WorldWideScience

Sample records for transportation statistics cross-classified

  1. Transport Statistics - Transport - UNECE

    Science.gov (United States)

    Sustainable Energy Statistics Trade Transport Themes UNECE and the SDGs Climate Change Gender Ideas 4 Change UNECE Weekly Videos UNECE Transport Areas of Work Transport Statistics Transport Transport Statistics About us Terms of Reference Meetings and Events Meetings Working Party on Transport Statistics (WP.6

  2. Robust Combining of Disparate Classifiers Through Order Statistics

    Science.gov (United States)

    Tumer, Kagan; Ghosh, Joydeep

    2001-01-01

    Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.

  3. Deconstructing Cross-Entropy for Probabilistic Binary Classifiers

    Directory of Open Access Journals (Sweden)

    Daniel Ramos

    2018-03-01

    Full Text Available In this work, we analyze the cross-entropy function, widely used in classifiers both as a performance measure and as an optimization objective. We contextualize cross-entropy in the light of Bayesian decision theory, the formal probabilistic framework for making decisions, and we thoroughly analyze its motivation, meaning and interpretation from an information-theoretical point of view. In this sense, this article presents several contributions: First, we explicitly analyze the contribution to cross-entropy of (i prior knowledge; and (ii the value of the features in the form of a likelihood ratio. Second, we introduce a decomposition of cross-entropy into two components: discrimination and calibration. This decomposition enables the measurement of different performance aspects of a classifier in a more precise way; and justifies previously reported strategies to obtain reliable probabilities by means of the calibration of the output of a discriminating classifier. Third, we give different information-theoretical interpretations of cross-entropy, which can be useful in different application scenarios, and which are related to the concept of reference probabilities. Fourth, we present an analysis tool, the Empirical Cross-Entropy (ECE plot, a compact representation of cross-entropy and its aforementioned decomposition. We show the power of ECE plots, as compared to other classical performance representations, in two diverse experimental examples: a speaker verification system, and a forensic case where some glass findings are present.

  4. On the statistical assessment of classifiers using DNA microarray data

    Directory of Open Access Journals (Sweden)

    Carella M

    2006-08-01

    Full Text Available Abstract Background In this paper we present a method for the statistical assessment of cancer predictors which make use of gene expression profiles. The methodology is applied to a new data set of microarray gene expression data collected in Casa Sollievo della Sofferenza Hospital, Foggia – Italy. The data set is made up of normal (22 and tumor (25 specimens extracted from 25 patients affected by colon cancer. We propose to give answers to some questions which are relevant for the automatic diagnosis of cancer such as: Is the size of the available data set sufficient to build accurate classifiers? What is the statistical significance of the associated error rates? In what ways can accuracy be considered dependant on the adopted classification scheme? How many genes are correlated with the pathology and how many are sufficient for an accurate colon cancer classification? The method we propose answers these questions whilst avoiding the potential pitfalls hidden in the analysis and interpretation of microarray data. Results We estimate the generalization error, evaluated through the Leave-K-Out Cross Validation error, for three different classification schemes by varying the number of training examples and the number of the genes used. The statistical significance of the error rate is measured by using a permutation test. We provide a statistical analysis in terms of the frequencies of the genes involved in the classification. Using the whole set of genes, we found that the Weighted Voting Algorithm (WVA classifier learns the distinction between normal and tumor specimens with 25 training examples, providing e = 21% (p = 0.045 as an error rate. This remains constant even when the number of examples increases. Moreover, Regularized Least Squares (RLS and Support Vector Machines (SVM classifiers can learn with only 15 training examples, with an error rate of e = 19% (p = 0.035 and e = 18% (p = 0.037 respectively. Moreover, the error rate

  5. State Transportation Statistics 2014

    Science.gov (United States)

    2014-12-15

    The Bureau of Transportation Statistics (BTS) presents State Transportation Statistics 2014, a statistical profile of transportation in the 50 states and the District of Columbia. This is the 12th annual edition of State Transportation Statistics, a ...

  6. State Transportation Statistics 2012

    Science.gov (United States)

    2013-08-15

    The Bureau of Transportation Statistics (BTS), a part of the U.S. Department of Transportation's (USDOT) Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2012, a statistical profile of transportation ...

  7. Statistical and Machine-Learning Classifier Framework to Improve Pulse Shape Discrimination System Design

    Energy Technology Data Exchange (ETDEWEB)

    Wurtz, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kaplan, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-10-28

    Pulse shape discrimination (PSD) is a variety of statistical classifier. Fully-­realized statistical classifiers rely on a comprehensive set of tools for designing, building, and implementing. PSD advances rely on improvements to the implemented algorithm. PSD advances can be improved by using conventional statistical classifier or machine learning methods. This paper provides the reader with a glossary of classifier-­building elements and their functions in a fully-­designed and operational classifier framework that can be used to discover opportunities for improving PSD classifier projects. This paper recommends reporting the PSD classifier’s receiver operating characteristic (ROC) curve and its behavior at a gamma rejection rate (GRR) relevant for realistic applications.

  8. Classifying hot water chemistry: Application of MULTIVARIATE STATISTICS

    OpenAIRE

    Sumintadireja, Prihadi; Irawan, Dasapta Erwin; Rezky, Yuanno; Gio, Prana Ugiana; Agustin, Anggita

    2016-01-01

    This file is the dataset for the following paper "Classifying hot water chemistry: Application of MULTIVARIATE STATISTICS". Authors: Prihadi Sumintadireja1, Dasapta Erwin Irawan1, Yuano Rezky2, Prana Ugiana Gio3, Anggita Agustin1

  9. State Transportation Statistics 2013

    Science.gov (United States)

    2014-09-19

    The Bureau of Transportation Statistics (BTS), a part of the U.S. Department of Transportations (USDOT) Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2013, a statistical profile of transportatio...

  10. State transportation statistics 2009

    Science.gov (United States)

    2009-01-01

    The Bureau of Transportation Statistics (BTS), a part of DOTs Research and : Innovative Technology Administration (RITA), presents State Transportation : Statistics 2009, a statistical profile of transportation in the 50 states and the : District ...

  11. State Transportation Statistics 2010

    Science.gov (United States)

    2011-09-14

    The Bureau of Transportation Statistics (BTS), a part of DOTs Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2010, a statistical profile of transportation in the 50 states and the District of Col...

  12. State Transportation Statistics 2011

    Science.gov (United States)

    2012-08-08

    The Bureau of Transportation Statistics (BTS), a part of DOTs Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2011, a statistical profile of transportation in the 50 states and the District of Col...

  13. National transportation statistics 2011

    Science.gov (United States)

    2011-04-01

    Compiled and published by the U.S. Department of Transportation's Bureau of Transportation Statistics : (BTS), National Transportation Statistics presents information on the U.S. transportation system, including : its physical components, safety reco...

  14. National Transportation Statistics 2008

    Science.gov (United States)

    2009-01-08

    Compiled and published by the U.S. Department of Transportations Bureau of Transportation Statistics (BTS), National Transportation Statistics presents information on the U.S. transportation system, including its physical components, safety record...

  15. National Transportation Statistics 2009

    Science.gov (United States)

    2010-01-21

    Compiled and published by the U.S. Department of Transportation's Bureau of Transportation Statistics (BTS), National Transportation Statistics presents information on the U.S. transportation system, including its physical components, safety record, ...

  16. Classification of THz pulse signals using two-dimensional cross-correlation feature extraction and non-linear classifiers.

    Science.gov (United States)

    Siuly; Yin, Xiaoxia; Hadjiloucas, Sillas; Zhang, Yanchun

    2016-04-01

    This work provides a performance comparison of four different machine learning classifiers: multinomial logistic regression with ridge estimators (MLR) classifier, k-nearest neighbours (KNN), support vector machine (SVM) and naïve Bayes (NB) as applied to terahertz (THz) transient time domain sequences associated with pixelated images of different powder samples. The six substances considered, although have similar optical properties, their complex insertion loss at the THz part of the spectrum is significantly different because of differences in both their frequency dependent THz extinction coefficient as well as differences in their refractive index and scattering properties. As scattering can be unquantifiable in many spectroscopic experiments, classification solely on differences in complex insertion loss can be inconclusive. The problem is addressed using two-dimensional (2-D) cross-correlations between background and sample interferograms, these ensure good noise suppression of the datasets and provide a range of statistical features that are subsequently used as inputs to the above classifiers. A cross-validation procedure is adopted to assess the performance of the classifiers. Firstly the measurements related to samples that had thicknesses of 2mm were classified, then samples at thicknesses of 4mm, and after that 3mm were classified and the success rate and consistency of each classifier was recorded. In addition, mixtures having thicknesses of 2 and 4mm as well as mixtures of 2, 3 and 4mm were presented simultaneously to all classifiers. This approach provided further cross-validation of the classification consistency of each algorithm. The results confirm the superiority in classification accuracy and robustness of the MLR (least accuracy 88.24%) and KNN (least accuracy 90.19%) algorithms which consistently outperformed the SVM (least accuracy 74.51%) and NB (least accuracy 56.86%) classifiers for the same number of feature vectors across all studies

  17. Statistical text classifier to detect specific type of medical incidents.

    Science.gov (United States)

    Wong, Zoie Shui-Yee; Akiyama, Masanori

    2013-01-01

    WHO Patient Safety has put focus to increase the coherence and expressiveness of patient safety classification with the foundation of International Classification for Patient Safety (ICPS). Text classification and statistical approaches has showed to be successful to identifysafety problems in the Aviation industryusing incident text information. It has been challenging to comprehend the taxonomy of medical incidents in a structured manner. Independent reporting mechanisms for patient safety incidents have been established in the UK, Canada, Australia, Japan, Hong Kong etc. This research demonstrates the potential to construct statistical text classifiers to detect specific type of medical incidents using incident text data. An illustrative example for classifying look-alike sound-alike (LASA) medication incidents using structured text from 227 advisories related to medication errors from Global Patient Safety Alerts (GPSA) is shown in this poster presentation. The classifier was built using logistic regression model. ROC curve and the AUC value indicated that this is a satisfactory good model.

  18. National transportation statistics 2010

    Science.gov (United States)

    2010-01-01

    National Transportation Statistics presents statistics on the U.S. transportation system, including its physical components, safety record, economic performance, the human and natural environment, and national security. This is a large online documen...

  19. Identifying Different Transportation Modes from Trajectory Data Using Tree-Based Ensemble Classifiers

    Directory of Open Access Journals (Sweden)

    Zhibin Xiao

    2017-02-01

    Full Text Available Recognition of transportation modes can be used in different applications including human behavior research, transport management and traffic control. Previous work on transportation mode recognition has often relied on using multiple sensors or matching Geographic Information System (GIS information, which is not possible in many cases. In this paper, an approach based on ensemble learning is proposed to infer hybrid transportation modes using only Global Position System (GPS data. First, in order to distinguish between different transportation modes, we used a statistical method to generate global features and extract several local features from sub-trajectories after trajectory segmentation, before these features were combined in the classification stage. Second, to obtain a better performance, we used tree-based ensemble models (Random Forest, Gradient Boosting Decision Tree, and XGBoost instead of traditional methods (K-Nearest Neighbor, Decision Tree, and Support Vector Machines to classify the different transportation modes. The experiment results on the later have shown the efficacy of our proposed approach. Among them, the XGBoost model produced the best performance with a classification accuracy of 90.77% obtained on the GEOLIFE dataset, and we used a tree-based ensemble method to ensure accurate feature selection to reduce the model complexity.

  20. Using Statistical Process Control Methods to Classify Pilot Mental Workloads

    National Research Council Canada - National Science Library

    Kudo, Terence

    2001-01-01

    .... These include cardiac, ocular, respiratory, and brain activity measures. The focus of this effort is to apply statistical process control methodology on different psychophysiological features in an attempt to classify pilot mental workload...

  1. Transportation statistics annual report 2010

    Science.gov (United States)

    2011-01-01

    The Transportation Statistics Annual Report (TSAR) presents data and information compiled by the Bureau of Transportation Statistics (BTS), a component of the U.S. Department of Transportations (USDOTs) Research and Innovative Technology Admini...

  2. Transportation statistics annual report 2009

    Science.gov (United States)

    2009-01-01

    The Transportation Statistics Annual Report (TSAR) presents data and information selected by the Bureau of Transportation Statistics (BTS), a component of the U.S. Department of Transportation's (USDOT's) Research and Innovative Technology Administra...

  3. STATISTICAL TOOLS FOR CLASSIFYING GALAXY GROUP DYNAMICS

    International Nuclear Information System (INIS)

    Hou, Annie; Parker, Laura C.; Harris, William E.; Wilman, David J.

    2009-01-01

    The dynamical state of galaxy groups at intermediate redshifts can provide information about the growth of structure in the universe. We examine three goodness-of-fit tests, the Anderson-Darling (A-D), Kolmogorov, and χ 2 tests, in order to determine which statistical tool is best able to distinguish between groups that are relaxed and those that are dynamically complex. We perform Monte Carlo simulations of these three tests and show that the χ 2 test is profoundly unreliable for groups with fewer than 30 members. Power studies of the Kolmogorov and A-D tests are conducted to test their robustness for various sample sizes. We then apply these tests to a sample of the second Canadian Network for Observational Cosmology Redshift Survey (CNOC2) galaxy groups and find that the A-D test is far more reliable and powerful at detecting real departures from an underlying Gaussian distribution than the more commonly used χ 2 and Kolmogorov tests. We use this statistic to classify a sample of the CNOC2 groups and find that 34 of 106 groups are inconsistent with an underlying Gaussian velocity distribution, and thus do not appear relaxed. In addition, we compute velocity dispersion profiles (VDPs) for all groups with more than 20 members and compare the overall features of the Gaussian and non-Gaussian groups, finding that the VDPs of the non-Gaussian groups are distinct from those classified as Gaussian.

  4. A novel statistical method for classifying habitat generalists and specialists

    DEFF Research Database (Denmark)

    Chazdon, Robin L; Chao, Anne; Colwell, Robert K

    2011-01-01

    in second-growth (SG) and old-growth (OG) rain forests in the Caribbean lowlands of northeastern Costa Rica. We evaluate the multinomial model in detail for the tree data set. Our results for birds were highly concordant with a previous nonstatistical classification, but our method classified a higher......: (1) generalist; (2) habitat A specialist; (3) habitat B specialist; and (4) too rare to classify with confidence. We illustrate our multinomial classification method using two contrasting data sets: (1) bird abundance in woodland and heath habitats in southeastern Australia and (2) tree abundance...... fraction (57.7%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest...

  5. ECLogger: Cross-Project Catch-Block Logging Prediction Using Ensemble of Classifiers

    Directory of Open Access Journals (Sweden)

    Sangeeta Lal

    2017-01-01

    Full Text Available Background: Software developers insert log statements in the source code to record program execution information. However, optimizing the number of log statements in the source code is challenging. Machine learning based within-project logging prediction tools, proposed in previous studies, may not be suitable for new or small software projects. For such software projects, we can use cross-project logging prediction. Aim: The aim of the study presented here is to investigate cross-project logging prediction methods and techniques. Method: The proposed method is ECLogger, which is a novel, ensemble-based, cross-project, catch-block logging prediction model. In the research We use 9 base classifiers were used and combined using ensemble techniques. The performance of ECLogger was evaluated on on three open-source Java projects: Tomcat, CloudStack and Hadoop. Results: ECLogger Bagging, ECLogger AverageVote, and ECLogger MajorityVote show a considerable improvement in the average Logged F-measure (LF on 3, 5, and 4 source -> target project pairs, respectively, compared to the baseline classifiers. ECLogger AverageVote performs best and shows improvements of 3.12% (average LF and 6.08% (average ACC – Accuracy. Conclusion: The classifier based on ensemble techniques, such as bagging, average vote, and majority vote outperforms the baseline classifier. Overall, the ECLogger AverageVote model performs best. The results show that the CloudStack project is more generalizable than the other projects.

  6. A Cross-Classified CFA-MTMM Model for Structurally Different and Nonindependent Interchangeable Methods.

    Science.gov (United States)

    Koch, Tobias; Schultze, Martin; Jeon, Minjeong; Nussbeck, Fridtjof W; Praetorius, Anna-Katharina; Eid, Michael

    2016-01-01

    Multirater (multimethod, multisource) studies are increasingly applied in psychology. Eid and colleagues (2008) proposed a multilevel confirmatory factor model for multitrait-multimethod (MTMM) data combining structurally different and multiple independent interchangeable methods (raters). In many studies, however, different interchangeable raters (e.g., peers, subordinates) are asked to rate different targets (students, supervisors), leading to violations of the independence assumption and to cross-classified data structures. In the present work, we extend the ML-CFA-MTMM model by Eid and colleagues (2008) to cross-classified multirater designs. The new C4 model (Cross-Classified CTC[M-1] Combination of Methods) accounts for nonindependent interchangeable raters and enables researchers to explicitly model the interaction between targets and raters as a latent variable. Using a real data application, it is shown how credibility intervals of model parameters and different variance components can be obtained using Bayesian estimation techniques.

  7. Statistical classifiers on multifractal parameters for optical diagnosis of cervical cancer

    Science.gov (United States)

    Mukhopadhyay, Sabyasachi; Pratiher, Sawon; Kumar, Rajeev; Krishnamoorthy, Vigneshram; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

    2017-06-01

    An augmented set of multifractal parameters with physical interpretations have been proposed to quantify the varying distribution and shape of the multifractal spectrum. The statistical classifier with accuracy of 84.17% validates the adequacy of multi-feature MFDFA characterization of elastic scattering spectroscopy for optical diagnosis of cancer.

  8. Transportation Statistics Annual Report 1997

    Energy Technology Data Exchange (ETDEWEB)

    Fenn, M.

    1997-01-01

    This document is the fourth Transportation Statistics Annual Report (TSAR) prepared by the Bureau of Transportation Statistics (BTS) for the President and Congress. As in previous years, it reports on the state of U.S. transportation system at two levels. First, in Part I, it provides a statistical and interpretive survey of the system—its physical characteristics, its economic attributes, aspects of its use and performance, and the scale and severity of unintended consequences of transportation, such as fatalities and injuries, oil import dependency, and environment impacts. Part I also explores the state of transportation statistics, and new needs of the rapidly changing world of transportation. Second, Part II of the report, as in prior years, explores in detail the performance of the U.S. transportation system from the perspective of desired social outcomes or strategic goals. This year, the performance aspect of transportation chosen for thematic treatment is “Mobility and Access,” which complements past TSAR theme sections on “The Economic Performance of Transportation” (1995) and “Transportation and the Environment” (1996). Mobility and access are at the heart of the transportation system’s performance from the user’s perspective. In what ways and to what extent does the geographic freedom provided by transportation enhance personal fulfillment of the nation’s residents and contribute to economic advancement of people and businesses? This broad question underlies many of the topics examined in Part II: What is the current level of personal mobility in the United States, and how does it vary by sex, age, income level, urban or rural location, and over time? What factors explain variations? Has transportation helped improve people’s access to work, shopping, recreational facilities, and medical services, and in what ways and in what locations? How have barriers, such as age, disabilities, or lack of an automobile, affected these

  9. Transport statistics 1996

    CSIR Research Space (South Africa)

    Shepperson, L

    1997-12-01

    Full Text Available This publication contains transport and related statistics on roads, vehicles, infrastructure, passengers, freight, rail, air, maritime and road traffic, and international comparisons. The information compiled in this publication has been gathered...

  10. Transportation statistics annual report, 2015

    Science.gov (United States)

    2016-01-01

    The Transportation Statistics Annual Report : describes the Nations transportation system, : the systems performance, its contributions to : the economy, and its effects on people and the : environment. This 20th edition of the report is : base...

  11. Transportation statistics annual report, 2013

    Science.gov (United States)

    2014-01-01

    The Transportation Statistics Annual Report : describes the Nations transportation system, : the systems performance, its contributions to : the economy, and its effects on people and the : environment. This 18th edition of the report is : base...

  12. CLASSIFYING BENIGN AND MALIGNANT MASSES USING STATISTICAL MEASURES

    Directory of Open Access Journals (Sweden)

    B. Surendiran

    2011-11-01

    Full Text Available Breast cancer is the primary and most common disease found in women which causes second highest rate of death after lung cancer. The digital mammogram is the X-ray of breast captured for the analysis, interpretation and diagnosis. According to Breast Imaging Reporting and Data System (BIRADS benign and malignant can be differentiated using its shape, size and density, which is how radiologist visualize the mammograms. According to BIRADS mass shape characteristics, benign masses tend to have round, oval, lobular in shape and malignant masses are lobular or irregular in shape. Measuring regular and irregular shapes mathematically is found to be a difficult task, since there is no single measure to differentiate various shapes. In this paper, the malignant and benign masses present in mammogram are classified using Hue, Saturation and Value (HSV weight function based statistical measures. The weight function is robust against noise and captures the degree of gray content of the pixel. The statistical measures use gray weight value instead of gray pixel value to effectively discriminate masses. The 233 mammograms from the Digital Database for Screening Mammography (DDSM benchmark dataset have been used. The PASW data mining modeler has been used for constructing Neural Network for identifying importance of statistical measures. Based on the obtained important statistical measure, the C5.0 tree has been constructed with 60-40 data split. The experimental results are found to be encouraging. Also, the results will agree to the standard specified by the American College of Radiology-BIRADS Systems.

  13. Transportation Statistics Annual Report, 2017

    Science.gov (United States)

    2018-01-01

    The Transportation Statistics Annual Report describes the Nations transportation system, the systems performance, its contributions to the economy, and its effects on people and the environment. This 22nd edition of the report is based on infor...

  14. Border Crossing/Entry Data - Border Crossing/Entry Data Time Series tool

    Data.gov (United States)

    Department of Transportation — The dataset is known as “Border Crossing/Entry Data.” The Bureau of Transportation Statistics (BTS) Border Crossing/Entry Data provides summary statistics to the...

  15. A system for classifying wood-using industries and recording statistics for automatic data processing.

    Science.gov (United States)

    E.W. Fobes; R.W. Rowe

    1968-01-01

    A system for classifying wood-using industries and recording pertinent statistics for automatic data processing is described. Forms and coding instructions for recording data of primary processing plants are included.

  16. A Statistical Classifier to Support Diagnose Meningitis in Less Developed Areas of Brazil.

    Science.gov (United States)

    Lélis, Viviane-Maria; Guzmán, Eduardo; Belmonte, María-Victoria

    2017-08-11

    This paper describes the development of statistical classifiers to help diagnose meningococcal meningitis, i.e. the most sever, infectious and deadliest type of this disease. The goal is to find a mechanism able to determine whether a patient has this type of meningitis from a set of symptoms that can be directly observed in the earliest stages of this pathology. Currently, in Brazil, a country that is heavily affected by meningitis, all suspected cases require immediate hospitalization and the beginning of a treatment with invasive tests and medicines. This procedure, therefore, entails expensive treatments unaffordable in less developed regions. For this purpose, we have gathered together a dataset of 22,602 records of suspected meningitis cases from the Brazilian state of Bahia. Seven classification techniques have been applied from input data of nine symptoms and other information about the patient such as age, sex and the area they live in, and a 10 cross-fold validation has been performed. Results show that the techniques applied are suitable for diagnosing the meningococcal meningitis. Several indexes, such as precision, recall or ROC area, have been computed to show the accuracy of the models. All of them provide good results, but the best corresponds to the J48 classifier with a precision of 0.942 and a ROC area over 0.95. These results indicate that our model can indeed help lead to a non-invasive and early diagnosis of this pathology. This is especially useful in less developed areas, where the epidemiologic risk is usually high and medical expenses, sometimes, unaffordable.

  17. Border Crossing Entry Data

    Data.gov (United States)

    Department of Transportation — The Bureau of Transportation Statistics (BTS) Border Crossing/Entry Data provides summary statistics for inbound crossings at the U.S.-Canadian and the U.S.-Mexican...

  18. Border Crossing/Entry Data

    Data.gov (United States)

    Department of Transportation — The dataset is known as “Border Crossing/Entry Data.” The Bureau of Transportation Statistics (BTS) Border Crossing/Entry Data provides summary statistics to the...

  19. Statistical data fusion for cross-tabulation

    NARCIS (Netherlands)

    Kamakura, W.A.; Wedel, M.

    The authors address the situation in which a researcher wants to cross-tabulate two sets of discrete variables collected in independent samples, but a subset of the variables is common to both samples. The authors propose a statistical data-fusion model that allows for statistical tests of

  20. A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition

    Directory of Open Access Journals (Sweden)

    Yago Saez

    2016-12-01

    Full Text Available Physical activity is widely known to be one of the key elements of a healthy life. The many benefits of physical activity described in the medical literature include weight loss and reductions in the risk factors for chronic diseases. With the recent advances in wearable devices, such as smartwatches or physical activity wristbands, motion tracking sensors are becoming pervasive, which has led to an impressive growth in the amount of physical activity data available and an increasing interest in recognizing which specific activity a user is performing. Moreover, big data and machine learning are now cross-fertilizing each other in an approach called “deep learning”, which consists of massive artificial neural networks able to detect complicated patterns from enormous amounts of input data to learn classification models. This work compares various state-of-the-art classification techniques for automatic cross-person activity recognition under different scenarios that vary widely in how much information is available for analysis. We have incorporated deep learning by using Google’s TensorFlow framework. The data used in this study were acquired from PAMAP2 (Physical Activity Monitoring in the Ageing Population, a publicly available dataset containing physical activity data. To perform cross-person prediction, we used the leave-one-subject-out (LOSO cross-validation technique. When working with large training sets, the best classifiers obtain very high average accuracies (e.g., 96% using extra randomized trees. However, when the data volume is drastically reduced (where available data are only 0.001% of the continuous data, deep neural networks performed the best, achieving 60% in overall prediction accuracy. We found that even when working with only approximately 22.67% of the full dataset, we can statistically obtain the same results as when working with the full dataset. This finding enables the design of more energy-efficient devices and

  1. A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition.

    Science.gov (United States)

    Saez, Yago; Baldominos, Alejandro; Isasi, Pedro

    2016-12-30

    Physical activity is widely known to be one of the key elements of a healthy life. The many benefits of physical activity described in the medical literature include weight loss and reductions in the risk factors for chronic diseases. With the recent advances in wearable devices, such as smartwatches or physical activity wristbands, motion tracking sensors are becoming pervasive, which has led to an impressive growth in the amount of physical activity data available and an increasing interest in recognizing which specific activity a user is performing. Moreover, big data and machine learning are now cross-fertilizing each other in an approach called "deep learning", which consists of massive artificial neural networks able to detect complicated patterns from enormous amounts of input data to learn classification models. This work compares various state-of-the-art classification techniques for automatic cross-person activity recognition under different scenarios that vary widely in how much information is available for analysis. We have incorporated deep learning by using Google's TensorFlow framework. The data used in this study were acquired from PAMAP2 (Physical Activity Monitoring in the Ageing Population), a publicly available dataset containing physical activity data. To perform cross-person prediction, we used the leave-one-subject-out (LOSO) cross-validation technique. When working with large training sets, the best classifiers obtain very high average accuracies (e.g., 96% using extra randomized trees). However, when the data volume is drastically reduced (where available data are only 0.001% of the continuous data), deep neural networks performed the best, achieving 60% in overall prediction accuracy. We found that even when working with only approximately 22.67% of the full dataset, we can statistically obtain the same results as when working with the full dataset. This finding enables the design of more energy-efficient devices and facilitates cold

  2. SpectraClassifier 1.0: a user friendly, automated MRS-based classifier-development system

    Directory of Open Access Journals (Sweden)

    Julià-Sapé Margarida

    2010-02-01

    Full Text Available Abstract Background SpectraClassifier (SC is a Java solution for designing and implementing Magnetic Resonance Spectroscopy (MRS-based classifiers. The main goal of SC is to allow users with minimum background knowledge of multivariate statistics to perform a fully automated pattern recognition analysis. SC incorporates feature selection (greedy stepwise approach, either forward or backward, and feature extraction (PCA. Fisher Linear Discriminant Analysis is the method of choice for classification. Classifier evaluation is performed through various methods: display of the confusion matrix of the training and testing datasets; K-fold cross-validation, leave-one-out and bootstrapping as well as Receiver Operating Characteristic (ROC curves. Results SC is composed of the following modules: Classifier design, Data exploration, Data visualisation, Classifier evaluation, Reports, and Classifier history. It is able to read low resolution in-vivo MRS (single-voxel and multi-voxel and high resolution tissue MRS (HRMAS, processed with existing tools (jMRUI, INTERPRET, 3DiCSI or TopSpin. In addition, to facilitate exchanging data between applications, a standard format capable of storing all the information needed for a dataset was developed. Each functionality of SC has been specifically validated with real data with the purpose of bug-testing and methods validation. Data from the INTERPRET project was used. Conclusions SC is a user-friendly software designed to fulfil the needs of potential users in the MRS community. It accepts all kinds of pre-processed MRS data types and classifies them semi-automatically, allowing spectroscopists to concentrate on interpretation of results with the use of its visualisation tools.

  3. Connection between recurrence time statistics and anomalous transport

    International Nuclear Information System (INIS)

    Zaslavsky, G.M.; Tippett, M.K.

    1991-01-01

    For a model stationary flow with hexagonal symmetry, the recurrence time statistics are studied. The model has been shown to have a sharp transition from normal to anomalous transport. Here it is shown that this transition is accompanied by a correspondent change of the recurrence time statistics from normal to anomalous. The latter one displays the existence of a power tail. Recurrence time statistics provide a local measurement of anomalous transport that is of practical interest

  4. Statistical tests for power-law cross-correlated processes

    Science.gov (United States)

    Podobnik, Boris; Jiang, Zhi-Qiang; Zhou, Wei-Xing; Stanley, H. Eugene

    2011-12-01

    For stationary time series, the cross-covariance and the cross-correlation as functions of time lag n serve to quantify the similarity of two time series. The latter measure is also used to assess whether the cross-correlations are statistically significant. For nonstationary time series, the analogous measures are detrended cross-correlations analysis (DCCA) and the recently proposed detrended cross-correlation coefficient, ρDCCA(T,n), where T is the total length of the time series and n the window size. For ρDCCA(T,n), we numerically calculated the Cauchy inequality -1≤ρDCCA(T,n)≤1. Here we derive -1≤ρDCCA(T,n)≤1 for a standard variance-covariance approach and for a detrending approach. For overlapping windows, we find the range of ρDCCA within which the cross-correlations become statistically significant. For overlapping windows we numerically determine—and for nonoverlapping windows we derive—that the standard deviation of ρDCCA(T,n) tends with increasing T to 1/T. Using ρDCCA(T,n) we show that the Chinese financial market's tendency to follow the U.S. market is extremely weak. We also propose an additional statistical test that can be used to quantify the existence of cross-correlations between two power-law correlated time series.

  5. A Preliminary Study on Sensitivity and Uncertainty Analysis with Statistic Method: Uncertainty Analysis with Cross Section Sampling from Lognormal Distribution

    Energy Technology Data Exchange (ETDEWEB)

    Song, Myung Sub; Kim, Song Hyun; Kim, Jong Kyung [Hanyang Univ., Seoul (Korea, Republic of); Noh, Jae Man [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-10-15

    The uncertainty evaluation with statistical method is performed by repetition of transport calculation with sampling the directly perturbed nuclear data. Hence, the reliable uncertainty result can be obtained by analyzing the results of the numerous transport calculations. One of the problems in the uncertainty analysis with the statistical approach is known as that the cross section sampling from the normal (Gaussian) distribution with relatively large standard deviation leads to the sampling error of the cross sections such as the sampling of the negative cross section. Some collection methods are noted; however, the methods can distort the distribution of the sampled cross sections. In this study, a sampling method of the nuclear data is proposed by using lognormal distribution. After that, the criticality calculations with sampled nuclear data are performed and the results are compared with that from the normal distribution which is conventionally used in the previous studies. In this study, the statistical sampling method of the cross section with the lognormal distribution was proposed to increase the sampling accuracy without negative sampling error. Also, a stochastic cross section sampling and writing program was developed. For the sensitivity and uncertainty analysis, the cross section sampling was pursued with the normal and lognormal distribution. The uncertainties, which are caused by covariance of (n,.) cross sections, were evaluated by solving GODIVA problem. The results show that the sampling method with lognormal distribution can efficiently solve the negative sampling problem referred in the previous studies. It is expected that this study will contribute to increase the accuracy of the sampling-based uncertainty analysis.

  6. A Preliminary Study on Sensitivity and Uncertainty Analysis with Statistic Method: Uncertainty Analysis with Cross Section Sampling from Lognormal Distribution

    International Nuclear Information System (INIS)

    Song, Myung Sub; Kim, Song Hyun; Kim, Jong Kyung; Noh, Jae Man

    2013-01-01

    The uncertainty evaluation with statistical method is performed by repetition of transport calculation with sampling the directly perturbed nuclear data. Hence, the reliable uncertainty result can be obtained by analyzing the results of the numerous transport calculations. One of the problems in the uncertainty analysis with the statistical approach is known as that the cross section sampling from the normal (Gaussian) distribution with relatively large standard deviation leads to the sampling error of the cross sections such as the sampling of the negative cross section. Some collection methods are noted; however, the methods can distort the distribution of the sampled cross sections. In this study, a sampling method of the nuclear data is proposed by using lognormal distribution. After that, the criticality calculations with sampled nuclear data are performed and the results are compared with that from the normal distribution which is conventionally used in the previous studies. In this study, the statistical sampling method of the cross section with the lognormal distribution was proposed to increase the sampling accuracy without negative sampling error. Also, a stochastic cross section sampling and writing program was developed. For the sensitivity and uncertainty analysis, the cross section sampling was pursued with the normal and lognormal distribution. The uncertainties, which are caused by covariance of (n,.) cross sections, were evaluated by solving GODIVA problem. The results show that the sampling method with lognormal distribution can efficiently solve the negative sampling problem referred in the previous studies. It is expected that this study will contribute to increase the accuracy of the sampling-based uncertainty analysis

  7. Asymptotic limits of a statistical transport description

    International Nuclear Information System (INIS)

    Malvagi, F.; Levermore, C.D.; Pomraning, G.C.; Department of Mathematics, University of Arizona, Tucson, AZ 85721)

    1989-01-01

    We consider three different asymptotic limits of a model describing linear particle transport in a stochastic medium consisting of two randomly mixed immiscible fluids. These three limits are: (1) the fluid packets are small compared to the particle mean free path in the packet; (2) a small amount of large cross section fluid is admixed with a large amount of small cross section fluid; and (3) the angular dependence of the intensity (angular flux) is nearly isotropic. The first two limits reduce the underlying model, which consists of two coupled transport equations, to a single transport equation of the usual form. The third limit yields a two-equation diffusion approximation, and a boundary layer analysis gives boundary conditions for these two coupled diffusion equations

  8. 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

  9. Border Crossing/Entry Data - Boarder Crossing

    Data.gov (United States)

    Department of Transportation — Border Crossing/Entry Data provides summary statistics for incoming crossings at the U.S.-Canadian and the U.S.-Mexican border at the port level. Data are available...

  10. Parent Involvement and Science Achievement: A Cross-Classified Multilevel Latent Growth Curve Analysis

    Science.gov (United States)

    Johnson, Ursula Y.; Hull, Darrell M.

    2014-01-01

    The authors examined science achievement growth at Grades 3, 5, and 8 and parent school involvement at the same time points using the Early Childhood Longitudinal Study-Kindergarten Class of 1998-1999. Data were analyzed using cross-classified multilevel latent growth curve modeling with time invariant and varying covariates. School-based…

  11. Crossing statistics of laser light scattered through a nanofluid.

    Science.gov (United States)

    Arshadi Pirlar, M; Movahed, S M S; Razzaghi, D; Karimzadeh, R

    2017-09-01

    In this paper, we investigate the crossing statistics of speckle patterns formed in the Fresnel diffraction region by a laser beam scattering through a nanofluid. We extend zero-crossing statistics to assess the dynamical properties of the nanofluid. According to the joint probability density function of laser beam fluctuation and its time derivative, the theoretical frameworks for Gaussian and non-Gaussian regimes are revisited. We count the number of crossings not only at zero level but also for all available thresholds to determine the average speed of moving particles. Using a probabilistic framework in determining crossing statistics, a priori Gaussianity is not essentially considered; therefore, even in the presence of deviation from Gaussian fluctuation, this modified approach is capable of computing relevant quantities, such as mean value of speed, more precisely. Generalized total crossing, which represents the weighted summation of crossings for all thresholds to quantify small deviation from Gaussian statistics, is introduced. This criterion can also manipulate the contribution of noises and trends to infer reliable physical quantities. The characteristic time scale for having successive crossings at a given threshold is defined. In our experimental setup, we find that increasing sample temperature leads to more consistency between Gaussian and perturbative non-Gaussian predictions. The maximum number of crossings does not necessarily occur at mean level, indicating that we should take into account other levels in addition to zero level to achieve more accurate assessments.

  12. 75 FR 24773 - Research and Innovative Technology Administration Advisory Council on Transportation Statistics...

    Science.gov (United States)

    2010-05-05

    ... DEPARTMENT OF TRANSPORTATION Bureau of Transportation Statistics Research and Innovative Technology Administration Advisory Council on Transportation Statistics; Notice of Meeting AGENCY: Research... Transportation, Research and Innovative Technology Administration, Bureau of Transportation Statistics, Attention...

  13. Bureau of Transportation Statistics Fellowship: Mid-Year Review

    Science.gov (United States)

    2018-01-01

    The Bureau of Transportation Statistics (BTS) Fellowships are post-graduate research and developmental opportunities at the U.S. Department of Transportation in Washington, DC. The BTS Fellowship program is in its first rotation with five Fel...

  14. Transport cross section for small-angle scattering

    International Nuclear Information System (INIS)

    D'yakonov, M.I.; Khaetskii, A.V.

    1991-01-01

    Classical mechanics is valid for describing potential scattering under the conditions (1) λ much-lt α and (2) U much-gt ℎυ/α, where λ is the de Broglie wavelength, α is the characteristic size of the scatterer, U is the characteristic value of the potential energy, and υ is the velocity of the scattered particle. The second of these conditions means that the typical value of the classical scattering angle is far larger than the diffraction angle λ/α. In this paper the authors show that this second condition need not hold in a derivation of the transport cross section. In other words, provided that the condition λ much-lt α holds, it is always possible to calculate the transport cross section from the expressions of classical mechanics, even in the region U approx-lt ℎυ/α, where the scattering is diffractive,and the differential cross section is greatly different from the classical cross section. The transport cross section is found from the classical expression even in the anticlassical case U much-lt ℎυ/α, where the Born approximation can be used

  15. Cross-Domain Statistical-Sequential Dependencies Are Difficult To Learn

    Directory of Open Access Journals (Sweden)

    Anne McClure Walk

    2016-02-01

    Full Text Available Recent studies have demonstrated participants’ ability to learn cross-modal associations during statistical learning tasks. However, these studies are all similar in that the cross-modal associations to be learned occur simultaneously, rather than sequentially. In addition, the majority of these studies focused on learning across sensory modalities but not across perceptual categories. To test both cross-modal and cross-categorical learning of sequential dependencies, we used an artificial grammar learning task consisting of a serial stream of auditory and/or visual stimuli containing both within- and cross-domain dependencies. Experiment 1 examined within-modal and cross-modal learning across two sensory modalities (audition and vision. Experiment 2 investigated within-categorical and cross-categorical learning across two perceptual categories within the same sensory modality (e.g. shape and color; tones and non-words. Our results indicated that individuals demonstrated learning of the within-modal and within-categorical but not the cross-modal or cross-categorical dependencies. These results stand in contrast to the previous demonstrations of cross-modal statistical learning, and highlight the presence of modality constraints that limit the effectiveness of learning in a multimodal environment.

  16. Classifying MCI Subtypes in Community-Dwelling Elderly Using Cross-Sectional and Longitudinal MRI-Based Biomarkers

    Directory of Open Access Journals (Sweden)

    Hao Guan

    2017-09-01

    Full Text Available Amnestic MCI (aMCI and non-amnestic MCI (naMCI are considered to differ in etiology and outcome. Accurately classifying MCI into meaningful subtypes would enable early intervention with targeted treatment. In this study, we employed structural magnetic resonance imaging (MRI for MCI subtype classification. This was carried out in a sample of 184 community-dwelling individuals (aged 73–85 years. Cortical surface based measurements were computed from longitudinal and cross-sectional scans. By introducing a feature selection algorithm, we identified a set of discriminative features, and further investigated the temporal patterns of these features. A voting classifier was trained and evaluated via 10 iterations of cross-validation. The best classification accuracies achieved were: 77% (naMCI vs. aMCI, 81% (aMCI vs. cognitively normal (CN and 70% (naMCI vs. CN. The best results for differentiating aMCI from naMCI were achieved with baseline features. Hippocampus, amygdala and frontal pole were found to be most discriminative for classifying MCI subtypes. Additionally, we observed the dynamics of classification of several MRI biomarkers. Learning the dynamics of atrophy may aid in the development of better biomarkers, as it may track the progression of cognitive impairment.

  17. A Novel Approach for Multi Class Fault Diagnosis in Induction Machine Based on Statistical Time Features and Random Forest Classifier

    Science.gov (United States)

    Sonje, M. Deepak; Kundu, P.; Chowdhury, A.

    2017-08-01

    Fault diagnosis and detection is the important area in health monitoring of electrical machines. This paper proposes the recently developed machine learning classifier for multi class fault diagnosis in induction machine. The classification is based on random forest (RF) algorithm. Initially, stator currents are acquired from the induction machine under various conditions. After preprocessing the currents, fourteen statistical time features are estimated for each phase of the current. These parameters are considered as inputs to the classifier. The main scope of the paper is to evaluate effectiveness of RF classifier for individual and mixed fault diagnosis in induction machine. The stator, rotor and mixed faults (stator and rotor faults) are classified using the proposed classifier. The obtained performance measures are compared with the multilayer perceptron neural network (MLPNN) classifier. The results show the much better performance measures and more accurate than MLPNN classifier. For demonstration of planned fault diagnosis algorithm, experimentally obtained results are considered to build the classifier more practical.

  18. Classifying Coding DNA with Nucleotide Statistics

    Directory of Open Access Journals (Sweden)

    Nicolas Carels

    2009-10-01

    Full Text Available In this report, we compared the success rate of classification of coding sequences (CDS vs. introns by Codon Structure Factor (CSF and by a method that we called Universal Feature Method (UFM. UFM is based on the scoring of purine bias (Rrr and stop codon frequency. We show that the success rate of CDS/intron classification by UFM is higher than by CSF. UFM classifies ORFs as coding or non-coding through a score based on (i the stop codon distribution, (ii the product of purine probabilities in the three positions of nucleotide triplets, (iii the product of Cytosine (C, Guanine (G, and Adenine (A probabilities in the 1st, 2nd, and 3rd positions of triplets, respectively, (iv the probabilities of G in 1st and 2nd position of triplets and (v the distance of their GC3 vs. GC2 levels to the regression line of the universal correlation. More than 80% of CDSs (true positives of Homo sapiens (>250 bp, Drosophila melanogaster (>250 bp and Arabidopsis thaliana (>200 bp are successfully classified with a false positive rate lower or equal to 5%. The method releases coding sequences in their coding strand and coding frame, which allows their automatic translation into protein sequences with 95% confidence. The method is a natural consequence of the compositional bias of nucleotides in coding sequences.

  19. A comprehensive statistical classifier of foci in the cell transformation assay for carcinogenicity testing.

    Science.gov (United States)

    Callegaro, Giulia; Malkoc, Kasja; Corvi, Raffaella; Urani, Chiara; Stefanini, Federico M

    2017-12-01

    The identification of the carcinogenic risk of chemicals is currently mainly based on animal studies. The in vitro Cell Transformation Assays (CTAs) are a promising alternative to be considered in an integrated approach. CTAs measure the induction of foci of transformed cells. CTAs model key stages of the in vivo neoplastic process and are able to detect both genotoxic and some non-genotoxic compounds, being the only in vitro method able to deal with the latter. Despite their favorable features, CTAs can be further improved, especially reducing the possible subjectivity arising from the last phase of the protocol, namely visual scoring of foci using coded morphological features. By taking advantage of digital image analysis, the aim of our work is to translate morphological features into statistical descriptors of foci images, and to use them to mimic the classification performances of the visual scorer to discriminate between transformed and non-transformed foci. Here we present a classifier based on five descriptors trained on a dataset of 1364 foci, obtained with different compounds and concentrations. Our classifier showed accuracy, sensitivity and specificity equal to 0.77 and an area under the curve (AUC) of 0.84. The presented classifier outperforms a previously published model. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. 77 FR 2345 - Advisory Council on Transportation Statistics; Request for Nominations

    Science.gov (United States)

    2012-01-17

    ... and Innovative Technology Administration (RITA), Bureau of Transportation Statistics (BTS), DOT... BTS solicits nominations for interested persons to serve on the ACTS. The ACTS is composed of BTS... transportation statistics and analyses collected, supported, or disseminated by the BTS and DOT. DATES...

  1. Comparison of the Effects of Cross-validation Methods on Determining Performances of Classifiers Used in Diagnosing Congestive Heart Failure

    Directory of Open Access Journals (Sweden)

    Isler Yalcin

    2015-08-01

    Full Text Available Congestive heart failure (CHF occurs when the heart is unable to provide sufficient pump action to maintain blood flow to meet the needs of the body. Early diagnosis is important since the mortality rate of the patients with CHF is very high. There are different validation methods to measure performances of classifier algorithms designed for this purpose. In this study, k-fold and leave-one-out cross-validation methods were tested for performance measures of five distinct classifiers in the diagnosis of the patients with CHF. Each algorithm was run 100 times and the average and the standard deviation of classifier performances were recorded. As a result, it was observed that average performance was enhanced and the variability of performances was decreased when the number of data sections used in the cross-validation method was increased.

  2. Adapting transport modes to supply chains classified by the uncertainty supply chain model: A case study at Manaus Industrial Pole

    Directory of Open Access Journals (Sweden)

    Fabiana Lucena Oliveira

    2017-01-01

    Full Text Available This paper discusses transport modes supporting Uncertainty Supply Chain Model (USCM in the case of Manaus Industrial Pole (PIM, an industrial cluster in the Brazilian Amazon that hosts six hundred factories with diverse logistics and supply chain managerial strategies. USCM (Lee, 2002; Fisher, 1997develops a dot matrix classification of the supply chains considering several attributes (e.g., agility, cost, security, responsiveness and argues that emergent economies industrial clusters, in the effort to keep attractiveness for technological frontier firms, need to adapt supply chain strategies according to USCM attributes. The paper takes a further step, discussing which transport modes are suitable to each supply chain classified at the USCM in PIM´s case. The research´s methods covered the use of PIM´s statistical official database (secondary data, interviews with the main logistical services providers of PIM and phone survey with a sample of firms (primary data. Findings confirm the theoretical argument that different supply chains will demand different transport modes running at the same time in the same industrial cluster (Oliveira, 2009. In the case of PIM, this implies investments on port and airport infrastructure and a strategic focus on air transport mode, due to (1 short life cycle of products, (2 distance from suppliers, (3 quick response to demand and (4 the fact that even PIM´s standard products use, in average, forty per cent of air transport at inbound logistics.

  3. Active transportation and bullying in Canadian schoolchildren: a cross-sectional study.

    Science.gov (United States)

    Cozma, Ioana; Kukaswadia, Atif; Janssen, Ian; Craig, Wendy; Pickett, William

    2015-02-07

    Bullying is a recognized social problem within child populations. Engagement in childhood bullying often occurs in settings that are away from adult supervision, such as en route to and from school. Bullying episodes may also have a negative impact on school childrens' decisions to engage in active transportation. Using a cross-sectional design, we analyzed reports from the 2009/10 cycle of the Canadian Health Behaviour in School-Aged Children (HBSC) study. Records from this general health survey were obtained for 3,997 urban students in grades 6-10 who lived in close proximity of their school and were hence ineligible for school bussing. Students who indicated walking or bicycling to school were classified as engaged in active transportation. Victims and perpetrators of bullying were defined using standard measures and a frequency cut-off of at least 2-3 times per month. Analyses focused on relations between bullying and active transportation, as well as barriers to active transportation as perceived by young people. 27% of young people indicated being victimized, and 12% indicated that they engaged in bullying. Girls were more likely to be victimized than boys, and younger students were more likely to be victimized than older students. Engagement in active transportation was reported by 63% of respondents, of these, 68% indicated that worrying about bullying on the way to school was an impediment to such transportation methods. Victimization by bullying (adjusted OR = 1.26, 95% CI: 1.00 - 1.59) was reported more frequently by children who used active transportation. Health promotion efforts to promote engagement in active transportation of students to school have obvious value. The potential for modest increases in exposure to bullying should be considered in the planning of such initiatives.

  4. GREY STATISTICS METHOD OF TECHNOLOGY SELECTION FOR ADVANCED PUBLIC TRANSPORTATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    Chien Hung WEI

    2003-01-01

    Full Text Available Taiwan is involved in intelligent transportation systems planning, and is now selecting its prior focus areas for investment and development. The high social and economic impact associated with which intelligent transportation systems technology are chosen explains the efforts of various electronics and transportation corporations for developing intelligent transportation systems technology to expand their business opportunities. However, there has been no detailed research conducted with regard to selecting technology for advanced public transportation systems in Taiwan. Thus, the present paper demonstrates a grey statistics method integrated with a scenario method for solving the problem of selecting advanced public transportation systems technology for Taiwan. A comprehensive questionnaire survey was conducted to demonstrate the effectiveness of the grey statistics method. The proposed approach indicated that contactless smart card technology is the appropriate technology for Taiwan to develop in the near future. The significance of our research results implies that the grey statistics method is an effective method for selecting advanced public transportation systems technologies. We feel our information will be beneficial to the private sector for developing an appropriate intelligent transportation systems technology strategy.

  5. Cross-Sectional Transport Imaging in a Multijunction Solar Cell

    Energy Technology Data Exchange (ETDEWEB)

    Haegel, Nancy M.; Ke, Chi-Wen; Taha, Hesham; Guthrey, Harvey; Fetzer, C. M.; King, Richard

    2015-06-14

    Combining highly localized electron-beam excitation at a point with the spatial resolution capability of optical near-field imaging, we have imaged carrier transport in a cross-sectioned multijunction (GaInP/GaInAs/Ge) solar cell. We image energy transport associated with carrier diffusion throughout the full width of the middle (GaInAs) cell and luminescent coupling from point excitation in the top cell GaInP to the middle cell. Supporting cathodoluminescence and near-field photoluminescence measurements demonstrate excitation-dependent Fermi level splitting effects that influence cross-sectioned spectroscopy results as well as transport limitations on the spatial resolution of cross-sectional measurements.

