Mathematical statistics and stochastic processes
Bosq, Denis
2013-01-01
Generally, books on mathematical statistics are restricted to the case of independent identically distributed random variables. In this book however, both this case AND the case of dependent variables, i.e. statistics for discrete and continuous time processes, are studied. This second case is very important for today's practitioners.Mathematical Statistics and Stochastic Processes is based on decision theory and asymptotic statistics and contains up-to-date information on the relevant topics of theory of probability, estimation, confidence intervals, non-parametric statistics and rob
Müller, M. F.; Thompson, S. E.
2016-02-01
The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drivers of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by frequent wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are favored over statistical models.
Bootstrap-based confidence estimation in PCA and multivariate statistical process control
DEFF Research Database (Denmark)
Babamoradi, Hamid
be used to detect outliers in the data since the outliers can distort the bootstrap estimates. Bootstrap-based confidence limits were suggested as alternative to the asymptotic limits for control charts and contribution plots in MSPC (Paper II). The results showed that in case of the Q-statistic......Traditional/Asymptotic confidence estimation has limited applicability since it needs statistical theories to estimate the confidences, which are not available for all indicators/parameters. Furthermore, in case the theories are available for a specific indicator/parameter, the theories are based....... The goal was to improve process monitoring by improving the quality of MSPC charts and contribution plots. Bootstrapping algorithm to build confidence limits was illustrated in a case study format (Paper I). The main steps in the algorithm were discussed where a set of sensible choices (plus...
Probability, Statistics, and Stochastic Processes
Olofsson, Peter
2011-01-01
A mathematical and intuitive approach to probability, statistics, and stochastic processes This textbook provides a unique, balanced approach to probability, statistics, and stochastic processes. Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area. This text combines a rigorous, calculus-based development of theory with a more intuitive approach that appeals to readers' sense of reason and logic, an approach developed through the author's many years of classroom experience. The text begins with three chapters that d
Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process
Directory of Open Access Journals (Sweden)
Yongchao Hou
2014-01-01
Full Text Available Uncertain statistics is a methodology for collecting and interpreting the expert’s experimental data by uncertainty theory. In order to estimate uncertainty distributions, an optimization model based on analytic hierarchy process (AHP and interpolation method is proposed in this paper. In addition, the principle of least squares method is presented to estimate uncertainty distributions with known functional form. Finally, the effectiveness of this method is illustrated by an example.
Using Statistical Process Control to Make Data-Based Clinical Decisions.
Pfadt, Al; Wheeler, Donald J.
1995-01-01
Statistical process control (SPC), which employs simple statistical tools and problem-solving techniques such as histograms, control charts, flow charts, and Pareto charts to implement continual product improvement procedures, can be incorporated into human service organizations. Examples illustrate use of SPC procedures to analyze behavioral data…
Statistical process control in wine industry using control cards
Dimitrieva, Evica; Atanasova-Pacemska, Tatjana; Pacemska, Sanja
2013-01-01
This paper is based on the research of the technological process of automatic filling of bottles of wine in winery in Stip, Republic of Macedonia. The statistical process control using statistical control card is created. The results and recommendations for improving the process are discussed.
Statistical Data Processing with R – Metadata Driven Approach
Directory of Open Access Journals (Sweden)
Rudi SELJAK
2016-06-01
Full Text Available In recent years the Statistical Office of the Republic of Slovenia has put a lot of effort into re-designing its statistical process. We replaced the classical stove-pipe oriented production system with general software solutions, based on the metadata driven approach. This means that one general program code, which is parametrized with process metadata, is used for data processing for a particular survey. Currently, the general program code is entirely based on SAS macros, but in the future we would like to explore how successfully statistical software R can be used for this approach. Paper describes the metadata driven principle for data validation, generic software solution and main issues connected with the use of statistical software R for this approach.
International Nuclear Information System (INIS)
Lacombe, J.P.
1985-12-01
Statistic study of Poisson non-homogeneous and spatial processes is the first part of this thesis. A Neyman-Pearson type test is defined concerning the intensity measurement of these processes. Conditions are given for which consistency of the test is assured, and others giving the asymptotic normality of the test statistics. Then some techniques of statistic processing of Poisson fields and their applications to a particle multidetector study are given. Quality tests of the device are proposed togetherwith signal extraction methods [fr
An Automated Energy Detection Algorithm Based on Morphological and Statistical Processing Techniques
2018-01-09
100 kHz, 1 MHz 100 MHz–1 GHz 1 100 kHz 3. Statistical Processing 3.1 Statistical Analysis Statistical analysis is the mathematical science...quantitative terms. In commercial prognostics and diagnostic vibrational monitoring applications , statistical techniques that are mainly used for alarm...Balakrishnan N, editors. Handbook of statistics . Amsterdam (Netherlands): Elsevier Science; 1998. p 555–602; (Order statistics and their applications
van Krimpen-Stoop, Edith M. L. A.; Meijer, Rob R.
Person-fit research in the context of paper-and-pencil tests is reviewed, and some specific problems regarding person fit in the context of computerized adaptive testing (CAT) are discussed. Some new methods are proposed to investigate person fit in a CAT environment. These statistics are based on Statistical Process Control (SPC) theory. A…
Statistical properties of several models of fractional random point processes
Bendjaballah, C.
2011-08-01
Statistical properties of several models of fractional random point processes have been analyzed from the counting and time interval statistics points of view. Based on the criterion of the reduced variance, it is seen that such processes exhibit nonclassical properties. The conditions for these processes to be treated as conditional Poisson processes are examined. Numerical simulations illustrate part of the theoretical calculations.
Multivariate Statistical Process Control Charts: An Overview
Bersimis, Sotiris; Psarakis, Stelios; Panaretos, John
2006-01-01
In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as p...
Statistical Inference at Work: Statistical Process Control as an Example
Bakker, Arthur; Kent, Phillip; Derry, Jan; Noss, Richard; Hoyles, Celia
2008-01-01
To characterise statistical inference in the workplace this paper compares a prototypical type of statistical inference at work, statistical process control (SPC), with a type of statistical inference that is better known in educational settings, hypothesis testing. Although there are some similarities between the reasoning structure involved in…
Xu, Min; Zhang, Lei; Yue, Hong-Shui; Pang, Hong-Wei; Ye, Zheng-Liang; Ding, Li
2017-10-01
To establish an on-line monitoring method for extraction process of Schisandrae Chinensis Fructus, the formula medicinal material of Yiqi Fumai lyophilized injection by combining near infrared spectroscopy with multi-variable data analysis technology. The multivariate statistical process control (MSPC) model was established based on 5 normal batches in production and 2 test batches were monitored by PC scores, DModX and Hotelling T2 control charts. The results showed that MSPC model had a good monitoring ability for the extraction process. The application of the MSPC model to actual production process could effectively achieve on-line monitoring for extraction process of Schisandrae Chinensis Fructus, and can reflect the change of material properties in the production process in real time. This established process monitoring method could provide reference for the application of process analysis technology in the process quality control of traditional Chinese medicine injections. Copyright© by the Chinese Pharmaceutical Association.
Parametric analysis of the statistical model of the stick-slip process
Lima, Roberta; Sampaio, Rubens
2017-06-01
In this paper it is performed a parametric analysis of the statistical model of the response of a dry-friction oscillator. The oscillator is a spring-mass system which moves over a base with a rough surface. Due to this roughness, the mass is subject to a dry-frictional force modeled as a Coulomb friction. The system is stochastically excited by an imposed bang-bang base motion. The base velocity is modeled by a Poisson process for which a probabilistic model is fully specified. The excitation induces in the system stochastic stick-slip oscillations. The system response is composed by a random sequence alternating stick and slip-modes. With realizations of the system, a statistical model is constructed for this sequence. In this statistical model, the variables of interest of the sequence are modeled as random variables, as for example, the number of time intervals in which stick or slip occur, the instants at which they begin, and their duration. Samples of the system response are computed by integration of the dynamic equation of the system using independent samples of the base motion. Statistics and histograms of the random variables which characterize the stick-slip process are estimated for the generated samples. The objective of the paper is to analyze how these estimated statistics and histograms vary with the system parameters, i.e., to make a parametric analysis of the statistical model of the stick-slip process.
Multivariate Statistical Process Control
DEFF Research Database (Denmark)
Kulahci, Murat
2013-01-01
As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control (SPC) and monitoring for which the aim...... is to identify “out-of-control” state of a process using control charts in order to reduce the excessive variation caused by so-called assignable causes. In practice, the most common method of monitoring multivariate data is through a statistic akin to the Hotelling’s T2. For high dimensional data with excessive...... amount of cross correlation, practitioners are often recommended to use latent structures methods such as Principal Component Analysis to summarize the data in only a few linear combinations of the original variables that capture most of the variation in the data. Applications of these control charts...
Statistical estimation of process holdup
International Nuclear Information System (INIS)
Harris, S.P.
1988-01-01
Estimates of potential process holdup and their random and systematic error variances are derived to improve the inventory difference (ID) estimate and its associated measure of uncertainty for a new process at the Savannah River Plant. Since the process is in a start-up phase, data have not yet accumulated for statistical modelling. The material produced in the facility will be a very pure, highly enriched 235U with very small isotopic variability. Therefore, data published in LANL's unclassified report on Estimation Methods for Process Holdup of a Special Nuclear Materials was used as a starting point for the modelling process. LANL's data were gathered through a series of designed measurements of special nuclear material (SNM) holdup at two of their materials-processing facilities. Also, they had taken steps to improve the quality of data through controlled, larger scale, experiments outside of LANL at highly enriched uranium processing facilities. The data they have accumulated are on an equipment component basis. Our modelling has been restricted to the wet chemistry area. We have developed predictive models for each of our process components based on the LANL data. 43 figs
Statistical Process Control for KSC Processing
Ford, Roger G.; Delgado, Hector; Tilley, Randy
1996-01-01
The 1996 Summer Faculty Fellowship Program and Kennedy Space Center (KSC) served as the basis for a research effort into statistical process control for KSC processing. The effort entailed several tasks and goals. The first was to develop a customized statistical process control (SPC) course for the Safety and Mission Assurance Trends Analysis Group. The actual teaching of this course took place over several weeks. In addition, an Internet version of the same course complete with animation and video excerpts from the course when it was taught at KSC was developed. The application of SPC to shuttle processing took up the rest of the summer research project. This effort entailed the evaluation of SPC use at KSC, both present and potential, due to the change in roles for NASA and the Single Flight Operations Contractor (SFOC). Individual consulting on SPC use was accomplished as well as an evaluation of SPC software for KSC use in the future. A final accomplishment of the orientation of the author to NASA changes, terminology, data format, and new NASA task definitions will allow future consultation when the needs arise.
Statistical process control of cocrystallization processes: A comparison between OPLS and PLS.
Silva, Ana F T; Sarraguça, Mafalda Cruz; Ribeiro, Paulo R; Santos, Adenilson O; De Beer, Thomas; Lopes, João Almeida
2017-03-30
Orthogonal partial least squares regression (OPLS) is being increasingly adopted as an alternative to partial least squares (PLS) regression due to the better generalization that can be achieved. Particularly in multivariate batch statistical process control (BSPC), the use of OPLS for estimating nominal trajectories is advantageous. In OPLS, the nominal process trajectories are expected to be captured in a single predictive principal component while uncorrelated variations are filtered out to orthogonal principal components. In theory, OPLS will yield a better estimation of the Hotelling's T 2 statistic and corresponding control limits thus lowering the number of false positives and false negatives when assessing the process disturbances. Although OPLS advantages have been demonstrated in the context of regression, its use on BSPC was seldom reported. This study proposes an OPLS-based approach for BSPC of a cocrystallization process between hydrochlorothiazide and p-aminobenzoic acid monitored on-line with near infrared spectroscopy and compares the fault detection performance with the same approach based on PLS. A series of cocrystallization batches with imposed disturbances were used to test the ability to detect abnormal situations by OPLS and PLS-based BSPC methods. Results demonstrated that OPLS was generally superior in terms of sensibility and specificity in most situations. In some abnormal batches, it was found that the imposed disturbances were only detected with OPLS. Copyright © 2017 Elsevier B.V. All rights reserved.
Statistical analysis and digital processing of the Mössbauer spectra
International Nuclear Information System (INIS)
Prochazka, Roman; Tucek, Jiri; Mashlan, Miroslav; Pechousek, Jiri; Tucek, Pavel; Marek, Jaroslav
2010-01-01
This work is focused on using the statistical methods and development of the filtration procedures for signal processing in Mössbauer spectroscopy. Statistical tools for noise filtering in the measured spectra are used in many scientific areas. The use of a pure statistical approach in accumulated Mössbauer spectra filtration is described. In Mössbauer spectroscopy, the noise can be considered as a Poisson statistical process with a Gaussian distribution for high numbers of observations. This noise is a superposition of the non-resonant photons counting with electronic noise (from γ-ray detection and discrimination units), and the velocity system quality that can be characterized by the velocity nonlinearities. The possibility of a noise-reducing process using a new design of statistical filter procedure is described. This mathematical procedure improves the signal-to-noise ratio and thus makes it easier to determine the hyperfine parameters of the given Mössbauer spectra. The filter procedure is based on a periodogram method that makes it possible to assign the statistically important components in the spectral domain. The significance level for these components is then feedback-controlled using the correlation coefficient test results. The estimation of the theoretical correlation coefficient level which corresponds to the spectrum resolution is performed. Correlation coefficient test is based on comparison of the theoretical and the experimental correlation coefficients given by the Spearman method. The correctness of this solution was analyzed by a series of statistical tests and confirmed by many spectra measured with increasing statistical quality for a given sample (absorber). The effect of this filter procedure depends on the signal-to-noise ratio and the applicability of this method has binding conditions
Statistical analysis and digital processing of the Mössbauer spectra
Prochazka, Roman; Tucek, Pavel; Tucek, Jiri; Marek, Jaroslav; Mashlan, Miroslav; Pechousek, Jiri
2010-02-01
This work is focused on using the statistical methods and development of the filtration procedures for signal processing in Mössbauer spectroscopy. Statistical tools for noise filtering in the measured spectra are used in many scientific areas. The use of a pure statistical approach in accumulated Mössbauer spectra filtration is described. In Mössbauer spectroscopy, the noise can be considered as a Poisson statistical process with a Gaussian distribution for high numbers of observations. This noise is a superposition of the non-resonant photons counting with electronic noise (from γ-ray detection and discrimination units), and the velocity system quality that can be characterized by the velocity nonlinearities. The possibility of a noise-reducing process using a new design of statistical filter procedure is described. This mathematical procedure improves the signal-to-noise ratio and thus makes it easier to determine the hyperfine parameters of the given Mössbauer spectra. The filter procedure is based on a periodogram method that makes it possible to assign the statistically important components in the spectral domain. The significance level for these components is then feedback-controlled using the correlation coefficient test results. The estimation of the theoretical correlation coefficient level which corresponds to the spectrum resolution is performed. Correlation coefficient test is based on comparison of the theoretical and the experimental correlation coefficients given by the Spearman method. The correctness of this solution was analyzed by a series of statistical tests and confirmed by many spectra measured with increasing statistical quality for a given sample (absorber). The effect of this filter procedure depends on the signal-to-noise ratio and the applicability of this method has binding conditions.
The statistical process control methods - SPC
Directory of Open Access Journals (Sweden)
Floreková Ľubica
1998-03-01
Full Text Available Methods of statistical evaluation of quality SPC (item 20 of the documentation system of quality control of ISO norm, series 900 of various processes, products and services belong amongst basic qualitative methods that enable us to analyse and compare data pertaining to various quantitative parameters. Also they enable, based on the latter, to propose suitable interventions with the aim of improving these processes, products and services. Theoretical basis and applicatibily of the principles of the: - diagnostics of a cause and effects, - Paret analysis and Lorentz curve, - number distribution and frequency curves of random variable distribution, - Shewhart regulation charts, are presented in the contribution.
Statistical data processing of mobility curves of univalent weak bases
Czech Academy of Sciences Publication Activity Database
Šlampová, Andrea; Boček, Petr
2008-01-01
Roč. 29, č. 2 (2008), s. 538-541 ISSN 0173-0835 R&D Projects: GA AV ČR IAA400310609; GA ČR GA203/05/2106 Institutional research plan: CEZ:AV0Z40310501 Keywords : mobility curve * univalent weak bases * statistical evaluation Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 3.509, year: 2008
Register-based statistics statistical methods for administrative data
Wallgren, Anders
2014-01-01
This book provides a comprehensive and up to date treatment of theory and practical implementation in Register-based statistics. It begins by defining the area, before explaining how to structure such systems, as well as detailing alternative approaches. It explains how to create statistical registers, how to implement quality assurance, and the use of IT systems for register-based statistics. Further to this, clear details are given about the practicalities of implementing such statistical methods, such as protection of privacy and the coordination and coherence of such an undertaking. Thi
Statistical Process Control in a Modern Production Environment
DEFF Research Database (Denmark)
Windfeldt, Gitte Bjørg
gathered here and standard statistical software. In Paper 2 a new method for process monitoring is introduced. The method uses a statistical model of the quality characteristic and a sliding window of observations to estimate the probability that the next item will not respect the specications......Paper 1 is aimed at practicians to help them test the assumption that the observations in a sample are independent and identically distributed. An assumption that is essential when using classical Shewhart charts. The test can easily be performed in the control chart setup using the samples....... If the estimated probability exceeds a pre-determined threshold the process will be stopped. The method is exible, allowing a complexity in modeling that remains invisible to the end user. Furthermore, the method allows to build diagnostic plots based on the parameters estimates that can provide valuable insight...
Pengendalian Kualitas Kertas Dengan Menggunakan Statistical Process Control di Paper Machine 3
Directory of Open Access Journals (Sweden)
Vera Devani
2017-01-01
Full Text Available Purpose of this research is to determine types and causes of defects commonly found in Paper Machine 3 by using statistical process control (SPC method. Statistical process control (SPC is a technique for solving problems and is used to monitor, control, analyze, manage and improve products and processes using statistical methods. Based on Pareto Diagrams, wavy defect is found as the most frequent defect, which is 81.7%. Human factor, meanwhile, is found as the main cause of defect, primarily due to lack of understanding on machinery and lack of training both leading to errors in data input.
Statistical aspects of determinantal point processes
DEFF Research Database (Denmark)
Lavancier, Frédéric; Møller, Jesper; Rubak, Ege
The statistical aspects of determinantal point processes (DPPs) seem largely unexplored. We review the appealing properties of DDPs, demonstrate that they are useful models for repulsiveness, detail a simulation procedure, and provide freely available software for simulation and statistical infer...
Statistical Process Control in the Practice of Program Evaluation.
Posavac, Emil J.
1995-01-01
A technique developed to monitor the quality of manufactured products, statistical process control (SPC), incorporates several features that may prove attractive to evaluators. This paper reviews the history of SPC, suggests how the approach can enrich program evaluation, and illustrates its use in a hospital-based example. (SLD)
Budin, Francois; Hoogstoel, Marion; Reynolds, Patrick; Grauer, Michael; O'Leary-Moore, Shonagh K; Oguz, Ipek
2013-01-01
Magnetic resonance imaging (MRI) of rodent brains enables study of the development and the integrity of the brain under certain conditions (alcohol, drugs etc.). However, these images are difficult to analyze for biomedical researchers with limited image processing experience. In this paper we present an image processing pipeline running on a Midas server, a web-based data storage system. It is composed of the following steps: rigid registration, skull-stripping, average computation, average parcellation, parcellation propagation to individual subjects, and computation of region-based statistics on each image. The pipeline is easy to configure and requires very little image processing knowledge. We present results obtained by processing a data set using this pipeline and demonstrate how this pipeline can be used to find differences between populations.
Applicability of statistical process control techniques
Schippers, W.A.J.
1998-01-01
This paper concerns the application of Process Control Techniques (PCTs) for the improvement of the technical performance of discrete production processes. Successful applications of these techniques, such as Statistical Process Control Techniques (SPC), can be found in the literature. However, some
Parametric statistical inference for discretely observed diffusion processes
DEFF Research Database (Denmark)
Pedersen, Asger Roer
Part 1: Theoretical results Part 2: Statistical applications of Gaussian diffusion processes in freshwater ecology......Part 1: Theoretical results Part 2: Statistical applications of Gaussian diffusion processes in freshwater ecology...
Statistical lamb wave localization based on extreme value theory
Harley, Joel B.
2018-04-01
Guided wave localization methods based on delay-and-sum imaging, matched field processing, and other techniques have been designed and researched to create images that locate and describe structural damage. The maximum value of these images typically represent an estimated damage location. Yet, it is often unclear if this maximum value, or any other value in the image, is a statistically significant indicator of damage. Furthermore, there are currently few, if any, approaches to assess the statistical significance of guided wave localization images. As a result, we present statistical delay-and-sum and statistical matched field processing localization methods to create statistically significant images of damage. Our framework uses constant rate of false alarm statistics and extreme value theory to detect damage with little prior information. We demonstrate our methods with in situ guided wave data from an aluminum plate to detect two 0.75 cm diameter holes. Our results show an expected improvement in statistical significance as the number of sensors increase. With seventeen sensors, both methods successfully detect damage with statistical significance.
Improving Instruction Using Statistical Process Control.
Higgins, Ronald C.; Messer, George H.
1990-01-01
Two applications of statistical process control to the process of education are described. Discussed are the use of prompt feedback to teachers and prompt feedback to students. A sample feedback form is provided. (CW)
Statistical process control using optimized neural networks: a case study.
Addeh, Jalil; Ebrahimzadeh, Ata; Azarbad, Milad; Ranaee, Vahid
2014-09-01
The most common statistical process control (SPC) tools employed for monitoring process changes are control charts. A control chart demonstrates that the process has altered by generating an out-of-control signal. This study investigates the design of an accurate system for the control chart patterns (CCPs) recognition in two aspects. First, an efficient system is introduced that includes two main modules: feature extraction module and classifier module. In the feature extraction module, a proper set of shape features and statistical feature are proposed as the efficient characteristics of the patterns. In the classifier module, several neural networks, such as multilayer perceptron, probabilistic neural network and radial basis function are investigated. Based on an experimental study, the best classifier is chosen in order to recognize the CCPs. Second, a hybrid heuristic recognition system is introduced based on cuckoo optimization algorithm (COA) algorithm to improve the generalization performance of the classifier. The simulation results show that the proposed algorithm has high recognition accuracy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Statistical aspects of determinantal point processes
DEFF Research Database (Denmark)
Lavancier, Frédéric; Møller, Jesper; Rubak, Ege Holger
The statistical aspects of determinantal point processes (DPPs) seem largely unexplored. We review the appealing properties of DDPs, demonstrate that they are useful models for repulsiveness, detail a simulation procedure, and provide freely available software for simulation and statistical...... inference. We pay special attention to stationary DPPs, where we give a simple condition ensuring their existence, construct parametric models, describe how they can be well approximated so that the likelihood can be evaluated and realizations can be simulated, and discuss how statistical inference...
The extraction and integration framework: a two-process account of statistical learning.
Thiessen, Erik D; Kronstein, Alexandra T; Hufnagle, Daniel G
2013-07-01
The term statistical learning in infancy research originally referred to sensitivity to transitional probabilities. Subsequent research has demonstrated that statistical learning contributes to infant development in a wide array of domains. The range of statistical learning phenomena necessitates a broader view of the processes underlying statistical learning. Learners are sensitive to a much wider range of statistical information than the conditional relations indexed by transitional probabilities, including distributional and cue-based statistics. We propose a novel framework that unifies learning about all of these kinds of statistical structure. From our perspective, learning about conditional relations outputs discrete representations (such as words). Integration across these discrete representations yields sensitivity to cues and distributional information. To achieve sensitivity to all of these kinds of statistical structure, our framework combines processes that extract segments of the input with processes that compare across these extracted items. In this framework, the items extracted from the input serve as exemplars in long-term memory. The similarity structure of those exemplars in long-term memory leads to the discovery of cues and categorical structure, which guides subsequent extraction. The extraction and integration framework provides a way to explain sensitivity to both conditional statistical structure (such as transitional probabilities) and distributional statistical structure (such as item frequency and variability), and also a framework for thinking about how these different aspects of statistical learning influence each other. 2013 APA, all rights reserved
PROCESS VARIABILITY REDUCTION THROUGH STATISTICAL PROCESS CONTROL FOR QUALITY IMPROVEMENT
Directory of Open Access Journals (Sweden)
B.P. Mahesh
2010-09-01
Full Text Available Quality has become one of the most important customer decision factors in the selection among the competing product and services. Consequently, understanding and improving quality is a key factor leading to business success, growth and an enhanced competitive position. Hence quality improvement program should be an integral part of the overall business strategy. According to TQM, the effective way to improve the Quality of the product or service is to improve the process used to build the product. Hence, TQM focuses on process, rather than results as the results are driven by the processes. Many techniques are available for quality improvement. Statistical Process Control (SPC is one such TQM technique which is widely accepted for analyzing quality problems and improving the performance of the production process. This article illustrates the step by step procedure adopted at a soap manufacturing company to improve the Quality by reducing process variability using Statistical Process Control.
Statistical data processing with automatic system for environmental radiation monitoring
International Nuclear Information System (INIS)
Zarkh, V.G.; Ostroglyadov, S.V.
1986-01-01
Practice of statistical data processing for radiation monitoring is exemplified, and some results obtained are presented. Experience in practical application of mathematical statistics methods for radiation monitoring data processing allowed to develop a concrete algorithm of statistical processing realized in M-6000 minicomputer. The suggested algorithm by its content is divided into 3 parts: parametrical data processing and hypotheses test, pair and multiple correlation analysis. Statistical processing programms are in a dialogue operation. The above algorithm was used to process observed data over radioactive waste disposal control region. Results of surface waters monitoring processing are presented
Using Statistical Process Control to Enhance Student Progression
Hanna, Mark D.; Raichura, Nilesh; Bernardes, Ednilson
2012-01-01
Public interest in educational outcomes has markedly increased in the most recent decade; however, quality management and statistical process control have not deeply penetrated the management of academic institutions. This paper presents results of an attempt to use Statistical Process Control (SPC) to identify a key impediment to continuous…
Advanced statistics to improve the physical interpretation of atomization processes
International Nuclear Information System (INIS)
Panão, Miguel R.O.; Radu, Lucian
2013-01-01
Highlights: ► Finite pdf mixtures improves physical interpretation of sprays. ► Bayesian approach using MCMC algorithm is used to find the best finite mixture. ► Statistical method identifies multiple droplet clusters in a spray. ► Multiple drop clusters eventually associated with multiple atomization mechanisms. ► Spray described by drop size distribution and not only its moments. -- Abstract: This paper reports an analysis of the physics of atomization processes using advanced statistical tools. Namely, finite mixtures of probability density functions, which best fitting is found using a Bayesian approach based on a Markov chain Monte Carlo (MCMC) algorithm. This approach takes into account eventual multimodality and heterogeneities in drop size distributions. Therefore, it provides information about the complete probability density function of multimodal drop size distributions and allows the identification of subgroups in the heterogeneous data. This allows improving the physical interpretation of atomization processes. Moreover, it also overcomes the limitations induced by analyzing the spray droplets characteristics through moments alone, particularly, the hindering of different natures of droplet formation. Finally, the method is applied to physically interpret a case-study based on multijet atomization processes
Statistical thermodynamics of nonequilibrium processes
Keizer, Joel
1987-01-01
The structure of the theory ofthermodynamics has changed enormously since its inception in the middle of the nineteenth century. Shortly after Thomson and Clausius enunciated their versions of the Second Law, Clausius, Maxwell, and Boltzmann began actively pursuing the molecular basis of thermo dynamics, work that culminated in the Boltzmann equation and the theory of transport processes in dilute gases. Much later, Onsager undertook the elucidation of the symmetry oftransport coefficients and, thereby, established himself as the father of the theory of nonequilibrium thermodynamics. Com bining the statistical ideas of Gibbs and Langevin with the phenomenological transport equations, Onsager and others went on to develop a consistent statistical theory of irreversible processes. The power of that theory is in its ability to relate measurable quantities, such as transport coefficients and thermodynamic derivatives, to the results of experimental measurements. As powerful as that theory is, it is linear and...
Fundamentals of statistical signal processing
Kay, Steven M
1993-01-01
A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms. Covers important approaches to obtaining an optimal estimator and analyzing its performance; and includes numerous examples as well as applications to real- world problems. MARKETS: For practicing engineers and scientists who design and analyze signal processing systems, i.e., to extract information from noisy signals — radar engineer, sonar engineer, geophysicist, oceanographer, biomedical engineer, communications engineer, economist, statistician, physicist, etc.
An integrated model of statistical process control and maintenance based on the delayed monitoring
International Nuclear Information System (INIS)
Yin, Hui; Zhang, Guojun; Zhu, Haiping; Deng, Yuhao; He, Fei
2015-01-01
This paper develops an integrated model of statistical process control and maintenance decision. The proposal of delayed monitoring policy postpones the sampling process till a scheduled time and contributes to ten-scenarios of the production process, where equipment failure may occur besides quality shift. The equipment failure and the control chart alert trigger the corrective maintenance and the predictive maintenance, respectively. The occurrence probability, the cycle time and the cycle cost of each scenario are obtained by integral calculation; therefore, a mathematical model is established to minimize the expected cost by using the genetic algorithm. A Monte Carlo simulation experiment is conducted and compared with the integral calculation in order to ensure the analysis of the ten-scenario model. Another ordinary integrated model without delayed monitoring is also established as comparison. The results of a numerical example indicate satisfactory economic performance of the proposed model. Finally, a sensitivity analysis is performed to investigate the effect of model parameters. - Highlights: • We develop an integrated model of statistical process control and maintenance. • We propose delayed monitoring policy and derive an economic model with 10 scenarios. • We consider two deterioration mechanisms, quality shift and equipment failure. • The delayed monitoring policy will help reduce the expected cost
Feature-Based Statistical Analysis of Combustion Simulation Data
Energy Technology Data Exchange (ETDEWEB)
Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T
2011-11-18
We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion
Statistical test data selection for reliability evalution of process computer software
International Nuclear Information System (INIS)
Volkmann, K.P.; Hoermann, H.; Ehrenberger, W.
1976-01-01
The paper presents a concept for converting knowledge about the characteristics of process states into practicable procedures for the statistical selection of test cases in testing process computer software. Process states are defined as vectors whose components consist of values of input variables lying in discrete positions or within given limits. Two approaches for test data selection, based on knowledge about cases of demand, are outlined referring to a purely probabilistic method and to the mathematics of stratified sampling. (orig.) [de
Management of Uncertainty by Statistical Process Control and a Genetic Tuned Fuzzy System
Directory of Open Access Journals (Sweden)
Stephan Birle
2016-01-01
Full Text Available In food industry, bioprocesses like fermentation often are a crucial part of the manufacturing process and decisive for the final product quality. In general, they are characterized by highly nonlinear dynamics and uncertainties that make it difficult to control these processes by the use of traditional control techniques. In this context, fuzzy logic controllers offer quite a straightforward way to control processes that are affected by nonlinear behavior and uncertain process knowledge. However, in order to maintain process safety and product quality it is necessary to specify the controller performance and to tune the controller parameters. In this work, an approach is presented to establish an intelligent control system for oxidoreductive yeast propagation as a representative process biased by the aforementioned uncertainties. The presented approach is based on statistical process control and fuzzy logic feedback control. As the cognitive uncertainty among different experts about the limits that define the control performance as still acceptable may differ a lot, a data-driven design method is performed. Based upon a historic data pool statistical process corridors are derived for the controller inputs control error and change in control error. This approach follows the hypothesis that if the control performance criteria stay within predefined statistical boundaries, the final process state meets the required quality definition. In order to keep the process on its optimal growth trajectory (model based reference trajectory a fuzzy logic controller is used that alternates the process temperature. Additionally, in order to stay within the process corridors, a genetic algorithm was applied to tune the input and output fuzzy sets of a preliminarily parameterized fuzzy controller. The presented experimental results show that the genetic tuned fuzzy controller is able to keep the process within its allowed limits. The average absolute error to the
77 FR 46096 - Statistical Process Controls for Blood Establishments; Public Workshop
2012-08-02
...] Statistical Process Controls for Blood Establishments; Public Workshop AGENCY: Food and Drug Administration... workshop entitled: ``Statistical Process Controls for Blood Establishments.'' The purpose of this public workshop is to discuss the implementation of statistical process controls to validate and monitor...
Miller, John
1994-01-01
Presents an approach to document numbering, document titling, and process measurement which, when used with fundamental techniques of statistical process control, reveals meaningful process-element variation as well as nominal productivity models. (SR)
An Efficient Graph-based Method for Long-term Land-use Change Statistics
Directory of Open Access Journals (Sweden)
Yipeng Zhang
2015-12-01
Full Text Available Statistical analysis of land-use change plays an important role in sustainable land management and has received increasing attention from scholars and administrative departments. However, the statistical process involving spatial overlay analysis remains difficult and needs improvement to deal with mass land-use data. In this paper, we introduce a spatio-temporal flow network model to reveal the hidden relational information among spatio-temporal entities. Based on graph theory, the constant condition of saturated multi-commodity flow is derived. A new method based on a network partition technique of spatio-temporal flow network are proposed to optimize the transition statistical process. The effectiveness and efficiency of the proposed method is verified through experiments using land-use data in Hunan from 2009 to 2014. In the comparison among three different land-use change statistical methods, the proposed method exhibits remarkable superiority in efficiency.
Statistical process control in nursing research.
Polit, Denise F; Chaboyer, Wendy
2012-02-01
In intervention studies in which randomization to groups is not possible, researchers typically use quasi-experimental designs. Time series designs are strong quasi-experimental designs but are seldom used, perhaps because of technical and analytic hurdles. Statistical process control (SPC) is an alternative analytic approach to testing hypotheses about intervention effects using data collected over time. SPC, like traditional statistical methods, is a tool for understanding variation and involves the construction of control charts that distinguish between normal, random fluctuations (common cause variation), and statistically significant special cause variation that can result from an innovation. The purpose of this article is to provide an overview of SPC and to illustrate its use in a study of a nursing practice improvement intervention. Copyright © 2011 Wiley Periodicals, Inc.
Nonparametric predictive inference in statistical process control
Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.
2000-01-01
New methods for statistical process control are presented, where the inferences have a nonparametric predictive nature. We consider several problems in process control in terms of uncertainties about future observable random quantities, and we develop inferences for these random quantities hased on
Hiemstra, Djoerd; de Jong, Franciska M.G.
2001-01-01
Traditionally, natural language processing techniques for information retrieval have always been studied outside the framework of formal models of information retrieval. In this article, we introduce a new formal model of information retrieval based on the application of statistical language models.
Statistic techniques of process control for MTR type
International Nuclear Information System (INIS)
Oliveira, F.S.; Ferrufino, F.B.J.; Santos, G.R.T.; Lima, R.M.
2002-01-01
This work aims at introducing some improvements on the fabrication of MTR type fuel plates, applying statistic techniques of process control. The work was divided into four single steps and their data were analyzed for: fabrication of U 3 O 8 fuel plates; fabrication of U 3 Si 2 fuel plates; rolling of small lots of fuel plates; applying statistic tools and standard specifications to perform a comparative study of these processes. (author)
Applying Statistical Process Control to Clinical Data: An Illustration.
Pfadt, Al; And Others
1992-01-01
Principles of statistical process control are applied to a clinical setting through the use of control charts to detect changes, as part of treatment planning and clinical decision-making processes. The logic of control chart analysis is derived from principles of statistical inference. Sample charts offer examples of evaluating baselines and…
Statistical process control for serially correlated data
Wieringa, Jakob Edo
1999-01-01
Statistical Process Control (SPC) aims at quality improvement through reduction of variation. The best known tool of SPC is the control chart. Over the years, the control chart has proved to be a successful practical technique for monitoring process measurements. However, its usefulness in practice
Monitoring a PVC batch process with multivariate statistical process control charts
Tates, A. A.; Louwerse, D. J.; Smilde, A. K.; Koot, G. L. M.; Berndt, H.
1999-01-01
Multivariate statistical process control charts (MSPC charts) are developed for the industrial batch production process of poly(vinyl chloride) (PVC). With these MSPC charts different types of abnormal batch behavior were detected on-line. With batch contribution plots, the probable causes of these
Chopra, Vikram; Bairagi, Mukesh; Trivedi, P; Nagar, Mona
2012-01-01
Statistical process control is the application of statistical methods to the measurement and analysis of variation process. Various regulatory authorities such as Validation Guidance for Industry (2011), International Conference on Harmonisation ICH Q10 (2009), the Health Canada guidelines (2009), Health Science Authority, Singapore: Guidance for Product Quality Review (2008), and International Organization for Standardization ISO-9000:2005 provide regulatory support for the application of statistical process control for better process control and understanding. In this study risk assessments, normal probability distributions, control charts, and capability charts are employed for selection of critical quality attributes, determination of normal probability distribution, statistical stability, and capability of production processes, respectively. The objective of this study is to determine tablet production process quality in the form of sigma process capability. By interpreting data and graph trends, forecasting of critical quality attributes, sigma process capability, and stability of process were studied. The overall study contributes to an assessment of process at the sigma level with respect to out-of-specification attributes produced. Finally, the study will point to an area where the application of quality improvement and quality risk assessment principles for achievement of six sigma-capable processes is possible. Statistical process control is the most advantageous tool for determination of the quality of any production process. This tool is new for the pharmaceutical tablet production process. In the case of pharmaceutical tablet production processes, the quality control parameters act as quality assessment parameters. Application of risk assessment provides selection of critical quality attributes among quality control parameters. Sequential application of normality distributions, control charts, and capability analyses provides a valid statistical
On statistical analysis of compound point process
Czech Academy of Sciences Publication Activity Database
Volf, Petr
2006-01-01
Roč. 35, 2-3 (2006), s. 389-396 ISSN 1026-597X R&D Projects: GA ČR(CZ) GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : counting process * compound process * hazard function * Cox -model Subject RIV: BB - Applied Statistics, Operational Research
Analysis of Variance in Statistical Image Processing
Kurz, Ludwik; Hafed Benteftifa, M.
1997-04-01
A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.
Silva, A F; Sarraguça, M C; Fonteyne, M; Vercruysse, J; De Leersnyder, F; Vanhoorne, V; Bostijn, N; Verstraeten, M; Vervaet, C; Remon, J P; De Beer, T; Lopes, J A
2017-08-07
A multivariate statistical process control (MSPC) strategy was developed for the monitoring of the ConsiGma™-25 continuous tablet manufacturing line. Thirty-five logged variables encompassing three major units, being a twin screw high shear granulator, a fluid bed dryer and a product control unit, were used to monitor the process. The MSPC strategy was based on principal component analysis of data acquired under normal operating conditions using a series of four process runs. Runs with imposed disturbances in the dryer air flow and temperature, in the granulator barrel temperature, speed and liquid mass flow and in the powder dosing unit mass flow were utilized to evaluate the model's monitoring performance. The impact of the imposed deviations to the process continuity was also evaluated using Hotelling's T 2 and Q residuals statistics control charts. The influence of the individual process variables was assessed by analyzing contribution plots at specific time points. Results show that the imposed disturbances were all detected in both control charts. Overall, the MSPC strategy was successfully developed and applied. Additionally, deviations not associated with the imposed changes were detected, mainly in the granulator barrel temperature control. Copyright © 2017 Elsevier B.V. All rights reserved.
Nonparametric predictive inference in statistical process control
Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.
2004-01-01
Statistical process control (SPC) is used to decide when to stop a process as confidence in the quality of the next item(s) is low. Information to specify a parametric model is not always available, and as SPC is of a predictive nature, we present a control chart developed using nonparametric
Strauch, R. L.; Istanbulluoglu, E.
2017-12-01
We develop a landslide hazard modeling approach that integrates a data-driven statistical model and a probabilistic process-based shallow landslide model for mapping probability of landslide initiation, transport, and deposition at regional scales. The empirical model integrates the influence of seven site attribute (SA) classes: elevation, slope, curvature, aspect, land use-land cover, lithology, and topographic wetness index, on over 1,600 observed landslides using a frequency ratio (FR) approach. A susceptibility index is calculated by adding FRs for each SA on a grid-cell basis. Using landslide observations we relate susceptibility index to an empirically-derived probability of landslide impact. This probability is combined with results from a physically-based model to produce an integrated probabilistic map. Slope was key in landslide initiation while deposition was linked to lithology and elevation. Vegetation transition from forest to alpine vegetation and barren land cover with lower root cohesion leads to higher frequency of initiation. Aspect effects are likely linked to differences in root cohesion and moisture controlled by solar insulation and snow. We demonstrate the model in the North Cascades of Washington, USA and identify locations of high and low probability of landslide impacts that can be used by land managers in their design, planning, and maintenance.
Statistical trajectory of an approximate EM algorithm for probabilistic image processing
International Nuclear Information System (INIS)
Tanaka, Kazuyuki; Titterington, D M
2007-01-01
We calculate analytically a statistical average of trajectories of an approximate expectation-maximization (EM) algorithm with generalized belief propagation (GBP) and a Gaussian graphical model for the estimation of hyperparameters from observable data in probabilistic image processing. A statistical average with respect to observed data corresponds to a configuration average for the random-field Ising model in spin glass theory. In the present paper, hyperparameters which correspond to interactions and external fields of spin systems are estimated by an approximate EM algorithm. A practical algorithm is described for gray-level image restoration based on a Gaussian graphical model and GBP. The GBP approach corresponds to the cluster variation method in statistical mechanics. Our main result in the present paper is to obtain the statistical average of the trajectory in the approximate EM algorithm by using loopy belief propagation and GBP with respect to degraded images generated from a probability density function with true values of hyperparameters. The statistical average of the trajectory can be expressed in terms of recursion formulas derived from some analytical calculations
Statistical process control for residential treated wood
Patricia K. Lebow; Timothy M. Young; Stan Lebow
2017-01-01
This paper is the first stage of a study that attempts to improve the process of manufacturing treated lumber through the use of statistical process control (SPC). Analysis of industrial and auditing agency data sets revealed there are differences between the industry and agency probability density functions (pdf) for normalized retention data. Resampling of batches of...
Probability, Statistics, and Stochastic Processes
Olofsson, Peter
2012-01-01
This book provides a unique and balanced approach to probability, statistics, and stochastic processes. Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area. The Second Edition features new coverage of analysis of variance (ANOVA), consistency and efficiency of estimators, asymptotic theory for maximum likelihood estimators, empirical distribution function and the Kolmogorov-Smirnov test, general linear models, multiple comparisons, Markov chain Monte Carlo (MCMC), Brownian motion, martingales, and
Vali Ahmadi, Mohammad; Doostparast, Mahdi; Ahmadi, Jafar
2015-04-01
In manufacturing industries, the lifetime of an item is usually characterised by a random variable X and considered to be satisfactory if X exceeds a given lower lifetime limit L. The probability of a satisfactory item is then ηL := P(X ≥ L), called conforming rate. In industrial companies, however, the lifetime performance index, proposed by Montgomery and denoted by CL, is widely used as a process capability index instead of the conforming rate. Assuming a parametric model for the random variable X, we show that there is a connection between the conforming rate and the lifetime performance index. Consequently, the statistical inferences about ηL and CL are equivalent. Hence, we restrict ourselves to statistical inference for CL based on generalised order statistics, which contains several ordered data models such as usual order statistics, progressively Type-II censored data and records. Various point and interval estimators for the parameter CL are obtained and optimal critical regions for the hypothesis testing problems concerning CL are proposed. Finally, two real data-sets on the lifetimes of insulating fluid and ball bearings, due to Nelson (1982) and Caroni (2002), respectively, and a simulated sample are analysed.
Memory-type control charts in statistical process control
Abbas, N.
2012-01-01
Control chart is the most important statistical tool to manage the business processes. It is a graph of measurements on a quality characteristic of the process on the vertical axis plotted against time on the horizontal axis. The graph is completed with control limits that cause variation mark. Once
Statistical image processing and multidimensional modeling
Fieguth, Paul
2010-01-01
Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. When these images are acquired from a microscope, telescope, satellite, or medical imaging device, there is a statistical image processing task: the inference of something - an artery, a road, a DNA marker, an oil spill - from imagery, possibly noisy, blurry, or incomplete. A great many textbooks have been written on image processing. However this book does not so much focus on images, per se, but rather on spatial data sets, with one or more measurements taken over
Rweb:Web-based Statistical Analysis
Directory of Open Access Journals (Sweden)
Jeff Banfield
1999-03-01
Full Text Available Rweb is a freely accessible statistical analysis environment that is delivered through the World Wide Web (WWW. It is based on R, a well known statistical analysis package. The only requirement to run the basic Rweb interface is a WWW browser that supports forms. If you want graphical output you must, of course, have a browser that supports graphics. The interface provides access to WWW accessible data sets, so you may run Rweb on your own data. Rweb can provide a four window statistical computing environment (code input, text output, graphical output, and error information through browsers that support Javascript. There is also a set of point and click modules under development for use in introductory statistics courses.
Statistical processing of technological and radiochemical data
International Nuclear Information System (INIS)
Lahodova, Zdena; Vonkova, Kateřina
2011-01-01
The project described in this article had two goals. The main goal was to compare technological and radiochemical data from two units of nuclear power plant. The other goal was to check the collection, organization and interpretation of routinely measured data. Monitoring of analytical and radiochemical data is a very valuable source of knowledge for some processes in the primary circuit. Exploratory analysis of one-dimensional data was performed to estimate location and variability and to find extreme values, data trends, distribution, autocorrelation etc. This process allowed for the cleaning and completion of raw data. Then multiple analyses such as multiple comparisons, multiple correlation, variance analysis, and so on were performed. Measured data was organized into a data matrix. The results and graphs such as Box plots, Mahalanobis distance, Biplot, Correlation, and Trend graphs are presented in this article as statistical analysis tools. Tables of data were replaced with graphs because graphs condense large amounts of information into easy-to-understand formats. The significant conclusion of this work is that the collection and comprehension of data is a very substantial part of statistical processing. With well-prepared and well-understood data, its accurate evaluation is possible. Cooperation between the technicians who collect data and the statistician who processes it is also very important. (author)
Reconstructing Macroeconomics Based on Statistical Physics
Aoki, Masanao; Yoshikawa, Hiroshi
We believe that time has come to integrate the new approach based on statistical physics or econophysics into macroeconomics. Toward this goal, there must be more dialogues between physicists and economists. In this paper, we argue that there is no reason why the methods of statistical physics so successful in many fields of natural sciences cannot be usefully applied to macroeconomics that is meant to analyze the macroeconomy comprising a large number of economic agents. It is, in fact, weird to regard the macroeconomy as a homothetic enlargement of the representative micro agent. We trust the bright future of the new approach to macroeconomies based on statistical physics.
Manufacturing Squares: An Integrative Statistical Process Control Exercise
Coy, Steven P.
2016-01-01
In the exercise, students in a junior-level operations management class are asked to manufacture a simple product. Given product specifications, they must design a production process, create roles and design jobs for each team member, and develop a statistical process control plan that efficiently and effectively controls quality during…
Statistical convergence of a non-positive approximation process
International Nuclear Information System (INIS)
Agratini, Octavian
2011-01-01
Highlights: → A general class of approximation processes is introduced. → The A-statistical convergence is studied. → Applications in quantum calculus are delivered. - Abstract: Starting from a general sequence of linear and positive operators of discrete type, we associate its r-th order generalization. This construction involves high order derivatives of a signal and it looses the positivity property. Considering that the initial approximation process is A-statistically uniform convergent, we prove that the property is inherited by the new sequence. Also, our result includes information about the uniform convergence. Two applications in q-Calculus are presented. We study q-analogues both of Meyer-Koenig and Zeller operators and Stancu operators.
Statistical inference based on divergence measures
Pardo, Leandro
2005-01-01
The idea of using functionals of Information Theory, such as entropies or divergences, in statistical inference is not new. However, in spite of the fact that divergence statistics have become a very good alternative to the classical likelihood ratio test and the Pearson-type statistic in discrete models, many statisticians remain unaware of this powerful approach.Statistical Inference Based on Divergence Measures explores classical problems of statistical inference, such as estimation and hypothesis testing, on the basis of measures of entropy and divergence. The first two chapters form an overview, from a statistical perspective, of the most important measures of entropy and divergence and study their properties. The author then examines the statistical analysis of discrete multivariate data with emphasis is on problems in contingency tables and loglinear models using phi-divergence test statistics as well as minimum phi-divergence estimators. The final chapter looks at testing in general populations, prese...
Discussion of "Modern statistics for spatial point processes"
DEFF Research Database (Denmark)
Jensen, Eva Bjørn Vedel; Prokesová, Michaela; Hellmund, Gunnar
2007-01-01
ABSTRACT. The paper ‘Modern statistics for spatial point processes’ by Jesper Møller and Rasmus P. Waagepetersen is based on a special invited lecture given by the authors at the 21st Nordic Conference on Mathematical Statistics, held at Rebild, Denmark, in June 2006. At the conference, Antti...
Applying Statistical Process Quality Control Methodology to Educational Settings.
Blumberg, Carol Joyce
A subset of Statistical Process Control (SPC) methodology known as Control Charting is introduced. SPC methodology is a collection of graphical and inferential statistics techniques used to study the progress of phenomena over time. The types of control charts covered are the null X (mean), R (Range), X (individual observations), MR (moving…
Using Paper Helicopters to Teach Statistical Process Control
Johnson, Danny J.
2011-01-01
This hands-on project uses a paper helicopter to teach students how to distinguish between common and special causes of variability when developing and using statistical process control charts. It allows the student to experience a process that is out-of-control due to imprecise or incomplete product design specifications and to discover how the…
Bellec, J; Delaby, N; Jouyaux, F; Perdrieux, M; Bouvier, J; Sorel, S; Henry, O; Lafond, C
2017-07-01
Robotic radiosurgery requires plan delivery quality assurance (DQA) but there has never been a published comprehensive analysis of a patient-specific DQA process in a clinic. We proposed to evaluate 350 consecutive film-based patient-specific DQAs using statistical process control. We evaluated the performance of the process to propose achievable tolerance criteria for DQA validation and we sought to identify suboptimal DQA using control charts. DQAs were performed on a CyberKnife-M6 using Gafchromic-EBT3 films. The signal-to-dose conversion was performed using a multichannel-correction and a scanning protocol that combined measurement and calibration in a single scan. The DQA analysis comprised a gamma-index analysis at 3%/1.5mm and a separate evaluation of spatial and dosimetric accuracy of the plan delivery. Each parameter was plotted on a control chart and control limits were calculated. A capability index (Cpm) was calculated to evaluate the ability of the process to produce results within specifications. The analysis of capability showed that a gamma pass rate of 85% at 3%/1.5mm was highly achievable as acceptance criteria for DQA validation using a film-based protocol (Cpm>1.33). 3.4% of DQA were outside a control limit of 88% for gamma pass-rate. The analysis of the out-of-control DQA helped identify a dosimetric error in our institute for a specific treatment type. We have defined initial tolerance criteria for DQA validations. We have shown that the implementation of a film-based patient-specific DQA protocol with the use of control charts is an effective method to improve patient treatment safety on CyberKnife. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
On-line statistical processing of radiation detector pulse trains with time-varying count rates
International Nuclear Information System (INIS)
Apostolopoulos, G.
