Spatially Explicit Estimation of Optimal Light Use Efficiency for Improved Satellite Data Driven Ecosystem Productivity Modeling

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Madani, N.; Kimball, J. S.; Running, S. W.

2014-12-01

Remote sensing based light use efficiency (LUE) models, including the MODIS (MODerate resolution Imaging Spectroradiometer) MOD17 algorithm are commonly used for regional estimation and monitoring of vegetation gross primary production (GPP) and photosynthetic carbon (CO2) uptake. A common model assumption is that plants in a biome matrix operate at their photosynthetic capacity under optimal climatic conditions. A prescribed biome maximum light use efficiency parameter defines the maximum photosynthetic carbon conversion rate under prevailing climate conditions and is a large source of model uncertainty. Here, we used tower (FLUXNET) eddy covariance measurement based carbon flux data for estimating optimal LUE (LUEopt) over a North American domain. LUEopt was first estimated using tower observed daily carbon fluxes, meteorology and satellite (MODIS) observed fraction of photosynthetically active radiation (FPAR). LUEopt was then spatially interpolated over the domain using empirical models derived from independent geospatial data including global plant traits, surface soil moisture, terrain aspect, land cover type and percent tree cover. The derived LUEopt maps were then used as primary inputs to the MOD17 LUE algorithm for regional GPP estimation; these results were evaluated against tower observations and alternate MOD17 GPP estimates determined using Biome-specific LUEopt constants. Estimated LUEopt shows large spatial variability within and among different land cover classes indicated from a sparse North American tower network. Leaf nitrogen content and soil moisture are two important factors explaining LUEopt spatial variability. GPP estimated from spatially explicit LUEopt inputs shows significantly improved model accuracy against independent tower observations (R2 = 0.76; Mean RMSE plant trait information can explain spatial heterogeneity in LUEopt, leading to improved GPP estimates from satellite based LUE models.

Understanding moisture stress on light use efficiency across terrestrial ecosystems based on global flux and remote-sensing data

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Yulong Zhang; Conghe Song; Ge Sun; Lawrence E. Band; Asko Noormets; Quanfa Zhang

2015-01-01

Light use efficiency (LUE) is a key biophysical parameter characterizing the ability of plants to convert absorbed light to carbohydrate. However, the environmental regulations on LUE, especially moisture stress, are poorly understood, leading to large uncertainties in primary productivity estimated by LUE models. The objective of this study is to investigate the...

Estimation of Mangrove Net Primary Production and Carbon Sequestration service using Light Use Efficiency model in the Sunderban Biosphere region, India

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Sannigrahi, Srikanta; Sen, Somnath; Paul, Saikat

2016-04-01

Net Primary Production (NPP) of mangrove ecosystem and its capacity to sequester carbon from the atmosphere may be used to quantify the regulatory ecosystem services. Three major group of parameters has been set up as BioClimatic Parameters (BCP): (Photosynthetically Active Radiation (PAR), Absorbed PAR (APAR), Fraction of PAR (FPAR), Photochemical Reflectance Index (PRI), Light Use Efficiency (LUE)), BioPhysical Parameters (BPP) :(Normalize Difference Vegetation Index (NDVI), scaled NDVI, Enhanced Vegetation Index (EVI), scaled EVI, Optimised and Modified Soil Adjusted Vegetation Index (OSAVI, MSAVI), Leaf Area Index (LAI)), and Environmental Limiting Parameters (ELP) (Temperature Stress (TS), Land Surface Water Index (LSWI), Normalize Soil Water Index (NSWI), Water Stress Scalar (WS), Inversed WS (iWS) Land Surface Temperature (LST), scaled LST, Vapor Pressure Deficit (VPD), scaled VPD, and Soil Water Deficit Index (SWDI)). Several LUE models namely Carnegie Ames Stanford Approach (CASA), Eddy Covariance - LUE (EC-LUE), Global Production Efficiency Model (GloPEM), Vegetation Photosynthesis Model (VPM), MOD NPP model, Temperature and Greenness Model (TG), Greenness and Radiation model (GR) and MOD17 was adopted in this study to assess the spatiotemporal nature of carbon fluxes. Above and Below Ground Biomass (AGB & BGB) was calculated using field based estimation of OSAVI and NDVI. Microclimatic zonation has been set up to assess the impact of coastal climate on environmental limiting factors. MODerate Resolution Imaging Spectroradiometer (MODIS) based yearly Gross Primary Production (GPP) and NPP product MOD17 was also tested with LUE based results with standard model validation statistics: Root Mean Square of Error (RMSE), Mean Absolute Error (MEA), Bias, Coefficient of Variation (CV) and Coefficient of Determination (R2). The performance of CASA NPP was tested with the ground based NPP with R2 = 0.89 RMSE = 3.28 P = 0.01. Among the all adopted models, EC-LUE

Does canopy mean N concentration explain differences in light use efficiency in 14 eddy-covariance sites?

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Peltoniemi, Mikko; Pulkkinen, Minna; Kolari, Pasi; Mäkelä, Annikki

2010-05-01

Production efficiency models aim at explaining variation of vegetation productivity with climatic input and information on vegetation cover often obtained from satellite observations. It has been acknowledged that different plant species differ in their potential to assimilate carbon dioxide per unit of PAR (i.e light use efficiency, LUE). Subsequently, some LUE-based models apply different LUE-coefficients for different plant functional types. Leaf N concentrations differ between plant species, and related differences in light saturated photosynthesis rate (A_max) have been detected. How much these differences affect the ecosystem production or LUE is more obscure. Canopies acclimate to prevailing environmental conditions, which causes variation e.g. in the proportion of leaves exposed to direct sunlight, leaf morphology, structure,orientation, and vertical N distibution. Furthermore, a fair proportion of photosynthesis occurs during cloudy days, in which case high A_max is unessential, and number of these days differs by location. We studied if canopy mean N concentration could explain differences in LUE derived for 14 forest sites using eddy-covariance measurements. The largest actual LUE was estimated for each site directly as an upper percentile of the ratio of Gross Primary Production (GPP) to absorbed PAR. Potential LUE for each site, on the other hand, was estimated by parameterising a LUE-based production efficiency model (Prelued), which accounts for daily changes in weather (temperature, VPD, PAR). In this model structure, the LUE-parameter for each site, can be interpreted as the potential LUE under optimal environmental conditions, i.e when the environment is not limiting production at all. Averages of the largest actual LUE and potential LUE were higher in deciduous sites than in conifer sites. Canopy mean N correlated weakly with both the largest actual and potential LUE, and the correlation was also significant in conifer subset in the former case

Estimating Diurnal Courses of Gross Primary Production for Maize: A Comparison of Sun-Induced Chlorophyll Fluorescence, Light-Use Efficiency and Process-Based Models

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Tianxiang Cui

2017-12-01

Full Text Available Accurately quantifying gross primary production (GPP is of vital importance to understanding the global carbon cycle. Light-use efficiency (LUE models and process-based models have been widely used to estimate GPP at different spatial and temporal scales. However, large uncertainties remain in quantifying GPP, especially for croplands. Recently, remote measurements of solar-induced chlorophyll fluorescence (SIF have provided a new perspective to assess actual levels of plant photosynthesis. In the presented study, we evaluated the performance of three approaches, including the LUE-based multi-source data synergized quantitative (MuSyQ GPP algorithm, the process-based boreal ecosystem productivity simulator (BEPS model, and the SIF-based statistical model, in estimating the diurnal courses of GPP at a maize site in Zhangye, China. A field campaign was conducted to acquire synchronous far-red SIF (SIF760 observations and flux tower-based GPP measurements. Our results showed that both SIF760 and GPP were linearly correlated with APAR, and the SIF760-GPP relationship was adequately characterized using a linear function. The evaluation of the modeled GPP against the GPP measured from the tower demonstrated that all three approaches provided reasonable estimates, with R2 values of 0.702, 0.867, and 0.667 and RMSE values of 0.247, 0.153, and 0.236 mg m−2 s−1 for the MuSyQ-GPP, BEPS and SIF models, respectively. This study indicated that the BEPS model simulated the GPP best due to its efficiency in describing the underlying physiological processes of sunlit and shaded leaves. The MuSyQ-GPP model was limited by its simplification of some critical ecological processes and its weakness in characterizing the contribution of shaded leaves. The SIF760-based model demonstrated a relatively limited accuracy but showed its potential in modeling GPP without dependency on climate inputs in short-term studies.

Combining Observations in the Reflective Solar and Thermal Domains for Improved Mapping of Carbon, Water and Energy FLuxes

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Houborg, Rasmus; Anderson, Martha; Kustas, Bill; Rodell, Matthew

2011-01-01

This study investigates the utility of integrating remotely sensed estimates of leaf chlorophyll (C(sub ab)) into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. Day to day variations in nominal LUE (LUE(sub n)) were assessed for a corn crop field in Maryland U.S.A. through model calibration with CO2 flux tower observations. The optimized daily LUE(sub n) values were then compared to estimates of C(sub ab) integrated from gridded maps of chlorophyll content weighted over the tower flux source area. Changes in Cab exhibited a curvilinear relationship with corresponding changes in daily calibrated LUE(sub n) values derived from the tower flux data, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C(sub ab) for delineating spatio-temporal variations in LUE(sub n). The results demonstrate the synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for monitoring of carbon and water fluxes.

Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data

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Yuan, W.; Liu, S.; Yu, G.; Bonnefond, J.-M.; Chen, J.; Davis, K.; Desai, A.R.; Goldstein, Allen H.; Gianelle, D.; Rossi, F.; Suyker, A.E.; Verma, S.B.

2010-01-01

The simulation of gross primary production (GPP) at various spatial and temporal scales remains a major challenge for quantifying the global carbon cycle. We developed a light use efficiency model, called EC-LUE, driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux. The EC-LUE model may have the most potential to adequately address the spatial and temporal dynamics of GPP because its parameters (i.e., the potential light use efficiency and optimal plant growth temperature) are invariant across the various land cover types. However, the application of the previous EC-LUE model was hampered by poor prediction of Bowen ratio at the large spatial scale. In this study, we substituted the Bowen ratio with the ratio of evapotranspiration (ET) to net radiation, and revised the RS-PM (Remote Sensing-Penman Monteith) model for quantifying ET. Fifty-four eddy covariance towers, including various ecosystem types, were selected to calibrate and validate the revised RS-PM and EC-LUE models. The revised RS-PM model explained 82% and 68% of the observed variations of ET for all the calibration and validation sites, respectively. Using estimated ET as input, the EC-LUE model performed well in calibration and validation sites, explaining 75% and 61% of the observed GPP variation for calibration and validation sites respectively.Global patterns of ET and GPP at a spatial resolution of 0.5° latitude by 0.6° longitude during the years 2000–2003 were determined using the global MERRA dataset (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate Resolution Imaging Spectroradiometer). The global estimates of ET and GPP agreed well with the other global models from the literature, with the highest ET and GPP over tropical forests and the lowest values in dry and high latitude areas. However, comparisons with observed

Remote Sensing of Ecosystem Light Use Efficiency Using MODIS

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Huemmrich, K. F.; Middleton, E.; Landis, D.; Black, T. A.; Barr, A. G.; McCaughey, J. H.; Hall, F.

2009-12-01

Understanding the dynamics of the global carbon cycle requires an accurate determination of the spatial and temporal distribution of photosynthetic CO2 uptake by terrestrial vegetation. Optimal photosynthetic function is negatively affected by stress factors that cause down-regulation (i.e., reduced rate of photosynthesis). Present modeling approaches to determine ecosystem carbon exchange rely on meteorological data as inputs to models that predict the relative photosynthetic function in response to environmental conditions inducing stress (e.g., drought, high/low temperatures). This study examines the determination of ecosystem photosynthetic light use efficiency (LUE) from remote sensing, through measurement of vegetation spectral reflectance changes associated with physiologic stress responses exhibited by photosynthetic pigments. This approach uses the Moderate-Resolution Spectroradiometer (MODIS) on Aqua and Terra to provide frequent, narrow-band measurements. The reflective ocean MODIS bands were used to calculate the Photochemical Reflectance Index (PRI), an index that is sensitive to reflectance changes near 531nm associated with vegetation stress responses exhibited by photosynthetic pigments in the xanthophyll cycle. MODIS PRI values were compared with LUE calculated from CO2 flux measured at four Canadian forest sites: A mature Douglas fir site in British Columbia, mature aspen and black spruce sites in Saskatchewan, and a mixed forest site in Ontario, all part of the Canadian Carbon Program network. The relationships between LUE and MODIS PRI were different among forest types, with clear differences in the slopes of the relationships for conifer and deciduous forests. The MODIS based LUE measurements provide a more accurate estimation of observed LUE than the values calculated in the MODIS GPP model. This suggests the possibility of a GPP model that uses MODIS LUE instead of modeled LUE. This type of model may provide a useful contrast to existing

Choses vues, choses lues : le reportage à l'épreuve de l'intertexte

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Myriam Boucharenc

2006-09-01

Full Text Available Le reportage qui s’impose dès la Belle Epoque comme le genre phare de la grande presse d’information, est en passe de devenir durant l’entre-deux-guerres un nouveau genre litté­raire : la tentation de l’enquête touche alors un nombre considérable d’écrivains et non des moindres – Colette, Cendrars, Dorgelès, Carco, Soupault, Vailland... – pour n’en citer que quelques-uns. L’ambiguïté du genre tient notam­ment à sa double postulation, l’une vers la littéralité (la soumission à la « chose vue », l’autre vers la littérarité : la chose « écrite » mais aussi « lue ». Partant, le reportage entre­tient un rapport hésitant et duplice avec le jeu intertextuel qui, variablement assumé, semble remplir différentes fonctions parmi lesquelles une fonction polémique (de démar­cation par rapport aux genres mitoyens du roman d’aventures et du récit de voyage, une fonction poétique s’exerçant dans le paradigme restreint d’un genre à la recherche de ses rituels d’écriture propres, une fonction génétique enfin, dans la mesure où l’œuvre de l’écrivain bien souvent s’amorce, se poursuit ou se réfléchit dans l’écriture du reportage.

Modified Light Use Efficiency Model for Assessment of Carbon Sequestration in Grasslands of Kazakhstan: Combining Ground Biomass Data and Remote-sensing

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Propastin, Pavel A.; Kappas, Martin W.; Herrmann, Stefanie M.; Tucker, Compton J.

2012-01-01

A modified light use efficiency (LUE) model was tested in the grasslands of central Kazakhstan in terms of its ability to characterize spatial patterns and interannual dynamics of net primary production (NPP) at a regional scale. In this model, the LUE of the grassland biome (en) was simulated from ground-based NPP measurements, absorbed photosynthetically active radiation (APAR) and meteorological observations using a new empirical approach. Using coarse-resolution satellite data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), monthly NPP was calculated from 1998 to 2008 over a large grassland region in Kazakhstan. The modelling results were verified against scaled up plot-level observations of grassland biomass and another available NPP data set derived from a field study in a similar grassland biome. The results indicated the reliability of productivity estimates produced by the model for regional monitoring of grassland NPP. The method for simulation of en suggested in this study can be used in grassland regions where no carbon flux measurements are accessible.

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007-2014

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Ma, J.; Xiao, X.; Zhang, Y.; Chen, B.; Zhao, B.

2017-12-01

Great significance exists in accurately estimating spatial-temporal patterns of gross primary production (GPP) because of its important role in global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatially time-sires GPP. However, the estimation of the accuracy of GPP simulations from LUE at both spatial and temporal scales is still a challenging work. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images of 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPPVPM) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPPVPM and SIF data over both single year (2010) and multiple years (2007-2014) in China. Annual GPPVPM is significantly positive correlated with SIF (R2>0.43) spatially for all years during 2007-2014 and all seasons in 2010 (R2>0.37). GPP dynamic trends is high spatial-temporal heterogeneous in China during 2007-2014. The results of this study indicate that GPPVPM is temporally and spatially in line with SIF data, and space-borne SIF data have great potential in validating and parameterizing GPP estimation of LUE-based models.

Combining Microbial Enzyme Kinetics Models with Light Use Efficiency Models to Predict CO2 and CH4 Ecosystem Exchange from Flooded and Drained Peatland Systems

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Oikawa, P. Y.; Jenerette, D.; Knox, S. H.; Sturtevant, C. S.; Verfaillie, J. G.; Baldocchi, D. D.

2014-12-01

Under California's Cap-and-Trade program, companies are looking to invest in land-use practices that will reduce greenhouse gas (GHG) emissions. The Sacramento-San Joaquin River Delta is a drained cultivated peatland system and a large source of CO2. To slow soil subsidence and reduce CO2 emissions, there is growing interest in converting drained peatlands to wetlands. However, wetlands are large sources of CH4 that could offset CO2-based GHG reductions. The goal of our research is to provide accurate measurements and model predictions of the changes in GHG budgets that occur when drained peatlands are restored to wetland conditions. We have installed a network of eddy covariance towers across multiple land use types in the Delta and have been measuring CO2 and CH4 ecosystem exchange for multiple years. In order to upscale these measurements through space and time we are using these data to parameterize and validate a process-based biogeochemical model. To predict gross primary productivity (GPP), we are using a simple light use efficiency (LUE) model which requires estimates of light, leaf area index and air temperature and can explain 90% of the observed variation in GPP in a mature wetland. To predict ecosystem respiration we have adapted the Dual Arrhenius Michaelis-Menten (DAMM) model. The LUE-DAMM model allows accurate simulation of half-hourly net ecosystem exchange (NEE) in a mature wetland (r2=0.85). We are working to expand the model to pasture, rice and alfalfa systems in the Delta. To predict methanogenesis, we again apply a modified DAMM model, using simple enzyme kinetics. However CH4 exchange is complex and we have thus expanded the model to predict not only microbial CH4 production, but also CH4 oxidation, CH4 storage and the physical processes regulating the release of CH4 to the atmosphere. The CH4-DAMM model allows accurate simulation of daily CH4 ecosystem exchange in a mature wetland (r2=0.55) and robust estimates of annual CH4 budgets. The LUE

Light use efficiency over two temperate steppes in inner Mongolia, China.

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Yu Wang

Full Text Available Vegetation light use efficiency (LUE is a key parameter of Production Efficiency Models (PEMs for simulating gross primary production (GPP of vegetation, from regional to global scales. Previous studies suggest that grasslands have the largest inter-site variation of LUE and controlling factors of grassland LUE differ from those of other biomes, since grasslands are usually water-limited ecosystems. Combining eddy covariance flux data with the fraction of photosynthetically active radiation absorbed by the plant canopy from MODIS, we report LUE on a typical steppe and a desert steppe in Inner Mongolia, northern China. Results show that both annual average LUE and maximum LUE were higher on the desert steppe (0.51 and 1.13 g C MJ(-1 than on the typical steppe (0.34 and 0.88 g C MJ(-1, despite the higher GPP of the latter. Water availability was the primary limiting factor of LUE at both sites. Evaporative fraction (EF or the ratio of actual evapotranspiration to potential evapotranspiration (AET/PET can explain 50-70% of seasonal LUE variations at both sites. However, the slope of linear regression between LUE and EF (or AET/PET differed significantly between the two sites. LUE increased with the diffuse radiation ratio on the typical steppe; however, such a trend was not found for the desert steppe. Our results suggest that a biome-dependent LUE(max is inappropriate, because of the large inter-site difference of LUE(max within the biome. EF could be a promising down-regulator on grassland LUE for PEMs, but there may be a site-specific relationship between LUE and EF.

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007-2014.

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Ma, Jun; Xiao, Xiangming; Zhang, Yao; Doughty, Russell; Chen, Bangqian; Zhao, Bin

2018-10-15

Accurately estimating spatial-temporal patterns of gross primary production (GPP) is important for the global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatial-temporal dynamics of GPP. However, the accuracy assessment of GPP simulations from LUE models at both spatial and temporal scales remains a challenge. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images with 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPP VPM ) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPP VPM and SIF data over a single year (2010) and multiple years (2007-2014) in most areas of China. GPP VPM is also significantly positive correlated with GOME-2 SIF (R 2  > 0.43) spatially for seasonal scales. However, poor consistency was detected between GPP VPM and SIF data at yearly scale. GPP dynamic trends have high spatial-temporal variation in China during 2007-2014. Temperature, leaf area index (LAI), and precipitation are the most important factors influence GPP VPM in the regions of East Qinghai-Tibet Plateau, Loss Plateau, and Southwestern China, respectively. The results of this study indicate that GPP VPM is temporally and spatially in line with GOME-2 SIF data, and space-borne SIF data have great potential for evaluating LUE-based GPP models. Copyright © 2018 Elsevier B.V. All rights reserved.

Simulation of the Unexpected Photosynthetic Seasonality in Amazonian Evergreen Forests by Using an Improved Diffuse Fraction-Based Light Use Efficiency Model

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Yan, Hao; Wang, Shao-Qiang; da Rocha, Humberto R.; Rap, Alexandru; Bonal, Damien; Butt, Nathalie; Coupe, Natalia Restrepo; Shugart, Herman H.

2017-11-01

Understanding the mechanism of photosynthetic seasonality in Amazonian evergreen forests is critical for its formulation in global climate and carbon cycle models. However, the control of the unexpected photosynthetic seasonality is highly uncertain. Here we use eddy-covariance data across a network of Amazonian research sites and a novel evapotranspiration (E) and two-leaf-photosynthesis-coupled model to investigate links between photosynthetic seasonality and climate factors on monthly scales. It reproduces the GPP seasonality (R2 = 0.45-0.69) with a root-mean-square error (RMSE) of 0.67-1.25 g C m-2 d-1 and a Bias of -0.03-1.04 g C m-2 d-1 for four evergreen forest sites. We find that the proportion of diffuse and direct sunlight governs the photosynthetic seasonality via their interaction with sunlit and shaded leaves, supported by a proof that canopy light use efficiency (LUE) has a strong linear relationship with the fraction of diffuse sunlight for Amazonian evergreen forests. In the transition from dry season to rainy season, incident total radiation (Q) decreased while LUE and diffuse fraction increased, which produced the large seasonal increase ( 34%) in GPP of evergreen forests. We conclude that diffuse radiation is an important environmental driver of the photosynthetic seasonality in tropical Amazon forests yet depending on light utilization by sunlit and shaded leaves. Besides, the GPP model simulates the precipitation-dominated GPP seasonality (R2 = 0.40-0.69) at pasture and savanna sites. These findings present an improved physiological method to relate light components with GPP in tropical Amazon.

Parameter identification of chaos system based on unknown parameter observer

International Nuclear Information System (INIS)

Wang Shaoming; Luo Haigeng; Yue Chaoyuan; Liao Xiaoxin

2008-01-01

Parameter identification of chaos system based on unknown parameter observer is discussed generally. Based on the work of Guan et al. [X.P. Guan, H.P. Peng, L.X. Li, et al., Acta Phys. Sinica 50 (2001) 26], the design of unknown parameter observer is improved. The application of the improved approach is extended greatly. The works in some literatures [X.P. Guan, H.P. Peng, L.X. Li, et al., Acta Phys. Sinica 50 (2001) 26; J.H. Lue, S.C. Zhang, Phys. Lett. A 286 (2001) 148; X.Q. Wu, J.A. Lu, Chaos Solitons Fractals 18 (2003) 721; J. Liu, S.H. Chen, J. Xie, Chaos Solitons Fractals 19 (2004) 533] are only the special cases of our Corollaries 1 and 2. Some observers for Lue system and a new chaos system are designed to test our improved method, and simulations results demonstrate the effectiveness and feasibility of the improved approach

Establishment of the Relationship between the Photochemical Reflectance Index and Canopy Light Use Efficiency Using Multi-angle Hyperspectral Observations

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Zhang, Qian; Chen, Jing; Zhang, Yongguang; Qiu, Feng; Fan, Weiliang; Ju, Weimin

2017-04-01

The gross primary production (GPP) of terrestrial ecosystems constitutes the largest global land carbon flux and exhibits significant spatial and temporal variations. Due to its wide spatial coverage, remote sensing technology is shown to be useful for improving the estimation of GPP in combination with light use efficiency (LUE) models. Accurate estimation of LUE is essential for calculating GPP using remote sensing data and LUE models at regional and global scales. A promising method used for estimating LUE is the photochemical reflectance index (PRI = (R531－R570)/(R531 + R570), where R531 and R570 are reflectance at wavelengths 531 and 570 nm) through remote sensing. However, it has been documented that there are certain issues with PRI at the canopy scale, which need to be considered systematically. For this purpose, an improved tower-based automatic canopy multi-angle hyperspectral observation system was established at the Qianyanzhou flux station in China since January of 2013. In each 15-minute observation cycle, PRI was observed at four view zenith angles fixed at solar zenith angle and (37°, 47°, 57°) or (42°, 52°, 62°) in the azimuth angle range from 45° to 325° (defined from geodetic north). To improve the ability of directional PRI observation to track canopy LUE, the canopy is treated as two-big leaves, i.e. sunlit and shaded leaves. On the basis of a geometrical optical model, the observed canopy reflectance for each view angle is separated to four components, i.e. sunlit and shaded leaves and sunlit and shaded backgrounds. To determine the fractions of these four components at each view angle, three models based on different theories are tested for simulating the fraction of sunlit leaves. Finally, a ratio of canopy reflectance to leaf reflectance is used to represent the fraction of sunlit leaves, and the fraction of shaded leaves is calculated with the four-scale geometrical optical model. Thus, sunlit and shaded PRI are estimated using

Estimating primary productivity of tropical oil palm in Malaysia using remote sensing technique and ancillary data

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Kanniah, K. D.; Tan, K. P.; Cracknell, A. P.

2014-10-01

The amount of carbon sequestration by vegetation can be estimated using vegetation productivity. At present, there is a knowledge gap in oil palm net primary productivity (NPP) at a regional scale. Therefore, in this study NPP of oil palm trees in Peninsular Malaysia was estimated using remote sensing based light use efficiency (LUE) model with inputs from local meteorological data, upscaled leaf area index/fractional photosynthetically active radiation (LAI/fPAR) derived using UK-DMC 2 satellite data and a constant maximum LUE value from the literature. NPP values estimated from the model was then compared and validated with NPP estimated using allometric equations developed by Corley and Tinker (2003), Henson (2003) and Syahrinudin (2005) with diameter at breast height, age and the height of the oil palm trees collected from three estates in Peninsular Malaysia. Results of this study show that oil palm NPP derived using a light use efficiency model increases with respect to the age of oil palm trees, and it stabilises after ten years old. The mean value of oil palm NPP at 118 plots as derived using the LUE model is 968.72 g C m-2 year-1 and this is 188% - 273% higher than the NPP derived from the allometric equations. The estimated oil palm NPP of young oil palm trees is lower compared to mature oil palm trees (oil palm trees contribute to lower oil palm LAI and therefore fPAR, which is an important variable in the LUE model. In contrast, it is noted that oil palm NPP decreases with respect to the age of oil palm trees as estimated using the allomeric equations. It was found in this study that LUE models could not capture NPP variation of oil palm trees if LAI/fPAR is used. On the other hand, tree height and DBH are found to be important variables that can capture changes in oil palm NPP as a function of age.

Improving Global Gross Primary Productivity Estimates by Computing Optimum Light Use Efficiencies Using Flux Tower Data

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Madani, Nima; Kimball, John S.; Running, Steven W.

2017-11-01

In the light use efficiency (LUE) approach of estimating the gross primary productivity (GPP), plant productivity is linearly related to absorbed photosynthetically active radiation assuming that plants absorb and convert solar energy into biomass within a maximum LUE (LUEmax) rate, which is assumed to vary conservatively within a given biome type. However, it has been shown that photosynthetic efficiency can vary within biomes. In this study, we used 149 global CO2 flux towers to derive the optimum LUE (LUEopt) under prevailing climate conditions for each tower location, stratified according to model training and test sites. Unlike LUEmax, LUEopt varies according to heterogeneous landscape characteristics and species traits. The LUEopt data showed large spatial variability within and between biome types, so that a simple biome classification explained only 29% of LUEopt variability over 95 global tower training sites. The use of explanatory variables in a mixed effect regression model explained 62.2% of the spatial variability in tower LUEopt data. The resulting regression model was used for global extrapolation of the LUEopt data and GPP estimation. The GPP estimated using the new LUEopt map showed significant improvement relative to global tower data, including a 15% R2 increase and 34% root-mean-square error reduction relative to baseline GPP calculations derived from biome-specific LUEmax constants. The new global LUEopt map is expected to improve the performance of LUE-based GPP algorithms for better assessment and monitoring of global terrestrial productivity and carbon dynamics.

Developing a Data Driven Process-Based Model for Remote Sensing of Ecosystem Production

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Elmasri, B.; Rahman, A. F.

2010-12-01

Estimating ecosystem carbon fluxes at various spatial and temporal scales is essential for quantifying the global carbon cycle. Numerous models have been developed for this purpose using several environmental variables as well as vegetation indices derived from remotely sensed data. Here we present a data driven modeling approach for gross primary production (GPP) that is based on a process based model BIOME-BGC. The proposed model was run using available remote sensing data and it does not depend on look-up tables. Furthermore, this approach combines the merits of both empirical and process models, and empirical models were used to estimate certain input variables such as light use efficiency (LUE). This was achieved by using remotely sensed data to the mathematical equations that represent biophysical photosynthesis processes in the BIOME-BGC model. Moreover, a new spectral index for estimating maximum photosynthetic activity, maximum photosynthetic rate index (MPRI), is also developed and presented here. This new index is based on the ratio between the near infrared and the green bands (ρ858.5/ρ555). The model was tested and validated against MODIS GPP product and flux measurements from two eddy covariance flux towers located at Morgan Monroe State Forest (MMSF) in Indiana and Harvard Forest in Massachusetts. Satellite data acquired by the Advanced Microwave Scanning Radiometer (AMSR-E) and MODIS were used. The data driven model showed a strong correlation between the predicted and measured GPP at the two eddy covariance flux towers sites. This methodology produced better predictions of GPP than did the MODIS GPP product. Moreover, the proportion of error in the predicted GPP for MMSF and Harvard forest was dominated by unsystematic errors suggesting that the results are unbiased. The analysis indicated that maintenance respiration is one of the main factors that dominate the overall model outcome errors and improvement in maintenance respiration estimation

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Science.gov (United States)

Huemmrich, Karl Fred; Gamon, John A.; Tweedie, Craig E.; Campbell, Petya K. Entcheva; Landis, David R.; Middleton, Elizabeth M.

2013-01-01

Non-vascular plants (lichens and mosses) are significant components of tundra landscapes and may respond to climate change differently from vascular plants affecting ecosystem carbon balance. Remote sensing provides critical tools for monitoring plant cover types, as optical signals provide a way to scale from plot measurements to regional estimates of biophysical properties, for which spatial-temporal patterns may be analyzed. Gas exchange measurements were collected for pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow, AK. These functional types were found to have three significantly different values of light use efficiency (LUE) with values of 0.013 plus or minus 0.0002, 0.0018 plus or minus 0.0002, and 0.0012 plus or minus 0.0001 mol C mol (exp -1) absorbed quanta for vascular plants, mosses and lichens, respectively. Discriminant analysis of the spectra reflectance of these patches identified five spectral bands that separated each of these vegetation functional types as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Along the transect, area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. The patch-level statistical discriminant functions applied to in situ hyperspectral reflectance data collected along the transect successfully unmixed cover fractions of the vegetation functional types. The unmixing functions, developed from the transect data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine variability in distribution of the vegetation functional types for an area near Barrow, AK. Spatial variability of LUE was derived from the observed functional type distributions. Across this landscape, a

Estimating crop net primary production using inventory data and MODIS-derived parameters

Energy Technology Data Exchange (ETDEWEB)

Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.; Izaurralde, Roberto C.

2013-06-03

National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois in years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.

Seasonal and within-canopy variation in shoot-scale resource-use efficiency trade-offs in a Norway spruce stand.

Science.gov (United States)

Tarvainen, Lasse; Räntfors, Mats; Wallin, Göran

2015-11-01

Previous leaf-scale studies of carbon assimilation describe short-term resource-use efficiency (RUE) trade-offs where high use efficiency of one resource requires low RUE of another. However, varying resource availabilities may cause long-term RUE trade-offs to differ from the short-term patterns. This may have important implications for understanding canopy-scale resource use and allocation. We used continuous gas exchange measurements collected at five levels within a Norway spruce, Picea abies (L.) karst., canopy over 3 years to assess seasonal differences in the interactions between shoot-scale resource availability (light, water and nitrogen), net photosynthesis (An ) and the use efficiencies of light (LUE), water (WUE) and nitrogen (NUE) for carbon assimilation. The continuous data set was used to develop and evaluate multiple regression models for predicting monthly shoot-scale An . These models showed that shoot-scale An was strongly dependent on light availability and was generally well described with simple one- or two-parameter models. WUE peaked in spring, NUE in summer and LUE in autumn. However, the relative importance of LUE for carbon assimilation increased with canopy depth at all times. Our results suggest that accounting for seasonal and within-canopy trade-offs may be important for RUE-based modelling of canopy carbon uptake. © 2015 John Wiley & Sons Ltd.

Guiding exploration in conformational feature space with Lipschitz underestimation for ab-initio protein structure prediction.

Science.gov (United States)

Hao, Xiaohu; Zhang, Guijun; Zhou, Xiaogen

2018-04-01

Computing conformations which are essential to associate structural and functional information with gene sequences, is challenging due to the high dimensionality and rugged energy surface of the protein conformational space. Consequently, the dimension of the protein conformational space should be reduced to a proper level, and an effective exploring algorithm should be proposed. In this paper, a plug-in method for guiding exploration in conformational feature space with Lipschitz underestimation (LUE) for ab-initio protein structure prediction is proposed. The conformational space is converted into ultrafast shape recognition (USR) feature space firstly. Based on the USR feature space, the conformational space can be further converted into Underestimation space according to Lipschitz estimation theory for guiding exploration. As a consequence of the use of underestimation model, the tight lower bound estimate information can be used for exploration guidance, the invalid sampling areas can be eliminated in advance, and the number of energy function evaluations can be reduced. The proposed method provides a novel technique to solve the exploring problem of protein conformational space. LUE is applied to differential evolution (DE) algorithm, and metropolis Monte Carlo(MMC) algorithm which is available in the Rosetta; When LUE is applied to DE and MMC, it will be screened by the underestimation method prior to energy calculation and selection. Further, LUE is compared with DE and MMC by testing on 15 small-to-medium structurally diverse proteins. Test results show that near-native protein structures with higher accuracy can be obtained more rapidly and efficiently with the use of LUE. Copyright © 2018 Elsevier Ltd. All rights reserved.

Temporal Variability of Canopy Light Use Efficiency and its Environmental Controls in a Subtropical Mangrove Wetland

Science.gov (United States)

Zhu, X.

2016-12-01

Mangrove wetlands play an important role in global carbon cycle due to their strong carbon sequestration resulting from high plant carbon assimilation and low soil respiration. However, temporal variability of carbon sequestration in mangrove wetlands is less understood since carbon processes of mangrove wetlands are influenced by many complicated and concurrent environmental controls including tidal activities, site climate and soil conditions. Canopy light use efficiency (LUE), is the most important plant physiological parameter that can be used to describe the temporal dynamics of canopy photosynthesis, and therefore a better characterization of temporal variability of canopy LUE will improve our understanding in mangrove photosynthesis and carbon balance. One of our aims is to study the temporal variability of canopy LUE and its environmental controls in a subtropical mangrove wetland. Half-hourly canopy LUE is derived from eddy covariance (EC) carbon flux and photosynthesis active radiation observations, and half-hourly environmental controls we measure include temperature, humidity, precipitation, radiation, tidal height, salinity, etc. Another aim is to explore the links between canopy LUE and spectral indices derived from near-surface tower-based remote sensing (normalized difference vegetation index, enhanced vegetation index, photochemical reflectance index, solar-induced chlorophyll fluorescence, etc.), and then identify potential quantitative relationships for developing remote sensing-based estimation methods of canopy LUE. At present, some instruments in our in-situ observation system have not yet been installed (planned in next months) and therefore we don't have enough measurements to support our analysis. However, a preliminary analysis of our historical EC and climate observations in past several years indicates that canopy LUE shows strong temporal variability and is greatly affected by environmental factors such as tidal activity. Detailed and

Combat Modeling Evaluation at the United States Military Academy.

Science.gov (United States)

1985-06-01

Sttuvt Prosres) * ktert Cal~ * kittemeasi qeemtii * mosl Slalsmite of hsamua Isse * omaptmbe vih Oiphies war"" * tm ktes (mse lads/54m TWO) 7ftm a. wa...difficuLty in WM. Onu feasibLe approach in the usP41nsien Of the artillery lsthaillty piarauuLir iste ia vector which reflects the letchal ity of that...ion voomqiutat Acso; wit ist Iivi .4,~~C4.LUisiab v0lueS. Thsu approoath Is apilrlllae fur a modial Much IV 11TH. J1. L’’A K tisnt/ntQuaial.in

Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing

DEFF Research Database (Denmark)

Tagesson, Håkan Torbern; Smith, Benjamin; Løfgren, Anders

2009-01-01

and the Beer-Lambert law. LAI estimates were compared with satellite-extrapolated field estimates of LAI, and the results were generally acceptable. NPP estimates directly from the dynamic vegetation model and estimates obtained by combining the model estimates with remote sensing information were, on average......The aim of this study was to investigate a combination of satellite images of leaf area index (LAI) with processbased vegetation modeling for the accurate assessment of the carbon balances of Swedish forest ecosystems at the scale of a landscape. Monthly climatologic data were used as inputs...... in a dynamic vegetation model, the Lund Potsdam Jena-General Ecosystem Simulator. Model estimates of net primary production (NPP) and the fraction of absorbed photosynthetic active radiation were constrained by combining them with satellite-based LAI images using a general light use efficiency (LUE) model...

Incorporating diffuse radiation into a light use efficiency and evapotranspiration model: An 11-year study in a high latitude deciduous forest

DEFF Research Database (Denmark)

Wang, Sheng; Ibrom, Andreas; Bauer-Gottwein, Peter

2018-01-01

set were used to statistically explore the independent and joint effects of diffuse PAR on GPP, ET, incident light use efficiency (LUE), evaporative fraction (EF) and ecosystem water use efficiency (WUE). The independent and joint effects of CI were compared from global sensitivity analysis...... pressure saturation deficit played a major role for the joint influence of CI on LUE and EF. In the growing season from May to October, variation in CI accounts for 11.9%, 3.0% and 7.8% of the total variation of GPP, ET and transpiration, respectively. As the influence of CI on GPP is larger than...... PAR with plant canopies, the largest model improvements using CI for GPP and ET occurred during the growing season and for the transpiration component, as suggested by comparisons to sap flow measurements. Furthermore, our study suggests a potential biophysical mechanism, not considered in other...

Development of estimation method for crop yield using MODIS satellite imagery data and process-based model for corn and soybean in US Corn-Belt region

Science.gov (United States)

Lee, J.; Kang, S.; Jang, K.; Ko, J.; Hong, S.

2012-12-01

Crop productivity is associated with the food security and hence, several models have been developed to estimate crop yield by combining remote sensing data with carbon cycle processes. In present study, we attempted to estimate crop GPP and NPP using algorithm based on the LUE model and a simplified respiration model. The state of Iowa and Illinois was chosen as the study site for estimating the crop yield for a period covering the 5 years (2006-2010), as it is the main Corn-Belt area in US. Present study focuses on developing crop-specific parameters for corn and soybean to estimate crop productivity and yield mapping using satellite remote sensing data. We utilized a 10 km spatial resolution daily meteorological data from WRF to provide cloudy-day meteorological variables but in clear-say days, MODIS-based meteorological data were utilized to estimate daily GPP, NPP, and biomass. County-level statistics on yield, area harvested, and productions were used to test model predicted crop yield. The estimated input meteorological variables from MODIS and WRF showed with good agreements with the ground observations from 6 Ameriflux tower sites in 2006. For examples, correlation coefficients ranged from 0.93 to 0.98 for Tmin and Tavg ; from 0.68 to 0.85 for daytime mean VPD; from 0.85 to 0.96 for daily shortwave radiation, respectively. We developed county-specific crop conversion coefficient, i.e. ratio of yield to biomass on 260 DOY and then, validated the estimated county-level crop yield with the statistical yield data. The estimated corn and soybean yields at the county level ranged from 671 gm-2 y-1 to 1393 gm-2 y-1 and from 213 gm-2 y-1 to 421 gm-2 y-1, respectively. The county-specific yield estimation mostly showed errors less than 10%. Furthermore, we estimated crop yields at the state level which were validated against the statistics data and showed errors less than 1%. Further analysis for crop conversion coefficient was conducted for 200 DOY and 280 DOY

Can a Satellite-Derived Estimate of the Fraction of PAR Absorbed by Chlorophyll (FAPAR(sub chl)) Improve Predictions of Light-Use Efficiency and Ecosystem Photosynthesis for a Boreal Aspen Forest?

