Actual Uncertainty Research Articles

An integrated analysis of port and coal storage development plan in a mining company with a simulation approach

Managing inbound logistics activities requires an integrated and comprehensive perspective to understand the operations complexity that affects inbound performance. This study proposes an integrated analysis in port and coal storage development plan in a mining company. The main goal of the analysis is creating a cost-effective plan. A discrete event simulation (DES) approach is used to model the complexity, and the model is applied to analyse the number of barge slip, port loading and unloading equipment, the number and the type of material transport equipment. It also analyses how storage capacity can achieve particular service levels. The model considers the actual restriction and uncertainties, such as tidal time, barge sailing and berthing time, loading and unloading time, material transportation time, availability of barge slip, material transportation, loading and unloading equipment. The simulation using 2020 data as the baseline of demand and 2027 data as the highest demand until 2030, this demand led to high queues at barge slip, making stockpile capacity insufficient, and high utility on trucks followed by long queues. Based on the simulation results, increasing the number of resources can be able to solve the overcome problems.

Topographic effects observed at Amatrice hill during the 2016–2017 Central Italy seismic sequence

The estimate of seismic site effects by experimental approaches is based on different assumptions aimed at simplifying the complex actual site conditions and related uncertainties. However, the reliability of the results can increase if the experimental data is focused on quite strong seismic sequences and the on-site acquisition of a large number of signals is deemed strategic for the assessment of the expected phenomena. Based on these considerations, the ground motion at the Red Zone sector of Amatrice hill, violently struck by the 2016–2017 Central Italy seismic sequence, was analyzed via an observational approach. A large set of weak motions (moment magnitudeMw 2.5–3.9) was analyzed in this study by means of standard (SSR) and horizontal to vertical (HVSR) spectral ratio techniques. The results from the experimental analysis of the site effects by using weak motion and noise signals show a significant amplification at the top of Amatrice hill with a remarkable polarization of the motion and changes in spectral shapes according to the topographic setting of the relief.

An online survey of the impact of examination cancellations amid the COVID-19 Pandemic: A perspective

The scrapping of board exams by the Indian government is a watershed moment in the country's educational history. An online survey was performed to determine the impact of the decision on students' lives. COVID-19 has caused mayhem in the world's educational institutions, affecting over 1.6 billion pupils in over 200 nations.School, institutional, and other learning facility closures have impacted more than 94 percent of the world's student population. As a result, substantial changes have occurred in every aspect of our lives. Social alienation and movement restrictions have wreaked havoc on traditional teaching practices. To discover more about the effects of the epidemic on students' lives, we surveyed 130 students aged 15 to 18, their teachers, and their parents from several educational establishments in Rajasthan, India. In addition, the study looked at how students of all ages used social networking platforms. Government officials should take all necessary steps, according to the findings, to improve the educational experience by reducing the harmful effects of the COVID-19 outbreak. Through the survey, we learned about the actual conflict and uncertainty that exists among individuals regarding the cancellation of the examination, where some believe it was a good decision taken by the government while others believe it would have an impact on the future education system. According to our findings, people genuinely need this exam to be done with sufficient protection and vaccinations for students, so that kids can have equitable and fair possibilities for their futures and the nation can find better human resources for quicker GDP growth. There are concerns that the academic year of 2021, as well as the succeeding years, may be lost. Alternative educational systems and assessment methodologies must be created and deployed as soon as possible. The outbreak of COVID-19 has provided us with an opportunity to create the foundation for digital learning. The goal of this study is to provide a detailed analysis of the influence of the COVID-19 epidemic on exam cancellations.

