2 2007Katalin Boer Most agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modeling of financial markets. We study the behavior of a learning market maker in a market with information asymmetry, and investigate the difference caused in the market dynamics between the discrete-time simulation and continuous-time, asynchronous simulation. We show that the characteristics of the market prices are different in the two cases, and observe that additional information is being revealed in the continuous-time, asynchronous models, which can be acted upon by the agents in such models. Because most financial markets are continuous and asynchronous in nature, our results indicate that explicit consideration of this fundamental characteristic of financial markets cannot be ignored in their agent-based modeling. [source] NEURAL NETWORK MODELING OF END-OVER-END THERMAL PROCESSING OF PARTICULATES IN VISCOUS FLUIDSJOURNAL OF FOOD PROCESS ENGINEERING, Issue 2010YANG MENG ABSTRACT Modeling of the heat transfer process in thermal processing is important for the process design and control. Artificial neural networks (ANNs) have been used in recent years in heat transfer modeling as a potential alternative to conventional dimensionless correlation approach and shown to be even better performers. In this study, ANN models were developed for apparent heat transfer coefficients associated with canned particulates in high viscous Newtonian and non-Newtonian fluids during end-over-end thermal processing in a pilot-scale rotary retort. A portion of experimental data obtained for the associated heat transfer coefficients were used for training while the rest were used for testing. The principal configuration parameters were the combination of learning rules and transfer functions, number of hidden layers, number of neurons in each hidden layer and number of learning runs. For the Newtonian fluids, the optimal conditions were two hidden layers, five neurons in each hidden layer, the delta learning rule, a sine transfer function and 40,000 learning runs, while for the non-Newtonian fluids, the optimal conditions were one hidden layer, six neurons in each hidden layer, the delta learning rule, a hyperbolic tangent transfer function and 50,000 learning runs. The prediction accuracies for the ANN models were much better compared with those from the dimensionless correlations. The trained network was found to predict responses with a mean relative error of 2.9,3.9% for the Newtonian fluids and 4.7,5.9% for the non-Newtonian fluids, which were 27,62% lower than those associated with the dimensionless correlations. Algebraic solutions were included, which could be used to predict the heat transfer coefficients without requiring an ANN. PRACTICAL APPLICATIONS The artificial neural network (ANN) model is a network of computational elements that was originally developed to mimic the function of the human brain. ANN models do not require the prior knowledge of the relationship between the input and output variables because they can discover the relationship through successive training. Moreover, ANN models can predict several output variables at the same time, which is difficult in general regression methods. ANN concepts have been successfully used in food processing for prediction, quality control and pattern recognition. ANN models have been used in recent years for heat transfer modeling as a potential alternative to conventional dimensionless correlation approach and shown to be even better performers. In this study, ANN models were successfully developed for the heat transfer parameters associated with canned particulate high viscous Newtonian and non-Newtonian fluids during an end-over-end rotation thermal processing. Optimized configuration parameters were obtained by choosing appropriate combinations of learning rule, transfer function, learning runs, hidden layers and number of neurons. The trained network was found to predict parameter responses with mean relative errors considerably lower than from dimensionless correlations. [source] ANALYSIS OF VARIABLES AND MODELING OF GEVUINA AVELLANA OIL EXTRACTION WITH ETHANOL NEAR AZEOTROPE CONDITIONSJOURNAL OF FOOD PROCESS ENGINEERING, Issue 5 2009DANIEL FRANCO ABSTRACT Oil extraction from Gevuina avellana Mol. (Chilean hazelnut) with ethanol, near the conditions of its azeotrope with water, was carried out in this work. The effects of solubility, liquid-to-solid ratio and moisture content of ethanol were studied using 92% ethanol, azeotropic (96%) and absolute ethanol (99.9%) as solvents. Water content had a high effect on oil solubility, which reached 140 g/L in 99.9% ethanol, whereas it was 40 g/L with azeotropic ethanol. Oil accounted for 93% of total extractable compounds with absolute ethanol. Kinetics studies of the extraction process were performed at 50C, giving as a result apparent diffusivity values near 10,11 m2/s, being the highest values obtained for ethanol 92% (7.5,16 × 10,11). It was also found that the higher the liquid-to-solid ratio, the higher the diffusivity. Simulation of four-stage countercurrent extraction with azeotropic ethanol yielded 23.5% oil extraction, whereas simulation of four-stage cross-flow extraction yielded 40.7%. Ethanol can be an alternative to batch