2008-01-01
Statistical analysis is of primary importance for the correct interpretation of nuclear measurements, due to the inherent random nature of radioactive decay processes. This paper discusses the application of statistical signal processing techniques to the random pulse trains generated by radiation detectors. The aims of the presented algorithms are: (i) continuous, on-line estimation of the underlying time-varying count rate θ(t) and its first-order derivative dθ/dt; (ii) detection of abrupt changes in both of these quantities and estimation of their new value after the change point. Maximum-likelihood techniques, based on the Poisson probability distribution, are employed for the on-line estimation of θ and dθ/dt. Detection of abrupt changes is achieved on the basis of the generalized likelihood ratio statistical test. The properties of the proposed algorithms are evaluated by extensive simulations and possible applications for on-line radiation monitoring are discussed
Statistical process control methods allow the analysis and improvement of anesthesia care.
Fasting, Sigurd; Gisvold, Sven E
2003-10-01
Quality aspects of the anesthetic process are reflected in the rate of intraoperative adverse events. The purpose of this report is to illustrate how the quality of the anesthesia process can be analyzed using statistical process control methods, and exemplify how this analysis can be used for quality improvement. We prospectively recorded anesthesia-related data from all anesthetics for five years. The data included intraoperative adverse events, which were graded into four levels, according to severity. We selected four adverse events, representing important quality and safety aspects, for statistical process control analysis. These were: inadequate regional anesthesia, difficult emergence from general anesthesia, intubation difficulties and drug errors. We analyzed the underlying process using 'p-charts' for statistical process control. In 65,170 anesthetics we recorded adverse events in 18.3%; mostly of lesser severity. Control charts were used to define statistically the predictable normal variation in problem rate, and then used as a basis for analysis of the selected problems with the following results: Inadequate plexus anesthesia: stable process, but unacceptably high failure rate; Difficult emergence: unstable process, because of quality improvement efforts; Intubation difficulties: stable process, rate acceptable; Medication errors: methodology not suited because of low rate of errors. By applying statistical process control methods to the analysis of adverse events, we have exemplified how this allows us to determine if a process is stable, whether an intervention is required, and if quality improvement efforts have the desired effect.
Comparison of Statistical Post-Processing Methods for Probabilistic Wind Speed Forecasting
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.
Analyzing a Mature Software Inspection Process Using Statistical Process Control (SPC)
Barnard, Julie; Carleton, Anita; Stamper, Darrell E. (Technical Monitor)
1999-01-01
This paper presents a cooperative effort where the Software Engineering Institute and the Space Shuttle Onboard Software Project could experiment applying Statistical Process Control (SPC) analysis to inspection activities. The topics include: 1) SPC Collaboration Overview; 2) SPC Collaboration Approach and Results; and 3) Lessons Learned.
Some properties of point processes in statistical optics
International Nuclear Information System (INIS)
Picinbono, B.; Bendjaballah, C.
2010-01-01
The analysis of the statistical properties of the point process (PP) of photon detection times can be used to determine whether or not an optical field is classical, in the sense that its statistical description does not require the methods of quantum optics. This determination is, however, more difficult than ordinarily admitted and the first aim of this paper is to illustrate this point by using some results of the PP theory. For example, it is well known that the analysis of the photodetection of classical fields exhibits the so-called bunching effect. But this property alone cannot be used to decide the nature of a given optical field. Indeed, we have presented examples of point processes for which a bunching effect appears and yet they cannot be obtained from a classical field. These examples are illustrated by computer simulations. Similarly, it is often admitted that for fields with very low light intensity the bunching or antibunching can be described by using the statistical properties of the distance between successive events of the point process, which simplifies the experimental procedure. We have shown that, while this property is valid for classical PPs, it has no reason to be true for nonclassical PPs, and we have presented some examples of this situation also illustrated by computer simulations.
Statistical Model-Based Face Pose Estimation
Institute of Scientific and Technical Information of China (English)
GE Xinliang; YANG Jie; LI Feng; WANG Huahua
2007-01-01
A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.
Applied Behavior Analysis and Statistical Process Control?
Hopkins, B. L.
1995-01-01
Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…
Statistical process control for alpha spectroscopy
Energy Technology Data Exchange (ETDEWEB)
Richardson, W; Majoras, R E [Oxford Instruments, Inc. P.O. Box 2560, Oak Ridge TN 37830 (United States); Joo, I O; Seymour, R S [Accu-Labs Research, Inc. 4663 Table Mountain Drive, Golden CO 80403 (United States)
1995-10-01
Statistical process control(SPC) allows for the identification of problems in alpha spectroscopy processes before they occur, unlike standard laboratory Q C which only identifies problems after a process fails. SPC tools that are directly applicable to alpha spectroscopy include individual X-charts and X-bar charts, process capability plots, and scatter plots. Most scientists are familiar with the concepts the and methods employed by SPC. These tools allow analysis of process bias, precision, accuracy and reproducibility as well as process capability. Parameters affecting instrument performance are monitored and analyzed using SPC methods. These instrument parameters can also be compared to sampling, preparation, measurement, and analysis Q C parameters permitting the evaluation of cause effect relationships. Three examples of SPC, as applied to alpha spectroscopy , are presented. The first example investigates background contamination using averaging to show trends quickly. A second example demonstrates how SPC can identify sample processing problems, analyzing both how and why this problem occurred. A third example illustrates how SPC can predict when an alpha spectroscopy process is going to fail. This allows for an orderly and timely shutdown of the process to perform preventative maintenance, avoiding the need to repeat costly sample analyses. 7 figs., 2 tabs.
Statistical process control for alpha spectroscopy
International Nuclear Information System (INIS)
Richardson, W.; Majoras, R.E.; Joo, I.O.; Seymour, R.S.
1995-01-01
Statistical process control(SPC) allows for the identification of problems in alpha spectroscopy processes before they occur, unlike standard laboratory Q C which only identifies problems after a process fails. SPC tools that are directly applicable to alpha spectroscopy include individual X-charts and X-bar charts, process capability plots, and scatter plots. Most scientists are familiar with the concepts the and methods employed by SPC. These tools allow analysis of process bias, precision, accuracy and reproducibility as well as process capability. Parameters affecting instrument performance are monitored and analyzed using SPC methods. These instrument parameters can also be compared to sampling, preparation, measurement, and analysis Q C parameters permitting the evaluation of cause effect relationships. Three examples of SPC, as applied to alpha spectroscopy , are presented. The first example investigates background contamination using averaging to show trends quickly. A second example demonstrates how SPC can identify sample processing problems, analyzing both how and why this problem occurred. A third example illustrates how SPC can predict when an alpha spectroscopy process is going to fail. This allows for an orderly and timely shutdown of the process to perform preventative maintenance, avoiding the need to repeat costly sample analyses. 7 figs., 2 tabs
Hall, Michelle G; Mattingley, Jason B; Dux, Paul E
2015-08-01
The brain exploits redundancies in the environment to efficiently represent the complexity of the visual world. One example of this is ensemble processing, which provides a statistical summary of elements within a set (e.g., mean size). Another is statistical learning, which involves the encoding of stable spatial or temporal relationships between objects. It has been suggested that ensemble processing over arrays of oriented lines disrupts statistical learning of structure within the arrays (Zhao, Ngo, McKendrick, & Turk-Browne, 2011). Here we asked whether ensemble processing and statistical learning are mutually incompatible, or whether this disruption might occur because ensemble processing encourages participants to process the stimulus arrays in a way that impedes statistical learning. In Experiment 1, we replicated Zhao and colleagues' finding that ensemble processing disrupts statistical learning. In Experiments 2 and 3, we found that statistical learning was unimpaired by ensemble processing when task demands necessitated (a) focal attention to individual items within the stimulus arrays and (b) the retention of individual items in working memory. Together, these results are consistent with an account suggesting that ensemble processing and statistical learning can operate over the same stimuli given appropriate stimulus processing demands during exposure to regularities. (c) 2015 APA, all rights reserved).
Limiting processes in non-equilibrium classical statistical mechanics
International Nuclear Information System (INIS)
Jancel, R.
1983-01-01
After a recall of the basic principles of the statistical mechanics, the results of ergodic theory, the transient at the thermodynamic limit and his link with the transport theory near the equilibrium are analyzed. The fundamental problems put by the description of non-equilibrium macroscopic systems are investigated and the kinetic methods are stated. The problems of the non-equilibrium statistical mechanics are analyzed: irreversibility and coarse-graining, macroscopic variables and kinetic description, autonomous reduced descriptions, limit processes, BBGKY hierarchy, limit theorems [fr
Thiessen, Erik D
2017-01-05
Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik
International Nuclear Information System (INIS)
Ono, A.; Horiuchi, H.
1996-01-01
Statistical properties of antisymmetrized molecular dynamics (AMD) are classical in the case of nucleon-emission processes, while they are quantum mechanical for the processes without nucleon emission. In order to understand this situation, we first clarify that there coexist mutually opposite two statistics in the AMD framework: One is the classical statistics of the motion of wave packet centroids and the other is the quantum statistics of the motion of wave packets which is described by the AMD wave function. We prove the classical statistics of wave packet centroids by using the framework of the microcanonical ensemble of the nuclear system with a realistic effective two-nucleon interaction. We show that the relation between the classical statistics of wave packet centroids and the quantum statistics of wave packets can be obtained by taking into account the effects of the wave packet spread. This relation clarifies how the quantum statistics of wave packets emerges from the classical statistics of wave packet centroids. It is emphasized that the temperature of the classical statistics of wave packet centroids is different from the temperature of the quantum statistics of wave packets. We then explain that the statistical properties of AMD for nucleon-emission processes are classical because nucleon-emission processes in AMD are described by the motion of wave packet centroids. We further show that when we improve the description of the nucleon-emission process so as to take into account the momentum fluctuation due to the wave packet spread, the AMD statistical properties for nucleon-emission processes change drastically into quantum statistics. Our study of nucleon-emission processes can be conversely regarded as giving another kind of proof of the fact that the statistics of wave packets is quantum mechanical while that of wave packet centroids is classical. copyright 1996 The American Physical Society
Is Cognitive Activity of Speech Based On Statistical Independence?
DEFF Research Database (Denmark)
Feng, Ling; Hansen, Lars Kai
2008-01-01
This paper explores the generality of COgnitive Component Analysis (COCA), which is defined as the process of unsupervised grouping of data such that the ensuing group structure is well-aligned with that resulting from human cognitive activity. The hypothesis of {COCA} is ecological......: the essentially independent features in a context defined ensemble can be efficiently coded using a sparse independent component representation. Our devised protocol aims at comparing the performance of supervised learning (invoking cognitive activity) and unsupervised learning (statistical regularities) based...... on similar representations, and the only difference lies in the human inferred labels. Inspired by the previous research on COCA, we introduce a new pair of models, which directly employ the independent hypothesis. Statistical regularities are revealed at multiple time scales on phoneme, gender, age...
Directory of Open Access Journals (Sweden)
Almeida Diogo
2016-10-01
Full Text Available Measuring differential methylation of the DNA is the nowadays most common approach to linking epigenetic modifications to diseases (called epigenome-wide association studies, EWAS. For its low cost, its efficiency and easy handling, the Illumina HumanMethylation450 BeadChip and its successor, the Infinium MethylationEPIC BeadChip, is the by far most popular techniques for conduction EWAS in large patient cohorts. Despite the popularity of this chip technology, raw data processing and statistical analysis of the array data remains far from trivial and still lacks dedicated software libraries enabling high quality and statistically sound downstream analyses. As of yet, only R-based solutions are freely available for low-level processing of the Illumina chip data. However, the lack of alternative libraries poses a hurdle for the development of new bioinformatic tools, in particular when it comes to web services or applications where run time and memory consumption matter, or EWAS data analysis is an integrative part of a bigger framework or data analysis pipeline. We have therefore developed and implemented Jllumina, an open-source Java library for raw data manipulation of Illumina Infinium HumanMethylation450 and Infinium MethylationEPIC BeadChip data, supporting the developer with Java functions covering reading and preprocessing the raw data, down to statistical assessment, permutation tests, and identification of differentially methylated loci. Jllumina is fully parallelizable and publicly available at http://dimmer.compbio.sdu.dk/download.html
Use of statistical process control in the production of blood components
DEFF Research Database (Denmark)
Magnussen, K; Quere, S; Winkel, P
2008-01-01
Introduction of statistical process control in the setting of a small blood centre was tested, both on the regular red blood cell production and specifically to test if a difference was seen in the quality of the platelets produced, when a change was made from a relatively large inexperienced...... by an experienced staff with four technologists. We applied statistical process control to examine if time series of quality control values were in statistical control. Leucocyte count in red blood cells was out of statistical control. Platelet concentration and volume of the platelets produced by the occasional...... occasional component manufacturing staff to an experienced regular manufacturing staff. Production of blood products is a semi-automated process in which the manual steps may be difficult to control. This study was performed in an ongoing effort to improve the control and optimize the quality of the blood...
Beach, Shaun E.; Semkow, Thomas M.; Remling, David J.; Bradt, Clayton J.
2017-07-01
We have developed accessible methods to demonstrate fundamental statistics in several phenomena, in the context of teaching electronic signal processing in a physics-based college-level curriculum. A relationship between the exponential time-interval distribution and Poisson counting distribution for a Markov process with constant rate is derived in a novel way and demonstrated using nuclear counting. Negative binomial statistics is demonstrated as a model for overdispersion and justified by the effect of electronic noise in nuclear counting. The statistics of digital packets on a computer network are shown to be compatible with the fractal-point stochastic process leading to a power-law as well as generalized inverse Gaussian density distributions of time intervals between packets.
Statistical dynamics of transient processes in a gas discharge plasma
International Nuclear Information System (INIS)
Smirnov, G.I.; Telegin, G.G.
1991-01-01
The properties of a gas discharge plasma to a great extent depend on random processes whose study has recently become particularly important. The present work is concerned with analyzing the statistical phenomena that occur during the prebreakdown stage in a gas discharge. Unlike other studies of breakdown in the discharge gap, in which secondary electron effects and photon processes at the electrodes must be considered, here the authors treat the case of an electrodeless rf discharge or a laser photoresonant plasma. The analysis is based on the balance between the rates of electron generation and recombination in the plasma. The fluctuation kinetics for ionization of atoms in the hot plasma may also play an important role when the electron temperature changes abruptly, as occurs during adiabatic pinching of the plasma or during electron cyclotron heating
Application of statistical process control to qualitative molecular diagnostic assays.
Directory of Open Access Journals (Sweden)
Cathal P O'brien
2014-11-01
Full Text Available Modern pathology laboratories and in particular high throughput laboratories such as clinical chemistry have developed a reliable system for statistical process control. Such a system is absent from the majority of molecular laboratories and where present is confined to quantitative assays. As the inability to apply statistical process control to assay is an obvious disadvantage this study aimed to solve this problem by using a frequency estimate coupled with a confidence interval calculation to detect deviations from an expected mutation frequency. The results of this study demonstrate the strengths and weaknesses of this approach and highlight minimum sample number requirements. Notably, assays with low mutation frequencies and detection of small deviations from an expected value require greater samples with a resultant protracted time to detection. Modelled laboratory data was also used to highlight how this approach might be applied in a routine molecular laboratory. This article is the first to describe the application of statistical process control to qualitative laboratory data.
Whist, A C; Liland, K H; Jonsson, M E; Sæbø, S; Sviland, S; Østerås, O; Norström, M; Hopp, P
2014-11-01
Surveillance programs for animal diseases are critical to early disease detection and risk estimation and to documenting a population's disease status at a given time. The aim of this study was to describe a risk-based surveillance program for detecting Mycobacterium avium ssp. paratuberculosis (MAP) infection in Norwegian dairy cattle. The included risk factors for detecting MAP were purchase of cattle, combined cattle and goat farming, and location of the cattle farm in counties containing goats with MAP. The risk indicators included production data [culling of animals >3 yr of age, carcass conformation of animals >3 yr of age, milk production decrease in older lactating cows (lactations 3, 4, and 5)], and clinical data (diarrhea, enteritis, or both, in animals >3 yr of age). Except for combined cattle and goat farming and cattle farm location, all data were collected at the cow level and summarized at the herd level. Predefined risk factors and risk indicators were extracted from different national databases and combined in a multivariate statistical process control to obtain a risk assessment for each herd. The ordinary Hotelling's T(2) statistic was applied as a multivariate, standardized measure of difference between the current observed state and the average state of the risk factors for a given herd. To make the analysis more robust and adapt it to the slowly developing nature of MAP, monthly risk calculations were based on data accumulated during a 24-mo period. Monitoring of these variables was performed to identify outliers that may indicate deviance in one or more of the underlying processes. The highest-ranked herds were scattered all over Norway and clustered in high-density dairy cattle farm areas. The resulting rankings of herds are being used in the national surveillance program for MAP in 2014 to increase the sensitivity of the ongoing surveillance program in which 5 fecal samples for bacteriological examination are collected from 25 dairy herds
Statistical process control support during Defense Waste Processing Facility chemical runs
International Nuclear Information System (INIS)
Brown, K.G.
1994-01-01
The Product Composition Control System (PCCS) has been developed to ensure that the wasteforms produced by the Defense Waste Processing Facility (DWPF) at the Savannah River Site (SRS) will satisfy the regulatory and processing criteria that will be imposed. The PCCS provides rigorous, statistically-defensible management of a noisy, multivariate system subject to multiple constraints. The system has been successfully tested and has been used to control the production of the first two melter feed batches during DWPF Chemical Runs. These operations will demonstrate the viability of the DWPF process. This paper provides a brief discussion of the technical foundation for the statistical process control algorithms incorporated into PCCS, and describes the results obtained and lessons learned from DWPF Cold Chemical Run operations. The DWPF will immobilize approximately 130 million liters of high-level nuclear waste currently stored at the Site in 51 carbon steel tanks. Waste handling operations separate this waste into highly radioactive sludge and precipitate streams and less radioactive water soluble salts. (In a separate facility, soluble salts are disposed of as low-level waste in a mixture of cement slag, and flyash.) In DWPF, the precipitate steam (Precipitate Hydrolysis Aqueous or PHA) is blended with the insoluble sludge and ground glass frit to produce melter feed slurry which is continuously fed to the DWPF melter. The melter produces a molten borosilicate glass which is poured into stainless steel canisters for cooling and, ultimately, shipment to and storage in a geologic repository
Zhang, Kai; Shardt, Yuri A W; Chen, Zhiwen; Peng, Kaixiang
2017-03-01
Using the expected detection delay (EDD) index to measure the performance of multivariate statistical process monitoring (MSPM) methods for constant additive faults have been recently developed. This paper, based on a statistical investigation of the T 2 - and Q-test statistics, extends the EDD index to the multiplicative and drift fault cases. As well, it is used to assess the performance of common MSPM methods that adopt these two test statistics. Based on how to use the measurement space, these methods can be divided into two groups, those which consider the complete measurement space, for example, principal component analysis-based methods, and those which only consider some subspace that reflects changes in key performance indicators, such as partial least squares-based methods. Furthermore, a generic form for them to use T 2 - and Q-test statistics are given. With the extended EDD index, the performance of these methods to detect drift and multiplicative faults is assessed using both numerical simulations and the Tennessee Eastman process. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Weathers, J.B.; Luck, R.; Weathers, J.W.
2009-01-01
The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.
Energy Technology Data Exchange (ETDEWEB)
Weathers, J.B. [Shock, Noise, and Vibration Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: James.Weathers@ngc.com; Luck, R. [Department of Mechanical Engineering, Mississippi State University, 210 Carpenter Engineering Building, P.O. Box ME, Mississippi State, MS 39762-5925 (United States)], E-mail: Luck@me.msstate.edu; Weathers, J.W. [Structural Analysis Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: Jeffrey.Weathers@ngc.com
2009-11-15
The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.
An introduction to statistical computing a simulation-based approach
Voss, Jochen
2014-01-01
A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced met
Statistical characterization of pitting corrosion process and life prediction
International Nuclear Information System (INIS)
Sheikh, A.K.; Younas, M.
1995-01-01
In order to prevent corrosion failures of machines and structures, it is desirable to know in advance when the corrosion damage will take place, and appropriate measures are needed to mitigate the damage. The corrosion predictions are needed both at development as well as operational stage of machines and structures. There are several forms of corrosion process through which varying degrees of damage can occur. Under certain conditions these corrosion processes at alone and in other set of conditions, several of these processes may occur simultaneously. For a certain type of machine elements and structures, such as gears, bearing, tubes, pipelines, containers, storage tanks etc., are particularly prone to pitting corrosion which is an insidious form of corrosion. The corrosion predictions are usually based on experimental results obtained from test coupons and/or field experiences of similar machines or parts of a structure. Considerable scatter is observed in corrosion processes. The probabilities nature and kinetics of pitting process makes in necessary to use statistical method to forecast the residual life of machine of structures. The focus of this paper is to characterization pitting as a time-dependent random process, and using this characterization the prediction of life to reach a critical level of pitting damage can be made. Using several data sets from literature on pitting corrosion, the extreme value modeling of pitting corrosion process, the evolution of the extreme value distribution in time, and their relationship to the reliability of machines and structure are explained. (author)
Signal processing and statistical analysis of spaced-based measurements
International Nuclear Information System (INIS)
Iranpour, K.
1996-05-01
The reports deals with data obtained by the ROSE rocket project. This project was designed to investigate the low altitude auroral instabilities in the electrojet region. The spectral and statistical analyses indicate the existence of unstable waves in the ionized gas in the region. An experimentally obtained dispersion relation for these waves were established. It was demonstrated that the characteristic phase velocities are much lower than what is expected from the standard theoretical results. This analysis of the ROSE data indicate the cascading of energy from lower to higher frequencies. 44 refs., 54 figs
Large-Deviation Results for Discriminant Statistics of Gaussian Locally Stationary Processes
Directory of Open Access Journals (Sweden)
Junichi Hirukawa
2012-01-01
Full Text Available This paper discusses the large-deviation principle of discriminant statistics for Gaussian locally stationary processes. First, large-deviation theorems for quadratic forms and the log-likelihood ratio for a Gaussian locally stationary process with a mean function are proved. Their asymptotics are described by the large deviation rate functions. Second, we consider the situations where processes are misspecified to be stationary. In these misspecified cases, we formally make the log-likelihood ratio discriminant statistics and derive the large deviation theorems of them. Since they are complicated, they are evaluated and illustrated by numerical examples. We realize the misspecification of the process to be stationary seriously affecting our discrimination.
Obtaining Application-based and Content-based Internet Traffic Statistics
DEFF Research Database (Denmark)
Bujlow, Tomasz; Pedersen, Jens Myrup
2012-01-01
the Volunteer-Based System for Research on the Internet, developed at Aalborg University, is capable of providing detailed statistics of Internet usage. Since an increasing amount of HTTP traffic has been observed during the last few years, the system also supports creating statistics of different kinds of HTTP...... traffic, like audio, video, file transfers, etc. All statistics can be obtained for individual users of the system, for groups of users, or for all users altogether. This paper presents results with real data collected from a limited number of real users over six months. We demonstrate that the system can...
The application of bayesian statistic in data fit processing
International Nuclear Information System (INIS)
Guan Xingyin; Li Zhenfu; Song Zhaohui
2010-01-01
The rationality and disadvantage of least squares fitting that is usually used in data processing is analyzed, and the theory and commonly method that Bayesian statistic is applied in data processing is shown in detail. As it is proved in analysis, Bayesian approach avoid the limitative hypothesis that least squares fitting has in data processing, and the result has traits that it is more scientific and more easily understood, may replace the least squares fitting to apply in data processing. (authors)
DEFF Research Database (Denmark)
Malzahn, Dorthe; Opper, Manfred
2003-01-01
We employ the replica method of statistical physics to study the average case performance of learning systems. The new feature of our theory is that general distributions of data can be treated, which enables applications to real data. For a class of Bayesian prediction models which are based...... on Gaussian processes, we discuss Bootstrap estimates for learning curves....
An easy and low cost option for economic statistical process control ...
African Journals Online (AJOL)
An easy and low cost option for economic statistical process control using Excel. ... in both economic and economic statistical designs of the X-control chart. ... in this paper and the numerical examples illustrated are executed on this program.
Statistical physics of media processes: Mediaphysics
Kuznetsov, Dmitri V.; Mandel, Igor
2007-04-01
The processes of mass communications in complicated social or sociobiological systems such as marketing, economics, politics, animal populations, etc. as a subject for the special scientific subbranch-“mediaphysics”-are considered in its relation with sociophysics. A new statistical physics approach to analyze these phenomena is proposed. A keystone of the approach is an analysis of population distribution between two or many alternatives: brands, political affiliations, or opinions. Relative distances between a state of a “person's mind” and the alternatives are measures of propensity to buy (to affiliate, or to have a certain opinion). The distribution of population by those relative distances is time dependent and affected by external (economic, social, marketing, natural) and internal (influential propagation of opinions, “word of mouth”, etc.) factors, considered as fields. Specifically, the interaction and opinion-influence field can be generalized to incorporate important elements of Ising-spin-based sociophysical models and kinetic-equation ones. The distributions were described by a Schrödinger-type equation in terms of Green's functions. The developed approach has been applied to a real mass-media efficiency problem for a large company and generally demonstrated very good results despite low initial correlations of factors and the target variable.
International Nuclear Information System (INIS)
Debón, A.; Carlos Garcia-Díaz, J.
2012-01-01
Advanced statistical models can help industry to design more economical and rational investment plans. Fault detection and diagnosis is an important problem in continuous hot dip galvanizing. Increasingly stringent quality requirements in the automotive industry also require ongoing efforts in process control to make processes more robust. Robust methods for estimating the quality of galvanized steel coils are an important tool for the comprehensive monitoring of the performance of the manufacturing process. This study applies different statistical regression models: generalized linear models, generalized additive models and classification trees to estimate the quality of galvanized steel coils on the basis of short time histories. The data, consisting of 48 galvanized steel coils, was divided into sets of conforming and nonconforming coils. Five variables were selected for monitoring the process: steel strip velocity and four bath temperatures. The present paper reports a comparative evaluation of statistical models for binary data using Receiver Operating Characteristic (ROC) curves. A ROC curve is a graph or a technique for visualizing, organizing and selecting classifiers based on their performance. The purpose of this paper is to examine their use in research to obtain the best model to predict defective steel coil probability. In relation to the work of other authors who only propose goodness of fit statistics, we should highlight one distinctive feature of the methodology presented here, which is the possibility of comparing the different models with ROC graphs which are based on model classification performance. Finally, the results are validated by bootstrap procedures.
Statistical reliability assessment of software-based systems
International Nuclear Information System (INIS)
Korhonen, J.; Pulkkinen, U.; Haapanen, P.
1997-01-01
Plant vendors nowadays propose software-based systems even for the most critical safety functions. The reliability estimation of safety critical software-based systems is difficult since the conventional modeling techniques do not necessarily apply to the analysis of these systems, and the quantification seems to be impossible. Due to lack of operational experience and due to the nature of software faults, the conventional reliability estimation methods can not be applied. New methods are therefore needed for the safety assessment of software-based systems. In the research project Programmable automation systems in nuclear power plants (OHA), financed together by the Finnish Centre for Radiation and Nuclear Safety (STUK), the Ministry of Trade and Industry and the Technical Research Centre of Finland (VTT), various safety assessment methods and tools for software based systems are developed and evaluated. This volume in the OHA-report series deals with the statistical reliability assessment of software based systems on the basis of dynamic test results and qualitative evidence from the system design process. Other reports to be published later on in OHA-report series will handle the diversity requirements in safety critical software-based systems, generation of test data from operational profiles and handling of programmable automation in plant PSA-studies. (orig.) (25 refs.)
Interrupted Time Series Versus Statistical Process Control in Quality Improvement Projects.
Andersson Hagiwara, Magnus; Andersson Gäre, Boel; Elg, Mattias
2016-01-01
To measure the effect of quality improvement interventions, it is appropriate to use analysis methods that measure data over time. Examples of such methods include statistical process control analysis and interrupted time series with segmented regression analysis. This article compares the use of statistical process control analysis and interrupted time series with segmented regression analysis for evaluating the longitudinal effects of quality improvement interventions, using an example study on an evaluation of a computerized decision support system.
Kottner, Jan; Halfens, Ruud
2010-05-01
Institutionally acquired pressure ulcers are used as outcome indicators to assess the quality of pressure ulcer prevention programs. Determining whether quality improvement projects that aim to decrease the proportions of institutionally acquired pressure ulcers lead to real changes in clinical practice depends on the measurement method and statistical analysis used. To examine whether nosocomial pressure ulcer prevalence rates in hospitals in the Netherlands changed, a secondary data analysis using different statistical approaches was conducted of annual (1998-2008) nationwide nursing-sensitive health problem prevalence studies in the Netherlands. Institutions that participated regularly in all survey years were identified. Risk-adjusted nosocomial pressure ulcers prevalence rates, grade 2 to 4 (European Pressure Ulcer Advisory Panel system) were calculated per year and hospital. Descriptive statistics, chi-square trend tests, and P charts based on statistical process control (SPC) were applied and compared. Six of the 905 healthcare institutions participated in every survey year and 11,444 patients in these six hospitals were identified as being at risk for pressure ulcers. Prevalence rates per year ranged from 0.05 to 0.22. Chi-square trend tests revealed statistically significant downward trends in four hospitals but based on SPC methods, prevalence rates of five hospitals varied by chance only. Results of chi-square trend tests and SPC methods were not comparable, making it impossible to decide which approach is more appropriate. P charts provide more valuable information than single P values and are more helpful for monitoring institutional performance. Empirical evidence about the decrease of nosocomial pressure ulcer prevalence rates in the Netherlands is contradictory and limited.
Ghavami, Behnam; Raji, Mohsen; Pedram, Hossein
2011-08-26
Carbon nanotube field-effect transistors (CNFETs) show great promise as building blocks of future integrated circuits. However, synthesizing single-walled carbon nanotubes (CNTs) with accurate chirality and exact positioning control has been widely acknowledged as an exceedingly complex task. Indeed, density and chirality variations in CNT growth can compromise the reliability of CNFET-based circuits. In this paper, we present a novel statistical compact model to estimate the failure probability of CNFETs to provide some material and process guidelines for the design of CNFETs in gigascale integrated circuits. We use measured CNT spacing distributions within the framework of detailed failure analysis to demonstrate that both the CNT density and the ratio of metallic to semiconducting CNTs play dominant roles in defining the failure probability of CNFETs. Besides, it is argued that the large-scale integration of these devices within an integrated circuit will be feasible only if a specific range of CNT density with an acceptable ratio of semiconducting to metallic CNTs can be adjusted in a typical synthesis process.
An introduction to statistical process control in research proteomics.
Bramwell, David
2013-12-16
Statistical process control is a well-established and respected method which provides a general purpose, and consistent framework for monitoring and improving the quality of a process. It is routinely used in many industries where the quality of final products is critical and is often required in clinical diagnostic laboratories [1,2]. To date, the methodology has been little utilised in research proteomics. It has been shown to be capable of delivering quantitative QC procedures for qualitative clinical assays [3] making it an ideal methodology to apply to this area of biological research. To introduce statistical process control as an objective strategy for quality control and show how it could be used to benefit proteomics researchers and enhance the quality of the results they generate. We demonstrate that rules which provide basic quality control are easy to derive and implement and could have a major impact on data quality for many studies. Statistical process control is a powerful tool for investigating and improving proteomics research work-flows. The process of characterising measurement systems and defining control rules forces the exploration of key questions that can lead to significant improvements in performance. This work asserts that QC is essential to proteomics discovery experiments. Every experimenter must know the current capabilities of their measurement system and have an objective means for tracking and ensuring that performance. Proteomic analysis work-flows are complicated and multi-variate. QC is critical for clinical chemistry measurements and huge strides have been made in ensuring the quality and validity of results in clinical biochemistry labs. This work introduces some of these QC concepts and works to bridge their use from single analyte QC to applications in multi-analyte systems. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. Copyright © 2013 The Author. Published by Elsevier
A comprehensive analysis of the IMRT dose delivery process using statistical process control (SPC)
Energy Technology Data Exchange (ETDEWEB)
Gerard, Karine; Grandhaye, Jean-Pierre; Marchesi, Vincent; Kafrouni, Hanna; Husson, Francois; Aletti, Pierre [Research Center for Automatic Control (CRAN), Nancy University, CNRS, 54516 Vandoeuvre-les-Nancy (France); Department of Medical Physics, Alexis Vautrin Cancer Center, 54511 Vandoeuvre-les-Nancy Cedex (France) and DOSIsoft SA, 94230 Cachan (France); Research Laboratory for Innovative Processes (ERPI), Nancy University, EA 3767, 5400 Nancy Cedex (France); Department of Medical Physics, Alexis Vautrin Cancer Center, 54511 Vandoeuvre-les-Nancy Cedex (France); DOSIsoft SA, 94230 Cachan (France); Research Center for Automatic Control (CRAN), Nancy University, CNRS, 54516 Vandoeuvre-les-Nancy, France and Department of Medical Physics, Alexis Vautrin Cancer Center, 54511 Vandoeuvre-les-Nancy Cedex (France)
2009-04-15
The aim of this study is to introduce tools to improve the security of each IMRT patient treatment by determining action levels for the dose delivery process. To achieve this, the patient-specific quality control results performed with an ionization chamber--and which characterize the dose delivery process--have been retrospectively analyzed using a method borrowed from industry: Statistical process control (SPC). The latter consisted in fulfilling four principal well-structured steps. The authors first quantified the short term variability of ionization chamber measurements regarding the clinical tolerances used in the cancer center ({+-}4% of deviation between the calculated and measured doses) by calculating a control process capability (C{sub pc}) index. The C{sub pc} index was found superior to 4, which implies that the observed variability of the dose delivery process is not biased by the short term variability of the measurement. Then, the authors demonstrated using a normality test that the quality control results could be approximated by a normal distribution with two parameters (mean and standard deviation). Finally, the authors used two complementary tools--control charts and performance indices--to thoroughly analyze the IMRT dose delivery process. Control charts aim at monitoring the process over time using statistical control limits to distinguish random (natural) variations from significant changes in the process, whereas performance indices aim at quantifying the ability of the process to produce data that are within the clinical tolerances, at a precise moment. The authors retrospectively showed that the analysis of three selected control charts (individual value, moving-range, and EWMA control charts) allowed efficient drift detection of the dose delivery process for prostate and head-and-neck treatments before the quality controls were outside the clinical tolerances. Therefore, when analyzed in real time, during quality controls, they should
A comprehensive analysis of the IMRT dose delivery process using statistical process control (SPC).
Gérard, Karine; Grandhaye, Jean-Pierre; Marchesi, Vincent; Kafrouni, Hanna; Husson, François; Aletti, Pierre
2009-04-01
The aim of this study is to introduce tools to improve the security of each IMRT patient treatment by determining action levels for the dose delivery process. To achieve this, the patient-specific quality control results performed with an ionization chamber--and which characterize the dose delivery process--have been retrospectively analyzed using a method borrowed from industry: Statistical process control (SPC). The latter consisted in fulfilling four principal well-structured steps. The authors first quantified the short-term variability of ionization chamber measurements regarding the clinical tolerances used in the cancer center (+/- 4% of deviation between the calculated and measured doses) by calculating a control process capability (C(pc)) index. The C(pc) index was found superior to 4, which implies that the observed variability of the dose delivery process is not biased by the short-term variability of the measurement. Then, the authors demonstrated using a normality test that the quality control results could be approximated by a normal distribution with two parameters (mean and standard deviation). Finally, the authors used two complementary tools--control charts and performance indices--to thoroughly analyze the IMRT dose delivery process. Control charts aim at monitoring the process over time using statistical control limits to distinguish random (natural) variations from significant changes in the process, whereas performance indices aim at quantifying the ability of the process to produce data that are within the clinical tolerances, at a precise moment. The authors retrospectively showed that the analysis of three selected control charts (individual value, moving-range, and EWMA control charts) allowed efficient drift detection of the dose delivery process for prostate and head-and-neck treatments before the quality controls were outside the clinical tolerances. Therefore, when analyzed in real time, during quality controls, they should improve the
A new instrument for statistical process control of thermoset molding
International Nuclear Information System (INIS)
Day, D.R.; Lee, H.L.; Shepard, D.D.; Sheppard, N.F.
1991-01-01
The recent development of a rugged ceramic mold mounted dielectric sensor and high speed dielectric instrumentation now enables monitoring and statistical process control of production molding over thousands of runs. In this work special instrumentation and software (ICAM-1000) was utilized that automatically extracts critical point during the molding process including flow point, viscosity minimum gel inflection, and reaction endpoint. In addition, other sensors were incorporated to measure temperature and pressure. The critical point as well as temperature and pressure were then recorded during normal production and then plotted in the form of statistical process control (SPC) charts. Experiments have been carried out in RIM, SMC, and RTM type molding operations. The influence of temperature, pressure chemistry, and other variables has been investigated. In this paper examples of both RIM and SMC are discussed
International Nuclear Information System (INIS)
Ung, M.N.; Wee, Leonard
2010-01-01
Full text: Portal imaging of implanted fiducial markers has been in use for image-guided radiotherapy (TORT) of prostate cancer, with ample attention to localization accuracy and organ motion. The geometric uncertainties in point-based rigid-body (PBRB) image registration during localization of prostate fiducial markers can be quantified in terms of a fiducial registration error (FRE). Statistical process control charts for individual patients can be designed to identify potentially significant deviation of FRE from expected behaviour. In this study, the aim was to retrospectively apply statistical process control methods to FREs in 34 individuals to identify parameters that may impact on the process stability in image-based localization. A robust procedure for estimating control parameters, control lim its and fixed tolerance levels from a small number of initial observations has been proposed and discussed. Four distinct types of qualitative control chart behavior have been observed. Probable clinical factors leading to IORT process instability are discussed in light of the control chart behaviour. Control charts have been shown to be a useful decision-making tool for detecting potentially out-of control processes on an individual basis. It can sensitively identify potential problems that warrant more detailed investigation in the 10RT of prostate cancer.
Statistical Inference on Memory Structure of Processes and Its Applications to Information Theory
2016-05-12
Distribution Unlimited UU UU UU UU 12-05-2016 15-May-2014 14-Feb-2015 Final Report: Statistical Inference on Memory Structure of Processes and Its Applications ...ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 mathematical statistics ; time series; Markov chains; random...journals: Final Report: Statistical Inference on Memory Structure of Processes and Its Applications to Information Theory Report Title Three areas
International Nuclear Information System (INIS)
Lopez de la Cruz, J.; Gutierrez, M.A.
2008-01-01
This paper presents a stochastic analysis of spatial point patterns as effect of localized pitting corrosion. The Quadrat Counts method is studied with two empirical pit patterns. The results are dependent on the quadrat size and bias is introduced when empty quadrats are accounted for the analysis. The spatially inhomogeneous Poisson process is used to improve the performance of the Quadrat Counts method. The latter combines Quadrat Counts with distance-based statistics in the analysis of pit patterns. The Inter-Event and the Nearest-Neighbour statistics are here implemented in order to compare their results. Further, the treatment of patterns in irregular domains is discussed
Statistical process control charts for monitoring military injuries.
Schuh, Anna; Canham-Chervak, Michelle; Jones, Bruce H
2017-12-01
An essential aspect of an injury prevention process is surveillance, which quantifies and documents injury rates in populations of interest and enables monitoring of injury frequencies, rates and trends. To drive progress towards injury reduction goals, additional tools are needed. Statistical process control charts, a methodology that has not been previously applied to Army injury monitoring, capitalise on existing medical surveillance data to provide information to leadership about injury trends necessary for prevention planning and evaluation. Statistical process control Shewhart u-charts were created for 49 US Army installations using quarterly injury medical encounter rates, 2007-2015, for active duty soldiers obtained from the Defense Medical Surveillance System. Injuries were defined according to established military injury surveillance recommendations. Charts display control limits three standard deviations (SDs) above and below an installation-specific historical average rate determined using 28 data points, 2007-2013. Charts are available in Army strategic management dashboards. From 2007 to 2015, Army injury rates ranged from 1254 to 1494 unique injuries per 1000 person-years. Installation injury rates ranged from 610 to 2312 injuries per 1000 person-years. Control charts identified four installations with injury rates exceeding the upper control limits at least once during 2014-2015, rates at three installations exceeded the lower control limit at least once and 42 installations had rates that fluctuated around the historical mean. Control charts can be used to drive progress towards injury reduction goals by indicating statistically significant increases and decreases in injury rates. Future applications to military subpopulations, other health outcome metrics and chart enhancements are suggested. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Research on Statistical Flow of the Complex Background Based on Image Method
Directory of Open Access Journals (Sweden)
Yang Huanhai
2014-06-01
Full Text Available Along with our country city changes a process continues to accelerate, city road traffic system pressure increasing. Therefore, the importance of intelligent transportation system based on computer vision technology is becoming more and more significant. Using the image processing technology for the vehicle detection has become a hot topic in the research field of. Only accurately segmented from the background of vehicle can recognize and track vehicles. Therefore, the application of video vehicle detection technology and image processing technology, identify a number of the same sight many car can, types and moving characteristics, can provide real-time basis for intelligent traffic control. This paper first introduces the concept of intelligent transportation system, the importance and the image processing technology in vehicle recognition in statistics, overview of video vehicle detection method, and the video detection technology and other detection technology, puts forward the superiority of video detection technology. Finally we design a real-time and reliable background subtraction method and the area of the vehicle recognition method based on information fusion algorithm, which is implemented with the MATLAB/GUI development tool in Windows operating system platform. In this paper, the application of the algorithm to study the frame traffic flow image. The experimental results show that, the algorithm of recognition of vehicle flow statistics, the effect is very good.
Tintle, Nathan; Topliff, Kylie; VanderStoep, Jill; Holmes, Vicki-Lynn; Swanson, Todd
2012-01-01
Previous research suggests that a randomization-based introductory statistics course may improve student learning compared to the consensus curriculum. However, it is unclear whether these gains are retained by students post-course. We compared the conceptual understanding of a cohort of students who took a randomization-based curriculum (n = 76)…
ASYMPTOTIC COMPARISONS OF U-STATISTICS, V-STATISTICS AND LIMITS OF BAYES ESTIMATES BY DEFICIENCIES
Toshifumi, Nomachi; Hajime, Yamato; Graduate School of Science and Engineering, Kagoshima University:Miyakonojo College of Technology; Faculty of Science, Kagoshima University
2001-01-01
As estimators of estimable parameters, we consider three statistics which are U-statistic, V-statistic and limit of Bayes estimate. This limit of Bayes estimate, called LB-statistic in this paper, is obtained from Bayes estimate of estimable parameter based on Dirichlet process, by letting its parameter tend to zero. For the estimable parameter with non-degenerate kernel, the asymptotic relative efficiencies of LB-statistic with respect to U-statistic and V-statistic and that of V-statistic w...
Kruger, Uwe
2012-01-01
The development and application of multivariate statistical techniques in process monitoring has gained substantial interest over the past two decades in academia and industry alike. Initially developed for monitoring and fault diagnosis in complex systems, such techniques have been refined and applied in various engineering areas, for example mechanical and manufacturing, chemical, electrical and electronic, and power engineering. The recipe for the tremendous interest in multivariate statistical techniques lies in its simplicity and adaptability for developing monitoring applica
On the joint statistics of stable random processes
International Nuclear Information System (INIS)
Hopcraft, K I; Jakeman, E
2011-01-01
A utilitarian continuous bi-variate random process whose first-order probability density function is a stable random variable is constructed. Results paralleling some of those familiar from the theory of Gaussian noise are derived. In addition to the joint-probability density for the process, these include fractional moments and structure functions. Although the correlation functions for stable processes other than Gaussian do not exist, we show that there is coherence between values adopted by the process at different times, which identifies a characteristic evolution with time. The distribution of the derivative of the process, and the joint-density function of the value of the process and its derivative measured at the same time are evaluated. These enable properties to be calculated analytically such as level crossing statistics and those related to the random telegraph wave. When the stable process is fractal, the proportion of time it spends at zero is finite and some properties of this quantity are evaluated, an optical interpretation for which is provided. (paper)
Statistical Process Control. Impact and Opportunities for Ohio.
Brown, Harold H.
The first purpose of this study is to help the reader become aware of the evolution of Statistical Process Control (SPC) as it is being implemented and used in industry today. This is approached through the presentation of a brief historical account of SPC, from its inception through the technological miracle that has occurred in Japan. The…
Incorporating Code-Based Software in an Introductory Statistics Course
Doehler, Kirsten; Taylor, Laura
2015-01-01
This article is based on the experiences of two statistics professors who have taught students to write and effectively utilize code-based software in a college-level introductory statistics course. Advantages of using software and code-based software in this context are discussed. Suggestions are made on how to ease students into using code with…
Bayesian models based on test statistics for multiple hypothesis testing problems.
Ji, Yuan; Lu, Yiling; Mills, Gordon B
2008-04-01
We propose a Bayesian method for the problem of multiple hypothesis testing that is routinely encountered in bioinformatics research, such as the differential gene expression analysis. Our algorithm is based on modeling the distributions of test statistics under both null and alternative hypotheses. We substantially reduce the complexity of the process of defining posterior model probabilities by modeling the test statistics directly instead of modeling the full data. Computationally, we apply a Bayesian FDR approach to control the number of rejections of null hypotheses. To check if our model assumptions for the test statistics are valid for various bioinformatics experiments, we also propose a simple graphical model-assessment tool. Using extensive simulations, we demonstrate the performance of our models and the utility of the model-assessment tool. In the end, we apply the proposed methodology to an siRNA screening and a gene expression experiment.
Statistical process control: separating signal from noise in emergency department operations.
Pimentel, Laura; Barrueto, Fermin
2015-05-01
Statistical process control (SPC) is a visually appealing and statistically rigorous methodology very suitable to the analysis of emergency department (ED) operations. We demonstrate that the control chart is the primary tool of SPC; it is constructed by plotting data measuring the key quality indicators of operational processes in rationally ordered subgroups such as units of time. Control limits are calculated using formulas reflecting the variation in the data points from one another and from the mean. SPC allows managers to determine whether operational processes are controlled and predictable. We review why the moving range chart is most appropriate for use in the complex ED milieu, how to apply SPC to ED operations, and how to determine when performance improvement is needed. SPC is an excellent tool for operational analysis and quality improvement for these reasons: 1) control charts make large data sets intuitively coherent by integrating statistical and visual descriptions; 2) SPC provides analysis of process stability and capability rather than simple comparison with a benchmark; 3) SPC allows distinction between special cause variation (signal), indicating an unstable process requiring action, and common cause variation (noise), reflecting a stable process; and 4) SPC keeps the focus of quality improvement on process rather than individual performance. Because data have no meaning apart from their context, and every process generates information that can be used to improve it, we contend that SPC should be seriously considered for driving quality improvement in emergency medicine. Copyright © 2015 Elsevier Inc. All rights reserved.
Zhang, Yu; Li, Fei; Zhang, Shengkai; Zhu, Tingting
2017-04-01
Synthetic Aperture Radar (SAR) is significantly important for polar remote sensing since it can provide continuous observations in all days and all weather. SAR can be used for extracting the surface roughness information characterized by the variance of dielectric properties and different polarization channels, which make it possible to observe different ice types and surface structure for deformation analysis. In November, 2016, Chinese National Antarctic Research Expedition (CHINARE) 33rd cruise has set sails in sea ice zone in Antarctic. Accurate leads spatial distribution in sea ice zone for routine planning of ship navigation is essential. In this study, the semantic relationship between leads and sea ice categories has been described by the Conditional Random Fields (CRF) model, and leads characteristics have been modeled by statistical distributions in SAR imagery. In the proposed algorithm, a mixture statistical distribution based CRF is developed by considering the contexture information and the statistical characteristics of sea ice for improving leads detection in Sentinel-1A dual polarization SAR imagery. The unary potential and pairwise potential in CRF model is constructed by integrating the posteriori probability estimated from statistical distributions. For mixture statistical distribution parameter estimation, Method of Logarithmic Cumulants (MoLC) is exploited for single statistical distribution parameters estimation. The iteration based Expectation Maximal (EM) algorithm is investigated to calculate the parameters in mixture statistical distribution based CRF model. In the posteriori probability inference, graph-cut energy minimization method is adopted in the initial leads detection. The post-processing procedures including aspect ratio constrain and spatial smoothing approaches are utilized to improve the visual result. The proposed method is validated on Sentinel-1A SAR C-band Extra Wide Swath (EW) Ground Range Detected (GRD) imagery with a
Wang, Xingsheng; Reid, Dave; Wang, Liping; Millar, Campbell; Burenkov, Alex; Evanschitzky, Peter; Baer, Eberhard; Lorenz, Juergen; Asenov, Asen
2016-01-01
This paper presents a TCAD based design technology co-optimization (DTCO) process for 14nm SOI FinFET based SRAM, which employs an enhanced variability aware compact modeling approach that fully takes process and lithography simulations and their impact on 6T-SRAM layout into account. Realistic double patterned gates and fins and their impacts are taken into account in the development of the variability-aware compact model. Finally, global process induced variability and local statistical var...
Design and Statistics in Quantitative Translation (Process) Research
DEFF Research Database (Denmark)
Balling, Laura Winther; Hvelplund, Kristian Tangsgaard
2015-01-01
Traditionally, translation research has been qualitative, but quantitative research is becoming increasingly important, especially in translation process research but also in other areas of translation studies. This poses problems to many translation scholars since this way of thinking...... is unfamiliar. In this article, we attempt to mitigate these problems by outlining our approach to good quantitative research, all the way from research questions and study design to data preparation and statistics. We concentrate especially on the nature of the variables involved, both in terms of their scale...... and their role in the design; this has implications for both design and choice of statistics. Although we focus on quantitative research, we also argue that such research should be supplemented with qualitative analyses and considerations of the translation product....
Statistical processing of experimental data
NAVRÁTIL, Pavel
2012-01-01
This thesis contains theory of probability and statistical sets. Solved and unsolved problems of probability, random variable and distributions random variable, random vector, statistical sets, regression and correlation analysis. Unsolved problems contains solutions.
Hantula, Donald A.
1995-01-01
Clinical applications of statistical process control (SPC) in human service organizations are considered. SPC is seen as providing a standard set of criteria that serves as a common interface for data-based decision making, which may bring decision making under the control of established contingencies rather than the immediate contingencies of…
Color Image Segmentation Based on Statistics of Location and Feature Similarity
Mori, Fumihiko; Yamada, Hiromitsu; Mizuno, Makoto; Sugano, Naotoshi
The process of “image segmentation and extracting remarkable regions” is an important research subject for the image understanding. However, an algorithm based on the global features is hardly found. The requisite of such an image segmentation algorism is to reduce as much as possible the over segmentation and over unification. We developed an algorithm using the multidimensional convex hull based on the density as the global feature. In the concrete, we propose a new algorithm in which regions are expanded according to the statistics of the region such as the mean value, standard deviation, maximum value and minimum value of pixel location, brightness and color elements and the statistics are updated. We also introduced a new concept of conspicuity degree and applied it to the various 21 images to examine the effectiveness. The remarkable object regions, which were extracted by the presented system, highly coincided with those which were pointed by the sixty four subjects who attended the psychological experiment.