  6. Nonequilibrium statistical operator in hot-electron transport theory

    International Nuclear Information System (INIS)

    Xing, D.Y.; Liu, M.

    1991-09-01

    The Nonequilibrium Statistical Operator method developed by Zubarev is generalized and applied to the study of hot-electron transport in semiconductors. The steady-state balance equations for momentum and energy are derived to the lowest order in the electron-lattice coupling. We show that the derived balance equations are exactly the same as those obtained by Lei and Ting. This equivalence stems from the fact that to the linear order in the electron-lattice coupling, two statistical density matrices have identical effect when they are used to calculate the average value of a dynamical operator. The application to the steady-state and transient hot-electron transport in multivalley semiconductors is also discussed. (author). 28 refs, 1 fig

  7. Percolation, statistical topography, and transport in random media

    International Nuclear Information System (INIS)

    Isichenko, M.B.

    1992-01-01

    A review of classical percolation theory is presented, with an emphasis on novel applications to statistical topography, turbulent diffusion, and heterogeneous media. Statistical topography involves the geometrical properties of the isosets (contour lines or surfaces) of a random potential ψ(x). For rapidly decaying correlations of ψ, the isopotentials fall into the same universality class as the perimeters of percolation clusters. The topography of long-range correlated potentials involves many length scales and is associated either with the correlated percolation problem or with Mandelbrot's fractional Brownian reliefs. In all cases, the concept of fractal dimension is particularly fruitful in characterizing the geometry of random fields. The physical applications of statistical topography include diffusion in random velocity fields, heat and particle transport in turbulent plasmas, quantum Hall effect, magnetoresistance in inhomogeneous conductors with the classical Hall effect, and many others where random isopotentials are relevant. A geometrical approach to studying transport in random media, which captures essential qualitative features of the described phenomena, is advocated

  8. 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.

  9. Analysis of transaction records of live freshwater finfish in China: A case study of customers’ claims of fish mortality using cross-classified modeling

    Directory of Open Access Journals (Sweden)

    Beibei Jia

    2016-11-01

    Full Text Available Customers of finfish in China place a high priority on healthy fish at the point of sale but factors that increase the risk of morbidity and mortality during transportation have had limited study. We designed a case study to investigate variation of mortalities claimed by customers receiving fish at markets with above-normal mortalities. We used daily transaction records of the 3 species transported from a company located in Guangdong province to its destination markets in Beijing between April and July 2013: largemouth bass (Micropterus salmoides, Chinese perch (Siniperca chuatsi, and longsnout catfish (Leiocassis longirostris. We quantified magnitudes and patterns of weekly mortalities of transported fish, and used cross-classified random-effect modeling to explore variation and clustering of fish mortality claims at wholesale destinations. Random effects for customer and market-week were interpreted by variance partition coefficients (VPC and intraclass correlation coefficients (ICC. A significant fixed effect of market was found in the model of mortality claims for longsnout catfish (p < 0.05, and changing patterns of VPC and ICC suggested that customers ordering longsnout catfish had more variation in claims than those ordering the other 2 species. Our findings indicate a need for better customer communication for live fish transportation and a need for detailed measurements during the process including physiological factors and transportation conditions, to better understand their role in reported mortalities.

  10. Two decades of change in transportation reflections from transportation statistics annual reports 1994–2014.

    Science.gov (United States)

    2015-01-01

    The Bureau of Transportation Statistics (BTS) provides information to support understanding and decision-making related to the transportation system, including the size and extent of the system, how it is used, how well it works, and its contribution...

  11. General renormalized statistical approach with finite cross-field correlations

    International Nuclear Information System (INIS)

    Vakulenko, M.O.

    1992-01-01

    The renormalized statistical approach is proposed, accounting for finite correlations of potential and magnetic fluctuations. It may be used for analysis of a wide class of nonlinear model equations describing the cross-correlated plasma states. The influence of a cross spectrum on stationary potential and magnetic ones is investigated. 10 refs. (author)

  12. Numerical computation of discrete differential scattering cross sections for Monte Carlo charged particle transport

    International Nuclear Information System (INIS)

    Walsh, Jonathan A.; Palmer, Todd S.; Urbatsch, Todd J.

    2015-01-01

    Highlights: • Generation of discrete differential scattering angle and energy loss cross sections. • Gauss–Radau quadrature utilizing numerically computed cross section moments. • Development of a charged particle transport capability in the Milagro IMC code. • Integration of cross section generation and charged particle transport capabilities. - Abstract: We investigate a method for numerically generating discrete scattering cross sections for use in charged particle transport simulations. We describe the cross section generation procedure and compare it to existing methods used to obtain discrete cross sections. The numerical approach presented here is generalized to allow greater flexibility in choosing a cross section model from which to derive discrete values. Cross section data computed with this method compare favorably with discrete data generated with an existing method. Additionally, a charged particle transport capability is demonstrated in the time-dependent Implicit Monte Carlo radiative transfer code, Milagro. We verify the implementation of charged particle transport in Milagro with analytic test problems and we compare calculated electron depth–dose profiles with another particle transport code that has a validated electron transport capability. Finally, we investigate the integration of the new discrete cross section generation method with the charged particle transport capability in Milagro.

  13. Rich in vitamin C or just a convenient snack? Multiple-category reasoning with cross-classified foods.

    Science.gov (United States)

    Hayes, Brett K; Kurniawan, Hendy; Newell, Ben R

    2011-01-01

    Two studies examined multiple category reasoning in property induction with cross-classified foods. Pilot tests identified foods that were more typical of a taxonomic category (e.g., "fruit"; termed 'taxonomic primary') or a script based category (e.g., "snack foods"; termed 'script primary'). They also confirmed that taxonomic categories were perceived as more coherent than script categories. In Experiment 1 participants completed an induction task in which information from multiple categories could be searched and combined to generate a property prediction about a target food. Multiple categories were more often consulted and used in prediction for script primary than for taxonomic primary foods. Experiment 2 replicated this finding across a range of property types but found that multiple category reasoning was reduced in the presence of a concurrent cognitive load. Property type affected which categories were consulted first and how information from multiple categories was weighted. The results show that multiple categories are more likely to be used for property predictions about cross-classified objects when an object is primarily associated with a category that has low coherence.

  14. Statistical analysis of anomalous transport in resistive interchange turbulence

    International Nuclear Information System (INIS)

    Sugama, Hideo; Wakatani, Masahiro.

    1992-01-01

    A new anomalous transport model for resistive interchange turbulence is derived from statistical analysis applying two-scale direct-interaction approximation to resistive magnetohydrodynamic equations with a gravity term. Our model is similar to the K-ε model for eddy viscosity of turbulent shear flows in that anomalous transport coefficients are expressed in terms of by the turbulent kinetic energy K and its dissipation rate ε while K and ε are determined by transport equations. This anomalous transport model can describe some nonlocal effects such as those from boundary conditions which cannot be treated by conventional models based on the transport coefficients represented by locally determined plasma parameters. (author)

  15. Evaluation of railway transportation efficiency based on super-cross efficiency

    Science.gov (United States)

    Kuang, Xiuyuan

    2018-01-01

    The efficiency of railway transportation is an important index. It can measure the development of railway transportation enterprises, and the efficiency of railway transportation has become a hot issue in the study of railway development. Data envelopment analysis (DEA) has been widely applied to railway efficiency analysis. In this paper, BBC model and super-cross efficiency model are constructed by using DEA theory, taking the 18 Railway Bureau as the research object, with the mileage, the number of employees, locomotive number, average daily loading number as input indicators, the passenger turnover, freight turnover and transport income as output indicators, then calculated and evaluated comprehensive efficiency, pure technical efficiency and scale efficiency. We get that the super-cross efficiency is more in line with the actual situation. Getting the super-cross efficiency is more in line with the actual situation.

  16. Statistical theory of resistive drift-wave turbulence and transport

    International Nuclear Information System (INIS)

    Hu, G.; Krommes, J.A.; Bowman, J.C.

    1997-01-01

    Resistive drift-wave turbulence in a slab geometry is studied by statistical closure methods and direct numerical simulations. The two-field Hasegawa endash Wakatani (HW) fluid model, which evolves the electrostatic potential and plasma density self-consistently, is a paradigm for understanding the generic nonlinear behavior of multiple-field plasma turbulence. A gyrokinetic derivation of the HW model is sketched. The recently developed Realizable Markovian Closure (RMC) is applied to the HW model; spectral properties, nonlinear energy transfers, and turbulent transport calculations are discussed. The closure results are also compared to direct numerical simulation results; excellent agreement is found. The transport scaling with the adiabaticity parameter, which measures the strength of the parallel electron resistivity, is analytically derived and understood through weak- and strong-turbulence analyses. No evidence is found to support previous suggestions that coherent structures cause a large depression of saturated transport from its quasilinear value in the hydrodynamic regime of the HW model. Instead, the depression of transport is well explained by the spectral balance equation of the (second-order) statistical closure when account is taken of incoherent noise. copyright 1997 American Institute of Physics

  17. Discussion of electron cross sections for transport calculations

    International Nuclear Information System (INIS)

    Berger, M.J.

    1983-01-01

    This paper deals with selected aspects of the cross sections needed as input for transport calculations and for the modeling of radiation effects in biological materials. Attention is centered mainly on the cross sections for inelastic interactions between electrons and water molecules and the use of these cross sections for the calculation of energy degradation spectra and of ionization and excitation yields. 40 references, 3 figures, 1 table

  18. Evaluation of Polarimetric SAR Decomposition for Classifying Wetland Vegetation Types

    Directory of Open Access Journals (Sweden)

    Sang-Hoon Hong

    2015-07-01

    Full Text Available The Florida Everglades is the largest subtropical wetland system in the United States and, as with subtropical and tropical wetlands elsewhere, has been threatened by severe environmental stresses. It is very important to monitor such wetlands to inform management on the status of these fragile ecosystems. This study aims to examine the applicability of TerraSAR-X quadruple polarimetric (quad-pol synthetic aperture radar (PolSAR data for classifying wetland vegetation in the Everglades. We processed quad-pol data using the Hong & Wdowinski four-component decomposition, which accounts for double bounce scattering in the cross-polarization signal. The calculated decomposition images consist of four scattering mechanisms (single, co- and cross-pol double, and volume scattering. We applied an object-oriented image analysis approach to classify vegetation types with the decomposition results. We also used a high-resolution multispectral optical RapidEye image to compare statistics and classification results with Synthetic Aperture Radar (SAR observations. The calculated classification accuracy was higher than 85%, suggesting that the TerraSAR-X quad-pol SAR signal had a high potential for distinguishing different vegetation types. Scattering components from SAR acquisition were particularly advantageous for classifying mangroves along tidal channels. We conclude that the typical scattering behaviors from model-based decomposition are useful for discriminating among different wetland vegetation types.

  19. A Supervised Multiclass Classifier for an Autocoding System

    Directory of Open Access Journals (Sweden)

    Yukako Toko

    2017-11-01

    Full Text Available Classification is often required in various contexts, including in the field of official statistics. In the previous study, we have developed a multiclass classifier that can classify short text descriptions with high accuracy. The algorithm borrows the concept of the naïve Bayes classifier and is so simple that its structure is easily understandable. The proposed classifier has the following two advantages. First, the processing times for both learning and classifying are extremely practical. Second, the proposed classifier yields high-accuracy results for a large portion of a dataset. We have previously developed an autocoding system for the Family Income and Expenditure Survey in Japan that has a better performing classifier. While the original system was developed in Perl in order to improve the efficiency of the coding process of short Japanese texts, the proposed system is implemented in the R programming language in order to explore versatility and is modified to make the system easily applicable to English text descriptions, in consideration of the increasing number of R users in the field of official statistics. We are planning to publish the proposed classifier as an R-package. The proposed classifier would be generally applicable to other classification tasks including coding activities in the field of official statistics, and it would contribute greatly to improving their efficiency.

  20. Microbial behaviour and cross contamination between cargoes in containerized transportation of food

    DEFF Research Database (Denmark)

    Abban, Stephen

    Transportation is central to the global food and feed supply chain. Thus issues of safety, especially cross contamination with pathogens during food transit should be important in food handling operations. A large proportion of the worlds’ food cargo is moved using intermodal cargo containers...... chain, its role in food safety cannot be ignored. Unfortunately not much effort has been put, scientifically, into understanding the role of the various features of the transportation links in food cross contamination (compared to studies for homes, processing factories and farm yards). The PhD project...... has attempted to shed light on containerized food transport and some of its important attributes as regards hygiene and cross contamination. The overall aim of the study was to ‘identify possible microbial hazards and ways of cross contamination during containerized transportation of foods...

  1. Data characteristics that determine classifier performance

    CSIR Research Space (South Africa)

    Van der Walt, Christiaan M

    2006-11-01

    Full Text Available available at [11]. The kNN uses a LinearNN nearest neighbour search algorithm with an Euclidean distance metric [8]. The optimal k value is determined by performing 10-fold cross-validation. An optimal k value between 1 and 10 is used for Experiments 1... classifiers. 10-fold cross-validation is used to evaluate and compare the performance of the classifiers on the different data sets. 3.1. Artificial data generation Multivariate Gaussian distributions are used to generate artificial data sets. We use d...

  2. Geomorphic Transport Laws and the Statistics of Topography and Stratigraphy

    Science.gov (United States)

    Schumer, R.; Taloni, A.; Furbish, D. J.

    2016-12-01

    Geomorphic transport laws take the form of partial differential equations in which sediment motion is a deterministic function of slope. The addition of a noise term, representing unmeasurable, or subgrid scale autogenic forcing, reproduces scaling properties similar to those observed in topography, landforms, and stratigraphy. Here we describe a transport law that generalizes previous equations by permitting transport that is local or non-local in addition to different types of noise. More importantly, we use this transport law to link the character of sediment transport to the statistics of topography and stratigraphy. In particular, we link the origin of the Sadler effect to the evolution of the earth surface via a transport law.

  3. Data base of accident and agricultural statistics for transportation risk assessment

    Energy Technology Data Exchange (ETDEWEB)

    Saricks, C.L.; Williams, R.G.; Hopf, M.R.

    1989-11-01

    A state-level data base of accident and agricultural statistics has been developed to support risk assessment for transportation of spent nuclear fuels and high-level radioactive wastes. This data base will enhance the modeling capabilities for more route-specific analyses of potential risks associated with transportation of these wastes to a disposal site. The data base and methodology used to develop state-specific accident and agricultural data bases are described, and summaries of accident and agricultural statistics are provided. 27 refs., 9 tabs.

  4. Data base of accident and agricultural statistics for transportation risk assessment

    International Nuclear Information System (INIS)

    Saricks, C.L.; Williams, R.G.; Hopf, M.R.

    1989-11-01

    A state-level data base of accident and agricultural statistics has been developed to support risk assessment for transportation of spent nuclear fuels and high-level radioactive wastes. This data base will enhance the modeling capabilities for more route-specific analyses of potential risks associated with transportation of these wastes to a disposal site. The data base and methodology used to develop state-specific accident and agricultural data bases are described, and summaries of accident and agricultural statistics are provided. 27 refs., 9 tabs

  5. Density limit and cross-field edge transport scaling in Alcator C-Mod

    International Nuclear Information System (INIS)

    LaBombard, B.; Greenwald, M.; Hughes, J.W.; Lipschultz, B.; Mossessian, D.; Terry, J.L.; Boivin, R.L.; Carreras, B.A.; Pitcher, C.S.; Zweben, S.J.

    2003-01-01

    Recent experiments in Alcator C-Mod have uncovered a direct link between the character and scaling of cross-field particle transport in the edge plasma and the density limit, n G . As n-bar e /n G is increased from low values to values approaching ∼1, an ordered progression in the cross-field edge transport physics occurs: first benign cross-field heat convection, then cross-field heat convection impacting the scrape-off layer (SOL) power loss channels and reducing the separatrix electron temperature, and finally 'bursty' transport (normally associated with the far SOL) invading into closed flux surface regions and carrying a convective power loss that impacts the power balance of the discharge. These observations suggest that SOL transport and its scaling with plasma conditions plays a key role in setting the empirically observed density limit scaling law. (author)

  6. Testing of a "smart-pebble" for measuring particle transport statistics

    Science.gov (United States)

    Kitsikoudis, Vasileios; Avgeris, Loukas; Valyrakis, Manousos

    2017-04-01

    This paper presents preliminary results from novel experiments aiming to assess coarse sediment transport statistics for a range of transport conditions, via the use of an innovative "smart-pebble" device. This device is a waterproof sphere, which has 7 cm diameter and is equipped with a number of sensors that provide information about the velocity, acceleration and positioning of the "smart-pebble" within the flow field. A series of specifically designed experiments are carried out to monitor the entrainment of a "smart-pebble" for fully developed, uniform, turbulent flow conditions over a hydraulically rough bed. Specifically, the bed surface is configured to three sections, each of them consisting of well packed glass beads of slightly increasing size at the downstream direction. The first section has a streamwise length of L1=150 cm and beads size of D1=15 mm, the second section has a length of L2=85 cm and beads size of D2=22 mm, and the third bed section has a length of L3=55 cm and beads size of D3=25.4 mm. Two cameras monitor the area of interest to provide additional information regarding the "smart-pebble" movement. Three-dimensional flow measurements are obtained with the aid of an acoustic Doppler velocimeter along a measurement grid to assess the flow forcing field. A wide range of flow rates near and above the threshold of entrainment is tested, while using four distinct densities for the "smart-pebble", which can affect its transport speed and total momentum. The acquired data are analyzed to derive Lagrangian transport statistics and the implications of such an important experiment for the transport of particles by rolling are discussed. The flow conditions for the initiation of motion, particle accelerations and equilibrium particle velocities (translating into transport rates), statistics of particle impact and its motion, can be extracted from the acquired data, which can be further compared to develop meaningful insights for sediment transport

  7. Entropy based classifier for cross-domain opinion mining

    Directory of Open Access Journals (Sweden)

    Jyoti S. Deshmukh

    2018-01-01

    Full Text Available In recent years, the growth of social network has increased the interest of people in analyzing reviews and opinions for products before they buy them. Consequently, this has given rise to the domain adaptation as a prominent area of research in sentiment analysis. A classifier trained from one domain often gives poor results on data from another domain. Expression of sentiment is different in every domain. The labeling cost of each domain separately is very high as well as time consuming. Therefore, this study has proposed an approach that extracts and classifies opinion words from one domain called source domain and predicts opinion words of another domain called target domain using a semi-supervised approach, which combines modified maximum entropy and bipartite graph clustering. A comparison of opinion classification on reviews on four different product domains is presented. The results demonstrate that the proposed method performs relatively well in comparison to the other methods. Comparison of SentiWordNet of domain-specific and domain-independent words reveals that on an average 72.6% and 88.4% words, respectively, are correctly classified.

  8. Identifying clusters of active transportation using spatial scan statistics.

    Science.gov (United States)

    Huang, Lan; Stinchcomb, David G; Pickle, Linda W; Dill, Jennifer; Berrigan, David

    2009-08-01

    There is an intense interest in the possibility that neighborhood characteristics influence active transportation such as walking or biking. The purpose of this paper is to illustrate how a spatial cluster identification method can evaluate the geographic variation of active transportation and identify neighborhoods with unusually high/low levels of active transportation. Self-reported walking/biking prevalence, demographic characteristics, street connectivity variables, and neighborhood socioeconomic data were collected from respondents to the 2001 California Health Interview Survey (CHIS; N=10,688) in Los Angeles County (LAC) and San Diego County (SDC). Spatial scan statistics were used to identify clusters of high or low prevalence (with and without age-adjustment) and the quantity of time spent walking and biking. The data, a subset from the 2001 CHIS, were analyzed in 2007-2008. Geographic clusters of significantly high or low prevalence of walking and biking were detected in LAC and SDC. Structural variables such as street connectivity and shorter block lengths are consistently associated with higher levels of active transportation, but associations between active transportation and socioeconomic variables at the individual and neighborhood levels are mixed. Only one cluster with less time spent walking and biking among walkers/bikers was detected in LAC, and this was of borderline significance. Age-adjustment affects the clustering pattern of walking/biking prevalence in LAC, but not in SDC. The use of spatial scan statistics to identify significant clustering of health behaviors such as active transportation adds to the more traditional regression analysis that examines associations between behavior and environmental factors by identifying specific geographic areas with unusual levels of the behavior independent of predefined administrative units.

  9. Classical scattering cross section in sputtering transport theory

    International Nuclear Information System (INIS)

    Zhang Zhulin

    2002-01-01

    For Lindhard scaling interaction potential scattering commonly used in sputtering theory, the authors analyzed the great difference between Sigmund's single power and the double power cross sections calculated. The double power cross sections can give a much better approximation to the Born-Mayer scattering in the low energy region (m∼0.1). In particular, to solve the transport equations by K r -C potential interaction given by Urbassek few years ago, only the double power cross sections (m∼0.1) can yield better approximate results for the number of recoils. Therefore, the Sigmund's single power cross section might be replaced by the double power cross sections in low energy collision cascade theory

  10. Cross-situational statistical word learning in young children.

    Science.gov (United States)

    Suanda, Sumarga H; Mugwanya, Nassali; Namy, Laura L

    2014-10-01

    Recent empirical work has highlighted the potential role of cross-situational statistical word learning in children's early vocabulary development. In the current study, we tested 5- to 7-year-old children's cross-situational learning by presenting children with a series of ambiguous naming events containing multiple words and multiple referents. Children rapidly learned word-to-object mappings by attending to the co-occurrence regularities across these ambiguous naming events. The current study begins to address the mechanisms underlying children's learning by demonstrating that the diversity of learning contexts affects performance. The implications of the current findings for the role of cross-situational word learning at different points in development are discussed along with the methodological implications of employing school-aged children to test hypotheses regarding the mechanisms supporting early word learning. Copyright © 2014 Elsevier Inc. All rights reserved.

  11. Contaminant transport at a waste residue deposit: 1. Inverse flow and non-reactive transport modelling

    DEFF Research Database (Denmark)

    Sonnenborg, Torben Obel; Engesgaard, Peter Knudegaard; Rosbjerg, Dan

    1996-01-01

    An application of an inverse flow and transport model to a contaminated aquifer is presented. The objective of the study is to identify physical and nonreactive flow and transport parameters through an optimization approach. The approach can be classified as a statistical procedure, where a flow...... to steady state versus transient flow conditions and to the amount of hydraulic and solute data used is investigated. The flow parameters, transmissivity and leakage factor, are estimated simultaneously with the transport parameters: source strength, porosity, and longitudinal dispersivity. This paper...

  12. 75 FR 54695 - Advisory Council on Transportation Statistics; Notice of Meeting

    Science.gov (United States)

    2010-09-08

    .... 2) to advise the Bureau of Transportation Statistics (BTS) on the quality, reliability, consistency... Strategic Plan and related BTS products; (4) Council Members review and discussion of statistical programs... E34-403, Washington, DC 20590, [email protected] or faxed to (202) 366-3640. BTS requests that...

  13. A method to obtain new cross-sections transport equivalent

    International Nuclear Information System (INIS)

    Palmiotti, G.

    1988-01-01

    We present a method, that allows the calculation, by the mean of variational principle, of equivalent cross-sections in order to take into account the transport and mesh size effects on reactivity variation calculations. The method validation has been made in two and three dimensions geometries. The reactivity variations calculated in three dimensional hexagonal geometry with seven points by subassembly using two sets of equivalent cross-sections for control rods are in a very good agreement with the ones of a transport, extrapolated to zero mesh size, calculation. The difficulty encountered in obtaining a good flux distribution has lead to the utilisation of a single set of equivalent cross-sections calculated by starting from an appropriated R-Z model that allows to take into account also the axial transport effects for the control rod followers. The global results in reactivity variations are still satisfactory with a good performance for the flux distribution. The main interest of the proposed method is the possibility to simulate a full 3D transport calculation, with fine mesh size, using a 3D diffusion code, with a larger mesh size. The results obtained should be affected by uncertainties, which do not exceed ± 4% for a large LMFBR control rod worth and for very different rod configurations. This uncertainty is by far smaller than the experimental uncertainties. (author). 5 refs, 8 figs, 9 tabs

  14. Transport statistics 1995

    CSIR Research Space (South Africa)

    De Haan, ML

    1996-04-01

    Full Text Available This publication contains information on all major modes of transport in South Africa. The transport sector is placed in perspective relative to the macro economy and a number of important transport indicators are given. The document also contains...

  15. 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

  16. Information gathering for the Transportation Statistics Data Bank

    International Nuclear Information System (INIS)

    Shappert, L.B.; Mason, P.J.

    1981-10-01

    The Transportation Statistics Data Bank (TSDB) was developed in 1974 to collect information on the transport of Department of Energy (DOE) materials. This computer program may be used to provide the framework for collecting more detailed information on DOE shipments of radioactive materials. This report describes the type of information that is needed in this area and concludes that the existing system could be readily modified to collect and process it. The additional needed information, available from bills of lading and similar documents, could be gathered from DOE field offices and transferred in a standard format to the TSDB system. Costs of the system are also discussed briefly

  17. CASTHY, Statistical Model for Neutron Cross-Sections and Gamma-Ray Spectra

    International Nuclear Information System (INIS)

    Igarasi, Sin-iti; Fukahori, Tokio

    1998-01-01

    Description of program or function: CASTHY calculates neutron cross sections of total, shape elastic scattering and compound nucleus formation with the optical model, and compound elastic, inelastic and capture cross sections by the statistical model. The other cross sections, such as (n,2n), (n,p), (n,f) reactions are treated as cross sections of competing processes, and their sum is given through input data. Capture gamma-ray spectra can also be calculated. The branching ratio for primary transition can be treated in a particular way, if required

  18. Statistical windows in angular momentum space: the basis of heavy-ion compound cross section

    International Nuclear Information System (INIS)

    Hussein, M.S.; Toledo, A.S. de.

    1981-04-01

    The concept of statistical windows in angular momentum space is introduced and utilized to develop a practical model for the heavy-ion compound cross section. Closed expressions for the average differential cross-section are derived and compared with Hauser-Feshbach calculations. The effects of the statistical windows are isolated and discussed. (Author) [pt

  19. Assessing apical transportation in curved canals: comparison between cross-sections and micro-computed tomography

    Directory of Open Access Journals (Sweden)

    Laila Gonzales Freire

    2012-06-01

    Full Text Available The aim of this study was to compare two methods of assessing apical transportation in curved canals after rotary instrumentation, namely, cross-sections and micro-computed tomography (µCT. Thirty mandibular molars were divided into two groups and prepared according to the requirements of each method. In G1 (cross-sections, teeth were embedded in resin blocks and sectioned at 2.0, 3.5, and 5.0 mm from the anatomic apex. Pre- and postoperative sections were photographed and analyzed. In G2 (µCT, teeth were embedded in a rubber-base impression material and scanned before and after instrumentation. Mesiobuccal canals were instrumented with the Twisted File (TF system (SybronEndo, Orange, USA, and mesiolingual canals, with the EndoSequence (ES system (Brasseler, Savannah, USA. Images were reconstructed, and sections corresponding to distances 2.0, 3.5, and 5.0 mm from the anatomic apex were selected for comparison. Data were analyzed using Mann-Whitney's test at a 5% significance level. The TF and ES instruments produced little deviation from the root canal center, with no statistical difference between them (P > 0.05. The canal transportation results were significantly lower (0.056 mm in G2 than in G1 (0.089 mm (p = 0.0012. The µCT method was superior to the cross-section method, especially in view of its ability to preserve specimens and provide results that are more closely related to clinical situations.

  20. From statistic mechanic outside equilibrium to transport equations

    International Nuclear Information System (INIS)

    Balian, R.

    1995-01-01

    This lecture notes give a synthetic view on the foundations of non-equilibrium statistical mechanics. The purpose is to establish the transport equations satisfied by the relevant variables, starting from the microscopic dynamics. The Liouville representation is introduced, and a projection associates with any density operator , for given choice of relevant observables, a reduced density operator. An exact integral-differential equation for the relevant variables is thereby derived. A short-memory approximation then yields the transport equations. A relevant entropy which characterizes the coarseness of the description is associated with each level of description. As an illustration, the classical gas, with its three levels of description and with the Chapman-Enskog method, is discussed. (author). 3 figs., 5 refs

  1. Electron collision cross sections and transport parameters in Cl2

    International Nuclear Information System (INIS)

    Pinhao, N.; Chouki, A.

    1995-01-01

    Molecular chlorine, Cl 2 , is a widely used gas with important application in gas discharge physics, namely in plasma etching, UV lasers and gas-filled particle detectors. However, due to experimental difficulties and to a complicated electronic spectrum, only some of the electron collision cross section have been measured and only recently the electronic structure has been resolved. This situation hampered the theoretical analysis of chlorine mixtures by a lack of relevant transport parameters. To our best knowledge there is only one published measurement of electron drift velocity and characteristic energy. Regrettably these data are considered of doubtful quality. There is also only one measurement of attachment and ionisation coefficients and one published set of cross sections. However those authors used the transport data from a He-Cl 2 mixture (80/20) where chlorine's effect can be hidden by the other component. Consequently that set is not completely consistent with the measurements in pure chlorine. This paper presents a new proposal of a consistent set of electron collision cross sections and the corresponding transport parameters and collision frequencies

  2. Transport and agricultural productivity: A cross-national analysis

    Directory of Open Access Journals (Sweden)

    Sike Liu

    2017-03-01

    Full Text Available The transportation infrastructure plays a significant role in the development of agriculture. In this study we examine the relationship between transport and agricultural performance by employing the World Bank’s roads infrastructure indicators. Based on a cross-country sample, a classic method is employed to test the hypothesis that better transport fosters agricultural productivity. The empirical results of the method support the hypothesis. As for this method, the estimation results of the widely-used inter-country aggregate agricultural production function describe that a country with better transport can produce more agricultural outputs given the same amounts of agricultural inputs and the same education level. Our empirical work lends support to the claim of Gollin and Rogerson (2010 [19] that transport is a basic factor explaining the poor economic performance of many developing countries, apart from physical and education investments, more emphasis should be placed on improving the transport infrastructure of these countries.

  3. 78 FR 11950 - Advisory Council on Transportation Statistics; Meeting

    Science.gov (United States)

    2013-02-20

    ... Committee Act (5 U.S.C., App. 2) to advise the Bureau of Transportation Statistics (BTS) on the quality...) Discussion of performance measures; (4) Update on BTS data programs and future plans; (5) Council Members review and discussion of BTS programs and plans; (6) Public Comments and Closing Remarks. Participation...

  4. 78 FR 14153 - Advisory Council on Transportation Statistics; Meeting

    Science.gov (United States)

    2013-03-04

    ...., Washington, DC. The Bureau of Transportation Statistics (BTS) will reschedule the meeting for a future date. Currently, BTS is developing a draft agenda. The following is a summary of the draft meeting agenda: (1... performance measures; (4) Update on BTS data programs and future plans (5) Council Members review and...

  5. A protocol for classifying ecologically relevant marine zones, a statistical approach

    Science.gov (United States)

    Verfaillie, Els; Degraer, Steven; Schelfaut, Kristien; Willems, Wouter; Van Lancker, Vera

    2009-06-01

    Mapping ecologically relevant zones in the marine environment has become increasingly important. Biological data are however often scarce and alternatives are being sought in optimal classifications of abiotic variables. The concept of 'marine landscapes' is based on a hierarchical classification of geological, hydrographic and other physical data. This approach is however subject to many assumptions and subjective decisions. An objective protocol for zonation is being proposed here where abiotic variables are subjected to a statistical approach, using principal components analysis (PCA) and a cluster analysis. The optimal number of clusters (or zones) is being defined using the Calinski-Harabasz criterion. The methodology has been applied on datasets of the Belgian part of the North Sea (BPNS), a shallow sandy shelf environment with a sandbank-swale topography. The BPNS was classified into 8 zones that represent well the natural variability of the seafloor. The internal cluster consistency was validated with a split-run procedure, with more than 99% correspondence between the validation and the original dataset. The ecological relevance of 6 out of the 8 zones was demonstrated, using indicator species analysis. The proposed protocol, as exemplified for the BPNS, can easily be applied to other areas and provides a strong knowledge basis for environmental protection and management of the marine environment. A SWOT-analysis, showing the strengths, weaknesses, opportunities and threats of the protocol was performed.

  6. Cross-situational statistically based word learning intervention for late-talking toddlers.

    Science.gov (United States)

    Alt, Mary; Meyers, Christina; Oglivie, Trianna; Nicholas, Katrina; Arizmendi, Genesis

    2014-01-01

    To explore the efficacy of a word learning intervention for late-talking toddlers that is based on principles of cross-situational statistical learning. Four late-talking toddlers were individually provided with 7-10 weeks of bi-weekly word learning intervention that incorporated principles of cross-situational statistical learning. Treatment was input-based meaning that, aside from initial probes, children were not asked to produce any language during the sessions. Pre-intervention data included parent-reported measures of productive vocabulary and language samples. Data collected during intervention included production on probes, spontaneous production during treatment, and parent report of words used spontaneously at home. Data were analyzed for number of target words learned relative to control words, effect sizes, and pre-post treatment vocabulary measures. All children learned more target words than control words and, on average, showed a large treatment effect size. Children made pre-post vocabulary gains, increasing their percentile scores on the MCDI, and demonstrated a rate of word learning that was faster than rates found in the literature. Cross-situational statistically based word learning intervention has the potential to improve vocabulary learning in late-talking toddlers. Limitations on interpretation are also discussed. Readers will describe what cross-situational learning is and how it might apply to treatment. They will identify how including lexical and contextual variability in a word learning intervention for toddlers affected treatment outcomes. They will also recognize evidence of improved rate of vocabulary learning following treatment. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. The Use of Advanced Transportation Monitoring Data for Official Statistics

    NARCIS (Netherlands)

    Y. Ma (Yinyi)

    2016-01-01

    markdownabstractTraffic and transportation statistics are mainly published as aggregated information, and are traditionally based on surveys or secondary data sources, like public registers and companies’ administrations. Nowadays, advanced monitoring systems are installed in the road network, offering

  8. Ohio Department of Transportation Financial & Statistical Report : Fiscal Year 2007

    Science.gov (United States)

    2007-01-01

    On behalf of the dedicated men and women of the Ohio Department of Transportation, I share with : you this Financial and Statistical Report for State Fiscal Year 2007, documenting the state and : federal dollars invested by ODOT into preserving, main...

  9. A Descriptive Study of Individual and Cross-Cultural Differences in Statistics Anxiety

    Science.gov (United States)

    Baloglu, Mustafa; Deniz, M. Engin; Kesici, Sahin

    2011-01-01

    The present study investigated individual and cross-cultural differences in statistics anxiety among 223 Turkish and 237 American college students. A 2 x 2 between-subjects factorial multivariate analysis of covariance (MANCOVA) was performed on the six dependent variables which are the six subscales of the Statistical Anxiety Rating Scale.…

  10. Influence of structural properties on ballistic transport in nanoscale epitaxial graphene cross junctions

    International Nuclear Information System (INIS)

    Bock, Claudia; Weingart, Sonja; Karaissaridis, Epaminondas; Kunze, Ulrich; Speck, Florian; Seyller, Thomas

    2012-01-01

    In this paper we investigate the influence of material and device properties on the ballistic transport in epitaxial monolayer graphene and epitaxial quasi-free-standing monolayer graphene. Our studies comprise (a) magneto-transport in two-dimensional (2D) Hall bars, (b) temperature- and magnetic-field-dependent bend resistance of unaligned and step-edge-aligned orthogonal cross junctions, and (c) the influence of the lead width of the cross junctions on ballistic transport. We found that ballistic transport is highly sensitive to scattering at the step edges of the silicon carbide substrate. A suppression of the ballistic transport is observed if the lead width of the cross junction is reduced from 50 nm to 30 nm. In a 50 nm wide device prepared on quasi-free-standing graphene we observe a gradual transition from the ballistic into the diffusive transport regime if the temperature is increased from 4.2 to about 50 K, although 2D Hall bars show a temperature-independent mobility. Thus, in 1D devices additional temperature-dependent scattering mechanisms play a pivotal role. (paper)

  11. Statistical Modelling of Resonant Cross Section Structure in URR, Model of the Characteristic Function

    International Nuclear Information System (INIS)

    Koyumdjieva, N.

    2006-01-01

    A statistical model for the resonant cross section structure in the Unresolved Resonance Region has been developed in the framework of the R-matrix formalism in Reich Moore approach with effective accounting of the resonance parameters fluctuations. The model uses only the average resonance parameters and can be effectively applied for analyses of cross sections functional, averaged over many resonances. Those are cross section moments, transmission and self-indication functions measured through thick sample. In this statistical model the resonant cross sections structure is accepted to be periodic and the R-matrix is a function of ε=E/D with period 0≤ε≤N; R nc (ε)=π/2√(S n *S c )1/NΣ(i=1,N)(β in *β ic *ctg[π(ε i - = ε-iS i )/N]; Here S n ,S c ,S i is respectively neutron strength function, strength function for fission or inelastic channel and strength function for radiative capture, N is the number of resonances (ε i ,β i ) that obey the statistic of Porter-Thomas and Wigner's one. The simple case of this statistical model concerns the resonant cross section structure for non-fissile nuclei under the threshold for inelastic scattering - the model of the characteristic function with HARFOR program. In the above model some improvements of calculation of the phases and logarithmic derivatives of neutron channels have been done. In the parameterization we use the free parameter R l ∞ , which accounts the influence of long-distant resonances. The above scheme for statistical modelling of the resonant cross section structure has been applied for evaluation of experimental data for total, capture and inelastic cross sections for 232 Th in the URR (4-150) keV and also the transmission and self-indication functions in (4-175) keV. The set of evaluated average resonance parameters have been obtained. The evaluated average resonance parameters in the URR are consistent with those in the Resolved Resonance Region (CRP for Th-U cycle, Vienna, 2006

  12. Density limit and cross-field edge transport scaling in Alcator C-Mod

    International Nuclear Information System (INIS)

    LaBombard, B.

    2002-01-01

    Experiments in Alcator C-Mod have uncovered a direct link between the character and scaling of edge transport and the empirical Greenwald density limit (n G ). In low to moderate density discharges, the scrape-off layer (SOL) exhibits a two-layer structure: a near SOL (∼5 mm zone) with steep density and temperature gradients and a far SOL with flatter profiles. In the far SOL, the transport fluxes exhibit large transport events ('bursts' which carry particles to main-chamber structures. In the near SOL, transport fluxes appear to be less 'bursty' particle diffusivities in this region is found to increase strongly with local plasma collisionality. As n/n G (or collisionality) is raised, cross-field heat convection begins to compete with parallel conduction to the divertor. At N/n G ∼0.5, T E at the separatrix is reduced. As n/n G approaches ∼1, regions inside the separatrix exhibit flatter profiles with 'bursty' transport behavior; cross-field heat convection to main-chamber structures becomes comparable to the radiated power. Thus as n/n G is increased, cross-field edge transport physics progressively changes, ultimately impacting the power balance of the discharge near N/n G ∼1. (author)

  13. Transport reduction via shear flow modification of the cross phase

    International Nuclear Information System (INIS)

    Ware, A.S.; Terry, P.W.; Diamond, P.H.; Carreras, B.A.

    1996-01-01

    As a model example of the effect of E x B shear flow on the cross phase between electrostatic potential and pressure fluctuations, a nonlinear theory of resistive pressure gradient driven turbulence (RPGDT) in a shear flow is presented. This work builds on numerical studies of RPGDT, which have shown that both flow shear and curvature can affect the cross phase as well as the fluctuation levels. In this work, we show that the effect of shear flow on transport can be expressed through the temporal response of pressure to potential. It is shown heuristically that even in the case where the fluctuation levels are not modified, the flow shear still acts to reduce the phase angle between potential and pressure fluctuations, thereby suppressing transport. The scaling of the cross phase with flow shear and flow curvature is presented. (author)

  14. Advanced statistics for tokamak transport colinearity and tokamak to tokamak variation

    International Nuclear Information System (INIS)

    Riedel, K.S.

    1989-03-01

    This is a compendium of three separate articles on the statistical analysis of tokamak transport. The first article is an expository introduction to advanced statistics and scaling laws. The second analyzes two important problems of tokamak data---colinearity and tokamak to tokamak variation in detail. The third article generalizes the Swamy random coefficient model to the case of degenerate matrices. Three papers have been processed separately

  15. α -induced reactions on 115In: Cross section measurements and statistical model analysis

    Science.gov (United States)

    Kiss, G. G.; Szücs, T.; Mohr, P.; Török, Zs.; Huszánk, R.; Gyürky, Gy.; Fülöp, Zs.

    2018-05-01

    Background: α -nucleus optical potentials are basic ingredients of statistical model calculations used in nucleosynthesis simulations. While the nucleon+nucleus optical potential is fairly well known, for the α +nucleus optical potential several different parameter sets exist and large deviations, reaching sometimes even an order of magnitude, are found between the cross section predictions calculated using different parameter sets. Purpose: A measurement of the radiative α -capture and the α -induced reaction cross sections on the nucleus 115In at low energies allows a stringent test of statistical model predictions. Since experimental data are scarce in this mass region, this measurement can be an important input to test the global applicability of α +nucleus optical model potentials and further ingredients of the statistical model. Methods: The reaction cross sections were measured by means of the activation method. The produced activities were determined by off-line detection of the γ rays and characteristic x rays emitted during the electron capture decay of the produced Sb isotopes. The 115In(α ,γ )119Sb and 115In(α ,n )Sb118m reaction cross sections were measured between Ec .m .=8.83 and 15.58 MeV, and the 115In(α ,n )Sb118g reaction was studied between Ec .m .=11.10 and 15.58 MeV. The theoretical analysis was performed within the statistical model. Results: The simultaneous measurement of the (α ,γ ) and (α ,n ) cross sections allowed us to determine a best-fit combination of all parameters for the statistical model. The α +nucleus optical potential is identified as the most important input for the statistical model. The best fit is obtained for the new Atomki-V1 potential, and good reproduction of the experimental data is also achieved for the first version of the Demetriou potentials and the simple McFadden-Satchler potential. The nucleon optical potential, the γ -ray strength function, and the level density parametrization are also

  16. Correlation Dimension-Based Classifier

    Czech Academy of Sciences Publication Activity Database

    Jiřina, Marcel; Jiřina jr., M.

    2014-01-01

    Roč. 44, č. 12 (2014), s. 2253-2263 ISSN 2168-2267 R&D Projects: GA MŠk(CZ) LG12020 Institutional support: RVO:67985807 Keywords : classifier * multidimensional data * correlation dimension * scaling exponent * polynomial expansion Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 3.469, year: 2014

  17. Using beryllium-7 to assess cross-tropopause transport in global models

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Hongyu [National Institute of Aerospace, Hampton, VA (United States); Considine, David B. [NASA Langley Research Center, Hampton, VA (United States); Horowitz, Larry W. [NOAA Geophysical Fluid and Dynamics Laboratory, Princeton, NJ (United States); and others

    2016-07-01

    We use the Global Modeling Initiative (GMI) modeling framework to assess the utility of cosmogenic beryllium-7 ({sup 7}Be), a natural aerosol tracer, for evaluating cross-tropopause transport in global models. The GMI chemical transport model (CTM) was used to simulate atmospheric {sup 7}Be distributions using four different meteorological data sets (GEOS1-STRAT DAS, GISS II{sup '} GCM, fvGCM, and GEOS4-DAS), featuring significantly different stratosphere-troposphere exchange (STE) characteristics. The simulations were compared with the upper troposphere and/or lower stratosphere (UT/LS) {sup 7}Be climatology constructed from ∝ 25 years of aircraft and balloon data, as well as climatological records of surface concentrations and deposition fluxes. Comparison of the fraction of surface air of stratospheric origin estimated from the {sup 7}Be simulations with observationally derived estimates indicates excessive cross-tropopause transport at mid-latitudes in simulations using GEOS1-STRAT and at high latitudes using GISS II{sup '} meteorological data. These simulations also overestimate {sup 7}Be deposition fluxes at mid-latitudes (GEOS1-STRAT) and at high latitudes (GISS II{sup '}), respectively. We show that excessive cross-tropopause transport of {sup 7}Be corresponds to overestimated stratospheric contribution to tropospheric ozone. Our perspectives on STE in these meteorological fields based on {sup 7}Be simulations are consistent with previous modeling studies of tropospheric ozone using the same meteorological fields. We conclude that the observational constraints for {sup 7}Be and observed {sup 7}Be total deposition fluxes can be used routinely as a first-order assessment of cross-tropopause transport in global models.

  18. Trans-European transport network and cross-border governance

    DEFF Research Database (Denmark)

    Guasco, Clement Nicolas

    2014-01-01

    for coordinating knowledge, efforts and solutions across several national systems. In order to understand this governance setting, one needs to understand the specific quality of transnational governance in the EU, which is neither purely international nor federally integrated. The transport corridor between Malmö......This article looks at the implementation of trans-European transport corridors in the EU and the influence it has on governance within EU member-states. It considers the implementation of such a scheme in the context of cross-border cooperation and discusses the system of governance necessary...

  19. Is There a Critical Distance for Fickian Transport? - a Statistical Approach to Sub-Fickian Transport Modelling in Porous Media

    Science.gov (United States)

    Most, S.; Nowak, W.; Bijeljic, B.

    2014-12-01

    Transport processes in porous media are frequently simulated as particle movement. This process can be formulated as a stochastic process of particle position increments. At the pore scale, the geometry and micro-heterogeneities prohibit the commonly made assumption of independent and normally distributed increments to represent dispersion. Many recent particle methods seek to loosen this assumption. Recent experimental data suggest that we have not yet reached the end of the need to generalize, because particle increments show statistical dependency beyond linear correlation and over many time steps. The goal of this work is to better understand the validity regions of commonly made assumptions. We are investigating after what transport distances can we observe: A statistical dependence between increments, that can be modelled as an order-k Markov process, boils down to order 1. This would be the Markovian distance for the process, where the validity of yet-unexplored non-Gaussian-but-Markovian random walks would start. A bivariate statistical dependence that simplifies to a multi-Gaussian dependence based on simple linear correlation (validity of correlated PTRW). Complete absence of statistical dependence (validity of classical PTRW/CTRW). The approach is to derive a statistical model for pore-scale transport from a powerful experimental data set via copula analysis. The model is formulated as a non-Gaussian, mutually dependent Markov process of higher order, which allows us to investigate the validity ranges of simpler models.

  20. 76 FR 50539 - Advisory Council on Transportation Statistics; Notice of Meeting

    Science.gov (United States)

    2011-08-15

    ... U.S.C., App. 2) to advise the Bureau of Transportation Statistics (BTS) on the quality, reliability..., DC 20590, [email protected] , or faxed to (202) 366-3640. BTS requests that written comments...

  1. 76 FR 2748 - Advisory Council on Transportation Statistics; Notice of Meeting

    Science.gov (United States)

    2011-01-14

    ... U.S.C., App. 2) to advise the Bureau of Transportation Statistics (BTS) on the quality, reliability...) 366-3640. BTS requests that written comments be received by February 9, 2011. Access to the DOT...

  2. The crossing statistic: dealing with unknown errors in the dispersion of Type Ia supernovae

    International Nuclear Information System (INIS)

    Shafieloo, Arman; Clifton, Timothy; Ferreira, Pedro

    2011-01-01

    We propose a new statistic that has been designed to be used in situations where the intrinsic dispersion of a data set is not well known: The Crossing Statistic. This statistic is in general less sensitive than χ 2 to the intrinsic dispersion of the data, and hence allows us to make progress in distinguishing between different models using goodness of fit to the data even when the errors involved are poorly understood. The proposed statistic makes use of the shape and trends of a model's predictions in a quantifiable manner. It is applicable to a variety of circumstances, although we consider it to be especially well suited to the task of distinguishing between different cosmological models using type Ia supernovae. We show that this statistic can easily distinguish between different models in cases where the χ 2 statistic fails. We also show that the last mode of the Crossing Statistic is identical to χ 2 , so that it can be considered as a generalization of χ 2

  3. Low-temperature ballistic transport in nanoscale epitaxial graphene cross junctions

    OpenAIRE

    Weingart, S.; Bock, C.; Kunze, U.; Speck, F.; Seyller, Th.; Ley, L.

    2009-01-01

    We report on the observation of inertial-ballistic transport in nanoscale cross junctions fabricated from epitaxial graphene grown on SiC(0001). Ballistic transport is indicated by a negative bend resistance of R12,43 ~ 170 ohm which is measured in a non-local, four-terminal configuration at 4.2 K and which vanishes as the temperature is increased above 80 K.

  4. Sensitivity of neutron air transport to nitrogen cross section uncertainties

    International Nuclear Information System (INIS)

    Niiler, A.; Beverly, W.B.; Banks, N.E.

    1975-01-01

    The sensitivity of the transport of 14-MeV neutrons in sea level air to uncertainties in the ENDF/B-III values of the various Nitrogen cross sections has been calculated using the correlated sampling Monte Carlo neutron transport code SAMCEP. The source consisted of a 14.0- to 14.9-MeV band of isotropic neutrons and the fluences (0.5 to 15.0 MeV) were calculated at radii from 50 to 1500 metres. The maximum perturbations, assigned to the ENDF/B-III or base cross section set in the 6.0- to 14.5-MeV energy range were; (1) 2 percent to the total, (2) 10 percent to the total elastic, (3) 40 percent to the inelastic and absorption and (4) 20 percent to the first Legendre coefficient and 10 percent to the second Legendre coefficient of the elastic angular distribtuions. Transport calculations were carried out using various physically realistic sets of perturbed cross sections, bounded by evaluator-assigned uncertainties, as well as the base set. Results show that in some energy intervals at 1500 metres, the differential fluence level with a perturbed set differed by almost a factor of two from the differential fluence level with the base set. 5 figures

  5. Deconvolution When Classifying Noisy Data Involving Transformations

    KAUST Repository

    Carroll, Raymond

    2012-09-01

    In the present study, we consider the problem of classifying spatial data distorted by a linear transformation or convolution and contaminated by additive random noise. In this setting, we show that classifier performance can be improved if we carefully invert the data before the classifier is applied. However, the inverse transformation is not constructed so as to recover the original signal, and in fact, we show that taking the latter approach is generally inadvisable. We introduce a fully data-driven procedure based on cross-validation, and use several classifiers to illustrate numerical properties of our approach. Theoretical arguments are given in support of our claims. Our procedure is applied to data generated by light detection and ranging (Lidar) technology, where we improve on earlier approaches to classifying aerosols. This article has supplementary materials online.

