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Sample records for maximum success probability

Probable maximum flood control

International Nuclear Information System (INIS)

DeGabriele, C.E.; Wu, C.L.

1991-11-01

This study proposes preliminary design concepts to protect the waste-handling facilities and all shaft and ramp entries to the underground from the probable maximum flood (PMF) in the current design configuration for the proposed Nevada Nuclear Waste Storage Investigation (NNWSI) repository protection provisions were furnished by the United States Bureau of Reclamation (USSR) or developed from USSR data. Proposed flood protection provisions include site grading, drainage channels, and diversion dikes. Figures are provided to show these proposed flood protection provisions at each area investigated. These areas are the central surface facilities (including the waste-handling building and waste treatment building), tuff ramp portal, waste ramp portal, men-and-materials shaft, emplacement exhaust shaft, and exploratory shafts facility
Effects of variability in probable maximum precipitation patterns on flood losses

Science.gov (United States)

Zischg, Andreas Paul; Felder, Guido; Weingartner, Rolf; Quinn, Niall; Coxon, Gemma; Neal, Jeffrey; Freer, Jim; Bates, Paul

2018-05-01

The assessment of the impacts of extreme floods is important for dealing with residual risk, particularly for critical infrastructure management and for insurance purposes. Thus, modelling of the probable maximum flood (PMF) from probable maximum precipitation (PMP) by coupling hydrological and hydraulic models has gained interest in recent years. Herein, we examine whether variability in precipitation patterns exceeds or is below selected uncertainty factors in flood loss estimation and if the flood losses within a river basin are related to the probable maximum discharge at the basin outlet. We developed a model experiment with an ensemble of probable maximum precipitation scenarios created by Monte Carlo simulations. For each rainfall pattern, we computed the flood losses with a model chain and benchmarked the effects of variability in rainfall distribution with other model uncertainties. The results show that flood losses vary considerably within the river basin and depend on the timing and superimposition of the flood peaks from the basin's sub-catchments. In addition to the flood hazard component, the other components of flood risk, exposure, and vulnerability contribute remarkably to the overall variability. This leads to the conclusion that the estimation of the probable maximum expectable flood losses in a river basin should not be based exclusively on the PMF. Consequently, the basin-specific sensitivities to different precipitation patterns and the spatial organization of the settlements within the river basin need to be considered in the analyses of probable maximum flood losses.
Maximum Entropy and Probability Kinematics Constrained by Conditionals

Directory of Open Access Journals (Sweden)

Stefan Lukits

2015-03-01

Full Text Available Two open questions of inductive reasoning are solved: (1 does the principle of maximum entropy (PME give a solution to the obverse Majerník problem; and (2 isWagner correct when he claims that Jeffrey’s updating principle (JUP contradicts PME? Majerník shows that PME provides unique and plausible marginal probabilities, given conditional probabilities. The obverse problem posed here is whether PME also provides such conditional probabilities, given certain marginal probabilities. The theorem developed to solve the obverse Majerník problem demonstrates that in the special case introduced by Wagner PME does not contradict JUP, but elegantly generalizes it and offers a more integrated approach to probability updating.
Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models.

Directory of Open Access Journals (Sweden)

Richard R Stein

2015-07-01

Full Text Available Maximum entropy-based inference methods have been successfully used to infer direct interactions from biological datasets such as gene expression data or sequence ensembles. Here, we review undirected pairwise maximum-entropy probability models in two categories of data types, those with continuous and categorical random variables. As a concrete example, we present recently developed inference methods from the field of protein contact prediction and show that a basic set of assumptions leads to similar solution strategies for inferring the model parameters in both variable types. These parameters reflect interactive couplings between observables, which can be used to predict global properties of the biological system. Such methods are applicable to the important problems of protein 3-D structure prediction and association of gene-gene networks, and they enable potential applications to the analysis of gene alteration patterns and to protein design.
Maximum parsimony, substitution model, and probability phylogenetic trees.

Science.gov (United States)

Weng, J F; Thomas, D A; Mareels, I

2011-01-01

The problem of inferring phylogenies (phylogenetic trees) is one of the main problems in computational biology. There are three main methods for inferring phylogenies-Maximum Parsimony (MP), Distance Matrix (DM) and Maximum Likelihood (ML), of which the MP method is the most well-studied and popular method. In the MP method the optimization criterion is the number of substitutions of the nucleotides computed by the differences in the investigated nucleotide sequences. However, the MP method is often criticized as it only counts the substitutions observable at the current time and all the unobservable substitutions that really occur in the evolutionary history are omitted. In order to take into account the unobservable substitutions, some substitution models have been established and they are now widely used in the DM and ML methods but these substitution models cannot be used within the classical MP method. Recently the authors proposed a probability representation model for phylogenetic trees and the reconstructed trees in this model are called probability phylogenetic trees. One of the advantages of the probability representation model is that it can include a substitution model to infer phylogenetic trees based on the MP principle. In this paper we explain how to use a substitution model in the reconstruction of probability phylogenetic trees and show the advantage of this approach with examples.
PROBABILITY CALIBRATION BY THE MINIMUM AND MAXIMUM PROBABILITY SCORES IN ONE-CLASS BAYES LEARNING FOR ANOMALY DETECTION

Data.gov (United States)

National Aeronautics and Space Administration — PROBABILITY CALIBRATION BY THE MINIMUM AND MAXIMUM PROBABILITY SCORES IN ONE-CLASS BAYES LEARNING FOR ANOMALY DETECTION GUICHONG LI, NATHALIE JAPKOWICZ, IAN HOFFMAN,...
The maximum entropy method of moments and Bayesian probability theory

Science.gov (United States)

Bretthorst, G. Larry

2013-08-01

The problem of density estimation occurs in many disciplines. For example, in MRI it is often necessary to classify the types of tissues in an image. To perform this classification one must first identify the characteristics of the tissues to be classified. These characteristics might be the intensity of a T1 weighted image and in MRI many other types of characteristic weightings (classifiers) may be generated. In a given tissue type there is no single intensity that characterizes the tissue, rather there is a distribution of intensities. Often this distributions can be characterized by a Gaussian, but just as often it is much more complicated. Either way, estimating the distribution of intensities is an inference problem. In the case of a Gaussian distribution, one must estimate the mean and standard deviation. However, in the Non-Gaussian case the shape of the density function itself must be inferred. Three common techniques for estimating density functions are binned histograms [1, 2], kernel density estimation [3, 4], and the maximum entropy method of moments [5, 6]. In the introduction, the maximum entropy method of moments will be reviewed. Some of its problems and conditions under which it fails will be discussed. Then in later sections, the functional form of the maximum entropy method of moments probability distribution will be incorporated into Bayesian probability theory. It will be shown that Bayesian probability theory solves all of the problems with the maximum entropy method of moments. One gets posterior probabilities for the Lagrange multipliers, and, finally, one can put error bars on the resulting estimated density function.
Unification of field theory and maximum entropy methods for learning probability densities

OpenAIRE

Kinney, Justin B.

2014-01-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy de...
Some uses of predictive probability of success in clinical drug development

Directory of Open Access Journals (Sweden)

Mauro Gasparini

2013-03-01

Full Text Available Predictive probability of success is a (subjective Bayesian evaluation of the prob- ability of a future successful event in a given state of information. In the context of pharmaceutical clinical drug development, successful events relate to the accrual of positive evidence on the therapy which is being developed, like demonstration of su- perior efficacy or ascertainment of safety. Positive evidence will usually be obtained via standard frequentist tools, according to the regulations imposed in the world of pharmaceutical development.Within a single trial, predictive probability of success can be identified with expected power, i.e. the evaluation of the success probability of the trial. Success means, for example, obtaining a significant result of a standard superiority test.Across trials, predictive probability of success can be the probability of a successful completion of an entire part of clinical development, for example a successful phase III development in the presence of phase II data.Calculations of predictive probability of success in the presence of normal data with known variance will be illustrated, both for within-trial and across-trial predictions.
Probabilistic Cloning of Three Real States with Optimal Success Probabilities

Science.gov (United States)

Rui, Pin-shu

2017-06-01

We investigate the probabilistic quantum cloning (PQC) of three real states with average probability distribution. To get the analytic forms of the optimal success probabilities we assume that the three states have only two pairwise inner products. Based on the optimal success probabilities, we derive the explicit form of 1 →2 PQC for cloning three real states. The unitary operation needed in the PQC process is worked out too. The optimal success probabilities are also generalized to the M→ N PQC case.
Unification of field theory and maximum entropy methods for learning probability densities

Science.gov (United States)

Kinney, Justin B.

2015-09-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.
Unification of field theory and maximum entropy methods for learning probability densities.

Science.gov (United States)

Kinney, Justin B

2015-09-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.
Probable maximum flood on the Ha Ha River

International Nuclear Information System (INIS)

Damov, D.; Masse, B.

1997-01-01

Results of a probable maximum flood (PMF) study conducted for various locations along the Ha Ha river, a tributary of the Saguenay River, were discussed. The study was undertaken for use in the design and construction of new hydraulic structures for water supply for a pulp and paper facility, following the Saguenay Flood in July 1996. Many different flood scenarios were considered, including combinations of snow-melt with rainfall. Using computer simulations, it was shown that the largest flood flows were generated by summer-fall PMF. 5 refs., 12 figs
Review of probable maximum flood definition at B.C. Hydro

International Nuclear Information System (INIS)

Keenhan, P.T.; Kroeker, M.G.; Neudorf, P.A.

1991-01-01

Probable maximum floods (PMF) have been derived for British Columbia Hydro structures since design of the W.C. Bennet Dam in 1965. A dam safety program for estimating PMF for structures designed before that time has been ongoing since 1979. The program, which has resulted in rehabilitative measures at dams not meeting current established standards, is now being directed at the more recently constructed larger structures on the Peace and Columbia rivers. Since 1965 detailed studies have produced 23 probable maximum precipitation (PMP) and 24 PMF estimates. What defines a PMF in British Columbia in terms of an appropriate combination of meteorological conditions varies due to basin size and the climatic effect of mountain barriers. PMP is estimated using three methods: storm maximization and transposition, orographic separation method, and modification of non-orographic PMP for orography. Details of, and problems encountered with, these methods are discussed. Tools or methods to assess meterological limits for antecedant conditions and for limits to runoff during extreme events have not been developed and require research effort. 11 refs., 2 figs., 3 tabs
On Selection of the Probability Distribution for Representing the Maximum Annual Wind Speed in East Cairo, Egypt

International Nuclear Information System (INIS)

El-Shanshoury, Gh. I.; El-Hemamy, S.T.

2013-01-01

The main objective of this paper is to identify an appropriate probability model and best plotting position formula which represent the maximum annual wind speed in east Cairo. This model can be used to estimate the extreme wind speed and return period at a particular site as well as to determine the radioactive release distribution in case of accident occurrence at a nuclear power plant. Wind speed probabilities can be estimated by using probability distributions. An accurate determination of probability distribution for maximum wind speed data is very important in expecting the extreme value . The probability plots of the maximum annual wind speed (MAWS) in east Cairo are fitted to six major statistical distributions namely: Gumbel, Weibull, Normal, Log-Normal, Logistic and Log- Logistic distribution, while eight plotting positions of Hosking and Wallis, Hazen, Gringorten, Cunnane, Blom, Filliben, Benard and Weibull are used for determining exceedance of their probabilities. A proper probability distribution for representing the MAWS is selected by the statistical test criteria in frequency analysis. Therefore, the best plotting position formula which can be used to select appropriate probability model representing the MAWS data must be determined. The statistical test criteria which represented in: the probability plot correlation coefficient (PPCC), the root mean square error (RMSE), the relative root mean square error (RRMSE) and the maximum absolute error (MAE) are used to select the appropriate probability position and distribution. The data obtained show that the maximum annual wind speed in east Cairo vary from 44.3 Km/h to 96.1 Km/h within duration of 39 years . Weibull plotting position combined with Normal distribution gave the highest fit, most reliable, accurate predictions and determination of the wind speed in the study area having the highest value of PPCC and lowest values of RMSE, RRMSE and MAE
Maximum Entropy Estimation of Transition Probabilities of Reversible Markov Chains

Directory of Open Access Journals (Sweden)

Erik Van der Straeten

2009-11-01

Full Text Available In this paper, we develop a general theory for the estimation of the transition probabilities of reversible Markov chains using the maximum entropy principle. A broad range of physical models can be studied within this approach. We use one-dimensional classical spin systems to illustrate the theoretical ideas. The examples studied in this paper are: the Ising model, the Potts model and the Blume-Emery-Griffiths model.
Estimation and prediction of maximum daily rainfall at Sagar Island using best fit probability models

Science.gov (United States)

Mandal, S.; Choudhury, B. U.

2015-07-01

Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.
Probable maximum flood analysis, Richton Dome, Mississippi-Phase I: Technical report

International Nuclear Information System (INIS)

1987-03-01

This report presents results of a preliminary analysis of the extent of inundation that would result from a probable maximum flood (PMF) event in the overdome area of Richton Dome, Mississippi. Bogue Homo and Thompson Creek watersheds drain the overdome area. The US Army Corps of Engineers' HEC-1 Flood Hydrograph Package was used to calculate runoff hydrographs, route computed flood hydrographs, and determine maximum flood stages at cross sections along overdome tributaries. The area and configuration of stream cross sections were determined from US Geological Survey topographic maps. Using maximum flood stages calculated by the HEC-1 analysis, areas of inundation were delineated on 10-ft (3-m) contour interval topographic maps. Approximately 10% of the overdome area, or 0.9 mi 2 (2 km 2 ), would be inundated by a PMF event. 34 refs., 3 figs., 1 tab
The effect of coupling hydrologic and hydrodynamic models on probable maximum flood estimation

Science.gov (United States)

Felder, Guido; Zischg, Andreas; Weingartner, Rolf

2017-07-01

Deterministic rainfall-runoff modelling usually assumes stationary hydrological system, as model parameters are calibrated with and therefore dependant on observed data. However, runoff processes are probably not stationary in the case of a probable maximum flood (PMF) where discharge greatly exceeds observed flood peaks. Developing hydrodynamic models and using them to build coupled hydrologic-hydrodynamic models can potentially improve the plausibility of PMF estimations. This study aims to assess the potential benefits and constraints of coupled modelling compared to standard deterministic hydrologic modelling when it comes to PMF estimation. The two modelling approaches are applied using a set of 100 spatio-temporal probable maximum precipitation (PMP) distribution scenarios. The resulting hydrographs, the resulting peak discharges as well as the reliability and the plausibility of the estimates are evaluated. The discussion of the results shows that coupling hydrologic and hydrodynamic models substantially improves the physical plausibility of PMF modelling, although both modelling approaches lead to PMF estimations for the catchment outlet that fall within a similar range. Using a coupled model is particularly suggested in cases where considerable flood-prone areas are situated within a catchment.
Probability of success for phase III after exploratory biomarker analysis in phase II.

Science.gov (United States)

Götte, Heiko; Kirchner, Marietta; Sailer, Martin Oliver

2017-05-01

The probability of success or average power describes the potential of a future trial by weighting the power with a probability distribution of the treatment effect. The treatment effect estimate from a previous trial can be used to define such a distribution. During the development of targeted therapies, it is common practice to look for predictive biomarkers. The consequence is that the trial population for phase III is often selected on the basis of the most extreme result from phase II biomarker subgroup analyses. In such a case, there is a tendency to overestimate the treatment effect. We investigate whether the overestimation of the treatment effect estimate from phase II is transformed into a positive bias for the probability of success for phase III. We simulate a phase II/III development program for targeted therapies. This simulation allows to investigate selection probabilities and allows to compare the estimated with the true probability of success. We consider the estimated probability of success with and without subgroup selection. Depending on the true treatment effects, there is a negative bias without selection because of the weighting by the phase II distribution. In comparison, selection increases the estimated probability of success. Thus, selection does not lead to a bias in probability of success if underestimation due to the phase II distribution and overestimation due to selection cancel each other out. We recommend to perform similar simulations in practice to get the necessary information about the risk and chances associated with such subgroup selection designs. Copyright © 2017 John Wiley & Sons, Ltd.

A general formula for computing maximum proportion correct scores in various psychophysical paradigms with arbitrary probability distributions of stimulus observations.

Science.gov (United States)

Dai, Huanping; Micheyl, Christophe

2015-05-01

Proportion correct (Pc) is a fundamental measure of task performance in psychophysics. The maximum Pc score that can be achieved by an optimal (maximum-likelihood) observer in a given task is of both theoretical and practical importance, because it sets an upper limit on human performance. Within the framework of signal detection theory, analytical solutions for computing the maximum Pc score have been established for several common experimental paradigms under the assumption of Gaussian additive internal noise. However, as the scope of applications of psychophysical signal detection theory expands, the need is growing for psychophysicists to compute maximum Pc scores for situations involving non-Gaussian (internal or stimulus-induced) noise. In this article, we provide a general formula for computing the maximum Pc in various psychophysical experimental paradigms for arbitrary probability distributions of sensory activity. Moreover, easy-to-use MATLAB code implementing the formula is provided. Practical applications of the formula are illustrated, and its accuracy is evaluated, for two paradigms and two types of probability distributions (uniform and Gaussian). The results demonstrate that Pc scores computed using the formula remain accurate even for continuous probability distributions, as long as the conversion from continuous probability density functions to discrete probability mass functions is supported by a sufficiently high sampling resolution. We hope that the exposition in this article, and the freely available MATLAB code, facilitates calculations of maximum performance for a wider range of experimental situations, as well as explorations of the impact of different assumptions concerning internal-noise distributions on maximum performance in psychophysical experiments.
Spectral shaping of a randomized PWM DC-DC converter using maximum entropy probability distributions

CSIR Research Space (South Africa)

Dove, Albert

2017-01-01

Full Text Available maintaining constraints in a DC-DC converter is investigated. A probability distribution whose aim is to ensure maximal harmonic spreading and yet mainaint constraints is presented. The PDFs are determined from a direct application of the method of Maximum...
Physical method to assess a probable maximum precipitation, using CRCM datas

International Nuclear Information System (INIS)

Beauchamp, J.

2009-01-01

'Full text:' For Nordic hydropower facilities, spillways are designed with a peak discharge based on extreme conditions. This peak discharge is generally derived using the concept of a probable maximum flood (PMF), which results from the combined effect of abundant downpours (probable maximum precipitation - PMP) and rapid snowmelt. On a gauged basin, the weather data record allows for the computation of the PMF. However, uncertainty in the future climate raises questions as to the accuracy of current PMP estimates for existing and future hydropower facilities. This project looks at the potential use of the Canadian Regional Climate Model (CRCM) data to compute the PMF in ungauged basins and to assess potential changes to the PMF in a changing climate. Several steps will be needed to accomplish this task. This paper presents the first step that aims at applying/adapting to CRCM data the in situ moisture maximization technique developed by the World Meteorological Organization, in order to compute the PMP at the watershed scale. The CRCM provides output data on a 45km grid at a six hour time step. All of the needed atmospheric data is available at sixteen different pressure levels. The methodology consists in first identifying extreme precipitation events under current climate conditions. Then, a maximum persisting twelve hours dew point is determined at each grid point and pressure level for the storm duration. Afterwards, the maximization ratio is approximated by merging the effective temperature with dew point and relative humidity values. The variables and maximization ratio are four-dimensional (x, y, z, t) values. Consequently, two different approaches are explored: a partial ratio at each step and a global ratio for the storm duration. For every identified extreme precipitation event, a maximized hyetograph is computed from the application of this ratio, either partial or global, on CRCM precipitation rates. Ultimately, the PMP is the depth of the
Physical method to assess a probable maximum precipitation, using CRCM datas

Energy Technology Data Exchange (ETDEWEB)

Beauchamp, J. [Univ. de Quebec, Ecole de technologie superior, Quebec (Canada)

2009-07-01

'Full text:' For Nordic hydropower facilities, spillways are designed with a peak discharge based on extreme conditions. This peak discharge is generally derived using the concept of a probable maximum flood (PMF), which results from the combined effect of abundant downpours (probable maximum precipitation - PMP) and rapid snowmelt. On a gauged basin, the weather data record allows for the computation of the PMF. However, uncertainty in the future climate raises questions as to the accuracy of current PMP estimates for existing and future hydropower facilities. This project looks at the potential use of the Canadian Regional Climate Model (CRCM) data to compute the PMF in ungauged basins and to assess potential changes to the PMF in a changing climate. Several steps will be needed to accomplish this task. This paper presents the first step that aims at applying/adapting to CRCM data the in situ moisture maximization technique developed by the World Meteorological Organization, in order to compute the PMP at the watershed scale. The CRCM provides output data on a 45km grid at a six hour time step. All of the needed atmospheric data is available at sixteen different pressure levels. The methodology consists in first identifying extreme precipitation events under current climate conditions. Then, a maximum persisting twelve hours dew point is determined at each grid point and pressure level for the storm duration. Afterwards, the maximization ratio is approximated by merging the effective temperature with dew point and relative humidity values. The variables and maximization ratio are four-dimensional (x, y, z, t) values. Consequently, two different approaches are explored: a partial ratio at each step and a global ratio for the storm duration. For every identified extreme precipitation event, a maximized hyetograph is computed from the application of this ratio, either partial or global, on CRCM precipitation rates. Ultimately, the PMP is the depth of the
Probable Maximum Earthquake Magnitudes for the Cascadia Subduction

Science.gov (United States)

Rong, Y.; Jackson, D. D.; Magistrale, H.; Goldfinger, C.

2013-12-01

The concept of maximum earthquake magnitude (mx) is widely used in seismic hazard and risk analysis. However, absolute mx lacks a precise definition and cannot be determined from a finite earthquake history. The surprising magnitudes of the 2004 Sumatra and the 2011 Tohoku earthquakes showed that most methods for estimating mx underestimate the true maximum if it exists. Thus, we introduced the alternate concept of mp(T), probable maximum magnitude within a time interval T. The mp(T) can be solved using theoretical magnitude-frequency distributions such as Tapered Gutenberg-Richter (TGR) distribution. The two TGR parameters, β-value (which equals 2/3 b-value in the GR distribution) and corner magnitude (mc), can be obtained by applying maximum likelihood method to earthquake catalogs with additional constraint from tectonic moment rate. Here, we integrate the paleoseismic data in the Cascadia subduction zone to estimate mp. The Cascadia subduction zone has been seismically quiescent since at least 1900. Fortunately, turbidite studies have unearthed a 10,000 year record of great earthquakes along the subduction zone. We thoroughly investigate the earthquake magnitude-frequency distribution of the region by combining instrumental and paleoseismic data, and using the tectonic moment rate information. To use the paleoseismic data, we first estimate event magnitudes, which we achieve by using the time interval between events, rupture extent of the events, and turbidite thickness. We estimate three sets of TGR parameters: for the first two sets, we consider a geographically large Cascadia region that includes the subduction zone, and the Explorer, Juan de Fuca, and Gorda plates; for the third set, we consider a narrow geographic region straddling the subduction zone. In the first set, the β-value is derived using the GCMT catalog. In the second and third sets, the β-value is derived using both the GCMT and paleoseismic data. Next, we calculate the corresponding mc
Evaluation of probable maximum snow accumulation: Development of a methodology for climate change studies

Science.gov (United States)

Klein, Iris M.; Rousseau, Alain N.; Frigon, Anne; Freudiger, Daphné; Gagnon, Patrick

2016-06-01

Probable maximum snow accumulation (PMSA) is one of the key variables used to estimate the spring probable maximum flood (PMF). A robust methodology for evaluating the PMSA is imperative so the ensuing spring PMF is a reasonable estimation. This is of particular importance in times of climate change (CC) since it is known that solid precipitation in Nordic landscapes will in all likelihood change over the next century. In this paper, a PMSA methodology based on simulated data from regional climate models is developed. Moisture maximization represents the core concept of the proposed methodology; precipitable water being the key variable. Results of stationarity tests indicate that CC will affect the monthly maximum precipitable water and, thus, the ensuing ratio to maximize important snowfall events. Therefore, a non-stationary approach is used to describe the monthly maximum precipitable water. Outputs from three simulations produced by the Canadian Regional Climate Model were used to give first estimates of potential PMSA changes for southern Quebec, Canada. A sensitivity analysis of the computed PMSA was performed with respect to the number of time-steps used (so-called snowstorm duration) and the threshold for a snowstorm to be maximized or not. The developed methodology is robust and a powerful tool to estimate the relative change of the PMSA. Absolute results are in the same order of magnitude as those obtained with the traditional method and observed data; but are also found to depend strongly on the climate projection used and show spatial variability.
Estimating success probability of a rugby goal kick and developing a ...

African Journals Online (AJOL)

The objective of this study was firstly to derive a formula to estimate the success probability of a particular rugby goal kick and, secondly to derive a goal kicker rating measure that could be used to rank rugby union goal kickers. Various factors that could influence the success of a particular goal kick were considered.
The estimation of probable maximum precipitation: the case of Catalonia.

Science.gov (United States)

Casas, M Carmen; Rodríguez, Raül; Nieto, Raquel; Redaño, Angel

2008-12-01

A brief overview of the different techniques used to estimate the probable maximum precipitation (PMP) is presented. As a particular case, the 1-day PMP over Catalonia has been calculated and mapped with a high spatial resolution. For this purpose, the annual maximum daily rainfall series from 145 pluviometric stations of the Instituto Nacional de Meteorología (Spanish Weather Service) in Catalonia have been analyzed. In order to obtain values of PMP, an enveloping frequency factor curve based on the actual rainfall data of stations in the region has been developed. This enveloping curve has been used to estimate 1-day PMP values of all the 145 stations. Applying the Cressman method, the spatial analysis of these values has been achieved. Monthly precipitation climatological data, obtained from the application of Geographic Information Systems techniques, have been used as the initial field for the analysis. The 1-day PMP at 1 km(2) spatial resolution over Catalonia has been objectively determined, varying from 200 to 550 mm. Structures with wavelength longer than approximately 35 km can be identified and, despite their general concordance, the obtained 1-day PMP spatial distribution shows remarkable differences compared to the annual mean precipitation arrangement over Catalonia.
Variation of Probable Maximum Precipitation in Brazos River Basin, TX

Science.gov (United States)

Bhatia, N.; Singh, V. P.

2017-12-01

The Brazos River basin, the second-largest river basin by area in Texas, generates the highest amount of flow volume of any river in a given year in Texas. With its headwaters located at the confluence of Double Mountain and Salt forks in Stonewall County, the third-longest flowline of the Brazos River traverses within narrow valleys in the area of rolling topography of west Texas, and flows through rugged terrains in mainly featureless plains of central Texas, before its confluence with Gulf of Mexico. Along its major flow network, the river basin covers six different climate regions characterized on the basis of similar attributes of vegetation, temperature, humidity, rainfall, and seasonal weather changes, by National Oceanic and Atmospheric Administration (NOAA). Our previous research on Texas climatology illustrated intensified precipitation regimes, which tend to result in extreme flood events. Such events have caused huge losses of lives and infrastructure in the Brazos River basin. Therefore, a region-specific investigation is required for analyzing precipitation regimes along the geographically-diverse river network. Owing to the topographical and hydroclimatological variations along the flow network, 24-hour Probable Maximum Precipitation (PMP) was estimated for different hydrologic units along the river network, using the revised Hershfield's method devised by Lan et al. (2017). The method incorporates the use of a standardized variable describing the maximum deviation from the average of a sample scaled by the standard deviation of the sample. The hydrometeorological literature identifies this method as more reasonable and consistent with the frequency equation. With respect to the calculation of stable data size required for statistically reliable results, this study also quantified the respective uncertainty associated with PMP values in different hydrologic units. The corresponding range of return periods of PMPs in different hydrologic units was
Probability of cesarean delivery after successful external cephalic version.

Science.gov (United States)

Burgos, Jorge; Iglesias, María; Pijoan, José I; Rodriguez, Leire; Fernández-Llebrez, Luis; Martínez-Astorquiza, Txantón

2015-11-01

To identify factors associated with cesarean delivery following successful external cephalic version (ECV). In a prospective study, data were obtained for ECV procedures performed at Cruces University Hospital, Spain, between March 2002 and June 2012. Women with a singleton pregnancy who had a successful, uncomplicated ECV and whose delivery was assisted at the study hospital, with the fetus in cephalic presentation, were included. A multivariate model of risk factors of cesarean delivery was developed. Among 627 women included, 92 (14.7%) delivered by cesarean. A cesarean was performed among 33 (8.5%) of 387 women with spontaneous labor versus 59 (24.6%) of 240 who were induced (P < 0.001). Multivariate analysis showed that higher BMI (P = 0.006), labor induction (P = 0.001), and prior cesarean (P < 0.001) were associated with cesarean. Time between ECV and delivery was inversely associated with probability of cesarean during the first 2 weeks. Thus, the probabilities of cesarean delivery on the first day were 0.53 (95% CI 0.35-0.71) and 0.34 (95% CI 0.18-0.51) following induced and spontaneous labor, respectively. On the seventh day, the probabilities were 0.23 (95% CI 0.15-0.32) and 0.12 (95% CI 0.07-0.18), respectively. Following ECV, induction of labor, an interval of less than 2 weeks to delivery, BMI, and previous cesarean were associated with an increased risk of cesarean. Copyright © 2015 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.
Estimation method for first excursion probability of secondary system with impact and friction using maximum response

International Nuclear Information System (INIS)

Shigeru Aoki

2005-01-01

The secondary system such as pipings, tanks and other mechanical equipment is installed in the primary system such as building. The important secondary systems should be designed to maintain their function even if they are subjected to destructive earthquake excitations. The secondary system has many nonlinear characteristics. Impact and friction characteristic, which are observed in mechanical supports and joints, are common nonlinear characteristics. As impact damper and friction damper, impact and friction characteristic are used for reduction of seismic response. In this paper, analytical methods of the first excursion probability of the secondary system with impact and friction, subjected to earthquake excitation are proposed. By using the methods, the effects of impact force, gap size and friction force on the first excursion probability are examined. When the tolerance level is normalized by the maximum response of the secondary system without impact or friction characteristics, variation of the first excursion probability is very small for various values of the natural period. In order to examine the effectiveness of the proposed method, the obtained results are compared with those obtained by the simulation method. Some estimation methods for the maximum response of the secondary system with nonlinear characteristics have been developed. (author)
Paddle River Dam : review of probable maximum flood

Energy Technology Data Exchange (ETDEWEB)

Clark, D. [UMA Engineering Ltd., Edmonton, AB (Canada); Neill, C.R. [Northwest Hydraulic Consultants Ltd., Edmonton, AB (Canada)

2008-07-01

The Paddle River Dam was built in northern Alberta in the mid 1980s for flood control. According to the 1999 Canadian Dam Association (CDA) guidelines, this 35 metre high, zoned earthfill dam with a spillway capacity sized to accommodate a probable maximum flood (PMF) is rated as a very high hazard. At the time of design, it was estimated to have a peak flow rate of 858 centimetres. A review of the PMF in 2002 increased the peak flow rate to 1,890 centimetres. In light of a 2007 revision of the CDA safety guidelines, the PMF was reviewed and the inflow design flood (IDF) was re-evaluated. This paper discussed the levels of uncertainty inherent in PMF determinations and some difficulties encountered with the SSARR hydrologic model and the HEC-RAS hydraulic model in unsteady mode. The paper also presented and discussed the analysis used to determine incremental damages, upon which a new IDF of 840 m{sup 3}/s was recommended. The paper discussed the PMF review, modelling methodology, hydrograph inputs, and incremental damage of floods. It was concluded that the PMF review, involving hydraulic routing through the valley bottom together with reconsideration of the previous runoff modeling provides evidence that the peak reservoir inflow could reasonably be reduced by approximately 20 per cent. 8 refs., 5 tabs., 8 figs.
Development of a methodology for probable maximum precipitation estimation over the American River watershed using the WRF model

Science.gov (United States)

Tan, Elcin

A new physically-based methodology for probable maximum precipitation (PMP) estimation is developed over the American River Watershed (ARW) using the Weather Research and Forecast (WRF-ARW) model. A persistent moisture flux convergence pattern, called Pineapple Express, is analyzed for 42 historical extreme precipitation events, and it is found that Pineapple Express causes extreme precipitation over the basin of interest. An average correlation between moisture flux convergence and maximum precipitation is estimated as 0.71 for 42 events. The performance of the WRF model is verified for precipitation by means of calibration and independent validation of the model. The calibration procedure is performed only for the first ranked flood event 1997 case, whereas the WRF model is validated for 42 historical cases. Three nested model domains are set up with horizontal resolutions of 27 km, 9 km, and 3 km over the basin of interest. As a result of Chi-square goodness-of-fit tests, the hypothesis that "the WRF model can be used in the determination of PMP over the ARW for both areal average and point estimates" is accepted at the 5% level of significance. The sensitivities of model physics options on precipitation are determined using 28 microphysics, atmospheric boundary layer, and cumulus parameterization schemes combinations. It is concluded that the best triplet option is Thompson microphysics, Grell 3D ensemble cumulus, and YSU boundary layer (TGY), based on 42 historical cases, and this TGY triplet is used for all analyses of this research. Four techniques are proposed to evaluate physically possible maximum precipitation using the WRF: 1. Perturbations of atmospheric conditions; 2. Shift in atmospheric conditions; 3. Replacement of atmospheric conditions among historical events; and 4. Thermodynamically possible worst-case scenario creation. Moreover, climate change effect on precipitation is discussed by emphasizing temperature increase in order to determine the
Estimation of the probability of success in petroleum exploration

Science.gov (United States)

Davis, J.C.

1977-01-01

A probabilistic model for oil exploration can be developed by assessing the conditional relationship between perceived geologic variables and the subsequent discovery of petroleum. Such a model includes two probabilistic components, the first reflecting the association between a geologic condition (structural closure, for example) and the occurrence of oil, and the second reflecting the uncertainty associated with the estimation of geologic variables in areas of limited control. Estimates of the conditional relationship between geologic variables and subsequent production can be found by analyzing the exploration history of a "training area" judged to be geologically similar to the exploration area. The geologic variables are assessed over the training area using an historical subset of the available data, whose density corresponds to the present control density in the exploration area. The success or failure of wells drilled in the training area subsequent to the time corresponding to the historical subset provides empirical estimates of the probability of success conditional upon geology. Uncertainty in perception of geological conditions may be estimated from the distribution of errors made in geologic assessment using the historical subset of control wells. These errors may be expressed as a linear function of distance from available control. Alternatively, the uncertainty may be found by calculating the semivariogram of the geologic variables used in the analysis: the two procedures will yield approximately equivalent results. The empirical probability functions may then be transferred to the exploration area and used to estimate the likelihood of success of specific exploration plays. These estimates will reflect both the conditional relationship between the geological variables used to guide exploration and the uncertainty resulting from lack of control. The technique is illustrated with case histories from the mid-Continent area of the U.S.A. ?? 1977 Plenum
On Field Size and Success Probability in Network Coding

DEFF Research Database (Denmark)

Geil, Hans Olav; Matsumoto, Ryutaroh; Thomsen, Casper

2008-01-01

Using tools from algebraic geometry and Gröbner basis theory we solve two problems in network coding. First we present a method to determine the smallest field size for which linear network coding is feasible. Second we derive improved estimates on the success probability of random linear network...... coding. These estimates take into account which monomials occur in the support of the determinant of the product of Edmonds matrices. Therefore we finally investigate which monomials can occur in the determinant of the Edmonds matrix....
Efficient reconfigurable hardware architecture for accurately computing success probability and data complexity of linear attacks

DEFF Research Database (Denmark)

Bogdanov, Andrey; Kavun, Elif Bilge; Tischhauser, Elmar

2012-01-01

An accurate estimation of the success probability and data complexity of linear cryptanalysis is a fundamental question in symmetric cryptography. In this paper, we propose an efficient reconfigurable hardware architecture to compute the success probability and data complexity of Matsui's Algorithm...... block lengths ensures that any empirical observations are not due to differences in statistical behavior for artificially small block lengths. Rather surprisingly, we observed in previous experiments a significant deviation between the theory and practice for Matsui's Algorithm 2 for larger block sizes...
Success probability orientated optimization model for resource allocation of the technological innovation multi-project system

Institute of Scientific and Technical Information of China (English)

Weixu Dai; Weiwei Wu; Bo Yu; Yunhao Zhu

2016-01-01

A success probability orientated optimization model for resource al ocation of the technological innovation multi-project system is studied. Based on the definition of the technological in-novation multi-project system, the leveling optimization of cost and success probability is set as the objective of resource al ocation. The cost function and the probability function of the optimization model are constructed. Then the objective function of the model is constructed and the solving process is explained. The model is applied to the resource al ocation of an enterprise’s technological innovation multi-project system. The results show that the pro-posed model is more effective in rational resource al ocation, and is more applicable in maximizing the utility of the technological innovation multi-project system.
Developing a Mathematical Model for Scheduling and Determining Success Probability of Research Projects Considering Complex-Fuzzy Networks

Directory of Open Access Journals (Sweden)

Gholamreza Norouzi

2015-01-01

Full Text Available In project management context, time management is one of the most important factors affecting project success. This paper proposes a new method to solve research project scheduling problems (RPSP containing Fuzzy Graphical Evaluation and Review Technique (FGERT networks. Through the deliverables of this method, a proper estimation of project completion time (PCT and success probability can be achieved. So algorithms were developed to cover all features of the problem based on three main parameters “duration, occurrence probability, and success probability.” These developed algorithms were known as PR-FGERT (Parallel and Reversible-Fuzzy GERT networks. The main provided framework includes simplifying the network of project and taking regular steps to determine PCT and success probability. Simplifications include (1 equivalent making of parallel and series branches in fuzzy network considering the concepts of probabilistic nodes, (2 equivalent making of delay or reversible-to-itself branches and impact of changing the parameters of time and probability based on removing related branches, (3 equivalent making of simple and complex loops, and (4 an algorithm that was provided to resolve no-loop fuzzy network, after equivalent making. Finally, the performance of models was compared with existing methods. The results showed proper and real performance of models in comparison with existing methods.
SENSITIVITY OF NEST SUCCESS, YOUNG FLEDGED, AND PROBABILITY OF RENESTING TO SEASONAL FECUNDITY IN MULTI-BROODED SPECIES

Science.gov (United States)

A considerable number of avian species can produce multiple broods within a season. Seasonal fecundity in these species can vary by changes in the number of young fledged per nest, the probability of a successful nest, and the probability of initiating additional nests (e.g., re...
Calculating the Prior Probability Distribution for a Causal Network Using Maximum Entropy: Alternative Approaches

Directory of Open Access Journals (Sweden)

Michael J. Markham

2011-07-01

Full Text Available Some problems occurring in Expert Systems can be resolved by employing a causal (Bayesian network and methodologies exist for this purpose. These require data in a specific form and make assumptions about the independence relationships involved. Methodologies using Maximum Entropy (ME are free from these conditions and have the potential to be used in a wider context including systems consisting of given sets of linear and independence constraints, subject to consistency and convergence. ME can also be used to validate results from the causal network methodologies. Three ME methods for determining the prior probability distribution of causal network systems are considered. The first method is Sequential Maximum Entropy in which the computation of a progression of local distributions leads to the over-all distribution. This is followed by development of the Method of Tribus. The development takes the form of an algorithm that includes the handling of explicit independence constraints. These fall into two groups those relating parents of vertices, and those deduced from triangulation of the remaining graph. The third method involves a variation in the part of that algorithm which handles independence constraints. Evidence is presented that this adaptation only requires the linear constraints and the parental independence constraints to emulate the second method in a substantial class of examples.

Estimating Probable Maximum Precipitation by Considering Combined Effect of Typhoon and Southwesterly Air Flow

Directory of Open Access Journals (Sweden)

Cheng-Chin Liu

2016-01-01

Full Text Available Typhoon Morakot hit southern Taiwan in 2009, bringing 48-hr of heavy rainfall [close to the Probable Maximum Precipitation (PMP] to the Tsengwen Reservoir catchment. This extreme rainfall event resulted from the combined (co-movement effect of two climate systems (i.e., typhoon and southwesterly air flow. Based on the traditional PMP estimation method (i.e., the storm transposition method, STM, two PMP estimation approaches, i.e., Amplification Index (AI and Independent System (IS approaches, which consider the combined effect are proposed in this work. The AI approach assumes that the southwesterly air flow precipitation in a typhoon event could reach its maximum value. The IS approach assumes that the typhoon and southwesterly air flow are independent weather systems. Based on these assumptions, calculation procedures for the two approaches were constructed for a case study on the Tsengwen Reservoir catchment. The results show that the PMP estimates for 6- to 60-hr durations using the two approaches are approximately 30% larger than the PMP estimates using the traditional STM without considering the combined effect. This work is a pioneer PMP estimation method that considers the combined effect of a typhoon and southwesterly air flow. Further studies on this issue are essential and encouraged.
Ignorance is not bliss: Statistical power is not probability of trial success.

Science.gov (United States)

Zierhut, M L; Bycott, P; Gibbs, M A; Smith, B P; Vicini, P

2016-04-01

The purpose of this commentary is to place probability of trial success, or assurance, in the context of decision making in drug development, and to illustrate its properties in an intuitive manner for the readers of Clinical Pharmacology and Therapeutics. The hope is that this will stimulate a dialog on how assurance should be incorporated into a quantitative decision approach for clinical development and trial design that uses all available information. © 2015 ASCPT.
Hardy's argument and successive spin-s measurements

International Nuclear Information System (INIS)

Ahanj, Ali

2010-01-01

We consider a hidden-variable theoretic description of successive measurements of noncommuting spin observables on an input spin-s state. In this scenario, the hidden-variable theory leads to a Hardy-type argument that quantum predictions violate it. We show that the maximum probability of success of Hardy's argument in quantum theory is ((1/2)) 4s , which is more than in the spatial case.
Credal Networks under Maximum Entropy

OpenAIRE

Lukasiewicz, Thomas

2013-01-01

We apply the principle of maximum entropy to select a unique joint probability distribution from the set of all joint probability distributions specified by a credal network. In detail, we start by showing that the unique joint distribution of a Bayesian tree coincides with the maximum entropy model of its conditional distributions. This result, however, does not hold anymore for general Bayesian networks. We thus present a new kind of maximum entropy models, which are computed sequentially. ...
Pattern formation, logistics, and maximum path probability

Science.gov (United States)

Kirkaldy, J. S.

1985-05-01

The concept of pattern formation, which to current researchers is a synonym for self-organization, carries the connotation of deductive logic together with the process of spontaneous inference. Defining a pattern as an equivalence relation on a set of thermodynamic objects, we establish that a large class of irreversible pattern-forming systems, evolving along idealized quasisteady paths, approaches the stable steady state as a mapping upon the formal deductive imperatives of a propositional function calculus. In the preamble the classical reversible thermodynamics of composite systems is analyzed as an externally manipulated system of space partitioning and classification based on ideal enclosures and diaphragms. The diaphragms have discrete classification capabilities which are designated in relation to conserved quantities by descriptors such as impervious, diathermal, and adiabatic. Differentiability in the continuum thermodynamic calculus is invoked as equivalent to analyticity and consistency in the underlying class or sentential calculus. The seat of inference, however, rests with the thermodynamicist. In the transition to an irreversible pattern-forming system the defined nature of the composite reservoirs remains, but a given diaphragm is replaced by a pattern-forming system which by its nature is a spontaneously evolving volume partitioner and classifier of invariants. The seat of volition or inference for the classification system is thus transferred from the experimenter or theoretician to the diaphragm, and with it the full deductive facility. The equivalence relations or partitions associated with the emerging patterns may thus be associated with theorems of the natural pattern-forming calculus. The entropy function, together with its derivatives, is the vehicle which relates the logistics of reservoirs and diaphragms to the analog logistics of the continuum. Maximum path probability or second-order differentiability of the entropy in isolation are
OL-DEC-MDP Model for Multiagent Online Scheduling with a Time-Dependent Probability of Success

Directory of Open Access Journals (Sweden)

Cheng Zhu

2014-01-01

Full Text Available Focusing on the on-line multiagent scheduling problem, this paper considers the time-dependent probability of success and processing duration and proposes an OL-DEC-MDP (opportunity loss-decentralized Markov Decision Processes model to include opportunity loss into scheduling decision to improve overall performance. The success probability of job processing as well as the process duration is dependent on the time at which the processing is started. The probability of completing the assigned job by an agent would be higher when the process is started earlier, but the opportunity loss could also be high due to the longer engaging duration. As a result, OL-DEC-MDP model introduces a reward function considering the opportunity loss, which is estimated based on the prediction of the upcoming jobs by a sampling method on the job arrival. Heuristic strategies are introduced in computing the best starting time for an incoming job by each agent, and an incoming job will always be scheduled to the agent with the highest reward among all agents with their best starting policies. The simulation experiments show that the OL-DEC-MDP model will improve the overall scheduling performance compared with models not considering opportunity loss in heavy-loading environment.
Understanding the Role of Reservoir Size on Probable Maximum Precipitation

Science.gov (United States)

Woldemichael, A. T.; Hossain, F.

2011-12-01

This study addresses the question 'Does surface area of an artificial reservoir matter in the estimation of probable maximum precipitation (PMP) for an impounded basin?' The motivation of the study was based on the notion that the stationarity assumption that is implicit in the PMP for dam design can be undermined in the post-dam era due to an enhancement of extreme precipitation patterns by an artificial reservoir. In addition, the study lays the foundation for use of regional atmospheric models as one way to perform life cycle assessment for planned or existing dams to formulate best management practices. The American River Watershed (ARW) with the Folsom dam at the confluence of the American River was selected as the study region and the Dec-Jan 1996-97 storm event was selected for the study period. The numerical atmospheric model used for the study was the Regional Atmospheric Modeling System (RAMS). First, the numerical modeling system, RAMS, was calibrated and validated with selected station and spatially interpolated precipitation data. Best combinations of parameterization schemes in RAMS were accordingly selected. Second, to mimic the standard method of PMP estimation by moisture maximization technique, relative humidity terms in the model were raised to 100% from ground up to the 500mb level. The obtained model-based maximum 72-hr precipitation values were named extreme precipitation (EP) as a distinction from the PMPs obtained by the standard methods. Third, six hypothetical reservoir size scenarios ranging from no-dam (all-dry) to the reservoir submerging half of basin were established to test the influence of reservoir size variation on EP. For the case of the ARW, our study clearly demonstrated that the assumption of stationarity that is implicit the traditional estimation of PMP can be rendered invalid to a large part due to the very presence of the artificial reservoir. Cloud tracking procedures performed on the basin also give indication of the
Bayesian maximum posterior probability method for interpreting plutonium urinalysis data

International Nuclear Information System (INIS)

Miller, G.; Inkret, W.C.

1996-01-01

A new internal dosimetry code for interpreting urinalysis data in terms of radionuclide intakes is described for the case of plutonium. The mathematical method is to maximise the Bayesian posterior probability using an entropy function as the prior probability distribution. A software package (MEMSYS) developed for image reconstruction is used. Some advantages of the new code are that it ensures positive calculated dose, it smooths out fluctuating data, and it provides an estimate of the propagated uncertainty in the calculated doses. (author)
A probability space for quantum models

Science.gov (United States)

Lemmens, L. F.

2017-06-01

A probability space contains a set of outcomes, a collection of events formed by subsets of the set of outcomes and probabilities defined for all events. A reformulation in terms of propositions allows to use the maximum entropy method to assign the probabilities taking some constraints into account. The construction of a probability space for quantum models is determined by the choice of propositions, choosing the constraints and making the probability assignment by the maximum entropy method. This approach shows, how typical quantum distributions such as Maxwell-Boltzmann, Fermi-Dirac and Bose-Einstein are partly related with well-known classical distributions. The relation between the conditional probability density, given some averages as constraints and the appropriate ensemble is elucidated.
Site Specific Probable Maximum Precipitation Estimates and Professional Judgement

Science.gov (United States)

Hayes, B. D.; Kao, S. C.; Kanney, J. F.; Quinlan, K. R.; DeNeale, S. T.

2015-12-01

State and federal regulatory authorities currently rely upon the US National Weather Service Hydrometeorological Reports (HMRs) to determine probable maximum precipitation (PMP) estimates (i.e., rainfall depths and durations) for estimating flooding hazards for relatively broad regions in the US. PMP estimates for the contributing watersheds upstream of vulnerable facilities are used to estimate riverine flooding hazards while site-specific estimates for small water sheds are appropriate for individual facilities such as nuclear power plants. The HMRs are often criticized due to their limitations on basin size, questionable applicability in regions affected by orographic effects, their lack of consist methods, and generally by their age. HMR-51 for generalized PMP estimates for the United States east of the 105th meridian, was published in 1978 and is sometimes perceived as overly conservative. The US Nuclear Regulatory Commission (NRC), is currently reviewing several flood hazard evaluation reports that rely on site specific PMP estimates that have been commercially developed. As such, NRC has recently investigated key areas of expert judgement via a generic audit and one in-depth site specific review as they relate to identifying and quantifying actual and potential storm moisture sources, determining storm transposition limits, and adjusting available moisture during storm transposition. Though much of the approach reviewed was considered a logical extension of HMRs, two key points of expert judgement stood out for further in-depth review. The first relates primarily to small storms and the use of a heuristic for storm representative dew point adjustment developed for the Electric Power Research Institute by North American Weather Consultants in 1993 in order to harmonize historic storms for which only 12 hour dew point data was available with more recent storms in a single database. The second issue relates to the use of climatological averages for spatially
A new method for estimating the probable maximum hail loss of a building portfolio based on hailfall intensity determined by radar measurements

Science.gov (United States)

Aller, D.; Hohl, R.; Mair, F.; Schiesser, H.-H.

2003-04-01

Extreme hailfall can cause massive damage to building structures. For the insurance and reinsurance industry it is essential to estimate the probable maximum hail loss of their portfolio. The probable maximum loss (PML) is usually defined with a return period of 1 in 250 years. Statistical extrapolation has a number of critical points, as historical hail loss data are usually only available from some events while insurance portfolios change over the years. At the moment, footprints are derived from historical hail damage data. These footprints (mean damage patterns) are then moved over a portfolio of interest to create scenario losses. However, damage patterns of past events are based on the specific portfolio that was damaged during that event and can be considerably different from the current spread of risks. A new method for estimating the probable maximum hail loss to a building portfolio is presented. It is shown that footprints derived from historical damages are different to footprints of hail kinetic energy calculated from radar reflectivity measurements. Based on the relationship between radar-derived hail kinetic energy and hail damage to buildings, scenario losses can be calculated. A systematic motion of the hail kinetic energy footprints over the underlying portfolio creates a loss set. It is difficult to estimate the return period of losses calculated with footprints derived from historical damages being moved around. To determine the return periods of the hail kinetic energy footprints over Switzerland, 15 years of radar measurements and 53 years of agricultural hail losses are available. Based on these data, return periods of several types of hailstorms were derived for different regions in Switzerland. The loss set is combined with the return periods of the event set to obtain an exceeding frequency curve, which can be used to derive the PML.
Probable Maximum Precipitation (PMP) over mountainous region of Cameron Highlands- Batang Padang Catchment of Malaysia

Science.gov (United States)

Sidek, L. M.; Mohd Nor, M. D.; Rakhecha, P. R.; Basri, H.; Jayothisa, W.; Muda, R. S.; Ahmad, M. N.; Razad, A. Z. Abdul

2013-06-01

The Cameron Highland Batang Padang (CHBP) catchment situated on the main mountain range of Peninsular Malaysia is of large economical importance where currently a series of three dams (Sultan Abu Bakar, Jor and Mahang) exist in the development of water resources and hydropower. The prediction of the design storm rainfall values for different return periods including PMP values can be useful to review the adequacy of the current spillway capacities of these dams. In this paper estimates of the design storm rainfalls for various return periods and also the PMP values for rainfall stations in the CHBP catchment have been computed for the three different durations of 1, 3 & 5 days. The maximum values for 1 day, 3 days and 5 days PMP values are found to be 730.08mm, 966.17mm and 969.0mm respectively at Station number 4513033 Gunung Brinchang. The PMP values obtained were compared with previous study results undertaken by NAHRIM. However, the highest ratio of 1 day, 3 day and 5 day PMP to highest observed rainfall are found to be 2.30, 1.94 and 1.82 respectively. This shows that the ratio tend to decrease as the duration increase. Finally, the temporal pattern for 1 day, 3day and 5 days have been developed based on observed extreme rainfall at station 4513033 Gunung Brinchang for the generation of Probable Maximum Flood (PMF) in dam break analysis.
Probable Maximum Precipitation (PMP) over mountainous region of Cameron Highlands- Batang Padang Catchment of Malaysia

International Nuclear Information System (INIS)

Sidek, L M; Basri, H; Jayothisa, W; Nor, M D Mohd; Rakhecha, P R; Muda, R S; Ahmad, M N; Razad, A Z Abdul

2013-01-01

The Cameron Highland Batang Padang (CHBP) catchment situated on the main mountain range of Peninsular Malaysia is of large economical importance where currently a series of three dams (Sultan Abu Bakar, Jor and Mahang) exist in the development of water resources and hydropower. The prediction of the design storm rainfall values for different return periods including PMP values can be useful to review the adequacy of the current spillway capacities of these dams. In this paper estimates of the design storm rainfalls for various return periods and also the PMP values for rainfall stations in the CHBP catchment have been computed for the three different durations of 1, 3 and 5 days. The maximum values for 1 day, 3 days and 5 days PMP values are found to be 730.08mm, 966.17mm and 969.0mm respectively at Station number 4513033 Gunung Brinchang. The PMP values obtained were compared with previous study results undertaken by NAHRIM. However, the highest ratio of 1 day, 3 day and 5 day PMP to highest observed rainfall are found to be 2.30, 1.94 and 1.82 respectively. This shows that the ratio tend to decrease as the duration increase. Finally, the temporal pattern for 1 day, 3day and 5 days have been developed based on observed extreme rainfall at station 4513033 Gunung Brinchang for the generation of Probable Maximum Flood (PMF) in dam break analysis.
Scheme for implementing N-qubit controlled phase gate of photons assisted by quantum-dot-microcavity coupled system: optimal probability of success

International Nuclear Information System (INIS)

Cui, Wen-Xue; Hu, Shi; Wang, Hong-Fu; Zhu, Ai-Dong; Zhang, Shou

2015-01-01

The direct implementation of multiqubit controlled phase gate of photons is appealing and important for reducing the complexity of the physical realization of linear-optics-based practical quantum computer and quantum algorithms. In this letter we propose a nondestructive scheme for implementing an N-qubit controlled phase gate of photons with a high success probability. The gate can be directly implemented with the self-designed quantum encoder circuits, which are probabilistic optical quantum entangler devices and can be achieved using linear optical elements, single-photon superposition state, and quantum dot coupled to optical microcavity. The calculated results indicate that both the success probabilities of the quantum encoder circuit and the N-qubit controlled phase gate in our scheme are higher than those in the previous schemes. We also consider the effects of the side leakage and cavity loss on the success probability and the fidelity of the quantum encoder circuit for a realistic quantum-dot-microcavity coupled system. (letter)
Probability-of-success studies for geothermal projects: from subsurface data to geological risk analysis

Science.gov (United States)

Schumacher, Sandra; Pierau, Roberto; Wirth, Wolfgang

2017-04-01

In recent years, the development of geothermal plants in Germany has increased significantly due to a favorable political setting and resulting financial incentives. However, most projects are developed by local communities or private investors, which cannot afford a project to fail. To cover the risk of total loss if the geothermal well should not provide the energy output necessary for an economically viable project, investors try to procure insurances for this worst case scenario. In order to issue such insurances, the insurance companies insist on so called probability-of-success studies (POS studies), in which the geological risk for not achieving the necessary temperatures and/or flow rates for an economically successful project is quantified. Quantifying the probability of reaching a minimum temperature, which has to be defined by the project investors, is relatively straight forward as subsurface temperatures in Germany are comparatively well known due tens of thousands of hydrocarbon wells. Moreover, for the German Molasse Basin a method to characterize the hydraulic potential of a site based on pump test analysis has been developed and refined in recent years. However, to quantify the probability of reaching a given flow rate with a given drawdown is much more challenging in areas where pump test data are generally not available (e.g. the North German Basin). Therefore, a new method based on log and core derived porosity and permeability data was developed to quantify the geological risk of reaching a determined flow rate in such areas. We present both methods for POS studies and show how subsurface data such as pump tests or log and core measurements can be used to predict the chances of a potential geothermal project from a geological point of view.
Developing a Model and Applications for Probabilities of Student Success: A Case Study of Predictive Analytics

Science.gov (United States)

Calvert, Carol Elaine

2014-01-01

This case study relates to distance learning students on open access courses. It demonstrates the use of predictive analytics to generate a model of the probabilities of success and retention at different points, or milestones, in a student journey. A core set of explanatory variables has been established and their varying relative importance at…
Plant calendar pattern based on rainfall forecast and the probability of its success in Deli Serdang regency of Indonesia

Science.gov (United States)

Darnius, O.; Sitorus, S.

2018-03-01

The objective of this study was to determine the pattern of plant calendar of three types of crops; namely, palawija, rice, andbanana, based on rainfall in Deli Serdang Regency. In the first stage, we forecasted rainfall by using time series analysis, and obtained appropriate model of ARIMA (1,0,0) (1,1,1)12. Based on the forecast result, we designed a plant calendar pattern for the three types of plant. Furthermore, the probability of success in the plant types following the plant calendar pattern was calculated by using the Markov process by discretizing the continuous rainfall data into three categories; namely, Below Normal (BN), Normal (N), and Above Normal (AN) to form the probability transition matrix. Finally, the combination of rainfall forecasting models and the Markov process were used to determine the pattern of cropping calendars and the probability of success in the three crops. This research used rainfall data of Deli Serdang Regency taken from the office of BMKG (Meteorologist Climatology and Geophysics Agency), Sampali Medan, Indonesia.
Level set segmentation of medical images based on local region statistics and maximum a posteriori probability.

