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Effects of model variability on the safeguard analysis of gamma-contaminated truck loads

MATHEMATICS AND COMPUTERS IN SIMULATION 2001年第1-3期55卷 159-166页

作者： Marseguerra, M Padovani, E Zio, E Politecn Milan Dept Nucl Engn I-20133 Milan Italy

In the past few decades, the problem of dealing with inadvertently contaminated steel has turned out to be of real importance in several countries. Typically, this problem originates at a foundry which recycles scrap iron: indeed, in several instances it happened that the material to be smelted contained hidden gamma-sources, thus giving rise to safety problems with major health and economical Ball backs. For this reason, the monitoring of the trucks arriving at the foundry gate is now of widely recognised importance. To date, most development efforts have been experimental with good results being achieved. More recently, the investigation of this problem using models is being pursued for a more fundamental understanding of the issues at stake. In this respect, the way of modelling the extreme geometrical variability of truck loads, even in case of same total scrap weight, is the crucial aspect and inevitably introduces elements of subjectivity and uncertainty. Correspondingly, the findings obtained by any modelling approach should be physically reasonable but one should be aware that their information content only resides in the general behaviour of the calculated results and their orders of magnitude. The very nature of the problem is such that the Monte Carlo simulation is the only appropriate and suitable method of solution. In this paper, we propose different conceptual models to depict the variability in the truck loads and analyse their effects on the responses of detectors placed at the foundry gate. The different results thereby obtained are discussed and compared. (C) 2001 IMACS. Published by Elsevier Science B.V. All rights reserved.

关键词： contaminated scrap truck loads model variability Monte Carlo

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BOOTSTRAP ESTIMATES OF FACTOR model variability

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ATMOSPHERIC ENVIRONMENT 1987年第5期21卷 1203-1217页

作者： HEIDAM, NZ National Agency of Environmental Protection Air Pollution Laboratory Risø National Laboratory DK-4000 Roskilde Denmark

Receptor models for air pollutants in an airshed are constructed from a set of measured concentrations and used for apportioning sources in a quantitative way. Such a dataset even if large is but a sample from the population of pollutants occurring over time in the airshed. Thus the ensuing receptor model and its parameter constitute but one localization of a range of possible experiments. The problem studied in this paper is how large the inherent ranges of variation of the model parameters are, i.e. how reliable the model is. Factor analysis models, whereas data are autoscaled prior to analysis, were selected for study. Pseudo-repititions of the experiment are carried out by bootstrapping of the original data and statistics on the model parameters are complied and reported. The validity of the results of such numerical experiments are based on the assumption that the original data are really representative since by bootstrapping, new artificial data are generated from this set. A number of screening tests for acceptance of data and models are applied to avoid bias and errors in the results. Means and standard tests for acceptance of data and models are applied to void bias and errors in the results. Means and standard deviations of communalities and factor loadings are computed and compared to the original parameters. Regression analysis is used in a search for functional relationships between standard deviations and model parameters. The general conclusion is that well modelled variables carry little model uncertainty and that the largest standard deviations amounting to about 10% are found for loadings in the mid-range.

关键词： Atmospheric aerosol bootstrap factor analysis model variability receptor models

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Quantification of model uncertainty and variability in Newmark displacement analysis

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SOIL DYNAMICS AND EARTHQUAKE ENGINEERING 2018年 109卷 286-298页

作者： Du, Wenqi Huang, Duruo Wang, Gang Nanyang Technol Univ Inst Catastrophe Risk Management 50 Nanyang Ave Singapore Singapore Tsinghua Univ Dept Hydraul Engn Beijing Peoples R China Hong Kong Univ Sci & Technol Dept Civil & Environm Engn Kowloon Hong Kong Peoples R China

Newmark displacement model has been extensively used to evaluate earthquake-induced displacement in earth systems. In this paper, model uncertainty and variability associated with the Newmark displacement analysis are systematically studied. Fourteen Newmark displacement models using scalar or vector intensity measures (IMs) as predictors are compared in this study. In general, model uncertainty for the vector-IM models is found smaller than that of the scalar-IM models, and remains consistent over different earthquake magnitude, distance and site conditions. Yet, the model uncertainty of these Newmark displacement models is still much larger than that of the ground-motion prediction equations (GMPEs) for IMs, indicating further development of the models is much needed. Considering the variabilities contributed from both GMPEs and Newmark displacement models, the total variability of the predicted Newmark displacements is rather consistent among the scalar- and vector-IM displacement models, due to extra sources of variability introduced by incorporating additional IMs. Finally, a logic tree scheme is implemented in the fully probabilistic Newmark displacement analysis to account for the model uncertainty and variability. Sensitivity analysis shows that specific weights would not significantly influence the displacement hazard curves as the results may be dominated by outlier models. Instead, selecting appropriate GMPEs and Newmark displacement models is more important in using the logic-tree framework.