  6. Deconvolution When Classifying Noisy Data Involving Transformations.

    Science.gov (United States)

    Carroll, Raymond; Delaigle, Aurore; Hall, Peter

    2012-09-01

    In the present study, we consider the problem of classifying spatial data distorted by a linear transformation or convolution and contaminated by additive random noise. In this setting, we show that classifier performance can be improved if we carefully invert the data before the classifier is applied. However, the inverse transformation is not constructed so as to recover the original signal, and in fact, we show that taking the latter approach is generally inadvisable. We introduce a fully data-driven procedure based on cross-validation, and use several classifiers to illustrate numerical properties of our approach. Theoretical arguments are given in support of our claims. Our procedure is applied to data generated by light detection and ranging (Lidar) technology, where we improve on earlier approaches to classifying aerosols. This article has supplementary materials online.

  7. Deconvolution When Classifying Noisy Data Involving Transformations

    KAUST Repository

    Carroll, Raymond; Delaigle, Aurore; Hall, Peter

    2012-01-01

    In the present study, we consider the problem of classifying spatial data distorted by a linear transformation or convolution and contaminated by additive random noise. In this setting, we show that classifier performance can be improved if we carefully invert the data before the classifier is applied. However, the inverse transformation is not constructed so as to recover the original signal, and in fact, we show that taking the latter approach is generally inadvisable. We introduce a fully data-driven procedure based on cross-validation, and use several classifiers to illustrate numerical properties of our approach. Theoretical arguments are given in support of our claims. Our procedure is applied to data generated by light detection and ranging (Lidar) technology, where we improve on earlier approaches to classifying aerosols. This article has supplementary materials online.

  8. Statistical properties of turbulent transport and fluctuations in tokamak and stellarator devices

    Energy Technology Data Exchange (ETDEWEB)

    Hidalgo, C; Pedrosa, M A; Milligen, B Van; Sanchez, E; Balbin, R; Garcia-Cortes, I [Euratom-CIEMAT Association, Madrid (Spain); Bleuel, J; Giannone, L.; Niedermeyer, H [Euratom-IPP Association, Garching (Germany)

    1997-05-01

    The statistical properties of fluctuations and turbulent transport have been studied in the plasma boundary region of stellarator (TJ-IU, W7-AS) and tokamak (TJ-I) devices. The local flux probability distribution function shows the bursty character of the flux and presents a systematic change as a function of the radial location. There exist large amplitude transport bursts that account for a significant part of the total flux. There is a strong similarity between the statistical properties of the turbulent fluxes in different devices. The value of the radial coherence associated with fluctuations and turbulent transport is strongly intermittent. This result emphasizes the importance of measurements with time resolution in understanding the interplay between the edge and the core regions in the plasma. For measurements in the plasma edge region of the TJ-IU torsatron, the turbulent flux does not, in general, show a larger radial coherence than the one associated with the fluctuations. (author). 14 refs, 6 figs.

  9. Statistical properties of cross-correlation in the Korean stock market

    Science.gov (United States)

    Oh, G.; Eom, C.; Wang, F.; Jung, W.-S.; Stanley, H. E.; Kim, S.

    2011-01-01

    We investigate the statistical properties of the cross-correlation matrix between individual stocks traded in the Korean stock market using the random matrix theory (RMT) and observe how these affect the portfolio weights in the Markowitz portfolio theory. We find that the distribution of the cross-correlation matrix is positively skewed and changes over time. We find that the eigenvalue distribution of original cross-correlation matrix deviates from the eigenvalues predicted by the RMT, and the largest eigenvalue is 52 times larger than the maximum value among the eigenvalues predicted by the RMT. The β_{473} coefficient, which reflect the largest eigenvalue property, is 0.8, while one of the eigenvalues in the RMT is approximately zero. Notably, we show that the entropy function E(σ) with the portfolio risk σ for the original and filtered cross-correlation matrices are consistent with a power-law function, E( σ) σ^{-γ}, with the exponent γ 2.92 and those for Asian currency crisis decreases significantly.

  10. MIDAS: Regionally linear multivariate discriminative statistical mapping.

    Science.gov (United States)

    Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

    2018-07-01

    Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the

  11. A statistical method to estimate low-energy hadronic cross sections

    Science.gov (United States)

    Balassa, Gábor; Kovács, Péter; Wolf, György

    2018-02-01

    In this article we propose a model based on the Statistical Bootstrap approach to estimate the cross sections of different hadronic reactions up to a few GeV in c.m.s. energy. The method is based on the idea, when two particles collide a so-called fireball is formed, which after a short time period decays statistically into a specific final state. To calculate the probabilities we use a phase space description extended with quark combinatorial factors and the possibility of more than one fireball formation. In a few simple cases the probability of a specific final state can be calculated analytically, where we show that the model is able to reproduce the ratios of the considered cross sections. We also show that the model is able to describe proton-antiproton annihilation at rest. In the latter case we used a numerical method to calculate the more complicated final state probabilities. Additionally, we examined the formation of strange and charmed mesons as well, where we used existing data to fit the relevant model parameters.

  12. 78 FR 26113 - Advisory Council on Transportation Statistics; Notice of Meeting

    Science.gov (United States)

    2013-05-03

    ... of Transportation Statistics (BTS) on the quality, reliability, consistency, objectivity, and... introduction of Council Members; (2) Discussion of the usefulness and visibility of current BTS products; (3) Strategies for assuring and enhancing quality of BTS products; (4) Preparations for reauthorization; (5...

  13. One-, two- and three-dimensional transport codes using multi-group double-differential form cross sections

    International Nuclear Information System (INIS)

    Mori, Takamasa; Nakagawa, Masayuki; Sasaki, Makoto.

    1988-11-01

    We have developed a group of computer codes to realize the accurate transport calculation by using the multi-group double-differential form cross section. This type of cross section can correctly take account of the energy-angle correlated reaction kinematics. Accordingly, the transport phenomena in materials with highly anisotropic scattering are accurately calculated by using this cross section. They include the following four codes or code systems: PROF-DD : a code system to generate the multi-group double-differential form cross section library by processing basic nuclear data file compiled in the ENDF / B-IV or -V format, ANISN-DD : a one-dimensional transport code based on the discrete ordinate method, DOT-DD : a two-dimensional transport code based on the discrete ordinate method, MORSE-DD : a three-dimensional transport code based on the Monte Carlo method. In addition to these codes, several auxiliary codes have been developed to process calculated results. This report describes the calculation algorithm employed in these codes and how to use them. (author)

  14. Recognition of pornographic web pages by classifying texts and images.

    Science.gov (United States)

    Hu, Weiming; Wu, Ou; Chen, Zhouyao; Fu, Zhouyu; Maybank, Steve

    2007-06-01

    With the rapid development of the World Wide Web, people benefit more and more from the sharing of information. However, Web pages with obscene, harmful, or illegal content can be easily accessed. It is important to recognize such unsuitable, offensive, or pornographic Web pages. In this paper, a novel framework for recognizing pornographic Web pages is described. A C4.5 decision tree is used to divide Web pages, according to content representations, into continuous text pages, discrete text pages, and image pages. These three categories of Web pages are handled, respectively, by a continuous text classifier, a discrete text classifier, and an algorithm that fuses the results from the image classifier and the discrete text classifier. In the continuous text classifier, statistical and semantic features are used to recognize pornographic texts. In the discrete text classifier, the naive Bayes rule is used to calculate the probability that a discrete text is pornographic. In the image classifier, the object's contour-based features are extracted to recognize pornographic images. In the text and image fusion algorithm, the Bayes theory is used to combine the recognition results from images and texts. Experimental results demonstrate that the continuous text classifier outperforms the traditional keyword-statistics-based classifier, the contour-based image classifier outperforms the traditional skin-region-based image classifier, the results obtained by our fusion algorithm outperform those by either of the individual classifiers, and our framework can be adapted to different categories of Web pages.

  15. 78 FR 66104 - Advisory Council on Transportation Statistics; Notice of Meeting

    Science.gov (United States)

    2013-11-04

    ... advise the Bureau of Transportation Statistics (BTS) on the quality, reliability, consistency... current BTS products; (3) Follow-up discussion of strategies for assuring and enhancing quality of BTS products; (4) Future directions for BTS programs; (5) Public Comments and Closing Remarks. Participation is...

  16. How to classify plantar plate injuries: parameters from history and physical examination.

    Science.gov (United States)

    Nery, Caio; Coughlin, Michael; Baumfeld, Daniel; Raduan, Fernando; Mann, Tania Szejnfeld; Catena, Fernanda

    2015-01-01

    To find the best clinical parameters for defining and classifying the degree of plantar plate injuries. Sixty-eight patients (100 metatarsophalangeal joints) were classified in accordance with the Arthroscopic Anatomical Classification for plantar plate injuries and were divided into five groups (0 to IV). Their medical files were reviewed and the incidence of each parameter for the respective group was correlated. These parameters were: use of high heels, sports, acute pain, local edema, Mulder's sign, widening of the interdigital space, pain in the head of the corresponding metatarsal, touching the ground, "drawer test", toe grip and toe deformities (in the sagittal, coronal and transversal planes). There were no statistically significant associations between the degree of injury and use of high-heel shoes, sports trauma, pain at the head of the metatarsal, Mulder's sign, deformity in pronation or displacement in the transversal and sagittal planes (although their combination, i.e. "cross toe", showed a statistically significant correlation). Positive correlations with the severity of the injuries were found in relation to initial acute pain, progressive widening of the interdigital space, loss of "touching the ground", positive results from the "drawer test" on the metatarsophalangeal joint, diminished grip strength and toe deformity in supination. The "drawer test" was seen to be the more reliable and precise tool for classifying the degree of plantar plate injury, followed by "touching the ground" and rotational deformities. It is possible to improve the precision of the diagnosis and the predictions of the anatomical classification for plantar plate injuries through combining the clinical history and data from the physical examination.

  17. Frog sound identification using extended k-nearest neighbor classifier

    Science.gov (United States)

    Mukahar, Nordiana; Affendi Rosdi, Bakhtiar; Athiar Ramli, Dzati; Jaafar, Haryati

    2017-09-01

    Frog sound identification based on the vocalization becomes important for biological research and environmental monitoring. As a result, different types of feature extractions and classifiers have been employed to evaluate the accuracy of frog sound identification. This paper presents a frog sound identification with Extended k-Nearest Neighbor (EKNN) classifier. The EKNN classifier integrates the nearest neighbors and mutual sharing of neighborhood concepts, with the aims of improving the classification performance. It makes a prediction based on who are the nearest neighbors of the testing sample and who consider the testing sample as their nearest neighbors. In order to evaluate the classification performance in frog sound identification, the EKNN classifier is compared with competing classifier, k -Nearest Neighbor (KNN), Fuzzy k -Nearest Neighbor (FKNN) k - General Nearest Neighbor (KGNN)and Mutual k -Nearest Neighbor (MKNN) on the recorded sounds of 15 frog species obtained in Malaysia forest. The recorded sounds have been segmented using Short Time Energy and Short Time Average Zero Crossing Rate (STE+STAZCR), sinusoidal modeling (SM), manual and the combination of Energy (E) and Zero Crossing Rate (ZCR) (E+ZCR) while the features are extracted by Mel Frequency Cepstrum Coefficient (MFCC). The experimental results have shown that the EKNCN classifier exhibits the best performance in terms of accuracy compared to the competing classifiers, KNN, FKNN, GKNN and MKNN for all cases.

  18. Transportation assimilation revisited: New evidence from repeated cross-sectional survey data

    Science.gov (United States)

    2018-01-01

    Background Based on single cross-sectional data, prior research finds evidence of “transportation assimilation” among U.S. immigrants: the length of stay in the U.S. is negatively correlated with public transit use. This paper revisits this question by using repeated cross-sectional data, and examines the trend of transportation assimilation over time. Methods and results Using 1980, 1990, 2000 1% census and 2010 (1%) American Community Survey, I examine the relationship between the length of stay in the U.S. and public transit ridership among immigrants. I first run regressions separately in four data sets: I regress public transit ridership on the length of stay, controlling for other individual and geographic variables. I then compare the magnitudes of the relationship in four regressions. To study how the rate of transportation assimilation changes over time, I pool the data set and regress public transit ridership on the length of stay and its interactions with year dummies to compare the coefficients across surveys. Results confirm the conclusion of transportation assimilation: as the length of stay in the U.S. increases, an immigrant’s public transit use decreases. However, the repeated cross-section analysis suggests the assimilation rate has been decreasing in the past few decades. Conclusions This paper finds evidence of transportation assimilation: immigrants become less likely to ride public transit as the length of stay in the U.S. increases. The assimilation rate, however, has been decreasing over time. This paper finds that the rate of public transit ridership among new immigrants upon arrival, the geographic distribution of immigrants, and the changing demographics of the U.S. immigrants play roles in affecting the trend of transportation assimilation. PMID:29668676

  19. Multigroup cross section collapsing optimization of a He-3 detector assembly model using deterministic transport techniques

    International Nuclear Information System (INIS)

    Huang, Mi; Yi, Ce; Manalo, Kevin L.; Sjoden, Glenn E.

    2011-01-01

    Multigroup optimization is performed on a neutron detector assembly to examine the validity of transport response in forward and adjoint modes. For SN transport simulations, we discuss the multigroup collapse of an 80 group library to 40, 30, and 16 groups, constructed from using the 3-D parallel PENTRAN and macroscopic cross section collapsing with YGROUP contribution weighting. The difference in using P_1 and P_3 Legendre order in scattering cross sections is investigated; also, associated forward and adjoint transport responses are calculated. We conclude that for the block analyzed, a 30 group cross section optimizes both computation time and accuracy relative to the 80 group transport calculations. (author)

  20. Transport methods: general. 2. Monte Carlo Particle Transport in Media with Exponentially Varying Time-Dependent Cross Sections

    International Nuclear Information System (INIS)

    Brown, Forrest B.; Martin, William R.

    2001-01-01

    We have investigated Monte Carlo schemes for analyzing particle transport through media with exponentially varying time-dependent cross sections. For such media, the cross sections are represented in the form Σ(t) = Σ 0 e -at (1) or equivalently as Σ(x) = Σ 0 e -bx (2) where b = av and v is the particle speed. For the following discussion, the parameters a and b may be either positive, for exponentially decreasing cross sections, or negative, for exponentially increasing cross sections. For most time-dependent Monte Carlo applications, the time and spatial variations of the cross-section data are handled by means of a stepwise procedure, holding the cross sections constant for each region over a small time interval Δt, performing the Monte Carlo random walk over the interval Δt, updating the cross sections, and then repeating for a series of time intervals. Continuously varying spatial- or time-dependent cross sections can be treated in a rigorous Monte Carlo fashion using delta-tracking, but inefficiencies may arise if the range of cross-section variation is large. In this paper, we present a new method for sampling collision distances directly for cross sections that vary exponentially in space or time. The method is exact and efficient and has direct application to Monte Carlo radiation transport methods. To verify that the probability density function (PDF) is correct and that the random-sampling procedure yields correct results, numerical experiments were performed using a one-dimensional Monte Carlo code. The physical problem consisted of a beam source impinging on a purely absorbing infinite slab, with a slab thickness of 1 cm and Σ 0 = 1 cm -1 . Monte Carlo calculations with 10 000 particles were run for a range of the exponential parameter b from -5 to +20 cm -1 . Two separate Monte Carlo calculations were run for each choice of b, a continuously varying case using the random-sampling procedures described earlier, and a 'conventional' case where the

  1. 77 FR 10616 - Advisory Council on Transportation Statistics; Notice of Meeting

    Science.gov (United States)

    2012-02-22

    .... 2) to advise the Bureau of Transportation Statistics (BTS) on the quality, reliability, consistency... budget; (4) Update on BTS data programs and future plans; (5) Council Members review and discussion of BTS programs and plans; (6) Public Comments and Closing Remarks. Participation is open to the public...

  2. Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.

    Science.gov (United States)

    Trainor, Patrick J; DeFilippis, Andrew P; Rai, Shesh N

    2017-06-21

    Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k -Nearest Neighbors ( k -NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction

  3. 77 FR 64375 - Advisory Council on Transportation Statistics; Notice of Meeting

    Science.gov (United States)

    2012-10-19

    ... of Transportation Statistics (BTS) on the quality, reliability, consistency, objectivity, and...) Update on BTS data programs and future plans; (5) Council Members review and discussion of BTS programs... Freiberg, 1200 New Jersey Avenue SE., Room E34-429, Washington, DC 20590, or faxed to (202) 366-3640. BTS...

  4. Seasonal and interannual cross-shelf transport over the Texas and Louisiana continental shelf

    Science.gov (United States)

    Thyng, Kristen M.; Hetland, Robert D.

    2018-05-01

    Numerical drifters are tracked in a hydrodynamic simulation of circulation over the Texas-Louisiana shelf to analyze patterns in cross-shelf transport of materials. While the important forcing mechanisms in the region (wind, river, and deep eddies) and associated flow patterns are known, the resultant material transport is less well understood. The primary metric used in the calculations is the percent of drifters released within a region that cross the 100 m isobath. Results of the analysis indicate that, averaged over the eleven years of the simulation, there are two regions on the shelf - over the Texas shelf during winter, and over the Louisiana shelf in summer - with increased seasonal probability for offshore transport. Among the two other distinct regions, the big bend region in Texas has increased probability for onshore transport, and the Mississippi Delta region has an increase in offshore transport, for both seasons. Some of these regions of offshore transport have marked interannual variability. This interannual variability is correlated to interannual changes in forcing conditions. Winter transport off of the Texas shelf is correlated with winter mean wind direction, with more northerly winds enhancing offshore transport; summer transport off the Louisiana shelf is correlated with Mississippi River discharge.

  5. Counting statistics of transport through Coulomb blockade nanostructures: High-order cumulants and non-Markovian effects

    DEFF Research Database (Denmark)

    Flindt, Christian; Novotny, Tomás; Braggio, Alessandro

    2010-01-01

    Recent experimental progress has made it possible to detect in real-time single electrons tunneling through Coulomb blockade nanostructures, thereby allowing for precise measurements of the statistical distribution of the number of transferred charges, the so-called full counting statistics...... interactions. Our recursive method can treat systems with many states as well as non-Markovian dynamics. We illustrate our approach with three examples of current experimental relevance: bunching transport through a two-level quantum dot, transport through a nanoelectromechanical system with dynamical Franck...

  6. The origin of fluctuations and cross-field transport in idealized magnetic confinement systems

    International Nuclear Information System (INIS)

    Riviere, A.C.; Ashby, D.E.T.F.; Cordey, J.G.; Edlington, T.; Rusbridge, M.G.

    1981-01-01

    The study of plasma fluctuations and confinement in idealized systems such as octupoles and levitrons has contributed to the understanding of cross-field transport processes. The linear theory of plasma instabilities that cause fluctuations can predict growth rates and wavelengths around lines of force. However, the theoretical prediction of cross-field transport coefficient is restricted to quasilinear estimates which usually far exceed the measured values. A general view of the results from octupole and levitron experiments shows that under collisional conditions the diffusion coefficient scales in the same way as classical collisional diffusion. Agreement is closely approached in many cases, sometimes even in the presence of fluctuations. Under collisionless conditions, Bohm diffusion scaling is found in the few cases where the scaling law has been determined. There is also experimental and theoretical evidence that long-wavelength low-frequency electric fields (convection cells) can be generated nonlinearly from high-frequency fluctuations and can contribute to cross-field transport. (author)

  7. Cross sections and transport properties for Na+ in (DXE gas

    Directory of Open Access Journals (Sweden)

    Nikitović Željka D.

    2016-01-01

    Full Text Available In this work we select most probable reactions of alkali metal ion Na+ with dimethoxyethane (DXE molecule. Appropriate gas phase enthalpies of formation for the products were used to calculate scattering cross section as a function of kinetic energy with Denpoh-Nanbu theory. Calculated cross sections were compared with existing experimental results obtained by guided ion beam tandem mass spectrometry. Three body association reactions of ions with DXE is studied and compared to experimental results. Calculated cross sections were used to obtain transport parameters for alkali metal ion in DXE gas. [Projekat Ministarstva nauke Republike Srbije, br. ON 171037 i br. III 410011

  8. Electron transport in silicon nanowires having different cross-sections

    Directory of Open Access Journals (Sweden)

    Muscato Orazio

    2016-06-01

    Full Text Available Transport phenomena in silicon nanowires with different cross-section are investigated using an Extended Hydrodynamic model, coupled to the Schrödinger-Poisson system. The model has been formulated by closing the moment system derived from the Boltzmann equation on the basis of the maximum entropy principle of Extended Thermodynamics, obtaining explicit closure relations for the high-order fluxes and the production terms. Scattering of electrons with acoustic and non polar optical phonons have been taken into account. The bulk mobility is evaluated for square and equilateral triangle cross-sections of the wire.

  9. Fishing effort statistics of the artisanal fisheries of the Cross River ...

    African Journals Online (AJOL)

    Frame surveys were carried out in 1997 and 1998 to assess the effort statistics of the artisanal fisheries of the Cross River Estuary. These surveys covered the inner Estuary and the West coast of the outer Estuary. Fishing effort was taken as number of fishers, number of canoes, and types of fishing gears. A total of 64 fishing ...

  10. Local curvature analysis for classifying breast tumors: Preliminary analysis in dedicated breast CT

    International Nuclear Information System (INIS)

    Lee, Juhun; Nishikawa, Robert M.; Reiser, Ingrid; Boone, John M.; Lindfors, Karen K.

    2015-01-01

    Purpose: The purpose of this study is to measure the effectiveness of local curvature measures as novel image features for classifying breast tumors. Methods: A total of 119 breast lesions from 104 noncontrast dedicated breast computed tomography images of women were used in this study. Volumetric segmentation was done using a seed-based segmentation algorithm and then a triangulated surface was extracted from the resulting segmentation. Total, mean, and Gaussian curvatures were then computed. Normalized curvatures were used as classification features. In addition, traditional image features were also extracted and a forward feature selection scheme was used to select the optimal feature set. Logistic regression was used as a classifier and leave-one-out cross-validation was utilized to evaluate the classification performances of the features. The area under the receiver operating characteristic curve (AUC, area under curve) was used as a figure of merit. Results: Among curvature measures, the normalized total curvature (C_T) showed the best classification performance (AUC of 0.74), while the others showed no classification power individually. Five traditional image features (two shape, two margin, and one texture descriptors) were selected via the feature selection scheme and its resulting classifier achieved an AUC of 0.83. Among those five features, the radial gradient index (RGI), which is a margin descriptor, showed the best classification performance (AUC of 0.73). A classifier combining RGI and C_T yielded an AUC of 0.81, which showed similar performance (i.e., no statistically significant difference) to the classifier with the above five traditional image features. Additional comparisons in AUC values between classifiers using different combinations of traditional image features and C_T were conducted. The results showed that C_T was able to replace the other four image features for the classification task. Conclusions: The normalized curvature measure

  11. Statistical uncertainty analysis of radon transport in nonisothermal, unsaturated soils

    International Nuclear Information System (INIS)

    Holford, D.J.; Owczarski, P.C.; Gee, G.W.; Freeman, H.D.

    1990-10-01

    To accurately predict radon fluxes soils to the atmosphere, we must know more than the radium content of the soil. Radon flux from soil is affected not only by soil properties, but also by meteorological factors such as air pressure and temperature changes at the soil surface, as well as the infiltration of rainwater. Natural variations in meteorological factors and soil properties contribute to uncertainty in subsurface model predictions of radon flux, which, when coupled with a building transport model, will also add uncertainty to predictions of radon concentrations in homes. A statistical uncertainty analysis using our Rn3D finite-element numerical model was conducted to assess the relative importance of these meteorological factors and the soil properties affecting radon transport. 10 refs., 10 figs., 3 tabs

  12. Bias correction for selecting the minimal-error classifier from many machine learning models.

    Science.gov (United States)

    Ding, Ying; Tang, Shaowu; Liao, Serena G; Jia, Jia; Oesterreich, Steffi; Lin, Yan; Tseng, George C

    2014-11-15

    Supervised machine learning is commonly applied in genomic research to construct a classifier from the training data that is generalizable to predict independent testing data. When test datasets are not available, cross-validation is commonly used to estimate the error rate. Many machine learning methods are available, and it is well known that no universally best method exists in general. It has been a common practice to apply many machine learning methods and report the method that produces the smallest cross-validation error rate. Theoretically, such a procedure produces a selection bias. Consequently, many clinical studies with moderate sample sizes (e.g. n = 30-60) risk reporting a falsely small cross-validation error rate that could not be validated later in independent cohorts. In this article, we illustrated the probabilistic framework of the problem and explored the statistical and asymptotic properties. We proposed a new bias correction method based on learning curve fitting by inverse power law (IPL) and compared it with three existing methods: nested cross-validation, weighted mean correction and Tibshirani-Tibshirani procedure. All methods were compared in simulation datasets, five moderate size real datasets and two large breast cancer datasets. The result showed that IPL outperforms the other methods in bias correction with smaller variance, and it has an additional advantage to extrapolate error estimates for larger sample sizes, a practical feature to recommend whether more samples should be recruited to improve the classifier and accuracy. An R package 'MLbias' and all source files are publicly available. tsenglab.biostat.pitt.edu/software.htm. ctseng@pitt.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  13. Transport in Stochastic Media

    International Nuclear Information System (INIS)

    Haran, O.; Shvarts, D.; Thieberger, R.

    1998-01-01

    Classical transport of neutral particles in a binary, scattering, stochastic media is discussed. It is assumed that the cross-sections of the constituent materials and their volume fractions are known. The inner structure of the media is stochastic, but there exist a statistical knowledge about the lump sizes, shapes and arrangement. The transmission through the composite media depends on the specific heterogeneous realization of the media. The current research focuses on the averaged transmission through an ensemble of realizations, frm which an effective cross-section for the media can be derived. The problem of one dimensional transport in stochastic media has been studied extensively [1]. In the one dimensional description of the problem, particles are transported along a line populated with alternating material segments of random lengths. The current work discusses transport in two-dimensional stochastic media. The phenomenon that is unique to the multi-dimensional description of the problem is obstacle bypassing. Obstacle bypassing tends to reduce the opacity of the media, thereby reducing its effective cross-section. The importance of this phenomenon depends on the manner in which the obstacles are arranged in the media. Results of transport simulations in multi-dimensional stochastic media are presented. Effective cross-sections derived from the simulations are compared against those obtained for the one-dimensional problem, and against those obtained from effective multi-dimensional models, which are partially based on a Markovian assumption

  14. AXMIX, ANISN Cross-Sections Mixing, Transport Corrections, Data Library Management

    International Nuclear Information System (INIS)

    2002-01-01

    1 - Nature of physical problem solved: Mixing, changing table length, adjoining, making scattering order adjustments (PN delta function subtraction), and transport corrections of ANISN-type cross sections, and management of cross section data sets and libraries. 2 - Method of solution: The number of energy groups which will fit into the core allocated is determined first. If all groups will fit, the solution is straightforward. If not, then the maximum number of groups which will fit is processed repeatedly using direct access I/O and storage disks. 3 - Restrictions on the complexity of the problem: Some flexibility in applying AXMIX is lost when cross sections to be processed contain up-scatter. A special section on up-scatter is therefore included in the report

  15. MODESTY, Statistical Reaction Cross-Sections and Particle Spectra in Decay Chain

    International Nuclear Information System (INIS)

    Mattes, W.

    1977-01-01

    1 - Nature of the physical problem solved: Code MODESTY calculates all energetically possible reaction cross sections and particle spectra within a nuclear decay chain. 2 - Method of solution: It is based on the statistical nuclear model following the method of Uhl (reference 1) where the optical model is used in the calculation of partial widths and the Blatt-Weisskopf single particle model for gamma rays

  16. Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics.

    Science.gov (United States)

    Chen, Chi-Hsin; Zhang, Yayun; Yu, Chen

    2018-05-01

    Objects in the world usually have names at different hierarchical levels (e.g., beagle, dog, animal). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use co-occurrence information to learn hierarchical labels in contexts where the labels for individual objects and labels for categories were presented in completely separated blocks, in interleaved blocks, or mixed in the same trial. Temporal presentation schedules significantly affected the learning of individual object labels, but not the learning of category labels. Learners' subsequent generalization of category labels indicated sensitivity to the structure of statistical input. Copyright © 2017 Cognitive Science Society, Inc.

  17. Transport theory of deep-inelastic collisions between heavy nuclei

    International Nuclear Information System (INIS)

    Ayik, S.; Noerenberg, W.; Schuermann, B.

    1975-01-01

    In collisions between heavy nuclei, the major part of the total cross-section is due to deep-inelastic processes. These processes have been studied within a quantum-statistical approach leading to transport equations of the Fokker-Planck type (generalized diffusion equation). Transport coefficients have been studied within a model. (orig./WL) [de

  18. Electronic transport in graphene-based structures: An effective cross-section approach

    DEFF Research Database (Denmark)

    Uppstu, Andreas; Saloriutta, Karri; Harju, Ari

    2012-01-01

    We show that transport in low-dimensional carbon structures with finite concentrations of scatterers can be modeled by utilizing scaling theory and effective cross sections. Our results are based on large-scale numerical simulations of carbon nanotubes and graphene nanoribbons, using a tight...

  19. North American Transportation Statistics Database

    Data.gov (United States)

    Department of Transportation — Contains tables of data for the United States, Canada, and Mexico. Data tables are divided up into 12 categories, including a country overview, transportation flows,...

  20. Fisher information metrics for binary classifier evaluation and training

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Different evaluation metrics for binary classifiers are appropriate to different scientific domains and even to different problems within the same domain. This presentation focuses on the optimisation of event selection to minimise statistical errors in HEP parameter estimation, a problem that is best analysed in terms of the maximisation of Fisher information about the measured parameters. After describing a general formalism to derive evaluation metrics based on Fisher information, three more specific metrics are introduced for the measurements of signal cross sections in counting experiments (FIP1) or distribution fits (FIP2) and for the measurements of other parameters from distribution fits (FIP3). The FIP2 metric is particularly interesting because it can be derived from any ROC curve, provided that prevalence is also known. In addition to its relation to measurement errors when used as an evaluation criterion (which makes it more interesting that the ROC AUC), a further advantage of the FIP2 metric is ...

  1. Evaluation of Oceanic Transport Statistics By Use of Transient Tracers and Bayesian Methods

    Science.gov (United States)

    Trossman, D. S.; Thompson, L.; Mecking, S.; Bryan, F.; Peacock, S.

    2013-12-01

    data (BayesPOP) and those estimated using tracer observations as data (BayesObs) provide information about the sources of model biases, and give a more nuanced picture than can be found by comparing the simulated CFC-11 concentrations with observed CFC-11 concentrations. Using the differences between the two oceanic transport parameters from BayesObs and those from BayesPOP with and without a constant Peclet number assumption along each of the hydrographic cross-sections considered here, it is found that the model's diffusivity tensor biases lead to larger model errors than the model's mean advection time biases. However, it is also found that mean advection time biases in the model are statistically significant at the 95% level where mode water is found.

  2. One Hundred Ways to be Non-Fickian - A Rigorous Multi-Variate Statistical Analysis of Pore-Scale Transport

    Science.gov (United States)

    Most, Sebastian; Nowak, Wolfgang; Bijeljic, Branko

    2015-04-01

    Fickian transport in groundwater flow is the exception rather than the rule. Transport in porous media is frequently simulated via particle methods (i.e. particle tracking random walk (PTRW) or continuous time random walk (CTRW)). These methods formulate transport as a stochastic process of particle position increments. At the pore scale, geometry and micro-heterogeneities prohibit the commonly made assumption of independent and normally distributed increments to represent dispersion. Many recent particle methods seek to loosen this assumption. Hence, it is important to get a better understanding of the processes at pore scale. For our analysis we track the positions of 10.000 particles migrating through the pore space over time. The data we use come from micro CT scans of a homogeneous sandstone and encompass about 10 grain sizes. Based on those images we discretize the pore structure and simulate flow at the pore scale based on the Navier-Stokes equation. This flow field realistically describes flow inside the pore space and we do not need to add artificial dispersion during the transport simulation. Next, we use particle tracking random walk and simulate pore-scale transport. Finally, we use the obtained particle trajectories to do a multivariate statistical analysis of the particle motion at the pore scale. Our analysis is based on copulas. Every multivariate joint distribution is a combination of its univariate marginal distributions. The copula represents the dependence structure of those univariate marginals and is therefore useful to observe correlation and non-Gaussian interactions (i.e. non-Fickian transport). The first goal of this analysis is to better understand the validity regions of commonly made assumptions. We are investigating three different transport distances: 1) The distance where the statistical dependence between particle increments can be modelled as an order-one Markov process. This would be the Markovian distance for the process, where

  3. On calculating phase shifts and performing fits to scattering cross sections or transport properties

    International Nuclear Information System (INIS)

    Hepburn, J.W.; Roy, R.J. Le

    1978-01-01

    Improved methods of calculating quantum mechanical phase shifts and for performing least-squares fits to scattering cross sections or transport properties, are described. Their use in a five-parameter fit to experimental differential cross sections reduces the computer time by a factor of 4-7. (Auth.)

  4. Advantages and disadvantages : longitudinal vs. repeated cross-section surveys

    Science.gov (United States)

    1996-06-20

    The benefits of a longitudinal analysis over a repeated cross-sectional study include increased statistical power and the capability to estimate a greater range of conditional probabilities. With the Puget Sound Transportation Panel (PSTP), and any s...

  5. A statistical method (cross-validation) for bone loss region detection after spaceflight

    Science.gov (United States)

    Zhao, Qian; Li, Wenjun; Li, Caixia; Chu, Philip W.; Kornak, John; Lang, Thomas F.

    2010-01-01

    Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes. PMID:20632144

  6. Indirect Transportation Cost in the border crossing process: The United States–Mexico trade

    Directory of Open Access Journals (Sweden)

    Carlos Obed Figueroa Ortiz

    2015-12-01

    Full Text Available Using a Social Accounting Matrix as database, a Computable General Equilibrium model is implemented in order to estimate the Indirect Transportations Costs (ITC present in the border crossing for the U.S.–Mexico bilateral trade. Here, an “iceberg–type” transportation function is assumed to determine the amount of loss that must be faced as a result of border crossing process through the ports of entry existing between the two countries. The study period covers annual data from 1995 to 2009 allowing the analysis of the trend of these costs considering the trade liberalisation that is experienced. Results show that the ITC have experienced a decrease of 12% during the period.Test

  7. Cross-sectional associations of active transport, employment status and objectively measured physical activity: analyses from the National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Yang, Lin; Hu, Liang; Hipp, J Aaron; Imm, Kellie R; Schutte, Rudolph; Stubbs, Brendon; Colditz, Graham A; Smith, Lee

    2018-05-05

    To investigate associations between active transport, employment status and objectively measured moderate-to-vigorous physical activity (MVPA) in a representative sample of US adults. Cross-sectional analyses of data from the National Health and Nutrition Examination Survey. A total of 5180 adults (50.2 years old, 49.0% men) were classified by levels of active transportation and employment status. Outcome measure was weekly time spent in MVPA as recorded by the Actigraph accelerometer. Associations between active transport, employment status and objectively measured MVPA were examined using multivariable linear regression models adjusted for age, body mass index, race and ethnicity, education level, marital status, smoking status, working hour duration (among the employed only) and self-reported leisure time physical activity. Patterns of active transport were similar between the employed (n=2897) and unemployed (n=2283), such that 76.0% employed and 77.5% unemployed engaged in no active transport. For employed adults, those engaging in high levels of active transport (≥90 min/week) had higher amount of MVPA than those who did not engage in active transport. This translated to 40.8 (95% CI 15.7 to 65.9) additional minutes MVPA per week in men and 57.9 (95% CI 32.1 to 83.7) additional minutes MVPA per week in women. Among the unemployed adults, higher levels of active transport were associated with more MVPA among men (44.8 min/week MVPA, 95% CI 9.2 to 80.5) only. Findings from the present study support interventions to promote active transport to increase population level physical activity. Additional strategies are likely required to promote physical activity among unemployed women. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  8. Mathematical model of statistical identification of information support of road transport

    Directory of Open Access Journals (Sweden)

    V. G. Kozlov

    2016-01-01

    Full Text Available In this paper based on the statistical identification method using the theory of self-organizing systems, built multifactor model the relationship of road transport and training system. Background information for the model represented by a number of parameters of average annual road transport operations and information provision, including training complex system parameters (inputs, road management and output parameters. Ask two criteria: stability criterion model and test correlation. The program determines their minimum, and is the only model of optimal complexity. The predetermined number of parameters established mathematical relationship of each output parameter with the others. To improve the accuracy and regularity of the forecast of the interpolation nodes allocated in the test data sequence. Other data form the training sequence. Decision model based on the principle of selection. Running it with the gradual complication of the mathematical description and exhaustive search of all possible variants of the models on the specified criteria. Advantages of the proposed model: adequately reflects the actual process, allows you to enter any additional input parameters and determine their impact on the individual output parameters of the road transport, allows in turn change the values of key parameters in a certain ratio and to determine the appropriate changes the output parameters of the road transport, allows to predict the output parameters road transport operations.

  9. Propagation of statistical and nuclear data uncertainties in Monte Carlo burn-up calculations

    International Nuclear Information System (INIS)

    Garcia-Herranz, Nuria; Cabellos, Oscar; Sanz, Javier; Juan, Jesus; Kuijper, Jim C.

    2008-01-01

    Two methodologies to propagate the uncertainties on the nuclide inventory in combined Monte Carlo-spectrum and burn-up calculations are presented, based on sensitivity/uncertainty and random sampling techniques (uncertainty Monte Carlo method). Both enable the assessment of the impact of uncertainties in the nuclear data as well as uncertainties due to the statistical nature of the Monte Carlo neutron transport calculation. The methodologies are implemented in our MCNP-ACAB system, which combines the neutron transport code MCNP-4C and the inventory code ACAB. A high burn-up benchmark problem is used to test the MCNP-ACAB performance in inventory predictions, with no uncertainties. A good agreement is found with the results of other participants. This benchmark problem is also used to assess the impact of nuclear data uncertainties and statistical flux errors in high burn-up applications. A detailed calculation is performed to evaluate the effect of cross-section uncertainties in the inventory prediction, taking into account the temporal evolution of the neutron flux level and spectrum. Very large uncertainties are found at the unusually high burn-up of this exercise (800 MWd/kgHM). To compare the impact of the statistical errors in the calculated flux with respect to the cross uncertainties, a simplified problem is considered, taking a constant neutron flux level and spectrum. It is shown that, provided that the flux statistical deviations in the Monte Carlo transport calculation do not exceed a given value, the effect of the flux errors in the calculated isotopic inventory are negligible (even at very high burn-up) compared to the effect of the large cross-section uncertainties available at present in the data files

  10. Propagation of statistical and nuclear data uncertainties in Monte Carlo burn-up calculations

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Herranz, Nuria [Departamento de Ingenieria Nuclear, Universidad Politecnica de Madrid, UPM (Spain)], E-mail: nuria@din.upm.es; Cabellos, Oscar [Departamento de Ingenieria Nuclear, Universidad Politecnica de Madrid, UPM (Spain); Sanz, Javier [Departamento de Ingenieria Energetica, Universidad Nacional de Educacion a Distancia, UNED (Spain); Juan, Jesus [Laboratorio de Estadistica, Universidad Politecnica de Madrid, UPM (Spain); Kuijper, Jim C. [NRG - Fuels, Actinides and Isotopes Group, Petten (Netherlands)

    2008-04-15

    Two methodologies to propagate the uncertainties on the nuclide inventory in combined Monte Carlo-spectrum and burn-up calculations are presented, based on sensitivity/uncertainty and random sampling techniques (uncertainty Monte Carlo method). Both enable the assessment of the impact of uncertainties in the nuclear data as well as uncertainties due to the statistical nature of the Monte Carlo neutron transport calculation. The methodologies are implemented in our MCNP-ACAB system, which combines the neutron transport code MCNP-4C and the inventory code ACAB. A high burn-up benchmark problem is used to test the MCNP-ACAB performance in inventory predictions, with no uncertainties. A good agreement is found with the results of other participants. This benchmark problem is also used to assess the impact of nuclear data uncertainties and statistical flux errors in high burn-up applications. A detailed calculation is performed to evaluate the effect of cross-section uncertainties in the inventory prediction, taking into account the temporal evolution of the neutron flux level and spectrum. Very large uncertainties are found at the unusually high burn-up of this exercise (800 MWd/kgHM). To compare the impact of the statistical errors in the calculated flux with respect to the cross uncertainties, a simplified problem is considered, taking a constant neutron flux level and spectrum. It is shown that, provided that the flux statistical deviations in the Monte Carlo transport calculation do not exceed a given value, the effect of the flux errors in the calculated isotopic inventory are negligible (even at very high burn-up) compared to the effect of the large cross-section uncertainties available at present in the data files.

  11. Analysis of multi-fragmentation reactions induced by relativistic heavy ions using the statistical multi-fragmentation model

    Energy Technology Data Exchange (ETDEWEB)

    Ogawa, T., E-mail: ogawa.tatsuhiko@jaea.go.jp [Research Group for Radiation Protection, Division of Environment and Radiation Sciences, Nuclear Science and Engineering Directorate, Japan Atomic Energy Agency, Shirakata-Shirane, Tokai, Ibaraki 319-1195 (Japan); Sato, T.; Hashimoto, S. [Research Group for Radiation Protection, Division of Environment and Radiation Sciences, Nuclear Science and Engineering Directorate, Japan Atomic Energy Agency, Shirakata-Shirane, Tokai, Ibaraki 319-1195 (Japan); Niita, K. [Research Organization for Information Science and Technology, Shirakata-shirane, Tokai, Ibaraki 319-1188 (Japan)

    2013-09-21

    The fragmentation cross-sections of relativistic energy nucleus–nucleus collisions were analyzed using the statistical multi-fragmentation model (SMM) incorporated with the Monte-Carlo radiation transport simulation code particle and heavy ion transport code system (PHITS). Comparison with the literature data showed that PHITS-SMM reproduces fragmentation cross-sections of heavy nuclei at relativistic energies better than the original PHITS by up to two orders of magnitude. It was also found that SMM does not degrade the neutron production cross-sections in heavy ion collisions or the fragmentation cross-sections of light nuclei, for which SMM has not been benchmarked. Therefore, SMM is a robust model that can supplement conventional nucleus–nucleus reaction models, enabling more accurate prediction of fragmentation cross-sections.

  12. Analysis of multi-fragmentation reactions induced by relativistic heavy ions using the statistical multi-fragmentation model

    International Nuclear Information System (INIS)

    Ogawa, T.; Sato, T.; Hashimoto, S.; Niita, K.

    2013-01-01

    The fragmentation cross-sections of relativistic energy nucleus–nucleus collisions were analyzed using the statistical multi-fragmentation model (SMM) incorporated with the Monte-Carlo radiation transport simulation code particle and heavy ion transport code system (PHITS). Comparison with the literature data showed that PHITS-SMM reproduces fragmentation cross-sections of heavy nuclei at relativistic energies better than the original PHITS by up to two orders of magnitude. It was also found that SMM does not degrade the neutron production cross-sections in heavy ion collisions or the fragmentation cross-sections of light nuclei, for which SMM has not been benchmarked. Therefore, SMM is a robust model that can supplement conventional nucleus–nucleus reaction models, enabling more accurate prediction of fragmentation cross-sections

  13. A support vector machine classifier reduces interscanner variation in the HRCT classification of regional disease pattern in diffuse lung disease: Comparison to a Bayesian classifier

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Yongjun; Lim, Jonghyuck; Kim, Namkug; Seo, Joon Beom [Department of Radiology, University of Ulsan College of Medicine, 388-1 Pungnap2-dong, Songpa-gu, Seoul 138-736 (Korea, Republic of); Lynch, David A. [Department of Radiology, National Jewish Medical and Research Center, Denver, Colorado 80206 (United States)

    2013-05-15

    Purpose: To investigate the effect of using different computed tomography (CT) scanners on the accuracy of high-resolution CT (HRCT) images in classifying regional disease patterns in patients with diffuse lung disease, support vector machine (SVM) and Bayesian classifiers were applied to multicenter data. Methods: Two experienced radiologists marked sets of 600 rectangular 20 Multiplication-Sign 20 pixel regions of interest (ROIs) on HRCT images obtained from two scanners (GE and Siemens), including 100 ROIs for each of local patterns of lungs-normal lung and five of regional pulmonary disease patterns (ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation). Each ROI was assessed using 22 quantitative features belonging to one of the following descriptors: histogram, gradient, run-length, gray level co-occurrence matrix, low-attenuation area cluster, and top-hat transform. For automatic classification, a Bayesian classifier and a SVM classifier were compared under three different conditions. First, classification accuracies were estimated using data from each scanner. Next, data from the GE and Siemens scanners were used for training and testing, respectively, and vice versa. Finally, all ROI data were integrated regardless of the scanner type and were then trained and tested together. All experiments were performed based on forward feature selection and fivefold cross-validation with 20 repetitions. Results: For each scanner, better classification accuracies were achieved with the SVM classifier than the Bayesian classifier (92% and 82%, respectively, for the GE scanner; and 92% and 86%, respectively, for the Siemens scanner). The classification accuracies were 82%/72% for training with GE data and testing with Siemens data, and 79%/72% for the reverse. The use of training and test data obtained from the HRCT images of different scanners lowered the classification accuracy compared to the use of HRCT images from the same scanner. For

  14. A support vector machine classifier reduces interscanner variation in the HRCT classification of regional disease pattern in diffuse lung disease: Comparison to a Bayesian classifier

    International Nuclear Information System (INIS)

    Chang, Yongjun; Lim, Jonghyuck; Kim, Namkug; Seo, Joon Beom; Lynch, David A.

    2013-01-01

    Purpose: To investigate the effect of using different computed tomography (CT) scanners on the accuracy of high-resolution CT (HRCT) images in classifying regional disease patterns in patients with diffuse lung disease, support vector machine (SVM) and Bayesian classifiers were applied to multicenter data. Methods: Two experienced radiologists marked sets of 600 rectangular 20 × 20 pixel regions of interest (ROIs) on HRCT images obtained from two scanners (GE and Siemens), including 100 ROIs for each of local patterns of lungs—normal lung and five of regional pulmonary disease patterns (ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation). Each ROI was assessed using 22 quantitative features belonging to one of the following descriptors: histogram, gradient, run-length, gray level co-occurrence matrix, low-attenuation area cluster, and top-hat transform. For automatic classification, a Bayesian classifier and a SVM classifier were compared under three different conditions. First, classification accuracies were estimated using data from each scanner. Next, data from the GE and Siemens scanners were used for training and testing, respectively, and vice versa. Finally, all ROI data were integrated regardless of the scanner type and were then trained and tested together. All experiments were performed based on forward feature selection and fivefold cross-validation with 20 repetitions. Results: For each scanner, better classification accuracies were achieved with the SVM classifier than the Bayesian classifier (92% and 82%, respectively, for the GE scanner; and 92% and 86%, respectively, for the Siemens scanner). The classification accuracies were 82%/72% for training with GE data and testing with Siemens data, and 79%/72% for the reverse. The use of training and test data obtained from the HRCT images of different scanners lowered the classification accuracy compared to the use of HRCT images from the same scanner. For integrated ROI

  15. Recognition of acute lymphoblastic leukemia cells in microscopic images using k-means clustering and support vector machine classifier.

    Science.gov (United States)

    Amin, Morteza Moradi; Kermani, Saeed; Talebi, Ardeshir; Oghli, Mostafa Ghelich

    2015-01-01

    Acute lymphoblastic leukemia is the most common form of pediatric cancer which is categorized into three L1, L2, and L3 and could be detected through screening of blood and bone marrow smears by pathologists. Due to being time-consuming and tediousness of the procedure, a computer-based system is acquired for convenient detection of Acute lymphoblastic leukemia. Microscopic images are acquired from blood and bone marrow smears of patients with Acute lymphoblastic leukemia and normal cases. After applying image preprocessing, cells nuclei are segmented by k-means algorithm. Then geometric and statistical features are extracted from nuclei and finally these cells are classified to cancerous and noncancerous cells by means of support vector machine classifier with 10-fold cross validation. These cells are also classified into their sub-types by multi-Support vector machine classifier. Classifier is evaluated by these parameters: Sensitivity, specificity, and accuracy which values for cancerous and noncancerous cells 98%, 95%, and 97%, respectively. These parameters are also used for evaluation of cell sub-types which values in mean 84.3%, 97.3%, and 95.6%, respectively. The results show that proposed algorithm could achieve an acceptable performance for the diagnosis of Acute lymphoblastic leukemia and its sub-types and can be used as an assistant diagnostic tool for pathologists.

  16. Silicon nanowire arrays as learning chemical vapour classifiers

    International Nuclear Information System (INIS)

    Niskanen, A O; Colli, A; White, R; Li, H W; Spigone, E; Kivioja, J M

    2011-01-01

    Nanowire field-effect transistors are a promising class of devices for various sensing applications. Apart from detecting individual chemical or biological analytes, it is especially interesting to use multiple selective sensors to look at their collective response in order to perform classification into predetermined categories. We show that non-functionalised silicon nanowire arrays can be used to robustly classify different chemical vapours using simple statistical machine learning methods. We were able to distinguish between acetone, ethanol and water with 100% accuracy while methanol, ethanol and 2-propanol were classified with 96% accuracy in ambient conditions.

  17. Crossing statistic: Bayesian interpretation, model selection and resolving dark energy parametrization problem

    International Nuclear Information System (INIS)

    Shafieloo, Arman

    2012-01-01

    By introducing Crossing functions and hyper-parameters I show that the Bayesian interpretation of the Crossing Statistics [1] can be used trivially for the purpose of model selection among cosmological models. In this approach to falsify a cosmological model there is no need to compare it with other models or assume any particular form of parametrization for the cosmological quantities like luminosity distance, Hubble parameter or equation of state of dark energy. Instead, hyper-parameters of Crossing functions perform as discriminators between correct and wrong models. Using this approach one can falsify any assumed cosmological model without putting priors on the underlying actual model of the universe and its parameters, hence the issue of dark energy parametrization is resolved. It will be also shown that the sensitivity of the method to the intrinsic dispersion of the data is small that is another important characteristic of the method in testing cosmological models dealing with data with high uncertainties

  18. Brief note on the statistical calculation of final continuum reaction cross sections of light nuclides

    International Nuclear Information System (INIS)

    Murata, Toru

    2003-01-01

    The level density parameters are determined to reproduce level structure and/or resonance level spacing of the nucleus. In the statistical compound nucleus model, cross sections to discrete levels decrease abruptly, and continuum level cross section increase strongly above the energy point where the continuum levels switched on. In the present study, for the nucleus which level scheme were well determined up to higher excitation energy more than 10 MeV, discrete level cross sections were calculated and summed up and compared with the cross section to the assumed continuum level corresponding to the discrete levels above several MeV excitation energy. Calculation of the (n, n') cross sections were made with CASTHY code of Moldauer model option using level density parameters determined with former method. It is shown that the assumed continuum cross section is fairly large compared with the summed up cross section. Origins of the discrepancy were discussed. (J.P.N.)

