Flexible Parameterization Research Articles

Fitting occupancy models with E‐SURGE: hidden Markov modelling of presence–absence data

Summary Occupancy – the proportion of area occupied by a species – is a key notion for addressing important questions in ecology, biogeography and conservation biology. Occupancy models allow estimating and inferring about species occurrence while accounting for false absences (or imperfect species detection). Occupancy models can be formulated as hidden Markov models (HMM) in which the state process captures the Markovian dynamic of the actual but latent states, while the observation process consists of observations that are made from these underlying states. We show how occupancy models can be implemented in program E‐SURGE, which was initially developed to analyse capture–recapture data in the HMM framework. Replacing individuals by sites provides the user with access to several features of E‐SURGE that are not available altogether or just not available in standard occupancy software: i) flexible model specification through a user‐friendly syntax without having to write custom code, ii) decomposition of the observation and state processes in several steps to provide flexible parameterisation, iii) up‐to‐date diagnostics of model identifiability, and iv) advanced numerical algorithms to produce fast and reliable results (including site random effects). To illustrate E‐SURGE features, we provide implementation and analysis details for several occupancy models. We also provide simulated and real‐world examples as well as further specifications and information in a companion wiki platform http://occupancyinesurge.wikidot.com/.

A parameterization method and application in breast tomosynthesis dosimetry

To present a parameterization method based on singular value decomposition (SVD), and to provide analytical parameterization of the mean glandular dose (MGD) conversion factors from eight references for evaluating breast tomosynthesis dose in the Mammography Quality Standards Act (MQSA) protocol and in the UK, European, and IAEA dosimetry protocols. MGD conversion factor is usually listed in lookup tables for the factors such as beam quality, breast thickness, breast glandularity, and projection angle. The authors analyzed multiple sets of MGD conversion factors from the Hologic Selenia Dimensions quality control manual and seven previous papers. Each data set was parameterized using a one- to three-dimensional polynomial function of 2-16 terms. Variable substitution was used to improve accuracy. A least-squares fit was conducted using the SVD. The differences between the originally tabulated MGD conversion factors and the results computed using the parameterization algorithms were (a) 0.08%-0.18% on average and 1.31% maximum for the Selenia Dimensions quality control manual, (b) 0.09%-0.66% on average and 2.97% maximum for the published data by Dance et al. [Phys. Med. Biol. 35, 1211-1219 (1990); ibid. 45, 3225-3240 (2000); ibid. 54, 4361-4372 (2009); ibid. 56, 453-471 (2011)], (c) 0.74%-0.99% on average and 3.94% maximum for the published data by Sechopoulos et al. [Med. Phys. 34, 221-232 (2007); J. Appl. Clin. Med. Phys. 9, 161-171 (2008)], and (d) 0.66%-1.33% on average and 2.72% maximum for the published data by Feng and Sechopoulos [Radiology 263, 35-42 (2012)], excluding one sample in (d) that does not follow the trends in the published data table. A flexible parameterization method is presented in this paper, and was applied to breast tomosynthesis dosimetry. The resultant data offer easy and accurate computations of MGD conversion factors for evaluating mean glandular breast dose in the MQSA protocol and in the UK, European, and IAEA dosimetry protocols. Microsoft Excel™ spreadsheets are provided for the convenience of readers.

Simultaneous joint inversion of amplitude-versus-offset and controlled-source electromagnetic data by implicit representation of common parameter structure

I evaluated a simultaneous joint inversion of seismic amplitude-versus-offset (AVO) and controlled-source electromagnetic (CSEM) data for fluid-flow monitoring. A new approach for structure-coupled joint inversion was presented, in which the coupling of the two data types was obtained by allowing for the direct identification of parameter structure that is shared by the different geophysical model parameters. The main idea was to use a composite parameter representation, which enables inversion with respect to the parameter magnitude and parameter structure. In the current application, parameter structure refers to transitions between dominating property values and is represented by the position and shape of the flooding front. Hence, with this approach, the position and shape of the flooding front are inverted for directly, and the coupling between the different data sets is obtained without the inclusion of an additional penalizing term in the objective function. Regularization of the inverse problem is obtained by using a flexible parameterization grid adapted to the resolution power of the available data. This approach is especially suited for problems in which the prior information is limited or highly uncertain. The solution approach is illustrated for two types of coupling: (1) identification of fluid saturation using rock-physics modeling and (2) for structure-coupled joint inversion with respect to P-wave velocity and electric conductivity. Through various synthetic examples in 2D, the proposed approach showed its efficiency for identifying the main features of the fluid distribution within the reservoir. Simultaneously inverting AVO and CSEM data was further seen to give results that were more robust with respect to certain random and more systematic (modeling) errors compared with inverting the data sets separately.