Science.gov (United States)

Cui, Wenchao; Wang, Yi; Lei, Tao; Fan, Yangyu; Feng, Yan

2013-01-01

This paper presents a variational level set method for simultaneous segmentation and bias field estimation of medical images with intensity inhomogeneity. In our model, the statistics of image intensities belonging to each different tissue in local regions are characterized by Gaussian distributions with different means and variances. According to maximum a posteriori probability (MAP) and Bayes' rule, we first derive a local objective function for image intensities in a neighborhood around each pixel. Then this local objective function is integrated with respect to the neighborhood center over the entire image domain to give a global criterion. In level set framework, this global criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, image segmentation and bias field estimation are simultaneously achieved via a level set evolution process. Experimental results for synthetic and real images show desirable performances of our method.
Classic maximum entropy recovery of the average joint distribution of apparent FRET efficiency and fluorescence photons for single-molecule burst measurements.

Science.gov (United States)

DeVore, Matthew S; Gull, Stephen F; Johnson, Carey K

2012-04-05

We describe a method for analysis of single-molecule Förster resonance energy transfer (FRET) burst measurements using classic maximum entropy. Classic maximum entropy determines the Bayesian inference for the joint probability describing the total fluorescence photons and the apparent FRET efficiency. The method was tested with simulated data and then with DNA labeled with fluorescent dyes. The most probable joint distribution can be marginalized to obtain both the overall distribution of fluorescence photons and the apparent FRET efficiency distribution. This method proves to be ideal for determining the distance distribution of FRET-labeled biomolecules, and it successfully predicts the shape of the recovered distributions.
Bayesian Probability Theory

Science.gov (United States)

von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo

2014-06-01

Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.

Review of the Probable Maximum Flood (PMF) Snowmelt Analysis for Success Dam

Science.gov (United States)

2015-11-01

watershed; and the USACE reports (1998, 2013) further describe the watershed characteris- tics, vegetation , climate, precipitation, and flooding. The...developed SCA product, MOD10A1, the MODIS/ Terra Snow Cover Daily L3 Global 500 m Grid (Hall et al. 2006), which provides a daily estimate of the fSCA of...find mean cloud persistence, or the average time between cloud-free scenes, to be less than a day at Terra MODIS’s temporal scale (approxi- mately 1
Explaining participation differentials in Dutch higher education: The impact of subjective success probabilities on level choice and field choice

NARCIS (Netherlands)

Tolsma, J.; Need, A.; Jong, U. de

2010-01-01

In this article we examine whether subjective estimates of success probabilities explain the effect of social origin, sex, and ethnicity on students' choices between different school tracks in Dutch higher education. The educational options analysed differ in level (i.e. university versus
Explaining participation differentials in Dutch higher education : the impact of subjective success probabilities on level choice and field choice

NARCIS (Netherlands)

Tolsma, J.; Need, A.; Jong, U. de

2010-01-01

In this article we examine whether subjective estimates of success probabilities explain the effect of social origin, sex, and ethnicity on students’ choices between different school tracks in Dutch higher education. The educational options analysed differ in level (i.e. university versus
Prestack inversion based on anisotropic Markov random field-maximum posterior probability inversion and its application to identify shale gas sweet spots

Science.gov (United States)

Wang, Kang-Ning; Sun, Zan-Dong; Dong, Ning

2015-12-01

Economic shale gas production requires hydraulic fracture stimulation to increase the formation permeability. Hydraulic fracturing strongly depends on geomechanical parameters such as Young's modulus and Poisson's ratio. Fracture-prone sweet spots can be predicted by prestack inversion, which is an ill-posed problem; thus, regularization is needed to obtain unique and stable solutions. To characterize gas-bearing shale sedimentary bodies, elastic parameter variations are regarded as an anisotropic Markov random field. Bayesian statistics are adopted for transforming prestack inversion to the maximum posterior probability. Two energy functions for the lateral and vertical directions are used to describe the distribution, and the expectation-maximization algorithm is used to estimate the hyperparameters of the prior probability of elastic parameters. Finally, the inversion yields clear geological boundaries, high vertical resolution, and reasonable lateral continuity using the conjugate gradient method to minimize the objective function. Antinoise and imaging ability of the method were tested using synthetic and real data.
Probable Maximum Precipitation in the U.S. Pacific Northwest in a Changing Climate

Science.gov (United States)

Chen, Xiaodong; Hossain, Faisal; Leung, L. Ruby

2017-11-01

The safety of large and aging water infrastructures is gaining attention in water management given the accelerated rate of change in landscape, climate, and society. In current engineering practice, such safety is ensured by the design of infrastructure for the Probable Maximum Precipitation (PMP). Recently, several numerical modeling approaches have been proposed to modernize the conventional and ad hoc PMP estimation approach. However, the underlying physics have not been fully investigated and thus differing PMP estimates are sometimes obtained without physics-based interpretations. In this study, we present a hybrid approach that takes advantage of both traditional engineering practice and modern climate science to estimate PMP for current and future climate conditions. The traditional PMP approach is modified and applied to five statistically downscaled CMIP5 model outputs, producing an ensemble of PMP estimates in the Pacific Northwest (PNW) during the historical (1970-2016) and future (2050-2099) time periods. The hybrid approach produced consistent historical PMP estimates as the traditional estimates. PMP in the PNW will increase by 50% ± 30% of the current design PMP by 2099 under the RCP8.5 scenario. Most of the increase is caused by warming, which mainly affects moisture availability through increased sea surface temperature, with minor contributions from changes in storm efficiency in the future. Moist track change tends to reduce the future PMP. Compared with extreme precipitation, PMP exhibits higher internal variability. Thus, long-time records of high-quality data in both precipitation and related meteorological fields (temperature, wind fields) are required to reduce uncertainties in the ensemble PMP estimates.
Nevada Test Site probable maximum flood study, part of US Geological Survey flood potential and debris hazard study, Yucca Mountain Site for US Department of Energy, Office of Civilian Radioactive Waste Management

International Nuclear Information System (INIS)

Bullard, K.L.

1994-01-01

The US Geological Survey (USGS), as part of the Yucca Mountain Project (YMP), is conducting studies at Yucca Mountain, Nevada. The purposes of these studies are to provide hydrologic and geologic information to evaluate the suitability of Yucca Mountain for development as a high-level nuclear waste repository, and to evaluate the ability of the mined geologic disposal system (MGDS) to isolate the waste in compliance with regulatory requirements. In particular, the project is designed to acquire information necessary for the Department of Energy (DOE) to demonstrate in its environmental impact statement (EIS) and license application whether the MGDS will meet the requirements of federal regulations 10 CFR Part 60, 10 CFR Part 960, and 40 CFR Part 191. Complete study plans for this part of the project were prepared by the USGS and approved by the DOE in August and September of 1990. The US Bureau of Reclamation (Reclamation) was selected by the USGS as a contractor to provide probable maximum flood (PMF) magnitudes and associated inundation maps for preliminary engineering design of the surface facilities at Yucca Mountain. These PMF peak flow estimates are necessary for successful waste repository design and construction. The PMF technique was chosen for two reasons: (1) this technique complies with ANSI requirements that PMF technology be used in the design of nuclear related facilities (ANSI/ANS, 1981), and (2) the PMF analysis has become a commonly used technology to predict a ''worst possible case'' flood scenario. For this PMF study, probable maximum precipitation (PMP) values were obtained for a local storm (thunderstorm) PMP event. These values were determined from the National Weather Services's Hydrometeorological Report No. 49 (HMR 49)
Neutron spectra unfolding with maximum entropy and maximum likelihood

International Nuclear Information System (INIS)

Itoh, Shikoh; Tsunoda, Toshiharu

1989-01-01

A new unfolding theory has been established on the basis of the maximum entropy principle and the maximum likelihood method. This theory correctly embodies the Poisson statistics of neutron detection, and always brings a positive solution over the whole energy range. Moreover, the theory unifies both problems of overdetermined and of underdetermined. For the latter, the ambiguity in assigning a prior probability, i.e. the initial guess in the Bayesian sense, has become extinct by virtue of the principle. An approximate expression of the covariance matrix for the resultant spectra is also presented. An efficient algorithm to solve the nonlinear system, which appears in the present study, has been established. Results of computer simulation showed the effectiveness of the present theory. (author)
A three-step Maximum-A-Posterior probability method for InSAR data inversion of coseismic rupture with application to four recent large earthquakes in Asia

Science.gov (United States)

Sun, J.; Shen, Z.; Burgmann, R.; Liang, F.

2012-12-01

We develop a three-step Maximum-A-Posterior probability (MAP) method for coseismic rupture inversion, which aims at maximizing the a posterior probability density function (PDF) of elastic solutions of earthquake rupture. The method originates from the Fully Bayesian Inversion (FBI) and the Mixed linear-nonlinear Bayesian inversion (MBI) methods , shares the same a posterior PDF with them and keeps most of their merits, while overcoming its convergence difficulty when large numbers of low quality data are used and improving the convergence rate greatly using optimization procedures. A highly efficient global optimization algorithm, Adaptive Simulated Annealing (ASA), is used to search for the maximum posterior probability in the first step. The non-slip parameters are determined by the global optimization method, and the slip parameters are inverted for using the least squares method without positivity constraint initially, and then damped to physically reasonable range. This step MAP inversion brings the inversion close to 'true' solution quickly and jumps over local maximum regions in high-dimensional parameter space. The second step inversion approaches the 'true' solution further with positivity constraints subsequently applied on slip parameters using the Monte Carlo Inversion (MCI) technique, with all parameters obtained from step one as the initial solution. Then the slip artifacts are eliminated from slip models in the third step MAP inversion with fault geometry parameters fixed. We first used a designed model with 45 degree dipping angle and oblique slip, and corresponding synthetic InSAR data sets to validate the efficiency and accuracy of method. We then applied the method on four recent large earthquakes in Asia, namely the 2010 Yushu, China earthquake, the 2011 Burma earthquake, the 2011 New Zealand earthquake and the 2008 Qinghai, China earthquake, and compared our results with those results from other groups. Our results show the effectiveness of
Joint probability of statistical success of multiple phase III trials.

Science.gov (United States)

Zhang, Jianliang; Zhang, Jenny J

2013-01-01

In drug development, after completion of phase II proof-of-concept trials, the sponsor needs to make a go/no-go decision to start expensive phase III trials. The probability of statistical success (PoSS) of the phase III trials based on data from earlier studies is an important factor in that decision-making process. Instead of statistical power, the predictive power of a phase III trial, which takes into account the uncertainty in the estimation of treatment effect from earlier studies, has been proposed to evaluate the PoSS of a single trial. However, regulatory authorities generally require statistical significance in two (or more) trials for marketing licensure. We show that the predictive statistics of two future trials are statistically correlated through use of the common observed data from earlier studies. Thus, the joint predictive power should not be evaluated as a simplistic product of the predictive powers of the individual trials. We develop the relevant formulae for the appropriate evaluation of the joint predictive power and provide numerical examples. Our methodology is further extended to the more complex phase III development scenario comprising more than two (K > 2) trials, that is, the evaluation of the PoSS of at least k₀ (k₀≤ K) trials from a program of K total trials. Copyright © 2013 John Wiley & Sons, Ltd.
Methods for estimating drought streamflow probabilities for Virginia streams

Science.gov (United States)

Austin, Samuel H.

2014-01-01

Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.
Bayesian optimization for computationally extensive probability distributions.

Science.gov (United States)

Tamura, Ryo; Hukushima, Koji

2018-01-01

An efficient method for finding a better maximizer of computationally extensive probability distributions is proposed on the basis of a Bayesian optimization technique. A key idea of the proposed method is to use extreme values of acquisition functions by Gaussian processes for the next training phase, which should be located near a local maximum or a global maximum of the probability distribution. Our Bayesian optimization technique is applied to the posterior distribution in the effective physical model estimation, which is a computationally extensive probability distribution. Even when the number of sampling points on the posterior distributions is fixed to be small, the Bayesian optimization provides a better maximizer of the posterior distributions in comparison to those by the random search method, the steepest descent method, or the Monte Carlo method. Furthermore, the Bayesian optimization improves the results efficiently by combining the steepest descent method and thus it is a powerful tool to search for a better maximizer of computationally extensive probability distributions.
The constraint rule of the maximum entropy principle

NARCIS (Netherlands)

Uffink, J.

1995-01-01

The principle of maximum entropy is a method for assigning values to probability distributions on the basis of partial information. In usual formulations of this and related methods of inference one assumes that this partial information takes the form of a constraint on allowed probability
THE MAXIMUM AMOUNTS OF RAINFALL FALLEN IN SHORT PERIODS OF TIME IN THE HILLY AREA OF CLUJ COUNTY - GENESIS, DISTRIBUTION AND PROBABILITY OF OCCURRENCE

Directory of Open Access Journals (Sweden)

BLAGA IRINA

2014-03-01

Full Text Available The maximum amounts of rainfall are usually characterized by high intensity, and their effects on the substrate are revealed, at slope level, by the deepening of the existing forms of torrential erosion and also by the formation of new ones, and by landslide processes. For the 1971-2000 period, for the weather stations in the hilly area of Cluj County: Cluj- Napoca, Dej, Huedin and Turda the highest values of rainfall amounts fallen in 24, 48 and 72 hours were analyzed and extracted, based on which the variation and the spatial and temporal distribution of the precipitation were analyzed. The annual probability of exceedance of maximum rainfall amounts fallen in short time intervals (24, 48 and 72 hours, based on thresholds and class values was determined, using climatological practices and the Hyfran program facilities.
Maximum Potential Score (MPS: An operating model for a successful customer-focused strategy.

Directory of Open Access Journals (Sweden)

Cabello González, José Manuel

2015-12-01

Full Text Available One of marketers’ chief objectives is to achieve customer loyalty, which is a key factor for profitable growth. Therefore, they need to develop a strategy that attracts and maintains customers, giving them adequate motives, both tangible (prices and promotions and intangible (personalized service and treatment, to satisfy a customer and make him loyal to the company. Finding a way to accurately measure satisfaction and customer loyalty is very important. With regard to typical Relationship Marketing measures, we can consider listening to customers, which can help to achieve a competitive sustainable advantage. Customer satisfaction surveys are essential tools for listening to customers. Short questionnaires have gained considerable acceptance among marketers as a means to achieve a customer satisfaction measure. Our research provides an indication of the benefits of a short questionnaire (one/three questions. We find that the number of questions survey is significantly related to the participation in the survey (Net Promoter Score or NPS. We also prove that a the three question survey is more likely to have more participants than a traditional survey (Maximum Potential Score or MPS . Our main goal is to analyse one method as a potential predictor of customer loyalty. Using surveys, we attempt to empirically establish the causal factors in determining the satisfaction of customers. This paper describes a maximum potential operating model that captures with a three questions survey, important elements for a successful customer-focused strategy. MPS may give us lower participation rates than NPS but important information that helps to convert unhappy customers or just satisfied customers, into loyal customers.
Probability in physics

CERN Document Server

Hemmo, Meir

2012-01-01

What is the role and meaning of probability in physical theory, in particular in two of the most successful theories of our age, quantum physics and statistical mechanics? Laws once conceived as universal and deterministic, such as Newton‘s laws of motion, or the second law of thermodynamics, are replaced in these theories by inherently probabilistic laws. This collection of essays by some of the world‘s foremost experts presents an in-depth analysis of the meaning of probability in contemporary physics. Among the questions addressed are: How are probabilities defined? Are they objective or subjective? What is their explanatory value? What are the differences between quantum and classical probabilities? The result is an informative and thought-provoking book for the scientifically inquisitive.
The numerical evaluation of maximum-likelihood estimates of the parameters for a mixture of normal distributions from partially identified samples

Science.gov (United States)

Walker, H. F.

1976-01-01

Likelihood equations determined by the two types of samples which are necessary conditions for a maximum-likelihood estimate are considered. These equations, suggest certain successive-approximations iterative procedures for obtaining maximum-likelihood estimates. These are generalized steepest ascent (deflected gradient) procedures. It is shown that, with probability 1 as N sub 0 approaches infinity (regardless of the relative sizes of N sub 0 and N sub 1, i=1,...,m), these procedures converge locally to the strongly consistent maximum-likelihood estimates whenever the step size is between 0 and 2. Furthermore, the value of the step size which yields optimal local convergence rates is bounded from below by a number which always lies between 1 and 2.
Probability, statistics, and queueing theory

CERN Document Server

Allen, Arnold O

1990-01-01

This is a textbook on applied probability and statistics with computer science applications for students at the upper undergraduate level. It may also be used as a self study book for the practicing computer science professional. The successful first edition of this book proved extremely useful to students who need to use probability, statistics and queueing theory to solve problems in other fields, such as engineering, physics, operations research, and management science. The book has also been successfully used for courses in queueing theory for operations research students. This second edit
High throughput nonparametric probability density estimation.

Science.gov (United States)

Farmer, Jenny; Jacobs, Donald

2018-01-01

In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity. Such an automated process for univariate data is implemented to achieve this goal by merging the maximum entropy method with single order statistics and maximum likelihood. The only required properties of the random variables are that they are continuous and that they are, or can be approximated as, independent and identically distributed. A quasi-log-likelihood function based on single order statistics for sampled uniform random data is used to empirically construct a sample size invariant universal scoring function. Then a probability density estimate is determined by iteratively improving trial cumulative distribution functions, where better estimates are quantified by the scoring function that identifies atypical fluctuations. This criterion resists under and over fitting data as an alternative to employing the Bayesian or Akaike information criterion. Multiple estimates for the probability density reflect uncertainties due to statistical fluctuations in random samples. Scaled quantile residual plots are also introduced as an effective diagnostic to visualize the quality of the estimated probability densities. Benchmark tests show that estimates for the probability density function (PDF) converge to the true PDF as sample size increases on particularly difficult test probability densities that include cases with discontinuities, multi-resolution scales, heavy tails, and singularities. These results indicate the method has general applicability for high throughput statistical inference.
Variable terrestrial GPS telemetry detection rates: Addressing the probability of successful acquisitions

Science.gov (United States)

Ironside, Kirsten E.; Mattson, David J.; Choate, David; Stoner, David; Arundel, Terry; Hansen, Jered R.; Theimer, Tad; Holton, Brandon; Jansen, Brian; Sexton, Joseph O.; Longshore, Kathleen M.; Edwards, Thomas C.; Peters, Michael

2017-01-01

Studies using global positioning system (GPS) telemetry rarely result in 100% fix success rates (FSR), which may bias datasets because data loss is systematic rather than a random process. Previous spatially explicit models developed to correct for sampling bias have been limited to small study areas, a small range of data loss, or were study-area specific. We modeled environmental effects on FSR from desert to alpine biomes, investigated the full range of potential data loss (0–100% FSR), and evaluated whether animal body position can contribute to lower FSR because of changes in antenna orientation based on GPS detection rates for 4 focal species: cougars (Puma concolor), desert bighorn sheep (Ovis canadensis nelsoni), Rocky Mountain elk (Cervus elaphus nelsoni), and mule deer (Odocoileus hemionus). Terrain exposure and height of over story vegetation were the most influential factors affecting FSR. Model evaluation showed a strong correlation (0.88) between observed and predicted FSR and no significant differences between predicted and observed FSRs using 2 independent validation datasets. We found that cougars and canyon-dwelling bighorn sheep may select for environmental features that influence their detectability by GPS technology, mule deer may select against these features, and elk appear to be nonselective. We observed temporal patterns in missed fixes only for cougars. We provide a model for cougars, predicting fix success by time of day that is likely due to circadian changes in collar orientation and selection of daybed sites. We also provide a model predicting the probability of GPS fix acquisitions given environmental conditions, which had a strong relationship (r 2 = 0.82) with deployed collar FSRs across species.
Joint probability safety assessment for NPP defense infrastructure against extreme external natural hazards

International Nuclear Information System (INIS)

Guilin, L.; Defu, L.; Huajun, L.; Fengqing, W.; Tao, Z.

2012-01-01

With the increasing tendency of natural hazards, the typhoon, hurricane and tropical Cyclone induced surge, wave, precipitation, flood and wind as extreme external loads menacing Nuclear Power Plants (NPP) in coastal and inland provinces of China. For all of planned, designed And constructed NPP the National Nuclear Safety Administration of China and IAEA recommended Probable Maximum Hurricane /Typhoon/(PMH/T), Probable Maximum Storm Surge (PMSS), Probable Maximum Flood (PMF), Design Basis Flood (DBF) as safety regulations for NPP defense infrastructures. This paper discusses the joint probability analysis of simultaneous occurrence typhoon induced extreme external hazards and compare with IAEA 2006-2009 recommended safety regulation design criteria for some NPP defense infrastructures along China coast. (authors)

A General Probability Formula of the Number of Location Areas' Boundaries Crossed by a Mobile Between Two Successive Call Arrivals

Institute of Scientific and Technical Information of China (English)

Yi-Hua Zhu; Ding-Hua Shi; Yong Xiong; Ji Gao; He-Zhi Luo

2004-01-01

Mobility management is a challenging topic in mobile computing environment. Studying the situation of mobiles crossing the boundaries of location areas is significant for evaluating the costs and performances of various location management strategies. Hitherto, several formulae were derived to describe the probability of the number of location areas' boundaries crossed by a mobile. Some of them were widely used in analyzing the costs and performances of mobility management strategies. Utilizing the density evolution method of vector Markov processes, we propose a general probability formula of the number of location areas' boundaries crossed by a mobile between two successive calls. Fortunately, several widely-used formulae are special cases of the proposed formula.
Wolf Attack Probability: A Theoretical Security Measure in Biometric Authentication Systems

Science.gov (United States)

Une, Masashi; Otsuka, Akira; Imai, Hideki

This paper will propose a wolf attack probability (WAP) as a new measure for evaluating security of biometric authentication systems. The wolf attack is an attempt to impersonate a victim by feeding “wolves” into the system to be attacked. The “wolf” means an input value which can be falsely accepted as a match with multiple templates. WAP is defined as a maximum success probability of the wolf attack with one wolf sample. In this paper, we give a rigorous definition of the new security measure which gives strength estimation of an individual biometric authentication system against impersonation attacks. We show that if one reestimates using our WAP measure, a typical fingerprint algorithm turns out to be much weaker than theoretically estimated by Ratha et al. Moreover, we apply the wolf attack to a finger-vein-pattern based algorithm. Surprisingly, we show that there exists an extremely strong wolf which falsely matches all templates for any threshold value.
Objective Bayesianism and the Maximum Entropy Principle

Directory of Open Access Journals (Sweden)

Jon Williamson

2013-09-01

Full Text Available Objective Bayesian epistemology invokes three norms: the strengths of our beliefs should be probabilities; they should be calibrated to our evidence of physical probabilities; and they should otherwise equivocate sufficiently between the basic propositions that we can express. The three norms are sometimes explicated by appealing to the maximum entropy principle, which says that a belief function should be a probability function, from all those that are calibrated to evidence, that has maximum entropy. However, the three norms of objective Bayesianism are usually justified in different ways. In this paper, we show that the three norms can all be subsumed under a single justification in terms of minimising worst-case expected loss. This, in turn, is equivalent to maximising a generalised notion of entropy. We suggest that requiring language invariance, in addition to minimising worst-case expected loss, motivates maximisation of standard entropy as opposed to maximisation of other instances of generalised entropy. Our argument also provides a qualified justification for updating degrees of belief by Bayesian conditionalisation. However, conditional probabilities play a less central part in the objective Bayesian account than they do under the subjective view of Bayesianism, leading to a reduced role for Bayes’ Theorem.
Encounter Probability of Individual Wave Height

DEFF Research Database (Denmark)

Liu, Z.; Burcharth, H. F.

1998-01-01

wave height corresponding to a certain exceedence probability within a structure lifetime (encounter probability), based on the statistical analysis of long-term extreme significant wave height. Then the design individual wave height is calculated as the expected maximum individual wave height...... associated with the design significant wave height, with the assumption that the individual wave heights follow the Rayleigh distribution. However, the exceedence probability of such a design individual wave height within the structure lifetime is unknown. The paper presents a method for the determination...... of the design individual wave height corresponding to an exceedence probability within the structure lifetime, given the long-term extreme significant wave height. The method can also be applied for estimation of the number of relatively large waves for fatigue analysis of constructions....
Maximum a posteriori probability estimates in infinite-dimensional Bayesian inverse problems

International Nuclear Information System (INIS)

Helin, T; Burger, M

2015-01-01

A demanding challenge in Bayesian inversion is to efficiently characterize the posterior distribution. This task is problematic especially in high-dimensional non-Gaussian problems, where the structure of the posterior can be very chaotic and difficult to analyse. Current inverse problem literature often approaches the problem by considering suitable point estimators for the task. Typically the choice is made between the maximum a posteriori (MAP) or the conditional mean (CM) estimate. The benefits of either choice are not well-understood from the perspective of infinite-dimensional theory. Most importantly, there exists no general scheme regarding how to connect the topological description of a MAP estimate to a variational problem. The recent results by Dashti and others (Dashti et al 2013 Inverse Problems 29 095017) resolve this issue for nonlinear inverse problems in Gaussian framework. In this work we improve the current understanding by introducing a novel concept called the weak MAP (wMAP) estimate. We show that any MAP estimate in the sense of Dashti et al (2013 Inverse Problems 29 095017) is a wMAP estimate and, moreover, how the wMAP estimate connects to a variational formulation in general infinite-dimensional non-Gaussian problems. The variational formulation enables to study many properties of the infinite-dimensional MAP estimate that were earlier impossible to study. In a recent work by the authors (Burger and Lucka 2014 Maximum a posteriori estimates in linear inverse problems with logconcave priors are proper bayes estimators preprint) the MAP estimator was studied in the context of the Bayes cost method. Using Bregman distances, proper convex Bayes cost functions were introduced for which the MAP estimator is the Bayes estimator. Here, we generalize these results to the infinite-dimensional setting. Moreover, we discuss the implications of our results for some examples of prior models such as the Besov prior and hierarchical prior. (paper)
Success of Chemotherapy in Soft Matter

OpenAIRE

Trifonova, I.; Kurteva, G.; Stefanov, S. Z.

2014-01-01

The success of chemotharapy in soft matter as a survival is found in the paper. Therefore, it is found the analogous tumor stretching force in soft matter; ultrasonography is performed for this tumor; restoration in soft matter with such a tumor is found; Bayes estimate of the probability of chemotherapy success is derived from the transferred chemical energy and from soft matter entropy; survival probability is juxtaposed to this probability of success.
Some simple applications of probability models to birth intervals

International Nuclear Information System (INIS)

Shrestha, G.

1987-07-01

An attempt has been made in this paper to apply some simple probability models to birth intervals under the assumption of constant fecundability and varying fecundability among women. The parameters of the probability models are estimated by using the method of moments and the method of maximum likelihood. (author). 9 refs, 2 tabs
An iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions

Science.gov (United States)

Peters, B. C., Jr.; Walker, H. F.

1978-01-01

This paper addresses the problem of obtaining numerically maximum-likelihood estimates of the parameters for a mixture of normal distributions. In recent literature, a certain successive-approximations procedure, based on the likelihood equations, was shown empirically to be effective in numerically approximating such maximum-likelihood estimates; however, the reliability of this procedure was not established theoretically. Here, we introduce a general iterative procedure, of the generalized steepest-ascent (deflected-gradient) type, which is just the procedure known in the literature when the step-size is taken to be 1. We show that, with probability 1 as the sample size grows large, this procedure converges locally to the strongly consistent maximum-likelihood estimate whenever the step-size lies between 0 and 2. We also show that the step-size which yields optimal local convergence rates for large samples is determined in a sense by the 'separation' of the component normal densities and is bounded below by a number between 1 and 2.
Probable Inference and Quantum Mechanics

International Nuclear Information System (INIS)

Grandy, W. T. Jr.

2009-01-01

In its current very successful interpretation the quantum theory is fundamentally statistical in nature. Although commonly viewed as a probability amplitude whose (complex) square is a probability, the wavefunction or state vector continues to defy consensus as to its exact meaning, primarily because it is not a physical observable. Rather than approach this problem directly, it is suggested that it is first necessary to clarify the precise role of probability theory in quantum mechanics, either as applied to, or as an intrinsic part of the quantum theory. When all is said and done the unsurprising conclusion is that quantum mechanics does not constitute a logic and probability unto itself, but adheres to the long-established rules of classical probability theory while providing a means within itself for calculating the relevant probabilities. In addition, the wavefunction is seen to be a description of the quantum state assigned by an observer based on definite information, such that the same state must be assigned by any other observer based on the same information, in much the same way that probabilities are assigned.
A three-step maximum a posteriori probability method for InSAR data inversion of coseismic rupture with application to the 14 April 2010 Mw 6.9 Yushu, China, earthquake

Science.gov (United States)

Sun, Jianbao; Shen, Zheng-Kang; Bürgmann, Roland; Wang, Min; Chen, Lichun; Xu, Xiwei

2013-08-01

develop a three-step maximum a posteriori probability method for coseismic rupture inversion, which aims at maximizing the a posterior probability density function (PDF) of elastic deformation solutions of earthquake rupture. The method originates from the fully Bayesian inversion and mixed linear-nonlinear Bayesian inversion methods and shares the same posterior PDF with them, while overcoming difficulties with convergence when large numbers of low-quality data are used and greatly improving the convergence rate using optimization procedures. A highly efficient global optimization algorithm, adaptive simulated annealing, is used to search for the maximum of a posterior PDF ("mode" in statistics) in the first step. The second step inversion approaches the "true" solution further using the Monte Carlo inversion technique with positivity constraints, with all parameters obtained from the first step as the initial solution. Then slip artifacts are eliminated from slip models in the third step using the same procedure of the second step, with fixed fault geometry parameters. We first design a fault model with 45° dip angle and oblique slip, and produce corresponding synthetic interferometric synthetic aperture radar (InSAR) data sets to validate the reliability and efficiency of the new method. We then apply this method to InSAR data inversion for the coseismic slip distribution of the 14 April 2010 Mw 6.9 Yushu, China earthquake. Our preferred slip model is composed of three segments with most of the slip occurring within 15 km depth and the maximum slip reaches 1.38 m at the surface. The seismic moment released is estimated to be 2.32e+19 Nm, consistent with the seismic estimate of 2.50e+19 Nm.
PTree: pattern-based, stochastic search for maximum parsimony phylogenies

OpenAIRE

Gregor, Ivan; Steinbr?ck, Lars; McHardy, Alice C.

2013-01-01

Phylogenetic reconstruction is vital to analyzing the evolutionary relationship of genes within and across populations of different species. Nowadays, with next generation sequencing technologies producing sets comprising thousands of sequences, robust identification of the tree topology, which is optimal according to standard criteria such as maximum parsimony, maximum likelihood or posterior probability, with phylogenetic inference methods is a computationally very demanding task. Here, we ...
An iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions, 2

Science.gov (United States)

Peters, B. C., Jr.; Walker, H. F.

1976-01-01

The problem of obtaining numerically maximum likelihood estimates of the parameters for a mixture of normal distributions is addressed. In recent literature, a certain successive approximations procedure, based on the likelihood equations, is shown empirically to be effective in numerically approximating such maximum-likelihood estimates; however, the reliability of this procedure was not established theoretically. Here, a general iterative procedure is introduced, of the generalized steepest-ascent (deflected-gradient) type, which is just the procedure known in the literature when the step-size is taken to be 1. With probability 1 as the sample size grows large, it is shown that this procedure converges locally to the strongly consistent maximum-likelihood estimate whenever the step-size lies between 0 and 2. The step-size which yields optimal local convergence rates for large samples is determined in a sense by the separation of the component normal densities and is bounded below by a number between 1 and 2.
The maximum entropy production and maximum Shannon information entropy in enzyme kinetics

Science.gov (United States)

Dobovišek, Andrej; Markovič, Rene; Brumen, Milan; Fajmut, Aleš

2018-04-01

We demonstrate that the maximum entropy production principle (MEPP) serves as a physical selection principle for the description of the most probable non-equilibrium steady states in simple enzymatic reactions. A theoretical approach is developed, which enables maximization of the density of entropy production with respect to the enzyme rate constants for the enzyme reaction in a steady state. Mass and Gibbs free energy conservations are considered as optimization constraints. In such a way computed optimal enzyme rate constants in a steady state yield also the most uniform probability distribution of the enzyme states. This accounts for the maximal Shannon information entropy. By means of the stability analysis it is also demonstrated that maximal density of entropy production in that enzyme reaction requires flexible enzyme structure, which enables rapid transitions between different enzyme states. These results are supported by an example, in which density of entropy production and Shannon information entropy are numerically maximized for the enzyme Glucose Isomerase.
Coronary ligation reduces maximum sustained swimming speed in Chinook salmon, Oncorhynchus tshawytscha

DEFF Research Database (Denmark)

Farrell, A P; Steffensen, J F

1987-01-01

The maximum aerobic swimming speed of Chinook salmon (Oncorhynchus tshawytscha) was measured before and after ligation of the coronary artery. Coronary artery ligation prevented blood flow to the compact layer of the ventricular myocardium, which represents 30% of the ventricular mass, and produced...... a statistically significant 35.5% reduction in maximum swimming speed. We conclude that the coronary circulation is important for maximum aerobic swimming and implicit in this conclusion is that maximum cardiac performance is probably necessary for maximum aerobic swimming performance....
Maximum-likelihood fitting of data dominated by Poisson statistical uncertainties

International Nuclear Information System (INIS)

Stoneking, M.R.; Den Hartog, D.J.

1996-06-01

The fitting of data by χ 2 -minimization is valid only when the uncertainties in the data are normally distributed. When analyzing spectroscopic or particle counting data at very low signal level (e.g., a Thomson scattering diagnostic), the uncertainties are distributed with a Poisson distribution. The authors have developed a maximum-likelihood method for fitting data that correctly treats the Poisson statistical character of the uncertainties. This method maximizes the total probability that the observed data are drawn from the assumed fit function using the Poisson probability function to determine the probability for each data point. The algorithm also returns uncertainty estimates for the fit parameters. They compare this method with a χ 2 -minimization routine applied to both simulated and real data. Differences in the returned fits are greater at low signal level (less than ∼20 counts per measurement). the maximum-likelihood method is found to be more accurate and robust, returning a narrower distribution of values for the fit parameters with fewer outliers
[Effect of stock abundance and environmental factors on the recruitment success of small yellow croaker in the East China Sea].

Science.gov (United States)

Liu, Zun-lei; Yuan, Xing-wei; Yang, Lin-lin; Yan, Li-ping; Zhang, Hui; Cheng, Jia-hua

2015-02-01

Multiple hypotheses are available to explain recruitment rate. Model selection methods can be used to identify the best model that supports a particular hypothesis. However, using a single model for estimating recruitment success is often inadequate for overexploited population because of high model uncertainty. In this study, stock-recruitment data of small yellow croaker in the East China Sea collected from fishery dependent and independent surveys between 1992 and 2012 were used to examine density-dependent effects on recruitment success. Model selection methods based on frequentist (AIC, maximum adjusted R2 and P-values) and Bayesian (Bayesian model averaging, BMA) methods were applied to identify the relationship between recruitment and environment conditions. Interannual variability of the East China Sea environment was indicated by sea surface temperature ( SST) , meridional wind stress (MWS), zonal wind stress (ZWS), sea surface pressure (SPP) and runoff of Changjiang River ( RCR). Mean absolute error, mean squared predictive error and continuous ranked probability score were calculated to evaluate the predictive performance of recruitment success. The results showed that models structures were not consistent based on three kinds of model selection methods, predictive variables of models were spawning abundance and MWS by AIC, spawning abundance by P-values, spawning abundance, MWS and RCR by maximum adjusted R2. The recruitment success decreased linearly with stock abundance (P recruitment success might be due to cannibalism or food competition. Meridional wind intensity showed marginally significant and positive effects on the recruitment success (P = 0.06), while runoff of Changjiang River showed a marginally negative effect (P = 0.07). Based on mean absolute error and continuous ranked probability score, predictive error associated with models obtained from BMA was the smallest amongst different approaches, while that from models selected based on the P
Estimation of flashover voltage probability of overhead line insulators under industrial pollution, based on maximum likelihood method

International Nuclear Information System (INIS)

Arab, M.N.; Ayaz, M.

2004-01-01

The performance of transmission line insulator is greatly affected by dust, fumes from industrial areas and saline deposit near the coast. Such pollutants in the presence of moisture form a coating on the surface of the insulator, which in turn allows the passage of leakage current. This leakage builds up to a point where flashover develops. The flashover is often followed by permanent failure of insulation resulting in prolong outages. With the increase in system voltage owing to the greater demand of electrical energy over the past few decades, the importance of flashover due to pollution has received special attention. The objective of the present work was to study the performance of overhead line insulators in the presence of contaminants such as induced salts. A detailed review of the literature and the mechanisms of insulator flashover due to the pollution are presented. Experimental investigations on the behavior of overhead line insulators under industrial salt contamination are carried out. A special fog chamber was designed in which the contamination testing of insulators was carried out. Flashover behavior under various degrees of contamination of insulators with the most common industrial fume components such as Nitrate and Sulphate compounds was studied. Substituting the normal distribution parameter in the probability distribution function based on maximum likelihood develops a statistical method. The method gives a high accuracy in the estimation of the 50% flashover voltage, which is then used to evaluate the critical flashover index at various contamination levels. The critical flashover index is a valuable parameter in insulation design for numerous applications. (author)
Maximum Entropy in Drug Discovery

Directory of Open Access Journals (Sweden)

Chih-Yuan Tseng

2014-07-01

Full Text Available Drug discovery applies multidisciplinary approaches either experimentally, computationally or both ways to identify lead compounds to treat various diseases. While conventional approaches have yielded many US Food and Drug Administration (FDA-approved drugs, researchers continue investigating and designing better approaches to increase the success rate in the discovery process. In this article, we provide an overview of the current strategies and point out where and how the method of maximum entropy has been introduced in this area. The maximum entropy principle has its root in thermodynamics, yet since Jaynes’ pioneering work in the 1950s, the maximum entropy principle has not only been used as a physics law, but also as a reasoning tool that allows us to process information in hand with the least bias. Its applicability in various disciplines has been abundantly demonstrated. We give several examples of applications of maximum entropy in different stages of drug discovery. Finally, we discuss a promising new direction in drug discovery that is likely to hinge on the ways of utilizing maximum entropy.
Maximum allowable load on wheeled mobile manipulators

International Nuclear Information System (INIS)

Habibnejad Korayem, M.; Ghariblu, H.

2003-01-01

This paper develops a computational technique for finding the maximum allowable load of mobile manipulator during a given trajectory. The maximum allowable loads which can be achieved by a mobile manipulator during a given trajectory are limited by the number of factors; probably the dynamic properties of mobile base and mounted manipulator, their actuator limitations and additional constraints applied to resolving the redundancy are the most important factors. To resolve extra D.O.F introduced by the base mobility, additional constraint functions are proposed directly in the task space of mobile manipulator. Finally, in two numerical examples involving a two-link planar manipulator mounted on a differentially driven mobile base, application of the method to determining maximum allowable load is verified. The simulation results demonstrates the maximum allowable load on a desired trajectory has not a unique value and directly depends on the additional constraint functions which applies to resolve the motion redundancy
Evidence for Truncated Exponential Probability Distribution of Earthquake Slip

KAUST Repository

Thingbaijam, Kiran Kumar; Mai, Paul Martin

2016-01-01

Earthquake ruptures comprise spatially varying slip on the fault surface, where slip represents the displacement discontinuity between the two sides of the rupture plane. In this study, we analyze the probability distribution of coseismic slip, which provides important information to better understand earthquake source physics. Although the probability distribution of slip is crucial for generating realistic rupture scenarios for simulation-based seismic and tsunami-hazard analysis, the statistical properties of earthquake slip have received limited attention so far. Here, we use the online database of earthquake source models (SRCMOD) to show that the probability distribution of slip follows the truncated exponential law. This law agrees with rupture-specific physical constraints limiting the maximum possible slip on the fault, similar to physical constraints on maximum earthquake magnitudes.We show the parameters of the best-fitting truncated exponential distribution scale with average coseismic slip. This scaling property reflects the control of the underlying stress distribution and fault strength on the rupture dimensions, which determines the average slip. Thus, the scale-dependent behavior of slip heterogeneity is captured by the probability distribution of slip. We conclude that the truncated exponential law accurately quantifies coseismic slip distribution and therefore allows for more realistic modeling of rupture scenarios. © 2016, Seismological Society of America. All rights reserverd.

Evidence for Truncated Exponential Probability Distribution of Earthquake Slip

KAUST Repository

Thingbaijam, Kiran K. S.

2016-07-13

Earthquake ruptures comprise spatially varying slip on the fault surface, where slip represents the displacement discontinuity between the two sides of the rupture plane. In this study, we analyze the probability distribution of coseismic slip, which provides important information to better understand earthquake source physics. Although the probability distribution of slip is crucial for generating realistic rupture scenarios for simulation-based seismic and tsunami-hazard analysis, the statistical properties of earthquake slip have received limited attention so far. Here, we use the online database of earthquake source models (SRCMOD) to show that the probability distribution of slip follows the truncated exponential law. This law agrees with rupture-specific physical constraints limiting the maximum possible slip on the fault, similar to physical constraints on maximum earthquake magnitudes.We show the parameters of the best-fitting truncated exponential distribution scale with average coseismic slip. This scaling property reflects the control of the underlying stress distribution and fault strength on the rupture dimensions, which determines the average slip. Thus, the scale-dependent behavior of slip heterogeneity is captured by the probability distribution of slip. We conclude that the truncated exponential law accurately quantifies coseismic slip distribution and therefore allows for more realistic modeling of rupture scenarios. © 2016, Seismological Society of America. All rights reserverd.
Last Glacial Maximum CO2 and d13C successfully reconciled

NARCIS (Netherlands)

Bouttes, N.; Paillard, D.; Roche, D.M.V.A.P.; Brovkin, V.; Bopp, L.

2011-01-01

During the Last Glacial Maximum (LGM, ∼21,000 years ago) the cold climate was strongly tied to low atmospheric CO2 concentration (∼190 ppm). Although it is generally assumed that this low CO2 was due to an expansion of the oceanic carbon reservoir, simulating the glacial level
Incidents in nuclear research reactor examined by deterministic probability and probabilistic safety analysis

International Nuclear Information System (INIS)

Lopes, Valdir Maciel

2010-01-01

This study aims to evaluate the potential risks submitted by the incidents in nuclear research reactors. For its development, two databases of the International Atomic Energy Agency, IAEA, were used, the Incident Report System for Research Reactor and Research Reactor Data Base. For this type of assessment was used the Probabilistic Safety Analysis (PSA), within a confidence level of 90% and the Deterministic Probability Analysis (DPA). To obtain the results of calculations of probabilities for PSA, were used the theory and equations in the paper IAEA TECDOC - 636. The development of the calculations of probabilities for PSA was used the program Scilab version 5.1.1, free access, executable on Windows and Linux platforms. A specific program to get the results of probability was developed within the main program Scilab 5.1.1., for two distributions Fischer and Chi-square, both with the confidence level of 90%. Using the Sordi equations and Origin 6.0 program, were obtained the maximum admissible doses related to satisfy the risk limits established by the International Commission on Radiological Protection, ICRP, and were also obtained these maximum doses graphically (figure 1) resulting from the calculations of probabilities x maximum admissible doses. It was found that the reliability of the results of probability is related to the operational experience (reactor x year and fractions) and that the larger it is, greater the confidence in the outcome. Finally, a suggested list of future work to complement this paper was gathered. (author)
Maximum phytoplankton concentrations in the sea

DEFF Research Database (Denmark)

Jackson, G.A.; Kiørboe, Thomas

2008-01-01

A simplification of plankton dynamics using coagulation theory provides predictions of the maximum algal concentration sustainable in aquatic systems. These predictions have previously been tested successfully against results from iron fertilization experiments. We extend the test to data collect...
Assignment of probability distributions for parameters in the 1996 performance assessment for the Waste Isolation Pilot Plant. Part 1: description of process

International Nuclear Information System (INIS)

Rechard, Rob P.; Tierney, Martin S.

2005-01-01

A managed process was used to consistently and traceably develop probability distributions for parameters representing epistemic uncertainty in four preliminary and the final 1996 performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP). The key to the success of the process was the use of a three-member team consisting of a Parameter Task Leader, PA Analyst, and Subject Matter Expert. This team, in turn, relied upon a series of guidelines for selecting distribution types. The primary function of the guidelines was not to constrain the actual process of developing a parameter distribution but rather to establish a series of well-defined steps where recognized methods would be consistently applied to all parameters. An important guideline was to use a small set of distributions satisfying the maximum entropy formalism. Another important guideline was the consistent use of the log transform for parameters with large ranges (i.e. maximum/minimum>10 3 ). A parameter development team assigned 67 probability density functions (PDFs) in the 1989 PA and 236 PDFs in the 1996 PA using these and other guidelines described
Maximum-confidence discrimination among symmetric qudit states

International Nuclear Information System (INIS)

Jimenez, O.; Solis-Prosser, M. A.; Delgado, A.; Neves, L.

2011-01-01

We study the maximum-confidence (MC) measurement strategy for discriminating among nonorthogonal symmetric qudit states. Restricting to linearly dependent and equally likely pure states, we find the optimal positive operator valued measure (POVM) that maximizes our confidence in identifying each state in the set and minimizes the probability of obtaining inconclusive results. The physical realization of this POVM is completely determined and it is shown that after an inconclusive outcome, the input states may be mapped into a new set of equiprobable symmetric states, restricted, however, to a subspace of the original qudit Hilbert space. By applying the MC measurement again onto this new set, we can still gain some information about the input states, although with less confidence than before. This leads us to introduce the concept of sequential maximum-confidence (SMC) measurements, where the optimized MC strategy is iterated in as many stages as allowed by the input set, until no further information can be extracted from an inconclusive result. Within each stage of this measurement our confidence in identifying the input states is the highest possible, although it decreases from one stage to the next. In addition, the more stages we accomplish within the maximum allowed, the higher will be the probability of correct identification. We will discuss an explicit example of the optimal SMC measurement applied in the discrimination among four symmetric qutrit states and propose an optical network to implement it.
Combining Experiments and Simulations Using the Maximum Entropy Principle

DEFF Research Database (Denmark)

Boomsma, Wouter; Ferkinghoff-Borg, Jesper; Lindorff-Larsen, Kresten

2014-01-01

are not in quantitative agreement with experimental data. The principle of maximum entropy is a general procedure for constructing probability distributions in the light of new data, making it a natural tool in cases when an initial model provides results that are at odds with experiments. The number of maximum entropy...... in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results....... Three very recent papers have explored this problem using the maximum entropy approach, providing both new theoretical and practical insights to the problem. We highlight each of these contributions in turn and conclude with a discussion on remaining challenges....
INVESTIGATION OF INFLUENCE OF ENCODING FUNCTION COMPLEXITY ON DISTRIBUTION OF ERROR MASKING PROBABILITY

Directory of Open Access Journals (Sweden)

A. B. Levina

2016-03-01

Full Text Available Error detection codes are mechanisms that enable robust delivery of data in unreliable communication channels and devices. Unreliable channels and devices are error-prone objects. Respectively, error detection codes allow detecting such errors. There are two classes of error detecting codes - classical codes and security-oriented codes. The classical codes have high percentage of detected errors; however, they have a high probability to miss an error in algebraic manipulation. In order, security-oriented codes are codes with a small Hamming distance and high protection to algebraic manipulation. The probability of error masking is a fundamental parameter of security-oriented codes. A detailed study of this parameter allows analyzing the behavior of the error-correcting code in the case of error injection in the encoding device. In order, the complexity of the encoding function plays an important role in the security-oriented codes. Encoding functions with less computational complexity and a low probability of masking are the best protection of encoding device against malicious acts. This paper investigates the influence of encoding function complexity on the error masking probability distribution. It will be shownthat the more complex encoding function reduces the maximum of error masking probability. It is also shown in the paper that increasing of the function complexity changes the error masking probability distribution. In particular, increasing of computational complexity decreases the difference between the maximum and average value of the error masking probability. Our resultshave shown that functions with greater complexity have smoothed maximums of error masking probability, which significantly complicates the analysis of error-correcting code by attacker. As a result, in case of complex encoding function the probability of the algebraic manipulation is reduced. The paper discusses an approach how to measure the error masking
Bayesian probability theory applications in the physical sciences

CERN Document Server

Linden, Wolfgang von der; Toussaint, Udo von

2014-01-01

From the basics to the forefront of modern research, this book presents all aspects of probability theory, statistics and data analysis from a Bayesian perspective for physicists and engineers. The book presents the roots, applications and numerical implementation of probability theory, and covers advanced topics such as maximum entropy distributions, stochastic processes, parameter estimation, model selection, hypothesis testing and experimental design. In addition, it explores state-of-the art numerical techniques required to solve demanding real-world problems. The book is ideal for students and researchers in physical sciences and engineering.
Statistical learning of action: the role of conditional probability.

Science.gov (United States)

Meyer, Meredith; Baldwin, Dare

2011-12-01

Identification of distinct units within a continuous flow of human action is fundamental to action processing. Such segmentation may rest in part on statistical learning. In a series of four experiments, we examined what types of statistics people can use to segment a continuous stream involving many brief, goal-directed action elements. The results of Experiment 1 showed no evidence for sensitivity to conditional probability, whereas Experiment 2 displayed learning based on joint probability. In Experiment 3, we demonstrated that additional exposure to the input failed to engender sensitivity to conditional probability. However, the results of Experiment 4 showed that a subset of adults-namely, those more successful at identifying actions that had been seen more frequently than comparison sequences-were also successful at learning conditional-probability statistics. These experiments help to clarify the mechanisms subserving processing of intentional action, and they highlight important differences from, as well as similarities to, prior studies of statistical learning in other domains, including language.
Simulation of Daily Weather Data Using Theoretical Probability Distributions.

Science.gov (United States)

Bruhn, J. A.; Fry, W. E.; Fick, G. W.

1980-09-01

A computer simulation model was constructed to supply daily weather data to a plant disease management model for potato late blight. In the weather model Monte Carlo techniques were employed to generate daily values of precipitation, maximum temperature, minimum temperature, minimum relative humidity and total solar radiation. Each weather variable is described by a known theoretical probability distribution but the values of the parameters describing each distribution are dependent on the occurrence of rainfall. Precipitation occurrence is described by a first-order Markov chain. The amount of rain, given that rain has occurred, is described by a gamma probability distribution. Maximum and minimum temperature are simulated with a trivariate normal probability distribution involving maximum temperature on the previous day, maximum temperature on the current day and minimum temperature on the current day. Parameter values for this distribution are dependent on the occurrence of rain on the previous day. Both minimum relative humidity and total solar radiation are assumed to be normally distributed. The values of the parameters describing the distribution of minimum relative humidity is dependent on rainfall occurrence on the previous day and current day. Parameter values for total solar radiation are dependent on the occurrence of rain on the current day. The assumptions made during model construction were found to be appropriate for actual weather data from Geneva, New York. The performance of the weather model was evaluated by comparing the cumulative frequency distributions of simulated weather data with the distributions of actual weather data from Geneva, New York and Fort Collins, Colorado. For each location, simulated weather data were similar to actual weather data in terms of mean response, variability and autocorrelation. The possible applications of this model when used with models of other components of the agro-ecosystem are discussed.
Probability as a Physical Motive

Directory of Open Access Journals (Sweden)

Peter Martin

2007-04-01

Full Text Available Recent theoretical progress in nonequilibrium thermodynamics, linking thephysical principle of Maximum Entropy Production (Ã¢Â€ÂœMEPÃ¢Â€Â to the information-theoreticalÃ¢Â€ÂœMaxEntÃ¢Â€Â principle of scientific inference, together with conjectures from theoreticalphysics that there may be no fundamental causal laws but only probabilities for physicalprocesses, and from evolutionary theory that biological systems expand Ã¢Â€Âœthe adjacentpossibleÃ¢Â€Â as rapidly as possible, all lend credence to the proposition that probability shouldbe recognized as a fundamental physical motive. It is further proposed that spatial order andtemporal order are two aspects of the same thing, and that this is the essence of the secondlaw of thermodynamics.
Probability, Statistics, and Stochastic Processes

CERN Document Server

Olofsson, Peter

2012-01-01

This book provides a unique and balanced approach to probability, statistics, and stochastic processes. Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area. The Second Edition features new coverage of analysis of variance (ANOVA), consistency and efficiency of estimators, asymptotic theory for maximum likelihood estimators, empirical distribution function and the Kolmogorov-Smirnov test, general linear models, multiple comparisons, Markov chain Monte Carlo (MCMC), Brownian motion, martingales, and
Bayesian probability theory and inverse problems

International Nuclear Information System (INIS)

Kopec, S.

1994-01-01

Bayesian probability theory is applied to approximate solving of the inverse problems. In order to solve the moment problem with the noisy data, the entropic prior is used. The expressions for the solution and its error bounds are presented. When the noise level tends to zero, the Bayesian solution tends to the classic maximum entropy solution in the L 2 norm. The way of using spline prior is also shown. (author)
Reliability of structures by using probability and fatigue theories

International Nuclear Information System (INIS)

Lee, Ouk Sub; Kim, Dong Hyeok; Park, Yeon Chang

2008-01-01

Methodologies to calculate failure probability and to estimate the reliability of fatigue loaded structures are developed. The applicability of the methodologies is evaluated with the help of the fatigue crack growth models suggested by Paris and Walker. The probability theories such as the FORM (first order reliability method), the SORM (second order reliability method) and the MCS (Monte Carlo simulation) are utilized. It is found that the failure probability decreases with the increase of the design fatigue life and the applied minimum stress, the decrease of the initial edge crack size, the applied maximum stress and the slope of Paris equation. Furthermore, according to the sensitivity analysis of random variables, the slope of Pairs equation affects the failure probability dominantly among other random variables in the Paris and the Walker models
Fluctuating States: What is the Probability of a Thermodynamical Transition?

Directory of Open Access Journals (Sweden)

Álvaro M. Alhambra

2016-10-01

Full Text Available If the second law of thermodynamics forbids a transition from one state to another, then it is still possible to make the transition happen by using a sufficient amount of work. But if we do not have access to this amount of work, can the transition happen probabilistically? In the thermodynamic limit, this probability tends to zero, but here we find that for finite-sized and quantum systems it can be finite. We compute the maximum probability of a transition or a thermodynamical fluctuation from any initial state to any final state and show that this maximum can be achieved for any final state that is block diagonal in the energy eigenbasis. We also find upper and lower bounds on this transition probability, in terms of the work of transition. As a by-product, we introduce a finite set of thermodynamical monotones related to the thermomajorization criteria which governs state transitions and compute the work of transition in terms of them. The trade-off between the probability of a transition and any partial work added to aid in that transition is also considered. Our results have applications in entanglement theory, and we find the amount of entanglement required (or gained when transforming one pure entangled state into any other.
Deference to the attorney general? The probability of success of the AG on the direct actions of unconstitutionality

Directory of Open Access Journals (Sweden)

Ivar Alberto Martins Hartmann

2016-01-01

Full Text Available The Brazilian equivalent of the Attorney General, as a brief historical analysis shows, plays an essential role in concentrated constitutional review. However, empirical studies of its performance remain scarce. Our goal is to test the AGs track record in Direct Actions of Unconstitutionality (ADIs at the Brazilian Supreme Court. We use a data set obtained from the Supreme Court in Numbers project’s database in order to run regressions with different models. The hypothesis we tested is that there is no statistically significant relationship between the performance of the AG as plaintiff in concentrated constitutional review and the outcome of the cases. This hypothesis was found to be disproved: ADIs started by the AG, as well as those proposed by representatives of the Executive branch, have, in fact, greater statistical probability of success.
PROCOPE, Collision Probability in Pin Clusters and Infinite Rod Lattices

International Nuclear Information System (INIS)

Amyot, L.; Daolio, C.; Benoist, P.

1984-01-01

1 - Nature of physical problem solved: Calculation of directional collision probabilities in pin clusters and infinite rod lattices. 2 - Method of solution: a) Gauss integration of analytical expressions for collision probabilities. b) alternately, an approximate closed expression (not involving integrals) may be used for pin-to-pin interactions. 3 - Restrictions on the complexity of the problem: number of fuel pins must be smaller than 62; maximum number of groups of symmetry is 300
What a successful grasp tells about the success chances of grasps in its vicinity

DEFF Research Database (Denmark)

Bodenhagen, Leon; Detry, Renaud; Piater, Justus

2011-01-01

Infants gradually improve their grasping competences, both in terms of motor abilities as well as in terms of the internal shape grasp representations. Grasp densities provide a statistical model of such an internal learning process. In the concept of grasp densities, kernel density estimation...... probabilities representing grasp success in the neighborhood of a successful grasp. The anisotropy has been determined utilizing a simulation environment that allowed for evaluation of large scale experiments. The anisotropic kernel has been fitted to the conditional probabilities obtained from the experiments...
Sur les estimateurs du maximum de vraisemblance dans les mod& ...

African Journals Online (AJOL)

Abstract. We are interested in the existence and uniqueness of maximum likelihood estimators of parameters in the two multiplicative regression models, with Poisson or negative binomial probability distributions. Following its work on the multiplicative Poisson model with two factors without repeated measures, Haberman ...