  19. A CUMULATIVE MIGRATION METHOD FOR COMPUTING RIGOROUS TRANSPORT CROSS SECTIONS AND DIFFUSION COEFFICIENTS FOR LWR LATTICES WITH MONTE CARLO

    Energy Technology Data Exchange (ETDEWEB)

    Zhaoyuan Liu; Kord Smith; Benoit Forget; Javier Ortensi

    2016-05-01

    A new method for computing homogenized assembly neutron transport cross sections and dif- fusion coefficients that is both rigorous and computationally efficient is proposed in this paper. In the limit of a homogeneous hydrogen slab, the new method is equivalent to the long-used, and only-recently-published CASMO transport method. The rigorous method is used to demonstrate the sources of inaccuracy in the commonly applied “out-scatter” transport correction. It is also demonstrated that the newly developed method is directly applicable to lattice calculations per- formed by Monte Carlo and is capable of computing rigorous homogenized transport cross sections for arbitrarily heterogeneous lattices. Comparisons of several common transport cross section ap- proximations are presented for a simple problem of infinite medium hydrogen. The new method has also been applied in computing 2-group diffusion data for an actual PWR lattice from BEAVRS benchmark.

  20. Histogram deconvolution - An aid to automated classifiers

    Science.gov (United States)

    Lorre, J. J.

    1983-01-01

    It is shown that N-dimensional histograms are convolved by the addition of noise in the picture domain. Three methods are described which provide the ability to deconvolve such noise-affected histograms. The purpose of the deconvolution is to provide automated classifiers with a higher quality N-dimensional histogram from which to obtain classification statistics.

  1. Statistical Model Analysis of (n, α Cross Sections for 4.0-6.5 MeV Neutrons

    Directory of Open Access Journals (Sweden)

    Khuukhenkhuu G.

    2016-01-01

    Full Text Available The statistical model based on the Weisskopf-Ewing theory and constant nuclear temperature approximation is used for systematical analysis of the 4.0-6.5 MeV neutron induced (n, α reaction cross sections. The α-clusterization effect was considered in the (n, α cross sections. A certain dependence of the (n, α cross sections on the relative neutron excess parameter of the target nuclei was observed. The systematic regularity of the (n, α cross sections behaviour is useful to estimate the same reaction cross sections for unstable isotopes. The results of our analysis can be used for nuclear astrophysical calculations such as helium burning and possible branching in the s-process.

  2. Cross shore transport by wind-driven turbidity plumes in western Lake Superior*

    Science.gov (United States)

    Turbidity plumes frequently occur in the western arm of Lake Superior and may represent a significant cross shelf transport mechanism for sediment, nutrient and biota. We characterize a plume that formed in late April 2016 using observations from in situ sensors and remote sensin...

  3. The momentum transfer cross section and transport coefficients for low energy electrons in mercury

    International Nuclear Information System (INIS)

    McEachran, R P; Elford, M T

    2003-01-01

    The momentum transfer cross section for electrons incident on mercury atoms has been determined from the solution of Dirac-Fock scattering equations which included both static and dynamic multipole polarization potentials as well as full anti-symmetrization to incorporate exchange effects. This cross section is in excellent agreement between 0.2 and 3.0 eV with the cross section derived from the most recent experimental measurements. The discrepancy below 0.2 eV has been investigated using two-term transport theory

  4. Inelastic cross-sections for electron transport in liquid water: a comparison of dielectric models

    International Nuclear Information System (INIS)

    Emfietzoglou, D.

    2003-01-01

    Various methodologies for constructing inelastic cross-sections for low-energy (<10 keV) electron transport in liquid water are presented and compared. They are all based on an optical-data model which provides the dependence on energy loss, and a dispersion algorithm which incorporates the momentum-transfer dependence. A Drude dielectric model was used to analytically represent the optical data. Various dispersion schemes were examined: the Bethe approximation, the δ-oscillator models of Ashley and Liljequist, and two forms of Ritchie's extended-Drude model. They all have been used in Monte-Carlo (MC) codes for analog electron transport in the condensed phase. Results in the form of differential and total inelastic cross-sections are presented. Where possible, comparisons with results of other studies are made. It was found that, despite the application of general constraints (e.g. sum rules), the optical model has a notable influence on the single-collision energy loss spectrum. In addition, both the shape and peak position of the total and differential cross-section distributions depend strongly on the dispersion model adopted. The work is particularly relevant to the development of event-by-event MC transport codes for liquid water, as well as, to the calculations of stopping-powers below the range of applicability of Bethe's formula

  5. Neutron secondary-particle production cross sections and their incorporation into Monte-Carlo transport codes

    International Nuclear Information System (INIS)

    Brenner, D.J.; Prael, R.E.; Little, R.C.

    1987-01-01

    Realistic simulations of the passage of fast neutrons through tissue require a large quantity of cross-sectional data. What are needed are differential (in particle type, energy and angle) cross sections. A computer code is described which produces such spectra for neutrons above ∼14 MeV incident on light nuclei such as carbon and oxygen. Comparisons have been made with experimental measurements of double-differential secondary charged-particle production on carbon and oxygen at energies from 27 to 60 MeV; they indicate that the model is adequate in this energy range. In order to utilize fully the results of these calculations, they should be incorporated into a neutron transport code. This requires defining a generalized format for describing charged-particle production, putting the calculated results in this format, interfacing the neutron transport code with these data, and charged-particle transport. The design and development of such a program is described. 13 refs., 3 figs

  6. Cross-shelf transport into nearshore waters due to shoaling internal tides in San Pedro Bay, CA

    Science.gov (United States)

    Noble, Marlene A.; Burt Jones,; Peter Hamilton,; Xu, Jingping; George Robertson,; Rosenfeld, Leslie; John Largier,

    2009-01-01

    In the summer of 2001, a coastal ocean measurement program in the southeastern portion of San Pedro Bay, CA, was designed and carried out. One aim of the program was to determine the strength and effectiveness of local cross-shelf transport processes. A particular objective was to assess the ability of semidiurnal internal tidal currents to move suspended material a net distance across the shelf. Hence, a dense array of moorings was deployed across the shelf to monitor the transport patterns associated with fluctuations in currents, temperature and salinity. An associated hydrographic program periodically monitored synoptic changes in the spatial patterns of temperature, salinity, nutrients and bacteria. This set of measurements show that a series of energetic internal tides can, but do not always, transport subthermocline water, dissolved and suspended material from the middle of the shelf into the surfzone. Effective cross-shelf transport occurs only when (1) internal tides at the shelf break are strong and (2) subtidal currents flow strongly downcoast. The subtidal downcoast flow causes isotherms to tilt upward toward the coast, which allows energetic, nonlinear internal tidal currents to carry subthermocline waters into the surfzone. During these events, which may last for several days, the transported water remains in the surfzone until the internal tidal current pulses and/or the downcoast subtidal currents disappear. This nonlinear internal tide cross-shelf transport process was capable of carrying water and the associated suspended or dissolved material from the mid-shelf into the surfzone, but there were no observation of transport from the shelf break into the surfzone. Dissolved nutrients and suspended particulates (such as phytoplankton) transported from the mid-shelf into the nearshore region by nonlinear internal tides may contribute to nearshore algal blooms, including harmful algal blooms that occur off local beaches.

  7. Classification of lung sounds using higher-order statistics: A divide-and-conquer approach.

    Science.gov (United States)

    Naves, Raphael; Barbosa, Bruno H G; Ferreira, Danton D

    2016-06-01

    Lung sound auscultation is one of the most commonly used methods to evaluate respiratory diseases. However, the effectiveness of this method depends on the physician's training. If the physician does not have the proper training, he/she will be unable to distinguish between normal and abnormal sounds generated by the human body. Thus, the aim of this study was to implement a pattern recognition system to classify lung sounds. We used a dataset composed of five types of lung sounds: normal, coarse crackle, fine crackle, monophonic and polyphonic wheezes. We used higher-order statistics (HOS) to extract features (second-, third- and fourth-order cumulants), Genetic Algorithms (GA) and Fisher's Discriminant Ratio (FDR) to reduce dimensionality, and k-Nearest Neighbors and Naive Bayes classifiers to recognize the lung sound events in a tree-based system. We used the cross-validation procedure to analyze the classifiers performance and the Tukey's Honestly Significant Difference criterion to compare the results. Our results showed that the Genetic Algorithms outperformed the Fisher's Discriminant Ratio for feature selection. Moreover, each lung class had a different signature pattern according to their cumulants showing that HOS is a promising feature extraction tool for lung sounds. Besides, the proposed divide-and-conquer approach can accurately classify different types of lung sounds. The classification accuracy obtained by the best tree-based classifier was 98.1% for classification accuracy on training, and 94.6% for validation data. The proposed approach achieved good results even using only one feature extraction tool (higher-order statistics). Additionally, the implementation of the proposed classifier in an embedded system is feasible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  8. A cascade of classifiers for extracting medication information from discharge summaries

    Directory of Open Access Journals (Sweden)

    Halgrim Scott

    2011-07-01

    Full Text Available Abstract Background Extracting medication information from clinical records has many potential applications, and recently published research, systems, and competitions reflect an interest therein. Much of the early extraction work involved rules and lexicons, but more recently machine learning has been applied to the task. Methods We present a hybrid system consisting of two parts. The first part, field detection, uses a cascade of statistical classifiers to identify medication-related named entities. The second part uses simple heuristics to link those entities into medication events. Results The system achieved performance that is comparable to other approaches to the same task. This performance is further improved by adding features that reference external medication name lists. Conclusions This study demonstrates that our hybrid approach outperforms purely statistical or rule-based systems. The study also shows that a cascade of classifiers works better than a single classifier in extracting medication information. The system is available as is upon request from the first author.

  9. 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

  10. Accurate corresponding point search using sphere-attribute-image for statistical bone model generation

    International Nuclear Information System (INIS)

    Saito, Toki; Nakajima, Yoshikazu; Sugita, Naohiko; Mitsuishi, Mamoru; Hashizume, Hiroyuki; Kuramoto, Kouichi; Nakashima, Yosio

    2011-01-01

    Statistical deformable model based two-dimensional/three-dimensional (2-D/3-D) registration is a promising method for estimating the position and shape of patient bone in the surgical space. Since its accuracy depends on the statistical model capacity, we propose a method for accurately generating a statistical bone model from a CT volume. Our method employs the Sphere-Attribute-Image (SAI) and has improved the accuracy of corresponding point search in statistical model generation. At first, target bone surfaces are extracted as SAIs from the CT volume. Then the textures of SAIs are classified to some regions using Maximally-stable-extremal-regions methods. Next, corresponding regions are determined using Normalized cross-correlation (NCC). Finally, corresponding points in each corresponding region are determined using NCC. The application of our method to femur bone models was performed, and worked well in the experiments. (author)

  11. Statistical Analysis of the Impacts of Regional Transportation on the Air Quality in Beijing

    Science.gov (United States)

    Huang, Zhongwen; Zhang, Huiling; Tong, Lei; Xiao, Hang

    2016-04-01

    From October to December 2015, Beijing-Tianjin-Hebei (BTH) region had experienced several severe haze events. In order to assess the effects of the regional transportation on the air quality in Beijing, the air monitoring data (PM2.5, SO2, NO2 and CO) from that period published by Chinese National Environmental Monitoring Center (CNEMC) was collected and analyzed with various statistical models. The cities within BTH area were clustered into three groups according to the geographical conditions, while the air pollutant concentrations of cities within a group sharing similar variation trends. The Granger causality test results indicate that significant causal relationships exist between the air pollutant data of Beijing and its surrounding cities (Baoding, Chengde, Tianjin and Zhangjiakou) for the reference period. Then, linear regression models were constructed to capture the interdependency among the multiple time series. It shows that the observed air pollutant concentrations in Beijing were well consistent with the model-fitted results. More importantly, further analysis suggests that the air pollutants in Beijing were strongly affected by regional transportation, as the local sources only contributed 17.88%, 27.12%, 14.63% and 31.36% of PM2.5, SO2, NO2 and CO concentrations, respectively. And the major foreign source for Beijing was from Southwest (Baoding) direction, account for more than 42% of all these air pollutants. Thus, by combining various statistical models, it may not only be able to quickly predict the air qualities of any cities on a regional scale, but also to evaluate the local and regional source contributions for a particular city. Key words: regional transportation, air pollution, Granger causality test, statistical models

  12. Evaluation of 10 cross-shore sediment transport morphological models

    CSIR Research Space (South Africa)

    Schoonees, JS

    1995-05-01

    Full Text Available .S. Schoonees, A.K. Theron/Coastal Engineering 25 (1995) 141 11 0.99 m cross-shore transport rate above mean sea level during the storm < 123 m3/m 0 m < storm surge < 3.2 m 4.2 h..., are beach and dune erosion that occurs under storm waves and high water levels, prediction of set-back lines, adjustment of beach-fill to long-term wave action and the prediction of sediment build-up or beach profile...

  13. Statistical analysis of correlated experimental data and neutron cross section evaluation

    International Nuclear Information System (INIS)

    Badikov, S.A.

    1998-01-01

    The technique for evaluation of neutron cross sections on the basis of statistical analysis of correlated experimental data is presented. The most important stages of evaluation beginning from compilation of correlation matrix for measurement uncertainties till representation of the analysis results in the ENDF-6 format are described in details. Special attention is paid to restrictions (positive uncertainty) on covariation matrix of approximate parameters uncertainties generated within the method of least square fit which is derived from physical reasons. The requirements for source experimental data assuring satisfaction of the restrictions mentioned above are formulated. Correlation matrices of measurement uncertainties in particular should be also positively determined. Variants of modelling the positively determined correlation matrices of measurement uncertainties in a situation when their consequent calculation on the basis of experimental information is impossible are discussed. The technique described is used for creating the new generation of estimates of dosimetric reactions cross sections for the first version of the Russian dosimetric file (including nontrivial covariation information)

  14. Thermally Cross-Linkable Hole Transport Materials for Solution Processed Phosphorescent OLEDs

    Science.gov (United States)

    Kim, Beom Seok; Kim, Ohyoung; Chin, Byung Doo; Lee, Chil Won

    2018-04-01

    Materials for unique fabrication of a solution-processed, multi-layered organic light-emitting diode (OLED) were developed. Preparation of a hole transport layer with a thermally cross-linkable chemical structure, which can be processed to form a thin film and then transformed into an insoluble film by using an amine-alcohol condensation reaction with heat treatment, was investigated. Functional groups, such as triplenylamine linked with phenylcarbazole or biphenyl, were employed in the chemical structure of the hole transport layer in order to maintain high triplet energy properties. When phenylcarbazole or biphenyl compounds continuously react with triphenylamine under acid catalysis, a chemically stable thin film material with desirable energy-level properties for a blue OLED could be obtained. The prepared hole transport materials showed excellent surface roughness and thermal stability in comparison with the commercial reference material. On the solution-processed model hole transport layer, we fabricated a device with a blue phosphorescent OLED by using sequential vacuum deposition. The maximum external quantum, 19.3%, was improved by more than 40% over devices with the commercial reference material (11.4%).

  15. Statistical investigation of avalanches of three-dimensional small-world networks and their boundary and bulk cross-sections

    Science.gov (United States)

    Najafi, M. N.; Dashti-Naserabadi, H.

    2018-03-01

    In many situations we are interested in the propagation of energy in some portions of a three-dimensional system with dilute long-range links. In this paper, a sandpile model is defined on the three-dimensional small-world network with real dissipative boundaries and the energy propagation is studied in three dimensions as well as the two-dimensional cross-sections. Two types of cross-sections are defined in the system, one in the bulk and another in the system boundary. The motivation of this is to make clear how the statistics of the avalanches in the bulk cross-section tend to the statistics of the dissipative avalanches, defined in the boundaries as the concentration of long-range links (α ) increases. This trend is numerically shown to be a power law in a manner described in the paper. Two regimes of α are considered in this work. For sufficiently small α s the dominant behavior of the system is just like that of the regular BTW, whereas for the intermediate values the behavior is nontrivial with some exponents that are reported in the paper. It is shown that the spatial extent up to which the statistics is similar to the regular BTW model scales with α just like the dissipative BTW model with the dissipation factor (mass in the corresponding ghost model) m2˜α for the three-dimensional system as well as its two-dimensional cross-sections.

  16. Experimental observations of Lagrangian sand grain kinematics under bedload transport: statistical description of the step and rest regimes

    Science.gov (United States)

    Guala, M.; Liu, M.

    2017-12-01

    The kinematics of sediment particles is investigated by non-intrusive imaging methods to provide a statistical description of bedload transport in conditions near the threshold of motion. In particular, we focus on the cyclic transition between motion and rest regimes to quantify the waiting time statistics inferred to be responsible for anomalous diffusion, and so far elusive. Despite obvious limitations in the spatio-temporal domain of the observations, we are able to identify the probability distributions of the particle step time and length, velocity, acceleration, waiting time, and thus distinguish which quantities exhibit well converged mean values, based on the thickness of their respective tails. The experimental results shown here for four different transport conditions highlight the importance of the waiting time distribution and represent a benchmark dataset for the stochastic modeling of bedload transport.

  17. Performance of oil industry cross-country pipelines in Western Europe: statistical summary of reported spillages, 1979

    Energy Technology Data Exchange (ETDEWEB)

    de Waal, A.; Hayward, P.; Panisi, C.; Groenhof, J.

    This report presents statistical data relating to spillages from oil industry cross-country pipelines during the calendar year 1979, with comments and comparisons for the five year period 1975-1979. (Copyright (c) CONCAWE 1980.)

  18. Proposed hybrid-classifier ensemble algorithm to map snow cover area

    Science.gov (United States)

    Nijhawan, Rahul; Raman, Balasubramanian; Das, Josodhir

    2018-01-01

    Metaclassification ensemble approach is known to improve the prediction performance of snow-covered area. The methodology adopted in this case is based on neural network along with four state-of-art machine learning algorithms: support vector machine, artificial neural networks, spectral angle mapper, K-mean clustering, and a snow index: normalized difference snow index. An AdaBoost ensemble algorithm related to decision tree for snow-cover mapping is also proposed. According to available literature, these methods have been rarely used for snow-cover mapping. Employing the above techniques, a study was conducted for Raktavarn and Chaturangi Bamak glaciers, Uttarakhand, Himalaya using multispectral Landsat 7 ETM+ (enhanced thematic mapper) image. The study also compares the results with those obtained from statistical combination methods (majority rule and belief functions) and accuracies of individual classifiers. Accuracy assessment is performed by computing the quantity and allocation disagreement, analyzing statistic measures (accuracy, precision, specificity, AUC, and sensitivity) and receiver operating characteristic curves. A total of 225 combinations of parameters for individual classifiers were trained and tested on the dataset and results were compared with the proposed approach. It was observed that the proposed methodology produced the highest classification accuracy (95.21%), close to (94.01%) that was produced by the proposed AdaBoost ensemble algorithm. From the sets of observations, it was concluded that the ensemble of classifiers produced better results compared to individual classifiers.

  19. Lack of cross-shelf transport of sediments on the western margin of India: Evidence from clay mineralogy

    Digital Repository Service at National Institute of Oceanography (India)

    Ramaswamy, V.; Nair, R.R.

    transported long distances along the shelf, cross-shelf transport appears to be minimal. Confirmatory evidence of qualitative differences in outer and inner shelf clays is provided by sediment trap clay mineralogy on the outer shelf. Clay bound pollutant...

  20. Cross Sections and Transport Properties of BR- Ions in AR

    Science.gov (United States)

    Jovanovic, Jasmina; Stojanovic, Vladimir; Raspopovic, Zoran; Petrovic, Zoran

    2014-10-01

    We have used a combination of a simple semi-analytic theory - Momentum Transfer Theory (MTT) and exact Monte Carlo (MC) simulations to develop Br- in Ar momentum transfer cross section based on the available data for reduced mobility at the temperature T = 300 K over the range 10 Td higher energies based on behavior of similar ions in similar gases and by the addition of the total detachment cross section that was used from the threshold around 7.7 eV. Relatively complete set was derived which can be used in modeling of plasmas by both hybrid, particle in cell (PIC) and fluid codes. A good agreement between calculated and measured ion mobilities and longitudinal diffusion coefficients is an independent proof of the validity of the cross sections that were derived for the negative ion mobility data. In addition to transport coefficients we have also calculated the net rate coefficients of elastic scattering and detachment. Author acknowledge Ministry of Education, Science and Technology, Proj. Nos. 171037 and 410011.

  1. Statistical inference methods for two crossing survival curves: a comparison of methods.

    Science.gov (United States)

    Li, Huimin; Han, Dong; Hou, Yawen; Chen, Huilin; Chen, Zheng

    2015-01-01

    A common problem that is encountered in medical applications is the overall homogeneity of survival distributions when two survival curves cross each other. A survey demonstrated that under this condition, which was an obvious violation of the assumption of proportional hazard rates, the log-rank test was still used in 70% of studies. Several statistical methods have been proposed to solve this problem. However, in many applications, it is difficult to specify the types of survival differences and choose an appropriate method prior to analysis. Thus, we conducted an extensive series of Monte Carlo simulations to investigate the power and type I error rate of these procedures under various patterns of crossing survival curves with different censoring rates and distribution parameters. Our objective was to evaluate the strengths and weaknesses of tests in different situations and for various censoring rates and to recommend an appropriate test that will not fail for a wide range of applications. Simulation studies demonstrated that adaptive Neyman's smooth tests and the two-stage procedure offer higher power and greater stability than other methods when the survival distributions cross at early, middle or late times. Even for proportional hazards, both methods maintain acceptable power compared with the log-rank test. In terms of the type I error rate, Renyi and Cramér-von Mises tests are relatively conservative, whereas the statistics of the Lin-Xu test exhibit apparent inflation as the censoring rate increases. Other tests produce results close to the nominal 0.05 level. In conclusion, adaptive Neyman's smooth tests and the two-stage procedure are found to be the most stable and feasible approaches for a variety of situations and censoring rates. Therefore, they are applicable to a wider spectrum of alternatives compared with other tests.

  2. Analysis of proton-induced fragment production cross sections by the Quantum Molecular Dynamics plus Statistical Decay Model

    Energy Technology Data Exchange (ETDEWEB)

    Chiba, Satoshi; Iwamoto, Osamu; Fukahori, Tokio; Niita, Koji; Maruyama, Toshiki; Maruyama, Tomoyuki; Iwamoto, Akira [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    1997-03-01

    The production cross sections of various fragments from proton-induced reactions on {sup 56}Fe and {sup 27}Al have been analyzed by the Quantum Molecular Dynamics (QMD) plus Statistical Decay Model (SDM). It was found that the mass and charge distributions calculated with and without the statistical decay have very different shapes. These results also depend strongly on the impact parameter, showing an importance of the dynamical treatment as realized by the QMD approach. The calculated results were compared with experimental data in the energy region from 50 MeV to 5 GeV. The QMD+SDM calculation could reproduce the production cross sections of the light clusters and intermediate-mass to heavy fragments in a good accuracy. The production cross section of {sup 7}Be was, however, underpredicted by approximately 2 orders of magnitude, showing the necessity of another reaction mechanism not taken into account in the present model. (author)

  3. Periodontal health status of transport workers of a union territory in India: A cross-sectional study

    Directory of Open Access Journals (Sweden)

    Ramandeep Singh Gambhir

    2015-01-01

    Full Text Available Background: Periodontal disease is one of the most prevalent dental diseases, which affects the adult population of the world, varying only in degree from mild to severe. Transport industry is considered an important pillar for socioeconomic development of any nation. The present study was carried out to assess the periodontal health status of transport workers working in Chandigarh Transport Undertaking (CTU buses, Chandigarh (Union territory. Materials and Methods: A cross-sectional study was conducted on all available CTU workers at all three bus depots. The data were recorded on a modified WHO format (1997. A total of 998 subjects were included for community periodontal index (CPI and attachment loss computations after doing necessary exclusions. Periodontal status was evaluated using CPI. Results: About 8.13% of the subjects had healthy periodontium while maximum subjects (73.2% had a score 2 (calculus as evaluated by CPI. 3.4% (12 of the subjects belonging to upper middle class had deep pockets as compared to 1.9% (10 of the subjects in the lower middle class. None of the subjects in the upper high, high, and upper middle socioeconomic status (SES category had a loss of attachment score 4. 25.9% of the postgraduates had a CPI score of 0 whereas 0.7% high school subjects had a loss of attachment score 4. Conclusion: Advanced periodontal disease (CPI score, 4 affected small number of subjects with maximum subjects (73% having a CPI score of 2. There was statistically significant association of SES and education level with the CPI score and loss of attachment level.

  4. EVALUATING A COMPUTER BASED SKILLS ACQUISITION TRAINER TO CLASSIFY BADMINTON PLAYERS

    Directory of Open Access Journals (Sweden)

    Minh Vu Huynh

    2011-09-01

    Full Text Available The aim of the present study was to compare the statistical ability of both neural networks and discriminant function analysis on the newly developed SATB program. Using these statistical tools, we identified the accuracy of the SATB in classifying badminton players into different skill level groups. Forty-one participants, classified as advanced, intermediate, or beginner skilled level, participated in this study. Results indicated neural networks are more effective in predicting group membership, and displayed higher predictive validity when compared to discriminant analysis. Using these outcomes, in conjunction with the physiological and biomechanical variables of the participants, we assessed the authenticity and accuracy of the SATB and commented on the overall effectiveness of the visual based training approach to training badminton athletes

  5. Absolute fragmentation cross sections in atom-molecule collisions : Scaling laws for non-statistical fragmentation of polycyclic aromatic hydrocarbon molecules

    NARCIS (Netherlands)

    Chen, T.; Gatchell, M.; Stockett, M. H.; Alexander, J. D.; Zhang, Y.; Rousseau, P.; Domaracka, A.; Maclot, S.; Delaunay, R.; Adoui, L.; Huber, B. A.; Schlathölter, T.; Schmidt, H. T.; Cederquist, H.; Zettergren, H.

    2014-01-01

    We present scaling laws for absolute cross sections for non-statistical fragmentation in collisions between Polycyclic Aromatic Hydrocarbons (PAH/PAH+) and hydrogen or helium atoms with kinetic energies ranging from 50 eV to 10 keV. Further, we calculate the total fragmentation cross sections

  6. Transport coefficients for electrons in argon in crossed electric and magnetic rf fields

    International Nuclear Information System (INIS)

    Raspopovic, Z M; Dujko, S; Makabe, T; Petrovic, Z Lj

    2005-01-01

    Monte Carlo simulations of electron transport have been performed in crossed electric and magnetic rf fields in argon. It was found that a magnetic field strongly affects electron transport, producing complex behaviour of the transport coefficients that cannot be predicted on the basis of dc field theory. In particular, it is important that a magnetic field, if it has sufficiently high amplitude, allows energy gain from the electric field only over a brief period of time, which leads to a pulse of directed motion and consequently to cyclotron oscillations being imprinted on the transport coefficients. Furthermore, this may lead to negative diffusion. The behaviour of drift velocities is also interesting, with a linear (sawtooth) dependence for the perpendicular drift velocity and bursts of drift for the longitudinal. Non-conservative effects are, on the other hand, reduced by the increasing magnetic field

  7. Radiation Transport in Random Media With Large Fluctuations

    Science.gov (United States)

    Olson, Aaron; Prinja, Anil; Franke, Brian

    2017-09-01

    Neutral particle transport in media exhibiting large and complex material property spatial variation is modeled by representing cross sections as lognormal random functions of space and generated through a nonlinear memory-less transformation of a Gaussian process with covariance uniquely determined by the covariance of the cross section. A Karhunen-Loève decomposition of the Gaussian process is implemented to effciently generate realizations of the random cross sections and Woodcock Monte Carlo used to transport particles on each realization and generate benchmark solutions for the mean and variance of the particle flux as well as probability densities of the particle reflectance and transmittance. A computationally effcient stochastic collocation method is implemented to directly compute the statistical moments such as the mean and variance, while a polynomial chaos expansion in conjunction with stochastic collocation provides a convenient surrogate model that also produces probability densities of output quantities of interest. Extensive numerical testing demonstrates that use of stochastic reduced-order modeling provides an accurate and cost-effective alternative to random sampling for particle transport in random media.

  8. Comparison between the International Physical Activity Questionnaire and the American College of Sports Medicine/American Heart Association criteria to classify the physical activity profile in adults.

    Science.gov (United States)

    de Moraes, Suzana Alves; Suzuki, Cláudio Shigueki; de Freitas, Isabel Cristina Martins

    2013-01-01

    the study aims to evaluate the reproducibility between the International Physical Activity Questionnaire and the American College of Sports Medicine/American Heart Association criteria to classify the physical activity profile in an adult population living in Ribeirão Preto, SP, Brazil. population-based cross-sectional study, including 930 adults of both genders. The reliability was evaluated by Kappa statistics, estimated according to socio-demographic strata. the kappa estimates showed good agreement between the two criteria in all strata. However, higher prevalence of "actives" was found by using the American College of Sports Medicine/American Heart Association. although the estimates have indicated good agreement, the findings suggest caution in choosing the criteria to classify physical activity profile mainly when "walking" is the main modality of physical activity.

  9. Passive Sonar Target Detection Using Statistical Classifier and Adaptive Threshold

    Directory of Open Access Journals (Sweden)

    Hamed Komari Alaie

    2018-01-01

    Full Text Available This paper presents the results of an experimental investigation about target detecting with passive sonar in Persian Gulf. Detecting propagated sounds in the water is one of the basic challenges of the researchers in sonar field. This challenge will be complex in shallow water (like Persian Gulf and noise less vessels. Generally, in passive sonar, the targets are detected by sonar equation (with constant threshold that increases the detection error in shallow water. The purpose of this study is proposed a new method for detecting targets in passive sonars using adaptive threshold. In this method, target signal (sound is processed in time and frequency domain. For classifying, Bayesian classification is used and posterior distribution is estimated by Maximum Likelihood Estimation algorithm. Finally, target was detected by combining the detection points in both domains using Least Mean Square (LMS adaptive filter. Results of this paper has showed that the proposed method has improved true detection rate by about 24% when compared other the best detection method.

  10. Rats classified as low or high cocaine locomotor responders: A unique model involving striatal dopamine transporters that predicts cocaine addiction-like behaviors

    Science.gov (United States)

    Yamamoto, Dorothy J.; Nelson, Anna M.; Mandt, Bruce H.; Larson, Gaynor A.; Rorabaugh, Jacki M.; Ng, Christopher M.C.; Barcomb, Kelsey M.; Richards, Toni L.; Allen, Richard M.; Zahniser, Nancy R.

    2013-01-01

    Individual differences are a hallmark of drug addiction. Here, we describe a rat model based on differential initial responsiveness to low dose cocaine. Despite similar brain cocaine levels, individual outbred Sprague-Dawley rats exhibit markedly different magnitudes of acute cocaine-induced locomotor activity and, thereby, can be classified as low or high cocaine responders (LCRs or HCRs). LCRs and HCRs differ in drug-induced, but not novelty-associated, hyperactivity. LCRs have higher basal numbers of striatal dopamine transporters (DATs) than HCRs and exhibit marginal cocaine inhibition of in vivo DAT activity and cocaine-induced increases in extracellular DA. Importantly, lower initial cocaine response predicts greater locomotor sensitization, conditioned place preference and greater motivation to self-administer cocaine following low dose acquisition. Further, outbred Long-Evans rats classified as LCRs, versus HCRs, are more sensitive to cocaine’s discriminative stimulus effects. Overall, results to date with the LCR/HCR model underscore the contribution of striatal DATs to individual differences in initial cocaine responsiveness and the value of assessing the influence of initial drug response on subsequent expression of addiction-like behaviors. PMID:23850581

  11. Total and fission cross-sections of 239Pu - statistical study of resonance parameters

    International Nuclear Information System (INIS)

    Derrien, H.; Blons, J.; Eggermann, C.; Michaudon, A.; Paya, D.; Ribon, P.

    1967-01-01

    The authors measured the total and fission cross-sections of 239 Pu with the linear accelerator at Saclay as a pulsed source of neutrons. The total cross-section was measured in the range from 4 to 700 eV and the best resolution used was 1.5 ns/m; the fission cross-section was measured between 4 eV and 6 keV, the best resolution having been 6 ns/m. The transmission measurements on five samples were made at the temperature of liquid nitrogen, and comparisons made with supplementary experiments at ambient temperature made it possible to determine the Doppler broadening factor (Δ = η√E). The resonances were identified from 4 to 500 eV in the total cross-section; the average level spacing was of the order of 2.4 eV. It would appear that, in this energy range, nearly all the levels were identified. The resonance parameters were determined by analysis of shape in conjunction with a least-squares programme on an IBM-7094 computer. The existence of a large number of broad resonances corresponding to very large fission widths has been shown to exist. Statistical study of the fission widths actually shows the existence of two families of resonances, one corresponding to a mean Γ f of the order of 45 meV and the other to a mean Γ/f of about 750 meV. The authors were therefore able to postulate a classification of resonances in terms of two spin states, the level population ratio in each family being: (2J 1 +1)/(2J 2 +1) = 1/3; J 1 = 0 corresponds to the broad resonances and J 2 = 1 to the narrow ones. The partial widths for radiative capture fluctuate slightly around a mean value of 40 meV. By using a multilevel programme, the authors were able to investigate the extent to which the existence of large fission widths might give rise to fictitious resonances (quasi-resonances) and perturbations and also to make a statistical study of the resonance parameters. (author) [fr

  12. Macroscopic cross sections for analyzing the transport of neutral particles in plasmas

    International Nuclear Information System (INIS)

    Suzuki, Tadakazu; Taji, Yuukichi; Nakahara, Yasuaki

    1975-05-01

    Algorithms have been developed for calculating the ionization and charge exchange cross sections required for analyzing the neutral transport in plasmas. In our algorithms, the integration of the expression for reaction rate of neutrals with plasmas is performed by expanding the integrand with the use of polynomials. At present, multi-energy-group sets of the cross sections depending on plasma temperature and energy of neutrals can be prepared by means of Maxwellian averages over energy. Calculational results are printed out in the FIDO format. Some numerical examples are given for several forms of spatial distributions assumed for the plasma ion temperature and source neutral energy. (auth.)

  13. Accuracy Evaluation of C4.5 and Naive Bayes Classifiers Using Attribute Ranking Method

    Directory of Open Access Journals (Sweden)

    S. Sivakumari

    2009-03-01

    Full Text Available This paper intends to classify the Ljubljana Breast Cancer dataset using C4.5 Decision Tree and Nai?ve Bayes classifiers. In this work, classification is carriedout using two methods. In the first method, dataset is analysed using all the attributes in the dataset. In the second method, attributes are ranked using information gain ranking technique and only the high ranked attributes are used to build the classification model. We are evaluating the results of C4.5 Decision Tree and Nai?ve Bayes classifiers in terms of classifier accuracy for various folds of cross validation. Our results show that both the classifiers achieve good accuracy on the dataset.

  14. Radiation transport in statistically inhomogeneous rocks

    International Nuclear Information System (INIS)

    Lukhminskij, B.E.

    1975-01-01

    A study has been made of radiation transfer in statistically inhomogeneous rocks. Account has been taken of the statistical character of rock composition through randomization of density. Formulas are summarized for sigma-distribution, homogeneous density, the Simpson and Cauchy distributions. Consideration is given to the statistics of mean square ranges in a medium, simulated by the jump Markov random function. A quantitative criterion of rock heterogeneity is proposed

  15. Thermal transport in low dimensions from statistical physics to nanoscale heat transfer

    CERN Document Server

    2016-01-01

    Understanding non-equilibrium properties of classical and quantum many-particle systems is one of the goals of contemporary statistical mechanics. Besides its own interest for the theoretical foundations of irreversible thermodynamics(e.g. of the Fourier's law of heat conduction), this topic is also relevant to develop innovative ideas for nanoscale thermal management with possible future applications to nanotechnologies and effective energetic resources. The first part of the volume (Chapters 1-6) describes the basic models, the phenomenology and the various theoretical approaches to understand heat transport in low-dimensional lattices (1D e 2D). The methods described will include equilibrium and nonequilibrium molecular dynamics simulations, hydrodynamic and kinetic approaches and the solution of stochastic models. The second part (Chapters 7-10) deals with applications to nano and microscale heat transfer, as for instance phononic transport in carbon-based nanomaterials, including the prominent case of na...

  16. Credit scoring using ensemble of various classifiers on reduced feature set

    Directory of Open Access Journals (Sweden)

    Dahiya Shashi

    2015-01-01

    Full Text Available Credit scoring methods are widely used for evaluating loan applications in financial and banking institutions. Credit score identifies if applicant customers belong to good risk applicant group or a bad risk applicant group. These decisions are based on the demographic data of the customers, overall business by the customer with bank, and loan payment history of the loan applicants. The advantages of using credit scoring models include reducing the cost of credit analysis, enabling faster credit decisions and diminishing possible risk. Many statistical and machine learning techniques such as Logistic Regression, Support Vector Machines, Neural Networks and Decision tree algorithms have been used independently and as hybrid credit scoring models. This paper proposes an ensemble based technique combining seven individual models to increase the classification accuracy. Feature selection has also been used for selecting important attributes for classification. Cross classification was conducted using three data partitions. German credit dataset having 1000 instances and 21 attributes is used in the present study. The results of the experiments revealed that the ensemble model yielded a very good accuracy when compared to individual models. In all three different partitions, the ensemble model was able to classify more than 80% of the loan customers as good creditors correctly. Also, for 70:30 partition there was a good impact of feature selection on the accuracy of classifiers. The results were improved for almost all individual models including the ensemble model.

  17. Coherent and correlated spin transport in nanoscale superconductors

    Energy Technology Data Exchange (ETDEWEB)

    Morten, Jan Petter

    2008-03-15

    Motivated by the desire for better understanding of nano electronic systems, we theoretically study the conductance and noise characteristics of current flow between superconductors, ferromagnets, and normal-metals. Such nano structures can reveal information about superconductor proximity effects, spin-relaxation processes, and spintronic effects with potential applications for different areas of mesoscopic physics. We employ the quasiclassical theory of superconductivity in the Keldysh formalism, and calculate the nonequilibrium transport of spin and charge using various approaches like the circuit theory of quantum transport and full counting statistics. For two of the studied structures, we have been able to compare our theory to experimental data and obtain good agreement. Transport and relaxation of spin polarized current in superconductors is governed by energy-dependent transport coefficients and spin-flip rates which are determined by quantum interference effects. We calculate the resulting temperature-dependent spin flow in ferromagnet-superconductor devices. Experimental data for spin accumulation and spin relaxation in a superconducting nano wire is in agreement with the theory, and allows for a spin-flip spectroscopy that determines the dominant mechanism for spin-flip relaxation in the studied samples. A ferromagnet precessing under resonance conditions can give rise to pure spin current injection into superconductors. We find that the absorbed spin current is measurable as a temperature dependent Gilbert damping, which we calculate and compare to experimental data. Crossed Andreev reflection denotes superconducting pairing of electrons flowing from different normal-metal or ferromagnet terminals into a superconductor. We calculate the nonlocal currents resulting from this process in competition with direct electron transport between the normal-metal terminals. We take dephasing into account, and study the nonlocal current when the types of contact in

  18. Non-statistically populated autoionizing levels of Li-like carbon: Hidden-crossings

    International Nuclear Information System (INIS)

    Deveney, E.F.; Krause, H.F.; Jones, N.L.

    1995-01-01

    The intensities of the Auger-electron lines from autoionizing (AI) states of Li-like (1s2s2l) configurations excited in ion-atom collisions vary as functions of the collision parameters such as, for example, the collision velocity. A statistical population of the three-electron levels is at best incomplete and underscores the intricate dynamical development of the electronic states. The authors compare several experimental studies to calculations using ''hidden-crossing'' techniques to explore some of the details of these Auger-electron intensity variation phenomena. The investigations show promising results suggesting that Auger-electron intensity variations can be used to probe collision dynamics

  19. Electron Cross-field Transport in a Miniaturized Cylindrical Hall Thruster

    International Nuclear Information System (INIS)

    Smirnov Artem; Raitses Yevgeny; Fisch Nathaniel J

    2005-01-01

    Conventional annular Hall thrusters become inefficient when scaled to low power. Cylindrical Hall thrusters, which have lower surface-to-volume ratio, are more promising for scaling down. They presently exhibit performance comparable with conventional annular Hall thrusters. The present paper gives a review of the experimental and numerical investigations of electron crossfield transport in the 2.6 cm miniaturized cylindrical Hall thruster (100 W power level). We show that, in order to explain the discharge current observed for the typical operating conditions, the electron anomalous collision frequency ν b has to be on the order of the Bohm value, ν B ∼ ω c /16. The contribution of electron-wall collisions to cross-field transport is found to be insignificant. The optimal regimes of thruster operation at low background pressure (below 10 -5 Torr) in the vacuum tank appear to be different from those at higher pressure (∼ 10 -4 Torr)

  20. Electroencephalography as a clinical tool for diagnosing and monitoring attention deficit hyperactivity disorder: a cross-sectional study

    Science.gov (United States)

    Helgadóttir, Halla; Gudmundsson, Ólafur Ó; Baldursson, Gísli; Magnússon, Páll; Blin, Nicolas; Brynjólfsdóttir, Berglind; Emilsdóttir, Ásdís; Gudmundsdóttir, Gudrún B; Lorange, Málfrídur; Newman, Paula K; Jóhannesson, Gísli H; Johnsen, Kristinn

    2015-01-01

    Objectives The aim of this study was to develop and test, for the first time, a multivariate diagnostic classifier of attention deficit hyperactivity disorder (ADHD) based on EEG coherence measures and chronological age. Setting The participants were recruited in two specialised centres and three schools in Reykjavik. Participants The data are from a large cross-sectional cohort of 310 patients with ADHD and 351 controls, covering an age range from 5.8 to 14 years. ADHD was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders fourth edition (DSM-IV) criteria using the K-SADS-PL semistructured interview. Participants in the control group were reported to be free of any mental or developmental disorders by their parents and had a score of less than 1.5 SDs above the age-appropriate norm on the ADHD Rating Scale-IV. Other than moderate or severe intellectual disability, no additional exclusion criteria were applied in order that the cohort reflected the typical cross section of patients with ADHD. Results Diagnostic classifiers were developed using statistical pattern recognition for the entire age range and for specific age ranges and were tested using cross-validation and by application to a separate cohort of recordings not used in the development process. The age-specific classification approach was more accurate (76% accuracy in the independent test cohort; 81% cross-validation accuracy) than the age-independent version (76%; 73%). Chronological age was found to be an important classification feature. Conclusions The novel application of EEG-based classification methods presented here can offer significant benefit to the clinician by improving both the accuracy of initial diagnosis and ongoing monitoring of children and adolescents with ADHD. The most accurate possible diagnosis at a single point in time can be obtained by the age-specific classifiers, but the age-independent classifiers are also useful as they enable longitudinal

  1. Validation of cross sections for Monte Carlo simulation of the photoelectric effect

    CERN Document Server

    Han, Min Cheol; Pia, Maria Grazia; Basaglia, Tullio; Batic, Matej; Hoff, Gabriela; Kim, Chan Hyeong; Saracco, Paolo

    2016-01-01

    Several total and partial photoionization cross section calculations, based on both theoretical and empirical approaches, are quantitatively evaluated with statistical analyses using a large collection of experimental data retrieved from the literature to identify the state of the art for modeling the photoelectric effect in Monte Carlo particle transport. Some of the examined cross section models are available in general purpose Monte Carlo systems, while others have been implemented and subjected to validation tests for the first time to estimate whether they could improve the accuracy of particle transport codes. The validation process identifies Scofield's 1973 non-relativistic calculations, tabulated in the Evaluated Photon Data Library(EPDL), as the one best reproducing experimental measurements of total cross sections. Specialized total cross section models, some of which derive from more recent calculations, do not provide significant improvements. Scofield's non-relativistic calculations are not surp...

  2. Classifying Microorganisms

    DEFF Research Database (Denmark)

    Sommerlund, Julie

    2006-01-01

    This paper describes the coexistence of two systems for classifying organisms and species: a dominant genetic system and an older naturalist system. The former classifies species and traces their evolution on the basis of genetic characteristics, while the latter employs physiological characteris......This paper describes the coexistence of two systems for classifying organisms and species: a dominant genetic system and an older naturalist system. The former classifies species and traces their evolution on the basis of genetic characteristics, while the latter employs physiological...... characteristics. The coexistence of the classification systems does not lead to a conflict between them. Rather, the systems seem to co-exist in different configurations, through which they are complementary, contradictory and inclusive in different situations-sometimes simultaneously. The systems come...

  3. Absolute fragmentation cross sections in atom-molecule collisions: Scaling laws for non-statistical fragmentation of polycyclic aromatic hydrocarbon molecules

    Energy Technology Data Exchange (ETDEWEB)

    Chen, T.; Gatchell, M.; Stockett, M. H.; Alexander, J. D.; Schmidt, H. T.; Cederquist, H.; Zettergren, H., E-mail: henning@fysik.su.se [Department of Physics, Stockholm University, S-106 91 Stockholm (Sweden); Zhang, Y. [Department of Mathematics, Faculty of Physics, M. V. Lomonosov Moscow State University, Leninskie Gory, 119991 Moscow (Russian Federation); Rousseau, P.; Maclot, S.; Delaunay, R.; Adoui, L. [CIMAP, UMR 6252, CEA/CNRS/ENSICAEN/Université de Caen Basse-Normandie, bd Henri Becquerel, BP 5133, F-14070 Caen Cedex 05 (France); Université de Caen Basse-Normandie, Esplanade de la Paix, F-14032 Caen (France); Domaracka, A.; Huber, B. A. [CIMAP, UMR 6252, CEA/CNRS/ENSICAEN/Université de Caen Basse-Normandie, bd Henri Becquerel, BP 5133, F-14070 Caen Cedex 05 (France); Schlathölter, T. [Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 4, 9747AG Groningen (Netherlands)

    2014-06-14

    We present scaling laws for absolute cross sections for non-statistical fragmentation in collisions between Polycyclic Aromatic Hydrocarbons (PAH/PAH{sup +}) and hydrogen or helium atoms with kinetic energies ranging from 50 eV to 10 keV. Further, we calculate the total fragmentation cross sections (including statistical fragmentation) for 110 eV PAH/PAH{sup +} + He collisions, and show that they compare well with experimental results. We demonstrate that non-statistical fragmentation becomes dominant for large PAHs and that it yields highly reactive fragments forming strong covalent bonds with atoms (H and N) and molecules (C{sub 6}H{sub 5}). Thus nonstatistical fragmentation may be an effective initial step in the formation of, e.g., Polycyclic Aromatic Nitrogen Heterocycles (PANHs). This relates to recent discussions on the evolution of PAHNs in space and the reactivities of defect graphene structures.

  4. Full counting statistics of level renormalization in electron transport through double quantum dots

    International Nuclear Information System (INIS)

    Luo Junyan; Shen Yu; Cen Gang; He Xiaoling; Wang Changrong; Jiao Hujun

    2011-01-01

    We examine the full counting statistics of electron transport through double quantum dots coupled in series, with particular attention being paid to the unique features originating from level renormalization. It is clearly illustrated that the energy renormalization gives rise to a dynamic charge blockade mechanism, which eventually results in super-Poissonian noise. Coupling of the double dots to an external heat bath leads to dephasing and relaxation mechanisms, which are demonstrated to suppress the noise in a unique way.

  5. Spreadsheet application to classify radioactive material for shipment

    International Nuclear Information System (INIS)

    Brown, A.N.

    1997-12-01

    A spreadsheet application has been developed at the Idaho National Engineering and Environmental Laboratory to aid the shipper when classifying nuclide mixtures of normal form, radioactive materials. The results generated by this spreadsheet are used to confirm the proper US Department of Transportation (DOT) classification when offering radioactive material packages for transport. The user must input to the spreadsheet the mass of the material being classified, the physical form (liquid or not), and the activity of each regulated nuclide. The spreadsheet uses these inputs to calculate two general values: (1) the specific activity of the material, and (2) a summation calculation of the nuclide content. The specific activity is used to determine if the material exceeds the DOT minimal threshold for a radioactive material (Yes or No). If the material is calculated to be radioactive, the specific activity is also used to determine if the material meets the activity requirement for one of the three Low Specific Activity designations (LSA-I, LSA-II, LSA-III, or Not LSA). Again, if the material is calculated to be radioactive, the summation calculation is then used to determine which activity category the material will meet (Limited Quantity, Type A, Type B, or Highway Route Controlled Quantity)

  6. Comparison of artificial intelligence classifiers for SIP attack data

    Science.gov (United States)

    Safarik, Jakub; Slachta, Jiri

    2016-05-01

    Honeypot application is a source of valuable data about attacks on the network. We run several SIP honeypots in various computer networks, which are separated geographically and logically. Each honeypot runs on public IP address and uses standard SIP PBX ports. All information gathered via honeypot is periodically sent to the centralized server. This server classifies all attack data by neural network algorithm. The paper describes optimizations of a neural network classifier, which lower the classification error. The article contains the comparison of two neural network algorithm used for the classification of validation data. The first is the original implementation of the neural network described in recent work; the second neural network uses further optimizations like input normalization or cross-entropy cost function. We also use other implementations of neural networks and machine learning classification algorithms. The comparison test their capabilities on validation data to find the optimal classifier. The article result shows promise for further development of an accurate SIP attack classification engine.

  7. A naïve Bayes classifier for planning transfusion requirements in heart surgery.

    Science.gov (United States)

    Cevenini, Gabriele; Barbini, Emanuela; Massai, Maria R; Barbini, Paolo

    2013-02-01

    Transfusion of allogeneic blood products is a key issue in cardiac surgery. Although blood conservation and standard transfusion guidelines have been published by different medical groups, actual transfusion practices after cardiac surgery vary widely among institutions. Models can be a useful support for decision making and may reduce the total cost of care. The objective of this study was to propose and evaluate a procedure to develop a simple locally customized decision-support system. We analysed 3182 consecutive patients undergoing cardiac surgery at the University Hospital of Siena, Italy. Univariate statistical tests were performed to identify a set of preoperative and intraoperative variables as likely independent features for planning transfusion quantities. These features were utilized to design a naïve Bayes classifier. Model performance was evaluated using the leave-one-out cross-validation approach. All computations were done using spss and matlab code. The overall correct classification percentage was not particularly high if several classes of patients were to be identified. Model performance improved appreciably when the patient sample was divided into two classes (transfused and non-transfused patients). In this case the naïve Bayes model correctly classified about three quarters of patients with 71.2% sensitivity and 78.4% specificity, thus providing useful information for recognizing patients with transfusion requirements in the specific scenario considered. Although the classifier is customized to a particular setting and cannot be generalized to other scenarios, the simplicity of its development and the results obtained make it a promising approach for designing a simple model for different heart surgery centres needing a customized decision-support system for planning transfusion requirements in intensive care unit. © 2011 Blackwell Publishing Ltd.