Science.gov (United States)

Zhang, Qingyuan; Middleton, Elizabeth M.; Margolis, Hank A.; Drolet, Guillaume G.; Barr, Alan A.; Black, T. Andrew

2009-01-01

Gross primary production (GPP) is a key terrestrial ecophysiological process that links atmospheric composition and vegetation processes. Study of GPP is important to global carbon cycles and global warming. One of the most important of these processes, plant photosynthesis, requires solar radiation in the 0.4-0.7 micron range (also known as photosynthetically active radiation or PAR), water, carbon dioxide (CO2), and nutrients. A vegetation canopy is composed primarily of photosynthetically active vegetation (PAV) and non-photosynthetic vegetation (NPV; e.g., senescent foliage, branches and stems). A green leaf is composed of chlorophyll and various proportions of nonphotosynthetic components (e.g., other pigments in the leaf, primary/secondary/tertiary veins, and cell walls). The fraction of PAR absorbed by whole vegetation canopy (FAPAR(sub canopy)) has been widely used in satellite-based Production Efficiency Models to estimate GPP (as a product of FAPAR(sub canopy)x PAR x LUE(sub canopy), where LUE(sub canopy) is light use efficiency at canopy level). However, only the PAR absorbed by chlorophyll (a product of FAPAR(sub chl) x PAR) is used for photosynthesis. Therefore, remote sensing driven biogeochemical models that use FAPAR(sub chl) in estimating GPP (as a product of FAPAR(sub chl x PAR x LUE(sub chl) are more likely to be consistent with plant photosynthesis processes.

Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales

DEFF Research Database (Denmark)

Wu, Xiaocui; Ju, Weimin; Zhou, Yanlian

2015-01-01

The reliable simulation of gross primary productivity (GPP) at various spatial and temporal scales is of significance to quantifying the net exchange of carbon between terrestrial ecosystems and the atmosphere. This study aimed to verify the ability of a nonlinear two-leaf model (TL-LUEn), a linear...... two-leaf model (TL-LUE), and a big-leaf light use efficiency model (MOD17) to simulate GPP at half-hourly, daily and 8-day scales using GPP derived from 58 eddy-covariance flux sites in Asia, Europe and North America as benchmarks. Model evaluation showed that the overall performance of TL...

Deriving a light use efficiency estimation algorithm using in situ hyperspectral and eddy covariance measurements for a maize canopy in Northeast China.

Science.gov (United States)

Zhang, Feng; Zhou, Guangsheng

2017-07-01

We estimated the light use efficiency ( LUE ) via vegetation canopy chlorophyll content ( CCC canopy ) based on in situ measurements of spectral reflectance, biophysical characteristics, ecosystem CO 2 fluxes and micrometeorological factors over a maize canopy in Northeast China. The results showed that among the common chlorophyll-related vegetation indices (VIs), CCC canopy had the most obviously exponential relationships with the red edge position (REP) ( R 2  = .97, p  <   .001) and normalized difference vegetation index (NDVI) ( R 2  = .91, p  <   .001). In a comparison of the indicating performances of NDVI, ratio vegetation index (RVI), wide dynamic range vegetation index (WDRVI), and 2-band enhanced vegetation index (EVI2) when estimating CCC canopy using all of the possible combinations of two separate wavelengths in the range 400-1300 nm, EVI2 [1214, 1259] and EVI2 [726, 1248] were better indicators, with R 2 values of .92 and .90 ( p  <   .001). Remotely monitoring LUE through estimating CCC canopy derived from field spectrometry data provided accurate prediction of midday gross primary productivity ( GPP ) in a rainfed maize agro-ecosystem ( R 2  = .95, p  <   .001). This study provides a new paradigm for monitoring vegetation GPP based on the combination of LUE models with plant physiological properties.

Evaluating the relationship between the photochemical reflectance index and the light use efficiency in a mangrove forest with Spartina alterniflora invasion

Science.gov (United States)

Shi, C.; Wang, L.; Yang, S.

2017-12-01

Mangrove forest is an important component of wetland ecosystems, which has high productivity, strong carbon sequestration capacity and great ecological values. The light use efficiency (LUE) of photosynthesis is a major parameter for estimating plant productivity. Recent studies have shown that the photochemical reflectance index (PRI) has a strong relationship with LUE and the relationship is significantly influenced by plant species and environmental factors. In this paper, we evaluated the relationship between PRI and LUE for different mangrove species (Avicennia marina and Aegiceras corniculatum) and the effects of Spartina alterniflora invasion on the PRI-LUE relationship. The results showed that the LUE of mangroves had a good correlation with PRI, and the correlation of Avicennia marina was stronger than that of Aegiceras corniculatum. In addition, the invasion of Spartina alterniflora impaired the PRI-LUE relationship for both mangrove species.

Photosynthetic Efficiency of Northern Forest Ecosystems Using a MODIS-Derived Photochemical Reflectance Index (PRI)

Science.gov (United States)

Middleton, E. M.; Huemmrich, K. F.; Landis, D. R.; Black, T. A.; Barr, A. G.; McCaughey, J. H.

2016-01-01

.003 moles per moles of carbon absorbed quanta). Nadir (VZA, 0 degrees plus or minus 15 degrees) and backscatter views (VZA, -16 degrees to -45 degrees) had lower performance in estimating LUE (nadir: r squared approximately equal to 0.62-0.67; backscatter: r squared approximately equal to 0.54-0.59) and similar estimation error (RMSE equals 0.004-0.005).When directional effects were not considered, only a moderately successful MODIS-PRI vs. LUE relationship (r squared equals 0.34, RMSE equals 0.007) was obtained in the full dataset (all views & sites, both satellites), but site-specific relationships were able to discriminate between coniferous and deciduous forests. Overall, MODIS-PRI values from Terra (late morning) were higher than those from Aqua (early afternoon), before/after the onset of diurnal stress responses expressed spectrally. Therefore, we identified ninety-two Terra-Aqua "same day" pairs, for which the sum of Terra morning and Aqua afternoon MODIS-PRI values (PRI (sub sum) using all available directional observations was linearly correlated with daily tower LUE (r squared equals 0.622, RMSE equals 0.013) and independent of site differences or meteorological information. Our study highlights the value of off-nadir directional reflectance observations, and the value of pairing morning and afternoon satellite observations to monitor stress responses that inhibit carbon uptake in Canadian forest ecosystems. In addition, we show that MODIS-PRI values, when derived from either: (i) forward views only, or (ii) Terra/Aqua same day (any view) combined observations, provided more accurate estimates of tower-measured daily LUE than those derived from either nadir or backscatter views or those calculated by the widely used semi-operational MODIS GPP model (MOD17) which is based on a theoretical maximum LUE and environmental data. Consequently, we demonstrate the importance of diurnal as well as off-nadir satellite observations for detecting vegetation physiological

Quantifying soil moisture impacts on light use efficiency across biomes.

Science.gov (United States)

Stocker, Benjamin D; Zscheischler, Jakob; Keenan, Trevor F; Prentice, I Colin; Peñuelas, Josep; Seneviratne, Sonia I

2018-06-01

Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Dynamics of spectral bio-indicators and their correlations with light use efficiency using directional observations at a Douglas-fir forest

Science.gov (United States)

Cheng, Yen-Ben; Middleton, Elizabeth M.; Hilker, Thomas; Coops, Nicholas C.; Black, T. Andrew; Krishnan, Praveena

2009-09-01

The carbon science community must rely on satellite remote sensing to obtain global estimates of photosynthetic activity, typically expressed as net primary production (NPP), gross primary production (GPP) or light use efficiency (LUE). The photochemical reflectance index (PRI), calculated as a normalized difference reflectance index using a physiologically active green band (~531 nm) and another physiologically insensitive green reference band (~570 nm), denoted as PRI(570), has been confirmed in many studies as being strongly related to LUE. Here, we examined the potential of utilizing PRI(570) observations under different illumination conditions for canopy LUE estimation of a forest. In order to evaluate this, directional hyperspectral reflectance measurements were collected continuously throughout the daytime periods using an automated spectroradiometer in conjunction with tower-based eddy covariance fluxes and environmental measurements at a coastal conifer forest in British Columbia, Canada throughout the 2006 growing season. A parameter calculated as the PRI(570) difference (dPRI(570)) between shaded versus sunlit canopy foliage sectors showed a strong correlation to tower-based LUE. The seasonal pattern for this correlation produced a dramatic change from high negative (r ~ -0.80) values in the springtime and early fall to high positive values (r ~ 0.80) during the summer months, which could represent the seasonality of physiological characteristics and environmental factors. Although the PRI(570) successfully tracked canopy LUE, one or both of its green bands (~531 and 570 nm) used to calculate the PRI are unavailable on most existing and planned near-term satellites. Therefore, we examined the potential to use 24 other spectral indexes for LUE monitoring that might be correlated to PRI, and thereby a substitute for it. We also continued our previous investigations into the influence of illumination conditions on the observed PRI(570) and other indexes

Dynamics of spectral bio-indicators and their correlations with light use efficiency using directional observations at a Douglas-fir forest

International Nuclear Information System (INIS)

Cheng, Yen-Ben; Middleton, Elizabeth M; Hilker, Thomas; Coops, Nicholas C; Black, T Andrew; Krishnan, Praveena

2009-01-01

The carbon science community must rely on satellite remote sensing to obtain global estimates of photosynthetic activity, typically expressed as net primary production (NPP), gross primary production (GPP) or light use efficiency (LUE). The photochemical reflectance index (PRI), calculated as a normalized difference reflectance index using a physiologically active green band (∼531 nm) and another physiologically insensitive green reference band (∼570 nm), denoted as PRI(570), has been confirmed in many studies as being strongly related to LUE. Here, we examined the potential of utilizing PRI(570) observations under different illumination conditions for canopy LUE estimation of a forest. In order to evaluate this, directional hyperspectral reflectance measurements were collected continuously throughout the daytime periods using an automated spectroradiometer in conjunction with tower-based eddy covariance fluxes and environmental measurements at a coastal conifer forest in British Columbia, Canada throughout the 2006 growing season. A parameter calculated as the PRI(570) difference (dPRI(570)) between shaded versus sunlit canopy foliage sectors showed a strong correlation to tower-based LUE. The seasonal pattern for this correlation produced a dramatic change from high negative (r ∼ −0.80) values in the springtime and early fall to high positive values (r ∼ 0.80) during the summer months, which could represent the seasonality of physiological characteristics and environmental factors. Although the PRI(570) successfully tracked canopy LUE, one or both of its green bands (∼531 and 570 nm) used to calculate the PRI are unavailable on most existing and planned near-term satellites. Therefore, we examined the potential to use 24 other spectral indexes for LUE monitoring that might be correlated to PRI, and thereby a substitute for it. We also continued our previous investigations into the influence of illumination conditions on the observed PRI(570) and other

Intrinsic climate dependency of ecosystem light and water-use-efficiencies across Australian biomes

International Nuclear Information System (INIS)

Shi, Hao; Li, Longhui; Eamus, Derek; Cleverly, James; Huete, Alfredo; Yu, Qiang; Beringer, Jason; Van Gorsel, Eva; Hutley, Lindsay

2014-01-01

The sensitivity of ecosystem gross primary production (GPP) to availability of water and photosynthetically active radiation (PAR) differs among biomes. Here we investigated variations of ecosystem light-use-efficiency (eLUE: GPP/PAR) and water-use-efficiency (eWUE: GPP/evapotranspiration) among seven Australian eddy covariance sites with differing annual precipitation, species composition and temperature. Changes to both eLUE and eWUE were primarily correlated with atmospheric vapor pressure deficit (VPD) at multiple temporal scales across biomes, with minor additional correlations observed with soil moisture and temperature. The effects of leaf area index on eLUE and eWUE were also relatively weak compared to VPD, indicating an intrinsic dependency of eLUE and eWUE on climate. Additionally, eLUE and eWUE were statistically different for biomes between summer and winter, except eWUE for savannas and the grassland. These findings will improve our understanding of how light- and water-use traits in Australian ecosystems may respond to climate change. (letter)

Variability in Light Use Efficiency With Changes in Vegetation Structure and Understory, Using a Temporally Changing Flux Footprint at the BERMS Old Jack Pine Site

Science.gov (United States)

Chasmer, L.; Barr, A.; Black, A.; Hopkinson, C.; Kljun, N.; McCaughey, H.; Treitz, P.; Shashkov, A.; Zha, T.

2006-12-01

Satellite remote sensing algorithms of vegetation gross primary productivity (GPP) often include a light use efficiency (LUE) term that varies depending on meteorological constraints and biome type. LUE is defined as the carbon fixed per mole of photosynthetically active radiation (PAR) absorbed by the canopy (APAR). LUE estimated using GPP from eddy covariance data is complex and changes over short time periods as the available resources (soil moisture, light, temperature, and nitrogen) vary. An understanding of the variability in LUE will improve local to regional estimates of GPP within complex vegetated land cover types using the variety of remote sensing technologies now available. This study examines variability in LUE and GPP at a mature jack pine site within the Fluxnet-Canada BERMS (Boreal Ecosystem Research and Monitoring Sites) study area using a flux footprint model (Kljun et al. 2004) and airborne lidar data (e.g. Chasmer et al. 2006). Three separate weeks of high frequency eddy covariance data are analyzed for June, July, and August 2002 to capture changes in photosynthesis and carbon uptake through the growing season with variations in precipitation and soil moisture. Footprint estimates are derived in half-hourly resolution to provide information on the spatial and temporal variation of the sources of measured C-fluxes. Airborne lidar directly samples ground topography and vegetation structure (i.e., canopy and understory height, gaps between trees, base of canopy), and may provide information on soil moisture and drainage at the ground surface via absorbed and reflected laser pulse energy. Two questions will be addressed specific to net ecosystem productivity (NEP) of the site as a whole, including parts of the ecosystem that may not be properly represented using eddy covariance techniques. These are: 1. How does C uptake and respiration spatially and temporally vary across the jack pine site? 2. How do vegetation characteristics vary with

Increased light-use efficiency in northern terrestrial ecosystems indicated by CO ₂ and greening observations: INCREASE IN NH LIGHT USE EFFICIENCY

Energy Technology Data Exchange (ETDEWEB)

Thomas, Rebecca T. [Science and Solutions for a Changing Planet DTP, Imperial College London, London UK; AXA Chair Programme in Biosphere and Climate Impacts, Department of Life Sciences, Imperial College London, London UK; Department of Physics, Imperial College London, London UK; Prentice, Iain Colin [AXA Chair Programme in Biosphere and Climate Impacts, Department of Life Sciences, Imperial College London, London UK; Grantham Institute: Climate Change and the Environment, Imperial College London, London UK; Graven, Heather [Department of Physics, Imperial College London, London UK; Grantham Institute: Climate Change and the Environment, Imperial College London, London UK; Ciais, Philippe [Laboratoire des Sciences du Climat et de l' Environnement, Saint-Aubin France; Fisher, Joshua B. [Jet Propulsion Laboratory, California Institute of Technology, Pasadena California USA; Hayes, Daniel J. [School of Forest Resources, University of Maine, Orono Maine USA; Huang, Maoyi [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland Washington USA; Huntzinger, Deborah N. [School of Earth Sciences and Environmental Sustainability, Northern Arizona University, Flagstaff Arizona USA; Ito, Akihiko [Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba Japan; Jain, Atul [Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana Illinois USA; Mao, Jiafu [Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge Tennessee USA; Michalak, Anna M. [Department of Global Ecology, Carnegie Institution for Science, Stanford California USA; Peng, Shushi [Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing China; Poulter, Benjamin [Department of Ecology, Montana State University, Bozeman Montana USA; Ricciuto, Daniel M. [Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge Tennessee USA; Shi, Xiaoying [Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge Tennessee USA; Schwalm, Christopher [Woods Hole Research Center, Falmouth Massachusetts USA; Tian, Hanqin [International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn Alabama USA; Zeng, Ning [Department of Atmospheric and Oceanic Science and Earth System Science Interdisciplinary Center, University of Maryland, College Park Maryland USA

2016-11-04

Observations show an increasing amplitude in the seasonal cycle of CO2 (ASC) north of 45°N of 56 ± 9.8% over the last 50 years and an increase in vegetation greenness of 7.5–15% in high northern latitudes since the 1980s. However, the causes of these changes remain uncertain. Historical simulations from terrestrial biosphere models in the Multiscale Synthesis and Terrestrial Model Intercomparison Project are compared to the ASC and greenness observations, using the TM3 atmospheric transport model to translate surface fluxes into CO2 concentrations. We find that the modeled change in ASC is too small but the mean greening trend is generally captured. Modeled increases in greenness are primarily driven by warming, whereas ASC changes are primarily driven by increasing CO2. We suggest that increases in ecosystem-scale light use efficiency (LUE) have contributed to the observed ASC increase but are underestimated by current models. We highlight potential mechanisms that could increase modeled LUE.

Estimating photosynthesis with high resolution field spectroscopy in a Mediterranean grassland under different nutrient availability

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Perez-Priego, O.; Guan, J.; Fava, F.; Rossini, M.; Wutzler, T.; Moreno, G.; Carrara, A.; Kolle, O.; Schrumpf, M.; Reichstein, M.; Migliavacca, M.

2014-12-01

Recent studies have shown how human induced N:P imbalances are affecting essential processes (e.g. photosynthesis, plant growth rate) that lead to important changes in ecosystem structure and function. In this regard, the accuracy of the approaches based on remotely-sensed data for monitoring and modeling gross primary production (GPP) relies on the ability of vegetation indices (VIs) to track the dynamics of vegetation physiological and biophysical properties/variables. Promising results have been recently obtained when Chlorophyll-sensitive VIs and Chlorophyll fluorescence are combined with structural indices in the framework of the Monteith's light use efficiency (LUE) model. However, further ground-based experiments are required to validate LUE model performances, and their capability to be generalized under different nutrient availability conditions. In this study, the overall objective was to investigate the sensitivity of VIs to track short- and long-term GPP variations in a Mediterranean grassland under different N and P fertilization treatments. Spectral VIs were acquired manually using high resolution spectrometers (HR4000, OceanOptics, USA) along a phenological cycle. The VIs examined included photochemical reflectance index (PRI), MERIS terrestrial-chlorophyll index (MTCI) and normalized difference vegetation index (NDVI). Solar-induced chlorophyll fluorescence calculated at the oxygen absorption band O2-A (F760) using spectral fitting methods was also used. Simultaneously, measurements of GPP and environmental variables were conducted using a transient-state canopy chamber. Overall, GPP, F760 and VIs showed a clear seasonal time-trend in all treatments, which was driven by the phenological development of the grassland. Results showed significant differences (p<0.05) in midday GPP values between N and without N addition plots, in particular at the peak of the growing season during the flowering stage and at the end of the season during senescence. While

Monitoring phenology of photosynthesis in temperate evergreen and mixed deciduous forests using the normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI) at leaf and canopy scales

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Wong, C. Y.; Arain, M. A.; Ensminger, I.

2016-12-01

Evergreen conifers in boreal and temperate regions undergo strong seasonal changes in photoperiod and temperatures, which determines their phenology of high photosynthetic activity in the growing season and downregulation during the winter. Monitoring the timing of the transition between summer activity and winter downregulation in evergreens is difficult since this is a largely invisible process, unlike in deciduous trees that have a visible budding and a sequence of leaf unfolding in the spring and leaf abscission in the fall. The light-use efficiency (LUE) model estimates gross primary productivity (GPP) and may be parameterized using remotely sensed vegetation indices. Using spectral reflectance data, we derived the normalized difference vegetation index (NDVI), a measure of leaf "greenness", and the photochemical reflectance index (PRI), a proxy for chlorophyll:carotenoid ratios which is related to photosynthetic activity. To better understand the relationship between these vegetation indices and photosynthetic activity and to contrast this relationship between plant functional types, the phenology of NDVI, PRI and photosynthesis was monitored in an evergreen forest and a mixed deciduous forest at the leaf and canopy scale. Our data indicates that the LUE model can be parameterized by NDVI and PRI to track forest phenology. Differences in the sensitivity of PRI and NDVI will be discussed. These findings have implications to address the phenology of evergreen conifers by using PRI to complement NDVI in the LUE model, potentially improving model productivity estimates in northern hemisphere forests, that are dominated by conifers.

Ecosystem carbon and radiative fluxes: a global synthesis based on the FLUXNET network.

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Cescatti, A.

2009-04-01

Solar radiation is the most important environmental factor driving the temporal and spatial variability of the gross primary productivity (GPP) in terrestrial ecosystems. At the ecosystem scale, the light use efficiency (LUE) depends not only on radiation quantity but also on radiation "quality" both in terms of spectral composition and angular distribution. The day-to-day variations in LUE are largely determined by changes in the ratio of diffuse to total radiation. The relative importance of the concurrent variation in total incoming radiation and in LUE is essential to estimate the sign and the magnitude of the GPP sensitivity to radiation. Despite the scientific relevance of this issue, a global assessment on the sensitivity of GPP to the variations of Phar is still missing. Such an analysis is needed to improve our understanding of the current and future impacts of aerosols and cloud cover on the spatio-temporal variability of GPP. The current availability of ecosystem carbon fluxes, together with separate measurements of incoming direct and diffuse Phar at a large number of flux sites, offers the unique opportunity to extend the previous investigation, both in terms of ecosystem, spatial and climate coverage, and to address questions about the internal (e.g. leaf area index, canopy structure) and external (e.g. cloudiness, covarying meteorology) factors affecting the ecosystem sensitivity to radiation geometry. For this purpose half-hourly measurements of carbon fluxes and radiation have been analyzed at about 220 flux sites for a total of about 660 site-years. This analysis demonstrates that the sensitivity of GPP to incoming radiation varies across the different plant functional types and is correlated with the leaf area index and the local climatology. In particular, the sensitivity of GPP to changes in incoming diffuse light maximizes for the broadleaved forests of the Northern Hemisphere.

Photoperiod and temperature constraints on the relationship between the photochemical reflectance index and the light use efficiency of photosynthesis in Pinus strobus.

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Fréchette, Emmanuelle; Chang, Christine Yao-Yun; Ensminger, Ingo

2016-03-01

The photochemical reflectance index (PRI) is a proxy for the activity of the photoprotective xanthophyll cycle and photosynthetic light use efficiency (LUE) in plants. Evergreen conifers downregulate photosynthesis in autumn in response to low temperature and shorter photoperiod, and the dynamic xanthophyll cycle-mediated non-photochemical quenching (NPQ) is replaced by sustained NPQ. We hypothesized that this shift in xanthophyll cycle-dependent energy partitioning during the autumn is the cause for variations in the PRI-LUE relationship. In order to test our hypothesis, we characterized energy partitioning and pigment composition during a simulated summer-autumn transition in a conifer and assessed the effects of temperature and photoperiod on the PRI-LUE relationship. We measured gas exchange, chlorophyll fluorescence and leaf reflectance during the photosynthetic downregulation in Pinus strobus L. seedlings exposed to low temperature/short photoperiod or elevated temperature/short photoperiod conditions. Shifts in energy partitioning during simulated autumn were observed when the pools of chlorophylls decreased and pools of photoprotective carotenoids increased. On a seasonal timescale, PRI was controlled by carotenoid pool sizes rather than xanthophyll cycle dynamics. Photochemical reflectance index variation under cold autumn conditions mainly reflected long-term pigment pool adjustments associated with sustained NPQ, which impaired the PRI-LUE relationship. Exposure to warm autumn conditions prevented the induction of sustained NPQ but still impaired the PRI-LUE relationship. We therefore conclude that alternative zeaxanthin-independent NPQ mechanisms, which remain undetected by the PRI, are present under both cold and warm autumn conditions, contributing to the discrepancy in the PRI-LUE relationship during autumn. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Monitoring Grassland Seasonal Carbon Dynamics, by Integrating MODIS NDVI, Proximal Optical Sampling, and Eddy Covariance Measurements

Czech Academy of Sciences Publication Activity Database

Nestola, E.; Calfapietra, Carlo; Emmerton, C. A.; Wrong, Ch. Y. S.; Thayer, D. R.; Gamon, J. A.

2016-01-01

Roč. 8, č. 3 (2016), č. článku 260. ISSN 2072-4292 Institutional support: RVO:67179843 Keywords : grassland * NDVI * CO2 flux * optical remote sensing * LUE model * gap filling Subject RIV: EH - Ecology, Behaviour Impact factor: 3.244, year: 2016

Response of gross ecosystem productivity, light use efficiency, and water use efficiency of Mongolian steppe to seasonal variations in soil moisture

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Li, Sheng-Gong; Eugster, Werner; Asanuma, Jun; Kotani, Ayumi; Davaa, Gombo; Oyunbaatar, Dambaravjaa; Sugita, Michiaki

2008-03-01

The examination of vegetation productivity and use of light and water resources is important for understanding the carbon and water cycles in semiarid and arid environments. We made continuous measurements of carbon dioxide and water vapor fluxes over an arid steppe ecosystem in Mongolia by using the eddy covariance (EC) technique. These measurements allow an examination of EC-estimated gross ecosystem productivity (GEP), light use efficiency (LUE), and water use efficiency (WUE) of the steppe. Daily variations of GEP, LUE, and WUE were associated with daily variations of incident photosynthetically active radiation (PAR), ambient temperature (Ta), and vapor pressure deficit (VPD). The magnitudes of these variations were also dependent on canopy development. On the daily basis, GEP linearly correlated with evapotranspiration rate and PAR. LUE correlated positively with leaf area index, Ta, and soil moisture availability but negatively with the surface reflectivity for short-wave solar radiation. Throughout the growing season, both GEP and LUE responded strongly to precipitation-fed soil moisture in the top 20 cm of the soil. An examination of the responses of LUE and WUE to PAR under different soil moisture conditions shows that when soil water availability exceeded VPD, the steppe was most efficient in light use, whereas it was less efficient in water use. The multivariate analysis of variance also suggests that soil moisture availability, especially water status in the upper 20-cm soil layer with dense distribution of grass roots, is the most significant factor that governs GEP, WUE, and LUE. This study provides a preliminary assessment of the use of available water and light by the Mongolian arid steppe ecosystems under seasonally varying soil moisture conditions. A better understanding of these functional responses is required to predict how climate change may affect arid steppe ecosystems.

Monitoring Forage Production of California Rangeland Using Remote Sensing Observations

Science.gov (United States)

Liu, H.; Jin, Y.; Dahlgren, R. A.; O'Geen, A. T.; Roche, L. M.; Smith, A. M.; Flavell, D.

2016-12-01

Pastures and rangeland cover more than 10 million hectares in California's coastal and inland foothill regions, providing feeds to livestock and important ecosystem services. Forage production in California has a large year-to-year variation due to large inter-annual and seasonal variabilities in precipitation and temperature. It also varies spatially due to the variability in climate and soils. Our goal is to develop a robust and cost-effective tool to map the near-real-time and historical forage productivity in California using remote sensing observations from Landsat and MODIS satellites. We used a Monteith's eco-physiological plant growth theory: the aboveground net primary production (ANPP) is determined by (i) the absorbed photosynthetically active radiation (APAR) and the (ii) light use efficiency (LUE): ANPP = APAR * LUEmax * f(T) * f(SM), where LUEmax is the maximum LUE, and f(T) and f(SM) are the temperature and soil moisture constrains on LUE. APAR was estimated with Landsat and MODIS vegetation index (VI), and LUE was calibrated with a statewide point dataset of peak forage production measurements at 75 annual rangeland sites. A non-linear optimization was performed to derive maximum LUE and the parameters for temperature and soil moisture regulation on LUE by minimizing the differences between the estimated and measured ANPP. Our results showed the satellite-derived annual forage production estimates correlated well withcontemporaneous in-situ forage measurements and captured both the spatial and temporal productivity patterns of forage productivity well. This remote sensing algorithm can be further improved as new field measurements become available. This tool will have a great importance in maintaining a sustainable range industry by providing key knowledge for ranchers and the stakeholders to make managerial decisions.

GPP estimates in a biodiesel crop using MERIS products

Science.gov (United States)

Sánchez, M. L.; Pardo, N.; Pérez, I.; García, M. A.; Paredes, V.

2012-04-01

Greenhouse gas emissions in Spain in 2008-2009 were 34.3 % higher than the base-year level, significantly above the burden-sharing target of 15 % for the period 2008-2012. Based on this result, our country will need to make a major effort to meet the committed target on time using domestic measures as well as others foreseen in the Kyoto Protocol, such as LULUFC activities. In this framework, agrofuels, in other words biofuels produced by crops that contain high amounts of vegetable oil such as sorghum, sunflower, rape seed and jatropha, appear to be an interesting mitigation alternative. Bearing in mind the meteorological conditions in Spain, sunflower and rape seed in particular are considered the most viable crops. Sunflower cultivated surface in Spain has remained fairly constant in recent years, in contrast to rapeseed crop surface which, although still scarce, has followed an increasing trend. In order to assess rape seed ability as a CO2 sink as well as to describe GPP dynamic evolution, we installed an eddy correlation station in an agricultural plot of the Spanish plateau. Measurements at the plot consisted of 30-min NEE flux measurements (using a LI-7500 and a METEK USA-1 sonic anemometer) as well as other common meteorological variables. Measurements were performed from March to October. This paper presents the results of the GPP 8-d estimated values using a Light Use Efficiency Model, LUE. Input data for the LUE model were the FPAR 8-d products supplied by MERIS, the PAR in situ measurements, and a scalar f varying, between 0 and 1, to take into account the reduction of the maximum PAR conversion efficiency, ɛ0, under limiting environmental conditions. The f values were assumed to be dependent on air temperature and the evaporative fraction, EF, which was considered as a proxy of soil moisture. ɛ0, a key parameter, which depends on biome types, was derived through the results of a linear regression fit between the GPP 8-d eddy covariance composites

Remote sensing of photosynthetic-light-use efficiency of a Siberian boreal forest

International Nuclear Information System (INIS)

Nichol, C.J.; Grace, J.; Shibistova, O.; Matsubara, S.

2002-01-01

The relationship between a physiological index called the photochemical reflectance index (PRI) and photosynthetic light-use-efficiency (LUE) of a Siberian boreal forest during the winter-spring transition, or green-up period, was investigated in 2000. During this time the photosynthetic apparatus was considered under stress as a result of extremes of temperature (from -20 to 35 deg C) coupled with a high radiation load. Reflectance measurements of four stands were made from a helicopter-mounted spectro radiometer and PRI was calculated from these data. Eddy covariance towers were operating at the four stands and offered a means to calculate LUE. A significant linear relationship was apparent between PRI, calculated from the helicopter spectral data, and LUE, calculated from the eddy covariance data, for the four sites sampled. Reflectance measurements were also made of a Scots pine stand from the eddy covariance tower. Needles were also sampled during the time of spectral data acquisition for xanthophyll pigment determination. Strong linear relationships were observed among PRI, the epoxidation state of the xanthophyll cycle (EPS) and LUE over the green-up period and the diurnal cycle at the canopy scale

The Global Drivers of Photosynthesis and Light Use Efficiency Seasonality: A Granger Frequency Causality Analysis

Science.gov (United States)

Nemani, Ramakrishna R.

2016-01-01

Photosynthesis and light use efficiency (LUE) are major factors in the evolution of the continental carbon cycle due to their contribution to gross primary production (GPP). However, while the drivers of photosynthesis and LUE on a plant or canopy scale can often be identified, significant uncertainties exist when modeling these on a global scale. This is due to sparse observations in regions such as the tropics and the lack of a direct global observation dataset. Although others have attempted to address this issue using correlations (Beer, 2010) or calculating GPP from vegetation indices (Running, 2004), in this study we take a new approach. We combine the statistical method of Granger frequency causality and partial Granger frequency causality with remote sensing data products (including sun-induced fluorescence used as a proxy for GPP) to determine the main environmental drivers of GPP across the globe.

Large and Small Scale Nitrogen and Phosporous Manipulation Experiment in a Tree-Grass Ecosystem: first year of results

Science.gov (United States)

Migliavacca, Mirco; Perez Priego, Oscar; El-Madany, Tarek; Guan, JinHong; Carrara, Arnaud; Fava, Francesco; Moreno, Gerardo; Kolle, Olaf; Rossini, Micol; Schrumpf, Marion; Julitta, Tommaso; Reichstein, Markus

2015-04-01

-induced chlorophyll fluorescence calculated at the oxygen absorption band O2-A (F760) using spectral fitting methods was also used. The results showed significant differences (pLight Use Efficiency (LUE) modelling approaches were applied and the results indicated that the use of LUE models based on VIs related to physiology and fluorescence are key to account for nutrient availability in LUE models and to better predict GPP.

Chaos synchronization in autonomous chaotic system via hybrid feedback control

International Nuclear Information System (INIS)

Yang Lixin; Chu Yandong; Zhang Jiangang; Li Xianfeng; Chang Yingxiang

2009-01-01

This paper presents the synchronization of chaos by designing united controller. First, this method is implemented in synchronization of a simple system, then we realize the synchronization of Lue hyperchaotic system, we also take tracking control to realize the synchronization of Lue hyperchaotic system. Comparing with results, we can find that hybrid feedback control approach is more effective than tracking control for hyperchaotic system. Numerical simulations show the united synchronization method works well.

NEE and GPP dynamic evolution at two biomes in the upper Spanish plateau

Science.gov (United States)

Sánchez, María Luisa; Pardo, Nuria; Pérez, Isidro Alberto; García, Maria de los Angeles

2014-05-01

In order to assess the ability of dominant biomes to act as a CO2 sink, two eddy correlation stations close to each other in central Spain have been concurrently operational since March 2008 until the present. The land use of the first station, AC, is a rapeseed rotating crop consisting of annual rotation of non-irrigated rapeseed, barley, peas, rye, and sunflower, respectively. The land use of the second, CIBA, is a mixture of open shrubs/crops, with open shrubs being markedly dominant. The period of measurements covered variable general meteorological conditions. 2009 and 2012 were dominated by drought, whereas 2010 was the rainiest year. Annual rainfall during 2008 and 2009 was close to the historical averaged annual means. This paper presents the dynamic evolution of NEE-8d and GPP-8d observed at the AC station over five years and compares the results with those concurrently observed at the CIBA station. GGP 8-d estimates at both stations were determined using a Light Use Efficiency Model, LUE. Input data for the LUE model were the FPAR 8-d products supplied by MODIS, PAR in situ measurements, and a scalar f, varying between 0 and 1, to take account of the reduction in maximum PAR conversion efficiency, ɛ0, under limiting environmental conditions. f values were assumed to be dependent on air temperature and evaporative fraction, EF, which was considered a proxy of soil moisture. ɛ0, a key parameter, which depends on land use types, was derived through the results of a linear regression fit between the GPP 8-d eddy covariance composites observed and the LUE concurrent 8-d model estimates. Over the five-year study period, both biomes behaved as CO2 sinks. However, the ratio of the NEE-8d total accumulated at AC and CIBA, respectively, was close to a factor two, revealing the effectiveness of the studied crops as CO2 sinks. On an annual basis, accumulated NEE-8d exhibited major variability in both biomes. At CIBA, the results were largely dominated by the

Unifying Model-Based and Reactive Programming within a Model-Based Executive

Science.gov (United States)

Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)

1999-01-01

Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.

Evaluating the potential of large-scale simulations to predict carbon fluxes of terrestrial ecosystems over a European Eddy Covariance network

International Nuclear Information System (INIS)

Balzarolo, M.; Boussetta, S.; Balsamo, G.; Beljaars, A.; Maignan, F.; Chevallier, F.; Poulter, B.

2014-01-01

This paper reports a comparison between large scale simulations of three different land surface models (LSMs), ORCHIDEE, ISBA-A-gs and CTESSEL, forced with the same meteorological data, and compared with the carbon fluxes measured at 32 eddy covariance (EC) flux tower sites in Europe. The results show that the three simulations have the best performance for forest sites and the poorest performance for cropland and grassland sites. In addition, the three simulations have difficulties capturing the seasonality of Mediterranean and sub-tropical biomes, characterized by dry summers. This reduced simulation performance is also reflected in deficiencies in diagnosed light-use efficiency (LUE) and vapour pressure deficit (VPD) dependencies compared to observations. Shortcomings in the forcing data may also play a role. These results indicate that more research is needed on the LUE and VPD functions for Mediterranean and sub-tropical biomes. Finally, this study highlights the importance of correctly representing phenology (i.e. leaf area evolution) and management (i.e. rotation-irrigation for cropland, and grazing-harvesting for grassland) to simulate the carbon dynamics of European ecosystems and the importance of ecosystem-level observations in model development and validation. (authors)

Evaluation of optical remote sensing parameters to improve modeling of gross primary productivity in a heterogeneous agricultural area

Science.gov (United States)

Schickling, A.; Damm, A.; Schween, J.; Rascher, U.; Crewell, S.; Wahner, A.

2011-12-01

Terrestrial photosynthesis greatly determines plant mediated exchange processes in the vegetation atmosphere system and substantially influences patterns in atmospheric carbon dioxide (CO2) concentrations and water vapor. Therefore, an accurate quantification of photosynthetic CO2 uptake, commonly referred to as gross primary productivity (GPP), is a key parameter to distinguish those atmospheric patterns on various spatio-temporal scales. Remote sensing (RS) offers the unique possibility to determine GPP at different spatial scales ranging from the local to the global scale. Attempts to estimate GPP from RS data focus on the light use efficiency (LUE) concept of Monteith which relates GPP to the absorbed photosynthetically active radiation and the efficiency of plant canopies to utilize the absorbed radiation for photosynthesis. To reliably predict GPP on different spatio-temporal scales LUE has to be linked to optical RS parameters which detect changes in photosynthetic efficiency due to environmental conditions. In this study we evaluated two optical RS parameters, namely the sun-induced fluorescence (Fs) and the photochemical reflectance index (PRI), for their potential to serve as a proxy for LUE. The parameters were derived from two ASD FieldSpec spectrometers which were operated in parallel. During several days one instrument was installed on the ground above the vegetation canopy of either a winter wheat or a sugar beet field. The second instrument was operated from a small research aircraft continuously crossing the observation sites at low altitude (sugar beet fields during the day. Results of this spatio-temporal investigation revealed a significant variability of GPP between different winter wheat fields compared to the within-field variability. In addition to the significant between-field variability of sugar beet the results also showed an increase of the within-field variability in the afternoon. Moreover, for the first time it could be shown that

Comparison between different synchronization methods of identical chaotic systems

International Nuclear Information System (INIS)

Haeri, Mohammad; Khademian, Behzad

2006-01-01

This paper studies and compares three nonadaptive (bidirectional, unidirectional, and sliding mode) and two adaptive (active control and backstepping) synchronization methods on the synchronizing of four pairs of identical chaotic systems (Chua's circuit, Roessler system, Lorenz system, and Lue system). Results from computer simulations are presented in order to illustrate the effectiveness of the methods and to compare them based on different criteria

Sun-induced Chlorophyll fluorescence and PRI improve remote sensing GPP estimates under varying nutrient availability in a typical Mediterranean savanna ecosystem

Science.gov (United States)

Perez-Priego, O.; Guan, J.; Rossini, M.; Fava, F.; Wutzler, T.; Moreno, G.; Carvalhais, N.; Carrara, A.; Kolle, O.; Julitta, T.; Schrumpf, M.; Reichstein, M.; Migliavacca, M.

2015-07-01

This study investigates the performances of different optical indices to estimate gross primary production (GPP) of herbaceous stratum in a Mediterranean savanna with different Nitrogen (N) and Phosphorous (P) availability. Sun-induced chlorophyll Fluorescence yield computed at 760 nm (Fy760), scaled-photochemical reflectance index (sPRI), MERIS terrestrial-chlorophyll index (MTCI) and Normalized difference vegetation index (NDVI) were computed from near-surface field spectroscopy measurements collected using high spectral resolution spectrometers covering the visible near-infrared regions. GPP was measured using canopy-chambers on the same locations sampled by the spectrometers. We hypothesized that light-use efficiency (LUE) models driven by remote sensing quantities (RSM) can better track changes in GPP caused by nutrient supplies compared to those driven exclusively by meteorological data (MM). Particularly, we compared the performances of different RSM formulations - relying on the use of Fy760 or sPRI as proxy for LUE and NDVI or MTCI as fraction of absorbed photosynthetically active radiation (fAPAR) - with those of classical MM. Results showed significantly higher GPP in the N fertilized experimental plots during the growing period. These differences in GPP disappeared in the drying period when senescence effects masked out potential differences due to plant N content. Consequently, although MTCI was tightly related to plant N content (r2 = 0.86, p < 0.01), it was poorly related to GPP (r2 = 0.45, p < 0.05). On the contrary sPRI and Fy760 correlated well with GPP during the whole measurement period. Results revealed that the relationship between GPP and Fy760 is not unique across treatments but it is affected by N availability. Results from a cross validation analysis showed that MM (AICcv = 127, MEcv = 0.879) outperformed RSM (AICcv = 140, MEcv = 0.8737) when soil moisture was used to constrain the seasonal dynamic of LUE. However, residual analyses

Sun-induced chlorophyll fluorescence and photochemical reflectance index improve remote-sensing gross primary production estimates under varying nutrient availability in a typical Mediterranean savanna ecosystem

Science.gov (United States)

Perez-Priego, O.; Guan, J.; Rossini, M.; Fava, F.; Wutzler, T.; Moreno, G.; Carvalhais, N.; Carrara, A.; Kolle, O.; Julitta, T.; Schrumpf, M.; Reichstein, M.; Migliavacca, M.