Ciftci, S. Koza; Karadag, Engin; Akdal, Pinar
2014-01-01
The purpose of this study was to determine the effect of statistics instruction using computer-based tools, on statistics anxiety, attitude, and achievement. This study was designed as quasi-experimental research and the pattern used was a matched pre-test/post-test with control group design. Data was collected using three scales: a Statistics…
Understanding advanced statistical methods
Westfall, Peter
2013-01-01
Introduction: Probability, Statistics, and ScienceReality, Nature, Science, and ModelsStatistical Processes: Nature, Design and Measurement, and DataModelsDeterministic ModelsVariabilityParametersPurely Probabilistic Statistical ModelsStatistical Models with Both Deterministic and Probabilistic ComponentsStatistical InferenceGood and Bad ModelsUses of Probability ModelsRandom Variables and Their Probability DistributionsIntroductionTypes of Random Variables: Nominal, Ordinal, and ContinuousDiscrete Probability Distribution FunctionsContinuous Probability Distribution FunctionsSome Calculus-Derivatives and Least SquaresMore Calculus-Integrals and Cumulative Distribution FunctionsProbability Calculation and SimulationIntroductionAnalytic Calculations, Discrete and Continuous CasesSimulation-Based ApproximationGenerating Random NumbersIdentifying DistributionsIntroductionIdentifying Distributions from Theory AloneUsing Data: Estimating Distributions via the HistogramQuantiles: Theoretical and Data-Based Estimate...
Testing for Statistical Discrimination based on Gender
DEFF Research Database (Denmark)
Lesner, Rune Vammen
. It is shown that the implications of both screening discrimination and stereotyping are consistent with observable wage dynamics. In addition, it is found that the gender wage gap decreases in tenure but increases in job transitions and that the fraction of women in high-ranking positions within a firm does......This paper develops a model which incorporates the two most commonly cited strands of the literature on statistical discrimination, namely screening discrimination and stereotyping. The model is used to provide empirical evidence of statistical discrimination based on gender in the labour market...... not affect the level of statistical discrimination by gender....
Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B
2013-03-23
Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.
Statistical Process Control: Going to the Limit for Quality.
Training, 1987
1987-01-01
Defines the concept of statistical process control, a quality control method used especially in manufacturing. Generally, concept users set specific standard levels that must be met. Makes the point that although employees work directly with the method, management is responsible for its success within the plant. (CH)
Villani, N; Gérard, K; Marchesi, V; Huger, S; François, P; Noël, A
2010-06-01
The first purpose of this study was to illustrate the contribution of statistical process control for a better security in intensity modulated radiotherapy (IMRT) treatments. This improvement is possible by controlling the dose delivery process, characterized by pretreatment quality control results. So, it is necessary to put under control portal dosimetry measurements (currently, the ionisation chamber measurements were already monitored by statistical process control thanks to statistical process control tools). The second objective was to state whether it is possible to substitute ionisation chamber with portal dosimetry in order to optimize time devoted to pretreatment quality control. At Alexis-Vautrin center, pretreatment quality controls in IMRT for prostate and head and neck treatments were performed for each beam of each patient. These controls were made with an ionisation chamber, which is the reference detector for the absolute dose measurement, and with portal dosimetry for the verification of dose distribution. Statistical process control is a statistical analysis method, coming from industry, used to control and improve the studied process quality. It uses graphic tools as control maps to follow-up process, warning the operator in case of failure, and quantitative tools to evaluate the process toward its ability to respect guidelines: this is the capability study. The study was performed on 450 head and neck beams and on 100 prostate beams. Control charts, showing drifts, both slow and weak, and also both strong and fast, of mean and standard deviation have been established and have shown special cause introduced (manual shift of the leaf gap of the multileaf collimator). Correlation between dose measured at one point, given with the EPID and the ionisation chamber has been evaluated at more than 97% and disagreement cases between the two measurements were identified. The study allowed to demonstrate the feasibility to reduce the time devoted to
International Nuclear Information System (INIS)
Villani, N.; Noel, A.; Villani, N.; Gerard, K.; Marchesi, V.; Huger, S.; Noel, A.; Francois, P.
2010-01-01
Purpose The first purpose of this study was to illustrate the contribution of statistical process control for a better security in intensity modulated radiotherapy (I.M.R.T.) treatments. This improvement is possible by controlling the dose delivery process, characterized by pretreatment quality control results. So, it is necessary to put under control portal dosimetry measurements (currently, the ionisation chamber measurements were already monitored by statistical process control thanks to statistical process control tools). The second objective was to state whether it is possible to substitute ionisation chamber with portal dosimetry in order to optimize time devoted to pretreatment quality control. Patients and methods At Alexis-Vautrin center, pretreatment quality controls in I.M.R.T. for prostate and head and neck treatments were performed for each beam of each patient. These controls were made with an ionisation chamber, which is the reference detector for the absolute dose measurement, and with portal dosimetry for the verification of dose distribution. Statistical process control is a statistical analysis method, coming from industry, used to control and improve the studied process quality. It uses graphic tools as control maps to follow-up process, warning the operator in case of failure, and quantitative tools to evaluate the process toward its ability to respect guidelines: this is the capability study. The study was performed on 450 head and neck beams and on 100 prostate beams. Results Control charts, showing drifts, both slow and weak, and also both strong and fast, of mean and standard deviation have been established and have shown special cause introduced (manual shift of the leaf gap of the multi-leaf collimator). Correlation between dose measured at one point, given with the E.P.I.D. and the ionisation chamber has been evaluated at more than 97% and disagreement cases between the two measurements were identified. Conclusion The study allowed to
Operational statistical analysis of the results of computer-based testing of students
Directory of Open Access Journals (Sweden)
Виктор Иванович Нардюжев
2018-12-01
Full Text Available The article is devoted to the issues of statistical analysis of results of computer-based testing for evaluation of educational achievements of students. The issues are relevant due to the fact that computerbased testing in Russian universities has become an important method for evaluation of educational achievements of students and quality of modern educational process. Usage of modern methods and programs for statistical analysis of results of computer-based testing and assessment of quality of developed tests is an actual problem for every university teacher. The article shows how the authors solve this problem using their own program “StatInfo”. For several years the program has been successfully applied in a credit system of education at such technological stages as loading computerbased testing protocols into a database, formation of queries, generation of reports, lists, and matrices of answers for statistical analysis of quality of test items. Methodology, experience and some results of its usage by university teachers are described in the article. Related topics of a test development, models, algorithms, technologies, and software for large scale computer-based testing has been discussed by the authors in their previous publications which are presented in the reference list.
Process-based organization design and hospital efficiency.
Vera, Antonio; Kuntz, Ludwig
2007-01-01
The central idea of process-based organization design is that organizing a firm around core business processes leads to cost reductions and quality improvements. We investigated theoretically and empirically whether the implementation of a process-based organization design is advisable in hospitals. The data came from a database compiled by the Statistical Office of the German federal state of Rheinland-Pfalz and from a written questionnaire, which was sent to the chief executive officers (CEOs) of all 92 hospitals in this federal state. We used data envelopment analysis (DEA) to measure hospital efficiency, and factor analysis and regression analysis to test our hypothesis. Our principal finding is that a high degree of process-based organization has a moderate but significant positive effect on the efficiency of hospitals. The main implication is that hospitals should implement a process-based organization to improve their efficiency. However, to actually achieve positive effects on efficiency, it is of paramount importance to observe some implementation rules, in particular to mobilize physician participation and to create an adequate organizational culture.
Statistics to the Rescue!: Using Data to Evaluate a Manufacturing Process
Keithley, Michael G.
2009-01-01
The use of statistics and process controls is too often overlooked in educating students. This article describes an activity appropriate for high school students who have a background in material processing. It gives them a chance to advance their knowledge by determining whether or not a manufacturing process works well. The activity follows a…
Directory of Open Access Journals (Sweden)
Fahad A Al-Hussein
2009-01-01
Conclusions: A process of audits in the context of statistical process control is necessary for any improvement in the implementation of guidelines in primary care. Statistical process control charts are an effective means of visual feedback to the care providers.
Mezzenga, Emilio; D'Errico, Vincenzo; Sarnelli, Anna; Strigari, Lidia; Menghi, Enrico; Marcocci, Francesco; Bianchini, David; Benassi, Marcello
2016-01-01
The purpose of this study was to retrospectively evaluate the results from a Helical TomoTherapy Hi-Art treatment system relating to quality controls based on daily static and dynamic output checks using statistical process control methods. Individual value X-charts, exponentially weighted moving average charts, and process capability and acceptability indices were used to monitor the treatment system performance. Daily output values measured from January 2014 to January 2015 were considered. The results obtained showed that, although the process was in control, there was an out-of-control situation in the principal maintenance intervention for the treatment system. In particular, process capability indices showed a decreasing percentage of points in control which was, however, acceptable according to AAPM TG148 guidelines. Our findings underline the importance of restricting the acceptable range of daily output checks and suggest a future line of investigation for a detailed process control of daily output checks for the Helical TomoTherapy Hi-Art treatment system.
Using Statistical Process Control Methods to Classify Pilot Mental Workloads
National Research Council Canada - National Science Library
Kudo, Terence
2001-01-01
.... These include cardiac, ocular, respiratory, and brain activity measures. The focus of this effort is to apply statistical process control methodology on different psychophysiological features in an attempt to classify pilot mental workload...
Obtaining Internet Flow Statistics by Volunteer-Based System
DEFF Research Database (Denmark)
Pedersen, Jens Myrup; Bujlow, Tomasz
2012-01-01
In this paper we demonstrate how the Volunteer Based System for Research on the Internet, developed at Aalborg University, can be used for creating statistics of Internet usage. Since the data is collected on individual machines, the statistics can be made on the basis of both individual users......, and average flow durations. The paper is concluded with a discussion on what further statistics can be made, and the further development of the system....
Statistical process control for radiotherapy quality assurance
International Nuclear Information System (INIS)
Pawlicki, Todd; Whitaker, Matthew; Boyer, Arthur L.
2005-01-01
Every quality assurance process uncovers random and systematic errors. These errors typically consist of many small random errors and a very few number of large errors that dominate the result. Quality assurance practices in radiotherapy do not adequately differentiate between these two sources of error. The ability to separate these types of errors would allow the dominant source(s) of error to be efficiently detected and addressed. In this work, statistical process control is applied to quality assurance in radiotherapy for the purpose of setting action thresholds that differentiate between random and systematic errors. The theoretical development and implementation of process behavior charts are described. We report on a pilot project is which these techniques are applied to daily output and flatness/symmetry quality assurance for a 10 MV photon beam in our department. This clinical case was followed over 52 days. As part of our investigation, we found that action thresholds set using process behavior charts were able to identify systematic changes in our daily quality assurance process. This is in contrast to action thresholds set using the standard deviation, which did not identify the same systematic changes in the process. The process behavior thresholds calculated from a subset of the data detected a 2% change in the process whereas with a standard deviation calculation, no change was detected. Medical physicists must make decisions on quality assurance data as it is acquired. Process behavior charts help decide when to take action and when to acquire more data before making a change in the process
Statistical models based on conditional probability distributions
International Nuclear Information System (INIS)
Narayanan, R.S.
1991-10-01
We present a formulation of statistical mechanics models based on conditional probability distribution rather than a Hamiltonian. We show that it is possible to realize critical phenomena through this procedure. Closely linked with this formulation is a Monte Carlo algorithm, in which a configuration generated is guaranteed to be statistically independent from any other configuration for all values of the parameters, in particular near the critical point. (orig.)
On the structure of dynamic principal component analysis used in statistical process monitoring
DEFF Research Database (Denmark)
Vanhatalo, Erik; Kulahci, Murat; Bergquist, Bjarne
2017-01-01
When principal component analysis (PCA) is used for statistical process monitoring it relies on the assumption that data are time independent. However, industrial data will often exhibit serial correlation. Dynamic PCA (DPCA) has been suggested as a remedy for high-dimensional and time...... for determining the number of principal components to retain. The number of retained principal components is determined by visual inspection of the serial correlation in the squared prediction error statistic, Q (SPE), together with the cumulative explained variance of the model. The methods are illustrated using...... driven method to determine the maximum number of lags in DPCA with a foundation in multivariate time series analysis. The method is based on the behavior of the eigenvalues of the lagged autocorrelation and partial autocorrelation matrices. Given a specific lag structure we also propose a method...
2015-03-26
universal definition” (Evans & Lindsay, 1996). Heizer and Render (2010) argue that several definitions of this term are user-based, meaning, that quality...for example, really good ice cream has high butterfat levels.” ( Heizer & Render , 2010). Garvin, in his Competing in Eight Dimensions of Quality...Montgomery, 2005). As for definition purposes, the concept adopted by this research was provided by Heizer and Render (2010), for whom Statistical Process
Radiographic rejection index using statistical process control
International Nuclear Information System (INIS)
Savi, M.B.M.B.; Camozzato, T.S.C.; Soares, F.A.P.; Nandi, D.M.
2015-01-01
The Repeat Analysis Index (IRR) is one of the items contained in the Quality Control Program dictated by brazilian law of radiological protection and should be performed frequently, at least every six months. In order to extract more and better information of IRR, this study presents the Statistical Quality Control applied to reject rate through Statistical Process Control (Control Chart for Attributes ρ - GC) and the Pareto Chart (GP). Data collection was performed for 9 months and the last four months of collection was given on a daily basis. The Limits of Control (LC) were established and Minitab 16 software used to create the charts. IRR obtained for the period was corresponding to 8.8% ± 2,3% and the generated charts analyzed. Relevant information such as orders for X-ray equipment and processors were crossed to identify the relationship between the points that exceeded the control limits and the state of equipment at the time. The GC demonstrated ability to predict equipment failures, as well as the GP showed clearly what causes are recurrent in IRR. (authors) [pt
Testing for Statistical Discrimination based on Gender
Lesner, Rune Vammen
2016-01-01
This paper develops a model which incorporates the two most commonly cited strands of the literature on statistical discrimination, namely screening discrimination and stereotyping. The model is used to provide empirical evidence of statistical discrimination based on gender in the labour market. It is shown that the implications of both screening discrimination and stereotyping are consistent with observable wage dynamics. In addition, it is found that the gender wage gap decreases in tenure...
Steganalysis based on reducing the differences of image statistical characteristics
Wang, Ran; Niu, Shaozhang; Ping, Xijian; Zhang, Tao
2018-04-01
Compared with the process of embedding, the image contents make a more significant impact on the differences of image statistical characteristics. This makes the image steganalysis to be a classification problem with bigger withinclass scatter distances and smaller between-class scatter distances. As a result, the steganalysis features will be inseparate caused by the differences of image statistical characteristics. In this paper, a new steganalysis framework which can reduce the differences of image statistical characteristics caused by various content and processing methods is proposed. The given images are segmented to several sub-images according to the texture complexity. Steganalysis features are separately extracted from each subset with the same or close texture complexity to build a classifier. The final steganalysis result is figured out through a weighted fusing process. The theoretical analysis and experimental results can demonstrate the validity of the framework.
Time Series Analysis Based on Running Mann Whitney Z Statistics
A sensitive and objective time series analysis method based on the calculation of Mann Whitney U statistics is described. This method samples data rankings over moving time windows, converts those samples to Mann-Whitney U statistics, and then normalizes the U statistics to Z statistics using Monte-...
Rolinski, S.; Müller, C.; Lotze-Campen, H.; Bondeau, A.
2010-12-01
More than a quarter of the Earth’s land surface is covered by grassland, which is also the major part (~ 70 %) of the agricultural area. Most of this area is used for livestock production in different degrees of intensity. The dynamic global vegetation model LPJmL (Sitch et al., Global Change Biology, 2003; Bondeau et al., Global Change Biology, 2007) is one of few process-based model that simulates biomass production on managed grasslands at the global scale. The implementation of managed grasslands and its evaluation has received little attention so far, as reference data on grassland productivity are scarce and the definition of grassland extent and usage are highly uncertain. However, grassland productivity is related to large areas, and strongly influences global estimates of carbon and water budgets and should thus be improved. Plants are implemented in LPJmL in an aggregated form as plant functional types assuming that processes concerning carbon and water fluxes are quite similar between species of the same type. Therefore, the parameterization of a functional type is possible with parameters in a physiologically meaningful range of values. The actual choice of the parameter values from the possible and reasonable phase space should satisfy the condition of the best fit of model results and measured data. In order to improve the parameterization of managed grass we follow a combined procedure using model output and measured data of carbon and water fluxes. By comparing carbon and water fluxes simultaneously, we expect well-balanced refinements and avoid over-tuning of the model in only one direction. The comparison of annual biomass from grassland to data from the Food and Agriculture Organization of the United Nations (FAO) per country provide an overview about the order of magnitude and the identification of deviations. The comparison of daily net primary productivity, soil respiration and water fluxes at specific sites (FluxNet Data) provides
Process simulation and statistical approaches for validating waste form qualification models
International Nuclear Information System (INIS)
Kuhn, W.L.; Toland, M.R.; Pulsipher, B.A.
1989-05-01
This report describes recent progress toward one of the principal objectives of the Nuclear Waste Treatment Program (NWTP) at the Pacific Northwest Laboratory (PNL): to establish relationships between vitrification process control and glass product quality. during testing of a vitrification system, it is important to show that departures affecting the product quality can be sufficiently detected through process measurements to prevent an unacceptable canister from being produced. Meeting this goal is a practical definition of a successful sampling, data analysis, and process control strategy. A simulation model has been developed and preliminarily tested by applying it to approximate operation of the West Valley Demonstration Project (WVDP) vitrification system at West Valley, New York. Multivariate statistical techniques have been identified and described that can be applied to analyze large sets of process measurements. Information on components, tanks, and time is then combined to create a single statistic through which all of the information can be used at once to determine whether the process has shifted away from a normal condition
Reaming process improvement and control: An application of statistical engineering
DEFF Research Database (Denmark)
Müller, Pavel; Genta, G.; Barbato, G.
2012-01-01
A reaming operation had to be performed within given technological and economical constraints. Process improvement under realistic conditions was the goal of a statistical engineering project, supported by a comprehensive experimental investigation providing detailed information on single...
Hutchens, Dale E.; Doan, Patrick A.; Boothe, Richard E.
1997-01-01
Bonding labs at both MSFC and the northern Utah production plant prepare bond test specimens which simulate or witness the production of NASA's Reusable Solid Rocket Motor (RSRM). The current process for preparing the bonding surfaces employs 1,1,1-trichloroethane vapor degreasing, which simulates the current RSRM process. Government regulations (e.g., the 1990 Amendments to the Clean Air Act) have mandated a production phase-out of a number of ozone depleting compounds (ODC) including 1,1,1-trichloroethane. In order to comply with these regulations, the RSRM Program is qualifying a spray-in-air (SIA) precision cleaning process using Brulin 1990, an aqueous blend of surfactants. Accordingly, surface preparation prior to bonding process simulation test specimens must reflect the new production cleaning process. The Bonding Lab Statistical Process Control (SPC) program monitors the progress of the lab and its capabilities, as well as certifies the bonding technicians, by periodically preparing D6AC steel tensile adhesion panels with EA-91 3NA epoxy adhesive using a standardized process. SPC methods are then used to ensure the process is statistically in control, thus producing reliable data for bonding studies, and identify any problems which might develop. Since the specimen cleaning process is being changed, new SPC limits must be established. This report summarizes side-by-side testing of D6AC steel tensile adhesion witness panels and tapered double cantilevered beams (TDCBs) using both the current baseline vapor degreasing process and a lab-scale spray-in-air process. A Proceco 26 inches Typhoon dishwasher cleaned both tensile adhesion witness panels and TDCBs in a process which simulates the new production process. The tests were performed six times during 1995, subsequent statistical analysis of the data established new upper control limits (UCL) and lower control limits (LCL). The data also demonstrated that the new process was equivalent to the vapor
Security of statistical data bases: invasion of privacy through attribute correlational modeling
Energy Technology Data Exchange (ETDEWEB)
Palley, M.A.
1985-01-01
This study develops, defines, and applies a statistical technique for the compromise of confidential information in a statistical data base. Attribute Correlational Modeling (ACM) recognizes that the information contained in a statistical data base represents real world statistical phenomena. As such, ACM assumes correlational behavior among the database attributes. ACM proceeds to compromise confidential information through creation of a regression model, where the confidential attribute is treated as the dependent variable. The typical statistical data base may preclude the direct application of regression. In this scenario, the research introduces the notion of a synthetic data base, created through legitimate queries of the actual data base, and through proportional random variation of responses to these queries. The synthetic data base is constructed to resemble the actual data base as closely as possible in a statistical sense. ACM then applies regression analysis to the synthetic data base, and utilizes the derived model to estimate confidential information in the actual database.
Moore, Sarah J; Herst, Patries M; Louwe, Robert J W
2018-05-01
A remarkable improvement in patient positioning was observed after the implementation of various process changes aiming to increase the consistency of patient positioning throughout the radiotherapy treatment chain. However, no tool was available to describe these changes over time in a standardised way. This study reports on the feasibility of Statistical Process Control (SPC) to highlight changes in patient positioning accuracy and facilitate correlation of these changes with the underlying process changes. Metrics were designed to quantify the systematic and random patient deformation as input for the SPC charts. These metrics were based on data obtained from multiple local ROI matches for 191 patients who were treated for head-and-neck cancer during the period 2011-2016. SPC highlighted a significant improvement in patient positioning that coincided with multiple intentional process changes. The observed improvements could be described as a combination of a reduction in outliers and a systematic improvement in the patient positioning accuracy of all patients. SPC is able to track changes in the reproducibility of patient positioning in head-and-neck radiation oncology, and distinguish between systematic and random process changes. Identification of process changes underlying these trends requires additional statistical analysis and seems only possible when the changes do not overlap in time. Copyright © 2018 Elsevier B.V. All rights reserved.
Tungsten Ions in Plasmas: Statistical Theory of Radiative-Collisional Processes
Directory of Open Access Journals (Sweden)
Alexander V. Demura
2015-05-01
Full Text Available The statistical model for calculations of the collisional-radiative processes in plasmas with tungsten impurity was developed. The electron structure of tungsten multielectron ions is considered in terms of both the Thomas-Fermi model and the Brandt-Lundquist model of collective oscillations of atomic electron density. The excitation or ionization of atomic electrons by plasma electron impacts are represented as photo-processes under the action of flux of equivalent photons introduced by E. Fermi. The total electron impact single ionization cross-sections of ions Wk+ with respective rates have been calculated and compared with the available experimental and modeling data (e.g., CADW. Plasma radiative losses on tungsten impurity were also calculated in a wide range of electron temperatures 1 eV–20 keV. The numerical code TFATOM was developed for calculations of radiative-collisional processes involving tungsten ions. The needed computational resources for TFATOM code are orders of magnitudes less than for the other conventional numerical codes. The transition from corona to Boltzmann limit was investigated in detail. The results of statistical approach have been tested by comparison with the vast experimental and conventional code data for a set of ions Wk+. It is shown that the universal statistical model accuracy for the ionization cross-sections and radiation losses is within the data scattering of significantly more complex quantum numerical codes, using different approximations for the calculation of atomic structure and the electronic cross-sections.
Statistical Multipath Model Based on Experimental GNSS Data in Static Urban Canyon Environment
Directory of Open Access Journals (Sweden)
Yuze Wang
2018-04-01
Full Text Available A deep understanding of multipath characteristics is essential to design signal simulators and receivers in global navigation satellite system applications. As a new constellation is deployed and more applications occur in the urban environment, the statistical multipath models of navigation signal need further study. In this paper, we present statistical distribution models of multipath time delay, multipath power attenuation, and multipath fading frequency based on the experimental data in the urban canyon environment. The raw data of multipath characteristics are obtained by processing real navigation signal to study the statistical distribution. By fitting the statistical data, it shows that the probability distribution of time delay follows a gamma distribution which is related to the waiting time of Poisson distributed events. The fading frequency follows an exponential distribution, and the mean of multipath power attenuation decreases linearly with an increasing time delay. In addition, the detailed statistical characteristics for different elevations and orbits satellites is studied, and the parameters of each distribution are quite different. The research results give useful guidance for navigation simulator and receiver designers.
Olimpo, Jeffrey T; Pevey, Ryan S; McCabe, Thomas M
2018-01-01
Course-based undergraduate research experiences (CUREs) provide an avenue for student participation in authentic scientific opportunities. Within the context of such coursework, students are often expected to collect, analyze, and evaluate data obtained from their own investigations. Yet, limited research has been conducted that examines mechanisms for supporting students in these endeavors. In this article, we discuss the development and evaluation of an interactive statistics workshop that was expressly designed to provide students with an open platform for graduate teaching assistant (GTA)-mentored data processing, statistical testing, and synthesis of their own research findings. Mixed methods analyses of pre/post-intervention survey data indicated a statistically significant increase in students' reasoning and quantitative literacy abilities in the domain, as well as enhancement of student self-reported confidence in and knowledge of the application of various statistical metrics to real-world contexts. Collectively, these data reify an important role for scaffolded instruction in statistics in preparing emergent scientists to be data-savvy researchers in a globally expansive STEM workforce.
Burggraeve, A; Van den Kerkhof, T; Hellings, M; Remon, J P; Vervaet, C; De Beer, T
2011-04-18
Fluid bed granulation is a batch process, which is characterized by the processing of raw materials for a predefined period of time, consisting of a fixed spraying phase and a subsequent drying period. The present study shows the multivariate statistical modeling and control of a fluid bed granulation process based on in-line particle size distribution (PSD) measurements (using spatial filter velocimetry) combined with continuous product temperature registration using a partial least squares (PLS) approach. Via the continuous in-line monitoring of the PSD and product temperature during granulation of various reference batches, a statistical batch model was developed allowing the real-time evaluation and acceptance or rejection of future batches. Continuously monitored PSD and product temperature process data of 10 reference batches (X-data) were used to develop a reference batch PLS model, regressing the X-data versus the batch process time (Y-data). Two PLS components captured 98.8% of the variation in the X-data block. Score control charts in which the average batch trajectory and upper and lower control limits are displayed were developed. Next, these control charts were used to monitor 4 new test batches in real-time and to immediately detect any deviations from the expected batch trajectory. By real-time evaluation of new batches using the developed control charts and by computation of contribution plots of deviating process behavior at a certain time point, batch losses or reprocessing can be prevented. Immediately after batch completion, all PSD and product temperature information (i.e., a batch progress fingerprint) was used to estimate some granule properties (density and flowability) at an early stage, which can improve batch release time. Individual PLS models relating the computed scores (X) of the reference PLS model (based on the 10 reference batches) and the density, respectively, flowabililty as Y-matrix, were developed. The scores of the 4 test
Software development for statistical handling of dosimetric and epidemiological data base
International Nuclear Information System (INIS)
Amaro, M.
1990-01-01
The dose records from different groups of occupationally exposed workers are available in a computerized data base whose main purpose is the individual dose follow-up. Apart from this objective, such a dosimetric data base can be useful to obtain statistical analysis. The type of statistical n formation that can be extracted from the data base may aim to attain mainly two kinds of objectives: - Individual and collective dose distributions and statistics. -Epidemiological statistics. The report describes the software developed to obtain the statistical reports required by the Regulatory Body, as well as any other type of dose distributions or statistics to be included in epidemiological studies A Users Guide for the operators who handle this software package, and the codes listings, are also included in the report. (Author) 2 refs
Software development for statistical handling of dosimetric and epidemiological data base
International Nuclear Information System (INIS)
Amaro, M.
1990-01-01
The dose records from different group of occupationally exposed workers are available in a computerized data base whose main purpose is the individual dose follow-up. Apart from this objective, such a dosimetric data base can be useful to obtain statistical analysis. The type of statistical information that can be extracted from the data base may aim to attain mainly two kinds of obsectives: - Individual and collective dose distributions and statistics. - Epidemiological statistics. The report describes the software developed to obtain the statistical reports required by the Regulatory Body, as well as any other type of dose distributions or statistics to be included in epidsemiological studies. A Users Guide for the operators who handle this sofware package, and the codes listings, are also included in the report. (Author)
Informing Evidence Based Decisions: Usage Statistics for Online Journal Databases
Directory of Open Access Journals (Sweden)
Alexei Botchkarev
2017-06-01
Full Text Available Abstract Objective – The primary objective was to examine online journal database usage statistics for a provincial ministry of health in the context of evidence based decision-making. In addition, the study highlights implementation of the Journal Access Centre (JAC that is housed and powered by the Ontario Ministry of Health and Long-Term Care (MOHLTC to inform health systems policy-making. Methods – This was a prospective case study using descriptive analysis of the JAC usage statistics of journal articles from January 2009 to September 2013. Results – JAC enables ministry employees to access approximately 12,000 journals with full-text articles. JAC usage statistics for the 2011-2012 calendar years demonstrate a steady level of activity in terms of searches, with monthly averages of 5,129. In 2009-2013, a total of 4,759 journal titles were accessed including 1,675 journals with full-text. Usage statistics demonstrate that the actual consumption was over 12,790 full-text downloaded articles or approximately 2,700 articles annually. Conclusion – JAC’s steady level of activities, revealed by the study, reflects continuous demand for JAC services and products. It testifies that access to online journal databases has become part of routine government knowledge management processes. MOHLTC’s broad area of responsibilities with dynamically changing priorities translates into the diverse information needs of its employees and a large set of required journals. Usage statistics indicate that MOHLTC information needs cannot be mapped to a reasonably compact set of “core” journals with a subsequent subscription to those.
National Research Council Canada - National Science Library
Willsky, Alan
2004-01-01
.... Our research blends methods from several fields-statistics and probability, signal and image processing, mathematical physics, scientific computing, statistical learning theory, and differential...
International Nuclear Information System (INIS)
Drecker, St.; Hoff, A.; Dietrich, M.; Guldner, R.
1999-01-01
Statistical Process Control (SPC) is one of the systematic tools to perform a valuable contribution to the control and planning activities for manufacturing processes and product quality. Advanced Nuclear Fuels GmbH (ANF) started a program to introduce SPC in all sections of the manufacturing process of fuel assemblies. The concept phase is based on a realization of SPC in 3 pilot projects. The existing manufacturing devices are reviewed for the utilization of SPC. Subsequent modifications were made to provide the necessary interfaces. The processes 'powder/pellet manufacturing'. 'cladding tube manufacturing' and 'laser-welding of spacers' are located at the different locations of ANF. Due to the completion of the first steps and the experience obtained by the pilot projects, the introduction program for SPC has already been extended to other manufacturing processes. (authors)
Directory of Open Access Journals (Sweden)
Sean Ekins
Full Text Available Dispensing and dilution processes may profoundly influence estimates of biological activity of compounds. Published data show Ephrin type-B receptor 4 IC50 values obtained via tip-based serial dilution and dispensing versus acoustic dispensing with direct dilution differ by orders of magnitude with no correlation or ranking of datasets. We generated computational 3D pharmacophores based on data derived by both acoustic and tip-based transfer. The computed pharmacophores differ significantly depending upon dispensing and dilution methods. The acoustic dispensing-derived pharmacophore correctly identified active compounds in a subsequent test set where the tip-based method failed. Data from acoustic dispensing generates a pharmacophore containing two hydrophobic features, one hydrogen bond donor and one hydrogen bond acceptor. This is consistent with X-ray crystallography studies of ligand-protein interactions and automatically generated pharmacophores derived from this structural data. In contrast, the tip-based data suggest a pharmacophore with two hydrogen bond acceptors, one hydrogen bond donor and no hydrophobic features. This pharmacophore is inconsistent with the X-ray crystallographic studies and automatically generated pharmacophores. In short, traditional dispensing processes are another important source of error in high-throughput screening that impacts computational and statistical analyses. These findings have far-reaching implications in biological research.
Statistical Process Control. A Summary. FEU/PICKUP Project Report.
Owen, M.; Clark, I.
A project was conducted to develop a curriculum and training materials to be used in training industrial operatives in statistical process control (SPC) techniques. During the first phase of the project, questionnaires were sent to 685 companies (215 of which responded) to determine where SPC was being used, what type of SPC firms needed, and how…
A generic statistical methodology to predict the maximum pit depth of a localized corrosion process
International Nuclear Information System (INIS)
Jarrah, A.; Bigerelle, M.; Guillemot, G.; Najjar, D.; Iost, A.; Nianga, J.-M.
2011-01-01
Highlights: → We propose a methodology to predict the maximum pit depth in a corrosion process. → Generalized Lambda Distribution and the Computer Based Bootstrap Method are combined. → GLD fit a large variety of distributions both in their central and tail regions. → Minimum thickness preventing perforation can be estimated with a safety margin. → Considering its applications, this new approach can help to size industrial pieces. - Abstract: This paper outlines a new methodology to predict accurately the maximum pit depth related to a localized corrosion process. It combines two statistical methods: the Generalized Lambda Distribution (GLD), to determine a model of distribution fitting with the experimental frequency distribution of depths, and the Computer Based Bootstrap Method (CBBM), to generate simulated distributions equivalent to the experimental one. In comparison with conventionally established statistical methods that are restricted to the use of inferred distributions constrained by specific mathematical assumptions, the major advantage of the methodology presented in this paper is that both the GLD and the CBBM enable a statistical treatment of the experimental data without making any preconceived choice neither on the unknown theoretical parent underlying distribution of pit depth which characterizes the global corrosion phenomenon nor on the unknown associated theoretical extreme value distribution which characterizes the deepest pits. Considering an experimental distribution of depths of pits produced on an aluminium sample, estimations of maximum pit depth using a GLD model are compared to similar estimations based on usual Gumbel and Generalized Extreme Value (GEV) methods proposed in the corrosion engineering literature. The GLD approach is shown having smaller bias and dispersion in the estimation of the maximum pit depth than the Gumbel approach both for its realization and mean. This leads to comparing the GLD approach to the GEV one
Statistical Outlier Detection for Jury Based Grading Systems
DEFF Research Database (Denmark)
Thompson, Mary Kathryn; Clemmensen, Line Katrine Harder; Rosas, Harvey
2013-01-01
This paper presents an algorithm that was developed to identify statistical outliers from the scores of grading jury members in a large project-based first year design course. The background and requirements for the outlier detection system are presented. The outlier detection algorithm...... and the follow-up procedures for score validation and appeals are described in detail. Finally, the impact of various elements of the outlier detection algorithm, their interactions, and the sensitivity of their numerical values are investigated. It is shown that the difference in the mean score produced...... by a grading jury before and after a suspected outlier is removed from the mean is the single most effective criterion for identifying potential outliers but that all of the criteria included in the algorithm have an effect on the outlier detection process....
A quantum computer based on recombination processes in microelectronic devices
International Nuclear Information System (INIS)
Theodoropoulos, K; Ntalaperas, D; Petras, I; Konofaos, N
2005-01-01
In this paper a quantum computer based on the recombination processes happening in semiconductor devices is presented. A 'data element' and a 'computational element' are derived based on Schokley-Read-Hall statistics and they can later be used to manifest a simple and known quantum computing process. Such a paradigm is shown by the application of the proposed computer onto a well known physical system involving traps in semiconductor devices
Hazard rate model and statistical analysis of a compound point process
Czech Academy of Sciences Publication Activity Database
Volf, Petr
2005-01-01
Roč. 41, č. 6 (2005), s. 773-786 ISSN 0023-5954 R&D Projects: GA ČR(CZ) GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : couting process * compound process * Cox regression model * intensity Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.343, year: 2005
Dupont, Corinne; Occelli, Pauline; Deneux-Tharaux, Catherine; Touzet, Sandrine; Duclos, Antoine; Bouvier-Colle, Marie-Hélène; Rudigoz, René-Charles; Huissoud, Cyril
2014-07-01
Severe postpartum haemorrhage after vaginal delivery: a statistical process control chart to report seven years of continuous quality improvement To use statistical process control charts to describe trends in the prevalence of severe postpartum haemorrhage after vaginal delivery. This assessment was performed 7 years after we initiated a continuous quality improvement programme that began with regular criteria-based audits Observational descriptive study, in a French maternity unit in the Rhône-Alpes region. Quarterly clinical audit meetings to analyse all cases of severe postpartum haemorrhage after vaginal delivery and provide feedback on quality of care with statistical process control tools. The primary outcomes were the prevalence of severe PPH after vaginal delivery and its quarterly monitoring with a control chart. The secondary outcomes included the global quality of care for women with severe postpartum haemorrhage, including the performance rate of each recommended procedure. Differences in these variables between 2005 and 2012 were tested. From 2005 to 2012, the prevalence of severe postpartum haemorrhage declined significantly, from 1.2% to 0.6% of vaginal deliveries (pcontrol limits, that is, been out of statistical control. The proportion of cases that were managed consistently with the guidelines increased for all of their main components. Implementation of continuous quality improvement efforts began seven years ago and used, among other tools, statistical process control charts. During this period, the prevalence of severe postpartum haemorrhage after vaginal delivery has been reduced by 50%. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Statistical Process Control Charts for Measuring and Monitoring Temporal Consistency of Ratings
Omar, M. Hafidz
2010-01-01
Methods of statistical process control were briefly investigated in the field of educational measurement as early as 1999. However, only the use of a cumulative sum chart was explored. In this article other methods of statistical quality control are introduced and explored. In particular, methods in the form of Shewhart mean and standard deviation…
International Nuclear Information System (INIS)
Sen, Biswajit; Mandal, Swapan
2007-01-01
An initially prepared coherent state coupled to a second-order nonlinear medium is responsible for stimulated and spontaneous hyper Raman processes. By using an intuitive approach based on perturbation theory, the Hamiltonian corresponding to the hyper Raman processes is analytically solved to obtain the temporal development of the field operators. It is true that these analytical solutions are valid for small coupling constants. However, the interesting part is that these solutions are valid for reasonably large time. Hence, the present analytical solutions are quite general and are fresh compared to those solutions under short-time approximations. By exploiting the analytical solutions of field operators for various modes, we investigate the squeezing, photon antibunching and nonclassical photon statistics for pure modes of the input coherent light responsible for hyper Raman processes. At least in one instance (stimulated hyper Raman processes for vibration phonon mode), we report the simultaneous appearance of classical (photon bunching) and nonclassical (squeezing) effects of the radiation field responsible for hyper Raman processes
ZnO crystals obtained by electrodeposition: Statistical analysis of most important process variables
International Nuclear Information System (INIS)
Cembrero, Jesus; Busquets-Mataix, David
2009-01-01
In this paper a comparative study by means of a statistical analysis of the main process variables affecting ZnO crystal electrodeposition is presented. ZnO crystals were deposited on two different substrates, silicon wafer and indium tin oxide. The control variables were substrate types, electrolyte concentration, temperature, exposition time and current density. The morphologies of the different substrates were observed using scanning electron microscopy. The percentage of substrate area covered by ZnO deposit was calculated by computational image analysis. The design of the applied experiments was based on a two-level factorial analysis involving a series of 32 experiments and an analysis of variance. Statistical results reveal that variables exerting a significant influence on the area covered by ZnO deposit are electrolyte concentration, substrate type and time of deposition, together with a combined two-factor interaction between temperature and current density. However, morphology is also influenced by surface roughness of the substrates
Olimpo, Jeffrey T.; Pevey, Ryan S.; McCabe, Thomas M.
2018-01-01
Course-based undergraduate research experiences (CUREs) provide an avenue for student participation in authentic scientific opportunities. Within the context of such coursework, students are often expected to collect, analyze, and evaluate data obtained from their own investigations. Yet, limited research has been conducted that examines mechanisms for supporting students in these endeavors. In this article, we discuss the development and evaluation of an interactive statistics workshop that was expressly designed to provide students with an open platform for graduate teaching assistant (GTA)-mentored data processing, statistical testing, and synthesis of their own research findings. Mixed methods analyses of pre/post-intervention survey data indicated a statistically significant increase in students’ reasoning and quantitative literacy abilities in the domain, as well as enhancement of student self-reported confidence in and knowledge of the application of various statistical metrics to real-world contexts. Collectively, these data reify an important role for scaffolded instruction in statistics in preparing emergent scientists to be data-savvy researchers in a globally expansive STEM workforce. PMID:29904549
Safford, Robert R.; Jackson, Andrew E.; Swart, William W.; Barth, Timothy S.
1994-01-01
Successful ground processing at KSC requires that flight hardware and ground support equipment conform to specifications at tens of thousands of checkpoints. Knowledge of conformance is an essential requirement for launch. That knowledge of conformance at every requisite point does not, however, enable identification of past problems with equipment, or potential problem areas. This paper describes how the introduction of Statistical Process Control and Process Capability Analysis identification procedures into existing shuttle processing procedures can enable identification of potential problem areas and candidates for improvements to increase processing performance measures. Results of a case study describing application of the analysis procedures to Thermal Protection System processing are used to illustrate the benefits of the approaches described in the paper.
Babamoradi, Hamid; van den Berg, Frans; Rinnan, Åsmund
2016-02-18
In Multivariate Statistical Process Control, when a fault is expected or detected in the process, contribution plots are essential for operators and optimization engineers in identifying those process variables that were affected by or might be the cause of the fault. The traditional way of interpreting a contribution plot is to examine the largest contributing process variables as the most probable faulty ones. This might result in false readings purely due to the differences in natural variation, measurement uncertainties, etc. It is more reasonable to compare variable contributions for new process runs with historical results achieved under Normal Operating Conditions, where confidence limits for contribution plots estimated from training data are used to judge new production runs. Asymptotic methods cannot provide confidence limits for contribution plots, leaving re-sampling methods as the only option. We suggest bootstrap re-sampling to build confidence limits for all contribution plots in online PCA-based MSPC. The new strategy to estimate CLs is compared to the previously reported CLs for contribution plots. An industrial batch process dataset was used to illustrate the concepts. Copyright © 2016 Elsevier B.V. All rights reserved.
Statistical features of pre-compound processes in nuclear reactions
International Nuclear Information System (INIS)
Hussein, M.S.; Rego, R.A.
1983-04-01
Several statistical aspects of multistep compound processes are discussed. The connection between the cross-section auto-correlation function and the average number of maxima is emphasized. The restrictions imposed by the non-zero value of the energy step used in measuring the excitation fuction and the experimental error are discussed. Applications are made to the system 25 Mg( 3 He,p) 27 Al. (Author) [pt
International Nuclear Information System (INIS)
Pulsipher, B.A.; Kuhn, W.L.
1987-01-01
Current planning for liquid high-level nuclear wastes existing in the United States includes processing in a liquid-fed ceramic melter to incorporate it into a high-quality glass, and placement in a deep geologic repository. The nuclear waste vitrification process requires assurance of a quality product with little or no final inspection. Statistical process control (SPC) is a quantitative approach to one quality assurance aspect of vitrified nuclear waste. This method for monitoring and controlling a process in the presence of uncertainties provides a statistical basis for decisions concerning product quality improvement. Statistical process control is shown to be a feasible and beneficial tool to help the waste glass producers demonstrate that the vitrification process can be controlled sufficiently to produce an acceptable product. This quantitative aspect of quality assurance could be an effective means of establishing confidence in the claims to a quality product
International Nuclear Information System (INIS)
Pulsipher, B.A.; Kuhn, W.L.
1987-02-01
Current planning for liquid high-level nuclear wastes existing in the US includes processing in a liquid-fed ceramic melter to incorporate it into a high-quality glass, and placement in a deep geologic repository. The nuclear waste vitrification process requires assurance of a quality product with little or no final inspection. Statistical process control (SPC) is a quantitative approach to one quality assurance aspect of vitrified nuclear waste. This method for monitoring and controlling a process in the presence of uncertainties provides a statistical basis for decisions concerning product quality improvement. Statistical process control is shown to be a feasible and beneficial tool to help the waste glass producers demonstrate that the vitrification process can be controlled sufficiently to produce an acceptable product. This quantitative aspect of quality assurance could be an effective means of establishing confidence in the claims to a quality product. 2 refs., 4 figs
Impact of Autocorrelation on Principal Components and Their Use in Statistical Process Control
DEFF Research Database (Denmark)
Vanhatalo, Erik; Kulahci, Murat
2015-01-01
A basic assumption when using principal component analysis (PCA) for inferential purposes, such as in statistical process control (SPC), is that the data are independent in time. In many industrial processes, frequent sampling and process dynamics make this assumption unrealistic rendering sampled...
Hybrid perturbation methods based on statistical time series models
San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario
2016-04-01
In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.
Directory of Open Access Journals (Sweden)
Mahmoud Moradi
Full Text Available Abstract In the present research, the simulation of the Nickel-base superalloy Inconel 718 fiber-laser drilling process with the thickness of 1mm is investigated through the Finite Element Method. In order to specify the appropriate Gaussian distribution of laser beam, the results of an experimental research on glass laser drilling were simulated using three types of Gaussian distribution. The DFLUX subroutine was used to implement the laser heat sources of the models using the Fortran language. After the appropriate Gaussian distribution was chosen, the model was validated with the experimental results of the Nickel-base superalloy Inconel 718 laser drilling process. The negligible error percentage among the experimental and simulation results demonstrates the high accuracy of this model. The experiments were performed based on the Response Surface Methodology (RSM as a statistical design of experiment (DOE approach to investigate the influence of process parameters on the responses, obtaining the mathematical regressions and predicting the new results. Four parameters i.e. laser pulse frequency (150 to 550 Hz, laser power (200 to 500 watts, laser focal plane position (-0.5 to +0.5 mm and the duty cycle (30 to 70% were considered to be the input variables in 5 levels and four external parameters i.e. the hole's entrance and exit diameters, hole taper angle and the weight of mass removed from the hole, were observed to be the process output responses of this central composite design. By performing the statistical analysis, the input and output parameters were found to have a direct relation with each other. By an increase in each of the input variables, the entrance and exit hole diameters, the hole taper angel, and the weight of mass removed from the hole increase. Finally, the results of the conducted simulations and statistical analyses having been used, the laser drilling process was optimized by means of the desire ability approach. Good
Mazzitello, Karina I.; Candia, Julián
2012-12-01
In every country, public and private agencies allocate extensive funding to collect large-scale statistical data, which in turn are studied and analyzed in order to determine local, regional, national, and international policies regarding all aspects relevant to the welfare of society. One important aspect of that process is the visualization of statistical data with embedded geographical information, which most often relies on archaic methods such as maps colored according to graded scales. In this work, we apply nonstandard visualization techniques based on physical principles. We illustrate the method with recent statistics on homicide rates in Brazil and their correlation to other publicly available data. This physics-based approach provides a novel tool that can be used by interdisciplinary teams investigating statistics and model projections in a variety of fields such as economics and gross domestic product research, public health and epidemiology, sociodemographics, political science, business and marketing, and many others.
Energy Technology Data Exchange (ETDEWEB)
Jiang, Qingchao; Yan, Xuefeng; Lv, Zhaomin; Guo, Meijin [East China University of Science and Technology, Shanghai (China)
2013-06-15
Considering that kernel entropy component analysis (KECA) is a promising new method of nonlinear data transformation and dimensionality reduction, a KECA based method is proposed for nonlinear chemical process monitoring. In this method, an angle-based statistic is designed because KECA reveals structure related to the Renyi entropy of input space data set, and the transformed data sets are produced with a distinct angle-based structure. Based on the angle difference between normal status and current sample data, the current status can be monitored effectively. And, the confidence limit of the angle-based statistics is determined by kernel density estimation based on sample data of the normal status. The effectiveness of the proposed method is demonstrated by case studies on both a numerical process and a simulated continuous stirred tank reactor (CSTR) process. The KECA based method can be an effective method for nonlinear chemical process monitoring.
International Nuclear Information System (INIS)
Jiang, Qingchao; Yan, Xuefeng; Lv, Zhaomin; Guo, Meijin
2013-01-01
Considering that kernel entropy component analysis (KECA) is a promising new method of nonlinear data transformation and dimensionality reduction, a KECA based method is proposed for nonlinear chemical process monitoring. In this method, an angle-based statistic is designed because KECA reveals structure related to the Renyi entropy of input space data set, and the transformed data sets are produced with a distinct angle-based structure. Based on the angle difference between normal status and current sample data, the current status can be monitored effectively. And, the confidence limit of the angle-based statistics is determined by kernel density estimation based on sample data of the normal status. The effectiveness of the proposed method is demonstrated by case studies on both a numerical process and a simulated continuous stirred tank reactor (CSTR) process. The KECA based method can be an effective method for nonlinear chemical process monitoring
Use of statistic control of the process as part of a quality assurance plan
International Nuclear Information System (INIS)
Acosta, S.; Lewis, C.
2013-01-01
One of the technical requirements of the standard IRAM ISO 17025 for the accreditation of testing laboratories, is the assurance of the quality of the results through the control and monitoring of the factors influencing the reliability of them. The grade the factors contribute to the total measurement uncertainty, determines which of them should be considered when developing a quality assurance plan. The laboratory of environmental measurements of strontium-90 in the accreditation process, performs most of its determinations in samples with values close to the detection limit. For this reason the correct characterization of the white, is a critical parameter and is verified through a letter for statistical process control. The scope of the present work is concerned the control of whites and so it was collected a statistically significant amount of data, for a period of time that is covered of different conditions. This allowed consider significant variables in the process, such as temperature and humidity, and build a graph of white control, which forms the basis of a statistical process control. The data obtained were lower and upper limits for the preparation of the charter white control. In this way the process of characterization of white was considered to operate under statistical control and concludes that it can be used as part of a plan of insurance of the quality
Statistics: a Bayesian perspective
National Research Council Canada - National Science Library
Berry, Donald A
1996-01-01
...: it is the only introductory textbook based on Bayesian ideas, it combines concepts and methods, it presents statistics as a means of integrating data into the significant process, it develops ideas...
Educational Process Material Base
Olga Ozerova; Irina Zabaturina; Vera Kuznetsova; Galina Kovaleva
2012-01-01
Based on the data obtained by the Institute for Statistical Studies and the Economics of Knowledge, National Research University - Higher School of Economics Olga Ozerova - Head of the Department for Statistics of Education, Institute for Statistical Studies and the Economics of Knowledge, National Research University - Higher School of Economics, Moscow, Russian Federation. Email: Address: 18 Myasnitskaya St., Moscow, 101000, Russian Federation.Irina Zabaturina - senior resea...
Gupta, Munish; Kaplan, Heather C
2017-09-01
Quality improvement (QI) is based on measuring performance over time, and variation in data measured over time must be understood to guide change and make optimal improvements. Common cause variation is natural variation owing to factors inherent to any process; special cause variation is unnatural variation owing to external factors. Statistical process control methods, and particularly control charts, are robust tools for understanding data over time and identifying common and special cause variation. This review provides a practical introduction to the use of control charts in health care QI, with a focus on neonatology. Copyright © 2017 Elsevier Inc. All rights reserved.
Statistical inference based on latent ability estimates
Hoijtink, H.J.A.; Boomsma, A.
The quality of approximations to first and second order moments (e.g., statistics like means, variances, regression coefficients) based on latent ability estimates is being discussed. The ability estimates are obtained using either the Rasch, oi the two-parameter logistic model. Straightforward use
Assessment of Problem-Based Learning in the Undergraduate Statistics Course
Karpiak, Christie P.
2011-01-01
Undergraduate psychology majors (N = 51) at a mid-sized private university took a statistics examination on the first day of the research methods course, a course for which a grade of "C" or higher in statistics is a prerequisite. Students who had taken a problem-based learning (PBL) section of the statistics course (n = 15) were compared to those…
Allen, Peter J; Dorozenko, Kate P; Roberts, Lynne D
2016-01-01
should function as a teaching tool, which engages the user with each choice-point in the decision making process, rather than simply providing an "answer." Based on these findings, we offer suggestions for tools and strategies that could be deployed in the research methods classroom to facilitate and strengthen students' statistical decision making abilities.
Reducing lumber thickness variation using real-time statistical process control
Thomas M. Young; Brian H. Bond; Jan Wiedenbeck
2002-01-01
A technology feasibility study for reducing lumber thickness variation was conducted from April 2001 until March 2002 at two sawmills located in the southern U.S. A real-time statistical process control (SPC) system was developed that featured Wonderware human machine interface technology (HMI) with distributed real-time control charts for all sawing centers and...
