Individual Uncertainty Research Articles

The User-Preferred Optimal Flight Parameters in an Active Navigational System in a Multi-Alternative Situation

Abstract The goal of this paper is to investigate the influence of the objectively existing effectiveness functions of an aircraft control system upon the control and managerial decision making process in the framework of the subjective entropy maximum princi-ple. The subjective analysis theory entropy paradigm makes it possible to consider the aircraft control system based upon personal preferences as an active system governed by an individual (active element of the control system) with the help of her/his individual subjective preferences optimal distributions obtained in conditions of operational multi-alternativeness and those operational alternatives the active system active element’s individual subjective preferences uncertainty. The described ap-proach takes into account the simple two-alternative operational situation in regards with the objectively existing effectiveness functions, related to the aircraft control system, in the view of a controlled parameter and a combination of it with its rate as the ratio. The obtained expressions for the objective functional extremal functions of the effectiveness and preferences, as well as the subjective entropy of the alternatives preferences, illustrated in diagrams visualize the situation and allow taking a good choice. The ideas of the required proper governing, managing, and control methods choice optimization with respect to only 2 alternative objective effectiveness functions arguments might be simple; nevertheless, increasing the number of parameters and further complication of the problem setting will not change the principle of the problem solution.

Comparative analysis of water budgets across the U.S. long-term agroecosystem research network

Understanding the movement and storage of water within agricultural landscapes as functions of management and climate is essential for more efficient and sustainable water use. However, knowledge of water storage and fluxes on U.S. agricultural lands is largely incomplete. The Long-Term Agroecosystem Research (LTAR) network provides a unique and geographically diverse set of agricultural study sites in the United States. The objectives of this study were to: 1) characterize the hydrologic variability across the LTAR network; 2) identify data gaps in the water budgets across the LTAR network; and 3) identify opportunities to leverage the LTAR network to improve understanding of water budgets across agricultural landscapes. For each of the 18 LTAR sites, we developed water budgets on an average annual basis. Uncertainty propagation methods combined individual component uncertainties to calculate an overall water budget uncertainty. Datasets length ranged from three to 50 years. The network covers a range of precipitation from 240 to 1400 mm yr−1, evapotranspiration from 228 to 1080 mm yr−1, and surface runoff and subsurface flow from negligible to 560 mm yr−1. However, uncertainties of where all the water is going remained high, in part because soil water storage and downward movement of water were often neglected or measured for very short periods, resulting in average water budget uncertainty of 25% of the water inputs. More accurate measurement of the major inputs and outputs, and direct measurement of water content and percolation are key to understanding how agricultural lands affect terrestrial water budgets.

To Wait or Not to Wait? Use of the Flexibility to Postpone Investment Decisions in Theory and in Practice

Business sustainability and real options are closely connected, as real options are managerial flexibility that allows organizations to adapt to changes in their environment, thus making the organization more robust and economically sustainable. Studies in real options theory abound, yet there is still a lack of evidence on whether people make decisions consistently with the predictions made by real options models. We run a laboratory experiment to study the role of option value and the laboratory time required to resolve uncertainty in individuals’ decision to price and adopt an option to wait. Specifically, we compare decision makers’ choices in two investment scenarios: One with a short time to maturity (implying a low option value), and another with a longer time to maturity (implying a high option value). In the lab, both scenarios are implemented with the waiting time of twenty and sixty minutes. Our results show that decision makers deviate from the theoretical predictions, recognizing the benefit of waiting, when the value of the option is higher, or when the waiting time is shorter. Our study does not only bring more insights into real options adoption at the individual level, but also emphasizes the great potential of behavioral and experimental approach to bridge the gap between theory and practice in the real options literature.

REDISTRIBUTION AND FISCAL UNCERTAINTY SHOCKS

AbstractThis article studies the impact of fiscal uncertainty shocks. In micro data, noncapital holders reduce consumption persistently in response to an increase in fiscal uncertainty whereas capital holders do not. Motivated by this evidence, I introduce limited capital market participation and show that it magnifies the fall in economic activity due to a fiscal uncertainty shock and induces macroeconomic comovement. This is because the limited participation model captures individual uncertainty about redistribution. When agents are ambiguity averse, this uncertainty about redistribution has first‐order effects. As a result, the model successfully matches the empirical responses of macro and household variables.