Geometry of q-Exponential Family of Probability Distributions

Directory of Open Access Journals (Sweden)

Shun-ichi Amari

2011-06-01

Full Text Available The Gibbs distribution of statistical physics is an exponential family of probability distributions, which has a mathematical basis of duality in the form of the Legendre transformation. Recent studies of complex systems have found lots of distributions obeying the power law rather than the standard Gibbs type distributions. The Tsallis q-entropy is a typical example capturing such phenomena. We treat the q-Gibbs distribution or the q-exponential family by generalizing the exponential function to the q-family of power functions, which is useful for studying various complex or non-standard physical phenomena. We give a new mathematical structure to the q-exponential family different from those previously given. It has a dually flat geometrical structure derived from the Legendre transformation and the conformal geometry is useful for understanding it. The q-version of the maximum entropy theorem is naturally induced from the q-Pythagorean theorem. We also show that the maximizer of the q-escort distribution is a Bayesian MAP (Maximum A posteriori Probability estimator.
Maximizing probable oil field profit: uncertainties on well spacing

International Nuclear Information System (INIS)

MacKay, J.A.; Lerche, I.

1997-01-01

The influence of uncertainties in field development costs, well costs, lifting costs, selling price, discount factor, and oil field reserves are evaluated for their impact on assessing probable ranges of uncertainty on present day worth (PDW), oil field lifetime τ 2/3 , optimum number of wells (OWI), and the minimum (n-) and maximum (n+) number of wells to produce a PDW ≥ O. The relative importance of different factors in contributing to the uncertainties in PDW, τ 2/3 , OWI, nsub(-) and nsub(+) is also analyzed. Numerical illustrations indicate how the maximum PDW depends on the ranges of parameter values, drawn from probability distributions using Monte Carlo simulations. In addition, the procedure illustrates the relative importance of contributions of individual factors to the total uncertainty, so that one can assess where to place effort to improve ranges of uncertainty; while the volatility of each estimate allows one to determine when such effort is needful. (author)
Modelling streambank erosion potential using maximum entropy in a central Appalachian watershed

Directory of Open Access Journals (Sweden)

J. Pitchford

2015-03-01

Full Text Available We used maximum entropy to model streambank erosion potential (SEP in a central Appalachian watershed to help prioritize sites for management. Model development included measuring erosion rates, application of a quantitative approach to locate Target Eroding Areas (TEAs, and creation of maps of boundary conditions. We successfully constructed a probability distribution of TEAs using the program Maxent. All model evaluation procedures indicated that the model was an excellent predictor, and that the major environmental variables controlling these processes were streambank slope, soil characteristics, bank position, and underlying geology. A classification scheme with low, moderate, and high levels of SEP derived from logistic model output was able to differentiate sites with low erosion potential from sites with moderate and high erosion potential. A major application of this type of modelling framework is to address uncertainty in stream restoration planning, ultimately helping to bridge the gap between restoration science and practice.
Applications of the maximum entropy principle in nuclear physics

International Nuclear Information System (INIS)

Froehner, F.H.

1990-01-01

Soon after the advent of information theory the principle of maximum entropy was recognized as furnishing the missing rationale for the familiar rules of classical thermodynamics. More recently it has also been applied successfully in nuclear physics. As an elementary example we derive a physically meaningful macroscopic description of the spectrum of neutrons emitted in nuclear fission, and compare the well known result with accurate data on 252 Cf. A second example, derivation of an expression for resonance-averaged cross sections for nuclear reactions like scattering or fission, is less trivial. Entropy maximization, constrained by given transmission coefficients, yields probability distributions for the R- and S-matrix elements, from which average cross sections can be calculated. If constrained only by the range of the spectrum of compound-nuclear levels it produces the Gaussian Orthogonal Ensemble (GOE) of Hamiltonian matrices that again yields expressions for average cross sections. Both avenues give practically the same numbers in spite of the quite different cross section formulae. These results were employed in a new model-aided evaluation of the 238 U neutron cross sections in the unresolved resonance region. (orig.) [de
Probability Judgements in Multi-Stage Problems : Experimental Evidence of Systematic Biases

NARCIS (Netherlands)

Gneezy, U.

1996-01-01

We report empirical evidence that in problems of random walk with positive drift, bounded rationality leads individuals to under-estimate the probability of success in the long run.In particular, individuals who were given the stage by stage probability distribution failed to aggregate this
On the maximum-entropy method for kinetic equation of radiation, particle and gas

International Nuclear Information System (INIS)

El-Wakil, S.A.; Madkour, M.A.; Degheidy, A.R.; Machali, H.M.

1995-01-01

The maximum-entropy approach is used to calculate some problems in radiative transfer and reactor physics such as the escape probability, the emergent and transmitted intensities for a finite slab as well as the emergent intensity for a semi-infinite medium. Also, it is employed to solve problems involving spherical geometry, such as luminosity (the total energy emitted by a sphere), neutron capture probability and the albedo problem. The technique is also employed in the kinetic theory of gases to calculate the Poiseuille flow and thermal creep of a rarefied gas between two plates. Numerical calculations are achieved and compared with the published data. The comparisons demonstrate that the maximum-entropy results are good in agreement with the exact ones. (orig.)
On an Objective Basis for the Maximum Entropy Principle

Directory of Open Access Journals (Sweden)

David J. Miller

2015-01-01

Full Text Available In this letter, we elaborate on some of the issues raised by a recent paper by Neapolitan and Jiang concerning the maximum entropy (ME principle and alternative principles for estimating probabilities consistent with known, measured constraint information. We argue that the ME solution for the “problematic” example introduced by Neapolitan and Jiang has stronger objective basis, rooted in results from information theory, than their alternative proposed solution. We also raise some technical concerns about the Bayesian analysis in their work, which was used to independently support their alternative to the ME solution. The letter concludes by noting some open problems involving maximum entropy statistical inference.
Probability, statistics, and computational science.

Science.gov (United States)

Beerenwinkel, Niko; Siebourg, Juliane

2012-01-01

In this chapter, we review basic concepts from probability theory and computational statistics that are fundamental to evolutionary genomics. We provide a very basic introduction to statistical modeling and discuss general principles, including maximum likelihood and Bayesian inference. Markov chains, hidden Markov models, and Bayesian network models are introduced in more detail as they occur frequently and in many variations in genomics applications. In particular, we discuss efficient inference algorithms and methods for learning these models from partially observed data. Several simple examples are given throughout the text, some of which point to models that are discussed in more detail in subsequent chapters.
Can the maximum entropy principle be explained as a consistency requirement?

NARCIS (Netherlands)

Uffink, J.

1997-01-01

The principle of maximum entropy is a general method to assign values to probability distributions on the basis of partial information. This principle, introduced by Jaynes in 1957, forms an extension of the classical principle of insufficient reason. It has been further generalized, both in
Maximum parsimony on subsets of taxa.

Science.gov (United States)

Fischer, Mareike; Thatte, Bhalchandra D

2009-09-21

In this paper we investigate mathematical questions concerning the reliability (reconstruction accuracy) of Fitch's maximum parsimony algorithm for reconstructing the ancestral state given a phylogenetic tree and a character. In particular, we consider the question whether the maximum parsimony method applied to a subset of taxa can reconstruct the ancestral state of the root more accurately than when applied to all taxa, and we give an example showing that this indeed is possible. A surprising feature of our example is that ignoring a taxon closer to the root improves the reliability of the method. On the other hand, in the case of the two-state symmetric substitution model, we answer affirmatively a conjecture of Li, Steel and Zhang which states that under a molecular clock the probability that the state at a single taxon is a correct guess of the ancestral state is a lower bound on the reconstruction accuracy of Fitch's method applied to all taxa.
Reactor materials program process water component failure probability

International Nuclear Information System (INIS)

Daugherty, W. L.

1988-01-01

The maximum rate loss of coolant accident for the Savannah River Production Reactors is presently specified as the abrupt double-ended guillotine break (DEGB) of a large process water pipe. This accident is not considered credible in light of the low applied stresses and the inherent ductility of the piping materials. The Reactor Materials Program was initiated to provide the technical basis for an alternate, credible maximum rate LOCA. The major thrust of this program is to develop an alternate worst case accident scenario by deterministic means. In addition, the probability of a DEGB is also being determined; to show that in addition to being mechanistically incredible, it is also highly improbable. The probability of a DEGB of the process water piping is evaluated in two parts: failure by direct means, and indirectly-induced failure. These two areas have been discussed in other reports. In addition, the frequency of a large bread (equivalent to a DEGB) in other process water system components is assessed. This report reviews the large break frequency for each component as well as the overall large break frequency for the reactor system
Probability of seeing increases saccadic readiness.

Directory of Open Access Journals (Sweden)

Thérèse Collins

Full Text Available Associating movement directions or endpoints with monetary rewards or costs influences movement parameters in humans, and associating movement directions or endpoints with food reward influences movement parameters in non-human primates. Rewarded movements are facilitated relative to non-rewarded movements. The present study examined to what extent successful foveation facilitated saccadic eye movement behavior, with the hypothesis that foveation may constitute an informational reward. Human adults performed saccades to peripheral targets that either remained visible after saccade completion or were extinguished, preventing visual feedback. Saccades to targets that were systematically extinguished were slower and easier to inhibit than saccades to targets that afforded successful foveation, and this effect was modulated by the probability of successful foveation. These results suggest that successful foveation facilitates behavior, and that obtaining the expected sensory consequences of a saccadic eye movement may serve as a reward for the oculomotor system.
Electrofishing capture probability of smallmouth bass in streams

Science.gov (United States)

Dauwalter, D.C.; Fisher, W.L.

2007-01-01

Abundance estimation is an integral part of understanding the ecology and advancing the management of fish populations and communities. Mark-recapture and removal methods are commonly used to estimate the abundance of stream fishes. Alternatively, abundance can be estimated by dividing the number of individuals sampled by the probability of capture. We conducted a mark-recapture study and used multiple repeated-measures logistic regression to determine the influence of fish size, sampling procedures, and stream habitat variables on the cumulative capture probability for smallmouth bass Micropterus dolomieu in two eastern Oklahoma streams. The predicted capture probability was used to adjust the number of individuals sampled to obtain abundance estimates. The observed capture probabilities were higher for larger fish and decreased with successive electrofishing passes for larger fish only. Model selection suggested that the number of electrofishing passes, fish length, and mean thalweg depth affected capture probabilities the most; there was little evidence for any effect of electrofishing power density and woody debris density on capture probability. Leave-one-out cross validation showed that the cumulative capture probability model predicts smallmouth abundance accurately. ?? Copyright by the American Fisheries Society 2007.
Maximum known stages and discharges of New York streams and their annual exceedance probabilities through September 2011

Science.gov (United States)

Wall, Gary R.; Murray, Patricia M.; Lumia, Richard; Suro, Thomas P.

2014-01-01

Maximum known stages and discharges at 1,400 sites on 796 streams within New York are tabulated. Stage data are reported in feet. Discharges are reported as cubic feet per second and in cubic feet per second per square mile. Drainage areas range from 0.03 to 298,800 square miles; excluding the three sites with larger drainage areas on the St. Lawrence and Niagara Rivers, which drain the Great Lakes, the maximum drainage area is 8,288 square miles (Hudson River at Albany). Most data were obtained from U.S. Geological Survey (USGS) compilations and records, but some were provided by State, local, and other Federal agencies and by private organizations. The stage and discharge information is grouped by major drainage basins and U.S. Geological Survey site number, in downstream order. Site locations and their associated drainage area, period(s) of record, stage and discharge data, and flood-frequency statistics are compiled in a Microsoft Excel spreadsheet. Flood frequencies were derived for 1,238 sites by using methods described in Bulletin 17B (Interagency Advisory Committee on Water Data, 1982), Ries and Crouse (2002), and Lumia and others (2006). Curves that “envelope” maximum discharges within their range of drainage areas were developed for each of six flood-frequency hydrologic regions and for sites on Long Island, as well as for the State of New York; the New York curve was compared with a curve derived from a plot of maximum known discharges throughout the United States. Discharges represented by the national curve range from at least 2.7 to 4.9 times greater than those represented by the New York curve for drainage areas of 1.0 and 1,000 square miles. The relative magnitudes of discharge and runoff in the six hydrologic regions of New York and Long Island suggest the largest known discharges per square mile are in the southern part of western New York and the Catskill Mountain area, and the smallest are on Long Island.
Generalized Probability-Probability Plots

NARCIS (Netherlands)

Mushkudiani, N.A.; Einmahl, J.H.J.

2004-01-01

We introduce generalized Probability-Probability (P-P) plots in order to study the one-sample goodness-of-fit problem and the two-sample problem, for real valued data.These plots, that are constructed by indexing with the class of closed intervals, globally preserve the properties of classical P-P
Quantum Probabilities as Behavioral Probabilities

Directory of Open Access Journals (Sweden)

Vyacheslav I. Yukalov

2017-03-01

Full Text Available We demonstrate that behavioral probabilities of human decision makers share many common features with quantum probabilities. This does not imply that humans are some quantum objects, but just shows that the mathematics of quantum theory is applicable to the description of human decision making. The applicability of quantum rules for describing decision making is connected with the nontrivial process of making decisions in the case of composite prospects under uncertainty. Such a process involves deliberations of a decision maker when making a choice. In addition to the evaluation of the utilities of considered prospects, real decision makers also appreciate their respective attractiveness. Therefore, human choice is not based solely on the utility of prospects, but includes the necessity of resolving the utility-attraction duality. In order to justify that human consciousness really functions similarly to the rules of quantum theory, we develop an approach defining human behavioral probabilities as the probabilities determined by quantum rules. We show that quantum behavioral probabilities of humans do not merely explain qualitatively how human decisions are made, but they predict quantitative values of the behavioral probabilities. Analyzing a large set of empirical data, we find good quantitative agreement between theoretical predictions and observed experimental data.
Probability Aggregates in Probability Answer Set Programming

OpenAIRE

Saad, Emad

2013-01-01

Probability answer set programming is a declarative programming that has been shown effective for representing and reasoning about a variety of probability reasoning tasks. However, the lack of probability aggregates, e.g. {\\em expected values}, in the language of disjunctive hybrid probability logic programs (DHPP) disallows the natural and concise representation of many interesting problems. In this paper, we extend DHPP to allow arbitrary probability aggregates. We introduce two types of p...
Predictive probability methods for interim monitoring in clinical trials with longitudinal outcomes.

Science.gov (United States)

Zhou, Ming; Tang, Qi; Lang, Lixin; Xing, Jun; Tatsuoka, Kay

2018-04-17

In clinical research and development, interim monitoring is critical for better decision-making and minimizing the risk of exposing patients to possible ineffective therapies. For interim futility or efficacy monitoring, predictive probability methods are widely adopted in practice. Those methods have been well studied for univariate variables. However, for longitudinal studies, predictive probability methods using univariate information from only completers may not be most efficient, and data from on-going subjects can be utilized to improve efficiency. On the other hand, leveraging information from on-going subjects could allow an interim analysis to be potentially conducted once a sufficient number of subjects reach an earlier time point. For longitudinal outcomes, we derive closed-form formulas for predictive probabilities, including Bayesian predictive probability, predictive power, and conditional power and also give closed-form solutions for predictive probability of success in a future trial and the predictive probability of success of the best dose. When predictive probabilities are used for interim monitoring, we study their distributions and discuss their analytical cutoff values or stopping boundaries that have desired operating characteristics. We show that predictive probabilities utilizing all longitudinal information are more efficient for interim monitoring than that using information from completers only. To illustrate their practical application for longitudinal data, we analyze 2 real data examples from clinical trials. Copyright © 2018 John Wiley & Sons, Ltd.
On the maximum of wave surface of sea waves

Energy Technology Data Exchange (ETDEWEB)

Zhang, B

1980-01-01

This article considers wave surface as a normal stationary random process to solve the estimation of the maximum of wave surface in a given time interval by means of the theoretical results of probability theory. The results are represented by formulas (13) to (19) in this article. It was proved in this article that when time interval approaches infinite, the formulas (3), (6) of E )eta max) that were derived from the references (Cartwright, Longuet-Higgins) can also be derived by asymptotic distribution of the maximum of wave surface provided by the article. The advantage of the results obtained from this point of view as compared with the results obtained from the references was discussed.
Statistic method of research reactors maximum permissible power calculation

International Nuclear Information System (INIS)

Grosheva, N.A.; Kirsanov, G.A.; Konoplev, K.A.; Chmshkyan, D.V.

1998-01-01

The technique for calculating maximum permissible power of a research reactor at which the probability of the thermal-process accident does not exceed the specified value, is presented. The statistical method is used for the calculations. It is regarded that the determining function related to the reactor safety is the known function of the reactor power and many statistically independent values which list includes the reactor process parameters, geometrical characteristics of the reactor core and fuel elements, as well as random factors connected with the reactor specific features. Heat flux density or temperature is taken as a limiting factor. The program realization of the method discussed is briefly described. The results of calculating the PIK reactor margin coefficients for different probabilities of the thermal-process accident are considered as an example. It is shown that the probability of an accident with fuel element melting in hot zone is lower than 10 -8 1 per year for the reactor rated power [ru

Bonding in Heavier Group 14 Zero-Valent Complexes-A Combined Maximum Probability Domain and Valence Bond Theory Approach.

Science.gov (United States)

Turek, Jan; Braïda, Benoît; De Proft, Frank

2017-10-17

The bonding in heavier Group 14 zero-valent complexes of a general formula L 2 E (E=Si-Pb; L=phosphine, N-heterocyclic and acyclic carbene, cyclic tetrylene and carbon monoxide) is probed by combining valence bond (VB) theory and maximum probability domain (MPD) approaches. All studied complexes are initially evaluated on the basis of the structural parameters and the shape of frontier orbitals revealing a bent structural motif and the presence of two lone pairs at the central E atom. For the VB calculations three resonance structures are suggested, representing the "ylidone", "ylidene" and "bent allene" structures, respectively. The influence of both ligands and central atoms on the bonding situation is clearly expressed in different weights of the resonance structures for the particular complexes. In general, the bonding in the studied E 0 compounds, the tetrylones, is best described as a resonating combination of "ylidone" and "ylidene" structures with a minor contribution of the "bent allene" structure. Moreover, the VB calculations allow for a straightforward assessment of the π-backbonding (E→L) stabilization energy. The validity of the suggested resonance model is further confirmed by the complementary MPD calculations focusing on the E lone pair region as well as the E-L bonding region. Likewise, the MPD method reveals a strong influence of the σ-donating and π-accepting properties of the ligand. In particular, either one single domain or two symmetrical domains are found in the lone pair region of the central atom, supporting the predominance of either the "ylidene" or "ylidone" structures having one or two lone pairs at the central atom, respectively. Furthermore, the calculated average populations in the lone pair MPDs correlate very well with the natural bond orbital (NBO) populations, and can be related to the average number of electrons that is backdonated to the ligands. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Dive characteristics can predict foraging success in Australian fur seals (Arctocephalus pusillus doriferus as validated by animal-borne video

Directory of Open Access Journals (Sweden)

Beth L. Volpov

2016-03-01

Full Text Available Dive characteristics and dive shape are often used to infer foraging success in pinnipeds. However, these inferences have not been directly validated in the field with video, and it remains unclear if this method can be applied to benthic foraging animals. This study assessed the ability of dive characteristics from time-depth recorders (TDR to predict attempted prey capture events (APC that were directly observed on animal-borne video in Australian fur seals (Arctocephalus pusillus doriferus, n=11. The most parsimonious model predicting the probability of a dive with ≥1 APC on video included only descent rate as a predictor variable. The majority (94% of the 389 total APC were successful, and the majority of the dives (68% contained at least one successful APC. The best model predicting these successful dives included descent rate as a predictor. Comparisons of the TDR model predictions to video yielded a maximum accuracy of 77.5% in classifying dives as either APC or non-APC or 77.1% in classifying dives as successful verses unsuccessful. Foraging intensity, measured as either total APC per dive or total successful APC per dive, was best predicted by bottom duration and ascent rate. The accuracy in predicting total APC per dive varied based on the number of APC per dive with maximum accuracy occurring at 1 APC for both total (54% and only successful APC (52%. Results from this study linking verified foraging dives to dive characteristics potentially opens the door to decades of historical TDR datasets across several otariid species.
Maximum entropy principal for transportation

International Nuclear Information System (INIS)

Bilich, F.; Da Silva, R.

2008-01-01

In this work we deal with modeling of the transportation phenomenon for use in the transportation planning process and policy-impact studies. The model developed is based on the dependence concept, i.e., the notion that the probability of a trip starting at origin i is dependent on the probability of a trip ending at destination j given that the factors (such as travel time, cost, etc.) which affect travel between origin i and destination j assume some specific values. The derivation of the solution of the model employs the maximum entropy principle combining a priori multinomial distribution with a trip utility concept. This model is utilized to forecast trip distributions under a variety of policy changes and scenarios. The dependence coefficients are obtained from a regression equation where the functional form is derived based on conditional probability and perception of factors from experimental psychology. The dependence coefficients encode all the information that was previously encoded in the form of constraints. In addition, the dependence coefficients encode information that cannot be expressed in the form of constraints for practical reasons, namely, computational tractability. The equivalence between the standard formulation (i.e., objective function with constraints) and the dependence formulation (i.e., without constraints) is demonstrated. The parameters of the dependence-based trip-distribution model are estimated, and the model is also validated using commercial air travel data in the U.S. In addition, policy impact analyses (such as allowance of supersonic flights inside the U.S. and user surcharge at noise-impacted airports) on air travel are performed.
Negative probability in the framework of combined probability

OpenAIRE

Burgin, Mark

2013-01-01

Negative probability has found diverse applications in theoretical physics. Thus, construction of sound and rigorous mathematical foundations for negative probability is important for physics. There are different axiomatizations of conventional probability. So, it is natural that negative probability also has different axiomatic frameworks. In the previous publications (Burgin, 2009; 2010), negative probability was mathematically formalized and rigorously interpreted in the context of extende...
Targeted search for continuous gravitational waves: Bayesian versus maximum-likelihood statistics

International Nuclear Information System (INIS)

Prix, Reinhard; Krishnan, Badri

2009-01-01

We investigate the Bayesian framework for detection of continuous gravitational waves (GWs) in the context of targeted searches, where the phase evolution of the GW signal is assumed to be known, while the four amplitude parameters are unknown. We show that the orthodox maximum-likelihood statistic (known as F-statistic) can be rediscovered as a Bayes factor with an unphysical prior in amplitude parameter space. We introduce an alternative detection statistic ('B-statistic') using the Bayes factor with a more natural amplitude prior, namely an isotropic probability distribution for the orientation of GW sources. Monte Carlo simulations of targeted searches show that the resulting Bayesian B-statistic is more powerful in the Neyman-Pearson sense (i.e., has a higher expected detection probability at equal false-alarm probability) than the frequentist F-statistic.
Maximum Entropy Approach in Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Science.gov (United States)

Farsani, Zahra Amini; Schmid, Volker J

2017-01-01

In the estimation of physiological kinetic parameters from Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) data, the determination of the arterial input function (AIF) plays a key role. This paper proposes a Bayesian method to estimate the physiological parameters of DCE-MRI along with the AIF in situations, where no measurement of the AIF is available. In the proposed algorithm, the maximum entropy method (MEM) is combined with the maximum a posterior approach (MAP). To this end, MEM is used to specify a prior probability distribution of the unknown AIF. The ability of this method to estimate the AIF is validated using the Kullback-Leibler divergence. Subsequently, the kinetic parameters can be estimated with MAP. The proposed algorithm is evaluated with a data set from a breast cancer MRI study. The application shows that the AIF can reliably be determined from the DCE-MRI data using MEM. Kinetic parameters can be estimated subsequently. The maximum entropy method is a powerful tool to reconstructing images from many types of data. This method is useful for generating the probability distribution based on given information. The proposed method gives an alternative way to assess the input function from the existing data. The proposed method allows a good fit of the data and therefore a better estimation of the kinetic parameters. In the end, this allows for a more reliable use of DCE-MRI. Schattauer GmbH.
Solar maximum observatory

International Nuclear Information System (INIS)

Rust, D.M.

1984-01-01

The successful retrieval and repair of the Solar Maximum Mission (SMM) satellite by Shuttle astronauts in April 1984 permitted continuance of solar flare observations that began in 1980. The SMM carries a soft X ray polychromator, gamma ray, UV and hard X ray imaging spectrometers, a coronagraph/polarimeter and particle counters. The data gathered thus far indicated that electrical potentials of 25 MeV develop in flares within 2 sec of onset. X ray data show that flares are composed of compressed magnetic loops that have come too close together. Other data have been taken on mass ejection, impacts of electron beams and conduction fronts with the chromosphere and changes in the solar radiant flux due to sunspots. 13 references
Predicting critical transitions in dynamical systems from time series using nonstationary probability density modeling.

Science.gov (United States)

Kwasniok, Frank

2013-11-01

A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.
A stochastic model for the probability of malaria extinction by mass drug administration.

Science.gov (United States)

Pemberton-Ross, Peter; Chitnis, Nakul; Pothin, Emilie; Smith, Thomas A

2017-09-18

Mass drug administration (MDA) has been proposed as an intervention to achieve local extinction of malaria. Although its effect on the reproduction number is short lived, extinction may subsequently occur in a small population due to stochastic fluctuations. This paper examines how the probability of stochastic extinction depends on population size, MDA coverage and the reproduction number under control, R c . A simple compartmental model is developed which is used to compute the probability of extinction using probability generating functions. The expected time to extinction in small populations after MDA for various scenarios in this model is calculated analytically. The results indicate that mass drug administration (Firstly, R c must be sustained at R c 95% to have a non-negligible probability of successful elimination. Stochastic fluctuations only significantly affect the probability of extinction in populations of about 1000 individuals or less. The expected time to extinction via stochastic fluctuation is less than 10 years only in populations less than about 150 individuals. Clustering of secondary infections and of MDA distribution both contribute positively to the potential probability of success, indicating that MDA would most effectively be administered at the household level. There are very limited circumstances in which MDA will lead to local malaria elimination with a substantial probability.
Estimating the probability that the Taser directly causes human ventricular fibrillation.

Science.gov (United States)

Sun, H; Haemmerich, D; Rahko, P S; Webster, J G

2010-04-01

This paper describes the first methodology and results for estimating the order of probability for Tasers directly causing human ventricular fibrillation (VF). The probability of an X26 Taser causing human VF was estimated using: (1) current density near the human heart estimated by using 3D finite-element (FE) models; (2) prior data of the maximum dart-to-heart distances that caused VF in pigs; (3) minimum skin-to-heart distances measured in erect humans by echocardiography; and (4) dart landing distribution estimated from police reports. The estimated mean probability of human VF was 0.001 for data from a pig having a chest wall resected to the ribs and 0.000006 for data from a pig with no resection when inserting a blunt probe. The VF probability for a given dart location decreased with the dart-to-heart horizontal distance (radius) on the skin surface.
Assigning probability distributions to input parameters of performance assessment models

Energy Technology Data Exchange (ETDEWEB)

Mishra, Srikanta [INTERA Inc., Austin, TX (United States)

2002-02-01

This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available.
Assigning probability distributions to input parameters of performance assessment models

International Nuclear Information System (INIS)

Mishra, Srikanta

2002-02-01

This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available
Maximum entropy reconstruction of spin densities involving non uniform prior

International Nuclear Information System (INIS)

Schweizer, J.; Ressouche, E.; Papoular, R.J.; Zheludev, A.I.

1997-01-01

Diffraction experiments give microscopic information on structures in crystals. A method which uses the concept of maximum of entropy (MaxEnt), appears to be a formidable improvement in the treatment of diffraction data. This method is based on a bayesian approach: among all the maps compatible with the experimental data, it selects that one which has the highest prior (intrinsic) probability. Considering that all the points of the map are equally probable, this probability (flat prior) is expressed via the Boltzman entropy of the distribution. This method has been used for the reconstruction of charge densities from X-ray data, for maps of nuclear densities from unpolarized neutron data as well as for distributions of spin density. The density maps obtained by this method, as compared to those resulting from the usual inverse Fourier transformation, are tremendously improved. In particular, any substantial deviation from the background is really contained in the data, as it costs entropy compared to a map that would ignore such features. However, in most of the cases, before the measurements are performed, some knowledge exists about the distribution which is investigated. It can range from the simple information of the type of scattering electrons to an elaborate theoretical model. In these cases, the uniform prior which considers all the different pixels as equally likely, is too weak a requirement and has to be replaced. In a rigorous bayesian analysis, Skilling has shown that prior knowledge can be encoded into the Maximum Entropy formalism through a model m(rvec r), via a new definition for the entropy given in this paper. In the absence of any data, the maximum of the entropy functional is reached for ρ(rvec r) = m(rvec r). Any substantial departure from the model, observed in the final map, is really contained in the data as, with the new definition, it costs entropy. This paper presents illustrations of model testing
Maximum entropy decomposition of quadrupole mass spectra

International Nuclear Information System (INIS)

Toussaint, U. von; Dose, V.; Golan, A.

2004-01-01

We present an information-theoretic method called generalized maximum entropy (GME) for decomposing mass spectra of gas mixtures from noisy measurements. In this GME approach to the noisy, underdetermined inverse problem, the joint entropies of concentration, cracking, and noise probabilities are maximized subject to the measured data. This provides a robust estimation for the unknown cracking patterns and the concentrations of the contributing molecules. The method is applied to mass spectroscopic data of hydrocarbons, and the estimates are compared with those received from a Bayesian approach. We show that the GME method is efficient and is computationally fast
Focus in High School Mathematics: Statistics and Probability

Science.gov (United States)

National Council of Teachers of Mathematics, 2009

2009-01-01

Reasoning about and making sense of statistics and probability are essential to students' future success. This volume belongs to a series that supports National Council of Teachers of Mathematics' (NCTM's) "Focus in High School Mathematics: Reasoning and Sense Making" by providing additional guidance for making reasoning and sense making part of…
Modeling highway travel time distribution with conditional probability models

Energy Technology Data Exchange (ETDEWEB)

Oliveira Neto, Francisco Moraes [ORNL; Chin, Shih-Miao [ORNL; Hwang, Ho-Ling [ORNL; Han, Lee [University of Tennessee, Knoxville (UTK)

2014-01-01

ABSTRACT Under the sponsorship of the Federal Highway Administration's Office of Freight Management and Operations, the American Transportation Research Institute (ATRI) has developed performance measures through the Freight Performance Measures (FPM) initiative. Under this program, travel speed information is derived from data collected using wireless based global positioning systems. These telemetric data systems are subscribed and used by trucking industry as an operations management tool. More than one telemetric operator submits their data dumps to ATRI on a regular basis. Each data transmission contains truck location, its travel time, and a clock time/date stamp. Data from the FPM program provides a unique opportunity for studying the upstream-downstream speed distributions at different locations, as well as different time of the day and day of the week. This research is focused on the stochastic nature of successive link travel speed data on the continental United States Interstates network. Specifically, a method to estimate route probability distributions of travel time is proposed. This method uses the concepts of convolution of probability distributions and bivariate, link-to-link, conditional probability to estimate the expected distributions for the route travel time. Major contribution of this study is the consideration of speed correlation between upstream and downstream contiguous Interstate segments through conditional probability. The established conditional probability distributions, between successive segments, can be used to provide travel time reliability measures. This study also suggests an adaptive method for calculating and updating route travel time distribution as new data or information is added. This methodology can be useful to estimate performance measures as required by the recent Moving Ahead for Progress in the 21st Century Act (MAP 21).
Exact results for survival probability in the multistate Landau-Zener model

International Nuclear Information System (INIS)

Volkov, M V; Ostrovsky, V N

2004-01-01

An exact formula is derived for survival probability in the multistate Landau-Zener model in the special case where the initially populated state corresponds to the extremal (maximum or minimum) slope of a linear diabatic potential curve. The formula was originally guessed by S Brundobler and V Elzer (1993 J. Phys. A: Math. Gen. 26 1211) based on numerical calculations. It is a simple generalization of the expression for the probability of diabatic passage in the famous two-state Landau-Zener model. Our result is obtained via analysis and summation of the entire perturbation theory series
Family of probability distributions derived from maximal entropy principle with scale invariant restrictions.

Science.gov (United States)

Sonnino, Giorgio; Steinbrecher, György; Cardinali, Alessandro; Sonnino, Alberto; Tlidi, Mustapha

2013-01-01

Using statistical thermodynamics, we derive a general expression of the stationary probability distribution for thermodynamic systems driven out of equilibrium by several thermodynamic forces. The local equilibrium is defined by imposing the minimum entropy production and the maximum entropy principle under the scale invariance restrictions. The obtained probability distribution presents a singularity that has immediate physical interpretation in terms of the intermittency models. The derived reference probability distribution function is interpreted as time and ensemble average of the real physical one. A generic family of stochastic processes describing noise-driven intermittency, where the stationary density distribution coincides exactly with the one resulted from entropy maximization, is presented.
Probability

CERN Document Server

Shiryaev, A N

1996-01-01

This book contains a systematic treatment of probability from the ground up, starting with intuitive ideas and gradually developing more sophisticated subjects, such as random walks, martingales, Markov chains, ergodic theory, weak convergence of probability measures, stationary stochastic processes, and the Kalman-Bucy filter Many examples are discussed in detail, and there are a large number of exercises The book is accessible to advanced undergraduates and can be used as a text for self-study This new edition contains substantial revisions and updated references The reader will find a deeper study of topics such as the distance between probability measures, metrization of weak convergence, and contiguity of probability measures Proofs for a number of some important results which were merely stated in the first edition have been added The author included new material on the probability of large deviations, and on the central limit theorem for sums of dependent random variables
Developing a probability-based model of aquifer vulnerability in an agricultural region

Science.gov (United States)

Chen, Shih-Kai; Jang, Cheng-Shin; Peng, Yi-Huei

2013-04-01

SummaryHydrogeological settings of aquifers strongly influence the regional groundwater movement and pollution processes. Establishing a map of aquifer vulnerability is considerably critical for planning a scheme of groundwater quality protection. This study developed a novel probability-based DRASTIC model of aquifer vulnerability in the Choushui River alluvial fan, Taiwan, using indicator kriging and to determine various risk categories of contamination potentials based on estimated vulnerability indexes. Categories and ratings of six parameters in the probability-based DRASTIC model were probabilistically characterized according to the parameter classification methods of selecting a maximum estimation probability and calculating an expected value. Moreover, the probability-based estimation and assessment gave us an excellent insight into propagating the uncertainty of parameters due to limited observation data. To examine the prediction capacity of pollutants for the developed probability-based DRASTIC model, medium, high, and very high risk categories of contamination potentials were compared with observed nitrate-N exceeding 0.5 mg/L indicating the anthropogenic groundwater pollution. The analyzed results reveal that the developed probability-based DRASTIC model is capable of predicting high nitrate-N groundwater pollution and characterizing the parameter uncertainty via the probability estimation processes.

How Life History Can Sway the Fixation Probability of Mutants

Science.gov (United States)

Li, Xiang-Yi; Kurokawa, Shun; Giaimo, Stefano; Traulsen, Arne

2016-01-01

In this work, we study the effects of demographic structure on evolutionary dynamics when selection acts on reproduction, survival, or both. In contrast to the previously discovered pattern that the fixation probability of a neutral mutant decreases while the population becomes younger, we show that a mutant with a constant selective advantage may have a maximum or a minimum of the fixation probability in populations with an intermediate fraction of young individuals. This highlights the importance of life history and demographic structure in studying evolutionary dynamics. We also illustrate the fundamental differences between selection on reproduction and selection on survival when age structure is present. In addition, we evaluate the relative importance of size and structure of the population in determining the fixation probability of the mutant. Our work lays the foundation for also studying density- and frequency-dependent effects in populations when demographic structures cannot be neglected. PMID:27129737
Estimating occurrence and detection probabilities for stream-breeding salamanders in the Gulf Coastal Plain

Science.gov (United States)

Lamb, Jennifer Y.; Waddle, J. Hardin; Qualls, Carl P.

2017-01-01

Large gaps exist in our knowledge of the ecology of stream-breeding plethodontid salamanders in the Gulf Coastal Plain. Data describing where these salamanders are likely to occur along environmental gradients, as well as their likelihood of detection, are important for the prevention and management of amphibian declines. We used presence/absence data from leaf litter bag surveys and a hierarchical Bayesian multispecies single-season occupancy model to estimate the occurrence of five species of plethodontids across reaches in headwater streams in the Gulf Coastal Plain. Average detection probabilities were high (range = 0.432–0.942) and unaffected by sampling covariates specific to the use of litter bags (i.e., bag submergence, sampling season, in-stream cover). Estimates of occurrence probabilities differed substantially between species (range = 0.092–0.703) and were influenced by the size of the upstream drainage area and by the maximum proportion of the reach that dried. The effects of these two factors were not equivalent across species. Our results demonstrate that hierarchical multispecies models successfully estimate occurrence parameters for both rare and common stream-breeding plethodontids. The resulting models clarify how species are distributed within stream networks, and they provide baseline values that will be useful in evaluating the conservation statuses of plethodontid species within lotic systems in the Gulf Coastal Plain.
Fractal Dimension and Maximum Sunspot Number in Solar Cycle

Directory of Open Access Journals (Sweden)

R.-S. Kim

2006-09-01

Full Text Available The fractal dimension is a quantitative parameter describing the characteristics of irregular time series. In this study, we use this parameter to analyze the irregular aspects of solar activity and to predict the maximum sunspot number in the following solar cycle by examining time series of the sunspot number. For this, we considered the daily sunspot number since 1850 from SIDC (Solar Influences Data analysis Center and then estimated cycle variation of the fractal dimension by using Higuchi's method. We examined the relationship between this fractal dimension and the maximum monthly sunspot number in each solar cycle. As a result, we found that there is a strong inverse relationship between the fractal dimension and the maximum monthly sunspot number. By using this relation we predicted the maximum sunspot number in the solar cycle from the fractal dimension of the sunspot numbers during the solar activity increasing phase. The successful prediction is proven by a good correlation (r=0.89 between the observed and predicted maximum sunspot numbers in the solar cycles.
Outlier identification procedures for contingency tables using maximum likelihood and $L_1$ estimates

NARCIS (Netherlands)

Kuhnt, S.

2004-01-01

Observed cell counts in contingency tables are perceived as outliers if they have low probability under an anticipated loglinear Poisson model. New procedures for the identification of such outliers are derived using the classical maximum likelihood estimator and an estimator based on the L1 norm.
Unrelated Hematopoietic Stem Cell Donor Matching Probability and Search Algorithm

Directory of Open Access Journals (Sweden)

J.-M. Tiercy

2012-01-01

Full Text Available In transplantation of hematopoietic stem cells (HSCs from unrelated donors a high HLA compatibility level decreases the risk of acute graft-versus-host disease and mortality. The diversity of the HLA system at the allelic and haplotypic level and the heterogeneity of HLA typing data of the registered donors render the search process a complex task. This paper summarizes our experience with a search algorithm that includes at the start of the search a probability estimate (high/intermediate/low to identify a HLA-A, B, C, DRB1, DQB1-compatible donor (a 10/10 match. Based on 2002–2011 searches about 30% of patients have a high, 30% an intermediate, and 40% a low probability search. Search success rate and duration are presented and discussed in light of the experience of other centers. Overall a 9-10/10 matched HSC donor can now be identified for 60–80% of patients of European descent. For high probability searches donors can be selected on the basis of DPB1-matching with an estimated success rate of >40%. For low probability searches there is no consensus on which HLA incompatibilities are more permissive, although HLA-DQB1 mismatches are generally considered as acceptable. Models for the discrimination of more detrimental mismatches based on specific amino acid residues rather than specific HLA alleles are presented.
Knotting probability of self-avoiding polygons under a topological constraint

Science.gov (United States)

Uehara, Erica; Deguchi, Tetsuo

2017-09-01

We define the knotting probability of a knot K by the probability for a random polygon or self-avoiding polygon (SAP) of N segments having the knot type K. We show fundamental and generic properties of the knotting probability particularly its dependence on the excluded volume. We investigate them for the SAP consisting of hard cylindrical segments of unit length and radius rex. For various prime and composite knots, we numerically show that a compact formula describes the knotting probabilities for the cylindrical SAP as a function of segment number N and radius rex. It connects the small-N to the large-N behavior and even to lattice knots in the case of large values of radius. As the excluded volume increases, the maximum of the knotting probability decreases for prime knots except for the trefoil knot. If it is large, the trefoil knot and its descendants are dominant among the nontrivial knots in the SAP. From the factorization property of the knotting probability, we derive a sum rule among the estimates of a fitting parameter for all prime knots, which suggests the local knot picture and the dominance of the trefoil knot in the case of large excluded volumes. Here we remark that the cylindrical SAP gives a model of circular DNA which is negatively charged and semiflexible, where radius rex corresponds to the screening length.
Knotting probability of self-avoiding polygons under a topological constraint.

Science.gov (United States)

Uehara, Erica; Deguchi, Tetsuo

2017-09-07

We define the knotting probability of a knot K by the probability for a random polygon or self-avoiding polygon (SAP) of N segments having the knot type K. We show fundamental and generic properties of the knotting probability particularly its dependence on the excluded volume. We investigate them for the SAP consisting of hard cylindrical segments of unit length and radius r ex . For various prime and composite knots, we numerically show that a compact formula describes the knotting probabilities for the cylindrical SAP as a function of segment number N and radius r ex . It connects the small-N to the large-N behavior and even to lattice knots in the case of large values of radius. As the excluded volume increases, the maximum of the knotting probability decreases for prime knots except for the trefoil knot. If it is large, the trefoil knot and its descendants are dominant among the nontrivial knots in the SAP. From the factorization property of the knotting probability, we derive a sum rule among the estimates of a fitting parameter for all prime knots, which suggests the local knot picture and the dominance of the trefoil knot in the case of large excluded volumes. Here we remark that the cylindrical SAP gives a model of circular DNA which is negatively charged and semiflexible, where radius r ex corresponds to the screening length.
Introduction to maximum entropy

International Nuclear Information System (INIS)

Sivia, D.S.

1989-01-01

The maximum entropy (MaxEnt) principle has been successfully used in image reconstruction in a wide variety of fields. The author reviews the need for such methods in data analysis and shows, by use of a very simple example, why MaxEnt is to be preferred over other regularizing functions. This leads to a more general interpretation of the MaxEnt method, and its use is illustrated with several different examples. Practical difficulties with non-linear problems still remain, this being highlighted by the notorious phase problem in crystallography. He concludes with an example from neutron scattering, using data from a filter difference spectrometer to contrast MaxEnt with a conventional deconvolution. 12 refs., 8 figs., 1 tab
Introduction to maximum entropy

International Nuclear Information System (INIS)

Sivia, D.S.

1988-01-01

The maximum entropy (MaxEnt) principle has been successfully used in image reconstruction in a wide variety of fields. We review the need for such methods in data analysis and show, by use of a very simple example, why MaxEnt is to be preferred over other regularizing functions. This leads to a more general interpretation of the MaxEnt method, and its use is illustrated with several different examples. Practical difficulties with non-linear problems still remain, this being highlighted by the notorious phase problem in crystallography. We conclude with an example from neutron scattering, using data from a filter difference spectrometer to contrast MaxEnt with a conventional deconvolution. 12 refs., 8 figs., 1 tab
Maximum likelihood approach for several stochastic volatility models

International Nuclear Information System (INIS)

Camprodon, Jordi; Perelló, Josep

2012-01-01

Volatility measures the amplitude of price fluctuations. Despite it being one of the most important quantities in finance, volatility is not directly observable. Here we apply a maximum likelihood method which assumes that price and volatility follow a two-dimensional diffusion process where volatility is the stochastic diffusion coefficient of the log-price dynamics. We apply this method to the simplest versions of the expOU, the OU and the Heston stochastic volatility models and we study their performance in terms of the log-price probability, the volatility probability, and its Mean First-Passage Time. The approach has some predictive power on the future returns amplitude by only knowing the current volatility. The assumed models do not consider long-range volatility autocorrelation and the asymmetric return-volatility cross-correlation but the method still yields very naturally these two important stylized facts. We apply the method to different market indices and with a good performance in all cases. (paper)
Applications of the principle of maximum entropy: from physics to ecology.

Science.gov (United States)

Banavar, Jayanth R; Maritan, Amos; Volkov, Igor

2010-02-17

There are numerous situations in physics and other disciplines which can be described at different levels of detail in terms of probability distributions. Such descriptions arise either intrinsically as in quantum mechanics, or because of the vast amount of details necessary for a complete description as, for example, in Brownian motion and in many-body systems. We show that an application of the principle of maximum entropy for estimating the underlying probability distribution can depend on the variables used for describing the system. The choice of characterization of the system carries with it implicit assumptions about fundamental attributes such as whether the system is classical or quantum mechanical or equivalently whether the individuals are distinguishable or indistinguishable. We show that the correct procedure entails the maximization of the relative entropy subject to known constraints and, additionally, requires knowledge of the behavior of the system in the absence of these constraints. We present an application of the principle of maximum entropy to understanding species diversity in ecology and introduce a new statistical ensemble corresponding to the distribution of a variable population of individuals into a set of species not defined a priori.
Applications of the principle of maximum entropy: from physics to ecology

International Nuclear Information System (INIS)

Banavar, Jayanth R; Volkov, Igor; Maritan, Amos

2010-01-01

There are numerous situations in physics and other disciplines which can be described at different levels of detail in terms of probability distributions. Such descriptions arise either intrinsically as in quantum mechanics, or because of the vast amount of details necessary for a complete description as, for example, in Brownian motion and in many-body systems. We show that an application of the principle of maximum entropy for estimating the underlying probability distribution can depend on the variables used for describing the system. The choice of characterization of the system carries with it implicit assumptions about fundamental attributes such as whether the system is classical or quantum mechanical or equivalently whether the individuals are distinguishable or indistinguishable. We show that the correct procedure entails the maximization of the relative entropy subject to known constraints and, additionally, requires knowledge of the behavior of the system in the absence of these constraints. We present an application of the principle of maximum entropy to understanding species diversity in ecology and introduce a new statistical ensemble corresponding to the distribution of a variable population of individuals into a set of species not defined a priori. (topical review)
Outage probability analysis of wireless sensor networks in the presence of channel fading and spatial correlation

KAUST Repository

Al-Murad, Tamim M.

2011-07-01

Evaluating the reliability of wireless sensor networks is becoming more important as theses networks are being used in crucial applications. The outage probability defined as the probability that the error in the system exceeds a maximum acceptable threshold has recently been used as a measure of the reliability of such systems. In this work we find the outage probability of wireless sensor network in different scenarios of distributed sensing where sensors\\' readings are affected by spatial correlation and in the presence of channel fading. © 2011 IEEE.
ELIPGRID-PC: A PC program for calculating hot spot probabilities

International Nuclear Information System (INIS)

Davidson, J.R.

1994-10-01

ELIPGRID-PC, a new personal computer program has been developed to provide easy access to Singer's 1972 ELIPGRID algorithm for hot-spot detection probabilities. Three features of the program are the ability to determine: (1) the grid size required for specified conditions, (2) the smallest hot spot that can be sampled with a given probability, and (3) the approximate grid size resulting from specified conditions and sampling cost. ELIPGRID-PC also provides probability of hit versus cost data for graphing with spread-sheets or graphics software. The program has been successfully tested using Singer's published ELIPGRID results. An apparent error in the original ELIPGRID code has been uncovered and an appropriate modification incorporated into the new program
Scaling Qualitative Probability

OpenAIRE

Burgin, Mark

2017-01-01

There are different approaches to qualitative probability, which includes subjective probability. We developed a representation of qualitative probability based on relational systems, which allows modeling uncertainty by probability structures and is more coherent than existing approaches. This setting makes it possible proving that any comparative probability is induced by some probability structure (Theorem 2.1), that classical probability is a probability structure (Theorem 2.2) and that i...
Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation

OpenAIRE

Rajiv D. Banker

1993-01-01

This paper provides a formal statistical basis for the efficiency evaluation techniques of data envelopment analysis (DEA). DEA estimators of the best practice monotone increasing and concave production function are shown to be also maximum likelihood estimators if the deviation of actual output from the efficient output is regarded as a stochastic variable with a monotone decreasing probability density function. While the best practice frontier estimator is biased below the theoretical front...
Physical Layer Security Using Two-Path Successive Relaying

Directory of Open Access Journals (Sweden)

Qian Yu Liau

2016-06-01

Full Text Available Relaying is one of the useful techniques to enhance wireless physical-layer security. Existing literature shows that employing full-duplex relay instead of conventional half-duplex relay improves secrecy capacity and secrecy outage probability, but this is at the price of sophisticated implementation. As an alternative, two-path successive relaying has been proposed to emulate operation of full-duplex relay by scheduling a pair of half-duplex relays to assist the source transmission alternately. However, the performance of two-path successive relaying in secrecy communication remains unexplored. This paper proposes a secrecy two-path successive relaying protocol for a scenario with one source, one destination and two half-duplex relays. The relays operate alternately in a time division mode to forward messages continuously from source to destination in the presence of an eavesdropper. Analytical results reveal that the use of two half-duplex relays in the proposed scheme contributes towards a quadratically lower probability of interception compared to full-duplex relaying. Numerical simulations show that the proposed protocol achieves the ergodic achievable secrecy rate of full-duplex relaying while delivering the lowest probability of interception and secrecy outage probability compared to the existing half duplex relaying, full duplex relaying and full duplex jamming schemes.
People's Intuitions about Randomness and Probability: An Empirical Study

Science.gov (United States)

Lecoutre, Marie-Paule; Rovira, Katia; Lecoutre, Bruno; Poitevineau, Jacques

2006-01-01

What people mean by randomness should be taken into account when teaching statistical inference. This experiment explored subjective beliefs about randomness and probability through two successive tasks. Subjects were asked to categorize 16 familiar items: 8 real items from everyday life experiences, and 8 stochastic items involving a repeatable…
How to model a negligible probability under the WTO sanitary and phytosanitary agreement?

Science.gov (United States)

Powell, Mark R

2013-06-01

Since the 1997 EC--Hormones decision, World Trade Organization (WTO) Dispute Settlement Panels have wrestled with the question of what constitutes a negligible risk under the Sanitary and Phytosanitary Agreement. More recently, the 2010 WTO Australia--Apples Panel focused considerable attention on the appropriate quantitative model for a negligible probability in a risk assessment. The 2006 Australian Import Risk Analysis for Apples from New Zealand translated narrative probability statements into quantitative ranges. The uncertainty about a "negligible" probability was characterized as a uniform distribution with a minimum value of zero and a maximum value of 10(-6) . The Australia - Apples Panel found that the use of this distribution would tend to overestimate the likelihood of "negligible" events and indicated that a triangular distribution with a most probable value of zero and a maximum value of 10⁻⁶ would correct the bias. The Panel observed that the midpoint of the uniform distribution is 5 × 10⁻⁷ but did not consider that the triangular distribution has an expected value of 3.3 × 10⁻⁷. Therefore, if this triangular distribution is the appropriate correction, the magnitude of the bias found by the Panel appears modest. The Panel's detailed critique of the Australian risk assessment, and the conclusions of the WTO Appellate Body about the materiality of flaws found by the Panel, may have important implications for the standard of review for risk assessments under the WTO SPS Agreement. © 2012 Society for Risk Analysis.
Applications of Fuss-Catalan Numbers to Success Runs of Bernoulli Trials

Directory of Open Access Journals (Sweden)

S. J. Dilworth

2016-01-01

Full Text Available In a recent paper, the authors derived the exact solution for the probability mass function of the geometric distribution of order k, expressing the roots of the associated auxiliary equation in terms of generating functions for Fuss-Catalan numbers. This paper applies the above formalism for the Fuss-Catalan numbers to treat additional problems pertaining to occurrences of success runs. New exact analytical expressions for the probability mass function and probability generating function and so forth are derived. First, we treat sequences of Bernoulli trials with r≥1 occurrences of success runs of length k with l-overlapping. The case l<0, where there must be a gap of at least l trials between success runs, is also studied. Next we treat the distribution of the waiting time for the rth nonoverlapping appearance of a pair of successes separated by at most k-2 failures (k≥2.

Modeling the probability distribution of peak discharge for infiltrating hillslopes

Science.gov (United States)

Baiamonte, Giorgio; Singh, Vijay P.

2017-07-01

Hillslope response plays a fundamental role in the prediction of peak discharge at the basin outlet. The peak discharge for the critical duration of rainfall and its probability distribution are needed for designing urban infrastructure facilities. This study derives the probability distribution, denoted as GABS model, by coupling three models: (1) the Green-Ampt model for computing infiltration, (2) the kinematic wave model for computing discharge hydrograph from the hillslope, and (3) the intensity-duration-frequency (IDF) model for computing design rainfall intensity. The Hortonian mechanism for runoff generation is employed for computing the surface runoff hydrograph. Since the antecedent soil moisture condition (ASMC) significantly affects the rate of infiltration, its effect on the probability distribution of peak discharge is investigated. Application to a watershed in Sicily, Italy, shows that with the increase of probability, the expected effect of ASMC to increase the maximum discharge diminishes. Only for low values of probability, the critical duration of rainfall is influenced by ASMC, whereas its effect on the peak discharge seems to be less for any probability. For a set of parameters, the derived probability distribution of peak discharge seems to be fitted by the gamma distribution well. Finally, an application to a small watershed, with the aim to test the possibility to arrange in advance the rational runoff coefficient tables to be used for the rational method, and a comparison between peak discharges obtained by the GABS model with those measured in an experimental flume for a loamy-sand soil were carried out.
Topological probability and connection strength induced activity in complex neural networks

International Nuclear Information System (INIS)

Du-Qu, Wei; Bo, Zhang; Dong-Yuan, Qiu; Xiao-Shu, Luo

2010-01-01

Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world (SW) connections. Network elements are described by two-dimensional map neurons (2DMNs) with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied. (general)
Analysis of QCD sum rule based on the maximum entropy method

International Nuclear Information System (INIS)

Gubler, Philipp

2012-01-01

QCD sum rule was developed about thirty years ago and has been used up to the present to calculate various physical quantities like hadrons. It has been, however, needed to assume 'pole + continuum' for the spectral function in the conventional analyses. Application of this method therefore came across with difficulties when the above assumption is not satisfied. In order to avoid this difficulty, analysis to make use of the maximum entropy method (MEM) has been developed by the present author. It is reported here how far this new method can be successfully applied. In the first section, the general feature of the QCD sum rule is introduced. In section 2, it is discussed why the analysis by the QCD sum rule based on the MEM is so effective. In section 3, the MEM analysis process is described, and in the subsection 3.1 likelihood function and prior probability are considered then in subsection 3.2 numerical analyses are picked up. In section 4, some cases of applications are described starting with ρ mesons, then charmoniums in the finite temperature and finally recent developments. Some figures of the spectral functions are shown. In section 5, summing up of the present analysis method and future view are given. (S. Funahashi)
Probability elicitation to inform early health economic evaluations of new medical technologies: a case study in heart failure disease management.

Science.gov (United States)

Cao, Qi; Postmus, Douwe; Hillege, Hans L; Buskens, Erik

2013-06-01

Early estimates of the commercial headroom available to a new medical device can assist producers of health technology in making appropriate product investment decisions. The purpose of this study was to illustrate how this quantity can be captured probabilistically by combining probability elicitation with early health economic modeling. The technology considered was a novel point-of-care testing device in heart failure disease management. First, we developed a continuous-time Markov model to represent the patients' disease progression under the current care setting. Next, we identified the model parameters that are likely to change after the introduction of the new device and interviewed three cardiologists to capture the probability distributions of these parameters. Finally, we obtained the probability distribution of the commercial headroom available per measurement by propagating the uncertainty in the model inputs to uncertainty in modeled outcomes. For a willingness-to-pay value of €10,000 per life-year, the median headroom available per measurement was €1.64 (interquartile range €0.05-€3.16) when the measurement frequency was assumed to be daily. In the subsequently conducted sensitivity analysis, this median value increased to a maximum of €57.70 for different combinations of the willingness-to-pay threshold and the measurement frequency. Probability elicitation can successfully be combined with early health economic modeling to obtain the probability distribution of the headroom available to a new medical technology. Subsequently feeding this distribution into a product investment evaluation method enables stakeholders to make more informed decisions regarding to which markets a currently available product prototype should be targeted. Copyright © 2013. Published by Elsevier Inc.
Toward a generalized probability theory: conditional probabilities

International Nuclear Information System (INIS)

Cassinelli, G.

1979-01-01

The main mathematical object of interest in the quantum logic approach to the foundations of quantum mechanics is the orthomodular lattice and a set of probability measures, or states, defined by the lattice. This mathematical structure is studied per se, independently from the intuitive or physical motivation of its definition, as a generalized probability theory. It is thought that the building-up of such a probability theory could eventually throw light on the mathematical structure of Hilbert-space quantum mechanics as a particular concrete model of the generalized theory. (Auth.)
Finite-size scaling of survival probability in branching processes.

Science.gov (United States)

Garcia-Millan, Rosalba; Font-Clos, Francesc; Corral, Álvaro

2015-04-01

Branching processes pervade many models in statistical physics. We investigate the survival probability of a Galton-Watson branching process after a finite number of generations. We derive analytically the existence of finite-size scaling for the survival probability as a function of the control parameter and the maximum number of generations, obtaining the critical exponents as well as the exact scaling function, which is G(y)=2ye(y)/(e(y)-1), with y the rescaled distance to the critical point. Our findings are valid for any branching process of the Galton-Watson type, independently of the distribution of the number of offspring, provided its variance is finite. This proves the universal behavior of the finite-size effects in branching processes, including the universality of the metric factors. The direct relation to mean-field percolation is also discussed.
Evaluation of parameters effect on the maximum fuel temperature in the core thermal and hydraulic design of HTTR

International Nuclear Information System (INIS)

Fujimoto, Nozomu; Maruyama, Soh; Sudo, Yukio; Fujii, Sadao; Niguma, Yoshinori.