Investigating the Uncertainties Propagation Analysis of CO2 Emissions Gridded Maps at the Urban Scale: A Case Study of Jinjiang City, China

Gridded CO2 emission maps at the urban scale can aid the design of low-carbon development strategies. However, the large uncertainties associated with such maps increase policy-related risks. Therefore, an investigation of the uncertainties in gridded maps at the urban scale is essential. This study proposed an analytic workflow to assess uncertainty propagation during the gridding process. Gridded CO2 emission maps were produced using two resolutions of geospatial datasets (e.g., remote sensing satellite-derived products) for Jinjiang City, China, and a workflow was applied to analyze uncertainties. The workflow involved four submodules that can be used to evaluate the uncertainties of CO2 emissions in gridded maps, caused by the gridded model and input. Fine-resolution (30 m) maps have a larger spatial variation in CO2 emissions, which gives the fine-resolution maps a higher degree of uncertainty propagation. Furthermore, the uncertainties of gridded CO2 emission maps, caused by inserting a random error into spatial proxies, were found to decrease after the gridding process. This can be explained by the “compensation of error” phenomenon, which may be attributed to the cancellation of the overestimated and underestimated values among the different sectors at the same grid. This indicates a nonlinear change between the sum of the uncertainties for different sectors and the actual uncertainties in the gridded maps. In conclusion, the present workflow determined uncertainties were caused by the gridded model and input. These results may aid decision-makers in establishing emission reduction targets, and in developing both low-carbon cities and community policies.

On the validation of a priori estimates of standard displacement uncertainties in T3-stereocorrelation

Uncertainty quantification is crucial for any measurement technique. The present work aims at validating a priori estimates of displacement uncertainties. Images acquired prior to fourteen thermomechanical tests were analyzed via FE-based stereocorrelation to determine actual displacement uncertainties, which were compared to a priori estimates. For the studied experimental database, a very good agreement was observed between a priori and a posteriori estimates of standard displacement uncertainties.

Real-Time Hybrid Test Using Two-Individual Actuators to Evaluate Seismic Performance of RC Frame Model Controlled by AMD

Seismic responses of a single-story RC frame building model under control using an active mass damper (AMD) are demonstrated through a real-time hybrid simulation (RTHS) method. In this study, the RTHS test is carried out by using a hydraulic actuator and a shaking table under a synchronization. Most parts of the target RC frame model are provided as an analytical model for an online computer simulation, and the only single column of the first story is prepared as an experimental substructure. A hydraulic actuator deforms the actual RC column, and uncertainty or nonlinearity of the RC column’s behavior is focused on this RTHS test. At the same time, a control device of AMD is actually tested under a situation of installing it on the target building's floor. The floor response of the target building model is generated using a shaking table. A control motion of the AMD is manipulated based on an online simulation of the entire RC building model. Firstly, a time delay compensation of the hydraulic actuator is considered. Time delay parameters are identified using a combination model of a time lag and a first-order delay. A PID controller and a time series compensator (TSC) are applied to improve actuator performances. Next, the reproducibility of the RTHS test using two-individual actuators is evaluated. The tracking of a restoring force and deformation of the actual RC column specimen generated by the hydraulic actuator and floor motion responses reproduced on the shaking table are investigated. To improve the online numerical simulation based on the measured force responses of the RC column specimen, a high-pass filter (HPF) is applied for a force correction to utilize its phase-lead property. The effect of this HPF force correction is evaluated in both a linear region and a strong nonlinear region of the actual RC column specimen. Finally, the RTHS test results are compared to fully-numerical simulations, and the control effect of the AMD to increase the damping effect for the target RC building model is also investigated.

Презумпція правомірності рішень платника податків у практиці адміністративних судів