2015-11-01

This study investigates the performances of different optical indices to estimate gross primary production (GPP) of herbaceous stratum in a Mediterranean savanna with different nitrogen (N) and phosphorous (P) availability. Sun-induced chlorophyll fluorescence yield computed at 760 nm (Fy760), scaled photochemical reflectance index (sPRI), MERIS terrestrial-chlorophyll index (MTCI) and normalized difference vegetation index (NDVI) were computed from near-surface field spectroscopy measurements collected using high spectral resolution spectrometers covering the visible near-infrared regions. GPP was measured using canopy chambers on the same locations sampled by the spectrometers. We tested whether light-use efficiency (LUE) models driven by remote-sensing quantities (RSMs) can better track changes in GPP caused by nutrient supplies compared to those driven exclusively by meteorological data (MM). Particularly, we compared the performances of different RSM formulations - relying on the use of Fy760 or sPRI as a proxy for LUE and NDVI or MTCI as a fraction of absorbed photosynthetically active radiation (fAPAR) - with those of classical MM. Results showed higher GPP in the N-fertilized experimental plots during the growing period. These differences in GPP disappeared in the drying period when senescence effects masked out potential differences due to plant N content. Consequently, although MTCI was closely related to the mean of plant N content across treatments (r2 = 0.86, p < 0.01), it was poorly related to GPP (r2 = 0.45, p < 0.05). On the contrary sPRI and Fy760 correlated well with GPP during the whole measurement period. Results revealed that the relationship between GPP and Fy760 is not unique across treatments, but it is affected by N availability. Results from a cross-validation analysis showed that MM (AICcv = 127, MEcv = 0.879) outperformed RSM (AICcv =140, MEcv = 0.8737) when soil moisture was used to constrain the seasonal dynamic of LUE. However

Comparison between different synchronization methods of identical chaotic systems

Energy Technology Data Exchange (ETDEWEB)

Haeri, Mohammad [Advanced Control System Laboratory, Electrical Engineering Department, Sharif University of Technology, Azadi Avenue, P.O. Box 11365-9363 Tehran (Iran, Islamic Republic of)]. E-mail: haeri@sina.sharif.edu; Khademian, Behzad [Advanced Control System Laboratory, Electrical Engineering Department, Sharif University of Technology, Azadi Avenue, P.O. Box 11365-9363 Tehran (Iran, Islamic Republic of)

2006-08-15

This paper studies and compares three nonadaptive (bidirectional, unidirectional, and sliding mode) and two adaptive (active control and backstepping) synchronization methods on the synchronizing of four pairs of identical chaotic systems (Chua's circuit, Roessler system, Lorenz system, and Lue system). Results from computer simulations are presented in order to illustrate the effectiveness of the methods and to compare them based on different criteria.

Event-Based Conceptual Modeling

DEFF Research Database (Denmark)

Bækgaard, Lars

The paper demonstrates that a wide variety of event-based modeling approaches are based on special cases of the same general event concept, and that the general event concept can be used to unify the otherwise unrelated fields of information modeling and process modeling. A set of event......-based modeling approaches are analyzed and the results are used to formulate a general event concept that can be used for unifying the seemingly unrelated event concepts. Events are characterized as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms...... of information structures. The general event concept can be used to guide systems analysis and design and to improve modeling approaches....

Rule-based decision making model

International Nuclear Information System (INIS)

Sirola, Miki

1998-01-01

A rule-based decision making model is designed in G2 environment. A theoretical and methodological frame for the model is composed and motivated. The rule-based decision making model is based on object-oriented modelling, knowledge engineering and decision theory. The idea of safety objective tree is utilized. Advanced rule-based methodologies are applied. A general decision making model 'decision element' is constructed. The strategy planning of the decision element is based on e.g. value theory and utility theory. A hypothetical process model is built to give input data for the decision element. The basic principle of the object model in decision making is division in tasks. Probability models are used in characterizing component availabilities. Bayes' theorem is used to recalculate the probability figures when new information is got. The model includes simple learning features to save the solution path. A decision analytic interpretation is given to the decision making process. (author)

Competition for light and light use efficiency for Acacia mangium and Eucalyptus grandis trees in mono-specific and mixed-species plantations in Brazil

Science.gov (United States)

Le Maire, G.; Nouvellon, Y.; Gonçalves, J.; Bouillet, J.; Laclau, J.

2010-12-01

Mixed plantations with N-fixing species might be an attractive option for limiting the use of fertilizer in highly productive Eucalyptus plantations. A randomized block design was set up in southern Brazil, including a replacement series and an additive series design, as well as a nitrogen fertilization treatment, and conducted during a full 6 years rotation. The gradient of competition between Eucalyptus and Acacia in this design resulted in very different conditions of growth of Acacia, from totally dominated up to dominant canopies. We used the MAESTRA model to estimate the amount of absorbed photosynthetically active radiation (APAR) at tree level. This model requires the description of the scene and distinct structural variables of the two species, and their evolution with time. The competition for light is analysed by comparing the inter-specific values of APAR during a period of 2 years at the end of the rotation. APAR is further compared to the measured increment in stem wood biomass of the tree, and their ratio is an estimation of the light use efficiency for stemwood production at tree-scale. Variability of these LUE are analysed in respect to the species, the size of the tree, and at plot scale (competition level). Stemwood production was 3400, 3900 and 2400 gDM/m2 while APAR was 1640, 2280 and 2900 MJ/y for the pure Eucalyptus, pure Acacia and 50/50 mixed plantation, respectively, for an average LAI of 3.7, 3.3 and 4.5, respectively. Individual LUE for stemwood was estimated at an average value of 1.72 and 1.41 gDM/MJ/tree for Eucalyptus and Acacia, respectively, and at 0.92 and 0.40 gDM/MJ/tree when they were planted in mixed 50/50 plantations. LUE was highly dependant on tree size for both species. At the plot scale, LUE for stemwood were 2.1 gDM/MJ and 1.75 for Eucalyptus and Acacias, respectively, and 0.85 for the mixed 50/50 plantation. These results suggest that the mixed 50/50 plantation, which absorbed a higher amount of light, produce less

Laser Induced Forced Motion and Stress Waves in Plates and Shells.

Science.gov (United States)

1981-08-01

the plate at the center, normal to the plate surface. The Laser used was a Holobeam model 630-QNd glass system. This Laser produces an output power (in...V o 0 0 I lue ceill I Ii 1)r1 i 11im and hot nchary\\ cond i t i ons S or tile i n it i aI I St ate toget her with ji(. 38c ) iiav he u ISed to

Introducing Model-Based System Engineering Transforming System Engineering through Model-Based Systems Engineering

Science.gov (United States)

2014-03-31

Web  Presentation...Software  .....................................................  20   Figure  6.  Published   Web  Page  from  Data  Collection...the  term  Model  Based  Engineering  (MBE),  Model  Driven  Engineering  ( MDE ),  or  Model-­‐Based  Systems  

Integration of Simulink Models with Component-based Software Models

DEFF Research Database (Denmark)

Marian, Nicolae

2008-01-01

Model based development aims to facilitate the development of embedded control systems by emphasizing the separation of the design level from the implementation level. Model based design involves the use of multiple models that represent different views of a system, having different semantics...... of abstract system descriptions. Usually, in mechatronics systems, design proceeds by iterating model construction, model analysis, and model transformation. Constructing a MATLAB/Simulink model, a plant and controller behavior is simulated using graphical blocks to represent mathematical and logical...... constraints. COMDES (Component-based Design of Software for Distributed Embedded Systems) is such a component-based system framework developed by the software engineering group of Mads Clausen Institute for Product Innovation (MCI), University of Southern Denmark. Once specified, the software model has...

Model-free and model-based reward prediction errors in EEG.

Science.gov (United States)

Sambrook, Thomas D; Hardwick, Ben; Wills, Andy J; Goslin, Jeremy

2018-05-24

Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain. Copyright © 2018 Elsevier Inc. All rights reserved.

Interpreting Carbon Fluxes from a Spatially Heterogeneous Peatland with Thawing Permafrost: Scaling from Plant Community Scale to Ecosystem Scale

Science.gov (United States)

Harder, S. R.; Roulet, N. T.; Strachan, I. B.; Crill, P. M.; Persson, A.; Pelletier, L.; Watt, C.

2014-12-01

Various microforms, created by spatial differential thawing of permafrost, make up the subarctic heterogeneous Stordalen peatland complex (68°22'N, 19°03'E), near Abisko, Sweden. This results in significantly different peatland vegetation communities across short distances, as well as differences in wetness, temperature and peat substrates. We have been measuring the spatially integrated CO2, heat and water vapour fluxes from this peatland complex using eddy covariance and the CO2 exchange from specific plant communities within the EC tower footprint since spring 2008. With this data we are examining if it is possible to derive the spatially integrated ecosystem-wide fluxes from community-level simple light use efficiency (LUE) and ecosystem respiration (ER) models. These models have been developed using several years of continuous autochamber flux measurements for the three major plant functional types (PFTs) as well as knowledge of the spatial variability of the vegetation, water table and active layer depths. LIDAR was used to produce a 1 m resolution digital evaluation model of the complex and the spatial distribution of PFTs was obtained from concurrent high-resolution digital colour air photography trained from vegetation surveys. Continuous water table depths have been measured for four years at over 40 locations in the complex, and peat temperatures and active layer depths are surveyed every 10 days at more than 100 locations. The EC footprint is calculated for every half-hour and the PFT based models are run with the corresponding environmental variables weighted for the PFTs within the EC footprint. Our results show that the Sphagnum, palsa, and sedge PFTs have distinctly different LUE models, and that the tower fluxes are dominated by a blend of the Sphagnum and palsa PFTs. We also see a distinctly different energy partitioning between the fetches containing intact palsa and those with thawed palsa: the evaporative efficiency is higher and the Bowen

Guide to APA-Based Models

Science.gov (United States)

Robins, Robert E.; Delisi, Donald P.

2008-01-01

In Robins and Delisi (2008), a linear decay model, a new IGE model by Sarpkaya (2006), and a series of APA-Based models were scored using data from three airports. This report is a guide to the APA-based models.

Traceability in Model-Based Testing

Directory of Open Access Journals (Sweden)

Mathew George

2012-11-01

Full Text Available The growing complexities of software and the demand for shorter time to market are two important challenges that face today’s IT industry. These challenges demand the increase of both productivity and quality of software. Model-based testing is a promising technique for meeting these challenges. Traceability modeling is a key issue and challenge in model-based testing. Relationships between the different models will help to navigate from one model to another, and trace back to the respective requirements and the design model when the test fails. In this paper, we present an approach for bridging the gaps between the different models in model-based testing. We propose relation definition markup language (RDML for defining the relationships between models.

Activity-based DEVS modeling

DEFF Research Database (Denmark)

Alshareef, Abdurrahman; Sarjoughian, Hessam S.; Zarrin, Bahram

2018-01-01

architecture and the UML concepts. In this paper, we further this work by grounding Activity-based DEVS modeling and developing a fully-fledged modeling engine to demonstrate applicability. We also detail the relevant aspects of the created metamodel in terms of modeling and simulation. A significant number......Use of model-driven approaches has been increasing to significantly benefit the process of building complex systems. Recently, an approach for specifying model behavior using UML activities has been devised to support the creation of DEVS models in a disciplined manner based on the model driven...... of the artifacts of the UML 2.5 activities and actions, from the vantage point of DEVS behavioral modeling, is covered in details. Their semantics are discussed to the extent of time-accurate requirements for simulation. We characterize them in correspondence with the specification of the atomic model behavior. We...

Lévy-based growth models

DEFF Research Database (Denmark)

Jónsdóttir, Kristjana Ýr; Schmiegel, Jürgen; Jensen, Eva Bjørn Vedel

2008-01-01

In the present paper, we give a condensed review, for the nonspecialist reader, of a new modelling framework for spatio-temporal processes, based on Lévy theory. We show the potential of the approach in stochastic geometry and spatial statistics by studying Lévy-based growth modelling of planar o...... objects. The growth models considered are spatio-temporal stochastic processes on the circle. As a by product, flexible new models for space–time covariance functions on the circle are provided. An application of the Lévy-based growth models to tumour growth is discussed....

Gradient-based model calibration with proxy-model assistance

Science.gov (United States)

Burrows, Wesley; Doherty, John

2016-02-01

Use of a proxy model in gradient-based calibration and uncertainty analysis of a complex groundwater model with large run times and problematic numerical behaviour is described. The methodology is general, and can be used with models of all types. The proxy model is based on a series of analytical functions that link all model outputs used in the calibration process to all parameters requiring estimation. In enforcing history-matching constraints during the calibration and post-calibration uncertainty analysis processes, the proxy model is run for the purposes of populating the Jacobian matrix, while the original model is run when testing parameter upgrades; the latter process is readily parallelized. Use of a proxy model in this fashion dramatically reduces the computational burden of complex model calibration and uncertainty analysis. At the same time, the effect of model numerical misbehaviour on calculation of local gradients is mitigated, this allowing access to the benefits of gradient-based analysis where lack of integrity in finite-difference derivatives calculation would otherwise have impeded such access. Construction of a proxy model, and its subsequent use in calibration of a complex model, and in analysing the uncertainties of predictions made by that model, is implemented in the PEST suite.

HMM-based Trust Model

DEFF Research Database (Denmark)

ElSalamouny, Ehab; Nielsen, Mogens; Sassone, Vladimiro

2010-01-01

Probabilistic trust has been adopted as an approach to taking security sensitive decisions in modern global computing environments. Existing probabilistic trust frameworks either assume fixed behaviour for the principals or incorporate the notion of ‘decay' as an ad hoc approach to cope...... with their dynamic behaviour. Using Hidden Markov Models (HMMs) for both modelling and approximating the behaviours of principals, we introduce the HMM-based trust model as a new approach to evaluating trust in systems exhibiting dynamic behaviour. This model avoids the fixed behaviour assumption which is considered...... the major limitation of existing Beta trust model. We show the consistency of the HMM-based trust model and contrast it against the well known Beta trust model with the decay principle in terms of the estimation precision....

Base Station Performance Model

OpenAIRE

Walsh, Barbara; Farrell, Ronan

2005-01-01

At present the testing of power amplifiers within base station transmitters is limited to testing at component level as opposed to testing at the system level. While the detection of catastrophic failure is possible, that of performance degradation is not. This paper proposes a base station model with respect to transmitter output power with the aim of introducing system level monitoring of the power amplifier behaviour within the base station. Our model reflects the expe...

Model based design introduction: modeling game controllers to microprocessor architectures

Science.gov (United States)

Jungwirth, Patrick; Badawy, Abdel-Hameed

2017-04-01

We present an introduction to model based design. Model based design is a visual representation, generally a block diagram, to model and incrementally develop a complex system. Model based design is a commonly used design methodology for digital signal processing, control systems, and embedded systems. Model based design's philosophy is: to solve a problem - a step at a time. The approach can be compared to a series of steps to converge to a solution. A block diagram simulation tool allows a design to be simulated with real world measurement data. For example, if an analog control system is being upgraded to a digital control system, the analog sensor input signals can be recorded. The digital control algorithm can be simulated with the real world sensor data. The output from the simulated digital control system can then be compared to the old analog based control system. Model based design can compared to Agile software develop. The Agile software development goal is to develop working software in incremental steps. Progress is measured in completed and tested code units. Progress is measured in model based design by completed and tested blocks. We present a concept for a video game controller and then use model based design to iterate the design towards a working system. We will also describe a model based design effort to develop an OS Friendly Microprocessor Architecture based on the RISC-V.

The impact of design-based modeling instruction on seventh graders' spatial abilities and model-based argumentation

Science.gov (United States)

McConnell, William J.

Due to the call of current science education reform for the integration of engineering practices within science classrooms, design-based instruction is receiving much attention in science education literature. Although some aspect of modeling is often included in well-known design-based instructional methods, it is not always a primary focus. The purpose of this study was to better understand how design-based instruction with an emphasis on scientific modeling might impact students' spatial abilities and their model-based argumentation abilities. In the following mixed-method multiple case study, seven seventh grade students attending a secular private school in the Mid-Atlantic region of the United States underwent an instructional intervention involving design-based instruction, modeling and argumentation. Through the course of a lesson involving students in exploring the interrelatedness of the environment and an animal's form and function, students created and used multiple forms of expressed models to assist them in model-based scientific argument. Pre/post data were collected through the use of The Purdue Spatial Visualization Test: Rotation, the Mental Rotation Test and interviews. Other data included a spatial activities survey, student artifacts in the form of models, notes, exit tickets, and video recordings of students throughout the intervention. Spatial abilities tests were analyzed using descriptive statistics while students' arguments were analyzed using the Instrument for the Analysis of Scientific Curricular Arguments and a behavior protocol. Models were analyzed using content analysis and interviews and all other data were coded and analyzed for emergent themes. Findings in the area of spatial abilities included increases in spatial reasoning for six out of seven participants, and an immense difference in the spatial challenges encountered by students when using CAD software instead of paper drawings to create models. Students perceived 3D printed

EPR-based material modelling of soils

Science.gov (United States)

Faramarzi, Asaad; Alani, Amir M.

2013-04-01

In the past few decades, as a result of the rapid developments in computational software and hardware, alternative computer aided pattern recognition approaches have been introduced to modelling many engineering problems, including constitutive modelling of materials. The main idea behind pattern recognition systems is that they learn adaptively from experience and extract various discriminants, each appropriate for its purpose. In this work an approach is presented for developing material models for soils based on evolutionary polynomial regression (EPR). EPR is a recently developed hybrid data mining technique that searches for structured mathematical equations (representing the behaviour of a system) using genetic algorithm and the least squares method. Stress-strain data from triaxial tests are used to train and develop EPR-based material models for soil. The developed models are compared with some of the well-known conventional material models and it is shown that EPR-based models can provide a better prediction for the behaviour of soils. The main benefits of using EPR-based material models are that it provides a unified approach to constitutive modelling of all materials (i.e., all aspects of material behaviour can be implemented within a unified environment of an EPR model); it does not require any arbitrary choice of constitutive (mathematical) models. In EPR-based material models there are no material parameters to be identified. As the model is trained directly from experimental data therefore, EPR-based material models are the shortest route from experimental research (data) to numerical modelling. Another advantage of EPR-based constitutive model is that as more experimental data become available, the quality of the EPR prediction can be improved by learning from the additional data, and therefore, the EPR model can become more effective and robust. The developed EPR-based material models can be incorporated in finite element (FE) analysis.

Issues in practical model-based diagnosis

NARCIS (Netherlands)

Bakker, R.R.; Bakker, R.R.; van den Bempt, P.C.A.; van den Bempt, P.C.A.; Mars, Nicolaas; Out, D.-J.; Out, D.J.; van Soest, D.C.; van Soes, D.C.

1993-01-01

The model-based diagnosis project at the University of Twente has been directed at improving the practical usefulness of model-based diagnosis. In cooperation with industrial partners, the research addressed the modeling problem and the efficiency problem in model-based reasoning. Main results of

Agent-based modeling and network dynamics

CERN Document Server

Namatame, Akira

2016-01-01

The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

Principles of models based engineering

Energy Technology Data Exchange (ETDEWEB)

Dolin, R.M.; Hefele, J.

1996-11-01

This report describes a Models Based Engineering (MBE) philosophy and implementation strategy that has been developed at Los Alamos National Laboratory`s Center for Advanced Engineering Technology. A major theme in this discussion is that models based engineering is an information management technology enabling the development of information driven engineering. Unlike other information management technologies, models based engineering encompasses the breadth of engineering information, from design intent through product definition to consumer application.

Model-based Software Engineering

DEFF Research Database (Denmark)

Kindler, Ekkart

2010-01-01

The vision of model-based software engineering is to make models the main focus of software development and to automatically generate software from these models. Part of that idea works already today. But, there are still difficulties when it comes to behaviour. Actually, there is no lack in models...

Using sampled-data feedback control and linear feedback synchronization in a new hyperchaotic system

International Nuclear Information System (INIS)

Zhao Junchan; Lu Junan

2008-01-01

This paper investigates control and synchronization of a new hyperchaotic system which was proposed by [Chen A, Lu J-A, Lue J, Yu S. Generating hyperchaotic Lue attractor via state feedback control. Physica A 2006;364:103-10]. Firstly, we give different sampled-data feedback control schemes with the variation of system parameter d. Specifically, we only use one controller to drive the system to the origin when d element of (-0.35, 0), and use two controllers if d element of [0, 1.3]. Next, we combine PC method with linear feedback approach to realize synchronization, and derive similar conclusions with varying d. Numerical simulations are also given to validate the proposed approaches

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

Directory of Open Access Journals (Sweden)

Nikola Simidjievski

Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

Model-based internal wave processing

Energy Technology Data Exchange (ETDEWEB)

Candy, J.V.; Chambers, D.H.

1995-06-09

A model-based approach is proposed to solve the oceanic internal wave signal processing problem that is based on state-space representations of the normal-mode vertical velocity and plane wave horizontal velocity propagation models. It is shown that these representations can be utilized to spatially propagate the modal (dept) vertical velocity functions given the basic parameters (wave numbers, Brunt-Vaisala frequency profile etc.) developed from the solution of the associated boundary value problem as well as the horizontal velocity components. Based on this framework, investigations are made of model-based solutions to the signal enhancement problem for internal waves.

Integration of Simulink Models with Component-based Software Models

Directory of Open Access Journals (Sweden)

MARIAN, N.

2008-06-01

Full Text Available Model based development aims to facilitate the development of embedded control systems by emphasizing the separation of the design level from the implementation level. Model based design involves the use of multiple models that represent different views of a system, having different semantics of abstract system descriptions. Usually, in mechatronics systems, design proceeds by iterating model construction, model analysis, and model transformation. Constructing a MATLAB/Simulink model, a plant and controller behavior is simulated using graphical blocks to represent mathematical and logical constructs and process flow, then software code is generated. A Simulink model is a representation of the design or implementation of a physical system that satisfies a set of requirements. A software component-based system aims to organize system architecture and behavior as a means of computation, communication and constraints, using computational blocks and aggregates for both discrete and continuous behavior, different interconnection and execution disciplines for event-based and time-based controllers, and so on, to encompass the demands to more functionality, at even lower prices, and with opposite constraints. COMDES (Component-based Design of Software for Distributed Embedded Systems is such a component-based system framework developed by the software engineering group of Mads Clausen Institute for Product Innovation (MCI, University of Southern Denmark. Once specified, the software model has to be analyzed. One way of doing that is to integrate in wrapper files the model back into Simulink S-functions, and use its extensive simulation features, thus allowing an early exploration of the possible design choices over multiple disciplines. The paper describes a safe translation of a restricted set of MATLAB/Simulink blocks to COMDES software components, both for continuous and discrete behavior, and the transformation of the software system into the S

Model-based machine learning.

Science.gov (United States)

Bishop, Christopher M

2013-02-13

Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

Event-based model diagnosis of rainfall-runoff model structures

International Nuclear Information System (INIS)

Stanzel, P.

2012-01-01

The objective of this research is a comparative evaluation of different rainfall-runoff model structures. Comparative model diagnostics facilitate the assessment of strengths and weaknesses of each model. The application of multiple models allows an analysis of simulation uncertainties arising from the selection of model structure, as compared with effects of uncertain parameters and precipitation input. Four different model structures, including conceptual and physically based approaches, are compared. In addition to runoff simulations, results for soil moisture and the runoff components of overland flow, interflow and base flow are analysed. Catchment runoff is simulated satisfactorily by all four model structures and shows only minor differences. Systematic deviations from runoff observations provide insight into model structural deficiencies. While physically based model structures capture some single runoff events better, they do not generally outperform conceptual model structures. Contributions to uncertainty in runoff simulations stemming from the choice of model structure show similar dimensions to those arising from parameter selection and the representation of precipitation input. Variations in precipitation mainly affect the general level and peaks of runoff, while different model structures lead to different simulated runoff dynamics. Large differences between the four analysed models are detected for simulations of soil moisture and, even more pronounced, runoff components. Soil moisture changes are more dynamical in the physically based model structures, which is in better agreement with observations. Streamflow contributions of overland flow are considerably lower in these models than in the more conceptual approaches. Observations of runoff components are rarely made and are not available in this study, but are shown to have high potential for an effective selection of appropriate model structures (author) [de

Adaptive-impulsive synchronization in drive-response networks of continuous systems and its application

International Nuclear Information System (INIS)

Sun Mei; Zeng Changyan; Tao Yangwei; Tian Lixin

2009-01-01

Based on the comparison theorem for the stability of impulsive control system, adaptive-impulsive synchronization in drive-response networks of continuous systems with time-delay and non-time-delay is investigated. And the continuous control input, the simple updated laws and a linear impulsive controller are proposed. Moreover, two numerical examples are presented to verify the effectiveness and correctness of the theorem, using the energy resource system and Lue's system as the nodes of the networks.

Chaos synchronization of a chaotic system via nonlinear control

International Nuclear Information System (INIS)

Park, Ju H.

2005-01-01

In this letter, the problem of chaos synchronization of a chaotic system which is proposed by Lue et al. [Int J Bifurcat Chaos 2004;14:1507] is considered. A novel nonlinear controller is designed based on the Lyapunov stability theory. The proposed controller ensures that the states of the controlled chaotic slave system asymptotically synchronizes the states of the master system. A numerical example is given to illuminate the design procedure and advantage of the result derived

Agent-based modeling of sustainable behaviors

CERN Document Server

Sánchez-Maroño, Noelia; Fontenla-Romero, Oscar; Polhill, J; Craig, Tony; Bajo, Javier; Corchado, Juan

2017-01-01

Using the O.D.D. (Overview, Design concepts, Detail) protocol, this title explores the role of agent-based modeling in predicting the feasibility of various approaches to sustainability. The chapters incorporated in this volume consist of real case studies to illustrate the utility of agent-based modeling and complexity theory in discovering a path to more efficient and sustainable lifestyles. The topics covered within include: households' attitudes toward recycling, designing decision trees for representing sustainable behaviors, negotiation-based parking allocation, auction-based traffic signal control, and others. This selection of papers will be of interest to social scientists who wish to learn more about agent-based modeling as well as experts in the field of agent-based modeling.

Measurement-based reliability/performability models

Science.gov (United States)

Hsueh, Mei-Chen

1987-01-01

Measurement-based models based on real error-data collected on a multiprocessor system are described. Model development from the raw error-data to the estimation of cumulative reward is also described. A workload/reliability model is developed based on low-level error and resource usage data collected on an IBM 3081 system during its normal operation in order to evaluate the resource usage/error/recovery process in a large mainframe system. Thus, both normal and erroneous behavior of the system are modeled. The results provide an understanding of the different types of errors and recovery processes. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A sensitivity analysis is performed to investigate the significance of using a semi-Markov process, as opposed to a Markov process, to model the measured system.

The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

Science.gov (United States)

Zsuga, Judit; Biro, Klara; Papp, Csaba; Tajti, Gabor; Gesztelyi, Rudolf

2016-02-01

Reinforcement learning (RL) is a powerful concept underlying forms of associative learning governed by the use of a scalar reward signal, with learning taking place if expectations are violated. RL may be assessed using model-based and model-free approaches. Model-based reinforcement learning involves the amygdala, the hippocampus, and the orbitofrontal cortex (OFC). The model-free system involves the pedunculopontine-tegmental nucleus (PPTgN), the ventral tegmental area (VTA) and the ventral striatum (VS). Based on the functional connectivity of VS, model-free and model based RL systems center on the VS that by integrating model-free signals (received as reward prediction error) and model-based reward related input computes value. Using the concept of reinforcement learning agent we propose that the VS serves as the value function component of the RL agent. Regarding the model utilized for model-based computations we turned to the proactive brain concept, which offers an ubiquitous function for the default network based on its great functional overlap with contextual associative areas. Hence, by means of the default network the brain continuously organizes its environment into context frames enabling the formulation of analogy-based association that are turned into predictions of what to expect. The OFC integrates reward-related information into context frames upon computing reward expectation by compiling stimulus-reward and context-reward information offered by the amygdala and hippocampus, respectively. Furthermore we suggest that the integration of model-based expectations regarding reward into the value signal is further supported by the efferent of the OFC that reach structures canonical for model-free learning (e.g., the PPTgN, VTA, and VS). (c) 2016 APA, all rights reserved).

The Use of Modeling-Based Text to Improve Students' Modeling Competencies

Science.gov (United States)

Jong, Jing-Ping; Chiu, Mei-Hung; Chung, Shiao-Lan

2015-01-01

This study investigated the effects of a modeling-based text on 10th graders' modeling competencies. Fifteen 10th graders read a researcher-developed modeling-based science text on the ideal gas law that included explicit descriptions and representations of modeling processes (i.e., model selection, model construction, model validation, model…

Knowledge-Based Environmental Context Modeling

Science.gov (United States)

Pukite, P. R.; Challou, D. J.

2017-12-01

As we move from the oil-age to an energy infrastructure based on renewables, the need arises for new educational tools to support the analysis of geophysical phenomena and their behavior and properties. Our objective is to present models of these phenomena to make them amenable for incorporation into more comprehensive analysis contexts. Starting at the level of a college-level computer science course, the intent is to keep the models tractable and therefore practical for student use. Based on research performed via an open-source investigation managed by DARPA and funded by the Department of Interior [1], we have adapted a variety of physics-based environmental models for a computer-science curriculum. The original research described a semantic web architecture based on patterns and logical archetypal building-blocks (see figure) well suited for a comprehensive environmental modeling framework. The patterns span a range of features that cover specific land, atmospheric and aquatic domains intended for engineering modeling within a virtual environment. The modeling engine contained within the server relied on knowledge-based inferencing capable of supporting formal terminology (through NASA JPL's Semantic Web for Earth and Environmental Technology (SWEET) ontology and a domain-specific language) and levels of abstraction via integrated reasoning modules. One of the key goals of the research was to simplify models that were ordinarily computationally intensive to keep them lightweight enough for interactive or virtual environment contexts. The breadth of the elements incorporated is well-suited for learning as the trend toward ontologies and applying semantic information is vital for advancing an open knowledge infrastructure. As examples of modeling, we have covered such geophysics topics as fossil-fuel depletion, wind statistics, tidal analysis, and terrain modeling, among others. Techniques from the world of computer science will be necessary to promote efficient

Evidence-based quantification of uncertainties induced via simulation-based modeling

International Nuclear Information System (INIS)

Riley, Matthew E.

2015-01-01

The quantification of uncertainties in simulation-based modeling traditionally focuses upon quantifying uncertainties in the parameters input into the model, referred to as parametric uncertainties. Often neglected in such an approach are the uncertainties induced by the modeling process itself. This deficiency is often due to a lack of information regarding the problem or the models considered, which could theoretically be reduced through the introduction of additional data. Because of the nature of this epistemic uncertainty, traditional probabilistic frameworks utilized for the quantification of uncertainties are not necessarily applicable to quantify the uncertainties induced in the modeling process itself. This work develops and utilizes a methodology – incorporating aspects of Dempster–Shafer Theory and Bayesian model averaging – to quantify uncertainties of all forms for simulation-based modeling problems. The approach expands upon classical parametric uncertainty approaches, allowing for the quantification of modeling-induced uncertainties as well, ultimately providing bounds on classical probability without the loss of epistemic generality. The approach is demonstrated on two different simulation-based modeling problems: the computation of the natural frequency of a simple two degree of freedom non-linear spring mass system and the calculation of the flutter velocity coefficient for the AGARD 445.6 wing given a subset of commercially available modeling choices. - Highlights: • Modeling-induced uncertainties are often mishandled or ignored in the literature. • Modeling-induced uncertainties are epistemic in nature. • Probabilistic representations of modeling-induced uncertainties are restrictive. • Evidence theory and Bayesian model averaging are integrated. • Developed approach is applicable for simulation-based modeling problems

Convex-based void filling method for CAD-based Monte Carlo geometry modeling

International Nuclear Information System (INIS)

Yu, Shengpeng; Cheng, Mengyun; Song, Jing; Long, Pengcheng; Hu, Liqin

2015-01-01

Highlights: • We present a new void filling method named CVF for CAD based MC geometry modeling. • We describe convex based void description based and quality-based space subdivision. • The results showed improvements provided by CVF for both modeling and MC calculation efficiency. - Abstract: CAD based automatic geometry modeling tools have been widely applied to generate Monte Carlo (MC) calculation geometry for complex systems according to CAD models. Automatic void filling is one of the main functions in the CAD based MC geometry modeling tools, because the void space between parts in CAD models is traditionally not modeled while MC codes such as MCNP need all the problem space to be described. A dedicated void filling method, named Convex-based Void Filling (CVF), is proposed in this study for efficient void filling and concise void descriptions. The method subdivides all the problem space into disjointed regions using Quality based Subdivision (QS) and describes the void space in each region with complementary descriptions of the convex volumes intersecting with that region. It has been implemented in SuperMC/MCAM, the Multiple-Physics Coupling Analysis Modeling Program, and tested on International Thermonuclear Experimental Reactor (ITER) Alite model. The results showed that the new method reduced both automatic modeling time and MC calculation time

Chaos control of chaotic dynamical systems using backstepping design

International Nuclear Information System (INIS)

Yassen, M.T.

2006-01-01

This work presents chaos control of chaotic dynamical systems by using backstepping design method. This technique is applied to achieve chaos control for each of the dynamical systems Lorenz, Chen and Lue systems. Based on Lyapunov stability theory, control laws are derived. We used the same technique to enable stabilization of chaotic motion to a steady state as well as tracking of any desired trajectory to be achieved in a systematic way. Numerical simulations are shown to verify the results

Model-based version management system framework

International Nuclear Information System (INIS)

Mehmood, W.

2016-01-01

In this paper we present a model-based version management system. Version Management System (VMS) a branch of software configuration management (SCM) aims to provide a controlling mechanism for evolution of software artifacts created during software development process. Controlling the evolution requires many activities to perform, such as, construction and creation of versions, identification of differences between versions, conflict detection and merging. Traditional VMS systems are file-based and consider software systems as a set of text files. File based VMS systems are not adequate for performing software configuration management activities such as, version control on software artifacts produced in earlier phases of the software life cycle. New challenges of model differencing, merge, and evolution control arise while using models as central artifact. The goal of this work is to present a generic framework model-based VMS which can be used to overcome the problem of tradition file-based VMS systems and provide model versioning services. (author)

Culturicon model: A new model for cultural-based emoticon

Science.gov (United States)

Zukhi, Mohd Zhafri Bin Mohd; Hussain, Azham

2017-10-01

Emoticons are popular among distributed collective interaction user in expressing their emotion, gestures and actions. Emoticons have been proved to be able to avoid misunderstanding of the message, attention saving and improved the communications among different native speakers. However, beside the benefits that emoticons can provide, the study regarding emoticons in cultural perspective is still lacking. As emoticons are crucial in global communication, culture should be one of the extensively research aspect in distributed collective interaction. Therefore, this study attempt to explore and develop model for cultural-based emoticon. Three cultural models that have been used in Human-Computer Interaction were studied which are the Hall Culture Model, Trompenaars and Hampden Culture Model and Hofstede Culture Model. The dimensions from these three models will be used in developing the proposed cultural-based emoticon model.

Least-squares model-based halftoning

Science.gov (United States)

Pappas, Thrasyvoulos N.; Neuhoff, David L.

1992-08-01

A least-squares model-based approach to digital halftoning is proposed. It exploits both a printer model and a model for visual perception. It attempts to produce an 'optimal' halftoned reproduction, by minimizing the squared error between the response of the cascade of the printer and visual models to the binary image and the response of the visual model to the original gray-scale image. Conventional methods, such as clustered ordered dither, use the properties of the eye only implicitly, and resist printer distortions at the expense of spatial and gray-scale resolution. In previous work we showed that our printer model can be used to modify error diffusion to account for printer distortions. The modified error diffusion algorithm has better spatial and gray-scale resolution than conventional techniques, but produces some well known artifacts and asymmetries because it does not make use of an explicit eye model. Least-squares model-based halftoning uses explicit eye models and relies on printer models that predict distortions and exploit them to increase, rather than decrease, both spatial and gray-scale resolution. We have shown that the one-dimensional least-squares problem, in which each row or column of the image is halftoned independently, can be implemented with the Viterbi's algorithm. Unfortunately, no closed form solution can be found in two dimensions. The two-dimensional least squares solution is obtained by iterative techniques. Experiments show that least-squares model-based halftoning produces more gray levels and better spatial resolution than conventional techniques. We also show that the least- squares approach eliminates the problems associated with error diffusion. Model-based halftoning can be especially useful in transmission of high quality documents using high fidelity gray-scale image encoders. As we have shown, in such cases halftoning can be performed at the receiver, just before printing. Apart from coding efficiency, this approach

Responses of photosynthetic parameters to drought in subtropical forest ecosystem of China

Science.gov (United States)

Zhou, Lei; Wang, Shaoqiang; Chi, Yonggang; Li, Qingkang; Huang, Kun; Yu, Quanzhou

2015-12-01

The mechanism underlying the effect of drought on the photosynthetic traits of leaves in forest ecosystems in subtropical regions is unclear. In this study, three limiting processes (stomatal, mesophyll and biochemical limitations) that control the photosynthetic capacity and three resource use efficiencies (intrinsic water use efficiency (iWUE), nitrogen use efficiency (NUE) and light use efficiency (LUE)), which were characterized as the interactions between photosynthesis and environmental resources, were estimated in two species (Schima superba and Pinus massoniana) under drought conditions. A quantitative limitation analysis demonstrated that the drought-induced limitation of photosynthesis in Schima superba was primarily due to stomatal limitation, whereas for Pinus massoniana, both stomatal and non-stomatal limitations generally exhibited similar magnitudes. Although the mesophyll limitation represented only 1% of the total limitation in Schima superba, it accounted for 24% of the total limitations for Pinus massoniana. Furthermore, a positive relationship between the LUE and NUE and a marginally negative relationship or trade-off between the NUE and iWUE were observed in the control plots. However, drought disrupted the relationships between the resource use efficiencies. Our findings may have important implications for reducing the uncertainties in model simulations and advancing the understanding of the interactions between ecosystem functions and climate change.

Model-based sensor diagnosis

International Nuclear Information System (INIS)

Milgram, J.; Dormoy, J.L.

1994-09-01

Running a nuclear power plant involves monitoring data provided by the installation's sensors. Operators and computerized systems then use these data to establish a diagnostic of the plant. However, the instrumentation system is complex, and is not immune to faults and failures. This paper presents a system for detecting sensor failures using a topological description of the installation and a set of component models. This model of the plant implicitly contains relations between sensor data. These relations must always be checked if all the components are functioning correctly. The failure detection task thus consists of checking these constraints. The constraints are extracted in two stages. Firstly, a qualitative model of their existence is built using structural analysis. Secondly, the models are formally handled according to the results of the structural analysis, in order to establish the constraints on the sensor data. This work constitutes an initial step in extending model-based diagnosis, as the information on which it is based is suspect. This work will be followed by surveillance of the detection system. When the instrumentation is assumed to be sound, the unverified constraints indicate errors on the plant model. (authors). 8 refs., 4 figs

Model-Based Learning Environment Based on The Concept IPS School-Based Management

Directory of Open Access Journals (Sweden)

Hamid Darmadi

2017-03-01

Full Text Available The results showed: (1 learning model IPS-oriented environment can grow and not you love the cultural values of the area as a basis for the development of national culture, (2 community participation, and the role of government in implementing learning model of IPS-based environment provides a positive impact for the improvement of management school resources, (3 learning model IPS-based environment effectively creating a way of life together peacefully, increase the intensity of togetherness and mutual respect (4 learning model IPS-based environment can improve student learning outcomes, (5 there are differences in the expression of attitudes and results learning among students who are located in the area of conflict with students who are outside the area of conflict (6 analysis of the scale of attitudes among school students da SMA result rewards high school students to the values of unity and nation, respect for diversity and peaceful coexistence, It is recommended that the Department of Education authority as an institution of Trustees and the development of social and cultural values in the province can apply IPS learning model based environments.

Model based process-product design and analysis

DEFF Research Database (Denmark)

Gani, Rafiqul

This paper gives a perspective on modelling and the important role it has within product-process design and analysis. Different modelling issues related to development and application of systematic model-based solution approaches for product-process design is discussed and the need for a hybrid...... model-based framework is highlighted. This framework should be able to manage knowledge-data, models, and associated methods and tools integrated with design work-flows and data-flows for specific product-process design problems. In particular, the framework needs to manage models of different types......, forms and complexity, together with their associated parameters. An example of a model-based system for design of chemicals based formulated products is also given....

