Statistical evaluation of vibration analysis techniques

Science.gov (United States)

Milner, G. Martin; Miller, Patrice S.

1987-01-01

An evaluation methodology is presented for a selection of candidate vibration analysis techniques applicable to machinery representative of the environmental control and life support system of advanced spacecraft; illustrative results are given. Attention is given to the statistical analysis of small sample experiments, the quantification of detection performance for diverse techniques through the computation of probability of detection versus probability of false alarm, and the quantification of diagnostic performance.

Statistical Theory of the Vector Random Decrement Technique

DEFF Research Database (Denmark)

Asmussen, J. C.; Brincker, Rune; Ibrahim, S. R.

1999-01-01

decays. Due to the speed and/or accuracy of the Vector Random Decrement technique, it was introduced as an attractive alternative to the Random Decrement technique. In this paper, the theory of the Vector Random Decrement technique is extended by applying a statistical description of the stochastic...

Baseline Statistics of Linked Statistical Data

NARCIS (Netherlands)

Scharnhorst, Andrea; Meroño-Peñuela, Albert; Guéret, Christophe

2014-01-01

We are surrounded by an ever increasing ocean of information, everybody will agree to that. We build sophisticated strategies to govern this information: design data models, develop infrastructures for data sharing, building tool for data analysis. Statistical datasets curated by National

Sophistication and Performance of Italian Agri‐food Exports

Directory of Open Access Journals (Sweden)

Anna Carbone

2012-06-01

Full Text Available Nonprice competition is increasingly important in world food markets. Recently, the expression ‘export sophistication’ has been introduced in the economic literature to refer to a wide set of attributes that increase product value. An index has been proposed to measure sophistication in an indirect way through the per capita GDP of exporting countries (Lall et al., 2006; Haussmann et al., 2007.The paper applies the sophistication measure to the Italian food export sector, moving from an analysis of trends and performance of Italian food exports. An original way to disentangle different components in the temporal variation of the sophistication index is also proposed.Results show that the sophistication index offers original insights on recent trends in world food exports and with respect to Italian core food exports.

TECHNIQUE OF THE STATISTICAL ANALYSIS OF INVESTMENT APPEAL OF THE REGION

Directory of Open Access Journals (Sweden)

А. А. Vershinina

2014-01-01

Full Text Available The technique of the statistical analysis of investment appeal of the region is given in scientific article for direct foreign investments. Definition of a technique of the statistical analysis is given, analysis stages reveal, the mathematico-statistical tools are considered.

The First Sophists and the Uses of History.

Science.gov (United States)

Jarratt, Susan C.

1987-01-01

Reviews the history of intellectual views on the Greek sophists in three phases: (1) their disparagement by Plato and Aristotle as the morally disgraceful "other"; (2) nineteenth century British positivists' reappraisal of these relativists as ethically and scientifically superior; and (3) twentieth century versions of the sophists as…

The application of statistical and/or non-statistical sampling techniques by internal audit functions in the South African banking industry

Directory of Open Access Journals (Sweden)

D.P. van der Nest

2015-03-01

Full Text Available This article explores the use by internal audit functions of audit sampling techniques in order to test the effectiveness of controls in the banking sector. The article focuses specifically on the use of statistical and/or non-statistical sampling techniques by internal auditors. The focus of the research for this article was internal audit functions in the banking sector of South Africa. The results discussed in the article indicate that audit sampling is still used frequently as an audit evidence-gathering technique. Non-statistical sampling techniques are used more frequently than statistical sampling techniques for the evaluation of the sample. In addition, both techniques are regarded as important for the determination of the sample size and the selection of the sample items

Cumulative Dominance and Probabilistic Sophistication

NARCIS (Netherlands)

Wakker, P.P.; Sarin, R.H.

2000-01-01

Machina & Schmeidler (Econometrica, 60, 1992) gave preference conditions for probabilistic sophistication, i.e. decision making where uncertainty can be expressed in terms of (subjective) probabilities without commitment to expected utility maximization. This note shows that simpler and more general

Does Investors' Sophistication Affect Persistence and Pricing of Discretionary Accruals?

OpenAIRE

Lanfeng Kao

2007-01-01

This paper examines whether the sophistication of market investors influences management's strategy on discretionary accounting choice, and thus changes the persistence of discretionary accruals. The results show that the persistence of discretionary accruals for firms face with naive investors is lower than that for firms face with sophisticated investors. The results also demonstrate that sophisticated investors indeed incorporate the implications of current earnings components into future ...

The conceptualization and measurement of cognitive health sophistication.

Science.gov (United States)

Bodie, Graham D; Collins, William B; Jensen, Jakob D; Davis, Lashara A; Guntzviller, Lisa M; King, Andy J

2013-01-01

This article develops a conceptualization and measure of cognitive health sophistication--the complexity of an individual's conceptual knowledge about health. Study 1 provides initial validity evidence for the measure--the Healthy-Unhealthy Other Instrument--by showing its association with other cognitive health constructs indicative of higher health sophistication. Study 2 presents data from a sample of low-income adults to provide evidence that the measure does not depend heavily on health-related vocabulary or ethnicity. Results from both studies suggest that the Healthy-Unhealthy Other Instrument can be used to capture variability in the sophistication or complexity of an individual's health-related schematic structures on the basis of responses to two simple open-ended questions. Methodological advantages of the Healthy-Unhealthy Other Instrument and suggestions for future research are highlighted in the discussion.

The statistical chopper in the time-of-flight technique

International Nuclear Information System (INIS)

Albuquerque Vieira, J. de.

1975-12-01

A detailed study of the 'statistical' chopper and of the method of analysis of the data obtained by this technique is made. The study includes the basic ideas behind correlation methods applied in time-of-flight techniques; comparisons with the conventional chopper made by an analysis of statistical errors; the development of a FORTRAN computer programme to analyse experimental results; the presentation of the related fields of work to demonstrate the potential of this method and suggestions for future study together with the criteria for a time-of-flight experiment using the method being studied [pt

Do we need statistics when we have linguistics?

Directory of Open Access Journals (Sweden)

Cantos Gómez Pascual

2002-01-01

Full Text Available Statistics is known to be a quantitative approach to research. However, most of the research done in the fields of language and linguistics is of a different kind, namely qualitative. Succinctly, qualitative analysis differs from quantitative analysis is that in the former no attempt is made to assign frequencies, percentages and the like, to the linguistic features found or identified in the data. In quantitative research, linguistic features are classified and counted, and even more complex statistical models are constructed in order to explain these observed facts. In qualitative research, however, we use the data only for identifying and describing features of language usage and for providing real occurrences/examples of particular phenomena. In this paper, we shall try to show how quantitative methods and statistical techniques can supplement qualitative analyses of language. We shall attempt to present some mathematical and statistical properties of natural languages, and introduce some of the quantitative methods which are of the most value in working empirically with texts and corpora, illustrating the various issues with numerous examples and moving from the most basic descriptive techniques (frequency counts and percentages to decision-taking techniques (chi-square and z-score and to more sophisticated statistical language models (Type-Token/Lemma-Token/Lemma-Type formulae, cluster analysis and discriminant function analysis.

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)

Obfuscation, Learning, and the Evolution of Investor Sophistication

OpenAIRE

Bruce Ian Carlin; Gustavo Manso

2011-01-01

Investor sophistication has lagged behind the growing complexity of retail financial markets. To explore this, we develop a dynamic model to study the interaction between obfuscation and investor sophistication in mutual fund markets. Taking into account different learning mechanisms within the investor population, we characterize the optimal timing of obfuscation for financial institutions who offer retail products. We show that educational initiatives that are directed to facilitate learnin...

Probabilistic Sophistication, Second Order Stochastic Dominance, and Uncertainty Aversion

OpenAIRE

Simone Cerreia-Vioglio; Fabio Maccheroni; Massimo Marinacci; Luigi Montrucchio

2010-01-01

We study the interplay of probabilistic sophistication, second order stochastic dominance, and uncertainty aversion, three fundamental notions in choice under uncertainty. In particular, our main result, Theorem 2, characterizes uncertainty averse preferences that satisfy second order stochastic dominance, as well as uncertainty averse preferences that are probabilistically sophisticated.

Application of multivariate statistical techniques in microbial ecology.

Science.gov (United States)

Paliy, O; Shankar, V

2016-03-01

Recent advances in high-throughput methods of molecular analyses have led to an explosion of studies generating large-scale ecological data sets. In particular, noticeable effect has been attained in the field of microbial ecology, where new experimental approaches provided in-depth assessments of the composition, functions and dynamic changes of complex microbial communities. Because even a single high-throughput experiment produces large amount of data, powerful statistical techniques of multivariate analysis are well suited to analyse and interpret these data sets. Many different multivariate techniques are available, and often it is not clear which method should be applied to a particular data set. In this review, we describe and compare the most widely used multivariate statistical techniques including exploratory, interpretive and discriminatory procedures. We consider several important limitations and assumptions of these methods, and we present examples of how these approaches have been utilized in recent studies to provide insight into the ecology of the microbial world. Finally, we offer suggestions for the selection of appropriate methods based on the research question and data set structure. © 2016 John Wiley & Sons Ltd.

Automatically Assessing Lexical Sophistication: Indices, Tools, Findings, and Application

Science.gov (United States)

Kyle, Kristopher; Crossley, Scott A.

2015-01-01

This study explores the construct of lexical sophistication and its applications for measuring second language lexical and speaking proficiency. In doing so, the study introduces the Tool for the Automatic Analysis of LExical Sophistication (TAALES), which calculates text scores for 135 classic and newly developed lexical indices related to word…

Statistical techniques for automating the detection of anomalous performance in rotating machinery

International Nuclear Information System (INIS)

Piety, K.R.; Magette, T.E.

1978-01-01

Surveillance techniques which extend the sophistication existing in automated systems monitoring in industrial rotating equipment are described. The monitoring system automatically established limiting criteria during an initial learning period of a few days; and subsequently, while monitoring the test rotor during an extended period of normal operation, experienced a false alarm rate of 0.5%. At the same time, the monitoring system successfully detected all fault types that introduced into the test setup. Tests on real equipment are needed to provide final verification of the monitoring techniques. There are areas that would profit from additional investigation in the laboratory environment. A comparison of the relative value of alternate descriptors under given fault conditions would be worthwhile. This should be pursued in conjunction with extending the set of fault types available, e.g., lecaring problems. Other tests should examine the effects of using fewer (more coarse) intervals to define the lumped operational states. finally, techniques to diagnose the most probable fault should be developed by drawing upon the extensive data automatically logged by the monitoring system

Background field removal technique using regularization enabled sophisticated harmonic artifact reduction for phase data with varying kernel sizes.

Science.gov (United States)

Kan, Hirohito; Kasai, Harumasa; Arai, Nobuyuki; Kunitomo, Hiroshi; Hirose, Yasujiro; Shibamoto, Yuta

2016-09-01

An effective background field removal technique is desired for more accurate quantitative susceptibility mapping (QSM) prior to dipole inversion. The aim of this study was to evaluate the accuracy of regularization enabled sophisticated harmonic artifact reduction for phase data with varying spherical kernel sizes (REV-SHARP) method using a three-dimensional head phantom and human brain data. The proposed REV-SHARP method used the spherical mean value operation and Tikhonov regularization in the deconvolution process, with varying 2-14mm kernel sizes. The kernel sizes were gradually reduced, similar to the SHARP with varying spherical kernel (VSHARP) method. We determined the relative errors and relationships between the true local field and estimated local field in REV-SHARP, VSHARP, projection onto dipole fields (PDF), and regularization enabled SHARP (RESHARP). Human experiment was also conducted using REV-SHARP, VSHARP, PDF, and RESHARP. The relative errors in the numerical phantom study were 0.386, 0.448, 0.838, and 0.452 for REV-SHARP, VSHARP, PDF, and RESHARP. REV-SHARP result exhibited the highest correlation between the true local field and estimated local field. The linear regression slopes were 1.005, 1.124, 0.988, and 0.536 for REV-SHARP, VSHARP, PDF, and RESHARP in regions of interest on the three-dimensional head phantom. In human experiments, no obvious errors due to artifacts were present in REV-SHARP. The proposed REV-SHARP is a new method combined with variable spherical kernel size and Tikhonov regularization. This technique might make it possible to be more accurate backgroud field removal and help to achive better accuracy of QSM. Copyright © 2016 Elsevier Inc. All rights reserved.

The role of sophisticated accounting system in strategy management

OpenAIRE

Naranjo Gil, David

2004-01-01

Organizations are designing more sophisticated accounting information systems to meet the strategic goals and enhance their performance. This study examines the effect of accounting information system design on the performance of organizations pursuing different strategic priorities. The alignment between sophisticated accounting information systems and organizational strategy is analyzed. The enabling effect of the accounting information system on performance is also examined. Relationships ...

Financial Literacy and Financial Sophistication in the Older Population

Science.gov (United States)

Lusardi, Annamaria; Mitchell, Olivia S.; Curto, Vilsa

2017-01-01

Using a special-purpose module implemented in the Health and Retirement Study, we evaluate financial sophistication in the American population over the age of 50. We combine several financial literacy questions into an overall index to highlight which questions best capture financial sophistication and examine the sensitivity of financial literacy responses to framing effects. Results show that many older respondents are not financially sophisticated: they fail to grasp essential aspects of risk diversification, asset valuation, portfolio choice, and investment fees. Subgroups with notable deficits include women, the least educated, non-Whites, and those over age 75. In view of the fact that retirees increasingly must take on responsibility for their own retirement security, such meager levels of knowledge have potentially serious and negative implications. PMID:28553191

Financial Literacy and Financial Sophistication in the Older Population.

Science.gov (United States)

Lusardi, Annamaria; Mitchell, Olivia S; Curto, Vilsa

2014-10-01

Using a special-purpose module implemented in the Health and Retirement Study, we evaluate financial sophistication in the American population over the age of 50. We combine several financial literacy questions into an overall index to highlight which questions best capture financial sophistication and examine the sensitivity of financial literacy responses to framing effects. Results show that many older respondents are not financially sophisticated: they fail to grasp essential aspects of risk diversification, asset valuation, portfolio choice, and investment fees. Subgroups with notable deficits include women, the least educated, non-Whites, and those over age 75. In view of the fact that retirees increasingly must take on responsibility for their own retirement security, such meager levels of knowledge have potentially serious and negative implications.

Statistical comparisons of Savannah River anemometer data applied to quality control of instrument networks

International Nuclear Information System (INIS)

Porch, W.M.; Dickerson, M.H.

1976-08-01

Continuous monitoring of extensive meteorological instrument arrays is a requirement in the study of important mesoscale atmospheric phenomena. The phenomena include pollution transport prediction from continuous area sources, or one time releases of toxic materials and wind energy prospecting in areas of topographic enhancement of the wind. Quality control techniques that can be applied to these data to determine if the instruments are operating within their prescribed tolerances were investigated. Savannah River Plant data were analyzed with both independent and comparative statistical techniques. The independent techniques calculate the mean, standard deviation, moments about the mean, kurtosis, skewness, probability density distribution, cumulative probability and power spectra. The comparative techniques include covariance, cross-spectral analysis and two dimensional probability density. At present the calculating and plotting routines for these statistical techniques do not reside in a single code so it is difficult to ascribe independent memory size and computation time accurately. However, given the flexibility of a data system which includes simple and fast running statistics at the instrument end of the data network (ASF) and more sophisticated techniques at the computational end (ACF) a proper balance will be attained. These techniques are described in detail and preliminary results are presented

Lightweight and Statistical Techniques for Petascale PetaScale Debugging

Energy Technology Data Exchange (ETDEWEB)

Miller, Barton

2014-06-30

This project investigated novel techniques for debugging scientific applications on petascale architectures. In particular, we developed lightweight tools that narrow the problem space when bugs are encountered. We also developed techniques that either limit the number of tasks and the code regions to which a developer must apply a traditional debugger or that apply statistical techniques to provide direct suggestions of the location and type of error. We extend previous work on the Stack Trace Analysis Tool (STAT), that has already demonstrated scalability to over one hundred thousand MPI tasks. We also extended statistical techniques developed to isolate programming errors in widely used sequential or threaded applications in the Cooperative Bug Isolation (CBI) project to large scale parallel applications. Overall, our research substantially improved productivity on petascale platforms through a tool set for debugging that complements existing commercial tools. Previously, Office Of Science application developers relied either on primitive manual debugging techniques based on printf or they use tools, such as TotalView, that do not scale beyond a few thousand processors. However, bugs often arise at scale and substantial effort and computation cycles are wasted in either reproducing the problem in a smaller run that can be analyzed with the traditional tools or in repeated runs at scale that use the primitive techniques. New techniques that work at scale and automate the process of identifying the root cause of errors were needed. These techniques significantly reduced the time spent debugging petascale applications, thus leading to a greater overall amount of time for application scientists to pursue the scientific objectives for which the systems are purchased. We developed a new paradigm for debugging at scale: techniques that reduced the debugging scenario to a scale suitable for traditional debuggers, e.g., by narrowing the search for the root-cause analysis

An Automated Energy Detection Algorithm Based on Morphological and Statistical Processing Techniques

Science.gov (United States)

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

Integrated statistical learning of metabolic ion mobility spectrometry profiles for pulmonary disease identification

DEFF Research Database (Denmark)

Hauschild, A.C.; Baumbach, Jan; Baumbach, J.

2012-01-01

sophisticated statistical learning techniques for VOC-based feature selection and supervised classification into patient groups. We analyzed breath data from 84 volunteers, each of them either suffering from chronic obstructive pulmonary disease (COPD), or both COPD and bronchial carcinoma (COPD + BC), as well...... as from 35 healthy volunteers, comprising a control group (CG). We standardized and integrated several statistical learning methods to provide a broad overview of their potential for distinguishing the patient groups. We found that there is strong potential for separating MCC/IMS chromatograms of healthy...... patients from healthy controls. We conclude that these statistical learning methods have a generally high accuracy when applied to well-structured, medical MCC/IMS data....

Short-term Local Forecasting by Artificial Intelligence Techniques and Assess Related Social Effects from Heterogeneous Data

OpenAIRE

Gong, Bing

2017-01-01

This work aims to use the sophisticated artificial intelligence and statistic techniques to forecast pollution and assess its social impact. To achieve the target of the research, this study is divided into several research sub-objectives as follows: First research sub-objective: propose a framework for relocating and reconfiguring the existing pollution monitoring networks by using feature selection, artificial intelligence techniques, and information theory. Second research sub-objective: c...

Probability, statistics, and associated computing techniques

International Nuclear Information System (INIS)

James, F.

1983-01-01

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

Combining heuristic and statistical techniques in landslide hazard assessments

Science.gov (United States)

Cepeda, Jose; Schwendtner, Barbara; Quan, Byron; Nadim, Farrokh; Diaz, Manuel; Molina, Giovanni

2014-05-01

As a contribution to the Global Assessment Report 2013 - GAR2013, coordinated by the United Nations International Strategy for Disaster Reduction - UNISDR, a drill-down exercise for landslide hazard assessment was carried out by entering the results of both heuristic and statistical techniques into a new but simple combination rule. The data available for this evaluation included landslide inventories, both historical and event-based. In addition to the application of a heuristic method used in the previous editions of GAR, the availability of inventories motivated the use of statistical methods. The heuristic technique is largely based on the Mora & Vahrson method, which estimates hazard as the product of susceptibility and triggering factors, where classes are weighted based on expert judgment and experience. Two statistical methods were also applied: the landslide index method, which estimates weights of the classes for the susceptibility and triggering factors based on the evidence provided by the density of landslides in each class of the factors; and the weights of evidence method, which extends the previous technique to include both positive and negative evidence of landslide occurrence in the estimation of weights for the classes. One key aspect during the hazard evaluation was the decision on the methodology to be chosen for the final assessment. Instead of opting for a single methodology, it was decided to combine the results of the three implemented techniques using a combination rule based on a normalization of the results of each method. The hazard evaluation was performed for both earthquake- and rainfall-induced landslides. The country chosen for the drill-down exercise was El Salvador. The results indicate that highest hazard levels are concentrated along the central volcanic chain and at the centre of the northern mountains.

Cognitive Load and Strategic Sophistication

OpenAIRE

Allred, Sarah; Duffy, Sean; Smith, John

2013-01-01

We study the relationship between the cognitive load manipulation and strategic sophistication. The cognitive load manipulation is designed to reduce the subject's cognitive resources that are available for deliberation on a choice. In our experiment, subjects are placed under a large cognitive load (given a difficult number to remember) or a low cognitive load (given a number which is not difficult to remember). Subsequently, the subjects play a one-shot game then they are asked to recall...

Statistics for wildlifers: how much and what kind?

Science.gov (United States)

Johnson, D.H.; Shaffer, T.L.; Newton, W.E.

2001-01-01

Quantitative methods are playing increasingly important roles in wildlife ecology and, ultimately, management. This change poses a challenge for wildlife practitioners and students who are not well-educated in mathematics and statistics. Here we give our opinions on what wildlife biologists should know about statistics, while recognizing that not everyone is inclined mathematically. For those who are, we recommend that they take mathematics coursework at least through calculus and linear algebra. They should take statistics courses that are focused conceptually , stressing the Why rather than the How of doing statistics. For less mathematically oriented wildlifers, introductory classes in statistical techniques will furnish some useful background in basic methods but may provide little appreciation of when the methods are appropriate. These wildlifers will have to rely much more on advice from statisticians. Far more important than knowing how to analyze data is an understanding of how to obtain and recognize good data. Regardless of the statistical education they receive, all wildlife biologists should appreciate the importance of controls, replication, and randomization in studies they conduct. Understanding these concepts requires little mathematical sophistication, but is critical to advancing the science of wildlife ecology.

Statistical and Machine-Learning Data Mining Techniques for Better Predictive Modeling and Analysis of Big Data

CERN Document Server

Ratner, Bruce

2011-01-01

The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data, contained 17 chapters of innovative and practical statistical data mining techniques. In this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has

Moral foundations and political attitudes: The moderating role of political sophistication.

Science.gov (United States)

Milesi, Patrizia

2016-08-01

Political attitudes can be associated with moral concerns. This research investigated whether people's level of political sophistication moderates this association. Based on the Moral Foundations Theory, this article examined whether political sophistication moderates the extent to which reliance on moral foundations, as categories of moral concerns, predicts judgements about policy positions. With this aim, two studies examined four policy positions shown by previous research to be best predicted by the endorsement of Sanctity, that is, the category of moral concerns focused on the preservation of physical and spiritual purity. The results showed that reliance on Sanctity predicted political sophisticates' judgements, as opposed to those of unsophisticates, on policy positions dealing with equal rights for same-sex and unmarried couples and with euthanasia. Political sophistication also interacted with Fairness endorsement, which includes moral concerns for equal treatment of everybody and reciprocity, in predicting judgements about equal rights for unmarried couples, and interacted with reliance on Authority, which includes moral concerns for obedience and respect for traditional authorities, in predicting opposition to stem cell research. Those findings suggest that, at least for these particular issues, endorsement of moral foundations can be associated with political attitudes more strongly among sophisticates than unsophisticates. © 2015 International Union of Psychological Science.

The application of statistical techniques to nuclear materials accountancy

International Nuclear Information System (INIS)

Annibal, P.S.; Roberts, P.D.

1990-02-01

Over the past decade much theoretical research has been carried out on the development of statistical methods for nuclear materials accountancy. In practice plant operation may differ substantially from the idealized models often cited. This paper demonstrates the importance of taking account of plant operation in applying the statistical techniques, to improve the accuracy of the estimates and the knowledge of the errors. The benefits are quantified either by theoretical calculation or by simulation. Two different aspects are considered; firstly, the use of redundant measurements to reduce the error on the estimate of the mass of heavy metal in an accountancy tank is investigated. Secondly, a means of improving the knowledge of the 'Material Unaccounted For' (the difference between the inventory calculated from input/output data, and the measured inventory), using information about the plant measurement system, is developed and compared with existing general techniques. (author)

Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

Science.gov (United States)

Mishra, D.; Goyal, P.

2014-12-01

Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

Aristotle and Social-Epistemic Rhetoric: The Systematizing of the Sophistic Legacy.

Science.gov (United States)

Allen, James E.

While Aristotle's philosophical views are more foundational than those of many of the Older Sophists, Aristotle's rhetorical theories inherit and incorporate many of the central tenets ascribed to Sophistic rhetoric, albeit in a more systematic fashion, as represented in the "Rhetoric." However, Aristotle was more than just a rhetorical…

A comparison of linear and nonlinear statistical techniques in performance attribution.

Science.gov (United States)

Chan, N H; Genovese, C R

2001-01-01

Performance attribution is usually conducted under the linear framework of multifactor models. Although commonly used by practitioners in finance, linear multifactor models are known to be less than satisfactory in many situations. After a brief survey of nonlinear methods, nonlinear statistical techniques are applied to performance attribution of a portfolio constructed from a fixed universe of stocks using factors derived from some commonly used cross sectional linear multifactor models. By rebalancing this portfolio monthly, the cumulative returns for procedures based on standard linear multifactor model and three nonlinear techniques-model selection, additive models, and neural networks-are calculated and compared. It is found that the first two nonlinear techniques, especially in combination, outperform the standard linear model. The results in the neural-network case are inconclusive because of the great variety of possible models. Although these methods are more complicated and may require some tuning, toolboxes are developed and suggestions on calibration are proposed. This paper demonstrates the usefulness of modern nonlinear statistical techniques in performance attribution.

Statistical optimisation techniques in fatigue signal editing problem

International Nuclear Information System (INIS)

Nopiah, Z. M.; Osman, M. H.; Baharin, N.; Abdullah, S.

2015-01-01

Success in fatigue signal editing is determined by the level of length reduction without compromising statistical constraints. A great reduction rate can be achieved by removing small amplitude cycles from the recorded signal. The long recorded signal sometimes renders the cycle-to-cycle editing process daunting. This has encouraged researchers to focus on the segment-based approach. This paper discusses joint application of the Running Damage Extraction (RDE) technique and single constrained Genetic Algorithm (GA) in fatigue signal editing optimisation.. In the first section, the RDE technique is used to restructure and summarise the fatigue strain. This technique combines the overlapping window and fatigue strain-life models. It is designed to identify and isolate the fatigue events that exist in the variable amplitude strain data into different segments whereby the retention of statistical parameters and the vibration energy are considered. In the second section, the fatigue data editing problem is formulated as a constrained single optimisation problem that can be solved using GA method. The GA produces the shortest edited fatigue signal by selecting appropriate segments from a pool of labelling segments. Challenges arise due to constraints on the segment selection by deviation level over three signal properties, namely cumulative fatigue damage, root mean square and kurtosis values. Experimental results over several case studies show that the idea of solving fatigue signal editing within a framework of optimisation is effective and automatic, and that the GA is robust for constrained segment selection

Statistical optimisation techniques in fatigue signal editing problem

Energy Technology Data Exchange (ETDEWEB)

Nopiah, Z. M.; Osman, M. H. [Fundamental Engineering Studies Unit Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM (Malaysia); Baharin, N.; Abdullah, S. [Department of Mechanical and Materials Engineering Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM (Malaysia)

2015-02-03

Success in fatigue signal editing is determined by the level of length reduction without compromising statistical constraints. A great reduction rate can be achieved by removing small amplitude cycles from the recorded signal. The long recorded signal sometimes renders the cycle-to-cycle editing process daunting. This has encouraged researchers to focus on the segment-based approach. This paper discusses joint application of the Running Damage Extraction (RDE) technique and single constrained Genetic Algorithm (GA) in fatigue signal editing optimisation.. In the first section, the RDE technique is used to restructure and summarise the fatigue strain. This technique combines the overlapping window and fatigue strain-life models. It is designed to identify and isolate the fatigue events that exist in the variable amplitude strain data into different segments whereby the retention of statistical parameters and the vibration energy are considered. In the second section, the fatigue data editing problem is formulated as a constrained single optimisation problem that can be solved using GA method. The GA produces the shortest edited fatigue signal by selecting appropriate segments from a pool of labelling segments. Challenges arise due to constraints on the segment selection by deviation level over three signal properties, namely cumulative fatigue damage, root mean square and kurtosis values. Experimental results over several case studies show that the idea of solving fatigue signal editing within a framework of optimisation is effective and automatic, and that the GA is robust for constrained segment selection.

Line identification studies using traditional techniques and wavelength coincidence statistics

International Nuclear Information System (INIS)

Cowley, C.R.; Adelman, S.J.

1990-01-01

Traditional line identification techniques result in the assignment of individual lines to an atomic or ionic species. These methods may be supplemented by wavelength coincidence statistics (WCS). The strength and weakness of these methods are discussed using spectra of a number of normal and peculiar B and A stars that have been studied independently by both methods. The present results support the overall findings of some earlier studies. WCS would be most useful in a first survey, before traditional methods have been applied. WCS can quickly make a global search for all species and in this way may enable identifications of an unexpected spectrum that could easily be omitted entirely from a traditional study. This is illustrated by O I. WCS is a subject to well known weakness of any statistical technique, for example, a predictable number of spurious results are to be expected. The danger of small number statistics are illustrated. WCS is at its best relative to traditional methods in finding a line-rich atomic species that is only weakly present in a complicated stellar spectrum

Statistical and Economic Techniques for Site-specific Nematode Management.

Science.gov (United States)

Liu, Zheng; Griffin, Terry; Kirkpatrick, Terrence L

2014-03-01

Recent advances in precision agriculture technologies and spatial statistics allow realistic, site-specific estimation of nematode damage to field crops and provide a platform for the site-specific delivery of nematicides within individual fields. This paper reviews the spatial statistical techniques that model correlations among neighboring observations and develop a spatial economic analysis to determine the potential of site-specific nematicide application. The spatial econometric methodology applied in the context of site-specific crop yield response contributes to closing the gap between data analysis and realistic site-specific nematicide recommendations and helps to provide a practical method of site-specifically controlling nematodes.

The predictors of economic sophistication: media, interpersonal communication and negative economic experiences

NARCIS (Netherlands)

Kalogeropoulos, A.; Albæk, E.; de Vreese, C.H.; van Dalen, A.

2015-01-01

In analogy to political sophistication, it is imperative that citizens have a certain level of economic sophistication, especially in times of heated debates about the economy. This study examines the impact of different influences (media, interpersonal communication and personal experiences) on

Statistical methods of evaluating and comparing imaging techniques

International Nuclear Information System (INIS)

Freedman, L.S.

1987-01-01

Over the past 20 years several new methods of generating images of internal organs and the anatomy of the body have been developed and used to enhance the accuracy of diagnosis and treatment. These include ultrasonic scanning, radioisotope scanning, computerised X-ray tomography (CT) and magnetic resonance imaging (MRI). The new techniques have made a considerable impact on radiological practice in hospital departments, not least on the investigational process for patients suspected or known to have malignant disease. As a consequence of the increased range of imaging techniques now available, there has developed a need to evaluate and compare their usefulness. Over the past 10 years formal studies of the application of imaging technology have been conducted and many reports have appeared in the literature. These studies cover a range of clinical situations. Likewise, the methodologies employed for evaluating and comparing the techniques in question have differed widely. While not attempting an exhaustive review of the clinical studies which have been reported, this paper aims to examine the statistical designs and analyses which have been used. First a brief review of the different types of study is given. Examples of each type are then chosen to illustrate statistical issues related to their design and analysis. In the final sections it is argued that a form of classification for these different types of study might be helpful in clarifying relationships between them and bringing a perspective to the field. A classification based upon a limited analogy with clinical trials is suggested

Categorical and nonparametric data analysis choosing the best statistical technique

CERN Document Server

Nussbaum, E Michael

2014-01-01

Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain

PAUL AND SOPHISTIC RHETORIC: A PERSPECTIVE ON HIS ...

African Journals Online (AJOL)

use of modern rhetorical theories but analyses the letter in terms of the clas- ..... If a critical reader would have had the traditional anti-sophistic arsenal ..... pressions and that 'rhetoric' is mainly a matter of communicating these thoughts.

Application of Multivariable Statistical Techniques in Plant-wide WWTP Control Strategies Analysis

DEFF Research Database (Denmark)

Flores Alsina, Xavier; Comas, J.; Rodríguez-Roda, I.

2007-01-01

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant...... analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii......) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation...

Statistics for economics

CERN Document Server

Naghshpour, Shahdad

2012-01-01

Statistics is the branch of mathematics that deals with real-life problems. As such, it is an essential tool for economists. Unfortunately, the way you and many other economists learn the concept of statistics is not compatible with the way economists think and learn. The problem is worsened by the use of mathematical jargon and complex derivations. Here's a book that proves none of this is necessary. All the examples and exercises in this book are constructed within the field of economics, thus eliminating the difficulty of learning statistics with examples from fields that have no relation to business, politics, or policy. Statistics is, in fact, not more difficult than economics. Anyone who can comprehend economics can understand and use statistics successfully within this field, including you! This book utilizes Microsoft Excel to obtain statistical results, as well as to perform additional necessary computations. Microsoft Excel is not the software of choice for performing sophisticated statistical analy...

Isocratean Discourse Theory and Neo-Sophistic Pedagogy: Implications for the Composition Classroom.

Science.gov (United States)

Blair, Kristine L.

With the recent interest in the fifth century B.C. theories of Protagoras and Gorgias come assumptions about the philosophical affinity of the Greek educator Isocrates to this pair of older sophists. Isocratean education in discourse, with its emphasis on collaborative political discourse, falls within recent definitions of a sophist curriculum.…

SMEs and new ventures need business model sophistication

DEFF Research Database (Denmark)

Kesting, Peter; Günzel-Jensen, Franziska

2015-01-01

, and Spreadshirt, this article develops a framework that introduces five business model sophistication strategies: (1) uncover additional functions of your product, (2) identify strategic benefits for third parties, (3) take advantage of economies of scope, (4) utilize cross-selling opportunities, and (5) involve...

Statistical techniques to extract information during SMAP soil moisture assimilation

Science.gov (United States)

Kolassa, J.; Reichle, R. H.; Liu, Q.; Alemohammad, S. H.; Gentine, P.

2017-12-01

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, the need for bias correction prior to an assimilation of these estimates is reduced, which could result in a more effective use of the independent information provided by the satellite observations. In this study, a statistical neural network (NN) retrieval algorithm is calibrated using SMAP brightness temperature observations and modeled soil moisture estimates (similar to those used to calibrate the SMAP Level 4 DA system). Daily values of surface soil moisture are estimated using the NN and then assimilated into the NASA Catchment model. The skill of the assimilation estimates is assessed based on a comprehensive comparison to in situ measurements from the SMAP core and sparse network sites as well as the International Soil Moisture Network. The NN retrieval assimilation is found to significantly improve the model skill, particularly in areas where the model does not represent processes related to agricultural practices. Additionally, the NN method is compared to assimilation experiments using traditional bias correction techniques. The NN retrieval assimilation is found to more effectively use the independent information provided by SMAP resulting in larger model skill improvements than assimilation experiments using traditional bias correction techniques.

Curve fitting and modeling with splines using statistical variable selection techniques

Science.gov (United States)

Smith, P. L.

1982-01-01

The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

Statistical Approaches Used to Assess the Equity of Access to Food Outlets: A Systematic Review.

Science.gov (United States)

Lamb, Karen E; Thornton, Lukar E; Cerin, Ester; Ball, Kylie

2015-01-01

Inequalities in eating behaviours are often linked to the types of food retailers accessible in neighbourhood environments. Numerous studies have aimed to identify if access to healthy and unhealthy food retailers is socioeconomically patterned across neighbourhoods, and thus a potential risk factor for dietary inequalities. Existing reviews have examined differences between methodologies, particularly focussing on neighbourhood and food outlet access measure definitions. However, no review has informatively discussed the suitability of the statistical methodologies employed; a key issue determining the validity of study findings. Our aim was to examine the suitability of statistical approaches adopted in these analyses. Searches were conducted for articles published from 2000-2014. Eligible studies included objective measures of the neighbourhood food environment and neighbourhood-level socio-economic status, with a statistical analysis of the association between food outlet access and socio-economic status. Fifty-four papers were included. Outlet accessibility was typically defined as the distance to the nearest outlet from the neighbourhood centroid, or as the number of food outlets within a neighbourhood (or buffer). To assess if these measures were linked to neighbourhood disadvantage, common statistical methods included ANOVA, correlation, and Poisson or negative binomial regression. Although all studies involved spatial data, few considered spatial analysis techniques or spatial autocorrelation. With advances in GIS software, sophisticated measures of neighbourhood outlet accessibility can be considered. However, approaches to statistical analysis often appear less sophisticated. Care should be taken to consider assumptions underlying the analysis and the possibility of spatially correlated residuals which could affect the results.

Statistical Approaches Used to Assess the Equity of Access to Food Outlets: A Systematic Review

Directory of Open Access Journals (Sweden)

Karen E. Lamb

2015-07-01

Full Text Available BackgroundInequalities in eating behaviours are often linked to the types of food retailers accessible in neighbourhood environments. Numerous studies have aimed to identify if access to healthy and unhealthy food retailers is socioeconomically patterned across neighbourhoods, and thus a potential risk factor for dietary inequalities. Existing reviews have examined differences between methodologies, particularly focussing on neighbourhood and food outlet access measure definitions. However, no review has informatively discussed the suitability of the statistical methodologies employed; a key issue determining the validity of study findings. Our aim was to examine the suitability of statistical approaches adopted in these analyses.MethodsSearches were conducted for articles published from 2000-2014. Eligible studies included objective measures of the neighbourhood food environment and neighbourhood-level socio-economic status, with a statistical analysis of the association between food outlet access and socio-economic status.ResultsFifty-four papers were included. Outlet accessibility was typically defined as the distance to the nearest outlet from the neighbourhood centroid, or as the number of food outlets within a neighbourhood (or buffer. To assess if these measures were linked to neighbourhood disadvantage, common statistical methods included ANOVA, correlation, and Poisson or negative binomial regression. Although all studies involved spatial data, few considered spatial analysis techniques or spatial autocorrelation.ConclusionsWith advances in GIS software, sophisticated measures of neighbourhood outlet accessibility can be considered. However, approaches to statistical analysis often appear less sophisticated. Care should be taken to consider assumptions underlying the analysis and the possibility of spatially correlated residuals which could affect the results.

Statistical precision of delayed-neutron nondestructive assay techniques

International Nuclear Information System (INIS)

Bayne, C.K.; McNeany, S.R.

1979-02-01

A theoretical analysis of the statistical precision of delayed-neutron nondestructive assay instruments is presented. Such instruments measure the fissile content of nuclear fuel samples by neutron irradiation and delayed-neutron detection. The precision of these techniques is limited by the statistical nature of the nuclear decay process, but the precision can be optimized by proper selection of system operating parameters. Our method is a three-part analysis. We first present differential--difference equations describing the fundamental physics of the measurements. We then derive and present complete analytical solutions to these equations. Final equations governing the expected number and variance of delayed-neutron counts were computer programmed to calculate the relative statistical precision of specific system operating parameters. Our results show that Poisson statistics do not govern the number of counts accumulated in multiple irradiation-count cycles and that, in general, maximum count precision does not correspond with maximum count as first expected. Covariance between the counts of individual cycles must be considered in determining the optimum number of irradiation-count cycles and the optimum irradiation-to-count time ratio. For the assay system in use at ORNL, covariance effects are small, but for systems with short irradiation-to-count transition times, covariance effects force the optimum number of irradiation-count cycles to be half those giving maximum count. We conclude that the equations governing the expected value and variance of delayed-neutron counts have been derived in closed form. These have been computerized and can be used to select optimum operating parameters for delayed-neutron assay devices

Cognitive ability rivals the effect of political sophistication on ideological voting

DEFF Research Database (Denmark)

Hebbelstrup Rye Rasmussen, Stig

2016-01-01

This article examines the impact of cognitive ability on ideological voting. We find, using a US sample and a Danish sample, that the effect of cognitive ability rivals the effect of the traditionally strongest predicter of ideological voting political sophistication. Furthermore, the results...... are consistent with the effect of cognitive ability being partly mediated by political sophistication. Much of the effect of cognitive ability remains however and is not explained by differences in education or Openness to experience either. The implications of these results for democratic theory are discussed....

The Statistical Analysis Techniques to Support the NGNP Fuel Performance Experiments

International Nuclear Information System (INIS)

Pham, Bihn T.; Einerson, Jeffrey J.

2010-01-01

This paper describes the development and application of statistical analysis techniques to support the AGR experimental program on NGNP fuel performance. The experiments conducted in the Idaho National Laboratory's Advanced Test Reactor employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule. The tests are instrumented with thermocouples embedded in graphite blocks and the target quantity (fuel/graphite temperature) is regulated by the He-Ne gas mixture that fills the gap volume. Three techniques for statistical analysis, namely control charting, correlation analysis, and regression analysis, are implemented in the SAS-based NGNP Data Management and Analysis System (NDMAS) for automated processing and qualification of the AGR measured data. The NDMAS also stores daily neutronic (power) and thermal (heat transfer) code simulation results along with the measurement data, allowing for their combined use and comparative scrutiny. The ultimate objective of this work includes (a) a multi-faceted system for data monitoring and data accuracy testing, (b) identification of possible modes of diagnostics deterioration and changes in experimental conditions, (c) qualification of data for use in code validation, and (d) identification and use of data trends to support effective control of test conditions with respect to the test target. Analysis results and examples given in the paper show the three statistical analysis techniques providing a complementary capability to warn of thermocouple failures. It also suggests that the regression analysis models relating calculated fuel temperatures and thermocouple readings can enable online regulation of experimental parameters (i.e. gas mixture content), to effectively maintain the target quantity (fuel temperature) within a given range.

The statistical analysis techniques to support the NGNP fuel performance experiments

Energy Technology Data Exchange (ETDEWEB)

Pham, Binh T., E-mail: Binh.Pham@inl.gov; Einerson, Jeffrey J.

2013-10-15

This paper describes the development and application of statistical analysis techniques to support the Advanced Gas Reactor (AGR) experimental program on Next Generation Nuclear Plant (NGNP) fuel performance. The experiments conducted in the Idaho National Laboratory’s Advanced Test Reactor employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule. The tests are instrumented with thermocouples embedded in graphite blocks and the target quantity (fuel temperature) is regulated by the He–Ne gas mixture that fills the gap volume. Three techniques for statistical analysis, namely control charting, correlation analysis, and regression analysis, are implemented in the NGNP Data Management and Analysis System for automated processing and qualification of the AGR measured data. The neutronic and thermal code simulation results are used for comparative scrutiny. The ultimate objective of this work includes (a) a multi-faceted system for data monitoring and data accuracy testing, (b) identification of possible modes of diagnostics deterioration and changes in experimental conditions, (c) qualification of data for use in code validation, and (d) identification and use of data trends to support effective control of test conditions with respect to the test target. Analysis results and examples given in the paper show the three statistical analysis techniques providing a complementary capability to warn of thermocouple failures. It also suggests that the regression analysis models relating calculated fuel temperatures and thermocouple readings can enable online regulation of experimental parameters (i.e. gas mixture content), to effectively maintain the fuel temperature within a given range.

Statistical evaluation of recorded knowledge in nuclear and other instrumental analytical techniques

International Nuclear Information System (INIS)

Braun, T.

1987-01-01

The main points addressed in this study are the following: Statistical distribution patterns of published literature on instrumental analytical techniques 1981-1984; structure of scientific literature and heuristics for identifying active specialities and emerging hot spot research areas in instrumental analytical techniques; growth and growth rates of the literature in some of the identified hot research areas; quality and quantity in instrumental analytical research output. (orig.)

Comparison of adaptive statistical iterative and filtered back projection reconstruction techniques in brain CT

International Nuclear Information System (INIS)

Ren, Qingguo; Dewan, Sheilesh Kumar; Li, Ming; Li, Jianying; Mao, Dingbiao; Wang, Zhenglei; Hua, Yanqing

2012-01-01

Purpose: To compare image quality and visualization of normal structures and lesions in brain computed tomography (CT) with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP) reconstruction techniques in different X-ray tube current–time products. Materials and methods: In this IRB-approved prospective study, forty patients (nineteen men, twenty-one women; mean age 69.5 ± 11.2 years) received brain scan at different tube current–time products (300 and 200 mAs) in 64-section multi-detector CT (GE, Discovery CT750 HD). Images were reconstructed with FBP and four levels of ASIR-FBP blending. Two radiologists (please note that our hospital is renowned for its geriatric medicine department, and these two radiologists are more experienced in chronic cerebral vascular disease than in neoplastic disease, so this research did not contain cerebral tumors but as a discussion) assessed all the reconstructed images for visibility of normal structures, lesion conspicuity, image contrast and diagnostic confidence in a blinded and randomized manner. Volume CT dose index (CTDI vol ) and dose-length product (DLP) were recorded. All the data were analyzed by using SPSS 13.0 statistical analysis software. Results: There was no statistically significant difference between the image qualities at 200 mAs with 50% ASIR blending technique and 300 mAs with FBP technique (p > .05). While between the image qualities at 200 mAs with FBP and 300 mAs with FBP technique a statistically significant difference (p < .05) was found. Conclusion: ASIR provided same image quality and diagnostic ability in brain imaging with greater than 30% dose reduction compared with FBP reconstruction technique

Comparison of adaptive statistical iterative and filtered back projection reconstruction techniques in brain CT

Energy Technology Data Exchange (ETDEWEB)

Ren, Qingguo, E-mail: renqg83@163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Dewan, Sheilesh Kumar, E-mail: sheilesh_d1@hotmail.com [Department of Geriatrics, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Li, Ming, E-mail: minli77@163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Li, Jianying, E-mail: Jianying.Li@med.ge.com [CT Imaging Research Center, GE Healthcare China, Beijing (China); Mao, Dingbiao, E-mail: maodingbiao74@163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Wang, Zhenglei, E-mail: Williswang_doc@yahoo.com.cn [Department of Radiology, Shanghai Electricity Hospital, Shanghai 200050 (China); Hua, Yanqing, E-mail: cjr.huayanqing@vip.163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China)

2012-10-15

Purpose: To compare image quality and visualization of normal structures and lesions in brain computed tomography (CT) with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP) reconstruction techniques in different X-ray tube current–time products. Materials and methods: In this IRB-approved prospective study, forty patients (nineteen men, twenty-one women; mean age 69.5 ± 11.2 years) received brain scan at different tube current–time products (300 and 200 mAs) in 64-section multi-detector CT (GE, Discovery CT750 HD). Images were reconstructed with FBP and four levels of ASIR-FBP blending. Two radiologists (please note that our hospital is renowned for its geriatric medicine department, and these two radiologists are more experienced in chronic cerebral vascular disease than in neoplastic disease, so this research did not contain cerebral tumors but as a discussion) assessed all the reconstructed images for visibility of normal structures, lesion conspicuity, image contrast and diagnostic confidence in a blinded and randomized manner. Volume CT dose index (CTDI{sub vol}) and dose-length product (DLP) were recorded. All the data were analyzed by using SPSS 13.0 statistical analysis software. Results: There was no statistically significant difference between the image qualities at 200 mAs with 50% ASIR blending technique and 300 mAs with FBP technique (p > .05). While between the image qualities at 200 mAs with FBP and 300 mAs with FBP technique a statistically significant difference (p < .05) was found. Conclusion: ASIR provided same image quality and diagnostic ability in brain imaging with greater than 30% dose reduction compared with FBP reconstruction technique.

The Relationship between Logistics Sophistication and Drivers of the Outsourcing of Logistics Activities

Directory of Open Access Journals (Sweden)

Peter Wanke

2008-10-01

Full Text Available A strong link has been established between operational excellence and the degree of sophistication of logistics organization, a function of factors such as performance monitoring, investment in Information Technology [IT] and the formalization of logistics organization, as proposed in the Bowersox, Daugherty, Dröge, Germain and Rogers (1992 Leading Edge model. At the same time, shippers have been increasingly outsourcing their logistics activities to third party providers. This paper, based on a survey with large Brazilian shippers, addresses a gap in the literature by investigating the relationship between dimensions of logistics organization sophistication and drivers of logistics outsourcing. To this end, the dimensions behind the logistics sophistication construct were first investigated. Results from factor analysis led to the identification of six dimensions of logistics sophistication. By means of multivariate logistical regression analyses it was possible to relate some of these dimensions, such as the formalization of the logistics organization, to certain drivers of the outsourcing of logistics activities of Brazilian shippers, such as cost savings. These results indicate the possibility of segmenting shippers according to characteristics of their logistics organization, which may be particularly useful to logistics service providers.

