Directory of Open Access Journals (Sweden)
Elsa Tavernier
Full Text Available We aimed to examine the extent to which inaccurate assumptions for nuisance parameters used to calculate sample size can affect the power of a randomized controlled trial (RCT. In a simulation study, we separately considered an RCT with continuous, dichotomous or time-to-event outcomes, with associated nuisance parameters of standard deviation, success rate in the control group and survival rate in the control group at some time point, respectively. For each type of outcome, we calculated a required sample size N for a hypothesized treatment effect, an assumed nuisance parameter and a nominal power of 80%. We then assumed a nuisance parameter associated with a relative error at the design stage. For each type of outcome, we randomly drew 10,000 relative errors of the associated nuisance parameter (from empirical distributions derived from a previously published review. Then, retro-fitting the sample size formula, we derived, for the pre-calculated sample size N, the real power of the RCT, taking into account the relative error for the nuisance parameter. In total, 23%, 0% and 18% of RCTs with continuous, binary and time-to-event outcomes, respectively, were underpowered (i.e., the real power was 90%. Even with proper calculation of sample size, a substantial number of trials are underpowered or overpowered because of imprecise knowledge of nuisance parameters. Such findings raise questions about how sample size for RCTs should be determined.
A geostatistical analysis of geostatistics
Hengl, T.; Minasny, B.; Gould, M.
2009-01-01
The bibliometric indices of the scientific field of geostatistics were analyzed using statistical and spatial data analysis. The publications and their citation statistics were obtained from the Web of Science (4000 most relevant), Scopus (2000 most relevant) and Google Scholar (5389). The focus was
Partial Deconvolution with Inaccurate Blur Kernel.
Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei
2017-10-17
Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning
Kitanidis, P. K.
1997-05-01
Introduction to Geostatistics presents practical techniques for engineers and earth scientists who routinely encounter interpolation and estimation problems when analyzing data from field observations. Requiring no background in statistics, and with a unique approach that synthesizes classic and geostatistical methods, this book offers linear estimation methods for practitioners and advanced students. Well illustrated with exercises and worked examples, Introduction to Geostatistics is designed for graduate-level courses in earth sciences and environmental engineering.
10th International Geostatistics Congress
Rodrigo-Ilarri, Javier; Rodrigo-Clavero, María; Cassiraga, Eduardo; Vargas-Guzmán, José
2017-01-01
This book contains selected contributions presented at the 10th International Geostatistics Congress held in Valencia from 5 to 9 September, 2016. This is a quadrennial congress that serves as the meeting point for any engineer, professional, practitioner or scientist working in geostatistics. The book contains carefully reviewed papers on geostatistical theory and applications in fields such as mining engineering, petroleum engineering, environmental science, hydrology, ecology, and other fields.
Geostatistical models for air pollution
International Nuclear Information System (INIS)
Pereira, M.J.; Soares, A.; Almeida, J.; Branquinho, C.
2000-01-01
The objective of this paper is to present geostatistical models applied to the spatial characterisation of air pollution phenomena. A concise presentation of the geostatistical methodologies is illustrated with practical examples. The case study was conducted in an underground copper-mine located on the southern of Portugal, where a biomonitoring program using lichens has been implemented. Given the characteristics of lichens as indicators of air pollution it was possible to gather a great amount of data in space, which enabled the development and application of geostatistical methodologies. The advantages of using geostatistical models compared with deterministic models, as environmental control tools, are highlighted. (author)
4th International Geostatistics Congress
1993-01-01
The contributions in this book were presented at the Fourth International Geostatistics Congress held in Tróia, Portugal, in September 1992. They provide a comprehensive account of the current state of the art of geostatistics, including recent theoretical developments and new applications. In particular, readers will find descriptions and applications of the more recent methods of stochastic simulation together with data integration techniques applied to the modelling of hydrocabon reservoirs. In other fields there are stationary and non-stationary geostatistical applications to geology, climatology, pollution control, soil science, hydrology and human sciences. The papers also provide an insight into new trends in geostatistics particularly the increasing interaction with many other scientific disciplines. This book is a significant reference work for practitioners of geostatistics both in academia and industry.
7th International Geostatistics Congress
Deutsch, Clayton
2005-01-01
The conference proceedings consist of approximately 120 technical papers presented at the Seventh International Geostatistics Congress held in Banff, Alberta, Canada in 2004. All the papers were reviewed by an international panel of leading geostatisticians. The five major sections are: theory, mining, petroleum, environmental and other applications. The first section showcases new and innovative ideas in the theoretical development of geostatistics as a whole; these ideas will have large impact on (1) the directions of future geostatistical research, and (2) the conventional approaches to heterogeneity modelling in a wide range of natural resource industries. The next four sections are focused on applications and innovations relating to the use of geostatistics in specific industries. Historically, mining, petroleum and environmental industries have embraced the use of geostatistics for uncertainty characterization, so these three industries are identified as major application areas. The last section is open...
Swaminathan, M
1997-01-01
Indian women do not have to be told the benefits of breast feeding or "rescued from the clutches of wicked multinational companies" by international agencies. There is no proof that breast feeding has declined in India; in fact, a 1987 survey revealed that 98% of Indian women breast feed. Efforts to promote breast feeding among the middle classes rely on such initiatives as the "baby friendly" hospital where breast feeding is promoted immediately after birth. This ignores the 76% of Indian women who give birth at home. Blaming this unproved decline in breast feeding on multinational companies distracts attention from more far-reaching and intractable effects of social change. While the Infant Milk Substitutes Act is helpful, it also deflects attention from more pressing issues. Another false assumption is that Indian women are abandoning breast feeding to comply with the demands of employment, but research indicates that most women give up employment for breast feeding, despite the economic cost to their families. Women also seek work in the informal sector to secure the flexibility to meet their child care responsibilities. Instead of being concerned about "teaching" women what they already know about the benefits of breast feeding, efforts should be made to remove the constraints women face as a result of their multiple roles and to empower them with the support of families, governmental policies and legislation, employers, health professionals, and the media.
Geostatistical inference using crosshole ground-penetrating radar
DEFF Research Database (Denmark)
Looms, Majken C; Hansen, Thomas Mejer; Cordua, Knud Skou
2010-01-01
of the subsurface are used to evaluate the uncertainty of the inversion estimate. We have explored the full potential of the geostatistical inference method using several synthetic models of varying correlation structures and have tested the influence of different assumptions concerning the choice of covariance...... reflection profile. Furthermore, the inferred values of the subsurface global variance and the mean velocity have been corroborated with moisturecontent measurements, obtained gravimetrically from samples collected at the field site....
Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model
Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.
2017-09-01
The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.
Seismic forecast using geostatistics
International Nuclear Information System (INIS)
Grecu, Valeriu; Mateiciuc, Doru
2007-01-01
The main idea of this research direction consists in the special way of constructing a new type of mathematical function as being a correlation between a computed statistical quantity and another physical quantity. This type of function called 'position function' was taken over by the authors of this study in the field of seismology with the hope of solving - at least partially - the difficult problem of seismic forecast. The geostatistic method of analysis focuses on the process of energy accumulation in a given seismic area, completing this analysis by a so-called loading function. This function - in fact a temporal function - describes the process of energy accumulation during a seismic cycle from a given seismic area. It was possible to discover a law of evolution of the seismic cycles that was materialized in a so-called characteristic function. This special function will help us to forecast the magnitude and the occurrence moment of the largest earthquake in the analysed area. Since 2000, the authors have been evolving to a new stage of testing: real - time analysis, in order to verify the quality of the method. There were five large earthquakes forecasts. (authors)
Computational system for geostatistical analysis
Directory of Open Access Journals (Sweden)
Vendrusculo Laurimar Gonçalves
2004-01-01
Full Text Available Geostatistics identifies the spatial structure of variables representing several phenomena and its use is becoming more intense in agricultural activities. This paper describes a computer program, based on Windows Interfaces (Borland Delphi, which performs spatial analyses of datasets through geostatistic tools: Classical statistical calculations, average, cross- and directional semivariograms, simple kriging estimates and jackknifing calculations. A published dataset of soil Carbon and Nitrogen was used to validate the system. The system was useful for the geostatistical analysis process, for the manipulation of the computational routines in a MS-DOS environment. The Windows development approach allowed the user to model the semivariogram graphically with a major degree of interaction, functionality rarely available in similar programs. Given its characteristic of quick prototypation and simplicity when incorporating correlated routines, the Delphi environment presents the main advantage of permitting the evolution of this system.
Geostatistical investigations of rock masses
International Nuclear Information System (INIS)
Matar, J.A.; Sarquis, M.A.; Girardi, J.P.; Tabbia, G.H.
1987-01-01
The geostatistical tehniques applied for the selection of a minimun fracturation volume in Sierra del Medio allow to quantify and qualify the variability of mechanic characteristics and density of fracture and also the level of reliability in estimations. The role of geostatistics is discussed in this work so as to select minimun fracturation blocks as a very important site selection step. The only variable used is the 'jointing density' so as to detect the principal fracture systems affecting the rocky massif. It was used on the semivariograms corresponding to the previously mentioned regionalized variables. The different results of fracturation are compared with the deep and shallow geological survey to obtain two and three dimensional models. The range of the geostatistical techniques to detect local geological phenomena such as faults is discussed. The variability model obtained from the borehole data computations is investigated taking as basis the vertical Columnar Model of Discontinuity (fractures) hypothesis derived from geological studies about spatial behaviour of the joint systems and from geostatistical interpretation. (Author) [es
A practical primer on geostatistics
Olea, Ricardo A.
2009-01-01
The Challenge—Most geological phenomena are extraordinarily complex in their interrelationships and vast in their geographical extension. Ordinarily, engineers and geoscientists are faced with corporate or scientific requirements to properly prepare geological models with measurements involving a small fraction of the entire area or volume of interest. Exact description of a system such as an oil reservoir is neither feasible nor economically possible. The results are necessarily uncertain. Note that the uncertainty is not an intrinsic property of the systems; it is the result of incomplete knowledge by the observer.The Aim of Geostatistics—The main objective of geostatistics is the characterization of spatial systems that are incompletely known, systems that are common in geology. A key difference from classical statistics is that geostatistics uses the sampling location of every measurement. Unless the measurements show spatial correlation, the application of geostatistics is pointless. Ordinarily the need for additional knowledge goes beyond a few points, which explains the display of results graphically as fishnet plots, block diagrams, and maps.Geostatistical Methods—Geostatistics is a collection of numerical techniques for the characterization of spatial attributes using primarily two tools: probabilistic models, which are used for spatial data in a manner similar to the way in which time-series analysis characterizes temporal data, or pattern recognition techniques. The probabilistic models are used as a way to handle uncertainty in results away from sampling locations, making a radical departure from alternative approaches like inverse distance estimation methods.Differences with Time Series—On dealing with time-series analysis, users frequently concentrate their attention on extrapolations for making forecasts. Although users of geostatistics may be interested in extrapolation, the methods work at their best interpolating. This simple difference
Gathering asychronous mobile robots with inaccurate compasses
Souissi, Samia; Defago, Xavier; Yamashita, Masafumi
2006-01-01
This paper considers a system of asynchronous autonomous mobile robots that can move freely in a twodimensional plane with no agreement on a common coordinate system. Starting from any initial configuration, the robots are required to eventually gather at a single point, not fixed in advance (gathering problem). Prior work has shown that gathering oblivious (i.e., stateless) robots cannot be achieved deterministically without additional assumptions. In particular, if robots can detect multipl...
Geostatistics - bloodhound of uranium exploration
International Nuclear Information System (INIS)
David, Michel
1979-01-01
Geostatistics makes possible the efficient use of the information contained in core samples obtained by diamond drilling. The probability that a core represents the true content of a deposit, and the likely content of an orebody between two core samples can both be estimated using geostatistical methods. A confidence interval can be given for the mean grade of a deposit. The use of a computer is essential in the calculation of the continuity function, the variogram, when as many as 800,000 core samples may be involved. The results may be used to determine where additional samples need to be taken, and to develop a picture of the probable grades throughout the deposit. The basic mathematical model is about 15 years old, but applications to different types of deposit require various adaptations. The Ecole Polytechnique is currently developing methods for uranium deposits. (LL)
Application of geostatistics in Beach Placer
International Nuclear Information System (INIS)
Sundar, G.
2016-01-01
The goal of Geostatistics is in the prediction of possible spatial distribution of a property. Application of Geostatistics has gained significance in the field of exploration, evaluation and mining. In the case of beach and inland placer sands exploration, geostatistics can be used in optimising the drill hole spacing, estimate resources of the total heavy minerals (THM), estimation on different grid pattern and grade - tonnage curves. Steps involved in a geostatistical study are exploratory data analysis, creation of experimental variogram, variogram model fitting, kriging and cross validation. Basic tools in geostatistics are variogram and kriging. Characteristics of a variogram are sill, range and nugget. There is a necessity for variogram model fitting prior to kriging. Commonly used variogram models are spherical, exponential and gaussian
Baskas, Richard S.
2011-01-01
The purpose of this study is to examine Knowles' theory of andragogy and his six assumptions of how adults learn while providing evidence to support two of his assumptions based on the theory of andragogy. As no single theory explains how adults learn, it can best be assumed that adults learn through the accumulation of formal and informal…
International Nuclear Information System (INIS)
Grasshoff, C.; Schetelig, K.; Tomschi, H.
1998-01-01
The following paper demonstrates, how a geostatistical approach can help interpolating hydrogeological parameters over a certain area. The basic elements developed by G. Matheron in the sixties are represented as the preconditions and assumptions, which provide the best results of the estimation. The variogram as the most important tool in geostatistics offers the opportunity to describe the correlating behaviour of a regionalized variable. Some kriging procedures are briefly introduced, which provide under varying circumstances estimating of non-measured values with the theoretical variogram-model. In the Ronneburg mine district 108 screened drill-holes could provide coefficients of hydraulic conductivity. These were interpolated with ordinary kriging over the whole investigation area. An error calculation was performed, which could prove the accuracy of the estimation. Short prospects point out some difficulties handling with geostatistic procedures and make suggestions for further investigations. (orig.) [de
Geostatistical methods applied to field model residuals
DEFF Research Database (Denmark)
Maule, Fox; Mosegaard, K.; Olsen, Nils
consists of measurement errors and unmodelled signal), and is typically assumed to be uncorrelated and Gaussian distributed. We have applied geostatistical methods to analyse the residuals of the Oersted(09d/04) field model [http://www.dsri.dk/Oersted/Field_models/IGRF_2005_candidates/], which is based...
Satellite Magnetic Residuals Investigated With Geostatistical Methods
DEFF Research Database (Denmark)
Fox Maule, Chaterine; Mosegaard, Klaus; Olsen, Nils
2005-01-01
(which consists of measurement errors and unmodeled signal), and is typically assumed to be uncorrelated and Gaussian distributed. We have applied geostatistical methods to analyze the residuals of the Oersted (09d/04) field model (www.dsri.dk/Oersted/Field models/IGRF 2005 candidates/), which is based...
Multiverse Assumptions and Philosophy
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James R. Johnson
2018-02-01
Full Text Available Multiverses are predictions based on theories. Focusing on each theory’s assumptions is key to evaluating a proposed multiverse. Although accepted theories of particle physics and cosmology contain non-intuitive features, multiverse theories entertain a host of “strange” assumptions classified as metaphysical (outside objective experience, concerned with fundamental nature of reality, ideas that cannot be proven right or wrong topics such as: infinity, duplicate yous, hypothetical fields, more than three space dimensions, Hilbert space, advanced civilizations, and reality established by mathematical relationships. It is easy to confuse multiverse proposals because many divergent models exist. This overview defines the characteristics of eleven popular multiverse proposals. The characteristics compared are: initial conditions, values of constants, laws of nature, number of space dimensions, number of universes, and fine tuning explanations. Future scientific experiments may validate selected assumptions; but until they do, proposals by philosophers may be as valid as theoretical scientific theories.
Adjusting case mix payment amounts for inaccurately reported comorbidity data.
Sutherland, Jason M; Hamm, Jeremy; Hatcher, Jeff
2010-03-01
Case mix methods such as diagnosis related groups have become a basis of payment for inpatient hospitalizations in many countries. Specifying cost weight values for case mix system payment has important consequences; recent evidence suggests case mix cost weight inaccuracies influence the supply of some hospital-based services. To begin to address the question of case mix cost weight accuracy, this paper is motivated by the objective of improving the accuracy of cost weight values due to inaccurate or incomplete comorbidity data. The methods are suitable to case mix methods that incorporate disease severity or comorbidity adjustments. The methods are based on the availability of detailed clinical and cost information linked at the patient level and leverage recent results from clinical data audits. A Bayesian framework is used to synthesize clinical data audit information regarding misclassification probabilities into cost weight value calculations. The models are implemented through Markov chain Monte Carlo methods. An example used to demonstrate the methods finds that inaccurate comorbidity data affects cost weight values by biasing cost weight values (and payments) downward. The implications for hospital payments are discussed and the generalizability of the approach is explored.
Sensitivity Analysis Without Assumptions.
Ding, Peng; VanderWeele, Tyler J
2016-05-01
Unmeasured confounding may undermine the validity of causal inference with observational studies. Sensitivity analysis provides an attractive way to partially circumvent this issue by assessing the potential influence of unmeasured confounding on causal conclusions. However, previous sensitivity analysis approaches often make strong and untestable assumptions such as having an unmeasured confounder that is binary, or having no interaction between the effects of the exposure and the confounder on the outcome, or having only one unmeasured confounder. Without imposing any assumptions on the unmeasured confounder or confounders, we derive a bounding factor and a sharp inequality such that the sensitivity analysis parameters must satisfy the inequality if an unmeasured confounder is to explain away the observed effect estimate or reduce it to a particular level. Our approach is easy to implement and involves only two sensitivity parameters. Surprisingly, our bounding factor, which makes no simplifying assumptions, is no more conservative than a number of previous sensitivity analysis techniques that do make assumptions. Our new bounding factor implies not only the traditional Cornfield conditions that both the relative risk of the exposure on the confounder and that of the confounder on the outcome must satisfy but also a high threshold that the maximum of these relative risks must satisfy. Furthermore, this new bounding factor can be viewed as a measure of the strength of confounding between the exposure and the outcome induced by a confounder.
A Practical pedestrian approach to parsimonious regression with inaccurate inputs
Directory of Open Access Journals (Sweden)
Seppo Karrila
2014-04-01
Full Text Available A measurement result often dictates an interval containing the correct value. Interval data is also created by roundoff, truncation, and binning. We focus on such common interval uncertainty in data. Inaccuracy in model inputs is typically ignored on model fitting. We provide a practical approach for regression with inaccurate data: the mathematics is easy, and the linear programming formulations simple to use even in a spreadsheet. This self-contained elementary presentation introduces interval linear systems and requires only basic knowledge of algebra. Feature selection is automatic; but can be controlled to find only a few most relevant inputs; and joint feature selection is enabled for multiple modeled outputs. With more features than cases, a novel connection to compressed sensing emerges: robustness against interval errors-in-variables implies model parsimony, and the input inaccuracies determine the regularization term. A small numerical example highlights counterintuitive results and a dramatic difference to total least squares.
Endoscopic Localization of Colon Cancer Is Frequently Inaccurate.
Nayor, Jennifer; Rotman, Stephen R; Chan, Walter W; Goldberg, Joel E; Saltzman, John R
2017-08-01
Colonoscopic location of a tumor can influence both the surgical procedure choice and overall treatment strategy. To determine the accuracy of colonoscopy in determining the location of colon cancer compared to surgical localization and to elucidate factors that predict discordant colon cancer localization. We conducted a retrospective cross-sectional study of colon cancers diagnosed on colonoscopy at two academic tertiary-care hospitals and two affiliated community hospitals from 2012 to 2014. Colon cancer location was obtained from the endoscopic and surgical pathology reports and characterized by colon segment. We collected data on patient demographics, tumor characteristics, endoscopic procedure characteristics, surgery planned, and surgery performed. Univariate analyses using Chi-squared test and multivariate analysis using forward stepwise logistic regression were performed to determine factors that predict discordant colon cancer localization. There were 110 colon cancer cases identified during the study period. Inaccurate endoscopic colon cancer localization was found in 29% (32/110) of cases. These included 14 cases (12.7%) that were discordant by more than one colonic segment and three cases where the presurgical planned procedure was significantly changed at the time of surgery. On univariate analyses, right-sided colon lesions were associated with increased inaccuracy (43.8 vs 24.4%, p = 0.04). On multivariate analysis, right-sided colon lesions remained independently associated with inaccuracy (OR 1.74, 95% CI 1.03-2.93, p = 0.04). Colon cancer location as determined by colonoscopy is often inaccurate, which can result in intraoperative changes to surgical management, particularly in the right colon.
Alzraiee, Ayman H.; Bau, Domenico A.; Garcia, Luis A.
2013-06-01
Effective sampling of hydrogeological systems is essential in guiding groundwater management practices. Optimal sampling of groundwater systems has previously been formulated based on the assumption that heterogeneous subsurface properties can be modeled using a geostatistical approach. Therefore, the monitoring schemes have been developed to concurrently minimize the uncertainty in the spatial distribution of systems' states and parameters, such as the hydraulic conductivity K and the hydraulic head H, and the uncertainty in the geostatistical model of system parameters using a single objective function that aggregates all objectives. However, it has been shown that the aggregation of possibly conflicting objective functions is sensitive to the adopted aggregation scheme and may lead to distorted results. In addition, the uncertainties in geostatistical parameters affect the uncertainty in the spatial prediction of K and H according to a complex nonlinear relationship, which has often been ineffectively evaluated using a first-order approximation. In this study, we propose a multiobjective optimization framework to assist the design of monitoring networks of K and H with the goal of optimizing their spatial predictions and estimating the geostatistical parameters of the K field. The framework stems from the combination of a data assimilation (DA) algorithm and a multiobjective evolutionary algorithm (MOEA). The DA algorithm is based on the ensemble Kalman filter, a Monte-Carlo-based Bayesian update scheme for nonlinear systems, which is employed to approximate the posterior uncertainty in K, H, and the geostatistical parameters of K obtained by collecting new measurements. Multiple MOEA experiments are used to investigate the trade-off among design objectives and identify the corresponding monitoring schemes. The methodology is applied to design a sampling network for a shallow unconfined groundwater system located in Rocky Ford, Colorado. Results indicate that
International Nuclear Information System (INIS)
Doctor, P.G.; Oberlander, P.L.; Rice, W.A.; Devary, J.L.; Nelson, R.W.; Tucker, P.E.
1982-09-01
The Office of Nuclear Waste Isolation (ONWI) requested Pacific Northwest Laboratory (PNL) to: (1) use geostatistical analyses to evaluate the adequacy of hydrologic data from three salt regions, each of which contains a potential nuclear waste repository site; and (2) demonstrate a methodology that allows quantification of the value of additional data collection. The three regions examined are the Paradox Basin in Utah, the Permian Basin in Texas, and the Mississippi Study Area. Additional and new data became available to ONWI during and following these analyses; therefore, this report must be considered a methodology demonstration here would apply as illustrated had the complete data sets been available. A combination of geostatistical and hydrologic analyses was used for this demonstration. Geostatistical analyses provided an optimal estimate of the potentiometric surface from the available data, a measure of the uncertainty of that estimate, and a means for selecting and evaluating the location of future data. The hydrologic analyses included the calculation of transmissivities, flow paths, travel times, and ground-water flow rates from hypothetical repository sites. Simulation techniques were used to evaluate the effect of optimally located future data on the potentiometric surface, flow lines, travel times, and flow rates. Data availability, quality, quantity, and conformance with model assumptions differed in each of the salt areas. Report highlights for the three locations are given
Contextuality under weak assumptions
International Nuclear Information System (INIS)
Simmons, Andrew W; Rudolph, Terry; Wallman, Joel J; Pashayan, Hakop; Bartlett, Stephen D
2017-01-01
The presence of contextuality in quantum theory was first highlighted by Bell, Kochen and Specker, who discovered that for quantum systems of three or more dimensions, measurements could not be viewed as deterministically revealing pre-existing properties of the system. More precisely, no model can assign deterministic outcomes to the projectors of a quantum measurement in a way that depends only on the projector and not the context (the full set of projectors) in which it appeared, despite the fact that the Born rule probabilities associated with projectors are independent of the context. A more general, operational definition of contextuality introduced by Spekkens, which we will term ‘probabilistic contextuality’, drops the assumption of determinism and allows for operations other than measurements to be considered contextual. Even two-dimensional quantum mechanics can be shown to be contextual under this generalised notion. Probabilistic noncontextuality represents the postulate that elements of an operational theory that cannot be distinguished from each other based on the statistics of arbitrarily many repeated experiments (they give rise to the same operational probabilities) are ontologically identical. In this paper, we introduce a framework that enables us to distinguish between different noncontextuality assumptions in terms of the relationships between the ontological representations of objects in the theory given a certain relation between their operational representations. This framework can be used to motivate and define a ‘possibilistic’ analogue, encapsulating the idea that elements of an operational theory that cannot be unambiguously distinguished operationally can also not be unambiguously distinguished ontologically. We then prove that possibilistic noncontextuality is equivalent to an alternative notion of noncontextuality proposed by Hardy. Finally, we demonstrate that these weaker noncontextuality assumptions are sufficient to prove
Exploring prediction uncertainty of spatial data in geostatistical and machine learning Approaches
Klump, J. F.; Fouedjio, F.
2017-12-01
Geostatistical methods such as kriging with external drift as well as machine learning techniques such as quantile regression forest have been intensively used for modelling spatial data. In addition to providing predictions for target variables, both approaches are able to deliver a quantification of the uncertainty associated with the prediction at a target location. Geostatistical approaches are, by essence, adequate for providing such prediction uncertainties and their behaviour is well understood. However, they often require significant data pre-processing and rely on assumptions that are rarely met in practice. Machine learning algorithms such as random forest regression, on the other hand, require less data pre-processing and are non-parametric. This makes the application of machine learning algorithms to geostatistical problems an attractive proposition. The objective of this study is to compare kriging with external drift and quantile regression forest with respect to their ability to deliver reliable prediction uncertainties of spatial data. In our comparison we use both simulated and real world datasets. Apart from classical performance indicators, comparisons make use of accuracy plots, probability interval width plots, and the visual examinations of the uncertainty maps provided by the two approaches. By comparing random forest regression to kriging we found that both methods produced comparable maps of estimated values for our variables of interest. However, the measure of uncertainty provided by random forest seems to be quite different to the measure of uncertainty provided by kriging. In particular, the lack of spatial context can give misleading results in areas without ground truth data. These preliminary results raise questions about assessing the risks associated with decisions based on the predictions from geostatistical and machine learning algorithms in a spatial context, e.g. mineral exploration.
The application of geostatistics in erosion hazard mapping
Beurden, S.A.H.A. van; Riezebos, H.Th.
1988-01-01
Geostatistical interpolation or kriging of soil and vegetation variables has become an important alternative to other mapping techniques. Although a reconnaissance sampling is necessary and basic requirements of geostatistics have to be met, kriging has the advantage of giving estimates with a
Forecasting Interest Rates Using Geostatistical Techniques
Directory of Open Access Journals (Sweden)
Giuseppe Arbia
2015-11-01
Full Text Available Geostatistical spatial models are widely used in many applied fields to forecast data observed on continuous three-dimensional surfaces. We propose to extend their use to finance and, in particular, to forecasting yield curves. We present the results of an empirical application where we apply the proposed method to forecast Euro Zero Rates (2003–2014 using the Ordinary Kriging method based on the anisotropic variogram. Furthermore, a comparison with other recent methods for forecasting yield curves is proposed. The results show that the model is characterized by good levels of predictions’ accuracy and it is competitive with the other forecasting models considered.
Testing Our Fundamental Assumptions
Kohler, Susanna
2016-06-01
Science is all about testing the things we take for granted including some of the most fundamental aspects of how we understand our universe. Is the speed of light in a vacuum the same for all photons regardless of their energy? Is the rest mass of a photon actually zero? A series of recent studies explore the possibility of using transient astrophysical sources for tests!Explaining Different Arrival TimesArtists illustration of a gamma-ray burst, another extragalactic transient, in a star-forming region. [NASA/Swift/Mary Pat Hrybyk-Keith and John Jones]Suppose you observe a distant transient astrophysical source like a gamma-ray burst, or a flare from an active nucleus and two photons of different energies arrive at your telescope at different times. This difference in arrival times could be due to several different factors, depending on how deeply you want to question some of our fundamental assumptions about physics:Intrinsic delayThe photons may simply have been emitted at two different times by the astrophysical source.Delay due to Lorentz invariance violationPerhaps the assumption that all massless particles (even two photons with different energies) move at the exact same velocity in a vacuum is incorrect.Special-relativistic delayMaybe there is a universal speed for massless particles, but the assumption that photons have zero rest mass is wrong. This, too, would cause photon velocities to be energy-dependent.Delay due to gravitational potentialPerhaps our understanding of the gravitational potential that the photons experience as they travel is incorrect, also causing different flight times for photons of different energies. This would mean that Einsteins equivalence principle, a fundamental tenet of general relativity (GR), is incorrect.If we now turn this problem around, then by measuring the arrival time delay between photons of different energies from various astrophysical sources the further away, the better we can provide constraints on these
Entanglement-fidelity relations for inaccurate ancilla-driven quantum computation
International Nuclear Information System (INIS)
Morimae, Tomoyuki; Kahn, Jonas
2010-01-01
It was shown by T. Morimae [Phys. Rev. A 81, 060307(R) (2010)] that the gate fidelity of an inaccurate one-way quantum computation is upper bounded by a decreasing function of the amount of entanglement in the register. This means that a strong entanglement causes the low gate fidelity in the one-way quantum computation with inaccurate measurements. In this paper, we derive similar entanglement-fidelity relations for the inaccurate ancilla-driven quantum computation. These relations again imply that a strong entanglement in the register causes the low gate fidelity in the ancilla-driven quantum computation if the measurements on the ancilla are inaccurate.
Geostatistical enhancement of european hydrological predictions
Pugliese, Alessio; Castellarin, Attilio; Parajka, Juraj; Arheimer, Berit; Bagli, Stefano; Mazzoli, Paolo; Montanari, Alberto; Blöschl, Günter
2016-04-01
Geostatistical Enhancement of European Hydrological Prediction (GEEHP) is a research experiment developed within the EU funded SWITCH-ON project, which proposes to conduct comparative experiments in a virtual laboratory in order to share water-related information and tackle changes in the hydrosphere for operational needs (http://www.water-switch-on.eu). The main objective of GEEHP deals with the prediction of streamflow indices and signatures in ungauged basins at different spatial scales. In particular, among several possible hydrological signatures we focus in our experiment on the prediction of flow-duration curves (FDCs) along the stream-network, which has attracted an increasing scientific attention in the last decades due to the large number of practical and technical applications of the curves (e.g. hydropower potential estimation, riverine habitat suitability and ecological assessments, etc.). We apply a geostatistical procedure based on Top-kriging, which has been recently shown to be particularly reliable and easy-to-use regionalization approach, employing two different type of streamflow data: pan-European E-HYPE simulations (http://hypeweb.smhi.se/europehype) and observed daily streamflow series collected in two pilot study regions, i.e. Tyrol (merging data from Austrian and Italian stream gauging networks) and Sweden. The merger of the two study regions results in a rather large area (~450000 km2) and might be considered as a proxy for a pan-European application of the approach. In a first phase, we implement a bidirectional validation, i.e. E-HYPE catchments are set as training sites to predict FDCs at the same sites where observed data are available, and vice-versa. Such a validation procedure reveals (1) the usability of the proposed approach for predicting the FDCs over the entire river network of interest using alternatively observed data and E-HYPE simulations and (2) the accuracy of E-HYPE-based predictions of FDCs in ungauged sites. In a
Geostatistical evaluation of travel time uncertainties
International Nuclear Information System (INIS)
Devary, J.L.
1983-08-01
Data on potentiometric head and hydraulic conductivity, gathered from the Wolfcamp Formation of the Permian System, have exhibited tremendous spatial variability as a result of heterogeneities in the media and the presence of petroleum and natural gas deposits. Geostatistical data analysis and error propagation techniques (kriging and conditional simulation) were applied to determine the effect of potentiometric head uncertainties on radionuclide travel paths and travel times through the Wolfcamp Formation. Blok-average kriging was utilized to remove measurement error from potentiometric head data. The travel time calculations have been enhanced by the use of an inverse technique to determine the relative hydraulic conductivity along travel paths. In this way, the spatial variability of the hydraulic conductivity corresponding to streamline convergence and divergence may be included in the analysis. 22 references, 11 figures, 1 table
Geostatistical interpolation for modelling SPT data in northern Izmir
Indian Academy of Sciences (India)
data scatter' stems from the natural randomness of the system under con- ... Geostatistical methods were originally used for ore reserve calculations by the ... ing grain size distribution, plasticity, strength parameters and water content, for ...
Do unreal assumptions pervert behaviour?
DEFF Research Database (Denmark)
Petersen, Verner C.
of the basic assumptions underlying the theories found in economics. Assumptions relating to the primacy of self-interest, to resourceful, evaluative, maximising models of man, to incentive systems and to agency theory. The major part of the paper then discusses how these assumptions and theories may pervert......-interested way nothing will. The purpose of this paper is to take a critical look at some of the assumptions and theories found in economics and discuss their implications for the models and the practices found in the management of business. The expectation is that the unrealistic assumptions of economics have...... become taken for granted and tacitly included into theories and models of management. Guiding business and manage¬ment to behave in a fashion that apparently makes these assumptions become "true". Thus in fact making theories and models become self-fulfilling prophecies. The paper elucidates some...
Directory of Open Access Journals (Sweden)
Jay Krishna Thakur
2015-08-01
Full Text Available The aim of this work is to investigate new approaches using methods based on statistics and geo-statistics for spatio-temporal optimization of groundwater monitoring networks. The formulated and integrated methods were tested with the groundwater quality data set of Bitterfeld/Wolfen, Germany. Spatially, the monitoring network was optimized using geo-statistical methods. Temporal optimization of the monitoring network was carried out using Sen’s method (1968. For geostatistical network optimization, a geostatistical spatio-temporal algorithm was used to identify redundant wells in 2- and 2.5-D Quaternary and Tertiary aquifers. Influences of interpolation block width, dimension, contaminant association, groundwater flow direction and aquifer homogeneity on statistical and geostatistical methods for monitoring network optimization were analysed. The integrated approach shows 37% and 28% redundancies in the monitoring network in Quaternary aquifer and Tertiary aquifer respectively. The geostatistical method also recommends 41 and 22 new monitoring wells in the Quaternary and Tertiary aquifers respectively. In temporal optimization, an overall optimized sampling interval was recommended in terms of lower quartile (238 days, median quartile (317 days and upper quartile (401 days in the research area of Bitterfeld/Wolfen. Demonstrated methods for improving groundwater monitoring network can be used in real monitoring network optimization with due consideration given to influencing factors.
The role of geostatistics in medical geology
Goovaerts, Pierre
2014-05-01
Since its development in the mining industry, geostatistics has emerged as the primary tool for spatial data analysis in various fields, ranging from earth and atmospheric sciences, to agriculture, soil science, remote sensing, and more recently environmental exposure assessment. In the last few years, these tools have been tailored to the field of medical geography or spatial epidemiology, which is concerned with the study of spatial patterns of disease incidence and mortality and the identification of potential 'causes' of disease, such as environmental exposure, diet and unhealthy behaviors, economic or socio-demographic factors. On the other hand, medical geology is an emerging interdisciplinary scientific field studying the relationship between natural geological factors and their effects on human and animal health. This paper provides an introduction to the field of medical geology with an overview of geostatistical methods available for the analysis of geological and health data. Key concepts are illustrated using the mapping of groundwater arsenic concentrations across eleven Michigan counties and the exploration of its relationship to the incidence of prostate cancer at the township level. Arsenic in drinking-water is a major problem and has received much attention because of the large human population exposed and the extremely high concentrations (e.g. 600 to 700 μg/L) recorded in many instances. Few studies have however assessed the risks associated with exposure to low levels of arsenic (say water in the United States. In the Michigan thumb region, arsenopyrite (up to 7% As by weight) has been identified in the bedrock of the Marshall Sandstone aquifer, one of the region's most productive aquifers. Epidemiologic studies have suggested a possible associationbetween exposure to inorganic arsenic and prostate cancer mortality, including a study of populations residing in Utah. The information available for the present ecological study (i.e. analysis of
Inverting reflections using full-waveform inversion with inaccurate starting models
AlTheyab, Abdullah; Schuster, Gerard T.
2015-01-01
We present a method for inverting seismic reflections using full-waveform inversion (FWI) with inaccurate starting models. For a layered medium, near-offset reflections (with zero angle of incidence) are unlikely to be cycle-skipped regardless
Geostatistical regularization operators for geophysical inverse problems on irregular meshes
Jordi, C.; Doetsch, J.; Günther, T.; Schmelzbach, C.; Robertsson, J. OA
2018-05-01
Irregular meshes allow to include complicated subsurface structures into geophysical modelling and inverse problems. The non-uniqueness of these inverse problems requires appropriate regularization that can incorporate a priori information. However, defining regularization operators for irregular discretizations is not trivial. Different schemes for calculating smoothness operators on irregular meshes have been proposed. In contrast to classical regularization constraints that are only defined using the nearest neighbours of a cell, geostatistical operators include a larger neighbourhood around a particular cell. A correlation model defines the extent of the neighbourhood and allows to incorporate information about geological structures. We propose an approach to calculate geostatistical operators for inverse problems on irregular meshes by eigendecomposition of a covariance matrix that contains the a priori geological information. Using our approach, the calculation of the operator matrix becomes tractable for 3-D inverse problems on irregular meshes. We tested the performance of the geostatistical regularization operators and compared them against the results of anisotropic smoothing in inversions of 2-D surface synthetic electrical resistivity tomography (ERT) data as well as in the inversion of a realistic 3-D cross-well synthetic ERT scenario. The inversions of 2-D ERT and seismic traveltime field data with geostatistical regularization provide results that are in good accordance with the expected geology and thus facilitate their interpretation. In particular, for layered structures the geostatistical regularization provides geologically more plausible results compared to the anisotropic smoothness constraints.
Geostatistics and GIS: tools for characterizing environmental contamination.
Henshaw, Shannon L; Curriero, Frank C; Shields, Timothy M; Glass, Gregory E; Strickland, Paul T; Breysse, Patrick N
2004-08-01
Geostatistics is a set of statistical techniques used in the analysis of georeferenced data that can be applied to environmental contamination and remediation studies. In this study, the 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) contamination at a Superfund site in western Maryland is evaluated. Concern about the site and its future clean up has triggered interest within the community because residential development surrounds the area. Spatial statistical methods, of which geostatistics is a subset, are becoming increasingly popular, in part due to the availability of geographic information system (GIS) software in a variety of application packages. In this article, the joint use of ArcGIS software and the R statistical computing environment are demonstrated as an approach for comprehensive geostatistical analyses. The spatial regression method, kriging, is used to provide predictions of DDE levels at unsampled locations both within the site and the surrounding areas where residential development is ongoing.
Sampling Assumptions in Inductive Generalization
Navarro, Daniel J.; Dry, Matthew J.; Lee, Michael D.
2012-01-01
Inductive generalization, where people go beyond the data provided, is a basic cognitive capability, and it underpins theoretical accounts of learning, categorization, and decision making. To complete the inductive leap needed for generalization, people must make a key "sampling" assumption about how the available data were generated.…
Major Assumptions of Mastery Learning.
Anderson, Lorin W.
Mastery learning can be described as a set of group-based, individualized, teaching and learning strategies based on the premise that virtually all students can and will, in time, learn what the school has to teach. Inherent in this description are assumptions concerning the nature of schools, classroom instruction, and learners. According to the…
Reducing uncertainty in geostatistical description with well testing pressure data
Energy Technology Data Exchange (ETDEWEB)
Reynolds, A.C.; He, Nanqun [Univ. of Tulsa, OK (United States); Oliver, D.S. [Chevron Petroleum Technology Company, La Habra, CA (United States)
1997-08-01
Geostatistics has proven to be an effective tool for generating realizations of reservoir properties conditioned to static data, e.g., core and log data and geologic knowledge. Due to the lack of closely spaced data in the lateral directions, there will be significant variability in reservoir descriptions generated by geostatistical simulation, i.e., significant uncertainty in the reservoir descriptions. In past work, we have presented procedures based on inverse problem theory for generating reservoir descriptions (rock property fields) conditioned to pressure data and geostatistical information represented as prior means for log-permeability and porosity and variograms. Although we have shown that the incorporation of pressure data reduces the uncertainty below the level contained in the geostatistical model based only on static information (the prior model), our previous results assumed did not explicitly account for uncertainties in the prior means and the parameters defining the variogram model. In this work, we investigate how pressure data can help detect errors in the prior means. If errors in the prior means are large and are not taken into account, realizations conditioned to pressure data represent incorrect samples of the a posteriori probability density function for the rock property fields, whereas, if the uncertainty in the prior mean is incorporated properly into the model, one obtains realistic realizations of the rock property fields.
Geostatistics for radiological characterization: overview and application cases
International Nuclear Information System (INIS)
Desnoyers, Yvon
2016-01-01
The objective of radiological characterization is to find a suitable balance between gathering data (constrained by cost, deadlines, accessibility or radiation) and managing the issues (waste volumes, levels of activity or exposure). It is necessary to have enough information to have confidence in the results without multiplying useless data. Geo-statistics processing of data considers all available pieces of information: historical data, non-destructive measurements and laboratory analyses of samples. The spatial structure modelling is then used to produce maps and to estimate the extent of radioactive contamination (surface and depth). Quantifications of local and global uncertainties are powerful decision-making tools for better management of remediation projects at contaminated sites, and for decontamination and dismantling projects at nuclear facilities. They can be used to identify hot spots, estimate contamination of surfaces and volumes, classify radioactive waste according to thresholds, estimate source terms, and so on. The spatial structure of radioactive contamination makes the optimization of sampling (number and position of data points) particularly important. Geo-statistics methodology can help determine the initial mesh size and reduce estimation uncertainties. Several show cases are presented to illustrate why and how geo-statistics can be applied to a range of radiological characterization where investigated units can represent very small areas (a few m 2 or a few m 3 ) or very large sites (at a country scale). The focus is then put on experience gained over years in the use of geo-statistics and sampling optimization. (author)
A Bayesian Markov geostatistical model for estimation of hydrogeological properties
International Nuclear Information System (INIS)
Rosen, L.; Gustafson, G.
1996-01-01
A geostatistical methodology based on Markov-chain analysis and Bayesian statistics was developed for probability estimations of hydrogeological and geological properties in the siting process of a nuclear waste repository. The probability estimates have practical use in decision-making on issues such as siting, investigation programs, and construction design. The methodology is nonparametric which makes it possible to handle information that does not exhibit standard statistical distributions, as is often the case for classified information. Data do not need to meet the requirements on additivity and normality as with the geostatistical methods based on regionalized variable theory, e.g., kriging. The methodology also has a formal way for incorporating professional judgments through the use of Bayesian statistics, which allows for updating of prior estimates to posterior probabilities each time new information becomes available. A Bayesian Markov Geostatistical Model (BayMar) software was developed for implementation of the methodology in two and three dimensions. This paper gives (1) a theoretical description of the Bayesian Markov Geostatistical Model; (2) a short description of the BayMar software; and (3) an example of application of the model for estimating the suitability for repository establishment with respect to the three parameters of lithology, hydraulic conductivity, and rock quality designation index (RQD) at 400--500 meters below ground surface in an area around the Aespoe Hard Rock Laboratory in southeastern Sweden
Gstat: a program for geostatistical modelling, prediction and simulation
Pebesma, Edzer J.; Wesseling, Cees G.
1998-01-01
Gstat is a computer program for variogram modelling, and geostatistical prediction and simulation. It provides a generic implementation of the multivariable linear model with trends modelled as a linear function of coordinate polynomials or of user-defined base functions, and independent or dependent, geostatistically modelled, residuals. Simulation in gstat comprises conditional or unconditional (multi-) Gaussian sequential simulation of point values or block averages, or (multi-) indicator sequential simulation. Besides many of the popular options found in other geostatistical software packages, gstat offers the unique combination of (i) an interactive user interface for modelling variograms and generalized covariances (residual variograms), that uses the device-independent plotting program gnuplot for graphical display, (ii) support for several ascii and binary data and map file formats for input and output, (iii) a concise, intuitive and flexible command language, (iv) user customization of program defaults, (v) no built-in limits, and (vi) free, portable ANSI-C source code. This paper describes the class of problems gstat can solve, and addresses aspects of efficiency and implementation, managing geostatistical projects, and relevant technical details.
Constrained optimisation of spatial sampling : a geostatistical approach
Groenigen, van J.W.
1999-01-01
This thesis aims at the development of optimal sampling strategies for geostatistical studies. Special emphasis is on the optimal use of ancillary data, such as co-related imagery, preliminary observations and historic knowledge. Although the object of all studies
Estimating Rainfall in Rodrigues by Geostatistics: (A) Theory | Proag ...
African Journals Online (AJOL)
This paper introduces the geostatistical method. Originally devised to treat problems that arise when conventional statistical theory is used in estimating changes in ore grade within a mine, it is, however, an abstract theory of statistical behaviour that is applicable to many circumstances in different areas of geology and other ...
A non-convex variational approach to photometric stereo under inaccurate lighting
DEFF Research Database (Denmark)
Quéau, Yvain; Wu, Tao; Lauze, Francois Bernard
2017-01-01
This paper tackles the photometric stereo problem in the presence of inaccurate lighting, obtained either by calibration or by an uncalibrated photometric stereo method. Based on a precise modeling of noise and outliers, a robust variational approach is introduced. It explicitly accounts for self...
Association between inaccurate estimation of body size and obesity in schoolchildren
Directory of Open Access Journals (Sweden)
Larissa da Cunha Feio Costa
2015-12-01
Full Text Available Objectives: To investigate the prevalence of inaccurate estimation of own body size among Brazilian schoolchildren of both sexes aged 7-10 years, and to test whether overweight/obesity; excess body fat and central obesity are associated with inaccuracy. Methods: Accuracy of body size estimation was assessed using the Figure Rating Scale for Brazilian Children. Multinomial logistic regression was used to analyze associations. Results: The overall prevalence of inaccurate body size estimation was 76%, with 34% of the children underestimating their body size and 42% overestimating their body size. Obesity measured by body mass index was associated with underestimation of body size in both sexes, while central obesity was only associated with overestimation of body size among girls. Conclusions: The results of this study suggest there is a high prevalence of inaccurate body size estimation and that inaccurate estimation is associated with obesity. Accurate estimation of own body size is important among obese schoolchildren because it may be the first step towards adopting healthy lifestyle behaviors.
Boer, Hendrik; Emons, P.A.A.; Emons, P.A.A.
2004-01-01
We assessed the relation between accurate beliefs about HIV transmission and inaccurate beliefs about HIV transmission and emotional reactions to people with AIDS (PWA) and AIDS risk groups, stigmatizing attitudes and motivation to protect from HIV. In Chiang Rai, northern Thailand, 219 respondents
Leg mass characteristics of accurate and inaccurate kickers--an Australian football perspective.
Hart, Nicolas H; Nimphius, Sophia; Cochrane, Jodie L; Newton, Robert U
2013-01-01
Athletic profiling provides valuable information to sport scientists, assisting in the optimal design of strength and conditioning programmes. Understanding the influence these physical characteristics may have on the generation of kicking accuracy is advantageous. The aim of this study was to profile and compare the lower limb mass characteristics of accurate and inaccurate Australian footballers. Thirty-one players were recruited from the Western Australian Football League to perform ten drop punt kicks over 20 metres to a player target. Players were separated into accurate (n = 15) and inaccurate (n = 16) groups, with leg mass characteristics assessed using whole body dual energy x-ray absorptiometry (DXA) scans. Accurate kickers demonstrated significantly greater relative lean mass (P ≤ 0.004) and significantly lower relative fat mass (P ≤ 0.024) across all segments of the kicking and support limbs, while also exhibiting significantly higher intra-limb lean-to-fat mass ratios for all segments across both limbs (P ≤ 0.009). Inaccurate kickers also produced significantly larger asymmetries between limbs than accurate kickers (P ≤ 0.028), showing considerably lower lean mass in their support leg. These results illustrate a difference in leg mass characteristics between accurate and inaccurate kickers, highlighting the potential influence these may have on technical proficiency of the drop punt.
Directory of Open Access Journals (Sweden)
Alinune N Kabaghe
Full Text Available In the context of malaria elimination, interventions will need to target high burden areas to further reduce transmission. Current tools to monitor and report disease burden lack the capacity to continuously detect fine-scale spatial and temporal variations of disease distribution exhibited by malaria. These tools use random sampling techniques that are inefficient for capturing underlying heterogeneity while health facility data in resource-limited settings are inaccurate. Continuous community surveys of malaria burden provide real-time results of local spatio-temporal variation. Adaptive geostatistical design (AGD improves prediction of outcome of interest compared to current random sampling techniques. We present findings of continuous malaria prevalence surveys using an adaptive sampling design.We conducted repeated cross sectional surveys guided by an adaptive sampling design to monitor the prevalence of malaria parasitaemia and anaemia in children below five years old in the communities living around Majete Wildlife Reserve in Chikwawa district, Southern Malawi. AGD sampling uses previously collected data to sample new locations of high prediction variance or, where prediction exceeds a set threshold. We fitted a geostatistical model to predict malaria prevalence in the area.We conducted five rounds of sampling, and tested 876 children aged 6-59 months from 1377 households over a 12-month period. Malaria prevalence prediction maps showed spatial heterogeneity and presence of hotspots-where predicted malaria prevalence was above 30%; predictors of malaria included age, socio-economic status and ownership of insecticide-treated mosquito nets.Continuous malaria prevalence surveys using adaptive sampling increased malaria prevalence prediction accuracy. Results from the surveys were readily available after data collection. The tool can assist local managers to target malaria control interventions in areas with the greatest health impact and is
Karabulut, Nevzat
2017-03-01
The aim of this study is to investigate the frequency of incorrect citations and its effects on the impact factor of a specific biomedical journal: the American Journal of Roentgenology. The Cited Reference Search function of Thomson Reuters' Web of Science database (formerly the Institute for Scientific Information's Web of Knowledge database) was used to identify erroneous citations. This was done by entering the journal name into the Cited Work field and entering "2011-2012" into the Cited Year(s) field. The errors in any part of the inaccurately cited references (e.g., author names, title, year, volume, issue, and page numbers) were recorded, and the types of errors (i.e., absent, deficient, or mistyped) were analyzed. Erroneous citations were corrected using the Suggest a Correction function of the Web of Science database. The effect of inaccurate citations on the impact factor of the AJR was calculated. Overall, 183 of 1055 citable articles published in 2011-2012 were inaccurately cited 423 times (mean [± SD], 2.31 ± 4.67 times; range, 1-44 times). Of these 183 articles, 110 (60.1%) were web-only articles and 44 (24.0%) were print articles. The most commonly identified errors were page number errors (44.8%) and misspelling of an author's name (20.2%). Incorrect citations adversely affected the impact factor of the AJR by 0.065 in 2012 and by 0.123 in 2013. Inaccurate citations are not infrequent in biomedical journals, yet they can be detected and corrected using the Web of Science database. Although the accuracy of references is primarily the responsibility of authors, the journal editorial office should also define a periodic inaccurate citation check task and correct erroneous citations to reclaim unnecessarily lost credit.
4th European Conference on Geostatistics for Environmental Applications
Carrera, Jesus; Gómez-Hernández, José
2004-01-01
The fourth edition of the European Conference on Geostatistics for Environmental Applications (geoENV IV) took place in Barcelona, November 27-29, 2002. As a proof that there is an increasing interest in environmental issues in the geostatistical community, the conference attracted over 100 participants, mostly Europeans (up to 10 European countries were represented), but also from other countries in the world. Only 46 contributions, selected out of around 100 submitted papers, were invited to be presented orally during the conference. Additionally 30 authors were invited to present their work in poster format during a special session. All oral and poster contributors were invited to submit their work to be considered for publication in this Kluwer series. All papers underwent a reviewing process, which consisted on two reviewers for oral presentations and one reviewer for posters. The book opens with one keynote paper by Philippe Naveau. It is followed by 40 papers that correspond to those presented orally d...
Geostatistics applied to estimation of uranium bearing ore reserves
International Nuclear Information System (INIS)
Urbina Galan, L.I.
1982-01-01
A computer assisted method for assessing uranium-bearing ore deposit reserves is analyzed. Determinations of quality-thickness, namely quality by thickness calculations of mineralization, were obtained by means of a mathematical method known as the theory of rational variables for each drill-hole layer. Geostatistical results were derived based on a Fortrand computer program on a DEC 20/40 system. (author)
On testing the missing at random assumption
DEFF Research Database (Denmark)
Jaeger, Manfred
2006-01-01
Most approaches to learning from incomplete data are based on the assumption that unobserved values are missing at random (mar). While the mar assumption, as such, is not testable, it can become testable in the context of other distributional assumptions, e.g. the naive Bayes assumption...
2nd European Conference on Geostatistics for Environmental Applications
Soares, Amílcar; Froidevaux, Roland
1999-01-01
The Second European Conference on Geostatistics for Environmental Ap plications took place in Valencia, November 18-20, 1998. Two years have past from the first meeting in Lisbon and the geostatistical community has kept active in the environmental field. In these days of congress inflation, we feel that continuity can only be achieved by ensuring quality in the papers. For this reason, all papers in the book have been reviewed by, at least, two referees, and care has been taken to ensure that the reviewer comments have been incorporated in the final version of the manuscript. We are thankful to the members of the scientific committee for their timely review of the scripts. All in all, there are three keynote papers from experts in soil science, climatology and ecology and 43 contributed papers providing a good indication of the status of geostatistics as applied in the environ mental field all over the world. We feel now confident that the geoENV conference series, seeded around a coffee table almost six...
3D vadose zone modeling using geostatistical inferences
International Nuclear Information System (INIS)
Knutson, C.F.; Lee, C.B.
1991-01-01
In developing a 3D model of the 600 ft thick interbedded basalt and sediment complex that constitutes the vadose zone at the Radioactive Waste Management Complex (RWMC) at the Idaho National Engineering Laboratory (INEL) geostatistical data were captured for 12--15 parameters (e.g. permeability, porosity, saturation, etc. and flow height, flow width, flow internal zonation, etc.). This two scale data set was generated from studies of subsurface core and geophysical log suites at RWMC and from surface outcrop exposures located at the Box Canyon of the Big Lost River and from Hell's Half Acre lava field all located in the general RWMC area. Based on these currently available data, it is possible to build a 3D stochastic model that utilizes: cumulative distribution functions obtained from the geostatistical data; backstripping and rebuilding of stratigraphic units; an ''expert'' system that incorporates rules based on expert geologic analysis and experimentally derived geostatistics for providing: (a) a structural and isopach map of each layer, (b) a realization of the flow geometry of each basalt flow unit, and (c) a realization of the internal flow parameters (eg permeability, porosity, and saturation) for each flow. 10 refs., 4 figs., 1 tab
Geostatistical methodology for waste optimization of contaminated premises - 59344
International Nuclear Information System (INIS)
Desnoyers, Yvon; Dubot, Didier
2012-01-01
The presented methodological study illustrates a Geo-statistical approach suitable for radiological evaluation in nuclear premises. The waste characterization is mainly focused on floor concrete surfaces. By modeling the spatial continuity of activities, Geo-statistics provide sound methods to estimate and map radiological activities, together with their uncertainty. The multivariate approach allows the integration of numerous surface radiation measurements in order to improve the estimation of activity levels from concrete samples. This way, a sequential and iterative investigation strategy proves to be relevant to fulfill the different evaluation objectives. Waste characterization is performed on risk maps rather than on direct interpolation maps (due to bias of the selection on kriging results). The use of several estimation supports (punctual, 1 m 2 , room) allows a relevant radiological waste categorization thanks to cost-benefit analysis according to the risk of exceeding a given activity threshold. Global results, mainly total activity, are similarly quantified to precociously lead the waste management for the dismantling and decommissioning project. This paper recalled the geo-statistics principles and demonstrated how this methodology provides innovative tools for the radiological evaluation of contaminated premises. The relevance of this approach relies on the presence of a spatial continuity for radiological contamination. In this case, geo-statistics provides reliable activity estimates, uncertainty quantification and risk analysis, which are essential decision-making tools for decommissioning and dismantling projects of nuclear installations. Waste characterization is then performed taking all relevant information into account: historical knowledge, surface measurements and samples. Thanks to the multivariate processing, the different investigation stages can be rationalized as regards quantity and positioning. Waste characterization is finally
International Nuclear Information System (INIS)
Xu Xiao; Wei Xuyong; Ling Qi; Wang Kai; Bao Haiwei; Xie Haiyang; Zhou Lin; Zheng Shusen
2012-01-01
Backgrounds and aims: Accurate assessment of graft bile duct is important to plan surgical procedure. Magnetic resonance cholangiopancreatography (MRCP) has become an important diagnostic procedure in evaluation of pancreaticobiliary ductal abnormalities and has been reported as highly accurate. We aim to estimate the efficacy of preoperative MRCP on depicting biliary anatomy in living donor liver transplantation (LDLT), and to determine whether inaccurate preoperative imaging assessment would increase the biliary complications after LDLT. Methods: The data of 118 cases LDLT were recorded. Information from preoperative MRCP was assessed using intraoperative cholangiography (IOC) as the gold standard. The possible risk factors of recipient biliary complications were analyzed. Results: Of 118 donors, 84 had normal anatomy (type A) and 34 had anatomic variants (19 cases of type B, 9 cases of type C, 1 case of type E, 2 cases of type F and 3 cases of type I) confirmed by IOC. MRCP correctly predicted all 84 normal cases and 17 of 34 variant cases, and showed an accuracy of 85.6% (101/118). The incidence of biliary complications was comparable between cases with accurate and inaccurate classification of biliary tree from MRCP, and between cases with normal and variant anatomy of bile duct. While cases with graft duct opening ≤5 mm showed a significant higher incidence of total biliary complications (21.1% vs. 6.6%, P = 0.028) and biliary stricture (10.5% vs. 1.6%, P = 0.041) compared with cases with large duct opening >5 mm. Conclusion: MRCP could correctly predict normal but not variant biliary anatomy. Inaccurate assessment of biliary anatomy from MRCP not increases the rate of biliary complications, while small-sized graft duct may cause an increase in biliary complications particularly biliary stricture after LDLT.
Near-Nash equilibrium strategies for LQ differential games with inaccurate state information
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available ε -Nash equilibrium or “near equilibrium” for a linear quadratic cost game is considered. Due to inaccurate state information, the standard solution for feedback Nash equilibrium cannot be applied. Instead, an estimation of the players' states is substituted into the optimal control strategies equation obtained for perfect state information. The magnitude of the ε in the ε -Nash equilibrium will depend on the quality of the estimation process. To illustrate this approach, a Luenberger-type observer is used in the numerical example to generate the players' state estimates in a two-player non-zero-sum LQ differential game.
Geostatistical ore reserve estimation for a roll-front type uranium deposit (practitioner's guide)
International Nuclear Information System (INIS)
Kim, Y.C.; Knudsen, H.P.
1977-01-01
This report comprises two parts. Part I contains illustrative examples of each phase of a geostatistical study using a roll-front type uranium deposit. Part II contains five computer programs and comprehensive users' manuals for these programs which are necessary to make a practical geostatistical study
Risk Assessment of Sediment Pollution Using Geostatistical Simulations
Golay, J.; Kanevski, M.