A probabilistic graphical model based stochastic input model construction

International Nuclear Information System (INIS)

Wan, Jiang; Zabaras, Nicholas

2014-01-01

Model reduction techniques have been widely used in modeling of high-dimensional stochastic input in uncertainty quantification tasks. However, the probabilistic modeling of random variables projected into reduced-order spaces presents a number of computational challenges. Due to the curse of dimensionality, the underlying dependence relationships between these random variables are difficult to capture. In this work, a probabilistic graphical model based approach is employed to learn the dependence by running a number of conditional independence tests using observation data. Thus a probabilistic model of the joint PDF is obtained and the PDF is factorized into a set of conditional distributions based on the dependence structure of the variables. The estimation of the joint PDF from data is then transformed to estimating conditional distributions under reduced dimensions. To improve the computational efficiency, a polynomial chaos expansion is further applied to represent the random field in terms of a set of standard random variables. This technique is combined with both linear and nonlinear model reduction methods. Numerical examples are presented to demonstrate the accuracy and efficiency of the probabilistic graphical model based stochastic input models. - Highlights: • Data-driven stochastic input models without the assumption of independence of the reduced random variables. • The problem is transformed to a Bayesian network structure learning problem. • Examples are given in flows in random media

Web Based VRML Modelling

NARCIS (Netherlands)

Kiss, S.; Sarfraz, M.

2004-01-01

Presents a method to connect VRML (Virtual Reality Modeling Language) and Java components in a Web page using EAI (External Authoring Interface), which makes it possible to interactively generate and edit VRML meshes. The meshes used are based on regular grids, to provide an interaction and modeling

Physics Based Modeling of Compressible Turbulance

Science.gov (United States)

2016-11-07

AFRL-AFOSR-VA-TR-2016-0345 PHYSICS -BASED MODELING OF COMPRESSIBLE TURBULENCE PARVIZ MOIN LELAND STANFORD JUNIOR UNIV CA Final Report 09/13/2016...on the AFOSR project (FA9550-11-1-0111) entitled: Physics based modeling of compressible turbulence. The period of performance was, June 15, 2011...by ANSI Std. Z39.18 Page 1 of 2FORM SF 298 11/10/2016https://livelink.ebs.afrl.af.mil/livelink/llisapi.dll PHYSICS -BASED MODELING OF COMPRESSIBLE

Devenir élue. Genre et carrière politique

OpenAIRE

Bérengère, Savinel

2017-01-01

L’ouvrage de Maud Navarre issu de sa thèse de doctorat en science politique se propose de mettre à l’épreuve l’hypothèse selon laquelle le « devenir élu.e » est marqué par un apprentissage spécifique des rôles politiques en fonction du genre. Pour ce faire, Maud Navarre mobilise une approche théorique en termes de « carrière » et de « rôle » afin de saisir les spécificités des processus de socialisation au « métier » en fonction des différents contextes institutionnels dans lesquels se déploi...

Probabilistic reasoning for assembly-based 3D modeling

KAUST Repository

Chaudhuri, Siddhartha; Kalogerakis, Evangelos; Guibas, Leonidas; Koltun, Vladlen

2011-01-01

Assembly-based modeling is a promising approach to broadening the accessibility of 3D modeling. In assembly-based modeling, new models are assembled from shape components extracted from a database. A key challenge in assembly-based modeling

Model Based Temporal Reasoning

Science.gov (United States)

Rabin, Marla J.; Spinrad, Paul R.; Fall, Thomas C.

1988-03-01

Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements. The differences among temporal reasoning schemes lies in the methods used to avoid computational intractability. If we had n pieces of data and we wanted to examine how they were related, the worst case would be where we had to examine every subset of these points to see if that subset satisfied the relations. This would be 2n, which is intractable. Models compress this; if several data points are all compatible with a model, then that model represents all those data points. Data points are then considered related if they lie within the same model or if they lie in models that are related. Models thus address the intractability problem. They also address the problem of determining unusual activities if the data do not agree with models that are indicated by earlier data then something out of the norm is taking place. The models can summarize what we know up to that time, so when they are not predicting correctly, either something unusual is happening or we need to revise our models. The model based reasoner developed at Advanced Decision Systems is thus both intuitive and powerful. It is currently being used on one operational system and several prototype systems. It has enough power to be used in domains spanning the spectrum from manufacturing engineering and project management to low-intensity conflict and strategic assessment.

Econophysics of agent-based models

CERN Document Server

Aoyama, Hideaki; Chakrabarti, Bikas; Chakraborti, Anirban; Ghosh, Asim

2014-01-01

The primary goal of this book is to present the research findings and conclusions of physicists, economists, mathematicians and financial engineers working in the field of "Econophysics" who have undertaken agent-based modelling, comparison with empirical studies and related investigations. Most standard economic models assume the existence of the representative agent, who is “perfectly rational” and applies the utility maximization principle when taking action. One reason for this is the desire to keep models mathematically tractable: no tools are available to economists for solving non-linear models of heterogeneous adaptive agents without explicit optimization. In contrast, multi-agent models, which originated from statistical physics considerations, allow us to go beyond the prototype theories of traditional economics involving the representative agent. This book is based on the Econophys-Kolkata VII Workshop, at which many such modelling efforts were presented. In the book, leading researchers in the...

A model-based framework for design of intensified enzyme-based processes

DEFF Research Database (Denmark)

Román-Martinez, Alicia

This thesis presents a generic and systematic model-based framework to design intensified enzyme-based processes. The development of the presented methodology was motivated by the needs of the bio-based industry for a more systematic approach to achieve intensification in its production plants...... in enzyme-based processes which have found significant application in the pharmaceutical, food, and renewable fuels sector. The framework uses model-based strategies for (bio)-chemical process design and optimization, including the use of a superstructure to generate all potential reaction......(s)-separation(s) options according to a desired performance criteria and a generic mathematical model represented by the superstructure to derive the specific models corresponding to a specific process option. In principle, three methods of intensification of bioprocess are considered in this thesis: 1. enzymatic one...

ANFIS-Based Modeling for Photovoltaic Characteristics Estimation

Directory of Open Access Journals (Sweden)

Ziqiang Bi

2016-09-01

Full Text Available Due to the high cost of photovoltaic (PV modules, an accurate performance estimation method is significantly valuable for studying the electrical characteristics of PV generation systems. Conventional analytical PV models are usually composed by nonlinear exponential functions and a good number of unknown parameters must be identified before using. In this paper, an adaptive-network-based fuzzy inference system (ANFIS based modeling method is proposed to predict the current-voltage characteristics of PV modules. The effectiveness of the proposed modeling method is evaluated through comparison with Villalva’s model, radial basis function neural networks (RBFNN based model and support vector regression (SVR based model. Simulation and experimental results confirm both the feasibility and the effectiveness of the proposed method.

Nucleus geometry and mechanical properties of resistance spot ...

Indian Academy of Sciences (India)

Keywords. Automotive steels; resistance spot welding; mechanical properties; nucleus geometry. 1. .... High va- lues of hardness can be explained with martensitic forma- ... interface of DP450–DP600 steels may have stainless steel properties.

Using Model Replication to Improve the Reliability of Agent-Based Models

Science.gov (United States)

Zhong, Wei; Kim, Yushim

The basic presupposition of model replication activities for a computational model such as an agent-based model (ABM) is that, as a robust and reliable tool, it must be replicable in other computing settings. This assumption has recently gained attention in the community of artificial society and simulation due to the challenges of model verification and validation. Illustrating the replication of an ABM representing fraudulent behavior in a public service delivery system originally developed in the Java-based MASON toolkit for NetLogo by a different author, this paper exemplifies how model replication exercises provide unique opportunities for model verification and validation process. At the same time, it helps accumulate best practices and patterns of model replication and contributes to the agenda of developing a standard methodological protocol for agent-based social simulation.

Skull base tumor model.

Science.gov (United States)

Gragnaniello, Cristian; Nader, Remi; van Doormaal, Tristan; Kamel, Mahmoud; Voormolen, Eduard H J; Lasio, Giovanni; Aboud, Emad; Regli, Luca; Tulleken, Cornelius A F; Al-Mefty, Ossama

2010-11-01

Resident duty-hours restrictions have now been instituted in many countries worldwide. Shortened training times and increased public scrutiny of surgical competency have led to a move away from the traditional apprenticeship model of training. The development of educational models for brain anatomy is a fascinating innovation allowing neurosurgeons to train without the need to practice on real patients and it may be a solution to achieve competency within a shortened training period. The authors describe the use of Stratathane resin ST-504 polymer (SRSP), which is inserted at different intracranial locations to closely mimic meningiomas and other pathological entities of the skull base, in a cadaveric model, for use in neurosurgical training. Silicone-injected and pressurized cadaveric heads were used for studying the SRSP model. The SRSP presents unique intrinsic metamorphic characteristics: liquid at first, it expands and foams when injected into the desired area of the brain, forming a solid tumorlike structure. The authors injected SRSP via different passages that did not influence routes used for the surgical approach for resection of the simulated lesion. For example, SRSP injection routes included endonasal transsphenoidal or transoral approaches if lesions were to be removed through standard skull base approach, or, alternatively, SRSP was injected via a cranial approach if the removal was planned to be via the transsphenoidal or transoral route. The model was set in place in 3 countries (US, Italy, and The Netherlands), and a pool of 13 physicians from 4 different institutions (all surgeons and surgeons in training) participated in evaluating it and provided feedback. All 13 evaluating physicians had overall positive impressions of the model. The overall score on 9 components evaluated--including comparison between the tumor model and real tumor cases, perioperative requirements, general impression, and applicability--was 88% (100% being the best possible

Firm Based Trade Models and Turkish Economy

Directory of Open Access Journals (Sweden)

Nilüfer ARGIN

2015-12-01

Full Text Available Among all international trade models, only The Firm Based Trade Models explains firm’s action and behavior in the world trade. The Firm Based Trade Models focuses on the trade behavior of individual firms that actually make intra industry trade. Firm Based Trade Models can explain globalization process truly. These approaches include multinational cooperation, supply chain and outsourcing also. Our paper aims to explain and analyze Turkish export with Firm Based Trade Models’ context. We use UNCTAD data on exports by SITC Rev 3 categorization to explain total export and 255 products and calculate intensive-extensive margins of Turkish firms.

Incident Duration Modeling Using Flexible Parametric Hazard-Based Models

Directory of Open Access Journals (Sweden)

Ruimin Li

2014-01-01

Full Text Available Assessing and prioritizing the duration time and effects of traffic incidents on major roads present significant challenges for road network managers. This study examines the effect of numerous factors associated with various types of incidents on their duration and proposes an incident duration prediction model. Several parametric accelerated failure time hazard-based models were examined, including Weibull, log-logistic, log-normal, and generalized gamma, as well as all models with gamma heterogeneity and flexible parametric hazard-based models with freedom ranging from one to ten, by analyzing a traffic incident dataset obtained from the Incident Reporting and Dispatching System in Beijing in 2008. Results show that different factors significantly affect different incident time phases, whose best distributions were diverse. Given the best hazard-based models of each incident time phase, the prediction result can be reasonable for most incidents. The results of this study can aid traffic incident management agencies not only in implementing strategies that would reduce incident duration, and thus reduce congestion, secondary incidents, and the associated human and economic losses, but also in effectively predicting incident duration time.

NASA Software Cost Estimation Model: An Analogy Based Estimation Model

Science.gov (United States)

Hihn, Jairus; Juster, Leora; Menzies, Tim; Mathew, George; Johnson, James

2015-01-01

The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K-­ nearest neighbor prediction model performance on the same data set.

Screening of thermophilic neutral lipase-producing Pseudomonas ...

African Journals Online (AJOL)

akpobome uruemuesiri

2013-02-27

Feb 27, 2013 ... Full Length Research Paper ... The main objective of this research was to isolate and ... liquid-state fermentation in shake flask. ..... lues generated signals, which were large in comparison .... production in a bioreactor. Proc.

Modeling Guru: Knowledge Base for NASA Modelers

Science.gov (United States)

Seablom, M. S.; Wojcik, G. S.; van Aartsen, B. H.

2009-05-01

Modeling Guru is an on-line knowledge-sharing resource for anyone involved with or interested in NASA's scientific models or High End Computing (HEC) systems. Developed and maintained by the NASA's Software Integration and Visualization Office (SIVO) and the NASA Center for Computational Sciences (NCCS), Modeling Guru's combined forums and knowledge base for research and collaboration is becoming a repository for the accumulated expertise of NASA's scientific modeling and HEC communities. All NASA modelers and associates are encouraged to participate and provide knowledge about the models and systems so that other users may benefit from their experience. Modeling Guru is divided into a hierarchy of communities, each with its own set forums and knowledge base documents. Current modeling communities include those for space science, land and atmospheric dynamics, atmospheric chemistry, and oceanography. In addition, there are communities focused on NCCS systems, HEC tools and libraries, and programming and scripting languages. Anyone may view most of the content on Modeling Guru (available at http://modelingguru.nasa.gov/), but you must log in to post messages and subscribe to community postings. The site offers a full range of "Web 2.0" features, including discussion forums, "wiki" document generation, document uploading, RSS feeds, search tools, blogs, email notification, and "breadcrumb" links. A discussion (a.k.a. forum "thread") is used to post comments, solicit feedback, or ask questions. If marked as a question, SIVO will monitor the thread, and normally respond within a day. Discussions can include embedded images, tables, and formatting through the use of the Rich Text Editor. Also, the user can add "Tags" to their thread to facilitate later searches. The "knowledge base" is comprised of documents that are used to capture and share expertise with others. The default "wiki" document lets users edit within the browser so others can easily collaborate on the

Model-reduced gradient-based history matching

NARCIS (Netherlands)

Kaleta, M.P.

2011-01-01

Since the world's energy demand increases every year, the oil & gas industry makes a continuous effort to improve fossil fuel recovery. Physics-based petroleum reservoir modeling and closed-loop model-based reservoir management concept can play an important role here. In this concept measured data

Stimulating Scientific Reasoning with Drawing-Based Modeling

Science.gov (United States)

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-01-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

Model-Based Requirements Management in Gear Systems Design Based On Graph-Based Design Languages

Directory of Open Access Journals (Sweden)

Kevin Holder

2017-10-01

Full Text Available For several decades, a wide-spread consensus concerning the enormous importance of an in-depth clarification of the specifications of a product has been observed. A weak clarification of specifications is repeatedly listed as a main cause for the failure of product development projects. Requirements, which can be defined as the purpose, goals, constraints, and criteria associated with a product development project, play a central role in the clarification of specifications. The collection of activities which ensure that requirements are identified, documented, maintained, communicated, and traced throughout the life cycle of a system, product, or service can be referred to as “requirements engineering”. These activities can be supported by a collection and combination of strategies, methods, and tools which are appropriate for the clarification of specifications. Numerous publications describe the strategy and the components of requirements management. Furthermore, recent research investigates its industrial application. Simultaneously, promising developments of graph-based design languages for a holistic digital representation of the product life cycle are presented. Current developments realize graph-based languages by the diagrams of the Unified Modelling Language (UML, and allow the automatic generation and evaluation of multiple product variants. The research presented in this paper seeks to present a method in order to combine the advantages of a conscious requirements management process and graph-based design languages. Consequently, the main objective of this paper is the investigation of a model-based integration of requirements in a product development process by means of graph-based design languages. The research method is based on an in-depth analysis of an exemplary industrial product development, a gear system for so-called “Electrical Multiple Units” (EMU. Important requirements were abstracted from a gear system

Event-Based Conceptual Modeling

DEFF Research Database (Denmark)

Bækgaard, Lars

2009-01-01

The purpose of the paper is to obtain insight into and provide practical advice for event-based conceptual modeling. We analyze a set of event concepts and use the results to formulate a conceptual event model that is used to identify guidelines for creation of dynamic process models and static...... information models. We characterize events as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms of information structures. The conceptual event model is used to characterize a variety of event concepts and it is used to illustrate how events can...... be used to integrate dynamic modeling of processes and static modeling of information structures. The results are unique in the sense that no other general event concept has been used to unify a similar broad variety of seemingly incompatible event concepts. The general event concept can be used...

Identification of walking human model using agent-based modelling

Science.gov (United States)

Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

2018-03-01

The interaction of walking people with large vibrating structures, such as footbridges and floors, in the vertical direction is an important yet challenging phenomenon to describe mathematically. Several different models have been proposed in the literature to simulate interaction of stationary people with vibrating structures. However, the research on moving (walking) human models, explicitly identified for vibration serviceability assessment of civil structures, is still sparse. In this study, the results of a comprehensive set of FRF-based modal tests were used, in which, over a hundred test subjects walked in different group sizes and walking patterns on a test structure. An agent-based model was used to simulate discrete traffic-structure interactions. The occupied structure modal parameters found in tests were used to identify the parameters of the walking individual's single-degree-of-freedom (SDOF) mass-spring-damper model using 'reverse engineering' methodology. The analysis of the results suggested that the normal distribution with the average of μ = 2.85Hz and standard deviation of σ = 0.34Hz can describe human SDOF model natural frequency. Similarly, the normal distribution with μ = 0.295 and σ = 0.047 can describe the human model damping ratio. Compared to the previous studies, the agent-based modelling methodology proposed in this paper offers significant flexibility in simulating multi-pedestrian walking traffics, external forces and simulating different mechanisms of human-structure and human-environment interaction at the same time.

Ground-Based Telescope Parametric Cost Model

Science.gov (United States)

Stahl, H. Philip; Rowell, Ginger Holmes

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.

Multiagent-Based Model For ESCM

Directory of Open Access Journals (Sweden)

Delia MARINCAS

2011-01-01

Full Text Available Web based applications for Supply Chain Management (SCM are now a necessity for every company in order to meet the increasing customer demands, to face the global competition and to make profit. Multiagent-based approach is appropriate for eSCM because it shows many of the characteristics a SCM system should have. For this reason, we have proposed a multiagent-based eSCM model which configures a virtual SC, automates the SC activities: selling, purchasing, manufacturing, planning, inventory, etc. This model will allow a better coordination of the supply chain network and will increase the effectiveness of Web and intel-ligent technologies employed in eSCM software.

SLS Navigation Model-Based Design Approach

Science.gov (United States)

Oliver, T. Emerson; Anzalone, Evan; Geohagan, Kevin; Bernard, Bill; Park, Thomas

2018-01-01

The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and

An acoustical model based monitoring network

NARCIS (Netherlands)

Wessels, P.W.; Basten, T.G.H.; Eerden, F.J.M. van der

2010-01-01

In this paper the approach for an acoustical model based monitoring network is demonstrated. This network is capable of reconstructing a noise map, based on the combination of measured sound levels and an acoustic model of the area. By pre-calculating the sound attenuation within the network the

Model-Based Security Testing

Directory of Open Access Journals (Sweden)

Ina Schieferdecker

2012-02-01

Full Text Available Security testing aims at validating software system requirements related to security properties like confidentiality, integrity, authentication, authorization, availability, and non-repudiation. Although security testing techniques are available for many years, there has been little approaches that allow for specification of test cases at a higher level of abstraction, for enabling guidance on test identification and specification as well as for automated test generation. Model-based security testing (MBST is a relatively new field and especially dedicated to the systematic and efficient specification and documentation of security test objectives, security test cases and test suites, as well as to their automated or semi-automated generation. In particular, the combination of security modelling and test generation approaches is still a challenge in research and of high interest for industrial applications. MBST includes e.g. security functional testing, model-based fuzzing, risk- and threat-oriented testing, and the usage of security test patterns. This paper provides a survey on MBST techniques and the related models as well as samples of new methods and tools that are under development in the European ITEA2-project DIAMONDS.

Model-based Abstraction of Data Provenance

DEFF Research Database (Denmark)

Probst, Christian W.; Hansen, René Rydhof

2014-01-01

to bigger models, and the analyses adapt accordingly. Our approach extends provenance both with the origin of data, the actors and processes involved in the handling of data, and policies applied while doing so. The model and corresponding analyses are based on a formal model of spatial and organisational......Identifying provenance of data provides insights to the origin of data and intermediate results, and has recently gained increased interest due to data-centric applications. In this work we extend a data-centric system view with actors handling the data and policies restricting actions....... This extension is based on provenance analysis performed on system models. System models have been introduced to model and analyse spatial and organisational aspects of organisations, to identify, e.g., potential insider threats. Both the models and analyses are naturally modular; models can be combined...

Model Validation in Ontology Based Transformations

Directory of Open Access Journals (Sweden)

Jesús M. Almendros-Jiménez

2012-10-01

Full Text Available Model Driven Engineering (MDE is an emerging approach of software engineering. MDE emphasizes the construction of models from which the implementation should be derived by applying model transformations. The Ontology Definition Meta-model (ODM has been proposed as a profile for UML models of the Web Ontology Language (OWL. In this context, transformations of UML models can be mapped into ODM/OWL transformations. On the other hand, model validation is a crucial task in model transformation. Meta-modeling permits to give a syntactic structure to source and target models. However, semantic requirements have to be imposed on source and target models. A given transformation will be sound when source and target models fulfill the syntactic and semantic requirements. In this paper, we present an approach for model validation in ODM based transformations. Adopting a logic programming based transformational approach we will show how it is possible to transform and validate models. Properties to be validated range from structural and semantic requirements of models (pre and post conditions to properties of the transformation (invariants. The approach has been applied to a well-known example of model transformation: the Entity-Relationship (ER to Relational Model (RM transformation.

Model-Based Knowing: How Do Students Ground Their Understanding About Climate Systems in Agent-Based Computer Models?

Science.gov (United States)

Markauskaite, Lina; Kelly, Nick; Jacobson, Michael J.

2017-12-01

This paper gives a grounded cognition account of model-based learning of complex scientific knowledge related to socio-scientific issues, such as climate change. It draws on the results from a study of high school students learning about the carbon cycle through computational agent-based models and investigates two questions: First, how do students ground their understanding about the phenomenon when they learn and solve problems with computer models? Second, what are common sources of mistakes in students' reasoning with computer models? Results show that students ground their understanding in computer models in five ways: direct observation, straight abstraction, generalisation, conceptualisation, and extension. Students also incorporate into their reasoning their knowledge and experiences that extend beyond phenomena represented in the models, such as attitudes about unsustainable carbon emission rates, human agency, external events, and the nature of computational models. The most common difficulties of the students relate to seeing the modelled scientific phenomenon and connecting results from the observations with other experiences and understandings about the phenomenon in the outside world. An important contribution of this study is the constructed coding scheme for establishing different ways of grounding, which helps to understand some challenges that students encounter when they learn about complex phenomena with agent-based computer models.

Data-based Non-Markovian Model Inference

Science.gov (United States)

Ghil, Michael

2015-04-01

This talk concentrates on obtaining stable and efficient data-based models for simulation and prediction in the geosciences and life sciences. The proposed model derivation relies on using a multivariate time series of partial observations from a large-dimensional system, and the resulting low-order models are compared with the optimal closures predicted by the non-Markovian Mori-Zwanzig formalism of statistical physics. Multilayer stochastic models (MSMs) are introduced as both a very broad generalization and a time-continuous limit of existing multilevel, regression-based approaches to data-based closure, in particular of empirical model reduction (EMR). We show that the multilayer structure of MSMs can provide a natural Markov approximation to the generalized Langevin equation (GLE) of the Mori-Zwanzig formalism. A simple correlation-based stopping criterion for an EMR-MSM model is derived to assess how well it approximates the GLE solution. Sufficient conditions are given for the nonlinear cross-interactions between the constitutive layers of a given MSM to guarantee the existence of a global random attractor. This existence ensures that no blow-up can occur for a very broad class of MSM applications. The EMR-MSM methodology is first applied to a conceptual, nonlinear, stochastic climate model of coupled slow and fast variables, in which only slow variables are observed. The resulting reduced model with energy-conserving nonlinearities captures the main statistical features of the slow variables, even when there is no formal scale separation and the fast variables are quite energetic. Second, an MSM is shown to successfully reproduce the statistics of a partially observed, generalized Lokta-Volterra model of population dynamics in its chaotic regime. The positivity constraint on the solutions' components replaces here the quadratic-energy-preserving constraint of fluid-flow problems and it successfully prevents blow-up. This work is based on a close

An Emotional Agent Model Based on Granular Computing

Directory of Open Access Journals (Sweden)

Jun Hu

2012-01-01

Full Text Available Affective computing has a very important significance for fulfilling intelligent information processing and harmonious communication between human being and computers. A new model for emotional agent is proposed in this paper to make agent have the ability of handling emotions, based on the granular computing theory and the traditional BDI agent model. Firstly, a new emotion knowledge base based on granular computing for emotion expression is presented in the model. Secondly, a new emotional reasoning algorithm based on granular computing is proposed. Thirdly, a new emotional agent model based on granular computing is presented. Finally, based on the model, an emotional agent for patient assistant in hospital is realized, experiment results show that it is efficient to handle simple emotions.

CEAI: CCM based Email Authorship Identification Model

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah

2013-01-01

In this paper we present a model for email authorship identification (EAI) by employing a Cluster-based Classification (CCM) technique. Traditionally, stylometric features have been successfully employed in various authorship analysis tasks; we extend the traditional feature-set to include some...... more interesting and effective features for email authorship identification (e.g. the last punctuation mark used in an email, the tendency of an author to use capitalization at the start of an email, or the punctuation after a greeting or farewell). We also included Info Gain feature selection based...... reveal that the proposed CCM-based email authorship identification model, along with the proposed feature set, outperforms the state-of-the-art support vector machine (SVM)-based models, as well as the models proposed by Iqbal et al. [1, 2]. The proposed model attains an accuracy rate of 94% for 10...

Individual-based modeling of fish: Linking to physical models and water quality.

Energy Technology Data Exchange (ETDEWEB)

Rose, K.A.

1997-08-01

The individual-based modeling approach for the simulating fish population and community dynamics is gaining popularity. Individual-based modeling has been used in many other fields, such as forest succession and astronomy. The popularity of the individual-based approach is partly a result of the lack of success of the more aggregate modeling approaches traditionally used for simulating fish population and community dynamics. Also, recent recognition that it is often the atypical individual that survives has fostered interest in the individual-based approach. Two general types of individual-based models are distribution and configuration. Distribution models follow the probability distributions of individual characteristics, such as length and age. Configuration models explicitly simulate each individual; the sum over individuals being the population. DeAngelis et al (1992) showed that, when distribution and configuration models were formulated from the same common pool of information, both approaches generated similar predictions. The distribution approach was more compact and general, while the configuration approach was more flexible. Simple biological changes, such as making growth rate dependent on previous days growth rates, were easy to implement in the configuration version but prevented simple analytical solution of the distribution version.

A general model for membrane-based separation processes

DEFF Research Database (Denmark)

Soni, Vipasha; Abildskov, Jens; Jonsson, Gunnar Eigil

2009-01-01

behaviour will play an important role. In this paper, modelling of membrane-based processes for separation of gas and liquid mixtures are considered. Two general models, one for membrane-based liquid separation processes (with phase change) and another for membrane-based gas separation are presented....... The separation processes covered are: membrane-based gas separation processes, pervaporation and various types of membrane distillation processes. The specific model for each type of membrane-based process is generated from the two general models by applying the specific system descriptions and the corresponding...

Anisotropy in wavelet-based phase field models

KAUST Repository

Korzec, Maciek; Mü nch, Andreas; Sü li, Endre; Wagner, Barbara

2016-01-01

When describing the anisotropic evolution of microstructures in solids using phase-field models, the anisotropy of the crystalline phases is usually introduced into the interfacial energy by directional dependencies of the gradient energy coefficients. We consider an alternative approach based on a wavelet analogue of the Laplace operator that is intrinsically anisotropic and linear. The paper focuses on the classical coupled temperature/Ginzburg--Landau type phase-field model for dendritic growth. For the model based on the wavelet analogue, existence, uniqueness and continuous dependence on initial data are proved for weak solutions. Numerical studies of the wavelet based phase-field model show dendritic growth similar to the results obtained for classical phase-field models.

Anisotropy in wavelet-based phase field models

KAUST Repository

Korzec, Maciek

2016-04-01

When describing the anisotropic evolution of microstructures in solids using phase-field models, the anisotropy of the crystalline phases is usually introduced into the interfacial energy by directional dependencies of the gradient energy coefficients. We consider an alternative approach based on a wavelet analogue of the Laplace operator that is intrinsically anisotropic and linear. The paper focuses on the classical coupled temperature/Ginzburg--Landau type phase-field model for dendritic growth. For the model based on the wavelet analogue, existence, uniqueness and continuous dependence on initial data are proved for weak solutions. Numerical studies of the wavelet based phase-field model show dendritic growth similar to the results obtained for classical phase-field models.

Computer Based Modelling and Simulation

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 6; Issue 3. Computer Based Modelling and Simulation - Modelling Deterministic Systems. N K Srinivasan. General Article Volume 6 Issue 3 March 2001 pp 46-54. Fulltext. Click here to view fulltext PDF. Permanent link:

Application of model-based and knowledge-based measuring methods as analytical redundancy

International Nuclear Information System (INIS)

Hampel, R.; Kaestner, W.; Chaker, N.; Vandreier, B.

1997-01-01

The safe operation of nuclear power plants requires the application of modern and intelligent methods of signal processing for the normal operation as well as for the management of accident conditions. Such modern and intelligent methods are model-based and knowledge-based ones being founded on analytical knowledge (mathematical models) as well as experiences (fuzzy information). In addition to the existing hardware redundancies analytical redundancies will be established with the help of these modern methods. These analytical redundancies support the operating staff during the decision-making. The design of a hybrid model-based and knowledge-based measuring method will be demonstrated by the example of a fuzzy-supported observer. Within the fuzzy-supported observer a classical linear observer is connected with a fuzzy-supported adaptation of the model matrices of the observer model. This application is realized for the estimation of the non-measurable variables as steam content and mixture level within pressure vessels with water-steam mixture during accidental depressurizations. For this example the existing non-linearities will be classified and the verification of the model will be explained. The advantages of the hybrid method in comparison to the classical model-based measuring methods will be demonstrated by the results of estimation. The consideration of the parameters which have an important influence on the non-linearities requires the inclusion of high-dimensional structures of fuzzy logic within the model-based measuring methods. Therefore methods will be presented which allow the conversion of these high-dimensional structures to two-dimensional structures of fuzzy logic. As an efficient solution of this problem a method based on cascaded fuzzy controllers will be presented. (author). 2 refs, 12 figs, 5 tabs

A hybrid agent-based approach for modeling microbiological systems.

Science.gov (United States)

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Cognitive components underpinning the development of model-based learning.

Science.gov (United States)

Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

2017-06-01

Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

An Agent-Based Monetary Production Simulation Model

DEFF Research Database (Denmark)

Bruun, Charlotte

2006-01-01

An Agent-Based Simulation Model Programmed in Objective Borland Pascal. Program and source code is downloadable......An Agent-Based Simulation Model Programmed in Objective Borland Pascal. Program and source code is downloadable...

Information modelling and knowledge bases XXV

CERN Document Server

Tokuda, T; Jaakkola, H; Yoshida, N

2014-01-01

Because of our ever increasing use of and reliance on technology and information systems, information modelling and knowledge bases continue to be important topics in those academic communities concerned with data handling and computer science. As the information itself becomes more complex, so do the levels of abstraction and the databases themselves. This book is part of the series Information Modelling and Knowledge Bases, which concentrates on a variety of themes in the important domains of conceptual modeling, design and specification of information systems, multimedia information modelin

Evaluating Emulation-based Models of Distributed Computing Systems

Energy Technology Data Exchange (ETDEWEB)

Jones, Stephen T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Cyber Initiatives; Gabert, Kasimir G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Cyber Initiatives; Tarman, Thomas D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Emulytics Initiatives

2017-08-01

Emulation-based models of distributed computing systems are collections of virtual ma- chines, virtual networks, and other emulation components configured to stand in for oper- ational systems when performing experimental science, training, analysis of design alterna- tives, test and evaluation, or idea generation. As with any tool, we should carefully evaluate whether our uses of emulation-based models are appropriate and justified. Otherwise, we run the risk of using a model incorrectly and creating meaningless results. The variety of uses of emulation-based models each have their own goals and deserve thoughtful evaluation. In this paper, we enumerate some of these uses and describe approaches that one can take to build an evidence-based case that a use of an emulation-based model is credible. Predictive uses of emulation-based models, where we expect a model to tell us something true about the real world, set the bar especially high and the principal evaluation method, called validation , is comensurately rigorous. We spend the majority of our time describing and demonstrating the validation of a simple predictive model using a well-established methodology inherited from decades of development in the compuational science and engineering community.

Model-Based Reasoning in Humans Becomes Automatic with Training.

Directory of Open Access Journals (Sweden)

Marcos Economides

2015-09-01

Full Text Available Model-based and model-free reinforcement learning (RL have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.

Modeling and simulation of complex systems a framework for efficient agent-based modeling and simulation

CERN Document Server

Siegfried, Robert

2014-01-01

Robert Siegfried presents a framework for efficient agent-based modeling and simulation of complex systems. He compares different approaches for describing structure and dynamics of agent-based models in detail. Based on this evaluation the author introduces the "General Reference Model for Agent-based Modeling and Simulation" (GRAMS). Furthermore he presents parallel and distributed simulation approaches for execution of agent-based models -from small scale to very large scale. The author shows how agent-based models may be executed by different simulation engines that utilize underlying hard

New Temperature-based Models for Predicting Global Solar Radiation

International Nuclear Information System (INIS)

Hassan, Gasser E.; Youssef, M. Elsayed; Mohamed, Zahraa E.; Ali, Mohamed A.; Hanafy, Ahmed A.

2016-01-01

Highlights: • New temperature-based models for estimating solar radiation are investigated. • The models are validated against 20-years measured data of global solar radiation. • The new temperature-based model shows the best performance for coastal sites. • The new temperature-based model is more accurate than the sunshine-based models. • The new model is highly applicable with weather temperature forecast techniques. - Abstract: This study presents new ambient-temperature-based models for estimating global solar radiation as alternatives to the widely used sunshine-based models owing to the unavailability of sunshine data at all locations around the world. Seventeen new temperature-based models are established, validated and compared with other three models proposed in the literature (the Annandale, Allen and Goodin models) to estimate the monthly average daily global solar radiation on a horizontal surface. These models are developed using a 20-year measured dataset of global solar radiation for the case study location (Lat. 30°51′N and long. 29°34′E), and then, the general formulae of the newly suggested models are examined for ten different locations around Egypt. Moreover, the local formulae for the models are established and validated for two coastal locations where the general formulae give inaccurate predictions. Mostly common statistical errors are utilized to evaluate the performance of these models and identify the most accurate model. The obtained results show that the local formula for the most accurate new model provides good predictions for global solar radiation at different locations, especially at coastal sites. Moreover, the local and general formulas of the most accurate temperature-based model also perform better than the two most accurate sunshine-based models from the literature. The quick and accurate estimations of the global solar radiation using this approach can be employed in the design and evaluation of performance for

Flow Formulation-based Model for the Curriculum-based Course Timetabling Problem

DEFF Research Database (Denmark)

Bagger, Niels-Christian Fink; Kristiansen, Simon; Sørensen, Matias

2015-01-01

problem. This decreases the number of integer variables signicantly and improves the performance compared to the basic formulation. It also shows competitiveness with other approaches based on mixed integer programming from the literature and improves the currently best known lower bound on one data...... instance in the benchmark data set from the second international timetabling competition.......In this work we will present a new mixed integer programming formulation for the curriculum-based course timetabling problem. We show that the model contains an underlying network model by dividing the problem into two models and then connecting the two models back into one model using a maximum ow...

Model-based reasoning technology for the power industry

International Nuclear Information System (INIS)

Touchton, R.A.; Subramanyan, N.S.; Naser, J.A.

1991-01-01

This paper reports on model-based reasoning which refers to an expert system implementation methodology that uses a model of the system which is being reasoned about. Model-based representation and reasoning techniques offer many advantages and are highly suitable for domains where the individual components, their interconnection, and their behavior is well-known. Technology Applications, Inc. (TAI), under contract to the Electric Power Research Institute (EPRI), investigated the use of model-based reasoning in the power industry including the nuclear power industry. During this project, a model-based monitoring and diagnostic tool, called ProSys, was developed. Also, an alarm prioritization system was developed as a demonstration prototype

Structure-Based Turbulence Model

National Research Council Canada - National Science Library

Reynolds, W

2000-01-01

.... Maire carried out this work as part of his Phi) research. During the award period we began to explore ways to simplify the structure-based modeling so that it could be used in repetitive engineering calculations...

Model-Based Motion Tracking of Infants

DEFF Research Database (Denmark)

Olsen, Mikkel Damgaard; Herskind, Anna; Nielsen, Jens Bo

2014-01-01

Even though motion tracking is a widely used technique to analyze and measure human movements, only a few studies focus on motion tracking of infants. In recent years, a number of studies have emerged focusing on analyzing the motion pattern of infants, using computer vision. Most of these studies...... are based on 2D images, but few are based on 3D information. In this paper, we present a model-based approach for tracking infants in 3D. The study extends a novel study on graph-based motion tracking of infants and we show that the extension improves the tracking results. A 3D model is constructed...

Model-based Prognostics with Concurrent Damage Progression Processes

Data.gov (United States)

National Aeronautics and Space Administration — Model-based prognostics approaches rely on physics-based models that describe the behavior of systems and their components. These models must account for the several...

Probabilistic Model-based Background Subtraction

DEFF Research Database (Denmark)

Krüger, Volker; Anderson, Jakob; Prehn, Thomas

2005-01-01

is the correlation between pixels. In this paper we introduce a model-based background subtraction approach which facilitates prior knowledge of pixel correlations for clearer and better results. Model knowledge is being learned from good training video data, the data is stored for fast access in a hierarchical...

Model-based optimization biofilm based systems performing autotrophic nitrogen removal using the comprehensive NDHA model

DEFF Research Database (Denmark)

Valverde Pérez, Borja; Ma, Yunjie; Morset, Martin

Completely autotrophic nitrogen removal (CANR) can be obtained in single stage biofilm-based bioreactors. However, their environmental footprint is compromised due to elevated N2O emissions. We developed novel spatially explicit biochemical process model of biofilm based CANR systems that predicts...

Probabilistic reasoning for assembly-based 3D modeling

KAUST Repository

Chaudhuri, Siddhartha

2011-01-01

Assembly-based modeling is a promising approach to broadening the accessibility of 3D modeling. In assembly-based modeling, new models are assembled from shape components extracted from a database. A key challenge in assembly-based modeling is the identification of relevant components to be presented to the user. In this paper, we introduce a probabilistic reasoning approach to this problem. Given a repository of shapes, our approach learns a probabilistic graphical model that encodes semantic and geometric relationships among shape components. The probabilistic model is used to present components that are semantically and stylistically compatible with the 3D model that is being assembled. Our experiments indicate that the probabilistic model increases the relevance of presented components. © 2011 ACM.

Multi-Domain Modeling Based on Modelica

Directory of Open Access Journals (Sweden)

Liu Jun

2016-01-01

Full Text Available With the application of simulation technology in large-scale and multi-field problems, multi-domain unified modeling become an effective way to solve these problems. This paper introduces several basic methods and advantages of the multidisciplinary model, and focuses on the simulation based on Modelica language. The Modelica/Mworks is a newly developed simulation software with features of an object-oriented and non-casual language for modeling of the large, multi-domain system, which makes the model easier to grasp, develop and maintain.It This article shows the single degree of freedom mechanical vibration system based on Modelica language special connection mechanism in Mworks. This method that multi-domain modeling has simple and feasible, high reusability. it closer to the physical system, and many other advantages.

Testing R&D-Based Endogenous Growth Models

DEFF Research Database (Denmark)

Kruse-Andersen, Peter Kjær

2017-01-01

R&D-based growth models are tested using US data for the period 1953-2014. A general growth model is developed which nests the model varieties of interest. The model implies a cointegrating relationship between multifactor productivity, research intensity, and employment. This relationship...... is estimated using cointegrated VAR models. The results provide evidence against the widely used fully endogenous variety and in favor of the semi-endogenous variety. Forecasts based on the empirical estimates suggest that the slowdown in US productivity growth will continue. Particularly, the annual long...

PV panel model based on datasheet values

DEFF Research Database (Denmark)

Sera, Dezso; Teodorescu, Remus; Rodriguez, Pedro

2007-01-01

This work presents the construction of a model for a PV panel using the single-diode five-parameters model, based exclusively on data-sheet parameters. The model takes into account the series and parallel (shunt) resistance of the panel. The equivalent circuit and the basic equations of the PV cell....... Based on these equations, a PV panel model, which is able to predict the panel behavior in different temperature and irradiance conditions, is built and tested....

Springer handbook of model-based science

CERN Document Server

Bertolotti, Tommaso

2017-01-01

The handbook offers the first comprehensive reference guide to the interdisciplinary field of model-based reasoning. It highlights the role of models as mediators between theory and experimentation, and as educational devices, as well as their relevance in testing hypotheses and explanatory functions. The Springer Handbook merges philosophical, cognitive and epistemological perspectives on models with the more practical needs related to the application of this tool across various disciplines and practices. The result is a unique, reliable source of information that guides readers toward an understanding of different aspects of model-based science, such as the theoretical and cognitive nature of models, as well as their practical and logical aspects. The inferential role of models in hypothetical reasoning, abduction and creativity once they are constructed, adopted, and manipulated for different scientific and technological purposes is also discussed. Written by a group of internationally renowned experts in ...