Predicting freshwater life history diversity: filtering potential life history tactics via habitat scenarios using ecosystem diagnosis and treatment

Hutchinson revolutionized ecology in the 1950s with his description of species requirements in terms of its “n-dimensional hypervolume” (Hutchinson 1957). The dimensions define the environmental requirements of a species or life history. EDT evaluates habitat quality using this Hutchinsonian niche concept, describing ecological space through the eyes of a focal species, where the realized niche is the fundamental niche constrained by real-world biotic and abiotic factors. EDT filters niche breadth via life-stage habitat rules, and niche height through the definition of life history tactics. EDT allows flexible parameterization of life-histories, and can be used to develop hypotheses regarding the success of various life histories under environmental scenarios. Examining potential success of multiple life history tactics emulates how selection may act on a diverse genetic framework and select for or against tactics to allow for viability under a given restoration and reintroduction scenario. We developed and peer reviewed seven biologically reasonable life history tactics (Table 1) to be evaluated against the current and future habitat conditions.

The application of the Modified Band Approach for the calculation of on-line photodissociation rate constants in TM5: implications for oxidative capacity

Abstract. A flexible and explicit on-line parameterization for the calculation of tropospheric photodissociation rate constants (J-values) has been integrated into the global Chemistry Transport Model TM5. Here we provide a comprehensive description of this Modified Band Approach (MBA) including details of the optimization procedure employed, the methodology applied for calculating actinic fluxes, the photochemical reaction data used for each chemical species, the aerosol climatology which is adopted and the parameterizations adopted for improving the description of scattering and absorption by clouds. The resulting J-values change markedly throughout the troposphere when compared to the offline approach used to date, with significant increases in the boundary layer and upper troposphere. Conversely, for the middle troposphere a reduction in the actinic flux results in a decrease in J-values. Integrating effects shows that application of the MBA introduces seasonal dependent differences in important trace gas oxidants. Tropospheric ozone (O3) changes by ±10% in the seasonal mean mixing ratios throughout the troposphere, especially over land. These changes and the perturbations in the photolysis rate of O3 induce changes of ±15% in tropospheric OH. In part this is due to an increase in the re-cycling efficiency of nitrogen oxides. The overall increase in northern hemispheric tropospheric ozone strengthens the oxidizing capacity of the troposphere significantly and reduces the lifetime of CO and CH4 by ~5 % and ~4%, respectively. Changes in the tropospheric CO burden, however, are limited to a few percent due to competing effects. Comparing the distribution of tropospheric ozone in the boundary layer and middle troposphere against observations in Europe shows there are improvements in the model performance during boreal winter in the Northern Hemisphere near regions affected by high nitrogen oxide emissions. Monthly mean total columns of nitrogen dioxide and formaldehyde also compare more favorably against OMI and SCIAMACHY total column observations.

Identification of Hammerstein-Weiner System for Normal and Shading Operation of PhotovoltaicSystem

This paper present an identification of model system performance for Photovoltaic (PV) System under normal and shading operating condition in UiTM Pulau Pinang, Malaysia of 2.4 kW systems. A system identification approach was implemented by employing a Hammerstein-Weiner (HW) model as model structure. The approach concerned on the estimation of the photovoltaic system basis of observed data. The nonlinearity input and output are taken from irradiance and dc output current data of the real system severally. These data were used in Hammerstein-Weiner model to generate a black-box model structure which provides a flexible parameterization for nonlinear models. The best fit nonlinear model when using data from normal operating condition is when HW model incorporate with piecewise linear as the input channel and wavelet network estimators as output channel. For normal operation of PV system, the percentage of best fit was 96.51% by means of bn = 1, fn = 3, and kn = 2 of the linear model order. While the percentage best fit model generate considering shading effect was 86.32% with bn = 1, fn = 3, and kn = 1 of the linear model order. The modelling is implemented using system identification toolbox of Matlab software package.

