CONSTRUCTION OF A CALIBRATED PROBABILISTIC CLASSIFICATION CATALOG: APPLICATION TO 50k VARIABLE SOURCES IN THE ALL-SKY AUTOMATED SURVEY

Energy Technology Data Exchange (ETDEWEB)

Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Brink, Henrik; Crellin-Quick, Arien [Astronomy Department, University of California, Berkeley, CA 94720-3411 (United States); Butler, Nathaniel R., E-mail: jwrichar@stat.berkeley.edu [School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287 (United States)

2012-12-15

With growing data volumes from synoptic surveys, astronomers necessarily must become more abstracted from the discovery and introspection processes. Given the scarcity of follow-up resources, there is a particularly sharp onus on the frameworks that replace these human roles to provide accurate and well-calibrated probabilistic classification catalogs. Such catalogs inform the subsequent follow-up, allowing consumers to optimize the selection of specific sources for further study and permitting rigorous treatment of classification purities and efficiencies for population studies. Here, we describe a process to produce a probabilistic classification catalog of variability with machine learning from a multi-epoch photometric survey. In addition to producing accurate classifications, we show how to estimate calibrated class probabilities and motivate the importance of probability calibration. We also introduce a methodology for feature-based anomaly detection, which allows discovery of objects in the survey that do not fit within the predefined class taxonomy. Finally, we apply these methods to sources observed by the All-Sky Automated Survey (ASAS), and release the Machine-learned ASAS Classification Catalog (MACC), a 28 class probabilistic classification catalog of 50,124 ASAS sources in the ASAS Catalog of Variable Stars. We estimate that MACC achieves a sub-20% classification error rate and demonstrate that the class posterior probabilities are reasonably calibrated. MACC classifications compare favorably to the classifications of several previous domain-specific ASAS papers and to the ASAS Catalog of Variable Stars, which had classified only 24% of those sources into one of 12 science classes.

An approximate methods approach to probabilistic structural analysis

Science.gov (United States)

Mcclung, R. C.; Millwater, H. R.; Wu, Y.-T.; Thacker, B. H.; Burnside, O. H.

1989-01-01

A probabilistic structural analysis method (PSAM) is described which makes an approximate calculation of the structural response of a system, including the associated probabilistic distributions, with minimal computation time and cost, based on a simplified representation of the geometry, loads, and material. The method employs the fast probability integration (FPI) algorithm of Wu and Wirsching. Typical solution strategies are illustrated by formulations for a representative critical component chosen from the Space Shuttle Main Engine (SSME) as part of a major NASA-sponsored program on PSAM. Typical results are presented to demonstrate the role of the methodology in engineering design and analysis.

Probabilistic methods for physics

International Nuclear Information System (INIS)

Cirier, G

2013-01-01

We present an asymptotic method giving a probability of presence of the iterated spots of R d by a polynomial function f. We use the well-known Perron Frobenius operator (PF) that lets certain sets and measure invariant by f. Probabilistic solutions can exist for the deterministic iteration. If the theoretical result is already known, here we quantify these probabilities. This approach seems interesting to use for computing situations when the deterministic methods don't run. Among the examined applications, are asymptotic solutions of Lorenz, Navier-Stokes or Hamilton's equations. In this approach, linearity induces many difficult problems, all of whom we have not yet resolved.

Probabilistic structural analysis methods for select space propulsion system components

Science.gov (United States)

Millwater, H. R.; Cruse, T. A.

1989-01-01

The Probabilistic Structural Analysis Methods (PSAM) project developed at the Southwest Research Institute integrates state-of-the-art structural analysis techniques with probability theory for the design and analysis of complex large-scale engineering structures. An advanced efficient software system (NESSUS) capable of performing complex probabilistic analysis has been developed. NESSUS contains a number of software components to perform probabilistic analysis of structures. These components include: an expert system, a probabilistic finite element code, a probabilistic boundary element code and a fast probability integrator. The NESSUS software system is shown. An expert system is included to capture and utilize PSAM knowledge and experience. NESSUS/EXPERT is an interactive menu-driven expert system that provides information to assist in the use of the probabilistic finite element code NESSUS/FEM and the fast probability integrator (FPI). The expert system menu structure is summarized. The NESSUS system contains a state-of-the-art nonlinear probabilistic finite element code, NESSUS/FEM, to determine the structural response and sensitivities. A broad range of analysis capabilities and an extensive element library is present.

Automating Flood Hazard Mapping Methods for Near Real-time Storm Surge Inundation and Vulnerability Assessment

Science.gov (United States)

Weigel, A. M.; Griffin, R.; Gallagher, D.

2015-12-01

Storm surge has enough destructive power to damage buildings and infrastructure, erode beaches, and threaten human life across large geographic areas, hence posing the greatest threat of all the hurricane hazards. The United States Gulf of Mexico has proven vulnerable to hurricanes as it has been hit by some of the most destructive hurricanes on record. With projected rises in sea level and increases in hurricane activity, there is a need to better understand the associated risks for disaster mitigation, preparedness, and response. GIS has become a critical tool in enhancing disaster planning, risk assessment, and emergency response by communicating spatial information through a multi-layer approach. However, there is a need for a near real-time method of identifying areas with a high risk of being impacted by storm surge. Research was conducted alongside Baron, a private industry weather enterprise, to facilitate automated modeling and visualization of storm surge inundation and vulnerability on a near real-time basis. This research successfully automated current flood hazard mapping techniques using a GIS framework written in a Python programming environment, and displayed resulting data through an Application Program Interface (API). Data used for this methodology included high resolution topography, NOAA Probabilistic Surge model outputs parsed from Rich Site Summary (RSS) feeds, and the NOAA Census tract level Social Vulnerability Index (SoVI). The development process required extensive data processing and management to provide high resolution visualizations of potential flooding and population vulnerability in a timely manner. The accuracy of the developed methodology was assessed using Hurricane Isaac as a case study, which through a USGS and NOAA partnership, contained ample data for statistical analysis. This research successfully created a fully automated, near real-time method for mapping high resolution storm surge inundation and vulnerability for the

Application of the probabilistic method at the E.D.F

International Nuclear Information System (INIS)

Gachot, Bernard

1976-01-01

Having first evoked the problems arising from the definition of a so-called 'acceptable risk', the probabilistic study programme on safety carried out at the E.D.F. is described. The different aspects of the probabilistic estimation of a hazard are presented as well as the different steps i.e. collecting the information, carrying out a quantitative and qualitative analysis, which characterize the probabilistic study of safety problems. The problem of data determination is considered on reliability of the equipment, noting as a conclusion, that in spite of the lack of accuracy of the present data, the probabilistic methods already appear as a highly valuable tool favouring an homogenous and coherent approach of nuclear plant safety [fr

a Probabilistic Embedding Clustering Method for Urban Structure Detection

Science.gov (United States)

Lin, X.; Li, H.; Zhang, Y.; Gao, L.; Zhao, L.; Deng, M.

2017-09-01

Urban structure detection is a basic task in urban geography. Clustering is a core technology to detect the patterns of urban spatial structure, urban functional region, and so on. In big data era, diverse urban sensing datasets recording information like human behaviour and human social activity, suffer from complexity in high dimension and high noise. And unfortunately, the state-of-the-art clustering methods does not handle the problem with high dimension and high noise issues concurrently. In this paper, a probabilistic embedding clustering method is proposed. Firstly, we come up with a Probabilistic Embedding Model (PEM) to find latent features from high dimensional urban sensing data by "learning" via probabilistic model. By latent features, we could catch essential features hidden in high dimensional data known as patterns; with the probabilistic model, we can also reduce uncertainty caused by high noise. Secondly, through tuning the parameters, our model could discover two kinds of urban structure, the homophily and structural equivalence, which means communities with intensive interaction or in the same roles in urban structure. We evaluated the performance of our model by conducting experiments on real-world data and experiments with real data in Shanghai (China) proved that our method could discover two kinds of urban structure, the homophily and structural equivalence, which means clustering community with intensive interaction or under the same roles in urban space.

A PROBABILISTIC EMBEDDING CLUSTERING METHOD FOR URBAN STRUCTURE DETECTION

Directory of Open Access Journals (Sweden)

X. Lin

2017-09-01

Full Text Available Urban structure detection is a basic task in urban geography. Clustering is a core technology to detect the patterns of urban spatial structure, urban functional region, and so on. In big data era, diverse urban sensing datasets recording information like human behaviour and human social activity, suffer from complexity in high dimension and high noise. And unfortunately, the state-of-the-art clustering methods does not handle the problem with high dimension and high noise issues concurrently. In this paper, a probabilistic embedding clustering method is proposed. Firstly, we come up with a Probabilistic Embedding Model (PEM to find latent features from high dimensional urban sensing data by “learning” via probabilistic model. By latent features, we could catch essential features hidden in high dimensional data known as patterns; with the probabilistic model, we can also reduce uncertainty caused by high noise. Secondly, through tuning the parameters, our model could discover two kinds of urban structure, the homophily and structural equivalence, which means communities with intensive interaction or in the same roles in urban structure. We evaluated the performance of our model by conducting experiments on real-world data and experiments with real data in Shanghai (China proved that our method could discover two kinds of urban structure, the homophily and structural equivalence, which means clustering community with intensive interaction or under the same roles in urban space.

Formalizing Probabilistic Safety Claims

Science.gov (United States)

Herencia-Zapana, Heber; Hagen, George E.; Narkawicz, Anthony J.

2011-01-01

A safety claim for a system is a statement that the system, which is subject to hazardous conditions, satisfies a given set of properties. Following work by John Rushby and Bev Littlewood, this paper presents a mathematical framework that can be used to state and formally prove probabilistic safety claims. It also enables hazardous conditions, their uncertainties, and their interactions to be integrated into the safety claim. This framework provides a formal description of the probabilistic composition of an arbitrary number of hazardous conditions and their effects on system behavior. An example is given of a probabilistic safety claim for a conflict detection algorithm for aircraft in a 2D airspace. The motivation for developing this mathematical framework is that it can be used in an automated theorem prover to formally verify safety claims.

Probabilistic safety analysis : a new nuclear power plants licensing method

International Nuclear Information System (INIS)

Oliveira, L.F.S. de.

1982-04-01

After a brief retrospect of the application of Probabilistic Safety Analysis in the nuclear field, the basic differences between the deterministic licensing method, currently in use, and the probabilistic method are explained. Next, the two main proposals (by the AIF and the ACRS) concerning the establishment of the so-called quantitative safety goals (or simply 'safety goals') are separately presented and afterwards compared in their most fundamental aspects. Finally, some recent applications and future possibilities are discussed. (Author) [pt

Optimization of structures subjected to dynamic load: deterministic and probabilistic methods

Directory of Open Access Journals (Sweden)

Élcio Cassimiro Alves

Full Text Available Abstract This paper deals with the deterministic and probabilistic optimization of structures against bending when submitted to dynamic loads. The deterministic optimization problem considers the plate submitted to a time varying load while the probabilistic one takes into account a random loading defined by a power spectral density function. The correlation between the two problems is made by one Fourier Transformed. The finite element method is used to model the structures. The sensitivity analysis is performed through the analytical method and the optimization problem is dealt with by the method of interior points. A comparison between the deterministic optimisation and the probabilistic one with a power spectral density function compatible with the time varying load shows very good results.

Probabilistic real-time contingency ranking method

International Nuclear Information System (INIS)

Mijuskovic, N.A.; Stojnic, D.

2000-01-01

This paper describes a real-time contingency method based on a probabilistic index-expected energy not supplied. This way it is possible to take into account the stochastic nature of the electric power system equipment outages. This approach enables more comprehensive ranking of contingencies and it is possible to form reliability cost values that can form the basis for hourly spot price calculations. The electric power system of Serbia is used as an example for the method proposed. (author)

An advanced probabilistic structural analysis method for implicit performance functions

Science.gov (United States)

Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

1989-01-01

In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

Formulation of probabilistic models of protein structure in atomic detail using the reference ratio method

DEFF Research Database (Denmark)

Valentin, Jan B.; Andreetta, Christian; Boomsma, Wouter

2014-01-01

We propose a method to formulate probabilistic models of protein structure in atomic detail, for a given amino acid sequence, based on Bayesian principles, while retaining a close link to physics. We start from two previously developed probabilistic models of protein structure on a local length s....... The results indicate that the proposed method and the probabilistic models show considerable promise for probabilistic protein structure prediction and related applications. © 2013 Wiley Periodicals, Inc....

NESSUS/EXPERT - An expert system for probabilistic structural analysis methods

Science.gov (United States)

Millwater, H.; Palmer, K.; Fink, P.

1988-01-01

An expert system (NESSUS/EXPERT) is presented which provides assistance in using probabilistic structural analysis methods. NESSUS/EXPERT is an interactive menu-driven expert system that provides information to assist in the use of the probabilistic finite element code NESSUS/FEM and the fast probability integrator. NESSUS/EXPERT was developed with a combination of FORTRAN and CLIPS, a C language expert system tool, to exploit the strengths of each language.

Automated methods of corrosion measurement

DEFF Research Database (Denmark)

Andersen, Jens Enevold Thaulov; Bech-Nielsen, Gregers; Reeve, John Ch

1997-01-01

to revise assumptions regarding the basis of the method, which sometimes leads to the discovery of as-yet unnoticed phenomena. The present selection of automated methods for corrosion measurements is not motivated simply by the fact that a certain measurement can be performed automatically. Automation...... is applied to nearly all types of measurements today....

River Flow Prediction Using the Nearest Neighbor Probabilistic Ensemble Method

Directory of Open Access Journals (Sweden)

H. Sanikhani

2016-02-01

Full Text Available Introduction: In the recent years, researchers interested on probabilistic forecasting of hydrologic variables such river flow.A probabilistic approach aims at quantifying the prediction reliability through a probability distribution function or a prediction interval for the unknown future value. The evaluation of the uncertainty associated to the forecast is seen as a fundamental information, not only to correctly assess the prediction, but also to compare forecasts from different methods and to evaluate actions and decisions conditionally on the expected values. Several probabilistic approaches have been proposed in the literature, including (1 methods that use resampling techniques to assess parameter and model uncertainty, such as the Metropolis algorithm or the Generalized Likelihood Uncertainty Estimation (GLUE methodology for an application to runoff prediction, (2 methods based on processing the forecast errors of past data to produce the probability distributions of future values and (3 methods that evaluate how the uncertainty propagates from the rainfall forecast to the river discharge prediction, as the Bayesian forecasting system. Materials and Methods: In this study, two different probabilistic methods are used for river flow prediction.Then the uncertainty related to the forecast is quantified. One approach is based on linear predictors and in the other, nearest neighbor was used. The nonlinear probabilistic ensemble can be used for nonlinear time series analysis using locally linear predictors, while NNPE utilize a method adapted for one step ahead nearest neighbor methods. In this regard, daily river discharge (twelve years of Dizaj and Mashin Stations on Baranduz-Chay basin in west Azerbijan and Zard-River basin in Khouzestan provinces were used, respectively. The first six years of data was applied for fitting the model. The next three years was used to calibration and the remained three yeas utilized for testing the models

Probabilistic structural analysis methods for space transportation propulsion systems

Science.gov (United States)

Chamis, C. C.; Moore, N.; Anis, C.; Newell, J.; Nagpal, V.; Singhal, S.

1991-01-01

Information on probabilistic structural analysis methods for space propulsion systems is given in viewgraph form. Information is given on deterministic certification methods, probability of failure, component response analysis, stress responses for 2nd stage turbine blades, Space Shuttle Main Engine (SSME) structural durability, and program plans. .

Probabilistic evaluation method of stability of ground and slope considering spatial randomness of soil properties

International Nuclear Information System (INIS)

Ohtori, Yasuki

2004-01-01

In the JEAG4601-1987 (Japan Electric Association Guide for earthquake resistance design), either the conventional deterministic method or probabilistic method is used for evaluating the stability of ground foundations and surrounding slopes in nuclear power plants. The deterministic method, in which the soil properties of 'mean ± coefficient x standard deviation' is adopted for the calculations, is generally used in the design stage to data. On the other hand, the probabilistic method, in which the soil properties assume to have probabilistic distributions, is stated as a future method. The deterministic method facilitates the evaluation, however, it is necessary to clarify the relation with the probabilistic method. In this paper, the relationship between the deterministic and the probabilistic methods are investigated. To do that, a simple model that can take into account the dynamic effect of structures and a simplified method for accounting the spatial randomness are proposed and used for the studies. As the results of studies, it is found that the strength of soil properties is most importation factor for the stability of ground structures and the probability below the safety factor evaluated with the soil properties of mean -1.0 x standard deviation' by the deterministic method is of much lower. (author)

Model checking optimal finite-horizon control for probabilistic gene regulatory networks.

Science.gov (United States)

Wei, Ou; Guo, Zonghao; Niu, Yun; Liao, Wenyuan

2017-12-14

Probabilistic Boolean networks (PBNs) have been proposed for analyzing external control in gene regulatory networks with incorporation of uncertainty. A context-sensitive PBN with perturbation (CS-PBNp), extending a PBN with context-sensitivity to reflect the inherent biological stability and random perturbations to express the impact of external stimuli, is considered to be more suitable for modeling small biological systems intervened by conditions from the outside. In this paper, we apply probabilistic model checking, a formal verification technique, to optimal control for a CS-PBNp that minimizes the expected cost over a finite control horizon. We first describe a procedure of modeling a CS-PBNp using the language provided by a widely used probabilistic model checker PRISM. We then analyze the reward-based temporal properties and the computation in probabilistic model checking; based on the analysis, we provide a method to formulate the optimal control problem as minimum reachability reward properties. Furthermore, we incorporate control and state cost information into the PRISM code of a CS-PBNp such that automated model checking a minimum reachability reward property on the code gives the solution to the optimal control problem. We conduct experiments on two examples, an apoptosis network and a WNT5A network. Preliminary experiment results show the feasibility and effectiveness of our approach. The approach based on probabilistic model checking for optimal control avoids explicit computation of large-size state transition relations associated with PBNs. It enables a natural depiction of the dynamics of gene regulatory networks, and provides a canonical form to formulate optimal control problems using temporal properties that can be automated solved by leveraging the analysis power of underlying model checking engines. This work will be helpful for further utilization of the advances in formal verification techniques in system biology.

Towards decision making via expressive probabilistic ontologies

NARCIS (Netherlands)

Acar, Erman; Thorne, Camilo; Stuckenschmidt, Heiner

2015-01-01

© Springer International Publishing Switzerland 2015. We propose a framework for automated multi-attribute deci- sion making, employing the probabilistic non-monotonic description log- ics proposed by Lukasiewicz in 2008. Using this framework, we can model artificial agents in decision-making

Automated Methods of Corrosion Measurements

DEFF Research Database (Denmark)

Andersen, Jens Enevold Thaulov

1997-01-01

. Mechanical control, recording, and data processing must therefore be automated to a high level of precision and reliability. These general techniques and the apparatus involved have been described extensively. The automated methods of such high-resolution microscopy coordinated with computerized...

Optimisation of technical specifications using probabilistic methods

International Nuclear Information System (INIS)

Ericsson, G.; Knochenhauer, M.; Hultqvist, G.

1986-01-01

During the last few years the development of methods for modifying and optimising nuclear power plant Technical Specifications (TS) for plant operations has received increased attention. Probalistic methods in general, and the plant and system models of probabilistic safety assessment (PSA) in particular, seem to provide the most forceful tools for optimisation. This paper first gives some general comments on optimisation, identifying important parameters and then gives a description of recent Swedish experiences from the use of nuclear power plant PSA models and results for TS optimisation

Patterns of probabilistic evaluation of the maintenance

International Nuclear Information System (INIS)

Torres V, A.; Rivero O, J.J.

2004-01-01

The Boolean equation represented by the minimum sets of court at level of a system or of all one Probabilistic safety analysis (APS) it has been used for to evaluate the output configurations of service of teams during the exploitation. It has been carried out through applications of APS for the optimization of operational regimes. The obtaining of such boolean equations as demands of a process of high mathematical complexity for what exhaustive studies are required, even for the application of their results. The important advantages for the maintenance that they obtain of these applications they require the development of methodologies that bring near these optimization methods to the systems of management of the maintenance, and not facilitate their use for a personnel specialized in the probabilistic topics. The article presents a methodology for the preparation, solution and utilization of the results of the fault tree leaving of technological outlines. This algorithm has been automated through the MOSEG code Win to Ver 1.0 (Author)

Use of adjoint methods in the probabilistic finite element approach to fracture mechanics

Science.gov (United States)

Liu, Wing Kam; Besterfield, Glen; Lawrence, Mark; Belytschko, Ted

1988-01-01

The adjoint method approach to probabilistic finite element methods (PFEM) is presented. When the number of objective functions is small compared to the number of random variables, the adjoint method is far superior to the direct method in evaluating the objective function derivatives with respect to the random variables. The PFEM is extended to probabilistic fracture mechanics (PFM) using an element which has the near crack-tip singular strain field embedded. Since only two objective functions (i.e., mode I and II stress intensity factors) are needed for PFM, the adjoint method is well suited.

Approximating methods for intractable probabilistic models: Applications in neuroscience

DEFF Research Database (Denmark)

Højen-Sørensen, Pedro

2002-01-01

This thesis investigates various methods for carrying out approximate inference in intractable probabilistic models. By capturing the relationships between random variables, the framework of graphical models hints at which sets of random variables pose a problem to the inferential step. The appro...

WE-H-BRC-06: A Unified Machine-Learning Based Probabilistic Model for Automated Anomaly Detection in the Treatment Plan Data

International Nuclear Information System (INIS)

Chang, X; Liu, S; Kalet, A; Yang, D

2016-01-01

Purpose: The purpose of this work was to investigate the ability of a machine-learning based probabilistic approach to detect radiotherapy treatment plan anomalies given initial disease classes information. Methods In total we obtained 1112 unique treatment plans with five plan parameters and disease information from a Mosaiq treatment management system database for use in the study. The plan parameters include prescription dose, fractions, fields, modality and techniques. The disease information includes disease site, and T, M and N disease stages. A Bayesian network method was employed to model the probabilistic relationships between tumor disease information, plan parameters and an anomaly flag. A Bayesian learning method with Dirichlet prior was useed to learn the joint probabilities between dependent variables in error-free plan data and data with artificially induced anomalies. In the study, we randomly sampled data with anomaly in a specified anomaly space.We tested the approach with three groups of plan anomalies – improper concurrence of values of all five plan parameters and values of any two out of five parameters, and all single plan parameter value anomalies. Totally, 16 types of plan anomalies were covered by the study. For each type, we trained an individual Bayesian network. Results: We found that the true positive rate (recall) and positive predictive value (precision) to detect concurrence anomalies of five plan parameters in new patient cases were 94.45±0.26% and 93.76±0.39% respectively. To detect other 15 types of plan anomalies, the average recall and precision were 93.61±2.57% and 93.78±3.54% respectively. The computation time to detect the plan anomaly of each type in a new plan is ∼0.08 seconds. Conclusion: The proposed method for treatment plan anomaly detection was found effective in the initial tests. The results suggest that this type of models could be applied to develop plan anomaly detection tools to assist manual and

WE-H-BRC-06: A Unified Machine-Learning Based Probabilistic Model for Automated Anomaly Detection in the Treatment Plan Data

Energy Technology Data Exchange (ETDEWEB)

Chang, X; Liu, S [Washington University in St. Louis, St. Louis, MO (United States); Kalet, A [University of Washington Medical Center, Seattle, WA (United States); Yang, D [Washington University in St Louis, St Louis, MO (United States)

2016-06-15

Purpose: The purpose of this work was to investigate the ability of a machine-learning based probabilistic approach to detect radiotherapy treatment plan anomalies given initial disease classes information. Methods In total we obtained 1112 unique treatment plans with five plan parameters and disease information from a Mosaiq treatment management system database for use in the study. The plan parameters include prescription dose, fractions, fields, modality and techniques. The disease information includes disease site, and T, M and N disease stages. A Bayesian network method was employed to model the probabilistic relationships between tumor disease information, plan parameters and an anomaly flag. A Bayesian learning method with Dirichlet prior was useed to learn the joint probabilities between dependent variables in error-free plan data and data with artificially induced anomalies. In the study, we randomly sampled data with anomaly in a specified anomaly space.We tested the approach with three groups of plan anomalies – improper concurrence of values of all five plan parameters and values of any two out of five parameters, and all single plan parameter value anomalies. Totally, 16 types of plan anomalies were covered by the study. For each type, we trained an individual Bayesian network. Results: We found that the true positive rate (recall) and positive predictive value (precision) to detect concurrence anomalies of five plan parameters in new patient cases were 94.45±0.26% and 93.76±0.39% respectively. To detect other 15 types of plan anomalies, the average recall and precision were 93.61±2.57% and 93.78±3.54% respectively. The computation time to detect the plan anomaly of each type in a new plan is ∼0.08 seconds. Conclusion: The proposed method for treatment plan anomaly detection was found effective in the initial tests. The results suggest that this type of models could be applied to develop plan anomaly detection tools to assist manual and

Machine learning a probabilistic perspective

CERN Document Server

Murphy, Kevin P

2012-01-01

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic method...

Next-generation probabilistic seismicity forecasting

Energy Technology Data Exchange (ETDEWEB)

Hiemer, S.

2014-07-01

novel automated method to investigate the significance of spatial b-value variations. The method incorporates an objective data-driven partitioning scheme, which is based on penalized likelihood estimates. These well-defined criteria avoid the difficult choice of commonly applied spatial mapping parameters, such as grid spacing or size of mapping radii. We construct a seismicity forecast that includes spatial b-value variations and demonstrate our model’s skill and reliability when applied to data from California. All proposed probabilistic seismicity forecasts were subjected to evaluation methods using state of the art algorithms provided by the 'Collaboratory for the Study of Earthquake Predictability' infrastructure. First, we evaluated the statistical agreement between the forecasted and observed rates of target events in terms of number, space and magnitude. Secondly, we assessed the performance of one forecast relative to another. We find that the forecasts presented in this thesis are reliable and show significant skills with respect to established classical forecasts. These next-generation probabilistic seismicity forecasts can thus provide hazard information that are potentially useful in reducing earthquake losses and enhancing community preparedness and resilience. (author)

Next-generation probabilistic seismicity forecasting

International Nuclear Information System (INIS)

Hiemer, S.

2014-01-01

novel automated method to investigate the significance of spatial b-value variations. The method incorporates an objective data-driven partitioning scheme, which is based on penalized likelihood estimates. These well-defined criteria avoid the difficult choice of commonly applied spatial mapping parameters, such as grid spacing or size of mapping radii. We construct a seismicity forecast that includes spatial b-value variations and demonstrate our model’s skill and reliability when applied to data from California. All proposed probabilistic seismicity forecasts were subjected to evaluation methods using state of the art algorithms provided by the 'Collaboratory for the Study of Earthquake Predictability' infrastructure. First, we evaluated the statistical agreement between the forecasted and observed rates of target events in terms of number, space and magnitude. Secondly, we assessed the performance of one forecast relative to another. We find that the forecasts presented in this thesis are reliable and show significant skills with respect to established classical forecasts. These next-generation probabilistic seismicity forecasts can thus provide hazard information that are potentially useful in reducing earthquake losses and enhancing community preparedness and resilience. (author)

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method

Energy Technology Data Exchange (ETDEWEB)

Wang, Qin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Florita, Anthony R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Krishnan, Venkat K [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cui, Mingjian [University of Texas at Dallas; Feng, Cong [University of Texas at Dallas; Wang, Zhenke [University of Texas at Dallas; Zhang, Jie [University of Texas at Dallas

2018-02-01

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power and currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start-time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.

Optimization of automation: I. Estimation method of cognitive automation rates reflecting the effects of automation on human operators in nuclear power plants

International Nuclear Information System (INIS)

Lee, Seung Min; Kim, Jong Hyun; Seong, Poong Hyun

2014-01-01

Highlights: • We propose an estimation method of the automation rate by taking the advantages of automation as the estimation measures. • We conduct the experiments to examine the validity of the suggested method. • The higher the cognitive automation rate is, the greater the decreased rate of the working time will be. • The usefulness of the suggested estimation method is proved by statistical analyses. - Abstract: Since automation was introduced in various industrial fields, the concept of the automation rate has been used to indicate the inclusion proportion of automation among all work processes or facilities. Expressions of the inclusion proportion of automation are predictable, as is the ability to express the degree of the enhancement of human performance. However, many researchers have found that a high automation rate does not guarantee high performance. Therefore, to reflect the effects of automation on human performance, this paper proposes a new estimation method of the automation rate that considers the effects of automation on human operators in nuclear power plants (NPPs). Automation in NPPs can be divided into two types: system automation and cognitive automation. Some general descriptions and characteristics of each type of automation are provided, and the advantages of automation are investigated. The advantages of each type of automation are used as measures of the estimation method of the automation rate. One advantage was found to be a reduction in the number of tasks, and another was a reduction in human cognitive task loads. The system and the cognitive automation rate were proposed as quantitative measures by taking advantage of the aforementioned benefits. To quantify the required human cognitive task loads and thus suggest the cognitive automation rate, Conant’s information-theory-based model was applied. The validity of the suggested method, especially as regards the cognitive automation rate, was proven by conducting

Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method

Science.gov (United States)

McIntosh, Chris; Welch, Mattea; McNiven, Andrea; Jaffray, David A.; Purdie, Thomas G.

2017-08-01

Recent works in automated radiotherapy treatment planning have used machine learning based on historical treatment plans to infer the spatial dose distribution for a novel patient directly from the planning image. We present a probabilistic, atlas-based approach which predicts the dose for novel patients using a set of automatically selected most similar patients (atlases). The output is a spatial dose objective, which specifies the desired dose-per-voxel, and therefore replaces the need to specify and tune dose-volume objectives. Voxel-based dose mimicking optimization then converts the predicted dose distribution to a complete treatment plan with dose calculation using a collapsed cone convolution dose engine. In this study, we investigated automated planning for right-sided oropharaynx head and neck patients treated with IMRT and VMAT. We compare four versions of our dose prediction pipeline using a database of 54 training and 12 independent testing patients by evaluating 14 clinical dose evaluation criteria. Our preliminary results are promising and demonstrate that automated methods can generate comparable dose distributions to clinical. Overall, automated plans achieved an average of 0.6% higher dose for target coverage evaluation criteria, and 2.4% lower dose at the organs at risk criteria levels evaluated compared with clinical. There was no statistically significant difference detected in high-dose conformity between automated and clinical plans as measured by the conformation number. Automated plans achieved nine more unique criteria than clinical across the 12 patients tested and automated plans scored a significantly higher dose at the evaluation limit for two high-risk target coverage criteria and a significantly lower dose in one critical organ maximum dose. The novel dose prediction method with dose mimicking can generate complete treatment plans in 12-13 min without user interaction. It is a promising approach for fully automated treatment

Advanced health monitor for automated driving functions

NARCIS (Netherlands)

Mikovski Iotov, I.

2017-01-01

There is a trend in the automotive domain where driving functions are taken from the driver by automated driving functions. In order to guarantee the correct behavior of these auto-mated driving functions, the report introduces an Advanced Health Monitor that uses Tem-poral Logic and Probabilistic

Probabilistic Structural Analysis Program

Science.gov (United States)

Pai, Shantaram S.; Chamis, Christos C.; Murthy, Pappu L. N.; Stefko, George L.; Riha, David S.; Thacker, Ben H.; Nagpal, Vinod K.; Mital, Subodh K.

2010-01-01

NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.

Probabilistic Seismic Hazard Assessment Method for Nonlinear Soil Sites based on the Hazard Spectrum of Bedrock Sites

International Nuclear Information System (INIS)

Hahm, Dae Gi; Seo, Jeong Moon; Choi, In Kil

2011-01-01

For the probabilistic safety assessment of the nuclear power plants (NPP) under seismic events, the rational probabilistic seismic hazard estimation should be performed. Generally, the probabilistic seismic hazard of NPP site is represented by the uniform hazard spectrum (UHS) for the specific annual frequency. In most case, since that the attenuation equations were defined for the bedrock sites, the standard attenuation laws cannot be applied to the general soft soil sites. Hence, for the probabilistic estimation of the seismic hazard of soft soil sites, a methodology of probabilistic seismic hazard analysis (PSHA) coupled with nonlinear dynamic analyses of the soil column are required. Two methods are commonly used for the site response analysis considering the nonlinearity of sites. The one is the deterministic method and another is the probabilistic method. In the analysis of site response, there exist many uncertainty factors such as the variation of the magnitude and frequency contents of input ground motion, and material properties of soil deposits. Hence, nowadays, it is recommended that the adoption of the probabilistic method for the PSHA of soft soil deposits considering such uncertainty factors. In this study, we estimated the amplification factor of the surface of the soft soil deposits with considering the uncertainties of the input ground motions and the soil material properties. Then, we proposed the probabilistic methodology to evaluate the UHS of the soft soil site by multiplying the amplification factor to that of the bedrock site. The proposed method was applied to four typical target sites of KNGR and APR1400 NPP site categories

Optimization of automation: III. Development of optimization method for determining automation rate in nuclear power plants

International Nuclear Information System (INIS)

Lee, Seung Min; Kim, Jong Hyun; Kim, Man Cheol; Seong, Poong Hyun

2016-01-01

Highlights: • We propose an appropriate automation rate that enables the best human performance. • We analyze the shortest working time considering Situation Awareness Recovery (SAR). • The optimized automation rate is estimated by integrating the automation and ostracism rate estimation methods. • The process to derive the optimized automation rate is demonstrated through case studies. - Abstract: Automation has been introduced in various industries, including the nuclear field, because it is commonly believed that automation promises greater efficiency, lower workloads, and fewer operator errors through reducing operator errors and enhancing operator and system performance. However, the excessive introduction of automation has deteriorated operator performance due to the side effects of automation, which are referred to as Out-of-the-Loop (OOTL), and this is critical issue that must be resolved. Thus, in order to determine the optimal level of automation introduction that assures the best human operator performance, a quantitative method of optimizing the automation is proposed in this paper. In order to propose the optimization method for determining appropriate automation levels that enable the best human performance, the automation rate and ostracism rate, which are estimation methods that quantitatively analyze the positive and negative effects of automation, respectively, are integrated. The integration was conducted in order to derive the shortest working time through considering the concept of situation awareness recovery (SAR), which states that the automation rate with the shortest working time assures the best human performance. The process to derive the optimized automation rate is demonstrated through an emergency operation scenario-based case study. In this case study, four types of procedures are assumed through redesigning the original emergency operating procedure according to the introduced automation and ostracism levels. Using the

Formulation of probabilistic models of protein structure in atomic detail using the reference ratio method.

Science.gov (United States)

Valentin, Jan B; Andreetta, Christian; Boomsma, Wouter; Bottaro, Sandro; Ferkinghoff-Borg, Jesper; Frellsen, Jes; Mardia, Kanti V; Tian, Pengfei; Hamelryck, Thomas

2014-02-01

We propose a method to formulate probabilistic models of protein structure in atomic detail, for a given amino acid sequence, based on Bayesian principles, while retaining a close link to physics. We start from two previously developed probabilistic models of protein structure on a local length scale, which concern the dihedral angles in main chain and side chains, respectively. Conceptually, this constitutes a probabilistic and continuous alternative to the use of discrete fragment and rotamer libraries. The local model is combined with a nonlocal model that involves a small number of energy terms according to a physical force field, and some information on the overall secondary structure content. In this initial study we focus on the formulation of the joint model and the evaluation of the use of an energy vector as a descriptor of a protein's nonlocal structure; hence, we derive the parameters of the nonlocal model from the native structure without loss of generality. The local and nonlocal models are combined using the reference ratio method, which is a well-justified probabilistic construction. For evaluation, we use the resulting joint models to predict the structure of four proteins. The results indicate that the proposed method and the probabilistic models show considerable promise for probabilistic protein structure prediction and related applications. Copyright © 2013 Wiley Periodicals, Inc.

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method: Preprint

Energy Technology Data Exchange (ETDEWEB)

Wang, Qin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Florita, Anthony R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Krishnan, Venkat K [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cui, Mingjian [Univ. of Texas-Dallas, Richardson, TX (United States); Feng, Cong [Univ. of Texas-Dallas, Richardson, TX (United States); Wang, Zhenke [Univ. of Texas-Dallas, Richardson, TX (United States); Zhang, Jie [Univ. of Texas-Dallas, Richardson, TX (United States)

2017-08-31

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power, and they are currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.

Survey of probabilistic methods in safety and risk assessment for nuclear power plant licensing

International Nuclear Information System (INIS)

1984-04-01

After an overview about the goals and general methods of probabilistic approaches in nuclear safety the main features of probabilistic safety or risk assessment (PRA) methods are discussed. Mostly in practical applications not a full-fledged PRA is applied but rather various levels of analysis leading from unavailability assessment of systems over the more complex analysis of the probable core damage stages up to the assessment of the overall health effects on the total population from a certain practice. The various types of application are discussed in relation to their limitation and benefits for different stages of design or operation of nuclear power plants. This gives guidance for licensing staff to judge the usefulness of the various methods for their licensing decisions. Examples of the application of probabilistic methods in several countries are given. Two appendices on reliability analysis and on containment and consequence analysis provide some more details on these subjects. (author)

Advanced health monitor for automated driving functions

OpenAIRE

Mikovski Iotov, I.

2017-01-01

There is a trend in the automotive domain where driving functions are taken from the driver by automated driving functions. In order to guarantee the correct behavior of these auto-mated driving functions, the report introduces an Advanced Health Monitor that uses Tem-poral Logic and Probabilistic Analysis to indicate the system’s health.

Probabilistic Design Storm Method for Improved Flood Estimation in Ungauged Catchments

Science.gov (United States)

Berk, Mario; Å pačková, Olga; Straub, Daniel

2017-12-01

The design storm approach with event-based rainfall-runoff models is a standard method for design flood estimation in ungauged catchments. The approach is conceptually simple and computationally inexpensive, but the underlying assumptions can lead to flawed design flood estimations. In particular, the implied average recurrence interval (ARI) neutrality between rainfall and runoff neglects uncertainty in other important parameters, leading to an underestimation of design floods. The selection of a single representative critical rainfall duration in the analysis leads to an additional underestimation of design floods. One way to overcome these nonconservative approximations is the use of a continuous rainfall-runoff model, which is associated with significant computational cost and requires rainfall input data that are often not readily available. As an alternative, we propose a novel Probabilistic Design Storm method that combines event-based flood modeling with basic probabilistic models and concepts from reliability analysis, in particular the First-Order Reliability Method (FORM). The proposed methodology overcomes the limitations of the standard design storm approach, while utilizing the same input information and models without excessive computational effort. Additionally, the Probabilistic Design Storm method allows deriving so-called design charts, which summarize representative design storm events (combinations of rainfall intensity and other relevant parameters) for floods with different return periods. These can be used to study the relationship between rainfall and runoff return periods. We demonstrate, investigate, and validate the method by means of an example catchment located in the Bavarian Pre-Alps, in combination with a simple hydrological model commonly used in practice.

Integration of Probabilistic Exposure Assessment and Probabilistic Hazard Characterization

NARCIS (Netherlands)

Voet, van der H.; Slob, W.

2007-01-01

A method is proposed for integrated probabilistic risk assessment where exposure assessment and hazard characterization are both included in a probabilistic way. The aim is to specify the probability that a random individual from a defined (sub)population will have an exposure high enough to cause a

A Novel TRM Calculation Method by Probabilistic Concept

Science.gov (United States)

Audomvongseree, Kulyos; Yokoyama, Akihiko; Verma, Suresh Chand; Nakachi, Yoshiki

In a new competitive environment, it becomes possible for the third party to access a transmission facility. From this structure, to efficiently manage the utilization of the transmission network, a new definition about Available Transfer Capability (ATC) has been proposed. According to the North American ElectricReliability Council (NERC)’s definition, ATC depends on several parameters, i. e. Total Transfer Capability (TTC), Transmission Reliability Margin (TRM), and Capacity Benefit Margin (CBM). This paper is focused on the calculation of TRM which is one of the security margin reserved for any uncertainty of system conditions. The TRM calculation by probabilistic method is proposed in this paper. Based on the modeling of load forecast error and error in transmission line limitation, various cases of transmission transfer capability and its related probabilistic nature can be calculated. By consideration of the proposed concept of risk analysis, the appropriate required amount of TRM can be obtained. The objective of this research is to provide realistic information on the actual ability of the network which may be an alternative choice for system operators to make an appropriate decision in the competitive market. The advantages of the proposed method are illustrated by application to the IEEJ-WEST10 model system.

Probabilistic Structural Analysis Theory Development

Science.gov (United States)

Burnside, O. H.

1985-01-01

The objective of the Probabilistic Structural Analysis Methods (PSAM) project is to develop analysis techniques and computer programs for predicting the probabilistic response of critical structural components for current and future space propulsion systems. This technology will play a central role in establishing system performance and durability. The first year's technical activity is concentrating on probabilistic finite element formulation strategy and code development. Work is also in progress to survey critical materials and space shuttle mian engine components. The probabilistic finite element computer program NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) is being developed. The final probabilistic code will have, in the general case, the capability of performing nonlinear dynamic of stochastic structures. It is the goal of the approximate methods effort to increase problem solving efficiency relative to finite element methods by using energy methods to generate trial solutions which satisfy the structural boundary conditions. These approximate methods will be less computer intensive relative to the finite element approach.

Deliverable D74.2. Probabilistic analysis methods for support structures

DEFF Research Database (Denmark)

Gintautas, Tomas

2018-01-01

Relevant Description: Report describing the probabilistic analysis for offshore substructures and results attained. This includes comparison with experimental data and with conventional design. Specific targets: 1) Estimate current reliability level of support structures 2) Development of basis...... for probabilistic calculations and evaluation of reliability for offshore support structures (substructures) 3) Development of a probabilistic model for stiffness and strength of soil parameters and for modeling geotechnical load bearing capacity 4) Comparison between probabilistic analysis and deterministic...

Comparison of Statistical Post-Processing Methods for Probabilistic Wind Speed Forecasting

Science.gov (United States)

Han, Keunhee; Choi, JunTae; Kim, Chansoo

2018-02-01

In this study, the statistical post-processing methods that include bias-corrected and probabilistic forecasts of wind speed measured in PyeongChang, which is scheduled to host the 2018 Winter Olympics, are compared and analyzed to provide more accurate weather information. The six post-processing methods used in this study are as follows: mean bias-corrected forecast, mean and variance bias-corrected forecast, decaying averaging forecast, mean absolute bias-corrected forecast, and the alternative implementations of ensemble model output statistics (EMOS) and Bayesian model averaging (BMA) models, which are EMOS and BMA exchangeable models by assuming exchangeable ensemble members and simplified version of EMOS and BMA models. Observations for wind speed were obtained from the 26 stations in PyeongChang and 51 ensemble member forecasts derived from the European Centre for Medium-Range Weather Forecasts (ECMWF Directorate, 2012) that were obtained between 1 May 2013 and 18 March 2016. Prior to applying the post-processing methods, reliability analysis was conducted by using rank histograms to identify the statistical consistency of ensemble forecast and corresponding observations. Based on the results of our study, we found that the prediction skills of probabilistic forecasts of EMOS and BMA models were superior to the biascorrected forecasts in terms of deterministic prediction, whereas in probabilistic prediction, BMA models showed better prediction skill than EMOS. Even though the simplified version of BMA model exhibited best prediction skill among the mentioned six methods, the results showed that the differences of prediction skills between the versions of EMOS and BMA were negligible.

Simple probabilistic method for relative risk evaluation of nuclear terrorism events

International Nuclear Information System (INIS)

Zhang Songbai; Wu Jun

2006-01-01

On the basis of the event-tree and probability analysis methods, a probabilistic method of nuclear terrorism risk was built, and the risk of terrorism events was analyzed. With the statistical data for and hypothetical data for relative events, the relative probabilities of the four kinds of nuclear terrorism events were obtained, as well as the relative risks of these four kinds of nuclear terrorism events were calculated by using this probabilistic method. The illustrated case show that the descending sequence of damages from the four kinds of nuclear terrorism events for single event is as following: nuclear explosive and improvised nuclear explosive, nuclear facility attacked, and 'dirty bomb'. Under the hypothetical condition, the descending sequence of possibilities for the four kinds of nuclear terrorism events is as following: 'dirty bomb', nuclear facility attacked, improvised nuclear explosive and nuclear explosive, but the descending sequence of risks is as following: 'dirty bomb', improvised nuclear explosive, nuclear facility attacked, and nuclear explosive . (authors)

Probabilistic record linkage.

Science.gov (United States)

Sayers, Adrian; Ben-Shlomo, Yoav; Blom, Ashley W; Steele, Fiona

2016-06-01

Studies involving the use of probabilistic record linkage are becoming increasingly common. However, the methods underpinning probabilistic record linkage are not widely taught or understood, and therefore these studies can appear to be a 'black box' research tool. In this article, we aim to describe the process of probabilistic record linkage through a simple exemplar. We first introduce the concept of deterministic linkage and contrast this with probabilistic linkage. We illustrate each step of the process using a simple exemplar and describe the data structure required to perform a probabilistic linkage. We describe the process of calculating and interpreting matched weights and how to convert matched weights into posterior probabilities of a match using Bayes theorem. We conclude this article with a brief discussion of some of the computational demands of record linkage, how you might assess the quality of your linkage algorithm, and how epidemiologists can maximize the value of their record-linked research using robust record linkage methods. © The Author 2015; Published by Oxford University Press on behalf of the International Epidemiological Association.

Research on probabilistic assessment method based on the corroded pipeline assessment criteria

International Nuclear Information System (INIS)

Zhang Guangli; Luo, Jinheng; Zhao Xinwei; Zhang Hua; Zhang Liang; Zhang Yi

2012-01-01

Pipeline integrity assessments are performed using conventional deterministic approaches, even though there are many uncertainties about the parameters in the pipeline integrity assessment. In this paper, a probabilistic assessment method is provided for the gas pipeline with corrosion defects based on the current corroded pipe evaluation criteria, and the failure probability of corroded pipelines due to the uncertainties of loadings, material property and measurement accuracy is estimated using Monte-Carlo technique. Furthermore, the sensitivity analysis approach is introduced to rank the influence of various random variables to the safety of pipeline. And the method to determine the critical defect size based on acceptable failure probability is proposed. Highlights: ► The folias factor in pipeline corrosion assessment methods was analyzed. ► The probabilistic method was applied in corrosion assessment methods. ► The influence of assessment variables to the reliability of pipeline was ranked. ► The acceptable failure probability was used to determine the critical defect size.

Application of deterministic and probabilistic methods in replacement of nuclear systems

International Nuclear Information System (INIS)

Vianna Filho, Alfredo Marques

2007-01-01

The economic equipment replacement problem is one of the oldest questions in Production Engineering. On the one hand, new equipment are more attractive given their best performance, better reliability, lower maintenance cost, etc. New equipment, however, require a higher initial investment and thus a higher opportunity cost, and impose special training of the labor force. On the other hand, old equipment represent the other way around, with lower performance, lower reliability and specially higher maintenance costs but in contrast having lower financial, insurance, and opportunity costs. The weighting of all these costs can be made with the various methods presented. The aim of this paper is to discuss deterministic and probabilistic methods applied to the study of equipment replacement. Two types of distinct problems will be examined, substitution imposed by the wearing and substitution imposed by the failures. In order to solve the problem of nuclear system substitution imposed by wearing, deterministic methods are discussed. In order to solve the problem of nuclear system substitution imposed by failures, probabilistic methods are discussed. (author)

Application of the probabilistic approximate analysis method to a turbopump blade analysis. [for Space Shuttle Main Engine

Science.gov (United States)

Thacker, B. H.; Mcclung, R. C.; Millwater, H. R.

1990-01-01

An eigenvalue analysis of a typical space propulsion system turbopump blade is presented using an approximate probabilistic analysis methodology. The methodology was developed originally to investigate the feasibility of computing probabilistic structural response using closed-form approximate models. This paper extends the methodology to structures for which simple closed-form solutions do not exist. The finite element method will be used for this demonstration, but the concepts apply to any numerical method. The results agree with detailed analysis results and indicate the usefulness of using a probabilistic approximate analysis in determining efficient solution strategies.

Evaluating a method for automated rigid registration

DEFF Research Database (Denmark)

Darkner, Sune; Vester-Christensen, Martin; Larsen, Rasmus

2007-01-01

to point distance. T-test for common mean are used to determine the performance of the two methods (supported by a Wilcoxon signed rank test). The performance influence of sampling density, sampling quantity, and norms is analyzed using a similar method.......We evaluate a novel method for fully automated rigid registration of 2D manifolds in 3D space based on distance maps, the Gibbs sampler and Iterated Conditional Modes (ICM). The method is tested against the ICP considered as the gold standard for automated rigid registration. Furthermore...