Image based 3D city modeling : Comparative study

Directory of Open Access Journals (Sweden)

S. P. Singh

2014-06-01

Full Text Available 3D city model is a digital representation of the Earth’s surface and it’s related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing rapidly for various engineering and non-engineering applications. Generally four main image based approaches were used for virtual 3D city models generation. In first approach, researchers were used Sketch based modeling, second method is Procedural grammar based modeling, third approach is Close range photogrammetry based modeling and fourth approach is mainly based on Computer Vision techniques. SketchUp, CityEngine, Photomodeler and Agisoft Photoscan are the main softwares to represent these approaches respectively. These softwares have different approaches & methods suitable for image based 3D city modeling. Literature study shows that till date, there is no complete such type of comparative study available to create complete 3D city model by using images. This paper gives a comparative assessment of these four image based 3D modeling approaches. This comparative study is mainly based on data acquisition methods, data processing techniques and output 3D model products. For this research work, study area is the campus of civil engineering department, Indian Institute of Technology, Roorkee (India. This 3D campus acts as a prototype for city. This study also explains various governing parameters, factors and work experiences. This research work also gives a brief introduction, strengths and weakness of these four image based techniques. Some personal comment is also given as what can do or what can’t do from these softwares. At the last, this study shows; it concluded that, each and every software has some advantages and limitations. Choice of software depends on user requirements of 3D project. For normal visualization project, SketchUp software is a good option. For 3D documentation record, Photomodeler gives good

Model-Based Integration and Interpretation of Data

DEFF Research Database (Denmark)

Petersen, Johannes

2004-01-01

Data integration and interpretation plays a crucial role in supervisory control. The paper defines a set of generic inference steps for the data integration and interpretation process based on a three-layer model of system representations. The three-layer model is used to clarify the combination...... of constraint and object-centered representations of the work domain throwing new light on the basic principles underlying the data integration and interpretation process of Rasmussen's abstraction hierarchy as well as other model-based approaches combining constraint and object-centered representations. Based...

CEAI: CCM-based email authorship identification model

Directory of Open Access Journals (Sweden)

Sarwat Nizamani

2013-11-01

Full Text Available In this paper we present a model for email authorship identification (EAI by employing a Cluster-based Classification (CCM technique. Traditionally, stylometric features have been successfully employed in various authorship analysis tasks; we extend the traditional feature set to include some more interesting and effective features for email authorship identification (e.g., the last punctuation mark used in an email, the tendency of an author to use capitalization at the start of an email, or the punctuation after a greeting or farewell. We also included Info Gain feature selection based content features. It is observed that the use of such features in the authorship identification process has a positive impact on the accuracy of the authorship identification task. We performed experiments to justify our arguments and compared the results with other base line models. Experimental results reveal that the proposed CCM-based email authorship identification model, along with the proposed feature set, outperforms the state-of-the-art support vector machine (SVM-based models, as well as the models proposed by Iqbal et al. (2010, 2013 [1,2]. The proposed model attains an accuracy rate of 94% for 10 authors, 89% for 25 authors, and 81% for 50 authors, respectively on Enron dataset, while 89.5% accuracy has been achieved on authors’ constructed real email dataset. The results on Enron dataset have been achieved on quite a large number of authors as compared to the models proposed by Iqbal et al. [1,2].

Guidelines for visualizing and annotating rule-based models.

Science.gov (United States)

Chylek, Lily A; Hu, Bin; Blinov, Michael L; Emonet, Thierry; Faeder, James R; Goldstein, Byron; Gutenkunst, Ryan N; Haugh, Jason M; Lipniacki, Tomasz; Posner, Richard G; Yang, Jin; Hlavacek, William S

2011-10-01

Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models.

Automated extraction of knowledge for model-based diagnostics

Science.gov (United States)

Gonzalez, Avelino J.; Myler, Harley R.; Towhidnejad, Massood; Mckenzie, Frederic D.; Kladke, Robin R.

1990-01-01

The concept of accessing computer aided design (CAD) design databases and extracting a process model automatically is investigated as a possible source for the generation of knowledge bases for model-based reasoning systems. The resulting system, referred to as automated knowledge generation (AKG), uses an object-oriented programming structure and constraint techniques as well as internal database of component descriptions to generate a frame-based structure that describes the model. The procedure has been designed to be general enough to be easily coupled to CAD systems that feature a database capable of providing label and connectivity data from the drawn system. The AKG system is capable of defining knowledge bases in formats required by various model-based reasoning tools.

Model-based accelerator controls: What, why and how

International Nuclear Information System (INIS)

Sidhu, S.S.

1987-01-01

Model-based control is defined as a gamut of techniques whose aim is to improve the reliability of an accelerator and enhance the capabilities of the operator, and therefore of the whole control system. The aim of model-based control is seen as gradually moving the function of model-reference from the operator to the computer. The role of the operator in accelerator control and the need for and application of model-based control are briefly summarized

Néron Models and Base Change

DEFF Research Database (Denmark)

Halle, Lars Halvard; Nicaise, Johannes

Presenting the first systematic treatment of the behavior of Néron models under ramified base change, this book can be read as an introduction to various subtle invariants and constructions related to Néron models of semi-abelian varieties, motivated by concrete research problems and complemented...... on Néron component groups, Edixhoven’s filtration and the base change conductor of Chai and Yu, and we study these invariants using various techniques such as models of curves, sheaves on Grothendieck sites and non-archimedean uniformization. We then apply our results to the study of motivic zeta functions...

7 CFR 905.5 - Variety.

Science.gov (United States)

2010-01-01

... of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and... Gong, and similar late maturing oranges of the Valencia type; (b) Valencia, Lue Gim Gong, and similar... seedless grapefruit; (g) Pink seeded grapefruit; (h) Tangelos; (i) Dancy and similar tangerines, excluding...

Learning of Chemical Equilibrium through Modelling-Based Teaching

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Maia, Poliana Flavia; Justi, Rosaria

2009-01-01

This paper presents and discusses students' learning process of chemical equilibrium from a modelling-based approach developed from the use of the "Model of Modelling" diagram. The investigation was conducted in a regular classroom (students 14-15 years old) and aimed at discussing how modelling-based teaching can contribute to students…

Model predictive control based on reduced order models applied to belt conveyor system.

Science.gov (United States)

Chen, Wei; Li, Xin

2016-11-01

In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Multivariate statistical modelling based on generalized linear models

CERN Document Server

Fahrmeir, Ludwig

1994-01-01

This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account to have on their desks. "The basic aim of the authors is to bring together and review a large part of recent advances in statistical modelling of m...

The Design of Model-Based Training Programs

Science.gov (United States)

Polson, Peter; Sherry, Lance; Feary, Michael; Palmer, Everett; Alkin, Marty; McCrobie, Dan; Kelley, Jerry; Rosekind, Mark (Technical Monitor)

1997-01-01

This paper proposes a model-based training program for the skills necessary to operate advance avionics systems that incorporate advanced autopilots and fight management systems. The training model is based on a formalism, the operational procedure model, that represents the mission model, the rules, and the functions of a modem avionics system. This formalism has been defined such that it can be understood and shared by pilots, the avionics software, and design engineers. Each element of the software is defined in terms of its intent (What?), the rationale (Why?), and the resulting behavior (How?). The Advanced Computer Tutoring project at Carnegie Mellon University has developed a type of model-based, computer aided instructional technology called cognitive tutors. They summarize numerous studies showing that training times to a specified level of competence can be achieved in one third the time of conventional class room instruction. We are developing a similar model-based training program for the skills necessary to operation the avionics. The model underlying the instructional program and that simulates the effects of pilots entries and the behavior of the avionics is based on the operational procedure model. Pilots are given a series of vertical flightpath management problems. Entries that result in violations, such as failure to make a crossing restriction or violating the speed limits, result in error messages with instruction. At any time, the flightcrew can request suggestions on the appropriate set of actions. A similar and successful training program for basic skills for the FMS on the Boeing 737-300 was developed and evaluated. The results strongly support the claim that the training methodology can be adapted to the cockpit.

Quality prediction modeling for sintered ores based on mechanism models of sintering and extreme learning machine based error compensation

Science.gov (United States)

Tiebin, Wu; Yunlian, Liu; Xinjun, Li; Yi, Yu; Bin, Zhang

2018-06-01

Aiming at the difficulty in quality prediction of sintered ores, a hybrid prediction model is established based on mechanism models of sintering and time-weighted error compensation on the basis of the extreme learning machine (ELM). At first, mechanism models of drum index, total iron, and alkalinity are constructed according to the chemical reaction mechanism and conservation of matter in the sintering process. As the process is simplified in the mechanism models, these models are not able to describe high nonlinearity. Therefore, errors are inevitable. For this reason, the time-weighted ELM based error compensation model is established. Simulation results verify that the hybrid model has a high accuracy and can meet the requirement for industrial applications.

Facilitating Change to a Problem-based Model

DEFF Research Database (Denmark)

Kolmos, Anette

2002-01-01

The paper presents the barriers which arise during the change process from a traditional educational system to a problem-based educational model.......The paper presents the barriers which arise during the change process from a traditional educational system to a problem-based educational model....

Energy based prediction models for building acoustics

DEFF Research Database (Denmark)

Brunskog, Jonas

2012-01-01

In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....

Pixel-based meshfree modelling of skeletal muscles.

Science.gov (United States)

Chen, Jiun-Shyan; Basava, Ramya Rao; Zhang, Yantao; Csapo, Robert; Malis, Vadim; Sinha, Usha; Hodgson, John; Sinha, Shantanu

2016-01-01

This paper introduces the meshfree Reproducing Kernel Particle Method (RKPM) for 3D image-based modeling of skeletal muscles. This approach allows for construction of simulation model based on pixel data obtained from medical images. The material properties and muscle fiber direction obtained from Diffusion Tensor Imaging (DTI) are input at each pixel point. The reproducing kernel (RK) approximation allows a representation of material heterogeneity with smooth transition. A multiphase multichannel level set based segmentation framework is adopted for individual muscle segmentation using Magnetic Resonance Images (MRI) and DTI. The application of the proposed methods for modeling the human lower leg is demonstrated.

Correlation between the model accuracy and model-based SOC estimation

International Nuclear Information System (INIS)

Wang, Qianqian; Wang, Jiao; Zhao, Pengju; Kang, Jianqiang; Yan, Few; Du, Changqing

2017-01-01

State-of-charge (SOC) estimation is a core technology for battery management systems. Considerable progress has been achieved in the study of SOC estimation algorithms, especially the algorithm on the basis of Kalman filter to meet the increasing demand of model-based battery management systems. The Kalman filter weakens the influence of white noise and initial error during SOC estimation but cannot eliminate the existing error of the battery model itself. As such, the accuracy of SOC estimation is directly related to the accuracy of the battery model. Thus far, the quantitative relationship between model accuracy and model-based SOC estimation remains unknown. This study summarizes three equivalent circuit lithium-ion battery models, namely, Thevenin, PNGV, and DP models. The model parameters are identified through hybrid pulse power characterization test. The three models are evaluated, and SOC estimation conducted by EKF-Ah method under three operating conditions are quantitatively studied. The regression and correlation of the standard deviation and normalized RMSE are studied and compared between the model error and the SOC estimation error. These parameters exhibit a strong linear relationship. Results indicate that the model accuracy affects the SOC estimation accuracy mainly in two ways: dispersion of the frequency distribution of the error and the overall level of the error. On the basis of the relationship between model error and SOC estimation error, our study provides a strategy for selecting a suitable cell model to meet the requirements of SOC precision using Kalman filter.

3-D model-based vehicle tracking.

Science.gov (United States)

Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J

2005-10-01

This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter.

Long-Term Urban Growth and Land Use Efficiency in Southern Europe: Implications for Sustainable Land Management

Directory of Open Access Journals (Sweden)

Marco Zitti

2015-03-01

Full Text Available The present study illustrates a multidimensional analysis of an indicator of urban land use efficiency (per-capita built-up area, LUE in mainland Attica, a Mediterranean urban region, along different expansion waves (1960–2010: compaction and densification in the 1960s, dispersed growth along the coasts and on Athens’ fringe in the 1970s, fringe consolidation in the 1980s, moderate re-polarization and discontinuous expansion in the 1990s and sprawl in remote areas in the 2000s. The non-linear trend in LUE (a continuous increase up to the 1980s and a moderate decrease in 1990 and 2000 preceding the rise observed over the last decade reflects Athens’ expansion waves. A total of 23 indicators were collected by decade for each municipality of the study area with the aim of identifying the drivers of land use efficiency. In 1960, municipalities with low efficiency in the use of land were concentrated on both coastal areas and Athens’ fringe, while in 2010, the lowest efficiency rate was observed in the most remote, rural areas. Typical urban functions (e.g., mixed land uses, multiple-use buildings, vertical profile are the variables most associated with high efficiency in the use of land. Policies for sustainable land management should consider local and regional factors shaping land use efficiency promoting self-contained expansion and more tightly protecting rural and remote land from dispersed urbanization. LUE is a promising indicator reflecting the increased complexity of growth patterns and may anticipate future urban trends.

Sandboxes for Model-Based Inquiry

Science.gov (United States)

Brady, Corey; Holbert, Nathan; Soylu, Firat; Novak, Michael; Wilensky, Uri

2015-04-01

In this article, we introduce a class of constructionist learning environments that we call Emergent Systems Sandboxes ( ESSs), which have served as a centerpiece of our recent work in developing curriculum to support scalable model-based learning in classroom settings. ESSs are a carefully specified form of virtual construction environment that support students in creating, exploring, and sharing computational models of dynamic systems that exhibit emergent phenomena. They provide learners with "entity"-level construction primitives that reflect an underlying scientific model. These primitives can be directly "painted" into a sandbox space, where they can then be combined, arranged, and manipulated to construct complex systems and explore the emergent properties of those systems. We argue that ESSs offer a means of addressing some of the key barriers to adopting rich, constructionist model-based inquiry approaches in science classrooms at scale. Situating the ESS in a large-scale science modeling curriculum we are implementing across the USA, we describe how the unique "entity-level" primitive design of an ESS facilitates knowledge system refinement at both an individual and social level, we describe how it supports flexible modeling practices by providing both continuous and discrete modes of executability, and we illustrate how it offers students a variety of opportunities for validating their qualitative understandings of emergent systems as they develop.

Dynamic modeling method for infrared smoke based on enhanced discrete phase model

Science.gov (United States)

Zhang, Zhendong; Yang, Chunling; Zhang, Yan; Zhu, Hongbo

2018-03-01

The dynamic modeling of infrared (IR) smoke plays an important role in IR scene simulation systems and its accuracy directly influences the system veracity. However, current IR smoke models cannot provide high veracity, because certain physical characteristics are frequently ignored in fluid simulation; simplifying the discrete phase as a continuous phase and ignoring the IR decoy missile-body spinning. To address this defect, this paper proposes a dynamic modeling method for IR smoke, based on an enhanced discrete phase model (DPM). A mathematical simulation model based on an enhanced DPM is built and a dynamic computing fluid mesh is generated. The dynamic model of IR smoke is then established using an extended equivalent-blackbody-molecule model. Experiments demonstrate that this model realizes a dynamic method for modeling IR smoke with higher veracity.

Ratio-based vs. model-based methods to correct for urinary creatinine concentrations.

Science.gov (United States)

Jain, Ram B

2016-08-01

Creatinine-corrected urinary analyte concentration is usually computed as the ratio of the observed level of analyte concentration divided by the observed level of the urinary creatinine concentration (UCR). This ratio-based method is flawed since it implicitly assumes that hydration is the only factor that affects urinary creatinine concentrations. On the contrary, it has been shown in the literature, that age, gender, race/ethnicity, and other factors also affect UCR. Consequently, an optimal method to correct for UCR should correct for hydration as well as other factors like age, gender, and race/ethnicity that affect UCR. Model-based creatinine correction in which observed UCRs are used as an independent variable in regression models has been proposed. This study was conducted to evaluate the performance of ratio-based and model-based creatinine correction methods when the effects of gender, age, and race/ethnicity are evaluated one factor at a time for selected urinary analytes and metabolites. It was observed that ratio-based method leads to statistically significant pairwise differences, for example, between males and females or between non-Hispanic whites (NHW) and non-Hispanic blacks (NHB), more often than the model-based method. However, depending upon the analyte of interest, the reverse is also possible. The estimated ratios of geometric means (GM), for example, male to female or NHW to NHB, were also compared for the two methods. When estimated UCRs were higher for the group (for example, males) in the numerator of this ratio, these ratios were higher for the model-based method, for example, male to female ratio of GMs. When estimated UCR were lower for the group (for example, NHW) in the numerator of this ratio, these ratios were higher for the ratio-based method, for example, NHW to NHB ratio of GMs. Model-based method is the method of choice if all factors that affect UCR are to be accounted for.

Tensions and Luescher terms for (2+1)-dimensional k-strings from holographic models

International Nuclear Information System (INIS)

Doran, Christopher A.; Rodgers, Vincent G.J.; Stiffler, Kory; Zayas, Leopoldo A. Pando

2009-01-01

The leading term for the energy of a bound state of k-quarks and k-antiquarks is proportional to its separation L. These k-string configurations have a Luescher term associated with their quantum fluctuations which is typically a 1/L correction to the energy. We review the status of tensions and Luescher terms in the context of lattice gauge theory, Hamiltonian methods, and gauge/gravity correspondence. Furthermore we explore how different representations of the k-string manifest themselves in the gauge/gravity duality. We calculate the Luescher term for a strongly coupled SU(N) gauge theory in (2+1) dimensions using the gauge/gravity correspondence. Namely, we compute one-loop corrections to a probe D4-brane embedded in the Cvetic, Gibbons, Lue, and Pope supergravity background. We investigate quantum fluctuations of both the bosonic and the fermionic sectors.

Agent Based Modeling Applications for Geosciences

Science.gov (United States)

Stein, J. S.

2004-12-01

Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in

Segment-based Eyring-Wilson viscosity model for polymer solutions

International Nuclear Information System (INIS)

Sadeghi, Rahmat

2005-01-01

A theory-based model is presented for correlating viscosity of polymer solutions and is based on the segment-based Eyring mixture viscosity model as well as the segment-based Wilson model for describing deviations from ideality. The model has been applied to several polymer solutions and the results show that it is reliable both for correlation and prediction of the viscosity of polymer solutions at different molar masses and temperature of the polymer

Language acquisition is model-based rather than model-free.

Science.gov (United States)

Wang, Felix Hao; Mintz, Toben H

2016-01-01

Christiansen & Chater (C&C) propose that learning language is learning to process language. However, we believe that the general-purpose prediction mechanism they propose is insufficient to account for many phenomena in language acquisition. We argue from theoretical considerations and empirical evidence that many acquisition tasks are model-based, and that different acquisition tasks require different, specialized models.

Drawing-Based Procedural Modeling of Chinese Architectures.

Science.gov (United States)

Fei Hou; Yue Qi; Hong Qin

2012-01-01

This paper presents a novel modeling framework to build 3D models of Chinese architectures from elevation drawing. Our algorithm integrates the capability of automatic drawing recognition with powerful procedural modeling to extract production rules from elevation drawing. First, different from the previous symbol-based floor plan recognition, based on the novel concept of repetitive pattern trees, small horizontal repetitive regions of the elevation drawing are clustered in a bottom-up manner to form architectural components with maximum repetition, which collectively serve as building blocks for 3D model generation. Second, to discover the global architectural structure and its components' interdependencies, the components are structured into a shape tree in a top-down subdivision manner and recognized hierarchically at each level of the shape tree based on Markov Random Fields (MRFs). Third, shape grammar rules can be derived to construct 3D semantic model and its possible variations with the help of a 3D component repository. The salient contribution lies in the novel integration of procedural modeling with elevation drawing, with a unique application to Chinese architectures.

Agent-based Modeling Methodology for Analyzing Weapons Systems

Science.gov (United States)

2015-03-26

technique involve model structure, system representation and the degree of validity, coupled with the simplicity, of the overall model. ABM is best suited... system representation of the air combat system . We feel that a simulation model that combines ABM with equation-based representation of weapons and...AGENT-BASED MODELING METHODOLOGY FOR ANALYZING WEAPONS SYSTEMS THESIS Casey D. Connors, Major, USA

Population PK modelling and simulation based on fluoxetine and norfluoxetine concentrations in milk: a milk concentration-based prediction model.

Science.gov (United States)

Tanoshima, Reo; Bournissen, Facundo Garcia; Tanigawara, Yusuke; Kristensen, Judith H; Taddio, Anna; Ilett, Kenneth F; Begg, Evan J; Wallach, Izhar; Ito, Shinya

2014-10-01

Population pharmacokinetic (pop PK) modelling can be used for PK assessment of drugs in breast milk. However, complex mechanistic modelling of a parent and an active metabolite using both blood and milk samples is challenging. We aimed to develop a simple predictive pop PK model for milk concentration-time profiles of a parent and a metabolite, using data on fluoxetine (FX) and its active metabolite, norfluoxetine (NFX), in milk. Using a previously published data set of drug concentrations in milk from 25 women treated with FX, a pop PK model predictive of milk concentration-time profiles of FX and NFX was developed. Simulation was performed with the model to generate FX and NFX concentration-time profiles in milk of 1000 mothers. This milk concentration-based pop PK model was compared with the previously validated plasma/milk concentration-based pop PK model of FX. Milk FX and NFX concentration-time profiles were described reasonably well by a one compartment model with a FX-to-NFX conversion coefficient. Median values of the simulated relative infant dose on a weight basis (sRID: weight-adjusted daily doses of FX and NFX through breastmilk to the infant, expressed as a fraction of therapeutic FX daily dose per body weight) were 0.028 for FX and 0.029 for NFX. The FX sRID estimates were consistent with those of the plasma/milk-based pop PK model. A predictive pop PK model based on only milk concentrations can be developed for simultaneous estimation of milk concentration-time profiles of a parent (FX) and an active metabolite (NFX). © 2014 The British Pharmacological Society.

GPU-accelerated 3-D model-based tracking

International Nuclear Information System (INIS)

Brown, J Anthony; Capson, David W

2010-01-01

Model-based approaches to tracking the pose of a 3-D object in video are effective but computationally demanding. While statistical estimation techniques, such as the particle filter, are often employed to minimize the search space, real-time performance remains unachievable on current generation CPUs. Recent advances in graphics processing units (GPUs) have brought massively parallel computational power to the desktop environment and powerful developer tools, such as NVIDIA Compute Unified Device Architecture (CUDA), have provided programmers with a mechanism to exploit it. NVIDIA GPUs' single-instruction multiple-thread (SIMT) programming model is well-suited to many computer vision tasks, particularly model-based tracking, which requires several hundred 3-D model poses to be dynamically configured, rendered, and evaluated against each frame in the video sequence. Using 6 degree-of-freedom (DOF) rigid hand tracking as an example application, this work harnesses consumer-grade GPUs to achieve real-time, 3-D model-based, markerless object tracking in monocular video.

Towards a standard model for research in agent-based modeling and simulation

Directory of Open Access Journals (Sweden)

Nuno Fachada

2015-11-01

Full Text Available Agent-based modeling (ABM is a bottom-up modeling approach, where each entity of the system being modeled is uniquely represented as an independent decision-making agent. ABMs are very sensitive to implementation details. Thus, it is very easy to inadvertently introduce changes which modify model dynamics. Such problems usually arise due to the lack of transparency in model descriptions, which constrains how models are assessed, implemented and replicated. In this paper, we present PPHPC, a model which aims to serve as a standard in agent based modeling research, namely, but not limited to, conceptual model specification, statistical analysis of simulation output, model comparison and parallelization studies. This paper focuses on the first two aspects (conceptual model specification and statistical analysis of simulation output, also providing a canonical implementation of PPHPC. The paper serves as a complete reference to the presented model, and can be used as a tutorial for simulation practitioners who wish to improve the way they communicate their ABMs.

Model-based Sensor Data Acquisition and Management

OpenAIRE

Aggarwal, Charu C.; Sathe, Saket; Papaioannou, Thanasis G.; Jeung, Ho Young; Aberer, Karl

2012-01-01

In recent years, due to the proliferation of sensor networks, there has been a genuine need of researching techniques for sensor data acquisition and management. To this end, a large number of techniques have emerged that advocate model-based sensor data acquisition and management. These techniques use mathematical models for performing various, day-to-day tasks involved in managing sensor data. In this chapter, we survey the state-of-the-art techniques for model-based sensor data acquisition...

INDIVIDUAL-BASED MODELS: POWERFUL OR POWER STRUGGLE?

Science.gov (United States)

Willem, L; Stijven, S; Hens, N; Vladislavleva, E; Broeckhove, J; Beutels, P

2015-01-01

Individual-based models (IBMs) offer endless possibilities to explore various research questions but come with high model complexity and computational burden. Large-scale IBMs have become feasible but the novel hardware architectures require adapted software. The increased model complexity also requires systematic exploration to gain thorough system understanding. We elaborate on the development of IBMs for vaccine-preventable infectious diseases and model exploration with active learning. Investment in IBM simulator code can lead to significant runtime reductions. We found large performance differences due to data locality. Sorting the population once, reduced simulation time by a factor two. Storing person attributes separately instead of using person objects also seemed more efficient. Next, we improved model performance up to 70% by structuring potential contacts based on health status before processing disease transmission. The active learning approach we present is based on iterative surrogate modelling and model-guided experimentation. Symbolic regression is used for nonlinear response surface modelling with automatic feature selection. We illustrate our approach using an IBM for influenza vaccination. After optimizing the parameter spade, we observed an inverse relationship between vaccination coverage and the clinical attack rate reinforced by herd immunity. These insights can be used to focus and optimise research activities, and to reduce both dimensionality and decision uncertainty.

Hybrid modelling framework by using mathematics-based and information-based methods

International Nuclear Information System (INIS)

Ghaboussi, J; Kim, J; Elnashai, A

2010-01-01

Mathematics-based computational mechanics involves idealization in going from the observed behaviour of a system into mathematical equations representing the underlying mechanics of that behaviour. Idealization may lead mathematical models that exclude certain aspects of the complex behaviour that may be significant. An alternative approach is data-centric modelling that constitutes a fundamental shift from mathematical equations to data that contain the required information about the underlying mechanics. However, purely data-centric methods often fail for infrequent events and large state changes. In this article, a new hybrid modelling framework is proposed to improve accuracy in simulation of real-world systems. In the hybrid framework, a mathematical model is complemented by information-based components. The role of informational components is to model aspects which the mathematical model leaves out. The missing aspects are extracted and identified through Autoprogressive Algorithms. The proposed hybrid modelling framework has a wide range of potential applications for natural and engineered systems. The potential of the hybrid methodology is illustrated through modelling highly pinched hysteretic behaviour of beam-to-column connections in steel frames.

Cluster Based Text Classification Model

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

2011-01-01

We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

Crowdsourcing Based 3d Modeling

Science.gov (United States)

Somogyi, A.; Barsi, A.; Molnar, B.; Lovas, T.

2016-06-01

Web-based photo albums that support organizing and viewing the users' images are widely used. These services provide a convenient solution for storing, editing and sharing images. In many cases, the users attach geotags to the images in order to enable using them e.g. in location based applications on social networks. Our paper discusses a procedure that collects open access images from a site frequently visited by tourists. Geotagged pictures showing the image of a sight or tourist attraction are selected and processed in photogrammetric processing software that produces the 3D model of the captured object. For the particular investigation we selected three attractions in Budapest. To assess the geometrical accuracy, we used laser scanner and DSLR as well as smart phone photography to derive reference values to enable verifying the spatial model obtained from the web-album images. The investigation shows how detailed and accurate models could be derived applying photogrammetric processing software, simply by using images of the community, without visiting the site.

Evolutionary modeling-based approach for model errors correction

Directory of Open Access Journals (Sweden)

S. Q. Wan

2012-08-01

Full Text Available The inverse problem of using the information of historical data to estimate model errors is one of the science frontier research topics. In this study, we investigate such a problem using the classic Lorenz (1963 equation as a prediction model and the Lorenz equation with a periodic evolutionary function as an accurate representation of reality to generate "observational data."

On the basis of the intelligent features of evolutionary modeling (EM, including self-organization, self-adaptive and self-learning, the dynamic information contained in the historical data can be identified and extracted by computer automatically. Thereby, a new approach is proposed to estimate model errors based on EM in the present paper. Numerical tests demonstrate the ability of the new approach to correct model structural errors. In fact, it can actualize the combination of the statistics and dynamics to certain extent.

Model-Based Reconstructive Elasticity Imaging Using Ultrasound

Directory of Open Access Journals (Sweden)

Salavat R. Aglyamov

2007-01-01

Full Text Available Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.

System Dynamics as Model-Based Theory Building

OpenAIRE

Schwaninger, Markus; Grösser, Stefan N.

2008-01-01

This paper introduces model-based theory building as a feature of system dynamics (SD) with large potential. It presents a systemic approach to actualizing that potential, thereby opening up a new perspective on theory building in the social sciences. The question addressed is if and how SD enables the construction of high-quality theories. This contribution is based on field experiment type projects which have been focused on model-based theory building, specifically the construction of a mi...

Search-based model identification of smart-structure damage

Science.gov (United States)

Glass, B. J.; Macalou, A.

1991-01-01

This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

Research on Turbofan Engine Model above Idle State Based on NARX Modeling Approach

Science.gov (United States)

Yu, Bing; Shu, Wenjun

2017-03-01

The nonlinear model for turbofan engine above idle state based on NARX is studied. Above all, the data sets for the JT9D engine from existing model are obtained via simulation. Then, a nonlinear modeling scheme based on NARX is proposed and several models with different parameters are built according to the former data sets. Finally, the simulations have been taken to verify the precise and dynamic performance the models, the results show that the NARX model can well reflect the dynamics characteristic of the turbofan engine with high accuracy.

Linking agent-based models and stochastic models of financial markets.

Science.gov (United States)

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

2012-05-29

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

Variability in Dopamine Genes Dissociates Model-Based and Model-Free Reinforcement Learning.

Science.gov (United States)

Doll, Bradley B; Bath, Kevin G; Daw, Nathaniel D; Frank, Michael J

2016-01-27

Considerable evidence suggests that multiple learning systems can drive behavior. Choice can proceed reflexively from previous actions and their associated outcomes, as captured by "model-free" learning algorithms, or flexibly from prospective consideration of outcomes that might occur, as captured by "model-based" learning algorithms. However, differential contributions of dopamine to these systems are poorly understood. Dopamine is widely thought to support model-free learning by modulating plasticity in striatum. Model-based learning may also be affected by these striatal effects, or by other dopaminergic effects elsewhere, notably on prefrontal working memory function. Indeed, prominent demonstrations linking striatal dopamine to putatively model-free learning did not rule out model-based effects, whereas other studies have reported dopaminergic modulation of verifiably model-based learning, but without distinguishing a prefrontal versus striatal locus. To clarify the relationships between dopamine, neural systems, and learning strategies, we combine a genetic association approach in humans with two well-studied reinforcement learning tasks: one isolating model-based from model-free behavior and the other sensitive to key aspects of striatal plasticity. Prefrontal function was indexed by a polymorphism in the COMT gene, differences of which reflect dopamine levels in the prefrontal cortex. This polymorphism has been associated with differences in prefrontal activity and working memory. Striatal function was indexed by a gene coding for DARPP-32, which is densely expressed in the striatum where it is necessary for synaptic plasticity. We found evidence for our hypothesis that variations in prefrontal dopamine relate to model-based learning, whereas variations in striatal dopamine function relate to model-free learning. Decisions can stem reflexively from their previously associated outcomes or flexibly from deliberative consideration of potential choice outcomes

Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis.

Science.gov (United States)

Voulgarelis, Dimitrios; Velayudhan, Ajoy; Smith, Frank

2017-01-01

Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale. This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis. For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Simple Models for Model-based Portfolio Load Balancing Controller Synthesis

DEFF Research Database (Denmark)

Edlund, Kristian Skjoldborg; Mølbak, Tommy; Bendtsen, Jan Dimon

2010-01-01

of generation units existing in an electrical power supply network, for instance in model-based predictive control or declarative control schemes. We focus on the effectuators found in the Danish power system. In particular, the paper presents models for boiler load, district heating, condensate throttling...

Whole body acid-base modeling revisited.

Science.gov (United States)

Ring, Troels; Nielsen, Søren

2017-04-01

The textbook account of whole body acid-base balance in terms of endogenous acid production, renal net acid excretion, and gastrointestinal alkali absorption, which is the only comprehensive model around, has never been applied in clinical practice or been formally validated. To improve understanding of acid-base modeling, we managed to write up this conventional model as an expression solely on urine chemistry. Renal net acid excretion and endogenous acid production were already formulated in terms of urine chemistry, and we could from the literature also see gastrointestinal alkali absorption in terms of urine excretions. With a few assumptions it was possible to see that this expression of net acid balance was arithmetically identical to minus urine charge, whereby under the development of acidosis, urine was predicted to acquire a net negative charge. The literature already mentions unexplained negative urine charges so we scrutinized a series of seminal papers and confirmed empirically the theoretical prediction that observed urine charge did acquire negative charge as acidosis developed. Hence, we can conclude that the conventional model is problematic since it predicts what is physiologically impossible. Therefore, we need a new model for whole body acid-base balance, which does not have impossible implications. Furthermore, new experimental studies are needed to account for charge imbalance in urine under development of acidosis. Copyright © 2017 the American Physiological Society.

Developing a Physiologically-Based Pharmacokinetic Model Knowledgebase in Support of Provisional Model Construction

Science.gov (United States)

Grulke, Christopher M.; Chang, Daniel T.; Brooks, Raina D.; Leonard, Jeremy A.; Phillips, Martin B.; Hypes, Ethan D.; Fair, Matthew J.; Tornero-Velez, Rogelio; Johnson, Jeffre; Dary, Curtis C.; Tan, Yu-Mei

2016-01-01

Developing physiologically-based pharmacokinetic (PBPK) models for chemicals can be resource-intensive, as neither chemical-specific parameters nor in vivo pharmacokinetic data are easily available for model construction. Previously developed, well-parameterized, and thoroughly-vetted models can be a great resource for the construction of models pertaining to new chemicals. A PBPK knowledgebase was compiled and developed from existing PBPK-related articles and used to develop new models. From 2,039 PBPK-related articles published between 1977 and 2013, 307 unique chemicals were identified for use as the basis of our knowledgebase. Keywords related to species, gender, developmental stages, and organs were analyzed from the articles within the PBPK knowledgebase. A correlation matrix of the 307 chemicals in the PBPK knowledgebase was calculated based on pharmacokinetic-relevant molecular descriptors. Chemicals in the PBPK knowledgebase were ranked based on their correlation toward ethylbenzene and gefitinib. Next, multiple chemicals were selected to represent exact matches, close analogues, or non-analogues of the target case study chemicals. Parameters, equations, or experimental data relevant to existing models for these chemicals and their analogues were used to construct new models, and model predictions were compared to observed values. This compiled knowledgebase provides a chemical structure-based approach for identifying PBPK models relevant to other chemical entities. Using suitable correlation metrics, we demonstrated that models of chemical analogues in the PBPK knowledgebase can guide the construction of PBPK models for other chemicals. PMID:26871706

Model-Based Power Plant Master Control

Energy Technology Data Exchange (ETDEWEB)

Boman, Katarina; Thomas, Jean; Funkquist, Jonas

2010-08-15

The main goal of the project has been to evaluate the potential of a coordinated master control for a solid fuel power plant in terms of tracking capability, stability and robustness. The control strategy has been model-based predictive control (MPC) and the plant used in the case study has been the Vattenfall power plant Idbaecken in Nykoeping. A dynamic plant model based on nonlinear physical models was used to imitate the true plant in MATLAB/SIMULINK simulations. The basis for this model was already developed in previous Vattenfall internal projects, along with a simulation model of the existing control implementation with traditional PID controllers. The existing PID control is used as a reference performance, and it has been thoroughly studied and tuned in these previous Vattenfall internal projects. A turbine model was developed with characteristics based on the results of steady-state simulations of the plant using the software EBSILON. Using the derived model as a representative for the actual process, an MPC control strategy was developed using linearization and gain-scheduling. The control signal constraints (rate of change) and constraints on outputs were implemented to comply with plant constraints. After tuning the MPC control parameters, a number of simulation scenarios were performed to compare the MPC strategy with the existing PID control structure. The simulation scenarios also included cases highlighting the robustness properties of the MPC strategy. From the study, the main conclusions are: - The proposed Master MPC controller shows excellent set-point tracking performance even though the plant has strong interactions and non-linearity, and the controls and their rate of change are bounded. - The proposed Master MPC controller is robust, stable in the presence of disturbances and parameter variations. Even though the current study only considered a very small number of the possible disturbances and modelling errors, the considered cases are

Semi-active control of magnetorheological elastomer base isolation system utilising learning-based inverse model

Science.gov (United States)

Gu, Xiaoyu; Yu, Yang; Li, Jianchun; Li, Yancheng

2017-10-01

Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.

Mechanics and model-based control of advanced engineering systems

CERN Document Server

Irschik, Hans; Krommer, Michael

2014-01-01

Mechanics and Model-Based Control of Advanced Engineering Systems collects 32 contributions presented at the International Workshop on Advanced Dynamics and Model Based Control of Structures and Machines, which took place in St. Petersburg, Russia in July 2012. The workshop continued a series of international workshops, which started with a Japan-Austria Joint Workshop on Mechanics and Model Based Control of Smart Materials and Structures and a Russia-Austria Joint Workshop on Advanced Dynamics and Model Based Control of Structures and Machines. In the present volume, 10 full-length papers based on presentations from Russia, 9 from Austria, 8 from Japan, 3 from Italy, one from Germany and one from Taiwan are included, which represent the state of the art in the field of mechanics and model based control, with particular emphasis on the application of advanced structures and machines.

Evaluation of MODIS gross primary productivity for Africa using eddy covariance data

CSIR Research Space (South Africa)

Sjöström, M

2013-04-01

Full Text Available MOD17A2 provides operational gross primary production (GPP) data globally at 1 km spatial resolution and 8-day temporal resolution. MOD17A2 estimates GPP according to the light use efficiency (LUE) concept assuming a fixed maximum rate of carbon...

Approximation Algorithms for Model-Based Diagnosis

NARCIS (Netherlands)

Feldman, A.B.

2010-01-01

Model-based diagnosis is an area of abductive inference that uses a system model, together with observations about system behavior, to isolate sets of faulty components (diagnoses) that explain the observed behavior, according to some minimality criterion. This thesis presents greedy approximation

Random sampling or geostatistical modelling? Choosing between design-based and model-based sampling strategies for soil (with discussion)

NARCIS (Netherlands)

Brus, D.J.; Gruijter, de J.J.

1997-01-01

Classical sampling theory has been repeatedly identified with classical statistics which assumes that data are identically and independently distributed. This explains the switch of many soil scientists from design-based sampling strategies, based on classical sampling theory, to the model-based

Néron Models and Base Change

DEFF Research Database (Denmark)

Halle, Lars Halvard; Nicaise, Johannes

Presenting the first systematic treatment of the behavior of Néron models under ramified base change, this book can be read as an introduction to various subtle invariants and constructions related to Néron models of semi-abelian varieties, motivated by concrete research problems and complemented...... with explicit examples. Néron models of abelian and semi-abelian varieties have become an indispensable tool in algebraic and arithmetic geometry since Néron introduced them in his seminal 1964 paper. Applications range from the theory of heights in Diophantine geometry to Hodge theory. We focus specifically...... on Néron component groups, Edixhoven’s filtration and the base change conductor of Chai and Yu, and we study these invariants using various techniques such as models of curves, sheaves on Grothendieck sites and non-archimedean uniformization. We then apply our results to the study of motivic zeta functions...

Elastoplastic cup model for cement-based materials

Directory of Open Access Journals (Sweden)

Yan Zhang

2010-03-01

Full Text Available Based on experimental data obtained from triaxial tests and a hydrostatic test, a cup model was formulated. Two plastic mechanisms, respectively a deviatoric shearing and a pore collapse, are taken into account. This model also considers the influence of confining pressure. In this paper, the calibration of the model is detailed and numerical simulations of the main mechanical behavior of cement paste over a large range of stress are described, showing good agreement with experimental results. The case study shows that this cup model has extensive applicability for cement-based materials and other quasi-brittle and high-porosity materials in a complex stress state.

Towards Modeling False Memory With Computational Knowledge Bases.

Science.gov (United States)

Li, Justin; Kohanyi, Emma

2017-01-01

One challenge to creating realistic cognitive models of memory is the inability to account for the vast common-sense knowledge of human participants. Large computational knowledge bases such as WordNet and DBpedia may offer a solution to this problem but may pose other challenges. This paper explores some of these difficulties through a semantic network spreading activation model of the Deese-Roediger-McDermott false memory task. In three experiments, we show that these knowledge bases only capture a subset of human associations, while irrelevant information introduces noise and makes efficient modeling difficult. We conclude that the contents of these knowledge bases must be augmented and, more important, that the algorithms must be refined and optimized, before large knowledge bases can be widely used for cognitive modeling. Copyright © 2016 Cognitive Science Society, Inc.