Cyclical wage movements in emerging markets compared to developed economies: The role of interest rates

This paper documents that, at the aggregate level, (i) real wages are positively correlated with output and, on average, lag output by about one quarter in emerging markets, while there are no systematic patterns in developed economies, and (ii) real wage volatility (relative to output volatility) is about twice as high in emerging markets compared with developed economies. We then present a small open economy model with productivity shocks and countercyclical interest rates. The model incorporates a working capital requirement and the Jaimovich and Rebelo (2009) preference that allows for flexible parameterization of the strength of income effects on labor supply. The model can account for the high volatility of wage and consumption relative to output and countercyclical trade balances that characterize emerging-market economies. During economic downturns, rising interest rates in emerging markets induce relatively large income effects on labor supply, so households would not reduce their labor input as much even though wages drop significantly.

Optimal control of Formula 1 race cars in a VDrift based virtual environment

AbstractControl of autonomous vehicles and providing recommendations to drivers in real time are challenging tasks from an algorithmic point of view. To include realistic effects, such as nonlinear tire dynamics, at least medium-sized mathematical models need to be considered. Yet, fast feedback is of utmost importance. Existing Nonlinear Model Predictive Control (NMPC) algorithms need to be enhanced to comply with these two contradictory requirements. As the testing of algorithms in an automatic driving context is cumbersome and expensive, we propose a virtual testbed for NMPC of driving cars. We use the open source race simulator VDrift as virtual real world, in which algorithms need to cope with the mismatch between the detailed physical model in the simulator and a coarser approximative model used for NMPC. We present the general framework of this virtual environment and an optimal control problem based on a medium-sized ordinary differential equation model and a generic and flexible parameterization of the track constraint. We discuss one possible algorithmic approach to the task of minimum time driving including gear shifts and give preliminary open loop numerical results for a Porsche on Germany's Formula One racing circuit Hockenheimring. This can be used as a reference against which other (closed loop) solutions can be compared in the future.

PARTONIC INTERPRETATION OF GENERALIZED PARTON DISTRIBUTIONS

Dispersion relations have been applied to hard exclusive processes suggesting that generalized parton distributions can be fully determined from their values on a kinematical ridge. We show significant pitfalls associated that vitiate this approach. We suggest an improved treatment of this assumption. Secondly, in order for a partonic interpretation to hold throughout the accessible kinematic region, semi-disconnected diagrams should not contribute. We show, however, that this condition is not satisfied for non-forward kinematics at leading order. Lastly we present our recent flexible parameterization of GPDs and indicate its application to neutral pseudoscalar electroproduction.

Parton distribution uncertainties using smoothness prior

A study of the parameterization uncertainty at low Bjorken x⩽0.1 for the parton distribution functions of the proton is presented. The study is based on the HERA I combined data using a flexible parameterization form based on Chebyshev polynomials with and without an additional regularization constraint. The accuracy of the data allows to determine the gluon density in the kinematic range of 0.0005⩽x⩽0.05 with a small parameterization uncertainty. An additional regularization prior leads to a significantly reduced uncertainty for x⩽0.0005.