Implementation of statistical process control for proteomic experiments via LC MS/MS.
Bereman, Michael S; Johnson, Richard; Bollinger, James; Boss, Yuval; Shulman, Nick; MacLean, Brendan; Hoofnagle, Andrew N; MacCoss, Michael J
2014-04-01
Statistical process control (SPC) is a robust set of tools that aids in the visualization, detection, and identification of assignable causes of variation in any process that creates products, services, or information. A tool has been developed termed Statistical Process Control in Proteomics (SProCoP) which implements aspects of SPC (e.g., control charts and Pareto analysis) into the Skyline proteomics software. It monitors five quality control metrics in a shotgun or targeted proteomic workflow. None of these metrics require peptide identification. The source code, written in the R statistical language, runs directly from the Skyline interface, which supports the use of raw data files from several of the mass spectrometry vendors. It provides real time evaluation of the chromatographic performance (e.g., retention time reproducibility, peak asymmetry, and resolution), and mass spectrometric performance (targeted peptide ion intensity and mass measurement accuracy for high resolving power instruments) via control charts. Thresholds are experiment- and instrument-specific and are determined empirically from user-defined quality control standards that enable the separation of random noise and systematic error. Finally, Pareto analysis provides a summary of performance metrics and guides the user to metrics with high variance. The utility of these charts to evaluate proteomic experiments is illustrated in two case studies.
Multivariate statistical process control in product quality review assessment - A case study.
Kharbach, M; Cherrah, Y; Vander Heyden, Y; Bouklouze, A
2017-11-01
According to the Food and Drug Administration and the European Good Manufacturing Practices (GMP) guidelines, Annual Product Review (APR) is a mandatory requirement in GMP. It consists of evaluating a large collection of qualitative or quantitative data in order to verify the consistency of an existing process. According to the Code of Federal Regulation Part 11 (21 CFR 211.180), all finished products should be reviewed annually for the quality standards to determine the need of any change in specification or manufacturing of drug products. Conventional Statistical Process Control (SPC) evaluates the pharmaceutical production process by examining only the effect of a single factor at the time using a Shewhart's chart. It neglects to take into account the interaction between the variables. In order to overcome this issue, Multivariate Statistical Process Control (MSPC) can be used. Our case study concerns an APR assessment, where 164 historical batches containing six active ingredients, manufactured in Morocco, were collected during one year. Each batch has been checked by assaying the six active ingredients by High Performance Liquid Chromatography according to European Pharmacopoeia monographs. The data matrix was evaluated both by SPC and MSPC. The SPC indicated that all batches are under control, while the MSPC, based on Principal Component Analysis (PCA), for the data being either autoscaled or robust scaled, showed four and seven batches, respectively, out of the Hotelling T 2 95% ellipse. Also, an improvement of the capability of the process is observed without the most extreme batches. The MSPC can be used for monitoring subtle changes in the manufacturing process during an APR assessment. Copyright © 2017 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.
Huser, Raphaël
2018-01-09
Extreme-value theory for stochastic processes has motivated the statistical use of max-stable models for spatial extremes. However, fitting such asymptotic models to maxima observed over finite blocks is problematic when the asymptotic stability of the dependence does not prevail in finite samples. This issue is particularly serious when data are asymptotically independent, such that the dependence strength weakens and eventually vanishes as events become more extreme. We here aim to provide flexible sub-asymptotic models for spatially indexed block maxima, which more realistically account for discrepancies between data and asymptotic theory. We develop models pertaining to the wider class of max-infinitely divisible processes, extending the class of max-stable processes while retaining dependence properties that are natural for maxima: max-id models are positively associated, and they yield a self-consistent family of models for block maxima defined over any time unit. We propose two parametric construction principles for max-id models, emphasizing a point process-based generalized spectral representation, that allows for asymptotic independence while keeping the max-stable extremal-$t$ model as a special case. Parameter estimation is efficiently performed by pairwise likelihood, and we illustrate our new modeling framework with an application to Dutch wind gust maxima calculated over different time units.
Assessment of the beryllium lymphocyte proliferation test using statistical process control.
Cher, Daniel J; Deubner, David C; Kelsh, Michael A; Chapman, Pamela S; Ray, Rose M
2006-10-01
Despite more than 20 years of surveillance and epidemiologic studies using the beryllium blood lymphocyte proliferation test (BeBLPT) as a measure of beryllium sensitization (BeS) and as an aid for diagnosing subclinical chronic beryllium disease (CBD), improvements in specific understanding of the inhalation toxicology of CBD have been limited. Although epidemiologic data suggest that BeS and CBD risks vary by process/work activity, it has proven difficult to reach specific conclusions regarding the dose-response relationship between workplace beryllium exposure and BeS or subclinical CBD. One possible reason for this uncertainty could be misclassification of BeS resulting from variation in BeBLPT testing performance. The reliability of the BeBLPT, a biological assay that measures beryllium sensitization, is unknown. To assess the performance of four laboratories that conducted this test, we used data from a medical surveillance program that offered testing for beryllium sensitization with the BeBLPT. The study population was workers exposed to beryllium at various facilities over a 10-year period (1992-2001). Workers with abnormal results were offered diagnostic workups for CBD. Our analyses used a standard statistical technique, statistical process control (SPC), to evaluate test reliability. The study design involved a repeated measures analysis of BeBLPT results generated from the company-wide, longitudinal testing. Analytical methods included use of (1) statistical process control charts that examined temporal patterns of variation for the stimulation index, a measure of cell reactivity to beryllium; (2) correlation analysis that compared prior perceptions of BeBLPT instability to the statistical measures of test variation; and (3) assessment of the variation in the proportion of missing test results and how time periods with more missing data influenced SPC findings. During the period of this study, all laboratories displayed variation in test results that
Directory of Open Access Journals (Sweden)
Zvi H. Perry
2014-01-01
Full Text Available Background. We changed the biostatistics curriculum for our medical students and have created a course entitled “Multivariate analysis of statistical data, using the SPSS package.” Purposes. The aim of this course was to develop students’ skills in computerized data analysis, as well as enhancing their ability to read and interpret statistical data analysis in the literature. Methods. In the current study we have shown that a computer-based course for biostatistics and advanced data analysis is feasible and efficient, using course specific evaluation questionnaires. Results. Its efficacy is both subjective (our subjects felt better prepared to do their theses, as well as to read articles with advanced statistical data analysis and objective (their knowledge of how and when to apply statistical procedures seemed to improve. Conclusions. We showed that a formal evaluative process for such a course is possible and that it enhances the learning experience both for the students and their teachers. In the current study we have shown that a computer-based course for biostatistics and advanced data analysis is feasible and efficient.
Optimizing DNA assembly based on statistical language modelling.
Fang, Gang; Zhang, Shemin; Dong, Yafei
2017-12-15
By successively assembling genetic parts such as BioBrick according to grammatical models, complex genetic constructs composed of dozens of functional blocks can be built. However, usually every category of genetic parts includes a few or many parts. With increasing quantity of genetic parts, the process of assembling more than a few sets of these parts can be expensive, time consuming and error prone. At the last step of assembling it is somewhat difficult to decide which part should be selected. Based on statistical language model, which is a probability distribution P(s) over strings S that attempts to reflect how frequently a string S occurs as a sentence, the most commonly used parts will be selected. Then, a dynamic programming algorithm was designed to figure out the solution of maximum probability. The algorithm optimizes the results of a genetic design based on a grammatical model and finds an optimal solution. In this way, redundant operations can be reduced and the time and cost required for conducting biological experiments can be minimized. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
No-Reference Video Quality Assessment Based on Statistical Analysis in 3D-DCT Domain.
Li, Xuelong; Guo, Qun; Lu, Xiaoqiang
2016-05-13
It is an important task to design models for universal no-reference video quality assessment (NR-VQA) in multiple video processing and computer vision applications. However, most existing NR-VQA metrics are designed for specific distortion types which are not often aware in practical applications. A further deficiency is that the spatial and temporal information of videos is hardly considered simultaneously. In this paper, we propose a new NR-VQA metric based on the spatiotemporal natural video statistics (NVS) in 3D discrete cosine transform (3D-DCT) domain. In the proposed method, a set of features are firstly extracted based on the statistical analysis of 3D-DCT coefficients to characterize the spatiotemporal statistics of videos in different views. These features are used to predict the perceived video quality via the efficient linear support vector regression (SVR) model afterwards. The contributions of this paper are: 1) we explore the spatiotemporal statistics of videos in 3DDCT domain which has the inherent spatiotemporal encoding advantage over other widely used 2D transformations; 2) we extract a small set of simple but effective statistical features for video visual quality prediction; 3) the proposed method is universal for multiple types of distortions and robust to different databases. The proposed method is tested on four widely used video databases. Extensive experimental results demonstrate that the proposed method is competitive with the state-of-art NR-VQA metrics and the top-performing FR-VQA and RR-VQA metrics.
Statistical representation of a spray as a point process
International Nuclear Information System (INIS)
Subramaniam, S.
2000-01-01
The statistical representation of a spray as a finite point process is investigated. One objective is to develop a better understanding of how single-point statistical information contained in descriptions such as the droplet distribution function (ddf), relates to the probability density functions (pdfs) associated with the droplets themselves. Single-point statistical information contained in the droplet distribution function (ddf) is shown to be related to a sequence of single surrogate-droplet pdfs, which are in general different from the physical single-droplet pdfs. It is shown that the ddf contains less information than the fundamental single-point statistical representation of the spray, which is also described. The analysis shows which events associated with the ensemble of spray droplets can be characterized by the ddf, and which cannot. The implications of these findings for the ddf approach to spray modeling are discussed. The results of this study also have important consequences for the initialization and evolution of direct numerical simulations (DNS) of multiphase flows, which are usually initialized on the basis of single-point statistics such as the droplet number density in physical space. If multiphase DNS are initialized in this way, this implies that even the initial representation contains certain implicit assumptions concerning the complete ensemble of realizations, which are invalid for general multiphase flows. Also the evolution of a DNS initialized in this manner is shown to be valid only if an as yet unproven commutation hypothesis holds true. Therefore, it is questionable to what extent DNS that are initialized in this manner constitute a direct simulation of the physical droplets. Implications of these findings for large eddy simulations of multiphase flows are also discussed. (c) 2000 American Institute of Physics
Catelani, Tiago A; Santos, João Rodrigo; Páscoa, Ricardo N M J; Pezza, Leonardo; Pezza, Helena R; Lopes, João A
2018-03-01
This work proposes the use of near infrared (NIR) spectroscopy in diffuse reflectance mode and multivariate statistical process control (MSPC) based on principal component analysis (PCA) for real-time monitoring of the coffee roasting process. The main objective was the development of a MSPC methodology able to early detect disturbances to the roasting process resourcing to real-time acquisition of NIR spectra. A total of fifteen roasting batches were defined according to an experimental design to develop the MSPC models. This methodology was tested on a set of five batches where disturbances of different nature were imposed to simulate real faulty situations. Some of these batches were used to optimize the model while the remaining was used to test the methodology. A modelling strategy based on a time sliding window provided the best results in terms of distinguishing batches with and without disturbances, resourcing to typical MSPC charts: Hotelling's T 2 and squared predicted error statistics. A PCA model encompassing a time window of four minutes with three principal components was able to efficiently detect all disturbances assayed. NIR spectroscopy combined with the MSPC approach proved to be an adequate auxiliary tool for coffee roasters to detect faults in a conventional roasting process in real-time. Copyright © 2017 Elsevier B.V. All rights reserved.
Competent statistical programmer: Need of business process outsourcing industry
Khan, Imran
2014-01-01
Over the last two decades Business Process Outsourcing (BPO) has evolved as much mature practice. India is looked as preferred destination for pharmaceutical outsourcing over a cost arbitrage. Among the biometrics outsourcing, statistical programming and analysis required very niche skill for service delivery. The demand and supply ratios are imbalance due to high churn out rate and less supply of competent programmer. Industry is moving from task delivery to ownership and accountability. The paradigm shift from an outsourcing to consulting is triggering the need for competent statistical programmer. Programmers should be trained in technical, analytical, problem solving, decision making and soft skill as the expectations from the customer are changing from task delivery to accountability of the project. This paper will highlight the common issue SAS programming service industry is facing and skills the programmers need to develop to cope up with these changes. PMID:24987578
Competent statistical programmer: Need of business process outsourcing industry.
Khan, Imran
2014-07-01
Over the last two decades Business Process Outsourcing (BPO) has evolved as much mature practice. India is looked as preferred destination for pharmaceutical outsourcing over a cost arbitrage. Among the biometrics outsourcing, statistical programming and analysis required very niche skill for service delivery. The demand and supply ratios are imbalance due to high churn out rate and less supply of competent programmer. Industry is moving from task delivery to ownership and accountability. The paradigm shift from an outsourcing to consulting is triggering the need for competent statistical programmer. Programmers should be trained in technical, analytical, problem solving, decision making and soft skill as the expectations from the customer are changing from task delivery to accountability of the project. This paper will highlight the common issue SAS programming service industry is facing and skills the programmers need to develop to cope up with these changes.
Competent statistical programmer: Need of business process outsourcing industry
Directory of Open Access Journals (Sweden)
Imran Khan
2014-01-01
Full Text Available Over the last two decades Business Process Outsourcing (BPO has evolved as much mature practice. India is looked as preferred destination for pharmaceutical outsourcing over a cost arbitrage. Among the biometrics outsourcing, statistical programming and analysis required very niche skill for service delivery. The demand and supply ratios are imbalance due to high churn out rate and less supply of competent programmer. Industry is moving from task delivery to ownership and accountability. The paradigm shift from an outsourcing to consulting is triggering the need for competent statistical programmer. Programmers should be trained in technical, analytical, problem solving, decision making and soft skill as the expectations from the customer are changing from task delivery to accountability of the project. This paper will highlight the common issue SAS programming service industry is facing and skills the programmers need to develop to cope up with these changes.
Net analyte signal based statistical quality control
Skibsted, E.T.S.; Boelens, H.F.M.; Westerhuis, J.A.; Smilde, A.K.; Broad, N.W.; Rees, D.R.; Witte, D.T.
2005-01-01
Net analyte signal statistical quality control (NAS-SQC) is a new methodology to perform multivariate product quality monitoring based on the net analyte signal approach. The main advantage of NAS-SQC is that the systematic variation in the product due to the analyte (or property) of interest is
Application of Statistical Process Control (SPC in it´s Quality control
Directory of Open Access Journals (Sweden)
Carlos Hernández-Pedrera
2015-12-01
Full Text Available The overall objective of this paper is to use the SPC to assess the possibility of improving the process of obtaining a sanitary device. As specific objectives we set out to identify the variables to be analyzed to enter the statistical control of process (SPC, analyze possible errors and variations indicated by the control charts in addition to evaluate and compare the results achieved with the study of SPC before and after monitoring direct in the production line were used sampling methods and laboratory replacement to determine the quality of the finished product, then statistical methods were applied seeking to emphasize the importance and contribution from its application to monitor corrective actions and support processes in production. It was shown that the process is under control because the results were found within established control limits. There is a tendency to be displaced toward one end of the boundary, the distribution exceeds the limits, creating the possibility that under certain conditions the process is out of control, the results also showed that the process being within the limits of quality control is operating far from the optimal conditions. In any of the study situations were obtained products outside the limits of weight and discoloration but defective products were obtained.
Statistical error in simulations of Poisson processes: Example of diffusion in solids
Nilsson, Johan O.; Leetmaa, Mikael; Vekilova, Olga Yu.; Simak, Sergei I.; Skorodumova, Natalia V.
2016-08-01
Simulations of diffusion in solids often produce poor statistics of diffusion events. We present an analytical expression for the statistical error in ion conductivity obtained in such simulations. The error expression is not restricted to any computational method in particular, but valid in the context of simulation of Poisson processes in general. This analytical error expression is verified numerically for the case of Gd-doped ceria by running a large number of kinetic Monte Carlo calculations.
Sparse Power-Law Network Model for Reliable Statistical Predictions Based on Sampled Data
Directory of Open Access Journals (Sweden)
Alexander P. Kartun-Giles
2018-04-01
Full Text Available A projective network model is a model that enables predictions to be made based on a subsample of the network data, with the predictions remaining unchanged if a larger sample is taken into consideration. An exchangeable model is a model that does not depend on the order in which nodes are sampled. Despite a large variety of non-equilibrium (growing and equilibrium (static sparse complex network models that are widely used in network science, how to reconcile sparseness (constant average degree with the desired statistical properties of projectivity and exchangeability is currently an outstanding scientific problem. Here we propose a network process with hidden variables which is projective and can generate sparse power-law networks. Despite the model not being exchangeable, it can be closely related to exchangeable uncorrelated networks as indicated by its information theory characterization and its network entropy. The use of the proposed network process as a null model is here tested on real data, indicating that the model offers a promising avenue for statistical network modelling.
Graphene growth process modeling: a physical-statistical approach
Wu, Jian; Huang, Qiang
2014-09-01
As a zero-band semiconductor, graphene is an attractive material for a wide variety of applications such as optoelectronics. Among various techniques developed for graphene synthesis, chemical vapor deposition on copper foils shows high potential for producing few-layer and large-area graphene. Since fabrication of high-quality graphene sheets requires the understanding of growth mechanisms, and methods of characterization and control of grain size of graphene flakes, analytical modeling of graphene growth process is therefore essential for controlled fabrication. The graphene growth process starts with randomly nucleated islands that gradually develop into complex shapes, grow in size, and eventually connect together to cover the copper foil. To model this complex process, we develop a physical-statistical approach under the assumption of self-similarity during graphene growth. The growth kinetics is uncovered by separating island shapes from area growth rate. We propose to characterize the area growth velocity using a confined exponential model, which not only has clear physical explanation, but also fits the real data well. For the shape modeling, we develop a parametric shape model which can be well explained by the angular-dependent growth rate. This work can provide useful information for the control and optimization of graphene growth process on Cu foil.
Nam, Sungsik
2010-11-01
Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs). With the proposed approach, we can systematically derive the joint statistics of any partial sums of ordered statistics, in terms of the moment generating function (MGF) and the probability density function (PDF). Our MGF-based approach applies not only when all the K ordered RVs are involved but also when only the Ks(Ks < K) best RVs are considered. In addition, we present the closed-form expressions for the exponential RV special case. These results apply to the performance analysis of various wireless communication systems over fading channels. © 2006 IEEE.
E.W. Fobes; R.W. Rowe
1968-01-01
A system for classifying wood-using industries and recording pertinent statistics for automatic data processing is described. Forms and coding instructions for recording data of primary processing plants are included.
Statistical Process Control: A Quality Tool for a Venous Thromboembolic Disease Registry.
Posadas-Martinez, Maria Lourdes; Rojas, Liliana Paloma; Vazquez, Fernando Javier; De Quiros, Fernan Bernaldo; Waisman, Gabriel Dario; Giunta, Diego Hernan
2016-01-01
We aim to describe Statistical Control Process as a quality tool for the Institutional Registry of Venous Thromboembolic Disease (IRTD), a registry developed in a community-care tertiary hospital in Buenos Aires, Argentina. The IRTD is a prospective cohort. The process of data acquisition began with the creation of a computerized alert generated whenever physicians requested imaging or laboratory study to diagnose venous thromboembolism, which defined eligible patients. The process then followed a structured methodology for patient's inclusion, evaluation, and posterior data entry. To control this process, process performance indicators were designed to be measured monthly. These included the number of eligible patients, the number of included patients, median time to patient's evaluation, and percentage of patients lost to evaluation. Control charts were graphed for each indicator. The registry was evaluated in 93 months, where 25,757 patients were reported and 6,798 patients met inclusion criteria. The median time to evaluation was 20 hours (SD, 12) and 7.7% of the total was lost to evaluation. Each indicator presented trends over time, caused by structural changes and improvement cycles, and therefore the central limit suffered inflexions. Statistical process control through process performance indicators allowed us to control the performance of the registry over time to detect systematic problems. We postulate that this approach could be reproduced for other clinical registries.
Wind gust estimation by combining numerical weather prediction model and statistical post-processing
Patlakas, Platon; Drakaki, Eleni; Galanis, George; Spyrou, Christos; Kallos, George
2017-04-01
The continuous rise of off-shore and near-shore activities as well as the development of structures, such as wind farms and various offshore platforms, requires the employment of state-of-the-art risk assessment techniques. Such analysis is used to set the safety standards and can be characterized as a climatologically oriented approach. Nevertheless, a reliable operational support is also needed in order to minimize cost drawbacks and human danger during the construction and the functioning stage as well as during maintenance activities. One of the most important parameters for this kind of analysis is the wind speed intensity and variability. A critical measure associated with this variability is the presence and magnitude of wind gusts as estimated in the reference level of 10m. The latter can be attributed to different processes that vary among boundary-layer turbulence, convection activities, mountain waves and wake phenomena. The purpose of this work is the development of a wind gust forecasting methodology combining a Numerical Weather Prediction model and a dynamical statistical tool based on Kalman filtering. To this end, the parameterization of Wind Gust Estimate method was implemented to function within the framework of the atmospheric model SKIRON/Dust. The new modeling tool combines the atmospheric model with a statistical local adaptation methodology based on Kalman filters. This has been tested over the offshore west coastline of the United States. The main purpose is to provide a useful tool for wind analysis and prediction and applications related to offshore wind energy (power prediction, operation and maintenance). The results have been evaluated by using observational data from the NOAA's buoy network. As it was found, the predicted output shows a good behavior that is further improved after the local adjustment post-process.
Franco, Ana; Gaillard, Vinciane; Cleeremans, Axel; Destrebecqz, Arnaud
2015-12-01
Statistical learning can be used to extract the words from continuous speech. Gómez, Bion, and Mehler (Language and Cognitive Processes, 26, 212-223, 2011) proposed an online measure of statistical learning: They superimposed auditory clicks on a continuous artificial speech stream made up of a random succession of trisyllabic nonwords. Participants were instructed to detect these clicks, which could be located either within or between words. The results showed that, over the length of exposure, reaction times (RTs) increased more for within-word than for between-word clicks. This result has been accounted for by means of statistical learning of the between-word boundaries. However, even though statistical learning occurs without an intention to learn, it nevertheless requires attentional resources. Therefore, this process could be affected by a concurrent task such as click detection. In the present study, we evaluated the extent to which the click detection task indeed reflects successful statistical learning. Our results suggest that the emergence of RT differences between within- and between-word click detection is neither systematic nor related to the successful segmentation of the artificial language. Therefore, instead of being an online measure of learning, the click detection task seems to interfere with the extraction of statistical regularities.
DEFF Research Database (Denmark)
Carstensen, Jakob; Madsen, Henrik; Poulsen, Niels Kjølstad
1994-01-01
of the processes, i.e. including prior knowledge, with the significant effects found in data by using statistical identification methods. Rates of the biochemical and hydraulic processes are identified by statistical methods and the related constants for the biochemical processes are estimated assuming Monod...... kinetics. The models only include those hydraulic and kinetic parameters, which have shown to be significant in a statistical sense, and hence they can be quantified. The application potential of these models is on-line control, because the present state of the plant is given by the variables of the models......The introduction of on-line sensors of nutrient salt concentrations on wastewater treatment plants opens a wide new area of modelling wastewater processes. Time series models of these processes are very useful for gaining insight in real time operation of wastewater treatment systems which deal...
Drug safety data mining with a tree-based scan statistic.
Kulldorff, Martin; Dashevsky, Inna; Avery, Taliser R; Chan, Arnold K; Davis, Robert L; Graham, David; Platt, Richard; Andrade, Susan E; Boudreau, Denise; Gunter, Margaret J; Herrinton, Lisa J; Pawloski, Pamala A; Raebel, Marsha A; Roblin, Douglas; Brown, Jeffrey S
2013-05-01
In post-marketing drug safety surveillance, data mining can potentially detect rare but serious adverse events. Assessing an entire collection of drug-event pairs is traditionally performed on a predefined level of granularity. It is unknown a priori whether a drug causes a very specific or a set of related adverse events, such as mitral valve disorders, all valve disorders, or different types of heart disease. This methodological paper evaluates the tree-based scan statistic data mining method to enhance drug safety surveillance. We use a three-million-member electronic health records database from the HMO Research Network. Using the tree-based scan statistic, we assess the safety of selected antifungal and diabetes drugs, simultaneously evaluating overlapping diagnosis groups at different granularity levels, adjusting for multiple testing. Expected and observed adverse event counts were adjusted for age, sex, and health plan, producing a log likelihood ratio test statistic. Out of 732 evaluated disease groupings, 24 were statistically significant, divided among 10 non-overlapping disease categories. Five of the 10 signals are known adverse effects, four are likely due to confounding by indication, while one may warrant further investigation. The tree-based scan statistic can be successfully applied as a data mining tool in drug safety surveillance using observational data. The total number of statistical signals was modest and does not imply a causal relationship. Rather, data mining results should be used to generate candidate drug-event pairs for rigorous epidemiological studies to evaluate the individual and comparative safety profiles of drugs. Copyright © 2013 John Wiley & Sons, Ltd.
International Nuclear Information System (INIS)
Eliazar, Iddo
2017-01-01
The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.
Energy Technology Data Exchange (ETDEWEB)
Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il
2017-05-15
The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.
Small, coded, pill-sized tracers embedded in grain are proposed as a method for grain traceability. A sampling process for a grain traceability system was designed and investigated by applying probability statistics using a science-based sampling approach to collect an adequate number of tracers fo...
Markovic, Gabriela; Schult, Marie-Louise; Bartfai, Aniko; Elg, Mattias
2017-01-31
Progress in early cognitive recovery after acquired brain injury is uneven and unpredictable, and thus the evaluation of rehabilitation is complex. The use of time-series measurements is susceptible to statistical change due to process variation. To evaluate the feasibility of using a time-series method, statistical process control, in early cognitive rehabilitation. Participants were 27 patients with acquired brain injury undergoing interdisciplinary rehabilitation of attention within 4 months post-injury. The outcome measure, the Paced Auditory Serial Addition Test, was analysed using statistical process control. Statistical process control identifies if and when change occurs in the process according to 3 patterns: rapid, steady or stationary performers. The statistical process control method was adjusted, in terms of constructing the baseline and the total number of measurement points, in order to measure a process in change. Statistical process control methodology is feasible for use in early cognitive rehabilitation, since it provides information about change in a process, thus enabling adjustment of the individual treatment response. Together with the results indicating discernible subgroups that respond differently to rehabilitation, statistical process control could be a valid tool in clinical decision-making. This study is a starting-point in understanding the rehabilitation process using a real-time-measurements approach.
Development and Assessment of a Preliminary Randomization-Based Introductory Statistics Curriculum
Tintle, Nathan; VanderStoep, Jill; Holmes, Vicki-Lynn; Quisenberry, Brooke; Swanson, Todd
2011-01-01
The algebra-based introductory statistics course is the most popular undergraduate course in statistics. While there is a general consensus for the content of the curriculum, the recent Guidelines for Assessment and Instruction in Statistics Education (GAISE) have challenged the pedagogy of this course. Additionally, some arguments have been made…
Nonlinear Process Fault Diagnosis Based on Serial Principal Component Analysis.
Deng, Xiaogang; Tian, Xuemin; Chen, Sheng; Harris, Chris J
2018-03-01
Many industrial processes contain both linear and nonlinear parts, and kernel principal component analysis (KPCA), widely used in nonlinear process monitoring, may not offer the most effective means for dealing with these nonlinear processes. This paper proposes a new hybrid linear-nonlinear statistical modeling approach for nonlinear process monitoring by closely integrating linear principal component analysis (PCA) and nonlinear KPCA using a serial model structure, which we refer to as serial PCA (SPCA). Specifically, PCA is first applied to extract PCs as linear features, and to decompose the data into the PC subspace and residual subspace (RS). Then, KPCA is performed in the RS to extract the nonlinear PCs as nonlinear features. Two monitoring statistics are constructed for fault detection, based on both the linear and nonlinear features extracted by the proposed SPCA. To effectively perform fault identification after a fault is detected, an SPCA similarity factor method is built for fault recognition, which fuses both the linear and nonlinear features. Unlike PCA and KPCA, the proposed method takes into account both linear and nonlinear PCs simultaneously, and therefore, it can better exploit the underlying process's structure to enhance fault diagnosis performance. Two case studies involving a simulated nonlinear process and the benchmark Tennessee Eastman process demonstrate that the proposed SPCA approach is more effective than the existing state-of-the-art approach based on KPCA alone, in terms of nonlinear process fault detection and identification.
On exploiting wavelet bases in statistical region-based segmentation
DEFF Research Database (Denmark)
Stegmann, Mikkel Bille; Forchhammer, Søren
2002-01-01
Statistical region-based segmentation methods such as the Active Appearance Models establish dense correspondences by modelling variation of shape and pixel intensities in low-resolution 2D images. Unfortunately, for high-resolution 2D and 3D images, this approach is rendered infeasible due to ex...... 9-7 wavelet on cardiac MRIs and human faces show that the segmentation accuracy is minimally degraded at compression ratios of 1:10 and 1:20, respectively....
Directory of Open Access Journals (Sweden)
Savic Marija V.
2015-09-01
Full Text Available This article presents the results of the statistical modeling of copper losses in the silicate slag of the sulfide concentrates smelting process. The aim of this study was to define the correlation dependence of the degree of copper losses in the silicate slag on the following parameters of technological processes: SiO2, FeO, Fe3O4, CaO and Al2O3 content in the slag and copper content in the matte. Multiple linear regression analysis (MLRA, artificial neural networks (ANNs and adaptive network based fuzzy inference system (ANFIS were used as tools for mathematical analysis of the indicated problem. The best correlation coefficient (R2 = 0.719 of the final model was obtained using the ANFIS modeling approach.
Statistical methods in quality assurance
International Nuclear Information System (INIS)
Eckhard, W.
1980-01-01
During the different phases of a production process - planning, development and design, manufacturing, assembling, etc. - most of the decision rests on a base of statistics, the collection, analysis and interpretation of data. Statistical methods can be thought of as a kit of tools to help to solve problems in the quality functions of the quality loop with respect to produce quality products and to reduce quality costs. Various statistical methods are represented, typical examples for their practical application are demonstrated. (RW)
Fast Quantum Algorithm for Predicting Descriptive Statistics of Stochastic Processes
Williams Colin P.
1999-01-01
Stochastic processes are used as a modeling tool in several sub-fields of physics, biology, and finance. Analytic understanding of the long term behavior of such processes is only tractable for very simple types of stochastic processes such as Markovian processes. However, in real world applications more complex stochastic processes often arise. In physics, the complicating factor might be nonlinearities; in biology it might be memory effects; and in finance is might be the non-random intentional behavior of participants in a market. In the absence of analytic insight, one is forced to understand these more complex stochastic processes via numerical simulation techniques. In this paper we present a quantum algorithm for performing such simulations. In particular, we show how a quantum algorithm can predict arbitrary descriptive statistics (moments) of N-step stochastic processes in just O(square root of N) time. That is, the quantum complexity is the square root of the classical complexity for performing such simulations. This is a significant speedup in comparison to the current state of the art.
Cognitive Transfer Outcomes for a Simulation-Based Introductory Statistics Curriculum
Backman, Matthew D.; Delmas, Robert C.; Garfield, Joan
2017-01-01
Cognitive transfer is the ability to apply learned skills and knowledge to new applications and contexts. This investigation evaluates cognitive transfer outcomes for a tertiary-level introductory statistics course using the CATALST curriculum, which exclusively used simulation-based methods to develop foundations of statistical inference. A…
Data base of accident and agricultural statistics for transportation risk assessment
Energy Technology Data Exchange (ETDEWEB)
Saricks, C.L.; Williams, R.G.; Hopf, M.R.
1989-11-01
A state-level data base of accident and agricultural statistics has been developed to support risk assessment for transportation of spent nuclear fuels and high-level radioactive wastes. This data base will enhance the modeling capabilities for more route-specific analyses of potential risks associated with transportation of these wastes to a disposal site. The data base and methodology used to develop state-specific accident and agricultural data bases are described, and summaries of accident and agricultural statistics are provided. 27 refs., 9 tabs.
Data base of accident and agricultural statistics for transportation risk assessment
International Nuclear Information System (INIS)
Saricks, C.L.; Williams, R.G.; Hopf, M.R.
1989-11-01
A state-level data base of accident and agricultural statistics has been developed to support risk assessment for transportation of spent nuclear fuels and high-level radioactive wastes. This data base will enhance the modeling capabilities for more route-specific analyses of potential risks associated with transportation of these wastes to a disposal site. The data base and methodology used to develop state-specific accident and agricultural data bases are described, and summaries of accident and agricultural statistics are provided. 27 refs., 9 tabs
Huser, Raphaë l; Opitz, Thomas; Thibaud, Emeric
2018-01-01
Extreme-value theory for stochastic processes has motivated the statistical use of max-stable models for spatial extremes. However, fitting such asymptotic models to maxima observed over finite blocks is problematic when the asymptotic stability
Directory of Open Access Journals (Sweden)
Schäffer Alejandro A
2006-12-01
Full Text Available Abstract Background TBLASTN is a mode of operation for BLAST that aligns protein sequences to a nucleotide database translated in all six frames. We present the first description of the modern implementation of TBLASTN, focusing on new techniques that were used to implement composition-based statistics for translated nucleotide searches. Composition-based statistics use the composition of the sequences being aligned to generate more accurate E-values, which allows for a more accurate distinction between true and false matches. Until recently, composition-based statistics were available only for protein-protein searches. They are now available as a command line option for recent versions of TBLASTN and as an option for TBLASTN on the NCBI BLAST web server. Results We evaluate the statistical and retrieval accuracy of the E-values reported by a baseline version of TBLASTN and by two variants that use different types of composition-based statistics. To test the statistical accuracy of TBLASTN, we ran 1000 searches using scrambled proteins from the mouse genome and a database of human chromosomes. To test retrieval accuracy, we modernize and adapt to translated searches a test set previously used to evaluate the retrieval accuracy of protein-protein searches. We show that composition-based statistics greatly improve the statistical accuracy of TBLASTN, at a small cost to the retrieval accuracy. Conclusion TBLASTN is widely used, as it is common to wish to compare proteins to chromosomes or to libraries of mRNAs. Composition-based statistics improve the statistical accuracy, and therefore the reliability, of TBLASTN results. The algorithms used by TBLASTN are not widely known, and some of the most important are reported here. The data used to test TBLASTN are available for download and may be useful in other studies of translated search algorithms.
A statistical-based approach for acoustic tomography of the atmosphere.
Kolouri, Soheil; Azimi-Sadjadi, Mahmood R; Ziemann, Astrid
2014-01-01
Acoustic travel-time tomography of the atmosphere is a nonlinear inverse problem which attempts to reconstruct temperature and wind velocity fields in the atmospheric surface layer using the dependence of sound speed on temperature and wind velocity fields along the propagation path. This paper presents a statistical-based acoustic travel-time tomography algorithm based on dual state-parameter unscented Kalman filter (UKF) which is capable of reconstructing and tracking, in time, temperature, and wind velocity fields (state variables) as well as the dynamic model parameters within a specified investigation area. An adaptive 3-D spatial-temporal autoregressive model is used to capture the state evolution in the UKF. The observations used in the dual state-parameter UKF process consist of the acoustic time of arrivals measured for every pair of transmitter/receiver nodes deployed in the investigation area. The proposed method is then applied to the data set collected at the Meteorological Observatory Lindenberg, Germany, as part of the STINHO experiment, and the reconstruction results are presented.
Directory of Open Access Journals (Sweden)
Peter James Allen
2016-02-01
particular, this aid should function as a teaching tool, which engages the user with each choice-point in the decision making process, rather than simply providing an ‘answer’. Based on these findings, we offer suggestions for tools and strategies that could be deployed in the research methods classroom to facilitate and strengthen students’ statistical decision making abilities.
Allen, Peter J.; Dorozenko, Kate P.; Roberts, Lynne D.
2016-01-01
should function as a teaching tool, which engages the user with each choice-point in the decision making process, rather than simply providing an “answer.” Based on these findings, we offer suggestions for tools and strategies that could be deployed in the research methods classroom to facilitate and strengthen students' statistical decision making abilities. PMID:26909064
Measuring streetscape complexity based on the statistics of local contrast and spatial frequency.
Directory of Open Access Journals (Sweden)
André Cavalcante
Full Text Available Streetscapes are basic urban elements which play a major role in the livability of a city. The visual complexity of streetscapes is known to influence how people behave in such built spaces. However, how and which characteristics of a visual scene influence our perception of complexity have yet to be fully understood. This study proposes a method to evaluate the complexity perceived in streetscapes based on the statistics of local contrast and spatial frequency. Here, 74 streetscape images from four cities, including daytime and nighttime scenes, were ranked for complexity by 40 participants. Image processing was then used to locally segment contrast and spatial frequency in the streetscapes. The statistics of these characteristics were extracted and later combined to form a single objective measure. The direct use of statistics revealed structural or morphological patterns in streetscapes related to the perception of complexity. Furthermore, in comparison to conventional measures of visual complexity, the proposed objective measure exhibits a higher correlation with the opinion of the participants. Also, the performance of this method is more robust regarding different time scenarios.
A Model of Statistics Performance Based on Achievement Goal Theory.
Bandalos, Deborah L.; Finney, Sara J.; Geske, Jenenne A.
2003-01-01
Tests a model of statistics performance based on achievement goal theory. Both learning and performance goals affected achievement indirectly through study strategies, self-efficacy, and test anxiety. Implications of these findings for teaching and learning statistics are discussed. (Contains 47 references, 3 tables, 3 figures, and 1 appendix.)…
Shahabi, Himan; Hashim, Mazlan
2015-04-22
This research presents the results of the GIS-based statistical models for generation of landslide susceptibility mapping using geographic information system (GIS) and remote-sensing data for Cameron Highlands area in Malaysia. Ten factors including slope, aspect, soil, lithology, NDVI, land cover, distance to drainage, precipitation, distance to fault, and distance to road were extracted from SAR data, SPOT 5 and WorldView-1 images. The relationships between the detected landslide locations and these ten related factors were identified by using GIS-based statistical models including analytical hierarchy process (AHP), weighted linear combination (WLC) and spatial multi-criteria evaluation (SMCE) models. The landslide inventory map which has a total of 92 landslide locations was created based on numerous resources such as digital aerial photographs, AIRSAR data, WorldView-1 images, and field surveys. Then, 80% of the landslide inventory was used for training the statistical models and the remaining 20% was used for validation purpose. The validation results using the Relative landslide density index (R-index) and Receiver operating characteristic (ROC) demonstrated that the SMCE model (accuracy is 96%) is better in prediction than AHP (accuracy is 91%) and WLC (accuracy is 89%) models. These landslide susceptibility maps would be useful for hazard mitigation purpose and regional planning.
Project T.E.A.M. (Technical Education Advancement Modules). Advanced Statistical Process Control.
Dunlap, Dale
This instructional guide, one of a series developed by the Technical Education Advancement Modules (TEAM) project, is a 20-hour advanced statistical process control (SPC) and quality improvement course designed to develop the following competencies: (1) understanding quality systems; (2) knowing the process; (3) solving quality problems; and (4)…
Spherical Process Models for Global Spatial Statistics
Jeong, Jaehong
2017-11-28
Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture the spatial and temporal behavior of these global data sets. Though the geodesic distance is the most natural metric for measuring distance on the surface of a sphere, mathematical limitations have compelled statisticians to use the chordal distance to compute the covariance matrix in many applications instead, which may cause physically unrealistic distortions. Therefore, covariance functions directly defined on a sphere using the geodesic distance are needed. We discuss the issues that arise when dealing with spherical data sets on a global scale and provide references to recent literature. We review the current approaches to building process models on spheres, including the differential operator, the stochastic partial differential equation, the kernel convolution, and the deformation approaches. We illustrate realizations obtained from Gaussian processes with different covariance structures and the use of isotropic and nonstationary covariance models through deformations and geographical indicators for global surface temperature data. To assess the suitability of each method, we compare their log-likelihood values and prediction scores, and we end with a discussion of related research problems.
Reporting and analyzing statistical uncertainties in Monte Carlo-based treatment planning
International Nuclear Information System (INIS)
Chetty, Indrin J.; Rosu, Mihaela; Kessler, Marc L.; Fraass, Benedick A.; Haken, Randall K. ten; Kong, Feng-Ming; McShan, Daniel L.
2006-01-01
Purpose: To investigate methods of reporting and analyzing statistical uncertainties in doses to targets and normal tissues in Monte Carlo (MC)-based treatment planning. Methods and Materials: Methods for quantifying statistical uncertainties in dose, such as uncertainty specification to specific dose points, or to volume-based regions, were analyzed in MC-based treatment planning for 5 lung cancer patients. The effect of statistical uncertainties on target and normal tissue dose indices was evaluated. The concept of uncertainty volume histograms for targets and organs at risk was examined, along with its utility, in conjunction with dose volume histograms, in assessing the acceptability of the statistical precision in dose distributions. The uncertainty evaluation tools were extended to four-dimensional planning for application on multiple instances of the patient geometry. All calculations were performed using the Dose Planning Method MC code. Results: For targets, generalized equivalent uniform doses and mean target doses converged at 150 million simulated histories, corresponding to relative uncertainties of less than 2% in the mean target doses. For the normal lung tissue (a volume-effect organ), mean lung dose and normal tissue complication probability converged at 150 million histories despite the large range in the relative organ uncertainty volume histograms. For 'serial' normal tissues such as the spinal cord, large fluctuations exist in point dose relative uncertainties. Conclusions: The tools presented here provide useful means for evaluating statistical precision in MC-based dose distributions. Tradeoffs between uncertainties in doses to targets, volume-effect organs, and 'serial' normal tissues must be considered carefully in determining acceptable levels of statistical precision in MC-computed dose distributions
Monitor-Based Statistical Model Checking for Weighted Metric Temporal Logic
DEFF Research Database (Denmark)
Bulychev, Petr; David, Alexandre; Larsen, Kim Guldstrand
2012-01-01
We present a novel approach and implementation for ana- lysing weighted timed automata (WTA) with respect to the weighted metric temporal logic (WMTL≤ ). Based on a stochastic semantics of WTAs, we apply statistical model checking (SMC) to estimate and test probabilities of satisfaction with desi......We present a novel approach and implementation for ana- lysing weighted timed automata (WTA) with respect to the weighted metric temporal logic (WMTL≤ ). Based on a stochastic semantics of WTAs, we apply statistical model checking (SMC) to estimate and test probabilities of satisfaction...
DEFF Research Database (Denmark)
Hansen, Jens Zangenberg; Brøndsted, Povl
2013-01-01
In a previous study, Trias et al. [1] determined the minimum size of a statistical representative volume element (SRVE) of a unidirectional fibre-reinforced composite primarily based on numerical analyses of the stress/strain field. In continuation of this, the present study determines the minimu...... size of an SRVE based on a statistical analysis on the spatial statistics of the fibre packing patterns found in genuine laminates, and those generated numerically using a microstructure generator. © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved....
Goodman, J. W.
This book is based on the thesis that some training in the area of statistical optics should be included as a standard part of any advanced optics curriculum. Random variables are discussed, taking into account definitions of probability and random variables, distribution functions and density functions, an extension to two or more random variables, statistical averages, transformations of random variables, sums of real random variables, Gaussian random variables, complex-valued random variables, and random phasor sums. Other subjects examined are related to random processes, some first-order properties of light waves, the coherence of optical waves, some problems involving high-order coherence, effects of partial coherence on imaging systems, imaging in the presence of randomly inhomogeneous media, and fundamental limits in photoelectric detection of light. Attention is given to deterministic versus statistical phenomena and models, the Fourier transform, and the fourth-order moment of the spectrum of a detected speckle image.
Directory of Open Access Journals (Sweden)
Zuzana ANDRÁSSYOVÁ
2012-07-01
Full Text Available Study deals with an analysis of data to the effect that it improves the quality of statistical tools in processes of assembly of automobile seats. Normal distribution of variables is one of inevitable conditions for the analysis, examination, and improvement of the manufacturing processes (f. e.: manufacturing process capability although, there are constantly more approaches to non‐normal data handling. An appropriate probability distribution of measured data is firstly tested by the goodness of fit of empirical distribution with theoretical normal distribution on the basis of hypothesis testing using programme StatGraphics Centurion XV.II. Data are collected from the assembly process of 1st row automobile seats for each characteristic of quality (Safety Regulation ‐S/R individually. Study closely processes the measured data of an airbag´s assembly and it aims to accomplish the normal distributed data and apply it the statistical process control. Results of the contribution conclude in a statement of rejection of the null hypothesis (measured variables do not follow the normal distribution therefore it is necessary to begin to work on data transformation supported by Minitab15. Even this approach does not reach a normal distributed data and so should be proposed a procedure that leads to the quality output of whole statistical control of manufacturing processes.
Bersimis, Sotiris; Panaretos, John; Psarakis, Stelios
2005-01-01
Woodall and Montgomery [35] in a discussion paper, state that multivariate process control is one of the most rapidly developing sections of statistical process control. Nowadays, in industry, there are many situations in which the simultaneous monitoring or control, of two or more related quality - process characteristics is necessary. Process monitoring problems in which several related variables are of interest are collectively known as Multivariate Statistical Process Control (MSPC).This ...
Saputra, K. V. I.; Cahyadi, L.; Sembiring, U. A.
2018-01-01
Start in this paper, we assess our traditional elementary statistics education and also we introduce elementary statistics with simulation-based inference. To assess our statistical class, we adapt the well-known CAOS (Comprehensive Assessment of Outcomes in Statistics) test that serves as an external measure to assess the student’s basic statistical literacy. This test generally represents as an accepted measure of statistical literacy. We also introduce a new teaching method on elementary statistics class. Different from the traditional elementary statistics course, we will introduce a simulation-based inference method to conduct hypothesis testing. From the literature, it has shown that this new teaching method works very well in increasing student’s understanding of statistics.
Statistical process control for electron beam monitoring.
López-Tarjuelo, Juan; Luquero-Llopis, Naika; García-Mollá, Rafael; Quirós-Higueras, Juan David; Bouché-Babiloni, Ana; Juan-Senabre, Xavier Jordi; de Marco-Blancas, Noelia; Ferrer-Albiach, Carlos; Santos-Serra, Agustín
2015-07-01
To assess the electron beam monitoring statistical process control (SPC) in linear accelerator (linac) daily quality control. We present a long-term record of our measurements and evaluate which SPC-led conditions are feasible for maintaining control. We retrieved our linac beam calibration, symmetry, and flatness daily records for all electron beam energies from January 2008 to December 2013, and retrospectively studied how SPC could have been applied and which of its features could be used in the future. A set of adjustment interventions designed to maintain these parameters under control was also simulated. All phase I data was under control. The dose plots were characterized by rising trends followed by steep drops caused by our attempts to re-center the linac beam calibration. Where flatness and symmetry trends were detected they were less-well defined. The process capability ratios ranged from 1.6 to 9.3 at a 2% specification level. Simulated interventions ranged from 2% to 34% of the total number of measurement sessions. We also noted that if prospective SPC had been applied it would have met quality control specifications. SPC can be used to assess the inherent variability of our electron beam monitoring system. It can also indicate whether a process is capable of maintaining electron parameters under control with respect to established specifications by using a daily checking device, but this is not practical unless a method to establish direct feedback from the device to the linac can be devised. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Morphology of Laplacian growth processes and statistics of equivalent many-body systems
International Nuclear Information System (INIS)
Blumenfeld, R.
1994-01-01
The authors proposes a theory for the nonlinear evolution of two dimensional interfaces in Laplacian fields. The growing region is conformally mapped onto the unit disk, generating an equivalent many-body system whose dynamics and statistics are studied. The process is shown to be Hamiltonian, with the Hamiltonian being the imaginary part of the complex electrostatic potential. Surface effects are introduced through the Hamiltonian as an external field. An extension to a continuous density of particles is presented. The results are used to study the morphology of the interface using statistical mechanics for the many-body system. The distribution of the curvature and the moments of the growth probability along the interface are calculated exactly from the distribution of the particles. In the dilute limit, the distribution of the curvature is shown to develop algebraic tails, which may, for the first time, explain the origin of fractality in diffusion controlled processes
Shiraishi, Satomi; Grams, Michael P; Fong de Los Santos, Luis E
2018-05-01
The purpose of this study was to demonstrate an objective quality control framework for the image review process. A total of 927 cone-beam computed tomography (CBCT) registrations were retrospectively analyzed for 33 bilateral head and neck cancer patients who received definitive radiotherapy. Two registration tracking volumes (RTVs) - cervical spine (C-spine) and mandible - were defined, within which a similarity metric was calculated and used as a registration quality tracking metric over the course of treatment. First, sensitivity to large misregistrations was analyzed for normalized cross-correlation (NCC) and mutual information (MI) in the context of statistical analysis. The distribution of metrics was obtained for displacements that varied according to a normal distribution with standard deviation of σ = 2 mm, and the detectability of displacements greater than 5 mm was investigated. Then, similarity metric control charts were created using a statistical process control (SPC) framework to objectively monitor the image registration and review process. Patient-specific control charts were created using NCC values from the first five fractions to set a patient-specific process capability limit. Population control charts were created using the average of the first five NCC values for all patients in the study. For each patient, the similarity metrics were calculated as a function of unidirectional translation, referred to as the effective displacement. Patient-specific action limits corresponding to 5 mm effective displacements were defined. Furthermore, effective displacements of the ten registrations with the lowest similarity metrics were compared with a three dimensional (3DoF) couch displacement required to align the anatomical landmarks. Normalized cross-correlation identified suboptimal registrations more effectively than MI within the framework of SPC. Deviations greater than 5 mm were detected at 2.8σ and 2.1σ from the mean for NCC and MI
International Nuclear Information System (INIS)
Zambra, M.; Favre, M.; Moreno, J.; Wyndham, E.; Chuaqui, H.; Choi, P.
1998-01-01
The charge formation processes in a hollow cathode region (HCR) of transient hollow cathode discharge have been studied at the final phase. The statistical distribution that describe different processes of ionization have been represented by Gaussian distributions. Nevertheless, was observed a better representation of these distributions when the pressure is near a minimum value, just before breakdown
Study of film data processing systems by means of a statistical simulation
International Nuclear Information System (INIS)
Deart, A.F.; Gromov, A.I.; Kapustinskaya, V.I.; Okorochenko, G.E.; Sychev, A.Yu.; Tatsij, L.I.
1974-01-01
Considered is a statistic model of the film information processing system. The given time diagrams illustrate the model operation algorithm. The program realizing this model of the system is described in detail. The elaborated program model has been tested at the film information processing system which represents a group of measuring devices operating in line with BESM computer. The obtained functioning quantitative characteristics of the system being tested permit to estimate the system operation efficiency
Tsutsumi, Morito; Seya, Hajime
2009-12-01
This study discusses the theoretical foundation of the application of spatial hedonic approaches—the hedonic approach employing spatial econometrics or/and spatial statistics—to benefits evaluation. The study highlights the limitations of the spatial econometrics approach since it uses a spatial weight matrix that is not employed by the spatial statistics approach. Further, the study presents empirical analyses by applying the Spatial Autoregressive Error Model (SAEM), which is based on the spatial econometrics approach, and the Spatial Process Model (SPM), which is based on the spatial statistics approach. SPMs are conducted based on both isotropy and anisotropy and applied to different mesh sizes. The empirical analysis reveals that the estimated benefits are quite different, especially between isotropic and anisotropic SPM and between isotropic SPM and SAEM; the estimated benefits are similar for SAEM and anisotropic SPM. The study demonstrates that the mesh size does not affect the estimated amount of benefits. Finally, the study provides a confidence interval for the estimated benefits and raises an issue with regard to benefit evaluation.