2012-04-01
Environmental monitoring networks (EMN) discreetly measure the intensities of continuous phenomena (e.g. pollution, temperature, etc.). Spatial prediction models, like kriging, are then used for modeling. But, they give rise to smooth representations of phenomena which leads to overestimations or underestimations of extreme values. Moreover, they do not reproduce the spatial variability of the original data and the corresponding uncertainties. When dealing with risk assessment, this is unacceptable, since extreme values must be retrieved and probabilities of exceeding given thresholds must be computed [Kanevski et al., 2009]. In order to overcome these obstacles, geostatistics provides another approach: conditional stochastic simulations. Here, the basic idea is to generate multiple estimates of variable values (e.g. pollution concentration) at every location of interest which are calculated as stochastic realizations of an unknown random function (see, for example, [Kanevski, 2008], where both theoretical concepts and real data case studies are presented in detail). Many algorithms implement this approach. The most widely used in spatial modeling are sequential Gaussian simulations/cosimulations, sequential indicator simulations/cosimulations and direct simulations. In the present study, several algorithms of geostatistical conditional simulations were applied on real data collected from Lake Geneva. The main objectives were to compare their effectiveness in reproducing global statistics (histograms, variograms) and the way they characterize the variability and uncertainty of the contamination patterns. The dataset is composed of 200 measurements of the contamination of the lake sediments by heavy metals (i.e. Cadmium, Mercury, Zinc, Copper, Titanium and Chromium). The results obtained show some differences highlighting that risk assessment can be influenced by the algorithm it relies on. Moreover, hybrid models based on machine learning algorithms and
Data analysis for radiological characterisation: Geostatistical and statistical complementarity
International Nuclear Information System (INIS)
Desnoyers, Yvon; Dubot, Didier
2012-01-01
Radiological characterisation may cover a large range of evaluation objectives during a decommissioning and dismantling (D and D) project: removal of doubt, delineation of contaminated materials, monitoring of the decontamination work and final survey. At each stage, collecting relevant data to be able to draw the conclusions needed is quite a big challenge. In particular two radiological characterisation stages require an advanced sampling process and data analysis, namely the initial categorization and optimisation of the materials to be removed and the final survey to demonstrate compliance with clearance levels. On the one hand the latter is widely used and well developed in national guides and norms, using random sampling designs and statistical data analysis. On the other hand a more complex evaluation methodology has to be implemented for the initial radiological characterisation, both for sampling design and for data analysis. The geostatistical framework is an efficient way to satisfy the radiological characterisation requirements providing a sound decision-making approach for the decommissioning and dismantling of nuclear premises. The relevance of the geostatistical methodology relies on the presence of a spatial continuity for radiological contamination. Thus geo-statistics provides reliable methods for activity estimation, uncertainty quantification and risk analysis, leading to a sound classification of radiological waste (surfaces and volumes). This way, the radiological characterization of contaminated premises can be divided into three steps. First, the most exhaustive facility analysis provides historical and qualitative information. Then, a systematic (exhaustive or not) surface survey of the contamination is implemented on a regular grid. Finally, in order to assess activity levels and contamination depths, destructive samples are collected at several locations within the premises (based on the surface survey results) and analysed. Combined with
Mercury emissions from coal combustion in Silesia, analysis using geostatistics
Zasina, Damian; Zawadzki, Jaroslaw
2015-04-01
Data provided by the UNEP's report on mercury [1] shows that solid fuel combustion in significant source of mercury emission to air. Silesia, located in southwestern Poland, is notably affected by mercury emission due to being one of the most industrialized Polish regions: the place of coal mining, production of metals, stone mining, mineral quarrying and chemical industry. Moreover, Silesia is the region with high population density. People are exposed to severe risk of mercury emitted from both: industrial and domestic sources (i.e. small household furnaces). Small sources have significant contribution to total emission of mercury. Official and statistical analysis, including prepared for international purposes [2] did not provide data about spatial distribution of the mercury emitted to air, however number of analysis on Polish public power and energy sector had been prepared so far [3; 4]. The distribution of locations exposed for mercury emission from small domestic sources is interesting matter merging information from various sources: statistical, economical and environmental. This paper presents geostatistical approach to distibution of mercury emission from coal combustion. Analysed data organized in 2 independent levels: individual, bottom-up approach derived from national emission reporting system [5; 6] and top down - regional data calculated basing on official statistics [7]. Analysis, that will be presented, will include comparison of spatial distributions of mercury emission using data derived from sources mentioned above. Investigation will include three voivodeships of Poland: Lower Silesian, Opole (voivodeship) and Silesian using selected geostatistical methodologies including ordinary kriging [8]. References [1] UNEP. Global Mercury Assessment 2013: Sources, Emissions, Releases and Environmental Transport. UNEP Chemicals Branch, Geneva, Switzerland, 2013. [2] NCEM. Poland's Informative Inventory Report 2014. NCEM at the IEP-NRI, 2014. http
Inverting reflections using full-waveform inversion with inaccurate starting models
AlTheyab, Abdullah
2015-08-19
We present a method for inverting seismic reflections using full-waveform inversion (FWI) with inaccurate starting models. For a layered medium, near-offset reflections (with zero angle of incidence) are unlikely to be cycle-skipped regardless of the low-wavenumber velocity error in the initial models. Therefore, we use them as a starting point for FWI, and the subsurface velocity model is then updated during the FWI iterations using reflection wavepaths from varying offsets that are not cycle-skipped. To enhance low-wavenumber updates and accelerate the convergence, we take several passes through the non-linear Gauss-Seidel iterations, where we invert traces from a narrow range of near offsets and finally end at the far offsets. Every pass is followed by applying smoothing to the cumulative slowness update. The smoothing is strong at the early stages and relaxed at later iterations to allow for a gradual reconstruction of the subsurface model in a multiscale manner. Applications to synthetic and field data, starting from inaccurate models, show significant low-wavenumber updates and flattening of common-image gathers after many iterations.
Validating spatial structure in canopy water content using geostatistics
Sanderson, E. W.; Zhang, M. H.; Ustin, S. L.; Rejmankova, E.; Haxo, R. S.
1995-01-01
Heterogeneity in ecological phenomena are scale dependent and affect the hierarchical structure of image data. AVIRIS pixels average reflectance produced by complex absorption and scattering interactions between biogeochemical composition, canopy architecture, view and illumination angles, species distributions, and plant cover as well as other factors. These scales affect validation of pixel reflectance, typically performed by relating pixel spectra to ground measurements acquired at scales of 1m(exp 2) or less (e.g., field spectra, foilage and soil samples, etc.). As image analysis becomes more sophisticated, such as those for detection of canopy chemistry, better validation becomes a critical problem. This paper presents a methodology for bridging between point measurements and pixels using geostatistics. Geostatistics have been extensively used in geological or hydrogeolocial studies but have received little application in ecological studies. The key criteria for kriging estimation is that the phenomena varies in space and that an underlying controlling process produces spatial correlation between the measured data points. Ecological variation meets this requirement because communities vary along environmental gradients like soil moisture, nutrient availability, or topography.
International Nuclear Information System (INIS)
Bambang-Supardiyono; Prayitno
2000-01-01
Accuracy of detector position toward the kidney location (preciseposition) in renography will resulting the maximum count figure, detectorposition change from the precise point (inaccurate) will decreasing the countrate. Therefore for it had been simulated the influence of count figure ofright kidney (fixed left kidney count) ± 5 % to ± 20 % to relativeuptake figure and individual excretion. Based on the calculation it was foundthat the relation of detector position ± 0.5 cm to ± 2 cm from theprecise point will have effect to relative uptake figure ± (1.25 % to 5.00%), the fixed individual excretion figure. The change is still can beaccepted because the qualitative information with 10 % accuracy is stillacceptable. (author)
Inaccurate DNA synthesis in cell extracts of yeast producing active human DNA polymerase iota.
Makarova, Alena V; Grabow, Corinn; Gening, Leonid V; Tarantul, Vyacheslav Z; Tahirov, Tahir H; Bessho, Tadayoshi; Pavlov, Youri I
2011-01-31
Mammalian Pol ι has an unusual combination of properties: it is stimulated by Mn(2+) ions, can bypass some DNA lesions and misincorporates "G" opposite template "T" more frequently than incorporates the correct "A." We recently proposed a method of detection of Pol ι activity in animal cell extracts, based on primer extension opposite the template T with a high concentration of only two nucleotides, dGTP and dATP (incorporation of "G" versus "A" method of Gening, abbreviated as "misGvA"). We provide unambiguous proof of the "misGvA" approach concept and extend the applicability of the method for the studies of variants of Pol ι in the yeast model system with different cation cofactors. We produced human Pol ι in baker's yeast, which do not have a POLI ortholog. The "misGvA" activity is absent in cell extracts containing an empty vector, or producing catalytically dead Pol ι, or Pol ι lacking exon 2, but is robust in the strain producing wild-type Pol ι or its catalytic core, or protein with the active center L62I mutant. The signature pattern of primer extension products resulting from inaccurate DNA synthesis by extracts of cells producing either Pol ι or human Pol η is different. The DNA sequence of the template is critical for the detection of the infidelity of DNA synthesis attributed to DNA Pol ι. The primer/template and composition of the exogenous DNA precursor pool can be adapted to monitor replication fidelity in cell extracts expressing various error-prone Pols or mutator variants of accurate Pols. Finally, we demonstrate that the mutation rates in yeast strains producing human DNA Pols ι and η are not elevated over the control strain, despite highly inaccurate DNA synthesis by their extracts.
Inaccurate DNA synthesis in cell extracts of yeast producing active human DNA polymerase iota.
Directory of Open Access Journals (Sweden)
Alena V Makarova
2011-01-01
Full Text Available Mammalian Pol ι has an unusual combination of properties: it is stimulated by Mn(2+ ions, can bypass some DNA lesions and misincorporates "G" opposite template "T" more frequently than incorporates the correct "A." We recently proposed a method of detection of Pol ι activity in animal cell extracts, based on primer extension opposite the template T with a high concentration of only two nucleotides, dGTP and dATP (incorporation of "G" versus "A" method of Gening, abbreviated as "misGvA". We provide unambiguous proof of the "misGvA" approach concept and extend the applicability of the method for the studies of variants of Pol ι in the yeast model system with different cation cofactors. We produced human Pol ι in baker's yeast, which do not have a POLI ortholog. The "misGvA" activity is absent in cell extracts containing an empty vector, or producing catalytically dead Pol ι, or Pol ι lacking exon 2, but is robust in the strain producing wild-type Pol ι or its catalytic core, or protein with the active center L62I mutant. The signature pattern of primer extension products resulting from inaccurate DNA synthesis by extracts of cells producing either Pol ι or human Pol η is different. The DNA sequence of the template is critical for the detection of the infidelity of DNA synthesis attributed to DNA Pol ι. The primer/template and composition of the exogenous DNA precursor pool can be adapted to monitor replication fidelity in cell extracts expressing various error-prone Pols or mutator variants of accurate Pols. Finally, we demonstrate that the mutation rates in yeast strains producing human DNA Pols ι and η are not elevated over the control strain, despite highly inaccurate DNA synthesis by their extracts.
How Symmetrical Assumptions Advance Strategic Management Research
DEFF Research Database (Denmark)
Foss, Nicolai Juul; Hallberg, Hallberg
2014-01-01
We develop the case for symmetrical assumptions in strategic management theory. Assumptional symmetry obtains when assumptions made about certain actors and their interactions in one of the application domains of a theory are also made about this set of actors and their interactions in other...... application domains of the theory. We argue that assumptional symmetry leads to theoretical advancement by promoting the development of theory with greater falsifiability and stronger ontological grounding. Thus, strategic management theory may be advanced by systematically searching for asymmetrical...
Wrong assumptions in the financial crisis
Aalbers, M.B.
2009-01-01
Purpose - The purpose of this paper is to show how some of the assumptions about the current financial crisis are wrong because they misunderstand what takes place in the mortgage market. Design/methodology/approach - The paper discusses four wrong assumptions: one related to regulation, one to
The relevance of ''theory rich'' bridge assumptions
Lindenberg, S
1996-01-01
Actor models are increasingly being used as a form of theory building in sociology because they can better represent the caul mechanisms that connect macro variables. However, actor models need additional assumptions, especially so-called bridge assumptions, for filling in the relatively empty
A Geostatistical Approach to Indoor Surface Sampling Strategies
DEFF Research Database (Denmark)
Schneider, Thomas; Petersen, Ole Holm; Nielsen, Allan Aasbjerg
1990-01-01
Particulate surface contamination is of concern in production industries such as food processing, aerospace, electronics and semiconductor manufacturing. There is also an increased awareness that surface contamination should be monitored in industrial hygiene surveys. A conceptual and theoretical...... framework for designing sampling strategies is thus developed. The distribution and spatial correlation of surface contamination can be characterized using concepts from geostatistical science, where spatial applications of statistics is most developed. The theory is summarized and particulate surface...... contamination, sampled from small areas on a table, have been used to illustrate the method. First, the spatial correlation is modelled and the parameters estimated from the data. Next, it is shown how the contamination at positions not measured can be estimated with kriging, a minimum mean square error method...
Geostatistical modeling of groundwater properties and assessment of their uncertainties
International Nuclear Information System (INIS)
Honda, Makoto; Yamamoto, Shinya; Sakurai, Hideyuki; Suzuki, Makoto; Sanada, Hiroyuki; Matsui, Hiroya; Sugita, Yutaka
2010-01-01
The distribution of groundwater properties is important for understanding of the deep underground hydrogeological environments. This paper proposes a geostatistical system for modeling the groundwater properties which have a correlation with the ground resistivity data obtained from widespread and exhaustive survey. That is, the methodology for the integration of resistivity data measured by various methods and the methodology for modeling the groundwater properties using the integrated resistivity data has been developed. The proposed system has also been validated using the data obtained in the Horonobe Underground Research Laboratory project. Additionally, the quantification of uncertainties in the estimated model has been tried by numerical simulations based on the data. As a result, the uncertainties of the proposal model have been estimated lower than other traditional model's. (author)
Indoor radon variations in central Iran and its geostatistical map
Hadad, Kamal; Mokhtari, Javad
2015-02-01
We present the results of 2 year indoor radon survey in 10 cities of Yazd province in Central Iran (covering an area of 80,000 km2). We used passive diffusive samplers with LATEX polycarbonate films as Solid State Nuclear Track Detector (SSNTD). This study carried out in central Iran where there are major minerals and uranium mines. Our results indicate that despite few extraordinary high concentrations, average annual concentrations of indoor radon are within ICRP guidelines. When geostatistical spatial distribution of radon mapped onto geographical features of the province it was observed that risk of high radon concentration increases near the Saqand, Bafq, Harat and Abarkooh cities, this depended on the elevation and vicinity of the ores and mines.
The use of sequential indicator simulation to characterize geostatistical uncertainty
International Nuclear Information System (INIS)
Hansen, K.M.
1992-10-01
Sequential indicator simulation (SIS) is a geostatistical technique designed to aid in the characterization of uncertainty about the structure or behavior of natural systems. This report discusses a simulation experiment designed to study the quality of uncertainty bounds generated using SIS. The results indicate that, while SIS may produce reasonable uncertainty bounds in many situations, factors like the number and location of available sample data, the quality of variogram models produced by the user, and the characteristics of the geologic region to be modeled, can all have substantial effects on the accuracy and precision of estimated confidence limits. It is recommended that users of SIS conduct validation studies for the technique on their particular regions of interest before accepting the output uncertainty bounds
Geostatistical Analysis Methods for Estimation of Environmental Data Homogeneity
Directory of Open Access Journals (Sweden)
Aleksandr Danilov
2018-01-01
Full Text Available The methodology for assessing the spatial homogeneity of ecosystems with the possibility of subsequent zoning of territories in terms of the degree of disturbance of the environment is considered in the study. The degree of pollution of the water body was reconstructed on the basis of hydrochemical monitoring data and information on the level of the technogenic load in one year. As a result, the greatest environmental stress zones were isolated and correct zoning using geostatistical analysis techniques was proved. Mathematical algorithm computing system was implemented in an object-oriented programming C #. A software application has been obtained that allows quickly assessing the scale and spatial localization of pollution during the initial analysis of the environmental situation.
Energy Technology Data Exchange (ETDEWEB)
Cassiraga, E F; Gomez-Hernandez, J J [Departamento de Ingenieria Hidraulica y Medio Ambiente, Universidad Politecnica de Valencia, Valencia (Spain)
1996-10-01
The main objective of this report is to describe the different geostatistical techniques to use the geophysical and hydrological parameters. We analyze the characteristics of estimation methods used in others studies.
Linear regression and the normality assumption.
Schmidt, Amand F; Finan, Chris
2017-12-16
Researchers often perform arbitrary outcome transformations to fulfill the normality assumption of a linear regression model. This commentary explains and illustrates that in large data settings, such transformations are often unnecessary, and worse may bias model estimates. Linear regression assumptions are illustrated using simulated data and an empirical example on the relation between time since type 2 diabetes diagnosis and glycated hemoglobin levels. Simulation results were evaluated on coverage; i.e., the number of times the 95% confidence interval included the true slope coefficient. Although outcome transformations bias point estimates, violations of the normality assumption in linear regression analyses do not. The normality assumption is necessary to unbiasedly estimate standard errors, and hence confidence intervals and P-values. However, in large sample sizes (e.g., where the number of observations per variable is >10) violations of this normality assumption often do not noticeably impact results. Contrary to this, assumptions on, the parametric model, absence of extreme observations, homoscedasticity, and independency of the errors, remain influential even in large sample size settings. Given that modern healthcare research typically includes thousands of subjects focusing on the normality assumption is often unnecessary, does not guarantee valid results, and worse may bias estimates due to the practice of outcome transformations. Copyright © 2017 Elsevier Inc. All rights reserved.
Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping.
Hampton, Kristen H; Serre, Marc L; Gesink, Dionne C; Pilcher, Christopher D; Miller, William C
2011-10-06
Disease maps of crude rates from routinely collected health data indexed at a small geographical resolution pose specific statistical problems due to the sparse nature of the data. Spatial smoothers allow areas to borrow strength from neighboring regions to produce a more stable estimate of the areal value. Geostatistical smoothers are able to quantify the uncertainty in smoothed rate estimates without a high computational burden. In this paper, we introduce a uniform model extension of Bayesian Maximum Entropy (UMBME) and compare its performance to that of Poisson kriging in measures of smoothing strength and estimation accuracy as applied to simulated data and the real data example of HIV infection in North Carolina. The aim is to produce more reliable maps of disease rates in small areas to improve identification of spatial trends at the local level. In all data environments, Poisson kriging exhibited greater smoothing strength than UMBME. With the simulated data where the true latent rate of infection was known, Poisson kriging resulted in greater estimation accuracy with data that displayed low spatial autocorrelation, while UMBME provided more accurate estimators with data that displayed higher spatial autocorrelation. With the HIV data, UMBME performed slightly better than Poisson kriging in cross-validatory predictive checks, with both models performing better than the observed data model with no smoothing. Smoothing methods have different advantages depending upon both internal model assumptions that affect smoothing strength and external data environments, such as spatial correlation of the observed data. Further model comparisons in different data environments are required to provide public health practitioners with guidelines needed in choosing the most appropriate smoothing method for their particular health dataset.
Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping
Directory of Open Access Journals (Sweden)
Pilcher Christopher D
2011-10-01
Full Text Available Abstract Background Disease maps of crude rates from routinely collected health data indexed at a small geographical resolution pose specific statistical problems due to the sparse nature of the data. Spatial smoothers allow areas to borrow strength from neighboring regions to produce a more stable estimate of the areal value. Geostatistical smoothers are able to quantify the uncertainty in smoothed rate estimates without a high computational burden. In this paper, we introduce a uniform model extension of Bayesian Maximum Entropy (UMBME and compare its performance to that of Poisson kriging in measures of smoothing strength and estimation accuracy as applied to simulated data and the real data example of HIV infection in North Carolina. The aim is to produce more reliable maps of disease rates in small areas to improve identification of spatial trends at the local level. Results In all data environments, Poisson kriging exhibited greater smoothing strength than UMBME. With the simulated data where the true latent rate of infection was known, Poisson kriging resulted in greater estimation accuracy with data that displayed low spatial autocorrelation, while UMBME provided more accurate estimators with data that displayed higher spatial autocorrelation. With the HIV data, UMBME performed slightly better than Poisson kriging in cross-validatory predictive checks, with both models performing better than the observed data model with no smoothing. Conclusions Smoothing methods have different advantages depending upon both internal model assumptions that affect smoothing strength and external data environments, such as spatial correlation of the observed data. Further model comparisons in different data environments are required to provide public health practitioners with guidelines needed in choosing the most appropriate smoothing method for their particular health dataset.
Reyes, J.; Vizuete, W.; Serre, M. L.; Xu, Y.
2015-12-01
The EPA employs a vast monitoring network to measure ambient PM2.5 concentrations across the United States with one of its goals being to quantify exposure within the population. However, there are several areas of the country with sparse monitoring spatially and temporally. One means to fill in these monitoring gaps is to use PM2.5 modeled estimates from Chemical Transport Models (CTMs) specifically the Community Multi-scale Air Quality (CMAQ) model. CMAQ is able to provide complete spatial coverage but is subject to systematic and random error due to model uncertainty. Due to the deterministic nature of CMAQ, often these uncertainties are not quantified. Much effort is employed to quantify the efficacy of these models through different metrics of model performance. Currently evaluation is specific to only locations with observed data. Multiyear studies across the United States are challenging because the error and model performance of CMAQ are not uniform over such large space/time domains. Error changes regionally and temporally. Because of the complex mix of species that constitute PM2.5, CMAQ error is also a function of increasing PM2.5 concentration. To address this issue we introduce a model performance evaluation for PM2.5 CMAQ that is regionalized and non-linear. This model performance evaluation leads to error quantification for each CMAQ grid. Areas and time periods of error being better qualified. The regionalized error correction approach is non-linear and is therefore more flexible at characterizing model performance than approaches that rely on linearity assumptions and assume homoscedasticity of CMAQ predictions errors. Corrected CMAQ data are then incorporated into the modern geostatistical framework of Bayesian Maximum Entropy (BME). Through cross validation it is shown that incorporating error-corrected CMAQ data leads to more accurate estimates than just using observed data by themselves.
Use of geostatistics for remediation planning to transcend urban political boundaries
International Nuclear Information System (INIS)
Milillo, Tammy M.; Sinha, Gaurav; Gardella, Joseph A.
2012-01-01
Soil remediation plans are often dictated by areas of jurisdiction or property lines instead of scientific information. This study exemplifies how geostatistically interpolated surfaces can substantially improve remediation planning. Ordinary kriging, ordinary co-kriging, and inverse distance weighting spatial interpolation methods were compared for analyzing surface and sub-surface soil sample data originally collected by the US EPA and researchers at the University at Buffalo in Hickory Woods, an industrial–residential neighborhood in Buffalo, NY, where both lead and arsenic contamination is present. Past clean-up efforts estimated contamination levels from point samples, but parcel and agency jurisdiction boundaries were used to define remediation sites, rather than geostatistical models estimating the spatial behavior of the contaminants in the soil. Residents were understandably dissatisfied with the arbitrariness of the remediation plan. In this study we show how geostatistical mapping and participatory assessment can make soil remediation scientifically defensible, socially acceptable, and economically feasible. - Highlights: ► Point samples and property boundaries do not appropriately determine the extent of soil contamination. ► Kriging and co-kriging provide best concentration estimates for mapping soil contamination and refining clean-up sites. ► Maps provide a visual representation of geostatistical results to communities to aid in geostatistical decision making. ► Incorporating community input into the assessment of neighborhoods is good public policy practice. - Using geostatistical interpolation and mapping results to involve the affected community can substantially improve remediation planning and promote its long-term effectiveness.
Inaccurate Dental Charting in an Audit of 1128 General Dental Practice Records.
Brown, Nathan L; Jephcote, Victoria E L
2017-03-01
Fourteen dentists at different practices in the UK assessed the dental charts of 1128 patients who were new to the dentist but not new to the practice; 44% of the dental charts were found to be inaccurate. Inaccuracy of the individual practice-based charts ranged between 16% for the best performing practices to 83% for the worst: 5% of dental charts had too many teeth charted and 5% had too few teeth charted; 13% of charts had missed amalgam restorations and 18% had missed tooth-coloured restorations; 5% of charts had amalgam restorations recorded but with the surfaces incorrect (eg an MO restoration charted but a DO restoration actually present); 9% of charts had tooth-coloured restoration surfaces incorrectly recorded. For 7.5% of charts, amalgams were charted but not actually present. Other inaccuracies were also noted. The authors reinforce the requirements of the GDC, the advice of defence organizations, and the forensic importance of accurate dental charts. Clinical relevance: Dental charting forms part of the patient’s dental records, and the GDC requires dentists to maintain complete and accurate dental records.
Location-based Mobile Relay Selection and Impact of Inaccurate Path Loss Model Parameters
DEFF Research Database (Denmark)
Nielsen, Jimmy Jessen; Madsen, Tatiana Kozlova; Schwefel, Hans-Peter
2010-01-01
In this paper we propose a relay selection scheme which uses collected location information together with a path loss model for relay selection, and analyze the performance impact of mobility and different error causes on this scheme. Performance is evaluated in terms of bit error rate...... by simulations. The SNR measurement based relay selection scheme proposed previously is unsuitable for use with fast moving users in e.g. vehicular scenarios due to a large signaling overhead. The proposed location based scheme is shown to work well with fast moving users due to a lower signaling overhead...... in these situations. As the location-based scheme relies on a path loss model to estimate link qualities and select relays, the sensitivity with respect to inaccurate estimates of the unknown path loss model parameters is investigated. The parameter ranges that result in useful performance were found...
Clinical models are inaccurate in predicting bile duct stones in situ for patients with gallbladder.
Topal, B; Fieuws, S; Tomczyk, K; Aerts, R; Van Steenbergen, W; Verslype, C; Penninckx, F
2009-01-01
The probability that a patient has common bile duct stones (CBDS) is a key factor in determining diagnostic and treatment strategies. This prospective cohort study evaluated the accuracy of clinical models in predicting CBDS for patients who will undergo cholecystectomy for lithiasis. From October 2005 until September 2006, 335 consecutive patients with symptoms of gallstone disease underwent cholecystectomy. Statistical analysis was performed on prospective patient data obtained at the time of first presentation to the hospital. Demonstrable CBDS at the time of endoscopic retrograde cholangiopancreatography (ERCP) or intraoperative cholangiography (IOC) was considered the gold standard for the presence of CBDS. Common bile duct stones were demonstrated in 53 patients. For 35 patients, ERCP was performed, with successful stone clearance in 24 of 30 patients who had proven CBDS. In 29 patients, IOC showed CBDS, which were managed successfully via laparoscopic common bile duct exploration, with stone extraction at the time of cholecystectomy. Prospective validation of the existing model for CBDS resulted in a predictive accuracy rate of 73%. The new model showed a predictive accuracy rate of 79%. Clinical models are inaccurate in predicting CBDS in patients with cholelithiasis. Management strategies should be based on the local availability of therapeutic expertise.
Chua, Elizabeth F; Hannula, Deborah E; Ranganath, Charan
2012-01-01
It is generally believed that accuracy and confidence in one's memory are related, but there are many instances when they diverge. Accordingly it is important to disentangle the factors that contribute to memory accuracy and confidence, especially those factors that contribute to confidence, but not accuracy. We used eye movements to separately measure fluent cue processing, the target recognition experience, and relative evidence assessment on recognition confidence and accuracy. Eye movements were monitored during a face-scene associative recognition task, in which participants first saw a scene cue, followed by a forced-choice recognition test for the associated face, with confidence ratings. Eye movement indices of the target recognition experience were largely indicative of accuracy, and showed a relationship to confidence for accurate decisions. In contrast, eye movements during the scene cue raised the possibility that more fluent cue processing was related to higher confidence for both accurate and inaccurate recognition decisions. In a second experiment we manipulated cue familiarity, and therefore cue fluency. Participants showed higher confidence for cue-target associations for when the cue was more familiar, especially for incorrect responses. These results suggest that over-reliance on cue familiarity and under-reliance on the target recognition experience may lead to erroneous confidence.
Chan, George C. Y. [Bloomington, IN; Hieftje, Gary M [Bloomington, IN
2010-08-03
A method for detecting and correcting inaccurate results in inductively coupled plasma-atomic emission spectrometry (ICP-AES). ICP-AES analysis is performed across a plurality of selected locations in the plasma on an unknown sample, collecting the light intensity at one or more selected wavelengths of one or more sought-for analytes, creating a first dataset. The first dataset is then calibrated with a calibration dataset creating a calibrated first dataset curve. If the calibrated first dataset curve has a variability along the location within the plasma for a selected wavelength, errors are present. Plasma-related errors are then corrected by diluting the unknown sample and performing the same ICP-AES analysis on the diluted unknown sample creating a calibrated second dataset curve (accounting for the dilution) for the one or more sought-for analytes. The cross-over point of the calibrated dataset curves yields the corrected value (free from plasma related errors) for each sought-for analyte.
Inaccurate pulse CO-oximetry of carboxyhemoglobin due to digital clubbing: case report.
Harlan, Nicole; Weaver, Lindell K; Deru, Kayla
2016-01-01
Newer pulse CO-oximeters provide a non-invasive and quick means of measuring oxyhemoglobin, carboxyhemoglobin and methemoglobin. Clubbing has been reported to cause inaccuracy in pulse oximeters. We present a case of inaccurate carboxy-hemoglobin measurement by pulse CO-oximetry due to digital clubbing. An 18-year-old man with a history of cystic fibrosis presented after a suicide attempt by inhalation of exhaust. At the initial emergency department evaluation, his blood carboxyhemoglobin was 33%. He was intubated, placed on 100% oxygen and transferred to our facility. Upon arrival, we placed three different pulse CO-oximeters on different fingers and toes. Carboxyhemoglobin levels measured by these meters ranged from 9%-11%. A venous blood gas drawn on arrival showed a carboxyhemoglobin level of 2.3% after four hours on 100% oxygen by endotracheal tube. Thirty minutes later, we checked arterial blood gas, which revealed a COHb level of 0.9%. Again, non-invasive carboxyhemoglobin measurements read 10%. The patient was treated with hyperbaric oxygen for carbon monoxide poisoning. This case suggests that non-invasive measurements of carboxyhemoglobin should be correlated with the clinic history and with an arterial or venous blood gas oximetry analysis.
Formalization and Analysis of Reasoning by Assumption
Bosse, T.; Jonker, C.M.; Treur, J.
2006-01-01
This article introduces a novel approach for the analysis of the dynamics of reasoning processes and explores its applicability for the reasoning pattern called reasoning by assumption. More specifically, for a case study in the domain of a Master Mind game, it is shown how empirical human reasoning traces can be formalized and automatically analyzed against dynamic properties they fulfill. To this end, for the pattern of reasoning by assumption a variety of dynamic properties have been speci...
Uniform background assumption produces misleading lung EIT images.
Grychtol, Bartłomiej; Adler, Andy
2013-06-01
Electrical impedance tomography (EIT) estimates an image of conductivity change within a body from stimulation and measurement at body surface electrodes. There is significant interest in EIT for imaging the thorax, as a monitoring tool for lung ventilation. To be useful in this application, we require an understanding of if and when EIT images can produce inaccurate images. In this paper, we study the consequences of the homogeneous background assumption, frequently made in linear image reconstruction, which introduces a mismatch between the reference measurement and the linearization point. We show in simulation and experimental data that the resulting images may contain large and clinically significant errors. A 3D finite element model of thorax conductivity is used to simulate EIT measurements for different heart and lung conductivity, size and position, as well as different amounts of gravitational collapse and ventilation-associated conductivity change. Three common linear EIT reconstruction algorithms are studied. We find that the asymmetric position of the heart can cause EIT images of ventilation to show up to 60% undue bias towards the left lung and that the effect is particularly strong for a ventilation distribution typical of mechanically ventilated patients. The conductivity gradient associated with gravitational lung collapse causes conductivity changes in non-dependent lung to be overestimated by up to 100% with respect to the dependent lung. Eliminating the mismatch by using a realistic conductivity distribution in the forward model of the reconstruction algorithm strongly reduces these undesirable effects. We conclude that subject-specific anatomically accurate forward models should be used in lung EIT and extra care is required when analysing EIT images of subjects whose background conductivity distribution in the lungs is known to be heterogeneous or exhibiting large changes.
Uniform background assumption produces misleading lung EIT images
International Nuclear Information System (INIS)
Grychtol, Bartłomiej; Adler, Andy
2013-01-01
Electrical impedance tomography (EIT) estimates an image of conductivity change within a body from stimulation and measurement at body surface electrodes. There is significant interest in EIT for imaging the thorax, as a monitoring tool for lung ventilation. To be useful in this application, we require an understanding of if and when EIT images can produce inaccurate images. In this paper, we study the consequences of the homogeneous background assumption, frequently made in linear image reconstruction, which introduces a mismatch between the reference measurement and the linearization point. We show in simulation and experimental data that the resulting images may contain large and clinically significant errors. A 3D finite element model of thorax conductivity is used to simulate EIT measurements for different heart and lung conductivity, size and position, as well as different amounts of gravitational collapse and ventilation-associated conductivity change. Three common linear EIT reconstruction algorithms are studied. We find that the asymmetric position of the heart can cause EIT images of ventilation to show up to 60% undue bias towards the left lung and that the effect is particularly strong for a ventilation distribution typical of mechanically ventilated patients. The conductivity gradient associated with gravitational lung collapse causes conductivity changes in non-dependent lung to be overestimated by up to 100% with respect to the dependent lung. Eliminating the mismatch by using a realistic conductivity distribution in the forward model of the reconstruction algorithm strongly reduces these undesirable effects. We conclude that subject-specific anatomically accurate forward models should be used in lung EIT and extra care is required when analysing EIT images of subjects whose background conductivity distribution in the lungs is known to be heterogeneous or exhibiting large changes. (paper)
Neugebauer, Romain; Fireman, Bruce; Roy, Jason A; Raebel, Marsha A; Nichols, Gregory A; O'Connor, Patrick J
2013-08-01
Clinical trials are unlikely to ever be launched for many comparative effectiveness research (CER) questions. Inferences from hypothetical randomized trials may however be emulated with marginal structural modeling (MSM) using observational data, but success in adjusting for time-dependent confounding and selection bias typically relies on parametric modeling assumptions. If these assumptions are violated, inferences from MSM may be inaccurate. In this article, we motivate the application of a data-adaptive estimation approach called super learning (SL) to avoid reliance on arbitrary parametric assumptions in CER. Using the electronic health records data from adults with new-onset type 2 diabetes, we implemented MSM with inverse probability weighting (IPW) estimation to evaluate the effect of three oral antidiabetic therapies on the worsening of glomerular filtration rate. Inferences from IPW estimation were noticeably sensitive to the parametric assumptions about the associations between both the exposure and censoring processes and the main suspected source of confounding, that is, time-dependent measurements of hemoglobin A1c. SL was successfully implemented to harness flexible confounding and selection bias adjustment from existing machine learning algorithms. Erroneous IPW inference about clinical effectiveness because of arbitrary and incorrect modeling decisions may be avoided with SL. Copyright © 2013 Elsevier Inc. All rights reserved.
Heritability of slow and/or inaccurate reading ability in 33,000 adult twins with self-reported data
DEFF Research Database (Denmark)
Fibiger-Dagnæs, Steen; von Bornemann Hjelmborg, Jacob; Erbs, Lena
2012-01-01
Genetic influence for adult slow and/or inaccurate reading ability was studied from selfreported answers, using a dichotomous question on having difficulties in reading the Danish subtitles on foreign TV programs. The data from 33,424 twins were population based and were used for biometric analys...
Monitoring Assumptions in Assume-Guarantee Contracts
Directory of Open Access Journals (Sweden)
Oleg Sokolsky
2016-05-01
Full Text Available Pre-deployment verification of software components with respect to behavioral specifications in the assume-guarantee form does not, in general, guarantee absence of errors at run time. This is because assumptions about the environment cannot be discharged until the environment is fixed. An intuitive approach is to complement pre-deployment verification of guarantees, up to the assumptions, with post-deployment monitoring of environment behavior to check that the assumptions are satisfied at run time. Such a monitor is typically implemented by instrumenting the application code of the component. An additional challenge for the monitoring step is that environment behaviors are typically obtained through an I/O library, which may alter the component's view of the input format. This transformation requires us to introduce a second pre-deployment verification step to ensure that alarms raised by the monitor would indeed correspond to violations of the environment assumptions. In this paper, we describe an approach for constructing monitors and verifying them against the component assumption. We also discuss limitations of instrumentation-based monitoring and potential ways to overcome it.
Formalization and analysis of reasoning by assumption.
Bosse, Tibor; Jonker, Catholijn M; Treur, Jan
2006-01-02
This article introduces a novel approach for the analysis of the dynamics of reasoning processes and explores its applicability for the reasoning pattern called reasoning by assumption. More specifically, for a case study in the domain of a Master Mind game, it is shown how empirical human reasoning traces can be formalized and automatically analyzed against dynamic properties they fulfill. To this end, for the pattern of reasoning by assumption a variety of dynamic properties have been specified, some of which are considered characteristic for the reasoning pattern, whereas some other properties can be used to discriminate among different approaches to the reasoning. These properties have been automatically checked for the traces acquired in experiments undertaken. The approach turned out to be beneficial from two perspectives. First, checking characteristic properties contributes to the empirical validation of a theory on reasoning by assumption. Second, checking discriminating properties allows the analyst to identify different classes of human reasoners. 2006 Lawrence Erlbaum Associates, Inc.
Bayesian Analysis of Geostatistical Models With an Auxiliary Lattice
Park, Jincheol
2012-04-01
The Gaussian geostatistical model has been widely used for modeling spatial data. However, this model suffers from a severe difficulty in computation: it requires users to invert a large covariance matrix. This is infeasible when the number of observations is large. In this article, we propose an auxiliary lattice-based approach for tackling this difficulty. By introducing an auxiliary lattice to the space of observations and defining a Gaussian Markov random field on the auxiliary lattice, our model completely avoids the requirement of matrix inversion. It is remarkable that the computational complexity of our method is only O(n), where n is the number of observations. Hence, our method can be applied to very large datasets with reasonable computational (CPU) times. The numerical results indicate that our model can approximate Gaussian random fields very well in terms of predictions, even for those with long correlation lengths. For real data examples, our model can generally outperform conventional Gaussian random field models in both prediction errors and CPU times. Supplemental materials for the article are available online. © 2012 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.
Bayesian geostatistical modeling of leishmaniasis incidence in Brazil.
Directory of Open Access Journals (Sweden)
Dimitrios-Alexios Karagiannis-Voules
Full Text Available BACKGROUND: Leishmaniasis is endemic in 98 countries with an estimated 350 million people at risk and approximately 2 million cases annually. Brazil is one of the most severely affected countries. METHODOLOGY: We applied Bayesian geostatistical negative binomial models to analyze reported incidence data of cutaneous and visceral leishmaniasis in Brazil covering a 10-year period (2001-2010. Particular emphasis was placed on spatial and temporal patterns. The models were fitted using integrated nested Laplace approximations to perform fast approximate Bayesian inference. Bayesian variable selection was employed to determine the most important climatic, environmental, and socioeconomic predictors of cutaneous and visceral leishmaniasis. PRINCIPAL FINDINGS: For both types of leishmaniasis, precipitation and socioeconomic proxies were identified as important risk factors. The predicted number of cases in 2010 were 30,189 (standard deviation [SD]: 7,676 for cutaneous leishmaniasis and 4,889 (SD: 288 for visceral leishmaniasis. Our risk maps predicted the highest numbers of infected people in the states of Minas Gerais and Pará for visceral and cutaneous leishmaniasis, respectively. CONCLUSIONS/SIGNIFICANCE: Our spatially explicit, high-resolution incidence maps identified priority areas where leishmaniasis control efforts should be targeted with the ultimate goal to reduce disease incidence.
Study on geological environment model using geostatistics method
International Nuclear Information System (INIS)
Honda, Makoto; Suzuki, Makoto; Sakurai, Hideyuki; Iwasa, Kengo; Matsui, Hiroya
2005-03-01
The purpose of this study is to develop the geostatistical procedure for modeling geological environments and to evaluate the quantitative relationship between the amount of information and the reliability of the model using the data sets obtained in the surface-based investigation phase (Phase 1) of the Horonobe Underground Research Laboratory Project. This study lasts for three years from FY2004 to FY2006 and this report includes the research in FY2005 as the second year of three-year study. In FY2005 research, the hydrogeological model was built as well as FY2004 research using the data obtained from the deep boreholes (HDB-6, 7 and 8) and the ground magnetotelluric (AMT) survey which were executed in FY2004 in addition to the data sets used in the first year of study. Above all, the relationship between the amount of information and the reliability of the model was demonstrated through a comparison of the models at each step which corresponds to the investigation stage in each FY. Furthermore, the statistical test was applied for detecting the difference of basic statistics of various data due to geological features with a view to taking the geological information into the modeling procedures. (author)
Life Support Baseline Values and Assumptions Document
Anderson, Molly S.; Ewert, Michael K.; Keener, John F.
2018-01-01
The Baseline Values and Assumptions Document (BVAD) provides analysts, modelers, and other life support researchers with a common set of values and assumptions which can be used as a baseline in their studies. This baseline, in turn, provides a common point of origin from which many studies in the community may depart, making research results easier to compare and providing researchers with reasonable values to assume for areas outside their experience. This document identifies many specific physical quantities that define life support systems, serving as a general reference for spacecraft life support system technology developers.
Comparative study of the geostatistical ore reserve estimation method over the conventional methods
International Nuclear Information System (INIS)
Kim, Y.C.; Knudsen, H.P.
1975-01-01
Part I contains a comprehensive treatment of the comparative study of the geostatistical ore reserve estimation method over the conventional methods. The conventional methods chosen for comparison were: (a) the polygon method, (b) the inverse of the distance squared method, and (c) a method similar to (b) but allowing different weights in different directions. Briefly, the overall result from this comparative study is in favor of the use of geostatistics in most cases because the method has lived up to its theoretical claims. A good exposition on the theory of geostatistics, the adopted study procedures, conclusions and recommended future research are given in Part I. Part II of this report contains the results of the second and the third study objectives, which are to assess the potential benefits that can be derived by the introduction of the geostatistical method to the current state-of-the-art in uranium reserve estimation method and to be instrumental in generating the acceptance of the new method by practitioners through illustrative examples, assuming its superiority and practicality. These are given in the form of illustrative examples on the use of geostatistics and the accompanying computer program user's guide
Industrial experience feedback of a geostatistical estimation of contaminated soil volumes - 59181
International Nuclear Information System (INIS)
Faucheux, Claire; Jeannee, Nicolas
2012-01-01
Geo-statistics meets a growing interest for the remediation forecast of potentially contaminated sites, by providing adapted methods to perform both chemical and radiological pollution mapping, to estimate contaminated volumes, potentially integrating auxiliary information, and to set up adaptive sampling strategies. As part of demonstration studies carried out for GeoSiPol (Geo-statistics for Polluted Sites), geo-statistics has been applied for the detailed diagnosis of a former oil depot in France. The ability within the geo-statistical framework to generate pessimistic / probable / optimistic scenarios for the contaminated volumes allows a quantification of the risks associated to the remediation process: e.g. the financial risk to excavate clean soils, the sanitary risk to leave contaminated soils in place. After a first mapping, an iterative approach leads to collect additional samples in areas previously identified as highly uncertain. Estimated volumes are then updated and compared to the volumes actually excavated. This benchmarking therefore provides a practical feedback on the performance of the geo-statistical methodology. (authors)
The homogeneous marginal utility of income assumption
Demuynck, T.
2015-01-01
We develop a test to verify if every agent from a population of heterogeneous consumers has the same marginal utility of income function. This homogeneous marginal utility of income assumption is often (implicitly) used in applied demand studies because it has nice aggregation properties and
Causal Mediation Analysis: Warning! Assumptions Ahead
Keele, Luke
2015-01-01
In policy evaluations, interest may focus on why a particular treatment works. One tool for understanding why treatments work is causal mediation analysis. In this essay, I focus on the assumptions needed to estimate mediation effects. I show that there is no "gold standard" method for the identification of causal mediation effects. In…
Critically Challenging Some Assumptions in HRD
O'Donnell, David; McGuire, David; Cross, Christine
2006-01-01
This paper sets out to critically challenge five interrelated assumptions prominent in the (human resource development) HRD literature. These relate to: the exploitation of labour in enhancing shareholder value; the view that employees are co-contributors to and co-recipients of HRD benefits; the distinction between HRD and human resource…
Formalization and Analysis of Reasoning by Assumption
Bosse, T.; Jonker, C.M.; Treur, J.
2006-01-01
This article introduces a novel approach for the analysis of the dynamics of reasoning processes and explores its applicability for the reasoning pattern called reasoning by assumption. More specifically, for a case study in the domain of a Master Mind game, it is shown how empirical human reasoning
Extracurricular Business Planning Competitions: Challenging the Assumptions
Watson, Kayleigh; McGowan, Pauric; Smith, Paul
2014-01-01
Business planning competitions [BPCs] are a commonly offered yet under-examined extracurricular activity. Given the extent of sceptical comment about business planning, this paper offers what the authors believe is a much-needed critical discussion of the assumptions that underpin the provision of such competitions. In doing so it is suggested…
Schuler, Eric R; Boals, Adriel
2016-05-01
Shattered Assumptions theory (Janoff-Bulman, 1992) posits that experiencing a traumatic event has the potential to diminish the degree of optimism in the assumptions of the world (assumptive world), which could lead to the development of posttraumatic stress disorder. Prior research assessed the assumptive world with a measure that was recently reported to have poor psychometric properties (Kaler et al., 2008). The current study had 3 aims: (a) to assess the psychometric properties of a recently developed measure of the assumptive world, (b) to retrospectively examine how prior adverse events affected the optimism of the assumptive world, and (c) to measure the impact of an intervening adverse event. An 8-week prospective design with a college sample (N = 882 at Time 1 and N = 511 at Time 2) was used to assess the study objectives. We split adverse events into those that were objectively or subjectively traumatic in nature. The new measure exhibited adequate psychometric properties. The report of a prior objective or subjective trauma at Time 1 was related to a less optimistic assumptive world. Furthermore, participants who experienced an intervening objectively traumatic event evidenced a decrease in optimistic views of the world compared with those who did not experience an intervening adverse event. We found support for Shattered Assumptions theory retrospectively and prospectively using a reliable measure of the assumptive world. We discuss future assessments of the measure of the assumptive world and clinical implications to help rebuild the assumptive world with current therapies. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Geostatistical Study of Precipitation on the Island of Crete
Agou, Vasiliki D.; Varouchakis, Emmanouil A.; Hristopulos, Dionissios T.
2015-04-01
precipitation which are fitted locally to a three-parameter probability distribution, based on which a normalized index is derived. We use the Spartan variogram function to model space-time correlations, because it is more flexible than classical models [3]. The performance of the variogram model is tested by means of leave-one-out cross validation. The variogram model is then used in connection with ordinary kriging to generate precipitation maps for the entire island. In the future, we will explore the joint spatiotemporal evolution of precipitation patterns on Crete. References [1] P. Goovaerts. Geostatistical approaches for incorporating elevation into the spatial interpolation of precipitation. Journal of Hydrology, 228(1):113-129, 2000. [2] N. B. Guttman. Accepting the standardized precipitation index: a calculation algorithm. American Water Resource Association, 35(2):311-322, 1999. [3] D. T Hristopulos. Spartan Gibbs random field models for geostatistical applications. SIAM Journal on Scientific Computing, 24(6):2125-2162, 2003. [4] A.G. Koutroulis, A.-E.K. Vrohidou, and I.K. Tsanis. Spatiotemporal characteristics of meteorological drought for the island of Crete. Journal of Hydrometeorology, 12(2):206-226, 2011. [5] T. B. McKee, N. J. Doesken, and J. Kleist. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology, page 179-184, Anaheim, California, 1993.
Unsupervised classification of multivariate geostatistical data: Two algorithms
Romary, Thomas; Ors, Fabien; Rivoirard, Jacques; Deraisme, Jacques
2015-12-01
With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the domain and to simplify the subsequent modeling step. The definition of these areas can be seen as a problem of unsupervised classification, or clustering, where we try to divide the domain into homogeneous domains with respect to the values taken by the variables in hand. The application of classical clustering methods, designed for independent observations, does not ensure the spatial coherence of the resulting classes. Image segmentation methods, based on e.g. Markov random fields, are not adapted to irregularly sampled data. Other existing approaches, based on mixtures of Gaussian random functions estimated via the expectation-maximization algorithm, are limited to reasonable sample sizes and a small number of variables. In this work, we propose two algorithms based on adaptations of classical algorithms to multivariate geostatistical data. Both algorithms are model free and can handle large volumes of multivariate, irregularly spaced data. The first one proceeds by agglomerative hierarchical clustering. The spatial coherence is ensured by a proximity condition imposed for two clusters to merge. This proximity condition relies on a graph organizing the data in the coordinates space. The hierarchical algorithm can then be seen as a graph-partitioning algorithm. Following this interpretation, a spatial version of the spectral clustering algorithm is also proposed. The performances of both algorithms are assessed on toy examples and a mining dataset.
Bayesian Geostatistical Modeling of Malaria Indicator Survey Data in Angola
Gosoniu, Laura; Veta, Andre Mia; Vounatsou, Penelope
2010-01-01
The 2006–2007 Angola Malaria Indicator Survey (AMIS) is the first nationally representative household survey in the country assessing coverage of the key malaria control interventions and measuring malaria-related burden among children under 5 years of age. In this paper, the Angolan MIS data were analyzed to produce the first smooth map of parasitaemia prevalence based on contemporary nationwide empirical data in the country. Bayesian geostatistical models were fitted to assess the effect of interventions after adjusting for environmental, climatic and socio-economic factors. Non-linear relationships between parasitaemia risk and environmental predictors were modeled by categorizing the covariates and by employing two non-parametric approaches, the B-splines and the P-splines. The results of the model validation showed that the categorical model was able to better capture the relationship between parasitaemia prevalence and the environmental factors. Model fit and prediction were handled within a Bayesian framework using Markov chain Monte Carlo (MCMC) simulations. Combining estimates of parasitaemia prevalence with the number of children under we obtained estimates of the number of infected children in the country. The population-adjusted prevalence ranges from in Namibe province to in Malanje province. The odds of parasitaemia in children living in a household with at least ITNs per person was by 41% lower (CI: 14%, 60%) than in those with fewer ITNs. The estimates of the number of parasitaemic children produced in this paper are important for planning and implementing malaria control interventions and for monitoring the impact of prevention and control activities. PMID:20351775
Inverse Tasks In The Tsunami Problem: Nonlinear Regression With Inaccurate Input Data
Lavrentiev, M.; Shchemel, A.; Simonov, K.
A variant of modified training functional that allows considering inaccurate input data is suggested. A limiting case when a part of input data is completely undefined, and, therefore, a problem of reconstruction of hidden parameters should be solved, is also considered. Some numerical experiments are presented. It is assumed that a dependence of known output variables on known input ones should be found is the classic problem definition, which is widely used in the majority of neural nets algorithms. The quality of approximation is evaluated as a performance function. Often the error of the task is evaluated as squared distance between known input data and predicted data multiplied by weighed coefficients. These coefficients may be named "precision coefficients". When inputs are not known exactly, natural generalization of performance function is adding member that responsible for distance between known inputs and shifted inputs, which lessen model's error. It is desirable that the set of variable parameters is compact for training to be con- verging. In the above problem it is possible to choose variants of demands of a priori compactness, which allow meaningful interpretation in the smoothness of the model dependence. Two kinds of regularization was used, first limited squares of coefficients responsible for nonlinearity and second limited multiplication of the above coeffi- cients and linear coefficients. Asymptotic universality of neural net ability to approxi- mate various smooth functions with any accuracy by increase of the number of tunable parameters is often the base for selecting a type of neural net approximation. It is pos- sible to show that used neural net will approach to Fourier integral transform, which approximate abilities are known, with increasing of the number of tunable parameters. In the limiting case, when input data is set with zero precision, the problem of recon- struction of hidden parameters with observed output data appears. The
Towards New Probabilistic Assumptions in Business Intelligence
Schumann Andrew; Szelc Andrzej
2015-01-01
One of the main assumptions of mathematical tools in science is represented by the idea of measurability and additivity of reality. For discovering the physical universe additive measures such as mass, force, energy, temperature, etc. are used. Economics and conventional business intelligence try to continue this empiricist tradition and in statistical and econometric tools they appeal only to the measurable aspects of reality. However, a lot of important variables of economic systems cannot ...
The 'revealed preferences' theory: Assumptions and conjectures
International Nuclear Information System (INIS)
Green, C.H.
1983-01-01
Being kind of intuitive psychology the 'Revealed-Preferences'- theory based approaches towards determining the acceptable risks are a useful method for the generation of hypotheses. In view of the fact that reliability engineering develops faster than methods for the determination of reliability aims the Revealed-Preferences approach is a necessary preliminary help. Some of the assumptions on which the 'Revealed-Preferences' theory is based will be identified and analysed and afterwards compared with experimentally obtained results. (orig./DG) [de
How to Handle Assumptions in Synthesis
Directory of Open Access Journals (Sweden)
Roderick Bloem
2014-07-01
Full Text Available The increased interest in reactive synthesis over the last decade has led to many improved solutions but also to many new questions. In this paper, we discuss the question of how to deal with assumptions on environment behavior. We present four goals that we think should be met and review several different possibilities that have been proposed. We argue that each of them falls short in at least one aspect.
Managerial and Organizational Assumptions in the CMM's
DEFF Research Database (Denmark)
Rose, Jeremy; Aaen, Ivan; Nielsen, Peter Axel
2008-01-01
Thinking about improving the management of software development in software firms is dominated by one approach: the capability maturity model devised and administered at the Software Engineering Institute at Carnegie Mellon University. Though CMM, and its replacement CMMI are widely known and used...... thinking about large production and manufacturing organisations (particularly in America) in the late industrial age. Many of the difficulties reported with CMMI can be attributed basing practice on these assumptions in organisations which have different cultures and management traditions, perhaps...
International Nuclear Information System (INIS)
MacKay, R.; Cooper, T.A.; Porter, J.D.; O'Connell, P.E.; Metcalfe, A.V.
1988-06-01
A geostatistical approach is applied in a study of the potential migration of contaminants from a hypothetical waste disposal facility near Elstow, Bedfordshire. A deterministic numerical model of groundwater flow in the Kellaways Sands formation and adjacent layers is coupled with geostatistical simulation of the heterogeneous transmissivity field of this principal formation. A particle tracking technique is used to predict the migration pathways for alternative realisations of flow. Alternative statistical descriptions of the spatial structure of the transmissivity field are implemented and the temporal and spatial distributions of escape of contaminants to the biosphere are investigated. (author)
Occupancy estimation and the closure assumption
Rota, Christopher T.; Fletcher, Robert J.; Dorazio, Robert M.; Betts, Matthew G.
2009-01-01
1. Recent advances in occupancy estimation that adjust for imperfect detection have provided substantial improvements over traditional approaches and are receiving considerable use in applied ecology. To estimate and adjust for detectability, occupancy modelling requires multiple surveys at a site and requires the assumption of 'closure' between surveys, i.e. no changes in occupancy between surveys. Violations of this assumption could bias parameter estimates; however, little work has assessed model sensitivity to violations of this assumption or how commonly such violations occur in nature. 2. We apply a modelling procedure that can test for closure to two avian point-count data sets in Montana and New Hampshire, USA, that exemplify time-scales at which closure is often assumed. These data sets illustrate different sampling designs that allow testing for closure but are currently rarely employed in field investigations. Using a simulation study, we then evaluate the sensitivity of parameter estimates to changes in site occupancy and evaluate a power analysis developed for sampling designs that is aimed at limiting the likelihood of closure. 3. Application of our approach to point-count data indicates that habitats may frequently be open to changes in site occupancy at time-scales typical of many occupancy investigations, with 71% and 100% of species investigated in Montana and New Hampshire respectively, showing violation of closure across time periods of 3 weeks and 8 days respectively. 4. Simulations suggest that models assuming closure are sensitive to changes in occupancy. Power analyses further suggest that the modelling procedure we apply can effectively test for closure. 5. Synthesis and applications. Our demonstration that sites may be open to changes in site occupancy over time-scales typical of many occupancy investigations, combined with the sensitivity of models to violations of the closure assumption, highlights the importance of properly addressing
Bayesian geostatistical analysis and prediction of Rhodesian human African trypanosomiasis.
Directory of Open Access Journals (Sweden)
Nicola A Wardrop
2010-12-01
Full Text Available The persistent spread of Rhodesian human African trypanosomiasis (HAT in Uganda in recent years has increased concerns of a potential overlap with the Gambian form of the disease. Recent research has aimed to increase the evidence base for targeting control measures by focusing on the environmental and climatic factors that control the spatial distribution of the disease.One recent study used simple logistic regression methods to explore the relationship between prevalence of Rhodesian HAT and several social, environmental and climatic variables in two of the most recently affected districts of Uganda, and suggested the disease had spread into the study area due to the movement of infected, untreated livestock. Here we extend this study to account for spatial autocorrelation, incorporate uncertainty in input data and model parameters and undertake predictive mapping for risk of high HAT prevalence in future.Using a spatial analysis in which a generalised linear geostatistical model is used in a Bayesian framework to account explicitly for spatial autocorrelation and incorporate uncertainty in input data and model parameters we are able to demonstrate a more rigorous analytical approach, potentially resulting in more accurate parameter and significance estimates and increased predictive accuracy, thereby allowing an assessment of the validity of the livestock movement hypothesis given more robust parameter estimation and appropriate assessment of covariate effects.Analysis strongly supports the theory that Rhodesian HAT was imported to the study area via the movement of untreated, infected livestock from endemic areas. The confounding effect of health care accessibility on the spatial distribution of Rhodesian HAT and the linkages between the disease's distribution and minimum land surface temperature have also been confirmed via the application of these methods.Predictive mapping indicates an increased risk of high HAT prevalence in the future
New Assumptions to Guide SETI Research
Colombano, S. P.
2018-01-01
The recent Kepler discoveries of Earth-like planets offer the opportunity to focus our attention on detecting signs of life and technology in specific planetary systems, but I feel we need to become more flexible in our assumptions. The reason is that, while it is still reasonable and conservative to assume that life is most likely to have originated in conditions similar to ours, the vast time differences in potential evolutions render the likelihood of "matching" technologies very slim. In light of these challenges I propose a more "aggressive"� approach to future SETI exploration in directions that until now have received little consideration.
Assumptions for the Annual Energy Outlook 1992
International Nuclear Information System (INIS)
1992-01-01
This report serves a auxiliary document to the Energy Information Administration (EIA) publication Annual Energy Outlook 1992 (AEO) (DOE/EIA-0383(92)), released in January 1992. The AEO forecasts were developed for five alternative cases and consist of energy supply, consumption, and price projections by major fuel and end-use sector, which are published at a national level of aggregation. The purpose of this report is to present important quantitative assumptions, including world oil prices and macroeconomic growth, underlying the AEO forecasts. The report has been prepared in response to external requests, as well as analyst requirements for background information on the AEO and studies based on the AEO forecasts
Limiting assumptions in molecular modeling: electrostatics.
Marshall, Garland R
2013-02-01
Molecular mechanics attempts to represent intermolecular interactions in terms of classical physics. Initial efforts assumed a point charge located at the atom center and coulombic interactions. It is been recognized over multiple decades that simply representing electrostatics with a charge on each atom failed to reproduce the electrostatic potential surrounding a molecule as estimated by quantum mechanics. Molecular orbitals are not spherically symmetrical, an implicit assumption of monopole electrostatics. This perspective reviews recent evidence that requires use of multipole electrostatics and polarizability in molecular modeling.
Confronting uncertainty in model-based geostatistics using Markov Chain Monte Carlo simulation
Minasny, B.; Vrugt, J.A.; McBratney, A.B.
2011-01-01
This paper demonstrates for the first time the use of Markov Chain Monte Carlo (MCMC) simulation for parameter inference in model-based soil geostatistics. We implemented the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm to jointly summarize the posterior
Quantifying natural delta variability using a multiple-point geostatistics prior uncertainty model
Scheidt, Céline; Fernandes, Anjali M.; Paola, Chris; Caers, Jef
2016-10-01
We address the question of quantifying uncertainty associated with autogenic pattern variability in a channelized transport system by means of a modern geostatistical method. This question has considerable relevance for practical subsurface applications as well, particularly those related to uncertainty quantification relying on Bayesian approaches. Specifically, we show how the autogenic variability in a laboratory experiment can be represented and reproduced by a multiple-point geostatistical prior uncertainty model. The latter geostatistical method requires selection of a limited set of training images from which a possibly infinite set of geostatistical model realizations, mimicking the training image patterns, can be generated. To that end, we investigate two methods to determine how many training images and what training images should be provided to reproduce natural autogenic variability. The first method relies on distance-based clustering of overhead snapshots of the experiment; the second method relies on a rate of change quantification by means of a computer vision algorithm termed the demon algorithm. We show quantitatively that with either training image selection method, we can statistically reproduce the natural variability of the delta formed in the experiment. In addition, we study the nature of the patterns represented in the set of training images as a representation of the "eigenpatterns" of the natural system. The eigenpattern in the training image sets display patterns consistent with previous physical interpretations of the fundamental modes of this type of delta system: a highly channelized, incisional mode; a poorly channelized, depositional mode; and an intermediate mode between the two.