Lexical Complexity Development from Dynamic Systems Theory Perspective: Lexical Density, Diversity, and Sophistication

Directory of Open Access Journals (Sweden)

Reza Kalantari

2017-10-01

Full Text Available This longitudinal case study explored Iranian EFL learners’ lexical complexity (LC through the lenses of Dynamic Systems Theory (DST. Fifty independent essays written by five intermediate to advanced female EFL learners in a TOEFL iBT preparation course over six months constituted the corpus of this study. Three Coh-Metrix indices (Graesser, McNamara, Louwerse, & Cai, 2004; McNamara & Graesser, 2012, three Lexical Complexity Analyzer indices (Lu, 2010, 2012; Lu & Ai, 2011, and four Vocabprofile indices (Cobb, 2000 were selected to measure different dimensions of LC. Results of repeated measures analysis of variance (RM ANOVA indicated an improvement with regard to only lexical sophistication. Positive and significant relationships were found between time and mean values in Academic Word List and Beyond-2000 as indicators of lexical sophistication. The remaining seven indices of LC, falling short of significance, tended to flatten over the course of this writing program. Correlation analyses among LC indices indicated that lexical density enjoyed positive correlations with lexical sophistication. However, lexical diversity revealed no significant correlations with both lexical density and lexical sophistication. This study suggests that DST perspective specifies a viable foundation for analyzing lexical complexity

Statistical physics

CERN Document Server

Guénault, Tony

2007-01-01

In this revised and enlarged second edition of an established text Tony Guénault provides a clear and refreshingly readable introduction to statistical physics, an essential component of any first degree in physics. The treatment itself is self-contained and concentrates on an understanding of the physical ideas, without requiring a high level of mathematical sophistication. A straightforward quantum approach to statistical averaging is adopted from the outset (easier, the author believes, than the classical approach). The initial part of the book is geared towards explaining the equilibrium properties of a simple isolated assembly of particles. Thus, several important topics, for example an ideal spin-½ solid, can be discussed at an early stage. The treatment of gases gives full coverage to Maxwell-Boltzmann, Fermi-Dirac and Bose-Einstein statistics. Towards the end of the book the student is introduced to a wider viewpoint and new chapters are included on chemical thermodynamics, interactions in, for exam...

Angular-momentum nonclassicality by breaking classical bounds on statistics

Energy Technology Data Exchange (ETDEWEB)

Luis, Alfredo [Departamento de Optica, Facultad de Ciencias Fisicas, Universidad Complutense, E-28040 Madrid (Spain); Rivas, Angel [Departamento de Fisica Teorica I, Facultad de Ciencias Fisicas, Universidad Complutense, E-28040 Madrid (Spain)

2011-10-15

We derive simple practical procedures revealing the quantum behavior of angular momentum variables by the violation of classical upper bounds on the statistics. Data analysis is minimum and definite conclusions are obtained without evaluation of moments, or any other more sophisticated procedures. These nonclassical tests are very general and independent of other typical quantum signatures of nonclassical behavior such as sub-Poissonian statistics, squeezing, or oscillatory statistics, being insensitive to the nonclassical behavior displayed by other variables.

Structural reliability in context of statistical uncertainties and modelling discrepancies

International Nuclear Information System (INIS)

Pendola, Maurice

2000-01-01

Structural reliability methods have been largely improved during the last years and have showed their ability to deal with uncertainties during the design stage or to optimize the functioning and the maintenance of industrial installations. They are based on a mechanical modeling of the structural behavior according to the considered failure modes and on a probabilistic representation of input parameters of this modeling. In practice, only limited statistical information is available to build the probabilistic representation and different sophistication levels of the mechanical modeling may be introduced. Thus, besides the physical randomness, other uncertainties occur in such analyses. The aim of this work is triple: 1. at first, to propose a methodology able to characterize the statistical uncertainties due to the limited number of data in order to take them into account in the reliability analyses. The obtained reliability index measures the confidence in the structure considering the statistical information available. 2. Then, to show a methodology leading to reliability results evaluated from a particular mechanical modeling but by using a less sophisticated one. The objective is then to decrease the computational efforts required by the reference modeling. 3. Finally, to propose partial safety factors that are evolving as a function of the number of statistical data available and as a function of the sophistication level of the mechanical modeling that is used. The concepts are illustrated in the case of a welded pipe and in the case of a natural draught cooling tower. The results show the interest of the methodologies in an industrial context. [fr

The New Toxicology of Sophisticated Materials: Nanotoxicology and Beyond

Science.gov (United States)

Maynard, Andrew D.; Warheit, David B.; Philbert, Martin A.

2011-01-01

It has long been recognized that the physical form of materials can mediate their toxicity—the health impacts of asbestiform materials, industrial aerosols, and ambient particulate matter are prime examples. Yet over the past 20 years, toxicology research has suggested complex and previously unrecognized associations between material physicochemistry at the nanoscale and biological interactions. With the rapid rise of the field of nanotechnology and the design and production of increasingly complex nanoscale materials, it has become ever more important to understand how the physical form and chemical composition of these materials interact synergistically to determine toxicity. As a result, a new field of research has emerged—nanotoxicology. Research within this field is highlighting the importance of material physicochemical properties in how dose is understood, how materials are characterized in a manner that enables quantitative data interpretation and comparison, and how materials move within, interact with, and are transformed by biological systems. Yet many of the substances that are the focus of current nanotoxicology studies are relatively simple materials that are at the vanguard of a new era of complex materials. Over the next 50 years, there will be a need to understand the toxicology of increasingly sophisticated materials that exhibit novel, dynamic and multifaceted functionality. If the toxicology community is to meet the challenge of ensuring the safe use of this new generation of substances, it will need to move beyond “nano” toxicology and toward a new toxicology of sophisticated materials. Here, we present a brief overview of the current state of the science on the toxicology of nanoscale materials and focus on three emerging toxicology-based challenges presented by sophisticated materials that will become increasingly important over the next 50 years: identifying relevant materials for study, physicochemical characterization, and

A Comparison of the Performance of Advanced Statistical Techniques for the Refinement of Day-ahead and Longer NWP-based Wind Power Forecasts

Science.gov (United States)

Zack, J. W.

2015-12-01

Predictions from Numerical Weather Prediction (NWP) models are the foundation for wind power forecasts for day-ahead and longer forecast horizons. The NWP models directly produce three-dimensional wind forecasts on their respective computational grids. These can be interpolated to the location and time of interest. However, these direct predictions typically contain significant systematic errors ("biases"). This is due to a variety of factors including the limited space-time resolution of the NWP models and shortcomings in the model's representation of physical processes. It has become common practice to attempt to improve the raw NWP forecasts by statistically adjusting them through a procedure that is widely known as Model Output Statistics (MOS). The challenge is to identify complex patterns of systematic errors and then use this knowledge to adjust the NWP predictions. The MOS-based improvements are the basis for much of the value added by commercial wind power forecast providers. There are an enormous number of statistical approaches that can be used to generate the MOS adjustments to the raw NWP forecasts. In order to obtain insight into the potential value of some of the newer and more sophisticated statistical techniques often referred to as "machine learning methods" a MOS-method comparison experiment has been performed for wind power generation facilities in 6 wind resource areas of California. The underlying NWP models that provided the raw forecasts were the two primary operational models of the US National Weather Service: the GFS and NAM models. The focus was on 1- and 2-day ahead forecasts of the hourly wind-based generation. The statistical methods evaluated included: (1) screening multiple linear regression, which served as a baseline method, (2) artificial neural networks, (3) a decision-tree approach called random forests, (4) gradient boosted regression based upon an decision-tree algorithm, (5) support vector regression and (6) analog ensemble

Procles the Carthaginian: A North African Sophist in Pausanias’ Periegesis

Directory of Open Access Journals (Sweden)

Juan Pablo Sánchez Hernández

2010-11-01

Full Text Available Procles, cited by Pausanias (in the imperfect tense about a display in Rome and for an opinion about Pyrrhus of Epirus, probably was not a historian of Hellenistic date, but a contemporary sophist whom Pausanias encountered in person in Rome.

Statistical Techniques For Real-time Anomaly Detection Using Spark Over Multi-source VMware Performance Data

Energy Technology Data Exchange (ETDEWEB)

Solaimani, Mohiuddin [Univ. of Texas-Dallas, Richardson, TX (United States); Iftekhar, Mohammed [Univ. of Texas-Dallas, Richardson, TX (United States); Khan, Latifur [Univ. of Texas-Dallas, Richardson, TX (United States); Thuraisingham, Bhavani [Univ. of Texas-Dallas, Richardson, TX (United States); Ingram, Joey Burton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-09-01

Anomaly detection refers to the identi cation of an irregular or unusual pat- tern which deviates from what is standard, normal, or expected. Such deviated patterns typically correspond to samples of interest and are assigned different labels in different domains, such as outliers, anomalies, exceptions, or malware. Detecting anomalies in fast, voluminous streams of data is a formidable chal- lenge. This paper presents a novel, generic, real-time distributed anomaly detection framework for heterogeneous streaming data where anomalies appear as a group. We have developed a distributed statistical approach to build a model and later use it to detect anomaly. As a case study, we investigate group anomaly de- tection for a VMware-based cloud data center, which maintains a large number of virtual machines (VMs). We have built our framework using Apache Spark to get higher throughput and lower data processing time on streaming data. We have developed a window-based statistical anomaly detection technique to detect anomalies that appear sporadically. We then relaxed this constraint with higher accuracy by implementing a cluster-based technique to detect sporadic and continuous anomalies. We conclude that our cluster-based technique out- performs other statistical techniques with higher accuracy and lower processing time.

Does underground storage still require sophisticated studies?

International Nuclear Information System (INIS)

Marsily, G. de

1997-01-01

Most countries agree to the necessity of burying high or medium-level wastes in geological layers situated at a few hundred meters below the ground level. The advantages and disadvantages of different types of rock such as salt, clay, granite and volcanic material are examined. Sophisticated studies are lead to determine the best geological confinement but questions arise about the time for which safety must be ensured. France has chosen 3 possible sites. These sites are geologically described in the article. The final place will be proposed after a testing phase of about 5 years in an underground facility. (A.C.)

Comparative evaluation of scatter correction techniques in 3D positron emission tomography

CERN Document Server

Zaidi, H

2000-01-01

Much research and development has been concentrated on the scatter compensation required for quantitative 3D PET. Increasingly sophisticated scatter correction procedures are under investigation, particularly those based on accurate scatter models, and iterative reconstruction-based scatter compensation approaches. The main difference among the correction methods is the way in which the scatter component in the selected energy window is estimated. Monte Carlo methods give further insight and might in themselves offer a possible correction procedure. Methods: Five scatter correction methods are compared in this paper where applicable. The dual-energy window (DEW) technique, the convolution-subtraction (CVS) method, two variants of the Monte Carlo-based scatter correction technique (MCBSC1 and MCBSC2) and our newly developed statistical reconstruction-based scatter correction (SRBSC) method. These scatter correction techniques are evaluated using Monte Carlo simulation studies, experimental phantom measurements...

Hierarchical probabilistic regionalization of volcanism for Sengan region in Japan using multivariate statistical techniques and geostatistical interpolation techniques

International Nuclear Information System (INIS)

Park, Jinyong; Balasingham, P.; McKenna, Sean Andrew; Kulatilake, Pinnaduwa H. S. W.

2004-01-01

Sandia National Laboratories, under contract to Nuclear Waste Management Organization of Japan (NUMO), is performing research on regional classification of given sites in Japan with respect to potential volcanic disruption using multivariate statistics and geo-statistical interpolation techniques. This report provides results obtained for hierarchical probabilistic regionalization of volcanism for the Sengan region in Japan by applying multivariate statistical techniques and geostatistical interpolation techniques on the geologic data provided by NUMO. A workshop report produced in September 2003 by Sandia National Laboratories (Arnold et al., 2003) on volcanism lists a set of most important geologic variables as well as some secondary information related to volcanism. Geologic data extracted for the Sengan region in Japan from the data provided by NUMO revealed that data are not available at the same locations for all the important geologic variables. In other words, the geologic variable vectors were found to be incomplete spatially. However, it is necessary to have complete geologic variable vectors to perform multivariate statistical analyses. As a first step towards constructing complete geologic variable vectors, the Universal Transverse Mercator (UTM) zone 54 projected coordinate system and a 1 km square regular grid system were selected. The data available for each geologic variable on a geographic coordinate system were transferred to the aforementioned grid system. Also the recorded data on volcanic activity for Sengan region were produced on the same grid system. Each geologic variable map was compared with the recorded volcanic activity map to determine the geologic variables that are most important for volcanism. In the regionalized classification procedure, this step is known as the variable selection step. The following variables were determined as most important for volcanism: geothermal gradient, groundwater temperature, heat discharge, groundwater

Finding the Fabulous Few: Why Your Program Needs Sophisticated Research.

Science.gov (United States)

Pfizenmaier, Emily

1981-01-01

Fund raising, it is argued, needs sophisticated prospect research. Professional prospect researchers play an important role in helping to identify prospective donors and also in helping to stimulate interest in gift giving. A sample of an individual work-up on a donor and a bibliography are provided. (MLW)

Reading wild minds: A computational assay of Theory of Mind sophistication across seven primate species.

Directory of Open Access Journals (Sweden)

Marie Devaine

2017-11-01

Full Text Available Theory of Mind (ToM, i.e. the ability to understand others' mental states, endows humans with highly adaptive social skills such as teaching or deceiving. Candidate evolutionary explanations have been proposed for the unique sophistication of human ToM among primates. For example, the Machiavellian intelligence hypothesis states that the increasing complexity of social networks may have induced a demand for sophisticated ToM. This type of scenario ignores neurocognitive constraints that may eventually be crucial limiting factors for ToM evolution. In contradistinction, the cognitive scaffolding hypothesis asserts that a species' opportunity to develop sophisticated ToM is mostly determined by its general cognitive capacity (on which ToM is scaffolded. However, the actual relationships between ToM sophistication and either brain volume (a proxy for general cognitive capacity or social group size (a proxy for social network complexity are unclear. Here, we let 39 individuals sampled from seven non-human primate species (lemurs, macaques, mangabeys, orangutans, gorillas and chimpanzees engage in simple dyadic games against artificial ToM players (via a familiar human caregiver. Using computational analyses of primates' choice sequences, we found that the probability of exhibiting a ToM-compatible learning style is mainly driven by species' brain volume (rather than by social group size. Moreover, primates' social cognitive sophistication culminates in a precursor form of ToM, which still falls short of human fully-developed ToM abilities.

Lexical Sophistication as a Multidimensional Phenomenon: Relations to Second Language Lexical Proficiency, Development, and Writing Quality

Science.gov (United States)

Kim, Minkyung; Crossley, Scott A.; Kyle, Kristopher

2018-01-01

This study conceptualizes lexical sophistication as a multidimensional phenomenon by reducing numerous lexical features of lexical sophistication into 12 aggregated components (i.e., dimensions) via a principal component analysis approach. These components were then used to predict second language (L2) writing proficiency levels, holistic lexical…

Few remarks on chiral theories with sophisticated topology

International Nuclear Information System (INIS)

Golo, V.L.; Perelomov, A.M.

1978-01-01

Two classes of the two-dimensional Euclidean chiral field theoreties are singled out: 1) the field phi(x) takes the values in the compact Hermitiam symmetric space 2) the field phi(x) takes the values in an orbit of the adjoint representation of the comcompact Lie group. The theories have sophisticated topological and rich analytical structures. They are considered with the help of topological invariants (topological charges). Explicit formulae for the topological charges are indicated, and the lower bound extimate for the action is given

Statistical learning and selective inference.

Science.gov (United States)

Taylor, Jonathan; Tibshirani, Robert J

2015-06-23

We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.

Machine learning and statistical techniques : an application to the prediction of insolvency in Spanish non-life insurance companies

OpenAIRE

Díaz, Zuleyka; Segovia, María Jesús; Fernández, José

2005-01-01

Prediction of insurance companies insolvency has arisen as an important problem in the field of financial research. Most methods applied in the past to tackle this issue are traditional statistical techniques which use financial ratios as explicative variables. However, these variables often do not satisfy statistical assumptions, which complicates the application of the mentioned methods. In this paper, a comparative study of the performance of two non-parametric machine learning techniques ...

Differential ethnic associations between maternal flexibility and play sophistication in toddlers born very low birth weight

Science.gov (United States)

Erickson, Sarah J.; Montague, Erica Q.; Maclean, Peggy C.; Bancroft, Mary E.; Lowe, Jean R.

2013-01-01

Children born very low birth weight (development of self-regulation and effective functional skills, and play serves as an important avenue of early intervention. The current study investigated associations between maternal flexibility and toddler play sophistication in Caucasian, Spanish speaking Hispanic, English speaking Hispanic, and Native American toddlers (18-22 months adjusted age) in a cross-sectional cohort of 73 toddlers born VLBW and their mothers. We found that the association between maternal flexibility and toddler play sophistication differed by ethnicity (F(3,65) = 3.34, p = .02). In particular, Spanish speaking Hispanic dyads evidenced a significant positive association between maternal flexibility and play sophistication of medium effect size. Results for Native Americans were parallel to those of Spanish speaking Hispanic dyads: the relationship between flexibility and play sophistication was positive and of small-medium effect size. Findings indicate that for Caucasians and English speaking Hispanics, flexibility evidenced a non-significant (negative and small effect size) association with toddler play sophistication. Significant follow-up contrasts revealed that the associations for Caucasian and English speaking Hispanic dyads were significantly different from those of the other two ethnic groups. Results remained unchanged after adjusting for the amount of maternal language, an index of maternal engagement and stimulation; and after adjusting for birth weight, gestational age, gender, test age, cognitive ability, as well maternal age, education, and income. Our results provide preliminary evidence that ethnicity and acculturation may mediate the association between maternal interactive behavior such as flexibility and toddler developmental outcomes, as indexed by play sophistication. Addressing these association differences is particularly important in children born VLBW because interventions targeting parent interaction strategies such as

Statistical uncertainty of extreme wind storms over Europe derived from a probabilistic clustering technique

Science.gov (United States)

Walz, Michael; Leckebusch, Gregor C.

2016-04-01

Extratropical wind storms pose one of the most dangerous and loss intensive natural hazards for Europe. However, due to only 50 years of high quality observational data, it is difficult to assess the statistical uncertainty of these sparse events just based on observations. Over the last decade seasonal ensemble forecasts have become indispensable in quantifying the uncertainty of weather prediction on seasonal timescales. In this study seasonal forecasts are used in a climatological context: By making use of the up to 51 ensemble members, a broad and physically consistent statistical base can be created. This base can then be used to assess the statistical uncertainty of extreme wind storm occurrence more accurately. In order to determine the statistical uncertainty of storms with different paths of progression, a probabilistic clustering approach using regression mixture models is used to objectively assign storm tracks (either based on core pressure or on extreme wind speeds) to different clusters. The advantage of this technique is that the entire lifetime of a storm is considered for the clustering algorithm. Quadratic curves are found to describe the storm tracks most accurately. Three main clusters (diagonal, horizontal or vertical progression of the storm track) can be identified, each of which have their own particulate features. Basic storm features like average velocity and duration are calculated and compared for each cluster. The main benefit of this clustering technique, however, is to evaluate if the clusters show different degrees of uncertainty, e.g. more (less) spread for tracks approaching Europe horizontally (diagonally). This statistical uncertainty is compared for different seasonal forecast products.

The CEO performance effect : Statistical issues and a complex fit perspective

NARCIS (Netherlands)

Blettner, D.P.; Chaddad, F.R.; Bettis, R.

2012-01-01

How CEOs affect strategy and performance is important to strategic management research. We show that sophisticated statistical analysis alone is problematic for establishing the magnitude and causes of CEO impact on performance. We discuss three problem areas that substantially distort the

Surveillance of arthropod vector-borne infectious diseases using remote sensing techniques: a review.

Directory of Open Access Journals (Sweden)

Satya Kalluri

2007-10-01

Full Text Available Epidemiologists are adopting new remote sensing techniques to study a variety of vector-borne diseases. Associations between satellite-derived environmental variables such as temperature, humidity, and land cover type and vector density are used to identify and characterize vector habitats. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced epidemiological data, collaboration between remote sensing scientists and biologists, and the availability of sophisticated, statistical geographic information system and image processing algorithms in a desktop environment creates a fertile research environment. The use of remote sensing techniques to map vector-borne diseases has evolved significantly over the past 25 years. In this paper, we review the status of remote sensing studies of arthropod vector-borne diseases due to mosquitoes, ticks, blackflies, tsetse flies, and sandflies, which are responsible for the majority of vector-borne diseases in the world. Examples of simple image classification techniques that associate land use and land cover types with vector habitats, as well as complex statistical models that link satellite-derived multi-temporal meteorological observations with vector biology and abundance, are discussed here. Future improvements in remote sensing applications in epidemiology are also discussed.

A survey of statistical downscaling techniques

Energy Technology Data Exchange (ETDEWEB)

Zorita, E.; Storch, H. von [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Hydrophysik

1997-12-31

The derivation of regional information from integrations of coarse-resolution General Circulation Models (GCM) is generally referred to as downscaling. The most relevant statistical downscaling techniques are described here and some particular examples are worked out in detail. They are classified into three main groups: linear methods, classification methods and deterministic non-linear methods. Their performance in a particular example, winter rainfall in the Iberian peninsula, is compared to a simple downscaling analog method. It is found that the analog method performs equally well than the more complicated methods. Downscaling analysis can be also used as a tool to validate regional performance of global climate models by analyzing the covariability of the simulated large-scale climate and the regional climates. (orig.) [Deutsch] Die Ableitung regionaler Information aus Integrationen grob aufgeloester Klimamodelle wird als `Regionalisierung` bezeichnet. Dieser Beitrag beschreibt die wichtigsten statistischen Regionalisierungsverfahren und gibt darueberhinaus einige detaillierte Beispiele. Regionalisierungsverfahren lassen sich in drei Hauptgruppen klassifizieren: lineare Verfahren, Klassifikationsverfahren und nicht-lineare deterministische Verfahren. Diese Methoden werden auf den Niederschlag auf der iberischen Halbinsel angewandt und mit den Ergebnissen eines einfachen Analog-Modells verglichen. Es wird festgestellt, dass die Ergebnisse der komplizierteren Verfahren im wesentlichen auch mit der Analog-Methode erzielt werden koennen. Eine weitere Anwendung der Regionalisierungsmethoden besteht in der Validierung globaler Klimamodelle, indem die simulierte und die beobachtete Kovariabilitaet zwischen dem grosskaligen und dem regionalen Klima miteinander verglichen wird. (orig.)

A survey of statistical downscaling techniques

Energy Technology Data Exchange (ETDEWEB)

Zorita, E; Storch, H von [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Hydrophysik

1998-12-31

The derivation of regional information from integrations of coarse-resolution General Circulation Models (GCM) is generally referred to as downscaling. The most relevant statistical downscaling techniques are described here and some particular examples are worked out in detail. They are classified into three main groups: linear methods, classification methods and deterministic non-linear methods. Their performance in a particular example, winter rainfall in the Iberian peninsula, is compared to a simple downscaling analog method. It is found that the analog method performs equally well than the more complicated methods. Downscaling analysis can be also used as a tool to validate regional performance of global climate models by analyzing the covariability of the simulated large-scale climate and the regional climates. (orig.) [Deutsch] Die Ableitung regionaler Information aus Integrationen grob aufgeloester Klimamodelle wird als `Regionalisierung` bezeichnet. Dieser Beitrag beschreibt die wichtigsten statistischen Regionalisierungsverfahren und gibt darueberhinaus einige detaillierte Beispiele. Regionalisierungsverfahren lassen sich in drei Hauptgruppen klassifizieren: lineare Verfahren, Klassifikationsverfahren und nicht-lineare deterministische Verfahren. Diese Methoden werden auf den Niederschlag auf der iberischen Halbinsel angewandt und mit den Ergebnissen eines einfachen Analog-Modells verglichen. Es wird festgestellt, dass die Ergebnisse der komplizierteren Verfahren im wesentlichen auch mit der Analog-Methode erzielt werden koennen. Eine weitere Anwendung der Regionalisierungsmethoden besteht in der Validierung globaler Klimamodelle, indem die simulierte und die beobachtete Kovariabilitaet zwischen dem grosskaligen und dem regionalen Klima miteinander verglichen wird. (orig.)

Does a more sophisticated storm erosion model improve probabilistic erosion estimates?

NARCIS (Netherlands)

Ranasinghe, R.W.M.R.J.B.; Callaghan, D.; Roelvink, D.

2013-01-01

The dependency between the accuracy/uncertainty of storm erosion exceedance estimates obtained via a probabilistic model and the level of sophistication of the structural function (storm erosion model) embedded in the probabilistic model is assessed via the application of Callaghan et al.'s (2008)

Sophisticating a naive Liapunov function

International Nuclear Information System (INIS)

Smith, D.; Lewins, J.D.

1985-01-01

The art of the direct method of Liapunov to determine system stability is to construct a suitable Liapunov or V function where V is to be positive definite (PD), to shrink to a center, which may be conveniently chosen as the origin, and where V is the negative definite (ND). One aid to the art is to solve an approximation to the system equations in order to provide a candidate V function. It can happen, however, that the V function is not strictly ND but vanishes at a finite number of isolated points. Naively, one anticipates that stability has been demonstrated since the trajectory of the system at such points is only momentarily tangential and immediately enters a region of inward directed trajectories. To demonstrate stability rigorously requires the construction of a sophisticated Liapunov function from what can be called the naive original choice. In this paper, the authors demonstrate the method of perturbing the naive function in the context of the well-known second-order oscillator and then apply the method to a more complicated problem based on a prompt jump model for a nuclear fission reactor

Strategic sophistication of individuals and teams. Experimental evidence

Science.gov (United States)

Sutter, Matthias; Czermak, Simon; Feri, Francesco

2013-01-01

Many important decisions require strategic sophistication. We examine experimentally whether teams act more strategically than individuals. We let individuals and teams make choices in simple games, and also elicit first- and second-order beliefs. We find that teams play the Nash equilibrium strategy significantly more often, and their choices are more often a best response to stated first order beliefs. Distributional preferences make equilibrium play less likely. Using a mixture model, the estimated probability to play strategically is 62% for teams, but only 40% for individuals. A model of noisy introspection reveals that teams differ from individuals in higher order beliefs. PMID:24926100

Leak detection and localization in a pipeline system by application of statistical analysis techniques

International Nuclear Information System (INIS)

Fukuda, Toshio; Mitsuoka, Toyokazu.

1985-01-01

The detection of leak in piping system is an important diagnostic technique for facilities to prevent accidents and to take maintenance measures, since the occurrence of leak lowers productivity and causes environmental destruction. As the first step, it is necessary to detect the occurrence of leak without delay, and as the second step, if the place of leak occurrence in piping system can be presumed, accident countermeasures become easy. The detection of leak by pressure is usually used for detecting large leak. But the method depending on pressure is simple and advantageous, therefore the extension of the detecting technique by pressure gradient method to the detection of smaller scale leak using statistical analysis techniques was examined for a pipeline in steady operation in this study. Since the flow in a pipe irregularly varies during pumping, statistical means is required for the detection of small leak by pressure. The index for detecting leak proposed in this paper is the difference of the pressure gradient at the both ends of a pipeline. The experimental results on water and air in nylon tubes are reported. (Kako, I.)

TRAN-STAT: statistics for environmental studies, Number 22. Comparison of soil-sampling techniques for plutonium at Rocky Flats

International Nuclear Information System (INIS)

Gilbert, R.O.; Bernhardt, D.E.; Hahn, P.B.

1983-01-01

A summary of a field soil sampling study conducted around the Rocky Flats Colorado plant in May 1977 is preseted. Several different soil sampling techniques that had been used in the area were applied at four different sites. One objective was to comparethe average 239 - 240 Pu concentration values obtained by the various soil sampling techniques used. There was also interest in determining whether there are differences in the reproducibility of the various techniques and how the techniques compared with the proposed EPA technique of sampling to 1 cm depth. Statistically significant differences in average concentrations between the techniques were found. The differences could be largely related to the differences in sampling depth-the primary physical variable between the techniques. The reproducibility of the techniques was evaluated by comparing coefficients of variation. Differences between coefficients of variation were not statistically significant. Average (median) coefficients ranged from 21 to 42 percent for the five sampling techniques. A laboratory study indicated that various sample treatment and particle sizing techniques could increase the concentration of plutonium in the less than 10 micrometer size fraction by up to a factor of about 4 compared to the 2 mm size fraction

A Comparison of Several Statistical Tests of Reciprocity of Self-Disclosure.

Science.gov (United States)

Dindia, Kathryn

1988-01-01

Reports the results of a study that used several statistical tests of reciprocity of self-disclosure. Finds little evidence for reciprocity of self-disclosure, and concludes that either reciprocity is an illusion, or that different or more sophisticated methods are needed to detect it. (MS)

Development Strategies for Tourism Destinations: Tourism Sophistication vs. Resource Investments

OpenAIRE

Rainer Andergassen; Guido Candela

2010-01-01

This paper investigates the effectiveness of development strategies for tourism destinations. We argue that resource investments unambiguously increase tourism revenues and that increasing the degree of tourism sophistication, that is increasing the variety of tourism related goods and services, increases tourism activity and decreases the perceived quality of the destination's resource endowment, leading to an ambiguous effect on tourism revenues. We disentangle these two effects and charact...

Mathematical and Statistical Techniques for Systems Medicine: The Wnt Signaling Pathway as a Case Study

KAUST Repository

MacLean, Adam L.; Harrington, Heather A.; Stumpf, Michael P. H.; Byrne, Helen M.

2015-01-01

mathematical and statistical techniques that enable modelers to gain insight into (models of) gene regulation and generate testable predictions. We introduce a range of modeling frameworks, but focus on ordinary differential equation (ODE) models since

Data on electrical energy conservation using high efficiency motors for the confidence bounds using statistical techniques.

Science.gov (United States)

Shaikh, Muhammad Mujtaba; Memon, Abdul Jabbar; Hussain, Manzoor

2016-09-01

In this article, we describe details of the data used in the research paper "Confidence bounds for energy conservation in electric motors: An economical solution using statistical techniques" [1]. The data presented in this paper is intended to show benefits of high efficiency electric motors over the standard efficiency motors of similar rating in the industrial sector of Pakistan. We explain how the data was collected and then processed by means of formulas to show cost effectiveness of energy efficient motors in terms of three important parameters: annual energy saving, cost saving and payback periods. This data can be further used to construct confidence bounds for the parameters using statistical techniques as described in [1].

Do organizations adopt sophisticated capital budgeting practices to deal with uncertainty in the investment decision? : A research note

NARCIS (Netherlands)

Verbeeten, Frank H M

This study examines the impact of uncertainty on the sophistication of capital budgeting practices. While the theoretical applications of sophisticated capital budgeting practices (defined as the use of real option reasoning and/or game theory decision rules) have been well documented, empirical

Systematization and sophistication of a comprehensive sensitivity analysis program. Phase 2

International Nuclear Information System (INIS)

Oyamada, Kiyoshi; Ikeda, Takao

2004-02-01

This study developed minute estimation by adopting comprehensive sensitivity analytical program for reliability of TRU waste repository concepts in a crystalline rock condition. We examined each components and groundwater scenario of geological repository and prepared systematic bases to examine the reliability from the point of comprehensiveness. Models and data are sophisticated to examine the reliability. Based on an existing TRU waste repository concepts, effects of parameters to nuclide migration were quantitatively classified. Those parameters, that will be decided quantitatively, are such as site character of natural barrier and design specification of engineered barriers. Considering the feasibility of those figures of specifications, reliability is re-examined on combinations of those parameters within a practical range. Future issues are; Comprehensive representation of hybrid geosphere model including the fractured medium and permeable matrix medium. Sophistication of tools to develop the reliable combinations of parameters. It is significant to continue this study because the disposal concepts and specification of TRU nuclides containing waste on various sites shall be determined rationally and safely through these studies. (author)

Statistical assessment of the learning curves of health technologies.

Science.gov (United States)

Ramsay, C R; Grant, A M; Wallace, S A; Garthwaite, P H; Monk, A F; Russell, I T

2001-01-01

in health technology assessment have been crude and the reporting of studies poor. CONCLUSIONS - NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH: A number of statistical methods for assessing learning effects were identified that had not hitherto been used in health technology assessment. There was a hierarchy of methods for the identification and measurement of learning, and the more sophisticated methods for both have had little if any use in health technology assessment. This demonstrated the value of considering fields outside clinical research when addressing methodological issues in health technology assessment. CONCLUSIONS - TESTING OF STATISTICAL METHODS: It has been demonstrated that the portfolio of techniques identified can enhance investigations of learning curve effects. (ABSTRACT TRUNCATED)

Studies on coal flotation in flotation column using statistical technique

Energy Technology Data Exchange (ETDEWEB)

M.S. Jena; S.K. Biswal; K.K. Rao; P.S.R. Reddy [Institute of Minerals & Materials Technology (IMMT), Orissa (India)

2009-07-01

Flotation of Indian high ash coking coal fines to obtain clean coal has been reported earlier by many authors. Here an attempt has been made to systematically analyse factors influencing the flotation process using statistical design of experiments technique. Studies carried out in a 100 mm diameter column using factorial design to establish weightage of factors such as feed rate, air rate and collector dosage indicated that all three parameters have equal influence on the flotation process. Subsequently RSM-CCD design was used to obtain best result and it is observed that 94% combustibles can be recovered with 82.5% weight recovery at 21.4% ash from a feed containing 31.3% ash content.

Sophistic Ethics in the Technical Writing Classroom: Teaching "Nomos," Deliberation, and Action.

Science.gov (United States)

Scott, J. Blake

1995-01-01

Claims that teaching ethics is particularly important to technical writing. Outlines a classical, sophistic approach to ethics based on the theories and pedagogies of Protagoras, Gorgias, and Isocrates, which emphasizes the Greek concept of "nomos," internal and external deliberation, and responsible action. Discusses problems and…

An Analysis of Research Methods and Statistical Techniques Used by Doctoral Dissertation at the Education Sciences in Turkey

Science.gov (United States)

Karadag, Engin

2010-01-01

To assess research methods and analysis of statistical techniques employed by educational researchers, this study surveyed unpublished doctoral dissertation from 2003 to 2007. Frequently used research methods consisted of experimental research; a survey; a correlational study; and a case study. Descriptive statistics, t-test, ANOVA, factor…

Statistical techniques applied to aerial radiometric surveys (STAARS): series introduction and the principal-components-analysis method

International Nuclear Information System (INIS)

Pirkle, F.L.

1981-04-01

STAARS is a new series which is being published to disseminate information concerning statistical procedures for interpreting aerial radiometric data. The application of a particular data interpretation technique to geologic understanding for delineating regions favorable to uranium deposition is the primary concern of STAARS. Statements concerning the utility of a technique on aerial reconnaissance data as well as detailed aerial survey data will be included

Sophisticated Fowl: The Complex Behaviour and Cognitive Skills of Chickens and Red Junglefowl

Directory of Open Access Journals (Sweden)

Laura Garnham

2018-01-01

Full Text Available The world’s most numerous bird, the domestic chicken, and their wild ancestor, the red junglefowl, have long been used as model species for animal behaviour research. Recently, this research has advanced our understanding of the social behaviour, personality, and cognition of fowl, and demonstrated their sophisticated behaviour and cognitive skills. Here, we overview some of this research, starting with describing research investigating the well-developed senses of fowl, before presenting how socially and cognitively complex they can be. The realisation that domestic chickens, our most abundant production animal, are behaviourally and cognitively sophisticated should encourage an increase in general appraise and fascination towards them. In turn, this should inspire increased use of them as both research and hobby animals, as well as improvements in their unfortunately often poor welfare.

Assessing Epistemic Sophistication by Considering Domain-Specific Absolute and Multiplicistic Beliefs Separately

Science.gov (United States)

Peter, Johannes; Rosman, Tom; Mayer, Anne-Kathrin; Leichner, Nikolas; Krampen, Günter

2016-01-01

Background: Particularly in higher education, not only a view of science as a means of finding absolute truths (absolutism), but also a view of science as generally tentative (multiplicism) can be unsophisticated and obstructive for learning. Most quantitative epistemic belief inventories neglect this and understand epistemic sophistication as…

A Review of Statistical Techniques for 2x2 and RxC Categorical Data Tables In SPSS

Directory of Open Access Journals (Sweden)

Cengiz BAL

2009-11-01

Full Text Available In this study, a review of statistical techniques for RxC categorical data tables is explained in detail. The emphasis is given to the association of techniques and their corresponding data considerations. Some suggestions to how to handle specific categorical data tables in SPSS and common mistakes in the interpretation of the SPSS outputs are shown.

Statistical mechanical analysis of LMFBR fuel cladding tubes

International Nuclear Information System (INIS)

Poncelet, J.-P.; Pay, A.

1977-01-01

The most important design requirement on fuel pin cladding for LMFBR's is its mechanical integrity. Disruptive factors include internal pressure from mixed oxide fuel fission gas release, thermal stresses and high temperature creep, neutron-induced differential void-swelling as a source of stress in the cladding and irradiation creep of stainless steel material, corrosion by fission products. Under irradiation these load-restraining mechanisms are accentuated by stainless steel embrittlement and strength alterations. To account for the numerous uncertainties involved in the analysis by theoretical models and computer codes statistical tools are unavoidably requested, i.e. Monte Carlo simulation methods. Thanks to these techniques, uncertainties in nominal characteristics, material properties and environmental conditions can be linked up in a correct way and used for a more accurate conceptual design. First, a thermal creep damage index is set up through a sufficiently sophisticated clad physical analysis including arbitrary time dependence of power and neutron flux as well as effects of sodium temperature, burnup and steel mechanical behavior. Although this strain limit approach implies a more general but time consuming model., on the counterpart the net output is improved and e.g. clad temperature, stress and strain maxima may be easily assessed. A full spectrum of variables are statistically treated to account for their probability distributions. Creep damage probability may be obtained and can contribute to a quantitative fuel probability estimation

Statistical Pattern Recognition

CERN Document Server

Webb, Andrew R

2011-01-01

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.  It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,

The State of Nursing Home Information Technology Sophistication in Rural and Nonrural US Markets.

Science.gov (United States)

Alexander, Gregory L; Madsen, Richard W; Miller, Erin L; Wakefield, Douglas S; Wise, Keely K; Alexander, Rachel L

2017-06-01

To test for significant differences in information technology sophistication (ITS) in US nursing homes (NH) based on location. We administered a primary survey January 2014 to July 2015 to NH in each US state. The survey was cross-sectional and examined 3 dimensions (IT capabilities, extent of IT use, degree of IT integration) among 3 domains (resident care, clinical support, administrative activities) of ITS. ITS was broken down by NH location. Mean responses were compared across 4 NH categories (Metropolitan, Micropolitan, Small Town, and Rural) for all 9 ITS dimensions and domains. Least square means and Tukey's method were used for multiple comparisons. Methods yielded 815/1,799 surveys (45% response rate). In every health care domain (resident care, clinical support, and administrative activities) statistical differences in facility ITS occurred in larger (metropolitan or micropolitan) and smaller (small town or rural) populated areas. This study represents the most current national assessment of NH IT since 2004. Historically, NH IT has been used solely for administrative activities and much less for resident care and clinical support. However, results are encouraging as ITS in other domains appears to be greater than previously imagined. © 2016 National Rural Health Association.

A review on diagnostic techniques for brucellosis | Kaltungo | African ...

African Journals Online (AJOL)

... but has not been validated for standard laboratory use. This paper highlights useful samples and, especially the different conventional to more sophisticated molecular techniques for the diagnosis of brucellosis. Keywords: Brucellosis, diagnosis, techniques. African Journal of Biotechnology, Vol. 13(1), pp. 1-10, 1 January, ...

Using statistical sensitivities for adaptation of a best-estimate thermo-hydraulic simulation model

International Nuclear Information System (INIS)

Liu, X.J.; Kerner, A.; Schaefer, A.

2010-01-01

On-line adaptation of best-estimate simulations of NPP behaviour to time-dependent measurement data can be used to insure that simulations performed in parallel to plant operation develop synchronously with the real plant behaviour even over extended periods of time. This opens a range of applications including operator support in non-standard-situations, improving diagnostics and validation of measurements in real plants or experimental facilities. A number of adaptation methods have been proposed and successfully applied to control problems. However, these methods are difficult to be applied to best-estimate thermal-hydraulic codes, such as TRACE and ATHLET, with their large nonlinear differential equation systems and sophisticated time integration techniques. This paper presents techniques to use statistical sensitivity measures to overcome those problems by reducing the number of parameters subject to adaptation. It describes how to identify the most significant parameters for adaptation and how this information can be used by combining: -decomposition techniques splitting the system into a small set of component parts with clearly defined interfaces where boundary conditions can be derived from the measurement data, -filtering techniques to insure that the time frame for adaptation is meaningful, -numerical sensitivities to find minimal error conditions. The suitability of combining those techniques is shown by application to an adaptive simulation of the PKL experiment.

Statistical Techniques Used in Three Applied Linguistics Journals: "Language Learning,""Applied Linguistics" and "TESOL Quarterly," 1980-1986: Implications for Readers and Researchers.

Science.gov (United States)

Teleni, Vicki; Baldauf, Richard B., Jr.

A study investigated the statistical techniques used by applied linguists and reported in three journals, "Language Learning,""Applied Linguistics," and "TESOL Quarterly," between 1980 and 1986. It was found that 47% of the published articles used statistical procedures. In these articles, 63% of the techniques used could be called basic, 28%…

Preparing systems engineering and computing science students in disciplined methods, quantitative, and advanced statistical techniques to improve process performance

Science.gov (United States)

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

GIS-based bivariate statistical techniques for groundwater potential analysis (an example of Iran)

Science.gov (United States)

Haghizadeh, Ali; Moghaddam, Davoud Davoudi; Pourghasemi, Hamid Reza

2017-12-01

Groundwater potential analysis prepares better comprehension of hydrological settings of different regions. This study shows the potency of two GIS-based data driven bivariate techniques namely statistical index (SI) and Dempster-Shafer theory (DST) to analyze groundwater potential in Broujerd region of Iran. The research was done using 11 groundwater conditioning factors and 496 spring positions. Based on the ground water potential maps (GPMs) of SI and DST methods, 24.22% and 23.74% of the study area is covered by poor zone of groundwater potential, and 43.93% and 36.3% of Broujerd region is covered by good and very good potential zones, respectively. The validation of outcomes displayed that area under the curve (AUC) of SI and DST techniques are 81.23% and 79.41%, respectively, which shows SI method has slightly a better performance than the DST technique. Therefore, SI and DST methods are advantageous to analyze groundwater capacity and scrutinize the complicated relation between groundwater occurrence and groundwater conditioning factors, which permits investigation of both systemic and stochastic uncertainty. Finally, it can be realized that these techniques are very beneficial for groundwater potential analyzing and can be practical for water-resource management experts.

Musical Sophistication and the Effect of Complexity on Auditory Discrimination in Finnish Speakers

Science.gov (United States)

Dawson, Caitlin; Aalto, Daniel; Šimko, Juraj; Vainio, Martti; Tervaniemi, Mari

2017-01-01

Musical experiences and native language are both known to affect auditory processing. The present work aims to disentangle the influences of native language phonology and musicality on behavioral and subcortical sound feature processing in a population of musically diverse Finnish speakers as well as to investigate the specificity of enhancement from musical training. Finnish speakers are highly sensitive to duration cues since in Finnish, vowel and consonant duration determine word meaning. Using a correlational approach with a set of behavioral sound feature discrimination tasks, brainstem recordings, and a musical sophistication questionnaire, we find no evidence for an association between musical sophistication and more precise duration processing in Finnish speakers either in the auditory brainstem response or in behavioral tasks, but they do show an enhanced pitch discrimination compared to Finnish speakers with less musical experience and show greater duration modulation in a complex task. These results are consistent with a ceiling effect set for certain sound features which corresponds to the phonology of the native language, leaving an opportunity for music experience-based enhancement of sound features not explicitly encoded in the language (such as pitch, which is not explicitly encoded in Finnish). Finally, the pattern of duration modulation in more musically sophisticated Finnish speakers suggests integrated feature processing for greater efficiency in a real world musical situation. These results have implications for research into the specificity of plasticity in the auditory system as well as to the effects of interaction of specific language features with musical experiences. PMID:28450829

Musical Sophistication and the Effect of Complexity on Auditory Discrimination in Finnish Speakers.

Science.gov (United States)

Dawson, Caitlin; Aalto, Daniel; Šimko, Juraj; Vainio, Martti; Tervaniemi, Mari

2017-01-01

Musical experiences and native language are both known to affect auditory processing. The present work aims to disentangle the influences of native language phonology and musicality on behavioral and subcortical sound feature processing in a population of musically diverse Finnish speakers as well as to investigate the specificity of enhancement from musical training. Finnish speakers are highly sensitive to duration cues since in Finnish, vowel and consonant duration determine word meaning. Using a correlational approach with a set of behavioral sound feature discrimination tasks, brainstem recordings, and a musical sophistication questionnaire, we find no evidence for an association between musical sophistication and more precise duration processing in Finnish speakers either in the auditory brainstem response or in behavioral tasks, but they do show an enhanced pitch discrimination compared to Finnish speakers with less musical experience and show greater duration modulation in a complex task. These results are consistent with a ceiling effect set for certain sound features which corresponds to the phonology of the native language, leaving an opportunity for music experience-based enhancement of sound features not explicitly encoded in the language (such as pitch, which is not explicitly encoded in Finnish). Finally, the pattern of duration modulation in more musically sophisticated Finnish speakers suggests integrated feature processing for greater efficiency in a real world musical situation. These results have implications for research into the specificity of plasticity in the auditory system as well as to the effects of interaction of specific language features with musical experiences.

Sophisticated Calculation of the 1oo4-architecture for Safety-related Systems Conforming to IEC61508

International Nuclear Information System (INIS)

Hayek, A; Al Bokhaiti, M; Schwarz, M H; Boercsoek, J

2012-01-01

With the publication and enforcement of the standard IEC 61508 of safety related systems, recent system architectures have been presented and evaluated. Among a number of techniques and measures to the evaluation of safety integrity level (SIL) for safety-related systems, several measures such as reliability block diagrams and Markov models are used to analyze the probability of failure on demand (PFD) and mean time to failure (MTTF) which conform to IEC 61508. The current paper deals with the quantitative analysis of the novel 1oo4-architecture (one out of four) presented in recent work. Therefore sophisticated calculations for the required parameters are introduced. The provided 1oo4-architecture represents an advanced safety architecture based on on-chip redundancy, which is 3-failure safe. This means that at least one of the four channels have to work correctly in order to trigger the safety function.

Connection between perturbation theory, projection-operator techniques, and statistical linearization for nonlinear systems

International Nuclear Information System (INIS)

Budgor, A.B.; West, B.J.

1978-01-01

We employ the equivalence between Zwanzig's projection-operator formalism and perturbation theory to demonstrate that the approximate-solution technique of statistical linearization for nonlinear stochastic differential equations corresponds to the lowest-order β truncation in both the consolidated perturbation expansions and in the ''mass operator'' of a renormalized Green's function equation. Other consolidated equations can be obtained by selectively modifying this mass operator. We particularize the results of this paper to the Duffing anharmonic oscillator equation

Industrial statistics with Minitab

CERN Document Server

Cintas, Pere Grima; Llabres, Xavier Tort-Martorell

2012-01-01

Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context. This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented. Industrial Statistics with MINITAB: Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry.Explores

ISOLATED SPEECH RECOGNITION SYSTEM FOR TAMIL LANGUAGE USING STATISTICAL PATTERN MATCHING AND MACHINE LEARNING TECHNIQUES

Directory of Open Access Journals (Sweden)

VIMALA C.

2015-05-01

Full Text Available In recent years, speech technology has become a vital part of our daily lives. Various techniques have been proposed for developing Automatic Speech Recognition (ASR system and have achieved great success in many applications. Among them, Template Matching techniques like Dynamic Time Warping (DTW, Statistical Pattern Matching techniques such as Hidden Markov Model (HMM and Gaussian Mixture Models (GMM, Machine Learning techniques such as Neural Networks (NN, Support Vector Machine (SVM, and Decision Trees (DT are most popular. The main objective of this paper is to design and develop a speaker-independent isolated speech recognition system for Tamil language using the above speech recognition techniques. The background of ASR system, the steps involved in ASR, merits and demerits of the conventional and machine learning algorithms and the observations made based on the experiments are presented in this paper. For the above developed system, highest word recognition accuracy is achieved with HMM technique. It offered 100% accuracy during training process and 97.92% for testing process.

Reacting to Neighborhood Cues?: Political Sophistication Moderates the Effect of Exposure to Immigrants

DEFF Research Database (Denmark)

Danckert, Bolette; Dinesen, Peter Thisted; Sønderskov, Kim Mannemar

2017-01-01

is founded on politically sophisticated individuals having a greater comprehension of news and other mass-mediated sources, which makes them less likely to rely on neighborhood cues as sources of information relevant for political attitudes. Based on a unique panel data set with fine-grained information...

Mathematical and Statistical Techniques for Systems Medicine: The Wnt Signaling Pathway as a Case Study

KAUST Repository

MacLean, Adam L.