1988-10-01

This report presents the results of quantitative evaluation on the effects of the dominant parameters on the maximum fuel temperature in the core thermal hydraulic design of the High Temperature Engineering Test Reactor(HTTR) of 30 MW in thermal power, 950 deg C in reactor outlet coolant temperature and 40 kg/cm 2 G in coolant pressure. The dominant parameters investigated are 1) Gap conductance. 2) Effect of eccertricity of fuel compacts in graphite sleeve. 3) Effect of spacer ribs on heat transfer coefficients. 4) Contact probability of fuel compact and graphite sleeve. 5) Validity of uniform radial power density in the fuel compacts. 6) Effect of impurity gas on gap conductance. 7) Effect of FP gas on gap conductance. The effects of these items on the maximum fuel temperature were quantitalively identified as hot spot factors. A probability of the appearance of the maximum fuel temperature was also evaluated in this report. (author)
A stochastic-deterministic approach for evaluation of uncertainty in the predicted maximum fuel bundle enthalpy in a CANDU postulated LBLOCA event

Energy Technology Data Exchange (ETDEWEB)

Serghiuta, D.; Tholammakkil, J.; Shen, W., E-mail: Dumitru.Serghiuta@cnsc-ccsn.gc.ca [Canadian Nuclear Safety Commission, Ottawa, Ontario (Canada)

2014-07-01

A stochastic-deterministic approach based on representation of uncertainties by subjective probabilities is proposed for evaluation of bounding values of functional failure probability and assessment of probabilistic safety margins. The approach is designed for screening and limited independent review verification. Its application is illustrated for a postulated generic CANDU LBLOCA and evaluation of the possibility distribution function of maximum bundle enthalpy considering the reactor physics part of LBLOCA power pulse simulation only. The computer codes HELIOS and NESTLE-CANDU were used in a stochastic procedure driven by the computer code DAKOTA to simulate the LBLOCA power pulse using combinations of core neutronic characteristics randomly generated from postulated subjective probability distributions with deterministic constraints and fixed transient bundle-wise thermal hydraulic conditions. With this information, a bounding estimate of functional failure probability using the limit for the maximum fuel bundle enthalpy can be derived for use in evaluation of core damage frequency. (author)
Maximum entropy reconstructions for crystallographic imaging; Cristallographie et reconstruction d`images par maximum d`entropie

Energy Technology Data Exchange (ETDEWEB)

Papoular, R

1997-07-01

The Fourier Transform is of central importance to Crystallography since it allows the visualization in real space of tridimensional scattering densities pertaining to physical systems from diffraction data (powder or single-crystal diffraction, using x-rays, neutrons, electrons or else). In turn, this visualization makes it possible to model and parametrize these systems, the crystal structures of which are eventually refined by Least-Squares techniques (e.g., the Rietveld method in the case of Powder Diffraction). The Maximum Entropy Method (sometimes called MEM or MaxEnt) is a general imaging technique, related to solving ill-conditioned inverse problems. It is ideally suited for tackling undetermined systems of linear questions (for which the number of variables is much larger than the number of equations). It is already being applied successfully in Astronomy, Radioastronomy and Medical Imaging. The advantages of using MAXIMUM Entropy over conventional Fourier and `difference Fourier` syntheses stem from the following facts: MaxEnt takes the experimental error bars into account; MaxEnt incorporate Prior Knowledge (e.g., the positivity of the scattering density in some instances); MaxEnt allows density reconstructions from incompletely phased data, as well as from overlapping Bragg reflections; MaxEnt substantially reduces truncation errors to which conventional experimental Fourier reconstructions are usually prone. The principles of Maximum Entropy imaging as applied to Crystallography are first presented. The method is then illustrated by a detailed example specific to Neutron Diffraction: the search for proton in solids. (author). 17 refs.
Establishment probability in newly founded populations

Directory of Open Access Journals (Sweden)

Gusset Markus

2012-06-01

Full Text Available Abstract Background Establishment success in newly founded populations relies on reaching the established phase, which is defined by characteristic fluctuations of the population’s state variables. Stochastic population models can be used to quantify the establishment probability of newly founded populations; however, so far no simple but robust method for doing so existed. To determine a critical initial number of individuals that need to be released to reach the established phase, we used a novel application of the “Wissel plot”, where –ln(1 – P0(t is plotted against time t. This plot is based on the equation P0t=1–c1e–ω1t, which relates the probability of extinction by time t, P0(t, to two constants: c1 describes the probability of a newly founded population to reach the established phase, whereas ω1 describes the population’s probability of extinction per short time interval once established. Results For illustration, we applied the method to a previously developed stochastic population model of the endangered African wild dog (Lycaon pictus. A newly founded population reaches the established phase if the intercept of the (extrapolated linear parts of the “Wissel plot” with the y-axis, which is –ln(c1, is negative. For wild dogs in our model, this is the case if a critical initial number of four packs, consisting of eight individuals each, are released. Conclusions The method we present to quantify the establishment probability of newly founded populations is generic and inferences thus are transferable to other systems across the field of conservation biology. In contrast to other methods, our approach disaggregates the components of a population’s viability by distinguishing establishment from persistence.
Quantum probability measures and tomographic probability densities

NARCIS (Netherlands)

Amosov, GG; Man'ko, [No Value

2004-01-01

Using a simple relation of the Dirac delta-function to generalized the theta-function, the relationship between the tomographic probability approach and the quantum probability measure approach with the description of quantum states is discussed. The quantum state tomogram expressed in terms of the
Probability distribution of extreme share returns in Malaysia

Science.gov (United States)

Zin, Wan Zawiah Wan; Safari, Muhammad Aslam Mohd; Jaaman, Saiful Hafizah; Yie, Wendy Ling Shin

2014-09-01

The objective of this study is to investigate the suitable probability distribution to model the extreme share returns in Malaysia. To achieve this, weekly and monthly maximum daily share returns are derived from share prices data obtained from Bursa Malaysia over the period of 2000 to 2012. The study starts with summary statistics of the data which will provide a clue on the likely candidates for the best fitting distribution. Next, the suitability of six extreme value distributions, namely the Gumbel, Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA), the Lognormal (GNO) and the Pearson (PE3) distributions are evaluated. The method of L-moments is used in parameter estimation. Based on several goodness of fit tests and L-moment diagram test, the Generalized Pareto distribution and the Pearson distribution are found to be the best fitted distribution to represent the weekly and monthly maximum share returns in Malaysia stock market during the studied period, respectively.
SureTrak Probability of Impact Display

Science.gov (United States)

Elliott, John

2012-01-01

The SureTrak Probability of Impact Display software was developed for use during rocket launch operations. The software displays probability of impact information for each ship near the hazardous area during the time immediately preceding the launch of an unguided vehicle. Wallops range safety officers need to be sure that the risk to humans is below a certain threshold during each use of the Wallops Flight Facility Launch Range. Under the variable conditions that can exist at launch time, the decision to launch must be made in a timely manner to ensure a successful mission while not exceeding those risk criteria. Range safety officers need a tool that can give them the needed probability of impact information quickly, and in a format that is clearly understandable. This application is meant to fill that need. The software is a reuse of part of software developed for an earlier project: Ship Surveillance Software System (S4). The S4 project was written in C++ using Microsoft Visual Studio 6. The data structures and dialog templates from it were copied into a new application that calls the implementation of the algorithms from S4 and displays the results as needed. In the S4 software, the list of ships in the area was received from one local radar interface and from operators who entered the ship information manually. The SureTrak Probability of Impact Display application receives ship data from two local radars as well as the SureTrak system, eliminating the need for manual data entry.
Contributions to quantum probability

International Nuclear Information System (INIS)

Fritz, Tobias

2010-01-01

distribution of a quantum-mechanical von Neumann measurement with postselection, given that the scalar product between the initial and the final state is known as well as the success probability of the postselection. An intermediate von Neumann measurement can enhance transition probabilities between states such that the error probability shrinks by a factor of up to 2. Chapter 4: A presentation of the category of stochastic matrices. This chapter gives generators and relations for the strict monoidal category of probabilistic maps on finite cardinals (i.e., stochastic matrices). Chapter 5: Convex Spaces: Definition and Examples. We try to promote convex spaces as an abstract concept of convexity which was introduced by Stone as ''barycentric calculus''. A convex space is a set where one can take convex combinations in a consistent way. By identifying the corresponding Lawvere theory as the category from chapter 4 and using the results obtained there, we give a different proof of a result of Swirszcz which shows that convex spaces can be identified with algebras of a finitary version of the Giry monad. After giving an extensive list of examples of convex sets as they appear throughout mathematics and theoretical physics, we note that there also exist convex spaces that cannot be embedded into a vector space: semilattices are a class of examples of purely combinatorial type. In an information-theoretic interpretation, convex subsets of vector spaces are probabilistic, while semilattices are possibilistic. Convex spaces unify these two concepts. (orig.)
Maximum likelihood pedigree reconstruction using integer linear programming.

Science.gov (United States)

Cussens, James; Bartlett, Mark; Jones, Elinor M; Sheehan, Nuala A

2013-01-01

Large population biobanks of unrelated individuals have been highly successful in detecting common genetic variants affecting diseases of public health concern. However, they lack the statistical power to detect more modest gene-gene and gene-environment interaction effects or the effects of rare variants for which related individuals are ideally required. In reality, most large population studies will undoubtedly contain sets of undeclared relatives, or pedigrees. Although a crude measure of relatedness might sometimes suffice, having a good estimate of the true pedigree would be much more informative if this could be obtained efficiently. Relatives are more likely to share longer haplotypes around disease susceptibility loci and are hence biologically more informative for rare variants than unrelated cases and controls. Distant relatives are arguably more useful for detecting variants with small effects because they are less likely to share masking environmental effects. Moreover, the identification of relatives enables appropriate adjustments of statistical analyses that typically assume unrelatedness. We propose to exploit an integer linear programming optimisation approach to pedigree learning, which is adapted to find valid pedigrees by imposing appropriate constraints. Our method is not restricted to small pedigrees and is guaranteed to return a maximum likelihood pedigree. With additional constraints, we can also search for multiple high-probability pedigrees and thus account for the inherent uncertainty in any particular pedigree reconstruction. The true pedigree is found very quickly by comparison with other methods when all individuals are observed. Extensions to more complex problems seem feasible. © 2012 Wiley Periodicals, Inc.
COVAL, Compound Probability Distribution for Function of Probability Distribution

International Nuclear Information System (INIS)

Astolfi, M.; Elbaz, J.

1979-01-01

1 - Nature of the physical problem solved: Computation of the probability distribution of a function of variables, given the probability distribution of the variables themselves. 'COVAL' has been applied to reliability analysis of a structure subject to random loads. 2 - Method of solution: Numerical transformation of probability distributions
Off-diagonal long-range order, cycle probabilities, and condensate fraction in the ideal Bose gas.

Science.gov (United States)

Chevallier, Maguelonne; Krauth, Werner

2007-11-01

We discuss the relationship between the cycle probabilities in the path-integral representation of the ideal Bose gas, off-diagonal long-range order, and Bose-Einstein condensation. Starting from the Landsberg recursion relation for the canonic partition function, we use elementary considerations to show that in a box of size L3 the sum of the cycle probabilities of length k>L2 equals the off-diagonal long-range order parameter in the thermodynamic limit. For arbitrary systems of ideal bosons, the integer derivative of the cycle probabilities is related to the probability of condensing k bosons. We use this relation to derive the precise form of the pik in the thermodynamic limit. We also determine the function pik for arbitrary systems. Furthermore, we use the cycle probabilities to compute the probability distribution of the maximum-length cycles both at T=0, where the ideal Bose gas reduces to the study of random permutations, and at finite temperature. We close with comments on the cycle probabilities in interacting Bose gases.
Component fragility data base for reliability and probability studies

International Nuclear Information System (INIS)

Bandyopadhyay, K.; Hofmayer, C.; Kassier, M.; Pepper, S.

1989-01-01

Safety-related equipment in a nuclear plant plays a vital role in its proper operation and control, and failure of such equipment due to an earthquake may pose a risk to the safe operation of the plant. Therefore, in order to assess the overall reliability of a plant, the reliability of performance of the equipment should be studied first. The success of a reliability or a probability study depends to a great extent on the data base. To meet this demand, Brookhaven National Laboratory (BNL) has formed a test data base relating the seismic capacity of equipment specimens to the earthquake levels. Subsequently, the test data have been analyzed for use in reliability and probability studies. This paper describes the data base and discusses the analysis methods. The final results that can be directly used in plant reliability and probability studies are also presented in this paper
On Probability Leakage

OpenAIRE

Briggs, William M.

2012-01-01

The probability leakage of model M with respect to evidence E is defined. Probability leakage is a kind of model error. It occurs when M implies that events $y$, which are impossible given E, have positive probability. Leakage does not imply model falsification. Models with probability leakage cannot be calibrated empirically. Regression models, which are ubiquitous in statistical practice, often evince probability leakage.
Future changes over the Himalayas: Maximum and minimum temperature

Science.gov (United States)

Dimri, A. P.; Kumar, D.; Choudhary, A.; Maharana, P.

2018-03-01

An assessment of the projection of minimum and maximum air temperature over the Indian Himalayan region (IHR) from the COordinated Regional Climate Downscaling EXperiment- South Asia (hereafter, CORDEX-SA) regional climate model (RCM) experiments have been carried out under two different Representative Concentration Pathway (RCP) scenarios. The major aim of this study is to assess the probable future changes in the minimum and maximum climatology and its long-term trend under different RCPs along with the elevation dependent warming over the IHR. A number of statistical analysis such as changes in mean climatology, long-term spatial trend and probability distribution function are carried out to detect the signals of changes in climate. The study also tries to quantify the uncertainties associated with different model experiments and their ensemble in space, time and for different seasons. The model experiments and their ensemble show prominent cold bias over Himalayas for present climate. However, statistically significant higher warming rate (0.23-0.52 °C/decade) for both minimum and maximum air temperature (Tmin and Tmax) is observed for all the seasons under both RCPs. The rate of warming intensifies with the increase in the radiative forcing under a range of greenhouse gas scenarios starting from RCP4.5 to RCP8.5. In addition to this, a wide range of spatial variability and disagreements in the magnitude of trend between different models describes the uncertainty associated with the model projections and scenarios. The projected rate of increase of Tmin may destabilize the snow formation at the higher altitudes in the northern and western parts of Himalayan region, while rising trend of Tmax over southern flank may effectively melt more snow cover. Such combined effect of rising trend of Tmin and Tmax may pose a potential threat to the glacial deposits. The overall trend of Diurnal temperature range (DTR) portrays increasing trend across entire area with

Maximum entropy approach to statistical inference for an ocean acoustic waveguide.

Science.gov (United States)

Knobles, D P; Sagers, J D; Koch, R A

2012-02-01

A conditional probability distribution suitable for estimating the statistical properties of ocean seabed parameter values inferred from acoustic measurements is derived from a maximum entropy principle. The specification of the expectation value for an error function constrains the maximization of an entropy functional. This constraint determines the sensitivity factor (β) to the error function of the resulting probability distribution, which is a canonical form that provides a conservative estimate of the uncertainty of the parameter values. From the conditional distribution, marginal distributions for individual parameters can be determined from integration over the other parameters. The approach is an alternative to obtaining the posterior probability distribution without an intermediary determination of the likelihood function followed by an application of Bayes' rule. In this paper the expectation value that specifies the constraint is determined from the values of the error function for the model solutions obtained from a sparse number of data samples. The method is applied to ocean acoustic measurements taken on the New Jersey continental shelf. The marginal probability distribution for the values of the sound speed ratio at the surface of the seabed and the source levels of a towed source are examined for different geoacoustic model representations. © 2012 Acoustical Society of America
PTree: pattern-based, stochastic search for maximum parsimony phylogenies

Directory of Open Access Journals (Sweden)

Ivan Gregor

2013-06-01

Full Text Available Phylogenetic reconstruction is vital to analyzing the evolutionary relationship of genes within and across populations of different species. Nowadays, with next generation sequencing technologies producing sets comprising thousands of sequences, robust identification of the tree topology, which is optimal according to standard criteria such as maximum parsimony, maximum likelihood or posterior probability, with phylogenetic inference methods is a computationally very demanding task. Here, we describe a stochastic search method for a maximum parsimony tree, implemented in a software package we named PTree. Our method is based on a new pattern-based technique that enables us to infer intermediate sequences efficiently where the incorporation of these sequences in the current tree topology yields a phylogenetic tree with a lower cost. Evaluation across multiple datasets showed that our method is comparable to the algorithms implemented in PAUP* or TNT, which are widely used by the bioinformatics community, in terms of topological accuracy and runtime. We show that our method can process large-scale datasets of 1,000–8,000 sequences. We believe that our novel pattern-based method enriches the current set of tools and methods for phylogenetic tree inference. The software is available under: http://algbio.cs.uni-duesseldorf.de/webapps/wa-download/.
PTree: pattern-based, stochastic search for maximum parsimony phylogenies.

Science.gov (United States)

Gregor, Ivan; Steinbrück, Lars; McHardy, Alice C

2013-01-01

Phylogenetic reconstruction is vital to analyzing the evolutionary relationship of genes within and across populations of different species. Nowadays, with next generation sequencing technologies producing sets comprising thousands of sequences, robust identification of the tree topology, which is optimal according to standard criteria such as maximum parsimony, maximum likelihood or posterior probability, with phylogenetic inference methods is a computationally very demanding task. Here, we describe a stochastic search method for a maximum parsimony tree, implemented in a software package we named PTree. Our method is based on a new pattern-based technique that enables us to infer intermediate sequences efficiently where the incorporation of these sequences in the current tree topology yields a phylogenetic tree with a lower cost. Evaluation across multiple datasets showed that our method is comparable to the algorithms implemented in PAUP* or TNT, which are widely used by the bioinformatics community, in terms of topological accuracy and runtime. We show that our method can process large-scale datasets of 1,000-8,000 sequences. We believe that our novel pattern-based method enriches the current set of tools and methods for phylogenetic tree inference. The software is available under: http://algbio.cs.uni-duesseldorf.de/webapps/wa-download/.
Bayesian Maximum Entropy prediction of soil categories using a traditional soil map as soft information.

NARCIS (Netherlands)

Brus, D.J.; Bogaert, P.; Heuvelink, G.B.M.

2008-01-01

Bayesian Maximum Entropy was used to estimate the probabilities of occurrence of soil categories in the Netherlands, and to simulate realizations from the associated multi-point pdf. Besides the hard observations (H) of the categories at 8369 locations, the soil map of the Netherlands 1:50 000 was
Quantum probabilities as Dempster-Shafer probabilities in the lattice of subspaces

International Nuclear Information System (INIS)

Vourdas, A.

2014-01-01

The orthocomplemented modular lattice of subspaces L[H(d)], of a quantum system with d-dimensional Hilbert space H(d), is considered. A generalized additivity relation which holds for Kolmogorov probabilities is violated by quantum probabilities in the full lattice L[H(d)] (it is only valid within the Boolean subalgebras of L[H(d)]). This suggests the use of more general (than Kolmogorov) probability theories, and here the Dempster-Shafer probability theory is adopted. An operator D(H 1 ,H 2 ), which quantifies deviations from Kolmogorov probability theory is introduced, and it is shown to be intimately related to the commutator of the projectors P(H 1 ),P(H 2 ), to the subspaces H 1 , H 2 . As an application, it is shown that the proof of the inequalities of Clauser, Horne, Shimony, and Holt for a system of two spin 1/2 particles is valid for Kolmogorov probabilities, but it is not valid for Dempster-Shafer probabilities. The violation of these inequalities in experiments supports the interpretation of quantum probabilities as Dempster-Shafer probabilities
Bayesian Reliability Estimation for Deteriorating Systems with Limited Samples Using the Maximum Entropy Approach

Directory of Open Access Journals (Sweden)

Ning-Cong Xiao

2013-12-01

Full Text Available In this paper the combinations of maximum entropy method and Bayesian inference for reliability assessment of deteriorating system is proposed. Due to various uncertainties, less data and incomplete information, system parameters usually cannot be determined precisely. These uncertainty parameters can be modeled by fuzzy sets theory and the Bayesian inference which have been proved to be useful for deteriorating systems under small sample sizes. The maximum entropy approach can be used to calculate the maximum entropy density function of uncertainty parameters more accurately for it does not need any additional information and assumptions. Finally, two optimization models are presented which can be used to determine the lower and upper bounds of systems probability of failure under vague environment conditions. Two numerical examples are investigated to demonstrate the proposed method.
Contributions to quantum probability

Energy Technology Data Exchange (ETDEWEB)

Fritz, Tobias

2010-06-25

finite set can occur as the outcome distribution of a quantum-mechanical von Neumann measurement with postselection, given that the scalar product between the initial and the final state is known as well as the success probability of the postselection. An intermediate von Neumann measurement can enhance transition probabilities between states such that the error probability shrinks by a factor of up to 2. Chapter 4: A presentation of the category of stochastic matrices. This chapter gives generators and relations for the strict monoidal category of probabilistic maps on finite cardinals (i.e., stochastic matrices). Chapter 5: Convex Spaces: Definition and Examples. We try to promote convex spaces as an abstract concept of convexity which was introduced by Stone as ''barycentric calculus''. A convex space is a set where one can take convex combinations in a consistent way. By identifying the corresponding Lawvere theory as the category from chapter 4 and using the results obtained there, we give a different proof of a result of Swirszcz which shows that convex spaces can be identified with algebras of a finitary version of the Giry monad. After giving an extensive list of examples of convex sets as they appear throughout mathematics and theoretical physics, we note that there also exist convex spaces that cannot be embedded into a vector space: semilattices are a class of examples of purely combinatorial type. In an information-theoretic interpretation, convex subsets of vector spaces are probabilistic, while semilattices are possibilistic. Convex spaces unify these two concepts. (orig.)
PROBABILITY SURVEYS , CONDITIONAL PROBABILITIES AND ECOLOGICAL RISK ASSESSMENT

Science.gov (United States)

We show that probability-based environmental resource monitoring programs, such as the U.S. Environmental Protection Agency's (U.S. EPA) Environmental Monitoring and Assessment Program, and conditional probability analysis can serve as a basis for estimating ecological risk over ...
Human errors evaluation for muster in emergency situations applying human error probability index (HEPI, in the oil company warehouse in Hamadan City

Directory of Open Access Journals (Sweden)

2012-12-01

Full Text Available Introduction: Emergency situation is one of the influencing factors on human error. The aim of this research was purpose to evaluate human error in emergency situation of fire and explosion at the oil company warehouse in Hamadan city applying human error probability index (HEPI. . Material and Method: First, the scenario of emergency situation of those situation of fire and explosion at the oil company warehouse was designed and then maneuver against, was performed. The scaled questionnaire of muster for the maneuver was completed in the next stage. Collected data were analyzed to calculate the probability success for the 18 actions required in an emergency situation from starting point of the muster until the latest action to temporary sheltersafe. .Result: The result showed that the highest probability of error occurrence was related to make safe workplace (evaluation phase with 32.4 % and lowest probability of occurrence error in detection alarm (awareness phase with 1.8 %, probability. The highest severity of error was in the evaluation phase and the lowest severity of error was in the awareness and recovery phase. Maximum risk level was related to the evaluating exit routes and selecting one route and choosy another exit route and minimum risk level was related to the four evaluation phases. . Conclusion: To reduce the risk of reaction in the exit phases of an emergency situation, the following actions are recommended, based on the finding in this study: A periodic evaluation of the exit phase and modifying them if necessary, conducting more maneuvers and analyzing this results along with a sufficient feedback to the employees.
Quantum operations, state transformations and probabilities

International Nuclear Information System (INIS)

Chefles, Anthony

2002-01-01

In quantum operations, probabilities characterize both the degree of the success of a state transformation and, as density operator eigenvalues, the degree of mixedness of the final state. We give a unified treatment of pure→pure state transformations, covering both probabilistic and deterministic cases. We then discuss the role of majorization in describing the dynamics of mixing in quantum operations. The conditions for mixing enhancement for all initial states are derived. We show that mixing is monotonically decreasing for deterministic pure→pure transformations, and discuss the relationship between these transformations and deterministic local operations with classical communication entanglement transformations
Probability Analysis of the Wave-Slamming Pressure Values of the Horizontal Deck with Elastic Support

Science.gov (United States)

Zuo, Weiguang; Liu, Ming; Fan, Tianhui; Wang, Pengtao

2018-06-01

This paper presents the probability distribution of the slamming pressure from an experimental study of regular wave slamming on an elastically supported horizontal deck. The time series of the slamming pressure during the wave impact were first obtained through statistical analyses on experimental data. The exceeding probability distribution of the maximum slamming pressure peak and distribution parameters were analyzed, and the results show that the exceeding probability distribution of the maximum slamming pressure peak accords with the three-parameter Weibull distribution. Furthermore, the range and relationships of the distribution parameters were studied. The sum of the location parameter D and the scale parameter L was approximately equal to 1.0, and the exceeding probability was more than 36.79% when the random peak was equal to the sample average during the wave impact. The variation of the distribution parameters and slamming pressure under different model conditions were comprehensively presented, and the parameter values of the Weibull distribution of wave-slamming pressure peaks were different due to different test models. The parameter values were found to decrease due to the increased stiffness of the elastic support. The damage criterion of the structure model caused by the wave impact was initially discussed, and the structure model was destroyed when the average slamming time was greater than a certain value during the duration of the wave impact. The conclusions of the experimental study were then described.
maximum neutron flux at thermal nuclear reactors

International Nuclear Information System (INIS)

Strugar, P.

1968-10-01

Since actual research reactors are technically complicated and expensive facilities it is important to achieve savings by appropriate reactor lattice configurations. There is a number of papers, and practical examples of reactors with central reflector, dealing with spatial distribution of fuel elements which would result in higher neutron flux. Common disadvantage of all the solutions is that the choice of best solution is done starting from the anticipated spatial distributions of fuel elements. The weakness of these approaches is lack of defined optimization criteria. Direct approach is defined as follows: determine the spatial distribution of fuel concentration starting from the condition of maximum neutron flux by fulfilling the thermal constraints. Thus the problem of determining the maximum neutron flux is solving a variational problem which is beyond the possibilities of classical variational calculation. This variational problem has been successfully solved by applying the maximum principle of Pontrjagin. Optimum distribution of fuel concentration was obtained in explicit analytical form. Thus, spatial distribution of the neutron flux and critical dimensions of quite complex reactor system are calculated in a relatively simple way. In addition to the fact that the results are innovative this approach is interesting because of the optimization procedure itself [sr
How long do centenarians survive? Life expectancy and maximum lifespan.

Science.gov (United States)

Modig, K; Andersson, T; Vaupel, J; Rau, R; Ahlbom, A

2017-08-01

The purpose of this study was to explore the pattern of mortality above the age of 100 years. In particular, we aimed to examine whether Scandinavian data support the theory that mortality reaches a plateau at particularly old ages. Whether the maximum length of life increases with time was also investigated. The analyses were based on individual level data on all Swedish and Danish centenarians born from 1870 to 1901; in total 3006 men and 10 963 women were included. Birth cohort-specific probabilities of dying were calculated. Exact ages were used for calculations of maximum length of life. Whether maximum age changed over time was analysed taking into account increases in cohort size. The results confirm that there has not been any improvement in mortality amongst centenarians in the past 30 years and that the current rise in life expectancy is driven by reductions in mortality below the age of 100 years. The death risks seem to reach a plateau of around 50% at the age 103 years for men and 107 years for women. Despite the rising life expectancy, the maximum age does not appear to increase, in particular after accounting for the increasing number of individuals of advanced age. Mortality amongst centenarians is not changing despite improvements at younger ages. An extension of the maximum lifespan and a sizeable extension of life expectancy both require reductions in mortality above the age of 100 years. © 2017 The Association for the Publication of the Journal of Internal Medicine.
Posterior probability of linkage and maximal lod score.

Science.gov (United States)

Génin, E; Martinez, M; Clerget-Darpoux, F

1995-01-01

To detect linkage between a trait and a marker, Morton (1955) proposed to calculate the lod score z(theta 1) at a given value theta 1 of the recombination fraction. If z(theta 1) reaches +3 then linkage is concluded. However, in practice, lod scores are calculated for different values of the recombination fraction between 0 and 0.5 and the test is based on the maximum value of the lod score Zmax. The impact of this deviation of the test on the probability that in fact linkage does not exist, when linkage was concluded, is documented here. This posterior probability of no linkage can be derived by using Bayes' theorem. It is less than 5% when the lod score at a predetermined theta 1 is used for the test. But, for a Zmax of +3, we showed that it can reach 16.4%. Thus, considering a composite alternative hypothesis instead of a single one decreases the reliability of the test. The reliability decreases rapidly when Zmax is less than +3. Given a Zmax of +2.5, there is a 33% chance that linkage does not exist. Moreover, the posterior probability depends not only on the value of Zmax but also jointly on the family structures and on the genetic model. For a given Zmax, the chance that linkage exists may then vary.
Effects of fasting on maximum thermogenesis in temperature-acclimated rats

Science.gov (United States)

Wang, L. C. H.

1981-09-01

To further investigate the limiting effect of substrates on maximum thermogenesis in acute cold exposure, the present study examined the prevalence of this effect at different thermogenic capabilities consequent to cold- or warm-acclimation. Male Sprague-Dawley rats (n=11) were acclimated to 6, 16 and 26‡C, in succession, their thermogenic capabilities after each acclimation temperature were measured under helium-oxygen (21% oxygen, balance helium) at -10‡C after overnight fasting or feeding. Regardless of feeding conditions, both maximum and total heat production were significantly greater in 6>16>26‡C-acclimated conditions. In the fed state, the total heat production was significantly greater than that in the fasted state at all acclimating temperatures but the maximum thermogenesis was significant greater only in the 6 and 16‡C-acclimated states. The results indicate that the limiting effect of substrates on maximum and total thermogenesis is independent of the magnitude of thermogenic capability, suggesting a substrate-dependent component in restricting the effective expression of existing aerobic metabolic capability even under severe stress.
A hydroclimatological approach to predicting regional landslide probability using Landlab

Directory of Open Access Journals (Sweden)

R. Strauch

2018-02-01

Full Text Available We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at mid-elevations (1400 to 2400 m, and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.
A hydroclimatological approach to predicting regional landslide probability using Landlab

Science.gov (United States)

Strauch, Ronda; Istanbulluoglu, Erkan; Nudurupati, Sai Siddhartha; Bandaragoda, Christina; Gasparini, Nicole M.; Tucker, Gregory E.

2018-02-01

We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at mid-elevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.
Probability an introduction

CERN Document Server

Goldberg, Samuel

1960-01-01

Excellent basic text covers set theory, probability theory for finite sample spaces, binomial theorem, probability distributions, means, standard deviations, probability function of binomial distribution, more. Includes 360 problems with answers for half.
PATTERNS OF THE MAXIMUM RAINFALL AMOUNTS REGISTERED IN 24 HOURS WITHIN THE OLTENIA PLAIN

Directory of Open Access Journals (Sweden)

ALINA VLĂDUŢ

2012-03-01

Full Text Available Patterns of the maximum rainfall amounts registered in 24 hours within the Oltenia Plain. The present study aims at rendering the main features of the maximum rainfall amounts registered in 24 h within the Oltenia Plain. We used 30-year time series (1980-2009 for seven meteorological stations. Generally, the maximum amounts in 24 h display the same pattern as the monthly mean amounts, namely higher values in the interval May-October. In terms of mean values, the highest amounts are registered in the western and northern extremity of the plain. The maximum values generally exceed 70 mm at all meteorological stations: D.T. Severin, 224 mm, July 1999; Slatina, 104.8 mm, August 2002; Caracal, 92.2 m, July 1991; Bechet, 80.8 mm, July 2006; Craiova, 77.6 mm, April 2003. During the cold season, there was noticed a greater uniformity all over the plain, due to the cyclonic origin of rainfalls compared to the warm season, when thermal convection is quite active and it triggers local showers. In order to better emphasize the peculiarities of this parameter, we have calculated the frequency on different value classes (eight classes, as well as the probability of appearance of different amounts. Thus, it resulted that the highest frequency (25-35% is held by the first two classes of values (0-10 mm; 10.1-20 mm. The lowest frequency is registered in case of the amounts of more than 100 mm, which generally display a probability of occurrence of less than 1% and only in the western and eastern extremities of the plain.
Success tree method of resources evaluation

International Nuclear Information System (INIS)

Chen Qinglan; Sun Wenpeng

1994-01-01

By applying the reliability theory in system engineering, the success tree method is used to transfer the expert's recognition on metallogenetic regularities into the form of the success tree. The aim of resources evaluation is achieved by means of calculating the metallogenetic probability or favorability of the top event of the success tree. This article introduces in detail, the source, principle of the success tree method and three kinds of calculation methods, expounds concretely how to establish the success tree of comprehensive uranium metallogenesis as well as the procedure from which the resources evaluation is performed. Because this method has not restrictions on the number of known deposits and calculated area, it is applicable to resources evaluation for different mineral species, types and scales and possesses good prospects of development

An extended car-following model considering random safety distance with different probabilities

Science.gov (United States)

Wang, Jufeng; Sun, Fengxin; Cheng, Rongjun; Ge, Hongxia; Wei, Qi

2018-02-01

Because of the difference in vehicle type or driving skill, the driving strategy is not exactly the same. The driving speeds of the different vehicles may be different for the same headway. Since the optimal velocity function is just determined by the safety distance besides the maximum velocity and headway, an extended car-following model accounting for random safety distance with different probabilities is proposed in this paper. The linear stable condition for this extended traffic model is obtained by using linear stability theory. Numerical simulations are carried out to explore the complex phenomenon resulting from multiple safety distance in the optimal velocity function. The cases of multiple types of safety distances selected with different probabilities are presented. Numerical results show that the traffic flow with multiple safety distances with different probabilities will be more unstable than that with single type of safety distance, and will result in more stop-and-go phenomena.
Probability 1/e

Science.gov (United States)

Koo, Reginald; Jones, Martin L.

2011-01-01

Quite a number of interesting problems in probability feature an event with probability equal to 1/e. This article discusses three such problems and attempts to explain why this probability occurs with such frequency.
Quantum theory of successive projective measurements

International Nuclear Information System (INIS)

Johansen, Lars M.

2007-01-01

We show that a quantum state may be represented as the sum of a joint probability and a complex quantum modification term. The joint probability and the modification term can both be observed in successive projective measurements. The complex modification term is a measure of measurement disturbance. A selective phase rotation is needed to obtain the imaginary part. This leads to a complex quasiprobability: The Kirkwood distribution. We show that the Kirkwood distribution contains full information about the state if the two observables are maximal and complementary. The Kirkwood distribution gives another picture of state reduction. In a nonselective measurement, the modification term vanishes. A selective measurement leads to a quantum state as a non-negative conditional probability. We demonstrate the special significance of the Schwinger basis
Maximum likelihood sequence estimation for optical complex direct modulation.

Science.gov (United States)

Che, Di; Yuan, Feng; Shieh, William

2017-04-17

Semiconductor lasers are versatile optical transmitters in nature. Through the direct modulation (DM), the intensity modulation is realized by the linear mapping between the injection current and the light power, while various angle modulations are enabled by the frequency chirp. Limited by the direct detection, DM lasers used to be exploited only as 1-D (intensity or angle) transmitters by suppressing or simply ignoring the other modulation. Nevertheless, through the digital coherent detection, simultaneous intensity and angle modulations (namely, 2-D complex DM, CDM) can be realized by a single laser diode. The crucial technique of CDM is the joint demodulation of intensity and differential phase with the maximum likelihood sequence estimation (MLSE), supported by a closed-form discrete signal approximation of frequency chirp to characterize the MLSE transition probability. This paper proposes a statistical method for the transition probability to significantly enhance the accuracy of the chirp model. Using the statistical estimation, we demonstrate the first single-channel 100-Gb/s PAM-4 transmission over 1600-km fiber with only 10G-class DM lasers.
Rejecting probability summation for radial frequency patterns, not so Quick!

Science.gov (United States)

Baldwin, Alex S; Schmidtmann, Gunnar; Kingdom, Frederick A A; Hess, Robert F

2016-05-01

Radial frequency (RF) patterns are used to assess how the visual system processes shape. They are thought to be detected globally. This is supported by studies that have found summation for RF patterns to be greater than what is possible if the parts were being independently detected and performance only then improved with an increasing number of cycles by probability summation between them. However, the model of probability summation employed in these previous studies was based on High Threshold Theory (HTT), rather than Signal Detection Theory (SDT). We conducted rating scale experiments to investigate the receiver operating characteristics. We find these are of the curved form predicted by SDT, rather than the straight lines predicted by HTT. This means that to test probability summation we must use a model based on SDT. We conducted a set of summation experiments finding that thresholds decrease as the number of modulated cycles increases at approximately the same rate as previously found. As this could be consistent with either additive or probability summation, we performed maximum-likelihood fitting of a set of summation models (Matlab code provided in our Supplementary material) and assessed the fits using cross validation. We find we are not able to distinguish whether the responses to the parts of an RF pattern are combined by additive or probability summation, because the predictions are too similar. We present similar results for summation between separate RF patterns, suggesting that the summation process there may be the same as that within a single RF. Copyright © 2016 Elsevier Ltd. All rights reserved.
Consistent probabilities in loop quantum cosmology

International Nuclear Information System (INIS)

Craig, David A; Singh, Parampreet

2013-01-01

A fundamental issue for any quantum cosmological theory is to specify how probabilities can be assigned to various quantum events or sequences of events such as the occurrence of singularities or bounces. In previous work, we have demonstrated how this issue can be successfully addressed within the consistent histories approach to quantum theory for Wheeler–DeWitt-quantized cosmological models. In this work, we generalize that analysis to the exactly solvable loop quantization of a spatially flat, homogeneous and isotropic cosmology sourced with a massless, minimally coupled scalar field known as sLQC. We provide an explicit, rigorous and complete decoherent-histories formulation for this model and compute the probabilities for the occurrence of a quantum bounce versus a singularity. Using the scalar field as an emergent internal time, we show for generic states that the probability for a singularity to occur in this model is zero, and that of a bounce is unity, complementing earlier studies of the expectation values of the volume and matter density in this theory. We also show from the consistent histories point of view that all states in this model, whether quantum or classical, achieve arbitrarily large volume in the limit of infinite ‘past’ or ‘future’ scalar ‘time’, in the sense that the wave function evaluated at any arbitrary fixed value of the volume vanishes in that limit. Finally, we briefly discuss certain misconceptions concerning the utility of the consistent histories approach in these models. (paper)
Surface of Maximums of AR(2 Process Spectral Densities and its Application in Time Series Statistics

Directory of Open Access Journals (Sweden)

Alexander V. Ivanov

2017-09-01

Conclusions. The obtained formula of surface of maximums of noise spectral densities gives an opportunity to realize for which values of AR(2 process characteristic polynomial coefficients it is possible to look for greater rate of convergence to zero of the probabilities of large deviations of the considered estimates.
Foundations of probability

International Nuclear Information System (INIS)

Fraassen, B.C. van

1979-01-01

The interpretation of probabilities in physical theories are considered, whether quantum or classical. The following points are discussed 1) the functions P(μ, Q) in terms of which states and propositions can be represented, are classical (Kolmogoroff) probabilities, formally speaking, 2) these probabilities are generally interpreted as themselves conditional, and the conditions are mutually incompatible where the observables are maximal and 3) testing of the theory typically takes the form of confronting the expectation values of observable Q calculated with probability measures P(μ, Q) for states μ; hence, of comparing the probabilities P(μ, Q)(E) with the frequencies of occurrence of the corresponding events. It seems that even the interpretation of quantum mechanics, in so far as it concerns what the theory says about the empirical (i.e. actual, observable) phenomena, deals with the confrontation of classical probability measures with observable frequencies. This confrontation is studied. (Auth./C.F.)
Precise charge density studies by maximum entropy method

CERN Document Server

Takata, M

2003-01-01

For the production research and development of nanomaterials, their structural information is indispensable. Recently, a sophisticated analytical method, which is based on information theory, the Maximum Entropy Method (MEM) using synchrotron radiation powder data, has been successfully applied to determine precise charge densities of metallofullerenes and nanochannel microporous compounds. The results revealed various endohedral natures of metallofullerenes and one-dimensional array formation of adsorbed gas molecules in nanochannel microporous compounds. The concept of MEM analysis was also described briefly. (author)
A Bernstein-Von Mises Theorem for discrete probability distributions

OpenAIRE

Boucheron, S.; Gassiat, E.

2008-01-01

We investigate the asymptotic normality of the posterior distribution in the discrete setting, when model dimension increases with sample size. We consider a probability mass function θ0 on ℕ∖{0} and a sequence of truncation levels (kn)n satisfying kn3≤ninf i≤knθ0(i). Let θ̂ denote the maximum likelihood estimate of (θ0(i))i≤kn and let Δn(θ0) denote the kn-dimensional vector which i-th coordinate is defined by $\\sqrt{n}(\\hat{\\theta}_{n}(i)-\\theta_{0}(i))$ for 1≤i≤kn. We check that under mild ...
External Validation of a Prediction Model for Successful External Cephalic Version

NARCIS (Netherlands)

de Hundt, Marcella; Vlemmix, Floortje; Kok, Marjolein; van der Steeg, Jan W.; Bais, Joke M.; Mol, Ben W.; van der Post, Joris A.

2012-01-01

We sought external validation of a prediction model for the probability of a successful external cephalic version (ECV). We evaluated the performance of the prediction model with calibration and discrimination. For clinical practice, we developed a score chart to calculate the probability of a
Non-Archimedean Probability

NARCIS (Netherlands)

Benci, Vieri; Horsten, Leon; Wenmackers, Sylvia

We propose an alternative approach to probability theory closely related to the framework of numerosity theory: non-Archimedean probability (NAP). In our approach, unlike in classical probability theory, all subsets of an infinite sample space are measurable and only the empty set gets assigned
Spatial patterns of breeding success of grizzly bears derived from hierarchical multistate models.

Science.gov (United States)

Fisher, Jason T; Wheatley, Matthew; Mackenzie, Darryl

2014-10-01

Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears (Ursus arctos) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low-elevation wetlands or mid-elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy-herbaceous alpine ecotones-were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection. © 2014 Society
Maximum Power Point Tracking of Photovoltaic System for Traffic Light Application

Directory of Open Access Journals (Sweden)

Riza Muhida

2013-07-01

Full Text Available Photovoltaic traffic light system is a significant application of renewable energy source. The development of the system is an alternative effort of local authority to reduce expenditure for paying fees to power supplier which the power comes from conventional energy source. Since photovoltaic (PV modules still have relatively low conversion efficiency, an alternative control of maximum power point tracking (MPPT method is applied to the traffic light system. MPPT is intended to catch up the maximum power at daytime in order to charge the battery at the maximum rate in which the power from the battery is intended to be used at night time or cloudy day. MPPT is actually a DC-DC converter that can step up or down voltage in order to achieve the maximum power using Pulse Width Modulation (PWM control. From experiment, we obtained the voltage of operation using MPPT is at 16.454 V, this value has error of 2.6%, if we compared with maximum power point voltage of PV module that is 16.9 V. Based on this result it can be said that this MPPT control works successfully to deliver the power from PV module to battery maximally.
Handbook of probability

CERN Document Server

Florescu, Ionut

2013-01-01

THE COMPLETE COLLECTION NECESSARY FOR A CONCRETE UNDERSTANDING OF PROBABILITY Written in a clear, accessible, and comprehensive manner, the Handbook of Probability presents the fundamentals of probability with an emphasis on the balance of theory, application, and methodology. Utilizing basic examples throughout, the handbook expertly transitions between concepts and practice to allow readers an inclusive introduction to the field of probability. The book provides a useful format with self-contained chapters, allowing the reader easy and quick reference. Each chapter includes an introductio
Probability-1

CERN Document Server

Shiryaev, Albert N

2016-01-01

This book contains a systematic treatment of probability from the ground up, starting with intuitive ideas and gradually developing more sophisticated subjects, such as random walks, martingales, Markov chains, the measure-theoretic foundations of probability theory, weak convergence of probability measures, and the central limit theorem. Many examples are discussed in detail, and there are a large number of exercises. The book is accessible to advanced undergraduates and can be used as a text for independent study. To accommodate the greatly expanded material in the third edition of Probability, the book is now divided into two volumes. This first volume contains updated references and substantial revisions of the first three chapters of the second edition. In particular, new material has been added on generating functions, the inclusion-exclusion principle, theorems on monotonic classes (relying on a detailed treatment of “π-λ” systems), and the fundamental theorems of mathematical statistics.
Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines

Science.gov (United States)

Malley, J. D.; Kruppa, J.; Dasgupta, A.; Malley, K. G.; Ziegler, A.

2011-01-01

Summary Background Most machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. Objectives The aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities. Methods Two random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians. Results Simulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software. Conclusions Random forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications. PMID:21915433
Maximum entropy and Bayesian methods

International Nuclear Information System (INIS)

Smith, C.R.; Erickson, G.J.; Neudorfer, P.O.

1992-01-01

Bayesian probability theory and Maximum Entropy methods are at the core of a new view of scientific inference. These 'new' ideas, along with the revolution in computational methods afforded by modern computers allow astronomers, electrical engineers, image processors of any type, NMR chemists and physicists, and anyone at all who has to deal with incomplete and noisy data, to take advantage of methods that, in the past, have been applied only in some areas of theoretical physics. The title workshops have been the focus of a group of researchers from many different fields, and this diversity is evident in this book. There are tutorial and theoretical papers, and applications in a very wide variety of fields. Almost any instance of dealing with incomplete and noisy data can be usefully treated by these methods, and many areas of theoretical research are being enhanced by the thoughtful application of Bayes' theorem. Contributions contained in this volume present a state-of-the-art overview that will be influential and useful for many years to come
Determination of point of maximum likelihood in failure domain using genetic algorithms

International Nuclear Information System (INIS)

Obadage, A.S.; Harnpornchai, N.

2006-01-01

The point of maximum likelihood in a failure domain yields the highest value of the probability density function in the failure domain. The maximum-likelihood point thus represents the worst combination of random variables that contribute in the failure event. In this work Genetic Algorithms (GAs) with an adaptive penalty scheme have been proposed as a tool for the determination of the maximum likelihood point. The utilization of only numerical values in the GAs operation makes the algorithms applicable to cases of non-linear and implicit single and multiple limit state function(s). The algorithmic simplicity readily extends its application to higher dimensional problems. When combined with Monte Carlo Simulation, the proposed methodology will reduce the computational complexity and at the same time will enhance the possibility in rare-event analysis under limited computational resources. Since, there is no approximation done in the procedure, the solution obtained is considered accurate. Consequently, GAs can be used as a tool for increasing the computational efficiency in the element and system reliability analyses
Approximate maximum parsimony and ancestral maximum likelihood.

Science.gov (United States)

Alon, Noga; Chor, Benny; Pardi, Fabio; Rapoport, Anat

2010-01-01

We explore the maximum parsimony (MP) and ancestral maximum likelihood (AML) criteria in phylogenetic tree reconstruction. Both problems are NP-hard, so we seek approximate solutions. We formulate the two problems as Steiner tree problems under appropriate distances. The gist of our approach is the succinct characterization of Steiner trees for a small number of leaves for the two distances. This enables the use of known Steiner tree approximation algorithms. The approach leads to a 16/9 approximation ratio for AML and asymptotically to a 1.55 approximation ratio for MP.

Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood

Science.gov (United States)

Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models
Decomposition of conditional probability for high-order symbolic Markov chains

Science.gov (United States)

Melnik, S. S.; Usatenko, O. V.

2017-07-01

The main goal of this paper is to develop an estimate for the conditional probability function of random stationary ergodic symbolic sequences with elements belonging to a finite alphabet. We elaborate on a decomposition procedure for the conditional probability function of sequences considered to be high-order Markov chains. We represent the conditional probability function as the sum of multilinear memory function monomials of different orders (from zero up to the chain order). This allows us to introduce a family of Markov chain models and to construct artificial sequences via a method of successive iterations, taking into account at each step increasingly high correlations among random elements. At weak correlations, the memory functions are uniquely expressed in terms of the high-order symbolic correlation functions. The proposed method fills the gap between two approaches, namely the likelihood estimation and the additive Markov chains. The obtained results may have applications for sequential approximation of artificial neural network training.
Application of Markov chain model to daily maximum temperature for thermal comfort in Malaysia

International Nuclear Information System (INIS)

Nordin, Muhamad Asyraf bin Che; Hassan, Husna

2015-01-01

The Markov chain’s first order principle has been widely used to model various meteorological fields, for prediction purposes. In this study, a 14-year (2000-2013) data of daily maximum temperatures in Bayan Lepas were used. Earlier studies showed that the outdoor thermal comfort range based on physiologically equivalent temperature (PET) index in Malaysia is less than 34°C, thus the data obtained were classified into two state: normal state (within thermal comfort range) and hot state (above thermal comfort range). The long-run results show the probability of daily temperature exceed TCR will be only 2.2%. On the other hand, the probability daily temperature within TCR will be 97.8%
On minimizing the maximum broadcast decoding delay for instantly decodable network coding

KAUST Repository

Douik, Ahmed S.

2014-09-01

In this paper, we consider the problem of minimizing the maximum broadcast decoding delay experienced by all the receivers of generalized instantly decodable network coding (IDNC). Unlike the sum decoding delay, the maximum decoding delay as a definition of delay for IDNC allows a more equitable distribution of the delays between the different receivers and thus a better Quality of Service (QoS). In order to solve this problem, we first derive the expressions for the probability distributions of maximum decoding delay increments. Given these expressions, we formulate the problem as a maximum weight clique problem in the IDNC graph. Although this problem is known to be NP-hard, we design a greedy algorithm to perform effective packet selection. Through extensive simulations, we compare the sum decoding delay and the max decoding delay experienced when applying the policies to minimize the sum decoding delay and our policy to reduce the max decoding delay. Simulations results show that our policy gives a good agreement among all the delay aspects in all situations and outperforms the sum decoding delay policy to effectively minimize the sum decoding delay when the channel conditions become harsher. They also show that our definition of delay significantly improve the number of served receivers when they are subject to strict delay constraints.
Social-philosophical practices of success

Directory of Open Access Journals (Sweden)

S. R. Karpenko

2017-01-01

Is social-philosophical experts of success represent the complicated system of various world outlook, speech, mental factors and events in life of the various professional, age and subcultural bunches producing assessments under different visual angles, from positions of various social installations and identity in what the social philosophy of success expresses. In the course of forming social an expert (both in daily, and in an institutional discourse are shaped also theoretical ideas success: instrumental, is social-philosophical, is social-psychological, world outlook, historical and cultural, etc., characterising thereby various systems of a social discourse. Examination is social-philosophical the success expert shows the real complexity and ambiguity of the given appearance. Besides the presented typology constructed as the most approximate abstract plan, in each separate case probably build-up of typological models according to a principle ad hoc. It looks quite justified, considering that circumstance that representations about success and the successful person are constantly transformed and acquire new performances. Efficiency of the further examinations of a discourse and a success expert will depend on accepting of new heuristic approaches, capable to consider multidimensionality and ambiguity of the given phenomenon.
Global Trends in Alzheimer Disease Clinical Development: Increasing the Probability of Success.

Science.gov (United States)

Sugino, Haruhiko; Watanabe, Akihito; Amada, Naoki; Yamamoto, Miho; Ohgi, Yuta; Kostic, Dusan; Sanchez, Raymond

2015-08-01

Alzheimer disease (AD) is a growing global health and economic issue as elderly populations increase dramatically across the world. Despite the many clinical trials conducted, currently no approved disease-modifying treatment exists. In this commentary, the present status of AD drug development and the grounds for collaborations between government, academia, and industry to accelerate the development of disease-modifying AD therapies are discussed. Official government documents, literature, and news releases were surveyed by MEDLINE and website research. Currently approved anti-AD drugs provide only short-lived symptomatic improvements, which have no effect on the underlying pathogenic mechanisms or progression of the disease. The failure to approve a disease-modifying drug for AD may be because the progression of AD in the patient populations enrolled in clinical studies was too advanced for drugs to demonstrate cognitive and functional improvements. The US Food and Drug Administration and the European Medicines Agency recently published draft guidance for industry which discusses approaches for conducting clinical studies with patients in early AD stages. For successful clinical trials in early-stage AD, however, it will be necessary to identify biomarkers highly correlated with the clinical onset and the longitudinal progress of AD. In addition, because of the high cost and length of clinical AD studies, support in the form of global initiatives and collaborations between government, industry, and academia is needed. In response to this situation, national guidance and international collaborations have been established. Global initiatives are focusing on 2025 as a goal to provide new treatment options, and early signs of success in biomarker and drug development are already emerging. Copyright © 2015 Elsevier HS Journals, Inc. All rights reserved.
Janus-faced probability

CERN Document Server

Rocchi, Paolo

2014-01-01

The problem of probability interpretation was long overlooked before exploding in the 20th century, when the frequentist and subjectivist schools formalized two conflicting conceptions of probability. Beyond the radical followers of the two schools, a circle of pluralist thinkers tends to reconcile the opposing concepts. The author uses two theorems in order to prove that the various interpretations of probability do not come into opposition and can be used in different contexts. The goal here is to clarify the multifold nature of probability by means of a purely mathematical approach and to show how philosophical arguments can only serve to deepen actual intellectual contrasts. The book can be considered as one of the most important contributions in the analysis of probability interpretation in the last 10-15 years.
Estimating the probability of rare events: addressing zero failure data.

Science.gov (United States)

Quigley, John; Revie, Matthew

2011-07-01

Traditional statistical procedures for estimating the probability of an event result in an estimate of zero when no events are realized. Alternative inferential procedures have been proposed for the situation where zero events have been realized but often these are ad hoc, relying on selecting methods dependent on the data that have been realized. Such data-dependent inference decisions violate fundamental statistical principles, resulting in estimation procedures whose benefits are difficult to assess. In this article, we propose estimating the probability of an event occurring through minimax inference on the probability that future samples of equal size realize no more events than that in the data on which the inference is based. Although motivated by inference on rare events, the method is not restricted to zero event data and closely approximates the maximum likelihood estimate (MLE) for nonzero data. The use of the minimax procedure provides a risk adverse inferential procedure where there are no events realized. A comparison is made with the MLE and regions of the underlying probability are identified where this approach is superior. Moreover, a comparison is made with three standard approaches to supporting inference where no event data are realized, which we argue are unduly pessimistic. We show that for situations of zero events the estimator can be simply approximated with 1/2.5n, where n is the number of trials. © 2011 Society for Risk Analysis.
Ruin probabilities

DEFF Research Database (Denmark)

Asmussen, Søren; Albrecher, Hansjörg

The book gives a comprehensive treatment of the classical and modern ruin probability theory. Some of the topics are Lundberg's inequality, the Cramér-Lundberg approximation, exact solutions, other approximations (e.g., for heavy-tailed claim size distributions), finite horizon ruin probabilities......, extensions of the classical compound Poisson model to allow for reserve-dependent premiums, Markov-modulation, periodicity, change of measure techniques, phase-type distributions as a computational vehicle and the connection to other applied probability areas, like queueing theory. In this substantially...... updated and extended second version, new topics include stochastic control, fluctuation theory for Levy processes, Gerber–Shiu functions and dependence....
A new maximum likelihood blood velocity estimator incorporating spatial and temporal correlation

DEFF Research Database (Denmark)

Schlaikjer, Malene; Jensen, Jørgen Arendt

2001-01-01

and space. This paper presents a new estimator (STC-MLE), which incorporates the correlation property. It is an expansion of the maximum likelihood estimator (MLE) developed by Ferrara et al. With the MLE a cross-correlation analysis between consecutive RF-lines on complex form is carried out for a range...... of possible velocities. In the new estimator an additional similarity investigation for each evaluated velocity and the available velocity estimates in a temporal (between frames) and spatial (within frames) neighborhood is performed. An a priori probability density term in the distribution...... of the observations gives a probability measure of the correlation between the velocities. Both the MLE and the STC-MLE have been evaluated on simulated and in-vivo RF-data obtained from the carotid artery. Using the MLE 4.1% of the estimates deviate significantly from the true velocities, when the performance...
Examination Of Gifted Students’ Probability Problem Solving Process In Terms Of Mathematical Thinking

Directory of Open Access Journals (Sweden)

Serdal BALTACI

2016-10-01

Full Text Available It is a widely known fact that gifted students have different skills compared to their peers. However, to what extent gifted students use mathematical thinking skills during probability problem solving process emerges as a significant question. Thence, the main aim of the present study is to examine 8th grade gifted students’ probability problem-solving process related to daily life in terms of mathematical thinking skills. In this regard, a case study was used in the study. The participants of the study were six students at 8th grade (four girls and two boys from the Science and Art Center. One of the purposeful sampling methods, maximum variation sampling was used for selecting the participants. Clinical interview and problems were used as a data collection tool. As a results of the study, it was determined that gifted students use reasoning and strategies skill, which is one of the mathematical thinking skills, mostly on the process of probability problem solving, and communication skills at least.
Anomalous maximum and minimum for the dissociation of a geminate pair in energetically disordered media

Science.gov (United States)

Govatski, J. A.; da Luz, M. G. E.; Koehler, M.