cold pressing or hexane solvent extraction, for G. savellana seeds or meal processing. PRACTICAL APPLICATIONS The results presented in this paper are applicable for obtaining oil from oilseeds by extraction with ethanol. It includes relevant results for the optimization of extraction conditions and particularly those regarding liquid-to-solid ratio and percentage of water. Considering the more specific focus of this research, the results are applicable to obtaining Gevuina avellana oil by using an ethanol-based process, which will allow to avoid one of the cold-pressing process drawbacks: the high oil content of the meal, which is a factor limiting its lifetime. [source] TWO-PHASE MODELING AND THE QUALITY OF SOYBEAN SEEDS DRIED IN A COUNTER-CURRENT MOVING BED DRIERJOURNAL OF FOOD PROCESS ENGINEERING, Issue 6 2004A.F. LACERDA ABSTRACT The purpose of the present work is to study the simultaneous heat and mass transfer between air and soybean seeds in a countercurrent moving bed dryer, based on the application of a two-phase model to the drying process. The numerical solution of the model is obtained by using a computational code based on backwards differential formulae. The experimental data of air humidity and temperature and of seed moisture content and temperature at the dryer outlet are compared to the simulated values, showing a good agreement. This work also analyzes the effect of the main process variables (drying air temperature, air relative humidity, air velocity and solids flow rate) on the soybean seeds quality during drying. Empirical equations fitted to the experimental data are proposed for predicting the soybean seed quality (germination, vigor and fissures) as a function of the investigated variables. [source] COMPUTATIONAL FLUID DYNAMICS MODELING OF FLUID FLOW IN HELICAL TUBESJOURNAL OF FOOD PROCESS ENGINEERING, Issue 2 2002T. KORAY PALAZOGLU ABSTRACT The effect of different processing parameters on the degree of mixing and axial and radial pressure drops, during single-phase flow in helical tubes was investigated by using CFD software. Correlations were developed to calculate axial and radial pressure drops, and also the ratio of maximum to average fluid velocities. All of these quantities were found to be dependent on curvature ratio (ratio of tube diameter to coil diameter). Flow visualization experiments were performed to assess the degree of mixing in different configurations. At identical conditions, the degree of mixing was higher in the system with the large curvature ratio, which is in agreement with the simulation results. A minimum ratio of maximum to average fluid velocities of 1.61 was achieved, representing a 20% reduction in hold tube length for Newtonian fluid in laminar flow. [source] A NEW APPROACH TO MODELING AND CONTROL OF A FOOD EXTRUSION PROCESS USING ARTIFICIAL NEURAL NETWORK AND AN EXPERT SYSTEMJOURNAL OF FOOD PROCESS ENGINEERING, Issue 1 2001OTILIA POPESCU ABSTRACT The paper presents a new approach to the modeling of the start-up part of a food extrusion process. A neural network model is proposed and its parameters are determined. Simulation results with real data are also presented. The inputs and outputs of the model are among those used by the human operator during the start-up process for control. An intelligent controller structure that uses an expert system and "delta-variations" to modify inputs is also proposed. [source] WATER DIFFUSION COEFFICIENT AND MODELING OF WATER UPTAKE IN PACKAGED YERBA MATEJOURNAL OF FOOD PROCESSING AND PRESERVATION, Issue 4 2007LAURA A. RAMALLO ABSTRACT Effective water diffusion coefficient (Deff) was determined from the kinetics of moisture gain in a yerba mate bed. A value of 1.5 × 10,9 ± 0.4 × 10,9 m2/s was obtained at 40C and 90% relative humidity, by fitting experimental data to the series solution of Fick's second law. A model was developed to predict moisture profile and water uptake in packaged yerba mate. In order to simulate moisture gain in the packaged food, the model considers that the global process of humidity gain is controlled by combined mechanisms of package permeability, product sorption balances and water diffusion within the food bed. The explicit finite difference method was used to numerically solve the resulting equations. The validity of the model was tested by comparing predicted and experimental moisture profiles for high (WVTR , 20 g/m2/day) and low (WVTR , 400 g/m2/day) barrier packages. The model was found to adequately predict the profile of moisture content. [source] MODELING OF HEAT AND MASS TRANSFER DURING BAKING OF BISCUITSJOURNAL OF FOOD PROCESSING AND PRESERVATION, Issue 6 2004MARIA ELENA SOSA-MORALES ABSTRACT Precooked biscuits (7 cm diameter × 2 cm thickness), preserved by freezing, were evaluated in a regional bakery. Heat and mass transfer during these processes and through the final baking were studied. Precooking was conducted at 180C for 18 min; convection and conduction were the predominant phenomena for heat transfer, with an ,, = 1.71 × 10,7 m2/s. Diffusion mechanism adequately modeled (r2 = 0.94, PEM < 2.5%) the moisture loss during cooking stage, with a D = 1.04 × 10,6 m2/s. The freezing point obtained inside a tunnel freezer (forced air at ,,40C), was , 6.73C, consistent with the