2015-12-16

The last decade has seen an explosion in models that describe phenomena in systems medicine. Such models are especially useful for studying signaling pathways, such as the Wnt pathway. In this chapter we use the Wnt pathway to showcase current mathematical and statistical techniques that enable modelers to gain insight into (models of) gene regulation and generate testable predictions. We introduce a range of modeling frameworks, but focus on ordinary differential equation (ODE) models since they remain the most widely used approach in systems biology and medicine and continue to offer great potential. We present methods for the analysis of a single model, comprising applications of standard dynamical systems approaches such as nondimensionalization, steady state, asymptotic and sensitivity analysis, and more recent statistical and algebraic approaches to compare models with data. We present parameter estimation and model comparison techniques, focusing on Bayesian analysis and coplanarity via algebraic geometry. Our intention is that this (non-exhaustive) review may serve as a useful starting point for the analysis of models in systems medicine.

Potential of modern sonographic techniques in paediatric uroradiology

Energy Technology Data Exchange (ETDEWEB)

Riccabona, Michael E-mail: michael.riccabona@kfunigraz.ac.at

2002-08-01

Objective: To describe the potential of modern sonographic techniques in paediatric uroradiology. Method: Ultrasound (US)--now being the primary imaging tool--has revolutionised imaging diagnostic in the urinary tract. Constant developments and technical refinements have secured the role of US in uroradiology. Colour Doppler Sonography (CDS) and innovative applications such as the transperineal approach or application of m-mode US to the urinary tract have helped to develop US from just a basic tool to a sophisticated and respected method. The ongoing introduction of new and even more sophisticated methods further enhance the sonographic potential, which shall be demonstrated by a more detailed discussion of these methods. Results: Harmonic imaging, extended field of view US, amplitude coded CDS, echo-enhanced US, and three-dimensional US as the most recent new sonographic techniques are successfully applicable to paediatric urinary tract disease. They improve sonographic diagnosis in many conditions, such as detection of vesico-ureteral reflux, renal parenchymal volume assessment, comprehensive visualisation of hydronephrosis and complex pathology, evaluation of renal perfusional disturbances or defects, superior documentation with improved comparability for follow-up, or simply by offering clearer tissue delineation and differentiation. Conclusion: Modern US techniques are successfully applicable to neonates, infants, and children, further boosting the value of US in the paediatric urinary tract. However, as handling became more sophisticated, and artefacts have to be considered, modern urosonography became not only a more powerful, but also a more demanding method, with the need for expert knowledge and dedicated training.

Potential of modern sonographic techniques in paediatric uroradiology

International Nuclear Information System (INIS)

Riccabona, Michael

2002-01-01

Objective: To describe the potential of modern sonographic techniques in paediatric uroradiology. Method: Ultrasound (US)--now being the primary imaging tool--has revolutionised imaging diagnostic in the urinary tract. Constant developments and technical refinements have secured the role of US in uroradiology. Colour Doppler Sonography (CDS) and innovative applications such as the transperineal approach or application of m-mode US to the urinary tract have helped to develop US from just a basic tool to a sophisticated and respected method. The ongoing introduction of new and even more sophisticated methods further enhance the sonographic potential, which shall be demonstrated by a more detailed discussion of these methods. Results: Harmonic imaging, extended field of view US, amplitude coded CDS, echo-enhanced US, and three-dimensional US as the most recent new sonographic techniques are successfully applicable to paediatric urinary tract disease. They improve sonographic diagnosis in many conditions, such as detection of vesico-ureteral reflux, renal parenchymal volume assessment, comprehensive visualisation of hydronephrosis and complex pathology, evaluation of renal perfusional disturbances or defects, superior documentation with improved comparability for follow-up, or simply by offering clearer tissue delineation and differentiation. Conclusion: Modern US techniques are successfully applicable to neonates, infants, and children, further boosting the value of US in the paediatric urinary tract. However, as handling became more sophisticated, and artefacts have to be considered, modern urosonography became not only a more powerful, but also a more demanding method, with the need for expert knowledge and dedicated training

Financial Sophistication and the Distribution of the Welfare Cost of Inflation

OpenAIRE

Paola Boel; Gabriele Camera

2009-01-01

The welfare cost of anticipated inflation is quantified in a calibrated model of the U.S. economy that exhibits tractable equilibrium dispersion in wealth and earnings. Inflation does not generate large losses in societal welfare, yet its impact varies noticeably across segments of society depending also on the financial sophistication of the economy. If money is the only asset, then inflation hurts mostly the wealthier and more productive agents, while those poorer and less productive may ev...

Statistical and particle physics: Common problems and techniques

International Nuclear Information System (INIS)

Bowler, K.C.; Mc Kane, A.J.

1984-01-01

These proceedings contain statistical mechanical studies in condensed matter physics; interfacial problems in statistical physics; string theory; general monte carlo methods and their application to Lattice gauge theories; topological excitations in field theory; phase transformation kinetics; and studies of chaotic systems

Application of multivariate statistical techniques for differentiation of ripe banana flour based on the composition of elements.

Science.gov (United States)

Alkarkhi, Abbas F M; Ramli, Saifullah Bin; Easa, Azhar Mat

2009-01-01

Major (sodium, potassium, calcium, magnesium) and minor elements (iron, copper, zinc, manganese) and one heavy metal (lead) of Cavendish banana flour and Dream banana flour were determined, and data were analyzed using multivariate statistical techniques of factor analysis and discriminant analysis. Factor analysis yielded four factors explaining more than 81% of the total variance: the first factor explained 28.73%, comprising magnesium, sodium, and iron; the second factor explained 21.47%, comprising only manganese and copper; the third factor explained 15.66%, comprising zinc and lead; while the fourth factor explained 15.50%, comprising potassium. Discriminant analysis showed that magnesium and sodium exhibited a strong contribution in discriminating the two types of banana flour, affording 100% correct assignation. This study presents the usefulness of multivariate statistical techniques for analysis and interpretation of complex mineral content data from banana flour of different varieties.

Statistical zonation technique and its application to the San Andres reservoir in the Poza Rica area, Vera Cruz, Mexico

Energy Technology Data Exchange (ETDEWEB)

Campa, M F; Romero, M R

1969-01-01

A statistical zonation technique developed by J.D. Testerman is presented referring to its application to the San Andres reservoir in the Poza Rica area in Veracruz, Mex. The method is based on a statistical technique which permits grouping of similar values of certain parameter, i.e., porosity, for individual wells within a field. The resulting groups or zones are used in a correlation analysis to deduce whether there is continuity of porosity in any direction. In the San Andres reservoir, there is a continuity of the porous media on NE-SW direction. This is an important fact for the waterflooding project being carried on.

Statistics and error considerations at the application of SSND T-technique in radon measurement

International Nuclear Information System (INIS)

Jonsson, G.

1993-01-01

Plastic films are used for the detection of alpha particles from disintegrating radon and radon daughter nuclei. After etching there are tracks (cones) or holes in the film as a result of the exposure. The step from a counted number of tracks/holes per surface unit of the film to a reliable value of the radon and radon daughter level is surrounded by statistical considerations of different nature. Some of them are the number of counted tracks, the length of the time of exposure, the season of the time of exposure, the etching technique and the method of counting the tracks or holes. The number of background tracks of an unexposed film increases the error of the measured radon level. Some of the mentioned effects of statistical nature will be discussed in the report. (Author)

Vibration impact acoustic emission technique for identification and analysis of defects in carbon steel tubes: Part A Statistical analysis

Energy Technology Data Exchange (ETDEWEB)

Halim, Zakiah Abd [Universiti Teknikal Malaysia Melaka (Malaysia); Jamaludin, Nordin; Junaidi, Syarif [Faculty of Engineering and Built, Universiti Kebangsaan Malaysia, Bangi (Malaysia); Yahya, Syed Yusainee Syed [Universiti Teknologi MARA, Shah Alam (Malaysia)

2015-04-15

Current steel tubes inspection techniques are invasive, and the interpretation and evaluation of inspection results are manually done by skilled personnel. This paper presents a statistical analysis of high frequency stress wave signals captured from a newly developed noninvasive, non-destructive tube inspection technique known as the vibration impact acoustic emission (VIAE) technique. Acoustic emission (AE) signals have been introduced into the ASTM A179 seamless steel tubes using an impact hammer, and the AE wave propagation was captured using an AE sensor. Specifically, a healthy steel tube as the reference tube and four steel tubes with through-hole artificial defect at different locations were used in this study. The AE features extracted from the captured signals are rise time, peak amplitude, duration and count. The VIAE technique also analysed the AE signals using statistical features such as root mean square (r.m.s.), energy, and crest factor. It was evident that duration, count, r.m.s., energy and crest factor could be used to automatically identify the presence of defect in carbon steel tubes using AE signals captured using the non-invasive VIAE technique.

Putin’s Russia: Russian Mentality and Sophisticated Imperialism in Military Policies

OpenAIRE

Szénási, Lieutenant-Colonel Endre

2016-01-01

According to my experiences, the Western world hopelessly fails to understand Russian mentality, or misinterprets it. During my analysis of the Russian way of thinking I devoted special attention to the examination of military mentality. I have connected the issue of the Russian way of thinking to the contemporary imperial policies of Putin’s Russia.  I have also attempted to prove the level of sophistication of both. I hope that a better understanding of both the Russian mentality and imperi...

Generic Techniques for the Calibration of Robots with Application of the 3-D Fixtures and Statistical Technique on the PUMA 500 and ARID Robots

Science.gov (United States)

Tawfik, Hazem

1991-01-01

A relatively simple, inexpensive, and generic technique that could be used in both laboratories and some operation site environments is introduced at the Robotics Applications and Development Laboratory (RADL) at Kennedy Space Center (KSC). In addition, this report gives a detailed explanation of the set up procedure, data collection, and analysis using this new technique that was developed at the State University of New York at Farmingdale. The technique was used to evaluate the repeatability, accuracy, and overshoot of the Unimate Industrial Robot, PUMA 500. The data were statistically analyzed to provide an insight into the performance of the systems and components of the robot. Also, the same technique was used to check the forward kinematics against the inverse kinematics of RADL's PUMA robot. Recommendations were made for RADL to use this technique for laboratory calibration of the currently existing robots such as the ASEA, high speed controller, Automated Radiator Inspection Device (ARID) etc. Also, recommendations were made to develop and establish other calibration techniques that will be more suitable for site calibration environment and robot certification.

The relation between maturity and sophistication shall be properly dealt with in nuclear power development

International Nuclear Information System (INIS)

Li Yongjiang

2009-01-01

The paper analyses the advantages and disadvantages of the second generation improved technologies and third generation technologies mainly developed in China in terms of safety and economy. The paper also discusses the maturity of the second generation improved technologies and the sophistication of the third generation technologies respectively. Meanwhile, the paper proposes that the advantage and disadvantage of second generation improved technologies and third generation technologies should be carefully taken into consideration and the relationship between the maturity and sophistication should be properly dealt with in the current stage. A two-step strategy shall be taken as a solution to solve the problem of insufficient capacity of nuclear power, trace and develop the third generation technologies, so as to ensure the sound and fast development of nuclear power. (authors)

Mathematical statistics

CERN Document Server

Pestman, Wiebe R

2009-01-01

This textbook provides a broad and solid introduction to mathematical statistics, including the classical subjects hypothesis testing, normal regression analysis, and normal analysis of variance. In addition, non-parametric statistics and vectorial statistics are considered, as well as applications of stochastic analysis in modern statistics, e.g., Kolmogorov-Smirnov testing, smoothing techniques, robustness and density estimation. For students with some elementary mathematical background. With many exercises. Prerequisites from measure theory and linear algebra are presented.

Statistical learning techniques applied to epidemiology: a simulated case-control comparison study with logistic regression

Directory of Open Access Journals (Sweden)

Land Walker H

2011-01-01

Full Text Available Abstract Background When investigating covariate interactions and group associations with standard regression analyses, the relationship between the response variable and exposure may be difficult to characterize. When the relationship is nonlinear, linear modeling techniques do not capture the nonlinear information content. Statistical learning (SL techniques with kernels are capable of addressing nonlinear problems without making parametric assumptions. However, these techniques do not produce findings relevant for epidemiologic interpretations. A simulated case-control study was used to contrast the information embedding characteristics and separation boundaries produced by a specific SL technique with logistic regression (LR modeling representing a parametric approach. The SL technique was comprised of a kernel mapping in combination with a perceptron neural network. Because the LR model has an important epidemiologic interpretation, the SL method was modified to produce the analogous interpretation and generate odds ratios for comparison. Results The SL approach is capable of generating odds ratios for main effects and risk factor interactions that better capture nonlinear relationships between exposure variables and outcome in comparison with LR. Conclusions The integration of SL methods in epidemiology may improve both the understanding and interpretation of complex exposure/disease relationships.

Testing of statistical techniques used in SYVAC

International Nuclear Information System (INIS)

Dalrymple, G.; Edwards, H.; Prust, J.

1984-01-01

Analysis of the SYVAC (SYstems Variability Analysis Code) output adopted four techniques to provide a cross comparison of their performance. The techniques used were: examination of scatter plots; correlation/regression; Kruskal-Wallis one-way analysis of variance by ranks; comparison of cumulative distribution functions and risk estimates between sub-ranges of parameter values. The analysis was conducted for the case of a single nuclide chain and was based mainly on simulated dose after 500,000 years. The results from this single SYVAC case showed that site parameters had the greatest influence on dose to man. The techniques of correlation/regression and Kruskal-Wallis were both successful and consistent in their identification of important parameters. Both techniques ranked the eight most important parameters in the same order when analysed for maximum dose. The results from a comparison of cdfs and risks in sub-ranges of the parameter values were not entirely consistent with other techniques. Further sampling of the high dose region is recommended in order to improve the accuracy of this method. (author)

A Statistical Primer: Understanding Descriptive and Inferential Statistics

OpenAIRE

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...

Water quality, Multivariate statistical techniques, submarine out fall, spatial variation, temporal variation

International Nuclear Information System (INIS)

Garcia, Francisco; Palacio, Carlos; Garcia, Uriel

2012-01-01

Multivariate statistical techniques were used to investigate the temporal and spatial variations of water quality at the Santa Marta coastal area where a submarine out fall that discharges 1 m3/s of domestic wastewater is located. Two-way analysis of variance (ANOVA), cluster and principal component analysis and Krigging interpolation were considered for this report. Temporal variation showed two heterogeneous periods. From December to April, and July, where the concentration of the water quality parameters is higher; the rest of the year (May, June, August-November) were significantly lower. The spatial variation reported two areas where the water quality is different, this difference is related to the proximity to the submarine out fall discharge.

Multi-Site and Multi-Variables Statistical Downscaling Technique in the Monsoon Dominated Region of Pakistan

Science.gov (United States)

Khan, Firdos; Pilz, Jürgen

2016-04-01

South Asia is under the severe impacts of changing climate and global warming. The last two decades showed that climate change or global warming is happening and the first decade of 21st century is considered as the warmest decade over Pakistan ever in history where temperature reached 53 0C in 2010. Consequently, the spatio-temporal distribution and intensity of precipitation is badly effected and causes floods, cyclones and hurricanes in the region which further have impacts on agriculture, water, health etc. To cope with the situation, it is important to conduct impact assessment studies and take adaptation and mitigation remedies. For impact assessment studies, we need climate variables at higher resolution. Downscaling techniques are used to produce climate variables at higher resolution; these techniques are broadly divided into two types, statistical downscaling and dynamical downscaling. The target location of this study is the monsoon dominated region of Pakistan. One reason for choosing this area is because the contribution of monsoon rains in this area is more than 80 % of the total rainfall. This study evaluates a statistical downscaling technique which can be then used for downscaling climatic variables. Two statistical techniques i.e. quantile regression and copula modeling are combined in order to produce realistic results for climate variables in the area under-study. To reduce the dimension of input data and deal with multicollinearity problems, empirical orthogonal functions will be used. Advantages of this new method are: (1) it is more robust to outliers as compared to ordinary least squares estimates and other estimation methods based on central tendency and dispersion measures; (2) it preserves the dependence among variables and among sites and (3) it can be used to combine different types of distributions. This is important in our case because we are dealing with climatic variables having different distributions over different meteorological

Evaluating Statistical Process Control (SPC) techniques and computing the uncertainty of force calibrations

Science.gov (United States)

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.

Quantitative Portfolio Optimization Techniques Applied to the Brazilian Stock Market

Directory of Open Access Journals (Sweden)

André Alves Portela Santos

2012-09-01

Full Text Available In this paper we assess the out-of-sample performance of two alternative quantitative portfolio optimization techniques - mean-variance and minimum variance optimization – and compare their performance with respect to a naive 1/N (or equally-weighted portfolio and also to the market portfolio given by the Ibovespa. We focus on short selling-constrained portfolios and consider alternative estimators for the covariance matrices: sample covariance matrix, RiskMetrics, and three covariance estimators proposed by Ledoit and Wolf (2003, Ledoit and Wolf (2004a and Ledoit and Wolf (2004b. Taking into account alternative portfolio re-balancing frequencies, we compute out-of-sample performance statistics which indicate that the quantitative approaches delivered improved results in terms of lower portfolio volatility and better risk-adjusted returns. Moreover, the use of more sophisticated estimators for the covariance matrix generated optimal portfolios with lower turnover over time.

A cost-saving statistically based screening technique for focused sampling of a lead-contaminated site

International Nuclear Information System (INIS)

Moscati, A.F. Jr.; Hediger, E.M.; Rupp, M.J.

1986-01-01

High concentrations of lead in soils along an abandoned railroad line prompted a remedial investigation to characterize the extent of contamination across a 7-acre site. Contamination was thought to be spotty across the site reflecting its past use in battery recycling operations at discrete locations. A screening technique was employed to delineate the more highly contaminated areas by testing a statistically determined minimum number of random samples from each of seven discrete site areas. The approach not only quickly identified those site areas which would require more extensive grid sampling, but also provided a statistically defensible basis for excluding other site areas from further consideration, thus saving the cost of additional sample collection and analysis. The reduction in the number of samples collected in ''clean'' areas of the site ranged from 45 to 60%

Close to the Clothes : Materiality and Sophisticated Archaism in Alexander van Slobbe’s Design Practices

NARCIS (Netherlands)

Baronian, M.-A.

This article looks at the work of contemporary Dutch fashion designer Alexander van Slobbe (1959) and examines how, since the 1990s, his fashion practices have consistently and consciously put forward a unique reflection on questions related to materiality, sophisticated archaism, luxury,

Close to the Clothes: Materiality and Sophisticated Archaism in Alexander van Slobbe’s Design Practices

NARCIS (Netherlands)

Baronian, M.-A.

This article looks at the work of contemporary Dutch fashion designer Alexander van Slobbe (1959) and examines how, since the 1990s, his fashion practices have consistently and consciously put forward a unique reflection on questions related to materiality, sophisticated archaism, luxury,

Hard X-ray techniques suitable for polymer experiments

Energy Technology Data Exchange (ETDEWEB)

Bras, W; Goossens, H; Goderis, B, E-mail: Wim.Bras@esrf.fr [Netherlands Organisation for Scientific Research (NWO) (Netherlands); DUBBLE-ESRF, BP 220, F38043 Grenoble Cedex (France); Department of Chemical Engineering and Chemistry, Eindhoven University of Technology, PO Box 513, 5600 MB Eindhoven (Netherlands); Molecular and Nanomaterials, Chemistry Department, Catholic University of Leuven, Celestijnenlaan 200F (Belgium)

2010-11-15

Polymers have been studied since 1979 with 8-12 keV synchrotron radiation X-ray scattering methods and the number and sophistication of the experiments have rapidly grown ever since. More recently, new experimental techniques have been developed that use softer or harder X-rays in less conventional ways. This article provides a brief overview of the possibilities of hard X-ray techniques and indicates some areas that might gain from further developments.

Hard X-ray techniques suitable for polymer experiments

International Nuclear Information System (INIS)

Bras, W; Goossens, H; Goderis, B

2010-01-01

Polymers have been studied since 1979 with 8-12 keV synchrotron radiation X-ray scattering methods and the number and sophistication of the experiments have rapidly grown ever since. More recently, new experimental techniques have been developed that use softer or harder X-rays in less conventional ways. This article provides a brief overview of the possibilities of hard X-ray techniques and indicates some areas that might gain from further developments.

Plasma transport studies using transient techniques

International Nuclear Information System (INIS)

Simonen, T.C.; Brower, D.L.; Efthimion, P.

1991-01-01

Selected topics from the Transient Transport sessions of the Transport Task Force Workshop, held February 19-23, 1990, in Hilton Head, South Carolina are summarized. Presentations on sawtooth propagation, ECH modulation, particle modulation, and H-mode transitions are included. The research results presented indicated a growing theoretical understanding and experimental sophistication in the application of transient techniques to transport studies. (Author)

Philosophy and the practice of Bayesian statistics.

Science.gov (United States)

Gelman, Andrew; Shalizi, Cosma Rohilla

2013-02-01

A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science. Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework. © 2012 The British Psychological Society.

The Novel Quantitative Technique for Assessment of Gait Symmetry Using Advanced Statistical Learning Algorithm

Directory of Open Access Journals (Sweden)

Jianning Wu

2015-01-01

Full Text Available The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis.

The novel quantitative technique for assessment of gait symmetry using advanced statistical learning algorithm.

Science.gov (United States)

Wu, Jianning; Wu, Bin

2015-01-01

The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis.

Evolution of tyre/road noise research in India: Investigations using statistical pass-by method and noise trailer

Directory of Open Access Journals (Sweden)

Vivek Khan

2018-05-01

Full Text Available The objective of this research study was to investigate and analyze the acoustical characteristics of asphalt concrete and cement concrete surface types by two noise measurement techniques: statistical pass-by (SPB and Close Proximity (CPX methods. A noise trailer was devised and manufactured as part of the CPX methodology to evaluate tyre/pavement noise interaction at source. Two national highway test sections covering over 11 km of asphalt and cement concrete surfaces were selected to carry out the noise measurements, and the effects of vehicle speeds and/or sizes on the overall noise profiles were investigated. The major contribution of this first of its kind study in India was the utilization of sophisticated tools and techniques to measure the tyre/pavement interaction noise at source through CPX, which helped correlate the influence of road surfaces on the generation of overall road traffic noise using SPB technique. The SPB method noise profiles revealed that the noise pressure levels increased with increasing vehicle speeds and weights. The noise trailer CPX findings corroborated the results obtained from the SPB method in that cement concrete surface produced a higher noise at source than that of the asphalt concrete surface by about 5 dBA. Further, there was about 5 dBA differential in noise between SPB and CPX methods for cement concrete pavement sections; also, there was about 10 dBA differential in noise between the two methods for asphalt concrete pavement stretches. Keywords: Tyre/road noise, Statistical pass-by, Close proximity, Noise trailer, Asphalt concrete, Cement concrete

Comment on the asymptotics of a distribution-free goodness of fit test statistic.

Science.gov (United States)

Browne, Michael W; Shapiro, Alexander

2015-03-01

In a recent article Jennrich and Satorra (Psychometrika 78: 545-552, 2013) showed that a proof by Browne (British Journal of Mathematical and Statistical Psychology 37: 62-83, 1984) of the asymptotic distribution of a goodness of fit test statistic is incomplete because it fails to prove that the orthogonal component function employed is continuous. Jennrich and Satorra (Psychometrika 78: 545-552, 2013) showed how Browne's proof can be completed satisfactorily but this required the development of an extensive and mathematically sophisticated framework for continuous orthogonal component functions. This short note provides a simple proof of the asymptotic distribution of Browne's (British Journal of Mathematical and Statistical Psychology 37: 62-83, 1984) test statistic by using an equivalent form of the statistic that does not involve orthogonal component functions and consequently avoids all complicating issues associated with them.

A Snapshot of Serial Rape: An Investigation of Criminal Sophistication and Use of Force on Victim Injury and Severity of the Assault.

Science.gov (United States)

de Heer, Brooke

2016-02-01

Prior research on rapes reported to law enforcement has identified criminal sophistication and the use of force against the victim as possible unique identifiers to serial rape versus one-time rape. This study sought to contribute to the current literature on reported serial rape by investigating how the level of criminal sophistication of the rapist and use of force used were associated with two important outcomes of rape: victim injury and overall severity of the assault. In addition, it was evaluated whether rapist and victim ethnicity affected these relationships. A nation-wide sample of serial rape cases reported to law enforcement collected by the Federal Bureau of Investigation (FBI) was analyzed (108 rapists, 543 victims). Results indicated that serial rapists typically used a limited amount of force against the victim and displayed a high degree of criminal sophistication. In addition, the more criminally sophisticated the perpetrator was, the more sexual acts he performed on his victim. Finally, rapes between a White rapist and White victim were found to exhibit higher levels of criminal sophistication and were more severe in terms of number and types of sexual acts committed. These findings provide a more in-depth understanding of serial rape that can inform both academics and practitioners in the field about contributors to victim injury and severity of the assault. © The Author(s) 2014.

Assessment of Surface Water Quality Using Multivariate Statistical Techniques in the Terengganu River Basin

International Nuclear Information System (INIS)

Aminu Ibrahim; Hafizan Juahir; Mohd Ekhwan Toriman; Mustapha, A.; Azman Azid; Isiyaka, H.A.

2015-01-01

Multivariate Statistical techniques including cluster analysis, discriminant analysis, and principal component analysis/factor analysis were applied to investigate the spatial variation and pollution sources in the Terengganu river basin during 5 years of monitoring 13 water quality parameters at thirteen different stations. Cluster analysis (CA) classified 13 stations into 2 clusters low polluted (LP) and moderate polluted (MP) based on similar water quality characteristics. Discriminant analysis (DA) rendered significant data reduction with 4 parameters (pH, NH 3 -NL, PO 4 and EC) and correct assignation of 95.80 %. The PCA/ FA applied to the data sets, yielded in five latent factors accounting 72.42 % of the total variance in the water quality data. The obtained varifactors indicate that parameters in charge for water quality variations are mainly related to domestic waste, industrial, runoff and agricultural (anthropogenic activities). Therefore, multivariate techniques are important in environmental management. (author)

Statistical methods

CERN Document Server

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

The challenges of transportation/traffic statistics in Japan and directions for the future

Directory of Open Access Journals (Sweden)

Shigeru Kawasaki

2015-07-01

Full Text Available In order to respond to new challenges in transportation and traffic problems, it is essential to enhance statistics in this field that provides the basis for policy researches. Many of the statistics in this field in Japan consist of “official statistics” created by the government. This paper gives a review of the current status of transportation and traffic statistics (hereinafter called “transportation statistics” in short in Japan. Furthermore, the paper discusses challenges in such statistics in the new environment and the direction that statistics that should take in the future. For Japan’s transportation statistics to play vital roles in more sophisticated analyses, it is necessary to improve the environment that facilitates the use of microdata for analysis. It is also necessary to establish an environment where big data can be more easily used for compilation of official statistics and performing policy researches. To achieve this end, close cooperation among the government, academia, and businesses will be essential.

The Recoverability of P-Technique Factor Analysis

Science.gov (United States)

Molenaar, Peter C. M.; Nesselroade, John R.

2009-01-01

It seems that just when we are about to lay P-technique factor analysis finally to rest as obsolete because of newer, more sophisticated multivariate time-series models using latent variables--dynamic factor models--it rears its head to inform us that an obituary may be premature. We present the results of some simulations demonstrating that even…

Performance evaluation of a hybrid-passive landfill leachate treatment system using multivariate statistical techniques

Energy Technology Data Exchange (ETDEWEB)

Wallace, Jack, E-mail: jack.wallace@ce.queensu.ca [Department of Civil Engineering, Queen’s University, Ellis Hall, 58 University Avenue, Kingston, Ontario K7L 3N6 (Canada); Champagne, Pascale, E-mail: champagne@civil.queensu.ca [Department of Civil Engineering, Queen’s University, Ellis Hall, 58 University Avenue, Kingston, Ontario K7L 3N6 (Canada); Monnier, Anne-Charlotte, E-mail: anne-charlotte.monnier@insa-lyon.fr [National Institute for Applied Sciences – Lyon, 20 Avenue Albert Einstein, 69621 Villeurbanne Cedex (France)

2015-01-15

Highlights: • Performance of a hybrid passive landfill leachate treatment system was evaluated. • 33 Water chemistry parameters were sampled for 21 months and statistically analyzed. • Parameters were strongly linked and explained most (>40%) of the variation in data. • Alkalinity, ammonia, COD, heavy metals, and iron were criteria for performance. • Eight other parameters were key in modeling system dynamics and criteria. - Abstract: A pilot-scale hybrid-passive treatment system operated at the Merrick Landfill in North Bay, Ontario, Canada, treats municipal landfill leachate and provides for subsequent natural attenuation. Collected leachate is directed to a hybrid-passive treatment system, followed by controlled release to a natural attenuation zone before entering the nearby Little Sturgeon River. The study presents a comprehensive evaluation of the performance of the system using multivariate statistical techniques to determine the interactions between parameters, major pollutants in the leachate, and the biological and chemical processes occurring in the system. Five parameters (ammonia, alkalinity, chemical oxygen demand (COD), “heavy” metals of interest, with atomic weights above calcium, and iron) were set as criteria for the evaluation of system performance based on their toxicity to aquatic ecosystems and importance in treatment with respect to discharge regulations. System data for a full range of water quality parameters over a 21-month period were analyzed using principal components analysis (PCA), as well as principal components (PC) and partial least squares (PLS) regressions. PCA indicated a high degree of association for most parameters with the first PC, which explained a high percentage (>40%) of the variation in the data, suggesting strong statistical relationships among most of the parameters in the system. Regression analyses identified 8 parameters (set as independent variables) that were most frequently retained for modeling

Multivariate mixed linear model analysis of longitudinal data: an information-rich statistical technique for analyzing disease resistance data

Science.gov (United States)

The mixed linear model (MLM) is currently among the most advanced and flexible statistical modeling techniques and its use in tackling problems in plant pathology has begun surfacing in the literature. The longitudinal MLM is a multivariate extension that handles repeatedly measured data, such as r...

Statistics For Dummies

CERN Document Server

Rumsey, Deborah

2011-01-01

The fun and easy way to get down to business with statistics Stymied by statistics? No fear ? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more.Tracks to a typical first semester statistics cou

Exploring the predictive power of interaction terms in a sophisticated risk equalization model using regression trees.

Science.gov (United States)

van Veen, S H C M; van Kleef, R C; van de Ven, W P M M; van Vliet, R C J A

2018-02-01

This study explores the predictive power of interaction terms between the risk adjusters in the Dutch risk equalization (RE) model of 2014. Due to the sophistication of this RE-model and the complexity of the associations in the dataset (N = ~16.7 million), there are theoretically more than a million interaction terms. We used regression tree modelling, which has been applied rarely within the field of RE, to identify interaction terms that statistically significantly explain variation in observed expenses that is not already explained by the risk adjusters in this RE-model. The interaction terms identified were used as additional risk adjusters in the RE-model. We found evidence that interaction terms can improve the prediction of expenses overall and for specific groups in the population. However, the prediction of expenses for some other selective groups may deteriorate. Thus, interactions can reduce financial incentives for risk selection for some groups but may increase them for others. Furthermore, because regression trees are not robust, additional criteria are needed to decide which interaction terms should be used in practice. These criteria could be the right incentive structure for risk selection and efficiency or the opinion of medical experts. Copyright © 2017 John Wiley & Sons, Ltd.

Introduction to statistical data analysis for the life sciences

CERN Document Server

Ekstrom, Claus Thorn

2014-01-01

This text provides a computational toolbox that enables students to analyze real datasets and gain the confidence and skills to undertake more sophisticated analyses. Although accessible with any statistical software, the text encourages a reliance on R. For those new to R, an introduction to the software is available in an appendix. The book also includes end-of-chapter exercises as well as an entire chapter of case exercises that help students apply their knowledge to larger datasets and learn more about approaches specific to the life sciences.

Application of statistical downscaling technique for the production of wine grapes (Vitis vinifera L.) in Spain

Science.gov (United States)

Gaitán Fernández, E.; García Moreno, R.; Pino Otín, M. R.; Ribalaygua Batalla, J.

2012-04-01

Climate and soil are two of the most important limiting factors for agricultural production. Nowadays climate change has been documented in many geographical locations affecting different cropping systems. The General Circulation Models (GCM) has become important tools to simulate the more relevant aspects of the climate expected for the XXI century in the frame of climatic change. These models are able to reproduce the general features of the atmospheric dynamic but their low resolution (about 200 Km) avoids a proper simulation of lower scale meteorological effects. Downscaling techniques allow overcoming this problem by adapting the model outcomes to local scale. In this context, FIC (Fundación para la Investigación del Clima) has developed a statistical downscaling technique based on a two step analogue methods. This methodology has been broadly tested on national and international environments leading to excellent results on future climate models. In a collaboration project, this statistical downscaling technique was applied to predict future scenarios for the grape growing systems in Spain. The application of such model is very important to predict expected climate for the different growing crops, mainly for grape, where the success of different varieties are highly related to climate and soil. The model allowed the implementation of agricultural conservation practices in the crop production, detecting highly sensible areas to negative impacts produced by any modification of climate in the different regions, mainly those protected with protected designation of origin, and the definition of new production areas with optimal edaphoclimatic conditions for the different varieties.

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.

The sophisticated control of the tram bogie on track

Directory of Open Access Journals (Sweden)

Radovan DOLECEK

2015-09-01

Full Text Available The paper deals with the problems of routing control algorithms of new conception of tram vehicle bogie. The main goal of these research activities is wear reduction of rail wheels and tracks, wear reduction of traction energy losses and increasing of running comfort. The testing experimental tram vehicle with special bogie construction powered by traction battery is utilized for these purposes. This vehicle has a rotary bogie with independent rotating wheels driven by permanent magnets synchronous motors and a solid axle. The wheel forces in bogie are measured by large amounts of the various sensors placed on the testing experimental tram vehicle. Nowadays the designed control algorithms are implemented to the vehicle superset control system. The traction requirements and track characteristics have an effect to these control algorithms. This control including sophisticated routing brings other improvements which is verified and corrected according to individual traction and driving characteristics, and opens new possibilities.

Are conventional statistical techniques exhaustive for defining metal background concentrations in harbour sediments? A case study: The Coastal Area of Bari (Southeast Italy).

Science.gov (United States)

Mali, Matilda; Dell'Anna, Maria Michela; Mastrorilli, Piero; Damiani, Leonardo; Ungaro, Nicola; Belviso, Claudia; Fiore, Saverio

2015-11-01

Sediment contamination by metals poses significant risks to coastal ecosystems and is considered to be problematic for dredging operations. The determination of the background values of metal and metalloid distribution based on site-specific variability is fundamental in assessing pollution levels in harbour sediments. The novelty of the present work consists of addressing the scope and limitation of analysing port sediments through the use of conventional statistical techniques (such as: linear regression analysis, construction of cumulative frequency curves and the iterative 2σ technique), that are commonly employed for assessing Regional Geochemical Background (RGB) values in coastal sediments. This study ascertained that although the tout court use of such techniques in determining the RGB values in harbour sediments seems appropriate (the chemical-physical parameters of port sediments fit well with statistical equations), it should nevertheless be avoided because it may be misleading and can mask key aspects of the study area that can only be revealed by further investigations, such as mineralogical and multivariate statistical analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

Transfer of physics detector models into CAD systems using modern techniques

International Nuclear Information System (INIS)

Dach, M.; Vuoskoski, J.

1996-01-01

Designing high energy physics detectors for future experiments requires sophisticated computer aided design and simulation tools. In order to satisfy the future demands in this domain, modern techniques, methods, and standards have to be applied. We present an interface application, designed and implemented using object-oriented techniques, for the widely used GEANT physics simulation package. It converts GEANT detector models into the future industrial standard, STEP. (orig.)

Flow prediction models using macroclimatic variables and multivariate statistical techniques in the Cauca River Valley

International Nuclear Information System (INIS)

Carvajal Escobar Yesid; Munoz, Flor Matilde

2007-01-01

The project this centred in the revision of the state of the art of the ocean-atmospheric phenomena that you affect the Colombian hydrology especially The Phenomenon Enos that causes a socioeconomic impact of first order in our country, it has not been sufficiently studied; therefore it is important to approach the thematic one, including the variable macroclimates associated to the Enos in the analyses of water planning. The analyses include revision of statistical techniques of analysis of consistency of hydrological data with the objective of conforming a database of monthly flow of the river reliable and homogeneous Cauca. Statistical methods are used (Analysis of data multivariante) specifically The analysis of principal components to involve them in the development of models of prediction of flows monthly means in the river Cauca involving the Lineal focus as they are the model autoregressive AR, ARX and Armax and the focus non lineal Net Artificial Network.

Comparison of adaptive statistical iterative and filtered back projection reconstruction techniques in quantifying coronary calcium.

Science.gov (United States)

Takahashi, Masahiro; Kimura, Fumiko; Umezawa, Tatsuya; Watanabe, Yusuke; Ogawa, Harumi

2016-01-01

Adaptive statistical iterative reconstruction (ASIR) has been used to reduce radiation dose in cardiac computed tomography. However, change of image parameters by ASIR as compared to filtered back projection (FBP) may influence quantification of coronary calcium. To investigate the influence of ASIR on calcium quantification in comparison to FBP. In 352 patients, CT images were reconstructed using FBP alone, FBP combined with ASIR 30%, 50%, 70%, and ASIR 100% based on the same raw data. Image noise, plaque density, Agatston scores and calcium volumes were compared among the techniques. Image noise, Agatston score, and calcium volume decreased significantly with ASIR compared to FBP (each P ASIR reduced Agatston score by 10.5% to 31.0%. In calcified plaques both of patients and a phantom, ASIR decreased maximum CT values and calcified plaque size. In comparison to FBP, adaptive statistical iterative reconstruction (ASIR) may significantly decrease Agatston scores and calcium volumes. Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Chemometric and Statistical Analyses of ToF-SIMS Spectra of Increasingly Complex Biological Samples

Energy Technology Data Exchange (ETDEWEB)

Berman, E S; Wu, L; Fortson, S L; Nelson, D O; Kulp, K S; Wu, K J

2007-10-24

Characterizing and classifying molecular variation within biological samples is critical for determining fundamental mechanisms of biological processes that will lead to new insights including improved disease understanding. Towards these ends, time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to examine increasingly complex samples of biological relevance, including monosaccharide isomers, pure proteins, complex protein mixtures, and mouse embryo tissues. The complex mass spectral data sets produced were analyzed using five common statistical and chemometric multivariate analysis techniques: principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLSDA), soft independent modeling of class analogy (SIMCA), and decision tree analysis by recursive partitioning. PCA was found to be a valuable first step in multivariate analysis, providing insight both into the relative groupings of samples and into the molecular basis for those groupings. For the monosaccharides, pure proteins and protein mixture samples, all of LDA, PLSDA, and SIMCA were found to produce excellent classification given a sufficient number of compound variables calculated. For the mouse embryo tissues, however, SIMCA did not produce as accurate a classification. The decision tree analysis was found to be the least successful for all the data sets, providing neither as accurate a classification nor chemical insight for any of the tested samples. Based on these results we conclude that as the complexity of the sample increases, so must the sophistication of the multivariate technique used to classify the samples. PCA is a preferred first step for understanding ToF-SIMS data that can be followed by either LDA or PLSDA for effective classification analysis. This study demonstrates the strength of ToF-SIMS combined with multivariate statistical and chemometric techniques to classify increasingly complex biological samples

Radiation dose reduction on multidetector abdominal CT using adaptive statistical iterative reconstruction technique in children

International Nuclear Information System (INIS)

Zhang Qifeng; Peng Yun; Duan Xiaomin; Sun Jihang; Yu Tong; Han Zhonglong

2013-01-01

Objective: To investigate the feasibility to reduce radiation doses on pediatric multidetector abdominal CT using the adaptive statistical iterative reconstruction technique (ASIR) associated with automated tube current modulation technique (ATCM). Methods: Thirty patients underwent abdominal CT with ATCM and the follow-up scan with ATCM cooperated with 40% ASIR. ATCM was used with age dependent noise index (NI) settings: NI = 9 for 0-5 year old and NI = 11 for > 5 years old for simple ATCM group, NI = 11 for 0-5 year old and NI = 15 for > 5 years old for ATCM cooperated with 40% ASIR group (AISR group). Two radiologists independently evaluated images for diagnostic quality and image noise with subjectively image quality score and image noise score using a 5-point scale. Interobserver agreement was assessed by Kappa test. The volume CT dose indexes (CTDIvol) for the two groups were recorded. Statistical significance for the CTDIvol value was analyzed by pair-sample t test. Results: The average CTDIvol for the ASIR group was (1.38 ± 0.64) mGy, about 60% lower than (3.56 ± 1.23) mGy for the simple ATCM group, and the CTDIvol of two groups had statistically significant differences. (t = 33.483, P < 0.05). The subjective image quality scores for the simple ATCM group were 4.43 ± 0.57 and 4.37 ±0.61, Kappa = 0.878, P < 0.01 (ASIR group: 4.70 ± 0.47 and 4.60 ± 0.50, Kappa = 0.783, P < 0.01), by two observers. The image noise score for the simple ATCM group were 4.03 ±0.56 and 3.83 ±0.53, Kappa = 0.572, P < 0.01 (ASIR group: 4.20 ± 0.48 and 4.10 ± 0.48, Kappa = 0.748, P < 0.01), by two observers. All images had acceptable diagnostic image quality. Conclusion: Lower radiation dose can be achieved by elevating NI with ASIR in pediatric CT abdominal studies, while maintaining diagnostically acceptable images. (authors)

Sophisticated approval voting, ignorance priors, and plurality heuristics: a behavioral social choice analysis in a Thurstonian framework.

Science.gov (United States)

Regenwetter, Michel; Ho, Moon-Ho R; Tsetlin, Ilia

2007-10-01

This project reconciles historically distinct paradigms at the interface between individual and social choice theory, as well as between rational and behavioral decision theory. The authors combine a utility-maximizing prescriptive rule for sophisticated approval voting with the ignorance prior heuristic from behavioral decision research and two types of plurality heuristics to model approval voting behavior. When using a sincere plurality heuristic, voters simplify their decision process by voting for their single favorite candidate. When using a strategic plurality heuristic, voters strategically focus their attention on the 2 front-runners and vote for their preferred candidate among these 2. Using a hierarchy of Thurstonian random utility models, the authors implemented these different decision rules and tested them statistically on 7 real world approval voting elections. They cross-validated their key findings via a psychological Internet experiment. Although a substantial number of voters used the plurality heuristic in the real elections, they did so sincerely, not strategically. Moreover, even though Thurstonian models do not force such agreement, the results show, in contrast to common wisdom about social choice rules, that the sincere social orders by Condorcet, Borda, plurality, and approval voting are identical in all 7 elections and in the Internet experiment. PsycINFO Database Record (c) 2007 APA, all rights reserved.

Coronary artery plaques: Cardiac CT with model-based and adaptive-statistical iterative reconstruction technique

International Nuclear Information System (INIS)

Scheffel, Hans; Stolzmann, Paul; Schlett, Christopher L.; Engel, Leif-Christopher; Major, Gyöngi Petra; Károlyi, Mihály; Do, Synho; Maurovich-Horvat, Pál; Hoffmann, Udo

2012-01-01

Objectives: To compare image quality of coronary artery plaque visualization at CT angiography with images reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model based iterative reconstruction (MBIR) techniques. Methods: The coronary arteries of three ex vivo human hearts were imaged by CT and reconstructed with FBP, ASIR and MBIR. Coronary cross-sectional images were co-registered between the different reconstruction techniques and assessed for qualitative and quantitative image quality parameters. Readers were blinded to the reconstruction algorithm. Results: A total of 375 triplets of coronary cross-sectional images were co-registered. Using MBIR, 26% of the images were rated as having excellent overall image quality, which was significantly better as compared to ASIR and FBP (4% and 13%, respectively, all p < 0.001). Qualitative assessment of image noise demonstrated a noise reduction by using ASIR as compared to FBP (p < 0.01) and further noise reduction by using MBIR (p < 0.001). The contrast-to-noise-ratio (CNR) using MBIR was better as compared to ASIR and FBP (44 ± 19, 29 ± 15, 26 ± 9, respectively; all p < 0.001). Conclusions: Using MBIR improved image quality, reduced image noise and increased CNR as compared to the other available reconstruction techniques. This may further improve the visualization of coronary artery plaque and allow radiation reduction.

Experimental Mathematics and Computational Statistics

Energy Technology Data Exchange (ETDEWEB)

Bailey, David H.; Borwein, Jonathan M.

2009-04-30

The field of statistics has long been noted for techniques to detect patterns and regularities in numerical data. In this article we explore connections between statistics and the emerging field of 'experimental mathematics'. These includes both applications of experimental mathematics in statistics, as well as statistical methods applied to computational mathematics.

New computing techniques in physics research

International Nuclear Information System (INIS)

Becks, Karl-Heinz; Perret-Gallix, Denis

1994-01-01

New techniques were highlighted by the ''Third International Workshop on Software Engineering, Artificial Intelligence and Expert Systems for High Energy and Nuclear Physics'' in Oberammergau, Bavaria, Germany, from October 4 to 8. It was the third workshop in the series; the first was held in Lyon in 1990 and the second at France-Telecom site near La Londe les Maures in 1992. This series of workshops covers a broad spectrum of problems. New, highly sophisticated experiments demand new techniques in computing, in hardware as well as in software. Software Engineering Techniques could in principle satisfy the needs for forthcoming accelerator experiments. The growing complexity of detector systems demands new techniques in experimental error diagnosis and repair suggestions; Expert Systems seem to offer a way of assisting the experimental crew during data-taking

Investigation of HIV-1 infected and uninfected cells using the optical trapping technique

CSIR Research Space (South Africa)

Ombinda-Lemboumba, Saturnin

2017-02-01

Full Text Available Optical trapping has emerged as an essential tool for manipulating single biological material and performing sophisticated spectroscopy analysis on individual cell. The optical trapping technique has been used to grab and immobilize cells from a...

Proficiency Testing for Determination of Water Content in Toluene of Chemical Reagents by iteration robust statistic technique

Science.gov (United States)

Wang, Hao; Wang, Qunwei; He, Ming

2018-05-01

In order to investigate and improve the level of detection technology of water content in liquid chemical reagents of domestic laboratories, proficiency testing provider PT0031 (CNAS) has organized proficiency testing program of water content in toluene, 48 laboratories from 18 provinces/cities/municipals took part in the PT. This paper introduces the implementation process of proficiency testing for determination of water content in toluene, including sample preparation, homogeneity and stability test, the results of statistics of iteration robust statistic technique and analysis, summarized and analyzed those of the different test standards which are widely used in the laboratories, put forward the technological suggestions for the improvement of the test quality of water content. Satisfactory results were obtained by 43 laboratories, amounting to 89.6% of the total participating laboratories.

Low Level RF Including a Sophisticated Phase Control System for CTF3

CERN Document Server

Mourier, J; Nonglaton, J M; Syratchev, I V; Tanner, L

2004-01-01

CTF3 (CLIC Test Facility 3), currently under construction at CERN, is a test facility designed to demonstrate the key feasibility issues of the CLIC (Compact LInear Collider) two-beam scheme. When completed, this facility will consist of a 150 MeV linac followed by two rings for bunch-interleaving, and a test stand where 30 GHz power will be generated. In this paper, the work that has been carried out on the linac's low power RF system is described. This includes, in particular, a sophisticated phase control system for the RF pulse compressor to produce a flat-top rectangular pulse over 1.4 µs.

Business statistics for dummies

CERN Document Server

Anderson, Alan

2013-01-01

Score higher in your business statistics course? Easy. Business statistics is a common course for business majors and MBA candidates. It examines common data sets and the proper way to use such information when conducting research and producing informational reports such as profit and loss statements, customer satisfaction surveys, and peer comparisons. Business Statistics For Dummies tracks to a typical business statistics course offered at the undergraduate and graduate levels and provides clear, practical explanations of business statistical ideas, techniques, formulas, and calculations, w

Statistical sampling techniques as applied to OSE inspections

International Nuclear Information System (INIS)

Davis, J.J.; Cote, R.W.

1987-01-01

The need has been recognized for statistically valid methods for gathering information during OSE inspections; and for interpretation of results, both from performance testing and from records reviews, interviews, etc. Battelle Columbus Division, under contract to DOE OSE has performed and is continuing to perform work in the area of statistical methodology for OSE inspections. This paper represents some of the sampling methodology currently being developed for use during OSE inspections. Topics include population definition, sample size requirements, level of confidence and practical logistical constraints associated with the conduct of an inspection based on random sampling. Sequential sampling schemes and sampling from finite populations are also discussed. The methods described are applicable to various data gathering activities, ranging from the sampling and examination of classified documents to the sampling of Protective Force security inspectors for skill testing

Beginning statistics with data analysis

CERN Document Server

Mosteller, Frederick; Rourke, Robert EK

2013-01-01

This introduction to the world of statistics covers exploratory data analysis, methods for collecting data, formal statistical inference, and techniques of regression and analysis of variance. 1983 edition.