  8. Connectivity-based fixel enhancement: Whole-brain statistical analysis of diffusion MRI measures in the presence of crossing fibres

    Science.gov (United States)

    Raffelt, David A.; Smith, Robert E.; Ridgway, Gerard R.; Tournier, J-Donald; Vaughan, David N.; Rose, Stephen; Henderson, Robert; Connelly, Alan

    2015-01-01

    In brain regions containing crossing fibre bundles, voxel-average diffusion MRI measures such as fractional anisotropy (FA) are difficult to interpret, and lack within-voxel single fibre population specificity. Recent work has focused on the development of more interpretable quantitative measures that can be associated with a specific fibre population within a voxel containing crossing fibres (herein we use fixel to refer to a specific fibre population within a single voxel). Unfortunately, traditional 3D methods for smoothing and cluster-based statistical inference cannot be used for voxel-based analysis of these measures, since the local neighbourhood for smoothing and cluster formation can be ambiguous when adjacent voxels may have different numbers of fixels, or ill-defined when they belong to different tracts. Here we introduce a novel statistical method to perform whole-brain fixel-based analysis called connectivity-based fixel enhancement (CFE). CFE uses probabilistic tractography to identify structurally connected fixels that are likely to share underlying anatomy and pathology. Probabilistic connectivity information is then used for tract-specific smoothing (prior to the statistical analysis) and enhancement of the statistical map (using a threshold-free cluster enhancement-like approach). To investigate the characteristics of the CFE method, we assessed sensitivity and specificity using a large number of combinations of CFE enhancement parameters and smoothing extents, using simulated pathology generated with a range of test-statistic signal-to-noise ratios in five different white matter regions (chosen to cover a broad range of fibre bundle features). The results suggest that CFE input parameters are relatively insensitive to the characteristics of the simulated pathology. We therefore recommend a single set of CFE parameters that should give near optimal results in future studies where the group effect is unknown. We then demonstrate the proposed method

  9. A probability-conserving cross-section biasing mechanism for variance reduction in Monte Carlo particle transport calculations

    OpenAIRE

    Mendenhall, Marcus H.; Weller, Robert A.

    2011-01-01

    In Monte Carlo particle transport codes, it is often important to adjust reaction cross sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analogous Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross section change. This makes it possible t...

  10. Predicting Classifier Performance with Limited Training Data: Applications to Computer-Aided Diagnosis in Breast and Prostate Cancer

    Science.gov (United States)

    Basavanhally, Ajay; Viswanath, Satish; Madabhushi, Anant

    2015-01-01

    Clinical trials increasingly employ medical imaging data in conjunction with supervised classifiers, where the latter require large amounts of training data to accurately model the system. Yet, a classifier selected at the start of the trial based on smaller and more accessible datasets may yield inaccurate and unstable classification performance. In this paper, we aim to address two common concerns in classifier selection for clinical trials: (1) predicting expected classifier performance for large datasets based on error rates calculated from smaller datasets and (2) the selection of appropriate classifiers based on expected performance for larger datasets. We present a framework for comparative evaluation of classifiers using only limited amounts of training data by using random repeated sampling (RRS) in conjunction with a cross-validation sampling strategy. Extrapolated error rates are subsequently validated via comparison with leave-one-out cross-validation performed on a larger dataset. The ability to predict error rates as dataset size increases is demonstrated on both synthetic data as well as three different computational imaging tasks: detecting cancerous image regions in prostate histopathology, differentiating high and low grade cancer in breast histopathology, and detecting cancerous metavoxels in prostate magnetic resonance spectroscopy. For each task, the relationships between 3 distinct classifiers (k-nearest neighbor, naive Bayes, Support Vector Machine) are explored. Further quantitative evaluation in terms of interquartile range (IQR) suggests that our approach consistently yields error rates with lower variability (mean IQRs of 0.0070, 0.0127, and 0.0140) than a traditional RRS approach (mean IQRs of 0.0297, 0.0779, and 0.305) that does not employ cross-validation sampling for all three datasets. PMID:25993029

  11. Monoenergetic time-dependent neutron transport in an infinite medium with time-varying cross sections

    International Nuclear Information System (INIS)

    Ganapol, B.D.

    1987-01-01

    For almost 20 yr, the main thrust of the author's research has been the generation of as many benchmark solutions to the time-dependent monoenergetic neutron transport equation as possible. The major motivation behind this effort has been to provide code developers with highly accurate numerical solutions to serve as standards in the assessment of numerical transport algorithms. In addition, these solutions provide excellent educational tools since the important physical features of neutron transport are still present even though the problems solved are idealized. A secondary motivation, though of equal importance, is the intellectual stimulation and understanding provided by the combination of the analytical, numerical, and computational techniques required to obtain these solutions. Therefore, to further the benchmark development, the added complication of time-dependent cross sections in the one-group transport equation is considered here

  12. Assessing the Importance of Cross-Stream Transport in Bedload Flux Estimates from Migrating Dunes: Colorado River, Grand Canyon National Park

    Science.gov (United States)

    Leary, K. P.; Buscombe, D.; Schmeeckle, M.; Kaplinski, M. A.

    2017-12-01

    Bedforms are ubiquitous in sand-bedded rivers, and understanding their morphodynamics is key to quantifying bedload transport. As such, mechanistic understanding of the spatiotemporal details of sand transport through and over bedforms is paramount to quantifying total sediment flux in sand-bedded river systems. However, due to the complexity of bedform field geometries and migration in natural settings, our ability to relate migration to bedload flux, and to quantify the relative role of tractive and suspended processes in their dynamics, is incomplete. Recent flume and numerical investigations indicate the potential importance of cross-stream transport, a process previously regarded as secondary and diffusive, to the three-dimensionality of bedforms and spatially variable translation and deformation rates. This research seeks to understand and quantify the importance of cross-stream transport in bedform three-dimensionality in a field setting. This work utilizes a high-resolution (0.25 m grid) data set of bedforms migrating in the channel of the Colorado River in Grand Canyon National Park. This data set comprises multi-beam sonar surveys collected at 3 different flow discharges ( 283, 566, and 1076 m3/s) along a reach of the Colorado River just upstream of the Diamond Creek USGS gage. Data were collected every 6 minutes almost continuously for 12 hours. Using bed elevation profiles (BEPs), we extract detailed bedform geometrical data (i.e. bedform height, wavelength) and spatial sediment flux data over a suite of bedforms at each flow. Coupling this spatially extensive data with a generalized Exner equation, we conduct mass balance calculations that evaluate the possibility, and potential importance, of cross-stream transport in the spatial variability of translation and deformation rates. Preliminary results suggest that intra-dune cross-stream transport can partially account for changes in the planform shape of dunes and may play an important role in spatially

  13. Stack filter classifiers

    Energy Technology Data Exchange (ETDEWEB)

    Porter, Reid B [Los Alamos National Laboratory; Hush, Don [Los Alamos National Laboratory

    2009-01-01

    Just as linear models generalize the sample mean and weighted average, weighted order statistic models generalize the sample median and weighted median. This analogy can be continued informally to generalized additive modeels in the case of the mean, and Stack Filters in the case of the median. Both of these model classes have been extensively studied for signal and image processing but it is surprising to find that for pattern classification, their treatment has been significantly one sided. Generalized additive models are now a major tool in pattern classification and many different learning algorithms have been developed to fit model parameters to finite data. However Stack Filters remain largely confined to signal and image processing and learning algorithms for classification are yet to be seen. This paper is a step towards Stack Filter Classifiers and it shows that the approach is interesting from both a theoretical and a practical perspective.

  14. High-frequency limit of the transport cross section in scattering by an obstacle with impedance boundary conditions

    Energy Technology Data Exchange (ETDEWEB)

    Aleksenko, A I; Cruz, J P; Lakshtanov, E L [Department of Mathematics, Aveiro University, Aveiro 3810 (Portugal)], E-mail: lakshtanov@rambler.ru

    2008-06-27

    The scalar scattering of a plane wave by a strictly convex obstacle with impedance boundary conditions is considered. A uniform bound of the total cross section for all values of the frequency is presented. The high-frequency limit of the transport cross section is calculated and presented as a classical functional of the variational calculus.

  15. High-frequency limit of the transport cross section in scattering by an obstacle with impedance boundary conditions

    International Nuclear Information System (INIS)

    Aleksenko, A I; Cruz, J P; Lakshtanov, E L

    2008-01-01

    The scalar scattering of a plane wave by a strictly convex obstacle with impedance boundary conditions is considered. A uniform bound of the total cross section for all values of the frequency is presented. The high-frequency limit of the transport cross section is calculated and presented as a classical functional of the variational calculus

  16. A review and experimental study on the application of classifiers and evolutionary algorithms in EEG-based brain-machine interface systems

    Science.gov (United States)

    Tahernezhad-Javazm, Farajollah; Azimirad, Vahid; Shoaran, Maryam

    2018-04-01

    Objective. Considering the importance and the near-future development of noninvasive brain-machine interface (BMI) systems, this paper presents a comprehensive theoretical-experimental survey on the classification and evolutionary methods for BMI-based systems in which EEG signals are used. Approach. The paper is divided into two main parts. In the first part, a wide range of different types of the base and combinatorial classifiers including boosting and bagging classifiers and evolutionary algorithms are reviewed and investigated. In the second part, these classifiers and evolutionary algorithms are assessed and compared based on two types of relatively widely used BMI systems, sensory motor rhythm-BMI and event-related potentials-BMI. Moreover, in the second part, some of the improved evolutionary algorithms as well as bi-objective algorithms are experimentally assessed and compared. Main results. In this study two databases are used, and cross-validation accuracy (CVA) and stability to data volume (SDV) are considered as the evaluation criteria for the classifiers. According to the experimental results on both databases, regarding the base classifiers, linear discriminant analysis and support vector machines with respect to CVA evaluation metric, and naive Bayes with respect to SDV demonstrated the best performances. Among the combinatorial classifiers, four classifiers, Bagg-DT (bagging decision tree), LogitBoost, and GentleBoost with respect to CVA, and Bagging-LR (bagging logistic regression) and AdaBoost (adaptive boosting) with respect to SDV had the best performances. Finally, regarding the evolutionary algorithms, single-objective invasive weed optimization (IWO) and bi-objective nondominated sorting IWO algorithms demonstrated the best performances. Significance. We present a general survey on the base and the combinatorial classification methods for EEG signals (sensory motor rhythm and event-related potentials) as well as their optimization methods

  17. Least Square Support Vector Machine Classifier vs a Logistic Regression Classifier on the Recognition of Numeric Digits

    Directory of Open Access Journals (Sweden)

    Danilo A. López-Sarmiento

    2013-11-01

    Full Text Available In this paper is compared the performance of a multi-class least squares support vector machine (LSSVM mc versus a multi-class logistic regression classifier to problem of recognizing the numeric digits (0-9 handwritten. To develop the comparison was used a data set consisting of 5000 images of handwritten numeric digits (500 images for each number from 0-9, each image of 20 x 20 pixels. The inputs to each of the systems were vectors of 400 dimensions corresponding to each image (not done feature extraction. Both classifiers used OneVsAll strategy to enable multi-classification and a random cross-validation function for the process of minimizing the cost function. The metrics of comparison were precision and training time under the same computational conditions. Both techniques evaluated showed a precision above 95 %, with LS-SVM slightly more accurate. However the computational cost if we found a marked difference: LS-SVM training requires time 16.42 % less than that required by the logistic regression model based on the same low computational conditions.

  18. Angular finite volume method for solving the multigroup transport equation with piecewise average scattering cross sections

    International Nuclear Information System (INIS)

    Calloo, A.; Vidal, J.F.; Le Tellier, R.; Rimpault, G.

    2011-01-01

    This paper deals with the solving of the multigroup integro-differential form of the transport equation for fine energy group structure. In that case, multigroup transfer cross sections display strongly peaked shape for light scatterers and the current Legendre polynomial expansion is not well-suited to represent them. Furthermore, even if considering an exact scattering cross sections representation, the scattering source in the discrete ordinates method (also known as the Sn method) being calculated by sampling the angular flux at given directions, may be wrongly computed due to lack of angular support for the angular flux. Hence, following the work of Gerts and Matthews, an angular finite volume solver has been developed for 2D Cartesian geometries. It integrates the multigroup transport equation over discrete volume elements obtained by meshing the unit sphere with a product grid over the polar and azimuthal coordinates and by considering the integrated flux per solid angle element. The convergence of this method has been compared to the S_n method for a highly anisotropic benchmark. Besides, piecewise-average scattering cross sections have been produced for non-bound Hydrogen atoms using a free gas model for thermal neutrons. LWR lattice calculations comparing Legendre representations of the Hydrogen scattering multigroup cross section at various orders and piecewise-average cross sections for this same atom are carried out (while keeping a Legendre representation for all other isotopes). (author)

  19. The role of suspension events in cross-shore and longshore suspended sediment transport in the surf zone

    Science.gov (United States)

    Jaffe, Bruce E.

    2015-01-01

    Suspension of sand in the surf zone is intermittent. Especially striking in a time series of concentration are periods of intense suspension, suspension events, when the water column suspended sediment concentration is an order of magnitude greater than the mean concentration. The prevalence, timing, and contribution of suspension events to cross-shore and longshore suspended sediment transport are explored using field data collected in the inner half of the surf zone during a large storm at Duck, NC. Suspension events are defined as periods when the concentration is above a threshold. Events tended to occur during onshore flow under the wave crest, resulting in an onshore contribution to the suspended sediment transport. Even though large events occurred less than 10 percent of the total time, at some locations onshore transport associated with suspension events was greater than mean-current driven offshore-directed transport during non-event periods, causing the net suspended sediment transport to be onshore. Events and fluctuations in longshore velocity were not correlated. However, events did increase the longshore suspended sediment transport by approximately the amount they increase the mean concentration, which can be up to 35%. Because of the lack of correlation, the longshore suspended sediment transport can be modeled without considering the details of the intensity and time of events as the vertical integration of the product of the time-averaged longshore velocity and an event-augmented time-averaged concentration. However, to accurately model cross-shore suspended sediment transport, the timing and intensity of suspension events must be reproduced.

  20. Usefulness of current international air transport statistics

    Science.gov (United States)

    1999-05-01

    International air transportation is the fastest growing segment of transportation. It performs a major function in the globalization process and is a significant feature of the late 20th century. Public policy regarding international air transportati...

  1. Classifying a smoker scale in adult daily and nondaily smokers.

    Science.gov (United States)

    Pulvers, Kim; Scheuermann, Taneisha S; Romero, Devan R; Basora, Brittany; Luo, Xianghua; Ahluwalia, Jasjit S

    2014-05-01

    Smoker identity, or the strength of beliefs about oneself as a smoker, is a robust marker of smoking behavior. However, many nondaily smokers do not identify as smokers, underestimating their risk for tobacco-related disease and resulting in missed intervention opportunities. Assessing underlying beliefs about characteristics used to classify smokers may help explain the discrepancy between smoking behavior and smoker identity. This study examines the factor structure, reliability, and validity of the Classifying a Smoker scale among a racially diverse sample of adult smokers. A cross-sectional survey was administered through an online panel survey service to 2,376 current smokers who were at least 25 years of age. The sample was stratified to obtain equal numbers of 3 racial/ethnic groups (African American, Latino, and White) across smoking level (nondaily and daily smoking). The Classifying a Smoker scale displayed a single factor structure and excellent internal consistency (α = .91). Classifying a Smoker scores significantly increased at each level of smoking, F(3,2375) = 23.68, p smoker identity, stronger dependence on cigarettes, greater health risk perceptions, more smoking friends, and were more likely to carry cigarettes. Classifying a Smoker scores explained unique variance in smoking variables above and beyond that explained by smoker identity. The present study supports the use of the Classifying a Smoker scale among diverse, experienced smokers. Stronger endorsement of characteristics used to classify a smoker (i.e., stricter criteria) was positively associated with heavier smoking and related characteristics. Prospective studies are needed to inform prevention and treatment efforts.

  2. Neural network classifier of attacks in IP telephony

    Science.gov (United States)

    Safarik, Jakub; Voznak, Miroslav; Mehic, Miralem; Partila, Pavol; Mikulec, Martin

    2014-05-01

    Various types of monitoring mechanism allow us to detect and monitor behavior of attackers in VoIP networks. Analysis of detected malicious traffic is crucial for further investigation and hardening the network. This analysis is typically based on statistical methods and the article brings a solution based on neural network. The proposed algorithm is used as a classifier of attacks in a distributed monitoring network of independent honeypot probes. Information about attacks on these honeypots is collected on a centralized server and then classified. This classification is based on different mechanisms. One of them is based on the multilayer perceptron neural network. The article describes inner structure of used neural network and also information about implementation of this network. The learning set for this neural network is based on real attack data collected from IP telephony honeypot called Dionaea. We prepare the learning set from real attack data after collecting, cleaning and aggregation of this information. After proper learning is the neural network capable to classify 6 types of most commonly used VoIP attacks. Using neural network classifier brings more accurate attack classification in a distributed system of honeypots. With this approach is possible to detect malicious behavior in a different part of networks, which are logically or geographically divided and use the information from one network to harden security in other networks. Centralized server for distributed set of nodes serves not only as a collector and classifier of attack data, but also as a mechanism for generating a precaution steps against attacks.

  3. Aquelarre. A computer code for fast neutron cross sections from the statistical model

    International Nuclear Information System (INIS)

    Guasp, J.

    1974-01-01

    A Fortran V computer code for Univac 1108/6 using the partial statistical (or compound nucleus) model is described. The code calculates fast neutron cross sections for the (n, n'), (n, p), (n, d) and (n, α reactions and the angular distributions and Legendre moments.for the (n, n) and (n, n') processes in heavy and intermediate spherical nuclei. A local Optical Model with spin-orbit interaction for each level is employed, allowing for the width fluctuation and Moldauer corrections, as well as the inclusion of discrete and continuous levels. (Author) 67 refs

  4. Development of statistical linear regression model for metals from transportation land uses.

    Science.gov (United States)

    Maniquiz, Marla C; Lee, Soyoung; Lee, Eunju; Kim, Lee-Hyung

    2009-01-01

    The transportation landuses possessing impervious surfaces such as highways, parking lots, roads, and bridges were recognized as the highly polluted non-point sources (NPSs) in the urban areas. Lots of pollutants from urban transportation are accumulating on the paved surfaces during dry periods and are washed-off during a storm. In Korea, the identification and monitoring of NPSs still represent a great challenge. Since 2004, the Ministry of Environment (MOE) has been engaged in several researches and monitoring to develop stormwater management policies and treatment systems for future implementation. The data over 131 storm events during May 2004 to September 2008 at eleven sites were analyzed to identify correlation relationships between particulates and metals, and to develop simple linear regression (SLR) model to estimate event mean concentration (EMC). Results indicate that there was no significant relationship between metals and TSS EMC. However, the SLR estimation models although not providing useful results are valuable indicators of high uncertainties that NPS pollution possess. Therefore, long term monitoring employing proper methods and precise statistical analysis of the data should be undertaken to eliminate these uncertainties.

  5. BTS statistical standards manual

    Science.gov (United States)

    2005-10-01

    The Bureau of Transportation Statistics (BTS), like other federal statistical agencies, establishes professional standards to guide the methods and procedures for the collection, processing, storage, and presentation of statistical data. Standards an...

  6. A comparative study of machine learning classifiers for modeling travel mode choice

    NARCIS (Netherlands)

    Hagenauer, J; Helbich, M

    2017-01-01

    The analysis of travel mode choice is an important task in transportation planning and policy making in order to understand and predict travel demands. While advances in machine learning have led to numerous powerful classifiers, their usefulness for modeling travel mode choice remains largely

  7. ZZ HPICE/F, Gamma Interaction Cross-Section Library in ENDF/B Format for Transport Calculation

    International Nuclear Information System (INIS)

    1984-01-01

    Nature of physical problem solved: Format: ENDF/B file 23; Number of groups: Point Cross Sections, energies 1 keV to 100 MeV. Nuclides: Z = 1-83, 86, 90, 92 an 94. Origin: Lawrence Livermore Laboratory; Weighting spectrum: none. The data are for use in general purpose gamma-ray transport codes. The Lawrence Livermore Laboratory has a continuing program to evaluate photon cross section. The data are given in units of (barns/atom) for energies 1 keV to 100 MeV and for elements Z = 1-83, 86, 90, 92 and 94. The MAT numbers are equal to the atomic numbers (Z). The following cross sections are tabulated: MT cross section type: 501 total; 502 coherent scattering; 504 incoherent scattering; 516 pair production (includes triplet); 603 photoelectric

  8. Driver's behavioural changes with new intelligent transport system interventions at railway level crossings--A driving simulator study.

    Science.gov (United States)

    Larue, Grégoire S; Kim, Inhi; Rakotonirainy, Andry; Haworth, Narelle L; Ferreira, Luis

    2015-08-01

    Improving safety at railway level crossings is an important issue for the Australian transport system. Governments, the rail industry and road organisations have tried a variety of countermeasures for many years to improve railway level crossing safety. New types of intelligent transport system (ITS) interventions are now emerging due to the availability and the affordability of technology. These interventions target both actively and passively protected railway level crossings and attempt to address drivers' errors at railway crossings, which are mainly a failure to detect the crossing or the train and misjudgement of the train approach speed and distance. This study aims to assess the effectiveness of three emerging ITS that the rail industry considers implementing in Australia: a visual in-vehicle ITS, an audio in-vehicle ITS, as well as an on-road flashing beacons intervention. The evaluation was conducted on an advanced driving simulator with 20 participants per trialled technology, each participant driving once without any technology and once with one of the ITS interventions. Every participant drove through a range of active and passive crossings with and without trains approaching. Their speed approach of the crossing, head movements and stopping compliance were measured. Results showed that driver behaviour was changed with the three ITS interventions at passive crossings, while limited effects were found at active crossings, even with reduced visibility. The on-road intervention trialled was unsuccessful in improving driver behaviour; the audio and visual ITS improved driver behaviour when a train was approaching. A trend toward worsening driver behaviour with the visual ITS was observed when no trains were approaching. This trend was not observed for the audio ITS intervention, which appears to be the ITS intervention with the highest potential for improving safety at passive crossings. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. A study of two unsupervised data driven statistical methodologies for detecting and classifying damages in structural health monitoring

    Science.gov (United States)

    Tibaduiza, D.-A.; Torres-Arredondo, M.-A.; Mujica, L. E.; Rodellar, J.; Fritzen, C.-P.

    2013-12-01

    This article is concerned with the practical use of Multiway Principal Component Analysis (MPCA), Discrete Wavelet Transform (DWT), Squared Prediction Error (SPE) measures and Self-Organizing Maps (SOM) to detect and classify damages in mechanical structures. The formalism is based on a distributed piezoelectric active sensor network for the excitation and detection of structural dynamic responses. Statistical models are built using PCA when the structure is known to be healthy either directly from the dynamic responses or from wavelet coefficients at different scales representing Time-frequency information. Different damages on the tested structures are simulated by adding masses at different positions. The data from the structure in different states (damaged or not) are then projected into the different principal component models by each actuator in order to obtain the input feature vectors for a SOM from the scores and the SPE measures. An aircraft fuselage from an Airbus A320 and a multi-layered carbon fiber reinforced plastic (CFRP) plate are used as examples to test the approaches. Results are presented, compared and discussed in order to determine their potential in structural health monitoring. These results showed that all the simulated damages were detectable and the selected features proved capable of separating all damage conditions from the undamaged state for both approaches.

  10. Active transport among Czech school-aged children

    Directory of Open Access Journals (Sweden)

    Jan Pavelka

    2012-09-01

    Full Text Available BACKGROUND: Active transport is a very important factor for increasing the level of physical activity in children, which is significant for both their health and positive physical behaviour in adult age. OBJECTIVE: The aim of the study was to establish the proportion of Czech children aged 11 to 15 who select active transport to and from school and, at the same time, describe socio-economic and socio-demographic factors influencing active transport to and from school among children. METHODS: To establish the socio-demographic factors affecting active transport, data of a national representative sample of 11 to 15 year-old elementary school children in the Czech Republic (n = 4,425. Research data collection was performed within an international research study called Health Behaviour in School Aged Children in June 2010. Statistical processing of the results was made using a logistic regression analysis in the statistical programme IBM SPSS v 20. RESULTS: Active transport to and from school is opted for in the Czech Republic by approximately 2/3 of children aged 11 to 15. Differences between genders are not statistically significant; most children opting for active transport are aged 11 (69%. An important factor increasing the probability of active transport as much as 16 times is whether a child's place of residence is in the same municipality as the school. Other factors influencing this choice include BMI, time spent using a computer or a privateroom in a family. A significant factor determining active transport by children is safety; safe road crossing, opportunity to leave a bicycle safely at school, no fear of being assaulted on the way or provision of school lockers where children can leave their items. CONCLUSIONS: Active transport plays an important role in increasing the overall level of physical activity in children. Promotion of active transport should focus on children who spend more time using a computer; attention should also be

  11. Statistical methods of discrimination and classification advances in theory and applications

    CERN Document Server

    Choi, Sung C

    1986-01-01

    Statistical Methods of Discrimination and Classification: Advances in Theory and Applications is a collection of papers that tackles the multivariate problems of discriminating and classifying subjects into exclusive population. The book presents 13 papers that cover that advancement in the statistical procedure of discriminating and classifying. The studies in the text primarily focus on various methods of discriminating and classifying variables, such as multiple discriminant analysis in the presence of mixed continuous and categorical data; choice of the smoothing parameter and efficiency o

  12. Angular finite volume method for solving the multigroup transport equation with piecewise average scattering cross sections

    Energy Technology Data Exchange (ETDEWEB)

    Calloo, A.; Vidal, J.F.; Le Tellier, R.; Rimpault, G., E-mail: ansar.calloo@cea.fr, E-mail: jean-francois.vidal@cea.fr, E-mail: romain.le-tellier@cea.fr, E-mail: gerald.rimpault@cea.fr [CEA, DEN, DER/SPRC/LEPh, Saint-Paul-lez-Durance (France)

    2011-07-01

    This paper deals with the solving of the multigroup integro-differential form of the transport equation for fine energy group structure. In that case, multigroup transfer cross sections display strongly peaked shape for light scatterers and the current Legendre polynomial expansion is not well-suited to represent them. Furthermore, even if considering an exact scattering cross sections representation, the scattering source in the discrete ordinates method (also known as the Sn method) being calculated by sampling the angular flux at given directions, may be wrongly computed due to lack of angular support for the angular flux. Hence, following the work of Gerts and Matthews, an angular finite volume solver has been developed for 2D Cartesian geometries. It integrates the multigroup transport equation over discrete volume elements obtained by meshing the unit sphere with a product grid over the polar and azimuthal coordinates and by considering the integrated flux per solid angle element. The convergence of this method has been compared to the S{sub n} method for a highly anisotropic benchmark. Besides, piecewise-average scattering cross sections have been produced for non-bound Hydrogen atoms using a free gas model for thermal neutrons. LWR lattice calculations comparing Legendre representations of the Hydrogen scattering multigroup cross section at various orders and piecewise-average cross sections for this same atom are carried out (while keeping a Legendre representation for all other isotopes). (author)

  13. Evaluation of the (n,xn) and (n,xnf) cross sections for heavy nuclei with the statistical model

    International Nuclear Information System (INIS)

    Jary, J.

    1975-01-01

    A method was presented to calculate the (n,xn) and (n,xnf) cross sections for the heavy nuclei having mass numbers of 232 1) without fission, according to the law of conventional statistical models, in the (n,xn) process. Fission can also compete with the emission of neutrons and γ-ray for the nuclei and the excitation energy considered. The fission cross sections of 235 U and 238 U recently evaluated by Sowerby and the fission cross section of 236 U have been used to determine the other parameters needed in the calculation. The fission widths of 239 U and 238 U have been obtained by fitting the first-chance and second-chance fission plateaus of the 238 U cross section. For the fission width of 238 U, good agreement was observed between the authors' results and Landrum and others' experimental data. (Iwase, T.)

  14. Automatic Pedestrian Crossing Detection and Impairment Analysis Based on Mobile Mapping System

    Science.gov (United States)

    Liu, X.; Zhang, Y.; Li, Q.

    2017-09-01

    Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians' lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

  15. AUTOMATIC PEDESTRIAN CROSSING DETECTION AND IMPAIRMENT ANALYSIS BASED ON MOBILE MAPPING SYSTEM

    Directory of Open Access Journals (Sweden)

    X. Liu

    2017-09-01

    Full Text Available Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians’ lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

  16. An SVM classifier to separate false signals from microcalcifications in digital mammograms

    Energy Technology Data Exchange (ETDEWEB)

    Bazzani, Armando; Bollini, Dante; Brancaccio, Rosa; Campanini, Renato; Riccardi, Alessandro; Romani, Davide [Department of Physics, University of Bologna (Italy); INFN, Bologna (Italy); Lanconelli, Nico [Department of Physics, University of Bologna, and INFN, Bologna (Italy). E-mail: nico.lanconelli@bo.infn.it; Bevilacqua, Alessandro [Department of Electronics, Computer Science and Systems, University of Bologna, and INFN, Bologna (Italy)

    2001-06-01

    In this paper we investigate the feasibility of using an SVM (support vector machine) classifier in our automatic system for the detection of clustered microcalcifications in digital mammograms. SVM is a technique for pattern recognition which relies on the statistical learning theory. It minimizes a function of two terms: the number of misclassified vectors of the training set and a term regarding the generalization classifier capability. We compare the SVM classifier with an MLP (multi-layer perceptron) in the false-positive reduction phase of our detection scheme: a detected signal is considered either microcalcification or false signal, according to the value of a set of its features. The SVM classifier gets slightly better results than the MLP one (Az value of 0.963 against 0.958) in the presence of a high number of training data; the improvement becomes much more evident (Az value of 0.952 against 0.918) in training sets of reduced size. Finally, the setting of the SVM classifier is much easier than the MLP one. (author)

  17. Full-counting statistics of energy transport of molecular junctions in the polaronic regime

    International Nuclear Information System (INIS)

    Tang, Gaomin; Yu, Zhizhou; Wang, Jian

    2017-01-01

    We investigate the full-counting statistics (FCS) of energy transport carried by electrons in molecular junctions for the Anderson–Holstein model in the polaronic regime. Using the two-time quantum measurement scheme, the generating function (GF) for the energy transport is derived and expressed as a Fredholm determinant in terms of Keldysh nonequilibrium Green’s function in the time domain. Dressed tunneling approximation is used in decoupling the phonon cloud operator in the polaronic regime. This formalism enables us to analyze the time evolution of energy transport dynamics after a sudden switch-on of the coupling between the dot and the leads towards the stationary state. The steady state energy current cumulant GF in the long time limit is obtained in the energy domain as well. Universal relations for steady state energy current FCS are derived under a finite temperature gradient with zero bias and this enabled us to express the equilibrium energy current cumulant by a linear combination of lower order cumulants. The behaviors of energy current cumulants in steady state under temperature gradient and external bias are numerically studied and explained. The transient dynamics of energy current cumulants is numerically calculated and analyzed. Universal scaling of normalized transient energy cumulants is found under both temperature gradient and external bias. (paper)

  18. Feature extraction using convolutional neural network for classifying breast density in mammographic images

    Science.gov (United States)

    Thomaz, Ricardo L.; Carneiro, Pedro C.; Patrocinio, Ana C.

    2017-03-01

    Breast cancer is the leading cause of death for women in most countries. The high levels of mortality relate mostly to late diagnosis and to the direct proportionally relationship between breast density and breast cancer development. Therefore, the correct assessment of breast density is important to provide better screening for higher risk patients. However, in modern digital mammography the discrimination among breast densities is highly complex due to increased contrast and visual information for all densities. Thus, a computational system for classifying breast density might be a useful tool for aiding medical staff. Several machine-learning algorithms are already capable of classifying small number of classes with good accuracy. However, machinelearning algorithms main constraint relates to the set of features extracted and used for classification. Although well-known feature extraction techniques might provide a good set of features, it is a complex task to select an initial set during design of a classifier. Thus, we propose feature extraction using a Convolutional Neural Network (CNN) for classifying breast density by a usual machine-learning classifier. We used 307 mammographic images downsampled to 260x200 pixels to train a CNN and extract features from a deep layer. After training, the activation of 8 neurons from a deep fully connected layer are extracted and used as features. Then, these features are feedforward to a single hidden layer neural network that is cross-validated using 10-folds to classify among four classes of breast density. The global accuracy of this method is 98.4%, presenting only 1.6% of misclassification. However, the small set of samples and memory constraints required the reuse of data in both CNN and MLP-NN, therefore overfitting might have influenced the results even though we cross-validated the network. Thus, although we presented a promising method for extracting features and classifying breast density, a greater database is

  19. The Question of Queue: Implications for -Best Practice- in Cross-country Transport of Commercial Spent Nuclear Fuel

    International Nuclear Information System (INIS)

    Williams, J.M.

    2009-01-01

    The 'Standard Contract' authorized by the Nuclear Waste Policy Act of 1982 (Section 302(a)) provides that priority for acceptance of spent nuclear fuel (SNF) shall be based on the date of its discharge from civilian nuclear reactors. Through 2007, about 2,100 discharges of about 58,000 metric tons have created a priority ranking (or 'queue') for US DOE spent fuel acceptance and transport. Since 1982, consideration of the task of large-scale, cross-country SNF transport (by the National Academies and others) has led to several recommendations for 'best practice' in such an unprecedented campaign. Many of these recommendations, however, are inconsistent with the acceptance priority established by the Standard Contract, and in fact cannot be implemented under its provisions. This paper considers the SNF acceptance rankings established by the Standard Contract, and the barrier these place on best practice cross-country transport of the nation's inventory of SNF. Using a series of case studies, the paper explores the challenge of best practice transport from selected shipment origins under current arrangements. The case studies support preliminary conclusions regarding the inconsistency between best practice SNF transport and the Standard Contract acceptance queue, with reference to particular origins sites and their utility owners. The paper concludes with a suggestion for resolving the inconsistencies, and recommended next steps in the inquiry. (authors)

  20. Evaluation of scattering laws and cross sections for calculation of production and transport of cold and ultracold neutrons

    International Nuclear Information System (INIS)

    Bernnat, W.; Keinert, J.; Mattes, M.

    2004-01-01

    For the calculation of neutron spectra in cold and super thermal sources scattering laws for a variety of liquid and solid cyrogenic materials were evaluated and prepared for use in deterministic and Monte Carlo transport calculations. For moderator materials like liquid and solid H 2 O, liquid He, liquid D 2 O, liquid and solid H 2 and D 2 , solid CH 4 and structure materials such as Al, Bi, Pb, ZrHx, and graphite scattering law data and cross sections are available. The evaluated data were validated by comparison with measured cross sections and comparison of measured and calculated neutron spectra as far as available. Further applications are the calculation of production and transport and storing of ultra cold neutrons (UCN) in different UCN sources. The data structures of the evaluated data are prepared for the common S N -transport codes and the Monte Carlo Code MCNP. (orig.)

  1. A cross-sectional evaluation of meditation experience on electroencephalography data by artificial neural network and support vector machine classifiers.

    Science.gov (United States)

    Lee, Yu-Hao; Hsieh, Ya-Ju; Shiah, Yung-Jong; Lin, Yu-Huei; Chen, Chiao-Yun; Tyan, Yu-Chang; GengQiu, JiaCheng; Hsu, Chung-Yao; Chen, Sharon Chia-Ju

    2017-04-01

    To quantitate the meditation experience is a subjective and complex issue because it is confounded by many factors such as emotional state, method of meditation, and personal physical condition. In this study, we propose a strategy with a cross-sectional analysis to evaluate the meditation experience with 2 artificial intelligence techniques: artificial neural network and support vector machine. Within this analysis system, 3 features of the electroencephalography alpha spectrum and variant normalizing scaling are manipulated as the evaluating variables for the detection of accuracy. Thereafter, by modulating the sliding window (the period of the analyzed data) and shifting interval of the window (the time interval to shift the analyzed data), the effect of immediate analysis for the 2 methods is compared. This analysis system is performed on 3 meditation groups, categorizing their meditation experiences in 10-year intervals from novice to junior and to senior. After an exhausted calculation and cross-validation across all variables, the high accuracy rate >98% is achievable under the criterion of 0.5-minute sliding window and 2 seconds shifting interval for both methods. In a word, the minimum analyzable data length is 0.5 minute and the minimum recognizable temporal resolution is 2 seconds in the decision of meditative classification. Our proposed classifier of the meditation experience promotes a rapid evaluation system to distinguish meditation experience and a beneficial utilization of artificial techniques for the big-data analysis.

  2. A statistical approach for predicting thermal diffusivity profiles in fusion plasmas as a transport model

    International Nuclear Information System (INIS)

    Yokoyama, Masayuki

    2014-01-01

    A statistical approach is proposed to predict thermal diffusivity profiles as a transport “model” in fusion plasmas. It can provide regression expressions for the ion and electron heat diffusivities (χ i and χ e ), separately, to construct their radial profiles. An approach that this letter is proposing outstrips the conventional scaling laws for the global confinement time (τ E ) since it also deals with profiles (temperature, density, heating depositions etc.). This approach has become possible with the analysis database accumulated by the extensive application of the integrated transport analysis suite to experiment data. In this letter, TASK3D-a analysis database for high-ion-temperature (high-T i ) plasmas in the LHD (Large Helical Device) is used as an example to describe an approach. (author)

  3. A novel application of t-statistics to objectively assess the quality of IC50 fits for P-glycoprotein and other transporters.

    Science.gov (United States)

    O'Connor, Michael; Lee, Caroline; Ellens, Harma; Bentz, Joe

    2015-02-01

    Current USFDA and EMA guidance for drug transporter interactions is dependent on IC50 measurements as these are utilized in determining whether a clinical interaction study is warranted. It is therefore important not only to standardize transport inhibition assay systems but also to develop uniform statistical criteria with associated probability statements for generation of robust IC50 values, which can be easily adopted across the industry. The current work provides a quantitative examination of critical factors affecting the quality of IC50 fits for P-gp inhibition through simulations of perfect data with randomly added error as commonly observed in the large data set collected by the P-gp IC50 initiative. The types of errors simulated were (1) variability in replicate measures of transport activity; (2) transformations of error-contaminated transport activity data prior to IC50 fitting (such as performed when determining an IC50 for inhibition of P-gp based on efflux ratio); and (3) the lack of well defined "no inhibition" and "complete inhibition" plateaus. The effect of the algorithm used in fitting the inhibition curve (e.g., two or three parameter fits) was also investigated. These simulations provide strong quantitative support for the recommendations provided in Bentz et al. (2013) for the determination of IC50 values for P-gp and demonstrate the adverse effect of data transformation prior to fitting. Furthermore, the simulations validate uniform statistical criteria for robust IC50 fits in general, which can be easily implemented across the industry. A calibration of the t-statistic is provided through calculation of confidence intervals associated with the t-statistic.

  4. Aortic Aneurysm Statistics

    Science.gov (United States)

    ... Summary Coverdell Program 2012-2015 State Summaries Data & Statistics Fact Sheets Heart Disease and Stroke Fact Sheets ... Roadmap for State Planning Other Data Resources Other Statistic Resources Grantee Information Cross-Program Information Online Tools ...

  5. An automated approach to the design of decision tree classifiers

    Science.gov (United States)

    Argentiero, P.; Chin, R.; Beaudet, P.

    1982-01-01

    An automated technique is presented for designing effective decision tree classifiers predicated only on a priori class statistics. The procedure relies on linear feature extractions and Bayes table look-up decision rules. Associated error matrices are computed and utilized to provide an optimal design of the decision tree at each so-called 'node'. A by-product of this procedure is a simple algorithm for computing the global probability of correct classification assuming the statistical independence of the decision rules. Attention is given to a more precise definition of decision tree classification, the mathematical details on the technique for automated decision tree design, and an example of a simple application of the procedure using class statistics acquired from an actual Landsat scene.

  6. Model Transport: Towards Scalable Transfer Learning on Manifolds

    DEFF Research Database (Denmark)

    Freifeld, Oren; Hauberg, Søren; Black, Michael J.

    2014-01-01

    We consider the intersection of two research fields: transfer learning and statistics on manifolds. In particular, we consider, for manifold-valued data, transfer learning of tangent-space models such as Gaussians distributions, PCA, regression, or classifiers. Though one would hope to simply use...... ordinary Rn-transfer learning ideas, the manifold structure prevents it. We overcome this by basing our method on inner-product-preserving parallel transport, a well-known tool widely used in other problems of statistics on manifolds in computer vision. At first, this straightforward idea seems to suffer...... “commutes” with learning. Consequently, our compact framework, applicable to a large class of manifolds, is not restricted by the size of either the training or test sets. We demonstrate the approach by transferring PCA and logistic-regression models of real-world data involving 3D shapes and image...

  7. TRANSPORTING CHILDREN IN CARS AND THE USE OF CHILD SAFETY RESTRAINT SYSTEMS.

    Science.gov (United States)

    Garcês, Allan Quadros; Coimbra, Igor Bonifacio Andrade; Silva, Diego Salvador Muniz DA

    2016-01-01

    To evaluate the transport of children in automobiles and the use of child restraints systems (CRS). This is a transversal descriptive study which included 200 vehicle drivers who carried 0-10 year old children in the city of São Luis, MA, Brazil. The drivers' passengers' and children's features were properly identified. The children's transportation using CRS were analyzed according to the Resolution 277/8 of the Brazilian National Traffic Department. The transportation of children was classified as inappropriate in 70.5% of the vehicles analyzed. The most common way for children transportation was free on the back seats (47%) or on the lap of passengers/drivers (17%). The main reasons to justify the improper transportation were either not understanding the importance of CRS use (64.5%) or not having financial resources to buy the devices. The child safety seat was the most used CRS (50.8 %) among vehicles with proper child transportation system. The transportation of children was inappropriate in most of the vehicles analyzed, reflecting the need for creating awareness among automobile drivers, including education, supervision and improvement of policies for health improvement and prevention of accidents involving children transportation. Level of Evidence III, Cross Sectional Study.

  8. Machine learning classifiers and fMRI: a tutorial overview.

    Science.gov (United States)

    Pereira, Francisco; Mitchell, Tom; Botvinick, Matthew

    2009-03-01

    Interpreting brain image experiments requires analysis of complex, multivariate data. In recent years, one analysis approach that has grown in popularity is the use of machine learning algorithms to train classifiers to decode stimuli, mental states, behaviours and other variables of interest from fMRI data and thereby show the data contain information about them. In this tutorial overview we review some of the key choices faced in using this approach as well as how to derive statistically significant results, illustrating each point from a case study. Furthermore, we show how, in addition to answering the question of 'is there information about a variable of interest' (pattern discrimination), classifiers can be used to tackle other classes of question, namely 'where is the information' (pattern localization) and 'how is that information encoded' (pattern characterization).

  9. Differential profiling of volatile organic compound biomarker signatures utilizing a logical statistical filter-set and novel hybrid evolutionary classifiers

    Science.gov (United States)

    Grigsby, Claude C.; Zmuda, Michael A.; Boone, Derek W.; Highlander, Tyler C.; Kramer, Ryan M.; Rizki, Mateen M.

    2012-06-01

    A growing body of discoveries in molecular signatures has revealed that volatile organic compounds (VOCs), the small molecules associated with an individual's odor and breath, can be monitored to reveal the identity and presence of a unique individual, as well their overall physiological status. Given the analysis requirements for differential VOC profiling via gas chromatography/mass spectrometry, our group has developed a novel informatics platform, Metabolite Differentiation and Discovery Lab (MeDDL). In its current version, MeDDL is a comprehensive tool for time-series spectral registration and alignment, visualization, comparative analysis, and machine learning to facilitate the efficient analysis of multiple, large-scale biomarker discovery studies. The MeDDL toolset can therefore identify a large differential subset of registered peaks, where their corresponding intensities can be used as features for classification. This initial screening of peaks yields results sets that are typically too large for incorporation into a portable, electronic nose based system in addition to including VOCs that are not amenable to classification; consequently, it is also important to identify an optimal subset of these peaks to increase classification accuracy and to decrease the cost of the final system. MeDDL's learning tools include a classifier similar to a K-nearest neighbor classifier used in conjunction with a genetic algorithm (GA) that simultaneously optimizes the classifier and subset of features. The GA uses ROC curves to produce classifiers having maximal area under their ROC curve. Experimental results on over a dozen recognition problems show many examples of classifiers and feature sets that produce perfect ROC curves.

  10. Building Road-Sign Classifiers Using a Trainable Similarity Measure

    Czech Academy of Sciences Publication Activity Database

    Paclík, P.; Novovičová, Jana; Duin, R.P.W.

    2006-01-01

    Roč. 7, č. 3 (2006), s. 309-321 ISSN 1524-9050 R&D Projects: GA AV ČR IAA2075302 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : classifier system design * road-sign classification * similarity data representation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.434, year: 2006 http://www.ewh.ieee.org/tc/its/trans.html

  11. ZZ AIRFEWG, Gamma, Neutron Transport Calculation in Air Using FEWG1 Cross-Section

    International Nuclear Information System (INIS)

    1985-01-01

    1 - Description of program or function: Format: ANISN; Number of groups: 37 neutron / 21 gamma-ray; Nuclides: air (79% N and 21% O); Origin: DLC-0031/FEWG1 cross sections (ENDF/B-IV). Weighting spectrum: 1/E. The AIRFEWG library has been generated by an ANISN multigroup calculation of gamma-ray, neutron, and secondary gamma-ray transport in infinite homogeneous air using DLC-0031/FEWG1 cross sections. 2 - Method of solution: The results were generated with a P3, ANISN run with a source in a single energy group. Thus, 58 such runs were required. For sources in the 37 neutron groups, both neutron and secondary gamma-ray fluence results were calculated. For gamma-ray sources only gamma-ray fluences were calculated

  12. Just-in-time adaptive classifiers-part II: designing the classifier.

    Science.gov (United States)

    Alippi, Cesare; Roveri, Manuel

    2008-12-01

    Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolution adaptive solutions must be envisaged to track its dynamics; in this direction, adaptive classifiers are generally designed by assuming the stationary hypothesis for the process generating the data with very few results addressing nonstationary environments. This paper proposes a methodology based on k-nearest neighbor (NN) classifiers for designing adaptive classification systems able to react to changing conditions just-in-time (JIT), i.e., exactly when it is needed. k-NN classifiers have been selected for their computational-free training phase, the possibility to easily estimate the model complexity k and keep under control the computational complexity of the classifier through suitable data reduction mechanisms. A JIT classifier requires a temporal detection of a (possible) process deviation (aspect tackled in a companion paper) followed by an adaptive management of the knowledge base (KB) of the classifier to cope with the process change. The novelty of the proposed approach resides in the general framework supporting the real-time update of the KB of the classification system in response to novel information coming from the process both in stationary conditions (accuracy improvement) and in nonstationary ones (process tracking) and in providing a suitable estimate of k. It is shown that the classification system grants consistency once the change targets the process generating the data in a new stationary state, as it is the case in many real applications.

  13. Crossing statistic: reconstructing the expansion history of the universe

    International Nuclear Information System (INIS)

    Shafieloo, Arman

    2012-01-01

    We present that by combining Crossing Statistic [1,2] and Smoothing method [3-5] one can reconstruct the expansion history of the universe with a very high precision without considering any prior on the cosmological quantities such as the equation of state of dark energy. We show that the presented method performs very well in reconstruction of the expansion history of the universe independent of the underlying models and it works well even for non-trivial dark energy models with fast or slow changes in the equation of state of dark energy. Accuracy of the reconstructed quantities along with independence of the method to any prior or assumption gives the proposed method advantages to the other non-parametric methods proposed before in the literature. Applying on the Union 2.1 supernovae combined with WiggleZ BAO data we present the reconstructed results and test the consistency of the two data sets in a model independent manner. Results show that latest available supernovae and BAO data are in good agreement with each other and spatially flat ΛCDM model is in concordance with the current data

  14. Adverse events during air and ground neonatal transport: 13 years' experience from a neonatal transport team in Northern Sweden.

    Science.gov (United States)

    van den Berg, Johannes; Olsson, Linn; Svensson, Amelie; Håkansson, Stellan

    2015-07-01

    To study the prevalence of adverse events (AEs) associated with neonatal transport, and to categorize, classify and assess the risk estimation of these events. Written comments in 1082 transport records during the period 1999-2011 were reviewed. Comments related to events that infringed on patient and staff safety were included as AEs, and categorized and further classified as complaint, imminent risk of incident/negative event, actual incident or actual negative event. AEs were also grouped into emergency or planned transports, and risk estimation was calculated according to a risk assessment tool and defined as low, intermediate, high or extreme risk. AEs (N = 883) were divided into five categories: logistics (n = 337), organization (n = 177), equipment (n = 165), vehicle (n = 129) and medical/nursing care (n = 75). Eighty-five percent of AEs were classified as incidents or negative events. The majority of AEs were estimated to be of low or intermediate risk in both planned and emergency transports. AEs estimated to be of high or extreme risk were significantly more frequent in emergency transports (OR = 10.1; 95% CI: 5.0-20.9; p transport, often related to imperfect transport logistics or equipment failure. AEs of high or extreme risk were more frequent in emergency transports.

  15. Evaluation of scattering laws and cross sections for calculation of production and transport of cold and ultracold neutrons

    Energy Technology Data Exchange (ETDEWEB)

    Bernnat, W.; Keinert, J.; Mattes, M. [Inst. for Nuclear Energy and Energy Systems, Univ. of Stuttgart, Stuttgart (Germany)

    2004-03-01

    For the calculation of neutron spectra in cold and super thermal sources scattering laws for a variety of liquid and solid cyrogenic materials were evaluated and prepared for use in deterministic and Monte Carlo transport calculations. For moderator materials like liquid and solid H{sub 2}O, liquid He, liquid D{sub 2}O, liquid and solid H{sub 2} and D{sub 2}, solid CH{sub 4} and structure materials such as Al, Bi, Pb, ZrHx, and graphite scattering law data and cross sections are available. The evaluated data were validated by comparison with measured cross sections and comparison of measured and calculated neutron spectra as far as available. Further applications are the calculation of production and transport and storing of ultra cold neutrons (UCN) in different UCN sources. The data structures of the evaluated data are prepared for the common S{sub N}-transport codes and the Monte Carlo Code MCNP. (orig.)