Water Markets, Water Courts, and Transaction Costs in Colorado

AbstractWater markets increasingly facilitate adaptation to water scarcity, but transaction costs can be barriers to expanded water marketing, particularly under water rights law in the western United States. However, transaction costs are rarely measured, and existing research commonly overlooks how transaction costs differ across individual water transfers and uncertainty in those costs. We collected hundreds of estimates of procedural transaction costs—costs incurred by transfer proponents for legal and hydrologic experts—by surveying 100 water professionals in the state of Colorado. There, water markets are among the most active in the United States, convey perhaps the most clearly defined private property rights of any state, and, unique to Colorado, require approval from specialized water courts. We elicited costs for water transfers with differing physical and legal characteristics, and we elicited separate assessments of (i) probabilities of legal outcomes for water transfers and (ii) transaction costs conditional on those outcomes. Then, we estimated expected transaction costs with a statistical model that combines (i) with (ii). The model reveals systematic differences in transaction costs, with scale economies and higher transaction costs for water‐scarce regions, senior water rights, and higher‐conflict legal outcomes. It also shows substantial transaction cost uncertainty, which itself can discourage trading. Our novel survey and estimation procedure develops a replicable approach for measuring transaction cost heterogeneity and uncertainty. Additionally, qualitative survey data we collected indicate transaction costs have increased over time due to growing competition for scarce water and that, despite high transaction costs, specialized water courts offer unique benefits.

Delayed Crises and Slow Recoveries

We present a rational expectations model of credit-driven crises, providing a new perspective to explain why credit booms can lead to severe financial crises and aftermath slow economic recoveries. In our model economy, banks can operate in two types of business a la Minsky's narratives. They are sequentially aware of the deterioration of fundamentals of the speculative business and decide whether to continue credit extension in that business or liquidate capital and move into the traditional business. However, because individual banks face uncertainty about how many of their peers have been aware, they rationally choose to extend credit in the speculative business for a longer time than is socially optimal, leading to an over-delayed crisis and consequently more banks being caught by the crisis. This in turn renders the financial crisis more severe and the subsequent economic recovery slower. Within a standard textbook macroeconomic growth setting, our model generates rich dynamics of economic booms, slowdowns, crashes, and recoveries.

OpenDose: Open-Access Resource for Nuclear Medicine Dosimetry.

Radiopharmaceutical dosimetry depends on the localization in space and time of radioactive sources and requires the estimation of the amount of energy emitted by the sources deposited within targets. In particular, when computing resources are not accessible, this task can be performed using precomputed tables of specific absorbed fractions (SAFs) or S values based on dosimetric models. The aim of the OpenDose collaboration is to generate and make freely available a range of dosimetric data and tools. Methods: OpenDose brings together resources and expertise from 18 international teams to produce and compare traceable dosimetric data using 6 of the most popular Monte Carlo codes in radiation transport (EGSnrc/EGS++, FLUKA, GATE, Geant4, MCNP/MCNPX, and PENELOPE). SAFs are uploaded, together with their associated statistical uncertainties, in a relational database. S values are then calculated from monoenergetic SAFs on the basis of the radioisotope decay data presented in International Commission on Radiological Protection Publication 107. Results: The OpenDose collaboration produced SAFs for all source region and target combinations of the 2 International Commission on Radiological Protection Publication 110 adult reference models. SAFs computed from the different Monte Carlo codes were in good agreement at all energies, with SDs below individual statistical uncertainties. Calculated S values were in good agreement with OLINDA/EXM 2.0 (commercial) and IDAC-Dose 2.1 (free) software. A dedicated website (www.opendose.org) has been developed to provide easy and open access to all data. Conclusion: The OpenDose website allows the display and downloading of SAFs and the corresponding S values for 1,252 radionuclides. The OpenDose collaboration, open to new research teams, will extend data production to other dosimetric models and implement new free features, such as online dosimetric tools and patient-specific absorbed dose calculation software, together with educational resources.

The Hubble Space Telescope UV Legacy Survey of Galactic Globular Clusters. XX. Ages of Single and Multiple Stellar Populations in Seven Bulge Globular Clusters

Abstract In the present work we analyzed seven globular clusters (GCs) selected from their location in the Galactic bulge and with metallicity values in the range −1.30 ≲ [Fe/H] ≲ −0.50. The aim of this work is first to derive cluster ages assuming single stellar populations and second to identify the stars from first (1G) and second generations (2G) from the main sequence, subgiant, and red giant branches, and to derive their age differences. Based on a combination of UV and optical filters used in this project, we apply the Gaussian mixture models to distinguish the multiple stellar populations. Applying statistical isochrone fitting, we derive self-consistent ages, distances, metallicities, and reddening values for the sample clusters. An average age of 12.3 ± 0.4 Gyr was obtained both using DSED and BaSTI (accounting atomic diffusion effects) isochrones, without a clear distinction between the moderately metal-poor and the more metal-rich bulge clusters, except for NGC 6717 and the inner halo NGC 6362 with ∼13.5 Gyr. We derived a weighted mean age difference between the multiple populations hosted by each GC of 41 ± 170 Myr adopting canonical He abundances; whereas for higher He in 2G stars, this difference reduces to 17 ± 170 Myr, but with individual uncertainties of 500 Myr.