Статтю присвячено детальному аналізу правової природи презумпції правомірності рішень платника податків як одного з вихідних положень податкового законодавства, змістовні аспекти якого розвивалися в межах судової практики. Так, автором було сконцентровано увагу на специфічних рисах презумпції правомірності рішень платників податків. Відповідні риси встановлюються на основі дослідження, серед іншого, практики Європейського суду з прав людини та Європейської комісії за демократію через право (Венеціанська комісія). Як дослідницьке завдання автором визначено специфіку взаємозв'язків судової доктрини презумпції правомірності рішень платника податків з іншими судовими доктринами, а саме: доктриною ділової мети, доктриною добросовісності платника податків тощо. Проведено розмежування судової доктрини презумпції правомірності рішень платника податків від доктрини добросовісності платника податків. Зазначено, що презумпція правомірності рішень покликана забезпечити правову визначеність у податковому правозастосуванні, саме тоді, коли закон передбачає неоднозначне трактування прав і обов'язків учасників податкових відносин. У статті проаналізовано актуальну судову практику, у рамках якої сформовано основні концептуальні вимоги даного презумптивного положення податкового законодавства. Встановлено, що суди розглядають презумпцію правомірності рішень платника податків як спеціальне правило, яке встановлює вимогу, відповідно до якої суб'єкти правозастосування повинні трактувати всі нормативно обумовлені сумніви на користь платника податків. Підкреслюється, що саме презумпція правомірності рішень перебуває в нерозривній єдності з вимогами принципу правової визначеності. Сам принцип правової визначеності є елементом принципу верховенства права. Саме дане вихідне положення забезпечує прогно-зованість правозастосовної практики. Принцип-пре-зумпція правомірності рішення платника податків є специфічним інструментом (техніко-юридичний прийом), який дозволяє забезпечити реалізацію інтересів платника податків у разі фактичної невизначеності алгоритмів правозастосування.

Evaluation of UV aerosol retrievals from an ozone lidar

Abstract. Aerosol retrieval using ozone lidars in the ultraviolet spectral region is challenging but necessary for correcting aerosol interference in ozone retrieval and for studying the ozone–aerosol correlations. This study describes the aerosol retrieval algorithm for a tropospheric ozone lidar, quantifies the retrieval error budget, and intercompares the aerosol retrieval products at 299 nm with those at 532 nm from a high spectral resolution lidar (HSRL) and with those at 340 nm from an AErosol RObotic NETwork radiometer. After the cloud-contaminated data are filtered out, the aerosol backscatter or extinction coefficients at 30 m and 10 min resolutions retrieved by the ozone lidar are highly correlated with the HSRL products, with a coefficient of 0.95 suggesting that the ozone lidar can reliably measure aerosol structures with high spatiotemporal resolution when the signal-to-noise ratio is sufficient. The actual uncertainties of the aerosol retrieval from the ozone lidar generally agree with our theoretical analysis. The backscatter color ratio (backscatter-related exponent of wavelength dependence) linking the coincident data measured by the two instruments at 299 and 532 nm is 1.34±0.11, while the Ångström (extinction-related) exponent is 1.49±0.16 for a mixture of urban and fire smoke aerosols within the troposphere above Huntsville, AL, USA.

Polymorphic uncertainty in met-ocean conditions and the influence on fatigue loads

An accurate numerical simulation of the structural lifetime of offshore wind turbines is a challenging task due to several reasons. One of them is the uncertainty of met-ocean conditions acting on a turbine, e.g. wind and waves. This uncertainty can be divided into two kinds of uncertainty: aleatory and epistemic uncertainty. If both types of uncertainty occur, this is called polymorphic uncertainty. According to the state of the art, for met-ocean conditions, mainly aleatory uncertainty is considered or both types of uncertainty are modelled using a single probability density function. This leads to a simplification of the actual uncertainty, whose effect on the lifetime estimation has not been analysed so far. In that sense, in this work, the influence of various uncertainty models for met-ocean conditions on long-term damage equivalent loads (DELs) - representing the wind turbine fatigue lifetime - is investigated. For this purpose, different uncertainty models for met-ocean conditions are derived using real measurement data. Not only purely probabilistic models are applied, but imprecise probabilities - here interval random variables - as well. It is shown that the uncertainty models have a considerable influence on the fatigue life of offshore wind turbines. Especially, the large fatigue load intervals, which are determined, clarify the importance of a well-founded decisions regarding uncertainty modelling of met-ocean conditions.