Statistics in a nutshell

CERN Document Server

Boslaugh, Sarah

2013-01-01

Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college texts. Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform common statistical analyses and learn a wide range of techniques without getting in over your head, this is your book.

Statistical Symbolic Execution with Informed Sampling

Science.gov (United States)

Filieri, Antonio; Pasareanu, Corina S.; Visser, Willem; Geldenhuys, Jaco

2014-01-01

Symbolic execution techniques have been proposed recently for the probabilistic analysis of programs. These techniques seek to quantify the likelihood of reaching program events of interest, e.g., assert violations. They have many promising applications but have scalability issues due to high computational demand. To address this challenge, we propose a statistical symbolic execution technique that performs Monte Carlo sampling of the symbolic program paths and uses the obtained information for Bayesian estimation and hypothesis testing with respect to the probability of reaching the target events. To speed up the convergence of the statistical analysis, we propose Informed Sampling, an iterative symbolic execution that first explores the paths that have high statistical significance, prunes them from the state space and guides the execution towards less likely paths. The technique combines Bayesian estimation with a partial exact analysis for the pruned paths leading to provably improved convergence of the statistical analysis. We have implemented statistical symbolic execution with in- formed sampling in the Symbolic PathFinder tool. We show experimentally that the informed sampling obtains more precise results and converges faster than a purely statistical analysis and may also be more efficient than an exact symbolic analysis. When the latter does not terminate symbolic execution with informed sampling can give meaningful results under the same time and memory limits.

Sophisticated Approval Voting, Ignorance Priors, and Plurality Heuristics: A Behavioral Social Choice Analysis in a Thurstonian Framework

Science.gov (United States)

Regenwetter, Michel; Ho, Moon-Ho R.; Tsetlin, Ilia

2007-01-01

This project reconciles historically distinct paradigms at the interface between individual and social choice theory, as well as between rational and behavioral decision theory. The authors combine a utility-maximizing prescriptive rule for sophisticated approval voting with the ignorance prior heuristic from behavioral decision research and two…

Vital statistics

CERN Document Server

MacKenzie, Dana

2004-01-01

The drawbacks of using 19th-century mathematics in physics and astronomy are illustrated. To continue with the expansion of the knowledge about the cosmos, the scientists will have to come in terms with modern statistics. Some researchers have deliberately started importing techniques that are used in medical research. However, the physicists need to identify the brand of statistics that will be suitable for them, and make a choice between the Bayesian and the frequentists approach. (Edited abstract).

Statistical techniques for modeling extreme price dynamics in the energy market

International Nuclear Information System (INIS)

Mbugua, L N; Mwita, P N

2013-01-01

Extreme events have large impact throughout the span of engineering, science and economics. This is because extreme events often lead to failure and losses due to the nature unobservable of extra ordinary occurrences. In this context this paper focuses on appropriate statistical methods relating to a combination of quantile regression approach and extreme value theory to model the excesses. This plays a vital role in risk management. Locally, nonparametric quantile regression is used, a method that is flexible and best suited when one knows little about the functional forms of the object being estimated. The conditions are derived in order to estimate the extreme value distribution function. The threshold model of extreme values is used to circumvent the lack of adequate observation problem at the tail of the distribution function. The application of a selection of these techniques is demonstrated on the volatile fuel market. The results indicate that the method used can extract maximum possible reliable information from the data. The key attraction of this method is that it offers a set of ready made approaches to the most difficult problem of risk modeling.

Bayesian statistics an introduction

CERN Document Server

Lee, Peter M

2012-01-01

Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as wel

CATDAT : A Program for Parametric and Nonparametric Categorical Data Analysis : User's Manual Version 1.0, 1998-1999 Progress Report.

Energy Technology Data Exchange (ETDEWEB)

Peterson, James T.

1999-12-01

Natural resource professionals are increasingly required to develop rigorous statistical models that relate environmental data to categorical responses data. Recent advances in the statistical and computing sciences have led to the development of sophisticated methods for parametric and nonparametric analysis of data with categorical responses. The statistical software package CATDAT was designed to make some of these relatively new and powerful techniques available to scientists. The CATDAT statistical package includes 4 analytical techniques: generalized logit modeling; binary classification tree; extended K-nearest neighbor classification; and modular neural network.

CATDAT - A program for parametric and nonparametric categorical data analysis user's manual, Version 1.0

International Nuclear Information System (INIS)

Peterson, James R.; Haas, Timothy C.; Lee, Danny C.

2000-01-01

Natural resource professionals are increasingly required to develop rigorous statistical models that relate environmental data to categorical responses data. Recent advances in the statistical and computing sciences have led to the development of sophisticated methods for parametric and nonparametric analysis of data with categorical responses. The statistical software package CATDAT was designed to make some of these relatively new and powerful techniques available to scientists. The CATDAT statistical package includes 4 analytical techniques: generalized logit modeling; binary classification tree; extended K-nearest neighbor classification; and modular neural network

Evolutionary Statistical Procedures

CERN Document Server

Baragona, Roberto; Poli, Irene

2011-01-01

This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions a

ActionScript 30 Design Patterns Object Oriented Programming Techniques

CERN Document Server

Sanders, William

2008-01-01

If you're an experienced Flash or Flex developer ready to tackle sophisticated programming techniques with ActionScript 3.0, this hands-on introduction to design patterns takes you step by step through the process. You learn about various types of design patterns and construct small abstract examples before trying your hand at building full-fledged working applications outlined in the book.

Statistical Methods for Environmental Pollution Monitoring

Energy Technology Data Exchange (ETDEWEB)

Gilbert, Richard O. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

1987-01-01

The application of statistics to environmental pollution monitoring studies requires a knowledge of statistical analysis methods particularly well suited to pollution data. This book fills that need by providing sampling plans, statistical tests, parameter estimation procedure techniques, and references to pertinent publications. Most of the statistical techniques are relatively simple, and examples, exercises, and case studies are provided to illustrate procedures. The book is logically divided into three parts. Chapters 1, 2, and 3 are introductory chapters. Chapters 4 through 10 discuss field sampling designs and Chapters 11 through 18 deal with a broad range of statistical analysis procedures. Some statistical techniques given here are not commonly seen in statistics book. For example, see methods for handling correlated data (Sections 4.5 and 11.12), for detecting hot spots (Chapter 10), and for estimating a confidence interval for the mean of a lognormal distribution (Section 13.2). Also, Appendix B lists a computer code that estimates and tests for trends over time at one or more monitoring stations using nonparametric methods (Chapters 16 and 17). Unfortunately, some important topics could not be included because of their complexity and the need to limit the length of the book. For example, only brief mention could be made of time series analysis using Box-Jenkins methods and of kriging techniques for estimating spatial and spatial-time patterns of pollution, although multiple references on these topics are provided. Also, no discussion of methods for assessing risks from environmental pollution could be included.

Statistics for lawyers

CERN Document Server

Finkelstein, Michael O

2015-01-01

This classic text, first published in 1990, is designed to introduce law students, law teachers, practitioners, and judges to the basic ideas of mathematical probability and statistics as they have been applied in the law. The third edition includes over twenty new sections, including the addition of timely topics, like New York City police stops, exonerations in death-sentence cases, projecting airline costs, and new material on various statistical techniques such as the randomized response survey technique, rare-events meta-analysis, competing risks, and negative binomial regression. The book consists of sections of exposition followed by real-world cases and case studies in which statistical data have played a role. The reader is asked to apply the theory to the facts, to calculate results (a hand calculator is sufficient), and to explore legal issues raised by quantitative findings. The authors' calculations and comments are given in the back of the book. As with previous editions, the cases and case stu...

Power system stabilizers based on modern control techniques

Energy Technology Data Exchange (ETDEWEB)

Malik, O P; Chen, G P; Zhang, Y; El-Metwally, K [Calgary Univ., AB (Canada). Dept. of Electrical and Computer Engineering

1994-12-31

Developments in digital technology have made it feasible to develop and implement improved controllers based on sophisticated control techniques. Power system stabilizers based on adaptive control, fuzzy logic and artificial networks are being developed. Each of these control techniques possesses unique features and strengths. In this paper, the relative performance of power systems stabilizers based on adaptive control, fuzzy logic and neural network, both in simulation studies and real time tests on a physical model of a power system, is presented and compared to that of a fixed parameter conventional power system stabilizer. (author) 16 refs., 45 figs., 3 tabs.

Analyzing the future climate change of Upper Blue Nile River basin using statistical downscaling techniques

Science.gov (United States)

Fenta Mekonnen, Dagnenet; Disse, Markus

2018-04-01

Climate change is becoming one of the most threatening issues for the world today in terms of its global context and its response to environmental and socioeconomic drivers. However, large uncertainties between different general circulation models (GCMs) and coarse spatial resolutions make it difficult to use the outputs of GCMs directly, especially for sustainable water management at regional scale, which introduces the need for downscaling techniques using a multimodel approach. This study aims (i) to evaluate the comparative performance of two widely used statistical downscaling techniques, namely the Long Ashton Research Station Weather Generator (LARS-WG) and the Statistical Downscaling Model (SDSM), and (ii) to downscale future climate scenarios of precipitation, maximum temperature (Tmax) and minimum temperature (Tmin) of the Upper Blue Nile River basin at finer spatial and temporal scales to suit further hydrological impact studies. The calibration and validation result illustrates that both downscaling techniques (LARS-WG and SDSM) have shown comparable and good ability to simulate the current local climate variables. Further quantitative and qualitative comparative performance evaluation was done by equally weighted and varying weights of statistical indexes for precipitation only. The evaluation result showed that SDSM using the canESM2 CMIP5 GCM was able to reproduce more accurate long-term mean monthly precipitation but LARS-WG performed best in capturing the extreme events and distribution of daily precipitation in the whole data range. Six selected multimodel CMIP3 GCMs, namely HadCM3, GFDL-CM2.1, ECHAM5-OM, CCSM3, MRI-CGCM2.3.2 and CSIRO-MK3 GCMs, were used for downscaling climate scenarios by the LARS-WG model. The result from the ensemble mean of the six GCM showed an increasing trend for precipitation, Tmax and Tmin. The relative change in precipitation ranged from 1.0 to 14.4 % while the change for mean annual Tmax may increase from 0.4 to 4.3 �

Improvement of Statistical Decisions under Parametric Uncertainty

Science.gov (United States)

Nechval, Nicholas A.; Nechval, Konstantin N.; Purgailis, Maris; Berzins, Gundars; Rozevskis, Uldis

2011-10-01

A large number of problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncertainty. Decision-making under uncertainty is a central problem in statistical inference, and has been formally studied in virtually all approaches to inference. The aim of the present paper is to show how the invariant embedding technique, the idea of which belongs to the authors, may be employed in the particular case of finding the improved statistical decisions under parametric uncertainty. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, an invariant embedding technique is independent of the choice of priors. It allows one to eliminate unknown parameters from the problem and to find the best invariant decision rule, which has smaller risk than any of the well-known decision rules. To illustrate the proposed technique, application examples are given.

Experimental design techniques in statistical practice a practical software-based approach

CERN Document Server

Gardiner, W P

1998-01-01

Provides an introduction to the diverse subject area of experimental design, with many practical and applicable exercises to help the reader understand, present and analyse the data. The pragmatic approach offers technical training for use of designs and teaches statistical and non-statistical skills in design and analysis of project studies throughout science and industry. Provides an introduction to the diverse subject area of experimental design and includes practical and applicable exercises to help understand, present and analyse the data Offers technical training for use of designs and teaches statistical and non-statistical skills in design and analysis of project studies throughout science and industry Discusses one-factor designs and blocking designs, factorial experimental designs, Taguchi methods and response surface methods, among other topics.

Purification through Emotions: The Role of Shame in Plato's "Sophist" 230B4-E5

Science.gov (United States)

Candiotto, Laura

2018-01-01

This article proposes an analysis of Plato's "Sophist" (230b4--e5) that underlines the bond between the logical and the emotional components of the Socratic "elenchus", with the aim of depicting the social valence of this philosophical practice. The use of emotions characterizing the 'elenctic' method described by Plato is…

Counting statistics in radioactivity measurements

International Nuclear Information System (INIS)

Martin, J.

1975-01-01

The application of statistical methods to radioactivity measurement problems is analyzed in several chapters devoted successively to: the statistical nature of radioactivity counts; the application to radioactive counting of two theoretical probability distributions, Poisson's distribution law and the Laplace-Gauss law; true counting laws; corrections related to the nature of the apparatus; statistical techniques in gamma spectrometry [fr

Developments in operator assistance techniques for nuclear power plant control and operation

International Nuclear Information System (INIS)

Poujol, A.; Papin, B.; Beltranda, G.; Soldermann, R.

1989-01-01

This paper describes an approach which has been developed in order to improve nuclear power plants control and monitoring in normal and abnormal situations. These developments take full advantage of the trend towards the computerization of control rooms in industrial continuous processes. This research program consists in a thorough exploration of different information processing techniques, ranking from the rather simple visual synthetization of informations on graphic displays to sophisticated Artificial Intelligence (AI) techniques. These techniques are put into application for the solving of man-machine interface problems in the different domains of plant operation

Multivariate Statistical Analysis of Orthogonal Mass Spectral Data for the Identification of Chemical Attribution Signatures of 3-Methylfentanyl

Energy Technology Data Exchange (ETDEWEB)

Mayer, B. P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Valdez, C. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); DeHope, A. J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Spackman, P. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sanner, R. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Martinez, H. P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Williams, A. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2016-11-28

Critical to many modern forensic investigations is the chemical attribution of the origin of an illegal drug. This process greatly relies on identification of compounds indicative of its clandestine or commercial production. The results of these studies can yield detailed information on method of manufacture, sophistication of the synthesis operation, starting material source, and final product. In the present work, chemical attribution signatures (CAS) associated with the synthesis of the analgesic 3- methylfentanyl, N-(3-methyl-1-phenethylpiperidin-4-yl)-N-phenylpropanamide, were investigated. Six synthesis methods were studied in an effort to identify and classify route-specific signatures. These methods were chosen to minimize the use of scheduled precursors, complicated laboratory equipment, number of overall steps, and demanding reaction conditions. Using gas and liquid chromatographies combined with mass spectrometric methods (GC-QTOF and LC-QTOF) in conjunction with inductivelycoupled plasma mass spectrometry (ICP-MS), over 240 distinct compounds and elements were monitored. As seen in our previous work with CAS of fentanyl synthesis the complexity of the resultant data matrix necessitated the use of multivariate statistical analysis. Using partial least squares discriminant analysis (PLS-DA), 62 statistically significant, route-specific CAS were identified. Statistical classification models using a variety of machine learning techniques were then developed with the ability to predict the method of 3-methylfentanyl synthesis from three blind crude samples generated by synthetic chemists without prior experience with these methods.

Evaluation of significantly modified water bodies in Vojvodina by using multivariate statistical techniques

Directory of Open Access Journals (Sweden)

Vujović Svetlana R.

2013-01-01

Full Text Available This paper illustrates the utility of multivariate statistical techniques for analysis and interpretation of water quality data sets and identification of pollution sources/factors with a view to get better information about the water quality and design of monitoring network for effective management of water resources. Multivariate statistical techniques, such as factor analysis (FA/principal component analysis (PCA and cluster analysis (CA, were applied for the evaluation of variations and for the interpretation of a water quality data set of the natural water bodies obtained during 2010 year of monitoring of 13 parameters at 33 different sites. FA/PCA attempts to explain the correlations between the observations in terms of the underlying factors, which are not directly observable. Factor analysis is applied to physico-chemical parameters of natural water bodies with the aim classification and data summation as well as segmentation of heterogeneous data sets into smaller homogeneous subsets. Factor loadings were categorized as strong and moderate corresponding to the absolute loading values of >0.75, 0.75-0.50, respectively. Four principal factors were obtained with Eigenvalues >1 summing more than 78 % of the total variance in the water data sets, which is adequate to give good prior information regarding data structure. Each factor that is significantly related to specific variables represents a different dimension of water quality. The first factor F1 accounting for 28 % of the total variance and represents the hydrochemical dimension of water quality. The second factor F2 accounting for 18% of the total variance and may be taken factor of water eutrophication. The third factor F3 accounting 17 % of the total variance and represents the influence of point sources of pollution on water quality. The fourth factor F4 accounting 13 % of the total variance and may be taken as an ecological dimension of water quality. Cluster analysis (CA is an

Time series prediction: statistical and neural techniques

Science.gov (United States)

Zahirniak, Daniel R.; DeSimio, Martin P.

1996-03-01

In this paper we compare the performance of nonlinear neural network techniques to those of linear filtering techniques in the prediction of time series. Specifically, we compare the results of using the nonlinear systems, known as multilayer perceptron and radial basis function neural networks, with the results obtained using the conventional linear Wiener filter, Kalman filter and Widrow-Hoff adaptive filter in predicting future values of stationary and non- stationary time series. Our results indicate the performance of each type of system is heavily dependent upon the form of the time series being predicted and the size of the system used. In particular, the linear filters perform adequately for linear or near linear processes while the nonlinear systems perform better for nonlinear processes. Since the linear systems take much less time to be developed, they should be tried prior to using the nonlinear systems when the linearity properties of the time series process are unknown.

Statistical techniques for sampling and monitoring natural resources

Science.gov (United States)

Hans T. Schreuder; Richard Ernst; Hugo Ramirez-Maldonado

2004-01-01

We present the statistical theory of inventory and monitoring from a probabilistic point of view. We start with the basics and show the interrelationships between designs and estimators illustrating the methods with a small artificial population as well as with a mapped realistic population. For such applications, useful open source software is given in Appendix 4....

Development of a technique for three-dimensional image reconstruction from emission computed tomograms (ECT)

International Nuclear Information System (INIS)

Gerischer, R.

1987-01-01

The described technique for three-dimensional image reconstruction from ECT sections is based on a simple procedure, which can be carried out with the aid of any standard-type computer used in nuclear medicine and requires no sophisticated arithmetic approach. (TRV) [de

Improved Statistical Fault Detection Technique and Application to Biological Phenomena Modeled by S-Systems.

Science.gov (United States)

Mansouri, Majdi; Nounou, Mohamed N; Nounou, Hazem N

2017-09-01

In our previous work, we have demonstrated the effectiveness of the linear multiscale principal component analysis (PCA)-based moving window (MW)-generalized likelihood ratio test (GLRT) technique over the classical PCA and multiscale principal component analysis (MSPCA)-based GLRT methods. The developed fault detection algorithm provided optimal properties by maximizing the detection probability for a particular false alarm rate (FAR) with different values of windows, and however, most real systems are nonlinear, which make the linear PCA method not able to tackle the issue of non-linearity to a great extent. Thus, in this paper, first, we apply a nonlinear PCA to obtain an accurate principal component of a set of data and handle a wide range of nonlinearities using the kernel principal component analysis (KPCA) model. The KPCA is among the most popular nonlinear statistical methods. Second, we extend the MW-GLRT technique to one that utilizes exponential weights to residuals in the moving window (instead of equal weightage) as it might be able to further improve fault detection performance by reducing the FAR using exponentially weighed moving average (EWMA). The developed detection method, which is called EWMA-GLRT, provides improved properties, such as smaller missed detection and FARs and smaller average run length. The idea behind the developed EWMA-GLRT is to compute a new GLRT statistic that integrates current and previous data information in a decreasing exponential fashion giving more weight to the more recent data. This provides a more accurate estimation of the GLRT statistic and provides a stronger memory that will enable better decision making with respect to fault detection. Therefore, in this paper, a KPCA-based EWMA-GLRT method is developed and utilized in practice to improve fault detection in biological phenomena modeled by S-systems and to enhance monitoring process mean. The idea behind a KPCA-based EWMA-GLRT fault detection algorithm is to

Exact distributions of two-sample rank statistics and block rank statistics using computer algebra

NARCIS (Netherlands)

Wiel, van de M.A.

1998-01-01

We derive generating functions for various rank statistics and we use computer algebra to compute the exact null distribution of these statistics. We present various techniques for reducing time and memory space used by the computations. We use the results to write Mathematica notebooks for

Statistical mechanics

CERN Document Server

Davidson, Norman

2003-01-01

Clear and readable, this fine text assists students in achieving a grasp of the techniques and limitations of statistical mechanics. The treatment follows a logical progression from elementary to advanced theories, with careful attention to detail and mathematical development, and is sufficiently rigorous for introductory or intermediate graduate courses.Beginning with a study of the statistical mechanics of ideal gases and other systems of non-interacting particles, the text develops the theory in detail and applies it to the study of chemical equilibrium and the calculation of the thermody

The nano-mechanical signature of Ultra High Performance Concrete by statistical nanoindentation techniques

International Nuclear Information System (INIS)

Sorelli, Luca; Constantinides, Georgios; Ulm, Franz-Josef; Toutlemonde, Francois

2008-01-01

Advances in engineering the microstructure of cementitious composites have led to the development of fiber reinforced Ultra High Performance Concretes (UHPC). The scope of this paper is twofold, first to characterize the nano-mechanical properties of the phases governing the UHPC microstructure by means of a novel statistical nanoindentation technique; then to upscale those nanoscale properties, by means of continuum micromechanics, to the macroscopic scale of engineering applications. In particular, a combined investigation of nanoindentation, scanning electron microscope (SEM) and X-ray Diffraction (XRD) indicates that the fiber-matrix transition zone is relatively defect free. On this basis, a four-level multiscale model with defect free interfaces allows to accurately determine the composite stiffness from the measured nano-mechanical properties. Besides evidencing the dominant role of high density calcium silicate hydrates and the stiffening effect of residual clinker, the suggested model may become a useful tool for further optimizing cement-based engineered composites

International Conference on Robust Statistics 2015

CERN Document Server

Basu, Ayanendranath; Filzmoser, Peter; Mukherjee, Diganta

2016-01-01

This book offers a collection of recent contributions and emerging ideas in the areas of robust statistics presented at the International Conference on Robust Statistics 2015 (ICORS 2015) held in Kolkata during 12–16 January, 2015. The book explores the applicability of robust methods in other non-traditional areas which includes the use of new techniques such as skew and mixture of skew distributions, scaled Bregman divergences, and multilevel functional data methods; application areas being circular data models and prediction of mortality and life expectancy. The contributions are of both theoretical as well as applied in nature. Robust statistics is a relatively young branch of statistical sciences that is rapidly emerging as the bedrock of statistical analysis in the 21st century due to its flexible nature and wide scope. Robust statistics supports the application of parametric and other inference techniques over a broader domain than the strictly interpreted model scenarios employed in classical statis...

Applied statistics for social and management sciences

CERN Document Server

Miah, Abdul Quader

2016-01-01

This book addresses the application of statistical techniques and methods across a wide range of disciplines. While its main focus is on the application of statistical methods, theoretical aspects are also provided as fundamental background information. It offers a systematic interpretation of results often discovered in general descriptions of methods and techniques such as linear and non-linear regression. SPSS is also used in all the application aspects. The presentation of data in the form of tables and graphs throughout the book not only guides users, but also explains the statistical application and assists readers in interpreting important features. The analysis of statistical data is presented consistently throughout the text. Academic researchers, practitioners and other users who work with statistical data will benefit from reading Applied Statistics for Social and Management Sciences. .

Analyzing the future climate change of Upper Blue Nile River basin using statistical downscaling techniques

Directory of Open Access Journals (Sweden)

D. Fenta Mekonnen

2018-04-01

Full Text Available Climate change is becoming one of the most threatening issues for the world today in terms of its global context and its response to environmental and socioeconomic drivers. However, large uncertainties between different general circulation models (GCMs and coarse spatial resolutions make it difficult to use the outputs of GCMs directly, especially for sustainable water management at regional scale, which introduces the need for downscaling techniques using a multimodel approach. This study aims (i to evaluate the comparative performance of two widely used statistical downscaling techniques, namely the Long Ashton Research Station Weather Generator (LARS-WG and the Statistical Downscaling Model (SDSM, and (ii to downscale future climate scenarios of precipitation, maximum temperature (Tmax and minimum temperature (Tmin of the Upper Blue Nile River basin at finer spatial and temporal scales to suit further hydrological impact studies. The calibration and validation result illustrates that both downscaling techniques (LARS-WG and SDSM have shown comparable and good ability to simulate the current local climate variables. Further quantitative and qualitative comparative performance evaluation was done by equally weighted and varying weights of statistical indexes for precipitation only. The evaluation result showed that SDSM using the canESM2 CMIP5 GCM was able to reproduce more accurate long-term mean monthly precipitation but LARS-WG performed best in capturing the extreme events and distribution of daily precipitation in the whole data range. Six selected multimodel CMIP3 GCMs, namely HadCM3, GFDL-CM2.1, ECHAM5-OM, CCSM3, MRI-CGCM2.3.2 and CSIRO-MK3 GCMs, were used for downscaling climate scenarios by the LARS-WG model. The result from the ensemble mean of the six GCM showed an increasing trend for precipitation, Tmax and Tmin. The relative change in precipitation ranged from 1.0 to 14.4 % while the change for mean annual Tmax may increase

Semiclassical analysis, Witten Laplacians, and statistical mechanis

CERN Document Server

Helffer, Bernard

2002-01-01

This important book explains how the technique of Witten Laplacians may be useful in statistical mechanics. It considers the problem of analyzing the decay of correlations, after presenting its origin in statistical mechanics. In addition, it compares the Witten Laplacian approach with other techniques, such as the transfer matrix approach and its semiclassical analysis. The author concludes by providing a complete proof of the uniform Log-Sobolev inequality. Contents: Witten Laplacians Approach; Problems in Statistical Mechanics with Discrete Spins; Laplace Integrals and Transfer Operators; S

A primer of multivariate statistics

CERN Document Server

Harris, Richard J

2014-01-01

Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why

Identification of heavy metals sources in the Mexico city atmosphere, using the proton induced x-ray analytical technique and multifactorial statistics techniques

International Nuclear Information System (INIS)

Hernandez M, B.

1997-01-01

The objectives of this work are: to identify the heavy metals present in the air, and its concentrations. To know the behavior from the polluting chemical elements to the long of an annual cycle corresponding to 1990, based on the concentrations of the same ones, obtained through the PIXE technique. To identify the suitable statistical methods to use to the data of metals concentration in form of total suspended particle (PST), found in this investigation. To relate the concentrations and the meteorological parameters considered to be able to suggest the possible pollution sources. In function of the obtained results, to serve as base to the decisions making and measures control that are planned by diverse institutions focused to the problem of the atmospheric pollution in the Metropolitan area of Mexico City (ZMCM). (Author)

Lectures on algebraic statistics

CERN Document Server

Drton, Mathias; Sullivant, Seth

2009-01-01

How does an algebraic geometer studying secant varieties further the understanding of hypothesis tests in statistics? Why would a statistician working on factor analysis raise open problems about determinantal varieties? Connections of this type are at the heart of the new field of "algebraic statistics". In this field, mathematicians and statisticians come together to solve statistical inference problems using concepts from algebraic geometry as well as related computational and combinatorial techniques. The goal of these lectures is to introduce newcomers from the different camps to algebraic statistics. The introduction will be centered around the following three observations: many important statistical models correspond to algebraic or semi-algebraic sets of parameters; the geometry of these parameter spaces determines the behaviour of widely used statistical inference procedures; computational algebraic geometry can be used to study parameter spaces and other features of statistical models.

State of the art of toshiba maintenance techniques for reactor internals

International Nuclear Information System (INIS)

Maekawa, Osamu; Hattori, Yasuhiro; Sudo, Akira

2002-01-01

As the number of aged plants increases, maintaining the integrity of the reactor pressure vessel and reactor internals in aged plants has become an essential issue to ensure continued stable operation and achieve higher plant operability. A major issue with regard to reactor internals is stress corrosion cracks (SCCs). Laser-applying techniques have many features suitable for preventive maintenance work on reactor internals. Toshiba has developed various laser-applying preventive maintenance techniques and accumulated considerable field experience utilizing these techniques in various aged plants. Moreover, in view of the importance of confirming the soundness of reactor internals in aged plants, Toshiba has developed and applied sophisticated nondestructive testing techniques for this purpose. (author)

Statistical analysis of non-homogeneous Poisson processes. Statistical processing of a particle multidetector

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

Business statistics for competitive advantage with Excel 2016 basics, model building, simulation and cases

CERN Document Server

Fraser, Cynthia

2016-01-01

The revised Fourth Edition of this popular textbook is redesigned with Excel 2016 to encourage business students to develop competitive advantages for use in their future careers as decision makers. Students learn to build models using logic and experience, produce statistics using Excel 2016 with shortcuts, and translate results into implications for decision makers. The textbook features new examples and assignments on global markets, including cases featuring Chipotle and Costco. Exceptional managers know that they can create competitive advantages by basing decisions on performance response under alternative scenarios, and managers need to understand how to use statistics to create such advantages. Statistics, from basic to sophisticated models, are illustrated with examples using real data such as students will encounter in their roles as managers. A number of examples focus on business in emerging global markets with particular emphasis on emerging markets in Latin America, China, and India. Results are...

Multiparametric statistics

CERN Document Server

Serdobolskii, Vadim Ivanovich

2007-01-01

This monograph presents mathematical theory of statistical models described by the essentially large number of unknown parameters, comparable with sample size but can also be much larger. In this meaning, the proposed theory can be called "essentially multiparametric". It is developed on the basis of the Kolmogorov asymptotic approach in which sample size increases along with the number of unknown parameters.This theory opens a way for solution of central problems of multivariate statistics, which up until now have not been solved. Traditional statistical methods based on the idea of an infinite sampling often break down in the solution of real problems, and, dependent on data, can be inefficient, unstable and even not applicable. In this situation, practical statisticians are forced to use various heuristic methods in the hope the will find a satisfactory solution.Mathematical theory developed in this book presents a regular technique for implementing new, more efficient versions of statistical procedures. ...

Library of sophisticated functions for analysis of nuclear spectra

Science.gov (United States)

Morháč, Miroslav; Matoušek, Vladislav

2009-10-01

In the paper we present compact library for analysis of nuclear spectra. The library consists of sophisticated functions for background elimination, smoothing, peak searching, deconvolution, and peak fitting. The functions can process one- and two-dimensional spectra. The software described in the paper comprises a number of conventional as well as newly developed methods needed to analyze experimental data. Program summaryProgram title: SpecAnalysLib 1.1 Catalogue identifier: AEDZ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDZ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 42 154 No. of bytes in distributed program, including test data, etc.: 2 379 437 Distribution format: tar.gz Programming language: C++ Computer: Pentium 3 PC 2.4 GHz or higher, Borland C++ Builder v. 6. A precompiled Windows version is included in the distribution package Operating system: Windows 32 bit versions RAM: 10 MB Word size: 32 bits Classification: 17.6 Nature of problem: The demand for advanced highly effective experimental data analysis functions is enormous. The library package represents one approach to give the physicists the possibility to use the advanced routines simply by calling them from their own programs. SpecAnalysLib is a collection of functions for analysis of one- and two-parameter γ-ray spectra, but they can be used for other types of data as well. The library consists of sophisticated functions for background elimination, smoothing, peak searching, deconvolution, and peak fitting. Solution method: The algorithms of background estimation are based on Sensitive Non-linear Iterative Peak (SNIP) clipping algorithm. The smoothing algorithms are based on the convolution of the original data with several types of filters and algorithms based on discrete

Statistical approach for selection of biologically informative genes.

Science.gov (United States)

Das, Samarendra; Rai, Anil; Mishra, D C; Rai, Shesh N

2018-05-20

Selection of informative genes from high dimensional gene expression data has emerged as an important research area in genomics. Many gene selection techniques have been proposed so far are either based on relevancy or redundancy measure. Further, the performance of these techniques has been adjudged through post selection classification accuracy computed through a classifier using the selected genes. This performance metric may be statistically sound but may not be biologically relevant. A statistical approach, i.e. Boot-MRMR, was proposed based on a composite measure of maximum relevance and minimum redundancy, which is both statistically sound and biologically relevant for informative gene selection. For comparative evaluation of the proposed approach, we developed two biological sufficient criteria, i.e. Gene Set Enrichment with QTL (GSEQ) and biological similarity score based on Gene Ontology (GO). Further, a systematic and rigorous evaluation of the proposed technique with 12 existing gene selection techniques was carried out using five gene expression datasets. This evaluation was based on a broad spectrum of statistically sound (e.g. subject classification) and biological relevant (based on QTL and GO) criteria under a multiple criteria decision-making framework. The performance analysis showed that the proposed technique selects informative genes which are more biologically relevant. The proposed technique is also found to be quite competitive with the existing techniques with respect to subject classification and computational time. Our results also showed that under the multiple criteria decision-making setup, the proposed technique is best for informative gene selection over the available alternatives. Based on the proposed approach, an R Package, i.e. BootMRMR has been developed and available at https://cran.r-project.org/web/packages/BootMRMR. This study will provide a practical guide to select statistical techniques for selecting informative genes

Techniques involving extreme environment, nondestructive techniques, computer methods in metals research, and data analysis

International Nuclear Information System (INIS)

Bunshah, R.F.

1976-01-01

A number of different techniques which range over several different aspects of materials research are covered in this volume. They are concerned with property evaluation of 4 0 K and below, surface characterization, coating techniques, techniques for the fabrication of composite materials, computer methods, data evaluation and analysis, statistical design of experiments and non-destructive test techniques. Topics covered in this part include internal friction measurements; nondestructive testing techniques; statistical design of experiments and regression analysis in metallurgical research; and measurement of surfaces of engineering materials

A Matlab user interface for the statistically assisted fluid registration algorithm and tensor-based morphometry

Science.gov (United States)

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.

Jsub(Ic)-testing of A-533 B - statistical evaluation of some different testing techniques

International Nuclear Information System (INIS)

Nilsson, F.

1978-01-01

The purpose of the present study was to compare statistically some different methods for the evaluation of fracture toughness of the nuclear reactor material A-533 B. Since linear elastic fracture mechanics is not applicable to this material at the interesting temperature (275 0 C), the so-called Jsub(Ic) testing method was employed. Two main difficulties are inherent in this type of testing. The first one is to determine the quantity J as a function of the deflection of the three-point bend specimens used. Three different techniques were used, the first two based on the experimentally observed input of energy to the specimen and the third employing finite element calculations. The second main problem is to determine the point when crack growth begins. For this, two methods were used, a direct electrical method and the indirect R-curve method. A total of forty specimens were tested at two laboratories. No statistically significant different results were obtained from the respective laboratories. The three methods of calculating J yielded somewhat different results, although the discrepancy was small. Also the two methods of determination of the growth initiation point yielded consistent results. The R-curve method, however, exhibited a larger uncertainty as measured by the standard deviation. The resulting Jsub(Ic) value also agreed well with earlier presented results. The relative standard deviation was of the order of 25%, which is quite small for this type of experiment. (author)

Engaging with the Art & Science of Statistics

Science.gov (United States)

Peters, Susan A.

2010-01-01

How can statistics clearly be mathematical and yet distinct from mathematics? The answer lies in the reality that statistics is both an art and a science, and both aspects are important for teaching and learning statistics. Statistics is a mathematical science in that it applies mathematical theories and techniques. Mathematics provides the…

Application of multivariate statistical techniques in the water quality assessment of Danube river, Serbia

Directory of Open Access Journals (Sweden)

Voza Danijela

2015-12-01

Full Text Available The aim of this article is to evaluate the quality of the Danube River in its course through Serbia as well as to demonstrate the possibilities for using three statistical methods: Principal Component Analysis (PCA, Factor Analysis (FA and Cluster Analysis (CA in the surface water quality management. Given that the Danube is an important trans-boundary river, thorough water quality monitoring by sampling at different distances during shorter and longer periods of time is not only ecological, but also a political issue. Monitoring was carried out at monthly intervals from January to December 2011, at 17 sampling sites. The obtained data set was treated by multivariate techniques in order, firstly, to identify the similarities and differences between sampling periods and locations, secondly, to recognize variables that affect the temporal and spatial water quality changes and thirdly, to present the anthropogenic impact on water quality parameters.

Post-fire debris flow prediction in Western United States: Advancements based on a nonparametric statistical technique

Science.gov (United States)

Nikolopoulos, E. I.; Destro, E.; Bhuiyan, M. A. E.; Borga, M., Sr.; Anagnostou, E. N.

2017-12-01

Fire disasters affect modern societies at global scale inducing significant economic losses and human casualties. In addition to their direct impacts they have various adverse effects on hydrologic and geomorphologic processes of a region due to the tremendous alteration of the landscape characteristics (vegetation, soil properties etc). As a consequence, wildfires often initiate a cascade of hazards such as flash floods and debris flows that usually follow the occurrence of a wildfire thus magnifying the overall impact in a region. Post-fire debris flows (PFDF) is one such type of hazards frequently occurring in Western United States where wildfires are a common natural disaster. Prediction of PDFD is therefore of high importance in this region and over the last years a number of efforts from United States Geological Survey (USGS) and National Weather Service (NWS) have been focused on the development of early warning systems that will help mitigate PFDF risk. This work proposes a prediction framework that is based on a nonparametric statistical technique (random forests) that allows predicting the occurrence of PFDF at regional scale with a higher degree of accuracy than the commonly used approaches that are based on power-law thresholds and logistic regression procedures. The work presented is based on a recently released database from USGS that reports a total of 1500 storms that triggered and did not trigger PFDF in a number of fire affected catchments in Western United States. The database includes information on storm characteristics (duration, accumulation, max intensity etc) and other auxiliary information of land surface properties (soil erodibility index, local slope etc). Results show that the proposed model is able to achieve a satisfactory prediction accuracy (threat score > 0.6) superior of previously published prediction frameworks highlighting the potential of nonparametric statistical techniques for development of PFDF prediction systems.

Introductory statistical inference

CERN Document Server

Mukhopadhyay, Nitis

2014-01-01

This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques.Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate topics. Introductory Statistical Inference studies multivariate random variables, exponential families of dist

Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: an example from a vertigo phase III study with longitudinal count data as primary endpoint.

Science.gov (United States)

Adrion, Christine; Mansmann, Ulrich

2012-09-10

within the SAP in a transparent way when structuring the primary analysis, sensitivity or ancillary analyses, and specific analyses for secondary endpoints. The mean logarithmic score and DIC discriminate well between different model scenarios. It becomes obvious that the naive choice of a conventional random effects Poisson model is often inappropriate for real-life count data. The findings are used to specify an appropriate mixed model employed in the sensitivity analyses of an ongoing phase III trial. The proposed Bayesian methods are not only appealing for inference but notably provide a sophisticated insight into different aspects of model performance, such as forecast verification or calibration checks, and can be applied within the model selection process. The mean of the logarithmic score is a robust tool for model ranking and is not sensitive to sample size. Therefore, these Bayesian model selection techniques offer helpful decision support for shaping sensitivity and ancillary analyses in a statistical analysis plan of a clinical trial with longitudinal count data as the primary endpoint.

Development of statistical and analytical techniques for use in national quality control schemes for steroid hormones

International Nuclear Information System (INIS)

Wilson, D.W.; Gaskell, S.J.; Fahmy, D.R.; Joyce, B.G.; Groom, G.V.; Griffiths, K.; Kemp, K.W.; Nix, A.B.J.; Rowlands, R.J.

1979-01-01

Adopting the rationale that the improvement of intra-laboratory performance of immunometric assays will enable the assessment of national QC schemes to become more meaningful, the group of participating laboratories has developed statistical and analytical techniques for the improvement of accuracy, precision and monitoring of error for the determination of steroid hormones. These developments are now described and their relevance to NQC schemes discussed. Attention has been focussed on some of the factors necessary for improving standards of quality in immunometric assays and their relevance to laboratories participating in NQC schemes as described. These have included the 'accuracy', precision and robustness of assay procedures as well as improved methods for internal quality control. (Auth.)

[Comments on] Statistical techniques for the development and application of SYVAC. (Document by Stephen Howe Ltd.)

International Nuclear Information System (INIS)

Beale, E.M.L.

1983-05-01

The Department of the Environment has embarked on a programme to develop computer models to help with assessment of sites suitable for the disposal of nuclear wastes. The first priority is to produce a system, based on the System Variability Analysis Code (SYVAC) obtained from Atomic Energy of Canada Ltd., suitable for assessing radioactive waste disposal in land repositories containing non heat producing wastes from typical UK sources. The requirements of the SYVAC system development were so diverse that each portion of the development was contracted to a different company. Scicon are responsible for software coordination, system integration and user interface. Their present report contains comments on 'Statistical techniques for the development and application of SYVAC'. (U.K.)

Search for a standard Higgs boson in the WH associated production channel with the final statistics of the Tevatron DO experiment

International Nuclear Information System (INIS)

Miconi, F.

2012-01-01

Higgs mechanism, introduced in 1964, gives a satisfactory solution to a major problem of the standard model of elementary particles: the origin of the mass. It predicts the existence of the Higgs scalar boson, which mass is not defined by the theory and which has not been discovered experimentally yet (June 2012). The Tevatron, a hadron accelerator based at Fermi National Accelerator Laboratory near Chicago, took data with its two multi-purpose detectors CDF and DO since 1983 up to september 2011. Leaving about 10 fb -1 of statistics to analyze. Associated production of Higgs (H) and vector gauge boson (W) is the main search channel for a light standard Higgs boson. A light Higgs boson is expected to decay in a pair of beauty quarks. Using data collected by DO, we are looking for this production mode taking advantage of sophisticated techniques to improve the signal sensitivity like b-jet identification and multivariate discriminating factors. In the end, a statistical approach allows us to set an upper limit on the ratio between the observed (resp. expected) Higgs production and its theoretical cross section. The results obtained in the WH channel using 9.7 fb -1 at DO is 3.15 (resp. 3.96) for a 115 GeV/c 2 Higgs boson. (author)

A statistical manual for chemists

CERN Document Server

Bauer, Edward

1971-01-01

A Statistical Manual for Chemists, Second Edition presents simple and fast statistical tools for data analysis of working chemists. This edition is organized into nine chapters and begins with an overview of the fundamental principles of the statistical techniques used in experimental data analysis. The subsequent chapters deal with the concept of statistical average, experimental design, and analysis of variance. The discussion then shifts to control charts, with particular emphasis on variable charts that are more useful to chemists and chemical engineers. A chapter focuses on the effect

Evaluation of Anomaly Detection Techniques for SCADA Communication Resilience

OpenAIRE

Shirazi, Syed Noor Ul Hassan; Gouglidis, Antonios; Syeda, Kanza Noor; Simpson, Steven; Mauthe, Andreas Ulrich; Stephanakis, Ioannis M.; Hutchison, David

2016-01-01

Attacks on critical infrastructures’ Supervisory Control and Data Acquisition (SCADA) systems are beginning to increase. They are often initiated by highly skilled attackers, who are capable of deploying sophisticated attacks to exfiltrate data or even to cause physical damage. In this paper, we rehearse the rationale for protecting against cyber attacks and evaluate a set of Anomaly Detection (AD) techniques in detecting attacks by analysing traffic captured in a SCADA network. For this purp...

Intuitive introductory statistics

CERN Document Server

Wolfe, Douglas A

2017-01-01

This textbook is designed to give an engaging introduction to statistics and the art of data analysis. The unique scope includes, but also goes beyond, classical methodology associated with the normal distribution. What if the normal model is not valid for a particular data set? This cutting-edge approach provides the alternatives. It is an introduction to the world and possibilities of statistics that uses exercises, computer analyses, and simulations throughout the core lessons. These elementary statistical methods are intuitive. Counting and ranking features prominently in the text. Nonparametric methods, for instance, are often based on counts and ranks and are very easy to integrate into an introductory course. The ease of computation with advanced calculators and statistical software, both of which factor into this text, allows important techniques to be introduced earlier in the study of statistics. This book's novel scope also includes measuring symmetry with Walsh averages, finding a nonp...

Statistical fluctuations of an ocean surface inferred from shoes and ships

Science.gov (United States)

Lerche, Ian; Maubeuge, Frédéric

1995-12-01

This paper shows that it is possible to roughly estimate some ocean properties using simple time-dependent statistical models of ocean fluctuations. Based on a real incident, the loss by a vessel of a Nike shoes container in the North Pacific Ocean, a statistical model was tested on data sets consisting of the Nike shoes found by beachcombers a few months later. This statistical treatment of the shoes' motion allows one to infer velocity trends of the Pacific Ocean, together with their fluctuation strengths. The idea is to suppose that there is a mean bulk flow speed that can depend on location on the ocean surface and time. The fluctuations of the surface flow speed are then treated as statistically random. The distribution of shoes is described in space and time using Markov probability processes related to the mean and fluctuating ocean properties. The aim of the exercise is to provide some of the properties of the Pacific Ocean that are otherwise calculated using a sophisticated numerical model, OSCURS, where numerous data are needed. Relevant quantities are sharply estimated, which can be useful to (1) constrain output results from OSCURS computations, and (2) elucidate the behavior patterns of ocean flow characteristics on long time scales.

Quantitative and statistical approaches to geography a practical manual

CERN Document Server

Matthews, John A

2013-01-01

Quantitative and Statistical Approaches to Geography: A Practical Manual is a practical introduction to some quantitative and statistical techniques of use to geographers and related scientists. This book is composed of 15 chapters, each begins with an outline of the purpose and necessary mechanics of a technique or group of techniques and is concluded with exercises and the particular approach adopted. These exercises aim to enhance student's ability to use the techniques as part of the process by which sound judgments are made according to scientific standards while tackling complex problems. After a brief introduction to the principles of quantitative and statistical geography, this book goes on dealing with the topics of measures of central tendency; probability statements and maps; the problem of time-dependence, time-series analysis, non-normality, and data transformations; and the elements of sampling methodology. Other chapters cover the confidence intervals and estimation from samples, statistical hy...

"SOCRATICS" AS ADDRESSES OF ISOCRATES’ EPIDEICTIC SPEECHES (Against the Sophists, Encomium of Helen, Busiris

Directory of Open Access Journals (Sweden)

Anna Usacheva

2012-06-01

Full Text Available This article analyses the three epideictic orations of Isocrates which are in themselves a precious testimony of the quality of intellectual life at the close of the fourth century before Christ. To this period belong also the Socratics who are generally seen as an important link between Socrates and Plato. The author of this article proposes a more productive approach to the study of Antisthenes, Euclid of Megara and other so-called Socratics, revealing them not as independent thinkers but rather as adherents of the sophistic school and also as teachers, thereby, including them among those who took part in the educative activity of their time

Method for statistical data analysis of multivariate observations

CERN Document Server

Gnanadesikan, R

1997-01-01

A practical guide for multivariate statistical techniques-- now updated and revised In recent years, innovations in computer technology and statistical methodologies have dramatically altered the landscape of multivariate data analysis. This new edition of Methods for Statistical Data Analysis of Multivariate Observations explores current multivariate concepts and techniques while retaining the same practical focus of its predecessor. It integrates methods and data-based interpretations relevant to multivariate analysis in a way that addresses real-world problems arising in many areas of inte

An introduction to statistical computing a simulation-based approach

CERN Document Server

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

Statistics for nuclear engineers and scientists. Part 1. Basic statistical inference

Energy Technology Data Exchange (ETDEWEB)

Beggs, W.J.

1981-02-01

This report is intended for the use of engineers and scientists working in the nuclear industry, especially at the Bettis Atomic Power Laboratory. It serves as the basis for several Bettis in-house statistics courses. The objectives of the report are to introduce the reader to the language and concepts of statistics and to provide a basic set of techniques to apply to problems of the collection and analysis of data. Part 1 covers subjects of basic inference. The subjects include: descriptive statistics; probability; simple inference for normally distributed populations, and for non-normal populations as well; comparison of two populations; the analysis of variance; quality control procedures; and linear regression analysis.

Playing at Statistical Mechanics

Science.gov (United States)

Clark, Paul M.; And Others

1974-01-01

Discussed are the applications of counting techniques of a sorting game to distributions and concepts in statistical mechanics. Included are the following distributions: Fermi-Dirac, Bose-Einstein, and most probable. (RH)

Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera: Tropiduchidae) habitat and population densities.

Science.gov (United States)

Al-Kindi, Khalifa M; Kwan, Paul; R Andrew, Nigel; Welch, Mitchell

2017-01-01

In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus . An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.

Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera: Tropiduchidae habitat and population densities

Directory of Open Access Journals (Sweden)

Khalifa M. Al-Kindi

2017-08-01

Full Text Available In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus. An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.

Statistical reconstruction for cosmic ray muon tomography.