The Use of Geostatistics in the Study of Floral Phenology of Vulpia geniculata (L. Link
Directory of Open Access Journals (Sweden)
Eduardo J. León Ruiz
2012-01-01
Full Text Available Traditionally phenology studies have been focused on changes through time, but there exist many instances in ecological research where it is necessary to interpolate among spatially stratified samples. The combined use of Geographical Information Systems (GIS and Geostatistics can be an essential tool for spatial analysis in phenological studies. Geostatistics are a family of statistics that describe correlations through space/time and they can be used for both quantifying spatial correlation and interpolating unsampled points. In the present work, estimations based upon Geostatistics and GIS mapping have enabled the construction of spatial models that reflect phenological evolution of Vulpia geniculata (L. Link throughout the study area during sampling season. Ten sampling points, scattered troughout the city and low mountains in the “Sierra de Córdoba” were chosen to carry out the weekly phenological monitoring during flowering season. The phenological data were interpolated by applying the traditional geostatitical method of Kriging, which was used to ellaborate weekly estimations of V. geniculata phenology in unsampled areas. Finally, the application of Geostatistics and GIS to create phenological maps could be an essential complement in pollen aerobiological studies, given the increased interest in obtaining automatic aerobiological forecasting maps.
International Nuclear Information System (INIS)
Magri, E.J.
1978-01-01
For life-of-mine planning, as well as for short- and medium-term planning of grades and mine layouts, it is extremely important to have a clear understanding of the patterns followed by the distribution of gold and uranium within the mining area. This study is an attempt to reconcile the geostatistical approach to the determination of ore-shoot directions, via an analysis of the spatial distribution of gold and uranium values, with the sedimentological approach, which is based on the direct measurement of geological features. For the routine geostatistical estimation of ore reserves, the Hartebeestfontein gold mine was divided into ll sections. In each of these sections, the ore-shoot directions were calculated for gold and uranium from the anisotropies disclosed by geostatistical variogram analyses. This study presents a comparison of these results with those obtained from direct geological measurements of paleo-current directions. The results suggest that geological and geostatistical studies could be of significant mutual benefit [af
Karami, Shawgar; Madani, Hassan; Katibeh, Homayoon; Fatehi Marj, Ahmad
2018-03-01
Geostatistical methods are one of the advanced techniques used for interpolation of groundwater quality data. The results obtained from geostatistics will be useful for decision makers to adopt suitable remedial measures to protect the quality of groundwater sources. Data used in this study were collected from 78 wells in Varamin plain aquifer located in southeast of Tehran, Iran, in 2013. Ordinary kriging method was used in this study to evaluate groundwater quality parameters. According to what has been mentioned in this paper, seven main quality parameters (i.e. total dissolved solids (TDS), sodium adsorption ratio (SAR), electrical conductivity (EC), sodium (Na+), total hardness (TH), chloride (Cl-) and sulfate (SO4 2-)), have been analyzed and interpreted by statistical and geostatistical methods. After data normalization by Nscore method in WinGslib software, variography as a geostatistical tool to define spatial regression was compiled and experimental variograms were plotted by GS+ software. Then, the best theoretical model was fitted to each variogram based on the minimum RSS. Cross validation method was used to determine the accuracy of the estimated data. Eventually, estimation maps of groundwater quality were prepared in WinGslib software and estimation variance map and estimation error map were presented to evaluate the quality of estimation in each estimated point. Results showed that kriging method is more accurate than the traditional interpolation methods.
Leakage-Resilient Circuits without Computational Assumptions
DEFF Research Database (Denmark)
Dziembowski, Stefan; Faust, Sebastian
2012-01-01
Physical cryptographic devices inadvertently leak information through numerous side-channels. Such leakage is exploited by so-called side-channel attacks, which often allow for a complete security breache. A recent trend in cryptography is to propose formal models to incorporate leakage...... on computational assumptions, our results are purely information-theoretic. In particular, we do not make use of public key encryption, which was required in all previous works...... into the model and to construct schemes that are provably secure within them. We design a general compiler that transforms any cryptographic scheme, e.g., a block-cipher, into a functionally equivalent scheme which is resilient to any continual leakage provided that the following three requirements are satisfied...
Assumptions and Challenges of Open Scholarship
Directory of Open Access Journals (Sweden)
George Veletsianos
2012-10-01
Full Text Available Researchers, educators, policymakers, and other education stakeholders hope and anticipate that openness and open scholarship will generate positive outcomes for education and scholarship. Given the emerging nature of open practices, educators and scholars are finding themselves in a position in which they can shape and/or be shaped by openness. The intention of this paper is (a to identify the assumptions of the open scholarship movement and (b to highlight challenges associated with the movement’s aspirations of broadening access to education and knowledge. Through a critique of technology use in education, an understanding of educational technology narratives and their unfulfilled potential, and an appreciation of the negotiated implementation of technology use, we hope that this paper helps spark a conversation for a more critical, equitable, and effective future for education and open scholarship.
Challenging the assumptions for thermal sensation scales
DEFF Research Database (Denmark)
Schweiker, Marcel; Fuchs, Xaver; Becker, Susanne
2016-01-01
Scales are widely used to assess the personal experience of thermal conditions in built environments. Most commonly, thermal sensation is assessed, mainly to determine whether a particular thermal condition is comfortable for individuals. A seven-point thermal sensation scale has been used...... extensively, which is suitable for describing a one-dimensional relationship between physical parameters of indoor environments and subjective thermal sensation. However, human thermal comfort is not merely a physiological but also a psychological phenomenon. Thus, it should be investigated how scales for its...... assessment could benefit from a multidimensional conceptualization. The common assumptions related to the usage of thermal sensation scales are challenged, empirically supported by two analyses. These analyses show that the relationship between temperature and subjective thermal sensation is non...
Towards New Probabilistic Assumptions in Business Intelligence
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Schumann Andrew
2015-01-01
Full Text Available One of the main assumptions of mathematical tools in science is represented by the idea of measurability and additivity of reality. For discovering the physical universe additive measures such as mass, force, energy, temperature, etc. are used. Economics and conventional business intelligence try to continue this empiricist tradition and in statistical and econometric tools they appeal only to the measurable aspects of reality. However, a lot of important variables of economic systems cannot be observable and additive in principle. These variables can be called symbolic values or symbolic meanings and studied within symbolic interactionism, the theory developed since George Herbert Mead and Herbert Blumer. In statistical and econometric tools of business intelligence we accept only phenomena with causal connections measured by additive measures. In the paper we show that in the social world we deal with symbolic interactions which can be studied by non-additive labels (symbolic meanings or symbolic values. For accepting the variety of such phenomena we should avoid additivity of basic labels and construct a new probabilistic method in business intelligence based on non-Archimedean probabilities.
Assumptions for the Annual Energy Outlook 1993
International Nuclear Information System (INIS)
1993-01-01
This report is an auxiliary document to the Annual Energy Outlook 1993 (AEO) (DOE/EIA-0383(93)). It presents a detailed discussion of the assumptions underlying the forecasts in the AEO. The energy modeling system is an economic equilibrium system, with component demand modules representing end-use energy consumption by major end-use sector. Another set of modules represents petroleum, natural gas, coal, and electricity supply patterns and pricing. A separate module generates annual forecasts of important macroeconomic and industrial output variables. Interactions among these components of energy markets generate projections of prices and quantities for which energy supply equals energy demand. This equilibrium modeling system is referred to as the Intermediate Future Forecasting System (IFFS). The supply models in IFFS for oil, coal, natural gas, and electricity determine supply and price for each fuel depending upon consumption levels, while the demand models determine consumption depending upon end-use price. IFFS solves for market equilibrium for each fuel by balancing supply and demand to produce an energy balance in each forecast year
Underlying assumptions and core beliefs in anorexia nervosa and dieting.
Cooper, M; Turner, H
2000-06-01
To investigate assumptions and beliefs in anorexia nervosa and dieting. The Eating Disorder Belief Questionnaire (EDBQ), was administered to patients with anorexia nervosa, dieters and female controls. The patients scored more highly than the other two groups on assumptions about weight and shape, assumptions about eating and negative self-beliefs. The dieters scored more highly than the female controls on assumptions about weight and shape. The cognitive content of anorexia nervosa (both assumptions and negative self-beliefs) differs from that found in dieting. Assumptions about weight and shape may also distinguish dieters from female controls.
Energy Technology Data Exchange (ETDEWEB)
Grasshoff, C.; Schetelig, K. [RWTH Aachen, Lehrstuhl fuer Ingenieurgeologie und Hydrogeologie (Germany); Tomschi, H. [Harress Pickel Consult GmbH, Huerth (Germany)
1998-12-31
The following paper demonstrates, how a geostatistical approach can help interpolating hydrogeological parameters over a certain area. The basic elements developed by G. Matheron in the sixties are represented as the preconditions and assumptions, which provide the best results of the estimation. The variogram as the most important tool in geostatistics offers the opportunity to describe the correlating behaviour of a regionalized variable. Some kriging procedures are briefly introduced, which provide under varying circumstances estimating of non-measured values with the theoretical variogram-model. In the Ronneburg mine district 108 screened drill-holes could provide coefficients of hydraulic conductivity. These were interpolated with ordinary kriging over the whole investigation area. An error calculation was performed, which could prove the accuracy of the estimation. Short prospects point out some difficulties handling with geostatistic procedures and make suggestions for further investigations. (orig.) [Deutsch] Der folgende Artikel soll aufzeigen, inwiefern ein geostatistischer Ansatz hilfreich ist, um hydrogeologische Parameter flaechenhaft zu interpolieren. Dabei werden die von Matheron in den sechziger Jahren entwickelten Grundlagen vorgestellt und die Voraussetzungen definiert, unter denen die geostatistischen Schaetzmethoden die besten Ergebnisse liefern. Das Variogramm, als wichtigstes Werkzeug, bietet die Moeglichkeit, die raeumliche Korrelation der untersuchten Variable zu belegen. Mehrere Kriging-Verfahren werden skizzenhaft vorgestellt, die es unter unterschiedlichen Voraussetzungen ermoeglichen, an den Stellen des Untersuchungsgebietes, wo keine Messungen vorliegen, Schaetzungen aus dem Variogramm-Modell zu errechnen. Im Ronneburger Bergbaugebiet wurden aus 108 verfilterten Bohrungen k{sub f}-Werte gewonnen, die mittels Ordinary Kriging flaechenhaft ueber das gesamte Untersuchungsgebiet interpoliert wurden. Eine Fehlerabschaetzung gibt ueber die
Directory of Open Access Journals (Sweden)
Scott O Lilienfeld
2015-08-01
Full Text Available The goal of this article is to promote clear thinking and clear writing among students and teachers of psychological science by curbing terminological misinformation and confusion. To this end, we present a provisional list of 50 commonly used terms in psychology, psychiatry, and allied fields that should be avoided, or at most used sparingly and with explicit caveats. We provide corrective information for students, instructors, and researchers regarding these terms, which we organize for expository purposes into five categories: inaccurate or misleading terms, frequently misused terms, ambiguous terms, oxymorons, and pleonasms. For each term, we (a explain why it is problematic, (b delineate one or more examples of its misuse, and (c when pertinent, offer recommendations for preferable terms. By being more judicious in their use of terminology, psychologists and psychiatrists can foster clearer thinking in their students and the field at large regarding mental phenomena.
Lilienfeld, Scott O; Sauvigné, Katheryn C; Lynn, Steven Jay; Cautin, Robin L; Latzman, Robert D; Waldman, Irwin D
2015-01-01
The goal of this article is to promote clear thinking and clear writing among students and teachers of psychological science by curbing terminological misinformation and confusion. To this end, we present a provisional list of 50 commonly used terms in psychology, psychiatry, and allied fields that should be avoided, or at most used sparingly and with explicit caveats. We provide corrective information for students, instructors, and researchers regarding these terms, which we organize for expository purposes into five categories: inaccurate or misleading terms, frequently misused terms, ambiguous terms, oxymorons, and pleonasms. For each term, we (a) explain why it is problematic, (b) delineate one or more examples of its misuse, and (c) when pertinent, offer recommendations for preferable terms. By being more judicious in their use of terminology, psychologists and psychiatrists can foster clearer thinking in their students and the field at large regarding mental phenomena.
Directory of Open Access Journals (Sweden)
Hahnbeom Park
Full Text Available Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.
Ore reserve evalution, through geostatistical methods, in sector C-09, Pocos de Caldas, MG-Brazil
International Nuclear Information System (INIS)
Guerra, P.A.G.; Censi, A.C.; Marques, J.P.M.; Huijbregts, Ch.
1978-01-01
In sector C-09, Pocos de Caldas in the state of Minas Gerais, geostatistical techniques have been used to evaluate the tonnage of U 3 O 8 and associated minerals and to delimit ore from sterile areas. The calculation of reserve was based on borehole information including the results of chemical and/or radiometric analysis. Two-and three dimensional evalutions were made following the existing geological models. Initially, the evaluation was based on chemical analysis using the more classical geostatistical technique of kriging. This was followed by a second evaluation using the more recent technique of co-kriging which permited the incorporation of radiometric information in the calculations. The correlation between ore grade and radiometric was studied using the method of cross-covariance. Following restrictions imposed by mining considerations, a probabilistic selection was made of blocks of appropriate dimensions so as to evaluate the grade tonnage curve for each panel. (Author) [pt
Energy Technology Data Exchange (ETDEWEB)
Song, Xuehang [Florida State Univ., Tallahassee, FL (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Chen, Xingyuan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ye, Ming [Florida State Univ., Tallahassee, FL (United States); Dai, Zhenxue [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hammond, Glenn Edward [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-07-01
This study develops a new framework of facies-based data assimilation for characterizing spatial distribution of hydrofacies and estimating their associated hydraulic properties. This framework couples ensemble data assimilation with transition probability-based geostatistical model via a parameterization based on a level set function. The nature of ensemble data assimilation makes the framework efficient and flexible to be integrated with various types of observation data. The transition probability-based geostatistical model keeps the updated hydrofacies distributions under geological constrains. The framework is illustrated by using a two-dimensional synthetic study that estimates hydrofacies spatial distribution and permeability in each hydrofacies from transient head data. Our results show that the proposed framework can characterize hydrofacies distribution and associated permeability with adequate accuracy even with limited direct measurements of hydrofacies. Our study provides a promising starting point for hydrofacies delineation in complex real problems.
Directory of Open Access Journals (Sweden)
Thayla Morandi Ridolfi de Carvalho
2012-01-01
Full Text Available The objective of this research was to evaluate different minimum ventilation systems, in relation to air quality and thermal comfort using geostatistics in brooding phase. The minimum ventilation systems were: Blue House I: exhaust fans + curtain management (end of the building; Blue House II: exhaust fans + side curtain management; and Dark House: exhaust fans + flag. The climate variables evaluated were: dry bulb temperature, relative humidity, air velocity, carbon dioxide and ammonia concentration, during winter time, at 9 a.m., in 80 equidistant points in brooding area. Data were evaluated by geostatistic technique. The results indicate that Wider broiler houses (above 15.0 m width present the greatest ammonia and humidity concentration. Blue House II present the best results in relation to air quality. However, none of the studied broiler houses present an ideal thermal comfort.
Geostatistical analyses and hazard assessment on soil lead in Silvermines area, Ireland
International Nuclear Information System (INIS)
McGrath, David; Zhang Chaosheng; Carton, Owen T.
2004-01-01
Spatial distribution and hazard assessment of soil lead in the mining site of Silvermines, Ireland, were investigated using statistics, geostatistics and geographic information system (GIS) techniques. Positively skewed distribution and possible outlying values of Pb and other heavy metals were observed. Box-Cox transformation was applied in order to achieve normality in the data set and to reduce the effect of outliers. Geostatistical analyses were carried out, including calculation of experimental variograms and model fitting. The ordinary point kriging estimates of Pb concentration were mapped. Kriging standard deviations were regarded as the standard deviations of the interpolated pixel values, and a second map was produced, that quantified the probability of Pb concentration higher than a threshold value of 1000 mg/kg. These maps provide valuable information for hazard assessment and for decision support. - A probability map was produced that was useful for hazard assessment and decision support
Geostatistical analysis and kriging of Hexachlorocyclohexane residues in topsoil from Tianjin, China
International Nuclear Information System (INIS)
Li, B.G.; Cao, J.; Liu, W.X.; Shen, W.R.; Wang, X.J.; Tao, S.
2006-01-01
A previously published data set of HCH isomer concentrations in topsoil samples from Tianjin, China, was subjected to geospatial analysis. Semivariograms were calculated and modeled using geostatistical techniques. Parameters of semivariogram models were analyzed and compared for four HCH isomers. Two-dimensional ordinary block kriging was applied to HCH isomers data set for mapping purposes. Dot maps and gray-scaled raster maps of HCH concentrations were presented based on kriging results. The appropriateness of the kriging procedure for mapping purposes was evaluated based on the kriging errors and kriging variances. It was found that ordinary block kriging can be applied to interpolate HCH concentrations in Tianjin topsoil with acceptable accuracy for mapping purposes. - Geostatistical analysis and kriging were applied to HCH concentrations in topsoil of Tianjin, China for mapping purposes
Assessment of effectiveness of geologic isolation systems: geostatistical modeling of pore velocity
International Nuclear Information System (INIS)
Devary, J.L.; Doctor, P.G.
1981-06-01
A significant part of evaluating a geologic formation as a nuclear waste repository involves the modeling of contaminant transport in the surrounding media in the event the repository is breached. The commonly used contaminant transport models are deterministic. However, the spatial variability of hydrologic field parameters introduces uncertainties into contaminant transport predictions. This paper discusses the application of geostatistical techniques to the modeling of spatially varying hydrologic field parameters required as input to contaminant transport analyses. Kriging estimation techniques were applied to Hanford Reservation field data to calculate hydraulic conductivity and the ground-water potential gradients. These quantities were statistically combined to estimate the groundwater pore velocity and to characterize the pore velocity estimation error. Combining geostatistical modeling techniques with product error propagation techniques results in an effective stochastic characterization of groundwater pore velocity, a hydrologic parameter required for contaminant transport analyses
Geostatistical risk estimation at waste disposal sites in the presence of hot spots
International Nuclear Information System (INIS)
Komnitsas, Kostas; Modis, Kostas
2009-01-01
The present paper aims to estimate risk by using geostatistics at the wider coal mining/waste disposal site of Belkovskaya, Tula region, in Russia. In this area the presence of hot spots causes a spatial trend in the mean value of the random field and a non-Gaussian data distribution. Prior to application of geostatistics, subtraction of trend and appropriate smoothing and transformation of the data into a Gaussian form were carried out; risk maps were then generated for the wider study area in order to assess the probability of exceeding risk thresholds. Finally, the present paper discusses the need for homogenization of soil risk thresholds regarding hazardous elements that will enhance reliability of risk estimation and enable application of appropriate rehabilitation actions in contaminated areas.
Geostatistical analyses and hazard assessment on soil lead in Silvermines area, Ireland
Energy Technology Data Exchange (ETDEWEB)
McGrath, David; Zhang Chaosheng; Carton, Owen T
2004-01-01
Spatial distribution and hazard assessment of soil lead in the mining site of Silvermines, Ireland, were investigated using statistics, geostatistics and geographic information system (GIS) techniques. Positively skewed distribution and possible outlying values of Pb and other heavy metals were observed. Box-Cox transformation was applied in order to achieve normality in the data set and to reduce the effect of outliers. Geostatistical analyses were carried out, including calculation of experimental variograms and model fitting. The ordinary point kriging estimates of Pb concentration were mapped. Kriging standard deviations were regarded as the standard deviations of the interpolated pixel values, and a second map was produced, that quantified the probability of Pb concentration higher than a threshold value of 1000 mg/kg. These maps provide valuable information for hazard assessment and for decision support. - A probability map was produced that was useful for hazard assessment and decision support.
Geostatistical simulations for radon indoor with a nested model including the housing factor.
Cafaro, C; Giovani, C; Garavaglia, M
2016-01-01
The radon prone areas definition is matter of many researches in radioecology, since radon is considered a leading cause of lung tumours, therefore the authorities ask for support to develop an appropriate sanitary prevention strategy. In this paper, we use geostatistical tools to elaborate a definition accounting for some of the available information about the dwellings. Co-kriging is the proper interpolator used in geostatistics to refine the predictions by using external covariates. In advance, co-kriging is not guaranteed to improve significantly the results obtained by applying the common lognormal kriging. Here, instead, such multivariate approach leads to reduce the cross-validation residual variance to an extent which is deemed as satisfying. Furthermore, with the application of Monte Carlo simulations, the paradigm provides a more conservative radon prone areas definition than the one previously made by lognormal kriging. Copyright © 2015 Elsevier Ltd. All rights reserved.
Geostatistical Spatio-Time model of crime in el Salvador: Structural and Predictive Analysis
Directory of Open Access Journals (Sweden)
Welman Rosa Alvarado
2011-07-01
Full Text Available Today, to study a geospatial and spatio-temporal phenomena requires searching statistical tools that enable the analysis of the dependency of space, time and interactions. The science that studies this kind of subjects is the Geoestatics which the goal is to predict spatial phenomenon. This science is considered the base for modeling phenomena that involves interactions between space and time. In the past 10 years, the Geostatistic had seen a great development in areas like the geology, soils, remote sensing, epidemiology, agriculture, ecology, economy, etc. In this research, the geostatistic had been apply to build a predictive map about crime in El Salvador; for that the variability of space and time together is studied to generate crime scenarios: crime hot spots are determined, crime vulnerable groups are identified, to improve political decisions and facilitate to decision makers about the insecurity in the country.
A geostatistical estimation of zinc grade in bore-core samples
International Nuclear Information System (INIS)
Starzec, A.
1987-01-01
Possibilities and preliminary results of geostatistical interpretation of the XRF determination of zinc in bore-core samples are considered. For the spherical model of the variogram the estimation variance of grade in a disk-shape sample (estimated from the grade on the circumference sample) is calculated. Variograms of zinc grade in core samples are presented and examples of the grade estimation are discussed. 4 refs., 7 figs., 1 tab. (author)
Troldborg, Mads; Nowak, Wolfgang; Lange, Ida V.; Santos, Marta C.; Binning, Philip J.; Bjerg, Poul L.
2012-09-01
Mass discharge estimates are increasingly being used when assessing risks of groundwater contamination and designing remedial systems at contaminated sites. Such estimates are, however, rather uncertain as they integrate uncertain spatial distributions of both concentration and groundwater flow. Here a geostatistical simulation method for quantifying the uncertainty of the mass discharge across a multilevel control plane is presented. The method accounts for (1) heterogeneity of both the flow field and the concentration distribution through Bayesian geostatistics, (2) measurement uncertainty, and (3) uncertain source zone and transport parameters. The method generates conditional realizations of the spatial flow and concentration distribution. An analytical macrodispersive transport solution is employed to simulate the mean concentration distribution, and a geostatistical model of the Box-Cox transformed concentration data is used to simulate observed deviations from this mean solution. By combining the flow and concentration realizations, a mass discharge probability distribution is obtained. The method has the advantage of avoiding the heavy computational burden of three-dimensional numerical flow and transport simulation coupled with geostatistical inversion. It may therefore be of practical relevance to practitioners compared to existing methods that are either too simple or computationally demanding. The method is demonstrated on a field site contaminated with chlorinated ethenes. For this site, we show that including a physically meaningful concentration trend and the cosimulation of hydraulic conductivity and hydraulic gradient across the transect helps constrain the mass discharge uncertainty. The number of sampling points required for accurate mass discharge estimation and the relative influence of different data types on mass discharge uncertainty is discussed.
International Nuclear Information System (INIS)
Quinn, J.J.
1996-01-01
Geostatistical analysis of hydraulic head data is useful in producing unbiased contour plots of head estimates and relative errors. However, at most sites being characterized, monitoring wells are generally present at different densities, with clusters of wells in some areas and few wells elsewhere. The problem that arises when kriging data at different densities is in achieving adequate resolution of the grid while maintaining computational efficiency and working within software limitations. For the site considered, 113 data points were available over a 14-mi 2 study area, including 57 monitoring wells within an area of concern of 1.5 mi 2 . Variogram analyses of the data indicate a linear model with a negligible nugget effect. The geostatistical package used in the study allows a maximum grid of 100 by 100 cells. Two-dimensional kriging was performed for the entire study area with a 500-ft grid spacing, while the smaller zone was modeled separately with a 100-ft spacing. In this manner, grid cells for the dense area and the sparse area remained small relative to the well separation distances, and the maximum dimensions of the program were not exceeded. The spatial head results for the detailed zone were then nested into the regional output by use of a graphical, object-oriented database that performed the contouring of the geostatistical output. This study benefitted from the two-scale approach and from very fine geostatistical grid spacings relative to typical data separation distances. The combining of the sparse, regional results with those from the finer-resolution area of concern yielded contours that honored the actual data at every measurement location. The method applied in this study can also be used to generate reproducible, unbiased representations of other types of spatial data
Tammy M. Milillo; Gaurav Sinha; Joseph A. Gardella Jr.
2017-01-01
The choice of a relevant, uncontaminated site for the determination of site-specific background concentrations for pollutants is critical for planning remediation of a contaminated site. The guidelines used to arrive at concentration levels vary from state to state, complicating this process. The residential neighborhood of Hickory Woods in Buffalo, NY is an area where heavy metal concentrations and spatial distributions were measured to plan remediation. A novel geostatistics based decision ...
Directory of Open Access Journals (Sweden)
Samuel de Assis Silva
2012-04-01
Full Text Available The spatial variability of soil and plant properties exerts great influence on the yeld of agricultural crops. This study analyzed the spatial variability of the fertility of a Humic Rhodic Hapludox with Arabic coffee, using principal component analysis, cluster analysis and geostatistics in combination. The experiment was carried out in an area under Coffea arabica L., variety Catucai 20/15 - 479. The soil was sampled at a depth 0.20 m, at 50 points of a sampling grid. The following chemical properties were determined: P, K+, Ca2+, Mg2+, Na+, S, Al3+, pH, H + Al, SB, t, T, V, m, OM, Na saturation index (SSI, remaining phosphorus (P-rem, and micronutrients (Zn, Fe, Mn, Cu and B. The data were analyzed with descriptive statistics, followed by principal component and cluster analyses. Geostatistics were used to check and quantify the degree of spatial dependence of properties, represented by principal components. The principal component analysis allowed a dimensional reduction of the problem, providing interpretable components, with little information loss. Despite the characteristic information loss of principal component analysis, the combination of this technique with geostatistical analysis was efficient for the quantification and determination of the structure of spatial dependence of soil fertility. In general, the availability of soil mineral nutrients was low and the levels of acidity and exchangeable Al were high.
Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.
1998-01-01
The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.
Eivazy, Hesameddin; Esmaieli, Kamran; Jean, Raynald
2017-12-01
An accurate characterization and modelling of rock mass geomechanical heterogeneity can lead to more efficient mine planning and design. Using deterministic approaches and random field methods for modelling rock mass heterogeneity is known to be limited in simulating the spatial variation and spatial pattern of the geomechanical properties. Although the applications of geostatistical techniques have demonstrated improvements in modelling the heterogeneity of geomechanical properties, geostatistical estimation methods such as Kriging result in estimates of geomechanical variables that are not fully representative of field observations. This paper reports on the development of 3D models for spatial variability of rock mass geomechanical properties using geostatistical conditional simulation method based on sequential Gaussian simulation. A methodology to simulate the heterogeneity of rock mass quality based on the rock mass rating is proposed and applied to a large open-pit mine in Canada. Using geomechanical core logging data collected from the mine site, a direct and an indirect approach were used to model the spatial variability of rock mass quality. The results of the two modelling approaches were validated against collected field data. The study aims to quantify the risks of pit slope failure and provides a measure of uncertainties in spatial variability of rock mass properties in different areas of the pit.
A geostatistical methodology to assess the accuracy of unsaturated flow models
International Nuclear Information System (INIS)
Smoot, J.L.; Williams, R.E.
1996-04-01
The Pacific Northwest National Laboratory spatiotemporal movement of water injected into (PNNL) has developed a Hydrologic unsaturated sediments at the Hanford Site in Evaluation Methodology (HEM) to assist the Washington State was used to develop a new U.S. Nuclear Regulatory Commission in method for evaluating mathematical model evaluating the potential that infiltrating meteoric predictions. Measured water content data were water will produce leachate at commercial low- interpolated geostatistically to a 16 x 16 x 36 level radioactive waste disposal sites. Two key grid at several time intervals. Then a issues are raised in the HEM: (1) evaluation of mathematical model was used to predict water mathematical models that predict facility content at the same grid locations at the selected performance, and (2) estimation of the times. Node-by-node comparison of the uncertainty associated with these mathematical mathematical model predictions with the model predictions. The technical objective of geostatistically interpolated values was this research is to adapt geostatistical tools conducted. The method facilitates a complete commonly used for model parameter estimation accounting and categorization of model error at to the problem of estimating the spatial every node. The comparison suggests that distribution of the dependent variable to be model results generally are within measurement calculated by the model. To fulfill this error. The worst model error occurs in silt objective, a database describing the lenses and is in excess of measurement error
Spatial Downscaling of TRMM Precipitation Using Geostatistics and Fine Scale Environmental Variables
Directory of Open Access Journals (Sweden)
No-Wook Park
2013-01-01
Full Text Available A geostatistical downscaling scheme is presented and can generate fine scale precipitation information from coarse scale Tropical Rainfall Measuring Mission (TRMM data by incorporating auxiliary fine scale environmental variables. Within the geostatistical framework, the TRMM precipitation data are first decomposed into trend and residual components. Quantitative relationships between coarse scale TRMM data and environmental variables are then estimated via regression analysis and used to derive trend components at a fine scale. Next, the residual components, which are the differences between the trend components and the original TRMM data, are then downscaled at a target fine scale via area-to-point kriging. The trend and residual components are finally added to generate fine scale precipitation estimates. Stochastic simulation is also applied to the residual components in order to generate multiple alternative realizations and to compute uncertainty measures. From an experiment using a digital elevation model (DEM and normalized difference vegetation index (NDVI, the geostatistical downscaling scheme generated the downscaling results that reflected detailed characteristics with better predictive performance, when compared with downscaling without the environmental variables. Multiple realizations and uncertainty measures from simulation also provided useful information for interpretations and further environmental modeling.
Martínez-Murillo, J F; Hueso-González, P; Ruiz-Sinoga, J D
2017-10-01
Soil mapping has been considered as an important factor in the widening of Soil Science and giving response to many different environmental questions. Geostatistical techniques, through kriging and co-kriging techniques, have made possible to improve the understanding of eco-geomorphologic variables, e.g., soil moisture. This study is focused on mapping of topsoil moisture using geostatistical techniques under different Mediterranean climatic conditions (humid, dry and semiarid) in three small watersheds and considering topography and soil properties as key factors. A Digital Elevation Model (DEM) with a resolution of 1×1m was derived from a topographical survey as well as soils were sampled to analyzed soil properties controlling topsoil moisture, which was measured during 4-years. Afterwards, some topography attributes were derived from the DEM, the soil properties analyzed in laboratory, and the topsoil moisture was modeled for the entire watersheds applying three geostatistical techniques: i) ordinary kriging; ii) co-kriging considering as co-variate topography attributes; and iii) co-kriging ta considering as co-variates topography attributes and gravel content. The results indicated topsoil moisture was more accurately mapped in the dry and semiarid watersheds when co-kriging procedure was performed. The study is a contribution to improve the efficiency and accuracy of studies about the Mediterranean eco-geomorphologic system and soil hydrology in field conditions. Copyright © 2017 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Fouquet, Ch. de; Deraisme, J.; Bobbia, M.
2007-01-01
Geo-statistics is increasingly applied to the study of environmental risks in a variety of sectors, especially in the fields of soil decontamination and the evaluation of the risks due to air pollution. Geo-statistics offers a rigorous stochastic modeling approach that makes it possible to answer questions expressed in terms of uncertainty and risk. This article focusses on nonlinear geo-statistical methods, based on the Gaussian random function model, whose essential properties are summarised. We use two examples to characterize situations where direct and thus rapid methods provide appropriate solutions and cases that inevitably require more laborious simulation techniques. Exposure of the population of the Rouen metropolitan area to the risk of NO 2 pollution is assessed by simulations, but the surface area where the pollution exceeds the threshold limit can be easily estimated with nonlinear conditional expectation techniques. A second example is used to discuss the bias introduced by direct simulation, here of a percentile of daily SO 2 concentration for one year in the city of Le Havre; an operational solution is proposed. (authors)
International Nuclear Information System (INIS)
Sandefur, R.L.; Grant, D.C.
1976-01-01
Studies of a roll-front uranium deposit in Shirley Basin Wyoming indicate that preliminary evaluation of the reserve potential of an ore body is possible with less drilling than currently practiced in industry. Estimating ore reserves from sparse drilling is difficult because most reserve calculation techniques do not give the accuracy of the estimate. A study of several deposits with a variety of drilling densities shows that geostatistics consistently provides a method of assessing the accuracy of an ore reserve estimate. Geostatistics provides the geologist with an additional descriptive technique - one which is valuable in the economic assessment of a uranium deposit. Closely spaced drilling on past properties provides both geological and geometric insight into the occurrence of uranium in roll-front type deposits. Just as the geological insight assists in locating new ore bodies and siting preferential drill locations, the geometric insight can be applied mathematically to evaluate the accuracy of a new ore reserve estimate. By expressing the geometry in numerical terms, geostatistics extracts important geological characteristics and uses this information to aid in describing the unknown characteristics of a property. (author)
A geostatistical methodology to assess the accuracy of unsaturated flow models
Energy Technology Data Exchange (ETDEWEB)
Smoot, J.L.; Williams, R.E.
1996-04-01
The Pacific Northwest National Laboratory spatiotemporal movement of water injected into (PNNL) has developed a Hydrologic unsaturated sediments at the Hanford Site in Evaluation Methodology (HEM) to assist the Washington State was used to develop a new U.S. Nuclear Regulatory Commission in method for evaluating mathematical model evaluating the potential that infiltrating meteoric predictions. Measured water content data were water will produce leachate at commercial low- interpolated geostatistically to a 16 x 16 x 36 level radioactive waste disposal sites. Two key grid at several time intervals. Then a issues are raised in the HEM: (1) evaluation of mathematical model was used to predict water mathematical models that predict facility content at the same grid locations at the selected performance, and (2) estimation of the times. Node-by-node comparison of the uncertainty associated with these mathematical mathematical model predictions with the model predictions. The technical objective of geostatistically interpolated values was this research is to adapt geostatistical tools conducted. The method facilitates a complete commonly used for model parameter estimation accounting and categorization of model error at to the problem of estimating the spatial every node. The comparison suggests that distribution of the dependent variable to be model results generally are within measurement calculated by the model. To fulfill this error. The worst model error occurs in silt objective, a database describing the lenses and is in excess of measurement error.
Jha, Sanjeev Kumar
2015-07-21
A geostatistical framework is proposed to downscale daily precipitation and temperature. The methodology is based on multiple-point geostatistics (MPS), where a multivariate training image is used to represent the spatial relationship between daily precipitation and daily temperature over several years. Here, the training image consists of daily rainfall and temperature outputs from the Weather Research and Forecasting (WRF) model at 50 km and 10 km resolution for a twenty year period ranging from 1985 to 2004. The data are used to predict downscaled climate variables for the year 2005. The result, for each downscaled pixel, is daily time series of precipitation and temperature that are spatially dependent. Comparison of predicted precipitation and temperature against a reference dataset indicates that both the seasonal average climate response together with the temporal variability are well reproduced. The explicit inclusion of time dependence is explored by considering the climate properties of the previous day as an additional variable. Comparison of simulations with and without inclusion of time dependence shows that the temporal dependence only slightly improves the daily prediction because the temporal variability is already well represented in the conditioning data. Overall, the study shows that the multiple-point geostatistics approach is an efficient tool to be used for statistical downscaling to obtain local scale estimates of precipitation and temperature from General Circulation Models. This article is protected by copyright. All rights reserved.
A conceptual sedimentological-geostatistical model of aquifer heterogeneity based on outcrop studies
International Nuclear Information System (INIS)
Davis, J.M.
1994-01-01
Three outcrop studies were conducted in deposits of different depositional environments. At each site, permeability measurements were obtained with an air-minipermeameter developed as part of this study. In addition, the geological units were mapped with either surveying, photographs, or both. Geostatistical analysis of the permeability data was performed to estimate the characteristics of the probability distribution function and the spatial correlation structure. The information obtained from the geological mapping was then compared with the results of the geostatistical analysis for any relationships that may exist. The main field site was located in the Albuquerque Basin of central New Mexico at an outcrop of the Pliocene-Pleistocene Sierra Ladrones Formation. The second study was conducted on the walls of waste pits in alluvial fan deposits at the Nevada Test Site. The third study was conducted on an outcrop of an eolian deposit (miocene) south of Socorro, New Mexico. The results of the three studies were then used to construct a conceptual model relating depositional environment to geostatistical models of heterogeneity. The model presented is largely qualitative but provides a basis for further hypothesis formulation and testing
Directory of Open Access Journals (Sweden)
Laura Grisotto
2016-04-01
Full Text Available In this paper the focus is on environmental statistics, with the aim of estimating the concentration surface and related uncertainty of an air pollutant. We used air quality data recorded by a network of monitoring stations within a Bayesian framework to overcome difficulties in accounting for prediction uncertainty and to integrate information provided by deterministic models based on emissions meteorology and chemico-physical characteristics of the atmosphere. Several authors have proposed such integration, but all the proposed approaches rely on representativeness and completeness of existing air pollution monitoring networks. We considered the situation in which the spatial process of interest and the sampling locations are not independent. This is known in the literature as the preferential sampling problem, which if ignored in the analysis, can bias geostatistical inferences. We developed a Bayesian geostatistical model to account for preferential sampling with the main interest in statistical integration and uncertainty. We used PM10 data arising from the air quality network of the Environmental Protection Agency of Lombardy Region (Italy and numerical outputs from the deterministic model. We specified an inhomogeneous Poisson process for the sampling locations intensities and a shared spatial random component model for the dependence between the spatial location of monitors and the pollution surface. We found greater predicted standard deviation differences in areas not properly covered by the air quality network. In conclusion, in this context inferences on prediction uncertainty may be misleading when geostatistical modelling does not take into account preferential sampling.
A conceptual sedimentological-geostatistical model of aquifer heterogeneity based on outcrop studies
Energy Technology Data Exchange (ETDEWEB)
Davis, J.M.
1994-01-01
Three outcrop studies were conducted in deposits of different depositional environments. At each site, permeability measurements were obtained with an air-minipermeameter developed as part of this study. In addition, the geological units were mapped with either surveying, photographs, or both. Geostatistical analysis of the permeability data was performed to estimate the characteristics of the probability distribution function and the spatial correlation structure. The information obtained from the geological mapping was then compared with the results of the geostatistical analysis for any relationships that may exist. The main field site was located in the Albuquerque Basin of central New Mexico at an outcrop of the Pliocene-Pleistocene Sierra Ladrones Formation. The second study was conducted on the walls of waste pits in alluvial fan deposits at the Nevada Test Site. The third study was conducted on an outcrop of an eolian deposit (miocene) south of Socorro, New Mexico. The results of the three studies were then used to construct a conceptual model relating depositional environment to geostatistical models of heterogeneity. The model presented is largely qualitative but provides a basis for further hypothesis formulation and testing.
The zero-sum assumption in neutral biodiversity theory
Etienne, R.S.; Alonso, D.; McKane, A.J.
2007-01-01
The neutral theory of biodiversity as put forward by Hubbell in his 2001 monograph has received much criticism for its unrealistic simplifying assumptions. These are the assumptions of functional equivalence among different species (neutrality), the assumption of point mutation speciation, and the
Philosophy of Technology Assumptions in Educational Technology Leadership
Webster, Mark David
2017-01-01
A qualitative study using grounded theory methods was conducted to (a) examine what philosophy of technology assumptions are present in the thinking of K-12 technology leaders, (b) investigate how the assumptions may influence technology decision making, and (c) explore whether technological determinist assumptions are present. Subjects involved…
Oginosawa, Yasushi; Kohno, Ritsuko; Honda, Toshihiro; Kikuchi, Kan; Nozoe, Masatsugu; Uchida, Takayuki; Minamiguchi, Hitoshi; Sonoda, Koichiro; Ogawa, Masahiro; Ideguchi, Takeshi; Kizaki, Yoshihisa; Nakamura, Toshihiro; Oba, Kageyuki; Higa, Satoshi; Yoshida, Keiki; Tsunoda, Soichi; Fujino, Yoshihisa; Abe, Haruhiko
2017-08-25
Shocks delivered by implanted anti-tachyarrhythmia devices, even when appropriate, lower the quality of life and survival. The new SmartShock Technology ® (SST) discrimination algorithm was developed to prevent the delivery of inappropriate shock. This prospective, multicenter, observational study compared the rate of inaccurate detection of ventricular tachyarrhythmia using the SST vs. a conventional discrimination algorithm.Methods and Results:Recipients of implantable cardioverter defibrillators (ICD) or cardiac resynchronization therapy defibrillators (CRT-D) equipped with the SST algorithm were enrolled and followed up every 6 months. The tachycardia detection rate was set at ≥150 beats/min with the SST algorithm. The primary endpoint was the time to first inaccurate detection of ventricular tachycardia (VT) with conventional vs. the SST discrimination algorithm, up to 2 years of follow-up. Between March 2012 and September 2013, 185 patients (mean age, 64.0±14.9 years; men, 74%; secondary prevention indication, 49.5%) were enrolled at 14 Japanese medical centers. Inaccurate detection was observed in 32 patients (17.6%) with the conventional, vs. in 19 patients (10.4%) with the SST algorithm. SST significantly lowered the rate of inaccurate detection by dual chamber devices (HR, 0.50; 95% CI: 0.263-0.950; P=0.034). Compared with previous algorithms, the SST discrimination algorithm significantly lowered the rate of inaccurate detection of VT in recipients of dual-chamber ICD or CRT-D.
Geostatistical methods for radiological evaluation and risk analysis of contaminated premises
International Nuclear Information System (INIS)
Desnoyers, Y.; Jeannee, N.; Chiles, J.P.; Dubot, D.
2009-01-01
Full text: At the end of process equipment dismantling, the complete decontamination of nuclear facilities requires the radiological assessment of residual activity levels of building structures. As stated by the IAEA, 'Segregation and characterization of contaminated materials are the key elements of waste minimization'. From this point of view, the set up of an appropriate evaluation methodology is of primordial importance. The radiological characterization of contaminated premises can be divided into three steps. First, the most exhaustive facility analysis provides historical, functional and qualitative information. Then, a systematic (exhaustive or not) control of the emergent signal is performed by means of in situ measurement methods such as surface control device combined with in situ gamma spectrometry. Besides, in order to assess the contamination depth, samples can be collected from boreholes at several locations within the premises and analyzed. Combined with historical information and emergent signal maps, such data improve and reinforce the preliminary waste zoning. In order to provide reliable estimates while avoiding supplementary investigation costs, there is therefore a crucial need for sampling optimization methods together with appropriate data processing techniques. The relevance of the geostatistical methodology relies on the presence of a spatial continuity for radiological contamination. In this case, geostatistics provides reliable methods for activity estimation, uncertainty quantification and risk analysis, which are essential decision-making tools for decommissioning and dismantling projects of nuclear installations. Besides, the ability of this geostatistical framework to provide answers to several key issues that generally occur during the clean-up preparation phase is discussed: How to optimise the investigation costs? How to deal with data quality issues? How to consistently take into account auxiliary information such as historical
Benchmarking a geostatistical procedure for the homogenisation of annual precipitation series
Caineta, Júlio; Ribeiro, Sara; Henriques, Roberto; Soares, Amílcar; Costa, Ana Cristina
2014-05-01
The European project COST Action ES0601, Advances in homogenisation methods of climate series: an integrated approach (HOME), has brought to attention the importance of establishing reliable homogenisation methods for climate data. In order to achieve that, a benchmark data set, containing monthly and daily temperature and precipitation data, was created to be used as a comparison basis for the effectiveness of those methods. Several contributions were submitted and evaluated by a number of performance metrics, validating the results against realistic inhomogeneous data. HOME also led to the development of new homogenisation software packages, which included feedback and lessons learned during the project. Preliminary studies have suggested a geostatistical stochastic approach, which uses Direct Sequential Simulation (DSS), as a promising methodology for the homogenisation of precipitation data series. Based on the spatial and temporal correlation between the neighbouring stations, DSS calculates local probability density functions at a candidate station to detect inhomogeneities. The purpose of the current study is to test and compare this geostatistical approach with the methods previously presented in the HOME project, using surrogate precipitation series from the HOME benchmark data set. The benchmark data set contains monthly precipitation surrogate series, from which annual precipitation data series were derived. These annual precipitation series were subject to exploratory analysis and to a thorough variography study. The geostatistical approach was then applied to the data set, based on different scenarios for the spatial continuity. Implementing this procedure also promoted the development of a computer program that aims to assist on the homogenisation of climate data, while minimising user interaction. Finally, in order to compare the effectiveness of this methodology with the homogenisation methods submitted during the HOME project, the obtained results
Troldborg, M.; Nowak, W.; Binning, P. J.; Bjerg, P. L.
2012-12-01
Estimates of mass discharge (mass/time) are increasingly being used when assessing risks of groundwater contamination and designing remedial systems at contaminated sites. Mass discharge estimates are, however, prone to rather large uncertainties as they integrate uncertain spatial distributions of both concentration and groundwater flow velocities. For risk assessments or any other decisions that are being based on mass discharge estimates, it is essential to address these uncertainties. We present a novel Bayesian geostatistical approach for quantifying the uncertainty of the mass discharge across a multilevel control plane. The method decouples the flow and transport simulation and has the advantage of avoiding the heavy computational burden of three-dimensional numerical flow and transport simulation coupled with geostatistical inversion. It may therefore be of practical relevance to practitioners compared to existing methods that are either too simple or computationally demanding. The method is based on conditional geostatistical simulation and accounts for i) heterogeneity of both the flow field and the concentration distribution through Bayesian geostatistics (including the uncertainty in covariance functions), ii) measurement uncertainty, and iii) uncertain source zone geometry and transport parameters. The method generates multiple equally likely realizations of the spatial flow and concentration distribution, which all honour the measured data at the control plane. The flow realizations are generated by analytical co-simulation of the hydraulic conductivity and the hydraulic gradient across the control plane. These realizations are made consistent with measurements of both hydraulic conductivity and head at the site. An analytical macro-dispersive transport solution is employed to simulate the mean concentration distribution across the control plane, and a geostatistical model of the Box-Cox transformed concentration data is used to simulate observed
HYPROLOG: A New Logic Programming Language with Assumptions and Abduction
DEFF Research Database (Denmark)
Christiansen, Henning; Dahl, Veronica
2005-01-01
We present HYPROLOG, a novel integration of Prolog with assumptions and abduction which is implemented in and partly borrows syntax from Constraint Handling Rules (CHR) for integrity constraints. Assumptions are a mechanism inspired by linear logic and taken over from Assumption Grammars. The lan......We present HYPROLOG, a novel integration of Prolog with assumptions and abduction which is implemented in and partly borrows syntax from Constraint Handling Rules (CHR) for integrity constraints. Assumptions are a mechanism inspired by linear logic and taken over from Assumption Grammars....... The language shows a novel flexibility in the interaction between the different paradigms, including all additional built-in predicates and constraints solvers that may be available. Assumptions and abduction are especially useful for language processing, and we can show how HYPROLOG works seamlessly together...
International Nuclear Information System (INIS)
Wang, S; Chao, C; Chang, J
2014-01-01
Purpose: This study investigates the calibration error of detector sensitivity for MapCheck due to inaccurate positioning of the device, which is not taken into account by the current commercial iterative calibration algorithm. We hypothesize the calibration is more vulnerable to the positioning error for the flatten filter free (FFF) beams than the conventional flatten filter flattened beams. Methods: MapCheck2 was calibrated with 10MV conventional and FFF beams, with careful alignment and with 1cm positioning error during calibration, respectively. Open fields of 37cmx37cm were delivered to gauge the impact of resultant calibration errors. The local calibration error was modeled as a detector independent multiplication factor, with which propagation error was estimated with positioning error from 1mm to 1cm. The calibrated sensitivities, without positioning error, were compared between the conventional and FFF beams to evaluate the dependence on the beam type. Results: The 1cm positioning error leads to 0.39% and 5.24% local calibration error in the conventional and FFF beams respectively. After propagating to the edges of MapCheck, the calibration errors become 6.5% and 57.7%, respectively. The propagation error increases almost linearly with respect to the positioning error. The difference of sensitivities between the conventional and FFF beams was small (0.11 ± 0.49%). Conclusion: The results demonstrate that the positioning error is not handled by the current commercial calibration algorithm of MapCheck. Particularly, the calibration errors for the FFF beams are ~9 times greater than those for the conventional beams with identical positioning error, and a small 1mm positioning error might lead to up to 8% calibration error. Since the sensitivities are only slightly dependent of the beam type and the conventional beam is less affected by the positioning error, it is advisable to cross-check the sensitivities between the conventional and FFF beams to detect
Investigating the Assumptions of Uses and Gratifications Research
Lometti, Guy E.; And Others
1977-01-01
Discusses a study designed to determine empirically the gratifications sought from communication channels and to test the assumption that individuals differentiate channels based on gratifications. (MH)
Legal assumptions for private company claim for additional (supplementary payment
Directory of Open Access Journals (Sweden)
Šogorov Stevan
2011-01-01
Full Text Available Subject matter of analyze in this article are legal assumptions which must be met in order to enable private company to call for additional payment. After introductory remarks discussion is focused on existence of provisions regarding additional payment in formation contract, or in shareholders meeting general resolution, as starting point for company's claim. Second assumption is concrete resolution of shareholders meeting which creates individual obligations for additional payments. Third assumption is defined as distinctness regarding sum of payment and due date. Sending of claim by relevant company body is set as fourth legal assumption for realization of company's right to claim additional payments from member of private company.
International Nuclear Information System (INIS)
Bossong, C.R.; Karlinger, M.R.; Troutman, B.M.; Vecchia, A.V.
1999-01-01
Technical and practical aspects of applying geostatistics are developed for individuals involved in investigation at hazardous-, toxic-, and radioactive-waste sites. Important geostatistical concepts, such as variograms and ordinary, universal, and indicator kriging, are described in general terms for introductory purposes and in more detail for practical applications. Variogram modeling using measured ground-water elevation data is described in detail to illustrate principles of stationarity, anisotropy, transformations, and cross validation. Several examples of kriging applications are described using ground-water-level elevations, bedrock elevations, and ground-water-quality data. A review of contemporary literature and selected public domain software associated with geostatistics also is provided, as is a discussion of alternative methods for spatial modeling, including inverse distance weighting, triangulation, splines, trend-surface analysis, and simulation
Energy Technology Data Exchange (ETDEWEB)
Gauthier, Y.
1997-10-20
Geostatistical tools are increasingly used to model permeability fields in subsurface reservoirs, which are considered as a particular random variable development depending of several geostatistical parameters such as variance and correlation length. The first part of the thesis is devoted to the study of relations existing between the transient well pressure (the well test) and the stochastic permeability field, using the apparent permeability concept.The well test performs a moving permeability average over larger and larger volume with increasing time. In the second part, the geostatistical parameters are evaluated using well test data; a Bayesian framework is used and parameters are estimated using the maximum likelihood principle by maximizing the well test data probability density function with respect to these parameters. This method, involving a well test fast evaluation, provides an estimation of the correlation length and the variance over different realizations of a two-dimensional permeability field
DEFF Research Database (Denmark)
Cordua, Knud Skou; Hansen, Thomas Mejer; Mosegaard, Klaus
2012-01-01
We present a general Monte Carlo full-waveform inversion strategy that integrates a priori information described by geostatistical algorithms with Bayesian inverse problem theory. The extended Metropolis algorithm can be used to sample the a posteriori probability density of highly nonlinear...... inverse problems, such as full-waveform inversion. Sequential Gibbs sampling is a method that allows efficient sampling of a priori probability densities described by geostatistical algorithms based on either two-point (e.g., Gaussian) or multiple-point statistics. We outline the theoretical framework......) Based on a posteriori realizations, complicated statistical questions can be answered, such as the probability of connectivity across a layer. (3) Complex a priori information can be included through geostatistical algorithms. These benefits, however, require more computing resources than traditional...
Spatial analysis of groundwater levels using Fuzzy Logic and geostatistical tools
Theodoridou, P. G.; Varouchakis, E. A.; Karatzas, G. P.
2017-12-01
The spatial variability evaluation of the water table of an aquifer provides useful information in water resources management plans. Geostatistical methods are often employed to map the free surface of an aquifer. In geostatistical analysis using Kriging techniques the selection of the optimal variogram is very important for the optimal method performance. This work compares three different criteria to assess the theoretical variogram that fits to the experimental one: the Least Squares Sum method, the Akaike Information Criterion and the Cressie's Indicator. Moreover, variable distance metrics such as the Euclidean, Minkowski, Manhattan, Canberra and Bray-Curtis are applied to calculate the distance between the observation and the prediction points, that affects both the variogram calculation and the Kriging estimator. A Fuzzy Logic System is then applied to define the appropriate neighbors for each estimation point used in the Kriging algorithm. The two criteria used during the Fuzzy Logic process are the distance between observation and estimation points and the groundwater level value at each observation point. The proposed techniques are applied to a data set of 250 hydraulic head measurements distributed over an alluvial aquifer. The analysis showed that the Power-law variogram model and Manhattan distance metric within ordinary kriging provide the best results when the comprehensive geostatistical analysis process is applied. On the other hand, the Fuzzy Logic approach leads to a Gaussian variogram model and significantly improves the estimation performance. The two different variogram models can be explained in terms of a fractional Brownian motion approach and of aquifer behavior at local scale. Finally, maps of hydraulic head spatial variability and of predictions uncertainty are constructed for the area with the two different approaches comparing their advantages and drawbacks.
Monte Carlo Analysis of Reservoir Models Using Seismic Data and Geostatistical Models
Zunino, A.; Mosegaard, K.; Lange, K.; Melnikova, Y.; Hansen, T. M.
2013-12-01
We present a study on the analysis of petroleum reservoir models consistent with seismic data and geostatistical constraints performed on a synthetic reservoir model. Our aim is to invert directly for structure and rock bulk properties of the target reservoir zone. To infer the rock facies, porosity and oil saturation seismology alone is not sufficient but a rock physics model must be taken into account, which links the unknown properties to the elastic parameters. We then combine a rock physics model with a simple convolutional approach for seismic waves to invert the "measured" seismograms. To solve this inverse problem, we employ a Markov chain Monte Carlo (MCMC) method, because it offers the possibility to handle non-linearity, complex and multi-step forward models and provides realistic estimates of uncertainties. However, for large data sets the MCMC method may be impractical because of a very high computational demand. To face this challenge one strategy is to feed the algorithm with realistic models, hence relying on proper prior information. To address this problem, we utilize an algorithm drawn from geostatistics to generate geologically plausible models which represent samples of the prior distribution. The geostatistical algorithm learns the multiple-point statistics from prototype models (in the form of training images), then generates thousands of different models which are accepted or rejected by a Metropolis sampler. To further reduce the computation time we parallelize the software and run it on multi-core machines. The solution of the inverse problem is then represented by a collection of reservoir models in terms of facies, porosity and oil saturation, which constitute samples of the posterior distribution. We are finally able to produce probability maps of the properties we are interested in by performing statistical analysis on the collection of solutions.
Yan, Hongxiang; Moradkhani, Hamid; Abbaszadeh, Peyman
2017-04-01
Assimilation of satellite soil moisture and streamflow data into hydrologic models using has received increasing attention over the past few years. Currently, these observations are increasingly used to improve the model streamflow and soil moisture predictions. However, the performance of this land data assimilation (DA) system still suffers from two limitations: 1) satellite data scarcity and quality; and 2) particle weight degeneration. In order to overcome these two limitations, we propose two possible solutions in this study. First, the general Gaussian geostatistical approach is proposed to overcome the limitation in the space/time resolution of satellite soil moisture products thus improving their accuracy at uncovered/biased grid cells. Secondly, an evolutionary PF approach based on Genetic Algorithm (GA) and Markov Chain Monte Carlo (MCMC), the so-called EPF-MCMC, is developed to further reduce weight degeneration and improve the robustness of the land DA system. This study provides a detailed analysis of the joint and separate assimilation of streamflow and satellite soil moisture into a distributed Sacramento Soil Moisture Accounting (SAC-SMA) model, with the use of recently developed EPF-MCMC and the general Gaussian geostatistical approach. Performance is assessed over several basins in the USA selected from Model Parameter Estimation Experiment (MOPEX) and located in different climate regions. The results indicate that: 1) the general Gaussian approach can predict the soil moisture at uncovered grid cells within the expected satellite data quality threshold; 2) assimilation of satellite soil moisture inferred from the general Gaussian model can significantly improve the soil moisture predictions; and 3) in terms of both deterministic and probabilistic measures, the EPF-MCMC can achieve better streamflow predictions. These results recommend that the geostatistical model is a helpful tool to aid the remote sensing technique and the EPF-MCMC is a
International Nuclear Information System (INIS)
La Pointe, P.R.
1994-11-01
This report describes the comparison of stationary and non-stationary geostatistical models for the purpose of inferring block-scale hydraulic conductivity values from packer tests at Aespoe. The comparison between models is made through the evaluation of cross-validation statistics for three experimental designs. The first experiment consisted of a 'Delete-1' test previously used at Finnsjoen. The second test consisted of 'Delete-10%' and the third test was a 'Delete-50%' test. Preliminary data analysis showed that the 3 m and 30 m packer test data can be treated as a sample from a single population for the purposes of geostatistical analyses. Analysis of the 3 m data does not indicate that there are any systematic statistical changes with depth, rock type, fracture zone vs non-fracture zone or other mappable factor. Directional variograms are ambiguous to interpret due to the clustered nature of the data, but do not show any obvious anisotropy that should be accounted for in geostatistical analysis. Stationary analysis suggested that there exists a sizeable spatially uncorrelated component ('Nugget Effect') in the 3 m data, on the order of 60% of the observed variance for the various models fitted. Four different nested models were automatically fit to the data. Results for all models in terms of cross-validation statistics were very similar for the first set of validation tests. Non-stationary analysis established that both the order of drift and the order of the intrinsic random functions is low. This study also suggests that conventional cross-validation studies and automatic variogram fitting are not necessarily evaluating how well a model will infer block scale hydraulic conductivity values. 20 refs, 20 figs, 14 tabs
Can Geostatistical Models Represent Nature's Variability? An Analysis Using Flume Experiments
Scheidt, C.; Fernandes, A. M.; Paola, C.; Caers, J.
2015-12-01
The lack of understanding in the Earth's geological and physical processes governing sediment deposition render subsurface modeling subject to large uncertainty. Geostatistics is often used to model uncertainty because of its capability to stochastically generate spatially varying realizations of the subsurface. These methods can generate a range of realizations of a given pattern - but how representative are these of the full natural variability? And how can we identify the minimum set of images that represent this natural variability? Here we use this minimum set to define the geostatistical prior model: a set of training images that represent the range of patterns generated by autogenic variability in the sedimentary environment under study. The proper definition of the prior model is essential in capturing the variability of the depositional patterns. This work starts with a set of overhead images from an experimental basin that showed ongoing autogenic variability. We use the images to analyze the essential characteristics of this suite of patterns. In particular, our goal is to define a prior model (a minimal set of selected training images) such that geostatistical algorithms, when applied to this set, can reproduce the full measured variability. A necessary prerequisite is to define a measure of variability. In this study, we measure variability using a dissimilarity distance between the images. The distance indicates whether two snapshots contain similar depositional patterns. To reproduce the variability in the images, we apply an MPS algorithm to the set of selected snapshots of the sedimentary basin that serve as training images. The training images are chosen from among the initial set by using the distance measure to ensure that only dissimilar images are chosen. Preliminary investigations show that MPS can reproduce fairly accurately the natural variability of the experimental depositional system. Furthermore, the selected training images provide
Directory of Open Access Journals (Sweden)
Goovaerts Pierre
2004-07-01
Full Text Available Abstract Background Complete Spatial Randomness (CSR is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new
Evaluation of spatial variability of metal bioavailability in soils using geostatistics
DEFF Research Database (Denmark)
Owsianiak, Mikolaj; Hauschild, Michael Zwicky; Rosenbaum, Ralph K.
2012-01-01
Soil properties show signifficant spatial variability at local, regional and continental scales. This is a challenge for life cycle impact assessment (LCIA) of metals, because fate, bioavailability and effect factors are controlled by environmental chemistry and can vary orders of magnitude...... is performed using ArcGIS Geostatistical Analyst. Results show that BFs of copper span a range of 6 orders of magnitude, and have signifficant spatial variability at local and continental scales. The model nugget variance is signifficantly higher than zero, suggesting the presence of spatial variability...