Photo-production of (99)Mo/(99m)Tc with electron linear accelerator beam.

Science.gov (United States)

Avagyan, R; Avetisyan, A; Kerobyan, I; Dallakyan, R

2014-09-01

We report on the development of a relatively new method for the production of (99)Mo/(99m)Tc. The method involves the irradiation of natural molybdenum using high-intensity bremsstrahlung photons from the electron beam of the LUE50 linear electron accelerator located at the Yerevan Physics Institute (YerPhi). The production method has been developed and shown to be successful. The linear electron accelerator at YerPhi was upgraded to allow for significant increases of the beam intensity and spatial density. The LUE50 was also instrumented by a remote control system for ease of operation. We have developed and tested the (99m)Tc extraction from the irradiation of natural MoO3. This paper reports on the optimal conditions of our method of (99)Mo production. We show the success of this method with the production and separation of the first usable amounts of (99m)Tc. Copyright © 2014 Elsevier Inc. All rights reserved.

A technology path to tactical agent-based modeling

Science.gov (United States)

James, Alex; Hanratty, Timothy P.

2017-05-01

Wargaming is a process of thinking through and visualizing events that could occur during a possible course of action. Over the past 200 years, wargaming has matured into a set of formalized processes. One area of growing interest is the application of agent-based modeling. Agent-based modeling and its additional supporting technologies has potential to introduce a third-generation wargaming capability to the Army, creating a positive overmatch decision-making capability. In its simplest form, agent-based modeling is a computational technique that helps the modeler understand and simulate how the "whole of a system" responds to change over time. It provides a decentralized method of looking at situations where individual agents are instantiated within an environment, interact with each other, and empowered to make their own decisions. However, this technology is not without its own risks and limitations. This paper explores a technology roadmap, identifying research topics that could realize agent-based modeling within a tactical wargaming context.

Modeling potential Emerald Ash Borer spread through GIS/cell-based/gravity models with data bolstered by web-based inputs

Science.gov (United States)

Louis R. Iverson; Anantha M. Prasad; Davis Sydnor; Jonathan Bossenbroek; Mark W. Schwartz; Mark W. Schwartz

2006-01-01

We model the susceptibility and potential spread of the organism across the eastern United States and especially through Michigan and Ohio using Forest Inventory and Analysis (FIA) data. We are also developing a cell-based model for the potential spread of the organism. We have developed a web-based tool for public agencies and private individuals to enter the...

Model Based Analysis and Test Generation for Flight Software

Science.gov (United States)

Pasareanu, Corina S.; Schumann, Johann M.; Mehlitz, Peter C.; Lowry, Mike R.; Karsai, Gabor; Nine, Harmon; Neema, Sandeep

2009-01-01

We describe a framework for model-based analysis and test case generation in the context of a heterogeneous model-based development paradigm that uses and combines Math- Works and UML 2.0 models and the associated code generation tools. This paradigm poses novel challenges to analysis and test case generation that, to the best of our knowledge, have not been addressed before. The framework is based on a common intermediate representation for different modeling formalisms and leverages and extends model checking and symbolic execution tools for model analysis and test case generation, respectively. We discuss the application of our framework to software models for a NASA flight mission.

Abstracting event-based control models for high autonomy systems

Science.gov (United States)

Luh, Cheng-Jye; Zeigler, Bernard P.

1993-01-01

A high autonomy system needs many models on which to base control, management, design, and other interventions. These models differ in level of abstraction and in formalism. Concepts and tools are needed to organize the models into a coherent whole. The paper deals with the abstraction processes for systematic derivation of related models for use in event-based control. The multifaceted modeling methodology is briefly reviewed. The morphism concepts needed for application to model abstraction are described. A theory for supporting the construction of DEVS models needed for event-based control is then presented. An implemented morphism on the basis of this theory is also described.

LEARNING CREATIVE WRITING MODEL BASED ON NEUROLINGUISTIC PROGRAMMING

OpenAIRE

Rustan, Edhy

2017-01-01

The objectives of the study are to determine: (1) condition on learning creative writing at high school students in Makassar, (2) requirement of learning model in creative writing, (3) program planning and design model in ideal creative writing, (4) feasibility of model study based on creative writing in neurolinguistic programming, and (5) the effectiveness of the learning model based on creative writing in neurolinguisticprogramming.The method of this research uses research development of L...

Simulation-Based Internal Models for Safer Robots

Directory of Open Access Journals (Sweden)

Christian Blum

2018-01-01

Full Text Available In this paper, we explore the potential of mobile robots with simulation-based internal models for safety in highly dynamic environments. We propose a robot with a simulation of itself, other dynamic actors and its environment, inside itself. Operating in real time, this simulation-based internal model is able to look ahead and predict the consequences of both the robot’s own actions and those of the other dynamic actors in its vicinity. Hence, the robot continuously modifies its own actions in order to actively maintain its own safety while also achieving its goal. Inspired by the problem of how mobile robots could move quickly and safely through crowds of moving humans, we present experimental results which compare the performance of our internal simulation-based controller with a purely reactive approach as a proof-of-concept study for the practical use of simulation-based internal models.

A Full-Body Layered Deformable Model for Automatic Model-Based Gait Recognition

Science.gov (United States)

Lu, Haiping; Plataniotis, Konstantinos N.; Venetsanopoulos, Anastasios N.

2007-12-01

This paper proposes a full-body layered deformable model (LDM) inspired by manually labeled silhouettes for automatic model-based gait recognition from part-level gait dynamics in monocular video sequences. The LDM is defined for the fronto-parallel gait with 22 parameters describing the human body part shapes (widths and lengths) and dynamics (positions and orientations). There are four layers in the LDM and the limbs are deformable. Algorithms for LDM-based human body pose recovery are then developed to estimate the LDM parameters from both manually labeled and automatically extracted silhouettes, where the automatic silhouette extraction is through a coarse-to-fine localization and extraction procedure. The estimated LDM parameters are used for model-based gait recognition by employing the dynamic time warping for matching and adopting the combination scheme in AdaBoost.M2. While the existing model-based gait recognition approaches focus primarily on the lower limbs, the estimated LDM parameters enable us to study full-body model-based gait recognition by utilizing the dynamics of the upper limbs, the shoulders and the head as well. In the experiments, the LDM-based gait recognition is tested on gait sequences with differences in shoe-type, surface, carrying condition and time. The results demonstrate that the recognition performance benefits from not only the lower limb dynamics, but also the dynamics of the upper limbs, the shoulders and the head. In addition, the LDM can serve as an analysis tool for studying factors affecting the gait under various conditions.

Problem-Oriented Corporate Knowledge Base Models on the Case-Based Reasoning Approach Basis

Science.gov (United States)

Gluhih, I. N.; Akhmadulin, R. K.

2017-07-01

One of the urgent directions of efficiency enhancement of production processes and enterprises activities management is creation and use of corporate knowledge bases. The article suggests a concept of problem-oriented corporate knowledge bases (PO CKB), in which knowledge is arranged around possible problem situations and represents a tool for making and implementing decisions in such situations. For knowledge representation in PO CKB a case-based reasoning approach is encouraged to use. Under this approach, the content of a case as a knowledge base component has been defined; based on the situation tree a PO CKB knowledge model has been developed, in which the knowledge about typical situations as well as specific examples of situations and solutions have been represented. A generalized problem-oriented corporate knowledge base structural chart and possible modes of its operation have been suggested. The obtained models allow creating and using corporate knowledge bases for support of decision making and implementing, training, staff skill upgrading and analysis of the decisions taken. The universal interpretation of terms “situation” and “solution” adopted in the work allows using the suggested models to develop problem-oriented corporate knowledge bases in different subject domains. It has been suggested to use the developed models for making corporate knowledge bases of the enterprises that operate engineer systems and networks at large production facilities.

Agent-based modelling of cholera diffusion

NARCIS (Netherlands)

Augustijn-Beckers, Petronella; Doldersum, Tom; Useya, Juliana; Augustijn, Dionysius C.M.

2016-01-01

This paper introduces a spatially explicit agent-based simulation model for micro-scale cholera diffusion. The model simulates both an environmental reservoir of naturally occurring V.cholerae bacteria and hyperinfectious V. cholerae. Objective of the research is to test if runoff from open refuse

Embracing model-based designs for dose-finding trials.

Science.gov (United States)

Love, Sharon B; Brown, Sarah; Weir, Christopher J; Harbron, Chris; Yap, Christina; Gaschler-Markefski, Birgit; Matcham, James; Caffrey, Louise; McKevitt, Christopher; Clive, Sally; Craddock, Charlie; Spicer, James; Cornelius, Victoria

2017-07-25

Dose-finding trials are essential to drug development as they establish recommended doses for later-phase testing. We aim to motivate wider use of model-based designs for dose finding, such as the continual reassessment method (CRM). We carried out a literature review of dose-finding designs and conducted a survey to identify perceived barriers to their implementation. We describe the benefits of model-based designs (flexibility, superior operating characteristics, extended scope), their current uptake, and existing resources. The most prominent barriers to implementation of a model-based design were lack of suitable training, chief investigators' preference for algorithm-based designs (e.g., 3+3), and limited resources for study design before funding. We use a real-world example to illustrate how these barriers can be overcome. There is overwhelming evidence for the benefits of CRM. Many leading pharmaceutical companies routinely implement model-based designs. Our analysis identified barriers for academic statisticians and clinical academics in mirroring the progress industry has made in trial design. Unified support from funders, regulators, and journal editors could result in more accurate doses for later-phase testing, and increase the efficiency and success of clinical drug development. We give recommendations for increasing the uptake of model-based designs for dose-finding trials in academia.

New approaches in agent-based modeling of complex financial systems

Science.gov (United States)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

Strong Links Between Teleconnections and Ecosystem Exchange Found at a Pacific Northwest Old-Growth Forest from Flux Tower and MODIS EVI Data

Energy Technology Data Exchange (ETDEWEB)

Wharton, S; Chasmer, L; Falk, M; Paw U, K T

2009-03-12

Variability in three Pacific teleconnection patterns are examined to see if net carbon exchange at a low-elevation, old-growth forest is affected by climatic changes associated with these periodicities. Examined are the Pacific Decadal Oscillation (PDO), Pacific/North American Oscillation (PNA) and El Nino-Southern Oscillation (ENSO). We use nine years of eddy covariance CO{sub 2}, H{sub 2}O and energy fluxes measured at the Wind River AmeriFlux site, Washington, USA and eight years of tower-pixel remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to address this question. We compute a new Composite Climate Index (CCI) based on the three Pacific Oscillations to divide the measurement period into positive- (2003 and 2005), negative- (1999 and 2000) and neutral-phase climate years (2001, 2002, 2004, 2006 and 2007). The forest transitioned from an annual net carbon sink (NEP = + 217 g C m{sup -2} year{sup -1}, 1999) to a source (NEP = - 100 g C m{sup -2} year{sup -1}, 2003) during two dominant teleconnection patterns. Net ecosystem productivity (NEP), water use efficiency (WUE) and light use efficiency (LUE) were significantly different (P < 0.01) during positive (NEP = -0.27 g C m{sup -2} day{sup -1}, WUE = 4.1 mg C/g H{sub 2}O, LUE = 0.94 g C MJ{sup -1}) and negative (NEP = +0.37 g C m{sup -2} day{sup -1}, WUE = 3.4 mg C/g H{sub 2}O, LUE = 0.83 g C MJ{sup -1}) climate phases. The CCI was linked to variability in the MODIS Enhanced Vegetation Index (EVI) but not to MODIS Fraction of absorbed Photosynthetically Active Radiation (FPAR). EVI was highest during negative climate phases (1999 and 2000) and was positively correlated with NEP and showed potential for using MODIS to estimate teleconnection-driven anomalies in ecosystem CO{sub 2} exchange in old-growth forests. This work suggests that any increase in the strength or frequency of ENSO coinciding with in-phase, low frequency Pacific oscillations (PDO and PNA) will likely increase

Impact of Nitrogen Fertilization on Forest Carbon Sequestration and Water Loss in a Chronosequence of Three Douglas-Fir Stands in the Pacific Northwest

Directory of Open Access Journals (Sweden)

Xianming Dou

2015-05-01

Full Text Available To examine the effect of nitrogen (N fertilization on forest carbon (C sequestration and water loss, we used an artificial neural network model to estimate C fluxes and evapotranspiration (ET in response to N fertilization during four post-fertilization years in a Pacific Northwest chronosequence of three Douglas-fir stands aged 61, 22 and 10 years old in 2010 (DF49, HDF88 and HDF00, respectively. Results showed that N fertilization increased gross primary productivity (GPP for all three sites in all four years with the largest absolute increase at HDF00 followed by HDF88. Ecosystem respiration increased in all four years at HDF00, but decreased over the last three years at HDF88 and over all four years at DF49. As a result, fertilization increased the net ecosystem productivity of all three stands with the largest increase at HDF88, followed by DF49. Fertilization had no discernible effect on ET in any of the stands. Consequently, fertilization increased water use efficiency (WUE in all four post-fertilization years at all three sites and also increased light use efficiency (LUE of all the stands, especially HDF00. Our results suggest that the effects of fertilization on forest C sequestration and water loss may be associated with stand age and fertilization; the two younger stands appeared to be more efficient than the older stand with respect to GPP, WUE and LUE.

SEP modeling based on global heliospheric models at the CCMC

Science.gov (United States)

Mays, M. L.; Luhmann, J. G.; Odstrcil, D.; Bain, H. M.; Schwadron, N.; Gorby, M.; Li, Y.; Lee, K.; Zeitlin, C.; Jian, L. K.; Lee, C. O.; Mewaldt, R. A.; Galvin, A. B.

2017-12-01

Heliospheric models provide contextual information of conditions in the heliosphere, including the background solar wind conditions and shock structures, and are used as input to SEP models, providing an essential tool for understanding SEP properties. The global 3D MHD WSA-ENLIL+Cone model provides a time-dependent background heliospheric description, into which a spherical shaped hydrodynamic CME can be inserted. ENLIL simulates solar wind parameters and additionally one can extract the magnetic topologies of observer-connected magnetic field lines and all plasma and shock properties along those field lines. An accurate representation of the background solar wind is necessary for simulating transients. ENLIL simulations also drive SEP models such as the Solar Energetic Particle Model (SEPMOD) (Luhmann et al. 2007, 2010) and the Energetic Particle Radiation Environment Module (EPREM) (Schwadron et al. 2010). The Community Coordinated Modeling Center (CCMC) is in the process of making these SEP models available to the community and offering a system to run SEP models driven by a variety of heliospheric models available at CCMC. SEPMOD injects protons onto a sequence of observer field lines at intensities dependent on the connected shock source strength which are then integrated at the observer to approximate the proton flux. EPREM couples with MHD models such as ENLIL and computes energetic particle distributions based on the focused transport equation along a Lagrangian grid of nodes that propagate out with the solar wind. The coupled SEP models allow us to derive the longitudinal distribution of SEP profiles of different types of events throughout the heliosphere. The coupled ENLIL and SEP models allow us to derive the longitudinal distribution of SEP profiles of different types of events throughout the heliosphere. In this presentation we demonstrate several case studies of SEP event modeling at different observers based on WSA-ENLIL+Cone simulations.

The evolution of process-based hydrologic models

NARCIS (Netherlands)

Clark, Martyn P.; Bierkens, Marc F.P.; Samaniego, Luis; Woods, Ross A.; Uijlenhoet, Remko; Bennett, Katrina E.; Pauwels, Valentijn R.N.; Cai, Xitian; Wood, Andrew W.; Peters-Lidard, Christa D.

2017-01-01

The diversity in hydrologic models has historically led to great controversy on the "correct" approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this

Modeling soft factors in computer-based wargames

Science.gov (United States)

Alexander, Steven M.; Ross, David O.; Vinarskai, Jonathan S.; Farr, Steven D.

2002-07-01

Computer-based wargames have seen much improvement in recent years due to rapid increases in computing power. Because these games have been developed for the entertainment industry, most of these advances have centered on the graphics, sound, and user interfaces integrated into these wargames with less attention paid to the game's fidelity. However, for a wargame to be useful to the military, it must closely approximate as many of the elements of war as possible. Among the elements that are typically not modeled or are poorly modeled in nearly all military computer-based wargames are systematic effects, command and control, intelligence, morale, training, and other human and political factors. These aspects of war, with the possible exception of systematic effects, are individually modeled quite well in many board-based commercial wargames. The work described in this paper focuses on incorporating these elements from the board-based games into a computer-based wargame. This paper will also address the modeling and simulation of the systemic paralysis of an adversary that is implied by the concept of Effects Based Operations (EBO). Combining the fidelity of current commercial board wargames with the speed, ease of use, and advanced visualization of the computer can significantly improve the effectiveness of military decision making and education. Once in place, the process of converting board wargames concepts to computer wargames will allow the infusion of soft factors into military training and planning.

Evaluating Water Demand Using Agent-Based Modeling

Science.gov (United States)

Lowry, T. S.

2004-12-01

The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage

CROWDSOURCING BASED 3D MODELING

Directory of Open Access Journals (Sweden)

A. Somogyi

2016-06-01

Full Text Available Web-based photo albums that support organizing and viewing the users’ images are widely used. These services provide a convenient solution for storing, editing and sharing images. In many cases, the users attach geotags to the images in order to enable using them e.g. in location based applications on social networks. Our paper discusses a procedure that collects open access images from a site frequently visited by tourists. Geotagged pictures showing the image of a sight or tourist attraction are selected and processed in photogrammetric processing software that produces the 3D model of the captured object. For the particular investigation we selected three attractions in Budapest. To assess the geometrical accuracy, we used laser scanner and DSLR as well as smart phone photography to derive reference values to enable verifying the spatial model obtained from the web-album images. The investigation shows how detailed and accurate models could be derived applying photogrammetric processing software, simply by using images of the community, without visiting the site.

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

Science.gov (United States)

Xiang, Lin

2011-01-01

This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

Nonlinear system modeling based on bilinear Laguerre orthonormal bases.

Science.gov (United States)

Garna, Tarek; Bouzrara, Kais; Ragot, José; Messaoud, Hassani

2013-05-01

This paper proposes a new representation of discrete bilinear model by developing its coefficients associated to the input, to the output and to the crossed product on three independent Laguerre orthonormal bases. Compared to classical bilinear model, the resulting model entitled bilinear-Laguerre model ensures a significant parameter number reduction as well as simple recursive representation. However, such reduction still constrained by an optimal choice of Laguerre pole characterizing each basis. To do so, we develop a pole optimization algorithm which constitutes an extension of that proposed by Tanguy et al.. The bilinear-Laguerre model as well as the proposed pole optimization algorithm are illustrated and tested on a numerical simulations and validated on the Continuous Stirred Tank Reactor (CSTR) System. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Modeling base excision repair in Escherichia coli bacterial cells

International Nuclear Information System (INIS)

Belov, O.V.

2011-01-01

A model describing the key processes in Escherichia coli bacterial cells during base excision repair is developed. The mechanism is modeled of damaged base elimination involving formamidopyrimidine DNA glycosylase (the Fpg protein), which possesses several types of activities. The modeling of the transitions between DNA states is based on a stochastic approach to the chemical reaction description

The fractional volatility model: An agent-based interpretation

Science.gov (United States)

Vilela Mendes, R.

2008-06-01

Based on the criteria of mathematical simplicity and consistency with empirical market data, a model with volatility driven by fractional noise has been constructed which provides a fairly accurate mathematical parametrization of the data. Here, some features of the model are reviewed and extended to account for leverage effects. Using agent-based models, one tries to find which agent strategies and (or) properties of the financial institutions might be responsible for the features of the fractional volatility model.

Néron models and base change

CERN Document Server

Halle, Lars Halvard

2016-01-01

Presenting the first systematic treatment of the behavior of Néron models under ramified base change, this book can be read as an introduction to various subtle invariants and constructions related to Néron models of semi-abelian varieties, motivated by concrete research problems and complemented with explicit examples. Néron models of abelian and semi-abelian varieties have become an indispensable tool in algebraic and arithmetic geometry since Néron introduced them in his seminal 1964 paper. Applications range from the theory of heights in Diophantine geometry to Hodge theory. We focus specifically on Néron component groups, Edixhoven’s filtration and the base change conductor of Chai and Yu, and we study these invariants using various techniques such as models of curves, sheaves on Grothendieck sites and non-archimedean uniformization. We then apply our results to the study of motivic zeta functions of abelian varieties. The final chapter contains a list of challenging open questions. This book is a...

Inference-based procedural modeling of solids

KAUST Repository

Biggers, Keith

2011-11-01

As virtual environments become larger and more complex, there is an increasing need for more automated construction algorithms to support the development process. We present an approach for modeling solids by combining prior examples with a simple sketch. Our algorithm uses an inference-based approach to incrementally fit patches together in a consistent fashion to define the boundary of an object. This algorithm samples and extracts surface patches from input models, and develops a Petri net structure that describes the relationship between patches along an imposed parameterization. Then, given a new parameterized line or curve, we use the Petri net to logically fit patches together in a manner consistent with the input model. This allows us to easily construct objects of varying sizes and configurations using arbitrary articulation, repetition, and interchanging of parts. The result of our process is a solid model representation of the constructed object that can be integrated into a simulation-based environment. © 2011 Elsevier Ltd. All rights reserved.

A Coupled Simulation Architecture for Agent-Based/Geohydrological Modelling

Science.gov (United States)

Jaxa-Rozen, M.

2016-12-01

The quantitative modelling of social-ecological systems can provide useful insights into the interplay between social and environmental processes, and their impact on emergent system dynamics. However, such models should acknowledge the complexity and uncertainty of both of the underlying subsystems. For instance, the agent-based models which are increasingly popular for groundwater management studies can be made more useful by directly accounting for the hydrological processes which drive environmental outcomes. Conversely, conventional environmental models can benefit from an agent-based depiction of the feedbacks and heuristics which influence the decisions of groundwater users. From this perspective, this work describes a Python-based software architecture which couples the popular NetLogo agent-based platform with the MODFLOW/SEAWAT geohydrological modelling environment. This approach enables users to implement agent-based models in NetLogo's user-friendly platform, while benefiting from the full capabilities of MODFLOW/SEAWAT packages or reusing existing geohydrological models. The software architecture is based on the pyNetLogo connector, which provides an interface between the NetLogo agent-based modelling software and the Python programming language. This functionality is then extended and combined with Python's object-oriented features, to design a simulation architecture which couples NetLogo with MODFLOW/SEAWAT through the FloPy library (Bakker et al., 2016). The Python programming language also provides access to a range of external packages which can be used for testing and analysing the coupled models, which is illustrated for an application of Aquifer Thermal Energy Storage (ATES).

Model-based Clustering of High-Dimensional Data in Astrophysics

Science.gov (United States)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

Fuzzy rule-based model for hydropower reservoirs operation

Energy Technology Data Exchange (ETDEWEB)

Moeini, R.; Afshar, A.; Afshar, M.H. [School of Civil Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)

2011-02-15

Real-time hydropower reservoir operation is a continuous decision-making process of determining the water level of a reservoir or the volume of water released from it. The hydropower operation is usually based on operating policies and rules defined and decided upon in strategic planning. This paper presents a fuzzy rule-based model for the operation of hydropower reservoirs. The proposed fuzzy rule-based model presents a set of suitable operating rules for release from the reservoir based on ideal or target storage levels. The model operates on an 'if-then' principle, in which the 'if' is a vector of fuzzy premises and the 'then' is a vector of fuzzy consequences. In this paper, reservoir storage, inflow, and period are used as premises and the release as the consequence. The steps involved in the development of the model include, construction of membership functions for the inflow, storage and the release, formulation of fuzzy rules, implication, aggregation and defuzzification. The required knowledge bases for the formulation of the fuzzy rules is obtained form a stochastic dynamic programming (SDP) model with a steady state policy. The proposed model is applied to the hydropower operation of ''Dez'' reservoir in Iran and the results are presented and compared with those of the SDP model. The results indicate the ability of the method to solve hydropower reservoir operation problems. (author)

A General Attribute and Rule Based Role-Based Access Control Model

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Growing numbers of users and many access control policies which involve many different resource attributes in service-oriented environments bring various problems in protecting resource. This paper analyzes the relationships of resource attributes to user attributes in all policies, and propose a general attribute and rule based role-based access control(GAR-RBAC) model to meet the security needs. The model can dynamically assign users to roles via rules to meet the need of growing numbers of users. These rules use different attribute expression and permission as a part of authorization constraints, and are defined by analyzing relations of resource attributes to user attributes in many access policies that are defined by the enterprise. The model is a general access control model, and can support many access control policies, and also can be used to wider application for service. The paper also describes how to use the GAR-RBAC model in Web service environments.

Improving Agent Based Modeling of Critical Incidents

Directory of Open Access Journals (Sweden)

Robert Till

2010-04-01

Full Text Available Agent Based Modeling (ABM is a powerful method that has been used to simulate potential critical incidents in the infrastructure and built environments. This paper will discuss the modeling of some critical incidents currently simulated using ABM and how they may be expanded and improved by using better physiological modeling, psychological modeling, modeling the actions of interveners, introducing Geographic Information Systems (GIS and open source models.

Model-based testing for software safety

NARCIS (Netherlands)

Gurbuz, Havva Gulay; Tekinerdogan, Bedir

2017-01-01

Testing safety-critical systems is crucial since a failure or malfunction may result in death or serious injuries to people, equipment, or environment. An important challenge in testing is the derivation of test cases that can identify the potential faults. Model-based testing adopts models of a

A standard protocol for describing individual-based and agent-based models

Science.gov (United States)

Grimm, Volker; Berger, Uta; Bastiansen, Finn; Eliassen, Sigrunn; Ginot, Vincent; Giske, Jarl; Goss-Custard, John; Grand, Tamara; Heinz, Simone K.; Huse, Geir; Huth, Andreas; Jepsen, Jane U.; Jorgensen, Christian; Mooij, Wolf M.; Muller, Birgit; Pe'er, Guy; Piou, Cyril; Railsback, Steven F.; Robbins, Andrew M.; Robbins, Martha M.; Rossmanith, Eva; Ruger, Nadja; Strand, Espen; Souissi, Sami; Stillman, Richard A.; Vabo, Rune; Visser, Ute; DeAngelis, Donald L.

2006-01-01

Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.

A subchannel based annular flow dryout model

International Nuclear Information System (INIS)

Hammouda, Najmeddine; Cheng, Zhong; Rao, Yanfei F.

2016-01-01

Highlights: • A modified annular flow dryout model for subchannel thermalhydraulic analysis. • Implementation of the model in Canadian subchannel code ASSERT-PV. • Assessment of the model against tube CHF experiments. • Assessment of the model against CANDU-bundle CHF experiments. - Abstract: This paper assesses a popular tube-based mechanistic critical heat flux model (Hewitt and Govan’s annular flow model (based on the model of Whalley et al.), and modifies and implements the model for bundle geometries. It describes the results of the ASSERT subchannel code predictions using the modified model, as applied to a single tube and the 28-element, 37-element and 43-element (CANFLEX) CANDU bundles. A quantitative comparison between the model predictions and experimental data indicates good agreement for a wide range of flow conditions. The comparison has resulted in an overall average error of −0.15% and an overall root-mean-square error of 5.46% with tube data representing annular film dryout type critical heat flux, and in an overall average error of −0.9% and an overall RMS error of 9.9% with Stern Laboratories’ CANDU-bundle data.

Evaluation of MODIS gross primary productivity for Africa using eddy covariance data

NARCIS (Netherlands)

Sjostrom, M.; Zhao, M.; Archibald, S.; Veenendaal, E.M.

2013-01-01

MOD17A2 provides operational gross primary production (GPP) data globally at 1 km spatial resolution and 8-day temporal resolution. MOD17A2 estimates GPP according to the light use efficiency (LUE) concept assuming a fixed maximum rate of carbon assimilation per unit photosynthetically active

Opinion dynamics model based on quantum formalism

Energy Technology Data Exchange (ETDEWEB)

Artawan, I. Nengah, E-mail: nengahartawan@gmail.com [Theoretical Physics Division, Department of Physics, Udayana University (Indonesia); Trisnawati, N. L. P., E-mail: nlptrisnawati@gmail.com [Biophysics, Department of Physics, Udayana University (Indonesia)

2016-03-11

Opinion dynamics model based on quantum formalism is proposed. The core of the quantum formalism is on the half spin dynamics system. In this research the implicit time evolution operators are derived. The analogy between the model with Deffuant dan Sznajd models is discussed.

Model-based testing for embedded systems

CERN Document Server

Zander, Justyna; Mosterman, Pieter J

2011-01-01

What the experts have to say about Model-Based Testing for Embedded Systems: "This book is exactly what is needed at the exact right time in this fast-growing area. From its beginnings over 10 years ago of deriving tests from UML statecharts, model-based testing has matured into a topic with both breadth and depth. Testing embedded systems is a natural application of MBT, and this book hits the nail exactly on the head. Numerous topics are presented clearly, thoroughly, and concisely in this cutting-edge book. The authors are world-class leading experts in this area and teach us well-used

Intelligent model-based diagnostics for vehicle health management

Science.gov (United States)

Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

2003-08-01

The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

Process-Based Modeling of Constructed Wetlands

Science.gov (United States)

Baechler, S.; Brovelli, A.; Rossi, L.; Barry, D. A.

2007-12-01

Constructed wetlands (CWs) are widespread facilities for wastewater treatment. In subsurface flow wetlands, contaminated wastewater flows through a porous matrix, where oxidation and detoxification phenomena occur. Despite the large number of working CWs, system design and optimization are still mainly based upon empirical equations or simplified first-order kinetics. This results from an incomplete understanding of the system functioning, and may in turn hinder the performance and effectiveness of the treatment process. As a result, CWs are often considered not suitable to meet high water quality-standards, or to treat water contaminated with recalcitrant anthropogenic contaminants. To date, only a limited number of detailed numerical models have been developed and successfully applied to simulate constructed wetland behavior. Among these, one of the most complete and powerful is CW2D, which is based on Hydrus2D. The aim of this work is to develop a comprehensive simulator tailored to model the functioning of horizontal flow constructed wetlands and in turn provide a reliable design and optimization tool. The model is based upon PHWAT, a general reactive transport code for saturated flow. PHWAT couples MODFLOW, MT3DMS and PHREEQC-2 using an operator-splitting approach. The use of PHREEQC to simulate reactions allows great flexibility in simulating biogeochemical processes. The biogeochemical reaction network is similar to that of CW2D, and is based on the Activated Sludge Model (ASM). Kinetic oxidation of carbon sources and nutrient transformations (nitrogen and phosphorous primarily) are modeled via Monod-type kinetic equations. Oxygen dissolution is accounted for via a first-order mass-transfer equation. While the ASM model only includes a limited number of kinetic equations, the new simulator permits incorporation of an unlimited number of both kinetic and equilibrium reactions. Changes in pH, redox potential and surface reactions can be easily incorporated

Models for the field-based toxicity of copper and zinc salts to wheat in 11 Australian soils and comparison to laboratory-based models

International Nuclear Information System (INIS)

Warne, Michael St.J.; Heemsbergen, Diane; McLaughlin, Mike; Bell, Mike; Broos, Kris; Whatmuff, Mark; Barry, Glenn; Nash, David; Pritchard, Deb; Penney, Nancy

2008-01-01

Laboratory-based relationships that model the phytotoxicity of metals using soil properties have been developed. This paper presents the first field-based phytotoxicity relationships. Wheat (Triticum aestivum L.) was grown at 11 Australian field sites at which soil was spiked with copper (Cu) and zinc (Zn) salts. Toxicity was measured as inhibition of plant growth at 8 weeks and grain yield at harvest. The added Cu and Zn EC10 values for both endpoints ranged from approximately 3 to 4760 mg/kg. There were no relationships between field-based 8-week biomass and grain yield toxicity values for either metal. Cu toxicity was best modelled using pH and organic carbon content while Zn toxicity was best modelled using pH and the cation exchange capacity. The best relationships estimated toxicity within a factor of two of measured values. Laboratory-based phytotoxicity relationships could not accurately predict field-based phytotoxicity responses. - Field-based toxicity of Cu and Zn to wheat can be modelled using soil properties. Laboratory-based models should not be used to estimate toxicity in the field

Model based energy benchmarking for glass furnace

International Nuclear Information System (INIS)

Sardeshpande, Vishal; Gaitonde, U.N.; Banerjee, Rangan

2007-01-01

Energy benchmarking of processes is important for setting energy efficiency targets and planning energy management strategies. Most approaches used for energy benchmarking are based on statistical methods by comparing with a sample of existing plants. This paper presents a model based approach for benchmarking of energy intensive industrial processes and illustrates this approach for industrial glass furnaces. A simulation model for a glass furnace is developed using mass and energy balances, and heat loss equations for the different zones and empirical equations based on operating practices. The model is checked with field data from end fired industrial glass furnaces in India. The simulation model enables calculation of the energy performance of a given furnace design. The model results show the potential for improvement and the impact of different operating and design preferences on specific energy consumption. A case study for a 100 TPD end fired furnace is presented. An achievable minimum energy consumption of about 3830 kJ/kg is estimated for this furnace. The useful heat carried by glass is about 53% of the heat supplied by the fuel. Actual furnaces operating at these production scales have a potential for reduction in energy consumption of about 20-25%

Thermodynamics-based models of transcriptional regulation with gene sequence.

Science.gov (United States)

Wang, Shuqiang; Shen, Yanyan; Hu, Jinxing

2015-12-01

Quantitative models of gene regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled or heuristic approximations of the underlying regulatory mechanisms. In this work, we have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence. The proposed model relies on a continuous time, differential equation description of transcriptional dynamics. The sequence features of the promoter are exploited to derive the binding affinity which is derived based on statistical molecular thermodynamics. Experimental results show that the proposed model can effectively identify the activity levels of transcription factors and the regulatory parameters. Comparing with the previous models, the proposed model can reveal more biological sense.

Comparing model-based and model-free analysis methods for QUASAR arterial spin labeling perfusion quantification.

Science.gov (United States)

Chappell, Michael A; Woolrich, Mark W; Petersen, Esben T; Golay, Xavier; Payne, Stephen J

2013-05-01

Amongst the various implementations of arterial spin labeling MRI methods for quantifying cerebral perfusion, the QUASAR method is unique. By using a combination of labeling with and without flow suppression gradients, the QUASAR method offers the separation of macrovascular and tissue signals. This permits local arterial input functions to be defined and "model-free" analysis, using numerical deconvolution, to be used. However, it remains unclear whether arterial spin labeling data are best treated using model-free or model-based analysis. This work provides a critical comparison of these two approaches for QUASAR arterial spin labeling in the healthy brain. An existing two-component (arterial and tissue) model was extended to the mixed flow suppression scheme of QUASAR to provide an optimal model-based analysis. The model-based analysis was extended to incorporate dispersion of the labeled bolus, generally regarded as the major source of discrepancy between the two analysis approaches. Model-free and model-based analyses were compared for perfusion quantification including absolute measurements, uncertainty estimation, and spatial variation in cerebral blood flow estimates. Major sources of discrepancies between model-free and model-based analysis were attributed to the effects of dispersion and the degree to which the two methods can separate macrovascular and tissue signal. Copyright © 2012 Wiley Periodicals, Inc.

Model-based monitoring of rotors with multiple coexisting faults

International Nuclear Information System (INIS)

Rossner, Markus

2015-01-01

Monitoring systems are applied to many rotors, but only few monitoring systems can separate coexisting errors and identify their quantity. This research project solves this problem using a combination of signal-based and model-based monitoring. The signal-based part performs a pre-selection of possible errors; these errors are further separated with model-based methods. This approach is demonstrated for the errors unbalance, bow, stator-fixed misalignment, rotor-fixed misalignment and roundness errors. For the model-based part, unambiguous error definitions and models are set up. The Ritz approach reduces the model order and therefore speeds up the diagnosis. Identification algorithms are developed for the different rotor faults. Hereto, reliable damage indicators and proper sub steps of the diagnosis have to be defined. For several monitoring problems, measuring both deflection and bearing force is very useful. The monitoring system is verified by experiments on an academic rotor test rig. The interpretation of the measurements requires much knowledge concerning the dynamics of the rotor. Due to the model-based approach, the system can separate errors with similar signal patterns and identify bow and roundness error online at operation speed. [de

Pixel-based meshfree modelling of skeletal muscles

OpenAIRE

Chen, Jiun-Shyan; Basava, Ramya Rao; Zhang, Yantao; Csapo, Robert; Malis, Vadim; Sinha, Usha; Hodgson, John; Sinha, Shantanu

2015-01-01

This paper introduces the meshfree Reproducing Kernel Particle Method (RKPM) for 3D image-based modeling of skeletal muscles. This approach allows for construction of simulation model based on pixel data obtained from medical images. The material properties and muscle fiber direction obtained from Diffusion Tensor Imaging (DTI) are input at each pixel point. The reproducing kernel (RK) approximation allows a representation of material heterogeneity with smooth transition. A ...

A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

Science.gov (United States)

Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

2005-01-01

Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

Surrogate-Based Optimization of Biogeochemical Transport Models

Science.gov (United States)

Prieß, Malte; Slawig, Thomas

2010-09-01

First approaches towards a surrogate-based optimization method for a one-dimensional marine biogeochemical model of NPZD type are presented. The model, developed by Oschlies and Garcon [1], simulates the distribution of nitrogen, phytoplankton, zooplankton and detritus in a water column and is driven by ocean circulation data. A key issue is to minimize the misfit between the model output and given observational data. Our aim is to reduce the overall optimization cost avoiding expensive function and derivative evaluations by using a surrogate model replacing the high-fidelity model in focus. This in particular becomes important for more complex three-dimensional models. We analyse a coarsening in the discretization of the model equations as one way to create such a surrogate. Here the numerical stability crucially depends upon the discrete stepsize in time and space and the biochemical terms. We show that for given model parameters the level of grid coarsening can be choosen accordingly yielding a stable and satisfactory surrogate. As one example of a surrogate-based optimization method we present results of the Aggressive Space Mapping technique (developed by John W. Bandler [2, 3]) applied to the optimization of this one-dimensional biogeochemical transport model.

Structural Acoustic Physics Based Modeling of Curved Composite Shells

Science.gov (United States)

2017-09-19

NUWC-NPT Technical Report 12,236 19 September 2017 Structural Acoustic Physics -Based Modeling of Curved Composite Shells Rachel E. Hesse...SUBTITLE Structural Acoustic Physics -Based Modeling of Curved Composite Shells 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...study was to use physics -based modeling (PBM) to investigate wave propagations through curved shells that are subjected to acoustic excitation. An

Agent-Based Modeling in Systems Pharmacology.

Science.gov (United States)

Cosgrove, J; Butler, J; Alden, K; Read, M; Kumar, V; Cucurull-Sanchez, L; Timmis, J; Coles, M

2015-11-01

Modeling and simulation (M&S) techniques provide a platform for knowledge integration and hypothesis testing to gain insights into biological systems that would not be possible a priori. Agent-based modeling (ABM) is an M&S technique that focuses on describing individual components rather than homogenous populations. This tutorial introduces ABM to systems pharmacologists, using relevant case studies to highlight how ABM-specific strengths have yielded success in the area of preclinical mechanistic modeling.

A pedagogical model for simulation-based learning in healthcare

Directory of Open Access Journals (Sweden)

Tuulikki Keskitalo

2015-11-01

Full Text Available The aim of this study was to design a pedagogical model for a simulation-based learning environment (SBLE in healthcare. Currently, simulation and virtual reality are a major focus in healthcare education. However, when and how these learning environments should be applied is not well-known. The present study tries to fill that gap. We pose the following research question: What kind of pedagogical model supports and facilitates students’ meaningful learning in SBLEs? The study used design-based research (DBR and case study approaches. We report the results from our second case study and how the pedagogical model was developed based on the lessons learned. The study involved nine facilitators and 25 students. Data were collected and analysed using mixed methods. The main result of this study is the refined pedagogical model. The model is based on the socio-cultural theory of learning and characteristics of meaningful learning as well as previous pedagogical models. The model will provide a more holistic and meaningful approach to teaching and learning in SBLEs. However, the model requires evidence and further development.

Development of a materials data base for modeling

International Nuclear Information System (INIS)

Iwata, S.; Ashino, T.; Ishino, S.

1988-01-01

Materials selection for fusion reactors requires a materials data base and a set of methods to estimate material properties in a ''virtual'' fusion reactor. This estimation process, namely, modeling, is analyzed as compromising of design requirements, available data bases and methods of estimation, and a concept of an ideal computer system to support this modeling process is proposed. The limitations of a commercial DBMS (Data Base Management System) to handle sophisticated materials data are described in accordance with our experiences. Secondly, ways to manipulate analytical expressions are discussed as the next step for computer assisted modeling. Finally, an advanced method is presented which is able to manage models and data in the same manner without paying attention to annoying rules compelled by constraints of using computers. (orig.)