Probabilistic method for evaluating reactivity margin of nuclear reactors

International Nuclear Information System (INIS)

Kaneko, Yoshihiko

1984-01-01

A probabilistic method is proposed that will permit in the design stage to estimate quantitatively the likelihood with which any or all design criteria applicable to a nuclear reactor are actually satisfied after its construction. The method is trially applied to the core reactivity balance problem of the experimental Very High Temperature Reactor, and calculations are performed on the probability with which a design study core will, upon construction, satisfy design criteria concerning (a) one rod stuck and (b) startup margin. The method should prove useful in making engineering judgments before approving reactor core design. (author)

A probabilistic method for testing and estimating selection differences between populations.

Science.gov (United States)

He, Yungang; Wang, Minxian; Huang, Xin; Li, Ran; Xu, Hongyang; Xu, Shuhua; Jin, Li

2015-12-01

Human populations around the world encounter various environmental challenges and, consequently, develop genetic adaptations to different selection forces. Identifying the differences in natural selection between populations is critical for understanding the roles of specific genetic variants in evolutionary adaptation. Although numerous methods have been developed to detect genetic loci under recent directional selection, a probabilistic solution for testing and quantifying selection differences between populations is lacking. Here we report the development of a probabilistic method for testing and estimating selection differences between populations. By use of a probabilistic model of genetic drift and selection, we showed that logarithm odds ratios of allele frequencies provide estimates of the differences in selection coefficients between populations. The estimates approximate a normal distribution, and variance can be estimated using genome-wide variants. This allows us to quantify differences in selection coefficients and to determine the confidence intervals of the estimate. Our work also revealed the link between genetic association testing and hypothesis testing of selection differences. It therefore supplies a solution for hypothesis testing of selection differences. This method was applied to a genome-wide data analysis of Han and Tibetan populations. The results confirmed that both the EPAS1 and EGLN1 genes are under statistically different selection in Han and Tibetan populations. We further estimated differences in the selection coefficients for genetic variants involved in melanin formation and determined their confidence intervals between continental population groups. Application of the method to empirical data demonstrated the outstanding capability of this novel approach for testing and quantifying differences in natural selection. © 2015 He et al.; Published by Cold Spring Harbor Laboratory Press.

An automatic formulation of inverse free second moment method for algebraic systems

International Nuclear Information System (INIS)

Shakshuki, Elhadi; Ponnambalam, Kumaraswamy

2002-01-01

In systems with probabilistic uncertainties, an estimation of reliability requires at least the first two moments. In this paper, we focus on probabilistic analysis of linear systems. The important tasks in this analysis are the formulation and the automation of the moment equations. The main objective of the formulation is to provide at least means and variances of the output variables with at least a second-order accuracy. The objective of the automation is to reduce the storage and computational complexities required for implementing (automating) those formulations. This paper extends the recent work done to calculate the first two moments of a set of random algebraic linear equations by developing a stamping procedure to facilitate its automation. The new method has an additional advantage of being able to solve problems when the mean matrix of a system is singular. Lastly, from storage and computational complexities and accuracy point of view, a comparison between the new method and another recently developed first order second moment method is made with numerical examples

Optimization-based Method for Automated Road Network Extraction

International Nuclear Information System (INIS)

Xiong, D

2001-01-01

Automated road information extraction has significant applicability in transportation. It provides a means for creating, maintaining, and updating transportation network databases that are needed for purposes ranging from traffic management to automated vehicle navigation and guidance. This paper is to review literature on the subject of road extraction and to describe a study of an optimization-based method for automated road network extraction

Human reliability analysis methods for probabilistic safety assessment

International Nuclear Information System (INIS)

Pyy, P.

2000-11-01

Human reliability analysis (HRA) of a probabilistic safety assessment (PSA) includes identifying human actions from safety point of view, modelling the most important of them in PSA models, and assessing their probabilities. As manifested by many incidents and studies, human actions may have both positive and negative effect on safety and economy. Human reliability analysis is one of the areas of probabilistic safety assessment (PSA) that has direct applications outside the nuclear industry. The thesis focuses upon developments in human reliability analysis methods and data. The aim is to support PSA by extending the applicability of HRA. The thesis consists of six publications and a summary. The summary includes general considerations and a discussion about human actions in the nuclear power plant (NPP) environment. A condensed discussion about the results of the attached publications is then given, including new development in methods and data. At the end of the summary part, the contribution of the publications to good practice in HRA is presented. In the publications, studies based on the collection of data on maintenance-related failures, simulator runs and expert judgement are presented in order to extend the human reliability analysis database. Furthermore, methodological frameworks are presented to perform a comprehensive HRA, including shutdown conditions, to study reliability of decision making, and to study the effects of wrong human actions. In the last publication, an interdisciplinary approach to analysing human decision making is presented. The publications also include practical applications of the presented methodological frameworks. (orig.)

Development of a localized probabilistic sensitivity method to determine random variable regional importance

International Nuclear Information System (INIS)

Millwater, Harry; Singh, Gulshan; Cortina, Miguel

2012-01-01

There are many methods to identify the important variable out of a set of random variables, i.e., “inter-variable” importance; however, to date there are no comparable methods to identify the “region” of importance within a random variable, i.e., “intra-variable” importance. Knowledge of the critical region of an input random variable (tail, near-tail, and central region) can provide valuable information towards characterizing, understanding, and improving a model through additional modeling or testing. As a result, an intra-variable probabilistic sensitivity method was developed and demonstrated for independent random variables that computes the partial derivative of a probabilistic response with respect to a localized perturbation in the CDF values of each random variable. These sensitivities are then normalized in absolute value with respect to the largest sensitivity within a distribution to indicate the region of importance. The methodology is implemented using the Score Function kernel-based method such that existing samples can be used to compute sensitivities for negligible cost. Numerical examples demonstrate the accuracy of the method through comparisons with finite difference and numerical integration quadrature estimates. - Highlights: ► Probabilistic sensitivity methodology. ► Determines the “region” of importance within random variables such as left tail, near tail, center, right tail, etc. ► Uses the Score Function approach to reuse the samples, hence, negligible cost. ► No restrictions on the random variable types or limit states.

Utilization of probabilistic methods for evaluating the safety of PWRs built in France

International Nuclear Information System (INIS)

Queniart, D.; Brisbois, J.; Lanore, J.M.

1985-01-01

Firstly, it is recalled that, in France, PWRs are designed on a deterministic basis by studying the consequences of a limited number of conventional incidents whose estimated frequency is specified in order-of-magnitude terms and for which it is shown that the consequences, for each category of frequency, predominate over those of the other situations in the same category. These situations are called dimensioning situations. The paper then describes the use made of probabilistic methods. External attacks and loss of redundant systems are examined in particular. A probabilistic approach is in fact well suited to the evaluation of risks due, among other things, to aircraft crashes and the industrial environment. Analysis of the reliability of redundant systems has shown that, in the light of the overall risk assessment objective, their loss should be examined with a view to instituting counteraction to reduce the risks associated with such loss (particularly the introduction of special control procedures). Probabilistic methods are used to evaluate the effectiveness of the counteraction proposed and such a study has been carried out for total loss of electric power supply. Finally, the probabilistic study of hazard initiated post factum by the French safety authorities for the standardized 900 MW(e) power units is described. The study, which is not yet complete, will serve as the basis for a permanent safety analysis tool taking into account control procedures and the total operating experience acquired using these power units. (author)

Application of Fragment Ion Information as Further Evidence in Probabilistic Compound Screening Using Bayesian Statistics and Machine Learning: A Leap Toward Automation.

Science.gov (United States)

Woldegebriel, Michael; Zomer, Paul; Mol, Hans G J; Vivó-Truyols, Gabriel

2016-08-02

In this work, we introduce an automated, efficient, and elegant model to combine all pieces of evidence (e.g., expected retention times, peak shapes, isotope distributions, fragment-to-parent ratio) obtained from liquid chromatography-tandem mass spectrometry (LC-MS/MS/MS) data for screening purposes. Combining all these pieces of evidence requires a careful assessment of the uncertainties in the analytical system as well as all possible outcomes. To-date, the majority of the existing algorithms are highly dependent on user input parameters. Additionally, the screening process is tackled as a deterministic problem. In this work we present a Bayesian framework to deal with the combination of all these pieces of evidence. Contrary to conventional algorithms, the information is treated in a probabilistic way, and a final probability assessment of the presence/absence of a compound feature is computed. Additionally, all the necessary parameters except the chromatographic band broadening for the method are learned from the data in training and learning phase of the algorithm, avoiding the introduction of a large number of user-defined parameters. The proposed method was validated with a large data set and has shown improved sensitivity and specificity in comparison to a threshold-based commercial software package.

A two-stage inexact joint-probabilistic programming method for air quality management under uncertainty.

Science.gov (United States)

Lv, Y; Huang, G H; Li, Y P; Yang, Z F; Sun, W

2011-03-01

A two-stage inexact joint-probabilistic programming (TIJP) method is developed for planning a regional air quality management system with multiple pollutants and multiple sources. The TIJP method incorporates the techniques of two-stage stochastic programming, joint-probabilistic constraint programming and interval mathematical programming, where uncertainties expressed as probability distributions and interval values can be addressed. Moreover, it can not only examine the risk of violating joint-probability constraints, but also account for economic penalties as corrective measures against any infeasibility. The developed TIJP method is applied to a case study of a regional air pollution control problem, where the air quality index (AQI) is introduced for evaluation of the integrated air quality management system associated with multiple pollutants. The joint-probability exists in the environmental constraints for AQI, such that individual probabilistic constraints for each pollutant can be efficiently incorporated within the TIJP model. The results indicate that useful solutions for air quality management practices have been generated; they can help decision makers to identify desired pollution abatement strategies with minimized system cost and maximized environmental efficiency. Copyright © 2010 Elsevier Ltd. All rights reserved.

14th International Probabilistic Workshop

CERN Document Server

Taerwe, Luc; Proske, Dirk

2017-01-01

This book presents the proceedings of the 14th International Probabilistic Workshop that was held in Ghent, Belgium in December 2016. Probabilistic methods are currently of crucial importance for research and developments in the field of engineering, which face challenges presented by new materials and technologies and rapidly changing societal needs and values. Contemporary needs related to, for example, performance-based design, service-life design, life-cycle analysis, product optimization, assessment of existing structures and structural robustness give rise to new developments as well as accurate and practically applicable probabilistic and statistical engineering methods to support these developments. These proceedings are a valuable resource for anyone interested in contemporary developments in the field of probabilistic engineering applications.

Review of probabilistic pollen-climate transfer methods

Science.gov (United States)

Ohlwein, Christian; Wahl, Eugene R.

2012-01-01

Pollen-climate transfer methods are reviewed from a Bayesian perspective and with a special focus on the formulation of uncertainties. This approach is motivated by recent developments of spatial multi-proxy Bayesian hierarchical models (BHM), which allow synthesizing local reconstructions from different proxies for a spatially complete picture of past climate. In order to enhance the pollen realism in these models we try to bridge the gap between spatial statistics and paleoclimatology and show how far classical pollen-climate transfer concepts such as regression methods, mutual climatic range, modern analogues, plant functional types, and biomes can be understood in novel ways by refining the data models used in BHMs. As a case study, we discuss modeling of uncertainty by introducing a new probabilistic pollen ratio model, which is a simplified variation of the modern analogue technique (MAT) including the concept of response surfaces and designed for later inclusion in a spatial multiproxy BHM. Applications to fossil pollen data from varved sediments in three nearby lakes in west-central Wisconsin, USA and for a Holocene fossil pollen record from southern California, USA provide local climate reconstructions of summer temperature for the past millennium and the Holocene respectively. The performance of the probabilistic model is generally similar in comparison to MAT-derived reconstructions using the same data. Furthermore, the combination of co-location and precise dating for the three fossil sites in Wisconsin allows us to study the issue of site-specific uncertainty and to test the assumption of ergodicity in a real-world example. A multivariate ensemble kernel dressing approach derived from the post-processing of climate simulations reveals that the overall interpretation based on the individual reconstructions remains essentially unchanged, but the single-site reconstructions underestimate the overall uncertainty.

Use of probabilistic methods for analysis of cost and duration uncertainties in a decision analysis framework

International Nuclear Information System (INIS)

Boak, D.M.; Painton, L.

1995-01-01

Probabilistic forecasting techniques have been used in many risk assessment and performance assessment applications on radioactive waste disposal projects such as Yucca Mountain and the Waste Isolation Pilot Plant (WIPP). Probabilistic techniques such as Monte Carlo and Latin Hypercube sampling methods are routinely used to treat uncertainties in physical parameters important in simulating radionuclide transport in a coupled geohydrologic system and assessing the ability of that system to comply with regulatory release limits. However, the use of probabilistic techniques in the treatment of uncertainties in the cost and duration of programmatic alternatives on risk and performance assessment projects is less common. Where significant uncertainties exist and where programmatic decisions must be made despite existing uncertainties, probabilistic techniques may yield important insights into decision options, especially when used in a decision analysis framework and when properly balanced with deterministic analyses. For relatively simple evaluations, these types of probabilistic evaluations can be made using personal computer-based software

Probabilistic Power Flow Method Considering Continuous and Discrete Variables

Directory of Open Access Journals (Sweden)

Xuexia Zhang

2017-04-01

Full Text Available This paper proposes a probabilistic power flow (PPF method considering continuous and discrete variables (continuous and discrete power flow, CDPF for power systems. The proposed method—based on the cumulant method (CM and multiple deterministic power flow (MDPF calculations—can deal with continuous variables such as wind power generation (WPG and loads, and discrete variables such as fuel cell generation (FCG. In this paper, continuous variables follow a normal distribution (loads or a non-normal distribution (WPG, and discrete variables follow a binomial distribution (FCG. Through testing on IEEE 14-bus and IEEE 118-bus power systems, the proposed method (CDPF has better accuracy compared with the CM, and higher efficiency compared with the Monte Carlo simulation method (MCSM.

Probabilistic finite elements for fracture mechanics

Science.gov (United States)

Besterfield, Glen

1988-01-01

The probabilistic finite element method (PFEM) is developed for probabilistic fracture mechanics (PFM). A finite element which has the near crack-tip singular strain embedded in the element is used. Probabilistic distributions, such as expectation, covariance and correlation stress intensity factors, are calculated for random load, random material and random crack length. The method is computationally quite efficient and can be expected to determine the probability of fracture or reliability.

A General Framework for Probabilistic Characterizing Formulae

DEFF Research Database (Denmark)

Sack, Joshua; Zhang, Lijun

2012-01-01

Recently, a general framework on characteristic formulae was proposed by Aceto et al. It offers a simple theory that allows one to easily obtain characteristic formulae of many non-probabilistic behavioral relations. Our paper studies their techniques in a probabilistic setting. We provide...... a general method for determining characteristic formulae of behavioral relations for probabilistic automata using fixed-point probability logics. We consider such behavioral relations as simulations and bisimulations, probabilistic bisimulations, probabilistic weak simulations, and probabilistic forward...

Optimisation of test and maintenance based on probabilistic methods

International Nuclear Information System (INIS)

Cepin, M.

2001-01-01

This paper presents a method, which based on models and results of probabilistic safety assessment, minimises the nuclear power plant risk by optimisation of arrangement of safety equipment outages. The test and maintenance activities of the safety equipment are timely arranged, so the classical static fault tree models are extended with the time requirements to be capable to model real plant states. A house event matrix is used, which enables modelling of the equipment arrangements through the discrete points of time. The result of the method is determination of such configuration of equipment outages, which result in the minimal risk. Minimal risk is represented by system unavailability. (authors)

Development of a regional ensemble prediction method for probabilistic weather prediction

International Nuclear Information System (INIS)

Nohara, Daisuke; Tamura, Hidetoshi; Hirakuchi, Hiromaru

2015-01-01

A regional ensemble prediction method has been developed to provide probabilistic weather prediction using a numerical weather prediction model. To obtain consistent perturbations with the synoptic weather pattern, both of initial and lateral boundary perturbations were given by differences between control and ensemble member of the Japan Meteorological Agency (JMA)'s operational one-week ensemble forecast. The method provides a multiple ensemble member with a horizontal resolution of 15 km for 48-hour based on a downscaling of the JMA's operational global forecast accompanied with the perturbations. The ensemble prediction was examined in the case of heavy snow fall event in Kanto area on January 14, 2013. The results showed that the predictions represent different features of high-resolution spatiotemporal distribution of precipitation affected by intensity and location of extra-tropical cyclone in each ensemble member. Although the ensemble prediction has model bias of mean values and variances in some variables such as wind speed and solar radiation, the ensemble prediction has a potential to append a probabilistic information to a deterministic prediction. (author)

Automated installation methods for photovoltaic arrays

Science.gov (United States)

Briggs, R.; Daniels, A.; Greenaway, R.; Oster, J., Jr.; Racki, D.; Stoeltzing, R.

1982-11-01

Since installation expenses constitute a substantial portion of the cost of a large photovoltaic power system, methods for reduction of these costs were investigated. The installation of the photovoltaic arrays includes all areas, starting with site preparation (i.e., trenching, wiring, drainage, foundation installation, lightning protection, grounding and installation of the panel) and concluding with the termination of the bus at the power conditioner building. To identify the optimum combination of standard installation procedures and automated/mechanized techniques, the installation process was investigated including the equipment and hardware available, the photovoltaic array structure systems and interfaces, and the array field and site characteristics. Preliminary designs of hardware for both the standard installation method, the automated/mechanized method, and a mix of standard installation procedures and mechanized procedures were identified to determine which process effectively reduced installation costs. In addition, costs associated with each type of installation method and with the design, development and fabrication of new installation hardware were generated.

Validation of programmable industrial automation systems for safety critical applications in NPP's; dynamic testing

International Nuclear Information System (INIS)

Haapanen, P.; Korhonen, J.

1995-01-01

The safety assessment of programmable automation systems cannot be totally be based on conventional probabilistic methods because of the difficulties in quantification of the reliability of the software as well as the hardware. Additional means shall therefore be used to gain more confidence on the system dependability. One central confidence building measure is the independent dynamic testing of the completed system. An automated test harness is needed to run the required large amount of test cases in a restricted time span. This paper describes a prototype dynamic testing harness for programmable digital systems developed at VTT. (author). 12 refs, 2 figs, 2 tabs

Probabilistic finite elements

Science.gov (United States)

Belytschko, Ted; Wing, Kam Liu

1987-01-01

In the Probabilistic Finite Element Method (PFEM), finite element methods have been efficiently combined with second-order perturbation techniques to provide an effective method for informing the designer of the range of response which is likely in a given problem. The designer must provide as input the statistical character of the input variables, such as yield strength, load magnitude, and Young's modulus, by specifying their mean values and their variances. The output then consists of the mean response and the variance in the response. Thus the designer is given a much broader picture of the predicted performance than with simply a single response curve. These methods are applicable to a wide class of problems, provided that the scale of randomness is not too large and the probabilistic density functions possess decaying tails. By incorporating the computational techniques we have developed in the past 3 years for efficiency, the probabilistic finite element methods are capable of handling large systems with many sources of uncertainties. Sample results for an elastic-plastic ten-bar structure and an elastic-plastic plane continuum with a circular hole subject to cyclic loadings with the yield stress on the random field are given.

Probabilistic assessment methods as a tool for developing nations to make safety decisions

International Nuclear Information System (INIS)

Gumley, P.; Inamdar, S.V.

1985-01-01

This paper advocates the use of probabilistic safety assessment methods in making safety decisions. It discusses the question of adequate safety - what it means to a country buying a nuclear power plant, and how probabilistic safety assessment studies of the reference plant can be used for ensuring this adequate safety. It is proposed that adequate safety means ensuring that the plant would behave, in accident conditions, in a manner similar to the way it is expected to behave were it in the country of origin. For this one needs to know how the plant responds under somewhat altered conditions. These altered conditions can arise from such factors as varying reliability of electrical grids, different manufacturing technology, local systems design and operator capability. In the design of nuclear power plants, the traditional approach to safety has led to the belief that availability and effectiveness of safety systems alone are all that is required to ensure plant safety. This belief can result in design oversights leading to potential problems arising from the power production systems and the service systems. Participation by the buying country in the design of such systems, and understanding the safety implications thereof, can be facilitated by probabilistic safety assessment methods. This philosophy is illustrated in this paper by examples. (author)

A probabilistic Hu-Washizu variational principle

Science.gov (United States)

Liu, W. K.; Belytschko, T.; Besterfield, G. H.

1987-01-01

A Probabilistic Hu-Washizu Variational Principle (PHWVP) for the Probabilistic Finite Element Method (PFEM) is presented. This formulation is developed for both linear and nonlinear elasticity. The PHWVP allows incorporation of the probabilistic distributions for the constitutive law, compatibility condition, equilibrium, domain and boundary conditions into the PFEM. Thus, a complete probabilistic analysis can be performed where all aspects of the problem are treated as random variables and/or fields. The Hu-Washizu variational formulation is available in many conventional finite element codes thereby enabling the straightforward inclusion of the probabilistic features into present codes.

Probabilistic studies of accident sequences

International Nuclear Information System (INIS)

Villemeur, A.; Berger, J.P.

1986-01-01

For several years, Electricite de France has carried out probabilistic assessment of accident sequences for nuclear power plants. In the framework of this program many methods were developed. As the interest in these studies was increasing and as adapted methods were developed, Electricite de France has undertaken a probabilistic safety assessment of a nuclear power plant [fr

Deployment Analysis of a Simple Tape-Spring Hinge Using Probabilistic Methods

Science.gov (United States)

Lyle, Karen H.; Horta, Lucas G.

2012-01-01

Acceptance of new deployable structures architectures and concepts requires validated design methods to minimize the expense involved with technology validation flight testing. Deployable concepts for large lightweight spacecraft include booms, antennae, and masts. This paper explores the implementation of probabilistic methods in the design process for the deployment of a strain-energy mechanism, specifically a simple tape-spring hinge. Strain-energy mechanisms are attractive for deployment in very lightweight systems because they do not require the added mass and complexity associated with motors and controllers. However, designers are hesitant to include free deployment, strain-energy mechanisms because of the potential for uncontrolled behavior. In the example presented here, the tapespring cross-sectional dimensions have been varied and a target displacement during deployment has been selected as the design metric. Specifically, the tape-spring should reach the final position in the shortest time with the minimal amount of overshoot and oscillations. Surrogate models have been used to reduce computational expense. Parameter values to achieve the target response have been computed and used to demonstrate the approach. Based on these results, the application of probabilistic methods for design of a tape-spring hinge has shown promise as a means of designing strain-energy components for more complex space concepts.

Patterns of probabilistic evaluation of the maintenance; Patrones de Evaluacion Probabilista del Mantenimiento

Energy Technology Data Exchange (ETDEWEB)

Torres V, A.; Rivero O, J.J. [Dpto. Ingenieria Nuclear, Instituto Superior de Tecnologias y Ciencias Aplicadas, Ave. Salvador Allende y Luaces, Quinta de los Molinos, Plaza, Ciudad Habana (Cuba)]. e-mail: atorres@fctn.isctn.edu.cu

2004-07-01

The Boolean equation represented by the minimum sets of court at level of a system or of all one Probabilistic safety analysis (APS) it has been used for to evaluate the output configurations of service of teams during the exploitation. It has been carried out through applications of APS for the optimization of operational regimes. The obtaining of such boolean equations as demands of a process of high mathematical complexity for what exhaustive studies are required, even for the application of their results. The important advantages for the maintenance that they obtain of these applications they require the development of methodologies that bring near these optimization methods to the systems of management of the maintenance, and not facilitate their use for a personnel specialized in the probabilistic topics. The article presents a methodology for the preparation, solution and utilization of the results of the fault tree leaving of technological outlines. This algorithm has been automated through the MOSEG code Win to Ver 1.0 (Author)

Suggestions for an improved HRA method for use in Probabilistic Safety Assessment

International Nuclear Information System (INIS)

Parry, Gareth W.

1995-01-01

This paper discusses why an improved Human Reliability Analysis (HRA) approach for use in Probabilistic Safety Assessments (PSAs) is needed, and proposes a set of requirements on the improved HRA method. The constraints imposed by the need to embed the approach into the PSA methodology are discussed. One approach to laying the foundation for an improved method, using models from the cognitive psychology and behavioral science disciplines, is outlined

A study on the weather sampling method for probabilistic consequence analysis

International Nuclear Information System (INIS)

Oh, Hae Cheol

1996-02-01

The main task of probabilistic accident consequence analysis model is to predict the radiological situation and to provide a reliable quantitative data base for making decisions on countermeasures. The magnitude of accident consequence is depended on the characteristic of the accident and the weather coincident. In probabilistic accident consequence analysis, it is necessary to repeat the atmospheric dispersion calculation with several hundreds of weather sequences to predict the full distribution of consequences which may occur following a postulated accident release. It is desirable to select a representative sample of weather sequences from a meteorological record which is typical of the area over which the released radionuclides will disperse and which spans a sufficiently long period. The selection process is done by means of sampling techniques from a full year of hourly weather data characteristic of the plant site. In this study, the proposed Weighted importance sampling method selects proportional to the each bin size to closely approximate the true frequency distribution of weather condition at the site. The Weighted importance sampling method results in substantially less sampling uncertainty than the previous technique. The proposed technique can result in improve confidence in risk estimates

Automated cloning methods.; TOPICAL

International Nuclear Information System (INIS)

Collart, F.

2001-01-01

Argonne has developed a series of automated protocols to generate bacterial expression clones by using a robotic system designed to be used in procedures associated with molecular biology. The system provides plate storage, temperature control from 4 to 37 C at various locations, and Biomek and Multimek pipetting stations. The automated system consists of a robot that transports sources from the active station on the automation system. Protocols for the automated generation of bacterial expression clones can be grouped into three categories (Figure 1). Fragment generation protocols are initiated on day one of the expression cloning procedure and encompass those protocols involved in generating purified coding region (PCR)

The Application of the Probabilistic Collocation Method to a Transonic Axial Flow Compressor

NARCIS (Netherlands)

Loeven, G.J.A.; Bijl, H.

2010-01-01

In this paper the Probabilistic Collocation method is used for uncertainty quantification of operational uncertainties in a transonic axial flow compressor (i.e. NASA Rotor 37). Compressor rotors are components of a gas turbine that are highly sensitive to operational and geometrical uncertainties.

Structural system reliability calculation using a probabilistic fault tree analysis method

Science.gov (United States)

Torng, T. Y.; Wu, Y.-T.; Millwater, H. R.

1992-01-01

The development of a new probabilistic fault tree analysis (PFTA) method for calculating structural system reliability is summarized. The proposed PFTA procedure includes: developing a fault tree to represent the complex structural system, constructing an approximation function for each bottom event, determining a dominant sampling sequence for all bottom events, and calculating the system reliability using an adaptive importance sampling method. PFTA is suitable for complicated structural problems that require computer-intensive computer calculations. A computer program has been developed to implement the PFTA.

An integral approach to the use of probabilistic risk assessment methods

International Nuclear Information System (INIS)

Schwarzblat, M.; Arellano, J.

1987-01-01

In this chapter some of the work developed at the Instituto de Investigaciones Electricas in the area of probabilistic risk analysis are presented. In this area, work has been basically focused in the following directions: development and implementation of methods, and applications to real systems. The first part of this paper describes the area of methods development and implementation, presenting an integrated package of computer programs for fault tree analysis. In the second part some of the most important applications developed for real systems are presented. (author)

Validation of programmable industrial automation systems for safety critical applications in NPP's dynamic testing

International Nuclear Information System (INIS)

Haapanen, P.; Korhonen, J.

1995-01-01

The safety assessment of programmable automation systems can not totally be based on conventional probabilistic methods because of the difficulties in quantification of the reliability of the software as well as the hardware. Additional means shall therefore be used to gain more confidence on the system dependability. One central confidence building measure is the independent dynamic testing of the completed system. An automated test harness is needed to run the required large amount of test cases in a restricted time span. The prototype dynamic testing harness for programmable digital systems developed at the Technical Research Centre of Finland (VTT) is described in the presentation. (12 refs., 2 figs., 2 tabs.)

Failure analysis of the cement mantle in total hip arthroplasty with an efficient probabilistic method.

Science.gov (United States)

Kaymaz, Irfan; Bayrak, Ozgu; Karsan, Orhan; Celik, Ayhan; Alsaran, Akgun

2014-04-01

Accurate prediction of long-term behaviour of cemented hip implants is very important not only for patient comfort but also for elimination of any revision operation due to failure of implants. Therefore, a more realistic computer model was generated and then used for both deterministic and probabilistic analyses of the hip implant in this study. The deterministic failure analysis was carried out for the most common failure states of the cement mantle. On the other hand, most of the design parameters of the cemented hip are inherently uncertain quantities. Therefore, the probabilistic failure analysis was also carried out considering the fatigue failure of the cement mantle since it is the most critical failure state. However, the probabilistic analysis generally requires large amount of time; thus, a response surface method proposed in this study was used to reduce the computation time for the analysis of the cemented hip implant. The results demonstrate that using an efficient probabilistic approach can significantly reduce the computation time for the failure probability of the cement from several hours to minutes. The results also show that even the deterministic failure analyses do not indicate any failure of the cement mantle with high safety factors, the probabilistic analysis predicts the failure probability of the cement mantle as 8%, which must be considered during the evaluation of the success of the cemented hip implants.

Strategic Team AI Path Plans: Probabilistic Pathfinding

Directory of Open Access Journals (Sweden)

Tng C. H. John

2008-01-01

Full Text Available This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002, in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006. We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.

Development of An Optimization Method for Determining Automation Rate in Nuclear Power Plants

International Nuclear Information System (INIS)

Lee, Seung Min; Seong, Poong Hyun; Kim, Jong Hyun

2014-01-01

Since automation was introduced in various industrial fields, it has been known that automation provides positive effects like greater efficiency and fewer human errors, and negative effect defined as out-of-the-loop (OOTL). Thus, before introducing automation in nuclear field, the estimation of the positive and negative effects of automation on human operators should be conducted. In this paper, by focusing on CPS, the optimization method to find an appropriate proportion of automation is suggested by integrating the suggested cognitive automation rate and the concepts of the level of ostracism. The cognitive automation rate estimation method was suggested to express the reduced amount of human cognitive loads, and the level of ostracism was suggested to express the difficulty in obtaining information from the automation system and increased uncertainty of human operators' diagnosis. The maximized proportion of automation that maintains the high level of attention for monitoring the situation is derived by an experiment, and the automation rate is estimated by the suggested automation rate estimation method. It is expected to derive an appropriate inclusion proportion of the automation system avoiding the OOTL problem and having maximum efficacy at the same time

Applying probabilistic methods for assessments and calculations for accident prevention

International Nuclear Information System (INIS)

Anon.

1984-01-01

The guidelines for the prevention of accidents require plant design-specific and radioecological calculations to be made in order to show that maximum acceptable expsoure values will not be exceeded in case of an accident. For this purpose, main parameters affecting the accident scenario have to be determined by probabilistic methods. This offers the advantage that parameters can be quantified on the basis of unambigious and realistic criteria, and final results can be defined in terms of conservativity. (DG) [de

Probabilistic methods in fire-risk analysis

International Nuclear Information System (INIS)

Brandyberry, M.D.

1989-01-01

The first part of this work outlines a method for assessing the frequency of ignition of a consumer product in a building and shows how the method would be used in an example scenario utilizing upholstered furniture as the product and radiant auxiliary heating devices (electric heaters, wood stoves) as the ignition source. Deterministic thermal models of the heat-transport processes are coupled with parameter uncertainty analysis of the models and with a probabilistic analysis of the events involved in a typical scenario. This leads to a distribution for the frequency of ignition for the product. In second part, fire-risk analysis as currently used in nuclear plants is outlines along with a discussion of the relevant uncertainties. The use of the computer code COMPBRN is discussed for use in the fire-growth analysis along with the use of response-surface methodology to quantify uncertainties in the code's use. Generalized response surfaces are developed for temperature versus time for a cable tray, as well as a surface for the hot gas layer temperature and depth for a room of arbitrary geometry within a typical nuclear power plant compartment. These surfaces are then used to simulate the cable tray damage time in a compartment fire experiment

Compression of Probabilistic XML documents

NARCIS (Netherlands)

Veldman, Irma

2009-01-01

Probabilistic XML (PXML) files resulting from data integration can become extremely large, which is undesired. For XML there are several techniques available to compress the document and since probabilistic XML is in fact (a special form of) XML, it might benefit from these methods even more. In

RNA-PAIRS: RNA probabilistic assignment of imino resonance shifts

International Nuclear Information System (INIS)

Bahrami, Arash; Clos, Lawrence J.; Markley, John L.; Butcher, Samuel E.; Eghbalnia, Hamid R.

2012-01-01

The significant biological role of RNA has further highlighted the need for improving the accuracy, efficiency and the reach of methods for investigating RNA structure and function. Nuclear magnetic resonance (NMR) spectroscopy is vital to furthering the goals of RNA structural biology because of its distinctive capabilities. However, the dispersion pattern in the NMR spectra of RNA makes automated resonance assignment, a key step in NMR investigation of biomolecules, remarkably challenging. Herein we present RNA Probabilistic Assignment of Imino Resonance Shifts (RNA-PAIRS), a method for the automated assignment of RNA imino resonances with synchronized verification and correction of predicted secondary structure. RNA-PAIRS represents an advance in modeling the assignment paradigm because it seeds the probabilistic network for assignment with experimental NMR data, and predicted RNA secondary structure, simultaneously and from the start. Subsequently, RNA-PAIRS sets in motion a dynamic network that reverberates between predictions and experimental evidence in order to reconcile and rectify resonance assignments and secondary structure information. The procedure is halted when assignments and base-parings are deemed to be most consistent with observed crosspeaks. The current implementation of RNA-PAIRS uses an initial peak list derived from proton-nitrogen heteronuclear multiple quantum correlation ( 1 H– 15 N 2D HMQC) and proton–proton nuclear Overhauser enhancement spectroscopy ( 1 H– 1 H 2D NOESY) experiments. We have evaluated the performance of RNA-PAIRS by using it to analyze NMR datasets from 26 previously studied RNAs, including a 111-nucleotide complex. For moderately sized RNA molecules, and over a range of comparatively complex structural motifs, the average assignment accuracy exceeds 90%, while the average base pair prediction accuracy exceeded 93%. RNA-PAIRS yielded accurate assignments and base pairings consistent with imino resonances for a

RNA-PAIRS: RNA probabilistic assignment of imino resonance shifts

Energy Technology Data Exchange (ETDEWEB)

Bahrami, Arash; Clos, Lawrence J.; Markley, John L.; Butcher, Samuel E. [National Magnetic Resonance Facility at Madison (United States); Eghbalnia, Hamid R., E-mail: eghbalhd@uc.edu [University of Cincinnati, Department of Molecular and Cellular Physiology (United States)

2012-04-15

The significant biological role of RNA has further highlighted the need for improving the accuracy, efficiency and the reach of methods for investigating RNA structure and function. Nuclear magnetic resonance (NMR) spectroscopy is vital to furthering the goals of RNA structural biology because of its distinctive capabilities. However, the dispersion pattern in the NMR spectra of RNA makes automated resonance assignment, a key step in NMR investigation of biomolecules, remarkably challenging. Herein we present RNA Probabilistic Assignment of Imino Resonance Shifts (RNA-PAIRS), a method for the automated assignment of RNA imino resonances with synchronized verification and correction of predicted secondary structure. RNA-PAIRS represents an advance in modeling the assignment paradigm because it seeds the probabilistic network for assignment with experimental NMR data, and predicted RNA secondary structure, simultaneously and from the start. Subsequently, RNA-PAIRS sets in motion a dynamic network that reverberates between predictions and experimental evidence in order to reconcile and rectify resonance assignments and secondary structure information. The procedure is halted when assignments and base-parings are deemed to be most consistent with observed crosspeaks. The current implementation of RNA-PAIRS uses an initial peak list derived from proton-nitrogen heteronuclear multiple quantum correlation ({sup 1}H-{sup 15}N 2D HMQC) and proton-proton nuclear Overhauser enhancement spectroscopy ({sup 1}H-{sup 1}H 2D NOESY) experiments. We have evaluated the performance of RNA-PAIRS by using it to analyze NMR datasets from 26 previously studied RNAs, including a 111-nucleotide complex. For moderately sized RNA molecules, and over a range of comparatively complex structural motifs, the average assignment accuracy exceeds 90%, while the average base pair prediction accuracy exceeded 93%. RNA-PAIRS yielded accurate assignments and base pairings consistent with imino

An automated method for the layup of fiberglass fabric

Science.gov (United States)

Zhu, Siqi

This dissertation presents an automated composite fabric layup solution based on a new method to deform fiberglass fabric referred to as shifting. A layup system was designed and implemented using a large robotic gantry and custom end-effector for shifting. Layup tests proved that the system can deposit fabric onto two-dimensional and three-dimensional tooling surfaces accurately and repeatedly while avoiding out-of-plane deformation. A process planning method was developed to generate tool paths for the layup system based on a geometric model of the tooling surface. The approach is analogous to Computer Numerical Controlled (CNC) machining, where Numerical Control (NC) code from a Computer-Aided Design (CAD) model is generated to drive the milling machine. Layup experiments utilizing the proposed method were conducted to validate the performance. The results show that the process planning software requires minimal time or human intervention and can generate tool paths leading to accurate composite fabric layups. Fiberglass fabric samples processed with shifting deformation were observed for meso-scale deformation. Tow thinning, bending and spacing was observed and measured. Overall, shifting did not create flaws in amounts that would disqualify the method from use in industry. This suggests that shifting is a viable method for use in automated manufacturing. The work of this dissertation provides a new method for the automated layup of broad width composite fabric that is not possible with any available composite automation systems to date.

Probabilistic safety analysis vs probabilistic fracture mechanics -relation and necessary merging

International Nuclear Information System (INIS)

Nilsson, Fred

1997-01-01

A comparison is made between some general features of probabilistic fracture mechanics (PFM) and probabilistic safety assessment (PSA) in its standard form. We conclude that: Result from PSA is a numerically expressed level of confidence in the system based on the state of current knowledge. It is thus not any objective measure of risk. It is important to carefully define the precise nature of the probabilistic statement and relate it to a well defined situation. Standardisation of PFM methods is necessary. PFM seems to be the only way to obtain estimates of the pipe break probability. Service statistics are of doubtful value because of scarcity of data and statistical inhomogeneity. Collection of service data should be directed towards the occurrence of growing cracks

The multi-element probabilistic collocation method (ME-PCM): Error analysis and applications

International Nuclear Information System (INIS)

Foo, Jasmine; Wan Xiaoliang; Karniadakis, George Em

2008-01-01

Stochastic spectral methods are numerical techniques for approximating solutions to partial differential equations with random parameters. In this work, we present and examine the multi-element probabilistic collocation method (ME-PCM), which is a generalized form of the probabilistic collocation method. In the ME-PCM, the parametric space is discretized and a collocation/cubature grid is prescribed on each element. Both full and sparse tensor product grids based on Gauss and Clenshaw-Curtis quadrature rules are considered. We prove analytically and observe in numerical tests that as the parameter space mesh is refined, the convergence rate of the solution depends on the quadrature rule of each element only through its degree of exactness. In addition, the L 2 error of the tensor product interpolant is examined and an adaptivity algorithm is provided. Numerical examples demonstrating adaptive ME-PCM are shown, including low-regularity problems and long-time integration. We test the ME-PCM on two-dimensional Navier-Stokes examples and a stochastic diffusion problem with various random input distributions and up to 50 dimensions. While the convergence rate of ME-PCM deteriorates in 50 dimensions, the error in the mean and variance is two orders of magnitude lower than the error obtained with the Monte Carlo method using only a small number of samples (e.g., 100). The computational cost of ME-PCM is found to be favorable when compared to the cost of other methods including stochastic Galerkin, Monte Carlo and quasi-random sequence methods

Probabilistic methods for evaluation of erosion-corrosion wall thinning in french pressurized water reactors

International Nuclear Information System (INIS)

Ardillon, E.; Bouchacourt, M.

1994-04-01

This paper describes the application of the probabilistic approach to a selected study section having known characteristics. The method is based on the physico-chemical model of erosion-corrosion, the variables of which are probabilized. The three main aspects of the model, namely the thermohydraulic flow conditions, the chemistry of the fluid, and the geometry of the installation, are described. The study ultimately makes it possible determine: - the evolution of wall thinning distribution, using the power station's measurements; - the main parameters of influence on the kinetics of wall thinning; - the evolution of the fracture probabilistic of the pipe in question. (authors). 10 figs., 7 refs

A Method for Automated Planning of FTTH Access Network Infrastructures

DEFF Research Database (Denmark)

Riaz, Muhammad Tahir; Pedersen, Jens Myrup; Madsen, Ole Brun

2005-01-01

In this paper a method for automated planning of Fiber to the Home (FTTH) access networks is proposed. We introduced a systematic approach for planning access network infrastructure. The GIS data and a set of algorithms were employed to make the planning process more automatic. The method explains...... method. The method, however, does not fully automate the planning but make the planning process significantly fast. The results and discussion are presented and conclusion is given in the end....

An Automated Processing Method for Agglomeration Areas

Directory of Open Access Journals (Sweden)

Chengming Li

2018-05-01

Full Text Available Agglomeration operations are a core component of the automated generalization of aggregated area groups. However, because geographical elements that possess agglomeration features are relatively scarce, the current literature has not given sufficient attention to agglomeration operations. Furthermore, most reports on the subject are limited to the general conceptual level. Consequently, current agglomeration methods are highly reliant on subjective determinations and cannot support intelligent computer processing. This paper proposes an automated processing method for agglomeration areas. Firstly, the proposed method automatically identifies agglomeration areas based on the width of the striped bridging area, distribution pattern index (DPI, shape similarity index (SSI, and overlap index (OI. Next, the progressive agglomeration operation is carried out, including the computation of the external boundary outlines and the extraction of agglomeration lines. The effectiveness and rationality of the proposed method has been validated by using actual census data of Chinese geographical conditions in the Jiangsu Province.

Comparison of manual and automated quantification methods of 123I-ADAM

International Nuclear Information System (INIS)

Kauppinen, T.; Keski-Rahkonen, A.; Sihvola, E.; Helsinki Univ. Central Hospital

2005-01-01

123 I-ADAM is a novel radioligand for imaging of the brain serotonin transporters (SERTs). Traditionally, the analysis of brain receptor studies has been based on observer-dependent manual region of interest definitions and visual interpretation. Our aim was to create a template for automated image registrations and volume of interest (VOI) quantification and to show that an automated quantification method of 123 I-ADAM is more repeatable than the manual method. Patients, methods: A template and a predefined VOI map was created from 123 I-ADAM scans done for healthy volunteers (n=15). Scans of another group of healthy persons (HS, n=12) and patients with bulimia nervosa (BN, n=10) were automatically fitted to the template and specific binding ratios (SBRs) were calculated by using the VOI map. Manual VOI definitions were done for the HS and BN groups by both one and two observers. The repeatability of the automated method was evaluated by using the BN group. Results: For the manual method, the interobserver coefficient of repeatability was 0.61 for the HS group and 1.00 for the BN group. The intra-observer coefficient of repeatability for the BN group was 0.70. For the automated method, the coefficient of repeatability was 0.13 for SBRs in midbrain. Conclusion: An automated quantification gives valuable information in addition to visual interpretation decreasing also the total image handling time and giving clear advantages for research work. An automated method for analysing 123 I-ADAM binding to the brain SERT gives repeatable results for fitting the studies to the template and for calculating SBRs, and could therefore replace manual methods. (orig.)

Multi-element probabilistic collocation method in high dimensions

International Nuclear Information System (INIS)

Foo, Jasmine; Karniadakis, George Em

2010-01-01

We combine multi-element polynomial chaos with analysis of variance (ANOVA) functional decomposition to enhance the convergence rate of polynomial chaos in high dimensions and in problems with low stochastic regularity. Specifically, we employ the multi-element probabilistic collocation method MEPCM and so we refer to the new method as MEPCM-A. We investigate the dependence of the convergence of MEPCM-A on two decomposition parameters, the polynomial order μ and the effective dimension ν, with ν<< N, and N the nominal dimension. Numerical tests for multi-dimensional integration and for stochastic elliptic problems suggest that ν≥μ for monotonic convergence of the method. We also employ MEPCM-A to obtain error bars for the piezometric head at the Hanford nuclear waste site under stochastic hydraulic conductivity conditions. Finally, we compare the cost of MEPCM-A against Monte Carlo in several hundred dimensions, and we find MEPCM-A to be more efficient for up to 600 dimensions for a specific multi-dimensional integration problem involving a discontinuous function.

Toponomics method for the automated quantification of membrane protein translocation.

Science.gov (United States)

Domanova, Olga; Borbe, Stefan; Mühlfeld, Stefanie; Becker, Martin; Kubitz, Ralf; Häussinger, Dieter; Berlage, Thomas

2011-09-19

Intra-cellular and inter-cellular protein translocation can be observed by microscopic imaging of tissue sections prepared immunohistochemically. A manual densitometric analysis is time-consuming, subjective and error-prone. An automated quantification is faster, more reproducible, and should yield results comparable to manual evaluation. The automated method presented here was developed on rat liver tissue sections to study the translocation of bile salt transport proteins in hepatocytes. For validation, the cholestatic liver state was compared to the normal biological state. An automated quantification method was developed to analyze the translocation of membrane proteins and evaluated in comparison to an established manual method. Firstly, regions of interest (membrane fragments) are identified in confocal microscopy images. Further, densitometric intensity profiles are extracted orthogonally to membrane fragments, following the direction from the plasma membrane to cytoplasm. Finally, several different quantitative descriptors were derived from the densitometric profiles and were compared regarding their statistical significance with respect to the transport protein distribution. Stable performance, robustness and reproducibility were tested using several independent experimental datasets. A fully automated workflow for the information extraction and statistical evaluation has been developed and produces robust results. New descriptors for the intensity distribution profiles were found to be more discriminative, i.e. more significant, than those used in previous research publications for the translocation quantification. The slow manual calculation can be substituted by the fast and unbiased automated method.

A comparison of a 3 dimensional probabilistic method of berthing structure design and the traditional method of a berthing structure design

NARCIS (Netherlands)

Kool, J.J.; De Gijt, J.G.; Groenewegen, L.

2013-01-01

Finite element method (FEM) is increasingly applied as a first choice tool for designing structures. The same trend is seen in probabilistic designing. Consequently, the application of the combination of these two methods is discussed in this paper.In this study the presence of potential

Probabilistic conditional independence structures

CERN Document Server

Studeny, Milan

2005-01-01

Probabilistic Conditional Independence Structures provides the mathematical description of probabilistic conditional independence structures; the author uses non-graphical methods of their description, and takes an algebraic approach.The monograph presents the methods of structural imsets and supermodular functions, and deals with independence implication and equivalence of structural imsets.Motivation, mathematical foundations and areas of application are included, and a rough overview of graphical methods is also given.In particular, the author has been careful to use suitable terminology, and presents the work so that it will be understood by both statisticians, and by researchers in artificial intelligence.The necessary elementary mathematical notions are recalled in an appendix.

Constant Jacobian Matrix-Based Stochastic Galerkin Method for Probabilistic Load Flow

Directory of Open Access Journals (Sweden)

Yingyun Sun

2016-03-01

Full Text Available An intrusive spectral method of probabilistic load flow (PLF is proposed in the paper, which can handle the uncertainties arising from renewable energy integration. Generalized polynomial chaos (gPC expansions of dependent random variables are utilized to build a spectral stochastic representation of PLF model. Instead of solving the coupled PLF model with a traditional, cumbersome method, a modified stochastic Galerkin (SG method is proposed based on the P-Q decoupling properties of load flow in power system. By introducing two pre-calculated constant sparse Jacobian matrices, the computational burden of the SG method is significantly reduced. Two cases, IEEE 14-bus and IEEE 118-bus systems, are used to verify the computation speed and efficiency of the proposed method.

Probabilistic numerics and uncertainty in computations.

Science.gov (United States)

Hennig, Philipp; Osborne, Michael A; Girolami, Mark

2015-07-08

We deliver a call to arms for probabilistic numerical methods : algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data have led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimizers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations.