Guardiola-Albert, Carolina; Díez-Herrero, Andrés; Amérigo, María; García, Juan Antonio; María Bodoque, José; Fernández-Naranjo, Nuria
2017-04-01
Flash floods provoke a high average mortality as they are usually unexpected events which evolve rapidly and affect relatively small areas. The short time available for minimizing risks requires preparedness and response actions to be put into practice. Therefore, it is necessary the development of emergency response plans to evacuate and rescue people in the context of a flash-flood hazard. In this framework, risk management has to integrate the social dimension of flash-flooding and its spatial distribution by understanding the characteristics of local communities in order to enhance community resilience during a flash-flood. In this regard, the flash-flood social risk perception of the village of Navaluenga (Central Spain) has been recently assessed, as well as the level of awareness of civil protection and emergency management strategies (Bodoque et al., 2016). This has been done interviewing 254 adults, representing roughly 12% of the population census. The present study wants to go further in the analysis of the resulting questionnaires, incorporating in the analysis the location of home spatial coordinates in order to characterize the spatial distribution and possible geographical interpretation of flood risk perception. We apply geostatistical methods to analyze spatial relations of social risk perception and level of awareness with distance to the rivers (Alberche and Chorrerón) or to the flood-prone areas (50-year, 100-year and 500-year flood plains). We want to discover spatial patterns, if any, using correlation functions (variograms). Geostatistical analyses results can help to either confirm the logical pattern (i.e., less awareness further to the rivers or high return period of flooding) or reveal departures from expected. It can also be possible to identify hot spots, cold spots, and spatial outliers. The interpretation of these spatial patterns can give valuable information to define strategies to improve the awareness regarding preparedness and
Geostatistical analysis of potentiometric data in Wolfcamp aquifer of the Palo Duro Basin, Texas
International Nuclear Information System (INIS)
Harper, W.V.; Furr, J.M.
1986-04-01
This report details a geostatistical analysis of potentiometric data from the Wolfcamp aquifer in the Palo Duro Basin, Texas. Such an analysis is a part of an overall uncertainty analysis for a high-level waste repository in salt. Both an expected potentiometric surface and the associated standard error surface are produced. The Wolfcamp data are found to be well explained by a linear trend with a superimposed spherical semivariogram. A cross-validation of the analysis confirms this. In addition, the cross-validation provides a point-by-point check to test for possible anomalous data
International Nuclear Information System (INIS)
Rohlig, K.J.; Fischer, H.; Poltl, B.
2004-01-01
This paper describes the stepwise utilization of geologic information from various sources for the construction of hydrogeological models of a sedimentary site by means of geostatistical simulation. It presents a practical application of aquifer characterisation by firstly simulating hydrogeological units and then the hydrogeological parameters. Due to the availability of a large amount of hydrogeological, geophysical and other data and information, the Gorleben site (Northern Germany) has been used for a case study in order to demonstrate the approach. The study, which has not yet been completed, tries to incorporate as much as possible of the available information and to characterise the remaining uncertainties. (author)
Schiemann, R.; Erdin, R.; Willi, M.; Frei, C.; Berenguer, M.; Sempere-Torres, D.
2011-05-01
Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation
DEFF Research Database (Denmark)
Troldborg, Mads; Nowak, Wolfgang; Lange, Ida Vedel
2012-01-01
, and (3) uncertain source zone and transport parameters. The method generates conditional realizations of the spatial flow and concentration distribution. An analytical macrodispersive transport solution is employed to simulate the mean concentration distribution, and a geostatistical model of the Box-Cox...... transformed concentration data is used to simulate observed deviations from this mean solution. By combining the flow and concentration realizations, a mass discharge probability distribution is obtained. The method has the advantage of avoiding the heavy computational burden of three-dimensional numerical...
DEFF Research Database (Denmark)
Troldborg, Mads; Nowak, Wolfgang; Binning, Philip John
and the hydraulic gradient across the control plane and are consistent with measurements of both hydraulic conductivity and head at the site. An analytical macro-dispersive transport solution is employed to simulate the mean concentration distribution across the control plane, and a geostatistical model of the Box-Cox...... transformed concentration data is used to simulate observed deviations from this mean solution. By combining the flow and concentration realizations, a mass discharge probability distribution is obtained. Tests show that the decoupled approach is both efficient and able to provide accurate uncertainty...
DEFF Research Database (Denmark)
Kessler, Timo Christian; Klint, K.E.S.; Renard, P.
2010-01-01
In low-permeability clay tills subsurface transport is governed by preferential flow in sand lenses and fractures. A proper geological model requires the integration of these features, i.e. the spatial distribution of the geological heterogeneities. Detailed mapping of sand lenses has been done...... at a clay till outcrop in Denmark to characterise the shapes and the spatial variability. Further, geostatistics were applied to simulate the distribution and to develop a heterogeneity model that can be incorporated into an existing geological model of, for example, a contaminated site....
Smith, Kelly M.; Gay, Robert S.; Stachowiak, Susan J.
2013-01-01
In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.
Smith, Kelly; Gay, Robert; Stachowiak, Susan
2013-01-01
In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles
Distributed automata in an assumption-commitment framework
Indian Academy of Sciences (India)
We propose a class of ﬁnite state systems of synchronizing distributed processes, where processes make assumptions at local states about the state of other processes in the system. This constrains the global states of the system to those where assumptions made by a process about another are compatible with the ...
40 CFR 264.150 - State assumption of responsibility.
2010-07-01
... FACILITIES Financial Requirements § 264.150 State assumption of responsibility. (a) If a State either assumes legal responsibility for an owner's or operator's compliance with the closure, post-closure care, or... 40 Protection of Environment 25 2010-07-01 2010-07-01 false State assumption of responsibility...
40 CFR 261.150 - State assumption of responsibility.
2010-07-01
... Excluded Hazardous Secondary Materials § 261.150 State assumption of responsibility. (a) If a State either assumes legal responsibility for an owner's or operator's compliance with the closure or liability... 40 Protection of Environment 25 2010-07-01 2010-07-01 false State assumption of responsibility...
40 CFR 265.150 - State assumption of responsibility.
2010-07-01
..., STORAGE, AND DISPOSAL FACILITIES Financial Requirements § 265.150 State assumption of responsibility. (a) If a State either assumes legal responsibility for an owner's or operator's compliance with the... 40 Protection of Environment 25 2010-07-01 2010-07-01 false State assumption of responsibility...
40 CFR 144.66 - State assumption of responsibility.
2010-07-01
... PROGRAMS (CONTINUED) UNDERGROUND INJECTION CONTROL PROGRAM Financial Responsibility: Class I Hazardous Waste Injection Wells § 144.66 State assumption of responsibility. (a) If a State either assumes legal... 40 Protection of Environment 22 2010-07-01 2010-07-01 false State assumption of responsibility...
40 CFR 267.150 - State assumption of responsibility.
2010-07-01
... STANDARDIZED PERMIT Financial Requirements § 267.150 State assumption of responsibility. (a) If a State either assumes legal responsibility for an owner's or operator's compliance with the closure care or liability... 40 Protection of Environment 26 2010-07-01 2010-07-01 false State assumption of responsibility...
Capturing Assumptions while Designing a Verification Model for Embedded Systems
Marincic, J.; Mader, Angelika H.; Wieringa, Roelf J.
A formal proof of a system correctness typically holds under a number of assumptions. Leaving them implicit raises the chance of using the system in a context that violates some assumptions, which in return may invalidate the correctness proof. The goal of this paper is to show how combining
PFP issues/assumptions development and management planning guide
International Nuclear Information System (INIS)
SINCLAIR, J.C.
1999-01-01
The PFP Issues/Assumptions Development and Management Planning Guide presents the strategy and process used for the identification, allocation, and maintenance of an Issues/Assumptions Management List for the Plutonium Finishing Plant (PFP) integrated project baseline. Revisions to this document will include, as attachments, the most recent version of the Issues/Assumptions Management List, both open and current issues/assumptions (Appendix A), and closed or historical issues/assumptions (Appendix B). This document is intended be a Project-owned management tool. As such, this document will periodically require revisions resulting from improvements of the information, processes, and techniques as now described. Revisions that suggest improved processes will only require PFP management approval
Mariethoz, Gregoire; Lefebvre, Sylvain
2014-05-01
Multiple-Point Simulations (MPS) is a family of geostatistical tools that has received a lot of attention in recent years for the characterization of spatial phenomena in geosciences. It relies on the definition of training images to represent a given type of spatial variability, or texture. We show that the algorithmic tools used are similar in many ways to techniques developed in computer graphics, where there is a need to generate large amounts of realistic textures for applications such as video games and animated movies. Similarly to MPS, these texture synthesis methods use training images, or exemplars, to generate realistic-looking graphical textures. Both domains of multiple-point geostatistics and example-based texture synthesis present similarities in their historic development and share similar concepts. These disciplines have however remained separated, and as a result significant algorithmic innovations in each discipline have not been universally adopted. Texture synthesis algorithms present drastically increased computational efficiency, patterns reproduction and user control. At the same time, MPS developed ways to condition models to spatial data and to produce 3D stochastic realizations, which have not been thoroughly investigated in the field of texture synthesis. In this paper we review the possible links between these disciplines and show the potential and limitations of using concepts and approaches from texture synthesis in MPS. We also provide guidelines on how recent developments could benefit both fields of research, and what challenges remain open.
Redesigning rain gauges network in Johor using geostatistics and simulated annealing
Energy Technology Data Exchange (ETDEWEB)
Aziz, Mohd Khairul Bazli Mohd, E-mail: mkbazli@yahoo.com [Centre of Preparatory and General Studies, TATI University College, 24000 Kemaman, Terengganu, Malaysia and Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Yusof, Fadhilah, E-mail: fadhilahy@utm.my [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Daud, Zalina Mohd, E-mail: zalina@ic.utm.my [UTM Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia, UTM KL, 54100 Kuala Lumpur (Malaysia); Yusop, Zulkifli, E-mail: zulyusop@utm.my [Institute of Environmental and Water Resource Management (IPASA), Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Kasno, Mohammad Afif, E-mail: mafifkasno@gmail.com [Malaysia - Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, UTM KL, 54100 Kuala Lumpur (Malaysia)
2015-02-03
Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.
Geostatistics: a common link between medical geography, mathematical geology, and medical geology.
Goovaerts, P
2014-08-01
Since its development in the mining industry, geostatistics has emerged as the primary tool for spatial data analysis in various fields, ranging from earth and atmospheric sciences to agriculture, soil science, remote sensing, and more recently environmental exposure assessment. In the last few years, these tools have been tailored to the field of medical geography or spatial epidemiology, which is concerned with the study of spatial patterns of disease incidence and mortality and the identification of potential 'causes' of disease, such as environmental exposure, diet and unhealthy behaviours, economic or socio-demographic factors. On the other hand, medical geology is an emerging interdisciplinary scientific field studying the relationship between natural geological factors and their effects on human and animal health. This paper provides an introduction to the field of medical geology with an overview of geostatistical methods available for the analysis of geological and health data. Key concepts are illustrated using the mapping of groundwater arsenic concentration across eleven Michigan counties and the exploration of its relationship to the incidence of prostate cancer at the township level.
Geostatistical Borehole Image-Based Mapping of Karst-Carbonate Aquifer Pores.
Sukop, Michael C; Cunningham, Kevin J
2016-03-01
Quantification of the character and spatial distribution of porosity in carbonate aquifers is important as input into computer models used in the calculation of intrinsic permeability and for next-generation, high-resolution groundwater flow simulations. Digital, optical, borehole-wall image data from three closely spaced boreholes in the karst-carbonate Biscayne aquifer in southeastern Florida are used in geostatistical experiments to assess the capabilities of various methods to create realistic two-dimensional models of vuggy megaporosity and matrix-porosity distribution in the limestone that composes the aquifer. When the borehole image data alone were used as the model training image, multiple-point geostatistics failed to detect the known spatial autocorrelation of vuggy megaporosity and matrix porosity among the three boreholes, which were only 10 m apart. Variogram analysis and subsequent Gaussian simulation produced results that showed a realistic conceptualization of horizontal continuity of strata dominated by vuggy megaporosity and matrix porosity among the three boreholes. © 2015, National Ground Water Association.
Directory of Open Access Journals (Sweden)
Md. Bodrud-Doza
2016-04-01
Full Text Available This study investigates the groundwater quality in the Faridpur district of central Bangladesh based on preselected 60 sample points. Water evaluation indices and a number of statistical approaches such as multivariate statistics and geostatistics are applied to characterize water quality, which is a major factor for controlling the groundwater quality in term of drinking purposes. The study reveal that EC, TDS, Ca2+, total As and Fe values of groundwater samples exceeded Bangladesh and international standards. Ground water quality index (GWQI exhibited that about 47% of the samples were belonging to good quality water for drinking purposes. The heavy metal pollution index (HPI, degree of contamination (Cd, heavy metal evaluation index (HEI reveal that most of the samples belong to low level of pollution. However, Cd provide better alternative than other indices. Principle component analysis (PCA suggests that groundwater quality is mainly related to geogenic (rock–water interaction and anthropogenic source (agrogenic and domestic sewage in the study area. Subsequently, the findings of cluster analysis (CA and correlation matrix (CM are also consistent with the PCA results. The spatial distributions of groundwater quality parameters are determined by geostatistical modeling. The exponential semivariagram model is validated as the best fitted models for most of the indices values. It is expected that outcomes of the study will provide insights for decision makers taking proper measures for groundwater quality management in central Bangladesh.
Directory of Open Access Journals (Sweden)
Waldir de Carvalho Junior
2014-06-01
Full Text Available Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR and geostatistical (ordinary kriging and co-kriging. The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap. Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI, soil wetness index (SWI, normalized difference vegetation index (NDVI, and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.
Redesigning rain gauges network in Johor using geostatistics and simulated annealing
International Nuclear Information System (INIS)
Aziz, Mohd Khairul Bazli Mohd; Yusof, Fadhilah; Daud, Zalina Mohd; Yusop, Zulkifli; Kasno, Mohammad Afif
2015-01-01
Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system
Deep fracturing of granite bodies. Literature survey, geostructural and geostatistic investigations
International Nuclear Information System (INIS)
Bles, J.L.; Blanchin, R.
1986-01-01
This report deals with investigations about deep fracturing of granite bodies, which were performed within two cost-sharing contracts between the Commission of the European Communities, the Commissariat a l'Energie Atomique and the Bureau de Recherches Geologiques et Minieres. The aim of this work was to study the evolution of fracturing in granite from the surface to larger depths, so that guidelines can be identified in order to extrapolate, at depth, the data obtained from surface investigations. These guidelines could eventually be used for feasibility studies about radioactive waste disposal. The results of structural and geostatistic investigations about the St. Sylvestre granite, as well as the literature survey about fractures encountered in two long Alpine galleries (Mont-Blanc tunnel and Arc-Isere water gallery), in the 1000 m deep borehole at Auriat, and in the Bassies granite body (Pyrenees) are presented. These results show that, for radioactive waste disposal feasibility studies: 1. The deep state of fracturing in a granite body can be estimated from results obtained at the surface; 2. Studying only the large fault network would be insufficient, both for surface investigations and for studies in deep boreholes and/or in underground galleries; 3. It is necessary to study orientations and frequencies of small fractures, so that structural mapping and statistical/geostatistical methods can be used in order to identify zones of higher and lower fracturing
Tang, Yunwei; Atkinson, Peter M.; Zhang, Jingxiong
2015-03-01
A cross-scale data integration method was developed and tested based on the theory of geostatistics and multiple-point geostatistics (MPG). The goal was to downscale remotely sensed images while retaining spatial structure by integrating images at different spatial resolutions. During the process of downscaling, a rich spatial correlation model in the form of a training image was incorporated to facilitate reproduction of similar local patterns in the simulated images. Area-to-point cokriging (ATPCK) was used as locally varying mean (LVM) (i.e., soft data) to deal with the change of support problem (COSP) for cross-scale integration, which MPG cannot achieve alone. Several pairs of spectral bands of remotely sensed images were tested for integration within different cross-scale case studies. The experiment shows that MPG can restore the spatial structure of the image at a fine spatial resolution given the training image and conditioning data. The super-resolution image can be predicted using the proposed method, which cannot be realised using most data integration methods. The results show that ATPCK-MPG approach can achieve greater accuracy than methods which do not account for the change of support issue.
Del Monego, Maurici; Ribeiro, Paulo Justiniano; Ramos, Patrícia
2015-04-01
In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the Matèrn models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.
Jha, Sanjeev Kumar; Mariethoz, Gregoire; Evans, Jason P.; McCabe, Matthew
2013-01-01
A downscaling approach based on multiple-point geostatistics (MPS) is presented. The key concept underlying MPS is to sample spatial patterns from within training images, which can then be used in characterizing the relationship between different variables across multiple scales. The approach is used here to downscale climate variables including skin surface temperature (TSK), soil moisture (SMOIS), and latent heat flux (LH). The performance of the approach is assessed by applying it to data derived from a regional climate model of the Murray-Darling basin in southeast Australia, using model outputs at two spatial resolutions of 50 and 10 km. The data used in this study cover the period from 1985 to 2006, with 1985 to 2005 used for generating the training images that define the relationships of the variables across the different spatial scales. Subsequently, the spatial distributions for the variables in the year 2006 are determined at 10 km resolution using the 50 km resolution data as input. The MPS geostatistical downscaling approach reproduces the spatial distribution of TSK, SMOIS, and LH at 10 km resolution with the correct spatial patterns over different seasons, while providing uncertainty estimates through the use of multiple realizations. The technique has the potential to not only bridge issues of spatial resolution in regional and global climate model simulations but also in feature sharpening in remote sensing applications through image fusion, filling gaps in spatial data, evaluating downscaled variables with available remote sensing images, and aggregating/disaggregating hydrological and groundwater variables for catchment studies.
Redesigning rain gauges network in Johor using geostatistics and simulated annealing
Aziz, Mohd Khairul Bazli Mohd; Yusof, Fadhilah; Daud, Zalina Mohd; Yusop, Zulkifli; Kasno, Mohammad Afif
2015-02-01
Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.
Geostatistical simulations for radon indoor with a nested model including the housing factor
International Nuclear Information System (INIS)
Cafaro, C.; Giovani, C.; Garavaglia, M.
2016-01-01
The radon prone areas definition is matter of many researches in radioecology, since radon is considered a leading cause of lung tumours, therefore the authorities ask for support to develop an appropriate sanitary prevention strategy. In this paper, we use geostatistical tools to elaborate a definition accounting for some of the available information about the dwellings. Co-kriging is the proper interpolator used in geostatistics to refine the predictions by using external covariates. In advance, co-kriging is not guaranteed to improve significantly the results obtained by applying the common lognormal kriging. Here, instead, such multivariate approach leads to reduce the cross-validation residual variance to an extent which is deemed as satisfying. Furthermore, with the application of Monte Carlo simulations, the paradigm provides a more conservative radon prone areas definition than the one previously made by lognormal kriging. - Highlights: • The housing class is inserted into co-kriging via an indicator function. • Inserting the housing classes in a co-kriging improves predictions. • The housing class has a structured component in space. • A nested model is implemented into the multigaussian algorithm. • A collection of risk maps is merged into one to create RPA.
Assumptions and Policy Decisions for Vital Area Identification Analysis
Energy Technology Data Exchange (ETDEWEB)
Kim, Myungsu; Bae, Yeon-Kyoung; Lee, Youngseung [KHNP CRI, Daejeon (Korea, Republic of)
2016-10-15
U.S. Nuclear Regulatory Commission and IAEA guidance indicate that certain assumptions and policy questions should be addressed to a Vital Area Identification (VAI) process. Korea Hydro and Nuclear Power conducted a VAI based on current Design Basis Threat and engineering judgement to identify APR1400 vital areas. Some of the assumptions were inherited from Probabilistic Safety Assessment (PSA) as a sabotage logic model was based on PSA logic tree and equipment location data. This paper illustrates some important assumptions and policy decisions for APR1400 VAI analysis. Assumptions and policy decisions could be overlooked at the beginning stage of VAI, however they should be carefully reviewed and discussed among engineers, plant operators, and regulators. Through APR1400 VAI process, some of the policy concerns and assumptions for analysis were applied based on document research and expert panel discussions. It was also found that there are more assumptions to define for further studies for other types of nuclear power plants. One of the assumptions is mission time, which was inherited from PSA.
MONITORED GEOLOGIC REPOSITORY LIFE CYCLE COST ESTIMATE ASSUMPTIONS DOCUMENT
International Nuclear Information System (INIS)
R.E. Sweeney
2001-01-01
The purpose of this assumptions document is to provide general scope, strategy, technical basis, schedule and cost assumptions for the Monitored Geologic Repository (MGR) life cycle cost (LCC) estimate and schedule update incorporating information from the Viability Assessment (VA) , License Application Design Selection (LADS), 1999 Update to the Total System Life Cycle Cost (TSLCC) estimate and from other related and updated information. This document is intended to generally follow the assumptions outlined in the previous MGR cost estimates and as further prescribed by DOE guidance
Monitored Geologic Repository Life Cycle Cost Estimate Assumptions Document
International Nuclear Information System (INIS)
Sweeney, R.
2000-01-01
The purpose of this assumptions document is to provide general scope, strategy, technical basis, schedule and cost assumptions for the Monitored Geologic Repository (MGR) life cycle cost estimate and schedule update incorporating information from the Viability Assessment (VA), License Application Design Selection (LADS), 1999 Update to the Total System Life Cycle Cost (TSLCC) estimate and from other related and updated information. This document is intended to generally follow the assumptions outlined in the previous MGR cost estimates and as further prescribed by DOE guidance
The stable model semantics under the any-world assumption
Straccia, Umberto; Loyer, Yann
2004-01-01
The stable model semantics has become a dominating approach to complete the knowledge provided by a logic program by means of the Closed World Assumption (CWA). The CWA asserts that any atom whose truth-value cannot be inferred from the facts and rules is supposed to be false. This assumption is orthogonal to the so-called the Open World Assumption (OWA), which asserts that every such atom's truth is supposed to be unknown. The topic of this paper is to be more fine-grained. Indeed, the objec...
Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu
2005-01-01
Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...
Fienen, Michael N.; D'Oria, Marco; Doherty, John E.; Hunt, Randall J.
2013-01-01
The application bgaPEST is a highly parameterized inversion software package implementing the Bayesian Geostatistical Approach in a framework compatible with the parameter estimation suite PEST. Highly parameterized inversion refers to cases in which parameters are distributed in space or time and are correlated with one another. The Bayesian aspect of bgaPEST is related to Bayesian probability theory in which prior information about parameters is formally revised on the basis of the calibration dataset used for the inversion. Conceptually, this approach formalizes the conditionality of estimated parameters on the speciﬁc data and model available. The geostatistical component of the method refers to the way in which prior information about the parameters is used. A geostatistical autocorrelation function is used to enforce structure on the parameters to avoid overﬁtting and unrealistic results. Bayesian Geostatistical Approach is designed to provide the smoothest solution that is consistent with the data. Optionally, users can specify a level of ﬁt or estimate a balance between ﬁt and model complexity informed by the data. Groundwater and surface-water applications are used as examples in this text, but the possible uses of bgaPEST extend to any distributed parameter applications.
Wang, Jun; Wang, Yang; Zeng, Hui
2016-01-01
A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.
Attenberger, Ulrike; Catana, Ciprian; Chandarana, Hersh; Catalano, Onofrio A; Friedman, Kent; Schonberg, Stefan A; Thrall, James; Salvatore, Marco; Rosen, Bruce R; Guimaraes, Alexander R
2015-08-01
Simultaneous data collection for positron emission tomography and magnetic resonance imaging (PET/MR) is now a reality. While the full benefits of concurrently acquiring PET and MR data and the potential added clinical value are still being evaluated, initial studies have identified several important potential pitfalls in the interpretation of fluorodeoxyglucose (FDG) PET/MRI in oncologic whole-body imaging, the majority of which being related to the errors in the attenuation maps created from the MR data. The purpose of this article was to present such pitfalls and artifacts using case examples, describe their etiology, and discuss strategies to overcome them. Using a case-based approach, we will illustrate artifacts related to (1) Inaccurate bone tissue segmentation; (2) Inaccurate air cavities segmentation; (3) Motion-induced misregistration; (4) RF coils in the PET field of view; (5) B0 field inhomogeneity; (6) B1 field inhomogeneity; (7) Metallic implants; (8) MR contrast agents.
Supporting calculations and assumptions for use in WESF safetyanalysis
Energy Technology Data Exchange (ETDEWEB)
Hey, B.E.
1997-03-07
This document provides a single location for calculations and assumptions used in support of Waste Encapsulation and Storage Facility (WESF) safety analyses. It also provides the technical details and bases necessary to justify the contained results.
A framework for the organizational assumptions underlying safety culture
International Nuclear Information System (INIS)
Packer, Charles
2002-01-01
The safety culture of the nuclear organization can be addressed at the three levels of culture proposed by Edgar Schein. The industry literature provides a great deal of insight at the artefact and espoused value levels, although as yet it remains somewhat disorganized. There is, however, an overall lack of understanding of the assumption level of safety culture. This paper describes a possible framework for conceptualizing the assumption level, suggesting that safety culture is grounded in unconscious beliefs about the nature of the safety problem, its solution and how to organize to achieve the solution. Using this framework, the organization can begin to uncover the assumptions at play in its normal operation, decisions and events and, if necessary, engage in a process to shift them towards assumptions more supportive of a strong safety culture. (author)
Psychopatholgy, fundamental assumptions and CD-4 T lymphocyte ...
African Journals Online (AJOL)
In addition, we explored whether psychopathology and negative fundamental assumptions in ... Method: Self-rating questionnaires to assess depressive symptoms, ... associated with all participants scoring in the positive range of the FA scale.
The Immoral Assumption Effect: Moralization Drives Negative Trait Attributions.
Meindl, Peter; Johnson, Kate M; Graham, Jesse
2016-04-01
Jumping to negative conclusions about other people's traits is judged as morally bad by many people. Despite this, across six experiments (total N = 2,151), we find that multiple types of moral evaluations--even evaluations related to open-mindedness, tolerance, and compassion--play a causal role in these potentially pernicious trait assumptions. Our results also indicate that moralization affects negative-but not positive-trait assumptions, and that the effect of morality on negative assumptions cannot be explained merely by people's general (nonmoral) preferences or other factors that distinguish moral and nonmoral traits, such as controllability or desirability. Together, these results suggest that one of the more destructive human tendencies--making negative assumptions about others--can be caused by the better angels of our nature. © 2016 by the Society for Personality and Social Psychology, Inc.
Idaho National Engineering Laboratory installation roadmap assumptions document
International Nuclear Information System (INIS)
1993-05-01
This document is a composite of roadmap assumptions developed for the Idaho National Engineering Laboratory (INEL) by the US Department of Energy Idaho Field Office and subcontractor personnel as a key element in the implementation of the Roadmap Methodology for the INEL Site. The development and identification of these assumptions in an important factor in planning basis development and establishes the planning baseline for all subsequent roadmap analysis at the INEL
Szatmári, Gábor; Laborczi, Annamária; Takács, Katalin; Pásztor, László
2017-04-01
The knowledge about soil organic carbon (SOC) baselines and changes, and the detection of vulnerable hot spots for SOC losses and gains under climate change and changed land management is still fairly limited. Thus Global Soil Partnership (GSP) has been requested to develop a global SOC mapping campaign by 2017. GSPs concept builds on official national data sets, therefore, a bottom-up (country-driven) approach is pursued. The elaborated Hungarian methodology suits the general specifications of GSOC17 provided by GSP. The input data for GSOC17@HU mapping approach has involved legacy soil data bases, as well as proper environmental covariates related to the main soil forming factors, such as climate, organisms, relief and parent material. Nowadays, digital soil mapping (DSM) highly relies on the assumption that soil properties of interest can be modelled as a sum of a deterministic and stochastic component, which can be treated and modelled separately. We also adopted this assumption in our methodology. In practice, multiple regression techniques are commonly used to model the deterministic part. However, this global (and usually linear) models commonly oversimplify the often complex and non-linear relationship, which has a crucial effect on the resulted soil maps. Thus, we integrated machine learning algorithms (namely random forest and quantile regression forest) in the elaborated methodology, supposing then to be more suitable for the problem in hand. This approach has enable us to model the GSOC17 soil properties in that complex and non-linear forms as the soil itself. Furthermore, it has enable us to model and assess the uncertainty of the results, which is highly relevant in decision making. The applied methodology has used geostatistical approach to model the stochastic part of the spatial variability of the soil properties of interest. We created GSOC17@HU map with 1 km grid resolution according to the GSPs specifications. The map contributes to the GSPs
Robidoux, P.; Roberge, J.; Urbina Oviedo, C. A.
2011-12-01
The origin of magmatism and the role of the subducted Coco's Plate in the Chichinautzin volcanic field (CVF), Mexico is still a subject of debate. It has been established that mafic magmas of alkali type (subduction) and calc-alkali type (OIB) are produced in the CVF and both groups cannot be related by simple fractional crystallization. Therefore, many geochemical studies have been done, and many models have been proposed. The main goal of the work present here is to provide a new tool for the visualization and interpretation of geochemical data using geostatistics and geospatial analysis techniques. It contains a complete geodatabase built from referred samples over the 2500 km2 area of CVF and its neighbour stratovolcanoes (Popocatepetl, Iztaccihuatl and Nevado de Toluca). From this database, map of different geochemical markers were done to visualise geochemical signature in a geographical manner, to test the statistic distribution with a cartographic technique and highlight any spatial correlations. The distribution and regionalization of the geochemical signatures can be viewed in a two-dimensional space using a specific spatial analysis tools from a Geographic Information System (GIS). The model of spatial distribution is tested with Linear Decrease (LD) and Inverse Distance Weight (IDW) interpolation technique because they best represent the geostatistical characteristics of the geodatabase. We found that ratio of Ba/Nb, Nb/Ta, Th/Nb show first order tendency, which means visible spatial variation over a large scale area. Monogenetic volcanoes in the center of the CVF have distinct values compare to those of the Popocatepetl-Iztaccihuatl polygenetic complex which are spatially well defined. Inside the Valley of Mexico, a large quantity of monogenetic cone in the eastern portion of CVF has ratios similar to the Iztaccihuatl and Popocatepetl complex. Other ratios like alkalis vs SiO2, V/Ti, La/Yb, Zr/Y show different spatial tendencies. In that case, second
Local Geostatistical Models and Big Data in Hydrological and Ecological Applications
Hristopulos, Dionissios
2015-04-01
The advent of the big data era creates new opportunities for environmental and ecological modelling but also presents significant challenges. The availability of remote sensing images and low-cost wireless sensor networks implies that spatiotemporal environmental data to cover larger spatial domains at higher spatial and temporal resolution for longer time windows. Handling such voluminous data presents several technical and scientific challenges. In particular, the geostatistical methods used to process spatiotemporal data need to overcome the dimensionality curse associated with the need to store and invert large covariance matrices. There are various mathematical approaches for addressing the dimensionality problem, including change of basis, dimensionality reduction, hierarchical schemes, and local approximations. We present a Stochastic Local Interaction (SLI) model that can be used to model local correlations in spatial data. SLI is a random field model suitable for data on discrete supports (i.e., regular lattices or irregular sampling grids). The degree of localization is determined by means of kernel functions and appropriate bandwidths. The strength of the correlations is determined by means of coefficients. In the "plain vanilla" version the parameter set involves scale and rigidity coefficients as well as a characteristic length. The latter determines in connection with the rigidity coefficient the correlation length of the random field. The SLI model is based on statistical field theory and extends previous research on Spartan spatial random fields [2,3] from continuum spaces to explicitly discrete supports. The SLI kernel functions employ adaptive bandwidths learned from the sampling spatial distribution [1]. The SLI precision matrix is expressed explicitly in terms of the model parameter and the kernel function. Hence, covariance matrix inversion is not necessary for parameter inference that is based on leave-one-out cross validation. This property
Implementation of the Iterative Proportion Fitting Algorithm for Geostatistical Facies Modeling
International Nuclear Information System (INIS)
Li Yupeng; Deutsch, Clayton V.
2012-01-01
In geostatistics, most stochastic algorithm for simulation of categorical variables such as facies or rock types require a conditional probability distribution. The multivariate probability distribution of all the grouped locations including the unsampled location permits calculation of the conditional probability directly based on its definition. In this article, the iterative proportion fitting (IPF) algorithm is implemented to infer this multivariate probability. Using the IPF algorithm, the multivariate probability is obtained by iterative modification to an initial estimated multivariate probability using lower order bivariate probabilities as constraints. The imposed bivariate marginal probabilities are inferred from profiles along drill holes or wells. In the IPF process, a sparse matrix is used to calculate the marginal probabilities from the multivariate probability, which makes the iterative fitting more tractable and practical. This algorithm can be extended to higher order marginal probability constraints as used in multiple point statistics. The theoretical framework is developed and illustrated with estimation and simulation example.
Directory of Open Access Journals (Sweden)
Kehinde D. Oyeyemi
2017-10-01
Full Text Available The dataset for this article contains geostatistical analysis of heavy metals contamination from limestone samples collected from Ewekoro Formation in the eastern Dahomey basin, Ogun State Nigeria. The samples were manually collected and analysed using Microwave Plasma Atomic Absorption Spectrometer (MPAS. Analysis of the twenty different samples showed different levels of heavy metals concentration. The analysed nine elements are Arsenic, Mercury, Cadmium, Cobalt, Chromium, Nickel, Lead, Vanadium and Zinc. Descriptive statistics was used to explore the heavy metal concentrations individually. Pearson, Kendall tau and Spearman rho correlation coefficients was used to establish the relationships among the elements and the analysis of variance showed that there is a significant difference in the mean distribution of the heavy metals concentration within and between the groups of the 20 samples analysed. The dataset can provide insights into the health implications of the contaminants especially when the mean concentration levels of the heavy metals are compared with recommended regulatory limit concentration.
Application of Geostatistics to the resolution of structural problems in homogeneous rocky massifs
International Nuclear Information System (INIS)
Lucero Michaut, H.N.
1985-01-01
The nature and possibilities of application of intrinsic functions to the structural research and the delimitation of the areas of influence in an ore deposit are briefly described. Main models to which the different distributions may be assimilated: 'logarithmic' and 'linear' among those with no sill value, and on the other hand, 'spherical', 'exponential' and 'gaussian' among those having a sill level, which allows the establishment of a range value liable to separate the field of independent samples from that of non-independent ones are shown. Thereafter as an original contribution to applied geostatistics the autor postulates 1) the application of the 'fracturing rank' as a regionalized variable after verifying its validity through strict probabilistic methodologies, and 2) a methodological extension of the conventional criterion of 'rock quality designation' to the analysis of the quality and degree of structural discontinuity in the rock surface. Finally, some examples are given of these applications. (M.E.L.) [es
International Nuclear Information System (INIS)
Desnoyers, Yvon; De Moura, Patrick
2012-01-01
The problem of site characterization is quite complex, especially for deep radiological contamination. This article illustrates the added value of the geo-statistical processing on a real application case dealing with grounds of facilities partially dismantled at the end of the 1950's in Fontenay-aux-Roses CEA Center (France). 12 years ago, a first exploratory drill-hole confirmed the presence of a deep radiological contamination (more than 4 m deep). More recently, 8 additional drill-holes failed to delineate the contamination extension. The integration of the former topography and other geological data led to the realization of 10 additional drill holes. This final stage significantly improved the characterization of the radiological contamination, which impacted the remediation project and the initially estimated volumes. (authors)
Evaluation of permeability of compacted bentonite ground considering heterogeneity by geostatistics
International Nuclear Information System (INIS)
Tanaka, Yukihisa; Nakamura, Kunihiko; Kudo, Kohji; Hironaga, Michihiko; Nakagami, Motonori; Niwase, Kazuhito; Komatsu, Shin-ichi
2007-01-01
The permeability of the bentonite ground as an engineered barrier is possibly designed to the value which is lower than that determined in terms of required performance because of heterogeneous distribution of permeability in the ground, which might be considerable when the ground is created by the compaction method. The effect of heterogeneity in the ground on the permeability of the bentonite ground should be evaluated by overall permeability of the ground, whereas in practice, the effect is evaluated by the distribution of permeability in the ground. Thus, in this study, overall permeability of the bentonite ground is evaluated from the permeability of the bentonite ground is evaluated from the permeability distribution determined using the geostatistical method with the dry density data as well as permeability data of the undisturbed sample recovered from the bentonite ground. Consequently, it was proved through this study that possibility of overestimation of permeability of the bentonite ground can be reduced if the overall permeability is used. (author)
Geostatistical modelling of carbon monoxide levels in Khartoum State (Sudan) - GIS pilot based study
Energy Technology Data Exchange (ETDEWEB)
Alhuseen, A [Comenius University in Bratislava, Faculty of Natural Sciences, Dept. of Landscape Ecology, 84215 Bratislava (Slovakia); Madani, M [Ministry of Environment and Physical Development, 1111 Khartoum (Sudan)
2012-04-25
The objective of this study is to develop a digital GIS model; that can evaluate, predict and visualize carbon monoxide (CO) levels in Khartoum state. To achieve this aim, sample data had been collected, processed and managed to generate a dynamic GIS model of carbon monoxide levels in the study area. Parametric data collected from the field and analysis carried throughout this study show that (CO) emissions were lower than the allowable ambient air quality standards released by National Environment Protection Council (NEPC-USA) for 1998. However, this pilot study has found emissions of (CO) in Omdurman city were the highest. This pilot study shows that GIS and geostatistical modeling can be used as a powerful tool to produce maps of exposure. (authors)
Use of geostatistics in high level radioactive waste repository site characterization
Energy Technology Data Exchange (ETDEWEB)
Doctor, P G [Pacific Northwest Laboratory, Richland, WA (USA)
1980-09-01
In evaluating and characterizing sites that are candidates for use as repositories for high-level radioactive waste, there is an increasing need to estimate the uncertainty in hydrogeologic data and in the quantities calculated from them. This paper discusses the use of geostatistical techniques to estimate hydrogeologic surfaces, such as the top of a basalt formation, and to provide a measure of the uncertainty in that estimate. Maps of the uncertainty estimate, called the kriging error, can be used to evaluate where new data should be taken to affect the greatest reduction in uncertainty in the estimated surface. The methods are illustrated on a set of site-characterization data; the top-of-basalt elevations at the Hanford Site near Richland, Washington.
Yadav, Bechu K V; Nandy, S
2015-05-01
Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m × 31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10-40, 40-70 and >70% of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m(3) ha(-1). The total growing stock of the forest was found to be 2,024,652.88 m(3). The AGWB ranged from 143 to 421 Mgha(-1). Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE) = 42.25 Mgha(-1)) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha(-1) respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha(-1). The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.
Model-Based Geostatistical Mapping of the Prevalence of Onchocerca volvulus in West Africa.
Directory of Open Access Journals (Sweden)
Simon J O'Hanlon
2016-01-01
Full Text Available The initial endemicity (pre-control prevalence of onchocerciasis has been shown to be an important determinant of the feasibility of elimination by mass ivermectin distribution. We present the first geostatistical map of microfilarial prevalence in the former Onchocerciasis Control Programme in West Africa (OCP before commencement of antivectorial and antiparasitic interventions.Pre-control microfilarial prevalence data from 737 villages across the 11 constituent countries in the OCP epidemiological database were used as ground-truth data. These 737 data points, plus a set of statistically selected environmental covariates, were used in a Bayesian model-based geostatistical (B-MBG approach to generate a continuous surface (at pixel resolution of 5 km x 5km of microfilarial prevalence in West Africa prior to the commencement of the OCP. Uncertainty in model predictions was measured using a suite of validation statistics, performed on bootstrap samples of held-out validation data. The mean Pearson's correlation between observed and estimated prevalence at validation locations was 0.693; the mean prediction error (average difference between observed and estimated values was 0.77%, and the mean absolute prediction error (average magnitude of difference between observed and estimated values was 12.2%. Within OCP boundaries, 17.8 million people were deemed to have been at risk, 7.55 million to have been infected, and mean microfilarial prevalence to have been 45% (range: 2-90% in 1975.This is the first map of initial onchocerciasis prevalence in West Africa using B-MBG. Important environmental predictors of infection prevalence were identified and used in a model out-performing those without spatial random effects or environmental covariates. Results may be compared with recent epidemiological mapping efforts to find areas of persisting transmission. These methods may be extended to areas where data are sparse, and may be used to help inform the
Jalali, Mohammad; Ramazi, Hamidreza
2018-04-01
This article is devoted to application of a simulation algorithm based on geostatistical methods to compile and update seismotectonic provinces in which Iran has been chosen as a case study. Traditionally, tectonic maps together with seismological data and information (e.g., earthquake catalogues, earthquake mechanism, and microseismic data) have been used to update seismotectonic provinces. In many cases, incomplete earthquake catalogues are one of the important challenges in this procedure. To overcome this problem, a geostatistical simulation algorithm, turning band simulation, TBSIM, was applied to make a synthetic data to improve incomplete earthquake catalogues. Then, the synthetic data was added to the traditional information to study the seismicity homogeneity and classify the areas according to tectonic and seismic properties to update seismotectonic provinces. In this paper, (i) different magnitude types in the studied catalogues have been homogenized to moment magnitude (Mw), and earthquake declustering was then carried out to remove aftershocks and foreshocks; (ii) time normalization method was introduced to decrease the uncertainty in a temporal domain prior to start the simulation procedure; (iii) variography has been carried out in each subregion to study spatial regressions (e.g., west-southwestern area showed a spatial regression from 0.4 to 1.4 decimal degrees; the maximum range identified in the azimuth of 135 ± 10); (iv) TBSIM algorithm was then applied to make simulated events which gave rise to make 68,800 synthetic events according to the spatial regression found in several directions; (v) simulated events (i.e., magnitudes) were classified based on their intensity in ArcGIS packages and homogenous seismic zones have been determined. Finally, according to the synthetic data, tectonic features, and actual earthquake catalogues, 17 seismotectonic provinces were introduced in four major classes introduced as very high, high, moderate, and low
Directory of Open Access Journals (Sweden)
Pasqualina Laganà
2015-12-01
Full Text Available [b]Introduction.[/b] Legionnaires’ disease is normally acquired by inhalation of legionellae from a contaminated environmental source. Water systems of large buildings, such as hospitals, are often contaminated with legionellae and therefore represent a potential risk for the hospital population. The aim of this study was to evaluate the potential contamination of [i]Legionella pneumophila[/i] (LP in a large hospital in Italy through georeferential statistical analysis to assess the possible sources of dispersion and, consequently, the risk of exposure for both health care staff and patients. [b]Materials and Method. [/b]LP serogroups 1 and 2–14 distribution was considered in the wards housed on two consecutive floors of the hospital building. On the basis of information provided by 53 bacteriological analysis, a ‘random’ grid of points was chosen and spatial geostatistics or [i]FAIk Kriging[/i] was applied and compared with the results of classical statistical analysis. [b]Results[/b]. Over 50% of the examined samples were positive for [i]Legionella pneumophila[/i]. LP 1 was isolated in 69% of samples from the ground floor and in 60% of sample from the first floor; LP 2–14 in 36% of sample from the ground floor and 24% from the first. The iso-estimation maps show clearly the most contaminated pipe and the difference in the diffusion of the different [i]L. pneumophila[/i] serogroups. [b]Conclusion.[/b] Experimental work has demonstrated that geostatistical methods applied to the microbiological analysis of water matrices allows a better modeling of the phenomenon under study, a greater potential for risk management and a greater choice of methods of prevention and environmental recovery to be put in place with respect to the classical statistical analysis.
International Nuclear Information System (INIS)
Lund Clausen, F.
1982-05-01
The uranium deposit at Kvanefjeld within the Ilimaussaq intrusion in South Greenland has been tested by diamond drilling, hole logging, chip sampling and field gamma-spectrometric surveys. Based on these different types of spatially distributed samples the uranium variation within the deposit was studied. The spatial variation, which comprises a large random component, was modelled, and the intrinsic function was used to establish gradetonnage curves by the best linear unbiased estimator of geostatistics (kriging). From data obtained by a ground surface gamma-spectrometric survey it is shown that the uranium variation is possibly subject to a spatial anisotropy consistent with the geology. The uranium variation has a second-order stationarity. A global estimation of the total reserves shows that single block grade values are always estimated with high errors. This is mainly caused by the poor spatial structure and the very sparse sampling pattern. The best way to solve this problem appears to be a selective type of kriging. The overall uranium reserves are estimated as 23600 tons with a mean grade of 297 ppm (cutoff grade 250 ppm U). Studies of data from a test adit show that local geostatistical estimation can be done with acceptably small errors provided that a close sampling pattern is used. A regression relationship is established to correct field gamma-spectrometric measures of bulk grades towards truer values. Multivariate cluster and discriminant analyses were used to classify lujavrite samples based on their trace element content. Misclassification is due to a possibly continuous transition between naujakasite lujavrite and arfvedsonite lujavrite. Some of the main mineralogical differences between the geological units are identified by the discriminating effect of the individual variable. (author)
Terry, N.; Day-Lewis, F. D.; Werkema, D. D.; Lane, J. W., Jr.
2017-12-01
Soil moisture is a critical parameter for agriculture, water supply, and management of landfills. Whereas direct data (as from TDR or soil moisture probes) provide localized point scale information, it is often more desirable to produce 2D and/or 3D estimates of soil moisture from noninvasive measurements. To this end, geophysical methods for indirectly assessing soil moisture have great potential, yet are limited in terms of quantitative interpretation due to uncertainty in petrophysical transformations and inherent limitations in resolution. Simple tools to produce soil moisture estimates from geophysical data are lacking. We present a new standalone program, MoisturEC, for estimating moisture content distributions from electrical conductivity data. The program uses an indicator kriging method within a geostatistical framework to incorporate hard data (as from moisture probes) and soft data (as from electrical resistivity imaging or electromagnetic induction) to produce estimates of moisture content and uncertainty. The program features data visualization and output options as well as a module for calibrating electrical conductivity with moisture content to improve estimates. The user-friendly program is written in R - a widely used, cross-platform, open source programming language that lends itself to further development and customization. We demonstrate use of the program with a numerical experiment as well as a controlled field irrigation experiment. Results produced from the combined geostatistical framework of MoisturEC show improved estimates of moisture content compared to those generated from individual datasets. This application provides a convenient and efficient means for integrating various data types and has broad utility to soil moisture monitoring in landfills, agriculture, and other problems.
Directory of Open Access Journals (Sweden)
Xujun Han
Full Text Available The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL; the other is observation localization (OL. Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.
Han, Xujun; Li, Xin; Rigon, Riccardo; Jin, Rui; Endrizzi, Stefano
2015-01-01
The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.
Changing Assumptions and Progressive Change in Theories of Strategic Organization
DEFF Research Database (Denmark)
Foss, Nicolai J.; Hallberg, Niklas L.
2017-01-01
are often decoupled from the results of empirical testing, changes in assumptions seem closely intertwined with theoretical progress. Using the case of the resource-based view, we suggest that progressive change in theories of strategic organization may come about as a result of scholarly debate and dispute......A commonly held view is that strategic organization theories progress as a result of a Popperian process of bold conjectures and systematic refutations. However, our field also witnesses vibrant debates or disputes about the specific assumptions that our theories rely on, and although these debates...... over what constitutes proper assumptions—even in the absence of corroborating or falsifying empirical evidence. We also discuss how changing assumptions may drive future progress in the resource-based view....
The Emperors sham - wrong assumption that sham needling is sham.
Lundeberg, Thomas; Lund, Iréne; Näslund, Jan; Thomas, Moolamanil
2008-12-01
During the last five years a large number of randomised controlled clinical trials (RCTs) have been published on the efficacy of acupuncture in different conditions. In most of these studies verum is compared with sham acupuncture. In general both verum and sham have been found to be effective, and often with little reported difference in outcome. This has repeatedly led to the conclusion that acupuncture is no more effective than placebo treatment. However, this conclusion is based on the assumption that sham acupuncture is inert. Since sham acupuncture evidently is merely another form of acupuncture from the physiological perspective, the assumption that sham is sham is incorrect and conclusions based on this assumption are therefore invalid. Clinical guidelines based on such conclusions may therefore exclude suffering patients from valuable treatments.
Evolution of Requirements and Assumptions for Future Exploration Missions
Anderson, Molly; Sargusingh, Miriam; Perry, Jay
2017-01-01
NASA programs are maturing technologies, systems, and architectures to enabling future exploration missions. To increase fidelity as technologies mature, developers must make assumptions that represent the requirements of a future program. Multiple efforts have begun to define these requirements, including team internal assumptions, planning system integration for early demonstrations, and discussions between international partners planning future collaborations. For many detailed life support system requirements, existing NASA documents set limits of acceptable values, but a future vehicle may be constrained in other ways, and select a limited range of conditions. Other requirements are effectively set by interfaces or operations, and may be different for the same technology depending on whether the hard-ware is a demonstration system on the International Space Station, or a critical component of a future vehicle. This paper highlights key assumptions representing potential life support requirements and explanations of the driving scenarios, constraints, or other issues that drive them.
Respondent-Driven Sampling – Testing Assumptions: Sampling with Replacement
Directory of Open Access Journals (Sweden)
Barash Vladimir D.
2016-03-01
Full Text Available Classical Respondent-Driven Sampling (RDS estimators are based on a Markov Process model in which sampling occurs with replacement. Given that respondents generally cannot be interviewed more than once, this assumption is counterfactual. We join recent work by Gile and Handcock in exploring the implications of the sampling-with-replacement assumption for bias of RDS estimators. We differ from previous studies in examining a wider range of sampling fractions and in using not only simulations but also formal proofs. One key finding is that RDS estimates are surprisingly stable even in the presence of substantial sampling fractions. Our analyses show that the sampling-with-replacement assumption is a minor contributor to bias for sampling fractions under 40%, and bias is negligible for the 20% or smaller sampling fractions typical of field applications of RDS.
DDH-Like Assumptions Based on Extension Rings
DEFF Research Database (Denmark)
Cramer, Ronald; Damgård, Ivan Bjerre; Kiltz, Eike
2012-01-01
We introduce and study a new type of DDH-like assumptions based on groups of prime order q. Whereas standard DDH is based on encoding elements of $\\mathbb{F}_{q}$ “in the exponent” of elements in the group, we ask what happens if instead we put in the exponent elements of the extension ring $R_f=......-Reingold style pseudorandom functions, and auxiliary input secure encryption. This can be seen as an alternative to the known family of k-LIN assumptions....
Emerging Assumptions About Organization Design, Knowledge And Action
Directory of Open Access Journals (Sweden)
Alan Meyer
2013-12-01
Full Text Available Participants in the Organizational Design Community’s 2013 Annual Conference faced the challenge of “making organization design knowledge actionable.” This essay summarizes the opinions and insights participants shared during the conference. I reflect on these ideas, connect them to recent scholarly thinking about organization design, and conclude that seeking to make design knowledge actionable is nudging the community away from an assumption set based upon linearity and equilibrium, and toward a new set of assumptions based on emergence, self-organization, and non-linearity.
International Nuclear Information System (INIS)
Kirchner, Tom
2014-01-01
Full text: The theoretical description of ion-atom and ion-molecule collisions is a difficult task: one deals with a two-center or a multi-center problem, for which standard angular momentum expansions do not work very well, and one typically faces the problem that several processes, such as electron transfer and ionization into the continuum, compete with each other. If more than two electrons are present, the numerical solution of the full Schrödinger equation of the collision system is out of reach and assumptions and approximations have to be introduced at the outset. This is to say that one solves (at most) a model in order to describe the collision system and, as a consequence, has to deal with a two-fold problem when it comes to estimating the uncertainties and inaccuracies of the calculated data: (i) to assess the limitations of the model (which may be compared with quantifying systematic errors in an experiment); (ii) to perform careful convergence studies for the numerical procedures involved (which may be compared with narrowing statistical experimental errors). These two interrelated problems were illustrated by using a recent work on X-ray emission from a highly-charged ion after electron capture as an example. The calculations for this problem are based on the assumption that collisional capture and post-collisional de-excitation processes can be treated independently. This introduces a first systematic error, but probably a very small one, because capture and de-excitation take place on different time scales. Similarly, the assumption of a classical straight-line projectile trajectory is uncritical. Three sources of significant uncertainties are present in the collision calculation: (i) usage of the independent-electron model, (ii) usage of a finite basis set to solve the single-electron time-dependent Schrödinger equation, (iii) usage of multinomial statistics to calculate multiple (shell-specific) capture probabilities, which form the starting
Ontological, Epistemological and Methodological Assumptions: Qualitative versus Quantitative
Ahmed, Abdelhamid
2008-01-01
The review to follow is a comparative analysis of two studies conducted in the field of TESOL in Education published in "TESOL QUARTERLY." The aspects to be compared are as follows. First, a brief description of each study will be presented. Second, the ontological, epistemological and methodological assumptions underlying each study…
Evaluating The Markov Assumption For Web Usage Mining
DEFF Research Database (Denmark)
Jespersen, S.; Pedersen, Torben Bach; Thorhauge, J.
2003-01-01
) model~\\cite{borges99data}. These techniques typically rely on the \\textit{Markov assumption with history depth} $n$, i.e., it is assumed that the next requested page is only dependent on the last $n$ pages visited. This is not always valid, i.e. false browsing patterns may be discovered. However, to our...
Interface Input/Output Automata: Splitting Assumptions from Guarantees
DEFF Research Database (Denmark)
Larsen, Kim Guldstrand; Nyman, Ulrik; Wasowski, Andrzej
2006-01-01
's \\IOAs [11], relying on a context dependent notion of refinement based on relativized language inclusion. There are two main contributions of the work. First, we explicitly separate assumptions from guarantees, increasing the modeling power of the specification language and demonstrating an interesting...
Exploring five common assumptions on Attention Deficit Hyperactivity Disorder
Batstra, Laura; Nieweg, Edo H.; Hadders-Algra, Mijna
The number of children diagnosed with attention deficit hyperactivity disorder (ADHD) and treated with medication is steadily increasing. The aim of this paper was to critically discuss five debatable assumptions on ADHD that may explain these trends to some extent. These are that ADHD (i) causes
Efficient pseudorandom generators based on the DDH assumption
Rezaeian Farashahi, R.; Schoenmakers, B.; Sidorenko, A.; Okamoto, T.; Wang, X.
2007-01-01
A family of pseudorandom generators based on the decisional Diffie-Hellman assumption is proposed. The new construction is a modified and generalized version of the Dual Elliptic Curve generator proposed by Barker and Kelsey. Although the original Dual Elliptic Curve generator is shown to be
Questioning Engelhardt's assumptions in Bioethics and Secular Humanism.
Ahmadi Nasab Emran, Shahram
2016-06-01
In Bioethics and Secular Humanism: The Search for a Common Morality, Tristram Engelhardt examines various possibilities of finding common ground for moral discourse among people from different traditions and concludes their futility. In this paper I will argue that many of the assumptions on which Engelhardt bases his conclusion about the impossibility of a content-full secular bioethics are problematic. By starting with the notion of moral strangers, there is no possibility, by definition, for a content-full moral discourse among moral strangers. It means that there is circularity in starting the inquiry with a definition of moral strangers, which implies that they do not share enough moral background or commitment to an authority to allow for reaching a moral agreement, and concluding that content-full morality is impossible among moral strangers. I argue that assuming traditions as solid and immutable structures that insulate people across their boundaries is problematic. Another questionable assumption in Engelhardt's work is the idea that religious and philosophical traditions provide content-full moralities. As the cardinal assumption in Engelhardt's review of the various alternatives for a content-full moral discourse among moral strangers, I analyze his foundationalist account of moral reasoning and knowledge and indicate the possibility of other ways of moral knowledge, besides the foundationalist one. Then, I examine Engelhardt's view concerning the futility of attempts at justifying a content-full secular bioethics, and indicate how the assumptions have shaped Engelhardt's critique of the alternatives for the possibility of content-full secular bioethics.
Consequences of Violated Equating Assumptions under the Equivalent Groups Design
Lyren, Per-Erik; Hambleton, Ronald K.
2011-01-01
The equal ability distribution assumption associated with the equivalent groups equating design was investigated in the context of a selection test for admission to higher education. The purpose was to assess the consequences for the test-takers in terms of receiving improperly high or low scores compared to their peers, and to find strong…
Measuring Productivity Change without Neoclassical Assumptions: A Conceptual Analysis
B.M. Balk (Bert)
2008-01-01
textabstractThe measurement of productivity change (or difference) is usually based on models that make use of strong assumptions such as competitive behaviour and constant returns to scale. This survey discusses the basics of productivity measurement and shows that one can dispense with most if not
Child Development Knowledge and Teacher Preparation: Confronting Assumptions.
Katz, Lilian G.
This paper questions the widely held assumption that acquiring knowledge of child development is an essential part of teacher preparation and teaching competence, especially among teachers of young children. After discussing the influence of culture, parenting style, and teaching style on developmental expectations and outcomes, the paper asserts…
The Metatheoretical Assumptions of Literacy Engagement: A Preliminary Centennial History
Hruby, George G.; Burns, Leslie D.; Botzakis, Stergios; Groenke, Susan L.; Hall, Leigh A.; Laughter, Judson; Allington, Richard L.
2016-01-01
In this review of literacy education research in North America over the past century, the authors examined the historical succession of theoretical frameworks on students' active participation in their own literacy learning, and in particular the metatheoretical assumptions that justify those frameworks. The authors used "motivation" and…
Making Predictions about Chemical Reactivity: Assumptions and Heuristics
Maeyer, Jenine; Talanquer, Vicente
2013-01-01
Diverse implicit cognitive elements seem to support but also constrain reasoning in different domains. Many of these cognitive constraints can be thought of as either implicit assumptions about the nature of things or reasoning heuristics for decision-making. In this study we applied this framework to investigate college students' understanding of…
Using Contemporary Art to Challenge Cultural Values, Beliefs, and Assumptions
Knight, Wanda B.
2006-01-01
Art educators, like many other educators born or socialized within the main-stream culture of a society, seldom have an opportunity to identify, question, and challenge their cultural values, beliefs, assumptions, and perspectives because school culture typically reinforces those they learn at home and in their communities (Bush & Simmons, 1990).…
Does Artificial Neural Network Support Connectivism's Assumptions?
AlDahdouh, Alaa A.
2017-01-01
Connectivism was presented as a learning theory for the digital age and connectivists claim that recent developments in Artificial Intelligence (AI) and, more specifically, Artificial Neural Network (ANN) support their assumptions of knowledge connectivity. Yet, very little has been done to investigate this brave allegation. Does the advancement…
Discourses and Theoretical Assumptions in IT Project Portfolio Management
DEFF Research Database (Denmark)
Hansen, Lars Kristian; Kræmmergaard, Pernille
2014-01-01
DISCOURSES AND THEORETICAL ASSUMPTIONS IN IT PROJECT PORTFOLIO MANAGEMENT: A REVIEW OF THE LITERATURE These years increasing interest is put on IT project portfolio management (IT PPM). Considering IT PPM an interdisciplinary practice, we conduct a concept-based literature review of relevant...
7 CFR 1980.476 - Transfer and assumptions.
2010-01-01
...-354 449-30 to recover its pro rata share of the actual loss at that time. In completing Form FmHA or... the lender on liquidations and property management. A. The State Director may approve all transfer and... Director will notify the Finance Office of all approved transfer and assumption cases on Form FmHA or its...
Origins and Traditions in Comparative Education: Challenging Some Assumptions
Manzon, Maria
2018-01-01
This article questions some of our assumptions about the history of comparative education. It explores new scholarship on key actors and ways of knowing in the field. Building on the theory of the social constructedness of the field of comparative education, the paper elucidates how power shapes our scholarly histories and identities.