Embodied carbon in construction materials: a framework for quantifying data quality in EPDs

Embodied carbon constitutes a significant portion of a building’s greenhouse gas (GHG) emissions and is a key challenge for the construction and real estate sectors. Embodied carbon includes construction product manufacturing, building construction, material replacement and end of life. During the specification and procurement stage, designers and contractors have the opportunity to prioritize products with lower carbon footprints. Environmental product declarations (EPDs) are a growing source of environmental data in the construction products market, and are increasingly being used for (1) environmental performance assessment of buildings and (2) product comparison for procurement decisions during the later stages of building design. An obstacle to identifying and purchasing lower embodied carbon products is a lack of data quality and the transparency of EPDs. However, EPDs vary widely in their data quality and specificity, which can lead to inaccurate and misleading comparisons. A new method is presented to account quantitatively for estimates of variation in underlying data specificity in EPDs to enable fairer comparisons between EPDs and to motivate the reporting of actual variability and uncertainty in EPDs. The application of this approach can help purchasers to assess EPDs quantitatively. Practice relevance Life-cycle assessments (LCAs) and LCA data can be used within the construction sector to evaluate buildings and to assist in design, specification and procurement decision-making. A new method is presented to support the assessment of comparability of functionally equivalent materials and products during the specification and procurement stage. Given the known variation and lack of precision within EPDs, this method provides quantitative metrics that correlate to a qualitative interpretation of EPD precision. This method can be used by anyone who is using EPD data to make product comparisons at the specification and procurement stage: It provides more confidence in choosing low-carbon material or product options when comparing between functionally equivalent options. It can incentivize product manufacturers and LCA practitioners to improve data quality and transparently report known variation in their EPDs. It may also motivate manufacturers to reduce GHGs from their products and processes.

A New Approach to 3D ICP Covariance Estimation

In mobile robotics, scan matching of point clouds using Iterative Closest Point (ICP) allows estimating sensor displacements. It may prove important to assess the associated uncertainty about the obtained rigid transformation, especially for sensor fusion purposes. In this paper we propose a novel approach to 3D uncertainty of ICP that accounts for all the sources of error as listed in Censi's pioneering work [1], namely wrong convergence, underconstrained situations, and sensor noise. Our approach builds on two facts. First, the uncertainty about the ICP's output fully depends on the initialization accuracy. Thus speaking of the covariance of ICP makes sense only in relation to the initialization uncertainty, which generally stems from odometry errors. We capture this using the unscented transform, which also reflects correlations between initial and final uncertainties. Then, assuming white sensor noise leads to overoptimism as ICP is biased owing to e.g. calibration biases, which we account for. Our solution is tested on publicly available real data ranging from structured to unstructured environments, where our algorithm predicts consistent results with actual uncertainty, and compares favorably to previous methods.

Iterative alignment of reflector panels for large-scale compact test range in non-metrology environment based on laser tracker

The reflector panel used for a large-scale compact test range (CTR) is usually divided into several sub-panels with appropriate size to be fabricated separately, and then these sub-panels are assembled and aligned for a long period to form a high-precision reflective surface. Toward that end, an iterative alignment system is established to accomplish alignment of reflector panels based on commercial laser tracker and 6-degree-of-freedom adjustment mechanism. The alignment is a very challenging task involving two aspects: coordinate system alignment and measurement uncertainty evaluation, especially in a non-metrology environment. For the former, an alignment method is developed to unify the measurement coordinate system of the system based on iteratively adding and modifying reference points. For the latter, the actual uncertainty model of laser tracker based on a large amount of field measurement data is analyzed and established using statistical analysis. Based on the uncertainty model, the measurement and alignment error is evaluated and verified by Monte Carlo simulations. As verification, 15 sub-panels of the CTR reflector with 12 m width and 7 m height are opportunely assembled and aligned using the iterative alignment system and algorithm. The final root-mean-square error of the deviation between the actual and theoretical profiles is achieved at 0.041 mm, where the accuracy loss caused by alignment is only 7.9% of the theoretical value. Results show that the alignment system and method proposed in this paper is effective and efficient to align the reflector panels for large-scale CTR in a non-metrology environment.

Towards a model of uncertainty distress in the context of Coronavirus (COVID-19).

(1)To define the concept of uncertainty distress.(2)To understand the role of threat, over-estimation of threat, perceived uncertainty, actual uncertainty, and intolerance of uncertainty in distress maintenance.(3)To understand how people may behave in response to uncertainty distress.(4)To describe a model of uncertainty distress.

Estimating the material parameters of an inhomogeneous poroelastic plate from ultrasonic measurements in water.