关键词： Newmark displacement model uncertainty model variability Probabilistic analysis

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Exploration of Continuous variability in Collections of 3D Shapes

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ACM TRANSACTIONS ON GRAPHICS 2011年第4期30卷 1-10页

作者： Ovsjanikov, Maks Li, Wilmot Guibas, Leonidas Mitra, Niloy J. Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)9781450309431

As large public repositories of 3D shapes continue to grow, the amount of shape variability in such collections also increases, both in terms of the number of different classes of shapes, as well as the geometric variability of shapes within each class. While this gives users more choice for shape selection, it can be difficult to explore large collections and understand the range of variations amongst the shapes. Exploration is particularly challenging for public shape repositories, which are often only loosely tagged and contain neither point-based nor part-based correspondences. In this paper, we present a method for discovering and exploring continuous variability in a collection of 3D shapes without correspondences. Our method is based on a novel navigation interface that allows users to explore a collection of related shapes by deforming a base template shape through a set of intuitive deformation controls. We also help the user to select the most meaningful deformations using a novel technique for learning shape variability in terms of deformations of the template. Our technique assumes that the set of shapes lies near a low-dimensional manifold in a certain descriptor space, which allows us to avoid establishing correspondences between shapes, while being rotation and scaling invariant. We present results on several shape collections taken directly from public repositories.

关键词： 3D database exploration shape descriptors shape analysis morphable models model variability

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Can dose-response models predict reliable normal tissue complication probabilities in radical radiotherapy of urinary bladder cancer? The impact of alternative radiation tolerance models and parameters

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INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS 2001年第3期50卷 627-637页

作者： Muren, LP Jebsen, N Gustafsson, A Dahl, O Haukeland Hosp Dept Radiophys N-5021 Bergen Norway Haukeland Hosp Inst Med Sect Oncol Fac Med N-5021 Bergen Norway Haukeland Hosp Dept Oncol N-5021 Bergen Norway MDS Nordion AB Uppsala Sweden

Purpose: To analyze the consequences of selecting alternative normal tissue complication probability (NTCP) models and parameters for evaluation of radiotherapy of urinary bladder cancer. Methods and Materials: Treatment plans of 24 bladder cancer patients referred to radical 4-field conformal radiotherapy were analyzed. Small intestinal and rectal NTCPs were determined using both the probit and relative seriality models with several sets of published radiation tolerance parameters, Various combinations of NTCP models and parameters were applied to find the prescription dose in individual patients as well as to estimate the benefit of the conformal radiotherapy setup. Results: Different risk estimates were predicted from the two NTCP models, even when the same clinical radiation tolerance doses were fitted into the two models, The demonstrated variability translated into significant deviations (7-10 Gy) in the recommended prescription doses. Even if it was possible to discriminate between a 2-field plan and the 4-field conformal setup using a given complication model and set of tolerance parameters, the estimated benefit of the conformal treatment in terms of permitted dose escalation varied with as much as 10-12 Gy between the different NTCP models/parameters used, Conclusion: Different NTCP models and tolerance parameters might propose different answers to important clinical questions in radiotherapy treatment of bladder cancer, such as dose prescription and scoring of rival treatment plans, We therefore recommend that the variability caused by tolerance parameter uncertainty and model selection should be taken into account in dose-response modeling of radiotherapy treatment. (C) 2001 Elsevier Science Inc.

关键词： urinary bladder cancer normal tissue complication probability models radiation tolerance doses model variability dose prescription

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modeling data protection and privacy: application and experience with GDPR

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SOFTWARE AND SYSTEMS modelING 2021年第6期20卷 2071-2087页

作者： Torre, Damiano Alferez, Mauricio Soltana, Ghanem Sabetzadeh, Mehrdad Briand, Lionel Univ Luxembourg SnT Ctr Secur Reliabil & Trust Esch Sur Alzette Luxembourg Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada Texas A&M Univ Cent Texas Dept Comp Informat Syst Killeen TX 76549 USA

In Europe and indeed worldwide, the General Data Protection Regulation (GDPR) provides protection to individuals regarding their personal data in the face of new technological developments. GDPR is widely viewed as the benchmark for data protection and privacy regulations that harmonizes data privacy laws across Europe. Although the GDPR is highly beneficial to individuals, it presents significant challenges for organizations monitoring or storing personal information. Since there is currently no automated solution with broad industrial applicability, organizations have no choice but to carry out expensive manual audits to ensure GDPR compliance. In this paper, we present a complete GDPR UML model as a first step toward designing automated methods for checking GDPR compliance. Given that the practical application of the GDPR is influenced by national laws of the EU Member States, we suggest a two-tiered description of the GDPR, generic and specialized. In this paper, we provide (1) the GDPR conceptual model we developed with complete traceability from its classes to the GDPR, (2) a glossary to help understand the model, (3) the plain-English description of 35 compliance rules derived from GDPR along with their encoding in OCL and (4) the set of 20 variations points derived from GDPR to specialize the generic model. We further present the challenges we faced in our modeling endeavor, the lessons we learned from it and future directions for research.