Science.gov (United States)

Schultz, Larry J; Blanpied, Gary S; Borozdin, Konstantin N; Fraser, Andrew M; Hengartner, Nicolas W; Klimenko, Alexei V; Morris, Christopher L; Orum, Chris; Sossong, Michael J

2007-08-01

Highly penetrating cosmic ray muons constantly shower the earth at a rate of about 1 muon per cm2 per minute. We have developed a technique which exploits the multiple Coulomb scattering of these particles to perform nondestructive inspection without the use of artificial radiation. In prior work [1]-[3], we have described heuristic methods for processing muon data to create reconstructed images. In this paper, we present a maximum likelihood/expectation maximization tomographic reconstruction algorithm designed for the technique. This algorithm borrows much from techniques used in medical imaging, particularly emission tomography, but the statistics of muon scattering dictates differences. We describe the statistical model for multiple scattering, derive the reconstruction algorithm, and present simulated examples. We also propose methods to improve the robustness of the algorithm to experimental errors and events departing from the statistical model.

The use of adaptive statistical iterative reconstruction (ASiR) technique in evaluation of patients with cervical spine trauma: impact on radiation dose reduction and image quality.

Science.gov (United States)

Patro, Satya N; Chakraborty, Santanu; Sheikh, Adnan

2016-01-01

The aim of this study was to evaluate the impact of adaptive statistical iterative reconstruction (ASiR) technique on the image quality and radiation dose reduction. The comparison was made with the traditional filtered back projection (FBP) technique. We retrospectively reviewed 78 patients, who underwent cervical spine CT for blunt cervical trauma between 1 June 2010 and 30 November 2010. 48 patients were imaged using traditional FBP technique and the remaining 30 patients were imaged using the ASiR technique. The patient demographics, radiation dose, objective image signal and noise were recorded; while subjective noise, sharpness, diagnostic acceptability and artefacts were graded by two radiologists blinded to the techniques. We found that the ASiR technique was able to reduce the volume CT dose index, dose-length product and effective dose by 36%, 36.5% and 36.5%, respectively, compared with the FBP technique. There was no significant difference in the image noise (p = 0.39), signal (p = 0.82) and signal-to-noise ratio (p = 0.56) between the groups. The subjective image quality was minimally better in the ASiR group but not statistically significant. There was excellent interobserver agreement on the subjective image quality and diagnostic acceptability for both groups. The use of ASiR technique allowed approximately 36% radiation dose reduction in the evaluation of cervical spine without degrading the image quality. The present study highlights that the ASiR technique is extremely helpful in reducing the patient radiation exposure while maintaining the image quality. It is highly recommended to utilize this novel technique in CT imaging of different body regions.

Automatic detection of health changes using statistical process control techniques on measured transfer times of elderly.

Science.gov (United States)

Baldewijns, Greet; Luca, Stijn; Nagels, William; Vanrumste, Bart; Croonenborghs, Tom

2015-01-01

It has been shown that gait speed and transfer times are good measures of functional ability in elderly. However, data currently acquired by systems that measure either gait speed or transfer times in the homes of elderly people require manual reviewing by healthcare workers. This reviewing process is time-consuming. To alleviate this burden, this paper proposes the use of statistical process control methods to automatically detect both positive and negative changes in transfer times. Three SPC techniques: tabular CUSUM, standardized CUSUM and EWMA, known for their ability to detect small shifts in the data, are evaluated on simulated transfer times. This analysis shows that EWMA is the best-suited method with a detection accuracy of 82% and an average detection time of 9.64 days.

Statistical inference a short course

CERN Document Server

Panik, Michael J

2012-01-01

A concise, easily accessible introduction to descriptive and inferential techniques Statistical Inference: A Short Course offers a concise presentation of the essentials of basic statistics for readers seeking to acquire a working knowledge of statistical concepts, measures, and procedures. The author conducts tests on the assumption of randomness and normality, provides nonparametric methods when parametric approaches might not work. The book also explores how to determine a confidence interval for a population median while also providing coverage of ratio estimation, randomness, and causal

Statistics for Finance

DEFF Research Database (Denmark)

Lindström, Erik; Madsen, Henrik; Nielsen, Jan Nygaard

Statistics for Finance develops students’ professional skills in statistics with applications in finance. Developed from the authors’ courses at the Technical University of Denmark and Lund University, the text bridges the gap between classical, rigorous treatments of financial mathematics...... that rarely connect concepts to data and books on econometrics and time series analysis that do not cover specific problems related to option valuation. The book discusses applications of financial derivatives pertaining to risk assessment and elimination. The authors cover various statistical...... and mathematical techniques, including linear and nonlinear time series analysis, stochastic calculus models, stochastic differential equations, Itō’s formula, the Black–Scholes model, the generalized method-of-moments, and the Kalman filter. They explain how these tools are used to price financial derivatives...

A Multidisciplinary Approach for Teaching Statistics and Probability

Science.gov (United States)

Rao, C. Radhakrishna

1971-01-01

The author presents a syllabus for an introductory (first year after high school) course in statistics and probability and some methods of teaching statistical techniques. The description comes basically from the procedures used at the Indian Statistical Institute, Calcutta. (JG)

DMA Friends: the mobilization of statistics in a media innovation experiment in the museum sector

Directory of Open Access Journals (Sweden)

GERMAN Ronan

2016-07-01

Full Text Available On January 23, 2013, the Dallas Museum of Art (DMA returned to free general admission. This announcement coincided with the official launching of two programs: DMA Friends, a loyalty program, and DMA Partners, a membership program which is free of charge. The aim of this article is to propose an analysis, at the crossroads of media semiology, of political science and the historical sociology of statistical rationality, with a view to studying the ways in which the DMA Friends program designers have mobilized the statistical argument to justify the soundness of their approach. In order to do so, they leaned on a range of media forms generated by a sophisticated techno-semiotic apparatus which represents, in a statistical form, the behavior of visitors inside the museum. The program (and the whole instrumentation that sustains it illustrates a media innovation experiment in the museum sector that questions the ways by which the statistical work is mediated according to the communicational situations in which it is mobilized and enhanced.

Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques

Science.gov (United States)

Gulgundi, Mohammad Shahid; Shetty, Amba

2018-03-01

Groundwater quality deterioration due to anthropogenic activities has become a subject of prime concern. The objective of the study was to assess the spatial and temporal variations in groundwater quality and to identify the sources in the western half of the Bengaluru city using multivariate statistical techniques. Water quality index rating was calculated for pre and post monsoon seasons to quantify overall water quality for human consumption. The post-monsoon samples show signs of poor quality in drinking purpose compared to pre-monsoon. Cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA) were applied to the groundwater quality data measured on 14 parameters from 67 sites distributed across the city. Hierarchical cluster analysis (CA) grouped the 67 sampling stations into two groups, cluster 1 having high pollution and cluster 2 having lesser pollution. Discriminant analysis (DA) was applied to delineate the most meaningful parameters accounting for temporal and spatial variations in groundwater quality of the study area. Temporal DA identified pH as the most important parameter, which discriminates between water quality in the pre-monsoon and post-monsoon seasons and accounts for 72% seasonal assignation of cases. Spatial DA identified Mg, Cl and NO3 as the three most important parameters discriminating between two clusters and accounting for 89% spatial assignation of cases. Principal component analysis was applied to the dataset obtained from the two clusters, which evolved three factors in each cluster, explaining 85.4 and 84% of the total variance, respectively. Varifactors obtained from principal component analysis showed that groundwater quality variation is mainly explained by dissolution of minerals from rock water interactions in the aquifer, effect of anthropogenic activities and ion exchange processes in water.

GIS-Based bivariate statistical techniques for groundwater potential ...

Indian Academy of Sciences (India)

24

This study shows the potency of two GIS-based data driven bivariate techniques namely ... In the view of these weaknesses , there is a strong requirement for reassessment of .... Font color: Text 1, Not Expanded by / Condensed by , ...... West Bengal (India) using remote sensing, geographical information system and multi-.

Statistical and physical content of low-energy photons in nuclear medicine imaging

International Nuclear Information System (INIS)

Gagnon, D.; Pouliot, N.; Laperriere, L.; Harel, F.; Gregoire, J.; Arsenault, A.

1990-01-01

Limit in the energy resolution of present gamma camera technology prevents a total rejection of Compton events: inclusion of bad photons in the image is inescapable. Various methods acquiring data over a large portion of the spectrum have already been described. This paper investigates the usefulness of low energy photons using statistical and physical models. Holospectral Imaging, for instance, exploits correlation between energy frames to build an information related transformation optimizing primary photon image. One can also use computer simulation to show that a portion of low energy photons is detected at the same location (pixel) as pure primary photons. These events are for instance: photons undergoing scatter interaction in the crystal; photons undergoing a small angle backscatter or forwardscatter interaction in the medium, photons backscattered by the Pyrex into the crystal. For a 140 keV source in 10 cm of water and a 1/4 inch thick crystal, more than 6% of all the photons detected do not have the primary energy and still are located in the right 4 mm pixel. Similarly, it is possible to show that more than 5% of all the photons detected at 140 keV deposit their energy in more than one pixel. These results give additional support to techniques considering low energy photons and more sophisticated ways to segregate between good and bad events

Reactive polymer coatings: A robust platform towards sophisticated surface engineering for biotechnology

Science.gov (United States)

Chen, Hsien-Yeh

Functionalized poly(p-xylylenes) or so-called reactive polymers can be synthesized via chemical vapor deposition (CVD) polymerization. The resulting ultra-thin coatings are pinhole-free and can be conformally deposited to a wide range of substrates and materials. More importantly, the equipped functional groups can served as anchoring sites for tailoring the surface properties, making these reactive coatings a robust platform that can deal with sophisticated challenges faced in biointerfaces. In this work presented herein, surface coatings presenting various functional groups were prepared by CVD process. Such surfaces include aldehyde-functionalized coating to precisely immobilize saccharide molecules onto well-defined areas and alkyne-functionalized coating to click azide-modified molecules via Huisgen 1,3-dipolar cycloaddition reaction. Moreover, CVD copolymerization has been conducted to prepare multifunctional coatings and their specific functions were demonstrated by the immobilization of biotin and NHS-ester molecules. By using a photodefinable coating, polyethylene oxides were immobilized onto a wide range of substrates through photo-immobilization. Spatially controlled protein resistant properties were characterized by selective adsorption of fibrinogen and bovine serum albumin as model systems. Alternatively, surface initiator coatings were used for polymer graftings of polyethylene glycol) methyl ether methacrylate, and the resultant protein- and cell- resistant properties were characterized by adsorption of kinesin motor proteins, fibrinogen, and murine fibroblasts (NIH3T3). Accessibility of reactive coatings within confined microgeometries was systematically studied, and the preparation of homogeneous polymer thin films within the inner surface of microchannels was demonstrated. Moreover, these advanced coatings were applied to develop a dry adhesion process for microfluidic devices. This process provides (i) excellent bonding strength, (ii) extended

A sophisticated simulation for the fracture behavior of concrete material using XFEM

Science.gov (United States)

Zhai, Changhai; Wang, Xiaomin; Kong, Jingchang; Li, Shuang; Xie, Lili

2017-10-01

The development of a powerful numerical model to simulate the fracture behavior of concrete material has long been one of the dominant research areas in earthquake engineering. A reliable model should be able to adequately represent the discontinuous characteristics of cracks and simulate various failure behaviors under complicated loading conditions. In this paper, a numerical formulation, which incorporates a sophisticated rigid-plastic interface constitutive model coupling cohesion softening, contact, friction and shear dilatation into the XFEM, is proposed to describe various crack behaviors of concrete material. An effective numerical integration scheme for accurately assembling the contribution to the weak form on both sides of the discontinuity is introduced. The effectiveness of the proposed method has been assessed by simulating several well-known experimental tests. It is concluded that the numerical method can successfully capture the crack paths and accurately predict the fracture behavior of concrete structures. The influence of mode-II parameters on the mixed-mode fracture behavior is further investigated to better determine these parameters.

Statistical modeling for degradation data

CERN Document Server

Lio, Yuhlong; Ng, Hon; Tsai, Tzong-Ru

2017-01-01

This book focuses on the statistical aspects of the analysis of degradation data. In recent years, degradation data analysis has come to play an increasingly important role in different disciplines such as reliability, public health sciences, and finance. For example, information on products’ reliability can be obtained by analyzing degradation data. In addition, statistical modeling and inference techniques have been developed on the basis of different degradation measures. The book brings together experts engaged in statistical modeling and inference, presenting and discussing important recent advances in degradation data analysis and related applications. The topics covered are timely and have considerable potential to impact both statistics and reliability engineering.

Computational statistics handbook with Matlab

CERN Document Server

Martinez, Wendy L

2007-01-01

Prefaces Introduction What Is Computational Statistics? An Overview of the Book Probability Concepts Introduction Probability Conditional Probability and Independence Expectation Common Distributions Sampling Concepts Introduction Sampling Terminology and Concepts Sampling Distributions Parameter Estimation Empirical Distribution Function Generating Random Variables Introduction General Techniques for Generating Random Variables Generating Continuous Random Variables Generating Discrete Random Variables Exploratory Data Analysis Introduction Exploring Univariate Data Exploring Bivariate and Trivariate Data Exploring Multidimensional Data Finding Structure Introduction Projecting Data Principal Component Analysis Projection Pursuit EDA Independent Component Analysis Grand Tour Nonlinear Dimensionality Reduction Monte Carlo Methods for Inferential Statistics Introduction Classical Inferential Statistics Monte Carlo Methods for Inferential Statist...

Validation of non-stationary precipitation series for site-specific impact assessment: comparison of two statistical downscaling techniques

Science.gov (United States)

Mullan, Donal; Chen, Jie; Zhang, Xunchang John

2016-02-01

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

Two statistics for evaluating parameter identifiability and error reduction

Science.gov (United States)

Doherty, John; Hunt, Randall J.

2009-01-01

Two statistics are presented that can be used to rank input parameters utilized by a model in terms of their relative identifiability based on a given or possible future calibration dataset. Identifiability is defined here as the capability of model calibration to constrain parameters used by a model. Both statistics require that the sensitivity of each model parameter be calculated for each model output for which there are actual or presumed field measurements. Singular value decomposition (SVD) of the weighted sensitivity matrix is then undertaken to quantify the relation between the parameters and observations that, in turn, allows selection of calibration solution and null spaces spanned by unit orthogonal vectors. The first statistic presented, "parameter identifiability", is quantitatively defined as the direction cosine between a parameter and its projection onto the calibration solution space. This varies between zero and one, with zero indicating complete non-identifiability and one indicating complete identifiability. The second statistic, "relative error reduction", indicates the extent to which the calibration process reduces error in estimation of a parameter from its pre-calibration level where its value must be assigned purely on the basis of prior expert knowledge. This is more sophisticated than identifiability, in that it takes greater account of the noise associated with the calibration dataset. Like identifiability, it has a maximum value of one (which can only be achieved if there is no measurement noise). Conceptually it can fall to zero; and even below zero if a calibration problem is poorly posed. An example, based on a coupled groundwater/surface-water model, is included that demonstrates the utility of the statistics. ?? 2009 Elsevier B.V.

On quantum statistical inference

NARCIS (Netherlands)

Barndorff-Nielsen, O.E.; Gill, R.D.; Jupp, P.E.

2003-01-01

Interest in problems of statistical inference connected to measurements of quantum systems has recently increased substantially, in step with dramatic new developments in experimental techniques for studying small quantum systems. Furthermore, developments in the theory of quantum measurements have

Impact of sophisticated fog spray models on accident analyses

International Nuclear Information System (INIS)

Roblyer, S.P.; Owzarski, P.C.

1978-01-01

The N-Reactor confinement system release dose to the public in a postulated accident is reduced by washing the confinement atmosphere with fog sprays. This allows a low pressure release of confinement atmosphere containing fission products through filters and out an elevated stack. The current accident analysis required revision of the CORRAL code and other codes such as CONTEMPT to properly model the N Reactor confinement into a system of multiple fog-sprayed compartments. In revising these codes, more sophisticated models for the fog sprays and iodine plateout were incorporated to remove some of the conservatism of steam condensing rate, fission product washout and iodine plateout than used in previous studies. The CORRAL code, which was used to describe the transport and deposition of airborne fission products in LWR containment systems for the Rasmussen Study, was revised to describe fog spray removal of molecular iodine (I 2 ) and particulates in multiple compartments for sprays having individual characteristics of on-off times, flow rates, fall heights, and drop sizes in changing containment atmospheres. During postulated accidents, the code determined the fission product removal rates internally rather than from input decontamination factors. A discussion is given of how the calculated plateout and washout rates vary with time throughout the analysis. The results of the accident analyses indicated that more credit could be given to fission product washout and plateout. An important finding was that the release of fission products to the atmosphere and adsorption of fission products on the filters were significantly lower than previous studies had indicated

Sophisticated Communication in the Brazilian Torrent Frog Hylodes japi.

Science.gov (United States)

de Sá, Fábio P; Zina, Juliana; Haddad, Célio F B

2016-01-01

Intraspecific communication in frogs plays an important role in the recognition of conspecifics in general and of potential rivals or mates in particular and therefore with relevant consequences for pre-zygotic reproductive isolation. We investigate intraspecific communication in Hylodes japi, an endemic Brazilian torrent frog with territorial males and an elaborate courtship behavior. We describe its repertoire of acoustic signals as well as one of the most complex repertoires of visual displays known in anurans, including five new visual displays. Previously unknown in frogs, we also describe a bimodal inter-sexual communication system where the female stimulates the male to emit a courtship call. As another novelty for frogs, we show that in addition to choosing which limb to signal with, males choose which of their two vocal sacs will be used for visual signaling. We explain how and why this is accomplished. Control of inflation also provides additional evidence that vocal sac movement and color must be important for visual communication, even while producing sound. Through the current knowledge on visual signaling in Neotropical torrent frogs (i.e. hylodids), we discuss and highlight the behavioral diversity in the family Hylodidae. Our findings indicate that communication in species of Hylodes is undoubtedly more sophisticated than we expected and that visual communication in anurans is more widespread than previously thought. This is especially true in tropical regions, most likely due to the higher number of species and phylogenetic groups and/or to ecological factors, such as higher microhabitat diversity.

Sophisticated Communication in the Brazilian Torrent Frog Hylodes japi.

Directory of Open Access Journals (Sweden)

Fábio P de Sá

Full Text Available Intraspecific communication in frogs plays an important role in the recognition of conspecifics in general and of potential rivals or mates in particular and therefore with relevant consequences for pre-zygotic reproductive isolation. We investigate intraspecific communication in Hylodes japi, an endemic Brazilian torrent frog with territorial males and an elaborate courtship behavior. We describe its repertoire of acoustic signals as well as one of the most complex repertoires of visual displays known in anurans, including five new visual displays. Previously unknown in frogs, we also describe a bimodal inter-sexual communication system where the female stimulates the male to emit a courtship call. As another novelty for frogs, we show that in addition to choosing which limb to signal with, males choose which of their two vocal sacs will be used for visual signaling. We explain how and why this is accomplished. Control of inflation also provides additional evidence that vocal sac movement and color must be important for visual communication, even while producing sound. Through the current knowledge on visual signaling in Neotropical torrent frogs (i.e. hylodids, we discuss and highlight the behavioral diversity in the family Hylodidae. Our findings indicate that communication in species of Hylodes is undoubtedly more sophisticated than we expected and that visual communication in anurans is more widespread than previously thought. This is especially true in tropical regions, most likely due to the higher number of species and phylogenetic groups and/or to ecological factors, such as higher microhabitat diversity.

Comprehensive comparison of gap filling techniques for eddy covariance net carbon fluxes

Science.gov (United States)

Moffat, A. M.; Papale, D.; Reichstein, M.; Hollinger, D. Y.; Richardson, A. D.; Barr, A. G.; Beckstein, C.; Braswell, B. H.; Churkina, G.; Desai, A. R.; Falge, E.; Gove, J. H.; Heimann, M.; Hui, D.; Jarvis, A. J.; Kattge, J.; Noormets, A.; Stauch, V. J.

2007-12-01

Review of fifteen techniques for estimating missing values of net ecosystem CO2 exchange (NEE) in eddy covariance time series and evaluation of their performance for different artificial gap scenarios based on a set of ten benchmark datasets from six forested sites in Europe. The goal of gap filling is the reproduction of the NEE time series and hence this present work focuses on estimating missing NEE values, not on editing or the removal of suspect values in these time series due to systematic errors in the measurements (e.g. nighttime flux, advection). The gap filling was examined by generating fifty secondary datasets with artificial gaps (ranging in length from single half-hours to twelve consecutive days) for each benchmark dataset and evaluating the performance with a variety of statistical metrics. The performance of the gap filling varied among sites and depended on the level of aggregation (native half- hourly time step versus daily), long gaps were more difficult to fill than short gaps, and differences among the techniques were more pronounced during the day than at night. The non-linear regression techniques (NLRs), the look-up table (LUT), marginal distribution sampling (MDS), and the semi-parametric model (SPM) generally showed good overall performance. The artificial neural network based techniques (ANNs) were generally, if only slightly, superior to the other techniques. The simple interpolation technique of mean diurnal variation (MDV) showed a moderate but consistent performance. Several sophisticated techniques, the dual unscented Kalman filter (UKF), the multiple imputation method (MIM), the terrestrial biosphere model (BETHY), but also one of the ANNs and one of the NLRs showed high biases which resulted in a low reliability of the annual sums, indicating that additional development might be needed. An uncertainty analysis comparing the estimated random error in the ten benchmark datasets with the artificial gap residuals suggested that the

Statistical analysis of management data

CERN Document Server

Gatignon, Hubert

2013-01-01

This book offers a comprehensive approach to multivariate statistical analyses. It provides theoretical knowledge of the concepts underlying the most important multivariate techniques and an overview of actual applications.

Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: An example from a vertigo phase III study with longitudinal count data as primary endpoint

Directory of Open Access Journals (Sweden)

Adrion Christine

2012-09-01

provide excellent tools for preparing decisions within the SAP in a transparent way when structuring the primary analysis, sensitivity or ancillary analyses, and specific analyses for secondary endpoints. The mean logarithmic score and DIC discriminate well between different model scenarios. It becomes obvious that the naive choice of a conventional random effects Poisson model is often inappropriate for real-life count data. The findings are used to specify an appropriate mixed model employed in the sensitivity analyses of an ongoing phase III trial. Conclusions The proposed Bayesian methods are not only appealing for inference but notably provide a sophisticated insight into different aspects of model performance, such as forecast verification or calibration checks, and can be applied within the model selection process. The mean of the logarithmic score is a robust tool for model ranking and is not sensitive to sample size. Therefore, these Bayesian model selection techniques offer helpful decision support for shaping sensitivity and ancillary analyses in a statistical analysis plan of a clinical trial with longitudinal count data as the primary endpoint.

Statistical methods for ranking data

CERN Document Server

Alvo, Mayer

2014-01-01

This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

Topology for statistical modeling of petascale data.

Energy Technology Data Exchange (ETDEWEB)

Pascucci, Valerio (University of Utah, Salt Lake City, UT); Mascarenhas, Ajith Arthur; Rusek, Korben (Texas A& M University, College Station, TX); Bennett, Janine Camille; Levine, Joshua (University of Utah, Salt Lake City, UT); Pebay, Philippe Pierre; Gyulassy, Attila (University of Utah, Salt Lake City, UT); Thompson, David C.; Rojas, Joseph Maurice (Texas A& M University, College Station, TX)

2011-07-01

This document presents current technical progress and dissemination of results for the Mathematics for Analysis of Petascale Data (MAPD) project titled 'Topology for Statistical Modeling of Petascale Data', funded by the Office of Science Advanced Scientific Computing Research (ASCR) Applied Math program. Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is thus to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, our approach is based on the complementary techniques of combinatorial topology and statistical modeling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modeling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. This document summarizes the technical advances we have made to date that were made possible in whole or in part by MAPD funding. These technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modeling, and (3) new integrated topological and statistical methods.

Statistical mechanics of superconductivity

CERN Document Server

Kita, Takafumi

2015-01-01

This book provides a theoretical, step-by-step comprehensive explanation of superconductivity for undergraduate and graduate students who have completed elementary courses on thermodynamics and quantum mechanics. To this end, it adopts the unique approach of starting with the statistical mechanics of quantum ideal gases and successively adding and clarifying elements and techniques indispensible for understanding it. They include the spin-statistics theorem, second quantization, density matrices, the Bloch–De Dominicis theorem, the variational principle in statistical mechanics, attractive interaction, and bound states. Ample examples of their usage are also provided in terms of topics from advanced statistical mechanics such as two-particle correlations of quantum ideal gases, derivation of the Hartree–Fock equations, and Landau’s Fermi-liquid theory, among others. With these preliminaries, the fundamental mean-field equations of superconductivity are derived with maximum mathematical clarity based on ...

Introductory statistics for engineering experimentation

CERN Document Server

Nelson, Peter R; Coffin, Marie

2003-01-01

The Accreditation Board for Engineering and Technology (ABET) introduced a criterion starting with their 1992-1993 site visits that "Students must demonstrate a knowledge of the application of statistics to engineering problems." Since most engineering curricula are filled with requirements in their own discipline, they generally do not have time for a traditional two semesters of probability and statistics. Attempts to condense that material into a single semester often results in so much time being spent on probability that the statistics useful for designing and analyzing engineering/scientific experiments is never covered. In developing a one-semester course whose purpose was to introduce engineering/scientific students to the most useful statistical methods, this book was created to satisfy those needs. - Provides the statistical design and analysis of engineering experiments & problems - Presents a student-friendly approach through providing statistical models for advanced learning techniques - Cove...

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

Science.gov (United States)

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

Sensitivity analysis and related analysis : A survey of statistical techniques

NARCIS (Netherlands)

Kleijnen, J.P.C.

1995-01-01

This paper reviews the state of the art in five related types of analysis, namely (i) sensitivity or what-if analysis, (ii) uncertainty or risk analysis, (iii) screening, (iv) validation, and (v) optimization. The main question is: when should which type of analysis be applied; which statistical

EU-Korea FTA and Its Impact on V4 Economies. A Comparative Analysis of Trade Sophistication and Intra-Industry Trade

Directory of Open Access Journals (Sweden)

Michalski Bartosz

2018-03-01

Full Text Available This paper investigates selected short- and mid-term effects in trade in goods between the Visegrad countries (V4: the Czech Republic, Hungary, Poland and the Slovak Republic and the Republic of Korea under the framework of the Free Trade Agreement between the European Union and the Republic of Korea. This Agreement is described in the “Trade for All” (2015: 9 strategy as the most ambitious trade deal ever implemented by the EU. The primary purpose of our analysis is to identify, compare, and evaluate the evolution of the technological sophistication of bilateral exports and imports. Another dimension of the paper concentrates on the developments within intra-industry trade. Moreover, these objectives are approached taking into account the context of the South Korean direct investment inflow to the V4. The evaluation of technological sophistication is based on UNCTAD’s methodology, while the intensity of intra-industry trade is measured by the GL-index and identification of its subcategories (horizontal and vertical trade. The analysis covers the timespan 2001–2015. The novelty of the paper lies in the fact that the study of South Korean-V4 trade relations has not so far been carried out from this perspective. Thus this paper investigates interesting phenomena identified in the trade between the Republic of Korea (ROK and V4 economies. The main findings imply an impact of South Korean direct investments on trade. This is represented by the trade deficit of the V4 with ROK and the structure of bilateral trade in terms of its technological sophistication. South Korean investments might also have had positive consequences for the evolution of IIT, particularly in the machinery sector. The political interpretation indicates that they may strengthen common threats associated with the middle-income trap, particularly the technological gap and the emphasis placed on lower costs of production.

Application of Statistical Downscaling Techniques to Predict Rainfall and Its Spatial Analysis Over Subansiri River Basin of Assam, India

Science.gov (United States)

Barman, S.; Bhattacharjya, R. K.

2017-12-01

The River Subansiri is the major north bank tributary of river Brahmaputra. It originates from the range of Himalayas beyond the Great Himalayan range at an altitude of approximately 5340m. Subansiri basin extends from tropical to temperate zones and hence exhibits a great diversity in rainfall characteristics. In the Northern and Central Himalayan tracts, precipitation is scarce on account of high altitudes. On the other hand, Southeast part of the Subansiri basin comprising the sub-Himalayan and the plain tract in Arunachal Pradesh and Assam, lies in the tropics. Due to Northeast as well as Southwest monsoon, precipitation occurs in this region in abundant quantities. Particularly, Southwest monsoon causes very heavy precipitation in the entire Subansiri basin during May to October. In this study, the rainfall over Subansiri basin has been studied at 24 different locations by multiple linear and non-linear regression based statistical downscaling techniques and by Artificial Neural Network based model. APHRODITE's gridded rainfall data of 0.25˚ x 0.25˚ resolutions and climatic parameters of HadCM3 GCM of resolution 2.5˚ x 3.75˚ (latitude by longitude) have been used in this study. It has been found that multiple non-linear regression based statistical downscaling technique outperformed the other techniques. Using this method, the future rainfall pattern over the Subansiri basin has been analyzed up to the year 2099 for four different time periods, viz., 2020-39, 2040-59, 2060-79, and 2080-99 at all the 24 locations. On the basis of historical rainfall, the months have been categorized as wet months, months with moderate rainfall and dry months. The spatial changes in rainfall patterns for all these three types of months have also been analyzed over the basin. Potential decrease of rainfall in the wet months and months with moderate rainfall and increase of rainfall in the dry months are observed for the future rainfall pattern of the Subansiri basin.

Arsenic health risk assessment in drinking water and source apportionment using multivariate statistical techniques in Kohistan region, northern Pakistan.

Science.gov (United States)

Muhammad, Said; Tahir Shah, M; Khan, Sardar

2010-10-01

The present study was conducted in Kohistan region, where mafic and ultramafic rocks (Kohistan island arc and Indus suture zone) and metasedimentary rocks (Indian plate) are exposed. Water samples were collected from the springs, streams and Indus river and analyzed for physical parameters, anions, cations and arsenic (As(3+), As(5+) and arsenic total). The water quality in Kohistan region was evaluated by comparing the physio-chemical parameters with permissible limits set by Pakistan environmental protection agency and world health organization. Most of the studied parameters were found within their respective permissible limits. However in some samples, the iron and arsenic concentrations exceeded their permissible limits. For health risk assessment of arsenic, the average daily dose, hazards quotient (HQ) and cancer risk were calculated by using statistical formulas. The values of HQ were found >1 in the samples collected from Jabba, Dubair, while HQ values were pollution load was also calculated by using multivariate statistical techniques like one-way ANOVA, correlation analysis, regression analysis, cluster analysis and principle component analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

An exercise in model validation: Comparing univariate statistics and Monte Carlo-based multivariate statistics

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.

An exercise in model validation: Comparing univariate statistics and Monte Carlo-based multivariate 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.

Optical Evaluation of the Rear Contacts of Crystalline Silicon Solar Cells by Coupled Electromagnetic and Statistical Ray-Optics Modeling

KAUST Repository

Dabirian, Ali

2017-02-15

High-efficiency crystalline silicon (c-Si) solar cells increasingly feature sophisticated electron and hole contacts aimed at minimizing electronic losses. At the rear of photovoltaic devices, such contacts—usually consisting of stacks of functional layers—offer opportunities to enhance the infrared response of the solar cells. Here, we propose an accurate and simple modeling procedure to evaluate the infrared performance of rear contacts in c-Si solar cells. Our method combines full-wave electromagnetic modeling of the rear contact with a statistical ray optics model to obtain the fraction of optical energy dissipated from the rear contact relative to that absorbed by the Si wafer. Using this technique, we study the impact of the refractive index, extinction coefficient, and thickness of the rear-passivating layer and establish basic design rules. In addition, we evaluate novel optical structures, including stratified thin films, nanoparticle composites, and conductive nanowires embedded in a low-index dielectric matrix, for integration into advanced rear contacts in c-Si photovoltaic devices. From an optical perspective, nanowire structures preserving low contact resistance appear to be the most effective approach to mitigating dissipation losses from the rear contact.

Prerequisites for Systems Analysts: Analytic and Management Demands of a New Approach to Educational Administration.

Science.gov (United States)

Ammentorp, William

There is much to be gained by using systems analysis in educational administration. Most administrators, presently relying on classical statistical techniques restricted to problems having few variables, should be trained to use more sophisticated tools such as systems analysis. The systems analyst, interested in the basic processes of a group or…

Statistics 101 for Radiologists.

Science.gov (United States)

Anvari, Arash; Halpern, Elkan F; Samir, Anthony E

2015-10-01

Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced. © RSNA, 2015.

Stupid statistics!

Science.gov (United States)

Tellinghuisen, Joel

2008-01-01

The method of least squares is probably the most powerful data analysis tool available to scientists. Toward a fuller appreciation of that power, this work begins with an elementary review of statistics fundamentals, and then progressively increases in sophistication as the coverage is extended to the theory and practice of linear and nonlinear least squares. The results are illustrated in application to data analysis problems important in the life sciences. The review of fundamentals includes the role of sampling and its connection to probability distributions, the Central Limit Theorem, and the importance of finite variance. Linear least squares are presented using matrix notation, and the significance of the key probability distributions-Gaussian, chi-square, and t-is illustrated with Monte Carlo calculations. The meaning of correlation is discussed, including its role in the propagation of error. When the data themselves are correlated, special methods are needed for the fitting, as they are also when fitting with constraints. Nonlinear fitting gives rise to nonnormal parameter distributions, but the 10% Rule of Thumb suggests that such problems will be insignificant when the parameter is sufficiently well determined. Illustrations include calibration with linear and nonlinear response functions, the dangers inherent in fitting inverted data (e.g., Lineweaver-Burk equation), an analysis of the reliability of the van't Hoff analysis, the problem of correlated data in the Guggenheim method, and the optimization of isothermal titration calorimetry procedures using the variance-covariance matrix for experiment design. The work concludes with illustrations on assessing and presenting results.

Comparison of process estimation techniques for on-line calibration monitoring

International Nuclear Information System (INIS)

Shumaker, B. D.; Hashemian, H. M.; Morton, G. W.

2006-01-01

The goal of on-line calibration monitoring is to reduce the number of unnecessary calibrations performed each refueling cycle on pressure, level, and flow transmitters in nuclear power plants. The effort requires a baseline for determining calibration drift and thereby the need for a calibration. There are two ways to establish the baseline: averaging and modeling. Averaging techniques have proven to be highly successful in the applications when there are a large number of redundant transmitters; but, for systems with little or no redundancy, averaging methods are not always reliable. That is, for non-redundant transmitters, more sophisticated process estimation techniques are needed to augment or replace the averaging techniques. This paper explores three well-known process estimation techniques; namely Independent Component Analysis (ICA), Auto-Associative Neural Networks (AANN), and Auto-Associative Kernel Regression (AAKR). Using experience and data from an operating nuclear plant, the paper will present an evaluation of the effectiveness of these methods in detecting transmitter drift in actual plant conditions. (authors)

Roman sophisticated surface modification methods to manufacture silver counterfeited coins

Science.gov (United States)

Ingo, G. M.; Riccucci, C.; Faraldi, F.; Pascucci, M.; Messina, E.; Fierro, G.; Di Carlo, G.

2017-11-01

By means of the combined use of X-ray photoelectron spectroscopy (XPS), optical microscopy (OM) and scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDS) the surface and subsurface chemical and metallurgical features of silver counterfeited Roman Republican coins are investigated to decipher some aspects of the manufacturing methods and to evaluate the technological ability of the Roman metallurgists to produce thin silver coatings. The results demonstrate that over 2000 ago important advances in the technology of thin layer deposition on metal substrates were attained by Romans. The ancient metallurgists produced counterfeited coins by combining sophisticated micro-plating methods and tailored surface chemical modification based on the mercury-silvering process. The results reveal that Romans were able systematically to chemically and metallurgically manipulate alloys at a micro scale to produce adherent precious metal layers with a uniform thickness up to few micrometers. The results converge to reveal that the production of forgeries was aimed firstly to save expensive metals as much as possible allowing profitable large-scale production at a lower cost. The driving forces could have been a lack of precious metals, an unexpected need to circulate coins for trade and/or a combinations of social, political and economic factors that requested a change in money supply. Finally, some information on corrosion products have been achieved useful to select materials and methods for the conservation of these important witnesses of technology and economy.

RSYST: From nuclear reactor calculations towards a highly sophisticated scientific software integration environment

International Nuclear Information System (INIS)

Noack, M.; Seybold, J.; Ruehle, R.

1996-01-01

The software environment RSYST was originally used to solve problems of reactor physics. The consideration of advanced scientific simulation requirements and the strict application of modern software design principles led to a system which is perfectly suitable to solve problems in various complex scientific problem domains. Starting with a review of the early days of RSYST, we describe the straight evolution driven by the need of software environment which combines the advantages of a high-performance database system with the capability to integrate sophisticated scientific technical applications. The RSYST architecture is presented and the data modelling capabilities are described. To demonstrate the powerful possibilities and flexibility of the RSYST environment, we describe a wide range of RSYST applications, e.g., mechanical simulations of multibody systems, which are used in biomechanical research, civil engineering and robotics. In addition, a hypermedia system which is used for scientific technical training and documentation is presented. (orig.) [de

Experimental statistics

CERN Document Server

Natrella, Mary Gibbons

1963-01-01

Formulated to assist scientists and engineers engaged in army ordnance research and development programs, this well-known and highly regarded handbook is a ready reference for advanced undergraduate and graduate students as well as for professionals seeking engineering information and quantitative data for designing, developing, constructing, and testing equipment. Topics include characterizing and comparing the measured performance of a material, product, or process; general considerations in planning experiments; statistical techniques for analyzing extreme-value data; use of transformations

statistical tests for frequency distribution of mean gravity anomalies

African Journals Online (AJOL)

ES Obe

1980-03-01

Mar 1, 1980 ... STATISTICAL TESTS FOR FREQUENCY DISTRIBUTION OF MEAN. GRAVITY ANOMALIES. By ... approach. Kaula [1,2] discussed the method of applying statistical techniques in the ..... mathematical foundation of physical ...

Statistical methods for astronomical data analysis

CERN Document Server

Chattopadhyay, Asis Kumar

2014-01-01

This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological framework. A unique feature is the inclusion of different possible sources of astronomical data, as well as software packages for converting the raw data into appropriate forms for data analysis. Readers can then use the appropriate statistical packages for their particular data analysis needs. The ideas of statistical inference discussed in the book help readers determine how to apply statistical tests. The authors cover different applications of statistical techniques already developed or specifically introduced for ...

Developments in functional neuroimaging techniques

International Nuclear Information System (INIS)

Aine, C.J.

1995-01-01

A recent review of neuroimaging techniques indicates that new developments have primarily occurred in the area of data acquisition hardware/software technology. For example, new pulse sequences on standard clinical imagers and high-powered, rapidly oscillating magnetic field gradients used in echo planar imaging (EPI) have advanced MRI into the functional imaging arena. Significant developments in tomograph design have also been achieved for monitoring the distribution of positron-emitting radioactive tracers in the body (PET). Detector sizes, which pose a limit on spatial resolution, have become smaller (e.g., 3--5 mm wide) and a new emphasis on volumetric imaging has emerged which affords greater sensitivity for determining locations of positron annihilations and permits smaller doses to be utilized. Electromagnetic techniques have also witnessed growth in the ability to acquire data from the whole head simultaneously. EEG techniques have increased their electrode coverage (e.g., 128 channels rather than 16 or 32) and new whole-head systems are now in use for MEG. But the real challenge now is in the design and implementation of more sophisticated analyses to effectively handle the tremendous amount of physiological/anatomical data that can be acquired. Furthermore, such analyses will be necessary for integrating data across techniques in order to provide a truly comprehensive understanding of the functional organization of the human brain

Parallel preconditioning techniques for sparse CG solvers

Energy Technology Data Exchange (ETDEWEB)

Basermann, A.; Reichel, B.; Schelthoff, C. [Central Institute for Applied Mathematics, Juelich (Germany)

1996-12-31

Conjugate gradient (CG) methods to solve sparse systems of linear equations play an important role in numerical methods for solving discretized partial differential equations. The large size and the condition of many technical or physical applications in this area result in the need for efficient parallelization and preconditioning techniques of the CG method. In particular for very ill-conditioned matrices, sophisticated preconditioner are necessary to obtain both acceptable convergence and accuracy of CG. Here, we investigate variants of polynomial and incomplete Cholesky preconditioners that markedly reduce the iterations of the simply diagonally scaled CG and are shown to be well suited for massively parallel machines.

Uncovering category specificity of genital sexual arousal in women: The critical role of analytic technique.

Science.gov (United States)

Pulverman, Carey S; Hixon, J Gregory; Meston, Cindy M

2015-10-01

Based on analytic techniques that collapse data into a single average value, it has been reported that women lack category specificity and show genital sexual arousal to a large range of sexual stimuli including those that both match and do not match their self-reported sexual interests. These findings may be a methodological artifact of the way in which data are analyzed. This study examined whether using an analytic technique that models data over time would yield different results. Across two studies, heterosexual (N = 19) and lesbian (N = 14) women viewed erotic films featuring heterosexual, lesbian, and gay male couples, respectively, as their physiological sexual arousal was assessed with vaginal photoplethysmography. Data analysis with traditional methods comparing average genital arousal between films failed to detect specificity of genital arousal for either group. When data were analyzed with smoothing regression splines and a within-subjects approach, both heterosexual and lesbian women demonstrated different patterns of genital sexual arousal to the different types of erotic films, suggesting that sophisticated statistical techniques may be necessary to more fully understand women's genital sexual arousal response. Heterosexual women showed category-specific genital sexual arousal. Lesbian women showed higher arousal to the heterosexual film than the other films. However, within subjects, lesbian women showed significantly different arousal responses suggesting that lesbian women's genital arousal discriminates between different categories of stimuli at the individual level. Implications for the future use of vaginal photoplethysmography as a diagnostic tool of sexual preferences in clinical and forensic settings are discussed. © 2015 Society for Psychophysiological Research.

Financial planning and analysis techniques of mining firms: a note on Canadian practice

Energy Technology Data Exchange (ETDEWEB)

Blanco, H.; Zanibbi, L.R. (Laurentian University, Sudbury, ON (Canada). School of Commerce and Administration)

1992-06-01

This paper reports on the results of a survey of the financial planning and analysis techniques in use in the mining industry in Canada. The study was undertaken to determine the current status of these practices within mining firms in Canada and to investigate the extent to which the techniques are grouped together within individual firms. In addition, tests were performed on the relationship between these groups of techniques and both organizational size and price volatility of end product. The results show that a few techniques are widely utilized in this industry but that the techniques used most frequently are not as sophisticated as reported in previous, more broadly based surveys. The results also show that firms tend to use 'bundles' of techniques and that the relative use of some of these groups of techniques is weakly associated with both organizational size and type of end product. 19 refs., 7 tabs.

Cutting-edge statistical methods for a life-course approach.

Science.gov (United States)

Bub, Kristen L; Ferretti, Larissa K

2014-01-01

Advances in research methods, data collection and record keeping, and statistical software have substantially increased our ability to conduct rigorous research across the lifespan. In this article, we review a set of cutting-edge statistical methods that life-course researchers can use to rigorously address their research questions. For each technique, we describe the method, highlight the benefits and unique attributes of the strategy, offer a step-by-step guide on how to conduct the analysis, and illustrate the technique using data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development. In addition, we recommend a set of technical and empirical readings for each technique. Our goal was not to address a substantive question of interest but instead to provide life-course researchers with a useful reference guide to cutting-edge statistical methods.

Pretreatment techniques of biodegradable municipal wastewater for sustainable development of surface and groundwater resources: a survey/case studies (abstract)

International Nuclear Information System (INIS)

Rashid, A.; Sajjad, M.R.

1999-01-01

Water being a scarce commodity, recharge of groundwater with clean surface water is important to maintain good quality water resources. This paper reviews and discusses the advantages and disadvantages of different techniques for the treatment of municipal wastewater's in developing countries. Different processes discussed include from simple stabilization ponds and land treatment to aerated lagoons and oxidation ditches. More sophisticated techniques of activated sludge and anaerobic digestion are also discussed. The feasibility of these techniques in terms of cost, land area, removal of pathogens, effluent quality and need of technical expertise is discussed. (author)

A Modified Moore Approach to Teaching Mathematical Statistics: An Inquiry Based Learning Technique to Teaching Mathematical Statistics

Science.gov (United States)

McLoughlin, M. Padraig M. M.

2008-01-01

The author of this paper submits the thesis that learning requires doing; only through inquiry is learning achieved, and hence this paper proposes a programme of use of a modified Moore method in a Probability and Mathematical Statistics (PAMS) course sequence to teach students PAMS. Furthermore, the author of this paper opines that set theory…

Dynamic re-weighted total variation technique and statistic Iterative reconstruction method for x-ray CT metal artifact reduction

Science.gov (United States)

Peng, Chengtao; Qiu, Bensheng; Zhang, Cheng; Ma, Changyu; Yuan, Gang; Li, Ming

2017-07-01

Over the years, the X-ray computed tomography (CT) has been successfully used in clinical diagnosis. However, when the body of the patient to be examined contains metal objects, the image reconstructed would be polluted by severe metal artifacts, which affect the doctor's diagnosis of disease. In this work, we proposed a dynamic re-weighted total variation (DRWTV) technique combined with the statistic iterative reconstruction (SIR) method to reduce the artifacts. The DRWTV method is based on the total variation (TV) and re-weighted total variation (RWTV) techniques, but it provides a sparser representation than TV and protects the tissue details better than RWTV. Besides, the DRWTV can suppress the artifacts and noise, and the SIR convergence speed is also accelerated. The performance of the algorithm is tested on both simulated phantom dataset and clinical dataset, which are the teeth phantom with two metal implants and the skull with three metal implants, respectively. The proposed algorithm (SIR-DRWTV) is compared with two traditional iterative algorithms, which are SIR and SIR constrained by RWTV regulation (SIR-RWTV). The results show that the proposed algorithm has the best performance in reducing metal artifacts and protecting tissue details.

Adaptive RAC codes employing statistical channel evaluation ...

African Journals Online (AJOL)

An adaptive encoding technique using row and column array (RAC) codes employing a different number of parity columns that depends on the channel state is proposed in this paper. The trellises of the proposed adaptive codes and a statistical channel evaluation technique employing these trellises are designed and ...

Statistical-Mechanical Analysis of Pre-training and Fine Tuning in Deep Learning

Science.gov (United States)

Ohzeki, Masayuki

2015-03-01

In this paper, we present a statistical-mechanical analysis of deep learning. We elucidate some of the essential components of deep learning — pre-training by unsupervised learning and fine tuning by supervised learning. We formulate the extraction of features from the training data as a margin criterion in a high-dimensional feature-vector space. The self-organized classifier is then supplied with small amounts of labelled data, as in deep learning. Although we employ a simple single-layer perceptron model, rather than directly analyzing a multi-layer neural network, we find a nontrivial phase transition that is dependent on the number of unlabelled data in the generalization error of the resultant classifier. In this sense, we evaluate the efficacy of the unsupervised learning component of deep learning. The analysis is performed by the replica method, which is a sophisticated tool in statistical mechanics. We validate our result in the manner of deep learning, using a simple iterative algorithm to learn the weight vector on the basis of belief propagation.

Curve ball baseball, statistics, and the role of chance in the game

CERN Document Server

Bennett, Jay

2001-01-01

In its formative years, from the 1970s through the 1990s, sabermetrics was p- marily an amateur undertaking. Publications were aimed at a relatively small audience of baseball fans. To be sure, this ever-growing group of aficionados brought a lot of sophistication to baseball analysis, and were constantly looking for statistical insights beyond the listings of the top ten batters found in popular newspapers and magazines. But their influence on the baseball profession was very limited. A few consultants like Craig Wright developed temporary relati- ships with various teams, but none were able to stay long enough to create a p- manent sabermetrician staff position. (See Rob Neyer’s November 11, 2002, arti- 1 cle on ESPN. com. ) All of this changed, however, in 2002 with the hiring of Bill James by the Boston Red Sox. With that move, we have seen the admittance of the foremost proponent of sabermetrics into the top echelon of professional ba- ball management. The art and science of careful statistical analysi...

A very simple technique to repair Grynfeltt-Lesshaft hernia.

Science.gov (United States)

Solaini, Leonardo; di Francesco, F; Gourgiotis, S; Solaini, Luciano

2010-08-01

A very simple technique to repair a superior lumbar hernia is described. The location of this type of hernia, also known as the Grynfeltt-Lesshaft hernia, is defined by a triangle placed in the lumbar region. An unusual case of a 67-year-old woman with a superior lumbar hernia is reported. The diagnosis was made by physical examination. The defect of the posterior abdominal wall was repaired with a polypropylene dart mesh. The patient had no evidence of recurrence at 11 months follow up. The surgical approach described in this paper is simple and easy to perform, and its result is comparable with other techniques that are much more sophisticated. No cases on the use of dart mesh to repair Grynfeltt-Lesshaft hernia have been reported by surgical journals indexed in PubMed.