  16. Study on the Cross Plane Thermal Transport of Polycrystalline Molybdenum Nanofilms by Applying Picosecond Laser Transient Thermoreflectance Method

    Directory of Open Access Journals (Sweden)

    Tingting Miao

    2014-01-01

    Full Text Available Thin metal films are widely used as interconnecting wires and coatings in electronic devices and optical components. Reliable thermophysical properties of the films are required from the viewpoint of thermal management. The cross plane thermal transport of four polycrystalline molybdenum nanofilms with different thickness deposited on glass substrates has been studied by applying the picosecond laser transient thermoreflectance technique. The measurement is performed by applying both front pump-front probe and rear pump-front probe configurations with high quality signal. The determined cross plane thermal diffusivity of the Mo films greatly decreases compared to the corresponding bulk value and tends to increase as films become thicker, exhibiting significant size effect. The main mechanism responsible for the thermal diffusivity decrease of the present polycrystalline Mo nanofilms is the grain boundary scattering on the free electrons. Comparing the cross plane thermal diffusivity and inplane electrical conductivity indicates the anisotropy of the transport properties of the Mo films.

  17. What is the role of laminar cirrus cloud on regulating the cross-tropopause water vapor transport?

    Science.gov (United States)

    Wu, D. L.; Gong, J.; Tsai, V.

    2016-12-01

    Laminar cirrus is an extremely thin ice cloud found persistently inhabit in the tropical and subtropical tropopause. Due to its sub-visible optical depth and high formation altitude, knowledge about the characteristics of this special type of cloud is very limited, and debates are ongoing about its role on regulating the cross-tropopause transport of water vapor. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite has been continuously providing us with unprecedented details of the laminar cirrus since its launch in 2006. In this research, we adapted Winker and Trepte (1998)'s eyeball detection method. A JAVA-based applet and graphical user interface (GUI) is developed to manually select the laminar, which then automatically record the cloud properties, such as spatial location, shape, thickness, tilt angle, and whether its isolated or directly above a deep convective cloud. Monthly statistics of the laminar cirrus are then separately analyzed according to the orbit node, isolated/convective, banded/non-banded, etc. Monthly statistics support a diurnal difference in the occurring frequency and formation height of the laminar cirrus. Also, isolated and convective laminars show diverse behaviors (height, location, distribution, etc.), which strongly implies that their formation mechanisms and their roles on depleting the upper troposphere water vapor are distinct. We further study the relationship between laminar characteristics and collocated and coincident water vapor gradient measurements from Aura Microwave Limb Sounder (MLS) observations below and above the laminars. The identified relationship provides a quantitative answer to the role laminar cirrus plays on regulating the water vapor entering the stratosphere.

  18. INEQUALITIES RESEARCH OF THE TRACK AT THE RAILROAD CROSSINGS

    Directory of Open Access Journals (Sweden)

    M. B. Kurhan

    2015-08-01

    Full Text Available Purpose. The intersection of highways and railways in one level – railway crossing, is a zone of increased danger for rail and road transport. Nearly half of all crossings are available on the main directions of passenger transportation. From this comes the problem of maintenance and service locations of intersection roads and railways. The purpose of this work is to evaluate the processes of emergence and development of inequalities in the area of railroad crossings and identify the factors that cause them. Methodology. The presence of derogation from the plan and profile within the railway crossing and approaches to it reduces evenness of riding and passenger comfort. Today, there are various possibilities for shooting natural geometry of a railway track. For research on a large number of areas during long service life, the tape of a track measuring car remains the most convenient. However, this tool is directed to assess the state of the railway line and does not determine the exact geometrical position. When trying to determine valid outlines of the track inequalities on track measuring tape, some difficulties arise. Findings. Performed statistical analysis showed a steady trend of growth of inequalities in the area of the railway crossings. Generally, the level of inequalities in the vertical plane increases in1.3−3.2 times and in 1.2−2.0 times in the horizontal plane (compared with areas that are outside crossing. During the deflection lines of action in the area of railroad crossing concrete slabs work as ribs that limit deflections of rail-tie grating. When placing the wheels of the bogie before (or after and within crossing the calculated modulus of elasticity under the rail base, brought to the point of wheels contact can vary up to 3 times. Originality. Issues of the assessment and investigation of inequalities on track started to be developed. The resulting statistics on inequalities accumulation gauge in the zone of crossing

  19. Magnetic fluctuation driven cross-field particle transport in the reversed-field pinch

    International Nuclear Information System (INIS)

    Scheffel, J.; Liu, D.

    1997-01-01

    Electrostatic and electromagnetic fluctuations generally cause cross-field particle transport in confined plasmas. Thus core localized turbulence must be kept at low levels for sufficient energy confinement in magnetic fusion plasmas. Reversed-field pinch (RFP) equilibria can, theoretically, be completely stable to ideal and resistive (tearing) magnetohydrodynamic (MHD) modes at zero beta. Unstable resistive interchange modes are, however, always present at experimentally relevant values of the poloidal beta β θ . An analytical quasilinear, ambipolar diffusion model is here used to model associated particle transport. The results indicate that core density fluctuations should not exceed a level of about 1% for plasmas of fusion interest. Parameters of experimentally relevant stationary states of the RFP were adjusted to minimize growth rates, using a fully resistive linearized MHD stability code. Density gradient effects are included through employing a parabolic density profile. The scaling of particle diffusion [D(r)∝λ 2 n 0.5 T/aB, where λ is the mode width] is such that the effects of particle transport are milder in present day RFP experiments than in future reactor-relevant plasmas. copyright 1997 American Institute of Physics

  20. Classifier for gravitational-wave inspiral signals in nonideal single-detector data

    Science.gov (United States)

    Kapadia, S. J.; Dent, T.; Dal Canton, T.

    2017-11-01

    We describe a multivariate classifier for candidate events in a templated search for gravitational-wave (GW) inspiral signals from neutron-star-black-hole (NS-BH) binaries, in data from ground-based detectors where sensitivity is limited by non-Gaussian noise transients. The standard signal-to-noise ratio (SNR) and chi-squared test for inspiral searches use only properties of a single matched filter at the time of an event; instead, we propose a classifier using features derived from a bank of inspiral templates around the time of each event, and also from a search using approximate sine-Gaussian templates. The classifier thus extracts additional information from strain data to discriminate inspiral signals from noise transients. We evaluate a random forest classifier on a set of single-detector events obtained from realistic simulated advanced LIGO data, using simulated NS-BH signals added to the data. The new classifier detects a factor of 1.5-2 more signals at low false positive rates as compared to the standard "reweighted SNR" statistic, and does not require the chi-squared test to be computed. Conversely, if only the SNR and chi-squared values of single-detector events are available, random forest classification performs nearly identically to the reweighted SNR.

  1. 49 CFR 236.384 - Cross protection.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 4 2010-10-01 2010-10-01 false Cross protection. 236.384 Section 236.384 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD ADMINISTRATION... and Tests § 236.384 Cross protection. Cross protection shall be tested at least once every six months...

  2. Hybrid classifiers methods of data, knowledge, and classifier combination

    CERN Document Server

    Wozniak, Michal

    2014-01-01

    This book delivers a definite and compact knowledge on how hybridization can help improving the quality of computer classification systems. In order to make readers clearly realize the knowledge of hybridization, this book primarily focuses on introducing the different levels of hybridization and illuminating what problems we will face with as dealing with such projects. In the first instance the data and knowledge incorporated in hybridization were the action points, and then a still growing up area of classifier systems known as combined classifiers was considered. This book comprises the aforementioned state-of-the-art topics and the latest research results of the author and his team from Department of Systems and Computer Networks, Wroclaw University of Technology, including as classifier based on feature space splitting, one-class classification, imbalance data, and data stream classification.

  3. Analysis of TCE Fate and Transport in Karst Groundwater Systems Using Statistical Mixed Models

    Science.gov (United States)

    Anaya, A. A.; Padilla, I. Y.

    2012-12-01

    Karst groundwater systems are highly productive and provide an important fresh water resource for human development and ecological integrity. Their high productivity is often associated with conduit flow and high matrix permeability. The same characteristics that make these aquifers productive also make them highly vulnerable to contamination and a likely for contaminant exposure. Of particular interest are trichloroethylene, (TCE) and Di-(2-Ethylhexyl) phthalate (DEHP). These chemicals have been identified as potential precursors of pre-term birth, a leading cause of neonatal complications with a significant health and societal cost. Both of these contaminants have been found in the karst groundwater formations in this area of the island. The general objectives of this work are to: (1) develop fundamental knowledge and determine the processes controlling the release, mobility, persistence, and possible pathways of contaminants in karst groundwater systems, and (2) characterize transport processes in conduit and diffusion-dominated flow under base flow and storm flow conditions. The work presented herein focuses on the use of geo-hydro statistical tools to characterize flow and transport processes under different flow regimes, and their application in the analysis of fate and transport of TCE. Multidimensional, laboratory-scale Geo-Hydrobed models (GHM) were used for this purpose. The models consist of stainless-steel tanks containing karstified limestone blocks collected from the karst aquifer formation of northern Puerto Rico. The models integrates a network of sampling wells to monitor flow, pressure, and solute concentrations temporally and spatially. Experimental work entails injecting dissolved CaCl2 tracers and TCE in the upstream boundary of the GHM while monitoring TCE and tracer concentrations spatially and temporally in the limestone under different groundwater flow regimes. Analysis of the temporal and spatial concentration distributions of solutes

  4. North American Transportation Statistics Database - Data Mining Tool

    Data.gov (United States)

    Department of Transportation — Contains tables of data for the United States, Canada, and Mexico. Data tables are divided up into 12 categories, including a country overview, transportation flows,...

  5. Stacking machine learning classifiers to identify Higgs bosons at the LHC

    International Nuclear Information System (INIS)

    Alves, A.

    2017-01-01

    Machine learning (ML) algorithms have been employed in the problem of classifying signal and background events with high accuracy in particle physics. In this paper, we compare the performance of a widespread ML technique, namely, stacked generalization , against the results of two state-of-art algorithms: (1) a deep neural network (DNN) in the task of discovering a new neutral Higgs boson and (2) a scalable machine learning system for tree boosting, in the Standard Model Higgs to tau leptons channel, both at the 8 TeV LHC. In a cut-and-count analysis, stacking three algorithms performed around 16% worse than DNN but demanding far less computation efforts, however, the same stacking outperforms boosted decision trees. Using the stacked classifiers in a multivariate statistical analysis (MVA), on the other hand, significantly enhances the statistical significance compared to cut-and-count in both Higgs processes, suggesting that combining an ensemble of simpler and faster ML algorithms with MVA tools is a better approach than building a complex state-of-art algorithm for cut-and-count.

  6. Effect of the Target Motion Sampling Temperature Treatment Method on the Statistics and Performance

    Science.gov (United States)

    Viitanen, Tuomas; Leppänen, Jaakko

    2014-06-01

    Target Motion Sampling (TMS) is a stochastic on-the-fly temperature treatment technique that is being developed as a part of the Monte Carlo reactor physics code Serpent. The method provides for modeling of arbitrary temperatures in continuous-energy Monte Carlo tracking routines with only one set of cross sections stored in the computer memory. Previously, only the performance of the TMS method in terms of CPU time per transported neutron has been discussed. Since the effective cross sections are not calculated at any point of a transport simulation with TMS, reaction rate estimators must be scored using sampled cross sections, which is expected to increase the variances and, consequently, to decrease the figures-of-merit. This paper examines the effects of the TMS on the statistics and performance in practical calculations involving reaction rate estimation with collision estimators. Against all expectations it turned out that the usage of sampled response values has no practical effect on the performance of reaction rate estimators when using TMS with elevated basis cross section temperatures (EBT), i.e. the usual way. With 0 Kelvin cross sections a significant increase in the variances of capture rate estimators was observed right below the energy region of unresolved resonances, but at these energies the figures-of-merit could be increased using a simple resampling technique to decrease the variances of the responses. It was, however, noticed that the usage of the TMS method increases the statistical deviances of all estimators, including the flux estimator, by tens of percents in the vicinity of very strong resonances. This effect is actually not related to the usage of sampled responses, but is instead an inherent property of the TMS tracking method and concerns both EBT and 0 K calculations.

  7. Statistical description of flume experiments on mixed-size bed-load transport and bed armoring processes

    Science.gov (United States)

    Chen, D.; Zhang, Y.

    2008-12-01

    The objective of this paper is to describe the statistical properties of experiments on non-uniform bed-load transport as well as the mechanism of bed armoring processes. Despite substantial effort made over the last two decades, the ability to compute the bed-load flux in a turbulent system remains poor. The major obstacles include the poor understanding of the formation of armor lays on bed surfaces. Such a layer is much flow-resistible than the underlying material and therefore significantly inhibits sediment transport from the reach. To study the problem, we conducted a flume study for mixed sand/gravel sediments. We observed that aggregated sediment blocks were the most common characters in armor layers - the largest sizes resist hydraulic forces, while the smaller sizes add interlocking support and prevent loss of fine material through gaps between the larger particles. Fractional transport rates with the existing of armor layers were measured with time by sediment trapping method at the end of flume. To address the intermittent and time-varying behavior of bed-load transport during bed armoring processes, we investigated the probability distribution of the fractional bed-load transport rates, and the underlying dynamic model derived from the continuous time random walk framework. Results indicate that it is critical to consider the impact of armor layers when a flow is sufficient to move some of the finer particles and yet insufficient to move all the larger particles on a channel bed.

  8. Klasifikasi Teks Bahasa Bali dengan Metode Information Gain dan Naive Bayes Classifier

    Directory of Open Access Journals (Sweden)

    Ida Bagus Gede Widnyana Putra

    2016-11-01

    Full Text Available Ketersediaan dokumen teks bahasa Bali yang meningkat jumlahnya membuat proses pencarian informasi pada dokumen teks berbahasa Bali menjadi semakin sulit. Mengklasifikasikanya secara manual menjadi tidak efisien mengingat peningkatan jumlah dokumen yang semakin banyak. Pada penelitian ini dikembangkan sebuah aplikasi yang dapat mengklasifikasikan teks bahasa Bali ke dalam kategori yang ditentukan. Aplikasi ini menggunakan metode klasifikasi Naive Bayes Classifier (NBC dan metode Information Gain(IG untuk seleksi fitur. Aplikasi ini diuji dengan teknik cross validation. Hasilnya adalah nilai rata-rata akurasi dari 10 fold cross validation sebesar  95,22%.

  9. Discrimination of soft tissues using laser-induced breakdown spectroscopy in combination with k nearest neighbors (kNN) and support vector machine (SVM) classifiers

    Science.gov (United States)

    Li, Xiaohui; Yang, Sibo; Fan, Rongwei; Yu, Xin; Chen, Deying

    2018-06-01

    In this paper, discrimination of soft tissues using laser-induced breakdown spectroscopy (LIBS) in combination with multivariate statistical methods is presented. Fresh pork fat, skin, ham, loin and tenderloin muscle tissues are manually cut into slices and ablated using a 1064 nm pulsed Nd:YAG laser. Discrimination analyses between fat, skin and muscle tissues, and further between highly similar ham, loin and tenderloin muscle tissues, are performed based on the LIBS spectra in combination with multivariate statistical methods, including principal component analysis (PCA), k nearest neighbors (kNN) classification, and support vector machine (SVM) classification. Performances of the discrimination models, including accuracy, sensitivity and specificity, are evaluated using 10-fold cross validation. The classification models are optimized to achieve best discrimination performances. The fat, skin and muscle tissues can be definitely discriminated using both kNN and SVM classifiers, with accuracy of over 99.83%, sensitivity of over 0.995 and specificity of over 0.998. The highly similar ham, loin and tenderloin muscle tissues can also be discriminated with acceptable performances. The best performances are achieved with SVM classifier using Gaussian kernel function, with accuracy of 76.84%, sensitivity of over 0.742 and specificity of over 0.869. The results show that the LIBS technique assisted with multivariate statistical methods could be a powerful tool for online discrimination of soft tissues, even for tissues of high similarity, such as muscles from different parts of the animal body. This technique could be used for discrimination of tissues suffering minor clinical changes, thus may advance the diagnosis of early lesions and abnormalities.

  10. Use of sparker signal to classify seafloor sediment

    Digital Repository Service at National Institute of Oceanography (India)

    Pathak, D.; Ranade, G.; Sudhakar, T.

    During the cruise 190 of R.V. Gaveshani, the sparker signal was recorded in the analog form on audio cassettes. This signal has been digitized and a statistical computation, viz. the normalized cross-correlation function between successive echoes...

  11. ELECTRON TEMPERATURE FLUCTUATIONS AND CROSS-FIELD HEAT TRANSPORT IN THE EDGE OF DIII-D

    International Nuclear Information System (INIS)

    RUDAKOV, DL; BOEDO, JA; MOYER, RA; KRASENINNIKOV, S; MAHDAVI, MA; McKEE, GR; PORTER, GD; STANGEBY, PC; WATKINS, JG; WEST, WP; WHYTE, DG.

    2003-01-01

    OAK-B135 The fluctuating E x B velocity due to electrostatic turbulence is widely accepted as a major contributor to the anomalous cross-field transport of particles and heat in the tokamak edge and scrape-off layer (SOL) plasmas. This has been confirmed by direct measurements of the turbulent E x B transport in a number of experiments. Correlated fluctuations of the plasma radial velocity v r , density n, and temperature T e result in time-average fluxes of particles and heat given by (for electrons): Equation 1--Λ r ES = r > = 1/B varφ θ ; Equation 2--Q r ES = e (tilde v) r > ∼ 3/2 kT e Λ r ES + 3 n e /2 B varφ e (tilde E) θ > Q conv + Q cond . The first term in Equation 2 is referred to as convective and the second term as conductive heat flux. Experimental determination of fluxes given by Equations 1 and 2 requires simultaneous measurements of the density, temperature and poloidal electric field fluctuations with high spatial and temporal resolution. Langmuir probes provide most readily available (if not the only) tool for such measurements. However, fast measurements of electron temperature using probes are non-trivial and are not always performed. Thus, the contribution of the T e fluctuations to the turbulent fluxes is usually neglected. Here they report results of the studies of T e fluctuations and their effect on the cross-field transport in the SOL of DIII-D

  12. Image Statistics and the Representation of Material Properties in the Visual Cortex.

    Science.gov (United States)

    Baumgartner, Elisabeth; Gegenfurtner, Karl R

    2016-01-01

    We explored perceived material properties (roughness, texturedness, and hardness) with a novel approach that compares perception, image statistics and brain activation, as measured with fMRI. We initially asked participants to rate 84 material images with respect to the above mentioned properties, and then scanned 15 of the participants with fMRI while they viewed the material images. The images were analyzed with a set of image statistics capturing their spatial frequency and texture properties. Linear classifiers were then applied to the image statistics as well as the voxel patterns of visually responsive voxels and early visual areas to discriminate between images with high and low perceptual ratings. Roughness and texturedness could be classified above chance level based on image statistics. Roughness and texturedness could also be classified based on the brain activation patterns in visual cortex, whereas hardness could not. Importantly, the agreement in classification based on image statistics and brain activation was also above chance level. Our results show that information about visual material properties is to a large degree contained in low-level image statistics, and that these image statistics are also partially reflected in brain activity patterns induced by the perception of material images.

  13. Classifying Aging as a Disease in the context of ICD-11

    Directory of Open Access Journals (Sweden)

    Alex eZhavoronkov

    2015-11-01

    Full Text Available Aging is a complex continuous multifactorial process leading to loss of function and crystalizing into the many age-related diseases. Here, we explore the arguments for classifying aging as a disease in the context of the upcoming World Health Organization’s 11th International Statistical Classification of Diseases and Related Health Problems (ICD-11, expected to be finalized in 2018. We hypothesize that classifying aging as a disease will result in new approaches and business models for addressing aging as a treatable condition, which will lead to both economic and healthcare benefits for all stakeholders. Classification of aging as a disease may lead to more efficient allocation of resources by enabling funding bodies and other stakeholders to use quality-adjusted life years (QALYs and healthy-years equivalent (HYE as metrics when evaluating both research and clinical programs. We propose forming a Task Force to interface the WHO in order to develop a multidisciplinary framework for classifying aging as a disease.

  14. Introducing StatHand: A Cross-Platform Mobile Application to Support Students' Statistical Decision Making.

    Science.gov (United States)

    Allen, Peter J; Roberts, Lynne D; Baughman, Frank D; Loxton, Natalie J; Van Rooy, Dirk; Rock, Adam J; Finlay, James

    2016-01-01

    Although essential to professional competence in psychology, quantitative research methods are a known area of weakness for many undergraduate psychology students. Students find selecting appropriate statistical tests and procedures for different types of research questions, hypotheses and data types particularly challenging, and these skills are not often practiced in class. Decision trees (a type of graphic organizer) are known to facilitate this decision making process, but extant trees have a number of limitations. Furthermore, emerging research suggests that mobile technologies offer many possibilities for facilitating learning. It is within this context that we have developed StatHand, a free cross-platform application designed to support students' statistical decision making. Developed with the support of the Australian Government Office for Learning and Teaching, StatHand guides users through a series of simple, annotated questions to help them identify a statistical test or procedure appropriate to their circumstances. It further offers the guidance necessary to run these tests and procedures, then interpret and report their results. In this Technology Report we will overview the rationale behind StatHand, before describing the feature set of the application. We will then provide guidelines for integrating StatHand into the research methods curriculum, before concluding by outlining our road map for the ongoing development and evaluation of StatHand.

  15. Performance analysis of a Principal Component Analysis ensemble classifier for Emotiv headset P300 spellers.

    Science.gov (United States)

    Elsawy, Amr S; Eldawlatly, Seif; Taher, Mohamed; Aly, Gamal M

    2014-01-01

    The current trend to use Brain-Computer Interfaces (BCIs) with mobile devices mandates the development of efficient EEG data processing methods. In this paper, we demonstrate the performance of a Principal Component Analysis (PCA) ensemble classifier for P300-based spellers. We recorded EEG data from multiple subjects using the Emotiv neuroheadset in the context of a classical oddball P300 speller paradigm. We compare the performance of the proposed ensemble classifier to the performance of traditional feature extraction and classifier methods. Our results demonstrate the capability of the PCA ensemble classifier to classify P300 data recorded using the Emotiv neuroheadset with an average accuracy of 86.29% on cross-validation data. In addition, offline testing of the recorded data reveals an average classification accuracy of 73.3% that is significantly higher than that achieved using traditional methods. Finally, we demonstrate the effect of the parameters of the P300 speller paradigm on the performance of the method.

  16. Semiconductor statistics

    CERN Document Server

    Blakemore, J S

    1962-01-01

    Semiconductor Statistics presents statistics aimed at complementing existing books on the relationships between carrier densities and transport effects. The book is divided into two parts. Part I provides introductory material on the electron theory of solids, and then discusses carrier statistics for semiconductors in thermal equilibrium. Of course a solid cannot be in true thermodynamic equilibrium if any electrical current is passed; but when currents are reasonably small the distribution function is but little perturbed, and the carrier distribution for such a """"quasi-equilibrium"""" co

  17. Symmetrical dimer of the human dopamine transporter revealed by cross-linking Cys-306 at the extracellular end of the sixth transmembrane segment.

    Science.gov (United States)

    Hastrup, H; Karlin, A; Javitch, J A

    2001-08-28

    There is evidence both for and against Na(+)- and Cl(-)-dependent neurotransmitter transporters forming oligomers. We found that cross-linking the human dopamine transporter (DAT), which is heterologously expressed in human embryonic kidney 293 cells, either with copper phenanthroline (CuP) or the bifunctional reagent bis-(2-methanethiosulfonatoethyl)amine hydrochloride (bis-EA) increased the apparent molecular mass determined with nonreducing SDS/PAGE from approximately 85 to approximately 195 kDa. After cross-linking, but not before, coexpressed, differentially epitope-tagged DAT molecules, solubilized in Triton X-100, were coimmunoprecipitated. Thus, the 195-kDa complex was a homodimer. Cross-linking of DAT did not affect tyramine uptake. Replacement of Cys-306 with Ala prevented cross-linking. Replacement of all of the non-disulfide-bonded cysteines in the extracellular and membrane domains, except for Cys-306, did not prevent cross-linking. We conclude that the cross-link is between Cys-306 at the extracellular end of TM6 in each of the two DATs. The motif GVXXGVXXA occurs at the intracellular end of TM6 in DAT and is found in a number of other neurotransmitter transporters. This sequence was originally found at the dimerization interface in glycophorin A, and it promotes dimerization in model systems. Mutation of either glycine disrupted DAT expression and function. The intracellular end of TM6, like the extracellular end, is likely to be part of the dimerization interface.

  18. Classifier models and architectures for EEG-based neonatal seizure detection

    International Nuclear Information System (INIS)

    Greene, B R; Marnane, W P; Lightbody, G; Reilly, R B; Boylan, G B

    2008-01-01

    Neonatal seizures are the most common neurological emergency in the neonatal period and are associated with a poor long-term outcome. Early detection and treatment may improve prognosis. This paper aims to develop an optimal set of parameters and a comprehensive scheme for patient-independent multi-channel EEG-based neonatal seizure detection. We employed a dataset containing 411 neonatal seizures. The dataset consists of multi-channel EEG recordings with a mean duration of 14.8 h from 17 neonatal patients. Early-integration and late-integration classifier architectures were considered for the combination of information across EEG channels. Three classifier models based on linear discriminants, quadratic discriminants and regularized discriminants were employed. Furthermore, the effect of electrode montage was considered. The best performing seizure detection system was found to be an early integration configuration employing a regularized discriminant classifier model. A referential EEG montage was found to outperform the more standard bipolar electrode montage for automated neonatal seizure detection. A cross-fold validation estimate of the classifier performance for the best performing system yielded 81.03% of seizures correctly detected with a false detection rate of 3.82%. With post-processing, the false detection rate was reduced to 1.30% with 59.49% of seizures correctly detected. These results represent a comprehensive illustration that robust reliable patient-independent neonatal seizure detection is possible using multi-channel EEG

  19. Effect of the Target Motion Sampling temperature treatment method on the statistics and performance

    International Nuclear Information System (INIS)

    Viitanen, Tuomas; Leppänen, Jaakko

    2015-01-01

    Highlights: • Use of the Target Motion Sampling (TMS) method with collision estimators is studied. • The expected values of the estimators agree with NJOY-based reference. • In most practical cases also the variances of the estimators are unaffected by TMS. • Transport calculation slow-down due to TMS dominates the impact on figures-of-merit. - Abstract: Target Motion Sampling (TMS) is a stochastic on-the-fly temperature treatment technique that is being developed as a part of the Monte Carlo reactor physics code Serpent. The method provides for modeling of arbitrary temperatures in continuous-energy Monte Carlo tracking routines with only one set of cross sections stored in the computer memory. Previously, only the performance of the TMS method in terms of CPU time per transported neutron has been discussed. Since the effective cross sections are not calculated at any point of a transport simulation with TMS, reaction rate estimators must be scored using sampled cross sections, which is expected to increase the variances and, consequently, to decrease the figures-of-merit. This paper examines the effects of the TMS on the statistics and performance in practical calculations involving reaction rate estimation with collision estimators. Against all expectations it turned out that the usage of sampled response values has no practical effect on the performance of reaction rate estimators when using TMS with elevated basis cross section temperatures (EBT), i.e. the usual way. With 0 Kelvin cross sections a significant increase in the variances of capture rate estimators was observed right below the energy region of unresolved resonances, but at these energies the figures-of-merit could be increased using a simple resampling technique to decrease the variances of the responses. It was, however, noticed that the usage of the TMS method increases the statistical deviances of all estimators, including the flux estimator, by tens of percents in the vicinity of very

  20. A probability-conserving cross-section biasing mechanism for variance reduction in Monte Carlo particle transport calculations

    Energy Technology Data Exchange (ETDEWEB)

    Mendenhall, Marcus H., E-mail: marcus.h.mendenhall@vanderbilt.edu [Vanderbilt University, Department of Electrical Engineering, P.O. Box 351824B, Nashville, TN 37235 (United States); Weller, Robert A., E-mail: robert.a.weller@vanderbilt.edu [Vanderbilt University, Department of Electrical Engineering, P.O. Box 351824B, Nashville, TN 37235 (United States)

    2012-03-01

    In Monte Carlo particle transport codes, it is often important to adjust reaction cross-sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analog Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross-section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross-section change. This makes it possible to increase the cross-section of nuclear reactions by factors exceeding 10{sup 4} (in appropriate cases), without distorting the results of energy deposition calculations or coincidence rates. The procedure is also valid for bias factors less than unity, which is useful in problems that involve the computation of particle penetration deep into a target (e.g. atmospheric showers or shielding studies).

  1. A probability-conserving cross-section biasing mechanism for variance reduction in Monte Carlo particle transport calculations

    International Nuclear Information System (INIS)

    Mendenhall, Marcus H.; Weller, Robert A.

    2012-01-01

    In Monte Carlo particle transport codes, it is often important to adjust reaction cross-sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analog Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross-section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross-section change. This makes it possible to increase the cross-section of nuclear reactions by factors exceeding 10 4 (in appropriate cases), without distorting the results of energy deposition calculations or coincidence rates. The procedure is also valid for bias factors less than unity, which is useful in problems that involve the computation of particle penetration deep into a target (e.g. atmospheric showers or shielding studies).

  2. Cross-layer restoration with software defined networking based on IP over optical transport networks

    Science.gov (United States)

    Yang, Hui; Cheng, Lei; Deng, Junni; Zhao, Yongli; Zhang, Jie; Lee, Young

    2015-10-01

    The IP over optical transport network is a very promising networking architecture applied to the interconnection of geographically distributed data centers due to the performance guarantee of low delay, huge bandwidth and high reliability at a low cost. It can enable efficient resource utilization and support heterogeneous bandwidth demands in highly-available, cost-effective and energy-effective manner. In case of cross-layer link failure, to ensure a high-level quality of service (QoS) for user request after the failure becomes a research focus. In this paper, we propose a novel cross-layer restoration scheme for data center services with software defined networking based on IP over optical network. The cross-layer restoration scheme can enable joint optimization of IP network and optical network resources, and enhance the data center service restoration responsiveness to the dynamic end-to-end service demands. We quantitatively evaluate the feasibility and performances through the simulation under heavy traffic load scenario in terms of path blocking probability and path restoration latency. Numeric results show that the cross-layer restoration scheme improves the recovery success rate and minimizes the overall recovery time.

  3. Application of the Naive Bayesian Classifier to optimize treatment decisions

    International Nuclear Information System (INIS)

    Kazmierska, Joanna; Malicki, Julian

    2008-01-01

    Background and purpose: To study the accuracy, specificity and sensitivity of the Naive Bayesian Classifier (NBC) in the assessment of individual risk of cancer relapse or progression after radiotherapy (RT). Materials and methods: Data of 142 brain tumour patients irradiated from 2000 to 2005 were analyzed. Ninety-six attributes related to disease, patient and treatment were chosen. Attributes in binary form consisted of the training set for NBC learning. NBC calculated an individual conditional probability of being assigned to: relapse or progression (1), or no relapse or progression (0) group. Accuracy, attribute selection and quality of classifier were determined by comparison with actual treatment results, leave-one-out and cross validation methods, respectively. Clinical setting test utilized data of 35 patients. Treatment results at classification were unknown and were compared with classification results after 3 months. Results: High classification accuracy (84%), specificity (0.87) and sensitivity (0.80) were achieved, both for classifier training and in progressive clinical evaluation. Conclusions: NBC is a useful tool to support the assessment of individual risk of relapse or progression in patients diagnosed with brain tumour undergoing RT postoperatively

  4. Statistical symmetries in physics

    International Nuclear Information System (INIS)

    Green, H.S.; Adelaide Univ., SA

    1994-01-01

    Every law of physics is invariant under some group of transformations and is therefore the expression of some type of symmetry. Symmetries are classified as geometrical, dynamical or statistical. At the most fundamental level, statistical symmetries are expressed in the field theories of the elementary particles. This paper traces some of the developments from the discovery of Bose statistics, one of the two fundamental symmetries of physics. A series of generalizations of Bose statistics is described. A supersymmetric generalization accommodates fermions as well as bosons, and further generalizations, including parastatistics, modular statistics and graded statistics, accommodate particles with properties such as 'colour'. A factorization of elements of ggl(n b ,n f ) can be used to define truncated boson operators. A general construction is given for q-deformed boson operators, and explicit constructions of the same type are given for various 'deformed' algebras. A summary is given of some of the applications and potential applications. 39 refs., 2 figs

  5. Plasma Soliton Turbulence and Statistical Mechanics

    International Nuclear Information System (INIS)

    Treumann, R.A.; Pottelette, R.

    1999-01-01

    Collisionless kinetic plasma turbulence is described approximately in terms of a superposition of non-interacting solitary waves. We discuss the relevance of such a description under astrophysical conditions. Several types of solitary waves may be of interest in this relation as generators of turbulence and turbulent transport. A consistent theory of turbulence can be given only in a few particular cases when the description can be reduced to the Korteweg-de Vries equation or some other simple equation like the Kadomtsev-Petviashvili equation. It turns out that the soliton turbulence is usually energetically harder than the ordinary weakly turbulent plasma description. This implies that interaction of particles with such kinds of turbulence can lead to stronger acceleration than in ordinary turbulence. However, the description in our model is only classical and non-relativistic. Transport in solitary turbulence is most important for drift wave turbulence. Such waves form solitary drift wave vortices which may provide cross-field transport. A more general discussion is given on transport. In a model of Levy flight trapping of particles in solitons (or solitary turbulence) one finds that the residence time of particles in the region of turbulence may be described by a generalized Lorentzian probability distribution. It is shown that under collisionless equilibrium conditions far away from thermal equilibrium such distributions are natural equilibrium distributions. A consistent thermodynamic description of such media can be given in terms of a generalized Lorentzian statistical mechanics and thermodynamics. (author)

  6. Framework of synchromodal transportation problems

    NARCIS (Netherlands)

    Juncker, M.A.M. de; Huizing, D.; Vecchyo, M.R.O. del; Phillipson, F.; Sangers, A.

    2017-01-01

    Problem statements and solution methods in mathematical synchromodal transportation problems depend greatly on a set of model choices for which no rule of thumb exists. In this paper, a framework is introduced with which the model choices in synchromodal transportation problems can be classified,

  7. Framework of Synchromodal Transportation Problems

    NARCIS (Netherlands)

    Huncker, M.A.M. de; Huizing, D.; Ortega del Vecchyo, M.R.; Phillipson, F.; Sangers, A.

    2017-01-01

    Problem statements and solution methods in mathematical synchromodal transportation problems depend greatly on a set of model choices for which no rule of thumb exists. In this paper, a framework is introduced with which the model choices in synchromodal transportation problems can be classified,

  8. NONINVASIVE DIAGNOSIS OF BLADDER CANCER BY CROSS-POLARIZATION OPTICAL COHERENCE TOMOGRAPHY: A BLIND STATISTICAL STUDY

    Directory of Open Access Journals (Sweden)

    O. S. Streltsova

    2014-07-01

    Full Text Available Whether cross-polarization (CP optical coherence tomography (OCT could be used to detect early bladder cancer was ascertained; it was compared with traditional OCT within the framework of blind (closed clinical statistical studies. One hundred and sixteen patients with local nonexophytic (flat pathological processes of the bladder were examined; 360 CP OCT images were obtained and analyzed. The study used an OCT 1300-U CP optical coherence tomographer. CP OCT showed a high (94% sensitivity and a high (84% specificity in the identification of suspected nonexophytic areas in the urinary bladder.

  9. Statistical analyses of local transport coefficients in Ohmic ASDEX discharges

    International Nuclear Information System (INIS)

    Simmet, E.; Stroth, U.; Wagner, F.; Fahrbach, H.U.; Herrmann, W.; Kardaun, O.J.W.F.; Mayer, H.M.

    1991-01-01

    Tokamak energy transport is still an unsolved problem. Many theoretical models have been developed, which try to explain the anomalous high energy-transport coefficients. Up to now these models have been applied to global plasma parameters. A comparison of transport coefficients with global confinement time is only conclusive if the transport is dominated by one process across the plasma diameter. This, however, is not the case in most Ohmic confinement regimes, where at least three different transport mechanisms play an important role. Sawtooth activity leads to an increase in energy transport in the plasma centre. In the intermediate region turbulent transport is expected. Candidates here are drift waves and resistive fluid turbulences. At the edge, ballooning modes or rippling modes could dominate the transport. For the intermediate region, one can deduce theoretical scaling laws for τ E from turbulent theories. Predicted scalings reproduce the experimentally found density dependence of τ E in the linear Ohmic confinement regime (LOC) and the saturated regime (SOC), but they do not show the correct dependence on the isotope mass. The relevance of these transport theories can only be tested in comparing them to experimental local transport coefficients. To this purpose we have performed transport calculations on more than a hundred Ohmic ASDEX discharges. By Principal Component Analysis we determine the dimensionless components which dominate the transport coefficients and we compare the results to the predictions of various theories. (author) 6 refs., 2 figs., 1 tab

  10. Neutron slowing down and transport in monoisotopic media with constant cross sections or with a square-well minimum

    International Nuclear Information System (INIS)

    Peng, W.H.

    1977-01-01

    A specialized moments-method computer code was constructed for the calculation of the even spatial moments of the scalar flux, phi/sub 2n/, through 2n = 80. Neutron slowing-down and transport in a medium with constant cross sections was examined and the effect of a superimposed square-well cross section minimum on the penetrating flux was studied. In the constant cross section case, for nuclei that are not too light, the scalar flux is essentially independent of the nuclide mass. The numerical results obtained were used to test the validity of existing analytic approximations to the flux at both small and large lethargies relative to the source energy. As a result it was possible to define the regions in the lethargy--distance plane where these analytic solutions apply with reasonable accuracy. A parametric study was made of the effect of a square-well cross section minimum on neutron fluxes at energies below the minimum. It was shown that the flux at energies well below the minimum is essentially independent of the position of the minimum in lethargy. The results can be described by a convolution-of-sources model involving only the lethargy separation between detector and source, the width and the relative depth of the minimum. On the basis of the computations and the corresponding model, it is possible to predict, e.g., the conditions under which transport in the region of minimum completely determines the penetrating flux. At the other extreme, the model describes when the transport in the minimum can be treated in the same manner as in any comparable lethargy interval. With the aid of these criteria it is possible to understand the apparent paradoxical effects of certain minima in neutron penetration through such media as iron and sodium

  11. Introducing StatHand: A cross-platform mobile application to support students’ statistical decision making

    Directory of Open Access Journals (Sweden)

    Peter James Allen

    2016-02-01

    Full Text Available Although essential to professional competence in psychology, quantitative research methods are a known area of weakness for many undergraduate psychology students. Students find selecting appropriate statistical tests and procedures for different types of research questions, hypotheses and data types particularly challenging, and these skills are not often practiced in class. Decision trees (a type of graphic organizer are known to facilitate this decision making process, but extant trees have a number of limitations. Furthermore, emerging research suggests that mobile technologies offer many possibilities for facilitating learning. It is within this context that we have developed StatHand, a free cross-platform application designed to support students’ statistical decision making. Developed with the support of the Australian Government Office for Learning and Teaching, StatHand guides users through a series of simple, annotated questions to help them identify a statistical test or procedure appropriate to their circumstances. It further offers the guidance necessary to run these tests and procedures, then interpret and report their results. In this Technology Report we will overview the rationale behind StatHand, before describing the feature set of the application. We will then provide guidelines for integrating StatHand into the research methods curriculum, before concluding by outlining our road map for the ongoing development and evaluation of StatHand.

  12. Speaker gender identification based on majority vote classifiers

    Science.gov (United States)

    Mezghani, Eya; Charfeddine, Maha; Nicolas, Henri; Ben Amar, Chokri

    2017-03-01

    Speaker gender identification is considered among the most important tools in several multimedia applications namely in automatic speech recognition, interactive voice response systems and audio browsing systems. Gender identification systems performance is closely linked to the selected feature set and the employed classification model. Typical techniques are based on selecting the best performing classification method or searching optimum tuning of one classifier parameters through experimentation. In this paper, we consider a relevant and rich set of features involving pitch, MFCCs as well as other temporal and frequency-domain descriptors. Five classification models including decision tree, discriminant analysis, nave Bayes, support vector machine and k-nearest neighbor was experimented. The three best perming classifiers among the five ones will contribute by majority voting between their scores. Experimentations were performed on three different datasets spoken in three languages: English, German and Arabic in order to validate language independency of the proposed scheme. Results confirm that the presented system has reached a satisfying accuracy rate and promising classification performance thanks to the discriminating abilities and diversity of the used features combined with mid-level statistics.

  13. Statistical assessment of numerous Monte Carlo tallies

    International Nuclear Information System (INIS)

    Kiedrowski, Brian C.; Solomon, Clell J.

    2011-01-01

    Four tests are developed to assess the statistical reliability of collections of tallies that number in thousands or greater. To this end, the relative-variance density function is developed and its moments are studied using simplified, non-transport models. The statistical tests are performed upon the results of MCNP calculations of three different transport test problems and appear to show that the tests are appropriate indicators of global statistical quality. (author)

  14. Classification of Focal and Non Focal Epileptic Seizures Using Multi-Features and SVM Classifier.

    Science.gov (United States)

    Sriraam, N; Raghu, S

    2017-09-02

    Identifying epileptogenic zones prior to surgery is an essential and crucial step in treating patients having pharmacoresistant focal epilepsy. Electroencephalogram (EEG) is a significant measurement benchmark to assess patients suffering from epilepsy. This paper investigates the application of multi-features derived from different domains to recognize the focal and non focal epileptic seizures obtained from pharmacoresistant focal epilepsy patients from Bern Barcelona database. From the dataset, five different classification tasks were formed. Total 26 features were extracted from focal and non focal EEG. Significant features were selected using Wilcoxon rank sum test by setting p-value (p z > 1.96) at 95% significance interval. Hypothesis was made that the effect of removing outliers improves the classification accuracy. Turkey's range test was adopted for pruning outliers from feature set. Finally, 21 features were classified using optimized support vector machine (SVM) classifier with 10-fold cross validation. Bayesian optimization technique was adopted to minimize the cross-validation loss. From the simulation results, it was inferred that the highest sensitivity, specificity, and classification accuracy of 94.56%, 89.74%, and 92.15% achieved respectively and found to be better than the state-of-the-art approaches. Further, it was observed that the classification accuracy improved from 80.2% with outliers to 92.15% without outliers. The classifier performance metrics ensures the suitability of the proposed multi-features with optimized SVM classifier. It can be concluded that the proposed approach can be applied for recognition of focal EEG signals to localize epileptogenic zones.

  15. Comparing performance of 30-day readmission risk classifiers among hospitalized primary care patients.

    Science.gov (United States)

    Garrison, Gregory M; Robelia, Paul M; Pecina, Jennifer L; Dawson, Nancy L

    2017-06-01

    Hospital readmission within 30 days of discharge occurs in almost 20% of US Medicare patients and may be a marker of poor quality inpatient care, ineffective hospital to home transitions, or disease severity. Within a patient centered medical home, care transition interventions may only be practical from cost and staffing perspectives if targeted at patients with the greatest risk of readmission. Various scoring algorithms attempt to predict patients at risk for 30-day readmission, but head-to-head comparison of performance is lacking. Compare published scoring algorithms which use generally available electronic medical record data on the same set of hospitalized primary care patients. The LACE index, the LACE+ index, the HOSPITAL score, and the readmission risk score were computed on a consecutive cohort of 26,278 hospital admissions. Classifier performance was assessed by plotting receiver operating characteristic curves comparing the computed score with the actual outcome of death or readmission within 30 days. Statistical significance of differences in performance was assessed using bootstrapping techniques. Correct readmission classification on this cohort was moderate with the following c-statistics: Readmission risk score 0.666; LACE 0.680; LACE+ 0.662; and HOSPITAL 0.675. There was no statistically significant difference in performance between classifiers. Logistic regression based classifiers yield only moderate performance when utilized to predict 30-day readmissions. The task is difficult due to the variety of underlying causes for readmission, nonlinearity, and the arbitrary time period of concern. More sophisticated classification techniques may be necessary to increase performance and allow patient centered medical homes to effectively focus efforts to reduce readmissions. © 2016 John Wiley & Sons, Ltd.

  16. Deep Learning to Classify Radiology Free-Text Reports.

    Science.gov (United States)

    Chen, Matthew C; Ball, Robyn L; Yang, Lingyao; Moradzadeh, Nathaniel; Chapman, Brian E; Larson, David B; Langlotz, Curtis P; Amrhein, Timothy J; Lungren, Matthew P

    2018-03-01

    Purpose To evaluate the performance of a deep learning convolutional neural network (CNN) model compared with a traditional natural language processing (NLP) model in extracting pulmonary embolism (PE) findings from thoracic computed tomography (CT) reports from two institutions. Materials and Methods Contrast material-enhanced CT examinations of the chest performed between January 1, 1998, and January 1, 2016, were selected. Annotations by two human radiologists were made for three categories: the presence, chronicity, and location of PE. Classification of performance of a CNN model with an unsupervised learning algorithm for obtaining vector representations of words was compared with the open-source application PeFinder. Sensitivity, specificity, accuracy, and F1 scores for both the CNN model and PeFinder in the internal and external validation sets were determined. Results The CNN model demonstrated an accuracy of 99% and an area under the curve value of 0.97. For internal validation report data, the CNN model had a statistically significant larger F1 score (0.938) than did PeFinder (0.867) when classifying findings as either PE positive or PE negative, but no significant difference in sensitivity, specificity, or accuracy was found. For external validation report data, no statistical difference between the performance of the CNN model and PeFinder was found. Conclusion A deep learning CNN model can classify radiology free-text reports with accuracy equivalent to or beyond that of an existing traditional NLP model. © RSNA, 2017 Online supplemental material is available for this article.

  17. A phenomenological model for cross-field plasma transport in non-ambipolar scrape-off layers

    International Nuclear Information System (INIS)

    LaBombard, B.; Grossman, A.A.; Conn, R.W.

    1990-01-01

    A simplified two-fluid transport model which includes phenomenological coefficients of particle diffusion, mobility, and thermal diffusivity is used to investigate the effects of nonambipolar particle transport on scrape-off layer (SOL) plasma profiles. A computer code (BSOLRAD3) has been written to iteratively solve for 2-D cross-field density, potential, and electron temperature profiles for arbitrary boundary conditions, including segments of 'limiters' that are electrically conducting or non-conducting. Numerical results are presented for two test cases: (1) a 1-D slab geometry showing the interdependency of the density, potential, and temperature gradient scale lengths on particle diffusion, mobility, and thermal diffusivity coefficients and limiter bias conditions, and (2) a 2-D geometry illustrating ExB plasma flow effects. It is shown that the SOL profiles can be quite sensitive to non-ambipolarity conditions imposed by the limiter and, in particular, whether the limiter surfaces are biased. Such effects, if overlooked in SOL transport analysis, can lead to erroreous conclusions about the magnitude of the local ambipolar diffusion coefficient. (orig.)

  18. Zero-crossing statistics for non-Markovian time series.

    Science.gov (United States)

    Nyberg, Markus; Lizana, Ludvig; Ambjörnsson, Tobias

    2018-03-01

    In applications spanning from image analysis and speech recognition to energy dissipation in turbulence and time-to failure of fatigued materials, researchers and engineers want to calculate how often a stochastic observable crosses a specific level, such as zero. At first glance this problem looks simple, but it is in fact theoretically very challenging, and therefore few exact results exist. One exception is the celebrated Rice formula that gives the mean number of zero crossings in a fixed time interval of a zero-mean Gaussian stationary process. In this study we use the so-called independent interval approximation to go beyond Rice's result and derive analytic expressions for all higher-order zero-crossing cumulants and moments. Our results agree well with simulations for the non-Markovian autoregressive model.

  19. Zero-crossing statistics for non-Markovian time series

    Science.gov (United States)

    Nyberg, Markus; Lizana, Ludvig; Ambjörnsson, Tobias

    2018-03-01

    In applications spanning from image analysis and speech recognition to energy dissipation in turbulence and time-to failure of fatigued materials, researchers and engineers want to calculate how often a stochastic observable crosses a specific level, such as zero. At first glance this problem looks simple, but it is in fact theoretically very challenging, and therefore few exact results exist. One exception is the celebrated Rice formula that gives the mean number of zero crossings in a fixed time interval of a zero-mean Gaussian stationary process. In this study we use the so-called independent interval approximation to go beyond Rice's result and derive analytic expressions for all higher-order zero-crossing cumulants and moments. Our results agree well with simulations for the non-Markovian autoregressive model.

  20. 49 CFR 236.787 - Protection, cross.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 4 2010-10-01 2010-10-01 false Protection, cross. 236.787 Section 236.787 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD ADMINISTRATION... Protection, cross. An arrangement to prevent the improper operation of a signal, switch, movable-point frog...

  1. Statistical Study in the mid-altitude cusp region: wave and particle data comparison using a normalized cusp crossing duration

    Science.gov (United States)

    Grison, B.; Escoubet, C. P.; Pitout, F.; Cornilleau-Wehrlin, N.; Dandouras, I.; Lucek, E.

    2009-04-01

    In the mid altitude cusp region the DC magnetic field presents a diamagnetic cavity due to intense ion earthward flux coming from the magnetosheath. A strong ultra low frequency (ULF) magnetic activity is also commonly observed in this region. Most of the mid altitude cusp statistical studies have focused on the location of the cusp and its dependence and response to solar wind, interplanetary magnetic field, dipole tilt angle parameters. In our study we use the database build by Pitout et al. (2006) in order to study the link of wave power in the ULF range (0.35-10Hz) measured by STAFF SC instrument with the ion plasma properties as measured by CIS (and CODIF) instrument as well as the diamagnetic cavity in the mid-altitude cusp region with FGM data. To compare the different crossings we don`t use the cusp position and dynamics but we use a normalized cusp crossing duration that permits to easily average the properties over a large number of crossings. As usual in the cusp, it is particularly relevant to sort the crossings by the corresponding interplanetary magnetic field (IMF) orientation in order to analyse the results. In particular we try to find out what is the most relevant parameter to link the strong wave activity with. The global statistic confirms previous single case observations that have noticed a simultaneity between ion injections and wave activity enhancements. We will also present results concerning other ion parameters and the diamagnetic cavity observed in the mid altitude cusp region.

  2. Classifying aging as a disease in the context of ICD-11.

    Science.gov (United States)

    Zhavoronkov, Alex; Bhullar, Bhupinder

    2015-01-01

    Aging is a complex continuous multifactorial process leading to loss of function and crystalizing into the many age-related diseases. Here, we explore the arguments for classifying aging as a disease in the context of the upcoming World Health Organization's 11th International Statistical Classification of Diseases and Related Health Problems (ICD-11), expected to be finalized in 2018. We hypothesize that classifying aging as a disease with a "non-garbage" set of codes will result in new approaches and business models for addressing aging as a treatable condition, which will lead to both economic and healthcare benefits for all stakeholders. Actionable classification of aging as a disease may lead to more efficient allocation of resources by enabling funding bodies and other stakeholders to use quality-adjusted life years (QALYs) and healthy-years equivalent (HYE) as metrics when evaluating both research and clinical programs. We propose forming a Task Force to interface the WHO in order to develop a multidisciplinary framework for classifying aging as a disease with multiple disease codes facilitating for therapeutic interventions and preventative strategies.

