Model updating in flexible-link multibody systems

NASA Astrophysics Data System (ADS)

Belotti, R.; Caneva, G.; Palomba, I.; Richiedei, D.; Trevisani, A.

2016-09-01

The dynamic response of flexible-link multibody systems (FLMSs) can be predicted through nonlinear models based on finite elements, to describe the coupling between rigid- body and elastic behaviour. Their accuracy should be as high as possible to synthesize controllers and observers. Model updating based on experimental measurements is hence necessary. By taking advantage of the experimental modal analysis, this work proposes a model updating procedure for FLMSs and applies it experimentally to a planar robot. Indeed, several peculiarities of the model of FLMS should be carefully tackled. On the one hand, nonlinear models of a FLMS should be linearized about static equilibrium configurations. On the other, the experimental mode shapes should be corrected to be consistent with the elastic displacements represented in the model, which are defined with respect to a fictitious moving reference (the equivalent rigid link system). Then, since rotational degrees of freedom are also represented in the model, interpolation of the experimental data should be performed to match the model displacement vector. Model updating has been finally cast as an optimization problem in the presence of bounds on the feasible values, by also adopting methods to improve the numerical conditioning and to compute meaningful updated inertial and elastic parameters.

Comparative Performance Evaluation of Rainfall-runoff Models, Six of Black-box Type and One of Conceptual Type, From The Galway Flow Forecasting System (gffs) Package, Applied On Two Irish Catchments

NASA Astrophysics Data System (ADS)

Goswami, M.; O'Connor, K. M.; Shamseldin, A. Y.

The "Galway Real-Time River Flow Forecasting System" (GFFS) is a software pack- age developed at the Department of Engineering Hydrology, of the National University of Ireland, Galway, Ireland. It is based on a selection of lumped black-box and con- ceptual rainfall-runoff models, all developed in Galway, consisting primarily of both the non-parametric (NP) and parametric (P) forms of two black-box-type rainfall- runoff models, namely, the Simple Linear Model (SLM-NP and SLM-P) and the seasonally-based Linear Perturbation Model (LPM-NP and LPM-P), together with the non-parametric wetness-index-based Linearly Varying Gain Factor Model (LVGFM), the black-box Artificial Neural Network (ANN) Model, and the conceptual Soil Mois- ture Accounting and Routing (SMAR) Model. Comprised of the above suite of mod- els, the system enables the user to calibrate each model individually, initially without updating, and it is capable also of producing combined (i.e. consensus) forecasts us- ing the Simple Average Method (SAM), the Weighted Average Method (WAM), or the Artificial Neural Network Method (NNM). The updating of each model output is achieved using one of four different techniques, namely, simple Auto-Regressive (AR) updating, Linear Transfer Function (LTF) updating, Artificial Neural Network updating (NNU), and updating by the Non-linear Auto-Regressive Exogenous-input method (NARXM). The models exhibit a considerable range of variation in degree of complexity of structure, with corresponding degrees of complication in objective func- tion evaluation. Operating in continuous river-flow simulation and updating modes, these models and techniques have been applied to two Irish catchments, namely, the Fergus and the Brosna. A number of performance evaluation criteria have been used to comparatively assess the model discharge forecast efficiency.

Separate encoding of model-based and model-free valuations in the human brain.

PubMed

Beierholm, Ulrik R; Anen, Cedric; Quartz, Steven; Bossaerts, Peter

2011-10-01

Behavioral studies have long shown that humans solve problems in two ways, one intuitive and fast (System 1, model-free), and the other reflective and slow (System 2, model-based). The neurobiological basis of dual process problem solving remains unknown due to challenges of separating activation in concurrent systems. We present a novel neuroeconomic task that predicts distinct subjective valuation and updating signals corresponding to these two systems. We found two concurrent value signals in human prefrontal cortex: a System 1 model-free reinforcement signal and a System 2 model-based Bayesian signal. We also found a System 1 updating signal in striatal areas and a System 2 updating signal in lateral prefrontal cortex. Further, signals in prefrontal cortex preceded choices that are optimal according to either updating principle, while signals in anterior cingulate cortex and globus pallidus preceded deviations from optimal choice for reinforcement learning. These deviations tended to occur when uncertainty regarding optimal values was highest, suggesting that disagreement between dual systems is mediated by uncertainty rather than conflict, confirming recent theoretical proposals. Copyright © 2011 Elsevier Inc. All rights reserved.

Highly efficient model updating for structural condition assessment of large-scale bridges.

DOT National Transportation Integrated Search

2015-02-01

For eciently updating models of large-scale structures, the response surface (RS) method based on radial basis : functions (RBFs) is proposed to model the input-output relationship of structures. The key issues for applying : the proposed method a...

Efficient Storage Scheme of Covariance Matrix during Inverse Modeling

NASA Astrophysics Data System (ADS)

Mao, D.; Yeh, T. J.

2013-12-01

During stochastic inverse modeling, the covariance matrix of geostatistical based methods carries the information about the geologic structure. Its update during iterations reflects the decrease of uncertainty with the incorporation of observed data. For large scale problem, its storage and update cost too much memory and computational resources. In this study, we propose a new efficient storage scheme for storage and update. Compressed Sparse Column (CSC) format is utilized to storage the covariance matrix, and users can assign how many data they prefer to store based on correlation scales since the data beyond several correlation scales are usually not very informative for inverse modeling. After every iteration, only the diagonal terms of the covariance matrix are updated. The off diagonal terms are calculated and updated based on shortened correlation scales with a pre-assigned exponential model. The correlation scales are shortened by a coefficient, i.e. 0.95, every iteration to show the decrease of uncertainty. There is no universal coefficient for all the problems and users are encouraged to try several times. This new scheme is tested with 1D examples first. The estimated results and uncertainty are compared with the traditional full storage method. In the end, a large scale numerical model is utilized to validate this new scheme.

Automatic updating and 3D modeling of airport information from high resolution images using GIS and LIDAR data

NASA Astrophysics Data System (ADS)

Lv, Zheng; Sui, Haigang; Zhang, Xilin; Huang, Xianfeng

2007-11-01

As one of the most important geo-spatial objects and military establishment, airport is always a key target in fields of transportation and military affairs. Therefore, automatic recognition and extraction of airport from remote sensing images is very important and urgent for updating of civil aviation and military application. In this paper, a new multi-source data fusion approach on automatic airport information extraction, updating and 3D modeling is addressed. Corresponding key technologies including feature extraction of airport information based on a modified Ostu algorithm, automatic change detection based on new parallel lines-based buffer detection algorithm, 3D modeling based on gradual elimination of non-building points algorithm, 3D change detecting between old airport model and LIDAR data, typical CAD models imported and so on are discussed in detail. At last, based on these technologies, we develop a prototype system and the results show our method can achieve good effects.

Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating.

PubMed

Lu, Xiaoman; Zheng, Guang; Miller, Colton; Alvarado, Ernesto

2017-09-08

Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% ( n = 35, p < 0.05, RMSE = 2.20 kg/m²) and 85% ( n = 100, p < 0.01, RMSE = 1.71 kg/m²) of variation in field- and ALS-based forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB.

Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating

PubMed Central

Lu, Xiaoman; Zheng, Guang; Miller, Colton

2017-01-01

Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% (n = 35, p < 0.05, RMSE = 2.20 kg/m2) and 85% (n = 100, p < 0.01, RMSE = 1.71 kg/m2) of variation in field- and ALS-based forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB. PMID:28885556

Spatiotemporal access model based on reputation for the sensing layer of the IoT.

PubMed

Guo, Yunchuan; Yin, Lihua; Li, Chao; Qian, Junyan

2014-01-01

Access control is a key technology in providing security in the Internet of Things (IoT). The mainstream security approach proposed for the sensing layer of the IoT concentrates only on authentication while ignoring the more general models. Unreliable communications and resource constraints make the traditional access control techniques barely meet the requirements of the sensing layer of the IoT. In this paper, we propose a model that combines space and time with reputation to control access to the information within the sensing layer of the IoT. This model is called spatiotemporal access control based on reputation (STRAC). STRAC uses a lattice-based approach to decrease the size of policy bases. To solve the problem caused by unreliable communications, we propose both nondeterministic authorizations and stochastic authorizations. To more precisely manage the reputation of nodes, we propose two new mechanisms to update the reputation of nodes. These new approaches are the authority-based update mechanism (AUM) and the election-based update mechanism (EUM). We show how the model checker UPPAAL can be used to analyze the spatiotemporal access control model of an application. Finally, we also implement a prototype system to demonstrate the efficiency of our model.

Dynamic model updating based on strain mode shape and natural frequency using hybrid pattern search technique

NASA Astrophysics Data System (ADS)

Guo, Ning; Yang, Zhichun; Wang, Le; Ouyang, Yan; Zhang, Xinping

2018-05-01

Aiming at providing a precise dynamic structural finite element (FE) model for dynamic strength evaluation in addition to dynamic analysis. A dynamic FE model updating method is presented to correct the uncertain parameters of the FE model of a structure using strain mode shapes and natural frequencies. The strain mode shape, which is sensitive to local changes in structure, is used instead of the displacement mode for enhancing model updating. The coordinate strain modal assurance criterion is developed to evaluate the correlation level at each coordinate over the experimental and the analytical strain mode shapes. Moreover, the natural frequencies which provide the global information of the structure are used to guarantee the accuracy of modal properties of the global model. Then, the weighted summation of the natural frequency residual and the coordinate strain modal assurance criterion residual is used as the objective function in the proposed dynamic FE model updating procedure. The hybrid genetic/pattern-search optimization algorithm is adopted to perform the dynamic FE model updating procedure. Numerical simulation and model updating experiment for a clamped-clamped beam are performed to validate the feasibility and effectiveness of the present method. The results show that the proposed method can be used to update the uncertain parameters with good robustness. And the updated dynamic FE model of the beam structure, which can correctly predict both the natural frequencies and the local dynamic strains, is reliable for the following dynamic analysis and dynamic strength evaluation.

Mining moving object trajectories in location-based services for spatio-temporal database update

NASA Astrophysics Data System (ADS)

Guo, Danhuai; Cui, Weihong

2008-10-01

Advances in wireless transmission and mobile technology applied to LBS (Location-based Services) flood us with amounts of moving objects data. Vast amounts of gathered data from position sensors of mobile phones, PDAs, or vehicles hide interesting and valuable knowledge and describe the behavior of moving objects. The correlation between temporal moving patterns of moving objects and geo-feature spatio-temporal attribute was ignored, and the value of spatio-temporal trajectory data was not fully exploited too. Urban expanding or frequent town plan change bring about a large amount of outdated or imprecise data in spatial database of LBS, and they cannot be updated timely and efficiently by manual processing. In this paper we introduce a data mining approach to movement pattern extraction of moving objects, build a model to describe the relationship between movement patterns of LBS mobile objects and their environment, and put up with a spatio-temporal database update strategy in LBS database based on trajectories spatiotemporal mining. Experimental evaluation reveals excellent performance of the proposed model and strategy. Our original contribution include formulation of model of interaction between trajectory and its environment, design of spatio-temporal database update strategy based on moving objects data mining, and the experimental application of spatio-temporal database update by mining moving objects trajectories.

The AFIS tree growth model for updating annual forest inventories in Minnesota

Treesearch

Margaret R. Holdaway

2000-01-01

As the Forest Service moves towards annual inventories, states may use model predictions of growth to update unmeasured plots. A tree growth model (AFIS) based on the scaled Weibull function and using the average-adjusted model form is presented. Annual diameter growth for four species was modeled using undisturbed plots from Minnesota's Aspen-Birch and Northern...

Communication: Introducing prescribed biases in out-of-equilibrium Markov models

NASA Astrophysics Data System (ADS)

Dixit, Purushottam D.

2018-03-01

Markov models are often used in modeling complex out-of-equilibrium chemical and biochemical systems. However, many times their predictions do not agree with experiments. We need a systematic framework to update existing Markov models to make them consistent with constraints that are derived from experiments. Here, we present a framework based on the principle of maximum relative path entropy (minimum Kullback-Leibler divergence) to update Markov models using stationary state and dynamical trajectory-based constraints. We illustrate the framework using a biochemical model network of growth factor-based signaling. We also show how to find the closest detailed balanced Markov model to a given Markov model. Further applications and generalizations are discussed.

Numerical modeling and model updating for smart laminated structures with viscoelastic damping

NASA Astrophysics Data System (ADS)

Lu, Jun; Zhan, Zhenfei; Liu, Xu; Wang, Pan

2018-07-01

This paper presents a numerical modeling method combined with model updating techniques for the analysis of smart laminated structures with viscoelastic damping. Starting with finite element formulation, the dynamics model with piezoelectric actuators is derived based on the constitutive law of the multilayer plate structure. The frequency-dependent characteristics of the viscoelastic core are represented utilizing the anelastic displacement fields (ADF) parametric model in the time domain. The analytical model is validated experimentally and used to analyze the influencing factors of kinetic parameters under parametric variations. Emphasis is placed upon model updating for smart laminated structures to improve the accuracy of the numerical model. Key design variables are selected through the smoothing spline ANOVA statistical technique to mitigate the computational cost. This updating strategy not only corrects the natural frequencies but also improves the accuracy of damping prediction. The effectiveness of the approach is examined through an application problem of a smart laminated plate. It is shown that a good consistency can be achieved between updated results and measurements. The proposed method is computationally efficient.

Dynamic updating atlas for heart segmentation with a nonlinear field-based model.

PubMed

Cai, Ken; Yang, Rongqian; Yue, Hongwei; Li, Lihua; Ou, Shanxing; Liu, Feng

2017-09-01

Segmentation of cardiac computed tomography (CT) images is an effective method for assessing the dynamic function of the heart and lungs. In the atlas-based heart segmentation approach, the quality of segmentation usually relies upon atlas images, and the selection of those reference images is a key step. The optimal goal in this selection process is to have the reference images as close to the target image as possible. This study proposes an atlas dynamic update algorithm using a scheme of nonlinear deformation field. The proposed method is based on the features among double-source CT (DSCT) slices. The extraction of these features will form a base to construct an average model and the created reference atlas image is updated during the registration process. A nonlinear field-based model was used to effectively implement a 4D cardiac segmentation. The proposed segmentation framework was validated with 14 4D cardiac CT sequences. The algorithm achieved an acceptable accuracy (1.0-2.8 mm). Our proposed method that combines a nonlinear field-based model and dynamic updating atlas strategies can provide an effective and accurate way for whole heart segmentation. The success of the proposed method largely relies on the effective use of the prior knowledge of the atlas and the similarity explored among the to-be-segmented DSCT sequences. Copyright © 2016 John Wiley & Sons, Ltd.

Using an ensemble smoother to evaluate parameter uncertainty of an integrated hydrological model of Yanqi basin

NASA Astrophysics Data System (ADS)

Li, Ning; McLaughlin, Dennis; Kinzelbach, Wolfgang; Li, WenPeng; Dong, XinGuang

2015-10-01

Model uncertainty needs to be quantified to provide objective assessments of the reliability of model predictions and of the risk associated with management decisions that rely on these predictions. This is particularly true in water resource studies that depend on model-based assessments of alternative management strategies. In recent decades, Bayesian data assimilation methods have been widely used in hydrology to assess uncertain model parameters and predictions. In this case study, a particular data assimilation algorithm, the Ensemble Smoother with Multiple Data Assimilation (ESMDA) (Emerick and Reynolds, 2012), is used to derive posterior samples of uncertain model parameters and forecasts for a distributed hydrological model of Yanqi basin, China. This model is constructed using MIKESHE/MIKE11software, which provides for coupling between surface and subsurface processes (DHI, 2011a-d). The random samples in the posterior parameter ensemble are obtained by using measurements to update 50 prior parameter samples generated with a Latin Hypercube Sampling (LHS) procedure. The posterior forecast samples are obtained from model runs that use the corresponding posterior parameter samples. Two iterative sample update methods are considered: one based on an a perturbed observation Kalman filter update and one based on a square root Kalman filter update. These alternatives give nearly the same results and converge in only two iterations. The uncertain parameters considered include hydraulic conductivities, drainage and river leakage factors, van Genuchten soil property parameters, and dispersion coefficients. The results show that the uncertainty in many of the parameters is reduced during the smoother updating process, reflecting information obtained from the observations. Some of the parameters are insensitive and do not benefit from measurement information. The correlation coefficients among certain parameters increase in each iteration, although they generally stay below 0.50.

Spatiotemporal Access Model Based on Reputation for the Sensing Layer of the IoT

PubMed Central

Guo, Yunchuan; Yin, Lihua; Li, Chao

2014-01-01

Access control is a key technology in providing security in the Internet of Things (IoT). The mainstream security approach proposed for the sensing layer of the IoT concentrates only on authentication while ignoring the more general models. Unreliable communications and resource constraints make the traditional access control techniques barely meet the requirements of the sensing layer of the IoT. In this paper, we propose a model that combines space and time with reputation to control access to the information within the sensing layer of the IoT. This model is called spatiotemporal access control based on reputation (STRAC). STRAC uses a lattice-based approach to decrease the size of policy bases. To solve the problem caused by unreliable communications, we propose both nondeterministic authorizations and stochastic authorizations. To more precisely manage the reputation of nodes, we propose two new mechanisms to update the reputation of nodes. These new approaches are the authority-based update mechanism (AUM) and the election-based update mechanism (EUM). We show how the model checker UPPAAL can be used to analyze the spatiotemporal access control model of an application. Finally, we also implement a prototype system to demonstrate the efficiency of our model. PMID:25177731

Stochastic filtering for damage identification through nonlinear structural finite element model updating

NASA Astrophysics Data System (ADS)

Astroza, Rodrigo; Ebrahimian, Hamed; Conte, Joel P.

2015-03-01

This paper describes a novel framework that combines advanced mechanics-based nonlinear (hysteretic) finite element (FE) models and stochastic filtering techniques to estimate unknown time-invariant parameters of nonlinear inelastic material models used in the FE model. Using input-output data recorded during earthquake events, the proposed framework updates the nonlinear FE model of the structure. The updated FE model can be directly used for damage identification and further used for damage prognosis. To update the unknown time-invariant parameters of the FE model, two alternative stochastic filtering methods are used: the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). A three-dimensional, 5-story, 2-by-1 bay reinforced concrete (RC) frame is used to verify the proposed framework. The RC frame is modeled using fiber-section displacement-based beam-column elements with distributed plasticity and is subjected to the ground motion recorded at the Sylmar station during the 1994 Northridge earthquake. The results indicate that the proposed framework accurately estimate the unknown material parameters of the nonlinear FE model. The UKF outperforms the EKF when the relative root-mean-square error of the recorded responses are compared. In addition, the results suggest that the convergence of the estimate of modeling parameters is smoother and faster when the UKF is utilized.

Updating Known Distribution Models for Forecasting Climate Change Impact on Endangered Species

PubMed Central

Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo

2013-01-01

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only. PMID:23840330

Updating known distribution models for forecasting climate change impact on endangered species.

PubMed

Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo

2013-01-01

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only.

Frequency response function (FRF) based updating of a laser spot welded structure

NASA Astrophysics Data System (ADS)

Zin, M. S. Mohd; Rani, M. N. Abdul; Yunus, M. A.; Sani, M. S. M.; Wan Iskandar Mirza, W. I. I.; Mat Isa, A. A.

2018-04-01

The objective of this paper is to present frequency response function (FRF) based updating as a method for matching the finite element (FE) model of a laser spot welded structure with a physical test structure. The FE model of the welded structure was developed using CQUAD4 and CWELD element connectors, and NASTRAN was used to calculate the natural frequencies, mode shapes and FRF. Minimization of the discrepancies between the finite element and experimental FRFs was carried out using the exceptional numerical capability of NASTRAN Sol 200. The experimental work was performed under free-free boundary conditions using LMS SCADAS. Avast improvement in the finite element FRF was achieved using the frequency response function (FRF) based updating with two different objective functions proposed.

Neuroadaptation in Nicotine Addiction: Update on the Sensitization-Homeostasis Model

PubMed Central

DiFranza, Joseph R.; Huang, Wei; King, Jean

2012-01-01

The role of neuronal plasticity in supporting the addictive state has generated much research and some conceptual theories. One such theory, the sensitization-homeostasis (SH) model, postulates that nicotine suppresses craving circuits, and this triggers the development of homeostatic adaptations that autonomously support craving. Based on clinical studies, the SH model predicts the existence of three distinct forms of neuroplasticity that are responsible for withdrawal, tolerance and the resolution of withdrawal. Over the past decade, many controversial aspects of the SH model have become well established by the literature, while some details have been disproven. Here we update the model based on new studies showing that nicotine dependence develops through a set sequence of symptoms in all smokers, and that the latency to withdrawal, the time it takes for withdrawal symptoms to appear during abstinence, is initially very long but shortens by several orders of magnitude over time. We conclude by outlining directions for future research based on the updated model, and commenting on how new experimental studies can gain from the framework put forth in the SH model. PMID:24961259

Inter-firm Networks, Organizational Learning and Knowledge Updating: An Empirical Study

NASA Astrophysics Data System (ADS)

Zhang, Su-rong; Wang, Wen-ping

In the era of knowledge-based economy which information technology develops rapidly, the rate of knowledge updating has become a critical factor for enterprises to gaining competitive advantage .We build an interactional theoretical model among inter-firm networks, organizational learning and knowledge updating thereby and demonstrate it with empirical study at last. The result shows that inter-firm networks and organizational learning is the source of knowledge updating.

Speciation and Toxic Emissions from On road Vehicles, and Particulate Matter Emissions from Light-Duty Gasoline Vehicles in MOVES201X

EPA Science Inventory

Updated methane, non-methane organic gas, and volatile organic compound calculations based on speciation data. Updated speciation and toxic emission rates for new model year 2010 and later heavy-duty diesel engines. Updated particulate matter emission rates for 2004 and later mod...

Examining the Impact of an Updated Toluene Mechanism on Air Quality in the Eastern US

EPA Science Inventory

Model simulations were performed using the CB05 chemical mechanism containing the base and an updated toluene mechanisms for the eastern US. The updated toluene mechanism increased monthly mean 8-hr ozone by 1.0-2.0 ppbv in urban areas of Chicago, the northeast US, Detroit, Cleve...

Recommendations for kidney disease guideline updating: a report by the KDIGO Methods Committee

PubMed Central

Uhlig, Katrin; Berns, Jeffrey S.; Carville, Serena; Chan, Wiley; Cheung, Michael; Guyatt, Gordon H.; Hart, Allyson; Lewis, Sandra Zelman; Tonelli, Marcello; Webster, Angela C.; Wilt, Timothy J.; Kasiske, Bertram L.

2017-01-01

Updating rather than de novo guideline development now accounts for the majority of guideline activities for many guideline development organizations, including Kidney Disease: Improving Global Outcomes (KDIGO), an international kidney disease guideline development entity that has produced guidelines on kidney diseases since 2008. Increasingly, guideline developers are moving away from updating at fixed intervals in favor of more flexible approaches that use periodic expert assessment of guideline currency (with or without an updated systematic review) to determine the need for updating. Determining the need for guideline updating in an efficient, transparent, and timely manner is challenging, and updating of systematic reviews and guidelines is labor intensive. Ideally, guidelines should be updated dynamically when new evidence indicates a need for a substantive change in the guideline based on a priori criteria. This dynamic updating (sometimes referred to as a living guideline model) can be facilitated with the use of integrated electronic platforms that allow updating of specific recommendations. This report summarizes consensus-based recommendations from a panel of guideline methodology professionals on how to keep KDIGO guidelines up to date. PMID:26994574

Model Updating of Complex Structures Using the Combination of Component Mode Synthesis and Kriging Predictor

PubMed Central

Li, Yan; Wang, Dejun; Zhang, Shaoyi

2014-01-01

Updating the structural model of complex structures is time-consuming due to the large size of the finite element model (FEM). Using conventional methods for these cases is computationally expensive or even impossible. A two-level method, which combined the Kriging predictor and the component mode synthesis (CMS) technique, was proposed to ensure the successful implementing of FEM updating of large-scale structures. In the first level, the CMS was applied to build a reasonable condensed FEM of complex structures. In the second level, the Kriging predictor that was deemed as a surrogate FEM in structural dynamics was generated based on the condensed FEM. Some key issues of the application of the metamodel (surrogate FEM) to FEM updating were also discussed. Finally, the effectiveness of the proposed method was demonstrated by updating the FEM of a real arch bridge with the measured modal parameters. PMID:24634612

iTree-Hydro: Snow hydrology update for the urban forest hydrology model

Treesearch

Yang Yang; Theodore A. Endreny; David J. Nowak

2011-01-01

This article presents snow hydrology updates made to iTree-Hydro, previously called the Urban Forest Effects—Hydrology model. iTree-Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process-based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate...

Model-Based Reinforcement Learning under Concurrent Schedules of Reinforcement in Rodents

ERIC Educational Resources Information Center

Huh, Namjung; Jo, Suhyun; Kim, Hoseok; Sul, Jung Hoon; Jung, Min Whan

2009-01-01

Reinforcement learning theories postulate that actions are chosen to maximize a long-term sum of positive outcomes based on value functions, which are subjective estimates of future rewards. In simple reinforcement learning algorithms, value functions are updated only by trial-and-error, whereas they are updated according to the decision-maker's…

Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

PubMed Central

Qin, Lei; Snoussi, Hichem; Abdallah, Fahed

2014-01-01

We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences. PMID:24865883

State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy

NASA Astrophysics Data System (ADS)

Rakovec, O.; Weerts, A. H.; Hazenberg, P.; Torfs, P. J. J. F.; Uijlenhoet, R.

2012-09-01

This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model. The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty.

Dynamic updating of hippocampal object representations reflects new conceptual knowledge

PubMed Central

Mack, Michael L.; Love, Bradley C.; Preston, Alison R.

2016-01-01

Concepts organize the relationship among individual stimuli or events by highlighting shared features. Often, new goals require updating conceptual knowledge to reflect relationships based on different goal-relevant features. Here, our aim is to determine how hippocampal (HPC) object representations are organized and updated to reflect changing conceptual knowledge. Participants learned two classification tasks in which successful learning required attention to different stimulus features, thus providing a means to index how representations of individual stimuli are reorganized according to changing task goals. We used a computational learning model to capture how people attended to goal-relevant features and organized object representations based on those features during learning. Using representational similarity analyses of functional magnetic resonance imaging data, we demonstrate that neural representations in left anterior HPC correspond with model predictions of concept organization. Moreover, we show that during early learning, when concept updating is most consequential, HPC is functionally coupled with prefrontal regions. Based on these findings, we propose that when task goals change, object representations in HPC can be organized in new ways, resulting in updated concepts that highlight the features most critical to the new goal. PMID:27803320

Comparison of two optimization algorithms for fuzzy finite element model updating for damage detection in a wind turbine blade

NASA Astrophysics Data System (ADS)

Turnbull, Heather; Omenzetter, Piotr

2018-03-01

vDifficulties associated with current health monitoring and inspection practices combined with harsh, often remote, operational environments of wind turbines highlight the requirement for a non-destructive evaluation system capable of remotely monitoring the current structural state of turbine blades. This research adopted a physics based structural health monitoring methodology through calibration of a finite element model using inverse techniques. A 2.36m blade from a 5kW turbine was used as an experimental specimen, with operational modal analysis techniques utilised to realize the modal properties of the system. Modelling the experimental responses as fuzzy numbers using the sub-level technique, uncertainty in the response parameters was propagated back through the model and into the updating parameters. Initially, experimental responses of the blade were obtained, with a numerical model of the blade created and updated. Deterministic updating was carried out through formulation and minimisation of a deterministic objective function using both firefly algorithm and virus optimisation algorithm. Uncertainty in experimental responses were modelled using triangular membership functions, allowing membership functions of updating parameters (Young's modulus and shear modulus) to be obtained. Firefly algorithm and virus optimisation algorithm were again utilised, however, this time in the solution of fuzzy objective functions. This enabled uncertainty associated with updating parameters to be quantified. Varying damage location and severity was simulated experimentally through addition of small masses to the structure intended to cause a structural alteration. A damaged model was created, modelling four variable magnitude nonstructural masses at predefined points and updated to provide a deterministic damage prediction and information in relation to the parameters uncertainty via fuzzy updating.

A refined 2010-based VOC emission inventory and its improvement on modeling regional ozone in the Pearl River Delta Region, China.

PubMed

Yin, Shasha; Zheng, Junyu; Lu, Qing; Yuan, Zibing; Huang, Zhijiong; Zhong, Liuju; Lin, Hui

2015-05-01

Accurate and gridded VOC emission inventories are important for improving regional air quality model performance. In this study, a four-level VOC emission source categorization system was proposed. A 2010-based gridded Pearl River Delta (PRD) regional VOC emission inventory was developed with more comprehensive source coverage, latest emission factors, and updated activity data. The total anthropogenic VOC emission was estimated to be about 117.4 × 10(4)t, in which on-road mobile source shared the largest contribution, followed by industrial solvent use and industrial processes sources. Among the industrial solvent use source, furniture manufacturing and shoemaking were major VOC emission contributors. The spatial surrogates of VOC emission were updated for major VOC sources such as industrial sectors and gas stations. Subsector-based temporal characteristics were investigated and their temporal variations were characterized. The impacts of updated VOC emission estimates and spatial surrogates were evaluated by modeling O₃ concentration in the PRD region in the July and October of 2010, respectively. The results indicated that both updated emission estimates and spatial allocations can effectively reduce model bias on O₃ simulation. Further efforts should be made on the refinement of source classification, comprehensive collection of activity data, and spatial-temporal surrogates in order to reduce uncertainty in emission inventory and improve model performance. Copyright © 2015 Elsevier B.V. All rights reserved.

A Fatigue Crack Size Evaluation Method Based on Lamb Wave Simulation and Limited Experimental Data

PubMed Central

He, Jingjing; Ran, Yunmeng; Liu, Bin; Yang, Jinsong; Guan, Xuefei

2017-01-01

This paper presents a systematic and general method for Lamb wave-based crack size quantification using finite element simulations and Bayesian updating. The method consists of construction of a baseline quantification model using finite element simulation data and Bayesian updating with limited Lamb wave data from target structure. The baseline model correlates two proposed damage sensitive features, namely the normalized amplitude and phase change, with the crack length through a response surface model. The two damage sensitive features are extracted from the first received S0 mode wave package. The model parameters of the baseline model are estimated using finite element simulation data. To account for uncertainties from numerical modeling, geometry, material and manufacturing between the baseline model and the target model, Bayesian method is employed to update the baseline model with a few measurements acquired from the actual target structure. A rigorous validation is made using in-situ fatigue testing and Lamb wave data from coupon specimens and realistic lap-joint components. The effectiveness and accuracy of the proposed method is demonstrated under different loading and damage conditions. PMID:28902148

Fast Updating National Geo-Spatial Databases with High Resolution Imagery: China's Methodology and Experience

NASA Astrophysics Data System (ADS)

Chen, J.; Wang, D.; Zhao, R. L.; Zhang, H.; Liao, A.; Jiu, J.

2014-04-01

Geospatial databases are irreplaceable national treasure of immense importance. Their up-to-dateness referring to its consistency with respect to the real world plays a critical role in its value and applications. The continuous updating of map databases at 1:50,000 scales is a massive and difficult task for larger countries of the size of more than several million's kilometer squares. This paper presents the research and technological development to support the national map updating at 1:50,000 scales in China, including the development of updating models and methods, production tools and systems for large-scale and rapid updating, as well as the design and implementation of the continuous updating workflow. The use of many data sources and the integration of these data to form a high accuracy, quality checked product were required. It had in turn required up to date techniques of image matching, semantic integration, generalization, data base management and conflict resolution. Design and develop specific software tools and packages to support the large-scale updating production with high resolution imagery and large-scale data generalization, such as map generalization, GIS-supported change interpretation from imagery, DEM interpolation, image matching-based orthophoto generation, data control at different levels. A national 1:50,000 databases updating strategy and its production workflow were designed, including a full coverage updating pattern characterized by all element topographic data modeling, change detection in all related areas, and whole process data quality controlling, a series of technical production specifications, and a network of updating production units in different geographic places in the country.

Off-Highway Gasoline Consuption Estimation Models Used in the Federal Highway Administration Attribution Process: 2008 Updates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hwang, Ho-Ling; Davis, Stacy Cagle

2009-12-01

This report is designed to document the analysis process and estimation models currently used by the Federal Highway Administration (FHWA) to estimate the off-highway gasoline consumption and public sector fuel consumption. An overview of the entire FHWA attribution process is provided along with specifics related to the latest update (2008) on the Off-Highway Gasoline Use Model and the Public Use of Gasoline Model. The Off-Highway Gasoline Use Model is made up of five individual modules, one for each of the off-highway categories: agricultural, industrial and commercial, construction, aviation, and marine. This 2008 update of the off-highway models was the secondmore » major update (the first model update was conducted during 2002-2003) after they were originally developed in mid-1990. The agricultural model methodology, specifically, underwent a significant revision because of changes in data availability since 2003. Some revision to the model was necessary due to removal of certain data elements used in the original estimation method. The revised agricultural model also made use of some newly available information, published by the data source agency in recent years. The other model methodologies were not drastically changed, though many data elements were updated to improve the accuracy of these models. Note that components in the Public Use of Gasoline Model were not updated in 2008. A major challenge in updating estimation methods applied by the public-use model is that they would have to rely on significant new data collection efforts. In addition, due to resource limitation, several components of the models (both off-highway and public-us models) that utilized regression modeling approaches were not recalibrated under the 2008 study. An investigation of the Environmental Protection Agency's NONROAD2005 model was also carried out under the 2008 model update. Results generated from the NONROAD2005 model were analyzed, examined, and compared, to the extent that is possible on the overall totals, to the current FHWA estimates. Because NONROAD2005 model was designed for emission estimation purposes (i.e., not for measuring fuel consumption), it covers different equipment populations from those the FHWA models were based on. Thus, a direct comparison generally was not possible in most sectors. As a result, NONROAD2005 data were not used in the 2008 update of the FHWA off-highway models. The quality of fuel use estimates directly affect the data quality in many tables published in the Highway Statistics. Although updates have been made to the Off-Highway Gasoline Use Model and the Public Use Gasoline Model, some challenges remain due to aging model equations and discontinuation of data sources.« less

Progress on Updating the 1961-1990 National Solar Radiation Database

NASA Technical Reports Server (NTRS)

Renne, D.; Wilcox, S.; Marion, B.; George, R.; Myers, D.

2003-01-01

The 1961-1990 National Solar Radiation Data Base (NSRDB) provides a 30-year climate summary and solar characterization of 239 locations throughout the United States. Over the past several years, the National Renewable Energy Laboratory (NREL) has received numerous inquiries from a range of constituents as to whether an update of the database to include the 1990s will be developed. However, there are formidable challenges to creating an update of the serially complete station-specific database for the 1971-2000 period. During the 1990s, the National Weather Service changed its observational procedures from a human-based to an automated system, resulting in the loss of important input variables to the model used to complete the 1961-1990 NSRDB. As a result, alternative techniques are required for an update that covers the 1990s. This paper examines several alternative approaches for creating this update and describes preliminary NREL plans for implementing the update.

Parallel updating and weighting of multiple spatial maps for visual stability during whole body motion

PubMed Central

Medendorp, W. P.

2015-01-01

It is known that the brain uses multiple reference frames to code spatial information, including eye-centered and body-centered frames. When we move our body in space, these internal representations are no longer in register with external space, unless they are actively updated. Whether the brain updates multiple spatial representations in parallel, or whether it restricts its updating mechanisms to a single reference frame from which other representations are constructed, remains an open question. We developed an optimal integration model to simulate the updating of visual space across body motion in multiple or single reference frames. To test this model, we designed an experiment in which participants had to remember the location of a briefly presented target while being translated sideways. The behavioral responses were in agreement with a model that uses a combination of eye- and body-centered representations, weighted according to the reliability in which the target location is stored and updated in each reference frame. Our findings suggest that the brain simultaneously updates multiple spatial representations across body motion. Because both representations are kept in sync, they can be optimally combined to provide a more precise estimate of visual locations in space than based on single-frame updating mechanisms. PMID:26490289

Selection of experimental modal data sets for damage detection via model update

NASA Technical Reports Server (NTRS)

Doebling, S. W.; Hemez, F. M.; Barlow, M. S.; Peterson, L. D.; Farhat, C.

1993-01-01

When using a finite element model update algorithm for detecting damage in structures, it is important that the experimental modal data sets used in the update be selected in a coherent manner. In the case of a structure with extremely localized modal behavior, it is necessary to use both low and high frequency modes, but many of the modes in between may be excluded. In this paper, we examine two different mode selection strategies based on modal strain energy, and compare their success to the choice of an equal number of modes based merely on lowest frequency. Additionally, some parameters are introduced to enable a quantitative assessment of the success of our damage detection algorithm when using the various set selection criteria.

DUAL STATE-PARAMETER UPDATING SCHEME ON A CONCEPTUAL HYDROLOGIC MODEL USING SEQUENTIAL MONTE CARLO FILTERS

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Tachikawa, Yasuto; Shiiba, Michiharu; Kim, Sunmin

Applications of data assimilation techniques have been widely used to improve upon the predictability of hydrologic modeling. Among various data assimilation techniques, sequential Monte Carlo (SMC) filters, known as "particle filters" provide the capability to handle non-linear and non-Gaussian state-space models. This paper proposes a dual state-parameter updating scheme (DUS) based on SMC methods to estimate both state and parameter variables of a hydrologic model. We introduce a kernel smoothing method for the robust estimation of uncertain model parameters in the DUS. The applicability of the dual updating scheme is illustrated using the implementation of the storage function model on a middle-sized Japanese catchment. We also compare performance results of DUS combined with various SMC methods, such as SIR, ASIR and RPF.

Automated Simulation Updates based on Flight Data

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.; Ward, David G.

2007-01-01

A statistically-based method for using flight data to update aerodynamic data tables used in flight simulators is explained and demonstrated. A simplified wind-tunnel aerodynamic database for the F/A-18 aircraft is used as a starting point. Flight data from the NASA F-18 High Alpha Research Vehicle (HARV) is then used to update the data tables so that the resulting aerodynamic model characterizes the aerodynamics of the F-18 HARV. Prediction cases are used to show the effectiveness of the automated method, which requires no ad hoc adjustments by the analyst.

XFEM-based modeling of successive resections for preoperative image updating

NASA Astrophysics Data System (ADS)

Vigneron, Lara M.; Robe, Pierre A.; Warfield, Simon K.; Verly, Jacques G.

2006-03-01

We present a new method for modeling organ deformations due to successive resections. We use a biomechanical model of the organ, compute its volume-displacement solution based on the eXtended Finite Element Method (XFEM). The key feature of XFEM is that material discontinuities induced by every new resection can be handled without remeshing or mesh adaptation, as would be required by the conventional Finite Element Method (FEM). We focus on the application of preoperative image updating for image-guided surgery. Proof-of-concept demonstrations are shown for synthetic and real data in the context of neurosurgery.

A Bayesian procedure for evaluating the frequency of calibration factor updates in highway safety manual (HSM) applications.

PubMed

Saha, Dibakar; Alluri, Priyanka; Gan, Albert

2017-01-01

The Highway Safety Manual (HSM) presents statistical models to quantitatively estimate an agency's safety performance. The models were developed using data from only a few U.S. states. To account for the effects of the local attributes and temporal factors on crash occurrence, agencies are required to calibrate the HSM-default models for crash predictions. The manual suggests updating calibration factors every two to three years, or preferably on an annual basis. Given that the calibration process involves substantial time, effort, and resources, a comprehensive analysis of the required calibration factor update frequency is valuable to the agencies. Accordingly, the objective of this study is to evaluate the HSM's recommendation and determine the required frequency of calibration factor updates. A robust Bayesian estimation procedure is used to assess the variation between calibration factors computed annually, biennially, and triennially using data collected from over 2400 miles of segments and over 700 intersections on urban and suburban facilities in Florida. Bayesian model yields a posterior distribution of the model parameters that give credible information to infer whether the difference between calibration factors computed at specified intervals is credibly different from the null value which represents unaltered calibration factors between the comparison years or in other words, zero difference. The concept of the null value is extended to include the range of values that are practically equivalent to zero. Bayesian inference shows that calibration factors based on total crash frequency are required to be updated every two years in cases where the variations between calibration factors are not greater than 0.01. When the variations are between 0.01 and 0.05, calibration factors based on total crash frequency could be updated every three years. Copyright © 2016 Elsevier Ltd. All rights reserved.

A model-updating procedure to stimulate piezoelectric transducers accurately.

PubMed

Piranda, B; Ballandras, S; Steichen, W; Hecart, B

2001-09-01

The use of numerical calculations based on finite element methods (FEM) has yielded significant improvements in the simulation and design of piezoelectric transducers piezoelectric transducer utilized in acoustic imaging. However, the ultimate precision of such models is directly controlled by the accuracy of material characterization. The present work is dedicated to the development of a model-updating technique adapted to the problem of piezoelectric transducer. The updating process is applied using the experimental admittance of a given structure for which a finite element analysis is performed. The mathematical developments are reported and then applied to update the entries of a FEM of a two-layer structure (a PbZrTi-PZT-ridge glued on a backing) for which measurements were available. The efficiency of the proposed approach is demonstrated, yielding the definition of a new set of constants well adapted to predict the structure response accurately. Improvement of the proposed approach, consisting of the updating of material coefficients not only on the admittance but also on the impedance data, is finally discussed.

Game-Theoretic Models of Information Overload in Social Networks

NASA Astrophysics Data System (ADS)

Borgs, Christian; Chayes, Jennifer; Karrer, Brian; Meeder, Brendan; Ravi, R.; Reagans, Ray; Sayedi, Amin

We study the effect of information overload on user engagement in an asymmetric social network like Twitter. We introduce simple game-theoretic models that capture rate competition between celebrities producing updates in such networks where users non-strategically choose a subset of celebrities to follow based on the utility derived from high quality updates as well as disutility derived from having to wade through too many updates. Our two variants model the two behaviors of users dropping some potential connections (followership model) or leaving the network altogether (engagement model). We show that under a simple formulation of celebrity rate competition, there is no pure strategy Nash equilibrium under the first model. We then identify special cases in both models when pure rate equilibria exist for the celebrities: For the followership model, we show existence of a pure rate equilibrium when there is a global ranking of the celebrities in terms of the quality of their updates to users. This result also generalizes to the case when there is a partial order consistent with all the linear orders of the celebrities based on their qualities to the users. Furthermore, these equilibria can be computed in polynomial time. For the engagement model, pure rate equilibria exist when all users are interested in the same number of celebrities, or when they are interested in at most two. Finally, we also give a finite though inefficient procedure to determine if pure equilibria exist in the general case of the followership model.

Self-learning Monte Carlo method and cumulative update in fermion systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Junwei; Shen, Huitao; Qi, Yang

2017-06-07

In this study, we develop the self-learning Monte Carlo (SLMC) method, a general-purpose numerical method recently introduced to simulate many-body systems, for studying interacting fermion systems. Our method uses a highly efficient update algorithm, which we design and dub “cumulative update”, to generate new candidate configurations in the Markov chain based on a self-learned bosonic effective model. From a general analysis and a numerical study of the double exchange model as an example, we find that the SLMC with cumulative update drastically reduces the computational cost of the simulation, while remaining statistically exact. Remarkably, its computational complexity is far lessmore » than the conventional algorithm with local updates.« less

A keyword searchable attribute-based encryption scheme with attribute update for cloud storage.

PubMed

Wang, Shangping; Ye, Jian; Zhang, Yaling

2018-01-01

Ciphertext-policy attribute-based encryption (CP-ABE) scheme is a new type of data encryption primitive, which is very suitable for data cloud storage for its fine-grained access control. Keyword-based searchable encryption scheme enables users to quickly find interesting data stored in the cloud server without revealing any information of the searched keywords. In this work, we provide a keyword searchable attribute-based encryption scheme with attribute update for cloud storage, which is a combination of attribute-based encryption scheme and keyword searchable encryption scheme. The new scheme supports the user's attribute update, especially in our new scheme when a user's attribute need to be updated, only the user's secret key related with the attribute need to be updated, while other user's secret key and the ciphertexts related with this attribute need not to be updated with the help of the cloud server. In addition, we outsource the operation with high computation cost to cloud server to reduce the user's computational burden. Moreover, our scheme is proven to be semantic security against chosen ciphertext-policy and chosen plaintext attack in the general bilinear group model. And our scheme is also proven to be semantic security against chosen keyword attack under bilinear Diffie-Hellman (BDH) assumption.

A keyword searchable attribute-based encryption scheme with attribute update for cloud storage

PubMed Central

Wang, Shangping; Zhang, Yaling

2018-01-01

Ciphertext-policy attribute-based encryption (CP-ABE) scheme is a new type of data encryption primitive, which is very suitable for data cloud storage for its fine-grained access control. Keyword-based searchable encryption scheme enables users to quickly find interesting data stored in the cloud server without revealing any information of the searched keywords. In this work, we provide a keyword searchable attribute-based encryption scheme with attribute update for cloud storage, which is a combination of attribute-based encryption scheme and keyword searchable encryption scheme. The new scheme supports the user's attribute update, especially in our new scheme when a user's attribute need to be updated, only the user's secret key related with the attribute need to be updated, while other user's secret key and the ciphertexts related with this attribute need not to be updated with the help of the cloud server. In addition, we outsource the operation with high computation cost to cloud server to reduce the user's computational burden. Moreover, our scheme is proven to be semantic security against chosen ciphertext-policy and chosen plaintext attack in the general bilinear group model. And our scheme is also proven to be semantic security against chosen keyword attack under bilinear Diffie-Hellman (BDH) assumption. PMID:29795577

Aircraft engine sensor fault diagnostics using an on-line OBEM update method.

PubMed

Liu, Xiaofeng; Xue, Naiyu; Yuan, Ye

2017-01-01

This paper proposed a method to update the on-line health reference baseline of the On-Board Engine Model (OBEM) to maintain the effectiveness of an in-flight aircraft sensor Fault Detection and Isolation (FDI) system, in which a Hybrid Kalman Filter (HKF) was incorporated. Generated from a rapid in-flight engine degradation, a large health condition mismatch between the engine and the OBEM can corrupt the performance of the FDI. Therefore, it is necessary to update the OBEM online when a rapid degradation occurs, but the FDI system will lose estimation accuracy if the estimation and update are running simultaneously. To solve this problem, the health reference baseline for a nonlinear OBEM was updated using the proposed channel controller method. Simulations based on the turbojet engine Linear-Parameter Varying (LPV) model demonstrated the effectiveness of the proposed FDI system in the presence of substantial degradation, and the channel controller can ensure that the update process finishes without interference from a single sensor fault.

Aircraft engine sensor fault diagnostics using an on-line OBEM update method

PubMed Central

Liu, Xiaofeng; Xue, Naiyu; Yuan, Ye

2017-01-01

This paper proposed a method to update the on-line health reference baseline of the On-Board Engine Model (OBEM) to maintain the effectiveness of an in-flight aircraft sensor Fault Detection and Isolation (FDI) system, in which a Hybrid Kalman Filter (HKF) was incorporated. Generated from a rapid in-flight engine degradation, a large health condition mismatch between the engine and the OBEM can corrupt the performance of the FDI. Therefore, it is necessary to update the OBEM online when a rapid degradation occurs, but the FDI system will lose estimation accuracy if the estimation and update are running simultaneously. To solve this problem, the health reference baseline for a nonlinear OBEM was updated using the proposed channel controller method. Simulations based on the turbojet engine Linear-Parameter Varying (LPV) model demonstrated the effectiveness of the proposed FDI system in the presence of substantial degradation, and the channel controller can ensure that the update process finishes without interference from a single sensor fault. PMID:28182692

PRMS-IV, the precipitation-runoff modeling system, version 4

USGS Publications Warehouse

Markstrom, Steven L.; Regan, R. Steve; Hay, Lauren E.; Viger, Roland J.; Webb, Richard M.; Payn, Robert A.; LaFontaine, Jacob H.

2015-01-01

Computer models that simulate the hydrologic cycle at a watershed scale facilitate assessment of variability in climate, biota, geology, and human activities on water availability and flow. This report describes an updated version of the Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of various combinations of climate and land use on streamflow and general watershed hydrology. Several new model components were developed, and all existing components were updated, to enhance performance and supportability. This report describes the history, application, concepts, organization, and mathematical formulation of the Precipitation-Runoff Modeling System and its model components. This updated version provides improvements in (1) system flexibility for integrated science, (2) verification of conservation of water during simulation, (3) methods for spatial distribution of climate boundary conditions, and (4) methods for simulation of soil-water flow and storage.

Geometry control of long-span continuous girder concrete bridge during construction through finite element model updating

NASA Astrophysics Data System (ADS)

Wu, Jie; Yan, Quan-sheng; Li, Jian; Hu, Min-yi

2016-04-01

In bridge construction, geometry control is critical to ensure that the final constructed bridge has the consistent shape as design. A common method is by predicting the deflections of the bridge during each construction phase through the associated finite element models. Therefore, the cambers of the bridge during different construction phases can be determined beforehand. These finite element models are mostly based on the design drawings and nominal material properties. However, the accuracy of these bridge models can be large due to significant uncertainties of the actual properties of the materials used in construction. Therefore, the predicted cambers may not be accurate to ensure agreement of bridge geometry with design, especially for long-span bridges. In this paper, an improved geometry control method is described, which incorporates finite element (FE) model updating during the construction process based on measured bridge deflections. A method based on the Kriging model and Latin hypercube sampling is proposed to perform the FE model updating due to its simplicity and efficiency. The proposed method has been applied to a long-span continuous girder concrete bridge during its construction. Results show that the method is effective in reducing construction error and ensuring the accuracy of the geometry of the final constructed bridge.

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

PubMed

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.

Crucial role of strategy updating for coexistence of strategies in interaction networks.

PubMed

Zhang, Jianlei; Zhang, Chunyan; Cao, Ming; Weissing, Franz J

2015-04-01

Network models are useful tools for studying the dynamics of social interactions in a structured population. After a round of interactions with the players in their local neighborhood, players update their strategy based on the comparison of their own payoff with the payoff of one of their neighbors. Here we show that the assumptions made on strategy updating are of crucial importance for the strategy dynamics. In the first step, we demonstrate that seemingly small deviations from the standard assumptions on updating have major implications for the evolutionary outcome of two cooperation games: cooperation can more easily persist in a Prisoner's Dilemma game, while it can go more easily extinct in a Snowdrift game. To explain these outcomes, we develop a general model for the updating of states in a network that allows us to derive conditions for the steady-state coexistence of states (or strategies). The analysis reveals that coexistence crucially depends on the number of agents consulted for updating. We conclude that updating rules are as important for evolution on a network as network structure and the nature of the interaction.

Crucial role of strategy updating for coexistence of strategies in interaction networks

NASA Astrophysics Data System (ADS)

Zhang, Jianlei; Zhang, Chunyan; Cao, Ming; Weissing, Franz J.

2015-04-01

Network models are useful tools for studying the dynamics of social interactions in a structured population. After a round of interactions with the players in their local neighborhood, players update their strategy based on the comparison of their own payoff with the payoff of one of their neighbors. Here we show that the assumptions made on strategy updating are of crucial importance for the strategy dynamics. In the first step, we demonstrate that seemingly small deviations from the standard assumptions on updating have major implications for the evolutionary outcome of two cooperation games: cooperation can more easily persist in a Prisoner's Dilemma game, while it can go more easily extinct in a Snowdrift game. To explain these outcomes, we develop a general model for the updating of states in a network that allows us to derive conditions for the steady-state coexistence of states (or strategies). The analysis reveals that coexistence crucially depends on the number of agents consulted for updating. We conclude that updating rules are as important for evolution on a network as network structure and the nature of the interaction.

Uncertainty aggregation and reduction in structure-material performance prediction

NASA Astrophysics Data System (ADS)

Hu, Zhen; Mahadevan, Sankaran; Ao, Dan

2018-02-01

An uncertainty aggregation and reduction framework is presented for structure-material performance prediction. Different types of uncertainty sources, structural analysis model, and material performance prediction model are connected through a Bayesian network for systematic uncertainty aggregation analysis. To reduce the uncertainty in the computational structure-material performance prediction model, Bayesian updating using experimental observation data is investigated based on the Bayesian network. It is observed that the Bayesian updating results will have large error if the model cannot accurately represent the actual physics, and that this error will be propagated to the predicted performance distribution. To address this issue, this paper proposes a novel uncertainty reduction method by integrating Bayesian calibration with model validation adaptively. The observation domain of the quantity of interest is first discretized into multiple segments. An adaptive algorithm is then developed to perform model validation and Bayesian updating over these observation segments sequentially. Only information from observation segments where the model prediction is highly reliable is used for Bayesian updating; this is found to increase the effectiveness and efficiency of uncertainty reduction. A composite rotorcraft hub component fatigue life prediction model, which combines a finite element structural analysis model and a material damage model, is used to demonstrate the proposed method.

Deductive Updating Is Not Bayesian

ERIC Educational Resources Information Center

Markovits, Henry; Brisson, Janie; de Chantal, Pier-Luc

2015-01-01

One of the major debates concerning the nature of inferential reasoning is between counterexample-based theories such as mental model theory and probabilistic theories. This study looks at conclusion updating after the addition of statistical information to examine the hypothesis that deductive reasoning cannot be explained by probabilistic…

Model-based vision for space applications

NASA Technical Reports Server (NTRS)

Chaconas, Karen; Nashman, Marilyn; Lumia, Ronald

1992-01-01

This paper describes a method for tracking moving image features by combining spatial and temporal edge information with model based feature information. The algorithm updates the two-dimensional position of object features by correlating predicted model features with current image data. The results of the correlation process are used to compute an updated model. The algorithm makes use of a high temporal sampling rate with respect to spatial changes of the image features and operates in a real-time multiprocessing environment. Preliminary results demonstrate successful tracking for image feature velocities between 1.1 and 4.5 pixels every image frame. This work has applications for docking, assembly, retrieval of floating objects and a host of other space-related tasks.

Scenario driven data modelling: a method for integrating diverse sources of data and data streams

DOEpatents

Brettin, Thomas S.; Cottingham, Robert W.; Griffith, Shelton D.; Quest, Daniel J.

2015-09-08

A system and method of integrating diverse sources of data and data streams is presented. The method can include selecting a scenario based on a topic, creating a multi-relational directed graph based on the scenario, identifying and converting resources in accordance with the scenario and updating the multi-directed graph based on the resources, identifying data feeds in accordance with the scenario and updating the multi-directed graph based on the data feeds, identifying analytical routines in accordance with the scenario and updating the multi-directed graph using the analytical routines and identifying data outputs in accordance with the scenario and defining queries to produce the data outputs from the multi-directed graph.

Input-output model for MACCS nuclear accident impacts estimation¹

DOE Office of Scientific and Technical Information (OSTI.GOV)

Outkin, Alexander V.; Bixler, Nathan E.; Vargas, Vanessa N

Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domesticmore » product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.« less

State updating of a distributed hydrological model with Ensemble Kalman Filtering: Effects of updating frequency and observation network density on forecast accuracy

NASA Astrophysics Data System (ADS)

Rakovec, O.; Weerts, A.; Hazenberg, P.; Torfs, P.; Uijlenhoet, R.

2012-12-01

This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model (Rakovec et al., 2012a). The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. The uncertain precipitation model forcings were obtained using a time-dependent multivariate spatial conditional simulation method (Rakovec et al., 2012b), which is further made conditional on preceding simulations. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty. Rakovec, O., Weerts, A. H., Hazenberg, P., Torfs, P. J. J. F., and Uijlenhoet, R.: State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy, Hydrol. Earth Syst. Sci. Discuss., 9, 3961-3999, doi:10.5194/hessd-9-3961-2012, 2012a. Rakovec, O., Hazenberg, P., Torfs, P. J. J. F., Weerts, A. H., and Uijlenhoet, R.: Generating spatial precipitation ensembles: impact of temporal correlation structure, Hydrol. Earth Syst. Sci. Discuss., 9, 3087-3127, doi:10.5194/hessd-9-3087-2012, 2012b.

Synthetic Modifications In the Frequency Domain for Finite Element Model Update and Damage Detection

DTIC Science & Technology

2017-09-01

Sensitivity-based finite element model updating and structural damage detection has been limited by the number of modes available in a vibration test and...increase the number of modes and corresponding sensitivity data by artificially constraining the structure under test, producing a large number of... structural modifications to the measured data, including both springs-to-ground and mass modifications. This is accomplished with frequency domain

A last updating evolution model for online social networks

NASA Astrophysics Data System (ADS)

Bu, Zhan; Xia, Zhengyou; Wang, Jiandong; Zhang, Chengcui

2013-05-01

As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. However, there is very limited knowledge about the actual evolution of the online social networks. In this paper, we propose and study a novel evolution network model with the new concept of “last updating time”, which exists in many real-life online social networks. The last updating evolution network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks. What is more, we also found that it has the “small-world effect”, which is the inherent property of most social networks. Simulation experiment based on this model show that the results and the real-life data are consistent, which means that our model is valid.

Early Prediction of Intensive Care Unit-Acquired Weakness: A Multicenter External Validation Study.

PubMed

Witteveen, Esther; Wieske, Luuk; Sommers, Juultje; Spijkstra, Jan-Jaap; de Waard, Monique C; Endeman, Henrik; Rijkenberg, Saskia; de Ruijter, Wouter; Sleeswijk, Mengalvio; Verhamme, Camiel; Schultz, Marcus J; van Schaik, Ivo N; Horn, Janneke

2018-01-01

An early diagnosis of intensive care unit-acquired weakness (ICU-AW) is often not possible due to impaired consciousness. To avoid a diagnostic delay, we previously developed a prediction model, based on single-center data from 212 patients (development cohort), to predict ICU-AW at 2 days after ICU admission. The objective of this study was to investigate the external validity of the original prediction model in a new, multicenter cohort and, if necessary, to update the model. Newly admitted ICU patients who were mechanically ventilated at 48 hours after ICU admission were included. Predictors were prospectively recorded, and the outcome ICU-AW was defined by an average Medical Research Council score <4. In the validation cohort, consisting of 349 patients, we analyzed performance of the original prediction model by assessment of calibration and discrimination. Additionally, we updated the model in this validation cohort. Finally, we evaluated a new prediction model based on all patients of the development and validation cohort. Of 349 analyzed patients in the validation cohort, 190 (54%) developed ICU-AW. Both model calibration and discrimination of the original model were poor in the validation cohort. The area under the receiver operating characteristics curve (AUC-ROC) was 0.60 (95% confidence interval [CI]: 0.54-0.66). Model updating methods improved calibration but not discrimination. The new prediction model, based on all patients of the development and validation cohort (total of 536 patients) had a fair discrimination, AUC-ROC: 0.70 (95% CI: 0.66-0.75). The previously developed prediction model for ICU-AW showed poor performance in a new independent multicenter validation cohort. Model updating methods improved calibration but not discrimination. The newly derived prediction model showed fair discrimination. This indicates that early prediction of ICU-AW is still challenging and needs further attention.

[Purity Detection Model Update of Maize Seeds Based on Active Learning].