Monte Carlo–Based Quantification of Uncertainties in Determining Ocean Remote Sensing Reflectance from Underwater Fixed-Depth Radiometry Measurements

AbstractA new framework that enables evaluation of the in situ ocean color radiometry measurement uncertainty is presented. The study was conducted on the multispectral data from a permanent mooring deployed in clear open ocean water. The uncertainty is evaluated for each component of the measurement equation and data processing step that leads to deriving the remote sensing reflectance. The Monte Carlo method was selected to handle the data complexity such as correlation and nonlinearity in an efficient manner. The results are presented for a prescreened dataset that is suitable for system vicarious calibration applications. The framework provides uncertainty value per measurement taking into consideration environmental conditions present during acquisition. A summary value is calculated from the statistics of the individual uncertainties per each spectral channel. This summary value is below 4% (k = 1) for the blue and green spectral range. For the red spectral channels, the summary uncertainty value increases to approximately 5%. The presented method helps to understand the significance of various uncertainty components and to provide a way of identifying major contributors. This can be used for efficient system performance improvement in the future.

Atypical processing of uncertainty in individuals at risk for psychosis.

Current theories of psychosis highlight the role of abnormal learning signals, i.e., prediction errors (PEs) and uncertainty, in the formation of delusional beliefs. We employed computational analyses of behaviour and functional magnetic resonance imaging (fMRI) to examine whether such abnormalities are evident in clinical high risk (CHR) individuals. Non-medicated CHR individuals (n=13) and control participants (n=13) performed a probabilistic learning paradigm during fMRI data acquisition. We used a hierarchical Bayesian model to infer subject-specific computations from behaviour - with a focus on PEs and uncertainty (or its inverse, precision) at different levels, including environmental 'volatility' - and used these computational quantities for analyses of fMRI data. Computational modelling of CHR individuals' behaviour indicated volatility estimates converged to significantly higher levels than in controls. Model-based fMRI demonstrated increased activity in prefrontal and insular regions of CHR individuals in response to precision-weighted low-level outcome PEs, while activations of prefrontal, orbitofrontal and anterior insula cortex by higher-level PEs (that serve to update volatility estimates) were reduced. Additionally, prefrontal cortical activity in response to outcome PEs in CHR was negatively associated with clinical measures of global functioning. Our results suggest a multi-faceted learning abnormality in CHR individuals under conditions of environmental uncertainty, comprising higher levels of volatility estimates combined with reduced cortical activation, and abnormally high activations in prefrontal and insular areas by precision-weighted outcome PEs. This atypical representation of high- and low-level learning signals might reflect a predisposition to delusion formation.

Machine Learning-Based Modeling for the Duration of Load Effect in Wood Structural Members Under Long-Term Sustained Load

The load resisting capacity of structural members will decrease when they are subjected to long-term sustained load. Such phenomenon is widely known as the duration of load effect, which is mainly caused by the damage accumulation in the material. The deterioration mechanism of the material is a typical stochastic process which is influenced by a large variety of parameters involving complex physical and chemical process. Although classical models have been proposed to evaluate the duration of load effect, it is nearly impossible to quantify the influence of various parameters and to achieve an accurate estimation. To optimize the combination of complexity and goodness-of-fit, a neural network model is proposed in this paper to evaluate the duration of load effect in wood structural members. Taking individual uncertainties into consideration, the proposed model treats the damage in wood as a Markov process and can estimate the residual strength distribution of the investigated wood structural members under long-term sustained load. The coefficient of determination reaches above 95% under sustained loading scenario, and it shows good adaptability across different wood properties. Moreover, the model can be adapted to continuously varied loading scenarios with a 98% coefficient of determination. This research aims to provide a useful and straightforward tool for accurately predicting the duration of load effect in wood structural members, and the proposed algorithm can be easily modified to deal with similar engineering problems for other construction materials.