  3. Mercury⊕: An evidential reasoning image classifier

    Science.gov (United States)

    Peddle, Derek R.

    1995-12-01

    MERCURY⊕ is a multisource evidential reasoning classification software system based on the Dempster-Shafer theory of evidence. The design and implementation of this software package is described for improving the classification and analysis of multisource digital image data necessary for addressing advanced environmental and geoscience applications. In the remote-sensing context, the approach provides a more appropriate framework for classifying modern, multisource, and ancillary data sets which may contain a large number of disparate variables with different statistical properties, scales of measurement, and levels of error which cannot be handled using conventional Bayesian approaches. The software uses a nonparametric, supervised approach to classification, and provides a more objective and flexible interface to the evidential reasoning framework using a frequency-based method for computing support values from training data. The MERCURY⊕ software package has been implemented efficiently in the C programming language, with extensive use made of dynamic memory allocation procedures and compound linked list and hash-table data structures to optimize the storage and retrieval of evidence in a Knowledge Look-up Table. The software is complete with a full user interface and runs under Unix, Ultrix, VAX/VMS, MS-DOS, and Apple Macintosh operating system. An example of classifying alpine land cover and permafrost active layer depth in northern Canada is presented to illustrate the use and application of these ideas.

  4. Building gene expression profile classifiers with a simple and efficient rejection option in R.

    Science.gov (United States)

    Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco; Savino, Alessandro; Hafeezurrehman, Hafeez

    2011-01-01

    The collection of gene expression profiles from DNA microarrays and their analysis with pattern recognition algorithms is a powerful technology applied to several biological problems. Common pattern recognition systems classify samples assigning them to a set of known classes. However, in a clinical diagnostics setup, novel and unknown classes (new pathologies) may appear and one must be able to reject those samples that do not fit the trained model. The problem of implementing a rejection option in a multi-class classifier has not been widely addressed in the statistical literature. Gene expression profiles represent a critical case study since they suffer from the curse of dimensionality problem that negatively reflects on the reliability of both traditional rejection models and also more recent approaches such as one-class classifiers. This paper presents a set of empirical decision rules that can be used to implement a rejection option in a set of multi-class classifiers widely used for the analysis of gene expression profiles. In particular, we focus on the classifiers implemented in the R Language and Environment for Statistical Computing (R for short in the remaining of this paper). The main contribution of the proposed rules is their simplicity, which enables an easy integration with available data analysis environments. Since in the definition of a rejection model tuning of the involved parameters is often a complex and delicate task, in this paper we exploit an evolutionary strategy to automate this process. This allows the final user to maximize the rejection accuracy with minimum manual intervention. This paper shows how the use of simple decision rules can be used to help the use of complex machine learning algorithms in real experimental setups. The proposed approach is almost completely automated and therefore a good candidate for being integrated in data analysis flows in labs where the machine learning expertise required to tune traditional

  5. SU-E-T-112: An OpenCL-Based Cross-Platform Monte Carlo Dose Engine (oclMC) for Coupled Photon-Electron Transport

    International Nuclear Information System (INIS)

    Tian, Z; Shi, F; Folkerts, M; Qin, N; Jiang, S; Jia, X

    2015-01-01

    Purpose: Low computational efficiency of Monte Carlo (MC) dose calculation impedes its clinical applications. Although a number of MC dose packages have been developed over the past few years, enabling fast MC dose calculations, most of these packages were developed under NVidia’s CUDA environment. This limited their code portability to other platforms, hindering the introduction of GPU-based MC dose engines to clinical practice. To solve this problem, we developed a cross-platform fast MC dose engine named oclMC under OpenCL environment for external photon and electron radiotherapy. Methods: Coupled photon-electron simulation was implemented with standard analogue simulation scheme for photon transport and Class II condensed history scheme for electron transport. We tested the accuracy and efficiency of oclMC by comparing the doses calculated using oclMC and gDPM, a previously developed GPU-based MC code on NVidia GPU platform, for a 15MeV electron beam and a 6MV photon beam in a homogenous water phantom, a water-bone-lung-water slab phantom and a half-slab phantom. We also tested code portability of oclMC on different devices, including an NVidia GPU, two AMD GPUs and an Intel CPU. Results: Satisfactory agreements were observed in all photon and electron cases, with ∼0.48%–0.53% average dose differences at regions within 10% isodose line for electron beam cases and ∼0.15%–0.17% for photon beam cases. It took oclMC 3–4 sec to perform transport simulation for electron beam on NVidia Titan GPU and 35–51 sec for photon beam, both with ∼0.5% statistical uncertainty. The computation was 6%–17% slower than gDPM due to the differences in both physics model and development environment, which is considered not significant for clinical applications. In terms of code portability, gDPM only runs on NVidia GPUs, while oclMC successfully runs on all the tested devices. Conclusion: oclMC is an accurate and fast MC dose engine. Its high cross

  6. SU-E-T-112: An OpenCL-Based Cross-Platform Monte Carlo Dose Engine (oclMC) for Coupled Photon-Electron Transport

    Energy Technology Data Exchange (ETDEWEB)

    Tian, Z; Shi, F; Folkerts, M; Qin, N; Jiang, S; Jia, X [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States)

    2015-06-15

    Purpose: Low computational efficiency of Monte Carlo (MC) dose calculation impedes its clinical applications. Although a number of MC dose packages have been developed over the past few years, enabling fast MC dose calculations, most of these packages were developed under NVidia’s CUDA environment. This limited their code portability to other platforms, hindering the introduction of GPU-based MC dose engines to clinical practice. To solve this problem, we developed a cross-platform fast MC dose engine named oclMC under OpenCL environment for external photon and electron radiotherapy. Methods: Coupled photon-electron simulation was implemented with standard analogue simulation scheme for photon transport and Class II condensed history scheme for electron transport. We tested the accuracy and efficiency of oclMC by comparing the doses calculated using oclMC and gDPM, a previously developed GPU-based MC code on NVidia GPU platform, for a 15MeV electron beam and a 6MV photon beam in a homogenous water phantom, a water-bone-lung-water slab phantom and a half-slab phantom. We also tested code portability of oclMC on different devices, including an NVidia GPU, two AMD GPUs and an Intel CPU. Results: Satisfactory agreements were observed in all photon and electron cases, with ∼0.48%–0.53% average dose differences at regions within 10% isodose line for electron beam cases and ∼0.15%–0.17% for photon beam cases. It took oclMC 3–4 sec to perform transport simulation for electron beam on NVidia Titan GPU and 35–51 sec for photon beam, both with ∼0.5% statistical uncertainty. The computation was 6%–17% slower than gDPM due to the differences in both physics model and development environment, which is considered not significant for clinical applications. In terms of code portability, gDPM only runs on NVidia GPUs, while oclMC successfully runs on all the tested devices. Conclusion: oclMC is an accurate and fast MC dose engine. Its high cross

  7. Simultaneous fitting of statistical-model parameters to symmetric and asymmetric fission cross sections

    International Nuclear Information System (INIS)

    Mancusi, D; Charity, R J; Cugnon, J

    2013-01-01

    The de-excitation of compound nuclei has been successfully described for several decades by means of statistical models. However, accurate predictions require some fine-tuning of the model parameters. This task can be simplified by studying several entrance channels, which populate different regions of the parameter space of the compound nucleus. Fusion reactions play an important role in this strategy because they minimise the uncertainty on the entrance channel by fixing mass, charge and excitation energy of the compound nucleus. If incomplete fusion is negligible, the only uncertainty on the compound nucleus comes from the spin distribution. However, some de-excitation channels, such as fission, are quite sensitive to spin. Other entrance channels can then be used to discriminate between equivalent parameter sets. The focus of this work is on fission and intermediate-mass-fragment emission cross sections of compound nuclei with 70 70 ≲ A ≲ 240. 240. The statistical de-excitation model is GEMINI++. The choice of the observables is natural in the framework of GEMINI++, which describes fragment emission using a fissionlike formalism. Equivalent parameter sets for fusion reactions can be resolved using the spallation entrance channel. This promising strategy can lead to the identification of a minimal set of physical ingredients necessary for a unified quantitative description of nuclear de-excitation.

  8. Quantum ensembles of quantum classifiers.

    Science.gov (United States)

    Schuld, Maria; Petruccione, Francesco

    2018-02-09

    Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

  9. Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

    Directory of Open Access Journals (Sweden)

    J. Sunil Rao

    2007-01-01

    Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

  10. Research into 2D Dynamics and Control of Small Oscillations of a Cross-Beam during Transportation by Two Overhead Cranes

    Directory of Open Access Journals (Sweden)

    Alexander V. Perig

    2017-01-01

    Full Text Available A new mathematical model of a 3DOF 2D mechanical system “transported cross-beam, two moving bridge cranes” has been proposed. Small system oscillations have been derived through the introduction of Lagrange equations. The numerical estimation of 3DOF system motion has been carried out with equation-based Modelica language. The present article uses the Lagrange method and numerical and optimization methods, realized with JModelica.org and Optimica freeware. The absolute swaying of the cross-beam with respect to the displacement of the two moving bridge cranes was estimated. The phase portraits of the 3DOF system for linear and angular coordinates were presented. An open loop optimal control problem was posed for the motion of the bridge cranes. A “bang-bang” control strategy was implemented for the derivation of an optimal control solution, which enables the travel of two bridge cranes at a prescribed distance for minimum time and minimum swaying of a heavy cross-beam. The derived results of the numerical simulation can be easily practically realized by crane operators with good agreement with simple engineering estimations. The proposed control strategy enables synchronous motion of two bridge cranes with a cross-beam that practically solves the posed problem of unwanted excessive oscillations of a heavy cross-beam during transportation.

  11. Using GPS-derived speed patterns for recognition of transport modes in adults.

    Science.gov (United States)

    Huss, Anke; Beekhuizen, Johan; Kromhout, Hans; Vermeulen, Roel

    2014-10-11

    Identification of active or sedentary modes of transport is of relevance for studies assessing physical activity or addressing exposure assessment. We assessed in a proof-of-principle study if speed as logged by GPSs could be used to identify modes of transport (walking, bicycling, and motorized transport: car, bus or train). 12 persons commuting to work walking, bicycling or with motorized transport carried GPSs for two commutes and recorded their mode of transport. We evaluated seven speed metrics: mean, 95th percentile of speed, standard deviation of the mean, rate-of-change, standardized-rate-of-change, acceleration and deceleration. We assessed which speed metric would best identify the transport mode using discriminant analyses. We applied cross validation and calculated agreement (Cohen's Kappa) between actual and derived modes of transport. Mode of transport was reliably classified whenever a person used a mode of transport for longer than one minute. Best results were observed when using the 95th percentile of speed, acceleration and deceleration (kappa 0.73). When we combined all motorized traffic into one category, kappa increased to 0.95. GPS-measured speed enable the identification of modes of transport. Given the current low costs of GPS devices and the built-in capacity of GPS tracking in most smartphones, the use of such devices in large epidemiological studies may facilitate the assessment of physical activity related to transport modes, or improve exposure assessment using automated travel mode detection.

  12. EVALUATION OF THE FREQUENCY OF DIAGNOSTICS OF COMPONENTS AND ASSEMBLIES FOR TRANSPORT AND TECHNOLOGICAL MACHINES ON THE BASIS OF HIDDEN MARKOV CHAINS

    Directory of Open Access Journals (Sweden)

    Andrey Borisovich Nikolaev

    2017-05-01

    Full Text Available In this article a statistical analysis of supply volumes of spare parts, components and accessories was carried out, with some persistent patterns and laws of distribution of failures of major components revealed. There are suggested evaluation models of components and assemblies reliability for the formation of order management procedures of spare parts, components and accessories for the maintenance and repair of transport and technological machines. For the purpose of identification of components operational condition there is proposed a model of hidden Markov chain which allows to classify the condition by indirect evidence, based on the collected statistics.

  13. Transport coefficients and cross sections for electrons in water vapour: Comparison of cross section sets using an improved Boltzmann equation solution

    Science.gov (United States)

    Ness, K. F.; Robson, R. E.; Brunger, M. J.; White, R. D.

    2012-01-01

    This paper revisits the issues surrounding computation of electron transport properties in water vapour as a function of E/n0 (the ratio of the applied electric field to the water vapour number density) up to 1200 Td. We solve the Boltzmann equation using an improved version of the code of Ness and Robson [Phys. Rev. A 38, 1446 (1988)], facilitating the calculation of transport coefficients to a considerably higher degree of accuracy. This allows a correspondingly more discriminating test of the various electron-water vapour cross section sets proposed by a number of authors, which has become an important issue as such sets are now being applied to study electron driven processes in atmospheric phenomena [P. Thorn, L. Campbell, and M. Brunger, PMC Physics B 2, 1 (2009)] and in modeling charged particle tracks in matter [A. Munoz, F. Blanco, G. Garcia, P. A. Thorn, M. J. Brunger, J. P. Sullivan, and S. J. Buckman, Int. J. Mass Spectrom. 277, 175 (2008)].

  14. Data and Statistics: Heart Failure

    Science.gov (United States)

    ... Summary Coverdell Program 2012-2015 State Summaries Data & Statistics Fact Sheets Heart Disease and Stroke Fact Sheets ... Roadmap for State Planning Other Data Resources Other Statistic Resources Grantee Information Cross-Program Information Online Tools ...

  15. An outline review of numerical transport methods

    International Nuclear Information System (INIS)

    Budd, C.

    1981-01-01

    A brief review is presented of numerical methods for solving the neutron transport equation in the context of reactor physics. First the various forms of transport equation are given. Second, the various ways of classifying numerical transport methods are discussed. Finally each method (or class of methods) is outlined in turn. (U.K.)

  16. Transportation of hazardous materials (hazmat a literature survey

    Directory of Open Access Journals (Sweden)

    Zafer YILMAZ

    2016-02-01

    Full Text Available ransportation has a great role in logistics. Many researchers have studied on transportation and vehicle routing problems. Transportation of hazardous materials (hazmat is a special subject for logistics. Causalities due to the accidents caused by trucks carrying hazardous materials will be intolerable. Many researchers have studied on risk assessment of hazmat transportation to find ways for reducing hazardous material transportation risks. Some researchers have studied routing of hazmat trucks. The emergency response models and network design problems for hazmat transportation were also studied by some researchers. The transportation of hazmats can also be classified according to the mode of transport. Mainly roads are used for hazmat transportation but some shipments are intermodal. There has been a great amount of effort spent to find convenient ways for hazmat transportation. In this study, a literature survey for the articles about hazmat transportation is prepared. After pointing out the importance of hazmat transportation by the example of US hazmat transportation data, the studies on hazmat transportation since 2005 have been examined. Totally 88 articles are classified as risk, routing, routing and scheduling, emergency response, network design and accident analysis. What can be studied in future researches is pointed out.Keywords: Hazardous materials, Network design, Transportation, Routing, Risk assessment

  17. Nonlocal transport in the presence of transport barriers

    Science.gov (United States)

    Del-Castillo-Negrete, D.

    2013-10-01

    There is experimental, numerical, and theoretical evidence that transport in plasmas can, under certain circumstances, depart from the standard local, diffusive description. Examples include fast pulse propagation phenomena in perturbative experiments, non-diffusive scaling in L-mode plasmas, and non-Gaussian statistics of fluctuations. From the theoretical perspective, non-diffusive transport descriptions follow from the relaxation of the restrictive assumptions (locality, scale separation, and Gaussian/Markovian statistics) at the foundation of diffusive models. We discuss an alternative class of models able to capture some of the observed non-diffusive transport phenomenology. The models are based on a class of nonlocal, integro-differential operators that provide a unifying framework to describe non- Fickian scale-free transport, and non-Markovian (memory) effects. We study the interplay between nonlocality and internal transport barriers (ITBs) in perturbative transport including cold edge pulses and power modulation. Of particular interest in the nonlocal ``tunnelling'' of perturbations through ITBs. Also, flux-gradient diagrams are discussed as diagnostics to detect nonlocal transport processes in numerical simulations and experiments. Work supported by the US Department of Energy.

  18. Statistical process control using optimized neural networks: a case study.

    Science.gov (United States)

    Addeh, Jalil; Ebrahimzadeh, Ata; Azarbad, Milad; Ranaee, Vahid

    2014-09-01

    The most common statistical process control (SPC) tools employed for monitoring process changes are control charts. A control chart demonstrates that the process has altered by generating an out-of-control signal. This study investigates the design of an accurate system for the control chart patterns (CCPs) recognition in two aspects. First, an efficient system is introduced that includes two main modules: feature extraction module and classifier module. In the feature extraction module, a proper set of shape features and statistical feature are proposed as the efficient characteristics of the patterns. In the classifier module, several neural networks, such as multilayer perceptron, probabilistic neural network and radial basis function are investigated. Based on an experimental study, the best classifier is chosen in order to recognize the CCPs. Second, a hybrid heuristic recognition system is introduced based on cuckoo optimization algorithm (COA) algorithm to improve the generalization performance of the classifier. The simulation results show that the proposed algorithm has high recognition accuracy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  19. Krylov iterative methods and synthetic acceleration for transport in binary statistical media

    International Nuclear Information System (INIS)

    Fichtl, Erin D.; Warsa, James S.; Prinja, Anil K.

    2009-01-01

    In particle transport applications there are numerous physical constructs in which heterogeneities are randomly distributed. The quantity of interest in these problems is the ensemble average of the flux, or the average of the flux over all possible material 'realizations.' The Levermore-Pomraning closure assumes Markovian mixing statistics and allows a closed, coupled system of equations to be written for the ensemble averages of the flux in each material. Generally, binary statistical mixtures are considered in which there are two (homogeneous) materials and corresponding coupled equations. The solution process is iterative, but convergence may be slow as either or both materials approach the diffusion and/or atomic mix limits. A three-part acceleration scheme is devised to expedite convergence, particularly in the atomic mix-diffusion limit where computation is extremely slow. The iteration is first divided into a series of 'inner' material and source iterations to attenuate the diffusion and atomic mix error modes separately. Secondly, atomic mix synthetic acceleration is applied to the inner material iteration and S 2 synthetic acceleration to the inner source iterations to offset the cost of doing several inner iterations per outer iteration. Finally, a Krylov iterative solver is wrapped around each iteration, inner and outer, to further expedite convergence. A spectral analysis is conducted and iteration counts and computing cost for the new two-step scheme are compared against those for a simple one-step iteration, to which a Krylov iterative method can also be applied.

  20. Fusion of classifiers for REIS-based detection of suspicious breast lesions

    Science.gov (United States)

    Lederman, Dror; Wang, Xingwei; Zheng, Bin; Sumkin, Jules H.; Tublin, Mitchell; Gur, David

    2011-03-01

    After developing a multi-probe resonance-frequency electrical impedance spectroscopy (REIS) system aimed at detecting women with breast abnormalities that may indicate a developing breast cancer, we have been conducting a prospective clinical study to explore the feasibility of applying this REIS system to classify younger women (breast cancer. The system comprises one central probe placed in contact with the nipple, and six additional probes uniformly distributed along an outside circle to be placed in contact with six points on the outer breast skin surface. In this preliminary study, we selected an initial set of 174 examinations on participants that have completed REIS examinations and have clinical status verification. Among these, 66 examinations were recommended for biopsy due to findings of a highly suspicious breast lesion ("positives"), and 108 were determined as negative during imaging based procedures ("negatives"). A set of REIS-based features, extracted using a mirror-matched approach, was computed and fed into five machine learning classifiers. A genetic algorithm was used to select an optimal subset of features for each of the five classifiers. Three fusion rules, namely sum rule, weighted sum rule and weighted median rule, were used to combine the results of the classifiers. Performance evaluation was performed using a leave-one-case-out cross-validation method. The results indicated that REIS may provide a new technology to identify younger women with higher than average risk of having or developing breast cancer. Furthermore, it was shown that fusion rule, such as a weighted median fusion rule and a weighted sum fusion rule may improve performance as compared with the highest performing single classifier.

  1. Transport upscaling from pore- to Darcy-scale: Incorporating pore-scale Berea sandstone Lagrangian velocity statistics into a Darcy-scale transport CTRW model

    Science.gov (United States)

    Puyguiraud, Alexandre; Dentz, Marco; Gouze, Philippe

    2017-04-01

    For the past several years a lot of attention has been given to pore-scale flow in order to understand and model transport, mixing and reaction in porous media. Nevertheless we believe that an accurate study of spatial and temporal evolution of velocities could bring important additional information for the upscaling from pore to higher scales. To gather these pieces of information, we perform Stokes flow simulations on pore-scale digitized images of a Berea sandstone core. First, micro-tomography (XRMT) imaging and segmentation processes allow us to obtain 3D black and white images of the sample [1]. Then we used an OpenFoam solver to perform the Stokes flow simulations mentioned above, which gives us the velocities at the interfaces of a cubic mesh. Subsequently, we use a particle streamline reconstruction technique which uses the Eulerian velocity field previously obtained. This technique, based on a modified Pollock algorithm [2], enables us to make particle tracking simulations on the digitized sample. In order to build a stochastic pore-scale transport model, we analyze the Lagrangian velocity series in two different ways. First we investigate the velocity evolution by sampling isochronically (t-Lagrangian), and by studying its statistical properties in terms of one- and two-points statistics. Intermittent patterns can be observed. These are due to the persistance of low velocities over a characteristic space length. Other results are investigated, such as correlation functions and velocity PDFs, which permit us to study more deeply this persistence in the velocities and to compute the correlation times. However, with the second approach, doing these same analysis in space by computing the velocities equidistantly, enables us to remove the intermittency shown in the temporal evolution and to model these velocity series as a Markov process. This renders the stochastic particle dynamics into a CTRW [3]. [1] Gjetvaj, F., A. Russian, P. Gouze, and M. Dentz (2015

  2. Cross sections for electron and photon processes required by electron-transport calculations

    International Nuclear Information System (INIS)

    Peek, J.M.

    1979-11-01

    Electron-transport calculations rely on a large collection of electron-atom and photon-atom cross-section data to represent the response characteristics of the target medium. These basic atomic-physics quantities, and certain qualities derived from them that are now commonly in use, are critically reviewed. Publications appearing after 1978 are not given consideration. Processes involving electron or photon energies less than 1 keV are ignored, while an attempt is made to exhaustively cover the remaining independent parameters and target possibilities. Cases for which data improvements can be made from existing information are identified. Ranges of parameters for which state-of-the-art data are not available are sought out, and recommendations for explicit measurements and/or calculations with presently available tools are presented. An attempt is made to identify the maturity of the atomic-physics data and to predict the possibilities for rapid changes in the quality of the data. Finally, weaknesses in the state-of-the-art atomic-physics data and in the conceptual usage of these data in the context of electron-transport theory are discussed. Brief attempts are made to weight the various aspects of these questions and to suggest possible remedies

  3. Transportation Satellite Accounts : A New Way of Measuring Transportation Services in America

    Science.gov (United States)

    2011-01-01

    Transportation Satellite Accounts (TSA), produced by the Bureau of Economic Analysis and the Bureau of Transportation Statistics, provides measures of national transportation output. TSA includes both in-house and for-hire transportation services. Fo...

  4. Machinery Bearing Fault Diagnosis Using Variational Mode Decomposition and Support Vector Machine as a Classifier

    Science.gov (United States)

    Rama Krishna, K.; Ramachandran, K. I.

    2018-02-01

    Crack propagation is a major cause of failure in rotating machines. It adversely affects the productivity, safety, and the machining quality. Hence, detecting the crack’s severity accurately is imperative for the predictive maintenance of such machines. Fault diagnosis is an established concept in identifying the faults, for observing the non-linear behaviour of the vibration signals at various operating conditions. In this work, we find the classification efficiencies for both original and the reconstructed vibrational signals. The reconstructed signals are obtained using Variational Mode Decomposition (VMD), by splitting the original signal into three intrinsic mode functional components and framing them accordingly. Feature extraction, feature selection and feature classification are the three phases in obtaining the classification efficiencies. All the statistical features from the original signals and reconstructed signals are found out in feature extraction process individually. A few statistical parameters are selected in feature selection process and are classified using the SVM classifier. The obtained results show the best parameters and appropriate kernel in SVM classifier for detecting the faults in bearings. Hence, we conclude that better results were obtained by VMD and SVM process over normal process using SVM. This is owing to denoising and filtering the raw vibrational signals.

  5. Do buoyant plumes enhance cross-shelf transport in the Black Sea?

    Science.gov (United States)

    Sedakov, Roman; Zavialov, Peter; Izhitsky, Alexander

    2017-04-01

    Like many inland seas, the Black Sea is exposed to massive continental discharges on the one hand and significant anthropogenic stresses, including pollution, on the other. It is, therefore, important to understand mechanisms of advection of continental water into the sea and factors that may influence transport of such water across shelf areas. In this study, we focus on the coastal segment of the Black Sea between the Feodosia Bay, which includes nature reserve and resort areas, and the Kerch Strait. The Sea of Azov outflow penetrates into the Black Sea through the latter, forming a plume of relatively fresh, light waters with elevated concentrations of suspended matter but also pollutants, especially hydrocarbons. This plume, which can be detected via satellite imagery of the region, extends on over 70 km from the Kerch Strait outfall along Crimea shore and reaches the Feodosia Bay, making that area the most polluted of the Crimea shoreline. In situ velocity measurements were conducted at a mooring station deployed in the area at the depth of 5 and 21.5 meters during the period 17th-23rd of May 2015. These data demonstrated high correlation of the wind stress with the cross-shore component of the velocity in the surface layer and anti-correlation with that in the bottom layer during the periods when a two-layered stratification of the water column due to the occurrence of the Azov plume was present, and lack of such correlation otherwise. In order to investigate whether the buoyant plume in the surface layer is capable of fortifying the wind-driven cross-shelf exchanges, we develop a dynamical model of current forming under the influence of wind tension, pressure gradient and Earth's rotation in a simple one- and a two- layer setups. Firstly, a 2D model was investigated that did not account Coriolis effect. Secondly, a 3D model with Coriolis effect was investigated. The main parameter of the problem is the eddy diffusivity coefficient, which we choose to be

  6. Discrimination of panti p → tanti t events by a neural network classifier

    International Nuclear Information System (INIS)

    Cherubini, A.; Odorico, R.

    1992-01-01

    Neural network and conventional statistical techniques are compared in the problem of discriminating panti p→tanti t events, with top quarks decaying into anything, from the associated hadronic background at the energy of the Fermilab collider. The NN we develop for this sake is an improved version of Kohonen's learning vector quantization scheme. Performance of the NN as a tanti t event classifier is found to be less satisfactory than that achievable by statistical methods. We conclude that the probable reasons for that are: i) The NN approach presents advantages only when dealing with event distributions in the feature space which substantially differ from Gaussians; ii) NN's require much larger training sets of events than statistical discrimination in order to give comparable results. (orig.)

  7. The role of the complete Coriolis force in cross-equatorial transport of the Antarctic Bottom Water

    Science.gov (United States)

    Stewart, Andrew; Dellar, Paul

    2010-05-01

    We investigate the equatorial crossing of the Antarctic Bottom Water using a shallow water model that includes the complete Coriolis force. Most theoretical models of the atmosphere and ocean neglect the component of the Coriolis force associated with the horizontal component of the Earth's rotation vector, the so-called traditional approximation. This approximation is typically justified on the basis that ratio of the ocean depth to the Rossby radius of deformation is negligibly small, H-Rd ≪ 1. However, the steep topography and weak stratification in the abyssal ocean magnify the role of the non-traditional component of the Coriolis force. This is most pronounced in equatorial regions, where the traditional component of the Coriolis force is weakest and the non-traditional component is strongest. The inclusion of the complete Coriolis force gives rise to a range of very long sub-inertial waves, whose frequencies lie below the inertial frequency, in the two-layer shallow water equations. These waves have a dramatically different structure to their traditional counterparts, particularly when the stratification is weak. We focus on the flow of the Antarctic Bottom Water from the Brazil Basin in the western South Atlantic to the Guiana Basin in the western North Atlantic. In this region, the current traverses a deep channel directed westwards and very slightly northwards across the equator. Previous attempts to model this flow have struggled to explain why the cross-equatorial transport is so high, with around 2.0-2.2 Sv exiting at the northern end of the channel. We present analytical and numerical solutions of the non-traditional shallow water equations for the cross-equatorial flow of the Antarctic Bottom Water. We obtain analytical solutions by considering the steady-state flow of a single layer of shallow water through a northwesterly channel with a simple geometry. We assume zero potential vorticity, as it may be shown that fluid whose potential vorticity q

  8. Performance of oil industry cross-country pipelines in Western Europe. Statistical summary of reported spillages: 1978

    Energy Technology Data Exchange (ETDEWEB)

    de Waal, A.; Baradat, Y.

    1979-01-01

    CONCAWE's annual report on oil industry cross-country pipelines in Western Europe shows that in 1978 the pipeline network reached a combined length of 18,500 kilometres and transported 594 million cubic metres of crude oil and refined products. The gross spillage amounted to 3639 m/sup 3/, that is 0.000613 percent or about 6.1 parts per million of the total quantity transported. The net spillage loss was 1,377 m/sup 3/ since 2,262 m/sup 3/ were recovered at site. There were 15 spillage incidents reported during 1978, all of which were directly related to pipelines (none to pump-stations). In 4 incidents the oil spilled was completely recovered, and in 10 cases clean-up was completed within one week of the discovery of the spillage. No contamination of potable water sources was reported. The causes of the spillages are attributed to corrosion (7 incidents), third party activities (4), mechanical failure (3) and natural hazards, i.e. excessive rainfall (1). The report also gives a comparison for the five-year period 1974 to 1978.

  9. Performance of oil industry cross-country pipelines in Western Europe. Statistical summary of reported spillages, 1978

    Energy Technology Data Exchange (ETDEWEB)

    de Waal, A.; Baradat, Y.

    1979-01-01

    CONCAW's annual report on oil industry cross-country pipelines in Western Europe shows that in 1978 the pipeline network reached a combined length of 18,500 kilometers and transported 594 million cubic meters of crude oil and refined products. The gross spillage amounted to 3639 m/sup 3/, that is 0.000613% or about 6.1 ppM of the total quantity transported. The new spillage loss was 1377 m/sup 3/ since 2262 m/sup 3/ were recovered at site. There were 15 spillage incidents reported during 1978, all of which were directly related to pipelines (none to pump-stations). In 4 incidents the oil spilled was completely recovered, and in 10 cases clean-up was completed within one week of the discovery of the spillage. No contamination of potable water sources was reported. The causes of the spillages are attributed to corrosion (7 incidents), third party activities (4), mechanical failure (3) and natural hazards, i.e., excessive rainfall (1). The report also gives a comparison for the five-year period 1974-1978.

  10. Performance of oil industry cross-country pipelines in Western Europe, statistical summary of reported spillages - 1978

    Energy Technology Data Exchange (ETDEWEB)

    de Waal, A.; Baradat, Y.

    CONCAWE's annual report on oil industry cross-country pipelines in Western Europe shows that in 1978 the pipeline network reached a combined length of 18,500 kilometers and transported 594 million cubic meters of crude oil and refined products. The gross spillage amounted to 3639 cu. m, that is 0.000613 per cent or about 6.1 parts per million of the total quantity transported. The net spillage loss was 1,377 cu. m since 2,262 cu. m were recovered at site. There were 15 spillage incidents reported during 1978, all of which were directly related to pipelines (none to pump-stations). In 4 incidents the oil spilled was completely recovered, and in 10 cases clean-up was completed within one week of the discovery of the spillage. No contamination of potable water sources was reported. The causes of the spillages are attributed to corrosion (7 incidents), third party activities (4), mechanical failure (3) and natural hazards, i.e. excessive rainfall (1). The report also gives a comparison for the five-year period 1974-1978. (Copyright (c) CONCAWE 1979.)

  11. Hypothetical Case and Scenario Description for International Transportation of Spent Nuclear Fuel.

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Adam David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Osborn, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Katherine A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kalinina, Elena Arkadievna [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Cohn, Brian [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Thomas, Maikael A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Parks, Mancel Jordan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Parks, Ethan Rutledge [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mohagheghi, Amir H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-12-01

    To support more rigorous analysis on global security issues at Sandia National Laboratories (SNL), there is a need to develop realistic data sets without using "real" data or identifying "real" vulnerabilities, hazards or geopolitically embarrassing shortcomings. In response, an interdisciplinary team led by subject matter experts in SNL's Center for Global Security and Cooperation (CGSC) developed a hypothetical case description. This hypothetical case description assigns various attributes related to international SNF transportation that are representative, illustrative and indicative of "real" characteristics of "real" countries. There is no intent to identify any particular country and any similarity with specific real-world events is purely coincidental. To support the goal of this report to provide a case description (and set of scenarios of concern) for international SNF transportation inclusive of as much "real-world" complexity as possible -- without crossing over into politically sensitive or classified information -- this SAND report provides a subject matter expert-validated (and detailed) description of both technical and political influences on the international transportation of spent nuclear fuel. [PAGE INTENTIONALLY LEFT BLANK

  12. A radial basis classifier for the automatic detection of aspiration in children with dysphagia

    Directory of Open Access Journals (Sweden)

    Blain Stefanie

    2006-07-01

    Full Text Available Abstract Background Silent aspiration or the inhalation of foodstuffs without overt physiological signs presents a serious health issue for children with dysphagia. To date, there are no reliable means of detecting aspiration in the home or community. An assistive technology that performs in these environments could inform caregivers of adverse events and potentially reduce the morbidity and anxiety of the feeding experience for the child and caregiver, respectively. This paper proposes a classifier for automatic classification of aspiration and swallow vibration signals non-invasively recorded on the neck of children with dysphagia. Methods Vibration signals associated with safe swallows and aspirations, both identified via videofluoroscopy, were collected from over 100 children with neurologically-based dysphagia using a single-axis accelerometer. Five potentially discriminatory mathematical features were extracted from the accelerometry signals. All possible combinations of the five features were investigated in the design of radial basis function classifiers. Performance of different classifiers was compared and the best feature sets were identified. Results Optimal feature combinations for two, three and four features resulted in statistically comparable adjusted accuracies with a radial basis classifier. In particular, the feature pairing of dispersion ratio and normality achieved an adjusted accuracy of 79.8 ± 7.3%, a sensitivity of 79.4 ± 11.7% and specificity of 80.3 ± 12.8% for aspiration detection. Addition of a third feature, namely energy, increased adjusted accuracy to 81.3 ± 8.5% but the change was not statistically significant. A closer look at normality and dispersion ratio features suggest leptokurticity and the frequency and magnitude of atypical values as distinguishing characteristics between swallows and aspirations. The achieved accuracies are 30% higher than those reported for bedside cervical auscultation. Conclusion

  13. Proposing an adaptive mutation to improve XCSF performance to classify ADHD and BMD patients

    Science.gov (United States)

    Sadatnezhad, Khadijeh; Boostani, Reza; Ghanizadeh, Ahmad

    2010-12-01

    There is extensive overlap of clinical symptoms observed among children with bipolar mood disorder (BMD) and those with attention deficit hyperactivity disorder (ADHD). Thus, diagnosis according to clinical symptoms cannot be very accurate. It is therefore desirable to develop quantitative criteria for automatic discrimination between these disorders. This study is aimed at designing an efficient decision maker to accurately classify ADHD and BMD patients by analyzing their electroencephalogram (EEG) signals. In this study, 22 channels of EEGs have been recorded from 21 subjects with ADHD and 22 individuals with BMD. Several informative features, such as fractal dimension, band power and autoregressive coefficients, were extracted from the recorded signals. Considering the multimodal overlapping distribution of the obtained features, linear discriminant analysis (LDA) was used to reduce the input dimension in a more separable space to make it more appropriate for the proposed classifier. A piecewise linear classifier based on the extended classifier system for function approximation (XCSF) was modified by developing an adaptive mutation rate, which was proportional to the genotypic content of best individuals and their fitness in each generation. The proposed operator controlled the trade-off between exploration and exploitation while maintaining the diversity in the classifier's population to avoid premature convergence. To assess the effectiveness of the proposed scheme, the extracted features were applied to support vector machine, LDA, nearest neighbor and XCSF classifiers. To evaluate the method, a noisy environment was simulated with different noise amplitudes. It is shown that the results of the proposed technique are more robust as compared to conventional classifiers. Statistical tests demonstrate that the proposed classifier is a promising method for discriminating between ADHD and BMD patients.

  14. Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier

    OpenAIRE

    Luqman, Muhammad Muzzamil; Brouard, Thierry; Ramel, Jean-Yves

    2010-01-01

    We present a new approach for recognition of complex graphic symbols in technical documents. Graphic symbol recognition is a well known challenge in the field of document image analysis and is at heart of most graphic recognition systems. Our method uses structural approach for symbol representation and statistical classifier for symbol recognition. In our system we represent symbols by their graph based signatures: a graphic symbol is vectorized and is converted to an attributed relational g...

  15. IAEA safeguards and classified materials

    International Nuclear Information System (INIS)

    Pilat, J.F.; Eccleston, G.W.; Fearey, B.L.; Nicholas, N.J.; Tape, J.W.; Kratzer, M.

    1997-01-01

    The international community in the post-Cold War period has suggested that the International Atomic Energy Agency (IAEA) utilize its expertise in support of the arms control and disarmament process in unprecedented ways. The pledges of the US and Russian presidents to place excess defense materials, some of which are classified, under some type of international inspections raises the prospect of using IAEA safeguards approaches for monitoring classified materials. A traditional safeguards approach, based on nuclear material accountancy, would seem unavoidably to reveal classified information. However, further analysis of the IAEA's safeguards approaches is warranted in order to understand fully the scope and nature of any problems. The issues are complex and difficult, and it is expected that common technical understandings will be essential for their resolution. Accordingly, this paper examines and compares traditional safeguards item accounting of fuel at a nuclear power station (especially spent fuel) with the challenges presented by inspections of classified materials. This analysis is intended to delineate more clearly the problems as well as reveal possible approaches, techniques, and technologies that could allow the adaptation of safeguards to the unprecedented task of inspecting classified materials. It is also hoped that a discussion of these issues can advance ongoing political-technical debates on international inspections of excess classified materials

  16. Trajectory structures and transport

    International Nuclear Information System (INIS)

    Vlad, Madalina; Spineanu, Florin

    2004-01-01

    The special problem of transport in two-dimensional divergence-free stochastic velocity fields is studied by developing a statistical approach, the nested subensemble method. The nonlinear process of trapping determined by such fields generates trajectory structures whose statistical characteristics are determined. These structures strongly influence the transport

  17. Statistical mechanics of nonequilibrium liquids

    CERN Document Server

    Evans, Denis J; Craig, D P; McWeeny, R

    1990-01-01

    Statistical Mechanics of Nonequilibrium Liquids deals with theoretical rheology. The book discusses nonlinear response of systems and outlines the statistical mechanical theory. In discussing the framework of nonequilibrium statistical mechanics, the book explains the derivation of a nonequilibrium analogue of the Gibbsian basis for equilibrium statistical mechanics. The book reviews the linear irreversible thermodynamics, the Liouville equation, and the Irving-Kirkwood procedure. The text then explains the Green-Kubo relations used in linear transport coefficients, the linear response theory,

  18. On the (In)Efficiency of the Cross-Correlation Statistic for Gravitational Wave Stochastic Background Signals with Non-Gaussian Noise and Heterogeneous Detector Sensitivities

    OpenAIRE

    Lionel, Martellini; Tania, Regimbau

    2015-01-01

    Under standard assumptions including stationary and serially uncorrelated Gaussian gravitational wave stochastic background signal and noise distributions, as well as homogenous detector sensitivities, the standard cross-correlation detection statistic is known to be optimal in the sense of minimizing the probability of a false dismissal at a fixed value of the probability of a false alarm. The focus of this paper is to analyze the comparative efficiency of this statistic, versus a simple alt...

  19. Transportation satellite accounts : a look at transportation's role in the economy.

    Science.gov (United States)

    2011-01-01

    To provide a more comprehensive measure of transportation services and their contribution to the national economy, the U.S. Department of Transportations Bureau of Transportation Statistics (BTS) and the U.S. Department of Commerces Bureau of E...

  20. Statistical methods and errors in family medicine articles between 2010 and 2014-Suez Canal University, Egypt: A cross-sectional study.

    Science.gov (United States)

    Nour-Eldein, Hebatallah

    2016-01-01

    With limited statistical knowledge of most physicians it is not uncommon to find statistical errors in research articles. To determine the statistical methods and to assess the statistical errors in family medicine (FM) research articles that were published between 2010 and 2014. This was a cross-sectional study. All 66 FM research articles that were published over 5 years by FM authors with affiliation to Suez Canal University were screened by the researcher between May and August 2015. Types and frequencies of statistical methods were reviewed in all 66 FM articles. All 60 articles with identified inferential statistics were examined for statistical errors and deficiencies. A comprehensive 58-item checklist based on statistical guidelines was used to evaluate the statistical quality of FM articles. Inferential methods were recorded in 62/66 (93.9%) of FM articles. Advanced analyses were used in 29/66 (43.9%). Contingency tables 38/66 (57.6%), regression (logistic, linear) 26/66 (39.4%), and t-test 17/66 (25.8%) were the most commonly used inferential tests. Within 60 FM articles with identified inferential statistics, no prior sample size 19/60 (31.7%), application of wrong statistical tests 17/60 (28.3%), incomplete documentation of statistics 59/60 (98.3%), reporting P value without test statistics 32/60 (53.3%), no reporting confidence interval with effect size measures 12/60 (20.0%), use of mean (standard deviation) to describe ordinal/nonnormal data 8/60 (13.3%), and errors related to interpretation were mainly for conclusions without support by the study data 5/60 (8.3%). Inferential statistics were used in the majority of FM articles. Data analysis and reporting statistics are areas for improvement in FM research articles.

  1. Classifying features in CT imagery: accuracy for some single- and multiple-species classifiers

    Science.gov (United States)

    Daniel L. Schmoldt; Jing He; A. Lynn Abbott

    1998-01-01

    Our current approach to automatically label features in CT images of hardwood logs classifies each pixel of an image individually. These feature classifiers use a back-propagation artificial neural network (ANN) and feature vectors that include a small, local neighborhood of pixels and the distance of the target pixel to the center of the log. Initially, this type of...

  2. Statistical determination of significant curved I-girder bridge seismic response parameters

    Science.gov (United States)

    Seo, Junwon

    2013-06-01

    Curved steel bridges are commonly used at interchanges in transportation networks and more of these structures continue to be designed and built in the United States. Though the use of these bridges continues to increase in locations that experience high seismicity, the effects of curvature and other parameters on their seismic behaviors have been neglected in current risk assessment tools. These tools can evaluate the seismic vulnerability of a transportation network using fragility curves. One critical component of fragility curve development for curved steel bridges is the completion of sensitivity analyses that help identify influential parameters related to their seismic response. In this study, an accessible inventory of existing curved steel girder bridges located primarily in the Mid-Atlantic United States (MAUS) was used to establish statistical characteristics used as inputs for a seismic sensitivity study. Critical seismic response quantities were captured using 3D nonlinear finite element models. Influential parameters from these quantities were identified using statistical tools that incorporate experimental Plackett-Burman Design (PBD), which included Pareto optimal plots and prediction profiler techniques. The findings revealed that the potential variation in the influential parameters included number of spans, radius of curvature, maximum span length, girder spacing, and cross-frame spacing. These parameters showed varying levels of influence on the critical bridge response.

  3. StAR: a simple tool for the statistical comparison of ROC curves

    Directory of Open Access Journals (Sweden)

    Melo Francisco

    2008-06-01

    Full Text Available Abstract Background As in many different areas of science and technology, most important problems in bioinformatics rely on the proper development and assessment of binary classifiers. A generalized assessment of the performance of binary classifiers is typically carried out through the analysis of their receiver operating characteristic (ROC curves. The area under the ROC curve (AUC constitutes a popular indicator of the performance of a binary classifier. However, the assessment of the statistical significance of the difference between any two classifiers based on this measure is not a straightforward task, since not many freely available tools exist. Most existing software is either not free, difficult to use or not easy to automate when a comparative assessment of the performance of many binary classifiers is intended. This constitutes the typical scenario for the optimization of parameters when developing new classifiers and also for their performance validation through the comparison to previous art. Results In this work we describe and release new software to assess the statistical significance of the observed difference between the AUCs of any two classifiers for a common task estimated from paired data or unpaired balanced data. The software is able to perform a pairwise comparison of many classifiers in a single run, without requiring any expert or advanced knowledge to use it. The software relies on a non-parametric test for the difference of the AUCs that accounts for the correlation of the ROC curves. The results are displayed graphically and can be easily customized by the user. A human-readable report is generated and the complete data resulting from the analysis are also available for download, which can be used for further analysis with other software. The software is released as a web server that can be used in any client platform and also as a standalone application for the Linux operating system. Conclusion A new software for

  4. [Continuity of hospital identifiers in hospital discharge data - Analysis of the nationwide German DRG Statistics from 2005 to 2013].

    Science.gov (United States)

    Nimptsch, Ulrike; Wengler, Annelene; Mansky, Thomas

    2016-11-01

    In Germany, nationwide hospital discharge data (DRG statistics provided by the research data centers of the Federal Statistical Office and the Statistical Offices of the 'Länder') are increasingly used as data source for health services research. Within this data hospitals can be separated via their hospital identifier ([Institutionskennzeichen] IK). However, this hospital identifier primarily designates the invoicing unit and is not necessarily equivalent to one hospital location. Aiming to investigate direction and extent of possible bias in hospital-level analyses this study examines the continuity of the hospital identifier within a cross-sectional and longitudinal approach and compares the results to official hospital census statistics. Within the DRG statistics from 2005 to 2013 the annual number of hospitals as classified by hospital identifiers was counted for each year of observation. The annual number of hospitals derived from DRG statistics was compared to the number of hospitals in the official census statistics 'Grunddaten der Krankenhäuser'. Subsequently, the temporal continuity of hospital identifiers in the DRG statistics was analyzed within cohorts of hospitals. Until 2013, the annual number of hospital identifiers in the DRG statistics fell by 175 (from 1,725 to 1,550). This decline affected only providers with small or medium case volume. The number of hospitals identified in the DRG statistics was lower than the number given in the census statistics (e.g., in 2013 1,550 IK vs. 1,668 hospitals in the census statistics). The longitudinal analyses revealed that the majority of hospital identifiers persisted in the years of observation, while one fifth of hospital identifiers changed. In cross-sectional studies of German hospital discharge data the separation of hospitals via the hospital identifier might lead to underestimating the number of hospitals and consequential overestimation of caseload per hospital. Discontinuities of hospital

  5. Electron stopping powers for transport calculations

    International Nuclear Information System (INIS)

    Berger, M.J.

    1988-01-01

    The reliability of radiation transport calculations depends on the accuracy of the input cross sections. Therefore, it is essential to review and update the cross sections from time to time. Even though the main interest of the author's group at NBS is in transport calculations and their applications, the group spends almost as much time on the analysis and preparation of cross sections as on the development of transport codes. Stopping powers, photon attenuation coefficients, bremsstrahlung cross sections, and elastic-scattering cross sections in recent years have claimed attention. This chapter deals with electron stopping powers (with emphasis on collision stopping powers), and reviews the state of the art as reflected by Report 37 of the International Commission on Radiation Units and Measurements

  6. Hybrid diffusion–transport spatial homogenization method

    International Nuclear Information System (INIS)

    Kooreman, Gabriel; Rahnema, Farzad

    2014-01-01

    Highlights: • A new hybrid diffusion–transport homogenization method. • An extension of the consistent spatial homogenization (CSH) transport method. • Auxiliary cross section makes homogenized diffusion consistent with heterogeneous diffusion. • An on-the-fly re-homogenization in transport. • The method is faster than fine-mesh transport by 6–8 times. - Abstract: A new hybrid diffusion–transport homogenization method has been developed by extending the consistent spatial homogenization (CSH) transport method to include diffusion theory. As in the CSH method, an “auxiliary cross section” term is introduced into the source term, making the resulting homogenized diffusion equation consistent with its heterogeneous counterpart. The method then utilizes an on-the-fly re-homogenization in transport theory at the assembly level in order to correct for core environment effects on the homogenized cross sections and the auxiliary cross section. The method has been derived in general geometry and tested in a 1-D boiling water reactor (BWR) core benchmark problem for both controlled and uncontrolled configurations. The method has been shown to converge to the reference solution with less than 1.7% average flux error in less than one third the computational time as the CSH method – 6 to 8 times faster than fine-mesh transport

  7. Genetic evidence and integration of various data sources for classifying uncertain variants into a single model.

    NARCIS (Netherlands)

    Goldgar, D.E.; Easton, D.F.; Byrnes, G.B.; Spurdle, A.B.; Iversen, E.S.; Greenblatt, M.S.; Boffetta, P.; Couch, F.J.; Wind, N. de; Eccles, D.; Foulkes, W.D.; Genuardi, M.; Hofstra, R.M.; Hogervorst, F.; Hoogerbrugge-van der Linden, N.; Plon, S.E.; Radice, P.; Rasmussen, L.; Sinilnikova, O.M.; Tavtigian, S.V.

    2008-01-01

    Genetic testing often results in the finding of a variant whose clinical significance is unknown. A number of different approaches have been employed in the attempt to classify such variants. For some variants, case-control, segregation, family history, or other statistical studies can provide

  8. New neural network classifier of fall-risk based on the Mahalanobis distance and kinematic parameters assessed by a wearable device

    International Nuclear Information System (INIS)

    Giansanti, Daniele; Macellari, Velio; Maccioni, Giovanni

    2008-01-01

    Fall prevention lacks easy, quantitative and wearable methods for the classification of fall-risk (FR). Efforts must be thus devoted to the choice of an ad hoc classifier both to reduce the size of the sample used to train the classifier and to improve performances. A new methodology that uses a neural network (NN) and a wearable device are hereby proposed for this purpose. The NN uses kinematic parameters assessed by a wearable device with accelerometers and rate gyroscopes during a posturography protocol. The training of the NN was based on the Mahalanobis distance and was carried out on two groups of 30 elderly subjects with varying fall-risk Tinetti scores. The validation was done on two groups of 100 subjects with different fall-risk Tinetti scores and showed that, both in terms of specificity and sensitivity, the NN performed better than other classifiers (naive Bayes, Bayes net, multilayer perceptron, support vector machines, statistical classifiers). In particular, (i) the proposed NN methodology improved the specificity and sensitivity by a mean of 3% when compared to the statistical classifier based on the Mahalanobis distance (SCMD) described in Giansanti (2006 Physiol. Meas. 27 1081–90); (ii) the assessed specificity was 97%, the assessed sensitivity was 98% and the area under receiver operator characteristics was 0.965. (note)

  9. Statistics Canada's Definition and Classification of Postsecondary and Adult Education Providers in Canada. Culture, Tourism and the Centre for Education Statistics. Research Paper. Catalogue no. 81-595-M No. 071

    Science.gov (United States)

    Orton, Larry

    2009-01-01

    This document outlines the definitions and the typology now used by Statistics Canada's Centre for Education Statistics to identify, classify and delineate the universities, colleges and other providers of postsecondary and adult education in Canada for which basic enrollments, graduates, professors and finance statistics are produced. These new…

  10. Conservation of targeting but divergence in function and quality control of peroxisomal ABC transporters: an analysis using cross-kingdom expression

    NARCIS (Netherlands)

    Zhang, Xuebin; de Marcos Lousa, Carine; Schutte-Lensink, Nellie; Ofman, Rob; Wanders, Ronald J.; Baldwin, Stephen A.; Baker, Alison; Kemp, Stephan; Theodoulou, Frederica L.