2015-01-01

We study the geminated pair dissociation probability φ as function of applied electric field and temperature in energetically disordered nD media. Regardless nD, for certain parameters regions φ versus the disorder degree (σ) displays anomalous minimum (maximum) at low (moderate) fields. This behavior is compatible with a transport energy which reaches a maximum and then decreases to negative values as σ increases. Our results explain the temperature dependence of the persistent photoconductivity in C60 single crystals going through order-disorder transitions. They also indicate how an energetic disorder spatial variation may contribute to higher exciton dissociation in multicomponent donor/acceptor systems.
Dynamics of non-stationary processes that follow the maximum of the Rényi entropy principle.

Science.gov (United States)

Shalymov, Dmitry S; Fradkov, Alexander L

2016-01-01

We propose dynamics equations which describe the behaviour of non-stationary processes that follow the maximum Rényi entropy principle. The equations are derived on the basis of the speed-gradient principle originated in the control theory. The maximum of the Rényi entropy principle is analysed for discrete and continuous cases, and both a discrete random variable and probability density function (PDF) are used. We consider mass conservation and energy conservation constraints and demonstrate the uniqueness of the limit distribution and asymptotic convergence of the PDF for both cases. The coincidence of the limit distribution of the proposed equations with the Rényi distribution is examined.
A maximum pseudo-likelihood approach for estimating species trees under the coalescent model

Directory of Open Access Journals (Sweden)

Edwards Scott V

2010-10-01

Full Text Available Abstract Background Several phylogenetic approaches have been developed to estimate species trees from collections of gene trees. However, maximum likelihood approaches for estimating species trees under the coalescent model are limited. Although the likelihood of a species tree under the multispecies coalescent model has already been derived by Rannala and Yang, it can be shown that the maximum likelihood estimate (MLE of the species tree (topology, branch lengths, and population sizes from gene trees under this formula does not exist. In this paper, we develop a pseudo-likelihood function of the species tree to obtain maximum pseudo-likelihood estimates (MPE of species trees, with branch lengths of the species tree in coalescent units. Results We show that the MPE of the species tree is statistically consistent as the number M of genes goes to infinity. In addition, the probability that the MPE of the species tree matches the true species tree converges to 1 at rate O(M -1. The simulation results confirm that the maximum pseudo-likelihood approach is statistically consistent even when the species tree is in the anomaly zone. We applied our method, Maximum Pseudo-likelihood for Estimating Species Trees (MP-EST to a mammal dataset. The four major clades found in the MP-EST tree are consistent with those in the Bayesian concatenation tree. The bootstrap supports for the species tree estimated by the MP-EST method are more reasonable than the posterior probability supports given by the Bayesian concatenation method in reflecting the level of uncertainty in gene trees and controversies over the relationship of four major groups of placental mammals. Conclusions MP-EST can consistently estimate the topology and branch lengths (in coalescent units of the species tree. Although the pseudo-likelihood is derived from coalescent theory, and assumes no gene flow or horizontal gene transfer (HGT, the MP-EST method is robust to a small amount of HGT in the
Interpretations of probability

CERN Document Server

Khrennikov, Andrei

2009-01-01

This is the first fundamental book devoted to non-Kolmogorov probability models. It provides a mathematical theory of negative probabilities, with numerous applications to quantum physics, information theory, complexity, biology and psychology. The book also presents an interesting model of cognitive information reality with flows of information probabilities, describing the process of thinking, social, and psychological phenomena.
Subspace Learning via Local Probability Distribution for Hyperspectral Image Classification

Directory of Open Access Journals (Sweden)

Huiwu Luo

2015-01-01

Full Text Available The computational procedure of hyperspectral image (HSI is extremely complex, not only due to the high dimensional information, but also due to the highly correlated data structure. The need of effective processing and analyzing of HSI has met many difficulties. It has been evidenced that dimensionality reduction has been found to be a powerful tool for high dimensional data analysis. Local Fisher’s liner discriminant analysis (LFDA is an effective method to treat HSI processing. In this paper, a novel approach, called PD-LFDA, is proposed to overcome the weakness of LFDA. PD-LFDA emphasizes the probability distribution (PD in LFDA, where the maximum distance is replaced with local variance for the construction of weight matrix and the class prior probability is applied to compute the affinity matrix. The proposed approach increases the discriminant ability of the transformed features in low dimensional space. Experimental results on Indian Pines 1992 data indicate that the proposed approach significantly outperforms the traditional alternatives.
Estimation of submarine mass failure probability from a sequence of deposits with age dates

Science.gov (United States)

Geist, Eric L.; Chaytor, Jason D.; Parsons, Thomas E.; ten Brink, Uri S.

2013-01-01

The empirical probability of submarine mass failure is quantified from a sequence of dated mass-transport deposits. Several different techniques are described to estimate the parameters for a suite of candidate probability models. The techniques, previously developed for analyzing paleoseismic data, include maximum likelihood and Type II (Bayesian) maximum likelihood methods derived from renewal process theory and Monte Carlo methods. The estimated mean return time from these methods, unlike estimates from a simple arithmetic mean of the center age dates and standard likelihood methods, includes the effects of age-dating uncertainty and of open time intervals before the first and after the last event. The likelihood techniques are evaluated using Akaike’s Information Criterion (AIC) and Akaike’s Bayesian Information Criterion (ABIC) to select the optimal model. The techniques are applied to mass transport deposits recorded in two Integrated Ocean Drilling Program (IODP) drill sites located in the Ursa Basin, northern Gulf of Mexico. Dates of the deposits were constrained by regional bio- and magnetostratigraphy from a previous study. Results of the analysis indicate that submarine mass failures in this location occur primarily according to a Poisson process in which failures are independent and return times follow an exponential distribution. However, some of the model results suggest that submarine mass failures may occur quasiperiodically at one of the sites (U1324). The suite of techniques described in this study provides quantitative probability estimates of submarine mass failure occurrence, for any number of deposits and age uncertainty distributions.
Variation of Time Domain Failure Probabilities of Jack-up with Wave Return Periods

Science.gov (United States)

Idris, Ahmad; Harahap, Indra S. H.; Ali, Montassir Osman Ahmed

2018-04-01

This study evaluated failure probabilities of jack up units on the framework of time dependent reliability analysis using uncertainty from different sea states representing different return period of the design wave. Surface elevation for each sea state was represented by Karhunen-Loeve expansion method using the eigenfunctions of prolate spheroidal wave functions in order to obtain the wave load. The stochastic wave load was propagated on a simplified jack up model developed in commercial software to obtain the structural response due to the wave loading. Analysis of the stochastic response to determine the failure probability in excessive deck displacement in the framework of time dependent reliability analysis was performed by developing Matlab codes in a personal computer. Results from the study indicated that the failure probability increases with increase in the severity of the sea state representing a longer return period. Although the results obtained are in agreement with the results of a study of similar jack up model using time independent method at higher values of maximum allowable deck displacement, it is in contrast at lower values of the criteria where the study reported that failure probability decreases with increase in the severity of the sea state.
Combining Marginal Probability Distributions via Minimization of Weighted Sum of Kullback-Leibler Divergences

Czech Academy of Sciences Publication Activity Database

Kracík, Jan

2011-01-01

Roč. 52, č. 6 (2011), s. 659-671 ISSN 0888-613X R&D Projects: GA ČR GA102/08/0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : combining probabilities * Kullback-Leibler divergence * maximum likelihood * expert opinions * linear opinion pool Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.948, year: 2011 http://library.utia.cas.cz/separaty/2011/AS/kracik-0359399. pdf
Application of at-site peak-streamflow frequency analyses for very low annual exceedance probabilities

Science.gov (United States)

Asquith, William H.; Kiang, Julie E.; Cohn, Timothy A.

2017-07-17

The U.S. Geological Survey (USGS), in cooperation with the U.S. Nuclear Regulatory Commission, has investigated statistical methods for probabilistic flood hazard assessment to provide guidance on very low annual exceedance probability (AEP) estimation of peak-streamflow frequency and the quantification of corresponding uncertainties using streamgage-specific data. The term “very low AEP” implies exceptionally rare events defined as those having AEPs less than about 0.001 (or 1 × 10–3 in scientific notation or for brevity 10–3). Such low AEPs are of great interest to those involved with peak-streamflow frequency analyses for critical infrastructure, such as nuclear power plants. Flood frequency analyses at streamgages are most commonly based on annual instantaneous peak streamflow data and a probability distribution fit to these data. The fitted distribution provides a means to extrapolate to very low AEPs. Within the United States, the Pearson type III probability distribution, when fit to the base-10 logarithms of streamflow, is widely used, but other distribution choices exist. The USGS-PeakFQ software, implementing the Pearson type III within the Federal agency guidelines of Bulletin 17B (method of moments) and updates to the expected moments algorithm (EMA), was specially adapted for an “Extended Output” user option to provide estimates at selected AEPs from 10–3 to 10–6. Parameter estimation methods, in addition to product moments and EMA, include L-moments, maximum likelihood, and maximum product of spacings (maximum spacing estimation). This study comprehensively investigates multiple distributions and parameter estimation methods for two USGS streamgages (01400500 Raritan River at Manville, New Jersey, and 01638500 Potomac River at Point of Rocks, Maryland). The results of this study specifically involve the four methods for parameter estimation and up to nine probability distributions, including the generalized extreme value, generalized

Novel Maximum-based Timing Acquisition for Spread-Spectrum Communications

Energy Technology Data Exchange (ETDEWEB)

Sibbetty, Taylor; Moradiz, Hussein; Farhang-Boroujeny, Behrouz

2016-12-01

This paper proposes and analyzes a new packet detection and timing acquisition method for spread spectrum systems. The proposed method provides an enhancement over the typical thresholding techniques that have been proposed for direct sequence spread spectrum (DS-SS). The effective implementation of thresholding methods typically require accurate knowledge of the received signal-to-noise ratio (SNR), which is particularly difficult to estimate in spread spectrum systems. Instead, we propose a method which utilizes a consistency metric of the location of maximum samples at the output of a filter matched to the spread spectrum waveform to achieve acquisition, and does not require knowledge of the received SNR. Through theoretical study, we show that the proposed method offers a low probability of missed detection over a large range of SNR with a corresponding probability of false alarm far lower than other methods. Computer simulations that corroborate our theoretical results are also presented. Although our work here has been motivated by our previous study of a filter bank multicarrier spread-spectrum (FB-MC-SS) system, the proposed method is applicable to DS-SS systems as well.
Improving Ranking Using Quantum Probability

OpenAIRE

Melucci, Massimo

2011-01-01

The paper shows that ranking information units by quantum probability differs from ranking them by classical probability provided the same data used for parameter estimation. As probability of detection (also known as recall or power) and probability of false alarm (also known as fallout or size) measure the quality of ranking, we point out and show that ranking by quantum probability yields higher probability of detection than ranking by classical probability provided a given probability of ...
Investigating the probability of detection of typical cavity shapes through modelling and comparison of geophysical techniques

Science.gov (United States)

James, P.

2011-12-01

assessed. The density of survey points required to achieve a required probability of detection can be calculated. The software aids discriminate choice of technique, improves survey design, and increases the likelihood of survey success; all factors sought in the engineering industry. As a simple example, the response from magnetometry, gravimetry, and gravity gradient techniques above an example 3m deep, 1m cube air cavity in limestone across a 15m grid was calculated. The maximum responses above the cavity are small (amplitudes of 0.018nT, 0.0013mGal, 8.3eotvos respectively), but at typical site noise levels the detection reliability is over 50% for the gradient gravity method on a single survey line. Increasing the number of survey points across the site increases the reliability of detection of the anomaly by the addition of probabilities. We can calculate the probability of detection at different profile spacings to assess the best possible survey design. At 1m spacing the overall probability of by the gradient gravity method is over 90%, and over 60% for magnetometry (at 3m spacing the probability drops to 32%). The use of modelling in near surface surveys is a useful tool to assess the feasibility of a range of techniques to detect subtle signals. Future work will integrate this work with borehole measured parameters.
Using multinomial and imprecise probability for non-parametric modelling of rainfall in Manizales (Colombia

Directory of Open Access Journals (Sweden)

Ibsen Chivatá Cárdenas

2008-05-01

Full Text Available This article presents a rainfall model constructed by applying non-parametric modelling and imprecise probabilities; these tools were used because there was not enough homogeneous information in the study area. The area’s hydro-logical information regarding rainfall was scarce and existing hydrological time series were not uniform. A distributed extended rainfall model was constructed from so-called probability boxes (p-boxes, multinomial probability distribu-tion and confidence intervals (a friendly algorithm was constructed for non-parametric modelling by combining the last two tools. This model confirmed the high level of uncertainty involved in local rainfall modelling. Uncertainty en-compassed the whole range (domain of probability values thereby showing the severe limitations on information, leading to the conclusion that a detailed estimation of probability would lead to significant error. Nevertheless, rele-vant information was extracted; it was estimated that maximum daily rainfall threshold (70 mm would be surpassed at least once every three years and the magnitude of uncertainty affecting hydrological parameter estimation. This paper’s conclusions may be of interest to non-parametric modellers and decisions-makers as such modelling and imprecise probability represents an alternative for hydrological variable assessment and maybe an obligatory proce-dure in the future. Its potential lies in treating scarce information and represents a robust modelling strategy for non-seasonal stochastic modelling conditions
Stimulus-dependent maximum entropy models of neural population codes.

Directory of Open Access Journals (Sweden)

Einat Granot-Atedgi

Full Text Available Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. For large populations, direct sampling of these distributions is impossible, and so we must rely on constructing appropriate models. We show here that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. We introduce the stimulus-dependent maximum entropy (SDME model-a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. We find that the SDME model gives a more accurate account of single cell responses and in particular significantly outperforms uncoupled models in reproducing the distributions of population codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like average surprise and information transmission in a neural population.
Calculating the Probability of Returning a Loan with Binary Probability Models

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Julian Vasilev

2014-12-01

Full Text Available The purpose of this article is to give a new approach in calculating the probability of returning a loan. A lot of factors affect the value of the probability. In this article by using statistical and econometric models some influencing factors are proved. The main approach is concerned with applying probit and logit models in loan management institutions. A new aspect of the credit risk analysis is given. Calculating the probability of returning a loan is a difficult task. We assume that specific data fields concerning the contract (month of signing, year of signing, given sum and data fields concerning the borrower of the loan (month of birth, year of birth (age, gender, region, where he/she lives may be independent variables in a binary logistics model with a dependent variable “the probability of returning a loan”. It is proved that the month of signing a contract, the year of signing a contract, the gender and the age of the loan owner do not affect the probability of returning a loan. It is proved that the probability of returning a loan depends on the sum of contract, the remoteness of the loan owner and the month of birth. The probability of returning a loan increases with the increase of the given sum, decreases with the proximity of the customer, increases for people born in the beginning of the year and decreases for people born at the end of the year.
Rank-Ordered Multifractal Analysis (ROMA of probability distributions in fluid turbulence

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C. C. Wu

2011-04-01

Full Text Available Rank-Ordered Multifractal Analysis (ROMA was introduced by Chang and Wu (2008 to describe the multifractal characteristic of intermittent events. The procedure provides a natural connection between the rank-ordered spectrum and the idea of one-parameter scaling for monofractals. This technique has successfully been applied to MHD turbulence simulations and turbulence data observed in various space plasmas. In this paper, the technique is applied to the probability distributions in the inertial range of the turbulent fluid flow, as given in the vast Johns Hopkins University (JHU turbulence database. In addition, a new way of finding the continuous ROMA spectrum and the scaled probability distribution function (PDF simultaneously is introduced.
On the Possibility of Assigning Probabilities to Singular Cases, or: Probability Is Subjective Too!

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Mark R. Crovelli

2009-06-01

Full Text Available Both Ludwig von Mises and Richard von Mises claimed that numerical probability could not be legitimately applied to singular cases. This paper challenges this aspect of the von Mises brothers’ theory of probability. It is argued that their denial that numerical probability could be applied to singular cases was based solely upon Richard von Mises’ exceptionally restrictive definition of probability. This paper challenges Richard von Mises’ definition of probability by arguing that the definition of probability necessarily depends upon whether the world is governed by time-invariant causal laws. It is argued that if the world is governed by time-invariant causal laws, a subjective definition of probability must be adopted. It is further argued that both the nature of human action and the relative frequency method for calculating numerical probabilities both presuppose that the world is indeed governed by time-invariant causal laws. It is finally argued that the subjective definition of probability undercuts the von Mises claim that numerical probability cannot legitimately be applied to singular, non-replicable cases.
Fast maximum likelihood estimation of mutation rates using a birth-death process.

Science.gov (United States)

Wu, Xiaowei; Zhu, Hongxiao

2015-02-07

Since fluctuation analysis was first introduced by Luria and Delbrück in 1943, it has been widely used to make inference about spontaneous mutation rates in cultured cells. Under certain model assumptions, the probability distribution of the number of mutants that appear in a fluctuation experiment can be derived explicitly, which provides the basis of mutation rate estimation. It has been shown that, among various existing estimators, the maximum likelihood estimator usually demonstrates some desirable properties such as consistency and lower mean squared error. However, its application in real experimental data is often hindered by slow computation of likelihood due to the recursive form of the mutant-count distribution. We propose a fast maximum likelihood estimator of mutation rates, MLE-BD, based on a birth-death process model with non-differential growth assumption. Simulation studies demonstrate that, compared with the conventional maximum likelihood estimator derived from the Luria-Delbrück distribution, MLE-BD achieves substantial improvement on computational speed and is applicable to arbitrarily large number of mutants. In addition, it still retains good accuracy on point estimation. Published by Elsevier Ltd.
Efficient Outage Probability Evaluation of Diversity Receivers Over Generalized Gamma Channels

KAUST Repository

Ben Issaid, Chaouki

2016-10-01

In this paper, we are interested in determining the cumulative distribution function of the sum of generalized Gamma in the setting of rare event simulations. To this end, we present an efficient importance sampling estimator. The main result of this work is the bounded relative property of the proposed estimator. This result is used to accurately estimate the outage probability of multibranch maximum ratio combining and equal gain combining diversity receivers over generalized Gamma fading channels. Selected numerical simulations are discussed to show the robustness of our estimator compared to naive Monte Carlo.
Efficient Outage Probability Evaluation of Diversity Receivers Over Generalized Gamma Channels

KAUST Repository

Ben Issaid, Chaouki; Alouini, Mohamed-Slim; Tempone, Raul

2016-01-01

In this paper, we are interested in determining the cumulative distribution function of the sum of generalized Gamma in the setting of rare event simulations. To this end, we present an efficient importance sampling estimator. The main result of this work is the bounded relative property of the proposed estimator. This result is used to accurately estimate the outage probability of multibranch maximum ratio combining and equal gain combining diversity receivers over generalized Gamma fading channels. Selected numerical simulations are discussed to show the robustness of our estimator compared to naive Monte Carlo.
Towards the prediction of pre-mining stresses in the European continent. [Estimates of vertical and probable maximum lateral stress in Europe

Energy Technology Data Exchange (ETDEWEB)

Blackwood, R. L.

1980-05-15

There are now available sufficient data from in-situ, pre-mining stress measurements to allow a first attempt at predicting the maximum stress magnitudes likely to occur in a given mining context. The sub-horizontal (lateral) stress generally dominates the stress field, becoming critical to stope stability in many cases. For cut-and-fill mining in particular, where developed fill pressures are influenced by lateral displacement of pillars or stope backs, extraction maximization planning by mathematical modelling techniques demands the best available estimate of pre-mining stresses. While field measurements are still essential for this purpose, in the present paper it is suggested that the worst stress case can be predicted for preliminary design or feasibility study purposes. In the Eurpoean continent the vertical component of pre-mining stress may be estimated by adding 2 MPa to the pressure due to overburden weight. The maximum lateral stress likely to be encountered is about 57 MPa at depths of some 800m to 1000m below the surface.
Maximum permissible dose

International Nuclear Information System (INIS)

Anon.

1979-01-01

This chapter presents a historic overview of the establishment of radiation guidelines by various national and international agencies. The use of maximum permissible dose and maximum permissible body burden limits to derive working standards is discussed
Effect of Urban Green Spaces and Flooded Area Type on Flooding Probability

Directory of Open Access Journals (Sweden)

Hyomin Kim

2016-01-01

Full Text Available Countermeasures to urban flooding should consider long-term perspectives, because climate change impacts are unpredictable and complex. Urban green spaces have emerged as a potential option to reduce urban flood risks, and their effectiveness has been highlighted in notable urban water management studies. In this study, flooded areas in Seoul, Korea, were divided into four flooded area types by cluster analysis based on topographic and physical characteristics and verified using discriminant analysis. After division by flooded area type, logistic regression analysis was performed to determine how the flooding probability changes with variations in green space area. Type 1 included regions where flooding occurred in a drainage basin that had a flood risk management infrastructure (FRMI. In Type 2, the slope was steep; the TWI (Topographic Wetness Index was relatively low; and soil drainage was favorable. Type 3 represented the gentlest sloping areas, and these were associated with the highest TWI values. In addition, these areas had the worst soil drainage. Type 4 had moderate slopes, imperfect soil drainage and lower than average TWI values. We found that green spaces exerted a considerable influence on urban flooding probabilities in Seoul, and flooding probabilities could be reduced by over 50% depending on the green space area and the locations where green spaces were introduced. Increasing the area of green spaces was the most effective method of decreasing flooding probability in Type 3 areas. In Type 2 areas, the maximum hourly precipitation affected the flooding probability significantly, and the flooding probability in these areas was high despite the extensive green space area. These findings can contribute towards establishing guidelines for urban spatial planning to respond to urban flooding.
Probability of Interference-Optimal and Energy-Efficient Analysis for Topology Control in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Ning Li

2016-11-01

Full Text Available Because wireless sensor networks (WSNs have been widely used in recent years, how to reduce their energy consumption and interference has become a major issue. Topology control is a common and effective approach to improve network performance, such as reducing the energy consumption and network interference, improving the network connectivity, etc. Many topology control algorithms reduce network interference by dynamically adjusting the node transmission range. However, reducing the network interference by adjusting the transmission range is probabilistic. Therefore, in this paper, we analyze the probability of interference-optimality for the WSNs and prove that the probability of interference-optimality increases with the increasing of the original transmission range. Under a specific transmission range, the probability reaches the maximum value when the transmission range is 0.85r in homogeneous networks and 0.84r in heterogeneous networks. In addition, we also prove that when the network is energy-efficient, the network is also interference-optimal with probability 1 both in the homogeneous and heterogeneous networks.
Mid-depth temperature maximum in an estuarine lake

Science.gov (United States)

Stepanenko, V. M.; Repina, I. A.; Artamonov, A. Yu; Gorin, S. L.; Lykossov, V. N.; Kulyamin, D. V.

2018-03-01

The mid-depth temperature maximum (TeM) was measured in an estuarine Bol’shoi Vilyui Lake (Kamchatka peninsula, Russia) in summer 2015. We applied 1D k-ɛ model LAKE to the case, and found it successfully simulating the phenomenon. We argue that the main prerequisite for mid-depth TeM development is a salinity increase below the freshwater mixed layer, sharp enough in order to increase the temperature with depth not to cause convective mixing and double diffusion there. Given that this condition is satisfied, the TeM magnitude is controlled by physical factors which we identified as: radiation absorption below the mixed layer, mixed-layer temperature dynamics, vertical heat conduction and water-sediments heat exchange. In addition to these, we formulate the mechanism of temperature maximum ‘pumping’, resulting from the phase shift between diurnal cycles of mixed-layer depth and temperature maximum magnitude. Based on the LAKE model results we quantify the contribution of the above listed mechanisms and find their individual significance highly sensitive to water turbidity. Relying on physical mechanisms identified we define environmental conditions favouring the summertime TeM development in salinity-stratified lakes as: small-mixed layer depth (roughly, ~wind and cloudless weather. We exemplify the effect of mixed-layer depth on TeM by a set of selected lakes.
Connections rigidity effect on probability of fracture in steel moment frames

Directory of Open Access Journals (Sweden)

Gholamreza Abdollahzadeh

2017-08-01

Full Text Available Connections in steel moment frames are idealized in full pinned and full rigid conditions. Because with this assumption, in spite of real behavior of connection, real story drifts are less anticipated and maybe frame is designed without performance of bracing. There are several methods for modeling actual behavior of semi rigid connections. In this method a connection with certain rigidity is modeled by a rotational spring with corresponding stiffness. This stiffness is achieved by certain formula. In other words, each percent of rigidity corresponds to one rotational spring stiffness. In this research in order to evaluate the real behavior of connection in analysis and designing process and fracture probability one frame including four stories and one bay with three types of connection has been modeled and designed in ETABS. Each model has an individual rigidity which is equal to 10, 75 and 90 percent. With respect to maximum drift and different PGA in roof, probabilities of low, medium, high and complete fracture were calculated. For this purpose, with applying different PGA to modeled frames, amounts of drift in the roof are achieved. Then these values are compared with given values in American code. Finally, investigation showed that when rigidity in frame connections increases, the probability of frame fracture decreases. In other words, fully rigid assumption of connection in analysis process leads to decreasing in real probability of fracture in frames which is a noticeable risk in building designing processes.
Population pharmacokinetics and maximum a posteriori probability Bayesian estimator of abacavir: application of individualized therapy in HIV-infected infants and toddlers.

NARCIS (Netherlands)

Zhao, W.; Cella, M.; Pasqua, O. Della; Burger, D.M.; Jacqz-Aigrain, E.

2012-01-01

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: Abacavir is used to treat HIV infection in both adults and children. The recommended paediatric dose is 8 mg kg(-1) twice daily up to a maximum of 300 mg twice daily. Weight was identified as the central covariate influencing pharmacokinetics of abacavir in
Maximum entropy production: Can it be used to constrain conceptual hydrological models?

Science.gov (United States)

M.C. Westhoff; E. Zehe

2013-01-01

In recent years, optimality principles have been proposed to constrain hydrological models. The principle of maximum entropy production (MEP) is one of the proposed principles and is subject of this study. It states that a steady state system is organized in such a way that entropy production is maximized. Although successful applications have been reported in...
Absolute transition probabilities in the NeI 3p-3s fine structure by beam-gas-dye laser spectroscopy

International Nuclear Information System (INIS)

Hartmetz, P.; Schmoranzer, H.

1983-01-01

The beam-gas-dye laser two-step excitation technique is further developed and applied to the direct measurement of absolute atomic transition probabilities in the NeI 3p-3s fine-structure transition array with a maximum experimental error of 5%. (orig.)

Improvement of maximum power point tracking perturb and observe algorithm for a standalone solar photovoltaic system

International Nuclear Information System (INIS)

Awan, M.M.A.; Awan, F.G.

2017-01-01

Extraction of maximum power from PV (Photovoltaic) cell is necessary to make the PV system efficient. Maximum power can be achieved by operating the system at MPP (Maximum Power Point) (taking the operating point of PV panel to MPP) and for this purpose MPPT (Maximum Power Point Trackers) are used. There are many tracking algorithms/methods used by these trackers which includes incremental conductance, constant voltage method, constant current method, short circuit current method, PAO (Perturb and Observe) method, and open circuit voltage method but PAO is the mostly used algorithm because it is simple and easy to implement. PAO algorithm has some drawbacks, one is low tracking speed under rapid changing weather conditions and second is oscillations of PV systems operating point around MPP. Little improvement is achieved in past papers regarding these issues. In this paper, a new method named 'Decrease and Fix' method is successfully introduced as improvement in PAO algorithm to overcome these issues of tracking speed and oscillations. Decrease and fix method is the first successful attempt with PAO algorithm for stability achievement and speeding up of tracking process in photovoltaic system. Complete standalone photovoltaic system's model with improved perturb and observe algorithm is simulated in MATLAB Simulink. (author)
Philosophical theories of probability

CERN Document Server

Gillies, Donald

2000-01-01

The Twentieth Century has seen a dramatic rise in the use of probability and statistics in almost all fields of research. This has stimulated many new philosophical ideas on probability. Philosophical Theories of Probability is the first book to present a clear, comprehensive and systematic account of these various theories and to explain how they relate to one another. Gillies also offers a distinctive version of the propensity theory of probability, and the intersubjective interpretation, which develops the subjective theory.
Assessing the Adequacy of Probability Distributions for Estimating the Extreme Events of Air Temperature in Dabaa Region

International Nuclear Information System (INIS)

El-Shanshoury, Gh.I.

2015-01-01

Assessing the adequacy of probability distributions for estimating the extreme events of air temperature in Dabaa region is one of the pre-requisite s for any design purpose at Dabaa site which can be achieved by probability approach. In the present study, three extreme value distributions are considered and compared to estimate the extreme events of monthly and annual maximum and minimum temperature. These distributions include the Gumbel/Frechet distributions for estimating the extreme maximum values and Gumbel /Weibull distributions for estimating the extreme minimum values. Lieblein technique and Method of Moments are applied for estimating the distribution para meters. Subsequently, the required design values with a given return period of exceedance are obtained. Goodness-of-Fit tests involving Kolmogorov-Smirnov and Anderson-Darling are used for checking the adequacy of fitting the method/distribution for the estimation of maximum/minimum temperature. Mean Absolute Relative Deviation, Root Mean Square Error and Relative Mean Square Deviation are calculated, as the performance indicators, to judge which distribution and method of parameters estimation are the most appropriate one to estimate the extreme temperatures. The present study indicated that the Weibull distribution combined with Method of Moment estimators gives the highest fit, most reliable, accurate predictions for estimating the extreme monthly and annual minimum temperature. The Gumbel distribution combined with Method of Moment estimators showed the highest fit, accurate predictions for the estimation of the extreme monthly and annual maximum temperature except for July, August, October and November. The study shows that the combination of Frechet distribution with Method of Moment is the most accurate for estimating the extreme maximum temperature in July, August and November months while t he Gumbel distribution and Lieblein technique is the best for October
Use of the maximum entropy method in X-ray astronomy

International Nuclear Information System (INIS)

Willingale, R.

1981-01-01

An algorithm used to apply the maximum entropy method in X-ray astronomy is described. It is easy to programme on a digital computer and fast enough to allow processing of two-dimensional images. The method gives good noise suppression without loss of instrumental resolution and has been successfully applied to several data analysis problems in X-ray astronomy. The restoration of a high-resolution image from the Einstein Observatory demonstrates the use of the algorithm. (author)
Optimal Portfolio Strategy under Rolling Economic Maximum Drawdown Constraints

Directory of Open Access Journals (Sweden)

Xiaojian Yu

2014-01-01

Full Text Available This paper deals with the problem of optimal portfolio strategy under the constraints of rolling economic maximum drawdown. A more practical strategy is developed by using rolling Sharpe ratio in computing the allocation proportion in contrast to existing models. Besides, another novel strategy named “REDP strategy” is further proposed, which replaces the rolling economic drawdown of the portfolio with the rolling economic drawdown of the risky asset. The simulation tests prove that REDP strategy can ensure the portfolio to satisfy the drawdown constraint and outperforms other strategies significantly. An empirical comparison research on the performances of different strategies is carried out by using the 23-year monthly data of SPTR, DJUBS, and 3-month T-bill. The investment cases of single risky asset and two risky assets are both studied in this paper. Empirical results indicate that the REDP strategy successfully controls the maximum drawdown within the given limit and performs best in both return and risk.
An empirical probability model of detecting species at low densities.

Science.gov (United States)

Delaney, David G; Leung, Brian

2010-06-01

False negatives, not detecting things that are actually present, are an important but understudied problem. False negatives are the result of our inability to perfectly detect species, especially those at low density such as endangered species or newly arriving introduced species. They reduce our ability to interpret presence-absence survey data and make sound management decisions (e.g., rapid response). To reduce the probability of false negatives, we need to compare the efficacy and sensitivity of different sampling approaches and quantify an unbiased estimate of the probability of detection. We conducted field experiments in the intertidal zone of New England and New York to test the sensitivity of two sampling approaches (quadrat vs. total area search, TAS), given different target characteristics (mobile vs. sessile). Using logistic regression we built detection curves for each sampling approach that related the sampling intensity and the density of targets to the probability of detection. The TAS approach reduced the probability of false negatives and detected targets faster than the quadrat approach. Mobility of targets increased the time to detection but did not affect detection success. Finally, we interpreted two years of presence-absence data on the distribution of the Asian shore crab (Hemigrapsus sanguineus) in New England and New York, using our probability model for false negatives. The type of experimental approach in this paper can help to reduce false negatives and increase our ability to detect species at low densities by refining sampling approaches, which can guide conservation strategies and management decisions in various areas of ecology such as conservation biology and invasion ecology.
Probabilistic Inference: Task Dependency and Individual Differences of Probability Weighting Revealed by Hierarchical Bayesian Modeling.

Science.gov (United States)

Boos, Moritz; Seer, Caroline; Lange, Florian; Kopp, Bruno

2016-01-01

Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modeling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design. Five computational models of cognitive processes were compared with the observed behavior. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted) S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model's success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modeling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modeling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.
Probabilistic inference: Task dependency and individual differences of probability weighting revealed by hierarchical Bayesian modelling

Directory of Open Access Journals (Sweden)

Moritz eBoos

2016-05-01

Full Text Available Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modelling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities by two (likelihoods design. Five computational models of cognitive processes were compared with the observed behaviour. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model’s success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modelling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modelling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.
Probability for statisticians

CERN Document Server

Shorack, Galen R

2017-01-01

This 2nd edition textbook offers a rigorous introduction to measure theoretic probability with particular attention to topics of interest to mathematical statisticians—a textbook for courses in probability for students in mathematical statistics. It is recommended to anyone interested in the probability underlying modern statistics, providing a solid grounding in the probabilistic tools and techniques necessary to do theoretical research in statistics. For the teaching of probability theory to post graduate statistics students, this is one of the most attractive books available. Of particular interest is a presentation of the major central limit theorems via Stein's method either prior to or alternative to a characteristic function presentation. Additionally, there is considerable emphasis placed on the quantile function as well as the distribution function. The bootstrap and trimming are both presented. Martingale coverage includes coverage of censored data martingales. The text includes measure theoretic...
Evolution of the Nova Vulpeculae no.1 1968 (LV Vul) spectrum after the maximum brightness

International Nuclear Information System (INIS)

Andrijya, I.; Antipova, L.I.; Babaev, M.B.; AN Azerbajdzhanskoj SSR, Baku. Shemakhinskaya Astrofizicheskaya Observatoriya)

1986-01-01

The analysis of the spectral evolution of LV Vulpeculae 1968 after the maximum brightness was carried out. It is shown that the pre-maximum spectrum was replaced by the principal one in less than 24sup(h). The diffuse enhanced scectrum and the Orion one existed already when the Nova brightness has decreased only by 0.4sup(m) and 0.5sup(m) respectively. The radial velocities of the Orion spectrum coincided with those of the diffuse enhanced one during the total observational period. The Orion spectrum consists of the lines of He I, N2, O 2 and may be H 1. The appearance of two additional components is probably due to splitting of the principal and diffuse enhanced spectrum
What is the probability of successive cases of Legionnaires' disease occurring in European hotels?

Science.gov (United States)

Ricketts, K D; Slaymaker, E; Verlander, N Q; Joseph, C A

2006-04-01

Public health officials will normally take action at accommodation sites following an association with a cluster of cases of Legionnaires' disease. This paper seeks to determine the likelihood of such a cluster occurring at a site once it has been associated with a single case of the disease, and therefore whether more should be done at sites following individual cases. Information for UK residents reported to the EWGLINET system between 1993 and 2000 was included in a dataset. The size and country of hotel visited by the cases were divided into six country groups (France, Italy, Spain, Turkey, other Europe and other World), and eight size groups (30%; the probability of a subsequent case occurring within 2 years of the first reached over 50% in some instances. There may be support for early intervention at some accommodation sites following a first case of Legionnaires' disease, in specific country and size groups.
Incidents in nuclear research reactor examined by deterministic probability and probabilistic safety analysis; Incidentes em reatores nucleares de pesquisa examinados por analise de probabilidade deterministica e analise probabilistica de seguranca

Energy Technology Data Exchange (ETDEWEB)

Lopes, Valdir Maciel

2010-07-01

This study aims to evaluate the potential risks submitted by the incidents in nuclear research reactors. For its development, two databases of the International Atomic Energy Agency, IAEA, were used, the Incident Report System for Research Reactor and Research Reactor Data Base. For this type of assessment was used the Probabilistic Safety Analysis (PSA), within a confidence level of 90% and the Deterministic Probability Analysis (DPA). To obtain the results of calculations of probabilities for PSA, were used the theory and equations in the paper IAEA TECDOC - 636. The development of the calculations of probabilities for PSA was used the program Scilab version 5.1.1, free access, executable on Windows and Linux platforms. A specific program to get the results of probability was developed within the main program Scilab 5.1.1., for two distributions Fischer and Chi-square, both with the confidence level of 90%. Using the Sordi equations and Origin 6.0 program, were obtained the maximum admissible doses related to satisfy the risk limits established by the International Commission on Radiological Protection, ICRP, and were also obtained these maximum doses graphically (figure 1) resulting from the calculations of probabilities x maximum admissible doses. It was found that the reliability of the results of probability is related to the operational experience (reactor x year and fractions) and that the larger it is, greater the confidence in the outcome. Finally, a suggested list of future work to complement this paper was gathered. (author)
A brief introduction to probability.

Science.gov (United States)

Di Paola, Gioacchino; Bertani, Alessandro; De Monte, Lavinia; Tuzzolino, Fabio

2018-02-01

The theory of probability has been debated for centuries: back in 1600, French mathematics used the rules of probability to place and win bets. Subsequently, the knowledge of probability has significantly evolved and is now an essential tool for statistics. In this paper, the basic theoretical principles of probability will be reviewed, with the aim of facilitating the comprehension of statistical inference. After a brief general introduction on probability, we will review the concept of the "probability distribution" that is a function providing the probabilities of occurrence of different possible outcomes of a categorical or continuous variable. Specific attention will be focused on normal distribution that is the most relevant distribution applied to statistical analysis.
Choice probability generating functions

DEFF Research Database (Denmark)

Fosgerau, Mogens; McFadden, Daniel; Bierlaire, Michel

2013-01-01

This paper considers discrete choice, with choice probabilities coming from maximization of preferences from a random utility field perturbed by additive location shifters (ARUM). Any ARUM can be characterized by a choice-probability generating function (CPGF) whose gradient gives the choice...... probabilities, and every CPGF is consistent with an ARUM. We relate CPGF to multivariate extreme value distributions, and review and extend methods for constructing CPGF for applications. The choice probabilities of any ARUM may be approximated by a cross-nested logit model. The results for ARUM are extended...
Probability of satellite collision

Science.gov (United States)

Mccarter, J. W.

1972-01-01

A method is presented for computing the probability of a collision between a particular artificial earth satellite and any one of the total population of earth satellites. The collision hazard incurred by the proposed modular Space Station is assessed using the technique presented. The results of a parametric study to determine what type of satellite orbits produce the greatest contribution to the total collision probability are presented. Collision probability for the Space Station is given as a function of Space Station altitude and inclination. Collision probability was also parameterized over miss distance and mission duration.
Real analysis and probability

CERN Document Server

Ash, Robert B; Lukacs, E

1972-01-01

Real Analysis and Probability provides the background in real analysis needed for the study of probability. Topics covered range from measure and integration theory to functional analysis and basic concepts of probability. The interplay between measure theory and topology is also discussed, along with conditional probability and expectation, the central limit theorem, and strong laws of large numbers with respect to martingale theory.Comprised of eight chapters, this volume begins with an overview of the basic concepts of the theory of measure and integration, followed by a presentation of var
Probability and Measure

CERN Document Server

Billingsley, Patrick

2012-01-01

Praise for the Third Edition "It is, as far as I'm concerned, among the best books in math ever written....if you are a mathematician and want to have the top reference in probability, this is it." (Amazon.com, January 2006) A complete and comprehensive classic in probability and measure theory Probability and Measure, Anniversary Edition by Patrick Billingsley celebrates the achievements and advancements that have made this book a classic in its field for the past 35 years. Now re-issued in a new style and format, but with the reliable content that the third edition was revered for, this
Experimental Probability in Elementary School

Science.gov (United States)

Andrew, Lane

2009-01-01

Concepts in probability can be more readily understood if students are first exposed to probability via experiment. Performing probability experiments encourages students to develop understandings of probability grounded in real events, as opposed to merely computing answers based on formulae.
Aggregate and Individual Replication Probability within an Explicit Model of the Research Process

Science.gov (United States)

Miller, Jeff; Schwarz, Wolf

2011-01-01

We study a model of the research process in which the true effect size, the replication jitter due to changes in experimental procedure, and the statistical error of effect size measurement are all normally distributed random variables. Within this model, we analyze the probability of successfully replicating an initial experimental result by…
Probabilities in physics

CERN Document Server

Hartmann, Stephan

2011-01-01

Many results of modern physics--those of quantum mechanics, for instance--come in a probabilistic guise. But what do probabilistic statements in physics mean? Are probabilities matters of objective fact and part of the furniture of the world, as objectivists think? Or do they only express ignorance or belief, as Bayesians suggest? And how are probabilistic hypotheses justified and supported by empirical evidence? Finally, what does the probabilistic nature of physics imply for our understanding of the world? This volume is the first to provide a philosophical appraisal of probabilities in all of physics. Its main aim is to make sense of probabilistic statements as they occur in the various physical theories and models and to provide a plausible epistemology and metaphysics of probabilities. The essays collected here consider statistical physics, probabilistic modelling, and quantum mechanics, and critically assess the merits and disadvantages of objectivist and subjectivist views of probabilities in these fie...

Probability an introduction

CERN Document Server

Grimmett, Geoffrey

2014-01-01

Probability is an area of mathematics of tremendous contemporary importance across all aspects of human endeavour. This book is a compact account of the basic features of probability and random processes at the level of first and second year mathematics undergraduates and Masters' students in cognate fields. It is suitable for a first course in probability, plus a follow-up course in random processes including Markov chains. A special feature is the authors' attention to rigorous mathematics: not everything is rigorous, but the need for rigour is explained at difficult junctures. The text is enriched by simple exercises, together with problems (with very brief hints) many of which are taken from final examinations at Cambridge and Oxford. The first eight chapters form a course in basic probability, being an account of events, random variables, and distributions - discrete and continuous random variables are treated separately - together with simple versions of the law of large numbers and the central limit th...
Evaluation of nuclear power plant component failure probability and core damage probability using simplified PSA model

International Nuclear Information System (INIS)

Shimada, Yoshio

2000-01-01

It is anticipated that the change of frequency of surveillance tests, preventive maintenance or parts replacement of safety related components may cause the change of component failure probability and result in the change of core damage probability. It is also anticipated that the change is different depending on the initiating event frequency or the component types. This study assessed the change of core damage probability using simplified PSA model capable of calculating core damage probability in a short time period, which is developed by the US NRC to process accident sequence precursors, when various component's failure probability is changed between 0 and 1, or Japanese or American initiating event frequency data are used. As a result of the analysis, (1) It was clarified that frequency of surveillance test, preventive maintenance or parts replacement of motor driven pumps (high pressure injection pumps, residual heat removal pumps, auxiliary feedwater pumps) should be carefully changed, since the core damage probability's change is large, when the base failure probability changes toward increasing direction. (2) Core damage probability change is insensitive to surveillance test frequency change, since the core damage probability change is small, when motor operated valves and turbine driven auxiliary feed water pump failure probability changes around one figure. (3) Core damage probability change is small, when Japanese failure probability data are applied to emergency diesel generator, even if failure probability changes one figure from the base value. On the other hand, when American failure probability data is applied, core damage probability increase is large, even if failure probability changes toward increasing direction. Therefore, when Japanese failure probability data is applied, core damage probability change is insensitive to surveillance tests frequency change etc. (author)
Conditional maximum-entropy method for selecting prior distributions in Bayesian statistics

Science.gov (United States)

Abe, Sumiyoshi

2014-11-01

The conditional maximum-entropy method (abbreviated here as C-MaxEnt) is formulated for selecting prior probability distributions in Bayesian statistics for parameter estimation. This method is inspired by a statistical-mechanical approach to systems governed by dynamics with largely separated time scales and is based on three key concepts: conjugate pairs of variables, dimensionless integration measures with coarse-graining factors and partial maximization of the joint entropy. The method enables one to calculate a prior purely from a likelihood in a simple way. It is shown, in particular, how it not only yields Jeffreys's rules but also reveals new structures hidden behind them.
Determination of Measurement Points in Urban Environments for Assessment of Maximum Exposure to EMF Associated with a Base Station

Directory of Open Access Journals (Sweden)

Agostinho Linhares

2014-01-01

Full Text Available A base station (BS antenna operates in accordance with the established exposure limits if the values of electromagnetic fields (EMF measured in points of maximum exposure are below these limits. In the case of BS in open areas, the maximum exposure to EMF probably occurs in the antenna’s boresight direction, from a few tens to a few hundred meters away. This is not a typical scenery for urban environments. However, in the line of sight (LOS situation, the region of maximum exposure can still be analytically estimated with good results. This paper presents a methodology for the choice of measurement points in urban areas in order to assess compliance with the limits for exposure to EMF.
Introduction to probability

CERN Document Server

Freund, John E

1993-01-01

Thorough, lucid coverage of permutations and factorials, probabilities and odds, frequency interpretation, mathematical expectation, decision making, postulates of probability, rule of elimination, binomial distribution, geometric distribution, standard deviation, law of large numbers, and much more. Exercises with some solutions. Summary. Bibliography. Includes 42 black-and-white illustrations. 1973 edition.
Probably not future prediction using probability and statistical inference

CERN Document Server

Dworsky, Lawrence N

2008-01-01

An engaging, entertaining, and informative introduction to probability and prediction in our everyday lives Although Probably Not deals with probability and statistics, it is not heavily mathematical and is not filled with complex derivations, proofs, and theoretical problem sets. This book unveils the world of statistics through questions such as what is known based upon the information at hand and what can be expected to happen. While learning essential concepts including "the confidence factor" and "random walks," readers will be entertained and intrigued as they move from chapter to chapter. Moreover, the author provides a foundation of basic principles to guide decision making in almost all facets of life including playing games, developing winning business strategies, and managing personal finances. Much of the book is organized around easy-to-follow examples that address common, everyday issues such as: How travel time is affected by congestion, driving speed, and traffic lights Why different gambling ...
Time at which the maximum of a random acceleration process is reached

International Nuclear Information System (INIS)

Majumdar, Satya N; Rosso, Alberto; Zoia, Andrea

2010-01-01

We study the random acceleration model, which is perhaps one of the simplest, yet nontrivial, non-Markov stochastic processes, and is key to many applications. For this non-Markov process, we present exact analytical results for the probability density p(t m |T) of the time t m at which the process reaches its maximum, within a fixed time interval [0, T]. We study two different boundary conditions, which correspond to the process representing respectively (i) the integral of a Brownian bridge and (ii) the integral of a free Brownian motion. Our analytical results are also verified by numerical simulations.
Emission lines in the hydrogen-deficient variable MV Sagittarii near maximum light

International Nuclear Information System (INIS)

Herbig, G.H.

1975-01-01

The H-deficient R CrB type variable MV Sgr near maximum light shows a rich emission spectrum in the 5800--8600 A region. Most of these lines are due to Fe ii, but Si ii, N i, O i, and Hα also are present. Such a spectrum has not been observed in any other R CrB star, but there is some resemblance to v Sgr. The emission lines in MV Sgr probably originate in an extended region of low temperature, which may also be responsible for the infrared excess observed by Feast and Glass
Risk Probabilities

DEFF Research Database (Denmark)

Rojas-Nandayapa, Leonardo

Tail probabilities of sums of heavy-tailed random variables are of a major importance in various branches of Applied Probability, such as Risk Theory, Queueing Theory, Financial Management, and are subject to intense research nowadays. To understand their relevance one just needs to think...... analytic expression for the distribution function of a sum of random variables. The presence of heavy-tailed random variables complicates the problem even more. The objective of this dissertation is to provide better approximations by means of sharp asymptotic expressions and Monte Carlo estimators...
A subjective supply–demand model: the maximum Boltzmann/Shannon entropy solution

International Nuclear Information System (INIS)

Piotrowski, Edward W; Sładkowski, Jan

2009-01-01

The present authors have put forward a projective geometry model of rational trading. The expected (mean) value of the time that is necessary to strike a deal and the profit strongly depend on the strategies adopted. A frequent trader often prefers maximal profit intensity to the maximization of profit resulting from a separate transaction because the gross profit/income is the adopted/recommended benchmark. To investigate activities that have different periods of duration we define, following the queuing theory, the profit intensity as a measure of this economic category. The profit intensity in repeated trading has a unique property of attaining its maximum at a fixed point regardless of the shape of demand curves for a wide class of probability distributions of random reverse transactions (i.e. closing of the position). These conclusions remain valid for an analogous model based on supply analysis. This type of market game is often considered in research aiming at finding an algorithm that maximizes profit of a trader who negotiates prices with the Rest of the World (a collective opponent), possessing a definite and objective supply profile. Such idealization neglects the sometimes important influence of an individual trader on the demand/supply profile of the Rest of the World and in extreme cases questions the very idea of demand/supply profile. Therefore we put forward a trading model in which the demand/supply profile of the Rest of the World induces the (rational) trader to (subjectively) presume that he/she lacks (almost) all knowledge concerning the market but his/her average frequency of trade. This point of view introduces maximum entropy principles into the model and broadens the range of economic phenomena that can be perceived as a sort of thermodynamical system. As a consequence, the profit intensity has a fixed point with an astonishing connection with Fibonacci classical works and looking for the quickest algorithm for obtaining the extremum of a
A subjective supply-demand model: the maximum Boltzmann/Shannon entropy solution

Science.gov (United States)

Piotrowski, Edward W.; Sładkowski, Jan

2009-03-01

The present authors have put forward a projective geometry model of rational trading. The expected (mean) value of the time that is necessary to strike a deal and the profit strongly depend on the strategies adopted. A frequent trader often prefers maximal profit intensity to the maximization of profit resulting from a separate transaction because the gross profit/income is the adopted/recommended benchmark. To investigate activities that have different periods of duration we define, following the queuing theory, the profit intensity as a measure of this economic category. The profit intensity in repeated trading has a unique property of attaining its maximum at a fixed point regardless of the shape of demand curves for a wide class of probability distributions of random reverse transactions (i.e. closing of the position). These conclusions remain valid for an analogous model based on supply analysis. This type of market game is often considered in research aiming at finding an algorithm that maximizes profit of a trader who negotiates prices with the Rest of the World (a collective opponent), possessing a definite and objective supply profile. Such idealization neglects the sometimes important influence of an individual trader on the demand/supply profile of the Rest of the World and in extreme cases questions the very idea of demand/supply profile. Therefore we put forward a trading model in which the demand/supply profile of the Rest of the World induces the (rational) trader to (subjectively) presume that he/she lacks (almost) all knowledge concerning the market but his/her average frequency of trade. This point of view introduces maximum entropy principles into the model and broadens the range of economic phenomena that can be perceived as a sort of thermodynamical system. As a consequence, the profit intensity has a fixed point with an astonishing connection with Fibonacci classical works and looking for the quickest algorithm for obtaining the extremum of a
13 CFR 107.1150 - Maximum amount of Leverage for a Section 301(c) Licensee.

Science.gov (United States)

2010-01-01

... up-to-date business plan that reflects continuation of the Licensee's successful investment strategy... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Maximum amount of Leverage for a Section 301(c) Licensee. 107.1150 Section 107.1150 Business Credit and Assistance SMALL BUSINESS...
Quantum processes: probability fluxes, transition probabilities in unit time and vacuum vibrations

International Nuclear Information System (INIS)

Oleinik, V.P.; Arepjev, Ju D.

1989-01-01

Transition probabilities in unit time and probability fluxes are compared in studying the elementary quantum processes -the decay of a bound state under the action of time-varying and constant electric fields. It is shown that the difference between these quantities may be considerable, and so the use of transition probabilities W instead of probability fluxes Π, in calculating the particle fluxes, may lead to serious errors. The quantity W represents the rate of change with time of the population of the energy levels relating partly to the real states and partly to the virtual ones, and it cannot be directly measured in experiment. The vacuum background is shown to be continuously distorted when a perturbation acts on a system. Because of this the viewpoint of an observer on the physical properties of real particles continuously varies with time. This fact is not taken into consideration in the conventional theory of quantum transitions based on using the notion of probability amplitude. As a result, the probability amplitudes lose their physical meaning. All the physical information on quantum dynamics of a system is contained in the mean values of physical quantities. The existence of considerable differences between the quantities W and Π permits one in principle to make a choice of the correct theory of quantum transitions on the basis of experimental data. (author)
Domestic wells have high probability of pumping septic tank leachate

Science.gov (United States)

Bremer, J. E.; Harter, T.

2012-08-01

Onsite wastewater treatment systems are common in rural and semi-rural areas around the world; in the US, about 25-30% of households are served by a septic (onsite) wastewater treatment system, and many property owners also operate their own domestic well nearby. Site-specific conditions and local groundwater flow are often ignored when installing septic systems and wells. In areas with small lots (thus high spatial septic system densities), shallow domestic wells are prone to contamination by septic system leachate. Mass balance approaches have been used to determine a maximum septic system density that would prevent contamination of groundwater resources. In this study, a source area model based on detailed groundwater flow and transport modeling is applied for a stochastic analysis of domestic well contamination by septic leachate. Specifically, we determine the probability that a source area overlaps with a septic system drainfield as a function of aquifer properties, septic system density and drainfield size. We show that high spatial septic system density poses a high probability of pumping septic system leachate. The hydraulic conductivity of the aquifer has a strong influence on the intersection probability. We find that mass balance calculations applied on a regional scale underestimate the contamination risk of individual drinking water wells by septic systems. This is particularly relevant for contaminants released at high concentrations, for substances that experience limited attenuation, and those that are harmful even at low concentrations (e.g., pathogens).
Domestic wells have high probability of pumping septic tank leachate

Directory of Open Access Journals (Sweden)

J. E. Bremer

2012-08-01

Full Text Available Onsite wastewater treatment systems are common in rural and semi-rural areas around the world; in the US, about 25–30% of households are served by a septic (onsite wastewater treatment system, and many property owners also operate their own domestic well nearby. Site-specific conditions and local groundwater flow are often ignored when installing septic systems and wells. In areas with small lots (thus high spatial septic system densities, shallow domestic wells are prone to contamination by septic system leachate. Mass balance approaches have been used to determine a maximum septic system density that would prevent contamination of groundwater resources. In this study, a source area model based on detailed groundwater flow and transport modeling is applied for a stochastic analysis of domestic well contamination by septic leachate. Specifically, we determine the probability that a source area overlaps with a septic system drainfield as a function of aquifer properties, septic system density and drainfield size. We show that high spatial septic system density poses a high probability of pumping septic system leachate. The hydraulic conductivity of the aquifer has a strong influence on the intersection probability. We find that mass balance calculations applied on a regional scale underestimate the contamination risk of individual drinking water wells by septic systems. This is particularly relevant for contaminants released at high concentrations, for substances that experience limited attenuation, and those that are harmful even at low concentrations (e.g., pathogens.
Uncertainty, probability and information-gaps

International Nuclear Information System (INIS)

Ben-Haim, Yakov

2004-01-01

This paper discusses two main ideas. First, we focus on info-gap uncertainty, as distinct from probability. Info-gap theory is especially suited for modelling and managing uncertainty in system models: we invest all our knowledge in formulating the best possible model; this leaves the modeller with very faulty and fragmentary information about the variation of reality around that optimal model. Second, we examine the interdependence between uncertainty modelling and decision-making. Good uncertainty modelling requires contact with the end-use, namely, with the decision-making application of the uncertainty model. The most important avenue of uncertainty-propagation is from initial data- and model-uncertainties into uncertainty in the decision-domain. Two questions arise. Is the decision robust to the initial uncertainties? Is the decision prone to opportune windfall success? We apply info-gap robustness and opportunity functions to the analysis of representation and propagation of uncertainty in several of the Sandia Challenge Problems
Modelling maximum likelihood estimation of availability

International Nuclear Information System (INIS)

Waller, R.A.; Tietjen, G.L.; Rock, G.W.