An Uncertainty Quantification and Aggregation Framework for System Performance Assessment in Industrial Maintenance

The exponential increase in technological complexity of modern engineering systems necessitates rigorous and accurate maintenance planning to determine optimum equipment availability and turnaround time whilst allowing for overruns and unforeseen costs. Quality and availability of quantitative data, as well as qualitative expert opinion and experience expose uncertainties that can result in under or over estimation of the above factors. Uncertainty quantification in complex engineering systems should consider inter-connected components and associated processes from a combination of quantitative and qualitative (compound) perspectives. This paper presents a framework to quantify and aggregate compound uncertainties and to be assessed against a predetermined acceptable level of uncertainty. This will provide maintenance planners with a confident, comprehensive view of parameters surrounding the above factors to improve decision making capabilities. The framework was validated by assessing individual and compound uncertainties in a bespoke heat exchanger test rig comprised of subsystem modules interact in a non-linear manner, as well as subjective opinions and actions of operators. The results demonstrate the framework’s ability to effectively quantify these factors with an indication of their impact on the system. Future work will include further validation with more complex case studies and development of methods to forecast the quantified uncertainty through the in-service phase of an asset’s life cycle.

CCT Supplementary comparison S2 on thermal conductivity measurements of insulating materials by guarded hot plate

Seven National Metrology Institutes (NMIs) from France, United States, United Kingdom, Russia, Mexico, China and Germany participated in an inter-laboratory comparison on thermal conductivity measurements by the Guarded Hot Plate method. This action was part of a series of supplementary inter-laboratory comparisons (including infrared spectral emittance and thermal diffusivity) sponsored by the Consultative Committee on Thermometry (CCT) Task Group on Thermophysical Quantities (TG-ThQ). The objective of this collaborative work was to strengthen the consistency of thermal conductivity measurements carried out worldwide on low conductive materials. Measurements were conducted successively by all participants on the same sets of specimens of insulating materials (mineral wool and expanded polystyrene) at temperatures ranging from 10 °C to 40 °C, according to the International Standard ISO 8302. This protocol aimed to minimize issues of material variability by circulating the same pairs of specimens among the laboratories following the strict format of a round-robin test program. More than 120 data points (combinations of material, thickness and temperature) were compared. Ninety-two percent (92 %) of the data points were in agreement, with differences to weighted mean values less than the expanded uncertainties calculated from the individual NMI uncertainties and uncertainties related to the comparison process.Main textTo reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/.The final report has been peer-reviewed and approved for publication by the CCT, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Stability Analysis of Multivariable Digital Control Systems with Uncertain Timing

The ever increasing complexity of real-time control systems results in significant deviations in the timing of sensing and actuation, which may lead to degraded performance or even instability. In this paper we present a method to analyze stability under mostly-periodic timing with bounded uncertainty, a timing model typical for the implementation of controllers that were actually designed for strictly periodic execution. In contrast to existing work, we include the case of multiple sensors and actuators with individual timing uncertainty. Our approach is based on the discretization of a linear impulsive system. To avoid the curse of dimensionality, we apply a decomposition that breaks down the complex timing dependency into the effects of individual sensor-actuator pairs. Finally, we verify stability by norm bounding and a Common Quadratic Lyapunov Function. Experimental results substantiate the effectiveness of our approach for moderately complex systems.

Equilibrium Selection via Optimal Transport

We propose a new dynamics for equilibrium selection of finite player discrete strategy games. The dynamics is motivated by optimal transportation, and models individual players' myopicity, greedy and uncertainty when making decisions. The stationary measure of the dynamics provides each pure Nash equilibrium a probability by which it is ranked. For potential games, its dynamical properties are characterized by entropy and Fisher information.

Uncertainties in retrieving microphysical properties of rain profiles using ground‐based dual‐frequency radar