Interactive Coherence-Based Façade Modeling

KAUST Repository

Musialski, Przemyslaw

2012-05-01

We propose a novel interactive framework for modeling building facades from images. Our method is based on the notion of coherence-based editing which allows exploiting partial symmetries across the facade at any level of detail. The proposed workflow mixes manual interaction with automatic splitting and grouping operations based on unsupervised cluster analysis. In contrast to previous work, our approach leads to detailed 3d geometric models with up to several thousand regions per facade. We compare our modeling scheme to others and evaluate our approach in a user study with an experienced user and several novice users.

Vehicle-specific emissions modeling based upon on-road measurements.

Science.gov (United States)

Frey, H Christopher; Zhang, Kaishan; Rouphail, Nagui M

2010-05-01

Vehicle-specific microscale fuel use and emissions rate models are developed based upon real-world hot-stabilized tailpipe measurements made using a portable emissions measurement system. Consecutive averaging periods of one to three multiples of the response time are used to compare two semiempirical physically based modeling schemes. One scheme is based on internally observable variables (IOVs), such as engine speed and manifold absolute pressure, while the other is based on externally observable variables (EOVs), such as speed, acceleration, and road grade. For NO, HC, and CO emission rates, the average R(2) ranged from 0.41 to 0.66 for the former and from 0.17 to 0.30 for the latter. The EOV models have R(2) for CO(2) of 0.43 to 0.79 versus 0.99 for the IOV models. The models are sensitive to episodic events in driving cycles such as high acceleration. Intervehicle and fleet average modeling approaches are compared; the former account for microscale variations that might be useful for some types of assessments. EOV-based models have practical value for traffic management or simulation applications since IOVs usually are not available or not used for emission estimation.

Empirical agent-based modelling challenges and solutions

CERN Document Server

Barreteau, Olivier

2014-01-01

This instructional book showcases techniques to parameterise human agents in empirical agent-based models (ABM). In doing so, it provides a timely overview of key ABM methodologies and the most innovative approaches through a variety of empirical applications.  It features cutting-edge research from leading academics and practitioners, and will provide a guide for characterising and parameterising human agents in empirical ABM.  In order to facilitate learning, this text shares the valuable experiences of other modellers in particular modelling situations. Very little has been published in the area of empirical ABM, and this contributed volume will appeal to graduate-level students and researchers studying simulation modeling in economics, sociology, ecology, and trans-disciplinary studies, such as topics related to sustainability. In a similar vein to the instruction found in a cookbook, this text provides the empirical modeller with a set of 'recipes'  ready to be implemented. Agent-based modeling (AB...

Model Based Mission Assurance: Emerging Opportunities for Robotic Systems

Science.gov (United States)

Evans, John W.; DiVenti, Tony

2016-01-01

The emergence of Model Based Systems Engineering (MBSE) in a Model Based Engineering framework has created new opportunities to improve effectiveness and efficiencies across the assurance functions. The MBSE environment supports not only system architecture development, but provides for support of Systems Safety, Reliability and Risk Analysis concurrently in the same framework. Linking to detailed design will further improve assurance capabilities to support failures avoidance and mitigation in flight systems. This also is leading new assurance functions including model assurance and management of uncertainty in the modeling environment. Further, the assurance cases, a structured hierarchal argument or model, are emerging as a basis for supporting a comprehensive viewpoint in which to support Model Based Mission Assurance (MBMA).

[GSH fermentation process modeling using entropy-criterion based RBF neural network model].

Science.gov (United States)

Tan, Zuoping; Wang, Shitong; Deng, Zhaohong; Du, Guocheng

2008-05-01

The prediction accuracy and generalization of GSH fermentation process modeling are often deteriorated by noise existing in the corresponding experimental data. In order to avoid this problem, we present a novel RBF neural network modeling approach based on entropy criterion. It considers the whole distribution structure of the training data set in the parameter learning process compared with the traditional MSE-criterion based parameter learning, and thus effectively avoids the weak generalization and over-learning. Then the proposed approach is applied to the GSH fermentation process modeling. Our results demonstrate that this proposed method has better prediction accuracy, generalization and robustness such that it offers a potential application merit for the GSH fermentation process modeling.

A community-based framework for aquatic ecosystem models

DEFF Research Database (Denmark)

Trolle, Didde; Hamilton, D. P.; Hipsey, M. R.

2012-01-01

Here, we communicate a point of departure in the development of aquatic ecosystem models, namely a new community-based framework, which supports an enhanced and transparent union between the collective expertise that exists in the communities of traditional ecologists and model developers. Through...... a literature survey, we document the growing importance of numerical aquatic ecosystem models while also noting the difficulties, up until now, of the aquatic scientific community to make significant advances in these models during the past two decades. Through a common forum for aquatic ecosystem modellers we...... aim to (i) advance collaboration within the aquatic ecosystem modelling community, (ii) enable increased use of models for research, policy and ecosystem-based management, (iii) facilitate a collective framework using common (standardised) code to ensure that model development is incremental, (iv...

NHPP-Based Software Reliability Models Using Equilibrium Distribution

Science.gov (United States)

Xiao, Xiao; Okamura, Hiroyuki; Dohi, Tadashi

Non-homogeneous Poisson processes (NHPPs) have gained much popularity in actual software testing phases to estimate the software reliability, the number of remaining faults in software and the software release timing. In this paper, we propose a new modeling approach for the NHPP-based software reliability models (SRMs) to describe the stochastic behavior of software fault-detection processes. The fundamental idea is to apply the equilibrium distribution to the fault-detection time distribution in NHPP-based modeling. We also develop efficient parameter estimation procedures for the proposed NHPP-based SRMs. Through numerical experiments, it can be concluded that the proposed NHPP-based SRMs outperform the existing ones in many data sets from the perspective of goodness-of-fit and prediction performance.

A knowledge representation meta-model for rule-based modelling of signalling networks

Directory of Open Access Journals (Sweden)

Adrien Basso-Blandin

2016-03-01

Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.

Intelligent Transportation and Evacuation Planning A Modeling-Based Approach

CERN Document Server

Naser, Arab

2012-01-01

Intelligent Transportation and Evacuation Planning: A Modeling-Based Approach provides a new paradigm for evacuation planning strategies and techniques. Recently, evacuation planning and modeling have increasingly attracted interest among researchers as well as government officials. This interest stems from the recent catastrophic hurricanes and weather-related events that occurred in the southeastern United States (Hurricane Katrina and Rita). The evacuation methods that were in place before and during the hurricanes did not work well and resulted in thousands of deaths. This book offers insights into the methods and techniques that allow for implementing mathematical-based, simulation-based, and integrated optimization and simulation-based engineering approaches for evacuation planning. This book also: Comprehensively discusses the application of mathematical models for evacuation and intelligent transportation modeling Covers advanced methodologies in evacuation modeling and planning Discusses principles a...

Distributed Prognostics Based on Structural Model Decomposition

Data.gov (United States)

National Aeronautics and Space Administration — Within systems health management, prognostics focuses on predicting the remaining useful life of a system. In the model-based prognostics paradigm, physics-based...

Model-based and model-free “plug-and-play” building energy efficient control

International Nuclear Information System (INIS)

Baldi, Simone; Michailidis, Iakovos; Ravanis, Christos; Kosmatopoulos, Elias B.

2015-01-01

Highlights: • “Plug-and-play” Building Optimization and Control (BOC) driven by building data. • Ability to handle the large-scale and complex nature of the BOC problem. • Adaptation to learn the optimal BOC policy when no building model is available. • Comparisons with rule-based and advanced BOC strategies. • Simulation and real-life experiments in a ten-office building. - Abstract: Considerable research efforts in Building Optimization and Control (BOC) have been directed toward the development of “plug-and-play” BOC systems that can achieve energy efficiency without compromising thermal comfort and without the need of qualified personnel engaged in a tedious and time-consuming manual fine-tuning phase. In this paper, we report on how a recently introduced Parametrized Cognitive Adaptive Optimization – abbreviated as PCAO – can be used toward the design of both model-based and model-free “plug-and-play” BOC systems, with minimum human effort required to accomplish the design. In the model-based case, PCAO assesses the performance of its control strategy via a simulation model of the building dynamics; in the model-free case, PCAO optimizes its control strategy without relying on any model of the building dynamics. Extensive simulation and real-life experiments performed on a 10-office building demonstrate the effectiveness of the PCAO–BOC system in providing significant energy efficiency and improved thermal comfort. The mechanisms embedded within PCAO render it capable of automatically and quickly learning an efficient BOC strategy either in the presence of complex nonlinear simulation models of the building dynamics (model-based) or when no model for the building dynamics is available (model-free). Comparative studies with alternative state-of-the-art BOC systems show the effectiveness of the PCAO–BOC solution

Model-based processing for underwater acoustic arrays

CERN Document Server

Sullivan, Edmund J

2015-01-01

This monograph presents a unified approach to model-based processing for underwater acoustic arrays. The use of physical models in passive array processing is not a new idea, but it has been used on a case-by-case basis, and as such, lacks any unifying structure. This work views all such processing methods as estimation procedures, which then can be unified by treating them all as a form of joint estimation based on a Kalman-type recursive processor, which can be recursive either in space or time, depending on the application. This is done for three reasons. First, the Kalman filter provides a natural framework for the inclusion of physical models in a processing scheme. Second, it allows poorly known model parameters to be jointly estimated along with the quantities of interest. This is important, since in certain areas of array processing already in use, such as those based on matched-field processing, the so-called mismatch problem either degrades performance or, indeed, prevents any solution at all. Third...

DEVELOPMENT MODEL OF PATISSERIE PROJECT-BASED LEARNING

OpenAIRE

Ana Ana; Lutfhiyah Nurlaela

2013-01-01

The study aims to find a model of patisserie project-based learning with production approach that can improve effectiveness of patisserie learning. Delphi Technique, Cohen's Kappa and percentages of agreements were used to assess model of patisserie project based learning. Data collection techniques employed in the study were questionnaire, check list worksheet, observation, and interview sheets. Subjects were 13 lectures of expertise food and nutrition and 91 students of Food and Nutrition ...

Model-based and model-free Pavlovian reward learning: revaluation, revision, and revelation.

Science.gov (United States)

Dayan, Peter; Berridge, Kent C

2014-06-01

Evidence supports at least two methods for learning about reward and punishment and making predictions for guiding actions. One method, called model-free, progressively acquires cached estimates of the long-run values of circumstances and actions from retrospective experience. The other method, called model-based, uses representations of the environment, expectations, and prospective calculations to make cognitive predictions of future value. Extensive attention has been paid to both methods in computational analyses of instrumental learning. By contrast, although a full computational analysis has been lacking, Pavlovian learning and prediction has typically been presumed to be solely model-free. Here, we revise that presumption and review compelling evidence from Pavlovian revaluation experiments showing that Pavlovian predictions can involve their own form of model-based evaluation. In model-based Pavlovian evaluation, prevailing states of the body and brain influence value computations, and thereby produce powerful incentive motivations that can sometimes be quite new. We consider the consequences of this revised Pavlovian view for the computational landscape of prediction, response, and choice. We also revisit differences between Pavlovian and instrumental learning in the control of incentive motivation.

Vibration-Based Damage Diagnosis in a Laboratory Cable-Stayed Bridge Model via an RCP-ARX Model Based Method

International Nuclear Information System (INIS)

Michaelides, P G; Apostolellis, P G; Fassois, S D

2011-01-01

Vibration-based damage detection and identification in a laboratory cable-stayed bridge model is addressed under inherent, environmental, and experimental uncertainties. The problem is challenging as conventional stochastic methods face difficulties due to uncertainty underestimation. A novel method is formulated based on identified Random Coefficient Pooled ARX (RCP-ARX) representations of the dynamics and statistical hypothesis testing. The method benefits from the ability of RCP models in properly capturing uncertainty. Its effectiveness is demonstrated via a high number of experiments under a variety of damage scenarios.

Vibration-Based Damage Diagnosis in a Laboratory Cable-Stayed Bridge Model via an RCP-ARX Model Based Method

Energy Technology Data Exchange (ETDEWEB)

Michaelides, P G; Apostolellis, P G; Fassois, S D, E-mail: mixail@mech.upatras.gr, E-mail: fassois@mech.upatras.gr [Laboratory for Stochastic Mechanical Systems and Automation (SMSA), Department of Mechanical and Aeronautical Engineering, University of Patras, GR 265 00 Patras (Greece)

2011-07-19

Vibration-based damage detection and identification in a laboratory cable-stayed bridge model is addressed under inherent, environmental, and experimental uncertainties. The problem is challenging as conventional stochastic methods face difficulties due to uncertainty underestimation. A novel method is formulated based on identified Random Coefficient Pooled ARX (RCP-ARX) representations of the dynamics and statistical hypothesis testing. The method benefits from the ability of RCP models in properly capturing uncertainty. Its effectiveness is demonstrated via a high number of experiments under a variety of damage scenarios.

Model-based security testing

OpenAIRE

Schieferdecker, Ina; Großmann, Jürgen; Schneider, Martin

2012-01-01

Security testing aims at validating software system requirements related to security properties like confidentiality, integrity, authentication, authorization, availability, and non-repudiation. Although security testing techniques are available for many years, there has been little approaches that allow for specification of test cases at a higher level of abstraction, for enabling guidance on test identification and specification as well as for automated test generation. Model-based security...

Bayesian Based Diagnostic Model for Condition Based Maintenance of Offshore Wind Farms

Directory of Open Access Journals (Sweden)

Masoud Asgarpour

2018-01-01

Full Text Available Operation and maintenance costs are a major contributor to the Levelized Cost of Energy for electricity produced by offshore wind and can be significantly reduced if existing corrective actions are performed as efficiently as possible and if future corrective actions are avoided by performing sufficient preventive actions. This paper presents an applied and generic diagnostic model for fault detection and condition based maintenance of offshore wind components. The diagnostic model is based on two probabilistic matrices; first, a confidence matrix, representing the probability of detection using each fault detection method, and second, a diagnosis matrix, representing the individual outcome of each fault detection method. Once the confidence and diagnosis matrices of a component are defined, the individual diagnoses of each fault detection method are combined into a final verdict on the fault state of that component. Furthermore, this paper introduces a Bayesian updating model based on observations collected by inspections to decrease the uncertainty of initial confidence matrix. The framework and implementation of the presented diagnostic model are further explained within a case study for a wind turbine component based on vibration, temperature, and oil particle fault detection methods. The last part of the paper will have a discussion of the case study results and present conclusions.

Predictor-Based Model Reference Adaptive Control

Science.gov (United States)

Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

2010-01-01

This paper is devoted to the design and analysis of a predictor-based model reference adaptive control. Stable adaptive laws are derived using Lyapunov framework. The proposed architecture is compared with the now classical model reference adaptive control. A simulation example is presented in which numerical evidence indicates that the proposed controller yields improved transient characteristics.

Agent-based Modeling Automated: Data-driven Generation of Innovation Diffusion Models

NARCIS (Netherlands)

Jensen, T.; Chappin, E.J.L.

2016-01-01

Simulation modeling is useful to gain insights into driving mechanisms of diffusion of innovations. This study aims to introduce automation to make identification of such mechanisms with agent-based simulation modeling less costly in time and labor. We present a novel automation procedure in which

Enabling Accessibility Through Model-Based User Interface Development.

Science.gov (United States)

Ziegler, Daniel; Peissner, Matthias

2017-01-01

Adaptive user interfaces (AUIs) can increase the accessibility of interactive systems. They provide personalized display and interaction modes to fit individual user needs. Most AUI approaches rely on model-based development, which is considered relatively demanding. This paper explores strategies to make model-based development more attractive for mainstream developers.

Variance-based sensitivity indices for models with dependent inputs

International Nuclear Information System (INIS)

Mara, Thierry A.; Tarantola, Stefano

2012-01-01

Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.

User Context Aware Base Station Power Flow Model

OpenAIRE

Walsh, Barbara; Farrell, Ronan

2005-01-01

At present the testing of power amplifiers within base station transmitters is limited to testing at component level as opposed to testing at the system level. While the detection of catastrophic failure is possible, that of performance degradation is not. This paper proposes a base station model with respect to transmitter output power with the aim of introducing system level monitoring of the power amplifier behaviour within the base station. Our model reflects the expe...

The Challenge of Forecasting Metropolitan Growth: Urban Characteristics Based Models versus Regional Dummy Based Models

OpenAIRE

NA

2005-01-01

This paper presents a study of errors in forecasting the population of Metropolitan Statistical Areas and the Primary MSAs of Consolidated Metropolitan Statistical Areas and New England MAs. The forecasts are for the year 2000 and are based on a semi-structural model estimated by Mills and Lubelle using 1970 to 1990 census data on population, employment and relative real wages. This model allows the testing of regional effects on population and employment growth. The year 2000 forecasts are f...

Fuzzy model-based control of a nuclear reactor

International Nuclear Information System (INIS)

Van Den Durpel, L.; Ruan, D.

1994-01-01

The fuzzy model-based control of a nuclear power reactor is an emerging research topic world-wide. SCK-CEN is dealing with this research in a preliminary stage, including two aspects, namely fuzzy control and fuzzy modelling. The aim is to combine both methodologies in contrast to conventional model-based PID control techniques, and to state advantages of including fuzzy parameters as safety and operator feedback. This paper summarizes the general scheme of this new research project

A stream-based mathematical model for distributed information processing systems - SysLab system model

OpenAIRE

Klein, Cornel; Rumpe, Bernhard; Broy, Manfred

2014-01-01

In the SysLab project we develop a software engineering method based on a mathematical foundation. The SysLab system model serves as an abstract mathematical model for information systems and their components. It is used to formalize the semantics of all used description techniques such as object diagrams state automata sequence charts or data-flow diagrams. Based on the requirements for such a reference model, we define the system model including its different views and their relationships.

Characteristic Model-Based Robust Model Predictive Control for Hypersonic Vehicles with Constraints

Directory of Open Access Journals (Sweden)

Jun Zhang

2017-06-01

Full Text Available Designing robust control for hypersonic vehicles in reentry is difficult, due to the features of the vehicles including strong coupling, non-linearity, and multiple constraints. This paper proposed a characteristic model-based robust model predictive control (MPC for hypersonic vehicles with reentry constraints. First, the hypersonic vehicle is modeled by a characteristic model composed of a linear time-varying system and a lumped disturbance. Then, the identification data are regenerated by the accumulative sum idea in the gray theory, which weakens effects of the random noises and strengthens regularity of the identification data. Based on the regenerated data, the time-varying parameters and the disturbance are online estimated according to the gray identification. At last, the mixed H2/H∞ robust predictive control law is proposed based on linear matrix inequalities (LMIs and receding horizon optimization techniques. Using active tackling system constraints of MPC, the input and state constraints are satisfied in the closed-loop control system. The validity of the proposed control is verified theoretically according to Lyapunov theory and illustrated by simulation results.

A continuum based fem model for friction stir welding-model development

Energy Technology Data Exchange (ETDEWEB)

Buffa, G. [Ohio State University, Department of Industrial, Welding and Systems Engineering, 1971 Neil Avenue, 210 Baker Systems, Columbus, OH 43210 (United States) and Dipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale, Universita di Palermo, Viale delle Scienze, 90128 Palermo (Italy)]. E-mail: g.buffa@dtpm.unipa.it; Hua, J. [Ohio State University, Department of Industrial, Welding and Systems Engineering, 1971 Neil Avenue, 210 Baker Systems, Columbus, OH 43210 (United States)]. E-mail: hua.14@osu.edu; Shivpuri, R. [Ohio State University, Department of Industrial, Welding and Systems Engineering, 1971 Neil Avenue, 210 Baker Systems, Columbus, OH 43210 (United States)]. E-mail: shivpuri.1@osu.edu; Fratini, L. [Dipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale, Universita di Palermo, Viale delle Scienze, 90128 Palermo (Italy)]. E-mail: abaqus@dtpm.unipa.it

2006-03-15

Although friction stir welding (FSW) has been successfully used to join materials that are difficult-to-weld or unweldeable by fusion welding methods, it is still in its early development stage and, therefore, a scientific knowledge based predictive model is of significant help for thorough understanding of FSW process. In this paper, a continuum based FEM model for friction stir welding process is proposed, that is 3D Lagrangian implicit, coupled, rigid-viscoplastic. This model is calibrated by comparing with experimental results of force and temperature distribution, then is used to investigate the distribution of temperature and strain in heat affect zone and the weld nugget. The model correctly predicts the non-symmetric nature of FSW process, and the relationships between the tool forces and the variation in the process parameters. It is found that the effective strain distribution is non-symmetric about the weld line while the temperature profile is almost symmetric in the weld zone.

A continuum based fem model for friction stir welding-model development

International Nuclear Information System (INIS)

Buffa, G.; Hua, J.; Shivpuri, R.; Fratini, L.

2006-01-01

Although friction stir welding (FSW) has been successfully used to join materials that are difficult-to-weld or unweldeable by fusion welding methods, it is still in its early development stage and, therefore, a scientific knowledge based predictive model is of significant help for thorough understanding of FSW process. In this paper, a continuum based FEM model for friction stir welding process is proposed, that is 3D Lagrangian implicit, coupled, rigid-viscoplastic. This model is calibrated by comparing with experimental results of force and temperature distribution, then is used to investigate the distribution of temperature and strain in heat affect zone and the weld nugget. The model correctly predicts the non-symmetric nature of FSW process, and the relationships between the tool forces and the variation in the process parameters. It is found that the effective strain distribution is non-symmetric about the weld line while the temperature profile is almost symmetric in the weld zone

Dissemination of Cultural Norms and Values: Agent-Based Modeling

Directory of Open Access Journals (Sweden)

Denis Andreevich Degterev

2016-12-01

Full Text Available This article shows how agent-based modeling allows us to explore the mechanisms of the dissemination of cultural norms and values both within one country and in the whole world. In recent years, this type of simulation is particularly prevalent in the analysis of international relations, becoming more popular than the system dynamics and discrete event simulation. The use of agent-based modeling in the analysis of international relations is connected with the agent-structure problem in international relations. Structure and agents act as interdependent and dynamically changing in the process of interaction between entities. Agent-structure interaction could be modeled by means of the theory of complex adaptive systems with the use of agent-based modeling techniques. One of the first examples of the use of agent-based modeling in political science is a model of racial segregation T. Shellinga. On the basis of this model, the author shows how the change in behavioral patterns at micro-level impacts on the macro-level. Patterns are changing due to the dynamics of cultural norms and values, formed by mass-media and other social institutes. The author shows the main areas of modern application of agent-based modeling in international studies including the analysis of ethnic conflicts, the formation of international coalitions. Particular attention is paid to Robert Axelrod approach based on the use of genetic algorithms to the spread of cultural norms and values. Agent-based modeling shows how to how to create such conditions that the norms that originally are not shared by a significant part of the population, eventually spread everywhere. Practical application of these algorithms is shown by the author of the article on the example of the situation in Ukraine in 2015-2016. The article also reveals the mechanisms of international spread of cultural norms and values. The main think-tanks using agent-based modeling in international studies are

PARTICIPATION BASED MODEL OF SHIP CREW MANAGEMENT

Directory of Open Access Journals (Sweden)

Toni Bielić

2014-10-01

Full Text Available 800x600 This paper analyse the participation - based model on board the ship as possibly optimal leadership model existing in the shipping industry with accent on decision - making process. In the paper authors have tried to define master’s behaviour model and management style identifying drawbacks and disadvantages of vertical, pyramidal organization with master on the top. Paper describes efficiency of decision making within team organization and optimization of a ship’s organisation by introducing teamwork on board the ship. Three examples of the ship’s accidents are studied and evaluated through “Leader - participation” model. The model of participation based management as a model of the teamwork has been applied in studying the cause - and - effect of accidents with the critical review of the communication and managing the human resources on a ship. The results have showed that the cause of all three accidents is the autocratic behaviour of the leaders and lack of communication within teams. Normal 0 21 false false false HR X-NONE X-NONE MicrosoftInternetExplorer4

Markov chain aggregation for agent-based models

CERN Document Server

Banisch, Sven

2016-01-01

This self-contained text develops a Markov chain approach that makes the rigorous analysis of a class of microscopic models that specify the dynamics of complex systems at the individual level possible. It presents a general framework of aggregation in agent-based and related computational models, one which makes use of lumpability and information theory in order to link the micro and macro levels of observation. The starting point is a microscopic Markov chain description of the dynamical process in complete correspondence with the dynamical behavior of the agent-based model (ABM), which is obtained by considering the set of all possible agent configurations as the state space of a huge Markov chain. An explicit formal representation of a resulting “micro-chain” including microscopic transition rates is derived for a class of models by using the random mapping representation of a Markov process. The type of probability distribution used to implement the stochastic part of the model, which defines the upd...

Expediting model-based optoacoustic reconstructions with tomographic symmetries

International Nuclear Information System (INIS)

Lutzweiler, Christian; Deán-Ben, Xosé Luís; Razansky, Daniel

2014-01-01

Purpose: Image quantification in optoacoustic tomography implies the use of accurate forward models of excitation, propagation, and detection of optoacoustic signals while inversions with high spatial resolution usually involve very large matrices, leading to unreasonably long computation times. The development of fast and memory efficient model-based approaches represents then an important challenge to advance on the quantitative and dynamic imaging capabilities of tomographic optoacoustic imaging. Methods: Herein, a method for simplification and acceleration of model-based inversions, relying on inherent symmetries present in common tomographic acquisition geometries, has been introduced. The method is showcased for the case of cylindrical symmetries by using polar image discretization of the time-domain optoacoustic forward model combined with efficient storage and inversion strategies. Results: The suggested methodology is shown to render fast and accurate model-based inversions in both numerical simulations andpost mortem small animal experiments. In case of a full-view detection scheme, the memory requirements are reduced by one order of magnitude while high-resolution reconstructions are achieved at video rate. Conclusions: By considering the rotational symmetry present in many tomographic optoacoustic imaging systems, the proposed methodology allows exploiting the advantages of model-based algorithms with feasible computational requirements and fast reconstruction times, so that its convenience and general applicability in optoacoustic imaging systems with tomographic symmetries is anticipated

A model-based risk management framework

Energy Technology Data Exchange (ETDEWEB)

Gran, Bjoern Axel; Fredriksen, Rune

2002-08-15

The ongoing research activity addresses these issues through two co-operative activities. The first is the IST funded research project CORAS, where Institutt for energiteknikk takes part as responsible for the work package for Risk Analysis. The main objective of the CORAS project is to develop a framework to support risk assessment of security critical systems. The second, called the Halden Open Dependability Demonstrator (HODD), is established in cooperation between Oestfold University College, local companies and HRP. The objective of HODD is to provide an open-source test bed for testing, teaching and learning about risk analysis methods, risk analysis tools, and fault tolerance techniques. The Inverted Pendulum Control System (IPCON), which main task is to keep a pendulum balanced and controlled, is the first system that has been established. In order to make risk assessment one need to know what a system does, or is intended to do. Furthermore, the risk assessment requires correct descriptions of the system, its context and all relevant features. A basic assumption is that a precise model of this knowledge, based on formal or semi-formal descriptions, such as UML, will facilitate a systematic risk assessment. It is also necessary to have a framework to integrate the different risk assessment methods. The experiences so far support this hypothesis. This report presents CORAS and the CORAS model-based risk management framework, including a preliminary guideline for model-based risk assessment. The CORAS framework for model-based risk analysis offers a structured and systematic approach to identify and assess security issues of ICT systems. From the initial assessment of IPCON, we also believe that the framework is applicable in a safety context. Further work on IPCON, as well as the experiences from the CORAS trials, will provide insight and feedback for further improvements. (Author)

Model-Based Software Testing for Object-Oriented Software

Science.gov (United States)

Biju, Soly Mathew

2008-01-01

Model-based testing is one of the best solutions for testing object-oriented software. It has a better test coverage than other testing styles. Model-based testing takes into consideration behavioural aspects of a class, which are usually unchecked in other testing methods. An increase in the complexity of software has forced the software industry…

Dynamic ligand-based pharmacophore modeling and virtual ...

Indian Academy of Sciences (India)

Five ligand-based pharmacophore models were generated from 40 different .... the Phase module of the Schrodinger program.35 Each model consisted of six types of ... ligand preparation included the OPLS_2005 force field and to retain the ...

Modeling and knowledge acquisition processes using case-based inference

Directory of Open Access Journals (Sweden)

Ameneh Khadivar

2017-03-01

Full Text Available The method of acquisition and presentation of the organizational Process Knowledge has considered by many KM researches. In this research a model for process knowledge acquisition and presentation has been presented by using the approach of Case Base Reasoning. The validation of the presented model was evaluated by conducting an expert panel. Then a software has been developed based on the presented model and implemented in Eghtesad Novin Bank of Iran. In this company, based on the stages of the presented model, first the knowledge intensive processes has been identified, then the Process Knowledge was stored in a knowledge base in the format of problem/solution/consequent .The retrieval of the knowledge was done based on the similarity of the nearest neighbor algorithm. For validating of the implemented system, results of the system has compared by the results of the decision making of the expert of the process.

Agent Based Modeling as an Educational Tool

Science.gov (United States)

Fuller, J. H.; Johnson, R.; Castillo, V.

2012-12-01

Motivation is a key element in high school education. One way to improve motivation and provide content, while helping address critical thinking and problem solving skills, is to have students build and study agent based models in the classroom. This activity visually connects concepts with their applied mathematical representation. "Engaging students in constructing models may provide a bridge between frequently disconnected conceptual and mathematical forms of knowledge." (Levy and Wilensky, 2011) We wanted to discover the feasibility of implementing a model based curriculum in the classroom given current and anticipated core and content standards.; Simulation using California GIS data ; Simulation of high school student lunch popularity using aerial photograph on top of terrain value map.

Multiscale agent-based cancer modeling.

Science.gov (United States)

Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

2009-04-01

Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

Model Predictive Control based on Finite Impulse Response Models

DEFF Research Database (Denmark)

Prasath, Guru; Jørgensen, John Bagterp

2008-01-01

We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...... and related to the uncertainty of the impulse response coefficients. The simulations can be used to benchmark l2 MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC....

Development of uncertainty-based work injury model using Bayesian structural equation modelling.

Science.gov (United States)

Chatterjee, Snehamoy

2014-01-01

This paper proposed a Bayesian method-based structural equation model (SEM) of miners' work injury for an underground coal mine in India. The environmental and behavioural variables for work injury were identified and causal relationships were developed. For Bayesian modelling, prior distributions of SEM parameters are necessary to develop the model. In this paper, two approaches were adopted to obtain prior distribution for factor loading parameters and structural parameters of SEM. In the first approach, the prior distributions were considered as a fixed distribution function with specific parameter values, whereas, in the second approach, prior distributions of the parameters were generated from experts' opinions. The posterior distributions of these parameters were obtained by applying Bayesian rule. The Markov Chain Monte Carlo sampling in the form Gibbs sampling was applied for sampling from the posterior distribution. The results revealed that all coefficients of structural and measurement model parameters are statistically significant in experts' opinion-based priors, whereas, two coefficients are not statistically significant when fixed prior-based distributions are applied. The error statistics reveals that Bayesian structural model provides reasonably good fit of work injury with high coefficient of determination (0.91) and less mean squared error as compared to traditional SEM.

Chaos synchronization of a new chaotic system via nonlinear control

International Nuclear Information System (INIS)

Zhang Qunjiao; Lu Junan

2008-01-01

This paper investigates chaos synchronization of a new chaotic system [Lue J, Chen G, Cheng D. A new chaotic system and beyond: the generalized Lorenz-like system. Int J Bifurcat Chaos 2004;14:1507-37]. Two kinds of novel nonlinear controllers are designed based on the Lyapunov stability theory. It can be viewed as an improvement to the existing results of reference [Park JH. Chaos synchronization of a chaotic system via nonlinear control. Chaos, Solitons and Fractals 2005;25:579-84] because we use less controllers but realize a global and exponential asymptotical synchronization. Numerical simulations are provided to show the effectiveness and advantage of this method

Radiation effects on components of orally administrated medicines

International Nuclear Information System (INIS)

Akhmatovich-Shmajke, T.; Yuz'byak, Kh.; Ovcharchik, A.

1976-01-01

Physicochemical changes occuring in starch, lactose, sucrose, gum arabic, talc, polyvinylpyrrolidone (PVP), and magnesium stearate irradiated on an electronic linear accelerator type LUE-13/9 were studied. Bond breakage in sugars and molecular degradation in starch and PVP were noted. Paramagnetic centers were found to form in most of the test substances. (author)

Model-based auditing using REA

NARCIS (Netherlands)

Weigand, H.; Elsas, P.

2012-01-01

The recent financial crisis has renewed interest in the value of the owner-ordered auditing tradition that starts from society's long-term interest rather than management interest. This tradition uses a model-based auditing approach in which control requirements are derived in a principled way. A

Dopamine selectively remediates 'model-based' reward learning: a computational approach.

Science.gov (United States)

Sharp, Madeleine E; Foerde, Karin; Daw, Nathaniel D; Shohamy, Daphna

2016-02-01

Patients with loss of dopamine due to Parkinson's disease are impaired at learning from reward. However, it remains unknown precisely which aspect of learning is impaired. In particular, learning from reward, or reinforcement learning, can be driven by two distinct computational processes. One involves habitual stamping-in of stimulus-response associations, hypothesized to arise computationally from 'model-free' learning. The other, 'model-based' learning, involves learning a model of the world that is believed to support goal-directed behaviour. Much work has pointed to a role for dopamine in model-free learning. But recent work suggests model-based learning may also involve dopamine modulation, raising the possibility that model-based learning may contribute to the learning impairment in Parkinson's disease. To directly test this, we used a two-step reward-learning task which dissociates model-free versus model-based learning. We evaluated learning in patients with Parkinson's disease tested ON versus OFF their dopamine replacement medication and in healthy controls. Surprisingly, we found no effect of disease or medication on model-free learning. Instead, we found that patients tested OFF medication showed a marked impairment in model-based learning, and that this impairment was remediated by dopaminergic medication. Moreover, model-based learning was positively correlated with a separate measure of working memory performance, raising the possibility of common neural substrates. Our results suggest that some learning deficits in Parkinson's disease may be related to an inability to pursue reward based on complete representations of the environment. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Model-Based Methods for Fault Diagnosis: Some Guide-Lines

DEFF Research Database (Denmark)

Patton, R.J.; Chen, J.; Nielsen, S.B.

1995-01-01

This paper provides a review of model-based fault diagnosis techniques. Starting from basic principles, the properties.......This paper provides a review of model-based fault diagnosis techniques. Starting from basic principles, the properties....

Mathematical Modeling of Column-Base Connections under Monotonic Loading

Directory of Open Access Journals (Sweden)

Gholamreza Abdollahzadeh

2014-12-01

Full Text Available Some considerable damage to steel structures during the Hyogo-ken Nanbu Earthquake occurred. Among them, many exposed-type column bases failed in several consistent patterns, such as brittle base plate fracture, excessive bolt elongation, unexpected early bolt failure, and inferior construction work, etc. The lessons from these phenomena led to the need for improved understanding of column base behavior. Joint behavior must be modeled when analyzing semi-rigid frames, which is associated with a mathematical model of the moment–rotation curve. The most accurate model uses continuous nonlinear functions. This article presents three areas of steel joint research: (1 analysis methods of semi-rigid joints; (2 prediction methods for the mechanical behavior of joints; (3 mathematical representations of the moment–rotation curve. In the current study, a new exponential model to depict the moment–rotation relationship of column base connection is proposed. The proposed nonlinear model represents an approach to the prediction of M–θ curves, taking into account the possible failure modes and the deformation characteristics of the connection elements. The new model has three physical parameters, along with two curve-fitted factors. These physical parameters are generated from dimensional details of the connection, as well as the material properties. The M–θ curves obtained by the model are compared with published connection tests and 3D FEM research. The proposed mathematical model adequately comes close to characterizing M–θ behavior through the full range of loading/rotations. As a result, modeling of column base connections using the proposed mathematical model can give crucial beforehand information, and overcome the disadvantages of time consuming workmanship and cost of experimental studies.

CAD-based automatic modeling method for Geant4 geometry model through MCAM

International Nuclear Information System (INIS)

Wang, D.; Nie, F.; Wang, G.; Long, P.; LV, Z.

2013-01-01

The full text of publication follows. Geant4 is a widely used Monte Carlo transport simulation package. Before calculating using Geant4, the calculation model need be established which could be described by using Geometry Description Markup Language (GDML) or C++ language. However, it is time-consuming and error-prone to manually describe the models by GDML. Automatic modeling methods have been developed recently, but there are some problems that exist in most present modeling programs, specially some of them were not accurate or adapted to specifically CAD format. To convert the GDML format models to CAD format accurately, a Geant4 Computer Aided Design (CAD) based modeling method was developed for automatically converting complex CAD geometry model into GDML geometry model. The essence of this method was dealing with CAD model represented with boundary representation (B-REP) and GDML model represented with constructive solid geometry (CSG). At first, CAD model was decomposed to several simple solids which had only one close shell. And then the simple solid was decomposed to convex shell set. Then corresponding GDML convex basic solids were generated by the boundary surfaces getting from the topological characteristic of a convex shell. After the generation of these solids, GDML model was accomplished with series boolean operations. This method was adopted in CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport (MCAM), and tested with several models including the examples in Geant4 install package. The results showed that this method could convert standard CAD model accurately, and can be used for Geant4 automatic modeling. (authors)

Model-based safety analysis of a control system using Simulink and Simscape extended models

Directory of Open Access Journals (Sweden)

Shao Nian

2017-01-01

Full Text Available The aircraft or system safety assessment process is an integral part of the overall aircraft development cycle. It is usually characterized by a very high timely and financial effort and can become a critical design driver in certain cases. Therefore, an increasing demand of effective methods to assist the safety assessment process arises within the aerospace community. One approach is the utilization of model-based technology, which is already well-established in the system development, for safety assessment purposes. This paper mainly describes a new tool for Model-Based Safety Analysis. A formal model for an example system is generated and enriched with extended models. Then, system safety analyses are performed on the model with the assistance of automation tools and compared to the results of a manual analysis. The objective of this paper is to improve the increasingly complex aircraft systems development process. This paper develops a new model-based analysis tool in Simulink/Simscape environment.

Modeling of driver's collision avoidance maneuver based on controller switching model.

Science.gov (United States)

Kim, Jong-Hae; Hayakawa, Soichiro; Suzuki, Tatsuya; Hayashi, Koji; Okuma, Shigeru; Tsuchida, Nuio; Shimizu, Masayuki; Kido, Shigeyuki

2005-12-01

This paper presents a modeling strategy of human driving behavior based on the controller switching model focusing on the driver's collision avoidance maneuver. The driving data are collected by using the three-dimensional (3-D) driving simulator based on the CAVE Automatic Virtual Environment (CAVE), which provides stereoscopic immersive virtual environment. In our modeling, the control scenario of the human driver, that is, the mapping from the driver's sensory information to the operation of the driver such as acceleration, braking, and steering, is expressed by Piecewise Polynomial (PWP) model. Since the PWP model includes both continuous behaviors given by polynomials and discrete logical conditions, it can be regarded as a class of Hybrid Dynamical System (HDS). The identification problem for the PWP model is formulated as the Mixed Integer Linear Programming (MILP) by transforming the switching conditions into binary variables. From the obtained results, it is found that the driver appropriately switches the "control law" according to the sensory information. In addition, the driving characteristics of the beginner driver and the expert driver are compared and discussed. These results enable us to capture not only the physical meaning of the driving skill but the decision-making aspect (switching conditions) in the driver's collision avoidance maneuver as well.

Observation-Based Modeling for Model-Based Testing

NARCIS (Netherlands)

Kanstrén, T.; Piel, E.; Gross, H.G.

2009-01-01

One of the single most important reasons that modeling and modelbased testing are not yet common practice in industry is the perceived difficulty of making the models up to the level of detail and quality required for their automated processing. Models unleash their full potential only through

Cloud-Based Model Calibration Using OpenStudio: Preprint

Energy Technology Data Exchange (ETDEWEB)

Hale, E.; Lisell, L.; Goldwasser, D.; Macumber, D.; Dean, J.; Metzger, I.; Parker, A.; Long, N.; Ball, B.; Schott, M.; Weaver, E.; Brackney, L.

2014-03-01

OpenStudio is a free, open source Software Development Kit (SDK) and application suite for performing building energy modeling and analysis. The OpenStudio Parametric Analysis Tool has been extended to allow cloud-based simulation of multiple OpenStudio models parametrically related to a baseline model. This paper describes the new cloud-based simulation functionality and presents a model cali-bration case study. Calibration is initiated by entering actual monthly utility bill data into the baseline model. Multiple parameters are then varied over multiple iterations to reduce the difference between actual energy consumption and model simulation results, as calculated and visualized by billing period and by fuel type. Simulations are per-formed in parallel using the Amazon Elastic Cloud service. This paper highlights model parameterizations (measures) used for calibration, but the same multi-nodal computing architecture is available for other purposes, for example, recommending combinations of retrofit energy saving measures using the calibrated model as the new baseline.