Observing gravitational-wave transient GW150914 with minimal assumptions
Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Phythian-Adams, A.T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwa, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Anderson, S. B.; Anderson, W. C.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, R.D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Behnke, B.; Bejger, M.; Bell, A. S.; Bell, C. J.; Berger, B. K.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, M.J.; Birney, R.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackburn, L.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, A.L.S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, J.G.; Bogan, C.; Bohe, A.; Bojtos, P.; Bond, T.C; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brocki, P.; Brooks, A. F.; Brown, A.D.; Brown, D.; Brown, N. M.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderon Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Diaz, J. Casanueva; Casentini, C.; Caudill, S.; Cavaglia, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Baiardi, L. Cerboni; Cerretani, G.; Cesarini, E.; Chakraborty, R.; Chatterji, S.; Chalermsongsak, T.; Chamberlin, S. J.; Chan, M.; Chao, D. S.; Charlton, P.; Chassande-Mottin, E.; Chen, H. Y.; Chen, Y; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Qian; Chua, S. E.; Chung, E.S.; Ciani, G.; Clara, F.; Clark, J. A.; Clark, M.; Cleva, F.; Coccia, E.; Cohadon, P. -F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M., Jr.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, A.C.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J. -P.; Countryman, S. T.; Couvares, P.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, A.L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dattilo, V.; Dave, I.; Daveloza, H. P.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; Debra, D.; Debreczeni, G.; Degallaix, J.; De laurentis, M.; Deleglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.A.; DeRosa, R. T.; Rosa, R.; DeSalvo, R.; Dhurandhar, S.; Diaz, M. C.; Di Fiore, L.; Giovanni, M.G.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H. -B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etzel, T.; Evans, T. M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.M.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. R.; Flaminio, R.; Fletcher, M; Fournier, J. -D.; Franco, S; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fricke, T. T.; Fritsche, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gatto, A.; Gaur, G.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.P.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; Gonzalez, Idelmis G.; Castro, J. M. Gonzalez; Gopakumar, A.; Gordon, N. A.; Gorodetsky, M. L.; Gossan, S. E.; Lee-Gosselin, M.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.M.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; de Haas, R.; Hacker, J. J.; Buffoni-Hall, R.; Hall, E. D.; Hammond, G.L.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, P.J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C. -J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hinder, I.; Hoak, D.; Hodge, K. A.; Hofman, D.; Hollitt, S. E.; Holt, K.; Holz, D. E.; Hopkins, P.; Hosken, D. J.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huang, S.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Idrisy, A.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J. -M.; Isi, M.; Islas, G.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jang, D.H.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jimenez-Forteza, F.; Johnson, W.; Jones, I.D.; Jones, R.; Jonker, R. J. G.; Ju, L.; Haris, K.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.H.; Kanner, J. B.; Karki, S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kefelian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.E.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khan, I.; Khan., S.; Khan, Z.; Khazanov, E. A.; Kijhunchoo, N.; Kim, C.; Kim, J.; Kim, K.; Kim, Nam-Gyu; Kim, Namjun; Kim, Y.M.; King, E. J.; King, P. J.; Kinsey, M.; Kinzel, D. L.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Kokeyama, K.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Krolak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Laguna, P.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Leaci, R.; Leavey, S.; Lebigot, E. O.; Lee, C.H.; Lee, K.H.; Lee, M.H.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B. M.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Logue, J.; Lombardi, A. L.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lueck, H.; Lundgren, A. P.; Luo, J.; Lynch, R.; Ma, Y.; MacDonald, T.T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magana-Sandoval, F.; Magee, R. M.; Mageswaran, M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Marka, S.; Marka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R.M.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mende, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B.C.; Moore, J.C.; Moraru, D.; Gutierrez Moreno, M.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, S.D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P.G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Gutierrez-Neri, M.; Neunzert, A.; Newton-Howes, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J.; Oh, S. H.; Ohme, F.; Oliver, M. B.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Page, J.; Paris, H. R.; Parker, W.S; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prolchorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Puerrer, M.; Qi, H.; Qin, J.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romanov, G.; Romie, J. H.; Rosinska, D.; Rowan, S.; Ruediger, A.; Ruggi, P.; Ryan, K.A.; Sachdev, P.S.; Sadecki, T.; Sadeghian, L.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J; Schmidt, P.; Schnabel, R.B.; Schofield, R. M. S.; Schoenbeck, A.; Schreiber, K.E.C.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, M.S.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Setyawati, Y.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shithriar, M. S.; Shaltev, M.; Shao, Z.M.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, António Dias da; Simakov, D.; Singer, A; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, R. J. E.; Smith, N.D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, J.R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sutton, P. J.; Swinkels, B. L.; Szczepanczyk, M. J.; Tacca, M.D.; Talukder, D.; Tanner, D. B.; Tapai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, W.R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Toyra, D.; Travasso, F.; Traylor, G.; Trifiro, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlhruch, H.; Vajente, G.; Valdes, G.; Van Bakel, N.; Van Beuzekom, Martin; Van den Brand, J. F. J.; Van Den Broeck, C.F.F.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasuth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, R. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Vicere, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J. -Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, MT; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L. -W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.M.; Wessels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Williams, D.; Williams, D.R.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Wright, J.L.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, H.; Yvert, M.; Zadrozny, A.; Zangrando, L.; Zanolin, M.; Zendri, J. -P.; Zevin, M.; Zhang, F.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.
2016-01-01
The gravitational-wave signal GW150914 was first identified on September 14, 2015, by searches for short-duration gravitational-wave transients. These searches identify time-correlated transients in multiple detectors with minimal assumptions about the signal morphology, allowing them to be
Deep Borehole Field Test Requirements and Controlled Assumptions.
Energy Technology Data Exchange (ETDEWEB)
Hardin, Ernest [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-07-01
This document presents design requirements and controlled assumptions intended for use in the engineering development and testing of: 1) prototype packages for radioactive waste disposal in deep boreholes; 2) a waste package surface handling system; and 3) a subsurface system for emplacing and retrieving packages in deep boreholes. Engineering development and testing is being performed as part of the Deep Borehole Field Test (DBFT; SNL 2014a). This document presents parallel sets of requirements for a waste disposal system and for the DBFT, showing the close relationship. In addition to design, it will also inform planning for drilling, construction, and scientific characterization activities for the DBFT. The information presented here follows typical preparations for engineering design. It includes functional and operating requirements for handling and emplacement/retrieval equipment, waste package design and emplacement requirements, borehole construction requirements, sealing requirements, and performance criteria. Assumptions are included where they could impact engineering design. Design solutions are avoided in the requirements discussion. Deep Borehole Field Test Requirements and Controlled Assumptions July 21, 2015 iv ACKNOWLEDGEMENTS This set of requirements and assumptions has benefited greatly from reviews by Gordon Appel, Geoff Freeze, Kris Kuhlman, Bob MacKinnon, Steve Pye, David Sassani, Dave Sevougian, and Jiann Su.
International Nuclear Information System (INIS)
Balcazar G, M.; Flores R, J.H.
1992-01-01
As part of the knowledge about the radiometric surface exploration, carried out in the geothermal field of Chipilapa, El Salvador, its were considered the geo-statistical parameters starting from the calculated variogram of the field data, being that the maxim distance of correlation of the samples in 'radon' in the different observation addresses (N-S, E-W, N W-S E, N E-S W), it was of 121 mts for the monitoring grill in future prospectus in the same area. Being derived of it an optimization (minimum cost) in the spacing of the field samples by means of geo-statistical techniques, without losing the detection of the anomaly. (Author)
Energy Technology Data Exchange (ETDEWEB)
De Ascencao, Erika M.; Munckton, Toni; Digregorio, Ricardo [Petropiar (Venezuela)
2011-07-01
The Huyapari field, situated within the Faja Petrolifera del Orinoco (FPO) of Venezuela presents unique problems in terms of modeling. This field is spread over a wide area and is therefore subject to variable oil quality and complex fluvial facies architecture. Ameriven and PDVSA have been working on characterizing the ld's reservoirs in this field since 2000 and the aim of this paper is to present these efforts. Among others, a 3-D seismic survey completed in 1998 and a stratigraphic framework built from 149 vertical wells were used for reservoir characterization. Geostatistical techniques such as sequential Gaussian simulation with locally varying mean and cloud transform were also used. Results showed that these geostatistical methods accurately represented the architecture and properties of the reservoir and its fluid distribution. This paper showed that the application of numerous different techniques in the Hamasca area permitted reservoir complexity to be captured.
Energy Technology Data Exchange (ETDEWEB)
Boden, S.; Jacques, D. [Institute for Environment, Health and Safety, Belgian Nuclear Research Centre (SCK-CEN), Boeretang 200, BE-2400, Mol (Belgium); Rogiers, B. [Dept. of Earth and Environmental Sciences, KU Leuven - University of Leuven Celestijnenlaan 200e - bus 2410, BE-3001, Leuven (Belgium)
2013-07-01
Reliable methods to determine the contamination depth in nuclear building structures are very much needed for minimizing the radioactive waste volume and the decontamination workload. This paper investigates the geostatistical integration of in situ gamma-ray spectroscopy measurements of different spatial supports. A case study is presented from the BR3 decommissioning project, yielding an estimated reduction of waste volume of ∼35%, and recommendations are made for future application of the proposed methodology. (authors)
Mayer, J. M.; Stead, D.
2017-04-01
With the increased drive towards deeper and more complex mine designs, geotechnical engineers are often forced to reconsider traditional deterministic design techniques in favour of probabilistic methods. These alternative techniques allow for the direct quantification of uncertainties within a risk and/or decision analysis framework. However, conventional probabilistic practices typically discretize geological materials into discrete, homogeneous domains, with attributes defined by spatially constant random variables, despite the fact that geological media display inherent heterogeneous spatial characteristics. This research directly simulates this phenomenon using a geostatistical approach, known as sequential Gaussian simulation. The method utilizes the variogram which imposes a degree of controlled spatial heterogeneity on the system. Simulations are constrained using data from the Ok Tedi mine site in Papua New Guinea and designed to randomly vary the geological strength index and uniaxial compressive strength using Monte Carlo techniques. Results suggest that conventional probabilistic techniques have a fundamental limitation compared to geostatistical approaches, as they fail to account for the spatial dependencies inherent to geotechnical datasets. This can result in erroneous model predictions, which are overly conservative when compared to the geostatistical results.
Holcomb, David Andrew; Messier, Kyle P; Serre, Marc L; Rowny, Jakob G; Stewart, Jill R
2018-06-11
Predictive modeling is promising as an inexpensive tool to assess water quality. We developed geostatistical predictive models of microbial water quality that empirically modelled spatiotemporal autocorrelation in measured fecal coliform (FC) bacteria concentrations to improve prediction. We compared five geostatistical models featuring different autocorrelation structures, fit to 676 observations from 19 locations in North Carolina's Jordan Lake watershed using meteorological and land cover predictor variables. Though stream distance metrics (with and without flow-weighting) failed to improve prediction over the Euclidean distance metric, incorporating temporal autocorrelation substantially improved prediction over the space-only models. We predicted FC throughout the stream network daily for one year, designating locations "impaired", "unimpaired", or "unassessed" if the probability of exceeding the state standard was >90%, 10% but <90%, respectively. We could assign impairment status to more of the stream network on days any FC were measured, suggesting frequent sample-based monitoring remains necessary, though implementing spatiotemporal predictive models may reduce the number of concurrent sampling locations required to adequately assess water quality. Together, these results suggest that prioritizing sampling at different times and conditions using geographically sparse monitoring networks is adequate to build robust and informative geostatistical models of water quality impairment.
Golay, Jean; Kanevski, Mikhaïl
2013-04-01
The present research deals with the exploration and modeling of a complex dataset of 200 measurement points of sediment pollution by heavy metals in Lake Geneva. The fundamental idea was to use multivariate Artificial Neural Networks (ANN) along with geostatistical models and tools in order to improve the accuracy and the interpretability of data modeling. The results obtained with ANN were compared to those of traditional geostatistical algorithms like ordinary (co)kriging and (co)kriging with an external drift. Exploratory data analysis highlighted a great variety of relationships (i.e. linear, non-linear, independence) between the 11 variables of the dataset (i.e. Cadmium, Mercury, Zinc, Copper, Titanium, Chromium, Vanadium and Nickel as well as the spatial coordinates of the measurement points and their depth). Then, exploratory spatial data analysis (i.e. anisotropic variography, local spatial correlations and moving window statistics) was carried out. It was shown that the different phenomena to be modeled were characterized by high spatial anisotropies, complex spatial correlation structures and heteroscedasticity. A feature selection procedure based on General Regression Neural Networks (GRNN) was also applied to create subsets of variables enabling to improve the predictions during the modeling phase. The basic modeling was conducted using a Multilayer Perceptron (MLP) which is a workhorse of ANN. MLP models are robust and highly flexible tools which can incorporate in a nonlinear manner different kind of high-dimensional information. In the present research, the input layer was made of either two (spatial coordinates) or three neurons (when depth as auxiliary information could possibly capture an underlying trend) and the output layer was composed of one (univariate MLP) to eight neurons corresponding to the heavy metals of the dataset (multivariate MLP). MLP models with three input neurons can be referred to as Artificial Neural Networks with EXternal
Thompson, L.M.; Van Manen, F.T.; King, T.L.
2005-01-01
Highways are one of the leading causes of wildlife habitat fragmentation and may particularly affect wide-ranging species, such as American black bears (Ursus americanus). We initiated a research project in 2000 to determine potential effects of a 4-lane highway on black bear ecology in Washington County, North Carolina. The research design included a treatment area (highway construction) and a control area and a pre- and post-construction phase. We used data from the pre-construction phase to determine whether we could detect scale dependency or directionality among allele occurrence patterns using geostatistics. Detection of such patterns could provide a powerful tool to measure the effects of landscape fragmentation on gene flow. We sampled DNA from roots of black bear hair at 70 hair-sampling sites on each study area for 7 weeks during fall of 2000. We used microsatellite analysis based on 10 loci to determine unique multi-locus genotypes. We examined all alleles sampled at ???25 sites on each study area and mapped their presence or absence at each hair-sample site. We calculated semivariograms, which measure the strength of statistical correlation as a function of distance, and adjusted them for anisotropy to determine the maximum direction of spatial continuity. We then calculated the mean direction of spatial continuity for all examined alleles. The mean direction of allele frequency variation was 118.3?? (SE = 8.5) on the treatment area and 172.3?? (SE = 6.0) on the control area. Rayleigh's tests showed that these directions differed from random distributions (P = 0.028 and P < 0.001, respectively), indicating consistent directional patterns for the alleles we examined in each area. Despite the small spatial scale of our study (approximately 11,000 ha for each study area), we observed distinct and consistent patterns of allele occurrence, suggesting different directions of gene flow between the study areas. These directions seemed to coincide with the
International Nuclear Information System (INIS)
Chen, DI-WEN
2001-01-01
Airborne hazardous plumes inadvertently released during nuclear/chemical/biological incidents are mostly of unknown composition and concentration until measurements are taken of post-accident ground concentrations from plume-ground deposition of constituents. Unfortunately, measurements often are days post-incident and rely on hazardous manned air-vehicle measurements. Before this happens, computational plume migration models are the only source of information on the plume characteristics, constituents, concentrations, directions of travel, ground deposition, etc. A mobile ''lighter than air'' (LTA) system is being developed at Oak Ridge National Laboratory that will be part of the first response in emergency conditions. These interactive and remote unmanned air vehicles will carry light-weight detectors and weather instrumentation to measure the conditions during and after plume release. This requires a cooperative computationally organized, GPS-controlled set of LTA's that self-coordinate around the objectives in an emergency situation in restricted time frames. A critical step before an optimum and cost-effective field sampling and monitoring program proceeds is the collection of data that provides statistically significant information, collected in a reliable and expeditious manner. Efficient aerial arrangements of the detectors taking the data (for active airborne release conditions) are necessary for plume identification, computational 3-dimensional reconstruction, and source distribution functions. This report describes the application of stochastic or geostatistical simulations to delineate the plume for guiding subsequent sampling and monitoring designs. A case study is presented of building digital plume images, based on existing ''hard'' experimental data and ''soft'' preliminary transport modeling results of Prairie Grass Trials Site. Markov Bayes Simulation, a coupled Bayesian/geostatistical methodology, quantitatively combines soft information
Directory of Open Access Journals (Sweden)
Goovaerts Pierre
2006-11-01
Full Text Available Abstract Background Geostatistical techniques that account for spatially varying population sizes and spatial patterns in the filtering of choropleth maps of cancer mortality were recently developed. Their implementation was facilitated by the initial assumption that all geographical units are the same size and shape, which allowed the use of geographic centroids in semivariogram estimation and kriging. Another implicit assumption was that the population at risk is uniformly distributed within each unit. This paper presents a generalization of Poisson kriging whereby the size and shape of administrative units, as well as the population density, is incorporated into the filtering of noisy mortality rates and the creation of isopleth risk maps. An innovative procedure to infer the point-support semivariogram of the risk from aggregated rates (i.e. areal data is also proposed. Results The novel methodology is applied to age-adjusted lung and cervix cancer mortality rates recorded for white females in two contrasted county geographies: 1 state of Indiana that consists of 92 counties of fairly similar size and shape, and 2 four states in the Western US (Arizona, California, Nevada and Utah forming a set of 118 counties that are vastly different geographical units. Area-to-point (ATP Poisson kriging produces risk surfaces that are less smooth than the maps created by a naïve point kriging of empirical Bayesian smoothed rates. The coherence constraint of ATP kriging also ensures that the population-weighted average of risk estimates within each geographical unit equals the areal data for this unit. Simulation studies showed that the new approach yields more accurate predictions and confidence intervals than point kriging of areal data where all counties are simply collapsed into their respective polygon centroids. Its benefit over point kriging increases as the county geography becomes more heterogeneous. Conclusion A major limitation of choropleth
Goovaerts, Pierre
2006-01-01
Background Geostatistical techniques that account for spatially varying population sizes and spatial patterns in the filtering of choropleth maps of cancer mortality were recently developed. Their implementation was facilitated by the initial assumption that all geographical units are the same size and shape, which allowed the use of geographic centroids in semivariogram estimation and kriging. Another implicit assumption was that the population at risk is uniformly distributed within each unit. This paper presents a generalization of Poisson kriging whereby the size and shape of administrative units, as well as the population density, is incorporated into the filtering of noisy mortality rates and the creation of isopleth risk maps. An innovative procedure to infer the point-support semivariogram of the risk from aggregated rates (i.e. areal data) is also proposed. Results The novel methodology is applied to age-adjusted lung and cervix cancer mortality rates recorded for white females in two contrasted county geographies: 1) state of Indiana that consists of 92 counties of fairly similar size and shape, and 2) four states in the Western US (Arizona, California, Nevada and Utah) forming a set of 118 counties that are vastly different geographical units. Area-to-point (ATP) Poisson kriging produces risk surfaces that are less smooth than the maps created by a naïve point kriging of empirical Bayesian smoothed rates. The coherence constraint of ATP kriging also ensures that the population-weighted average of risk estimates within each geographical unit equals the areal data for this unit. Simulation studies showed that the new approach yields more accurate predictions and confidence intervals than point kriging of areal data where all counties are simply collapsed into their respective polygon centroids. Its benefit over point kriging increases as the county geography becomes more heterogeneous. Conclusion A major limitation of choropleth maps is the common biased
Models for waste life cycle assessment: Review of technical assumptions
DEFF Research Database (Denmark)
Gentil, Emmanuel; Damgaard, Anders; Hauschild, Michael Zwicky
2010-01-01
A number of waste life cycle assessment (LCA) models have been gradually developed since the early 1990s, in a number of countries, usually independently from each other. Large discrepancies in results have been observed among different waste LCA models, although it has also been shown that results...... from different LCA studies can be consistent. This paper is an attempt to identify, review and analyse methodologies and technical assumptions used in various parts of selected waste LCA models. Several criteria were identified, which could have significant impacts on the results......, such as the functional unit, system boundaries, waste composition and energy modelling. The modelling assumptions of waste management processes, ranging from collection, transportation, intermediate facilities, recycling, thermal treatment, biological treatment, and landfilling, are obviously critical when comparing...
Validity of the mockwitness paradigm: testing the assumptions.
McQuiston, Dawn E; Malpass, Roy S
2002-08-01
Mockwitness identifications are used to provide a quantitative measure of lineup fairness. Some theoretical and practical assumptions of this paradigm have not been studied in terms of mockwitnesses' decision processes and procedural variation (e.g., instructions, lineup presentation method), and the current experiment was conducted to empirically evaluate these assumptions. Four hundred and eighty mockwitnesses were given physical information about a culprit, received 1 of 4 variations of lineup instructions, and were asked to identify the culprit from either a fair or unfair sequential lineup containing 1 of 2 targets. Lineup bias estimates varied as a result of lineup fairness and the target presented. Mockwitnesses generally reported that the target's physical description was their main source of identifying information. Our findings support the use of mockwitness identifications as a useful technique for sequential lineup evaluation, but only for mockwitnesses who selected only 1 lineup member. Recommendations for the use of this evaluation procedure are discussed.
Determining Bounds on Assumption Errors in Operational Analysis
Directory of Open Access Journals (Sweden)
Neal M. Bengtson
2014-01-01
Full Text Available The technique of operational analysis (OA is used in the study of systems performance, mainly for estimating mean values of various measures of interest, such as, number of jobs at a device and response times. The basic principles of operational analysis allow errors in assumptions to be quantified over a time period. The assumptions which are used to derive the operational analysis relationships are studied. Using Karush-Kuhn-Tucker (KKT conditions bounds on error measures of these OA relationships are found. Examples of these bounds are used for representative performance measures to show limits on the difference between true performance values and those estimated by operational analysis relationships. A technique for finding tolerance limits on the bounds is demonstrated with a simulation example.
The sufficiency assumption of the reasoned approach to action
Directory of Open Access Journals (Sweden)
David Trafimow
2015-12-01
Full Text Available The reasoned action approach to understanding and predicting behavior includes the sufficiency assumption. Although variables not included in the theory may influence behavior, these variables work through the variables in the theory. Once the reasoned action variables are included in an analysis, the inclusion of other variables will not increase the variance accounted for in behavioral intentions or behavior. Reasoned action researchers are very concerned with testing if new variables account for variance (or how much traditional variables account for variance, to see whether they are important, in general or with respect to specific behaviors under investigation. But this approach tacitly assumes that accounting for variance is highly relevant to understanding the production of variance, which is what really is at issue. Based on the variance law, I question this assumption.
Forecasting Value-at-Risk under Different Distributional Assumptions
Directory of Open Access Journals (Sweden)
Manuela Braione
2016-01-01
Full Text Available Financial asset returns are known to be conditionally heteroskedastic and generally non-normally distributed, fat-tailed and often skewed. These features must be taken into account to produce accurate forecasts of Value-at-Risk (VaR. We provide a comprehensive look at the problem by considering the impact that different distributional assumptions have on the accuracy of both univariate and multivariate GARCH models in out-of-sample VaR prediction. The set of analyzed distributions comprises the normal, Student, Multivariate Exponential Power and their corresponding skewed counterparts. The accuracy of the VaR forecasts is assessed by implementing standard statistical backtesting procedures used to rank the different specifications. The results show the importance of allowing for heavy-tails and skewness in the distributional assumption with the skew-Student outperforming the others across all tests and confidence levels.
Energy Technology Data Exchange (ETDEWEB)
Costa Reis, L.
2001-01-01
We have developed in this thesis a methodology of integrated characterization of heterogeneous reservoirs, from geologic modeling to history matching. This methodology is applied to the reservoir PBR, situated in Campos Basin, offshore Brazil, which has been producing since June 1979. This work is an extension of two other thesis concerning geologic and geostatistical modeling of the reservoir PBR from well data and seismic information. We extended the geostatistical litho-type model to the whole reservoir by using a particular approach of the non-stationary truncated Gaussian simulation method. This approach facilitated the application of the gradual deformation method to history matching. The main stages of the methodology for dynamic data integration in a geostatistical reservoir model are presented. We constructed a reservoir model and the initial difficulties in the history matching led us to modify some choices in the geological, geostatistical and flow models. These difficulties show the importance of dynamic data integration in reservoir modeling. The petrophysical property assignment within the litho-types was done by using well test data. We used an inversion procedure to evaluate the petrophysical parameters of the litho-types. The up-scaling is a necessary stage to reduce the flow simulation time. We compared several up-scaling methods and we show that the passage from the fine geostatistical model to the coarse flow model should be done very carefully. The choice of the fitting parameter depends on the objective of the study. In the case of the reservoir PBR, where water is injected in order to improve the oil recovery, the water rate of the producing wells is directly related to the reservoir heterogeneity. Thus, the water rate was chosen as the fitting parameter. We obtained significant improvements in the history matching of the reservoir PBR. First, by using a method we have proposed, called patchwork. This method allows us to built a coherent
Sensitivity of probabilistic MCO water content estimates to key assumptions
International Nuclear Information System (INIS)
DUNCAN, D.R.
1999-01-01
Sensitivity of probabilistic multi-canister overpack (MCO) water content estimates to key assumptions is evaluated with emphasis on the largest non-cladding film-contributors, water borne by particulates adhering to damage sites, and water borne by canister particulate. Calculations considered different choices of damage state degree of independence, different choices of percentile for reference high inputs, three types of input probability density function (pdfs): triangular, log-normal, and Weibull, and the number of scrap baskets in an MCO
Spatial Angular Compounding for Elastography without the Incompressibility Assumption
Rao, Min; Varghese, Tomy
2005-01-01
Spatial-angular compounding is a new technique that enables the reduction of noise artifacts in ultrasound elastography. Previous results using spatial angular compounding, however, were based on the use of the tissue incompressibility assumption. Compounded elastograms were obtained from a spatially-weighted average of local strain estimated from radiofrequency echo signals acquired at different insonification angles. In this paper, we present a new method for reducing the noise artifacts in...
Estimators for longitudinal latent exposure models: examining measurement model assumptions.
Sánchez, Brisa N; Kim, Sehee; Sammel, Mary D
2017-06-15
Latent variable (LV) models are increasingly being used in environmental epidemiology as a way to summarize multiple environmental exposures and thus minimize statistical concerns that arise in multiple regression. LV models may be especially useful when multivariate exposures are collected repeatedly over time. LV models can accommodate a variety of assumptions but, at the same time, present the user with many choices for model specification particularly in the case of exposure data collected repeatedly over time. For instance, the user could assume conditional independence of observed exposure biomarkers given the latent exposure and, in the case of longitudinal latent exposure variables, time invariance of the measurement model. Choosing which assumptions to relax is not always straightforward. We were motivated by a study of prenatal lead exposure and mental development, where assumptions of the measurement model for the time-changing longitudinal exposure have appreciable impact on (maximum-likelihood) inferences about the health effects of lead exposure. Although we were not particularly interested in characterizing the change of the LV itself, imposing a longitudinal LV structure on the repeated multivariate exposure measures could result in high efficiency gains for the exposure-disease association. We examine the biases of maximum likelihood estimators when assumptions about the measurement model for the longitudinal latent exposure variable are violated. We adapt existing instrumental variable estimators to the case of longitudinal exposures and propose them as an alternative to estimate the health effects of a time-changing latent predictor. We show that instrumental variable estimators remain unbiased for a wide range of data generating models and have advantages in terms of mean squared error. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Data-driven smooth tests of the proportional hazards assumption
Czech Academy of Sciences Publication Activity Database
Kraus, David
2007-01-01
Roč. 13, č. 1 (2007), s. 1-16 ISSN 1380-7870 R&D Projects: GA AV ČR(CZ) IAA101120604; GA ČR(CZ) GD201/05/H007 Institutional research plan: CEZ:AV0Z10750506 Keywords : Cox model * Neyman's smooth test * proportional hazards assumption * Schwarz's selection rule Subject RIV: BA - General Mathematics Impact factor: 0.491, year: 2007
Assumptions behind size-based ecosystem models are realistic
DEFF Research Database (Denmark)
Andersen, Ken Haste; Blanchard, Julia L.; Fulton, Elizabeth A.
2016-01-01
A recent publication about balanced harvesting (Froese et al., ICES Journal of Marine Science; doi:10.1093/icesjms/fsv122) contains several erroneous statements about size-spectrum models. We refute the statements by showing that the assumptions pertaining to size-spectrum models discussed by Fro...... that there is indeed a constructive role for a wide suite of ecosystem models to evaluate fishing strategies in an ecosystem context...
Bank stress testing under different balance sheet assumptions
Busch, Ramona; Drescher, Christian; Memmel, Christoph
2017-01-01
Using unique supervisory survey data on the impact of a hypothetical interest rate shock on German banks, we analyse price and quantity effects on banks' net interest margin components under different balance sheet assumptions. In the first year, the cross-sectional variation of banks' simulated price effect is nearly eight times as large as the one of the simulated quantity effect. After five years, however, the importance of both effects converges. Large banks adjust their balance sheets mo...
The incompressibility assumption in computational simulations of nasal airflow.
Cal, Ismael R; Cercos-Pita, Jose Luis; Duque, Daniel
2017-06-01
Most of the computational works on nasal airflow up to date have assumed incompressibility, given the low Mach number of these flows. However, for high temperature gradients, the incompressibility assumption could lead to a loss of accuracy, due to the temperature dependence of air density and viscosity. In this article we aim to shed some light on the influence of this assumption in a model of calm breathing in an Asian nasal cavity, by solving the fluid flow equations in compressible and incompressible formulation for different ambient air temperatures using the OpenFOAM package. At low flow rates and warm climatological conditions, similar results were obtained from both approaches, showing that density variations need not be taken into account to obtain a good prediction of all flow features, at least for usual breathing conditions. This agrees with most of the simulations previously reported, at least as far as the incompressibility assumption is concerned. However, parameters like nasal resistance and wall shear stress distribution differ for air temperatures below [Formula: see text]C approximately. Therefore, density variations should be considered for simulations at such low temperatures.
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Marcin Kiedrzyński
2014-07-01
Full Text Available Attempts to study biodiversity hotspots on a regional scale should combine compositional and functionalist criteria. The detection of hotspots in this study uses one ecologically similar group of high conservation value species as hotspot indicators, as well as focal habitat indicators, to detect the distribution of suitable environmental conditions. The method is assessed with reference to thermophilous forests in Poland – key habitats for many rare and relict species. Twenty-six high conservation priority species were used as hotspot indicators, and ten plant taxa characteristic of the Quercetalia pubescenti-petraeae phytosociological order were used as focal habitat indicators. Species distribution data was based on a 10 × 10 km grid. The number of species per grid square was interpolated by the ordinary kriging geostatistical method. Our analysis largely determined the distribution of areas with concentration of thermophilous forest flora, but also regional disjunctions and geographical barriers. Indicator species richness can be interpreted as a reflection of the actual state of habitat conditions. It can also be used to determine the location of potential species refugia and possible past and future migration routes.
Geostatistical Approach to Find ‘Hotspots’ Where Biodiversity is at Risk in a Transition Country
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Petrişor Alexandru-Ionuţ
2014-10-01
Full Text Available Global change‟ is a relatively recent concept, related to the energy - land use - climate change nexus, and designated to include all changes produced by the human species and the consequences of its activities over natural ecological complexes and biodiversity. The joint effects of these drivers of change are particularly relevant to understanding the changes of biodiversity. This study overlaps results of previous studies developed in Romania to find, explain and predict potential threats on biodiversity, including the effects of very high temperatures and low precipitations, urban sprawl and deforestation in order to identify „hotspots‟ of high risk for the loss of biodiversity using geostatistical tools. The results found two hotspots, one in the center and the other one in the south, and show that the area affected by three factors simultaneously represents 0.2% of the national territory, while paired effects cover 4% of it. The methodological advantage of this approach is its capacity to pinpoint hotspots with practical relevance. Nevertheless, its generalizing character impairs its use at the local scale..
A general parallelization strategy for random path based geostatistical simulation methods
Mariethoz, Grégoire
2010-07-01
The size of simulation grids used for numerical models has increased by many orders of magnitude in the past years, and this trend is likely to continue. Efficient pixel-based geostatistical simulation algorithms have been developed, but for very large grids and complex spatial models, the computational burden remains heavy. As cluster computers become widely available, using parallel strategies is a natural step for increasing the usable grid size and the complexity of the models. These strategies must profit from of the possibilities offered by machines with a large number of processors. On such machines, the bottleneck is often the communication time between processors. We present a strategy distributing grid nodes among all available processors while minimizing communication and latency times. It consists in centralizing the simulation on a master processor that calls other slave processors as if they were functions simulating one node every time. The key is to decouple the sending and the receiving operations to avoid synchronization. Centralization allows having a conflict management system ensuring that nodes being simulated simultaneously do not interfere in terms of neighborhood. The strategy is computationally efficient and is versatile enough to be applicable to all random path based simulation methods.
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Jay Ram Lamichhane
Full Text Available Incidence of Xanthomonas arboricola pv. corylina, the causal agent of hazelnut bacterial blight, was analyzed spatially in relation to the pedoclimatic factors. Hazelnut grown in twelve municipalities situated in the province of Viterbo, central Italy was studied. A consistent number of bacterial isolates were obtained from the infected tissues of hazelnut collected in three years (2010-2012. The isolates, characterized by phenotypic tests, did not show any difference among them. Spatial patterns of pedoclimatic data, analyzed by geostatistics showed a strong positive correlation of disease incidence with higher values of rainfall, thermal shock and soil nitrogen; a weak positive correlation with soil aluminium content and a strong negative correlation with the values of Mg/K ratio. No correlation of the disease incidence was found with soil pH. Disease incidence ranged from very low (<1% to very high (almost 75% across the orchards. Young plants (4-year old were the most affected by the disease confirming a weak negative correlation of the disease incidence with plant age. Plant cultivars did not show any difference in susceptibility to the pathogen. Possible role of climate change on the epidemiology of the disease is discussed. Improved management practices are recommended for effective control of the disease.
Kolyaie, S.; Yaghooti, M.; Majidi, G.
2011-12-01
This paper is a part of an ongoing research to examine the capability of geostatistical analysis for mobile networks coverage prediction, simulation and tuning. Mobile network coverage predictions are used to find network coverage gaps and areas with poor serviceability. They are essential data for engineering and management in order to make better decision regarding rollout, planning and optimisation of mobile networks.The objective of this research is to evaluate different interpolation techniques in coverage prediction. In method presented here, raw data collected from drive testing a sample of roads in study area is analysed and various continuous surfaces are created using different interpolation methods. Two general interpolation methods are used in this paper with different variables; first, Inverse Distance Weighting (IDW) with various powers and number of neighbours and second, ordinary kriging with Gaussian, spherical, circular and exponential semivariogram models with different number of neighbours. For the result comparison, we have used check points coming from the same drive test data. Prediction values for check points are extracted from each surface and the differences with actual value are computed. The output of this research helps finding an optimised and accurate model for coverage prediction.
Forward modeling of gravity data using geostatistically generated subsurface density variations
Phelps, Geoffrey
2016-01-01
Using geostatistical models of density variations in the subsurface, constrained by geologic data, forward models of gravity anomalies can be generated by discretizing the subsurface and calculating the cumulative effect of each cell (pixel). The results of such stochastically generated forward gravity anomalies can be compared with the observed gravity anomalies to find density models that match the observed data. These models have an advantage over forward gravity anomalies generated using polygonal bodies of homogeneous density because generating numerous realizations explores a larger region of the solution space. The stochastic modeling can be thought of as dividing the forward model into two components: that due to the shape of each geologic unit and that due to the heterogeneous distribution of density within each geologic unit. The modeling demonstrates that the internally heterogeneous distribution of density within each geologic unit can contribute significantly to the resulting calculated forward gravity anomaly. Furthermore, the stochastic models match observed statistical properties of geologic units, the solution space is more broadly explored by producing a suite of successful models, and the likelihood of a particular conceptual geologic model can be compared. The Vaca Fault near Travis Air Force Base, California, can be successfully modeled as a normal or strike-slip fault, with the normal fault model being slightly more probable. It can also be modeled as a reverse fault, although this structural geologic configuration is highly unlikely given the realizations we explored.
Geostatistics for Mapping Leaf Area Index over a Cropland Landscape: Efficiency Sampling Assessment
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Javier Garcia-Haro
2010-11-01
Full Text Available This paper evaluates the performance of spatial methods to estimate leaf area index (LAI fields from ground-based measurements at high-spatial resolution over a cropland landscape. Three geostatistical model variants of the kriging technique, the ordinary kriging (OK, the collocated cokriging (CKC and kriging with an external drift (KED are used. The study focused on the influence of the spatial sampling protocol, auxiliary information, and spatial resolution in the estimates. The main advantage of these models lies in the possibility of considering the spatial dependence of the data and, in the case of the KED and CKC, the auxiliary information for each location used for prediction purposes. A high-resolution NDVI image computed from SPOT TOA reflectance data is used as an auxiliary variable in LAI predictions. The CKC and KED predictions have proven the relevance of the auxiliary information to reproduce the spatial pattern at local scales, proving the KED model to be the best estimator when a non-stationary trend is observed. Advantages and limitations of the methods in LAI field predictions for two systematic and two stratified spatial samplings are discussed for high (20 m, medium (300 m and coarse (1 km spatial scales. The KED has exhibited the best observed local accuracy for all the spatial samplings. Meanwhile, the OK model provides comparable results when a well stratified sampling scheme is considered by land cover.
Spatiotemporal mapping of ground water pollution in a Greek lignite basin, using geostatistics
International Nuclear Information System (INIS)
Modis, K.
2010-01-01
An issue of significant interest in the mining industry in Greece is the occurrence of chemical pollutants in ground water. Ammonium, nitrites and nitrates concentrations have been monitored through an extensive sampling network in the Ptolemais lignite opencast mining area in Greece. Due to intensive mining efforts in the area, the surface topology is continuously altered, affecting the life span of the water boreholes and resulting in messy spatiotemporal distribution of data. This paper discussed the spatiotemporal mapping of ground water pollution in the Ptolemais lignite basin, using geostatistics. More specifically, the spatiotemporal distribution of ground water contamination was examined by the application of the bayesian maximum entropy theory which allows merging spatial and temporal estimations in a single model. The paper provided a description of the site and discussed the materials and methods, including samples and statistics; variography; and spatiotemporal mapping. It was concluded that in the case of the Ptolemais mining area, results revealed an underlying average yearly variation pattern of pollutant concentrations. Inspection of the produced spatiotemporal maps demonstrated a continuous increase in the risk of ammonium contamination, while risk for the other two pollutants appeared in hot spots. 18 refs., 1 tab., 7 figs.
Directory of Open Access Journals (Sweden)
Tammy M. Milillo
2017-03-01
Full Text Available The choice of a relevant, uncontaminated site for the determination of site-specific background concentrations for pollutants is critical for planning remediation of a contaminated site. The guidelines used to arrive at concentration levels vary from state to state, complicating this process. The residential neighborhood of Hickory Woods in Buffalo, NY is an area where heavy metal concentrations and spatial distributions were measured to plan remediation. A novel geostatistics based decision making framework that relies on maps generated from indicator kriging (IK and indicator co-kriging (ICK of samples from the contaminated site itself is shown to be a viable alternative to the traditional method of choosing a reference site for remediation planning. GIS based IK and ICK, and map based analysis are performed on lead and arsenic surface and subsurface datasets to determine site-specific background concentration levels were determined to be 50 μg/g for lead and 10 μg/g for arsenic. With these results, a remediation plan was proposed which identified regions of interest and maps were created to effectively communicate the results to the environmental agencies, residents and other interested parties.
Kolosionis, Konstantinos; Papadopoulou, Maria P.
2017-04-01
Monitoring networks provide essential information for water resources management especially in areas with significant groundwater exploitation due to extensive agricultural activities. In this work, a simulation-optimization framework is developed based on heuristic optimization methodologies and geostatistical modeling approaches to obtain an optimal design for a groundwater quality monitoring network. Groundwater quantity and quality data obtained from 43 existing observation locations at 3 different hydrological periods in Mires basin in Crete, Greece will be used in the proposed framework in terms of Regression Kriging to develop the spatial distribution of nitrates concentration in the aquifer of interest. Based on the existing groundwater quality mapping, the proposed optimization tool will determine a cost-effective observation wells network that contributes significant information to water managers and authorities. The elimination of observation wells that add little or no beneficial information to groundwater level and quality mapping of the area can be obtain using estimations uncertainty and statistical error metrics without effecting the assessment of the groundwater quality. Given the high maintenance cost of groundwater monitoring networks, the proposed tool could used by water regulators in the decision-making process to obtain a efficient network design that is essential.
Zha, Yuanyuan; Yeh, Tian-Chyi J.; Illman, Walter A.; Zeng, Wenzhi; Zhang, Yonggen; Sun, Fangqiang; Shi, Liangsheng
2018-03-01
Hydraulic tomography (HT) is a recently developed technology for characterizing high-resolution, site-specific heterogeneity using hydraulic data (nd) from a series of cross-hole pumping tests. To properly account for the subsurface heterogeneity and to flexibly incorporate additional information, geostatistical inverse models, which permit a large number of spatially correlated unknowns (ny), are frequently used to interpret the collected data. However, the memory storage requirements for the covariance of the unknowns (ny × ny) in these models are prodigious for large-scale 3-D problems. Moreover, the sensitivity evaluation is often computationally intensive using traditional difference method (ny forward runs). Although employment of the adjoint method can reduce the cost to nd forward runs, the adjoint model requires intrusive coding effort. In order to resolve these issues, this paper presents a Reduced-Order Successive Linear Estimator (ROSLE) for analyzing HT data. This new estimator approximates the covariance of the unknowns using Karhunen-Loeve Expansion (KLE) truncated to nkl order, and it calculates the directional sensitivities (in the directions of nkl eigenvectors) to form the covariance and cross-covariance used in the Successive Linear Estimator (SLE). In addition, the covariance of unknowns is updated every iteration by updating the eigenvalues and eigenfunctions. The computational advantages of the proposed algorithm are demonstrated through numerical experiments and a 3-D transient HT analysis of data from a highly heterogeneous field site.
International Nuclear Information System (INIS)
Wahid, Ali; Salim, Ahmed Mohamed Ahmed; Yusoff, Wan Ismail Wan; Gaafar, Gamal Ragab
2016-01-01
Geostatistics or statistical approach is based on the studies of temporal and spatial trend, which depend upon spatial relationships to model known information of variable(s) at unsampled locations. The statistical technique known as kriging was used for petrophycial and facies analysis, which help to assume spatial relationship to model the geological continuity between the known data and the unknown to produce a single best guess of the unknown. Kriging is also known as optimal interpolation technique, which facilitate to generate best linear unbiased estimation of each horizon. The idea is to construct a numerical model of the lithofacies and rock properties that honor available data and further integrate with interpreting seismic sections, techtonostratigraphy chart with sea level curve (short term) and regional tectonics of the study area to find the structural and stratigraphic growth history of the NW Bonaparte Basin. By using kriging technique the models were built which help to estimate different parameters like horizons, facies, and porosities in the study area. The variograms were used to determine for identification of spatial relationship between data which help to find the depositional history of the North West (NW) Bonaparte Basin
Goovaerts, P; Albuquerque, Teresa; Antunes, Margarida
2016-11-01
This paper describes a multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration, with an application to an abandoned sedimentary gold mining region in Portugal. The main challenge was the existence of only a dozen gold measurements confined to the grounds of the old gold mines, which precluded the application of traditional interpolation techniques, such as cokriging. The analysis could, however, capitalize on 376 stream sediment samples that were analyzed for twenty two elements. Gold (Au) was first predicted at all 376 locations using linear regression (R 2 =0.798) and four metals (Fe, As, Sn and W), which are known to be mostly associated with the local gold's paragenesis. One hundred realizations of the spatial distribution of gold content were generated using sequential indicator simulation and a soft indicator coding of regression estimates, to supplement the hard indicator coding of gold measurements. Each simulated map then underwent a local cluster analysis to identify significant aggregates of low or high values. The one hundred classified maps were processed to derive the most likely classification of each simulated node and the associated probability of occurrence. Examining the distribution of the hot-spots and cold-spots reveals a clear enrichment in Au along the Erges River downstream from the old sedimentary mineralization.
Assessing TCE source bioremediation by geostatistical analysis of a flux fence.
Cai, Zuansi; Wilson, Ryan D; Lerner, David N
2012-01-01
Mass discharge across transect planes is increasingly used as a metric for performance assessment of in situ groundwater remediation systems. Mass discharge estimates using concentrations measured in multilevel transects are often made by assuming a uniform flow field, and uncertainty contributions from spatial concentration and flow field variability are often overlooked. We extend our recently developed geostatistical approach to estimate mass discharge using transect data of concentration and hydraulic conductivity, so accounting for the spatial variability of both datasets. The magnitude and uncertainty of mass discharge were quantified by conditional simulation. An important benefit of the approach is that uncertainty is quantified as an integral part of the mass discharge estimate. We use this approach for performance assessment of a bioremediation experiment of a trichloroethene (TCE) source zone. Analyses of dissolved parent and daughter compounds demonstrated that the engineered bioremediation has elevated the degradation rate of TCE, resulting in a two-thirds reduction in the TCE mass discharge from the source zone. The biologically enhanced dissolution of TCE was not significant (~5%), and was less than expected. However, the discharges of the daughter products cis-1,2, dichloroethene (cDCE) and vinyl chloride (VC) increased, probably because of the rapid transformation of TCE from the source zone to the measurement transect. This suggests that enhancing the biodegradation of cDCE and VC will be crucial to successful engineered bioremediation of TCE source zones. © 2012, The Author(s). Ground Water © 2012, National Ground Water Association.
Messier, Kyle P; Akita, Yasuyuki; Serre, Marc L
2012-03-06
Geographic information systems (GIS) based techniques are cost-effective and efficient methods used by state agencies and epidemiology researchers for estimating concentration and exposure. However, budget limitations have made statewide assessments of contamination difficult, especially in groundwater media. Many studies have implemented address geocoding, land use regression, and geostatistics independently, but this is the first to examine the benefits of integrating these GIS techniques to address the need of statewide exposure assessments. A novel framework for concentration exposure is introduced that integrates address geocoding, land use regression (LUR), below detect data modeling, and Bayesian Maximum Entropy (BME). A LUR model was developed for tetrachloroethylene that accounts for point sources and flow direction. We then integrate the LUR model into the BME method as a mean trend while also modeling below detects data as a truncated Gaussian probability distribution function. We increase available PCE data 4.7 times from previously available databases through multistage geocoding. The LUR model shows significant influence of dry cleaners at short ranges. The integration of the LUR model as mean trend in BME results in a 7.5% decrease in cross validation mean square error compared to BME with a constant mean trend.
Reyes, Jeanette M; Hubbard, Heidi F; Stiegel, Matthew A; Pleil, Joachim D; Serre, Marc L
2018-01-09
Currently in the United States there are no regulatory standards for ambient concentrations of polycyclic aromatic hydrocarbons (PAHs), a class of organic compounds with known carcinogenic species. As such, monitoring data are not routinely collected resulting in limited exposure mapping and epidemiologic studies. This work develops the log-mass fraction (LMF) Bayesian maximum entropy (BME) geostatistical prediction method used to predict the concentration of nine particle-bound PAHs across the US state of North Carolina. The LMF method develops a relationship between a relatively small number of collocated PAH and fine Particulate Matter (PM2.5) samples collected in 2005 and applies that relationship to a larger number of locations where PM2.5 is routinely monitored to more broadly estimate PAH concentrations across the state. Cross validation and mapping results indicate that by incorporating both PAH and PM2.5 data, the LMF BME method reduces mean squared error by 28.4% and produces more realistic spatial gradients compared to the traditional kriging approach based solely on observed PAH data. The LMF BME method efficiently creates PAH predictions in a PAH data sparse and PM2.5 data rich setting, opening the door for more expansive epidemiologic exposure assessments of ambient PAH.
A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data
Liang, Faming
2013-03-01
The Gaussian geostatistical model has been widely used in modeling of spatial data. However, it is challenging to computationally implement this method because it requires the inversion of a large covariance matrix, particularly when there is a large number of observations. This article proposes a resampling-based stochastic approximation method to address this challenge. At each iteration of the proposed method, a small subsample is drawn from the full dataset, and then the current estimate of the parameters is updated accordingly under the framework of stochastic approximation. Since the proposed method makes use of only a small proportion of the data at each iteration, it avoids inverting large covariance matrices and thus is scalable to large datasets. The proposed method also leads to a general parameter estimation approach, maximum mean log-likelihood estimation, which includes the popular maximum (log)-likelihood estimation (MLE) approach as a special case and is expected to play an important role in analyzing large datasets. Under mild conditions, it is shown that the estimator resulting from the proposed method converges in probability to a set of parameter values of equivalent Gaussian probability measures, and that the estimator is asymptotically normally distributed. To the best of the authors\\' knowledge, the present study is the first one on asymptotic normality under infill asymptotics for general covariance functions. The proposed method is illustrated with large datasets, both simulated and real. Supplementary materials for this article are available online. © 2013 American Statistical Association.
International Nuclear Information System (INIS)
Becker, J.K.; Marschall, P.; Brunner, P.; Cholet, C.; Renard, P.; Buckley, S.; Kurz, T.
2012-01-01
Document available in extended abstract form only. Flow and transport processes in geological formations are controlled by the porosity and permeability which in turn are mainly controlled by the fabric and the mineralogical composition of the rock. For the assessment of transport processes in water-saturated Clay-stone formations, the relevant scales are ranging essentially from kilometers to nanometers. The spatial variability of the mineralogical composition is a key indicator for the separation of transport scales and for the derivation of the effective transport properties at a given scale. Various laboratory and in-situ techniques are available for characterizing the mineralogical composition of a rock on different scales. The imaging spectroscopy presented in this paper is a new site investigation method suitable for mapping the mineralogical composition of geological formations in 2D on a large range of scales. A combination of imaging spectrometry with other site characterization methods allows the inference of the spatial variability of the mineralogical composition in 3D over a wide range of scales with the help of advanced geostatistical methods. The method of image spectrometry utilizes the fact that the reflection of electromagnetic radiation from a surface is a function of the wavelength, the chemical-mineralogical surface properties, and physical parameters such as the grain size and surface roughness. In remote sensing applications using the sun as the light source, the reflectance is measured within the visible and infrared range, according to the atmospheric transmissibility. Many rock-forming minerals exhibit diagnostic absorption features within this range, which are caused by electronic and vibrational processes within the crystal lattice. The exact wavelength of an absorption feature is controlled by the type of ion, as well as the position of the ion within the lattice. Spectral signatures of minerals are described by a number of authors
Geostatistical three-dimensional modeling of oolite shoals, St. Louis Limestone, southwest Kansas
Qi, L.; Carr, T.R.; Goldstein, R.H.
2007-01-01
In the Hugoton embayment of southwestern Kansas, reservoirs composed of relatively thin (Big Bow and Sand Arroyo Creek fields. Lithofacies in uncored wells were predicted from digital logs using a neural network. The tilting effect from the Laramide orogeny was removed to construct restored structural surfaces at the time of deposition. Well data and structural maps were integrated to build 3-D models of oolitic reservoirs using stochastic simulations with geometry data. Three-dimensional models provide insights into the distribution, the external and internal geometry of oolitic deposits, and the sedimentologic processes that generated reservoir intervals. The structural highs and general structural trend had a significant impact on the distribution and orientation of the oolitic complexes. The depositional pattern and connectivity analysis suggest an overall aggradation of shallow-marine deposits during pulses of relative sea level rise followed by deepening near the top of the St. Louis Limestone. Cemented oolitic deposits were modeled as barriers and baffles and tend to concentrate at the edge of oolitic complexes. Spatial distribution of porous oolitic deposits controls the internal geometry of rock properties. Integrated geostatistical modeling methods can be applicable to other complex carbonate or siliciclastic reservoirs in shallow-marine settings. Copyright ?? 2007. The American Association of Petroleum Geologists. All rights reserved.
Geostatistics as a tool to study mite dispersion in physic nut plantations.
Rosado, J F; Picanço, M C; Sarmento, R A; Pereira, R M; Pedro-Neto, M; Galdino, T V S; de Sousa Saraiva, A; Erasmo, E A L
2015-08-01
Spatial distribution studies in pest management identify the locations where pest attacks on crops are most severe, enabling us to understand and predict the movement of such pests. Studies on the spatial distribution of two mite species, however, are rather scarce. The mites Polyphagotarsonemus latus and Tetranychus bastosi are the major pests affecting physic nut plantations (Jatropha curcas). Therefore, the objective of this study was to measure the spatial distributions of P. latus and T. bastosi in the physic nut plantations. Mite densities were monitored over 2 years in two different plantations. Sample locations were georeferenced. The experimental data were analyzed using geostatistical analyses. The total mite density was found to be higher when only one species was present (T. bastosi). When both the mite species were found in the same plantation, their peak densities occurred at different times. These mites, however, exhibited uniform spatial distribution when found at extreme densities (low or high). However, the mites showed an aggregated distribution in intermediate densities. Mite spatial distribution models were isotropic. Mite colonization commenced at the periphery of the areas under study, whereas the high-density patches extended until they reached 30 m in diameter. This has not been reported for J. curcas plants before.
Geostatistical methods in the assessment of the spatial variability of the quality of river water
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Krasowska Małgorzata
2017-01-01
Full Text Available The research was conducted in the agricultural catchment in north–eastern Poland. The aim of this study was to check how geostatistical analysis can be useful for the detection zones and forms of supply stream by water from different sources. The work was included the implementation of hydrochemical profiles. These profiles were made by measuring the electrical conductivity (EC values and temperature along the river. On the basis of these results, the authors calculated the coefficient of Moran I and performed semivariogram and found that the EC values are correlated on a stretch of about 140 m. This means that the spatial correlation between samples of water in the stream is readable over a distance of about 140 meters. Therefore it is believed that the degree of water mineralization on this section is shaped by water entering the river channel migration in different ways: through tributaries, leachate drainage and surface runoff. In the case of the analyzed catchment, the potential sources of pollution were drainage systems. Therefore, the spatial analysis allowed the identification pollution sources in a catchment, especially in drained agricultural catchments.
A Bayesian spatio-temporal geostatistical model with an auxiliary lattice for large datasets
Xu, Ganggang
2015-01-01
When spatio-temporal datasets are large, the computational burden can lead to failures in the implementation of traditional geostatistical tools. In this paper, we propose a computationally efficient Bayesian hierarchical spatio-temporal model in which the spatial dependence is approximated by a Gaussian Markov random field (GMRF) while the temporal correlation is described using a vector autoregressive model. By introducing an auxiliary lattice on the spatial region of interest, the proposed method is not only able to handle irregularly spaced observations in the spatial domain, but it is also able to bypass the missing data problem in a spatio-temporal process. Because the computational complexity of the proposed Markov chain Monte Carlo algorithm is of the order O(n) with n the total number of observations in space and time, our method can be used to handle very large spatio-temporal datasets with reasonable CPU times. The performance of the proposed model is illustrated using simulation studies and a dataset of precipitation data from the coterminous United States.
International Nuclear Information System (INIS)
Lucero Michaut, H.N.
1980-01-01
After presenting some general conceptual considerations regarding the theory of regionalized variables, the paper deals with specific applications of the intrinsic dispersion law to the determination, description and quantification of structures. It then briefly describes two uranium deposits in Cordoba province, the study of which yielded the basic data and parameters for compiling the geostatistical results presented. Before taking up the matter of structural interpretations, it refers briefly to the mathematical relationship between the number of sampling points available and the number of directions that can be investigated by the variogram method and also emphasizes the need for quantifying regionalization concepts on the basis of a table of absolute dimensionalities. In the case of the ''Rodolfo'' deposit it presents and comments on the hemivariograms for concentrations, thicknesses and accumulations, drawing attention at the same time to the existence of significant nest-like phenomena (gigogne structures). In this connection there is also a discussion of the case of iterative lenticular mineralization on a natural and a simulated model. The ''Schlagintweit'' deposit is dealt with in the same way, with descriptions and evaluations of the subjacent structures revealed by the hemivariographic analysis of grades, mineralization thicknesses and accumulations. This is followed by some considerations on the possibility of applying Krige and Matheron correctors in the moderation of anomalous mineralized thicknesses. In conclusion, the paper presents a ''range ellipse'' for grades; this is designed to supplement the grid of sampling points for the ''Rodolfo'' deposit by means of Matheronian kriging techniques. (author)
Rodrigo-Ilarri, J.; Li, T.; Grathwohl, P.; Blum, P.; Bayer, P.
2009-04-01
The design of geothermal systems such as aquifer thermal energy storage systems (ATES) must account for a comprehensive characterisation of all relevant parameters considered for the numerical design model. Hydraulic and thermal conductivities are the most relevant parameters and its distribution determines not only the technical design but also the economic viability of such systems. Hence, the knowledge of the spatial distribution of these parameters is essential for a successful design and operation of such systems. This work shows the first results obtained when applying geostatistical techniques to the characterisation of the Esseling Site in Germany. In this site a long-term thermal tracer test (> 1 year) was performed. On this open system the spatial temperature distribution inside the aquifer was observed over time in order to obtain as much information as possible that yield to a detailed characterisation both of the hydraulic and thermal relevant parameters. This poster shows the preliminary results obtained for the Esseling Site. It has been observed that the common homogeneous approach is not sufficient to explain the observations obtained from the TRT and that parameter heterogeneity must be taken into account.
Geostatistical methods for rock mass quality prediction using borehole and geophysical survey data
Chen, J.; Rubin, Y.; Sege, J. E.; Li, X.; Hehua, Z.
2015-12-01
For long, deep tunnels, the number of geotechnical borehole investigations during the preconstruction stage is generally limited. Yet tunnels are often constructed in geological structures with complex geometries, and in which the rock mass is fragmented from past structural deformations. Tunnel Geology Prediction (TGP) is a geophysical technique widely used during tunnel construction in China to ensure safety during construction and to prevent geological disasters. In this paper, geostatistical techniques were applied in order to integrate seismic velocity from TGP and borehole information into spatial predictions of RMR (Rock Mass Rating) in unexcavated areas. This approach is intended to apply conditional probability methods to transform seismic velocities to directly observed RMR values. The initial spatial distribution of RMR, inferred from the boreholes, was updated by including geophysical survey data in a co-kriging approach. The method applied to a real tunnel project shows significant improvements in rock mass quality predictions after including geophysical survey data, leading to better decision-making for construction safety design.
Spatiotemporal mapping of ground water pollution in a Greek lignite basin, using geostatistics
Energy Technology Data Exchange (ETDEWEB)
Modis, K. [National Technical Univ. of Athens, Athens (Greece)
2010-07-01
An issue of significant interest in the mining industry in Greece is the occurrence of chemical pollutants in ground water. Ammonium, nitrites and nitrates concentrations have been monitored through an extensive sampling network in the Ptolemais lignite opencast mining area in Greece. Due to intensive mining efforts in the area, the surface topology is continuously altered, affecting the life span of the water boreholes and resulting in messy spatiotemporal distribution of data. This paper discussed the spatiotemporal mapping of ground water pollution in the Ptolemais lignite basin, using geostatistics. More specifically, the spatiotemporal distribution of ground water contamination was examined by the application of the bayesian maximum entropy theory which allows merging spatial and temporal estimations in a single model. The paper provided a description of the site and discussed the materials and methods, including samples and statistics; variography; and spatiotemporal mapping. It was concluded that in the case of the Ptolemais mining area, results revealed an underlying average yearly variation pattern of pollutant concentrations. Inspection of the produced spatiotemporal maps demonstrated a continuous increase in the risk of ammonium contamination, while risk for the other two pollutants appeared in hot spots. 18 refs., 1 tab., 7 figs.
LSHSIM: A Locality Sensitive Hashing based method for multiple-point geostatistics
Moura, Pedro; Laber, Eduardo; Lopes, Hélio; Mesejo, Daniel; Pavanelli, Lucas; Jardim, João; Thiesen, Francisco; Pujol, Gabriel
2017-10-01
Reservoir modeling is a very important task that permits the representation of a geological region of interest, so as to generate a considerable number of possible scenarios. Since its inception, many methodologies have been proposed and, in the last two decades, multiple-point geostatistics (MPS) has been the dominant one. This methodology is strongly based on the concept of training image (TI) and the use of its characteristics, which are called patterns. In this paper, we propose a new MPS method that combines the application of a technique called Locality Sensitive Hashing (LSH), which permits to accelerate the search for patterns similar to a target one, with a Run-Length Encoding (RLE) compression technique that speeds up the calculation of the Hamming similarity. Experiments with both categorical and continuous images show that LSHSIM is computationally efficient and produce good quality realizations. In particular, for categorical data, the results suggest that LSHSIM is faster than MS-CCSIM, one of the state-of-the-art methods.
Wallace, C.S.A.; Marsh, S.E.
2005-01-01
Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts. ?? 2005 Taylor & Francis Group Ltd.
International Nuclear Information System (INIS)
Sauquet, Eric
2004-01-01
Regional hydrology is one topic that shows real improvement in partly due to new statistical development and computation facilities. Nevertheless theoretical difficulties for mapping river regime characteristics or recover these features at un gauged location remain because of the nature of the variable under study: river flows are related to a specific area that is defined by the drainage basin, are spatially organised by the river network with upstream-downstream dependencies. Estimations of hydrological descriptors are required for studying links with ecological processes at different spatial scale, from local site where biological or/and water quality data are available to large scale for sustainable development purposes. This presentation aims at describing a method for runoff pattern along the main river network. The approach dedicated to mean annual runoff is based on geostatistical interpolation procedures to which a constraint of water budget has been added. Expansion in Empirical Orthogonal Function has been considered in combination with kriging for interpolating mean monthly discharges. The methodologies are implemented within a Geographical Information System and illustrated by two study cases (two large basins in France). River flow regime descriptors are estimated for basins of more than 50km 2 . Opportunities of collaboration with a partition of France into hydro-eco regions derived from geology and climate considerations is discussed. (Author)
Directory of Open Access Journals (Sweden)
Peter W Gething
2006-06-01
Full Text Available Reliable and timely information on disease-specific treatment burdens within a health system is critical for the planning and monitoring of service provision. Health management information systems (HMIS exist to address this need at national scales across Africa but are failing to deliver adequate data because of widespread underreporting by health facilities. Faced with this inadequacy, vital public health decisions often rely on crudely adjusted regional and national estimates of treatment burdens.This study has taken the example of presumed malaria in outpatients within the largely incomplete Kenyan HMIS database and has defined a geostatistical modelling framework that can predict values for all data that are missing through space and time. The resulting complete set can then be used to define treatment burdens for presumed malaria at any level of spatial and temporal aggregation. Validation of the model has shown that these burdens are quantified to an acceptable level of accuracy at the district, provincial, and national scale.The modelling framework presented here provides, to our knowledge for the first time, reliable information from imperfect HMIS data to support evidence-based decision-making at national and sub-national levels.