Accounting for subgrid scale topographic variations in flood propagation modeling using MODFLOW

To be computationally viable, grid‐based spatially distributed hydrological models of large wetlands or floodplains must be set up using relatively large cells (order of hundreds of meters to kilometers). Computational costs are especially high when considering the numerous model runs or model time steps necessary in calibration and long‐term simulation. To parameterize such models, upscaling procedures are required in furnishing equivalent hydrological model parameters on the grid scale. Here we investigate the effect of a new upscaling technique for hydrological flow parameters dependent upon the small‐scale terrain elevation distribution, namely, resistance to flow, infiltration, and depression storage volume. In the new procedure, these hydrological model parameters on the grid scale become functions of the water table elevation. These functions are established by preparatory, nonrecurring, simulations using the highest available topographic data as input. In this way, the variability and spatial correlation of elevation data on the subscale is preserved on the model scale, at least to some extent. The MODFLOW‐based hydrological model of the Okavango Wetlands is used as a study case. The effectiveness of the new upscaling technique is judged on the basis of comparison of computed flooding patterns with and without implementation of the new technique. It is shown that model results are considerably influenced by this new more flexible parameterization. The partitioning of flows toward the different distributary systems of the Okavango Wetlands is improved by the new technique.

Identification of Groundwater Parameters Using an Adaptative Multiscale Method

The identification of groundwater parameters in heterogeneous systems is a major challenge in groundwater modeling. Flexible parameterization methods are needed to assess the complexity of the spatial distributions of these parameters in real aquifers. In this article, we introduce an adaptative parameterization to identify the distribution of hydraulic conductivity within the large-scale (4400 km(2) ) Upper Rhine aquifer. The method is based on adaptative multiscale triangulation (AMT) coupled with an inverse problem procedure that identifies the parameters' distributions by reducing the error between measured and simulated heads. The AMT method has the advantage of combining both zonation and interpolation approaches. The AMT method uses area-based interpolation rather than an interpolation based on stochastic features. The method is applied to a standard 2D groundwater model that takes into account the interactions between the aquifer and surface water bodies, groundwater recharge, and pumping wells. The simulation period covers 204 months, from January 1986 to December 2002. Recordings at 109 piezometers are used for model calibration. The simulated heads are globally quite accurate and reproduce the main dynamics of the system. The local hydraulic conductivities resulting from the AMT method agree qualitatively with existing local experimental observations across the Rhine aquifer.

Effects of Kinematic Constraints on Teleseismic Finite-Source Rupture Inversions: Great Peruvian Earthquakes of 23 June 2001 and 15 August 2007

Two great underthrusting earthquakes that occurred along the coast of Peru in 2001 and 2007 involve spatiotemporal slip distributions that differ from the predominantly unilateral or bilateral rupture expansion of many great events. Commonly used finite-source rupture model parameterizations, with specified rupture velocity and/or short duration of slip at each grid point applied to the seismic data for these two events, lead to incorrect slip-distributions or inaccurate estimation of rupture velocities as a result of intrinsic kinematic constraints imposed on the model slip distributions. Guided by large aperture array back projections of teleseismic broadband P-wave signals that image slip locations without imposing a priori kinematic constraints on the rupture process, we exploit the availability of large global broadband body and surface wave data sets to consider the effects of varying the kinematic constraints in teleseismic finite-source waveform inversions. By allowing longer than usual rupture durations at each point on the fault using a flexible subfault source-time function parameterization, we find that the anomalous attributes of the 2001 and 2007 Peru earthquake ruptures are readily recognized and accounted for by compound rupture models. The great 23 June 2001 (M_w 8.4 8.4) earthquake involved an initial modest-size event that appears to have triggered a much larger secondary event about 120 km away that developed an overall slip distribution with significant slip located back along the megathrust in the vicinity of the initial rupture. The great 15 August 2007 (M_w 8.0 8.0) earthquake was also a composite event, with a modest size initial rupture followed by a 60-sec delayed larger rupture that initiated 50–60 km away and spread up-dip and bilaterally. When back projections indicate greater rupture complexity than captured in a simple slip-pulse-type rupture model, one should allow for possible long-subfault slip-duration or composite triggered sequences, and not overly constrain the earthquake slip distribution.