Probabilistic Geoacoustic Inversion in Complex Environments

Science.gov (United States)

2015-09-30

Probabilistic Geoacoustic Inversion in Complex Environments Jan Dettmer School of Earth and Ocean Sciences, University of Victoria, Victoria BC...long-range inversion methods can fail to provide sufficient resolution. For proper quantitative examination of variability, parameter uncertainty must...project aims to advance probabilistic geoacoustic inversion methods for complex ocean environments for a range of geoacoustic data types. The work is

Students’ difficulties in probabilistic problem-solving

Science.gov (United States)

Arum, D. P.; Kusmayadi, T. A.; Pramudya, I.

2018-03-01

There are many errors can be identified when students solving mathematics problems, particularly in solving the probabilistic problem. This present study aims to investigate students’ difficulties in solving the probabilistic problem. It focuses on analyzing and describing students errors during solving the problem. This research used the qualitative method with case study strategy. The subjects in this research involve ten students of 9th grade that were selected by purposive sampling. Data in this research involve students’ probabilistic problem-solving result and recorded interview regarding students’ difficulties in solving the problem. Those data were analyzed descriptively using Miles and Huberman steps. The results show that students have difficulties in solving the probabilistic problem and can be divided into three categories. First difficulties relate to students’ difficulties in understanding the probabilistic problem. Second, students’ difficulties in choosing and using appropriate strategies for solving the problem. Third, students’ difficulties with the computational process in solving the problem. Based on the result seems that students still have difficulties in solving the probabilistic problem. It means that students have not able to use their knowledge and ability for responding probabilistic problem yet. Therefore, it is important for mathematics teachers to plan probabilistic learning which could optimize students probabilistic thinking ability.

Recent developments of the NESSUS probabilistic structural analysis computer program

Science.gov (United States)

Millwater, H.; Wu, Y.-T.; Torng, T.; Thacker, B.; Riha, D.; Leung, C. P.

1992-01-01

The NESSUS probabilistic structural analysis computer program combines state-of-the-art probabilistic algorithms with general purpose structural analysis methods to compute the probabilistic response and the reliability of engineering structures. Uncertainty in loading, material properties, geometry, boundary conditions and initial conditions can be simulated. The structural analysis methods include nonlinear finite element and boundary element methods. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. The scope of the code has recently been expanded to include probabilistic life and fatigue prediction of structures in terms of component and system reliability and risk analysis of structures considering cost of failure. The code is currently being extended to structural reliability considering progressive crack propagation. Several examples are presented to demonstrate the new capabilities.

Method of extracting significant trouble information of nuclear power plants using probabilistic analysis technique

International Nuclear Information System (INIS)

Shimada, Yoshio; Miyazaki, Takamasa

2005-01-01

In order to analyze and evaluate large amounts of trouble information of overseas nuclear power plants, it is necessary to select information that is significant in terms of both safety and reliability. In this research, a method of efficiently and simply classifying degrees of importance of components in terms of safety and reliability while paying attention to root-cause components appearing in the information was developed. Regarding safety, the reactor core damage frequency (CDF), which is used in the probabilistic analysis of a reactor, was used. Regarding reliability, the automatic plant trip probability (APTP), which is used in the probabilistic analysis of automatic reactor trips, was used. These two aspects were reflected in the development of criteria for classifying degrees of importance of components. By applying these criteria, a simple method of extracting significant trouble information of overseas nuclear power plants was developed. (author)

Integrated Deterministic-Probabilistic Safety Assessment Methodologies

Energy Technology Data Exchange (ETDEWEB)

Kudinov, P.; Vorobyev, Y.; Sanchez-Perea, M.; Queral, C.; Jimenez Varas, G.; Rebollo, M. J.; Mena, L.; Gomez-Magin, J.

2014-02-01

IDPSA (Integrated Deterministic-Probabilistic Safety Assessment) is a family of methods which use tightly coupled probabilistic and deterministic approaches to address respective sources of uncertainties, enabling Risk informed decision making in a consistent manner. The starting point of the IDPSA framework is that safety justification must be based on the coupling of deterministic (consequences) and probabilistic (frequency) considerations to address the mutual interactions between stochastic disturbances (e.g. failures of the equipment, human actions, stochastic physical phenomena) and deterministic response of the plant (i.e. transients). This paper gives a general overview of some IDPSA methods as well as some possible applications to PWR safety analyses. (Author)

A Methods and procedures to apply probabilistic safety Assessment (PSA) techniques to the cobalt-therapy process. Cuban experience

International Nuclear Information System (INIS)

Vilaragut Llanes, J.J.; Ferro Fernandez, R.; Lozano Lima, B; De la Fuente Puch, A.; Dumenigo Gonzalez, C.; Troncoso Fleitas, M.; Perez Reyes, Y.

2003-01-01

This paper presents the results of the Probabilistic Safety Analysis (PSA) to the Cobalt Therapy Process, which was performed as part of the International Atomic Energy Agency's Coordinated Research Project (CRP) to Investigate Appropriate Methods and Procedures to Apply Probabilistic Safety Assessment (PSA) Techniques to Large Radiation Sources. The primary methodological tools used in the analysis were Failure Modes and Effects Analysis (FMEA), Event Trees and Fault Trees. These tools were used to evaluate occupational, public and medical exposures during cobalt therapy treatment. The emphasis of the study was on the radiological protection of patients. During the course of the PSA, several findings were analysed concerning the cobalt treatment process. In relation with the Undesired Events Probabilities, the lowest exposures probabilities correspond to the public exposures during the treatment process (Z21); around 10-10 per year, being the workers exposures (Z11); around 10-4 per year. Regarding to the patient, the Z33 probabilities prevail (not desired dose to normal tissue) and Z34 (not irradiated portion to target volume). Patient accidental exposures are also classified in terms of the extent to which the error is likely to affect individual treatments, individual patients, or all the patients treated on a specific unit. Sensitivity analyses were realised to determine the influence of certain tasks or critical stages on the results. As a conclusion the study establishes that the PSA techniques may effectively and reasonably determine the risk associated to the cobalt-therapy treatment process, though there are some weaknesses in its methodological application for this kind of study requiring further research. These weaknesses are due to the fact that the traditional PSA has been mainly applied to complex hardware systems designed to operate with a high automation level, whilst the cobalt therapy treatment is a relatively simple hardware system with a

Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions.

Directory of Open Access Journals (Sweden)

Vasanthan Maruthapillai

Full Text Available In recent years, real-time face recognition has been a major topic of interest in developing intelligent human-machine interaction systems. Over the past several decades, researchers have proposed different algorithms for facial expression recognition, but there has been little focus on detection in real-time scenarios. The present work proposes a new algorithmic method of automated marker placement used to classify six facial expressions: happiness, sadness, anger, fear, disgust, and surprise. Emotional facial expressions were captured using a webcam, while the proposed algorithm placed a set of eight virtual markers on each subject's face. Facial feature extraction methods, including marker distance (distance between each marker to the center of the face and change in marker distance (change in distance between the original and new marker positions, were used to extract three statistical features (mean, variance, and root mean square from the real-time video sequence. The initial position of each marker was subjected to the optical flow algorithm for marker tracking with each emotional facial expression. Finally, the extracted statistical features were mapped into corresponding emotional facial expressions using two simple non-linear classifiers, K-nearest neighbor and probabilistic neural network. The results indicate that the proposed automated marker placement algorithm effectively placed eight virtual markers on each subject's face and gave a maximum mean emotion classification rate of 96.94% using the probabilistic neural network.

Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions.

Science.gov (United States)

Maruthapillai, Vasanthan; Murugappan, Murugappan

2016-01-01

In recent years, real-time face recognition has been a major topic of interest in developing intelligent human-machine interaction systems. Over the past several decades, researchers have proposed different algorithms for facial expression recognition, but there has been little focus on detection in real-time scenarios. The present work proposes a new algorithmic method of automated marker placement used to classify six facial expressions: happiness, sadness, anger, fear, disgust, and surprise. Emotional facial expressions were captured using a webcam, while the proposed algorithm placed a set of eight virtual markers on each subject's face. Facial feature extraction methods, including marker distance (distance between each marker to the center of the face) and change in marker distance (change in distance between the original and new marker positions), were used to extract three statistical features (mean, variance, and root mean square) from the real-time video sequence. The initial position of each marker was subjected to the optical flow algorithm for marker tracking with each emotional facial expression. Finally, the extracted statistical features were mapped into corresponding emotional facial expressions using two simple non-linear classifiers, K-nearest neighbor and probabilistic neural network. The results indicate that the proposed automated marker placement algorithm effectively placed eight virtual markers on each subject's face and gave a maximum mean emotion classification rate of 96.94% using the probabilistic neural network.

A Systematic, Automated Network Planning Method

DEFF Research Database (Denmark)

Holm, Jens Åge; Pedersen, Jens Myrup

2006-01-01

This paper describes a case study conducted to evaluate the viability of a systematic, automated network planning method. The motivation for developing the network planning method was that many data networks are planned in an adhoc manner with no assurance of quality of the solution with respect...... structures, that are ready to implement in a real world scenario, are discussed in the end of the paper. These are in the area of ensuring line independence and complexity of the design rules for the planning method....

Bayesian methods for hackers probabilistic programming and Bayesian inference

CERN Document Server

Davidson-Pilon, Cameron

2016-01-01

Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples a...

A Control Variate Method for Probabilistic Performance Assessment. Improved Estimates for Mean Performance Quantities of Interest

Energy Technology Data Exchange (ETDEWEB)

MacKinnon, Robert J.; Kuhlman, Kristopher L

2016-05-01

We present a method of control variates for calculating improved estimates for mean performance quantities of interest, E(PQI) , computed from Monte Carlo probabilistic simulations. An example of a PQI is the concentration of a contaminant at a particular location in a problem domain computed from simulations of transport in porous media. To simplify the presentation, the method is described in the setting of a one- dimensional elliptical model problem involving a single uncertain parameter represented by a probability distribution. The approach can be easily implemented for more complex problems involving multiple uncertain parameters and in particular for application to probabilistic performance assessment of deep geologic nuclear waste repository systems. Numerical results indicate the method can produce estimates of E(PQI)having superior accuracy on coarser meshes and reduce the required number of simulations needed to achieve an acceptable estimate.

Learning Probabilistic Logic Models from Probabilistic Examples.

Science.gov (United States)

Chen, Jianzhong; Muggleton, Stephen; Santos, José

2008-10-01

We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks. The example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset of the Kyoto Encyclopedia of Genes and Genomes (KEGG). We now apply two Probabilistic ILP (PILP) approaches - abductive Stochastic Logic Programs (SLPs) and PRogramming In Statistical modeling (PRISM) to the application. Both approaches support abductive learning and probability predictions. Abductive SLPs are a PILP framework that provides possible worlds semantics to SLPs through abduction. Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard scientific experimental setting involving control and treated data. Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant decrease in error accompanied by improved insight from the learned results compared with the PILP models learned from non-probabilistic examples.

Comparison between Canadian probabilistic safety assessment methods formulated by Atomic Energy of Canada limited and probabilistic risk assessment methods

International Nuclear Information System (INIS)

Shapiro, H.S.; Smith, J.E.

1989-01-01

The procedures used by Atomic Energy of Canada Limited (AECL) to perform probabilistic safety assessments (PRAs) differ somewhat from conventionally accepted probabilistic risk assessment (PRA) procedures used elsewhere. In Canada, PSA is used by AECL as an audit tool for an evolving design. The purpose is to assess the safety of the plant in engineering terms. Thus, the PSA procedures are geared toward providing engineering feedback so that necessary changes can be made to the design at an early stage, input can be made to operating procedures, and test and maintenance programs can be optimized in terms of costs. Most PRAs, by contrast, are performed in plants that are already built. Their main purpose is to establish the core melt frequency and the risk to the public due to core melt. Also, any design modification is very expensive. The differences in purpose and timing between PSA and PRA have resulted in differences in methodology and scope. The PSA procedures are used on all plants being designed by AECL

Comparison of manual and automated quantification methods of {sup 123}I-ADAM

Energy Technology Data Exchange (ETDEWEB)

Kauppinen, T. [Helsinki Univ. Central Hospital (Finland). HUS Helsinki Medical Imaging Center; Helsinki Univ. Central Hospital (Finland). Division of Nuclear Medicine; Koskela, A.; Ahonen, A. [Helsinki Univ. Central Hospital (Finland). Division of Nuclear Medicine; Diemling, M. [Hermes Medical Solutions, Stockholm (Sweden); Keski-Rahkonen, A.; Sihvola, E. [Helsinki Univ. (Finland). Dept. of Public Health; Helsinki Univ. Central Hospital (Finland). Dept. of Psychiatry

2005-07-01

{sup 123}I-ADAM is a novel radioligand for imaging of the brain serotonin transporters (SERTs). Traditionally, the analysis of brain receptor studies has been based on observer-dependent manual region of interest definitions and visual interpretation. Our aim was to create a template for automated image registrations and volume of interest (VOI) quantification and to show that an automated quantification method of {sup 123}I-ADAM is more repeatable than the manual method. Patients, methods: A template and a predefined VOI map was created from {sup 123}I-ADAM scans done for healthy volunteers (n=15). Scans of another group of healthy persons (HS, n=12) and patients with bulimia nervosa (BN, n=10) were automatically fitted to the template and specific binding ratios (SBRs) were calculated by using the VOI map. Manual VOI definitions were done for the HS and BN groups by both one and two observers. The repeatability of the automated method was evaluated by using the BN group. Results: For the manual method, the interobserver coefficient of repeatability was 0.61 for the HS group and 1.00 for the BN group. The intra-observer coefficient of repeatability for the BN group was 0.70. For the automated method, the coefficient of repeatability was 0.13 for SBRs in midbrain. Conclusion: An automated quantification gives valuable information in addition to visual interpretation decreasing also the total image handling time and giving clear advantages for research work. An automated method for analysing {sup 123}I-ADAM binding to the brain SERT gives repeatable results for fitting the studies to the template and for calculating SBRs, and could therefore replace manual methods. (orig.)

A comparison of the weights-of-evidence method and probabilistic neural networks

Science.gov (United States)

Singer, Donald A.; Kouda, Ryoichi

1999-01-01

The need to integrate large quantities of digital geoscience information to classify locations as mineral deposits or nondeposits has been met by the weights-of-evidence method in many situations. Widespread selection of this method may be more the result of its ease of use and interpretation rather than comparisons with alternative methods. A comparison of the weights-of-evidence method to probabilistic neural networks is performed here with data from Chisel Lake-Andeson Lake, Manitoba, Canada. Each method is designed to estimate the probability of belonging to learned classes where the estimated probabilities are used to classify the unknowns. Using these data, significantly lower classification error rates were observed for the neural network, not only when test and training data were the same (0.02 versus 23%), but also when validation data, not used in any training, were used to test the efficiency of classification (0.7 versus 17%). Despite these data containing too few deposits, these tests of this set of data demonstrate the neural network's ability at making unbiased probability estimates and lower error rates when measured by number of polygons or by the area of land misclassified. For both methods, independent validation tests are required to ensure that estimates are representative of real-world results. Results from the weights-of-evidence method demonstrate a strong bias where most errors are barren areas misclassified as deposits. The weights-of-evidence method is based on Bayes rule, which requires independent variables in order to make unbiased estimates. The chi-square test for independence indicates no significant correlations among the variables in the Chisel Lake–Andeson Lake data. However, the expected number of deposits test clearly demonstrates that these data violate the independence assumption. Other, independent simulations with three variables show that using variables with correlations of 1.0 can double the expected number of deposits

A review on automated pavement distress detection methods

NARCIS (Netherlands)

Coenen, Tom B.J.; Golroo, Amir

2017-01-01

In recent years, extensive research has been conducted on pavement distress detection. A large part of these studies applied automated methods to capture different distresses. In this paper, a literature review on the distresses and related detection methods are presented. This review also includes

A new method for automated high-dimensional lesion segmentation evaluated in vascular injury and applied to the human occipital lobe.

Science.gov (United States)

Mah, Yee-Haur; Jager, Rolf; Kennard, Christopher; Husain, Masud; Nachev, Parashkev

2014-07-01

Making robust inferences about the functional neuroanatomy of the brain is critically dependent on experimental techniques that examine the consequences of focal loss of brain function. Unfortunately, the use of the most comprehensive such technique-lesion-function mapping-is complicated by the need for time-consuming and subjective manual delineation of the lesions, greatly limiting the practicability of the approach. Here we exploit a recently-described general measure of statistical anomaly, zeta, to devise a fully-automated, high-dimensional algorithm for identifying the parameters of lesions within a brain image given a reference set of normal brain images. We proceed to evaluate such an algorithm in the context of diffusion-weighted imaging of the commonest type of lesion used in neuroanatomical research: ischaemic damage. Summary performance metrics exceed those previously published for diffusion-weighted imaging and approach the current gold standard-manual segmentation-sufficiently closely for fully-automated lesion-mapping studies to become a possibility. We apply the new method to 435 unselected images of patients with ischaemic stroke to derive a probabilistic map of the pattern of damage in lesions involving the occipital lobe, demonstrating the variation of anatomical resolvability of occipital areas so as to guide future lesion-function studies of the region. Copyright © 2012 Elsevier Ltd. All rights reserved.

Probabilistic broadcasting of mixed states

International Nuclear Information System (INIS)

Li Lvjun; Li Lvzhou; Wu Lihua; Zou Xiangfu; Qiu Daowen

2009-01-01

It is well known that the non-broadcasting theorem proved by Barnum et al is a fundamental principle of quantum communication. As we are aware, optimal broadcasting (OB) is the only method to broadcast noncommuting mixed states approximately. In this paper, motivated by the probabilistic cloning of quantum states proposed by Duan and Guo, we propose a new way for broadcasting noncommuting mixed states-probabilistic broadcasting (PB), and we present a sufficient condition for PB of mixed states. To a certain extent, we generalize the probabilistic cloning theorem from pure states to mixed states, and in particular, we generalize the non-broadcasting theorem, since the case that commuting mixed states can be exactly broadcast can be thought of as a special instance of PB where the success ratio is 1. Moreover, we discuss probabilistic local broadcasting (PLB) of separable bipartite states

Probabilistic liver atlas construction.

Science.gov (United States)

Dura, Esther; Domingo, Juan; Ayala, Guillermo; Marti-Bonmati, Luis; Goceri, E

2017-01-13

Anatomical atlases are 3D volumes or shapes representing an organ or structure of the human body. They contain either the prototypical shape of the object of interest together with other shapes representing its statistical variations (statistical atlas) or a probability map of belonging to the object (probabilistic atlas). Probabilistic atlases are mostly built with simple estimations only involving the data at each spatial location. A new method for probabilistic atlas construction that uses a generalized linear model is proposed. This method aims to improve the estimation of the probability to be covered by the liver. Furthermore, all methods to build an atlas involve previous coregistration of the sample of shapes available. The influence of the geometrical transformation adopted for registration in the quality of the final atlas has not been sufficiently investigated. The ability of an atlas to adapt to a new case is one of the most important quality criteria that should be taken into account. The presented experiments show that some methods for atlas construction are severely affected by the previous coregistration step. We show the good performance of the new approach. Furthermore, results suggest that extremely flexible registration methods are not always beneficial, since they can reduce the variability of the atlas and hence its ability to give sensible values of probability when used as an aid in segmentation of new cases.

Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method

Science.gov (United States)

Denis Valle; Benjamin Baiser; Christopher W. Woodall; Robin Chazdon; Jerome. Chave

2014-01-01

We propose a novel multivariate method to analyse biodiversity data based on the Latent Dirichlet Allocation (LDA) model. LDA, a probabilistic model, reduces assemblages to sets of distinct component communities. It produces easily interpretable results, can represent abrupt and gradual changes in composition, accommodates missing data and allows for coherent estimates...

Automated migration analysis based on cell texture: method & reliability

Directory of Open Access Journals (Sweden)

Chittenden Thomas W

2005-03-01

Full Text Available Abstract Background In this paper, we present and validate a way to measure automatically the extent of cell migration based on automated examination of a series of digital photographs. It was designed specifically to identify the impact of Second Hand Smoke (SHS on endothelial cell migration but has broader applications. The analysis has two stages: (1 preprocessing of image texture, and (2 migration analysis. Results The output is a graphic overlay that indicates the front lines of cell migration superimposed on each original image, with automated reporting of the distance traversed vs. time. Expert preference compares to manual placement of leading edge shows complete equivalence of automated vs. manual leading edge definition for cell migration measurement. Conclusion Our method is indistinguishable from careful manual determinations of cell front lines, with the advantages of full automation, objectivity, and speed.

Non-probabilistic defect assessment for structures with cracks based on interval model

International Nuclear Information System (INIS)

Dai, Qiao; Zhou, Changyu; Peng, Jian; Chen, Xiangwei; He, Xiaohua

2013-01-01

Highlights: • Non-probabilistic approach is introduced to defect assessment. • Definition and establishment of IFAC are put forward. • Determination of assessment rectangle is proposed. • Solution of non-probabilistic reliability index is presented. -- Abstract: Traditional defect assessment methods conservatively treat uncertainty of parameters as safety factors, while the probabilistic method is based on the clear understanding of detailed statistical information of parameters. In this paper, the non-probabilistic approach is introduced to the failure assessment diagram (FAD) to propose a non-probabilistic defect assessment method for structures with cracks. This novel defect assessment method contains three critical processes: establishment of the interval failure assessment curve (IFAC), determination of the assessment rectangle, and solution of the non-probabilistic reliability degree. Based on the interval theory, uncertain parameters such as crack sizes, material properties and loads are considered as interval variables. As a result, the failure assessment curve (FAC) will vary in a certain range, which is defined as IFAC. And the assessment point will vary within a rectangle zone which is defined as an assessment rectangle. Based on the interval model, the establishment of IFAC and the determination of the assessment rectangle are presented. Then according to the interval possibility degree method, the non-probabilistic reliability degree of IFAC can be determined. Meanwhile, in order to clearly introduce the non-probabilistic defect assessment method, a numerical example for the assessment of a pipe with crack is given. In addition, the assessment result of the proposed method is compared with that of the traditional probabilistic method, which confirms that this non-probabilistic defect assessment can reasonably resolve the practical problem with interval variables

Non-probabilistic defect assessment for structures with cracks based on interval model

Energy Technology Data Exchange (ETDEWEB)

Dai, Qiao; Zhou, Changyu, E-mail: changyu_zhou@163.com; Peng, Jian; Chen, Xiangwei; He, Xiaohua

2013-09-15

Highlights: • Non-probabilistic approach is introduced to defect assessment. • Definition and establishment of IFAC are put forward. • Determination of assessment rectangle is proposed. • Solution of non-probabilistic reliability index is presented. -- Abstract: Traditional defect assessment methods conservatively treat uncertainty of parameters as safety factors, while the probabilistic method is based on the clear understanding of detailed statistical information of parameters. In this paper, the non-probabilistic approach is introduced to the failure assessment diagram (FAD) to propose a non-probabilistic defect assessment method for structures with cracks. This novel defect assessment method contains three critical processes: establishment of the interval failure assessment curve (IFAC), determination of the assessment rectangle, and solution of the non-probabilistic reliability degree. Based on the interval theory, uncertain parameters such as crack sizes, material properties and loads are considered as interval variables. As a result, the failure assessment curve (FAC) will vary in a certain range, which is defined as IFAC. And the assessment point will vary within a rectangle zone which is defined as an assessment rectangle. Based on the interval model, the establishment of IFAC and the determination of the assessment rectangle are presented. Then according to the interval possibility degree method, the non-probabilistic reliability degree of IFAC can be determined. Meanwhile, in order to clearly introduce the non-probabilistic defect assessment method, a numerical example for the assessment of a pipe with crack is given. In addition, the assessment result of the proposed method is compared with that of the traditional probabilistic method, which confirms that this non-probabilistic defect assessment can reasonably resolve the practical problem with interval variables.

Systematic evaluations of probabilistic floor response spectrum generation

International Nuclear Information System (INIS)

Lilhanand, K.; Wing, D.W.; Tseng, W.S.

1985-01-01

The relative merits of the current methods for direct generation of probabilistic floor response spectra (FRS) from the prescribed design response spectra (DRS) are evaluated. The explicit probabilistic methods, which explicitly use the relationship between the power spectral density function (PSDF) and response spectra (RS), i.e., the PSDF-RS relationship, are found to have advantages for practical applications over the implicit methods. To evaluate the accuracy of the explicit methods, the root-mean-square (rms) response and the peak factor contained in the PSDF-RS relationship are systematically evaluated, especially for the narrow-band floor spectral response, by comparing the analytical results with simulation results. Based on the evaluation results, a method is recommended for practical use for the direct generation of probabilistic FRS. (orig.)

Grasping devices and methods in automated production processes

DEFF Research Database (Denmark)

Fantoni, Gualtiero; Santochi, Marco; Dini, Gino

2014-01-01

assembly to disassembly, from aerospace to food industry, from textile to logistics) are discussed. Finally, the most recent research is reviewed in order to introduce the new trends in grasping. They provide an outlook on the future of both grippers and robotic hands in automated production processes. (C......In automated production processes grasping devices and methods play a crucial role in the handling of many parts, components and products. This keynote paper starts with a classification of grasping phases, describes how different principles are adopted at different scales in different applications...

An Advanced Bayesian Method for Short-Term Probabilistic Forecasting of the Generation of Wind Power

Directory of Open Access Journals (Sweden)

Antonio Bracale

2015-09-01

Full Text Available Currently, among renewable distributed generation systems, wind generators are receiving a great deal of interest due to the great economic, technological, and environmental incentives they involve. However, the uncertainties due to the intermittent nature of wind energy make it difficult to operate electrical power systems optimally and make decisions that satisfy the needs of all the stakeholders of the electricity energy market. Thus, there is increasing interest determining how to forecast wind power production accurately. Most the methods that have been published in the relevant literature provided deterministic forecasts even though great interest has been focused recently on probabilistic forecast methods. In this paper, an advanced probabilistic method is proposed for short-term forecasting of wind power production. A mixture of two Weibull distributions was used as a probability function to model the uncertainties associated with wind speed. Then, a Bayesian inference approach with a particularly-effective, autoregressive, integrated, moving-average model was used to determine the parameters of the mixture Weibull distribution. Numerical applications also are presented to provide evidence of the forecasting performance of the Bayesian-based approach.

Probabilistic dual heuristic programming-based adaptive critic

Science.gov (United States)

Herzallah, Randa

2010-02-01

Adaptive critic (AC) methods have common roots as generalisations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, non-linear and non-stationary environments. In this study, a novel probabilistic dual heuristic programming (DHP)-based AC controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) AC method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterised by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the probabilistic critic network is then calculated and shown to be equal to the analytically derived correct value. Full derivation of the Riccati solution for this non-standard stochastic linear quadratic control problem is also provided. Moreover, the performance of the proposed probabilistic controller is demonstrated on linear and non-linear control examples.

Analysis of truncation limit in probabilistic safety assessment

International Nuclear Information System (INIS)

Cepin, Marko

2005-01-01

A truncation limit defines the boundaries of what is considered in the probabilistic safety assessment and what is neglected. The truncation limit that is the focus here is the truncation limit on the size of the minimal cut set contribution at which to cut off. A new method was developed, which defines truncation limit in probabilistic safety assessment. The method specifies truncation limits with more stringency than presenting existing documents dealing with truncation criteria in probabilistic safety assessment do. The results of this paper indicate that the truncation limits for more complex probabilistic safety assessments, which consist of larger number of basic events, should be more severe than presently recommended in existing documents if more accuracy is desired. The truncation limits defined by the new method reduce the relative errors of importance measures and produce more accurate results for probabilistic safety assessment applications. The reduced relative errors of importance measures can prevent situations, where the acceptability of change of equipment under investigation according to RG 1.174 would be shifted from region, where changes can be accepted, to region, where changes cannot be accepted, if the results would be calculated with smaller truncation limit

A catalog of automated analysis methods for enterprise models.

Science.gov (United States)

Florez, Hector; Sánchez, Mario; Villalobos, Jorge

2016-01-01

Enterprise models are created for documenting and communicating the structure and state of Business and Information Technologies elements of an enterprise. After models are completed, they are mainly used to support analysis. Model analysis is an activity typically based on human skills and due to the size and complexity of the models, this process can be complicated and omissions or miscalculations are very likely. This situation has fostered the research of automated analysis methods, for supporting analysts in enterprise analysis processes. By reviewing the literature, we found several analysis methods; nevertheless, they are based on specific situations and different metamodels; then, some analysis methods might not be applicable to all enterprise models. This paper presents the work of compilation (literature review), classification, structuring, and characterization of automated analysis methods for enterprise models, expressing them in a standardized modeling language. In addition, we have implemented the analysis methods in our modeling tool.

Probabilistic uniformities of uniform spaces

Energy Technology Data Exchange (ETDEWEB)

Rodriguez Lopez, J.; Romaguera, S.; Sanchis, M.

2017-07-01

The theory of metric spaces in the fuzzy context has shown to be an interesting area of study not only from a theoretical point of view but also for its applications. Nevertheless, it is usual to consider these spaces as classical topological or uniform spaces and there are not too many results about constructing fuzzy topological structures starting from a fuzzy metric. Maybe, H/{sup o}hle was the first to show how to construct a probabilistic uniformity and a Lowen uniformity from a probabilistic pseudometric /cite{Hohle78,Hohle82a}. His method can be directly translated to the context of fuzzy metrics and allows to characterize the categories of probabilistic uniform spaces or Lowen uniform spaces by means of certain families of fuzzy pseudometrics /cite{RL}. On the other hand, other different fuzzy uniformities can be constructed in a fuzzy metric space: a Hutton $[0,1]$-quasi-uniformity /cite{GGPV06}; a fuzzifiying uniformity /cite{YueShi10}, etc. The paper /cite{GGRLRo} gives a study of several methods of endowing a fuzzy pseudometric space with a probabilistic uniformity and a Hutton $[0,1]$-quasi-uniformity. In 2010, J. Guti/'errez Garc/'{/i}a, S. Romaguera and M. Sanchis /cite{GGRoSanchis10} proved that the category of uniform spaces is isomorphic to a category formed by sets endowed with a fuzzy uniform structure, i. e. a family of fuzzy pseudometrics satisfying certain conditions. We will show here that, by means of this isomorphism, we can obtain several methods to endow a uniform space with a probabilistic uniformity. Furthermore, these constructions allow to obtain a factorization of some functors introduced in /cite{GGRoSanchis10}. (Author)

Valid Probabilistic Predictions for Ginseng with Venn Machines Using Electronic Nose

Directory of Open Access Journals (Sweden)

You Wang

2016-07-01

Full Text Available In the application of electronic noses (E-noses, probabilistic prediction is a good way to estimate how confident we are about our prediction. In this work, a homemade E-nose system embedded with 16 metal-oxide semi-conductive gas sensors was used to discriminate nine kinds of ginsengs of different species or production places. A flexible machine learning framework, Venn machine (VM was introduced to make probabilistic predictions for each prediction. Three Venn predictors were developed based on three classical probabilistic prediction methods (Platt’s method, Softmax regression and Naive Bayes. Three Venn predictors and three classical probabilistic prediction methods were compared in aspect of classification rate and especially the validity of estimated probability. A best classification rate of 88.57% was achieved with Platt’s method in offline mode, and the classification rate of VM-SVM (Venn machine based on Support Vector Machine was 86.35%, just 2.22% lower. The validity of Venn predictors performed better than that of corresponding classical probabilistic prediction methods. The validity of VM-SVM was superior to the other methods. The results demonstrated that Venn machine is a flexible tool to make precise and valid probabilistic prediction in the application of E-nose, and VM-SVM achieved the best performance for the probabilistic prediction of ginseng samples.

A probabilistic method for species sensitivity distributions taking into account the inherent uncertainty and variability of effects to estimate environmental risk.

Science.gov (United States)

Gottschalk, Fadri; Nowack, Bernd

2013-01-01

This article presents a method of probabilistically computing species sensitivity distributions (SSD) that is well-suited to cope with distinct data scarcity and variability. First, a probability distribution that reflects the uncertainty and variability of sensitivity is modeled for each species considered. These single species sensitivity distributions are then combined to create an SSD for a particular ecosystem. A probabilistic estimation of the risk is carried out by combining the probability of critical environmental concentrations with the probability of organisms being impacted negatively by these concentrations. To evaluate the performance of the method, we developed SSD and risk calculations for the aquatic environment exposed to triclosan. The case studies showed that the probabilistic results reflect the empirical information well, and the method provides a valuable alternative or supplement to more traditional methods for calculating SSDs based on averaging raw data and/or on using theoretical distributional forms. A comparison and evaluation with single SSD values (5th-percentile [HC5]) revealed the robustness of the proposed method. Copyright © 2012 SETAC.

Probabilistic fracture failure analysis of nuclear piping containing defects using R6 method

International Nuclear Information System (INIS)

Lin, Y.C.; Xie, Y.J.; Wang, X.H.

2004-01-01

Failure analysis of in-service nuclear piping containing defects is an important subject in the nuclear power plants. Considering the uncertainties in various internal operating loadings and external forces, including earthquake and wind, flaw sizes, material fracture toughness and flow stress, this paper presents a probabilistic assessment methodology for in-service nuclear piping containing defects, which is especially designed for programming. A general sampling computation method of the stress intensity factor (SIF), in the form of the relationship between the SIF and the axial force, bending moment and torsion, is adopted in the probabilistic assessment methodology. This relationship has been successfully used in developing the software, Safety Assessment System of In-service Pressure Piping Containing Flaws (SAPP-2003), based on a well-known engineering safety assessment procedure R6. A numerical example is given to show the application of the SAPP-2003 software. The failure probabilities of each defect and the whole piping can be obtained by this software

Application of probabilistic methods to accident analysis at waste management facilities

International Nuclear Information System (INIS)

Banz, I.

1986-01-01

Probabilistic risk assessment is a technique used to systematically analyze complex technical systems, such as nuclear waste management facilities, in order to identify and measure their public health, environmental, and economic risks. Probabilistic techniques have been utilized at the Waste Isolation Pilot Plant (WIPP) near Carlsbad, New Mexico, to evaluate the probability of a catastrophic waste hoist accident. A probability model was developed to represent the hoisting system, and fault trees were constructed to identify potential sequences of events that could result in a hoist accident. Quantification of the fault trees using statistics compiled by the Mine Safety and Health Administration (MSHA) indicated that the annual probability of a catastrophic hoist accident at WIPP is less than one in 60 million. This result allowed classification of a catastrophic hoist accident as ''not credible'' at WIPP per DOE definition. Potential uses of probabilistic techniques at other waste management facilities are discussed

A framework for the probabilistic analysis of meteotsunamis

Science.gov (United States)

Geist, Eric L.; ten Brink, Uri S.; Gove, Matthew D.

2014-01-01

A probabilistic technique is developed to assess the hazard from meteotsunamis. Meteotsunamis are unusual sea-level events, generated when the speed of an atmospheric pressure or wind disturbance is comparable to the phase speed of long waves in the ocean. A general aggregation equation is proposed for the probabilistic analysis, based on previous frameworks established for both tsunamis and storm surges, incorporating different sources and source parameters of meteotsunamis. Parameterization of atmospheric disturbances and numerical modeling is performed for the computation of maximum meteotsunami wave amplitudes near the coast. A historical record of pressure disturbances is used to establish a continuous analytic distribution of each parameter as well as the overall Poisson rate of occurrence. A demonstration study is presented for the northeast U.S. in which only isolated atmospheric pressure disturbances from squall lines and derechos are considered. For this study, Automated Surface Observing System stations are used to determine the historical parameters of squall lines from 2000 to 2013. The probabilistic equations are implemented using a Monte Carlo scheme, where a synthetic catalog of squall lines is compiled by sampling the parameter distributions. For each entry in the catalog, ocean wave amplitudes are computed using a numerical hydrodynamic model. Aggregation of the results from the Monte Carlo scheme results in a meteotsunami hazard curve that plots the annualized rate of exceedance with respect to maximum event amplitude for a particular location along the coast. Results from using multiple synthetic catalogs, resampled from the parent parameter distributions, yield mean and quantile hazard curves. Further refinements and improvements for probabilistic analysis of meteotsunamis are discussed.

An Automated Approach to Syntax-based Analysis of Classical Latin

Directory of Open Access Journals (Sweden)

Anjalie Field

2016-12-01

Full Text Available The goal of this study is to present an automated method for analyzing the style of Latin authors. Many of the common automated methods in stylistic analysis are based on lexical measures, which do not work well with Latin because of the language’s high degree of inflection and free word order. In contrast, this study focuses on analysis at a syntax level by examining two constructions, the ablative absolute and the cum clause. These constructions are often interchangeable, which suggests an author’s choice of construction is typically more stylistic than functional. We first identified these constructions in hand-annotated texts. Next we developed a method for identifying the constructions in unannotated texts, using probabilistic morphological tagging. Our methods identified constructions with enough accuracy to distinguish among different genres and different authors. In particular, we were able to determine which book of Caesar’s Commentarii de Bello Gallico was not written by Caesar. Furthermore, the usage of ablative absolutes and cum clauses observed in this study is consistent with the usage scholars have observed when analyzing these texts by hand. The proposed methods for an automatic syntax-based analysis are shown to be valuable for the study of classical literature.

Probabilist methods applied to electric source problems in nuclear safety

International Nuclear Information System (INIS)

Carnino, A.; Llory, M.

1979-01-01

Nuclear Safety has frequently been asked to quantify safety margins and evaluate the hazard. In order to do so, the probabilist methods have proved to be the most promising. Without completely replacing determinist safety, they are now commonly used at the reliability or availability stages of systems as well as for determining the likely accidental sequences. In this paper an application linked to the problem of electric sources is described, whilst at the same time indicating the methods used. This is the calculation of the probable loss of all the electric sources of a pressurized water nuclear power station, the evaluation of the reliability of diesels by event trees of failures and the determination of accidental sequences which could be brought about by the 'total electric source loss' initiator and affect the installation or the environment [fr

Use of Probabilistic Engineering Methods in the Detailed Design and Development Phases of the NASA Ares Launch Vehicle

Science.gov (United States)

Fayssal, Safie; Weldon, Danny

2008-01-01

The United States National Aeronautics and Space Administration (NASA) is in the midst of a space exploration program called Constellation to send crew and cargo to the international Space Station, to the moon, and beyond. As part of the Constellation program, a new launch vehicle, Ares I, is being developed by NASA Marshall Space Flight Center. Designing a launch vehicle with high reliability and increased safety requires a significant effort in understanding design variability and design uncertainty at the various levels of the design (system, element, subsystem, component, etc.) and throughout the various design phases (conceptual, preliminary design, etc.). In a previous paper [1] we discussed a probabilistic functional failure analysis approach intended mainly to support system requirements definition, system design, and element design during the early design phases. This paper provides an overview of the application of probabilistic engineering methods to support the detailed subsystem/component design and development as part of the "Design for Reliability and Safety" approach for the new Ares I Launch Vehicle. Specifically, the paper discusses probabilistic engineering design analysis cases that had major impact on the design and manufacturing of the Space Shuttle hardware. The cases represent important lessons learned from the Space Shuttle Program and clearly demonstrate the significance of probabilistic engineering analysis in better understanding design deficiencies and identifying potential design improvement for Ares I. The paper also discusses the probabilistic functional failure analysis approach applied during the early design phases of Ares I and the forward plans for probabilistic design analysis in the detailed design and development phases.

Probabilistic assessment of pressure vessel and piping reliability

International Nuclear Information System (INIS)

Sundararajan, C.

1986-01-01

The paper presents a critical review of the state-of-the-art in probabilistic assessment of pressure vessel and piping reliability. First the differences in assessing the reliability directly from historical failure data and indirectly by a probabilistic analysis of the failure phenomenon are discussed and the advantages and disadvantages are pointed out. The rest of the paper deals with the latter approach of reliability assessment. Methods of probabilistic reliability assessment are described and major projects where these methods are applied for pressure vessel and piping problems are discussed. An extensive list of references is provided at the end of the paper

Some thoughts on the future of probabilistic structural design of nuclear components

International Nuclear Information System (INIS)

Stancampiano, P.A.

1978-01-01

This paper presents some views on the future role of probabilistic methods in the structural design of nuclear components. The existing deterministic design approach is discussed and compared to the probabilistic approach. Some of the objections to both deterministic and probabilistic design are listed. Extensive research and development activities are required to mature the probabilistic approach suficiently to make it cost-effective and competitive with current deterministic design practices. The required research activities deal with probabilistic methods development, more realistic casual failure mode models development, and statistical data models development. A quasi-probabilistic structural design approach is recommended which accounts for the random error in the design models. (Auth.)

Comparison of manual & automated analysis methods for corneal endothelial cell density measurements by specular microscopy.

Science.gov (United States)

Huang, Jianyan; Maram, Jyotsna; Tepelus, Tudor C; Modak, Cristina; Marion, Ken; Sadda, SriniVas R; Chopra, Vikas; Lee, Olivia L

2017-08-07

To determine the reliability of corneal endothelial cell density (ECD) obtained by automated specular microscopy versus that of validated manual methods and factors that predict such reliability. Sharp central images from 94 control and 106 glaucomatous eyes were captured with Konan specular microscope NSP-9900. All images were analyzed by trained graders using Konan CellChek Software, employing the fully- and semi-automated methods as well as Center Method. Images with low cell count (input cells number <100) and/or guttata were compared with the Center and Flex-Center Methods. ECDs were compared and absolute error was used to assess variation. The effect on ECD of age, cell count, cell size, and cell size variation was evaluated. No significant difference was observed between the Center and Flex-Center Methods in corneas with guttata (p=0.48) or low ECD (p=0.11). No difference (p=0.32) was observed in ECD of normal controls <40 yrs old between the fully-automated method and manual Center Method. However, in older controls and glaucomatous eyes, ECD was overestimated by the fully-automated method (p=0.034) and semi-automated method (p=0.025) as compared to manual method. Our findings show that automated analysis significantly overestimates ECD in the eyes with high polymegathism and/or large cell size, compared to the manual method. Therefore, we discourage reliance upon the fully-automated method alone to perform specular microscopy analysis, particularly if an accurate ECD value is imperative. Copyright © 2017. Published by Elsevier España, S.L.U.

A Probabilistic Recommendation Method Inspired by Latent Dirichlet Allocation Model

Directory of Open Access Journals (Sweden)

WenBo Xie

2014-01-01

Full Text Available The recent decade has witnessed an increasing popularity of recommendation systems, which help users acquire relevant knowledge, commodities, and services from an overwhelming information ocean on the Internet. Latent Dirichlet Allocation (LDA, originally presented as a graphical model for text topic discovery, now has found its application in many other disciplines. In this paper, we propose an LDA-inspired probabilistic recommendation method by taking the user-item collecting behavior as a two-step process: every user first becomes a member of one latent user-group at a certain probability and each user-group will then collect various items with different probabilities. Gibbs sampling is employed to approximate all the probabilities in the two-step process. The experiment results on three real-world data sets MovieLens, Netflix, and Last.fm show that our method exhibits a competitive performance on precision, coverage, and diversity in comparison with the other four typical recommendation methods. Moreover, we present an approximate strategy to reduce the computing complexity of our method with a slight degradation of the performance.

Development of Nuclear Safety Culture evaluation method for an operation team based on the probabilistic approach

International Nuclear Information System (INIS)

Han, Sang Min; Lee, Seung Min; Yim, Ho Bin; Seong, Poong Hyun

2018-01-01

Highlights: •We proposed a Probabilistic Safety Culture Healthiness Evaluation Method. •Positive relationship between the ‘success’ states of NSC and performance was shown. •The state probability profile showed a unique ratio regardless of the scenarios. •Cutset analysis provided not only root causes but also the latent causes of failures. •Pro-SCHEMe was found to be applicable to Korea NPPs. -- Abstract: The aim of this study is to propose a new quantitative evaluation method for Nuclear Safety Culture (NSC) in Nuclear Power Plant (NPP) operation teams based on the probabilistic approach. Various NSC evaluation methods have been developed, and the Korea NPP utility company has conducted the NSC assessment according to international practice. However, most of methods are conducted by interviews, observations, and the self-assessment. Consequently, the results are often qualitative, subjective, and mainly dependent on evaluator’s judgement, so the assessment results can be interpreted from different perspectives. To resolve limitations of present evaluation methods, the concept of Safety Culture Healthiness was suggested to produce quantitative results and provide faster evaluation process. This paper presents Probabilistic Safety Culture Healthiness Evaluation Method (Pro-SCHEMe) to generate quantitative inputs for Human Reliability Assessment (HRA) in Probabilistic Safety Assessment (PSA). Evaluation items which correspond to a basic event in PSA are derived in the first part of the paper through the literature survey; mostly from nuclear-related organizations such as the International Atomic Energy Agency (IAEA), the United States Nuclear Regulatory Commission (U.S.NRC), and the Institute of Nuclear Power Operations (INPO). Event trees (ETs) and fault trees (FTs) are devised to apply evaluation items to PSA based on the relationships among such items. The Modeling Guidelines are also suggested to classify and calculate NSC characteristics of

Biasing transition rate method based on direct MC simulation for probabilistic safety assessment

Institute of Scientific and Technical Information of China (English)

Xiao-Lei Pan; Jia-Qun Wang; Run Yuan; Fang Wang; Han-Qing Lin; Li-Qin Hu; Jin Wang

2017-01-01

Direct Monte Carlo (MC) simulation is a powerful probabilistic safety assessment method for accounting dynamics of the system.But it is not efficient at simulating rare events.A biasing transition rate method based on direct MC simulation is proposed to solve the problem in this paper.This method biases transition rates of the components by adding virtual components to them in series to increase the occurrence probability of the rare event,hence the decrease in the variance of MC estimator.Several cases are used to benchmark this method.The results show that the method is effective at modeling system failure and is more efficient at collecting evidence of rare events than the direct MC simulation.The performance is greatly improved by the biasing transition rate method.

A probabilistic method for streamflow projection and associated uncertainty analysis in a data sparse alpine region

Science.gov (United States)

Ren, Weiwei; Yang, Tao; Shi, Pengfei; Xu, Chong-yu; Zhang, Ke; Zhou, Xudong; Shao, Quanxi; Ciais, Philippe

2018-06-01

Climate change imposes profound influence on regional hydrological cycle and water security in many alpine regions worldwide. Investigating regional climate impacts using watershed scale hydrological models requires a large number of input data such as topography, meteorological and hydrological data. However, data scarcity in alpine regions seriously restricts evaluation of climate change impacts on water cycle using conventional approaches based on global or regional climate models, statistical downscaling methods and hydrological models. Therefore, this study is dedicated to development of a probabilistic model to replace the conventional approaches for streamflow projection. The probabilistic model was built upon an advanced Bayesian Neural Network (BNN) approach directly fed by the large-scale climate predictor variables and tested in a typical data sparse alpine region, the Kaidu River basin in Central Asia. Results show that BNN model performs better than the general methods across a number of statistical measures. The BNN method with flexible model structures by active indicator functions, which reduce the dependence on the initial specification for the input variables and the number of hidden units, can work well in a data limited region. Moreover, it can provide more reliable streamflow projections with a robust generalization ability. Forced by the latest bias-corrected GCM scenarios, streamflow projections for the 21st century under three RCP emission pathways were constructed and analyzed. Briefly, the proposed probabilistic projection approach could improve runoff predictive ability over conventional methods and provide better support to water resources planning and management under data limited conditions as well as enable a facilitated climate change impact analysis on runoff and water resources in alpine regions worldwide.

Development of an Automated Decision-Making Tool for Supervisory Control System

Energy Technology Data Exchange (ETDEWEB)

Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Muhlheim, Michael David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Flanagan, George F. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kisner, Roger A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2014-09-01

This technical report was generated as a product of the Supervisory Control for Multi-Modular Small Modular Reactor (SMR) Plants project within the Instrumentation, Control and Human-Machine Interface technology area under the Advanced Small Modular Reactor (AdvSMR) Research and Development Program of the US Department of Energy. The report documents the definition of strategies, functional elements, and the structural architecture of a supervisory control system for multi-modular AdvSMR plants. This research activity advances the state of the art by incorporating real-time, probabilistic-based decision-making into the supervisory control system architectural layers through the introduction of a tiered-plant system approach. The report provides background information on the state of the art of automated decision-making, including the description of existing methodologies. It then presents a description of a generalized decision-making framework, upon which the supervisory control decision-making algorithm is based. The probabilistic portion of automated decision-making is demonstrated through a simple hydraulic loop example.