Physics-based statistical model and simulation method of RF propagation in urban environments
Pao, Hsueh-Yuan; Dvorak, Steven L.
2010-09-14
A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.
GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments
Directory of Open Access Journals (Sweden)
Kohlbacher Oliver
2008-12-01
Full Text Available Abstract Background High-throughput methods that allow for measuring the expression of thousands of genes or proteins simultaneously have opened new avenues for studying biochemical processes. While the noisiness of the data necessitates an extensive pre-processing of the raw data, the high dimensionality requires effective statistical analysis methods that facilitate the identification of crucial biological features and relations. For these reasons, the evaluation and interpretation of expression data is a complex, labor-intensive multi-step process. While a variety of tools for normalizing, analysing, or visualizing expression profiles has been developed in the last years, most of these tools offer only functionality for accomplishing certain steps of the evaluation pipeline. Results Here, we present a web-based toolbox that provides rich functionality for all steps of the evaluation pipeline. Our tool GeneTrailExpress offers besides standard normalization procedures powerful statistical analysis methods for studying a large variety of biological categories and pathways. Furthermore, an integrated graph visualization tool, BiNA, enables the user to draw the relevant biological pathways applying cutting-edge graph-layout algorithms. Conclusion Our gene expression toolbox with its interactive visualization of the pathways and the expression values projected onto the nodes will simplify the analysis and interpretation of biochemical pathways considerably.
Navard, Sharon E.
1989-01-01
In recent years there has been a push within NASA to use statistical techniques to improve the quality of production. Two areas where statistics are used are in establishing product and process quality control of flight hardware and in evaluating the uncertainty of calibration of instruments. The Flight Systems Quality Engineering branch is responsible for developing and assuring the quality of all flight hardware; the statistical process control methods employed are reviewed and evaluated. The Measurement Standards and Calibration Laboratory performs the calibration of all instruments used on-site at JSC as well as those used by all off-site contractors. These calibrations must be performed in such a way as to be traceable to national standards maintained by the National Institute of Standards and Technology, and they must meet a four-to-one ratio of the instrument specifications to calibrating standard uncertainty. In some instances this ratio is not met, and in these cases it is desirable to compute the exact uncertainty of the calibration and determine ways of reducing it. A particular example where this problem is encountered is with a machine which does automatic calibrations of force. The process of force calibration using the United Force Machine is described in detail. The sources of error are identified and quantified when possible. Suggestions for improvement are made.
Speech emotion recognition based on statistical pitch model
Institute of Scientific and Technical Information of China (English)
WANG Zhiping; ZHAO Li; ZOU Cairong
2006-01-01
A modified Parzen-window method, which keep high resolution in low frequencies and keep smoothness in high frequencies, is proposed to obtain statistical model. Then, a gender classification method utilizing the statistical model is proposed, which have a 98% accuracy of gender classification while long sentence is dealt with. By separation the male voice and female voice, the mean and standard deviation of speech training samples with different emotion are used to create the corresponding emotion models. Then the Bhattacharyya distance between the test sample and statistical models of pitch, are utilized for emotion recognition in speech.The normalization of pitch for the male voice and female voice are also considered, in order to illustrate them into a uniform space. Finally, the speech emotion recognition experiment based on K Nearest Neighbor shows that, the correct rate of 81% is achieved, where it is only 73.85%if the traditional parameters are utilized.
Feature Statistics Modulate the Activation of Meaning during Spoken Word Processing
Devereux, Barry J.; Taylor, Kirsten I.; Randall, Billi; Geertzen, Jeroen; Tyler, Lorraine K.
2016-01-01
Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature-based conceptual account assumes that the statistical characteristics of concepts' features--the number of concepts they occur in ("distinctiveness/sharedness") and likelihood of co-occurrence ("correlational…
The Playground Game: Inquiry‐Based Learning About Research Methods and Statistics
Westera, Wim; Slootmaker, Aad; Kurvers, Hub
2014-01-01
The Playground Game is a web-based game that was developed for teaching research methods and statistics to nursing and social sciences students in higher education and vocational training. The complexity and abstract nature of research methods and statistics poses many challenges for students. The
Li, Wen-Long; Qu, Hai-Bin
2016-10-01
In this paper, the principle of NIRS (near infrared spectroscopy)-based process trajectory technology was introduced.The main steps of the technique include:① in-line collection of the processes spectra of different technics; ② unfolding of the 3-D process spectra;③ determination of the process trajectories and their normal limits;④ monitoring of the new batches with the established MSPC (multivariate statistical process control) models.Applications of the technology in the chemical and biological medicines were reviewed briefly. By a comprehensive introduction of our feasibility research on the monitoring of traditional Chinese medicine technical process using NIRS-based multivariate process trajectories, several important problems of the practical applications which need urgent solutions are proposed, and also the application prospect of the NIRS-based process trajectory technology is fully discussed and put forward in the end. Copyright© by the Chinese Pharmaceutical Association.
Processing data base information having nonwhite noise
Gross, Kenneth C.; Morreale, Patricia
1995-01-01
A method and system for processing a set of data from an industrial process and/or a sensor. The method and system can include processing data from either real or calculated data related to an industrial process variable. One of the data sets can be an artificial signal data set generated by an autoregressive moving average technique. After obtaining two data sets associated with one physical variable, a difference function data set is obtained by determining the arithmetic difference between the two pairs of data sets over time. A frequency domain transformation is made of the difference function data set to obtain Fourier modes describing a composite function data set. A residual function data set is obtained by subtracting the composite function data set from the difference function data set and the residual function data set (free of nonwhite noise) is analyzed by a statistical probability ratio test to provide a validated data base.
Mathematical SETI Statistics, Signal Processing, Space Missions
Maccone, Claudio
2012-01-01
This book introduces the Statistical Drake Equation where, from a simple product of seven positive numbers, the Drake Equation is turned into the product of seven positive random variables. The mathematical consequences of this transformation are demonstrated and it is proven that the new random variable N for the number of communicating civilizations in the Galaxy must follow the lognormal probability distribution when the number of factors in the Drake equation is allowed to increase at will. Mathematical SETI also studies the proposed FOCAL (Fast Outgoing Cyclopean Astronomical Lens) space mission to the nearest Sun Focal Sphere at 550 AU and describes its consequences for future interstellar precursor missions and truly interstellar missions. In addition the author shows how SETI signal processing may be dramatically improved by use of the Karhunen-Loève Transform (KLT) rather than Fast Fourier Transform (FFT). Finally, he describes the efforts made to persuade the United Nations to make the central part...
Statistical Processing Algorithms for Human Population Databases
Directory of Open Access Journals (Sweden)
Camelia COLESCU
2012-01-01
Full Text Available The article is describing some algoritms for statistic functions aplied to a human population database. The samples are specific for the most interesting periods, when the evolution of statistical datas has spectacolous value. The article describes the most usefull form of grafical prezentation of the results
Scalable Integrated Region-Based Image Retrieval Using IRM and Statistical Clustering.
Wang, James Z.; Du, Yanping
Statistical clustering is critical in designing scalable image retrieval systems. This paper presents a scalable algorithm for indexing and retrieving images based on region segmentation. The method uses statistical clustering on region features and IRM (Integrated Region Matching), a measure developed to evaluate overall similarity between images…
Multivariate statistical process control of batch processes based on three-way models
Louwerse, D. J.; Smilde, A. K.
2000-01-01
The theory of batch MSPC control charts is extended and improved control charts an developed. Unfold-PCA, PARAFAC and Tucker3 models are discussed and used as a basis for these charts. The results of the different models are compared and the performance of the control charts based on these models is
Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals
Directory of Open Access Journals (Sweden)
Syafiq Hazwan
2016-01-01
Full Text Available Cooling systems is a key point for hot forming process of Ultra High Strength Steels (UHSS. Normally, cooling systems is made using deep drilling technique. Although deep twist drill is better than other drilling techniques in term of higher productivity however its main problem is premature tool breakage, which affects the production quality. In this paper, analysis of deep twist drill process parameters such as cutting speed, feed rate and depth of cut by using statistical analysis to identify the tool condition is presented. The comparisons between different two tool geometries are also studied. Measured data from vibrations and force sensors are being analyzed through several statistical parameters such as root mean square (RMS, mean, kurtosis, standard deviation and skewness. Result found that kurtosis and skewness value are the most appropriate parameters to represent the deep twist drill tool conditions behaviors from vibrations and forces data. The condition of the deep twist drill process been classified according to good, blunt and fracture. It also found that the different tool geometry parameters affect the performance of the tool drill. It believe the results of this study are useful in determining the suitable analysis method to be used for developing online tool condition monitoring system to identify the tertiary tool life stage and helps to avoid mature of tool fracture during drilling process.
Glushak, P. A.; Markiv, B. B.; Tokarchuk, M. V.
2018-01-01
We present a generalization of Zubarev's nonequilibrium statistical operator method based on the principle of maximum Renyi entropy. In the framework of this approach, we obtain transport equations for the basic set of parameters of the reduced description of nonequilibrium processes in a classical system of interacting particles using Liouville equations with fractional derivatives. For a classical systems of particles in a medium with a fractal structure, we obtain a non-Markovian diffusion equation with fractional spatial derivatives. For a concrete model of the frequency dependence of a memory function, we obtain generalized Kettano-type diffusion equation with the spatial and temporal fractality taken into account. We present a generalization of nonequilibrium thermofield dynamics in Zubarev's nonequilibrium statistical operator method in the framework of Renyi statistics.
Statistical process control applied to the manufacturing of beryllia ceramics
International Nuclear Information System (INIS)
Ferguson, G.P.; Jech, D.E.; Sepulveda, J.L.
1991-01-01
To compete effectively in an international market, scrap and re-work costs must be minimized. Statistical Process Control (SPC) provides powerful tools to optimize production performance. These techniques are currently being applied to the forming, metallizing, and brazing of beryllia ceramic components. This paper describes specific examples of applications of SPC to dry-pressing of beryllium oxide 2x2 substrates, to Mo-Mn refractory metallization, and to metallization and brazing of plasma tubes used in lasers where adhesion strength is critical
Statistical Validation for Clinical Measures: Repeatability and Agreement of Kinect™-Based Software.
Lopez, Natalia; Perez, Elisa; Tello, Emanuel; Rodrigo, Alejandro; Valentinuzzi, Max E
2018-01-01
The rehabilitation process is a fundamental stage for recovery of people's capabilities. However, the evaluation of the process is performed by physiatrists and medical doctors, mostly based on their observations, that is, a subjective appreciation of the patient's evolution. This paper proposes a tracking platform of the movement made by an individual's upper limb using Kinect sensor(s) to be applied for the patient during the rehabilitation process. The main contribution is the development of quantifying software and the statistical validation of its performance, repeatability, and clinical use in the rehabilitation process. The software determines joint angles and upper limb trajectories for the construction of a specific rehabilitation protocol and quantifies the treatment evolution. In turn, the information is presented via a graphical interface that allows the recording, storage, and report of the patient's data. For clinical purposes, the software information is statistically validated with three different methodologies, comparing the measures with a goniometer in terms of agreement and repeatability. The agreement of joint angles measured with the proposed software and goniometer is evaluated with Bland-Altman plots; all measurements fell well within the limits of agreement, meaning interchangeability of both techniques. Additionally, the results of Bland-Altman analysis of repeatability show 95% confidence. Finally, the physiotherapists' qualitative assessment shows encouraging results for the clinical use. The main conclusion is that the software is capable of offering a clinical history of the patient and is useful for quantification of the rehabilitation success. The simplicity, low cost, and visualization possibilities enhance the use of the software Kinect for rehabilitation and other applications, and the expert's opinion endorses the choice of our approach for clinical practice. Comparison of the new measurement technique with established
THE FLUORBOARD A STATISTICALLY BASED DASHBOARD METHOD FOR IMPROVING SAFETY
International Nuclear Information System (INIS)
PREVETTE, S.S.
2005-01-01
The FluorBoard is a statistically based dashboard method for improving safety. Fluor Hanford has achieved significant safety improvements--including more than a 80% reduction in OSHA cases per 200,000 hours, during its work at the US Department of Energy's Hanford Site in Washington state. The massive project on the former nuclear materials production site is considered one of the largest environmental cleanup projects in the world. Fluor Hanford's safety improvements were achieved by a committed partnering of workers, managers, and statistical methodology. Safety achievements at the site have been due to a systematic approach to safety. This includes excellent cooperation between the field workers, the safety professionals, and management through OSHA Voluntary Protection Program principles. Fluor corporate values are centered around safety, and safety excellence is important for every manager in every project. In addition, Fluor Hanford has utilized a rigorous approach to using its safety statistics, based upon Dr. Shewhart's control charts, and Dr. Deming's management and quality methods
Protecting the Force: Application of Statistical Process Control for Force Protection in Bosnia
National Research Council Canada - National Science Library
Finken, Paul
2000-01-01
.... In Operations Other Than War (OOTW), environments where the enemy is disorganized and incapable of mounting a deception plan, staffs could model hostile events as stochastic events and use statistical methods to detect changes to the process...
International Nuclear Information System (INIS)
Alfatni, M S M; Shariff, A R M; Marhaban, M H; Shafie, S B; Saaed, O M B; Abdullah, M Z; BAmiruddin, M D
2014-01-01
There is a processing need for a fast, easy and accurate classification system for oil palm fruit ripeness. Such a system will be invaluable to farmers and plantation managers who need to sell their oil palm fresh fruit bunch (FFB) for the mill as this will avoid disputes. In this paper,a new approach was developed under the name of expert rules-based systembased on the image processing techniques results of thethree different oil palm FFB region of interests (ROIs), namely; ROI1 (300x300 pixels), ROI2 (50x50 pixels) and ROI3 (100x100 pixels). The results show that the best rule-based ROIs for statistical colour feature extraction with k-nearest neighbors (KNN) classifier at 94% were chosen as well as the ROIs that indicated results higher than the rule-based outcome, such as the ROIs of statistical colour feature extraction with artificial neural network (ANN) classifier at 94%, were selected for further FFB ripeness inspection system
Learning Psychological Research and Statistical Concepts using Retrieval-based Practice
Stephen Wee Hun eLim; Gavin Jun Peng eNg; Gabriel Qi Hao eWong
2015-01-01
Research methods and statistics are an indispensable subject in the undergraduate psychology curriculum, but there are challenges associated with engaging students in it, such as making learning durable. Here we hypothesized that retrieval-based learning promotes long-term retention of statistical knowledge in psychology. Participants either studied the educational material in four consecutive periods, or studied it just once and practiced retrieving the information in the subsequent three pe...
Parallel processing approach to transform-based image coding
Normile, James O.; Wright, Dan; Chu, Ken; Yeh, Chia L.
1991-06-01
This paper describes a flexible parallel processing architecture designed for use in real time video processing. The system consists of floating point DSP processors connected to each other via fast serial links, each processor has access to a globally shared memory. A multiple bus architecture in combination with a dual ported memory allows communication with a host control processor. The system has been applied to prototyping of video compression and decompression algorithms. The decomposition of transform based algorithms for decompression into a form suitable for parallel processing is described. A technique for automatic load balancing among the processors is developed and discussed, results ar presented with image statistics and data rates. Finally techniques for accelerating the system throughput are analyzed and results from the application of one such modification described.
An Automated Statistical Process Control Study of Inline Mixing Using Spectrophotometric Detection
Dickey, Michael D.; Stewart, Michael D.; Willson, C. Grant
2006-01-01
An experiment is described, which is designed for a junior-level chemical engineering "fundamentals of measurements and data analysis" course, where students are introduced to the concept of statistical process control (SPC) through a simple inline mixing experiment. The students learn how to create and analyze control charts in an effort to…
Directory of Open Access Journals (Sweden)
Yun Tian
2016-01-01
Full Text Available The segmentation of coronary arteries is a vital process that helps cardiovascular radiologists detect and quantify stenosis. In this paper, we propose a fully automated coronary artery segmentation from cardiac data volume. The method is built on a statistics region growing together with a heuristic decision. First, the heart region is extracted using a multi-atlas-based approach. Second, the vessel structures are enhanced via a 3D multiscale line filter. Next, seed points are detected automatically through a threshold preprocessing and a subsequent morphological operation. Based on the set of detected seed points, a statistics-based region growing is applied. Finally, results are obtained by setting conservative parameters. A heuristic decision method is then used to obtain the desired result automatically because parameters in region growing vary in different patients, and the segmentation requires full automation. The experiments are carried out on a dataset that includes eight-patient multivendor cardiac computed tomography angiography (CTA volume data. The DICE similarity index, mean distance, and Hausdorff distance metrics are employed to compare the proposed algorithm with two state-of-the-art methods. Experimental results indicate that the proposed algorithm is capable of performing complete, robust, and accurate extraction of coronary arteries.
Automating Exams for a Statistics Course: II. A Case Study.
Michener, R. Dean; And Others
A specific application of the process of automating exams for any introductory statistics course is described. The process of automating exams was accomplished by using the Statistical Test Item Collection System (STICS). This system was first used to select a set of questions based on course requirements established in advance; afterward, STICS…
Case-based reasoning combined with statistics for diagnostics and prognosis
International Nuclear Information System (INIS)
Olsson, T; Funk, P
2012-01-01
Many approaches used for diagnostics today are based on a precise model. This excludes diagnostics of many complex types of machinery that cannot be modelled and simulated easily or without great effort. Our aim is to show that by including human experience it is possible to diagnose complex machinery when there is no or limited models or simulations available. This also enables diagnostics in a dynamic application where conditions change and new cases are often added. In fact every new solved case increases the diagnostic power of the system. We present a number of successful projects where we have used feature extraction together with case-based reasoning to diagnose faults in industrial robots, welding, cutting machinery and we also present our latest project for diagnosing transmissions by combining Case-Based Reasoning (CBR) with statistics. We view the fault diagnosis process as three consecutive steps. In the first step, sensor fault signals from machines and/or input from human operators are collected. Then, the second step consists of extracting relevant fault features. In the final diagnosis/prognosis step, status and faults are identified and classified. We view prognosis as a special case of diagnosis where the prognosis module predicts a stream of future features.
Nuclear material statistical accountancy system
International Nuclear Information System (INIS)
Argentest, F.; Casilli, T.; Franklin, M.
1979-01-01
The statistical accountancy system developed at JRC Ispra is refered as 'NUMSAS', ie Nuclear Material Statistical Accountancy System. The principal feature of NUMSAS is that in addition to an ordinary material balance calcultation, NUMSAS can calculate an estimate of the standard deviation of the measurement error accumulated in the material balance calculation. The purpose of the report is to describe in detail, the statistical model on wich the standard deviation calculation is based; the computational formula which is used by NUMSAS in calculating the standard deviation and the information about nuclear material measurements and the plant measurement system which are required as data for NUMSAS. The material balance records require processing and interpretation before the material balance calculation is begun. The material balance calculation is the last of four phases of data processing undertaken by NUMSAS. Each of these phases is implemented by a different computer program. The activities which are carried out in each phase can be summarised as follows; the pre-processing phase; the selection and up-date phase; the transformation phase, and the computation phase
International Nuclear Information System (INIS)
Tadaki, Kohtaro
2010-01-01
The statistical mechanical interpretation of algorithmic information theory (AIT, for short) was introduced and developed by our former works [K. Tadaki, Local Proceedings of CiE 2008, pp. 425-434, 2008] and [K. Tadaki, Proceedings of LFCS'09, Springer's LNCS, vol. 5407, pp. 422-440, 2009], where we introduced the notion of thermodynamic quantities, such as partition function Z(T), free energy F(T), energy E(T), statistical mechanical entropy S(T), and specific heat C(T), into AIT. We then discovered that, in the interpretation, the temperature T equals to the partial randomness of the values of all these thermodynamic quantities, where the notion of partial randomness is a stronger representation of the compression rate by means of program-size complexity. Furthermore, we showed that this situation holds for the temperature T itself, which is one of the most typical thermodynamic quantities. Namely, we showed that, for each of the thermodynamic quantities Z(T), F(T), E(T), and S(T) above, the computability of its value at temperature T gives a sufficient condition for T is an element of (0,1) to satisfy the condition that the partial randomness of T equals to T. In this paper, based on a physical argument on the same level of mathematical strictness as normal statistical mechanics in physics, we develop a total statistical mechanical interpretation of AIT which actualizes a perfect correspondence to normal statistical mechanics. We do this by identifying a microcanonical ensemble in the framework of AIT. As a result, we clarify the statistical mechanical meaning of the thermodynamic quantities of AIT.
Exploring the use of statistical process control methods to assess course changes
Vollstedt, Ann-Marie
This dissertation pertains to the field of Engineering Education. The Department of Mechanical Engineering at the University of Nevada, Reno (UNR) is hosting this dissertation under a special agreement. This study was motivated by the desire to find an improved, quantitative measure of student quality that is both convenient to use and easy to evaluate. While traditional statistical analysis tools such as ANOVA (analysis of variance) are useful, they are somewhat time consuming and are subject to error because they are based on grades, which are influenced by numerous variables, independent of student ability and effort (e.g. inflation and curving). Additionally, grades are currently the only measure of quality in most engineering courses even though most faculty agree that grades do not accurately reflect student quality. Based on a literature search, in this study, quality was defined as content knowledge, cognitive level, self efficacy, and critical thinking. Nineteen treatments were applied to a pair of freshmen classes in an effort in increase the qualities. The qualities were measured via quiz grades, essays, surveys, and online critical thinking tests. Results from the quality tests were adjusted and filtered prior to analysis. All test results were subjected to Chauvenet's criterion in order to detect and remove outlying data. In addition to removing outliers from data sets, it was felt that individual course grades needed adjustment to accommodate for the large portion of the grade that was defined by group work. A new method was developed to adjust grades within each group based on the residual of the individual grades within the group and the portion of the course grade defined by group work. It was found that the grade adjustment method agreed 78% of the time with the manual ii grade changes instructors made in 2009, and also increased the correlation between group grades and individual grades. Using these adjusted grades, Statistical Process Control
The Initial Regression Statistical Characteristics of Intervals Between Zeros of Random Processes
Directory of Open Access Journals (Sweden)
V. K. Hohlov
2014-01-01
Full Text Available The article substantiates the initial regression statistical characteristics of intervals between zeros of realizing random processes, studies their properties allowing the use these features in the autonomous information systems (AIS of near location (NL. Coefficients of the initial regression (CIR to minimize the residual sum of squares of multiple initial regression views are justified on the basis of vector representations associated with a random vector notion of analyzed signal parameters. It is shown that even with no covariance-based private CIR it is possible to predict one random variable through another with respect to the deterministic components. The paper studies dependences of CIR interval sizes between zeros of the narrowband stationary in wide-sense random process with its energy spectrum. Particular CIR for random processes with Gaussian and rectangular energy spectra are obtained. It is shown that the considered CIRs do not depend on the average frequency of spectra, are determined by the relative bandwidth of the energy spectra, and weakly depend on the type of spectrum. CIR properties enable its use as an informative parameter when implementing temporary regression methods of signal processing, invariant to the average rate and variance of the input implementations. We consider estimates of the average energy spectrum frequency of the random stationary process by calculating the length of the time interval corresponding to the specified number of intervals between zeros. It is shown that the relative variance in estimation of the average energy spectrum frequency of stationary random process with increasing relative bandwidth ceases to depend on the last process implementation in processing above ten intervals between zeros. The obtained results can be used in the AIS NL to solve the tasks of detection and signal recognition, when a decision is made in conditions of unknown mathematical expectations on a limited observation
Statistical analysis of questionnaires a unified approach based on R and Stata
Bartolucci, Francesco; Gnaldi, Michela
2015-01-01
Statistical Analysis of Questionnaires: A Unified Approach Based on R and Stata presents special statistical methods for analyzing data collected by questionnaires. The book takes an applied approach to testing and measurement tasks, mirroring the growing use of statistical methods and software in education, psychology, sociology, and other fields. It is suitable for graduate students in applied statistics and psychometrics and practitioners in education, health, and marketing.The book covers the foundations of classical test theory (CTT), test reliability, va
Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu
2015-09-01
Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Analysis of statistical misconception in terms of statistical reasoning
Maryati, I.; Priatna, N.
2018-05-01
Reasoning skill is needed for everyone to face globalization era, because every person have to be able to manage and use information from all over the world which can be obtained easily. Statistical reasoning skill is the ability to collect, group, process, interpret, and draw conclusion of information. Developing this skill can be done through various levels of education. However, the skill is low because many people assume that statistics is just the ability to count and using formulas and so do students. Students still have negative attitude toward course which is related to research. The purpose of this research is analyzing students’ misconception in descriptive statistic course toward the statistical reasoning skill. The observation was done by analyzing the misconception test result and statistical reasoning skill test; observing the students’ misconception effect toward statistical reasoning skill. The sample of this research was 32 students of math education department who had taken descriptive statistic course. The mean value of misconception test was 49,7 and standard deviation was 10,6 whereas the mean value of statistical reasoning skill test was 51,8 and standard deviation was 8,5. If the minimal value is 65 to state the standard achievement of a course competence, students’ mean value is lower than the standard competence. The result of students’ misconception study emphasized on which sub discussion that should be considered. Based on the assessment result, it was found that students’ misconception happen on this: 1) writing mathematical sentence and symbol well, 2) understanding basic definitions, 3) determining concept that will be used in solving problem. In statistical reasoning skill, the assessment was done to measure reasoning from: 1) data, 2) representation, 3) statistic format, 4) probability, 5) sample, and 6) association.
Billings, Paul H.
This instructional guide, one of a series developed by the Technical Education Advancement Modules (TEAM) project, is a 6-hour introductory module on statistical process control (SPC), designed to develop competencies in the following skill areas: (1) identification of the three classes of SPC use; (2) understanding a process and how it works; (3)…
Single photon laser altimeter simulator and statistical signal processing
Vacek, Michael; Prochazka, Ivan
2013-05-01
Spaceborne altimeters are common instruments onboard the deep space rendezvous spacecrafts. They provide range and topographic measurements critical in spacecraft navigation. Simultaneously, the receiver part may be utilized for Earth-to-satellite link, one way time transfer, and precise optical radiometry. The main advantage of single photon counting approach is the ability of processing signals with very low signal-to-noise ratio eliminating the need of large telescopes and high power laser source. Extremely small, rugged and compact microchip lasers can be employed. The major limiting factor, on the other hand, is the acquisition time needed to gather sufficient volume of data in repetitive measurements in order to process and evaluate the data appropriately. Statistical signal processing is adopted to detect signals with average strength much lower than one photon per measurement. A comprehensive simulator design and range signal processing algorithm are presented to identify a mission specific altimeter configuration. Typical mission scenarios (celestial body surface landing and topographical mapping) are simulated and evaluated. The high interest and promising single photon altimeter applications are low-orbit (˜10 km) and low-radial velocity (several m/s) topographical mapping (asteroids, Phobos and Deimos) and landing altimetry (˜10 km) where range evaluation repetition rates of ˜100 Hz and 0.1 m precision may be achieved. Moon landing and asteroid Itokawa topographical mapping scenario simulations are discussed in more detail.
Official Statistics and Statistics Education: Bridging the Gap
Directory of Open Access Journals (Sweden)
Gal Iddo
2017-03-01
Full Text Available This article aims to challenge official statistics providers and statistics educators to ponder on how to help non-specialist adult users of statistics develop those aspects of statistical literacy that pertain to official statistics. We first document the gap in the literature in terms of the conceptual basis and educational materials needed for such an undertaking. We then review skills and competencies that may help adults to make sense of statistical information in areas of importance to society. Based on this review, we identify six elements related to official statistics about which non-specialist adult users should possess knowledge in order to be considered literate in official statistics: (1 the system of official statistics and its work principles; (2 the nature of statistics about society; (3 indicators; (4 statistical techniques and big ideas; (5 research methods and data sources; and (6 awareness and skills for citizens’ access to statistical reports. Based on this ad hoc typology, we discuss directions that official statistics providers, in cooperation with statistics educators, could take in order to (1 advance the conceptualization of skills needed to understand official statistics, and (2 expand educational activities and services, specifically by developing a collaborative digital textbook and a modular online course, to improve public capacity for understanding of official statistics.
Directory of Open Access Journals (Sweden)
Đurić I.
2010-01-01
Full Text Available This paper presents the results of defining the mathematical model which describes the dependence of leaching degree of Al2O3 in bauxite from the most influential input parameters in industrial conditions of conducting the leaching process in the Bayer technology of alumina production. Mathematical model is defined using the stepwise MLRA method, with R2 = 0.764 and significant statistical reliability - VIF<2 and p<0.05, on the one-year statistical sample. Validation of the acquired model was performed using the data from the following year, collected from the process conducted under industrial conditions, rendering the same statistical reliability, with R2 = 0.759.
International Nuclear Information System (INIS)
Bennett, J.T.; Crowder, C.A.; Connolly, M.J.
1994-01-01
Gas samples from drums of radioactive waste at the Department of Energy (DOE) Idaho National Engineering Laboratory are being characterized for 29 volatile organic compounds to determine the feasibility of storing the waste in DOE's Waste Isolation Pilot Plant (WIPP) in Carlsbad, New Mexico. Quality requirements for the gas chromatography (GC) and GC/mass spectrometry chemical methods used to analyze the waste are specified in the Quality Assurance Program Plan for the WIPP Experimental Waste Characterization Program. Quality requirements consist of both objective criteria (data quality objectives, DQOs) and statistical criteria (process control). The DQOs apply to routine sample analyses, while the statistical criteria serve to determine and monitor precision and accuracy (P ampersand A) of the analysis methods and are also used to assign upper confidence limits to measurement results close to action levels. After over two years and more than 1000 sample analyses there are two general conclusions concerning the two approaches to quality control: (1) Objective criteria (e.g., ± 25% precision, ± 30% accuracy) based on customer needs and the usually prescribed criteria for similar EPA- approved methods are consistently attained during routine analyses. (2) Statistical criteria based on short term method performance are almost an order of magnitude more stringent than objective criteria and are difficult to satisfy following the same routine laboratory procedures which satisfy the objective criteria. A more cost effective and representative approach to establishing statistical method performances criteria would be either to utilize a moving average of P ampersand A from control samples over a several month time period or to determine within a sample variation by one-way analysis of variance of several months replicate sample analysis results or both. Confidence intervals for results near action levels could also be determined by replicate analysis of the sample in
Diagnosis of students' ability in a statistical course based on Rasch probabilistic outcome
Mahmud, Zamalia; Ramli, Wan Syahira Wan; Sapri, Shamsiah; Ahmad, Sanizah
2017-06-01
Measuring students' ability and performance are important in assessing how well students have learned and mastered the statistical courses. Any improvement in learning will depend on the student's approaches to learning, which are relevant to some factors of learning, namely assessment methods carrying out tasks consisting of quizzes, tests, assignment and final examination. This study has attempted an alternative approach to measure students' ability in an undergraduate statistical course based on the Rasch probabilistic model. Firstly, this study aims to explore the learning outcome patterns of students in a statistics course (Applied Probability and Statistics) based on an Entrance-Exit survey. This is followed by investigating students' perceived learning ability based on four Course Learning Outcomes (CLOs) and students' actual learning ability based on their final examination scores. Rasch analysis revealed that students perceived themselves as lacking the ability to understand about 95% of the statistics concepts at the beginning of the class but eventually they had a good understanding at the end of the 14 weeks class. In terms of students' performance in their final examination, their ability in understanding the topics varies at different probability values given the ability of the students and difficulty of the questions. Majority found the probability and counting rules topic to be the most difficult to learn.
Statistical inference for remote sensing-based estimates of net deforestation
Ronald E. McRoberts; Brian F. Walters
2012-01-01
Statistical inference requires expression of an estimate in probabilistic terms, usually in the form of a confidence interval. An approach to constructing confidence intervals for remote sensing-based estimates of net deforestation is illustrated. The approach is based on post-classification methods using two independent forest/non-forest classifications because...
Juvenile Court Statistics, 1974.
Corbett, Jacqueline; Vereb, Thomas S.
This report presents information on juvenile court processing of youth in the U.S. during 1974. It is based on data gathered under the National Juvenile Court Statistical Reporting System. Findings can be summarized as follows: (1) 1,252,700 juvenile delinquency cases, excluding traffic offenses, were handled by courts in the U.S. in 1974; (2) the…
Marrakesh International Conference on Probability and Statistics
Ouassou, Idir; Rachdi, Mustapha
2015-01-01
This volume, which highlights recent advances in statistical methodology and applications, is divided into two main parts. The first part presents theoretical results on estimation techniques in functional statistics, while the second examines three key areas of application: estimation problems in queuing theory, an application in signal processing, and the copula approach to epidemiologic modelling. The book’s peer-reviewed contributions are based on papers originally presented at the Marrakesh International Conference on Probability and Statistics held in December 2013.
Poster - Thur Eve - 29: Detecting changes in IMRT QA using statistical process control.
Drever, L; Salomons, G
2012-07-01
Statistical process control (SPC) methods were used to analyze 239 measurement based individual IMRT QA events. The selected IMRT QA events were all head and neck (H&N) cases with 70Gy in 35 fractions, and all prostate cases with 76Gy in 38 fractions planned between March 2009 and 2012. The results were used to determine if the tolerance limits currently being used for IMRT QA were able to indicate if the process was under control. The SPC calculations were repeated for IMRT QA of the same type of cases that were planned after the treatment planning system was upgraded from Eclipse version 8.1.18 to version 10.0.39. The initial tolerance limits were found to be acceptable for two of the three metrics tested prior to the upgrade. After the upgrade to the treatment planning system the SPC analysis found that the a priori limits were no longer capable of indicating control for 2 of the 3 metrics analyzed. The changes in the IMRT QA results were clearly identified using SPC, indicating that it is a useful tool for finding changes in the IMRT QA process. Routine application of SPC to IMRT QA results would help to distinguish unintentional trends and changes from the random variation in the IMRT QA results for individual plans. © 2012 American Association of Physicists in Medicine.
Directory of Open Access Journals (Sweden)
Sutikno Sutikno
2010-08-01
Full Text Available One of the climate models used to predict the climatic conditions is Global Circulation Models (GCM. GCM is a computer-based model that consists of different equations. It uses numerical and deterministic equation which follows the physics rules. GCM is a main tool to predict climate and weather, also it uses as primary information source to review the climate change effect. Statistical Downscaling (SD technique is used to bridge the large-scale GCM with a small scale (the study area. GCM data is spatial and temporal data most likely to occur where the spatial correlation between different data on the grid in a single domain. Multicollinearity problems require the need for pre-processing of variable data X. Continuum Regression (CR and pre-processing with Principal Component Analysis (PCA methods is an alternative to SD modelling. CR is one method which was developed by Stone and Brooks (1990. This method is a generalization from Ordinary Least Square (OLS, Principal Component Regression (PCR and Partial Least Square method (PLS methods, used to overcome multicollinearity problems. Data processing for the station in Ambon, Pontianak, Losarang, Indramayu and Yuntinyuat show that the RMSEP values and R2 predict in the domain 8x8 and 12x12 by uses CR method produces results better than by PCR and PLS.
International Nuclear Information System (INIS)
Jiselmark, J.
2017-01-01
There are different standards for the characterization and clearance process used globally in the radiological industry. All of them have advantages and disadvantages. This paper is describing a decommissioning project which is combining two methods in order to use the advantages of both and minimizing the disadvantages. In Sweden there have been a standard since several years to use a method based on parametric Bayesian statistics for the characterization and clearance process. This method has great advantages close to the clearance limits due to few measurements per m"2, an ability to add extra measurements if needed and an ability to reshape area units without restarting the clearance process. Since the method is based on units with a normal or LOG-normal distribution of the contamination there can be several units far from the clearance limits. The American MARSSIM method use non parametric statistics instead of parametric. In comparison to the Bayesian methods this results in the disadvantage of less accuracy close to the clearance limits but also in the great advantage with few units far from the clearance limits. In the characterizing and clearance process of old radiological facilities at the Karolinska University Hospital in Stockholm the MARSSIM method is combined with the Bayesian statistics method to minimize the amount of measurements and by that the cost for clearance. By using Bayesian statistics close to the clearance limits, more areas will be approved for clearance and the risk of having to redo the survey is minimized. By using MARSSIM methods in the area with an assumed contamination below 25 % of the clearance limits, the areas are not needed to be divided into units with normal or LOG-normal distributed activity. Bigger areas can be handled as units which result in fewer measurements and a faster process. (authors)
Heimann, Dennis; Nieschulze, Jens; König-Ries, Birgitta
2010-04-20
Data management in the life sciences has evolved from simple storage of data to complex information systems providing additional functionalities like analysis and visualization capabilities, demanding the integration of statistical tools. In many cases the used statistical tools are hard-coded within the system. That leads to an expensive integration, substitution, or extension of tools because all changes have to be done in program code. Other systems are using generic solutions for tool integration but adapting them to another system is mostly rather extensive work. This paper shows a way to provide statistical functionality over a statistics web service, which can be easily integrated in any information system and set up using XML configuration files. The statistical functionality is extendable by simply adding the description of a new application to a configuration file. The service architecture as well as the data exchange process between client and service and the adding of analysis applications to the underlying service provider are described. Furthermore a practical example demonstrates the functionality of the service.
Statistical Analysis of the First Passage Path Ensemble of Jump Processes
von Kleist, Max; Schütte, Christof; Zhang, Wei
2018-02-01
The transition mechanism of jump processes between two different subsets in state space reveals important dynamical information of the processes and therefore has attracted considerable attention in the past years. In this paper, we study the first passage path ensemble of both discrete-time and continuous-time jump processes on a finite state space. The main approach is to divide each first passage path into nonreactive and reactive segments and to study them separately. The analysis can be applied to jump processes which are non-ergodic, as well as continuous-time jump processes where the waiting time distributions are non-exponential. In the particular case that the jump processes are both Markovian and ergodic, our analysis elucidates the relations between the study of the first passage paths and the study of the transition paths in transition path theory. We provide algorithms to numerically compute statistics of the first passage path ensemble. The computational complexity of these algorithms scales with the complexity of solving a linear system, for which efficient methods are available. Several examples demonstrate the wide applicability of the derived results across research areas.
Wali, F.; Knotter, D. Martin; Wortelboer, Ronald; Mud, Auke
2007-01-01
Ultra pure water supplied inside the Fab is used in different tools at different stages of processing. Data of the particles measured in ultra pure water was compared with the defect density on wafers processed on these tools and a statistical relation is found Keywords— Yield, defect density,
Wind Statistics Offshore based on Satellite Images
DEFF Research Database (Denmark)
Hasager, Charlotte Bay; Mouche, Alexis; Badger, Merete
2009-01-01
-based observations become available. At present preliminary results are obtained using the routine methods. The first step in the process is to retrieve raw SAR data, calibrate the images and use a priori wind direction as input to the geophysical model function. From this process the wind speed maps are produced....... The wind maps are geo-referenced. The second process is the analysis of a series of geo-referenced SAR-based wind maps. Previous research has shown that a relatively large number of images are needed for achieving certain accuracies on mean wind speed, Weibull A and k (scale and shape parameters......Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy...
Spectral deformation techniques applied to the study of quantum statistical irreversible processes
International Nuclear Information System (INIS)
Courbage, M.
1978-01-01
A procedure of analytic continuation of the resolvent of Liouville operators for quantum statistical systems is discussed. When applied to the theory of irreversible processes of the Brussels School, this method supports the idea that the restriction to a class of initial conditions is necessary to obtain an irreversible behaviour. The general results are tested on the Friedrichs model. (Auth.)
Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model
Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.
2014-02-01
Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation
McCray, Wilmon Wil L., Jr.
The research was prompted by a need to conduct a study that assesses process improvement, quality management and analytical techniques taught to students in U.S. colleges and universities undergraduate and graduate systems engineering and the computing science discipline (e.g., software engineering, computer science, and information technology) degree programs during their academic training that can be applied to quantitatively manage processes for performance. Everyone involved in executing repeatable processes in the software and systems development lifecycle processes needs to become familiar with the concepts of quantitative management, statistical thinking, process improvement methods and how they relate to process-performance. Organizations are starting to embrace the de facto Software Engineering Institute (SEI) Capability Maturity Model Integration (CMMI RTM) Models as process improvement frameworks to improve business processes performance. High maturity process areas in the CMMI model imply the use of analytical, statistical, quantitative management techniques, and process performance modeling to identify and eliminate sources of variation, continually improve process-performance; reduce cost and predict future outcomes. The research study identifies and provides a detail discussion of the gap analysis findings of process improvement and quantitative analysis techniques taught in U.S. universities systems engineering and computing science degree programs, gaps that exist in the literature, and a comparison analysis which identifies the gaps that exist between the SEI's "healthy ingredients " of a process performance model and courses taught in U.S. universities degree program. The research also heightens awareness that academicians have conducted little research on applicable statistics and quantitative techniques that can be used to demonstrate high maturity as implied in the CMMI models. The research also includes a Monte Carlo simulation optimization
Content-based VLE designs improve learning efficiency in constructivist statistics education.
Wessa, Patrick; De Rycker, Antoon; Holliday, Ian Edward
2011-01-01
We introduced a series of computer-supported workshops in our undergraduate statistics courses, in the hope that it would help students to gain a deeper understanding of statistical concepts. This raised questions about the appropriate design of the Virtual Learning Environment (VLE) in which such an approach had to be implemented. Therefore, we investigated two competing software design models for VLEs. In the first system, all learning features were a function of the classical VLE. The second system was designed from the perspective that learning features should be a function of the course's core content (statistical analyses), which required us to develop a specific-purpose Statistical Learning Environment (SLE) based on Reproducible Computing and newly developed Peer Review (PR) technology. The main research question is whether the second VLE design improved learning efficiency as compared to the standard type of VLE design that is commonly used in education. As a secondary objective we provide empirical evidence about the usefulness of PR as a constructivist learning activity which supports non-rote learning. Finally, this paper illustrates that it is possible to introduce a constructivist learning approach in large student populations, based on adequately designed educational technology, without subsuming educational content to technological convenience. Both VLE systems were tested within a two-year quasi-experiment based on a Reliable Nonequivalent Group Design. This approach allowed us to draw valid conclusions about the treatment effect of the changed VLE design, even though the systems were implemented in successive years. The methodological aspects about the experiment's internal validity are explained extensively. The effect of the design change is shown to have substantially increased the efficiency of constructivist, computer-assisted learning activities for all cohorts of the student population under investigation. The findings demonstrate that a
Content-based VLE designs improve learning efficiency in constructivist statistics education.
Directory of Open Access Journals (Sweden)
Patrick Wessa
Full Text Available BACKGROUND: We introduced a series of computer-supported workshops in our undergraduate statistics courses, in the hope that it would help students to gain a deeper understanding of statistical concepts. This raised questions about the appropriate design of the Virtual Learning Environment (VLE in which such an approach had to be implemented. Therefore, we investigated two competing software design models for VLEs. In the first system, all learning features were a function of the classical VLE. The second system was designed from the perspective that learning features should be a function of the course's core content (statistical analyses, which required us to develop a specific-purpose Statistical Learning Environment (SLE based on Reproducible Computing and newly developed Peer Review (PR technology. OBJECTIVES: The main research question is whether the second VLE design improved learning efficiency as compared to the standard type of VLE design that is commonly used in education. As a secondary objective we provide empirical evidence about the usefulness of PR as a constructivist learning activity which supports non-rote learning. Finally, this paper illustrates that it is possible to introduce a constructivist learning approach in large student populations, based on adequately designed educational technology, without subsuming educational content to technological convenience. METHODS: Both VLE systems were tested within a two-year quasi-experiment based on a Reliable Nonequivalent Group Design. This approach allowed us to draw valid conclusions about the treatment effect of the changed VLE design, even though the systems were implemented in successive years. The methodological aspects about the experiment's internal validity are explained extensively. RESULTS: The effect of the design change is shown to have substantially increased the efficiency of constructivist, computer-assisted learning activities for all cohorts of the student
Content-Based VLE Designs Improve Learning Efficiency in Constructivist Statistics Education
Wessa, Patrick; De Rycker, Antoon; Holliday, Ian Edward
2011-01-01
Background We introduced a series of computer-supported workshops in our undergraduate statistics courses, in the hope that it would help students to gain a deeper understanding of statistical concepts. This raised questions about the appropriate design of the Virtual Learning Environment (VLE) in which such an approach had to be implemented. Therefore, we investigated two competing software design models for VLEs. In the first system, all learning features were a function of the classical VLE. The second system was designed from the perspective that learning features should be a function of the course's core content (statistical analyses), which required us to develop a specific–purpose Statistical Learning Environment (SLE) based on Reproducible Computing and newly developed Peer Review (PR) technology. Objectives The main research question is whether the second VLE design improved learning efficiency as compared to the standard type of VLE design that is commonly used in education. As a secondary objective we provide empirical evidence about the usefulness of PR as a constructivist learning activity which supports non-rote learning. Finally, this paper illustrates that it is possible to introduce a constructivist learning approach in large student populations, based on adequately designed educational technology, without subsuming educational content to technological convenience. Methods Both VLE systems were tested within a two-year quasi-experiment based on a Reliable Nonequivalent Group Design. This approach allowed us to draw valid conclusions about the treatment effect of the changed VLE design, even though the systems were implemented in successive years. The methodological aspects about the experiment's internal validity are explained extensively. Results The effect of the design change is shown to have substantially increased the efficiency of constructivist, computer-assisted learning activities for all cohorts of the student population under
Brouwer, D.; Meijer, R.R.; Zevalkink, D.J.
2013-01-01
Several researchers have emphasized that item response theory (IRT)-based methods should be preferred over classical approaches in measuring change for individual patients. In the present study we discuss and evaluate the use of IRT-based statistics to measure statistical significant individual
International Nuclear Information System (INIS)
Heising, C.D.; Grenzebach, W.S.
1990-01-01
In engineering science, statistical quality control techniques have traditionally been applied to control manufacturing processes. An application to commercial nuclear power plant maintenance and control is presented that can greatly improve safety. As a demonstration of such an approach to plant maintenance and control, a specific system is analyzed: the reactor coolant pumps of the St. Lucie Unit 2 nuclear power plant located in Florida. A 30-day history of the four pumps prior to a plant shutdown caused by pump failure and a related fire within the containment was analyzed. Statistical quality control charts of recorded variables were constructed for each pump, which were shown to go out of statistical control many days before the plant trip. The analysis shows that statistical process control methods can be applied as an early warning system capable of identifying significant equipment problems well in advance of traditional control room alarm indicators
Compliance strategy for statistically based neutron overpower protection safety analysis methodology
International Nuclear Information System (INIS)
Holliday, E.; Phan, B.; Nainer, O.
2009-01-01
The methodology employed in the safety analysis of the slow Loss of Regulation (LOR) event in the OPG and Bruce Power CANDU reactors, referred to as Neutron Overpower Protection (NOP) analysis, is a statistically based methodology. Further enhancement to this methodology includes the use of Extreme Value Statistics (EVS) for the explicit treatment of aleatory and epistemic uncertainties, and probabilistic weighting of the initial core states. A key aspect of this enhanced NOP methodology is to demonstrate adherence, or compliance, with the analysis basis. This paper outlines a compliance strategy capable of accounting for the statistical nature of the enhanced NOP methodology. (author)
Statistical method application to knowledge base building for reactor accident diagnostic system
International Nuclear Information System (INIS)
Yoshida, Kazuo; Yokobayashi, Masao; Matsumoto, Kiyoshi; Kohsaka, Atsuo
1989-01-01
In the development of a knowledge based expert system, one of key issues is how to build the knowledge base (KB) in an efficient way with keeping the objectivity of KB. In order to solve this issue, an approach has been proposed to build a prototype KB systematically by a statistical method, factor analysis. For the verification of this approach, factor analysis was applied to build a prototype KB for the JAERI expert system DISKET. To this end, alarm and process information was generated by a PWR simulator and the factor analysis was applied to this information to define taxonomy of accident hypotheses and to extract rules for each hypothesis. The prototype KB thus built was tested through inferring against several types of transients including double-failures. In each diagnosis, the transient type was well identified. Furthermore, newly introduced standards for rule extraction showed good effects on the enhancement of the performance of prototype KB. (author)
Cashin, Andrew; Gallagher, Hilary; Newman, Claire; Hughes, Mark
2012-08-01
The next iteration of the Diagnostic and Statistical Manual of Mental Disorders is due for release in May 2013. The current diagnostic criteria for autism are based on a behavioral triad of impairment, which has been helpful for diagnosis and identifying the need for intervention, but is not useful with regard to developing interventions. Revised diagnostic criteria are needed to better inform research and therapeutic intervention. This article examines the research underpinning the behavioral triad of impairment to consider alternative explanations and a more useful framing for diagnosis and intervention. Contemporary research and literature on autism were used in this study. It is proposed that the cognitive processing triad of impaired abstraction, impaired theory of mind, and impaired linguistic processing become the triad of impairment for autism in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. These are investigable at the diagnostic level and can usefully inform intervention. Further, in addressing the debate on whether restrictive and repetitive behavior should remain central to diagnosis or be replaced by a deficit in imagination, the authors argue that both behavioral manifestations are underpinned by impaired abstraction. © 2012 Wiley Periodicals, Inc.
A Statistical Primer: Understanding Descriptive and Inferential Statistics
Gillian Byrne
2007-01-01
As libraries and librarians move more towards evidence‐based decision making, the data being generated in libraries is growing. Understanding the basics of statistical analysis is crucial for evidence‐based practice (EBP), in order to correctly design and analyze researchas well as to evaluate the research of others. This article covers the fundamentals of descriptive and inferential statistics, from hypothesis construction to sampling to common statistical techniques including chi‐square, co...
Müller, M. F.; Thompson, S. E.
2015-09-01
The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drives of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by a strong wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are strongly favored over statistical models.
Hybrid statistics-simulations based method for atom-counting from ADF STEM images.
De Wael, Annelies; De Backer, Annick; Jones, Lewys; Nellist, Peter D; Van Aert, Sandra
2017-06-01
A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. Copyright © 2017 Elsevier B.V. All rights reserved.
Algorithm for image retrieval based on edge gradient orientation statistical code.
Zeng, Jiexian; Zhao, Yonggang; Li, Weiye; Fu, Xiang
2014-01-01
Image edge gradient direction not only contains important information of the shape, but also has a simple, lower complexity characteristic. Considering that the edge gradient direction histograms and edge direction autocorrelogram do not have the rotation invariance, we put forward the image retrieval algorithm which is based on edge gradient orientation statistical code (hereinafter referred to as EGOSC) by sharing the application of the statistics method in the edge direction of the chain code in eight neighborhoods to the statistics of the edge gradient direction. Firstly, we construct the n-direction vector and make maximal summation restriction on EGOSC to make sure this algorithm is invariable for rotation effectively. Then, we use Euclidean distance of edge gradient direction entropy to measure shape similarity, so that this method is not sensitive to scaling, color, and illumination change. The experimental results and the algorithm analysis demonstrate that the algorithm can be used for content-based image retrieval and has good retrieval results.