predicted value. Volume changes were minimal during frozen storage because of high fat content and few variations in the freezer temperature. Final baking in conventional gas and microwave ovens were compared. Higher moisture loss and minimal color change occurred in the microwave baking. Instrumental texture of both final treatments were significantly different, in contrary to sensory evaluation (, = 0.05). The methods produced a good choice for product commercialization after baking. [source] DYNAMIC MODELING OF RETORT PROCESSING USING NEURAL NETWORKSJOURNAL OF FOOD PROCESSING AND PRESERVATION, Issue 2 2002C. R. CHEN ABSTRACT Two neural network approaches , a moving-window and hybrid neural network , which combine neural network with polynomial regression models, were used for modeling F(t) and Qv(t) dynamic functions under constant retort temperature processing. The dynamic functions involved six variables: retort temperature (116,132C), thermal diffusivity (1.5,2.3 × 10,7m2/s), can radius (40,61 mm), can height (40,61 mm), and quality kinetic parameters z (15,39C) and D (150,250 min). A computer simulation designed for process calculations of food thermal processing systems was used to provide the fundamental data for training and generalization of ANN models. Training data and testing data were constructed by both second order central composite design and orthogonal array, respectively. The optimal configurations of ANN models were obtained by varying the number of hidden layers, number of neurons in hidden layer and learning runs, and a combination of learning rules and transfer function. Results demonstrated that both neural network models well described the F(t) and Qv(t) dynamic functions, but moving-window network had better modeling performance than the hybrid ANN models. By comparison of the configuration parameters, moving-window ANN models required more neurons in the hidden layer and more learning runs for training than the hybrid ANN models. [source] ECOSYSTEM MODELING: A TOOL TO UNDERSTAND THE INTERACTIONS BETWEEN EXTRACTIVE AND FED AQUACULTUREJOURNAL OF PHYCOLOGY, Issue 2001Article first published online: 24 SEP 200 Yarish, C. 1, Rawson, Jr. M. V.2, Chopin, T.3, Wang, D. R.4, Chen, C.4, Carmona, R.1, Chen, C.5 , Wang, L.4, Ji , R.5 and Sullivan, J.5 1University of Connecticut, Stamford, Connecticut 06901-2315, USA; 2Georgia Sea Grant College Program, Athens, GA 30602-3636, USA; 3University of New Brunswick, Saint John, NB, E2L 4L5, Canada; 4Marine and Fishery Dept. of Hainan Province, Haikou, Hainan, P. R. China; 5The University of Georgia, Athens, GA 30602-3636, USA One of the most difficult tasks resource managers face is understanding the carrying capacity of coastal waters for aquaculture. Aquaculture, like many other human activities, can threaten coastal waters. Aquaculture producing shrimp and finfish depends on supplemental feeding and can contribute to eutrophication. A second type, involving shellfish and macroalgae, extracts plankton and nutrients from surrounding waters, and can have a significant positive impact on moderately eutrophic waters. Ecosystem modeling offers a 3-dimensional physical, chemical and biological simulation that can help understand and predict the impacts of aquaculture on coastal embayments. Such a model is being explored for Xincun Bay (22 km2), which is located in southeastern Hainan Province, China. Aquaculture in Xincun Bay includes 6500 fish pens, 100 ha of shrimp ponds, pearl oyster culture rafts and Kappaphycus alvarezii culture that produces 2,000 mt (Oct.-May). The surrounding area has ~ 15,000 people and Xincun City is a major offshore fishing and tourist center. The annual nitrogen and phosphorus removal capacity of Kappaphycus in Xincun Bay may have been in the order of 53.8 and 3.7 mt, respectively, during the 1999-2000 growing season. Lian Bay (~ 15 km2), a nearby bay with only Kappaphycus and pearl oyster culture (and little anthropogenic input), has a macroalgal production of 1,500 mt annually. The annual nitrogen and phosphorus removal capacity of Kappaphycus here may have been in the order of 25 and 0.33 mt, respectively. Our prototype model may hold the promise for showing the importance of integrating seaweed culture activities in the maintenance and health of coastal embayments. [source] A STRUCTURAL EQUATION MODELING OF ALCOHOL USE AMONG YOUNG ADULTS IN THE U.S. MILITARY: COMPLEXITIES AMONG STRESS, DRINKING MOTIVES, IMPULSIVITIY, ALCOHOL USE AND JOB PERFORMANCEALCOHOLISM, Issue 2008Sunju Sohn Aims:, Young male adults in the U. S. military drink at much higher rates than civilians and females of the same age. Drinking has been shown to be associated with stress and individuals' ability to effectively cope with stressors. Despite numerous studies conducted on young adults' drinking behaviors such as college drinking, current literature is limited in fully understanding alcohol use patterns of the young military population. The aim of the present study was to develop and test the hypothesized Structural Equation Model (SEM) of alcohol use to determine if stress coping styles moderate the relationship between stress, drinking motives, impulsivity, alcohol consumption and job performance. Methods:, Structural equation models for multiple group