The estimation of poroelastic material parameters based on ultrasound measurements is considered. The acoustical characterisation of poroelastic materials based on various measurements is typically carried out by minimising a cost functional of model residuals, such as the least squares functional. With a limited number of unknown parameters, least squares type approaches can provide both reliable parameter and error estimates. With an increasing number of parameters, both the least squares parameter estimates and, in particular, the error estimates often become unreliable. In this paper, the estimation of the material parameters of an inhomogeneous poroelastic (Biot) plate in the Bayesian framework for inverse problems is considered. Reflection and transmission measurements are performed and 11 poroelastic parameters, as well as 4 measurement setup-related nuisance parameters, are estimated. A Markov chain Monte Carlo algorithm is employed for the computational inference to assess the actual uncertainty of the estimated parameters. The results suggest that the proposed approach for poroelastic material characterisation can reveal the heterogeneities in the object, and yield reliable parameter and uncertainty estimates.

A Comprehensive Probabilistic Model of Traffic Loads based on Weigh-in-Motion Data for Applications to Bridge Structures

In various efforts to assure safety and serviceability of a bridge structure throughout its lifetime, it is essential to accurately estimate the traffic load effects. Although traffic loads involve large uncertainties and can vary significantly with site-specific traffic environments, bridge design codes and maintenance strategies do not utilize a probabilistic model that can reflect the actual environments and uncertainties of the target bridge. Rapid developments of weigh-in-motion (WIM) technologies now make it possible to collect various types of data describing the characteristics of vehicles and traffic patterns. Based on actual WIM data collected in South Korea, this paper develops a comprehensive probabilistic model describing the characteristics of vehicles and traffic flow so that the traffic load effects of a target bridge can be assessed using a Monte Carlo simulation approach. To describe the characteristics of vehicles and traffic flow in the WIM data, several important random variables are first identified. These key random variables are then incorporated into a comprehensive probabilistic model based on fitted probability distributions and theories of transportation engineering. The developed model is successfully verified by comparing the daily maximum total loads estimated using actual WIM data with those estimated using artificial WIM data generated from the model. Furthermore, bridge traffic load effects, e.g., moment and tension, are estimated using the influence lines of an actual cable-stayed bridge in South Korea (the Incheon Bridge) and are compared with those from the live load model of a design code. Finally, a brief parametric study is performed to explore the possibility that a probabilistic model developed by the proposed approach can be used as a generic probabilistic traffic load model capable of estimating the site-specific traffic loads through customizations based on partial measurements and available information regarding the target bridge.

Diving physiopathology: the end of certainties? Food for thought

Our understanding of decompression physiopathology has slowly improved during this last decade and some uncertainties have disappeared. A better understanding of anatomy and functional aspects of patent foramen ovale (PFO) have slowly resulted in a more liberal approach toward the medical fitness to dive for those bearing a PFO. Circulating vascular gas emboli (VGE) are considered the key actors in development of decompression sickness and can be considered as markers of decompression stress indicating induction of pathophysiological processes not necessarily leading to occurrence of disease symptoms. During the last decade, it has appeared possible to influence post-dive VGE by a so-called "preconditioning" as a pre-dive denitrogenation, exercise or some pharmacological agents. In the text we have deeply examined all the scientific evidence about this complicated but challenging theme. Finally, the role of the "normobaric oxygen paradox" has been clarified and it is not surprising that it could be involved in neuroprotection and cardioprotection. However, the best level of inspired oxygen and the exact time frame to achieve optimal effect is still not known. The aim of this paper was to reflect upon the most actual uncertainties and distil out of them a coherent, balanced advice towards the researchers involved in gas-bubbles-related pathologies.

Tau-decay determination of the strong coupling

We review the current status of the determination of the strong coupling from tau decay. Using the most recent release of the ALEPH data, a very comprehensive phenomenological analysis has been performed, exploring all strategies previously considered in the literature and several complementary approaches. Once their actual uncertainties are properly assessed, the results from all adopted methodologies are in excellent agreement, leading to a very robust and reliable value of the strong coupling, \alpha_s^{(n_f=3)}(m_\tau^2) = 0.328\pm 0.013αs(nf=3)(mτ2)=0.328±0.013, which implies \alpha_s^{(n_f=5)}(M_Z^2) = 0.1197\pm 0.0015αs(nf=5)(MZ2)=0.1197±0.0015.