关键词： General Data Protection Regulation (GDPR) Conceptual modeling model variability Regulatory compliance Unified modeling Language (UML)

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Forced trends and internal variability in climate change projections of extreme European windstorm frequency and severity

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QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY 2024年第765期150卷 4933-4950页

作者： Priestley, Matthew D. K. Stephenson, David B. Scaife, Adam A. Bannister, Daniel Allen, Christopher J. T. Wilkie, David Univ Exeter Dept Math & Stat Exeter England Met Off Exeter England WTW Res Network WTW London England Gallagher Re Model Res & Evaluat London England

Climate change projections of European windstorm damages are highly uncertain because of different climate model responses and large internal variability. This study uses generalized linear models and a weighted median estimation to optimally extract forced trends in a number of European windstorm metrics. Footprints of windstorms associated with extratropical cyclones are created for an ensemble of models from the Coupled model Intercomparison Project Phase 6 (CMIP6) across a full transient time series from 1980 to 2100. Trends are assessed over time, but also as a function of global mean surface temperature changes. Trends in aggregate severity are attributed to changes in storm average severity, frequency, and area impacted, with changes in area being the dominant driver of changes to average storm severity. Confidence in the findings is assessed, with high confidence of declines in frequency for southern and northern Europe, medium confidence of an increase in average windstorm severity for parts of northwestern Europe, and low confidence of any changes for eastern Europe. A 15-member ensemble of the MPI-ESM1-2-LR model is used to assess internal variability. Trends between individual members can vary significantly;however, the uncertainty due to internal variability in the 15-member ensemble is generally only 50% of that in the multimodel ensemble of CMIP6 models for aggregate severity. With largest uncertainty coming from model differences, a large proportion of uncertainty in future windstorms is therefore potentially reducible with modelling advances. This study provides an assessment of changes to European windstorm severity and frequency in a warming climate. The results show increases in storm average and aggregate severity for western Europe, central Europe, and Great Britain/Ireland, driven by an increase in the area of a windstorm footprint. An assessment of internal variability indicates that it is smaller than model variability, although considerable

关键词： Climate change trends European windstorm internal variability model variability storm severity weighted median

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Relation-based parametrization and exploration of shape collections

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COMPUTERS & GRAPHICS-UK 2017年 67卷 127-137页

作者： Leimer, Kurt Gersthofer, Lukas Wimmer, Michael Musialski, Przemyslaw TU Wien Karlspl 13 A-1040 Vienna Austria

With online repositories for 3D models like 3D Warehouse becoming more prevalent and growing ever larger, new possibilities have emerged for both experienced and inexperienced users. These large collections of shapes can provide inspiration for designers or make it possible to synthesize new shapes by combining different parts from already existing shapes, which can be both easy to learn and a fast way of creating new shapes. But exploring large shape collections or searching for particular kinds of shapes can be difficult and time-consuming tasks as well, especially considering that online repositories are often disorganized. In our work, we propose a relation-based way to parametrize shape collections, allowing the user to explore the entire set of shapes based on the variability of spatial arrangements between pairs of parts. The way in which shapes differ from each other is captured automatically, resulting in a small number of exploration parameters. Furthermore, a copy-and-paste system for parts allows the user to change the structure of a shape, making it possible to explore the entire collection from any initial shape. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： 3D database exploration model variability Shape analysis Shape collections

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Filling the matrix: an ANOVA-based method to emulate regional climate model simulations for equally-weighted properties of ensembles of opportunity

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CLIMATE DYNAMICS 2022年第9-10期58卷 2371-2385页

作者： Christensen, Ole B. Kjellstrom, Erik Danish Meteorol Inst DMI Copenhagen Denmark Swedish Meteorol & Hydrol Inst SMHI Norrkoping Sweden Stockholm Univ Dept Meteorol Stockholm Sweden Stockholm Univ Bolin Ctr Climate Res Stockholm Sweden