Implications of probabilistic risk assessment

International Nuclear Information System (INIS)

Cullingford, M.C.; Shah, S.M.; Gittus, J.H.

1987-01-01

Probabilistic risk assessment (PRA) is an analytical process that quantifies the likelihoods, consequences and associated uncertainties of the potential outcomes of postulated events. Starting with planned or normal operation, probabilistic risk assessment covers a wide range of potential accidents and considers the whole plant and the interactions of systems and human actions. Probabilistic risk assessment can be applied in safety decisions in design, licensing and operation of industrial facilities, particularly nuclear power plants. The proceedings include a review of PRA procedures, methods and technical issues in treating uncertainties, operating and licensing issues and future trends. Risk assessment for specific reactor types or components and specific risks (eg aircraft crashing onto a reactor) are used to illustrate the points raised. All 52 articles are indexed separately. (U.K.)

Decomposing the Hounsfield unit: probabilistic segmentation of brain tissue in computed tomography.

Science.gov (United States)

Kemmling, A; Wersching, H; Berger, K; Knecht, S; Groden, C; Nölte, I

2012-03-01

The aim of this study was to present and evaluate a standardized technique for brain segmentation of cranial computed tomography (CT) using probabilistic partial volume tissue maps based on a database of high resolution T1 magnetic resonance images (MRI). Probabilistic tissue maps of white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) were derived from 600 normal brain MRIs (3.0 Tesla, T1-3D-turbo-field-echo) of 2 large community-based population studies (BiDirect and SEARCH Health studies). After partial tissue segmentation (FAST 4.0), MR images were linearly registered to MNI-152 standard space (FLIRT 5.5) with non-linear refinement (FNIRT 1.0) to obtain non-binary probabilistic volume images for each tissue class which were subsequently used for CT segmentation. From 150 normal cerebral CT scans a customized reference image in standard space was constructed with iterative non-linear registration to MNI-152 space. The inverse warp of tissue-specific probability maps to CT space (MNI-152 to individual CT) was used to decompose a CT image into tissue specific components (GM, WM, CSF). Potential benefits and utility of this novel approach with regard to unsupervised quantification of CT images and possible visual enhancement are addressed. Illustrative examples of tissue segmentation in different pathological cases including perfusion CT are presented. Automated tissue segmentation of cranial CT images using highly refined tissue probability maps derived from high resolution MR images is feasible. Potential applications include automated quantification of WM in leukoaraiosis, CSF in hydrocephalic patients, GM in neurodegeneration and ischemia and perfusion maps with separate assessment of GM and WM.

Lossed in translation: an off-the-shelf method to recover probabilistic beliefs from loss-averse agents.

Science.gov (United States)

Offerman, Theo; Palley, Asa B

2016-01-01

Strictly proper scoring rules are designed to truthfully elicit subjective probabilistic beliefs from risk neutral agents. Previous experimental studies have identified two problems with this method: (i) risk aversion causes agents to bias their reports toward the probability of [Formula: see text], and (ii) for moderate beliefs agents simply report [Formula: see text]. Applying a prospect theory model of risk preferences, we show that loss aversion can explain both of these behavioral phenomena. Using the insights of this model, we develop a simple off-the-shelf probability assessment mechanism that encourages loss-averse agents to report true beliefs. In an experiment, we demonstrate the effectiveness of this modification in both eliminating uninformative reports and eliciting true probabilistic beliefs.

Testing an Automated Accuracy Assessment Method on Bibliographic Data

Directory of Open Access Journals (Sweden)

Marlies Olensky

2014-12-01

Full Text Available This study investigates automated data accuracy assessment as described in data quality literature for its suitability to assess bibliographic data. The data samples comprise the publications of two Nobel Prize winners in the field of Chemistry for a 10-year-publication period retrieved from the two bibliometric data sources, Web of Science and Scopus. The bibliographic records are assessed against the original publication (gold standard and an automatic assessment method is compared to a manual one. The results show that the manual assessment method reflects truer accuracy scores. The automated assessment method would need to be extended by additional rules that reflect specific characteristics of bibliographic data. Both data sources had higher accuracy scores per field than accumulated per record. This study contributes to the research on finding a standardized assessment method of bibliographic data accuracy as well as defining the impact of data accuracy on the citation matching process.

The dialectical thinking about deterministic and probabilistic safety analysis

International Nuclear Information System (INIS)

Qian Yongbai; Tong Jiejuan; Zhang Zuoyi; He Xuhong

2005-01-01

There are two methods in designing and analysing the safety performance of a nuclear power plant, the traditional deterministic method and the probabilistic method. To date, the design of nuclear power plant is based on the deterministic method. It has been proved in practice that the deterministic method is effective on current nuclear power plant. However, the probabilistic method (Probabilistic Safety Assessment - PSA) considers a much wider range of faults, takes an integrated look at the plant as a whole, and uses realistic criteria for the performance of the systems and constructions of the plant. PSA can be seen, in principle, to provide a broader and realistic perspective on safety issues than the deterministic approaches. In this paper, the historical origins and development trend of above two methods are reviewed and summarized in brief. Based on the discussion of two application cases - one is the changes to specific design provisions of the general design criteria (GDC) and the other is the risk-informed categorization of structure, system and component, it can be concluded that the deterministic method and probabilistic method are dialectical and unified, and that they are being merged into each other gradually, and being used in coordination. (authors)

Probabilistic method/techniques of evaluation/modeling that permits to optimize/reduce the necessary resources

International Nuclear Information System (INIS)

Florescu, G.; Apostol, M.; Farcasiu, M.; Luminita Bedreaga, M.; Nitoi, M.; Turcu, I.

2004-01-01

Fault tree/event tree modeling approach is widely used in modeling and behavior simulation of nuclear structures, systems and components (NSSCs), during different condition of operation. Evaluation of NSSCs reliability, availability, risk or safety, during operation, by using probabilistic techniques, is also largely used. Development of computer capabilities offered new possibilities for large NSSCs models designing, processing and using. There are situations where large, complex and correct NSSC models are desired to be associated with rapid results/solutions/decisions or with multiple processing in order to obtain specific results. Large fault/event trees are hardly to be developed, reviewed and processed. During operation of NSSCs, the time, especially, is an important factor in taking decision. The paper presents a probabilistic method that permits evaluation/modeling of NSSCs and intents to solve the above problems by adopting appropriate techniques. The method is stated for special applications and is based on specific PSA analysis steps, information, algorithms, criteria and relations, in correspondence with the fault tree/event tree modeling and similar techniques, in order to obtain appropriate results for NSSC model analysis. Special classification of NSSCs is stated in order to reflect aspects of use of the method. Also the common reliability databases are part of information necessary to complete the analysis process. Special data and information bases contribute to state the proposed method/techniques. The paper also presents the specific steps of the method, its applicability, the main advantages and problems to be furthermore studied. The method permits optimization/reducing of resources used to perform the PSA activities. (author)

A method for automated processing of measurement information during mechanical drilling

Energy Technology Data Exchange (ETDEWEB)

Samonenko, V.I.; Belinkov, V.G.; Romanova, L.A.

1984-01-01

An algorithm is cited for a developed method for automated processing of measurement information during mechanical drilling. Its use in conditions of operation of an automated control system (ASU) from drilling will make it possible to precisely identify a change in the lithology, the physical and mechanical and the abrasive properties, in the stratum (pore) pressure in the rock being drilled out during mechanical drilling, which along with other methods for testing the drilling process will increase the reliability of the decisions made.

Study radiolabeling of urea-based PSMA inhibitor with 68-Galliu: Comparative evaluation of automated and not automated methods

International Nuclear Information System (INIS)

Alcarde, Lais Fernanda

2016-01-01

The methods for clinical diagnosis of prostate cancer include rectal examination and the dosage of the prostatic specific antigen (PSA). However, the PSA level is elevated in about 20 to 30% of cases related to benign pathologies, resulting in false positives and leading patients to unnecessary biopsies. The prostate specific membrane antigen (PSMA), in contrast, is over expressed in prostate cancer and founded at low levels in healthy organs. As a result, it stimulated the development of small molecule inhibitors of PSMA, which carry imaging agents to the tumor and are not affected by their microvasculature. Recent studies suggest that the HBED-CC chelator intrinsically contributes to the binding of the PSMA inhibitor peptide based on urea (Glu-urea-Lys) to the pharmacophore group. This work describes the optimization of radiolabeling conditions of PSMA-HBED-CC with "6"8Ga, using automated system (synthesis module) and no automated method, seeking to establish an appropriate condition to prepare this new radiopharmaceutical, with emphasis on the labeling yield and radiochemical purity of the product. It also aimed to evaluate the stability of the radiolabeled peptide in transport conditions and study the biological distribution of the radiopharmaceutical in healthy mice. The study of radiolabeling parameters enabled to define a non-automated method which resulted in high radiochemical purity (> 95 %) without the need for purification of the labeled peptide. The automated method has been adapted, using a module of synthesis and software already available at IPEN, and also resulted in high synthetic yield (≥ 90%) specially when compared with those described in the literature, with the associated benefit of greater control of the production process in compliance with Good Manufacturing Practices. The study of radiolabeling parameters afforded the PSMA-HBED-CC-"6"8Ga with higher specific activity than observed in published clinical studies (≥ 140,0 GBq

Probabilistic insurance

OpenAIRE

Wakker, P.P.; Thaler, R.H.; Tversky, A.

1997-01-01

textabstractProbabilistic insurance is an insurance policy involving a small probability that the consumer will not be reimbursed. Survey data suggest that people dislike probabilistic insurance and demand more than a 20% reduction in the premium to compensate for a 1% default risk. While these preferences are intuitively appealing they are difficult to reconcile with expected utility theory. Under highly plausible assumptions about the utility function, willingness to pay for probabilistic i...

Fully probabilistic design: the way for optimizing of concrete structures

Directory of Open Access Journals (Sweden)

I. Laníková

Full Text Available Some standards for the design of concrete structures (e.g. EC2 and the original ČSN 73 1201-86 allow a structure to be designed by several methods. This contribution documents the fact that even if a structure does not comply with the partial reliability factor method, according to EC2, it can satisfy the conditions during the application of the fully probabilistic approach when using the same standard. From an example of the reliability of a prestressed spun concrete pole designed by the partial factor method and fully probabilistic approach according to the Eurocode it is evident that an expert should apply a more precise (though unfortunately more complicated method in the limiting cases. The Monte Carlo method, modified by the Latin Hypercube Sampling (LHS method, has been used for the calculation of reliability. Ultimate and serviceability limit states were checked for the partial factor method and fully probabilistic design. As a result of fully probabilistic design it is possible to obtain a more efficient design for a structure.

Non-destructive automated express method for determining the inclination of chromium-nickel steels IGC

International Nuclear Information System (INIS)

Nazarov, A.A.; Kamenev, Yu.B.; Kuusk, L.V.; Kormin, E.G.; Vasil'ev, A.N.; Sumbaeva, T.E.

1986-01-01

Methods of automated control of 18-10-type steel inclination to IGC are developed and a corresponding automated testing complex (ATS) is created. 08Kh18N10T steel samples had two variants of thermal treatment: 1) 1200 deg (5 h), 600 deg (50 h); 2) 1200 deg (5 h). Methods of non-destructive automated control of 18-10-type steel inclination to IGC are developed on the basis of potentiodynamic reactivation (PR) principle. Automated testing complex is developed, which has undergone experimental running and demonstrated a high confidence of results, reliability and easy operation

Automatic segmentation of coronary angiograms based on fuzzy inferring and probabilistic tracking

Directory of Open Access Journals (Sweden)

Shoujun Zhou

2010-08-01

Full Text Available Abstract Background Segmentation of the coronary angiogram is important in computer-assisted artery motion analysis or reconstruction of 3D vascular structures from a single-plan or biplane angiographic system. Developing fully automated and accurate vessel segmentation algorithms is highly challenging, especially when extracting vascular structures with large variations in image intensities and noise, as well as with variable cross-sections or vascular lesions. Methods This paper presents a novel tracking method for automatic segmentation of the coronary artery tree in X-ray angiographic images, based on probabilistic vessel tracking and fuzzy structure pattern inferring. The method is composed of two main steps: preprocessing and tracking. In preprocessing, multiscale Gabor filtering and Hessian matrix analysis were used to enhance and extract vessel features from the original angiographic image, leading to a vessel feature map as well as a vessel direction map. In tracking, a seed point was first automatically detected by analyzing the vessel feature map. Subsequently, two operators [e.g., a probabilistic tracking operator (PTO and a vessel structure pattern detector (SPD] worked together based on the detected seed point to extract vessel segments or branches one at a time. The local structure pattern was inferred by a multi-feature based fuzzy inferring function employed in the SPD. The identified structure pattern, such as crossing or bifurcation, was used to control the tracking process, for example, to keep tracking the current segment or start tracking a new one, depending on the detected pattern. Results By appropriate integration of these advanced preprocessing and tracking steps, our tracking algorithm is able to extract both vessel axis lines and edge points, as well as measure the arterial diameters in various complicated cases. For example, it can walk across gaps along the longitudinal vessel direction, manage varying vessel

Automated Methods Of Corrosion Measurements

DEFF Research Database (Denmark)

Bech-Nielsen, Gregers; Andersen, Jens Enevold Thaulov; Reeve, John Ch

1997-01-01

The chapter describes the following automated measurements: Corrosion Measurements by Titration, Imaging Corrosion by Scanning Probe Microscopy, Critical Pitting Temperature and Application of the Electrochemical Hydrogen Permeation Cell.......The chapter describes the following automated measurements: Corrosion Measurements by Titration, Imaging Corrosion by Scanning Probe Microscopy, Critical Pitting Temperature and Application of the Electrochemical Hydrogen Permeation Cell....

Workload Capacity: A Response Time-Based Measure of Automation Dependence.

Science.gov (United States)

Yamani, Yusuke; McCarley, Jason S

2016-05-01

An experiment used the workload capacity measure C(t) to quantify the processing efficiency of human-automation teams and identify operators' automation usage strategies in a speeded decision task. Although response accuracy rates and related measures are often used to measure the influence of an automated decision aid on human performance, aids can also influence response speed. Mean response times (RTs), however, conflate the influence of the human operator and the automated aid on team performance and may mask changes in the operator's performance strategy under aided conditions. The present study used a measure of parallel processing efficiency, or workload capacity, derived from empirical RT distributions as a novel gauge of human-automation performance and automation dependence in a speeded task. Participants performed a speeded probabilistic decision task with and without the assistance of an automated aid. RT distributions were used to calculate two variants of a workload capacity measure, COR(t) and CAND(t). Capacity measures gave evidence that a diagnosis from the automated aid speeded human participants' responses, and that participants did not moderate their own decision times in anticipation of diagnoses from the aid. Workload capacity provides a sensitive and informative measure of human-automation performance and operators' automation dependence in speeded tasks. © 2016, Human Factors and Ergonomics Society.

Probabilistic Design of Coastal Flood Defences in Vietnam

NARCIS (Netherlands)

Mai Van, C.

2010-01-01

This study further develops the method of probabilistic design and to address a knowledge gap in its application regarding safety and reliability, risk assessment and risk evaluation to the fields of flood defences. The thesis discusses: - a generic probabilistic design framework for assessing flood

Probabilistic evaluation method for axial capacity of single pile based on pile test information. Saika shiken kekka wo koryoshita kuienchoku shijiryoku no kakuritsuronteki hyokaho

Energy Technology Data Exchange (ETDEWEB)

Ishii, K.; Suzuki, M. (Shimizu Construction Co. Ltd., Tokyo (Japan)); Nakatani, S. (Ministry of Construction Tokyo (Japan)); Matsui, K. (CTI Engineering Co. Ltd., Tokyo (Japan))

1991-12-20

To consider the safety and economics in the design of pile, the reasonable evaluation on estimated accuracy from the accuracy of equation of pile capacity and probabilistic evaluation method is necessary. Therefore, the data analysis based on the collection and summary of the results from load tests of piles is one of powerful approach. In this study, selection of the parameters that cannot obtained from probabilistic model and load test and combination between statistical and experimental data by using Baysian probabilistic theory was examined. As the feature of this study, use of the design pile capacity equation based on the model of evaluation of pile capacity, consideration of the intrinsic difference between statistical data and results of load tests by using Baysian probabilistic theory and quantitative examination of applicability of the proposed method and the results of load tests are given. 24 refs., 5 figs., 7 tabs.

ISSUES ASSOCIATED WITH PROBABILISTIC FAILURE MODELING OF DIGITAL SYSTEMS

International Nuclear Information System (INIS)

CHU, T.L.; MARTINEZ-GURIDI, G.; LIHNER, J.; OVERLAND, D.

2004-01-01

The current U.S. Nuclear Regulatory Commission (NRC) licensing process of instrumentation and control (I and C) systems is based on deterministic requirements, e.g., single failure criteria, and defense in depth and diversity. Probabilistic considerations can be used as supplements to the deterministic process. The National Research Council has recommended development of methods for estimating failure probabilities of digital systems, including commercial off-the-shelf (COTS) equipment, for use in probabilistic risk assessment (PRA). NRC staff has developed informal qualitative and quantitative requirements for PRA modeling of digital systems. Brookhaven National Laboratory (BNL) has performed a review of the-state-of-the-art of the methods and tools that can potentially be used to model digital systems. The objectives of this paper are to summarize the review, discuss the issues associated with probabilistic modeling of digital systems, and identify potential areas of research that would enhance the state of the art toward a satisfactory modeling method that could be integrated with a typical probabilistic risk assessment

Review of the Brunswick Steam Electric Plant Probabilistic Risk Assessment

International Nuclear Information System (INIS)

Sattison, M.B.; Davis, P.R.; Satterwhite, D.G.; Gilmore, W.E.; Gregg, R.E.

1989-11-01

A review of the Brunswick Steam Electric Plant probabilistic risk Assessment was conducted with the objective of confirming the safety perspectives brought to light by the probabilistic risk assessment. The scope of the review included the entire Level I probabilistic risk assessment including external events. This is consistent with the scope of the probabilistic risk assessment. The review included an assessment of the assumptions, methods, models, and data used in the study. 47 refs., 14 figs., 15 tabs

Probabilistic Design and Analysis Framework

Science.gov (United States)

Strack, William C.; Nagpal, Vinod K.

2010-01-01

PRODAF is a software package designed to aid analysts and designers in conducting probabilistic analysis of components and systems. PRODAF can integrate multiple analysis programs to ease the tedious process of conducting a complex analysis process that requires the use of multiple software packages. The work uses a commercial finite element analysis (FEA) program with modules from NESSUS to conduct a probabilistic analysis of a hypothetical turbine blade, disk, and shaft model. PRODAF applies the response surface method, at the component level, and extrapolates the component-level responses to the system level. Hypothetical components of a gas turbine engine are first deterministically modeled using FEA. Variations in selected geometrical dimensions and loading conditions are analyzed to determine the effects of the stress state within each component. Geometric variations include the cord length and height for the blade, inner radius, outer radius, and thickness, which are varied for the disk. Probabilistic analysis is carried out using developing software packages like System Uncertainty Analysis (SUA) and PRODAF. PRODAF was used with a commercial deterministic FEA program in conjunction with modules from the probabilistic analysis program, NESTEM, to perturb loads and geometries to provide a reliability and sensitivity analysis. PRODAF simplified the handling of data among the various programs involved, and will work with many commercial and opensource deterministic programs, probabilistic programs, or modules.

Probabilistic assessment of nuclear safety and safeguards

International Nuclear Information System (INIS)

Higson, D.J.

1987-01-01

Nuclear reactor accidents and diversions of materials from the nuclear fuel cycle are perceived by many people as particularly serious threats to society. Probabilistic assessment is a rational approach to the evaluation of both threats, and may provide a basis for decisions on appropriate actions to control them. Probabilistic method have become standard tools used in the analysis of safety, but there are disagreements on the criteria to be applied when assessing the results of analysis. Probabilistic analysis and assessment of the effectiveness of nuclear material safeguards are still at an early stage of development. (author)

Non-unitary probabilistic quantum computing

Science.gov (United States)

Gingrich, Robert M.; Williams, Colin P.

2004-01-01

We present a method for designing quantum circuits that perform non-unitary quantum computations on n-qubit states probabilistically, and give analytic expressions for the success probability and fidelity.

Potential theory for stationary Schrödinger operators: a survey of results obtained with non-probabilistic methods

Directory of Open Access Journals (Sweden)

Marco Bramanti

1992-05-01

Full Text Available In this paper we deal with a uniformly elliptic operator of the kind: Lu  Au + Vu, where the principal part A is in divergence form, and V is a function assumed in a “Kato class”. This operator has been studied in different contexts, especially using probabilistic techniques. The aim of the present work is to give a unified and simplified presentation of the results obtained with non probabilistic methods for the operator L on a bounded Lipschitz domain. These results regard: continuity of the solutions of Lu=0; Harnack inequality; estimates on the Green's function and L-harmonic measure; boundary behavior of positive solutions of Lu=0, in particular a “Fatou's theorem”.

An automated repair method of water pipe infrastructure using carbon fiber bundles

Science.gov (United States)

Wisotzkey, Sean; Carr, Heath; Fyfe, Ed

2011-04-01

The United States water pipe infrastructure is made up of over 2 million miles of pipe. Due to age and deterioration, a large portion of this pipe is in need of repair to prevent catastrophic failures. Current repair methods generally involve intrusive techniques that can be time consuming and costly, but also can cause major societal impacts. A new automated repair method incorporating innovative carbon fiber technology is in development. This automated method would eliminate the need for trenching and would vastly cut time and labor costs, providing a much more economical pipe repair solution.

An application of probabilistic safety assessment methods to model aircraft systems and accidents

Energy Technology Data Exchange (ETDEWEB)

Martinez-Guridi, G.; Hall, R.E.; Fullwood, R.R.

1998-08-01

A case study modeling the thrust reverser system (TRS) in the context of the fatal accident of a Boeing 767 is presented to illustrate the application of Probabilistic Safety Assessment methods. A simplified risk model consisting of an event tree with supporting fault trees was developed to represent the progression of the accident, taking into account the interaction between the TRS and the operating crew during the accident, and the findings of the accident investigation. A feasible sequence of events leading to the fatal accident was identified. Several insights about the TRS and the accident were obtained by applying PSA methods. Changes proposed for the TRS also are discussed.

The Halden Reactor Project workshop meeting on human centred automation and function allocation methods

International Nuclear Information System (INIS)

Sebok, Angelia; Green, Marit; Larsen, Marit; Miberg, Ann Britt; Morisseau, Dolores

1998-02-01

A workshop on Human Centred Automation (HCA) and Function Allocation Methods was organised in Halden, September 29-30, 1997. The purpose of the workshop was to discuss and make recommendations on requirements for the Halden Project research agenda. The workshop meeting began with several presentations summarising current issues in HCA, Function Allocation Methods and Functional Modelling. Invited speakers presented their research or modelling efforts. Following the presentations, the workshop was divided into three working groups, all tasked with answering the same four questions: (1) What are the most important issues in Human Centred Automation? (2) Which strengths could be achieved by integrating Functional Modelling Methods into experimental Human Centred Automation research? (3) How should analytical and experimental methods be balanced? (4) What are the most important aspects in automation design methodology? Each group discussed the questions and produced specific recommendations that were summarised by the group's facilitator in a joint session of the workshop. (author)

Methods for Probabilistic Fault Diagnosis: An Electrical Power System Case Study

Science.gov (United States)

Ricks, Brian W.; Mengshoel, Ole J.

2009-01-01

Health management systems that more accurately and quickly diagnose faults that may occur in different technical systems on-board a vehicle will play a key role in the success of future NASA missions. We discuss in this paper the diagnosis of abrupt continuous (or parametric) faults within the context of probabilistic graphical models, more specifically Bayesian networks that are compiled to arithmetic circuits. This paper extends our previous research, within the same probabilistic setting, on diagnosis of abrupt discrete faults. Our approach and diagnostic algorithm ProDiagnose are domain-independent; however we use an electrical power system testbed called ADAPT as a case study. In one set of ADAPT experiments, performed as part of the 2009 Diagnostic Challenge, our system turned out to have the best performance among all competitors. In a second set of experiments, we show how we have recently further significantly improved the performance of the probabilistic model of ADAPT. While these experiments are obtained for an electrical power system testbed, we believe they can easily be transitioned to real-world systems, thus promising to increase the success of future NASA missions.

Method and system for dynamic probabilistic risk assessment

Science.gov (United States)

Dugan, Joanne Bechta (Inventor); Xu, Hong (Inventor)

2013-01-01

The DEFT methodology, system and computer readable medium extends the applicability of the PRA (Probabilistic Risk Assessment) methodology to computer-based systems, by allowing DFT (Dynamic Fault Tree) nodes as pivot nodes in the Event Tree (ET) model. DEFT includes a mathematical model and solution algorithm, supports all common PRA analysis functions and cutsets. Additional capabilities enabled by the DFT include modularization, phased mission analysis, sequence dependencies, and imperfect coverage.

Toward automated assessment of health Web page quality using the DISCERN instrument.

Science.gov (United States)

Allam, Ahmed; Schulz, Peter J; Krauthammer, Michael

2017-05-01

As the Internet becomes the number one destination for obtaining health-related information, there is an increasing need to identify health Web pages that convey an accurate and current view of medical knowledge. In response, the research community has created multicriteria instruments for reliably assessing online medical information quality. One such instrument is DISCERN, which measures health Web page quality by assessing an array of features. In order to scale up use of the instrument, there is interest in automating the quality evaluation process by building machine learning (ML)-based DISCERN Web page classifiers. The paper addresses 2 key issues that are essential before constructing automated DISCERN classifiers: (1) generation of a robust DISCERN training corpus useful for training classification algorithms, and (2) assessment of the usefulness of the current DISCERN scoring schema as a metric for evaluating the performance of these algorithms. Using DISCERN, 272 Web pages discussing treatment options in breast cancer, arthritis, and depression were evaluated and rated by trained coders. First, different consensus models were compared to obtain a robust aggregated rating among the coders, suitable for a DISCERN ML training corpus. Second, a new DISCERN scoring criterion was proposed (features-based score) as an ML performance metric that is more reflective of the score distribution across different DISCERN quality criteria. First, we found that a probabilistic consensus model applied to the DISCERN instrument was robust against noise (random ratings) and superior to other approaches for building a training corpus. Second, we found that the established DISCERN scoring schema (overall score) is ill-suited to measure ML performance for automated classifiers. Use of a probabilistic consensus model is advantageous for building a training corpus for the DISCERN instrument, and use of a features-based score is an appropriate ML metric for automated DISCERN

Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

Science.gov (United States)

Orhan, A Emin; Ma, Wei Ji

2017-07-26

Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

Probabilistic Structural Analysis of SSME Turbopump Blades: Probabilistic Geometry Effects

Science.gov (United States)

Nagpal, V. K.

1985-01-01

A probabilistic study was initiated to evaluate the precisions of the geometric and material properties tolerances on the structural response of turbopump blades. To complete this study, a number of important probabilistic variables were identified which are conceived to affect the structural response of the blade. In addition, a methodology was developed to statistically quantify the influence of these probabilistic variables in an optimized way. The identified variables include random geometric and material properties perturbations, different loadings and a probabilistic combination of these loadings. Influences of these probabilistic variables are planned to be quantified by evaluating the blade structural response. Studies of the geometric perturbations were conducted for a flat plate geometry as well as for a space shuttle main engine blade geometry using a special purpose code which uses the finite element approach. Analyses indicate that the variances of the perturbations about given mean values have significant influence on the response.

A random probabilistic approach to seismic nuclear power plant analysis

International Nuclear Information System (INIS)

Romo, M.P.

1985-01-01

A probabilistic method for the seismic analysis of structures which takes into account the random nature of earthquakes and of the soil parameter uncertainties is presented in this paper. The method was developed combining elements of the theory of perturbations, the Random vibration theory and the complex response method. The probabilistic method is evaluated by comparing the responses of a single degree of freedom system computed with this approach and the Monte Carlo method. (orig.)

Biological sequence analysis: probabilistic models of proteins and nucleic acids

National Research Council Canada - National Science Library

Durbin, Richard

1998-01-01

... analysis methods are now based on principles of probabilistic modelling. Examples of such methods include the use of probabilistically derived score matrices to determine the significance of sequence alignments, the use of hidden Markov models as the basis for profile searches to identify distant members of sequence families, and the inference...

Probabilistic assessment of faults

International Nuclear Information System (INIS)

Foden, R.W.

1987-01-01

Probabilistic safety analysis (PSA) is the process by which the probability (or frequency of occurrence) of reactor fault conditions which could lead to unacceptable consequences is assessed. The basic objective of a PSA is to allow a judgement to be made as to whether or not the principal probabilistic requirement is satisfied. It also gives insights into the reliability of the plant which can be used to identify possible improvements. This is explained in the article. The scope of a PSA and the PSA performed by the National Nuclear Corporation (NNC) for the Heysham II and Torness AGRs and Sizewell-B PWR are discussed. The NNC methods for hazards, common cause failure and operator error are mentioned. (UK)

On Probabilistic Alpha-Fuzzy Fixed Points and Related Convergence Results in Probabilistic Metric and Menger Spaces under Some Pompeiu-Hausdorff-Like Probabilistic Contractive Conditions

OpenAIRE

De la Sen, M.

2015-01-01

In the framework of complete probabilistic metric spaces and, in particular, in probabilistic Menger spaces, this paper investigates some relevant properties of convergence of sequences to probabilistic α-fuzzy fixed points under some types of probabilistic contractive conditions.

Comparison of probabilistic and deterministic fiber tracking of cranial nerves.

Science.gov (United States)

Zolal, Amir; Sobottka, Stephan B; Podlesek, Dino; Linn, Jennifer; Rieger, Bernhard; Juratli, Tareq A; Schackert, Gabriele; Kitzler, Hagen H

2017-09-01

OBJECTIVE The depiction of cranial nerves (CNs) using diffusion tensor imaging (DTI) is of great interest in skull base tumor surgery and DTI used with deterministic tracking methods has been reported previously. However, there are still no good methods usable for the elimination of noise from the resulting depictions. The authors have hypothesized that probabilistic tracking could lead to more accurate results, because it more efficiently extracts information from the underlying data. Moreover, the authors have adapted a previously described technique for noise elimination using gradual threshold increases to probabilistic tracking. To evaluate the utility of this new approach, a comparison is provided with this work between the gradual threshold increase method in probabilistic and deterministic tracking of CNs. METHODS Both tracking methods were used to depict CNs II, III, V, and the VII+VIII bundle. Depiction of 240 CNs was attempted with each of the above methods in 30 healthy subjects, which were obtained from 2 public databases: the Kirby repository (KR) and Human Connectome Project (HCP). Elimination of erroneous fibers was attempted by gradually increasing the respective thresholds (fractional anisotropy [FA] and probabilistic index of connectivity [PICo]). The results were compared with predefined ground truth images based on corresponding anatomical scans. Two label overlap measures (false-positive error and Dice similarity coefficient) were used to evaluate the success of both methods in depicting the CN. Moreover, the differences between these parameters obtained from the KR and HCP (with higher angular resolution) databases were evaluated. Additionally, visualization of 10 CNs in 5 clinical cases was attempted with both methods and evaluated by comparing the depictions with intraoperative findings. RESULTS Maximum Dice similarity coefficients were significantly higher with probabilistic tracking (p cranial nerves. Probabilistic tracking with a gradual

On revision of partially specified convex probabilistic belief bases

CSIR Research Space (South Africa)

Rens, G

2016-08-01

Full Text Available We propose a method for an agent to revise its incomplete probabilistic beliefs when a new piece of propositional information is observed. In this work, an agent’s beliefs are represented by a set of probabilistic formulae – a belief base...

White matter hyperintensities segmentation: a new semi-automated method

Directory of Open Access Journals (Sweden)

Mariangela eIorio

2013-12-01

Full Text Available White matter hyperintensities (WMH are brain areas of increased signal on T2-weighted or fluid attenuated inverse recovery magnetic resonance imaging (MRI scans. In this study we present a new semi-automated method to measure WMH load that is based on the segmentation of the intensity histogram of fluid-attenuated inversion recovery images. Thirty patients with Mild Cognitive Impairment with variable WMH load were enrolled. The semi-automated WMH segmentation included: removal of non-brain tissue, spatial normalization, removal of cerebellum and brain stem, spatial filtering, thresholding to segment probable WMH, manual editing for correction of false positives and negatives, generation of WMH map and volumetric estimation of the WMH load. Accuracy was quantitatively evaluated by comparing semi-automated and manual WMH segmentations performed by two independent raters. Differences between the two procedures were assessed using Student’s t tests and similarity was evaluated using linear regression model and Dice Similarity Coefficient (DSC. The volumes of the manual and semi-automated segmentations did not statistically differ (t-value= -1.79, DF=29, p= 0.839 for rater 1; t-value= 1.113, DF=29, p= 0.2749 for rater 2, were highly correlated (R²= 0.921, F (1,29 =155,54, p

Probabilistic Insurance

NARCIS (Netherlands)

Wakker, P.P.; Thaler, R.H.; Tversky, A.

1997-01-01

Probabilistic insurance is an insurance policy involving a small probability that the consumer will not be reimbursed. Survey data suggest that people dislike probabilistic insurance and demand more than a 20% reduction in premium to compensate for a 1% default risk. These observations cannot be

Probabilistic Insurance

NARCIS (Netherlands)

P.P. Wakker (Peter); R.H. Thaler (Richard); A. Tversky (Amos)

1997-01-01

textabstractProbabilistic insurance is an insurance policy involving a small probability that the consumer will not be reimbursed. Survey data suggest that people dislike probabilistic insurance and demand more than a 20% reduction in the premium to compensate for a 1% default risk. While these

A semi-automated method for bone age assessment using cervical vertebral maturation.

Science.gov (United States)

Baptista, Roberto S; Quaglio, Camila L; Mourad, Laila M E H; Hummel, Anderson D; Caetano, Cesar Augusto C; Ortolani, Cristina Lúcia F; Pisa, Ivan T

2012-07-01

To propose a semi-automated method for pattern classification to predict individuals' stage of growth based on morphologic characteristics that are described in the modified cervical vertebral maturation (CVM) method of Baccetti et al. A total of 188 lateral cephalograms were collected, digitized, evaluated manually, and grouped into cervical stages by two expert examiners. Landmarks were located on each image and measured. Three pattern classifiers based on the Naïve Bayes algorithm were built and assessed using a software program. The classifier with the greatest accuracy according to the weighted kappa test was considered best. The classifier showed a weighted kappa coefficient of 0.861 ± 0.020. If an adjacent estimated pre-stage or poststage value was taken to be acceptable, the classifier would show a weighted kappa coefficient of 0.992 ± 0.019. Results from this study show that the proposed semi-automated pattern classification method can help orthodontists identify the stage of CVM. However, additional studies are needed before this semi-automated classification method for CVM assessment can be implemented in clinical practice.

An automated approach for annual layer counting in ice cores

Directory of Open Access Journals (Sweden)

M. Winstrup

2012-11-01

Full Text Available A novel method for automated annual layer counting in seasonally-resolved paleoclimate records has been developed. It relies on algorithms from the statistical framework of hidden Markov models (HMMs, which originally was developed for use in machine speech recognition. The strength of the layer detection algorithm lies in the way it is able to imitate the manual procedures for annual layer counting, while being based on statistical criteria for annual layer identification. The most likely positions of multiple layer boundaries in a section of ice core data are determined simultaneously, and a probabilistic uncertainty estimate of the resulting layer count is provided, ensuring an objective treatment of ambiguous layers in the data. Furthermore, multiple data series can be incorporated and used simultaneously. In this study, the automated layer counting algorithm has been applied to two ice core records from Greenland: one displaying a distinct annual signal and one which is more challenging. The algorithm shows high skill in reproducing the results from manual layer counts, and the resulting timescale compares well to absolute-dated volcanic marker horizons where these exist.

Comparison of manual and automated pretreatment methods for AMS radiocarbon dating of plant fossils

Science.gov (United States)

Bradley, L.A.; Stafford, Thomas W.

1994-01-01

A new automated pretreatment system for the preparation of materials submitted for accelerator mass spectrometry (AMS) analysis is less time-consuming and results in a higher sample yield. The new procedure was tested using two groups of plant fossils: one group was pretreated using the traditional method, and the second, using the automated pretreatment apparatus. The time it took to complete the procedure and the amount of sample material remaining were compared. The automated pretreatment apparatus proved to be more than three times faster and, in most cases, produced a higher yield. A darker discoloration of the KOH solutions was observed indicating that the automated system is more thorough in removing humates from the specimen compared to the manual method. -Authors

Automated search method for AFM and profilers

Science.gov (United States)

Ray, Michael; Martin, Yves C.

2001-08-01

A new automation software creates a search model as an initial setup and searches for a user-defined target in atomic force microscopes or stylus profilometers used in semiconductor manufacturing. The need for such automation has become critical in manufacturing lines. The new method starts with a survey map of a small area of a chip obtained from a chip-design database or an image of the area. The user interface requires a user to point to and define a precise location to be measured, and to select a macro function for an application such as line width or contact hole. The search algorithm automatically constructs a range of possible scan sequences within the survey, and provides increased speed and functionality compared to the methods used in instruments to date. Each sequence consists in a starting point relative to the target, a scan direction, and a scan length. The search algorithm stops when the location of a target is found and criteria for certainty in positioning is met. With today's capability in high speed processing and signal control, the tool can simultaneously scan and search for a target in a robotic and continuous manner. Examples are given that illustrate the key concepts.

An automated full-symmetry Patterson search method

International Nuclear Information System (INIS)

Rius, J.; Miravitlles, C.

1987-01-01

A full-symmetry Patterson search method is presented that performs a molecular coarse rotation search in vector space and orientation refinement using the σ function. The oriented molecule is positioned using the fast translation function τ 0 , which is based on the automated interpretation of τ projections using the sum function. This strategy reduces the number of Patterson-function values to be stored in the rotation search, and the use of the τ 0 function minimizes the required time for the development of all probable rotation search solutions. The application of this method to five representative test examples is shown. (orig.)

A new automated colorimetric method for measuring total oxidant status.

Science.gov (United States)

Erel, Ozcan

2005-12-01

To develop a new, colorimetric and automated method for measuring total oxidation status (TOS). The assay is based on the oxidation of ferrous ion to ferric ion in the presence of various oxidant species in acidic medium and the measurement of the ferric ion by xylenol orange. The oxidation reaction of the assay was enhanced and precipitation of proteins was prevented. In addition, autoxidation of ferrous ion present in the reagent was prevented during storage. The method was applied to an automated analyzer, which was calibrated with hydrogen peroxide and the analytical performance characteristics of the assay were determined. There were important correlations with hydrogen peroxide, tert-butyl hydroperoxide and cumene hydroperoxide solutions (r=0.99, Ptotal antioxidant capacity (TAC) (r=-0.66 Ptotal oxidant status.

Probabilistic costing of transmission services

International Nuclear Information System (INIS)

Wijayatunga, P.D.C.

1992-01-01

Costing of transmission services of electrical utilities is required for transactions involving the transport of energy over a power network. The calculation of these costs based on Short Run Marginal Costing (SRMC) is preferred over other methods proposed in the literature due to its economic efficiency. In the research work discussed here, the concept of probabilistic costing of use-of-system based on SRMC which emerges as a consequence of the uncertainties in a power system is introduced using two different approaches. The first approach, based on the Monte Carlo method, generates a large number of possible system states by simulating random variables in the system using pseudo random number generators. A second approach to probabilistic use-of-system costing is proposed based on numerical convolution and multi-area representation of the transmission network. (UK)

Automated PCR setup for forensic casework samples using the Normalization Wizard and PCR Setup robotic methods.

Science.gov (United States)

Greenspoon, S A; Sykes, K L V; Ban, J D; Pollard, A; Baisden, M; Farr, M; Graham, N; Collins, B L; Green, M M; Christenson, C C

2006-12-20

Human genome, pharmaceutical and research laboratories have long enjoyed the application of robotics to performing repetitive laboratory tasks. However, the utilization of robotics in forensic laboratories for processing casework samples is relatively new and poses particular challenges. Since the quantity and quality (a mixture versus a single source sample, the level of degradation, the presence of PCR inhibitors) of the DNA contained within a casework sample is unknown, particular attention must be paid to procedural susceptibility to contamination, as well as DNA yield, especially as it pertains to samples with little biological material. The Virginia Department of Forensic Science (VDFS) has successfully automated forensic casework DNA extraction utilizing the DNA IQ(trade mark) System in conjunction with the Biomek 2000 Automation Workstation. Human DNA quantitation is also performed in a near complete automated fashion utilizing the AluQuant Human DNA Quantitation System and the Biomek 2000 Automation Workstation. Recently, the PCR setup for casework samples has been automated, employing the Biomek 2000 Automation Workstation and Normalization Wizard, Genetic Identity version, which utilizes the quantitation data, imported into the software, to create a customized automated method for DNA dilution, unique to that plate of DNA samples. The PCR Setup software method, used in conjunction with the Normalization Wizard method and written for the Biomek 2000, functions to mix the diluted DNA samples, transfer the PCR master mix, and transfer the diluted DNA samples to PCR amplification tubes. Once the process is complete, the DNA extracts, still on the deck of the robot in PCR amplification strip tubes, are transferred to pre-labeled 1.5 mL tubes for long-term storage using an automated method. The automation of these steps in the process of forensic DNA casework analysis has been accomplished by performing extensive optimization, validation and testing of the

Probabilistic biological network alignment.

Science.gov (United States)

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-01-01

Interactions between molecules are probabilistic events. An interaction may or may not happen with some probability, depending on a variety of factors such as the size, abundance, or proximity of the interacting molecules. In this paper, we consider the problem of aligning two biological networks. Unlike existing methods, we allow one of the two networks to contain probabilistic interactions. Allowing interaction probabilities makes the alignment more biologically relevant at the expense of explosive growth in the number of alternative topologies that may arise from different subsets of interactions that take place. We develop a novel method that efficiently and precisely characterizes this massive search space. We represent the topological similarity between pairs of aligned molecules (i.e., proteins) with the help of random variables and compute their expected values. We validate our method showing that, without sacrificing the running time performance, it can produce novel alignments. Our results also demonstrate that our method identifies biologically meaningful mappings under a comprehensive set of criteria used in the literature as well as the statistical coherence measure that we developed to analyze the statistical significance of the similarity of the functions of the aligned protein pairs.

Foundations of the Formal Sciences VI: Probabilistic reasoning and reasoning with probabilities

NARCIS (Netherlands)

Löwe, B.; Pacuit, E.; Romeijn, J.W.

2009-01-01

Probabilistic methods are increasingly becoming an important tool in a variety of disciplines including computer science, mathematics, artificial intelligence, epistemology, game and decision theory and linguistics. In addition to the discussion on applications of probabilistic methods there is an

Probabilistic Simulation of Multi-Scale Composite Behavior

Science.gov (United States)

Chamis, Christos C.

2012-01-01

A methodology is developed to computationally assess the non-deterministic composite response at all composite scales (from micro to structural) due to the uncertainties in the constituent (fiber and matrix) properties, in the fabrication process and in structural variables (primitive variables). The methodology is computationally efficient for simulating the probability distributions of composite behavior, such as material properties, laminate and structural responses. Bi-products of the methodology are probabilistic sensitivities of the composite primitive variables. The methodology has been implemented into the computer codes PICAN (Probabilistic Integrated Composite ANalyzer) and IPACS (Integrated Probabilistic Assessment of Composite Structures). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in composite typical laminates and comparing the results with the Monte Carlo simulation method. Available experimental data of composite laminate behavior at all scales fall within the scatters predicted by PICAN. Multi-scaling is extended to simulate probabilistic thermo-mechanical fatigue and to simulate the probabilistic design of a composite redome in order to illustrate its versatility. Results show that probabilistic fatigue can be simulated for different temperature amplitudes and for different cyclic stress magnitudes. Results also show that laminate configurations can be selected to increase the redome reliability by several orders of magnitude without increasing the laminate thickness--a unique feature of structural composites. The old reference denotes that nothing fundamental has been done since that time.

Quantifying diffusion MRI tractography of the corticospinal tract in brain tumors with deterministic and probabilistic methods.

Science.gov (United States)

Bucci, Monica; Mandelli, Maria Luisa; Berman, Jeffrey I; Amirbekian, Bagrat; Nguyen, Christopher; Berger, Mitchel S; Henry, Roland G

2013-01-01

sensitivity (79%) as determined from cortical IES compared to deterministic q-ball (50%), probabilistic DTI (36%), and deterministic DTI (10%). The sensitivity using the q-ball algorithm (65%) was significantly higher than using DTI (23%) (p probabilistic algorithms (58%) were more sensitive than deterministic approaches (30%) (p = 0.003). Probabilistic q-ball fiber tracks had the smallest offset to the subcortical stimulation sites. The offsets between diffusion fiber tracks and subcortical IES sites were increased significantly for those cases where the diffusion fiber tracks were visibly thinner than expected. There was perfect concordance between the subcortical IES function (e.g. hand stimulation) and the cortical connection of the nearest diffusion fiber track (e.g. upper extremity cortex). This study highlights the tremendous utility of intraoperative stimulation sites to provide a gold standard from which to evaluate diffusion MRI fiber tracking methods and has provided an object standard for evaluation of different diffusion models and approaches to fiber tracking. The probabilistic q-ball fiber tractography was significantly better than DTI methods in terms of sensitivity and accuracy of the course through the white matter. The commonly used DTI fiber tracking approach was shown to have very poor sensitivity (as low as 10% for deterministic DTI fiber tracking) for delineation of the lateral aspects of the corticospinal tract in our study. Effects of the tumor/edema resulted in significantly larger offsets between the subcortical IES and the preoperative fiber tracks. The provided data show that probabilistic HARDI tractography is the most objective and reproducible analysis but given the small sample and number of stimulation points a generalization about our results should be given with caution. Indeed our results inform the capabilities of preoperative diffusion fiber tracking and indicate that such data should be used carefully when making pre-surgical and

Comparative study of probabilistic methodologies for small signal stability assessment

Energy Technology Data Exchange (ETDEWEB)

Rueda, J.L.; Colome, D.G. [Universidad Nacional de San Juan (IEE-UNSJ), San Juan (Argentina). Inst. de Energia Electrica], Emails: joseluisrt@iee.unsj.edu.ar, colome@iee.unsj.edu.ar

2009-07-01

Traditional deterministic approaches for small signal stability assessment (SSSA) are unable to properly reflect the existing uncertainties in real power systems. Hence, the probabilistic analysis of small signal stability (SSS) is attracting more attention by power system engineers. This paper discusses and compares two probabilistic methodologies for SSSA, which are based on the two point estimation method and the so-called Monte Carlo method, respectively. The comparisons are based on the results obtained for several power systems of different sizes and with different SSS performance. It is demonstrated that although with an analytical approach the amount of computation of probabilistic SSSA can be reduced, the different degrees of approximations that are adopted, lead to deceptive results. Conversely, Monte Carlo based probabilistic SSSA can be carried out with reasonable computational effort while holding satisfactory estimation precision. (author)

Application of probabilistic risk assessment to advanced liquid metal reactor designs

International Nuclear Information System (INIS)

Carroll, W.P.; Temme, M.I.

1987-01-01

The United States Department of Energy (US DOE) has been active in the development and application of probabilistic risk assessment methods within its liquid metal breeder reactor development program for the past eleven years. These methods have been applied to comparative risk evaluations, the selection of design features for reactor concepts, the selection and emphasis of research and development programs, and regulatory discussions. The application of probabilistic methods to reactors which are in the conceptual design stage presents unique data base, modeling, and timing challenges, and excellent opportunities to improve the final design. We provide here the background and insights on the experience which the US DOE liquid metal breeder reactor program has had in its application of probabilistic methods to the Clinch River Breeder Reactor Plant project, the Conceptual Design State of the Large Development Plant, and updates on this design. Plans for future applications of probabilistic risk assessment methods are also discussed. The US DOE is embarking on an innovative design program for liquid metal reactors. (author)

Probabilistic Networks

DEFF Research Database (Denmark)

Jensen, Finn Verner; Lauritzen, Steffen Lilholt

2001-01-01

This article describes the basic ideas and algorithms behind specification and inference in probabilistic networks based on directed acyclic graphs, undirected graphs, and chain graphs.......This article describes the basic ideas and algorithms behind specification and inference in probabilistic networks based on directed acyclic graphs, undirected graphs, and chain graphs....