Rule-based statistical data mining agents for an e-commerce application
Qin, Yi; Zhang, Yan-Qing; King, K. N.; Sunderraman, Rajshekhar
2003-03-01
Intelligent data mining techniques have useful e-Business applications. Because an e-Commerce application is related to multiple domains such as statistical analysis, market competition, price comparison, profit improvement and personal preferences, this paper presents a hybrid knowledge-based e-Commerce system fusing intelligent techniques, statistical data mining, and personal information to enhance QoS (Quality of Service) of e-Commerce. A Web-based e-Commerce application software system, eDVD Web Shopping Center, is successfully implemented uisng Java servlets and an Oracle81 database server. Simulation results have shown that the hybrid intelligent e-Commerce system is able to make smart decisions for different customers.
Al-Hussein, Fahad A
2009-01-01
To use statistical control charts in a series of audits to improve the acceptance and consistant use of guidelines, and reduce the variations in prescription processing in primary health care. A series of audits were done at the main satellite of King Saud Housing Family and Community Medicine Center, National Guard Health Affairs, Riyadh, where three general practitioners and six pharmacists provide outpatient care to about 3000 residents. Audits were carried out every fortnight to calculate the proportion of prescriptions that did not conform to the given guidelines of prescribing and dispensing. Simple random samples of thirty were chosen from a sampling frame of all prescriptions given in the two previous weeks. Thirty six audits were carried out from September 2004 to February 2006. P-charts were constructed around a parametric specification of non-conformities not exceeding 25%. Of the 1081 prescriptions, the most frequent non-conformity was failure to write generic names (35.5%), followed by the failure to record patient's weight (16.4%), pharmacist's name (14.3%), duration of therapy (9.1%), and the use of inappropriate abbreviations (6.0%). Initially, 100% of prescriptions did not conform to the guidelines, but within a period of three months, this came down to 40%. A process of audits in the context of statistical process control is necessary for any improvement in the implementation of guidelines in primary care. Statistical process control charts are an effective means of visual feedback to the care providers.
Learning Psychological Research and Statistical Concepts using Retrieval-based Practice
Directory of Open Access Journals (Sweden)
Stephen Wee Hun eLim
2015-10-01
Full Text Available Research methods and statistics are an indispensable subject in the undergraduate psychology curriculum, but there are challenges associated with teaching it, such as making learning durable. Here we hypothesized that retrieval-based learning promotes long-term retention of statistical knowledge in psychology. Participants either studied the educational material in four consecutive periods, or studied it just once and practised retrieving the information in the subsequent three periods, and then took a final test through which their learning was assessed. Whereas repeated studying yielded better test performance when the final test was immediately administered, repeated practice yielded better performance when the test was administered a week after. The data suggest that retrieval practice enhanced the learning – produced better long-term retention – of statistical knowledge in psychology than did repeated studying.
Simulation-based optimization for product and process design
Driessen, L.
2006-01-01
The design of products and processes has gradually shifted from a purely physical process towards a process that heavily relies on computer simulations (virtual prototyping). To optimize this virtual design process in terms of speed and final product quality, statistical methods and mathematical
DEFF Research Database (Denmark)
Colone, L.; Hovgaard, K.; Glavind, Lars
2018-01-01
A method for mass change detection on wind turbine blades using natural frequencies is presented. The approach is based on two statistical tests. The first test decides if there is a significant mass change and the second test is a statistical group classification based on Linear Discriminant Ana...
A Framework for Assessing High School Students' Statistical Reasoning.
Chan, Shiau Wei; Ismail, Zaleha; Sumintono, Bambang
2016-01-01
Based on a synthesis of literature, earlier studies, analyses and observations on high school students, this study developed an initial framework for assessing students' statistical reasoning about descriptive statistics. Framework descriptors were established across five levels of statistical reasoning and four key constructs. The former consisted of idiosyncratic reasoning, verbal reasoning, transitional reasoning, procedural reasoning, and integrated process reasoning. The latter include describing data, organizing and reducing data, representing data, and analyzing and interpreting data. In contrast to earlier studies, this initial framework formulated a complete and coherent statistical reasoning framework. A statistical reasoning assessment tool was then constructed from this initial framework. The tool was administered to 10 tenth-grade students in a task-based interview. The initial framework was refined, and the statistical reasoning assessment tool was revised. The ten students then participated in the second task-based interview, and the data obtained were used to validate the framework. The findings showed that the students' statistical reasoning levels were consistent across the four constructs, and this result confirmed the framework's cohesion. Developed to contribute to statistics education, this newly developed statistical reasoning framework provides a guide for planning learning goals and designing instruction and assessments.
Statistical Thermodynamics and Microscale Thermophysics
Carey, Van P.
1999-08-01
Many exciting new developments in microscale engineering are based on the application of traditional principles of statistical thermodynamics. In this text Van Carey offers a modern view of thermodynamics, interweaving classical and statistical thermodynamic principles and applying them to current engineering systems. He begins with coverage of microscale energy storage mechanisms from a quantum mechanics perspective and then develops the fundamental elements of classical and statistical thermodynamics. Subsequent chapters discuss applications of equilibrium statistical thermodynamics to solid, liquid, and gas phase systems. The remainder of the book is devoted to nonequilibrium thermodynamics of transport phenomena and to nonequilibrium effects and noncontinuum behavior at the microscale. Although the text emphasizes mathematical development, Carey includes many examples and exercises to illustrate how the theoretical concepts are applied to systems of scientific and engineering interest. In the process he offers a fresh view of statistical thermodynamics for advanced undergraduate and graduate students, as well as practitioners, in mechanical, chemical, and materials engineering.
Directory of Open Access Journals (Sweden)
Isabel M. Joao
2017-09-01
Full Text Available Projects thematically focused on simulation and statistical techniques for designing and optimizing chemical processes can be helpful in chemical engineering education in order to meet the needs of engineers. We argue for the relevance of the projects to improve a student centred approach and boost higher order thinking skills. This paper addresses the use of Aspen HYSYS by Portuguese chemical engineering master students to model distillation systems together with statistical experimental design techniques in order to optimize the systems highlighting the value of applying problem specific knowledge, simulation tools and sound statistical techniques. The paper summarizes the work developed by the students in order to model steady-state processes, dynamic processes and optimize the distillation systems emphasizing the benefits of the simulation tools and statistical techniques in helping the students learn how to learn. Students strengthened their domain specific knowledge and became motivated to rethink and improve chemical processes in their future chemical engineering profession. We discuss the main advantages of the methodology from the students’ and teachers perspective
Shewhart, Mark
1991-01-01
Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts.
van den Ende, Jan; van Oost, Elizabeth C.J.
2001-01-01
This article is a longitudinal analysis of the relation between gendered labour divisions and new data processing technologies at the Dutch Central Bureau of Statistics (CBS). Following social-constructivist and evolutionary economic approaches, the authors hold that the relation between technology
Statistical model of stress corrosion cracking based on extended ...
Indian Academy of Sciences (India)
2016-09-07
Sep 7, 2016 ... Abstract. In the previous paper (Pramana – J. Phys. 81(6), 1009 (2013)), the mechanism of stress corrosion cracking (SCC) based on non-quadratic form of Dirichlet energy was proposed and its statistical features were discussed. Following those results, we discuss here how SCC propagates on pipe wall ...
Moddemeijer, R
In the case of two signals with independent pairs of observations (x(n),y(n)) a statistic to estimate the variance of the histogram based mutual information estimator has been derived earlier. We present such a statistic for dependent pairs. To derive this statistic it is necessary to avail of a
Solution of the statistical bootstrap with Bose statistics
International Nuclear Information System (INIS)
Engels, J.; Fabricius, K.; Schilling, K.
1977-01-01
A brief and transparent way to introduce Bose statistics into the statistical bootstrap of Hagedorn and Frautschi is presented. The resulting bootstrap equation is solved by a cluster expansion for the grand canonical partition function. The shift of the ultimate temperature due to Bose statistics is determined through an iteration process. We discuss two-particle spectra of the decaying fireball (with given mass) as obtained from its grand microcanonical level density
MANAGERIAL DECISION IN INNOVATIVE EDUCATION SYSTEMS STATISTICAL SURVEY BASED ON SAMPLE THEORY
Directory of Open Access Journals (Sweden)
Gheorghe SĂVOIU
2012-12-01
Full Text Available Before formulating the statistical hypotheses and the econometrictesting itself, a breakdown of some of the technical issues is required, which are related to managerial decision in innovative educational systems, the educational managerial phenomenon tested through statistical and mathematical methods, respectively the significant difference in perceiving the current qualities, knowledge, experience, behaviour and desirable health, obtained through a questionnaire applied to a stratified population at the end,in the educational environment, either with educational activities, or with simultaneously managerial and educational activities. The details having to do with research focused on the survey theory, turning into a working tool the questionnaires and statistical data that are processed from those questionnaires, are summarized below.
Statistical learning and auditory processing in children with music training: An ERP study.
Mandikal Vasuki, Pragati Rao; Sharma, Mridula; Ibrahim, Ronny; Arciuli, Joanne
2017-07-01
The question whether musical training is associated with enhanced auditory and cognitive abilities in children is of considerable interest. In the present study, we compared children with music training versus those without music training across a range of auditory and cognitive measures, including the ability to detect implicitly statistical regularities in input (statistical learning). Statistical learning of regularities embedded in auditory and visual stimuli was measured in musically trained and age-matched untrained children between the ages of 9-11years. In addition to collecting behavioural measures, we recorded electrophysiological measures to obtain an online measure of segmentation during the statistical learning tasks. Musically trained children showed better performance on melody discrimination, rhythm discrimination, frequency discrimination, and auditory statistical learning. Furthermore, grand-averaged ERPs showed that triplet onset (initial stimulus) elicited larger responses in the musically trained children during both auditory and visual statistical learning tasks. In addition, children's music skills were associated with performance on auditory and visual behavioural statistical learning tasks. Our data suggests that individual differences in musical skills are associated with children's ability to detect regularities. The ERP data suggest that musical training is associated with better encoding of both auditory and visual stimuli. Although causality must be explored in further research, these results may have implications for developing music-based remediation strategies for children with learning impairments. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Evaluation of extreme temperature events in northern Spain based on process control charts
Villeta, M.; Valencia, J. L.; Saá, A.; Tarquis, A. M.
2018-02-01
Extreme climate events have recently attracted the attention of a growing number of researchers because these events impose a large cost on agriculture and associated insurance planning. This study focuses on extreme temperature events and proposes a new method for their evaluation based on statistical process control tools, which are unusual in climate studies. A series of minimum and maximum daily temperatures for 12 geographical areas of a Spanish region between 1931 and 2009 were evaluated by applying statistical process control charts to statistically test whether evidence existed for an increase or a decrease of extreme temperature events. Specification limits were determined for each geographical area and used to define four types of extreme anomalies: lower and upper extremes for the minimum and maximum anomalies. A new binomial Markov extended process that considers the autocorrelation between extreme temperature events was generated for each geographical area and extreme anomaly type to establish the attribute control charts for the annual fraction of extreme days and to monitor the occurrence of annual extreme days. This method was used to assess the significance of changes and trends of extreme temperature events in the analysed region. The results demonstrate the effectiveness of an attribute control chart for evaluating extreme temperature events. For example, the evaluation of extreme maximum temperature events using the proposed statistical process control charts was consistent with the evidence of an increase in maximum temperatures during the last decades of the last century.
Symbolic Processing Combined with Model-Based Reasoning
James, Mark
2009-01-01
A computer program for the detection of present and prediction of future discrete states of a complex, real-time engineering system utilizes a combination of symbolic processing and numerical model-based reasoning. One of the biggest weaknesses of a purely symbolic approach is that it enables prediction of only future discrete states while missing all unmodeled states or leading to incorrect identification of an unmodeled state as a modeled one. A purely numerical approach is based on a combination of statistical methods and mathematical models of the applicable physics and necessitates development of a complete model to the level of fidelity required for prediction. In addition, a purely numerical approach does not afford the ability to qualify its results without some form of symbolic processing. The present software implements numerical algorithms to detect unmodeled events and symbolic algorithms to predict expected behavior, correlate the expected behavior with the unmodeled events, and interpret the results in order to predict future discrete states. The approach embodied in this software differs from that of the BEAM methodology (aspects of which have been discussed in several prior NASA Tech Briefs articles), which provides for prediction of future measurements in the continuous-data domain.
Nonequilibrium Statistical Operator Method and Generalized Kinetic Equations
Kuzemsky, A. L.
2018-01-01
We consider some principal problems of nonequilibrium statistical thermodynamics in the framework of the Zubarev nonequilibrium statistical operator approach. We present a brief comparative analysis of some approaches to describing irreversible processes based on the concept of nonequilibrium Gibbs ensembles and their applicability to describing nonequilibrium processes. We discuss the derivation of generalized kinetic equations for a system in a heat bath. We obtain and analyze a damped Schrödinger-type equation for a dynamical system in a heat bath. We study the dynamical behavior of a particle in a medium taking the dissipation effects into account. We consider the scattering problem for neutrons in a nonequilibrium medium and derive a generalized Van Hove formula. We show that the nonequilibrium statistical operator method is an effective, convenient tool for describing irreversible processes in condensed matter.
Directory of Open Access Journals (Sweden)
N. V. Zhelninskaya
2015-01-01
Full Text Available Statistical methods play an important role in the objective evaluation of quantitative and qualitative characteristics of the process and are one of the most important elements of the quality assurance system production and total quality management process. To produce a quality product, one must know the real accuracy of existing equipment, to determine compliance with the accuracy of a selected technological process specified accuracy products, assess process stability. Most of the random events in life, particularly in manufacturing and scientific research, are characterized by the presence of a large number of random factors, is described by a normal distribution, which is the main in many practical studies. Modern statistical methods is quite difficult to grasp and wide practical use without in-depth mathematical training of all participants in the process. When we know the distribution of a random variable, you can get all the features of this batch of products, to determine the mean value and the variance. Using statistical control methods and quality control in the analysis of accuracy and stability of the technological process of production of epoxy resin ED20. Estimated numerical characteristics of the law of distribution of controlled parameters and determined the percentage of defects of the investigated object products. For sustainability assessment of manufacturing process of epoxy resin ED-20 selected Shewhart control charts, using quantitative data, maps of individual values of X and sliding scale R. Using Pareto charts identify the causes that affect low dynamic viscosity in the largest extent. For the analysis of low values of dynamic viscosity were the causes of defects using Ishikawa diagrams, which shows the most typical factors of the variability of the results of the process. To resolve the problem, it is recommended to modify the polymer composition of carbon fullerenes and to use the developed method for the production of
Segmentation of Brain MRI Using SOM-FCM-Based Method and 3D Statistical Descriptors
Directory of Open Access Journals (Sweden)
Andrés Ortiz
2013-01-01
Full Text Available Current medical imaging systems provide excellent spatial resolution, high tissue contrast, and up to 65535 intensity levels. Thus, image processing techniques which aim to exploit the information contained in the images are necessary for using these images in computer-aided diagnosis (CAD systems. Image segmentation may be defined as the process of parcelling the image to delimit different neuroanatomical tissues present on the brain. In this paper we propose a segmentation technique using 3D statistical features extracted from the volume image. In addition, the presented method is based on unsupervised vector quantization and fuzzy clustering techniques and does not use any a priori information. The resulting fuzzy segmentation method addresses the problem of partial volume effect (PVE and has been assessed using real brain images from the Internet Brain Image Repository (IBSR.
Swanson, David M; Blacker, Deborah; Alchawa, Taofik; Ludwig, Kerstin U; Mangold, Elisabeth; Lange, Christoph
2013-11-07
The advent of genome-wide association studies has led to many novel disease-SNP associations, opening the door to focused study on their biological underpinnings. Because of the importance of analyzing these associations, numerous statistical methods have been devoted to them. However, fewer methods have attempted to associate entire genes or genomic regions with outcomes, which is potentially more useful knowledge from a biological perspective and those methods currently implemented are often permutation-based. One property of some permutation-based tests is that their power varies as a function of whether significant markers are in regions of linkage disequilibrium (LD) or not, which we show from a theoretical perspective. We therefore develop two methods for quantifying the degree of association between a genomic region and outcome, both of whose power does not vary as a function of LD structure. One method uses dimension reduction to "filter" redundant information when significant LD exists in the region, while the other, called the summary-statistic test, controls for LD by scaling marker Z-statistics using knowledge of the correlation matrix of markers. An advantage of this latter test is that it does not require the original data, but only their Z-statistics from univariate regressions and an estimate of the correlation structure of markers, and we show how to modify the test to protect the type 1 error rate when the correlation structure of markers is misspecified. We apply these methods to sequence data of oral cleft and compare our results to previously proposed gene tests, in particular permutation-based ones. We evaluate the versatility of the modification of the summary-statistic test since the specification of correlation structure between markers can be inaccurate. We find a significant association in the sequence data between the 8q24 region and oral cleft using our dimension reduction approach and a borderline significant association using the
International Nuclear Information System (INIS)
Zuniga Santana, J.F.; Fernadez Rondon, M.; Viant Garrido, E.; Torres Berdeguez, M.B.; Fernadez, A.
1998-01-01
Nowadays the statistic has an action change and its applications have to do with all the branches of the scientific knowledge. Constantly new applications arise for the statistic, one of those is in the insurance of the quality of productive processes. The process of serial production of the devices of shielding gamma type CPb-m and CPb-g are carried out in correspondence with the designed methodology and validated in the Department of Technologic Design of the Center of Nuclear Technology (CTN). With view to execute the normative ones national and international for this packing type were designed a System of Insurance of the Quality (SAC) based on the normative ISO composed by a manual of quality and a manual of procedures where is described of detailed way each one of the stages. Presently work different statistical methods are analyzed with the objective of selecting the good one to determine the factors that have bigger influence in to the quality of production of the devices of shielding gamma used by the CENTIS for the packing and transportation of the radioactive preparations
A robust statistical method for association-based eQTL analysis.
Directory of Open Access Journals (Sweden)
Ning Jiang
Full Text Available It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS is statistical inference of linkage disequilibrium (LD between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation.We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations.The analyses show that the new method confers an improved statistical power for detecting genuine genetic association in subpopulations and an effective control of spurious associations stemmed from population structure when compared with other two popularly implemented methods in the literature of GWAS.
Average Nuclear properties based on statistical model
International Nuclear Information System (INIS)
El-Jaick, L.J.
1974-01-01
The rough properties of nuclei were investigated by statistical model, in systems with the same and different number of protons and neutrons, separately, considering the Coulomb energy in the last system. Some average nuclear properties were calculated based on the energy density of nuclear matter, from Weizsscker-Beth mass semiempiric formulae, generalized for compressible nuclei. In the study of a s surface energy coefficient, the great influence exercised by Coulomb energy and nuclear compressibility was verified. For a good adjust of beta stability lines and mass excess, the surface symmetry energy were established. (M.C.K.) [pt
Visual wetness perception based on image color statistics.
Sawayama, Masataka; Adelson, Edward H; Nishida, Shin'ya
2017-05-01
Color vision provides humans and animals with the abilities to discriminate colors based on the wavelength composition of light and to determine the location and identity of objects of interest in cluttered scenes (e.g., ripe fruit among foliage). However, we argue that color vision can inform us about much more than color alone. Since a trichromatic image carries more information about the optical properties of a scene than a monochromatic image does, color can help us recognize complex material qualities. Here we show that human vision uses color statistics of an image for the perception of an ecologically important surface condition (i.e., wetness). Psychophysical experiments showed that overall enhancement of chromatic saturation, combined with a luminance tone change that increases the darkness and glossiness of the image, tended to make dry scenes look wetter. Theoretical analysis along with image analysis of real objects indicated that our image transformation, which we call the wetness enhancing transformation, is consistent with actual optical changes produced by surface wetting. Furthermore, we found that the wetness enhancing transformation operator was more effective for the images with many colors (large hue entropy) than for those with few colors (small hue entropy). The hue entropy may be used to separate surface wetness from other surface states having similar optical properties. While surface wetness and surface color might seem to be independent, there are higher order color statistics that can influence wetness judgments, in accord with the ecological statistics. The present findings indicate that the visual system uses color image statistics in an elegant way to help estimate the complex physical status of a scene.
Directory of Open Access Journals (Sweden)
M. N. Ivliev
2016-01-01
Full Text Available The work is devoted to methods of analysis the company financial condition, including aggregated ratings. It is proposed to use the generalized solvency and liquidity indicator and the capital structure composite index. Mathematically, the generalized index is a sum of variables-characteristics and weighting factors characterizing the relative importance of individual characteristics composition. It is offered to select the significant features from a set of standard financial ratios, calculated according to enterprises balance sheets. To obtain the weighting factors values it is proposed to use one of the expert statistical approaches, the analytic hierarchy process. The method is as follows: we choose the most important characteristic and after the experts determine the degree of preference for the main feature based on the linguistic scale. Further, matrix of pairwise comparisons based on the assigned ranks is compiled, which characterizes the relative importance of attributes. The required coefficients are determined as elements of a vector of priorities, which is the first vector of the matrix of paired comparisons. The paper proposes a mechanism for finding the fields for rating numbers analysis. In addition, the paper proposes a method for the statistical evaluation of the balance sheets of various companies by calculating the mutual correlation matrices. Based on the considered mathematical methods to determine quantitative characteristics of technical objects financial and economic activities, was developed algorithms, information and software allowing to realize of different systems economic analysis.
Hybrid statistics-simulations based method for atom-counting from ADF STEM images
Energy Technology Data Exchange (ETDEWEB)
De wael, Annelies, E-mail: annelies.dewael@uantwerpen.be [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium); De Backer, Annick [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium); Jones, Lewys; Nellist, Peter D. [Department of Materials, University of Oxford, Parks Road, OX1 3PH Oxford (United Kingdom); Van Aert, Sandra, E-mail: sandra.vanaert@uantwerpen.be [Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium)
2017-06-15
A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. - Highlights: • A hybrid method for atom-counting from ADF STEM images is introduced. • Image simulations are incorporated into a statistical framework in a reliable manner. • Limits of the existing methods for atom-counting are far exceeded. • Reliable counting results from an experimental low dose image are obtained. • Progress towards reliable quantitative analysis of beam-sensitive materials is made.
Farthouat, Juliane; Franco, Ana; Mary, Alison; Delpouve, Julie; Wens, Vincent; Op de Beeck, Marc; De Tiège, Xavier; Peigneux, Philippe
2017-03-01
Humans are highly sensitive to statistical regularities in their environment. This phenomenon, usually referred as statistical learning, is most often assessed using post-learning behavioural measures that are limited by a lack of sensibility and do not monitor the temporal dynamics of learning. In the present study, we used magnetoencephalographic frequency-tagged responses to investigate the neural sources and temporal development of the ongoing brain activity that supports the detection of regularities embedded in auditory streams. Participants passively listened to statistical streams in which tones were grouped as triplets, and to random streams in which tones were randomly presented. Results show that during exposure to statistical (vs. random) streams, tritone frequency-related responses reflecting the learning of regularities embedded in the stream increased in the left supplementary motor area and left posterior superior temporal sulcus (pSTS), whereas tone frequency-related responses decreased in the right angular gyrus and right pSTS. Tritone frequency-related responses rapidly developed to reach significance after 3 min of exposure. These results suggest that the incidental extraction of novel regularities is subtended by a gradual shift from rhythmic activity reflecting individual tone succession toward rhythmic activity synchronised with triplet presentation, and that these rhythmic processes are subtended by distinct neural sources.
Integrating source-language context into phrase-based statistical machine translation
Haque, R.; Kumar Naskar, S.; Bosch, A.P.J. van den; Way, A.
2011-01-01
The translation features typically used in Phrase-Based Statistical Machine Translation (PB-SMT) model dependencies between the source and target phrases, but not among the phrases in the source language themselves. A swathe of research has demonstrated that integrating source context modelling
Statistical inference for financial engineering
Taniguchi, Masanobu; Ogata, Hiroaki; Taniai, Hiroyuki
2014-01-01
This monograph provides the fundamentals of statistical inference for financial engineering and covers some selected methods suitable for analyzing financial time series data. In order to describe the actual financial data, various stochastic processes, e.g. non-Gaussian linear processes, non-linear processes, long-memory processes, locally stationary processes etc. are introduced and their optimal estimation is considered as well. This book also includes several statistical approaches, e.g., discriminant analysis, the empirical likelihood method, control variate method, quantile regression, realized volatility etc., which have been recently developed and are considered to be powerful tools for analyzing the financial data, establishing a new bridge between time series and financial engineering. This book is well suited as a professional reference book on finance, statistics and statistical financial engineering. Readers are expected to have an undergraduate-level knowledge of statistics.
Statistical evaluation of tablet coating processes: influence of pan design and solvent type
Directory of Open Access Journals (Sweden)
Valdomero Pereira de Melo Junior
2010-12-01
Full Text Available Partially and fully perforated pan coaters are among the most relevant types of equipment currently used in the process of coating tablets. The goal of this study was to assess the performance differences among these types of equipment employing a factorial design. This statistical approach allowed the simultaneous study of the process variables and verification of interactions among them. The study included partially-perforated and fully-perforated pan coaters, aqueous and organic solvents, as well as hypromellose-based immediate-release coating. The dependent variables were process time, energy consumption, mean weight of tablets and process yield. For the tests, placebo tablets with a mean weight of 250 mg were produced, divided into eight lots of two kilograms each and coated in duplicate, using both partially perforated pan and fully perforated pan coaters. The results showed a significant difference between the type of equipment used (partially and fully perforated pan coaters with regard to process time and energy consumption, whereas no significant difference was identified for mean weight of the coated tablets and process yield.Entre os tipos de equipamentos de maior relevância utilizados atualmente no processo de revestimento de comprimidos estão os de tambor parcial e totalmente perfurados. A proposta desse trabalho foi avaliar as diferenças de desempenho entre esses equipamentos empregando projeto fatorial. Essa abordagem estatística possibilitou o estudo simultâneo das variáveis do processo, permitindo verificar interações entre elas. O trabalho incluiu equipamento com tambor parcialmente perfurado e totalmente perfurado, solventes aquoso e orgânico, assim como revestimento de liberação imediata à base de hipromelose. As variáveis dependentes ou respostas foram tempo de processo, consumo de energia, peso médio e rendimento do processo. Para os ensaios, foram produzidos comprimidos de placebo de 250 mg de peso m
New Statistics for Texture Classification Based on Gabor Filters
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J. Pavlovicova
2007-09-01
Full Text Available The paper introduces a new method of texture segmentation efficiency evaluation. One of the well known texture segmentation methods is based on Gabor filters because of their orientation and spatial frequency character. Several statistics are used to extract more information from results obtained by Gabor filtering. Big amount of input parameters causes a wide set of results which need to be evaluated. The evaluation method is based on the normal distributions Gaussian curves intersection assessment and provides a new point of view to the segmentation method selection.
Farrell, Brian F.; Ioannou, Petros J.
2017-08-01
This paper describes a study of the self-sustaining process in wall turbulence. The study is based on a second order statistical state dynamics model of Couette flow in which the state variables are the streamwise mean flow (first cumulant) and perturbation covariance (second cumulant). This statistical state dynamics model is closed by either setting the third cumulant to zero or by replacing it with a stochastic parametrization. Statistical state dynamics models with this form are referred to as S3T models. S3T models have been shown to self-sustain turbulence with a mean flow and second order perturbation structure similar to that obtained by direct numerical simulation of the equations of motion. The use of a statistical state dynamics model to study the physical mechanisms underlying turbulence has important advantages over the traditional approach of studying the dynamics of individual realizations of turbulence. One advantage is that the analytical structure of S3T statistical state dynamics models isolates the interaction between the mean flow and the perturbation components of the turbulence. Isolation of the interaction between these components reveals how this interaction underlies both the maintenance of the turbulence variance by transfer of energy from the externally driven flow to the perturbation components as well as the enforcement of the observed statistical mean turbulent state by feedback regulation between the mean and perturbation fields. Another advantage of studying turbulence using statistical state dynamics models of S3T form is that the analytical structure of S3T turbulence can be completely characterized. For example, the perturbation component of turbulence in the S3T system is demonstrably maintained by a parametric perturbation growth mechanism in which fluctuation of the mean flow maintains the perturbation field which in turn maintains the mean flow fluctuations in a synergistic interaction. Furthermore, the equilibrium
Lee, Robert H; Bott, Marjorie J; Forbes, Sarah; Redford, Linda; Swagerty, Daniel L; Taunton, Roma Lee
2003-01-01
Understanding how quality improvement affects costs is important. Unfortunately, low-cost, reliable ways of measuring direct costs are scarce. This article builds on the principles of process improvement to develop a costing strategy that meets both criteria. Process-based costing has 4 steps: developing a flowchart, estimating resource use, valuing resources, and calculating direct costs. To illustrate the technique, this article uses it to cost the care planning process in 3 long-term care facilities. We conclude that process-based costing is easy to implement; generates reliable, valid data; and allows nursing managers to assess the costs of new or modified processes.
Statistical Inference for Partially Observed Diffusion Processes
DEFF Research Database (Denmark)
Jensen, Anders Christian
This thesis is concerned with parameter estimation for multivariate diffusion models. It gives a short introduction to diffusion models, and related mathematical concepts. we then introduce the method of prediction-based estimating functions and describe in detail the application for a two......-Uhlenbeck process, while chapter eight describes the detials of an R-package that was developed in relations to the application of the estimationprocedure of chapters five and six....
Directory of Open Access Journals (Sweden)
Vera Devani
2014-06-01
Full Text Available PKS “XYZ” merupakan perusahaan yang bergerak di bidang pengolahan kelapa sawit. Produk yang dihasilkan adalah Crude Palm Oil (CPO dan Palm Kernel Oil (PKO. Tujuan penelitian ini adalah menganalisa kehilangan minyak (oil losses dan faktor-faktor penyebab dengan menggunakan metoda Statistical Process Control. Statistical Process Control adalah sekumpulan strategi, teknik, dan tindakan yang diambil oleh sebuah organisasi untuk memastikan bahwa strategi tersebut menghasilkan produk yang berkualitas atau menyediakan pelayanan yang berkualitas. Sampel terjadinya oil losses pada CPO yang diteliti adalah tandan kosong (tankos, biji (nut, ampas (fibre, dan sludge akhir. Berdasarkan Peta Kendali I-MR dapat disimpulkan bahwa kondisi keempat jenis oil losses CPO berada dalam batas kendali dan konsisten. Sedangkan nilai Cpk dari total oil losses berada di luar batas kendali rata-rata proses, hal ini berarti CPO yang diproduksi telah memenuhi kebutuhan pelanggan, dengan total oil losses kurang dari batas maksimum yang ditetapkan oleh perusahaan yaitu 1,65%.
Statistical reliability analyses of two wood plastic composite extrusion processes
International Nuclear Information System (INIS)
Crookston, Kevin A.; Mark Young, Timothy; Harper, David; Guess, Frank M.
2011-01-01
Estimates of the reliability of wood plastic composites (WPC) are explored for two industrial extrusion lines. The goal of the paper is to use parametric and non-parametric analyses to examine potential differences in the WPC metrics of reliability for the two extrusion lines that may be helpful for use by the practitioner. A parametric analysis of the extrusion lines reveals some similarities and disparities in the best models; however, a non-parametric analysis reveals unique and insightful differences between Kaplan-Meier survival curves for the modulus of elasticity (MOE) and modulus of rupture (MOR) of the WPC industrial data. The distinctive non-parametric comparisons indicate the source of the differences in strength between the 10.2% and 48.0% fractiles [3,183-3,517 MPa] for MOE and for MOR between the 2.0% and 95.1% fractiles [18.9-25.7 MPa]. Distribution fitting as related to selection of the proper statistical methods is discussed with relevance to estimating the reliability of WPC. The ability to detect statistical differences in the product reliability of WPC between extrusion processes may benefit WPC producers in improving product reliability and safety of this widely used house-decking product. The approach can be applied to many other safety and complex system lifetime comparisons.
A powerful score-based test statistic for detecting gene-gene co-association.
Xu, Jing; Yuan, Zhongshang; Ji, Jiadong; Zhang, Xiaoshuai; Li, Hongkai; Wu, Xuesen; Xue, Fuzhong; Liu, Yanxun
2016-01-29
The genetic variants identified by Genome-wide association study (GWAS) can only account for a small proportion of the total heritability for complex disease. The existence of gene-gene joint effects which contains the main effects and their co-association is one of the possible explanations for the "missing heritability" problems. Gene-gene co-association refers to the extent to which the joint effects of two genes differ from the main effects, not only due to the traditional interaction under nearly independent condition but the correlation between genes. Generally, genes tend to work collaboratively within specific pathway or network contributing to the disease and the specific disease-associated locus will often be highly correlated (e.g. single nucleotide polymorphisms (SNPs) in linkage disequilibrium). Therefore, we proposed a novel score-based statistic (SBS) as a gene-based method for detecting gene-gene co-association. Various simulations illustrate that, under different sample sizes, marginal effects of causal SNPs and co-association levels, the proposed SBS has the better performance than other existed methods including single SNP-based and principle component analysis (PCA)-based logistic regression model, the statistics based on canonical correlations (CCU), kernel canonical correlation analysis (KCCU), partial least squares path modeling (PLSPM) and delta-square (δ (2)) statistic. The real data analysis of rheumatoid arthritis (RA) further confirmed its advantages in practice. SBS is a powerful and efficient gene-based method for detecting gene-gene co-association.
International Nuclear Information System (INIS)
Boning, Duane S.; Chung, James E.
1998-01-01
Advanced process technology will require more detailed understanding and tighter control of variation in devices and interconnects. The purpose of statistical metrology is to provide methods to measure and characterize variation, to model systematic and random components of that variation, and to understand the impact of variation on both yield and performance of advanced circuits. Of particular concern are spatial or pattern-dependencies within individual chips; such systematic variation within the chip can have a much larger impact on performance than wafer-level random variation. Statistical metrology methods will play an important role in the creation of design rules for advanced technologies. For example, a key issue in multilayer interconnect is the uniformity of interlevel dielectric (ILD) thickness within the chip. For the case of ILD thickness, we describe phases of statistical metrology development and application to understanding and modeling thickness variation arising from chemical-mechanical polishing (CMP). These phases include screening experiments including design of test structures and test masks to gather electrical or optical data, techniques for statistical decomposition and analysis of the data, and approaches to calibrating empirical and physical variation models. These models can be integrated with circuit CAD tools to evaluate different process integration or design rule strategies. One focus for the generation of interconnect design rules are guidelines for the use of 'dummy fill' or 'metal fill' to improve the uniformity of underlying metal density and thus improve the uniformity of oxide thickness within the die. Trade-offs that can be evaluated via statistical metrology include the improvements to uniformity possible versus the effect of increased capacitance due to additional metal
Application of pedagogy reflective in statistical methods course and practicum statistical methods
Julie, Hongki
2017-08-01
Subject Elementary Statistics, Statistical Methods and Statistical Methods Practicum aimed to equip students of Mathematics Education about descriptive statistics and inferential statistics. The students' understanding about descriptive and inferential statistics were important for students on Mathematics Education Department, especially for those who took the final task associated with quantitative research. In quantitative research, students were required to be able to present and describe the quantitative data in an appropriate manner, to make conclusions from their quantitative data, and to create relationships between independent and dependent variables were defined in their research. In fact, when students made their final project associated with quantitative research, it was not been rare still met the students making mistakes in the steps of making conclusions and error in choosing the hypothetical testing process. As a result, they got incorrect conclusions. This is a very fatal mistake for those who did the quantitative research. There were some things gained from the implementation of reflective pedagogy on teaching learning process in Statistical Methods and Statistical Methods Practicum courses, namely: 1. Twenty two students passed in this course and and one student did not pass in this course. 2. The value of the most accomplished student was A that was achieved by 18 students. 3. According all students, their critical stance could be developed by them, and they could build a caring for each other through a learning process in this course. 4. All students agreed that through a learning process that they undergo in the course, they can build a caring for each other.
The application of statistical process control in linac quality assurance
International Nuclear Information System (INIS)
Li Dingyu; Dai Jianrong
2009-01-01
Objective: To improving linac quality assurance (QA) program with statistical process control (SPC) method. Methods: SPC is applied to set the control limit of QA data, draw charts and differentiate the random and systematic errors. A SPC quality assurance software named QA M ANAGER has been developed by VB programming for clinical use. Two clinical cases are analyzed with SPC to study daily output QA of a 6MV photon beam. Results: In the clinical case, the SPC is able to identify the systematic errors. Conclusion: The SPC application may be assistant to detect systematic errors in linac quality assurance thus it alarms the abnormal trend to eliminate the systematic errors and improves quality control. (authors)
Damage localization by statistical evaluation of signal-processed mode shapes
DEFF Research Database (Denmark)
Ulriksen, Martin Dalgaard; Damkilde, Lars
2015-01-01
Due to their inherent ability to provide structural information on a local level, mode shapes and their derivatives are utilized extensively for structural damage identification. Typically, more or less advanced mathematical methods are implemented to identify damage-induced discontinuities in th...... is conducted on the basis of T2-statistics. The proposed method is demonstrated in the context of analytical work with a free-vibrating Euler-Bernoulli beam under noisy conditions.......) and subsequent application of a generalized discrete Teager-Kaiser energy operator (GDTKEO) to identify damage-induced mode shape discontinuities. In order to evaluate whether the identified discontinuities are in fact damage-induced, outlier analysis of principal components of the signal-processed mode shapes...
Duncan, Fiona; Haigh, Carol
2013-10-01
To explore and improve the quality of continuous epidural analgesia for pain relief using Statistical Process Control tools. Measuring the quality of pain management interventions is complex. Intermittent audits do not accurately capture the results of quality improvement initiatives. The failure rate for one intervention, epidural analgesia, is approximately 30% in everyday practice, so it is an important area for improvement. Continuous measurement and analysis are required to understand the multiple factors involved in providing effective pain relief. Process control and quality improvement Routine prospectively acquired data collection started in 2006. Patients were asked about their pain and side effects of treatment. Statistical Process Control methods were applied for continuous data analysis. A multidisciplinary group worked together to identify reasons for variation in the data and instigated ideas for improvement. The key measure for improvement was a reduction in the percentage of patients with an epidural in severe pain. The baseline control charts illustrated the recorded variation in the rate of several processes and outcomes for 293 surgical patients. The mean visual analogue pain score (VNRS) was four. There was no special cause variation when data were stratified by surgeons, clinical area or patients who had experienced pain before surgery. Fifty-seven per cent of patients were hypotensive on the first day after surgery. We were able to demonstrate a significant improvement in the failure rate of epidurals as the project continued with quality improvement interventions. Statistical Process Control is a useful tool for measuring and improving the quality of pain management. The applications of Statistical Process Control methods offer the potential to learn more about the process of change and outcomes in an Acute Pain Service both locally and nationally. We have been able to develop measures for improvement and benchmarking in routine care that
Szulc, Stefan
1965-01-01
Statistical Methods provides a discussion of the principles of the organization and technique of research, with emphasis on its application to the problems in social statistics. This book discusses branch statistics, which aims to develop practical ways of collecting and processing numerical data and to adapt general statistical methods to the objectives in a given field.Organized into five parts encompassing 22 chapters, this book begins with an overview of how to organize the collection of such information on individual units, primarily as accomplished by government agencies. This text then
Improved model for statistical alignment
Energy Technology Data Exchange (ETDEWEB)
Miklos, I.; Toroczkai, Z. (Zoltan)
2001-01-01
The statistical approach to molecular sequence evolution involves the stochastic modeling of the substitution, insertion and deletion processes. Substitution has been modeled in a reliable way for more than three decades by using finite Markov-processes. Insertion and deletion, however, seem to be more difficult to model, and thc recent approaches cannot acceptably deal with multiple insertions and deletions. A new method based on a generating function approach is introduced to describe the multiple insertion process. The presented algorithm computes the approximate joint probability of two sequences in 0(13) running time where 1 is the geometric mean of the sequence lengths.
Directory of Open Access Journals (Sweden)
Jose M. Bernal-de-Lázaro
2016-05-01
Full Text Available This article summarizes the main contributions of the PhD thesis titled: "Application of learning techniques based on kernel methods for the fault diagnosis in Industrial processes". This thesis focuses on the analysis and design of fault diagnosis systems (DDF based on historical data. Specifically this thesis provides: (1 new criteria for adjustment of the kernel methods used to select features with a high discriminative capacity for the fault diagnosis tasks, (2 a proposed approach process monitoring using statistical techniques multivariate that incorporates a reinforced information concerning to the dynamics of the Hotelling's T2 and SPE statistics, whose combination with kernel methods improves the detection of small-magnitude faults; (3 an robustness index to compare the diagnosis classifiers performance taking into account their insensitivity to possible noise and disturbance on historical data.
Errors in patient specimen collection: application of statistical process control.
Dzik, Walter Sunny; Beckman, Neil; Selleng, Kathleen; Heddle, Nancy; Szczepiorkowski, Zbigniew; Wendel, Silvano; Murphy, Michael
2008-10-01
Errors in the collection and labeling of blood samples for pretransfusion testing increase the risk of transfusion-associated patient morbidity and mortality. Statistical process control (SPC) is a recognized method to monitor the performance of a critical process. An easy-to-use SPC method was tested to determine its feasibility as a tool for monitoring quality in transfusion medicine. SPC control charts were adapted to a spreadsheet presentation. Data tabulating the frequency of mislabeled and miscollected blood samples from 10 hospitals in five countries from 2004 to 2006 were used to demonstrate the method. Control charts were produced to monitor process stability. The participating hospitals found the SPC spreadsheet very suitable to monitor the performance of the sample labeling and collection and applied SPC charts to suit their specific needs. One hospital monitored subcategories of sample error in detail. A large hospital monitored the number of wrong-blood-in-tube (WBIT) events. Four smaller-sized facilities, each following the same policy for sample collection, combined their data on WBIT samples into a single control chart. One hospital used the control chart to monitor the effect of an educational intervention. A simple SPC method is described that can monitor the process of sample collection and labeling in any hospital. SPC could be applied to other critical steps in the transfusion processes as a tool for biovigilance and could be used to develop regional or national performance standards for pretransfusion sample collection. A link is provided to download the spreadsheet for free.
Nakae, Ken; Ikegaya, Yuji; Ishikawa, Tomoe; Oba, Shigeyuki; Urakubo, Hidetoshi; Koyama, Masanori; Ishii, Shin
2014-01-01
Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron–glia network. We attempted to identify neuron–glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP)-based parameter estimation by developing a generalized linear model (GLM) of a neuron–glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron–glia systems. PMID:25393874
Multivariate statistical analysis of a multi-step industrial processes
DEFF Research Database (Denmark)
Reinikainen, S.P.; Høskuldsson, Agnar
2007-01-01
Monitoring and quality control of industrial processes often produce information on how the data have been obtained. In batch processes, for instance, the process is carried out in stages; some process or control parameters are set at each stage. However, the obtained data might not be utilized...... efficiently, even if this information may reveal significant knowledge about process dynamics or ongoing phenomena. When studying the process data, it may be important to analyse the data in the light of the physical or time-wise development of each process step. In this paper, a unified approach to analyse...... multivariate multi-step processes, where results from each step are used to evaluate future results, is presented. The methods presented are based on Priority PLS Regression. The basic idea is to compute the weights in the regression analysis for given steps, but adjust all data by the resulting score vectors...
Karimi, Hamid; O'Brian, Sue; Onslow, Mark; Jones, Mark; Menzies, Ross; Packman, Ann
2013-01-01
Purpose: Stuttering varies between and within speaking situations. In this study, the authors used statistical process control charts with 10 case studies to investigate variability of stuttering frequency. Method: Participants were 10 adults who stutter. The authors counted the percentage of syllables stuttered (%SS) for segments of their speech…
Energy Technology Data Exchange (ETDEWEB)
Teodoro, Rodrigo; Dias, Carla R.B.R.; Osso Junior, Joao A., E-mail: jaosso@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Fernandez Nunez, Eutimio Gustavo [Universidade de Sao Paulo (EP/USP), SP (Brazil). Escola Politecnica. Dept. de Engenharia Quimica
2011-07-01
Precipitation of {sup 99}Mo by {alpha}-benzoin oxime ({alpha}-Bz) is a standard precipitation method for molybdenum due the high selectivity of this agent. Nowadays, statistical analysis tools have been employed in analytical systems to prove its efficiency and feasibility. IPEN has a project aiming the production of {sup 99}Mo by the fission of {sup 235}U route. The processing uses as the first step the precipitation of {sup 99}Mo with {alpha}-Bz. This precipitation step involves many key reaction parameters. The aim of this work is based on the development of the already known acidic route to produce {sup 99}Mo as well as the optimization of the reactional parameters applying statistical tools. In order to simulate {sup 99}Mo precipitation, the study was conducted in acidic media using HNO{sub 3}, {alpha}Bz as precipitant agent and NaOH /1%H{sub 2}O{sub 2} as dissolver solution. Then, a Mo carrier, KMnO{sub 4} solutions and {sup 99}Mo tracer were added to the reaction flask. The reactional parameters ({alpha}-Bz/Mo ratio, Mo carrier, reaction time and temperature, and cooling reaction time before filtration) were evaluated under a fractional factorial design of resolution V. The best values of each reactional parameter were determined by a response surface statistical planning. The precipitation and recovery yields of {sup 99}Mo were measured using HPGe detector. Statistical analysis from experimental data suggested that the reactional parameters {alpha}-Bz/Mo ratio, reaction time and temperature have a significant impact on {sup 99}Mo precipitation. Optimization statistical planning showed that higher {alpha}Bz/Mo ratios, room temperature, and lower reaction time lead to higher {sup 99}Mo yields. (author)
Directory of Open Access Journals (Sweden)
Partha Sindu I Gede
2018-01-01
Full Text Available The purpose of this study was to determine the effect of the use of the instructional media based on lecture video and slide synchronization system on Statistics learning achievement of the students of PTI department . The benefit of this research is to help lecturers in the instructional process i to improve student's learning achievements that lead to better students’ learning outcomes. Students can use instructional media which is created from the lecture video and slide synchronization system to support more interactive self-learning activities. Students can conduct learning activities more efficiently and conductively because synchronized lecture video and slide can assist students in the learning process. The population of this research was all students of semester VI (six majoring in Informatics Engineering Education. The sample of the research was the students of class VI B and VI D of the academic year 2016/2017. The type of research used in this study was quasi-experiment. The research design used was post test only with non equivalent control group design. The result of this research concluded that there was a significant influence in the application of learning media based on lectures video and slide synchronization system on statistics learning result on PTI department.
International Nuclear Information System (INIS)
Kim, K.; Devred, A.; Coles, M.; Tompkins, J.
1993-05-01
All of the SSC production magnets will be measured at room temperature (warm), but only a fraction of these will be measured at liquid helium temperature (cold). The fractional information will then be analyzed to determine warm acceptance criteria for the field quality of the SSC magnets. Regarding predictors of the field quality based on partial information, there are several observations and studies based on the warm/cold correlation. A different facet of the acceptance test is production control, which interprets the warm/cold correlation to adjust the process parameters. For these applications, we are evaluating statistical techniques relying on asymptotic estimators of the systematic errors and random errors, and their respective confidence intervals. The estimators are useful to qualify the population magnets based on a subset of sample magnets. We present the status of our work, including: (i) a recapitulation of analytic formulas, (ii) a justification based on HERA magnet experience, and (iii) a practical interpretation of these estimators
Improved air ventilation rate estimation based on a statistical model
International Nuclear Information System (INIS)
Brabec, M.; Jilek, K.
2004-01-01
A new approach to air ventilation rate estimation from CO measurement data is presented. The approach is based on a state-space dynamic statistical model, allowing for quick and efficient estimation. Underlying computations are based on Kalman filtering, whose practical software implementation is rather easy. The key property is the flexibility of the model, allowing various artificial regimens of CO level manipulation to be treated. The model is semi-parametric in nature and can efficiently handle time-varying ventilation rate. This is a major advantage, compared to some of the methods which are currently in practical use. After a formal introduction of the statistical model, its performance is demonstrated on real data from routine measurements. It is shown how the approach can be utilized in a more complex situation of major practical relevance, when time-varying air ventilation rate and radon entry rate are to be estimated simultaneously from concurrent radon and CO measurements
Categorical data processing for real estate objects valuation using statistical analysis
Parygin, D. S.; Malikov, V. P.; Golubev, A. V.; Sadovnikova, N. P.; Petrova, T. M.; Finogeev, A. G.
2018-05-01
Theoretical and practical approaches to the use of statistical methods for studying various properties of infrastructure objects are analyzed in the paper. Methods of forecasting the value of objects are considered. A method for coding categorical variables describing properties of real estate objects is proposed. The analysis of the results of modeling the price of real estate objects using regression analysis and an algorithm based on a comparative approach is carried out.
On the fractal characterization of Paretian Poisson processes
Eliazar, Iddo I.; Sokolov, Igor M.
2012-06-01
Paretian Poisson processes are Poisson processes which are defined on the positive half-line, have maximal points, and are quantified by power-law intensities. Paretian Poisson processes are elemental in statistical physics, and are the bedrock of a host of power-law statistics ranging from Pareto's law to anomalous diffusion. In this paper we establish evenness-based fractal characterizations of Paretian Poisson processes. Considering an array of socioeconomic evenness-based measures of statistical heterogeneity, we show that: amongst the realm of Poisson processes which are defined on the positive half-line, and have maximal points, Paretian Poisson processes are the unique class of 'fractal processes' exhibiting scale-invariance. The results established in this paper are diametric to previous results asserting that the scale-invariance of Poisson processes-with respect to physical randomness-based measures of statistical heterogeneity-is characterized by exponential Poissonian intensities.
Lee, Rena; Kim, Kyubo; Cho, Samju; Lim, Sangwook; Lee, Suk; Shim, Jang Bo; Huh, Hyun Do; Lee, Sang Hoon; Ahn, Sohyun
2017-11-01
This study applied statistical process control to set and verify the quality assurances (QA) tolerance standard for our hospital's characteristics with the criteria standards that are applied to all the treatment sites with this analysis. Gamma test factor of delivery quality assurances (DQA) was based on 3%/3 mm. Head and neck, breast, prostate cases of intensity modulated radiation therapy (IMRT) or volumetric arc radiation therapy (VMAT) were selected for the analysis of the QA treatment sites. The numbers of data used in the analysis were 73 and 68 for head and neck patients. Prostate and breast were 49 and 152 by MapCHECK and ArcCHECK respectively. C p value of head and neck and prostate QA were above 1.0, C pml is 1.53 and 1.71 respectively, which is close to the target value of 100%. C pml value of breast (IMRT) was 1.67, data values are close to the target value of 95%. But value of was 0.90, which means that the data values are widely distributed. C p and C pml of breast VMAT QA were respectively 1.07 and 2.10. This suggests that the VMAT QA has better process capability than the IMRT QA. Consequently, we should pay more attention to planning and QA before treatment for breast Radiotherapy.
Smith, Toni M.; Hjalmarson, Margret A.