AbstractDual‐frequency radar (DFR) could improve the accuracy of estimating the microphysical properties of rain profiles. Unfortunately, factors that cause inaccuracies in retrieved rain profiles include uncertainties in raindrop size distribution (DSD) parameterizations, DFR retrieval methods and radar measurement errors. The primary objective of this study was to assess the uncertainties in retrieving rain profiles to offer insight into application considerations for ground‐based DFRs in China. The uncertainties caused by DSD models are assessed by comparing attenuation coefficients and rain rates from DFR algorithms with those directly derived from DSD spectra from disdrometers. Then, based on a DSD model, the impacts of retrieval methods, radar range resolution, measurement error and errors in temperature on DFR retrievals are explored by comparing the rain profiles obtained using DFR algorithms with those directly output from the Weather Research and Forecasting model. Overall, the impact of measurement error on the DFR retrievals is relatively significant for both the forward retrieval method and the iterative backward retrieval method and should be eliminated in practical applications. At an individual uncertainty level, the impact of DSD parameterizations on the retrievals from the dual‐frequency technique is less than ±10% bias when the shape factor μ of the gamma distribution ranges from 2 to 4. The retrieved rain profiles from the forward retrieval method are relatively sensitive to radar range resolution and the retrieval performance can be improved with increasing the range resolution, while the iterative backward retrieval method exhibits stable retrieval performance. The impact of temperature errors on the retrieved rain profiles is negligible.

Technical note: Uncertainty in multi-source partitioning using large tracer data sets

Abstract. The availability of large tracer data sets opened up the opportunity to investigate multiple source contributions to a mixture. However, the source contributions may be uncertain and, apart from Bayesian approaches, to date there are only solid methods to estimate such uncertainties for two and three sources. We introduce an alternative uncertainty estimation method for four sources based on multiple tracers as input data. Taylor series approximation is used to solve the set of linear mass balance equations. We illustrate the method to compute individual uncertainties in the calculation of source contributions to a mixture, with an example from hydrology, using a 14-tracer set from water sources and streamflow from a tropical, high-elevation catchment. Moreover, this method has the potential to be generalized to any number of tracers across a range of disciplines.

Uncertanity of Measurement During Estimation of 23 Organophosphorus Pesticides Residue Present in Bottle Gourd

46The study presents the assessment of uncertainty calculation generated, within the analysis of selected 23 organophosphrus pesticides residues of bottle guard. The samples were prepared by using a modified quick, easy, cheap, effective, rugged and safe (QuEChERS) analytical protocol. Multiresidue method used for analysis of samples consisted of (i) acetonitrile extraction, (ii) PSA/C18 clean-up and (iii) identification/quantification of residues by GC utilizing either (nitrogen–phosphorus) or mass-selective detectors (quadrupole analyzer) were evaluated. Major sources like weighing of standard, purity of certified reference material, precision study i.e repeatability and standard solution preparation for calculation of uncertainty of method, was considered. Identification of uncertainty sources, quantification of uncertainty sources and calculation of combined uncertainty are steps for calculation of uncertainty. All the individual uncertainty calculated are combined, later converted to expanded uncertainty.

Flow through calorimeter to measure fluid heat capacity in CSP applications

Performance tests of concentrating solar collectors are based on energy balance studies which require accurate measurements of fluid mass flow rate, temperature difference over the collector length and the knowledge of the specific heat capacity of the used heat transfer fluid (HTF). Especially at operation temperatures in the range of 200–400 °C, the accuracy of HTF manufacturer data regarding the specific heat capacity of used HTFs is insufficient. This shortcoming contributes significantly to the overall measurement uncertainty of thermal collector assessments. In the present paper, the measurement results of a flow through calorimeter measuring the specific heat capacity of SYLTHERM 800 under field conditions at temperatures up to 330 °C are presented. The HTF measurement shows good agreement (deviation below 1.2%) with a Differential Scanning Calorimetry (DSC) measurement for temperatures below 270 °C. For higher temperatures, the deviation between flow through calorimeter and DSC measurement increases to 3.7% at 330 °C. Furthermore, several technical design and measurement improvements over the calorimeter design presented in 2012 are described in detail. A validation measurement using water reveals deviations below 0.1% from the water reference values at ambient temperatures. A stringent uncertainty analysis reveals the largest individual measurement uncertainty. The unexpectedly large uncertainty of the Coriolis mass flow sensors at temperatures above 270 °C is distinguished by a large individual uncertainty and the comparison to DSC.

Remedial discretion and dilemmas in Asia

Asian courts have mitigated the individual harms and institutional uncertainties associated with the judicial use of delayed remedies by incentivizing the government to comply with the court’s ruling or putting in place judicial safeguards against any legislative delinquency. Expedited remedies like remedial reinterpretation and judicial directives in certain contexts may also be necessary or desirable, even if the judicially imposed result may not be what the enacting legislature had originally intended. Insofar as the legislature can respond and amend these judicial reinterpretation or directives by ordinary legislation, the judiciary does not have the final word and has merely facilitated a constitutional dialogue on rights with the current legislature.