PubMed

Tang, Jin-ya; Huang, Min; Zhu, Qi-bing

2015-08-01

Seed purity reflects the degree of seed varieties in typical consistent characteristics, so it is great important to improve the reliability and accuracy of seed purity detection to guarantee the quality of seeds. Hyperspectral imaging can reflect the internal and external characteristics of seeds at the same time, which has been widely used in nondestructive detection of agricultural products. The essence of nondestructive detection of agricultural products using hyperspectral imaging technique is to establish the mathematical model between the spectral information and the quality of agricultural products. Since the spectral information is easily affected by the sample growth environment, the stability and generalization of model would weaken when the test samples harvested from different origin and year. Active learning algorithm was investigated to add representative samples to expand the sample space for the original model, so as to implement the rapid update of the model's ability. Random selection (RS) and Kennard-Stone algorithm (KS) were performed to compare the model update effect with active learning algorithm. The experimental results indicated that in the division of different proportion of sample set (1:1, 3:1, 4:1), the updated purity detection model for maize seeds from 2010 year which was added 40 samples selected by active learning algorithm from 2011 year increased the prediction accuracy for 2011 new samples from 47%, 33.75%, 49% to 98.89%, 98.33%, 98.33%. For the updated purity detection model of 2011 year, its prediction accuracy for 2010 new samples increased by 50.83%, 54.58%, 53.75% to 94.57%, 94.02%, 94.57% after adding 56 new samples from 2010 year. Meanwhile the effect of model updated by active learning algorithm was better than that of RS and KS. Therefore, the update for purity detection model of maize seeds is feasible by active learning algorithm.

Nonlinear finite element model updating for damage identification of civil structures using batch Bayesian estimation

NASA Astrophysics Data System (ADS)

Ebrahimian, Hamed; Astroza, Rodrigo; Conte, Joel P.; de Callafon, Raymond A.

2017-02-01

This paper presents a framework for structural health monitoring (SHM) and damage identification of civil structures. This framework integrates advanced mechanics-based nonlinear finite element (FE) modeling and analysis techniques with a batch Bayesian estimation approach to estimate time-invariant model parameters used in the FE model of the structure of interest. The framework uses input excitation and dynamic response of the structure and updates a nonlinear FE model of the structure to minimize the discrepancies between predicted and measured response time histories. The updated FE model can then be interrogated to detect, localize, classify, and quantify the state of damage and predict the remaining useful life of the structure. As opposed to recursive estimation methods, in the batch Bayesian estimation approach, the entire time history of the input excitation and output response of the structure are used as a batch of data to estimate the FE model parameters through a number of iterations. In the case of non-informative prior, the batch Bayesian method leads to an extended maximum likelihood (ML) estimation method to estimate jointly time-invariant model parameters and the measurement noise amplitude. The extended ML estimation problem is solved efficiently using a gradient-based interior-point optimization algorithm. Gradient-based optimization algorithms require the FE response sensitivities with respect to the model parameters to be identified. The FE response sensitivities are computed accurately and efficiently using the direct differentiation method (DDM). The estimation uncertainties are evaluated based on the Cramer-Rao lower bound (CRLB) theorem by computing the exact Fisher Information matrix using the FE response sensitivities with respect to the model parameters. The accuracy of the proposed uncertainty quantification approach is verified using a sampling approach based on the unscented transformation. Two validation studies, based on realistic structural FE models of a bridge pier and a moment resisting steel frame, are performed to validate the performance and accuracy of the presented nonlinear FE model updating approach and demonstrate its application to SHM. These validation studies show the excellent performance of the proposed framework for SHM and damage identification even in the presence of high measurement noise and/or way-out initial estimates of the model parameters. Furthermore, the detrimental effects of the input measurement noise on the performance of the proposed framework are illustrated and quantified through one of the validation studies.

Exhaust Emission Rates for Heavy-Duty On road Vehicles in MOVES201X

EPA Science Inventory

Updated running exhaust gaseous emission rates (THC, CO, NOx, CO2) for heavy-duty diesel trucks model year 2010 and later based on portable emission measurements from the manufacturer-run, heavy-duty in-use testing (HDIUT) program. Updated cold start emission rates and soak adjus...

Impact of observation error structure on satellite soil moisture assimilation into a rainfall-runoff model

USDA-ARS?s Scientific Manuscript database

In Ensemble Kalman Filter (EnKF)-based data assimilation, the background prediction of a model is updated using observations and relative weights based on the model prediction and observation uncertainties. In practice, both model and observation uncertainties are difficult to quantify and they have...

Updates to the NASA Space Telecommunications Radio System (STRS) Architecture

NASA Technical Reports Server (NTRS)

Kacpura, Thomas J.; Handler, Louis M.; Briones, Janette; Hall, Charles S.

2008-01-01

This paper describes an update of the Space Telecommunications Radio System (STRS) open architecture for NASA space based radios. The STRS architecture has been defined as a framework for the design, development, operation and upgrade of space based software defined radios, where processing resources are constrained. The architecture has been updated based upon reviews by NASA missions, radio providers, and component vendors. The STRS Standard prescribes the architectural relationship between the software elements used in software execution and defines the Application Programmer Interface (API) between the operating environment and the waveform application. Modeling tools have been adopted to present the architecture. The paper will present a description of the updated API, configuration files, and constraints. Minimum compliance is discussed for early implementations. The paper then closes with a summary of the changes made and discussion of the relevant alignment with the Object Management Group (OMG) SWRadio specification, and enhancements to the specialized signal processing abstraction.

The Cancer Family Caregiving Experience: An Updated and Expanded Conceptual Model

PubMed Central

Fletcher, Barbara Swore; Miaskowski, Christine; Given, Barbara; Schumacher, Karen

2011-01-01

Objective The decade from 2000–2010 was an era of tremendous growth in family caregiving research specific to the cancer population. This research has implications for how cancer family caregiving is conceptualized, yet the most recent comprehensive model of cancer family caregiving was published ten years ago. Our objective was to develop an updated and expanded comprehensive model of the cancer family caregiving experience, derived from concepts and variables used in research during past ten years. Methods A conceptual model was developed based on cancer family caregiving research published from 2000–2010. Results Our updated and expanded model has three main elements: 1) the stress process, 2) contextual factors, and 3) the cancer trajectory. Emerging ways of conceptualizing the relationships between and within model elements are addressed, as well as an emerging focus on caregiver-patient dyads as the unit of analysis. Conclusions Cancer family caregiving research has grown dramatically since 2000 resulting in a greatly expanded conceptual landscape. This updated and expanded model of the cancer family caregiving experience synthesizes the conceptual implications of an international body of work and demonstrates tremendous progress in how cancer family caregiving research is conceptualized. PMID:22000812

Systematic Review: A Reevaluation and Update of the Integrative (Trajectory) Model of Pediatric Medical Traumatic Stress.

PubMed

Price, Julia; Kassam-Adams, Nancy; Alderfer, Melissa A; Christofferson, Jennifer; Kazak, Anne E

2016-01-01

The objective of this systematic review is to reevaluate and update the Integrative Model of Pediatric Medical Traumatic Stress (PMTS; Kazak et al., 2006), which provides a conceptual framework for traumatic stress responses across pediatric illnesses and injuries. Using established systematic review guidelines, we searched PsycINFO, Cumulative Index to Nursing and Allied Health Literature, and PubMed (producing 216 PMTS papers published since 2005), extracted findings for review, and organized and interpreted findings within the Integrative Model framework. Recent PMTS research has included additional pediatric populations, used advanced longitudinal modeling techniques, clarified relations between parent and child PMTS, and considered effects of PMTS on health outcomes. Results support and extend the model's five assumptions, and suggest a sixth assumption related to health outcomes and PMTS. Based on new evidence, the renamed Integrative Trajectory Model includes phases corresponding with medical events, adds family-centered trajectories, reaffirms a competency-based framework, and suggests updated assessment and intervention implications. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Physiologically-based pharmacokinetic (PBPK) modeling to explore potential metabolic pathways of bromochloromethane in rats.

EPA Science Inventory

Bromochloromethane (BCM) is a volatile organic compound and a by-product of disinfection of water by chlorination. Physiologically based pharmacokinetic (PBPK) models are used in risk assessment applications and a PBPK model for BCM, Updated with F-344 specific input parameters,...

Update on Small Modular Reactors Dynamic System Modeling Tool: Web Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hale, Richard Edward; Cetiner, Sacit M.; Fugate, David L.

Previous reports focused on the development of component and system models as well as end-to-end system models using Modelica and Dymola for two advanced reactor architectures: (1) Advanced Liquid Metal Reactor and (2) fluoride high-temperature reactor (FHR). The focus of this report is the release of the first beta version of the web-based application for model use and collaboration, as well as an update on the FHR model. The web-based application allows novice users to configure end-to-end system models from preconfigured choices to investigate the instrumentation and controls implications of these designs and allows for the collaborative development of individualmore » component models that can be benchmarked against test systems for potential inclusion in the model library. A description of this application is provided along with examples of its use and a listing and discussion of all the models that currently exist in the library.« less

The diagnostic value of specific IgE to Ara h 2 to predict peanut allergy in children is comparable to a validated and updated diagnostic prediction model.

PubMed

Klemans, Rob J B; Otte, Dianne; Knol, Mirjam; Knol, Edward F; Meijer, Yolanda; Gmelig-Meyling, Frits H J; Bruijnzeel-Koomen, Carla A F M; Knulst, André C; Pasmans, Suzanne G M A

2013-01-01

A diagnostic prediction model for peanut allergy in children was recently published, using 6 predictors: sex, age, history, skin prick test, peanut specific immunoglobulin E (sIgE), and total IgE minus peanut sIgE. To validate this model and update it by adding allergic rhinitis, atopic dermatitis, and sIgE to peanut components Ara h 1, 2, 3, and 8 as candidate predictors. To develop a new model based only on sIgE to peanut components. Validation was performed by testing discrimination (diagnostic value) with an area under the receiver operating characteristic curve and calibration (agreement between predicted and observed frequencies of peanut allergy) with the Hosmer-Lemeshow test and a calibration plot. The performance of the (updated) models was similarly analyzed. Validation of the model in 100 patients showed good discrimination (88%) but poor calibration (P < .001). In the updating process, age, history, and additional candidate predictors did not significantly increase discrimination, being 94%, and leaving only 4 predictors of the original model: sex, skin prick test, peanut sIgE, and total IgE minus sIgE. When building a model with sIgE to peanut components, Ara h 2 was the only predictor, with a discriminative ability of 90%. Cutoff values with 100% positive and negative predictive values could be calculated for both the updated model and sIgE to Ara h 2. In this way, the outcome of the food challenge could be predicted with 100% accuracy in 59% (updated model) and 50% (Ara h 2) of the patients. Discrimination of the validated model was good; however, calibration was poor. The discriminative ability of Ara h 2 was almost comparable to that of the updated model, containing 4 predictors. With both models, the need for peanut challenges could be reduced by at least 50%. Copyright © 2012 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Development of an updated PBPK model for trichloroethylene and metabolites in mice, and its application to discern the role of oxidative metabolism in TCE-induced hepatomegaly.

PubMed

Evans, M V; Chiu, W A; Okino, M S; Caldwell, J C

2009-05-01

Trichloroethylene (TCE) is a lipophilic solvent rapidly absorbed and metabolized via oxidation and conjugation to a variety of metabolites that cause toxicity to several internal targets. Increases in liver weight (hepatomegaly) have been reported to occur quickly in rodents after TCE exposure, with liver tumor induction reported in mice after long-term exposure. An integrated dataset for gavage and inhalation TCE exposure and oral data for exposure to two of its oxidative metabolites (TCA and DCA) was used, in combination with an updated and more accurate physiologically-based pharmacokinetic (PBPK) model, to examine the question as to whether the presence of TCA in the liver is responsible for TCE-induced hepatomegaly in mice. The updated PBPK model was used to help discern the quantitative contribution of metabolites to this effect. The update of the model was based on a detailed evaluation of predictions from previously published models and additional preliminary analyses based on gas uptake inhalation data in mice. The parameters of the updated model were calibrated using Bayesian methods with an expanded pharmacokinetic database consisting of oral, inhalation, and iv studies of TCE administration as well as studies of TCE metabolites in mice. The dose-response relationships for hepatomegaly derived from the multi-study database showed that the proportionality of dose to response for TCE- and DCA-induced hepatomegaly is not observed for administered doses of TCA in the studied range. The updated PBPK model was used to make a quantitative comparison of internal dose of metabolized and administered TCA. While the internal dose of TCA predicted by modeling of TCE exposure (i.e., mg TCA/kg-d) showed a linear relationship with hepatomegaly, the slope of the relationship was much greater than that for directly administered TCA. Thus, the degree of hepatomegaly induced per unit of TCA produced through TCE oxidation is greater than that expected per unit of TCA administered directly, which is inconsistent with the hypothesis that TCA alone accounts for TCE-induced hepatomegaly. In addition, TCE-induced hepatomegaly showed a much more consistent relationship with PBPK model predictions of total oxidative metabolism than with predictions of TCE area-under-the-curve in blood, consistent with toxicity being induced by oxidative metabolites rather than the parent compound. Therefore, these results strongly suggest that oxidative metabolites in addition to TCA are necessary contributors to TCE-induced liver weight changes in mice.

Optimal regulation in systems with stochastic time sampling

NASA Technical Reports Server (NTRS)

Montgomery, R. C.; Lee, P. S.

1980-01-01

An optimal control theory that accounts for stochastic variable time sampling in a distributed microprocessor based flight control system is presented. The theory is developed by using a linear process model for the airplane dynamics and the information distribution process is modeled as a variable time increment process where, at the time that information is supplied to the control effectors, the control effectors know the time of the next information update only in a stochastic sense. An optimal control problem is formulated and solved for the control law that minimizes the expected value of a quadratic cost function. The optimal cost obtained with a variable time increment Markov information update process where the control effectors know only the past information update intervals and the Markov transition mechanism is almost identical to that obtained with a known and uniform information update interval.

Research Supports Value of Updated School Facilities

ERIC Educational Resources Information Center

Fielding, Randall

2012-01-01

Two recent peer-reviewed studies support the need to update the traditional school design model that has remained fundamentally unchanged for over a century. In a 2011 study published by the American Educational Research Journal, entitled "Problem-Based Learning in K-12 Education," Clarice Wirkala and Deanna Kuhn document a 200-500…

A Model-Based Anomaly Detection Approach for Analyzing Streaming Aircraft Engine Measurement Data

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Rinehart, Aidan W.

2014-01-01

This paper presents a model-based anomaly detection architecture designed for analyzing streaming transient aircraft engine measurement data. The technique calculates and monitors residuals between sensed engine outputs and model predicted outputs for anomaly detection purposes. Pivotal to the performance of this technique is the ability to construct a model that accurately reflects the nominal operating performance of the engine. The dynamic model applied in the architecture is a piecewise linear design comprising steady-state trim points and dynamic state space matrices. A simple curve-fitting technique for updating the model trim point information based on steadystate information extracted from available nominal engine measurement data is presented. Results from the application of the model-based approach for processing actual engine test data are shown. These include both nominal fault-free test case data and seeded fault test case data. The results indicate that the updates applied to improve the model trim point information also improve anomaly detection performance. Recommendations for follow-on enhancements to the technique are also presented and discussed.

A Model-Based Anomaly Detection Approach for Analyzing Streaming Aircraft Engine Measurement Data

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Rinehart, Aidan Walker

2015-01-01

This paper presents a model-based anomaly detection architecture designed for analyzing streaming transient aircraft engine measurement data. The technique calculates and monitors residuals between sensed engine outputs and model predicted outputs for anomaly detection purposes. Pivotal to the performance of this technique is the ability to construct a model that accurately reflects the nominal operating performance of the engine. The dynamic model applied in the architecture is a piecewise linear design comprising steady-state trim points and dynamic state space matrices. A simple curve-fitting technique for updating the model trim point information based on steadystate information extracted from available nominal engine measurement data is presented. Results from the application of the model-based approach for processing actual engine test data are shown. These include both nominal fault-free test case data and seeded fault test case data. The results indicate that the updates applied to improve the model trim point information also improve anomaly detection performance. Recommendations for follow-on enhancements to the technique are also presented and discussed.

Information distribution in distributed microprocessor based flight control systems

NASA Technical Reports Server (NTRS)

Montgomery, R. C.; Lee, P. S.

1977-01-01

This paper presents an optimal control theory that accounts for variable time intervals in the information distribution to control effectors in a distributed microprocessor based flight control system. The theory is developed using a linear process model for the aircraft dynamics and the information distribution process is modeled as a variable time increment process where, at the time that information is supplied to the control effectors, the control effectors know the time of the next information update only in a stochastic sense. An optimal control problem is formulated and solved that provides the control law that minimizes the expected value of a quadratic cost function. An example is presented where the theory is applied to the control of the longitudinal motions of the F8-DFBW aircraft. Theoretical and simulation results indicate that, for the example problem, the optimal cost obtained using a variable time increment Markov information update process where the control effectors know only the past information update intervals and the Markov transition mechanism is almost identical to that obtained using a known uniform information update interval.

A Bayesian spawning habitat suitability model for American shad in southeastern United States rivers

USGS Publications Warehouse

Hightower, Joseph E.; Harris, Julianne E.; Raabe, Joshua K.; Brownell, Prescott; Drew, C. Ashton

2012-01-01

Habitat suitability index models for American shad Alosa sapidissima were developed by Stier and Crance in 1985. These models, which were based on a combination of published information and expert opinion, are often used to make decisions about hydropower dam operations and fish passage. The purpose of this study was to develop updated habitat suitability index models for spawning American shad in the southeastern United States, building on the many field and laboratory studies completed since 1985. We surveyed biologists who had knowledge about American shad spawning grounds, assembled a panel of experts to discuss important habitat variables, and used raw data from published and unpublished studies to develop new habitat suitability curves. The updated curves are based on resource selection functions, which can model habitat selectivity based on use and availability of particular habitats. Using field data collected in eight rivers from Virginia to Florida (Mattaponi, Pamunkey, Roanoke, Tar, Neuse, Cape Fear, Pee Dee, St. Johns), we obtained new curves for temperature, current velocity, and depth that were generally similar to the original models. Our new suitability function for substrate was also similar to the original pattern, except that sand (optimal in the original model) has a very low estimated suitability. The Bayesian approach that we used to develop habitat suitability curves provides an objective framework for updating the model as new studies are completed and for testing the model's applicability in other parts of the species' range.

Designing an Adaptive Web-Based Learning System Based on Students' Cognitive Styles Identified Online

ERIC Educational Resources Information Center

Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen

2012-01-01

This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…

Data update in a land information network

NASA Astrophysics Data System (ADS)

Mullin, Robin C.

1988-01-01

The on-going update of data exchanged in a land information network is examined. In the past, major developments have been undertaken to enable the exchange of data between land information systems. A model of a land information network and the data update process have been developed. Based on these, a functional description of the database and software to perform data updating is presented. A prototype of the data update process was implemented using the ARC/INFO geographic information system. This was used to test four approaches to data updating, i.e., bulk, block, incremental, and alert updates. A bulk update is performed by replacing a complete file with an updated file. A block update requires that the data set be partitioned into blocks. When an update occurs, only the blocks which are affected need to be transferred. An incremental update approach records each feature which is added or deleted and transmits only the features needed to update the copy of the file. An alert is a marker indicating that an update has occurred. It can be placed in a file to warn a user that if he is active in an area containing markers, updated data is available. The four approaches have been tested using a cadastral data set.

Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors

PubMed Central

Wu, Bitao; Lu, Huaxi; Chen, Bo; Gao, Zhicheng

2017-01-01

A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model. PMID:28753912

Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors.

PubMed

Wu, Bitao; Lu, Huaxi; Chen, Bo; Gao, Zhicheng

2017-07-19

A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model.

Experiments on individual strategy updating in iterated snowdrift game under random rematching.

PubMed

Qi, Hang; Ma, Shoufeng; Jia, Ning; Wang, Guangchao

2015-03-07

How do people actually play the iterated snowdrift games, particularly under random rematching protocol is far from well explored. Two sets of laboratory experiments on snowdrift game were conducted to investigate human strategy updating rules. Four groups of subjects were modeled by experience-weighted attraction learning theory at individual-level. Three out of the four groups (75%) passed model validation. Substantial heterogeneity is observed among the players who update their strategies in four typical types, whereas rare people behave like belief-based learners even under fixed pairing. Most subjects (63.9%) adopt the reinforcement learning (or alike) rules; but, interestingly, the performance of averaged reinforcement learners suffered. It is observed that two factors seem to benefit players in competition, i.e., the sensitivity to their recent experiences and the overall consideration of forgone payoffs. Moreover, subjects with changing opponents tend to learn faster based on their own recent experience, and display more diverse strategy updating rules than they do with fixed opponent. These findings suggest that most of subjects do apply reinforcement learning alike updating rules even under random rematching, although these rules may not improve their performance. The findings help evolutionary biology researchers to understand sophisticated human behavioral strategies in social dilemmas. Copyright © 2015 Elsevier Ltd. All rights reserved.

Earthquake Hazard and Risk in Alaska

NASA Astrophysics Data System (ADS)

Black Porto, N.; Nyst, M.

2014-12-01

Alaska is one of the most seismically active and tectonically diverse regions in the United States. To examine risk, we have updated the seismic hazard model in Alaska. The current RMS Alaska hazard model is based on the 2007 probabilistic seismic hazard maps for Alaska (Wesson et al., 2007; Boyd et al., 2007). The 2015 RMS model will update several key source parameters, including: extending the earthquake catalog, implementing a new set of crustal faults, updating the subduction zone geometry and reoccurrence rate. First, we extend the earthquake catalog to 2013; decluster the catalog, and compute new background rates. We then create a crustal fault model, based on the Alaska 2012 fault and fold database. This new model increased the number of crustal faults from ten in 2007, to 91 faults in the 2015 model. This includes the addition of: the western Denali, Cook Inlet folds near Anchorage, and thrust faults near Fairbanks. Previously the subduction zone was modeled at a uniform depth. In this update, we model the intraslab as a series of deep stepping events. We also use the best available data, such as Slab 1.0, to update the geometry of the subduction zone. The city of Anchorage represents 80% of the risk exposure in Alaska. In the 2007 model, the hazard in Alaska was dominated by the frequent rate of magnitude 7 to 8 events (Gutenberg-Richter distribution), and large magnitude 8+ events had a low reoccurrence rate (Characteristic) and therefore didn't contribute as highly to the overall risk. We will review these reoccurrence rates, and will present the results and impact to Anchorage. We will compare our hazard update to the 2007 USGS hazard map, and discuss the changes and drivers for these changes. Finally, we will examine the impact model changes have on Alaska earthquake risk. Consider risk metrics include average annual loss, an annualized expected loss level used by insurers to determine the costs of earthquake insurance (and premium levels), and the loss exceedance probability curve used by insurers to address their solvency and manage their portfolio risk. We analyze risk profile changes in areas with large population density and for structures of economic and financial importance: the Trans-Alaska pipeline, industrial facilities in Valdez, and typical residential wood buildings in Anchorage, Fairbanks and Juneau.

Earthquake Hazard and Risk in New Zealand

NASA Astrophysics Data System (ADS)

Apel, E. V.; Nyst, M.; Fitzenz, D. D.; Molas, G.

2014-12-01

To quantify risk in New Zealand we examine the impact of updating the seismic hazard model. The previous RMS New Zealand hazard model is based on the 2002 probabilistic seismic hazard maps for New Zealand (Stirling et al., 2002). The 2015 RMS model, based on Stirling et al., (2012) will update several key source parameters. These updates include: implementation a new set of crustal faults including multi-segment ruptures, updating the subduction zone geometry and reccurrence rate and implementing new background rates and a robust methodology for modeling background earthquake sources. The number of crustal faults has increased by over 200 from the 2002 model, to the 2012 model which now includes over 500 individual fault sources. This includes the additions of many offshore faults in northern, east-central, and southwest regions. We also use the recent data to update the source geometry of the Hikurangi subduction zone (Wallace, 2009; Williams et al., 2013). We compare hazard changes in our updated model with those from the previous version. Changes between the two maps are discussed as well as the drivers for these changes. We examine the impact the hazard model changes have on New Zealand earthquake risk. Considered risk metrics include average annual loss, an annualized expected loss level used by insurers to determine the costs of earthquake insurance (and premium levels), and the loss exceedance probability curve used by insurers to address their solvency and manage their portfolio risk. We analyze risk profile changes in areas with large population density and for structures of economic and financial importance. New Zealand is interesting in that the city with the majority of the risk exposure in the country (Auckland) lies in the region of lowest hazard, where we don't have a lot of information about the location of faults and distributed seismicity is modeled by averaged Mw-frequency relationships on area sources. Thus small changes to the background rates can have a large impact on the risk profile for the area. Wellington, another area of high exposure is particularly sensitive to how the Hikurangi subduction zone and the Wellington fault are modeled. Minor changes on these sources have substantial impacts for the risk profile of the city and the country at large.

Mitigating nonlinearity in full waveform inversion using scaled-Sobolev pre-conditioning

NASA Astrophysics Data System (ADS)

Zuberi, M. AH; Pratt, R. G.

2018-04-01

The Born approximation successfully linearizes seismic full waveform inversion if the background velocity is sufficiently accurate. When the background velocity is not known it can be estimated by using model scale separation methods. A frequently used technique is to separate the spatial scales of the model according to the scattering angles present in the data, by using either first- or second-order terms in the Born series. For example, the well-known `banana-donut' and the `rabbit ear' shaped kernels are, respectively, the first- and second-order Born terms in which at least one of the scattering events is associated with a large angle. Whichever term of the Born series is used, all such methods suffer from errors in the starting velocity model because all terms in the Born series assume that the background Green's function is known. An alternative approach to Born-based scale separation is to work in the model domain, for example, by Gaussian smoothing of the update vectors, or some other approach for separation by model wavenumbers. However such model domain methods are usually based on a strict separation in which only the low-wavenumber updates are retained. This implies that the scattered information in the data is not taken into account. This can lead to the inversion being trapped in a false (local) minimum when sharp features are updated incorrectly. In this study we propose a scaled-Sobolev pre-conditioning (SSP) of the updates to achieve a constrained scale separation in the model domain. The SSP is obtained by introducing a scaled Sobolev inner product (SSIP) into the measure of the gradient of the objective function with respect to the model parameters. This modified measure seeks reductions in the L2 norm of the spatial derivatives of the gradient without changing the objective function. The SSP does not rely on the Born prediction of scale based on scattering angles, and requires negligible extra computational cost per iteration. Synthetic examples from the Marmousi model show that the constrained scale separation using SSP is able to keep the background updates in the zone of attraction of the global minimum, in spite of using a poor starting model in which conventional methods fail.

TRMM Microwave Imager (TMI) Updates for Final Data Version Release

NASA Technical Reports Server (NTRS)

Kroodsma, Rachael A; Bilanow, Stephen; Ji, Yimin; McKague, Darren

2017-01-01

The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) dataset released by the Precipitation Processing System (PPS) will be updated to a final version within the next year. These updates are based on increased knowledge in recent years of radiometer calibration and sensor performance issues. In particular, the Global Precipitation Measurement (GPM) Microwave Imager (GMI) is used as a model for many of the TMI version updates. This paper discusses four aspects of the TMI data product that will be improved: spacecraft attitude, calibration and quality control, along-scan bias corrections, and sensor pointing accuracy. These updates will be incorporated into the final TMI data version, improving the quality of the data product and ensuring accurate geophysical parameters can be derived from TMI.

A cell-based study on pedestrian acceleration and overtaking in a transfer station corridor

NASA Astrophysics Data System (ADS)

Ji, Xiangfeng; Zhou, Xuemei; Ran, Bin

2013-04-01

Pedestrian speed in a transfer station corridor is faster than usual and sometimes running can be found among some of them. In this paper, pedestrians are divided into two categories. The first one is aggressive, and the other is conservative. Aggressive pedestrians weaving their way through crowd in the corridor are the study object of this paper. During recent decades, much attention has been paid to the pedestrians' behavior, such as overtaking (also deceleration) and collision avoidance, and that continues in this paper. After sufficiently analyzing the characteristics of pedestrian flow in transfer station corridor, a cell-based model is presented in this paper, including the acceleration (also deceleration) and overtaking analysis. Acceleration (also deceleration) in a corridor is fixed according to Newton's Law and then speed calculated with a kinematic formula is discretized into cells based on the fuzzy logic. After the speed is updated, overtaking is analyzed based on updated speed and force explicitly, compared to rule-based models, which herein we call implicit ones. During the analysis of overtaking, a threshold value to determine the overtaking direction is introduced. Actually, model in this paper is a two-step one. The first step is to update speed, which is the cells the pedestrian can move in one time interval and the other is to analyze the overtaking. Finally, a comparison between the rule-based cellular automata, the model in this paper and data in HCM 2000 is made to demonstrate our model can be used to achieve reasonable simulation of acceleration (also deceleration) and overtaking among pedestrians.

Theory of quantized systems: formal basis for DEVS/HLA distributed simulation environment

NASA Astrophysics Data System (ADS)

Zeigler, Bernard P.; Lee, J. S.

1998-08-01

In the context of a DARPA ASTT project, we are developing an HLA-compliant distributed simulation environment based on the DEVS formalism. This environment will provide a user- friendly, high-level tool-set for developing interoperable discrete and continuous simulation models. One application is the study of contract-based predictive filtering. This paper presents a new approach to predictive filtering based on a process called 'quantization' to reduce state update transmission. Quantization, which generates state updates only at quantum level crossings, abstracts a sender model into a DEVS representation. This affords an alternative, efficient approach to embedding continuous models within distributed discrete event simulations. Applications of quantization to message traffic reduction are discussed. The theory has been validated by DEVSJAVA simulations of test cases. It will be subject to further test in actual distributed simulations using the DEVS/HLA modeling and simulation environment.

Enumeration and extension of non-equivalent deterministic update schedules in Boolean networks.

PubMed

Palma, Eduardo; Salinas, Lilian; Aracena, Julio

2016-03-01

Boolean networks (BNs) are commonly used to model genetic regulatory networks (GRNs). Due to the sensibility of the dynamical behavior to changes in the updating scheme (order in which the nodes of a network update their state values), it is increasingly common to use different updating rules in the modeling of GRNs to better capture an observed biological phenomenon and thus to obtain more realistic models.In Aracena et al. equivalence classes of deterministic update schedules in BNs, that yield exactly the same dynamical behavior of the network, were defined according to a certain label function on the arcs of the interaction digraph defined for each scheme. Thus, the interaction digraph so labeled (update digraphs) encode the non-equivalent schemes. We address the problem of enumerating all non-equivalent deterministic update schedules of a given BN. First, we show that it is an intractable problem in general. To solve it, we first construct an algorithm that determines the set of update digraphs of a BN. For that, we use divide and conquer methodology based on the structural characteristics of the interaction digraph. Next, for each update digraph we determine a scheme associated. This algorithm also works in the case where there is a partial knowledge about the relative order of the updating of the states of the nodes. We exhibit some examples of how the algorithm works on some GRNs published in the literature. An executable file of the UpdateLabel algorithm made in Java and the files with the outputs of the algorithms used with the GRNs are available at: www.inf.udec.cl/ ∼lilian/UDE/ CONTACT: lilisalinas@udec.cl Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Forecasting the (un)productivity of the 2014 M 6.0 South Napa aftershock sequence

USGS Publications Warehouse

Llenos, Andrea L.; Michael, Andrew J.

2017-01-01

The 24 August 2014 Mw 6.0 South Napa mainshock produced fewer aftershocks than expected for a California earthquake of its magnitude. In the first 4.5 days, only 59 M≥1.8 aftershocks occurred, the largest of which was an M 3.9 that happened a little over two days after the mainshock. We investigate the aftershock productivity of the South Napa sequence and compare it with other M≥5.5 California strike‐slip mainshock–aftershock sequences. While the productivity of the South Napa sequence is among the lowest, northern California mainshocks generally have fewer aftershocks than mainshocks further south, although the productivities vary widely in both regions. An epidemic‐type aftershock sequence (ETAS) model (Ogata, 1988) fit to Napa seismicity from 1980 to 23 August 2014 fits the sequence well and suggests that low‐productivity sequences are typical of this area. Utilizing regional variations in productivity could improve operational earthquake forecasting (OEF) by improving the model used immediately after the mainshock. We show this by comparing the daily rate of M≥2 aftershocks to forecasts made with the generic California model (Reasenberg and Jones, 1989; hereafter, RJ89), RJ89 models with productivity updated daily, a generic California ETAS model, an ETAS model based on premainshock seismicity, and ETAS models updated daily following the mainshock. RJ89 models for which only the productivity is updated provide better forecasts than the generic RJ89 California model, and the Napa‐specific ETAS models forecast the aftershock rates more accurately than either generic model. Therefore, forecasts that use localized initial parameters and that rapidly update the productivity may be better for OEF than using a generic model and/or updating all parameters.

CyanoBase: the cyanobacteria genome database update 2010.

PubMed

Nakao, Mitsuteru; Okamoto, Shinobu; Kohara, Mitsuyo; Fujishiro, Tsunakazu; Fujisawa, Takatomo; Sato, Shusei; Tabata, Satoshi; Kaneko, Takakazu; Nakamura, Yasukazu

2010-01-01

CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in various formats with other tools, seamlessly.

Symmetric tridiagonal structure preserving finite element model updating problem for the quadratic model

NASA Astrophysics Data System (ADS)

Rakshit, Suman; Khare, Swanand R.; Datta, Biswa Nath

2018-07-01

One of the most important yet difficult aspect of the Finite Element Model Updating Problem is to preserve the finite element inherited structures in the updated model. Finite element matrices are in general symmetric, positive definite (or semi-definite) and banded (tridiagonal, diagonal, penta-diagonal, etc.). Though a large number of papers have been published in recent years on various aspects of solutions of this problem, papers dealing with structure preservation almost do not exist. A novel optimization based approach that preserves the symmetric tridiagonal structures of the stiffness and damping matrices is proposed in this paper. An analytical expression for the global minimum solution of the associated optimization problem along with the results of numerical experiments obtained by both the analytical expressions and by an appropriate numerical optimization algorithm are presented. The results of numerical experiments support the validity of the proposed method.

An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies.

PubMed

Yang, Xiaohuan; Huang, Yaohuan; Dong, Pinliang; Jiang, Dong; Liu, Honghui

2009-01-01

The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.

Assessment Update: Progress, Trends, and Practices in Higher Education. Volume 24, Issue 2, March-April 2012

ERIC Educational Resources Information Center

Banta, Trudy W., Ed.

2012-01-01

This issue of "Assessment Update" presents the following articles: (1) Mission Accomplished! The Development of a Competence-based E-portfolio Assessment Model (Shelley Schuurman, Scott Berlin, Jamie Langlois, and Julie Guevara); (2) The Third Rail of Assessment--Dangerous but Powerful (Dale L. Mort); (3) Video Killed the Radio…

Imitate or innovate: Competition of strategy updating attitudes in spatial social dilemma games

NASA Astrophysics Data System (ADS)

Danku, Zsuzsa; Wang, Zhen; Szolnoki, Attila

2018-01-01

Evolution is based on the assumption that competing players update their strategies to increase their individual payoffs. However, while the applied updating method can be different, most of previous works proposed uniform models where players use identical way to revise their strategies. In this work we explore how imitation-based or learning attitude and innovation-based or myopic best-response attitude compete for space in a complex model where both attitudes are available. In the absence of additional cost the best response trait practically dominates the whole snow-drift game parameter space which is in agreement with the average payoff difference of basic models. When additional cost is involved then the imitation attitude can gradually invade the whole parameter space but this transition happens in a highly nontrivial way. However, the role of competing attitudes is reversed in the stag-hunt parameter space where imitation is more successful in general. Interestingly, a four-state solution can be observed for the latter game which is a consequence of an emerging cyclic dominance between possible states. These phenomena can be understood by analyzing the microscopic invasion processes, which reveals the unequal propagation velocities of strategies and attitudes.

Orbital frontal cortex updates state-induced value change for decision-making.

PubMed

Baltz, Emily T; Yalcinbas, Ege A; Renteria, Rafael; Gremel, Christina M

2018-06-13

Recent hypotheses have posited that orbital frontal cortex (OFC) is important for using inferred consequences to guide behavior. Less clear is OFC's contribution to goal-directed or model-based behavior, where the decision to act is controlled by previous experience with the consequence or outcome. Investigating OFC's role in learning about changed outcomes separate from decision-making is not trivial and often the two are confounded. Here we adapted an incentive learning task to mice, where we investigated processes controlling experience-based outcome updating independent from inferred action control. We found chemogenetic OFC attenuation did not alter the ability to perceive motivational state-induced changes in outcome value but did prevent the experience-based updating of this change. Optogenetic inhibition of OFC excitatory neuron activity selectively when experiencing an outcome change disrupted the ability to update, leaving mice unable to infer the appropriate behavior. Our findings support a role for OFC in learning that controls decision-making. © 2018, Baltz et al.

Damage identification of a reinforced concrete frame by finite element model updating using damage parameterization

NASA Astrophysics Data System (ADS)

Fang, Sheng-En; Perera, Ricardo; De Roeck, Guido

2008-06-01

This paper develops a sensitivity-based updating method to identify the damage in a tested reinforced concrete (RC) frame modeled with a two-dimensional planar finite element (FE) by minimizing the discrepancies of modal frequencies and mode shapes. In order to reduce the number of unknown variables, a bidimensional damage (element) function is proposed, resulting in a considerable improvement of the optimization performance. For damage identification, a reference FE model of the undamaged frame divided into a few damage functions is firstly obtained and then a rough identification is carried out to detect possible damage locations, which are subsequently refined with new damage functions to accurately identify the damage. From a design point of view, it would be useful to evaluate, in a simplified way, the remaining bending stiffness of cracked beam sections or segments. Hence, an RC damage model based on a static mechanism is proposed to estimate the remnant stiffness of a cracked RC beam segment. The damage model is based on the assumption that the damage effect spreads over a region and the stiffness in the segment changes linearly. Furthermore, the stiffness reduction evaluated using this damage model is compared with the FE updating result. It is shown that the proposed bidimensional damage function is useful in producing a well-conditioned optimization problem and the aforementioned damage model can be used for an approximate stiffness estimation of a cracked beam segment.

Dissociable Frontal–Striatal and Frontal–Parietal Networks Involved in Updating Hierarchical Contexts in Working Memory

PubMed Central

Nee, Derek Evan; Brown, Joshua W.

2013-01-01

Recent theories propose that the prefrontal cortex (PFC) is organized in a hierarchical fashion with more abstract, higher level information represented in anterior regions and more concrete, lower level information represented in posterior regions. This hierarchical organization affords flexible adjustments of action plans based on the context. Computational models suggest that such hierarchical organization in the PFC is achieved through interactions with the basal ganglia (BG) wherein the BG gate relevant contexts into the PFC. Here, we tested this proposal using functional magnetic resonance imaging (fMRI). Participants were scanned while updating working memory (WM) with 2 levels of hierarchical contexts. Consistent with PFC abstraction proposals, higher level context updates involved anterior portions of the PFC (BA 46), whereas lower level context updates involved posterior portions of the PFC (BA 6). Computational models were only partially supported as the BG were sensitive to higher, but not lower level context updates. The posterior parietal cortex (PPC) showed the opposite pattern. Analyses examining changes in functional connectivity confirmed dissociable roles of the anterior PFC–BG during higher level context updates and posterior PFC–PPC during lower level context updates. These results suggest that hierarchical contexts are organized by distinct frontal–striatal and frontal–parietal networks. PMID:22798339

Recent Updates of A Multi-Phase Transport (AMPT) Model

NASA Astrophysics Data System (ADS)

Lin, Zi-Wei

2008-10-01

We will present recent updates to the AMPT model, a Monte Carlo transport model for high energy heavy ion collisions, since its first public release in 2004 and the corresponding detailed descriptions in Phys. Rev. C 72, 064901 (2005). The updates often result from user requests. Some of these updates expand the physics processes or descriptions in the model, while some updates improve the usability of the model such as providing the initial parton distributions or help avoid crashes on some operating systems. We will also explain how the AMPT model is being maintained and updated.

A Model to Assess the Behavioral Impacts of Consultative Knowledge Based Systems.

ERIC Educational Resources Information Center

Mak, Brenda; Lyytinen, Kalle

1997-01-01

This research model studies the behavioral impacts of consultative knowledge based systems (KBS). A study of graduate students explored to what extent their decisions were affected by user participation in updating the knowledge base; ambiguity of decision setting; routinization of usage; and source credibility of the expertise embedded in the…

A heuristic for efficient data distribution management in distributed simulation

NASA Astrophysics Data System (ADS)

Gupta, Pankaj; Guha, Ratan K.

2005-05-01

In this paper, we propose an algorithm for reducing the complexity of region matching and efficient multicasting in data distribution management component of High Level Architecture (HLA) Run Time Infrastructure (RTI). The current data distribution management (DDM) techniques rely on computing the intersection between the subscription and update regions. When a subscription region and an update region of different federates overlap, RTI establishes communication between the publisher and the subscriber. It subsequently routes the updates from the publisher to the subscriber. The proposed algorithm computes the update/subscription regions matching for dynamic allocation of multicast group. It provides new multicast routines that exploit the connectivity of federation by communicating updates regarding interactions and routes information only to those federates that require them. The region-matching problem in DDM reduces to clique-covering problem using the connections graph abstraction where the federations represent the vertices and the update/subscribe relations represent the edges. We develop an abstract model based on connection graph for data distribution management. Using this abstract model, we propose a heuristic for solving the region-matching problem of DDM. We also provide complexity analysis of the proposed heuristics.

CyanoBase: the cyanobacteria genome database update 2010

PubMed Central

Nakao, Mitsuteru; Okamoto, Shinobu; Kohara, Mitsuyo; Fujishiro, Tsunakazu; Fujisawa, Takatomo; Sato, Shusei; Tabata, Satoshi; Kaneko, Takakazu; Nakamura, Yasukazu

2010-01-01

CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in various formats with other tools, seamlessly. PMID:19880388

Automotive Maintenance Data Base for Model Years 1976-1979. Part I

DOT National Transportation Integrated Search

1980-12-01

An update of the existing data base was developed to include life cycle maintenance costs of representative vehicles for the model years 1976-1979. Repair costs as a function of time are also developed for a passenger car in each of the compact, subc...

Physiologically-based pharmacokinetic (PBPK) modeling to explore potential metabolic pathways of bromochloromethane in rats

EPA Science Inventory

Bromochloromethane (BCM) is a volatile compound and a by-product of disinfection of water by ofchlorination. Physiologically based pharmacokinetic (PBPK) models are used in risk assessment applications. An updated PBPKmodel for BCM is generated and applied to hypotheses testing c...

A MULTILAYER BIOCHEMICAL DRY DEPOSITION MODEL 1. MODEL FORMULATION

EPA Science Inventory

A multilayer biochemical dry deposition model has been developed based on the NOAA Multilayer Model (MLM) to study gaseous exchanges between the soil, plants, and the atmosphere. Most of the parameterizations and submodels have been updated or replaced. The numerical integration ...

Situation Model Updating in Young and Older Adults: Global versus Incremental Mechanisms

PubMed Central

Bailey, Heather R.; Zacks, Jeffrey M.

2015-01-01

Readers construct mental models of situations described by text. Activity in narrative text is dynamic, so readers must frequently update their situation models when dimensions of the situation change. Updating can be incremental, such that a change leads to updating just the dimension that changed, or global, such that the entire model is updated. Here, we asked whether older and young adults make differential use of incremental and global updating. Participants read narratives containing changes in characters and spatial location and responded to recognition probes throughout the texts. Responses were slower when probes followed a change, suggesting that situation models were updated at changes. When either dimension changed, responses to probes for both dimensions were slowed; this provides evidence for global updating. Moreover, older adults showed stronger evidence of global updating than did young adults. One possibility is that older adults perform more global updating to offset reduced ability to manipulate information in working memory. PMID:25938248

Application of Bayesian population physiologically based pharmacokinetic (PBPK) modeling and Markov chain Monte Carlo simulations to pesticide kinetics studies in protected marine mammals: DDT, DDE, and DDD in harbor porpoises.

PubMed

Weijs, Liesbeth; Yang, Raymond S H; Das, Krishna; Covaci, Adrian; Blust, Ronny

2013-05-07

Physiologically based pharmacokinetic (PBPK) modeling in marine mammals is a challenge because of the lack of parameter information and the ban on exposure experiments. To minimize uncertainty and variability, parameter estimation methods are required for the development of reliable PBPK models. The present study is the first to develop PBPK models for the lifetime bioaccumulation of p,p'-DDT, p,p'-DDE, and p,p'-DDD in harbor porpoises. In addition, this study is also the first to apply the Bayesian approach executed with Markov chain Monte Carlo simulations using two data sets of harbor porpoises from the Black and North Seas. Parameters from the literature were used as priors for the first "model update" using the Black Sea data set, the resulting posterior parameters were then used as priors for the second "model update" using the North Sea data set. As such, PBPK models with parameters specific for harbor porpoises could be strengthened with more robust probability distributions. As the science and biomonitoring effort progress in this area, more data sets will become available to further strengthen and update the parameters in the PBPK models for harbor porpoises as a species anywhere in the world. Further, such an approach could very well be extended to other protected marine mammals.

Update on ɛK with lattice QCD inputs

NASA Astrophysics Data System (ADS)

Jang, Yong-Chull; Lee, Weonjong; Lee, Sunkyu; Leem, Jaehoon

2018-03-01

We report updated results for ɛK, the indirect CP violation parameter in neutral kaons, which is evaluated directly from the standard model with lattice QCD inputs. We use lattice QCD inputs to fix B\\hatk,|Vcb|,ξ0,ξ2,|Vus|, and mc(mc). Since Lattice 2016, the UTfit group has updated the Wolfenstein parameters in the angle-only-fit method, and the HFLAV group has also updated |Vcb|. Our results show that the evaluation of ɛK with exclusive |Vcb| (lattice QCD inputs) has 4.0σ tension with the experimental value, while that with inclusive |Vcb| (heavy quark expansion based on OPE and QCD sum rules) shows no tension.

Fish tracking by combining motion based segmentation and particle filtering

NASA Astrophysics Data System (ADS)

Bichot, E.; Mascarilla, L.; Courtellemont, P.

2006-01-01

In this paper, we suggest a new importance sampling scheme to improve a particle filtering based tracking process. This scheme relies on exploitation of motion segmentation. More precisely, we propagate hypotheses from particle filtering to blobs of similar motion to target. Hence, search is driven toward regions of interest in the state space and prediction is more accurate. We also propose to exploit segmentation to update target model. Once the moving target has been identified, a representative model is learnt from its spatial support. We refer to this model in the correction step of the tracking process. The importance sampling scheme and the strategy to update target model improve the performance of particle filtering in complex situations of occlusions compared to a simple Bootstrap approach as shown by our experiments on real fish tank sequences.

An Update of the Analytical Groundwater Modeling to Assess Water Resource Impacts at the Afton Solar Energy Zone

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quinn, John J.; Greer, Christopher B.; Carr, Adrianne E.

2014-10-01

The purpose of this study is to update a one-dimensional analytical groundwater flow model to examine the influence of potential groundwater withdrawal in support of utility-scale solar energy development at the Afton Solar Energy Zone (SEZ) as a part of the Bureau of Land Management’s (BLM’s) Solar Energy Program. This report describes the modeling for assessing the drawdown associated with SEZ groundwater pumping rates for a 20-year duration considering three categories of water demand (high, medium, and low) based on technology-specific considerations. The 2012 modeling effort published in the Final Programmatic Environmental Impact Statement for Solar Energy Development in Sixmore » Southwestern States (Solar PEIS; BLM and DOE 2012) has been refined based on additional information described below in an expanded hydrogeologic discussion.« less

A Comparative Study of Spectral Auroral Intensity Predictions From Multiple Electron Transport Models

NASA Astrophysics Data System (ADS)

Grubbs, Guy; Michell, Robert; Samara, Marilia; Hampton, Donald; Hecht, James; Solomon, Stanley; Jahn, Jorg-Micha

2018-01-01

It is important to routinely examine and update models used to predict auroral emissions resulting from precipitating electrons in Earth's magnetotail. These models are commonly used to invert spectral auroral ground-based images to infer characteristics about incident electron populations when in situ measurements are unavailable. In this work, we examine and compare auroral emission intensities predicted by three commonly used electron transport models using varying electron population characteristics. We then compare model predictions to same-volume in situ electron measurements and ground-based imaging to qualitatively examine modeling prediction error. Initial comparisons showed differences in predictions by the GLobal airglOW (GLOW) model and the other transport models examined. Chemical reaction rates and radiative rates in GLOW were updated using recent publications, and predictions showed better agreement with the other models and the same-volume data, stressing that these rates are important to consider when modeling auroral processes. Predictions by each model exhibit similar behavior for varying atmospheric constants, energies, and energy fluxes. Same-volume electron data and images are highly correlated with predictions by each model, showing that these models can be used to accurately derive electron characteristics and ionospheric parameters based solely on multispectral optical imaging data.

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

A reassessment of Galileo radiation exposures in the Jupiter magnetosphere.

PubMed

Atwell, William; Townsend, Lawrence; Miller, Thomas; Campbell, Christina

2005-01-01

Earlier particle experiments in the 1970s on Pioneer-10 and -11 and Voyager-1 and -2 provided Jupiter flyby particle data, which were used by Divine and Garrett to develop the first Jupiter trapped radiation environment model. This model was used to establish a baseline radiation effects design limit for the Galileo onboard electronics. Recently, Garrett et al. have developed an updated Galileo Interim Radiation Environment (GIRE) model based on Galileo electron data. In this paper, we have used the GIRE model to reassess the computed radiation exposures and dose effects for Galileo. The 34-orbit 'as flown' Galileo trajectory data and the updated GIRE model were used to compute the electron and proton spectra for each of the 34 orbits. The total ionisation doses of electrons and protons have been computed based on a parametric shielding configuration, and these results are compared with previously published results.

Updating National Topographic Data Base Using Change Detection Methods

NASA Astrophysics Data System (ADS)

Keinan, E.; Felus, Y. A.; Tal, Y.; Zilberstien, O.; Elihai, Y.

2016-06-01

The traditional method for updating a topographic database on a national scale is a complex process that requires human resources, time and the development of specialized procedures. In many National Mapping and Cadaster Agencies (NMCA), the updating cycle takes a few years. Today, the reality is dynamic and the changes occur every day, therefore, the users expect that the existing database will portray the current reality. Global mapping projects which are based on community volunteers, such as OSM, update their database every day based on crowdsourcing. In order to fulfil user's requirements for rapid updating, a new methodology that maps major interest areas while preserving associated decoding information, should be developed. Until recently, automated processes did not yield satisfactory results, and a typically process included comparing images from different periods. The success rates in identifying the objects were low, and most were accompanied by a high percentage of false alarms. As a result, the automatic process required significant editorial work that made it uneconomical. In the recent years, the development of technologies in mapping, advancement in image processing algorithms and computer vision, together with the development of digital aerial cameras with NIR band and Very High Resolution satellites, allow the implementation of a cost effective automated process. The automatic process is based on high-resolution Digital Surface Model analysis, Multi Spectral (MS) classification, MS segmentation, object analysis and shape forming algorithms. This article reviews the results of a novel change detection methodology as a first step for updating NTDB in the Survey of Israel.

A multipopulation PSO based memetic algorithm for permutation flow shop scheduling.

PubMed

Liu, Ruochen; Ma, Chenlin; Ma, Wenping; Li, Yangyang

2013-01-01

The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS) and individual improvement scheme (IIS). Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA) and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA) and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA), on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

Physiologically Based Pharmacokinetic Modeling Suggests Limited Drug–Drug Interaction Between Clopidogrel and Dasabuvir

PubMed Central

Fu, W; Badri, P; Bow, DAJ; Fischer, V

2017-01-01

Dasabuvir, a nonnucleoside NS5B polymerase inhibitor, is a sensitive substrate of cytochrome P450 (CYP) 2C8 with a potential for drug–drug interaction (DDI) with clopidogrel. A physiologically based pharmacokinetic (PBPK) model was developed for dasabuvir to evaluate the DDI potential with clopidogrel, the acyl‐β‐D glucuronide metabolite of which has been reported as a strong mechanism‐based inhibitor of CYP2C8 based on an interaction with repaglinide. In addition, the PBPK model for clopidogrel and its metabolite were updated with additional in vitro data. Sensitivity analyses using these PBPK models suggested that CYP2C8 inhibition by clopidogrel acyl‐β‐D glucuronide may not be as potent as previously suggested. The dasabuvir and updated clopidogrel PBPK models predict a moderate increase of 1.5–1.9‐fold for Cmax and 1.9–2.8‐fold for AUC of dasabuvir when coadministered with clopidogrel. While the PBPK results suggest there is a potential for DDI between dasabuvir and clopidogrel, the magnitude is not expected to be clinically relevant. PMID:28411400

Updated aerosol module and its application to simulate secondary organic aerosols during IMPACT campaign May 2008

NASA Astrophysics Data System (ADS)

Li, Y. P.; Elbern, H.; Lu, K. D.; Friese, E.; Kiendler-Scharr, A.; Mentel, Th. F.; Wang, X. S.; Wahner, A.; Zhang, Y. H.

2013-03-01

The formation of Secondary organic aerosol (SOA) was simulated with the Secondary ORGanic Aerosol Model (SORGAM) by a classical gas-particle partitioning concept, using the two-product model approach, which is widely used in chemical transport models. In this study, we extensively updated SORGAM including three major modifications: firstly, we derived temperature dependence functions of the SOA yields for aromatics and biogenic VOCs, based on recent chamber studies within a sophisticated mathematic optimization framework; secondly, we implemented the SOA formation pathways from photo oxidation (OH initiated) of isoprene; thirdly, we implemented the SOA formation channel from NO3-initiated oxidation of reactive biogenic hydrocarbons (isoprene and monoterpenes). The temperature dependence functions of the SOA yields were validated against available chamber experiments. Moreover, the whole updated SORGAM module was validated against ambient SOA observations represented by the summed oxygenated organic aerosol (OOA) concentrations abstracted from Aerosol Mass Spectrometer (AMS) measurements at a rural site near Rotterdam, the Netherlands, performed during the IMPACT campaign in May 2008. In this case, we embedded both the original and the updated SORGAM module into the EURopean Air pollution and Dispersion-Inverse Model (EURAD-IM), which showed general good agreements with the observed meteorological parameters and several secondary products such as O3, sulfate and nitrate. With the updated SORGAM module, the EURAD-IM model also captured the observed SOA concentrations reasonably well especially those during nighttime. In contrast, the EURAD-IM model before update underestimated the observations by a factor of up to 5. The large improvements of the modeled SOA concentrations by updated SORGAM were attributed to the mentioned three modifications. Embedding the temperature dependence functions of the SOA yields, including the new pathways from isoprene photo oxidations, and switching on the SOA formation from NO3 initiated biogenic VOCs oxidations contributed to this enhancement by 10%, 22% and 47%, respectively. However, the EURAD-IM model with updated SORGAM still clearly underestimated the afternoon SOA observations up to a factor of two. More work such as to improve the simulated OH concentrations under high VOCs and low NOx concentrations, further including the SOA formation from semi-volatile organic compounds, the correct aging process of aerosols, oligomerization process and the influence on the biogenic SOA by the anthropogenic SOA, are still required to fill the gap.

A biokinetic model for systemic nickel

DOE PAGES

Melo, Dunstana; Leggett, Richard Wayne

2017-01-01

The International Commission on Radiological Protection (ICRP) is updating its suite of reference biokinetic models for internally deposited radionuclides. This paper reviews data for nickel and proposes an updated biokinetic model for systemic (absorbed) nickel in adult humans for use in radiation protection. Compared with the ICRP s current model for nickel, the proposed model is based on a larger set of observations of the behavior of nickel in human subjects and laboratory animals and provides a more realistic description of the paths of movement of nickel in the body. For the two most important radioisotopes of nickel, 59Ni andmore » 63Ni, the proposed model yields substantially lower dose estimates per unit of activity reaching blood than the current ICRP model.« less

A biokinetic model for systemic nickel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Melo, Dunstana; Leggett, Richard Wayne

The International Commission on Radiological Protection (ICRP) is updating its suite of reference biokinetic models for internally deposited radionuclides. This paper reviews data for nickel and proposes an updated biokinetic model for systemic (absorbed) nickel in adult humans for use in radiation protection. Compared with the ICRP s current model for nickel, the proposed model is based on a larger set of observations of the behavior of nickel in human subjects and laboratory animals and provides a more realistic description of the paths of movement of nickel in the body. For the two most important radioisotopes of nickel, 59Ni andmore » 63Ni, the proposed model yields substantially lower dose estimates per unit of activity reaching blood than the current ICRP model.« less

Sequential updating of multimodal hydrogeologic parameter fields using localization and clustering techniques

NASA Astrophysics Data System (ADS)

Sun, Alexander Y.; Morris, Alan P.; Mohanty, Sitakanta

2009-07-01

Estimated parameter distributions in groundwater models may contain significant uncertainties because of data insufficiency. Therefore, adaptive uncertainty reduction strategies are needed to continuously improve model accuracy by fusing new observations. In recent years, various ensemble Kalman filters have been introduced as viable tools for updating high-dimensional model parameters. However, their usefulness is largely limited by the inherent assumption of Gaussian error statistics. Hydraulic conductivity distributions in alluvial aquifers, for example, are usually non-Gaussian as a result of complex depositional and diagenetic processes. In this study, we combine an ensemble Kalman filter with grid-based localization and a Gaussian mixture model (GMM) clustering techniques for updating high-dimensional, multimodal parameter distributions via dynamic data assimilation. We introduce innovative strategies (e.g., block updating and dimension reduction) to effectively reduce the computational costs associated with these modified ensemble Kalman filter schemes. The developed data assimilation schemes are demonstrated numerically for identifying the multimodal heterogeneous hydraulic conductivity distributions in a binary facies alluvial aquifer. Our results show that localization and GMM clustering are very promising techniques for assimilating high-dimensional, multimodal parameter distributions, and they outperform the corresponding global ensemble Kalman filter analysis scheme in all scenarios considered.

Automotive Maintenance Data Base for Model Years 1976-1979. Part II : Appendix E and F

DOT National Transportation Integrated Search

1980-12-01

An update of the existing data base was developed to include life cycle maintenance costs of representative vehicles for the model years 1976-1979. Repair costs as a function of time are also developed for a passenger car in each of the compact, subc...

Update on Parametric Cost Models for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl. H. Philip; Henrichs, Todd; Luedtke, Alexander; West, Miranda

2011-01-01

Since the June 2010 Astronomy Conference, an independent review of our cost data base discovered some inaccuracies and inconsistencies which can modify our previously reported results. This paper will review changes to the data base, our confidence in those changes and their effect on various parametric cost models

Improving the representation of secondary organic aerosol (SOA) in the MOZART-4 global chemical transport model

NASA Astrophysics Data System (ADS)

Mahmud, A.; Barsanti, K. C.