Assessing model-based reasoning using evidence-centered design a suite of research-based design patterns

CERN Document Server

Mislevy, Robert J; Riconscente, Michelle; Wise Rutstein, Daisy; Ziker, Cindy

2017-01-01

This Springer Brief provides theory, practical guidance, and support tools to help designers create complex, valid assessment tasks for hard-to-measure, yet crucial, science education standards. Understanding, exploring, and interacting with the world through models characterizes science in all its branches and at all levels of education. Model-based reasoning is central to science education and thus science assessment. Current interest in developing and using models has increased with the release of the Next Generation Science Standards, which identified this as one of the eight practices of science and engineering. However, the interactive, complex, and often technology-based tasks that are needed to assess model-based reasoning in its fullest forms are difficult to develop. Building on research in assessment, science education, and learning science, this Brief describes a suite of design patterns that can help assessment designers, researchers, and teachers create tasks for assessing aspects of model-based...

Stochastic Differential Equation-Based Flexible Software Reliability Growth Model

Directory of Open Access Journals (Sweden)

P. K. Kapur

2009-01-01

Full Text Available Several software reliability growth models (SRGMs have been developed by software developers in tracking and measuring the growth of reliability. As the size of software system is large and the number of faults detected during the testing phase becomes large, so the change of the number of faults that are detected and removed through each debugging becomes sufficiently small compared with the initial fault content at the beginning of the testing phase. In such a situation, we can model the software fault detection process as a stochastic process with continuous state space. In this paper, we propose a new software reliability growth model based on Itô type of stochastic differential equation. We consider an SDE-based generalized Erlang model with logistic error detection function. The model is estimated and validated on real-life data sets cited in literature to show its flexibility. The proposed model integrated with the concept of stochastic differential equation performs comparatively better than the existing NHPP-based models.

Dependability modeling and assessment in UML-based software development.

Science.gov (United States)

Bernardi, Simona; Merseguer, José; Petriu, Dorina C

2012-01-01

Assessment of software nonfunctional properties (NFP) is an important problem in software development. In the context of model-driven development, an emerging approach for the analysis of different NFPs consists of the following steps: (a) to extend the software models with annotations describing the NFP of interest; (b) to transform automatically the annotated software model to the formalism chosen for NFP analysis; (c) to analyze the formal model using existing solvers; (d) to assess the software based on the results and give feedback to designers. Such a modeling→analysis→assessment approach can be applied to any software modeling language, be it general purpose or domain specific. In this paper, we focus on UML-based development and on the dependability NFP, which encompasses reliability, availability, safety, integrity, and maintainability. The paper presents the profile used to extend UML with dependability information, the model transformation to generate a DSPN formal model, and the assessment of the system properties based on the DSPN results.

Model based rib-cage unfolding for trauma CT

Science.gov (United States)

von Berg, Jens; Klinder, Tobias; Lorenz, Cristian

2018-03-01

A CT rib-cage unfolding method is proposed that does not require to determine rib centerlines but determines the visceral cavity surface by model base segmentation. Image intensities are sampled across this surface that is flattened using a model based 3D thin-plate-spline registration. An average rib centerline model projected onto this surface serves as a reference system for registration. The flattening registration is designed so that ribs similar to the centerline model are mapped onto parallel lines preserving their relative length. Ribs deviating from this model appear deviating from straight parallel ribs in the unfolded view, accordingly. As the mapping is continuous also the details in intercostal space and those adjacent to the ribs are rendered well. The most beneficial application area is Trauma CT where a fast detection of rib fractures is a crucial task. Specifically in trauma, automatic rib centerline detection may not be guaranteed due to fractures and dislocations. The application by visual assessment on the large public LIDC data base of lung CT proved general feasibility of this early work.

Graph Model Based Indoor Tracking

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Lu, Hua; Yang, Bin

2009-01-01

The tracking of the locations of moving objects in large indoor spaces is important, as it enables a range of applications related to, e.g., security and indoor navigation and guidance. This paper presents a graph model based approach to indoor tracking that offers a uniform data management...

Modelling Web-Based Instructional Systems

NARCIS (Netherlands)

Retalis, Symeon; Avgeriou, Paris

2002-01-01

The size and complexity of modern instructional systems, which are based on the World Wide Web, bring about great intricacy in their crafting, as there is not enough knowledge or experience in this field. This imposes the use of new instructional design models in order to achieve risk-mitigation,

Computer Based Modelling and Simulation

Indian Academy of Sciences (India)

GENERAL I ARTICLE. Computer Based ... universities, and later did system analysis, ... sonal computers (PC) and low cost software packages and tools. They can serve as useful learning experience through student projects. Models are .... Let us consider a numerical example: to calculate the velocity of a trainer aircraft ...

Bridging process-based and empirical approaches to modeling tree growth

Science.gov (United States)

Harry T. Valentine; Annikki Makela; Annikki Makela

2005-01-01

The gulf between process-based and empirical approaches to modeling tree growth may be bridged, in part, by the use of a common model. To this end, we have formulated a process-based model of tree growth that can be fitted and applied in an empirical mode. The growth model is grounded in pipe model theory and an optimal control model of crown development. Together, the...

ARIMA-Based Time Series Model of Stochastic Wind Power Generation

DEFF Research Database (Denmark)

Chen, Peiyuan; Pedersen, Troels; Bak-Jensen, Birgitte

2010-01-01

This paper proposes a stochastic wind power model based on an autoregressive integrated moving average (ARIMA) process. The model takes into account the nonstationarity and physical limits of stochastic wind power generation. The model is constructed based on wind power measurement of one year from...... the Nysted offshore wind farm in Denmark. The proposed limited-ARIMA (LARIMA) model introduces a limiter and characterizes the stochastic wind power generation by mean level, temporal correlation and driving noise. The model is validated against the measurement in terms of temporal correlation...... and probability distribution. The LARIMA model outperforms a first-order transition matrix based discrete Markov model in terms of temporal correlation, probability distribution and model parameter number. The proposed LARIMA model is further extended to include the monthly variation of the stochastic wind power...

A semi-analytical bearing model considering outer race flexibility for model based bearing load monitoring

Science.gov (United States)

Kerst, Stijn; Shyrokau, Barys; Holweg, Edward

2018-05-01

This paper proposes a novel semi-analytical bearing model addressing flexibility of the bearing outer race structure. It furthermore presents the application of this model in a bearing load condition monitoring approach. The bearing model is developed as current computational low cost bearing models fail to provide an accurate description of the more and more common flexible size and weight optimized bearing designs due to their assumptions of rigidity. In the proposed bearing model raceway flexibility is described by the use of static deformation shapes. The excitation of the deformation shapes is calculated based on the modelled rolling element loads and a Fourier series based compliance approximation. The resulting model is computational low cost and provides an accurate description of the rolling element loads for flexible outer raceway structures. The latter is validated by a simulation-based comparison study with a well-established bearing simulation software tool. An experimental study finally shows the potential of the proposed model in a bearing load monitoring approach.

Annotation-based feature extraction from sets of SBML models.

Science.gov (United States)

Alm, Rebekka; Waltemath, Dagmar; Wolfien, Markus; Wolkenhauer, Olaf; Henkel, Ron

2015-01-01

Model repositories such as BioModels Database provide computational models of biological systems for the scientific community. These models contain rich semantic annotations that link model entities to concepts in well-established bio-ontologies such as Gene Ontology. Consequently, thematically similar models are likely to share similar annotations. Based on this assumption, we argue that semantic annotations are a suitable tool to characterize sets of models. These characteristics improve model classification, allow to identify additional features for model retrieval tasks, and enable the comparison of sets of models. In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in SBML format which were composed from BioModels Database. To characterize each of these sets, we analyzed and extracted concepts from three frequently used ontologies, namely Gene Ontology, ChEBI and SBO. We find that three out of the methods are suitable to determine characteristic features for arbitrary sets of models: The selected features vary depending on the underlying model set, and they are also specific to the chosen model set. We show that the identified features map on concepts that are higher up in the hierarchy of the ontologies than the concepts used for model annotations. Our analysis also reveals that the information content of concepts in ontologies and their usage for model annotation do not correlate. Annotation-based feature extraction enables the comparison of model sets, as opposed to existing methods for model-to-keyword comparison, or model-to-model comparison.

An ontology-based approach for modelling architectural styles

OpenAIRE

Pahl, Claus; Giesecke, Simon; Hasselbring, Wilhelm

2007-01-01

peer-reviewed The conceptual modelling of software architectures is of central importance for the quality of a software system. A rich modelling language is required to integrate the different aspects of architecture modelling, such as architectural styles, structural and behavioural modelling, into a coherent framework.We propose an ontological approach for architectural style modelling based on description logic as an abstract, meta-level modelling instrument. Architect...

Global parameterization and validation of a two-leaf light use efficiency model for predicting gross primary production across FLUXNET sites: TL-LUE Parameterization and Validation

Energy Technology Data Exchange (ETDEWEB)

Zhou, Yanlian [Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing China; Joint Center for Global Change Studies, Beijing China; Wu, Xiaocui [International Institute for Earth System Sciences, Nanjing University, Nanjing China; Joint Center for Global Change Studies, Beijing China; Ju, Weimin [International Institute for Earth System Sciences, Nanjing University, Nanjing China; Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing China; Chen, Jing M. [International Institute for Earth System Sciences, Nanjing University, Nanjing China; Joint Center for Global Change Studies, Beijing China; Wang, Shaoqiang [Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing China; Wang, Huimin [Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing China; Yuan, Wenping [State Key Laboratory of Earth Surface Processes and Resource Ecology, Future Earth Research Institute, Beijing Normal University, Beijing China; Andrew Black, T. [Faculty of Land and Food Systems, University of British Columbia, Vancouver British Columbia Canada; Jassal, Rachhpal [Faculty of Land and Food Systems, University of British Columbia, Vancouver British Columbia Canada; Ibrom, Andreas [Department of Environmental Engineering, Technical University of Denmark (DTU), Kgs. Lyngby Denmark; Han, Shijie [Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang China; Yan, Junhua [South China Botanical Garden, Chinese Academy of Sciences, Guangzhou China; Margolis, Hank [Centre for Forest Studies, Faculty of Forestry, Geography and Geomatics, Laval University, Quebec City Quebec Canada; Roupsard, Olivier [CIRAD-Persyst, UMR Ecologie Fonctionnelle and Biogéochimie des Sols et Agroécosystèmes, SupAgro-CIRAD-INRA-IRD, Montpellier France; CATIE (Tropical Agricultural Centre for Research and Higher Education), Turrialba Costa Rica; Li, Yingnian [Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining China; Zhao, Fenghua [Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing China; Kiely, Gerard [Environmental Research Institute, Civil and Environmental Engineering Department, University College Cork, Cork Ireland; Starr, Gregory [Department of Biological Sciences, University of Alabama, Tuscaloosa Alabama USA; Pavelka, Marian [Laboratory of Plants Ecological Physiology, Institute of Systems Biology and Ecology AS CR, Prague Czech Republic; Montagnani, Leonardo [Forest Services, Autonomous Province of Bolzano, Bolzano Italy; Faculty of Sciences and Technology, Free University of Bolzano, Bolzano Italy; Wohlfahrt, Georg [Institute for Ecology, University of Innsbruck, Innsbruck Austria; European Academy of Bolzano, Bolzano Italy; D' Odorico, Petra [Grassland Sciences Group, Institute of Agricultural Sciences, ETH Zurich Switzerland; Cook, David [Atmospheric and Climate Research Program, Environmental Science Division, Argonne National Laboratory, Argonne Illinois USA; Arain, M. Altaf [McMaster Centre for Climate Change and School of Geography and Earth Sciences, McMaster University, Hamilton Ontario Canada; Bonal, Damien [INRA Nancy, UMR EEF, Champenoux France; Beringer, Jason [School of Earth and Environment, The University of Western Australia, Crawley Australia; Blanken, Peter D. [Department of Geography, University of Colorado Boulder, Boulder Colorado USA; Loubet, Benjamin [UMR ECOSYS, INRA, AgroParisTech, Université Paris-Saclay, Thiverval-Grignon France; Leclerc, Monique Y. [Department of Crop and Soil Sciences, College of Agricultural and Environmental Sciences, University of Georgia, Athens Georgia USA; Matteucci, Giorgio [Viea San Camillo Ed LellisViterbo, University of Tuscia, Viterbo Italy; Nagy, Zoltan [MTA-SZIE Plant Ecology Research Group, Szent Istvan University, Godollo Hungary; Olejnik, Janusz [Meteorology Department, Poznan University of Life Sciences, Poznan Poland; Department of Matter and Energy Fluxes, Global Change Research Center, Brno Czech Republic; Paw U, Kyaw Tha [Department of Land, Air and Water Resources, University of California, Davis California USA; Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge USA; Varlagin, Andrej [A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow Russia

2016-04-01

We present the first extended validation of satellitemicrowave (MW) liquidwater path (LWP) for low nonprecipitating clouds, from four operational sensors, against ship-borne observations from a three-channel MW radiometer collected along ship transects over the northeast Pacific during May–August 2013. Satellite MW retrievals have an overall correlation of 0.84 with ship observations and a bias of 9.3 g/m2. The bias for broken cloud scenes increases linearly with water vapor path and remains below 17.7 g/m2. In contrast, satelliteMWLWP is unbiased in overcast scenes with correlations up to 0.91, demonstrating that the retrievals are accurate and reliable under these conditions. Satellite MW retrievals produce a diurnal cycle amplitude consistent with ship-based observations (33 g/m2). Observations taken aboard extended ship cruises to evaluate not only satellite MW LWP but also LWP derived from visible/infrared sensors offer a new way to validate this important property over vast oceanic regions.

A DSM-based framework for integrated function modelling

DEFF Research Database (Denmark)

Eisenbart, Boris; Gericke, Kilian; Blessing, Lucienne T. M.

2017-01-01

an integrated function modelling framework, which specifically aims at relating between the different function modelling perspectives prominently addressed in different disciplines. It uses interlinked matrices based on the concept of DSM and MDM in order to facilitate cross-disciplinary modelling and analysis...... of the functionality of a system. The article further presents the application of the framework based on a product example. Finally, an empirical study in industry is presented. Therein, feedback on the potential of the proposed framework to support interdisciplinary design practice as well as on areas of further...

Bayesian based Diagnostic Model for Condition based Maintenance of Offshore Wind Farms

DEFF Research Database (Denmark)

Asgarpour, Masoud; Sørensen, John Dalsgaard

2018-01-01

Operation and maintenance costs are a major contributor to the Levelized Cost of Energy for electricity produced by offshore wind and can be significantly reduced if existing corrective actions are performed as efficiently as possible and if future corrective actions are avoided by performing...... sufficient preventive actions. This paper presents an applied and generic diagnostic model for fault detection and condition based maintenance of offshore wind components. The diagnostic model is based on two probabilistic matrices; first, a confidence matrix, representing the probability of detection using...... for a wind turbine component based on vibration, temperature, and oil particle fault detection methods. The last part of the paper will have a discussion of the case study results and present conclusions....

Model Based Control of Reefer Container Systems

DEFF Research Database (Denmark)

Sørensen, Kresten Kjær

This thesis is concerned with the development of model based control for the Star Cool refrigerated container (reefer) with the objective of reducing energy consumption. This project has been carried out under the Danish Industrial PhD programme and has been financed by Lodam together with the Da......This thesis is concerned with the development of model based control for the Star Cool refrigerated container (reefer) with the objective of reducing energy consumption. This project has been carried out under the Danish Industrial PhD programme and has been financed by Lodam together...

Perti Net-Based Workflow Access Control Model

Institute of Scientific and Technical Information of China (English)

陈卓; 骆婷; 石磊; 洪帆

2004-01-01

Access control is an important protection mechanism for information systems. This paper shows how to make access control in workflow system. We give a workflow access control model (WACM) based on several current access control models. The model supports roles assignment and dynamic authorization. The paper defines the workflow using Petri net. It firstly gives the definition and description of the workflow, and then analyzes the architecture of the workflow access control model (WACM). Finally, an example of an e-commerce workflow access control model is discussed in detail.

Not just the norm: exemplar-based models also predict face aftereffects.

Science.gov (United States)

Ross, David A; Deroche, Mickael; Palmeri, Thomas J

2014-02-01

The face recognition literature has considered two competing accounts of how faces are represented within the visual system: Exemplar-based models assume that faces are represented via their similarity to exemplars of previously experienced faces, while norm-based models assume that faces are represented with respect to their deviation from an average face, or norm. Face identity aftereffects have been taken as compelling evidence in favor of a norm-based account over an exemplar-based account. After a relatively brief period of adaptation to an adaptor face, the perceived identity of a test face is shifted toward a face with attributes opposite to those of the adaptor, suggesting an explicit psychological representation of the norm. Surprisingly, despite near universal recognition that face identity aftereffects imply norm-based coding, there have been no published attempts to simulate the predictions of norm- and exemplar-based models in face adaptation paradigms. Here, we implemented and tested variations of norm and exemplar models. Contrary to common claims, our simulations revealed that both an exemplar-based model and a version of a two-pool norm-based model, but not a traditional norm-based model, predict face identity aftereffects following face adaptation.

Perceptual decision neurosciences: a model-based review

NARCIS (Netherlands)

Mulder, M.J.; van Maanen, L.; Forstmann, B.U.

2014-01-01

In this review we summarize findings published over the past 10 years focusing on the neural correlates of perceptual decision-making. Importantly, this review highlights only studies that employ a model-based approach, i.e., they use quantitative cognitive models in combination with neuroscientific

Model-based uncertainty in species range prediction

DEFF Research Database (Denmark)

Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel

2006-01-01

Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions...

Structuring Qualitative Data for Agent-Based Modelling

NARCIS (Netherlands)

Ghorbani, Amineh; Dijkema, Gerard P.J.; Schrauwen, Noortje

2015-01-01

Using ethnography to build agent-based models may result in more empirically grounded simulations. Our study on innovation practice and culture in the Westland horticulture sector served to explore what information and data from ethnographic analysis could be used in models and how. MAIA, a

Knowledge representation to support reasoning based on multiple models

Science.gov (United States)

Gillam, April; Seidel, Jorge P.; Parker, Alice C.

1990-01-01

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

Map-based model of the cardiac action potential

International Nuclear Information System (INIS)

Pavlov, Evgeny A.; Osipov, Grigory V.; Chan, C.K.; Suykens, Johan A.K.

2011-01-01

A simple computationally efficient model which is capable of replicating the basic features of cardiac cell action potential is proposed. The model is a four-dimensional map and demonstrates good correspondence with real cardiac cells. Various regimes of cardiac activity, which can be reproduced by the proposed model, are shown. Bifurcation mechanisms of these regimes transitions are explained using phase space analysis. The dynamics of 1D and 2D lattices of coupled maps which model the behavior of electrically connected cells is discussed in the context of synchronization theory. -- Highlights: → Recent experimental-data based models are complicated for analysis and simulation. → The simplified map-based model of the cardiac cell is constructed. → The model is capable for replication of different types of cardiac activity. → The spatio-temporal dynamics of ensembles of coupled maps are investigated. → Received data are analyzed in context of biophysical processes in the myocardium.

Map-based model of the cardiac action potential

Energy Technology Data Exchange (ETDEWEB)

Pavlov, Evgeny A., E-mail: genie.pavlov@gmail.com [Department of Computational Mathematics and Cybernetics, Nizhny Novgorod State University, 23, Gagarin Avenue, 603950 Nizhny Novgorod (Russian Federation); Osipov, Grigory V. [Department of Computational Mathematics and Cybernetics, Nizhny Novgorod State University, 23, Gagarin Avenue, 603950 Nizhny Novgorod (Russian Federation); Chan, C.K. [Institute of Physics, Academia Sinica, 128 Sec. 2, Academia Road, Nankang, Taipei 115, Taiwan (China); Suykens, Johan A.K. [K.U. Leuven, ESAT-SCD/SISTA, Kasteelpark Arenberg 10, B-3001 Leuven (Heverlee) (Belgium)

2011-07-25

A simple computationally efficient model which is capable of replicating the basic features of cardiac cell action potential is proposed. The model is a four-dimensional map and demonstrates good correspondence with real cardiac cells. Various regimes of cardiac activity, which can be reproduced by the proposed model, are shown. Bifurcation mechanisms of these regimes transitions are explained using phase space analysis. The dynamics of 1D and 2D lattices of coupled maps which model the behavior of electrically connected cells is discussed in the context of synchronization theory. -- Highlights: → Recent experimental-data based models are complicated for analysis and simulation. → The simplified map-based model of the cardiac cell is constructed. → The model is capable for replication of different types of cardiac activity. → The spatio-temporal dynamics of ensembles of coupled maps are investigated. → Received data are analyzed in context of biophysical processes in the myocardium.

Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability

International Nuclear Information System (INIS)

Ouyang, Min; Zhao, Lijing; Hong, Liu; Pan, Zhezhe

2014-01-01

Recently numerous studies have applied complex network based models to study the performance and vulnerability of infrastructure systems under various types of attacks and hazards. But how effective are these models to capture their real performance response is still a question worthy of research. Taking the Chinese railway system as an example, this paper selects three typical complex network based models, including purely topological model (PTM), purely shortest path model (PSPM), and weight (link length) based shortest path model (WBSPM), to analyze railway accessibility and flow-based vulnerability and compare their results with those from the real train flow model (RTFM). The results show that the WBSPM can produce the train routines with 83% stations and 77% railway links identical to the real routines and can approach the RTFM the best for railway vulnerability under both single and multiple component failures. The correlation coefficient for accessibility vulnerability from WBSPM and RTFM under single station failures is 0.96 while it is 0.92 for flow-based vulnerability; under multiple station failures, where each station has the same failure probability fp, the WBSPM can produce almost identical vulnerability results with those from the RTFM under almost all failures scenarios when fp is larger than 0.62 for accessibility vulnerability and 0.86 for flow-based vulnerability

[Model-based biofuels system analysis: a review].

Science.gov (United States)

Chang, Shiyan; Zhang, Xiliang; Zhao, Lili; Ou, Xunmin

2011-03-01

Model-based system analysis is an important tool for evaluating the potential and impacts of biofuels, and for drafting biofuels technology roadmaps and targets. The broad reach of the biofuels supply chain requires that biofuels system analyses span a range of disciplines, including agriculture/forestry, energy, economics, and the environment. Here we reviewed various models developed for or applied to modeling biofuels, and presented a critical analysis of Agriculture/Forestry System Models, Energy System Models, Integrated Assessment Models, Micro-level Cost, Energy and Emission Calculation Models, and Specific Macro-level Biofuel Models. We focused on the models' strengths, weaknesses, and applicability, facilitating the selection of a suitable type of model for specific issues. Such an analysis was a prerequisite for future biofuels system modeling, and represented a valuable resource for researchers and policy makers.

Modeling analysis of pulsed magnetization process of magnetic core based on inverse Jiles-Atherton model

Science.gov (United States)

Liu, Yi; Zhang, He; Liu, Siwei; Lin, Fuchang

2018-05-01

The J-A (Jiles-Atherton) model is widely used to describe the magnetization characteristics of magnetic cores in a low-frequency alternating field. However, this model is deficient in the quantitative analysis of the eddy current loss and residual loss in a high-frequency magnetic field. Based on the decomposition of magnetization intensity, an inverse J-A model is established which uses magnetic flux density B as an input variable. Static and dynamic core losses under high frequency excitation are separated based on the inverse J-A model. Optimized parameters of the inverse J-A model are obtained based on particle swarm optimization. The platform for the pulsed magnetization characteristic test is designed and constructed. The hysteresis curves of ferrite and Fe-based nanocrystalline cores at high magnetization rates are measured. The simulated and measured hysteresis curves are presented and compared. It is found that the inverse J-A model can be used to describe the magnetization characteristics at high magnetization rates and to separate the static loss and dynamic loss accurately.

3D virtual human rapid modeling method based on top-down modeling mechanism

Directory of Open Access Journals (Sweden)

LI Taotao

2017-01-01

Full Text Available Aiming to satisfy the vast custom-made character demand of 3D virtual human and the rapid modeling in the field of 3D virtual reality, a new virtual human top-down rapid modeling method is put for-ward in this paper based on the systematic analysis of the current situation and shortage of the virtual hu-man modeling technology. After the top-level realization of virtual human hierarchical structure frame de-sign, modular expression of the virtual human and parameter design for each module is achieved gradu-al-level downwards. While the relationship of connectors and mapping restraints among different modules is established, the definition of the size and texture parameter is also completed. Standardized process is meanwhile produced to support and adapt the virtual human top-down rapid modeling practice operation. Finally, the modeling application, which takes a Chinese captain character as an example, is carried out to validate the virtual human rapid modeling method based on top-down modeling mechanism. The result demonstrates high modelling efficiency and provides one new concept for 3D virtual human geometric mod-eling and texture modeling.

Mechanics model for actin-based motility.

Science.gov (United States)

Lin, Yuan

2009-02-01

We present here a mechanics model for the force generation by actin polymerization. The possible adhesions between the actin filaments and the load surface, as well as the nucleation and capping of filament tips, are included in this model on top of the well-known elastic Brownian ratchet formulation. A closed form solution is provided from which the force-velocity relationship, summarizing the mechanics of polymerization, can be drawn. Model predictions on the velocity of moving beads driven by actin polymerization are consistent with experiment observations. This model also seems capable of explaining the enhanced actin-based motility of Listeria monocytogenes and beads by the presence of Vasodilator-stimulated phosphoprotein, as observed in recent experiments.

Discounted cost model for condition-based maintenance optimization

International Nuclear Information System (INIS)

Weide, J.A.M. van der; Pandey, M.D.; Noortwijk, J.M. van

2010-01-01

This paper presents methods to evaluate the reliability and optimize the maintenance of engineering systems that are damaged by shocks or transients arriving randomly in time and overall degradation is modeled as a cumulative stochastic point process. The paper presents a conceptually clear and comprehensive derivation of formulas for computing the discounted cost associated with a maintenance policy combining both condition-based and age-based criteria for preventive maintenance. The proposed discounted cost model provides a more realistic basis for optimizing the maintenance policies than those based on the asymptotic, non-discounted cost rate criterion.

Promoting Model-based Definition to Establish a Complete Product Definition.

Science.gov (United States)

Ruemler, Shawn P; Zimmerman, Kyle E; Hartman, Nathan W; Hedberg, Thomas; Feeny, Allison Barnard

2017-05-01

The manufacturing industry is evolving and starting to use 3D models as the central knowledge artifact for product data and product definition, or what is known as Model-based Definition (MBD). The Model-based Enterprise (MBE) uses MBD as a way to transition away from using traditional paper-based drawings and documentation. As MBD grows in popularity, it is imperative to understand what information is needed in the transition from drawings to models so that models represent all the relevant information needed for processes to continue efficiently. Finding this information can help define what data is common amongst different models in different stages of the lifecycle, which could help establish a Common Information Model. The Common Information Model is a source that contains common information from domain specific elements amongst different aspects of the lifecycle. To help establish this Common Information Model, information about how models are used in industry within different workflows needs to be understood. To retrieve this information, a survey mechanism was administered to industry professionals from various sectors. Based on the results of the survey a Common Information Model could not be established. However, the results gave great insight that will help in further investigation of the Common Information Model.

Cluster-based analysis of multi-model climate ensembles

Science.gov (United States)

Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

2018-06-01

Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and

Designing Network-based Business Model Ontology

DEFF Research Database (Denmark)

Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz

2015-01-01

Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....

Agent-based models in economics a toolkit

CERN Document Server

Fagiolo, Giorgio; Gallegati, Mauro; Richiardi, Matteo; Russo, Alberto

2018-01-01

In contrast to mainstream economics, complexity theory conceives the economy as a complex system of heterogeneous interacting agents characterised by limited information and bounded rationality. Agent Based Models (ABMs) are the analytical and computational tools developed by the proponents of this emerging methodology. Aimed at students and scholars of contemporary economics, this book includes a comprehensive toolkit for agent-based computational economics, now quickly becoming the new way to study evolving economic systems. Leading scholars in the field explain how ABMs can be applied fruitfully to many real-world economic examples and represent a great advancement over mainstream approaches. The essays discuss the methodological bases of agent-based approaches and demonstrate step-by-step how to build, simulate and analyse ABMs and how to validate their outputs empirically using the data. They also present a wide set of applications of these models to key economic topics, including the business cycle, lab...

A model-based approach to estimating forest area

Science.gov (United States)

Ronald E. McRoberts

2006-01-01

A logistic regression model based on forest inventory plot data and transformations of Landsat Thematic Mapper satellite imagery was used to predict the probability of forest for 15 study areas in Indiana, USA, and 15 in Minnesota, USA. Within each study area, model-based estimates of forest area were obtained for circular areas with radii of 5 km, 10 km, and 15 km and...

Base Flow Model Validation, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — The program focuses on turbulence modeling enhancements for predicting high-speed rocket base flows. A key component of the effort is the collection of high-fidelity...

Introducing Waqf Based Takaful Model in India

Directory of Open Access Journals (Sweden)

Syed Ahmed Salman

2014-03-01

Full Text Available Objective – Waqf is a unique feature of the socioeconomic system of Islam in a multi- religious and developing country like India. India is a rich country with waqf assets. The history of waqf in India can be traced back to 800 years ago. Most of the researchers, suggest how waqf can be used a tool to mitigate the poverty of Muslims. India has the third highest Muslim population after Indonesia and Pakistan. However, the majority of Muslims belong to the low income group and they are in need of help. It is believed that waqf can be utilized for the betterment of Indian Muslim community. Among the available uses of waqf assets, the main objective of this paper is to introduce waqf based takaful model in India. In addition, how this proposed model can be adopted in India is highlighted.Methods – Library research is applied since this paper relies on secondary data by thoroughlyreviewing the most relevant literature.Result – India as a rich country with waqf assets should fully utilize the resources to help the Muslims through takaful.Conclusion – In this study, we have proposed waqf based takaful model with the combination of the concepts mudarabah and wakalah for India. We recommend this model based on the background of the  country and situations. Since we have not tested the viability of this model in India, future research should be continued on this testing.Keywords : Wakaf, Takaful, Kemiskinan dan India

TP-model transformation-based-control design frameworks

CERN Document Server

Baranyi, Péter

2016-01-01

This book covers new aspects and frameworks of control, design, and optimization based on the TP model transformation and its various extensions. The author outlines the three main steps of polytopic and LMI based control design: 1) development of the qLPV state-space model, 2) generation of the polytopic model; and 3) application of LMI to derive controller and observer. He goes on to describe why literature has extensively studied LMI design, but has not focused much on the second step, in part because the generation and manipulation of the polytopic form was not tractable in many cases. The author then shows how the TP model transformation facilitates this second step and hence reveals new directions, leading to powerful design procedures and the formulation of new questions. The chapters of this book, and the complex dynamical control tasks which they cover, are organized so as to present and analyze the beneficial aspect of the family of approaches (control, design, and optimization). Additionally, the b...

Variability-Specific Abstraction Refinement for Family-Based Model Checking

DEFF Research Database (Denmark)

Dimovski, Aleksandar; Wasowski, Andrzej

2017-01-01

and property, while the number of possible scenarios is very large. In this work, we present an automatic iterative abstraction refinement procedure for family-based model checking. We use Craig interpolation to refine abstract variational models based on the obtained spurious counterexamples (traces...

Augment clinical measurement using a constraint-based esophageal model

Science.gov (United States)

Kou, Wenjun; Acharya, Shashank; Kahrilas, Peter; Patankar, Neelesh; Pandolfino, John

2017-11-01

Quantifying the mechanical properties of the esophageal wall is crucial to understanding impairments of trans-esophageal flow characteristic of several esophageal diseases. However, these data are unavailable owing to technological limitations of current clinical diagnostic instruments that instead display esophageal luminal cross sectional area based on intraluminal impedance change. In this work, we developed an esophageal model to predict bolus flow and the wall property based on clinical measurements. The model used the constraint-based immersed-boundary method developed previously by our group. Specifically, we first approximate the time-dependent wall geometry based on impedance planimetry data on luminal cross sectional area. We then fed these along with pressure data into the model and computed wall tension based on simulated pressure and flow fields, and the material property based on the strain-stress relationship. As examples, we applied this model to augment FLIP (Functional Luminal Imaging Probe) measurements in three clinical cases: a normal subject, achalasia, and eosinophilic esophagitis (EoE). Our findings suggest that the wall stiffness was greatest in the EoE case, followed by the achalasia case, and then the normal. This is supported by NIH Grant R01 DK56033 and R01 DK079902.

Development of a robust model-based reactivity control system

International Nuclear Information System (INIS)

Rovere, L.A.; Otaduy, P.J.; Brittain, C.R.

1990-01-01

This paper describes the development and implementation of a digital model-based reactivity control system that incorporates a knowledge of the plant physics into the control algorithm to improve system performance. This controller is composed of a model-based module and modified proportional-integral-derivative (PID) module. The model-based module has an estimation component to synthesize unmeasurable process variables that are necessary for the control action computation. These estimated variables, besides being used within the control algorithm, will be used for diagnostic purposes by a supervisory control system under development. The PID module compensates for inaccuracies in model coefficients by supplementing the model-based output with a correction term that eliminates any demand tracking or steady state errors. This control algorithm has been applied to develop controllers for a simulation of liquid metal reactors in a multimodular plant. It has shown its capability to track demands in neutron power much more accurately than conventional controllers, reducing overshoots to almost negligible value while providing a good degree of robustness to unmodeled dynamics. 10 refs., 4 figs

Agent-based modeling and simulation Part 3 : desktop ABMS.

Energy Technology Data Exchange (ETDEWEB)

Macal, C. M.; North, M. J.; Decision and Information Sciences

2007-01-01

Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use electronic laboratories to support their research. Some have gone so far as to contend that ABMS 'is a third way of doing science,' in addition to traditional deductive and inductive reasoning (Axelrod 1997b). Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, the threat of bio-warfare, and the factors responsible for the fall of ancient civilizations. This tutorial describes the theoretical and practical foundations of ABMS, identifies toolkits and methods for developing agent models, and illustrates the development of a simple agent-based model of shopper behavior using spreadsheets.

Model identification methodology for fluid-based inerters

Science.gov (United States)

Liu, Xiaofu; Jiang, Jason Zheng; Titurus, Branislav; Harrison, Andrew

2018-06-01

Inerter is the mechanical dual of the capacitor via the force-current analogy. It has the property that the force across the terminals is proportional to their relative acceleration. Compared with flywheel-based inerters, fluid-based forms have advantages of improved durability, inherent damping and simplicity of design. In order to improve the understanding of the physical behaviour of this fluid-based device, especially caused by the hydraulic resistance and inertial effects in the external tube, this work proposes a comprehensive model identification methodology. Firstly, a modelling procedure is established, which allows the topological arrangement of the mechanical networks to be obtained by mapping the damping, inertance and stiffness effects directly to their respective hydraulic counterparts. Secondly, an experimental sequence is followed, which separates the identification of friction, stiffness and various damping effects. Furthermore, an experimental set-up is introduced, where two pressure gauges are used to accurately measure the pressure drop across the external tube. The theoretical models with improved confidence are obtained using the proposed methodology for a helical-tube fluid inerter prototype. The sources of remaining discrepancies are further analysed.

Similar words analysis based on POS-CBOW language model

Directory of Open Access Journals (Sweden)

Dongru RUAN

2015-10-01

Full Text Available Similar words analysis is one of the important aspects in the field of natural language processing, and it has important research and application values in text classification, machine translation and information recommendation. Focusing on the features of Sina Weibo's short text, this paper presents a language model named as POS-CBOW, which is a kind of continuous bag-of-words language model with the filtering layer and part-of-speech tagging layer. The proposed approach can adjust the word vectors' similarity according to the cosine similarity and the word vectors' part-of-speech metrics. It can also filter those similar words set on the base of the statistical analysis model. The experimental result shows that the similar words analysis algorithm based on the proposed POS-CBOW language model is better than that based on the traditional CBOW language model.

A 4DCT imaging-based breathing lung model with relative hysteresis

Energy Technology Data Exchange (ETDEWEB)

Miyawaki, Shinjiro; Choi, Sanghun [IIHR – Hydroscience & Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Hoffman, Eric A. [Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Medicine, The University of Iowa, Iowa City, IA 52242 (United States); Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Lin, Ching-Long, E-mail: ching-long-lin@uiowa.edu [IIHR – Hydroscience & Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Mechanical and Industrial Engineering, The University of Iowa, 3131 Seamans Center, Iowa City, IA 52242 (United States)

2016-12-01

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry. - Highlights: • We developed a breathing human lung CFD model based on 4D-dynamic CT images. • The 4DCT-based breathing lung model is able to capture lung relative hysteresis. • A new boundary condition for lung model based on one static CT image was proposed. • The difference between lung models based on 4D and static CT images was quantified.

INDIVIDUAL BASED MODELLING APPROACH TO THERMAL ...

Science.gov (United States)

Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the costs and benefits of spatially-distributed cold water refugia for adult migrating salmon. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec

Gradient based filtering of digital elevation models

DEFF Research Database (Denmark)

Knudsen, Thomas; Andersen, Rune Carbuhn

We present a filtering method for digital terrain models (DTMs). The method is based on mathematical morphological filtering within gradient (slope) defined domains. The intention with the filtering procedure is to improbé the cartographic quality of height contours generated from a DTM based...

COMPARISON of FUZZY-BASED MODELS in LANDSLIDE HAZARD MAPPING

Directory of Open Access Journals (Sweden)

N. Mijani

2017-09-01

Full Text Available Landslide is one of the main geomorphic processes which effects on the development of prospect in mountainous areas and causes disastrous accidents. Landslide is an event which has different uncertain criteria such as altitude, slope, aspect, land use, vegetation density, precipitation, distance from the river and distance from the road network. This research aims to compare and evaluate different fuzzy-based models including Fuzzy Analytic Hierarchy Process (Fuzzy-AHP, Fuzzy Gamma and Fuzzy-OR. The main contribution of this paper reveals to the comprehensive criteria causing landslide hazard considering their uncertainties and comparison of different fuzzy-based models. The quantify of evaluation process are calculated by Density Ratio (DR and Quality Sum (QS. The proposed methodology implemented in Sari, one of the city of Iran which has faced multiple landslide accidents in recent years due to the particular environmental conditions. The achieved results of accuracy assessment based on the quantifier strated that Fuzzy-AHP model has higher accuracy compared to other two models in landslide hazard zonation. Accuracy of zoning obtained from Fuzzy-AHP model is respectively 0.92 and 0.45 based on method Precision (P and QS indicators. Based on obtained landslide hazard maps, Fuzzy-AHP, Fuzzy Gamma and Fuzzy-OR respectively cover 13, 26 and 35 percent of the study area with a very high risk level. Based on these findings, fuzzy-AHP model has been selected as the most appropriate method of zoning landslide in the city of Sari and the Fuzzy-gamma method with a minor difference is in the second order.

A physiological foundation for the nutrition-based efficiency wage model

DEFF Research Database (Denmark)

Dalgaard, Carl-Johan Lars; Strulik, Holger

2011-01-01

Drawing on recent research on allometric scaling and energy consumption, the present paper develops a nutrition-based efficiency wage model from first principles. The biologically micro-founded model allows us to address empirical criticism of the original nutrition-based efficiency wage model...

Knowledge-based inspection:modelling complex processes with the integrated Safeguards Modelling Method (iSMM)

International Nuclear Information System (INIS)

Abazi, F.

2011-01-01

Increased level of complexity in almost every discipline and operation today raises the demand for knowledge in order to successfully run an organization whether to generate profit or to attain a non-profit mission. Traditional way of transferring knowledge to information systems rich in data structures and complex algorithms continue to hinder the ability to swiftly turnover concepts into operations. Diagrammatic modelling commonly applied in engineering in order to represent concepts or reality remains to be an excellent way of converging knowledge from domain experts. The nuclear verification domain represents ever more a matter which has great importance to the World safety and security. Demand for knowledge about nuclear processes and verification activities used to offset potential misuse of nuclear technology will intensify with the growth of the subject technology. This Doctoral thesis contributes with a model-based approach for representing complex process such as nuclear inspections. The work presented contributes to other domains characterized with knowledge intensive and complex processes. Based on characteristics of a complex process a conceptual framework was established as the theoretical basis for creating a number of modelling languages to represent the domain. The integrated Safeguards Modelling Method (iSMM) is formalized through an integrated meta-model. The diagrammatic modelling languages represent the verification domain and relevant nuclear verification aspects. Such a meta-model conceptualizes the relation between practices of process management, knowledge management and domain specific verification principles. This fusion is considered as necessary in order to create quality processes. The study also extends the formalization achieved through a meta-model by contributing with a formalization language based on Pattern Theory. Through the use of graphical and mathematical constructs of the theory, process structures are formalized enhancing

Energy-based ferromagnetic material model with magnetic anisotropy