Probabilistic Capacity of a Grid connected Wind Farm

DEFF Research Database (Denmark)

Zhao, Menghua; Chen, Zhe; Blaabjerg, Frede

2005-01-01

This paper proposes a method to find the maximum acceptable wind power injection regarding the thermal limits, steady state stability limits and voltage limits of the grid system. The probabilistic wind power is introduced based on the probability distribution of wind speed. Based on Power Transfer...... Distribution Factor (PTDF) and voltage sensitivities, a predictor-corrector method is suggested to calculate the acceptable active power injection. Then this method is combined with the probabilistic model of wind power to compute the allowable capacity of the wind farm. Finally, an example is illustrated...... to test this method. It is concluded that proposed method in this paper is a feasible, fast, and accurate approach to find the size of a wind farm....

THE METHOD OF FORMING THE PIGGYBACK TECHNOLOGIES USING THE AUTOMATED HEURISTIC SYSTEM

Directory of Open Access Journals (Sweden)

Ye. Nahornyi

2015-07-01

Full Text Available In order to choose a rational piggyback technology there was offered a method that envisages the automated system improvement by giving it a heuristic nature. The automated system is based on a set of methods, techniques and strategies aimed at creating optimal resource saving technologies, which makes it possible to take into account with maximum efficiency the interests of all the participants of the delivery process. When organizing the piggyback traffic there is presupposed the coordination of operations between the piggyback traffic participants to minimize the cargo travel time.

Automated Model Fit Method for Diesel Engine Control Development

NARCIS (Netherlands)

Seykens, X.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.

2014-01-01

This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is

Automated model fit method for diesel engine control development

NARCIS (Netherlands)

Seykens, X.L.J.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.J.H.

2014-01-01

This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is

Simple heuristics: A bridge between manual core design and automated optimization methods

International Nuclear Information System (INIS)

White, J.R.; Delmolino, P.M.

1993-01-01

The primary function of RESCUE is to serve as an aid in the analysis and identification of feasible loading patterns for LWR reload cores. The unique feature of RESCUE is that its physics model is based on some recent advances in generalized perturbation theory (GPT) methods. The high order GPT techniques offer the accuracy, computational efficiency, and flexibility needed for the implementation of a full range of capabilities within a set of compatible interactive (manual and semi-automated) and automated design tools. The basic design philosophy and current features within RESCUE are reviewed, and the new semi-automated capability is highlighted. The online advisor facility appears quite promising and it provides a natural bridge between the traditional trial-and-error manual process and the recent progress towards fully automated optimization sequences. (orig.)

Comparison of subjective and fully automated methods for measuring mammographic density.

Science.gov (United States)

Moshina, Nataliia; Roman, Marta; Sebuødegård, Sofie; Waade, Gunvor G; Ursin, Giske; Hofvind, Solveig

2018-02-01

Background Breast radiologists of the Norwegian Breast Cancer Screening Program subjectively classified mammographic density using a three-point scale between 1996 and 2012 and changed into the fourth edition of the BI-RADS classification since 2013. In 2015, an automated volumetric breast density assessment software was installed at two screening units. Purpose To compare volumetric breast density measurements from the automated method with two subjective methods: the three-point scale and the BI-RADS density classification. Material and Methods Information on subjective and automated density assessment was obtained from screening examinations of 3635 women recalled for further assessment due to positive screening mammography between 2007 and 2015. The score of the three-point scale (I = fatty; II = medium dense; III = dense) was available for 2310 women. The BI-RADS density score was provided for 1325 women. Mean volumetric breast density was estimated for each category of the subjective classifications. The automated software assigned volumetric breast density to four categories. The agreement between BI-RADS and volumetric breast density categories was assessed using weighted kappa (k w ). Results Mean volumetric breast density was 4.5%, 7.5%, and 13.4% for categories I, II, and III of the three-point scale, respectively, and 4.4%, 7.5%, 9.9%, and 13.9% for the BI-RADS density categories, respectively ( P for trend density categories was k w  = 0.5 (95% CI = 0.47-0.53; P density increased with increasing density category of the subjective classifications. The agreement between BI-RADS and volumetric breast density categories was moderate.

Engineering systems for novel automation methods

International Nuclear Information System (INIS)

Fischer, H.D.

1997-01-01

Modern automation methods of Optimal Control, or for state reconstruction or parameter identification, require a discrete dynamic path model. This is established among others by time and location discretisation of a system of partial differential equations. The digital wave filter principle is paricularly suitable for this purpose, since the numeric stability of the derived algorithms can be easily guaranteed, and their robustness as to effects of word length limitations can be proven. This principle is also particularly attractive in that it can be excellently integrated into currently existing engineering systems for instrumentation and control. (orig./CB) [de

Probabilistic Logical Characterization

DEFF Research Database (Denmark)

Hermanns, Holger; Parma, Augusto; Segala, Roberto

2011-01-01

Probabilistic automata exhibit both probabilistic and non-deterministic choice. They are therefore a powerful semantic foundation for modeling concurrent systems with random phenomena arising in many applications ranging from artificial intelligence, security, systems biology to performance...... modeling. Several variations of bisimulation and simulation relations have proved to be useful as means to abstract and compare different automata. This paper develops a taxonomy of logical characterizations of these relations on image-finite and image-infinite probabilistic automata....

Probabilistic metric spaces

CERN Document Server

Schweizer, B

2005-01-01

Topics include special classes of probabilistic metric spaces, topologies, and several related structures, such as probabilistic normed and inner-product spaces. 1983 edition, updated with 3 new appendixes. Includes 17 illustrations.

Probabilistic Harmonic Analysis on Distributed Photovoltaic Integration Considering Typical Weather Scenarios

Science.gov (United States)

Bin, Che; Ruoying, Yu; Dongsheng, Dang; Xiangyan, Wang

2017-05-01

Distributed Generation (DG) integrating to the network would cause the harmonic pollution which would cause damages on electrical devices and affect the normal operation of power system. On the other hand, due to the randomness of the wind and solar irradiation, the output of DG is random, too, which leads to an uncertainty of the harmonic generated by the DG. Thus, probabilistic methods are needed to analyse the impacts of the DG integration. In this work we studied the harmonic voltage probabilistic distribution and the harmonic distortion in distributed network after the distributed photovoltaic (DPV) system integrating in different weather conditions, mainly the sunny day, cloudy day, rainy day and the snowy day. The probabilistic distribution function of the DPV output power in different typical weather conditions could be acquired via the parameter identification method of maximum likelihood estimation. The Monte-Carlo simulation method was adopted to calculate the probabilistic distribution of harmonic voltage content at different frequency orders as well as the harmonic distortion (THD) in typical weather conditions. The case study was based on the IEEE33 system and the results of harmonic voltage content probabilistic distribution as well as THD in typical weather conditions were compared.

Probabilistic approaches to life prediction of nuclear plant structural components

International Nuclear Information System (INIS)

Villain, B.; Pitner, P.; Procaccia, H.

1996-01-01

In the last decade there has been an increasing interest at EDF in developing and applying probabilistic methods for a variety of purposes. In the field of structural integrity and reliability they are used to evaluate the effect of deterioration due to aging mechanisms, mainly on major passive structural components such as steam generators, pressure vessels and piping in nuclear plants. Because there can be numerous uncertainties involved in an assessment of the performance of these structural components, probabilistic methods provide an attractive alternative or supplement to more conventional deterministic methods. The benefits of a probabilistic approach are the clear treatment of uncertainty and the possibility to perform sensitivity studies from which it is possible to identify and quantify the effect of key factors and mitigative actions. They thus provide information to support effective decisions to optimize In-Service Inspection planning and maintenance strategies and for realistic lifetime prediction or reassessment. The purpose of the paper is to discuss and illustrate the methods available at EDF for probabilistic component life prediction. This includes a presentation of software tools in classical, Bayesian and structural reliability, and an application on two case studies (steam generator tube bundle, reactor pressure vessel)

Preliminary Structural Sensitivity Study of Hypersonic Inflatable Aerodynamic Decelerator Using Probabilistic Methods

Science.gov (United States)

Lyle, Karen H.

2014-01-01

Acceptance of new spacecraft structural architectures and concepts requires validated design methods to minimize the expense involved with technology validation via flighttesting. This paper explores the implementation of probabilistic methods in the sensitivity analysis of the structural response of a Hypersonic Inflatable Aerodynamic Decelerator (HIAD). HIAD architectures are attractive for spacecraft deceleration because they are lightweight, store compactly, and utilize the atmosphere to decelerate a spacecraft during re-entry. However, designers are hesitant to include these inflatable approaches for large payloads or spacecraft because of the lack of flight validation. In the example presented here, the structural parameters of an existing HIAD model have been varied to illustrate the design approach utilizing uncertainty-based methods. Surrogate models have been used to reduce computational expense several orders of magnitude. The suitability of the design is based on assessing variation in the resulting cone angle. The acceptable cone angle variation would rely on the aerodynamic requirements.

A Novel Automated Method for Analyzing Cylindrical Computed Tomography Data

Science.gov (United States)

Roth, D. J.; Burke, E. R.; Rauser, R. W.; Martin, R. E.

2011-01-01

A novel software method is presented that is applicable for analyzing cylindrical and partially cylindrical objects inspected using computed tomography. This method involves unwrapping and re-slicing data so that the CT data from the cylindrical object can be viewed as a series of 2-D sheets in the vertical direction in addition to volume rendering and normal plane views provided by traditional CT software. The method is based on interior and exterior surface edge detection and under proper conditions, is FULLY AUTOMATED and requires no input from the user except the correct voxel dimension from the CT scan. The software is available from NASA in 32- and 64-bit versions that can be applied to gigabyte-sized data sets, processing data either in random access memory or primarily on the computer hard drive. Please inquire with the presenting author if further interested. This software differentiates itself in total from other possible re-slicing software solutions due to complete automation and advanced processing and analysis capabilities.

A computational method for probabilistic safety assessment of I and C systems and human operators in nuclear power plants

International Nuclear Information System (INIS)

Kim, Man Cheol; Seong, Poong Hyun

2006-01-01

To make probabilistic safety assessment (PSA) more realistic, the improvements of human reliability analysis (HRA) are essential. But, current HRA methods have many limitations including the lack of considerations on the interdependency between instrumentation and control (I and C) systems and human operators, and lack of theoretical basis for situation assessment of human operators. To overcome these limitations, we propose a new method for the quantitative safety assessment of I and C systems and human operators. The proposed method is developed based on the computational models for the knowledge-driven monitoring and the situation assessment of human operators, with the consideration of the interdependency between I and C systems and human operators. The application of the proposed method to an example situation demonstrates that the quantitative description by the proposed method for a probable scenario well matches with the qualitative description of the scenario. It is also demonstrated that the proposed method can probabilistically consider all possible scenarios and the proposed method can be used to quantitatively evaluate the effects of various context factor on the safety of nuclear power plants. In our opinion, the proposed method can be used as the basis for the development of advanced HRA methods

Automated general temperature correction method for dielectric soil moisture sensors

Science.gov (United States)

Kapilaratne, R. G. C. Jeewantinie; Lu, Minjiao

2017-08-01

An effective temperature correction method for dielectric sensors is important to ensure the accuracy of soil water content (SWC) measurements of local to regional-scale soil moisture monitoring networks. These networks are extensively using highly temperature sensitive dielectric sensors due to their low cost, ease of use and less power consumption. Yet there is no general temperature correction method for dielectric sensors, instead sensor or site dependent correction algorithms are employed. Such methods become ineffective at soil moisture monitoring networks with different sensor setups and those that cover diverse climatic conditions and soil types. This study attempted to develop a general temperature correction method for dielectric sensors which can be commonly used regardless of the differences in sensor type, climatic conditions and soil type without rainfall data. In this work an automated general temperature correction method was developed by adopting previously developed temperature correction algorithms using time domain reflectometry (TDR) measurements to ThetaProbe ML2X, Stevens Hydra probe II and Decagon Devices EC-TM sensor measurements. The rainy day effects removal procedure from SWC data was automated by incorporating a statistical inference technique with temperature correction algorithms. The temperature correction method was evaluated using 34 stations from the International Soil Moisture Monitoring Network and another nine stations from a local soil moisture monitoring network in Mongolia. Soil moisture monitoring networks used in this study cover four major climates and six major soil types. Results indicated that the automated temperature correction algorithms developed in this study can eliminate temperature effects from dielectric sensor measurements successfully even without on-site rainfall data. Furthermore, it has been found that actual daily average of SWC has been changed due to temperature effects of dielectric sensors with a

A Probabilistic Analysis of the Sacco and Vanzetti Evidence

CERN Document Server

Kadane, Joseph B

2011-01-01

A Probabilistic Analysis of the Sacco and Vanzetti Evidence is a Bayesian analysis of the trial and post-trial evidence in the Sacco and Vanzetti case, based on subjectively determined probabilities and assumed relationships among evidential events. It applies the ideas of charting evidence and probabilistic assessment to this case, which is perhaps the ranking cause celebre in all of American legal history. Modern computation methods applied to inference networks are used to show how the inferential force of evidence in a complicated case can be graded. The authors employ probabilistic assess

Human reliability analysis for probabilistic safety assessments - review of methods and issues

International Nuclear Information System (INIS)

Srinivas, G.; Guptan, Rajee; Malhotra, P.K.; Ghadge, S.G.; Chandra, Umesh

2011-01-01

It is well known that the two major events in World Nuclear Power Plant Operating history, namely the Three Mile Island and Chernobyl, were Human failure events. Subsequent to these two events, several significant changes have been incorporated in Plant Design, Control Room Design and Operator Training to reduce the possibility of Human errors during plant transients. Still, human error contribution to Risk in Nuclear Power Plant operations has been a topic of continued attention for research, development and analysis. Probabilistic Safety Assessments attempt to capture all potential human errors with a scientifically computed failure probability, through Human Reliability Analysis. Several methods are followed by different countries to quantify the Human error probability. This paper reviews the various popular methods being followed, critically examines them with reference to their criticisms and brings out issues for future research. (author)

A method to establish seismic noise baselines for automated station assessment

Science.gov (United States)

McNamara, D.E.; Hutt, C.R.; Gee, L.S.; Benz, H.M.; Buland, R.P.

2009-01-01

We present a method for quantifying station noise baselines and characterizing the spectral shape of out-of-nominal noise sources. Our intent is to automate this method in order to ensure that only the highest-quality data are used in rapid earthquake products at NEIC. In addition, the station noise baselines provide a valuable tool to support the quality control of GSN and ANSS backbone data and metadata. The procedures addressed here are currently in development at the NEIC, and work is underway to understand how quickly changes from nominal can be observed and used within the NEIC processing framework. The spectral methods and software used to compute station baselines and described herein (PQLX) can be useful to both permanent and portable seismic stations operators. Applications include: general seismic station and data quality control (QC), evaluation of instrument responses, assessment of near real-time communication system performance, characterization of site cultural noise conditions, and evaluation of sensor vault design, as well as assessment of gross network capabilities (McNamara et al. 2005). Future PQLX development plans include incorporating station baselines for automated QC methods and automating station status report generation and notification based on user-defined QC parameters. The PQLX software is available through the USGS (http://earthquake. usgs.gov/research/software/pqlx.php) and IRIS (http://www.iris.edu/software/ pqlx/).

An assessment of dietary exposure to glyphosate using refined deterministic and probabilistic methods.

Science.gov (United States)

Stephenson, C L; Harris, C A

2016-09-01

Glyphosate is a herbicide used to control broad-leaved weeds. Some uses of glyphosate in crop production can lead to residues of the active substance and related metabolites in food. This paper uses data on residue levels, processing information and consumption patterns, to assess theoretical lifetime dietary exposure to glyphosate. Initial estimates were made assuming exposure to the highest permitted residue levels in foods. These intakes were then refined using median residue levels from trials, processing information, and monitoring data to achieve a more realistic estimate of exposure. Estimates were made using deterministic and probabilistic methods. Exposures were compared to the acceptable daily intake (ADI)-the amount of a substance that can be consumed daily without an appreciable health risk. Refined deterministic intakes for all consumers were at or below 2.1% of the ADI. Variations were due to cultural differences in consumption patterns and the level of aggregation of the dietary information in calculation models, which allows refinements for processing. Probabilistic exposure estimates ranged from 0.03% to 0.90% of the ADI, depending on whether optimistic or pessimistic assumptions were made in the calculations. Additional refinements would be possible if further data on processing and from residues monitoring programmes were available. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Evaluation of Nonparametric Probabilistic Forecasts of Wind Power

DEFF Research Database (Denmark)

Pinson, Pierre; Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg, orlov 31.07.2008

Predictions of wind power production for horizons up to 48-72 hour ahead comprise a highly valuable input to the methods for the daily management or trading of wind generation. Today, users of wind power predictions are not only provided with point predictions, which are estimates of the most...... likely outcome for each look-ahead time, but also with uncertainty estimates given by probabilistic forecasts. In order to avoid assumptions on the shape of predictive distributions, these probabilistic predictions are produced from nonparametric methods, and then take the form of a single or a set...

Development of a Risk-Based Probabilistic Performance-Assessment Method for Long-Term Cover Systems - 2nd Edition

International Nuclear Information System (INIS)

HO, CLIFFORD K.; ARNOLD, BILL W.; COCHRAN, JOHN R.; TAIRA, RANDAL Y.

2002-01-01

A probabilistic, risk-based performance-assessment methodology has been developed to assist designers, regulators, and stakeholders in the selection, design, and monitoring of long-term covers for contaminated subsurface sites. This report describes the method, the software tools that were developed, and an example that illustrates the probabilistic performance-assessment method using a repository site in Monticello, Utah. At the Monticello site, a long-term cover system is being used to isolate long-lived uranium mill tailings from the biosphere. Computer models were developed to simulate relevant features, events, and processes that include water flux through the cover, source-term release, vadose-zone transport, saturated-zone transport, gas transport, and exposure pathways. The component models were then integrated into a total-system performance-assessment model, and uncertainty distributions of important input parameters were constructed and sampled in a stochastic Monte Carlo analysis. Multiple realizations were simulated using the integrated model to produce cumulative distribution functions of the performance metrics, which were used to assess cover performance for both present- and long-term future conditions. Performance metrics for this study included the water percolation reaching the uranium mill tailings, radon gas flux at the surface, groundwater concentrations, and dose. Results from uncertainty analyses, sensitivity analyses, and alternative design comparisons are presented for each of the performance metrics. The benefits from this methodology include a quantification of uncertainty, the identification of parameters most important to performance (to prioritize site characterization and monitoring activities), and the ability to compare alternative designs using probabilistic evaluations of performance (for cost savings)

Chiefly Symmetric: Results on the Scalability of Probabilistic Model Checking for Operating-System Code

Directory of Open Access Journals (Sweden)

Marcus Völp

2012-11-01

Full Text Available Reliability in terms of functional properties from the safety-liveness spectrum is an indispensable requirement of low-level operating-system (OS code. However, with evermore complex and thus less predictable hardware, quantitative and probabilistic guarantees become more and more important. Probabilistic model checking is one technique to automatically obtain these guarantees. First experiences with the automated quantitative analysis of low-level operating-system code confirm the expectation that the naive probabilistic model checking approach rapidly reaches its limits when increasing the numbers of processes. This paper reports on our work-in-progress to tackle the state explosion problem for low-level OS-code caused by the exponential blow-up of the model size when the number of processes grows. We studied the symmetry reduction approach and carried out our experiments with a simple test-and-test-and-set lock case study as a representative example for a wide range of protocols with natural inter-process dependencies and long-run properties. We quickly see a state-space explosion for scenarios where inter-process dependencies are insignificant. However, once inter-process dependencies dominate the picture models with hundred and more processes can be constructed and analysed.

Symbolic Computing in Probabilistic and Stochastic Analysis

Directory of Open Access Journals (Sweden)

Kamiński Marcin

2015-12-01

Full Text Available The main aim is to present recent developments in applications of symbolic computing in probabilistic and stochastic analysis, and this is done using the example of the well-known MAPLE system. The key theoretical methods discussed are (i analytical derivations, (ii the classical Monte-Carlo simulation approach, (iii the stochastic perturbation technique, as well as (iv some semi-analytical approaches. It is demonstrated in particular how to engage the basic symbolic tools implemented in any system to derive the basic equations for the stochastic perturbation technique and how to make an efficient implementation of the semi-analytical methods using an automatic differentiation and integration provided by the computer algebra program itself. The second important illustration is probabilistic extension of the finite element and finite difference methods coded in MAPLE, showing how to solve boundary value problems with random parameters in the environment of symbolic computing. The response function method belongs to the third group, where interference of classical deterministic software with the non-linear fitting numerical techniques available in various symbolic environments is displayed. We recover in this context the probabilistic structural response in engineering systems and show how to solve partial differential equations including Gaussian randomness in their coefficients.

Process for computing geometric perturbations for probabilistic analysis

Science.gov (United States)

Fitch, Simeon H. K. [Charlottesville, VA; Riha, David S [San Antonio, TX; Thacker, Ben H [San Antonio, TX

2012-04-10

A method for computing geometric perturbations for probabilistic analysis. The probabilistic analysis is based on finite element modeling, in which uncertainties in the modeled system are represented by changes in the nominal geometry of the model, referred to as "perturbations". These changes are accomplished using displacement vectors, which are computed for each node of a region of interest and are based on mean-value coordinate calculations.

Variational approach to probabilistic finite elements

Science.gov (United States)

Belytschko, T.; Liu, W. K.; Mani, A.; Besterfield, G.

1991-08-01

Probabilistic finite element methods (PFEM), synthesizing the power of finite element methods with second-moment techniques, are formulated for various classes of problems in structural and solid mechanics. Time-invariant random materials, geometric properties and loads are incorporated in terms of their fundamental statistics viz. second-moments. Analogous to the discretization of the displacement field in finite element methods, the random fields are also discretized. Preserving the conceptual simplicity, the response moments are calculated with minimal computations. By incorporating certain computational techniques, these methods are shown to be capable of handling large systems with many sources of uncertainties. By construction, these methods are applicable when the scale of randomness is not very large and when the probabilistic density functions have decaying tails. The accuracy and efficiency of these methods, along with their limitations, are demonstrated by various applications. Results obtained are compared with those of Monte Carlo simulation and it is shown that good accuracy can be obtained for both linear and nonlinear problems. The methods are amenable to implementation in deterministic FEM based computer codes.

Probabilistic Tsunami Hazard Analysis

Science.gov (United States)

Thio, H. K.; Ichinose, G. A.; Somerville, P. G.; Polet, J.

2006-12-01

The recent tsunami disaster caused by the 2004 Sumatra-Andaman earthquake has focused our attention to the hazard posed by large earthquakes that occur under water, in particular subduction zone earthquakes, and the tsunamis that they generate. Even though these kinds of events are rare, the very large loss of life and material destruction caused by this earthquake warrant a significant effort towards the mitigation of the tsunami hazard. For ground motion hazard, Probabilistic Seismic Hazard Analysis (PSHA) has become a standard practice in the evaluation and mitigation of seismic hazard to populations in particular with respect to structures, infrastructure and lifelines. Its ability to condense the complexities and variability of seismic activity into a manageable set of parameters greatly facilitates the design of effective seismic resistant buildings but also the planning of infrastructure projects. Probabilistic Tsunami Hazard Analysis (PTHA) achieves the same goal for hazards posed by tsunami. There are great advantages of implementing such a method to evaluate the total risk (seismic and tsunami) to coastal communities. The method that we have developed is based on the traditional PSHA and therefore completely consistent with standard seismic practice. Because of the strong dependence of tsunami wave heights on bathymetry, we use a full waveform tsunami waveform computation in lieu of attenuation relations that are common in PSHA. By pre-computing and storing the tsunami waveforms at points along the coast generated for sets of subfaults that comprise larger earthquake faults, we can efficiently synthesize tsunami waveforms for any slip distribution on those faults by summing the individual subfault tsunami waveforms (weighted by their slip). This efficiency make it feasible to use Green's function summation in lieu of attenuation relations to provide very accurate estimates of tsunami height for probabilistic calculations, where one typically computes

Probabilistic methods for the simulation of fuel particles behavior under irradiation; Apport des methodes probabilistes dans la simulation du comportement sous irradiation du combustible a particules

Energy Technology Data Exchange (ETDEWEB)

Cannamela, C

2007-09-15

This work is devoted to the evaluation of mathematical expectations in the context of structural reliability. We seek a failure probability estimate (that we assume low), taking into account the uncertainty of influential parameters of the System. Our goal is to reach a good compromise between the accuracy of the estimate and the associated computational cost. This approach is used to estimate the failure probability of fuel particles from a HTR-type nuclear reactor. This estimate is obtain by means of costly numerical simulations. We consider different probabilistic methods to tackle the problem. First, we consider a variance reducing Monte Carlo method: importance sampling. For the parametric case, we propose adaptive algorithms in order to build a series of probability densities that will eventually converge to optimal importance density. We then present several estimates of the mathematical expectation based on this series of densities. Next, we consider a multi-level method using Monte Carlo Markov Chain algorithm. Finally, we turn our attention to the related problem of quantile estimation (non extreme) of physical output from a large-scale numerical code. We propose a controlled stratification method. The random input parameters are sampled in specific regions obtained from surrogate of the response. The estimation of the quantile is then computed from this sample. (author)

Method for semi-automated microscopy of filtration-enriched circulating tumor cells.

Science.gov (United States)

Pailler, Emma; Oulhen, Marianne; Billiot, Fanny; Galland, Alexandre; Auger, Nathalie; Faugeroux, Vincent; Laplace-Builhé, Corinne; Besse, Benjamin; Loriot, Yohann; Ngo-Camus, Maud; Hemanda, Merouan; Lindsay, Colin R; Soria, Jean-Charles; Vielh, Philippe; Farace, Françoise

2016-07-14

Circulating tumor cell (CTC)-filtration methods capture high numbers of CTCs in non-small-cell lung cancer (NSCLC) and metastatic prostate cancer (mPCa) patients, and hold promise as a non-invasive technique for treatment selection and disease monitoring. However filters have drawbacks that make the automation of microscopy challenging. We report the semi-automated microscopy method we developed to analyze filtration-enriched CTCs from NSCLC and mPCa patients. Spiked cell lines in normal blood and CTCs were enriched by ISET (isolation by size of epithelial tumor cells). Fluorescent staining was carried out using epithelial (pan-cytokeratins, EpCAM), mesenchymal (vimentin, N-cadherin), leukocyte (CD45) markers and DAPI. Cytomorphological staining was carried out with Mayer-Hemalun or Diff-Quik. ALK-, ROS1-, ERG-rearrangement were detected by filter-adapted-FISH (FA-FISH). Microscopy was carried out using an Ariol scanner. Two combined assays were developed. The first assay sequentially combined four-color fluorescent staining, scanning, automated selection of CD45(-) cells, cytomorphological staining, then scanning and analysis of CD45(-) cell phenotypical and cytomorphological characteristics. CD45(-) cell selection was based on DAPI and CD45 intensity, and a nuclear area >55 μm(2). The second assay sequentially combined fluorescent staining, automated selection of CD45(-) cells, FISH scanning on CD45(-) cells, then analysis of CD45(-) cell FISH signals. Specific scanning parameters were developed to deal with the uneven surface of filters and CTC characteristics. Thirty z-stacks spaced 0.6 μm apart were defined as the optimal setting, scanning 82 %, 91 %, and 95 % of CTCs in ALK-, ROS1-, and ERG-rearranged patients respectively. A multi-exposure protocol consisting of three separate exposure times for green and red fluorochromes was optimized to analyze the intensity, size and thickness of FISH signals. The semi-automated microscopy method reported here

Probabilistic safety analysis procedures guide

International Nuclear Information System (INIS)

Papazoglou, I.A.; Bari, R.A.; Buslik, A.J.

1984-01-01

A procedures guide for the performance of probabilistic safety assessment has been prepared for interim use in the Nuclear Regulatory Commission programs. The probabilistic safety assessment studies performed are intended to produce probabilistic predictive models that can be used and extended by the utilities and by NRC to sharpen the focus of inquiries into a range of tissues affecting reactor safety. This guide addresses the determination of the probability (per year) of core damage resulting from accident initiators internal to the plant and from loss of offsite electric power. The scope includes analyses of problem-solving (cognitive) human errors, a determination of importance of the various core damage accident sequences, and an explicit treatment and display of uncertainties for the key accident sequences. Ultimately, the guide will be augmented to include the plant-specific analysis of in-plant processes (i.e., containment performance) and the risk associated with external accident initiators, as consensus is developed regarding suitable methodologies in these areas. This guide provides the structure of a probabilistic safety study to be performed, and indicates what products of the study are essential for regulatory decision making. Methodology is treated in the guide only to the extent necessary to indicate the range of methods which is acceptable; ample reference is given to alternative methodologies which may be utilized in the performance of the study

Assessment selection in human-automation interaction studies: The Failure-GAM2E and review of assessment methods for highly automated driving.

Science.gov (United States)

Grane, Camilla

2018-01-01

Highly automated driving will change driver's behavioural patterns. Traditional methods used for assessing manual driving will only be applicable for the parts of human-automation interaction where the driver intervenes such as in hand-over and take-over situations. Therefore, driver behaviour assessment will need to adapt to the new driving scenarios. This paper aims at simplifying the process of selecting appropriate assessment methods. Thirty-five papers were reviewed to examine potential and relevant methods. The review showed that many studies still relies on traditional driving assessment methods. A new method, the Failure-GAM 2 E model, with purpose to aid assessment selection when planning a study, is proposed and exemplified in the paper. Failure-GAM 2 E includes a systematic step-by-step procedure defining the situation, failures (Failure), goals (G), actions (A), subjective methods (M), objective methods (M) and equipment (E). The use of Failure-GAM 2 E in a study example resulted in a well-reasoned assessment plan, a new way of measuring trust through feet movements and a proposed Optimal Risk Management Model. Failure-GAM 2 E and the Optimal Risk Management Model are believed to support the planning process for research studies in the field of human-automation interaction. Copyright © 2017 Elsevier Ltd. All rights reserved.

Research for developing precise tsunami evaluation methods. Probabilistic tsunami hazard analysis/numerical simulation method with dispersion and wave breaking

International Nuclear Information System (INIS)

2007-01-01

The present report introduces main results of investigations on precise tsunami evaluation methods, which were carried out from the viewpoint of safety evaluation for nuclear power facilities and deliberated by the Tsunami Evaluation Subcommittee. A framework for the probabilistic tsunami hazard analysis (PTHA) based on logic tree is proposed and calculation on the Pacific side of northeastern Japan is performed as a case study. Tsunami motions with dispersion and wave breaking were investigated both experimentally and numerically. The numerical simulation method is verified for its practicability by applying to a historical tsunami. Tsunami force is also investigated and formulae of tsunami pressure acting on breakwaters and on building due to inundating tsunami are proposed. (author)

Probabilistic Design of Wave Energy Devices

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Kofoed, Jens Peter; Ferreira, C.B.

2011-01-01

Wave energy has a large potential for contributing significantly to production of renewable energy. However, the wave energy sector is still not able to deliver cost competitive and reliable solutions. But the sector has already demonstrated several proofs of concepts. The design of wave energy...... devices is a new and expanding technical area where there is no tradition for probabilistic design—in fact very little full scale devices has been build to date, so it can be said that no design tradition really exists in this area. For this reason it is considered to be of great importance to develop...... and advocate for a probabilistic design approach, as it is assumed (in other areas this has been demonstrated) that this leads to more economical designs compared to designs based on deterministic methods. In the present paper a general framework for probabilistic design and reliability analysis of wave energy...

Probabilistic simulation applications to reliability assessments

International Nuclear Information System (INIS)

Miller, Ian; Nutt, Mark W.; Hill, Ralph S. III

2003-01-01

Probabilistic risk/reliability (PRA) analyses for engineered systems are conventionally based on fault-tree methods. These methods are mature and efficient, and are well suited to systems consisting of interacting components with known, low probabilities of failure. Even complex systems, such as nuclear power plants or aircraft, are modeled by the careful application of these approaches. However, for systems that may evolve in complex and nonlinear ways, and where the performance of components may be a sensitive function of the history of their working environments, fault-tree methods can be very demanding. This paper proposes an alternative method of evaluating such systems, based on probabilistic simulation using intelligent software objects to represent the components of such systems. Using a Monte Carlo approach, simulation models can be constructed from relatively simple interacting objects that capture the essential behavior of the components that they represent. Such models are capable of reflecting the complex behaviors of the systems that they represent in a natural and realistic way. (author)

A semi-automated method of monitoring dam passage of American Eels Anguilla rostrata

Science.gov (United States)

Welsh, Stuart A.; Aldinger, Joni L.

2014-01-01

Fish passage facilities at dams have become an important focus of fishery management in riverine systems. Given the personnel and travel costs associated with physical monitoring programs, automated or semi-automated systems are an attractive alternative for monitoring fish passage facilities. We designed and tested a semi-automated system for eel ladder monitoring at Millville Dam on the lower Shenandoah River, West Virginia. A motion-activated eel ladder camera (ELC) photographed each yellow-phase American Eel Anguilla rostrata that passed through the ladder. Digital images (with date and time stamps) of American Eels allowed for total daily counts and measurements of eel TL using photogrammetric methods with digital imaging software. We compared physical counts of American Eels with camera-based counts; TLs obtained with a measuring board were compared with TLs derived from photogrammetric methods. Data from the ELC were consistent with data obtained by physical methods, thus supporting the semi-automated camera system as a viable option for monitoring American Eel passage. Time stamps on digital images allowed for the documentation of eel passage time—data that were not obtainable from physical monitoring efforts. The ELC has application to eel ladder facilities but can also be used to monitor dam passage of other taxa, such as crayfishes, lampreys, and water snakes.

Non-unitary probabilistic quantum computing circuit and method

Science.gov (United States)

Williams, Colin P. (Inventor); Gingrich, Robert M. (Inventor)

2009-01-01

A quantum circuit performing quantum computation in a quantum computer. A chosen transformation of an initial n-qubit state is probabilistically obtained. The circuit comprises a unitary quantum operator obtained from a non-unitary quantum operator, operating on an n-qubit state and an ancilla state. When operation on the ancilla state provides a success condition, computation is stopped. When operation on the ancilla state provides a failure condition, computation is performed again on the ancilla state and the n-qubit state obtained in the previous computation, until a success condition is obtained.

Disjunctive Probabilistic Modal Logic is Enough for Bisimilarity on Reactive Probabilistic Systems

OpenAIRE

Bernardo, Marco; Miculan, Marino

2016-01-01

Larsen and Skou characterized probabilistic bisimilarity over reactive probabilistic systems with a logic including true, negation, conjunction, and a diamond modality decorated with a probabilistic lower bound. Later on, Desharnais, Edalat, and Panangaden showed that negation is not necessary to characterize the same equivalence. In this paper, we prove that the logical characterization holds also when conjunction is replaced by disjunction, with negation still being not necessary. To this e...

Forecasting the vibrational behavior of large turbogenerators on elastic foundations in accordance with probabilistic methods

International Nuclear Information System (INIS)

Simon, G.

1990-01-01

Using advanced calculation programs, the inherent behavior and response behavior of structures can reliably be predetermined. In contrast, the dynamic forces affecting a system, in particular unbalances, are often unkown. From balancing of individual rotors, only the vibration path amplitudes at the measuring points used are known. However, these may originate from quite different unbalance distributions. Using probabilistic methods, however, values for the vibrational behavior of the overall structure can be derived from this. (orig.) [de

Development of a Probabilistic Dynamic Synthesis Method for the Analysis of Nondeterministic Structures

Science.gov (United States)

Brown, A. M.

1998-01-01

Accounting for the statistical geometric and material variability of structures in analysis has been a topic of considerable research for the last 30 years. The determination of quantifiable measures of statistical probability of a desired response variable, such as natural frequency, maximum displacement, or stress, to replace experience-based "safety factors" has been a primary goal of these studies. There are, however, several problems associated with their satisfactory application to realistic structures, such as bladed disks in turbomachinery. These include the accurate definition of the input random variables (rv's), the large size of the finite element models frequently used to simulate these structures, which makes even a single deterministic analysis expensive, and accurate generation of the cumulative distribution function (CDF) necessary to obtain the probability of the desired response variables. The research presented here applies a methodology called probabilistic dynamic synthesis (PDS) to solve these problems. The PDS method uses dynamic characteristics of substructures measured from modal test as the input rv's, rather than "primitive" rv's such as material or geometric uncertainties. These dynamic characteristics, which are the free-free eigenvalues, eigenvectors, and residual flexibility (RF), are readily measured and for many substructures, a reasonable sample set of these measurements can be obtained. The statistics for these rv's accurately account for the entire random character of the substructure. Using the RF method of component mode synthesis, these dynamic characteristics are used to generate reduced-size sample models of the substructures, which are then coupled to form system models. These sample models are used to obtain the CDF of the response variable by either applying Monte Carlo simulation or by generating data points for use in the response surface reliability method, which can perform the probabilistic analysis with an order of

Sensitivity analysis in multi-parameter probabilistic systems

International Nuclear Information System (INIS)

Walker, J.R.

1987-01-01

Probabilistic methods involving the use of multi-parameter Monte Carlo analysis can be applied to a wide range of engineering systems. The output from the Monte Carlo analysis is a probabilistic estimate of the system consequence, which can vary spatially and temporally. Sensitivity analysis aims to examine how the output consequence is influenced by the input parameter values. Sensitivity analysis provides the necessary information so that the engineering properties of the system can be optimized. This report details a package of sensitivity analysis techniques that together form an integrated methodology for the sensitivity analysis of probabilistic systems. The techniques have known confidence limits and can be applied to a wide range of engineering problems. The sensitivity analysis methodology is illustrated by performing the sensitivity analysis of the MCROC rock microcracking model

Probabilistic Design of Wind Turbines

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Toft, H.S.

2010-01-01

Probabilistic design of wind turbines requires definition of the structural elements to be included in the probabilistic basis: e.g., blades, tower, foundation; identification of important failure modes; careful stochastic modeling of the uncertain parameters; recommendations for target reliability....... It is described how uncertainties in wind turbine design related to computational models, statistical data from test specimens, results from a few full-scale tests and from prototype wind turbines can be accounted for using the Maximum Likelihood Method and a Bayesian approach. Assessment of the optimal...... reliability level by cost-benefit optimization is illustrated by an offshore wind turbine example. Uncertainty modeling is illustrated by an example where physical, statistical and model uncertainties are estimated....

Optimization of the kernel functions in a probabilistic neural network analyzing the local pattern distribution.

Science.gov (United States)

Galleske, I; Castellanos, J

2002-05-01

This article proposes a procedure for the automatic determination of the elements of the covariance matrix of the gaussian kernel function of probabilistic neural networks. Two matrices, a rotation matrix and a matrix of variances, can be calculated by analyzing the local environment of each training pattern. The combination of them will form the covariance matrix of each training pattern. This automation has two advantages: First, it will free the neural network designer from indicating the complete covariance matrix, and second, it will result in a network with better generalization ability than the original model. A variation of the famous two-spiral problem and real-world examples from the UCI Machine Learning Repository will show a classification rate not only better than the original probabilistic neural network but also that this model can outperform other well-known classification techniques.

Probabilistic Design of Offshore Structural Systems

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

1988-01-01

Probabilistic design of structural systems is considered in this paper. The reliability is estimated using first-order reliability methods (FORM). The design problem is formulated as the optimization problem to minimize a given cost function such that the reliability of the single elements...... satisfies given requirements or such that the systems reliability satisfies a given requirement. Based on a sensitivity analysis optimization procedures to solve the optimization problems are presented. Two of these procedures solve the system reliability-based optimization problem sequentially using quasi......-analytical derivatives. Finally an example of probabilistic design of an offshore structure is considered....

Probabilistic Design of Offshore Structural Systems

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

Probabilistic design of structural systems is considered in this paper. The reliability is estimated using first-order reliability methods (FORM). The design problem is formulated as the optimization problem to minimize a given cost function such that the reliability of the single elements...... satisfies given requirements or such that the systems reliability satisfies a given requirement. Based on a sensitivity analysis optimization procedures to solve the optimization problems are presented. Two of these procedures solve the system reliability-based optimization problem sequentially using quasi......-analytical derivatives. Finally an example of probabilistic design of an offshore structure is considered....

GUI program to compute probabilistic seismic hazard analysis

International Nuclear Information System (INIS)

Shin, Jin Soo; Chi, H. C.; Cho, J. C.; Park, J. H.; Kim, K. G.; Im, I. S.

2006-12-01

The development of program to compute probabilistic seismic hazard is completed based on Graphic User Interface(GUI). The main program consists of three part - the data input processes, probabilistic seismic hazard analysis and result output processes. The probabilistic seismic hazard analysis needs various input data which represent attenuation formulae, seismic zoning map, and earthquake event catalog. The input procedure of previous programs based on text interface take a much time to prepare the data. The data cannot be checked directly on screen to prevent input erroneously in existing methods. The new program simplifies the input process and enable to check the data graphically in order to minimize the artificial error within limits of the possibility

Probabilistic methods in nuclear power plant component ageing analysis

International Nuclear Information System (INIS)

Simola, K.

1992-03-01

The nuclear power plant ageing research is aimed to ensure that the plant safety and reliability are maintained at a desired level through the designed, and possibly extended lifetime. In ageing studies, the reliability of components, systems and structures is evaluated taking into account the possible time- dependent decrease in reliability. The results of analyses can be used in the evaluation of the remaining lifetime of components and in the development of preventive maintenance, testing and replacement programmes. The report discusses the use of probabilistic models in the evaluations of the ageing of nuclear power plant components. The principles of nuclear power plant ageing studies are described and examples of ageing management programmes in foreign countries are given. The use of time-dependent probabilistic models to evaluate the ageing of various components and structures is described and the application of models is demonstrated with two case studies. In the case study of motor- operated closing valves the analysis are based on failure data obtained from a power plant. In the second example, the environmentally assisted crack growth is modelled with a computer code developed in United States, and the applicability of the model is evaluated on the basis of operating experience

Probabilistic Linguistic Power Aggregation Operators for Multi-Criteria Group Decision Making

Directory of Open Access Journals (Sweden)

Agbodah Kobina

2017-12-01

Full Text Available As an effective aggregation tool, power average (PA allows the input arguments being aggregated to support and reinforce each other, which provides more versatility in the information aggregation process. Under the probabilistic linguistic term environment, we deeply investigate the new power aggregation (PA operators for fusing the probabilistic linguistic term sets (PLTSs. In this paper, we firstly develop the probabilistic linguistic power average (PLPA, the weighted probabilistic linguistic power average (WPLPA operators, the probabilistic linguistic power geometric (PLPG and the weighted probabilistic linguistic power geometric (WPLPG operators. At the same time, we carefully analyze the properties of these new aggregation operators. With the aid of the WPLPA and WPLPG operators, we further design the approaches for the application of multi-criteria group decision-making (MCGDM with PLTSs. Finally, we use an illustrated example to expound our proposed methods and verify their performances.

A simple method for validation and verification of pipettes mounted on automated liquid handlers

DEFF Research Database (Denmark)

Stangegaard, Michael; Hansen, Anders Johannes; Frøslev, Tobias Guldberg

 We have implemented a simple method for validation and verification of the performance of pipettes mounted on automated liquid handlers as necessary for laboratories accredited under ISO 17025. An 8-step serial dilution of Orange G was prepared in quadruplicates in a flat bottom 96-well microtit...... available. In conclusion, we have set up a simple solution for the continuous validation of automated liquid handlers used for accredited work. The method is cheap, simple and easy to use for aqueous solutions but requires a spectrophotometer that can read microtiter plates....... We have implemented a simple method for validation and verification of the performance of pipettes mounted on automated liquid handlers as necessary for laboratories accredited under ISO 17025. An 8-step serial dilution of Orange G was prepared in quadruplicates in a flat bottom 96-well microtiter...

A review of probabilistic risk assessment of contaminated land

International Nuclear Information System (INIS)

Oeberg, T.; Bergbaeck, B.

2005-01-01

Background, Aims and Scope. The management and decisions concerning restoration of contaminated land often require indepth risk analyses. An environmental risk assessment is generally described as proceeding in four separate steps: hazard identification, dose-response assessment, exposure assessment, and risk characterization. The risk assessment should acknowledge and quantify the uncertainty in risk predictions. This can be achieved by applying probabilistic methods which, although they have been available for many years, are still not generally used. Risk assessment of contaminated land is an area where probabilistic methods have proved particularly useful. Many reports have appeared in the literature, mostly by North American researchers. The aim of this review is to summarize the experience gained so far, provide a number of useful examples, and suggest what may be done to promote probabilistic methods in Europe and the rest of the world. Methods. The available literature has been explored through searches in the major scientific and technical databases, WWW resources, textbooks and direct contacts with active researchers. A calculation example was created using standard simulation software. (orig.)

A probabilistic analysis method to evaluate the effect of human factors on plant safety

International Nuclear Information System (INIS)

Ujita, H.

1987-01-01

A method to evaluate the effect of human factors on probabilistic safety analysis (PSA) is developed. The main features of the method are as follows: 1. A time-dependent multibranch tree is constructed to treat time dependency of human error probability. 2. A sensitivity analysis is done to determine uncertainty in the PSA due to branch time of human error occurrence, human error data source, extraneous act probability, and human recovery probability. The method is applied to a large-break, loss-of-coolant accident of a boiling water reactor-5. As a result, core melt probability and risk do not depend on the number of time branches, which means that a small number of branches are sufficient. These values depend on the first branch time and the human error probability

A study on the fatigue life prediction of tire belt-layers using probabilistic method

International Nuclear Information System (INIS)

Lee, Dong Woo; Park, Jong Sang; Lee, Tae Won; Kim, Seong Rae; Sung, Ki Deug; Huh, Sun Chul

2013-01-01

Tire belt separation failure is occurred by internal cracks generated in *1 and *2 belt layers and by its growth. And belt failure seriously affects tire endurance. Therefore, to improve the tire endurance, it is necessary to analyze tire crack growth behavior and predict fatigue life. Generally, the prediction of tire endurance is performed by the experimental method using tire test machine. But it takes much cost and time to perform experiment. In this paper, to predict tire fatigue life, we applied deterministic fracture mechanics approach, based on finite element analysis. Also, probabilistic analysis method based on statistics using Monte Carlo simulation is presented. Above mentioned two methods include a global-local finite element analysis to provide the detail necessary to model explicitly an internal crack and calculate the J-integral for tire life prediction.

Probabilistic methods for the simulation of fuel particles behavior under irradiation

International Nuclear Information System (INIS)

Cannamela, C.

2007-09-01

This work is devoted to the evaluation of mathematical expectations in the context of structural reliability. We seek a failure probability estimate (that we assume low), taking into account the uncertainty of influential parameters of the System. Our goal is to reach a good compromise between the accuracy of the estimate and the associated computational cost. This approach is used to estimate the failure probability of fuel particles from a HTR-type nuclear reactor. This estimate is obtain by means of costly numerical simulations. We consider different probabilistic methods to tackle the problem. First, we consider a variance reducing Monte Carlo method: importance sampling. For the parametric case, we propose adaptive algorithms in order to build a series of probability densities that will eventually converge to optimal importance density. We then present several estimates of the mathematical expectation based on this series of densities. Next, we consider a multi-level method using Monte Carlo Markov Chain algorithm. Finally, we turn our attention to the related problem of quantile estimation (non extreme) of physical output from a large-scale numerical code. We propose a controlled stratification method. The random input parameters are sampled in specific regions obtained from surrogate of the response. The estimation of the quantile is then computed from this sample. (author)

Probabilistic approaches to life prediction of nuclear plant structural components

International Nuclear Information System (INIS)

Villain, B.; Pitner, P.; Procaccia, H.