Energy Technology Data Exchange (ETDEWEB)
Wahid, Ali, E-mail: ali.wahid@live.com; Salim, Ahmed Mohamed Ahmed, E-mail: mohamed.salim@petronas.com.my; Yusoff, Wan Ismail Wan, E-mail: wanismail-wanyusoff@petronas.com.my [Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610 Tronoh, Perak (Malaysia); Gaafar, Gamal Ragab, E-mail: gaafargr@gmail.com [Petroleum Engineering Division, PETRONAS Carigali Sdn Bhd, Kuala Lumpur (Malaysia)
2016-02-01
Geostatistics or statistical approach is based on the studies of temporal and spatial trend, which depend upon spatial relationships to model known information of variable(s) at unsampled locations. The statistical technique known as kriging was used for petrophycial and facies analysis, which help to assume spatial relationship to model the geological continuity between the known data and the unknown to produce a single best guess of the unknown. Kriging is also known as optimal interpolation technique, which facilitate to generate best linear unbiased estimation of each horizon. The idea is to construct a numerical model of the lithofacies and rock properties that honor available data and further integrate with interpreting seismic sections, techtonostratigraphy chart with sea level curve (short term) and regional tectonics of the study area to find the structural and stratigraphic growth history of the NW Bonaparte Basin. By using kriging technique the models were built which help to estimate different parameters like horizons, facies, and porosities in the study area. The variograms were used to determine for identification of spatial relationship between data which help to find the depositional history of the North West (NW) Bonaparte Basin.
Energy Technology Data Exchange (ETDEWEB)
Hammond, Glenn Edward; Song, Xuehang; Ye, Ming; Dai, Zhenxue; Zachara, John; Chen, Xingyuan
2017-03-01
A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. The spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.
Definition of radon prone areas in Friuli Venezia Giulia region, Italy, using geostatistical tools.
Cafaro, C; Bossew, P; Giovani, C; Garavaglia, M
2014-12-01
Studying the geographical distribution of indoor radon concentration, using geostatistical interpolation methods, has become common for predicting and estimating the risk to the population. Here we analyse the case of Friuli Venezia Giulia (FVG), the north easternmost region of Italy. Mean value and standard deviation are, respectively, 153 Bq/m(3) and 183 Bq/m(3). The geometric mean value is 100 Bq/m(3). Spatial datasets of indoor radon concentrations are usually affected by clustering and apparent non-stationarity issues, which can eventually yield arguable results. The clustering of the present dataset seems to be non preferential. Therefore the areal estimations are not expected to be affected. Conversely, nothing can be said on the non stationarity issues and its effects. After discussing the correlation of geology with indoor radon concentration It appears they are created by the same geologic features influencing the mean and median values, and can't be eliminated via a map-based approach. To tackle these problems, in this work we deal with multiple definitions of RPA, but only in quaternary areas of FVG, using extensive simulation techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.
Definition of radon prone areas in Friuli Venezia Giulia region, Italy, using geostatistical tools
International Nuclear Information System (INIS)
Cafaro, C.; Bossew, P.; Giovani, C.; Garavaglia, M.
2014-01-01
Studying the geographical distribution of indoor radon concentration, using geostatistical interpolation methods, has become common for predicting and estimating the risk to the population. Here we analyse the case of Friuli Venezia Giulia (FVG), the north easternmost region of Italy. Mean value and standard deviation are, respectively, 153 Bq/m 3 and 183 Bq/m 3 . The geometric mean value is 100 Bq/m 3 . Spatial datasets of indoor radon concentrations are usually affected by clustering and apparent non-stationarity issues, which can eventually yield arguable results. The clustering of the present dataset seems to be non preferential. Therefore the areal estimations are not expected to be affected. Conversely, nothing can be said on the non stationarity issues and its effects. After discussing the correlation of geology with indoor radon concentration It appears they are created by the same geologic features influencing the mean and median values, and can't be eliminated via a map-based approach. To tackle these problems, in this work we deal with multiple definitions of RPA, but only in quaternary areas of FVG, using extensive simulation techniques. - Highlights: • The data are clustered in a preferential way, but natural clustering renders preferentiality undetectable. • Different soil classes lead to different variograms, then the database is divided to improve predictions. • The geological classes do not improve the quality of prediction more than a quadratic drift and yield arguable results. • Simulation conditioned by kriging are used to solve the change of support problem
Masoud, Alaa A.; El-Horiny, Mohamed M.; Atwia, Mohamed G.; Gemail, Khaled S.; Koike, Katsuaki
2018-06-01
Salinization of groundwater and soil resources has long been a serious environmental hazard in arid regions. This study was conducted to investigate and document the factors controlling such salinization and their inter-relationships in the Dakhla Oasis (Egypt). To accomplish this, 60 groundwater samples and 31 soil samples were collected in February 2014. Factor analysis (FA) and hierarchical cluster analysis (HCA) were integrated with geostatistical analyses to characterize the chemical properties of groundwater and soil and their spatial patterns, identify the factors controlling the pattern variability, and clarify the salinization mechanism. Groundwater quality standards revealed emergence of salinization (av. 885.8 mg/L) and extreme occurrences of Fe2+ (av. 17.22 mg/L) and Mn2+ (av. 2.38 mg/L). Soils were highly salt-affected (av. 15.2 dS m-1) and slightly alkaline (av. pH = 7.7). Evaporation and ion-exchange processes governed the evolution of two main water types: Na-Cl (52%) and Ca-Mg-Cl (47%), respectively. Salinization leads the chemical variability of both resources. Distinctive patterns of slight salinization marked the northern part and intense salinization marked the middle and southern parts. Congruence in the resources clusters confirmed common geology, soil types, and urban and agricultural practices. Minimizing the environmental and socioeconomic impacts of the resources salinization urges the need for better understanding of the hydrochemical characteristics and prediction of quality changes.
Visser, A; Moran, J E; Hillegonds, Darren; Singleton, M J; Kulongoski, Justin T; Belitz, Kenneth; Esser, B K
2016-03-15
Key characteristics of California groundwater systems related to aquifer vulnerability, sustainability, recharge locations and mechanisms, and anthropogenic impact on recharge are revealed in a spatial geostatistical analysis of a unique data set of tritium, noble gases and other isotopic analyses unprecedented in size at nearly 4000 samples. The correlation length of key groundwater residence time parameters varies between tens of kilometers ((3)H; age) to the order of a hundred kilometers ((4)Heter; (14)C; (3)Hetrit). The correlation length of parameters related to climate, topography and atmospheric processes is on the order of several hundred kilometers (recharge temperature; δ(18)O). Young groundwater ages that highlight regional recharge areas are located in the eastern San Joaquin Valley, in the southern Santa Clara Valley Basin, in the upper LA basin and along unlined canals carrying Colorado River water, showing that much of the recent recharge in central and southern California is dominated by river recharge and managed aquifer recharge. Modern groundwater is found in wells with the top open intervals below 60 m depth in the southeastern San Joaquin Valley, Santa Clara Valley and Los Angeles basin, as the result of intensive pumping and/or managed aquifer recharge operations. Copyright © 2016 Elsevier Ltd. All rights reserved.
Mapping of Aspergillus Section Nigri in Southern Europe and Israel based on geostatistical analysis.
Battilani, P; Barbano, C; Marin, S; Sanchis, V; Kozakiewicz, Z; Magan, N
2006-09-01
Geostatistical analysis was applied to the incidence of Aspergillus Section Nigri and A. carbonarius in Southern Europe and Israel for the 3-year period 2001-2003 to facilitate identification of regions of high risk from contamination with these fungi and production of ochratoxin. The highest incidence of black aspergilli was normally observed at harvesting. At this grape growth stage, spatial variability of black aspergilli was significantly related to latitude and longitude, showing a positive West-East and North-South gradient. Predictive maps of infected berries incidence were drawn and showed the same trend in the 3 years, but incidence was highest in 2003, followed by 2001 and 2002. The highest incidence was always observed in Israel, Greece and Southern France, associated with the highest incidence of A. carbonarius. Southern Spain and Southern Italy also had relevant incidence of black aspergilli. The thermo-wetness maps for the 3 years showed a trend similar to the incidence of black aspergilli. The coldest and wettest year was 2002, while 2003 was the hottest and driest, particularly during August, with Israel being the hottest and driest country, followed by Greece and Southern Italy. This indicates that meteorological conditions can contribute to explain spatial distribution variation of black aspergilli within the Mediterranean basin.
Maurya, S. P.; Singh, K. H.; Singh, N. P.
2018-05-01
In present study, three recently developed geostatistical methods, single attribute analysis, multi-attribute analysis and probabilistic neural network algorithm have been used to predict porosity in inter well region for Blackfoot field, Alberta, Canada, an offshore oil field. These techniques make use of seismic attributes, generated by model based inversion and colored inversion techniques. The principle objective of the study is to find the suitable combination of seismic inversion and geostatistical techniques to predict porosity and identification of prospective zones in 3D seismic volume. The porosity estimated from these geostatistical approaches is corroborated with the well log porosity. The results suggest that all the three implemented geostatistical methods are efficient and reliable to predict the porosity but the multi-attribute and probabilistic neural network analysis provide more accurate and high resolution porosity sections. A low impedance (6000-8000 m/s g/cc) and high porosity (> 15%) zone is interpreted from inverted impedance and porosity sections respectively between 1060 and 1075 ms time interval and is characterized as reservoir. The qualitative and quantitative results demonstrate that of all the employed geostatistical methods, the probabilistic neural network along with model based inversion is the most efficient method for predicting porosity in inter well region.
THE COMPLEX OF ASSUMPTION CATHEDRAL OF THE ASTRAKHAN KREMLIN
Directory of Open Access Journals (Sweden)
Savenkova Aleksandra Igorevna
2016-08-01
Full Text Available This article is devoted to an architectural and historical analysis of the constructions forming a complex of Assumption Cathedral of the Astrakhan Kremlin, which earlier hasn’t been considered as a subject of special research. Basing on the archival sources, photographic materials, publications and on-site investigations of monuments, the creation history of the complete architectural complex sustained in one style of the Muscovite baroque, unique in its composite construction, is considered. Its interpretation in the all-Russian architectural context is offered. Typological features of single constructions come to light. The typology of the Prechistinsky bell tower has an untypical architectural solution - “hexagonal structure on octagonal and quadrangular structures”. The way of connecting the building of the Cathedral and the chambers by the passage was characteristic of monastic constructions and was exclusively seldom in kremlins, farmsteads and ensembles of city cathedrals. The composite scheme of the Assumption Cathedral includes the Lobnoye Mesto (“the Place of Execution” located on an axis from the West, it is connected with the main building by a quarter-turn with landing. The only prototype of the structure is a Lobnoye Mesto on the Red Square in Moscow. In the article the version about the emergence of the Place of Execution on the basis of earlier existing construction - a tower “the Peal” which is repeatedly mentioned in written sources in connection with S. Razin’s revolt is considered. The metropolitan Sampson, trying to keep the value of the Astrakhan metropolitanate, builds the Assumption Cathedral and the Place of Execution directly appealing to a capital prototype to emphasize the continuity and close connection with Moscow.
Are Prescription Opioids Driving the Opioid Crisis? Assumptions vs Facts.
Rose, Mark Edmund
2018-04-01
Sharp increases in opioid prescriptions, and associated increases in overdose deaths in the 2000s, evoked widespread calls to change perceptions of opioid analgesics. Medical literature discussions of opioid analgesics began emphasizing patient and public health hazards. Repetitive exposure to this information may influence physician assumptions. While highly consequential to patients with pain whose function and quality of life may benefit from opioid analgesics, current assumptions about prescription opioid analgesics, including their role in the ongoing opioid overdose epidemic, have not been scrutinized. Information was obtained by searching PubMed, governmental agency websites, and conference proceedings. Opioid analgesic prescribing and associated overdose deaths both peaked around 2011 and are in long-term decline; the sharp overdose increase recorded in 2014 was driven by illicit fentanyl and heroin. Nonmethadone prescription opioid analgesic deaths, in the absence of co-ingested benzodiazepines, alcohol, or other central nervous system/respiratory depressants, are infrequent. Within five years of initial prescription opioid misuse, 3.6% initiate heroin use. The United States consumes 80% of the world opioid supply, but opioid access is nonexistent for 80% and severely restricted for 4.1% of the global population. Many current assumptions about opioid analgesics are ill-founded. Illicit fentanyl and heroin, not opioid prescribing, now fuel the current opioid overdose epidemic. National discussion has often neglected the potentially devastating effects of uncontrolled chronic pain. Opioid analgesic prescribing and related overdoses are in decline, at great cost to patients with pain who have benefited or may benefit from, but cannot access, opioid analgesic therapy.
Radiation hormesis and the linear-no-threshold assumption
Sanders, Charles L
2009-01-01
Current radiation protection standards are based upon the application of the linear no-threshold (LNT) assumption, which considers that even very low doses of ionizing radiation can cause cancer. The radiation hormesis hypothesis, by contrast, proposes that low-dose ionizing radiation is beneficial. In this book, the author examines all facets of radiation hormesis in detail, including the history of the concept and mechanisms, and presents comprehensive, up-to-date reviews for major cancer types. It is explained how low-dose radiation can in fact decrease all-cause and all-cancer mortality an
First assumptions and overlooking competing causes of death
DEFF Research Database (Denmark)
Leth, Peter Mygind; Andersen, Anh Thao Nguyen
2014-01-01
Determining the most probable cause of death is important, and it is sometimes tempting to assume an obvious cause of death, when it readily presents itself, and stop looking for other competing causes of death. The case story presented in the article illustrates this dilemma. The first assumption...... of cause of death, which was based on results from bacteriology tests, proved to be wrong when the results from the forensic toxicology testing became available. This case also illustrates how post mortem computed tomography (PMCT) findings of radio opaque material in the stomach alerted the pathologist...
Assumptions of Corporate Social Responsibility as Competitiveness Factor
Directory of Open Access Journals (Sweden)
Zaneta Simanaviciene
2017-09-01
Full Text Available The purpose of this study was to examine the assumptions of corporate social responsibility (CSR as competitiveness factor in economic downturn. Findings indicate that factors affecting the quality of the micro-economic business environment, i.e., the sophistication of enterprise’s strategy and management processes, the quality of the human capital resources, the increase of product / service demand, the development of related and supporting sectors and the efficiency of natural resources, and competitive capacities of enterprise impact competitiveness at a micro-level. The outcomes suggest that the implementation of CSR elements, i.e., economic, environmental and social responsibilities, gives good opportunities to increase business competitiveness.
ψ -ontology result without the Cartesian product assumption
Myrvold, Wayne C.
2018-05-01
We introduce a weakening of the preparation independence postulate of Pusey et al. [Nat. Phys. 8, 475 (2012), 10.1038/nphys2309] that does not presuppose that the space of ontic states resulting from a product-state preparation can be represented by the Cartesian product of subsystem state spaces. On the basis of this weakened assumption, it is shown that, in any model that reproduces the quantum probabilities, any pair of pure quantum states |ψ >,|ϕ > with ≤1 /√{2 } must be ontologically distinct.
Unconditionally Secure and Universally Composable Commitments from Physical Assumptions
DEFF Research Database (Denmark)
Damgård, Ivan Bjerre; Scafuro, Alessandra
2013-01-01
We present a constant-round unconditional black-box compiler that transforms any ideal (i.e., statistically-hiding and statistically-binding) straight-line extractable commitment scheme, into an extractable and equivocal commitment scheme, therefore yielding to UC-security [9]. We exemplify the u...... of unconditional UC-security with (malicious) PUFs and stateless tokens, our compiler can be instantiated with any ideal straight-line extractable commitment scheme, thus allowing the use of various setup assumptions which may better fit the application or the technology available....
International Nuclear Information System (INIS)
Hashemi, Seyyedhossein; Javaherian, Abdolrahim; Ataee-pour, Majid; Khoshdel, Hossein
2014-01-01
Facies models try to explain facies architectures which have a primary control on the subsurface heterogeneities and the fluid flow characteristics of a given reservoir. In the process of facies modeling, geostatistical methods are implemented to integrate different sources of data into a consistent model. The facies models should describe facies interactions; the shape and geometry of the geobodies as they occur in reality. Two distinct categories of geostatistical techniques are two-point and multiple-point (geo) statistics (MPS). In this study, both of the aforementioned categories were applied to generate facies models. A sequential indicator simulation (SIS) and a truncated Gaussian simulation (TGS) represented two-point geostatistical methods, and a single normal equation simulation (SNESIM) selected as an MPS simulation representative. The dataset from an extremely channelized carbonate reservoir located in southwest Iran was applied to these algorithms to analyze their performance in reproducing complex curvilinear geobodies. The SNESIM algorithm needs consistent training images (TI) in which all possible facies architectures that are present in the area are included. The TI model was founded on the data acquired from modern occurrences. These analogies delivered vital information about the possible channel geometries and facies classes that are typically present in those similar environments. The MPS results were conditioned to both soft and hard data. Soft facies probabilities were acquired from a neural network workflow. In this workflow, seismic-derived attributes were implemented as the input data. Furthermore, MPS realizations were conditioned to hard data to guarantee the exact positioning and continuity of the channel bodies. A geobody extraction workflow was implemented to extract the most certain parts of the channel bodies from the seismic data. These extracted parts of the channel bodies were applied to the simulation workflow as hard data
Drug policy in sport: hidden assumptions and inherent contradictions.
Smith, Aaron C T; Stewart, Bob
2008-03-01
This paper considers the assumptions underpinning the current drugs-in-sport policy arrangements. We examine the assumptions and contradictions inherent in the policy approach, paying particular attention to the evidence that supports different policy arrangements. We find that the current anti-doping policy of the World Anti-Doping Agency (WADA) contains inconsistencies and ambiguities. WADA's policy position is predicated upon four fundamental principles; first, the need for sport to set a good example; secondly, the necessity of ensuring a level playing field; thirdly, the responsibility to protect the health of athletes; and fourthly, the importance of preserving the integrity of sport. A review of the evidence, however, suggests that sport is a problematic institution when it comes to setting a good example for the rest of society. Neither is it clear that sport has an inherent or essential integrity that can only be sustained through regulation. Furthermore, it is doubtful that WADA's anti-doping policy is effective in maintaining a level playing field, or is the best means of protecting the health of athletes. The WADA anti-doping policy is based too heavily on principals of minimising drug use, and gives insufficient weight to the minimisation of drug-related harms. As a result drug-related harms are being poorly managed in sport. We argue that anti-doping policy in sport would benefit from placing greater emphasis on a harm minimisation model.
The extended evolutionary synthesis: its structure, assumptions and predictions
Laland, Kevin N.; Uller, Tobias; Feldman, Marcus W.; Sterelny, Kim; Müller, Gerd B.; Moczek, Armin; Jablonka, Eva; Odling-Smee, John
2015-01-01
Scientific activities take place within the structured sets of ideas and assumptions that define a field and its practices. The conceptual framework of evolutionary biology emerged with the Modern Synthesis in the early twentieth century and has since expanded into a highly successful research program to explore the processes of diversification and adaptation. Nonetheless, the ability of that framework satisfactorily to accommodate the rapid advances in developmental biology, genomics and ecology has been questioned. We review some of these arguments, focusing on literatures (evo-devo, developmental plasticity, inclusive inheritance and niche construction) whose implications for evolution can be interpreted in two ways—one that preserves the internal structure of contemporary evolutionary theory and one that points towards an alternative conceptual framework. The latter, which we label the ‘extended evolutionary synthesis' (EES), retains the fundaments of evolutionary theory, but differs in its emphasis on the role of constructive processes in development and evolution, and reciprocal portrayals of causation. In the EES, developmental processes, operating through developmental bias, inclusive inheritance and niche construction, share responsibility for the direction and rate of evolution, the origin of character variation and organism–environment complementarity. We spell out the structure, core assumptions and novel predictions of the EES, and show how it can be deployed to stimulate and advance research in those fields that study or use evolutionary biology. PMID:26246559
Basic concepts and assumptions behind the new ICRP recommendations
International Nuclear Information System (INIS)
Lindell, B.
1979-01-01
A review is given of some of the basic concepts and assumptions behind the current recommendations by the International Commission on Radiological Protection in ICRP Publications 26 and 28, which form the basis for the revision of the Basic Safety Standards jointly undertaken by IAEA, ILO, NEA and WHO. Special attention is given to the assumption of a linear, non-threshold dose-response relationship for stochastic radiation effects such as cancer and hereditary harm. The three basic principles of protection are discussed: justification of practice, optimization of protection and individual risk limitation. In the new ICRP recommendations particular emphasis is given to the principle of keeping all radiation doses as low as is reasonably achievable. A consequence of this is that the ICRP dose limits are now given as boundary conditions for the justification and optimization procedures rather than as values that should be used for purposes of planning and design. The fractional increase in total risk at various ages after continuous exposure near the dose limits is given as an illustration. The need for taking other sources, present and future, into account when applying the dose limits leads to the use of the commitment concept. This is briefly discussed as well as the new quantity, the effective dose equivalent, introduced by ICRP. (author)
Stable isotopes and elasmobranchs: tissue types, methods, applications and assumptions.
Hussey, N E; MacNeil, M A; Olin, J A; McMeans, B C; Kinney, M J; Chapman, D D; Fisk, A T
2012-04-01
Stable-isotope analysis (SIA) can act as a powerful ecological tracer with which to examine diet, trophic position and movement, as well as more complex questions pertaining to community dynamics and feeding strategies or behaviour among aquatic organisms. With major advances in the understanding of the methodological approaches and assumptions of SIA through dedicated experimental work in the broader literature coupled with the inherent difficulty of studying typically large, highly mobile marine predators, SIA is increasingly being used to investigate the ecology of elasmobranchs (sharks, skates and rays). Here, the current state of SIA in elasmobranchs is reviewed, focusing on available tissues for analysis, methodological issues relating to the effects of lipid extraction and urea, the experimental dynamics of isotopic incorporation, diet-tissue discrimination factors, estimating trophic position, diet and mixing models and individual specialization and niche-width analyses. These areas are discussed in terms of assumptions made when applying SIA to the study of elasmobranch ecology and the requirement that investigators standardize analytical approaches. Recommendations are made for future SIA experimental work that would improve understanding of stable-isotope dynamics and advance their application in the study of sharks, skates and rays. © 2012 The Authors. Journal of Fish Biology © 2012 The Fisheries Society of the British Isles.
Has the "Equal Environments" assumption been tested in twin studies?
Eaves, Lindon; Foley, Debra; Silberg, Judy
2003-12-01
A recurring criticism of the twin method for quantifying genetic and environmental components of human differences is the necessity of the so-called "equal environments assumption" (EEA) (i.e., that monozygotic and dizygotic twins experience equally correlated environments). It has been proposed to test the EEA by stratifying twin correlations by indices of the amount of shared environment. However, relevant environments may also be influenced by genetic differences. We present a model for the role of genetic factors in niche selection by twins that may account for variation in indices of the shared twin environment (e.g., contact between members of twin pairs). Simulations reveal that stratification of twin correlations by amount of contact can yield spurious evidence of large shared environmental effects in some strata and even give false indications of genotype x environment interaction. The stratification approach to testing the equal environments assumption may be misleading and the results of such tests may actually be consistent with a simpler theory of the role of genetic factors in niche selection.
Halo-Independent Direct Detection Analyses Without Mass Assumptions
Anderson, Adam J.; Kahn, Yonatan; McCullough, Matthew
2015-10-06
Results from direct detection experiments are typically interpreted by employing an assumption about the dark matter velocity distribution, with results presented in the $m_\\chi-\\sigma_n$ plane. Recently methods which are independent of the DM halo velocity distribution have been developed which present results in the $v_{min}-\\tilde{g}$ plane, but these in turn require an assumption on the dark matter mass. Here we present an extension of these halo-independent methods for dark matter direct detection which does not require a fiducial choice of the dark matter mass. With a change of variables from $v_{min}$ to nuclear recoil momentum ($p_R$), the full halo-independent content of an experimental result for any dark matter mass can be condensed into a single plot as a function of a new halo integral variable, which we call $\\tilde{h}(p_R)$. The entire family of conventional halo-independent $\\tilde{g}(v_{min})$ plots for all DM masses are directly found from the single $\\tilde{h}(p_R)$ plot through a simple re...
Directory of Open Access Journals (Sweden)
S. W. Lyon
2006-01-01
Full Text Available Shallow water tables near-streams often lead to saturated, overland flow generating areas in catchments in humid climates. While these saturated areas are assumed to be principal biogeochemical hot-spots and important for issues such as non-point pollution sources, the spatial and temporal behavior of shallow water tables, and associated saturated areas, is not completely understood. This study demonstrates how geostatistical methods can be used to characterize the spatial and temporal variation of the shallow water table for the near-stream region. Event-based and seasonal changes in the spatial structure of the shallow water table, which influences the spatial pattern of surface saturation and related runoff generation, can be identified and used in conjunction to characterize the hydrology of an area. This is accomplished through semivariogram analysis and indicator kriging to produce maps combining soft data (i.e., proxy information to the variable of interest representing general shallow water table patterns with hard data (i.e., actual measurements that represent variation in the spatial structure of the shallow water table per rainfall event. The area used was a hillslope in the Catskill Mountains region of New York State. The shallow water table was monitored for a 120 m×180 m near-stream region at 44 sampling locations on 15-min intervals. Outflow of the area was measured at the same time interval. These data were analyzed at a short time interval (15 min and at a long time interval (months to characterize the changes in the hydrologic behavior of the hillslope. Indicator semivariograms based on binary-transformed ground water table data (i.e., 1 if exceeding the time-variable median depth to water table and 0 if not were created for both short and long time intervals. For the short time interval, the indicator semivariograms showed a high degree of spatial structure in the shallow water table for the spring, with increased range
A connectionist-geostatistical approach for classification of deformation types in ice surfaces
Goetz-Weiss, L. R.; Herzfeld, U. C.; Hale, R. G.; Hunke, E. C.; Bobeck, J.
2014-12-01
Deformation is a class of highly non-linear geophysical processes from which one can infer other geophysical variables in a dynamical system. For example, in an ice-dynamic model, deformation is related to velocity, basal sliding, surface elevation changes, and the stress field at the surface as well as internal to a glacier. While many of these variables cannot be observed, deformation state can be an observable variable, because deformation in glaciers (once a viscosity threshold is exceeded) manifests itself in crevasses.Given the amount of information that can be inferred from observing surface deformation, an automated method for classifying surface imagery becomes increasingly desirable. In this paper a Neural Network is used to recognize classes of crevasse types over the Bering Bagley Glacier System (BBGS) during a surge (2011-2013-?). A surge is a spatially and temporally highly variable and rapid acceleration of the glacier. Therefore, many different crevasse types occur in a short time frame and in close proximity, and these crevasse fields hold information on the geophysical processes of the surge.The connectionist-geostatistical approach uses directional experimental (discrete) variograms to parameterize images into a form that the Neural Network can recognize. Recognizing that each surge wave results in different crevasse types and that environmental conditions affect the appearance in imagery, we have developed a semi-automated pre-training software to adapt the Neural Net to chaining conditions.The method is applied to airborne and satellite imagery to classify surge crevasses from the BBGS surge. This method works well for classifying spatially repetitive images such as the crevasses over Bering Glacier. We expand the network for less repetitive images in order to analyze imagery collected over the Arctic sea ice, to assess the percentage of deformed ice for model calibration.
Directory of Open Access Journals (Sweden)
ABDULKADIR T. SHOLAGBERU
2017-11-01
Full Text Available Soil erosion hazard is the second biggest environmental challenges after population growth causing land degradation, desertification and water deterioration. Its impacts on watersheds include loss of soil nutrients, reduced reservoir capacity through siltation which may lead to flood risk, landslide, high water turbidity, etc. These problems become more pronounced in human altered mountainous areas through intensive agricultural activities, deforestation and increased urbanization among others. However, due to challenging nature of soil erosion management, there is great interest in assessing its spatial distribution and susceptibility levels. This study is thus intend to review the recent literatures and develop a novel framework for soil erosion susceptibility mapping using geostatistical based support vector machine (SVM, remote sensing and GIS techniques. The conceptual framework is to bridge the identified knowledge gaps in the area of causative factors’ (CFs selection. In this research, RUSLE model, field studies and the existing soil erosion maps for the study area will be integrated for the development of inventory map. Spatial data such as Landsat 8, digital soil and geological maps, digital elevation model and hydrological data shall be processed for the extraction of erosion CFs. GISbased SVM techniques will be adopted for the establishment of spatial relationships between soil erosion and its CFs, and subsequently for the development of erosion susceptibility maps. The results of this study include evaluation of predictive capability of GIS-based SVM in soil erosion mapping and identification of the most influential CFs for erosion susceptibility assessment. This study will serve as a guide to watershed planners and to alleviate soil erosion challenges and its related hazards.
Li, A.; Tsai, F. T. C.; Jafari, N.; Chen, Q. J.; Bentley, S. J.
2017-12-01
A vast area of river deltaic wetlands stretches across southern Louisiana coast. The wetlands are suffering from a high rate of land loss, which increasingly threats coastal community and energy infrastructure. A regional stratigraphic framework of the delta plain is now imperative to answer scientific questions (such as how the delta plain grows and decays?) and to provide information to coastal protection and restoration projects (such as marsh creation and construction of levees and floodwalls). Through years, subsurface investigations in Louisiana have been conducted by state and federal agencies (Louisiana Department of Natural Resources, United States Geological Survey, United States Army Corps of Engineers, etc.), research institutes (Louisiana Geological Survey, LSU Coastal Studies Institute, etc.), engineering firms, and oil-gas companies. This has resulted in the availability of various types of data, including geological, geotechnical, and geophysical data. However, it is challenging to integrate different types of data and construct three-dimensional stratigraphy models in regional scale. In this study, a set of geostatistical methods were used to tackle this problem. An ordinary kriging method was used to regionalize continuous data, such as grain size, water content, liquid limit, plasticity index, and cone penetrometer tests (CPTs). Indicator kriging and multiple indicator kriging methods were used to regionalize categorized data, such as soil classification. A compositional kriging method was used to regionalize compositional data, such as soil composition (fractions of sand, silt and clay). Stratigraphy models were constructed for three cases in the coastal zone: (1) Inner Harbor Navigation Canal (IHNC) area: soil classification and soil behavior type (SBT) stratigraphies were constructed using ordinary kriging; (2) Middle Barataria Bay area: a soil classification stratigraphy was constructed using multiple indicator kriging; (3) Lower Barataria
Murakami, Haruko
Probabilistic risk assessment of groundwater contamination requires us to incorporate large and diverse datasets at the site into the stochastic modeling of flow and transport for prediction. In quantifying the uncertainty in our predictions, we must not only combine the best estimates of the parameters based on each dataset, but also integrate the uncertainty associated with each dataset caused by measurement errors and limited number of measurements. This dissertation presents a Bayesian geostatistical data assimilation method that integrates various types of field data for characterizing heterogeneous hydrological properties. It quantifies the parameter uncertainty as a posterior distribution conditioned on all the datasets, which can be directly used in stochastic simulations to compute possible outcomes of flow and transport processes. The goal of this framework is to remove the discontinuity between data analysis and prediction. Such a direct connection between data and prediction also makes it possible to evaluate the worth of each dataset or combined worth of multiple datasets. The synthetic studies described here confirm that the data assimilation method introduced in this dissertation successfully captures the true parameter values and predicted values within the posterior distribution. The shape of the inferred posterior distributions from the method indicates the importance of estimating the entire distribution in fully accounting for parameter uncertainty. The method is then applied to integrate multiple types of datasets at the Hanford 300 Area for characterizing a three-dimensional heterogeneous hydraulic conductivity field. Comparing the results based on the different numbers or combinations of datasets shows that increasing data do not always contribute in a straightforward way to improving the posterior distribution: increasing numbers of the same data type would not necessarily be beneficial above a certain number, and also the combined effect of
A geostatistical approach to identify and mitigate agricultural nitrous oxide emission hotspots.
Turner, P A; Griffis, T J; Mulla, D J; Baker, J M; Venterea, R T
2016-12-01
Anthropogenic emissions of nitrous oxide (N 2 O), a trace gas with severe environmental costs, are greatest from agricultural soils amended with nitrogen (N) fertilizer. However, accurate N 2 O emission estimates at fine spatial scales are made difficult by their high variability, which represents a critical challenge for the management of N 2 O emissions. Here, static chamber measurements (n=60) and soil samples (n=129) were collected at approximately weekly intervals (n=6) for 42-d immediately following the application of N in a southern Minnesota cornfield (15.6-ha), typical of the systems prevalent throughout the U.S. Corn Belt. These data were integrated into a geostatistical model that resolved N 2 O emissions at a high spatial resolution (1-m). Field-scale N 2 O emissions exhibited a high degree of spatial variability, and were partitioned into three classes of emission strength: hotspots, intermediate, and coldspots. Rates of emission from hotspots were 2-fold greater than non-hotspot locations. Consequently, 36% of the field-scale emissions could be attributed to hotspots, despite representing only 21% of the total field area. Variations in elevation caused hotspots to develop in predictable locations, which were prone to nutrient and moisture accumulation caused by terrain focusing. Because these features are relatively static, our data and analyses indicate that targeted management of hotspots could efficiently reduce field-scale emissions by as much 17%, a significant benefit considering the deleterious effects of atmospheric N 2 O. Copyright © 2016 Elsevier B.V. All rights reserved.
Training-Image Based Geostatistical Inversion Using a Spatial Generative Adversarial Neural Network
Laloy, Eric; Hérault, Romain; Jacques, Diederik; Linde, Niklas
2018-01-01
Probabilistic inversion within a multiple-point statistics framework is often computationally prohibitive for high-dimensional problems. To partly address this, we introduce and evaluate a new training-image based inversion approach for complex geologic media. Our approach relies on a deep neural network of the generative adversarial network (GAN) type. After training using a training image (TI), our proposed spatial GAN (SGAN) can quickly generate 2-D and 3-D unconditional realizations. A key characteristic of our SGAN is that it defines a (very) low-dimensional parameterization, thereby allowing for efficient probabilistic inversion using state-of-the-art Markov chain Monte Carlo (MCMC) methods. In addition, available direct conditioning data can be incorporated within the inversion. Several 2-D and 3-D categorical TIs are first used to analyze the performance of our SGAN for unconditional geostatistical simulation. Training our deep network can take several hours. After training, realizations containing a few millions of pixels/voxels can be produced in a matter of seconds. This makes it especially useful for simulating many thousands of realizations (e.g., for MCMC inversion) as the relative cost of the training per realization diminishes with the considered number of realizations. Synthetic inversion case studies involving 2-D steady state flow and 3-D transient hydraulic tomography with and without direct conditioning data are used to illustrate the effectiveness of our proposed SGAN-based inversion. For the 2-D case, the inversion rapidly explores the posterior model distribution. For the 3-D case, the inversion recovers model realizations that fit the data close to the target level and visually resemble the true model well.
International Nuclear Information System (INIS)
Wingle, W.L.; Poeter, E.P.; McKenna, S.A.
1999-01-01
UNCERT is a 2D and 3D geostatistics, uncertainty analysis and visualization software package applied to ground water flow and contaminant transport modeling. It is a collection of modules that provides tools for linear regression, univariate statistics, semivariogram analysis, inverse-distance gridding, trend-surface analysis, simple and ordinary kriging and discrete conditional indicator simulation. Graphical user interfaces for MODFLOW and MT3D, ground water flow and contaminant transport models, are provided for streamlined data input and result analysis. Visualization tools are included for displaying data input and output. These include, but are not limited to, 2D and 3D scatter plots, histograms, box and whisker plots, 2D contour maps, surface renderings of 2D gridded data and 3D views of gridded data. By design, UNCERT's graphical user interface and visualization tools facilitate model design and analysis. There are few built in restrictions on data set sizes and each module (with two exceptions) can be run in either graphical or batch mode. UNCERT is in the public domain and is available from the World Wide Web with complete on-line and printable (PDF) documentation. UNCERT is written in ANSI-C with a small amount of FORTRAN77, for UNIX workstations running X-Windows and Motif (or Lesstif). This article discusses the features of each module and demonstrates how they can be used individually and in combination. The tools are applicable to a wide range of fields and are currently used by researchers in the ground water, mining, mathematics, chemistry and geophysics, to name a few disciplines. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)
Massively Parallel Geostatistical Inversion of Coupled Processes in Heterogeneous Porous Media
Ngo, A.; Schwede, R. L.; Li, W.; Bastian, P.; Ippisch, O.; Cirpka, O. A.
2012-04-01
The quasi-linear geostatistical approach is an inversion scheme that can be used to estimate the spatial distribution of a heterogeneous hydraulic conductivity field. The estimated parameter field is considered to be a random variable that varies continuously in space, meets the measurements of dependent quantities (such as the hydraulic head, the concentration of a transported solute or its arrival time) and shows the required spatial correlation (described by certain variogram models). This is a method of conditioning a parameter field to observations. Upon discretization, this results in as many parameters as elements of the computational grid. For a full three dimensional representation of the heterogeneous subsurface it is hardly sufficient to work with resolutions (up to one million parameters) of the model domain that can be achieved on a serial computer. The forward problems to be solved within the inversion procedure consists of the elliptic steady-state groundwater flow equation and the formally elliptic but nearly hyperbolic steady-state advection-dominated solute transport equation in a heterogeneous porous medium. Both equations are discretized by Finite Element Methods (FEM) using fully scalable domain decomposition techniques. Whereas standard conforming FEM is sufficient for the flow equation, for the advection dominated transport equation, which rises well known numerical difficulties at sharp fronts or boundary layers, we use the streamline diffusion approach. The arising linear systems are solved using efficient iterative solvers with an AMG (algebraic multigrid) pre-conditioner. During each iteration step of the inversion scheme one needs to solve a multitude of forward and adjoint problems in order to calculate the sensitivities of each measurement and the related cross-covariance matrix of the unknown parameters and the observations. In order to reduce interprocess communications and to improve the scalability of the code on larger clusters
Dalla Libera, Nico; Fabbri, Paolo; Mason, Leonardo; Piccinini, Leonardo; Pola, Marco
2017-11-15
The Natural Background Level (NBL), suggested by UE BRIDGE project, is suited for spatially distributed datasets providing a regional value that could be higher than the Threshold Value (TV) set by every country. In hydro-geochemically dis-homogeneous areas, the use of a unique regional NBL, higher than TV, could arise problems to distinguish between natural occurrences and anthropogenic contaminant sources. Hence, the goal of this study is to improve the NBL definition employing a geostatistical approach, which reconstructs the contaminant spatial structure accounting geochemical and hydrogeological relationships. This integrated mapping is fundamental to evaluate the contaminant's distribution impact on the NBL, giving indications to improve it. We decided to test this method on the Drainage Basin of Venice Lagoon (DBVL, NE Italy), where the existing NBL is seven times higher than the TV. This area is notoriously affected by naturally occurring arsenic contamination. An available geochemical dataset collected by 50 piezometers was used to reconstruct the spatial distribution of arsenic in the densely populated area of the DBVL. A cokriging approach was applied exploiting the geochemical relationships among As, Fe and NH4+. The obtained spatial predictions of arsenic concentrations were divided into three different zones: i) areas with an As concentration lower than the TV, ii) areas with an As concentration between the TV and the median of the values higher than the TV, and iii) areas with an As concentration higher than the median. Following the BRIDGE suggestions, where enough samples were available, the 90th percentile for each zone was calculated to obtain a local NBL (LNBL). Differently from the original NBL, this local value gives more detailed water quality information accounting the hydrogeological and geochemical setting, and contaminant spatial variation. Hence, the LNBL could give more indications about the distinction between natural occurrence and
Vasquez, D. A.; Swift, J. N.; Tan, S.; Darrah, T. H.
2013-12-01
The integration of precise geochemical analyses with quantitative engineering modeling into an interactive GIS system allows for a sophisticated and efficient method of reservoir engineering and characterization. Geographic Information Systems (GIS) is utilized as an advanced technique for oil field reservoir analysis by combining field engineering and geological/geochemical spatial datasets with the available systematic modeling and mapping methods to integrate the information into a spatially correlated first-hand approach in defining surface and subsurface characteristics. Three key methods of analysis include: 1) Geostatistical modeling to create a static and volumetric 3-dimensional representation of the geological body, 2) Numerical modeling to develop a dynamic and interactive 2-dimensional model of fluid flow across the reservoir and 3) Noble gas geochemistry to further define the physical conditions, components and history of the geologic system. Results thus far include using engineering algorithms for interpolating electrical well log properties across the field (spontaneous potential, resistivity) yielding a highly accurate and high-resolution 3D model of rock properties. Results so far also include using numerical finite difference methods (crank-nicholson) to solve for equations describing the distribution of pressure across field yielding a 2D simulation model of fluid flow across reservoir. Ongoing noble gas geochemistry results will also include determination of the source, thermal maturity and the extent/style of fluid migration (connectivity, continuity and directionality). Future work will include developing an inverse engineering algorithm to model for permeability, porosity and water saturation.This combination of new and efficient technological and analytical capabilities is geared to provide a better understanding of the field geology and hydrocarbon dynamics system with applications to determine the presence of hydrocarbon pay zones (or
Directory of Open Access Journals (Sweden)
Federica Giardina
Full Text Available The Research Center for Human Development in Dakar (CRDH with the technical assistance of ICF Macro and the National Malaria Control Programme (NMCP conducted in 2008/2009 the Senegal Malaria Indicator Survey (SMIS, the first nationally representative household survey collecting parasitological data and malaria-related indicators. In this paper, we present spatially explicit parasitaemia risk estimates and number of infected children below 5 years. Geostatistical Zero-Inflated Binomial models (ZIB were developed to take into account the large number of zero-prevalence survey locations (70% in the data. Bayesian variable selection methods were incorporated within a geostatistical framework in order to choose the best set of environmental and climatic covariates associated with the parasitaemia risk. Model validation confirmed that the ZIB model had a better predictive ability than the standard Binomial analogue. Markov chain Monte Carlo (MCMC methods were used for inference. Several insecticide treated nets (ITN coverage indicators were calculated to assess the effectiveness of interventions. After adjusting for climatic and socio-economic factors, the presence of at least one ITN per every two household members and living in urban areas reduced the odds of parasitaemia by 86% and 81% respectively. Posterior estimates of the ORs related to the wealth index show a decreasing trend with the quintiles. Infection odds appear to be increasing with age. The population-adjusted prevalence ranges from 0.12% in Thillé-Boubacar to 13.1% in Dabo. Tambacounda has the highest population-adjusted predicted prevalence (8.08% whereas the region with the highest estimated number of infected children under the age of 5 years is Kolda (13940. The contemporary map and estimates of malaria burden identify the priority areas for future control interventions and provide baseline information for monitoring and evaluation. Zero-Inflated formulations are more appropriate
DEFF Research Database (Denmark)
Kessler, Timo Christian; Nilsson, Bertel; Klint, Knud Erik
2010-01-01
(TPROGS) of alternating geological facies. The second method, multiple-point statistics, uses training images to estimate the conditional probability of sand-lenses at a certain location. Both methods respect field observations such as local stratigraphy, however, only the multiple-point statistics can...... of sand-lenses in clay till. Sand-lenses mainly account for horizontal transport and are prioritised in this study. Based on field observations, the distribution has been modeled using two different geostatistical approaches. One method uses a Markov chain model calculating the transition probabilities...
Experimental assessment of unvalidated assumptions in classical plasticity theory.
Energy Technology Data Exchange (ETDEWEB)
Brannon, Rebecca Moss (University of Utah, Salt Lake City, UT); Burghardt, Jeffrey A. (University of Utah, Salt Lake City, UT); Bauer, Stephen J.; Bronowski, David R.
2009-01-01
This report investigates the validity of several key assumptions in classical plasticity theory regarding material response to changes in the loading direction. Three metals, two rock types, and one ceramic were subjected to non-standard loading directions, and the resulting strain response increments were displayed in Gudehus diagrams to illustrate the approximation error of classical plasticity theories. A rigorous mathematical framework for fitting classical theories to the data, thus quantifying the error, is provided. Further data analysis techniques are presented that allow testing for the effect of changes in loading direction without having to use a new sample and for inferring the yield normal and flow directions without having to measure the yield surface. Though the data are inconclusive, there is indication that classical, incrementally linear, plasticity theory may be inadequate over a certain range of loading directions. This range of loading directions also coincides with loading directions that are known to produce a physically inadmissible instability for any nonassociative plasticity model.
Factor structure and concurrent validity of the world assumptions scale.
Elklit, Ask; Shevlin, Mark; Solomon, Zahava; Dekel, Rachel
2007-06-01
The factor structure of the World Assumptions Scale (WAS) was assessed by means of confirmatory factor analysis. The sample was comprised of 1,710 participants who had been exposed to trauma that resulted in whiplash. Four alternative models were specified and estimated using LISREL 8.72. A correlated 8-factor solution was the best explanation of the sample data. The estimates of reliability of eight subscales of the WAS ranged from .48 to .82. Scores from five subscales correlated significantly with trauma severity as measured by the Harvard Trauma Questionnaire, although the magnitude of the correlations was low to modest, ranging from .08 to -.43. It is suggested that the WAS has adequate psychometric properties for use in both clinical and research settings.
Posttraumatic Growth and Shattered World Assumptions Among Ex-POWs
DEFF Research Database (Denmark)
Lahav, Y.; Bellin, Elisheva S.; Solomon, Z.
2016-01-01
Objective: The controversy regarding the nature of posttraumatic growth (PTG) includes two main competing claims: one which argues that PTG reflects authentic positive changes and the other which argues that PTG reflects illusionary defenses. The former also suggests that PTG evolves from shattered...... world assumptions (WAs) and that the co-occurrence of high PTG and negative WAs among trauma survivors reflects reconstruction of an integrative belief system. The present study aimed to test these claims by investigating, for the first time, the mediating role of dissociation in the relation between...... PTG and WAs. Method: Former prisoners of war (ex-POWs; n = 158) and comparable controls (n = 106) were assessed 38 years after the Yom Kippur War. Results: Ex-POWs endorsed more negative WAs and higher PTG and dissociation compared to controls. Ex-POWs with posttraumatic stress disorder (PTSD...
Ancestral assumptions and the clinical uncertainty of evolutionary medicine.
Cournoyea, Michael
2013-01-01
Evolutionary medicine is an emerging field of medical studies that uses evolutionary theory to explain the ultimate causes of health and disease. Educational tools, online courses, and medical school modules are being developed to help clinicians and students reconceptualize health and illness in light of our evolutionary past. Yet clinical guidelines based on our ancient life histories are epistemically weak, relying on the controversial assumptions of adaptationism and advocating a strictly biophysical account of health. To fulfill the interventionist goals of clinical practice, it seems that proximate explanations are all we need to develop successful diagnostic and therapeutic guidelines. Considering these epistemic concerns, this article argues that the clinical relevance of evolutionary medicine remains uncertain at best.
Assumptions of Customer Knowledge Enablement in the Open Innovation Process
Directory of Open Access Journals (Sweden)
Jokubauskienė Raminta
2017-08-01
Full Text Available In the scientific literature, open innovation is one of the most effective means to innovate and gain a competitive advantage. In practice, there is a variety of open innovation activities, but, nevertheless, customers stand as the cornerstone in this area, since the customers’ knowledge is one of the most important sources of new knowledge and ideas. Evaluating the context where are the interactions of open innovation and customer knowledge enablement, it is necessary to take into account the importance of customer knowledge management. Increasingly it is highlighted that customers’ knowledge management facilitates the creation of innovations. However, it should be an examination of other factors that influence the open innovation, and, at the same time, customers’ knowledge management. This article presents a theoretical model, which reveals the assumptions of open innovation process and the impact on the firm’s performance.
Polarized BRDF for coatings based on three-component assumption
Liu, Hong; Zhu, Jingping; Wang, Kai; Xu, Rong
2017-02-01
A pBRDF(polarized bidirectional reflection distribution function) model for coatings is given based on three-component reflection assumption in order to improve the polarized scattering simulation capability for space objects. In this model, the specular reflection is given based on microfacet theory, the multiple reflection and volume scattering are given separately according to experimental results. The polarization of specular reflection is considered from Fresnel's law, and both multiple reflection and volume scattering are assumed depolarized. Simulation and measurement results of two satellite coating samples SR107 and S781 are given to validate that the pBRDF modeling accuracy can be significantly improved by the three-component model given in this paper.
Dynamic Group Diffie-Hellman Key Exchange under standard assumptions
International Nuclear Information System (INIS)
Bresson, Emmanuel; Chevassut, Olivier; Pointcheval, David
2002-01-01
Authenticated Diffie-Hellman key exchange allows two principals communicating over a public network, and each holding public-private keys, to agree on a shared secret value. In this paper we study the natural extension of this cryptographic problem to a group of principals. We begin from existing formal security models and refine them to incorporate major missing details (e.g., strong-corruption and concurrent sessions). Within this model we define the execution of a protocol for authenticated dynamic group Diffie-Hellman and show that it is provably secure under the decisional Diffie-Hellman assumption. Our security result holds in the standard model and thus provides better security guarantees than previously published results in the random oracle model
Halo-independent direct detection analyses without mass assumptions
International Nuclear Information System (INIS)
Anderson, Adam J.; Fox, Patrick J.; Kahn, Yonatan; McCullough, Matthew
2015-01-01
Results from direct detection experiments are typically interpreted by employing an assumption about the dark matter velocity distribution, with results presented in the m χ −σ n plane. Recently methods which are independent of the DM halo velocity distribution have been developed which present results in the v min −g-tilde plane, but these in turn require an assumption on the dark matter mass. Here we present an extension of these halo-independent methods for dark matter direct detection which does not require a fiducial choice of the dark matter mass. With a change of variables from v min to nuclear recoil momentum (p R ), the full halo-independent content of an experimental result for any dark matter mass can be condensed into a single plot as a function of a new halo integral variable, which we call h-til-tilde(p R ). The entire family of conventional halo-independent g-tilde(v min ) plots for all DM masses are directly found from the single h-tilde(p R ) plot through a simple rescaling of axes. By considering results in h-tilde(p R ) space, one can determine if two experiments are inconsistent for all masses and all physically possible halos, or for what range of dark matter masses the results are inconsistent for all halos, without the necessity of multiple g-tilde(v min ) plots for different DM masses. We conduct a sample analysis comparing the CDMS II Si events to the null results from LUX, XENON10, and SuperCDMS using our method and discuss how the results can be strengthened by imposing the physically reasonable requirement of a finite halo escape velocity
Wartime Paris, cirrhosis mortality, and the ceteris paribus assumption.
Fillmore, Kaye Middleton; Roizen, Ron; Farrell, Michael; Kerr, William; Lemmens, Paul
2002-07-01
This article critiques the ceteris paribus assumption, which tacitly sustains the epidemiologic literature's inference that the sharp decline in cirrhosis mortality observed in Paris during the Second World War derived from a sharp constriction in wine consumption. Paris's wartime circumstances deviate substantially from the "all else being equal" assumption, and at least three other hypotheses for the cirrhosis decline may be contemplated. Historical and statistical review. Wartime Paris underwent tumultuous changes. Wine consumption did decline, but there were, as well, a myriad of other changes in diet and life experience, many involving new or heightened hardships, nutritional, experiential, institutional, health and mortality risks. Three competing hypotheses are presented: (1) A fraction of the candidates for cirrhosis mortality may have fallen to more sudden forms of death; (2) alcoholics, heavy drinkers and Paris's clochard subpopulation may have been differentially likely to become removed from the city's wartime population, whether by self-initiated departure, arrest and deportation, or death from other causes, even murder; and (3) there was mismeasurement in the cirrhosis mortality decline. The alcohol-cirrhosis connection provided the template for the alcohol research effort (now more than 20 years old) aimed at re-establishing scientific recognition of alcohol's direct alcohol-problems-generating associations and causal responsibilities. In a time given to reports of weaker associations of the alcohol-cirrhosis connection, the place and importance of the Paris curve in the wider literature, as regards that connection, remains. For this reason, the Paris findings should be subjected to as much research scrutiny as they undoubtedly deserve.
Breakdown of Hydrostatic Assumption in Tidal Channel with Scour Holes
Directory of Open Access Journals (Sweden)
Chunyan Li
2016-10-01
Full Text Available Hydrostatic condition is a common assumption in tidal and subtidal motions in oceans and estuaries.. Theories with this assumption have been largely successful. However, there is no definite criteria separating the hydrostatic from the non-hydrostatic regimes in real applications because real problems often times have multiple scales. With increased refinement of high resolution numerical models encompassing smaller and smaller spatial scales, the need for non-hydrostatic models is increasing. To evaluate the vertical motion over bathymetric changes in tidal channels and assess the validity of the hydrostatic approximation, we conducted observations using a vessel-based acoustic Doppler current profiler (ADCP. Observations were made along a straight channel 18 times over two scour holes of 25 m deep, separated by 330 m, in and out of an otherwise flat 8 m deep tidal pass leading to the Lake Pontchartrain over a time period of 8 hours covering part of the diurnal tidal cycle. Out of the 18 passages over the scour holes, 11 of them showed strong upwelling and downwelling which resulted in the breakdown of hydrostatic condition. The maximum observed vertical velocity was ~ 0.35 m/s, a high value in a tidal channel, and the estimated vertical acceleration reached a high value of 1.76×10-2 m/s2. Analysis demonstrated that the barotropic non-hydrostatic acceleration was dominant. The cause of the non-hydrostatic flow was the that over steep slopes. This demonstrates that in such a system, the bathymetric variation can lead to the breakdown of hydrostatic conditions. Models with hydrostatic restrictions will not be able to correctly capture the dynamics in such a system with significant bathymetric variations particularly during strong tidal currents.
Forecasts: uncertain, inaccurate and biased?
DEFF Research Database (Denmark)
Nicolaisen, Morten Skou; Ambrasaite, Inga; Salling, Kim Bang
2012-01-01
Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts of cons....... It is recommended that more attention is given to monitoring completed projects so future forecasts can benefit from better data availability through systematic ex-post evaluations, and an example of how to utilize such data in practice is presented.......Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts...... of construction costs, which account for the majority of total project costs. Second are the forecasts of travel time savings, which account for the majority of total project benefits. The latter of these is, inter alia, determined by forecasts of travel demand, which we shall use as a proxy for the forecasting...
Accounting for non-stationary variance in geostatistical mapping of soil properties
Wadoux, Alexandre M.J.C.; Brus, Dick J.; Heuvelink, Gerard B.M.
2018-01-01
Simple and ordinary kriging assume a constant mean and variance of the soil variable of interest. This assumption is often implausible because the mean and/or variance are linked to terrain attributes, parent material or other soil forming factors. In kriging with external drift (KED)
Money, Eric S; Sackett, Dana K; Aday, D Derek; Serre, Marc L
2011-09-15
Mercury in fish tissue is a major human health concern. Consumption of mercury-contaminated fish poses risks to the general population, including potentially serious developmental defects and neurological damage in young children. Therefore, it is important to accurately identify areas that have the potential for high levels of bioaccumulated mercury. However, due to time and resource constraints, it is difficult to adequately assess fish tissue mercury on a basin wide scale. We hypothesized that, given the nature of fish movement along streams, an analytical approach that takes into account distance traveled along these streams would improve the estimation accuracy for fish tissue mercury in unsampled streams. Therefore, we used a river-based Bayesian Maximum Entropy framework (river-BME) for modern space/time geostatistics to estimate fish tissue mercury at unsampled locations in the Cape Fear and Lumber Basins in eastern North Carolina. We also compared the space/time geostatistical estimation using river-BME to the more traditional Euclidean-based BME approach, with and without the inclusion of a secondary variable. Results showed that this river-based approach reduced the estimation error of fish tissue mercury by more than 13% and that the median estimate of fish tissue mercury exceeded the EPA action level of 0.3 ppm in more than 90% of river miles for the study domain.
Kumari, Madhuri; Singh, Chander Kumar; Bakimchandra, Oinam; Basistha, Ashoke
2017-10-01
In mountainous region with heterogeneous topography, the geostatistical modeling of the rainfall using global data set may not confirm to the intrinsic hypothesis of stationarity. This study was focused on improving the precision of the interpolated rainfall maps by spatial stratification in complex terrain. Predictions of the normal annual rainfall data were carried out by ordinary kriging, universal kriging, and co-kriging, using 80-point observations in the Indian Himalayas extending over an area of 53,484 km2. A two-step spatial clustering approach is proposed. In the first step, the study area was delineated into two regions namely lowland and upland based on the elevation derived from the digital elevation model. The delineation was based on the natural break classification method. In the next step, the rainfall data was clustered into two groups based on its spatial location in lowland or upland. The terrain ruggedness index (TRI) was incorporated as a co-variable in co-kriging interpolation algorithm. The precision of the kriged and co-kriged maps was assessed by two accuracy measures, root mean square error and Chatfield's percent better. It was observed that the stratification of rainfall data resulted in 5-20 % of increase in the performance efficiency of interpolation methods. Co-kriging outperformed the kriging models at annual and seasonal scale. The result illustrates that the stratification of the study area improves the stationarity characteristic of the point data, thus enhancing the precision of the interpolated rainfall maps derived using geostatistical methods.
International Nuclear Information System (INIS)
Bossew, P.; Žunić, Z.S.; Stojanovska, Z.; Tollefsen, T.; Carpentieri, C.; Veselinović, N.; Komatina, S.; Vaupotič, J.; Simović, R.D.; Antignani, S.; Bochicchio, F.
2014-01-01
Between 2008 and 2011 a survey of radon ( 222 Rn) was performed in schools of several districts of Southern Serbia. Some results have been published previously (Žunić et al., 2010; Carpentieri et al., 2011; Žunić et al., 2013). This article concentrates on the geographical distribution of the measured Rn concentrations. Applying geostatistical methods we generate “school radon maps” of expected concentrations and of estimated probabilities that a concentration threshold is exceeded. The resulting maps show a clearly structured spatial pattern which appears related to the geological background. In particular in areas with vulcanite and granitoid rocks, elevated radon (Rn) concentrations can be expected. The “school radon map” can therefore be considered as proxy to a map of the geogenic radon potential, and allows identification of radon-prone areas, i.e. areas in which higher Rn radon concentrations can be expected for natural reasons. It must be stressed that the “radon hazard”, or potential risk, estimated this way, has to be distinguished from the actual radon risk, which is a function of exposure. This in turn may require (depending on the target variable which is supposed to measure risk) considering demographic and sociological reality, i.e. population density, distribution of building styles and living habits. -- Highlights: • A map of Rn concentrations in primary schools of Southern Serbia. • Application of geostatistical methods. • Correlation with geology found. • Can serve as proxy to identify radon prone areas
Energy Technology Data Exchange (ETDEWEB)
Flipo, Nicolas [Centre de Geosciences, UMR Sisyphe, ENSMP, 35 rue Saint-Honore, F-77305 Fontainebleau (France)]. E-mail: nicolas.flipo@ensmp.fr; Jeannee, Nicolas [Geovariances, 49 bis, avenue Franklin Roosevelt, F-77212 Avon (France); Poulin, Michel [Centre de Geosciences, UMR Sisyphe, ENSMP, 35 rue Saint-Honore, F-77305 Fontainebleau (France); Even, Stephanie [Centre de Geosciences, UMR Sisyphe, ENSMP, 35 rue Saint-Honore, F-77305 Fontainebleau (France); Ledoux, Emmanuel [Centre de Geosciences, UMR Sisyphe, ENSMP, 35 rue Saint-Honore, F-77305 Fontainebleau (France)
2007-03-15
The objective of this work is to combine several approaches to better understand nitrate fate in the Grand Morin aquifers (2700 km{sup 2}), part of the Seine basin. CAWAQS results from the coupling of the hydrogeological model NEWSAM with the hydrodynamic and biogeochemical model of river PROSE. CAWAQS is coupled with the agronomic model STICS in order to simulate nitrate migration in basins. First, kriging provides a satisfactory representation of aquifer nitrate contamination from local observations, to set initial conditions for the physically based model. Then associated confidence intervals, derived from data using geostatistics, are used to validate CAWAQS results. Results and evaluation obtained from the combination of these approaches are given (period 1977-1988). Then CAWAQS is used to simulate nitrate fate for a 20-year period (1977-1996). The mean nitrate concentrations increase in aquifers is 0.09 mgN L{sup -1} yr{sup -1}, resulting from an average infiltration flux of 3500 kgN.km{sup -2} yr{sup -1}. - Combined use of geostatistics and physically based modeling allows assessment of nitrate concentrations in aquifer systems.