Modern techniques for condition monitoring of railway vehicle dynamics

International Nuclear Information System (INIS)

Ngigi, R W; Pislaru, C; Ball, A; Gu, F

2012-01-01

A modern railway system relies on sophisticated monitoring systems for maintenance and renewal activities. Some of the existing conditions monitoring techniques perform fault detection using advanced filtering, system identification and signal analysis methods. These theoretical approaches do not require complex mathematical models of the system and can overcome potential difficulties associated with nonlinearities and parameter variations in the system. Practical applications of condition monitoring tools use sensors which are mounted either on the track or rolling stock. For instance, monitoring wheelset dynamics could be done through the use of track-mounted sensors, while vehicle-based sensors are preferred for monitoring the train infrastructure. This paper attempts to collate and critically appraise the modern techniques used for condition monitoring of railway vehicle dynamics by analysing the advantages and shortcomings of these methods.

Analytical system availability techniques

NARCIS (Netherlands)

Brouwers, J.J.H.; Verbeek, P.H.J.; Thomson, W.R.

1987-01-01

Analytical techniques are presented to assess the probability distributions and related statistical parameters of loss of production from equipment networks subject to random failures and repairs. The techniques are based on a theoretical model for system availability, which was further developed

The problem of sexual imbalance and techniques of the self in the Diagnostic and Statistical Manual of Mental Disorders.

Science.gov (United States)

Flore, Jacinthe

2016-09-01

This article examines the problematization of sexual appetite and its imbalances in the development of the Diagnostic and Statistical Manual of Mental Disorders (DSM) in the twentieth and twenty-first centuries. The dominant strands of historiographies of sexuality have focused on historicizing sexual object choice and understanding the emergence of sexual identities. This article emphasizes the need to contextualize these histories within a broader frame of historical interest in the problematization of sexual appetite. The first part highlights how sexual object choice, as a paradigm of sexual dysfunctions, progressively receded from medical interest in the twentieth century as the clinical gaze turned to the problem of sexual appetite and its imbalances. The second part uses the example of the newly introduced Female Sexual Interest/Arousal Disorder in the DSM-5 to explore how the Manual functions as a technique for taking care of the self. I argue that the design of the Manual and associated inventories and questionnaires paved the way for their interpretation and application as techniques for self-examination. © The Author(s) 2016.

A Case Study on E - Banking Security – When Security Becomes Too Sophisticated for the User to Access Their Information

OpenAIRE

Aaron M. French

2012-01-01

While eBanking security continues to increase in sophistication to protect against threats, the usability of the eBanking decreases resulting in poor security behaviors by the users. The current research evaluates se curity risks and measures taken for eBanking solutions. A case study is presented describing how increased complexity decreases vulnerabilities online but increases vulnerabilities from internal threats and eBanking users

Performance of pile-up mitigation techniques for jets in pp collisions with the ATLAS detector

CERN Document Server

Testa, Marianna; The ATLAS collaboration

2015-01-01

The large rate of multiple simultaneous proton-proton interactions, or pile-up, generated by the Large Hadron Collider in Run I required the development of many new techniques to mitigate the adverse effects of these conditions. This presentation shows the methods employed to correct for the impact of pile-up on jet energy, jet shapes, and even spurious additional jets. Energy correction techniques that incorporate sophisticated estimates of the average pile-up energy density and tracking information are described in detail. Jet-to-vertex association techniques are also presented. We also describe the extension of these techniques to ameliorate the effect of pile-up on jet shapes using both subtraction and grooming procedures. Prospects for pile-up suppression at the HL-LHC will be also discussed.

Statistical Analysis and Comparison of Harmonics Measured in Offshore Wind Farms

DEFF Research Database (Denmark)

Kocewiak, Lukasz Hubert; Hjerrild, Jesper; Bak, Claus Leth

2011-01-01

The paper shows statistical analysis of harmonic components measured in different offshore wind farms. Harmonic analysis is a complex task and requires many aspects, such as measurements, data processing, modeling, validation, to be taken into consideration. The paper describes measurement process...... and shows sophisticated analysis on representative harmonic measurements from Avedøre Holme, Gunfleet Sands and Burbo Bank wind farms. The nature of generation and behavior of harmonic components in offshore wind farms clearly presented and explained based on probabilistic approach. Some issues regarding...... commonly applied standards are also put forward in the discussion. Based on measurements and data analysis it is shown that a general overview about wind farm harmonic behaviour cannot be fully observed only based on single-value measurements as suggested in the standards but using more descriptive...

Powerful Statistical Inference for Nested Data Using Sufficient Summary Statistics

Science.gov (United States)

Dowding, Irene; Haufe, Stefan

2018-01-01

Hierarchically-organized data arise naturally in many psychology and neuroscience studies. As the standard assumption of independent and identically distributed samples does not hold for such data, two important problems are to accurately estimate group-level effect sizes, and to obtain powerful statistical tests against group-level null hypotheses. A common approach is to summarize subject-level data by a single quantity per subject, which is often the mean or the difference between class means, and treat these as samples in a group-level t-test. This “naive” approach is, however, suboptimal in terms of statistical power, as it ignores information about the intra-subject variance. To address this issue, we review several approaches to deal with nested data, with a focus on methods that are easy to implement. With what we call the sufficient-summary-statistic approach, we highlight a computationally efficient technique that can improve statistical power by taking into account within-subject variances, and we provide step-by-step instructions on how to apply this approach to a number of frequently-used measures of effect size. The properties of the reviewed approaches and the potential benefits over a group-level t-test are quantitatively assessed on simulated data and demonstrated on EEG data from a simulated-driving experiment. PMID:29615885

Statistical models and methods for reliability and survival analysis

CERN Document Server

Couallier, Vincent; Huber-Carol, Catherine; Mesbah, Mounir; Huber -Carol, Catherine; Limnios, Nikolaos; Gerville-Reache, Leo

2013-01-01

Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical

Statistical tests for the Gaussian nature of primordial fluctuations through CBR experiments

International Nuclear Information System (INIS)

Luo, X.

1994-01-01

Information about the physical processes that generate the primordial fluctuations in the early Universe can be gained by testing the Gaussian nature of the fluctuations through cosmic microwave background radiation (CBR) temperature anisotropy experiments. One of the crucial aspects of density perturbations that are produced by the standard inflation scenario is that they are Gaussian, whereas seeds produced by topological defects left over from an early cosmic phase transition tend to be non-Gaussian. To carry out this test, sophisticated statistical tools are required. In this paper, we will discuss several such statistical tools, including multivariant skewness and kurtosis, Euler-Poincare characteristics, the three-point temperature correlation function, and Hotelling's T 2 statistic defined through bispectral estimates of a one-dimensional data set. The effect of noise present in the current data is discussed in detail and the COBE 53 GHz data set is analyzed. Our analysis shows that, on the large angular scale to which COBE is sensitive, the statistics are probably Gaussian. On the small angular scales, the importance of Hotelling's T 2 statistic is stressed, and the minimum sample size required to test Gaussianity is estimated. Although the current data set available from various experiments at half-degree scales is still too small, improvement of the data set by roughly a factor of 2 will be enough to test the Gaussianity statistically. On the arc min scale, we analyze the recent RING data through bispectral analysis, and the result indicates possible deviation from Gaussianity. Effects of point sources are also discussed. It is pointed out that the Gaussianity problem can be resolved in the near future by ground-based or balloon-borne experiments

Analysis of Variance in Statistical Image Processing

Science.gov (United States)

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.

Nurturing Opportunity Identification for Business Sophistication in a Cross-disciplinary Study Environment

Directory of Open Access Journals (Sweden)

Karine Oganisjana

2012-12-01

Full Text Available Opportunity identification is the key element of the entrepreneurial process; therefore the issue of developing this skill in students is a crucial task in contemporary European education which has recognized entrepreneurship as one of the lifelong learning key competences. The earlier opportunity identification becomes a habitual way of thinking and behavior across a broad range of contexts, the more likely that entrepreneurial disposition will steadily reside in students. In order to nurture opportunity identification in students for making them able to organize sophisticated businesses in the future, certain demands ought to be put forward as well to the teacher – the person who is to promote these qualities in their students. The paper reflects some findings of a research conducted within the frameworks of a workplace learning project for the teachers of one of Riga secondary schools (Latvia. The main goal of the project was to teach the teachers to identify hidden inner links between apparently unrelated things, phenomena and events within 10th grade study curriculum and connect them together and create new opportunities. The creation and solution of cross-disciplinary tasks were the means for achieving this goal.

Statistical methods in nuclear material accountancy: Past, present and future

International Nuclear Information System (INIS)

Pike, D.J.; Woods, A.J.

1983-01-01

The analysis of nuclear material inventory data is motivated by the desire to detect any loss or diversion of nuclear material, insofar as such detection may be feasible by statistical analysis of repeated inventory and throughput measurements. The early regulations, which laid down the specifications for the analysis of inventory data, were framed without acknowledging the essentially sequential nature of the data. It is the broad aim of this paper to discuss the historical nature of statistical analysis of inventory data including an evaluation of why statistical methods should be required at all. If it is accepted that statistical techniques are required, then two main areas require extensive discussion. First, it is important to assess the extent to which stated safeguards aims can be met in practice. Second, there is a vital need for reassessment of the statistical techniques which have been proposed for use in nuclear material accountancy. Part of this reassessment must involve a reconciliation of the apparent differences in philosophy shown by statisticians; but, in addition, the techniques themselves need comparative study to see to what extent they are capable of meeting realistic safeguards aims. This paper contains a brief review of techniques with an attempt to compare and contrast the approaches. It will be suggested that much current research is following closely similar lines, and that national and international bodies should encourage collaborative research and practical in-plant implementations. The techniques proposed require credibility and power; but at this point in time statisticians require credibility and a greater level of unanimity in their approach. A way ahead is proposed based on a clear specification of realistic safeguards aims, and a development of a unified statistical approach with encouragement for the performance of joint research. (author)

A statistical framework for the validation of a population exposure model based on personal exposure data

Science.gov (United States)

Rodriguez, Delphy; Valari, Myrto; Markakis, Konstantinos; Payan, Sébastien

2016-04-01

Currently, ambient pollutant concentrations at monitoring sites are routinely measured by local networks, such as AIRPARIF in Paris, France. Pollutant concentration fields are also simulated with regional-scale chemistry transport models such as CHIMERE (http://www.lmd.polytechnique.fr/chimere) under air-quality forecasting platforms (e.g. Prev'Air http://www.prevair.org) or research projects. These data may be combined with more or less sophisticated techniques to provide a fairly good representation of pollutant concentration spatial gradients over urban areas. Here we focus on human exposure to atmospheric contaminants. Based on census data on population dynamics and demographics, modeled outdoor concentrations and infiltration of outdoor air-pollution indoors we have developed a population exposure model for ozone and PM2.5. A critical challenge in the field of population exposure modeling is model validation since personal exposure data are expensive and therefore, rare. However, recent research has made low cost mobile sensors fairly common and therefore personal exposure data should become more and more accessible. In view of planned cohort field-campaigns where such data will be available over the Paris region, we propose in the present study a statistical framework that makes the comparison between modeled and measured exposures meaningful. Our ultimate goal is to evaluate the exposure model by comparing modeled exposures to monitor data. The scientific question we address here is how to downscale modeled data that are estimated on the county population scale at the individual scale which is appropriate to the available measurements. To assess this question we developed a Bayesian hierarchical framework that assimilates actual individual data into population statistics and updates the probability estimate.

Nondestructive evaluation of reinforced plastics by a radiometric measurement technique

International Nuclear Information System (INIS)

Entine, Gerald; Afshari, Sia; Verlinden, Matt

1990-01-01

The demand for new high-performance plastics has greatly increased with advances in the performance characteristics of sophisticated reinforced engineering resins. However, conventional methods for the evaluation of the glass and filler contents of reinforced plastics are destructive, labor intensive, and time consuming. We have developed a new instrument, to address this problem, which provides for the rapid, accurate, and nondestructive measurement of glass or filler content in reinforced plastics. This instrument utilizes radiation transmission and scattering techniques for analytical measurement of glass, graphite and other fillers used in reinforced plastics. (author)

Marrakesh International Conference on Probability and Statistics

CERN Document Server

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.

Statistical and thermal physics with computer applications

CERN Document Server

Gould, Harvey

2010-01-01

This textbook carefully develops the main ideas and techniques of statistical and thermal physics and is intended for upper-level undergraduate courses. The authors each have more than thirty years' experience in teaching, curriculum development, and research in statistical and computational physics. Statistical and Thermal Physics begins with a qualitative discussion of the relation between the macroscopic and microscopic worlds and incorporates computer simulations throughout the book to provide concrete examples of important conceptual ideas. Unlike many contemporary texts on the

Lightweight and Statistical Techniques for Petascale Debugging: Correctness on Petascale Systems (CoPS) Preliminry Report

Energy Technology Data Exchange (ETDEWEB)

de Supinski, B R; Miller, B P; Liblit, B

2011-09-13

Petascale platforms with O(10{sup 5}) and O(10{sup 6}) processing cores are driving advancements in a wide range of scientific disciplines. These large systems create unprecedented application development challenges. Scalable correctness tools are critical to shorten the time-to-solution on these systems. Currently, many DOE application developers use primitive manual debugging based on printf or traditional debuggers such as TotalView or DDT. This paradigm breaks down beyond a few thousand cores, yet bugs often arise above that scale. Programmers must reproduce problems in smaller runs to analyze them with traditional tools, or else perform repeated runs at scale using only primitive techniques. Even when traditional tools run at scale, the approach wastes substantial effort and computation cycles. Continued scientific progress demands new paradigms for debugging large-scale applications. The Correctness on Petascale Systems (CoPS) project is developing a revolutionary debugging scheme that will reduce the debugging problem to a scale that human developers can comprehend. The scheme can provide precise diagnoses of the root causes of failure, including suggestions of the location and the type of errors down to the level of code regions or even a single execution point. Our fundamentally new strategy combines and expands three relatively new complementary debugging approaches. The Stack Trace Analysis Tool (STAT), a 2011 R&D 100 Award Winner, identifies behavior equivalence classes in MPI jobs and highlights behavior when elements of the class demonstrate divergent behavior, often the first indicator of an error. The Cooperative Bug Isolation (CBI) project has developed statistical techniques for isolating programming errors in widely deployed code that we will adapt to large-scale parallel applications. Finally, we are developing a new approach to parallelizing expensive correctness analyses, such as analysis of memory usage in the Memgrind tool. In the first two

Statistics for Physical Sciences An Introduction

CERN Document Server

Martin, Brian

2012-01-01

Statistical Methods for the Physical Sciences is an informal, relatively short, but systematic, guide to the more commonly used ideas and techniques in statistical analysis, as used in physical sciences, together with explanations of their origins. It steers a path between the extremes of a recipe of methods with a collection of useful formulas, and a full mathematical account of statistics, while at the same time developing the subject in a logical way. The book can be read in its entirety by anyone with a basic exposure to mathematics at the level of a first-year undergraduate student

IBM SPSS statistics 19 made simple

CERN Document Server

Gray, Colin D

2012-01-01

This new edition of one of the most widely read textbooks in its field introduces the reader to data analysis with the most powerful and versatile statistical package on the market: IBM SPSS Statistics 19. Each new release of SPSS Statistics features new options and other improvements. There remains a core of fundamental operating principles and techniques which have continued to apply to all releases issued in recent years and have been proved to be worth communicating in a small volume. This practical and informal book combines simplicity and clarity of presentation with a comprehensive trea

REANALYSIS OF F-STATISTIC GRAVITATIONAL-WAVE SEARCHES WITH THE HIGHER CRITICISM STATISTIC

International Nuclear Information System (INIS)

Bennett, M. F.; Melatos, A.; Delaigle, A.; Hall, P.

2013-01-01

We propose a new method of gravitational-wave detection using a modified form of higher criticism, a statistical technique introduced by Donoho and Jin. Higher criticism is designed to detect a group of sparse, weak sources, none of which are strong enough to be reliably estimated or detected individually. We apply higher criticism as a second-pass method to synthetic F-statistic and C-statistic data for a monochromatic periodic source in a binary system and quantify the improvement relative to the first-pass methods. We find that higher criticism on C-statistic data is more sensitive by ∼6% than the C-statistic alone under optimal conditions (i.e., binary orbit known exactly) and the relative advantage increases as the error in the orbital parameters increases. Higher criticism is robust even when the source is not monochromatic (e.g., phase-wandering in an accreting system). Applying higher criticism to a phase-wandering source over multiple time intervals gives a ∼> 30% increase in detectability with few assumptions about the frequency evolution. By contrast, in all-sky searches for unknown periodic sources, which are dominated by the brightest source, second-pass higher criticism does not provide any benefits over a first-pass search.

The new statistics: why and how.

Science.gov (United States)

Cumming, Geoff

2014-01-01

We need to make substantial changes to how we conduct research. First, in response to heightened concern that our published research literature is incomplete and untrustworthy, we need new requirements to ensure research integrity. These include prespecification of studies whenever possible, avoidance of selection and other inappropriate data-analytic practices, complete reporting, and encouragement of replication. Second, in response to renewed recognition of the severe flaws of null-hypothesis significance testing (NHST), we need to shift from reliance on NHST to estimation and other preferred techniques. The new statistics refers to recommended practices, including estimation based on effect sizes, confidence intervals, and meta-analysis. The techniques are not new, but adopting them widely would be new for many researchers, as well as highly beneficial. This article explains why the new statistics are important and offers guidance for their use. It describes an eight-step new-statistics strategy for research with integrity, which starts with formulation of research questions in estimation terms, has no place for NHST, and is aimed at building a cumulative quantitative discipline.

The application of full spectrum gamma-gamma techniques to density/photoelectric cross section logging

International Nuclear Information System (INIS)

Minette, D.C.; Hubner, B.G.; Koudelka, J.C.; Schmidt, M.

1986-01-01

The Compensated Z-Densilog instrument is a new full spectrum gamma-gamma logging instrument, measuring the density and photoelectric cross section (Pe) of the formation. This instrument represents an advancement over present instruments in that the observed gamma spectrum is sent to the surface as a full 256-channel spectrum instead of count rates in a few energy gates. This advancement is made possible by the use of high speed digital electronics which are protected from the high temperatures observed downhole by custom-built flasks. In this paper, the new advanced electronics are considered in some detail. This consideration includes a comparison of full spectrum data acquisition with the multiple discriminator window technique, which is the foundation of the ''few gate'' method. Both of these methods are critiqued based upon electronic stability and the information obtained. The full spectrum provided by high speed electronics facilitates a much more sophisticated data analysis. This data analysis, based on phenomenological model of the instrument (Minette, 1984), includes real time compensation for changes in detector gain and crystal resolution. It also includes a ''four-dimensional'' rib-spine plot, which separates the compensation for mudcake density from the compensation for the Pe of the formation and the mudcake. Also included in the software are real time error minimization and real time decision-making techniques. These techniques maximize the sensitivity of the instrument to the density and Pe of the formation and minimize error due to statistical fluctuations. Gain and resolution compensation completes the data analysis. This compensation virtually eliminates density and Pe errors caused by changing gain and resolution

Correlation analysis of energy indicators for sustainable development using multivariate statistical techniques

International Nuclear Information System (INIS)

Carneiro, Alvaro Luiz Guimaraes; Santos, Francisco Carlos Barbosa dos

2007-01-01

Energy is an essential input for social development and economic growth. The production and use of energy cause environmental degradation at all levels, being local, regional and global such as, combustion of fossil fuels causing air pollution; hydropower often causes environmental damage due to the submergence of large areas of land; and global climate change associated with the increasing concentration of greenhouse gases in the atmosphere. As mentioned in chapter 9 of Agenda 21, the Energy is essential to economic and social development and improved quality of life. Much of the world's energy, however, is currently produced and consumed in ways that could not be sustained if technologies were remain constant and if overall quantities were to increase substantially. All energy sources will need to be used in ways that respect the atmosphere, human health, and the environment as a whole. The energy in the context of sustainable development needs a set of quantifiable parameters, called indicators, to measure and monitor important changes and significant progress towards the achievement of the objectives of sustainable development policies. The indicators are divided into four dimensions: social, economic, environmental and institutional. This paper shows a methodology of analysis using Multivariate Statistical Technique that provide the ability to analyse complex sets of data. The main goal of this study is to explore the correlation analysis among the indicators. The data used on this research work, is an excerpt of IBGE (Instituto Brasileiro de Geografia e Estatistica) data census. The core indicators used in this study follows The IAEA (International Atomic Energy Agency) framework: Energy Indicators for Sustainable Development. (author)

Remote sensing estimation of the total phosphorus concentration in a large lake using band combinations and regional multivariate statistical modeling techniques.

Science.gov (United States)

Gao, Yongnian; Gao, Junfeng; Yin, Hongbin; Liu, Chuansheng; Xia, Ting; Wang, Jing; Huang, Qi

2015-03-15

Remote sensing has been widely used for ater quality monitoring, but most of these monitoring studies have only focused on a few water quality variables, such as chlorophyll-a, turbidity, and total suspended solids, which have typically been considered optically active variables. Remote sensing presents a challenge in estimating the phosphorus concentration in water. The total phosphorus (TP) in lakes has been estimated from remotely sensed observations, primarily using the simple individual band ratio or their natural logarithm and the statistical regression method based on the field TP data and the spectral reflectance. In this study, we investigated the possibility of establishing a spatial modeling scheme to estimate the TP concentration of a large lake from multi-spectral satellite imagery using band combinations and regional multivariate statistical modeling techniques, and we tested the applicability of the spatial modeling scheme. The results showed that HJ-1A CCD multi-spectral satellite imagery can be used to estimate the TP concentration in a lake. The correlation and regression analysis showed a highly significant positive relationship between the TP concentration and certain remotely sensed combination variables. The proposed modeling scheme had a higher accuracy for the TP concentration estimation in the large lake compared with the traditional individual band ratio method and the whole-lake scale regression-modeling scheme. The TP concentration values showed a clear spatial variability and were high in western Lake Chaohu and relatively low in eastern Lake Chaohu. The northernmost portion, the northeastern coastal zone and the southeastern portion of western Lake Chaohu had the highest TP concentrations, and the other regions had the lowest TP concentration values, except for the coastal zone of eastern Lake Chaohu. These results strongly suggested that the proposed modeling scheme, i.e., the band combinations and the regional multivariate

Introduction to high-dimensional statistics

CERN Document Server

Giraud, Christophe

2015-01-01

Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise.Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for ha

Newer techniques of mechanical ventilation: an overview.

Science.gov (United States)

Donn, Steven M; Sinha, Sunil K

2002-10-01

The introduction of newer, state-of-the-art, microprocessor controlled ventilator systems provides clinicians with opportunities to apply a number of advanced ventilatory modalities which were not previously available for treating newborns. Some of these techniques will need further scientific evaluation in controlled trials, but this should not preclude their use in clinical settings, as their safety has already been proved by "standard setters" for use in neonates. There is a firm physiological rationale for their use, and individual centres have already acquired substantial experience in the application of these modalities. The trend towards increasing sophistication and greater versatility is likely to continue, and clinicians involved in the care of sick newborn infants must keep abreast of these developments.

Statistics and probability with applications for engineers and scientists

CERN Document Server

Gupta, Bhisham C

2013-01-01

Introducing the tools of statistics and probability from the ground up An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences. Unique among books of this kind, Statistics and Prob

Statistical core design

International Nuclear Information System (INIS)

Oelkers, E.; Heller, A.S.; Farnsworth, D.A.; Kearfott, K.J.

1978-01-01

The report describes the statistical analysis of DNBR thermal-hydraulic margin of a 3800 MWt, 205-FA core under design overpower conditions. The analysis used LYNX-generated data at predetermined values of the input variables whose uncertainties were to be statistically combined. LYNX data were used to construct an efficient response surface model in the region of interest; the statistical analysis was accomplished through the evaluation of core reliability; utilizing propagation of the uncertainty distributions of the inputs. The response surface model was implemented in both the analytical error propagation and Monte Carlo Techniques. The basic structural units relating to the acceptance criteria are fuel pins. Therefore, the statistical population of pins with minimum DNBR values smaller than specified values is determined. The specified values are designated relative to the most probable and maximum design DNBR values on the power limiting pin used in present design analysis, so that gains over the present design criteria could be assessed for specified probabilistic acceptance criteria. The results are equivalent to gains ranging from 1.2 to 4.8 percent of rated power dependent on the acceptance criterion. The corresponding acceptance criteria range from 95 percent confidence that no pin will be in DNB to 99.9 percent of the pins, which are expected to avoid DNB

A statistical forecast model using the time-scale decomposition technique to predict rainfall during flood period over the middle and lower reaches of the Yangtze River Valley

Science.gov (United States)

Hu, Yijia; Zhong, Zhong; Zhu, Yimin; Ha, Yao

2018-04-01

In this paper, a statistical forecast model using the time-scale decomposition method is established to do the seasonal prediction of the rainfall during flood period (FPR) over the middle and lower reaches of the Yangtze River Valley (MLYRV). This method decomposites the rainfall over the MLYRV into three time-scale components, namely, the interannual component with the period less than 8 years, the interdecadal component with the period from 8 to 30 years, and the interdecadal component with the period larger than 30 years. Then, the predictors are selected for the three time-scale components of FPR through the correlation analysis. At last, a statistical forecast model is established using the multiple linear regression technique to predict the three time-scale components of the FPR, respectively. The results show that this forecast model can capture the interannual and interdecadal variation of FPR. The hindcast of FPR during 14 years from 2001 to 2014 shows that the FPR can be predicted successfully in 11 out of the 14 years. This forecast model performs better than the model using traditional scheme without time-scale decomposition. Therefore, the statistical forecast model using the time-scale decomposition technique has good skills and application value in the operational prediction of FPR over the MLYRV.

Statistical Mechanics of Turbulent Flows

International Nuclear Information System (INIS)

Cambon, C

2004-01-01

This is a handbook for a computational approach to reacting flows, including background material on statistical mechanics. In this sense, the title is somewhat misleading with respect to other books dedicated to the statistical theory of turbulence (e.g. Monin and Yaglom). In the present book, emphasis is placed on modelling (engineering closures) for computational fluid dynamics. The probabilistic (pdf) approach is applied to the local scalar field, motivated first by the nonlinearity of chemical source terms which appear in the transport equations of reacting species. The probabilistic and stochastic approaches are also used for the velocity field and particle position; nevertheless they are essentially limited to Lagrangian models for a local vector, with only single-point statistics, as for the scalar. Accordingly, conventional techniques, such as single-point closures for RANS (Reynolds-averaged Navier-Stokes) and subgrid-scale models for LES (large-eddy simulations), are described and in some cases reformulated using underlying Langevin models and filtered pdfs. Even if the theoretical approach to turbulence is not discussed in general, the essentials of probabilistic and stochastic-processes methods are described, with a useful reminder concerning statistics at the molecular level. The book comprises 7 chapters. Chapter 1 briefly states the goals and contents, with a very clear synoptic scheme on page 2. Chapter 2 presents definitions and examples of pdfs and related statistical moments. Chapter 3 deals with stochastic processes, pdf transport equations, from Kramer-Moyal to Fokker-Planck (for Markov processes), and moments equations. Stochastic differential equations are introduced and their relationship to pdfs described. This chapter ends with a discussion of stochastic modelling. The equations of fluid mechanics and thermodynamics are addressed in chapter 4. Classical conservation equations (mass, velocity, internal energy) are derived from their

Statistical Model Checking of Rich Models and Properties

DEFF Research Database (Denmark)

Poulsen, Danny Bøgsted

in undecidability issues for the traditional model checking approaches. Statistical model checking has proven itself a valuable supplement to model checking and this thesis is concerned with extending this software validation technique to stochastic hybrid systems. The thesis consists of two parts: the first part...... motivates why existing model checking technology should be supplemented by new techniques. It also contains a brief introduction to probability theory and concepts covered by the six papers making up the second part. The first two papers are concerned with developing online monitoring techniques...... systems. The fifth paper shows how stochastic hybrid automata are useful for modelling biological systems and the final paper is concerned with showing how statistical model checking is efficiently distributed. In parallel with developing the theory contained in the papers, a substantial part of this work...

An Overview of Short-term Statistical Forecasting Methods

DEFF Research Database (Denmark)

Elias, Russell J.; Montgomery, Douglas C.; Kulahci, Murat

2006-01-01

An overview of statistical forecasting methodology is given, focusing on techniques appropriate to short- and medium-term forecasts. Topics include basic definitions and terminology, smoothing methods, ARIMA models, regression methods, dynamic regression models, and transfer functions. Techniques...... for evaluating and monitoring forecast performance are also summarized....

A modified bonded-interface technique with improved features for studying indentation damage of materials

International Nuclear Information System (INIS)

Low, I.M.

1998-01-01

A modified 'bonded-interface' technique with improved features for studying contact damage of ceramic (Al 2 O 3 graded Al 2 TiO 5 /Al 2 O 3 , Ti 3 SiC 2 ) and non-ceramic (epoxy, tooth) materials is developed and compared with the conventional method. This technique enables the surface damage around and below an indentor to be studied. When used in conjunction with Nomarski illumination and atomic force microscopy, this technique can reveal substantial information on the topography of indentation surface damage. In particular, it is ideal for monitoring the evolution of deformation-micro fracture damage of quasi-plastic materials. The technique is much less sophisticated, less time consuming, and user-friendly. It does not require a highly experience user to be proficient in the procedure. When compared with the conventional tool- clamp method, this modified technique gives similar, if not, identical results. Copyright (1998) Australasian Ceramic Society

A DIY guide to statistical strategy

International Nuclear Information System (INIS)

Pregibon, D.

1986-01-01

This chapter is a do it yourself (DIY) guide to developing statistical strategy for a particular data analysis task. The primary audience of the chapter is research statisticians. The material should also be of interest to nonstatisticians, especially knowledge engineers, who are interested in using statistical data analysis as an application domain for Artificial Intelligence techniques. The do's and don'ts of strategy development are outlined. The ''linear regression'' task is used to illustrate many of the ideas

Probability and statistics for computer science

CERN Document Server

Johnson, James L

2011-01-01

Comprehensive and thorough development of both probability and statistics for serious computer scientists; goal-oriented: ""to present the mathematical analysis underlying probability results"" Special emphases on simulation and discrete decision theory Mathematically-rich, but self-contained text, at a gentle pace Review of calculus and linear algebra in an appendix Mathematical interludes (in each chapter) which examine mathematical techniques in the context of probabilistic or statistical importance Numerous section exercises, summaries, historical notes, and Further Readings for reinforcem

Telling the truth with statistics

CERN Multimedia

CERN. Geneva; CERN. Geneva. Audiovisual Unit

2002-01-01

This course of lectures will cover probability, distributions, fitting, errors and confidence levels, for practising High Energy Physicists who need to use Statistical techniques to express their results. Concentrating on these appropriate specialist techniques means that they can be covered in appropriate depth, while assuming only the knowledge and experience of a typical Particle Physicist. The different definitions of probability will be explained, and it will be appear why this basic subject is so controversial; there are several viewpoints and it is important to understand them all, rather than abusing the adherents of different beliefs. Distributions will be covered: the situations they arise in, their useful properties, and the amazing result of the Central Limit Theorem. Fitting a parametrisation to a set of data is one of the most widespread uses of statistics: these are lots of ways of doing this and these will be presented, with discussion of which is appropriate in different circumstances. This t...

Ultra-mini PNL (UMP): Material, indications, technique, advantages and results.

Science.gov (United States)

Desai, Janak D

2017-01-01

Stone disease has afflicted mankind since centuries; records from ancient civilisations of India and Egypt have shown stones in human bodies. The scientific mind of humans has always made smart endeavours to remove the kidney stones. From large instruments made like the beaks of different animals and birds in 600 BC (Indian civilisation) to extremely sophisticated and miniaturised endoscopic intruments of today the human race has travelled a long way. The theme has always been to remove the stones with minimal morbidity and mortality and with minimum pain to the patient. The article takes you through the journey of instruments used in 600 BC until today. The story of instrumentation is a symbiosis of the medical minds along with engineering advances. The story of miniaturisation could not have moved further without the development of lasers, fiberoptics and sophisticated cameras. As the field stands today, we remove more complex stones by larger endoscopic intervention and smaller stones by miniaturised instruments. The article discusses all the merits and shortcomings of various techniques: from open surgery to standard PCNL to Mini PCNL to Ultra- Mini PCNL to Micro-PCNL.

Statistics of Monte Carlo methods used in radiation transport calculation

International Nuclear Information System (INIS)

Datta, D.

2009-01-01

Radiation transport calculation can be carried out by using either deterministic or statistical methods. Radiation transport calculation based on statistical methods is basic theme of the Monte Carlo methods. The aim of this lecture is to describe the fundamental statistics required to build the foundations of Monte Carlo technique for radiation transport calculation. Lecture note is organized in the following way. Section (1) will describe the introduction of Basic Monte Carlo and its classification towards the respective field. Section (2) will describe the random sampling methods, a key component of Monte Carlo radiation transport calculation, Section (3) will provide the statistical uncertainty of Monte Carlo estimates, Section (4) will describe in brief the importance of variance reduction techniques while sampling particles such as photon, or neutron in the process of radiation transport

Enseignement technique : Séminaire de l'enseigement technique

CERN Multimedia

2004-01-01

Mardi 4 mai 2004 SEMINAIRE DE L'ENSEIGNEMENT TECHNIQUE de 14:00 à 17:00 - Training Centre Auditorium - bât. 593 Le SPC - Statistical Process Control - dans une démarche de qualité totale Hakim Bourahla, Maurice Arrius, Charbel Tannous - ABW Concept - F-74950 SCIONZIER, France Ce nouveau séminaire de l'Enseignement Technique sera consacré à la présentation du SPC, le Statistical Process Control. Le SPC apporte une grande efficacité dans l'amélioration de la qualité des produits. Cette méthode, permettant d'assurer une qualité optimum à l'aide d'un outil statistique, est fondée sur deux concepts de base : le suivi et le pilotage des procédés industriels par cartes de contrôle, et l'étude des capabilités des systèmes de production. - Origine et objectifs du SPC - Concepts du ...

Enseignement technique : Séminaire de l'enseignement technique

CERN Multimedia

2004-01-01

Mardi 4 mai 2004 SEMINAIRE DE L'ENSEIGNEMENT TECHNIQUE de 14:00 à 17:00 - Training Centre Auditorium - bât. 593 Le SPC - Statistical Process Control - dans une démarche de qualité totale Hakim Bourahla, Maurice Arrius, Charbel Tannous - ABW Concept - F-74950 SCIONZIER, France Ce nouveau séminaire de l'Enseignement Technique sera consacré à la présentation du SPC, le Statistical Process Control. Le SPC apporte une grande efficacité dans l'amélioration de la qualité des produits. Cette méthode, permettant d'assurer une qualité optimum à l'aide d'un outil statistique, est fondée sur deux concepts de base : le suivi et le pilotage des procédés industriels par cartes de contrôle, et l'étude des capabilités des systèmes de production. - Origine et objectifs du SPC - Concepts du ...

Sophisticated Epistemologies of Physics versus High-Stakes Tests: How Do Elite High School Students Respond to Competing Influences about How to Learn Physics?

Science.gov (United States)

Yerdelen-Damar, Sevda; Elby, Andrew

2016-01-01

This study investigates how elite Turkish high school physics students claim to approach learning physics when they are simultaneously (i) engaged in a curriculum that led to significant gains in their epistemological sophistication and (ii) subject to a high-stakes college entrance exam. Students reported taking surface (rote) approaches to…

Initiating statistical maintenance optimization

International Nuclear Information System (INIS)

Doyle, E. Kevin; Tuomi, Vesa; Rowley, Ian

2007-01-01

Since the 1980 s maintenance optimization has been centered around various formulations of Reliability Centered Maintenance (RCM). Several such optimization techniques have been implemented at the Bruce Nuclear Station. Further cost refinement of the Station preventive maintenance strategy includes evaluation of statistical optimization techniques. A review of successful pilot efforts in this direction is provided as well as initial work with graphical analysis. The present situation reguarding data sourcing, the principle impediment to use of stochastic methods in previous years, is discussed. The use of Crowe/AMSAA (Army Materials Systems Analysis Activity) plots is demonstrated from the point of view of justifying expenditures in optimization efforts. (author)

Гибкое решение задачи оптимизации двухслойного персептрона по его размеру и соотношению гладких искажений в обучающем множестве для классификации объектов простой структуры

Directory of Open Access Journals (Sweden)

Vadim V. Romanuke

2017-12-01

Conclusions. The obtained flexible solution fits other datasets similar to EEACL26. Number of classes can vary between 20 and 30, and number of features can vary between a few hundred and a few thousand. The stated example of achieving high-performance classification with two-layer perceptrons is a part of the common technique of statistical optimization relating to neural network classifiers. For a more sophisticated dataset of objects, this technique is built and executed in a similar way.

Three-dimensional MR imaging of the cerebrospinal system with the RARE technique

International Nuclear Information System (INIS)

Hennig, J.; Ott, D.; Ylayasski, J.

1987-01-01

Three-dimensional RARE myelography is a fast technique for high-resolution imaging of the cerebrospinal fluid. A data set with 1 x 1 x 1-mm resolution can be generated with a 12-minute acquisition time. Sophisticated three-dimensional display algorithms allow reconstruction of planes at arbitrary angles and full three-dimensional displays, which yield extremely useful information for neurosurgical planning. Additionally, the injection of contrast agent can be simulated on the computer and communication pathways between structures of interest can be found noninvasively

Understanding search trees via statistical physics

Indian Academy of Sciences (India)

ary search tree model (where stands for the number of branches of the search tree), an important problem for data storage in computer science, using a variety of statistical physics techniques that allow us to obtain exact asymptotic results.

Multivariate Statistical Process Control Charts: An Overview

OpenAIRE

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...

A statistical method for the detection of alternative splicing using RNA-seq.

Directory of Open Access Journals (Sweden)

Liguo Wang

2010-01-01

Full Text Available Deep sequencing of transcriptome (RNA-seq provides unprecedented opportunity to interrogate plausible mRNA splicing patterns by mapping RNA-seq reads to exon junctions (thereafter junction reads. In most previous studies, exon junctions were detected by using the quantitative information of junction reads. The quantitative criterion (e.g. minimum of two junction reads, although is straightforward and widely used, usually results in high false positive and false negative rates, owning to the complexity of transcriptome. Here, we introduced a new metric, namely Minimal Match on Either Side of exon junction (MMES, to measure the quality of each junction read, and subsequently implemented an empirical statistical model to detect exon junctions. When applied to a large dataset (>200M reads consisting of mouse brain, liver and muscle mRNA sequences, and using independent transcripts databases as positive control, our method was proved to be considerably more accurate than previous ones, especially for detecting junctions originated from low-abundance transcripts. Our results were also confirmed by real time RT-PCR assay. The MMES metric can be used either in this empirical statistical model or in other more sophisticated classifiers, such as logistic regression.

Statistical Model Checking for Biological Systems

DEFF Research Database (Denmark)

David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel

2014-01-01

Statistical Model Checking (SMC) is a highly scalable simulation-based verification approach for testing and estimating the probability that a stochastic system satisfies a given linear temporal property. The technique has been applied to (discrete and continuous time) Markov chains, stochastic...

Preserved statistical learning of tonal and linguistic material in congenital amusia.

Science.gov (United States)

Omigie, Diana; Stewart, Lauren

2011-01-01

Congenital amusia is a lifelong disorder whereby individuals have pervasive difficulties in perceiving and producing music. In contrast, typical individuals display a sophisticated understanding of musical structure, even in the absence of musical training. Previous research has shown that they acquire this knowledge implicitly, through exposure to music's statistical regularities. The present study tested the hypothesis that congenital amusia may result from a failure to internalize statistical regularities - specifically, lower-order transitional probabilities. To explore the specificity of any potential deficits to the musical domain, learning was examined with both tonal and linguistic material. Participants were exposed to structured tonal and linguistic sequences and, in a subsequent test phase, were required to identify items which had been heard in the exposure phase, as distinct from foils comprising elements that had been present during exposure, but presented in a different temporal order. Amusic and control individuals showed comparable learning, for both tonal and linguistic material, even when the tonal stream included pitch intervals around one semitone. However analysis of binary confidence ratings revealed that amusic individuals have less confidence in their abilities and that their performance in learning tasks may not be contingent on explicit knowledge formation or level of awareness to the degree shown in typical individuals. The current findings suggest that the difficulties amusic individuals have with real-world music cannot be accounted for by an inability to internalize lower-order statistical regularities but may arise from other factors.

Preserved Statistical Learning of Tonal and Linguistic Material in Congenital Amusia

Directory of Open Access Journals (Sweden)

Diana eOmigie

2011-06-01

Full Text Available Congenital amusia is a lifelong disorder whereby individuals have pervasive difficulties in perceiving and producing music. In contrast, typical individuals display a sophisticated understanding of musical structure, even in the absence of musical training. Previous research has shown that they acquire this knowledge implicitly, through exposure to music’s statistical regularities. The present study tested the hypothesis that congenital amusia may result from a failure to internalize statistical regularities - specifically, lower-order transitional probabilities. To explore the specificity of any potential deficits to the musical domain, learning was examined with both tonal and linguistic material. Participants were exposed to structured tonal and linguistic sequences and, in a subsequent test phase, were required to identify items which had been heard in the exposure phase, as distinct from foils comprising elements that had been present during exposure, but presented in a different temporal order. Amusic and control individuals showed comparable learning, for both tonal and linguistic material, even when the tonal stream included pitch intervals around one semitone. However analysis of binary confidence ratings revealed that amusic individuals have less confidence in their abilities and that their performance in learning tasks may not be contingent on explicit knowledge formation or level of awareness to the degree shown in typical individuals. The current findings suggest that the difficulties amusic individuals have with real-world music cannot be accounted for by an inability to internalize lower-order statistical regularities but may arise from other factors.

Are medical articles highlighting detailed statistics more cited?

Directory of Open Access Journals (Sweden)

Mike Thelwall

2015-06-01

Full Text Available When conducting a literature review, it is natural to search for articles and read their abstracts in order to select papers to read fully. Hence, informative abstracts are important to ensure that research is read. The description of a paper's methods may help to give confidence that a study is of high quality. This article assesses whether medical articles that mention three statistical methods, each of which is arguably indicative of a more detailed statistical analysis than average, are more highly cited. The results show that medical articles mentioning Bonferroni corrections, bootstrapping and effect size tend to be 7%, 8% and 15% more highly ranked for citations than average, respectively. Although this is consistent with the hypothesis that mentioning more detailed statistical techniques generate more highly cited research, these techniques may also tend to be used in more highly cited areas of Medicine.

Evaluation of radiographic imaging techniques in lung nodule detection

International Nuclear Information System (INIS)

Ho, J.T.; Kruger, R.A.

1989-01-01

Dual-energy radiography appears to be the most effective technique to address bone superposition that compromises conventional chest radiography. A dual-energy, single-exposure, film-based technique was compared with a dual-energy, dual-exposure technique and conventional chest radiography in a simulated lung nodule detection study. Observers detected more nodules on images produced by dual-energy techniques than on images produced by conventional chest radiography. The difference between dual-energy and conventional chest radiography is statistically significant and the difference between dual-energy, dual-exposure and single-exposure techniques is statistically insignificant. The single-exposure technique has the potential to replace the dual-exposure technique in future clinical application

A scanning electron microscope study and statistical analysis of adipocyte morphology in lipofilling: comparing the effects of harvesting and purification procedures with 2 different techniques.

Science.gov (United States)

Rubino, Corrado; Mazzarello, Vittorio; Faenza, Mario; Montella, Andrea; Santanelli, Fabio; Farace, Francesco

2015-06-01

The aim of this study was to evaluate the effects on adipocyte morphology of 2 techniques of fat harvesting and of fat purification in lipofilling, considering that the number of viable healthy adipocytes is important in fat survival in recipient areas of lipofilling. Fat harvesting was performed in 10 female patients from flanks, on one side with a 2-mm Coleman cannula and on the other side with a 3-mm Mercedes cannula. Thirty milliliter of fat tissue from each side was collected and divided into three 10 mL syringes: A, B, and C. The fat inside syringe A was left untreated, the fat in syringe B underwent simple sedimentation, and the fat inside syringe C underwent centrifugation at 3000 rpm for 3 minutes. Each fat graft specimen was processed for examination under low-vacuum scanning electron microscope. Diameter (μ) and number of adipocytes per square millimeter and number of altered adipocytes per square millimeter were evaluated. Untreated specimens harvested with the 2 different techniques were first compared, then sedimented versus centrifuged specimens harvested with the same technique were compared. Statistical analysis was performed using Wilcoxon signed rank test. The number of adipocytes per square millimeter was statistically higher in specimens harvested with the 3-mm Mercedes cannula (P = 0.0310). The number of altered cells was statistically higher in centrifuged specimens than in sedimented ones using both methods of fat harvesting (P = 0.0080) with a 2-mm Coleman cannula and (P = 0.0050) with a 3-mm Mercedes cannula. Alterations in adipocyte morphology consisted in wrinkling of the membrane, opening of pore with leakage of oily material, reduction of cellular diameter, and total collapse of the cellular membrane. Fat harvesting by a 3-mm cannula results in a higher number of adipocytes and centrifugation of the harvested fat results in a higher number of morphologic altered cells than sedimentation.

Predicting radiotherapy outcomes using statistical learning techniques

International Nuclear Information System (INIS)

El Naqa, Issam; Bradley, Jeffrey D; Deasy, Joseph O; Lindsay, Patricia E; Hope, Andrew J

2009-01-01

Radiotherapy outcomes are determined by complex interactions between treatment, anatomical and patient-related variables. A common obstacle to building maximally predictive outcome models for clinical practice is the failure to capture potential complexity of heterogeneous variable interactions and applicability beyond institutional data. We describe a statistical learning methodology that can automatically screen for nonlinear relations among prognostic variables and generalize to unseen data before. In this work, several types of linear and nonlinear kernels to generate interaction terms and approximate the treatment-response function are evaluated. Examples of institutional datasets of esophagitis, pneumonitis and xerostomia endpoints were used. Furthermore, an independent RTOG dataset was used for 'generalizabilty' validation. We formulated the discrimination between risk groups as a supervised learning problem. The distribution of patient groups was initially analyzed using principle components analysis (PCA) to uncover potential nonlinear behavior. The performance of the different methods was evaluated using bivariate correlations and actuarial analysis. Over-fitting was controlled via cross-validation resampling. Our results suggest that a modified support vector machine (SVM) kernel method provided superior performance on leave-one-out testing compared to logistic regression and neural networks in cases where the data exhibited nonlinear behavior on PCA. For instance, in prediction of esophagitis and pneumonitis endpoints, which exhibited nonlinear behavior on PCA, the method provided 21% and 60% improvements, respectively. Furthermore, evaluation on the independent pneumonitis RTOG dataset demonstrated good generalizabilty beyond institutional data in contrast with other models. This indicates that the prediction of treatment response can be improved by utilizing nonlinear kernel methods for discovering important nonlinear interactions among model

Workshop on Analytical Methods in Statistics

CERN Document Server

Jurečková, Jana; Maciak, Matúš; Pešta, Michal

2017-01-01

This volume collects authoritative contributions on analytical methods and mathematical statistics. The methods presented include resampling techniques; the minimization of divergence; estimation theory and regression, eventually under shape or other constraints or long memory; and iterative approximations when the optimal solution is difficult to achieve. It also investigates probability distributions with respect to their stability, heavy-tailness, Fisher information and other aspects, both asymptotically and non-asymptotically. The book not only presents the latest mathematical and statistical methods and their extensions, but also offers solutions to real-world problems including option pricing. The selected, peer-reviewed contributions were originally presented at the workshop on Analytical Methods in Statistics, AMISTAT 2015, held in Prague, Czech Republic, November 10-13, 2015.

Isotopic safeguards statistics

International Nuclear Information System (INIS)

Timmerman, C.L.; Stewart, K.B.

1978-06-01

The methods and results of our statistical analysis of isotopic data using isotopic safeguards techniques are illustrated using example data from the Yankee Rowe reactor. The statistical methods used in this analysis are the paired comparison and the regression analyses. A paired comparison results when a sample from a batch is analyzed by two different laboratories. Paired comparison techniques can be used with regression analysis to detect and identify outlier batches. The second analysis tool, linear regression, involves comparing various regression approaches. These approaches use two basic types of models: the intercept model (y = α + βx) and the initial point model [y - y 0 = β(x - x 0 )]. The intercept model fits strictly the exposure or burnup values of isotopic functions, while the initial point model utilizes the exposure values plus the initial or fabricator's data values in the regression analysis. Two fitting methods are applied to each of these models. These methods are: (1) the usual least squares fitting approach where x is measured without error, and (2) Deming's approach which uses the variance estimates obtained from the paired comparison results and considers x and y are both measured with error. The Yankee Rowe data were first measured by Nuclear Fuel Services (NFS) and remeasured by Nuclear Audit and Testing Company (NATCO). The ratio of Pu/U versus 235 D (in which 235 D is the amount of depleted 235 U expressed in weight percent) using actual numbers is the isotopic function illustrated. Statistical results using the Yankee Rowe data indicates the attractiveness of Deming's regression model over the usual approach by simple comparison of the given regression variances with the random variance from the paired comparison results

Intermediate statistics a modern approach

CERN Document Server

Stevens, James P

2007-01-01

Written for those who use statistical techniques, this text focuses on a conceptual understanding of the material. It uses definitional formulas on small data sets to provide conceptual insight into what is being measured. It emphasizes the assumptions underlying each analysis, and shows how to test the critical assumptions using SPSS or SAS.