2012-12-01

The secondary organic aerosol (SOA) module in the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4) has been updated by replacing existing two-product (2p) parameters with those obtained from two-product volatility basis set (2p-VBS) fits, and by treating SOA formation from the following volatile organic compounds (VOCs): isoprene, propene and lumped alkenes. Strong seasonal and spatial variations in global SOA distributions were demonstrated, with significant differences in the predicted concentrations between the base-case and updated model versions. The base-case MOZART-4 predicted annual average SOA of 0.36 ± 0.50 μg m-3 in South America, 0.31 ± 0.38 μg m-3 in Indonesia, 0.09 ± 0.05 μg m-3 in the USA, and 0.12 ± 0.07 μg m-3 in Europe. Concentrations from the updated versions of the model showed a~marked increase in annual average SOA. Using the updated set of parameters alone (MZ4-v1) increased annual average SOA by ~8%, ~16%, ~56%, and ~108% from the base-case in South America, Indonesia, USA, and Europe, respectively. Treatment of additional parent VOCs (MZ4-v2) resulted in an even more dramatic increase of ~178-406% in annual average SOA for these regions over the base-case. The increases in predicted SOA concentrations further resulted in increases in corresponding SOA contributions to annual average total aerosol optical depth (AOD) by <1% for MZ4-v1 and ~1-6% for MZ4-v2. Estimated global SOA production was ~6.6 Tg yr-1 and ~19.1 Tg yr-1 with corresponding burdens of ~0.24 Tg and ~0.59 Tg using MZ4-v1 and MZ4-v2, respectively. The SOA budgets predicted in the current study fall well within reported ranges for similar modeling studies, 6.7 to 96 Tg yr-1, but are lower than recently reported observationally-constrained values, 50 to 380 Tg yr-1. With MZ4-v2, simulated SOA concentrations at the surface were also in reasonable agreement with comparable modeling studies and observations. Concentrations of estimated organic aerosol (OA) at the surface, however, showed under-prediction in Europe and over-prediction in the Amazonian regions and Malaysian Borneo during certain months of the year. Overall, the updated version of MOZART-4, MZ4-v2, showed consistently better skill in predicting SOA and OA levels and spatial distributions as compared with unmodified MOZART-4. The MZ4-v2 updates may be particularly important when MOZART-4 output is used to generate boundary conditions for regional air quality simulations that require more accurate representation of SOA concentrations and distributions.

A Physics-Based Vibrotactile Feedback Library for Collision Events.

PubMed

Park, Gunhyuk; Choi, Seungmoon

2017-01-01

We present PhysVib: a software solution on the mobile platform extending an open-source physics engine in a multi-rate rendering architecture for automatic vibrotactile feedback upon collision events. PhysVib runs concurrently with a physics engine at a low update rate and generates vibrotactile feedback commands at a high update rate based on the simulation results of the physics engine using an exponentially-decaying sinusoidal model. We demonstrate through a user study that this vibration model is more appropriate to our purpose in terms of perceptual quality than more complex models based on sound synthesis. We also evaluated the perceptual performance of PhysVib by comparing eight vibrotactile rendering methods. Experimental results suggested that PhysVib enables more realistic vibrotactile feedback than the other methods as to perceived similarity to the visual events. PhysVib is an effective solution for providing physically plausible vibrotactile responses while reducing application development time to great extent.

Finite element modelling and updating of a lively footbridge: The complete process

NASA Astrophysics Data System (ADS)

Živanović, Stana; Pavic, Aleksandar; Reynolds, Paul

2007-03-01

The finite element (FE) model updating technology was originally developed in the aerospace and mechanical engineering disciplines to automatically update numerical models of structures to match their experimentally measured counterparts. The process of updating identifies the drawbacks in the FE modelling and the updated FE model could be used to produce more reliable results in further dynamic analysis. In the last decade, the updating technology has been introduced into civil structural engineering. It can serve as an advanced tool for getting reliable modal properties of large structures. The updating process has four key phases: initial FE modelling, modal testing, manual model tuning and automatic updating (conducted using specialist software). However, the published literature does not connect well these phases, although this is crucial when implementing the updating technology. This paper therefore aims to clarify the importance of this linking and to describe the complete model updating process as applicable in civil structural engineering. The complete process consisting the four phases is outlined and brief theory is presented as appropriate. Then, the procedure is implemented on a lively steel box girder footbridge. It was found that even a very detailed initial FE model underestimated the natural frequencies of all seven experimentally identified modes of vibration, with the maximum error being almost 30%. Manual FE model tuning by trial and error found that flexible supports in the longitudinal direction should be introduced at the girder ends to improve correlation between the measured and FE-calculated modes. This significantly reduced the maximum frequency error to only 4%. It was demonstrated that only then could the FE model be automatically updated in a meaningful way. The automatic updating was successfully conducted by updating 22 uncertain structural parameters. Finally, a physical interpretation of all parameter changes is discussed. This interpretation is often missing in the published literature. It was found that the composite slabs were less stiff than originally assumed and that the asphalt layer contributed considerably to the deck stiffness.

Exploration of Metaphorical and Contextual Affect Sensing in a Virtual Improvisational Drama

NASA Astrophysics Data System (ADS)

Zhang, Li

Real-time affect detection from open-ended text-based dialogue is challenging but essential for the building of effective intelligent user interfaces. In this paper, we report updated developments of an affect detection model from text, including affect detection from one particular type of metaphorical affective expression (cooking metaphor) and affect detection based on context. The overall affect detection model has been embedded in an intelligent conversational AI agent interacting with human users under loose scenarios. Evaluation for the updated affect detection component is also provided. Our work contributes to the conference themes on engagement and emotion, interactions in games, storytelling and narrative in education, and virtual characters/agents development.

On Theoretical Limits of Dynamic Model Updating Using a Sensitivity-Based Approach

NASA Astrophysics Data System (ADS)

GOLA, M. M.; SOMÀ, A.; BOTTO, D.

2001-07-01

The present work deals with the determination of the newly discovered conditions necessary for model updating with the eigensensitivity approach. The treatment concerns the maximum number of identifiable parameters regarding the structure of the eigenvectors derivatives. A mathematical demonstration is based on the evaluation of the rank of the least-squares matrix and produces the algebraic limiting conditions. Numerical application to a lumped parameter structure is employed to validate the mathematical limits taking into account different subsets of mode shapes. The demonstration is extended to the calculation of the eigenvector derivatives with both the Fox and Kapoor, and Nelson methods. III conditioning of the least-squares sensitivity matrix is revealed through the covariance jump.

Modeling and performance analysis of an improved movement-based location management scheme for packet-switched mobile communication systems.

PubMed

Chung, Yun Won; Kwon, Jae Kyun; Park, Suwon

2014-01-01

One of the key technologies to support mobility of mobile station (MS) in mobile communication systems is location management which consists of location update and paging. In this paper, an improved movement-based location management scheme with two movement thresholds is proposed, considering bursty data traffic characteristics of packet-switched (PS) services. The analytical modeling for location update and paging signaling loads of the proposed scheme is developed thoroughly and the performance of the proposed scheme is compared with that of the conventional scheme. We show that the proposed scheme outperforms the conventional scheme in terms of total signaling load with an appropriate selection of movement thresholds.

A response surface methodology based damage identification technique

NASA Astrophysics Data System (ADS)

Fang, S. E.; Perera, R.

2009-06-01

Response surface methodology (RSM) is a combination of statistical and mathematical techniques to represent the relationship between the inputs and outputs of a physical system by explicit functions. This methodology has been widely employed in many applications such as design optimization, response prediction and model validation. But so far the literature related to its application in structural damage identification (SDI) is scarce. Therefore this study attempts to present a systematic SDI procedure comprising four sequential steps of feature selection, parameter screening, primary response surface (RS) modeling and updating, and reference-state RS modeling with SDI realization using the factorial design (FD) and the central composite design (CCD). The last two steps imply the implementation of inverse problems by model updating in which the RS models substitute the FE models. The proposed method was verified against a numerical beam, a tested reinforced concrete (RC) frame and an experimental full-scale bridge with the modal frequency being the output responses. It was found that the proposed RSM-based method performs well in predicting the damage of both numerical and experimental structures having single and multiple damage scenarios. The screening capacity of the FD can provide quantitative estimation of the significance levels of updating parameters. Meanwhile, the second-order polynomial model established by the CCD provides adequate accuracy in expressing the dynamic behavior of a physical system.

Updated lateral attenuation in FAA's Integrated Noise Model

DOT National Transportation Integrated Search

2000-08-27

The lateral attenuation algorithm in the Federal Aviation Administration's (FAA) Integrated Noise Model (INM) has historically been based on the two regression equations described in the Society of Automotive Engineers' (SAE) Aerospace Information Re...

Community Multiscale Air Quality (CMAQ) Modeling for Regional and Hemispheric Scales

EPA Science Inventory

The CMAQ model is a Eulerian model that produces gridded values of atmospheric concentration and deposition. Recent updates to the model are highlighted that impact estimates of dry and wet deposition of nitrogen, sulfur and base cations. Output from the CMAQ model is used in t...

Seismic hazard in the Nation's breadbasket

USGS Publications Warehouse

Boyd, Oliver; Haller, Kathleen; Luco, Nicolas; Moschetti, Morgan P.; Mueller, Charles; Petersen, Mark D.; Rezaeian, Sanaz; Rubinstein, Justin L.

2015-01-01

The USGS National Seismic Hazard Maps were updated in 2014 and included several important changes for the central United States (CUS). Background seismicity sources were improved using a new moment-magnitude-based catalog; a new adaptive, nearest-neighbor smoothing kernel was implemented; and maximum magnitudes for background sources were updated. Areal source zones developed by the Central and Eastern United States Seismic Source Characterization for Nuclear Facilities project were simplified and adopted. The weighting scheme for ground motion models was updated, giving more weight to models with a faster attenuation with distance compared to the previous maps. Overall, hazard changes (2% probability of exceedance in 50 years, across a range of ground-motion frequencies) were smaller than 10% in most of the CUS relative to the 2008 USGS maps despite new ground motion models and their assigned logic tree weights that reduced the probabilistic ground motions by 5–20%.

Nonlinear model updating applied to the IMAC XXXII Round Robin benchmark system

NASA Astrophysics Data System (ADS)

Kurt, Mehmet; Moore, Keegan J.; Eriten, Melih; McFarland, D. Michael; Bergman, Lawrence A.; Vakakis, Alexander F.

2017-05-01

We consider the application of a new nonlinear model updating strategy to a computational benchmark system. The approach relies on analyzing system response time series in the frequency-energy domain by constructing both Hamiltonian and forced and damped frequency-energy plots (FEPs). The system parameters are then characterized and updated by matching the backbone branches of the FEPs with the frequency-energy wavelet transforms of experimental and/or computational time series. The main advantage of this method is that no nonlinearity model is assumed a priori, and the system model is updated solely based on simulation and/or experimental measured time series. By matching the frequency-energy plots of the benchmark system and its reduced-order model, we show that we are able to retrieve the global strongly nonlinear dynamics in the frequency and energy ranges of interest, identify bifurcations, characterize local nonlinearities, and accurately reconstruct time series. We apply the proposed methodology to a benchmark problem, which was posed to the system identification community prior to the IMAC XXXII (2014) and XXXIII (2015) Conferences as a "Round Robin Exercise on Nonlinear System Identification". We show that we are able to identify the parameters of the non-linear element in the problem with a priori knowledge about its position.

Numerical model updating technique for structures using firefly algorithm

NASA Astrophysics Data System (ADS)

Sai Kubair, K.; Mohan, S. C.

2018-03-01

Numerical model updating is a technique used for updating the existing experimental models for any structures related to civil, mechanical, automobiles, marine, aerospace engineering, etc. The basic concept behind this technique is updating the numerical models to closely match with experimental data obtained from real or prototype test structures. The present work involves the development of numerical model using MATLAB as a computational tool and with mathematical equations that define the experimental model. Firefly algorithm is used as an optimization tool in this study. In this updating process a response parameter of the structure has to be chosen, which helps to correlate the numerical model developed with the experimental results obtained. The variables for the updating can be either material or geometrical properties of the model or both. In this study, to verify the proposed technique, a cantilever beam is analyzed for its tip deflection and a space frame has been analyzed for its natural frequencies. Both the models are updated with their respective response values obtained from experimental results. The numerical results after updating show that there is a close relationship that can be brought between the experimental and the numerical models.

On the adaptive daily forecasting of seismic aftershock hazard

NASA Astrophysics Data System (ADS)

Ebrahimian, Hossein; Jalayer, Fatemeh; Asprone, Domenico; Lombardi, Anna Maria; Marzocchi, Warner; Prota, Andrea; Manfredi, Gaetano

2013-04-01

Post-earthquake ground motion hazard assessment is a fundamental initial step towards time-dependent seismic risk assessment for buildings in a post main-shock environment. Therefore, operative forecasting of seismic aftershock hazard forms a viable support basis for decision-making regarding search and rescue, inspection, repair, and re-occupation in a post main-shock environment. Arguably, an adaptive procedure for integrating the aftershock occurrence rate together with suitable ground motion prediction relations is key to Probabilistic Seismic Aftershock Hazard Assessment (PSAHA). In the short-term, the seismic hazard may vary significantly (Jordan et al., 2011), particularly after the occurrence of a high magnitude earthquake. Hence, PSAHA requires a reliable model that is able to track the time evolution of the earthquake occurrence rates together with suitable ground motion prediction relations. This work focuses on providing adaptive daily forecasts of the mean daily rate of exceeding various spectral acceleration values (the aftershock hazard). Two well-established earthquake occurrence models suitable for daily seismicity forecasts associated with the evolution of an aftershock sequence, namely, the modified Omori's aftershock model and the Epidemic Type Aftershock Sequence (ETAS) are adopted. The parameters of the modified Omori model are updated on a daily basis using Bayesian updating and based on the data provided by the ongoing aftershock sequence based on the methodology originally proposed by Jalayer et al. (2011). The Bayesian updating is used also to provide sequence-based parameter estimates for a given ground motion prediction model, i.e. the aftershock events in an ongoing sequence are exploited in order to update in an adaptive manner the parameters of an existing ground motion prediction model. As a numerical example, the mean daily rates of exceeding specific spectral acceleration values are estimated adaptively for the L'Aquila 2009 aftershock catalog. The parameters of the modified Omori model are estimated in an adaptive manner using the Bayesian updating based on the aftershock events that had already taken place at each day elapsed and using the Italian generic sequence (Lolli and Gasperini 2003) as prior information. For the ETAS model, the real-time daily forecast of the spatio-temporal evolution of the L'Aquila sequence provided for the Italian Civil Protection for managing the emergency (Marzocchi and Lombardi, 2009) is utilized. Moreover, the parameters of the ground motion prediction relation proposed by Sabetta and Pugliese (1996) are updated adaptively and on a daily basis using Bayesian updating based on the ongoing aftershock sequence. Finally, the forecasted daily rates of exceeding (first-mode) spectral acceleration values are compared with observed rates of exceedance calculated based on the wave-forms that have actually taken place. References Jalayer, F., Asprone, D., Prota, A., Manfredi, G. (2011). A decision support system for post-earthquake reliability assessment of structures subjected to after-shocks: an application to L'Aquila earthquake, 2009. Bull. Earthquake Eng. 9(4) 997-1014. Jordan, T.H., Chen Y-T., Gasparini P., Madariaga R., Main I., Marzocchi W., Papadopoulos G., Sobolev G., Yamaoka K., and J. Zschau (2011). Operational earthquake forecasting: State of knowledge and guidelines for implementation, Ann. Geophys. 54(4) 315-391, doi 10.4401/ag-5350. Lolli, B., and P. Gasperini (2003). Aftershocks hazard in Italy part I: estimation of time-magnitude distribution model parameters and computation of probabilities of occurrence. Journal of Seismology 7(2) 235-257. Marzocchi, W., and A.M. Lombardi (2009). Real-time forecasting following a damaging earthquake, Geophys. Res. Lett. 36, L21302, doi: 10.1029/2009GL040233. Sabetta F., A. Pugliese (1996) Estimation of response spectra and simulation of nonstationary earthquake ground motions. Bull Seismol Soc Am 86(2) 337-352.

Objective analysis of observational data from the FGGE observing systems

NASA Technical Reports Server (NTRS)

Baker, W.; Edelmann, D.; Iredell, M.; Han, D.; Jakkempudi, S.

1981-01-01

An objective analysis procedure for updating the GLAS second and fourth order general atmospheric circulation models using observational data from the first GARP global experiment is described. The objective analysis procedure is based on a successive corrections method and the model is updated in a data assimilation cycle. Preparation of the observational data for analysis and the objective analysis scheme are described. The organization of the program and description of the required data sets are presented. The program logic and detailed descriptions of each subroutine are given.

Numerical simulation of groundwater flow at Puget Sound Naval Shipyard, Naval Base Kitsap, Bremerton, Washington

USGS Publications Warehouse

Jones, Joseph L.; Johnson, Kenneth H.; Frans, Lonna M.

2016-08-18

Information about groundwater-flow paths and locations where groundwater discharges at and near Puget Sound Naval Shipyard is necessary for understanding the potential migration of subsurface contaminants by groundwater at the shipyard. The design of some remediation alternatives would be aided by knowledge of whether groundwater flowing at specific locations beneath the shipyard will eventually discharge directly to Sinclair Inlet of Puget Sound, or if it will discharge to the drainage system of one of the six dry docks located in the shipyard. A 1997 numerical (finite difference) groundwater-flow model of the shipyard and surrounding area was constructed to help evaluate the potential for groundwater discharge to Puget Sound. That steady-state, multilayer numerical model with homogeneous hydraulic characteristics indicated that groundwater flowing beneath nearly all of the shipyard discharges to the dry-dock drainage systems, and only shallow groundwater flowing beneath the western end of the shipyard discharges directly to Sinclair Inlet.Updated information from a 2016 regional groundwater-flow model constructed for the greater Kitsap Peninsula was used to update the 1997 groundwater model of the Puget Sound Naval Shipyard. That information included a new interpretation of the hydrogeologic units underlying the area, as well as improved recharge estimates. Other updates to the 1997 model included finer discretization of the finite-difference model grid into more layers, rows, and columns, all with reduced dimensions. This updated Puget Sound Naval Shipyard model was calibrated to 2001–2005 measured water levels, and hydraulic characteristics of the model layers representing different hydrogeologic units were estimated with the aid of state-of-the-art parameter optimization techniques.The flow directions and discharge locations predicted by this updated model generally match the 1997 model despite refinements and other changes. In the updated model, most groundwater discharge recharged within the boundaries of the shipyard is to the dry docks; only at the western end of the shipyard does groundwater discharge directly to Puget Sound. Particle tracking for the existing long-term monitoring well network suggests that only a few wells intercept groundwater that originates as recharge within the shipyard boundary.

ASKI: A modular toolbox for scattering-integral-based seismic full waveform inversion and sensitivity analysis utilizing external forward codes

NASA Astrophysics Data System (ADS)

Schumacher, Florian; Friederich, Wolfgang

Due to increasing computational resources, the development of new numerically demanding methods and software for imaging Earth's interior remains of high interest in Earth sciences. Here, we give a description from a user's and programmer's perspective of the highly modular, flexible and extendable software package ASKI-Analysis of Sensitivity and Kernel Inversion-recently developed for iterative scattering-integral-based seismic full waveform inversion. In ASKI, the three fundamental steps of solving the seismic forward problem, computing waveform sensitivity kernels and deriving a model update are solved by independent software programs that interact via file output/input only. Furthermore, the spatial discretizations of the model space used for solving the seismic forward problem and for deriving model updates, respectively, are kept completely independent. For this reason, ASKI does not contain a specific forward solver but instead provides a general interface to established community wave propagation codes. Moreover, the third fundamental step of deriving a model update can be repeated at relatively low costs applying different kinds of model regularization or re-selecting/weighting the inverted dataset without need to re-solve the forward problem or re-compute the kernels. Additionally, ASKI offers the user sensitivity and resolution analysis tools based on the full sensitivity matrix and allows to compose customized workflows in a consistent computational environment. ASKI is written in modern Fortran and Python, it is well documented and freely available under terms of the GNU General Public License (http://www.rub.de/aski).

Updating of states in operational hydrological models

NASA Astrophysics Data System (ADS)

Bruland, O.; Kolberg, S.; Engeland, K.; Gragne, A. S.; Liston, G.; Sand, K.; Tøfte, L.; Alfredsen, K.

2012-04-01

Operationally the main purpose of hydrological models is to provide runoff forecasts. The quality of the model state and the accuracy of the weather forecast together with the model quality define the runoff forecast quality. Input and model errors accumulate over time and may leave the model in a poor state. Usually model states can be related to observable conditions in the catchment. Updating of these states, knowing their relation to observable catchment conditions, influence directly the forecast quality. Norway is internationally in the forefront in hydropower scheduling both on short and long terms. The inflow forecasts are fundamental to this scheduling. Their quality directly influence the producers profit as they optimize hydropower production to market demand and at the same time minimize spill of water and maximize available hydraulic head. The quality of the inflow forecasts strongly depends on the quality of the models applied and the quality of the information they use. In this project the focus has been to improve the quality of the model states which the forecast is based upon. Runoff and snow storage are two observable quantities that reflect the model state and are used in this project for updating. Generally the methods used can be divided in three groups: The first re-estimates the forcing data in the updating period; the second alters the weights in the forecast ensemble; and the third directly changes the model states. The uncertainty related to the forcing data through the updating period is due to both uncertainty in the actual observation and to how well the gauging stations represent the catchment both in respect to temperatures and precipitation. The project looks at methodologies that automatically re-estimates the forcing data and tests the result against observed response. Model uncertainty is reflected in a joint distribution of model parameters estimated using the Dream algorithm.

An Ensemble-Based Smoother with Retrospectively Updated Weights for Highly Nonlinear Systems

NASA Technical Reports Server (NTRS)

Chin, T. M.; Turmon, M. J.; Jewell, J. B.; Ghil, M.

2006-01-01

Monte Carlo computational methods have been introduced into data assimilation for nonlinear systems in order to alleviate the computational burden of updating and propagating the full probability distribution. By propagating an ensemble of representative states, algorithms like the ensemble Kalman filter (EnKF) and the resampled particle filter (RPF) rely on the existing modeling infrastructure to approximate the distribution based on the evolution of this ensemble. This work presents an ensemble-based smoother that is applicable to the Monte Carlo filtering schemes like EnKF and RPF. At the minor cost of retrospectively updating a set of weights for ensemble members, this smoother has demonstrated superior capabilities in state tracking for two highly nonlinear problems: the double-well potential and trivariate Lorenz systems. The algorithm does not require retrospective adaptation of the ensemble members themselves, and it is thus suited to a streaming operational mode. The accuracy of the proposed backward-update scheme in estimating non-Gaussian distributions is evaluated by comparison to the more accurate estimates provided by a Markov chain Monte Carlo algorithm.

Fuel consumption modeling in support of ATM environmental decision-making

DOT National Transportation Integrated Search

2009-07-01

The FAA has recently updated the airport terminal : area fuel consumption methods used in its environmental models. : These methods are based on fitting manufacturers fuel : consumption data to empirical equations. The new fuel : consumption metho...

Walking Distance Estimation Using Walking Canes with Inertial Sensors

PubMed Central

Suh, Young Soo

2018-01-01

A walking distance estimation algorithm for cane users is proposed using an inertial sensor unit attached to various positions on the cane. A standard inertial navigation algorithm using an indirect Kalman filter was applied to update the velocity and position of the cane during movement. For quadripod canes, a standard zero-velocity measurement-updating method is proposed. For standard canes, a velocity-updating method based on an inverted pendulum model is proposed. The proposed algorithms were verified by three walking experiments with two different types of canes and different positions of the sensor module. PMID:29342971

Damage severity assessment in wind turbine blade laboratory model through fuzzy finite element model updating

NASA Astrophysics Data System (ADS)

Turnbull, Heather; Omenzetter, Piotr

2017-04-01

The recent shift towards development of clean, sustainable energy sources has provided a new challenge in terms of structural safety and reliability: with aging, manufacturing defects, harsh environmental and operational conditions, and extreme events such as lightning strikes wind turbines can become damaged resulting in production losses and environmental degradation. To monitor the current structural state of the turbine, structural health monitoring (SHM) techniques would be beneficial. Physics based SHM in the form of calibration of a finite element model (FEMs) by inverse techniques is adopted in this research. Fuzzy finite element model updating (FFEMU) techniques for damage severity assessment of a small-scale wind turbine blade are discussed and implemented. The main advantage is the ability of FFEMU to account in a simple way for uncertainty within the problem of model updating. Uncertainty quantification techniques, such as fuzzy sets, enable a convenient mathematical representation of the various uncertainties. Experimental frequencies obtained from modal analysis on a small-scale wind turbine blade were described by fuzzy numbers to model measurement uncertainty. During this investigation, damage severity estimation was investigated through addition of small masses of varying magnitude to the trailing edge of the structure. This structural modification, intended to be in lieu of damage, enabled non-destructive experimental simulation of structural change. A numerical model was constructed with multiple variable additional masses simulated upon the blades trailing edge and used as updating parameters. Objective functions for updating were constructed and minimized using both particle swarm optimization algorithm and firefly algorithm. FFEMU was able to obtain a prediction of baseline material properties of the blade whilst also successfully predicting, with sufficient accuracy, a larger magnitude of structural alteration and its location.

Integrated Functional and Executional Modelling of Software Using Web-Based Databases

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Marietta, Roberta

1998-01-01

NASA's software subsystems undergo extensive modification and updates over the operational lifetimes. It is imperative that modified software should satisfy safety goals. This report discusses the difficulties encountered in doing so and discusses a solution based on integrated modelling of software, use of automatic information extraction tools, web technology and databases.

Characterization of Orbital Debris via Hyper-Velocity Laboratory-Based Tests

NASA Technical Reports Server (NTRS)

Cowardin, Heather; Liou, J.-C.; Anz-Meador, Phillip; Sorge, Marlon; Opiela, John; Fitz-Coy, Norman; Huynh, Tom; Krisko, Paula

2017-01-01

Existing DOD and NASA satellite breakup models are based on a key laboratory test, Satellite Orbital debris Characterization Impact Test (SOCIT), which has supported many applications and matched on-orbit events involving older satellite designs reasonably well over the years. In order to update and improve these models, the NASA Orbital Debris Program Office, in collaboration with the Air Force Space and Missile Systems Center, The Aerospace Corporation, and the University of Florida, replicated a hypervelocity impact using a mock-up satellite, DebriSat, in controlled laboratory conditions. DebriSat is representative of present-day LEO satellites, built with modern spacecraft materials and construction techniques. Fragments down to 2 mm in size will be characterized by their physical and derived properties. A subset of fragments will be further analyzed in laboratory radar and optical facilities to update the existing radar-based NASA Size Estimation Model (SEM) and develop a comparable optical-based SEM. A historical overview of the project, status of the characterization process, and plans for integrating the data into various models will be discussed herein.

Characterization of Orbital Debris via Hyper-Velocity Laboratory-Based Tests

NASA Technical Reports Server (NTRS)

Cowardin, Heather; Liou, J.-C.; Krisko, Paula; Opiela, John; Fitz-Coy, Norman; Sorge, Marlon; Huynh, Tom

2017-01-01

Existing DoD and NASA satellite breakup models are based on a key laboratory test, Satellite Orbital debris Characterization Impact Test (SOCIT), which has supported many applications and matched on-orbit events involving older satellite designs reasonably well over the years. In order to update and improve these models, the NASA Orbital Debris Program Office, in collaboration with the Air Force Space and Missile Systems Center, The Aerospace Corporation, and the University of Florida, replicated a hypervelocity impact using a mock-up satellite, DebriSat, in controlled laboratory conditions. DebriSat is representative of present-day LEO satellites, built with modern spacecraft materials and construction techniques. Fragments down to 2 mm in size will be characterized by their physical and derived properties. A subset of fragments will be further analyzed in laboratory radar and optical facilities to update the existing radar-based NASA Size Estimation Model (SEM) and develop a comparable optical-based SEM. A historical overview of the project, status of the characterization process, and plans for integrating the data into various models will be discussed herein.

HARMONIZATION AND COMMUNICATION OF PBPK MODELS USING THE EXPOSURE RELATED DOSE ESTIMATION MODEL (ERDEM) SYSTEM: TRICHLOROETHYLENE

EPA Science Inventory

In support of the trichloroethylene (TCE) risk assessment for the Office of Air and Radiation, Office of Solid Waste and Emergency Response, and Office of Water, NERL and NCEA are developing an updated physiologically-based pharmacokinetic (PBPK) model. The PBPK modeling effort ...

HARMONIZATION AND COMMUNICATION OF PBPK MODELS USING THE EXPOSURE RELATED DOSE MODEL (ERDEM) SYSTEM: TRICHLOROETHYLENE

EPA Science Inventory

In support of the trichloroethylene (TCE) risk assessment for the Office of Air and Radiation, Office of Solid Waste and Emergency Response, and Office of Water, NERL and NCEA are developing an updated physiologically-based pharmacokinetic (PBPK) model. The PBPK modeling effor...

An updated geospatial liquefaction model for global application

USGS Publications Warehouse

Zhu, Jing; Baise, Laurie G.; Thompson, Eric M.

2017-01-01

We present an updated geospatial approach to estimation of earthquake-induced liquefaction from globally available geospatial proxies. Our previous iteration of the geospatial liquefaction model was based on mapped liquefaction surface effects from four earthquakes in Christchurch, New Zealand, and Kobe, Japan, paired with geospatial explanatory variables including slope-derived VS30, compound topographic index, and magnitude-adjusted peak ground acceleration from ShakeMap. The updated geospatial liquefaction model presented herein improves the performance and the generality of the model. The updates include (1) expanding the liquefaction database to 27 earthquake events across 6 countries, (2) addressing the sampling of nonliquefaction for incomplete liquefaction inventories, (3) testing interaction effects between explanatory variables, and (4) overall improving model performance. While we test 14 geospatial proxies for soil density and soil saturation, the most promising geospatial parameters are slope-derived VS30, modeled water table depth, distance to coast, distance to river, distance to closest water body, and precipitation. We found that peak ground velocity (PGV) performs better than peak ground acceleration (PGA) as the shaking intensity parameter. We present two models which offer improved performance over prior models. We evaluate model performance using the area under the curve under the Receiver Operating Characteristic (ROC) curve (AUC) and the Brier score. The best-performing model in a coastal setting uses distance to coast but is problematic for regions away from the coast. The second best model, using PGV, VS30, water table depth, distance to closest water body, and precipitation, performs better in noncoastal regions and thus is the model we recommend for global implementation.

Multiplexed Predictive Control of a Large Commercial Turbofan Engine

NASA Technical Reports Server (NTRS)

Richter, hanz; Singaraju, Anil; Litt, Jonathan S.

2008-01-01

Model predictive control is a strategy well-suited to handle the highly complex, nonlinear, uncertain, and constrained dynamics involved in aircraft engine control problems. However, it has thus far been infeasible to implement model predictive control in engine control applications, because of the combination of model complexity and the time allotted for the control update calculation. In this paper, a multiplexed implementation is proposed that dramatically reduces the computational burden of the quadratic programming optimization that must be solved online as part of the model-predictive-control algorithm. Actuator updates are calculated sequentially and cyclically in a multiplexed implementation, as opposed to the simultaneous optimization taking place in conventional model predictive control. Theoretical aspects are discussed based on a nominal model, and actual computational savings are demonstrated using a realistic commercial engine model.

Timing Interactions in Social Simulations: The Voter Model

NASA Astrophysics Data System (ADS)

Fernández-Gracia, Juan; Eguíluz, Víctor M.; Miguel, Maxi San

The recent availability of huge high resolution datasets on human activities has revealed the heavy-tailed nature of the interevent time distributions. In social simulations of interacting agents the standard approach has been to use Poisson processes to update the state of the agents, which gives rise to very homogeneous activity patterns with a well defined characteristic interevent time. As a paradigmatic opinion model we investigate the voter model and review the standard update rules and propose two new update rules which are able to account for heterogeneous activity patterns. For the new update rules each node gets updated with a probability that depends on the time since the last event of the node, where an event can be an update attempt (exogenous update) or a change of state (endogenous update). We find that both update rules can give rise to power law interevent time distributions, although the endogenous one more robustly. Apart from that for the exogenous update rule and the standard update rules the voter model does not reach consensus in the infinite size limit, while for the endogenous update there exist a coarsening process that drives the system toward consensus configurations.

Experimental Validation of Model Updating and Damage Detection via Eigenvalue Sensitivity Methods with Artificial Boundary Conditions

DTIC Science & Technology

2017-09-01

VALIDATION OF MODEL UPDATING AND DAMAGE DETECTION VIA EIGENVALUE SENSITIVITY METHODS WITH ARTIFICIAL BOUNDARY CONDITIONS by Matthew D. Bouwense...VALIDATION OF MODEL UPDATING AND DAMAGE DETECTION VIA EIGENVALUE SENSITIVITY METHODS WITH ARTIFICIAL BOUNDARY CONDITIONS 5. FUNDING NUMBERS 6. AUTHOR...unlimited. EXPERIMENTAL VALIDATION OF MODEL UPDATING AND DAMAGE DETECTION VIA EIGENVALUE SENSITIVITY METHODS WITH ARTIFICIAL BOUNDARY

ERM model analysis for adaptation to hydrological model errors

NASA Astrophysics Data System (ADS)

Baymani-Nezhad, M.; Han, D.

2018-05-01

Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.

Single and multiple object tracking using log-euclidean Riemannian subspace and block-division appearance model.

PubMed

Hu, Weiming; Li, Xi; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen; Zhang, Zhongfei

2012-12-01

Object appearance modeling is crucial for tracking objects, especially in videos captured by nonstationary cameras and for reasoning about occlusions between multiple moving objects. Based on the log-euclidean Riemannian metric on symmetric positive definite matrices, we propose an incremental log-euclidean Riemannian subspace learning algorithm in which covariance matrices of image features are mapped into a vector space with the log-euclidean Riemannian metric. Based on the subspace learning algorithm, we develop a log-euclidean block-division appearance model which captures both the global and local spatial layout information about object appearances. Single object tracking and multi-object tracking with occlusion reasoning are then achieved by particle filtering-based Bayesian state inference. During tracking, incremental updating of the log-euclidean block-division appearance model captures changes in object appearance. For multi-object tracking, the appearance models of the objects can be updated even in the presence of occlusions. Experimental results demonstrate that the proposed tracking algorithm obtains more accurate results than six state-of-the-art tracking algorithms.

Graphical user interface for intraoperative neuroimage updating

NASA Astrophysics Data System (ADS)

Rick, Kyle R.; Hartov, Alex; Roberts, David W.; Lunn, Karen E.; Sun, Hai; Paulsen, Keith D.

2003-05-01

Image-guided neurosurgery typically relies on preoperative imaging information that is subject to errors resulting from brain shift and deformation in the OR. A graphical user interface (GUI) has been developed to facilitate the flow of data from OR to image volume in order to provide the neurosurgeon with updated views concurrent with surgery. Upon acquisition of registration data for patient position in the OR (using fiducial markers), the Matlab GUI displays ultrasound image overlays on patient specific, preoperative MR images. Registration matrices are also applied to patient-specific anatomical models used for image updating. After displaying the re-oriented brain model in OR coordinates and digitizing the edge of the craniotomy, gravitational sagging of the brain is simulated using the finite element method. Based on this model, interpolation to the resolution of the preoperative images is performed and re-displayed to the surgeon during the procedure. These steps were completed within reasonable time limits and the interface was relatively easy to use after a brief training period. The techniques described have been developed and used retrospectively prior to this study. Based on the work described here, these steps can now be accomplished in the operating room and provide near real-time feedback to the surgeon.

A review of statistical updating methods for clinical prediction models.

PubMed

Su, Ting-Li; Jaki, Thomas; Hickey, Graeme L; Buchan, Iain; Sperrin, Matthew

2018-01-01

A clinical prediction model is a tool for predicting healthcare outcomes, usually within a specific population and context. A common approach is to develop a new clinical prediction model for each population and context; however, this wastes potentially useful historical information. A better approach is to update or incorporate the existing clinical prediction models already developed for use in similar contexts or populations. In addition, clinical prediction models commonly become miscalibrated over time, and need replacing or updating. In this article, we review a range of approaches for re-using and updating clinical prediction models; these fall in into three main categories: simple coefficient updating, combining multiple previous clinical prediction models in a meta-model and dynamic updating of models. We evaluated the performance (discrimination and calibration) of the different strategies using data on mortality following cardiac surgery in the United Kingdom: We found that no single strategy performed sufficiently well to be used to the exclusion of the others. In conclusion, useful tools exist for updating existing clinical prediction models to a new population or context, and these should be implemented rather than developing a new clinical prediction model from scratch, using a breadth of complementary statistical methods.

Derivation of low flow frequency distributions under human activities and its implications

NASA Astrophysics Data System (ADS)

Gao, Shida; Liu, Pan; Pan, Zhengke; Ming, Bo; Guo, Shenglian; Xiong, Lihua

2017-06-01

Low flow, refers to a minimum streamflow in dry seasons, is crucial to water supply, agricultural irrigation and navigation. Human activities, such as groundwater pumping, influence low flow severely. In order to derive the low flow frequency distribution functions under human activities, this study incorporates groundwater pumping and return flow as variables in the recession process. Steps are as follows: (1) the original low flow without human activities is assumed to follow a Pearson type three distribution, (2) the probability distribution of climatic dry spell periods is derived based on a base flow recession model, (3) the base flow recession model is updated under human activities, and (4) the low flow distribution under human activities is obtained based on the derived probability distribution of dry spell periods and the updated base flow recession model. Linear and nonlinear reservoir models are used to describe the base flow recession, respectively. The Wudinghe basin is chosen for the case study, with daily streamflow observations during 1958-2000. Results show that human activities change the location parameter of the low flow frequency curve for the linear reservoir model, while alter the frequency distribution function for the nonlinear one. It is indicated that alter the parameters of the low flow frequency distribution is not always feasible to tackle the changing environment.

A new frequency matching technique for FRF-based model updating

NASA Astrophysics Data System (ADS)

Yang, Xiuming; Guo, Xinglin; Ouyang, Huajiang; Li, Dongsheng

2017-05-01

Frequency Response Function (FRF) residues have been widely used to update Finite Element models. They are a kind of original measurement information and have the advantages of rich data and no extraction errors, etc. However, like other sensitivity-based methods, an FRF-based identification method also needs to face the ill-conditioning problem which is even more serious since the sensitivity of the FRF in the vicinity of a resonance is much greater than elsewhere. Furthermore, for a given frequency measurement, directly using a theoretical FRF at a frequency may lead to a huge difference between the theoretical FRF and the corresponding experimental FRF which finally results in larger effects of measurement errors and damping. Hence in the solution process, correct selection of the appropriate frequency to get the theoretical FRF in every iteration in the sensitivity-based approach is an effective way to improve the robustness of an FRF-based algorithm. A primary tool for right frequency selection based on the correlation of FRFs is the Frequency Domain Assurance Criterion. This paper presents a new frequency selection method which directly finds the frequency that minimizes the difference of the order of magnitude between the theoretical and experimental FRFs. A simulated truss structure is used to compare the performance of different frequency selection methods. For the sake of reality, it is assumed that not all the degrees of freedom (DoFs) are available for measurement. The minimum number of DoFs required in each approach to correctly update the analytical model is regarded as the right identification standard.

A Multipopulation PSO Based Memetic Algorithm for Permutation Flow Shop Scheduling

PubMed Central

Liu, Ruochen; Ma, Chenlin; Ma, Wenping; Li, Yangyang

2013-01-01

The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS) and individual improvement scheme (IIS). Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA) and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA) and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA), on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP. PMID:24453841

Update rules and interevent time distributions: slow ordering versus no ordering in the voter model.

PubMed

Fernández-Gracia, J; Eguíluz, V M; San Miguel, M

2011-07-01

We introduce a general methodology of update rules accounting for arbitrary interevent time (IET) distributions in simulations of interacting agents. We consider in particular update rules that depend on the state of the agent, so that the update becomes part of the dynamical model. As an illustration we consider the voter model in fully connected, random, and scale-free networks with an activation probability inversely proportional to the time since the last action, where an action can be an update attempt (an exogenous update) or a change of state (an endogenous update). We find that in the thermodynamic limit, at variance with standard updates and the exogenous update, the system orders slowly for the endogenous update. The approach to the absorbing state is characterized by a power-law decay of the density of interfaces, observing that the mean time to reach the absorbing state might be not well defined. The IET distributions resulting from both update schemes show power-law tails.

Multi-level damage identification with response reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Chao-Dong; Xu, You-Lin

2017-10-01

Damage identification through finite element (FE) model updating usually forms an inverse problem. Solving the inverse identification problem for complex civil structures is very challenging since the dimension of potential damage parameters in a complex civil structure is often very large. Aside from enormous computation efforts needed in iterative updating, the ill-condition and non-global identifiability features of the inverse problem probably hinder the realization of model updating based damage identification for large civil structures. Following a divide-and-conquer strategy, a multi-level damage identification method is proposed in this paper. The entire structure is decomposed into several manageable substructures and each substructure is further condensed as a macro element using the component mode synthesis (CMS) technique. The damage identification is performed at two levels: the first is at macro element level to locate the potentially damaged region and the second is over the suspicious substructures to further locate as well as quantify the damage severity. In each level's identification, the damage searching space over which model updating is performed is notably narrowed down, not only reducing the computation amount but also increasing the damage identifiability. Besides, the Kalman filter-based response reconstruction is performed at the second level to reconstruct the response of the suspicious substructure for exact damage quantification. Numerical studies and laboratory tests are both conducted on a simply supported overhanging steel beam for conceptual verification. The results demonstrate that the proposed multi-level damage identification via response reconstruction does improve the identification accuracy of damage localization and quantization considerably.

Moving vehicles segmentation based on Gaussian motion model

NASA Astrophysics Data System (ADS)

Zhang, Wei; Fang, Xiang Z.; Lin, Wei Y.

2005-07-01

Moving objects segmentation is a challenge in computer vision. This paper focuses on the segmentation of moving vehicles in dynamic scene. We analyses the psychology of human vision and present a framework for segmenting moving vehicles in the highway. The proposed framework consists of two parts. Firstly, we propose an adaptive background update method in which the background is updated according to the change of illumination conditions and thus can adapt to the change of illumination sensitively. Secondly, we construct a Gaussian motion model to segment moving vehicles, in which the motion vectors of the moving pixels are modeled as a Gaussian model and an on-line EM algorithm is used to update the model. The Gaussian distribution of the adaptive model is elevated to determine which moving vectors result from moving vehicles and which from other moving objects such as waving trees. Finally, the pixels with motion vector result from the moving vehicles are segmented. Experimental results of several typical scenes show that the proposed model can detect the moving vehicles correctly and is immune from influence of the moving objects caused by the waving trees and the vibration of camera.

A gradual update method for simulating the steady-state solution of stiff differential equations in metabolic circuits.

PubMed

Shiraishi, Emi; Maeda, Kazuhiro; Kurata, Hiroyuki

2009-02-01

Numerical simulation of differential equation systems plays a major role in the understanding of how metabolic network models generate particular cellular functions. On the other hand, the classical and technical problems for stiff differential equations still remain to be solved, while many elegant algorithms have been presented. To relax the stiffness problem, we propose new practical methods: the gradual update of differential-algebraic equations based on gradual application of the steady-state approximation to stiff differential equations, and the gradual update of the initial values in differential-algebraic equations. These empirical methods show a high efficiency for simulating the steady-state solutions for the stiff differential equations that existing solvers alone cannot solve. They are effective in extending the applicability of dynamic simulation to biochemical network models.

Update of aircraft profile data for the Integrated Noise Model computer program, vol 1: final report

DOT National Transportation Integrated Search

1992-03-01

This report provides aircraft takeoff and landing profiles, aircraft aerodynamic performance coefficients and engine performance coefficients for the aircraft data base (Database 9) in the Integrated Noise Model (INM) computer program. Flight profile...

Numerical simulation of intelligent compaction technology for construction quality control.

DOT National Transportation Integrated Search

2015-02-01

For eciently updating models of large-scale structures, the response surface (RS) method based on radial basis : functions (RBFs) is proposed to model the input-output relationship of structures. The key issues for applying : the proposed method a...

An Overview of the Object Protocol Model (OPM) and the OPM Data Management Tools.

ERIC Educational Resources Information Center

Chen, I-Min A.; Markowitz, Victor M.

1995-01-01

Discussion of database management tools for scientific information focuses on the Object Protocol Model (OPM) and data management tools based on OPM. Topics include the need for new constructs for modeling scientific experiments, modeling object structures and experiments in OPM, queries and updates, and developing scientific database applications…

Update on SU(2) gauge theory with NF = 2 fundamental flavours.

NASA Astrophysics Data System (ADS)

Drach, Vincent; Janowski, Tadeusz; Pica, Claudio

2018-03-01

We present a non perturbative study of SU(2) gauge theory with two fundamental Dirac flavours. This theory provides a minimal template which is ideal for a wide class of Standard Model extensions featuring novel strong dynamics, such as a minimal realization of composite Higgs models. We present an update on the status of the meson spectrum and decay constants based on increased statistics on our existing ensembles and the inclusion of new ensembles with lighter pion masses, resulting in a more reliable chiral extrapolation. Preprint: CP3-Origins-2017-048 DNRF90

Multiplicative Forests for Continuous-Time Processes

PubMed Central

Weiss, Jeremy C.; Natarajan, Sriraam; Page, David

2013-01-01

Learning temporal dependencies between variables over continuous time is an important and challenging task. Continuous-time Bayesian networks effectively model such processes but are limited by the number of conditional intensity matrices, which grows exponentially in the number of parents per variable. We develop a partition-based representation using regression trees and forests whose parameter spaces grow linearly in the number of node splits. Using a multiplicative assumption we show how to update the forest likelihood in closed form, producing efficient model updates. Our results show multiplicative forests can be learned from few temporal trajectories with large gains in performance and scalability. PMID:25284967

Multiplicative Forests for Continuous-Time Processes.

PubMed

Weiss, Jeremy C; Natarajan, Sriraam; Page, David

2012-01-01

Learning temporal dependencies between variables over continuous time is an important and challenging task. Continuous-time Bayesian networks effectively model such processes but are limited by the number of conditional intensity matrices, which grows exponentially in the number of parents per variable. We develop a partition-based representation using regression trees and forests whose parameter spaces grow linearly in the number of node splits. Using a multiplicative assumption we show how to update the forest likelihood in closed form, producing efficient model updates. Our results show multiplicative forests can be learned from few temporal trajectories with large gains in performance and scalability.

Updates to watershed modeling in the Potholes Reservoir basin, Washington-a supplement to Scientific Investigation Report 2009-5081

USGS Publications Warehouse

Mastin, Mark

2012-01-01

A previous collaborative effort between the U.S. Geological Survey and the Bureau of Reclamation resulted in a watershed model for four watersheds that discharge into Potholes Reservoir, Washington. Since the model was constructed, two new meteorological sites have been established that provide more reliable real-time information. The Bureau of Reclamation was interested in incorporating this new information into the existing watershed model developed in 2009, and adding measured snowpack information to update simulated results and to improve forecasts of runoff. This report includes descriptions of procedures to aid a user in making model runs, including a description of the Object User Interface for the watershed model with details on specific keystrokes to generate model runs for the contributing basins. A new real-time, data-gathering computer program automates the creation of the model input files and includes the new meteorological sites. The 2009 watershed model was updated with the new sites and validated by comparing simulated results to measured data. As in the previous study, the updated model (2012 model) does a poor job of simulating individual storms, but a reasonably good job of simulating seasonal runoff volumes. At three streamflow-gaging stations, the January 1 to June 30 retrospective forecasts of runoff volume for years 2010 and 2011 were within 40 percent of the measured runoff volume for five of the six comparisons, ranging from -39.4 to 60.3 percent difference. A procedure for collecting measured snowpack data and using the data in the watershed model for forecast model runs, based on the Ensemble Streamflow Prediction method, is described, with an example that uses 2004 snow-survey data.

The Voronoi spatio-temporal data structure

NASA Astrophysics Data System (ADS)

Mioc, Darka

2002-04-01

Current GIS models cannot integrate the temporal dimension of spatial data easily. Indeed, current GISs do not support incremental (local) addition and deletion of spatial objects, and they can not support the temporal evolution of spatial data. Spatio-temporal facilities would be very useful in many GIS applications: harvesting and forest planning, cadastre, urban and regional planning, and emergency planning. The spatio-temporal model that can overcome these problems is based on a topological model---the Voronoi data structure. Voronoi diagrams are irregular tessellations of space, that adapt to spatial objects and therefore they are a synthesis of raster and vector spatial data models. The main advantage of the Voronoi data structure is its local and sequential map updates, which allows us to automatically record each event and performed map updates within the system. These map updates are executed through map construction commands that are composed of atomic actions (geometric algorithms for addition, deletion, and motion of spatial objects) on the dynamic Voronoi data structure. The formalization of map commands led to the development of a spatial language comprising a set of atomic operations or constructs on spatial primitives (points and lines), powerful enough to define the complex operations. This resulted in a new formal model for spatio-temporal change representation, where each update is uniquely characterized by the numbers of newly created and inactivated Voronoi regions. This is used for the extension of the model towards the hierarchical Voronoi data structure. In this model, spatio-temporal changes induced by map updates are preserved in a hierarchical data structure that combines events and corresponding changes in topology. This hierarchical Voronoi data structure has an implicit time ordering of events visible through changes in topology, and it is equivalent to an event structure that can support temporal data without precise temporal information. This formal model of spatio-temporal change representation is currently applied to retroactive map updates and visualization of map evolution. It offers new possibilities in the domains of temporal GIS, transaction processing, spatio-temporal queries, spatio-temporal analysis, map animation and map visualization.

Characterization of Oribtal Debris via Hyper-Velocity Ground-Based Tests

NASA Technical Reports Server (NTRS)

Cowardin, H.

2015-01-01

Existing DoD and NASA satellite breakup models are based on a key laboratory-based test, Satellite Orbital debris Characterization Impact Test (SOCIT), which has supported many applications and matched on-orbit events involving older satellite designs reasonably well over the years. In order to update and improve the break-up models and the NASA Size Estimation Model (SEM) for events involving more modern satellite designs, the NASA Orbital Debris Program Office has worked in collaboration with the University of Florida to replicate a hypervelocity impact using a satellite built with modern-day spacecraft materials and construction techniques. The spacecraft, called DebriSat, was intended to be a representative of modern LEO satellites and all major designs decisions were reviewed and approved by subject matter experts at Aerospace Corporation. DebriSat is composed of 7 major subsystems including attitude determination and control system (ADCS), command and data handling (C&DH), electrical power system (EPS), payload, propulsion, telemetry tracking and command (TT&C), and thermal management. To reduce cost, most components are emulated based on existing design of flight hardware and fabricated with the same materials. All fragments down to 2 mm is size will be characterized via material, size, shape, bulk density, and the associated data will be stored in a database for multiple users to access. Laboratory radar and optical measurements will be performed on a subset of fragments to provide a better understanding of the data products from orbital debris acquired from ground-based radars and telescopes. The resulting data analysis from DebriSat will be used to update break-up models and develop the first optical SEM in conjunction with updates into the current NASA SEM. The characterization of the fragmentation will be discussed in the subsequent presentation.

A Probabilistic Approach to Model Update

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Reaves, Mercedes C.; Voracek, David F.

2001-01-01

Finite element models are often developed for load validation, structural certification, response predictions, and to study alternate design concepts. In rare occasions, models developed with a nominal set of parameters agree with experimental data without the need to update parameter values. Today, model updating is generally heuristic and often performed by a skilled analyst with in-depth understanding of the model assumptions. Parameter uncertainties play a key role in understanding the model update problem and therefore probabilistic analysis tools, developed for reliability and risk analysis, may be used to incorporate uncertainty in the analysis. In this work, probability analysis (PA) tools are used to aid the parameter update task using experimental data and some basic knowledge of potential error sources. Discussed here is the first application of PA tools to update parameters of a finite element model for a composite wing structure. Static deflection data at six locations are used to update five parameters. It is shown that while prediction of individual response values may not be matched identically, the system response is significantly improved with moderate changes in parameter values.

Time dependent data, time independent models: challenges of updating Australia's National Seismic Hazard Assessment

NASA Astrophysics Data System (ADS)

Griffin, J.; Clark, D.; Allen, T.; Ghasemi, H.; Leonard, M.

2017-12-01

Standard probabilistic seismic hazard assessment (PSHA) simulates earthquake occurrence as a time-independent process. However paleoseismic studies in slowly deforming regions such as Australia show compelling evidence that large earthquakes on individual faults cluster within active periods, followed by long periods of quiescence. Therefore the instrumental earthquake catalog, which forms the basis of PSHA earthquake recurrence calculations, may only capture the state of the system over the period of the catalog. Together this means that data informing our PSHA may not be truly time-independent. This poses challenges in developing PSHAs for typical design probabilities (such as 10% in 50 years probability of exceedance): Is the present state observed through the instrumental catalog useful for estimating the next 50 years of earthquake hazard? Can paleo-earthquake data, that shows variations in earthquake frequency over time-scales of 10,000s of years or more, be robustly included in such PSHA models? Can a single PSHA logic tree be useful over a range of different probabilities of exceedance? In developing an updated PSHA for Australia, decadal-scale data based on instrumental earthquake catalogs (i.e. alternative area based source models and smoothed seismicity models) is integrated with paleo-earthquake data through inclusion of a fault source model. Use of time-dependent non-homogeneous Poisson models allows earthquake clustering to be modeled on fault sources with sufficient paleo-earthquake data. This study assesses the performance of alternative models by extracting decade-long segments of the instrumental catalog, developing earthquake probability models based on the remaining catalog, and testing performance against the extracted component of the catalog. Although this provides insights into model performance over the short-term, for longer timescales it is recognised that model choice is subject to considerable epistemic uncertainty. Therefore a formal expert elicitation process has been used to assign weights to alternative models for the 2018 update to Australia's national PSHA.

Efficient model learning methods for actor-critic control.

PubMed

Grondman, Ivo; Vaandrager, Maarten; Buşoniu, Lucian; Babuska, Robert; Schuitema, Erik

2012-06-01

We propose two new actor-critic algorithms for reinforcement learning. Both algorithms use local linear regression (LLR) to learn approximations of the functions involved. A crucial feature of the algorithms is that they also learn a process model, and this, in combination with LLR, provides an efficient policy update for faster learning. The first algorithm uses a novel model-based update rule for the actor parameters. The second algorithm does not use an explicit actor but learns a reference model which represents a desired behavior, from which desired control actions can be calculated using the inverse of the learned process model. The two novel methods and a standard actor-critic algorithm are applied to the pendulum swing-up problem, in which the novel methods achieve faster learning than the standard algorithm.

Publishing web-based guidelines using interactive decision models.

PubMed

Sanders, G D; Nease, R F; Owens, D K

2001-05-01

Commonly used methods for guideline development and dissemination do not enable developers to tailor guidelines systematically to specific patient populations and update guidelines easily. We developed a web-based system, ALCHEMIST, that uses decision models and automatically creates evidence-based guidelines that can be disseminated, tailored and updated over the web. Our objective was to demonstrate the use of this system with clinical scenarios that provide challenges for guideline development. We used the ALCHEMIST system to develop guidelines for three clinical scenarios: (1) Chlamydia screening for adolescent women, (2) antiarrhythmic therapy for the prevention of sudden cardiac death; and (3) genetic testing for the BRCA breast-cancer mutation. ALCHEMIST uses information extracted directly from the decision model, combined with the additional information from the author of the decision model, to generate global guidelines. ALCHEMIST generated electronic web-based guidelines for each of the three scenarios. Using ALCHEMIST, we demonstrate that tailoring a guideline for a population at high-risk for Chlamydia changes the recommended policy for control of Chlamydia from contact tracing of reported cases to a population-based screening programme. We used ALCHEMIST to incorporate new evidence about the effectiveness of implantable cardioverter defibrillators (ICD) and demonstrate that the cost-effectiveness of use of ICDs improves from $74 400 per quality-adjusted life year (QALY) gained to $34 500 per QALY gained. Finally, we demonstrate how a clinician could use ALCHEMIST to incorporate a woman's utilities for relevant health states and thereby develop patient-specific recommendations for BRCA testing; the patient-specific recommendation improved quality-adjusted life expectancy by 37 days. The ALCHEMIST system enables guideline developers to publish both a guideline and an interactive decision model on the web. This web-based tool enables guideline developers to tailor guidelines systematically, to update guidelines easily, and to make the underlying evidence and analysis transparent for users.

Modeling and performance analysis of movement-based group location management using RFID sensing in public transportation systems.

PubMed

Chung, Yun Won

2012-11-22

Location management, which consists of location registration and paging, is essential to provide mobile communication services to mobile stations (MSs). Since MSs riding on a public transportation system (TS) generates significant location registration signaling loads simultaneously when a TS with riding MSs moves between location areas (LAs), group location management was proposed. Under the group location management, an MS performs group registration when it gets on a TS and performs group deregistration when it gets off a TS. Then, only a TS updates its current location when it changes LA, on behalf of all riding MSs. In this paper, movement-based group location management using radio frequency identification (RFID) is proposed, where the MS's getting on and getting off behaviors are detected using RFID and only location update of a TS is carried out if the number of crossed cells from the last updated cell exceeds a predefined movement threshold, on behalf of all riding MSs. Then, we develop an analytical model for the performance analysis of the movement-based group location management and analyze the effects of various parameters on the performance. The results show that the movement-based group location management has reduced signaling cost compared with movement-based individual location management, and optimal performance can be achieved by choosing appropriate movement threshold values.

Modeling and Performance Analysis of Movement-Based Group Location Management Using RFID Sensing in Public Transportation Systems

PubMed Central

Chung, Yun Won

2012-01-01

Location management, which consists of location registration and paging, is essential to provide mobile communication services to mobile stations (MSs). Since MSs riding on a public transportation system (TS) generates significant location registration signaling loads simultaneously when a TS with riding MSs moves between location areas (LAs), group location management was proposed. Under the group location management, an MS performs group registration when it gets on a TS and performs group deregistration when it gets off a TS. Then, only a TS updates its current location when it changes LA, on behalf of all riding MSs. In this paper, movement-based group location management using radio frequency identification (RFID) is proposed, where the MS’s getting on and getting off behaviors are detected using RFID and only location update of a TS is carried out if the number of crossed cells from the last updated cell exceeds a predefined movement threshold, on behalf of all riding MSs. Then, we develop an analytical model for the performance analysis of the movement-based group location management and analyze the effects of various parameters on the performance. The results show that the movement-based group location management has reduced signaling cost compared with movement-based individual location management, and optimal performance can be achieved by choosing appropriate movement threshold values. PMID:23443368

Frequency-domain full-waveform inversion with non-linear descent directions

NASA Astrophysics Data System (ADS)

Geng, Yu; Pan, Wenyong; Innanen, Kristopher A.