1996-01-01

In the last decade there has been an increasing interest at EDF in developing and applying probabilistic methods for a variety of purposes. In the field of structural integrity and reliability they are used to evaluate the effect of deterioration due to aging mechanisms, mainly on major passive structural components such as steam generators, pressure vessels and piping in nuclear plants. Because there can be numerous uncertainties involved in a assessment of the performance of these structural components, probabilistic methods. The benefits of a probabilistic approach are the clear treatment of uncertainly and the possibility to perform sensitivity studies from which it is possible to identify and quantify the effect of key factors and mitigative actions. They thus provide information to support effective decisions to optimize In-Service Inspection planning and maintenance strategies and for realistic lifetime prediction or reassessment. The purpose of the paper is to discuss and illustrate the methods available at EDF for probabilistic component life prediction. This includes a presentation of software tools in classical, Bayesian and structural reliability, and an application on two case studies (steam generator tube bundle, reactor pressure vessel). (authors)

Automatic Probabilistic Program Verification through Random Variable Abstraction

Directory of Open Access Journals (Sweden)

Damián Barsotti

2010-06-01

Full Text Available The weakest pre-expectation calculus has been proved to be a mature theory to analyze quantitative properties of probabilistic and nondeterministic programs. We present an automatic method for proving quantitative linear properties on any denumerable state space using iterative backwards fixed point calculation in the general framework of abstract interpretation. In order to accomplish this task we present the technique of random variable abstraction (RVA and we also postulate a sufficient condition to achieve exact fixed point computation in the abstract domain. The feasibility of our approach is shown with two examples, one obtaining the expected running time of a probabilistic program, and the other the expected gain of a gambling strategy. Our method works on general guarded probabilistic and nondeterministic transition systems instead of plain pGCL programs, allowing us to easily model a wide range of systems including distributed ones and unstructured programs. We present the operational and weakest precondition semantics for this programs and prove its equivalence.

Comparison of event tree, fault tree and Markov methods for probabilistic safety assessment and application to accident mitigation

International Nuclear Information System (INIS)

James, H.; Harris, M.J.; Hall, S.F.

1992-01-01

Probabilistic safety assessment (PSA) is used extensively in the nuclear industry. The main stages of PSA and the traditional event tree method are described. Focussing on hydrogen explosions, an event tree model is compared to a novel Markov model and a fault tree, and unexpected implication for accident mitigation is revealed. (author)

Probabilistic finite elements for fracture and fatigue analysis

Science.gov (United States)

Liu, W. K.; Belytschko, T.; Lawrence, M.; Besterfield, G. H.

1989-01-01

The fusion of the probabilistic finite element method (PFEM) and reliability analysis for probabilistic fracture mechanics (PFM) is presented. A comprehensive method for determining the probability of fatigue failure for curved crack growth was developed. The criterion for failure or performance function is stated as: the fatigue life of a component must exceed the service life of the component; otherwise failure will occur. An enriched element that has the near-crack-tip singular strain field embedded in the element is used to formulate the equilibrium equation and solve for the stress intensity factors at the crack-tip. Performance and accuracy of the method is demonstrated on a classical mode 1 fatigue problem.

Duplicate Detection in Probabilistic Data

NARCIS (Netherlands)

Panse, Fabian; van Keulen, Maurice; de Keijzer, Ander; Ritter, Norbert

2009-01-01

Collected data often contains uncertainties. Probabilistic databases have been proposed to manage uncertain data. To combine data from multiple autonomous probabilistic databases, an integration of probabilistic data has to be performed. Until now, however, data integration approaches have focused

A Probabilistic Design Methodology for a Turboshaft Engine Overall Performance Analysis

Directory of Open Access Journals (Sweden)

Min Chen

2014-05-01

Full Text Available In reality, the cumulative effect of the many uncertainties in engine component performance may stack up to affect the engine overall performance. This paper aims to quantify the impact of uncertainty in engine component performance on the overall performance of a turboshaft engine based on Monte-Carlo probabilistic design method. A novel probabilistic model of turboshaft engine, consisting of a Monte-Carlo simulation generator, a traditional nonlinear turboshaft engine model, and a probability statistical model, was implemented to predict this impact. One of the fundamental results shown herein is that uncertainty in component performance has a significant impact on the engine overall performance prediction. This paper also shows that, taking into consideration the uncertainties in component performance, the turbine entry temperature and overall pressure ratio based on the probabilistic design method should increase by 0.76% and 8.33%, respectively, compared with the ones of deterministic design method. The comparison shows that the probabilistic approach provides a more credible and reliable way to assign the design space for a target engine overall performance.

The Role of Probabilistic Design Analysis Methods in Safety and Affordability

Science.gov (United States)

Safie, Fayssal M.

2016-01-01

For the last several years, NASA and its contractors have been working together to build space launch systems to commercialize space. Developing commercial affordable and safe launch systems becomes very important and requires a paradigm shift. This paradigm shift enforces the need for an integrated systems engineering environment where cost, safety, reliability, and performance need to be considered to optimize the launch system design. In such an environment, rule based and deterministic engineering design practices alone may not be sufficient to optimize margins and fault tolerance to reduce cost. As a result, introduction of Probabilistic Design Analysis (PDA) methods to support the current deterministic engineering design practices becomes a necessity to reduce cost without compromising reliability and safety. This paper discusses the importance of PDA methods in NASA's new commercial environment, their applications, and the key role they can play in designing reliable, safe, and affordable launch systems. More specifically, this paper discusses: 1) The involvement of NASA in PDA 2) Why PDA is needed 3) A PDA model structure 4) A PDA example application 5) PDA link to safety and affordability.

Structure of the automated uchebno-methodical complex on technical disciplines

Directory of Open Access Journals (Sweden)

Вячеслав Михайлович Дмитриев

2010-12-01

Full Text Available In article it is put and the problem of automation and information of process of training of students on the basis of the entered system-organizational forms which have received in aggregate the name of education methodical complexes on discipline dares.

A semi-automated method for measuring thickness and white matter ...

African Journals Online (AJOL)

A semi-automated method for measuring thickness and white matter integrity of the corpus callosum. ... and interhemispheric differences. Future research will determine normal values for age and compare CC thickness with peripheral white matter volume loss in large groups of patients, using the semiautomated technique.

The probabilistic approach in the licensing process and the development of probabilistic risk assessment methodology in Japan

International Nuclear Information System (INIS)

Togo, Y.; Sato, K.

1981-01-01

The probabilistic approach has long seemed to be one of the most comprehensive methods for evaluating the safety of nuclear plants. So far, most of the guidelines and criteria for licensing are based on the deterministic concept. However, there have been a few examples to which the probabilistic approach was directly applied, such as the evaluation of aircraft crashes and turbine missiles. One may find other examples of such applications. However, a much more important role is now to be played by this concept, in implementing the 52 recommendations from the lessons learned from the TMI accident. To develop the probabilistic risk assessment methodology most relevant to Japanese situations, a five-year programme plan has been adopted and is to be conducted by the Japan Atomic Research Institute from fiscal 1980. Various problems have been identified and are to be solved through this programme plan. The current status of developments is described together with activities outside the government programme. (author)

When to conduct probabilistic linkage vs. deterministic linkage? A simulation study.

Science.gov (United States)

Zhu, Ying; Matsuyama, Yutaka; Ohashi, Yasuo; Setoguchi, Soko

2015-08-01

When unique identifiers are unavailable, successful record linkage depends greatly on data quality and types of variables available. While probabilistic linkage theoretically captures more true matches than deterministic linkage by allowing imperfection in identifiers, studies have shown inconclusive results likely due to variations in data quality, implementation of linkage methodology and validation method. The simulation study aimed to understand data characteristics that affect the performance of probabilistic vs. deterministic linkage. We created ninety-six scenarios that represent real-life situations using non-unique identifiers. We systematically introduced a range of discriminative power, rate of missing and error, and file size to increase linkage patterns and difficulties. We assessed the performance difference of linkage methods using standard validity measures and computation time. Across scenarios, deterministic linkage showed advantage in PPV while probabilistic linkage showed advantage in sensitivity. Probabilistic linkage uniformly outperformed deterministic linkage as the former generated linkages with better trade-off between sensitivity and PPV regardless of data quality. However, with low rate of missing and error in data, deterministic linkage performed not significantly worse. The implementation of deterministic linkage in SAS took less than 1min, and probabilistic linkage took 2min to 2h depending on file size. Our simulation study demonstrated that the intrinsic rate of missing and error of linkage variables was key to choosing between linkage methods. In general, probabilistic linkage was a better choice, but for exceptionally good quality data (<5% error), deterministic linkage was a more resource efficient choice. Copyright © 2015 Elsevier Inc. All rights reserved.

Advances in probabilistic risk analysis

International Nuclear Information System (INIS)

Hardung von Hardung, H.

1982-01-01

Probabilistic risk analysis can now look back upon almost a quarter century of intensive development. The early studies, whose methods and results are still referred to occasionally, however, only permitted rough estimates to be made of the probabilities of recognizable accident scenarios, failing to provide a method which could have served as a reference base in calculating the overall risk associated with nuclear power plants. The first truly solid attempt was the Rasmussen Study and, partly based on it, the German Risk Study. In those studies, probabilistic risk analysis has been given a much more precise basis. However, new methodologies have been developed in the meantime, which allow much more informative risk studies to be carried out. They have been found to be valuable tools for management decisions with respect to backfitting, reinforcement and risk limitation. Today they are mainly applied by specialized private consultants and have already found widespread application especially in the USA. (orig.) [de

Confluence reduction for probabilistic systems

NARCIS (Netherlands)

Timmer, Mark; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette

In this presentation we introduce a novel technique for state space reduction of probabilistic specifications, based on a newly developed notion of confluence for probabilistic automata. We proved that this reduction preserves branching probabilistic bisimulation and can be applied on-the-fly. To

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components

Science.gov (United States)

1991-01-01

This annual report summarizes the work completed during the third year of technical effort on the referenced contract. Principal developments continue to focus on the Probabilistic Finite Element Method (PFEM) which has been under development for three years. Essentially all of the linear capabilities within the PFEM code are in place. Major progress in the application or verifications phase was achieved. An EXPERT module architecture was designed and partially implemented. EXPERT is a user interface module which incorporates an expert system shell for the implementation of a rule-based interface utilizing the experience and expertise of the user community. The Fast Probability Integration (FPI) Algorithm continues to demonstrate outstanding performance characteristics for the integration of probability density functions for multiple variables. Additionally, an enhanced Monte Carlo simulation algorithm was developed and demonstrated for a variety of numerical strategies.

Probabilistic systems coalgebraically: A survey

Science.gov (United States)

Sokolova, Ana

2011-01-01

We survey the work on both discrete and continuous-space probabilistic systems as coalgebras, starting with how probabilistic systems are modeled as coalgebras and followed by a discussion of their bisimilarity and behavioral equivalence, mentioning results that follow from the coalgebraic treatment of probabilistic systems. It is interesting to note that, for different reasons, for both discrete and continuous probabilistic systems it may be more convenient to work with behavioral equivalence than with bisimilarity. PMID:21998490

Basic design of parallel computational program for probabilistic structural analysis

International Nuclear Information System (INIS)

Kaji, Yoshiyuki; Arai, Taketoshi; Gu, Wenwei; Nakamura, Hitoshi

1999-06-01

In our laboratory, for 'development of damage evaluation method of structural brittle materials by microscopic fracture mechanics and probabilistic theory' (nuclear computational science cross-over research) we examine computational method related to super parallel computation system which is coupled with material strength theory based on microscopic fracture mechanics for latent cracks and continuum structural model to develop new structural reliability evaluation methods for ceramic structures. This technical report is the review results regarding probabilistic structural mechanics theory, basic terms of formula and program methods of parallel computation which are related to principal terms in basic design of computational mechanics program. (author)

Basic design of parallel computational program for probabilistic structural analysis

Energy Technology Data Exchange (ETDEWEB)

Kaji, Yoshiyuki; Arai, Taketoshi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Gu, Wenwei; Nakamura, Hitoshi

1999-06-01

In our laboratory, for `development of damage evaluation method of structural brittle materials by microscopic fracture mechanics and probabilistic theory` (nuclear computational science cross-over research) we examine computational method related to super parallel computation system which is coupled with material strength theory based on microscopic fracture mechanics for latent cracks and continuum structural model to develop new structural reliability evaluation methods for ceramic structures. This technical report is the review results regarding probabilistic structural mechanics theory, basic terms of formula and program methods of parallel computation which are related to principal terms in basic design of computational mechanics program. (author)

Twelve automated thresholding methods for segmentation of PET images: a phantom study

International Nuclear Information System (INIS)

Prieto, Elena; Peñuelas, Iván; Martí-Climent, Josep M; Lecumberri, Pablo; Gómez, Marisol; Pagola, Miguel; Bilbao, Izaskun; Ecay, Margarita

2012-01-01

Tumor volume delineation over positron emission tomography (PET) images is of great interest for proper diagnosis and therapy planning. However, standard segmentation techniques (manual or semi-automated) are operator dependent and time consuming while fully automated procedures are cumbersome or require complex mathematical development. The aim of this study was to segment PET images in a fully automated way by implementing a set of 12 automated thresholding algorithms, classical in the fields of optical character recognition, tissue engineering or non-destructive testing images in high-tech structures. Automated thresholding algorithms select a specific threshold for each image without any a priori spatial information of the segmented object or any special calibration of the tomograph, as opposed to usual thresholding methods for PET. Spherical 18 F-filled objects of different volumes were acquired on clinical PET/CT and on a small animal PET scanner, with three different signal-to-background ratios. Images were segmented with 12 automatic thresholding algorithms and results were compared with the standard segmentation reference, a threshold at 42% of the maximum uptake. Ridler and Ramesh thresholding algorithms based on clustering and histogram-shape information, respectively, provided better results that the classical 42%-based threshold (p < 0.05). We have herein demonstrated that fully automated thresholding algorithms can provide better results than classical PET segmentation tools. (paper)

Improving allowed outage time and surveillance test interval requirements: a study of their interactions using probabilistic methods

International Nuclear Information System (INIS)

Martorell, S.A.; Serradell, V.G.; Samanta, P.K.

1995-01-01

Technical Specifications (TS) define the limits and conditions for operating nuclear plants safely. We selected the Limiting Conditions for Operations (LCO) and Surveillance Requirements (SR), both within TS, as the main items to be evaluated using probabilistic methods. In particular, we focused on the Allowed Outage Time (AOT) and Surveillance Test Interval (STI) requirements in LCO and SR, respectively. Already, significant operating and design experience has accumulated revealing several problems which require modifications in some TS rules. Developments in Probabilistic Safety Assessment (PSA) allow the evaluation of effects due to such modifications in AOT and STI from a risk point of view. Thus, some changes have already been adopted in some plants. However, the combined effect of several changes in AOT and STI, i.e. through their interactions, is not addressed. This paper presents a methodology which encompasses, along with the definition of AOT and STI interactions, the quantification of interactions in terms of risk using PSA methods, an approach for evaluating simultaneous AOT and STI modifications, and an assessment of strategies for giving flexibility to plant operation through simultaneous changes on AOT and STI using trade-off-based risk criteria

Comparison of three flaw-location methods for automated ultrasonic testing

International Nuclear Information System (INIS)

Seiger, H.

1982-01-01

Two well-known methods for locating flaws by measurement of the transit time of ultrasonic pulses are examined theoretically. It is shown that neither is sufficiently reliable for use in automated ultrasonic testing. A third method, which takes into account the shape of the sound field from the probe and the uncertainty in measurement of probe-flaw distance and probe position, is introduced. An experimental comparison of the three methods indicates that use of the advanced method results in more accurate location of flaws. (author)

Method for semi-automated microscopy of filtration-enriched circulating tumor cells

International Nuclear Information System (INIS)

Pailler, Emma; Oulhen, Marianne; Billiot, Fanny; Galland, Alexandre; Auger, Nathalie; Faugeroux, Vincent; Laplace-Builhé, Corinne; Besse, Benjamin; Loriot, Yohann; Ngo-Camus, Maud; Hemanda, Merouan; Lindsay, Colin R.; Soria, Jean-Charles; Vielh, Philippe; Farace, Françoise

2016-01-01

Circulating tumor cell (CTC)-filtration methods capture high numbers of CTCs in non-small-cell lung cancer (NSCLC) and metastatic prostate cancer (mPCa) patients, and hold promise as a non-invasive technique for treatment selection and disease monitoring. However filters have drawbacks that make the automation of microscopy challenging. We report the semi-automated microscopy method we developed to analyze filtration-enriched CTCs from NSCLC and mPCa patients. Spiked cell lines in normal blood and CTCs were enriched by ISET (isolation by size of epithelial tumor cells). Fluorescent staining was carried out using epithelial (pan-cytokeratins, EpCAM), mesenchymal (vimentin, N-cadherin), leukocyte (CD45) markers and DAPI. Cytomorphological staining was carried out with Mayer-Hemalun or Diff-Quik. ALK-, ROS1-, ERG-rearrangement were detected by filter-adapted-FISH (FA-FISH). Microscopy was carried out using an Ariol scanner. Two combined assays were developed. The first assay sequentially combined four-color fluorescent staining, scanning, automated selection of CD45 − cells, cytomorphological staining, then scanning and analysis of CD45 − cell phenotypical and cytomorphological characteristics. CD45 − cell selection was based on DAPI and CD45 intensity, and a nuclear area >55 μm 2 . The second assay sequentially combined fluorescent staining, automated selection of CD45 − cells, FISH scanning on CD45 − cells, then analysis of CD45 − cell FISH signals. Specific scanning parameters were developed to deal with the uneven surface of filters and CTC characteristics. Thirty z-stacks spaced 0.6 μm apart were defined as the optimal setting, scanning 82 %, 91 %, and 95 % of CTCs in ALK-, ROS1-, and ERG-rearranged patients respectively. A multi-exposure protocol consisting of three separate exposure times for green and red fluorochromes was optimized to analyze the intensity, size and thickness of FISH signals. The semi-automated microscopy method reported here

Advanced methods for a probabilistic safety analysis of fires. Development of advanced methods for performing as far as possible realistic plant specific fire risk analysis (fire PSA)

International Nuclear Information System (INIS)

Hofer, E.; Roewekamp, M.; Tuerschmann, M.

2003-07-01

In the frame of the research project RS 1112 'Development of Methods for a Recent Probabilistic Safety Analysis, Particularly Level 2' funded by the German Federal Ministry of Economics and Technology (BMWi), advanced methods, in particular for performing as far as possible realistic plant specific fire risk analyses (fire PSA), should be developed. The present Technical Report gives an overview on the methodologies developed in this context for assessing the fire hazard. In the context of developing advanced methodologies for fire PSA, a probabilistic dynamics analysis with a fire simulation code including an uncertainty and sensitivity study has been performed for an exemplary scenario of a cable fire induced by an electric cabinet inside the containment of a modern Konvoi type German nuclear power plant taking into consideration the effects of fire detection and fire extinguishing means. With the present study, it was possible for the first time to determine the probabilities of specified fire effects from a class of fire events by means of probabilistic dynamics supplemented by uncertainty and sensitivity analyses. The analysis applies a deterministic dynamics model, consisting of a dynamic fire simulation code and a model of countermeasures, considering effects of the stochastics (so-called aleatory uncertainties) as well as uncertainties in the state of knowledge (so-called epistemic uncertainties). By this means, probability assessments including uncertainties are provided to be used within the PSA. (orig.) [de

Online probabilistic operational safety assessment of multi-mode engineering systems using Bayesian methods

International Nuclear Information System (INIS)

Lin, Yufei; Chen, Maoyin; Zhou, Donghua

2013-01-01

In the past decades, engineering systems become more and more complex, and generally work at different operational modes. Since incipient fault can lead to dangerous accidents, it is crucial to develop strategies for online operational safety assessment. However, the existing online assessment methods for multi-mode engineering systems commonly assume that samples are independent, which do not hold for practical cases. This paper proposes a probabilistic framework of online operational safety assessment of multi-mode engineering systems with sample dependency. To begin with, a Gaussian mixture model (GMM) is used to characterize multiple operating modes. Then, based on the definition of safety index (SI), the SI for one single mode is calculated. At last, the Bayesian method is presented to calculate the posterior probabilities belonging to each operating mode with sample dependency. The proposed assessment strategy is applied in two examples: one is the aircraft gas turbine, another is an industrial dryer. Both examples illustrate the efficiency of the proposed method

Simplified Probabilistic Analysis of Settlement of Cyclically Loaded Soil Stratum by Point Estimate Method

Science.gov (United States)

Przewłócki, Jarosław; Górski, Jarosław; Świdziński, Waldemar

2016-12-01

The paper deals with the probabilistic analysis of the settlement of a non-cohesive soil layer subjected to cyclic loading. Originally, the settlement assessment is based on a deterministic compaction model, which requires integration of a set of differential equations. However, with the use of the Bessel functions, the settlement of a soil stratum can be calculated by a simplified algorithm. The compaction model parameters were determined for soil samples taken from subsoil near the Izmit Bay, Turkey. The computations were performed for various sets of random variables. The point estimate method was applied, and the results were verified by the Monte Carlo method. The outcome leads to a conclusion that can be useful in the prediction of soil settlement under seismic loading.

Conditional Probabilistic Population Forecasting

OpenAIRE

Sanderson, Warren C.; Scherbov, Sergei; O'Neill, Brian C.; Lutz, Wolfgang

2004-01-01

Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because...

Orbit transfer rocket engine technology program: Automated preflight methods concept definition

Science.gov (United States)

Erickson, C. M.; Hertzberg, D. W.

1991-01-01

The possibility of automating preflight engine checkouts on orbit transfer engines is discussed. The minimum requirements in terms of information and processing necessary to assess the engine'e integrity and readiness to perform its mission were first defined. A variety of ways for remotely obtaining that information were generated. The sophistication of these approaches varied from a simple preliminary power up, where the engine is fired up for the first time, to the most advanced approach where the sensor and operational history data system alone indicates engine integrity. The critical issues and benefits of these methods were identified, outlined, and prioritized. The technology readiness of each of these automated preflight methods were then rated on a NASA Office of Exploration scale used for comparing technology options for future mission choices. Finally, estimates were made of the remaining cost to advance the technology for each method to a level where the system validation models have been demonstrated in a simulated environment.

Probabilistic calculation for angular dependence collision

International Nuclear Information System (INIS)

Villarino, E.A.

1990-01-01

This collision probabilistic method is broadly used in cylindrical geometry (in one- or two-dimensions). It constitutes a powerful tool for the heterogeneous Response Method where, the coupling current is of the cosine type, that is, without angular dependence at azimuthal angle θ and proportional to μ (cosine of the θ polar angle). (Author) [es

Probabilistic forecasting and Bayesian data assimilation

CERN Document Server

Reich, Sebastian

2015-01-01

In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in ap...

Evaluation of seismic reliability of steel moment resisting frames rehabilitated by concentric braces with probabilistic models

Directory of Open Access Journals (Sweden)

Fateme Rezaei

2017-08-01

Full Text Available Probability of structure failure which has been designed by "deterministic methods" can be more than the one which has been designed in similar situation using probabilistic methods and models considering "uncertainties". The main purpose of this research was to evaluate the seismic reliability of steel moment resisting frames rehabilitated with concentric braces by probabilistic models. To do so, three-story and nine-story steel moment resisting frames were designed based on resistant criteria of Iranian code and then they were rehabilitated based on controlling drift limitations by concentric braces. Probability of frames failure was evaluated by probabilistic models of magnitude, location of earthquake, ground shaking intensity in the area of the structure, probabilistic model of building response (based on maximum lateral roof displacement and probabilistic methods. These frames were analyzed under subcrustal source by sampling probabilistic method "Risk Tools" (RT. Comparing the exceedance probability of building response curves (or selected points on it of the three-story and nine-story model frames (before and after rehabilitation, seismic response of rehabilitated frames, was reduced and their reliability was improved. Also the main effective variables in reducing the probability of frames failure were determined using sensitivity analysis by FORM probabilistic method. The most effective variables reducing the probability of frames failure are  in the magnitude model, ground shaking intensity model error and magnitude model error

Low cost automation

International Nuclear Information System (INIS)

1987-03-01

This book indicates method of building of automation plan, design of automation facilities, automation and CHIP process like basics of cutting, NC processing machine and CHIP handling, automation unit, such as drilling unit, tapping unit, boring unit, milling unit and slide unit, application of oil pressure on characteristics and basic oil pressure circuit, application of pneumatic, automation kinds and application of process, assembly, transportation, automatic machine and factory automation.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise.

Science.gov (United States)

Herzallah, Randa

2015-03-01

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained. Copyright © 2014 Elsevier Ltd. All rights reserved.

Conditional Probabilistic Population Forecasting

OpenAIRE

Sanderson, W.C.; Scherbov, S.; O'Neill, B.C.; Lutz, W.

2003-01-01

Since policy makers often prefer to think in terms of scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy makers it allows them to answer "what if"...

Conditional probabilistic population forecasting

OpenAIRE

Sanderson, Warren; Scherbov, Sergei; O'Neill, Brian; Lutz, Wolfgang

2003-01-01

Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because it allows them...

Statistical modelling of networked human-automation performance using working memory capacity.

Science.gov (United States)

Ahmed, Nisar; de Visser, Ewart; Shaw, Tyler; Mohamed-Ameen, Amira; Campbell, Mark; Parasuraman, Raja

2014-01-01

This study examines the challenging problem of modelling the interaction between individual attentional limitations and decision-making performance in networked human-automation system tasks. Analysis of real experimental data from a task involving networked supervision of multiple unmanned aerial vehicles by human participants shows that both task load and network message quality affect performance, but that these effects are modulated by individual differences in working memory (WM) capacity. These insights were used to assess three statistical approaches for modelling and making predictions with real experimental networked supervisory performance data: classical linear regression, non-parametric Gaussian processes and probabilistic Bayesian networks. It is shown that each of these approaches can help designers of networked human-automated systems cope with various uncertainties in order to accommodate future users by linking expected operating conditions and performance from real experimental data to observable cognitive traits like WM capacity. Practitioner Summary: Working memory (WM) capacity helps account for inter-individual variability in operator performance in networked unmanned aerial vehicle supervisory tasks. This is useful for reliable performance prediction near experimental conditions via linear models; robust statistical prediction beyond experimental conditions via Gaussian process models and probabilistic inference about unknown task conditions/WM capacities via Bayesian network models.

Automation of Classical QEEG Trending Methods for Early Detection of Delayed Cerebral Ischemia: More Work to Do.

Science.gov (United States)

Wickering, Ellis; Gaspard, Nicolas; Zafar, Sahar; Moura, Valdery J; Biswal, Siddharth; Bechek, Sophia; OʼConnor, Kathryn; Rosenthal, Eric S; Westover, M Brandon

2016-06-01

The purpose of this study is to evaluate automated implementations of continuous EEG monitoring-based detection of delayed cerebral ischemia based on methods used in classical retrospective studies. We studied 95 patients with either Fisher 3 or Hunt Hess 4 to 5 aneurysmal subarachnoid hemorrhage who were admitted to the Neurosciences ICU and underwent continuous EEG monitoring. We implemented several variations of two classical algorithms for automated detection of delayed cerebral ischemia based on decreases in alpha-delta ratio and relative alpha variability. Of 95 patients, 43 (45%) developed delayed cerebral ischemia. Our automated implementation of the classical alpha-delta ratio-based trending method resulted in a sensitivity and specificity (Se,Sp) of (80,27)%, compared with the values of (100,76)% reported in the classic study using similar methods in a nonautomated fashion. Our automated implementation of the classical relative alpha variability-based trending method yielded (Se,Sp) values of (65,43)%, compared with (100,46)% reported in the classic study using nonautomated analysis. Our findings suggest that improved methods to detect decreases in alpha-delta ratio and relative alpha variability are needed before an automated EEG-based early delayed cerebral ischemia detection system is ready for clinical use.

Probabilistic fatigue life of balsa cored sandwich composites subjected to transverse shear

DEFF Research Database (Denmark)

Dimitrov, Nikolay Krasimirov; Berggreen, Christian

2015-01-01

A probabilistic fatigue life model for end-grain balsa cored sandwich composites subjectedto transverse shear is proposed. The model is calibrated to measured three-pointbending constant-amplitude fatigue test data using the maximum likelihood method. Some possible applications of the probabilistic...

Policy challenges of increasing automation in driving

Directory of Open Access Journals (Sweden)

Ata M. Khan

2012-03-01

Full Text Available The convergence of information and communication technologies (ICT with automotive technologies has already resulted in automation features in road vehicles and this trend is expected to continue in the future owing to consumer demand, dropping costs of components, and improved reliability. While the automation features that have taken place so far are mainly in the form of information and driver warning technologies (classified as level I pre-2010, future developments in the medium term (level II 2010–2025 are expected to exhibit connected cognitive vehicle features and encompass increasing degree of automation in the form of advanced driver assistance systems. Although autonomous vehicles have been developed for research purposes and are being tested in controlled driving missions, the autonomous driving case is only a long term (level III 2025+ scenario. This paper contributes knowledge on technological forecasts regarding automation, policy challenges for each level of technology development and application context, and the essential instrument of cost-effectiveness for policy analysis which enables policy decisions on the automation systems to be assessed in a consistent and balanced manner. The cost of a system per vehicle is viewed against its effectiveness in meeting policy objectives of improving safety, efficiency, mobility, convenience and reducing environmental effects. Example applications are provided that illustrate the contribution of the methodology in providing information for supporting policy decisions. Given the uncertainties in system costs as well as effectiveness, the tool for assessing policies for future generation features probabilistic and utility-theoretic analysis capability. The policy issues defined and the assessment framework enable the resolution of policy challenges while allowing worthy innovative automation in driving to enhance future road transportation.

Characterizing the topology of probabilistic biological networks.

Science.gov (United States)

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-01-01

Biological interactions are often uncertain events, that may or may not take place with some probability. This uncertainty leads to a massive number of alternative interaction topologies for each such network. The existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. In this paper, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. Using our mathematical representation, we develop a method that can accurately describe the degree distribution of such networks. We also take one more step and extend our method to accurately compute the joint-degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. Our method works quickly even for entire protein-protein interaction (PPI) networks. It also helps us find an adequate mathematical model using MLE. We perform a comparative study of node-degree and joint-degree distributions in two types of biological networks: the classical deterministic networks and the more flexible probabilistic networks. Our results confirm that power-law and log-normal models best describe degree distributions for both probabilistic and deterministic networks. Moreover, the inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected. We also show that probabilistic networks are more robust for node-degree distribution computation than the deterministic ones. all the data sets used, the software

A New Automated Method and Sample Data Flow for Analysis of Volatile Nitrosamines in Human Urine*

Science.gov (United States)

Hodgson, James A.; Seyler, Tiffany H.; McGahee, Ernest; Arnstein, Stephen; Wang, Lanqing

2016-01-01

Volatile nitrosamines (VNAs) are a group of compounds classified as probable (group 2A) and possible (group 2B) carcinogens in humans. Along with certain foods and contaminated drinking water, VNAs are detected at high levels in tobacco products and in both mainstream and sidestream smoke. Our laboratory monitors six urinary VNAs—N-nitrosodimethylamine (NDMA), N-nitrosomethylethylamine (NMEA), N-nitrosodiethylamine (NDEA), N-nitrosopiperidine (NPIP), N-nitrosopyrrolidine (NPYR), and N-nitrosomorpholine (NMOR)—using isotope dilution GC-MS/MS (QQQ) for large population studies such as the National Health and Nutrition Examination Survey (NHANES). In this paper, we report for the first time a new automated sample preparation method to more efficiently quantitate these VNAs. Automation is done using Hamilton STAR™ and Caliper Staccato™ workstations. This new automated method reduces sample preparation time from 4 hours to 2.5 hours while maintaining precision (inter-run CV < 10%) and accuracy (85% - 111%). More importantly this method increases sample throughput while maintaining a low limit of detection (<10 pg/mL) for all analytes. A streamlined sample data flow was created in parallel to the automated method, in which samples can be tracked from receiving to final LIMs output with minimal human intervention, further minimizing human error in the sample preparation process. This new automated method and the sample data flow are currently applied in bio-monitoring of VNAs in the US non-institutionalized population NHANES 2013-2014 cycle. PMID:26949569

Memristive Probabilistic Computing

KAUST Repository

Alahmadi, Hamzah

2017-10-01

In the era of Internet of Things and Big Data, unconventional techniques are rising to accommodate the large size of data and the resource constraints. New computing structures are advancing based on non-volatile memory technologies and different processing paradigms. Additionally, the intrinsic resiliency of current applications leads to the development of creative techniques in computations. In those applications, approximate computing provides a perfect fit to optimize the energy efficiency while compromising on the accuracy. In this work, we build probabilistic adders based on stochastic memristor. Probabilistic adders are analyzed with respect of the stochastic behavior of the underlying memristors. Multiple adder implementations are investigated and compared. The memristive probabilistic adder provides a different approach from the typical approximate CMOS adders. Furthermore, it allows for a high area saving and design exibility between the performance and power saving. To reach a similar performance level as approximate CMOS adders, the memristive adder achieves 60% of power saving. An image-compression application is investigated using the memristive probabilistic adders with the performance and the energy trade-off.

An automated approach for annual layer counting in ice cores

Science.gov (United States)

Winstrup, M.; Svensson, A.; Rasmussen, S. O.; Winther, O.; Steig, E.; Axelrod, A.

2012-04-01

The temporal resolution of some ice cores is sufficient to preserve seasonal information in the ice core record. In such cases, annual layer counting represents one of the most accurate methods to produce a chronology for the core. Yet, manual layer counting is a tedious and sometimes ambiguous job. As reliable layer recognition becomes more difficult, a manual approach increasingly relies on human interpretation of the available data. Thus, much may be gained by an automated and therefore objective approach for annual layer identification in ice cores. We have developed a novel method for automated annual layer counting in ice cores, which relies on Bayesian statistics. It uses algorithms from the statistical framework of Hidden Markov Models (HMM), originally developed for use in machine speech recognition. The strength of this layer detection algorithm lies in the way it is able to imitate the manual procedures for annual layer counting, while being based on purely objective criteria for annual layer identification. With this methodology, it is possible to determine the most likely position of multiple layer boundaries in an entire section of ice core data at once. It provides a probabilistic uncertainty estimate of the resulting layer count, hence ensuring a proper treatment of ambiguous layer boundaries in the data. Furthermore multiple data series can be incorporated to be used at once, hence allowing for a full multi-parameter annual layer counting method similar to a manual approach. In this study, the automated layer counting algorithm has been applied to data from the NGRIP ice core, Greenland. The NGRIP ice core has very high temporal resolution with depth, and hence the potential to be dated by annual layer counting far back in time. In previous studies [Andersen et al., 2006; Svensson et al., 2008], manual layer counting has been carried out back to 60 kyr BP. A comparison between the counted annual layers based on the two approaches will be presented

A new automated method of e-learner's satisfaction measurement

Directory of Open Access Journals (Sweden)

Armands Strazds

2007-06-01

Full Text Available This paper presents a new method of measuring learner’s satisfaction while using electronic learning materials (e-courses, edutainment games, etc. in virtual non-linear environments. Method is based on a relation of Discovering and Learning probability distribution curves obtained by collecting and evaluating the human-computer interaction data. While being near real-time, this measurement is considered highly unobtrusive and cost-effective because of its automated approach. The first working prototype EDUSA 1.0 was developed and successfully tested by the Distance Education Studies Centre of Riga Technical University.

GUI program to compute probabilistic seismic hazard analysis

International Nuclear Information System (INIS)

Shin, Jin Soo; Chi, H. C.; Cho, J. C.; Park, J. H.; Kim, K. G.; Im, I. S.

2005-12-01

The first stage of development of program to compute probabilistic seismic hazard is completed based on Graphic User Interface (GUI). The main program consists of three part - the data input processes, probabilistic seismic hazard analysis and result output processes. The first part has developed and others are developing now in this term. The probabilistic seismic hazard analysis needs various input data which represent attenuation formulae, seismic zoning map, and earthquake event catalog. The input procedure of previous programs based on text interface take a much time to prepare the data. The data cannot be checked directly on screen to prevent input erroneously in existing methods. The new program simplifies the input process and enable to check the data graphically in order to minimize the artificial error within the limits of the possibility

Comparative performance evaluation of automated segmentation methods of hippocampus from magnetic resonance images of temporal lobe epilepsy patients.

Science.gov (United States)

Hosseini, Mohammad-Parsa; Nazem-Zadeh, Mohammad-Reza; Pompili, Dario; Jafari-Khouzani, Kourosh; Elisevich, Kost; Soltanian-Zadeh, Hamid

2016-01-01

Segmentation of the hippocampus from magnetic resonance (MR) images is a key task in the evaluation of mesial temporal lobe epilepsy (mTLE) patients. Several automated algorithms have been proposed although manual segmentation remains the benchmark. Choosing a reliable algorithm is problematic since structural definition pertaining to multiple edges, missing and fuzzy boundaries, and shape changes varies among mTLE subjects. Lack of statistical references and guidance for quantifying the reliability and reproducibility of automated techniques has further detracted from automated approaches. The purpose of this study was to develop a systematic and statistical approach using a large dataset for the evaluation of automated methods and establish a method that would achieve results better approximating those attained by manual tracing in the epileptogenic hippocampus. A template database of 195 (81 males, 114 females; age range 32-67 yr, mean 49.16 yr) MR images of mTLE patients was used in this study. Hippocampal segmentation was accomplished manually and by two well-known tools (FreeSurfer and hammer) and two previously published methods developed at their institution [Automatic brain structure segmentation (ABSS) and LocalInfo]. To establish which method was better performing for mTLE cases, several voxel-based, distance-based, and volume-based performance metrics were considered. Statistical validations of the results using automated techniques were compared with the results of benchmark manual segmentation. Extracted metrics were analyzed to find the method that provided a more similar result relative to the benchmark. Among the four automated methods, ABSS generated the most accurate results. For this method, the Dice coefficient was 5.13%, 14.10%, and 16.67% higher, Hausdorff was 22.65%, 86.73%, and 69.58% lower, precision was 4.94%, -4.94%, and 12.35% higher, and the root mean square (RMS) was 19.05%, 61.90%, and 65.08% lower than LocalInfo, FreeSurfer, and

A probabilistic assessment procedure for evaluating and comparing various NDT methods

International Nuclear Information System (INIS)

Kauer, R.; Guo, W.F.; Schall, M.

2005-01-01

By applying NDT methodologies to assess the integrity of a certain structure, it is strictly recommended to have knowledge about the advantages and disadvantages of the various methods. Especially when new technologies shall be applied, the final question always will be: What is the influence on the overall integrity of the structure? Here, different Probability of Detection (PoD) capacities in combination with different accuracies in sizing a flaw and in combination with different initial crack distributions e.g. resulting from various fabrication methods yield to different values regarding false call rate, rejection rate, and failure rate. So the final goal must be to select the most appropriate and efficient methodology as well as a suitable acceptance criteria addressing the specific advantages and disadvantages of each method. Usually these acceptance criteria are given in the relevant codes. However, often there are various levels of acceptance given, depending on the criticality of the service conditions. In other cases, more information is needed about the consequences of those acceptance criteria to a specific structure. Another application might be the evaluation of a 'new' NDT technology in comparison to an established one. For this purpose, we present a probabilistic evaluation method starting with the initial failure distribution and taking into account PoD and sizing capacities of certain NDT-methods. Finally, Failure Rate, False Call Rate, and Rejection Rate can be presented with respect to the acceptance criteria chosen. (authors)

Probabilistic Durability Analysis in Advanced Engineering Design

Directory of Open Access Journals (Sweden)

A. Kudzys

2000-01-01

Full Text Available Expedience of probabilistic durability concepts and approaches in advanced engineering design of building materials, structural members and systems is considered. Target margin values of structural safety and serviceability indices are analyzed and their draft values are presented. Analytical methods of the cumulative coefficient of correlation and the limit transient action effect for calculation of reliability indices are given. Analysis can be used for probabilistic durability assessment of carrying and enclosure metal, reinforced concrete, wood, plastic, masonry both homogeneous and sandwich or composite structures and some kinds of equipments. Analysis models can be applied in other engineering fields.

Automated immunohistochemical method to analyze large areas of the human cortex.

Science.gov (United States)

Abbass, Mohamad; Trought, Kathleen; Long, David; Semechko, Anton; Wong, Albert H C

2018-01-15

There have been inconsistencies in the histological abnormalities found in the cerebral cortex from patients with schizophrenia, bipolar disorder and major depression. Discrepancies in previously published reports may arise from small sample sizes, inconsistent methodology and biased cell counting. We applied automated quantification of neuron density, neuron size and cortical layer thickness in large regions of the cerebral cortex in psychiatric patients. This method accurately segments DAPI positive cells that are also stained with CUX2 and FEZF2. Cortical layer thickness, neuron density and neuron size were automatically computed for each cortical layer in numerous Brodmann areas. We did not find pronounced cytoarchitectural abnormalities in the anterior cingulate cortex or orbitofrontal cortex in patients with schizophrenia, bipolar disorder or major depressive disorder. There were no significant differences in layer thickness measured in immunohistochemically stained slides compared with traditional Nissl stained slides. Automated cell counts were correlated, reliable and consistent with manual counts, while being much less time-consuming. We demonstrate the validity of using a novel automated analysis approach to post-mortem brain tissue. We were able to analyze large cortical areas and quantify specific cell populations using immunohistochemical markers. Future analyses could benefit from efficient automated analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Probabilistic generation assessment system of renewable energy in Korea

Directory of Open Access Journals (Sweden)

Yeonchan Lee

2016-01-01

Full Text Available This paper proposes probabilistic generation assessment system introduction of renewable energy generators. This paper is focused on wind turbine generator and solar cell generator. The proposed method uses an assessment model based on probabilistic model considering uncertainty of resources (wind speed and solar radiation. Equivalent generation function of the wind and solar farms are evaluated. The equivalent generation curves of wind farms and solar farms are assessed using regression analysis method using typical least square method from last actual generation data for wind farms. The proposed model is applied to Korea Renewable Generation System of 8 grouped 41 wind farms and 9 grouped around 600 solar farms in South Korea.

Probabilistic Logic and Probabilistic Networks

NARCIS (Netherlands)

Haenni, R.; Romeijn, J.-W.; Wheeler, G.; Williamson, J.

2009-01-01

While in principle probabilistic logics might be applied to solve a range of problems, in practice they are rarely applied at present. This is perhaps because they seem disparate, complicated, and computationally intractable. However, we shall argue in this programmatic paper that several approaches

A Comparison of Two Scoring Methods for an Automated Speech Scoring System

Science.gov (United States)

Xi, Xiaoming; Higgins, Derrick; Zechner, Klaus; Williamson, David

2012-01-01

This paper compares two alternative scoring methods--multiple regression and classification trees--for an automated speech scoring system used in a practice environment. The two methods were evaluated on two criteria: construct representation and empirical performance in predicting human scores. The empirical performance of the two scoring models…

Bayesian statistic methods and theri application in probabilistic simulation models

Directory of Open Access Journals (Sweden)

Sergio Iannazzo

2007-03-01

Full Text Available Bayesian statistic methods are facing a rapidly growing level of interest and acceptance in the field of health economics. The reasons of this success are probably to be found on the theoretical fundaments of the discipline that make these techniques more appealing to decision analysis. To this point should be added the modern IT progress that has developed different flexible and powerful statistical software framework. Among them probably one of the most noticeably is the BUGS language project and its standalone application for MS Windows WinBUGS. Scope of this paper is to introduce the subject and to show some interesting applications of WinBUGS in developing complex economical models based on Markov chains. The advantages of this approach reside on the elegance of the code produced and in its capability to easily develop probabilistic simulations. Moreover an example of the integration of bayesian inference models in a Markov model is shown. This last feature let the analyst conduce statistical analyses on the available sources of evidence and exploit them directly as inputs in the economic model.

Engineering Mathematical Analysis Method for Productivity Rate in Linear Arrangement Serial Structure Automated Flow Assembly Line

Directory of Open Access Journals (Sweden)

Tan Chan Sin

2015-01-01

Full Text Available Productivity rate (Q or production rate is one of the important indicator criteria for industrial engineer to improve the system and finish good output in production or assembly line. Mathematical and statistical analysis method is required to be applied for productivity rate in industry visual overviews of the failure factors and further improvement within the production line especially for automated flow line since it is complicated. Mathematical model of productivity rate in linear arrangement serial structure automated flow line with different failure rate and bottleneck machining time parameters becomes the basic model for this productivity analysis. This paper presents the engineering mathematical analysis method which is applied in an automotive company which possesses automated flow assembly line in final assembly line to produce motorcycle in Malaysia. DCAS engineering and mathematical analysis method that consists of four stages known as data collection, calculation and comparison, analysis, and sustainable improvement is used to analyze productivity in automated flow assembly line based on particular mathematical model. Variety of failure rate that causes loss of productivity and bottleneck machining time is shown specifically in mathematic figure and presents the sustainable solution for productivity improvement for this final assembly automated flow line.

Automated method of phasing difficult nuclear magnetic resonance spectra with application to the unsaturated carbon analysis of oils

Energy Technology Data Exchange (ETDEWEB)

Sterna, L.L.; Tong, V.P. (Shell Development Company, Houston, TX (USA). Westhollow Research Center)

1991-08-01

A new method for the automated phasing of n.m.r. spectra is described. The basis of the automation is that the software performs the phasing in the same fashion as a trained n.m.r. operator rather than using mathematical relationships between absorptive and dispersive spectra. The method is illustrated with processing of the {sup 13}C n.m.r. spectrum of a catalytic cracking feedstock. The software readily phased the spectrum even though the spectrum had very broad features and a significant baseline correction. The software performed well even when the time-domain data was left-shifted to introduce a large first-order phase error. The method was applied to measure the percentage of unsaturated carbon in hydrocarbons. Extensive tests were performed to compare automated processing with manual processing for this application; the automated method was found to give both better precision and accuracy. The method can be easily tailored to many other types of analyses. 9 refs., 4 figs., 3 tabs.

Probabilistic Requirements (Partial) Verification Methods Best Practices Improvement. Variables Acceptance Sampling Calculators: Empirical Testing. Volume 2

Science.gov (United States)

Johnson, Kenneth L.; White, K. Preston, Jr.

2012-01-01

The NASA Engineering and Safety Center was requested to improve on the Best Practices document produced for the NESC assessment, Verification of Probabilistic Requirements for the Constellation Program, by giving a recommended procedure for using acceptance sampling by variables techniques as an alternative to the potentially resource-intensive acceptance sampling by attributes method given in the document. In this paper, the results of empirical tests intended to assess the accuracy of acceptance sampling plan calculators implemented for six variable distributions are presented.

Probabilistic Output Analysis by Program Manipulation

DEFF Research Database (Denmark)

Rosendahl, Mads; Kirkeby, Maja Hanne

2015-01-01

The aim of a probabilistic output analysis is to derive a probability distribution of possible output values for a program from a probability distribution of its input. We present a method for performing static output analysis, based on program transformation techniques. It generates a probability...

Ambient Surveillance by Probabilistic-Possibilistic Perception

NARCIS (Netherlands)

Bittermann, M.S.; Ciftcioglu, O.

2013-01-01

A method for quantifying ambient surveillance is presented, which is based on probabilistic-possibilistic perception. The human surveillance of a scene through observing camera sensed images on a monitor is modeled in three steps. First immersion of the observer is simulated by modeling perception

Probabilistic programmable quantum processors

International Nuclear Information System (INIS)

Buzek, V.; Ziman, M.; Hillery, M.

2004-01-01

We analyze how to improve performance of probabilistic programmable quantum processors. We show how the probability of success of the probabilistic processor can be enhanced by using the processor in loops. In addition, we show that an arbitrary SU(2) transformations of qubits can be encoded in program state of a universal programmable probabilistic quantum processor. The probability of success of this processor can be enhanced by a systematic correction of errors via conditional loops. Finally, we show that all our results can be generalized also for qudits. (Abstract Copyright [2004], Wiley Periodicals, Inc.)

Applications of Automation Methods for Nonlinear Fracture Test Analysis

Science.gov (United States)

Allen, Phillip A.; Wells, Douglas N.

2013-01-01

Using automated and standardized computer tools to calculate the pertinent test result values has several advantages such as: 1. allowing high-fidelity solutions to complex nonlinear phenomena that would be impractical to express in written equation form, 2. eliminating errors associated with the interpretation and programing of analysis procedures from the text of test standards, 3. lessening the need for expertise in the areas of solid mechanics, fracture mechanics, numerical methods, and/or finite element modeling, to achieve sound results, 4. and providing one computer tool and/or one set of solutions for all users for a more "standardized" answer. In summary, this approach allows a non-expert with rudimentary training to get the best practical solution based on the latest understanding with minimum difficulty.Other existing ASTM standards that cover complicated phenomena use standard computer programs: 1. ASTM C1340/C1340M-10- Standard Practice for Estimation of Heat Gain or Loss Through Ceilings Under Attics Containing Radiant Barriers by Use of a Computer Program 2. ASTM F 2815 - Standard Practice for Chemical Permeation through Protective Clothing Materials: Testing Data Analysis by Use of a Computer Program 3. ASTM E2807 - Standard Specification for 3D Imaging Data Exchange, Version 1.0 The verification, validation, and round-robin processes required of a computer tool closely parallel the methods that are used to ensure the solution validity for equations included in test standard. The use of automated analysis tools allows the creation and practical implementation of advanced fracture mechanics test standards that capture the physics of a nonlinear fracture mechanics problem without adding undue burden or expense to the user. The presented approach forms a bridge between the equation-based fracture testing standards of today and the next generation of standards solving complex problems through analysis automation.