The tool for the automatic analysis of lexical sophistication (TAALES): version 2.0.

Science.gov (United States)

Kyle, Kristopher; Crossley, Scott; Berger, Cynthia

2017-07-11

This study introduces the second release of the Tool for the Automatic Analysis of Lexical Sophistication (TAALES 2.0), a freely available and easy-to-use text analysis tool. TAALES 2.0 is housed on a user's hard drive (allowing for secure data processing) and is available on most operating systems (Windows, Mac, and Linux). TAALES 2.0 adds 316 indices to the original tool. These indices are related to word frequency, word range, n-gram frequency, n-gram range, n-gram strength of association, contextual distinctiveness, word recognition norms, semantic network, and word neighbors. In this study, we validated TAALES 2.0 by investigating whether its indices could be used to model both holistic scores of lexical proficiency in free writes and word choice scores in narrative essays. The results indicated that the TAALES 2.0 indices could be used to explain 58% of the variance in lexical proficiency scores and 32% of the variance in word-choice scores. Newly added TAALES 2.0 indices, including those related to n-gram association strength, word neighborhood, and word recognition norms, featured heavily in these predictor models, suggesting that TAALES 2.0 represents a substantial upgrade.

Neural engineering from advanced biomaterials to 3D fabrication techniques

CERN Document Server

Kaplan, David

2016-01-01

This book covers the principles of advanced 3D fabrication techniques, stem cells and biomaterials for neural engineering. Renowned contributors cover topics such as neural tissue regeneration, peripheral and central nervous system repair, brain-machine interfaces and in vitro nervous system modeling. Within these areas, focus remains on exciting and emerging technologies such as highly developed neuroprostheses and the communication channels between the brain and prostheses, enabling technologies that are beneficial for development of therapeutic interventions, advanced fabrication techniques such as 3D bioprinting, photolithography, microfluidics, and subtractive fabrication, and the engineering of implantable neural grafts. There is a strong focus on stem cells and 3D bioprinting technologies throughout the book, including working with embryonic, fetal, neonatal, and adult stem cells and a variety of sophisticated 3D bioprinting methods for neural engineering applications. There is also a strong focus on b...

xSyn: A Software Tool for Identifying Sophisticated 3-Way Interactions From Cancer Expression Data

Directory of Open Access Journals (Sweden)

Baishali Bandyopadhyay

2017-08-01

Full Text Available Background: Constructing gene co-expression networks from cancer expression data is important for investigating the genetic mechanisms underlying cancer. However, correlation coefficients or linear regression models are not able to model sophisticated relationships among gene expression profiles. Here, we address the 3-way interaction that 2 genes’ expression levels are clustered in different space locations under the control of a third gene’s expression levels. Results: We present xSyn, a software tool for identifying such 3-way interactions from cancer gene expression data based on an optimization procedure involving the usage of UPGMA (Unweighted Pair Group Method with Arithmetic Mean and synergy. The effectiveness is demonstrated by application to 2 real gene expression data sets. Conclusions: xSyn is a useful tool for decoding the complex relationships among gene expression profiles. xSyn is available at http://www.bdxconsult.com/xSyn.html .

When not to copy: female fruit flies use sophisticated public information to avoid mated males

Science.gov (United States)

Loyau, Adeline; Blanchet, Simon; van Laere, Pauline; Clobert, Jean; Danchin, Etienne

2012-10-01

Semen limitation (lack of semen to fertilize all of a female's eggs) imposes high fitness costs to female partners. Females should therefore avoid mating with semen-limited males. This can be achieved by using public information extracted from watching individual males' previous copulating activities. This adaptive preference should be flexible given that semen limitation is temporary. We first demonstrate that the number of offspring produced by males Drosophila melanogaster gradually decreases over successive copulations. We then show that females avoid mating with males they just watched copulating and that visual public cues are sufficient to elicit this response. Finally, after males were given the time to replenish their sperm reserves, females did not avoid the males they previously saw copulating anymore. These results suggest that female fruit flies may have evolved sophisticated behavioural processes of resistance to semen-limited males, and demonstrate unsuspected adaptive context-dependent mate choice in an invertebrate.

The Network Structure of Symptoms of the Diagnostic and Statistical Manual of Mental Disorders.

Science.gov (United States)

Boschloo, Lynn; van Borkulo, Claudia D; Rhemtulla, Mijke; Keyes, Katherine M; Borsboom, Denny; Schoevers, Robert A

2015-01-01

Although current classification systems have greatly contributed to the reliability of psychiatric diagnoses, they ignore the unique role of individual symptoms and, consequently, potentially important information is lost. The network approach, in contrast, assumes that psychopathology results from the causal interplay between psychiatric symptoms and focuses specifically on these symptoms and their complex associations. By using a sophisticated network analysis technique, this study constructed an empirically based network structure of 120 psychiatric symptoms of twelve major DSM-IV diagnoses using cross-sectional data of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, second wave; N = 34,653). The resulting network demonstrated that symptoms within the same diagnosis showed differential associations and indicated that the strategy of summing symptoms, as in current classification systems, leads to loss of information. In addition, some symptoms showed strong connections with symptoms of other diagnoses, and these specific symptom pairs, which both concerned overlapping and non-overlapping symptoms, may help to explain the comorbidity across diagnoses. Taken together, our findings indicated that psychopathology is very complex and can be more adequately captured by sophisticated network models than current classification systems. The network approach is, therefore, promising in improving our understanding of psychopathology and moving our field forward.

Estudo teórico das transições eletrônicas usando métodos simples e sofisticados Theoretical study of electronic transitions using simple and sophisticated methods

Directory of Open Access Journals (Sweden)

Nelson H. Morgon

2013-01-01

Full Text Available In this paper, the use of both simple and sophisticated models in the study of electronic transitions was explored for a set of molecular systems: C2H4, C4H4, C4H6, C6H6, C6H8, "C8", C60, and [H2NCHCH(CHCHkCHNH2]+, where k = 0 to 4. The simple model of the free particle (1D, 2D, and 3D boxes, rings or spherical surfaces, considering the boundary conditions, was found to yield similar results to the sophisticated theoretical methods such as EOM-CCSD/6-311++G** or TD(NStates=5,Root=1-M06-2X/6-311++G**.

An Applied Statistics Course for Systematics and Ecology PhD Students

Science.gov (United States)

Ojeda, Mario Miguel; Sosa, Victoria

2002-01-01

Statistics education is under review at all educational levels. Statistical concepts, as well as the use of statistical methods and techniques, can be taught in at least two contrasting ways. Specifically, (1) teaching can be theoretically and mathematically oriented, or (2) it can be less mathematically oriented being focused, instead, on…

Renormalization group theory outperforms other approaches in statistical comparison between upscaling techniques for porous media

Science.gov (United States)

Hanasoge, Shravan; Agarwal, Umang; Tandon, Kunj; Koelman, J. M. Vianney A.

2017-09-01

Determining the pressure differential required to achieve a desired flow rate in a porous medium requires solving Darcy's law, a Laplace-like equation, with a spatially varying tensor permeability. In various scenarios, the permeability coefficient is sampled at high spatial resolution, which makes solving Darcy's equation numerically prohibitively expensive. As a consequence, much effort has gone into creating upscaled or low-resolution effective models of the coefficient while ensuring that the estimated flow rate is well reproduced, bringing to the fore the classic tradeoff between computational cost and numerical accuracy. Here we perform a statistical study to characterize the relative success of upscaling methods on a large sample of permeability coefficients that are above the percolation threshold. We introduce a technique based on mode-elimination renormalization group theory (MG) to build coarse-scale permeability coefficients. Comparing the results with coefficients upscaled using other methods, we find that MG is consistently more accurate, particularly due to its ability to address the tensorial nature of the coefficients. MG places a low computational demand, in the manner in which we have implemented it, and accurate flow-rate estimates are obtained when using MG-upscaled permeabilities that approach or are beyond the percolation threshold.

Calculational methods used to obtain evaluated data above 3 MeV

International Nuclear Information System (INIS)

Arthur, E.D.

1980-01-01

Calculational methods used to provide evaluated neutron data for nuclei between A = 19 and 220 at incident energies above several MeV range from empirical techniques based on cross-section systematics to sophisticated nuclear-model codes that describe the major mechanisms governing neutron reactions in this mass and energy range. Examples of empirical approaches are given along with discussion concerning regions of applicability and accuracies that can be expected. The application of more sophisticated nuclear models (Hauser-Feshbach statistical, preequilibrium, and direct-reaction theories) is discussed, particularly with regard to improved parameter determinations that can be used in such calculations. Efforts to improve the consistency and to unify these theoretical approaches are addressed along with benefits to evaluated data that can be realized through careful application of such nuclear-model techniques. 76 references, 13 figures, 3 tables

Topology for Statistical Modeling of Petascale Data

Energy Technology Data Exchange (ETDEWEB)

Pascucci, Valerio [Univ. of Utah, Salt Lake City, UT (United States); Levine, Joshua [Univ. of Utah, Salt Lake City, UT (United States); Gyulassy, Attila [Univ. of Utah, Salt Lake City, UT (United States); Bremer, P. -T. [Univ. of Utah, Salt Lake City, UT (United States)

2013-10-31

Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, the approach of the entire team involving all three institutions is based on the complementary techniques of combinatorial topology and statistical modelling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modelling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. The overall technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modelling, and (3) new integrated topological and statistical methods. Roughly speaking, the division of labor between our 3 groups (Sandia Labs in Livermore, Texas A&M in College Station, and U Utah in Salt Lake City) is as follows: the Sandia group focuses on statistical methods and their formulation in algebraic terms, and finds the application problems (and data sets) most relevant to this project, the Texas A&M Group develops new algebraic geometry algorithms, in particular with fewnomial theory, and the Utah group develops new algorithms in computational topology via Discrete Morse Theory. However, we hasten to point out that our three groups stay in tight contact via videconference every 2 weeks, so there is much synergy of ideas between the groups. The following of this document is focused on the contributions that had grater direct involvement from the team at the University of Utah in Salt Lake City.

Multivariate methods and forecasting with IBM SPSS statistics

CERN Document Server

Aljandali, Abdulkader

2017-01-01

This is the second of a two-part guide to quantitative analysis using the IBM SPSS Statistics software package; this volume focuses on multivariate statistical methods and advanced forecasting techniques. More often than not, regression models involve more than one independent variable. For example, forecasting methods are commonly applied to aggregates such as inflation rates, unemployment, exchange rates, etc., that have complex relationships with determining variables. This book introduces multivariate regression models and provides examples to help understand theory underpinning the model. The book presents the fundamentals of multivariate regression and then moves on to examine several related techniques that have application in business-orientated fields such as logistic and multinomial regression. Forecasting tools such as the Box-Jenkins approach to time series modeling are introduced, as well as exponential smoothing and naïve techniques. This part also covers hot topics such as Factor Analysis, Dis...

Workshop statistics discovery with data and Minitab

CERN Document Server

Rossman, Allan J

1998-01-01

Shorn of all subtlety and led naked out of the protec­ tive fold of educational research literature, there comes a sheepish little fact: lectures don't work nearly as well as many of us would like to think. -George Cobb (1992) This book contains activities that guide students to discover statistical concepts, explore statistical principles, and apply statistical techniques. Students work toward these goals through the analysis of genuine data and through inter­ action with one another, with their instructor, and with technology. Providing a one-semester introduction to fundamental ideas of statistics for college and advanced high school students, Warkshop Statistics is designed for courses that employ an interactive learning environment by replacing lectures with hands­ on activities. The text contains enough expository material to stand alone, but it can also be used to supplement a more traditional textbook. Some distinguishing features of Workshop Statistics are its emphases on active learning, conceptu...

Decomposition of the Inequality of Income Distribution by Income Types—Application for Romania

Science.gov (United States)

Andrei, Tudorel; Oancea, Bogdan; Richmond, Peter; Dhesi, Gurjeet; Herteliu, Claudiu

2017-09-01

This paper identifies the salient factors that characterize the inequality income distribution for Romania. Data analysis is rigorously carried out using sophisticated techniques borrowed from classical statistics (Theil). Decomposition of the inequalities measured by the Theil index is also performed. This study relies on an exhaustive (11.1 million records for 2014) data-set for total personal gross income of Romanian citizens.

Statistics and Corporate Environmental Management: Relations and Problems

DEFF Research Database (Denmark)

Madsen, Henning; Ulhøi, John Parm

1997-01-01

Statistical methods have long been used to analyse the macroeconomic consequences of environmentally damaging activities, political actions to control, prevent, or reduce these damages, and environmental problems in the natural environment. Up to now, however, they have had a limited and not very...... in the external environment. The nature and extent of the practical use of quantitative techniques in corporate environmental management systems is discussed on the basis of a number of company surveys in four European countries.......Statistical methods have long been used to analyse the macroeconomic consequences of environmentally damaging activities, political actions to control, prevent, or reduce these damages, and environmental problems in the natural environment. Up to now, however, they have had a limited and not very...... specific use in corporate environmental management systems. This paper will address some of the special problems related to the use of statistical techniques in corporate environmental management systems. One important aspect of this is the interaction of internal decisions and activities with conditions...

Estimation of global network statistics from incomplete data.

Directory of Open Access Journals (Sweden)

Catherine A Bliss

Full Text Available Complex networks underlie an enormous variety of social, biological, physical, and virtual systems. A profound complication for the science of complex networks is that in most cases, observing all nodes and all network interactions is impossible. Previous work addressing the impacts of partial network data is surprisingly limited, focuses primarily on missing nodes, and suggests that network statistics derived from subsampled data are not suitable estimators for the same network statistics describing the overall network topology. We generate scaling methods to predict true network statistics, including the degree distribution, from only partial knowledge of nodes, links, or weights. Our methods are transparent and do not assume a known generating process for the network, thus enabling prediction of network statistics for a wide variety of applications. We validate analytical results on four simulated network classes and empirical data sets of various sizes. We perform subsampling experiments by varying proportions of sampled data and demonstrate that our scaling methods can provide very good estimates of true network statistics while acknowledging limits. Lastly, we apply our techniques to a set of rich and evolving large-scale social networks, Twitter reply networks. Based on 100 million tweets, we use our scaling techniques to propose a statistical characterization of the Twitter Interactome from September 2008 to November 2008. Our treatment allows us to find support for Dunbar's hypothesis in detecting an upper threshold for the number of active social contacts that individuals maintain over the course of one week.

Ranking network of a captive rhesus macaque society: a sophisticated corporative kingdom.

Science.gov (United States)

Fushing, Hsieh; McAssey, Michael P; Beisner, Brianne; McCowan, Brenda

2011-03-15

We develop a three-step computing approach to explore a hierarchical ranking network for a society of captive rhesus macaques. The computed network is sufficiently informative to address the question: Is the ranking network for a rhesus macaque society more like a kingdom or a corporation? Our computations are based on a three-step approach. These steps are devised to deal with the tremendous challenges stemming from the transitivity of dominance as a necessary constraint on the ranking relations among all individual macaques, and the very high sampling heterogeneity in the behavioral conflict data. The first step simultaneously infers the ranking potentials among all network members, which requires accommodation of heterogeneous measurement error inherent in behavioral data. Our second step estimates the social rank for all individuals by minimizing the network-wide errors in the ranking potentials. The third step provides a way to compute confidence bounds for selected empirical features in the social ranking. We apply this approach to two sets of conflict data pertaining to two captive societies of adult rhesus macaques. The resultant ranking network for each society is found to be a sophisticated mixture of both a kingdom and a corporation. Also, for validation purposes, we reanalyze conflict data from twenty longhorn sheep and demonstrate that our three-step approach is capable of correctly computing a ranking network by eliminating all ranking error.

Ranking network of a captive rhesus macaque society: a sophisticated corporative kingdom.

Directory of Open Access Journals (Sweden)

Hsieh Fushing

2011-03-01

Full Text Available We develop a three-step computing approach to explore a hierarchical ranking network for a society of captive rhesus macaques. The computed network is sufficiently informative to address the question: Is the ranking network for a rhesus macaque society more like a kingdom or a corporation? Our computations are based on a three-step approach. These steps are devised to deal with the tremendous challenges stemming from the transitivity of dominance as a necessary constraint on the ranking relations among all individual macaques, and the very high sampling heterogeneity in the behavioral conflict data. The first step simultaneously infers the ranking potentials among all network members, which requires accommodation of heterogeneous measurement error inherent in behavioral data. Our second step estimates the social rank for all individuals by minimizing the network-wide errors in the ranking potentials. The third step provides a way to compute confidence bounds for selected empirical features in the social ranking. We apply this approach to two sets of conflict data pertaining to two captive societies of adult rhesus macaques. The resultant ranking network for each society is found to be a sophisticated mixture of both a kingdom and a corporation. Also, for validation purposes, we reanalyze conflict data from twenty longhorn sheep and demonstrate that our three-step approach is capable of correctly computing a ranking network by eliminating all ranking error.

TRAN-STAT: statistics for environmental studies

International Nuclear Information System (INIS)

Gilbert, R.O.

1984-09-01

This issue of TRAN-STAT discusses statistical methods for assessing the uncertainty in predictions of pollutant transport models, particularly for radionuclides. Emphasis is placed on radionuclide transport models but the statistical assessment techniques also apply in general to other types of pollutants. The report begins with an outline of why an assessment of prediction uncertainties is important. This is followed by an introduction to several methods currently used in these assessments. This in turn is followed by more detailed discussion of the methods, including examples. 43 references, 2 figures

Applying Statistical Process Quality Control Methodology to Educational Settings.

Science.gov (United States)

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…

Use of statistical procedures in Brazilian and international dental journals.

Science.gov (United States)

Ambrosano, Gláucia Maria Bovi; Reis, André Figueiredo; Giannini, Marcelo; Pereira, Antônio Carlos

2004-01-01

A descriptive survey was performed in order to assess the statistical content and quality of Brazilian and international dental journals, and compare their evolution throughout the last decades. The authors identified the reporting and accuracy of statistical techniques in 1000 papers published from 1970 to 2000 in seven dental journals: three Brazilian (Brazilian Dental Journal, Revista de Odontologia da Universidade de Sao Paulo and Revista de Odontologia da UNESP) and four international journals (Journal of the American Dental Association, Journal of Dental Research, Caries Research and Journal of Periodontology). Papers were divided into two time periods: from 1970 to 1989, and from 1990 to 2000. A slight increase in the number of articles that presented some form of statistical technique was noticed for Brazilian journals (from 61.0 to 66.7%), whereas for international journals, a significant increase was observed (65.8 to 92.6%). In addition, a decrease in the number of statistical errors was verified. The most commonly used statistical tests as well as the most frequent errors found in dental journals were assessed. Hopefully, this investigation will encourage dental educators to better plan the teaching of biostatistics, and to improve the statistical quality of submitted manuscripts.

Data Analysis Techniques for Physical Scientists

Science.gov (United States)

Pruneau, Claude A.

2017-10-01

Preface; How to read this book; 1. The scientific method; Part I. Foundation in Probability and Statistics: 2. Probability; 3. Probability models; 4. Classical inference I: estimators; 5. Classical inference II: optimization; 6. Classical inference III: confidence intervals and statistical tests; 7. Bayesian inference; Part II. Measurement Techniques: 8. Basic measurements; 9. Event reconstruction; 10. Correlation functions; 11. The multiple facets of correlation functions; 12. Data correction methods; Part III. Simulation Techniques: 13. Monte Carlo methods; 14. Collision and detector modeling; List of references; Index.

Statistical ultrasonics: the influence of Robert F. Wagner

Science.gov (United States)

Insana, Michael F.

2009-02-01

An important ongoing question for higher education is how to successfully mentor the next generation of scientists and engineers. It has been my privilege to have been mentored by one of the best, Dr Robert F. Wagner and his colleagues at the CDRH/FDA during the mid 1980s. Bob introduced many of us in medical ultrasonics to statistical imaging techniques. These ideas continue to broadly influence studies on adaptive aperture management (beamforming, speckle suppression, compounding), tissue characterization (texture features, Rayleigh/Rician statistics, scatterer size and number density estimators), and fundamental questions about how limitations of the human eye-brain system for extracting information from textured images can motivate image processing. He adapted the classical techniques of signal detection theory to coherent imaging systems that, for the first time in ultrasonics, related common engineering metrics for image quality to task-based clinical performance. This talk summarizes my wonderfully-exciting three years with Bob as I watched him explore topics in statistical image analysis that formed a rational basis for many of the signal processing techniques used in commercial systems today. It is a story of an exciting time in medical ultrasonics, and of how a sparkling personality guided and motivated the development of junior scientists who flocked around him in admiration and amazement.

Statistical methods with applications to demography and life insurance

CERN Document Server

Khmaladze, Estáte V

2013-01-01

Suitable for statisticians, mathematicians, actuaries, and students interested in the problems of insurance and analysis of lifetimes, Statistical Methods with Applications to Demography and Life Insurance presents contemporary statistical techniques for analyzing life distributions and life insurance problems. It not only contains traditional material but also incorporates new problems and techniques not discussed in existing actuarial literature. The book mainly focuses on the analysis of an individual life and describes statistical methods based on empirical and related processes. Coverage ranges from analyzing the tails of distributions of lifetimes to modeling population dynamics with migrations. To help readers understand the technical points, the text covers topics such as the Stieltjes, Wiener, and Itô integrals. It also introduces other themes of interest in demography, including mixtures of distributions, analysis of longevity and extreme value theory, and the age structure of a population. In addi...

Characterization of stress degradation products of benazepril by using sophisticated hyphenated techniques.

Science.gov (United States)

Narayanam, Mallikarjun; Sahu, Archana; Singh, Saranjit

2013-01-04

Benazepril, an anti-hypertensive drug, was subjected to forced degradation studies. The drug was unstable under hydrolytic conditions, yielding benazeprilat, which is a known major degradation product (DP) and an active metabolite. It also underwent photochemical degradation in acid and neutral pH conditions, resulting in multiple minor DPs. The products were separated on a reversed phase (C18) column in a gradient mode, and subjected to LC-MS and LC-NMR studies. Initially, comprehensive mass fragmentation pathway of the drug was established through support of high resolution mass spectrometric (HR-MS) and multi stage tandem mass spectrometric (MS(n)) data. The DPs were also subjected to LC-MS/TOF studies to obtain their accurate masses. Along with, on-line H/D exchange data were obtained to ascertain the number of exchangeable hydrogens in each molecule. LC-(1)H NMR and LC-2DNMR data were additionally acquired in a fraction loop mode. The whole information was successfully employed for the characterization of all the DPs. A complete degradation pathway of the drug was also established. Copyright © 2012 Elsevier B.V. All rights reserved.

7th International Workshop on Statistical Simulation

CERN Document Server

Mignani, Stefania; Monari, Paola; Salmaso, Luigi

2014-01-01

The Department of Statistical Sciences of the University of Bologna in collaboration with the Department of Management and Engineering of the University of Padova, the Department of Statistical Modelling of Saint Petersburg State University, and INFORMS Simulation Society sponsored the Seventh Workshop on Simulation. This international conference was devoted to statistical techniques in stochastic simulation, data collection, analysis of scientific experiments, and studies representing broad areas of interest. The previous workshops took place in St. Petersburg, Russia in 1994, 1996, 1998, 2001, 2005, and 2009. The Seventh Workshop took place in the Rimini Campus of the University of Bologna, which is in Rimini’s historical center.

The Novel Quantitative Technique for Assessment of Gait Symmetry Using Advanced Statistical Learning Algorithm

OpenAIRE

Wu, Jianning; Wu, Bin

2015-01-01

The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of...

Fuzzy statistical decision-making theory and applications

CERN Document Server

Kabak, Özgür

2016-01-01

This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete information or insufficient data, where classical statistics cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including: fuzzy probability distributions, fuzzy frequency distributions, fuzzy Bayesian inference, fuzzy mean, mode and median, fuzzy dispersion, fuzzy p-value, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on fuzzy statistics. Moreover, by extending all the main aspects of classical statistical decision-making to its fuzzy counterpart, the book presents a dynamic snapshot of the field that is expected to stimu...

Statistical analysis of aging trend of mechanical properties in ethylene propylene rubber-insulated safety-related cables sampled from containments (Denryoko Chuo Kenkyusho Hokoku, December 2013 issue)

International Nuclear Information System (INIS)

Fuse, Norikazu; Kanegami, Masaki; Misaka, Hideki; Homma, Hiroya; Okamoto, Tatsuki

2013-01-01

As for polymeric insulations used in nuclear power plant safety cables, it is known that the present prediction model sometimes estimates the service life conservatively. In order to sophisticate the model to reflect to the aging in containments, disconnections between the prediction and realities are needed to be clarified. In the present paper, statistical analysis has been carried out on various aging status of insulations removed from domestic containments. Aging in operational environment is found to be slower than the one expected from acceleration aging test results. Temperature dependence of estimated lifetime on Arrhenius plot also suggests that elementary chemical reaction dominant under the two aging conditions is different, which results in apparent difference in activation energies and pre-exponential factors. Following two kinds of issues are found necessary to be clarified for the model sophistication; temperature change in predominant degradation chemical processes, and the effect of low oxygen concentration environment in boiling water reactor type containment. (author)

Using Statistical Process Control to Make Data-Based Clinical Decisions.

Science.gov (United States)

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…

Wind speed prediction using statistical regression and neural network

Indian Academy of Sciences (India)

Prediction of wind speed in the atmospheric boundary layer is important for wind energy assess- ment,satellite launching and aviation,etc.There are a few techniques available for wind speed prediction,which require a minimum number of input parameters.Four different statistical techniques,viz.,curve fitting,Auto Regressive ...

Spatial, spectral and statistical properties of the electrostatic fluctuations and measurements of the scattering of the beam in a strongly turbulent plasma

Science.gov (United States)

McFarland, Michael Duane

The purpose of this investigation is to measure the spatial, spectral and statistical properties of the high (/omega/ ~/ ω pe) and low (/omega/ ~/ ωpi) frequency electrostatic fluctuations in an unmagnetized, statistically stable, beam-driven, strongly turbulent plasma and compare the results to theoretical predictions. In addition the scattering of the electron beam in both angle and energy is measured and compared to theory. This study is motivated by the recent advances in statistical theories of strong Langmuir turbulence and the glaring lack of confirmatory experimental data. With the advent of modern computers and electronics, enormous data sets are now routinely digitize and subjected to sophisticated statistical and spectral analysis. These methods, along with traditional procedures and an innovative technique known as a 'conditional trigger', are used to extract ensemble averages from the turbulent system for comparison with the theoretical models. It is found that the high-frequency fluctuations consist of low-level wave activity /langle W/rangle/ ~/ 10-2 - 103 punctuated by semi-periodic, intense, spiky field events /langle W/rangle/ ~/ 1, where /langle W/rangle is the normalized intensity. The low- level wave activity has a spectral spread Δ k/k/ ~/ /Delta/omega//omega/ ~ 30%, dispersion relation v beam/ ~/ /omega/k, and correlation length lc/ /approx/ 3λES, where λES is the electrostatic wavelength, and shows evidence of low-intensity parametric decay products. The intense field events, on the other hand, show little correlation for l/ >/ λES, have a full-width-at-half-maximum of 1 f/ /n2/ /propto/ β where β ~/ 1.3 for the experiment and is predicted to be β ~/ 1.98 by the model. The scattering of the electron beam in angle for a typical wave intensity level /langle W/rangle/ ~/ 0.04 is Θ ~/ 3o, and in energy is Δ U/ ~/ 25 eV for a 400 eV beam. The scattering of the beam in both angle and energy is found to agree well with theory.

Sensitivity analysis and optimization of system dynamics models : Regression analysis and statistical design of experiments

NARCIS (Netherlands)

Kleijnen, J.P.C.

1995-01-01

This tutorial discusses what-if analysis and optimization of System Dynamics models. These problems are solved, using the statistical techniques of regression analysis and design of experiments (DOE). These issues are illustrated by applying the statistical techniques to a System Dynamics model for

Territories typification technique with use of statistical models

Science.gov (United States)

Galkin, V. I.; Rastegaev, A. V.; Seredin, V. V.; Andrianov, A. V.

2018-05-01

Territories typification is required for solution of many problems. The results of geological zoning received by means of various methods do not always agree. That is why the main goal of the research given is to develop a technique of obtaining a multidimensional standard classified indicator for geological zoning. In the course of the research, the probabilistic approach was used. In order to increase the reliability of geological information classification, the authors suggest using complex multidimensional probabilistic indicator P K as a criterion of the classification. The second criterion chosen is multidimensional standard classified indicator Z. These can serve as characteristics of classification in geological-engineering zoning. Above mentioned indicators P K and Z are in good correlation. Correlation coefficient values for the entire territory regardless of structural solidity equal r = 0.95 so each indicator can be used in geological-engineering zoning. The method suggested has been tested and the schematic map of zoning has been drawn.

A Comparison of Selected Statistical Techniques to Model Soil Cation Exchange Capacity

Science.gov (United States)

Khaledian, Yones; Brevik, Eric C.; Pereira, Paulo; Cerdà, Artemi; Fattah, Mohammed A.; Tazikeh, Hossein

2017-04-01

Cation exchange capacity (CEC) measures the soil's ability to hold positively charged ions and is an important indicator of soil quality (Khaledian et al., 2016). However, other soil properties are more commonly determined and reported, such as texture, pH, organic matter and biology. We attempted to predict CEC using different advanced statistical methods including monotone analysis of variance (MONANOVA), artificial neural networks (ANNs), principal components regressions (PCR), and particle swarm optimization (PSO) in order to compare the utility of these approaches and identify the best predictor. We analyzed 170 soil samples from four different nations (USA, Spain, Iran and Iraq) under three land uses (agriculture, pasture, and forest). Seventy percent of the samples (120 samples) were selected as the calibration set and the remaining 50 samples (30%) were used as the prediction set. The results indicated that the MONANOVA (R2= 0.82 and Root Mean Squared Error (RMSE) =6.32) and ANNs (R2= 0.82 and RMSE=5.53) were the best models to estimate CEC, PSO (R2= 0.80 and RMSE=5.54) and PCR (R2= 0.70 and RMSE=6.48) also worked well and the overall results were very similar to each other. Clay (positively correlated) and sand (negatively correlated) were the most influential variables for predicting CEC for the entire data set, while the most influential variables for the various countries and land uses were different and CEC was affected by different variables in different situations. Although the MANOVA and ANNs provided good predictions of the entire dataset, PSO gives a formula to estimate soil CEC using commonly tested soil properties. Therefore, PSO shows promise as a technique to estimate soil CEC. Establishing effective pedotransfer functions to predict CEC would be productive where there are limitations of time and money, and other commonly analyzed soil properties are available. References Khaledian, Y., Kiani, F., Ebrahimi, S., Brevik, E.C., Aitkenhead

Audit sampling: A qualitative study on the role of statistical and non-statistical sampling approaches on audit practices in Sweden

OpenAIRE

Ayam, Rufus Tekoh

2011-01-01

PURPOSE: The two approaches to audit sampling; statistical and nonstatistical have been examined in this study. The overall purpose of the study is to explore the current extent at which statistical and nonstatistical sampling approaches are utilized by independent auditors during auditing practices. Moreover, the study also seeks to achieve two additional purposes; the first is to find out whether auditors utilize different sampling techniques when auditing SME´s (Small and Medium-Sized Ente...

Advances in statistical multisource-multitarget information fusion

CERN Document Server

Mahler, Ronald PS

2014-01-01

This is the sequel to the 2007 Artech House bestselling title, Statistical Multisource-Multitarget Information Fusion. That earlier book was a comprehensive resource for an in-depth understanding of finite-set statistics (FISST), a unified, systematic, and Bayesian approach to information fusion. The cardinalized probability hypothesis density (CPHD) filter, which was first systematically described in the earlier book, has since become a standard multitarget detection and tracking technique, especially in research and development.Since 2007, FISST has inspired a considerable amount of research

Statistical analysis of RHIC beam position monitors performance

Science.gov (United States)

Calaga, R.; Tomás, R.

2004-04-01

A detailed statistical analysis of beam position monitors (BPM) performance at RHIC is a critical factor in improving regular operations and future runs. Robust identification of malfunctioning BPMs plays an important role in any orbit or turn-by-turn analysis. Singular value decomposition and Fourier transform methods, which have evolved as powerful numerical techniques in signal processing, will aid in such identification from BPM data. This is the first attempt at RHIC to use a large set of data to statistically enhance the capability of these two techniques and determine BPM performance. A comparison from run 2003 data shows striking agreement between the two methods and hence can be used to improve BPM functioning at RHIC and possibly other accelerators.

Statistical analysis of RHIC beam position monitors performance

Directory of Open Access Journals (Sweden)

R. Calaga

2004-04-01

Full Text Available A detailed statistical analysis of beam position monitors (BPM performance at RHIC is a critical factor in improving regular operations and future runs. Robust identification of malfunctioning BPMs plays an important role in any orbit or turn-by-turn analysis. Singular value decomposition and Fourier transform methods, which have evolved as powerful numerical techniques in signal processing, will aid in such identification from BPM data. This is the first attempt at RHIC to use a large set of data to statistically enhance the capability of these two techniques and determine BPM performance. A comparison from run 2003 data shows striking agreement between the two methods and hence can be used to improve BPM functioning at RHIC and possibly other accelerators.

9th Symposium on Computational Statistics

CERN Document Server

Mildner, Vesna

1990-01-01

Although no-one is, probably, too enthused about the idea, it is a fact that the development of most empirical sciences to a great extent depends on the development of data analysis methods and techniques, which, due to the necessity of application of computers for that purpose, actually means that it practically depends on the advancement and orientation of computer statistics. Every other year the International Association for Statistical Computing sponsors the organizition of meetings of individual s professiona77y involved in computational statistics. Since these meetings attract professionals from allover the world, they are a good sample for the estimation of trends in this area which some believe is a statistics proper while others claim it is computer science. It seems, though, that an increasing number of colleagues treat it as an independent scientific or at least technical discipline. This volume contains six invited papers, 41 contributed papers and, finally, two papers which are, formally, softwa...

MODEL APPLICATION MULTIVARIATE ANALYSIS OF STATISTICAL TECHNIQUES PCA AND HCA ASSESSMENT QUESTIONNAIRE ON CUSTOMER SATISFACTION: CASE STUDY IN A METALLURGICAL COMPANY OF METAL CONTAINERS

Directory of Open Access Journals (Sweden)

Cláudio Roberto Rosário

2012-07-01

Full Text Available The purpose of this research is to improve the practice on customer satisfaction analysis The article presents an analysis model to analyze the answers of a customer satisfaction evaluation in a systematic way with the aid of multivariate statistical techniques, specifically, exploratory analysis with PCA – Partial Components Analysis with HCA - Hierarchical Cluster Analysis. It was tried to evaluate the applicability of the model to be used by the issue company as a tool to assist itself on identifying the value chain perceived by the customer when applied the questionnaire of customer satisfaction. It was found with the assistance of multivariate statistical analysis that it was observed similar behavior among customers. It also allowed the company to conduct reviews on questions of the questionnaires, using analysis of the degree of correlation between the questions that was not a company’s practice before this research.

The Role of the Sampling Distribution in Understanding Statistical Inference

Science.gov (United States)

Lipson, Kay

2003-01-01

Many statistics educators believe that few students develop the level of conceptual understanding essential for them to apply correctly the statistical techniques at their disposal and to interpret their outcomes appropriately. It is also commonly believed that the sampling distribution plays an important role in developing this understanding.…

Comparative Analysis Between Computed and Conventional Inferior Alveolar Nerve Block Techniques.

Science.gov (United States)

Araújo, Gabriela Madeira; Barbalho, Jimmy Charles Melo; Dias, Tasiana Guedes de Souza; Santos, Thiago de Santana; Vasconcellos, Ricardo José de Holanda; de Morais, Hécio Henrique Araújo

2015-11-01

The aim of this randomized, double-blind, controlled trial was to compare the computed and conventional inferior alveolar nerve block techniques in symmetrically positioned inferior third molars. Both computed and conventional anesthetic techniques were performed in 29 healthy patients (58 surgeries) aged between 18 and 40 years. The anesthetic of choice was 2% lidocaine with 1: 200,000 epinephrine. The Visual Analogue Scale assessed the pain variable after anesthetic infiltration. Patient satisfaction was evaluated using the Likert Scale. Heart and respiratory rates, mean time to perform technique, and the need for additional anesthesia were also evaluated. Pain variable means were higher for the conventional technique as compared with computed, 3.45 ± 2.73 and 2.86 ± 1.96, respectively, but no statistically significant differences were found (P > 0.05). Patient satisfaction showed no statistically significant differences. The average computed technique runtime and the conventional were 3.85 and 1.61 minutes, respectively, showing statistically significant differences (P <0.001). The computed anesthetic technique showed lower mean pain perception, but did not show statistically significant differences when contrasted to the conventional technique.

Statistics in the Workplace: A Survey of Use by Recent Graduates with Higher Degrees

Science.gov (United States)

Harraway, John A.; Barker, Richard J.

2005-01-01

A postal survey was conducted regarding statistical techniques, research methods and software used in the workplace by 913 graduates with PhD and Masters degrees in the biological sciences, psychology, business, economics, and statistics. The study identified gaps between topics and techniques learned at university and those used in the workplace,…

Incorporating Nonparametric Statistics into Delphi Studies in Library and Information Science

Science.gov (United States)

Ju, Boryung; Jin, Tao

2013-01-01

Introduction: The Delphi technique is widely used in library and information science research. However, many researchers in the field fail to employ standard statistical tests when using this technique. This makes the technique vulnerable to criticisms of its reliability and validity. The general goal of this article is to explore how…

Statistical error estimation of the Feynman-α method using the bootstrap method

International Nuclear Information System (INIS)

Endo, Tomohiro; Yamamoto, Akio; Yagi, Takahiro; Pyeon, Cheol Ho

2016-01-01

Applicability of the bootstrap method is investigated to estimate the statistical error of the Feynman-α method, which is one of the subcritical measurement techniques on the basis of reactor noise analysis. In the Feynman-α method, the statistical error can be simply estimated from multiple measurements of reactor noise, however it requires additional measurement time to repeat the multiple times of measurements. Using a resampling technique called 'bootstrap method' standard deviation and confidence interval of measurement results obtained by the Feynman-α method can be estimated as the statistical error, using only a single measurement of reactor noise. In order to validate our proposed technique, we carried out a passive measurement of reactor noise without any external source, i.e. with only inherent neutron source by spontaneous fission and (α,n) reactions in nuclear fuels at the Kyoto University Criticality Assembly. Through the actual measurement, it is confirmed that the bootstrap method is applicable to approximately estimate the statistical error of measurement results obtained by the Feynman-α method. (author)

Using statistics to understand the environment

CERN Document Server

Cook, Penny A

2000-01-01

Using Statistics to Understand the Environment covers all the basic tests required for environmental practicals and projects and points the way to the more advanced techniques that may be needed in more complex research designs. Following an introduction to project design, the book covers methods to describe data, to examine differences between samples, and to identify relationships and associations between variables.Featuring: worked examples covering a wide range of environmental topics, drawings and icons, chapter summaries, a glossary of statistical terms and a further reading section, this book focuses on the needs of the researcher rather than on the mathematics behind the tests.

Statistical-mechanical formulation of Lyapunov exponents

International Nuclear Information System (INIS)

Tanase-Nicola, Sorin; Kurchan, Jorge

2003-01-01

We show how the Lyapunov exponents of a dynamic system can, in general, be expressed in terms of the free energy of a (non-Hermitian) quantum many-body problem. This puts their study as a problem of statistical mechanics, whose intuitive concepts and techniques of approximation can hence be borrowed

Statistical shape analysis with applications in R

CERN Document Server

Dryden, Ian L

2016-01-01

A thoroughly revised and updated edition of this introduction to modern statistical methods for shape analysis Shape analysis is an important tool in the many disciplines where objects are compared using geometrical features. Examples include comparing brain shape in schizophrenia; investigating protein molecules in bioinformatics; and describing growth of organisms in biology. This book is a significant update of the highly-regarded `Statistical Shape Analysis’ by the same authors. The new edition lays the foundations of landmark shape analysis, including geometrical concepts and statistical techniques, and extends to include analysis of curves, surfaces, images and other types of object data. Key definitions and concepts are discussed throughout, and the relative merits of different approaches are presented. The authors have included substantial new material on recent statistical developments and offer numerous examples throughout the text. Concepts are introduced in an accessible manner, while reta...

Spatial analysis statistics, visualization, and computational methods

CERN Document Server

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...

On-the-fly confluence detection for statistical model checking (extended version)

NARCIS (Netherlands)

Hartmanns, Arnd; Timmer, Mark

Statistical model checking is an analysis method that circumvents the state space explosion problem in model-based verification by combining probabilistic simulation with statistical methods that provide clear error bounds. As a simulation-based technique, it can only provide sound results if the

Statistical atmospheric inversion of local gas emissions by coupling the tracer release technique and local-scale transport modelling: a test case with controlled methane emissions

Directory of Open Access Journals (Sweden)

S. Ars

2017-12-01

Full Text Available This study presents a new concept for estimating the pollutant emission rates of a site and its main facilities using a series of atmospheric measurements across the pollutant plumes. This concept combines the tracer release method, local-scale atmospheric transport modelling and a statistical atmospheric inversion approach. The conversion between the controlled emission and the measured atmospheric concentrations of the released tracer across the plume places valuable constraints on the atmospheric transport. This is used to optimise the configuration of the transport model parameters and the model uncertainty statistics in the inversion system. The emission rates of all sources are then inverted to optimise the match between the concentrations simulated with the transport model and the pollutants' measured atmospheric concentrations, accounting for the transport model uncertainty. In principle, by using atmospheric transport modelling, this concept does not strongly rely on the good colocation between the tracer and pollutant sources and can be used to monitor multiple sources within a single site, unlike the classical tracer release technique. The statistical inversion framework and the use of the tracer data for the configuration of the transport and inversion modelling systems should ensure that the transport modelling errors are correctly handled in the source estimation. The potential of this new concept is evaluated with a relatively simple practical implementation based on a Gaussian plume model and a series of inversions of controlled methane point sources using acetylene as a tracer gas. The experimental conditions are chosen so that they are suitable for the use of a Gaussian plume model to simulate the atmospheric transport. In these experiments, different configurations of methane and acetylene point source locations are tested to assess the efficiency of the method in comparison to the classic tracer release technique in coping

Statistical atmospheric inversion of local gas emissions by coupling the tracer release technique and local-scale transport modelling: a test case with controlled methane emissions

Science.gov (United States)

Ars, Sébastien; Broquet, Grégoire; Yver Kwok, Camille; Roustan, Yelva; Wu, Lin; Arzoumanian, Emmanuel; Bousquet, Philippe

2017-12-01

This study presents a new concept for estimating the pollutant emission rates of a site and its main facilities using a series of atmospheric measurements across the pollutant plumes. This concept combines the tracer release method, local-scale atmospheric transport modelling and a statistical atmospheric inversion approach. The conversion between the controlled emission and the measured atmospheric concentrations of the released tracer across the plume places valuable constraints on the atmospheric transport. This is used to optimise the configuration of the transport model parameters and the model uncertainty statistics in the inversion system. The emission rates of all sources are then inverted to optimise the match between the concentrations simulated with the transport model and the pollutants' measured atmospheric concentrations, accounting for the transport model uncertainty. In principle, by using atmospheric transport modelling, this concept does not strongly rely on the good colocation between the tracer and pollutant sources and can be used to monitor multiple sources within a single site, unlike the classical tracer release technique. The statistical inversion framework and the use of the tracer data for the configuration of the transport and inversion modelling systems should ensure that the transport modelling errors are correctly handled in the source estimation. The potential of this new concept is evaluated with a relatively simple practical implementation based on a Gaussian plume model and a series of inversions of controlled methane point sources using acetylene as a tracer gas. The experimental conditions are chosen so that they are suitable for the use of a Gaussian plume model to simulate the atmospheric transport. In these experiments, different configurations of methane and acetylene point source locations are tested to assess the efficiency of the method in comparison to the classic tracer release technique in coping with the distances

Explorations in statistics: the log transformation.

Science.gov (United States)

Curran-Everett, Douglas

2018-06-01

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This thirteenth installment of Explorations in Statistics explores the log transformation, an established technique that rescales the actual observations from an experiment so that the assumptions of some statistical analysis are better met. A general assumption in statistics is that the variability of some response Y is homogeneous across groups or across some predictor variable X. If the variability-the standard deviation-varies in rough proportion to the mean value of Y, a log transformation can equalize the standard deviations. Moreover, if the actual observations from an experiment conform to a skewed distribution, then a log transformation can make the theoretical distribution of the sample mean more consistent with a normal distribution. This is important: the results of a one-sample t test are meaningful only if the theoretical distribution of the sample mean is roughly normal. If we log-transform our observations, then we want to confirm the transformation was useful. We can do this if we use the Box-Cox method, if we bootstrap the sample mean and the statistic t itself, and if we assess the residual plots from the statistical model of the actual and transformed sample observations.

Water quality assessment and apportionment of pollution sources of Gomti river (India) using multivariate statistical techniques--a case study

International Nuclear Information System (INIS)

Singh, Kunwar P.; Malik, Amrita; Sinha, Sarita

2005-01-01

Multivariate statistical techniques, such as cluster analysis (CA), factor analysis (FA), principal component analysis (PCA) and discriminant analysis (DA) were applied to the data set on water quality of the Gomti river (India), generated during three years (1999-2001) monitoring at eight different sites for 34 parameters (9792 observations). This study presents usefulness of multivariate statistical techniques for evaluation and interpretation of large complex water quality data sets and apportionment of pollution sources/factors with a view to get better information about the water quality and design of monitoring network for effective management of water resources. Three significant groups, upper catchments (UC), middle catchments (MC) and lower catchments (LC) of sampling sites were obtained through CA on the basis of similarity between them. FA/PCA applied to the data sets pertaining to three catchments regions of the river resulted in seven, seven and six latent factors, respectively responsible for the data structure, explaining 74.3, 73.6 and 81.4% of the total variance of the respective data sets. These included the trace metals group (leaching from soil and industrial waste disposal sites), organic pollution group (municipal and industrial effluents), nutrients group (agricultural runoff), alkalinity, hardness, EC and solids (soil leaching and runoff process). DA showed the best results for data reduction and pattern recognition during both temporal and spatial analysis. It rendered five parameters (temperature, total alkalinity, Cl, Na and K) affording more than 94% right assignations in temporal analysis, while 10 parameters (river discharge, pH, BOD, Cl, F, PO 4 , NH 4 -N, NO 3 -N, TKN and Zn) to afford 97% right assignations in spatial analysis of three different regions in the basin. Thus, DA allowed reduction in dimensionality of the large data set, delineating a few indicator parameters responsible for large variations in water quality. Further

Statistical mechanics of sensing and communications: Insights and techniques

International Nuclear Information System (INIS)

Murayama, T; Davis, P

2008-01-01

In this article we review a basic model for analysis of large sensor networks from the point of view of collective estimation under bandwidth constraints. We compare different sensing aggregation levels as alternative 'strategies' for collective estimation: moderate aggregation from a moderate number of sensors for which communication bandwidth is enough that data encoding can be reversible, and large scale aggregation from very many sensors - in which case communication bandwidth constraints require the use of nonreversible encoding. We show the non-trivial trade-off between sensing quality, which can be increased by increasing the number of sensors, and communication quality under bandwidth constraints, which decreases if the number of sensors is too large. From a practical standpoint, we verify that such a trade-off exists in constructively defined communications schemes. We introduce a probabilistic encoding scheme and define rate distortion models that are suitable for analysis of the large network limit. Our description shows that the methods and ideas from statistical physics can play an important role in formulating effective models for such schemes

Statistical classification techniques in high energy physics (SDDT algorithm)

International Nuclear Information System (INIS)

Bouř, Petr; Kůs, Václav; Franc, Jiří

2016-01-01

We present our proposal of the supervised binary divergence decision tree with nested separation method based on the generalized linear models. A key insight we provide is the clustering driven only by a few selected physical variables. The proper selection consists of the variables achieving the maximal divergence measure between two different classes. Further, we apply our method to Monte Carlo simulations of physics processes corresponding to a data sample of top quark-antiquark pair candidate events in the lepton+jets decay channel. The data sample is produced in pp̅ collisions at √S = 1.96 TeV. It corresponds to an integrated luminosity of 9.7 fb"-"1 recorded with the D0 detector during Run II of the Fermilab Tevatron Collider. The efficiency of our algorithm achieves 90% AUC in separating signal from background. We also briefly deal with the modification of statistical tests applicable to weighted data sets in order to test homogeneity of the Monte Carlo simulations and measured data. The justification of these modified tests is proposed through the divergence tests. (paper)

New Statistical Methodology for Determining Cancer Clusters

Science.gov (United States)

The development of an innovative statistical technique that shows that women living in a broad stretch of the metropolitan northeastern United States, which includes Long Island, are slightly more likely to die from breast cancer than women in other parts of the Northeast.