2018-05-01

Full-waveform inversion (FWI) is a highly non-linear inverse problem, normally solved iteratively, with each iteration involving an update constructed through linear operations on the residuals. Incorporating a flexible degree of non-linearity within each update may have important consequences for convergence rates, determination of low model wavenumbers and discrimination of parameters. We examine one approach for doing so, wherein higher order scattering terms are included within the sensitivity kernel during the construction of the descent direction, adjusting it away from that of the standard Gauss-Newton approach. These scattering terms are naturally admitted when we construct the sensitivity kernel by varying not the current but the to-be-updated model at each iteration. Linear and/or non-linear inverse scattering methodologies allow these additional sensitivity contributions to be computed from the current data residuals within any given update. We show that in the presence of pre-critical reflection data, the error in a second-order non-linear update to a background of s0 is, in our scheme, proportional to at most (Δs/s0)3 in the actual parameter jump Δs causing the reflection. In contrast, the error in a standard Gauss-Newton FWI update is proportional to (Δs/s0)2. For numerical implementation of more complex cases, we introduce a non-linear frequency-domain scheme, with an inner and an outer loop. A perturbation is determined from the data residuals within the inner loop, and a descent direction based on the resulting non-linear sensitivity kernel is computed in the outer loop. We examine the response of this non-linear FWI using acoustic single-parameter synthetics derived from the Marmousi model. The inverted results vary depending on data frequency ranges and initial models, but we conclude that the non-linear FWI has the capability to generate high-resolution model estimates in both shallow and deep regions, and to converge rapidly, relative to a benchmark FWI approach involving the standard gradient.

Adaptive classifier for steel strip surface defects

NASA Astrophysics Data System (ADS)

Jiang, Mingming; Li, Guangyao; Xie, Li; Xiao, Mang; Yi, Li

2017-01-01

Surface defects detection system has been receiving increased attention as its precision, speed and less cost. One of the most challenges is reacting to accuracy deterioration with time as aged equipment and changed processes. These variables will make a tiny change to the real world model but a big impact on the classification result. In this paper, we propose a new adaptive classifier with a Bayes kernel (BYEC) which update the model with small sample to it adaptive for accuracy deterioration. Firstly, abundant features were introduced to cover lots of information about the defects. Secondly, we constructed a series of SVMs with the random subspace of the features. Then, a Bayes classifier was trained as an evolutionary kernel to fuse the results from base SVMs. Finally, we proposed the method to update the Bayes evolutionary kernel. The proposed algorithm is experimentally compared with different algorithms, experimental results demonstrate that the proposed method can be updated with small sample and fit the changed model well. Robustness, low requirement for samples and adaptive is presented in the experiment.

Integrating recent land cover mapping efforts to update the National Gap Analysis Program's species habitat map

USGS Publications Warehouse

McKerrow, Alexa; Davidson, A.; Earnhardt, Todd; Benson, Abigail L.; Toth, Charles; Holm, Thomas; Jutz, Boris

2014-01-01

Over the past decade, great progress has been made to develop national extent land cover mapping products to address natural resource issues. One of the core products of the GAP Program is range-wide species distribution models for nearly 2000 terrestrial vertebrate species in the U.S. We rely on deductive modeling of habitat affinities using these products to create models of habitat availability. That approach requires that we have a thematically rich and ecologically meaningful map legend to support the modeling effort. In this work, we tested the integration of the Multi-Resolution Landscape Characterization Consortium's National Land Cover Database 2011 and LANDFIRE's Disturbance Products to update the 2001 National GAP Vegetation Dataset to reflect 2011 conditions. The revised product can then be used to update the species models. We tested the update approach in three geographic areas (Northeast, Southeast, and Interior Northwest). We used the NLCD product to identify areas where the cover type mapped in 2011 was different from what was in the 2001 land cover map. We used Google Earth and ArcGIS base maps as reference imagery in order to label areas identified as "changed" to the appropriate class from our map legend. Areas mapped as urban or water in the 2011 NLCD map that were mapped differently in the 2001 GAP map were accepted without further validation and recoded to the corresponding GAP class. We used LANDFIRE's Disturbance products to identify changes that are the result of recent disturbance and to inform the reassignment of areas to their updated thematic label. We ran species habitat models for three species including Lewis's Woodpecker (Melanerpes lewis) and the White-tailed Jack Rabbit (Lepus townsendii) and Brown Headed nuthatch (Sitta pusilla). For each of three vertebrate species we found important differences in the amount and location of suitable habitat between the 2001 and 2011 habitat maps. Specifically, Brown headed nuthatch habitat in 2011 was −14% of the 2001 modeled habitat, whereas Lewis's Woodpecker increased by 4%. The white-tailed jack rabbit (Lepus townsendii) had a net change of −1% (11% decline, 10% gain). For that species we found the updates related to opening of forest due to burning and regenerating shrubs following harvest to be the locally important main transitions. In the Southeast updates related to timber management and urbanization are locally important.

A Monte Carlo simulation based inverse propagation method for stochastic model updating

NASA Astrophysics Data System (ADS)

Bao, Nuo; Wang, Chunjie

2015-08-01

This paper presents an efficient stochastic model updating method based on statistical theory. Significant parameters have been selected implementing the F-test evaluation and design of experiments, and then the incomplete fourth-order polynomial response surface model (RSM) has been developed. Exploiting of the RSM combined with Monte Carlo simulation (MCS), reduces the calculation amount and the rapid random sampling becomes possible. The inverse uncertainty propagation is given by the equally weighted sum of mean and covariance matrix objective functions. The mean and covariance of parameters are estimated synchronously by minimizing the weighted objective function through hybrid of particle-swarm and Nelder-Mead simplex optimization method, thus the better correlation between simulation and test is achieved. Numerical examples of a three degree-of-freedom mass-spring system under different conditions and GARTEUR assembly structure validated the feasibility and effectiveness of the proposed method.

On the implicit density based OpenFOAM solver for turbulent compressible flows

NASA Astrophysics Data System (ADS)

Fürst, Jiří

The contribution deals with the development of coupled implicit density based solver for compressible flows in the framework of open source package OpenFOAM. However the standard distribution of OpenFOAM contains several ready-made segregated solvers for compressible flows, the performance of those solvers is rather week in the case of transonic flows. Therefore we extend the work of Shen [15] and we develop an implicit semi-coupled solver. The main flow field variables are updated using lower-upper symmetric Gauss-Seidel method (LU-SGS) whereas the turbulence model variables are updated using implicit Euler method.

Update of aircraft profile data for the Integrated Noise Model computer program, vol. 3 : appendix B aircraft performance coefficients

DOT National Transportation Integrated Search

1992-03-01

This report provides aircraft takeoff and landing profiles, : aircraft aerodynamic performance coefficients and engine : performance coefficients for the aircraft data base : (Database 9) in the Integrated Noise Model (INM) computer : program. Flight...

Development of a Dynamic Traffic Assignment Model for Northern Nevada

DOT National Transportation Integrated Search

2014-06-01

The objective of this research is to build and calibrate a DTA model for Northern Nevada (RenoSparks Area) based on the network profile and travel demand information updated to date. The critical procedures include development of consistent and readi...

Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

PubMed Central

2012-01-01

Background Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model’s predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Conclusions Yeast 5 expands and refines the computational reconstruction of yeast metabolism and improves the predictive accuracy of a stoichiometrically constrained yeast metabolic model. It differs from previous reconstructions and models by emphasizing the distinction between the yeast metabolic reconstruction and the stoichiometrically constrained model, and makes both available as Additional file 4 and Additional file 5 and at http://yeast.sf.net/ as separate systems biology markup language (SBML) files. Through this separation, we intend to make the modeling process more accessible, explicit, transparent, and reproducible. PMID:22663945

Predictive spatial modeling of narcotic crop growth patterns

USGS Publications Warehouse

Waltz, Frederick A.; Moore, D.G.

1986-01-01

Spatial models for predicting the geographic distribution of marijuana crops have been developed and are being evaluated for use in law enforcement programs. The models are based on growing condition preferences and on psychological inferences regarding grower behavior. Experiences of local law officials were used to derive the initial model, which was updated and improved as data from crop finds were archived and statistically analyzed. The predictive models are changed as crop locations are moved in response to the pressures of law enforcement. The models use spatial data in a raster geographic information system. The spatial data are derived from the U.S. Geological Survey's US GeoData, standard 7.5-minute topographic quadrangle maps, interpretations of aerial photographs, and thematic maps. Updating of cultural patterns, canopy closure, and other dynamic features is conducted through interpretation of aerial photographs registered to the 7.5-minute quadrangle base. The model is used to numerically weight various data layers that have been processed using spread functions, edge definition, and categorization. The building of the spatial data base, model development, model application, product generation, and use are collectively referred to as the Area Reduction Program (ARP). The goal of ARP is to provide law enforcement officials with tactical maps that show the most likely locations for narcotic crops.

Revised mineral dust emissions in the atmospheric chemistry-climate model EMAC (MESSy 2.52 DU_Astitha1 KKDU2017 patch)

NASA Astrophysics Data System (ADS)

Klingmüller, Klaus; Metzger, Swen; Abdelkader, Mohamed; Karydis, Vlassis A.; Stenchikov, Georgiy L.; Pozzer, Andrea; Lelieveld, Jos

2018-03-01

To improve the aeolian dust budget calculations with the global ECHAM/MESSy atmospheric chemistry-climate model (EMAC), which combines the Modular Earth Submodel System (MESSy) with the ECMWF/Hamburg (ECHAM) climate model developed at the Max Planck Institute for Meteorology in Hamburg based on a weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF), we have implemented new input data and updates of the emission scheme.The data set comprises land cover classification, vegetation, clay fraction and topography. It is based on up-to-date observations, which are crucial to account for the rapid changes of deserts and semi-arid regions in recent decades. The new Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover and vegetation data are time dependent, and the effect of long-term trends and variability of the relevant parameters is therefore considered by the emission scheme. All input data have a spatial resolution of at least 0.1° compared to 1° in the previous version, equipping the model for high-resolution simulations.We validate the updates by comparing the aerosol optical depth (AOD) at 550 nm wavelength from a 1-year simulation at T106 (about 1.1°) resolution with Aerosol Robotic Network (AERONET) and MODIS observations, the 10 µm dust AOD (DAOD) with Infrared Atmospheric Sounding Interferometer (IASI) retrievals, and dust concentration and deposition results with observations from the Aerosol Comparisons between Observations and Models (AeroCom) dust benchmark data set. The update significantly improves agreement with the observations and is therefore recommended to be used in future simulations.

Results of investigations conducted in the LaRC 8-foot transonic pressure tunnel using the 0.010-scale 72-OTS model of the space shuttle integrated vehicle (IA93)

NASA Technical Reports Server (NTRS)

Nichols, M. E.

1976-01-01

Test procedures, history, and data from the wind tunnel test are presented. Aero-loads were investigated on the updated configuration-5 space shuttle launch vehicle at Mach numbers from 0.600 to 1.205. Six-component vehicle forces and moments, base and sting-cavity pressures, elevon hinge moments, wing-root bending and torsion moments, and normal shear force data were obtained. Full simulation of updated vehicle protuberances and attach hardware was employed. Various elevon deflection angles were tested with two different forward orbiter-to-external-tank attach-strut configurations. The entire model was supported by means of a balance mounted in the orbiter through its base and suspended from a sting.

Results of investigations conducted in the LaRC 4-foot unitary plan wind tunnel leg no. 1 using the 0.010-scale 72-OTS model of the space shuttle integrated vehicle (IA94A)

NASA Technical Reports Server (NTRS)

Nichols, M. E.

1976-01-01

Aero-loads investigations were conducted on the updated configuration-5 space shuttle launch vehicle at Mach numbers 2.50, 3.50, and 4.50. Six-component vehicle forces and moments, base and sting-cavity pressures, elevon hinge moments, wing-root bending and torsion moments, and normal shear force data were obtained. Full simulation of updated vehicle protuberances and attach hardware was employed. Various elevon deflection angles were tested, with two different forward orbiter-to-external-tank attach-strut configurations. The entire vehicle model 72-OTS was supported by means of a balance mounted in the orbiter through its base and suspended from an appropriate sting for the specific tunnel.

Inquiry-Based Learning of Molecular Phylogenetics

ERIC Educational Resources Information Center

Campo, Daniel; Garcia-Vazquez, Eva

2008-01-01

Reconstructing phylogenies from nucleotide sequences is a challenge for students because it strongly depends on evolutionary models and computer tools that are frequently updated. We present here an inquiry-based course aimed at learning how to trace a phylogeny based on sequences existing in public databases. Computer tools are freely available…

A model of professional competences in mathematics to update mathematical and didactic knowledge of teachers

NASA Astrophysics Data System (ADS)

Díaz, Verónica; Poblete, Alvaro

2017-07-01

This paper describes part of a research and development project carried out in public elementary schools. Its objective was to update the mathematical and didactic knowledge of teachers in two consecutive levels in urban and rural public schools of Region de Los Lagos and Region de Los Rios of southern Chile. To that effect, and by means of an advanced training project based on a professional competences model, didactic interventions based on types of problems and types of mathematical competences with analysis of contents and learning assessment were designed. The teachers' competence regarding the didactic strategy used and its results, as well as the students' learning achievements are specified. The project made possible to validate a strategy of lifelong improvement in mathematics, based on the professional competences of teachers and their didactic transposition in the classroom, as an alternative to consolidate learning in areas considered vulnerable in two regions of the country.

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization.

PubMed

Sun, Yanfeng; Gao, Junbin; Hong, Xia; Mishra, Bamdev; Yin, Baocai

2016-03-01

Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.

Model-Based Compositional Reasoning for Complex Systems of Systems (SoS)

DTIC Science & Technology

2016-11-01

more structured approach for finding flaws /weaknesses in the systems . As the system is updated, either in response to a found flaw or new...AFRL-RQ-WP-TR-2016-0172 MODEL-BASED COMPOSITIONAL REASONING FOR COMPLEX SYSTEMS OF SYSTEMS (SoS) M. Anthony Aiello, Benjamin D. Rodes...LABORATORY AEROSPACE SYSTEMS DIRECTORATE WRIGHT-PATTERSON AIR FORCE BASE, OH 45433-7541 AIR FORCE MATERIEL COMMAND UNITED STATES AIR FORCE NOTICE

The Mixed Instrumental Controller: Using Value of Information to Combine Habitual Choice and Mental Simulation

PubMed Central

Pezzulo, Giovanni; Rigoli, Francesco; Chersi, Fabian

2013-01-01

Instrumental behavior depends on both goal-directed and habitual mechanisms of choice. Normative views cast these mechanisms in terms of model-free and model-based methods of reinforcement learning, respectively. An influential proposal hypothesizes that model-free and model-based mechanisms coexist and compete in the brain according to their relative uncertainty. In this paper we propose a novel view in which a single Mixed Instrumental Controller produces both goal-directed and habitual behavior by flexibly balancing and combining model-based and model-free computations. The Mixed Instrumental Controller performs a cost-benefits analysis to decide whether to chose an action immediately based on the available “cached” value of actions (linked to model-free mechanisms) or to improve value estimation by mentally simulating the expected outcome values (linked to model-based mechanisms). Since mental simulation entails cognitive effort and increases the reward delay, it is activated only when the associated “Value of Information” exceeds its costs. The model proposes a method to compute the Value of Information, based on the uncertainty of action values and on the distance of alternative cached action values. Overall, the model by default chooses on the basis of lighter model-free estimates, and integrates them with costly model-based predictions only when useful. Mental simulation uses a sampling method to produce reward expectancies, which are used to update the cached value of one or more actions; in turn, this updated value is used for the choice. The key predictions of the model are tested in different settings of a double T-maze scenario. Results are discussed in relation with neurobiological evidence on the hippocampus – ventral striatum circuit in rodents, which has been linked to goal-directed spatial navigation. PMID:23459512

The mixed instrumental controller: using value of information to combine habitual choice and mental simulation.

PubMed

Pezzulo, Giovanni; Rigoli, Francesco; Chersi, Fabian

2013-01-01

Instrumental behavior depends on both goal-directed and habitual mechanisms of choice. Normative views cast these mechanisms in terms of model-free and model-based methods of reinforcement learning, respectively. An influential proposal hypothesizes that model-free and model-based mechanisms coexist and compete in the brain according to their relative uncertainty. In this paper we propose a novel view in which a single Mixed Instrumental Controller produces both goal-directed and habitual behavior by flexibly balancing and combining model-based and model-free computations. The Mixed Instrumental Controller performs a cost-benefits analysis to decide whether to chose an action immediately based on the available "cached" value of actions (linked to model-free mechanisms) or to improve value estimation by mentally simulating the expected outcome values (linked to model-based mechanisms). Since mental simulation entails cognitive effort and increases the reward delay, it is activated only when the associated "Value of Information" exceeds its costs. The model proposes a method to compute the Value of Information, based on the uncertainty of action values and on the distance of alternative cached action values. Overall, the model by default chooses on the basis of lighter model-free estimates, and integrates them with costly model-based predictions only when useful. Mental simulation uses a sampling method to produce reward expectancies, which are used to update the cached value of one or more actions; in turn, this updated value is used for the choice. The key predictions of the model are tested in different settings of a double T-maze scenario. Results are discussed in relation with neurobiological evidence on the hippocampus - ventral striatum circuit in rodents, which has been linked to goal-directed spatial navigation.

Medicare and Medicaid Programs; CY 2017 Home Health Prospective Payment System Rate Update; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements. Final rule.

PubMed

2016-11-03

This final rule updates the Home Health Prospective Payment System (HH PPS) payment rates, including the national, standardized 60-day episode payment rates, the national per-visit rates, and the non-routine medical supply (NRS) conversion factor; effective for home health episodes of care ending on or after January 1, 2017. This rule also: Implements the last year of the 4-year phase-in of the rebasing adjustments to the HH PPS payment rates; updates the HH PPS case-mix weights using the most current, complete data available at the time of rulemaking; implements the 2nd-year of a 3-year phase-in of a reduction to the national, standardized 60-day episode payment to account for estimated case-mix growth unrelated to increases in patient acuity (that is, nominal case-mix growth) between CY 2012 and CY 2014; finalizes changes to the methodology used to calculate payments made under the HH PPS for high-cost "outlier" episodes of care; implements changes in payment for furnishing Negative Pressure Wound Therapy (NPWT) using a disposable device for patients under a home health plan of care; discusses our efforts to monitor the potential impacts of the rebasing adjustments; includes an update on subsequent research and analysis as a result of the findings from the home health study; and finalizes changes to the Home Health Value-Based Purchasing (HHVBP) Model, which was implemented on January 1, 2016; and updates to the Home Health Quality Reporting Program (HH QRP).

Update to the Ground-Water Withdrawals Database for the Death Valley Regional Ground-Water Flow System, Nevada and California, 1913-2003

USGS Publications Warehouse

Moreo, Michael T.; Justet, Leigh

2008-01-01

Ground-water withdrawal estimates from 1913 through 2003 for the Death Valley regional ground-water flow system are compiled in an electronic database to support a regional, three-dimensional, transient ground-water flow model. This database updates a previously published database that compiled estimates of ground-water withdrawals for 1913-1998. The same methodology is used to construct each database. Primary differences between the 2 databases are an additional 5 years of ground-water withdrawal data, well locations in the updated database are restricted to Death Valley regional ground-water flow system model boundary, and application rates are from 0 to 1.5 feet per year lower than original estimates. The lower application rates result from revised estimates of crop consumptive use, which are based on updated estimates of potential evapotranspiration. In 2003, about 55,700 acre-feet of ground water was pumped in the DVRFS, of which 69 percent was used for irrigation, 13 percent for domestic, and 18 percent for public supply, commercial, and mining activities.

The LANDFIRE Refresh strategy: updating the national dataset

USGS Publications Warehouse

Nelson, Kurtis J.; Connot, Joel A.; Peterson, Birgit E.; Martin, Charley

2013-01-01

The LANDFIRE Program provides comprehensive vegetation and fuel datasets for the entire United States. As with many large-scale ecological datasets, vegetation and landscape conditions must be updated periodically to account for disturbances, growth, and natural succession. The LANDFIRE Refresh effort was the first attempt to consistently update these products nationwide. It incorporated a combination of specific systematic improvements to the original LANDFIRE National data, remote sensing based disturbance detection methods, field collected disturbance information, vegetation growth and succession modeling, and vegetation transition processes. This resulted in the creation of two complete datasets for all 50 states: LANDFIRE Refresh 2001, which includes the systematic improvements, and LANDFIRE Refresh 2008, which includes the disturbance and succession updates to the vegetation and fuel data. The new datasets are comparable for studying landscape changes in vegetation type and structure over a decadal period, and provide the most recent characterization of fuel conditions across the country. The applicability of the new layers is discussed and the effects of using the new fuel datasets are demonstrated through a fire behavior modeling exercise using the 2011 Wallow Fire in eastern Arizona as an example.

Importance of land use update during the calibration period and simulation of water balance response to land use change in the upper Rio das Mortes Catchment (Cerrado Biome, Central-Western Brazil)

NASA Astrophysics Data System (ADS)

Lamparter, Gabriele; Kovacs, Kristof; Nobrega, Rodolfo; Gerold, Gerhard

2015-04-01

Changes in the hydrological balance and following degradation of the water ecosystem services due to large scale land use changes are reported from agricultural frontiers all over the world. Traditionally, hydrological models including vegetation and land use as a part of the hydrological cycle use a fixed distribution of land use for the calibration period. We believe that a meaningful calibration - especially when investigating the effects of land use change on hydrology - demands the inclusion of land use change during the calibration period into the calibration procedure. The SWAT (Soil and Water Assessment Tool) model is a process-based, semi-distributed model calculating the different components of the water balance. The model bases on the definition of hydrological response units (HRUs) which are based on soil, vegetation and slope distribution. It specifically emphasises the role of land use and land management on the water balance. The Central-Western region of Brazil is one of the leading agricultural frontiers, which experienced rapid and radical deforestation and agricultural intensification in the last 40 years (from natural Cerrado savannah to cattle grazing to intensive corn and soya cropland). The land use history of the upper Rio das Mortes catchment (with 17500 km²) is reasonably well documented since the 1970th. At the same time there are almost continuous climate and runoff data available for the period between 1988 and 2011. Therefore, the work presented here shows the model calibration and validation of the SWAT model with the land use update function for three different periods (1988 to 1998, 1998 to 2007 and 2007 to 2011) in comparison with the same calibration periods using a steady state land use distribution. The use of the land use update function allows a clearer identification which changes in the discharge are due to climatic variability and which are due to changes in the vegetation cover. With land use update included into the calibration procedure, the impact of land use change on overall modelled runoff was more pronounced. For example, the accordance of modelled peak discharge improved for the period from 1988 to 1998 (with a decrease of primary Cerrado from 60 to 30 %) with the use of the land use update function compared to the steady state calibration. The effect for the following two periods 1998 to 2007 and 2007 to 2011 (with a decrease of primary Cerrado from 30 to 24 % and 24 to 19 % respectively) show only a small improvement of the model fit.

BehavePlus fire modeling system, version 5.0: Variables

Treesearch

Patricia L. Andrews

2009-01-01

This publication has been revised to reflect updates to version 4.0 of the BehavePlus software. It was originally published as the BehavePlus fire modeling system, version 4.0: Variables in July, 2008.The BehavePlus fire modeling system is a computer program based on mathematical models that describe wildland fire behavior and effects and the...

A Geo-referenced 3D model of the Juan de Fuca Slab and associated seismicity

USGS Publications Warehouse

Blair, J.L.; McCrory, P.A.; Oppenheimer, D.H.; Waldhauser, F.

2011-01-01

We present a Geographic Information System (GIS) of a new 3-dimensional (3D) model of the subducted Juan de Fuca Plate beneath western North America and associated seismicity of the Cascadia subduction system. The geo-referenced 3D model was constructed from weighted control points that integrate depth information from hypocenter locations and regional seismic velocity studies. We used the 3D model to differentiate earthquakes that occur above the Juan de Fuca Plate surface from earthquakes that occur below the plate surface. This GIS project of the Cascadia subduction system supersedes the one previously published by McCrory and others (2006). Our new slab model updates the model with new constraints. The most significant updates to the model include: (1) weighted control points to incorporate spatial uncertainty, (2) an additional gridded slab surface based on the Generic Mapping Tools (GMT) Surface program which constructs surfaces based on splines in tension (see expanded description below), (3) double-differenced hypocenter locations in northern California to better constrain slab location there, and (4) revised slab shape based on new hypocenter profiles that incorporate routine depth uncertainties as well as data from new seismic-reflection and seismic-refraction studies. We also provide a 3D fly-through animation of the model for use as a visualization tool.

OMI Global Tropospheric Bromine Oxide (BrO) Column Densities: Algorithm, Retrieval and Initial Validation

NASA Astrophysics Data System (ADS)

Suleiman, R. M.; Chance, K.; Liu, X.; Kurosu, T. P.; Gonzalez Abad, G.

2014-12-01

We present and discuss a detailed description of the retrieval algorithms for the OMI BrO product. The BrO algorithms are based on direct fitting of radiances from 319.0-347.5 nm. Radiances are modeled from the solar irradiance, attenuated and adjusted by contributions from the target gas and interfering gases, rotational Raman scattering, undersampling, additive and multiplicative closure polynomials and a common mode spectrum. The version of the algorithm used for both BrO includes relevant changes with respect to the operational code, including the fit of the O2-O2 collisional complex, updates in the high resolution solar reference spectrum, updates in spectroscopy, an updated Air Mass Factor (AMF) calculation scheme, and the inclusion of scattering weights and vertical profiles in the level 2 products. Updates to the algorithms include accurate scattering weights and air mass factor calculations, scattering weights and profiles in outputs and available cross sections. We include retrieval parameter and window optimization to reduce the interference from O3, HCHO, O2-O2, SO2, improve fitting accuracy and uncertainty, reduce striping, and improve the long-term stability. We validate OMI BrO with ground-based measurements from Harestua and with chemical transport model simulations. We analyze the global distribution and seasonal variation of BrO and investigate BrO emissions from volcanoes and salt lakes.

Model documentation for relations between continuous real-time and discrete water-quality constituents in Cheney Reservoir near Cheney, Kansas, 2001--2009

USGS Publications Warehouse

Stone, Mandy L.; Graham, Jennifer L.; Gatotho, Jackline W.

2013-01-01

Cheney Reservoir, located in south-central Kansas, is one of the primary water supplies for the city of Wichita, Kansas. The U.S. Geological Survey has operated a continuous real-time water-quality monitoring station in Cheney Reservoir since 2001; continuously measured physicochemical properties include specific conductance, pH, water temperature, dissolved oxygen, turbidity, fluorescence (wavelength range 650 to 700 nanometers; estimate of total chlorophyll), and reservoir elevation. Discrete water-quality samples were collected during 2001 through 2009 and analyzed for sediment, nutrients, taste-and-odor compounds, cyanotoxins, phytoplankton community composition, actinomycetes bacteria, and other water-quality measures. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physicochemical properties to compute concentrations of constituents that are not easily measured in real time. The water-quality information in this report is important to the city of Wichita because it allows quantification and characterization of potential constituents of concern in Cheney Reservoir. This report updates linear regression models published in 2006 that were based on data collected during 2001 through 2003. The update uses discrete and continuous data collected during May 2001 through December 2009. Updated models to compute dissolved solids, sodium, chloride, and suspended solids were similar to previously published models. However, several other updated models changed substantially from previously published models. In addition to updating relations that were previously developed, models also were developed for four new constituents, including magnesium, dissolved phosphorus, actinomycetes bacteria, and the cyanotoxin microcystin. In addition, a conversion factor of 0.74 was established to convert the Yellow Springs Instruments (YSI) model 6026 turbidity sensor measurements to the newer YSI model 6136 sensor at the Cheney Reservoir site. Because a high percentage of geosmin and microcystin data were below analytical detection thresholds (censored data), multiple logistic regression was used to develop models that best explained the probability of geosmin and microcystin concentrations exceeding relevant thresholds. The geosmin and microcystin models are particularly important because geosmin is a taste-and-odor compound and microcystin is a cyanotoxin.

Model-data assimilation of multiple phenological observations to constrain and predict leaf area index.

PubMed

Viskari, Toni; Hardiman, Brady; Desai, Ankur R; Dietze, Michael C

2015-03-01

Our limited ability to accurately simulate leaf phenology is a leading source of uncertainty in models of ecosystem carbon cycling. We evaluate if continuously updating canopy state variables with observations is beneficial for predicting phenological events. We employed ensemble adjustment Kalman filter (EAKF) to update predictions of leaf area index (LAI) and leaf extension using tower-based photosynthetically active radiation (PAR) and moderate resolution imaging spectrometer (MODIS) data for 2002-2005 at Willow Creek, Wisconsin, USA, a mature, even-aged, northern hardwood, deciduous forest. The ecosystem demography model version 2 (ED2) was used as the prediction model, forced by offline climate data. EAKF successfully incorporated information from both the observations and model predictions weighted by their respective uncertainties. The resulting. estimate reproduced the observed leaf phenological cycle in the spring and the fall better than a parametric model prediction. These results indicate that during spring the observations contribute most in determining the correct bud-burst date, after which the model performs well, but accurately modeling fall leaf senesce requires continuous model updating from observations. While the predicted net ecosystem exchange (NEE) of CO2 precedes tower observations and unassimilated model predictions in the spring, overall the prediction follows observed NEE better than the model alone. Our results show state data assimilation successfully simulates the evolution of plant leaf phenology and improves model predictions of forest NEE.

SHINE Virtual Machine Model for In-flight Updates of Critical Mission Software

NASA Technical Reports Server (NTRS)

Plesea, Lucian

2008-01-01

This software is a new target for the Spacecraft Health Inference Engine (SHINE) knowledge base that compiles a knowledge base to a language called Tiny C - an interpreted version of C that can be embedded on flight processors. This new target allows portions of a running SHINE knowledge base to be updated on a "live" system without needing to halt and restart the containing SHINE application. This enhancement will directly provide this capability without the risk of software validation problems and can also enable complete integration of BEAM and SHINE into a single application. This innovation enables SHINE deployment in domains where autonomy is used during flight-critical applications that require updates. This capability eliminates the need for halting the application and performing potentially serious total system uploads before resuming the application with the loss of system integrity. This software enables additional applications at JPL (microsensors, embedded mission hardware) and increases the marketability of these applications outside of JPL.

Medicare and Medicaid Programs; CY 2018 Home Health Prospective Payment System Rate Update and CY 2019 Case-Mix Adjustment Methodology Refinements; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements. Final rule.

PubMed

2017-11-07

This final rule updates the home health prospective payment system (HH PPS) payment rates, including the national, standardized 60-day episode payment rates, the national per-visit rates, and the non-routine medical supply (NRS) conversion factor, effective for home health episodes of care ending on or after January 1, 2018. This rule also: Updates the HH PPS case-mix weights using the most current, complete data available at the time of rulemaking; implements the third year of a 3-year phase-in of a reduction to the national, standardized 60-day episode payment to account for estimated case-mix growth unrelated to increases in patient acuity (that is, nominal case-mix growth) between calendar year (CY) 2012 and CY 2014; and discusses our efforts to monitor the potential impacts of the rebasing adjustments that were implemented in CY 2014 through CY 2017. In addition, this rule finalizes changes to the Home Health Value-Based Purchasing (HHVBP) Model and to the Home Health Quality Reporting Program (HH QRP). We are not finalizing the implementation of the Home Health Groupings Model (HHGM) in this final rule.

Finite element model updating of a prestressed concrete box girder bridge using subproblem approximation

NASA Astrophysics Data System (ADS)

Chen, G. W.; Omenzetter, P.

2016-04-01

This paper presents the implementation of an updating procedure for the finite element model (FEM) of a prestressed concrete continuous box-girder highway off-ramp bridge. Ambient vibration testing was conducted to excite the bridge, assisted by linear chirp sweepings induced by two small electrodynamic shakes deployed to enhance the excitation levels, since the bridge was closed to traffic. The data-driven stochastic subspace identification method was executed to recover the modal properties from measurement data. An initial FEM was developed and correlation between the experimental modal results and their analytical counterparts was studied. Modelling of the pier and abutment bearings was carefully adjusted to reflect the real operational conditions of the bridge. The subproblem approximation method was subsequently utilized to automatically update the FEM. For this purpose, the influences of bearing stiffness, and mass density and Young's modulus of materials were examined as uncertain parameters using sensitivity analysis. The updating objective function was defined based on a summation of squared values of relative errors of natural frequencies between the FEM and experimentation. All the identified modes were used as the target responses with the purpose of putting more constrains for the optimization process and decreasing the number of potentially feasible combinations for parameter changes. The updated FEM of the bridge was able to produce sufficient improvements in natural frequencies in most modes of interest, and can serve for a more precise dynamic response prediction or future investigation of the bridge health.

Updating Sea Spray Aerosol Emissions in the Community Multiscale Air Quality Model

NASA Astrophysics Data System (ADS)

Gantt, B.; Bash, J. O.; Kelly, J.

2014-12-01

Sea spray aerosols (SSA) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. In this study, the Community Multiscale Air Quality (CMAQ) model is updated to enhance fine mode SSA emissions, include sea surface temperature (SST) dependency, and revise surf zone emissions. Based on evaluation with several regional and national observational datasets in the continental U.S., the updated emissions generally improve surface concentrations predictions of primary aerosols composed of sea-salt and secondary aerosols affected by sea-salt chemistry in coastal and near-coastal sites. Specifically, the updated emissions lead to better predictions of the magnitude and coastal-to-inland gradient of sodium, chloride, and nitrate concentrations at Bay Regional Atmospheric Chemistry Experiment (BRACE) sites near Tampa, FL. Including SST-dependency to the SSA emission parameterization leads to increased sodium concentrations in the southeast U.S. and decreased concentrations along the Pacific coast and northeastern U.S., bringing predictions into closer agreement with observations at most Interagency Monitoring of Protected Visual Environments (IMPROVE) and Chemical Speciation Network (CSN) sites. Model comparison with California Research at the Nexus of Air Quality and Climate Change (CalNex) observations will also be discussed, with particular focus on the South Coast Air Basin where clean marine air mixes with anthropogenic pollution in a complex environment. These SSA emission updates enable more realistic simulation of chemical processes in coastal environments, both in clean marine air masses and mixtures of clean marine and polluted conditions.

Assessing the performance of eight real-time updating models and procedures for the Brosna River

NASA Astrophysics Data System (ADS)

Goswami, M.; O'Connor, K. M.; Bhattarai, K. P.; Shamseldin, A. Y.

2005-10-01

The flow forecasting performance of eight updating models, incorporated in the Galway River Flow Modelling and Forecasting System (GFMFS), was assessed using daily data (rainfall, evaporation and discharge) of the Irish Brosna catchment (1207 km2), considering their one to six days lead-time discharge forecasts. The Perfect Forecast of Input over the Forecast Lead-time scenario was adopted, where required, in place of actual rainfall forecasts. The eight updating models were: (i) the standard linear Auto-Regressive (AR) model, applied to the forecast errors (residuals) of a simulation (non-updating) rainfall-runoff model; (ii) the Neural Network Updating (NNU) model, also using such residuals as input; (iii) the Linear Transfer Function (LTF) model, applied to the simulated and the recently observed discharges; (iv) the Non-linear Auto-Regressive eXogenous-Input Model (NARXM), also a neural network-type structure, but having wide options of using recently observed values of one or more of the three data series, together with non-updated simulated outflows, as inputs; (v) the Parametric Simple Linear Model (PSLM), of LTF-type, using recent rainfall and observed discharge data; (vi) the Parametric Linear perturbation Model (PLPM), also of LTF-type, using recent rainfall and observed discharge data, (vii) n-AR, an AR model applied to the observed discharge series only, as a naïve updating model; and (viii) n-NARXM, a naive form of the NARXM, using only the observed discharge data, excluding exogenous inputs. The five GFMFS simulation (non-updating) models used were the non-parametric and parametric forms of the Simple Linear Model and of the Linear Perturbation Model, the Linearly-Varying Gain Factor Model, the Artificial Neural Network Model, and the conceptual Soil Moisture Accounting and Routing (SMAR) model. As the SMAR model performance was found to be the best among these models, in terms of the Nash-Sutcliffe R2 value, both in calibration and in verification, the simulated outflows of this model only were selected for the subsequent exercise of producing updated discharge forecasts. All the eight forms of updating models for producing lead-time discharge forecasts were found to be capable of producing relatively good lead-1 (1-day ahead) forecasts, with R2 values almost 90% or above. However, for higher lead time forecasts, only three updating models, viz., NARXM, LTF, and NNU, were found to be suitable, with lead-6 values of R2 about 90% or higher. Graphical comparisons were made of the lead-time forecasts for the two largest floods, one in the calibration period and the other in the verification period.

The factor structure of posttraumatic stress disorder: a literature update, critique of methodology, and agenda for future research.

PubMed

Elhai, Jon D; Palmieri, Patrick A

2011-08-01

We present an update of recent literature (since 2007) exploring the factor structure of posttraumatic stress disorder (PTSD) symptom measures. Research supporting a four-factor emotional numbing model and a four-factor dysphoria model is presented, with these models fitting better than all other models examined. Variables accounting for factor structure differences are reviewed, including PTSD query instructions, type of PTSD measure, extent of trauma exposure, ethnicity, and timing of administration. Methodological and statistical limitations with recent studies are presented. Finally, a research agenda and recommendations are offered to push this research area forward, including suggestions to validate PTSD’s factors against external measures of psychopathology, test moderators of factor structure, and examine heterogeneity of symptom presentations based on factor structure examination.

Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices

NASA Astrophysics Data System (ADS)

Chen, Yan; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

The key in stock trading model is to take the right actions for trading at the right time, primarily based on the accurate forecast of future stock trends. Since an effective trading with given information of stock prices needs an intelligent strategy for the decision making, we applied Genetic Network Programming (GNP) to creating a stock trading model. In this paper, we propose a new method called Real Time Updating Genetic Network Programming (RTU-GNP) for adapting to the change of stock prices. There are three important points in this paper: First, the RTU-GNP method makes a stock trading decision considering both the recommendable information of technical indices and the candlestick charts according to the real time stock prices. Second, we combine RTU-GNP with a Sarsa learning algorithm to create the programs efficiently. Also, sub-nodes are introduced in each judgment and processing node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. Third, a Real Time Updating system has been firstly introduced in our paper considering the change of the trend of stock prices. The experimental results on the Japanese stock market show that the trading model with the proposed RTU-GNP method outperforms other models without real time updating. We also compared the experimental results using the proposed method with Buy&Hold method to confirm its effectiveness, and it is clarified that the proposed trading model can obtain much higher profits than Buy&Hold method.

Planned updates and refinements to the central valley hydrologic model, with an emphasis on improving the simulation of land subsidence in the San Joaquin Valley

USGS Publications Warehouse

Faunt, C.C.; Hanson, R.T.; Martin, P.; Schmid, W.

2011-01-01

California's Central Valley has been one of the most productive agricultural regions in the world for more than 50 years. To better understand the groundwater availability in the valley, the U.S. Geological Survey (USGS) developed the Central Valley hydrologic model (CVHM). Because of recent water-level declines and renewed subsidence, the CVHM is being updated to better simulate the geohydrologic system. The CVHM updates and refinements can be grouped into two general categories: (1) model code changes and (2) data updates. The CVHM updates and refinements will require that the model be recalibrated. The updated CVHM will provide a detailed transient analysis of changes in groundwater availability and flow paths in relation to climatic variability, urbanization, stream flow, and changes in irrigated agricultural practices and crops. The updated CVHM is particularly focused on more accurately simulating the locations and magnitudes of land subsidence. The intent of the updated CVHM is to help scientists better understand the availability and sustainability of water resources and the interaction of groundwater levels with land subsidence. ?? 2011 ASCE.

Planned updates and refinements to the Central Valley hydrologic model with an emphasis on improving the simulation of land subsidence in the San Joaquin Valley

USGS Publications Warehouse

Faunt, Claudia C.; Hanson, Randall T.; Martin, Peter; Schmid, Wolfgang

2011-01-01

California's Central Valley has been one of the most productive agricultural regions in the world for more than 50 years. To better understand the groundwater availability in the valley, the U.S. Geological Survey (USGS) developed the Central Valley hydrologic model (CVHM). Because of recent water-level declines and renewed subsidence, the CVHM is being updated to better simulate the geohydrologic system. The CVHM updates and refinements can be grouped into two general categories: (1) model code changes and (2) data updates. The CVHM updates and refinements will require that the model be recalibrated. The updated CVHM will provide a detailed transient analysis of changes in groundwater availability and flow paths in relation to climatic variability, urbanization, stream flow, and changes in irrigated agricultural practices and crops. The updated CVHM is particularly focused on more accurately simulating the locations and magnitudes of land subsidence. The intent of the updated CVHM is to help scientists better understand the availability and sustainability of water resources and the interaction of groundwater levels with land subsidence.

Optimization Based Efficiencies in First Order Reliability Analysis

NASA Technical Reports Server (NTRS)

Peck, Jeffrey A.; Mahadevan, Sankaran

2003-01-01

This paper develops a method for updating the gradient vector of the limit state function in reliability analysis using Broyden's rank one updating technique. In problems that use commercial code as a black box, the gradient calculations are usually done using a finite difference approach, which becomes very expensive for large system models. The proposed method replaces the finite difference gradient calculations in a standard first order reliability method (FORM) with Broyden's Quasi-Newton technique. The resulting algorithm of Broyden updates within a FORM framework (BFORM) is used to run several example problems, and the results compared to standard FORM results. It is found that BFORM typically requires fewer functional evaluations that FORM to converge to the same answer.

3D Reconstruction of human bones based on dictionary learning.

PubMed

Zhang, Binkai; Wang, Xiang; Liang, Xiao; Zheng, Jinjin

2017-11-01

An effective method for reconstructing a 3D model of human bones from computed tomography (CT) image data based on dictionary learning is proposed. In this study, the dictionary comprises the vertices of triangular meshes, and the sparse coefficient matrix indicates the connectivity information. For better reconstruction performance, we proposed a balance coefficient between the approximation and regularisation terms and a method for optimisation. Moreover, we applied a local updating strategy and a mesh-optimisation method to update the dictionary and the sparse matrix, respectively. The two updating steps are iterated alternately until the objective function converges. Thus, a reconstructed mesh could be obtained with high accuracy and regularisation. The experimental results show that the proposed method has the potential to obtain high precision and high-quality triangular meshes for rapid prototyping, medical diagnosis, and tissue engineering. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Obtaining manufactured geometries of deep-drawn components through a model updating procedure using geometric shape parameters

NASA Astrophysics Data System (ADS)

Balla, Vamsi Krishna; Coox, Laurens; Deckers, Elke; Plyumers, Bert; Desmet, Wim; Marudachalam, Kannan

2018-01-01

The vibration response of a component or system can be predicted using the finite element method after ensuring numerical models represent realistic behaviour of the actual system under study. One of the methods to build high-fidelity finite element models is through a model updating procedure. In this work, a novel model updating method of deep-drawn components is demonstrated. Since the component is manufactured with a high draw ratio, significant deviations in both profile and thickness distributions occurred in the manufacturing process. A conventional model updating, involving Young's modulus, density and damping ratios, does not lead to a satisfactory match between simulated and experimental results. Hence a new model updating process is proposed, where geometry shape variables are incorporated, by carrying out morphing of the finite element model. This morphing process imitates the changes that occurred during the deep drawing process. An optimization procedure that uses the Global Response Surface Method (GRSM) algorithm to maximize diagonal terms of the Modal Assurance Criterion (MAC) matrix is presented. This optimization results in a more accurate finite element model. The advantage of the proposed methodology is that the CAD surface of the updated finite element model can be readily obtained after optimization. This CAD model can be used for carrying out analysis, as it represents the manufactured part more accurately. Hence, simulations performed using this updated model with an accurate geometry, will therefore yield more reliable results.

Update of aircraft profile data for the Integrated Noise Model computer program, vol. 2 : appendix A aircraft takeoff and landing profiles

DOT National Transportation Integrated Search

1992-03-01

This report provides aircraft takeoff and landing profiles, aircraft aerodynamic performance coefficients and engine performance coefficients for the aircraft data base (Database 9) in the Integrated Noise Model (INM) computer program. Flight profile...

Updating the Duplex Design for Test-Based Accountability in the Twenty-First Century

ERIC Educational Resources Information Center

Bejar, Isaac I.; Graf, E. Aurora

2010-01-01

The duplex design by Bock and Mislevy for school-based testing is revisited and evaluated as a potential platform in test-based accountability assessments today. We conclude that the model could be useful in meeting the many competing demands of today's test-based accountability assessments, although many research questions will need to be…

Object-oriented fault tree models applied to system diagnosis

NASA Technical Reports Server (NTRS)

Iverson, David L.; Patterson-Hine, F. A.

1990-01-01

When a diagnosis system is used in a dynamic environment, such as the distributed computer system planned for use on Space Station Freedom, it must execute quickly and its knowledge base must be easily updated. Representing system knowledge as object-oriented augmented fault trees provides both features. The diagnosis system described here is based on the failure cause identification process of the diagnostic system described by Narayanan and Viswanadham. Their system has been enhanced in this implementation by replacing the knowledge base of if-then rules with an object-oriented fault tree representation. This allows the system to perform its task much faster and facilitates dynamic updating of the knowledge base in a changing diagnosis environment. Accessing the information contained in the objects is more efficient than performing a lookup operation on an indexed rule base. Additionally, the object-oriented fault trees can be easily updated to represent current system status. This paper describes the fault tree representation, the diagnosis algorithm extensions, and an example application of this system. Comparisons are made between the object-oriented fault tree knowledge structure solution and one implementation of a rule-based solution. Plans for future work on this system are also discussed.

Balancing exploration and exploitation in population-based sampling improves fragment-based de novo protein structure prediction.

PubMed

Simoncini, David; Schiex, Thomas; Zhang, Kam Y J

2017-05-01

Conformational search space exploration remains a major bottleneck for protein structure prediction methods. Population-based meta-heuristics typically enable the possibility to control the search dynamics and to tune the balance between local energy minimization and search space exploration. EdaFold is a fragment-based approach that can guide search by periodically updating the probability distribution over the fragment libraries used during model assembly. We implement the EdaFold algorithm as a Rosetta protocol and provide two different probability update policies: a cluster-based variation (EdaRose c ) and an energy-based one (EdaRose en ). We analyze the search dynamics of our new Rosetta protocols and show that EdaRose c is able to provide predictions with lower C αRMSD to the native structure than EdaRose en and Rosetta AbInitio Relax protocol. Our software is freely available as a C++ patch for the Rosetta suite and can be downloaded from http://www.riken.jp/zhangiru/software/. Our protocols can easily be extended in order to create alternative probability update policies and generate new search dynamics. Proteins 2017; 85:852-858. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Continuous Improvement of a Groundwater Model over a 20-Year Period: Lessons Learned.

PubMed

Andersen, Peter F; Ross, James L; Fenske, Jon P

2018-04-17

Groundwater models developed for specific sites generally become obsolete within a few years due to changes in: (1) modeling technology; (2) site/project personnel; (3) project funding; and (4) modeling objectives. Consequently, new models are sometimes developed for the same sites using the latest technology and data, but without potential knowledge gained from the prior models. When it occurs, this practice is particularly problematic because, although technology, data, and observed conditions change, development of the new numerical model may not consider the conceptual model's underpinnings. As a contrary situation, we present the unique case of a numerical flow and trichloroethylene (TCE) transport model that was first developed in 1993 and since revised and updated annually by the same personnel. The updates are prompted by an increase in the amount of data, exposure to a wider range of hydrologic conditions over increasingly longer timeframes, technological advances, evolving modeling objectives, and revised modeling methodologies. The history of updates shows smooth, incremental changes in the conceptual model and modeled aquifer parameters that result from both increase and decrease in complexity. Myriad modeling objectives have included demonstrating the ineffectiveness of a groundwater extraction/injection system, evaluating potential TCE degradation, locating new monitoring points, and predicting likelihood of exceedance of groundwater standards. The application emphasizes an original tenet of successful groundwater modeling: iterative adjustment of the conceptual model based on observations of actual vs. model response. © 2018, National Ground Water Association.

Summary of Expansions, Updates, and Results in GREET 2017 Suite of Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Michael; Elgowainy, Amgad; Han, Jeongwoo

This report provides a technical summary of the expansions and updates to the 2017 release of Argonne National Laboratory’s Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET®) model, including references and links to key technical documents related to these expansions and updates. The GREET 2017 release includes an updated version of the GREET1 (the fuel-cycle GREET model) and GREET2 (the vehicle-cycle GREET model), both in the Microsoft Excel platform and in the GREET.net modeling platform. Figure 1 shows the structure of the GREET Excel modeling platform. The .net platform integrates all GREET modules together seamlessly.

Integrated Functional and Executional Modelling of Software Using Web-Based Databases

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Marietta, Roberta

1998-01-01

NASA's software subsystems undergo extensive modification and updates over the operational lifetimes. It is imperative that modified software should satisfy safety goals. This report discusses the difficulties encountered in doing so and discusses a solution based on integrated modelling of software, use of automatic information extraction tools, web technology and databases. To appear in an article of Journal of Database Management.

DecAID: a decaying wood advisory model for Oregon and Washington.

Treesearch

Kim Mellen; Bruce G. Marcot; Janet L. Ohmann; Karen L. Waddell; Elizabeth A. Willhite; Bruce B. Hostetler; Susan A. Livingston; Cay Ogden

2002-01-01

DecAID is a knowledge-based advisory model that provides guidance to managers in determining the size, amount, and distribution of dead and decaying wood (dead and partially dead trees and down wood) necessary to maintain wildlife habitat and ecosystem functions. The intent of the model is to update and replace existing snag-wildlife models in Washington and Oregon....

Global Modeling and Assimilation Office Annual Report and Research Highlights 2011-2012

NASA Technical Reports Server (NTRS)

Rienecker, Michele M.

2012-01-01

Over the last year, the Global Modeling and Assimilation Office (GMAO) has continued to advance our GEOS-5-based systems, updating products for both weather and climate applications. We contributed hindcasts and forecasts to the National Multi-Model Ensemble (NMME) of seasonal forecasts and the suite of decadal predictions to the Coupled Model Intercomparison Project (CMIP5).

A Methodology for Cybercraft Requirement Definition and Initial System Design

DTIC Science & Technology

2008-06-01

the software development concepts of the SDLC , requirements, use cases and domain modeling . It ...collectively as Software Development 5 Life Cycle ( SDLC ) models . While there are numerous models that fit under the SDLC definition, all are based on... developed that provided expanded understanding of the domain, it is necessary to either update an existing domain model or create another domain

Updates to the Demographic and Spatial Allocation Models to ...

EPA Pesticide Factsheets

EPA's announced the availability of the final report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) (Version 2). This update furthered land change modeling by providing nationwide housing development scenarios up to 2100. This newest version includes updated population and land use data sets and addresses limitations identified in ICLUS v1 in both the migration and spatial allocation models. The companion user guide (Final Report) describes the development of ICLUS v2 and the updates that were made to the original data sets and the demographic and spatial allocation models. The GIS tool enables users to run SERGoM with the population projections developed for the ICLUS project and allows users to modify the spatial allocation housing density across the landscape.

Ground Operations of the ISS GNC Babb-Mueller Atmospheric Density Model

NASA Technical Reports Server (NTRS)

Brogan, Jonathan

2002-01-01

The ISS GNC system was updated recently with a new software release that provides onboard state determination capability. Prior to this release, only the Russian segment maintained and propagated the onboard state, which was periodically updated through Russian ground tracking. The new software gives the US segment the capability for maintaining the onboard state, and includes new GPS and state vector propagation capabilities. Part of this software package is an atmospheric density model based on the Babb-Mueller algorithm. Babb-Mueller efficiently mimics a full analytical density model, such as the Jacchia model. While lacchia is very robust and is used in the Mission Control Center, it is too computationally intensive for use onboard. Thus, Babb-Mueller was chosen as an alternative. The onboard model depends on a set of calibration coefficients that produce a curve fit to the lacchia model. The ISS GNC system only maintains one set of coefficients onboard, so a new set must be uplinked by controllers when the atmospheric conditions change. The onboard density model provides a real-time density value, which is used to calculate the drag experienced by the ISS. This drag value is then incorporated into the onboard propagation of the state vector. The propagation of the state vector, and therefore operation of the BabbMueller algorithm, will be most critical when GPS updates and secondary state vector sources fail. When GPS is active, the onboard state vector will be updated every ten seconds, so the propagation error is irrelevant. When GPS is inactive, the state vector must be updated at least every 24 hours, based on current protocol. Therefore, the Babb-Mueller coefficients must be accurate enough to fulfill the state vector accuracy requirements for at least one day. A ground operations concept was needed in order to manage both the on board Babb-Mueller density model and the onboard state quality. The Babb-Mueller coefficients can be determined operationally in two ways. The first method is to calibrate the coefficients in real-time, where a set of custom coefficients is generated for the real-time atmospheric conditions. The second approach is to generate pre-canned sets of coefficients that encompass the expected atmospheric conditions over the lifetime of the vehicle. These predetermined sets are known as occurrences. Even though a particular occurrence will not match the true atmospheric conditions, the error will be constrained by limiting the breadth of each occurrence. Both methods were investigated and the advantages and disadvantages of each were considered. The choice between these implementations was a trade-off between the additional accuracy of the real-time calibration and the simpler development for the approach using occurrences. The operations concept for the frequency of updates was also explored, and depends on the deviation in solar flux that still achieves the necessary accuracy of the coefficients. This was determined based on historical solar flux trends. This analysis resulted in an accurate and reliable implementation of the Babb-Mueller coefficients and how flight controllers use them during realtime operations.

Designing the Architecture of Hierachical Neural Networks Model Attention, Learning and Goal-Oriented Behavior

DTIC Science & Technology

1993-12-31

19,23,25,26,27,28,32,33,35,41]) - A new cost function is postulated and an algorithm that employs this cost function is proposed for the learning of...updates the controller parameters from time to time [53]. The learning control algorithm consist of updating the parameter estimates as used in the...proposed cost function with the other learning type algorithms , such as based upon learning of iterative tasks [Kawamura-85], variable structure

Scale-adaptive compressive tracking with feature integration

NASA Astrophysics Data System (ADS)

Liu, Wei; Li, Jicheng; Chen, Xiao; Li, Shuxin

2016-05-01

Numerous tracking-by-detection methods have been proposed for robust visual tracking, among which compressive tracking (CT) has obtained some promising results. A scale-adaptive CT method based on multifeature integration is presented to improve the robustness and accuracy of CT. We introduce a keypoint-based model to achieve the accurate scale estimation, which can additionally give a prior location of the target. Furthermore, by the high efficiency of data-independent random projection matrix, multiple features are integrated into an effective appearance model to construct the naïve Bayes classifier. At last, an adaptive update scheme is proposed to update the classifier conservatively. Experiments on various challenging sequences demonstrate substantial improvements by our proposed tracker over CT and other state-of-the-art trackers in terms of dealing with scale variation, abrupt motion, deformation, and illumination changes.

Status Update on Translation of Integrated Primary Dental-Medical Care Delivery for Management of Diabetic Patients.

PubMed

Glurich, Ingrid; Nycz, Gregory; Acharya, Amit

2017-06-01

Escalating prevalence of both diabetes and periodontal disease, two diseases associated with bi-directional exacerbation, has been reported. Periodontal disease represents a modifiable risk factor that may reduce diabetes onset or progression, and integrated models of cross-disciplinary care are needed to establish and manage glycemic control in affected patients. An ad-hoc environmental scan of current literature and media sought to characterize factors impacting status of integrated care models based on review of the existing evidence base in literature and media surrounding: (1) current cross-disciplinary practice patterns, (2) epidemiological updates, (3) status on risk assessment and screening for dysglycemia in the dental setting, (4) status on implementation of quality metrics for oral health, (5) care model pilots, and (6) public health perspectives. The survey revealed: escalating prevalence of diabetes and periodontitis globally; greater emphasis on oral health assessment for diabetic patients in recent medical clinical practice guidelines; high knowledgeability surrounding oral-systemic impacts on diabetes and growing receptivity to medical-dental integration among medical and dental providers; increasing numbers of programs/studies reporting on positive impact of emerging integrated dental-medical care models on diabetic patient healthcare access and health outcomes; a growing evidence base for clinically significant rates of undiagnosed dysglycemia among dental patients reported by point-of-care pilot studies; no current recommendation for population-based screening for dysglycemia in dental settings pending a stronger evidence base; improved definition of true periodontitis prevalence in (pre)/diabetics; emerging recognition of the need for oral health quality indicators and tracking; evidence of persistence in dental access disparity; updated status on barriers to integration. The potential benefit of creating clinically-applicable integrated care models to support holistic management of an escalating diabetic population by targeting modifiable risk factors including periodontitis is being recognized by the health industry. Cross-disciplinary efforts supported by high quality research are needed to mitigate previously- and newly-defined barriers of care integration and expedite development and implementation of integrated care models in various practice settings. Implementation of quality monitoring in the dental setting will support definition of the impact and efficacy of interventional clinical care models on patient outcomes. © 2017 Marshfield Clinic.

Model Update of a Micro Air Vehicle (MAV) Flexible Wing Frame with Uncertainty Quantification

NASA Technical Reports Server (NTRS)

Reaves, Mercedes C.; Horta, Lucas G.; Waszak, Martin R.; Morgan, Benjamin G.

2004-01-01

This paper describes a procedure to update parameters in the finite element model of a Micro Air Vehicle (MAV) to improve displacement predictions under aerodynamics loads. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with Multidisciplinary Design Optimization (MDO) is used to modify key model parameters. Static test data collected using photogrammetry are used to correlate with model predictions. Results show significant improvements in model predictions after parameters are updated; however, computed probabilities values indicate low confidence in updated values and/or model structure errors. Lessons learned in the areas of wing design, test procedures, modeling approaches with geometric nonlinearities, and uncertainties quantification are all documented.