Development of a simple method for classifying the degree of importance of components in nuclear power plants using probabilistic analysis technique

International Nuclear Information System (INIS)

Shimada, Yoshio; Miyazaki, Takamasa

2006-01-01

In order to analyze large amounts of trouble information of overseas nuclear power plants, it is necessary to select information that is significant in terms of both safety and reliability. In this research, a method of efficiently and simply classifying degrees of importance of components in terms of safety and reliability while paying attention to root-cause components appearing in the information was developed. Regarding safety, the reactor core damage frequency (CDF), which is used in the probabilistic analysis of a reactor, was used. Regarding reliability, the automatic plant trip probability (APTP), which is used in the probabilistic analysis of automatic reactor trips, was used. These two aspects were reflected in the development of criteria for classifying degrees of importance of components. By applying these criteria, a method of quantitatively and simply judging the significance of trouble information of overseas nuclear power plants was developed. (author)

PROBABILISTIC RELATIONAL MODELS OF COMPLETE IL-SEMIRINGS

OpenAIRE

Tsumagari, Norihiro

2012-01-01

This paper studies basic properties of probabilistic multirelations which are generalized the semantic domain of probabilistic systems and then provides two probabilistic models of complete IL-semirings using probabilistic multirelations. Also it is shown that these models need not be models of complete idempotentsemirings.

Probabilistic assessment of dry transport with burnup credit

International Nuclear Information System (INIS)

Lake, W.H.

2003-01-01

The general concept of probabilistic analysis and its application to the use of burnup credit in spent fuel transport is explored. Discussion of the probabilistic analysis method is presented. The concepts of risk and its perception are introduced, and models are suggested for performing probability and risk estimates. The general probabilistic models are used for evaluating the application of burnup credit for dry spent nuclear fuel transport. Two basic cases are considered. The first addresses the question of the relative likelihood of exceeding an established criticality safety limit with and without burnup credit. The second examines the effect of using burnup credit on the overall risk for dry spent fuel transport. Using reasoned arguments and related failure probability and consequence data analysis is performed to estimate the risks of using burnup credit for dry transport of spent nuclear fuel. (author)

Automated quality control methods for sensor data: a novel observatory approach

Directory of Open Access Journals (Sweden)

J. R. Taylor

2013-07-01

Full Text Available National and international networks and observatories of terrestrial-based sensors are emerging rapidly. As such, there is demand for a standardized approach to data quality control, as well as interoperability of data among sensor networks. The National Ecological Observatory Network (NEON has begun constructing their first terrestrial observing sites, with 60 locations expected to be distributed across the US by 2017. This will result in over 14 000 automated sensors recording more than > 100 Tb of data per year. These data are then used to create other datasets and subsequent "higher-level" data products. In anticipation of this challenge, an overall data quality assurance plan has been developed and the first suite of data quality control measures defined. This data-driven approach focuses on automated methods for defining a suite of plausibility test parameter thresholds. Specifically, these plausibility tests scrutinize the data range and variance of each measurement type by employing a suite of binary checks. The statistical basis for each of these tests is developed, and the methods for calculating test parameter thresholds are explored here. While these tests have been used elsewhere, we apply them in a novel approach by calculating their relevant test parameter thresholds. Finally, implementing automated quality control is demonstrated with preliminary data from a NEON prototype site.

Sound Probabilistic #SAT with Projection

Directory of Open Access Journals (Sweden)

Vladimir Klebanov

2016-10-01

Full Text Available We present an improved method for a sound probabilistic estimation of the model count of a boolean formula under projection. The problem solved can be used to encode a variety of quantitative program analyses, such as concerning security of resource consumption. We implement the technique and discuss its application to quantifying information flow in programs.

Comparison of manual versus automated data collection method for an evidence-based nursing practice study.

Science.gov (United States)

Byrne, M D; Jordan, T R; Welle, T

2013-01-01

The objective of this study was to investigate and improve the use of automated data collection procedures for nursing research and quality assurance. A descriptive, correlational study analyzed 44 orthopedic surgical patients who were part of an evidence-based practice (EBP) project examining post-operative oxygen therapy at a Midwestern hospital. The automation work attempted to replicate a manually-collected data set from the EBP project. Automation was successful in replicating data collection for study data elements that were available in the clinical data repository. The automation procedures identified 32 "false negative" patients who met the inclusion criteria described in the EBP project but were not selected during the manual data collection. Automating data collection for certain data elements, such as oxygen saturation, proved challenging because of workflow and practice variations and the reliance on disparate sources for data abstraction. Automation also revealed instances of human error including computational and transcription errors as well as incomplete selection of eligible patients. Automated data collection for analysis of nursing-specific phenomenon is potentially superior to manual data collection methods. Creation of automated reports and analysis may require initial up-front investment with collaboration between clinicians, researchers and information technology specialists who can manage the ambiguities and challenges of research and quality assurance work in healthcare.

Probabilistic and sensitivity analysis of Botlek Bridge structures

Directory of Open Access Journals (Sweden)

Králik Juraj

2017-01-01

Full Text Available This paper deals with the probabilistic and sensitivity analysis of the largest movable lift bridge of the world. The bridge system consists of six reinforced concrete pylons and two steel decks 4000 tons weight each connected through ropes with counterweights. The paper focuses the probabilistic and sensitivity analysis as the base of dynamic study in design process of the bridge. The results had a high importance for practical application and design of the bridge. The model and resistance uncertainties were taken into account in LHS simulation method.

Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

Science.gov (United States)

Fei, Cheng-Wei; Bai, Guang-Chen

2014-12-01

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.

An adaptive multi-element probabilistic collocation method for statistical EMC/EMI characterization

KAUST Repository

Yücel, Abdulkadir C.

2013-12-01

An adaptive multi-element probabilistic collocation (ME-PC) method for quantifying uncertainties in electromagnetic compatibility and interference phenomena involving electrically large, multi-scale, and complex platforms is presented. The method permits the efficient and accurate statistical characterization of observables (i.e., quantities of interest such as coupled voltages) that potentially vary rapidly and/or are discontinuous in the random variables (i.e., parameters that characterize uncertainty in a system\\'s geometry, configuration, or excitation). The method achieves its efficiency and accuracy by recursively and adaptively dividing the domain of the random variables into subdomains using as a guide the decay rate of relative error in a polynomial chaos expansion of the observables. While constructing local polynomial expansions on each subdomain, a fast integral-equation-based deterministic field-cable-circuit simulator is used to compute the observable values at the collocation/integration points determined by the adaptive ME-PC scheme. The adaptive ME-PC scheme requires far fewer (computationally costly) deterministic simulations than traditional polynomial chaos collocation and Monte Carlo methods for computing averages, standard deviations, and probability density functions of rapidly varying observables. The efficiency and accuracy of the method are demonstrated via its applications to the statistical characterization of voltages in shielded/unshielded microwave amplifiers and magnetic fields induced on car tire pressure sensors. © 2013 IEEE.

Fast probabilistic file fingerprinting for big data.

Science.gov (United States)

Tretyakov, Konstantin; Laur, Sven; Smant, Geert; Vilo, Jaak; Prins, Pjotr

2013-01-01

Biological data acquisition is raising new challenges, both in data analysis and handling. Not only is it proving hard to analyze the data at the rate it is generated today, but simply reading and transferring data files can be prohibitively slow due to their size. This primarily concerns logistics within and between data centers, but is also important for workstation users in the analysis phase. Common usage patterns, such as comparing and transferring files, are proving computationally expensive and are tying down shared resources. We present an efficient method for calculating file uniqueness for large scientific data files, that takes less computational effort than existing techniques. This method, called Probabilistic Fast File Fingerprinting (PFFF), exploits the variation present in biological data and computes file fingerprints by sampling randomly from the file instead of reading it in full. Consequently, it has a flat performance characteristic, correlated with data variation rather than file size. We demonstrate that probabilistic fingerprinting can be as reliable as existing hashing techniques, with provably negligible risk of collisions. We measure the performance of the algorithm on a number of data storage and access technologies, identifying its strengths as well as limitations. Probabilistic fingerprinting may significantly reduce the use of computational resources when comparing very large files. Utilisation of probabilistic fingerprinting techniques can increase the speed of common file-related workflows, both in the data center and for workbench analysis. The implementation of the algorithm is available as an open-source tool named pfff, as a command-line tool as well as a C library. The tool can be downloaded from http://biit.cs.ut.ee/pfff.

Probabilistic risk assessment of HTGRs

International Nuclear Information System (INIS)

Fleming, K.N.; Houghton, W.J.; Hannaman, G.W.; Joksimovic, V.

1980-08-01

Probabilistic Risk Assessment methods have been applied to gas-cooled reactors for more than a decade and to HTGRs for more than six years in the programs sponsored by the US Department of Energy. Significant advancements to the development of PRA methodology in these programs are summarized as are the specific applications of the methods to HTGRs. Emphasis here is on PRA as a tool for evaluating HTGR design options. Current work and future directions are also discussed

A multi-atlas based method for automated anatomical rat brain MRI segmentation and extraction of PET activity.

Science.gov (United States)

Lancelot, Sophie; Roche, Roxane; Slimen, Afifa; Bouillot, Caroline; Levigoureux, Elise; Langlois, Jean-Baptiste; Zimmer, Luc; Costes, Nicolas

2014-01-01

Preclinical in vivo imaging requires precise and reproducible delineation of brain structures. Manual segmentation is time consuming and operator dependent. Automated segmentation as usually performed via single atlas registration fails to account for anatomo-physiological variability. We present, evaluate, and make available a multi-atlas approach for automatically segmenting rat brain MRI and extracting PET activies. High-resolution 7T 2DT2 MR images of 12 Sprague-Dawley rat brains were manually segmented into 27-VOI label volumes using detailed protocols. Automated methods were developed with 7/12 atlas datasets, i.e. the MRIs and their associated label volumes. MRIs were registered to a common space, where an MRI template and a maximum probability atlas were created. Three automated methods were tested: 1/registering individual MRIs to the template, and using a single atlas (SA), 2/using the maximum probability atlas (MP), and 3/registering the MRIs from the multi-atlas dataset to an individual MRI, propagating the label volumes and fusing them in individual MRI space (propagation & fusion, PF). Evaluation was performed on the five remaining rats which additionally underwent [18F]FDG PET. Automated and manual segmentations were compared for morphometric performance (assessed by comparing volume bias and Dice overlap index) and functional performance (evaluated by comparing extracted PET measures). Only the SA method showed volume bias. Dice indices were significantly different between methods (PF>MP>SA). PET regional measures were more accurate with multi-atlas methods than with SA method. Multi-atlas methods outperform SA for automated anatomical brain segmentation and PET measure's extraction. They perform comparably to manual segmentation for FDG-PET quantification. Multi-atlas methods are suitable for rapid reproducible VOI analyses.

A probabilistic design method for LMFBR fuel rods

International Nuclear Information System (INIS)

Peck, S.O.; Lovejoy, W.S.

1977-01-01

Fuel rod performance analyses for design purposes are dependent upon material properties, dimensions, and loads that are statistical in nature. Conventional design practice accounts for the uncertainties in relevant parameters by designing to a 'safety factor', set so as to assure safe operation. Arbitrary assignment of these safety factors, based upon a number of 'worst case' assumptions, may result in costly over-design. Probabilistic design methods provide a systematic way to reflect the uncertainties in design parameters. PECS-III is a computer code which employs Monte Carlo techniques to generate the probability density and distribution functions for time-to-failure and cumulative damage for sealed plenum LMFBR fuel rods on a single rod or whole core basis. In Monte Carlo analyses, a deterministic model (that maps single-valued inputs into single-valued outputs) is coupled to a statistical 'driver'. Uncertainties in the input are reflected by assigning probability densities to the input parameters. Dependent input variables are considered multivariate normal. Independent input variables may be arbitrarily distributed. Sample values are drawn from these input densities, and a complete analysis is done by the deterministic model to generate a sample point in the output distribution. This process is repeated many times, and the number of times each output value occurs is accumulated. The probability that some measure of rod performance will fall within given limits is estimated by the relative frequency with which the Monte Carlo samples fall within tho

Japanese round robin analysis for probabilistic fracture mechanics

International Nuclear Information System (INIS)

Yagawa, G.; Yoshimura, S.; Handa, N.

1991-01-01

Recently attention is focused on the probabilistic fracture mechanics, a branch of fracture mechanics with probability theory for a rational mean to assess the strength of components and structures. In particular, the probabilistic fracture mechanics is recognized as the powerful means for quantitative investigation of significance of factors and rational evaluation of life on problems involving a number of uncertainties, such as degradation of material strength, accuracy and frequency of inspection. Comparison with reference experiments are generally employed to assure the analytical accuracy. However, accuracy and reliability of analytical methods in the probabilistic fracture mechanics are hardly verified by experiments. Therefore, it is strongly needed to verify the probabilistic fracture mechanics through the round robin analysis. This paper describes results from the round robin analysis of flat plate with semi-elliptic cracks on the surface, conducted by the PFM Working Group of LE Subcommittee of the Japan Welding Society under the contract of the Japan Atomic Energy Research Institute and participated by Tokyo University, Yokohama National University, the Power Reactor and Nuclear Fuel Corporation, Tokyo Electric Power Co. Central Research Institute of Electric Power Industry, Toshiba Corporation, Kawasaki Heavy Industry Co. and Mitsubishi Heavy Industry Co. (author)

Probabilistic peak detection for first-order chromatographic data

NARCIS (Netherlands)

Lopatka, M.; Vivó-Truyols, G.; Sjerps, M.J.

2014-01-01

We present a novel algorithm for probabilistic peak detection in first-order chromatographic data. Unlike conventional methods that deliver a binary answer pertaining to the expected presence or absence of a chromatographic peak, our method calculates the probability of a point being affected by

On synchronous parallel computations with independent probabilistic choice

International Nuclear Information System (INIS)

Reif, J.H.

1984-01-01

This paper introduces probabilistic choice to synchronous parallel machine models; in particular parallel RAMs. The power of probabilistic choice in parallel computations is illustrate by parallelizing some known probabilistic sequential algorithms. The authors characterize the computational complexity of time, space, and processor bounded probabilistic parallel RAMs in terms of the computational complexity of probabilistic sequential RAMs. They show that parallelism uniformly speeds up time bounded probabilistic sequential RAM computations by nearly a quadratic factor. They also show that probabilistic choice can be eliminated from parallel computations by introducing nonuniformity

A probabilistic model of RNA conformational space

DEFF Research Database (Denmark)

Frellsen, Jes; Moltke, Ida; Thiim, Martin

2009-01-01

, the discrete nature of the fragments necessitates the use of carefully tuned, unphysical energy functions, and their non-probabilistic nature impairs unbiased sampling. We offer a solution to the sampling problem that removes these important limitations: a probabilistic model of RNA structure that allows...... conformations for 9 out of 10 test structures, solely using coarse-grained base-pairing information. In conclusion, the method provides a theoretical and practical solution for a major bottleneck on the way to routine prediction and simulation of RNA structure and dynamics in atomic detail.......The increasing importance of non-coding RNA in biology and medicine has led to a growing interest in the problem of RNA 3-D structure prediction. As is the case for proteins, RNA 3-D structure prediction methods require two key ingredients: an accurate energy function and a conformational sampling...

Probabilistic Modeling of Wind Turbine Drivetrain Components

DEFF Research Database (Denmark)

Rafsanjani, Hesam Mirzaei

Wind energy is one of several energy sources in the world and a rapidly growing industry in the energy sector. When placed in offshore or onshore locations, wind turbines are exposed to wave excitations, highly dynamic wind loads and/or the wakes from other wind turbines. Therefore, most components...... in a wind turbine experience highly dynamic and time-varying loads. These components may fail due to wear or fatigue, and this can lead to unplanned shutdown repairs that are very costly. The design by deterministic methods using safety factors is generally unable to account for the many uncertainties. Thus......, a reliability assessment should be based on probabilistic methods where stochastic modeling of failures is performed. This thesis focuses on probabilistic models and the stochastic modeling of the fatigue life of the wind turbine drivetrain. Hence, two approaches are considered for stochastic modeling...

Probabilistic analysis of deformed mode of engineering constructions’ soil-cement grounds

Directory of Open Access Journals (Sweden)

Vynnykov Yuriy

2017-01-01

Full Text Available The results of the analysis of probabilistic methods that are used to assess the deformed state of the foundations of engineering structures are presented. A finite element analysis of the stress-strain state of the “man made soil ground – foundation – structure” system was carried out. A method for probabilistic calculation using the finite element method is proposed. On a real example, the level of reliability of a design decision based on a deterministic calculation is estimated by probabilistic calculation. On the basis of the statistic data obtained by imitational modeling, the probability of failure and no-failure operation of the structure regarding the absolute value of settlement and regarding the value of tilt against the reinforcement ratio of soft soil grounds settlements was determined. The probability of failure regarding the value of tilt against the reinforcement ratio was taken (15 to 25%, which is 0.03 – 0.05.

Validation of hippocampal volumes measured using a manual method and two automated methods (FreeSurfer and IBASPM) in chronic major depressive disorder

Energy Technology Data Exchange (ETDEWEB)

Tae, Woo Suk; Lee, Kang Uk; Nam, Eui-Cheol; Kim, Keun Woo [Kangwon National University College of Medicine, Neuroscience Research Institute, Kangwon (Korea); Kim, Sam Soo [Kangwon National University College of Medicine, Neuroscience Research Institute, Kangwon (Korea); Kangwon National University Hospital, Department of Radiology, Kangwon-do (Korea)

2008-07-15

To validate the usefulness of the packages available for automated hippocampal volumetry, we measured hippocampal volumes using one manual and two recently developed automated volumetric methods. The study included T1-weighted magnetic resonance imaging (MRI) of 21 patients with chronic major depressive disorder (MDD) and 20 normal controls. Using coronal turbo field echo (TFE) MRI with a slice thickness of 1.3 mm, the hippocampal volumes were measured using three methods: manual volumetry, surface-based parcellation using FreeSurfer, and individual atlas-based volumetry using IBASPM. In addition, the intracranial cavity volume (ICV) was measured manually. The absolute left hippocampal volume of the patients with MDD measured using all three methods was significantly smaller than the left hippocampal volume of the normal controls (manual P=0.029, FreeSurfer P=0.035, IBASPM P=0.018). After controlling for the ICV, except for the right hippocampal volume measured using FreeSurfer, both measured hippocampal volumes of the patients with MDD were significantly smaller than the measured hippocampal volumes of the normal controls (right manual P=0.019, IBASPM P=0.012; left manual P=0.003, FreeSurfer P=0.010, IBASPM P=0.002). In the intrarater reliability test, the intraclass correlation coefficients (ICCs) were all excellent (manual right 0.947, left 0.934; FreeSurfer right 1.000, left 1.000; IBASPM right 1.000, left 1.000). In the test of agreement between the volumetric methods, the ICCs were right 0.846 and left 0.848 (manual and FreeSurfer), and right 0.654 and left 0.717 (manual and IBASPM). The automated hippocampal volumetric methods showed good agreement with manual hippocampal volumetry, but the volume measured using FreeSurfer was 35% larger and the agreement was questionable with IBASPM. Although the automated methods could detect hippocampal atrophy in the patients with MDD, the results indicate that manual hippocampal volumetry is still the gold standard

Validation of hippocampal volumes measured using a manual method and two automated methods (FreeSurfer and IBASPM) in chronic major depressive disorder

International Nuclear Information System (INIS)

Tae, Woo Suk; Lee, Kang Uk; Nam, Eui-Cheol; Kim, Keun Woo; Kim, Sam Soo

2008-01-01

To validate the usefulness of the packages available for automated hippocampal volumetry, we measured hippocampal volumes using one manual and two recently developed automated volumetric methods. The study included T1-weighted magnetic resonance imaging (MRI) of 21 patients with chronic major depressive disorder (MDD) and 20 normal controls. Using coronal turbo field echo (TFE) MRI with a slice thickness of 1.3 mm, the hippocampal volumes were measured using three methods: manual volumetry, surface-based parcellation using FreeSurfer, and individual atlas-based volumetry using IBASPM. In addition, the intracranial cavity volume (ICV) was measured manually. The absolute left hippocampal volume of the patients with MDD measured using all three methods was significantly smaller than the left hippocampal volume of the normal controls (manual P=0.029, FreeSurfer P=0.035, IBASPM P=0.018). After controlling for the ICV, except for the right hippocampal volume measured using FreeSurfer, both measured hippocampal volumes of the patients with MDD were significantly smaller than the measured hippocampal volumes of the normal controls (right manual P=0.019, IBASPM P=0.012; left manual P=0.003, FreeSurfer P=0.010, IBASPM P=0.002). In the intrarater reliability test, the intraclass correlation coefficients (ICCs) were all excellent (manual right 0.947, left 0.934; FreeSurfer right 1.000, left 1.000; IBASPM right 1.000, left 1.000). In the test of agreement between the volumetric methods, the ICCs were right 0.846 and left 0.848 (manual and FreeSurfer), and right 0.654 and left 0.717 (manual and IBASPM). The automated hippocampal volumetric methods showed good agreement with manual hippocampal volumetry, but the volume measured using FreeSurfer was 35% larger and the agreement was questionable with IBASPM. Although the automated methods could detect hippocampal atrophy in the patients with MDD, the results indicate that manual hippocampal volumetry is still the gold standard

Improved detection of chemical substances from colorimetric sensor data using probabilistic machine learning

Science.gov (United States)

Mølgaard, Lasse L.; Buus, Ole T.; Larsen, Jan; Babamoradi, Hamid; Thygesen, Ida L.; Laustsen, Milan; Munk, Jens Kristian; Dossi, Eleftheria; O'Keeffe, Caroline; Lässig, Lina; Tatlow, Sol; Sandström, Lars; Jakobsen, Mogens H.

2017-05-01

We present a data-driven machine learning approach to detect drug- and explosives-precursors using colorimetric sensor technology for air-sampling. The sensing technology has been developed in the context of the CRIM-TRACK project. At present a fully- integrated portable prototype for air sampling with disposable sensing chips and automated data acquisition has been developed. The prototype allows for fast, user-friendly sampling, which has made it possible to produce large datasets of colorimetric data for different target analytes in laboratory and simulated real-world application scenarios. To make use of the highly multi-variate data produced from the colorimetric chip a number of machine learning techniques are employed to provide reliable classification of target analytes from confounders found in the air streams. We demonstrate that a data-driven machine learning method using dimensionality reduction in combination with a probabilistic classifier makes it possible to produce informative features and a high detection rate of analytes. Furthermore, the probabilistic machine learning approach provides a means of automatically identifying unreliable measurements that could produce false predictions. The robustness of the colorimetric sensor has been evaluated in a series of experiments focusing on the amphetamine pre-cursor phenylacetone as well as the improvised explosives pre-cursor hydrogen peroxide. The analysis demonstrates that the system is able to detect analytes in clean air and mixed with substances that occur naturally in real-world sampling scenarios. The technology under development in CRIM-TRACK has the potential as an effective tool to control trafficking of illegal drugs, explosive detection, or in other law enforcement applications.

Probabilistic Latent Semantic Analyses (PLSA in Bibliometric Analysis for Technology Forecasting

Directory of Open Access Journals (Sweden)

Wang Zan

2007-03-01

Full Text Available Due to the availability of internet-based abstract services and patent databases, bibliometric analysis has become one of key technology forecasting approaches. Recently, latent semantic analysis (LSA has been applied to improve the accuracy in document clustering. In this paper, a new LSA method, probabilistic latent semantic analysis (PLSA which uses probabilistic methods and algebra to search latent space in the corpus is further applied in document clustering. The results show that PLSA is more accurate than LSA and the improved iteration method proposed by authors can simplify the computing process and improve the computing efficiency

[Accuracy, precision and speed of parenteral nutrition admixture bags manufacturing: comparison between automated and manual methods].

Science.gov (United States)

Zegbeh, H; Pirot, F; Quessada, T; Durand, T; Vételé, F; Rose, A; Bréant, V; Aulagner, G

2011-01-01

The parenteral nutrition admixture (PNA) manufacturing in hospital pharmacy is realized by aseptic transfer (AT) or sterilizing filtration (SF). The development of filling systems for PNA manufacturing requires, without standard, an evaluation comparing to traditional methods of SF. The filling accuracy of automated AT and SF was evaluated by mass and physical-chemistry tests in repeatability conditions (identical composition of PNA; n=five bags) and reproducibility conditions (different composition of PNA; n=57 bags). For each manufacturing method, the filling precision and the average time for PNA bags manufacturing were evaluated starting from an identical composition and volume PNA (n=five trials). Both manufacturing methods did not show significant difference of accuracy. Precision of both methods was lower than limits generally admitted for acceptability of mass and physical-chemistry tests. However, the manufacturing time for SF was superior (five different binary admixtures in five bags) or inferior (one identical binary admixture in five bags) to time recorded for automated AT. We show that serial manufacturing of PNA bags by SF with identical composition is faster than automated AT. Nevertheless, automated AT is faster than SF in variable composition of PNA. The manufacturing method choice will be motivate by the nature (i. e., variable composition or not) of the manufactured bags. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

Optimization of technical specifications by use of probabilistic methods

International Nuclear Information System (INIS)

Laakso, K.

1990-01-01

The Technical Specifications of a nuclear power plant specify the limits for plant operation from the safety point of view. These operational safety rules were originally defined on the basis of deterministic analyses and engineering judgement. As experience has accumulated, it has proved necessary to consider problems and make specific modifications in these rules. Developments in probabilistic safety assessment have provided a new tool to analyse, present and compare the risk effects of proposed rule modificatons. The main areas covered in the project are operational decisions in failure situations, preventive maintenance during power operation and surveillance tests of standby safety systems. (author)

Some probabilistic aspects of fracture

International Nuclear Information System (INIS)

Thomas, J.M.

1982-01-01

Some probabilistic aspects of fracture in structural and mechanical components are examined. The principles of fracture mechanics, material quality and inspection uncertainty are formulated into a conceptual and analytical framework for prediction of failure probability. The role of probabilistic fracture mechanics in a more global context of risk and optimization of decisions is illustrated. An example, where Monte Carlo simulation was used to implement a probabilistic fracture mechanics analysis, is discussed. (orig.)

Probabilistic structural analysis using a general purpose finite element program

Science.gov (United States)

Riha, D. S.; Millwater, H. R.; Thacker, B. H.

1992-07-01

This paper presents an accurate and efficient method to predict the probabilistic response for structural response quantities, such as stress, displacement, natural frequencies, and buckling loads, by combining the capabilities of MSC/NASTRAN, including design sensitivity analysis and fast probability integration. Two probabilistic structural analysis examples have been performed and verified by comparison with Monte Carlo simulation of the analytical solution. The first example consists of a cantilevered plate with several point loads. The second example is a probabilistic buckling analysis of a simply supported composite plate under in-plane loading. The coupling of MSC/NASTRAN and fast probability integration is shown to be orders of magnitude more efficient than Monte Carlo simulation with excellent accuracy.

A simple and robust method for automated photometric classification of supernovae using neural networks

Science.gov (United States)

Karpenka, N. V.; Feroz, F.; Hobson, M. P.

2013-02-01

A method is presented for automated photometric classification of supernovae (SNe) as Type Ia or non-Ia. A two-step approach is adopted in which (i) the SN light curve flux measurements in each observing filter are fitted separately to an analytical parametrized function that is sufficiently flexible to accommodate virtually all types of SNe and (ii) the fitted function parameters and their associated uncertainties, along with the number of flux measurements, the maximum-likelihood value of the fit and Bayesian evidence for the model, are used as the input feature vector to a classification neural network that outputs the probability that the SN under consideration is of Type Ia. The method is trained and tested using data released following the Supernova Photometric Classification Challenge (SNPCC), consisting of light curves for 20 895 SNe in total. We consider several random divisions of the data into training and testing sets: for instance, for our sample D_1 (D_4), a total of 10 (40) per cent of the data are involved in training the algorithm and the remainder used for blind testing of the resulting classifier; we make no selection cuts. Assigning a canonical threshold probability of pth = 0.5 on the network output to class an SN as Type Ia, for the sample D_1 (D_4) we obtain a completeness of 0.78 (0.82), purity of 0.77 (0.82) and SNPCC figure of merit of 0.41 (0.50). Including the SN host-galaxy redshift and its uncertainty as additional inputs to the classification network results in a modest 5-10 per cent increase in these values. We find that the quality of the classification does not vary significantly with SN redshift. Moreover, our probabilistic classification method allows one to calculate the expected completeness, purity and figure of merit (or other measures of classification quality) as a function of the threshold probability pth, without knowing the true classes of the SNe in the testing sample, as is the case in the classification of real SNe

Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression

Science.gov (United States)

Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen

2018-05-01

To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.

Using ELM-based weighted probabilistic model in the classification of synchronous EEG BCI.

Science.gov (United States)

Tan, Ping; Tan, Guan-Zheng; Cai, Zi-Xing; Sa, Wei-Ping; Zou, Yi-Qun

2017-01-01

Extreme learning machine (ELM) is an effective machine learning technique with simple theory and fast implementation, which has gained increasing interest from various research fields recently. A new method that combines ELM with probabilistic model method is proposed in this paper to classify the electroencephalography (EEG) signals in synchronous brain-computer interface (BCI) system. In the proposed method, the softmax function is used to convert the ELM output to classification probability. The Chernoff error bound, deduced from the Bayesian probabilistic model in the training process, is adopted as the weight to take the discriminant process. Since the proposed method makes use of the knowledge from all preceding training datasets, its discriminating performance improves accumulatively. In the test experiments based on the datasets from BCI competitions, the proposed method is compared with other classification methods, including the linear discriminant analysis, support vector machine, ELM and weighted probabilistic model methods. For comparison, the mutual information, classification accuracy and information transfer rate are considered as the evaluation indicators for these classifiers. The results demonstrate that our method shows competitive performance against other methods.

Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets.

Science.gov (United States)

Chen, Jonathan H; Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B

2017-05-01

Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% ( P  sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Probabilistic risk assessment of HTGRs

International Nuclear Information System (INIS)

Fleming, K.N.; Houghton, W.J.; Hannaman, G.W.; Joksimovic, V.

1981-01-01

Probabilistic Risk Assessment methods have been applied to gas-cooled reactors for more than a decade and to HTGRs for more than six years in the programs sponsored by the U.S. Department of Energy. Significant advancements to the development of PRA methodology in these programs are summarized as are the specific applications of the methods to HTGRs. Emphasis here is on PRA as a tool for evaluating HTGR design options. Current work and future directions are also discussed. (author)

Development of advanced methods and related software for human reliability evaluation within probabilistic safety analyses

International Nuclear Information System (INIS)

Kosmowski, K.T.; Mertens, J.; Degen, G.; Reer, B.

1994-06-01

Human Reliability Analysis (HRA) is an important part of Probabilistic Safety Analysis (PSA). The first part of this report consists of an overview of types of human behaviour and human error including the effect of significant performance shaping factors on human reliability. Particularly with regard to safety assessments for nuclear power plants a lot of HRA methods have been developed. The most important of these methods are presented and discussed in the report, together with techniques for incorporating HRA into PSA and with models of operator cognitive behaviour. Based on existing HRA methods the concept of a software system is described. For the development of this system the utilization of modern programming tools is proposed; the essential goal is the effective application of HRA methods. A possible integration of computeraided HRA within PSA is discussed. The features of Expert System Technology and examples of applications (PSA, HRA) are presented in four appendices. (orig.) [de

Validation of commercially available automated canine-specific immunoturbidimetric method for measuring canine C-reactive protein

DEFF Research Database (Denmark)

Hillström, Anna; Hagman, Ragnvi; Tvedten, Harold

2014-01-01

BACKGROUND: Measurement of C-reactive protein (CRP) is used for diagnosing and monitoring systemic inflammatory disease in canine patients. An automated human immunoturbidimetric assay has been validated for measuring canine CRP, but cross-reactivity with canine CRP is unpredictable. OBJECTIVE......: The purpose of the study was to validate a new automated canine-specific immunoturbidimetric CRP method (Gentian cCRP). METHODS: Studies of imprecision, accuracy, prozone effect, interference, limit of quantification, and stability under different storage conditions were performed. The new method was compared...... with a human CRP assay previously validated for canine CRP determination. Samples from 40 healthy dogs were analyzed to establish a reference interval. RESULTS: Total imprecision was

Guided SAR image despeckling with probabilistic non local weights

Science.gov (United States)

Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

2017-12-01

SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

Probabilistic wind power forecasting based on logarithmic transformation and boundary kernel

International Nuclear Information System (INIS)

Zhang, Yao; Wang, Jianxue; Luo, Xu

2015-01-01

Highlights: • Quantitative information on the uncertainty of wind power generation. • Kernel density estimator provides non-Gaussian predictive distributions. • Logarithmic transformation reduces the skewness of wind power density. • Boundary kernel method eliminates the density leakage near the boundary. - Abstracts: Probabilistic wind power forecasting not only produces the expectation of wind power output, but also gives quantitative information on the associated uncertainty, which is essential for making better decisions about power system and market operations with the increasing penetration of wind power generation. This paper presents a novel kernel density estimator for probabilistic wind power forecasting, addressing two characteristics of wind power which have adverse impacts on the forecast accuracy, namely, the heavily skewed and double-bounded nature of wind power density. Logarithmic transformation is used to reduce the skewness of wind power density, which improves the effectiveness of the kernel density estimator in a transformed scale. Transformations partially relieve the boundary effect problem of the kernel density estimator caused by the double-bounded nature of wind power density. However, the case study shows that there are still some serious problems of density leakage after the transformation. In order to solve this problem in the transformed scale, a boundary kernel method is employed to eliminate the density leak at the bounds of wind power distribution. The improvement of the proposed method over the standard kernel density estimator is demonstrated by short-term probabilistic forecasting results based on the data from an actual wind farm. Then, a detailed comparison is carried out of the proposed method and some existing probabilistic forecasting methods

CANDU type fuel behavior evaluation - a probabilistic approach

International Nuclear Information System (INIS)

Moscalu, D.R.; Horhoianu, G.; Popescu, I.A.; Olteanu, G.

1995-01-01

In order to realistically assess the behavior of the fuel elements during in-reactor operation, probabilistic methods have recently been introduced in the analysis of fuel performance. The present paper summarizes the achievements in this field at the Institute for Nuclear Research (INR), pointing out some advantages of the utilized method in the evaluation of CANDU type fuel behavior in steady state conditions. The Response Surface Method (RSM) has been selected for the investigation of the effects of the variability in fuel element computer code inputs on the code outputs (fuel element performance parameters). A new developed version of the probabilistic code APMESRA based on RSM is briefly presented. The examples of application include the analysis of the results of an in-reactor fuel element experiment and the investigation of the calculated performance parameter distribution for a new CANDU type extended burnup fuel element design. (author)

Suppression of panel flutter of near-space aircraft based on non-probabilistic reliability theory

Directory of Open Access Journals (Sweden)

Ye-Wei Zhang

2016-03-01

Full Text Available The vibration active control of the composite panels with the uncertain parameters in the hypersonic flow is studied using the non-probabilistic reliability theory. Using the piezoelectric patches as active control actuators, dynamic equations of panel are established by finite element method and Hamilton’s principle. And the control model of panel with uncertain parameters is obtained. According to the non-probabilistic reliability index, and besides being based on H∞ robust control theory and non-probabilistic reliability theory, the non-probabilistic reliability performance function is given. Moreover, the relationships between the robust controller and H∞ performance index and reliability are established. Numerical results show that the control method under the influence of reliability, H∞ performance index, and approaching velocity is effective to the vibration suppression of panel in the whole interval of uncertain parameters.

Highly selective coulometric method and equipment for the automated determination of plutonium

International Nuclear Information System (INIS)

Jackson, D.D.; Hollen, R.M.; Roensch, F.R.; Rein, J.E.

1977-01-01

A highly selective, controlled-potential coulometric method has been developed for the determination of plutonium. An automated instrument, consisting of commercial electronic components under control of a programmable calculator, is being constructed. Half-cell potentials and interfering anions are listed

Systems analysis approach to probabilistic modeling of fault trees

International Nuclear Information System (INIS)

Bartholomew, R.J.; Qualls, C.R.

1985-01-01

A method of probabilistic modeling of fault tree logic combined with stochastic process theory (Markov modeling) has been developed. Systems are then quantitatively analyzed probabilistically in terms of their failure mechanisms including common cause/common mode effects and time dependent failure and/or repair rate effects that include synergistic and propagational mechanisms. The modeling procedure results in a state vector set of first order, linear, inhomogeneous, differential equations describing the time dependent probabilities of failure described by the fault tree. The solutions of this Failure Mode State Variable (FMSV) model are cumulative probability distribution functions of the system. A method of appropriate synthesis of subsystems to form larger systems is developed and applied to practical nuclear power safety systems

Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo

Science.gov (United States)

Schön, Thomas B.; Svensson, Andreas; Murray, Lawrence; Lindsten, Fredrik

2018-05-01

Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data. Specifically, we consider learning of probabilistic nonlinear state-space models. There is no closed-form solution available for this problem, implying that we are forced to use approximations. In this tutorial we will provide a self-contained introduction to one of the state-of-the-art methods-the particle Metropolis-Hastings algorithm-which has proven to offer a practical approximation. This is a Monte Carlo based method, where the particle filter is used to guide a Markov chain Monte Carlo method through the parameter space. One of the key merits of the particle Metropolis-Hastings algorithm is that it is guaranteed to converge to the "true solution" under mild assumptions, despite being based on a particle filter with only a finite number of particles. We will also provide a motivating numerical example illustrating the method using a modeling language tailored for sequential Monte Carlo methods. The intention of modeling languages of this kind is to open up the power of sophisticated Monte Carlo methods-including particle Metropolis-Hastings-to a large group of users without requiring them to know all the underlying mathematical details.

Automated image-based colon cleansing for laxative-free CT colonography computer-aided polyp detection

International Nuclear Information System (INIS)

Linguraru, Marius George; Panjwani, Neil; Fletcher, Joel G.; Summer, Ronald M.

2011-01-01

Purpose: To evaluate the performance of a computer-aided detection (CAD) system for detecting colonic polyps at noncathartic computed tomography colonography (CTC) in conjunction with an automated image-based colon cleansing algorithm. Methods: An automated colon cleansing algorithm was designed to detect and subtract tagged-stool, accounting for heterogeneity and poor tagging, to be used in conjunction with a colon CAD system. The method is locally adaptive and combines intensity, shape, and texture analysis with probabilistic optimization. CTC data from cathartic-free bowel preparation were acquired for testing and training the parameters. Patients underwent various colonic preparations with barium or Gastroview in divided doses over 48 h before scanning. No laxatives were administered and no dietary modifications were required. Cases were selected from a polyp-enriched cohort and included scans in which at least 90% of the solid stool was visually estimated to be tagged and each colonic segment was distended in either the prone or supine view. The CAD system was run comparatively with and without the stool subtraction algorithm. Results: The dataset comprised 38 CTC scans from prone and/or supine scans of 19 patients containing 44 polyps larger than 10 mm (22 unique polyps, if matched between prone and supine scans). The results are robust on fine details around folds, thin-stool linings on the colonic wall, near polyps and in large fluid/stool pools. The sensitivity of the CAD system is 70.5% per polyp at a rate of 5.75 false positives/scan without using the stool subtraction module. This detection improved significantly (p = 0.009) after automated colon cleansing on cathartic-free data to 86.4% true positive rate at 5.75 false positives/scan. Conclusions: An automated image-based colon cleansing algorithm designed to overcome the challenges of the noncathartic colon significantly improves the sensitivity of colon CAD by approximately 15%.

Semi-automated extraction of longitudinal subglacial bedforms from digital terrain models - Two new methods

Science.gov (United States)

Jorge, Marco G.; Brennand, Tracy A.

2017-07-01

Relict drumlin and mega-scale glacial lineation (positive relief, longitudinal subglacial bedforms - LSBs) morphometry has been used as a proxy for paleo ice-sheet dynamics. LSB morphometric inventories have relied on manual mapping, which is slow and subjective and thus potentially difficult to reproduce. Automated methods are faster and reproducible, but previous methods for LSB semi-automated mapping have not been highly successful. Here, two new object-based methods for the semi-automated extraction of LSBs (footprints) from digital terrain models are compared in a test area in the Puget Lowland, Washington, USA. As segmentation procedures to create LSB-candidate objects, the normalized closed contour method relies on the contouring of a normalized local relief model addressing LSBs on slopes, and the landform elements mask method relies on the classification of landform elements derived from the digital terrain model. For identifying which LSB-candidate objects correspond to LSBs, both methods use the same LSB operational definition: a ruleset encapsulating expert knowledge, published morphometric data, and the morphometric range of LSBs in the study area. The normalized closed contour method was separately applied to four different local relief models, two computed in moving windows and two hydrology-based. Overall, the normalized closed contour method outperformed the landform elements mask method. The normalized closed contour method performed on a hydrological relief model from a multiple direction flow routing algorithm performed best. For an assessment of its transferability, the normalized closed contour method was evaluated on a second area, the Chautauqua drumlin field, Pennsylvania and New York, USA where it performed better than in the Puget Lowland. A broad comparison to previous methods suggests that the normalized relief closed contour method may be the most capable method to date, but more development is required.

Probabilistic fuel rod analyses using the TRANSURANUS code

Energy Technology Data Exchange (ETDEWEB)

Lassmann, K; O` Carroll, C; Laar, J Van De [CEC Joint Research Centre, Karlsruhe (Germany)

1997-08-01

After more than 25 years of fuel rod modelling research, the basic concepts are well established and the limitations of the specific approaches are known. However, the widely used mechanistic approach leads in many cases to discrepancies between theoretical predictions and experimental evidence indicating that models are not exact and that some of the physical processes encountered are of stochastic nature. To better understand uncertainties and their consequences, the mechanistic approach must therefore be augmented by statistical analyses. In the present paper the basic probabilistic methods are briefly discussed. Two such probabilistic approaches are included in the fuel rod performance code TRANSURANUS: the Monte Carlo method and the Numerical Noise Analysis. These two techniques are compared and their capabilities are demonstrated. (author). 12 refs, 4 figs, 2 tabs.

Growing hierarchical probabilistic self-organizing graphs.

Science.gov (United States)

López-Rubio, Ezequiel; Palomo, Esteban José

2011-07-01

Since the introduction of the growing hierarchical self-organizing map, much work has been done on self-organizing neural models with a dynamic structure. These models allow adjusting the layers of the model to the features of the input dataset. Here we propose a new self-organizing model which is based on a probabilistic mixture of multivariate Gaussian components. The learning rule is derived from the stochastic approximation framework, and a probabilistic criterion is used to control the growth of the model. Moreover, the model is able to adapt to the topology of each layer, so that a hierarchy of dynamic graphs is built. This overcomes the limitations of the self-organizing maps with a fixed topology, and gives rise to a faithful visualization method for high-dimensional data.

Cooling method with automated seasonal freeze protection

Science.gov (United States)

Cambell, Levi; Chu, Richard; David, Milnes; Ellsworth, Jr, Michael; Iyengar, Madhusudan; Simons, Robert; Singh, Prabjit; Zhang, Jing

2016-05-31

An automated multi-fluid cooling method is provided for cooling an electronic component(s). The method includes obtaining a coolant loop, and providing a coolant tank, multiple valves, and a controller. The coolant loop is at least partially exposed to outdoor ambient air temperature(s) during normal operation, and the coolant tank includes first and second reservoirs containing first and second fluids, respectively. The first fluid freezes at a lower temperature than the second, the second fluid has superior cooling properties compared with the first, and the two fluids are soluble. The multiple valves are controllable to selectively couple the first or second fluid into the coolant in the coolant loop, wherein the coolant includes at least the second fluid. The controller automatically controls the valves to vary first fluid concentration level in the coolant loop based on historical, current, or anticipated outdoor air ambient temperature(s) for a time of year.

Evaluation of Probabilistic Disease Forecasts.

Science.gov (United States)

Hughes, Gareth; Burnett, Fiona J

2017-10-01

The statistical evaluation of probabilistic disease forecasts often involves calculation of metrics defined conditionally on disease status, such as sensitivity and specificity. However, for the purpose of disease management decision making, metrics defined conditionally on the result of the forecast-predictive values-are also important, although less frequently reported. In this context, the application of scoring rules in the evaluation of probabilistic disease forecasts is discussed. An index of separation with application in the evaluation of probabilistic disease forecasts, described in the clinical literature, is also considered and its relation to scoring rules illustrated. Scoring rules provide a principled basis for the evaluation of probabilistic forecasts used in plant disease management. In particular, the decomposition of scoring rules into interpretable components is an advantageous feature of their application in the evaluation of disease forecasts.

Short-term Probabilistic Load Forecasting with the Consideration of Human Body Amenity

Directory of Open Access Journals (Sweden)

Ning Lu

2013-02-01

Full Text Available Load forecasting is the basis of power system planning and design. It is important for the economic operation and reliability assurance of power system. However, the results of load forecasting given by most existing methods are deterministic. This study aims at probabilistic load forecasting. First, the support vector machine regression is used to acquire the deterministic results of load forecasting with the consideration of human body amenity. Then the probabilistic load forecasting at a certain confidence level is given after the analysis of error distribution law corresponding to certain heat index interval. The final simulation shows that this probabilistic forecasting method is easy to implement and can provide more information than the deterministic forecasting results, and thus is helpful for decision-makers to make reasonable decisions.

Residual stress measurement by X-ray diffraction with the Gaussian curve method and its automation

International Nuclear Information System (INIS)

Kurita, M.

1987-01-01

X-ray technique with the Gaussian curve method and its automation are described for rapid and nondestructive measurement of residual stress. A simplified equation for measuring the stress by the Gaussian curve method is derived because in its previous form this method required laborious calculation. The residual stress can be measured in a few minutes, depending on materials, using an automated X-ray stress analyzer with a microcomputer which was developed in the laboratory. The residual stress distribution of a partially induction hardened and tempered (at 280 0 C) steel bar was measured with the Gaussian curve method. A sharp residual tensile stress peak of 182 MPa appeared right outside the hardened region at which fatigue failure is liable to occur

Specific Methods of Information Security for Nuclear Materials Control and Accounting Automate Systems

Directory of Open Access Journals (Sweden)

Konstantin Vyacheslavovich Ivanov

2013-02-01

Full Text Available The paper is devoted to specific methods of information security for nuclear materials control and accounting automate systems which is not required of OS and DBMS certifications and allowed to programs modification for clients specific without defenses modification. System ACCORD-2005 demonstrates the realization of this method.

Development of Nuclear Power Plant Safety Evaluation Method for the Automation Algorithm Application

Energy Technology Data Exchange (ETDEWEB)

Kim, Seung Geun; Seong, Poong Hyun [KAIST, Daejeon (Korea, Republic of)

2016-10-15

It is commonly believed that replacing human operators to the automated system would guarantee greater efficiency, lower workloads, and fewer human error. Conventional machine learning techniques are considered as not capable to handle complex situations in NPP. Due to these kinds of issues, automation is not actively adopted although human error probability drastically increases during abnormal situations in NPP due to overload of information, high workload, and short time available for diagnosis. Recently, new machine learning techniques, which are known as ‘deep learning’ techniques have been actively applied to many fields, and the deep learning technique-based artificial intelligences (AIs) are showing better performance than conventional AIs. In 2015, deep Q-network (DQN) which is one of the deep learning techniques was developed and applied to train AI that automatically plays various Atari 2800 games, and this AI surpassed the human-level playing in many kind of games. Also in 2016, ‘Alpha-Go’, which was developed by ‘Google Deepmind’ based on deep learning technique to play the game of Go (i.e. Baduk), was defeated Se-dol Lee who is the World Go champion with score of 4:1. By the effort for reducing human error in NPPs, the ultimate goal of this study is the development of automation algorithm which can cover various situations in NPPs. As the first part, quantitative and real-time NPP safety evaluation method is being developed in order to provide the training criteria for automation algorithm. For that, EWS concept of medical field was adopted, and the applicability is investigated in this paper. Practically, the application of full automation (i.e. fully replaces human operators) may requires much more time for the validation and investigation of side-effects after the development of automation algorithm, and so the adoption in the form of full automation will take long time.