Accurate and Precise Prediction of Soil Properties from a Large Mid-Infrared Spectral Library

Diffuse reflectance spectroscopy (DRS) is emerging as a rapid and cost-effective alternative to routine laboratory analysis for many soil properties. However, it has primarily been applied in project-specific contexts. Here, we provide an assessment of DRS spectroscopy at the scale of the continental United States by utilizing the large (n > 50,000) USDA National Soil Survey Center mid-infrared spectral library and associated soil characterization database. We tested and optimized several advanced statistical approaches for providing routine predictions of numerous soil properties relevant to studying carbon cycling. On independent validation sets, the machine learning algorithms Cubist and memory-based learner (MBL) both outperformed random forest (RF) and partial least squares regressions (PLSR) and produced excellent overall models with a mean R2 of 0.92 (mean ratio of performance to deviation = 6.5) across all 10 soil properties. We found that the use of root-mean-square error (RMSE) was misleading for understanding the actual uncertainty about any particular prediction; therefore, we developed routines to assess the prediction uncertainty for all models except Cubist. The MBL models produced much more precise predictions compared with global PLSR and RF. Finally, we present several techniques that can be used to flag predictions of new samples that may not be reliable because their spectra fall outside of the calibration set.

Analyzing and Projecting Soil Moisture and Cone Penetrability Variations in Forest Soils

This article details how forest soil moisture content (MC) and subsequent resistances to cone penetration (referred below as Cone Index, CI) vary by daily weather, season, topography, site and soil properties across eleven harvest blocks in northwestern New Brunswick. The MC- and CI-affecting soil variables refer to density, texture, organic matter content, coarse fragment content, and topographic position (i.e., elevation, and the seasonally affected cartographic depth-to-water (DTW) pattern). The harvest blocks were transect-sampled inside and outside their wood-forwarding tracks at varying times throughout the year. In detail, 61% of the pore-filled moisture content (MCPS) determinations inside and outside the tracks could be related to topographic position, coarse fragments, bulk density, and forest cover type specifications. In addition, 40% of the CI variations could be related to soil depth, MCPS, and block-specific cover type. Actual versus model-projected uncertainties amounted to ΔMCPS ≤ ± 15% and ΔCI ≤ ± 0.5 MPa, 8 times out of 10. Block-centered MC and CI projections were obtained through: 1) daily hydrological modelling using daily precipitation and air temperature weather-station records nearest each block, and 2) digitally mapped variations in soil properties, elevation, DTW and forest cover type, done at 10 m resolution.

What They Don’t Know Says A Lot: Residents’ Knowledge of Neighborhood Crime in Contemporary China

Our study questions the common assumption of random DK responses in criminology survey data and emphasizes the importance of understanding and handling DK for gaining substantive criminological knowledge. It examines the individual-level and neighborhood-level correlates of the propensity to give the DK response to questions on individual perception of neighborhood crime in Chongqing, China. We designed and conducted an original survey of 4839 residents from 100 urban neighborhoods in Chongqing, China in 2016. Random intercept hierarchical linear models were used to examine the effects of individual-level variables on uncertainty towards neighborhood crime and the effects of neighborhood social process variables, controlling for neighborhood composition. At least in some instances, DK appears to be the most valid response, reflecting actual uncertainty and lack of knowledge about neighborhood crime. DK responses have substantive correlates at both the individual and neighborhood level. Of particular interest, neighborhood social cohesion is negatively associated with individual uncertainty about neighborhood crime, controlling for neighborhood composition. There is a significant interaction between neighborhood semi-public social control and neighborhood poverty in predicting DK. Understanding the meanings behind DK has important implications for whether to include the DK option in survey designs and how to handle DK responses in data analysis when they occur. When DK is a valid answer for many respondents, not including the DK option in the survey instrument forces respondents to choose a nonexistent answer, which can result in misleading interpretations.