Detection of Earthquake-Induced Damage in a Framed Structure Using a Finite Element Model Updating Procedure

PubMed Central

Kim, Seung-Nam; Park, Taewon; Lee, Sang-Hyun

2014-01-01

Damage of a 5-story framed structure was identified from two types of measured data, which are frequency response functions (FRF) and natural frequencies, using a finite element (FE) model updating procedure. In this study, a procedure to determine the appropriate weightings for different groups of observations was proposed. In addition, a modified frame element which included rotational springs was used to construct the FE model for updating to represent concentrated damage at the member ends (a formulation for plastic hinges in framed structures subjected to strong earthquakes). The results of the model updating and subsequent damage detection when the rotational springs (RS model) were used were compared with those obtained using the conventional frame elements (FS model). Comparisons indicated that the RS model gave more accurate results than the FS model. That is, the errors in the natural frequencies of the updated models were smaller, and the identified damage showed clearer distinctions between damaged and undamaged members and was more consistent with observed damage. PMID:24574888

A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology

NASA Astrophysics Data System (ADS)

Ait-El-Fquih, Boujemaa; El Gharamti, Mohamad; Hoteit, Ibrahim

2016-08-01

Ensemble Kalman filtering (EnKF) is an efficient approach to addressing uncertainties in subsurface groundwater models. The EnKF sequentially integrates field data into simulation models to obtain a better characterization of the model's state and parameters. These are generally estimated following joint and dual filtering strategies, in which, at each assimilation cycle, a forecast step by the model is followed by an update step with incoming observations. The joint EnKF directly updates the augmented state-parameter vector, whereas the dual EnKF empirically employs two separate filters, first estimating the parameters and then estimating the state based on the updated parameters. To develop a Bayesian consistent dual approach and improve the state-parameter estimates and their consistency, we propose in this paper a one-step-ahead (OSA) smoothing formulation of the state-parameter Bayesian filtering problem from which we derive a new dual-type EnKF, the dual EnKFOSA. Compared with the standard dual EnKF, it imposes a new update step to the state, which is shown to enhance the performance of the dual approach with almost no increase in the computational cost. Numerical experiments are conducted with a two-dimensional (2-D) synthetic groundwater aquifer model to investigate the performance and robustness of the proposed dual EnKFOSA, and to evaluate its results against those of the joint and dual EnKFs. The proposed scheme is able to successfully recover both the hydraulic head and the aquifer conductivity, providing further reliable estimates of their uncertainties. Furthermore, it is found to be more robust to different assimilation settings, such as the spatial and temporal distribution of the observations, and the level of noise in the data. Based on our experimental setups, it yields up to 25 % more accurate state and parameter estimations than the joint and dual approaches.

The effects of a FRAX revision for the US

USDA-ARS?s Scientific Manuscript database

The aim of this study was to determine the effects of a revision of the epidemiological data used to compute fracture probabilities in the US with FRAX (registered trademark). Models were constructed to compute fracture probabilities based on updated epidemiology of fracture in the US. The models c...

Summer Session Organizational Models at Canadian Universities

ERIC Educational Resources Information Center

Kops, Bill

2010-01-01

The issue of summer session organizational models continues to be of interest to summer session deans/directors and university administrators. The University of Victoria surveyed Canadian universities on this issue in 1994. Based on a similar survey done in 2009, this paper updates the status of Canadian university summer session organizational…

The Behavior of Preschool Handicapped Children and Their Interactions with Model Children: An Update.

ERIC Educational Resources Information Center

Montemurro, Theodore J.

The behavior patterns of 6 handicapped children and 14 nonhandicapped children were recorded during participation in a model developmental-interactive based curriculum for preschool children. Interactions were recorded using the Coping Analysis Schedule for Educational Settings. Among findings were the following: the consistently high occurrence…

Continuous data assimilation experiments with the NMC eta model: A GALE IOP 1 case study. [NMC (National Meteorological Center); GALE IOP (Genesis of Atlantic Lows Experiment intensive observing period)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramamurthy, M.K.; Xu, T.Y.

1993-11-01

The current major expansion in observational capability of the National Weather Service is principally in the volume of asynchronous data rather than synchronous observations at the standard synoptic times. Hence, the National Meteorological Center is considering a continuous data assimilation system to replace at some time the intermittent system now used by its regional and global operational models. We describe this system, based on the Newtonian relaxation technique, as developed for the eta model. Experiments are performed for the first intensive observing period of the Genesis of Atlantic Lows Experiment (GALE) in January 1986, when strong upper-level cyclogenesis occurred, withmore » a pronounced tropopause fold but only modest surface development. The GALE level IIIb dataset was used for initializing and updating the model. Issues addressed in the experiments include choice of update variable, number, and length of update segments; need for updating moisture and surface pressure information; nudging along boundaries; and noise control. Assimilation of data from a single level was also studied. Use of a preforecast assimilation cycle was found to eliminate the spinup problem almost entirely. Multiple, shorter assimilation segments produced better forecasts than a single, longer cycle. Updating the mass field was less effective than nudging the wind field but assimilating both was best. Assimilation of moisture data, surprisingly, affected the spinup adversely, but nudging the surface pressure information reduced the spurious pillow effect. Assimilation of single-level information was ineffective unless accompanied by increased vertical coupling, obtained from a control integration. 52 refs., 19 figs., 1 tab.« less

Selected aspects of prior and likelihood information for a Bayesian classifier in a road safety analysis.

PubMed

Nowakowska, Marzena

2017-04-01

The development of the Bayesian logistic regression model classifying the road accident severity is discussed. The already exploited informative priors (method of moments, maximum likelihood estimation, and two-stage Bayesian updating), along with the original idea of a Boot prior proposal, are investigated when no expert opinion has been available. In addition, two possible approaches to updating the priors, in the form of unbalanced and balanced training data sets, are presented. The obtained logistic Bayesian models are assessed on the basis of a deviance information criterion (DIC), highest probability density (HPD) intervals, and coefficients of variation estimated for the model parameters. The verification of the model accuracy has been based on sensitivity, specificity and the harmonic mean of sensitivity and specificity, all calculated from a test data set. The models obtained from the balanced training data set have a better classification quality than the ones obtained from the unbalanced training data set. The two-stage Bayesian updating prior model and the Boot prior model, both identified with the use of the balanced training data set, outperform the non-informative, method of moments, and maximum likelihood estimation prior models. It is important to note that one should be careful when interpreting the parameters since different priors can lead to different models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Future-year ozone prediction for the United States using updated models and inputs.

PubMed

Collet, Susan; Kidokoro, Toru; Karamchandani, Prakash; Shah, Tejas; Jung, Jaegun

2017-08-01

The relationship between emission reductions and changes in ozone can be studied using photochemical grid models. These models are updated with new information as it becomes available. The primary objective of this study was to update the previous Collet et al. studies by using the most up-to-date (at the time the study was done) modeling emission tools, inventories, and meteorology available to conduct ozone source attribution and sensitivity studies. Results show future-year, 2030, design values for 8-hr ozone concentrations were lower than base-year values, 2011. The ozone source attribution results for selected cities showed that boundary conditions were the dominant contributors to ozone concentrations at the western U.S. locations, and were important for many of the eastern U.S. Point sources were generally more important in the eastern United States than in the western United States. The contributions of on-road mobile emissions were less than 5 ppb at a majority of the cities selected for analysis. The higher-order decoupled direct method (HDDM) results showed that in most of the locations selected for analysis, NOx emission reductions were more effective than VOC emission reductions in reducing ozone levels. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies. The relationship between emission reductions and changes in ozone can be studied using photochemical grid models, which are updated with new available information. This study was to update the previous Collet et al. studies by using the most current, at the time the study was done, models and inventory to conduct ozone source attribution and sensitivity studies. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies.

Stereotype threat and executive functions: which functions mediate different threat-related outcomes?

PubMed

Rydell, Robert J; Van Loo, Katie J; Boucher, Kathryn L

2014-03-01

Stereotype threat research shows that women's math performance can be reduced by activating gender-based math stereotypes. Models of stereotype threat assert that threat reduces cognitive functioning, thereby accounting for its negative effects. This work provides a more detailed understanding of the cognitive processes through which stereotype threat leads women to underperform at math and to take risks, by examining which basic executive functions (inhibition, shifting, and updating) account for these outcomes. In Experiments 1 and 2, women under threat showed reduced inhibition, reduced updating, and reduced math performance compared with women in a control condition (or men); however, only updating accounted for women's poor math performance under threat. In Experiment 3, only updating accounted for stereotype threat's effect on women's math performance, whereas only inhibition accounted for the effect of threat on risk-taking, suggesting that distinct executive functions can account for different stereotype threat-related outcomes.

Web-based Altimeter Service

NASA Astrophysics Data System (ADS)

Callahan, P. S.; Wilson, B. D.; Xing, Z.; Raskin, R. G.

2010-12-01

We have developed a web-based system to allow updating and subsetting of TOPEX data. The Altimeter Service will be operated by PODAAC along with their other provision of oceanographic data. The Service could be easily expanded to other mission data. An Altimeter Service is crucial to the improvement and expanded use of altimeter data. A service is necessary for altimetry because the result of most interest - sea surface height anomaly (SSHA) - is composed of several components that are updated individually and irregularly by specialized experts. This makes it difficult for projects to provide the most up-to-date products. Some components are the subject of ongoing research, so the ability for investigators to make products for comparison or sharing is important. The service will allow investigators/producers to get their component models or processing into widespread use much more quickly. For coastal altimetry, the ability to subset the data to the area of interest and insert specialized models (e.g., tides) or data processing results is crucial. A key part of the Altimeter Service is having data producers provide updated or local models and data. In order for this to succeed, producers need to register their products with the Altimeter Service and to provide the product in a form consistent with the service update methods. We will describe the capabilities of the web service and the methods for providing new components. Currently the Service is providing TOPEX GDRs with Retracking (RGDRs) in netCDF format that has been coordinated with Jason data. Users can add new orbits, tide models, gridded geophysical fields such as mean sea surface, and along-track corrections as they become available and are installed by PODAAC. The updated fields are inserted into the netCDF files while the previous values are retained for comparison. The Service will also generate SSH and SSHA. In addition, the Service showcases a feature that plots any variable from files in netCDF. The research described here was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

Real-Time Tracking by Double Templates Matching Based on Timed Motion History Image with HSV Feature

PubMed Central

Li, Zhiyong; Li, Pengfei; Yu, Xiaoping; Hashem, Mervat

2014-01-01

It is a challenge to represent the target appearance model for moving object tracking under complex environment. This study presents a novel method with appearance model described by double templates based on timed motion history image with HSV color histogram feature (tMHI-HSV). The main components include offline template and online template initialization, tMHI-HSV-based candidate patches feature histograms calculation, double templates matching (DTM) for object location, and templates updating. Firstly, we initialize the target object region and calculate its HSV color histogram feature as offline template and online template. Secondly, the tMHI-HSV is used to segment the motion region and calculate these candidate object patches' color histograms to represent their appearance models. Finally, we utilize the DTM method to trace the target and update the offline template and online template real-timely. The experimental results show that the proposed method can efficiently handle the scale variation and pose change of the rigid and nonrigid objects, even in illumination change and occlusion visual environment. PMID:24592185

Model updating strategy for structures with localised nonlinearities using frequency response measurements

NASA Astrophysics Data System (ADS)

Wang, Xing; Hill, Thomas L.; Neild, Simon A.; Shaw, Alexander D.; Haddad Khodaparast, Hamed; Friswell, Michael I.

2018-02-01

This paper proposes a model updating strategy for localised nonlinear structures. It utilises an initial finite-element (FE) model of the structure and primary harmonic response data taken from low and high amplitude excitations. The underlying linear part of the FE model is first updated using low-amplitude test data with established techniques. Then, using this linear FE model, the nonlinear elements are localised, characterised, and quantified with primary harmonic response data measured under stepped-sine or swept-sine excitations. Finally, the resulting model is validated by comparing the analytical predictions with both the measured responses used in the updating and with additional test data. The proposed strategy is applied to a clamped beam with a nonlinear mechanism and good agreements between the analytical predictions and measured responses are achieved. Discussions on issues of damping estimation and dealing with data from amplitude-varying force input in the updating process are also provided.

Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2013)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, David C.; Syamlal, Madhava; Cottrell, Roger

2013-09-30

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools asmore » necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories’ core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI’s industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI’s academic participants (Carnegie Mellon University, Princeton University, West Virginia University, Boston University and the University of Texas at Austin) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 13, CCSI announced the initial release of its first set of computational tools and models during the October 2012 meeting of its Industry Advisory Board. This initial release led to five companies licensing the CCSI Toolset under a Test and Evaluation Agreement this year. By the end of FY13, the CCSI Technical Team had completed development of an updated suite of computational tools and models. The list below summarizes the new and enhanced toolset components that were released following comprehensive testing during October 2013. 1. FOQUS. Framework for Optimization and Quantification of Uncertainty and Sensitivity. Package includes: FOQUS Graphic User Interface (GUI), simulation-based optimization engine, Turbine Client, and heat integration capabilities. There is also an updated simulation interface and new configuration GUI for connecting Aspen Plus or Aspen Custom Modeler (ACM) simulations to FOQUS and the Turbine Science Gateway. 2. A new MFIX-based Computational Fluid Dynamics (CFD) model to predict particle attrition. 3. A new dynamic reduced model (RM) builder, which generates computationally efficient RMs of the behavior of a dynamic system. 4. A completely re-written version of the algebraic surrogate model builder for optimization (ALAMO). The new version is several orders of magnitude faster than the initial release and eliminates the MATLAB dependency. 5. A new suite of high resolution filtered models for the hydrodynamics associated with horizontal cylindrical objects in a flow path. 6. The new Turbine Science Gateway (Cluster), which supports FOQUS for running multiple simulations for optimization or UQ using a local computer or cluster. 7. A new statistical tool (BSS-ANOVA-UQ) for calibration and validation of CFD models. 8. A new basic data submodel in Aspen Plus format for a representative high viscosity capture solvent, 2-MPZ system. 9. An updated RM tool for CFD (REVEAL) that can create a RM from MFIX. A new lightweight, stand-alone version will be available in late 2013. 10. An updated RM integration tool to convert the RM from REVEAL into a CAPE-OPEN or ACM model for use in a process simulator. 11. An updated suite of unified steady-state and dynamic process models for solid sorbent carbon capture included bubbling fluidized bed and moving bed reactors. 12. An updated and unified set of compressor models including steady-state design point model and dynamic model with surge detection. 13. A new framework for the synthesis and optimization of coal oxycombustion power plants using advanced optimization algorithms. This release focuses on modeling and optimization of a cryogenic air separation unit (ASU). 14. A new technical risk model in spreadsheet format. 15. An updated version of the sorbent kinetic/equilibrium model for parameter estimation for the 1st generation sorbent model. 16. An updated process synthesis superstructure model to determine optimal process configurations utilizing surrogate models from ALAMO for adsorption and regeneration in a solid sorbent process. 17. Validation models for NETL Carbon Capture Unit utilizing sorbent AX. Additional validation models will be available for sorbent 32D in 2014. 18. An updated hollow fiber membrane model and system example for carbon capture. 19. An updated reference power plant model in Thermoflex that includes additional steam extraction and reinjection points to enable heat integration module. 20. An updated financial risk model in spreadsheet format.« less

Utilizing Flight Data to Update Aeroelastic Stability Estimates

NASA Technical Reports Server (NTRS)

Lind, Rick; Brenner, Marty

1997-01-01

Stability analysis of high performance aircraft must account for errors in the system model. A method for computing flutter margins that incorporates flight data has been developed using robust stability theory. This paper considers applying this method to update flutter margins during a post-flight or on-line analysis. Areas of modeling uncertainty that arise when using flight data with this method are investigated. The amount of conservatism in the resulting flutter margins depends on the flight data sets used to update the model. Post-flight updates of flutter margins for an F/A-18 are presented along with a simulation of on-line updates during a flight test.

Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) (Final Report, Version 2)

EPA Science Inventory

EPA's announced the availability of the final report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) (Version 2). This update furthered land change modeling by providing nationwide housing developmen...

View Estimation Based on Value System

NASA Astrophysics Data System (ADS)

Takahashi, Yasutake; Shimada, Kouki; Asada, Minoru

Estimation of a caregiver's view is one of the most important capabilities for a child to understand the behavior demonstrated by the caregiver, that is, to infer the intention of behavior and/or to learn the observed behavior efficiently. We hypothesize that the child develops this ability in the same way as behavior learning motivated by an intrinsic reward, that is, he/she updates the model of the estimated view of his/her own during the behavior imitated from the observation of the behavior demonstrated by the caregiver based on minimizing the estimation error of the reward during the behavior. From this view, this paper shows a method for acquiring such a capability based on a value system from which values can be obtained by reinforcement learning. The parameters of the view estimation are updated based on the temporal difference error (hereafter TD error: estimation error of the state value), analogous to the way such that the parameters of the state value of the behavior are updated based on the TD error. Experiments with simple humanoid robots show the validity of the method, and the developmental process parallel to young children's estimation of its own view during the imitation of the observed behavior of the caregiver is discussed.

A comprehensive iso-octane combustion model with improved thermochemistry and chemical kinetics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Atef, Nour; Kukkadapu, Goutham; Mohamed, Samah Y.

Iso-Octane (2,2,4-trimethylpentane) is a primary reference fuel and an important component of gasoline fuels. Furthermore, it is a key component used in surrogates to study the ignition and burning characteristics of gasoline fuels. This paper presents an updated chemical kinetic model for iso-octane combustion. Specifically, the thermodynamic data and reaction kinetics of iso-octane have been re-assessed based on new thermodynamic group values and recently evaluated rate coefficients from the literature. The adopted rate coefficients were either experimentally measured or determined by analogy to theoretically calculated values. New alternative isomerization pathways for peroxy-alkyl hydroperoxide (more » $$\\dot{O}$$OQOOH) radicals were added to the reaction mechanism. The updated kinetic model was compared against new ignition delay data measured in rapid compression machines (RCM) and a high-pressure shock tube. Our experiments were conducted at pressures of 20 and 40 atm, at equivalence ratios of 0.4 and 1.0, and at temperatures in the range of 632–1060 K. The updated model was further compared against shock tube ignition delay times, jet-stirred reactor oxidation speciation data, premixed laminar flame speeds, counterflow diffusion flame ignition, and shock tube pyrolysis speciation data available in the literature. Finally, the updated model was used to investigate the importance of alternative isomerization pathways in the low temperature oxidation of highly branched alkanes. When compared to available models in the literature, the present model represents the current state-of-the-art in fundamental thermochemistry and reaction kinetics of iso-octane; and thus provides the best prediction of wide ranging experimental data and fundamental insights into iso-octane combustion chemistry.« less

A comprehensive iso-octane combustion model with improved thermochemistry and chemical kinetics

DOE PAGES

Atef, Nour; Kukkadapu, Goutham; Mohamed, Samah Y.; ...

2017-02-05

Iso-Octane (2,2,4-trimethylpentane) is a primary reference fuel and an important component of gasoline fuels. Furthermore, it is a key component used in surrogates to study the ignition and burning characteristics of gasoline fuels. This paper presents an updated chemical kinetic model for iso-octane combustion. Specifically, the thermodynamic data and reaction kinetics of iso-octane have been re-assessed based on new thermodynamic group values and recently evaluated rate coefficients from the literature. The adopted rate coefficients were either experimentally measured or determined by analogy to theoretically calculated values. New alternative isomerization pathways for peroxy-alkyl hydroperoxide (more » $$\\dot{O}$$OQOOH) radicals were added to the reaction mechanism. The updated kinetic model was compared against new ignition delay data measured in rapid compression machines (RCM) and a high-pressure shock tube. Our experiments were conducted at pressures of 20 and 40 atm, at equivalence ratios of 0.4 and 1.0, and at temperatures in the range of 632–1060 K. The updated model was further compared against shock tube ignition delay times, jet-stirred reactor oxidation speciation data, premixed laminar flame speeds, counterflow diffusion flame ignition, and shock tube pyrolysis speciation data available in the literature. Finally, the updated model was used to investigate the importance of alternative isomerization pathways in the low temperature oxidation of highly branched alkanes. When compared to available models in the literature, the present model represents the current state-of-the-art in fundamental thermochemistry and reaction kinetics of iso-octane; and thus provides the best prediction of wide ranging experimental data and fundamental insights into iso-octane combustion chemistry.« less

The Role of Probability-Based Inference in an Intelligent Tutoring System.

ERIC Educational Resources Information Center

Mislevy, Robert J.; Gitomer, Drew H.

Probability-based inference in complex networks of interdependent variables is an active topic in statistical research, spurred by such diverse applications as forecasting, pedigree analysis, troubleshooting, and medical diagnosis. This paper concerns the role of Bayesian inference networks for updating student models in intelligent tutoring…

Utility pole crash modeling.

DOT National Transportation Integrated Search

2001-02-01

Maine was recently ranked 9th in the nation concerning fatalities caused by collisions with utility poles based on : Miles of Travel. The number of collisions and fatalities can be reduced significantly with an updated Utility Pole : Placement Policy...

Annual Plan - Fiscal Year 2009

EPA Pesticide Factsheets

Includes Strategic Plan Update and Draft Plans for Oversight of the American Recovery and Reinvestment Act of 2009 Based Upon the Enterprise Risk Management Integrated Framework Model Developed by the Committee of Sponsoring Orgs of the Treadway Commission

Human substantia nigra and ventral tegmental area involvement in computing social error signals during the ultimatum game

PubMed Central

Hétu, Sébastien; Luo, Yi; D’Ardenne, Kimberlee; Lohrenz, Terry

2017-01-01

Abstract As models of shared expectations, social norms play an essential role in our societies. Since our social environment is changing constantly, our internal models of it also need to change. In humans, there is mounting evidence that neural structures such as the insula and the ventral striatum are involved in detecting norm violation and updating internal models. However, because of methodological challenges, little is known about the possible involvement of midbrain structures in detecting norm violation and updating internal models of our norms. Here, we used high-resolution cardiac-gated functional magnetic resonance imaging and a norm adaptation paradigm in healthy adults to investigate the role of the substantia nigra/ventral tegmental area (SN/VTA) complex in tracking signals related to norm violation that can be used to update internal norms. We show that the SN/VTA codes for the norm’s variance prediction error (PE) and norm PE with spatially distinct regions coding for negative and positive norm PE. These results point to a common role played by the SN/VTA complex in supporting both simple reward-based and social decision making. PMID:28981876

Action Recommendation for Cyber Resilience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choudhury, Sutanay; Rodriguez, Luke R.; Curtis, Darren S.

2015-09-01

This paper presents an unifying graph-based model for representing the infrastructure, behavior and missions of an enterprise. We describe how the model can be used to achieve resiliency against a wide class of failures and attacks. We introduce an algorithm for recommending resilience establishing actions based on dynamic updates to the models. Without loss of generality, we show the effectiveness of the algorithm for preserving latency based quality of service (QoS). Our models and the recommendation algorithms are implemented in a software framework that we seek to release as an open source framework for simulating resilient cyber systems.

Updating finite element dynamic models using an element-by-element sensitivity methodology

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Hemez, Francois M.

1993-01-01

A sensitivity-based methodology for improving the finite element model of a given structure using test modal data and a few sensors is presented. The proposed method searches for both the location and sources of the mass and stiffness errors and does not interfere with the theory behind the finite element model while correcting these errors. The updating algorithm is derived from the unconstrained minimization of the squared L sub 2 norms of the modal dynamic residuals via an iterative two-step staggered procedure. At each iteration, the measured mode shapes are first expanded assuming that the model is error free, then the model parameters are corrected assuming that the expanded mode shapes are exact. The numerical algorithm is implemented in an element-by-element fashion and is capable of 'zooming' on the detected error locations. Several simulation examples which demonstate the potential of the proposed methodology are discussed.

Advances in land modeling of KIAPS based on the Noah Land Surface Model

NASA Astrophysics Data System (ADS)

Koo, Myung-Seo; Baek, Sunghye; Seol, Kyung-Hee; Cho, Kyoungmi

2017-08-01

As of 2013, the Noah Land Surface Model (LSM) version 2.7.1 was implemented in a new global model being developed at the Korea Institute of Atmospheric Prediction Systems (KIAPS). This land surface scheme is further refined in two aspects, by adding new physical processes and by updating surface input parameters. Thus, the treatment of glacier land, sea ice, and snow cover are addressed more realistically. Inconsistencies in the amount of absorbed solar flux at ground level by the land surface and radiative processes are rectified. In addition, new parameters are available by using 1-km land cover data, which had usually not been possible at a global scale. Land surface albedo/emissivity climatology is newly created using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellitebased data and adjusted parameterization. These updates have been applied to the KIAPS-developed model and generally provide a positive impact on near-surface weather forecasting.

Modelling the spatial distribution of ammonia emissions in the UK.

PubMed

Hellsten, S; Dragosits, U; Place, C J; Vieno, M; Dore, A J; Misselbrook, T H; Tang, Y S; Sutton, M A

2008-08-01

Ammonia emissions (NH3) are characterised by a high spatial variability at a local scale. When modelling the spatial distribution of NH3 emissions, it is important to provide robust emission estimates, since the model output is used to assess potential environmental impacts, e.g. exceedance of critical loads. The aim of this study was to provide a new, updated spatial NH3 emission inventory for the UK for the year 2000, based on an improved modelling approach and the use of updated input datasets. The AENEID model distributes NH3 emissions from a range of agricultural activities, such as grazing and housing of livestock, storage and spreading of manures, and fertilizer application, at a 1-km grid resolution over the most suitable landcover types. The results of the emission calculation for the year 2000 are analysed and the methodology is compared with a previous spatial emission inventory for 1996.

An improved design method of a tuned mass damper for an in-service footbridge

NASA Astrophysics Data System (ADS)

Shi, Weixing; Wang, Liangkun; Lu, Zheng

2018-03-01

Tuned mass damper (TMD) has a wide range of applications in the vibration control of footbridges. However, the traditional engineering design method may lead to a mistuned TMD. In this paper, an improved TMD design method based on the model updating is proposed. Firstly, the original finite element model (FEM) is studied and the natural characteristics of the in-service or newly built footbridge is identified by field test, and then the original FEM is updated. TMD is designed according to the new updated FEM, and it is optimized according to the simulation on vibration control effects. Finally, the installation and field measurement of TMD are carried out. The improved design method can be applied to both in-service and newly built footbridges. This paper illustrates the improved design method with an engineering example. The frequency identification results of field test and original FEM show that there is a relatively large difference between them. The TMD designed according to the updated FEM has better vibration control effect than the TMD designed according to the original FEM. The site test results show that TMD has good effect on controlling human-induced vibrations.

Overview and Evaluation of the Community Multiscale Air ...

EPA Pesticide Factsheets

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In late 2016 or early 2017, CMAQ version 5.2 will be released. This new version of CMAQ will contain important updates from the current CMAQv5.1 modeling system, along with several instrumented versions of the model (e.g. decoupled direct method and sulfur tracking). Some specific model updates include the implementation of a new wind-blown dust treatment in CMAQv5.2, a significant improvement over the treatment in v5.1 which can severely overestimate wind-blown dust under certain conditions. Several other major updates to the modeling system include an update to the calculation of aerosols; implementation of full halogen chemistry (CMAQv5.1 contains a partial implementation of halogen chemistry); the new carbon bond 6 (CB6) chemical mechanism; updates to cloud model in CMAQ; and a new lightning assimilation scheme for the WRF model which significant improves the placement and timing of convective precipitation in the WRF precipitation fields. Numerous other updates to the modeling system will also be available in v5.2.

SCADA-based Operator Support System for Power Plant Equipment Fault Forecasting

NASA Astrophysics Data System (ADS)

Mayadevi, N.; Ushakumari, S. S.; Vinodchandra, S. S.

2014-12-01

Power plant equipment must be monitored closely to prevent failures from disrupting plant availability. Online monitoring technology integrated with hybrid forecasting techniques can be used to prevent plant equipment faults. A self learning rule-based expert system is proposed in this paper for fault forecasting in power plants controlled by supervisory control and data acquisition (SCADA) system. Self-learning utilizes associative data mining algorithms on the SCADA history database to form new rules that can dynamically update the knowledge base of the rule-based expert system. In this study, a number of popular associative learning algorithms are considered for rule formation. Data mining results show that the Tertius algorithm is best suited for developing a learning engine for power plants. For real-time monitoring of the plant condition, graphical models are constructed by K-means clustering. To build a time-series forecasting model, a multi layer preceptron (MLP) is used. Once created, the models are updated in the model library to provide an adaptive environment for the proposed system. Graphical user interface (GUI) illustrates the variation of all sensor values affecting a particular alarm/fault, as well as the step-by-step procedure for avoiding critical situations and consequent plant shutdown. The forecasting performance is evaluated by computing the mean absolute error and root mean square error of the predictions.

Failure detection and correction for turbofan engines

NASA Technical Reports Server (NTRS)

Corley, R. C.; Spang, H. A., III

1977-01-01

In this paper, a failure detection and correction strategy for turbofan engines is discussed. This strategy allows continuing control of the engines in the event of a sensor failure. An extended Kalman filter is used to provide the best estimate of the state of the engine based on currently available sensor outputs. Should a sensor failure occur the control is based on the best estimate rather than the sensor output. The extended Kalman filter consists of essentially two parts, a nonlinear model of the engine and up-date logic which causes the model to track the actual engine. Details on the model and up-date logic are presented. To allow implementation, approximations are made to the feedback gain matrix which result in a single feedback matrix which is suitable for use over the entire flight envelope. The effect of these approximations on stability and response is discussed. Results from a detailed nonlinear simulation indicate that good control can be maintained even under multiple failures.

Rapid Structural Design Change Evaluation with AN Experiment Based FEM

NASA Astrophysics Data System (ADS)

Chu, C.-H.; Trethewey, M. W.

1998-04-01

The work in this paper proposes a dynamic structural design model that can be developed in a rapid fashion. The approach endeavours to produce a simplified FEM developed in conjunction with an experimental modal database. The FEM is formulated directly from the geometry and connectivity used in an experimental modal test using beam/frame elements. The model sacrifices fine detail for a rapid development time. The FEM is updated at the element level so the dynamic response replicates the experimental results closely. The physical attributes of the model are retained, making it well suited to evaluate the effect of potential design changes. The capabilities are evaluated in a series of computational and laboratory tests. First, a study is performed with a simulated cantilever beam with a variable mass and stiffness distribution. The modal characteristics serve as the updating target with random noise added to simulate experimental uncertainty. A uniformly distributed FEM is developed and updated. The results show excellent results, all natural frequencies are within 0·001% with MAC values above 0·99. Next, the method is applied to predict the dynamic changes of a hardware portal frame structure for a radical design change. Natural frequency predictions from the original FEM differ by as much as almost 18% with reasonable MAC values. The results predicted from the updated model produce excellent results when compared to the actual hardware changes, the first five modal natural frequency difference is around 5% and the corresponding mode shapes producing MAC values above 0·98.

Dose conversion coefficients for neutron exposure to the lens of the human eye.

PubMed

Manger, R P; Bellamy, M B; Eckerman, K F

2012-03-01

Dose conversion coefficients for the lens of the human eye have been calculated for neutron exposure at energies from 1 × 10(-9) to 20 MeV and several standard orientations: anterior-to-posterior, rotational and right lateral. MCNPX version 2.6.0, a Monte Carlo-based particle transport package, was used to determine the energy deposited in the lens of the eye. The human eyeball model was updated by partitioning the lens into sensitive and insensitive volumes as the anterior portion (sensitive volume) of the lens being more radiosensitive and prone to cataract formation. The updated eye model was used with the adult UF-ORNL mathematical phantom in the MCNPX transport calculations.

Damage identification via asymmetric active magnetic bearing acceleration feedback control

NASA Astrophysics Data System (ADS)

Zhao, Jie; DeSmidt, Hans; Yao, Wei

2015-04-01

A Floquet-based damage detection methodology for cracked rotor systems is developed and demonstrated on a shaft-disk system. This approach utilizes measured changes in the system natural frequencies to estimate the severity and location of shaft structural cracks during operation. The damage detection algorithms are developed with the initial guess solved by least square method and iterative damage parameter vector by updating the eigenvector updating. Active Magnetic Bearing is introduced to break the symmetric structure of rotor system and the tuning range of proper stiffness/virtual mass gains is studied. The system model is built based on energy method and the equations of motion are derived by applying assumed modes method and Lagrange Principle. In addition, the crack model is based on the Strain Energy Release Rate (SERR) concept in fracture mechanics. Finally, the method is synthesized via harmonic balance and numerical examples for a shaft/disk system demonstrate the effectiveness in detecting both location and severity of the structural damage.

Orientation Modeling for Amateur Cameras by Matching Image Line Features and Building Vector Data

NASA Astrophysics Data System (ADS)

Hung, C. H.; Chang, W. C.; Chen, L. C.

2016-06-01

With the popularity of geospatial applications, database updating is getting important due to the environmental changes over time. Imagery provides a lower cost and efficient way to update the database. Three dimensional objects can be measured by space intersection using conjugate image points and orientation parameters of cameras. However, precise orientation parameters of light amateur cameras are not always available due to their costliness and heaviness of precision GPS and IMU. To automatize data updating, the correspondence of object vector data and image may be built to improve the accuracy of direct georeferencing. This study contains four major parts, (1) back-projection of object vector data, (2) extraction of image feature lines, (3) object-image feature line matching, and (4) line-based orientation modeling. In order to construct the correspondence of features between an image and a building model, the building vector features were back-projected onto the image using the initial camera orientation from GPS and IMU. Image line features were extracted from the imagery. Afterwards, the matching procedure was done by assessing the similarity between the extracted image features and the back-projected ones. Then, the fourth part utilized line features in orientation modeling. The line-based orientation modeling was performed by the integration of line parametric equations into collinearity condition equations. The experiment data included images with 0.06 m resolution acquired by Canon EOS Mark 5D II camera on a Microdrones MD4-1000 UAV. Experimental results indicate that 2.1 pixel accuracy may be reached, which is equivalent to 0.12 m in the object space.

Real-time projections of cholera outbreaks through data assimilation and rainfall forecasting

NASA Astrophysics Data System (ADS)

Pasetto, Damiano; Finger, Flavio; Rinaldo, Andrea; Bertuzzo, Enrico

2017-10-01

Although treatment for cholera is well-known and cheap, outbreaks in epidemic regions still exact high death tolls mostly due to the unpreparedness of health care infrastructures to face unforeseen emergencies. In this context, mathematical models for the prediction of the evolution of an ongoing outbreak are of paramount importance. Here, we test a real-time forecasting framework that readily integrates new information as soon as available and periodically issues an updated forecast. The spread of cholera is modeled by a spatially-explicit scheme that accounts for the dynamics of susceptible, infected and recovered individuals hosted in different local communities connected through hydrologic and human mobility networks. The framework presents two major innovations for cholera modeling: the use of a data assimilation technique, specifically an ensemble Kalman filter, to update both state variables and parameters based on the observations, and the use of rainfall forecasts to force the model. The exercise of simulating the state of the system and the predictive capabilities of the novel tools, set at the initial phase of the 2010 Haitian cholera outbreak using only information that was available at that time, serves as a benchmark. Our results suggest that the assimilation procedure with the sequential update of the parameters outperforms calibration schemes based on Markov chain Monte Carlo. Moreover, in a forecasting mode the model usefully predicts the spatial incidence of cholera at least one month ahead. The performance decreases for longer time horizons yet allowing sufficient time to plan for deployment of medical supplies and staff, and to evaluate alternative strategies of emergency management.

A prediction model for colon cancer surveillance data.

PubMed

Good, Norm M; Suresh, Krithika; Young, Graeme P; Lockett, Trevor J; Macrae, Finlay A; Taylor, Jeremy M G

2015-08-15

Dynamic prediction models make use of patient-specific longitudinal data to update individualized survival probability predictions based on current and past information. Colonoscopy (COL) and fecal occult blood test (FOBT) results were collected from two Australian surveillance studies on individuals characterized as high-risk based on a personal or family history of colorectal cancer. Motivated by a Poisson process, this paper proposes a generalized nonlinear model with a complementary log-log link as a dynamic prediction tool that produces individualized probabilities for the risk of developing advanced adenoma or colorectal cancer (AAC). This model allows predicted risk to depend on a patient's baseline characteristics and time-dependent covariates. Information on the dates and results of COLs and FOBTs were incorporated using time-dependent covariates that contributed to patient risk of AAC for a specified period following the test result. These covariates serve to update a person's risk as additional COL, and FOBT test information becomes available. Model selection was conducted systematically through the comparison of Akaike information criterion. Goodness-of-fit was assessed with the use of calibration plots to compare the predicted probability of event occurrence with the proportion of events observed. Abnormal COL results were found to significantly increase risk of AAC for 1 year following the test. Positive FOBTs were found to significantly increase the risk of AAC for 3 months following the result. The covariates that incorporated the updated test results were of greater significance and had a larger effect on risk than the baseline variables. Copyright © 2015 John Wiley & Sons, Ltd.

Application of tissue time course data to elucidate mechanistic details of carbon tetrachloride (CC14) transport using an updated physiologically based pharmacokinetic (PBPK) model in rats

EPA Science Inventory

CCl4 is a common environmental contaminant in water and superfund sites, and a model liver toxicant. One application of PBPK models used in risk assessment is simulation of internal dose for the metric involved with toxicity, particularly for different routes of exposure. Time-co...

12 CFR Appendix H to Part 222 - Appendix H-Model Forms for Risk-Based Pricing and Credit Score Disclosure Exception Notices

Code of Federal Regulations, 2012 CFR

2012-01-01

... appendix are models; their use is optional. 3. A person may change the forms by rearranging the format or... when rearranging the format of the model forms. a. Acceptable changes include, for example: i. Corrections or updates to telephone numbers, mailing addresses, or Web site addresses that may change over...

Integration of Models of Building Interiors with Cadastral Data

NASA Astrophysics Data System (ADS)

Gotlib, Dariusz; Karabin, Marcin

2017-12-01

Demands for applications which use models of building interiors is growing and highly diversified. Those models are applied at the stage of designing and construction of a building, in applications which support real estate management, in navigation and marketing systems and, finally, in crisis management and security systems. They are created on the basis of different data: architectural and construction plans, both, in the analogue form, as well as CAD files, BIM data files, by means of laser scanning (TLS) and conventional surveys. In this context the issue of searching solutions which would integrate the existing models and lead to elimination of data redundancy is becoming more important. The authors analysed the possible input- of cadastral data (legal extent of premises) at the stage of the creation and updating different models of building's interiors. The paper focuses on one issue - the way of describing the geometry of premises basing on the most popular source data, i.e. architectural and construction plans. However, the described rules may be considered as universal and also may be applied in practice concerned may be used during the process of creation and updating indoor models based on BIM dataset or laser scanning clouds

Adapting to change: The role of the right hemisphere in mental model building and updating.

PubMed

Filipowicz, Alex; Anderson, Britt; Danckert, James

2016-09-01

We recently proposed that the right hemisphere plays a crucial role in the processes underlying mental model building and updating. Here, we review the evidence we and others have garnered to support this novel account of right hemisphere function. We begin by presenting evidence from patient work that suggests a critical role for the right hemisphere in the ability to learn from the statistics in the environment (model building) and adapt to environmental change (model updating). We then provide a review of neuroimaging research that highlights a network of brain regions involved in mental model updating. Next, we outline specific roles for particular regions within the network such that the anterior insula is purported to maintain the current model of the environment, the medial prefrontal cortex determines when to explore new or alternative models, and the inferior parietal lobule represents salient and surprising information with respect to the current model. We conclude by proposing some future directions that address some of the outstanding questions in the field of mental model building and updating. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The 2006 Cape Canaveral Air Force Station Range Reference Atmosphere Model Validation Study and Sensitivity Analysis to the National Aeronautics and Space Administration's Space Shuttle

NASA Technical Reports Server (NTRS)

Burns, Lee; Merry, Carl; Decker, Ryan; Harrington, Brian

2008-01-01

The 2006 Cape Canaveral Air Force Station (CCAFS) Range Reference Atmosphere (RRA) is a statistical model summarizing the wind and thermodynamic atmospheric variability from surface to 70 kin. Launches of the National Aeronautics and Space Administration's (NASA) Space Shuttle from Kennedy Space Center utilize CCAFS RRA data to evaluate environmental constraints on various aspects of the vehicle during ascent. An update to the CCAFS RRA was recently completed. As part of the update, a validation study on the 2006 version was conducted as well as a comparison analysis of the 2006 version to the existing CCAFS RRA database version 1983. Assessments to the Space Shuttle vehicle ascent profile characteristics were performed to determine impacts of the updated model to the vehicle performance. Details on the model updates and the vehicle sensitivity analyses with the update model are presented.

Application and Evaluation of MODIS LAI, FPAR, and Albedo ...

EPA Pesticide Factsheets

MODIS vegetation and albedo products provide a more realistic representation of surface conditions for input to the WRF/CMAQ modeling system. However, the initial evaluation of ingesting MODIS data into the system showed mixed results, with increased bias and error for 2-m temperature and reduced bias and error for 2-m mixing ratio. Recently, the WRF/CMAQ land surface and boundary laywer processes have been updated. In this study, MODIS vegetation and albedo data are input to the updated WRF/CMAQ meteorology and air quality simulations for 2006 over a North American (NA) 12-km domain. The evaluation of the simulation results shows that the updated WRF/CMAQ system improves 2-m temperature estimates over the pre-update base modeling system estimates. The MODIS vegetation input produces a realistic spring green-up that progresses through time from the south to north. Overall, MODIS input reduces 2-m mixing ration bias during the growing season. The NA west shows larger positive O3 bias during the growing season because of reduced gas phase deposition resulting from lower O3 deposition velocities driven by reduced vegetation cover. The O3 bias increase associated with the realistic vegetation representation indicates that further improvement may be needed in the WRF/CMAQ system. The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment. AMAD’s rese

Open Pit Mine 3d Mapping by Tls and Digital Photogrammetry: 3d Model Update Thanks to a Slam Based Approach

NASA Astrophysics Data System (ADS)

Vassena, G.; Clerici, A.

2018-05-01

The state of the art of 3D surveying technologies, if correctly applied, allows to obtain 3D coloured models of large open pit mines using different technologies as terrestrial laser scanner (TLS), with images, combined with UAV based digital photogrammetry. GNSS and/or total station are also currently used to geo reference the model. The University of Brescia has been realised a project to map in 3D an open pit mine located in Botticino, a famous location of marble extraction close to Brescia in North Italy. Terrestrial Laser Scanner 3D point clouds combined with RGB images and digital photogrammetry from UAV have been used to map a large part of the cave. By rigorous and well know procedures a 3D point cloud and mesh model have been obtained using an easy and rigorous approach. After the description of the combined mapping process, the paper describes the innovative process proposed for the daily/weekly update of the model itself. To realize this task a SLAM technology approach is described, using an innovative approach based on an innovative instrument capable to run an automatic localization process and real time on the field change detection analysis.

Simplifying Bridge Expansion Joint Design and Maintenance

DOT National Transportation Integrated Search

2011-10-19

This report presents a study focused on identifying the most durable expansion joints for the South : Carolina Department of Transportation. This is performed by proposing a degradation model for the : expansion joints and updating it based on bridge...

Artificial Boundary Conditions for Finite Element Model Update and Damage Detection

DTIC Science & Technology

2017-03-01

BOUNDARY CONDITIONS FOR FINITE ELEMENT MODEL UPDATE AND DAMAGE DETECTION by Emmanouil Damanakis March 2017 Thesis Advisor: Joshua H. Gordis...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE ARTIFICIAL BOUNDARY CONDITIONS FOR FINITE ELEMENT MODEL UPDATE AND DAMAGE DETECTION...release. Distribution is unlimited. 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) In structural engineering, a finite element model is often

An Investigation Into the Effects of Frequency Response Function Estimators on Model Updating

NASA Astrophysics Data System (ADS)

Ratcliffe, M. J.; Lieven, N. A. J.

1999-03-01

Model updating is a very active research field, in which significant effort has been invested in recent years. Model updating methodologies are invariably successful when used on noise-free simulated data, but tend to be unpredictable when presented with real experimental data that are—unavoidably—corrupted with uncorrelated noise content. In the development and validation of model-updating strategies, a random zero-mean Gaussian variable is added to simulated test data to tax the updating routines more fully. This paper proposes a more sophisticated model for experimental measurement noise, and this is used in conjunction with several different frequency response function estimators, from the classical H1and H2to more refined estimators that purport to be unbiased. Finite-element model case studies, in conjunction with a genuine experimental test, suggest that the proposed noise model is a more realistic representation of experimental noise phenomena. The choice of estimator is shown to have a significant influence on the viability of the FRF sensitivity method. These test cases find that the use of the H2estimator for model updating purposes is contraindicated, and that there is no advantage to be gained by using the sophisticated estimators over the classical H1estimator.

Adaptation of clinical prediction models for application in local settings.

PubMed

Kappen, Teus H; Vergouwe, Yvonne; van Klei, Wilton A; van Wolfswinkel, Leo; Kalkman, Cor J; Moons, Karel G M

2012-01-01

When planning to use a validated prediction model in new patients, adequate performance is not guaranteed. For example, changes in clinical practice over time or a different case mix than the original validation population may result in inaccurate risk predictions. To demonstrate how clinical information can direct updating a prediction model and development of a strategy for handling missing predictor values in clinical practice. A previously derived and validated prediction model for postoperative nausea and vomiting was updated using a data set of 1847 patients. The update consisted of 1) changing the definition of an existing predictor, 2) reestimating the regression coefficient of a predictor, and 3) adding a new predictor to the model. The updated model was then validated in a new series of 3822 patients. Furthermore, several imputation models were considered to handle real-time missing values, so that possible missing predictor values could be anticipated during actual model use. Differences in clinical practice between our local population and the original derivation population guided the update strategy of the prediction model. The predictive accuracy of the updated model was better (c statistic, 0.68; calibration slope, 1.0) than the original model (c statistic, 0.62; calibration slope, 0.57). Inclusion of logistical variables in the imputation models, besides observed patient characteristics, contributed to a strategy to deal with missing predictor values at the time of risk calculation. Extensive knowledge of local, clinical processes provides crucial information to guide the process of adapting a prediction model to new clinical practices.

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

NASA Technical Reports Server (NTRS)

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.

Calibrating random forests for probability estimation.

PubMed

Dankowski, Theresa; Ziegler, Andreas

2016-09-30

Probabilities can be consistently estimated using random forests. It is, however, unclear how random forests should be updated to make predictions for other centers or at different time points. In this work, we present two approaches for updating random forests for probability estimation. The first method has been proposed by Elkan and may be used for updating any machine learning approach yielding consistent probabilities, so-called probability machines. The second approach is a new strategy specifically developed for random forests. Using the terminal nodes, which represent conditional probabilities, the random forest is first translated to logistic regression models. These are, in turn, used for re-calibration. The two updating strategies were compared in a simulation study and are illustrated with data from the German Stroke Study Collaboration. In most simulation scenarios, both methods led to similar improvements. In the simulation scenario in which the stricter assumptions of Elkan's method were not met, the logistic regression-based re-calibration approach for random forests outperformed Elkan's method. It also performed better on the stroke data than Elkan's method. The strength of Elkan's method is its general applicability to any probability machine. However, if the strict assumptions underlying this approach are not met, the logistic regression-based approach is preferable for updating random forests for probability estimation. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Digital filtering and model updating methods for improving the robustness of near-infrared multivariate calibrations.

PubMed

Kramer, Kirsten E; Small, Gary W

2009-02-01

Fourier transform near-infrared (NIR) transmission spectra are used for quantitative analysis of glucose for 17 sets of prediction data sampled as much as six months outside the timeframe of the corresponding calibration data. Aqueous samples containing physiological levels of glucose in a matrix of bovine serum albumin and triacetin are used to simulate clinical samples such as blood plasma. Background spectra of a single analyte-free matrix sample acquired during the instrumental warm-up period on the prediction day are used for calibration updating and for determining the optimal frequency response of a preprocessing infinite impulse response time-domain digital filter. By tuning the filter and the calibration model to the specific instrumental response associated with the prediction day, the calibration model is given enhanced ability to operate over time. This methodology is demonstrated in conjunction with partial least squares calibration models built with a spectral range of 4700-4300 cm(-1). By using a subset of the background spectra to evaluate the prediction performance of the updated model, projections can be made regarding the success of subsequent glucose predictions. If a threshold standard error of prediction (SEP) of 1.5 mM is used to establish successful model performance with the glucose samples, the corresponding threshold for the SEP of the background spectra is found to be 1.3 mM. For calibration updating in conjunction with digital filtering, SEP values of all 17 prediction sets collected over 3-178 days displaced from the calibration data are below 1.5 mM. In addition, the diagnostic based on the background spectra correctly assesses the prediction performance in 16 of the 17 cases.

A review and update of the Virginia Department of Transportation cash flow forecasting model.

DOT National Transportation Integrated Search

1996-01-01

This report details the research done to review and update components of the VDOT cash flow forecasting model. Specifically, the study updated the monthly factors submodel used to predict payments on construction contracts. For the other submodel rev...

Solar radiation on Mars: Update 1990

NASA Technical Reports Server (NTRS)

Appelbaum, Joseph; Flood, Dennis J.

1990-01-01

Detailed information on solar radiation characteristics on Mars are necessary for effective design of future planned solar energy systems operating on the surface of Mars. The authors present a procedure and solar radiation related data from which the diurnally and daily variation of the global, direct beam and diffuse insolation on Mars are calculated. The radiation data are based on measured optical depth of the Martian atmosphere derived from images taken of the Sun with a special diode on the Viking Lander cameras and computation based on multiple wavelength and multiple scattering of the solar radiation. This work is an update to NASA-TM-102299 and includes a refinement of the solar radiation model.

Advanced Test Reactor Core Modeling Update Project Annual Report for Fiscal Year 2011

DOE Office of Scientific and Technical Information (OSTI.GOV)

David W. Nigg; Devin A. Steuhm

2011-09-01

Legacy computational reactor physics software tools and protocols currently used for support of Advanced Test Reactor (ATR) core fuel management and safety assurance and, to some extent, experiment management are obsolete, inconsistent with the state of modern nuclear engineering practice, and are becoming increasingly difficult to properly verify and validate (V&V). Furthermore, the legacy staff knowledge required for application of these tools and protocols from the 1960s and 1970s is rapidly being lost due to staff turnover and retirements. In 2009 the Idaho National Laboratory (INL) initiated a focused effort to address this situation through the introduction of modern high-fidelitymore » computational software and protocols, with appropriate V&V, within the next 3-4 years via the ATR Core Modeling and Simulation and V&V Update (or 'Core Modeling Update') Project. This aggressive computational and experimental campaign will have a broad strategic impact on the operation of the ATR, both in terms of improved computational efficiency and accuracy for support of ongoing DOE programs as well as in terms of national and international recognition of the ATR National Scientific User Facility (NSUF). The ATR Core Modeling Update Project, targeted for full implementation in phase with the anticipated ATR Core Internals Changeout (CIC) in the 2014 time frame, began during the last quarter of Fiscal Year 2009, and has just completed its first full year. Key accomplishments so far have encompassed both computational as well as experimental work. A new suite of stochastic and deterministic transport theory based reactor physics codes and their supporting nuclear data libraries (SCALE, KENO-6, HELIOS, NEWT, and ATTILA) have been installed at the INL under various permanent sitewide license agreements and corresponding baseline models of the ATR and ATRC are now operational, demonstrating the basic feasibility of these code packages for their intended purpose. Furthermore, a capability for rigorous sensitivity analysis and uncertainty quantification based on the TSUNAMI system is being implemented and initial computational results have been obtained. This capability will have many applications in 2011 and beyond as a tool for understanding the margins of uncertainty in the new models as well as for validation experiment design and interpretation. Finally we note that although full implementation of the new computational models and protocols will extend over a period 3-4 years as noted above, interim applications in the much nearer term have already been demonstrated. In particular, these demonstrations included an analysis that was useful for understanding the cause of some issues in December 2009 that were triggered by a larger than acceptable discrepancy between the measured excess core reactivity and a calculated value that was based on the legacy computational methods. As the Modeling Update project proceeds we anticipate further such interim, informal, applications in parallel with formal qualification of the system under the applicable INL Quality Assurance procedures and standards.« less

General Separations Area (GSA) Groundwater Flow Model Update: Hydrostratigraphic Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bagwell, L.; Bennett, P.; Flach, G.

2017-02-21

This document describes the assembly, selection, and interpretation of hydrostratigraphic data for input to an updated groundwater flow model for the General Separations Area (GSA; Figure 1) at the Department of Energy’s (DOE) Savannah River Site (SRS). This report is one of several discrete but interrelated tasks that support development of an updated groundwater model (Bagwell and Flach, 2016).

Non-local gravity and comparison with observational datasets. II. Updated results and Bayesian model comparison with ΛCDM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dirian, Yves; Foffa, Stefano; Kunz, Martin

We present a comprehensive and updated comparison with cosmological observations of two non-local modifications of gravity previously introduced by our group, the so called RR and RT models. We implement the background evolution and the cosmological perturbations of the models in a modified Boltzmann code, using CLASS. We then test the non-local models against the Planck 2015 TT, TE, EE and Cosmic Microwave Background (CMB) lensing data, isotropic and anisotropic Baryonic Acoustic Oscillations (BAO) data, JLA supernovae, H {sub 0} measurements and growth rate data, and we perform Bayesian parameter estimation. We then compare the RR, RT and ΛCDM models,more » using the Savage-Dickey method. We find that the RT model and ΛCDM perform equally well, while the performance of the RR model with respect to ΛCDM depends on whether or not we include a prior on H {sub 0} based on local measurements.« less

Model compilation: An approach to automated model derivation

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Baudin, Catherine; Iwasaki, Yumi; Nayak, Pandurang; Tanaka, Kazuo

1990-01-01

An approach is introduced to automated model derivation for knowledge based systems. The approach, model compilation, involves procedurally generating the set of domain models used by a knowledge based system. With an implemented example, how this approach can be used to derive models of different precision and abstraction is illustrated, and models are tailored to different tasks, from a given set of base domain models. In particular, two implemented model compilers are described, each of which takes as input a base model that describes the structure and behavior of a simple electromechanical device, the Reaction Wheel Assembly of NASA's Hubble Space Telescope. The compilers transform this relatively general base model into simple task specific models for troubleshooting and redesign, respectively, by applying a sequence of model transformations. Each transformation in this sequence produces an increasingly more specialized model. The compilation approach lessens the burden of updating and maintaining consistency among models by enabling their automatic regeneration.

A Long-Term Performance Enhancement Method for FOG-Based Measurement While Drilling

PubMed Central

Zhang, Chunxi; Lin, Tie

2016-01-01

In the oil industry, the measurement-while-drilling (MWD) systems are usually used to provide the real-time position and orientation of the bottom hole assembly (BHA) during drilling. However, the present MWD systems based on magnetic surveying technology can barely ensure good performance because of magnetic interference phenomena. In this paper, a MWD surveying system based on a fiber optic gyroscope (FOG) was developed to replace the magnetic surveying system. To accommodate the size of the downhole drilling conditions, a new design method is adopted. In order to realize long-term and high position precision and orientation surveying, an integrated surveying algorithm is proposed based on inertial navigation system (INS) and drilling features. In addition, the FOG-based MWD error model is built and the drilling features are analyzed. The state-space system model and the observation updates model of the Kalman filter are built. To validate the availability and utility of the algorithm, the semi-physical simulation is conducted under laboratory conditions. The results comparison with the traditional algorithms show that the errors were suppressed and the measurement precision of the proposed algorithm is better than the traditional ones. In addition, the proposed method uses a lot less time than the zero velocity update (ZUPT) method. PMID:27483270

A Long-Term Performance Enhancement Method for FOG-Based Measurement While Drilling.

PubMed

Zhang, Chunxi; Lin, Tie

2016-07-28

In the oil industry, the measurement-while-drilling (MWD) systems are usually used to provide the real-time position and orientation of the bottom hole assembly (BHA) during drilling. However, the present MWD systems based on magnetic surveying technology can barely ensure good performance because of magnetic interference phenomena. In this paper, a MWD surveying system based on a fiber optic gyroscope (FOG) was developed to replace the magnetic surveying system. To accommodate the size of the downhole drilling conditions, a new design method is adopted. In order to realize long-term and high position precision and orientation surveying, an integrated surveying algorithm is proposed based on inertial navigation system (INS) and drilling features. In addition, the FOG-based MWD error model is built and the drilling features are analyzed. The state-space system model and the observation updates model of the Kalman filter are built. To validate the availability and utility of the algorithm, the semi-physical simulation is conducted under laboratory conditions. The results comparison with the traditional algorithms show that the errors were suppressed and the measurement precision of the proposed algorithm is better than the traditional ones. In addition, the proposed method uses a lot less time than the zero velocity update (ZUPT) method.

Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management

USGS Publications Warehouse

Coates, Peter S.; Casazza, Michael L.; Brussee, Brianne E.; Ricca, Mark A.; Gustafson, K. Benjamin; Sanchez-Chopitea, Erika; Mauch, Kimberly; Niell, Lara; Gardner, Scott; Espinosa, Shawn; Delehanty, David J.

2016-05-20

Successful adaptive management hinges largely upon integrating new and improved sources of information as they become available. As a timely example of this tenet, we updated a management decision support tool that was previously developed for greater sage-grouse (Centrocercus urophasianus, hereinafter referred to as “sage-grouse”) populations in Nevada and California. Specifically, recently developed spatially explicit habitat maps derived from empirical data played a key role in the conservation of this species facing listing under the Endangered Species Act. This report provides an updated process for mapping relative habitat suitability and management categories for sage-grouse in Nevada and northeastern California (Coates and others, 2014, 2016). These updates include: (1) adding radio and GPS telemetry locations from sage-grouse monitored at multiple sites during 2014 to the original location dataset beginning in 1998; (2) integrating output from high resolution maps (1–2 m2) of sagebrush and pinyon-juniper cover as covariates in resource selection models; (3) modifying the spatial extent of the analyses to match newly available vegetation layers; (4) explicit modeling of relative habitat suitability during three seasons (spring, summer, winter) that corresponded to critical life history periods for sage-grouse (breeding, brood-rearing, over-wintering); (5) accounting for differences in habitat availability between more mesic sagebrush steppe communities in the northern part of the study area and drier Great Basin sagebrush in more southerly regions by categorizing continuous region-wide surfaces of habitat suitability index (HSI) with independent locations falling within two hydrological zones; (6) integrating the three seasonal maps into a composite map of annual relative habitat suitability; (7) deriving updated land management categories based on previously determined cut-points for intersections of habitat suitability and an updated index of sage-grouse abundance and space-use (AUI); and (8) masking urban footprints and major roadways out of the final map products.Seasonal habitat maps were generated based on model-averaged resource selection functions (RSF) derived for 10 project areas (813 sage-grouse; 14,085 locations) during the spring season, 10 during the summer season (591 sage-grouse, 11,743 locations), and 7 during the winter season (288 sage-grouse, 4,862 locations). RSF surfaces were transformed to HSIs and averaged in a GIS framework for every pixel for each season. Validation analyses of categorized HSI surfaces using a suite of independent datasets resulted in an agreement of 93–97 percent for habitat versus non-habitat on an annual basis. Spring and summer maps validated similarly well at 94–97 percent, while winter maps validated slightly less accurately at 87–93 percent.We then provide an updated example of how space use models can be integrated with habitat models to help inform conservation planning. We used updated lek count data to calculate a composite abundance and space use index (AUI) that comprised the combination of probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek. The AUI was then classified into two categories of use (high and low-to-no) and intersected with the HSI categories to create potential management prioritization scenarios based on information about sage-grouse occupancy coupled with habitat suitability. Compared to Coates and others (2014, 2016), the amount of area classified as habitat across the region increased by 6.5 percent (approximately 1,700,000 acres). For management categories, core increased by 7.2 percent (approximately 865,000 acres), priority increased by 9.6 percent (approximately 855,000 acres), and general increased by 9.2 percent (approximately 768,000 acres), while non-habitat decreased (that is, classified non-habitat occurring outside of areas of concentrated use) by 11.9 percent (approximately 2,500,000 acres). Importantly, seasonal and annual maps represent habitat for all age and sex classes of sage-grouse (that is, sample sizes of marked grouse were insufficient to only construct models for reproductive females). This revised sage-grouse habitat mapping product helps improve adaptive application of conservation planning tools based on intersections of spatially explicit habitat suitability, abundance, and space use indices.