Collections of large ensembles of regional climate model (RCM) downscaled climate data for particular regions and scenarios can be organized in a usually incomplete matrix consisting of GCM (global climate model) x RCM combinations. When simple ensemble averages are calculated, each GCM will effectively be weighted by the number of times it has been downscaled. In order to facilitate more equal and less arbitrary weighting among downscaled GCM results, we present a method to emulate the missing combinations in such a matrix, enabling equal weighting among participating GCMs and hence among regional consequences of large-scale climate change simulated by each GCM. This method is based on a traditional Analysis of Variance (ANOVA) approach. The method is applied and studied for fields of seasonal average temperature, precipitation and surface wind and for the 10-year return value of daily precipitation and of 10-m wind speed for a completely filled matrix consisting of 5 GCMs and 4 RCMs. We quantify the skill of the two averaging methods for different numbers of missing simulations and show that ensembles where lacking members have been emulated by the ANOVA technique are better at representing the full ensemble than corresponding simple ensemble averages, particularly in cases where only a few model combinations are absent. The technique breaks down when the number of missing simulations reaches the sum of the numbers of GCMs and RCMs. Also, the method is only useful when inter-simulation variability is limited. This is the case for the average fields that have been studied, but not for the extremes. We have developed analytical expressions for the degree of improvement obtained with the present method, which quantify this conclusion.

关键词： Ensemble Regional climate model model matrix ANOVA EURO-CORDEX model variability

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Regional uncertainty analysis between crop phenology model structures and optimal parameters

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AGRICULTURAL AND FOREST METEOROLOGY 2024年 355卷

作者： Yang, Chenyao Lei, Na Menz, Christoph Ceglar, Andrej Matallana, Jairo Arturo Torres- Li, Siqi Jiang, Yanling Tan, Xianming Tao, Lei He, Fang Li, Shigui Liu, Bing Yang, Feng Fraga, Helder Santos, Joa A. Sichuan Agr Univ Coll Agron Chengdu 611130 Peoples R China Univ Tras Os Montes & Alto Douro UTAD Inst Innovat Capac Bldg & Sustainabil Agrifood Pro Ctr Res & Technol Agroenvironm & Biol Sci CITAB P-5000801 Vila Real Portugal Sichuan Agr Univ Key Lab Agr Bioinformat Minist Educ Chengdu Peoples R China Potsdam Inst Climate Impact Res eV P Telegrafenberg 31 D-14473 Potsdam Germany European Cent Bank Climate Change Ctr Sonnemannstr 20 D-60314 Frankfurt Germany Helmholtz Zentrum Hereon Climate Serv Ctr Germany GERICS Fischertwiete 1 D-20095 Hamburg Germany Sichuan Seed Stn 5 Yulin North Rd Chengdu 610044 Peoples R China Sichuan Agr Univ Rice Res Inst Chengdu 611130 Peoples R China Nanjing Agr Univ Minist Agr Natl Engn & Technol Ctr Informat Agr Engn Res Ctr Smart AgrMinist EducKey Lab Crop Sy Nanjing Peoples R China

Crop phenology models are pivotal for simulating crop development, predicting yields and guiding agricultural practices. However, uncertainties exist in simulations due to different model structures and variability in model parameters. Although quantifying these contributions to total variability is often conducted at a site-specific level, few attempts to address this for regional crop modelling using field-calibrated parameters. Our study employs six crop phenology models (APSIM, CERES, GDD, Richardson, Sigmoid and Wang) for simulating maturity timings of three representative rice cultivars using trial data within the Sichuan Basin, China. The Leave-One-Out Cross-Validation (LOOCV) is applied for model calibration with a global parameter optimization algorithm and evaluation. Calibrated models show robust prediction capabilities during LOOCV with R2 2 of 0.68-0.95 and RMSE of 2-4 days, though a larger variance is found for evaluation data than for calibration data. models calibrated with data from sites having frequent high-temperature (Tmax >= 32 max >= 32 degrees C) episodes tend to have better predictability than without high-temperature episodes. Parameter variability, calibrated with different subsets of each cultivar during LOOCV, is low-to-moderate (mostly CV <= 20 %) except for the Sigmoid models curve steepness parameter. For the early-maturity cultivar, parameter variability is spatially the main uncertainty factor, relating to its greater variability of site-specific calibrated parameter values. For the medium- maturity and late-maturity cultivars, the dominant uncertainty source arises from the interplay between model structures and parameters. Parameter variability notably influences the overall uncertainty more than the model structure variability across the region, except in areas prone to high-temperature extremes where divergent model responses predominate. These findings highlight the cultivar-specific nature of simulation uncertain

关键词： Crop Phenology model Ensemble Simulation Parameter Uncertainty model variability Cross Validation Regional modelling

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