International Nuclear Information System (INIS)
Flipo, Nicolas; Jeannee, Nicolas; Poulin, Michel; Even, Stephanie; Ledoux, Emmanuel
2007-01-01
The objective of this work is to combine several approaches to better understand nitrate fate in the Grand Morin aquifers (2700 km 2 ), part of the Seine basin. CAWAQS results from the coupling of the hydrogeological model NEWSAM with the hydrodynamic and biogeochemical model of river PROSE. CAWAQS is coupled with the agronomic model STICS in order to simulate nitrate migration in basins. First, kriging provides a satisfactory representation of aquifer nitrate contamination from local observations, to set initial conditions for the physically based model. Then associated confidence intervals, derived from data using geostatistics, are used to validate CAWAQS results. Results and evaluation obtained from the combination of these approaches are given (period 1977-1988). Then CAWAQS is used to simulate nitrate fate for a 20-year period (1977-1996). The mean nitrate concentrations increase in aquifers is 0.09 mgN L -1 yr -1 , resulting from an average infiltration flux of 3500 kgN.km -2 yr -1 . - Combined use of geostatistics and physically based modeling allows assessment of nitrate concentrations in aquifer systems
Martins, Júlio C; Picanço, Marcelo C; Silva, Ricardo S; Gonring, Alfredo Hr; Galdino, Tarcísio Vs; Guedes, Raul Nc
2018-01-01
The spatial distribution of insects is due to the interaction between individuals and the environment. Knowledge about the within-field pattern of spatial distribution of a pest is critical to planning control tactics, developing efficient sampling plans, and predicting pest damage. The leaf miner Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) is the main pest of tomato crops in several regions of the world. Despite the importance of this pest, the pattern of spatial distribution of T. absoluta on open-field tomato cultivation remains unknown. Therefore, this study aimed to characterize the spatial distribution of T. absoluta in 22 commercial open-field tomato cultivations with plants at the three phenological development stages by using geostatistical analysis. Geostatistical analysis revealed that there was strong evidence for spatially dependent (aggregated) T. absoluta eggs in 19 of the 22 sample tomato cultivations. The maps that were obtained demonstrated the aggregated structure of egg densities at the edges of the crops. Further, T. absoluta was found to accomplish egg dispersal along the rows more frequently than it does between rows. Our results indicate that the greatest egg densities of T. absoluta occur at the edges of tomato crops. These results are discussed in relation to the behavior of T. absoluta distribution within fields and in terms of their implications for improved sampling guidelines and precision targeting control methods that are essential for effective pest monitoring and management. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.
International Nuclear Information System (INIS)
Lanyon, G.W.; Marschall, P.; Vomvoris, S.; Jaquet, O.; Mazurek, M.
1998-01-01
This paper describes the methodology used to estimate effective hydraulic properties for input into a regional geostatistical model of groundwater flow at the Wellenberg site in Switzerland. The methodology uses a geologically-based discrete fracture network model to calculate effective hydraulic properties for 100m blocks along each borehole. A description of the most transmissive features (Water Conducting Features or WCFs) in each borehole is used to determine local transmissivity distributions which are combined with descriptions of WCF extent, orientation and channelling to create fracture network models. WCF geometry is dependent on the class of WCF. WCF classes are defined for each type of geological structure associated with identified borehole inflows. Local to each borehole, models are conditioned on the observed transmissivity and occurrence of WCFs. Multiple realisations are calculated for each 100m block over approximately 400m of borehole. The results from the numerical upscaling are compared with conservative estimates of hydraulic conductivity. Results from unconditioned models are also compared to identify the consequences of conditioning and interval of boreholes that appear to be atypical. An inverse method is also described by which realisations of the geostatistical model can be used to condition discrete fracture network models away from the boreholes. The method can be used as a verification of the modelling approach by prediction of data at borehole locations. Applications of the models to estimation of post-closure repository performance, including cavern inflow and seal zone modelling, are illustrated
International Nuclear Information System (INIS)
Metcalfe, D.E.; Campbell, J.E.; RamaRao, B.S.; Harper, W.V.; Battelle Project Management Div., Columbus, OH)
1985-01-01
Sensitivity and uncertainty analysis are important components of performance assessment activities for potential high-level radioactive waste repositories. The application of geostatistical and adjoint sensitivity techniques to aid in the calibration of an existing conceptual model of ground-water flow is demonstrated for the Leadville Limestone in Paradox Basin, Utah. The geostatistical method called kriging is used to statistically analyze the measured potentiometric data for the Leadville. This analysis consists of identifying anomalous data and data trends and characterizing the correlation structure between data points. Adjoint sensitivity analysis is then performed to aid in the calibration of a conceptual model of ground-water flow to the Leadville measured potentiometric data. Sensitivity derivatives of the fit between the modeled Leadville potentiometric surface and the measured potentiometric data to model parameters and boundary conditions are calculated by the adjoint method. These sensitivity derivatives are used to determine which model parameter and boundary condition values should be modified to most efficiently improve the fit of modeled to measured potentiometric conditions
The Impact of Modeling Assumptions in Galactic Chemical Evolution Models
Côté, Benoit; O'Shea, Brian W.; Ritter, Christian; Herwig, Falk; Venn, Kim A.
2017-02-01
We use the OMEGA galactic chemical evolution code to investigate how the assumptions used for the treatment of galactic inflows and outflows impact numerical predictions. The goal is to determine how our capacity to reproduce the chemical evolution trends of a galaxy is affected by the choice of implementation used to include those physical processes. In pursuit of this goal, we experiment with three different prescriptions for galactic inflows and outflows and use OMEGA within a Markov Chain Monte Carlo code to recover the set of input parameters that best reproduces the chemical evolution of nine elements in the dwarf spheroidal galaxy Sculptor. This provides a consistent framework for comparing the best-fit solutions generated by our different models. Despite their different degrees of intended physical realism, we found that all three prescriptions can reproduce in an almost identical way the stellar abundance trends observed in Sculptor. This result supports the similar conclusions originally claimed by Romano & Starkenburg for Sculptor. While the three models have the same capacity to fit the data, the best values recovered for the parameters controlling the number of SNe Ia and the strength of galactic outflows, are substantially different and in fact mutually exclusive from one model to another. For the purpose of understanding how a galaxy evolves, we conclude that only reproducing the evolution of a limited number of elements is insufficient and can lead to misleading conclusions. More elements or additional constraints such as the Galaxy’s star-formation efficiency and the gas fraction are needed in order to break the degeneracy between the different modeling assumptions. Our results show that the successes and failures of chemical evolution models are predominantly driven by the input stellar yields, rather than by the complexity of the Galaxy model itself. Simple models such as OMEGA are therefore sufficient to test and validate stellar yields. OMEGA
International Nuclear Information System (INIS)
Lefranc, Marie
2007-01-01
Andra (National Radioactive Waste Management Agency) has conducted studies in its Meuse/Haute-Marne Underground Research Laboratory located at a depth of about 490 m in a 155-million-year-old argillaceous rock: the Callovo-Oxfordian argillite. The purpose of the present work is to obtain as much information as possible from high-resolution log data and to optimize their analysis to specify and characterize space-time variations of the argillites from the Meuse/Haute-Marne site and subsequently predict the evolution of argillite properties on a 250 km 2 zone around the underground laboratory (transposition zone). The aim is to outline a methodology to transform depth intervals into geological time intervals and thus to quantify precisely the sedimentation rate variation, estimate duration; for example the duration of bio-stratigraphical units or of hiatuses. The latter point is particularly important because a continuous time recording is often assumed in geological modelling. The spatial variations can be studied on various scales. First, well-to-well correlations are established between seven wells at different scales. Relative variations of the thickness are observed locally. Second, FMI (Full-bore Formation Micro-Imager, Schlumberger) data are studied in detail to extract as much information as possible. For example, the analysis of FMI images reveals a clear carbonate - clay inter-bedding which displays cycles. Third, geostatistical tools are used to study these cycles. The vario-graphic analysis of conventional log data shows one metre cycles. With FMI data, smaller periods can be detected. Variogram modelling and factorial kriging analysis suggest that three spatial periods exist. They vary vertically and laterally in the boreholes but cycle ratios are stable and similar to orbital-cycle ratios (Milankovitch cycles). The three periods correspond to eccentricity, obliquity and precession. Since the duration of these orbital cycles is known, depth intervals can
Karagiannis-Voules, Dimitrios-Alexios; Odermatt, Peter; Biedermann, Patricia; Khieu, Virak; Schär, Fabian; Muth, Sinuon; Utzinger, Jürg; Vounatsou, Penelope
2015-01-01
Soil-transmitted helminth infections are intimately connected with poverty. Yet, there is a paucity of using socioeconomic proxies in spatially explicit risk profiling. We compiled household-level socioeconomic data pertaining to sanitation, drinking-water, education and nutrition from readily available Demographic and Health Surveys, Multiple Indicator Cluster Surveys and World Health Surveys for Cambodia and aggregated the data at village level. We conducted a systematic review to identify parasitological surveys and made every effort possible to extract, georeference and upload the data in the open source Global Neglected Tropical Diseases database. Bayesian geostatistical models were employed to spatially align the village-aggregated socioeconomic predictors with the soil-transmitted helminth infection data. The risk of soil-transmitted helminth infection was predicted at a grid of 1×1km covering Cambodia. Additionally, two separate individual-level spatial analyses were carried out, for Takeo and Preah Vihear provinces, to assess and quantify the association between soil-transmitted helminth infection and socioeconomic indicators at an individual level. Overall, we obtained socioeconomic proxies from 1624 locations across the country. Surveys focussing on soil-transmitted helminth infections were extracted from 16 sources reporting data from 238 unique locations. We found that the risk of soil-transmitted helminth infection from 2000 onwards was considerably lower than in surveys conducted earlier. Population-adjusted prevalences for school-aged children from 2000 onwards were 28.7% for hookworm, 1.5% for Ascaris lumbricoides and 0.9% for Trichuris trichiura. Surprisingly, at the country-wide analyses, we did not find any significant association between soil-transmitted helminth infection and village-aggregated socioeconomic proxies. Based also on the individual-level analyses we conclude that socioeconomic proxies might not be good predictors at an
Determination of geostatistically representative sampling locations in Porsuk Dam Reservoir (Turkey)
Aksoy, A.; Yenilmez, F.; Duzgun, S.
2013-12-01
Several factors such as wind action, bathymetry and shape of a lake/reservoir, inflows, outflows, point and diffuse pollution sources result in spatial and temporal variations in water quality of lakes and reservoirs. The guides by the United Nations Environment Programme and the World Health Organization to design and implement water quality monitoring programs suggest that even a single monitoring station near the center or at the deepest part of a lake will be sufficient to observe long-term trends if there is good horizontal mixing. In stratified water bodies, several samples can be required. According to the guide of sampling and analysis under the Turkish Water Pollution Control Regulation, a minimum of five sampling locations should be employed to characterize the water quality in a reservoir or a lake. The European Union Water Framework Directive (2000/60/EC) states to select a sufficient number of monitoring sites to assess the magnitude and impact of point and diffuse sources and hydromorphological pressures in designing a monitoring program. Although existing regulations and guidelines include frameworks for the determination of sampling locations in surface waters, most of them do not specify a procedure in establishment of monitoring aims with representative sampling locations in lakes and reservoirs. In this study, geostatistical tools are used to determine the representative sampling locations in the Porsuk Dam Reservoir (PDR). Kernel density estimation and kriging were used in combination to select the representative sampling locations. Dissolved oxygen and specific conductivity were measured at 81 points. Sixteen of them were used for validation. In selection of the representative sampling locations, care was given to keep similar spatial structure in distributions of measured parameters. A procedure was proposed for that purpose. Results indicated that spatial structure was lost under 30 sampling points. This was as a result of varying water
Hošek, Michal; Matys Grygar, Tomáš; Popelka, Jan; Kiss, Timea; Elznicová, Jitka; Faměra, Martin
2017-04-01
units. Those findings must, however, be checked by sediment examination and analysis in selected points. We processed the crucial characteristics obtained by geochemical mapping, namely depth of maximum pollution, amount of contamination, and lithology (Al/Si and Zr/Rb ratios), using geostatistics. Moreover, some parts of floodplain were dated by optically stimulated luminescence (OSL) which revealed, that recycling of top decimetres of floodplain fine fill (silts) in Boreček site has proceeded relatively recently (in decades and centuries) as compared to deeper lying coarser (sandy) strata (millennia). The results of geochemical mapping show complexity of pollution hotspots and need of their integrated interpretation. Key words: Dipole electromagneting profilling, electric resistivity tomography, floodplain contamination, geochemical mapping
Regional-scale geostatistical inverse modeling of North American CO2 fluxes: a synthetic data study
Directory of Open Access Journals (Sweden)
A. M. Michalak
2010-07-01
Full Text Available A series of synthetic data experiments is performed to investigate the ability of a regional atmospheric inversion to estimate grid-scale CO2 fluxes during the growing season over North America. The inversions are performed within a geostatistical framework without the use of any prior flux estimates or auxiliary variables, in order to focus on the atmospheric constraint provided by the nine towers collecting continuous, calibrated CO2 measurements in 2004. Using synthetic measurements and their associated concentration footprints, flux and model-data mismatch covariance parameters are first optimized, and then fluxes and their uncertainties are estimated at three different temporal resolutions. These temporal resolutions, which include a four-day average, a four-day-average diurnal cycle with 3-hourly increments, and 3-hourly fluxes, are chosen to help assess the impact of temporal aggregation errors on the estimated fluxes and covariance parameters. Estimating fluxes at a temporal resolution that can adjust the diurnal variability is found to be critical both for recovering covariance parameters directly from the atmospheric data, and for inferring accurate ecoregion-scale fluxes. Accounting for both spatial and temporal a priori covariance in the flux distribution is also found to be necessary for recovering accurate a posteriori uncertainty bounds on the estimated fluxes. Overall, the results suggest that even a fairly sparse network of 9 towers collecting continuous CO2 measurements across the continent, used with no auxiliary information or prior estimates of the flux distribution in time or space, can be used to infer relatively accurate monthly ecoregion scale CO2 surface fluxes over North America within estimated uncertainty bounds. Simulated random transport error is shown to decrease the quality of flux estimates in under-constrained areas at the ecoregion scale, although the uncertainty bounds remain realistic. While these synthetic
Venhuis, B J; Zwaagstra, M E; Keizers, P H J; de Kaste, D
2014-02-01
In this report, we show three examples of how the variability in dose units in single packages of counterfeit medicines and adulterated dietary supplements may contribute to a false negative screening result and inaccurate health risk assessments. We describe a counterfeit Viagra 100mg blister pack and a box of an instant coffee both containing dose units with and without an active pharmaceutical ingredient (API). We also describe a purportedly herbal slimming product with capsules that mutually differed in API and impurities. The adulterated dietary supplements contained sibutramine, benzyl-sibutramine, N-desmethyl-sibutramine (DMS), N,N-didesmethyl-sibutramine (DDMS) and several other related impurities. Counterfeit medicines and adulterated dietary supplements are a health risk because their quality is unreliable. Health risks are even greater when such unreliability extends to fundamental differences between dose units in one package. Because dose-to-dose variability for these products is unpredictable, the confidence interval of a sample size is unknown. Consequently, the analyses of a selection of dose units may not be representative for the package. In the worst case, counterfeit or unauthorised medicines are not recognised as such or a health risk is not identified. In order to reduce erroneous results particular care should be taken when analysing a composite of dose units, when finding no API in a dietary supplement and when finding conformity in a suspect counterfeit medicine. Copyright © 2013 Elsevier B.V. All rights reserved.
Speakers' assumptions about the lexical flexibility of idioms.
Gibbs, R W; Nayak, N P; Bolton, J L; Keppel, M E
1989-01-01
In three experiments, we examined why some idioms can be lexically altered and still retain their figurative meanings (e.g., John buttoned his lips about Mary can be changed into John fastened his lips about Mary and still mean "John didn't say anything about Mary"), whereas other idioms cannot be lexically altered without losing their figurative meanings (e.g., John kicked the bucket, meaning "John died," loses its idiomatic meaning when changed into John kicked the pail). Our hypothesis was that the lexical flexibility of idioms is determined by speakers' assumptions about the ways in which parts of idioms contribute to their figurative interpretations as a whole. The results of the three experiments indicated that idioms whose individual semantic components contribute to their overall figurative meanings (e.g., go out on a limb) were judged as less disrupted by changes in their lexical items (e.g., go out on a branch) than were nondecomposable idioms (e.g., kick the bucket) when their individual words were altered (e.g., punt the pail). These findings lend support to the idea that both the syntactic productivity and the lexical makeup of idioms are matters of degree, depending on the idioms' compositional properties. This conclusion suggests that idioms do not form a unique class of linguistic items, but share many of the properties of more literal language.
Weak convergence of Jacobian determinants under asymmetric assumptions
Directory of Open Access Journals (Sweden)
Teresa Alberico
2012-05-01
Full Text Available Let $\\Om$ be a bounded open set in $\\R^2$ sufficiently smooth and $f_k=(u_k,v_k$ and $f=(u,v$ mappings belong to the Sobolev space $W^{1,2}(\\Om,\\R^2$. We prove that if the sequence of Jacobians $J_{f_k}$ converges to a measure $\\mu$ in sense of measures andif one allows different assumptions on the two components of $f_k$ and $f$, e.g.$$u_k \\rightharpoonup u \\;\\;\\mbox{weakly in} \\;\\; W^{1,2}(\\Om \\qquad \\, v_k \\rightharpoonup v \\;\\;\\mbox{weakly in} \\;\\; W^{1,q}(\\Om$$for some $q\\in(1,2$, then\\begin{equation}\\label{0}d\\mu=J_f\\,dz.\\end{equation}Moreover, we show that this result is optimal in the sense that conclusion fails for $q=1$.On the other hand, we prove that \\eqref{0} remains valid also if one considers the case $q=1$, but it is necessary to require that $u_k$ weakly converges to $u$ in a Zygmund-Sobolev space with a slightly higher degree of regularity than $W^{1,2}(\\Om$ and precisely$$ u_k \\rightharpoonup u \\;\\;\\mbox{weakly in} \\;\\; W^{1,L^2 \\log^\\alpha L}(\\Om$$for some $\\alpha >1$.
Stream of consciousness: Quantum and biochemical assumptions regarding psychopathology.
Tonello, Lucio; Cocchi, Massimo; Gabrielli, Fabio; Tuszynski, Jack A
2017-04-01
The accepted paradigms of mainstream neuropsychiatry appear to be incompletely adequate and in various cases offer equivocal analyses. However, a growing number of new approaches are being proposed that suggest the emergence of paradigm shifts in this area. In particular, quantum theories of mind, brain and consciousness seem to offer a profound change to the current approaches. Unfortunately these quantum paradigms harbor at least two serious problems. First, they are simply models, theories, and assumptions, with no convincing experiments supporting their claims. Second, they deviate from contemporary mainstream views of psychiatric illness and do so in revolutionary ways. We suggest a possible way to integrate experimental neuroscience with quantum models in order to address outstanding issues in psychopathology. A key role is played by the phenomenon called the "stream of consciousness", which can be linked to the so-called "Gamma Synchrony" (GS), which is clearly demonstrated by EEG data. In our novel proposal, a unipolar depressed patient could be seen as a subject with an altered stream of consciousness. In particular, some clues suggest that depression is linked to an "increased power" stream of consciousness. It is additionally suggested that such an approach to depression might be extended to psychopathology in general with potential benefits to diagnostics and therapeutics in neuropsychiatry. Copyright © 2017 Elsevier Ltd. All rights reserved.
Assumptions of the primordial spectrum and cosmological parameter estimation
International Nuclear Information System (INIS)
Shafieloo, Arman; Souradeep, Tarun
2011-01-01
The observables of the perturbed universe, cosmic microwave background (CMB) anisotropy and large structures depend on a set of cosmological parameters, as well as the assumed nature of primordial perturbations. In particular, the shape of the primordial power spectrum (PPS) is, at best, a well-motivated assumption. It is known that the assumed functional form of the PPS in cosmological parameter estimation can affect the best-fit-parameters and their relative confidence limits. In this paper, we demonstrate that a specific assumed form actually drives the best-fit parameters into distinct basins of likelihood in the space of cosmological parameters where the likelihood resists improvement via modifications to the PPS. The regions where considerably better likelihoods are obtained allowing free-form PPS lie outside these basins. In the absence of a preferred model of inflation, this raises a concern that current cosmological parameter estimates are strongly prejudiced by the assumed form of PPS. Our results strongly motivate approaches toward simultaneous estimation of the cosmological parameters and the shape of the primordial spectrum from upcoming cosmological data. It is equally important for theorists to keep an open mind towards early universe scenarios that produce features in the PPS. (paper)
Fourth-order structural steganalysis and analysis of cover assumptions
Ker, Andrew D.
2006-02-01
We extend our previous work on structural steganalysis of LSB replacement in digital images, building detectors which analyse the effect of LSB operations on pixel groups as large as four. Some of the method previously applied to triplets of pixels carries over straightforwardly. However we discover new complexities in the specification of a cover image model, a key component of the detector. There are many reasonable symmetry assumptions which we can make about parity and structure in natural images, only some of which provide detection of steganography, and the challenge is to identify the symmetries a) completely, and b) concisely. We give a list of possible symmetries and then reduce them to a complete, non-redundant, and approximately independent set. Some experimental results suggest that all useful symmetries are thus described. A weighting is proposed and its approximate variance stabilisation verified empirically. Finally, we apply symmetries to create a novel quadruples detector for LSB replacement steganography. Experimental results show some improvement, in most cases, over other detectors. However the gain in performance is moderate compared with the increased complexity in the detection algorithm, and we suggest that, without new insight, further extension of structural steganalysis may provide diminishing returns.
On Some Unwarranted Tacit Assumptions in Cognitive Neuroscience†
Mausfeld, Rainer
2011-01-01
The cognitive neurosciences are based on the idea that the level of neurons or neural networks constitutes a privileged level of analysis for the explanation of mental phenomena. This paper brings to mind several arguments to the effect that this presumption is ill-conceived and unwarranted in light of what is currently understood about the physical principles underlying mental achievements. It then scrutinizes the question why such conceptions are nevertheless currently prevailing in many areas of psychology. The paper argues that corresponding conceptions are rooted in four different aspects of our common-sense conception of mental phenomena and their explanation, which are illegitimately transferred to scientific enquiry. These four aspects pertain to the notion of explanation, to conceptions about which mental phenomena are singled out for enquiry, to an inductivist epistemology, and, in the wake of behavioristic conceptions, to a bias favoring investigations of input–output relations at the expense of enquiries into internal principles. To the extent that the cognitive neurosciences methodologically adhere to these tacit assumptions, they are prone to turn into a largely a-theoretical and data-driven endeavor while at the same time enhancing the prospects for receiving widespread public appreciation of their empirical findings. PMID:22435062
On some unwarranted tacit assumptions in cognitive neuroscience.
Mausfeld, Rainer
2012-01-01
The cognitive neurosciences are based on the idea that the level of neurons or neural networks constitutes a privileged level of analysis for the explanation of mental phenomena. This paper brings to mind several arguments to the effect that this presumption is ill-conceived and unwarranted in light of what is currently understood about the physical principles underlying mental achievements. It then scrutinizes the question why such conceptions are nevertheless currently prevailing in many areas of psychology. The paper argues that corresponding conceptions are rooted in four different aspects of our common-sense conception of mental phenomena and their explanation, which are illegitimately transferred to scientific enquiry. These four aspects pertain to the notion of explanation, to conceptions about which mental phenomena are singled out for enquiry, to an inductivist epistemology, and, in the wake of behavioristic conceptions, to a bias favoring investigations of input-output relations at the expense of enquiries into internal principles. To the extent that the cognitive neurosciences methodologically adhere to these tacit assumptions, they are prone to turn into a largely a-theoretical and data-driven endeavor while at the same time enhancing the prospects for receiving widespread public appreciation of their empirical findings.
Are waves of relational assumptions eroding traditional analysis?
Meredith-Owen, William
2013-11-01
The author designates as 'traditional' those elements of psychoanalytic presumption and practice that have, in the wake of Fordham's legacy, helped to inform analytical psychology and expand our capacity to integrate the shadow. It is argued that this element of the broad spectrum of Jungian practice is in danger of erosion by the underlying assumptions of the relational approach, which is fast becoming the new establishment. If the maps of the traditional landscape of symbolic reference (primal scene, Oedipus et al.) are disregarded, analysts are left with only their own self-appointed authority with which to orientate themselves. This self-centric epistemological basis of the relationalists leads to a revision of 'analytic attitude' that may be therapeutic but is not essentially analytic. This theme is linked to the perennial challenge of balancing differentiation and merger and traced back, through Chasseguet-Smirgel, to its roots in Genesis. An endeavour is made to illustrate this within the Journal convention of clinically based discussion through a commentary on Colman's (2013) avowedly relational treatment of the case material presented in his recent Journal paper 'Reflections on knowledge and experience' and through an assessment of Jessica Benjamin's (2004) relational critique of Ron Britton's (1989) transference embodied approach. © 2013, The Society of Analytical Psychology.
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Mohammad Doustmohammadi
2014-12-01
Full Text Available Uniaxial compressive strength (UCS is one of the most significant factors on the stability of underground excavation projects. Most of the time, this factor can be obtained by exploratory boreholes evaluation. Due to the large distance between exploratory boreholes in the majority of geotechnical projects, the application of geostatistical methods has increased as an estimator of rock mass properties. The present paper ties the estimation of UCS values of intact rock to the distance between boreholes of the Behesht-Abad tunnel in central Iran, using SGEMS geostatistical program. Variography showed that UCS estimation of intact rock using geostatistical methods is reasonable. The model establishment and validation was done after assessment that the model was trustworthy. Cross validation proved the high accuracy (98% and reliability of the model to estimate uniaxial compressive strength. The UCS values were then estimated along the tunnel axis. Moreover, using geostatistical estimation led to better identification of the pros and cons of geotechnical explorations in each location of tunnel route.
DEFF Research Database (Denmark)
Jansen, T; Kristensen, K; Fairweather, T. P.
2017-01-01
paradoxus are not reflected in the current assessment and management practices for the Benguela Current Large Marine Ecosystem. In this study, we compiled data from multiple demersal trawl surveys from the entire distribution area and applied state-of the-art geostatistical population modelling (Geo...
Freire, J.; González-Gurriarán, E.; Olaso, I.
1992-12-01
Geostatistical methodology was used to analyse spatial structure and distribution of the epibenthic crustaceans Munida intermedia and M. sarsi within sets of data which had been collected during three survey cruises carried out on the Galician continental shelf (1983 and 1984). This study investigates the feasibility of using geostatistics for data collected according to traditional methods and of enhancing such methodology. The experimental variograms were calculated (pooled variance minus spatial covariance between samples taken one pair at a time vs. distance) and fitted to a 'spherical' model. The spatial structure model was used to estimate the abundance and distribution of the populations studied using the technique of kriging. The species display spatial structures, which are well marked during high density periods and in some areas (especially northern shelf). Geostatistical analysis allows identification of the density gradients in space as well as the patch grain along the continental shelf of 16-25 km diameter for M. intermedia and 12-20 km for M. sarsi. Patches of both species have a consistent location throughout the different cruises. As in other geographical areas, M. intermedia and M. sarsi usually appear at depths ranging from 200 to 500 m, with the highest densities in the continental shelf area located between Fisterra and Estaca de Bares. Althouh sampling was not originally designed specifically for geostatistics, this assay provides a measurement of spatial covariance, and shows variograms with variable structure depending on population density and geographical area. These ideas are useful in improving the design of future sampling cruises.
Providing security assurance in line with national DBT assumptions
Bajramovic, Edita; Gupta, Deeksha
2017-01-01
As worldwide energy requirements are increasing simultaneously with climate change and energy security considerations, States are thinking about building nuclear power to fulfill their electricity requirements and decrease their dependence on carbon fuels. New nuclear power plants (NPPs) must have comprehensive cybersecurity measures integrated into their design, structure, and processes. In the absence of effective cybersecurity measures, the impact of nuclear security incidents can be severe. Some of the current nuclear facilities were not specifically designed and constructed to deal with the new threats, including targeted cyberattacks. Thus, newcomer countries must consider the Design Basis Threat (DBT) as one of the security fundamentals during design of physical and cyber protection systems of nuclear facilities. IAEA NSS 10 describes the DBT as "comprehensive description of the motivation, intentions and capabilities of potential adversaries against which protection systems are designed and evaluated". Nowadays, many threat actors, including hacktivists, insider threat, cyber criminals, state and non-state groups (terrorists) pose security risks to nuclear facilities. Threat assumptions are made on a national level. Consequently, threat assessment closely affects the design structures of nuclear facilities. Some of the recent security incidents e.g. Stuxnet worm (Advanced Persistent Threat) and theft of sensitive information in South Korea Nuclear Power Plant (Insider Threat) have shown that these attacks should be considered as the top threat to nuclear facilities. Therefore, the cybersecurity context is essential for secure and safe use of nuclear power. In addition, States should include multiple DBT scenarios in order to protect various target materials, types of facilities, and adversary objectives. Development of a comprehensive DBT is a precondition for the establishment and further improvement of domestic state nuclear-related regulations in the
Ribeiro, Manuel C; Pinho, P; Branquinho, C; Llop, Esteve; Pereira, Maria J
2016-08-15
In most studies correlating health outcomes with air pollution, personal exposure assignments are based on measurements collected at air-quality monitoring stations not coinciding with health data locations. In such cases, interpolators are needed to predict air quality in unsampled locations and to assign personal exposures. Moreover, a measure of the spatial uncertainty of exposures should be incorporated, especially in urban areas where concentrations vary at short distances due to changes in land use and pollution intensity. These studies are limited by the lack of literature comparing exposure uncertainty derived from distinct spatial interpolators. Here, we addressed these issues with two interpolation methods: regression Kriging (RK) and ordinary Kriging (OK). These methods were used to generate air-quality simulations with a geostatistical algorithm. For each method, the geostatistical uncertainty was drawn from generalized linear model (GLM) analysis. We analyzed the association between air quality and birth weight. Personal health data (n=227) and exposure data were collected in Sines (Portugal) during 2007-2010. Because air-quality monitoring stations in the city do not offer high-spatial-resolution measurements (n=1), we used lichen data as an ecological indicator of air quality (n=83). We found no significant difference in the fit of GLMs with any of the geostatistical methods. With RK, however, the models tended to fit better more often and worse less often. Moreover, the geostatistical uncertainty results showed a marginally higher mean and precision with RK. Combined with lichen data and land-use data of high spatial resolution, RK is a more effective geostatistical method for relating health outcomes with air quality in urban areas. This is particularly important in small cities, which generally do not have expensive air-quality monitoring stations with high spatial resolution. Further, alternative ways of linking human activities with their
Henine, Hocine; Tournebize, Julien; Laurent, Gourdol; Christophe, Hissler; Cournede, Paul-Henry; Clement, Remi
2017-04-01
Research on the Critical Zone (CZ) is a prerequisite for undertaking issues related to ecosystemic services that human societies rely on (nutrient cycles, water supply and quality). However, while the upper part of CZ (vegetation, soil, surface water) is readily accessible, knowledge of the subsurface remains limited, due to the point-scale character of conventional direct observations. While the potential for geophysical methods to overcome this limitation is recognized, the translation of the geophysical information into physical properties or states of interest remains a challenge (e.g. the translation of soil electrical resistivity into soil water content). In this study, we propose a geostatistical framework using the Bayesian Maximum Entropy (BME) approach to assimilate geophysical and point-scale data. We especially focus on the prediction of the spatial distribution of soil water content using (1) TDR point-scale measurements of soil water content, which are considered as accurate data, and (2) soil water content data derived from electrical resistivity measurements, which are uncertain data but spatially dense. We used a synthetic dataset obtained with a vertical 2D domain to evaluate the performance of this geostatistical approach. Spatio-temporal simulations of soil water content were carried out using Hydrus-software for different scenarios: homogeneous or heterogeneous hydraulic conductivity distribution, and continuous or punctual infiltration pattern. From the simulations of soil water content, conceptual soil resistivity models were built using a forward modeling approach and point sampling of water content values, vertically ranged, were done. These two datasets are similar to field measurements of soil electrical resistivity (using electrical resistivity tomography, ERT) and soil water content (using TDR probes) obtained at the Boissy-le-Chatel site, in Orgeval catchment (East of Paris, France). We then integrated them into a specialization
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Dempsey Mary E
2009-06-01
Full Text Available Abstract Background In many parts of the world, salt marshes play a key ecological role as the interface between the marine and the terrestrial environments. Salt marshes are also exceedingly important for public health as larval habitat for mosquitoes that are vectors of disease and significant biting pests. Although grid ditching and pesticides have been effective in salt marsh mosquito control, marsh degradation and other environmental considerations compel a different approach. Targeted habitat modification and biological control methods known as Open Marsh Water Management (OMWM had been proposed as a viable alternative to marsh-wide physical alterations and chemical control. However, traditional larval sampling techniques may not adequately assess the impacts of marsh management on mosquito larvae. To assess the effectiveness of integrated OMWM and marsh restoration techniques for mosquito control, we analyzed the results of a 5-year OMWM/marsh restoration project to determine changes in mosquito larval production using GIS and geostatistical methods. Methods The following parameters were evaluated using "Before-After-Control-Impact" (BACI design: frequency and geographic extent of larval production, intensity of larval production, changes in larval habitat, and number of larvicide applications. The analyses were performed using Moran's I, Getis-Ord, and Spatial Scan statistics on aggregated before and after data as well as data collected over time. This allowed comparison of control and treatment areas to identify changes attributable to the OMWM/marsh restoration modifications. Results The frequency of finding mosquito larvae in the treatment areas was reduced by 70% resulting in a loss of spatial larval clusters compared to those found in the control areas. This effect was observed directly following OMWM treatment and remained significant throughout the study period. The greatly reduced frequency of finding larvae in the treatment
Rochlin, Ilia; Iwanejko, Tom; Dempsey, Mary E; Ninivaggi, Dominick V
2009-06-23
In many parts of the world, salt marshes play a key ecological role as the interface between the marine and the terrestrial environments. Salt marshes are also exceedingly important for public health as larval habitat for mosquitoes that are vectors of disease and significant biting pests. Although grid ditching and pesticides have been effective in salt marsh mosquito control, marsh degradation and other environmental considerations compel a different approach. Targeted habitat modification and biological control methods known as Open Marsh Water Management (OMWM) had been proposed as a viable alternative to marsh-wide physical alterations and chemical control. However, traditional larval sampling techniques may not adequately assess the impacts of marsh management on mosquito larvae. To assess the effectiveness of integrated OMWM and marsh restoration techniques for mosquito control, we analyzed the results of a 5-year OMWM/marsh restoration project to determine changes in mosquito larval production using GIS and geostatistical methods. The following parameters were evaluated using "Before-After-Control-Impact" (BACI) design: frequency and geographic extent of larval production, intensity of larval production, changes in larval habitat, and number of larvicide applications. The analyses were performed using Moran's I, Getis-Ord, and Spatial Scan statistics on aggregated before and after data as well as data collected over time. This allowed comparison of control and treatment areas to identify changes attributable to the OMWM/marsh restoration modifications. The frequency of finding mosquito larvae in the treatment areas was reduced by 70% resulting in a loss of spatial larval clusters compared to those found in the control areas. This effect was observed directly following OMWM treatment and remained significant throughout the study period. The greatly reduced frequency of finding larvae in the treatment areas led to a significant decrease (approximately 44%) in
Singhi, Aatur D; Zeh, Herbert J; Brand, Randall E; Nikiforova, Marina N; Chennat, Jennifer S; Fasanella, Kenneth E; Khalid, Asif; Papachristou, Georgios I; Slivka, Adam; Hogg, Melissa; Lee, Kenneth K; Tsung, Allan; Zureikat, Amer H; McGrath, Kevin
2016-06-01
The American Gastroenterological Association (AGA) recently reported evidence-based guidelines for the management of asymptomatic neoplastic pancreatic cysts. These guidelines advocate a higher threshold for surgical resection than prior guidelines and imaging surveillance for a considerable number of patients with pancreatic cysts. The aims of this study were to assess the accuracy of the AGA guidelines in detecting advanced neoplasia and present an alternative approach to pancreatic cysts. The study population consisted of 225 patients who underwent EUS-guided FNA for pancreatic cysts between January 2014 and May 2015. For each patient, clinical findings, EUS features, cytopathology results, carcinoembryonic antigen analysis, and molecular testing of pancreatic cyst fluid were reviewed. Molecular testing included the assessment of hotspot mutations and deletions for KRAS, GNAS, VHL, TP53, PIK3CA, and PTEN. Diagnostic pathology results were available for 41 patients (18%), with 13 (6%) harboring advanced neoplasia. Among these cases, the AGA guidelines identified advanced neoplasia with 62% sensitivity, 79% specificity, 57% positive predictive value, and 82% negative predictive value. Moreover, the AGA guidelines missed 45% of intraductal papillary mucinous neoplasms with adenocarcinoma or high-grade dysplasia. For cases without confirmatory pathology, 27 of 184 patients (15%) with serous cystadenomas (SCAs) based on EUS findings and/or VHL alterations would continue magnetic resonance imaging (MRI) surveillance. In comparison, a novel algorithmic pathway using molecular testing of pancreatic cyst fluid detected advanced neoplasias with 100% sensitivity, 90% specificity, 79% positive predictive value, and 100% negative predictive value. The AGA guidelines were inaccurate in detecting pancreatic cysts with advanced neoplasia. Furthermore, because the AGA guidelines manage all neoplastic cysts similarly, patients with SCAs will continue to undergo unnecessary MRI
Geostatistical Sampling Methods for Efficient Uncertainty Analysis in Flow and Transport Problems
Liodakis, Stylianos; Kyriakidis, Phaedon; Gaganis, Petros
2015-04-01
In hydrogeological applications involving flow and transport of in heterogeneous porous media the spatial distribution of hydraulic conductivity is often parameterized in terms of a lognormal random field based on a histogram and variogram model inferred from data and/or synthesized from relevant knowledge. Realizations of simulated conductivity fields are then generated using geostatistical simulation involving simple random (SR) sampling and are subsequently used as inputs to physically-based simulators of flow and transport in a Monte Carlo framework for evaluating the uncertainty in the spatial distribution of solute concentration due to the uncertainty in the spatial distribution of hydraulic con- ductivity [1]. Realistic uncertainty analysis, however, calls for a large number of simulated concentration fields; hence, can become expensive in terms of both time and computer re- sources. A more efficient alternative to SR sampling is Latin hypercube (LH) sampling, a special case of stratified random sampling, which yields a more representative distribution of simulated attribute values with fewer realizations [2]. Here, term representative implies realizations spanning efficiently the range of possible conductivity values corresponding to the lognormal random field. In this work we investigate the efficiency of alternative methods to classical LH sampling within the context of simulation of flow and transport in a heterogeneous porous medium. More precisely, we consider the stratified likelihood (SL) sampling method of [3], in which attribute realizations are generated using the polar simulation method by exploring the geometrical properties of the multivariate Gaussian distribution function. In addition, we propose a more efficient version of the above method, here termed minimum energy (ME) sampling, whereby a set of N representative conductivity realizations at M locations is constructed by: (i) generating a representative set of N points distributed on the
IN SITU NON-INVASIVE SOIL CARBON ANALYSIS: SAMPLE SIZE AND GEOSTATISTICAL CONSIDERATIONS.
Energy Technology Data Exchange (ETDEWEB)
WIELOPOLSKI, L.
2005-04-01
I discuss a new approach for quantitative carbon analysis in soil based on INS. Although this INS method is not simple, it offers critical advantages not available with other newly emerging modalities. The key advantages of the INS system include the following: (1) It is a non-destructive method, i.e., no samples of any kind are taken. A neutron generator placed above the ground irradiates the soil, stimulating carbon characteristic gamma-ray emission that is counted by a detection system also placed above the ground. (2) The INS system can undertake multielemental analysis, so expanding its usefulness. (3) It can be used either in static or scanning modes. (4) The volume sampled by the INS method is large with a large footprint; when operating in a scanning mode, the sampled volume is continuous. (5) Except for a moderate initial cost of about $100,000 for the system, no additional expenses are required for its operation over two to three years after which a NG has to be replenished with a new tube at an approximate cost of $10,000, this regardless of the number of sites analyzed. In light of these characteristics, the INS system appears invaluable for monitoring changes in the carbon content in the field. For this purpose no calibration is required; by establishing a carbon index, changes in carbon yield can be followed with time in exactly the same location, thus giving a percent change. On the other hand, with calibration, it can be used to determine the carbon stock in the ground, thus estimating the soil's carbon inventory. However, this requires revising the standard practices for deciding upon the number of sites required to attain a given confidence level, in particular for the purposes of upward scaling. Then, geostatistical considerations should be incorporated in considering properly the averaging effects of the large volumes sampled by the INS system that would require revising standard practices in the field for determining the number of spots to
Regional soil erosion assessment based on a sample survey and geostatistics
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S. Yin
2018-03-01
Full Text Available Soil erosion is one of the most significant environmental problems in China. From 2010 to 2012, the fourth national census for soil erosion sampled 32 364 PSUs (Primary Sampling Units, small watersheds with the areas of 0.2–3 km2. Land use and soil erosion controlling factors including rainfall erosivity, soil erodibility, slope length, slope steepness, biological practice, engineering practice, and tillage practice for the PSUs were surveyed, and the soil loss rate for each land use in the PSUs was estimated using an empirical model, the Chinese Soil Loss Equation (CSLE. Though the information collected from the sample units can be aggregated to estimate soil erosion conditions on a large scale; the problem of estimating soil erosion condition on a regional scale has not been addressed well. The aim of this study is to introduce a new model-based regional soil erosion assessment method combining a sample survey and geostatistics. We compared seven spatial interpolation models based on the bivariate penalized spline over triangulation (BPST method to generate a regional soil erosion assessment from the PSUs. Shaanxi Province (3116 PSUs in China was selected for the comparison and assessment as it is one of the areas with the most serious erosion problem. Ten-fold cross-validation based on the PSU data showed the model assisted by the land use, rainfall erosivity factor (R, soil erodibility factor (K, slope steepness factor (S, and slope length factor (L derived from a 1 : 10 000 topography map is the best one, with the model efficiency coefficient (ME being 0.75 and the MSE being 55.8 % of that for the model assisted by the land use alone. Among four erosion factors as the covariates, the S factor contributed the most information, followed by K and L factors, and R factor made almost no contribution to the spatial estimation of soil loss. The LS factor derived from 30 or 90 m Shuttle Radar Topography Mission
Regional soil erosion assessment based on a sample survey and geostatistics
Yin, Shuiqing; Zhu, Zhengyuan; Wang, Li; Liu, Baoyuan; Xie, Yun; Wang, Guannan; Li, Yishan
2018-03-01
Soil erosion is one of the most significant environmental problems in China. From 2010 to 2012, the fourth national census for soil erosion sampled 32 364 PSUs (Primary Sampling Units, small watersheds) with the areas of 0.2-3 km2. Land use and soil erosion controlling factors including rainfall erosivity, soil erodibility, slope length, slope steepness, biological practice, engineering practice, and tillage practice for the PSUs were surveyed, and the soil loss rate for each land use in the PSUs was estimated using an empirical model, the Chinese Soil Loss Equation (CSLE). Though the information collected from the sample units can be aggregated to estimate soil erosion conditions on a large scale; the problem of estimating soil erosion condition on a regional scale has not been addressed well. The aim of this study is to introduce a new model-based regional soil erosion assessment method combining a sample survey and geostatistics. We compared seven spatial interpolation models based on the bivariate penalized spline over triangulation (BPST) method to generate a regional soil erosion assessment from the PSUs. Shaanxi Province (3116 PSUs) in China was selected for the comparison and assessment as it is one of the areas with the most serious erosion problem. Ten-fold cross-validation based on the PSU data showed the model assisted by the land use, rainfall erosivity factor (R), soil erodibility factor (K), slope steepness factor (S), and slope length factor (L) derived from a 1 : 10 000 topography map is the best one, with the model efficiency coefficient (ME) being 0.75 and the MSE being 55.8 % of that for the model assisted by the land use alone. Among four erosion factors as the covariates, the S factor contributed the most information, followed by K and L factors, and R factor made almost no contribution to the spatial estimation of soil loss. The LS factor derived from 30 or 90 m Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data
Directory of Open Access Journals (Sweden)
Ali Akbar Moosavi
2017-02-01
Full Text Available Introduction: Saturated hydraulic conductivity and the other hydraulic properties of soils are essential vital soil attributes that play role in the modeling of hydrological phenomena, designing irrigation-drainage systems, transportation of salts and chemical and biological pollutants within the soil. Measurement of these hydraulic properties needs some special instruments, expert technician, and are time consuming and expensive and due to their high temporal and spatial variability, a large number of measurements are needed. Nowadays, prediction of these attributes using the readily available soil data using pedotransfer functions or using the limited measurement with applying the geostatistical approaches has been receiving high attention. The study aimed to determine the spatial variability and prediction of saturated (Ks and near saturated (Kfs hydraulic conductivity, the power of Gardner equation (α, sorptivity (S, hydraulic diffusivity (D and matric flux potential (Фm of a calcareous soil. Material and Methods: The study was carried out on the soil series of Daneshkadeh located in the Bajgah Agricultural Experimental Station of Agricultural College, Shiraz University, Shiraz, Iran (1852 m above the mean sea level. This soil series with about 745 ha is a deep yellowish brow calcareous soil with textural classes of loam to clay. In the studied soil series 50 sampling locations with the sampling distances of 16, 8 , and 4 m were selected on the relatively regular sampling design. The saturated hydraulic conductivity (Ks, near saturated hydraulic conductivity (Kfs, the power of Gardner equation (α, sorptivity (S, hydraulic diffusivity (D and matric flux potential (Фm of the aforementioned sampling locations was determined using the Single Ring and Droplet methods. After, initial statistical processing, including a normality test of data, trend and stationary analysis of data, the semivariograms of each studied hydraulic attributes were
School Principals' Assumptions about Human Nature: Implications for Leadership in Turkey
Sabanci, Ali
2008-01-01
This article considers principals' assumptions about human nature in Turkey and the relationship between the assumptions held and the leadership style adopted in schools. The findings show that school principals hold Y-type assumptions and prefer a relationship-oriented style in their relations with assistant principals. However, both principals…
Taylor, Maureen; Kent, Michael L.
1999-01-01
Explores assumptions underlying Malaysia's and the United States' public-relations practice. Finds many assumptions guiding Western theories and practices are not applicable to other countries. Examines the assumption that the practice of public relations targets a variety of key organizational publics. Advances international public-relations…
Kruger-Ross, Matthew J.; Holcomb, Lori B.
2012-01-01
The use of educational technologies is grounded in the assumptions of teachers, learners, and administrators. Assumptions are choices that structure our understandings and help us make meaning. Current advances in Web 2.0 and social media technologies challenge our assumptions about teaching and learning. The intersection of technology and…
Namysłowska-Wilczyńska, Barbara; Wynalek, Janusz
2017-12-01
Geostatistical methods make the analysis of measurement data possible. This article presents the problems directed towards the use of geostatistics in spatial analysis of displacements based on geodetic monitoring. Using methods of applied (spatial) statistics, the research deals with interesting and current issues connected to space-time analysis, modeling displacements and deformations, as applied to any large-area objects on which geodetic monitoring is conducted (e.g., water dams, urban areas in the vicinity of deep excavations, areas at a macro-regional scale subject to anthropogenic influences caused by mining, etc.). These problems are very crucial, especially for safety assessment of important hydrotechnical constructions, as well as for modeling and estimating mining damage. Based on the geodetic monitoring data, a substantial basic empirical material was created, comprising many years of research results concerning displacements of controlled points situated on the crown and foreland of an exemplary earth dam, and used to assess the behaviour and safety of the object during its whole operating period. A research method at a macro-regional scale was applied to investigate some phenomena connected with the operation of the analysed big hydrotechnical construction. Applying a semivariogram function enabled the spatial variability analysis of displacements. Isotropic empirical semivariograms were calculated and then, theoretical parameters of analytical functions were determined, which approximated the courses of the mentioned empirical variability measure. Using ordinary (block) kriging at the grid nodes of an elementary spatial grid covering the analysed object, the values of the Z* estimated means of displacements were calculated together with the accompanying assessment of uncertainty estimation - a standard deviation of estimation σk. Raster maps of the distribution of estimated averages Z* and raster maps of deviations of estimation σk (in perspective
International Nuclear Information System (INIS)
Larsson, Arne; Lidar, Per; Desnoyers, Yvon
2014-01-01
Radiological characterisation plays an important role in the process to recycle contaminated or potentially contaminated metals. It is a platform for planning, identification of the extent and nature of contamination, assessing potential risk impacts, cost estimation, radiation protection, management of material arising from decommissioning as well as for the release of the materials as well as the disposal of the generated secondary waste as radioactive waste. Key issues in radiological characterisation are identification of objectives, development of a measurement and sampling strategy (probabilistic, judgmental or a combination thereof), knowledge management, traceability, recording and processing of obtained information. By applying advanced combination of statistical and geostatistical in the concept better performance can be achieved at a lower cost. This paper will describe the benefits with the usage of the available methods in the different stages of the characterisation, treatment and clearance processes aiming for reliable results in line with the data quality objectives. (authors)
El Sebai, T; Lagacherie, B; Soulas, G; Martin-Laurent, F
2007-02-01
We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass.
Babcock, Chad; Finley, Andrew O.; Andersen, Hans-Erik; Pattison, Robert; Cook, Bruce D.; Morton, Douglas C.; Alonzo, Michael; Nelson, Ross; Gregoire, Timothy; Ene, Liviu; Gobakken, Terje; Næsset, Erik
2018-06-01
The goal of this research was to develop and examine the performance of a geostatistical coregionalization modeling approach for combining field inventory measurements, strip samples of airborne lidar and Landsat-based remote sensing data products to predict aboveground biomass (AGB) in interior Alaska's Tanana Valley. The proposed modeling strategy facilitates pixel-level mapping of AGB density predictions across the entire spatial domain. Additionally, the coregionalization framework allows for statistically sound estimation of total AGB for arbitrary areal units within the study area---a key advance to support diverse management objectives in interior Alaska. This research focuses on appropriate characterization of prediction uncertainty in the form of posterior predictive coverage intervals and standard deviations. Using the framework detailed here, it is possible to quantify estimation uncertainty for any spatial extent, ranging from pixel-level predictions of AGB density to estimates of AGB stocks for the full domain. The lidar-informed coregionalization models consistently outperformed their counterpart lidar-free models in terms of point-level predictive performance and total AGB precision. Additionally, the inclusion of Landsat-derived forest cover as a covariate further improved estimation precision in regions with lower lidar sampling intensity. Our findings also demonstrate that model-based approaches that do not explicitly account for residual spatial dependence can grossly underestimate uncertainty, resulting in falsely precise estimates of AGB. On the other hand, in a geostatistical setting, residual spatial structure can be modeled within a Bayesian hierarchical framework to obtain statistically defensible assessments of uncertainty for AGB estimates.
Bellotti, F.; Capra, L.; Sarocchi, D.; D'Antonio, M.
2010-03-01
Grain size analysis of volcaniclastic deposits is mainly used to study flow transport and depositional processes, in most cases by comparing some statistical parameters and how they change with distance from the source. In this work the geospatial and multivariate analyses are presented as a strong adaptable geostatistical tool applied to volcaniclastic deposits in order to provide an effective and relatively simple methodology for texture description, deposit discrimination and interpretation of depositional processes. We choose the case of Nevado de Toluca volcano (Mexico) due to existing knowledge of its geological evolution, stratigraphic succession and spatial distribution of volcaniclastic units. Grain size analyses and frequency distribution curves have been carried out to characterize and compare the 28-ka block-and-ash flow deposit associated to a dome destruction episode, and the El Morral debris avalanche deposit originated from the collapse of the south-eastern sector of the volcano. The geostatistical interpolation of sedimentological data allows to realize bidimensional maps draped over the volcano topography, showing the granulometric distribution, sorting and fine material concentration into the whole deposit with respect to topographic changes. In this way, it is possible to analyze a continuous surface of the grain size distribution of volcaniclastic deposits and better understand flow transport processes. The application of multivariate statistic analysis (discriminant function) indicates that this methodology could be useful in discriminating deposits with different origin or different depositional lithofacies within the same deposit. The proposed methodology could be an interesting approach to sustain more classical analysis of volcaniclastic deposits, especially where a clear field classification appears problematic because of a homogeneous texture of the deposits or their scarce and discontinuous outcrops. Our study is an example of the
Fabijańczyk, Piotr; Zawadzki, Jarosław
2016-04-01
Field magnetometry is fast method that was previously effectively used to assess the potential soil pollution. One of the most popular devices that are used to measure the soil magnetic susceptibility on the soil surface is a MS2D Bartington. Single reading using MS2D device of soil magnetic susceptibility is low time-consuming but often characterized by considerable errors related to the instrument or environmental and lithogenic factors. In this connection, measured values of soil magnetic susceptibility have to be usually validated using more precise, but also much more expensive, chemical measurements. The goal of this study was to analyze validation methods of magnetometric measurements using chemical analyses of a concentration of elements in soil. Additionally, validation of surface measurements of soil magnetic susceptibility was performed using selected parameters of a distribution of magnetic susceptibility in a soil profile. Validation was performed using selected geostatistical measures of cross-correlation. The geostatistical approach was compared with validation performed using the classic statistics. Measurements were performed at selected areas located in the Upper Silesian Industrial Area in Poland, and in the selected parts of Norway. In these areas soil magnetic susceptibility was measured on the soil surface using a MS2D Bartington device and in the soil profile using MS2C Bartington device. Additionally, soil samples were taken in order to perform chemical measurements. Acknowledgment The research leading to these results has received funding from the Polish-Norwegian Research Programme operated by the National Centre for Research and Development under the Norwegian Financial Mechanism 2009-2014 in the frame of Project IMPACT - Contract No Pol-Nor/199338/45/2013.
Ernst, Anja F; Albers, Casper J
2017-01-01
Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking.
Energy Technology Data Exchange (ETDEWEB)
Salter, P.F.; Apted, M.J. [Monitor Scientific LLC, Denver, CO (United States); Sasamoto, Hiroshi; Yui, Mikazu
1999-05-01
The groundwater chemistry is one of important geological environment for performance assessment of high level radioactive disposal system. This report describes the results of geostatistical analysis of groundwater chemistry in Japan. Over 15,000 separate groundwater analyses have been collected of deep Japanese groundwaters for the purpose of evaluating the range of geochemical conditions for geological radioactive waste repositories in Japan. The significance to issues such as radioelement solubility limits, sorption, corrosion of overpack, behavior of compacted clay buffers, and many other factors involved in safety assessment. It is important therefore, that a small, but representative set of groundwater types be identified so that defensible models and data for generic repository performance assessment can be established. Principal component analysis (PCA) is used to categorize representative deep groundwater types from this extensive data set. PCA is a multi-variate statistical analysis technique, similar to factor analysis or eigenvector analysis, designed to provide the best possible resolution of the variability within multi-variate data sets. PCA allows the graphical inspection of the most important similarities (clustering) and differences among samples, based on simultaneous consideration of all variables in the dataset, in a low dimensionality plot. It also allows the analyst to determine the reasons behind any pattern that is observed. In this study, PCA has been aided by hierarchical cluster analysis (HCA), in which statistical indices of similarity among multiple samples are used to distinguish distinct clusters of samples. HCA allows the natural, a priori, grouping of data into clusters showing similar attributes and is graphically represented in a dendrogram Pirouette is the multivariate statistical software package used to conduct the PCA and HCA for the Japanese groundwater dataset. An audit of the initial 15,000 sample dataset on the basis of
Directory of Open Access Journals (Sweden)
Masoud Davari
2017-01-01
distribution of SOC were carried out with the geostatistical software GS+ (version 5. 1. Maps were generated by using ILWIS (version 3.3 GIS software. Results and Discussion: The results revealed that the raw SOC data have a long tail towards higher concentrations, whereas that squareroot transformed data can be satisfactorily modelled by a normal distribution. The probability distribution of SOC appeared to be positively skewed and have a positive kurtosis. The square root transformed data showed small skewness and kurtosis, and passed the K–S normality test at a significance level of higher than 0.05. Therefore, the square root transformed data of SOC was used for analyses. The SOC concentration varied from 0.08 to 2.39%, with an arithmetic mean of 0.81% and geometric mean of 0.73%. The coefficient of variation (CV, as an index of overall variability of SOC, was 44.49%. According to the classification system presented by Nielson and Bouma (1985, a variable is moderately varying if the CV is between 10% and 100%. Therefore, the content of SOC in the Aligodarz watershed can be considered to be in moderate variability. The experimental variogram of SOC was fitted by an exponential model. The values of the range, nugget, sill, and nugget/sill ratio of the best-fitted model were 6.80 km, 0.058, 0.133, and 43.6%, respectively. The positive nugget value can be explained by sampling error, short range variability, and unexplained and inherent variability. The nugget/sill ratio of 43.6% showed a moderate spatial dependence of SOC in the study area. The parameters of the exponential smivariogram model were used for kriging method to produce a spatial distribution map of SOC in the study area. The interpolated values ranged between 0.30 and 1.40%. Southern and central parts of this study area have the highest SOC concentrations, while the northern parts have the lowest concentrations of SOC. Kriging results also showed that the major parts of the Aligodarz watershed (about 87% have
International Nuclear Information System (INIS)
Ye, Ming; Pan, Feng; Hu, Xiaolong; Zhu, Jianting
2007-01-01
Yucca Mountain has been proposed by the U.S. Department of Energy as the nation's long-term, permanent geologic repository for spent nuclear fuel or high-level radioactive waste. The potential repository would be located in Yucca Mountain's unsaturated zone (UZ), which acts as a critical natural barrier delaying arrival of radionuclides to the water table. Since radionuclide transport in groundwater can pose serious threats to human health and the environment, it is important to understand how much and how fast water and radionuclides travel through the UZ to groundwater. The UZ system consists of multiple hydrogeologic units whose hydraulic and geochemical properties exhibit systematic and random spatial variation, or heterogeneity, at multiple scales. Predictions of radionuclide transport under such complicated conditions are uncertain, and the uncertainty complicates decision making and risk analysis. This project aims at using geostatistical and stochastic methods to assess uncertainty of unsaturated flow and radionuclide transport in the UZ at Yucca Mountain. Focus of this study is parameter uncertainty of hydraulic and transport properties of the UZ. The parametric uncertainty arises since limited parameter measurements are unable to deterministically describe spatial variability of the parameters. In this project, matrix porosity, permeability and sorption coefficient of the reactive tracer (neptunium) of the UZ are treated as random variables. Corresponding propagation of parametric uncertainty is quantitatively measured using mean, variance, 5th and 95th percentiles of simulated state variables (e.g., saturation, capillary pressure, percolation flux, and travel time). These statistics are evaluated using a Monte Carlo method, in which a three-dimensional flow and transport model implemented using the TOUGH2 code is executed with multiple parameter realizations of the random model parameters. The project specifically studies uncertainty of unsaturated flow
Energy Technology Data Exchange (ETDEWEB)
Korn, Stefan
2012-05-15
Since the amendment of the EEG in January 2012, enormous amounts of electric power from renewable energy sources are marketed directly, i.e. outside the control of power supply grid owners and operators that formerly sold the electric power in the stock exchange. Inaccurate prognoses made by the direct marketers as well as their marketing strategies have increased the demand for balancing power and made critical situations in the power grid even more difficult.
Energy Technology Data Exchange (ETDEWEB)
Zargar, G
2005-10-15
In this thesis, we present a new approach, which consists in directly up-scaling the geostatistical permeability distribution rather than the individual realizations. Practically, filtering techniques based on. the FFT (Fast Fourier Transform), allows us to generate geostatistical images, which sample the up-scaled distributions. In the log normal case, an equivalence hydraulic criterion is proposed, allowing to re-estimate the geometric mean of the permeabilities. In the anisotropic case, the effective geometric mean becomes a tensor which depends on the level of filtering used and it can be calculated by a method of renormalisation. Then, the method was generalized for the categorial model. Numerical tests of the method were set up for isotropic, anisotropic and categorial models, which shows good agreement with theory. (author)
Energy Technology Data Exchange (ETDEWEB)
Zargar, G.
2005-10-15
In this thesis, we present a new approach, which consists in directly up-scaling the geostatistical permeability distribution rather than the individual realizations. Practically, filtering techniques based on. the FFT (Fast Fourier Transform), allows us to generate geostatistical images, which sample the up-scaled distributions. In the log normal case, an equivalence hydraulic criterion is proposed, allowing to re-estimate the geometric mean of the permeabilities. In the anisotropic case, the effective geometric mean becomes a tensor which depends on the level of filtering used and it can be calculated by a method of renormalisation. Then, the method was generalized for the categorial model. Numerical tests of the method were set up for isotropic, anisotropic and categorial models, which shows good agreement with theory. (author)
Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.
2018-01-01
Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.