comparisons were estimated based on a sample of 1,715 young (aged 18 to 25) male military personnel using the 2005 Department of Defense Survey of Health Related Behaviors among Military Personnel. Coping style was used as the grouping factor in the multi-group analysis and this variable was developed through numerous steps to reflect positive and negative behaviors of coping. The equivalences of the structural relations between the study variables were then compared across two groups at a time, controlling for installation region, race/ethnicity, marital status, education, and pay grade, resulting in two model comparisons with four coping groups. If the structural weight showed differences across groups, each parameter was constrained and tested one at a time to see where the models are different. Results:, The results showed that the hypothesized model applies across all groups. The structural weights revealed that a moderation effect exists between a group whose tendency is to mostly use positive coping strategies and a group whose tendency is to mostly use negative coping strategies (,,2(39)= 65.116, p<.05). More specifically, the models were different (with and without Bonferroni Type I error correction) in the paths between "motive and alcohol use" and "alcohol use and alcohol-related consequences (job performance)." Conclusions:, It seems plausible that coping style significantly factors into moderating alcohol use among young male military personnel who reportedly drink more excessively than civilians of the same age. The results indicate that it may be particularly important for the military to assess different stress coping styles ofyoung male military personnel so as to limit excessive drinking as well as to promote individual wellness and improve job performance. [source] MODELING OF SWEET, BITTER AND IRRITANT SENSATIONS AND THEIR INTERACTIONS ELICITED BY MODEL ICE WINESJOURNAL OF SENSORY STUDIES, Issue 5 2006CANAN NURGEL ABSTRACT Interactions between taste and irritant sensations elicited by model ice wine solutions were investigated, including the use of U and ,, models for predicting the perceived intensity of these sensory interactions. Fifteen solutions of varying ethanol and sugar concentrations representative of commercial ice wine values were evaluated in two trials by a trained sensory panel (n = 12) for perceived sweetness, bitterness and heat intensities. Sweetness perception of lower sugar-concentration level in ice wine model solution was affected by ethanol concentration. The sweetness intensities of the sugar and ethanol mixtures are higher than the sweetness intensities of sugar solutions. The ,, index indicates a slight synergy between ethanol and sugar on sweetness perception. The bitterness intensities elicited by ethanol,sugar mixtures are lower than those elicited by unmixed ethanol solutions. The ,, index indicates inhibition of ethanol and sugar perception on bitterness perception. Suppression of heat sensation was found in model base wine solutions across sugar and ethanol concentrations. [source] MODELING OF TEXTURE EVOLUTION OF CAKES DURING STORAGEJOURNAL OF TEXTURE STUDIES, Issue 1 2010MANUEL GÓMEZ ABSTRACT The aim of this work is to model the variation of texture parameters in cakes during staling. The evolution was studied in layer cakes (cake A) and sponge cakes (cake B). The effect of storage temperature and the addition of fiber, xanthan gum (cake A) and emulsifier (cake B) were also studied. The best model to adjust the texture parameters variation during storage in both kinds of cakes was square root x (y = a + b * x1/2), except for firmness and springiness in cakes B. Firmness and springiness were adjusted the best to the linear model. In the model, y stood for the textural parameters and x for the time. a and b were related to the initial value of the studied parameter and with its change over time respectively. In both kinds of cakes, A and B, the firmness and gumminess increased, and the cohesiveness, springiness and resilience decreased, as the storage time increased. The increase in the storage temperature and the addition of fiber minimized the firmness changes in both kinds of cakes. PRACTICAL APPLICATIONS This methodology simplifies the study of cake textural parameters during storage and the result interpretation. Moreover, the correlation analysis has demonstrated that the number of textural parameters of cakes to study can be reduced. [source] NUMERICAL MODELING AND SIMULATION ON THE SWALLOWING OF JELLYJOURNAL OF TEXTURE STUDIES, Issue 4 2009H. MIZUNUMA ABSTRACT Studies of the swallowing process are especially important for the development of care foods for dysphagia. However, the effectiveness of experiments on human subjects is somewhat limited due to instrument resolution, stress to the subjects and the risk of aspiration. These problems may be resolved if numerical simulation of swallowing can be used as an alternative investigative tool. On this basis, a numerical model is proposed to simulate the swallowing of a simple jelly bolus. The structure of the pharynx was modeled using a finite element method, and the swallowing movements were defined by pharynx posterior wall shift, laryngeal elevation and epiglottis retroflexion. The rheological