Dynamic analysis of I cross beam section dissimilar plate joined by TIG welding

NASA Astrophysics Data System (ADS)

Sani, M. S. M.; Nazri, N. A.; Rani, M. N. Abdul; Yunus, M. A.

2018-04-01

In this paper, finite element (FE) joint modelling technique for prediction of dynamic properties of sheet metal jointed by tungsten inert gas (TTG) will be presented. I cross section dissimilar flat plate with different series of aluminium alloy; AA7075 and AA6061 joined by TTG are used. In order to find the most optimum set of TTG welding dissimilar plate, the finite element model with three types of joint modelling were engaged in this study; bar element (CBAR), beam element and spot weld element connector (CWELD). Experimental modal analysis (EMA) was carried out by impact hammer excitation on the dissimilar plates that welding by TTG method. Modal properties of FE model with joints were compared and validated with model testing. CWELD element was chosen to represent weld model for TTG joints due to its accurate prediction of mode shapes and contains an updating parameter for weld modelling compare to other weld modelling. Model updating was performed to improve correlation between EMA and FEA and before proceeds to updating, sensitivity analysis was done to select the most sensitive updating parameter. After perform model updating, average percentage of error of the natural frequencies for CWELD model is improved significantly.

Test and analysis procedures for updating math models of Space Shuttle payloads

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.

1991-01-01

Over the next decade or more, the Space Shuttle will continue to be the primary transportation system for delivering payloads to Earth orbit. Although a number of payloads have already been successfully carried by the Space Shuttle in the payload bay of the Orbiter vehicle, there continues to be a need for evaluation of the procedures used for verifying and updating the math models of the payloads. The verified payload math models is combined with an Orbiter math model for the coupled-loads analysis, which is required before any payload can fly. Several test procedures were employed for obtaining data for use in verifying payload math models and for carrying out the updating of the payload math models. Research was directed at the evaluation of test/update procedures for use in the verification of Space Shuttle payload math models. The following research tasks are summarized: (1) a study of free-interface test procedures; (2) a literature survey and evaluation of model update procedures; and (3) the design and construction of a laboratory payload simulator.

Build-up Approach to Updating the Mock Quiet Spike(TradeMark) Beam Model

NASA Technical Reports Server (NTRS)

Herrera, Claudia Y.; Pak, Chan-gi

2007-01-01

A crucial part of aircraft design is ensuring that the required margin for flutter is satisfied. A trustworthy flutter analysis, which begins by possessing an accurate dynamics model, is necessary for this task. Traditionally, a model was updated manually by fine tuning specific stiffness parameters until the analytical results matched test data. This is a time consuming iterative process. NASA Dryden Flight Research Center has developed a mode matching code to execute this process in a more efficient manner. Recently, this code was implemented in the F-15B/Quiet Spike(TradeMark) (Gulfstream Aerospace Corporation, Savannah, Georgia) model update. A build-up approach requiring several ground vibration test configurations and a series of model updates was implemented in order to determine the connection stiffness between aircraft and test article. The mode matching code successfully updated various models for the F-15B/Quiet Spike(TradeMark) project to within 1 percent error in frequency and the modal assurance criteria values ranged from 88.51-99.42 percent.

Build-up Approach to Updating the Mock Quiet Spike(TM)Beam Model

NASA Technical Reports Server (NTRS)

Herrera, Claudia Y.; Pak, Chan-gi

2007-01-01

A crucial part of aircraft design is ensuring that the required margin for flutter is satisfied. A trustworthy flutter analysis, which begins by possessing an accurate dynamics model, is necessary for this task. Traditionally, a model was updated manually by fine tuning specific stiffness parameters until the analytical results matched test data. This is a time consuming iterative process. The NASA Dryden Flight Research Center has developed a mode matching code to execute this process in a more efficient manner. Recently, this code was implemented in the F-15B/Quiet Spike (Gulfstream Aerospace Corporation, Savannah, Georgia) model update. A build-up approach requiring several ground vibration test configurations and a series of model updates was implemented to determine the connection stiffness between aircraft and test article. The mode matching code successfully updated various models for the F-15B/Quiet Spike project to within 1 percent error in frequency and the modal assurance criteria values ranged from 88.51-99.42 percent.

Updates to the Demographic and Spatial Allocation Models to ...

EPA Pesticide Factsheets

EPA announced the availability of the draft report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) for a 30-day public comment period. The ICLUS version 2 (v2) modeling tool furthered land change modeling by providing nationwide housing development scenarios up to 2100. ICLUS V2 includes updated population and land use data sets and addressing limitations identified in ICLUS v1 in both the migration and spatial allocation models. The companion user guide describes the development of ICLUS v2 and the updates that were made to the original data sets and the demographic and spatial allocation models. [2017 UPDATE] Get the latest version of ICLUS and stay up-to-date by signing up to the ICLUS mailing list. The GIS tool enables users to run SERGoM with the population projections developed for the ICLUS project and allows users to modify the spatial allocation housing density across the landscape.

BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface

PubMed Central

Lee, A J; Cunningham, A P; Kuchenbaecker, K B; Mavaddat, N; Easton, D F; Antoniou, A C

2014-01-01

Background: The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) is a risk prediction model that is used to compute probabilities of carrying mutations in the high-risk breast and ovarian cancer susceptibility genes BRCA1 and BRCA2, and to estimate the future risks of developing breast or ovarian cancer. In this paper, we describe updates to the BOADICEA model that extend its capabilities, make it easier to use in a clinical setting and yield more accurate predictions. Methods: We describe: (1) updates to the statistical model to include cancer incidences from multiple populations; (2) updates to the distributions of tumour pathology characteristics using new data on BRCA1 and BRCA2 mutation carriers and women with breast cancer from the general population; (3) improvements to the computational efficiency of the algorithm so that risk calculations now run substantially faster; and (4) updates to the model's web interface to accommodate these new features and to make it easier to use in a clinical setting. Results: We present results derived using the updated model, and demonstrate that the changes have a significant impact on risk predictions. Conclusion: All updates have been implemented in a new version of the BOADICEA web interface that is now available for general use: http://ccge.medschl.cam.ac.uk/boadicea/. PMID:24346285

Catchment Tomography - Joint Estimation of Surface Roughness and Hydraulic Conductivity with the EnKF

NASA Astrophysics Data System (ADS)

Baatz, D.; Kurtz, W.; Hendricks Franssen, H. J.; Vereecken, H.; Kollet, S. J.

2017-12-01

Parameter estimation for physically based, distributed hydrological models becomes increasingly challenging with increasing model complexity. The number of parameters is usually large and the number of observations relatively small, which results in large uncertainties. A moving transmitter - receiver concept to estimate spatially distributed hydrological parameters is presented by catchment tomography. In this concept, precipitation, highly variable in time and space, serves as a moving transmitter. As response to precipitation, runoff and stream discharge are generated along different paths and time scales, depending on surface and subsurface flow properties. Stream water levels are thus an integrated signal of upstream parameters, measured by stream gauges which serve as the receivers. These stream water level observations are assimilated into a distributed hydrological model, which is forced with high resolution, radar based precipitation estimates. Applying a joint state-parameter update with the Ensemble Kalman Filter, the spatially distributed Manning's roughness coefficient and saturated hydraulic conductivity are estimated jointly. The sequential data assimilation continuously integrates new information into the parameter estimation problem, especially during precipitation events. Every precipitation event constrains the possible parameter space. In the approach, forward simulations are performed with ParFlow, a variable saturated subsurface and overland flow model. ParFlow is coupled to the Parallel Data Assimilation Framework for the data assimilation and the joint state-parameter update. In synthetic, 3-dimensional experiments including surface and subsurface flow, hydraulic conductivity and the Manning's coefficient are efficiently estimated with the catchment tomography approach. A joint update of the Manning's coefficient and hydraulic conductivity tends to improve the parameter estimation compared to a single parameter update, especially in cases of biased initial parameter ensembles. The computational experiments additionally show to which degree of spatial heterogeneity and to which degree of uncertainty of subsurface flow parameters the Manning's coefficient and hydraulic conductivity can be estimated efficiently.

Ground control system for the midcourse space experiment UTC clock

NASA Technical Reports Server (NTRS)

Dragonette, Richard

1994-01-01

One goal of the Midcourse Space Experiment (MSX) spacecraft Operations Planning Center is to maintain the onboard satellite UTC clock (UTC(MSX)) to within 1 millisecond of UTC(APL) (the program requirement is 10 msec). The UTC(MSX) clock employs as its time base an APL built 5 MHz quartz oscillator, which is expected to have frequency instabilities (aging rate + drift rate + frequency offset) that will cause the clock to drift approximately two to ten milliseconds per day. The UTC(MSX) clock can be advanced or retarded by the APL MSX satellite ground control center by integer multiples of 1 millisecond. The MSX Operations Planning Center is developing software which records the drift of UTC(MSX) relative to UTC(APL) and which schedules the time of day and magnitude of UTC(MSX) clock updates up to 48 hours in advance. Because of the manner in which MSX spacecraft activities are scheduled, MSX clock updates are planned 24 to 48 hours in advance, and stored in the satellite's computer controller for later execution. Data will be collected on the drift of UTC(MSX) relative to UTC(APL) over a three to five day period. Approximately six times per day, the time offset between UTC(MSX) and UTC(APL) will be measured by APL with a resolution of less than 100 microseconds. From this data a second order analytical model of the clock's drift will be derived. This model will be used to extrapolate the offset of the MSX clock in time from the present to 48 hours in the future. MSX clock updates will be placed on the spacecraft's daily schedule whenever the predicted clock offset exceeds 0.5 milliseconds. The paper includes a discussion of how the empirical model of the MSX clock is derived from satellite telemetry data, as well as the algorithm used to schedule MSX clock updates based on the model.

Results of investigations conducted in the LaRC 8-foot transonic pressure tunnel using the 0.010-scale 72-OTS model of the space shuttle integrated vehicle (IA93), volume 2

NASA Technical Reports Server (NTRS)

Nichols, M. E.

1976-01-01

Test procedures, history, and plotted coefficient data are presented for an aero-loads investigation on the updated configuration-5 space shuttle launch vehicle at Mach numbers from 0.600 to 1.205. Six-component vehicle forces and moments, base and sting-cavity pressures, elevon hinge moments, wing-root bending and torsion moments, and normal shear force data were obtained. Full simulation of updated vehicle protuberances and attach hardware was employed.

Error Quantification and Confidence Assessment of Aerothermal Model Predictions for Hypersonic Aircraft (Preprint)

DTIC Science & Technology

2013-09-01

based confidence metric is used to compare several different model predictions with the experimental data. II. Aerothermal Model Definition and...whereas 5% measurement uncertainty is assumed for aerodynamic pressure and heat flux measurements 4p y and 4Q y . Bayesian updating according... definitive conclusions for these particular aerodynamic models. However, given the confidence associated with the 4 sdp predictions for Run 30 (H/D

Dissociable effects of surprise and model update in parietal and anterior cingulate cortex

PubMed Central

O’Reilly, Jill X.; Schüffelgen, Urs; Cuell, Steven F.; Behrens, Timothy E. J.; Mars, Rogier B.; Rushworth, Matthew F. S.

2013-01-01

Brains use predictive models to facilitate the processing of expected stimuli or planned actions. Under a predictive model, surprising (low probability) stimuli or actions necessitate the immediate reallocation of processing resources, but they can also signal the need to update the underlying predictive model to reflect changes in the environment. Surprise and updating are often correlated in experimental paradigms but are, in fact, distinct constructs that can be formally defined as the Shannon information (IS) and Kullback–Leibler divergence (DKL) associated with an observation. In a saccadic planning task, we observed that distinct behaviors and brain regions are associated with surprise/IS and updating/DKL. Although surprise/IS was associated with behavioral reprogramming as indexed by slower reaction times, as well as with activity in the posterior parietal cortex [human lateral intraparietal area (LIP)], the anterior cingulate cortex (ACC) was specifically activated during updating of the predictive model (DKL). A second saccade-sensitive region in the inferior posterior parietal cortex (human 7a), which has connections to both LIP and ACC, was activated by surprise and modulated by updating. Pupillometry revealed a further dissociation between surprise and updating with an early positive effect of surprise and late negative effect of updating on pupil area. These results give a computational account of the roles of the ACC and two parietal saccade regions, LIP and 7a, by which their involvement in diverse tasks can be understood mechanistically. The dissociation of functional roles between regions within the reorienting/reprogramming network may also inform models of neurological phenomena, such as extinction and Balint syndrome, and neglect. PMID:23986499

Online coupled camera pose estimation and dense reconstruction from video

DOEpatents

Medioni, Gerard; Kang, Zhuoliang

2016-11-01

A product may receive each image in a stream of video image of a scene, and before processing the next image, generate information indicative of the position and orientation of an image capture device that captured the image at the time of capturing the image. The product may do so by identifying distinguishable image feature points in the image; determining a coordinate for each identified image feature point; and for each identified image feature point, attempting to identify one or more distinguishable model feature points in a three dimensional (3D) model of at least a portion of the scene that appears likely to correspond to the identified image feature point. Thereafter, the product may find each of the following that, in combination, produce a consistent projection transformation of the 3D model onto the image: a subset of the identified image feature points for which one or more corresponding model feature points were identified; and, for each image feature point that has multiple likely corresponding model feature points, one of the corresponding model feature points. The product may update a 3D model of at least a portion of the scene following the receipt of each video image and before processing the next video image base on the generated information indicative of the position and orientation of the image capture device at the time of capturing the received image. The product may display the updated 3D model after each update to the model.

Comparison of Models for Ball Bearing Dynamic Capacity and Life

NASA Technical Reports Server (NTRS)

Gupta, Pradeep K.; Oswald, Fred B.; Zaretsky, Erwin V.

2015-01-01

Generalized formulations for dynamic capacity and life of ball bearings, based on the models introduced by Lundberg and Palmgren and Zaretsky, have been developed and implemented in the bearing dynamics computer code, ADORE. Unlike the original Lundberg-Palmgren dynamic capacity equation, where the elastic properties are part of the life constant, the generalized formulations permit variation of elastic properties of the interacting materials. The newly updated Lundberg-Palmgren model allows prediction of life as a function of elastic properties. For elastic properties similar to those of AISI 52100 bearing steel, both the original and updated Lundberg-Palmgren models provide identical results. A comparison between the Lundberg-Palmgren and the Zaretsky models shows that at relatively light loads the Zaretsky model predicts a much higher life than the Lundberg-Palmgren model. As the load increases, the Zaretsky model provides a much faster drop off in life. This is because the Zaretsky model is much more sensitive to load than the Lundberg-Palmgren model. The generalized implementation where all model parameters can be varied provides an effective tool for future model validation and enhancement in bearing life prediction capabilities.

Chemical transport model simulations of organic aerosol in ...

EPA Pesticide Factsheets

Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we updated the organic aerosol module and organic emissions inventory of a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ), using recent, experimentally derived inputs and parameterizations for mobile sources. The updated model included a revised volatile organic compound (VOC) speciation for mobile sources and secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOCs). The updated model was used to simulate air quality in southern California during May and June 2010, when the California Research at the Nexus of Air Quality and Climate Change (CalNex) study was conducted. Compared to the Traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted organic aerosol (OA) mass concentrations but did substantially improve predictions of OA sources and composition (e.g., POA–SOA split), as well as ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performed similar to a recently released research version of CMAQ (Woody et al., 2016) that did not include the updated VOC and IVOC emissions and SOA data

Improved solar models constructed with a formulation of convection for stellar structure and evolution calculations without the mixing-length theory approximations

NASA Technical Reports Server (NTRS)

Lydon, Thomas J.; Fox, Peter A.; Sofia, Sabatino

1993-01-01

We have updated a previous attempt to incorporate within a solar model a treatment of convection based upon numerical simulations of convection rather than mixing-length theory (MLT). We have modified our formulation of convection for a better treatment of the kinetic energy flux. Our solar model has been updated to include a complete range of OPAL opacities, the Debye-Hueckel correction to the equation of state, helium diffusion due to gravitational settling, and atmospheres by Kurucz. We construct a series of models using both MLT and our revised formulation of convection and the compared results to measurements of the solar radius, the solar luminosity, and the depth of the solar convection zone as inferred from helioseismology. We find X(solar) = 0.702 +/- 0.005, Y(solar) = 0.278 +/- 0.005, and Z(solar) = 0.0193 +/- 0.0005.

DOT2: Macromolecular Docking With Improved Biophysical Models

PubMed Central

Roberts, Victoria A.; Thompson, Elaine E.; Pique, Michael E.; Perez, Martin S.; Eyck, Lynn Ten

2015-01-01

Computational docking is a useful tool for predicting macromolecular complexes, which are often difficult to determine experimentally. Here we present the DOT2 software suite, an updated version of the DOT intermolecular docking program. DOT2 provides straightforward, automated construction of improved biophysical models based on molecular coordinates, offering checkpoints that guide the user to include critical features. DOT has been updated to run more quickly, allow flexibility in grid size and spacing, and generate a complete list of favorable candidate configu-rations. Output can be filtered by experimental data and rescored by the sum of electrostatic and atomic desolvation energies. We show that this rescoring method improves the ranking of correct complexes for a wide range of macromolecular interactions, and demonstrate that biologically relevant models are essential for biologically relevant results. The flexibility and versatility of DOT2 accommodate realistic models of complex biological systems, improving the likelihood of a successful docking outcome. PMID:23695987

Assessment of NHTSA’s Report “Relationships Between Fatality Risk, Mass, and Footprint in Model Year 2000-2007 Passenger Cars and LTVs”

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wenzel, Tom

2012-08-01

NHTSA recently completed a logistic regression analysis updating its 2003 and 2010 studies of the relationship between vehicle mass and US fatality risk per vehicle mile traveled (VMT). The new study updates the previous analyses in several ways: updated FARS data from 2002 to 2008 for MY00 to MY07 vehicles are used; induced exposure data from police reported crashes in several additional states are added; a new vehicle category for car-based crossover utility vehicles (CUVs) and minivans is created; crashes with other light-duty vehicles are divided into two groups based on the crash partner vehicle’s weight, and a category formore » all other fatal crashes is added; and new control variables for new safety technologies and designs, such as electronic stability controls (ESC), side airbags, and methods to meet voluntary agreement to improve light truck compatibility with cars, are included.« less

A System for Supporting Development and Update of the International Classification of Health Interventions (ICHI).

PubMed

Donada, Marc; Della Mea, Vincenzo; Cumerlato, Megan; Rankin, Nicole; Madden, Richard

2018-01-01

The International Classification of Health Interventions (ICHI) is a member of the WHO Family of International Classifications, being developed to provide a common tool for reporting and analysing health interventions for statistical purposes. A web-based platform for classification development and update has been specifically developed to support the initial development step and then, after final approval, the continuous revision and update of the classification. The platform provides features for classification editing, versioning, comment management and URI identifiers. During the last 12 months it has been used for developing the ICHI Beta version, replacing the previous process based on the exchange of Excel files. At November 2017, 90 users have provided input to the development of the classification, which has resulted in 2913 comments and 2971 changes in the classification, since June 2017. Further work includes the development of an URI API for machine to machine communication, following the model established for ICD-11.

Assessment of NHTSA’s Report “Relationships Between Fatality Risk, Mass, and Footprint in Model Year 2000-2007 Passenger Cars and LTVs”

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wenzel, Tom

2011-09-01

NHTSA recently completed a logistic regression analysis updating its 2003 and 2010 studies of the relationship between vehicle mass and US fatality risk per vehicle mile traveled (VMT). The new study updates the previous analyses in several ways: updated FARS data from 2002 to 2008 for MY00 to MY07 vehicles are used; induced exposure data from police reported crashes in several additional states are added; a new vehicle category for car-based crossover utility vehicles (CUVs) and minivans is created; crashes with other light-duty vehicles are divided into two groups based on the crash partner vehicle’s weight, and a category formore » all other fatal crashes is added; and new control variables for new safety technologies and designs, such as electronic stability controls (ESC), side airbags, and methods to meet voluntary agreement to improve light truck compatibility with cars, are included.« less

An Analysis of the Relationship between Casualty Risk Per Crash and Vehicle Mass and Footprint for Model Year 2000-2007 Light-Duty Vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wenzel, Tom

2012-08-01

NHTSA recently completed a logistic regression analysis (Kahane 2012) updating its 2003 and 2010 studies of the relationship between vehicle mass and US fatality risk per vehicle mile traveled (VMT). The new study updates the previous analyses in several ways: updated FARS data for 2002 to 2008 involving MY00 to MY07 vehicles are used; induced exposure data from police reported crashes in several additional states are added; a new vehicle category for car-based crossover utility vehicles (CUVs) and minivans is created; crashes with other light-duty vehicles are divided into two groups based on the crash partner vehicle’s weight, and amore » category for all other fatal crashes is added; and new control variables for new safety technologies and designs, such as electronic stability controls (ESC), side airbags, and methods to meet voluntary agreement to improve light truck compatibility with cars, are included.« less

Insights on multivariate updates of physical and biogeochemical ocean variables using an Ensemble Kalman Filter and an idealized model of upwelling

NASA Astrophysics Data System (ADS)

Yu, Liuqian; Fennel, Katja; Bertino, Laurent; Gharamti, Mohamad El; Thompson, Keith R.

2018-06-01

Effective data assimilation methods for incorporating observations into marine biogeochemical models are required to improve hindcasts, nowcasts and forecasts of the ocean's biogeochemical state. Recent assimilation efforts have shown that updating model physics alone can degrade biogeochemical fields while only updating biogeochemical variables may not improve a model's predictive skill when the physical fields are inaccurate. Here we systematically investigate whether multivariate updates of physical and biogeochemical model states are superior to only updating either physical or biogeochemical variables. We conducted a series of twin experiments in an idealized ocean channel that experiences wind-driven upwelling. The forecast model was forced with biased wind stress and perturbed biogeochemical model parameters compared to the model run representing the "truth". Taking advantage of the multivariate nature of the deterministic Ensemble Kalman Filter (DEnKF), we assimilated different combinations of synthetic physical (sea surface height, sea surface temperature and temperature profiles) and biogeochemical (surface chlorophyll and nitrate profiles) observations. We show that when biogeochemical and physical properties are highly correlated (e.g., thermocline and nutricline), multivariate updates of both are essential for improving model skill and can be accomplished by assimilating either physical (e.g., temperature profiles) or biogeochemical (e.g., nutrient profiles) observations. In our idealized domain, the improvement is largely due to a better representation of nutrient upwelling, which results in a more accurate nutrient input into the euphotic zone. In contrast, assimilating surface chlorophyll improves the model state only slightly, because surface chlorophyll contains little information about the vertical density structure. We also show that a degradation of the correlation between observed subsurface temperature and nutrient fields, which has been an issue in several previous assimilation studies, can be reduced by multivariate updates of physical and biogeochemical fields.

Response Surface Model (RSM)-based Benefit Per Ton Estimates

EPA Pesticide Factsheets

The tables below are updated versions of the tables appearing in The influence of location, source, and emission type in estimates of the human health benefits of reducing a ton of air pollution (Fann, Fulcher and Hubbell 2009).

Documentation Supplement for Base Case v4.10_FTransport - Updates for Final Transport Rule

EPA Pesticide Factsheets

View the document that describes the changes implemented as a result for the Final Cross-State Air Pollution Rule (Transport Rule) analysis in EPA’s application of the Integrated Planning Model (IPM).

Investigating the Impact on Modeled Ozone Concentrations Using Meteorological Fields From WRF With and Updated Four-Dimensional Data Assimilation Approach”

EPA Science Inventory

The four-dimensional data assimilation (FDDA) technique in the Weather Research and Forecasting (WRF) meteorological model has recently undergone an important update from the original version. Previous evaluation results have demonstrated that the updated FDDA approach in WRF pr...

Optimizing dynamic downscaling in one-way nesting using a regional ocean model

NASA Astrophysics Data System (ADS)

Pham, Van Sy; Hwang, Jin Hwan; Ku, Hyeyun

2016-10-01

Dynamical downscaling with nested regional oceanographic models has been demonstrated to be an effective approach for both operationally forecasted sea weather on regional scales and projections of future climate change and its impact on the ocean. However, when nesting procedures are carried out in dynamic downscaling from a larger-scale model or set of observations to a smaller scale, errors are unavoidable due to the differences in grid sizes and updating intervals. The present work assesses the impact of errors produced by nesting procedures on the downscaled results from Ocean Regional Circulation Models (ORCMs). Errors are identified and evaluated based on their sources and characteristics by employing the Big-Brother Experiment (BBE). The BBE uses the same model to produce both nesting and nested simulations; so it addresses those error sources separately (i.e., without combining the contributions of errors from different sources). Here, we focus on discussing errors resulting from the spatial grids' differences, the updating times and the domain sizes. After the BBE was separately run for diverse cases, a Taylor diagram was used to analyze the results and recommend an optimal combination of grid size, updating period and domain sizes. Finally, suggested setups for the downscaling were evaluated by examining the spatial correlations of variables and the relative magnitudes of variances between the nested model and the original data.

Aqua/Aura Updated Inclination Adjust Maneuver Performance Prediction Model

NASA Technical Reports Server (NTRS)

Boone, Spencer

2017-01-01

This presentation will discuss the updated Inclination Adjust Maneuver (IAM) performance prediction model that was developed for Aqua and Aura following the 2017 IAM series. This updated model uses statistical regression methods to identify potential long-term trends in maneuver parameters, yielding improved predictions when re-planning past maneuvers. The presentation has been reviewed and approved by Eric Moyer, ESMO Deputy Project Manager.

Meteorological air quality forecasting using the WRF-Chem model during the LMOS2017 field campaign

NASA Astrophysics Data System (ADS)

Stanier, C. O.; Abdioskouei, M.; Carmichael, G. R.; Christiansen, M.; Sobhani, N.

2017-12-01

The Lake Michigan Ozone Study (LMOS 2017) occurred during May and June 2017 to address the high ozone episodes in coastal communities surrounding Lake Michigan. Aircraft, ship, mobile lab, and ground-based stations were used in this campaign to build an extensive dataset regarding ozone, its precursors, and particulate matter. The University of Iowa produced high-resolution (4x4 km2 horizontal resolution and 53 vertical levels) forecast products using the WRF-Chem modeling system in support of experimental planning during LMOS 2017. The base forecast system used WRF-Chem 3.6.1 and updated National Emission Inventory (NEI-2011v2). In the updated NEI-2011v2, we reduced the NOx emissions by 28% based on EPA's estimated NOx trends from 2011 to 2017. We ran another daily forecast (perturbed forecast) with 50% reduced NOx emission to capture the sensitivity of ozone to NOx emission and account for the impact of weekend emissions on ozone values. Preliminary in-field evaluation of model performance for clouds, on-shore flows, and surface and aircraft sampled ozone and NOx concentrations found that the model successfully captured much of the observed synoptic variability of onshore flows. The model captured the variability of O3 well, but underpredicted peak ozone during high O3 episodes. In post-campaign WRF-Chem simulations, we investigated the sensitivity of the model to the hydrocarbon emission.

Attentional focus affects how events are segmented and updated in narrative reading.

PubMed

Bailey, Heather R; Kurby, Christopher A; Sargent, Jesse Q; Zacks, Jeffrey M

2017-08-01

Readers generate situation models representing described events, but the nature of these representations may differ depending on the reading goals. We assessed whether instructions to pay attention to different situational dimensions affect how individuals structure their situation models (Exp. 1) and how they update these models when situations change (Exp. 2). In Experiment 1, participants read and segmented narrative texts into events. Some readers were oriented to pay specific attention to characters or space. Sentences containing character or spatial-location changes were perceived as event boundaries-particularly if the reader was oriented to characters or space, respectively. In Experiment 2, participants read narratives and responded to recognition probes throughout the texts. Readers who were oriented to the spatial dimension were more likely to update their situation models at spatial changes; all readers tracked the character dimension. The results from both experiments indicated that attention to individual situational dimensions influences how readers segment and update their situation models. More broadly, the results provide evidence for a global situation model updating mechanism that serves to set up new models at important narrative changes.

CRUST1.0: An Updated Global Model of Earth's Crust

NASA Astrophysics Data System (ADS)

Laske, G.; Masters, G.; Ma, Z.; Pasyanos, M. E.

2012-04-01

We present an updated global model of Earth's crustal structure. The new model, CRUST1.0, serves as starting model in a more comprehensive effort to compile a global model of Earth's crust and lithosphere, LITHO1.0. CRUST1.0 is defined on a 1-degree grid and is based on a new database of crustal thickness data from active source seismic studies as well as from receiver function studies. In areas where such constraints are still missing, for example in Antarctica, crustal thicknesses are estimated using gravity constraints. The compilation of the new crustal model initially follows the philosophy of the widely used crustal model CRUST2.0 (Bassin et al., 2000; http://igppweb.ucsd.edu/~gabi/crust2.html). Crustal types representing properties in the crystalline crust are assigned according to basement age or tectonic setting. The classification of the latter loosely follows that of an updated map by Artemieva and Mooney (2001) (http://www.lithosphere.info). Statistical averages of crustal properties in each of these crustal types are extrapolated to areas with no local seismic or gravity constraint. In each 1-degree cell, boundary depth, compressional and shear velocity as well as density is given for 8 layers: water, ice, 3-layer sediment cover and upper, middle and lower crystalline crust. Topography, bathymetry and ice cover are taken from ETOPO1. The sediment cover is essentially that of our sediment model (Laske and Masters, 1997; http://igppweb.ucsd.edu/~sediment.html), with several near-coastal updates. In the sediment cover and the crystalline crust, updated scaling relationships are used to assign compressional and shear velocity as well as density. In an initial step toward LITHO1.0, the model is then validated against our new global group velocity maps for Rayleigh and Love waves, particularly at frequencies between 30 and 40 mHz. CRUST1.0 is then adjusted in areas of extreme misfit where we suspect deficiencies in the crustal model. These currently include some near-coastal areas with thick sediment cover and several larger orogenic belts. Some remaining discrepancies, such as in backarc basins, may result from variations in the deeper uppermost mantle and remain unchanged in CRUST1.0 but will likely be modified in LITHO1.0. CRUST1.0 is available for download.

Prognostics of lithium-ion batteries based on Dempster-Shafer theory and the Bayesian Monte Carlo method

NASA Astrophysics Data System (ADS)

He, Wei; Williard, Nicholas; Osterman, Michael; Pecht, Michael

A new method for state of health (SOH) and remaining useful life (RUL) estimations for lithium-ion batteries using Dempster-Shafer theory (DST) and the Bayesian Monte Carlo (BMC) method is proposed. In this work, an empirical model based on the physical degradation behavior of lithium-ion batteries is developed. Model parameters are initialized by combining sets of training data based on DST. BMC is then used to update the model parameters and predict the RUL based on available data through battery capacity monitoring. As more data become available, the accuracy of the model in predicting RUL improves. Two case studies demonstrating this approach are presented.

On Using Exponential Parameter Estimators with an Adaptive Controller

NASA Technical Reports Server (NTRS)

Patre, Parag; Joshi, Suresh M.

2011-01-01

Typical adaptive controllers are restricted to using a specific update law to generate parameter estimates. This paper investigates the possibility of using any exponential parameter estimator with an adaptive controller such that the system tracks a desired trajectory. The goal is to provide flexibility in choosing any update law suitable for a given application. The development relies on a previously developed concept of controller/update law modularity in the adaptive control literature, and the use of a converse Lyapunov-like theorem. Stability analysis is presented to derive gain conditions under which this is possible, and inferences are made about the tracking error performance. The development is based on a class of Euler-Lagrange systems that are used to model various engineering systems including space robots and manipulators.

Evaluation of the groundwater-flow model for the Ohio River alluvial aquifer near Carrollton, Kentucky, updated to conditions in September 2010

USGS Publications Warehouse

Unthank, Michael D.

2013-01-01

The Ohio River alluvial aquifer near Carrollton, Ky., is an important water resource for the cities of Carrollton and Ghent, as well as for several industries in the area. The groundwater of the aquifer is the primary source of drinking water in the region and a highly valued natural resource that attracts various water-dependent industries because of its quantity and quality. This report evaluates the performance of a numerical model of the groundwater-flow system in the Ohio River alluvial aquifer near Carrollton, Ky., published by the U.S. Geological Survey in 1999. The original model simulated conditions in November 1995 and was updated to simulate groundwater conditions estimated for September 2010. The files from the calibrated steady-state model of November 1995 conditions were imported into MODFLOW-2005 to update the model to conditions in September 2010. The model input files modified as part of this update were the well and recharge files. The design of the updated model and other input files are the same as the original model. The ability of the updated model to match hydrologic conditions for September 2010 was evaluated by comparing water levels measured in wells to those computed by the model. Water-level measurements were available for 48 wells in September 2010. Overall, the updated model underestimated the water levels at 36 of the 48 measured wells. The average difference between measured water levels and model-computed water levels was 3.4 feet and the maximum difference was 10.9 feet. The root-mean-square error of the simulation was 4.45 for all 48 measured water levels. The updated steady-state model could be improved by introducing more accurate and site-specific estimates of selected field parameters, refined model geometry, and additional numerical methods. Collection of field data to better estimate hydraulic parameters, together with continued review of available data and information from area well operators, could provide the model with revised estimates of conductance values for the riverbed and valley wall, hydraulic conductivities for the model layer, and target water levels for future simulations. Additional model layers, a redesigned model grid, and revised boundary conditions could provide a better framework for more accurate simulations. Additional numerical methods would identify possible parameter estimates and determine parameter sensitivities.

Performance evaluation of four directional emissivity analytical models with thermal SAIL model and airborne images.

PubMed

Ren, Huazhong; Liu, Rongyuan; Yan, Guangjian; Li, Zhao-Liang; Qin, Qiming; Liu, Qiang; Nerry, Françoise

2015-04-06

Land surface emissivity is a crucial parameter in the surface status monitoring. This study aims at the evaluation of four directional emissivity models, including two bi-directional reflectance distribution function (BRDF) models and two gap-frequency-based models. Results showed that the kernel-driven BRDF model could well represent directional emissivity with an error less than 0.002, and was consequently used to retrieve emissivity with an accuracy of about 0.012 from an airborne multi-angular thermal infrared data set. Furthermore, we updated the cavity effect factor relating to multiple scattering inside canopy, which improved the performance of the gap-frequency-based models.

A Watershed-Scale Agent-Based Model Incorporating Agent Learning and Interaction of Farmers' Decisions Subject to Carbon and Miscanthus Prices

NASA Astrophysics Data System (ADS)

Ng, T.; Eheart, J.; Cai, X.; Braden, J. B.

2010-12-01

Agricultural watersheds are coupled human-natural systems where the land use decisions of human agents (farmers) affect surface water quality, and in turn, are affected by the weather and yields. The reliable modeling of such systems requires an approach that considers both the human and natural aspects. Agent-based modeling (ABM), representing the human aspect, coupled with hydrologic modeling, representing the natural aspect, is one such approach. ABM is a relatively new modeling paradigm that formulates the system from the perspectives of the individual agents, i.e., each agent is modeled as a discrete autonomous entity with distinct goals and actions. The primary objective of this study is to demonstrate the applicability of this approach to agricultural watershed management. This is done using a semi-hypothetical case study of farmers in the Salt Creek watershed in East-Central Illinois under the influence markets for carbon and second-generation bioenergy crop (specifically, miscanthus). An agent-based model of the system is developed and linked to a hydrologic model of the watershed. The former is based on fundamental economic and mathematical programming principles, while the latter is based on the Soil and Water Assessment Tool (SWAT). Carbon and second-generation bioenergy crop markets are of interest here due to climate change and energy independence concerns. The agent-based model is applied to fifty hypothetical heterogeneous farmers. The farmers' decisions depend on their perceptions of future conditions. Those perceptions are updated, according to a pre-defined algorithm, as the farmers make new observations of prices, costs, yields and the weather with time. The perceptions are also updated as the farmers interact with each other as they share new information on initially unfamiliar activities (e.g., carbon trading, miscanthus cultivation). The updating algorithm is set differently for different farmers such that each is unique in his processing of new information. The results provide insights on how differences in the way farmers learn and adapt affect their forecasts of the future, and hence, decisions. Farmers who are interacting, less risk averse, quick to adjust their expectations with new observations, and slow to reduce their forecast confidence when there are unexpected changes are more likely to practice conservation tillage (farmers may claim carbon credits for sale when practicing conservation tillage), and switch from conventional crops to miscanthus. The results, though empirically untested, appear plausible and consistent with general behavior by farmers. All this demonstrates the ability and potential of ABM to capture, at least partially, the complexities of human decision-making.

Technical Evaluation of the NASA Model for Cancer Risk to Astronauts Due to Space Radiation

NASA Technical Reports Server (NTRS)

2012-01-01

At the request of NASA, the National Research Council's (NRC's) Committee for Evaluation of Space Radiation Cancer Risk Model1 reviewed a number of changes that NASA proposes to make to its model for estimating the risk of radiation-induced cancer in astronauts. The NASA model in current use was last updated in 2005, and the proposed model would incorporate recent research directed at improving the quantification and understanding of the health risks posed by the space radiation environment. NASA's proposed model is defined by the 2011 NASA report Space Radiation Cancer Risk Projections and Uncertainties--2010 . The committee's evaluation is based primarily on this source, which is referred to hereafter as the 2011 NASA report, with mention of specific sections or tables. The overall process for estimating cancer risks due to low linear energy transfer (LET) radiation exposure has been fully described in reports by a number of organizations. The approaches described in the reports from all of these expert groups are quite similar. NASA's proposed space radiation cancer risk assessment model calculates, as its main output, age- and gender-specific risk of exposure-induced death (REID) for use in the estimation of mission and astronaut-specific cancer risk. The model also calculates the associated uncertainties in REID. The general approach for estimating risk and uncertainty in the proposed model is broadly similar to that used for the current (2005) NASA model and is based on recommendations by the National Council on Radiation Protection and Measurements. However, NASA's proposed model has significant changes with respect to the following: the integration of new findings and methods into its components by taking into account newer epidemiological data and analyses, new radiobiological data indicating that quality factors differ for leukemia and solid cancers, an improved method for specifying quality factors in terms of radiation track structure concepts as opposed to the previous approach based on linear energy transfer, the development of a new solar particle event (SPE) model, and the updates to galactic cosmic ray (GCR) and shielding transport models. The newer epidemiological information includes updates to the cancer incidence rates from the life span study (LSS) of the Japanese atomic bomb survivors, transferred to the U.S. population and converted to cancer mortality rates from U.S. population statistics. In addition, the proposed model provides an alternative analysis applicable to lifetime never-smokers (NSs). Details of the uncertainty analysis in the model have also been updated and revised. NASA's proposed model and associated uncertainties are complex in their formulation and as such require a very clear and precise set of descriptions. The committee found the 2011 NASA report challenging to review largely because of the lack of clarity in the model descriptions and derivation of the various parameters used. The committee requested some clarifications from NASA throughout its review and was able to resolve many, but not all, of the ambiguities in the written description.

Dose conversion coefficients for neutron exposure to the lens of the human eye

DOE Office of Scientific and Technical Information (OSTI.GOV)

Manger, Ryan P; Bellamy, Michael B; Eckerman, Keith F

Dose conversion coefficients for the lens of the human eye have been calculated for neutron exposure at energies from 1 x 10{sup -9} to 20 MeV and several standard orientations: anterior-to-posterior, rotational and right lateral. MCNPX version 2.6.0, a Monte Carlo-based particle transport package, was used to determine the energy deposited in the lens of the eye. The human eyeball model was updated by partitioning the lens into sensitive and insensitive volumes as the anterior portion (sensitive volume) of the lens being more radiosensitive and prone to cataract formation. The updated eye model was used with the adult UF-ORNL mathematicalmore » phantom in the MCNPX transport calculations.« less

Identification of cracks in thick beams with a cracked beam element model

NASA Astrophysics Data System (ADS)

Hou, Chuanchuan; Lu, Yong

2016-12-01

The effect of a crack on the vibration of a beam is a classical problem, and various models have been proposed, ranging from the basic stiffness reduction method to the more sophisticated model involving formulation based on the additional flexibility due to a crack. However, in the damage identification or finite element model updating applications, it is still common practice to employ a simple stiffness reduction factor to represent a crack in the identification process, whereas the use of a more realistic crack model is rather limited. In this paper, the issues with the simple stiffness reduction method, particularly concerning thick beams, are highlighted along with a review of several other crack models. A robust finite element model updating procedure is then presented for the detection of cracks in beams. The description of the crack parameters is based on the cracked beam flexibility formulated by means of the fracture mechanics, and it takes into consideration of shear deformation and coupling between translational and longitudinal vibrations, and thus is particularly suitable for thick beams. The identification procedure employs a global searching technique using Genetic Algorithms, and there is no restriction on the location, severity and the number of cracks to be identified. The procedure is verified to yield satisfactory identification for practically any configurations of cracks in a beam.

Protein structure modeling and refinement by global optimization in CASP12.

PubMed

Hong, Seung Hwan; Joung, InSuk; Flores-Canales, Jose C; Manavalan, Balachandran; Cheng, Qianyi; Heo, Seungryong; Kim, Jong Yun; Lee, Sun Young; Nam, Mikyung; Joo, Keehyoung; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2018-03-01

For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequence-structure alignment, three-dimensional (3D) chain building, and side-chain re-modeling. For better template selection and model selection, we updated our model quality assessment (QA) method with the newly developed SVMQA (support vector machine for quality assessment). For 3D chain building, we updated our energy function by including restraints generated from predicted residue-residue contacts. New energy terms for the predicted secondary structure and predicted solvent accessible surface area were also introduced. For difficult targets, we proposed a new method, LEEab, where the template term played a less significant role than it did in LEE, complemented by increased contributions from other terms such as the predicted contact term. For TBM (template-based modeling) targets, LEE performed better than LEEab, but for FM targets, LEEab was better. For model refinement, we modified our CASP11 molecular dynamics (MD) based protocol by using explicit solvents and tuning down restraint weights. Refinement results from MD simulations that used a new augmented statistical energy term in the force field were quite promising. Finally, when using inaccurate information (such as the predicted contacts), it was important to use the Lorentzian function for which the maximal penalty arising from wrong information is always bounded. © 2017 Wiley Periodicals, Inc.

A Novel Dynamic Update Framework for Epileptic Seizure Prediction

PubMed Central

Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices. PMID:25050381

A novel dynamic update framework for epileptic seizure prediction.

PubMed

Han, Min; Ge, Sunan; Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices.

The 2006 Kennedy Space Center Range Reference Atmosphere Model Validation Study and Sensitivity Analysis to the Performance of the National Aeronautics and Space Administration's Space Shuttle Vehicle

NASA Technical Reports Server (NTRS)

Burns, Lee; Decker, Ryan; Harrington, Brian; Merry, Carl

2008-01-01

The Kennedy Space Center (KSC) Range Reference Atmosphere (RRA) is a statistical model that summarizes wind and thermodynamic atmospheric variability from surface to 70 km. The National Aeronautics and Space Administration's (NASA) Space Shuttle program, which launches from KSC, utilizes the KSC RRA data to evaluate environmental constraints on various aspects of the vehicle during ascent. An update to the KSC RRA was recently completed. As part of the update, the Natural Environments Branch at NASA's Marshall Space Flight Center (MSFC) conducted a validation study and a comparison analysis to the existing KSC RRA database version 1983. Assessments to the Space Shuttle vehicle ascent profile characteristics were performed by JSC/Ascent Flight Design Division to determine impacts of the updated model to the vehicle performance. Details on the model updates and the vehicle sensitivity analyses with the update model are presented.

Exploration of cellular reaction systems.

PubMed

Kirkilionis, Markus

2010-01-01

We discuss and review different ways to map cellular components and their temporal interaction with other such components to different non-spatially explicit mathematical models. The essential choices made in the literature are between discrete and continuous state spaces, between rule and event-based state updates and between deterministic and stochastic series of such updates. The temporal modelling of cellular regulatory networks (dynamic network theory) is compared with static network approaches in two first introductory sections on general network modelling. We concentrate next on deterministic rate-based dynamic regulatory networks and their derivation. In the derivation, we include methods from multiscale analysis and also look at structured large particles, here called macromolecular machines. It is clear that mass-action systems and their derivatives, i.e. networks based on enzyme kinetics, play the most dominant role in the literature. The tools to analyse cellular reaction networks are without doubt most complete for mass-action systems. We devote a long section at the end of the review to make a comprehensive review of related tools and mathematical methods. The emphasis is to show how cellular reaction networks can be analysed with the help of different associated graphs and the dissection into modules, i.e. sub-networks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Savy, J.

New design and evaluation guidelines for department of energy facilities subjected to natural phenomena hazard, are being finalized. Although still in draft form at this time, the document describing those guidelines should be considered to be an update of previously available guidelines. The recommendations in the guidelines document mentioned above, and simply referred to as the guidelines'' thereafter, are based on the best information at the time of its development. In particular, the seismic hazard model for the Princeton site was based on a study performed in 1981 for Lawrence Livermore National Laboratory (LLNL), which relied heavily on the resultsmore » of the NRC's Systematic Evaluation Program and was based on a methodology and data sets developed in 1977 and 1978. Considerable advances have been made in the last ten years in the domain of seismic hazard modeling. Thus, it is recommended to update the estimate of the seismic hazard at the DOE sites whenever possible. The major differences between previous estimates and the ones proposed in this study for the PPPL are in the modeling of the strong ground motion at the site, and the treatment of the total uncertainty in the estimates to include knowledge uncertainty, random uncertainty, and expert opinion diversity as well. 28 refs.« less

Creation of a High-Resolution Product CLC2006_BACKDATING by a Backward Look from the Digital Land Cover Model DLM-DE2009 to 2006 - a Contribution to the German Corine Land Cover 2012 Project Within a Bottom-Up Approach

NASA Astrophysics Data System (ADS)

Keil, M.; Esch, T.; Feigenspan, S.; Marconcini, M.; Metz, A.; Ottinger, M.; Zeidler, J.

2015-04-01

For the update 2012 of CORINE Land Cover, in Germany a new approach has been developed in order to profit from the higher accuracies of the national topographic database. In agreement between the Federal Environment Agency (UBA) and the Federal Agency for Cartography and Geodesy (BKG), CLC2012 has been derived from an updated digital landscape model DLM-DE, which is based on the Official Topographical Cartographic Information System ATKIS of the land survey authorities. The DLM-DE 2009 created by the BKG served as the base for the update 2012 in the national and EU context, both under the responsibility of the BKG. In addition to the updated CLC2012, a second product, the layer "CLC_Change" (2006-2012) was also requested by the European Environment Agency. The objective of the project part of DLR-DFD was to contribute the primary change areas from 2006 to 2009 in the phase of method change using the refined 2009 geometry of the DLM-DE 2009 for a retrospective view back to 2006. A semiautomatic approach was developed for this task, with an important role of AWiFS time series data of 2005 / 2006 in the context of separation between grassland - arable land. Other valuable datasets for the project were already available GMES land monitoring products of 2006 like the soil sealing layer 2006. The paper describes the developed method and discusses exemplary results of the CORINE backdating project part.

Evaluation of improved land use and canopy representation in ...

EPA Pesticide Factsheets

Biogenic volatile organic compounds (BVOC) participate in reactions that can lead to secondarily formed ozone and particulate matter (PM) impacting air quality and climate. BVOC emissions are important inputs to chemical transport models applied on local to global scales but considerable uncertainty remains in the representation of canopy parameterizations and emission algorithms from different vegetation species. The Biogenic Emission Inventory System (BEIS) has been used to support both scientific and regulatory model assessments for ozone and PM. Here we describe a new version of BEIS which includes updated input vegetation data and canopy model formulation for estimating leaf temperature and vegetation data on estimated BVOC. The Biogenic Emission Landuse Database (BELD) was revised to incorporate land use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land product and 2006 National Land Cover Database (NLCD) land coverage. Vegetation species data are based on the US Forest Service (USFS) Forest Inventory and Analysis (FIA) version 5.1 for 2002–2013 and US Department of Agriculture (USDA) 2007 census of agriculture data. This update results in generally higher BVOC emissions throughout California compared with the previous version of BEIS. Baseline and updated BVOC emission estimates are used in Community Multiscale Air Quality (CMAQ) Model simulations with 4 km grid resolution and evaluated with measurements of isoprene and monoterp

An update on the potential role of intestinal first-pass metabolism for the prediction of drug-drug interactions: the role of PBPK modeling.

PubMed

Alqahtani, Saeed; Bukhari, Ishfaq; Albassam, Ahmed; Alenazi, Maha

2018-05-28

The intestinal absorption process is a combination of several events that are governed by various factors. Several transport mechanisms are involved in drug absorption through enterocytes via active and/or passive processes. The transported molecules then undergo intestinal metabolism, which together with intestinal transport may affect the systemic availability of drugs. Many studies have provided clear evidence on the significant role of intestinal first-pass metabolism on drug bioavailability and degree of drug-drug interactions (DDIs). Areas covered: This review provides an update on the role of intestinal first-pass metabolism in the oral bioavailability of drugs and prediction of drug-drug interactions. It also provides a comprehensive overview and summary of the latest update in the role of PBPK modeling in prediction of intestinal metabolism and DDIs in humans. Expert opinion: The contribution of intestinal first-pass metabolism in the oral bioavailability of drugs and prediction of DDIs has become more evident over the last few years. Several in vitro, in situ, and in vivo models have been developed to evaluate the role of first-pass metabolism and to predict DDIs. Currently, physiologically based pharmacokinetic modeling is considered the most valuable tool for the prediction of intestinal first-pass metabolism and DDIs.

Quantitative critical thinking: Student activities using Bayesian updating

NASA Astrophysics Data System (ADS)

Warren, Aaron R.

2018-05-01

One of the central roles of physics education is the development of students' ability to evaluate proposed hypotheses and models. This ability is important not just for students' understanding of physics but also to prepare students for future learning beyond physics. In particular, it is often hoped that students will better understand the manner in which physicists leverage the availability of prior knowledge to guide and constrain the construction of new knowledge. Here, we discuss how the use of Bayes' Theorem to update the estimated likelihood of hypotheses and models can help achieve these educational goals through its integration with evaluative activities that use hypothetico-deductive reasoning. Several types of classroom and laboratory activities are presented that engage students in the practice of Bayesian likelihood updating on the basis of either consistency with experimental data or consistency with pre-established principles and models. This approach is sufficiently simple for introductory physics students while offering a robust mechanism to guide relatively sophisticated student reflection concerning models, hypotheses, and problem-solutions. A quasi-experimental study utilizing algebra-based introductory courses is presented to assess the impact of these activities on student epistemological development. The results indicate gains on the Epistemological Beliefs Assessment for Physical Science (EBAPS) at a minimal cost of class-time.

Key algorithms used in GR02: A computer simulation model for predicting tree and stand growth

Treesearch

Garrett A. Hughes; Paul E. Sendak; Paul E. Sendak

1985-01-01

GR02 is an individual tree, distance-independent simulation model for predicting tree and stand growth over time. It performs five major functions during each run: (1) updates diameter at breast height, (2) updates total height, (3) estimates mortality, (4) determines regeneration, and (5) updates crown class.

Processing arctic eddy-flux data using a simple carbon-exchange model embedded in the ensemble Kalman filter.

PubMed

Rastetter, Edward B; Williams, Mathew; Griffin, Kevin L; Kwiatkowski, Bonnie L; Tomasky, Gabrielle; Potosnak, Mark J; Stoy, Paul C; Shaver, Gaius R; Stieglitz, Marc; Hobbie, John E; Kling, George W

2010-07-01

Continuous time-series estimates of net ecosystem carbon exchange (NEE) are routinely made using eddy covariance techniques. Identifying and compensating for errors in the NEE time series can be automated using a signal processing filter like the ensemble Kalman filter (EnKF). The EnKF compares each measurement in the time series to a model prediction and updates the NEE estimate by weighting the measurement and model prediction relative to a specified measurement error estimate and an estimate of the model-prediction error that is continuously updated based on model predictions of earlier measurements in the time series. Because of the covariance among model variables, the EnKF can also update estimates of variables for which there is no direct measurement. The resulting estimates evolve through time, enabling the EnKF to be used to estimate dynamic variables like changes in leaf phenology. The evolving estimates can also serve as a means to test the embedded model and reconcile persistent deviations between observations and model predictions. We embedded a simple arctic NEE model into the EnKF and filtered data from an eddy covariance tower located in tussock tundra on the northern foothills of the Brooks Range in northern Alaska, USA. The model predicts NEE based only on leaf area, irradiance, and temperature and has been well corroborated for all the major vegetation types in the Low Arctic using chamber-based data. This is the first application of the model to eddy covariance data. We modified the EnKF by adding an adaptive noise estimator that provides a feedback between persistent model data deviations and the noise added to the ensemble of Monte Carlo simulations in the EnKF. We also ran the EnKF with both a specified leaf-area trajectory and with the EnKF sequentially recalibrating leaf-area estimates to compensate for persistent model-data deviations. When used together, adaptive noise estimation and sequential recalibration substantially improved filter performance, but it did not improve performance when used individually. The EnKF estimates of leaf area followed the expected springtime canopy phenology. However, there were also diel fluctuations in the leaf-area estimates; these are a clear indication of a model deficiency possibly related to vapor pressure effects on canopy conductance.

User's guide to the MESOI diffusion model and to the utility programs UPDATE and LOGRVU

DOE Office of Scientific and Technical Information (OSTI.GOV)

Athey, G.F.; Allwine, K.J.; Ramsdell, J.V.

MESOI is an interactive, Lagrangian puff trajectory diffusion model. The model is documented separately (Ramsdell and Athey, 1981); this report is intended to provide MESOI users with the information needed to successfully conduct model simulations. The user is also provided with guidance in the use of the data file maintenance and review programs; UPDATE and LOGRVU. Complete examples are given for the operaton of all three programs and an appendix documents UPDATE and LOGRVU.

Modelling and Prediction of Spark-ignition Engine Power Performance Using Incremental Least Squares Support Vector Machines

NASA Astrophysics Data System (ADS)

Wong, Pak-kin; Vong, Chi-man; Wong, Hang-cheong; Li, Ke

2010-05-01

Modern automotive spark-ignition (SI) power performance usually refers to output power and torque, and they are significantly affected by the setup of control parameters in the engine management system (EMS). EMS calibration is done empirically through tests on the dynamometer (dyno) because no exact mathematical engine model is yet available. With an emerging nonlinear function estimation technique of Least squares support vector machines (LS-SVM), the approximate power performance model of a SI engine can be determined by training the sample data acquired from the dyno. A novel incremental algorithm based on typical LS-SVM is also proposed in this paper, so the power performance models built from the incremental LS-SVM can be updated whenever new training data arrives. With updating the models, the model accuracies can be continuously increased. The predicted results using the estimated models from the incremental LS-SVM are good agreement with the actual test results and with the almost same average accuracy of retraining the models from scratch, but the incremental algorithm can significantly shorten the model construction time when new training data arrives.

An extended plasma model for Saturn

NASA Technical Reports Server (NTRS)

Richardson, John D.

1995-01-01

The Saturn magnetosphere model of Richardson and Sittler (1990) is extended to include the outer magnetosphere. The inner magnetospheric portion of this model is updated based on a recent reanalysis of the plasma data near the Voyager 2 ring plane crossing. The result is an axially symmetric model of the plasma parameters which is designed to provide accurate input for models needing either in situ or line-of-sight data and to be a useful tool for Cassini planning.

Frequency Response Function Based Damage Identification for Aerospace Structures

NASA Astrophysics Data System (ADS)

Oliver, Joseph Acton

Structural health monitoring technologies continue to be pursued for aerospace structures in the interests of increased safety and, when combined with health prognosis, efficiency in life-cycle management. The current dissertation develops and validates damage identification technology as a critical component for structural health monitoring of aerospace structures and, in particular, composite unmanned aerial vehicles. The primary innovation is a statistical least-squares damage identification algorithm based in concepts of parameter estimation and model update. The algorithm uses frequency response function based residual force vectors derived from distributed vibration measurements to update a structural finite element model through statistically weighted least-squares minimization producing location and quantification of the damage, estimation uncertainty, and an updated model. Advantages compared to other approaches include robust applicability to systems which are heavily damped, large, and noisy, with a relatively low number of distributed measurement points compared to the number of analytical degrees-of-freedom of an associated analytical structural model (e.g., modal finite element model). Motivation, research objectives, and a dissertation summary are discussed in Chapter 1 followed by a literature review in Chapter 2. Chapter 3 gives background theory and the damage identification algorithm derivation followed by a study of fundamental algorithm behavior on a two degree-of-freedom mass-spring system with generalized damping. Chapter 4 investigates the impact of noise then successfully proves the algorithm against competing methods using an analytical eight degree-of-freedom mass-spring system with non-proportional structural damping. Chapter 5 extends use of the algorithm to finite element models, including solutions for numerical issues, approaches for modeling damping approximately in reduced coordinates, and analytical validation using a composite sandwich plate model. Chapter 6 presents the final extension to experimental systems-including methods for initial baseline correlation and data reduction-and validates the algorithm on an experimental composite plate with impact damage. The final chapter deviates from development and validation of the primary algorithm to discuss development of an experimental scaled-wing test bed as part of a collaborative effort for developing structural health monitoring and prognosis technology. The dissertation concludes with an overview of technical conclusions and recommendations for future work.

Development and verification of NRC`s single-rod fuel performance codes FRAPCON-3 AND FRAPTRAN

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beyer, C.E.; Cunningham, M.E.; Lanning, D.D.

1998-03-01

The FRAPCON and FRAP-T code series, developed in the 1970s and early 1980s, are used by the US Nuclear Regulatory Commission (NRC) to predict fuel performance during steady-state and transient power conditions, respectively. Both code series are now being updated by Pacific Northwest National Laboratory to improve their predictive capabilities at high burnup levels. The newest versions of the codes are called FRAPCON-3 and FRAPTRAN. The updates to fuel property and behavior models are focusing on providing best estimate predictions under steady-state and fast transient power conditions up to extended fuel burnups (> 55 GWd/MTU). Both codes will be assessedmore » against a data base independent of the data base used for code benchmarking and an estimate of code predictive uncertainties will be made based on comparisons to the benchmark and independent data bases.« less

A BEME systematic review of the effects of interprofessional education: BEME Guide No. 39.