2013-01-01
The purpose of this study is to examine prospective mathematics specialists' engagement in an instructional sequence designed to elicit and develop their understandings of random processes. The study was conducted with two different sections of a probability and statistics course for K-8 teachers. Thirty-two teachers participated. Video analyses…
A bibliometric analysis of 50 years of worldwide research on statistical process control
Directory of Open Access Journals (Sweden)
Fabiane Letícia Lizarelli
Full Text Available Abstract An increasing number of papers on statistical process control (SPC has emerged in the last fifty years, especially in the last fifteen years. This may be attributed to the increased global competitiveness generated by innovation and the continuous improvement of products and processes. In this sense, SPC has a fundamentally important role in quality and production systems. The research in this paper considers the context of technological improvement and innovation of products and processes to increase corporate competitiveness. There are several other statistical technics and tools for assisting continuous improvement and innovation of products and processes but, despite the limitations in their use in the improvement projects, there is growing concern about the use of SPC. A gap between the SPC technics taught in engineering courses and their practical applications to industrial problems is observed in empirical research; thus, it is important to understand what has been done and identify the trends in SPC research. The bibliometric study in this paper is proposed in this direction and uses the Web of Science (WoS database. Data analysis indicates that there was a growth rate of more than 90% in the number of publications on SPC after 1990. Our results reveal the countries where these publications have come from, the authors with the highest number of papers and their networks. Main sources of publications are also identified; it is observed that the publications of SPC papers are concentrated in some of the international research journals, not necessarily those with the major high-impact factors. Furthermore, the papers are focused on industrial engineering, operations research and management science fields. The most common term found in the papers was cumulative sum control charts, but new topics have emerged and have been researched in the past ten years, such as multivariate methods for process monitoring and nonparametric methods.
Statistical methods to assess and control processes and products during nuclear fuel fabrication
International Nuclear Information System (INIS)
Weidinger, H.
1999-01-01
Very good statistical tools and techniques are available today to access the quality and the reliability of fabrication process as the original sources for a good and reliable quality of the fabricated processes. Quality control charts of different types play a key role and the high capability of modern electronic data acquisition technologies proved, at least potentially, a high efficiency in the more or less online application of these methods. These techniques focus mainly on stability and the reliability of the fabrication process. In addition, relatively simple statistical tolls are available to access the capability of fabrication process, assuming they are stable, to fulfill the product specifications. All these techniques can only result in as good a product as the product design is able to describe the product requirements necessary for good performance. Therefore it is essential that product design is strictly and closely performance oriented. However, performance orientation is only successful through an open and effective cooperation with the customer who uses or applies those products. During the last one to two decades in the west, a multi-vendor strategy has been developed by the utility, sometimes leading to three different fuel vendors for one reactor core. This development resulted in better economic conditions for the user but did not necessarily increase an open attitude with the vendor toward the using utility. The responsibility of the utility increased considerably to ensure an adequate quality of the fuel they received. As a matter of fact, sometimes the utilities had to pay a high price because of unexpected performance problems. Thus the utilities are now learning that they need to increase their knowledge and experience in the area of nuclear fuel quality management and technology. This process started some time ago in the west. However, it now also reaches the utilities in the eastern countries. (author)
Nicolae Lerma, Alexandre; Bulteau, Thomas; Elineau, Sylvain; Paris, François; Durand, Paul; Anselme, Brice; Pedreros, Rodrigo
2018-01-01
A modelling chain was implemented in order to propose a realistic appraisal of the risk in coastal areas affected by overflowing as well as overtopping processes. Simulations are performed through a nested downscaling strategy from regional to local scale at high spatial resolution with explicit buildings, urban structures such as sea front walls and hydraulic structures liable to affect the propagation of water in urban areas. Validation of the model performance is based on hard and soft available data analysis and conversion of qualitative to quantitative information to reconstruct the area affected by flooding and the succession of events during two recent storms. Two joint probability approaches (joint exceedance contour and environmental contour) are used to define 100-year offshore conditions scenarios and to investigate the flood response to each scenario in terms of (1) maximum spatial extent of flooded areas, (2) volumes of water propagation inland and (3) water level in flooded areas. Scenarios of sea level rise are also considered in order to evaluate the potential hazard evolution. Our simulations show that for a maximising 100-year hazard scenario, for the municipality as a whole, 38 % of the affected zones are prone to overflow flooding and 62 % to flooding by propagation of overtopping water volume along the seafront. Results also reveal that for the two kinds of statistic scenarios a difference of about 5 % in the forcing conditions (water level, wave height and period) can produce significant differences in terms of flooding like +13.5 % of water volumes propagating inland or +11.3 % of affected surfaces. In some areas, flood response appears to be very sensitive to the chosen scenario with differences of 0.3 to 0.5 m in water level. The developed approach enables one to frame the 100-year hazard and to characterize spatially the robustness or the uncertainty over the results. Considering a 100-year scenario with mean sea level rise (0.6 m), hazard
BTS statistical standards manual
2005-10-01
The Bureau of Transportation Statistics (BTS), like other federal statistical agencies, establishes professional standards to guide the methods and procedures for the collection, processing, storage, and presentation of statistical data. Standards an...
Statistical Learning Framework with Adaptive Retraining for Condition-Based Maintenance
International Nuclear Information System (INIS)
An, Sang Ha; Chang, Soon Heung; Heo, Gyun Young; Seo, Ho Joon; Kim, Su Young
2009-01-01
As systems become more complex and more critical in our daily lives, the need for the maintenance based on the reliable monitoring and diagnosis has become more apparent. However, in reality, the general opinion has been that 'maintenance is a necessary evil' or 'nothing can be done to improve maintenance costs'. Perhaps these were true statements twenty years ago when many of the diagnostic technologies were not fully developed. The developments of microprocessor or computer based instrumentation that can be used to monitor the operating condition of plant equipment, machinery and systems have provided the means to manage the maintenance operation. They have provided the means to reduce or eliminate unnecessary repairs, prevent catastrophic machine failures and reduce the negative impact of the maintenance operation on the profitability of manufacturing and production plants. Condition-based maintenance (CBM) techniques help determine the condition of in-service equipment in order to predict when maintenance should be performed. Most of the statistical learning techniques are only valid as long as the physics of a system does not change. If any significant change such as the replacement of a component or equipment occurs in the system, the statistical learning model should be re-trained or re-developed to adapt the new system. In this research, authors will propose a statistical learning framework which can be applicable for various CBMs, and the concept of the adaptive retraining technique will be described to support the execution of the framework so that the monitoring system does not need to be re-developed or re-trained even though there are any significant changes in the system or component
Hart, Carl R; Reznicek, Nathan J; Wilson, D Keith; Pettit, Chris L; Nykaza, Edward T
2016-05-01
Many outdoor sound propagation models exist, ranging from highly complex physics-based simulations to simplified engineering calculations, and more recently, highly flexible statistical learning methods. Several engineering and statistical learning models are evaluated by using a particular physics-based model, namely, a Crank-Nicholson parabolic equation (CNPE), as a benchmark. Narrowband transmission loss values predicted with the CNPE, based upon a simulated data set of meteorological, boundary, and source conditions, act as simulated observations. In the simulated data set sound propagation conditions span from downward refracting to upward refracting, for acoustically hard and soft boundaries, and low frequencies. Engineering models used in the comparisons include the ISO 9613-2 method, Harmonoise, and Nord2000 propagation models. Statistical learning methods used in the comparisons include bagged decision tree regression, random forest regression, boosting regression, and artificial neural network models. Computed skill scores are relative to sound propagation in a homogeneous atmosphere over a rigid ground. Overall skill scores for the engineering noise models are 0.6%, -7.1%, and 83.8% for the ISO 9613-2, Harmonoise, and Nord2000 models, respectively. Overall skill scores for the statistical learning models are 99.5%, 99.5%, 99.6%, and 99.6% for bagged decision tree, random forest, boosting, and artificial neural network regression models, respectively.
Statistics for Learning Genetics
Charles, Abigail Sheena
This study investigated the knowledge and skills that biology students may need to help them understand statistics/mathematics as it applies to genetics. The data are based on analyses of current representative genetics texts, practicing genetics professors' perspectives, and more directly, students' perceptions of, and performance in, doing statistically-based genetics problems. This issue is at the emerging edge of modern college-level genetics instruction, and this study attempts to identify key theoretical components for creating a specialized biological statistics curriculum. The goal of this curriculum will be to prepare biology students with the skills for assimilating quantitatively-based genetic processes, increasingly at the forefront of modern genetics. To fulfill this, two college level classes at two universities were surveyed. One university was located in the northeastern US and the other in the West Indies. There was a sample size of 42 students and a supplementary interview was administered to a select 9 students. Interviews were also administered to professors in the field in order to gain insight into the teaching of statistics in genetics. Key findings indicated that students had very little to no background in statistics (55%). Although students did perform well on exams with 60% of the population receiving an A or B grade, 77% of them did not offer good explanations on a probability question associated with the normal distribution provided in the survey. The scope and presentation of the applicable statistics/mathematics in some of the most used textbooks in genetics teaching, as well as genetics syllabi used by instructors do not help the issue. It was found that the text books, often times, either did not give effective explanations for students, or completely left out certain topics. The omission of certain statistical/mathematical oriented topics was seen to be also true with the genetics syllabi reviewed for this study. Nonetheless
Spherical Process Models for Global Spatial Statistics
Jeong, Jaehong; Jun, Mikyoung; Genton, Marc G.
2017-01-01
Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture
THE INTEGRATED SHORT-TERM STATISTICAL SURVEYS: EXPERIENCE OF NBS IN MOLDOVA
Directory of Open Access Journals (Sweden)
Oleg CARA
2012-07-01
Full Text Available The users’ rising need for relevant, reliable, coherent, timely data for the early diagnosis of the economic vulnerability and of the turning points in the business cycles, especially during a financial and economic crisis, asks for a prompt answer, coordinated by statistical institutions. High quality short term statistics are of special interest for the emerging market economies, such as the Moldavian one, being extremely vulnerable when facing economic recession. Answering to the challenges of producing a coherent and adequate image of the economic activity, by using the system of indicators and definitions efficiently applied at the level of the European Union, the National Bureau of Statistics (NBS of the Republic of Moldova has launched the development process of an integrated system of short term statistics (STS based on the advanced international experience.Thus, in 2011, BNS implemented the integrated statistical survey on STS based on consistent concepts, harmonized with the EU standards. The integration of the production processes, which were previously separated, is based on a common technical infrastructure, standardized procedures and techniques for data production. The achievement of this complex survey with holistic approach has allowed the consolidation of the statistical data quality, comparable at European level and the signifi cant reduction of information burden on business units, especially of small size.The reformation of STS based on the integrated survey has been possible thanks to the consistent methodological and practical support given to NBS by the National Institute of Statistics (INS of Romania, for which we would like to thank to our Romanian colleagues.
A Statistics-Based Material Property Analysis to Support TPS Characterization
Copeland, Sean R.; Cozmuta, Ioana; Alonso, Juan J.
2012-01-01
Accurate characterization of entry capsule heat shield material properties is a critical component in modeling and simulating Thermal Protection System (TPS) response in a prescribed aerothermal environment. The thermal decomposition of the TPS material during the pyrolysis and charring processes is poorly characterized and typically results in large uncertainties in material properties as inputs for ablation models. These material property uncertainties contribute to large design margins on flight systems and cloud re- construction efforts for data collected during flight and ground testing, making revision to existing models for entry systems more challenging. The analysis presented in this work quantifies how material property uncertainties propagate through an ablation model and guides an experimental test regimen aimed at reducing these uncertainties and characterizing the dependencies between properties in the virgin and charred states for a Phenolic Impregnated Carbon Ablator (PICA) based TPS. A sensitivity analysis identifies how the high-fidelity model behaves in the expected flight environment, while a Monte Carlo based uncertainty propagation strategy is used to quantify the expected spread in the in-depth temperature response of the TPS. An examination of how perturbations to the input probability density functions affect output temperature statistics is accomplished using a Kriging response surface of the high-fidelity model. Simulations are based on capsule configuration and aerothermal environments expected during the Mars Science Laboratory (MSL) entry sequence. We identify and rank primary sources of uncertainty from material properties in a flight-relevant environment, show the dependence on spatial orientation and in-depth location on those uncertainty contributors, and quantify how sensitive the expected results are.
Kreyenfeld, Michaela; Peters, Frederik; Scholz, Rembrandt; Wlosnewski, Ines
2014-01-01
Until 2008, German vital statistics has not provided information on biological birth order. We have tried to close part of this gap by providing order-specific fertility rates generated from Perinatal Statistics and statistics on out-of-hospital births for the period 2001-2008. This investigation has been published in Comparative Population Studies (CPoS) (see Kreyenfeld, Scholz, Peters and Wlosnewski 2010). The CPoS-paper describes how data from the Perinatal Statistics and statistics on out...
Fitting the Statistical Distribution for Daily Rainfall in Ibadan, Based ...
African Journals Online (AJOL)
PROF. O. E. OSUAGWU
2013-06-01
Jun 1, 2013 ... Abstract. This paper presents several types of statistical distributions to describe rainfall distribution in Ibadan metropolis over a period of 30 years. The exponential, gamma, normal and poison distributions are compared to identify the optimal model for daily rainfall amount based on data recorded at rain ...
The Practicality of Statistical Physics Handout Based on KKNI and the Constructivist Approach
Sari, S. Y.; Afrizon, R.
2018-04-01
Statistical physics lecture shows that: 1) the performance of lecturers, social climate, students’ competence and soft skills needed at work are in enough category, 2) students feel difficulties in following the lectures of statistical physics because it is abstract, 3) 40.72% of students needs more understanding in the form of repetition, practice questions and structured tasks, and 4) the depth of statistical physics material needs to be improved gradually and structured. This indicates that learning materials in accordance of The Indonesian National Qualification Framework or Kerangka Kualifikasi Nasional Indonesia (KKNI) with the appropriate learning approach are needed to help lecturers and students in lectures. The author has designed statistical physics handouts which have very valid criteria (90.89%) according to expert judgment. In addition, the practical level of handouts designed also needs to be considered in order to be easy to use, interesting and efficient in lectures. The purpose of this research is to know the practical level of statistical physics handout based on KKNI and a constructivist approach. This research is a part of research and development with 4-D model developed by Thiagarajan. This research activity has reached part of development test at Development stage. Data collection took place by using a questionnaire distributed to lecturers and students. Data analysis using descriptive data analysis techniques in the form of percentage. The analysis of the questionnaire shows that the handout of statistical physics has very practical criteria. The conclusion of this study is statistical physics handouts based on the KKNI and constructivist approach have been practically used in lectures.
A General Accelerated Degradation Model Based on the Wiener Process.
Liu, Le; Li, Xiaoyang; Sun, Fuqiang; Wang, Ning
2016-12-06
Accelerated degradation testing (ADT) is an efficient tool to conduct material service reliability and safety evaluations by analyzing performance degradation data. Traditional stochastic process models are mainly for linear or linearization degradation paths. However, those methods are not applicable for the situations where the degradation processes cannot be linearized. Hence, in this paper, a general ADT model based on the Wiener process is proposed to solve the problem for accelerated degradation data analysis. The general model can consider the unit-to-unit variation and temporal variation of the degradation process, and is suitable for both linear and nonlinear ADT analyses with single or multiple acceleration variables. The statistical inference is given to estimate the unknown parameters in both constant stress and step stress ADT. The simulation example and two real applications demonstrate that the proposed method can yield reliable lifetime evaluation results compared with the existing linear and time-scale transformation Wiener processes in both linear and nonlinear ADT analyses.
A General Accelerated Degradation Model Based on the Wiener Process
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Le Liu
2016-12-01
Full Text Available Accelerated degradation testing (ADT is an efficient tool to conduct material service reliability and safety evaluations by analyzing performance degradation data. Traditional stochastic process models are mainly for linear or linearization degradation paths. However, those methods are not applicable for the situations where the degradation processes cannot be linearized. Hence, in this paper, a general ADT model based on the Wiener process is proposed to solve the problem for accelerated degradation data analysis. The general model can consider the unit-to-unit variation and temporal variation of the degradation process, and is suitable for both linear and nonlinear ADT analyses with single or multiple acceleration variables. The statistical inference is given to estimate the unknown parameters in both constant stress and step stress ADT. The simulation example and two real applications demonstrate that the proposed method can yield reliable lifetime evaluation results compared with the existing linear and time-scale transformation Wiener processes in both linear and nonlinear ADT analyses.
Jandrisevits, Carmen; Marschallinger, Robert
2014-05-01
/erosional processes and geometric shapes of hydrofacies can be integrated. The Training Image can be constructed with object based Training Image generators which offer predefined geometric shapes for modeling sediment facies associations. Training Images can also be constructed in a Computer Aided Design (CAD) system. Non-uniform rational B-Splines are implemented in CAD systems and enable to generate even more realistic geometric shapes of sediment bodies than by means of object based training image generators. Multiple Point Statistics Simulation aims to produce local patterns from the Training Image and conditionally anchor them to the investigation data. Regarding geometric shapes and lateral extensions of derived sediment structures, the Multiple Point Statistics simulations yielded the most sensible hydrofacies models while reproducing input data proportions.
The rule of nuclear power in the base-load portfolio optimization process
International Nuclear Information System (INIS)
Desiata, L.; D'Alberti, F.
2007-01-01
The pursuit of optimal portfolios, maximizing long-term profitability, is the main strategic challenge faced by electricity producers nowadays. Investment decisions, worth billions of euros, are affected by spot factors (such as current fuel prices volatility) that often lead to unbalanced generation mixes. Our analysis presents a statistical-financial approach that highlights the role of nuclear within the base-load portfolio optimisation process [it
Directory of Open Access Journals (Sweden)
Fabiano Rodrigues Soriano
Full Text Available Abstract The Statistical Process Control - SPC is a set of statistical techniques focused on process control, monitoring and analyzing variation causes in the quality characteristics and/or in the parameters used to control and process improvements. Implementing SPC in organizations is a complex task. The reasons for its failure are related to organizational or social factors such as lack of top management commitment and little understanding about its potential benefits. Other aspects concern technical factors such as lack of training on and understanding about the statistical techniques. The main aim of the present article is to understand the interrelations between conditioning factors associated with top management commitment (Support, SPC Training and Application, as well as to understand the relationships between these factors and the benefits associated with the implementation of the program. The Partial Least Squares Structural Equation Modeling (PLS-SEM was used in the analysis since the main goal is to establish the causal relations. A cross-section survey was used as research method to collect information of samples from Brazilian auto-parts companies, which were selected according to guides from the auto-parts industry associations. A total of 170 companies were contacted by e-mail and by phone in order to be invited to participate in the survey. However, just 93 industries agreed on participating, and only 43 answered the questionnaire. The results showed that the senior management support considerably affects the way companies develop their training programs. In turn, these trainings affect the way companies apply the techniques. Thus, it will reflect on the benefits gotten from implementing the program. It was observed that the managerial and technical aspects are closely connected to each other and that they are represented by the ratio between top management and training support. The technical aspects observed through SPC
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Vahid Reza Jalali
2017-10-01
water was taken from Maharlu Lake, Fars province, Iran. This natural and highly saline water with electrical conductivity of 512 dS/m diluted with fresh water to obtain the designated saline waters required for the experimental treatments. The designed experimental treatments were consisted of a non-saline water and five salinity levels of 2, 4, 6, 8 and 10 dS/m with three replicates. Three statistics of modified coefficient efficiency (E', modified index of agreement (d' and coefficient of residual mass (CRM were used to compare the used models and to assess their performances. Results and discussion Comparing the relative performance of models based on statistical indices of Modified Coefficient Efficiency (E' and Modified Index of agreement (d' indicated that the nonlinear model of Homaee et al. is most accurate between process-physical models and Modified Gompertz Function is most accurate between statistical-experimental models. Comparison assessment of all models based on statistical index indicated that Homaee et al. model was the most accurate model for simulation of durum wheat yield. This is while the parameters of Homaee et al. equation is well-defined concept and is easily measurable, but in statistical-experimental models, parameters of each model have no biophysical concept and the absolute values of each parameter do not express any information about development status of the plant. So, the nonlinear model of Homaee et al. was chosen as the optimal model in this research. Conclusion Most of the plants such as wheat, are sensitive to salinity and by increasing the age, their sensitivity to salinity are reduced. Based on the obtained results of this study, by knowing and quantitative assessment of the dominant cultivars sensitivity of each region, as well as using appropriate simulation models, one can use brackish or saline waters to partly compensate fresh water shortage for scientific and extension Agricultural programs.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Gyro's fault diagnosis plays a critical role in inertia navigation systems for higher reliability and precision. A new fault diagnosis strategy based on the statistical parameter analysis (SPA) and support vector machine(SVM) classification model was proposed for dynamically tuned gyroscopes (DTG). The SPA, a kind of time domain analysis approach, was introduced to compute a set of statistical parameters of vibration signal as the state features of DTG, with which the SVM model, a novel learning machine based on statistical learning theory (SLT), was applied and constructed to train and identify the working state of DTG. The experimental results verify that the proposed diagnostic strategy can simply and effectively extract the state features of DTG, and it outperforms the radial-basis function (RBF) neural network based diagnostic method and can more reliably and accurately diagnose the working state of DTG.
Parisi Kern, Andrea; Ferreira Dias, Michele; Piva Kulakowski, Marlova; Paulo Gomes, Luciana
2015-05-01
Reducing construction waste is becoming a key environmental issue in the construction industry. The quantification of waste generation rates in the construction sector is an invaluable management tool in supporting mitigation actions. However, the quantification of waste can be a difficult process because of the specific characteristics and the wide range of materials used in different construction projects. Large variations are observed in the methods used to predict the amount of waste generated because of the range of variables involved in construction processes and the different contexts in which these methods are employed. This paper proposes a statistical model to determine the amount of waste generated in the construction of high-rise buildings by assessing the influence of design process and production system, often mentioned as the major culprits behind the generation of waste in construction. Multiple regression was used to conduct a case study based on multiple sources of data of eighteen residential buildings. The resulting statistical model produced dependent (i.e. amount of waste generated) and independent variables associated with the design and the production system used. The best regression model obtained from the sample data resulted in an adjusted R(2) value of 0.694, which means that it predicts approximately 69% of the factors involved in the generation of waste in similar constructions. Most independent variables showed a low determination coefficient when assessed in isolation, which emphasizes the importance of assessing their joint influence on the response (dependent) variable. Copyright © 2015 Elsevier Ltd. All rights reserved.
Capturing rogue waves by multi-point statistics
International Nuclear Information System (INIS)
Hadjihosseini, A; Wächter, Matthias; Peinke, J; Hoffmann, N P
2016-01-01
As an example of a complex system with extreme events, we investigate ocean wave states exhibiting rogue waves. We present a statistical method of data analysis based on multi-point statistics which for the first time allows the grasping of extreme rogue wave events in a highly satisfactory statistical manner. The key to the success of the approach is mapping the complexity of multi-point data onto the statistics of hierarchically ordered height increments for different time scales, for which we can show that a stochastic cascade process with Markov properties is governed by a Fokker–Planck equation. Conditional probabilities as well as the Fokker–Planck equation itself can be estimated directly from the available observational data. With this stochastic description surrogate data sets can in turn be generated, which makes it possible to work out arbitrary statistical features of the complex sea state in general, and extreme rogue wave events in particular. The results also open up new perspectives for forecasting the occurrence probability of extreme rogue wave events, and even for forecasting the occurrence of individual rogue waves based on precursory dynamics. (paper)
A comparison of test statistics for the recovery of rapid growth-based enumeration tests
van den Heuvel, Edwin R.; IJzerman-Boon, Pieta C.
This paper considers five test statistics for comparing the recovery of a rapid growth-based enumeration test with respect to the compendial microbiological method using a specific nonserial dilution experiment. The finite sample distributions of these test statistics are unknown, because they are
Practical application and statistical analysis of titrimetric monitoring ...
African Journals Online (AJOL)
2008-09-18
Sep 18, 2008 ... The statistical tests showed that, depending on the titrant concentration ... The ASD process offers the possibility of transferring waste streams into ..... (1993) Weak acid/bases and pH control in anaerobic system – A review.
Whole vertebral bone segmentation method with a statistical intensity-shape model based approach
Hanaoka, Shouhei; Fritscher, Karl; Schuler, Benedikt; Masutani, Yoshitaka; Hayashi, Naoto; Ohtomo, Kuni; Schubert, Rainer
2011-03-01
An automatic segmentation algorithm for the vertebrae in human body CT images is presented. Especially we focused on constructing and utilizing 4 different statistical intensity-shape combined models for the cervical, upper / lower thoracic and lumbar vertebrae, respectively. For this purpose, two previously reported methods were combined: a deformable model-based initial segmentation method and a statistical shape-intensity model-based precise segmentation method. The former is used as a pre-processing to detect the position and orientation of each vertebra, which determines the initial condition for the latter precise segmentation method. The precise segmentation method needs prior knowledge on both the intensities and the shapes of the objects. After PCA analysis of such shape-intensity expressions obtained from training image sets, vertebrae were parametrically modeled as a linear combination of the principal component vectors. The segmentation of each target vertebra was performed as fitting of this parametric model to the target image by maximum a posteriori estimation, combined with the geodesic active contour method. In the experimental result by using 10 cases, the initial segmentation was successful in 6 cases and only partially failed in 4 cases (2 in the cervical area and 2 in the lumbo-sacral). In the precise segmentation, the mean error distances were 2.078, 1.416, 0.777, 0.939 mm for cervical, upper and lower thoracic, lumbar spines, respectively. In conclusion, our automatic segmentation algorithm for the vertebrae in human body CT images showed a fair performance for cervical, thoracic and lumbar vertebrae.
The statistical stability phenomenon
Gorban, Igor I
2017-01-01
This monograph investigates violations of statistical stability of physical events, variables, and processes and develops a new physical-mathematical theory taking into consideration such violations – the theory of hyper-random phenomena. There are five parts. The first describes the phenomenon of statistical stability and its features, and develops methods for detecting violations of statistical stability, in particular when data is limited. The second part presents several examples of real processes of different physical nature and demonstrates the violation of statistical stability over broad observation intervals. The third part outlines the mathematical foundations of the theory of hyper-random phenomena, while the fourth develops the foundations of the mathematical analysis of divergent and many-valued functions. The fifth part contains theoretical and experimental studies of statistical laws where there is violation of statistical stability. The monograph should be of particular interest to engineers...
Learning Axes and Bridging Tools in a Technology-Based Design for Statistics
Abrahamson, Dor; Wilensky, Uri
2007-01-01
We introduce a design-based research framework, "learning axes and bridging tools," and demonstrate its application in the preparation and study of an implementation of a middle-school experimental computer-based unit on probability and statistics, "ProbLab" (Probability Laboratory, Abrahamson and Wilensky 2002 [Abrahamson, D., & Wilensky, U.…
Statistical learning problem of artificial neural network to control roofing process
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Lapidus Azariy
2017-01-01
Full Text Available Now software developed on the basis of artificial neural networks (ANN has been actively implemented in construction companies to support decision-making in organization and management of construction processes. ANN learning is the main stage of its development. A key question for supervised learning is how many number of training examples we need to approximate the true relationship between network inputs and output with the desired accuracy. Also designing of ANN architecture is related to learning problem known as “curse of dimensionality”. This problem is important for the study of construction process management because of the difficulty to get training data from construction sites. In previous studies the authors have designed a 4-layer feedforward ANN with a unit model of 12-5-4-1 to approximate estimation and prediction of roofing process. This paper presented the statistical learning side of created ANN with simple-error-minimization algorithm. The sample size to efficient training and the confidence interval of network outputs defined. In conclusion the authors predicted successful ANN learning in a large construction business company within a short space of time.
Matthews, Tansy E.
2009-01-01
This article describes the development of the Virtual Library of Virginia (VIVA). The VIVA statistics-processing system remains a work in progress. Member libraries will benefit from the ability to obtain the actual data from the VIVA site, rather than just the summaries, so a project to make these data available is currently being planned. The…
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Zhai Chengxiang
2010-05-01
Full Text Available Abstract Background Large-scale genomic studies often identify large gene lists, for example, the genes sharing the same expression patterns. The interpretation of these gene lists is generally achieved by extracting concepts overrepresented in the gene lists. This analysis often depends on manual annotation of genes based on controlled vocabularies, in particular, Gene Ontology (GO. However, the annotation of genes is a labor-intensive process; and the vocabularies are generally incomplete, leaving some important biological domains inadequately covered. Results We propose a statistical method that uses the primary literature, i.e. free-text, as the source to perform overrepresentation analysis. The method is based on a statistical framework of mixture model and addresses the methodological flaws in several existing programs. We implemented this method within a literature mining system, BeeSpace, taking advantage of its analysis environment and added features that facilitate the interactive analysis of gene sets. Through experimentation with several datasets, we showed that our program can effectively summarize the important conceptual themes of large gene sets, even when traditional GO-based analysis does not yield informative results. Conclusions We conclude that the current work will provide biologists with a tool that effectively complements the existing ones for overrepresentation analysis from genomic experiments. Our program, Genelist Analyzer, is freely available at: http://workerbee.igb.uiuc.edu:8080/BeeSpace/Search.jsp
DE-STRIPING FOR TDICCD REMOTE SENSING IMAGE BASED ON STATISTICAL FEATURES OF HISTOGRAM
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H.-T. Gao
2016-06-01
Full Text Available Aim to striping noise brought by non-uniform response of remote sensing TDI CCD, a novel de-striping method based on statistical features of image histogram is put forward. By analysing the distribution of histograms,the centroid of histogram is selected to be an eigenvalue representing uniformity of ground objects,histogrammic centroid of whole image and each pixels are calculated first,the differences between them are regard as rough correction coefficients, then in order to avoid the sensitivity caused by single parameter and considering the strong continuity and pertinence of ground objects between two adjacent pixels,correlation coefficient of the histograms is introduces to reflect the similarities between them,fine correction coefficient is obtained by searching around the rough correction coefficient,additionally,in view of the influence of bright cloud on histogram,an automatic cloud detection based on multi-feature including grey level,texture,fractal dimension and edge is used to pre-process image.Two 0-level panchromatic images of SJ-9A satellite with obvious strip noise are processed by proposed method to evaluate the performance, results show that the visual quality of images are improved because the strip noise is entirely removed,we quantitatively analyse the result by calculating the non-uniformity ,which has reached about 1% and is better than histogram matching method.
Statistical process control analysis for patient-specific IMRT and VMAT QA.
Sanghangthum, Taweap; Suriyapee, Sivalee; Srisatit, Somyot; Pawlicki, Todd
2013-05-01
This work applied statistical process control to establish the control limits of the % gamma pass of patient-specific intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) quality assurance (QA), and to evaluate the efficiency of the QA process by using the process capability index (Cpml). A total of 278 IMRT QA plans in nasopharyngeal carcinoma were measured with MapCHECK, while 159 VMAT QA plans were undertaken with ArcCHECK. Six megavolts with nine fields were used for the IMRT plan and 2.5 arcs were used to generate the VMAT plans. The gamma (3%/3 mm) criteria were used to evaluate the QA plans. The % gamma passes were plotted on a control chart. The first 50 data points were employed to calculate the control limits. The Cpml was calculated to evaluate the capability of the IMRT/VMAT QA process. The results showed higher systematic errors in IMRT QA than VMAT QA due to the more complicated setup used in IMRT QA. The variation of random errors was also larger in IMRT QA than VMAT QA because the VMAT plan has more continuity of dose distribution. The average % gamma pass was 93.7% ± 3.7% for IMRT and 96.7% ± 2.2% for VMAT. The Cpml value of IMRT QA was 1.60 and VMAT QA was 1.99, which implied that the VMAT QA process was more accurate than the IMRT QA process. Our lower control limit for % gamma pass of IMRT is 85.0%, while the limit for VMAT is 90%. Both the IMRT and VMAT QA processes are good quality because Cpml values are higher than 1.0.
A spatial scan statistic for survival data based on Weibull distribution.
Bhatt, Vijaya; Tiwari, Neeraj
2014-05-20
The spatial scan statistic has been developed as a geographical cluster detection analysis tool for different types of data sets such as Bernoulli, Poisson, ordinal, normal and exponential. We propose a scan statistic for survival data based on Weibull distribution. It may also be used for other survival distributions, such as exponential, gamma, and log normal. The proposed method is applied on the survival data of tuberculosis patients for the years 2004-2005 in Nainital district of Uttarakhand, India. Simulation studies reveal that the proposed method performs well for different survival distribution functions. Copyright © 2013 John Wiley & Sons, Ltd.
The product composition control system at Savannah River: Statistical process control algorithm
International Nuclear Information System (INIS)
Brown, K.G.
1994-01-01
The Defense Waste Processing Facility (DWPF) at the Savannah River Site (SRS) will be used to immobilize the approximately 130 million liters of high-level nuclear waste currently stored at the site in 51 carbon steel tanks. Waste handling operations separate this waste into highly radioactive insoluble sludge and precipitate and less radioactive water soluble salts. In DWPF, precipitate (PHA) is blended with insoluble sludge and ground glass frit to produce melter feed slurry which is continuously fed to the DWPF melter. The melter produces a molten borosilicate glass which is poured into stainless steel canisters for cooling and, ultimately, shipment to and storage in an geologic repository. Described here is the Product Composition Control System (PCCS) process control algorithm. The PCCS is the amalgam of computer hardware and software intended to ensure that the melt will be processable and that the glass wasteform produced will be acceptable. Within PCCS, the Statistical Process Control (SPC) Algorithm is the means which guides control of the DWPF process. The SPC Algorithm is necessary to control the multivariate DWPF process in the face of uncertainties arising from the process, its feeds, sampling, modeling, and measurement systems. This article describes the functions performed by the SPC Algorithm, characterization of DWPF prior to making product, accounting for prediction uncertainty, accounting for measurement uncertainty, monitoring a SME batch, incorporating process information, and advantages of the algorithm. 9 refs., 6 figs
Pearce, Marcus T
2018-05-11
Music perception depends on internal psychological models derived through exposure to a musical culture. It is hypothesized that this musical enculturation depends on two cognitive processes: (1) statistical learning, in which listeners acquire internal cognitive models of statistical regularities present in the music to which they are exposed; and (2) probabilistic prediction based on these learned models that enables listeners to organize and process their mental representations of music. To corroborate these hypotheses, I review research that uses a computational model of probabilistic prediction based on statistical learning (the information dynamics of music (IDyOM) model) to simulate data from empirical studies of human listeners. The results show that a broad range of psychological processes involved in music perception-expectation, emotion, memory, similarity, segmentation, and meter-can be understood in terms of a single, underlying process of probabilistic prediction using learned statistical models. Furthermore, IDyOM simulations of listeners from different musical cultures demonstrate that statistical learning can plausibly predict causal effects of differential cultural exposure to musical styles, providing a quantitative model of cultural distance. Understanding the neural basis of musical enculturation will benefit from close coordination between empirical neuroimaging and computational modeling of underlying mechanisms, as outlined here. © 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.
Nam, Sungsik; Alouini, Mohamed-Slim; Yang, Hongchuan
2010-01-01
Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs
International Nuclear Information System (INIS)
Suzuki, Mitsutoshi; Hori, Masato; Asou, Ryoji; Usuda, Shigekazu
2006-01-01
The multiscale statistical process control (MSSPC) method is applied to clarify the elements of material unaccounted for (MUF) in large scale reprocessing plants using numerical calculations. Continuous wavelet functions are used to decompose the process data, which simulate batch operation superimposed by various types of disturbance, and the disturbance components included in the data are divided into time and frequency spaces. The diagnosis of MSSPC is applied to distinguish abnormal events from the process data and shows how to detect abrupt and protracted diversions using principle component analysis. Quantitative performance of MSSPC for the time series data is shown with average run lengths given by Monte-Carlo simulation to compare to the non-detection probability β. Recent discussion about bias corrections in material balances is introduced and another approach is presented to evaluate MUF without assuming the measurement error model. (author)
Cross-situational statistically based word learning intervention for late-talking toddlers.
Alt, Mary; Meyers, Christina; Oglivie, Trianna; Nicholas, Katrina; Arizmendi, Genesis
2014-01-01
To explore the efficacy of a word learning intervention for late-talking toddlers that is based on principles of cross-situational statistical learning. Four late-talking toddlers were individually provided with 7-10 weeks of bi-weekly word learning intervention that incorporated principles of cross-situational statistical learning. Treatment was input-based meaning that, aside from initial probes, children were not asked to produce any language during the sessions. Pre-intervention data included parent-reported measures of productive vocabulary and language samples. Data collected during intervention included production on probes, spontaneous production during treatment, and parent report of words used spontaneously at home. Data were analyzed for number of target words learned relative to control words, effect sizes, and pre-post treatment vocabulary measures. All children learned more target words than control words and, on average, showed a large treatment effect size. Children made pre-post vocabulary gains, increasing their percentile scores on the MCDI, and demonstrated a rate of word learning that was faster than rates found in the literature. Cross-situational statistically based word learning intervention has the potential to improve vocabulary learning in late-talking toddlers. Limitations on interpretation are also discussed. Readers will describe what cross-situational learning is and how it might apply to treatment. They will identify how including lexical and contextual variability in a word learning intervention for toddlers affected treatment outcomes. They will also recognize evidence of improved rate of vocabulary learning following treatment. Copyright © 2014 Elsevier Inc. All rights reserved.
Oliveira, Sérgio C.; Zêzere, José L.; Lajas, Sara; Melo, Raquel
2017-07-01
Approaches used to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. The former are based on the assumption that the same causes are more likely to produce the same effects, whereas the latter are based on the comparison between forces which tend to promote movement along the slope and the counteracting forces that are resistant to motion. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodologically distinct, the statistical and deterministic methods generate similar shallow slide susceptibility results regarding the model's predictive capacity and spatial agreement; and (ii) the combination of shallow slide susceptibility maps obtained with statistical and physically based methods, for the same study area, generate a more reliable susceptibility model for shallow slide occurrence. These hypotheses were tested at a small test site (13.9 km2) located north of Lisbon (Portugal), using a statistical method (the information value method, IV) and a physically based method (the infinite slope method, IS). The landslide susceptibility maps produced with the statistical and deterministic methods were combined into a new landslide susceptibility map. The latter was based on a set of integration rules defined by the cross tabulation of the susceptibility classes of both maps and analysis of the corresponding contingency tables. The results demonstrate a higher predictive capacity of the new shallow slide susceptibility map, which combines the independent results obtained with statistical and physically based models. Moreover, the combination of the two models allowed the identification of areas where the results of the information value and the infinite slope methods are contradictory. Thus, these areas were classified as uncertain and deserve additional investigation at a more detailed scale.
Agile manufacturing from a statistical perspective
Energy Technology Data Exchange (ETDEWEB)
Easterling, R.G. [Sandia National Labs., Albuquerque, NM (United States). New Initiatives Dept.
1995-10-01
The objective of agile manufacturing is to provide the ability to quickly realize high-quality, highly-customized, in-demand products at a cost commensurate with mass production. More broadly, agility in manufacturing, or any other endeavor, is defined as change-proficiency; the ability to thrive in an environment of unpredictable change. This report discusses the general direction of the agile manufacturing initiative, including research programs at the National Institute of Standards and Technology (NIST), the Department of Energy, and other government agencies, but focuses on agile manufacturing from a statistical perspective. The role of statistics can be important because agile manufacturing requires the collection and communication of process characterization and capability information, much of which will be data-based. The statistical community should initiate collaborative work in this important area.
Hldreth, Laura A.; Robison-Cox, Jim; Schmidt, Jade
2018-01-01
This study examines the transferability of results from previous studies of simulation-based curriculum in introductory statistics using data from 3,500 students enrolled in an introductory statistics course at Montana State University from fall 2013 through spring 2016. During this time, four different curricula, a traditional curriculum and…
Hagenlocher, Michael; Delmelle, Eric; Casas, Irene; Kienberger, Stefan
2013-08-14
As a result of changes in climatic conditions and greater resistance to insecticides, many regions across the globe, including Colombia, have been facing a resurgence of vector-borne diseases, and dengue fever in particular. Timely information on both (1) the spatial distribution of the disease, and (2) prevailing vulnerabilities of the population are needed to adequately plan targeted preventive intervention. We propose a methodology for the spatial assessment of current socioeconomic vulnerabilities to dengue fever in Cali, a tropical urban environment of Colombia. Based on a set of socioeconomic and demographic indicators derived from census data and ancillary geospatial datasets, we develop a spatial approach for both expert-based and purely statistical-based modeling of current vulnerability levels across 340 neighborhoods of the city using a Geographic Information System (GIS). The results of both approaches are comparatively evaluated by means of spatial statistics. A web-based approach is proposed to facilitate the visualization and the dissemination of the output vulnerability index to the community. The statistical and the expert-based modeling approach exhibit a high concordance, globally, and spatially. The expert-based approach indicates a slightly higher vulnerability mean (0.53) and vulnerability median (0.56) across all neighborhoods, compared to the purely statistical approach (mean = 0.48; median = 0.49). Both approaches reveal that high values of vulnerability tend to cluster in the eastern, north-eastern, and western part of the city. These are poor neighborhoods with high percentages of young (i.e., local expertise, statistical approaches could be used, with caution. By decomposing identified vulnerability "hotspots" into their underlying factors, our approach provides valuable information on both (1) the location of neighborhoods, and (2) vulnerability factors that should be given priority in the context of targeted intervention
Monte Carlo testing in spatial statistics, with applications to spatial residuals
DEFF Research Database (Denmark)
Mrkvička, Tomáš; Soubeyrand, Samuel; Myllymäki, Mari
2016-01-01
This paper reviews recent advances made in testing in spatial statistics and discussed at the Spatial Statistics conference in Avignon 2015. The rank and directional quantile envelope tests are discussed and practical rules for their use are provided. These tests are global envelope tests...... with an appropriate type I error probability. Two novel examples are given on their usage. First, in addition to the test based on a classical one-dimensional summary function, the goodness-of-fit of a point process model is evaluated by means of the test based on a higher dimensional functional statistic, namely...
Wu, Chong; Liu, Liping; Wei, Ming; Xi, Baozhu; Yu, Minghui
2018-03-01
A modified hydrometeor classification algorithm (HCA) is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results—especially in the mixed rain-hail region—can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar-detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.
Licensing process for safety-critical software-based systems
Energy Technology Data Exchange (ETDEWEB)
Haapanen, P. [VTT Automation, Espoo (Finland); Korhonen, J. [VTT Electronics, Espoo (Finland); Pulkkinen, U. [VTT Automation, Espoo (Finland)
2000-12-01
System vendors nowadays propose software-based technology even for the most critical safety functions in nuclear power plants. Due to the nature of software faults and the way they cause system failures new methods are needed for the safety and reliability evaluation of these systems. In the research project 'Programmable automation systems in nuclear power plants (OHA)', financed together by the Radiation and Nuclear Safety Authority (STUK), the Ministry of Trade and Industry (KTM) and the Technical Research Centre of Finland (VTT), various safety assessment methods and tools for software based systems are developed and evaluated. As a part of the OHA-work a reference model for the licensing process for software-based safety automation systems is defined. The licensing process is defined as the set of interrelated activities whose purpose is to produce and assess evidence concerning the safety and reliability of the system/application to be licensed and to make the decision about the granting the construction and operation permissions based on this evidence. The parties of the licensing process are the authority, the licensee (the utility company), system vendors and their subcontractors and possible external independent assessors. The responsibility about the production of the evidence in first place lies at the licensee who in most cases rests heavily on the vendor expertise. The evaluation and gauging of the evidence is carried out by the authority (possibly using external experts), who also can acquire additional evidence by using their own (independent) methods and tools. Central issue in the licensing process is to combine the quality evidence about the system development process with the information acquired through tests, analyses and operational experience. The purpose of the licensing process described in this report is to act as a reference model both for the authority and the licensee when planning the licensing of individual applications
Licensing process for safety-critical software-based systems
International Nuclear Information System (INIS)
Haapanen, P.; Korhonen, J.; Pulkkinen, U.
2000-12-01
System vendors nowadays propose software-based technology even for the most critical safety functions in nuclear power plants. Due to the nature of software faults and the way they cause system failures new methods are needed for the safety and reliability evaluation of these systems. In the research project 'Programmable automation systems in nuclear power plants (OHA)', financed together by the Radiation and Nuclear Safety Authority (STUK), the Ministry of Trade and Industry (KTM) and the Technical Research Centre of Finland (VTT), various safety assessment methods and tools for software based systems are developed and evaluated. As a part of the OHA-work a reference model for the licensing process for software-based safety automation systems is defined. The licensing process is defined as the set of interrelated activities whose purpose is to produce and assess evidence concerning the safety and reliability of the system/application to be licensed and to make the decision about the granting the construction and operation permissions based on this evidence. The parties of the licensing process are the authority, the licensee (the utility company), system vendors and their subcontractors and possible external independent assessors. The responsibility about the production of the evidence in first place lies at the licensee who in most cases rests heavily on the vendor expertise. The evaluation and gauging of the evidence is carried out by the authority (possibly using external experts), who also can acquire additional evidence by using their own (independent) methods and tools. Central issue in the licensing process is to combine the quality evidence about the system development process with the information acquired through tests, analyses and operational experience. The purpose of the licensing process described in this report is to act as a reference model both for the authority and the licensee when planning the licensing of individual applications. Many of the
Hydration sites of unpaired RNA bases: a statistical analysis of the PDB structures
Directory of Open Access Journals (Sweden)
Carugo Oliviero
2011-10-01
Full Text Available Abstract Background Hydration is crucial for RNA structure and function. X-ray crystallography is the most commonly used method to determine RNA structures and hydration and, therefore, statistical surveys are based on crystallographic results, the number of which is quickly increasing. Results A statistical analysis of the water molecule distribution in high-resolution X-ray structures of unpaired RNA nucleotides showed that: different bases have the same penchant to be surrounded by water molecules; clusters of water molecules indicate possible hydration sites, which, in some cases, match those of the major and minor grooves of RNA and DNA double helices; complex hydrogen bond networks characterize the solvation of the nucleotides, resulting in a significant rigidity of the base and its surrounding water molecules. Interestingly, the hydration sites around unpaired RNA bases do not match, in general, the positions that are occupied by the second nucleotide when the base-pair is formed. Conclusions The hydration sites around unpaired RNA bases were found. They do not replicate the atom positions of complementary bases in the Watson-Crick pairs.
Uniting statistical and individual-based approaches for animal movement modelling.
Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel
2014-01-01
The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.
Taylor, Kirsten I; Devereux, Barry J; Acres, Kadia; Randall, Billi; Tyler, Lorraine K
2012-03-01
Conceptual representations are at the heart of our mental lives, involved in every aspect of cognitive functioning. Despite their centrality, a long-standing debate persists as to how the meanings of concepts are represented and processed. Many accounts agree that the meanings of concrete concepts are represented by their individual features, but disagree about the importance of different feature-based variables: some views stress the importance of the information carried by distinctive features in conceptual processing, others the features which are shared over many concepts, and still others the extent to which features co-occur. We suggest that previously disparate theoretical positions and experimental findings can be unified by an account which claims that task demands determine how concepts are processed in addition to the effects of feature distinctiveness and co-occurrence. We tested these predictions in a basic-level naming task which relies on distinctive feature information (Experiment 1) and a domain decision task which relies on shared feature information (Experiment 2). Both used large-scale regression designs with the same visual objects, and mixed-effects models incorporating participant, session, stimulus-related and feature statistic variables to model the performance. We found that concepts with relatively more distinctive and more highly correlated distinctive relative to shared features facilitated basic-level naming latencies, while concepts with relatively more shared and more highly correlated shared relative to distinctive features speeded domain decisions. These findings demonstrate that the feature statistics of distinctiveness (shared vs. distinctive) and correlational strength, as well as the task demands, determine how concept meaning is processed in the conceptual system. Copyright © 2011 Elsevier B.V. All rights reserved.
Averitt, Sallie D.
This instructor guide, which was developed for use in a manufacturing firm's advanced technical preparation program, contains the materials required to present a learning module that is designed to prepare trainees for the program's statistical process control module by improving their basic math skills and instructing them in basic calculator…
Heterogeneous Rock Simulation Using DIP-Micromechanics-Statistical Methods
Directory of Open Access Journals (Sweden)
H. Molladavoodi
2018-01-01
Full Text Available Rock as a natural material is heterogeneous. Rock material consists of minerals, crystals, cement, grains, and microcracks. Each component of rock has a different mechanical behavior under applied loading condition. Therefore, rock component distribution has an important effect on rock mechanical behavior, especially in the postpeak region. In this paper, the rock sample was studied by digital image processing (DIP, micromechanics, and statistical methods. Using image processing, volume fractions of the rock minerals composing the rock sample were evaluated precisely. The mechanical properties of the rock matrix were determined based on upscaling micromechanics. In order to consider the rock heterogeneities effect on mechanical behavior, the heterogeneity index was calculated in a framework of statistical method. A Weibull distribution function was fitted to the Young modulus distribution of minerals. Finally, statistical and Mohr–Coulomb strain-softening models were used simultaneously as a constitutive model in DEM code. The acoustic emission, strain energy release, and the effect of rock heterogeneities on the postpeak behavior process were investigated. The numerical results are in good agreement with experimental data.
The Computer Student Worksheet Based Mathematical Literacy for Statistics
Manoy, J. T.; Indarasati, N. A.
2018-01-01
The student worksheet is one of media teaching which is able to improve teaching an activity in the classroom. Indicators in mathematical literacy were included in a student worksheet is able to help the students for applying the concept in daily life. Then, the use of computers in learning can create learning with environment-friendly. This research used developmental research which was Thiagarajan (Four-D) development design. There are 4 stages in the Four-D, define, design, develop, and disseminate. However, this research was finish until the third stage, develop stage. The computer student worksheet based mathematical literacy for statistics executed good quality. This student worksheet is achieving the criteria if able to achieve three aspects, validity, practicality, and effectiveness. The subject in this research was the students at The 1st State Senior High School of Driyorejo, Gresik, grade eleven of The 5th Mathematics and Natural Sciences. The computer student worksheet products based mathematical literacy for statistics executed good quality, while it achieved the aspects for validity, practical, and effectiveness. This student worksheet achieved the validity aspects with an average of 3.79 (94.72%), and practical aspects with an average of 2.85 (71.43%). Besides, it achieved the effectiveness aspects with a percentage of the classical complete students of 94.74% and a percentage of the student positive response of 75%.
Application of Statistical Model in Wastewater Treatment Process Modeling Using Data Analysis
Directory of Open Access Journals (Sweden)
Alireza Raygan Shirazinezhad
2015-06-01
Full Text Available Background: Wastewater treatment includes very complex and interrelated physical, chemical and biological processes which using data analysis techniques can be rigorously modeled by a non-complex mathematical calculation models. Materials and Methods: In this study, data on wastewater treatment processes from water and wastewater company of Kohgiluyeh and Boyer Ahmad were used. A total of 3306 data for COD, TSS, PH and turbidity were collected, then analyzed by SPSS-16 software (descriptive statistics and data analysis IBM SPSS Modeler 14.2, through 9 algorithm. Results: According to the results on logistic regression algorithms, neural networks, Bayesian networks, discriminant analysis, decision tree C5, tree C & R, CHAID, QUEST and SVM had accuracy precision of 90.16, 94.17, 81.37, 70.48, 97.89, 96.56, 96.46, 96.84 and 88.92, respectively. Discussion and conclusion: The C5 algorithm as the best and most applicable algorithms for modeling of wastewater treatment processes were chosen carefully with accuracy of 97.899 and the most influential variables in this model were PH, COD, TSS and turbidity.