characteristics of the jelly were investigated using an oscillatory rheometer and a compression test. A Maxwell three-element model was applied to the rheological model of the jelly. The model constants were obtained from compression tests because the mode of deformation and the stress level of the compression tests were similar to those of the swallowed jelly. The frictional relationship between the organs and the jelly was estimated experimentally from some frictional measurements between the jelly and a wet sloping surface. The results of the simulations for the soft and hard jellies showed different patterns of swallowing that depended on their hardness, and the soft jelly produced faster swallowing because of its flexibility. PRACTICAL APPLICATIONS The object of this study is to develop a numerical simulation model of swallowing. Numerical modeling is suitable for the quantitative analysis of the swallowing process and may also be expected to enable a systematic study of care foods that are safe and offer some degree of comfort to patients suffering from swallowing disorders. The computer simulation can be used for evaluation without dangerous risks to the patient. [source] HYDROLOGIC MODELING OF A BIOINFILTRATION BEST MANAGEMENT PRACTICE,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 5 2006William Heasom ABSTRACT: The goal of this research was to develop a methodology for modeling a bioinfiltration best management practice (BMP) built in a dormitory area on the campus of Villanova University in Pennsylvania. The objectives were to quantify the behavior of the BMP through the different seasons and rainfall events; better understand the physical processes governing the system's behavior; and develop design criteria. The BMP was constructed in 2001 by excavating within an existing traffic island, backfilling with a sand/soil mixture, and planting with salt tolerant grasses and shrubs native to the Atlantic shore. It receives runoff from the asphalt (0.26 hectare) and turf (0.27 hectare) surfaces of the watershed. Monitoring supported by the hydrologic model shows that the facility infiltrates a significant fraction of the annual precipitation, substantially reducing the delivery of nonpoint source pollution and erosive surges downstream. A hydrologic model was developed using HEC-HMS to represent the site and the BMP using Green-Ampt and kinematic wave methods. Instruments allow comparison of the modeled and measured water budget parameters. The model, incorporating seasonally variable parameters, predicts the volumes infiltrated and bypassed by the BMP, confirming the applicability of the selected methods for the analysis of bioinfiltration BMPs. [source] COMPARISON OF PROCESS-BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 3 2006Puneet Srivastava ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash-Sutcliffe coefficient of efficiency (E) and coefficient of determination (R2) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R2 were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ,0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds. [source] STATEWIDE EMPIRICAL MODELING OF BACTERIAL CONTAMINATION OF SURFACE WATERS,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 3 2006James D. Wickham ABSTRACT: Bacterial contamination of surface waters is attributed to both urban and agricultural land use practices and is one of the most frequently cited reasons for failure to meet standards established under the Clean Water Act (CWA) (P.L. 92,500). Statewide modeling can be used to determine if bacterial contamination occurs predominantly in urban or agricultural settings. Such information is useful for directing future monitoring and allocating resources for protection and restoration activities. Logistic regression was used to model the likelihood of bacterial contamination using watershed factors for the state of Maryland. Watershed factors included land cover, soils, topography, hydrography, locations of septic systems, and animal feeding operations. Results indicated that bacterial contamination occurred predominantly in urban settings. Likelihood of bacterial contamination was highest for small watersheds with well drained and erodible soils and a high proportion of urban land adjacent to streams. The number of septic systems and animal feeding operations and the amount of agricultural land were not significant explanatory factors. The urban infrastructure tends to "connect" more of the watershed to the stream network through the creation of roads, storm sewers, and wastewater treatment plants. This may partly explain the relationship between urbanization and bacterial contamination found in this study. [source] POST-HARVEST RIPARIAN BUFFER RESPONSE: IMPLICATIONS FOR WOOD RECRUITMENT MODELING AND BUFFER DESIGN,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 1 2006Michael K. Liquori ABSTRACT: Despite the importance of riparian buffers in providing aquatic functions to forested streams, few studies have sought to capture key differences in ecological and geomorphic processes between buffered sites and forested conditions. This study examines post-harvest buffer conditions from 20 randomly selected harvest sites within a managed tree farm in the Cascade Mountains of western