PubMed

Reeves, Scott; Fletcher, Simon; Barr, Hugh; Birch, Ivan; Boet, Sylvain; Davies, Nigel; McFadyen, Angus; Rivera, Josette; Kitto, Simon

2016-07-01

Interprofessional education (IPE) aims to bring together different professionals to learn with, from, and about one another in order to collaborate more effectively in the delivery of safe, high-quality care for patients/clients. Given its potential for improving collaboration and care delivery, there have been repeated calls for the wider-scale implementation of IPE across education and clinical settings. Increasingly, a range of IPE initiatives are being implemented and evaluated which are adding to the growth of evidence for this form of education. The overall aim of this review is to update a previous BEME review published in 2007. In doing so, this update sought to synthesize the evolving nature of the IPE evidence. Medline, CINAHL, BEI, and ASSIA were searched from May 2005 to June 2014. Also, journal hand searches were undertaken. All potential abstracts and papers were screened by pairs of reviewers to determine inclusion. All included papers were assessed for methodological quality and those deemed as "high quality" were included. The presage-process-product (3P) model and a modified Kirkpatrick model were employed to analyze and synthesize the included studies. Twenty-five new IPE studies were included in this update. These studies were added to the 21 studies from the previous review to form a complete data set of 46 high-quality IPE studies. In relation to the 3P model, overall the updated review found that most of the presage and process factors identified from the previous review were further supported in the newer studies. In regard to the products (outcomes) reported, the results from this review continue to show far more positive than neutral or mixed outcomes reported in the included studies. Based on the modified Kirkpatrick model, the included studies suggest that learners respond well to IPE, their attitudes and perceptions of one another improve, and they report increases in collaborative knowledge and skills. There is more limited, but growing, evidence related to changes in behavior, organizational practice, and benefits to patients/clients. This updated review found that key context (presage) and process factors reported in the previous review continue to have resonance on the delivery of IPE. In addition, the newer studies have provided further evidence for the effects on IPE related to a number of different outcomes. Based on these conclusions, a series of key implications for the development of IPE are offered.

A groundwater data assimilation application study in the Heihe mid-reach

NASA Astrophysics Data System (ADS)

Ragettli, S.; Marti, B. S.; Wolfgang, K.; Li, N.

2017-12-01

The present work focuses on modelling of the groundwater flow in the mid-reach of the endorheic river Heihe in the Zhangye oasis (Gansu province) in arid north-west China. In order to optimise the water resources management in the oasis, reliable forecasts of groundwater level development under different management options and environmental boundary conditions have to be produced. For this means, groundwater flow is modelled with Modflow and coupled to an Ensemble Kalman Filter programmed in Matlab. The model is updated with monthly time steps, featuring perturbed boundary conditions to account for uncertainty in model forcing. Constant biases between model and observations have been corrected prior to updating and compared to model runs without bias correction. Different options for data assimilation (states and/or parameters), updating frequency, and measures against filter inbreeding (damping factor, covariance inflation, spatial localization) have been tested against each other. Results show a high dependency of the Ensemble Kalman filter performance on the selection of observations for data assimilation. For the present regional model, bias correction is necessary for a good filter performance. A combination of spatial localization and covariance inflation is further advisable to reduce filter inbreeding problems. Best performance is achieved if parameter updates are not large, an indication for good prior model calibration. Asynchronous updating of parameter values once every five years (with data of the past five years) and synchronous updating of the groundwater levels is better suited for this groundwater system with not or slow changing parameter values than synchronous updating of both groundwater levels and parameters at every time step applying a damping factor. The filter is not able to correct time lags of signals.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramuhalli, Pradeep; Hirt, Evelyn H.; Veeramany, Arun

This research report summaries the development and evaluation of a prototypic enhanced risk monitor (ERM) methodology (framework) that includes alternative risk metrics and uncertainty analysis. This updated ERM methodology accounts for uncertainty in the equipment condition assessment (ECA), the prognostic result, and the probabilistic risk assessment (PRA) model. It is anticipated that the ability to characterize uncertainty in the estimated risk and update the risk estimates in real time based on equipment condition assessment (ECA) will provide a mechanism for optimizing plant performance while staying within specified safety margins. These results (based on impacting active component O&M using real-time equipmentmore » condition information) are a step towards ERMs that, if integrated with AR supervisory plant control systems, can help control O&M costs and improve affordability of advanced reactors.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Segev, A.; Fang, W.

In currency-based updates, processing a query to a materialized view has to satisfy a currency constraint which specifies the maximum time lag of the view data with respect to a transaction database. Currency-based update policies are more general than periodical, deferred, and immediate updates; they provide additional opportunities for optimization and allow updating a materialized view from other materialized views. In this paper, we present algorithms to determine the source and timing of view updates and validate the resulting cost savings through simulation results. 20 refs.

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2

EPA Pesticide Factsheets

The uploaded data consists of the BRACE Na aerosol observations paired with CMAQ model output, the updated model's parameterization of sea salt aerosol emission size distribution, and the model's parameterization of the sea salt emission factor as a function of sea surface temperature. This dataset is associated with the following publication:Gantt , B., J. Kelly , and J. Bash. Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 8: 3733-3746, (2015).

An updating of the SIRM model

NASA Astrophysics Data System (ADS)

Perna, L.; Pezzopane, M.; Pietrella, M.; Zolesi, B.; Cander, L. R.

2017-09-01

The SIRM model proposed by Zolesi et al. (1993, 1996) is an ionospheric regional model for predicting the vertical-sounding characteristics that has been frequently used in developing ionospheric web prediction services (Zolesi and Cander, 2014). Recently the model and its outputs were implemented in the framework of two European projects: DIAS (DIgital upper Atmosphere Server; http://www.iono.noa.gr/DIAS/ (Belehaki et al., 2005, 2015) and ESPAS (Near-Earth Space Data Infrastructure for e-Science; http://www.espas-fp7.eu/) (Belehaki et al., 2016). In this paper an updated version of the SIRM model, called SIRMPol, is described and corresponding outputs in terms of the F2-layer critical frequency (foF2) are compared with values recorded at the mid-latitude station of Rome (41.8°N, 12.5°E), for extremely high (year 1958) and low (years 2008 and 2009) solar activity. The main novelties introduced in the SIRMPol model are: (1) an extension of the Rome ionosonde input dataset that, besides data from 1957 to 1987, includes also data from 1988 to 2007; (2) the use of second order polynomial regressions, instead of linear ones, to fit the relation foF2 vs. solar activity index R12; (3) the use of polynomial relations, instead of linear ones, to fit the relations A0 vs. R12, An vs. R12 and Yn vs. R12, where A0, An and Yn are the coefficients of the Fourier analysis performed by the SIRM model to reproduce the values calculated by using relations in (2). The obtained results show that SIRMPol outputs are better than those of the SIRM model. As the SIRMPol model represents only a partial updating of the SIRM model based on inputs from only Rome ionosonde data, it can be considered a particular case of a single-station model. Nevertheless, the development of the SIRMPol model allowed getting some useful guidelines for a future complete and more accurate updating of the SIRM model, of which both DIAS and ESPAS could benefit.

Artificial neural networks and approximate reasoning for intelligent control in space

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

An Updated Performance Assessment For A New Low-Level Radioactive Waste Disposal Facility In West Texas - 12192

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dornsife, William P.; Kirk, J. Scott; Shaw, Chris G.

2012-07-01

This Performance Assessment (PA) submittal is an update to the original PA that was developed to support the licensing of the Waste Control Specialists LLC Low-Level Radioactive Waste (LLRW) disposal facility. This update includes both the Compact Waste Facility (CWF) and the Federal Waste Facility (FWF), in accordance with Radioactive Material License (RML) No. R04100, License Condition (LC) 87. While many of the baseline assumptions supporting the initial license application PA were incorporated in this update, a new transport code, GoldSim, and new deterministic groundwater flow codes, including HYDRUS and MODFLOWSURFACT{sup TM}, were employed to demonstrate compliance with the performancemore » objectives codified in the regulations and RML No. R04100, LC 87. A revised source term, provided by the Texas Commission on Environmental Quality staff, was used to match the initial 15 year license term. This updated PA clearly confirms and demonstrates the robustness of the characteristics of the site's geology and the advanced engineering design of the disposal units. Based on the simulations from fate and transport models, the radiation doses to members of the general public and site workers predicted in the initial and updated PA were a small fraction of the criterion doses of 0.25 mSv and 50 mSv, respectively. In a comparison between the results of the updated PA against the one developed in support of the initial license, both clearly demonstrated the robustness of the characteristics of the site's geology and engineering design of the disposal units. Based on the simulations from fate and transport models, the radiation doses to members of the general public predicted in the initial and updated PA were a fraction of the allowable 25 mrem/yr (0.25 m sievert/yr) dose standard for tens-of-thousands of years into the future. Draft Texas guidance on performance assessment (TCEQ, 2004) recommends a period of analysis equal to 1,000 years or until peak doses from the more mobile radionuclides occur. The EPA National Emissions Standards for Hazardous Air Pollutants limits radionuclide doses through the air pathway to 10 mrem/yr. Gaseous radionuclide doses from the CWF and the FWF, due to decomposition gases, are a small fraction of the dose limit. The radon flux from the CWF and FWF were compared to the flux limit of 20 pCi/m{sup 2}-s from 40 CFR 192. Because of the thick cover system, the calculated radon flux was a very small fraction of the limit. (authors)« less

Operational Impact of Improved Space Tracking on Collision Avoidance in the Future LEO Space Debris Environment

NASA Astrophysics Data System (ADS)

Sibert, D.; Borgeson, D.; Peterson, G.; Jenkin, A.; Sorge, M.

2010-09-01

Even if global space policy successfully curtails on orbit explosions and ASAT demonstrations, studies indicate that the number of debris objects in Low Earth Orbit (LEO) will continue to grow solely from debris on debris collisions and debris generated from new launches. This study examines the threat posed by this growing space debris population over the next 30 years and how improvements in our space tracking capabilities can reduce the number of Collision Avoidance (COLA) maneuvers required keep the risk of operational satellite loss within tolerable limits. Particular focus is given to satellites operated by the Department of Defense (DoD) and Intelligence Community (IC) in Low Earth Orbit (LEO). The following debris field and space tracking performance parameters were varied parametrically in the experiment to study the impact on the number of collision avoidance maneuvers required: - Debris Field Density (by year 2009, 2019, 2029, and 2039) - Quality of Track Update (starting 1 sigma error ellipsoid) - Future Propagator Accuracy (error ellipsoid growth rates - Special Perturbations in 3 axes) - Track Update Rate for Debris (stochastic) - Track Update Rate for Payloads (stochastic) Baseline values matching present day tracking performance for quality of track update, propagator accuracy, and track update rate were derived by analyzing updates to the unclassified Satellite Catalog (SatCat). Track update rates varied significantly for active payloads and debris and as such we used different models for the track update rates for military payloads and debris. The analysis was conducted using the System Effectiveness Analysis Simulation (SEAS) an agent based model developed by the United States Air Force Space Command’s Space and Missile Systems Center to evaluate the military utility of space systems. The future debris field was modeled by The Aerospace Corporation using a tool chain which models the growth of the 10cm+ debris field using high fidelity propagation, collision, and breakup models. Our analysis uses Two Line Element (TLE) sets and surface area data generated by this model sampled at the years 2019, 2029, and 2039. Data for the 2009 debris field is taken from the unclassified SatCat. By using Monte Carlo simulation techniques and varying the epoch of the military constellation relative to the debris field we were able to remove the bias of initial conditions. Additional analysis was conducted looking at the military utility impact of temporarily losing the use of Intelligence Surveillance and Reconnaissance (ISR) assets due to COLA maneuvers during a large classified scenario with stressful satellite tasking. This paper and presentation will focus only on unclassified results quantifying the potential reduction in the risk assumed by satellite flyers, and the potential reduction in Delta-V usage that is possible if we are able to improve our tracking performance in any of these three areas and reduce the positional uncertainty of space objects at the time of closest approach.

Improved meteorology from an updated WRF/CMAQ modeling ...

EPA Pesticide Factsheets

Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) that employs the Pleim-Xiu land surface model (PX LSM). Recently, PX LSM WRF/CMAQ has been updated in vegetation, soil, and boundary layer processes resulting in improved 2 m temperature (T) and mixing ratio (Q), 10 m wind speed, and surface ozone simulations across the domain compared to the previous version for a period around August 2006. Yearlong meteorology simulations with the updated system demonstrate that MODIS input helps reduce bias of the 2 m Q estimation during the growing season from April to September. Improvements follow the green-up in the southeast from April and move toward the west and north through August. From October to March, MODIS input does not have much influence on the system because vegetation is not as active. The greatest effects of MODIS input include more accurate phenology, better representation of leaf area index (LAI) for various forest ecosystems and agricultural areas, and realistically sparse vegetation coverage in the western drylands. Despite the improved meteorology, MODIS input causes higher bias for the surface O3 simulation in April, August, and October in areas where MODIS LAI is much less than the base LAI. Thus, improvement

Seluge++: A Secure Over-the-Air Programming Scheme in Wireless Sensor Networks

PubMed Central

Doroodgar, Farzan; Razzaque, Mohammad Abdur; Isnin, Ismail Fauzi

2014-01-01

Over-the-air dissemination of code updates in wireless sensor networks have been researchers' point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge. PMID:24618781

Seluge++: a secure over-the-air programming scheme in wireless sensor networks.

PubMed

Doroodgar, Farzan; Abdur Razzaque, Mohammad; Isnin, Ismail Fauzi

2014-03-11

Over-the-air dissemination of code updates in wireless sensor networks have been researchers' point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge.

Data Assimilation - Advances and Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Brian J.

2014-07-30

This presentation provides an overview of data assimilation (model calibration) for complex computer experiments. Calibration refers to the process of probabilistically constraining uncertain physics/engineering model inputs to be consistent with observed experimental data. An initial probability distribution for these parameters is updated using the experimental information. Utilization of surrogate models and empirical adjustment for model form error in code calibration form the basis for the statistical methodology considered. The role of probabilistic code calibration in supporting code validation is discussed. Incorporation of model form uncertainty in rigorous uncertainty quantification (UQ) analyses is also addressed. Design criteria used within a batchmore » sequential design algorithm are introduced for efficiently achieving predictive maturity and improved code calibration. Predictive maturity refers to obtaining stable predictive inference with calibrated computer codes. These approaches allow for augmentation of initial experiment designs for collecting new physical data. A standard framework for data assimilation is presented and techniques for updating the posterior distribution of the state variables based on particle filtering and the ensemble Kalman filter are introduced.« less

Continuous movement decoding using a target-dependent model with EMG inputs.

PubMed

Sachs, Nicholas A; Corbett, Elaine A; Miller, Lee E; Perreault, Eric J

2011-01-01

Trajectory-based models that incorporate target position information have been shown to accurately decode reaching movements from bio-control signals, such as muscle (EMG) and cortical activity (neural spikes). One major hurdle in implementing such models for neuroprosthetic control is that they are inherently designed to decode single reaches from a position of origin to a specific target. Gaze direction can be used to identify appropriate targets, however information regarding movement intent is needed to determine when a reach is meant to begin and when it has been completed. We used linear discriminant analysis to classify limb states into movement classes based on recorded EMG from a sparse set of shoulder muscles. We then used the detected state transitions to update target information in a mixture of Kalman filters that incorporated target position explicitly in the state, and used EMG activity to decode arm movements. Updating the target position initiated movement along new trajectories, allowing a sequence of appropriately timed single reaches to be decoded in series and enabling highly accurate continuous control.

A Cognitive Architecture for Human Performance Process Model Research

DTIC Science & Technology

1992-11-01

individually defined, updatable world representation which is a description of the world as the operator knows it. It contains rules for decisions, an...operate it), and rules of engagement (knowledge about the operator’s expected behavior). The HPP model works in the following way. Information enters...based models depict the problem-solving processes of experts. The experts’ knowledge is represented in symbol structures, along with rules for

Evaluation of the ground-water flow model for northern Utah Valley, Utah, updated to conditions through 2002

USGS Publications Warehouse

Thiros, Susan A.

2006-01-01

This report evaluates the performance of a numerical model of the ground-water system in northern Utah Valley, Utah, that originally simulated ground-water conditions during 1947-1980 and was updated to include conditions estimated for 1981-2002. Estimates of annual recharge to the ground-water system and discharge from wells in the area were added to the original ground-water flow model of the area.The files used in the original transient-state model of the ground-water flow system in northern Utah Valley were imported into MODFLOW-96, an updated version of MODFLOW. The main model input files modified as part of this effort were the well and recharge files. Discharge from pumping wells in northern Utah Valley was estimated on an annual basis for 1981-2002. Although the amount of average annual withdrawals from wells has not changed much since the previous study, there have been changes in the distribution of well discharge in the area. Discharge estimates for flowing wells during 1981-2002 were assumed to be the same as those used in the last stress period of the original model because of a lack of new data. Variations in annual recharge were assumed to be proportional to changes in total surface-water inflow to northern Utah Valley. Recharge specified in the model during the additional stress periods varied from 255,000 acre-feet in 1986 to 137,000 acre-feet in 1992.The ability of the updated transient-state model to match hydrologic conditions determined for 1981-2002 was evaluated by comparing water-level changes measured in wells to those computed by the model. Water-level measurements made in February, March, or April were available for 39 wells in the modeled area during all or part of 1981-2003. In most cases, the magnitude and direction of annual water-level change from 1981 to 2002 simulated by the updated model reasonably matched the measured change. The greater-than-normal precipitation that occurred during 1982-84 resulted in period-of-record high water levels measured in many of the observation wells in March 1984. The model-computed water levels at the end of 1982-84 also are among the highest for the period. Both measured and computed water levels decreased during the period representing ground-water conditions from 1999 to 2002. Precipitation was less than normal during 1999-2002.The ability of the model to adequately simulate climatic extremes such as the wetter-than-normal conditions of 1982-84 and the drier-than-normal conditions of 1999-2002 indicates that the annual variation of recharge to the ground-water system based on streamflow entering the valley, which in turn is primarily dependent upon precipitation, is appropriate but can be improved. The updated transient-state model of the ground-water system in northern Utah Valley can be improved by making revisions on the basis of currently available data and information.

Hybrid Adaptive Flight Control with Model Inversion Adaptation

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2011-01-01

This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

Finite element model updating and damage detection for bridges using vibration measurement.

DOT National Transportation Integrated Search

2013-12-01

In this report, the results of a study on developing a damage detection methodology based on Statistical Pattern Recognition are : presented. This methodology uses a new damage sensitive feature developed in this study that relies entirely on modal :...

Renewable Fuels Legislation Impact Analysis

EIA Publications

2005-01-01

An analysis based on an extension of the ethanol supply curve in our model to allow for enough ethanol production to meet the requirements of S. 650. This analysis provides an update of the May 23, 2005 analysis, with revised ethanol production and cost assumptions.

UPDATE ON DEVELOPMENT OF NUDGING FDDA FOR ADVANCED RESEARCH WRF

EPA Science Inventory

A nudging-based four-dimensional data assimilation (FDDA) system is being developed for the Weather Research and Forecasting (WRF) Model. This effort represents a collaboration between The Pennsylvania State University (i.e., Penn State), the National Center for Atmospheric Rese...

Simulated and observed 2010 floodwater elevations in selected river reaches in the Pawtuxet River Basin, Rhode Island

USGS Publications Warehouse

Zarriello, Phillip J.; Olson, Scott A.; Flynn, Robert H.; Strauch, Kellan R.; Murphy, Elizabeth A.

2014-01-01

Heavy, persistent rains from late February through March 2010 caused severe flooding that set, or nearly set, peaks of record for streamflows and water levels at many long-term streamgages in Rhode Island. In response to this event, hydraulic models were updated for selected reaches covering about 56 river miles in the Pawtuxet River Basin to simulate water-surface elevations (WSEs) at specified flows and boundary conditions. Reaches modeled included the main stem of the Pawtuxet River, the North and South Branches of the Pawtuxet River, Pocasset River, Simmons Brook, Dry Brook, Meshanticut Brook, Furnace Hill Brook, Flat River, Quidneck Brook, and two unnamed tributaries referred to as South Branch Pawtuxet River Tributary A1 and Tributary A2. All the hydraulic models were updated to Hydrologic Engineering Center-River Analysis System (HEC-RAS) version 4.1.0 using steady-state simulations. Updates to the models included incorporation of new field-survey data at structures, high resolution land-surface elevation data, and updated flood flows from a related study. The models were assessed using high-water marks (HWMs) obtained in a related study following the March– April 2010 flood and the simulated water levels at the 0.2-percent annual exceedance probability (AEP), which is the estimated AEP of the 2010 flood in the basin. HWMs were obtained at 110 sites along the main stem of the Pawtuxet River, the North and South Branches of the Pawtuxet River, Pocasset River, Simmons Brook, Furnace Hill Brook, Flat River, and Quidneck Brook. Differences between the 2010 HWM elevations and the simulated 0.2-percent AEP WSEs from flood insurance studies (FISs) and the updated models developed in this study varied with most differences attributed to the magnitude of the 0.2-percent AEP flows. WSEs from the updated models generally are in closer agreement with the observed 2010 HWMs than with the FIS WSEs. The improved agreement of the updated simulated water elevations to observed 2010 HWMs provides a measure of the hydraulic model performance, which indicates the updated models better represent flooding at other AEPs than the existing FIS models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dykstra, D.; Blomer, J.

Both the CernVM File System (CVMFS) and the Frontier Distributed Database Caching System (Frontier) distribute centrally updated data worldwide for LHC experiments using http proxy caches. Neither system provides privacy or access control on reading the data, but both control access to updates of the data and can guarantee the authenticity and integrity of the data transferred to clients over the internet. CVMFS has since its early days required digital signatures and secure hashes on all distributed data, and recently Frontier has added X.509-based authenticity and integrity checking. In this paper we detail and compare the security models of CVMFSmore » and Frontier.« less

On the difficulty to optimally implement the Ensemble Kalman filter: An experiment based on many hydrological models and catchments

NASA Astrophysics Data System (ADS)

Thiboult, A.; Anctil, F.

2015-10-01

Forecast reliability and accuracy is a prerequisite for successful hydrological applications. This aim may be attained by using data assimilation techniques such as the popular Ensemble Kalman filter (EnKF). Despite its recognized capacity to enhance forecasting by creating a new set of initial conditions, implementation tests have been mostly carried out with a single model and few catchments leading to case specific conclusions. This paper performs an extensive testing to assess ensemble bias and reliability on 20 conceptual lumped models and 38 catchments in the Province of Québec with perfect meteorological forecast forcing. The study confirms that EnKF is a powerful tool for short range forecasting but also that it requires a more subtle setting than it is frequently recommended. The success of the updating procedure depends to a great extent on the specification of the hyper-parameters. In the implementation of the EnKF, the identification of the hyper-parameters is very unintuitive if the model error is not explicitly accounted for and best estimates of forcing and observation error lead to overconfident forecasts. It is shown that performance are also related to the choice of updated state variables and that all states variables should not systematically be updated. Additionally, the improvement over the open loop scheme depends on the watershed and hydrological model structure, as some models exhibit a poor compatibility with EnKF updating. Thus, it is not possible to conclude in detail on a single ideal manner to identify an optimal implementation; conclusions drawn from a unique event, catchment, or model are likely to be misleading since transferring hyper-parameters from a case to another may be hazardous. Finally, achieving reliability and bias jointly is a daunting challenge as the optimization of one score is done at the cost of the other.

Stellar Parameters for Trappist-1

NASA Astrophysics Data System (ADS)

Van Grootel, Valérie; Fernandes, Catarina S.; Gillon, Michael; Jehin, Emmanuel; Manfroid, Jean; Scuflaire, Richard; Burgasser, Adam J.; Barkaoui, Khalid; Benkhaldoun, Zouhair; Burdanov, Artem; Delrez, Laetitia; Demory, Brice-Olivier; de Wit, Julien; Queloz, Didier; Triaud, Amaury H. M. J.

2018-01-01

TRAPPIST-1 is an ultracool dwarf star transited by seven Earth-sized planets, for which thorough characterization of atmospheric properties, surface conditions encompassing habitability, and internal compositions is possible with current and next-generation telescopes. Accurate modeling of the star is essential to achieve this goal. We aim to obtain updated stellar parameters for TRAPPIST-1 based on new measurements and evolutionary models, compared to those used in discovery studies. We present a new measurement for the parallax of TRAPPIST-1, 82.4 ± 0.8 mas, based on 188 epochs of observations with the TRAPPIST and Liverpool Telescopes from 2013 to 2016. This revised parallax yields an updated luminosity of {L}* =(5.22+/- 0.19)× {10}-4 {L}ȯ , which is very close to the previous estimate but almost two times more precise. We next present an updated estimate for TRAPPIST-1 stellar mass, based on two approaches: mass from stellar evolution modeling, and empirical mass derived from dynamical masses of equivalently classified ultracool dwarfs in astrometric binaries. We combine them using a Monte-Carlo approach to derive a semi-empirical estimate for the mass of TRAPPIST-1. We also derive estimate for the radius by combining this mass with stellar density inferred from transits, as well as an estimate for the effective temperature from our revised luminosity and radius. Our final results are {M}* =0.089+/- 0.006 {M}ȯ , {R}* =0.121+/- 0.003 {R}ȯ , and {T}{eff} = 2516 ± 41 K. Considering the degree to which the TRAPPIST-1 system will be scrutinized in coming years, these revised and more precise stellar parameters should be considered when assessing the properties of TRAPPIST-1 planets.

Machine learning in updating predictive models of planning and scheduling transportation projects

DOT National Transportation Integrated Search

1997-01-01

A method combining machine learning and regression analysis to automatically and intelligently update predictive models used in the Kansas Department of Transportations (KDOTs) internal management system is presented. The predictive models used...

Benefits of Model Updating: A Case Study Using the Micro-Precision Interferometer Testbed

NASA Technical Reports Server (NTRS)

Neat, Gregory W.; Kissil, Andrew; Joshi, Sanjay S.

1997-01-01

This paper presents a case study on the benefits of model updating using the Micro-Precision Interferometer (MPI) testbed, a full-scale model of a future spaceborne optical interferometer located at JPL.

Preliminary Model of Porphyry Copper Deposits

USGS Publications Warehouse

Berger, Byron R.; Ayuso, Robert A.; Wynn, Jeffrey C.; Seal, Robert R.

2008-01-01

The U.S. Geological Survey (USGS) Mineral Resources Program develops mineral-deposit models for application in USGS mineral-resource assessments and other mineral resource-related activities within the USGS as well as for nongovernmental applications. Periodic updates of models are published in order to incorporate new concepts and findings on the occurrence, nature, and origin of specific mineral deposit types. This update is a preliminary model of porphyry copper deposits that begins an update process of porphyry copper models published in USGS Bulletin 1693 in 1986. This update includes a greater variety of deposit attributes than were included in the 1986 model as well as more information about each attribute. It also includes an expanded discussion of geophysical and remote sensing attributes and tools useful in resource evaluations, a summary of current theoretical concepts of porphyry copper deposit genesis, and a summary of the environmental attributes of unmined and mined deposits.

Effective Visual Tracking Using Multi-Block and Scale Space Based on Kernelized Correlation Filters

PubMed Central

Jeong, Soowoong; Kim, Guisik; Lee, Sangkeun

2017-01-01

Accurate scale estimation and occlusion handling is a challenging problem in visual tracking. Recently, correlation filter-based trackers have shown impressive results in terms of accuracy, robustness, and speed. However, the model is not robust to scale variation and occlusion. In this paper, we address the problems associated with scale variation and occlusion by employing a scale space filter and multi-block scheme based on a kernelized correlation filter (KCF) tracker. Furthermore, we develop a more robust algorithm using an appearance update model that approximates the change of state of occlusion and deformation. In particular, an adaptive update scheme is presented to make each process robust. The experimental results demonstrate that the proposed method outperformed 29 state-of-the-art trackers on 100 challenging sequences. Specifically, the results obtained with the proposed scheme were improved by 8% and 18% compared to those of the KCF tracker for 49 occlusion and 64 scale variation sequences, respectively. Therefore, the proposed tracker can be a robust and useful tool for object tracking when occlusion and scale variation are involved. PMID:28241475

Effective Visual Tracking Using Multi-Block and Scale Space Based on Kernelized Correlation Filters.

PubMed

Jeong, Soowoong; Kim, Guisik; Lee, Sangkeun

2017-02-23

Accurate scale estimation and occlusion handling is a challenging problem in visual tracking. Recently, correlation filter-based trackers have shown impressive results in terms of accuracy, robustness, and speed. However, the model is not robust to scale variation and occlusion. In this paper, we address the problems associated with scale variation and occlusion by employing a scale space filter and multi-block scheme based on a kernelized correlation filter (KCF) tracker. Furthermore, we develop a more robust algorithm using an appearance update model that approximates the change of state of occlusion and deformation. In particular, an adaptive update scheme is presented to make each process robust. The experimental results demonstrate that the proposed method outperformed 29 state-of-the-art trackers on 100 challenging sequences. Specifically, the results obtained with the proposed scheme were improved by 8% and 18% compared to those of the KCF tracker for 49 occlusion and 64 scale variation sequences, respectively. Therefore, the proposed tracker can be a robust and useful tool for object tracking when occlusion and scale variation are involved.

Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers

PubMed Central

Chang, Xiaodong; Huang, Jinquan; Lu, Feng

2017-01-01

For a sensor fault diagnostic system of aircraft engines, the health performance degradation is an inevitable interference that cannot be neglected. To address this issue, this paper investigates an integrated on-line sensor fault diagnostic scheme for a commercial aircraft engine based on a sliding mode observer (SMO). In this approach, one sliding mode observer is designed for engine health performance tracking, and another for sensor fault reconstruction. Both observers are employed in in-flight applications. The results of the former SMO are analyzed for post-flight updating the baseline model of the latter. This idea is practical and feasible since the updating process does not require the algorithm to be regulated or redesigned, so that ground-based intervention is avoided, and the update process is implemented in an economical and efficient way. With this setup, the robustness of the proposed scheme to the health degradation is much enhanced and the latter SMO is able to fulfill sensor fault reconstruction over the course of the engine life. The proposed sensor fault diagnostic system is applied to a nonlinear simulation of a commercial aircraft engine, and its effectiveness is evaluated in several fault scenarios. PMID:28398255

An investigation of soil-structure interaction effects observed at the MIT Green Building

USGS Publications Warehouse

Taciroglu, Ertugrul; Çelebi, Mehmet; Ghahari, S. Farid; Abazarsa, Fariba

2016-01-01

The soil-foundation impedance function of the MIT Green Building is identified from its response signals recorded during an earthquake. Estimation of foundation impedance functions from seismic response signals is a challenging task, because: (1) the foundation input motions (FIMs) are not directly measurable, (2) the as-built properties of the super-structure are only approximately known, and (3) the soil-foundation impedance functions are inherently frequency-dependent. In the present study, aforementioned difficulties are circumvented by using, in succession, a blind modal identification (BMID) method, a simplified Timoshenko beam model (TBM), and a parametric updating of transfer functions (TFs). First, the flexible-base modal properties of the building are identified from response signals using the BMID method. Then, a flexible-base TBM is updated using the identified modal data. Finally, the frequency-dependent soil-foundation impedance function is estimated by minimizing the discrepancy between TFs (of pairs instrumented floors) that are (1) obtained experimentally from earthquake data and (2) analytically from the updated TBM. Using the fully identified flexible-base TBM, the FIMs as well as building responses at locations without instruments can be predicted, as demonstrated in the present study.

Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers.

PubMed

Chang, Xiaodong; Huang, Jinquan; Lu, Feng

2017-04-11

For a sensor fault diagnostic system of aircraft engines, the health performance degradation is an inevitable interference that cannot be neglected. To address this issue, this paper investigates an integrated on-line sensor fault diagnostic scheme for a commercial aircraft engine based on a sliding mode observer (SMO). In this approach, one sliding mode observer is designed for engine health performance tracking, and another for sensor fault reconstruction. Both observers are employed in in-flight applications. The results of the former SMO are analyzed for post-flight updating the baseline model of the latter. This idea is practical and feasible since the updating process does not require the algorithm to be regulated or redesigned, so that ground-based intervention is avoided, and the update process is implemented in an economical and efficient way. With this setup, the robustness of the proposed scheme to the health degradation is much enhanced and the latter SMO is able to fulfill sensor fault reconstruction over the course of the engine life. The proposed sensor fault diagnostic system is applied to a nonlinear simulation of a commercial aircraft engine, and its effectiveness is evaluated in several fault scenarios.

Finite grade pheromone ant colony optimization for image segmentation

NASA Astrophysics Data System (ADS)

Yuanjing, F.; Li, Y.; Liangjun, K.

2008-06-01

By combining the decision process of ant colony optimization (ACO) with the multistage decision process of image segmentation based on active contour model (ACM), an algorithm called finite grade ACO (FACO) for image segmentation is proposed. This algorithm classifies pheromone into finite grades and updating of the pheromone is achieved by changing the grades and the updated quantity of pheromone is independent from the objective function. The algorithm that provides a new approach to obtain precise contour is proved to converge to the global optimal solutions linearly by means of finite Markov chains. The segmentation experiments with ultrasound heart image show the effectiveness of the algorithm. Comparing the results for segmentation of left ventricle images shows that the ACO for image segmentation is more effective than the GA approach and the new pheromone updating strategy appears good time performance in optimization process.

Kalman approach to accuracy management for interoperable heterogeneous model abstraction within an HLA-compliant simulation

NASA Astrophysics Data System (ADS)

Leskiw, Donald M.; Zhau, Junmei

2000-06-01

This paper reports on results from an ongoing project to develop methodologies for representing and managing multiple, concurrent levels of detail and enabling high performance computing using parallel arrays within distributed object-based simulation frameworks. At this time we present the methodology for representing and managing multiple, concurrent levels of detail and modeling accuracy by using a representation based on the Kalman approach for estimation. The Kalman System Model equations are used to represent model accuracy, Kalman Measurement Model equations provide transformations between heterogeneous levels of detail, and interoperability among disparate abstractions is provided using a form of the Kalman Update equations.

Moving target detection method based on improved Gaussian mixture model

NASA Astrophysics Data System (ADS)

Ma, J. Y.; Jie, F. R.; Hu, Y. J.

2017-07-01

Gaussian Mixture Model is often employed to build background model in background difference methods for moving target detection. This paper puts forward an adaptive moving target detection algorithm based on improved Gaussian Mixture Model. According to the graylevel convergence for each pixel, adaptively choose the number of Gaussian distribution to learn and update background model. Morphological reconstruction method is adopted to eliminate the shadow.. Experiment proved that the proposed method not only has good robustness and detection effect, but also has good adaptability. Even for the special cases when the grayscale changes greatly and so on, the proposed method can also make outstanding performance.

Build-Up Approach to Updating the Mock Quiet Spike Beam Model

NASA Technical Reports Server (NTRS)

Herrera, Claudia Y.; Pak, Chan-gi

2007-01-01

When a new aircraft is designed or a modification is done to an existing aircraft, the aeroelastic properties of the aircraft should be examined to ensure the aircraft is flight worthy. Evaluating the aeroelastic properties of a new or modified aircraft can include performing a variety of analyses, such as modal and flutter analyses. In order to produce accurate results from these analyses, it is imperative to work with finite element models (FEM) that have been validated by or correlated to ground vibration test (GVT) data, Updating an analytical model using measured data is a challenge in the area of structural dynamics. The analytical model update process encompasses a series of optimizations that match analytical frequencies and mode shapes to the measured modal characteristics of structure. In the past, the method used to update a model to test data was "trial and error." This is an inefficient method - running a modal analysis, comparing the analytical results to the GVT data, manually modifying one or more structural parameters (mass, CG, inertia, area, etc.), rerunning the analysis, and comparing the new analytical modal characteristics to the GVT modal data. If the match is close enough (close enough defined by analyst's updating requirements), then the updating process is completed. If the match does not meet updating-requirements, then the parameters are changed again and the process is repeated. Clearly, this manual optimization process is highly inefficient for large FEM's and/or a large number of structural parameters. NASA Dryden Flight Research Center (DFRC) has developed, in-house, a Mode Matching Code that automates the above-mentioned optimization process, DFRC's in-house Mode Matching Code reads mode shapes and frequencies acquired from GVT to create the target model. It also reads the current analytical model, as we11 as the design variables and their upper and lower limits. It performs a modal analysis on this model and modifies it to create an updated model that has similar mode shapes and frequencies as those of the target model. The Mode Matching Code output frequencies and modal assurance criteria (MAC) values that allow for the quantified comparison of the updated model versus the target model. A recent application of this code is the F453 supersonic flight testing platform, NASA DFRC possesses a modified F-15B that is used as a test bed aircraft for supersonic flight experiments. Traditionally, the finite element model of the test article is generated. A GVT is done on the test article ta validate and update its FEM. This FEM is then mated to the F-15B model, which was correlated to GVT data in fall of 2004, A GVT is conducted with the test article mated to the aircraft, and this mated F-15B/ test article FEM is correlated to this final GVT.

Simulation and analyses of the aeroassist flight experiment attitude update method

NASA Technical Reports Server (NTRS)

Carpenter, J. R.

1991-01-01

A method which will be used to update the alignment of the Aeroassist Flight Experiment's Inertial Measuring Unit is simulated and analyzed. This method, the Star Line Maneuver, uses measurements from the Space Shuttle Orbiter star trackers along with an extended Kalman filter to estimate a correction to the attitude quaternion maintained by an Inertial Measuring Unit in the Orbiter's payload bay. This quaternion is corrupted by on-orbit bending of the Orbiter payload bay with respect to the Orbiter navigation base, which is incorporated into the payload quaternion when it is initialized via a direct transfer of the Orbiter attitude state. The method of updating this quaternion is examined through verification of baseline cases and Monte Carlo analysis using a simplified simulation, The simulation uses nominal state dynamics and measurement models from the Kalman filter as its real world models, and is programmed on Microvax minicomputer using Matlab, and interactive matrix analysis tool. Results are presented which confirm and augment previous performance studies, thereby enhancing confidence in the Star Line Maneuver design methodology.

Improved version of the PHOBOS Glauber Monte Carlo

DOE PAGES

Loizides, C.; Nagle, J.; Steinberg, P.

2015-09-01

“Glauber” models are used to calculate geometric quantities in the initial state of heavy ion collisions, such as impact parameter, number of participating nucleons and initial eccentricity. Experimental heavy-ion collaborations, in particular at RHIC and LHC, use Glauber Model calculations for various geometric observables for determination of the collision centrality. In this document, we describe the assumptions inherent to the approach, and provide an updated implementation (v2) of the Monte Carlo based Glauber Model calculation, which originally was used by the PHOBOS collaboration. The main improvement w.r.t. the earlier version (v1) (Alver et al. 2008) is the inclusion of Tritium,more » Helium-3, and Uranium, as well as the treatment of deformed nuclei and Glauber–Gribov fluctuations of the proton in p +A collisions. A users’ guide (updated to reflect changes in v2) is provided for running various calculations.« less

a Model for Brand Competition Within a Social Network

NASA Astrophysics Data System (ADS)

Huerta-Quintanilla, R.; Canto-Lugo, E.; Rodríguez-Achach, M.

An agent-based model was built representing an economic environment in which m brands are competing for a product market. These agents represent companies that interact within a social network in which a certain agent persuades others to update or shift their brands; the brands of the products they are using. Decision rules were established that caused each agent to react according to the economic benefits it would receive; they updated/shifted only if it was beneficial. Each agent can have only one of the m possible brands, and she can interact with its two nearest neighbors and another set of agents which are chosen according to a particular set of rules in the network topology. An absorbing state was always reached in which a single brand monopolized the network (known as condensation). The condensation time varied as a function of model parameters is studied including an analysis of brand competition using different networks.

Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant

DOEpatents

Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa

2013-09-17

System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.

Simulated and observed 2010 floodwater elevations in the Pawcatuck and Wood Rivers, Rhode Island

USGS Publications Warehouse

Zarriello, Phillip J.; Straub, David E.; Smith, Thor E.

2014-01-01

Heavy, persistent rains from late February through March 2010 caused severe flooding that set, or nearly set, peaks of record for streamflows and water levels at many long-term U.S. Geological Survey streamgages in Rhode Island. In response to this flood, hydraulic models of Pawcatuck River (26.9 miles) and Wood River (11.6 miles) were updated from the most recent approved U.S. Department of Homeland Security-Federal Emergency Management Agency flood insurance study (FIS) to simulate water-surface elevations (WSEs) for specified flows and boundary conditions. The hydraulic models were updated to Hydrologic Engineering Center-River Analysis System (HEC-RAS) using steady-state simulations and incorporate new field-survey data at structures, high resolution land-surface elevation data, and updated flood flows from a related study. The models were used to simulate the 0.2-percent annual exceedance probability (AEP) flood, which is the AEP determined for the 2010 flood in the Pawcatuck and Wood Rivers. The simulated WSEs were compared to high-water mark (HWM) elevation data obtained in a related study following the March–April 2010 flood, which included 39 HWMs along the Pawcatuck River and 11 HWMs along the Wood River. The 2010 peak flow generally was larger than the 0.2-percent AEP flow, which, in part, resulted in the FIS and updated model WSEs to be lower than the 2010 HWMs. The 2010 HWMs for the Pawcatuck River averaged about 1.6 feet (ft) higher than the 0.2-percent AEP WSEs simulated in the updated model and 2.5 ft higher than the WSEs in the FIS. The 2010 HWMs for the Wood River averaged about 1.3 ft higher than the WSEs simulated in the updated model and 2.5 ft higher than the WSEs in the FIS. The improved agreement of the updated simulated water elevations to observed 2010 HWMs provides a measure of the hydraulic model performance, which indicates the updated models better represent flooding at other AEPs than the existing FIS models.

Management of undescended testis may be improved with educational updates and new transferring model.

PubMed

Yi, Wei; Sheng-de, Wu; Lian-Ju, Shen; Tao, Lin; Da-Wei, He; Guang-Hui, Wei

2018-05-24

To investigate whether management of undescended testis (UDT) may be improved with educational updates and new transferring model among referring providers (RPs). The age of orchidopexies performed in Children's Hospital of Chongqing Medical University were reviewed. We then proposed educational updates and new transferring model among RPs. The age of orchidopexies performed after our intervention were collected. Data were represented graphically and statistical analysis Chi-square for trend were used. A total of 1543 orchidopexies were performed. The median age of orchidopexy did not matched the target age of 6-12 months in any subsequent year. Survey of the RPs showed that 48.85% of their recommended age was below 12 months. However, only 25.50% of them would directly make a surgical referral to pediatric surgery specifically at this point. After we proposed educational updates, tracking the age of orchidopexy revealed a statistically significant trend downward. The management of undescended testis may be improved with educational updates and new transferring model among primary healthcare practitioners.

Building a Better Campus: An Update on Building Codes.

ERIC Educational Resources Information Center

Madden, Michael J.

2002-01-01

Discusses the implications for higher education institutions in terms of facility planning, design, construction, and renovation of the move from regionally-developed model-building codes to two international sets of codes. Also addresses the new performance-based design option within the codes. (EV)

Uncertainty Estimation in Elastic Full Waveform Inversion by Utilising the Hessian Matrix

NASA Astrophysics Data System (ADS)

Hagen, V. S.; Arntsen, B.; Raknes, E. B.

2017-12-01

Elastic Full Waveform Inversion (EFWI) is a computationally intensive iterative method for estimating elastic model parameters. A key element of EFWI is the numerical solution of the elastic wave equation which lies as a foundation to quantify the mismatch between synthetic (modelled) and true (real) measured seismic data. The misfit between the modelled and true receiver data is used to update the parameter model to yield a better fit between the modelled and true receiver signal. A common approach to the EFWI model update problem is to use a conjugate gradient search method. In this approach the resolution and cross-coupling for the estimated parameter update can be found by computing the full Hessian matrix. Resolution of the estimated model parameters depend on the chosen parametrisation, acquisition geometry, and temporal frequency range. Although some understanding has been gained, it is still not clear which elastic parameters can be reliably estimated under which conditions. With few exceptions, previous analyses have been based on arguments using radiation pattern analysis. We use the known adjoint-state technique with an expansion to compute the Hessian acting on a model perturbation to conduct our study. The Hessian is used to infer parameter resolution and cross-coupling for different selections of models, acquisition geometries, and data types, including streamer and ocean bottom seismic recordings. Information about the model uncertainty is obtained from the exact Hessian, and is essential when evaluating the quality of estimated parameters due to the strong influence of source-receiver geometry and frequency content. Investigation is done on both a homogeneous model and the Gullfaks model where we illustrate the influence of offset on parameter resolution and cross-coupling as a way of estimating uncertainty.

Space-Based Sensorweb Monitoring of Wildfires in Thailand

NASA Technical Reports Server (NTRS)

Chien, Steve; Doubleday, Joshua; Mclaren, David; Davies, Ashley; Tran, Daniel; Tanpipat, Veerachai; Akaakara, Siri; Ratanasuwan, Anuchit; Mandl, Daniel

2011-01-01

We describe efforts to apply sensorweb technologies to the monitoring of forest fires in Thailand. In this approach, satellite data and ground reports are assimilated to assess the current state of the forest system in terms of forest fire risk, active fires, and likely progression of fires and smoke plumes. This current and projected assessment can then be used to actively direct sensors and assets to best acquire further information. This process operates continually with new data updating models of fire activity leading to further sensing and updating of models. As the fire activity is tracked, products such as active fire maps, burn scar severity maps, and alerts are automatically delivered to relevant parties.We describe the current state of the Thailand Fire Sensorweb which utilizes the MODIS-based FIRMS system to track active fires and trigger Earth Observing One / Advanced Land Imager to acquire imagery and produce active fire maps, burn scar severity maps, and alerts. We describe ongoing work to integrate additional sensor sources and generate additional products.

Revisit of cosmic ray antiprotons from dark matter annihilation with updated constraints on the background model from AMS-02 and collider data

NASA Astrophysics Data System (ADS)

Cui, Ming-Yang; Pan, Xu; Yuan, Qiang; Fan, Yi-Zhong; Zong, Hong-Shi

2018-06-01

We study the cosmic ray antiprotons with updated constraints on the propagation, proton injection, and solar modulation parameters based on the newest AMS-02 data near the Earth and Voyager data in the local interstellar space, and on the cross section of antiproton production due to proton-proton collisions based on new collider data. We use a Bayesian approach to properly consider the uncertainties of the model predictions of both the background and the dark matter (DM) annihilation components of antiprotons. We find that including an extra component of antiprotons from the annihilation of DM particles into a pair of quarks can improve the fit to the AMS-02 antiproton data considerably. The favored mass of DM particles is about 60~100 GeV, and the annihilation cross section is just at the level of the thermal production of DM (langleσvrangle ~ O(10‑26) cm3 s‑1).

Competition in high dimensional spaces using a sparse approximation of neural fields.

PubMed

Quinton, Jean-Charles; Girau, Bernard; Lefort, Mathieu

2011-01-01

The Continuum Neural Field Theory implements competition within topologically organized neural networks with lateral inhibitory connections. However, due to the polynomial complexity of matrix-based implementations, updating dense representations of the activity becomes computationally intractable when an adaptive resolution or an arbitrary number of input dimensions is required. This paper proposes an alternative to self-organizing maps with a sparse implementation based on Gaussian mixture models, promoting a trade-off in redundancy for higher computational efficiency and alleviating constraints on the underlying substrate.This version reproduces the emergent attentional properties of the original equations, by directly applying them within a continuous approximation of a high dimensional neural field. The model is compatible with preprocessed sensory flows but can also be interfaced with artificial systems. This is particularly important for sensorimotor systems, where decisions and motor actions must be taken and updated in real-time. Preliminary tests are performed on a reactive color tracking application, using spatially distributed color features.

Formulation of consumables management models: Consumables flight planning worksheet update. [space shuttles

NASA Technical Reports Server (NTRS)

Newman, C. M.

1977-01-01

The updated consumables flight planning worksheet (CFPWS) is documented. The update includes: (1) additional consumables: ECLSS ammonia, APU propellant, HYD water; (2) additional on orbit activity for development flight instrumentation (DFI); (3) updated use factors for all consumables; and (4) sources and derivations of the use factors.

Update of global TC simulations using a variable resolution non-hydrostatic model

NASA Astrophysics Data System (ADS)

Park, S. H.

2017-12-01

Using in a variable resolution meshes in MPAS during 2017 summer., Tropical cyclone (TC) forecasts are simulated. Two physics suite are tested to explore performance and bias of each physics suite for TC forecasting. A WRF physics suite is selected from experience on weather forecasting and CAM (Community Atmosphere Model) physics is taken from a AMIP type climate simulation. Based on the last year results from CAM5 physical parameterization package and comparing with WRF physics, we investigated a issue with intensity bias using updated version of CAM physics (CAM6). We also compared these results with coupled version of TC simulations. During this talk, TC structure will be compared specially around of boundary layer and investigate their relationship between TC intensity and different physics package.

Nonequivalence of updating rules in evolutionary games under high mutation rates.

PubMed

Kaiping, G A; Jacobs, G S; Cox, S J; Sluckin, T J

2014-10-01

Moran processes are often used to model selection in evolutionary simulations. The updating rule in Moran processes is a birth-death process, i. e., selection according to fitness of an individual to give birth, followed by the death of a random individual. For well-mixed populations with only two strategies this updating rule is known to be equivalent to selecting unfit individuals for death and then selecting randomly for procreation (biased death-birth process). It is, however, known that this equivalence does not hold when considering structured populations. Here we study whether changing the updating rule can also have an effect in well-mixed populations in the presence of more than two strategies and high mutation rates. We find, using three models from different areas of evolutionary simulation, that the choice of updating rule can change model results. We show, e. g., that going from the birth-death process to the death-birth process can change a public goods game with punishment from containing mostly defectors to having a majority of cooperative strategies. From the examples given we derive guidelines indicating when the choice of the updating rule can be expected to have an impact on the results of the model.

Nonequivalence of updating rules in evolutionary games under high mutation rates

NASA Astrophysics Data System (ADS)

Kaiping, G. A.; Jacobs, G. S.; Cox, S. J.; Sluckin, T. J.

2014-10-01

Moran processes are often used to model selection in evolutionary simulations. The updating rule in Moran processes is a birth-death process, i. e., selection according to fitness of an individual to give birth, followed by the death of a random individual. For well-mixed populations with only two strategies this updating rule is known to be equivalent to selecting unfit individuals for death and then selecting randomly for procreation (biased death-birth process). It is, however, known that this equivalence does not hold when considering structured populations. Here we study whether changing the updating rule can also have an effect in well-mixed populations in the presence of more than two strategies and high mutation rates. We find, using three models from different areas of evolutionary simulation, that the choice of updating rule can change model results. We show, e. g., that going from the birth-death process to the death-birth process can change a public goods game with punishment from containing mostly defectors to having a majority of cooperative strategies. From the examples given we derive guidelines indicating when the choice of the updating rule can be expected to have an impact on the results of the model.

MOS 2.0: Modeling the Next Revolutionary Mission Operations System

NASA Technical Reports Server (NTRS)

Delp, Christopher L.; Bindschadler, Duane; Wollaeger, Ryan; Carrion, Carlos; McCullar, Michelle; Jackson, Maddalena; Sarrel, Marc; Anderson, Louise; Lam, Doris

2011-01-01

Designed and implemented in the 1980's, the Advanced Multi-Mission Operations System (AMMOS) was a breakthrough for deep-space NASA missions, enabling significant reductions in the cost and risk of implementing ground systems. By designing a framework for use across multiple missions and adaptability to specific mission needs, AMMOS developers created a set of applications that have operated dozens of deep-space robotic missions over the past 30 years. We seek to leverage advances in technology and practice of architecting and systems engineering, using model-based approaches to update the AMMOS. We therefore revisit fundamental aspects of the AMMOS, resulting in a major update to the Mission Operations System (MOS): MOS 2.0. This update will ensure that the MOS can support an increasing range of mission types, (such as orbiters, landers, rovers, penetrators and balloons), and that the operations systems for deep-space robotic missions can reap the benefits of an iterative multi-mission framework.12 This paper reports on the first phase of this major update. Here we describe the methods and formal semantics used to address MOS 2.0 architecture and some early results. Early benefits of this approach include improved stakeholder input and buy-in, the ability to articulate and focus effort on key, system-wide principles, and efficiency gains obtained by use of well-architected design patterns and the use of models to improve the quality of documentation and decrease the effort required to produce and maintain it. We find that such methods facilitate reasoning, simulation, analysis on the system design in terms of design impacts, generation of products (e.g., project-review and software-delivery products), and use of formal process descriptions to enable goal-based operations. This initial phase yields a forward-looking and principled MOS 2.0 architectural vision, which considers both the mission-specific context and long-term system sustainability.

Geodesy- and geology-based slip-rate models for the Western United States (excluding California) national seismic hazard maps

USGS Publications Warehouse

Petersen, Mark D.; Zeng, Yuehua; Haller, Kathleen M.; McCaffrey, Robert; Hammond, William C.; Bird, Peter; Moschetti, Morgan; Shen, Zhengkang; Bormann, Jayne; Thatcher, Wayne

2014-01-01

The 2014 National Seismic Hazard Maps for the conterminous United States incorporate additional uncertainty in fault slip-rate parameter that controls the earthquake-activity rates than was applied in previous versions of the hazard maps. This additional uncertainty is accounted for by new geodesy- and geology-based slip-rate models for the Western United States. Models that were considered include an updated geologic model based on expert opinion and four combined inversion models informed by both geologic and geodetic input. The two block models considered indicate significantly higher slip rates than the expert opinion and the two fault-based combined inversion models. For the hazard maps, we apply 20 percent weight with equal weighting for the two fault-based models. Off-fault geodetic-based models were not considered in this version of the maps. Resulting changes to the hazard maps are generally less than 0.05 g (acceleration of gravity). Future research will improve the maps and interpret differences between the new models.

OSATE Overview & Community Updates

DTIC Science & Technology

2015-02-15

update 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Delange /Julien 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK...main language capabilities Modeling patterns & model samples for beginners Error-Model examples EMV2 model constructs Demonstration of tools Case

A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating.

PubMed

Knips, Guido; Zibner, Stephan K U; Reimann, Hendrik; Schöner, Gregor

2017-01-01

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp.

A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating

PubMed Central

Knips, Guido; Zibner, Stephan K. U.; Reimann, Hendrik; Schöner, Gregor

2017-01-01

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp. PMID:28303100

Description and evaluation of the Community Multiscale Air ...

EPA Pesticide Factsheets

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O3) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM2. 5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O3 mixing ratios, primarily due to reduced

An interval model updating strategy using interval response surface models

NASA Astrophysics Data System (ADS)

Fang, Sheng-En; Zhang, Qiu-Hu; Ren, Wei-Xin

2015-08-01

Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass-spring system and also against a set of experimentally tested steel plates.

Updating the Behavior Engineering Model.

ERIC Educational Resources Information Center

Chevalier, Roger

2003-01-01

Considers Thomas Gilbert's Behavior Engineering Model as a tool for systematically identifying barriers to individual and organizational performance. Includes a detailed case study and a performance aid that incorporates gap analysis, cause analysis, and force field analysis to update the original model. (Author/LRW)

mRNA translation and protein synthesis: an analysis of different modelling methodologies and a new PBN based approach

PubMed Central

2014-01-01

Background mRNA translation involves simultaneous movement of multiple ribosomes on the mRNA and is also subject to regulatory mechanisms at different stages. Translation can be described by various codon-based models, including ODE, TASEP, and Petri net models. Although such models have been extensively used, the overlap and differences between these models and the implications of the assumptions of each model has not been systematically elucidated. The selection of the most appropriate modelling framework, and the most appropriate way to develop coarse-grained/fine-grained models in different contexts is not clear. Results We systematically analyze and compare how different modelling methodologies can be used to describe translation. We define various statistically equivalent codon-based simulation algorithms and analyze the importance of the update rule in determining the steady state, an aspect often neglected. Then a novel probabilistic Boolean network (PBN) model is proposed for modelling translation, which enjoys an exact numerical solution. This solution matches those of numerical simulation from other methods and acts as a complementary tool to analytical approximations and simulations. The advantages and limitations of various codon-based models are compared, and illustrated by examples with real biological complexities such as slow codons, premature termination and feedback regulation. Our studies reveal that while different models gives broadly similiar trends in many cases, important differences also arise and can be clearly seen, in the dependence of the translation rate on different parameters. Furthermore, the update rule affects the steady state solution. Conclusions The codon-based models are based on different levels of abstraction. Our analysis suggests that a multiple model approach to understanding translation allows one to ascertain which aspects of the conclusions are robust with respect to the choice of modelling methodology, and when (and why) important differences may arise. This approach also allows for an optimal use of analysis tools, which is especially important when additional complexities or regulatory mechanisms are included. This approach can provide a robust platform for dissecting translation, and results in an improved predictive framework for applications in systems and synthetic biology. PMID:24576337

The Nature of Belief-Directed Exploratory Choice in Human Decision-Making

PubMed Central

Knox, W. Bradley; Otto, A. Ross; Stone, Peter; Love, Bradley C.

2011-01-01

In non-stationary environments, there is a conflict between exploiting currently favored options and gaining information by exploring lesser-known options that in the past have proven less rewarding. Optimal decision-making in such tasks requires considering future states of the environment (i.e., planning) and properly updating beliefs about the state of the environment after observing outcomes associated with choices. Optimal belief-updating is reflective in that beliefs can change without directly observing environmental change. For example, after 10 s elapse, one might correctly believe that a traffic light last observed to be red is now more likely to be green. To understand human decision-making when rewards associated with choice options change over time, we develop a variant of the classic “bandit” task that is both rich enough to encompass relevant phenomena and sufficiently tractable to allow for ideal actor analysis of sequential choice behavior. We evaluate whether people update beliefs about the state of environment in a reflexive (i.e., only in response to observed changes in reward structure) or reflective manner. In contrast to purely “random” accounts of exploratory behavior, model-based analyses of the subjects’ choices and latencies indicate that people are reflective belief updaters. However, unlike the Ideal Actor model, our analyses indicate that people’s choice behavior does not reflect consideration of future environmental states. Thus, although people update beliefs in a reflective manner consistent with the Ideal Actor, they do not engage in optimal long-term planning, but instead myopically choose the option on every trial that is believed to have the highest immediate payoff. PMID:22319503

Full-wave Moment Tensor and Tomographic Inversions Based on 3D Strain Green Tensor

DTIC Science & Technology

2010-01-31

propagation in three-dimensional (3D) earth, linearizes the inverse problem by iteratively updating the earth model , and provides an accurate way to...self-consistent FD-SGT databases constructed from finite-difference simulations of wave propagation in full-wave tomographic models can be used to...determine the moment tensors within minutes after a seismic event, making it possible for real time monitoring using 3D models . 15. SUBJECT TERMS

Using discharge data to reduce structural deficits in a hydrological model with a Bayesian inference approach and the implications for the prediction of critical source areas

NASA Astrophysics Data System (ADS)

Frey, M. P.; Stamm, C.; Schneider, M. K.; Reichert, P.