1975-01-01

Suppose the performance of a nuclear powered electrical generating power plant is continuously monitored to record the sequence of failure and repairs during sustained operation. The purpose of this study is to assess one method of estimating the performance of the power plant when the measure of performance is availability. That is, we determine the probability that the plant is operational at time t. To study the availability of a power plant, we first assume statistical models for the variables, X and Y, which denote the time-to-failure and the time-to-repair variables, respectively. Once those statistical models are specified, the availability, A(t), can be expressed as a function of some or all of their parameters. Usually those parameters are unknown in practice and so A(t) is unknown. This paper discusses the maximum likelihood estimator of A(t) when the time-to-failure model for X is an exponential density with parameter, lambda, and the time-to-repair model for Y is an exponential density with parameter, theta. Under the assumption of exponential models for X and Y, it follows that the instantaneous availability at time t is A(t)=lambda/(lambda+theta)+theta/(lambda+theta)exp[-[(1/lambda)+(1/theta)]t] with t>0. Also, the steady-state availability is A(infinity)=lambda/(lambda+theta). We use the observations from n failure-repair cycles of the power plant, say X 1 , X 2 , ..., Xsub(n), Y 1 , Y 2 , ..., Ysub(n) to present the maximum likelihood estimators of A(t) and A(infinity). The exact sampling distributions for those estimators and some statistical properties are discussed before a simulation model is used to determine 95% simulation intervals for A(t). The methodology is applied to two examples which approximate the operating history of two nuclear power plants. (author)
Fuzzy probability based fault tree analysis to propagate and quantify epistemic uncertainty

International Nuclear Information System (INIS)

Purba, Julwan Hendry; Sony Tjahyani, D.T.; Ekariansyah, Andi Sofrany; Tjahjono, Hendro

2015-01-01

Highlights: • Fuzzy probability based fault tree analysis is to evaluate epistemic uncertainty in fuzzy fault tree analysis. • Fuzzy probabilities represent likelihood occurrences of all events in a fault tree. • A fuzzy multiplication rule quantifies epistemic uncertainty of minimal cut sets. • A fuzzy complement rule estimate epistemic uncertainty of the top event. • The proposed FPFTA has successfully evaluated the U.S. Combustion Engineering RPS. - Abstract: A number of fuzzy fault tree analysis approaches, which integrate fuzzy concepts into the quantitative phase of conventional fault tree analysis, have been proposed to study reliabilities of engineering systems. Those new approaches apply expert judgments to overcome the limitation of the conventional fault tree analysis when basic events do not have probability distributions. Since expert judgments might come with epistemic uncertainty, it is important to quantify the overall uncertainties of the fuzzy fault tree analysis. Monte Carlo simulation is commonly used to quantify the overall uncertainties of conventional fault tree analysis. However, since Monte Carlo simulation is based on probability distribution, this technique is not appropriate for fuzzy fault tree analysis, which is based on fuzzy probabilities. The objective of this study is to develop a fuzzy probability based fault tree analysis to overcome the limitation of fuzzy fault tree analysis. To demonstrate the applicability of the proposed approach, a case study is performed and its results are then compared to the results analyzed by a conventional fault tree analysis. The results confirm that the proposed fuzzy probability based fault tree analysis is feasible to propagate and quantify epistemic uncertainties in fault tree analysis
Probability, statistics, and associated computing techniques

International Nuclear Information System (INIS)

James, F.

1983-01-01

This chapter attempts to explore the extent to which it is possible for the experimental physicist to find optimal statistical techniques to provide a unique and unambiguous quantitative measure of the significance of raw data. Discusses statistics as the inverse of probability; normal theory of parameter estimation; normal theory (Gaussian measurements); the universality of the Gaussian distribution; real-life resolution functions; combination and propagation of uncertainties; the sum or difference of 2 variables; local theory, or the propagation of small errors; error on the ratio of 2 discrete variables; the propagation of large errors; confidence intervals; classical theory; Bayesian theory; use of the likelihood function; the second derivative of the log-likelihood function; multiparameter confidence intervals; the method of MINOS; least squares; the Gauss-Markov theorem; maximum likelihood for uniform error distribution; the Chebyshev fit; the parameter uncertainties; the efficiency of the Chebyshev estimator; error symmetrization; robustness vs. efficiency; testing of hypotheses (e.g., the Neyman-Pearson test); goodness-of-fit; distribution-free tests; comparing two one-dimensional distributions; comparing multidimensional distributions; and permutation tests for comparing two point sets
Propensity, Probability, and Quantum Theory

Science.gov (United States)

Ballentine, Leslie E.

2016-08-01

Quantum mechanics and probability theory share one peculiarity. Both have well established mathematical formalisms, yet both are subject to controversy about the meaning and interpretation of their basic concepts. Since probability plays a fundamental role in QM, the conceptual problems of one theory can affect the other. We first classify the interpretations of probability into three major classes: (a) inferential probability, (b) ensemble probability, and (c) propensity. Class (a) is the basis of inductive logic; (b) deals with the frequencies of events in repeatable experiments; (c) describes a form of causality that is weaker than determinism. An important, but neglected, paper by P. Humphreys demonstrated that propensity must differ mathematically, as well as conceptually, from probability, but he did not develop a theory of propensity. Such a theory is developed in this paper. Propensity theory shares many, but not all, of the axioms of probability theory. As a consequence, propensity supports the Law of Large Numbers from probability theory, but does not support Bayes theorem. Although there are particular problems within QM to which any of the classes of probability may be applied, it is argued that the intrinsic quantum probabilities (calculated from a state vector or density matrix) are most naturally interpreted as quantum propensities. This does not alter the familiar statistical interpretation of QM. But the interpretation of quantum states as representing knowledge is untenable. Examples show that a density matrix fails to represent knowledge.

Neuromuscular factors related to success in Olympic wrestling

Directory of Open Access Journals (Sweden)

Alfonso Martínez-Moreno

2011-03-01

Full Text Available Abstract This study was undertaken to determine the relationship between maximum dynamic and isometric strength and success in male and female Olympic wrestling. Thirty-five female and thirty-seven male wrestlers were assigned into 4 groups according to their gender and competitive level: men elite (♂ ET, n = 18 and amateur (AT ♂, n = 19 and female elite (♀ ET n = 13 and amateur (AT ♀, n = 22. All subjects underwent assessments of body composition, countermovement jump, maximum dynamic strength test in full squat and bench press exercises and maximum isometric strength test of grip and hip extension. All the neuromuscular markers studied showed significantly higher values in the two elite groups compared to their respective amateur groups results, except the jump height between ♀ET y ♀AT, where no significant differences were detected. The present results suggest that the higher maximum isometric and dynamic strength values, explained in part by the differences in lean mass, will give elite wrestlers a clear advantage during the most frequently used techniques in Olympic wrestling. Key Words: bench press; squat; maximum dynamic strength; maximum isometric strength; combat.
Neuromuscular factors related to success in Olympic wrestling

Directory of Open Access Journals (Sweden)

Alfonso Martínez-Moreno

2011-03-01

Full Text Available AbstractThis study was undertaken to determine the relationship between maximum dynamic and isometric strength and success in male and female Olympic wrestling. Thirty-five female and thirty-seven male wrestlers were assigned into 4 groups according to their gender and competitive level: men elite (♂ ET, n = 18 and amateur (AT ♂, n = 19 and female elite (♀ ET n = 13 and amateur (AT ♀, n = 22. All subjects underwent assessments of body composition, countermovement jump, maximum dynamic strength test in full squat and bench press exercises and maximum isometric strength test of grip and hip extension. All the neuromuscular markers studied showed significantly higher values in the two elite groups compared to their respective amateur groups results, except the jump height between ♀ET y ♀AT, where no significant differences were detected. The present results suggest that the higher maximum isometric and dynamic strength values, explained in part by the differences in lean mass, will give elite wrestlers a clear advantage during the most frequently used techniques in Olympic wrestling. Key Words: bench press; squat; maximum dynamic strength; maximum isometric strength; combat.
Principle of maximum entropy for reliability analysis in the design of machine components

Science.gov (United States)

Zhang, Yimin

2018-03-01

We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy (PME). We used PME to select the statistical distribution that best fits the available information. We also established a probability density function (PDF) and a failure probability model for the parameters of mechanical components using the concept of entropy and the PME. We obtained the first four moments of the state function for reliability analysis and design. Furthermore, we attained an estimate of the PDF with the fewest human bias factors using the PME. This function was used to calculate the reliability of the machine components, including a connecting rod, a vehicle half-shaft, a front axle, a rear axle housing, and a leaf spring, which have parameters that typically follow a non-normal distribution. Simulations were conducted for comparison. This study provides a design methodology for the reliability of mechanical components for practical engineering projects.
Optimal methods for fitting probability distributions to propagule retention time in studies of zoochorous dispersal.

Science.gov (United States)

Viana, Duarte S; Santamaría, Luis; Figuerola, Jordi

2016-02-01

Propagule retention time is a key factor in determining propagule dispersal distance and the shape of "seed shadows". Propagules dispersed by animal vectors are either ingested and retained in the gut until defecation or attached externally to the body until detachment. Retention time is a continuous variable, but it is commonly measured at discrete time points, according to pre-established sampling time-intervals. Although parametric continuous distributions have been widely fitted to these interval-censored data, the performance of different fitting methods has not been evaluated. To investigate the performance of five different fitting methods, we fitted parametric probability distributions to typical discretized retention-time data with known distribution using as data-points either the lower, mid or upper bounds of sampling intervals, as well as the cumulative distribution of observed values (using either maximum likelihood or non-linear least squares for parameter estimation); then compared the estimated and original distributions to assess the accuracy of each method. We also assessed the robustness of these methods to variations in the sampling procedure (sample size and length of sampling time-intervals). Fittings to the cumulative distribution performed better for all types of parametric distributions (lognormal, gamma and Weibull distributions) and were more robust to variations in sample size and sampling time-intervals. These estimated distributions had negligible deviations of up to 0.045 in cumulative probability of retention times (according to the Kolmogorov-Smirnov statistic) in relation to original distributions from which propagule retention time was simulated, supporting the overall accuracy of this fitting method. In contrast, fitting the sampling-interval bounds resulted in greater deviations that ranged from 0.058 to 0.273 in cumulative probability of retention times, which may introduce considerable biases in parameter estimates. We
Choice Probability Generating Functions

DEFF Research Database (Denmark)

Fosgerau, Mogens; McFadden, Daniel L; Bierlaire, Michel

This paper considers discrete choice, with choice probabilities coming from maximization of preferences from a random utility field perturbed by additive location shifters (ARUM). Any ARUM can be characterized by a choice-probability generating function (CPGF) whose gradient gives the choice...... probabilities, and every CPGF is consistent with an ARUM. We relate CPGF to multivariate extreme value distributions, and review and extend methods for constructing CPGF for applications....
Superthermal photon bunching in terms of simple probability distributions

Science.gov (United States)

Lettau, T.; Leymann, H. A. M.; Melcher, B.; Wiersig, J.

2018-05-01

We analyze the second-order photon autocorrelation function g(2 ) with respect to the photon probability distribution and discuss the generic features of a distribution that results in superthermal photon bunching [g(2 )(0 ) >2 ]. Superthermal photon bunching has been reported for a number of optical microcavity systems that exhibit processes such as superradiance or mode competition. We show that a superthermal photon number distribution cannot be constructed from the principle of maximum entropy if only the intensity and the second-order autocorrelation are given. However, for bimodal systems, an unbiased superthermal distribution can be constructed from second-order correlations and the intensities alone. Our findings suggest modeling superthermal single-mode distributions by a mixture of a thermal and a lasinglike state and thus reveal a generic mechanism in the photon probability distribution responsible for creating superthermal photon bunching. We relate our general considerations to a physical system, i.e., a (single-emitter) bimodal laser, and show that its statistics can be approximated and understood within our proposed model. Furthermore, the excellent agreement of the statistics of the bimodal laser and our model reveals that the bimodal laser is an ideal source of bunched photons, in the sense that it can generate statistics that contain no other features but the superthermal bunching.
Prediction and probability in sciences

International Nuclear Information System (INIS)

Klein, E.; Sacquin, Y.

1998-01-01

This book reports the 7 presentations made at the third meeting 'physics and fundamental questions' whose theme was probability and prediction. The concept of probability that was invented to apprehend random phenomena has become an important branch of mathematics and its application range spreads from radioactivity to species evolution via cosmology or the management of very weak risks. The notion of probability is the basis of quantum mechanics and then is bound to the very nature of matter. The 7 topics are: - radioactivity and probability, - statistical and quantum fluctuations, - quantum mechanics as a generalized probability theory, - probability and the irrational efficiency of mathematics, - can we foresee the future of the universe?, - chance, eventuality and necessity in biology, - how to manage weak risks? (A.C.)
Error Probability Analysis of Hardware Impaired Systems with Asymmetric Transmission

KAUST Repository

Javed, Sidrah; Amin, Osama; Ikki, Salama S.; Alouini, Mohamed-Slim

2018-01-01

Error probability study of the hardware impaired (HWI) systems highly depends on the adopted model. Recent models have proved that the aggregate noise is equivalent to improper Gaussian signals. Therefore, considering the distinct noise nature and self-interfering (SI) signals, an optimal maximum likelihood (ML) receiver is derived. This renders the conventional minimum Euclidean distance (MED) receiver as a sub-optimal receiver because it is based on the assumptions of ideal hardware transceivers and proper Gaussian noise in communication systems. Next, the average error probability performance of the proposed optimal ML receiver is analyzed and tight bounds and approximations are derived for various adopted systems including transmitter and receiver I/Q imbalanced systems with or without transmitter distortions as well as transmitter or receiver only impaired systems. Motivated by recent studies that shed the light on the benefit of improper Gaussian signaling in mitigating the HWIs, asymmetric quadrature amplitude modulation or phase shift keying is optimized and adapted for transmission. Finally, different numerical and simulation results are presented to support the superiority of the proposed ML receiver over MED receiver, the tightness of the derived bounds and effectiveness of asymmetric transmission in dampening HWIs and improving overall system performance
Error Probability Analysis of Hardware Impaired Systems with Asymmetric Transmission

KAUST Repository

Javed, Sidrah

2018-04-26

Error probability study of the hardware impaired (HWI) systems highly depends on the adopted model. Recent models have proved that the aggregate noise is equivalent to improper Gaussian signals. Therefore, considering the distinct noise nature and self-interfering (SI) signals, an optimal maximum likelihood (ML) receiver is derived. This renders the conventional minimum Euclidean distance (MED) receiver as a sub-optimal receiver because it is based on the assumptions of ideal hardware transceivers and proper Gaussian noise in communication systems. Next, the average error probability performance of the proposed optimal ML receiver is analyzed and tight bounds and approximations are derived for various adopted systems including transmitter and receiver I/Q imbalanced systems with or without transmitter distortions as well as transmitter or receiver only impaired systems. Motivated by recent studies that shed the light on the benefit of improper Gaussian signaling in mitigating the HWIs, asymmetric quadrature amplitude modulation or phase shift keying is optimized and adapted for transmission. Finally, different numerical and simulation results are presented to support the superiority of the proposed ML receiver over MED receiver, the tightness of the derived bounds and effectiveness of asymmetric transmission in dampening HWIs and improving overall system performance
Modeling of the Maximum Entropy Problem as an Optimal Control Problem and its Application to Pdf Estimation of Electricity Price

Directory of Open Access Journals (Sweden)

M. E. Haji Abadi

2013-09-01

Full Text Available In this paper, the continuous optimal control theory is used to model and solve the maximum entropy problem for a continuous random variable. The maximum entropy principle provides a method to obtain least-biased probability density function (Pdf estimation. In this paper, to find a closed form solution for the maximum entropy problem with any number of moment constraints, the entropy is considered as a functional measure and the moment constraints are considered as the state equations. Therefore, the Pdf estimation problem can be reformulated as the optimal control problem. Finally, the proposed method is applied to estimate the Pdf of the hourly electricity prices of New England and Ontario electricity markets. Obtained results show the efficiency of the proposed method.
An analysis of annual maximum streamflows in Terengganu, Malaysia using TL-moments approach

Science.gov (United States)

Ahmad, Ummi Nadiah; Shabri, Ani; Zakaria, Zahrahtul Amani

2013-02-01

TL-moments approach has been used in an analysis to determine the best-fitting distributions to represent the annual series of maximum streamflow data over 12 stations in Terengganu, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: generalized pareto (GPA), generalized logistic, and generalized extreme value distribution. The influence of TL-moments on estimated probability distribution functions are examined by evaluating the relative root mean square error and relative bias of quantile estimates through Monte Carlo simulations. The boxplot is used to show the location of the median and the dispersion of the data, which helps in reaching the decisive conclusions. For most of the cases, the results show that TL-moments with one smallest value was trimmed from the conceptual sample (TL-moments (1,0)), of GPA distribution was the most appropriate in majority of the stations for describing the annual maximum streamflow series in Terengganu, Malaysia.
The quantum probability calculus

International Nuclear Information System (INIS)

Jauch, J.M.

1976-01-01

The Wigner anomaly (1932) for the joint distribution of noncompatible observables is an indication that the classical probability calculus is not applicable for quantum probabilities. It should, therefore, be replaced by another, more general calculus, which is specifically adapted to quantal systems. In this article this calculus is exhibited and its mathematical axioms and the definitions of the basic concepts such as probability field, random variable, and expectation values are given. (B.R.H)
Analysis of Minute Features in Speckled Imagery with Maximum Likelihood Estimation

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Alejandro C. Frery

2004-12-01

Full Text Available This paper deals with numerical problems arising when performing maximum likelihood parameter estimation in speckled imagery using small samples. The noise that appears in images obtained with coherent illumination, as is the case of sonar, laser, ultrasound-B, and synthetic aperture radar, is called speckle, and it can neither be assumed Gaussian nor additive. The properties of speckle noise are well described by the multiplicative model, a statistical framework from which stem several important distributions. Amongst these distributions, one is regarded as the universal model for speckled data, namely, the Ã°ÂÂ’Â¢0 law. This paper deals with amplitude data, so the Ã°ÂÂ’Â¢A0 distribution will be used. The literature reports that techniques for obtaining estimates (maximum likelihood, based on moments and on order statistics of the parameters of the Ã°ÂÂ’Â¢A0 distribution require samples of hundreds, even thousands, of observations in order to obtain sensible values. This is verified for maximum likelihood estimation, and a proposal based on alternate optimization is made to alleviate this situation. The proposal is assessed with real and simulated data, showing that the convergence problems are no longer present. A Monte Carlo experiment is devised to estimate the quality of maximum likelihood estimators in small samples, and real data is successfully analyzed with the proposed alternated procedure. Stylized empirical influence functions are computed and used to choose a strategy for computing maximum likelihood estimates that is resistant to outliers.
Formulating informative, data-based priors for failure probability estimation in reliability analysis

International Nuclear Information System (INIS)

Guikema, Seth D.

2007-01-01

Priors play an important role in the use of Bayesian methods in risk analysis, and using all available information to formulate an informative prior can lead to more accurate posterior inferences. This paper examines the practical implications of using five different methods for formulating an informative prior for a failure probability based on past data. These methods are the method of moments, maximum likelihood (ML) estimation, maximum entropy estimation, starting from a non-informative 'pre-prior', and fitting a prior based on confidence/credible interval matching. The priors resulting from the use of these different methods are compared qualitatively, and the posteriors are compared quantitatively based on a number of different scenarios of observed data used to update the priors. The results show that the amount of information assumed in the prior makes a critical difference in the accuracy of the posterior inferences. For situations in which the data used to formulate the informative prior is an accurate reflection of the data that is later observed, the ML approach yields the minimum variance posterior. However, the maximum entropy approach is more robust to differences between the data used to formulate the prior and the observed data because it maximizes the uncertainty in the prior subject to the constraints imposed by the past data
Excluding joint probabilities from quantum theory

Science.gov (United States)

Allahverdyan, Armen E.; Danageozian, Arshag

2018-03-01

Quantum theory does not provide a unique definition for the joint probability of two noncommuting observables, which is the next important question after the Born's probability for a single observable. Instead, various definitions were suggested, e.g., via quasiprobabilities or via hidden-variable theories. After reviewing open issues of the joint probability, we relate it to quantum imprecise probabilities, which are noncontextual and are consistent with all constraints expected from a quantum probability. We study two noncommuting observables in a two-dimensional Hilbert space and show that there is no precise joint probability that applies for any quantum state and is consistent with imprecise probabilities. This contrasts with theorems by Bell and Kochen-Specker that exclude joint probabilities for more than two noncommuting observables, in Hilbert space with dimension larger than two. If measurement contexts are included into the definition, joint probabilities are not excluded anymore, but they are still constrained by imprecise probabilities.
Self-Organized Complexity and Coherent Infomax from the Viewpoint of Jaynes’s Probability Theory

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William A. Phillips

2012-01-01

Full Text Available This paper discusses concepts of self-organized complexity and the theory of Coherent Infomax in the light of Jaynes’s probability theory. Coherent Infomax, shows, in principle, how adaptively self-organized complexity can be preserved and improved by using probabilistic inference that is context-sensitive. It argues that neural systems do this by combining local reliability with flexible, holistic, context-sensitivity. Jaynes argued that the logic of probabilistic inference shows it to be based upon Bayesian and Maximum Entropy methods or special cases of them. He presented his probability theory as the logic of science; here it is considered as the logic of life. It is concluded that the theory of Coherent Infomax specifies a general objective for probabilistic inference, and that contextual interactions in neural systems perform functions required of the scientist within Jaynes’s theory.
Cosmic shear measurement with maximum likelihood and maximum a posteriori inference

Science.gov (United States)

Hall, Alex; Taylor, Andy

2017-06-01

We investigate the problem of noise bias in maximum likelihood and maximum a posteriori estimators for cosmic shear. We derive the leading and next-to-leading order biases and compute them in the context of galaxy ellipticity measurements, extending previous work on maximum likelihood inference for weak lensing. We show that a large part of the bias on these point estimators can be removed using information already contained in the likelihood when a galaxy model is specified, without the need for external calibration. We test these bias-corrected estimators on simulated galaxy images similar to those expected from planned space-based weak lensing surveys, with promising results. We find that the introduction of an intrinsic shape prior can help with mitigation of noise bias, such that the maximum a posteriori estimate can be made less biased than the maximum likelihood estimate. Second-order terms offer a check on the convergence of the estimators, but are largely subdominant. We show how biases propagate to shear estimates, demonstrating in our simple set-up that shear biases can be reduced by orders of magnitude and potentially to within the requirements of planned space-based surveys at mild signal-to-noise ratio. We find that second-order terms can exhibit significant cancellations at low signal-to-noise ratio when Gaussian noise is assumed, which has implications for inferring the performance of shear-measurement algorithms from simplified simulations. We discuss the viability of our point estimators as tools for lensing inference, arguing that they allow for the robust measurement of ellipticity and shear.
Linear positivity and virtual probability

International Nuclear Information System (INIS)

Hartle, James B.

2004-01-01

We investigate the quantum theory of closed systems based on the linear positivity decoherence condition of Goldstein and Page. The objective of any quantum theory of a closed system, most generally the universe, is the prediction of probabilities for the individual members of sets of alternative coarse-grained histories of the system. Quantum interference between members of a set of alternative histories is an obstacle to assigning probabilities that are consistent with the rules of probability theory. A quantum theory of closed systems therefore requires two elements: (1) a condition specifying which sets of histories may be assigned probabilities and (2) a rule for those probabilities. The linear positivity condition of Goldstein and Page is the weakest of the general conditions proposed so far. Its general properties relating to exact probability sum rules, time neutrality, and conservation laws are explored. Its inconsistency with the usual notion of independent subsystems in quantum mechanics is reviewed. Its relation to the stronger condition of medium decoherence necessary for classicality is discussed. The linear positivity of histories in a number of simple model systems is investigated with the aim of exhibiting linearly positive sets of histories that are not decoherent. The utility of extending the notion of probability to include values outside the range of 0-1 is described. Alternatives with such virtual probabilities cannot be measured or recorded, but can be used in the intermediate steps of calculations of real probabilities. Extended probabilities give a simple and general way of formulating quantum theory. The various decoherence conditions are compared in terms of their utility for characterizing classicality and the role they might play in further generalizations of quantum mechanics
The pleasures of probability

CERN Document Server

Isaac, Richard

1995-01-01

The ideas of probability are all around us. Lotteries, casino gambling, the al most non-stop polling which seems to mold public policy more and more these are a few of the areas where principles of probability impinge in a direct way on the lives and fortunes of the general public. At a more re moved level there is modern science which uses probability and its offshoots like statistics and the theory of random processes to build mathematical descriptions of the real world. In fact, twentieth-century physics, in embrac ing quantum mechanics, has a world view that is at its core probabilistic in nature, contrary to the deterministic one of classical physics. In addition to all this muscular evidence of the importance of probability ideas it should also be said that probability can be lots of fun. It is a subject where you can start thinking about amusing, interesting, and often difficult problems with very little mathematical background. In this book, I wanted to introduce a reader with at least a fairl...
Sharp Bounds by Probability-Generating Functions and Variable Drift

DEFF Research Database (Denmark)

Doerr, Benjamin; Fouz, Mahmoud; Witt, Carsten

2011-01-01

We introduce to the runtime analysis of evolutionary algorithms two powerful techniques: probability-generating functions and variable drift analysis. They are shown to provide a clean framework for proving sharp upper and lower bounds. As an application, we improve the results by Doerr et al....... (GECCO 2010) in several respects. First, the upper bound on the expected running time of the most successful quasirandom evolutionary algorithm for the OneMax function is improved from 1.28nln n to 0.982nlnn, which breaks the barrier of nln n posed by coupon-collector processes. Compared to the classical...

Venus atmosphere profile from a maximum entropy principle

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L. N. Epele

2007-10-01

Full Text Available The variational method with constraints recently developed by Verkley and Gerkema to describe maximum-entropy atmospheric profiles is generalized to ideal gases but with temperature-dependent specific heats. In so doing, an extended and non standard potential temperature is introduced that is well suited for tackling the problem under consideration. This new formalism is successfully applied to the atmosphere of Venus. Three well defined regions emerge in this atmosphere up to a height of 100 km from the surface: the lowest one up to about 35 km is adiabatic, a transition layer located at the height of the cloud deck and finally a third region which is practically isothermal.
Estimation of typhoon rainfall in GaoPing River: A Multivariate Maximum Entropy Method

Science.gov (United States)

Pei-Jui, Wu; Hwa-Lung, Yu

2016-04-01

The heavy rainfall from typhoons is the main factor of the natural disaster in Taiwan, which causes the significant loss of human lives and properties. Statistically average 3.5 typhoons invade Taiwan every year, and the serious typhoon, Morakot in 2009, impacted Taiwan in recorded history. Because the duration, path and intensity of typhoon, also affect the temporal and spatial rainfall type in specific region , finding the characteristics of the typhoon rainfall type is advantageous when we try to estimate the quantity of rainfall. This study developed a rainfall prediction model and can be divided three parts. First, using the EEOF(extended empirical orthogonal function) to classify the typhoon events, and decompose the standard rainfall type of all stations of each typhoon event into the EOF and PC(principal component). So we can classify the typhoon events which vary similarly in temporally and spatially as the similar typhoon types. Next, according to the classification above, we construct the PDF(probability density function) in different space and time by means of using the multivariate maximum entropy from the first to forth moment statistically. Therefore, we can get the probability of each stations of each time. Final we use the BME(Bayesian Maximum Entropy method) to construct the typhoon rainfall prediction model , and to estimate the rainfall for the case of GaoPing river which located in south of Taiwan.This study could be useful for typhoon rainfall predictions in future and suitable to government for the typhoon disaster prevention .
Psychophysics of the probability weighting function

Science.gov (United States)

Takahashi, Taiki

2011-03-01

A probability weighting function w(p) for an objective probability p in decision under risk plays a pivotal role in Kahneman-Tversky prospect theory. Although recent studies in econophysics and neuroeconomics widely utilized probability weighting functions, psychophysical foundations of the probability weighting functions have been unknown. Notably, a behavioral economist Prelec (1998) [4] axiomatically derived the probability weighting function w(p)=exp(-() (01e)=1e,w(1)=1), which has extensively been studied in behavioral neuroeconomics. The present study utilizes psychophysical theory to derive Prelec's probability weighting function from psychophysical laws of perceived waiting time in probabilistic choices. Also, the relations between the parameters in the probability weighting function and the probability discounting function in behavioral psychology are derived. Future directions in the application of the psychophysical theory of the probability weighting function in econophysics and neuroeconomics are discussed.
Maximum likelihood estimation of dose-response parameters for therapeutic operating characteristic (TOC) analysis of carcinoma of the nasopharynx

International Nuclear Information System (INIS)

Metz, C.E.; Tokars, R.P.; Kronman, H.B.; Griem, M.L.

1982-01-01

A Therapeutic Operating Characteristic (TOC) curve for radiation therapy plots, for all possible treatment doses, the probability of tumor ablation as a function of the probability of radiation-induced complication. Application of this analysis to actual therapeutic situation requires that dose-response curves for ablation and for complication be estimated from clinical data. We describe an approach in which ''maximum likelihood estimates'' of these dose-response curves are made, and we apply this approach to data collected on responses to radiotherapy for carcinoma of the nasopharynx. TOC curves constructed from the estimated dose-response curves are subject to moderately large uncertainties because of the limitations of available data.These TOC curves suggest, however, that treatment doses greater than 1800 rem may substantially increase the probability of tumor ablation with little increase in the risk of radiation-induced cervical myelopathy, especially for T1 and T2 tumors
Probability concepts in quality risk management.

Science.gov (United States)

Claycamp, H Gregg

2012-01-01

Essentially any concept of risk is built on fundamental concepts of chance, likelihood, or probability. Although risk is generally a probability of loss of something of value, given that a risk-generating event will occur or has occurred, it is ironic that the quality risk management literature and guidelines on quality risk management tools are relatively silent on the meaning and uses of "probability." The probability concept is typically applied by risk managers as a combination of frequency-based calculation and a "degree of belief" meaning of probability. Probability as a concept that is crucial for understanding and managing risk is discussed through examples from the most general, scenario-defining and ranking tools that use probability implicitly to more specific probabilistic tools in risk management. A rich history of probability in risk management applied to other fields suggests that high-quality risk management decisions benefit from the implementation of more thoughtful probability concepts in both risk modeling and risk management. Essentially any concept of risk is built on fundamental concepts of chance, likelihood, or probability. Although "risk" generally describes a probability of loss of something of value, given that a risk-generating event will occur or has occurred, it is ironic that the quality risk management literature and guidelines on quality risk management methodologies and respective tools focus on managing severity but are relatively silent on the in-depth meaning and uses of "probability." Pharmaceutical manufacturers are expanding their use of quality risk management to identify and manage risks to the patient that might occur in phases of the pharmaceutical life cycle from drug development to manufacture, marketing to product discontinuation. A probability concept is typically applied by risk managers as a combination of data-based measures of probability and a subjective "degree of belief" meaning of probability. Probability as
Maximum flood hazard assessment for OPG's deep geologic repository for low and intermediate level waste

International Nuclear Information System (INIS)

Nimmrichter, P.; McClintock, J.; Peng, J.; Leung, H.

2011-01-01

Ontario Power Generation (OPG) has entered a process to seek Environmental Assessment and licensing approvals to construct a Deep Geologic Repository (DGR) for Low and Intermediate Level Radioactive Waste (L&ILW) near the existing Western Waste Management Facility (WWMF) at the Bruce nuclear site in the Municipality of Kincardine, Ontario. In support of the design of the proposed DGR project, maximum flood stages were estimated for potential flood hazard risks associated with coastal, riverine and direct precipitation flooding. The estimation of lake/coastal flooding for the Bruce nuclear site considered potential extreme water levels in Lake Huron, storm surge and seiche, wind waves, and tsunamis. The riverine flood hazard assessment considered the Probable Maximum Flood (PMF) within the local watersheds, and within local drainage areas that will be directly impacted by the site development. A series of hydraulic models were developed, based on DGR project site grading and ditching, to assess the impact of a Probable Maximum Precipitation (PMP) occurring directly at the DGR site. Overall, this flood assessment concluded there is no potential for lake or riverine based flooding and the DGR area is not affected by tsunamis. However, it was also concluded from the results of this analysis that the PMF in proximity to the critical DGR operational areas and infrastructure would be higher than the proposed elevation of the entrance to the underground works. This paper provides an overview of the assessment of potential flood hazard risks associated with coastal, riverine and direct precipitation flooding that was completed for the DGR development. (author)
The perception of probability.

Science.gov (United States)

Gallistel, C R; Krishan, Monika; Liu, Ye; Miller, Reilly; Latham, Peter E

2014-01-01

We present a computational model to explain the results from experiments in which subjects estimate the hidden probability parameter of a stepwise nonstationary Bernoulli process outcome by outcome. The model captures the following results qualitatively and quantitatively, with only 2 free parameters: (a) Subjects do not update their estimate after each outcome; they step from one estimate to another at irregular intervals. (b) The joint distribution of step widths and heights cannot be explained on the assumption that a threshold amount of change must be exceeded in order for them to indicate a change in their perception. (c) The mapping of observed probability to the median perceived probability is the identity function over the full range of probabilities. (d) Precision (how close estimates are to the best possible estimate) is good and constant over the full range. (e) Subjects quickly detect substantial changes in the hidden probability parameter. (f) The perceived probability sometimes changes dramatically from one observation to the next. (g) Subjects sometimes have second thoughts about a previous change perception, after observing further outcomes. (h) The frequency with which they perceive changes moves in the direction of the true frequency over sessions. (Explaining this finding requires 2 additional parametric assumptions.) The model treats the perception of the current probability as a by-product of the construction of a compact encoding of the experienced sequence in terms of its change points. It illustrates the why and the how of intermittent Bayesian belief updating and retrospective revision in simple perception. It suggests a reinterpretation of findings in the recent literature on the neurobiology of decision making. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
Probabilities for profitable fungicide use against gray leaf spot in hybrid maize.

Science.gov (United States)

Munkvold, G P; Martinson, C A; Shriver, J M; Dixon, P M

2001-05-01

ABSTRACT Gray leaf spot, caused by the fungus Cercospora zeae-maydis, causes considerable yield losses in hybrid maize grown in the north-central United States and elsewhere. Nonchemical management tactics have not adequately prevented these losses. The probability of profitably using fungicide application as a management tool for gray leaf spot was evaluated in 10 field experiments under conditions of natural inoculum in Iowa. Gray leaf spot severity in untreated control plots ranged from 2.6 to 72.8% for the ear leaf and from 3.0 to 7.7 (1 to 9 scale) for whole-plot ratings. In each experiment, fungicide applications with propiconazole or mancozeb significantly reduced gray leaf spot severity. Fungicide treatment significantly (P probability of achieving a positive net return with one or two propiconazole applications, based on the mean yields and standard deviations for treated and untreated plots, the price of grain, and the costs of the fungicide applications. For one application, the probability ranged from approximately 0.06 to more than 0.99, and exceeded 0.50 in six of nine scenarios (specific experiment/hybrid). The highest probabilities occurred in the 1995 experiments with the most susceptible hybrid. Probabilities were almost always higher for a single application of propiconazole than for two applications. These results indicate that a single application of propiconazole frequently can be profitable for gray leaf spot management in Iowa, but the probability of a profitable application is strongly influenced by hybrid susceptibility. The calculation of probabilities for positive net returns was more informative than mean separation in terms of assessing the economic success of the fungicide applications.
A statistical analysis on failure-to open/close probability of pneumatic valve in sodium cooling systems

International Nuclear Information System (INIS)

Kurisaka, Kenichi

1999-11-01

The objective of this study is to develop fundamental data for examination on efficiency of preventive maintenance and surveillance test from the standpoint of failure probability. In this study, as a major standby component, a pneumatic valve in sodium cooling systems was selected. A statistical analysis was made about a trend of valve in sodium cooling systems was selected. A statistical analysis was made about a trend of valve failure-to-open/close (FTOC) probability depending on number of demands ('n'), time since installation ('t') and standby time since last open/close action ('T'). The analysis is based on the field data of operating- and failure-experiences stored in the Component Reliability Database and Statistical Analysis System for LMFBR's (CORDS). In the analysis, the FTOC probability ('P') was expressed as follows: P=1-exp{-C-En-F/n-λT-aT(t-T/2)-AT 2 /2}. The functional parameters, 'C', 'E', 'F', 'λ', 'a' and 'A', were estimated with the maximum likelihood estimation method. As a result, the FTOC probability is almost expressed with the failure probability being derived from the failure rate under assumption of the Poisson distribution only when valve cycle (i.e. open-close-open cycle) exceeds about 100 days. When the valve cycle is shorter than about 100 days, the FTOC probability can be adequately estimated with the parameter model proposed in this study. The results obtained from this study may make it possible to derive an adequate frequency of surveillance test for a given target of the FTOC probability. (author)
Maximum warming occurs about one decade after a carbon dioxide emission

International Nuclear Information System (INIS)

Ricke, Katharine L; Caldeira, Ken

2014-01-01

It is known that carbon dioxide emissions cause the Earth to warm, but no previous study has focused on examining how long it takes to reach maximum warming following a particular CO 2 emission. Using conjoined results of carbon-cycle and physical-climate model intercomparison projects (Taylor et al 2012, Joos et al 2013), we find the median time between an emission and maximum warming is 10.1 years, with a 90% probability range of 6.6–30.7 years. We evaluate uncertainties in timing and amount of warming, partitioning them into three contributing factors: carbon cycle, climate sensitivity and ocean thermal inertia. If uncertainty in any one factor is reduced to zero without reducing uncertainty in the other factors, the majority of overall uncertainty remains. Thus, narrowing uncertainty in century-scale warming depends on narrowing uncertainty in all contributing factors. Our results indicate that benefit from avoided climate damage from avoided CO 2 emissions will be manifested within the lifetimes of people who acted to avoid that emission. While such avoidance could be expected to benefit future generations, there is potential for emissions avoidance to provide substantial benefit to current generations. (letter)
Maximum warming occurs about one decade after a carbon dioxide emission

Science.gov (United States)

Ricke, Katharine L.; Caldeira, Ken

2014-12-01

It is known that carbon dioxide emissions cause the Earth to warm, but no previous study has focused on examining how long it takes to reach maximum warming following a particular CO2 emission. Using conjoined results of carbon-cycle and physical-climate model intercomparison projects (Taylor et al 2012, Joos et al 2013), we find the median time between an emission and maximum warming is 10.1 years, with a 90% probability range of 6.6-30.7 years. We evaluate uncertainties in timing and amount of warming, partitioning them into three contributing factors: carbon cycle, climate sensitivity and ocean thermal inertia. If uncertainty in any one factor is reduced to zero without reducing uncertainty in the other factors, the majority of overall uncertainty remains. Thus, narrowing uncertainty in century-scale warming depends on narrowing uncertainty in all contributing factors. Our results indicate that benefit from avoided climate damage from avoided CO2 emissions will be manifested within the lifetimes of people who acted to avoid that emission. While such avoidance could be expected to benefit future generations, there is potential for emissions avoidance to provide substantial benefit to current generations.
Birth/birth-death processes and their computable transition probabilities with biological applications.

Science.gov (United States)

Ho, Lam Si Tung; Xu, Jason; Crawford, Forrest W; Minin, Vladimir N; Suchard, Marc A

2018-03-01

Birth-death processes track the size of a univariate population, but many biological systems involve interaction between populations, necessitating models for two or more populations simultaneously. A lack of efficient methods for evaluating finite-time transition probabilities of bivariate processes, however, has restricted statistical inference in these models. Researchers rely on computationally expensive methods such as matrix exponentiation or Monte Carlo approximation, restricting likelihood-based inference to small systems, or indirect methods such as approximate Bayesian computation. In this paper, we introduce the birth/birth-death process, a tractable bivariate extension of the birth-death process, where rates are allowed to be nonlinear. We develop an efficient algorithm to calculate its transition probabilities using a continued fraction representation of their Laplace transforms. Next, we identify several exemplary models arising in molecular epidemiology, macro-parasite evolution, and infectious disease modeling that fall within this class, and demonstrate advantages of our proposed method over existing approaches to inference in these models. Notably, the ubiquitous stochastic susceptible-infectious-removed (SIR) model falls within this class, and we emphasize that computable transition probabilities newly enable direct inference of parameters in the SIR model. We also propose a very fast method for approximating the transition probabilities under the SIR model via a novel branching process simplification, and compare it to the continued fraction representation method with application to the 17th century plague in Eyam. Although the two methods produce similar maximum a posteriori estimates, the branching process approximation fails to capture the correlation structure in the joint posterior distribution.
A (simplified) Bluetooth Maximum A posteriori Probability (MAP) receiver

NARCIS (Netherlands)

Schiphorst, Roelof; Hoeksema, F.W.; Slump, Cornelis H.

2003-01-01

In our software-defined radio project we aim at combining two standards: Bluetooth and HiperLAN/2. The Hiper- LAN/2 receiver requires the most computation power in comparison with Bluetooth. We choose to use this computational power also for Bluetooth and look for more advanced demodulation
Introduction to probability with R

CERN Document Server

Baclawski, Kenneth

2008-01-01

FOREWORD PREFACE Sets, Events, and Probability The Algebra of Sets The Bernoulli Sample Space The Algebra of Multisets The Concept of Probability Properties of Probability Measures Independent Events The Bernoulli Process The R Language Finite Processes The Basic Models Counting Rules Computing Factorials The Second Rule of Counting Computing Probabilities Discrete Random Variables The Bernoulli Process: Tossing a Coin The Bernoulli Process: Random Walk Independence and Joint Distributions Expectations The Inclusion-Exclusion Principle General Random Variable
Applied probability and stochastic processes

CERN Document Server

Sumita, Ushio

1999-01-01

Applied Probability and Stochastic Processes is an edited work written in honor of Julien Keilson. This volume has attracted a host of scholars in applied probability, who have made major contributions to the field, and have written survey and state-of-the-art papers on a variety of applied probability topics, including, but not limited to: perturbation method, time reversible Markov chains, Poisson processes, Brownian techniques, Bayesian probability, optimal quality control, Markov decision processes, random matrices, queueing theory and a variety of applications of stochastic processes. The book has a mixture of theoretical, algorithmic, and application chapters providing examples of the cutting-edge work that Professor Keilson has done or influenced over the course of his highly-productive and energetic career in applied probability and stochastic processes. The book will be of interest to academic researchers, students, and industrial practitioners who seek to use the mathematics of applied probability i...
A least squares approach to estimating the probability distribution of unobserved data in multiphoton microscopy

Science.gov (United States)

Salama, Paul

2008-02-01

Multi-photon microscopy has provided biologists with unprecedented opportunities for high resolution imaging deep into tissues. Unfortunately deep tissue multi-photon microscopy images are in general noisy since they are acquired at low photon counts. To aid in the analysis and segmentation of such images it is sometimes necessary to initially enhance the acquired images. One way to enhance an image is to find the maximum a posteriori (MAP) estimate of each pixel comprising an image, which is achieved by finding a constrained least squares estimate of the unknown distribution. In arriving at the distribution it is assumed that the noise is Poisson distributed, the true but unknown pixel values assume a probability mass function over a finite set of non-negative values, and since the observed data also assumes finite values because of low photon counts, the sum of the probabilities of the observed pixel values (obtained from the histogram of the acquired pixel values) is less than one. Experimental results demonstrate that it is possible to closely estimate the unknown probability mass function with these assumptions.
Integrating spatial, temporal, and size probabilities for the annual landslide hazard maps in the Shihmen watershed, Taiwan

Directory of Open Access Journals (Sweden)

C. Y. Wu

2013-09-01

Full Text Available Landslide spatial, temporal, and size probabilities were used to perform a landslide hazard assessment in this study. Eleven intrinsic geomorphological, and two extrinsic rainfall factors were evaluated as landslide susceptibility related factors as they related to the success rate curves, landslide ratio plots, frequency distributions of landslide and non-landslide groups, as well as probability–probability plots. Data on landslides caused by Typhoon Aere in the Shihmen watershed were selected to train the susceptibility model. The landslide area probability, based on the power law relationship between the landslide area and a noncumulative number, was analyzed using the Pearson type 5 probability density function. The exceedance probabilities of rainfall with various recurrence intervals, including 2, 5, 10, 20, 50, 100 and 200 yr, were used to determine the temporal probabilities of the events. The study was conducted in the Shihmen watershed, which has an area of 760 km2 and is one of the main water sources for northern Taiwan. The validation result of Typhoon Krosa demonstrated that this landslide hazard model could be used to predict the landslide probabilities. The results suggested that integration of spatial, area, and exceedance probabilities to estimate the annual probability of each slope unit is feasible. The advantage of this annual landslide probability model lies in its ability to estimate the annual landslide risk, instead of a scenario-based risk.
CGC/saturation approach for soft interactions at high energy: survival probability of central exclusive production

Energy Technology Data Exchange (ETDEWEB)

Gotsman, E.; Maor, U. [Tel Aviv University, Department of Particle Physics, Raymond and Beverly Sackler Faculty of Exact Science, School of Physics and Astronomy, Tel Aviv (Israel); Levin, E. [Tel Aviv University, Department of Particle Physics, Raymond and Beverly Sackler Faculty of Exact Science, School of Physics and Astronomy, Tel Aviv (Israel); Universidad Tecnica Federico Santa Maria, Departemento de Fisica, Centro Cientifico-Tecnologico de Valparaiso, Valparaiso (Chile)

2016-04-15

We estimate the value of the survival probability for central exclusive production in a model which is based on the CGC/saturation approach. Hard and soft processes are described in the same framework. At LHC energies, we obtain a small value for the survival probability. The source of the small value is the impact parameter dependence of the hard amplitude. Our model has successfully described a large body of soft data: elastic, inelastic and diffractive cross sections, inclusive production and rapidity correlations, as well as the t-dependence of deep inelastic diffractive production of vector mesons. (orig.)
A microcomputer program for energy assessment and aggregation using the triangular probability distribution

Science.gov (United States)

Crovelli, R.A.; Balay, R.H.

1991-01-01

A general risk-analysis method was developed for petroleum-resource assessment and other applications. The triangular probability distribution is used as a model with an analytic aggregation methodology based on probability theory rather than Monte-Carlo simulation. Among the advantages of the analytic method are its computational speed and flexibility, and the saving of time and cost on a microcomputer. The input into the model consists of a set of components (e.g. geologic provinces) and, for each component, three potential resource estimates: minimum, most likely (mode), and maximum. Assuming a triangular probability distribution, the mean, standard deviation, and seven fractiles (F100, F95, F75, F50, F25, F5, and F0) are computed for each component, where for example, the probability of more than F95 is equal to 0.95. The components are aggregated by combining the means, standard deviations, and respective fractiles under three possible siutations (1) perfect positive correlation, (2) complete independence, and (3) any degree of dependence between these two polar situations. A package of computer programs named the TRIAGG system was written in the Turbo Pascal 4.0 language for performing the analytic probabilistic methodology. The system consists of a program for processing triangular probability distribution assessments and aggregations, and a separate aggregation routine for aggregating aggregations. The user's documentation and program diskette of the TRIAGG system are available from USGS Open File Services. TRIAGG requires an IBM-PC/XT/AT compatible microcomputer with 256kbyte of main memory, MS-DOS 3.1 or later, either two diskette drives or a fixed disk, and a 132 column printer. A graphics adapter and color display are optional. ?? 1991.
Estimate of annual daily maximum rainfall and intense rain equation for the Formiga municipality, MG, Brazil

Directory of Open Access Journals (Sweden)

Giovana Mara Rodrigues Borges

2016-11-01

Full Text Available Knowledge of the probabilistic behavior of rainfall is extremely important to the design of drainage systems, dam spillways, and other hydraulic projects. This study therefore examined statistical models to predict annual daily maximum rainfall as well as models of heavy rain for the city of Formiga - MG. To do this, annual maximum daily rainfall data were ranked in decreasing order that best describes the statistical distribution by exceedance probability. Daily rainfall disaggregation methodology was used for the intense rain model studies and adjusted with Intensity-Duration-Frequency (IDF and Exponential models. The study found that the Gumbel model better adhered to the data regarding observed frequency as indicated by the Chi-squared test, and that the exponential model best conforms to the observed data to predict intense rains.

Collision Probability Analysis

DEFF Research Database (Denmark)

Hansen, Peter Friis; Pedersen, Preben Terndrup

1998-01-01

It is the purpose of this report to apply a rational model for prediction of ship-ship collision probabilities as function of the ship and the crew characteristics and the navigational environment for MS Dextra sailing on a route between Cadiz and the Canary Islands.The most important ship and crew...... characteristics are: ship speed, ship manoeuvrability, the layout of the navigational bridge, the radar system, the number and the training of navigators, the presence of a look out etc. The main parameters affecting the navigational environment are ship traffic density, probability distributions of wind speeds...... probability, i.e. a study of the navigator's role in resolving critical situations, a causation factor is derived as a second step.The report documents the first step in a probabilistic collision damage analysis. Future work will inlcude calculation of energy released for crushing of structures giving...
Noise-level determination for discrete spectra with Gaussian or Lorentzian probability density functions

International Nuclear Information System (INIS)

Moriya, Netzer

2010-01-01

A method, based on binomial filtering, to estimate the noise level of an arbitrary, smoothed pure signal, contaminated with an additive, uncorrelated noise component is presented. If the noise characteristics of the experimental spectrum are known, as for instance the type of the corresponding probability density function (e.g., Gaussian), the noise properties can be extracted. In such cases, both the noise level, as may arbitrarily be defined, and a simulated white noise component can be generated, such that the simulated noise component is statistically indistinguishable from the true noise component present in the original signal. In this paper we present a detailed analysis of the noise level extraction when the additive noise is Gaussian or Lorentzian. We show that the statistical parameters in these cases (mainly the variance and the half width at half maximum, respectively) can directly be obtained from the experimental spectrum even when the pure signal is erratic. Further discussion is given for cases where the noise probability density function is initially unknown.
Irreversibility and conditional probability

International Nuclear Information System (INIS)

Stuart, C.I.J.M.

1989-01-01

The mathematical entropy - unlike physical entropy - is simply a measure of uniformity for probability distributions in general. So understood, conditional entropies have the same logical structure as conditional probabilities. If, as is sometimes supposed, conditional probabilities are time-reversible, then so are conditional entropies and, paradoxically, both then share this symmetry with physical equations of motion. The paradox is, of course that probabilities yield a direction to time both in statistical mechanics and quantum mechanics, while the equations of motion do not. The supposed time-reversibility of both conditionals seems also to involve a form of retrocausality that is related to, but possibly not the same as, that described by Costa de Beaurgard. The retrocausality is paradoxically at odds with the generally presumed irreversibility of the quantum mechanical measurement process. Further paradox emerges if the supposed time-reversibility of the conditionals is linked with the idea that the thermodynamic entropy is the same thing as 'missing information' since this confounds the thermodynamic and mathematical entropies. However, it is shown that irreversibility is a formal consequence of conditional entropies and, hence, of conditional probabilities also. 8 refs. (Author)
SOCIAL EXPERIENTIAL FEATURES OF CHILDREN SWIMMERS AND THEIR SUCCESS IN SPORT

Directory of Open Access Journals (Sweden)

Vojinović Jugoslav

2009-11-01

Full Text Available The aim of this research was to perceive a mutual connection of social - experien- tial features of children swimmers on one hand, and their success in sport on the other hand. According to the available methods and possibilities of their application, for this research the most relevant is empirical – unexperimental method or Survey method. An access in the obtained results shows that higher education of parents leads to less suc- cess of children in swimming. One more interesting social psychological category is a connection of parents’ pleasure and sports success. Here is also a connection negative – bigger parents’ pleasure leads more rare to sports success than less parents’ satisfac- tion (33,3 % versus 48,5 % . Probably it is being discussed about children swimmers of those parents who have more striking ambitions when the sports success of their children is concerned. Namely, their children are successful but they would like that they are mo- re successful. The reason for that attitude of those parents probably lies in the fact that all those things that they didn’t achieve in sport in their youth, they want to achieve and compensate through their children. Or vice versa, parents who are more prominently satisfied with the behaviour of their children do not have such great expectations when the success of their children in swimming is concerned. They are cheerful because their children do some sport and because they are not exposed to all those well-known temp- tations of young people today.
Introduction to probability with Mathematica

CERN Document Server

Hastings, Kevin J

2009-01-01

Discrete ProbabilityThe Cast of Characters Properties of Probability Simulation Random SamplingConditional ProbabilityIndependenceDiscrete DistributionsDiscrete Random Variables, Distributions, and ExpectationsBernoulli and Binomial Random VariablesGeometric and Negative Binomial Random Variables Poisson DistributionJoint, Marginal, and Conditional Distributions More on ExpectationContinuous ProbabilityFrom the Finite to the (Very) Infinite Continuous Random Variables and DistributionsContinuous ExpectationContinuous DistributionsThe Normal Distribution Bivariate Normal DistributionNew Random Variables from OldOrder Statistics Gamma DistributionsChi-Square, Student's t, and F-DistributionsTransformations of Normal Random VariablesAsymptotic TheoryStrong and Weak Laws of Large Numbers Central Limit TheoremStochastic Processes and ApplicationsMarkov ChainsPoisson Processes QueuesBrownian MotionFinancial MathematicsAppendixIntroduction to Mathematica Glossary of Mathematica Commands for Probability Short Answers...
Failure probability under parameter uncertainty.

Science.gov (United States)

Gerrard, R; Tsanakas, A

2011-05-01

In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location-scale families (including the log-normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications. © 2010 Society for Risk Analysis.
MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods

Science.gov (United States)

Tamura, Koichiro; Peterson, Daniel; Peterson, Nicholas; Stecher, Glen; Nei, Masatoshi; Kumar, Sudhir

2011-01-01

Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net. PMID:21546353
Maximum Acceleration Recording Circuit

Science.gov (United States)

Bozeman, Richard J., Jr.

1995-01-01

Coarsely digitized maximum levels recorded in blown fuses. Circuit feeds power to accelerometer and makes nonvolatile record of maximum level to which output of accelerometer rises during measurement interval. In comparison with inertia-type single-preset-trip-point mechanical maximum-acceleration-recording devices, circuit weighs less, occupies less space, and records accelerations within narrower bands of uncertainty. In comparison with prior electronic data-acquisition systems designed for same purpose, circuit simpler, less bulky, consumes less power, costs and analysis of data recorded in magnetic or electronic memory devices. Circuit used, for example, to record accelerations to which commodities subjected during transportation on trucks.
Characteristics of Plantar Loads in Maximum Forward Lunge Tasks in Badminton.

Science.gov (United States)

Hu, Xiaoyue; Li, Jing Xian; Hong, Youlian; Wang, Lin

2015-01-01

Badminton players often perform powerful and long-distance lunges during such competitive matches. The objective of this study is to compare the plantar loads of three one-step maximum forward lunges in badminton. Fifteen right-handed male badminton players participated in the study. Each participant performed five successful maximum lunges at three directions. For each direction, the participant wore three different shoe brands. Plantar loading, including peak pressure, maximum force, and contact area, was measured by using an insole pressure measurement system. Two-way ANOVA with repeated measures was employed to determine the effects of the different lunge directions and different shoes, as well as the interaction of these two variables, on the measurements. The maximum force (MF) on the lateral midfoot was lower when performing left-forward lunges than when performing front-forward lunges (p = 0.006, 95% CI = -2.88 to -0.04%BW). The MF and peak pressures (PP) on the great toe region were lower for the front-forward lunge than for the right-forward lunge (MF, p = 0.047, 95% CI = -3.62 to -0.02%BW; PP, p = 0.048, 95% CI = -37.63 to -0.16 KPa) and left-forward lunge (MF, p = 0.015, 95% CI = -4.39 to -0.38%BW; PP, p = 0.008, 95% CI = -47.76 to -5.91 KPa). These findings indicate that compared with the front-forward lunge, left and right maximum forward lunges induce greater plantar loads on the great toe region of the dominant leg of badminton players. The differences in the plantar loads of the different lunge directions may be potential risks for injuries to the lower extremities of badminton players.
Rock Sparrow Song Reflects Male Age and Reproductive Success

DEFF Research Database (Denmark)

Nemeth, Erwin; Kempenaers, Bart; Matessi, Giuliano

2012-01-01

The evolution of mating signals is closely linked to sexual selection. Acoustic ornaments are often used as secondary sexual traits that signal the quality of the signaller. Here we show that song performance reflects age and reproductive success in the rock sparrow (Petronia petronia...... nests. Older males could be distinguished from yearlings by singing at lower rate and higher amplitudes. Our findings suggest that song rate may be used as a signal of age and together with song pitch as a signal of reproductive success in this species. Alternatively, younger and less successful males...... success. Males with higher breeding success sang at a lower rate and with a higher maximum frequency. We found also that older males gained more extra-pair young and had a higher overall breeding success, although they also differed almost significantly by having a higher loss of paternity in their own...
Which factors affect the success or failure of eradication campaigns against alien species?

Directory of Open Access Journals (Sweden)

Therese Pluess

Full Text Available Although issues related to the management of invasive alien species are receiving increasing attention, little is known about which factors affect the likelihood of success of management measures. We applied two data mining techniques, classification trees and boosted trees, to identify factors that relate to the success of management campaigns aimed at eradicating invasive alien invertebrates, plants and plant pathogens. We assembled a dataset of 173 different eradication campaigns against 94 species worldwide, about a half of which (50.9% were successful. Eradications in man-made habitats, greenhouses in particular, were more likely to succeed than those in (semi-natural habitats. In man-made habitats the probability of success was generally high in Australasia, while in Europe and the Americas it was higher for local infestations that are easier to deal with, and for international campaigns that are likely to profit from cross-border cooperation. In (semi- natural habitats, eradication campaigns were more likely to succeed for plants introduced as an ornamental and escaped from cultivation prior to invasion. Averaging out all other factors in boosted trees, pathogens, bacteria and viruses were most, and fungi the least likely to be eradicated; for plants and invertebrates the probability was intermediate. Our analysis indicates that initiating the campaign before the extent of infestation reaches the critical threshold, starting to eradicate within the first four years since the problem has been noticed, paying special attention to species introduced by the cultivation pathway, and applying sanitary measures can substantially increase the probability of eradication success. Our investigations also revealed that information on socioeconomic factors, which are often considered to be crucial for eradication success, is rarely available, and thus their relative importance cannot be evaluated. Future campaigns should carefully document
Maximum Power from a Solar Panel

Directory of Open Access Journals (Sweden)

Michael Miller

2010-01-01

Full Text Available Solar energy has become a promising alternative to conventional fossil fuel sources. Solar panels are used to collect solar radiation and convert it into electricity. One of the techniques used to maximize the effectiveness of this energy alternative is to maximize the power output of the solar collector. In this project the maximum power is calculated by determining the voltage and the current of maximum power. These quantities are determined by finding the maximum value for the equation for power using differentiation. After the maximum values are found for each time of day, each individual quantity, voltage of maximum power, current of maximum power, and maximum power is plotted as a function of the time of day.
Conditional Probability Modulates Visual Search Efficiency

Directory of Open Access Journals (Sweden)

Bryan eCort

2013-10-01

Full Text Available We investigated the effects of probability on visual search. Previous work has shown that people can utilize spatial and sequential probability information to improve target detection. We hypothesized that performance improvements from probability information would extend to the efficiency of visual search. Our task was a simple visual search in which the target was always present among a field of distractors, and could take one of two colors. The absolute probability of the target being either color was 0.5; however, the conditional probability – the likelihood of a particular color given a particular combination of two cues – varied from 0.1 to 0.9. We found that participants searched more efficiently for high conditional probability targets and less efficiently for low conditional probability targets, but only when they were explicitly informed of the probability relationship between cues and target color.
Maruhn-Greiner Maximum of Uranium Fission for Confirmation of Low Energy Nuclear Reactions LENR via a Compound Nucleus with Double Magic Numbers

Science.gov (United States)

Hora, H.; Miley, G. H.