DEFF Research Database (Denmark)
Skovbjerg, Helle Marie; Bekker, Tilde; Barendregt, Wolmet
2016-01-01
In this full-day workshop we want to discuss how the IDC community can make underlying assumptions, values and views regarding children and childhood in making design decisions more explicit. What assumptions do IDC designers and researchers make, and how can they be supported in reflecting......, and intends to share different approaches for uncovering and reflecting on values, assumptions and views about children and childhood in design....
Sarmadian, Fereydoon; Keshavarzi, Ali
2010-05-01
Most of soils in iran, were located in the arid and semi-arid regions and have high pH (more than 7) and high amount of calcium carbonate and this problem cause to their calcification.In calcareous soils, plant growing and production is difficult. Most part of this problem, in relation to high pH and high concentration of calcium ion that cause to fixation and unavailability of elements which were dependent to pH, especially Phosphorous and some micro nutrients such as Fe, Zn, Mn and Cu. Prediction of soil calcium carbonate in non-sampled areas and mapping the calcium carbonate variability in order to sustainable management of soil fertility is very important.So, this research was done with the aim of evaluation and analyzing spatial variability of topsoil calcium carbonate as an aspect of soil fertility and plant nutrition, comparing geostatistical methods such as kriging and co-kriging and mapping topsoil calcium carbonate. For geostatistical analyzing, sampling was done with stratified random method and soil samples from 0 to 15 cm depth were collected with auger within 23 locations.In co-kriging method, salinity data was used as auxiliary variable. For comparing and evaluation of geostatistical methods, cross validation were used by statistical parameters of RMSE. The results showed that co-kriging method has the highest correlation coefficient and less RMSE and has the higher accuracy than kriging method to prediction of calcium carbonate content in non-sampled areas.
Parasyris, Antonios E.; Spanoudaki, Katerina; Kampanis, Nikolaos A.
2016-04-01
Groundwater level monitoring networks provide essential information for water resources management, especially in areas with significant groundwater exploitation for agricultural and domestic use. Given the high maintenance costs of these networks, development of tools, which can be used by regulators for efficient network design is essential. In this work, a monitoring network optimisation tool is presented. The network optimisation tool couples geostatistical modelling based on the Spartan family variogram with a genetic algorithm method and is applied to Mires basin in Crete, Greece, an area of high socioeconomic and agricultural interest, which suffers from groundwater overexploitation leading to a dramatic decrease of groundwater levels. The purpose of the optimisation tool is to determine which wells to exclude from the monitoring network because they add little or no beneficial information to groundwater level mapping of the area. Unlike previous relevant investigations, the network optimisation tool presented here uses Ordinary Kriging with the recently-established non-differentiable Spartan variogram for groundwater level mapping, which, based on a previous geostatistical study in the area leads to optimal groundwater level mapping. Seventy boreholes operate in the area for groundwater abstraction and water level monitoring. The Spartan variogram gives overall the most accurate groundwater level estimates followed closely by the power-law model. The geostatistical model is coupled to an integer genetic algorithm method programmed in MATLAB 2015a. The algorithm is used to find the set of wells whose removal leads to the minimum error between the original water level mapping using all the available wells in the network and the groundwater level mapping using the reduced well network (error is defined as the 2-norm of the difference between the original mapping matrix with 70 wells and the mapping matrix of the reduced well network). The solution to the
International Nuclear Information System (INIS)
Khorsandi, Jahon; Aven, Terje
2017-01-01
Quantitative risk assessments (QRAs) of complex engineering systems are based on numerous assumptions and expert judgments, as there is limited information available for supporting the analysis. In addition to sensitivity analyses, the concept of assumption deviation risk has been suggested as a means for explicitly considering the risk related to inaccuracies and deviations in the assumptions, which can significantly impact the results of the QRAs. However, challenges remain for its practical implementation, considering the number of assumptions and magnitude of deviations to be considered. This paper presents an approach for integrating an assumption deviation risk analysis as part of QRAs. The approach begins with identifying the safety objectives for which the QRA aims to support, and then identifies critical assumptions with respect to ensuring the objectives are met. Key issues addressed include the deviations required to violate the safety objectives, the uncertainties related to the occurrence of such events, and the strength of knowledge supporting the assessments. Three levels of assumptions are considered, which include assumptions related to the system's structural and operational characteristics, the effectiveness of the established barriers, as well as the consequence analysis process. The approach is illustrated for the case of an offshore installation. - Highlights: • An approach for assessing the risk of deviations in QRA assumptions is presented. • Critical deviations and uncertainties related to their occurrence are addressed. • The analysis promotes critical thinking about the foundation and results of QRAs. • The approach is illustrated for the case of an offshore installation.
International Nuclear Information System (INIS)
Park, Jinyong; Balasingham, P.; McKenna, Sean Andrew; Kulatilake, Pinnaduwa H. S. W.
2004-01-01
Sandia National Laboratories, under contract to Nuclear Waste Management Organization of Japan (NUMO), is performing research on regional classification of given sites in Japan with respect to potential volcanic disruption using multivariate statistics and geo-statistical interpolation techniques. This report provides results obtained for hierarchical probabilistic regionalization of volcanism for the Sengan region in Japan by applying multivariate statistical techniques and geostatistical interpolation techniques on the geologic data provided by NUMO. A workshop report produced in September 2003 by Sandia National Laboratories (Arnold et al., 2003) on volcanism lists a set of most important geologic variables as well as some secondary information related to volcanism. Geologic data extracted for the Sengan region in Japan from the data provided by NUMO revealed that data are not available at the same locations for all the important geologic variables. In other words, the geologic variable vectors were found to be incomplete spatially. However, it is necessary to have complete geologic variable vectors to perform multivariate statistical analyses. As a first step towards constructing complete geologic variable vectors, the Universal Transverse Mercator (UTM) zone 54 projected coordinate system and a 1 km square regular grid system were selected. The data available for each geologic variable on a geographic coordinate system were transferred to the aforementioned grid system. Also the recorded data on volcanic activity for Sengan region were produced on the same grid system. Each geologic variable map was compared with the recorded volcanic activity map to determine the geologic variables that are most important for volcanism. In the regionalized classification procedure, this step is known as the variable selection step. The following variables were determined as most important for volcanism: geothermal gradient, groundwater temperature, heat discharge, groundwater
Directory of Open Access Journals (Sweden)
Asma Shaheen
2018-03-01
Full Text Available In third world countries, industries mainly cause environmental contamination due to lack of environmental policies or oversight during their implementation. The Sheikhupura industrial zone, which includes industries such as tanneries, leather, chemical, textiles, and colour and dyes, contributes massive amounts of untreated effluents that are released directly into drains and used for the irrigation of crops and vegetables. This practice causes not only soil contamination with an excessive amount of heavy metals, but is also considered a source of toxicity in the food chain, i.e., bioaccumulation in plants and ultimately in human body organs. The objective of this research study was to assess the spatial distribution of the heavy metals chromium (Cr, cadmium (Cd, and lead (Pb, at three depths of soil using geostatistics and the selection of significant contributing variables to soil contamination using the Random Forest (RF function of the Boruta Algorithm. A total of 60 sampling locations were selected in the study area to collect soil samples (180 samples at three depths (0–15 cm, 15–30 cm, and 60–90 cm. The soil samples were analysed for their physico-chemical properties, i.e., soil saturation, electrical conductivity (EC, organic matter (OM, pH, phosphorus (P, potassium (K, and Cr, Cd, and Pb using standard laboratory procedures. The data were analysed with comprehensive statistics and geostatistical techniques. The correlation coefficient matrix between the heavy metals and the physico-chemical properties revealed that electrical conductivity (EC had a significant (p ≤ 0.05 negative correlation with Cr, Cd, and Pb. The RF function of the Boruta Algorithm employed soil depth as a classifier and ranked the significant soil contamination parameters (Cr, Cd, Pb, EC, and P in relation to depth. The mobility factor indicated the leachate percentage of heavy metals at different vertical depths of soil. The spatial distribution pattern of
Wegerif, Rupert
2008-01-01
This article explores the relationship between ontological assumptions and studies of educational dialogue through a focus on Bakhtin's "dialogic". The term dialogic is frequently appropriated to a modernist framework of assumptions, in particular the neo-Vygotskian or sociocultural tradition. However, Vygotsky's theory of education is dialectic,…
7 CFR 772.10 - Transfer and assumption-AMP loans.
2010-01-01
... 7 Agriculture 7 2010-01-01 2010-01-01 false Transfer and assumption-AMP loans. 772.10 Section 772..., DEPARTMENT OF AGRICULTURE SPECIAL PROGRAMS SERVICING MINOR PROGRAM LOANS § 772.10 Transfer and assumption—AMP loans. (a) Eligibility. The Agency may approve transfers and assumptions of AMP loans when: (1) The...
Directory of Open Access Journals (Sweden)
Engin Oner
2015-06-01
Full Text Available Adam Smith being its founder, in the Classical School, which gives prominence to supply and adopts an approach of unbiased finance, the economy is always in a state of full employment equilibrium. In this system of thought, the main philosophy of which is budget balance, that asserts that there is flexibility between prices and wages and regards public debt as an extraordinary instrument, the interference of the state with the economic and social life is frowned upon. In line with the views of the classical thought, the classical fiscal policy is based on three basic assumptions. These are the "Consumer State Assumption", the assumption accepting that "Public Expenditures are Always Ineffectual" and the assumption concerning the "Impartiality of the Taxes and Expenditure Policies Implemented by the State". On the other hand, the Keynesian School founded by John Maynard Keynes, gives prominence to demand, adopts the approach of functional finance, and asserts that cases of underemployment equilibrium and over-employment equilibrium exist in the economy as well as the full employment equilibrium, that problems cannot be solved through the invisible hand, that prices and wages are strict, the interference of the state is essential and at this point fiscal policies have to be utilized effectively.Keynesian fiscal policy depends on three primary assumptions. These are the assumption of "Filter State", the assumption that "public expenditures are sometimes effective and sometimes ineffective or neutral" and the assumption that "the tax, debt and expenditure policies of the state can never be impartial".
A Proposal for Testing Local Realism Without Using Assumptions Related to Hidden Variable States
Ryff, Luiz Carlos
1996-01-01
A feasible experiment is discussed which allows us to prove a Bell's theorem for two particles without using an inequality. The experiment could be used to test local realism against quantum mechanics without the introduction of additional assumptions related to hidden variables states. Only assumptions based on direct experimental observation are needed.
Evaluating growth assumptions using diameter or radial increments in natural even-aged longleaf pine
John C. Gilbert; Ralph S. Meldahl; Jyoti N. Rayamajhi; John S. Kush
2010-01-01
When using increment cores to predict future growth, one often assumes future growth is identical to past growth for individual trees. Once this assumption is accepted, a decision has to be made between which growth estimate should be used, constant diameter growth or constant basal area growth. Often, the assumption of constant diameter growth is used due to the ease...
Sensitivity of TRIM projections to management, harvest, yield, and stocking adjustment assumptions.
Susan J. Alexander
1991-01-01
The Timber Resource Inventory Model (TRIM) was used to make several projections of forest industry timber supply for the Douglas-fir region. The sensitivity of these projections to assumptions about management and yields is discussed. A base run is compared to runs in which yields were altered, stocking adjustment was eliminated, harvest assumptions were changed, and...
The Importance of the Assumption of Uncorrelated Errors in Psychometric Theory
Raykov, Tenko; Marcoulides, George A.; Patelis, Thanos
2015-01-01
A critical discussion of the assumption of uncorrelated errors in classical psychometric theory and its applications is provided. It is pointed out that this assumption is essential for a number of fundamental results and underlies the concept of parallel tests, the Spearman-Brown's prophecy and the correction for attenuation formulas as well as…
Recognising the Effects of Costing Assumptions in Educational Business Simulation Games
Eckardt, Gordon; Selen, Willem; Wynder, Monte
2015-01-01
Business simulations are a powerful way to provide experiential learning that is focussed, controlled, and concentrated. Inherent in any simulation, however, are numerous assumptions that determine feedback, and hence the lessons learnt. In this conceptual paper we describe some common cost assumptions that are implicit in simulation design and…
Ali, Holi Ibrahim Holi
2012-01-01
This study is set to investigate students' and teachers' perceptions and assumptions about newly implemented CALL Programme at the School of Foundation Studies, Caledonian College of Engineering, Oman. Two versions of questionnaire were administered to 24 teachers and 90 students to collect their beliefs and assumption about CALL programame. The…
Semi-Supervised Transductive Hot Spot Predictor Working on Multiple Assumptions
Wang, Jim Jing-Yan; Almasri, Islam; Shi, Yuexiang; Gao, Xin
2014-01-01
of the transductive semi-supervised algorithms takes all the three semisupervised assumptions, i.e., smoothness, cluster and manifold assumptions, together into account during learning. In this paper, we propose a novel semi-supervised method for hot spot residue
Kirby, Moira
2017-01-01
Introduction: Everyday millions of students in the United States receive special education services. Special education is an institution shaped by societal norms. Inherent in these norms are implicit assumptions regarding disability and the nature of special education services. The two dominant implicit assumptions evident in the American…
Sensitivity of the OMI ozone profile retrieval (OMO3PR) to a priori assumptions
Mielonen, T.; De Haan, J.F.; Veefkind, J.P.
2014-01-01
We have assessed the sensitivity of the operational OMI ozone profile retrieval (OMO3PR) algorithm to a number of a priori assumptions. We studied the effect of stray light correction, surface albedo assumptions and a priori ozone profiles on the retrieved ozone profile. Then, we studied how to
The Arundel Assumption And Revision Of Some Large-Scale Maps ...
African Journals Online (AJOL)
The rather common practice of stating or using the Arundel Assumption without reference to appropriate mapping standards (except mention of its use for graphical plotting) is a major cause of inaccuracies in map revision. This paper describes an investigation to ascertain the applicability of the Assumption to the revision of ...
The Role of Policy Assumptions in Validating High-stakes Testing Programs.
Kane, Michael
L. Cronbach has made the point that for validity arguments to be convincing to diverse audiences, they need to be based on assumptions that are credible to these audiences. The interpretations and uses of high stakes test scores rely on a number of policy assumptions about what should be taught in schools, and more specifically, about the content…
Directory of Open Access Journals (Sweden)
Annamaria Castrignanò
2017-12-01
Full Text Available To assess spatial variability at the very fine scale required by Precision Agriculture, different proximal and remote sensors have been used. They provide large amounts and different types of data which need to be combined. An integrated approach, using multivariate geostatistical data-fusion techniques and multi-source geophysical sensor data to determine simple summary scale-dependent indices, is described here. These indices can be used to delineate management zones to be submitted to differential management. Such a data fusion approach with geophysical sensors was applied in a soil of an agronomic field cropped with tomato. The synthetic regionalized factors determined, contributed to split the 3D edaphic environment into two main horizontal structures with different hydraulic properties and to disclose two main horizons in the 0–1.0-m depth with a discontinuity probably occurring between 0.40 m and 0.70 m. Comparing this partition with the soil properties measured with a shallow sampling, it was possible to verify the coherence in the topsoil between the dielectric properties and other properties more directly related to agronomic management. These results confirm the advantages of using proximal sensing as a preliminary step in the application of site-specific management. Combining disparate spatial data (data fusion is not at all a naive problem and novel and powerful methods need to be developed.
Hatvani, István Gábor; Leuenberger, Markus; Kohán, Balázs; Kern, Zoltán
2017-09-01
Water stable isotopes preserved in ice cores provide essential information about polar precipitation. In the present study, multivariate regression and variogram analyses were conducted on 22 δ2H and 53 δ18O records from 60 ice cores covering the second half of the 20th century. Taking the multicollinearity of the explanatory variables into account, as also the model's adjusted R2 and its mean absolute error, longitude, elevation and distance from the coast were found to be the main independent geographical driving factors governing the spatial δ18O variability of firn/ice in the chosen Antarctic macro region. After diminishing the effects of these factors, using variography, the weights for interpolation with kriging were obtained and the spatial autocorrelation structure of the dataset was revealed. This indicates an average area of influence with a radius of 350 km. This allows the determination of the areas which are as yet not covered by the spatial variability of the existing network of ice cores. Finally, the regional isoscape was obtained for the study area, and this may be considered the first step towards a geostatistically improved isoscape for Antarctica.
Spatial variability of soil pH based on GIS combined with geostatistics in Panzhihua tobacco area
International Nuclear Information System (INIS)
Du Wei; Wang Changquan; Li Bing; Li Qiquan; Du Qian; Hu Jianxin; Liu Chaoke
2012-01-01
GIS and geostatistics were utilized to study the spatial variability of soil pH in Panzhihua tobacco area. Results showed that pH values in this area ranged from 4.5 to 8.3, especially 5.5 to 6.5, and in few areas were lower than 5.0 or higher than 7.0 which can meet the need of high-quality tobacco production. The best fitting model of variogram was exponential model with the nugget/sill of soil pH in 13.61% indicating strong spatial correlation. The change process was 5.40 km and the coefficient of determination was 0.491. The spatial variability of soil pH was mainly caused by structural factors such as cane, topography and soil type. The soil pH in Panzhihua tobacco area also showed a increasing trend of northwest to southeast trend. The pH of some areas in Caochang, Gonghe and Yumen were lower, and in Dalongtan were slightly higher. (authors)
International Nuclear Information System (INIS)
Marquis, S.A. Jr.; Smith, E.A.
1994-01-01
Traditional environmental investigations at tidally influenced hazardous waste sites such as marine fuel storage terminals have generally failed to characterize ground-water flow and chemical transport because they have been based on only a cursory knowledge of plume geometry, chemicals encountered, and hydrogeologic setting and synoptic ground-water level measurement. Single-time observations cannot be used to accurately determine flow direction and gradient in tidally fluctuating aquifers since these measurements delineate hydraulic head at only one point in time during a tidal cycle, not the net effect of the fluctuations. In this study, a more rigorous approach was used to characterize flow and chemical transport in a tidally influenced aquifer at a marine fuel storage terminal using: (1) ground-water-level monitoring over three tidal cycles (72 hours), (2) geostatistical filtering of ground-water-level data using 25-hour and 71-hour filtering methods, and (3) hydrocarbon fingerprinting analysis. The results from the study indicate that naphtha released from one of the on-site naphtha tanks has been the predominant contributor to the hydrocarbon plume both on-site and downgradient off-site and that net ground-water and hydrocarbon movement has been to the southeast away from the tank since 1989
Directory of Open Access Journals (Sweden)
M. Hashemi
2017-02-01
Full Text Available Introduction: In order to provide a database, it is essential having access to accurate information on soil spatial variation for soil sustainable management such as proper application of fertilizers. Spatial variations in soil properties are common but it is important for understanding these changes, particularly in agricultural lands for careful planning and land management. Materials and Methods: To this end, in winter 1391, 189 undisturbed soil samples (0-30 cm depth in a regular lattice with a spacing of 500 m were gathered from the surface of Miankangi land, Sistan plain, and their physical and chemical properties were studied. The land area of the region is about 4,500 hectares; the average elevation of studied area is 489.2 meters above sea level with different land uses. Soil texture was measured by the hydrometer methods (11, Also EC and pH (39, calcium carbonate equivalent (37 and the saturation percentage of soils were determined. Kriging, Co-Kriging, Inverse Distance Weighting and Local Polynomial Interpolation techniques were evaluated to produce a soil characteristics map of the study area zoning and to select the best geostatistical methods. Cross-validation techniques and Root Mean Square Error (RMSE were used. Results and Discussion: Normalized test results showed that all of the soil properties except calcium carbonate and soil clay content had normal distribution. In addition, the results of correlation test showed that the soil saturation percentage was positively correlated with silt content (r=0.43 and p
Gething, Peter W; Patil, Anand P; Hay, Simon I
2010-04-01
Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty--the fidelity of predictions at each mapped pixel--but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.
Demougeot-Renard, Helene; De Fouquet, Chantal
2004-10-01
Assessing the volume of soil requiring remediation and the accuracy of this assessment constitutes an essential step in polluted site management. If this remediation volume is not properly assessed, misclassification may lead both to environmental risks (polluted soils may not be remediated) and financial risks (unexpected discovery of polluted soils may generate additional remediation costs). To minimize such risks, this paper proposes a geostatistical methodology based on stochastic simulations that allows the remediation volume and the uncertainty to be assessed using investigation data. The methodology thoroughly reproduces the conditions in which the soils are classified and extracted at the remediation stage. The validity of the approach is tested by applying it on the data collected during the investigation phase of a former lead smelting works and by comparing the results with the volume that has actually been remediated. This real remediated volume was composed of all the remediation units that were classified as polluted after systematic sampling and analysis during clean-up stage. The volume estimated from the 75 samples collected during site investigation slightly overestimates (5.3% relative error) the remediated volume deduced from 212 remediation units. Furthermore, the real volume falls within the range of uncertainty predicted using the proposed methodology.
Castrignanò, Annamaria; Buttafuoco, Gabriele; Quarto, Ruggiero; Vitti, Carolina; Langella, Giuliano; Terribile, Fabio; Venezia, Accursio
2017-12-03
To assess spatial variability at the very fine scale required by Precision Agriculture, different proximal and remote sensors have been used. They provide large amounts and different types of data which need to be combined. An integrated approach, using multivariate geostatistical data-fusion techniques and multi-source geophysical sensor data to determine simple summary scale-dependent indices, is described here. These indices can be used to delineate management zones to be submitted to differential management. Such a data fusion approach with geophysical sensors was applied in a soil of an agronomic field cropped with tomato. The synthetic regionalized factors determined, contributed to split the 3D edaphic environment into two main horizontal structures with different hydraulic properties and to disclose two main horizons in the 0-1.0-m depth with a discontinuity probably occurring between 0.40 m and 0.70 m. Comparing this partition with the soil properties measured with a shallow sampling, it was possible to verify the coherence in the topsoil between the dielectric properties and other properties more directly related to agronomic management. These results confirm the advantages of using proximal sensing as a preliminary step in the application of site-specific management. Combining disparate spatial data (data fusion) is not at all a naive problem and novel and powerful methods need to be developed.
Energy Technology Data Exchange (ETDEWEB)
El Sebai, T. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France); Lagacherie, B. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France); Soulas, G. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France); Martin-Laurent, F. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France)]. E-mail: fmartin@dijon.inra.fr
2007-02-15
We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass. - In field spatial variation of isoproturon mineralization mainly results from the spatial heterogeneity of soil pH and microbial C biomass.
International Nuclear Information System (INIS)
El Sebai, T.; Lagacherie, B.; Soulas, G.; Martin-Laurent, F.
2007-01-01
We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass. - In field spatial variation of isoproturon mineralization mainly results from the spatial heterogeneity of soil pH and microbial C biomass
Austin, Peter C
2018-01-01
The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest.
Ernst, Anja F.
2017-01-01
Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking. PMID:28533971
Directory of Open Access Journals (Sweden)
Anja F. Ernst
2017-05-01
Full Text Available Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking.
Selecting between-sample RNA-Seq normalization methods from the perspective of their assumptions.
Evans, Ciaran; Hardin, Johanna; Stoebel, Daniel M
2017-02-27
RNA-Seq is a widely used method for studying the behavior of genes under different biological conditions. An essential step in an RNA-Seq study is normalization, in which raw data are adjusted to account for factors that prevent direct comparison of expression measures. Errors in normalization can have a significant impact on downstream analysis, such as inflated false positives in differential expression analysis. An underemphasized feature of normalization is the assumptions on which the methods rely and how the validity of these assumptions can have a substantial impact on the performance of the methods. In this article, we explain how assumptions provide the link between raw RNA-Seq read counts and meaningful measures of gene expression. We examine normalization methods from the perspective of their assumptions, as an understanding of methodological assumptions is necessary for choosing methods appropriate for the data at hand. Furthermore, we discuss why normalization methods perform poorly when their assumptions are violated and how this causes problems in subsequent analysis. To analyze a biological experiment, researchers must select a normalization method with assumptions that are met and that produces a meaningful measure of expression for the given experiment. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
The crux of the method: assumptions in ordinary least squares and logistic regression.
Long, Rebecca G
2008-10-01
Logistic regression has increasingly become the tool of choice when analyzing data with a binary dependent variable. While resources relating to the technique are widely available, clear discussions of why logistic regression should be used in place of ordinary least squares regression are difficult to find. The current paper compares and contrasts the assumptions of ordinary least squares with those of logistic regression and explains why logistic regression's looser assumptions make it adept at handling violations of the more important assumptions in ordinary least squares.
Hack, Daniel R.
2005-01-01
Sand-and-gravel (aggregate) resources are a critical component of the Nation's infrastructure, yet aggregate-mining technologies lag far behind those of metalliferous mining and other sectors. Deposit-evaluation and site-characterization methodologies are antiquated, and few serious studies of the potential applications of spatial-data analysis and geostatistics have been published. However, because of commodity usage and the necessary proximity of a mine to end use, aggregate-resource exploration and evaluation differ fundamentally from comparable activities for metalliferous ores. Acceptable practices, therefore, can reflect this cruder scale. The increasing use of computer technologies is colliding with the need for sand-and-gravel mines to modernize and improve their overall efficiency of exploration, mine planning, scheduling, automation, and other operations. The emergence of megaquarries in the 21st century will also be a contributing factor. Preliminary research into the practical applications of exploratory-data analysis (EDA) have been promising. For example, EDA was used to develop a linear-regression equation to forecast freeze-thaw durability from absorption values for Lower Paleozoic carbonate rocks mined for crushed aggregate from quarries in Oklahoma. Applications of EDA within a spatial context, a method of spatial-data analysis, have also been promising, as with the investigation of undeveloped sand-and-gravel resources in the sedimentary deposits of Pleistocene Lake Bonneville, Utah. Formal geostatistical investigations of sand-and-gravel deposits are quite rare, and the primary focus of those studies that have been completed is on the spatial characterization of deposit thickness and its subsequent effect on ore reserves. A thorough investigation of a gravel deposit in an active aggregate-mining area in central Essex, U.K., emphasized the problems inherent in the geostatistical characterization of particle-size-analysis data. Beyond such factors
Energy Technology Data Exchange (ETDEWEB)
Fang, L. [LMP, Ecole Centrale de Pékin, Beihang University, Beijing 100191 (China); Co-Innovation Center for Advanced Aero-Engine, Beihang University, Beijing 100191 (China); Sun, X.Y. [LMP, Ecole Centrale de Pékin, Beihang University, Beijing 100191 (China); Liu, Y.W., E-mail: liuyangwei@126.com [National Key Laboratory of Science and Technology on Aero-Engine Aero-Thermodynamics, School of Energy and Power Engineering, Beihang University, Beijing 100191 (China); Co-Innovation Center for Advanced Aero-Engine, Beihang University, Beijing 100191 (China)
2016-12-09
In order to shed light on understanding the subgrid-scale (SGS) modelling methodology, we analyze and define the concepts of assumption and restriction in the modelling procedure, then show by a generalized derivation that if there are multiple stationary restrictions in a modelling, the corresponding assumption function must satisfy a criterion of orthogonality. Numerical tests using one-dimensional nonlinear advection equation are performed to validate this criterion. This study is expected to inspire future research on generally guiding the SGS modelling methodology. - Highlights: • The concepts of assumption and restriction in the SGS modelling procedure are defined. • A criterion of orthogonality on the assumption and restrictions is derived. • Numerical tests using one-dimensional nonlinear advection equation are performed to validate this criterion.
Who needs the assumption of opportunistic behavior? Transaction cost economics does not!
DEFF Research Database (Denmark)
Koch, Carsten Allan
2000-01-01
The assumption of opportunistic behavior, familiar from transaction cost economics, has been and remains highly controversial. But opportunistic behavior, albeit undoubtedly an extremely important form of motivation, is not a necessary condition for the contractual problems studied by transaction...
2014-01-01
The sinkhole located in Assumption Parish, Louisiana, threatens the stability of Highway 70, a state maintained route. In order to : mitigate the potential damaging e ects of the sinkhole on this infrastructure, the Louisiana Department of Transpo...
Bayou Corne sinkhole : control measurements of State Highway 70 in Assumption Parish, Louisiana.
2014-01-01
This project measured and assessed the surface stability of the portion of LA Highway 70 that is : potentially vulnerable to the Assumption Parish sinkhole. Using Global Positioning Systems (GPS) : enhanced by a real-time network (RTN) of continuousl...
2012-09-01
The sinkhole located in northern Assumption Parish, Louisiana, threatens : the stability of Highway 70, a state-maintained route. In order to monitor : and mitigate potential damage eff ects on this infrastructure, the Louisiana : Department of Trans...
Energy Technology Data Exchange (ETDEWEB)
Babiuch, Bill [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bilello, Daniel E. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Cowlin, Shannon C. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mann, Margaret [National Renewable Energy Lab. (NREL), Golden, CO (United States); Wise, Alison [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2008-08-01
This report describes the methodology and assumptions used by NREL in quantifying the potential CO2 reductions resulting from more than 140 governments, international organizations, and private-sector representatives pledging to advance the uptake of renewable energy.
Ernst, Anja F.; Albers, Casper J.
2017-01-01
Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated
International Nuclear Information System (INIS)
Geier, J.
1993-06-01
This report describes preliminary verification and demonstration of the geostatistical inference code, INFERENS Version 1.1. This code performs regularization of packer test conductivities, and iterative generalized least-squares estimation (IGLSE) of nested covariance models and spatial trends for the regularized data. Cross-validation is used to assess the quality of the estimated models in terms of statistics for the kriging errors. The code includes a capability to generate synthetic datasets for a given configuration of packer tests; this capability can be used for verification exercises and numerical experiments to aid in the design of packer testing programs. The report presents the results of a set of verification test cases. The test cases were designed to test the ability of INFERENS 1.1 to estimate the parameters of a variety of covariance models, with or without trends. This was done using synthetic datasets. This report also describes an application of INFERENS 1.1 to the dataset from the Finnsjoen site. The results are roughly similar to those obtained previously by Norman (1992a) using INFERENS 1.0, for the comparable cases. The actual numerical results are different, which may be due to changes in the fitting algorithms, and differences in how the lag pairs are divided into lag classes. The demonstrations confirm the result previously obtained by Norman, that the fitted horizontally isotropic models are less good, in terms of their cross-validation statistics, than the corresponding isotropic models. The use of nested covariance models is demonstrated to give visually improved fits to the sample semivariograms, at both short and long lag distances. However, despite the good match to the semivariograms, the nested models obtained are not better than the simple models, in terms of cross-validation statistics
Scholte, Ronaldo G C; Schur, Nadine; Bavia, Maria E; Carvalho, Edgar M; Chammartin, Frédérique; Utzinger, Jürg; Vounatsou, Penelope
2013-11-01
Soil-transmitted helminths (Ascaris lumbricoides, Trichuris trichiura and hookworm) negatively impact the health and wellbeing of hundreds of millions of people, particularly in tropical and subtropical countries, including Brazil. Reliable maps of the spatial distribution and estimates of the number of infected people are required for the control and eventual elimination of soil-transmitted helminthiasis. We used advanced Bayesian geostatistical modelling, coupled with geographical information systems and remote sensing to visualize the distribution of the three soil-transmitted helminth species in Brazil. Remotely sensed climatic and environmental data, along with socioeconomic variables from readily available databases were employed as predictors. Our models provided mean prevalence estimates for A. lumbricoides, T. trichiura and hookworm of 15.6%, 10.1% and 2.5%, respectively. By considering infection risk and population numbers at the unit of the municipality, we estimate that 29.7 million Brazilians are infected with A. lumbricoides, 19.2 million with T. trichiura and 4.7 million with hookworm. Our model-based maps identified important risk factors related to the transmission of soiltransmitted helminths and confirm that environmental variables are closely associated with indices of poverty. Our smoothed risk maps, including uncertainty, highlight areas where soil-transmitted helminthiasis control interventions are most urgently required, namely in the North and along most of the coastal areas of Brazil. We believe that our predictive risk maps are useful for disease control managers for prioritising control interventions and for providing a tool for more efficient surveillance-response mechanisms.
Sedda, Luigi; Qi, Qiuyin; Tatem, Andrew J
2015-12-16
The absence of conflict in a country has been cited as a crucial factor affecting the operational feasibility of achieving malaria control and elimination, yet mixed evidence exists on the influence that conflicts have had on malaria transmission. Over the past two decades, Africa has seen substantial numbers of armed conflicts of varying length and scale, creating conditions that can disrupt control efforts and impact malaria transmission. However, very few studies have quantitatively assessed the associations between conflicts and malaria transmission, particularly in a consistent way across multiple countries. In this analysis an explicit geostatistical, autoregressive, mixed model is employed to quantitatively assess the association between conflicts and variations in Plasmodium falciparum parasite prevalence across a 13-year period in sub-Saharan Africa. Analyses of geolocated, malaria prevalence survey variations against armed conflict data in general showed a wide, but short-lived impact of conflict events geographically. The number of countries with decreased P. falciparum parasite prevalence (17) is larger than the number of countries with increased transmission (12), and notably, some of the countries with the highest transmission pre-conflict were still found with lower transmission post-conflict. For four countries, there were no significant changes in parasite prevalence. Finally, distance from conflicts, duration of conflicts, violence of conflict, and number of conflicts were significant components in the model explaining the changes in P. falciparum parasite rate. The results suggest that the maintenance of intervention coverage and provision of healthcare in conflict situations to protect vulnerable populations can maintain gains in even the most difficult of circumstances, and that conflict does not represent a substantial barrier to elimination goals.
Yin, Gaohong
2016-05-01
Since the failure of the Scan Line Corrector (SLC) instrument on Landsat 7, observable gaps occur in the acquired Landsat 7 imagery, impacting the spatial continuity of observed imagery. Due to the highly geometric and radiometric accuracy provided by Landsat 7, a number of approaches have been proposed to fill the gaps. However, all proposed approaches have evident constraints for universal application. The main issues in gap-filling are an inability to describe the continuity features such as meandering streams or roads, or maintaining the shape of small objects when filling gaps in heterogeneous areas. The aim of the study is to validate the feasibility of using the Direct Sampling multiple-point geostatistical method, which has been shown to reconstruct complicated geological structures satisfactorily, to fill Landsat 7 gaps. The Direct Sampling method uses a conditional stochastic resampling of known locations within a target image to fill gaps and can generate multiple reconstructions for one simulation case. The Direct Sampling method was examined across a range of land cover types including deserts, sparse rural areas, dense farmlands, urban areas, braided rivers and coastal areas to demonstrate its capacity to recover gaps accurately for various land cover types. The prediction accuracy of the Direct Sampling method was also compared with other gap-filling approaches, which have been previously demonstrated to offer satisfactory results, under both homogeneous area and heterogeneous area situations. Studies have shown that the Direct Sampling method provides sufficiently accurate prediction results for a variety of land cover types from homogeneous areas to heterogeneous land cover types. Likewise, it exhibits superior performances when used to fill gaps in heterogeneous land cover types without input image or with an input image that is temporally far from the target image in comparison with other gap-filling approaches.
Obida, Christopher B; Alan Blackburn, G; Duncan Whyatt, J; Semple, Kirk T
2018-02-01
The Niger Delta is one of the largest oil producing regions of the world. Large numbers and volumes of oil spills have been reported in this region. What has not been quantified is the putative exposure of humans and/or the environment to this hydrocarbon pollution. In this novel study, advanced geostatistical techniques were applied to an extensive database of oil spill incidents from 2007 to 2015. The aims were to (i) identify and analyse spill hotspots along the oil pipeline network and (ii) estimate the exposure of the hydrocarbon pollution to the human population and the environment within the Niger Delta. Over the study period almost 90millionlitres of oil were released. Approximately 29% of the human population living in proximity to the pipeline network has been potentially exposed to oil contamination, of which 565,000 people live within high or very high spill intensity sectors. Over 1000km 2 of land has been contaminated by oil pollution, with broadleaved forest, mangroves and agricultural land the most heavily impacted land cover types. Proximity to the coast, roads and cities are the strongest spatial factors contributing to spill occurrence, which largely determine the accessibility of sites for pipeline sabotage and oil theft. Overall, the findings demonstrate the high levels of environmental and human exposure to hydrocarbon pollutants in the Niger Delta. These results provide evidence with which to spatially target interventions to reduce future spill incidents and mitigate the impacts of previous spills on human communities and ecosystem health. Copyright © 2017 Elsevier Ltd. All rights reserved.
Cronin, S. P.; Trainor Guitton, W.; Team, P.; Pare, A.; Jreij, S.; Powers, H.
2017-12-01
In March 2016, a 4-week field data acquisition took place at Brady's Natural Lab (BNL), an enhanced geothermal system (EGS) in Fallan, NV. During these 4 weeks, a vibe truck executed 6,633 sweeps, recorded by nodal seismometers, horizontal distributed acoustic sensing (DAS) cable, and 400 meters of vertical DAS cable. DAS provides lower signal to noise ratio than traditional geophones but better spatial resolution. The analysis of DAS VSP included Fourier transform, and filtering to remove all up-going energy. Thus, allowing for accurate first arrival picking. We present an example of the Gradual Deformation Method (GDM) using DAS VSP and lithological data to produce a distribution of valid velocity models of BNL. GDM generates continuous perturbations of prior model realizations seeking the best match to the data (i.e. minimize the misfit). Prior model realizations honoring the lithological data were created using sequential Gaussian simulation, a commonly used noniterative geostatistical method. Unlike least-squares-based methods of inversion, GDM readily incorporates a priori information, such as a variogram calculated from well-based lithology information. Additionally, by producing a distribution of models, as opposed to one optimal model, GDM allows for uncertainty quantification. This project aims at assessing the integrated technologies ability to monitor changes in the water table (possibly to one meter resolution) by exploiting the dependence of seismic wave velocities on water saturation of the subsurface. This project, which was funded in part by the National Science Foundation, is a part of the PoroTomo project, funded by a grant from the U.S. Department of Energy.
Xiaopeng, Q I; Liang, Wei; Barker, Laurie; Lekiachvili, Akaki; Xingyou, Zhang
Temperature changes are known to have significant impacts on human health. Accurate estimates of population-weighted average monthly air temperature for US counties are needed to evaluate temperature's association with health behaviours and disease, which are sampled or reported at the county level and measured on a monthly-or 30-day-basis. Most reported temperature estimates were calculated using ArcGIS, relatively few used SAS. We compared the performance of geostatistical models to estimate population-weighted average temperature in each month for counties in 48 states using ArcGIS v9.3 and SAS v 9.2 on a CITGO platform. Monthly average temperature for Jan-Dec 2007 and elevation from 5435 weather stations were used to estimate the temperature at county population centroids. County estimates were produced with elevation as a covariate. Performance of models was assessed by comparing adjusted R 2 , mean squared error, root mean squared error, and processing time. Prediction accuracy for split validation was above 90% for 11 months in ArcGIS and all 12 months in SAS. Cokriging in SAS achieved higher prediction accuracy and lower estimation bias as compared to cokriging in ArcGIS. County-level estimates produced by both packages were positively correlated (adjusted R 2 range=0.95 to 0.99); accuracy and precision improved with elevation as a covariate. Both methods from ArcGIS and SAS are reliable for U.S. county-level temperature estimates; However, ArcGIS's merits in spatial data pre-processing and processing time may be important considerations for software selection, especially for multi-year or multi-state projects.
International Nuclear Information System (INIS)
Yeşilkanat, Cafer Mert; Kobya, Yaşar; Taşkin, Halim; Çevik, Uğur
2015-01-01
In this study, compliance of geostatistical estimation methods is compared to ensure investigation and imaging natural Fon radiation using the minimum number of data. Artvin province, which has a quite hilly terrain and wide variety of soil and located in the north–east of Turkey, is selected as the study area. Outdoor gamma dose rate (OGDR), which is an important determinant of environmental radioactivity level, is measured in 204 stations. Spatial structure of OGDR is determined by anisotropic, isotropic and residual variograms. Ordinary kriging (OK) and universal kriging (UK) interpolation estimations were calculated with the help of model parameters obtained from these variograms. In OK, although calculations are made based on positions of points where samples are taken, in the UK technique, general soil groups and altitude values directly affecting OGDR are included in the calculations. When two methods are evaluated based on their performances, it has been determined that UK model (r = 0.88, p < 0.001) gives quite better results than OK model (r = 0.64, p < 0.001). In addition, as a result of the maps created at the end of the study, it was illustrated that local changes are better reflected by UK method compared to OK method and its error variance is found to be lower. - Highlights: • The spatial dispersion of gamma dose rates in Artvin, which possesses one of the roughest lands in Turkey were studied. • The performance of different Geostatistic methods (OK and UK methods) for dispersion of gamma dose rates were compared. • Estimation values were calculated for non-sampling points by using the geostatistical model, the results were mapped. • The general radiological structure was determined in much less time with lower costs compared to experimental methods. • When theoretical methods are evaluated, it was obtained that UK gives more descriptive results compared to OK.
International Nuclear Information System (INIS)
Andrews, R.W.; LaVenue, A.M.; McNeish, J.A.
1989-01-01
Ground-water travel time predictions at potential high-level waste repositories are subject to a degree of uncertainty due to the scale of averaging incorporated in conceptual models of the ground-water flow regime as well as the lack of data on the spatial variability of the hydrogeologic parameters. The present study describes the effect of limited observations of a spatially correlated permeability field on the predicted ground-water travel time uncertainty. Varying permeability correlation lengths have been used to investigate the importance of this geostatistical property on the tails of the travel time distribution. This study uses both geostatistical and differential analysis techniques. Following the generation of a spatially correlated permeability field which is considered reality, semivariogram analyses are performed upon small random subsets of the generated field to determine the geostatistical properties of the field represented by the observations. Kriging is then employed to generate a kriged permeability field and the corresponding standard deviation of the estimated field conditioned by the limited observations. Using both the real and kriged fields, the ground-water flow regime is simulated and ground-water travel paths and travel times are determined for various starting points. These results are used to define the ground-water travel time uncertainty due to path variability. The variance of the ground-water travel time along particular paths due to the variance of the permeability field estimated using kriging is then calculated using the first order, second moment method. The uncertainties in predicted travel time due to path and parameter uncertainties are then combined into a single distribution
Shattering Man’s Fundamental Assumptions in Don DeLillo’s Falling Man
Hazim Adnan Hashim; Rosli Bin Talif; Lina Hameed Ali
2016-01-01
The present study addresses effects of traumatic events such as the September 11 attacks on victims’ fundamental assumptions. These beliefs or assumptions provide individuals with expectations about the world and their sense of self-worth. Thus, they ground people’s sense of security, stability, and orientation. The September 11 terrorist attacks in the U.S.A. were very tragic for Americans because this fundamentally changed their understandings about many aspects in life. The attacks led man...
Testing the rationality assumption using a design difference in the TV game show 'Jeopardy'
Sjögren Lindquist, Gabriella; Säve-Söderbergh, Jenny
2006-01-01
Abstract This paper empirically investigates the rationality assumption commonly applied in economic modeling by exploiting a design difference in the game-show Jeopardy between the US and Sweden. In particular we address the assumption of individuals’ capabilities to process complex mathematical problems to find optimal strategies. The vital difference is that US contestants are given explicit information before they act, while Swedish contestants individually need to calculate the same info...
van Huizen, T.M.
2012-01-01
The aim of this dissertation is to test behavioural assumptions in labour economics models and thereby improve our understanding of labour market behaviour. The assumptions under scrutiny in this study are derived from an analysis of recent influential policy proposals: the introduction of savings schemes in the system of social security. A central question is how this reform will affect labour market incentives and behaviour. Part I (Chapter 2 and 3) evaluates savings schemes. Chapter 2 exam...
Mesa-Frias, Marco; Chalabi, Zaid; Foss, Anna M
2013-09-01
Health impact assessment (HIA) is often used to determine ex ante the health impact of an environmental policy or an environmental intervention. Underpinning any HIA is the framing assumption, which defines the causal pathways mapping environmental exposures to health outcomes. The sensitivity of the HIA to the framing assumptions is often ignored. A novel method based on fuzzy cognitive map (FCM) is developed to quantify the framing assumptions in the assessment stage of a HIA, and is then applied to a housing intervention (tightening insulation) as a case-study. Framing assumptions of the case-study were identified through a literature search of Ovid Medline (1948-2011). The FCM approach was used to identify the key variables that have the most influence in a HIA. Changes in air-tightness, ventilation, indoor air quality and mould/humidity have been identified as having the most influence on health. The FCM approach is widely applicable and can be used to inform the formulation of the framing assumptions in any quantitative HIA of environmental interventions. We argue that it is necessary to explore and quantify framing assumptions prior to conducting a detailed quantitative HIA during the assessment stage. Copyright © 2013 Elsevier Ltd. All rights reserved.
Unrealistic Assumptions in Economics: an Analysis under the Logic of Socioeconomic Processes
Directory of Open Access Journals (Sweden)
Leonardo Ivarola
2014-11-01
Full Text Available The realism of assumptions is an ongoing debate within the philosophy of economics. One of the most referenced papers in this matter belongs to Milton Friedman. He defends the use of unrealistic assumptions, not only because of a pragmatic issue, but also the intrinsic difficulties of determining the extent of realism. On the other hand, realists have criticized (and still do today the use of unrealistic assumptions - such as the assumption of rational choice, perfect information, homogeneous goods, etc. However, they did not accompany their statements with a proper epistemological argument that supports their positions. In this work it is expected to show that the realism of (a particular sort of assumptions is clearly relevant when examining economic models, since the system under study (the real economies is not compatible with logic of invariance and of mechanisms, but with the logic of possibility trees. Because of this, models will not function as tools for predicting outcomes, but as representations of alternative scenarios, whose similarity to the real world will be examined in terms of the verisimilitude of a class of model assumptions
Shattering Man’s Fundamental Assumptions in Don DeLillo’s Falling Man
Directory of Open Access Journals (Sweden)
Hazim Adnan Hashim
2016-09-01
Full Text Available The present study addresses effects of traumatic events such as the September 11 attacks on victims’ fundamental assumptions. These beliefs or assumptions provide individuals with expectations about the world and their sense of self-worth. Thus, they ground people’s sense of security, stability, and orientation. The September 11 terrorist attacks in the U.S.A. were very tragic for Americans because this fundamentally changed their understandings about many aspects in life. The attacks led many individuals to build new kind of beliefs and assumptions about themselves and the world. Many writers have written about the human ordeals that followed this incident. Don DeLillo’s Falling Man reflects the traumatic repercussions of this disaster on Americans’ fundamental assumptions. The objective of this study is to examine the novel from the traumatic perspective that has afflicted the victims’ fundamental understandings of the world and the self. Individuals’ fundamental understandings could be changed or modified due to exposure to certain types of events like war, terrorism, political violence or even the sense of alienation. The Assumptive World theory of Ronnie Janoff-Bulman will be used as a framework to study the traumatic experience of the characters in Falling Man. The significance of the study lies in providing a new perception to the field of trauma that can help trauma victims to adopt alternative assumptions or reshape their previous ones to heal from traumatic effects.
International Nuclear Information System (INIS)
Post, C.
2001-01-01
The remediation of the former Wismut mines in Thuringia has been planed and prepared since 1990. Objects of remediation are mines, tailing ponds and waste rock piles. Since more than 40 years of mining have had a great affect on the exploited aquifer, special emphasis is given to groundwater recharge so that minery-flooding is one of the conceivable remedial options. Controlled flooding supports minimising the expanded oxidation zone, which renders an immense pollutant potential, while at the same time the flooding reduces the quantity of acid mine water, that has to be treated. One of the main tasks of modelling the flooding progress is to determine and prognosticate the wateroutlet-places. Due to the inadequacy of the database from the production period, limited accuracy of the available data and because of the inherent uncertainty of approximations used in numerical modelling, a stochastic approach is prospected. The flooding predictions, i.e. modelling of hydrodynamical and hydrochemical conditions during and after completion of flooding predominantly depend on the spatial distribution of the hydraulic conductivity. In order to get a better understanding of the spatial heterogeneity of the Palaeozoic fractured rock aquifer, certain geostatistical interpolation methods are tested to achieve the best approach for describing the hydrogeological parameters in space. This work deals in detail with two selected geostatistical interpolation methods (ordinary and indicator kriging) and discusses their applicability and limitations including the application of the presented case. Another important target is the specification of the database and the improvement of consistency with statistical standards. The main emphasis lies on the spatial distribution of the measured hydraulic conductivity coefficient, its estimation at non-measured places and the influence of its spatial variability on modelling results. This topic is followed by the calculation of the estimation
Geostatistical mapping of leakance in a regional aquitard, Oak Ridges Moraine area, Ontario, Canada
Desbarats, A. J.; Hinton, M. J.; Logan, C. E.; Sharpe, D. R.
2001-01-01
The Newmarket Till forms a regionally extensive aquitard separating two major aquifer systems in the Greater Toronto area, Canada. The till is incised, and sometimes eroded entirely, by a network of sand- and gravel-filled channels forming productive aquifers and, locally, high-conductivity windows between aquifer systems. Leakage through the till may also be substantial in places. This study investigates the spatial variability of aquitard leakance in order to assess the relative importance of recharge processes to the lower aquifers. With a large database derived from water-well records and containing both hard and soft information, the Sequential Indicator Simulation method is used to generate maps of aquitard thickness and window probability. These can be used for targeting channel aquifers and for identifying potential areas of recharge to the lower aquifers. Conductivities are modeled from sparse data assuming that their correlation range is much smaller than the grid spacing. Block-scale leakances are obtained by upscaling nodal values based on simulated conductivity and thickness fields. Under the "aquifer-flow'' assumption, upscaling is performed by arithmetic spatial averaging. Histograms and maps of upscaled leakances show that heterogeneities associated with aquitard windows have the largest effect on regional groundwater flow patterns. Résumé. La moraine glaciaire de Newmarket constitue un imperméable d'extension régionale séparant deux systèmes aquifères dans la région du Grand Toronto (Canada). La moraine est entaillée, et parfois entièrement érodée, par un réseau de chenaux comblés de sables et de graviers formant des aquifères productifs et, localement, des «fenêtres», zones à forte conductivité hydraulique reliant les systèmes aquifères. Une drainance au travers de la moraine peut également être significative par endroits. Cette étude s'intéresse à la variabilité spatiale de la drainance au travers de l
Impacts of cloud overlap assumptions on radiative budgets and heating fields in convective regions
Wang, XiaoCong; Liu, YiMin; Bao, Qing
2016-01-01
Impacts of cloud overlap assumptions on radiative budgets and heating fields are explored with the aid of a cloud-resolving model (CRM), which provided cloud geometry as well as cloud micro and macro properties. Large-scale forcing data to drive the CRM are from TRMM Kwajalein Experiment and the Global Atmospheric Research Program's Atlantic Tropical Experiment field campaigns during which abundant convective systems were observed. The investigated overlap assumptions include those that were traditional and widely used in the past and the one that was recently addressed by Hogan and Illingworth (2000), in which the vertically projected cloud fraction is expressed by a linear combination of maximum and random overlap, with the weighting coefficient depending on the so-called decorrelation length Lcf. Results show that both shortwave and longwave cloud radiative forcings (SWCF/LWCF) are significantly underestimated under maximum (MO) and maximum-random (MRO) overlap assumptions, whereas remarkably overestimated under the random overlap (RO) assumption in comparison with that using CRM inherent cloud geometry. These biases can reach as high as 100 Wm- 2 for SWCF and 60 Wm- 2 for LWCF. By its very nature, the general overlap (GenO) assumption exhibits an encouraging performance on both SWCF and LWCF simulations, with the biases almost reduced by 3-fold compared with traditional overlap assumptions. The superiority of GenO assumption is also manifested in the simulation of shortwave and longwave radiative heating fields, which are either significantly overestimated or underestimated under traditional overlap assumptions. The study also pointed out the deficiency of constant assumption on Lcf in GenO assumption. Further examinations indicate that the CRM diagnostic Lcf varies among different cloud types and tends to be stratified in the vertical. The new parameterization that takes into account variation of Lcf in the vertical well reproduces such a relationship and
Contemporary assumptions on human nature and work and approach to human potential managing
Directory of Open Access Journals (Sweden)
Vujić Dobrila
2006-01-01
Full Text Available A general problem of this research is to identify if there is a relationship between the assumption on human nature and work (Mcgregor, Argyris, Schein, Steers and Porter and a general organizational model preference, as well as a mechanism of human resource management? This research was carried out in 2005/2006. The sample consisted of 317 subjects (197 managers, 105 highly educated subordinates and 15 entrepreneurs in 7 big enterprises in a group of small business enterprises differentiating in terms of the entrepreneur’s structure and a type of activity. A general hypothesis "that assumptions on human nature and work are statistically significant in connection to the preference approach (models, of work motivation commitment", has been confirmed. A specific hypothesis have been also confirmed: ·The assumptions on a human as a rational economic being are statistically significant in correlation with only two mechanisms of traditional models, the mechanism of method work control and the working discipline mechanism. ·Statistically significant assumptions on a human as a social being are correlated with all mechanisms of engaging employees, which belong to the model of the human relations, except the mechanism introducing the adequate type of prizes for all employees independently of working results. ·The assumptions on a human as a creative being are statistically significant, positively correlating with preference of two mechanisms belonging to the human resource model by investing into education and training and making conditions for the application of knowledge and skills. The young with assumptions on a human as a creative being prefer much broader repertoire of mechanisms belonging to the human resources model from the remaining category of subjects in the pattern. The connection between the assumption on human nature and preference models of engaging appears especially in the sub-pattern of managers, in the category of young subjects
Koopmeiners, Joseph S; Hobbs, Brian P
2018-05-01
Randomized, placebo-controlled clinical trials are the gold standard for evaluating a novel therapeutic agent. In some instances, it may not be considered ethical or desirable to complete a placebo-controlled clinical trial and, instead, the placebo is replaced by an active comparator with the objective of showing either superiority or non-inferiority to the active comparator. In a non-inferiority trial, the experimental treatment is considered non-inferior if it retains a pre-specified proportion of the effect of the active comparator as represented by the non-inferiority margin. A key assumption required for valid inference in the non-inferiority setting is the constancy assumption, which requires that the effect of the active comparator in the non-inferiority trial is consistent with the effect that was observed in previous trials. It has been shown that violations of the constancy assumption can result in a dramatic increase in the rate of incorrectly concluding non-inferiority in the presence of ineffective or even harmful treatment. In this paper, we illustrate how Bayesian hierarchical modeling can be used to facilitate multi-source smoothing of the data from the current trial with the data from historical studies, enabling direct probabilistic evaluation of the constancy assumption. We then show how this result can be used to adapt the non-inferiority margin when the constancy assumption is violated and present simulation results illustrating that our method controls the type-I error rate when the constancy assumption is violated, while retaining the power of the standard approach when the constancy assumption holds. We illustrate our adaptive procedure using a non-inferiority trial of raltegravir, an antiretroviral drug for the treatment of HIV.
Geospatial measurements of ancillary sensor data, such as bulk soil electrical conductivity or remotely sensed imagery data, are commonly used to characterize spatial variation in soil or crop properties. Geostatistical techniques like kriging with external drift or regression kriging are often use...
Linde, Klaus; Rücker, Gerta; Schneider, Antonius; Kriston, Levente
2016-03-01
We aimed to evaluate the underlying assumptions of a network meta-analysis investigating which depression treatment works best in primary care and to highlight challenges and pitfalls of interpretation under consideration of these assumptions. We reviewed 100 randomized trials investigating pharmacologic and psychological treatments for primary care patients with depression. Network meta-analysis was carried out within a frequentist framework using response to treatment as outcome measure. Transitivity was assessed by epidemiologic judgment based on theoretical and empirical investigation of the distribution of trial characteristics across comparisons. Homogeneity and consistency were investigated by decomposing the Q statistic. There were important clinical and statistically significant differences between "pure" drug trials comparing pharmacologic substances with each other or placebo (63 trials) and trials including a psychological treatment arm (37 trials). Overall network meta-analysis produced results well comparable with separate meta-analyses of drug trials and psychological trials. Although the homogeneity and consistency assumptions were mostly met, we considered the transitivity assumption unjustifiable. An exchange of experience between reviewers and, if possible, some guidance on how reviewers addressing important clinical questions can proceed in situations where important assumptions for valid network meta-analysis are not met would be desirable. Copyright © 2016 Elsevier Inc. All rights reserved.
2012-01-01
Background Changes in world assumptions are a fundamental concept within theories that explain posttraumatic stress disorder. The objective of the present study was to gain a greater understanding of how changes in world assumptions are related to quality of life and posttraumatic stress symptoms after a natural disaster. Methods A longitudinal study of 574 Norwegian adults who survived the Southeast Asian tsunami in 2004 was undertaken. Multilevel analyses were used to identify which factors at six months post-tsunami predicted quality of life and posttraumatic stress symptoms two years post-tsunami. Results Good quality of life and posttraumatic stress symptoms were negatively related. However, major differences in the predictors of these outcomes were found. Females reported significantly higher quality of life and more posttraumatic stress than men. The association between level of exposure to the tsunami and quality of life seemed to be mediated by posttraumatic stress. Negative perceived changes in the assumption “the world is just” were related to adverse outcome in both quality of life and posttraumatic stress. Positive perceived changes in the assumptions “life is meaningful” and “feeling that I am a valuable human” were associated with higher levels of quality of life but not with posttraumatic stress. Conclusions Quality of life and posttraumatic stress symptoms demonstrate differences in their etiology. World assumptions may be less specifically related to posttraumatic stress than has been postulated in some cognitive theories. PMID:22742447
Manzione, Rodrigo L.; Wendland, Edson; Tanikawa, Diego H.
2012-11-01
Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.
Takodjou Wambo, Jonas Didero; Ganno, Sylvestre; Djonthu Lahe, Yannick Sthopira; Kouankap Nono, Gus Djibril; Fossi, Donald Hermann; Tchouatcha, Milan Stafford; Nzenti, Jean Paul
2018-06-01
Linear and nonlinear geostatistic is commonly used in ore grade estimation and seldom used in Geographical Information System (GIS) technology. In this study, we suggest an approach based on geostatistic linear ordinary kriging (OK) and Geographical Information System (GIS) techniques to investigate the spatial distribution of alluvial gold content, mineralized and gangue layers thicknesses from 73 pits at the Ngoura-Colomines area with the aim to determine controlling factors for the spatial distribution of mineralization and delineate the most prospective area for primary gold mineralization. Gold content varies between 0.1 and 4.6 g/m3 and has been broadly grouped into three statistical classes. These classes have been spatially subdivided into nine zones using ordinary kriging model based on physical and topographical characteristics. Both mineralized and barren layer thicknesses show randomly spatial distribution, and there is no correlation between these parameters and the gold content. This approach has shown that the Ngoura-Colomines area is located in a large shear zone compatible with the Riedel fault system composed of P and P‧ fractures oriented NE-SW and NNE-SSW respectively; E-W trending R fractures and R‧ fractures with NW-SE trends that could have contributed significantly to the establishment of this gold mineralization. The combined OK model and GIS analysis have led to the delineation of Colomines, Tissongo, Madubal and Boutou villages as the most prospective areas for the exploration of primary gold deposit in the study area.
Liu, Geng; Niu, Junjie; Zhang, Chao; Guo, Guanlin
2015-12-01
Data distribution is usually skewed severely by the presence of hot spots in contaminated sites. This causes difficulties for accurate geostatistical data transformation. Three types of typical normal distribution transformation methods termed the normal score, Johnson, and Box-Cox transformations were applied to compare the effects of spatial interpolation with normal distribution transformation data of benzo(b)fluoranthene in a large-scale coking plant-contaminated site in north China. Three normal transformation methods decreased the skewness and kurtosis of the benzo(b)fluoranthene, and all the transformed data passed the Kolmogorov-Smirnov test threshold. Cross validation showed that Johnson ordinary kriging has a minimum root-mean-square error of 1.17 and a mean error of 0.19, which was more accurate than the other two models. The area with fewer sampling points and that with high levels of contamination showed the largest prediction standard errors based on the Johnson ordinary kriging prediction map. We introduce an ideal normal transformation method prior to geostatistical estimation for severely skewed data, which enhances the reliability of risk estimation and improves the accuracy for determination of remediation boundaries.
Garcia, A G; Araujo, M R; Uramoto, K; Walder, J M M; Zucchi, R A
2017-12-08
Fruit flies are among the most damaging insect pests of commercial fruit in Brazil. It is important to understand the landscape elements that may favor these flies. In the present study, spatial data from surveys of species of Anastrepha Schiner (Diptera: Tephritidae) in an urban area with forest fragments were analyzed, using geostatistics and Geographic Information System (GIS) to map the diversity of insects and evaluate how the forest fragments drive the spatial patterns. The results indicated a high diversity of species associated with large fragments, and a trend toward lower diversity in the more urbanized area, as the fragment sizes decreased. We concluded that the diversity of Anastrepha species is directly and positively related to large and continuous forest fragments in urbanized areas, and that combining geostatistics and GIS is a promising method for use in insect-pest management and sampling involving fruit flies. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.