Washington. Post-harvest wind derived treefall rates in buffers up to three years post-harvest averaged 268 trees/km/year, 26 times greater than competition-induced mortality rate estimates. Treefall rates and stem breakage were strongly tied to tree species and relatively unaffected by stream direction. Observed treefall direction is strongly biased toward the channel, irrespective of channel or buffer orientation. Fall direction bias can deliver significantly more wood recruitment relative to randomly directed treefall, suggesting that models that utilize the random fall assumption will significantly underpredict recruitment. A simple estimate of post-harvest wood recruitment from buffers can be obtained from species specific treefall and breakage rates, combined with bias corrected recruitment probability as a function of source distance from the channel. Post-harvest wind effects may reduce the standing density of trees enough to significantly reduce or eliminate competition mortality and thus indirectly alter bank erosion rates, resulting in substantially different wood recruitment dynamics from buffers as compared to unmanaged forests. [source] INTEGRATING LANDSCAPE ASSESSMENT AND HYDROLOGIC MODELING FOR LAND COVER CHANGE ANALYSIS,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 4 2002Scott N. Miller ABSTRACT: Significant land cover changes have occurred in the watersheds that contribute runoff to the upper San Pedro River in Sonora, Mexico, and southeast Arizona. These changes, observed using a series of remotely sensed images taken in the 1970s, 1980s, and 1990s, have been implicated in the alteration of the basin hydrologic response. The Cannonsville subwatershed, located in the Catskill/Delaware watershed complex that delivers water to New York City, provides a contrast in land cover change. In this region, the Cannonsville watershed condition has improved over a comparable time period. A landscape assessment tool using a geographic information system (GIS) has been developed that automates the parameterization of the Soil and Water Assessment Tool (SWAT) and KINEmatic Runoff and EROSion (KINEROS) hydrologic models. The Automated Geospatial Watershed Assessment (AGWA) tool was used to prepare parameter input files for the Upper San Pedro Basin, a subwatershed within the San Pedro undergoing significant changes, and the Cannonsville watershed using historical land cover data. Runoff and sediment yield were simulated using these models. In the Cannonsville watershed, land cover change had a beneficial impact on modeled watershed response due to the transition from agriculture to forest land cover. Simulation results for the San Pedro indicate that increasing urban and agricultural areas and the simultaneous invasion of woody plants and decline of grasslands resulted in increased annual and event runoff volumes, flashier flood response, and decreased water quality due to sediment loading. These results demonstrate the usefulness of integrating remote sensing and distributed hydrologic models through the use of GIS for assessing watershed condition and the relative impacts of land cover transitions on hydrologic response. [source] WATER QUALITY MODELING OF ALTERNATIVE AGRICULTURAL SCENARIOS IN THE U.S. CORN BELT,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 3 2002Kellie B. Vaché ABSTRACT: Simulated water quality resulting from three alternative future land-use scenarios for two agricultural watersheds in central Iowa was compared to water quality under current and historic land use/land cover to explore both the potential water quality impact of perpetuating current trends and potential benefits of major changes in agricultural practices in the U.S. Corn Belt. The Soil Water Assessment Tool (SWAT) was applied to evaluate the effect of management practices on surface water discharge and annual loads of sediment and nitrate in these watersheds. The agricultural practices comprising Scenario 1, which assumes perpetuation of current trends (conversion to conservation tillage, increase in farm size and land in production, use of currently-employed Best Management Practices (BMPs)) result in simulated increased export of nitrate and decreased export of sediment relative to the present. However, simulations indicate that the substantial changes in agricultural practices envisioned in Scenarios 2 and 3 (conversion to conservation tillage, strip intercropping, rotational grazing, conservation set-asides and greatly extended use of best management practices (BMPs) such as riparian buffers, engineered wetlands, grassed waterways, filter strips and field borders) could potentially reduce current loadings of sediment by 37 to 67 percent and nutrients by 54 to 75 percent. Results from the study indicate that major improvements in water quality in these agricultural watersheds could be achieved if such environmentally-targeted agricultural practices were employed. Traditional approaches to water quality improvement through application of traditional BMPs will result in little or no change in nutrient export and minor decreases in sediment export from Corn Belt watersheds. [source] GIS-BASED HYIROLOGIC MODELING OF RIPARIAN AREAS: IMPLICATIONS FOR STREAM WATER QUALITY,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 