Path-Weighted Diffusivity Functions for Parameterization of Heat Deposition Processes

General parameterizations are constructed for spatial modulation of heat diffusion patterns according to energy deposition characteristics occurring within a volume of material where there exist inhomogeneous or anisotropic thermal diffusivity. These parameterizations are formulated in terms of path-weighted diffusivity functions. The construction of a general parameterization of energy deposition processes where spatially dependent thermal diffusivity exists is necessary for their inverse analysis. The structure of such a parameterization follows from the concepts of model and data spaces that imply the existence of an optimal parametric representation for a given class of inverse problems. Accordingly, the optimal parametric representation is determined by the characteristics of the available data, which, in principle, can contain both experimental measurements and numerical simulation data. Parameterizations for spatial modulation of heat diffusion follow from the observation that many different types of energy deposition processes can be represented by weighted sums of basis functions whose general forms are that of spatially modulated diffusion. The parameterizations presented are constructed according to a specific definition of the inverse heat deposition problem that provides a rigorous foundation for a highly flexible and general parameterization of energy deposition processes, which is essential for their inverse analysis.

The composition and structure of volcanic rifted continental margins in the North Atlantic: Further insight from shear waves

Imaging challenges caused by highly attenuative flood basalt sequences have resulted in the understanding of volcanic rifted continental margins lagging behind that of non-volcanic rifted and convergent margins. Massive volcanism occurred during break-up at 70% of the passive margins bordering the Atlantic Ocean, the causes and dynamics of which are still debated. This paper shows results from traveltime tomography of compressional and converted shear wave arrivals recorded on 170 four-component ocean bottom seismometers along two North Atlantic continental margin profiles. This traveltime tomography was performed using two different approaches. The first, a flexible layer-based parameterisation, enables the quality control of traveltime picks and investigation of the crustal structure. The second, with a regularised grid-based parameterisation, requires correction of converted shear wave traveltimes to effective symmetric raypaths and allows exploration of the model space via Monte Carlo analyses. The velocity models indicate high lower-crustal velocities and sharp transitions in both velocity and Vp/Vs ratios across the continent–ocean transition. The velocities are consistent with established mixing trends between felsic continental crust and high magnesium mafic rock on both margins. Interpretation of the high quality seismic reflection profile on the Faroes margin confirms that this mixing is through crustal intrusion. Converted shear wave data also provide constraints on the sub-basalt lithology on the Faroes margin, which is interpreted as a pre-break-up Mesozoic to Paleocene sedimentary system intruded by sills.

Spatial Modulation and Filtering of Diffusion Patterns for Inverse Analysis of Heat Deposition

General parameterizations are constructed for spatial modulation and filtering of heat diffusion patterns according to general energy deposition characteristics occurring within a volume of material resulting from a volumetrically coupled energy source. These parameterizations include previously constructed models of energy deposition as special cases. The construction of a general parameterization of energy deposition processes is necessary for their inverse analysis. The structure of such a parameterization follows from the concepts of model and data spaces that imply the existence of an optimal parametric representation for a given class of inverse problems. Accordingly, the optimal parametric representation is determined by the characteristics of the available data, which in principle can contain both experimental measurements and numerical simulation data. Parameterizations for spatial modulation and filtering of heat diffusion follow from the observation that many different types of energy deposition processes can be represented by weighted sums of basis functions whose general forms are that of spatially modulated or filtered diffusion. A significant aspect of the parameterizations presented is that the definition of the inverse heat deposition problem, which is adopted for their construction, provides a rigorous foundation for a highly flexible and general parameterization of energy deposition processes, which is essential for their inverse analysis. A preliminary proof is presented that shows the significance of these parameterizations for the application of similarity transformations to the inverse analysis of energy deposition processes. The applicability of similarity transforms to the inverse analysis of heat deposition is another property that follows from the specific definition of the inverse heat deposition problem considered here.