Statistics and Informatics in Space Astrophysics

Science.gov (United States)

Feigelson, E.

2017-12-01

The interest in statistical and computational methodology has seen rapid growth in space-based astrophysics, parallel to the growth seen in Earth remote sensing. There is widespread agreement that scientific interpretation of the cosmic microwave background, discovery of exoplanets, and classifying multiwavelength surveys is too complex to be accomplished with traditional techniques. NASA operates several well-functioning Science Archive Research Centers providing 0.5 PBy datasets to the research community. These databases are integrated with full-text journal articles in the NASA Astrophysics Data System (200K pageviews/day). Data products use interoperable formats and protocols established by the International Virtual Observatory Alliance. NASA supercomputers also support complex astrophysical models of systems such as accretion disks and planet formation. Academic researcher interest in methodology has significantly grown in areas such as Bayesian inference and machine learning, and statistical research is underway to treat problems such as irregularly spaced time series and astrophysical model uncertainties. Several scholarly societies have created interest groups in astrostatistics and astroinformatics. Improvements are needed on several fronts. Community education in advanced methodology is not sufficiently rapid to meet the research needs. Statistical procedures within NASA science analysis software are sometimes not optimal, and pipeline development may not use modern software engineering techniques. NASA offers few grant opportunities supporting research in astroinformatics and astrostatistics.

Adaptive Statistical Iterative Reconstruction-V Versus Adaptive Statistical Iterative Reconstruction: Impact on Dose Reduction and Image Quality in Body Computed Tomography.

Science.gov (United States)

Gatti, Marco; Marchisio, Filippo; Fronda, Marco; Rampado, Osvaldo; Faletti, Riccardo; Bergamasco, Laura; Ropolo, Roberto; Fonio, Paolo

The aim of this study was to evaluate the impact on dose reduction and image quality of the new iterative reconstruction technique: adaptive statistical iterative reconstruction (ASIR-V). Fifty consecutive oncologic patients acted as case controls undergoing during their follow-up a computed tomography scan both with ASIR and ASIR-V. Each study was analyzed in a double-blinded fashion by 2 radiologists. Both quantitative and qualitative analyses of image quality were conducted. Computed tomography scanner radiation output was 38% (29%-45%) lower (P ASIR-V examinations than for the ASIR ones. The quantitative image noise was significantly lower (P ASIR-V. Adaptive statistical iterative reconstruction-V had a higher performance for the subjective image noise (P = 0.01 for 5 mm and P = 0.009 for 1.25 mm), the other parameters (image sharpness, diagnostic acceptability, and overall image quality) being similar (P > 0.05). Adaptive statistical iterative reconstruction-V is a new iterative reconstruction technique that has the potential to provide image quality equal to or greater than ASIR, with a dose reduction around 40%.

Statistical Estimators Using Jointly Administrative and Survey Data to Produce French Structural Business Statistics

Directory of Open Access Journals (Sweden)

Brion Philippe

2015-12-01

Full Text Available Using as much administrative data as possible is a general trend among most national statistical institutes. Different kinds of administrative sources, from tax authorities or other administrative bodies, are very helpful material in the production of business statistics. However, these sources often have to be completed by information collected through statistical surveys. This article describes the way Insee has implemented such a strategy in order to produce French structural business statistics. The originality of the French procedure is that administrative and survey variables are used jointly for the same enterprises, unlike the majority of multisource systems, in which the two kinds of sources generally complement each other for different categories of units. The idea is to use, as much as possible, the richness of the administrative sources combined with the timeliness of a survey, even if the latter is conducted only on a sample of enterprises. One main issue is the classification of enterprises within the NACE nomenclature, which is a cornerstone variable in producing the breakdown of the results by industry. At a given date, two values of the corresponding code may coexist: the value of the register, not necessarily up to date, and the value resulting from the data collected via the survey, but only from a sample of enterprises. Using all this information together requires the implementation of specific statistical estimators combining some properties of the difference estimators with calibration techniques. This article presents these estimators, as well as their statistical properties, and compares them with those of other methods.

The Impact of Services on Economic Complexity: Service Sophistication as Route for Economic Growth.

Science.gov (United States)

Stojkoski, Viktor; Utkovski, Zoran; Kocarev, Ljupco

2016-01-01

Economic complexity reflects the amount of knowledge that is embedded in the productive structure of an economy. By combining tools from network science and econometrics, a robust and stable relationship between a country's productive structure and its economic growth has been established. Here we report that not only goods but also services are important for predicting the rate at which countries will grow. By adopting a terminology which classifies manufactured goods and delivered services as products, we investigate the influence of services on the country's productive structure. In particular, we provide evidence that complexity indices for services are in general higher than those for goods, which is reflected in a general tendency to rank countries with developed service sector higher than countries with economy centred on manufacturing of goods. By focusing on country dynamics based on experimental data, we investigate the impact of services on the economic complexity of countries measured in the product space (consisting of both goods and services). Importantly, we show that diversification of service exports and its sophistication can provide an additional route for economic growth in both developing and developed countries.

Statistical modelling for social researchers principles and practice

CERN Document Server

Tarling, Roger

2008-01-01

This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist looking to apply statistical modelling techniques in research. The book also serves as an introduction for those wishing to develop more detailed knowledge and skills in statistical modelling. Rather than present a limited number of statistical models in great depth, the aim is to provide a comprehensive overview of the statistical models currently adopted in social research, in order that the researcher can make appropriate choices and select the most suitable model for the research question to be addressed. To facilitate application, the book also offers practical guidance and instruction in fitting models using SPSS and Stata, the most popular statistical computer software which is available to most social researchers. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic regression, log-l...

On Quantum Statistical Inference, II

OpenAIRE

Barndorff-Nielsen, O. E.; Gill, R. D.; Jupp, P. E.

2003-01-01

Interest in problems of statistical inference connected to measurements of quantum systems has recently increased substantially, in step with dramatic new developments in experimental techniques for studying small quantum systems. Furthermore, theoretical developments in the theory of quantum measurements have brought the basic mathematical framework for the probability calculations much closer to that of classical probability theory. The present paper reviews this field and proposes and inte...

Descriptive and inferential statistical methods used in burns research.

Science.gov (United States)

Al-Benna, Sammy; Al-Ajam, Yazan; Way, Benjamin; Steinstraesser, Lars

2010-05-01

Burns research articles utilise a variety of descriptive and inferential methods to present and analyse data. The aim of this study was to determine the descriptive methods (e.g. mean, median, SD, range, etc.) and survey the use of inferential methods (statistical tests) used in articles in the journal Burns. This study defined its population as all original articles published in the journal Burns in 2007. Letters to the editor, brief reports, reviews, and case reports were excluded. Study characteristics, use of descriptive statistics and the number and types of statistical methods employed were evaluated. Of the 51 articles analysed, 11(22%) were randomised controlled trials, 18(35%) were cohort studies, 11(22%) were case control studies and 11(22%) were case series. The study design and objectives were defined in all articles. All articles made use of continuous and descriptive data. Inferential statistics were used in 49(96%) articles. Data dispersion was calculated by standard deviation in 30(59%). Standard error of the mean was quoted in 19(37%). The statistical software product was named in 33(65%). Of the 49 articles that used inferential statistics, the tests were named in 47(96%). The 6 most common tests used (Student's t-test (53%), analysis of variance/co-variance (33%), chi(2) test (27%), Wilcoxon & Mann-Whitney tests (22%), Fisher's exact test (12%)) accounted for the majority (72%) of statistical methods employed. A specified significance level was named in 43(88%) and the exact significance levels were reported in 28(57%). Descriptive analysis and basic statistical techniques account for most of the statistical tests reported. This information should prove useful in deciding which tests should be emphasised in educating burn care professionals. These results highlight the need for burn care professionals to have a sound understanding of basic statistics, which is crucial in interpreting and reporting data. Advice should be sought from professionals

Spatial Analysis Along Networks Statistical and Computational Methods

CERN Document Server

Okabe, Atsuyuki

2012-01-01

In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Process

Advances in statistical monitoring of complex multivariate processes with applications in industrial process control

CERN Document Server

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

Can Low Frequency Measurements Be Good Enough? - A Statistical Assessment of Citizen Hydrology Streamflow Observations

Science.gov (United States)

Davids, J. C.; Rutten, M.; Van De Giesen, N.

2016-12-01

Hydrologic data has traditionally been collected with permanent installations of sophisticated and relatively accurate but expensive monitoring equipment at limited numbers of sites. Consequently, the spatial coverage of the data is limited and costs are high. Achieving adequate maintenance of sophisticated monitoring equipment often exceeds local technical and resource capacity, and permanently deployed monitoring equipment is susceptible to vandalism, theft, and other hazards. Rather than using expensive, vulnerable installations at a few points, SmartPhones4Water (S4W), a form of Citizen Hydrology, leverages widely available mobile technology to gather hydrologic data at many sites in a manner that is repeatable and scalable. However, there is currently a limited understanding of the impact of decreased observational frequency on the accuracy of key streamflow statistics like minimum flow, maximum flow, and runoff. As a first step towards evaluating the tradeoffs between traditional continuous monitoring approaches and emerging Citizen Hydrology methods, we randomly selected 50 active U.S. Geological Survey (USGS) streamflow gauges in California. We used historical 15 minute flow data from 01/01/2008 through 12/31/2014 to develop minimum flow, maximum flow, and runoff values (7 year total) for each gauge. In order to mimic lower frequency Citizen Hydrology observations, we developed a bootstrap randomized subsampling with replacement procedure. We calculated the same statistics, along with their respective distributions, from 50 subsample iterations with four different subsampling intervals (i.e. daily, three day, weekly, and monthly). Based on our results we conclude that, depending on the types of questions being asked, and the watershed characteristics, Citizen Hydrology streamflow measurements can provide useful and accurate information. Depending on watershed characteristics, minimum flows were reasonably estimated with subsample intervals ranging from

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.)

Statistical process control for serially correlated data

NARCIS (Netherlands)

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

Analysis of thrips distribution: application of spatial statistics and Kriging

Science.gov (United States)

John Aleong; Bruce L. Parker; Margaret Skinner; Diantha Howard

1991-01-01

Kriging is a statistical technique that provides predictions for spatially and temporally correlated data. Observations of thrips distribution and density in Vermont soils are made in both space and time. Traditional statistical analysis of such data assumes that the counts taken over space and time are independent, which is not necessarily true. Therefore, to analyze...

Two sampling techniques for game meat

OpenAIRE

van der Merwe, Maretha; Jooste, Piet J.; Hoffman, Louw C.; Calitz, Frikkie J.

2013-01-01

A study was conducted to compare the excision sampling technique used by the export market and the sampling technique preferred by European countries, namely the biotrace cattle and swine test. The measuring unit for the excision sampling was grams (g) and square centimetres (cm2) for the swabbing technique. The two techniques were compared after a pilot test was conducted on spiked approved beef carcasses (n = 12) that statistically proved the two measuring units correlated. The two sampling...

Experimental techniques for cement hydration studies

Directory of Open Access Journals (Sweden)

Andreas Luttge

2011-10-01

Full Text Available Cement hydration kinetics is a complex problem of dissolution, nucleation and growth that is still not well understood, particularly in a quantitative way. While cement systems are unique in certain aspects they are also comparable to natural mineral systems. Therefore, geochemistry and particularly the study of mineral dissolution and growth may be able to provide insight and methods that can be utilized in cement hydration research. Here, we review mainly what is not known or what is currently used and applied in a problematic way. Examples are the typical Avrami approach, the application of Transition State Theory (TST to overall reaction kinetics and the problem of reactive surface area. Finally, we suggest an integrated approach that combines vertical scanning interferometry (VSI with other sophisticated analytical techniques such as atomic force microscopy (AFM and theoretical model calculations based on a stochastic treatment.

[Combined use of wide-detector and adaptive statistical iterative reconstruction-V technique in abdominal CT with low radiation dose].

Science.gov (United States)

Wang, H X; Lü, P J; Yue, S W; Chang, L Y; Li, Y; Zhao, H P; Li, W R; Gao, J B

2017-12-05

Objective: To investigate the image quality and radiation dose with wide-detector(80 mm) and adaptive statistical iterative reconstruction-V (ASIR-V) technique at abdominal contrast enhanced CT scan. Methods: In the first phantom experiment part, the percentage of ASIR-V for half dose of combined wide detector with ASIR-V technique as compared with standard-detector (40 mm) technique was determined. The human experiment was performed based on the phantom study, 160 patients underwent contrast-enhanced abdominal CT scan were prospectively collected and divided into the control group ( n =40) with image reconstruction using 40% ASIR (group A) and the study group ( n =120) with random number table. According to pre-ASIR-V percentage, the study group was assigned into three groups[40 cases in each group, group B: 0 pre-ASIR-V scan with image reconstruction of 0-100% post-ASIR-V (interval 10%, subgroups B0-B10); group C: 20% pre-ASIR-V with 20%, 40% and 60% post-ASIR-V (subgroups C1-C3); group D: 40%pre-ASIR-V with 40% and 60% post-ASIR-V (subgroups D1-D2)]. Image noise, CT attenuation values and CNR of the liver, pancreas, aorta and portal vein were compared by using two sample t test and One-way ANOVA. Qualitative visual parameters (overall image quality as graded on a 5-point scale) was compared by Mann-Whitney U test and Kruskal-Wallis H test. Results: The phantom experiment showed that the percentage of pre-ASIR-V for half dose was 40%. With the 40% pre-ASIR-V, radiation dose in the study group was reduced by 35.5% as compared with the control group. Image noise in the subgroups of B2-B10, C2-C3 and D1-D2 were lower ( t =-14.681--3.046, all P 0.05). The subjective image quality scores increased gradually in the range of 0-60% post-ASIR-V and decreased with post-ASIR-V larger than 70%. The overall image quality of subgroup B3-B8, C2-C3 and D1-D2 were higher than that in group A ( Z =-2.229--6.533, all P ASIR technique, wide-detector combined with 40% pre

Source Identification of Heavy Metals in Soils Surrounding the Zanjan Zinc Town by Multivariate Statistical Techniques

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M.A. Delavar

2016-02-01

Full Text Available Introduction: The accumulation of heavy metals (HMs in the soil is of increasing concern due to food safety issues, potential health risks, and the detrimental effects on soil ecosystems. HMs may be considered as the most important soil pollutants, because they are not biodegradable and their physical movement through the soil profile is relatively limited. Therefore, root uptake process may provide a big chance for these pollutants to transfer from the surface soil to natural and cultivated plants, which may eventually steer them to human bodies. The general behavior of HMs in the environment, especially their bioavailability in the soil, is influenced by their origin. Hence, source apportionment of HMs may provide some essential information for better management of polluted soils to restrict the HMs entrance to the human food chain. This paper explores the applicability of multivariate statistical techniques in the identification of probable sources that can control the concentration and distribution of selected HMs in the soils surrounding the Zanjan Zinc Specialized Industrial Town (briefly Zinc Town. Materials and Methods: The area under investigation has a size of approximately 4000 ha.It is located around the Zinc Town, Zanjan province. A regular grid sampling pattern with an interval of 500 meters was applied to identify the sample location, and 184 topsoil samples (0-10 cm were collected. The soil samples were air-dried and sieved through a 2 mm polyethylene sieve and then, were digested using HNO3. The total concentrations of zinc (Zn, lead (Pb, cadmium (Cd, Nickel (Ni and copper (Cu in the soil solutions were determined via Atomic Absorption Spectroscopy (AAS. Data were statistically analyzed using the SPSS software version 17.0 for Windows. Correlation Matrix (CM, Principal Component Analyses (PCA and Factor Analyses (FA techniques were performed in order to identify the probable sources of HMs in the studied soils. Results and

BOOK REVIEW: Statistical Mechanics of Turbulent Flows

Science.gov (United States)

Cambon, C.

2004-10-01

This is a handbook for a computational approach to reacting flows, including background material on statistical mechanics. In this sense, the title is somewhat misleading with respect to other books dedicated to the statistical theory of turbulence (e.g. Monin and Yaglom). In the present book, emphasis is placed on modelling (engineering closures) for computational fluid dynamics. The probabilistic (pdf) approach is applied to the local scalar field, motivated first by the nonlinearity of chemical source terms which appear in the transport equations of reacting species. The probabilistic and stochastic approaches are also used for the velocity field and particle position; nevertheless they are essentially limited to Lagrangian models for a local vector, with only single-point statistics, as for the scalar. Accordingly, conventional techniques, such as single-point closures for RANS (Reynolds-averaged Navier-Stokes) and subgrid-scale models for LES (large-eddy simulations), are described and in some cases reformulated using underlying Langevin models and filtered pdfs. Even if the theoretical approach to turbulence is not discussed in general, the essentials of probabilistic and stochastic-processes methods are described, with a useful reminder concerning statistics at the molecular level. The book comprises 7 chapters. Chapter 1 briefly states the goals and contents, with a very clear synoptic scheme on page 2. Chapter 2 presents definitions and examples of pdfs and related statistical moments. Chapter 3 deals with stochastic processes, pdf transport equations, from Kramer-Moyal to Fokker-Planck (for Markov processes), and moments equations. Stochastic differential equations are introduced and their relationship to pdfs described. This chapter ends with a discussion of stochastic modelling. The equations of fluid mechanics and thermodynamics are addressed in chapter 4. Classical conservation equations (mass, velocity, internal energy) are derived from their

First of all: Do not harm! Use of simulation for the training of regional anaesthesia techniques: Which skills can be trained without the patient as substitute for a mannequin.

Science.gov (United States)

Sujatta, Susanne

2015-03-01

Character of clinical skills training is always influenced by technical improvement and cultural changes. Over the last years, two trends have changed the way of traditional apprenticeship-style training in regional anaesthesia: firstly, the development in ultrasound-guided regional anaesthesia, and secondly, the reduced acceptance of using patients as mannequins for invasive techniques. Against this background, simulation techniques are explored, ranging from simple low-fidelity part-task training models to train skills in needle application, to highly sophisticated virtual reality models – the full range is covered. This review tries to discuss all available options with benefits and neglects. The task in clinical practice will be in choosing the right level of sophistication for the desired approach and trainee level. However, the transfer of simulated skills to clinical practice has not been evaluated. It has to be proven whether simulation-trained skills could, as a last consequence, reduce the risk to patients. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assessment of statistical agreement of three techniques for the study of cut marks: 3D digital microscope, laser scanning confocal microscopy and micro-photogrammetry.

Science.gov (United States)

Maté-González, Miguel Ángel; Aramendi, Julia; Yravedra, José; Blasco, Ruth; Rosell, Jordi; González-Aguilera, Diego; Domínguez-Rodrigo, Manuel

2017-09-01

In the last few years, the study of cut marks on bone surfaces has become fundamental for the interpretation of prehistoric butchery practices. Due to the difficulties in the correct identification of cut marks, many criteria for their description and classification have been suggested. Different techniques, such as three-dimensional digital microscope (3D DM), laser scanning confocal microscopy (LSCM) and micro-photogrammetry (M-PG) have been recently applied to the study of cut marks. Although the 3D DM and LSCM microscopic techniques are the most commonly used for the 3D identification of cut marks, M-PG has also proved to be very efficient and a low-cost method. M-PG is a noninvasive technique that allows the study of the cortical surface without any previous preparation of the samples, and that generates high-resolution models. Despite the current application of microscopic and micro-photogrammetric techniques to taphonomy, their reliability has never been tested. In this paper, we compare 3D DM, LSCM and M-PG in order to assess their resolution and results. In this study, we analyse 26 experimental cut marks generated with a metal knife. The quantitative and qualitative information registered is analysed by means of standard multivariate statistics and geometric morphometrics to assess the similarities and differences obtained with the different methodologies. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

TOF-SIMS imaging technique with information entropy

International Nuclear Information System (INIS)

Aoyagi, Satoka; Kawashima, Y.; Kudo, Masahiro

2005-01-01

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is capable of chemical imaging of proteins on insulated samples in principal. However, selection of specific peaks related to a particular protein, which are necessary for chemical imaging, out of numerous candidates had been difficult without an appropriate spectrum analysis technique. Therefore multivariate analysis techniques, such as principal component analysis (PCA), and analysis with mutual information defined by information theory, have been applied to interpret SIMS spectra of protein samples. In this study mutual information was applied to select specific peaks related to proteins in order to obtain chemical images. Proteins on insulated materials were measured with TOF-SIMS and then SIMS spectra were analyzed by means of the analysis method based on the comparison using mutual information. Chemical mapping of each protein was obtained using specific peaks related to each protein selected based on values of mutual information. The results of TOF-SIMS images of proteins on the materials provide some useful information on properties of protein adsorption, optimality of immobilization processes and reaction between proteins. Thus chemical images of proteins by TOF-SIMS contribute to understand interactions between material surfaces and proteins and to develop sophisticated biomaterials

Advanced statistics for tokamak transport colinearity and tokamak to tokamak variation

International Nuclear Information System (INIS)

Riedel, K.S.

1989-01-01

This paper is an expository introduction to advanced statistics and scaling laws and their application to tokamak devices. Topics of discussion are as follows: implicit assumptions in the standard analysis; advanced regression techniques; specialized tools in statistics and their applications in fusion physics; and improved datasets for transport studies

DATA ANALYSIS TECHNIQUES IN SERVICE QUALITY LITERATURE: ESSENTIALS AND ADVANCES

Directory of Open Access Journals (Sweden)

Mohammed naved Khan

2013-05-01

Full Text Available Academic and business researchers have for long debated on the most appropriate data analysis techniques that can be employed in conducting empirical researches in the domain of services marketing. On the basis of an exhaustive review of literature, the present paper attempts to provide a concise and schematic portrayal of generally followed data analysis techniques in the field of services quality literature. Collectively, the extant literature suggests that there is a growing trend among researchers to rely on higher order multivariate techniques viz. confirmatory factor analysis, structural equation modeling etc. to generate and analyze complex models, while at times ignoring very basic and yet powerful procedures such as mean, t-Test, ANOVA and correlation. The marked shift in orientation of researchers towards using sophisticated analytical techniques can largely beattributed to the competition within the community of researchers in social sciences in general and those working in the area of service quality in particular as also growing demands of reviewers ofjournals. From a pragmatic viewpoint, it is expected that the paper will serve as a useful source of information and provide deeper insights to academic researchers, consultants, and practitionersinterested in modelling patterns of service quality and arriving at optimal solutions to increasingly complex management problems.

Evaluating statistical tests on OLAP cubes to compare degree of disease.

Science.gov (United States)

Ordonez, Carlos; Chen, Zhibo

2009-09-01

Statistical tests represent an important technique used to formulate and validate hypotheses on a dataset. They are particularly useful in the medical domain, where hypotheses link disease with medical measurements, risk factors, and treatment. In this paper, we propose to compute parametric statistical tests treating patient records as elements in a multidimensional cube. We introduce a technique that combines dimension lattice traversal and statistical tests to discover significant differences in the degree of disease within pairs of patient groups. In order to understand a cause-effect relationship, we focus on patient group pairs differing in one dimension. We introduce several optimizations to prune the search space, to discover significant group pairs, and to summarize results. We present experiments showing important medical findings and evaluating scalability with medical datasets.

Fundamentals of modern statistical methods substantially improving power and accuracy

CERN Document Server

Wilcox, Rand R

2001-01-01

Conventional statistical methods have a very serious flaw They routinely miss differences among groups or associations among variables that are detected by more modern techniques - even under very small departures from normality Hundreds of journal articles have described the reasons standard techniques can be unsatisfactory, but simple, intuitive explanations are generally unavailable Improved methods have been derived, but they are far from obvious or intuitive based on the training most researchers receive Situations arise where even highly nonsignificant results become significant when analyzed with more modern methods Without assuming any prior training in statistics, Part I of this book describes basic statistical principles from a point of view that makes their shortcomings intuitive and easy to understand The emphasis is on verbal and graphical descriptions of concepts Part II describes modern methods that address the problems covered in Part I Using data from actual studies, many examples are include...

Application of Statistical Potential Techniques to Runaway Transport Studies

International Nuclear Information System (INIS)

Eguilior, S.; Castejon, F.; Parrondo, J. M.

2001-01-01

A method is presented for computing runaway production rate based on techniques of noise-activated escape in a potential is presented in this work. A generalised potential in 2D momentum space is obtained from the deterministic or drift terms of Langevin equations. The diffusive or stochastic terms that arise directly from the stochastic nature of collisions, play the role of the noise that activates barrier crossings. The runaway electron source is given by the escape rate in such a potential which is obtained from an Arrenius-like relation. Runaway electrons are those skip the potential barrier due to the effect of stochastic collisions. In terms of computation time, this method allows one to quickly obtain the source term for a runway electron transport code.(Author) 11 refs

Analysis of tribological behaviour of zirconia reinforced Al-SiC hybrid composites using statistical and artificial neural network technique

Science.gov (United States)

Arif, Sajjad; Tanwir Alam, Md; Ansari, Akhter H.; Bilal Naim Shaikh, Mohd; Arif Siddiqui, M.

2018-05-01

The tribological performance of aluminium hybrid composites reinforced with micro SiC (5 wt%) and nano zirconia (0, 3, 6 and 9 wt%) fabricated through powder metallurgy technique were investigated using statistical and artificial neural network (ANN) approach. The influence of zirconia reinforcement, sliding distance and applied load were analyzed with test based on full factorial design of experiments. Analysis of variance (ANOVA) was used to evaluate the percentage contribution of each process parameters on wear loss. ANOVA approach suggested that wear loss be mainly influenced by sliding distance followed by zirconia reinforcement and applied load. Further, a feed forward back propagation neural network was applied on input/output date for predicting and analyzing the wear behaviour of fabricated composite. A very close correlation between experimental and ANN output were achieved by implementing the model. Finally, ANN model was effectively used to find the influence of various control factors on wear behaviour of hybrid composites.

Renyi statistics in equilibrium statistical mechanics

International Nuclear Information System (INIS)

Parvan, A.S.; Biro, T.S.

2010-01-01

The Renyi statistics in the canonical and microcanonical ensembles is examined both in general and in particular for the ideal gas. In the microcanonical ensemble the Renyi statistics is equivalent to the Boltzmann-Gibbs statistics. By the exact analytical results for the ideal gas, it is shown that in the canonical ensemble, taking the thermodynamic limit, the Renyi statistics is also equivalent to the Boltzmann-Gibbs statistics. Furthermore it satisfies the requirements of the equilibrium thermodynamics, i.e. the thermodynamical potential of the statistical ensemble is a homogeneous function of first degree of its extensive variables of state. We conclude that the Renyi statistics arrives at the same thermodynamical relations, as those stemming from the Boltzmann-Gibbs statistics in this limit.

A course in statistics with R

CERN Document Server

Tattar, Prabhanjan N; Manjunath, B G

2016-01-01

Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R basics and quickly covers visualization and exploratory analysis. Probability and statistical inference, inclusive of classical, nonparametric, and Bayesian schools, is developed with definitions, motivations, mathematical expression and R programs in a way which will help the reader to understand the mathematical development as well as R implementation. Linear regression models, experimental designs, multivariate analysis, and categorical data analysis are treated in a way which makes effective use of visualization techniques and...

Semi-Poisson statistics in quantum chaos.

Science.gov (United States)

García-García, Antonio M; Wang, Jiao

2006-03-01

We investigate the quantum properties of a nonrandom Hamiltonian with a steplike singularity. It is shown that the eigenfunctions are multifractals and, in a certain range of parameters, the level statistics is described exactly by semi-Poisson statistics (SP) typical of pseudointegrable systems. It is also shown that our results are universal, namely, they depend exclusively on the presence of the steplike singularity and are not modified by smooth perturbations of the potential or the addition of a magnetic flux. Although the quantum properties of our system are similar to those of a disordered conductor at the Anderson transition, we report important quantitative differences in both the level statistics and the multifractal dimensions controlling the transition. Finally, the study of quantum transport properties suggests that the classical singularity induces quantum anomalous diffusion. We discuss how these findings may be experimentally corroborated by using ultracold atoms techniques.

Statistics and analysis of scientific data

CERN Document Server

Bonamente, Massimiliano

2017-01-01

The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains. Features new to this edition include: • a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets. • a new chapter on the various measures of the mean including logarithmic averages. • new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors. • a new case study and additional worked examples. • mathematical derivations and theoretical background material have been appropriately marked,to improve the readabili...

Set Theory : Techniques and Applications : Curaçao 1995 and Barcelona 1996 Conferences

CERN Document Server

Larson, Jean; Bagaria, Joan; Mathias, A

1998-01-01

During the past 25 years, set theory has developed in several interesting directions. The most outstanding results cover the application of sophisticated techniques to problems in analysis, topology, infinitary combinatorics and other areas of mathematics. This book contains a selection of contributions, some of which are expository in nature, embracing various aspects of the latest developments. Amongst topics treated are forcing axioms and their applications, combinatorial principles used to construct models, and a variety of other set theoretical tools including inner models, partitions and trees. Audience: This book will be of interest to graduate students and researchers in foundational problems of mathematics.

Science Academies' Refresher Course in Statistical Physics

Indian Academy of Sciences (India)

The Course is aimed at college teachers of statistical physics at BSc/MSc level. It will cover basic principles and techniques, in a pedagogical manner, through lectures and tutorials, with illustrative problems. Some advanced topics, and common difficulties faced by students will also be discussed. College/University ...

Sound statistical model checking for MDP using partial order and confluence reduction

NARCIS (Netherlands)

Hartmanns, Arnd; Timmer, Mark

Statistical model checking (SMC) is an analysis method that circumvents the state space explosion problem in model-based verification by combining probabilistic simulation with statistical methods that provide clear error bounds. As a simulation-based technique, it can in general only provide sound

Dynamical and statistical downscaling of precipitation and temperature in a Mediterranean area

KAUST Repository

Pizzigalli, Claudia

2012-03-28

In this paper we present and discuss a comparison between statistical and regional climate modeling techniques for downscaling GCM prediction . The comparison is carried out over the “Capitanata” region, an area of agricultural interest in south-eastern Italy, for current (1961-1990) and future (2071–2100) climate. The statistical model is based on Canonical Correlation Analysis (CCA), associated with a data pre-filtering obtained by a Principal Component Analysis (PCA), whereas the Regional Climate Model REGCM3 was used for dynamical downscaling. Downscaling techniques were applied to estimate rainfall, maximum and minimum temperatures and average number of consecutive wet and dry days. Both methods have comparable skills in estimating stations data. They show good results for spring, the most important season for agriculture. Both statistical and dynamical models reproduce the statistical properties of precipitation well, the crucial variable for the growth of crops.

Statistical lamb wave localization based on extreme value theory

Science.gov (United States)

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.

Analytical Techniques and the Air Force Logistics Readiness Officer

National Research Council Canada - National Science Library

Main, Bryan D

2008-01-01

.... Over 500 LROs and supervisors provided inputs. Analysis of survey responses found that Forecasting, Graphical Statistics, and Descriptive Statistics are the analytical techniques valued most by both LROs and their supervisors...

A clinical perspective of accelerated statistical reconstruction

International Nuclear Information System (INIS)

Hutton, B.F.; Hudson, H.M.; Beekman, F.J.

1997-01-01

Although the potential benefits of maximum likelihood reconstruction have been recognised for many years, the technique has only recently found widespread popularity in clinical practice. Factors which have contributed to the wider acceptance include improved models for the emission process, better understanding of the properties of the algorithm and, not least, the practicality of application with the development of acceleration schemes and the improved speed of computers. The objective in this article is to present a framework for applying maximum likelihood reconstruction for a wide range of clinically based problems. The article draws particularly on the experience of the three authors in applying an acceleration scheme involving use of ordered subsets to a range of applications. The potential advantages of statistical reconstruction techniques include: (a) the ability to better model the emission and detection process, in order to make the reconstruction converge to a quantitative image, (b) the inclusion of a statistical noise model which results in better noise characteristics, and (c) the possibility to incorporate prior knowledge about the distribution being imaged. The great flexibility in adapting the reconstruction for a specific model results in these techniques having wide applicability to problems in clinical nuclear medicine. (orig.). With 8 figs., 1 tab

Time resolved techniques: An overview

International Nuclear Information System (INIS)

Larson, B.C.; Tischler, J.Z.

1990-06-01

Synchrotron sources provide exceptional opportunities for carrying out time-resolved x-ray diffraction investigations. The high intensity, high angular resolution, and continuously tunable energy spectrum of synchrotron x-ray beams lend themselves directly to carrying out sophisticated time-resolved x-ray scattering measurements on a wide range of materials and phenomena. When these attributes are coupled with the pulsed time-structure of synchrotron sources, entirely new time-resolved scattering possibilities are opened. Synchrotron beams typically consist of sub-nanosecond pulses of x-rays separated in time by a few tens of nanoseconds to a few hundred nanoseconds so that these beams appear as continuous x-ray sources for investigations of phenomena on time scales ranging from hours down to microseconds. Studies requiring time-resolution ranging from microseconds to fractions of a nanosecond can be carried out in a triggering mode by stimulating the phenomena under investigation in coincidence with the x-ray pulses. Time resolution on the picosecond scale can, in principle, be achieved through the use of streak camera techniques in which the time structure of the individual x-ray pulses are viewed as quasi-continuous sources with ∼100--200 picoseconds duration. Techniques for carrying out time-resolved scattering measurements on time scales varying from picoseconds to kiloseconds at present and proposed synchrotron sources are discussed and examples of time-resolved studies are cited. 17 refs., 8 figs

Use of run statistics to validate tensile tests

International Nuclear Information System (INIS)

Eatherly, W.P.

1981-01-01

In tensile testing of irradiated graphites, it is difficult to assure alignment of sample and train for tensile measurements. By recording location of fractures, run (sequential) statistics can readily detect lack of randomness. The technique is based on partitioning binomial distributions

Statistical perspectives on inverse problems

DEFF Research Database (Denmark)

Andersen, Kim Emil

of the interior of an object from electrical boundary measurements. One part of this thesis concerns statistical approaches for solving, possibly non-linear, inverse problems. Thus inverse problems are recasted in a form suitable for statistical inference. In particular, a Bayesian approach for regularisation...... problem is given in terms of probability distributions. Posterior inference is obtained by Markov chain Monte Carlo methods and new, powerful simulation techniques based on e.g. coupled Markov chains and simulated tempering is developed to improve the computational efficiency of the overall simulation......Inverse problems arise in many scientific disciplines and pertain to situations where inference is to be made about a particular phenomenon from indirect measurements. A typical example, arising in diffusion tomography, is the inverse boundary value problem for non-invasive reconstruction...

Data Mining and Statistics for Decision Making

CERN Document Server

Tufféry, Stéphane

2011-01-01

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of data mining, such as clustering, discriminant analysis, logistic regression, generalized lin

Multivariate Analysis, Mass Balance Techniques, and Statistical Tests as Tools in Igneous Petrology: Application to the Sierra de las Cruces Volcanic Range (Mexican Volcanic Belt)

Science.gov (United States)

Velasco-Tapia, Fernando

2014-01-01

Magmatic processes have usually been identified and evaluated using qualitative or semiquantitative geochemical or isotopic tools based on a restricted number of variables. However, a more complete and quantitative view could be reached applying multivariate analysis, mass balance techniques, and statistical tests. As an example, in this work a statistical and quantitative scheme is applied to analyze the geochemical features for the Sierra de las Cruces (SC) volcanic range (Mexican Volcanic Belt). In this locality, the volcanic activity (3.7 to 0.5 Ma) was dominantly dacitic, but the presence of spheroidal andesitic enclaves and/or diverse disequilibrium features in majority of lavas confirms the operation of magma mixing/mingling. New discriminant-function-based multidimensional diagrams were used to discriminate tectonic setting. Statistical tests of discordancy and significance were applied to evaluate the influence of the subducting Cocos plate, which seems to be rather negligible for the SC magmas in relation to several major and trace elements. A cluster analysis following Ward's linkage rule was carried out to classify the SC volcanic rocks geochemical groups. Finally, two mass-balance schemes were applied for the quantitative evaluation of the proportion of the end-member components (dacitic and andesitic magmas) in the comingled lavas (binary mixtures). PMID:24737994

Multivariate Analysis, Mass Balance Techniques, and Statistical Tests as Tools in Igneous Petrology: Application to the Sierra de las Cruces Volcanic Range (Mexican Volcanic Belt

Directory of Open Access Journals (Sweden)

Fernando Velasco-Tapia

2014-01-01

Full Text Available Magmatic processes have usually been identified and evaluated using qualitative or semiquantitative geochemical or isotopic tools based on a restricted number of variables. However, a more complete and quantitative view could be reached applying multivariate analysis, mass balance techniques, and statistical tests. As an example, in this work a statistical and quantitative scheme is applied to analyze the geochemical features for the Sierra de las Cruces (SC volcanic range (Mexican Volcanic Belt. In this locality, the volcanic activity (3.7 to 0.5 Ma was dominantly dacitic, but the presence of spheroidal andesitic enclaves and/or diverse disequilibrium features in majority of lavas confirms the operation of magma mixing/mingling. New discriminant-function-based multidimensional diagrams were used to discriminate tectonic setting. Statistical tests of discordancy and significance were applied to evaluate the influence of the subducting Cocos plate, which seems to be rather negligible for the SC magmas in relation to several major and trace elements. A cluster analysis following Ward’s linkage rule was carried out to classify the SC volcanic rocks geochemical groups. Finally, two mass-balance schemes were applied for the quantitative evaluation of the proportion of the end-member components (dacitic and andesitic magmas in the comingled lavas (binary mixtures.

A wavenumber-partitioning scheme for two-dimensional statistical closures

International Nuclear Information System (INIS)

Bowman, J.C.

1994-11-01

One of the principal advantages of statistical closure approximations for fluid turbulence is that they involve smoothly varying functions of wavenumber. This suggests the possibility of modeling a flow by following the evolution of only a few representative wavenumbers. This work presents two new techniques for the implementation of two-dimensional isotropic statistical closures that for the first time allows the inertial-range scalings of these approximation to be numerically demonstrated. A technique of wavenumber partitioning that conserves both energy and enstrophy is developed for two-dimensional statistical closures. Coupled with a new time-stepping scheme based on a variable integrating factor, this advance facilitates the computation of energy spectra over seven wavenumber decades, a task that will clearly remain outside the realm of conventional numerical simulations for the foreseeable future. Within the context of the test-field model, the method is used to demonstrate Kraichnan's logarithmically-corrected scaling for the enstrophy inertial range and to make a quantitative assessment of the effect of replacing the physical Laplacian viscosity with an enhanced hyperviscosity

SEGMENTATION AND CLASSIFICATION OF CERVICAL CYTOLOGY IMAGES USING MORPHOLOGICAL AND STATISTICAL OPERATIONS

Directory of Open Access Journals (Sweden)

S Anantha Sivaprakasam

2017-02-01

Full Text Available Cervical cancer that is a disease, in which malignant (cancer cells form in the tissues of the cervix, is one of the fourth leading causes of cancer death in female community worldwide. The cervical cancer can be prevented and/or cured if it is diagnosed in the pre-cancerous lesion stage or earlier. A common physical examination technique widely used in the screening is called Papanicolaou test or Pap test which is used to detect the abnormality of the cell. Due to intricacy of the cell nature, automating of this procedure is still a herculean task for the pathologist. This paper addresses solution for the challenges in terms of a simple and novel method to segment and classify the cervical cell automatically. The primary step of this procedure is pre-processing in which de-nosing, de-correlation operation and segregation of colour components are carried out, Then, two new techniques called Morphological and Statistical Edge based segmentation and Morphological and Statistical Region Based segmentation Techniques- put forward in this paper, and that are applied on the each component of image to segment the nuclei from cervical image. Finally, all segmented colour components are combined together to make a final segmentation result. After extracting the nuclei, the morphological features are extracted from the nuclei. The performance of two techniques mentioned above outperformed than standard segmentation techniques. Besides, Morphological and Statistical Edge based segmentation is outperformed than Morphological and Statistical Region based Segmentation. Finally, the nuclei are classified based on the morphological value The segmentation accuracy is echoed in classification accuracy. The overall segmentation accuracy is 97%.

Quantitation of PET data with the EM reconstruction technique

International Nuclear Information System (INIS)

Rosenqvist, G.; Dahlbom, M.; Erikson, L.; Bohm, C.; Blomqvist, G.

1989-01-01

The expectation maximization (EM) algorithm offers high spatial resolution and excellent noise reduction with low statistics PET data, since it incorporates the Poisson nature of the data. The main difficulties are long computation times, difficulties to find appropriate criteria to terminate the reconstruction and to quantify the resulting image data. In the present work a modified EM algorithm has been implements on a VAX 11/780. Its capability to quantify image data has been tested in phantom studies and in two clinical cases, cerebral blood flow studies and dopamine D2-receptor studies. Data from phantom studies indicate the superiority of images reconstructed with the EM technique compared to images reconstructed with the conventional filtered back-projection (FB) technique in areas with low statistics. At higher statistics the noise characteristics of the two techniques coincide. Clinical data support these findings

Statistics of extremes theory and applications

CERN Document Server

Beirlant, Jan; Segers, Johan; Teugels, Jozef; De Waal, Daniel; Ferro, Chris

2006-01-01

Research in the statistical analysis of extreme values has flourished over the past decade: new probability models, inference and data analysis techniques have been introduced; and new application areas have been explored. Statistics of Extremes comprehensively covers a wide range of models and application areas, including risk and insurance: a major area of interest and relevance to extreme value theory. Case studies are introduced providing a good balance of theory and application of each model discussed, incorporating many illustrated examples and plots of data. The last part of the book covers some interesting advanced topics, including  time series, regression, multivariate and Bayesian modelling of extremes, the use of which has huge potential.  

Statistical physics of medical ultrasonic images

International Nuclear Information System (INIS)

Wagner, R.F.; Insana, M.F.; Brown, D.G.; Smith, S.W.

1987-01-01

The physical and statistical properties of backscattered signals in medical ultrasonic imaging are reviewed in terms of: 1) the radiofrequency signal; 2) the envelope (video or magnitude) signal; and 3) the density of samples in simple and in compounded images. There is a wealth of physical information in backscattered signals in medical ultrasound. This information is contained in the radiofrequency spectrum - which is not typically displayed to the viewer - as well as in the higher statistical moments of the envelope or video signal - which are not readily accessed by the human viewer of typical B-scans. This information may be extracted from the detected backscattered signals by straightforward signal processing techniques at low resolution

Nanosilver conductive lines made by spray coating and aerosol jet printing technique

Science.gov (United States)

Krzeminski, Jakub; Wroblewski, Grzegorz; Dybowska-Sarapuk, Lucja; Lepak, Sandra; Jakubowska, Malgorzata

2017-08-01

Printing electronics even though the printing techniques are known for a long time, are gaining in importance. The possibility of making the electronic circuits on flexible, big-area substrates with efficient and cheap technology make it attractive for the electronic industry. Spray coating, as a one of printing methods, additionally provide the chance to print on the non-flat, complicated shaped substrates. Despite the spray coating is mostly used to print a big pads, it is reachable to spray the separate conductive lines both as a quickly-produced prototype and as a fully manufactured circuit. Our work presents the directly printed lines with spray coating technique. For the printing process self-made ink was used. We tested three different approaches to line formation and compare them in the terms of line edge, resistivity and thickness. Line profiles provide the information about the roughness and the line size. In the end we showed the aerosol jet printed meander to give an overview of this similar to spray coating but more sophisticated technique.

Statistics and Corporate Environmental Management: Relations and Problems

DEFF Research Database (Denmark)

Madsen, Henning; Ulhøi, John Parm

1997-01-01

Statistical methods have long been used to analyse the macroeconomic consequences of environmentally damaging activities, political actions to control, prevent, or reduce these damages, and environmental problems in the natural environment. Up to now, however, they have had a limited and not very...... specific use in corporate environmental management systems. This paper will address some of the special problems related to the use of statistical techniques in corporate environmental management systems. One important aspect of this is the interaction of internal decisions and activities with conditions...

Radar Derived Spatial Statistics of Summer Rain. Volume 2; Data Reduction and Analysis

Science.gov (United States)

Konrad, T. G.; Kropfli, R. A.

1975-01-01

Data reduction and analysis procedures are discussed along with the physical and statistical descriptors used. The statistical modeling techniques are outlined and examples of the derived statistical characterization of rain cells in terms of the several physical descriptors are presented. Recommendations concerning analyses which can be pursued using the data base collected during the experiment are included.

Time-series-analysis techniques applied to nuclear-material accounting

International Nuclear Information System (INIS)

Pike, D.H.; Morrison, G.W.; Downing, D.J.

1982-05-01

This document is designed to introduce the reader to the applications of Time Series Analysis techniques to Nuclear Material Accountability data. Time series analysis techniques are designed to extract information from a collection of random variables ordered by time by seeking to identify any trends, patterns, or other structure in the series. Since nuclear material accountability data is a time series, one can extract more information using time series analysis techniques than by using other statistical techniques. Specifically, the objective of this document is to examine the applicability of time series analysis techniques to enhance loss detection of special nuclear materials. An introductory section examines the current industry approach which utilizes inventory differences. The error structure of inventory differences is presented. Time series analysis techniques discussed include the Shewhart Control Chart, the Cumulative Summation of Inventory Differences Statistics (CUSUM) and the Kalman Filter and Linear Smoother

On quantum statistical inference

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Gill, Richard D.; Jupp, Peter E.

Recent developments in the mathematical foundations of quantum mechanics have brought the theory closer to that of classical probability and statistics. On the other hand, the unique character of quantum physics sets many of the questions addressed apart from those met classically in stochastics....... Furthermore, concurrent advances in experimental techniques and in the theory of quantum computation have led to a strong interest in questions of quantum information, in particular in the sense of the amount of information about unknown parameters in given observational data or accessible through various...

Noise removing in encrypted color images by statistical analysis

Science.gov (United States)

Islam, N.; Puech, W.

2012-03-01

Cryptographic techniques are used to secure confidential data from unauthorized access but these techniques are very sensitive to noise. A single bit change in encrypted data can have catastrophic impact over the decrypted data. This paper addresses the problem of removing bit error in visual data which are encrypted using AES algorithm in the CBC mode. In order to remove the noise, a method is proposed which is based on the statistical analysis of each block during the decryption. The proposed method exploits local statistics of the visual data and confusion/diffusion properties of the encryption algorithm to remove the errors. Experimental results show that the proposed method can be used at the receiving end for the possible solution for noise removing in visual data in encrypted domain.

Statistical iterative reconstruction to improve image quality for digital breast tomosynthesis

International Nuclear Information System (INIS)

Xu, Shiyu; Chen, Ying; Lu, Jianping; Zhou, Otto

2015-01-01

Purpose: Digital breast tomosynthesis (DBT) is a novel modality with the potential to improve early detection of breast cancer by providing three-dimensional (3D) imaging with a low radiation dose. 3D image reconstruction presents some challenges: cone-beam and flat-panel geometry, and highly incomplete sampling. A promising means to overcome these challenges is statistical iterative reconstruction (IR), since it provides the flexibility of accurate physics modeling and a general description of system geometry. The authors’ goal was to develop techniques for applying statistical IR to tomosynthesis imaging data. Methods: These techniques include the following: a physics model with a local voxel-pair based prior with flexible parameters to fine-tune image quality; a precomputed parameter λ in the prior, to remove data dependence and to achieve a uniform resolution property; an effective ray-driven technique to compute the forward and backprojection; and an oversampled, ray-driven method to perform high resolution reconstruction with a practical region-of-interest technique. To assess the performance of these techniques, the authors acquired phantom data on the stationary DBT prototype system. To solve the estimation problem, the authors proposed an optimization-transfer based algorithm framework that potentially allows fewer iterations to achieve an acceptably converged reconstruction. Results: IR improved the detectability of low-contrast and small microcalcifications, reduced cross-plane artifacts, improved spatial resolution, and lowered noise in reconstructed images. Conclusions: Although the computational load remains a significant challenge for practical development, the superior image quality provided by statistical IR, combined with advancing computational techniques, may bring benefits to screening, diagnostics, and intraoperative imaging in clinical applications