2007-12-01

One of the most convincing facts about LENR due to deuterons of very high concentration in host metals as palladium is the measurement of the large scale minimum of the reaction probability depending on the nucleon number A of generated elements at A = 153 where a local maximum was measured. This is similar to the fission of uranium at A = 119 where the local maximum follows from the Maruhn-Greiner theory if the splitting nuclei are excited to about MeV energy. The LENR generated elements can be documented any time after the reaction by SIMS or K-shell X-ray excitation to show the very unique distribution with the local maximum. An explanation is based on the strong Debye screening of the Maxwellian deuterons within the degenerate rigid electron background especially within the swimming electron layer at the metal surface or at interfaces. The deuterons behave like neutrals at distances of about 2 picometers. They may form clusters due to soft attraction in the range above thermal energy. Clusters of 10 pm diameter may react over long time probabilities (megaseconds) with Pd nuclei leading to a double magic number compound nucleus which splits like in fission to the A = 153 element distribution.
Factors affecting nesting success in the Great-crested Grebe ...

African Journals Online (AJOL)

The overall nesting success was 70.4% (N = 209), with nest failure caused mainly by predation (65%) and flooding (23%). Breeding outcome was significantly and positively related to nest size, with bigger nests conferring better survival to eggs and young probably through affording better protection during spells of adverse ...
Analysis of meteorological droughts and dry spells in semiarid regions: a comparative analysis of probability distribution functions in the Segura Basin (SE Spain)

Science.gov (United States)

Pérez-Sánchez, Julio; Senent-Aparicio, Javier

2017-08-01

Dry spells are an essential concept of drought climatology that clearly defines the semiarid Mediterranean environment and whose consequences are a defining feature for an ecosystem, so vulnerable with regard to water. The present study was conducted to characterize rainfall drought in the Segura River basin located in eastern Spain, marked by the self seasonal nature of these latitudes. A daily precipitation set has been utilized for 29 weather stations during a period of 20 years (1993-2013). Furthermore, four sets of dry spell length (complete series, monthly maximum, seasonal maximum, and annual maximum) are used and simulated for all the weather stations with the following probability distribution functions: Burr, Dagum, error, generalized extreme value, generalized logistic, generalized Pareto, Gumbel Max, inverse Gaussian, Johnson SB, Log-Logistic, Log-Pearson 3, Triangular, Weibull, and Wakeby. Only the series of annual maximum spell offer a good adjustment for all the weather stations, thereby gaining the role of Wakeby as the best result, with a p value means of 0.9424 for the Kolmogorov-Smirnov test (0.2 significance level). Probability of dry spell duration for return periods of 2, 5, 10, and 25 years maps reveal the northeast-southeast gradient, increasing periods with annual rainfall of less than 0.1 mm in the eastern third of the basin, in the proximity of the Mediterranean slope.
An Upper Bound on Orbital Debris Collision Probability When Only One Object has Position Uncertainty Information

Science.gov (United States)

Frisbee, Joseph H., Jr.

2015-01-01

Upper bounds on high speed satellite collision probability, P (sub c), have been investigated. Previous methods assume an individual position error covariance matrix is available for each object. The two matrices being combined into a single, relative position error covariance matrix. Components of the combined error covariance are then varied to obtain a maximum P (sub c). If error covariance information for only one of the two objects was available, either some default shape has been used or nothing could be done. An alternative is presented that uses the known covariance information along with a critical value of the missing covariance to obtain an approximate but useful P (sub c) upper bound. There are various avenues along which an upper bound on the high speed satellite collision probability has been pursued. Typically, for the collision plane representation of the high speed collision probability problem, the predicted miss position in the collision plane is assumed fixed. Then the shape (aspect ratio of ellipse), the size (scaling of standard deviations) or the orientation (rotation of ellipse principal axes) of the combined position error ellipse is varied to obtain a maximum P (sub c). Regardless as to the exact details of the approach, previously presented methods all assume that an individual position error covariance matrix is available for each object and the two are combined into a single, relative position error covariance matrix. This combined position error covariance matrix is then modified according to the chosen scheme to arrive at a maximum P (sub c). But what if error covariance information for one of the two objects is not available? When error covariance information for one of the objects is not available the analyst has commonly defaulted to the situation in which only the relative miss position and velocity are known without any corresponding state error covariance information. The various usual methods of finding a maximum P (sub c) do
A first course in probability

CERN Document Server

Ross, Sheldon

2014-01-01

A First Course in Probability, Ninth Edition, features clear and intuitive explanations of the mathematics of probability theory, outstanding problem sets, and a variety of diverse examples and applications. This book is ideal for an upper-level undergraduate or graduate level introduction to probability for math, science, engineering and business students. It assumes a background in elementary calculus.
On the prior probabilities for two-stage Bayesian estimates

International Nuclear Information System (INIS)

Kohut, P.

1992-01-01

The method of Bayesian inference is reexamined for its applicability and for the required underlying assumptions in obtaining and using prior probability estimates. Two different approaches are suggested to determine the first-stage priors in the two-stage Bayesian analysis which avoid certain assumptions required for other techniques. In the first scheme, the prior is obtained through a true frequency based distribution generated at selected intervals utilizing actual sampling of the failure rate distributions. The population variability distribution is generated as the weighed average of the frequency distributions. The second method is based on a non-parametric Bayesian approach using the Maximum Entropy Principle. Specific features such as integral properties or selected parameters of prior distributions may be obtained with minimal assumptions. It is indicated how various quantiles may also be generated with a least square technique
Estimating Subjective Probabilities

DEFF Research Database (Denmark)

Andersen, Steffen; Fountain, John; Harrison, Glenn W.

2014-01-01

either construct elicitation mechanisms that control for risk aversion, or construct elicitation mechanisms which undertake 'calibrating adjustments' to elicited reports. We illustrate how the joint estimation of risk attitudes and subjective probabilities can provide the calibration adjustments...... that theory calls for. We illustrate this approach using data from a controlled experiment with real monetary consequences to the subjects. This allows the observer to make inferences about the latent subjective probability, under virtually any well-specified model of choice under subjective risk, while still...

M≥7 Earthquake rupture forecast and time-dependent probability for the Sea of Marmara region, Turkey

Science.gov (United States)

Murru, Maura; Akinci, Aybige; Falcone, Guiseppe; Pucci, Stefano; Console, Rodolfo; Parsons, Thomas E.

2016-01-01

We forecast time-independent and time-dependent earthquake ruptures in the Marmara region of Turkey for the next 30 years using a new fault-segmentation model. We also augment time-dependent Brownian Passage Time (BPT) probability with static Coulomb stress changes (ΔCFF) from interacting faults. We calculate Mw > 6.5 probability from 26 individual fault sources in the Marmara region. We also consider a multisegment rupture model that allows higher-magnitude ruptures over some segments of the Northern branch of the North Anatolian Fault Zone (NNAF) beneath the Marmara Sea. A total of 10 different Mw=7.0 to Mw=8.0 multisegment ruptures are combined with the other regional faults at rates that balance the overall moment accumulation. We use Gaussian random distributions to treat parameter uncertainties (e.g., aperiodicity, maximum expected magnitude, slip rate, and consequently mean recurrence time) of the statistical distributions associated with each fault source. We then estimate uncertainties of the 30-year probability values for the next characteristic event obtained from three different models (Poisson, BPT, and BPT+ΔCFF) using a Monte Carlo procedure. The Gerede fault segment located at the eastern end of the Marmara region shows the highest 30-yr probability, with a Poisson value of 29%, and a time-dependent interaction probability of 48%. We find an aggregated 30-yr Poisson probability of M >7.3 earthquakes at Istanbul of 35%, which increases to 47% if time dependence and stress transfer are considered. We calculate a 2-fold probability gain (ratio time-dependent to time-independent) on the southern strands of the North Anatolian Fault Zone.
Probability and Bayesian statistics

CERN Document Server

1987-01-01

This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics an...
Market-implied risk-neutral probabilities, actual probabilities, credit risk and news

Directory of Open Access Journals (Sweden)

Shashidhar Murthy

2011-09-01

Full Text Available Motivated by the credit crisis, this paper investigates links between risk-neutral probabilities of default implied by markets (e.g. from yield spreads and their actual counterparts (e.g. from ratings. It discusses differences between the two and clarifies underlying economic intuition using simple representations of credit risk pricing. Observed large differences across bonds in the ratio of the two probabilities are shown to imply that apparently safer securities can be more sensitive to news.
Efficient reliability analysis of structures with the rotational quasi-symmetric point- and the maximum entropy methods

Science.gov (United States)

Xu, Jun; Dang, Chao; Kong, Fan

2017-10-01

This paper presents a new method for efficient structural reliability analysis. In this method, a rotational quasi-symmetric point method (RQ-SPM) is proposed for evaluating the fractional moments of the performance function. Then, the derivation of the performance function's probability density function (PDF) is carried out based on the maximum entropy method in which constraints are specified in terms of fractional moments. In this regard, the probability of failure can be obtained by a simple integral over the performance function's PDF. Six examples, including a finite element-based reliability analysis and a dynamic system with strong nonlinearity, are used to illustrate the efficacy of the proposed method. All the computed results are compared with those by Monte Carlo simulation (MCS). It is found that the proposed method can provide very accurate results with low computational effort.
Modelling the Probability of Landslides Impacting Road Networks

Science.gov (United States)

Taylor, F. E.; Malamud, B. D.

2012-04-01

During a landslide triggering event, the threat of landslides blocking roads poses a risk to logistics, rescue efforts and communities dependant on those road networks. Here we present preliminary results of a stochastic model we have developed to evaluate the probability of landslides intersecting a simple road network during a landslide triggering event and apply simple network indices to measure the state of the road network in the affected region. A 4000 x 4000 cell array with a 5 m x 5 m resolution was used, with a pre-defined simple road network laid onto it, and landslides 'randomly' dropped onto it. Landslide areas (AL) were randomly selected from a three-parameter inverse gamma probability density function, consisting of a power-law decay of about -2.4 for medium and large values of AL and an exponential rollover for small values of AL; the rollover (maximum probability) occurs at about AL = 400 m2 This statistical distribution was chosen based on three substantially complete triggered landslide inventories recorded in existing literature. The number of landslide areas (NL) selected for each triggered event iteration was chosen to have an average density of 1 landslide km-2, i.e. NL = 400 landslide areas chosen randomly for each iteration, and was based on several existing triggered landslide event inventories. A simple road network was chosen, in a 'T' shape configuration, with one road 1 x 4000 cells (5 m x 20 km) in a 'T' formation with another road 1 x 2000 cells (5 m x 10 km). The landslide areas were then randomly 'dropped' over the road array and indices such as the location, size (ABL) and number of road blockages (NBL) recorded. This process was performed 500 times (iterations) in a Monte-Carlo type simulation. Initial results show that for a landslide triggering event with 400 landslides over a 400 km2 region, the number of road blocks per iteration, NBL,ranges from 0 to 7. The average blockage area for the 500 iterations (A¯ BL) is about 3000 m
Spatial probability aids visual stimulus discrimination

Directory of Open Access Journals (Sweden)

Michael Druker

2010-08-01

Full Text Available We investigated whether the statistical predictability of a target's location would influence how quickly and accurately it was classified. Recent results have suggested that spatial probability can be a cue for the allocation of attention in visual search. One explanation for probability cuing is spatial repetition priming. In our two experiments we used probability distributions that were continuous across the display rather than relying on a few arbitrary screen locations. This produced fewer spatial repeats and allowed us to dissociate the effect of a high probability location from that of short-term spatial repetition. The task required participants to quickly judge the color of a single dot presented on a computer screen. In Experiment 1, targets were more probable in an off-center hotspot of high probability that gradually declined to a background rate. Targets garnered faster responses if they were near earlier target locations (priming and if they were near the high probability hotspot (probability cuing. In Experiment 2, target locations were chosen on three concentric circles around fixation. One circle contained 80% of targets. The value of this ring distribution is that it allowed for a spatially restricted high probability zone in which sequentially repeated trials were not likely to be physically close. Participant performance was sensitive to the high-probability circle in addition to the expected effects of eccentricity and the distance to recent targets. These two experiments suggest that inhomogeneities in spatial probability can be learned and used by participants on-line and without prompting as an aid for visual stimulus discrimination and that spatial repetition priming is not a sufficient explanation for this effect. Future models of attention should consider explicitly incorporating the probabilities of targets locations and features.
NASA Lewis Launch Collision Probability Model Developed and Analyzed

Science.gov (United States)

Bollenbacher, Gary; Guptill, James D

1999-01-01

. With these, and some additional simplifying assumptions, a closed-form solution for the probability of collision is obtained. This solution provides clear insights into how each of the independent parameters affects the probability of collision. It shows that for a given maximum probability of collision and prior knowledge of the objects position uncertainties and sizes, only knowledge of the nominal closest approach distance is required to make the launch/no launch decision. The model was completed and used for the mission assurance COLA analysis for the Cassini spacecraft, which was launched on a Titan IV/Centaur rocket on October 15, 1997. Although the model was specifically developed for the Cassini mission, it is clearly applicable for other launches as well. The effect of COLA closures on the launch window is shown. The bar represents the entire 140-min launch window on October 15, 1997; the blackened areas represent the loss of launch opportunities due to the potential for a collision with an orbiting object.
The sudden success of prose

DEFF Research Database (Denmark)

Mortensen, Lars Boje

2017-01-01

The article presents a new model for understanding the sudden success of prose in four literatures: Greek, Latin, French and Old Norse. Through comparison and quantitative observations, and by focusing on the success of prose rather than its invention, it is shown that in all four cases two...... reading aloud) has been underplayed in previous scholarship mostly focused on authorial choices and invention. For two of the literatures (Greek, French) the fast dynamics of the rise of prose has already been identified and discussed, but for the two others (Latin, Old Norse), the observation is new....... It is also suggested that the exactly contemporary rise of French and Old Norse prose (c. 1200-1230) most probably is connected. The four literatures are each shown in chronological charts so as to visualize the timeline and the relation between poetic and prosaic works. The article furthermore reflects...
Probability, Nondeterminism and Concurrency

DEFF Research Database (Denmark)

Varacca, Daniele

Nondeterminism is modelled in domain theory by the notion of a powerdomain, while probability is modelled by that of the probabilistic powerdomain. Some problems arise when we want to combine them in order to model computation in which both nondeterminism and probability are present. In particula...
A probable example of a nonmesonic double hypernucleus

CERN Document Server

Mondal, A S; Husain, A; Kasim, M M

1975-01-01

A search is made to identify hypernuclear species with two or more decay centres in nuclear emulsion exposed to a separated beam of 3.0 GeV/c K/sup -/-mesons at the CERN Proton Synchrotron. In a sample of 493 hypernuclei one event has been observed whose most probable interpretation turns out to be /sup 31/Si/sub Lambda Lambda / with the successive decay modes /sup 31/Si/sub Lambda Lambda / to /sup 14/C/sub Lambda /+/sup 16/O+n, followed by /sup 14/C/sub Lambda / to /sup 4/He+ /sup 3/He+/sup 3/He+/sup 2/H+/sup 1/H+n, and binding energy B/sub Lambda Lambda /=(38.2+or-6.3) MeV. (18 refs).
Importance of structural stability to success of mourning dove nests

Science.gov (United States)

Coon, R.A.; Nichols, J.D.; Percival, H.F.

1981-01-01

Studies of nest-site selection and nesting habitats often involve a "characterization" of nests and of habitats in which nests are found. Our objective in the present work is to identify nest-site characteristics that are associated with variation in components of Mourning Dove (Zenaida macroura) fitness (e.g. the probability of a nest succeeding), as opposed to simply "characterizing" dove nest sites. If certain nest- site characteristics affect the probability that a nest will succeed, then we suspect that these characteristics will be associated with either concealment (the probability of detection by certain predators) or structural stability (the probability of eggs or entire nests falling to the ground as a result of wind, rain storms, parental activity, etc.). Although other workers agree that structural stability is an important determinant of Mourning Dove nesting success (e.g. McClure 1944: 384; Woolfenden and Rohwer 1969: 59), we are aware of no actual tests of this hypothesis.
Ignition Probability

Data.gov (United States)

Earth Data Analysis Center, University of New Mexico — USFS, State Forestry, BLM, and DOI fire occurrence point locations from 1987 to 2008 were combined and converted into a fire occurrence probability or density grid...
Maximum mutual information vector quantization of log-likelihood ratios for memory efficient HARQ implementations

DEFF Research Database (Denmark)

Danieli, Matteo; Forchhammer, Søren; Andersen, Jakob Dahl

2010-01-01

analysis leads to using maximum mutual information (MMI) as optimality criterion and in turn Kullback-Leibler (KL) divergence as distortion measure. Simulations run based on an LTE-like system have proven that VQ can be implemented in a computationally simple way at low rates of 2-3 bits per LLR value......Modern mobile telecommunication systems, such as 3GPP LTE, make use of Hybrid Automatic Repeat reQuest (HARQ) for efficient and reliable communication between base stations and mobile terminals. To this purpose, marginal posterior probabilities of the received bits are stored in the form of log...
Probability of Failure in Random Vibration

DEFF Research Database (Denmark)

Nielsen, Søren R.K.; Sørensen, John Dalsgaard

1988-01-01

Close approximations to the first-passage probability of failure in random vibration can be obtained by integral equation methods. A simple relation exists between the first-passage probability density function and the distribution function for the time interval spent below a barrier before out......-crossing. An integral equation for the probability density function of the time interval is formulated, and adequate approximations for the kernel are suggested. The kernel approximation results in approximate solutions for the probability density function of the time interval and thus for the first-passage probability...
Feasible Histories, Maximum Entropy

International Nuclear Information System (INIS)

Pitowsky, I.

1999-01-01

We consider the broadest possible consistency condition for a family of histories, which extends all previous proposals. A family that satisfies this condition is called feasible. On each feasible family of histories we choose a probability measure by maximizing entropy, while keeping the probabilities of commuting histories to their quantum mechanical values. This procedure is justified by the assumption that decoherence increases entropy. Finally, a criterion for identifying the nearly classical families is proposed
Parental Post-traumatic Stress Disorder Symptoms Are Related to Successful Aging in Offspring of Holocaust Survivors

Science.gov (United States)

Shrira, Amit; Ayalon, Liat; Bensimon, Moshe; Bodner, Ehud; Rosenbloom, Tova; Yadid, Gal

2017-01-01

A fascinating, yet underexplored, question is whether traumatic events experienced by previous generations affect the aging process of subsequent generations. This question is especially relevant for offspring of Holocaust survivors (OHS), who begin to face the aging process. Some preliminary findings point to greater physical dysfunction among middle-aged OHS, yet the mechanisms behind this dysfunction need further clarification. Therefore, the current studies assess aging OHS using the broad-scoped conceptualization of successful aging, while examining whether offspring successful aging relates to parental post-traumatic stress disorder (PTSD) symptoms and offspring’s secondary traumatization symptoms. In Study 1, 101 adult offspring (mean age = 62.31) completed measures of parental PTSD, secondary traumatization, as well as successful aging indices – objective (medical conditions, disability and somatic symptoms) and subjective (perceptions of one’s aging). Relative to comparisons and OHS who reported that none of their parents suffered from probable PTSD, OHS who reported that their parents suffered from probable PTSD had lower scores in objective and subjective measures of successful aging. Mediation analyses showed that higher level of secondary traumatization mediated the relationship between parental PTSD and less successful aging in the offspring. Study 2 included 154 dyads of parents (mean age = 81.86) and their adult offspring (mean age = 54.48). Parents reported PTSD symptoms and offspring reported secondary traumatization and completed measures of objective successful aging. Relative to comparisons, OHS whose parent had probable PTSD have aged less successfully. Once again, offspring secondary traumatization mediated the effect. The findings suggest that parental post-traumatic reactions assessed both by offspring (Study 1) and by parents themselves (Study 2) take part in shaping the aging of the subsequent generation via reactions of secondary
Parental Post-traumatic Stress Disorder Symptoms Are Related to Successful Aging in Offspring of Holocaust Survivors

Directory of Open Access Journals (Sweden)

Amit Shrira

2017-06-01

Full Text Available A fascinating, yet underexplored, question is whether traumatic events experienced by previous generations affect the aging process of subsequent generations. This question is especially relevant for offspring of Holocaust survivors (OHS, who begin to face the aging process. Some preliminary findings point to greater physical dysfunction among middle-aged OHS, yet the mechanisms behind this dysfunction need further clarification. Therefore, the current studies assess aging OHS using the broad-scoped conceptualization of successful aging, while examining whether offspring successful aging relates to parental post-traumatic stress disorder (PTSD symptoms and offspring’s secondary traumatization symptoms. In Study 1, 101 adult offspring (mean age = 62.31 completed measures of parental PTSD, secondary traumatization, as well as successful aging indices – objective (medical conditions, disability and somatic symptoms and subjective (perceptions of one’s aging. Relative to comparisons and OHS who reported that none of their parents suffered from probable PTSD, OHS who reported that their parents suffered from probable PTSD had lower scores in objective and subjective measures of successful aging. Mediation analyses showed that higher level of secondary traumatization mediated the relationship between parental PTSD and less successful aging in the offspring. Study 2 included 154 dyads of parents (mean age = 81.86 and their adult offspring (mean age = 54.48. Parents reported PTSD symptoms and offspring reported secondary traumatization and completed measures of objective successful aging. Relative to comparisons, OHS whose parent had probable PTSD have aged less successfully. Once again, offspring secondary traumatization mediated the effect. The findings suggest that parental post-traumatic reactions assessed both by offspring (Study 1 and by parents themselves (Study 2 take part in shaping the aging of the subsequent generation via reactions of
Measures, Probability and Holography in Cosmology

Science.gov (United States)

Phillips, Daniel

This dissertation compiles four research projects on predicting values for cosmological parameters and models of the universe on the broadest scale. The first examines the Causal Entropic Principle (CEP) in inhomogeneous cosmologies. The CEP aims to predict the unexpectedly small value of the cosmological constant Lambda using a weighting by entropy increase on causal diamonds. The original work assumed a purely isotropic and homogeneous cosmology. But even the level of inhomogeneity observed in our universe forces reconsideration of certain arguments about entropy production. In particular, we must consider an ensemble of causal diamonds associated with each background cosmology and we can no longer immediately discard entropy production in the far future of the universe. Depending on our choices for a probability measure and our treatment of black hole evaporation, the prediction for Lambda may be left intact or dramatically altered. The second related project extends the CEP to universes with curvature. We have found that curvature values larger than rho k = 40rhom are disfavored by more than $99.99% and a peak value at rhoLambda = 7.9 x 10-123 and rhok =4.3rho m for open universes. For universes that allow only positive curvature or both positive and negative curvature, we find a correlation between curvature and dark energy that leads to an extended region of preferred values. Our universe is found to be disfavored to an extent depending the priors on curvature. We also provide a comparison to previous anthropic constraints on open universes and discuss future directions for this work. The third project examines how cosmologists should formulate basic questions of probability. We argue using simple models that all successful practical uses of probabilities originate in quantum fluctuations in the microscopic physical world around us, often propagated to macroscopic scales. Thus we claim there is no physically verified fully classical theory of probability. We
Characteristics of Plantar Loads in Maximum Forward Lunge Tasks in Badminton.

Directory of Open Access Journals (Sweden)

Xiaoyue Hu

Full Text Available Badminton players often perform powerful and long-distance lunges during such competitive matches. The objective of this study is to compare the plantar loads of three one-step maximum forward lunges in badminton.Fifteen right-handed male badminton players participated in the study. Each participant performed five successful maximum lunges at three directions. For each direction, the participant wore three different shoe brands. Plantar loading, including peak pressure, maximum force, and contact area, was measured by using an insole pressure measurement system. Two-way ANOVA with repeated measures was employed to determine the effects of the different lunge directions and different shoes, as well as the interaction of these two variables, on the measurements.The maximum force (MF on the lateral midfoot was lower when performing left-forward lunges than when performing front-forward lunges (p = 0.006, 95% CI = -2.88 to -0.04%BW. The MF and peak pressures (PP on the great toe region were lower for the front-forward lunge than for the right-forward lunge (MF, p = 0.047, 95% CI = -3.62 to -0.02%BW; PP, p = 0.048, 95% CI = -37.63 to -0.16 KPa and left-forward lunge (MF, p = 0.015, 95% CI = -4.39 to -0.38%BW; PP, p = 0.008, 95% CI = -47.76 to -5.91 KPa.These findings indicate that compared with the front-forward lunge, left and right maximum forward lunges induce greater plantar loads on the great toe region of the dominant leg of badminton players. The differences in the plantar loads of the different lunge directions may be potential risks for injuries to the lower extremities of badminton players.
Strategy evolution driven by switching probabilities in structured multi-agent systems

Science.gov (United States)

Zhang, Jianlei; Chen, Zengqiang; Li, Zhiqi

2017-10-01

Evolutionary mechanism driving the commonly seen cooperation among unrelated individuals is puzzling. Related models for evolutionary games on graphs traditionally assume that players imitate their successful neighbours with higher benefits. Notably, an implicit assumption here is that players are always able to acquire the required pay-off information. To relax this restrictive assumption, a contact-based model has been proposed, where switching probabilities between strategies drive the strategy evolution. However, the explicit and quantified relation between a player's switching probability for her strategies and the number of her neighbours remains unknown. This is especially a key point in heterogeneously structured system, where players may differ in the numbers of their neighbours. Focusing on this, here we present an augmented model by introducing an attenuation coefficient and evaluate its influence on the evolution dynamics. Results show that the individual influence on others is negatively correlated with the contact numbers specified by the network topologies. Results further provide the conditions under which the coexisting strategies can be calculated analytically.

Quantification of a decision-making failure probability of the accident management using cognitive analysis model

Energy Technology Data Exchange (ETDEWEB)

Yoshida, Yoshitaka; Ohtani, Masanori [Institute of Nuclear Safety System, Inc., Mihama, Fukui (Japan); Fujita, Yushi [TECNOVA Corp., Tokyo (Japan)

2002-09-01

In the nuclear power plant, much knowledge is acquired through probabilistic safety assessment (PSA) of a severe accident, and accident management (AM) is prepared. It is necessary to evaluate the effectiveness of AM using the decision-making failure probability of an emergency organization, operation failure probability of operators, success criteria of AM and reliability of AM equipments in PSA. However, there has been no suitable qualification method for PSA so far to obtain the decision-making failure probability, because the decision-making failure of an emergency organization treats the knowledge based error. In this work, we developed a new method for quantification of the decision-making failure probability of an emergency organization using cognitive analysis model, which decided an AM strategy, in a nuclear power plant at the severe accident, and tried to apply it to a typical pressurized water reactor (PWR) plant. As a result: (1) It could quantify the decision-making failure probability adjusted to PSA for general analysts, who do not necessarily possess professional human factors knowledge, by choosing the suitable value of a basic failure probability and an error-factor. (2) The decision-making failure probabilities of six AMs were in the range of 0.23 to 0.41 using the screening evaluation method and in the range of 0.10 to 0.19 using the detailed evaluation method as the result of trial evaluation based on severe accident analysis of a typical PWR plant, and a result of sensitivity analysis of the conservative assumption, failure probability decreased about 50%. (3) The failure probability using the screening evaluation method exceeded that using detailed evaluation method by 99% of probability theoretically, and the failure probability of AM in this study exceeded 100%. From this result, it was shown that the decision-making failure probability was more conservative than the detailed evaluation method, and the screening evaluation method satisfied
Quantification of a decision-making failure probability of the accident management using cognitive analysis model

International Nuclear Information System (INIS)

Yoshida, Yoshitaka; Ohtani, Masanori; Fujita, Yushi

2002-01-01

In the nuclear power plant, much knowledge is acquired through probabilistic safety assessment (PSA) of a severe accident, and accident management (AM) is prepared. It is necessary to evaluate the effectiveness of AM using the decision-making failure probability of an emergency organization, operation failure probability of operators, success criteria of AM and reliability of AM equipments in PSA. However, there has been no suitable qualification method for PSA so far to obtain the decision-making failure probability, because the decision-making failure of an emergency organization treats the knowledge based error. In this work, we developed a new method for quantification of the decision-making failure probability of an emergency organization using cognitive analysis model, which decided an AM strategy, in a nuclear power plant at the severe accident, and tried to apply it to a typical pressurized water reactor (PWR) plant. As a result: (1) It could quantify the decision-making failure probability adjusted to PSA for general analysts, who do not necessarily possess professional human factors knowledge, by choosing the suitable value of a basic failure probability and an error-factor. (2) The decision-making failure probabilities of six AMs were in the range of 0.23 to 0.41 using the screening evaluation method and in the range of 0.10 to 0.19 using the detailed evaluation method as the result of trial evaluation based on severe accident analysis of a typical PWR plant, and a result of sensitivity analysis of the conservative assumption, failure probability decreased about 50%. (3) The failure probability using the screening evaluation method exceeded that using detailed evaluation method by 99% of probability theoretically, and the failure probability of AM in this study exceeded 100%. From this result, it was shown that the decision-making failure probability was more conservative than the detailed evaluation method, and the screening evaluation method satisfied
The modulation of simple reaction time by the spatial probability of a visual stimulus

Directory of Open Access Journals (Sweden)

Carreiro L.R.R.

2003-01-01

Full Text Available Simple reaction time (SRT in response to visual stimuli can be influenced by many stimulus features. The speed and accuracy with which observers respond to a visual stimulus may be improved by prior knowledge about the stimulus location, which can be obtained by manipulating the spatial probability of the stimulus. However, when higher spatial probability is achieved by holding constant the stimulus location throughout successive trials, the resulting improvement in performance can also be due to local sensory facilitation caused by the recurrent spatial location of a visual target (position priming. The main objective of the present investigation was to quantitatively evaluate the modulation of SRT by the spatial probability structure of a visual stimulus. In two experiments the volunteers had to respond as quickly as possible to the visual target presented on a computer screen by pressing an optic key with the index finger of the dominant hand. Experiment 1 (N = 14 investigated how SRT changed as a function of both the different levels of spatial probability and the subject's explicit knowledge about the precise probability structure of visual stimulation. We found a gradual decrease in SRT with increasing spatial probability of a visual target regardless of the observer's previous knowledge concerning the spatial probability of the stimulus. Error rates, below 2%, were independent of the spatial probability structure of the visual stimulus, suggesting the absence of a speed-accuracy trade-off. Experiment 2 (N = 12 examined whether changes in SRT in response to a spatially recurrent visual target might be accounted for simply by sensory and temporally local facilitation. The findings indicated that the decrease in SRT brought about by a spatially recurrent target was associated with its spatial predictability, and could not be accounted for solely in terms of sensory priming.
Controlling principles for prior probability assignments in nuclear risk assessment

International Nuclear Information System (INIS)

Cook, I.; Unwin, S.D.

1986-01-01

As performed conventionally, nuclear probabilistic risk assessment (PRA) may be criticized as utilizing inscrutable and unjustifiably ''precise'' quantitative informed judgment or extrapolation from that judgment. To meet this criticism, controlling principles that govern the formulation of probability densities are proposed, given only the informed input that would be required for a simple bounding analysis. These principles are founded upon information theoretic ideas of maximum uncertainty and cover both cases in which there exists a stochastic model of the phenomenon of interest and cases in which these is no such model. In part, the principles are conventional, and such an approach is justified by appealing to certain analogies in accounting practice and judicial decision making. Examples are given. Appropriate employment of these principles is expected to facilitate substantial progress toward PRA scrutability and transparency
Developing the fuzzy c-means clustering algorithm based on maximum entropy for multitarget tracking in a cluttered environment

Science.gov (United States)

Chen, Xiao; Li, Yaan; Yu, Jing; Li, Yuxing

2018-01-01

For fast and more effective implementation of tracking multiple targets in a cluttered environment, we propose a multiple targets tracking (MTT) algorithm called maximum entropy fuzzy c-means clustering joint probabilistic data association that combines fuzzy c-means clustering and the joint probabilistic data association (PDA) algorithm. The algorithm uses the membership value to express the probability of the target originating from measurement. The membership value is obtained through fuzzy c-means clustering objective function optimized by the maximum entropy principle. When considering the effect of the public measurement, we use a correction factor to adjust the association probability matrix to estimate the state of the target. As this algorithm avoids confirmation matrix splitting, it can solve the high computational load problem of the joint PDA algorithm. The results of simulations and analysis conducted for tracking neighbor parallel targets and cross targets in a different density cluttered environment show that the proposed algorithm can realize MTT quickly and efficiently in a cluttered environment. Further, the performance of the proposed algorithm remains constant with increasing process noise variance. The proposed algorithm has the advantages of efficiency and low computational load, which can ensure optimum performance when tracking multiple targets in a dense cluttered environment.
Invariant probabilities of transition functions

CERN Document Server

Zaharopol, Radu

2014-01-01

The structure of the set of all the invariant probabilities and the structure of various types of individual invariant probabilities of a transition function are two topics of significant interest in the theory of transition functions, and are studied in this book. The results obtained are useful in ergodic theory and the theory of dynamical systems, which, in turn, can be applied in various other areas (like number theory). They are illustrated using transition functions defined by flows, semiflows, and one-parameter convolution semigroups of probability measures. In this book, all results on transition probabilities that have been published by the author between 2004 and 2008 are extended to transition functions. The proofs of the results obtained are new. For transition functions that satisfy very general conditions the book describes an ergodic decomposition that provides relevant information on the structure of the corresponding set of invariant probabilities. Ergodic decomposition means a splitting of t...
Maximum one-shot dissipated work from Rényi divergences

Science.gov (United States)

Yunger Halpern, Nicole; Garner, Andrew J. P.; Dahlsten, Oscar C. O.; Vedral, Vlatko

2018-05-01

Thermodynamics describes large-scale, slowly evolving systems. Two modern approaches generalize thermodynamics: fluctuation theorems, which concern finite-time nonequilibrium processes, and one-shot statistical mechanics, which concerns small scales and finite numbers of trials. Combining these approaches, we calculate a one-shot analog of the average dissipated work defined in fluctuation contexts: the cost of performing a protocol in finite time instead of quasistatically. The average dissipated work has been shown to be proportional to a relative entropy between phase-space densities, to a relative entropy between quantum states, and to a relative entropy between probability distributions over possible values of work. We derive one-shot analogs of all three equations, demonstrating that the order-infinity Rényi divergence is proportional to the maximum possible dissipated work in each case. These one-shot analogs of fluctuation-theorem results contribute to the unification of these two toolkits for small-scale, nonequilibrium statistical physics.
The concept of probability

International Nuclear Information System (INIS)

Bitsakis, E.I.; Nicolaides, C.A.

1989-01-01

The concept of probability is now, and always has been, central to the debate on the interpretation of quantum mechanics. Furthermore, probability permeates all of science, as well as our every day life. The papers included in this volume, written by leading proponents of the ideas expressed, embrace a broad spectrum of thought and results: mathematical, physical epistemological, and experimental, both specific and general. The contributions are arranged in parts under the following headings: Following Schroedinger's thoughts; Probability and quantum mechanics; Aspects of the arguments on nonlocality; Bell's theorem and EPR correlations; Real or Gedanken experiments and their interpretation; Questions about irreversibility and stochasticity; and Epistemology, interpretation and culture. (author). refs.; figs.; tabs
Choice probability generating functions

DEFF Research Database (Denmark)

Fosgerau, Mogens; McFadden, Daniel; Bierlaire, Michel

2010-01-01

This paper establishes that every random utility discrete choice model (RUM) has a representation that can be characterized by a choice-probability generating function (CPGF) with specific properties, and that every function with these specific properties is consistent with a RUM. The choice...... probabilities from the RUM are obtained from the gradient of the CPGF. Mixtures of RUM are characterized by logarithmic mixtures of their associated CPGF. The paper relates CPGF to multivariate extreme value distributions, and reviews and extends methods for constructing generating functions for applications....... The choice probabilities of any ARUM may be approximated by a cross-nested logit model. The results for ARUM are extended to competing risk survival models....
Maximum concentrations at work and maximum biologically tolerable concentration for working materials 1991

International Nuclear Information System (INIS)

1991-01-01

The meaning of the term 'maximum concentration at work' in regard of various pollutants is discussed. Specifically, a number of dusts and smokes are dealt with. The valuation criteria for maximum biologically tolerable concentrations for working materials are indicated. The working materials in question are corcinogeneous substances or substances liable to cause allergies or mutate the genome. (VT) [de
Success in the Academic Labour Market for Economics - The German Experience

OpenAIRE

Heining, Jörg; Jerger, Jürgen; Lingens, Jörg

2007-01-01

Based on CV information of tenured professors and post-doc researchers in the field of economics at German universities we construct a unique data set. This data set contains detailed information on the career path and on personal characteristics of individuals. Using this data we analyse the determinants of success in the academic labour market. Our notion of success is the (conditional) probability of becoming tenured, i.e. the hazard rate. Estimating a Cox (1972) regressi...
Limited test data: The choice between confidence limits and inverse probability

International Nuclear Information System (INIS)

Nichols, P.

1975-01-01

For a unit which has been successfully designed to a high standard of reliability, any test programme of reasonable size will result in only a small number of failures. In these circumstances the failure rate estimated from the tests will depend on the statistical treatment applied. When a large number of units is to be manufactured, an unexpected high failure rate will certainly result in a large number of failures, so it is necessary to guard against optimistic unrepresentative test results by using a confidence limit approach. If only a small number of production units is involved, failures may not occur even with a higher than expected failure rate, and so one may be able to accept a method which allows for the possibility of either optimistic or pessimistic test results, and in this case an inverse probability approach, based on Bayes' theorem, might be used. The paper first draws attention to an apparently significant difference in the numerical results from the two methods, particularly for the overall probability of several units arranged in redundant logic. It then discusses a possible objection to the inverse method, followed by a demonstration that, for a large population and a very reasonable choice of prior probability, the inverse probability and confidence limit methods give the same numerical result. Finally, it is argued that a confidence limit approach is overpessimistic when a small number of production units is involved, and that both methods give the same answer for a large population. (author)
40 CFR 1042.140 - Maximum engine power, displacement, power density, and maximum in-use engine speed.

Science.gov (United States)

2010-07-01

... cylinders having an internal diameter of 13.0 cm and a 15.5 cm stroke length, the rounded displacement would... 40 Protection of Environment 32 2010-07-01 2010-07-01 false Maximum engine power, displacement... Maximum engine power, displacement, power density, and maximum in-use engine speed. This section describes...
Probability via expectation

CERN Document Server

Whittle, Peter

1992-01-01

This book is a complete revision of the earlier work Probability which ap peared in 1970. While revised so radically and incorporating so much new material as to amount to a new text, it preserves both the aim and the approach of the original. That aim was stated as the provision of a 'first text in probability, de manding a reasonable but not extensive knowledge of mathematics, and taking the reader to what one might describe as a good intermediate level'. In doing so it attempted to break away from stereotyped applications, and consider applications of a more novel and significant character. The particular novelty of the approach was that expectation was taken as the prime concept, and the concept of expectation axiomatized rather than that of a probability measure. In the preface to the original text of 1970 (reproduced below, together with that to the Russian edition of 1982) I listed what I saw as the advantages of the approach in as unlaboured a fashion as I could. I also took the view that the text...
The probability outcome correpondence principle : a dispositional view of the interpretation of probability statements

NARCIS (Netherlands)

Keren, G.; Teigen, K.H.

2001-01-01

This article presents a framework for lay people's internal representations of probabilities, which supposedly reflect the strength of underlying dispositions, or propensities, associated with the predicted event. From this framework, we derive the probability-outcome correspondence principle, which
Poisson Processes in Free Probability

OpenAIRE

An, Guimei; Gao, Mingchu

2015-01-01

We prove a multidimensional Poisson limit theorem in free probability, and define joint free Poisson distributions in a non-commutative probability space. We define (compound) free Poisson process explicitly, similar to the definitions of (compound) Poisson processes in classical probability. We proved that the sum of finitely many freely independent compound free Poisson processes is a compound free Poisson processes. We give a step by step procedure for constructing a (compound) free Poisso...
Solving probability reasoning based on DNA strand displacement and probability modules.

Science.gov (United States)

Zhang, Qiang; Wang, Xiaobiao; Wang, Xiaojun; Zhou, Changjun

2017-12-01

In computation biology, DNA strand displacement technology is used to simulate the computation process and has shown strong computing ability. Most researchers use it to solve logic problems, but it is only rarely used in probabilistic reasoning. To process probabilistic reasoning, a conditional probability derivation model and total probability model based on DNA strand displacement were established in this paper. The models were assessed through the game "read your mind." It has been shown to enable the application of probabilistic reasoning in genetic diagnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.
Measurement and estimation of maximum skin dose to the patient for different interventional procedures

International Nuclear Information System (INIS)

Cheng Yuxi; Liu Lantao; Wei Kedao; Yu Peng; Yan Shulin; Li Tianchang

2005-01-01

Objective: To determine the dose distribution and maximum skin dose to the patient for four interventional procedures: coronary angiography (CA), hepatic angiography (HA), radiofrequency ablation (RF) and cerebral angiography (CAG), and to estimate the definitive effect of radiation on skin. Methods: Skin dose was measured using LiF: Mg, Cu, P TLD chips. A total of 9 measuring points were chosen on the back of the patient with two TLDs placed at each point, for CA, HA and RF interventional procedures, whereas two TLDs were placed on one point each at the postero-anterior (PA) and lateral side (LAT) respectively, during the CAG procedure. Results: The results revealed that the maximum skin dose to the patient was 1683.91 mGy for the HA procedure with a mean value of 607.29 mGy. The maximum skin dose at the PA point was 959.3 mGy for the CAG with a mean value of 418.79 mGy; While the maximum and the mean doses at the LAT point were 704 mGy and 191.52 mGy, respectively. For the RF procedure the maximum dose was 853.82 mGy and the mean was 219.67 mGy. For the CA procedure the maximum dose was 456.1 mGy and the mean was 227.63 mGy. Conclusion: All the measured dose values in this study are estimated ones which could not provide the accurate maximum value because it is difficult to measure using a great deal of TLDs. On the other hand, the small area of skin exposed to high dose could be missed as the distribution of the dose is successive. (authors)
Sensitivity of the probability of failure to probability of detection curve regions

International Nuclear Information System (INIS)

Garza, J.; Millwater, H.

2016-01-01

Non-destructive inspection (NDI) techniques have been shown to play a vital role in fracture control plans, structural health monitoring, and ensuring availability and reliability of piping, pressure vessels, mechanical and aerospace equipment. Probabilistic fatigue simulations are often used in order to determine the efficacy of an inspection procedure with the NDI method modeled as a probability of detection (POD) curve. These simulations can be used to determine the most advantageous NDI method for a given application. As an aid to this process, a first order sensitivity method of the probability-of-failure (POF) with respect to regions of the POD curve (lower tail, middle region, right tail) is developed and presented here. The sensitivity method computes the partial derivative of the POF with respect to a change in each region of a POD or multiple POD curves. The sensitivities are computed at no cost by reusing the samples from an existing Monte Carlo (MC) analysis. A numerical example is presented considering single and multiple inspections. - Highlights: • Sensitivities of probability-of-failure to a region of probability-of-detection curve. • The sensitivities are computed with negligible cost. • Sensitivities identify the important region of a POD curve. • Sensitivities can be used as a guide to selecting the optimal POD curve.
Truth, possibility and probability new logical foundations of probability and statistical inference

CERN Document Server

Chuaqui, R

1991-01-01

Anyone involved in the philosophy of science is naturally drawn into the study of the foundations of probability. Different interpretations of probability, based on competing philosophical ideas, lead to different statistical techniques, and frequently to mutually contradictory consequences. This unique book presents a new interpretation of probability, rooted in the traditional interpretation that was current in the 17th and 18th centuries. Mathematical models are constructed based on this interpretation, and statistical inference and decision theory are applied, including some examples in artificial intelligence, solving the main foundational problems. Nonstandard analysis is extensively developed for the construction of the models and in some of the proofs. Many nonstandard theorems are proved, some of them new, in particular, a representation theorem that asserts that any stochastic process can be approximated by a process defined over a space with equiprobable outcomes.

Predicting Manual Therapy Treatment Success in Patients With Chronic Ankle Instability: Improving Self-Reported Function.

Science.gov (United States)

Wikstrom, Erik A; McKeon, Patrick O

2017-04-01

Therapeutic modalities that stimulate sensory receptors around the foot-ankle complex improve chronic ankle instability (CAI)-associated impairments. However, not all patients have equal responses to these modalities. Identifying predictors of treatment success could improve clinician efficiency when treating patients with CAI. To conduct a response analysis on existing data to identify predictors of improved self-reported function in patients with CAI. Secondary analysis of a randomized controlled clinical trial. Sports medicine research laboratories. Fifty-nine patients with CAI, which was defined in accordance with the International Ankle Consortium recommendations. Participants were randomized into 3 treatment groups (plantar massage [PM], ankle-joint mobilization [AJM], or calf stretching [CS]) that received six 5-minute treatments over 2 weeks. Treatment success, defined as a patient exceeding the minimally clinically important difference of the Foot and Ankle Ability Measure-Sport (FAAM-S). Patients with ≤5 recurrent sprains and ≤82.73% on the Foot and Ankle Ability Measure had a 98% probability of having a meaningful FAAM-S improvement after AJM. As well, ≥5 balance errors demonstrated 98% probability of meaningful FAAM-S improvements from AJM. Patients <22 years old and with ≤9.9 cm of dorsiflexion had a 99% probability of a meaningful FAAM-S improvement after PM. Also, those who made ≥2 single-limb-stance errors had a 98% probability of a meaningful FAAM-S improvement from PM. Patients with ≤53.1% on the FAAM-S had an 83% probability of a meaningful FAAM-S improvement after CS. Each sensory-targeted ankle-rehabilitation strategy resulted in a unique combination of predictors of success for patients with CAI. Specific indicators of success with AJM were deficits in self-reported function, single-limb balance, and <5 previous sprains. Age, weight-bearing-dorsiflexion restrictions, and single-limb balance
Maximum Quantum Entropy Method

OpenAIRE

Sim, Jae-Hoon; Han, Myung Joon

2018-01-01

Maximum entropy method for analytic continuation is extended by introducing quantum relative entropy. This new method is formulated in terms of matrix-valued functions and therefore invariant under arbitrary unitary transformation of input matrix. As a result, the continuation of off-diagonal elements becomes straightforward. Without introducing any further ambiguity, the Bayesian probabilistic interpretation is maintained just as in the conventional maximum entropy method. The applications o...
Logic, probability, and human reasoning.

Science.gov (United States)

Johnson-Laird, P N; Khemlani, Sangeet S; Goodwin, Geoffrey P

2015-04-01

This review addresses the long-standing puzzle of how logic and probability fit together in human reasoning. Many cognitive scientists argue that conventional logic cannot underlie deductions, because it never requires valid conclusions to be withdrawn - not even if they are false; it treats conditional assertions implausibly; and it yields many vapid, although valid, conclusions. A new paradigm of probability logic allows conclusions to be withdrawn and treats conditionals more plausibly, although it does not address the problem of vapidity. The theory of mental models solves all of these problems. It explains how people reason about probabilities and postulates that the machinery for reasoning is itself probabilistic. Recent investigations accordingly suggest a way to integrate probability and deduction. Copyright © 2015 Elsevier Ltd. All rights reserved.
Pre-Aggregation with Probability Distributions

DEFF Research Database (Denmark)

Timko, Igor; Dyreson, Curtis E.; Pedersen, Torben Bach

2006-01-01

Motivated by the increasing need to analyze complex, uncertain multidimensional data this paper proposes probabilistic OLAP queries that are computed using probability distributions rather than atomic values. The paper describes how to create probability distributions from base data, and how...... the distributions can be subsequently used in pre-aggregation. Since the probability distributions can become large, we show how to achieve good time and space efficiency by approximating the distributions. We present the results of several experiments that demonstrate the effectiveness of our methods. The work...... is motivated with a real-world case study, based on our collaboration with a leading Danish vendor of location-based services. This paper is the first to consider the approximate processing of probabilistic OLAP queries over probability distributions....
Conditional probability distribution associated to the E-M image reconstruction algorithm for neutron stimulated emission tomography

International Nuclear Information System (INIS)

Viana, R.S.; Yoriyaz, H.; Santos, A.

2011-01-01

The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)
Conditional probability distribution associated to the E-M image reconstruction algorithm for neutron stimulated emission tomography

Energy Technology Data Exchange (ETDEWEB)

Viana, R.S.; Yoriyaz, H.; Santos, A., E-mail: rodrigossviana@gmail.com, E-mail: hyoriyaz@ipen.br, E-mail: asantos@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2011-07-01

The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)
Probability and stochastic modeling

CERN Document Server

Rotar, Vladimir I

2012-01-01

Basic NotionsSample Space and EventsProbabilitiesCounting TechniquesIndependence and Conditional ProbabilityIndependenceConditioningThe Borel-Cantelli TheoremDiscrete Random VariablesRandom Variables and VectorsExpected ValueVariance and Other Moments. Inequalities for DeviationsSome Basic DistributionsConvergence of Random Variables. The Law of Large NumbersConditional ExpectationGenerating Functions. Branching Processes. Random Walk RevisitedBranching Processes Generating Functions Branching Processes Revisited More on Random WalkMarkov ChainsDefinitions and Examples. Probability Distributions of Markov ChainsThe First Step Analysis. Passage TimesVariables Defined on a Markov ChainErgodicity and Stationary DistributionsA Classification of States and ErgodicityContinuous Random VariablesContinuous DistributionsSome Basic Distributions Continuous Multivariate Distributions Sums of Independent Random Variables Conditional Distributions and ExpectationsDistributions in the General Case. SimulationDistribution F...
Transitional Probabilities Are Prioritized over Stimulus/Pattern Probabilities in Auditory Deviance Detection: Memory Basis for Predictive Sound Processing.

Science.gov (United States)

Mittag, Maria; Takegata, Rika; Winkler, István

2016-09-14

Representations encoding the probabilities of auditory events do not directly support predictive processing. In contrast, information about the probability with which a given sound follows another (transitional probability) allows predictions of upcoming sounds. We tested whether behavioral and cortical auditory deviance detection (the latter indexed by the mismatch negativity event-related potential) relies on probabilities of sound patterns or on transitional probabilities. We presented healthy adult volunteers with three types of rare tone-triplets among frequent standard triplets of high-low-high (H-L-H) or L-H-L pitch structure: proximity deviant (H-H-H/L-L-L), reversal deviant (L-H-L/H-L-H), and first-tone deviant (L-L-H/H-H-L). If deviance detection was based on pattern probability, reversal and first-tone deviants should be detected with similar latency because both differ from the standard at the first pattern position. If deviance detection was based on transitional probabilities, then reversal deviants should be the most difficult to detect because, unlike the other two deviants, they contain no low-probability pitch transitions. The data clearly showed that both behavioral and cortical auditory deviance detection uses transitional probabilities. Thus, the memory traces underlying cortical deviance detection may provide a link between stimulus probability-based change/novelty detectors operating at lower levels of the auditory system and higher auditory cognitive functions that involve predictive processing. Our research presents the first definite evidence for the auditory system prioritizing transitional probabilities over probabilities of individual sensory events. Forming representations for transitional probabilities paves the way for predictions of upcoming sounds. Several recent theories suggest that predictive processing provides the general basis of human perception, including important auditory functions, such as auditory scene analysis. Our
Weighted Maximum-Clique Transversal Sets of Graphs

OpenAIRE

Chuan-Min Lee

2011-01-01

A maximum-clique transversal set of a graph G is a subset of vertices intersecting all maximum cliques of G. The maximum-clique transversal set problem is to find a maximum-clique transversal set of G of minimum cardinality. Motivated by the placement of transmitters for cellular telephones, Chang, Kloks, and Lee introduced the concept of maximum-clique transversal sets on graphs in 2001. In this paper, we study the weighted version of the maximum-clique transversal set problem for split grap...
Probability tales

CERN Document Server

Grinstead, Charles M; Snell, J Laurie

2011-01-01

This book explores four real-world topics through the lens of probability theory. It can be used to supplement a standard text in probability or statistics. Most elementary textbooks present the basic theory and then illustrate the ideas with some neatly packaged examples. Here the authors assume that the reader has seen, or is learning, the basic theory from another book and concentrate in some depth on the following topics: streaks, the stock market, lotteries, and fingerprints. This extended format allows the authors to present multiple approaches to problems and to pursue promising side discussions in ways that would not be possible in a book constrained to cover a fixed set of topics. To keep the main narrative accessible, the authors have placed the more technical mathematical details in appendices. The appendices can be understood by someone who has taken one or two semesters of calculus.
High performance monolithic power management system with dynamic maximum power point tracking for microbial fuel cells.

Science.gov (United States)

Erbay, Celal; Carreon-Bautista, Salvador; Sanchez-Sinencio, Edgar; Han, Arum

2014-12-02

Microbial fuel cell (MFC) that can directly generate electricity from organic waste or biomass is a promising renewable and clean technology. However, low power and low voltage output of MFCs typically do not allow directly operating most electrical applications, whether it is supplementing electricity to wastewater treatment plants or for powering autonomous wireless sensor networks. Power management systems (PMSs) can overcome this limitation by boosting the MFC output voltage and managing the power for maximum efficiency. We present a monolithic low-power-consuming PMS integrated circuit (IC) chip capable of dynamic maximum power point tracking (MPPT) to maximize the extracted power from MFCs, regardless of the power and voltage fluctuations from MFCs over time. The proposed PMS continuously detects the maximum power point (MPP) of the MFC and matches the load impedance of the PMS for maximum efficiency. The system also operates autonomously by directly drawing power from the MFC itself without any external power. The overall system efficiency, defined as the ratio between input energy from the MFC and output energy stored into the supercapacitor of the PMS, was 30%. As a demonstration, the PMS connected to a 240 mL two-chamber MFC (generating 0.4 V and 512 μW at MPP) successfully powered a wireless temperature sensor that requires a voltage of 2.5 V and consumes power of 85 mW each time it transmit the sensor data, and successfully transmitted a sensor reading every 7.5 min. The PMS also efficiently managed the power output of a lower-power producing MFC, demonstrating that the PMS works efficiently at various MFC power output level.
A Tale of Two Probabilities

Science.gov (United States)

Falk, Ruma; Kendig, Keith

2013-01-01

Two contestants debate the notorious probability problem of the sex of the second child. The conclusions boil down to explication of the underlying scenarios and assumptions. Basic principles of probability theory are highlighted.
Spatial variability in cost and success of revegetation in a Wyoming big sagebrush community.

Science.gov (United States)

Boyd, Chad S; Davies, Kirk W

2012-09-01

The ecological integrity of the Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis Beetle and A. Young) alliance is being severely interrupted by post-fire invasion of non-native annual grasses. To curtail this invasion, successful post-fire revegetation of perennial grasses is required. Environmental factors impacting post-fire restoration success vary across space within the Wyoming big sagebrush alliance; however, most restorative management practices are applied uniformly. Our objectives were to define probability of revegetation success over space using relevant soil-related environmental factors, use this information to model cost of successful revegetation and compare the importance of vegetation competition and soil factors to revegetation success. We studied a burned Wyoming big sagebrush landscape in southeast Oregon that was reseeded with perennial grasses. We collected soil and vegetation data at plots spaced at 30 m intervals along a 1.5 km transect in the first two years post-burn. Plots were classified as successful (>5 seedlings/m(2)) or unsuccessful based on density of seeded species. Using logistic regression we found that abundance of competing vegetation correctly predicted revegetation success on 51 % of plots, and soil-related variables correctly predicted revegetation performance on 82.4 % of plots. Revegetation estimates varied from $167.06 to $43,033.94/ha across the 1.5 km transect based on probability of success, but were more homogenous at larger scales. Our experimental protocol provides managers with a technique to identify important environmental drivers of restoration success and this process will be of value for spatially allocating logistical and capital expenditures in a variable restoration environment.
Development and application of a most probable number-PCR assay to quantify flagellate populations in soil samples

DEFF Research Database (Denmark)

Fredslund, Line; Ekelund, Flemming; Jacobsen, Carsten Suhr

2001-01-01

This paper reports on the first successful molecular detection and quantification of soil protozoa. Quantification of heterotrophic flagellates and naked amoebae in soil has traditionally relied on dilution culturing techniques, followed by most-probable-number (MPN) calculations. Such methods...... are biased by differences in the culturability of soil protozoa and are unable to quantify specific taxonomic groups, and the results are highly dependent on the choice of media and the skills of the microscopists. Successful detection of protozoa in soil by DNA techniques requires (i) the development...
Maximum power demand cost

International Nuclear Information System (INIS)

Biondi, L.