2011-12-01

A distributed hydrological model was used to simulate the distribution of fast runoff formation as a proxy for critical source areas for herbicide pollution in a small agricultural catchment in Switzerland. We tested to what degree predictions based on prior knowledge without local measurements could be improved upon relying on observed discharge. This learning process consisted of five steps: For the prior prediction (step 1), knowledge of the model parameters was coarse and predictions were fairly uncertain. In the second step, discharge data were used to update the prior parameter distribution. Effects of uncertainty in input data and model structure were accounted for by an autoregressive error model. This step decreased the width of the marginal distributions of parameters describing the lower boundary (percolation rates) but hardly affected soil hydraulic parameters. Residual analysis (step 3) revealed model structure deficits. We modified the model, and in the subsequent Bayesian updating (step 4) the widths of the posterior marginal distributions were reduced for most parameters compared to those of the prior. This incremental procedure led to a strong reduction in the uncertainty of the spatial prediction. Thus, despite only using spatially integrated data (discharge), the spatially distributed effect of the improved model structure can be expected to improve the spatially distributed predictions also. The fifth step consisted of a test with independent spatial data on herbicide losses and revealed ambiguous results. The comparison depended critically on the ratio of event to preevent water that was discharged. This ratio cannot be estimated from hydrological data only. The results demonstrate that the value of local data is strongly dependent on a correct model structure. An iterative procedure of Bayesian updating, model testing, and model modification is suggested.

Seismic source characterization for the 2014 update of the U.S. National Seismic Hazard Model

USGS Publications Warehouse

Moschetti, Morgan P.; Powers, Peter; Petersen, Mark D.; Boyd, Oliver; Chen, Rui; Field, Edward H.; Frankel, Arthur; Haller, Kathleen; Harmsen, Stephen; Mueller, Charles S.; Wheeler, Russell; Zeng, Yuehua

2015-01-01

We present the updated seismic source characterization (SSC) for the 2014 update of the National Seismic Hazard Model (NSHM) for the conterminous United States. Construction of the seismic source models employs the methodology that was developed for the 1996 NSHM but includes new and updated data, data types, source models, and source parameters that reflect the current state of knowledge of earthquake occurrence and state of practice for seismic hazard analyses. We review the SSC parameterization and describe the methods used to estimate earthquake rates, magnitudes, locations, and geometries for all seismic source models, with an emphasis on new source model components. We highlight the effects that two new model components—incorporation of slip rates from combined geodetic-geologic inversions and the incorporation of adaptively smoothed seismicity models—have on probabilistic ground motions, because these sources span multiple regions of the conterminous United States and provide important additional epistemic uncertainty for the 2014 NSHM.

On non-negative matrix factorization algorithms for signal-dependent noise with application to electromyography data

PubMed Central

Devarajan, Karthik; Cheung, Vincent C.K.

2017-01-01

Non-negative matrix factorization (NMF) by the multiplicative updates algorithm is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into two nonnegative matrices, W and H where V ~ WH. It has been successfully applied in the analysis and interpretation of large-scale data arising in neuroscience, computational biology and natural language processing, among other areas. A distinctive feature of NMF is its nonnegativity constraints that allow only additive linear combinations of the data, thus enabling it to learn parts that have distinct physical representations in reality. In this paper, we describe an information-theoretic approach to NMF for signal-dependent noise based on the generalized inverse Gaussian model. Specifically, we propose three novel algorithms in this setting, each based on multiplicative updates and prove monotonicity of updates using the EM algorithm. In addition, we develop algorithm-specific measures to evaluate their goodness-of-fit on data. Our methods are demonstrated using experimental data from electromyography studies as well as simulated data in the extraction of muscle synergies, and compared with existing algorithms for signal-dependent noise. PMID:24684448

Robust non-rigid registration algorithm based on local affine registration

NASA Astrophysics Data System (ADS)

Wu, Liyang; Xiong, Lei; Du, Shaoyi; Bi, Duyan; Fang, Ting; Liu, Kun; Wu, Dongpeng

2018-04-01

Aiming at the problem that the traditional point set non-rigid registration algorithm has low precision and slow convergence speed for complex local deformation data, this paper proposes a robust non-rigid registration algorithm based on local affine registration. The algorithm uses a hierarchical iterative method to complete the point set non-rigid registration from coarse to fine. In each iteration, the sub data point sets and sub model point sets are divided and the shape control points of each sub point set are updated. Then we use the control point guided affine ICP algorithm to solve the local affine transformation between the corresponding sub point sets. Next, the local affine transformation obtained by the previous step is used to update the sub data point sets and their shape control point sets. When the algorithm reaches the maximum iteration layer K, the loop ends and outputs the updated sub data point sets. Experimental results demonstrate that the accuracy and convergence of our algorithm are greatly improved compared with the traditional point set non-rigid registration algorithms.

The Development of Time-Based Prospective Memory in Childhood: The Role of Working Memory Updating

ERIC Educational Resources Information Center

Voigt, Babett; Mahy, Caitlin E. V.; Ellis, Judi; Schnitzspahn, Katharina; Krause, Ivonne; Altgassen, Mareike; Kliegel, Matthias

2014-01-01

This large-scale study examined the development of time-based prospective memory (PM) across childhood and the roles that working memory updating and time monitoring play in driving age effects in PM performance. One hundred and ninety-seven children aged 5 to 14 years completed a time-based PM task where working memory updating load was…

Information dissemination model for social media with constant updates

NASA Astrophysics Data System (ADS)

Zhu, Hui; Wu, Heng; Cao, Jin; Fu, Gang; Li, Hui

2018-07-01

With the development of social media tools and the pervasiveness of smart terminals, social media has become a significant source of information for many individuals. However, false information can spread rapidly, which may result in negative social impacts and serious economic losses. Thus, reducing the unfavorable effects of false information has become an urgent challenge. In this paper, a new competitive model called DMCU is proposed to describe the dissemination of information with constant updates in social media. In the model, we focus on the competitive relationship between the original false information and updated information, and then propose the priority of related information. To more effectively evaluate the effectiveness of the proposed model, data sets containing actual social media activity are utilized in experiments. Simulation results demonstrate that the DMCU model can precisely describe the process of information dissemination with constant updates, and that it can be used to forecast information dissemination trends on social media.

Seismic hazard in the eastern United States

USGS Publications Warehouse

Mueller, Charles; Boyd, Oliver; Petersen, Mark D.; Moschetti, Morgan P.; Rezaeian, Sanaz; Shumway, Allison

2015-01-01

The U.S. Geological Survey seismic hazard maps for the central and eastern United States were updated in 2014. We analyze results and changes for the eastern part of the region. Ratio maps are presented, along with tables of ground motions and deaggregations for selected cities. The Charleston fault model was revised, and a new fault source for Charlevoix was added. Background seismicity sources utilized an updated catalog, revised completeness and recurrence models, and a new adaptive smoothing procedure. Maximum-magnitude models and ground motion models were also updated. Broad, regional hazard reductions of 5%–20% are mostly attributed to new ground motion models with stronger near-source attenuation. The revised Charleston fault geometry redistributes local hazard, and the new Charlevoix source increases hazard in northern New England. Strong increases in mid- to high-frequency hazard at some locations—for example, southern New Hampshire, central Virginia, and eastern Tennessee—are attributed to updated catalogs and/or smoothing.

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

DOE PAGES

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.; ...

2017-01-01

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain–Fritsch +more » Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.« less

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain–Fritsch +more » Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.« less

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

NASA Astrophysics Data System (ADS)

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.; Berg, Larry K.; Fast, Jerome D.; Easter, Richard C.; Shrivastava, Manish; Thomas, Jennie L.

2017-10-01

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain-Fritsch + Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.

On-Line Mu Method for Robust Flutter Prediction in Expanding a Safe Flight Envelope for an Aircraft Model Under Flight Test

NASA Technical Reports Server (NTRS)

Lind, Richard C. (Inventor); Brenner, Martin J.

2001-01-01

A structured singular value (mu) analysis method of computing flutter margins has robust stability of a linear aeroelastic model with uncertainty operators (Delta). Flight data is used to update the uncertainty operators to accurately account for errors in the computed model and the observed range of aircraft dynamics of the aircraft under test caused by time-varying aircraft parameters, nonlinearities, and flight anomalies, such as test nonrepeatability. This mu-based approach computes predict flutter margins that are worst case with respect to the modeling uncertainty for use in determining when the aircraft is approaching a flutter condition and defining an expanded safe flight envelope for the aircraft that is accepted with more confidence than traditional methods that do not update the analysis algorithm with flight data by introducing mu as a flutter margin parameter that presents several advantages over tracking damping trends as a measure of a tendency to instability from available flight data.

Disruption of the Right Temporoparietal Junction Impairs Probabilistic Belief Updating.

PubMed

Mengotti, Paola; Dombert, Pascasie L; Fink, Gereon R; Vossel, Simone

2017-05-31

Generating and updating probabilistic models of the environment is a fundamental modus operandi of the human brain. Although crucial for various cognitive functions, the neural mechanisms of these inference processes remain to be elucidated. Here, we show the causal involvement of the right temporoparietal junction (rTPJ) in updating probabilistic beliefs and we provide new insights into the chronometry of the process by combining online transcranial magnetic stimulation (TMS) with computational modeling of behavioral responses. Female and male participants performed a modified location-cueing paradigm, where false information about the percentage of cue validity (%CV) was provided in half of the experimental blocks to prompt updating of prior expectations. Online double-pulse TMS over rTPJ 300 ms (but not 50 ms) after target appearance selectively decreased participants' updating of false prior beliefs concerning %CV, reflected in a decreased learning rate of a Rescorla-Wagner model. Online TMS over rTPJ also impacted on participants' explicit beliefs, causing them to overestimate %CV. These results confirm the involvement of rTPJ in updating of probabilistic beliefs, thereby advancing our understanding of this area's function during cognitive processing. SIGNIFICANCE STATEMENT Contemporary views propose that the brain maintains probabilistic models of the world to minimize surprise about sensory inputs. Here, we provide evidence that the right temporoparietal junction (rTPJ) is causally involved in this process. Because neuroimaging has suggested that rTPJ is implicated in divergent cognitive domains, the demonstration of an involvement in updating internal models provides a novel unifying explanation for these findings. We used computational modeling to characterize how participants change their beliefs after new observations. By interfering with rTPJ activity through online transcranial magnetic stimulation, we showed that participants were less able to update prior beliefs with TMS delivered at 300 ms after target onset. Copyright © 2017 the authors 0270-6474/17/375419-10$15.00/0.

FORCARB2: An updated version of the U.S. Forest Carbon Budget Model

Treesearch

Linda S. Heath; Michael C. Nichols; James E. Smith; John R. Mills

2010-01-01

FORCARB2, an updated version of the U.S. FORest CARBon Budget Model (FORCARB), produces estimates of carbon stocks and stock changes for forest ecosystems and forest products at 5-year intervals. FORCARB2 includes a new methodology for carbon in harvested wood products, updated initial inventory data, a revised algorithm for dead wood, and now includes public forest...

Consideration of Real World Factors Influencing Greenhouse Gas Emissions in ALPHA

EPA Science Inventory

Discuss a variety of factors that influence the simulated fuel economy and GHG emissions that are often overlooked and updates made to ALPHA based on actual benchmarking data observed across a range of vehicles and transmissions. ALPHA model calibration is also examined, focusin...

Face Adaptation and Attractiveness Aftereffects in 8-Year-Olds and Adults

ERIC Educational Resources Information Center

Anzures, Gizelle; Mondloch, Catherine J.; Lackner, Christine

2009-01-01

A novel method was used to investigate developmental changes in face processing: attractiveness aftereffects. Consistent with the norm-based coding model, viewing consistently distorted faces shifts adults' attractiveness preferences toward the adapting stimuli. Thus, adults' attractiveness judgments are influenced by a continuously updated face…

Aeroservoelastic Uncertainty Model Identification from Flight Data

NASA Technical Reports Server (NTRS)

Brenner, Martin J.

2001-01-01

Uncertainty modeling is a critical element in the estimation of robust stability margins for stability boundary prediction and robust flight control system development. There has been a serious deficiency to date in aeroservoelastic data analysis with attention to uncertainty modeling. Uncertainty can be estimated from flight data using both parametric and nonparametric identification techniques. The model validation problem addressed in this paper is to identify aeroservoelastic models with associated uncertainty structures from a limited amount of controlled excitation inputs over an extensive flight envelope. The challenge to this problem is to update analytical models from flight data estimates while also deriving non-conservative uncertainty descriptions consistent with the flight data. Multisine control surface command inputs and control system feedbacks are used as signals in a wavelet-based modal parameter estimation procedure for model updates. Transfer function estimates are incorporated in a robust minimax estimation scheme to get input-output parameters and error bounds consistent with the data and model structure. Uncertainty estimates derived from the data in this manner provide an appropriate and relevant representation for model development and robust stability analysis. This model-plus-uncertainty identification procedure is applied to aeroservoelastic flight data from the NASA Dryden Flight Research Center F-18 Systems Research Aircraft.

Sequential updating of a new dynamic pharmacokinetic model for caffeine in premature neonates.

PubMed

Micallef, Sandrine; Amzal, Billy; Bach, Véronique; Chardon, Karen; Tourneux, Pierre; Bois, Frédéric Y

2007-01-01

Caffeine treatment is widely used in nursing care to reduce the risk of apnoea in premature neonates. To check the therapeutic efficacy of the treatment against apnoea, caffeine concentration in blood is an important indicator. The present study was aimed at building a pharmacokinetic model as a basis for a medical decision support tool. In the proposed model, time dependence of physiological parameters is introduced to describe rapid growth of neonates. To take into account the large variability in the population, the pharmacokinetic model is embedded in a population structure. The whole model is inferred within a Bayesian framework. To update caffeine concentration predictions as data of an incoming patient are collected, we propose a fast method that can be used in a medical context. This involves the sequential updating of model parameters (at individual and population levels) via a stochastic particle algorithm. Our model provides better predictions than the ones obtained with models previously published. We show, through an example, that sequential updating improves predictions of caffeine concentration in blood (reduce bias and length of credibility intervals). The update of the pharmacokinetic model using body mass and caffeine concentration data is studied. It shows how informative caffeine concentration data are in contrast to body mass data. This study provides the methodological basis to predict caffeine concentration in blood, after a given treatment if data are collected on the treated neonate.

UPDATE ON EPA'S URBAN WATERSHED MANAGEMENT BRANCH MODELING ACTIVITIES

EPA Science Inventory

This paper provides the Stormwater Management Model (SWMM) user community with a description of the Environmental Protection Agency (EPA's) Office of Research and Development (ORD) approach to urban watershed modeling research and provides an update on current ORD SWMM-related pr...

WHEN ONSET MEETS DESISTANCE: COGNITIVE TRANSFORMATION AND ADOLESCENT MARIJUANA EXPERIMENTATION.

PubMed

Kreager, Derek A; Ragan, Daniel T; Nguyen, Holly; Staff, Jeremy

2016-06-01

Desistance scholars primarily focus on changing social roles, cognitive transformations, and shifting identities to understand the cessation of serious crime and illicit drug use in adulthood. In the current study, we move the spotlight away from adulthood and toward adolescence, the developmental stage when the prevalence of offending and substance use peak and desistance from most of these behaviors begins. Our primary hypothesis is that changes in perceived psychic rewards surrounding initial forays into marijuana use strongly predict adolescents' decisions to cease or persist that behavior. In addition, based on social learning expectations, we hypothesize that peer perceptions and behaviors provide mechanisms for perceptual change. We test these hypotheses using longitudinal data of marijuana use, perceptions, and peer networks from the PROmoting School-community-university Partnerships to Enhance Resilience (PROSPER) study. We estimate hazard models of marijuana initiation and within-person models of perceptual updating for youth from grades 6 to 12 ( n =6,154). We find that changes in marijuana's perceived psychic rewards surrounding initiation differentiated experimenters from persisters. Experimenters had significantly lower updated perceptions of marijuana as a fun behavior compared to persisters and these perceptions dropped after the initiation wave. In contrast, persisters updated their perceptions in upward directions and maintained more positive perceptions over time. Inconsistent with social learning expectations, initiators' updated perceptions of marijuana as a fun activity were not explained by peer-reported behaviors or attitudes.

Update schemes of multi-velocity floor field cellular automaton for pedestrian dynamics

NASA Astrophysics Data System (ADS)

Luo, Lin; Fu, Zhijian; Cheng, Han; Yang, Lizhong

2018-02-01

Modeling pedestrian movement is an interesting problem both in statistical physics and in computational physics. Update schemes of cellular automaton (CA) models for pedestrian dynamics govern the schedule of pedestrian movement. Usually, different update schemes make the models behave in different ways, which should be carefully recalibrated. Thus, in this paper, we investigated the influence of four different update schemes, namely parallel/synchronous scheme, random scheme, order-sequential scheme and shuffled scheme, on pedestrian dynamics. The multi-velocity floor field cellular automaton (FFCA) considering the changes of pedestrians' moving properties along walking paths and heterogeneity of pedestrians' walking abilities was used. As for parallel scheme only, the collisions detection and resolution should be considered, resulting in a great difference from any other update schemes. For pedestrian evacuation, the evacuation time is enlarged, and the difference in pedestrians' walking abilities is better reflected, under parallel scheme. In face of a bottleneck, for example a exit, using a parallel scheme leads to a longer congestion period and a more dispersive density distribution. The exit flow and the space-time distribution of density and velocity have significant discrepancies under four different update schemes when we simulate pedestrian flow with high desired velocity. Update schemes may have no influence on pedestrians in simulation to create tendency to follow others, but sequential and shuffled update scheme may enhance the effect of pedestrians' familiarity with environments.

Bayesian nonlinear structural FE model and seismic input identification for damage assessment of civil structures

NASA Astrophysics Data System (ADS)

Astroza, Rodrigo; Ebrahimian, Hamed; Li, Yong; Conte, Joel P.

2017-09-01

A methodology is proposed to update mechanics-based nonlinear finite element (FE) models of civil structures subjected to unknown input excitation. The approach allows to jointly estimate unknown time-invariant model parameters of a nonlinear FE model of the structure and the unknown time histories of input excitations using spatially-sparse output response measurements recorded during an earthquake event. The unscented Kalman filter, which circumvents the computation of FE response sensitivities with respect to the unknown model parameters and unknown input excitations by using a deterministic sampling approach, is employed as the estimation tool. The use of measurement data obtained from arrays of heterogeneous sensors, including accelerometers, displacement sensors, and strain gauges is investigated. Based on the estimated FE model parameters and input excitations, the updated nonlinear FE model can be interrogated to detect, localize, classify, and assess damage in the structure. Numerically simulated response data of a three-dimensional 4-story 2-by-1 bay steel frame structure with six unknown model parameters subjected to unknown bi-directional horizontal seismic excitation, and a three-dimensional 5-story 2-by-1 bay reinforced concrete frame structure with nine unknown model parameters subjected to unknown bi-directional horizontal seismic excitation are used to illustrate and validate the proposed methodology. The results of the validation studies show the excellent performance and robustness of the proposed algorithm to jointly estimate unknown FE model parameters and unknown input excitations.

Updating the U.S. Life Cycle GHG Petroleum Baseline to 2014 with Projections to 2040 Using Open-Source Engineering-Based Models.

PubMed

Cooney, Gregory; Jamieson, Matthew; Marriott, Joe; Bergerson, Joule; Brandt, Adam; Skone, Timothy J

2017-01-17

The National Energy Technology Laboratory produced a well-to-wheels (WTW) life cycle greenhouse gas analysis of petroleum-based fuels consumed in the U.S. in 2005, known as the NETL 2005 Petroleum Baseline. This study uses a set of engineering-based, open-source models combined with publicly available data to calculate baseline results for 2014. An increase between the 2005 baseline and the 2014 results presented here (e.g., 92.4 vs 96.2 g CO 2 e/MJ gasoline, + 4.1%) are due to changes both in modeling platform and in the U.S. petroleum sector. An updated result for 2005 was calculated to minimize the effect of the change in modeling platform, and emissions for gasoline in 2014 were about 2% lower than in 2005 (98.1 vs 96.2 g CO 2 e/MJ gasoline). The same methods were utilized to forecast emissions from fuels out to 2040, indicating maximum changes from the 2014 gasoline result between +2.1% and -1.4%. The changing baseline values lead to potential compliance challenges with frameworks such as the Energy Independence and Security Act (EISA) Section 526, which states that Federal agencies should not purchase alternative fuels unless their life cycle GHG emissions are less than those of conventionally produced, petroleum-derived fuels.

Selective updating of working memory content modulates meso-cortico-striatal activity.

PubMed

Murty, Vishnu P; Sambataro, Fabio; Radulescu, Eugenia; Altamura, Mario; Iudicello, Jennifer; Zoltick, Bradley; Weinberger, Daniel R; Goldberg, Terry E; Mattay, Venkata S

2011-08-01

Accumulating evidence from non-human primates and computational modeling suggests that dopaminergic signals arising from the midbrain (substantia nigra/ventral tegmental area) mediate striatal gating of the prefrontal cortex during the selective updating of working memory. Using event-related functional magnetic resonance imaging, we explored the neural mechanisms underlying the selective updating of information stored in working memory. Participants were scanned during a novel working memory task that parses the neurophysiology underlying working memory maintenance, overwriting, and selective updating. Analyses revealed a functionally coupled network consisting of a midbrain region encompassing the substantia nigra/ventral tegmental area, caudate, and dorsolateral prefrontal cortex that was selectively engaged during working memory updating compared to the overwriting and maintenance of working memory content. Further analysis revealed differential midbrain-dorsolateral prefrontal interactions during selective updating between low-performing and high-performing individuals. These findings highlight the role of this meso-cortico-striatal circuitry during the selective updating of working memory in humans, which complements previous research in behavioral neuroscience and computational modeling. Published by Elsevier Inc.

TSARINA: A Computer Model for Assessing Conventional and Chemical Attacks on Airbases

DTIC Science & Technology

1990-09-01

IV, and has been updated to FORTRAN 77; it has been adapted to various computer systems, as was the widely used AIDA model and the previous versions of...conventional and chemical attacks on sortie generation. In the first version of TSARINA [1 2], several key additions were made to the AIDA model so that (1...various on-base resources, in addition to the estimates of hits and facility damage that are generated by the original AIDA model . The second version

Propagation of Bayesian Belief for Near-Real Time Statistical Assessment of Geosynchronous Satellite Status Based on Non-Resolved Photometry Data

DTIC Science & Technology

2014-09-01

of the BRDF for the Body and Panel. In order to provide a continuously updated baseline, the Photometry Model application is performed using a...brightness to its predicted brightness. The brightness predictions can be obtained using any analytical model chosen by the user. The inference for a...the analytical model as possible; and to mitigate the effect of bias that could be introduced by the choice of analytical model . It considers that a

Using the PhysX engine for physics-based virtual surgery with force feedback.

PubMed

Maciel, Anderson; Halic, Tansel; Lu, Zhonghua; Nedel, Luciana P; De, Suvranu

2009-09-01

The development of modern surgical simulators is highly challenging, as they must support complex simulation environments. The demand for higher realism in such simulators has driven researchers to adopt physics-based models, which are computationally very demanding. This poses a major problem, since real-time interactions must permit graphical updates of 30 Hz and a much higher rate of 1 kHz for force feedback (haptics). Recently several physics engines have been developed which offer multi-physics simulation capabilities, including rigid and deformable bodies, cloth and fluids. While such physics engines provide unique opportunities for the development of surgical simulators, their higher latencies, compared to what is necessary for real-time graphics and haptics, offer significant barriers to their use in interactive simulation environments. In this work, we propose solutions to this problem and demonstrate how a multimodal surgical simulation environment may be developed based on NVIDIA's PhysX physics library. Hence, models that are undergoing relatively low-frequency updates in PhysX can exist in an environment that demands much higher frequency updates for haptics. We use a collision handling layer to interface between the physical response provided by PhysX and the haptic rendering device to provide both real-time tissue response and force feedback. Our simulator integrates a bimanual haptic interface for force feedback and per-pixel shaders for graphics realism in real time. To demonstrate the effectiveness of our approach, we present the simulation of the laparoscopic adjustable gastric banding (LAGB) procedure as a case study. To develop complex and realistic surgical trainers with realistic organ geometries and tissue properties demands stable physics-based deformation methods, which are not always compatible with the interaction level required for such trainers. We have shown that combining different modelling strategies for behaviour, collision and graphics is possible and desirable. Such multimodal environments enable suitable rates to simulate the major steps of the LAGB procedure.

Identification and calibration of the structural model of historical masonry building damaged during the 2016 Italian earthquakes: The case study of Palazzo del Podestà in Montelupone

NASA Astrophysics Data System (ADS)

Catinari, Federico; Pierdicca, Alessio; Clementi, Francesco; Lenci, Stefano

2017-11-01

The results of an ambient-vibration based investigation conducted on the "Palazzo del Podesta" in Montelupone (Italy) is presented. The case study was damaged during the 20I6 Italian earthquakes that stroke the central part of the Italy. The assessment procedure includes full-scale ambient vibration testing, modal identification from ambient vibration responses, finite element modeling and dynamic-based identification of the uncertain structural parameters of the model. A very good match between theoretical and experimental modal parameters was reached and the model updating has been performed identifying some structural parameters.

Implementation of NGA-West2 ground motion models in the 2014 U.S. National Seismic Hazard Maps

USGS Publications Warehouse

Rezaeian, Sanaz; Petersen, Mark D.; Moschetti, Morgan P.; Powers, Peter; Harmsen, Stephen C.; Frankel, Arthur D.

2014-01-01

The U.S. National Seismic Hazard Maps (NSHMs) have been an important component of seismic design regulations in the United States for the past several decades. These maps present earthquake ground shaking intensities at specified probabilities of being exceeded over a 50-year time period. The previous version of the NSHMs was developed in 2008; during 2012 and 2013, scientists at the U.S. Geological Survey have been updating the maps based on their assessment of the “best available science,” resulting in the 2014 NSHMs. The update includes modifications to the seismic source models and the ground motion models (GMMs) for sites across the conterminous United States. This paper focuses on updates in the Western United States (WUS) due to the use of new GMMs for shallow crustal earthquakes in active tectonic regions developed by the Next Generation Attenuation (NGA-West2) project. Individual GMMs, their weighted combination, and their impact on the hazard maps relative to 2008 are discussed. In general, the combined effects of lower medians and increased standard deviations in the new GMMs have caused only small changes, within 5–20%, in the probabilistic ground motions for most sites across the WUS compared to the 2008 NSHMs.

Efficient Ensemble State-Parameters Estimation Techniques in Ocean Ecosystem Models: Application to the North Atlantic

NASA Astrophysics Data System (ADS)

El Gharamti, M.; Bethke, I.; Tjiputra, J.; Bertino, L.

2016-02-01

Given the recent strong international focus on developing new data assimilation systems for biological models, we present in this comparative study the application of newly developed state-parameters estimation tools to an ocean ecosystem model. It is quite known that the available physical models are still too simple compared to the complexity of the ocean biology. Furthermore, various biological parameters remain poorly unknown and hence wrong specifications of such parameters can lead to large model errors. Standard joint state-parameters augmentation technique using the ensemble Kalman filter (Stochastic EnKF) has been extensively tested in many geophysical applications. Some of these assimilation studies reported that jointly updating the state and the parameters might introduce significant inconsistency especially for strongly nonlinear models. This is usually the case for ecosystem models particularly during the period of the spring bloom. A better handling of the estimation problem is often carried out by separating the update of the state and the parameters using the so-called Dual EnKF. The dual filter is computationally more expensive than the Joint EnKF but is expected to perform more accurately. Using a similar separation strategy, we propose a new EnKF estimation algorithm in which we apply a one-step-ahead smoothing to the state. The new state-parameters estimation scheme is derived in a consistent Bayesian filtering framework and results in separate update steps for the state and the parameters. Unlike the classical filtering path, the new scheme starts with an update step and later a model propagation step is performed. We test the performance of the new smoothing-based schemes against the standard EnKF in a one-dimensional configuration of the Norwegian Earth System Model (NorESM) in the North Atlantic. We use nutrients profile (up to 2000 m deep) data and surface partial CO2 measurements from Mike weather station (66o N, 2o E) to estimate different biological parameters of phytoplanktons and zooplanktons. We analyze the performance of the filters in terms of complexity and accuracy of the state and parameters estimates.

Key science issues in the central and eastern United States for the next version of the USGS National Seismic Hazard Maps

USGS Publications Warehouse

Peterson, M.D.; Mueller, C.S.

2011-01-01

The USGS National Seismic Hazard Maps are updated about every six years by incorporating newly vetted science on earthquakes and ground motions. The 2008 hazard maps for the central and eastern United States region (CEUS) were updated by using revised New Madrid and Charleston source models, an updated seismicity catalog and an estimate of magnitude uncertainties, a distribution of maximum magnitudes, and several new ground-motion prediction equations. The new models resulted in significant ground-motion changes at 5 Hz and 1 Hz spectral acceleration with 5% damping compared to the 2002 version of the hazard maps. The 2008 maps have now been incorporated into the 2009 NEHRP Recommended Provisions, the 2010 ASCE-7 Standard, and the 2012 International Building Code. The USGS is now planning the next update of the seismic hazard maps, which will be provided to the code committees in December 2013. Science issues that will be considered for introduction into the CEUS maps include: 1) updated recurrence models for New Madrid sources, including new geodetic models and magnitude estimates; 2) new earthquake sources and techniques considered in the 2010 model developed by the nuclear industry; 3) new NGA-East ground-motion models (currently under development); and 4) updated earthquake catalogs. We will hold a regional workshop in late 2011 or early 2012 to discuss these and other issues that will affect the seismic hazard evaluation in the CEUS.

An Update of the Bodeker Scientific Vertically Resolved, Global, Gap-Free Ozone Database

NASA Astrophysics Data System (ADS)

Kremser, S.; Bodeker, G. E.; Lewis, J.; Hassler, B.

2016-12-01

High vertical resolution ozone measurements from multiple satellite-based instruments have been merged with measurements from the global ozonesonde network to calculate monthly mean ozone values in 5º latitude zones. Ozone number densities and ozone mixing ratios are provided on 70 altitude levels (1 to 70 km) and on 70 pressure levels spaced approximately 1 km apart (878.4 hPa to 0.046 hPa). These data are sparse and do not cover the entire globe or altitude range. To provide a gap-free database, a least squares regression model is fitted to these data and then evaluated globally. By applying a single fit at each level, and using the approach of allowing the regression fits to change only slightly from one level to the next, the regression is less sensitive to measurement anomalies at individual stations or to individual satellite-based instruments. Particular attention is paid to ensuring that the low ozone abundances in the polar regions are captured. This presentation reports on updates to an earlier version of the vertically resolved ozone database, including the incorporation of new ozone measurements and new techniques for combining the data. Compared to previous versions of the database, particular attention is paid to avoiding spatial and temporal sampling biases and tracing uncertainties through to the final product. This updated database, developed within the New Zealand Deep South National Science Challenge, is suitable for assessing ozone fields from chemistry-climate model simulations or for providing the ozone boundary conditions for global climate model simulations that do not treat stratospheric chemistry interactively.

Recognition of genetically modified product based on affinity propagation clustering and terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Jianjun; Kan, Jianquan

2018-04-01

In this paper, based on the terahertz spectrum, a new identification method of genetically modified material by support vector machine (SVM) based on affinity propagation clustering is proposed. This algorithm mainly uses affinity propagation clustering algorithm to make cluster analysis and labeling on unlabeled training samples, and in the iterative process, the existing SVM training data are continuously updated, when establishing the identification model, it does not need to manually label the training samples, thus, the error caused by the human labeled samples is reduced, and the identification accuracy of the model is greatly improved.

WebbPSF: Updated PSF Models Based on JWST Ground Testing Results

NASA Astrophysics Data System (ADS)

Osborne, Shannon; Perrin, Marshall D.; Melendez Hernandez, Marcio

2018-06-01

WebbPSF is a widely-used package that allows astronomers to create simulated point spread functions (PSFs) for the James Webb Space Telescope (JWST). WebbPSF provides the user with the flexibility to produce PSFs for direct imaging and coronographic modes, for a range of filters and masks, and across all the JWST instruments. These PSFs can then be analyzed with built-in evaluation tools or can be output to be used with users’ own tools. In the most recent round of updates, the accuracy of the PSFs have been improved with updated analyses of the instrument test data from NASA Goddard and with the new data from the testing of the combined Optical Telescope Element and Integrated Science Instrument Module (OTIS) at NASA Johnson. A post-processing function applying detector effects and pupil distortions to input PSFs has also been added to the WebbPSF package.

Coupling a regional warning system to a semantic engine on online news for enhancing landslide prediction

NASA Astrophysics Data System (ADS)

Battistini, Alessandro; Rosi, Ascanio; Segoni, Samuele; Catani, Filippo; Casagli, Nicola

2017-04-01

Landslide inventories are basic data for large scale landslide modelling, e.g. they are needed to calibrate and validate rainfall thresholds, physically based models and early warning systems. The setting up of landslide inventories with traditional methods (e.g. remote sensing, field surveys and manual retrieval of data from technical reports and local newspapers) is time consuming. The objective of this work is to automatically set up a landslide inventory using a state-of-the art semantic engine based on data mining on online news (Battistini et al., 2013) and to evaluate if the automatically generated inventory can be used to validate a regional scale landslide warning system based on rainfall-thresholds. The semantic engine scanned internet news in real time in a 50 months test period. At the end of the process, an inventory of approximately 900 landslides was set up for the Tuscany region (23,000 km2, Italy). The inventory was compared with the outputs of the regional landslide early warning system based on rainfall thresholds, and a good correspondence was found: e.g. 84% of the events reported in the news is correctly identified by the model. In addition, the cases of not correspondence were forwarded to the rainfall threshold developers, which used these inputs to update some of the thresholds. On the basis of the results obtained, we conclude that automatic validation of landslide models using geolocalized landslide events feedback is possible. The source of data for validation can be obtained directly from the internet channel using an appropriate semantic engine. We also automated the validation procedure, which is based on a comparison between forecasts and reported events. We verified that our approach can be automatically used for a near real time validation of the warning system and for a semi-automatic update of the rainfall thresholds, which could lead to an improvement of the forecasting effectiveness of the warning system. In the near future, the proposed procedure could operate in continuous time and could allow for a periodic update of landslide hazard models and landslide early warning systems with minimum human intervention. References: Battistini, A., Segoni, S., Manzo, G., Catani, F., Casagli, N. (2013). Web data mining for automatic inventory of geohazards at national scale. Applied Geography, 43, 147-158.

SysML model of exoplanet archive functionality and activities

NASA Astrophysics Data System (ADS)

Ramirez, Solange

2016-08-01

The NASA Exoplanet Archive is an online service that serves data and information on exoplanets and their host stars to help astronomical research related to search for and characterization of extra-solar planetary systems. In order to provide the most up to date data sets to the users, the exoplanet archive performs weekly updates that include additions into the database and updates to the services as needed. These weekly updates are complex due to interfaces within the archive. I will be presenting a SysML model that helps us perform these update activities in a weekly basis.

Structural Finite Element Model Updating Using Vibration Tests and Modal Analysis for NPL footbridge - SHM demonstrator

NASA Astrophysics Data System (ADS)

Barton, E.; Middleton, C.; Koo, K.; Crocker, L.; Brownjohn, J.

2011-07-01

This paper presents the results from collaboration between the National Physical Laboratory (NPL) and the University of Sheffield on an ongoing research project at NPL. A 50 year old reinforced concrete footbridge has been converted to a full scale structural health monitoring (SHM) demonstrator. The structure is monitored using a variety of techniques; however, interrelating results and converting data to knowledge are not possible without a reliable numerical model. During the first stage of the project, the work concentrated on static loading and an FE model of the undamaged bridge was created, and updated, under specified static loading and temperature conditions. This model was found to accurately represent the response under static loading and it was used to identify locations for sensor installation. The next stage involves the evaluation of repair/strengthening patches under both static and dynamic loading. Therefore, before deliberately introducing significant damage, the first set of dynamic tests was conducted and modal properties were estimated. The measured modal properties did not match the modal analysis from the statically updated FE model; it was clear that the existing model required updating. This paper introduces the results of the dynamic testing and model updating. It is shown that the structure exhibits large non-linear, amplitude dependant characteristics. This creates a difficult updating process, but we attempt to produce the best linear representation of the structure. A sensitivity analysis is performed to determine the most sensitive locations for planned damage/repair scenarios and is used to decide whether additional sensors will be necessary.

Summary of Expansions, Updates, and Results in GREET® 2016 Suite of Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

None, None

2016-10-01

This report documents the technical content of the expansions and updates in Argonne National Laboratory’s GREET® 2016 release and provides references and links to key documents related to these expansions and updates.

Electronic Education System Model-2

ERIC Educational Resources Information Center

Güllü, Fatih; Kuusik, Rein; Laanpere, Mart

2015-01-01

In this study we presented new EES Model-2 extended from EES model for more productive implementation in e-learning process design and modelling in higher education. The most updates were related to uppermost instructional layer. We updated learning processes object of the layer for adaptation of educational process for young and old people,…

Direct coal liquefaction baseline design and system analysis. Quarterly report, January--March 1991

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1991-04-01

The primary objective of the study is to develop a computer model for a base line direct coal liquefaction design based on two stage direct coupled catalytic reactors. This primary objective is to be accomplished by completing the following: a base line design based on previous DOE/PETC results from Wilsonville pilot plant and other engineering evaluations; a cost estimate and economic analysis; a computer model incorporating the above two steps over a wide range of capacities and selected process alternatives; a comprehensive training program for DOE/PETC Staff to understand and use the computer model; a thorough documentation of all underlyingmore » assumptions for baseline economics; and a user manual and training material which will facilitate updating of the model in the future.« less

Direct coal liquefaction baseline design and system analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1991-04-01

The primary objective of the study is to develop a computer model for a base line direct coal liquefaction design based on two stage direct coupled catalytic reactors. This primary objective is to be accomplished by completing the following: a base line design based on previous DOE/PETC results from Wilsonville pilot plant and other engineering evaluations; a cost estimate and economic analysis; a computer model incorporating the above two steps over a wide range of capacities and selected process alternatives; a comprehensive training program for DOE/PETC Staff to understand and use the computer model; a thorough documentation of all underlyingmore » assumptions for baseline economics; and a user manual and training material which will facilitate updating of the model in the future.« less

Capital update factor: a new era approaches.

PubMed

Grimaldi, P L

1993-02-01

The Health Care Financing Administration (HCFA) has constructed a preliminary model of a new capital update method which is consistent with the framework being developed to refine the update method for PPS operating costs. HCFA's eventual goal is to develop a single update framework for operating and capital costs. Initial results suggest that adopting the new capital update method would reduce capital payments substantially, which might intensify creditor's concerns about extending loans to hospitals.

Proposed reporting model update creates dialogue between FASB and not-for-profits.

PubMed

Mosrie, Norman C

2016-04-01

Seeing a need to refresh the current guidelines, the Financial Accounting Standards Board (FASB) proposed an update to the financial accounting and reporting model for not-for-profit entities. In a response to solicited feedback, the board is now revisiting its proposed update and has set forth a plan to finalize its new guidelines. The FASB continues to solicit and respond to feedback as the process progresses.

Security in the CernVM File System and the Frontier Distributed Database Caching System

NASA Astrophysics Data System (ADS)

Dykstra, D.; Blomer, J.

2014-06-01

Both the CernVM File System (CVMFS) and the Frontier Distributed Database Caching System (Frontier) distribute centrally updated data worldwide for LHC experiments using http proxy caches. Neither system provides privacy or access control on reading the data, but both control access to updates of the data and can guarantee the authenticity and integrity of the data transferred to clients over the internet. CVMFS has since its early days required digital signatures and secure hashes on all distributed data, and recently Frontier has added X.509-based authenticity and integrity checking. In this paper we detail and compare the security models of CVMFS and Frontier.

Updates to research on recommended minimum levels for pavement marking retroreflectivity to meet driver night visibility needs

DOT National Transportation Integrated Search

2007-10-01

This study was aimed at completing the research to develop and scrutinize minimum levels for pavement marking retroreflectivity to meet nighttime driving needs. A previous study carried out in the 1990s was based on the CARVE model developed at Ohio ...

Vibration analysis of resistance spot welding joint for dissimilar plate structure (mild steel 1010 and stainless steel 304)

NASA Astrophysics Data System (ADS)

Sani, M. S. M.; Nazri, N. A.; Alawi, D. A. J.

2017-09-01

Resistance spot welding (RSW) is a proficient joining method commonly used for sheet metal joining and become one of the oldest spot welding processes use in industry especially in the automotive. RSW involves the application of heat and pressure without neglecting time taken when joining two or more metal sheets at a localized area which is claimed as the most efficient welding process in metal fabrication. The purpose of this project is to perform model updating of RSW plate structure between mild steel 1010 and stainless steel 304. In order to do the updating, normal mode finite element analysis (FEA) and experimental modal analysis (EMA) have been carried out. Result shows that the discrepancies of natural frequency between FEA and EMA are below than 10 %. Sensitivity model updating is evaluated in order to make sure which parameters are influences in this structural dynamic modification. Young’s modulus and density both materials are indicate significant parameters to do model updating. As a conclusion, after perform model updating, total average error of dissimilar RSW plate is improved significantly.

NODA for EPA's Updated Ozone Transport Modeling

EPA Pesticide Factsheets

Find EPA's NODA for the Updated Ozone Transport Modeling Data for the 2008 Ozone National Ambient Air Quality Standard (NAAQS) along with the ExitExtension of Public Comment Period on CSAPR for the 2008 NAAQS.

Adaptive object tracking via both positive and negative models matching

NASA Astrophysics Data System (ADS)

Li, Shaomei; Gao, Chao; Wang, Yawen

2015-03-01

To improve tracking drift which often occurs in adaptive tracking, an algorithm based on the fusion of tracking and detection is proposed in this paper. Firstly, object tracking is posed as abinary classification problem and is modeled by partial least squares (PLS) analysis. Secondly, tracking object frame by frame via particle filtering. Thirdly, validating the tracking reliability based on both positive and negative models matching. Finally, relocating the object based on SIFT features matching and voting when drift occurs. Object appearance model is updated at the same time. The algorithm can not only sense tracking drift but also relocate the object whenever needed. Experimental results demonstrate that this algorithm outperforms state-of-the-art algorithms on many challenging sequences.

Update to the USDA-ARS fixed-wing spray nozzle models

USDA-ARS?s Scientific Manuscript database

The current USDA ARS Aerial Spray Nozzle Models were updated to reflect both new standardized measurement methods and systems, as well as, to increase operational spray pressure, aircraft airspeed and nozzle orientation angle limits. The new models were developed using both Central Composite Design...

Lazy Updating of hubs can enable more realistic models by speeding up stochastic simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ehlert, Kurt; Loewe, Laurence, E-mail: loewe@wisc.edu; Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, Wisconsin 53715

2014-11-28

To respect the nature of discrete parts in a system, stochastic simulation algorithms (SSAs) must update for each action (i) all part counts and (ii) each action's probability of occurring next and its timing. This makes it expensive to simulate biological networks with well-connected “hubs” such as ATP that affect many actions. Temperature and volume also affect many actions and may be changed significantly in small steps by the network itself during fever and cell growth, respectively. Such trends matter for evolutionary questions, as cell volume determines doubling times and fever may affect survival, both key traits for biological evolution.more » Yet simulations often ignore such trends and assume constant environments to avoid many costly probability updates. Such computational convenience precludes analyses of important aspects of evolution. Here we present “Lazy Updating,” an add-on for SSAs designed to reduce the cost of simulating hubs. When a hub changes, Lazy Updating postpones all probability updates for reactions depending on this hub, until a threshold is crossed. Speedup is substantial if most computing time is spent on such updates. We implemented Lazy Updating for the Sorting Direct Method and it is easily integrated into other SSAs such as Gillespie's Direct Method or the Next Reaction Method. Testing on several toy models and a cellular metabolism model showed >10× faster simulations for its use-cases—with a small loss of accuracy. Thus we see Lazy Updating as a valuable tool for some special but important simulation problems that are difficult to address efficiently otherwise.« less

42 CFR 412.328 - Determining and updating the hospital-specific rate.

Code of Federal Regulations, 2012 CFR

2012-10-01

...-year cost reporting period—(1) Last 12 month cost reporting period ending on or before December 31... intermediary updates the case-mix adjusted base period costs per discharge to FY 1992 based on the national... determined under paragraph (d) of this section by the following factors: (1) Update factor. After FY 1992...

42 CFR 412.328 - Determining and updating the hospital-specific rate.

Code of Federal Regulations, 2013 CFR

2013-10-01

...-year cost reporting period—(1) Last 12 month cost reporting period ending on or before December 31... intermediary updates the case-mix adjusted base period costs per discharge to FY 1992 based on the national... determined under paragraph (d) of this section by the following factors: (1) Update factor. After FY 1992...

42 CFR 412.328 - Determining and updating the hospital-specific rate.

Code of Federal Regulations, 2011 CFR

2011-10-01

...-year cost reporting period—(1) Last 12 month cost reporting period ending on or before December 31... intermediary updates the case-mix adjusted base period costs per discharge to FY 1992 based on the national... determined under paragraph (d) of this section by the following factors: (1) Update factor. After FY 1992...

42 CFR 412.328 - Determining and updating the hospital-specific rate.

Code of Federal Regulations, 2014 CFR

2014-10-01

...-year cost reporting period—(1) Last 12 month cost reporting period ending on or before December 31... intermediary updates the case-mix adjusted base period costs per discharge to FY 1992 based on the national... determined under paragraph (d) of this section by the following factors: (1) Update factor. After FY 1992...

Forests of Louisiana, 2014

Treesearch

S.N. Oswalt

2017-01-01

This resource update provides an overview of forest resources in Louisiana based on an inventory conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program at the Southern Research Station. Estimates are based on field data collected using the FIA annualized sample design and are updated yearly. The estimates presented in this update are for the...

Forests of Kentucky, 2014

Treesearch

Thomas Brandeis; Andy Hartsell; KaDonna Randolph; Sonja Oswalt; Consuelo Brandeis

2016-01-01

This resource update provides an overview of forest resources in Kentucky based on an inventory conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program at the Southern Research Station. Estimates are based on field data collected using the FIA annualized sample design and are updated yearly. The estimates presented in this update are...

Determination of replicate composite bone material properties using modal analysis.

PubMed

Leuridan, Steven; Goossens, Quentin; Pastrav, Leonard; Roosen, Jorg; Mulier, Michiel; Denis, Kathleen; Desmet, Wim; Sloten, Jos Vander

2017-02-01

Replicate composite bones are used extensively for in vitro testing of new orthopedic devices. Contrary to tests with cadaveric bone material, which inherently exhibits large variability, they offer a standardized alternative with limited variability. Accurate knowledge of the composite's material properties is important when interpreting in vitro test results and when using them in FE models of biomechanical constructs. The cortical bone analogue material properties of three different fourth-generation composite bone models were determined by updating FE bone models using experimental and numerical modal analyses results. The influence of the cortical bone analogue material model (isotropic or transversely isotropic) and the inter- and intra-specimen variability were assessed. Isotropic cortical bone analogue material models failed to represent the experimental behavior in a satisfactory way even after updating the elastic material constants. When transversely isotropic material models were used, the updating procedure resulted in a reduction of the longitudinal Young's modulus from 16.00GPa before updating to an average of 13.96 GPa after updating. The shear modulus was increased from 3.30GPa to an average value of 3.92GPa. The transverse Young's modulus was lowered from an initial value of 10.00GPa to 9.89GPa. Low inter- and intra-specimen variability was found. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automatic online and real-time tumour motion monitoring during stereotactic liver treatments on a conventional linac by combined optical and sparse monoscopic imaging with kilovoltage x-rays (COSMIK)

NASA Astrophysics Data System (ADS)

Bertholet, Jenny; Toftegaard, Jakob; Hansen, Rune; Worm, Esben S.; Wan, Hanlin; Parikh, Parag J.; Weber, Britta; Høyer, Morten; Poulsen, Per R.

2018-03-01

The purpose of this study was to develop, validate and clinically demonstrate fully automatic tumour motion monitoring on a conventional linear accelerator by combined optical and sparse monoscopic imaging with kilovoltage x-rays (COSMIK). COSMIK combines auto-segmentation of implanted fiducial markers in cone-beam computed tomography (CBCT) projections and intra-treatment kV images with simultaneous streaming of an external motion signal. A pre-treatment CBCT is acquired with simultaneous recording of the motion of an external marker block on the abdomen. The 3-dimensional (3D) marker motion during the CBCT is estimated from the auto-segmented positions in the projections and used to optimize an external correlation model (ECM) of internal motion as a function of external motion. During treatment, the ECM estimates the internal motion from the external motion at 20 Hz. KV images are acquired every 3 s, auto-segmented, and used to update the ECM for baseline shifts between internal and external motion. The COSMIK method was validated using Calypso-recorded internal tumour motion with simultaneous camera-recorded external motion for 15 liver stereotactic body radiotherapy (SBRT) patients. The validation included phantom experiments and simulations hereof for 12 fractions and further simulations for 42 fractions. The simulations compared the accuracy of COSMIK with ECM-based monitoring without model updates and with model updates based on stereoscopic imaging as well as continuous kilovoltage intrafraction monitoring (KIM) at 10 Hz without an external signal. Clinical real-time tumour motion monitoring with COSMIK was performed offline for 14 liver SBRT patients (41 fractions) and online for one patient (two fractions). The mean 3D root-mean-square error for the four monitoring methods was 1.61 mm (COSMIK), 2.31 mm (ECM without updates), 1.49 mm (ECM with stereoscopic updates) and 0.75 mm (KIM). COSMIK is the first combined kV/optical real-time motion monitoring method used clinically online on a conventional accelerator. COSMIK gives less imaging dose than KIM and is in addition applicable when the kV imager cannot be deployed such as during non-coplanar fields.

Through-process modelling of texture and anisotropy in AA5182

NASA Astrophysics Data System (ADS)

Crumbach, M.; Neumann, L.; Goerdeler, M.; Aretz, H.; Gottstein, G.; Kopp, R.

2006-07-01

A through-process texture and anisotropy prediction for AA5182 sheet production from hot rolling through cold rolling and annealing is reported. Thermo-mechanical process data predicted by the finite element method (FEM) package T-Pack based on the software LARSTRAN were fed into a combination of physics based microstructure models for deformation texture (GIA), work hardening (3IVM), nucleation texture (ReNuc), and recrystallization texture (StaRT). The final simulated sheet texture was fed into a FEM simulation of cup drawing employing a new concept of interactively updated texture based yield locus predictions. The modelling results of texture development and anisotropy were compared to experimental data. The applicability to other alloys and processes is discussed.

An initial study on the estimation of time-varying volumetric treatment images and 3D tumor localization from single MV cine EPID images

PubMed Central

Mishra, Pankaj; Li, Ruijiang; Mak, Raymond H.; Rottmann, Joerg; Bryant, Jonathan H.; Williams, Christopher L.; Berbeco, Ross I.; Lewis, John H.

2014-01-01

Purpose: In this work the authors develop and investigate the feasibility of a method to estimate time-varying volumetric images from individual MV cine electronic portal image device (EPID) images. Methods: The authors adopt a two-step approach to time-varying volumetric image estimation from a single cine EPID image. In the first step, a patient-specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient-specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculated through deformable image registration (DIR) of a reference 4DCT phase image (typically peak-exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen-coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen-coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. Results: The algorithm was tested on (1) Eight digital eXtended CArdiac-Torso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root-mean-squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. Conclusions: The authors introduced a novel method of estimating volumetric time-varying images from single cine EPID images and a PCA-based lung motion model. This is the first method to estimate volumetric time-varying images from single MV cine EPID images, and has the potential to provide volumetric information with no additional imaging dose to the patient. PMID:25086523

An initial study on the estimation of time-varying volumetric treatment images and 3D tumor localization from single MV cine EPID images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, Pankaj, E-mail: pankaj.mishra@varian.com; Mak, Raymond H.; Rottmann, Joerg

2014-08-15

Purpose: In this work the authors develop and investigate the feasibility of a method to estimate time-varying volumetric images from individual MV cine electronic portal image device (EPID) images. Methods: The authors adopt a two-step approach to time-varying volumetric image estimation from a single cine EPID image. In the first step, a patient-specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient-specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculatedmore » through deformable image registration (DIR) of a reference 4DCT phase image (typically peak-exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen-coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen-coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. Results: The algorithm was tested on (1) Eight digital eXtended CArdiac-Torso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root-mean-squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. Conclusions: The authors introduced a novel method of estimating volumetric time-varying images from single cine EPID images and a PCA-based lung motion model. This is the first method to estimate volumetric time-varying images from single MV cine EPID images, and has the potential to provide volumetric information with no additional imaging dose to the patient.« less

"Updates to Model Algorithms & Inputs for the Biogenic ...

EPA Pesticide Factsheets

We have developed new canopy emission algorithms and land use data for BEIS. Simulations with BEIS v3.4 and these updates in CMAQ v5.0.2 are compared these changes to the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and evaluated the simulations against observations. This has resulted in improvements in model evaluations of modeled isoprene, NOx, and O3. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.

LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models.

PubMed

Soto, Axel J; Zerva, Chrysoula; Batista-Navarro, Riza; Ananiadou, Sophia

2018-04-15

Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find information relevant to a model, which is a laborious and knowledge-intensive task. Furthermore, models curated manually cannot be easily updated and maintained with new evidence extracted from the literature without automated support. We have developed LitPathExplorer, a visual text analytics tool that integrates advanced text mining, semi-supervised learning and interactive visualization, to facilitate the exploration and analysis of pathway models using statements (i.e. events) extracted automatically from the literature and organized according to levels of confidence. LitPathExplorer supports pathway modellers and curators alike by: (i) extracting events from the literature that corroborate existing models with evidence; (ii) discovering new events which can update models; and (iii) providing a confidence value for each event that is automatically computed based on linguistic features and article metadata. Our evaluation of event extraction showed a precision of 89% and a recall of 71%. Evaluation of our confidence measure, when used for ranking sampled events, showed an average precision ranging between 61 and 73%, which can be improved to 95% when the user is involved in the semi-supervised learning process. Qualitative evaluation using pair analytics based on the feedback of three domain experts confirmed the utility of our tool within the context of pathway model exploration. LitPathExplorer is available at http://nactem.ac.uk/LitPathExplorer_BI/. sophia.ananiadou@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

Nonuniformity correction for an infrared focal plane array based on diamond search block matching.

PubMed

Sheng-Hui, Rong; Hui-Xin, Zhou; Han-Lin, Qin; Rui, Lai; Kun, Qian

2016-05-01

In scene-based nonuniformity correction algorithms, artificial ghosting and image blurring degrade the correction quality severely. In this paper, an improved algorithm based on the diamond search block matching algorithm and the adaptive learning rate is proposed. First, accurate transform pairs between two adjacent frames are estimated by the diamond search block matching algorithm. Then, based on the error between the corresponding transform pairs, the gradient descent algorithm is applied to update correction parameters. During the process of gradient descent, the local standard deviation and a threshold are utilized to control the learning rate to avoid the accumulation of matching error. Finally, the nonuniformity correction would be realized by a linear model with updated correction parameters. The performance of the proposed algorithm is thoroughly studied with four real infrared image sequences. Experimental results indicate that the proposed algorithm can reduce the nonuniformity with less ghosting artifacts in moving areas and can also overcome the problem of image blurring in static areas.

Research on navigation of satellite constellation based on an asynchronous observation model using X-ray pulsar

NASA Astrophysics Data System (ADS)

Guo, Pengbin; Sun, Jian; Hu, Shuling; Xue, Ju

2018-02-01

Pulsar navigation is a promising navigation method for high-altitude orbit space tasks or deep space exploration. At present, an important reason for restricting the development of pulsar navigation is that navigation accuracy is not high due to the slow update of the measurements. In order to improve the accuracy of pulsar navigation, an asynchronous observation model which can improve the update rate of the measurements is proposed on the basis of satellite constellation which has a broad space for development because of its visibility and reliability. The simulation results show that the asynchronous observation model improves the positioning accuracy by 31.48% and velocity accuracy by 24.75% than that of the synchronous observation model. With the new Doppler effects compensation method in the asynchronous observation model proposed in this paper, the positioning accuracy is improved by 32.27%, and the velocity accuracy is improved by 34.07% than that of the traditional method. The simulation results show that without considering the clock error will result in a filtering divergence.

Some safe and sensible shortcuts for efficiently upscaled updates of existing elevation models.

NASA Astrophysics Data System (ADS)

Knudsen, Thomas; Aasbjerg Nielsen, Allan

2013-04-01

The Danish national elevation model, DK-DEM, was introduced in 2009 and is based on LiDAR data collected in the time frame 2005-2007. Hence, DK-DEM is aging, and it is time to consider how to integrate new data with the current model in a way that improves the representation of new landscape features, while still preserving the overall (very high) quality of the model. In LiDAR terms, 2005 is equivalent to some time between the palaeolithic and the neolithic. So evidently, when (and if) an update project is launched, we may expect some notable improvements due to the technical and scientific developments from the last half decade. To estimate the magnitude of these potential improvements, and to devise efficient and effective ways of integrating the new and old data, we currently carry out a number of case studies based on comparisons between the current terrain model (with a ground sample distance, GSD, of 1.6 m), and a number of new high resolution point clouds (10-70 points/m2). Not knowing anything about the terms of a potential update project, we consider multiple scenarios ranging from business as usual: A new model with the same GSD, but improved precision, to aggressive upscaling: A new model with 4 times better GSD, i.e. a 16-fold increase in the amount of data. Especially in the latter case speeding up the gridding process is important. Luckily recent results from one of our case studies reveal that for very high resolution data in smooth terrain (which is the common case in Denmark), using local mean (LM) as grid value estimator is only negligibly worse than using the theoretically "best" estimator, i.e. ordinary kriging (OK) with rigorous modelling of the semivariogram. The bias in a leave one out cross validation differs on the micrometer level, while the RMSE differs on the 0.1 mm level. This is fortunate, since a LM estimator can be implemented in plain stream mode, letting the points from the unstructured point cloud (i.e. no TIN generation) stream through the processor, individually contributing to the nearest grid posts in a memory mapped grid file. Algorithmically this is very efficient, but it would be even more efficient if we did not have to handle so much data. Another of our recent case studies focuses on this. The basic idea is to ignore data that does not tell us anything new. We do this by looking at anomalies between the current height model and the new point cloud, then computing a correction grid for the current model. Points with insignificant anomalies are simply removed from the point cloud, and the correction grid is computed using the remaining point anomalies only. Hence, we only compute updates in areas of significant change, speeding up the process, and giving us new insight of the precision of the current model which in turn results in improved metadata for both the current and the new model. Currently we focus on simple approaches for creating a smooth update process for integration of heterogeneous data sets. On the other hand, as years go by and multiple generations of data become available, more advanced approaches will probably become necessary (e.g. a multi campaign bundle adjustment, improving the oldest data using cross-over adjustment with newer campaigns). But to prepare for such approaches, it is important already now to organize and evaluate the ancillary (GPS, INS) and engineering level data for the current data sets. This is essential if future generations of DEM users should be able to benefit from future conceptions of "some safe and sensible shortcuts for efficiently upscaled updates of existing elevation models".

Optimal updating magnitude in adaptive flat-distribution sampling

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Drake, Justin A.; Ma, Jianpeng; Pettitt, B. Montgomery

2017-11-01

We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.

Optimal updating magnitude in adaptive flat-distribution sampling.

PubMed

Zhang, Cheng; Drake, Justin A; Ma, Jianpeng; Pettitt, B Montgomery

2017-11-07

We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.