Development of Nuclear Power Plant Safety Evaluation Method for the Automation Algorithm Application

International Nuclear Information System (INIS)

Kim, Seung Geun; Seong, Poong Hyun

2016-01-01

It is commonly believed that replacing human operators to the automated system would guarantee greater efficiency, lower workloads, and fewer human error. Conventional machine learning techniques are considered as not capable to handle complex situations in NPP. Due to these kinds of issues, automation is not actively adopted although human error probability drastically increases during abnormal situations in NPP due to overload of information, high workload, and short time available for diagnosis. Recently, new machine learning techniques, which are known as ‘deep learning’ techniques have been actively applied to many fields, and the deep learning technique-based artificial intelligences (AIs) are showing better performance than conventional AIs. In 2015, deep Q-network (DQN) which is one of the deep learning techniques was developed and applied to train AI that automatically plays various Atari 2800 games, and this AI surpassed the human-level playing in many kind of games. Also in 2016, ‘Alpha-Go’, which was developed by ‘Google Deepmind’ based on deep learning technique to play the game of Go (i.e. Baduk), was defeated Se-dol Lee who is the World Go champion with score of 4:1. By the effort for reducing human error in NPPs, the ultimate goal of this study is the development of automation algorithm which can cover various situations in NPPs. As the first part, quantitative and real-time NPP safety evaluation method is being developed in order to provide the training criteria for automation algorithm. For that, EWS concept of medical field was adopted, and the applicability is investigated in this paper. Practically, the application of full automation (i.e. fully replaces human operators) may requires much more time for the validation and investigation of side-effects after the development of automation algorithm, and so the adoption in the form of full automation will take long time

Improved transformer protection using probabilistic neural network ...

African Journals Online (AJOL)

This article presents a novel technique to distinguish between magnetizing inrush current and internal fault current of power transformer. An algorithm has been developed around the theme of the conventional differential protection method in which parallel combination of Probabilistic Neural Network (PNN) and Power ...

Probabilistic Methods for the Quantification of Uncertainty and Error in Computational Fluid Dynamic Simulations

National Research Council Canada - National Science Library

Faragher, John

2004-01-01

... conservatism to allow for them. This report examines the feasibility of using a probabilistic approach for modelling the component temperatures in an engine using CFD (Computational Fluid Dynamics).

Probabilistic methodology for assessing steam generator tube inspection - Phase II: CANTIA - a probabilistic method for assessing steam generator tube inspections

International Nuclear Information System (INIS)

Harris, J.E.; Gorman, J.A.; Turner, A.P.L.

1997-03-01

The objectives of this project were to develop a computer-based method for probabilistic assessment of inspection strategies for steam generator tubes, and to document the source code and to provide a user's manual for it. The program CANTIA was created to fulfill this objective, and the documentation and verification of the code is provided in this volume. The user's manual for CANTIA is provided as a separate report. CANTIA uses Monte Carlo techniques to determine approximate probabilities of steam generator tube failures under accident conditions and primary-to-secondary leak rates under normal and accident conditions at future points in time. The program also determines approximate future flaw distributions and non-destructive examination results from the input data. The probabilities of failure and leak rates and the future flaw distributions can be influenced by performing inspections of the steam generator tubes at some future points in time, and removing defective tubes from the population. The effect of different inspection and maintenance strategies can therefore be determined as a direct effect on the probability of tube failure and primary-to-secondary leak rate

Compression of Probabilistic XML Documents

Science.gov (United States)

Veldman, Irma; de Keijzer, Ander; van Keulen, Maurice

Database techniques to store, query and manipulate data that contains uncertainty receives increasing research interest. Such UDBMSs can be classified according to their underlying data model: relational, XML, or RDF. We focus on uncertain XML DBMS with as representative example the Probabilistic XML model (PXML) of [10,9]. The size of a PXML document is obviously a factor in performance. There are PXML-specific techniques to reduce the size, such as a push down mechanism, that produces equivalent but more compact PXML documents. It can only be applied, however, where possibilities are dependent. For normal XML documents there also exist several techniques for compressing a document. Since Probabilistic XML is (a special form of) normal XML, it might benefit from these methods even more. In this paper, we show that existing compression mechanisms can be combined with PXML-specific compression techniques. We also show that best compression rates are obtained with a combination of PXML-specific technique with a rather simple generic DAG-compression technique.

A geometrically based method for automated radiosurgery planning

International Nuclear Information System (INIS)

Wagner, Thomas H.; Yi Taeil; Meeks, Sanford L.; Bova, Francis J.; Brechner, Beverly L.; Chen Yunmei; Buatti, John M.; Friedman, William A.; Foote, Kelly D.; Bouchet, Lionel G.

2000-01-01

Purpose: A geometrically based method of multiple isocenter linear accelerator radiosurgery treatment planning optimization was developed, based on a target's solid shape. Methods and Materials: Our method uses an edge detection process to determine the optimal sphere packing arrangement with which to cover the planning target. The sphere packing arrangement is converted into a radiosurgery treatment plan by substituting the isocenter locations and collimator sizes for the spheres. Results: This method is demonstrated on a set of 5 irregularly shaped phantom targets, as well as a set of 10 clinical example cases ranging from simple to very complex in planning difficulty. Using a prototype implementation of the method and standard dosimetric radiosurgery treatment planning tools, feasible treatment plans were developed for each target. The treatment plans generated for the phantom targets showed excellent dose conformity and acceptable dose homogeneity within the target volume. The algorithm was able to generate a radiosurgery plan conforming to the Radiation Therapy Oncology Group (RTOG) guidelines on radiosurgery for every clinical and phantom target examined. Conclusions: This automated planning method can serve as a valuable tool to assist treatment planners in rapidly and consistently designing conformal multiple isocenter radiosurgery treatment plans.

Probabilistic modeling of timber structures

DEFF Research Database (Denmark)

Köhler, Jochen; Sørensen, John Dalsgaard; Faber, Michael Havbro

2007-01-01

The present paper contains a proposal for the probabilistic modeling of timber material properties. It is produced in the context of the Probabilistic Model Code (PMC) of the Joint Committee on Structural Safety (JCSS) [Joint Committee of Structural Safety. Probabilistic Model Code, Internet...... Publication: www.jcss.ethz.ch; 2001] and of the COST action E24 ‘Reliability of Timber Structures' [COST Action E 24, Reliability of timber structures. Several meetings and Publications, Internet Publication: http://www.km.fgg.uni-lj.si/coste24/coste24.htm; 2005]. The present proposal is based on discussions...... and comments from participants of the COST E24 action and the members of the JCSS. The paper contains a description of the basic reference properties for timber strength parameters and ultimate limit state equations for timber components. The recommended probabilistic model for these basic properties...

Probabilistic safety analysis and interpretation thereof

International Nuclear Information System (INIS)

Steininger, U.; Sacher, H.

1999-01-01

Increasing use of the instrumentation of PSA is being made in Germany for quantitative technical safety assessment, for example with regard to incidents which must be reported and forwarding of information, especially in the case of modification of nuclear plants. The Commission for Nuclear Reactor Safety recommends regular execution of PSA on a cycle period of ten years. According to the PSA guidance instructions, probabilistic analyses serve for assessing the degree of safety of the entire plant, expressed as the expectation value for the frequency of endangering conditions. The authors describe the method, action sequence and evaluation of the probabilistic safety analyses. The limits of probabilistic safety analyses arise in the practical implementation. Normally the guidance instructions for PSA are confined to the safety systems, so that in practice they are at best suitable for operational optimisation only to a limited extent. The present restriction of the analyses has a similar effect on power output operation of the plant. This seriously degrades the utilitarian value of these analyses for the plant operators. In order to further develop PSA as a supervisory and operational optimisation instrument, both authors consider it to be appropriate to bring together the specific know-how of analysts, manufacturers, plant operators and experts. (orig.) [de

Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods.

Directory of Open Access Journals (Sweden)

Philippe Burlina

Full Text Available To evaluate the use of ultrasound coupled with machine learning (ML and deep learning (DL techniques for automated or semi-automated classification of myositis.Eighty subjects comprised of 19 with inclusion body myositis (IBM, 14 with polymyositis (PM, 14 with dermatomyositis (DM, and 33 normal (N subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally were acquired. We considered three problems of classification including (A normal vs. affected (DM, PM, IBM; (B normal vs. IBM patients; and (C IBM vs. other types of myositis (DM or PM. We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF and "engineered" features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification.The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A, 86.6% ± 2.4% for (B and 74.8% ± 3.9% for (C, while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A, 84.3% ± 2.3% for (B and 68.9% ± 2.5% for (C.This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.

Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods.

Science.gov (United States)

Burlina, Philippe; Billings, Seth; Joshi, Neil; Albayda, Jemima

2017-01-01

To evaluate the use of ultrasound coupled with machine learning (ML) and deep learning (DL) techniques for automated or semi-automated classification of myositis. Eighty subjects comprised of 19 with inclusion body myositis (IBM), 14 with polymyositis (PM), 14 with dermatomyositis (DM), and 33 normal (N) subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally) were acquired. We considered three problems of classification including (A) normal vs. affected (DM, PM, IBM); (B) normal vs. IBM patients; and (C) IBM vs. other types of myositis (DM or PM). We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs) for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF) and "engineered" features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification. The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A), 86.6% ± 2.4% for (B) and 74.8% ± 3.9% for (C), while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A), 84.3% ± 2.3% for (B) and 68.9% ± 2.5% for (C). This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.

Structural reliability codes for probabilistic design

DEFF Research Database (Denmark)

Ditlevsen, Ove Dalager

1997-01-01

probabilistic code format has not only strong influence on the formal reliability measure, but also on the formal cost of failure to be associated if a design made to the target reliability level is considered to be optimal. In fact, the formal cost of failure can be different by several orders of size for two...... different, but by and large equally justifiable probabilistic code formats. Thus, the consequence is that a code format based on decision theoretical concepts and formulated as an extension of a probabilistic code format must specify formal values to be used as costs of failure. A principle of prudence...... is suggested for guiding the choice of the reference probabilistic code format for constant reliability. In the author's opinion there is an urgent need for establishing a standard probabilistic reliability code. This paper presents some considerations that may be debatable, but nevertheless point...

Comparison of human septal nuclei MRI measurements using automated segmentation and a new manual protocol based on histology

Science.gov (United States)

Butler, Tracy; Zaborszky, Laszlo; Pirraglia, Elizabeth; Li, Jinyu; Wang, Xiuyuan Hugh; Li, Yi; Tsui, Wai; Talos, Delia; Devinsky, Orrin; Kuchna, Izabela; Nowicki, Krzysztof; French, Jacqueline; Kuzniecky, Rubin; Wegiel, Jerzy; Glodzik, Lidia; Rusinek, Henry; DeLeon, Mony J.; Thesen, Thomas

2014-01-01

Septal nuclei, located in basal forebrain, are strongly connected with hippocampi and important in learning and memory, but have received limited research attention in human MRI studies. While probabilistic maps for estimating septal volume on MRI are now available, they have not been independently validated against manual tracing of MRI, typically considered the gold standard for delineating brain structures. We developed a protocol for manual tracing of the human septal region on MRI based on examination of neuroanatomical specimens. We applied this tracing protocol to T1 MRI scans (n=86) from subjects with temporal epilepsy and healthy controls to measure septal volume. To assess the inter-rater reliability of the protocol, a second tracer used the same protocol on 20 scans that were randomly selected from the 72 healthy controls. In addition to measuring septal volume, maximum septal thickness between the ventricles was measured and recorded. The same scans (n=86) were also analysed using septal probabilistic maps and Dartel toolbox in SPM. Results show that our manual tracing algorithm is reliable, and that septal volume measurements obtained via manual and automated methods correlate significantly with each other (pautomated methods detected significantly enlarged septal nuclei in patients with temporal lobe epilepsy in accord with a proposed compensatory neuroplastic process related to the strong connections between septal nuclei and hippocampi. Septal thickness, which was simple to measure with excellent inter-rater reliability, correlated well with both manual and automated septal volume, suggesting it could serve as an easy-to-measure surrogate for septal volume in future studies. Our results call attention to the important though understudied human septal region, confirm its enlargement in temporal lobe epilepsy, and provide a reliable new manual delineation protocol that will facilitate continued study of this critical region. PMID:24736183

A standard analysis method (SAM) for the automated analysis of polychlorinated biphenyls (PCBs) in soils using the chemical analysis automation (CAA) paradigm: validation and performance

International Nuclear Information System (INIS)

Rzeszutko, C.; Johnson, C.R.; Monagle, M.; Klatt, L.N.

1997-10-01

The Chemical Analysis Automation (CAA) program is developing a standardized modular automation strategy for chemical analysis. In this automation concept, analytical chemistry is performed with modular building blocks that correspond to individual elements of the steps in the analytical process. With a standardized set of behaviors and interactions, these blocks can be assembled in a 'plug and play' manner into a complete analysis system. These building blocks, which are referred to as Standard Laboratory Modules (SLM), interface to a host control system that orchestrates the entire analytical process, from sample preparation through data interpretation. The integrated system is called a Standard Analysis Method (SAME). A SAME for the automated determination of Polychlorinated Biphenyls (PCB) in soils, assembled in a mobile laboratory, is undergoing extensive testing and validation. The SAME consists of the following SLMs: a four channel Soxhlet extractor, a High Volume Concentrator, column clean up, a gas chromatograph, a PCB data interpretation module, a robot, and a human- computer interface. The SAME is configured to meet the requirements specified in U.S. Environmental Protection Agency's (EPA) SW-846 Methods 3541/3620A/8082 for the analysis of pcbs in soils. The PCB SAME will be described along with the developmental test plan. Performance data obtained during developmental testing will also be discussed

From sub-source to source: Interpreting results of biological trace investigations using probabilistic models

NARCIS (Netherlands)

Oosterman, W.T.; Kokshoorn, B.; Maaskant-van Wijk, P.A.; de Zoete, J.

2015-01-01

The current method of reporting a putative cell type is based on a non-probabilistic assessment of test results by the forensic practitioner. Additionally, the association between donor and cell type in mixed DNA profiles can be exceedingly complex. We present a probabilistic model for

Automated Cross-Sectional Measurement Method of Intracranial Dural Venous Sinuses.

Science.gov (United States)

Lublinsky, S; Friedman, A; Kesler, A; Zur, D; Anconina, R; Shelef, I

2016-03-01

MRV is an important blood vessel imaging and diagnostic tool for the evaluation of stenosis, occlusions, or aneurysms. However, an accurate image-processing tool for vessel comparison is unavailable. The purpose of this study was to develop and test an automated technique for vessel cross-sectional analysis. An algorithm for vessel cross-sectional analysis was developed that included 7 main steps: 1) image registration, 2) masking, 3) segmentation, 4) skeletonization, 5) cross-sectional planes, 6) clustering, and 7) cross-sectional analysis. Phantom models were used to validate the technique. The method was also tested on a control subject and a patient with idiopathic intracranial hypertension (4 large sinuses tested: right and left transverse sinuses, superior sagittal sinus, and straight sinus). The cross-sectional area and shape measurements were evaluated before and after lumbar puncture in patients with idiopathic intracranial hypertension. The vessel-analysis algorithm had a high degree of stability with <3% of cross-sections manually corrected. All investigated principal cranial blood sinuses had a significant cross-sectional area increase after lumbar puncture (P ≤ .05). The average triangularity of the transverse sinuses was increased, and the mean circularity of the sinuses was decreased by 6% ± 12% after lumbar puncture. Comparison of phantom and real data showed that all computed errors were <1 voxel unit, which confirmed that the method provided a very accurate solution. In this article, we present a novel automated imaging method for cross-sectional vessels analysis. The method can provide an efficient quantitative detection of abnormalities in the dural sinuses. © 2016 by American Journal of Neuroradiology.

Probabilistic safety assessment

International Nuclear Information System (INIS)

Hoertner, H.; Schuetz, B.

1982-09-01

For the purpose of assessing applicability and informativeness on risk-analysis methods in licencing procedures under atomic law, the choice of instruments for probabilistic analysis, the problems in and experience gained in their application, and the discussion of safety goals with respect to such instruments are of paramount significance. Naturally, such a complex field can only be dealt with step by step, making contribution relative to specific problems. The report on hand shows the essentials of a 'stocktaking' of systems relability studies in the licencing procedure under atomic law and of an American report (NUREG-0739) on 'Quantitative Safety Goals'. (orig.) [de

Probabilistic Requirements (Partial) Verification Methods Best Practices Improvement. Variables Acceptance Sampling Calculators: Derivations and Verification of Plans. Volume 1

Science.gov (United States)

Johnson, Kenneth L.; White, K, Preston, Jr.

2012-01-01

The NASA Engineering and Safety Center was requested to improve on the Best Practices document produced for the NESC assessment, Verification of Probabilistic Requirements for the Constellation Program, by giving a recommended procedure for using acceptance sampling by variables techniques. This recommended procedure would be used as an alternative to the potentially resource-intensive acceptance sampling by attributes method given in the document. This document contains the outcome of the assessment.

Confluence Reduction for Probabilistic Systems (extended version)

NARCIS (Netherlands)

Timmer, Mark; Stoelinga, Mariëlle Ida Antoinette; van de Pol, Jan Cornelis

2010-01-01

This paper presents a novel technique for state space reduction of probabilistic specifications, based on a newly developed notion of confluence for probabilistic automata. We prove that this reduction preserves branching probabilistic bisimulation and can be applied on-the-fly. To support the

Breast Density Estimation with Fully Automated Volumetric Method: Comparison to Radiologists' Assessment by BI-RADS Categories.

Science.gov (United States)

Singh, Tulika; Sharma, Madhurima; Singla, Veenu; Khandelwal, Niranjan

2016-01-01

The objective of our study was to calculate mammographic breast density with a fully automated volumetric breast density measurement method and to compare it to breast imaging reporting and data system (BI-RADS) breast density categories assigned by two radiologists. A total of 476 full-field digital mammography examinations with standard mediolateral oblique and craniocaudal views were evaluated by two blinded radiologists and BI-RADS density categories were assigned. Using a fully automated software, mean fibroglandular tissue volume, mean breast volume, and mean volumetric breast density were calculated. Based on percentage volumetric breast density, a volumetric density grade was assigned from 1 to 4. The weighted overall kappa was 0.895 (almost perfect agreement) for the two radiologists' BI-RADS density estimates. A statistically significant difference was seen in mean volumetric breast density among the BI-RADS density categories. With increased BI-RADS density category, increase in mean volumetric breast density was also seen (P BI-RADS categories and volumetric density grading by fully automated software (ρ = 0.728, P BI-RADS density category by two observers showed fair agreement (κ = 0.398 and 0.388, respectively). In our study, a good correlation was seen between density grading using fully automated volumetric method and density grading using BI-RADS density categories assigned by the two radiologists. Thus, the fully automated volumetric method may be used to quantify breast density on routine mammography. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Probabilistic methods for seasonal forecasting in a changing climate: Cox-type regression models

NARCIS (Netherlands)

Maia, A.H.N.; Meinke, H.B.

2010-01-01

For climate risk management, cumulative distribution functions (CDFs) are an important source of information. They are ideally suited to compare probabilistic forecasts of primary (e.g. rainfall) or secondary data (e.g. crop yields). Summarised as CDFs, such forecasts allow an easy quantitative

System and Method for Automated Rendezvous, Docking and Capture of Autonomous Underwater Vehicles

Science.gov (United States)

Stone, William C. (Inventor); Clark, Evan (Inventor); Richmond, Kristof (Inventor); Paulus, Jeremy (Inventor); Kapit, Jason (Inventor); Scully, Mark (Inventor); Kimball, Peter (Inventor)

2018-01-01

A system for automated rendezvous, docking, and capture of autonomous underwater vehicles at the conclusion of a mission comprising of comprised of a docking rod having lighted, pulsating (in both frequency and light intensity) series of LED light strips thereon, with the LEDs at a known spacing, and the autonomous underwater vehicle specially designed to detect and capture the docking rod and then be lifted structurally by a spherical end strop about which the vehicle can be pivoted and hoisted up (e.g., onto a ship). The method of recovery allows for very routine and reliable automated recovery of an unmanned underwater asset.

Advanced Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Technical Exchange Meeting

Energy Technology Data Exchange (ETDEWEB)

Smith, Curtis [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2013-09-01

During FY13, the INL developed an advanced SMR PRA framework which has been described in the report Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Detailed Technical Framework Specification, INL/EXT-13-28974 (April 2013). In this framework, the various areas are considered: Probabilistic models to provide information specific to advanced SMRs Representation of specific SMR design issues such as having co-located modules and passive safety features Use of modern open-source and readily available analysis methods Internal and external events resulting in impacts to safety All-hazards considerations Methods to support the identification of design vulnerabilities Mechanistic and probabilistic data needs to support modeling and tools In order to describe this framework more fully and obtain feedback on the proposed approaches, the INL hosted a technical exchange meeting during August 2013. This report describes the outcomes of that meeting.

An automated image processing method for classification of diabetic retinopathy stages from conjunctival microvasculature images

Science.gov (United States)

Khansari, Maziyar M.; O'Neill, William; Penn, Richard; Blair, Norman P.; Chau, Felix; Shahidi, Mahnaz

2017-03-01

The conjunctiva is a densely vascularized tissue of the eye that provides an opportunity for imaging of human microcirculation. In the current study, automated fine structure analysis of conjunctival microvasculature images was performed to discriminate stages of diabetic retinopathy (DR). The study population consisted of one group of nondiabetic control subjects (NC) and 3 groups of diabetic subjects, with no clinical DR (NDR), non-proliferative DR (NPDR), or proliferative DR (PDR). Ordinary least square regression and Fisher linear discriminant analyses were performed to automatically discriminate images between group pairs of subjects. Human observers who were masked to the grouping of subjects performed image discrimination between group pairs. Over 80% and 70% of images of subjects with clinical and non-clinical DR were correctly discriminated by the automated method, respectively. The discrimination rates of the automated method were higher than human observers. The fine structure analysis of conjunctival microvasculature images provided discrimination of DR stages and can be potentially useful for DR screening and monitoring.

The BoneXpert method for automated determination of skeletal maturity

DEFF Research Database (Denmark)

Thodberg, Hans Henrik; Kreiborg, Sven; Juul, Anders

2009-01-01

Bone age rating is associated with a considerable variability from the human interpretation, and this is the motivation for presenting a new method for automated determination of bone age (skeletal maturity). The method, called BoneXpert, reconstructs, from radiographs of the hand, the borders...... component analysis; 3) the consensus bone age concept that defines bone age of each bone as the best estimate of the bone age of the other bones in the hand; 4) a common bone age model for males and females; and 5) the unified modelling of TW and GP bone age. BoneXpert is developed on 1559 images...

Generalized outcome-based strategy classification: comparing deterministic and probabilistic choice models.

Science.gov (United States)

Hilbig, Benjamin E; Moshagen, Morten

2014-12-01

Model comparisons are a vital tool for disentangling which of several strategies a decision maker may have used--that is, which cognitive processes may have governed observable choice behavior. However, previous methodological approaches have been limited to models (i.e., decision strategies) with deterministic choice rules. As such, psychologically plausible choice models--such as evidence-accumulation and connectionist models--that entail probabilistic choice predictions could not be considered appropriately. To overcome this limitation, we propose a generalization of Bröder and Schiffer's (Journal of Behavioral Decision Making, 19, 361-380, 2003) choice-based classification method, relying on (1) parametric order constraints in the multinomial processing tree framework to implement probabilistic models and (2) minimum description length for model comparison. The advantages of the generalized approach are demonstrated through recovery simulations and an experiment. In explaining previous methods and our generalization, we maintain a nontechnical focus--so as to provide a practical guide for comparing both deterministic and probabilistic choice models.

Probabilistic Accident Progression Analysis with application to a LMFBR design

International Nuclear Information System (INIS)

Jamali, K.M.

1982-01-01

A method for probabilistic analysis of accident sequences in nuclear power plant systems referred to as ''Probabilistic Accident Progression Analysis'' (PAPA) is described. Distinctive features of PAPA include: (1) definition and analysis of initiator-dependent accident sequences on the component level; (2) a new fault-tree simplification technique; (3) a new technique for assessment of the effect of uncertainties in the failure probabilities in the probabilistic ranking of accident sequences; (4) techniques for quantification of dependent failures of similar components, including an iterative technique for high-population components. The methodology is applied to the Shutdown Heat Removal System (SHRS) of the Clinch River Breeder Reactor Plant during its short-term (0 -2 . Major contributors to this probability are the initiators loss of main feedwater system, loss of offsite power, and normal shutdown

Diffusion tensor tractography of the arcuate fasciculus in patients with brain tumors: Comparison between deterministic and probabilistic models.

Science.gov (United States)

Li, Zhixi; Peck, Kyung K; Brennan, Nicole P; Jenabi, Mehrnaz; Hsu, Meier; Zhang, Zhigang; Holodny, Andrei I; Young, Robert J

2013-02-01

The purpose of this study was to compare the deterministic and probabilistic tracking methods of diffusion tensor white matter fiber tractography in patients with brain tumors. We identified 29 patients with left brain tumors probabilistic method based on an extended Monte Carlo Random Walk algorithm. Tracking was controlled using two ROIs corresponding to Broca's and Wernicke's areas. Tracts in tumoraffected hemispheres were examined for extension between Broca's and Wernicke's areas, anterior-posterior length and volume, and compared with the normal contralateral tracts. Probabilistic tracts displayed more complete anterior extension to Broca's area than did FACT tracts on the tumor-affected and normal sides (p probabilistic tracts than FACT tracts (p probabilistic tracts than FACT tracts (p = 0.01). Probabilistic tractography reconstructs the arcuate fasciculus more completely and performs better through areas of tumor and/or edema. The FACT algorithm tends to underestimate the anterior-most fibers of the arcuate fasciculus, which are crossed by primary motor fibers.

Probabilistic liquefaction hazard analysis at liquefied sites of 1956 Dunaharaszti earthquake, in Hungary

Science.gov (United States)

Győri, Erzsébet; Gráczer, Zoltán; Tóth, László; Bán, Zoltán; Horváth, Tibor

2017-04-01

Liquefaction potential evaluations are generally made to assess the hazard from specific scenario earthquakes. These evaluations may estimate the potential in a binary fashion (yes/no), define a factor of safety or predict the probability of liquefaction given a scenario event. Usually the level of ground shaking is obtained from the results of PSHA. Although it is determined probabilistically, a single level of ground shaking is selected and used within the liquefaction potential evaluation. In contrary, the fully probabilistic liquefaction potential assessment methods provide a complete picture of liquefaction hazard, namely taking into account the joint probability distribution of PGA and magnitude of earthquake scenarios; both of which are key inputs in the stress-based simplified methods. Kramer and Mayfield (2007) has developed a fully probabilistic liquefaction potential evaluation method using a performance-based earthquake engineering (PBEE) framework. The results of the procedure are the direct estimate of the return period of liquefaction and the liquefaction hazard curves in function of depth. The method combines the disaggregation matrices computed for different exceedance frequencies during probabilistic seismic hazard analysis with one of the recent models for the conditional probability of liquefaction. We have developed a software for the assessment of performance-based liquefaction triggering on the basis of Kramer and Mayfield method. Originally the SPT based probabilistic method of Cetin et al. (2004) was built-in into the procedure of Kramer and Mayfield to compute the conditional probability however there is no professional consensus about its applicability. Therefore we have included not only Cetin's method but Idriss and Boulanger (2012) SPT based moreover Boulanger and Idriss (2014) CPT based procedures into our computer program. In 1956, a damaging earthquake of magnitude 5.6 occurred in Dunaharaszti, in Hungary. Its epicenter was located

Probabilistic models and machine learning in structural bioinformatics

DEFF Research Database (Denmark)

Hamelryck, Thomas

2009-01-01

. Recently, probabilistic models and machine learning methods based on Bayesian principles are providing efficient and rigorous solutions to challenging problems that were long regarded as intractable. In this review, I will highlight some important recent developments in the prediction, analysis...

Probabilistic Mu-Calculus

DEFF Research Database (Denmark)

Larsen, Kim Guldstrand; Mardare, Radu Iulian; Xue, Bingtian

2016-01-01

We introduce a version of the probabilistic µ-calculus (PMC) built on top of a probabilistic modal logic that allows encoding n-ary inequational conditions on transition probabilities. PMC extends previously studied calculi and we prove that, despite its expressiveness, it enjoys a series of good...... metaproperties. Firstly, we prove the decidability of satisfiability checking by establishing the small model property. An algorithm for deciding the satisfiability problem is developed. As a second major result, we provide a complete axiomatization for the alternation-free fragment of PMC. The completeness proof...

Online Monitoring of Water-Quality Anomaly in Water Distribution Systems Based on Probabilistic Principal Component Analysis by UV-Vis Absorption Spectroscopy

Directory of Open Access Journals (Sweden)

Dibo Hou

2014-01-01

Full Text Available This study proposes a probabilistic principal component analysis- (PPCA- based method for online monitoring of water-quality contaminant events by UV-Vis (ultraviolet-visible spectroscopy. The purpose of this method is to achieve fast and sound protection against accidental and intentional contaminate injection into the water distribution system. The method is achieved first by properly imposing a sliding window onto simultaneously updated online monitoring data collected by the automated spectrometer. The PPCA algorithm is then executed to simplify the large amount of spectrum data while maintaining the necessary spectral information to the largest extent. Finally, a monitoring chart extensively employed in fault diagnosis field methods is used here to search for potential anomaly events and to determine whether the current water-quality is normal or abnormal. A small-scale water-pipe distribution network is tested to detect water contamination events. The tests demonstrate that the PPCA-based online monitoring model can achieve satisfactory results under the ROC curve, which denotes a low false alarm rate and high probability of detecting water contamination events.

Probabilistic Fatigue Analysis of Jacket Support Structures for Offshore Wind Turbines Exemplified on Tubular Joints

OpenAIRE

Kelma, Sebastian; Schaumann, Peter

2015-01-01

The design of offshore wind turbines is usually based on the semi-probabilistic safety concept. Using probabilistic methods, the aim is to find an advanced structural design of OWTs in order to improve safety and reduce costs. The probabilistic design is exemplified on tubular joints of a jacket substructure. Loads and resistance are considered by their respective probability distributions. Time series of loads are generated by fully-coupled numerical simulation of the offshore wind turbine. ...

Quantum probability for probabilists

CERN Document Server

Meyer, Paul-André

1993-01-01

In recent years, the classical theory of stochastic integration and stochastic differential equations has been extended to a non-commutative set-up to develop models for quantum noises. The author, a specialist of classical stochastic calculus and martingale theory, tries to provide anintroduction to this rapidly expanding field in a way which should be accessible to probabilists familiar with the Ito integral. It can also, on the other hand, provide a means of access to the methods of stochastic calculus for physicists familiar with Fock space analysis.

Generative probabilistic models extend the scope of inferential structure determination

DEFF Research Database (Denmark)

Olsson, Simon; Boomsma, Wouter; Frellsen, Jes

2011-01-01

demonstrate that the use of generative probabilistic models instead of physical forcefields in the Bayesian formalism is not only conceptually attractive, but also improves precision and efficiency. Our results open new vistas for the use of sophisticated probabilistic models of biomolecular structure......Conventional methods for protein structure determination from NMR data rely on the ad hoc combination of physical forcefields and experimental data, along with heuristic determination of free parameters such as weight of experimental data relative to a physical forcefield. Recently, a theoretically...

Automation-aided Task Loads Index based on the Automation Rate Reflecting the Effects on Human Operators in NPPs

International Nuclear Information System (INIS)

Lee, Seungmin; Seong, Poonghyun; Kim, Jonghyun

2013-01-01

Many researchers have found that a high automation rate does not guarantee high performance. Therefore, to reflect the effects of automation on human performance, a new estimation method of the automation rate that considers the effects of automation on human operators in nuclear power plants (NPPs) was suggested. These suggested measures express how much automation support human operators but it cannot express the change of human operators' workload, whether the human operators' workload is increased or decreased. Before considering automation rates, whether the adopted automation is good or bad might be estimated in advance. In this study, to estimate the appropriateness of automation according to the change of the human operators' task loads, automation-aided task loads index is suggested based on the concept of the suggested automation rate. To insure plant safety and efficiency on behalf of human operators, various automation systems have been installed in NPPs, and many works which were previously conducted by human operators can now be supported by computer-based operator aids. According to the characteristics of the automation types, the estimation method of the system automation and the cognitive automation rate were suggested. The proposed estimation method concentrates on the effects of introducing automation, so it directly express how much the automated system support human operators. Based on the suggested automation rates, the way to estimate how much the automated system can affect the human operators' cognitive task load is suggested in this study. When there is no automation, the calculated index is 1, and it means there is no change of human operators' task load

Information fusion in signal and image processing major probabilistic and non-probabilistic numerical approaches

CERN Document Server

Bloch, Isabelle

2010-01-01

The area of information fusion has grown considerably during the last few years, leading to a rapid and impressive evolution. In such fast-moving times, it is important to take stock of the changes that have occurred. As such, this books offers an overview of the general principles and specificities of information fusion in signal and image processing, as well as covering the main numerical methods (probabilistic approaches, fuzzy sets and possibility theory and belief functions).

Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods

DEFF Research Database (Denmark)

Warby, Simon C.; Wendt, Sabrina Lyngbye; Welinder, Peter

2014-01-01

to crowdsource spindle identification by human experts and non-experts, and we compared their performance with that of automated detection algorithms in data from middle- to older-aged subjects from the general population. We also refined methods for forming group consensus and evaluating the performance...... of event detectors in physiological data such as electroencephalographic recordings from polysomnography. Compared to the expert group consensus gold standard, the highest performance was by individual experts and the non-expert group consensus, followed by automated spindle detectors. This analysis showed...... that crowdsourcing the scoring of sleep data is an efficient method to collect large data sets, even for difficult tasks such as spindle identification. Further refinements to spindle detection algorithms are needed for middle- to older-aged subjects....

Application of probabilistic risk assessment to reprocessing

International Nuclear Information System (INIS)

Perkins, W.C.

1984-01-01

The Savannah River Laboratory uses probabilistic methods of risk assessment in safety analyses of reprocessing facilities at the Savannah River Plant. This method uses both the probability of an accident and its consequence to calculate the risks from radiological, chemical, and industrial hazards. The three principal steps in such an assesment are identification of accidents, calculation of frequencies, and consequence quantification. The tools used at SRL include several databanks, logic tree methods, and computer-assisted methods for calculating both frequencies and consequences. 5 figures

Early detection of pharmacovigilance signals with automated methods based on false discovery rates: a comparative study.

Science.gov (United States)

Ahmed, Ismaïl; Thiessard, Frantz; Miremont-Salamé, Ghada; Haramburu, Françoise; Kreft-Jais, Carmen; Bégaud, Bernard; Tubert-Bitter, Pascale

2012-06-01

Improving the detection of drug safety signals has led several pharmacovigilance regulatory agencies to incorporate automated quantitative methods into their spontaneous reporting management systems. The three largest worldwide pharmacovigilance databases are routinely screened by the lower bound of the 95% confidence interval of proportional reporting ratio (PRR₀₂.₅), the 2.5% quantile of the Information Component (IC₀₂.₅) or the 5% quantile of the Gamma Poisson Shrinker (GPS₀₅). More recently, Bayesian and non-Bayesian False Discovery Rate (FDR)-based methods were proposed that address the arbitrariness of thresholds and allow for a built-in estimate of the FDR. These methods were also shown through simulation studies to be interesting alternatives to the currently used methods. The objective of this work was twofold. Based on an extensive retrospective study, we compared PRR₀₂.₅, GPS₀₅ and IC₀₂.₅ with two FDR-based methods derived from the Fisher's exact test and the GPS model (GPS(pH0) [posterior probability of the null hypothesis H₀ calculated from the Gamma Poisson Shrinker model]). Secondly, restricting the analysis to GPS(pH0), we aimed to evaluate the added value of using automated signal detection tools compared with 'traditional' methods, i.e. non-automated surveillance operated by pharmacovigilance experts. The analysis was performed sequentially, i.e. every month, and retrospectively on the whole French pharmacovigilance database over the period 1 January 1996-1 July 2002. Evaluation was based on a list of 243 reference signals (RSs) corresponding to investigations launched by the French Pharmacovigilance Technical Committee (PhVTC) during the same period. The comparison of detection methods was made on the basis of the number of RSs detected as well as the time to detection. Results comparing the five automated quantitative methods were in favour of GPS(pH0) in terms of both number of detections of true signals and

Probabilistic Infinite Secret Sharing

OpenAIRE

Csirmaz, László

2013-01-01

The study of probabilistic secret sharing schemes using arbitrary probability spaces and possibly infinite number of participants lets us investigate abstract properties of such schemes. It highlights important properties, explains why certain definitions work better than others, connects this topic to other branches of mathematics, and might yield new design paradigms. A probabilistic secret sharing scheme is a joint probability distribution of the shares and the secret together with a colle...

Solving probabilistic inverse problems rapidly with prior samples

NARCIS (Netherlands)

Käufl, Paul; Valentine, Andrew P.; de Wit, Ralph W.; Trampert, Jeannot

2016-01-01

Owing to the increasing availability of computational resources, in recent years the probabilistic solution of non-linear, geophysical inverse problems by means of sampling methods has become increasingly feasible. Nevertheless, we still face situations in which a Monte Carlo approach is not

Probabilistic Approach to Conditional Probability of Release of Hazardous Materials from Railroad Tank Cars during Accidents

Science.gov (United States)

2009-10-13

This paper describes a probabilistic approach to estimate the conditional probability of release of hazardous materials from railroad tank cars during train accidents. Monte Carlo methods are used in developing a probabilistic model to simulate head ...

Probabilistic predictive modelling of carbon nanocomposites for medical implants design.

Science.gov (United States)

Chua, Matthew; Chui, Chee-Kong

2015-04-01

Modelling of the mechanical properties of carbon nanocomposites based on input variables like percentage weight of Carbon Nanotubes (CNT) inclusions is important for the design of medical implants and other structural scaffolds. Current constitutive models for the mechanical properties of nanocomposites may not predict well due to differences in conditions, fabrication techniques and inconsistencies in reagents properties used across industries and laboratories. Furthermore, the mechanical properties of the designed products are not deterministic, but exist as a probabilistic range. A predictive model based on a modified probabilistic surface response algorithm is proposed in this paper to address this issue. Tensile testing of three groups of different CNT weight fractions of carbon nanocomposite samples displays scattered stress-strain curves, with the instantaneous stresses assumed to vary according to a normal distribution at a specific strain. From the probabilistic density function of the experimental data, a two factors Central Composite Design (CCD) experimental matrix based on strain and CNT weight fraction input with their corresponding stress distribution was established. Monte Carlo simulation was carried out on this design matrix to generate a predictive probabilistic polynomial equation. The equation and method was subsequently validated with more tensile experiments and Finite Element (FE) studies. The method was subsequently demonstrated in the design of an artificial tracheal implant. Our algorithm provides an effective way to accurately model the mechanical properties in implants of various compositions based on experimental data of samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

Probabilistic safety assessment for research reactors

International Nuclear Information System (INIS)

1986-12-01

Increasing interest in using Probabilistic Safety Assessment (PSA) methods for research reactor safety is being observed in many countries throughout the world. This is mainly because of the great ability of this approach in achieving safe and reliable operation of research reactors. There is also a need to assist developing countries to apply Probabilistic Safety Assessment to existing nuclear facilities which are simpler and therefore less complicated to analyse than a large Nuclear Power Plant. It may be important, therefore, to develop PSA for research reactors. This might also help to better understand the safety characteristics of the reactor and to base any backfitting on a cost-benefit analysis which would ensure that only necessary changes are made. This document touches on all the key aspects of PSA but placed greater emphasis on so-called systems analysis aspects rather than the in-plant or ex-plant consequences

Completely automated modal analysis procedure based on the combination of different OMA methods

Science.gov (United States)

Ripamonti, Francesco; Bussini, Alberto; Resta, Ferruccio

2018-03-01

In this work a completely automated output-only Modal Analysis procedure is presented and all its benefits are listed. Based on the merging of different Operational Modal Analysis methods and a statistical approach, the identification process has been improved becoming more robust and giving as results only the real natural frequencies, damping ratios and mode shapes of the system. The effect of the temperature can be taken into account as well, leading to the creation of a better tool for automated Structural Health Monitoring. The algorithm has been developed and tested on a numerical model of a scaled three-story steel building present in the laboratories of Politecnico di Milano.

Probabilistic cost estimating of nuclear power plant construction projects

International Nuclear Information System (INIS)

Finch, W.C.; Perry, L.W.; Postula, F.D.

1978-01-01

This paper shows how to identify and isolate cost accounts by developing probability trees down to component levels as justified by value and cost uncertainty. Examples are given of the procedure for assessing uncertainty in all areas contributing to cost: design, factory equipment pricing, and field labor and materials. The method of combining these individual uncertainties is presented so that the cost risk can be developed for components, systems and the total plant construction project. Formats which enable management to use the probabilistic cost estimate information for business planning and risk control are illustrated. Topics considered include code estimate performance, cost allocation, uncertainty encoding, probabilistic cost distributions, and interpretation. Effective cost control of nuclear power plant construction projects requires insight into areas of greatest cost uncertainty and a knowledge of the factors which can cause costs to vary from the single value estimates. It is concluded that probabilistic cost estimating can provide the necessary assessment of uncertainties both as to the cause and the consequences

Probabilistic DHP adaptive critic for nonlinear stochastic control systems.

Science.gov (United States)

Herzallah, Randa

2013-06-01

Following the recently developed algorithms for fully probabilistic control design for general dynamic stochastic systems (Herzallah & Káarnáy, 2011; Kárný, 1996), this paper presents the solution to the probabilistic dual heuristic programming (DHP) adaptive critic method (Herzallah & Káarnáy, 2011) and randomized control algorithm for stochastic nonlinear dynamical systems. The purpose of the randomized control input design is to make the joint probability density function of the closed loop system as close as possible to a predetermined ideal joint probability density function. This paper completes the previous work (Herzallah & Káarnáy, 2011; Kárný, 1996) by formulating and solving the fully probabilistic control design problem on the more general case of nonlinear stochastic discrete time systems. A simulated example is used to demonstrate the use of the algorithm and encouraging results have been obtained. Copyright © 2013 Elsevier Ltd. All rights reserved.

Integrated probabilistic risk assessment for nanoparticles: the case of nanosilica in food.

Science.gov (United States)

Jacobs, Rianne; van der Voet, Hilko; Ter Braak, Cajo J F

Insight into risks of nanotechnology and the use of nanoparticles is an essential condition for the social acceptance and safe use of nanotechnology. One of the problems with which the risk assessment of nanoparticles is faced is the lack of data, resulting in uncertainty in the risk assessment. We attempt to quantify some of this uncertainty by expanding a previous deterministic study on nanosilica (5-200 nm) in food into a fully integrated probabilistic risk assessment. We use the integrated probabilistic risk assessment method in which statistical distributions and bootstrap methods are used to quantify uncertainty and variability in the risk assessment. Due to the large amount of uncertainty present, this probabilistic method, which separates variability from uncertainty, contributed to a better understandable risk assessment. We found that quantifying the uncertainties did not increase the perceived risk relative to the outcome of the deterministic study. We pinpointed particular aspects of the hazard characterization that contributed most to the total uncertainty in the risk assessment, suggesting that further research would benefit most from obtaining more reliable data on those aspects.

Integrated probabilistic risk assessment for nanoparticles: the case of nanosilica in food

International Nuclear Information System (INIS)

Jacobs, Rianne; Voet, Hilko van der; Braak, Cajo J. F. ter

2015-01-01

Insight into risks of nanotechnology and the use of nanoparticles is an essential condition for the social acceptance and safe use of nanotechnology. One of the problems with which the risk assessment of nanoparticles is faced is the lack of data, resulting in uncertainty in the risk assessment. We attempt to quantify some of this uncertainty by expanding a previous deterministic study on nanosilica (5–200 nm) in food into a fully integrated probabilistic risk assessment. We use the integrated probabilistic risk assessment method in which statistical distributions and bootstrap methods are used to quantify uncertainty and variability in the risk assessment. Due to the large amount of uncertainty present, this probabilistic method, which separates variability from uncertainty, contributed to a better understandable risk assessment. We found that quantifying the uncertainties did not increase the perceived risk relative to the outcome of the deterministic study. We pinpointed particular aspects of the hazard characterization that contributed most to the total uncertainty in the risk assessment, suggesting that further research would benefit most from obtaining more reliable data on those aspects

Integrated probabilistic risk assessment for nanoparticles: the case of nanosilica in food

Energy Technology Data Exchange (ETDEWEB)

Jacobs, Rianne, E-mail: rianne.jacobs@wur.nl; Voet, Hilko van der; Braak, Cajo J. F. ter [Wageningen University and Research Centre, Biometris (Netherlands)

2015-06-15

Insight into risks of nanotechnology and the use of nanoparticles is an essential condition for the social acceptance and safe use of nanotechnology. One of the problems with which the risk assessment of nanoparticles is faced is the lack of data, resulting in uncertainty in the risk assessment. We attempt to quantify some of this uncertainty by expanding a previous deterministic study on nanosilica (5–200 nm) in food into a fully integrated probabilistic risk assessment. We use the integrated probabilistic risk assessment method in which statistical distributions and bootstrap methods are used to quantify uncertainty and variability in the risk assessment. Due to the large amount of uncertainty present, this probabilistic method, which separates variability from uncertainty, contributed to a better understandable risk assessment. We found that quantifying the uncertainties did not increase the perceived risk relative to the outcome of the deterministic study. We pinpointed particular aspects of the hazard characterization that contributed most to the total uncertainty in the risk assessment, suggesting that further research would benefit most from obtaining more reliable data on those aspects.

Probabilistic brains: knowns and unknowns

Science.gov (United States)

Pouget, Alexandre; Beck, Jeffrey M; Ma, Wei Ji; Latham, Peter E

2015-01-01

There is strong behavioral and physiological evidence that the brain both represents probability distributions and performs probabilistic inference. Computational neuroscientists have started to shed light on how these probabilistic representations and computations might be implemented in neural circuits. One particularly appealing aspect of these theories is their generality: they can be used to model a wide range of tasks, from sensory processing to high-level cognition. To date, however, these theories have only been applied to very simple tasks. Here we discuss the challenges that will emerge as researchers start focusing their efforts on real-life computations, with a focus on probabilistic learning, structural learning and approximate inference. PMID:23955561

Probabilistic simple sticker systems

Science.gov (United States)

Selvarajoo, Mathuri; Heng, Fong Wan; Sarmin, Nor Haniza; Turaev, Sherzod

2017-04-01

A model for DNA computing using the recombination behavior of DNA molecules, known as a sticker system, was introduced by by L. Kari, G. Paun, G. Rozenberg, A. Salomaa, and S. Yu in the paper entitled DNA computing, sticker systems and universality from the journal of Acta Informatica vol. 35, pp. 401-420 in the year 1998. A sticker system uses the Watson-Crick complementary feature of DNA molecules: starting from the incomplete double stranded sequences, and iteratively using sticking operations until a complete double stranded sequence is obtained. It is known that sticker systems with finite sets of axioms and sticker rules generate only regular languages. Hence, different types of restrictions have been considered to increase the computational power of sticker systems. Recently, a variant of restricted sticker systems, called probabilistic sticker systems, has been introduced [4]. In this variant, the probabilities are initially associated with the axioms, and the probability of a generated string is computed by multiplying the probabilities of all occurrences of the initial strings in the computation of the string. Strings for the language are selected according to some probabilistic requirements. In this paper, we study fundamental properties of probabilistic simple sticker systems. We prove that the probabilistic enhancement increases the computational power of simple sticker systems.

Probabilistic fracture finite elements

Science.gov (United States)

Liu, W. K.; Belytschko, T.; Lua, Y. J.

1991-05-01

The Probabilistic Fracture Mechanics (PFM) is a promising method for estimating the fatigue life and inspection cycles for mechanical and structural components. The Probability Finite Element Method (PFEM), which is based on second moment analysis, has proved to be a promising, practical approach to handle problems with uncertainties. As the PFEM provides a powerful computational tool to determine first and second moment of random parameters, the second moment reliability method can be easily combined with PFEM to obtain measures of the reliability of the structural system. The method is also being applied to fatigue crack growth. Uncertainties in the material properties of advanced materials such as polycrystalline alloys, ceramics, and composites are commonly observed from experimental tests. This is mainly attributed to intrinsic microcracks, which are randomly distributed as a result of the applied load and the residual stress.