6 2001Matthew E. Baker ABSTRACT: Riparian buffers have potential for reducing excess nutrient levels in surface water. Spatial variation in riparian buffer effectiveness is well recognized, yet researchers and managers still lack effective general tools for understanding the relevance of different hydrologic settings. We present several terrain-based GIS models to predict spatial patterns of shallow, subsurface hydrologic flux and riparian hydrology. We then link predictions of riparian hydrology to patterns of nutrient export in order to demonstrate potential for augmenting the predictive power of land use/land cover (LU/LC) maps. Using predicted hydrology in addition to LUILC, we observed increases in the explained variation of nutrient exports from 290 sites across Lower Michigan. The results suggest that our hydrologic predictions relate more strongly to patterns of nutrient export than the presence or absence of wetland vegetation, and that in fact the influence of vegetative structure largely depends on its hydrologic context. Such GIS models are useful and complimentary tools for exploring the role of hydrologic routing in riparian ecosystem function and stream water quality. Modeling efforts that take a similar GIS approach to material transport might be used to further explore the causal implications of riparian buffers in heterogeneous watersheds. [source] STREAMFLOW DEPLETION: MODELING OF REDUCED BASEFLOW ANI INDUCED STREAM INFILTRATION FROM SEASONALLY PUMPED WELLS,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 1 2001Xunhong Chen ABSTRACT: Numerical modeling techniques are used to analyze streamflow depletion for stream-aquifer systems with baseflow. The analyses calculated two flow components generated by a pumping well located at a given distance from a river that is hydraulically connected to an unconfined aquifer. The two components are induced stream infiltration and reduced baseflow; both contribute to total streamflow depletion. Simulation results suggest that the induced infiltration, the volume of water discharged from the stream to the aquifer, has a shorter term impact on streamflow, while the reduced baseflow curves show a longer term effect. The peak impacts of the two hydrologic processes on streamflow occur separately. The separate analysis helps in understanding the hydrologic interactions between stream and aquifer. Practically, it provides useful information about contaminant transport from stream to aquifer when water quality is a concern, and for areas where water quantity is an issue, the separate analysis offers additional information to the development of water resource management plan. [source] HYDROLOGIC MODELING AT THE WATERSHED SCALE USING NPSM,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 6 2000Lee Carrubba ABSTRACT: The Nonpoint Source Model (NPSM) was chosen for nonpoint source pollutant modeling within three different watersheds. The first step in using NPSM, hydrologic calibration, is discussed here for three 8-digit Hydrologic Unit Codes (HUCs) from the White River Basin in Indiana (Driftwood HUC), the Albemarle-Pamlico River Basin in Virginia and North Carolina (Contentnea HUC), and the Apalachicola-Chattahoochee-Flint River Basin in Alabama, Georgia, and Florida (Ichawaynochaway HUC). Model predicted flows were compared statistically with USGS gauge data at the HUC outflow points for an uncalibrated and calibrated model run for the period from January 1, 1990, through December 31, 1992, and a validation run for the period from January 1, 1993, through December 31, 1995. Least squares regression of NPSM predicted flows versus USGS gauge data were 0.75, 0.44, and 0.69 for the calibration runs and 0.71, 0.69, and 0.64 for the validation runs in the Driftwood, Contentnea, and Ichawaynochaway HUCs, respectively. Nash Sutcliffe coefficient values were not as strong, ranging from ,0.66 to 0.45 for the calibration runs and 0.31 to 0.37 for the validation runs of the model. The Ichawaynochaway HUC proved the most difficult to calibrate indicating that the model may not be as useful in some geographic locations. [source] ARTIFICIAL NEURAL NETWORK MODELING FOR REFORESTATION DESIGN THROUGH THE DOMINANT TREES BOLE-VOLUME ESTIMATIONNATURAL RESOURCE MODELING, Issue 4 2009MARIA J. DIAMANTOPOULOU Abstract In the management of restoration reforestations or recreational reforestations of trees, the density of the planted trees and the site conditions can influence the growth and bole volume of the dominant tree. The ability to influence growth of these trees in a reforestation contributes greatly to the formation of large dimension trees and thereby to the production of commercially valuable wood. The potential of two artificial neural network (ANN) architectures in modeling the dominant,Pinus brutia,tree bole volume in reforestation configuration at 12 years of age was investigated: (1) the multilayer perceptron architecture using a back-propagation algorithm and (2) the cascade-correlation architecture, utilizing (a) either the nonlinear Kalman's filter theory or (b) the adaptive gradient descent learning rule. The incentive for developing bole-volume equations using ANN techniques was to demonstrate an alternative new methodology in the field of reforestation