A standard curve based method for relative real time PCR data processing
Directory of Open Access Journals (Sweden)
Krause Andreas
2005-03-01
Full Text Available Abstract Background Currently real time PCR is the most precise method by which to measure gene expression. The method generates a large amount of raw numerical data and processing may notably influence final results. The data processing is based either on standard curves or on PCR efficiency assessment. At the moment, the PCR efficiency approach is preferred in relative PCR whilst the standard curve is often used for absolute PCR. However, there are no barriers to employ standard curves for relative PCR. This article provides an implementation of the standard curve method and discusses its advantages and limitations in relative real time PCR. Results We designed a procedure for data processing in relative real time PCR. The procedure completely avoids PCR efficiency assessment, minimizes operator involvement and provides a statistical assessment of intra-assay variation. The procedure includes the following steps. (I Noise is filtered from raw fluorescence readings by smoothing, baseline subtraction and amplitude normalization. (II The optimal threshold is selected automatically from regression parameters of the standard curve. (III Crossing points (CPs are derived directly from coordinates of points where the threshold line crosses fluorescence plots obtained after the noise filtering. (IV The means and their variances are calculated for CPs in PCR replicas. (V The final results are derived from the CPs' means. The CPs' variances are traced to results by the law of error propagation. A detailed description and analysis of this data processing is provided. The limitations associated with the use of parametric statistical methods and amplitude normalization are specifically analyzed and found fit to the routine laboratory practice. Different options are discussed for aggregation of data obtained from multiple reference genes. Conclusion A standard curve based procedure for PCR data processing has been compiled and validated. It illustrates that
Spatial analysis statistics, visualization, and computational methods
Oyana, Tonny J
2015-01-01
An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis-containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS-as well as detailed illustrations and numerous case studies. The book enables readers to: Identify types and characterize non-spatial and spatial data Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results Construct testable hypotheses that require inferential statistical analysis Process spatial data, extract explanatory variables, conduct statisti...
Statistical learning of action: the role of conditional probability.
Meyer, Meredith; Baldwin, Dare
2011-12-01
Identification of distinct units within a continuous flow of human action is fundamental to action processing. Such segmentation may rest in part on statistical learning. In a series of four experiments, we examined what types of statistics people can use to segment a continuous stream involving many brief, goal-directed action elements. The results of Experiment 1 showed no evidence for sensitivity to conditional probability, whereas Experiment 2 displayed learning based on joint probability. In Experiment 3, we demonstrated that additional exposure to the input failed to engender sensitivity to conditional probability. However, the results of Experiment 4 showed that a subset of adults-namely, those more successful at identifying actions that had been seen more frequently than comparison sequences-were also successful at learning conditional-probability statistics. These experiments help to clarify the mechanisms subserving processing of intentional action, and they highlight important differences from, as well as similarities to, prior studies of statistical learning in other domains, including language.
Rah, Jeong-Eun; Shin, Dongho; Oh, Do Hoon; Kim, Tae Hyun; Kim, Gwe-Ya
2014-09-01
To evaluate and improve the reliability of proton quality assurance (QA) processes and, to provide an optimal customized tolerance level using the statistical process control (SPC) methodology. The authors investigated the consistency check of dose per monitor unit (D/MU) and range in proton beams to see whether it was within the tolerance level of the daily QA process. This study analyzed the difference between the measured and calculated ranges along the central axis to improve the patient-specific QA process in proton beams by using process capability indices. The authors established a customized tolerance level of ±2% for D/MU and ±0.5 mm for beam range in the daily proton QA process. In the authors' analysis of the process capability indices, the patient-specific range measurements were capable of a specification limit of ±2% in clinical plans. SPC methodology is a useful tool for customizing the optimal QA tolerance levels and improving the quality of proton machine maintenance, treatment delivery, and ultimately patient safety.
International Nuclear Information System (INIS)
Rah, Jeong-Eun; Oh, Do Hoon; Shin, Dongho; Kim, Tae Hyun; Kim, Gwe-Ya
2014-01-01
Purpose: To evaluate and improve the reliability of proton quality assurance (QA) processes and, to provide an optimal customized tolerance level using the statistical process control (SPC) methodology. Methods: The authors investigated the consistency check of dose per monitor unit (D/MU) and range in proton beams to see whether it was within the tolerance level of the daily QA process. This study analyzed the difference between the measured and calculated ranges along the central axis to improve the patient-specific QA process in proton beams by using process capability indices. Results: The authors established a customized tolerance level of ±2% for D/MU and ±0.5 mm for beam range in the daily proton QA process. In the authors’ analysis of the process capability indices, the patient-specific range measurements were capable of a specification limit of ±2% in clinical plans. Conclusions: SPC methodology is a useful tool for customizing the optimal QA tolerance levels and improving the quality of proton machine maintenance, treatment delivery, and ultimately patient safety
Control cards as a statistical quality control resource
Directory of Open Access Journals (Sweden)
Aleksandar Živan Drenovac
2013-02-01
Full Text Available Normal 0 false false false MicrosoftInternetExplorer4 This paper proves that applying of statistical methods can significantly contribute increasing of products and services quality, as well as increasing of institutions rating. Determining of optimal, apropos anticipatory and limitary values, is based on sample`s statistical analyze. Control cards represent very confident instrument, which is simple for use and efficient for control of process, by which process is maintained in set borders. Thus, control cards can be applied in quality control of procesess of weapons and military equipment production, maintenance of technical systems, as well as for seting of standards and increasing of quality level for many other activities.
Statistical 21-cm Signal Separation via Gaussian Process Regression Analysis
Mertens, F. G.; Ghosh, A.; Koopmans, L. V. E.
2018-05-01
Detecting and characterizing the Epoch of Reionization and Cosmic Dawn via the redshifted 21-cm hyperfine line of neutral hydrogen will revolutionize the study of the formation of the first stars, galaxies, black holes and intergalactic gas in the infant Universe. The wealth of information encoded in this signal is, however, buried under foregrounds that are many orders of magnitude brighter. These must be removed accurately and precisely in order to reveal the feeble 21-cm signal. This requires not only the modeling of the Galactic and extra-galactic emission, but also of the often stochastic residuals due to imperfect calibration of the data caused by ionospheric and instrumental distortions. To stochastically model these effects, we introduce a new method based on `Gaussian Process Regression' (GPR) which is able to statistically separate the 21-cm signal from most of the foregrounds and other contaminants. Using simulated LOFAR-EoR data that include strong instrumental mode-mixing, we show that this method is capable of recovering the 21-cm signal power spectrum across the entire range k = 0.07 - 0.3 {h cMpc^{-1}}. The GPR method is most optimal, having minimal and controllable impact on the 21-cm signal, when the foregrounds are correlated on frequency scales ≳ 3 MHz and the rms of the signal has σ21cm ≳ 0.1 σnoise. This signal separation improves the 21-cm power-spectrum sensitivity by a factor ≳ 3 compared to foreground avoidance strategies and enables the sensitivity of current and future 21-cm instruments such as the Square Kilometre Array to be fully exploited.
Pixel based statistical analysis of differences between lung SPECT images: methodological aspects
International Nuclear Information System (INIS)
Bendada, S.; Rocchisani, J.L.M.; Moretti, J.L.
2002-01-01
The statistical parametric mapping method is applied in Neurology for activation studies. We had adapted this powerful method on Lungs SPECT to help for the diagnosis and the follow-up of pulmonary embolism and other lung diseases. The SPECT slices of pairs of examination were normalized thanks to the total acquired counts, reconstruction background subtracted, smoothed and realigned. A parametric image of statistical differences was finally computed. We had thus obtained a 3D image showing regions of improved or altered region under treatment. A tuning of the various parameters could lead to more accurate image. This new approach of lung SPECT processing appears to be a promising useful tool for the physician. (author)
Lepore, Natasha; Brun, Caroline; Chou, Yi-Yu; Chiang, Ming-Chang; Dutton, Rebecca A.; Hayashi, Kiralee M.; Luders, Eileen; Lopez, Oscar L.; Aizenstein, Howard J.; Toga, Arthur W.; Becker, James T.; Thompson, Paul M.
2008-01-01
This paper investigates the performance of a new multivariate method for tensor-based morphometry (TBM). Statistics on Riemannian manifolds are developed that exploit the full information in deformation tensor fields. In TBM, multiple brain images are warped to a common neuroanatomical template via 3-D nonlinear registration; the resulting deformation fields are analyzed statistically to identify group differences in anatomy. Rather than study the Jacobian determinant (volume expansion factor...
Ren, W. X.; Lin, Y. Q.; Fang, S. E.
2011-11-01
One of the key issues in vibration-based structural health monitoring is to extract the damage-sensitive but environment-insensitive features from sampled dynamic response measurements and to carry out the statistical analysis of these features for structural damage detection. A new damage feature is proposed in this paper by using the system matrices of the forward innovation model based on the covariance-driven stochastic subspace identification of a vibrating system. To overcome the variations of the system matrices, a non-singularity transposition matrix is introduced so that the system matrices are normalized to their standard forms. For reducing the effects of modeling errors, noise and environmental variations on measured structural responses, a statistical pattern recognition paradigm is incorporated into the proposed method. The Mahalanobis and Euclidean distance decision functions of the damage feature vector are adopted by defining a statistics-based damage index. The proposed structural damage detection method is verified against one numerical signal and two numerical beams. It is demonstrated that the proposed statistics-based damage index is sensitive to damage and shows some robustness to the noise and false estimation of the system ranks. The method is capable of locating damage of the beam structures under different types of excitations. The robustness of the proposed damage detection method to the variations in environmental temperature is further validated in a companion paper by a reinforced concrete beam tested in the laboratory and a full-scale arch bridge tested in the field.
Statistical Analysis of CMC Constituent and Processing Data
Fornuff, Jonathan
2004-01-01
observed using statistical analysis software. The ultimate purpose of this study is to determine what variations in material processing can lead to the most critical changes in the materials property. The work I have taken part in this summer explores, in general, the key properties needed In this study SiC/SiC composites of varying architectures, utilizing a boron-nitride (BN)
LOR-OSEM: statistical PET reconstruction from raw line-of-response histograms
International Nuclear Information System (INIS)
Kadrmas, Dan J
2004-01-01
Iterative statistical reconstruction methods are becoming the standard in positron emission tomography (PET). Conventional maximum-likelihood expectation-maximization (MLEM) and ordered-subsets (OSEM) algorithms act on data which have been pre-processed into corrected, evenly-spaced histograms; however, such pre-processing corrupts the Poisson statistics. Recent advances have incorporated attenuation, scatter and randoms compensation into the iterative reconstruction. The objective of this work was to incorporate the remaining pre-processing steps, including arc correction, to reconstruct directly from raw unevenly-spaced line-of-response (LOR) histograms. This exactly preserves Poisson statistics and full spatial information in a manner closely related to listmode ML, making full use of the ML statistical model. The LOR-OSEM algorithm was implemented using a rotation-based projector which maps directly to the unevenly-spaced LOR grid. Simulation and phantom experiments were performed to characterize resolution, contrast and noise properties for 2D PET. LOR-OSEM provided a beneficial noise-resolution tradeoff, outperforming AW-OSEM by about the same margin that AW-OSEM outperformed pre-corrected OSEM. The relationship between LOR-ML and listmode ML algorithms was explored, and implementation differences are discussed. LOR-OSEM is a viable alternative to AW-OSEM for histogram-based reconstruction with improved spatial resolution and noise properties
2018-01-01
kHz 3. Statistical Processing 3.1 Statistical Analysis Statistical analysis is the mathematical science dealing with the analysis or...diagnostic vibrational monitoring applications , statistical techniques that are mainly used for alarm purposes in industrial plants are the...SUPPLEMENTARY NOTES 14. ABSTRACT This report is the result of applying morphological image and statistical processing techniques to the energy
Statistical inference for noisy nonlinear ecological dynamic systems.
Wood, Simon N
2010-08-26
Chaotic ecological dynamic systems defy conventional statistical analysis. Systems with near-chaotic dynamics are little better. Such systems are almost invariably driven by endogenous dynamic processes plus demographic and environmental process noise, and are only observable with error. Their sensitivity to history means that minute changes in the driving noise realization, or the system parameters, will cause drastic changes in the system trajectory. This sensitivity is inherited and amplified by the joint probability density of the observable data and the process noise, rendering it useless as the basis for obtaining measures of statistical fit. Because the joint density is the basis for the fit measures used by all conventional statistical methods, this is a major theoretical shortcoming. The inability to make well-founded statistical inferences about biological dynamic models in the chaotic and near-chaotic regimes, other than on an ad hoc basis, leaves dynamic theory without the methods of quantitative validation that are essential tools in the rest of biological science. Here I show that this impasse can be resolved in a simple and general manner, using a method that requires only the ability to simulate the observed data on a system from the dynamic model about which inferences are required. The raw data series are reduced to phase-insensitive summary statistics, quantifying local dynamic structure and the distribution of observations. Simulation is used to obtain the mean and the covariance matrix of the statistics, given model parameters, allowing the construction of a 'synthetic likelihood' that assesses model fit. This likelihood can be explored using a straightforward Markov chain Monte Carlo sampler, but one further post-processing step returns pure likelihood-based inference. I apply the method to establish the dynamic nature of the fluctuations in Nicholson's classic blowfly experiments.
Yepes-Calderon, Fernando; Brun, Caroline; Sant, Nishita; Thompson, Paul; Lepore, Natasha
2015-01-01
Tensor-Based Morphometry (TBM) is an increasingly popular method for group analysis of brain MRI data. The main steps in the analysis consist of a nonlinear registration to align each individual scan to a common space, and a subsequent statistical analysis to determine morphometric differences, or difference in fiber structure between groups. Recently, we implemented the Statistically-Assisted Fluid Registration Algorithm or SAFIRA,1 which is designed for tracking morphometric differences among populations. To this end, SAFIRA allows the inclusion of statistical priors extracted from the populations being studied as regularizers in the registration. This flexibility and degree of sophistication limit the tool to expert use, even more so considering that SAFIRA was initially implemented in command line mode. Here, we introduce a new, intuitive, easy to use, Matlab-based graphical user interface for SAFIRA's multivariate TBM. The interface also generates different choices for the TBM statistics, including both the traditional univariate statistics on the Jacobian matrix, and comparison of the full deformation tensors.2 This software will be freely disseminated to the neuroimaging research community.
Birth tourism: socio-demographic and statistical aspects
Directory of Open Access Journals (Sweden)
Anatoly V. Korotkov
2016-01-01
Full Text Available The purpose of the study is to research birth tourism issue. The article gives the socio-demographic and statistical aspects of research problems of birth inbound tourism in the Russian Federation. Following the literature analysis, the degree of study for birth tourism lags behind its actual size. Currently, the media has accumulated a significant amount of information on birth tourism in Russia, that requires processing, systematization and understanding that can and should become an independent area of study of sociologists and demographers to develop recommendations for the management of socio-demographic processes in birth tourism in our country. It is necessary to identify the problems that will inevitably arise. At present, this process is almost not regulated.These problems are complex, it requires the joint efforts of sociologists and demographers. However, it is impossible to obtain reliable results and to develop management decisions without attention to the statistical aspect of this problem. It is necessary to create methodological support for collecting and information processing and model development of the birth tourism. At the initial stage it is necessary to identify the direction and objectives of the analysis to determine the factors in the development of this process, to develop a hierarchical system of statistical indicators, to receive the information, needed for calculating of specific indicators.The complex research of the birth tourism issues should be based on the methodology of sociology, demography and statistics, including statistical observation, interviews with residents, structure analysis and birth tourism concentration in the country, the analysis of the dynamics, classification of factors and reasons, the grouping of regions for the development of the studied processes and, of course, the development of economic-statistical indicators.The article reveals the problem of the significant influence of the
Hawe, David; Hernández Fernández, Francisco R; O'Suilleabháin, Liam; Huang, Jian; Wolsztynski, Eric; O'Sullivan, Finbarr
2012-05-01
In dynamic mode, positron emission tomography (PET) can be used to track the evolution of injected radio-labelled molecules in living tissue. This is a powerful diagnostic imaging technique that provides a unique opportunity to probe the status of healthy and pathological tissue by examining how it processes substrates. The spatial aspect of PET is well established in the computational statistics literature. This article focuses on its temporal aspect. The interpretation of PET time-course data is complicated because the measured signal is a combination of vascular delivery and tissue retention effects. If the arterial time-course is known, the tissue time-course can typically be expressed in terms of a linear convolution between the arterial time-course and the tissue residue. In statistical terms, the residue function is essentially a survival function - a familiar life-time data construct. Kinetic analysis of PET data is concerned with estimation of the residue and associated functionals such as flow, flux, volume of distribution and transit time summaries. This review emphasises a nonparametric approach to the estimation of the residue based on a piecewise linear form. Rapid implementation of this by quadratic programming is described. The approach provides a reference for statistical assessment of widely used one- and two-compartmental model forms. We illustrate the method with data from two of the most well-established PET radiotracers, (15)O-H(2)O and (18)F-fluorodeoxyglucose, used for assessment of blood perfusion and glucose metabolism respectively. The presentation illustrates the use of two open-source tools, AMIDE and R, for PET scan manipulation and model inference.
Acceleration transforms and statistical kinetic models
International Nuclear Information System (INIS)
LuValle, M.J.; Welsher, T.L.; Svoboda, K.
1988-01-01
For a restricted class of problems a mathematical model of microscopic degradation processes, statistical kinetics, is developed and linked through acceleration transforms to the information which can be obtained from a system in which the only observable sign of degradation is sudden and catastrophic failure. The acceleration transforms were developed in accelerated life testing applications as a tool for extrapolating from the observable results of an accelerated life test to the dynamics of the underlying degradation processes. A particular concern of a physicist attempting to interpreted the results of an analysis based on acceleration transforms is determining the physical species involved in the degradation process. These species may be (a) relatively abundant or (b) relatively rare. The main results of this paper are a theorem showing that for an important subclass of statistical kinetic models, acceleration transforms cannot be used to distinguish between cases a and b, and an example showing that in some cases falling outside the restrictions of the theorem, cases a and b can be distinguished by their acceleration transforms
SOCR Analyses - an Instructional Java Web-based Statistical Analysis Toolkit.
Chu, Annie; Cui, Jenny; Dinov, Ivo D
2009-03-01
The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test.The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website.In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most
Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun
2017-08-01
Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM 2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM 2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R 2 = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM 2.5 estimates.
Statistical tests for power-law cross-correlated processes
Podobnik, Boris; Jiang, Zhi-Qiang; Zhou, Wei-Xing; Stanley, H. Eugene
2011-12-01
For stationary time series, the cross-covariance and the cross-correlation as functions of time lag n serve to quantify the similarity of two time series. The latter measure is also used to assess whether the cross-correlations are statistically significant. For nonstationary time series, the analogous measures are detrended cross-correlations analysis (DCCA) and the recently proposed detrended cross-correlation coefficient, ρDCCA(T,n), where T is the total length of the time series and n the window size. For ρDCCA(T,n), we numerically calculated the Cauchy inequality -1≤ρDCCA(T,n)≤1. Here we derive -1≤ρDCCA(T,n)≤1 for a standard variance-covariance approach and for a detrending approach. For overlapping windows, we find the range of ρDCCA within which the cross-correlations become statistically significant. For overlapping windows we numerically determine—and for nonoverlapping windows we derive—that the standard deviation of ρDCCA(T,n) tends with increasing T to 1/T. Using ρDCCA(T,n) we show that the Chinese financial market's tendency to follow the U.S. market is extremely weak. We also propose an additional statistical test that can be used to quantify the existence of cross-correlations between two power-law correlated time series.
Pitard, Francis F
1993-01-01
Pierre Gy's Sampling Theory and Sampling Practice, Second Edition is a concise, step-by-step guide for process variability management and methods. Updated and expanded, this new edition provides a comprehensive study of heterogeneity, covering the basic principles of sampling theory and its various applications. It presents many practical examples to allow readers to select appropriate sampling protocols and assess the validity of sampling protocols from others. The variability of dynamic process streams using variography is discussed to help bridge sampling theory with statistical process control. Many descriptions of good sampling devices, as well as descriptions of poor ones, are featured to educate readers on what to look for when purchasing sampling systems. The book uses its accessible, tutorial style to focus on professional selection and use of methods. The book will be a valuable guide for mineral processing engineers; metallurgists; geologists; miners; chemists; environmental scientists; and practit...
Some statistical properties of gene expression clustering for array data
DEFF Research Database (Denmark)
Abreu, G C G; Pinheiro, A; Drummond, R D
2010-01-01
DNA array data without a corresponding statistical error measure. We propose an easy-to-implement and simple-to-use technique that uses bootstrap re-sampling to evaluate the statistical error of the nodes provided by SOM-based clustering. Comparisons between SOM and parametric clustering are presented...... for simulated as well as for two real data sets. We also implement a bootstrap-based pre-processing procedure for SOM, that improves the false discovery ratio of differentially expressed genes. Code in Matlab is freely available, as well as some supplementary material, at the following address: https...
Meijer, Rob R.; van Krimpen-Stoop, Edith M. L. A.
In this study a cumulative-sum (CUSUM) procedure from the theory of Statistical Process Control was modified and applied in the context of person-fit analysis in a computerized adaptive testing (CAT) environment. Six person-fit statistics were proposed using the CUSUM procedure, and three of them could be used to investigate the CAT in online test…
Statistical evaluation of cleanup: How should it be done?
International Nuclear Information System (INIS)
Gilbert, R.O.
1993-02-01
This paper discusses statistical issues that must be addressed when conducting statistical tests for the purpose of evaluating if a site has been remediated to guideline values or standards. The importance of using the Data Quality Objectives (DQO) process to plan and design the sampling plan is emphasized. Other topics discussed are: (1) accounting for the uncertainty of cleanup standards when conducting statistical tests, (2) determining the number of samples and measurements needed to attain specified DQOs, (3) considering whether the appropriate testing philosophy in a given situation is ''guilty until proven innocent'' or ''innocent until proven guilty'' when selecting a statistical test for evaluating the attainment of standards, (4) conducting tests using data sets that contain measurements that have been reported by the laboratory as less than the minimum detectable activity, and (5) selecting statistical tests that are appropriate for risk-based or background-based standards. A recent draft report by Berger that provides guidance on sampling plans and data analyses for final status surveys at US Nuclear Regulatory Commission licensed facilities serves as a focal point for discussion
Statistical-uncertainty-based adaptive filtering of lidar signals
International Nuclear Information System (INIS)
Fuehrer, P. L.; Friehe, C. A.; Hristov, T. S.; Cooper, D. I.; Eichinger, W. E.
2000-01-01
An adaptive filter signal processing technique is developed to overcome the problem of Raman lidar water-vapor mixing ratio (the ratio of the water-vapor density to the dry-air density) with a highly variable statistical uncertainty that increases with decreasing photomultiplier-tube signal strength and masks the true desired water-vapor structure. The technique, applied to horizontal scans, assumes only statistical horizontal homogeneity. The result is a variable spatial resolution water-vapor signal with a constant variance out to a range limit set by a specified signal-to-noise ratio. The technique was applied to Raman water-vapor lidar data obtained at a coastal pier site together with in situ instruments located 320 m from the lidar. The micrometerological humidity data were used to calibrate the ratio of the lidar gains of the H 2 O and the N 2 photomultiplier tubes and set the water-vapor mixing ratio variance for the adaptive filter. For the coastal experiment the effective limit of the lidar range was found to be approximately 200 m for a maximum noise-to-signal variance ratio of 0.1 with the implemented data-reduction procedure. The technique can be adapted to off-horizontal scans with a small reduction in the constraints and is also applicable to other remote-sensing devices that exhibit the same inherent range-dependent signal-to-noise ratio problem. (c) 2000 Optical Society of America
Peng, Fei; Li, Jiao-ting; Long, Min
2015-03-01
To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.
[Statistics for statistics?--Thoughts about psychological tools].
Berger, Uwe; Stöbel-Richter, Yve
2007-12-01
Statistical methods take a prominent place among psychologists' educational programs. Being known as difficult to understand and heavy to learn, students fear of these contents. Those, who do not aspire after a research carrier at the university, will forget the drilled contents fast. Furthermore, because it does not apply for the work with patients and other target groups at a first glance, the methodological education as a whole was often questioned. For many psychological practitioners the statistical education makes only sense by enforcing respect against other professions, namely physicians. For the own business, statistics is rarely taken seriously as a professional tool. The reason seems to be clear: Statistics treats numbers, while psychotherapy treats subjects. So, does statistics ends in itself? With this article, we try to answer the question, if and how statistical methods were represented within the psychotherapeutical and psychological research. Therefore, we analyzed 46 Originals of a complete volume of the journal Psychotherapy, Psychosomatics, Psychological Medicine (PPmP). Within the volume, 28 different analyse methods were applied, from which 89 per cent were directly based upon statistics. To be able to write and critically read Originals as a backbone of research, presumes a high degree of statistical education. To ignore statistics means to ignore research and at least to reveal the own professional work to arbitrariness.
Neural networks in signal processing
International Nuclear Information System (INIS)
Govil, R.
2000-01-01
Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)
Glass viscosity calculation based on a global statistical modelling approach
Energy Technology Data Exchange (ETDEWEB)
Fluegel, Alex
2007-02-01
A global statistical glass viscosity model was developed for predicting the complete viscosity curve, based on more than 2200 composition-property data of silicate glasses from the scientific literature, including soda-lime-silica container and float glasses, TV panel glasses, borosilicate fiber wool and E type glasses, low expansion borosilicate glasses, glasses for nuclear waste vitrification, lead crystal glasses, binary alkali silicates, and various further compositions from over half a century. It is shown that within a measurement series from a specific laboratory the reported viscosity values are often over-estimated at higher temperatures due to alkali and boron oxide evaporation during the measurement and glass preparation, including data by Lakatos et al. (1972) and the recently published High temperature glass melt property database for process modeling by Seward et al. (2005). Similarly, in the glass transition range many experimental data of borosilicate glasses are reported too high due to phase separation effects. The developed global model corrects those errors. The model standard error was 9-17°C, with R^2 = 0.985-0.989. The prediction 95% confidence interval for glass in mass production largely depends on the glass composition of interest, the composition uncertainty, and the viscosity level. New insights in the mixed-alkali effect are provided.
Biologically-based pharmacokinetic models are being increasingly used in the risk assessment of environmental chemicals. These models are based on biological, mathematical, statistical and engineering principles. Their potential uses in risk assessment include extrapolation betwe...
Functional summary statistics for the Johnson-Mehl model
DEFF Research Database (Denmark)
Møller, Jesper; Ghorbani, Mohammad
The Johnson-Mehl germination-growth model is a spatio-temporal point process model which among other things have been used for the description of neurotransmitters datasets. However, for such datasets parametric Johnson-Mehl models fitted by maximum likelihood have yet not been evaluated by means...... of functional summary statistics. This paper therefore invents four functional summary statistics adapted to the Johnson-Mehl model, with two of them based on the second-order properties and the other two on the nuclei-boundary distances for the associated Johnson-Mehl tessellation. The functional summary...... statistics theoretical properties are investigated, non-parametric estimators are suggested, and their usefulness for model checking is examined in a simulation study. The functional summary statistics are also used for checking fitted parametric Johnson-Mehl models for a neurotransmitters dataset....
International Nuclear Information System (INIS)
Ma, Lingling; Lv, Enmin; Du, Lixiong; Lu, Jie; Ding, Jincheng
2016-01-01
Highlights: • Microwave irradiation was employed for the esterification of acidified oil. • Optimization and modeling of the process was performed by RSM and ANN. • Both models have reliable prediction abilities but the ANN was superior over the RSM. • Membrane vapor permeation and in-situ dehydration were used to shift the equilibrium. • Two dehydration approaches improved the FFAs conversion rate by 20.0% approximately. - Abstract: The esterification of acidified oil with ethanol under microwave radiation was modeled and optimized using response surface methodology (RSM) and artificial neural network (ANN). The impacts of mass ratio of ethanol to acidified oil, catalyst loading, microwave power and reaction time are evaluated by Box-Behnken design (BBD) of RSM and multi-layer perceptron (MLP) of ANN. RSM combined with BBD shows the optimal conditions as catalyst loading of 5.85 g, mass ratio of ethanol to acidified oil of 0.35 (20.0 g acidified oil), microwave power of 328 W and reaction time of 98.0 min with the free fatty acids (FFAs) conversion of 78.57%. Both of the models are fitted well with the experimental data, however, ANN exhibits better prediction accuracy than RSM based on the statistical analyses. Furthermore, membrane vapor permeation and in-situ molecular sieve dehydration were investigated to enhance the esterification under the optimized conditions.
Fracture criterion for brittle materials based on statistical cells of finite volume
International Nuclear Information System (INIS)
Cords, H.; Kleist, G.; Zimmermann, R.
1986-06-01
An analytical consideration of the Weibull Statistical Analysis of brittle materials established the necessity of including one additional material constant for a more comprehensive description of the failure behaviour. The Weibull analysis is restricted to infinitesimal volume elements in consequence of the differential calculus applied. It was found that infinitesimally small elements are in conflict with the basic statistical assumption and that the differential calculus is not needed in fact since nowadays most of the stress analyses are based on finite element calculations, and these are most suitable for a subsequent statistical analysis of strength. The size of a finite statistical cell has been introduced as the third material parameter. It should represent the minimum volume containing all statistical features of the material such as distribution of pores, flaws and grains. The new approach also contains a unique treatment of failure under multiaxial stresses. The quantity responsible for failure under multiaxial stresses is introduced as a modified strain energy. Sixteen different tensile specimens including CT-specimens have been investigated experimentally and analyzed with the probabilistic fracture criterion. As a result it can be stated that the failure rates of all types of specimens made from three different grades of graphite are predictable. The accuracy of the prediction is one standard deviation. (orig.) [de
Mohammed, Mohammed A; Panesar, Jagdeep S; Laney, David B; Wilson, Richard
2013-04-01
The use of statistical process control (SPC) charts in healthcare is increasing. The primary purpose of SPC is to distinguish between common-cause variation which is attributable to the underlying process, and special-cause variation which is extrinsic to the underlying process. This is important because improvement under common-cause variation requires action on the process, whereas special-cause variation merits an investigation to first find the cause. Nonetheless, when dealing with attribute or count data (eg, number of emergency admissions) involving very large sample sizes, traditional SPC charts often produce tight control limits with most of the data points appearing outside the control limits. This can give a false impression of common and special-cause variation, and potentially misguide the user into taking the wrong actions. Given the growing availability of large datasets from routinely collected databases in healthcare, there is a need to present a review of this problem (which arises because traditional attribute charts only consider within-subgroup variation) and its solutions (which consider within and between-subgroup variation), which involve the use of the well-established measurements chart and the more recently developed attribute charts based on Laney's innovative approach. We close by making some suggestions for practice.
Azila Che Musa, Nor; Mahmud, Zamalia; Baharun, Norhayati
2017-09-01
One of the important skills that is required from any student who are learning statistics is knowing how to solve statistical problems correctly using appropriate statistical methods. This will enable them to arrive at a conclusion and make a significant contribution and decision for the society. In this study, a group of 22 students majoring in statistics at UiTM Shah Alam were given problems relating to topics on testing of hypothesis which require them to solve the problems using confidence interval, traditional and p-value approach. Hypothesis testing is one of the techniques used in solving real problems and it is listed as one of the difficult concepts for students to grasp. The objectives of this study is to explore students’ perceived and actual ability in solving statistical problems and to determine which item in statistical problem solving that students find difficult to grasp. Students’ perceived and actual ability were measured based on the instruments developed from the respective topics. Rasch measurement tools such as Wright map and item measures for fit statistics were used to accomplish the objectives. Data were collected and analysed using Winsteps 3.90 software which is developed based on the Rasch measurement model. The results showed that students’ perceived themselves as moderately competent in solving the statistical problems using confidence interval and p-value approach even though their actual performance showed otherwise. Item measures for fit statistics also showed that the maximum estimated measures were found on two problems. These measures indicate that none of the students have attempted these problems correctly due to reasons which include their lack of understanding in confidence interval and probability values.
Evaluating statistical cloud schemes: What can we gain from ground-based remote sensing?
Grützun, V.; Quaas, J.; Morcrette, C. J.; Ament, F.
2013-09-01
Statistical cloud schemes with prognostic probability distribution functions have become more important in atmospheric modeling, especially since they are in principle scale adaptive and capture cloud physics in more detail. While in theory the schemes have a great potential, their accuracy is still questionable. High-resolution three-dimensional observational data of water vapor and cloud water, which could be used for testing them, are missing. We explore the potential of ground-based remote sensing such as lidar, microwave, and radar to evaluate prognostic distribution moments using the "perfect model approach." This means that we employ a high-resolution weather model as virtual reality and retrieve full three-dimensional atmospheric quantities and virtual ground-based observations. We then use statistics from the virtual observation to validate the modeled 3-D statistics. Since the data are entirely consistent, any discrepancy occurring is due to the method. Focusing on total water mixing ratio, we find that the mean ratio can be evaluated decently but that it strongly depends on the meteorological conditions as to whether the variance and skewness are reliable. Using some simple schematic description of different synoptic conditions, we show how statistics obtained from point or line measurements can be poor at representing the full three-dimensional distribution of water in the atmosphere. We argue that a careful analysis of measurement data and detailed knowledge of the meteorological situation is necessary to judge whether we can use the data for an evaluation of higher moments of the humidity distribution used by a statistical cloud scheme.
Generalization bounds of ERM-based learning processes for continuous-time Markov chains.
Zhang, Chao; Tao, Dacheng
2012-12-01
Many existing results on statistical learning theory are based on the assumption that samples are independently and identically distributed (i.i.d.). However, the assumption of i.i.d. samples is not suitable for practical application to problems in which samples are time dependent. In this paper, we are mainly concerned with the empirical risk minimization (ERM) based learning process for time-dependent samples drawn from a continuous-time Markov chain. This learning process covers many kinds of practical applications, e.g., the prediction for a time series and the estimation of channel state information. Thus, it is significant to study its theoretical properties including the generalization bound, the asymptotic convergence, and the rate of convergence. It is noteworthy that, since samples are time dependent in this learning process, the concerns of this paper cannot (at least straightforwardly) be addressed by existing methods developed under the sample i.i.d. assumption. We first develop a deviation inequality for a sequence of time-dependent samples drawn from a continuous-time Markov chain and present a symmetrization inequality for such a sequence. By using the resultant deviation inequality and symmetrization inequality, we then obtain the generalization bounds of the ERM-based learning process for time-dependent samples drawn from a continuous-time Markov chain. Finally, based on the resultant generalization bounds, we analyze the asymptotic convergence and the rate of convergence of the learning process.
Feiveson, Alan H.; Foy, Millennia; Ploutz-Snyder, Robert; Fiedler, James
2014-01-01
Do you have elevated p-values? Is the data analysis process getting you down? Do you experience anxiety when you need to respond to criticism of statistical methods in your manuscript? You may be suffering from Insufficient Statistical Support Syndrome (ISSS). For symptomatic relief of ISSS, come for a free consultation with JSC biostatisticians at our help desk during the poster sessions at the HRP Investigators Workshop. Get answers to common questions about sample size, missing data, multiple testing, when to trust the results of your analyses and more. Side effects may include sudden loss of statistics anxiety, improved interpretation of your data, and increased confidence in your results.
Directory of Open Access Journals (Sweden)
Sungju Lee
2016-09-01
Full Text Available A fundamental key for enterprise users is a cloud-based parameter-driven statistical service and it has become a substantial impact on companies worldwide. In this paper, we demonstrate the statistical analysis for some certain criteria that are related to data and applied to the cloud server for a comparison of results. In addition, we present a statistical analysis and cloud-based resource allocation method for a heterogeneous platform environment by performing a data and information analysis with consideration of the application workload and the server capacity, and subsequently propose a service prediction model using a polynomial regression model. In particular, our aim is to provide stable service in a given large-scale enterprise cloud computing environment. The virtual machines (VMs for cloud-based services are assigned to each server with a special methodology to satisfy the uniform utilization distribution model. It is also implemented between users and the platform, which is a main idea of our cloud computing system. Based on the experimental results, we confirm that our prediction model can provide sufficient resources for statistical services to large-scale users while satisfying the uniform utilization distribution.
International Nuclear Information System (INIS)
Bai, T; Yan, H; Shi, F; Jia, X; Jiang, Steve B.; Lou, Y; Xu, Q; Mou, X
2014-01-01
Purpose: To develop a 3D dictionary learning based statistical reconstruction algorithm on graphic processing units (GPU), to improve the quality of low-dose cone beam CT (CBCT) imaging with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms) of 3x3x3 voxels was trained from a high quality volume image. During reconstruction, we utilized a Cholesky decomposition based orthogonal matching pursuit algorithm to find a sparse representation on this dictionary basis of each patch in the reconstructed image, in order to regularize the image quality. To accelerate the time-consuming sparse coding in the 3D case, we implemented our algorithm in a parallel fashion by taking advantage of the tremendous computational power of GPU. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with a tight frame (TF) based one using a subset data of 121 projections. The image qualities under different resolutions in z-direction, with or without statistical weighting are also studied. Results: Compared to the TF-based CBCT reconstruction, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, to remove more streaking artifacts, and is less susceptible to blocky artifacts. It is also observed that statistical reconstruction approach is sensitive to inconsistency between the forward and backward projection operations in parallel computing. Using high a spatial resolution along z direction helps improving the algorithm robustness. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppressing noise, and hence to achieve high quality reconstruction. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential
Energy Technology Data Exchange (ETDEWEB)
Bai, T [Xi' an Jiaotong University, Xi' an (China); UT Southwestern Medical Center, Dallas, TX (United States); Yan, H; Shi, F; Jia, X; Jiang, Steve B. [UT Southwestern Medical Center, Dallas, TX (United States); Lou, Y [University of California Irvine, Irvine, CA (United States); Xu, Q; Mou, X [Xi' an Jiaotong University, Xi' an (China)
2014-06-15
Purpose: To develop a 3D dictionary learning based statistical reconstruction algorithm on graphic processing units (GPU), to improve the quality of low-dose cone beam CT (CBCT) imaging with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms) of 3x3x3 voxels was trained from a high quality volume image. During reconstruction, we utilized a Cholesky decomposition based orthogonal matching pursuit algorithm to find a sparse representation on this dictionary basis of each patch in the reconstructed image, in order to regularize the image quality. To accelerate the time-consuming sparse coding in the 3D case, we implemented our algorithm in a parallel fashion by taking advantage of the tremendous computational power of GPU. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with a tight frame (TF) based one using a subset data of 121 projections. The image qualities under different resolutions in z-direction, with or without statistical weighting are also studied. Results: Compared to the TF-based CBCT reconstruction, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, to remove more streaking artifacts, and is less susceptible to blocky artifacts. It is also observed that statistical reconstruction approach is sensitive to inconsistency between the forward and backward projection operations in parallel computing. Using high a spatial resolution along z direction helps improving the algorithm robustness. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppressing noise, and hence to achieve high quality reconstruction. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential
Infant Statistical-Learning Ability Is Related to Real-Time Language Processing
Lany, Jill; Shoaib, Amber; Thompson, Abbie; Estes, Katharine Graf
2018-01-01
Infants are adept at learning statistical regularities in artificial language materials, suggesting that the ability to learn statistical structure may support language development. Indeed, infants who perform better on statistical learning tasks tend to be more advanced in parental reports of infants' language skills. Work with adults suggests…
[Hydrologic variability and sensitivity based on Hurst coefficient and Bartels statistic].
Lei, Xu; Xie, Ping; Wu, Zi Yi; Sang, Yan Fang; Zhao, Jiang Yan; Li, Bin Bin
2018-04-01
Due to the global climate change and frequent human activities in recent years, the pure stochastic components of hydrological sequence is mixed with one or several of the variation ingredients, including jump, trend, period and dependency. It is urgently needed to clarify which indices should be used to quantify the degree of their variability. In this study, we defined the hydrological variability based on Hurst coefficient and Bartels statistic, and used Monte Carlo statistical tests to test and analyze their sensitivity to different variants. When the hydrological sequence had jump or trend variation, both Hurst coefficient and Bartels statistic could reflect the variation, with the Hurst coefficient being more sensitive to weak jump or trend variation. When the sequence had period, only the Bartels statistic could detect the mutation of the sequence. When the sequence had a dependency, both the Hurst coefficient and the Bartels statistics could reflect the variation, with the latter could detect weaker dependent variations. For the four variations, both the Hurst variability and Bartels variability increased with the increases of variation range. Thus, they could be used to measure the variation intensity of the hydrological sequence. We analyzed the temperature series of different weather stations in the Lancang River basin. Results showed that the temperature of all stations showed the upward trend or jump, indicating that the entire basin had experienced warming in recent years and the temperature variability in the upper and lower reaches was much higher. This case study showed the practicability of the proposed method.
Mahalanobis, P C
1965-01-01
Contributions to Statistics focuses on the processes, methodologies, and approaches involved in statistics. The book is presented to Professor P. C. Mahalanobis on the occasion of his 70th birthday. The selection first offers information on the recovery of ancillary information and combinatorial properties of partially balanced designs and association schemes. Discussions focus on combinatorial applications of the algebra of association matrices, sample size analogy, association matrices and the algebra of association schemes, and conceptual statistical experiments. The book then examines latt
Al-Hussein, Fahad Abdullah
2008-01-01
Diabetes constitutes a major burden of disease globally. Both primary and secondary prevention need to improve in order to face this challenge. Improving management of diabetes in primary care is therefore of fundamental importance. The objective of these series of audits was to find means of improving diabetes management in chronic disease mini-clinics in primary health care. In the process, we were able to study the effect and practical usefulness of different audit designs - those measuring clinical outcomes, process of care, or both. King Saud City Family and Community Medicine Centre, Saudi National Guard Health Affairs in Riyadh city, Saudi Arabia. Simple random samples of 30 files were selected every two weeks from a sampling frame of file numbers for all diabetes clients seen over the period. Information was transferred to a form, entered on the computer and an automated response was generated regarding the appropriateness of management, a criterion mutually agreed upon by care providers. The results were plotted on statistical process control charts, p charts, displayed for all employees. Data extraction, archiving, entry, analysis, plotting and design and preparation of p charts were managed by nursing staff specially trained for the purpose by physicians with relevant previous experience. Audit series with mixed outcome and process measures failed to detect any changes in the proportion of non-conforming cases over a period of one year. The process measures series, on the other hand, showed improvement in care corresponding to a reduction in the proportion non-conforming by 10% within a period of 3 months. Non-conformities dropped from a mean of 5.0 to 1.4 over the year (P process audits and feedbacks. Frequent process audits in the context of statistical process control should be supplemented with concurrent outcome audits, once or twice a year.
Oravec, Heather Ann; Daniels, Christopher C.
2014-01-01
The National Aeronautics and Space Administration has been developing a novel docking system to meet the requirements of future exploration missions to low-Earth orbit and beyond. A dynamic gas pressure seal is located at the main interface between the active and passive mating components of the new docking system. This seal is designed to operate in the harsh space environment, but is also to perform within strict loading requirements while maintaining an acceptable level of leak rate. In this study, a candidate silicone elastomer seal was designed, and multiple subscale test articles were manufactured for evaluation purposes. The force required to fully compress each test article at room temperature was quantified and found to be below the maximum allowable load for the docking system. However, a significant amount of scatter was observed in the test results. Due to the stochastic nature of the mechanical performance of this candidate docking seal, a statistical process control technique was implemented to isolate unusual compression behavior from typical mechanical performance. The results of this statistical analysis indicated a lack of process control, suggesting a variation in the manufacturing phase of the process. Further investigation revealed that changes in the manufacturing molding process had occurred which may have influenced the mechanical performance of the seal. This knowledge improves the chance of this and future space seals to satisfy or exceed design specifications.
An approach to build knowledge base for reactor accident diagnostic system using statistical method
International Nuclear Information System (INIS)
Kohsaka, Atsuo; Yokobayashi, Masao; Matsumoto, Kiyoshi; Fujii, Minoru
1988-01-01
In the development of a rule based expert system, one of key issues is how to build a knowledge base (KB). A systematic approach has been attempted for building an objective KB efficiently. The approach is based on the concept that a prototype KB should first be generated in a systematic way and then it is to be modified and/or improved by expert for practical use. The statistical method, Factor Analysis, was applied to build a prototype KB for the JAERI expert system DISKET using source information obtained from a PWR simulator. The prototype KB was obtained and the inference with this KB was performed against several types of transients. In each diagnosis, the transient type was well identified. From this study, it is concluded that the statistical method used is useful for building a prototype knowledge base. (author)
Kravchuk, Olena; Elliott, Antony; Bhandari, Bhesh
2005-01-01
A simple laboratory experiment, based on the Maillard reaction, served as a project in Introductory Statistics for undergraduates in Food Science and Technology. By using the principles of randomization and replication and reflecting on the sources of variation in the experimental data, students reinforced the statistical concepts and techniques…
Popescu, M D; Draghici, L; Secheli, I; Secheli, M; Codrescu, M; Draghici, I
2015-01-01
Infantile Hemangiomas (IH) are the most frequent tumors of vascular origin, and the differential diagnosis from vascular malformations is difficult to establish. Specific types of IH due to the location, dimensions and fast evolution, can determine important functional and esthetic sequels. To avoid these unfortunate consequences it is necessary to establish the exact appropriate moment to begin the treatment and decide which the most adequate therapeutic procedure is. Based on clinical data collected by a serial clinical observations correlated with imaging data, and processed by a computer-aided diagnosis system (CAD), the study intended to develop a treatment algorithm to accurately predict the best final results, from the esthetical and functional point of view, for a certain type of lesion. The preliminary database was composed of 75 patients divided into 4 groups according to the treatment management they received: medical therapy, sclerotherapy, surgical excision and no treatment. The serial clinical observation was performed each month and all the data was processed by using CAD. The project goal was to create a software that incorporated advanced methods to accurately measure the specific IH lesions, integrated medical information, statistical methods and computational methods to correlate this information with that obtained from the processing of images. Based on these correlations, a prediction mechanism of the evolution of hemangioma, which helped determine the best method of therapeutic intervention to minimize further complications, was established.
National Research Council Canada - National Science Library
Willsky, Alan S
2008-01-01
...: (a) the use of graphical, hierarchical, and multiresolution representations for the development of statistical modeling methodologies for complex phenomena and for the construction of scalable algorithms...
Methodology of Maqamat Hamadani and Hariri Based on Buseman’s statistical methodology
Directory of Open Access Journals (Sweden)
Hamed Sedghi
2016-02-01
Full Text Available Abstract Stylistics can be defined as analysis and interpretation of the expression and different forms of speech, based on linguistic elements. German theorist , Buseman , devised his theses in statistical style based on the ratio of verbs to adjectives, generalizing a variety of literary and non- literary genera in German Language and Literature . According to Buseman , increasing the number of verbs in verses, makes the text closer to literary style. Therefore, increasing the number of adjectives, makes the text closer to scientific or subjective style. The most important achievement of statistical methodology of Buseman can be considered as: a comparison of author’s style, literary periods and genres; b studying the language system and variety of words; and, c classification and grading differences or similarities of literary, periods and genres. The purpose of this study: Stylistic analysis of Maqamat Hamadani and al-Hariri based on the statistical model of Buseman. The question proposed in this study : a How effective is the use of the statistical methods , in identifying and analyzing a variety of literature including Maqamat? b How effective is the quantitative scope of verbs and adjectives , as two key parameters in determining the style of literary works? And c Which element of fiction is most effective in enriching the literary approach ? Specific research method is statistical – analysis ; We initially discovered and classified the number of verbs and adjectives in the Fifty- one of Hamadani Maqamehs and Fifty of Hariri Maqamehs ; then the scope of verbs and adjectives usage is shown in the form of tables and graphs . After that , we will assess the style of the literary work , based on the use of verbs and adjectives. The research findings show : All Hamadani and Hariri Maqamat s quantitatively benefit from high -active approach, for the use of the verb . At 46 Maqameh Hamadani , and 48 Maqameh Hariri the
Frontiers in statistical quality control
Wilrich, Peter-Theodor
2001-01-01
The book is a collection of papers presented at the 5th International Workshop on Intelligent Statistical Quality Control in Würzburg, Germany. Contributions deal with methodology and successful industrial applications. They can be grouped in four catagories: Sampling Inspection, Statistical Process Control, Data Analysis and Process Capability Studies and Experimental Design.
A population based statistical model for daily geometric variations in the thorax
Szeto, Yenny Z.; Witte, Marnix G.; van Herk, Marcel; Sonke, Jan-Jakob
2017-01-01
To develop a population based statistical model of the systematic interfraction geometric variations between the planning CT and first treatment week of lung cancer patients for inclusion as uncertainty term in future probabilistic planning. Deformable image registrations between the planning CT and
International Nuclear Information System (INIS)
Slowinski, B.
1987-01-01
A description of a simple phenomenological model of electromagnetic cascade process (ECP) initiated by high-energy gamma quanta in heavy absorbents is given. Within this model spatial structure and fluctuations of ionization losses of shower electrons and positrons are described. Concrete formulae have been obtained as a result of statistical analysis of experimental data from the xenon bubble chamber of ITEP (Moscow)
Frontiers in statistical quality control 11
Schmid, Wolfgang
2015-01-01
The main focus of this edited volume is on three major areas of statistical quality control: statistical process control (SPC), acceptance sampling and design of experiments. The majority of the papers deal with statistical process control, while acceptance sampling and design of experiments are also treated to a lesser extent. The book is organized into four thematic parts, with Part I addressing statistical process control. Part II is devoted to acceptance sampling. Part III covers the design of experiments, while Part IV discusses related fields. The twenty-three papers in this volume stem from The 11th International Workshop on Intelligent Statistical Quality Control, which was held in Sydney, Australia from August 20 to August 23, 2013. The event was hosted by Professor Ross Sparks, CSIRO Mathematics, Informatics and Statistics, North Ryde, Australia and was jointly organized by Professors S. Knoth, W. Schmid and Ross Sparks. The papers presented here were carefully selected and reviewed by the scientifi...
Statistical and Visualization Data Mining Tools for Foundry Production
Directory of Open Access Journals (Sweden)
M. Perzyk
2007-07-01
Full Text Available In recent years a rapid development of a new, interdisciplinary knowledge area, called data mining, is observed. Its main task is extracting useful information from previously collected large amount of data. The main possibilities and potential applications of data mining in manufacturing industry are characterized. The main types of data mining techniques are briefly discussed, including statistical, artificial intelligence, data base and visualization tools. The statistical methods and visualization methods are presented in more detail, showing their general possibilities, advantages as well as characteristic examples of applications in foundry production. Results of the author’s research are presented, aimed at validation of selected statistical tools which can be easily and effectively used in manufacturing industry. A performance analysis of ANOVA and contingency tables based methods, dedicated for determination of the most significant process parameters as well as for detection of possible interactions among them, has been made. Several numerical tests have been performed using simulated data sets, with assumed hidden relationships as well some real data, related to the strength of ductile cast iron, collected in a foundry. It is concluded that the statistical methods offer relatively easy and fairly reliable tools for extraction of that type of knowledge about foundry manufacturing processes. However, further research is needed, aimed at explanation of some imperfections of the investigated tools as well assessment of their validity for more complex tasks.
Statistical and RBF NN models : providing forecasts and risk assessment
Marček, Milan
2009-01-01
Forecast accuracy of economic and financial processes is a popular measure for quantifying the risk in decision making. In this paper, we develop forecasting models based on statistical (stochastic) methods, sometimes called hard computing, and on a soft method using granular computing. We consider the accuracy of forecasting models as a measure for risk evaluation. It is found that the risk estimation process based on soft methods is simplified and less critical to the question w...
Wink, AM; Roerdink, JBTM; Sonka, M; Fitzpatrick, JM
2003-01-01
The quality of statistical analyses of functional neuroimages is studied after applying various preprocessing methods. We present wavelet-based denoising as an alternative to Gaussian smoothing, the standard denoising method in statistical parametric mapping (SPM). The wavelet-based denoising