1998-01-01

The charging for a service is a supplier's remuneration for the expenses incurred in providing it. There are currently two charges for electricity: consumption and maximum demand. While no problem arises about the former, the issue is more complicated for the latter and the analysis in this article tends to show that the annual charge for maximum demand arbitrarily discriminates among consumer groups, to the disadvantage of some [it
Impact of controlling the sum of error probability in the sequential probability ratio test

Directory of Open Access Journals (Sweden)

Bijoy Kumarr Pradhan

2013-05-01

Full Text Available A generalized modified method is proposed to control the sum of error probabilities in sequential probability ratio test to minimize the weighted average of the two average sample numbers under a simple null hypothesis and a simple alternative hypothesis with the restriction that the sum of error probabilities is a pre-assigned constant to find the optimal sample size and finally a comparison is done with the optimal sample size found from fixed sample size procedure. The results are applied to the cases when the random variate follows a normal law as well as Bernoullian law.
Vulnerability assessment: Determining probabilities of neutralization of adversaries

International Nuclear Information System (INIS)

Graves, B.R.

1987-01-01

The Security Manager charged with the responsibility of designing Safeguards and Security Systems at Department of Energy facilities must take many factors into consideration. There must be a clear understanding, supported by documented guidance, of the level of threat to be addressed; the nature of the facility to be protected, and the funds available to design, implement, and maintain the Safeguards and Security System. Armed with these prerequisites, the Security Manager may then determine the characteristics of the Safeguards measures and security forces necessary to protect the facility. Security forces selection and training programs may then be established based on realistic facility needs. The next step is to attempt to determine the probability of security forces winning in a confrontation with adversaries. To determine the probability of success the Security Manager must consider the characteristics of the facility and surrounding area; the characteristics of the security forces and safeguards system at the facility; the response time and capabilities of the augmentation forces and the characteristics and capabilities of the adversary threat level to be addressed. Obviously, the Safeguards and Security Systems must initially address ''worst case'' scenarios consistent with stated guidelines. Validation of the assessment of the Safeguards and Security Systems must then be determined by simulation testing of the capabilities of the response forces against the capabilities of the adversary
A short course on measure and probability theories

Energy Technology Data Exchange (ETDEWEB)

Pebay, Philippe Pierre

2004-02-01

This brief Introduction to Measure Theory, and its applications to Probabilities, corresponds to the lecture notes of a seminar series given at Sandia National Laboratories in Livermore, during the spring of 2003. The goal of these seminars was to provide a minimal background to Computational Combustion scientists interested in using more advanced stochastic concepts and methods, e.g., in the context of uncertainty quantification. Indeed, most mechanical engineering curricula do not provide students with formal training in the field of probability, and even in less in measure theory. However, stochastic methods have been used more and more extensively in the past decade, and have provided more successful computational tools. Scientists at the Combustion Research Facility of Sandia National Laboratories have been using computational stochastic methods for years. Addressing more and more complex applications, and facing difficult problems that arose in applications showed the need for a better understanding of theoretical foundations. This is why the seminar series was launched, and these notes summarize most of the concepts which have been discussed. The goal of the seminars was to bring a group of mechanical engineers and computational combustion scientists to a full understanding of N. WIENER'S polynomial chaos theory. Therefore, these lectures notes are built along those lines, and are not intended to be exhaustive. In particular, the author welcomes any comments or criticisms.
Upgrading Probability via Fractions of Events

Directory of Open Access Journals (Sweden)

Frič Roman

2016-08-01

Full Text Available The influence of “Grundbegriffe” by A. N. Kolmogorov (published in 1933 on education in the area of probability and its impact on research in stochastics cannot be overestimated. We would like to point out three aspects of the classical probability theory “calling for” an upgrade: (i classical random events are black-and-white (Boolean; (ii classical random variables do not model quantum phenomena; (iii basic maps (probability measures and observables { dual maps to random variables have very different “mathematical nature”. Accordingly, we propose an upgraded probability theory based on Łukasiewicz operations (multivalued logic on events, elementary category theory, and covering the classical probability theory as a special case. The upgrade can be compared to replacing calculations with integers by calculations with rational (and real numbers. Namely, to avoid the three objections, we embed the classical (Boolean random events (represented by the f0; 1g-valued indicator functions of sets into upgraded random events (represented by measurable {0; 1}-valued functions, the minimal domain of probability containing “fractions” of classical random events, and we upgrade the notions of probability measure and random variable.
A Comprehensive Probability Project for the Upper Division One-Semester Probability Course Using Yahtzee

Science.gov (United States)

Wilson, Jason; Lawman, Joshua; Murphy, Rachael; Nelson, Marissa

2011-01-01

This article describes a probability project used in an upper division, one-semester probability course with third-semester calculus and linear algebra prerequisites. The student learning outcome focused on developing the skills necessary for approaching project-sized math/stat application problems. These skills include appropriately defining…

Estimating the chance of success in IVF treatment using a ranking algorithm.

Science.gov (United States)

Güvenir, H Altay; Misirli, Gizem; Dilbaz, Serdar; Ozdegirmenci, Ozlem; Demir, Berfu; Dilbaz, Berna

2015-09-01

In medicine, estimating the chance of success for treatment is important in deciding whether to begin the treatment or not. This paper focuses on the domain of in vitro fertilization (IVF), where estimating the outcome of a treatment is very crucial in the decision to proceed with treatment for both the clinicians and the infertile couples. IVF treatment is a stressful and costly process. It is very stressful for couples who want to have a baby. If an initial evaluation indicates a low pregnancy rate, decision of the couple may change not to start the IVF treatment. The aim of this study is twofold, firstly, to develop a technique that can be used to estimate the chance of success for a couple who wants to have a baby and secondly, to determine the attributes and their particular values affecting the outcome in IVF treatment. We propose a new technique, called success estimation using a ranking algorithm (SERA), for estimating the success of a treatment using a ranking-based algorithm. The particular ranking algorithm used here is RIMARC. The performance of the new algorithm is compared with two well-known algorithms that assign class probabilities to query instances. The algorithms used in the comparison are Naïve Bayes Classifier and Random Forest. The comparison is done in terms of area under the ROC curve, accuracy and execution time, using tenfold stratified cross-validation. The results indicate that the proposed SERA algorithm has a potential to be used successfully to estimate the probability of success in medical treatment.
Comparison of Extremum-Seeking Control Techniques for Maximum Power Point Tracking in Photovoltaic Systems

Directory of Open Access Journals (Sweden)

Chen-Han Wu

2011-12-01

Full Text Available Due to Japan’s recent nuclear crisis and petroleum price hikes, the search for renewable energy sources has become an issue of immediate concern. A promising candidate attracting much global attention is solar energy, as it is green and also inexhaustible. A maximum power point tracking (MPPT controller is employed in such a way that the output power provided by a photovoltaic (PV system is boosted to its maximum level. However, in the context of abrupt changes in irradiance, conventional MPPT controller approaches suffer from insufficient robustness against ambient variation, inferior transient response and a loss of output power as a consequence of the long duration required of tracking procedures. Accordingly, in this work the maximum power point tracking is carried out successfully using a sliding mode extremum-seeking control (SMESC method, and the tracking performances of three controllers are compared by simulations, that is, an extremum-seeking controller, a sinusoidal extremum-seeking controller and a sliding mode extremum-seeking controller. Being able to track the maximum power point promptly in the case of an abrupt change in irradiance, the SMESC approach is proven by simulations to be superior in terms of system dynamic and steady state responses, and an excellent robustness along with system stability is demonstrated as well.
Is probability of frequency too narrow?

International Nuclear Information System (INIS)

Martz, H.F.

1993-01-01

Modern methods of statistical data analysis, such as empirical and hierarchical Bayesian methods, should find increasing use in future Probabilistic Risk Assessment (PRA) applications. In addition, there will be a more formalized use of expert judgment in future PRAs. These methods require an extension of the probabilistic framework of PRA, in particular, the popular notion of probability of frequency, to consideration of frequency of frequency, frequency of probability, and probability of probability. The genesis, interpretation, and examples of these three extended notions are discussed
An Alternative Version of Conditional Probabilities and Bayes' Rule: An Application of Probability Logic

Science.gov (United States)

Satake, Eiki; Amato, Philip P.

2008-01-01

This paper presents an alternative version of formulas of conditional probabilities and Bayes' rule that demonstrate how the truth table of elementary mathematical logic applies to the derivations of the conditional probabilities of various complex, compound statements. This new approach is used to calculate the prior and posterior probabilities…
Normal probability plots with confidence.

Science.gov (United States)

Chantarangsi, Wanpen; Liu, Wei; Bretz, Frank; Kiatsupaibul, Seksan; Hayter, Anthony J; Wan, Fang

2015-01-01

Normal probability plots are widely used as a statistical tool for assessing whether an observed simple random sample is drawn from a normally distributed population. The users, however, have to judge subjectively, if no objective rule is provided, whether the plotted points fall close to a straight line. In this paper, we focus on how a normal probability plot can be augmented by intervals for all the points so that, if the population distribution is normal, then all the points should fall into the corresponding intervals simultaneously with probability 1-α. These simultaneous 1-α probability intervals provide therefore an objective mean to judge whether the plotted points fall close to the straight line: the plotted points fall close to the straight line if and only if all the points fall into the corresponding intervals. The powers of several normal probability plot based (graphical) tests and the most popular nongraphical Anderson-Darling and Shapiro-Wilk tests are compared by simulation. Based on this comparison, recommendations are given in Section 3 on which graphical tests should be used in what circumstances. An example is provided to illustrate the methods. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Simulation model of ANN based maximum power point tracking controller for solar PV system

Energy Technology Data Exchange (ETDEWEB)

Rai, Anil K.; Singh, Bhupal [Department of Electrical and Electronics Engineering, Ajay Kumar Garg Engineering College, Ghaziabad 201009 (India); Kaushika, N.D.; Agarwal, Niti [School of Research and Development, Bharati Vidyapeeth College of Engineering, A-4 Paschim Vihar, New Delhi 110063 (India)

2011-02-15

In this paper the simulation model of an artificial neural network (ANN) based maximum power point tracking controller has been developed. The controller consists of an ANN tracker and the optimal control unit. The ANN tracker estimates the voltages and currents corresponding to a maximum power delivered by solar PV (photovoltaic) array for variable cell temperature and solar radiation. The cell temperature is considered as a function of ambient air temperature, wind speed and solar radiation. The tracker is trained employing a set of 124 patterns using the back propagation algorithm. The mean square error of tracker output and target values is set to be of the order of 10{sup -5} and the successful convergent of learning process takes 1281 epochs. The accuracy of the ANN tracker has been validated by employing different test data sets. The control unit uses the estimates of the ANN tracker to adjust the duty cycle of the chopper to optimum value needed for maximum power transfer to the specified load. (author)
Free probability and random matrices

CERN Document Server

Mingo, James A

2017-01-01

This volume opens the world of free probability to a wide variety of readers. From its roots in the theory of operator algebras, free probability has intertwined with non-crossing partitions, random matrices, applications in wireless communications, representation theory of large groups, quantum groups, the invariant subspace problem, large deviations, subfactors, and beyond. This book puts a special emphasis on the relation of free probability to random matrices, but also touches upon the operator algebraic, combinatorial, and analytic aspects of the theory. The book serves as a combination textbook/research monograph, with self-contained chapters, exercises scattered throughout the text, and coverage of important ongoing progress of the theory. It will appeal to graduate students and all mathematicians interested in random matrices and free probability from the point of view of operator algebras, combinatorics, analytic functions, or applications in engineering and statistical physics.
Long-Term Fatigue and Its Probability of Failure Applied to Dental Implants

Directory of Open Access Journals (Sweden)

María Prados-Privado

2016-01-01

Full Text Available It is well known that dental implants have a high success rate but even so, there are a lot of factors that can cause dental implants failure. Fatigue is very sensitive to many variables involved in this phenomenon. This paper takes a close look at fatigue analysis and explains a new method to study fatigue from a probabilistic point of view, based on a cumulative damage model and probabilistic finite elements, with the goal of obtaining the expected life and the probability of failure. Two different dental implants were analysed. The model simulated a load of 178 N applied with an angle of 0°, 15°, and 20° and a force of 489 N with the same angles. Von Mises stress distribution was evaluated and once the methodology proposed here was used, the statistic of the fatigue life and the probability cumulative function were obtained. This function allows us to relate each cycle life with its probability of failure. Cylindrical implant has a worst behaviour under the same loading force compared to the conical implant analysed here. Methodology employed in the present study provides very accuracy results because all possible uncertainties have been taken in mind from the beginning.
Probability with applications and R

CERN Document Server

Dobrow, Robert P

2013-01-01

An introduction to probability at the undergraduate level Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability. With real-life examples and thoughtful exercises from fields as diverse as biology, computer science, cryptology, ecology, public health, and sports, the book is accessible for a variety of readers. The book's emphasis on simulation through the use of the popular R software language c
A philosophical essay on probabilities

CERN Document Server

Laplace, Marquis de

1996-01-01

A classic of science, this famous essay by ""the Newton of France"" introduces lay readers to the concepts and uses of probability theory. It is of especial interest today as an application of mathematical techniques to problems in social and biological sciences.Generally recognized as the founder of the modern phase of probability theory, Laplace here applies the principles and general results of his theory ""to the most important questions of life, which are, in effect, for the most part, problems in probability."" Thus, without the use of higher mathematics, he demonstrates the application
Precipitation intensity probability distribution modelling for hydrological and construction design purposes

International Nuclear Information System (INIS)

Koshinchanov, Georgy; Dimitrov, Dobri

2008-01-01

The characteristics of rainfall intensity are important for many purposes, including design of sewage and drainage systems, tuning flood warning procedures, etc. Those estimates are usually statistical estimates of the intensity of precipitation realized for certain period of time (e.g. 5, 10 min., etc) with different return period (e.g. 20, 100 years, etc). The traditional approach in evaluating the mentioned precipitation intensities is to process the pluviometer's records and fit probability distribution to samples of intensities valid for certain locations ore regions. Those estimates further become part of the state regulations to be used for various economic activities. Two problems occur using the mentioned approach: 1. Due to various factors the climate conditions are changed and the precipitation intensity estimates need regular update; 2. As far as the extremes of the probability distribution are of particular importance for the practice, the methodology of the distribution fitting needs specific attention to those parts of the distribution. The aim of this paper is to make review of the existing methodologies for processing the intensive rainfalls and to refresh some of the statistical estimates for the studied areas. The methodologies used in Bulgaria for analyzing the intensive rainfalls and produce relevant statistical estimates: - The method of the maximum intensity, used in the National Institute of Meteorology and Hydrology to process and decode the pluviometer's records, followed by distribution fitting for each precipitation duration period; - As the above, but with separate modeling of probability distribution for the middle and high probability quantiles. - Method is similar to the first one, but with a threshold of 0,36 mm/min of intensity; - Another method proposed by the Russian hydrologist G. A. Aleksiev for regionalization of estimates over some territory, improved and adapted by S. Gerasimov for Bulgaria; - Next method is considering only
Maximum spreading of liquid drop on various substrates with different wettabilities

Science.gov (United States)

Choudhury, Raihan; Choi, Junho; Yang, Sangsun; Kim, Yong-Jin; Lee, Donggeun

2017-09-01

This paper describes a novel model developed for a priori prediction of the maximal spread of a liquid drop on a surface. As a first step, a series of experiments were conducted under precise control of the initial drop diameter, its falling height, roughness, and wettability of dry surfaces. The transient liquid spreading was recorded by a high-speed camera to obtain its maximum spreading under various conditions. Eight preexisting models were tested for accurate prediction of the maximum spread; however, most of the model predictions were not satisfactory except one, in comparison with our experimental data. A comparative scaling analysis of the literature models was conducted to elucidate the condition-dependent prediction characteristics of the models. The conditioned bias in the predictions was mainly attributed to the inappropriate formulations of viscous dissipation or interfacial energy of liquid on the surface. Hence, a novel model based on energy balance during liquid impact was developed to overcome the limitations of the previous models. As a result, the present model was quite successful in predicting the liquid spread in all the conditions.
Comparative evaluation of the efficacy of occlusal splints fabricated in centric relation or maximum intercuspation in temporomandibular disorders patients

Directory of Open Access Journals (Sweden)

Marcelo Matida Hamata

2009-02-01

Full Text Available Fabrication of occlusal splints in centric relation for temporomandibular disorders (TMD patients is arguable, since this position has been defined for asymptomatic stomatognathic system. Thus, maximum intercuspation might be employed in patients with occlusal stability, eliminating the need for interocclusal records. This study compared occlusal splints fabricated in centric relation and maximum intercuspation in muscle pain reduction of TMD patients. Twenty patients with TMD of myogenous origin and bruxism were divided into 2 groups treated with splints in maximum intercuspation (I or centric relation (II. Clinical, electrognathographic and electromyographic examinations were performed before and 3 months after therapy. Data were analyzed by the Student's t test. Differences at 5% level of probability were considered statistically significant. There was a remarkable reduction in pain symptomatology, without statistically significant differences (p>0.05 between the groups. There was mandibular repositioning during therapy, as demonstrated by the change in occlusal contacts on the splints. Electrognathographic examination demonstrated a significant increase in maximum left lateral movement for group I and right lateral movement for group II (p0.05 in the electromyographic activities at rest after utilization of both splints. In conclusion, both occlusal splints were effective for pain control and presented similar action. The results suggest that maximum intercuspation may be used for fabrication of occlusal splints in patients with occlusal stability without large discrepancies between centric relation and maximum intercuspation. Moreover, this technique is simpler and less expensive.
Comparative evaluation of the efficacy of occlusal splints fabricated in centric relation or maximum intercuspation in temporomandibular disorders patients.

Science.gov (United States)

Hamata, Marcelo Matida; Zuim, Paulo Renato Junqueira; Garcia, Alicio Rosalino

2009-01-01

Fabrication of occlusal splints in centric relation for temporomandibular disorders (TMD) patients is arguable, since this position has been defined for asymptomatic stomatognathic system. Thus, maximum intercuspation might be employed in patients with occlusal stability, eliminating the need for interocclusal records. This study compared occlusal splints fabricated in centric relation and maximum intercuspation in muscle pain reduction of TMD patients. Twenty patients with TMD of myogenous origin and bruxism were divided into 2 groups treated with splints in maximum intercuspation (I) or centric relation (II). Clinical, electrognathographic and electromyographic examinations were performed before and 3 months after therapy. Data were analyzed by the Student's t test. Differences at 5% level of probability were considered statistically significant. There was a remarkable reduction in pain symptomatology, without statistically significant differences (p>0.05) between the groups. There was mandibular repositioning during therapy, as demonstrated by the change in occlusal contacts on the splints. Electrognathographic examination demonstrated a significant increase in maximum left lateral movement for group I and right lateral movement for group II (p0.05) in the electromyographic activities at rest after utilization of both splints. In conclusion, both occlusal splints were effective for pain control and presented similar action. The results suggest that maximum intercuspation may be used for fabrication of occlusal splints in patients with occlusal stability without large discrepancies between centric relation and maximum intercuspation. Moreover, this technique is simpler and less expensive.
Alternative probability theories for cognitive psychology.

Science.gov (United States)

Narens, Louis

2014-01-01

Various proposals for generalizing event spaces for probability functions have been put forth in the mathematical, scientific, and philosophic literatures. In cognitive psychology such generalizations are used for explaining puzzling results in decision theory and for modeling the influence of context effects. This commentary discusses proposals for generalizing probability theory to event spaces that are not necessarily boolean algebras. Two prominent examples are quantum probability theory, which is based on the set of closed subspaces of a Hilbert space, and topological probability theory, which is based on the set of open sets of a topology. Both have been applied to a variety of cognitive situations. This commentary focuses on how event space properties can influence probability concepts and impact cognitive modeling. Copyright © 2013 Cognitive Science Society, Inc.
Live attenuated vaccines: Historical successes and current challenges

Energy Technology Data Exchange (ETDEWEB)

Minor, Philip D., E-mail: Philip.Minor@nibsc.org

2015-05-15

Live attenuated vaccines against human viral diseases have been amongst the most successful cost effective interventions in medical history. Smallpox was declared eradicated in 1980; poliomyelitis is nearing global eradication and measles has been controlled in most parts of the world. Vaccines function well for acute diseases such as these but chronic infections such as HIV are more challenging for reasons of both likely safety and probable efficacy. The derivation of the vaccines used has in general not been purely rational except in the sense that it has involved careful clinical trials of candidates and subsequent careful follow up in clinical use; the identification of the candidates is reviewed. - Highlights: • Live vaccines against human diseases caused by viruses have been very successful. • They have been developed by empirical clinical studies and problems identified in later use. • It can be difficult to balance ability to cause disease and ability to immunise for a strain. • There is currently no reliable basis for predicting success from pure virological studies. • Vaccinia, which eradicated smallpox, is the paradigm for all successes and issues.
Live attenuated vaccines: Historical successes and current challenges

International Nuclear Information System (INIS)

Minor, Philip D.

2015-01-01

Live attenuated vaccines against human viral diseases have been amongst the most successful cost effective interventions in medical history. Smallpox was declared eradicated in 1980; poliomyelitis is nearing global eradication and measles has been controlled in most parts of the world. Vaccines function well for acute diseases such as these but chronic infections such as HIV are more challenging for reasons of both likely safety and probable efficacy. The derivation of the vaccines used has in general not been purely rational except in the sense that it has involved careful clinical trials of candidates and subsequent careful follow up in clinical use; the identification of the candidates is reviewed. - Highlights: • Live vaccines against human diseases caused by viruses have been very successful. • They have been developed by empirical clinical studies and problems identified in later use. • It can be difficult to balance ability to cause disease and ability to immunise for a strain. • There is currently no reliable basis for predicting success from pure virological studies. • Vaccinia, which eradicated smallpox, is the paradigm for all successes and issues
Probability theory and mathematical statistics for engineers

CERN Document Server

Pugachev, V S

1984-01-01

Probability Theory and Mathematical Statistics for Engineers focuses on the concepts of probability theory and mathematical statistics for finite-dimensional random variables.The publication first underscores the probabilities of events, random variables, and numerical characteristics of random variables. Discussions focus on canonical expansions of random vectors, second-order moments of random vectors, generalization of the density concept, entropy of a distribution, direct evaluation of probabilities, and conditional probabilities. The text then examines projections of random vector
Introduction to probability theory with contemporary applications

CERN Document Server

Helms, Lester L

2010-01-01

This introduction to probability theory transforms a highly abstract subject into a series of coherent concepts. Its extensive discussions and clear examples, written in plain language, expose students to the rules and methods of probability. Suitable for an introductory probability course, this volume requires abstract and conceptual thinking skills and a background in calculus.Topics include classical probability, set theory, axioms, probability functions, random and independent random variables, expected values, and covariance and correlations. Additional subjects include stochastic process
Probability in quantum mechanics

Directory of Open Access Journals (Sweden)

J. G. Gilson

1982-01-01

Full Text Available By using a fluid theory which is an alternative to quantum theory but from which the latter can be deduced exactly, the long-standing problem of how quantum mechanics is related to stochastic processes is studied. It can be seen how the Schrödinger probability density has a relationship to time spent on small sections of an orbit, just as the probability density has in some classical contexts.

Pre-Service Teachers' Conceptions of Probability

Science.gov (United States)

Odafe, Victor U.

2011-01-01

Probability knowledge and skills are needed in science and in making daily decisions that are sometimes made under uncertain conditions. Hence, there is the need to ensure that the pre-service teachers of our children are well prepared to teach probability. Pre-service teachers' conceptions of probability are identified, and ways of helping them…
Nuclear data uncertainties: I, Basic concepts of probability

Energy Technology Data Exchange (ETDEWEB)

Smith, D.L.

1988-12-01

Some basic concepts of probability theory are presented from a nuclear-data perspective, in order to provide a foundation for thorough understanding of the role of uncertainties in nuclear data research. Topics included in this report are: events, event spaces, calculus of events, randomness, random variables, random-variable distributions, intuitive and axiomatic probability, calculus of probability, conditional probability and independence, probability distributions, binomial and multinomial probability, Poisson and interval probability, normal probability, the relationships existing between these probability laws, and Bayes' theorem. This treatment emphasizes the practical application of basic mathematical concepts to nuclear data research, and it includes numerous simple examples. 34 refs.
Nuclear data uncertainties: I, Basic concepts of probability

International Nuclear Information System (INIS)

Smith, D.L.

1988-12-01

Some basic concepts of probability theory are presented from a nuclear-data perspective, in order to provide a foundation for thorough understanding of the role of uncertainties in nuclear data research. Topics included in this report are: events, event spaces, calculus of events, randomness, random variables, random-variable distributions, intuitive and axiomatic probability, calculus of probability, conditional probability and independence, probability distributions, binomial and multinomial probability, Poisson and interval probability, normal probability, the relationships existing between these probability laws, and Bayes' theorem. This treatment emphasizes the practical application of basic mathematical concepts to nuclear data research, and it includes numerous simple examples. 34 refs
Exploiting Outage and Error Probability of Cooperative Incremental Relaying in Underwater Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Hina Nasir

2016-07-01

Full Text Available This paper embeds a bi-fold contribution for Underwater Wireless Sensor Networks (UWSNs; performance analysis of incremental relaying in terms of outage and error probability, and based on the analysis proposition of two new cooperative routing protocols. Subject to the first contribution, a three step procedure is carried out; a system model is presented, the number of available relays are determined, and based on cooperative incremental retransmission methodology, closed-form expressions for outage and error probability are derived. Subject to the second contribution, Adaptive Cooperation in Energy (ACE efficient depth based routing and Enhanced-ACE (E-ACE are presented. In the proposed model, feedback mechanism indicates success or failure of data transmission. If direct transmission is successful, there is no need for relaying by cooperative relay nodes. In case of failure, all the available relays retransmit the data one by one till the desired signal quality is achieved at destination. Simulation results show that the ACE and E-ACE significantly improves network performance, i.e., throughput, when compared with other incremental relaying protocols like Cooperative Automatic Repeat reQuest (CARQ. E-ACE and ACE achieve 69% and 63% more throughput respectively as compared to CARQ in hard underwater environment.
Economic choices reveal probability distortion in macaque monkeys.

Science.gov (United States)

Stauffer, William R; Lak, Armin; Bossaerts, Peter; Schultz, Wolfram

2015-02-18

Economic choices are largely determined by two principal elements, reward value (utility) and probability. Although nonlinear utility functions have been acknowledged for centuries, nonlinear probability weighting (probability distortion) was only recently recognized as a ubiquitous aspect of real-world choice behavior. Even when outcome probabilities are known and acknowledged, human decision makers often overweight low probability outcomes and underweight high probability outcomes. Whereas recent studies measured utility functions and their corresponding neural correlates in monkeys, it is not known whether monkeys distort probability in a manner similar to humans. Therefore, we investigated economic choices in macaque monkeys for evidence of probability distortion. We trained two monkeys to predict reward from probabilistic gambles with constant outcome values (0.5 ml or nothing). The probability of winning was conveyed using explicit visual cues (sector stimuli). Choices between the gambles revealed that the monkeys used the explicit probability information to make meaningful decisions. Using these cues, we measured probability distortion from choices between the gambles and safe rewards. Parametric modeling of the choices revealed classic probability weighting functions with inverted-S shape. Therefore, the animals overweighted low probability rewards and underweighted high probability rewards. Empirical investigation of the behavior verified that the choices were best explained by a combination of nonlinear value and nonlinear probability distortion. Together, these results suggest that probability distortion may reflect evolutionarily preserved neuronal processing. Copyright © 2015 Stauffer et al.
Maximum entropy estimation of a Benzene contaminated plume using ecotoxicological assays

International Nuclear Information System (INIS)

Wahyudi, Agung; Bartzke, Mariana; Küster, Eberhard; Bogaert, Patrick

2013-01-01

Ecotoxicological bioassays, e.g. based on Danio rerio teratogenicity (DarT) or the acute luminescence inhibition with Vibrio fischeri, could potentially lead to significant benefits for detecting on site contaminations on qualitative or semi-quantitative bases. The aim was to use the observed effects of two ecotoxicological assays for estimating the extent of a Benzene groundwater contamination plume. We used a Maximum Entropy (MaxEnt) method to rebuild a bivariate probability table that links the observed toxicity from the bioassays with Benzene concentrations. Compared with direct mapping of the contamination plume as obtained from groundwater samples, the MaxEnt concentration map exhibits on average slightly higher concentrations though the global pattern is close to it. This suggest MaxEnt is a valuable method to build a relationship between quantitative data, e.g. contaminant concentrations, and more qualitative or indirect measurements, in a spatial mapping framework, which is especially useful when clear quantitative relation is not at hand. - Highlights: ► Ecotoxicological shows significant benefits for detecting on site contaminations. ► MaxEnt to rebuild qualitative link on concentration and ecotoxicological assays. ► MaxEnt shows similar pattern when compared with concentrations map of groundwater. ► MaxEnt is a valuable method especially when quantitative relation is not at hand. - A Maximum Entropy method to rebuild qualitative relationships between Benzene groundwater concentrations and their ecotoxicological effect.
Identifying attendance patterns in a smoking cessation treatment and their relationships with quit success.

Science.gov (United States)

Jacquart, Jolene; Papini, Santiago; Davis, Michelle L; Rosenfield, David; Powers, Mark B; Frierson, Georita M; Hopkins, Lindsey B; Baird, Scarlett O; Marcus, Bess H; Church, Timothy S; Otto, Michael W; Zvolensky, Michael J; Smits, Jasper A J

2017-05-01

While important for substance use outcomes, knowledge about treatment attendance patterns, and their relation with clinical outcomes is limited. We examined the association between attendance patterns and smoking outcomes in a randomized, controlled smoking cessation intervention trial. In addition to standard smoking cessation treatment, participants were randomized to 15 weeks of an exercise intervention (n=72) or an education control condition (n=64). Latent class growth analysis (LCGA) tested whether intervention attendance would be better modeled as qualitatively distinct attendance patterns rather than as a single mean pattern. Multivariate generalized linear mixed modeling (GLMM) was used to evaluate associations between the attendance patterns and abstinence at the end of treatment and at 6-month follow-up. The LCGA solution with three patterns characterized by high probability of attendance throughout (Completers, 46.3%), gradual decreasing probability of attendance (Titrators, 23.5%), and high probability of dropout within the first few weeks (Droppers, 30.1%) provided the best fit. The GLMM analysis indicated an interaction of attendance pattern by treatment condition, such that titration was associated with lower probability of quit success for those in the control condition. Probability of quit success was not significantly different between Titrators and Completers in the exercise condition. These findings underscore the importance of examining how treatment efficacy may vary as a function of attendance patterns. Importantly, treatment discontinuation is not necessarily indicative of poorer abstinence outcome. Copyright © 2017 Elsevier B.V. All rights reserved.
49 CFR 230.24 - Maximum allowable stress.

Science.gov (United States)

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Maximum allowable stress. 230.24 Section 230.24... Allowable Stress § 230.24 Maximum allowable stress. (a) Maximum allowable stress value. The maximum allowable stress value on any component of a steam locomotive boiler shall not exceed 1/4 of the ultimate...
SU-E-T-144: Bayesian Inference of Local Relapse Data Using a Poisson-Based Tumour Control Probability Model

Energy Technology Data Exchange (ETDEWEB)

La Russa, D [The Ottawa Hospital Cancer Centre, Ottawa, ON (Canada)

2015-06-15

Purpose: The purpose of this project is to develop a robust method of parameter estimation for a Poisson-based TCP model using Bayesian inference. Methods: Bayesian inference was performed using the PyMC3 probabilistic programming framework written in Python. A Poisson-based TCP regression model that accounts for clonogen proliferation was fit to observed rates of local relapse as a function of equivalent dose in 2 Gy fractions for a population of 623 stage-I non-small-cell lung cancer patients. The Slice Markov Chain Monte Carlo sampling algorithm was used to sample the posterior distributions, and was initiated using the maximum of the posterior distributions found by optimization. The calculation of TCP with each sample step required integration over the free parameter α, which was performed using an adaptive 24-point Gauss-Legendre quadrature. Convergence was verified via inspection of the trace plot and posterior distribution for each of the fit parameters, as well as with comparisons of the most probable parameter values with their respective maximum likelihood estimates. Results: Posterior distributions for α, the standard deviation of α (σ), the average tumour cell-doubling time (Td), and the repopulation delay time (Tk), were generated assuming α/β = 10 Gy, and a fixed clonogen density of 10{sup 7} cm−{sup 3}. Posterior predictive plots generated from samples from these posterior distributions are in excellent agreement with the observed rates of local relapse used in the Bayesian inference. The most probable values of the model parameters also agree well with maximum likelihood estimates. Conclusion: A robust method of performing Bayesian inference of TCP data using a complex TCP model has been established.
Expected utility with lower probabilities

DEFF Research Database (Denmark)

Hendon, Ebbe; Jacobsen, Hans Jørgen; Sloth, Birgitte

1994-01-01

An uncertain and not just risky situation may be modeled using so-called belief functions assigning lower probabilities to subsets of outcomes. In this article we extend the von Neumann-Morgenstern expected utility theory from probability measures to belief functions. We use this theory...
Identifying critical constraints for the maximum loadability of electric power systems - analysis via interior point method

Energy Technology Data Exchange (ETDEWEB)

Barboza, Luciano Vitoria [Sul-riograndense Federal Institute for Education, Science and Technology (IFSul), Pelotas, RS (Brazil)], E-mail: luciano@pelotas.ifsul.edu.br

2009-07-01

This paper presents an overview about the maximum load ability problem and aims to study the main factors that limit this load ability. Specifically this study focuses its attention on determining which electric system buses influence directly on the power demand supply. The proposed approach uses the conventional maximum load ability method modelled by an optimization problem. The solution of this model is performed using the Interior Point methodology. As consequence of this solution method, the Lagrange multipliers are used as parameters that identify the probable 'bottlenecks' in the electric power system. The study also shows the relationship between the Lagrange multipliers and the cost function in the Interior Point optimization interpreted like sensitivity parameters. In order to illustrate the proposed methodology, the approach was applied to an IEEE test system and to assess its performance, a real equivalent electric system from the South- Southeast region of Brazil was simulated. (author)
Estimation of occupancy, breeding success, and predicted abundance of golden eagles (Aquila chrysaetos) in the Diablo Range, California, 2014

Science.gov (United States)

Wiens, J. David; Kolar, Patrick S.; Fuller, Mark R.; Hunt, W. Grainger; Hunt, Teresa

2015-01-01

We used a multistate occupancy sampling design to estimate occupancy, breeding success, and abundance of territorial pairs of golden eagles (Aquila chrysaetos) in the Diablo Range, California, in 2014. This method uses the spatial pattern of detections and non-detections over repeated visits to survey sites to estimate probabilities of occupancy and successful reproduction while accounting for imperfect detection of golden eagles and their young during surveys. The estimated probability of detecting territorial pairs of golden eagles and their young was less than 1 and varied with time of the breeding season, as did the probability of correctly classifying a pair’s breeding status. Imperfect detection and breeding classification led to a sizeable difference between the uncorrected, naïve estimate of the proportion of occupied sites where successful reproduction was observed (0.20) and the model-based estimate (0.30). The analysis further indicated a relatively high overall probability of landscape occupancy by pairs of golden eagles (0.67, standard error = 0.06), but that areas with the greatest occupancy and reproductive potential were patchily distributed. We documented a total of 138 territorial pairs of golden eagles during surveys completed in the 2014 breeding season, which represented about one-half of the 280 pairs we estimated to occur in the broader 5,169-square kilometer region sampled. The study results emphasize the importance of accounting for imperfect detection and spatial heterogeneity in studies of site occupancy, breeding success, and abundance of golden eagles.
Audio feature extraction using probability distribution function

Science.gov (United States)

Suhaib, A.; Wan, Khairunizam; Aziz, Azri A.; Hazry, D.; Razlan, Zuradzman M.; Shahriman A., B.

2015-05-01

Voice recognition has been one of the popular applications in robotic field. It is also known to be recently used for biometric and multimedia information retrieval system. This technology is attained from successive research on audio feature extraction analysis. Probability Distribution Function (PDF) is a statistical method which is usually used as one of the processes in complex feature extraction methods such as GMM and PCA. In this paper, a new method for audio feature extraction is proposed which is by using only PDF as a feature extraction method itself for speech analysis purpose. Certain pre-processing techniques are performed in prior to the proposed feature extraction method. Subsequently, the PDF result values for each frame of sampled voice signals obtained from certain numbers of individuals are plotted. From the experimental results obtained, it can be seen visually from the plotted data that each individuals' voice has comparable PDF values and shapes.
Striatal activity is modulated by target probability.

Science.gov (United States)

Hon, Nicholas

2017-06-14

Target probability has well-known neural effects. In the brain, target probability is known to affect frontal activity, with lower probability targets producing more prefrontal activation than those that occur with higher probability. Although the effect of target probability on cortical activity is well specified, its effect on subcortical structures such as the striatum is less well understood. Here, I examined this issue and found that the striatum was highly responsive to target probability. This is consistent with its hypothesized role in the gating of salient information into higher-order task representations. The current data are interpreted in light of that fact that different components of the striatum are sensitive to different types of task-relevant information.
Failure probability analysis of optical grid

Science.gov (United States)

Zhong, Yaoquan; Guo, Wei; Sun, Weiqiang; Jin, Yaohui; Hu, Weisheng

2008-11-01

Optical grid, the integrated computing environment based on optical network, is expected to be an efficient infrastructure to support advanced data-intensive grid applications. In optical grid, the faults of both computational and network resources are inevitable due to the large scale and high complexity of the system. With the optical network based distributed computing systems extensive applied in the processing of data, the requirement of the application failure probability have been an important indicator of the quality of application and an important aspect the operators consider. This paper will present a task-based analysis method of the application failure probability in optical grid. Then the failure probability of the entire application can be quantified, and the performance of reducing application failure probability in different backup strategies can be compared, so that the different requirements of different clients can be satisfied according to the application failure probability respectively. In optical grid, when the application based DAG (directed acyclic graph) is executed in different backup strategies, the application failure probability and the application complete time is different. This paper will propose new multi-objective differentiated services algorithm (MDSA). New application scheduling algorithm can guarantee the requirement of the failure probability and improve the network resource utilization, realize a compromise between the network operator and the application submission. Then differentiated services can be achieved in optical grid.
A maximum power point tracking for photovoltaic-SPE system using a maximum current controller

Energy Technology Data Exchange (ETDEWEB)

Muhida, Riza [Osaka Univ., Dept. of Physical Science, Toyonaka, Osaka (Japan); Osaka Univ., Dept. of Electrical Engineering, Suita, Osaka (Japan); Park, Minwon; Dakkak, Mohammed; Matsuura, Kenji [Osaka Univ., Dept. of Electrical Engineering, Suita, Osaka (Japan); Tsuyoshi, Akira; Michira, Masakazu [Kobe City College of Technology, Nishi-ku, Kobe (Japan)

2003-02-01

Processes to produce hydrogen from solar photovoltaic (PV)-powered water electrolysis using solid polymer electrolysis (SPE) are reported. An alternative control of maximum power point tracking (MPPT) in the PV-SPE system based on the maximum current searching methods has been designed and implemented. Based on the characteristics of voltage-current and theoretical analysis of SPE, it can be shown that the tracking of the maximum current output of DC-DC converter in SPE side will track the MPPT of photovoltaic panel simultaneously. This method uses a proportional integrator controller to control the duty factor of DC-DC converter with pulse-width modulator (PWM). The MPPT performance and hydrogen production performance of this method have been evaluated and discussed based on the results of the experiment. (Author)
Ecological succession as an energy dispersal process.

Science.gov (United States)

Würtz, Peter; Annila, Arto

2010-04-01

Ecological succession is described by the 2nd law of thermodynamics. According to the universal law of the maximal energy dispersal, an ecosystem evolves toward a stationary state in its surroundings by consuming free energy via diverse mechanisms. Species are the mechanisms that conduct energy down along gradients between repositories of energy which consist of populations at various thermodynamic levels. The salient characteristics of succession, growing biomass production, increasing species richness and shifting distributions of species are found as consequences of the universal quest to diminish energy density differences in least time. The analysis reveals that during succession the ecosystem's energy transduction network, i.e., the food web organizes increasingly more effective in the free energy reduction by acquiring new, more effective and abandoning old, less effective species of energy transduction. The number of species does not necessarily peak at the climax state that corresponds to the maximum-entropy partition of species maximizing consumption of free energy. According to the theory of evolution by natural selection founded on statistical physics of open systems, ecological succession is one among many other evolutionary processes. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.
An Objective Theory of Probability (Routledge Revivals)

CERN Document Server

Gillies, Donald

2012-01-01

This reissue of D. A. Gillies highly influential work, first published in 1973, is a philosophical theory of probability which seeks to develop von Mises' views on the subject. In agreement with von Mises, the author regards probability theory as a mathematical science like mechanics or electrodynamics, and probability as an objective, measurable concept like force, mass or charge. On the other hand, Dr Gillies rejects von Mises' definition of probability in terms of limiting frequency and claims that probability should be taken as a primitive or undefined term in accordance with modern axioma
Fundamentals of applied probability and random processes

CERN Document Server

Ibe, Oliver

2014-01-01

The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability t
Defining Probability in Sex Offender Risk Assessment.

Science.gov (United States)

Elwood, Richard W

2016-12-01

There is ongoing debate and confusion over using actuarial scales to predict individuals' risk of sexual recidivism. Much of the debate comes from not distinguishing Frequentist from Bayesian definitions of probability. Much of the confusion comes from applying Frequentist probability to individuals' risk. By definition, only Bayesian probability can be applied to the single case. The Bayesian concept of probability resolves most of the confusion and much of the debate in sex offender risk assessment. Although Bayesian probability is well accepted in risk assessment generally, it has not been widely used to assess the risk of sex offenders. I review the two concepts of probability and show how the Bayesian view alone provides a coherent scheme to conceptualize individuals' risk of sexual recidivism.

UT Biomedical Informatics Lab (BMIL) probability wheel

Science.gov (United States)

Huang, Sheng-Cheng; Lee, Sara; Wang, Allen; Cantor, Scott B.; Sun, Clement; Fan, Kaili; Reece, Gregory P.; Kim, Min Soon; Markey, Mia K.

A probability wheel app is intended to facilitate communication between two people, an "investigator" and a "participant", about uncertainties inherent in decision-making. Traditionally, a probability wheel is a mechanical prop with two colored slices. A user adjusts the sizes of the slices to indicate the relative value of the probabilities assigned to them. A probability wheel can improve the adjustment process and attenuate the effect of anchoring bias when it is used to estimate or communicate probabilities of outcomes. The goal of this work was to develop a mobile application of the probability wheel that is portable, easily available, and more versatile. We provide a motivating example from medical decision-making, but the tool is widely applicable for researchers in the decision sciences.
Quantum computing and probability.

Science.gov (United States)

Ferry, David K

2009-11-25

Over the past two decades, quantum computing has become a popular and promising approach to trying to solve computationally difficult problems. Missing in many descriptions of quantum computing is just how probability enters into the process. Here, we discuss some simple examples of how uncertainty and probability enter, and how this and the ideas of quantum computing challenge our interpretations of quantum mechanics. It is found that this uncertainty can lead to intrinsic decoherence, and this raises challenges for error correction.
Quantum computing and probability

International Nuclear Information System (INIS)

Ferry, David K

2009-01-01

Over the past two decades, quantum computing has become a popular and promising approach to trying to solve computationally difficult problems. Missing in many descriptions of quantum computing is just how probability enters into the process. Here, we discuss some simple examples of how uncertainty and probability enter, and how this and the ideas of quantum computing challenge our interpretations of quantum mechanics. It is found that this uncertainty can lead to intrinsic decoherence, and this raises challenges for error correction. (viewpoint)
An internally validated prognostic model for success in revision stapes surgery for otosclerosis.

Science.gov (United States)

Wegner, Inge; Vincent, Robert; Derks, Laura S M; Rauh, Simone P; Heymans, Martijn W; Stegeman, Inge; Grolman, Wilko

2018-03-09

To develop a prediction model that can accurately predict the chance of success following revision stapes surgery in patients with recurrent or persistent otosclerosis at 2- to 6-months follow-up and to validate this model internally. A retrospective cohort study of prospectively gathered data in a tertiary referral center. The associations of 11 prognostic factors with treatment success were tested in 705 cases using multivariable logistic regression analysis with backward selection. Success was defined as a mean air-bone gap closure to 10 dB or less. The most relevant predictors were used to derive a clinical prediction rule to determine the probability of success. Internal validation by means of bootstrapping was performed. Model performance indices, including the Hosmer-Lemeshow test, the area under the receiver operating characteristics curve (AUC), and the explained variance were calculated. Success was achieved in 57.7% of cases at 2- to 6-months follow-up. Certain previous surgical techniques, primary causes of failure leading up to revision stapes surgery, and positions of the prosthesis placed during revision surgery were associated with higher success percentages. The clinical prediction rule performed moderately well in the original dataset (Hosmer-Lemeshow P = .78; AUC = 0.73; explained variance = 22%), which slightly decreased following internal validation by means of bootstrapping (AUC = 0.69; explained variance = 13%). Our study established the importance of previous surgical technique, primary cause of failure, and type of the prosthesis placed during the revision surgery in predicting the probability of success following stapes surgery at 2- to 6-months follow-up. 2b. Laryngoscope, 2018. © 2018 The American Laryngological, Rhinological and Otological Society, Inc.
Lake Basin Fetch and Maximum Length/Width

Data.gov (United States)

Minnesota Department of Natural Resources — Linear features representing the Fetch, Maximum Length and Maximum Width of a lake basin. Fetch, maximum length and average width are calcuated from the lake polygon...
Constructing probability distributions of uncertain variables in models of the performance of the Waste Isolation Pilot Plant: The 1990 performance simulations

International Nuclear Information System (INIS)

Tierney, M.S.

1990-12-01

A five-step procedure was used in the 1990 performance simulations to construct probability distributions of the uncertain variables appearing in the mathematical models used to simulate the Waste Isolation Pilot Plant's (WIPP's) performance. This procedure provides a consistent approach to the construction of probability distributions in cases where empirical data concerning a variable are sparse or absent and minimizes the amount of spurious information that is often introduced into a distribution by assumptions of nonspecialists. The procedure gives first priority to the professional judgment of subject-matter experts and emphasizes the use of site-specific empirical data for the construction of the probability distributions when such data are available. In the absence of sufficient empirical data, the procedure employs the Maximum Entropy Formalism and the subject-matter experts' subjective estimates of the parameters of the distribution to construct a distribution that can be used in a performance simulation. (author)
Constructing probability distributions of uncertain variables in models of the performance of the Waste Isolation Pilot Plant: The 1990 performance simulations

Energy Technology Data Exchange (ETDEWEB)

Tierney, M S

1990-12-15

A five-step procedure was used in the 1990 performance simulations to construct probability distributions of the uncertain variables appearing in the mathematical models used to simulate the Waste Isolation Pilot Plant's (WIPP's) performance. This procedure provides a consistent approach to the construction of probability distributions in cases where empirical data concerning a variable are sparse or absent and minimizes the amount of spurious information that is often introduced into a distribution by assumptions of nonspecialists. The procedure gives first priority to the professional judgment of subject-matter experts and emphasizes the use of site-specific empirical data for the construction of the probability distributions when such data are available. In the absence of sufficient empirical data, the procedure employs the Maximum Entropy Formalism and the subject-matter experts' subjective estimates of the parameters of the distribution to construct a distribution that can be used in a performance simulation. (author)
[Biometric bases: basic concepts of probability calculation].

Science.gov (United States)

Dinya, E

1998-04-26

The author gives or outline of the basic concepts of probability theory. The bases of the event algebra, definition of the probability, the classical probability model and the random variable are presented.
Pre-aggregation for Probability Distributions

DEFF Research Database (Denmark)

Timko, Igor; Dyreson, Curtis E.; Pedersen, Torben Bach

Motivated by the increasing need to analyze complex uncertain multidimensional data (e.g., in order to optimize and personalize location-based services), this paper proposes novel types of {\\em probabilistic} OLAP queries that operate on aggregate values that are probability distributions...... and the techniques to process these queries. The paper also presents the methods for computing the probability distributions, which enables pre-aggregation, and for using the pre-aggregated distributions for further aggregation. In order to achieve good time and space efficiency, the methods perform approximate...... multidimensional data analysis that is considered in this paper (i.e., approximate processing of probabilistic OLAP queries over probability distributions)....
Maximum permissible voltage of YBCO coated conductors

Energy Technology Data Exchange (ETDEWEB)

Wen, J.; Lin, B.; Sheng, J.; Xu, J.; Jin, Z. [Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai (China); Hong, Z., E-mail: zhiyong.hong@sjtu.edu.cn [Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai (China); Wang, D.; Zhou, H.; Shen, X.; Shen, C. [Qingpu Power Supply Company, State Grid Shanghai Municipal Electric Power Company, Shanghai (China)

2014-06-15

Highlights: • We examine three kinds of tapes’ maximum permissible voltage. • We examine the relationship between quenching duration and maximum permissible voltage. • Continuous I{sub c} degradations under repetitive quenching where tapes reaching maximum permissible voltage. • The relationship between maximum permissible voltage and resistance, temperature. - Abstract: Superconducting fault current limiter (SFCL) could reduce short circuit currents in electrical power system. One of the most important thing in developing SFCL is to find out the maximum permissible voltage of each limiting element. The maximum permissible voltage is defined as the maximum voltage per unit length at which the YBCO coated conductors (CC) do not suffer from critical current (I{sub c}) degradation or burnout. In this research, the time of quenching process is changed and voltage is raised until the I{sub c} degradation or burnout happens. YBCO coated conductors test in the experiment are from American superconductor (AMSC) and Shanghai Jiao Tong University (SJTU). Along with the quenching duration increasing, the maximum permissible voltage of CC decreases. When quenching duration is 100 ms, the maximum permissible of SJTU CC, 12 mm AMSC CC and 4 mm AMSC CC are 0.72 V/cm, 0.52 V/cm and 1.2 V/cm respectively. Based on the results of samples, the whole length of CCs used in the design of a SFCL can be determined.
Probability inequalities for decomposition integrals

Czech Academy of Sciences Publication Activity Database

Agahi, H.; Mesiar, Radko

2017-01-01

Roč. 315, č. 1 (2017), s. 240-248 ISSN 0377-0427 Institutional support: RVO:67985556 Keywords : Decomposition integral * Superdecomposition integral * Probability inequalities Subject RIV: BA - General Mathematics OBOR OECD: Statistics and probability Impact factor: 1.357, year: 2016 http://library.utia.cas.cz/separaty/2017/E/mesiar-0470959.pdf
Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal

International Nuclear Information System (INIS)

Helton, J.C.

1996-03-01

A formal description of the structure of several recent performance assessments (PAs) for the Waste Isolation Pilot Plant (WIPP) is given in terms of the following three components: a probability space (S st , S st , p st ) for stochastic uncertainty, a probability space (S su , S su , p su ) for subjective uncertainty and a function (i.e., a random variable) defined on the product space associated with (S st , S st , p st ) and (S su , S su , p su ). The explicit recognition of the existence of these three components allows a careful description of the use of probability, conditional probability and complementary cumulative distribution functions within the WIPP PA. This usage is illustrated in the context of the U.S. Environmental Protection Agency's standard for the geologic disposal of radioactive waste (40 CFR 191, Subpart B). The paradigm described in this presentation can also be used to impose a logically consistent structure on PAs for other complex systems
Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal

International Nuclear Information System (INIS)

Helton, J.C.

1996-01-01

A formal description of the structure of several recent performance assessments (PAs) for the Waste Isolation Pilot Plant (WIPP) is given in terms of the following three components: a probability space (S st , L st , P st ) for stochastic uncertainty, a probability space (S su , L su , P su ) for subjective uncertainty and a function (i.e., a random variable) defined on the product space associated with (S st , L st , P st ) and (S su , L su , P su ). The explicit recognition of the existence of these three components allows a careful description of the use of probability, conditional probability and complementary cumulative distribution functions within the WIPP PA. This usage is illustrated in the context of the US Environmental Protection Agency's standard for the geologic disposal of radioactive waste (40 CFR 191, Subpart B). The paradigm described in this presentation can also be used to impose a logically consistent structure on PAs for other complex systems
Void probability scaling in hadron nucleus interactions

International Nuclear Information System (INIS)

Ghosh, Dipak; Deb, Argha; Bhattacharyya, Swarnapratim; Ghosh, Jayita; Bandyopadhyay, Prabhat; Das, Rupa; Mukherjee, Sima

2002-01-01

Heygi while investigating with the rapidity gap probability (that measures the chance of finding no particle in the pseudo-rapidity interval Δη) found that a scaling behavior in the rapidity gap probability has a close correspondence with the scaling of a void probability in galaxy correlation study. The main aim in this paper is to study the scaling behavior of the rapidity gap probability
Receiver function estimated by maximum entropy deconvolution

Institute of Scientific and Technical Information of China (English)

吴庆举; 田小波; 张乃铃; 李卫平; 曾融生

2003-01-01

Maximum entropy deconvolution is presented to estimate receiver function, with the maximum entropy as the rule to determine auto-correlation and cross-correlation functions. The Toeplitz equation and Levinson algorithm are used to calculate the iterative formula of error-predicting filter, and receiver function is then estimated. During extrapolation, reflective coefficient is always less than 1, which keeps maximum entropy deconvolution stable. The maximum entropy of the data outside window increases the resolution of receiver function. Both synthetic and real seismograms show that maximum entropy deconvolution is an effective method to measure receiver function in time-domain.
Paraconsistent Probabilities: Consistency, Contradictions and Bayes’ Theorem

Directory of Open Access Journals (Sweden)

Juliana Bueno-Soler

2016-09-01

Full Text Available This paper represents the first steps towards constructing a paraconsistent theory of probability based on the Logics of Formal Inconsistency (LFIs. We show that LFIs encode very naturally an extension of the notion of probability able to express sophisticated probabilistic reasoning under contradictions employing appropriate notions of conditional probability and paraconsistent updating, via a version of Bayes’ theorem for conditionalization. We argue that the dissimilarity between the notions of inconsistency and contradiction, one of the pillars of LFIs, plays a central role in our extended notion of probability. Some critical historical and conceptual points about probability theory are also reviewed.
Probabilistic Design Analysis (PDA) Approach to Determine the Probability of Cross-System Failures for a Space Launch Vehicle

Science.gov (United States)

Shih, Ann T.; Lo, Yunnhon; Ward, Natalie C.

2010-01-01

Quantifying the probability of significant launch vehicle failure scenarios for a given design, while still in the design process, is critical to mission success and to the safety of the astronauts. Probabilistic risk assessment (PRA) is chosen from many system safety and reliability tools to verify the loss of mission (LOM) and loss of crew (LOC) requirements set by the NASA Program Office. To support the integrated vehicle PRA, probabilistic design analysis (PDA) models are developed by using vehicle design and operation data to better quantify failure probabilities and to better understand the characteristics of a failure and its outcome. This PDA approach uses a physics-based model to describe the system behavior and response for a given failure scenario. Each driving parameter in the model is treated as a random variable with a distribution function. Monte Carlo simulation is used to perform probabilistic calculations to statistically obtain the failure probability. Sensitivity analyses are performed to show how input parameters affect the predicted failure probability, providing insight for potential design improvements to mitigate the risk. The paper discusses the application of the PDA approach in determining the probability of failure for two scenarios from the NASA Ares I project
Exploring non-signalling polytopes with negative probability

International Nuclear Information System (INIS)

Oas, G; Barros, J Acacio de; Carvalhaes, C

2014-01-01

Bipartite and tripartite EPR–Bell type systems are examined via joint quasi-probability distributions where probabilities are permitted to be negative. It is shown that such distributions exist only when the no-signalling condition is satisfied. A characteristic measure, the probability mass, is introduced and, via its minimization, limits the number of quasi-distributions describing a given marginal probability distribution. The minimized probability mass is shown to be an alternative way to characterize non-local systems. Non-signalling polytopes for two to eight settings in the bipartite scenario are examined and compared to prior work. Examining perfect cloning of non-local systems within the tripartite scenario suggests defining two categories of signalling. It is seen that many properties of non-local systems can be efficiently described by quasi-probability theory. (paper)
Fundamentals of applied probability and random processes

CERN Document Server

Ibe, Oliver

2005-01-01

This book is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book''s clear writing style and homework problems make it ideal for the classroom or for self-study.* Good and solid introduction to probability theory and stochastic processes * Logically organized; writing is presented in a clear manner * Choice of topics is comprehensive within the area of probability * Ample homework problems are organized into chapter sections
The enigma of probability and physics

International Nuclear Information System (INIS)

Mayants, L.

1984-01-01

This volume contains a coherent exposition of the elements of two unique sciences: probabilistics (science of probability) and probabilistic physics (application of probabilistics to physics). Proceeding from a key methodological principle, it starts with the disclosure of the true content of probability and the interrelation between probability theory and experimental statistics. This makes is possible to introduce a proper order in all the sciences dealing with probability and, by conceiving the real content of statistical mechanics and quantum mechanics in particular, to construct both as two interconnected domains of probabilistic physics. Consistent theories of kinetics of physical transformations, decay processes, and intramolecular rearrangements are also outlined. The interrelation between the electromagnetic field, photons, and the theoretically discovered subatomic particle 'emon' is considered. Numerous internal imperfections of conventional probability theory, statistical physics, and quantum physics are exposed and removed - quantum physics no longer needs special interpretation. EPR, Bohm, and Bell paradoxes are easily resolved, among others. (Auth.)

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