Domain-Element Method for Aerodynamic Shape Optimization Applied to Modern Transport Wing

Generic wraparound aerodynamic shape optimization technology is presented and applied to a modern commercial aircraft wing in transonic cruise. The wing geometry is parameterized by a novel domain-element method, which uses efficient global interpolation functions to deform both the surface geometry and corresponding computational fluid dynamics volume mesh. The technique also provides a method that allows geometries to be parameterized at various levels, ranging from global three-dimensional planform alterations to detailed local surface changes. Combining all levels of parameterization allows for free-form design control with very few design variables. The method provides an efficient combined shape parameterization and high-quality mesh deformation technique that is totally independent of mesh type (structured or unstructured). Optimization independence from the flow solver is achieved by obtaining sensitivity information for an advanced gradient-based optimizer by finite differences. The entire optimization suite has also been parallelized to allow optimization with highly flexible parameterization in practical times. Results are presented for highly constrained optimizations of the modern aircraft wing in transonic cruise, using three levels of parameterization (number of design variables) to assess the effect of parameterization level on the optimization. The highest-level optimization results in a totally-shock-free geometry with an associated substantial reduction in drag.

The Hypergeometric Process: A Flexible Parameterization of the Moving Average Process Time Series

We introduce an apparently new parameterisation of the Wold decomposition of a standard Box-Jenkins time series model in terms of the Hypergeometric Function pFq(.). This parameterization is sufficiently flexible to treat both finite standard ARMA(p, q) models and also fractionally integrated models such as FI(d). We demonstrate the parametric domain over which the process is variance stationary and also over which it is ergodic. We compute the autocovariance function for the general process and illustrate how the parameterization proposed here may be used to model other well known parameterizations of the MA(q) process.

A Simple Parameterization for Detrainment in Shallow Cumulus

Abstract For a wide range of shallow cumulus convection cases, large-eddy simulation (LES) model results have been used to investigate lateral mixing as expressed by the fractional entrainment and fractional detrainment rates. It appears that the fractional entrainment rates show much less variation from hour to hour and case to case than the fractional detrainment rates. Therefore, in the parameterization proposed here, the fractional entrainment rates are assumed to be described as a fixed function of height, roughly following the LES results. Based on the LES results a new, more flexible parameterization for the detrainment process is developed that contains two important dependencies. First, based on cloud ensemble principles it can be understood that deeper cloud layers call for smaller detrainment rates. All current mass flux schemes ignore this cloud-height dependence, which evidently leads to large discrepancies with observed mass flux profiles. The new detrainment formulation deals with this dependence by considering the mass flux profile in a nondimensionalized way. Second, both relative humidity of the environmental air and the buoyancy excess of the updraft influence the detrainment rates and, therefore, the mass flux profiles. This influence can be taken into account by borrowing a parameter from the buoyancy-sorting concept and using it in a bulk sense. LES results show that with this bulk parameter, the effect of environmental conditions on the fractional detrainment rate can be accurately described. A simple, practical but flexible parameterization for the fractional detrainment rate is derived and evaluated in a single-column model (SCM) for three different shallow cumulus cases, which shows the clear potential of this parameterization. The proposed parameterization is an attractive and more robust alternative for existing, more complex, buoyancy-sorting-based mixing schemes, and can be easily incorporated in current mass flux schemes.

Spectrum matching method for estimating the chlorophyll-a concentration, CDOM ratio, and backscatter fraction from remote sensing of ocean color

Light emerging from the sea surface carries information about the water constituents, which also includes contributions from inelastic processes, such as Raman scattering, chlorophyll fluorescence, and colored dissolved organic matter (CDOM) fluorescence. The inclusion of inelastic processes, however, has not been fully considered in most of the existing ocean color algorithms. This research presents an approach to substantially decrease the computation time of the nonlinear optimization approach using a look-up table (LUT) to correct for the effects of inelastic scattering. A series of sensitivity tests was conducted to determine the factors required to accurately simulate remote sensing reflectance. Our results show that the inherent optical properties (IOPs) and inelastic scattering play a significant role, whereas the role played by variations of the ambient optical environment and surface wind speed is negligible. An LUT was derived from 22 575 forward simulations using the Hydrolight radiative transfer model. A flexible parameterization of IOPs was formulated by considering all processes of inelastic scattering and a set of three-variable (chlorophyll-a concentration, CDOM ratio, and backscattering fraction) biooptical models. The set of models can be applied to case 1 waters and case 2 waters that happen to be gelbstoff rich, and the volume-scattering phase function can be generated dynamically based on the backscatter fraction. This research may provide a new approach of inversion for including inelastic processes in developing ocean color algorithms.