design, which would enable estimation and optimization of the bole volume of dominant trees in reforestations using easily measurable site and competition factors. The usage of the ANNs for the estimation of dominant tree bole volume through site and competition factors can be a very useful tool in forest management practice. [source] INTRODUCTION TO SPECIAL ISSUE: INTEGRATED MODELING OF ECONOMIES AND ECOSYSTEMSNATURAL RESOURCE MODELING, Issue 1 2007John Tschirhart [source] USING LEAST SQUARE SVM FOR NONLINEAR SYSTEMS MODELING AND CONTROLASIAN JOURNAL OF CONTROL, Issue 2 2007Haoran Zhang ABSTRACT Support vector machine is a learning technique based on the structural risk minimization principle, and it is also a class of regression method with good generalization ability. The paper firstly introduces the mathematical model of regression least squares support vector machine (LSSVM), and designs incremental learning algorithms by the calculation formula of block matrix, then uses LSSVM to model nonlinear system, based on which to control nonlinear systems by model predictive method. Simulation experiments indicate that the proposed method provides satisfactory performance, and it achieves superior modeling performance to the conventional method based on neural networks, moreover it achieves well control performance. [source] MODELING AND CONTROL OF THE ACTIVE SUSPENSION SYSTEM USING PROPORTIONAL INTEGRAL SLIDING MODE APPROACHASIAN JOURNAL OF CONTROL, Issue 2 2005Yahaya Md. ABSTRACT The purposes of this paper are to present a new method in modeling an active suspension system for half-car model in state space form and to develop a robust strategy in controlling the active suspension system. Proportional integral sliding mode control strategy is proposed for the system. A simulation study is performed to prove the effectiveness and robustness of the control approach and performance of the controller is compared to the linear quadratic regulator and the existing passive suspension system. [source] DRAMA MANAGEMENT AND PLAYER MODELING FOR INTERACTIVE FICTION GAMESCOMPUTATIONAL INTELLIGENCE, Issue 2 2010Manu Sharma A growing research community is working toward employing drama management components in story-based games. These components gently guide the story toward a narrative arc that improves the player's gaming experience. In this article we evaluate a novel drama management approach deployed in an interactive fiction game called Anchorhead. This approach uses player's feedback as the basis for guiding the personalization of the interaction. The results indicate that adding our Case-based Drama manaGer (C-DraGer) to the game guides the players through the interaction and provides a better overall player experience. Unlike previous approaches to drama management, this article focuses on exhibiting the success of our approach by evaluating results using human players in a real game implementation. Based on this work, we report several insights on drama management which were possible only due to an evaluation with real players. [source] Interactive animation of cloth-like objects in virtual realityCOMPUTER ANIMATION AND VIRTUAL WORLDS (PREV: JNL OF VISUALISATION & COMPUTER ANIMATION), Issue 1 2001Mark Meyer Abstract Modeling and animation of cloth have experienced important developments in recent years. As a consequence, complex textile models can be used to realistically drape objects or human characters in a fairly efficient way. However, real-time realistic simulation remains a major challenge, even if applications are numerous, from rapid prototyping to e-commerce. In this paper, we present a stable, real-time algorithm for animating cloth-like materials. Using a hybrid explicit/implicit algorithm, we perform fast and stable time integration of a physically based model with rapid collision detection and response, as well as wind or liquid drag effects to enhance realism. We demonstrate our approach through a series of examples in virtual reality environments, proving that real-time animation of cloth, even on low-end computers, is now achievable. Copyright © 2001 John Wiley & Sons, Ltd. [source] Hierarchical Structure Recovery of Point-Sampled SurfacesCOMPUTER GRAPHICS FORUM, Issue 6 2010Marco Attene I.3 COMPUTER GRAPHICS; I.3.5 Computational Geometry and Object Modeling,Object hierarchies Abstract We focus on the class of ,regular' models defined by Várady et al. for reverse engineering purposes. Given a 3D surface,,represented through a dense set of points, we present a novel algorithm that converts,,to a hierarchical representation,. In,, the surface is encoded through patches of various shape and size, which form a hierarchical atlas. If,,belongs to the class of regular models, then,,captures the most significant features of,,at all the levels of detail. In this case, we show that,,can be exploited to interactively select regions of interest on,,and intuitively re-design the model. Furthermore,,,intrinsically encodes a hierarchy of useful ,segmentations' of,. We present a simple though efficient approach to extract and optimize such segmentations, and we show how they can be used to approximate the input point sets through idealized manifold meshes. [source] | ||||||||||||||||||||||||||||||||||||||||||||||