    2011-01-01

    ABC (ATP-binding cassette) subfamily D transporters are found in all eukaryotic kingdoms and are known to play essential roles in mammals and plants; however, their number, organization and physiological contexts differ. Via cross-kingdom expression experiments, we have explored the conservation of

  11. LCC: Light Curves Classifier

    Science.gov (United States)

    Vo, Martin

    2017-08-01

    Light Curves Classifier uses data mining and machine learning to obtain and classify desired objects. This task can be accomplished by attributes of light curves or any time series, including shapes, histograms, or variograms, or by other available information about the inspected objects, such as color indices, temperatures, and abundances. After specifying features which describe the objects to be searched, the software trains on a given training sample, and can then be used for unsupervised clustering for visualizing the natural separation of the sample. The package can be also used for automatic tuning parameters of used methods (for example, number of hidden neurons or binning ratio). Trained classifiers can be used for filtering outputs from astronomical databases or data stored locally. The Light Curve Classifier can also be used for simple downloading of light curves and all available information of queried stars. It natively can connect to OgleII, OgleIII, ASAS, CoRoT, Kepler, Catalina and MACHO, and new connectors or descriptors can be implemented. In addition to direct usage of the package and command line UI, the program can be used through a web interface. Users can create jobs for ”training” methods on given objects, querying databases and filtering outputs by trained filters. Preimplemented descriptors, classifier and connectors can be picked by simple clicks and their parameters can be tuned by giving ranges of these values. All combinations are then calculated and the best one is used for creating the filter. Natural separation of the data can be visualized by unsupervised clustering.

  12. 49 CFR 1248.1 - Freight commodity statistics.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 9 2010-10-01 2010-10-01 false Freight commodity statistics. 1248.1 Section 1248... STATISTICS § 1248.1 Freight commodity statistics. All class I railroads, as described in § 1240.1 of this... statistics on the basis of the commodity codes named in § 1248.101. Carriers shall report quarterly on the...

  13. 15 CFR 4.8 - Classified Information.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Classified Information. 4.8 Section 4... INFORMATION Freedom of Information Act § 4.8 Classified Information. In processing a request for information..., the information shall be reviewed to determine whether it should remain classified. Ordinarily the...

  14. Statistical properties of transport in plasma turbulence

    DEFF Research Database (Denmark)

    Naulin, V.; Garcia, O.E.; Nielsen, A.H.

    2004-01-01

    The statistical properties of the particle flux in different types of plasma turbulence models are numerically investigated using probability distribution functions (PDFs). The physics included in the models range from two-dimensional drift wave turbulence to three-dimensional MHD dynamics...

  15. Transport phenomena

    International Nuclear Information System (INIS)

    Kirczenow, G.; Marro, J.

    1974-01-01

    Some simple remarks on the basis of transport theory. - Entropy, dynamics and scattering theory. - Response, relaxation and fluctuation. - Fluctuating hydrodynamics and renormalization of susceptibilities and transport coefficients. - Irreversibility of the transport equations. - Ergodic theory and statistical mechanics. - Correlation functions in Heisenberg magnets. - On the Enskog hard-sphere kinetic eqquation and the transport phenomena of dense simple gases. - What can one learn from Lorentz models. - Conductivity in a magnetic field. - Transport properties in gases in presence of external fields. - Transport properties of dilute gases with internal structure. (orig.) [de

  16. Fingerprint prediction using classifier ensembles

    CSIR Research Space (South Africa)

    Molale, P

    2011-11-01

    Full Text Available ); logistic discrimination (LgD), k-nearest neighbour (k-NN), artificial neural network (ANN), association rules (AR) decision tree (DT), naive Bayes classifier (NBC) and the support vector machine (SVM). The performance of several multiple classifier systems...

  17. 14 CFR Section 19 - Uniform Classification of Operating Statistics

    Science.gov (United States)

    2010-01-01

    ... Statistics Section 19 Section 19 Aeronautics and Space OFFICE OF THE SECRETARY, DEPARTMENT OF TRANSPORTATION... AIR CARRIERS Operating Statistics Classifications Section 19 Uniform Classification of Operating Statistics ...

  18. Cross-Lingual Lexical Triggers in Statistical Language Modeling

    National Research Council Canada - National Science Library

    Kim, Woosung; Khudanpur, Sanjeev

    2003-01-01

    .... We achieve this through an extension of the method of lexical triggers to the cross-language problem, and by developing a likelihoodbased adaptation scheme for combining a trigger model with an N-gram model...

  19. Criticality benchmark guide for light-water-reactor fuel in transportation and storage packages

    International Nuclear Information System (INIS)

    Lichtenwalter, J.J.; Bowman, S.M.; DeHart, M.D.; Hopper, C.M.

    1997-03-01

    This report is designed as a guide for performing criticality benchmark calculations for light-water-reactor (LWR) fuel applications. The guide provides documentation of 180 criticality experiments with geometries, materials, and neutron interaction characteristics representative of transportation packages containing LWR fuel or uranium oxide pellets or powder. These experiments should benefit the U.S. Nuclear Regulatory Commission (NRC) staff and licensees in validation of computational methods used in LWR fuel storage and transportation concerns. The experiments are classified by key parameters such as enrichment, water/fuel volume, hydrogen-to-fissile ratio (H/X), and lattice pitch. Groups of experiments with common features such as separator plates, shielding walls, and soluble boron are also identified. In addition, a sample validation using these experiments and a statistical analysis of the results are provided. Recommendations for selecting suitable experiments and determination of calculational bias and uncertainty are presented as part of this benchmark guide

  20. 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

  1. Improving the Crossing-SIBTEST Statistic for Detecting Non-uniform DIF.

    Science.gov (United States)

    Chalmers, R Philip

    2018-06-01

    This paper demonstrates that, after applying a simple modification to Li and Stout's (Psychometrika 61(4):647-677, 1996) CSIBTEST statistic, an improved variant of the statistic could be realized. It is shown that this modified version of CSIBTEST has a more direct association with the SIBTEST statistic presented by Shealy and Stout (Psychometrika 58(2):159-194, 1993). In particular, the asymptotic sampling distributions and general interpretation of the effect size estimates are the same for SIBTEST and the new CSIBTEST. Given the more natural connection to SIBTEST, it is shown that Li and Stout's hypothesis testing approach is insufficient for CSIBTEST; thus, an improved hypothesis testing procedure is required. Based on the presented arguments, a new chi-squared-based hypothesis testing approach is proposed for the modified CSIBTEST statistic. Positive results from a modest Monte Carlo simulation study strongly suggest the original CSIBTEST procedure and randomization hypothesis testing approach should be replaced by the modified statistic and hypothesis testing method.

  2. Nonequilibrium statistical physics of small systems: fluctuation relations and beyond (annual reviews of nonlinear dynamics and complexity (vch))

    CERN Document Server

    2013-01-01

    This book offers a comprehensive picture of nonequilibrium phenomena in nanoscale systems. Written by internationally recognized experts in the field, this book strikes a balance between theory and experiment, and includes in-depth introductions to nonequilibrium fluctuation relations, nonlinear dynamics and transport, single molecule experiments, and molecular diffusion in nanopores. The authors explore the application of these concepts to nano- and biosystems by cross-linking key methods and ideas from nonequilibrium statistical physics, thermodynamics, stochastic theory, and dynamical s

  3. Cross-separatrix Coupling in Nonlinear Global Electrostatic Turbulent Transport in C-2U

    Science.gov (United States)

    Lau, Calvin; Fulton, Daniel; Bao, Jian; Lin, Zhihong; Binderbauer, Michl; Tajima, Toshiki; Schmitz, Lothar; TAE Team

    2017-10-01

    In recent years, the progress of the C-2/C-2U advanced beam-driven field-reversed configuration (FRC) experiments at Tri Alpha Energy, Inc. has pushed FRCs to transport limited regimes. Understanding particle and energy transport is a vital step towards an FRC reactor, and two particle-in-cell microturbulence codes, the Gyrokinetic Toroidal Code (GTC) and A New Code (ANC), are being developed and applied toward this goal. Previous local electrostatic GTC simulations find the core to be robustly stable with drift-wave instability only in the scrape-off layer (SOL) region. However, experimental measurements showed fluctuations in both regions; one possibility is that fluctuations in the core originate from the SOL, suggesting the need for non-local simulations with cross-separatrix coupling. Current global ANC simulations with gyrokinetic ions and adiabatic electrons find that non-local effects (1) modify linear growth-rates and frequencies of instabilities and (2) allow instability to move from the unstable SOL to the linearly stable core. Nonlinear spreading is also seen prior to mode saturation. We also report on the progress of the first turbulence simulations in the SOL. This work is supported by the Norman Rostoker Fellowship.

  4. Elementary statistical physics

    CERN Document Server

    Kittel, C

    1965-01-01

    This book is intended to help physics students attain a modest working knowledge of several areas of statistical mechanics, including stochastic processes and transport theory. The areas discussed are among those forming a useful part of the intellectual background of a physicist.

  5. Assessment of fractures classified as non-mineralised in the Sicada database

    Energy Technology Data Exchange (ETDEWEB)

    Claesson Liljedahl, Lillemor; Munier, Raymond (Swedish Nuclear Fuel and Waste Management Co., Stockholm (Sweden)); Sandstroem, Bjoern (WSP Sverige AB, Goeteborg (Sweden)); Drake, Henrik (Isochron GeoConsulting, Varberg (Sweden)); Tullborg, Eva-Lena (Terralogica AB, Graabo (Sweden))

    2011-03-15

    The general objective of this report was to describe the results of the investigation of fractures classified as non-mineralised in Sicada. Such fractures exist at Forsmark and at Laxemar. The main aims of the investigation of these fractures were to: - Quantify the number of non-mineralised fractures (i.e. fractures lacking mineral coating) in Sicada (table: p{_}fract{_}core{_}eshi). - Closely examine a selection of fractures recorded as non-mineralised in Sicada. - Outline possible reasons for the existence of non-mineralised fractures. The work has involved extraction of fracture data from Sicada and subsequent statistical analysis. Since several thousand fractures are classified as non-mineralised in Sicada, it was not a practical possibility to include all these in this study, we examined one fracture sub-set from each site. We investigated a sample of 204 of these fractures in detail (see Sections 1.1 and 2.4). Rock mechanical differences between Forsmark and Laxemar and kinematic analysis of fracture surfaces is not discussed in this report

  6. Pharmacokinetic Tumor Heterogeneity as a Prognostic Biomarker for Classifying Breast Cancer Recurrence Risk.

    Science.gov (United States)

    Mahrooghy, Majid; Ashraf, Ahmed B; Daye, Dania; McDonald, Elizabeth S; Rosen, Mark; Mies, Carolyn; Feldman, Michael; Kontos, Despina

    2015-06-01

    Heterogeneity in cancer can affect response to therapy and patient prognosis. Histologic measures have classically been used to measure heterogeneity, although a reliable noninvasive measurement is needed both to establish baseline risk of recurrence and monitor response to treatment. Here, we propose using spatiotemporal wavelet kinetic features from dynamic contrast-enhanced magnetic resonance imaging to quantify intratumor heterogeneity in breast cancer. Tumor pixels are first partitioned into homogeneous subregions using pharmacokinetic measures. Heterogeneity wavelet kinetic (HetWave) features are then extracted from these partitions to obtain spatiotemporal patterns of the wavelet coefficients and the contrast agent uptake. The HetWave features are evaluated in terms of their prognostic value using a logistic regression classifier with genetic algorithm wrapper-based feature selection to classify breast cancer recurrence risk as determined by a validated gene expression assay. Receiver operating characteristic analysis and area under the curve (AUC) are computed to assess classifier performance using leave-one-out cross validation. The HetWave features outperform other commonly used features (AUC = 0.88 HetWave versus 0.70 standard features). The combination of HetWave and standard features further increases classifier performance (AUCs 0.94). The rate of the spatial frequency pattern over the pharmacokinetic partitions can provide valuable prognostic information. HetWave could be a powerful feature extraction approach for characterizing tumor heterogeneity, providing valuable prognostic information.

  7. The statistical power to detect cross-scale interactions at macroscales

    Science.gov (United States)

    Wagner, Tyler; Fergus, C. Emi; Stow, Craig A.; Cheruvelil, Kendra S.; Soranno, Patricia A.

    2016-01-01

    Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

  8. Identification and optimization of classifier genes from multi-class earthworm microarray dataset.

    Directory of Open Access Journals (Sweden)

    Ying Li

    Full Text Available Monitoring, assessment and prediction of environmental risks that chemicals pose demand rapid and accurate diagnostic assays. A variety of toxicological effects have been associated with explosive compounds TNT and RDX. One important goal of microarray experiments is to discover novel biomarkers for toxicity evaluation. We have developed an earthworm microarray containing 15,208 unique oligo probes and have used it to profile gene expression in 248 earthworms exposed to TNT, RDX or neither. We assembled a new machine learning pipeline consisting of several well-established feature filtering/selection and classification techniques to analyze the 248-array dataset in order to construct classifier models that can separate earthworm samples into three groups: control, TNT-treated, and RDX-treated. First, a total of 869 genes differentially expressed in response to TNT or RDX exposure were identified using a univariate statistical algorithm of class comparison. Then, decision tree-based algorithms were applied to select a subset of 354 classifier genes, which were ranked by their overall weight of significance. A multiclass support vector machine (MC-SVM method and an unsupervised K-mean clustering method were applied to independently refine the classifier, producing a smaller subset of 39 and 30 classifier genes, separately, with 11 common genes being potential biomarkers. The combined 58 genes were considered the refined subset and used to build MC-SVM and clustering models with classification accuracy of 83.5% and 56.9%, respectively. This study demonstrates that the machine learning approach can be used to identify and optimize a small subset of classifier/biomarker genes from high dimensional datasets and generate classification models of acceptable precision for multiple classes.

  9. 49 CFR 369.11 - Quarterly reports of passenger revenues, expenses, and statistics.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 5 2010-10-01 2010-10-01 false Quarterly reports of passenger revenues, expenses, and statistics. 369.11 Section 369.11 Transportation Other Regulations Relating to Transportation..., and statistics. Commencing with reports for the quarter ended March 31, 1968, and for subsequent...

  10. Fault Diagnosis for Distribution Networks Using Enhanced Support Vector Machine Classifier with Classical Multidimensional Scaling

    Directory of Open Access Journals (Sweden)

    Ming-Yuan Cho

    2017-09-01

    Full Text Available In this paper, a new fault diagnosis techniques based on time domain reflectometry (TDR method with pseudo-random binary sequence (PRBS stimulus and support vector machine (SVM classifier has been investigated to recognize the different types of fault in the radial distribution feeders. This novel technique has considered the amplitude of reflected signals and the peaks of cross-correlation (CCR between the reflected and incident wave for generating fault current dataset for SVM. Furthermore, this multi-layer enhanced SVM classifier is combined with classical multidimensional scaling (CMDS feature extraction algorithm and kernel parameter optimization to increase training speed and improve overall classification accuracy. The proposed technique has been tested on a radial distribution feeder to identify ten different types of fault considering 12 input features generated by using Simulink software and MATLAB Toolbox. The success rate of SVM classifier is over 95% which demonstrates the effectiveness and the high accuracy of proposed method.

  11. Heterogeneity wavelet kinetics from DCE-MRI for classifying gene expression based breast cancer recurrence risk.

    Science.gov (United States)

    Mahrooghy, Majid; Ashraf, Ahmed B; Daye, Dania; Mies, Carolyn; Feldman, Michael; Rosen, Mark; Kontos, Despina

    2013-01-01

    Breast tumors are heterogeneous lesions. Intra-tumor heterogeneity presents a major challenge for cancer diagnosis and treatment. Few studies have worked on capturing tumor heterogeneity from imaging. Most studies to date consider aggregate measures for tumor characterization. In this work we capture tumor heterogeneity by partitioning tumor pixels into subregions and extracting heterogeneity wavelet kinetic (HetWave) features from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to obtain the spatiotemporal patterns of the wavelet coefficients and contrast agent uptake from each partition. Using a genetic algorithm for feature selection, and a logistic regression classifier with leave one-out cross validation, we tested our proposed HetWave features for the task of classifying breast cancer recurrence risk. The classifier based on our features gave an ROC AUC of 0.78, outperforming previously proposed kinetic, texture, and spatial enhancement variance features which give AUCs of 0.69, 0.64, and 0.65, respectively.

  12. The Tsallis Statistics applied to the calculation of absorption cross section of {sup 238}U, {sup 232}Th and {sup 240}Pu isotopes

    Energy Technology Data Exchange (ETDEWEB)

    Guedes, Guilherme, E-mail: gguedes.cefet@gmail.com [Centro Federal de Educacao Tecnologica Celso Suckow da Fonseca (CEFET-RJ), Nova Friburgo, RJ (Brazil); Gonçalves, Alessandro C., E-mail: alessandrocgnuclear@gmail.com [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil); Palma, Daniel A.P., E-mail: dapalma@cnen.gov.br [Comissão Nacional de Energia Nuclear (CNEN), Rio de Janeiro, RJ (Brazil)

    2017-07-01

    The thermal agitation movement in the reactor core is adequately represented by the microscopic cross section of the neutron-nucleus interaction through the Doppler broadening function. In the last decades several researches had been done on fundamentals and applications of generalized statistical theories based on quasi-Maxwellian distribution of probabilities. In this paper the effect of taking into account the non extensive Tsallis statistics in the evaluation of the absorption cross section in 3-dimension is discussed. In this context, it is obtained an integral form for a generalized Doppler broadening function in the scope of the single-level formalism given by the Bethe-Placzek approximations. This new function reproduces the well-established conventional Doppler broadening function on the limit when q removes the deformation. Numerical tests were carried out and by varying the q parameter it was possible to study the range of values where the effect is appreciable. (author)

  13. 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

  14. 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

  15. Application of Snowfall and Wind Statistics to Snow Transport Modeling for Snowdrift Control in Minnesota.

    Science.gov (United States)

    Shulski, Martha D.; Seeley, Mark W.

    2004-11-01

    Models were utilized to determine the snow accumulation season (SAS) and to quantify windblown snow for the purpose of snowdrift control for locations in Minnesota. The models require mean monthly temperature, snowfall, density of snow, and wind frequency distribution statistics. Temperature and precipitation data were obtained from local cooperative observing sites, and wind data came from Automated Surface Observing System (ASOS)/Automated Weather Observing System (AWOS) sites in the region. The temperature-based algorithm used to define the SAS reveals a geographic variability in the starting and ending dates of the season, which is determined by latitude and elevation. Mean seasonal snowfall shows a geographic distribution that is affected by topography and proximity to Lake Superior. Mean snowfall density also exhibits variability, with lower-density snow events displaced to higher-latitude positions. Seasonal wind frequencies show a strong bimodal distribution with peaks from the northwest and southeast vector direction, with an exception for locations in close proximity to the Lake Superior shoreline. In addition, for western and south-central Minnesota there is a considerably higher frequency of wind speeds above the mean snow transport threshold of 7 m s-1. As such, this area is more conducive to higher potential snow transport totals. Snow relocation coefficients in this area are in the range of 0.4 0.9, and, according to the empirical models used in this analysis, this range implies that actual snow transport is 40% 90% of the total potential in south-central and western areas of the state.

  16. Classifying Sluice Occurrences in Dialogue

    DEFF Research Database (Denmark)

    Baird, Austin; Hamza, Anissa; Hardt, Daniel

    2018-01-01

    perform manual annotation with acceptable inter-coder agreement. We build classifier models with Decision Trees and Naive Bayes, with accuracy of 67%. We deploy a classifier to automatically classify sluice occurrences in OpenSubtitles, resulting in a corpus with 1.7 million occurrences. This will support....... Despite this, the corpus can be of great use in research on sluicing and development of systems, and we are making the corpus freely available on request. Furthermore, we are in the process of improving the accuracy of sluice identification and annotation for the purpose of created a subsequent version...

  17. Statistical thermodynamics of nonequilibrium processes

    CERN Document Server

    Keizer, Joel

    1987-01-01

    The structure of the theory ofthermodynamics has changed enormously since its inception in the middle of the nineteenth century. Shortly after Thomson and Clausius enunciated their versions of the Second Law, Clausius, Maxwell, and Boltzmann began actively pursuing the molecular basis of thermo­ dynamics, work that culminated in the Boltzmann equation and the theory of transport processes in dilute gases. Much later, Onsager undertook the elucidation of the symmetry oftransport coefficients and, thereby, established himself as the father of the theory of nonequilibrium thermodynamics. Com­ bining the statistical ideas of Gibbs and Langevin with the phenomenological transport equations, Onsager and others went on to develop a consistent statistical theory of irreversible processes. The power of that theory is in its ability to relate measurable quantities, such as transport coefficients and thermodynamic derivatives, to the results of experimental measurements. As powerful as that theory is, it is linear and...

  18. Transportation Energy Data Book, Edition 19

    Energy Technology Data Exchange (ETDEWEB)

    Davis, S.C.

    1999-09-01

    The Transportation Energy Data Book: Edition 19 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the Office of Transportation Technologies in the Department of Energy (DOE). Designed for use as a desk-top reference, the data book represents an assembly and display of statistics and information that characterize transportation activity, and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. The latest editions of the Data Book are available to a larger audience via the Internet (http://www-cta.ornl.gov/data/tedb.htm).

  19. Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology

    Directory of Open Access Journals (Sweden)

    Ashley I. Heinson

    2017-02-01

    Full Text Available Reverse vaccinology (RV is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of the BEXSERO® vaccine against Neisseria meningitidis serogroup B. RV studies have begun to incorporate machine learning (ML techniques to distinguish bacterial protective antigens (BPAs from non-BPAs. This research contributes significantly to the RV field by using permutation analysis to demonstrate that a signal for protective antigens can be curated from published data. Furthermore, the effects of the following on an ML approach to RV were also assessed: nested cross-validation, balancing selection of non-BPAs for subcellular localization, increasing the training data, and incorporating greater numbers of protein annotation tools for feature generation. These enhancements yielded a support vector machine (SVM classifier that could discriminate BPAs (n = 200 from non-BPAs (n = 200 with an area under the curve (AUC of 0.787. In addition, hierarchical clustering of BPAs revealed that intracellular BPAs clustered separately from extracellular BPAs. However, no immediate benefit was derived when training SVM classifiers on data sets exclusively containing intra- or extracellular BPAs. In conclusion, this work demonstrates that ML classifiers have great utility in RV approaches and will lead to new subunit vaccines in the future.

  20. Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology

    KAUST Repository

    Heinson, Ashley

    2017-02-01

    Reverse vaccinology (RV) is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of the BEXSERO® vaccine against Neisseria meningitidis serogroup B. RV studies have begun to incorporate machine learning (ML) techniques to distinguish bacterial protective antigens (BPAs) from non-BPAs. This research contributes significantly to the RV field by using permutation analysis to demonstrate that a signal for protective antigens can be curated from published data. Furthermore, the effects of the following on an ML approach to RV were also assessed: nested cross-validation, balancing selection of non-BPAs for subcellular localization, increasing the training data, and incorporating greater numbers of protein annotation tools for feature generation. These enhancements yielded a support vector machine (SVM) classifier that could discriminate BPAs (n = 200) from non-BPAs (n = 200) with an area under the curve (AUC) of 0.787. In addition, hierarchical clustering of BPAs revealed that intracellular BPAs clustered separately from extracellular BPAs. However, no immediate benefit was derived when training SVM classifiers on data sets exclusively containing intra- or extracellular BPAs. In conclusion, this work demonstrates that ML classifiers have great utility in RV approaches and will lead to new subunit vaccines in the future.

  1. Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology

    KAUST Repository

    Heinson, Ashley; Gunawardana, Yawwani; Moesker, Bastiaan; Hume, Carmen; Vataga, Elena; Hall, Yper; Stylianou, Elena; McShane, Helen; Williams, Ann; Niranjan, Mahesan; Woelk, Christopher

    2017-01-01

    Reverse vaccinology (RV) is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of the BEXSERO® vaccine against Neisseria meningitidis serogroup B. RV studies have begun to incorporate machine learning (ML) techniques to distinguish bacterial protective antigens (BPAs) from non-BPAs. This research contributes significantly to the RV field by using permutation analysis to demonstrate that a signal for protective antigens can be curated from published data. Furthermore, the effects of the following on an ML approach to RV were also assessed: nested cross-validation, balancing selection of non-BPAs for subcellular localization, increasing the training data, and incorporating greater numbers of protein annotation tools for feature generation. These enhancements yielded a support vector machine (SVM) classifier that could discriminate BPAs (n = 200) from non-BPAs (n = 200) with an area under the curve (AUC) of 0.787. In addition, hierarchical clustering of BPAs revealed that intracellular BPAs clustered separately from extracellular BPAs. However, no immediate benefit was derived when training SVM classifiers on data sets exclusively containing intra- or extracellular BPAs. In conclusion, this work demonstrates that ML classifiers have great utility in RV approaches and will lead to new subunit vaccines in the future.

  2. Fluid transport with time on peritoneal dialysis: the contribution of free water transport and solute coupled water transport

    NARCIS (Netherlands)

    Coester, Annemieke M.; Smit, Watske; Struijk, Dirk G.; Krediet, Raymond T.

    2009-01-01

    Ultrafiltration in peritoneal dialysis occurs through endothelial water channels (free water transport) and together with solutes across small pores: solute coupled water transport. A review is given of cross-sectional studies and on the results of longitudinal follow-up

  3. Matrix association effects on hydrodynamic sorting and degradation of terrestrial organic matter during cross-shelf transport in the Laptev and East Siberian shelf seas

    Science.gov (United States)

    Tesi, Tommaso; Semiletov, Igor; Dudarev, Oleg; Andersson, August; Gustafsson, Örjan

    2016-03-01

    This study seeks an improved understanding of how matrix association affects the redistribution and degradation of terrigenous organic carbon (TerrOC) during cross-shelf transport in the Siberian margin. Sediments were collected at increasing distance from two river outlets (Lena and Kolyma Rivers) and one coastal region affected by erosion. Samples were fractionated according to density, size, and settling velocity. The chemical composition in each fraction was characterized using elemental analyses and terrigenous biomarkers. In addition, a dual-carbon-isotope mixing model (δ13C and Δ14C) was used to quantify the relative TerrOC contributions from active layer (Topsoil) and Pleistocene Ice Complex Deposits (ICD). Results indicate that physical properties of particles exert first-order control on the redistribution of different TerrOC pools. Because of its coarse nature, plant debris is hydraulically retained in the coastal region. With increasing distance from the coast, the OC is mainly associated with fine/ultrafine mineral particles. Furthermore, biomarkers indicate that the selective transport of fine-grained sediment results in mobilizing high-molecular weight (HMW) lipid-rich, diagenetically altered TerrOC while lignin-rich, less degraded TerrOC is retained near the coast. The loading (µg/m2) of lignin and HMW wax lipids on the fine/ultrafine fraction drastically decreases with increasing distance from the coast (98% and 90%, respectively), which indicates extensive degradation during cross-shelf transport. Topsoil-C degrades more readily (90 ± 3.5%) compared to the ICD-C (60 ± 11%) during transport. Altogether, our results indicate that TerrOC is highly reactive and its accelerated remobilization from thawing permafrost followed by cross-shelf transport will likely represent a positive feedback to climate warming.

  4. The importance of parameter variances, correlations lengths, and cross-correlations in reactive transport models: key considerations for assessing the need for microscale information

    Energy Technology Data Exchange (ETDEWEB)

    Reimus, Paul W [Los Alamos National Laboratory

    2010-12-08

    A process-oriented modeling approach is implemented to examine the importance of parameter variances, correlation lengths, and especially cross-correlations in contaminant transport predictions over large scales. It is shown that the most important consideration is the correlation between flow rates and retardation processes (e.g., sorption, matrix diffusion) in the system. lf flow rates are negatively correlated with retardation factors in systems containing multiple flow pathways, then characterizing these negative correlation(s) may have more impact on reactive transport modeling than microscale information. Such negative correlations are expected in porous-media systems where permeability is negatively correlated with clay content and rock alteration (which are usually associated with increased sorption). Likewise, negative correlations are expected in fractured rocks where permeability is positively correlated with fracture apertures, which in turn are negatively correlated with sorption and matrix diffusion. Parameter variances and correlation lengths are also shown to have important effects on reactive transport predictions, but they are less important than parameter cross-correlations. Microscale information pertaining to contaminant transport has become more readily available as characterization methods and spectroscopic instrumentation have achieved lower detection limits, greater resolution, and better precision. Obtaining detailed mechanistic insights into contaminant-rock-water interactions is becoming a routine practice in characterizing reactive transport processes in groundwater systems (almost necessary for high-profile publications). Unfortunately, a quantitative link between microscale information and flow and transport parameter distributions or cross-correlations has not yet been established. One reason for this is that quantitative microscale information is difficult to obtain in complex, heterogeneous systems. So simple systems that lack the

  5. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha

    2013-11-25

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  6. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2013-01-01

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  7. Statistical approach to modeling transport of pollutants in groundwater

    International Nuclear Information System (INIS)

    Ross, B.; Koplik, C.M.; Crawford, B.S.

    1978-01-01

    The transport of pollutants in the subsurface can be affected by random geologic events. Prediction of such transport therefore requires solution of a partial differential equation whose coefficients are random processes. A method of finding the expected (mean) values of solutions of such equations is derived. This method is used to assess the impact of fault movement and formation of breccia pipes on risk from radioactive waste disposal. Preliminary results indicate that these events, considered probabilistically, do not make a large contribution to risk

  8. Statistical theory of multi-step compound and direct reactions

    International Nuclear Information System (INIS)

    Feshbach, H.; Kerman, A.; Koonin, S.

    1980-01-01

    The theory of nuclear reactions is extended so as to include a statistical treatment of multi-step processes. Two types are distinguished, the multi-step compound and the multi-step direct. The wave functions for the system are grouped according to their complexity. The multi-step direct process involves explicitly those states which are open, while the multi-step compound involves those which are bound. In addition to the random phase assumption which is applied differently to the multi-step direct and to the multi-step compound cross-sections, it is assumed that the residual interaction will have non-vanishing matrix elements between states whose complexities differ by at most one unit. This is referred to as the chaining hypothesis. Explicit expressions for the double differential cross-section giving the angular distribution and energy spectrum are obtained for both reaction types. The statistical multi-step compound cross-sections are symmetric about 90 0 . The classical statistical theory of nuclear reactions is a special limiting case. The cross-section for the statistical multi-step direct reaction consists of a set of convolutions of single-step direct cross-sections. For the many step case it is possible to derive a diffusion equation in momentum space. Application is made to the reaction 181 Ta(p,n) 181 W using the statistical multi-step compound formalism

  9. Machine learning classifier using abnormal brain network topological metrics in major depressive disorder.

    Science.gov (United States)

    Guo, Hao; Cao, Xiaohua; Liu, Zhifen; Li, Haifang; Chen, Junjie; Zhang, Kerang

    2012-12-05

    Resting state functional brain networks have been widely studied in brain disease research. However, it is currently unclear whether abnormal resting state functional brain network metrics can be used with machine learning for the classification of brain diseases. Resting state functional brain networks were constructed for 28 healthy controls and 38 major depressive disorder patients by thresholding partial correlation matrices of 90 regions. Three nodal metrics were calculated using graph theory-based approaches. Nonparametric permutation tests were then used for group comparisons of topological metrics, which were used as classified features in six different algorithms. We used statistical significance as the threshold for selecting features and measured the accuracies of six classifiers with different number of features. A sensitivity analysis method was used to evaluate the importance of different features. The result indicated that some of the regions exhibited significantly abnormal nodal centralities, including the limbic system, basal ganglia, medial temporal, and prefrontal regions. Support vector machine with radial basis kernel function algorithm and neural network algorithm exhibited the highest average accuracy (79.27 and 78.22%, respectively) with 28 features (Pdisorder is associated with abnormal functional brain network topological metrics and statistically significant nodal metrics can be successfully used for feature selection in classification algorithms.

  10. Solid waste bin detection and classification using Dynamic Time Warping and MLP classifier

    Energy Technology Data Exchange (ETDEWEB)

    Islam, Md. Shafiqul, E-mail: shafique@eng.ukm.my [Dept. of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Selangore (Malaysia); Hannan, M.A., E-mail: hannan@eng.ukm.my [Dept. of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Selangore (Malaysia); Basri, Hassan [Dept. of Civil and Structural Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Selangore (Malaysia); Hussain, Aini; Arebey, Maher [Dept. of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Selangore (Malaysia)

    2014-02-15

    Highlights: • Solid waste bin level detection using Dynamic Time Warping (DTW). • Gabor wavelet filter is used to extract the solid waste image features. • Multi-Layer Perceptron classifier network is used for bin image classification. • The classification performance evaluated by ROC curve analysis. - Abstract: The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensor intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.

  11. Ensemble Classifiers for Predicting HIV-1 Resistance from Three Rule-Based Genotypic Resistance Interpretation Systems.

    Science.gov (United States)

    Raposo, Letícia M; Nobre, Flavio F

    2017-08-30

    Resistance to antiretrovirals (ARVs) is a major problem faced by HIV-infected individuals. Different rule-based algorithms were developed to infer HIV-1 susceptibility to antiretrovirals from genotypic data. However, there is discordance between them, resulting in difficulties for clinical decisions about which treatment to use. Here, we developed ensemble classifiers integrating three interpretation algorithms: Agence Nationale de Recherche sur le SIDA (ANRS), Rega, and the genotypic resistance interpretation system from Stanford HIV Drug Resistance Database (HIVdb). Three approaches were applied to develop a classifier with a single resistance profile: stacked generalization, a simple plurality vote scheme and the selection of the interpretation system with the best performance. The strategies were compared with the Friedman's test and the performance of the classifiers was evaluated using the F-measure, sensitivity and specificity values. We found that the three strategies had similar performances for the selected antiretrovirals. For some cases, the stacking technique with naïve Bayes as the learning algorithm showed a statistically superior F-measure. This study demonstrates that ensemble classifiers can be an alternative tool for clinical decision-making since they provide a single resistance profile from the most commonly used resistance interpretation systems.

  12. Using cross-classified multilevel models to disentangle school and neighborhood effects: an example focusing on smoking behaviors among adolescents in the United States.

    Science.gov (United States)

    Dunn, Erin C; Richmond, Tracy K; Milliren, Carly E; Subramanian, S V

    2015-01-01

    Despite much interest in understanding the influence of contexts on health, most research has focused on one context at a time, ignoring the reality that individuals have simultaneous memberships in multiple settings. Using the example of smoking behavior among adolescents in the National Longitudinal Study of Adolescent Health, we applied cross-classified multilevel modeling (CCMM) to examine fixed and random effects for schools and neighborhoods. We compared the CCMM results with those obtained from a traditional multilevel model (MLM) focused on either the school and neighborhood separately. In the MLMs, 5.2% of the variation in smoking was due to differences between neighborhoods (when schools were ignored) and 6.3% of the variation in smoking was due to differences between schools (when neighborhoods were ignored). However in the CCMM examining neighborhood and school variation simultaneously, the neighborhood-level variation was reduced to 0.4%. Results suggest that using MLM, instead of CCMM, could lead to overestimating the importance of certain contexts and could ultimately lead to targeting interventions or policies to the wrong settings. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Robust Framework to Combine Diverse Classifiers Assigning Distributed Confidence to Individual Classifiers at Class Level

    Directory of Open Access Journals (Sweden)

    Shehzad Khalid

    2014-01-01

    Full Text Available We have presented a classification framework that combines multiple heterogeneous classifiers in the presence of class label noise. An extension of m-Mediods based modeling is presented that generates model of various classes whilst identifying and filtering noisy training data. This noise free data is further used to learn model for other classifiers such as GMM and SVM. A weight learning method is then introduced to learn weights on each class for different classifiers to construct an ensemble. For this purpose, we applied genetic algorithm to search for an optimal weight vector on which classifier ensemble is expected to give the best accuracy. The proposed approach is evaluated on variety of real life datasets. It is also compared with existing standard ensemble techniques such as Adaboost, Bagging, and Random Subspace Methods. Experimental results show the superiority of proposed ensemble method as compared to its competitors, especially in the presence of class label noise and imbalance classes.

  14. Investigation of anisotropic thermal transport in cross-linked polymers

    Science.gov (United States)

    Simavilla, David Nieto

    Thermal transport in lightly cross-linked polyisoprene and polybutadine subjected to uniaxial elongation is investigated experimentally. We employ two experimental techniques to assess the effect that deformation has on this class of materials. The first technique, which is based on Forced Rayleigh Scattering (FRS), allows us to measure the two independent components of the thermal diffusivity tensor as a function of deformation. These measurements along with independent measurements of the tensile stress and birefringence are used to evaluate the stress-thermal and stress-optic rules. The stress-thermal rule is found to be valid for the entire range of elongations applied. In contrast, the stress-optic rule fails for moderate to large stretch ratios. This suggests that the degree of anisotropy in thermal conductivity depends on both orientation and tension in polymer chain segments. The second technique, which is based on infrared thermography (IRT), allows us to measure anisotropy in thermal conductivity and strain induced changes in heat capacity. We validate this method measurements of anisotropic thermal conductivity by comparing them with those obtained using FRS. We find excellent agreement between the two techniques. Uncertainty in the infrared thermography method measurements is estimated to be about 2-5 %. The accuracy of the method and its potential application to non-transparent materials makes it a good alternative to extend current research on anisotropic thermal transport in polymeric materials. A second IRT application allows us to investigate the dependence of heat capacity on deformation. We find that heat capacity increases with stretch ratio in polyisoprene specimens under uniaxial extension. The deviation from the equilibrium value of heat capacity is consistent with an independent set of experiments comparing anisotropy in thermal diffusivity and conductivity employing FRS and IRT techniques. We identify finite extensibility and strain

  15. A statistical study of gyro-averaging effects in a reduced model of drift-wave transport

    Science.gov (United States)

    da Fonseca, J. D.; del-Castillo-Negrete, D.; Sokolov, I. M.; Caldas, I. L.

    2016-08-01

    A statistical study of finite Larmor radius (FLR) effects on transport driven by electrostatic drift-waves is presented. The study is based on a reduced discrete Hamiltonian dynamical system known as the gyro-averaged standard map (GSM). In this system, FLR effects are incorporated through the gyro-averaging of a simplified weak-turbulence model of electrostatic fluctuations. Formally, the GSM is a modified version of the standard map in which the perturbation amplitude, K0, becomes K0J0(ρ ̂ ) , where J0 is the zeroth-order Bessel function and ρ ̂ is the Larmor radius. Assuming a Maxwellian probability density function (pdf) for ρ ̂ , we compute analytically and numerically the pdf and the cumulative distribution function of the effective drift-wave perturbation amplitude K0J0(ρ ̂ ) . Using these results, we compute the probability of loss of confinement (i.e., global chaos), Pc, and the probability of trapping in the main drift-wave resonance, Pt. It is shown that Pc provides an upper bound for the escape rate, and that Pt provides a good estimate of the particle trapping rate. The analytical results are compared with direct numerical Monte-Carlo simulations of particle transport.

  16. Statistics of high-level scene context.

    Science.gov (United States)

    Greene, Michelle R

    2013-01-01

    CONTEXT IS CRITICAL FOR RECOGNIZING ENVIRONMENTS AND FOR SEARCHING FOR OBJECTS WITHIN THEM: contextual associations have been shown to modulate reaction time and object recognition accuracy, as well as influence the distribution of eye movements and patterns of brain activations. However, we have not yet systematically quantified the relationships between objects and their scene environments. Here I seek to fill this gap by providing descriptive statistics of object-scene relationships. A total of 48, 167 objects were hand-labeled in 3499 scenes using the LabelMe tool (Russell et al., 2008). From these data, I computed a variety of descriptive statistics at three different levels of analysis: the ensemble statistics that describe the density and spatial distribution of unnamed "things" in the scene; the bag of words level where scenes are described by the list of objects contained within them; and the structural level where the spatial distribution and relationships between the objects are measured. The utility of each level of description for scene categorization was assessed through the use of linear classifiers, and the plausibility of each level for modeling human scene categorization is discussed. Of the three levels, ensemble statistics were found to be the most informative (per feature), and also best explained human patterns of categorization errors. Although a bag of words classifier had similar performance to human observers, it had a markedly different pattern of errors. However, certain objects are more useful than others, and ceiling classification performance could be achieved using only the 64 most informative objects. As object location tends not to vary as a function of category, structural information provided little additional information. Additionally, these data provide valuable information on natural scene redundancy that can be exploited for machine vision, and can help the visual cognition community to design experiments guided by statistics

  17. Probabilistic safety analysis of transportation of spent fuel

    International Nuclear Information System (INIS)

    Subramaniam, Chitra

    1999-11-01

    The report presents the results of the study carried out to estimate the accident risk involved in the transport of spent fuel from Rajasthan Atomic Power Station near Kota to the fuel reprocessing plant at Tarapur. The technique of probabilistic safety analysis is used. The fuel considered is the Indian pressurised heavy water reactor fuel with a minimum cooling period of 485 days. The spent fuel is transported in a cuboidal, naturally-cooled shipping cask over a distance of 822 km by rail. The Indian rail accident statistics are used to estimate the basic rail accident frequency. The possible ways in which a release of radioactive material can occur from the spent fuel cask are identified by the fault tree analysis technique. The release sequences identified are classified into eight accident severity categories, and release fractions are assigned to each. The consequences resulting from the release are estimated by the computer code RADTRAN 4. Results of the risk analysis indicate that the accident risk values are very low and hence acceptable. Parametric studies show that the risk would continue to be small even if the controlling parameters were to simultaneously take extreme adverse values. (author)

  18. 49 CFR 614.101 - Cross-reference to management systems.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 7 2010-10-01 2010-10-01 false Cross-reference to management systems. 614.101... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION TRANSPORTATION INFRASTRUCTURE MANAGEMENT § 614.101 Cross-reference to management systems. The regulations in 23 CFR Part 500, subparts A and B shall be followed in...

  19. Selecting non-classified hotels in Kenya: what really matters for business guests?

    Directory of Open Access Journals (Sweden)

    Alex K Kivuva

    2014-01-01

    Full Text Available Non-classified hotels, which comprise small hotels and guest houses, are important accommodation providers offering limited services and products as compared to the classified hotels. Through guest satisfaction, they can achieve repeat business and also get new business through word of mouth from previous guests. The main focus is for the hoteliers to know exactly the determinants of selection of hotels by their guests. In this case, the focus was on non-classified hotels in Mtwapa town at the Kenyan coast. The study adopted a cross-sectional descriptive survey design. Results from this study clearly indicate that all aspects of hotel operations are important to business guests’ selection of a non-classified hotel. However, it was revealed that this was not on equal basis. Results indicate that the core product (guestroom comfortability, hygiene and cleanliness were the most important factors in determining guests’ selection of where to stay. This research therefore suggests that any efforts towards quality improvement in a hotel should focus primarily on ensuring customer satisfaction with the guestroom. While acknowledging the importance of all aspects of hotel operations, managers should recognize the importance of the guestroom and its facilities towards hotel selection and overall customer satisfaction. Therefore, it is imperative that managers channel their resources towards improving guest services in the guestrooms in accordance with the requirements of the clientele. This includes such aspects as the look of the guest rooms, facilities provided in the guest rooms and comfortability of the bed and mattress.

  20. Estimating External Costs of Transportation in Regional Areas: Using Available Statistical Data the Case of the Region of Campania

    Directory of Open Access Journals (Sweden)

    Mariano Gallo

    2010-04-01

    Full Text Available In this paper simplified methods for estimating the external costs due to transportation in regional areas are proposed. The methods are based on data available by national and regional statistical sources and do not need specific surveys; they allow obtaining approximate estimates useful for a preliminary evaluation of transportation plans, policies and projects. In more detail, a negative externality is defined as a cost that is produced by subject A and is borne by subject B; moreover, subject A does not consider the effects of his/her behavior on subject B and does not compensate subject B for the costs that this last one is forced to bear. In this paper after a literature review on methodologies proposed for estimating external costs, in national and international ambits, the main external costs produced by transportation systems in the Region of Campania are estimated. The main external costs considered are: greenhouse gas emissions, air pollution, noise, accidents and congestion. In the paper the secondary external costs are neglected; the main ones are: water and soil pollution; landscape and nature damages; upstream and downstream effects; visual intrusion; separation effects; soil occupancy. In this paper the external costs estimated are the ones produced not only by road traffic, that anyway is the main “culprit”, but also by rail and air transportation systems. The evaluation of external costs has required the collection of several data on the regional mobility and the estimation of veh-kms per year produced in Campania by cars and freight vehicles. The estimation of veh-kms per year is based on circulating vehicles, subdivided by the COPERT classification, and on average yearly distances covered by each vehicle class. Other regional statistical data are collected about regional rail transport and air services at the main airports of the region. Moreover, since the evaluation of some external costs is based on damages on human

  1. Adaptive Histogram Equalization Based Image Forensics Using Statistics of DC DCT Coefficients

    Directory of Open Access Journals (Sweden)

    Neetu Singh

    2018-01-01

    Full Text Available The vulnerability of digital images is growing towards manipulation. This motivated an area of research to deal with digital image forgeries. The certifying origin and content of digital images is an open problem in the multimedia world. One of the ways to find the truth of images is finding the presence of any type of contrast enhancement. In this work, novel and simple machine learning tool is proposed to detect the presence of histogram equalization using statistical parameters of DC Discrete Cosine Transform (DCT coefficients. The statistical parameters of the Gaussian Mixture Model (GMM fitted to DC DCT coefficients are used as features for classifying original and histogram equalized images. An SVM classifier has been developed to classify original and histogram equalized image which can detect histogram equalized image with accuracy greater than 95% when false rate is less than 5%.

  2. Data and Statistics: Women and Heart Disease

    Science.gov (United States)

    ... Summary Coverdell Program 2012-2015 State Summaries Data & Statistics Fact Sheets Heart Disease and Stroke Fact Sheets ... Roadmap for State Planning Other Data Resources Other Statistic Resources Grantee Information Cross-Program Information Online Tools ...

  3. 76 FR 34761 - Classified National Security Information

    Science.gov (United States)

    2011-06-14

    ... MARINE MAMMAL COMMISSION Classified National Security Information [Directive 11-01] AGENCY: Marine... Commission's (MMC) policy on classified information, as directed by Information Security Oversight Office... of Executive Order 13526, ``Classified National Security Information,'' and 32 CFR part 2001...

  4. Error minimizing algorithms for nearest eighbor classifiers

    Energy Technology Data Exchange (ETDEWEB)

    Porter, Reid B [Los Alamos National Laboratory; Hush, Don [Los Alamos National Laboratory; Zimmer, G. Beate [TEXAS A& M

    2011-01-03

    Stack Filters define a large class of discrete nonlinear filter first introd uced in image and signal processing for noise removal. In recent years we have suggested their application to classification problems, and investigated their relationship to other types of discrete classifiers such as Decision Trees. In this paper we focus on a continuous domain version of Stack Filter Classifiers which we call Ordered Hypothesis Machines (OHM), and investigate their relationship to Nearest Neighbor classifiers. We show that OHM classifiers provide a novel framework in which to train Nearest Neighbor type classifiers by minimizing empirical error based loss functions. We use the framework to investigate a new cost sensitive loss function that allows us to train a Nearest Neighbor type classifier for low false alarm rate applications. We report results on both synthetic data and real-world image data.

  5. Classifying spatially heterogeneous wetland communities using machine learning algorithms and spectral and textural features.

    Science.gov (United States)

    Szantoi, Zoltan; Escobedo, Francisco J; Abd-Elrahman, Amr; Pearlstine, Leonard; Dewitt, Bon; Smith, Scot

    2015-05-01

    Mapping of wetlands (marsh vs. swamp vs. upland) is a common remote sensing application.Yet, discriminating between similar freshwater communities such as graminoid/sedge fromremotely sensed imagery is more difficult. Most of this activity has been performed using medium to low resolution imagery. There are only a few studies using highspatial resolutionimagery and machine learning image classification algorithms for mapping heterogeneouswetland plantcommunities. This study addresses this void by analyzing whether machine learning classifierssuch as decisiontrees (DT) and artificial neural networks (ANN) can accurately classify graminoid/sedgecommunities usinghigh resolution aerial imagery and image texture data in the Everglades National Park, Florida.In addition tospectral bands, the normalized difference vegetation index, and first- and second-order texturefeatures derivedfrom the near-infrared band were analyzed. Classifier accuracies were assessed using confusiontablesand the calculated kappa coefficients of the resulting maps. The results indicated that an ANN(multilayerperceptron based on backpropagation) algorithm produced a statistically significantly higheraccuracy(82.04%) than the DT (QUEST) algorithm (80.48%) or the maximum likelihood (80.56%)classifier (αtexture features.

  6. Aggregation Operator Based Fuzzy Pattern Classifier Design

    DEFF Research Database (Denmark)

    Mönks, Uwe; Larsen, Henrik Legind; Lohweg, Volker

    2009-01-01

    This paper presents a novel modular fuzzy pattern classifier design framework for intelligent automation systems, developed on the base of the established Modified Fuzzy Pattern Classifier (MFPC) and allows designing novel classifier models which are hardware-efficiently implementable....... The performances of novel classifiers using substitutes of MFPC's geometric mean aggregator are benchmarked in the scope of an image processing application against the MFPC to reveal classification improvement potentials for obtaining higher classification rates....

  7. Requirements for design of accelerator, beam transport, and target in a study of thermonuclear reaction cross section

    Energy Technology Data Exchange (ETDEWEB)

    Itahashi, T; Takahisa, K; Fujiwara, M; Toki, H; Ejiri, H [Osaka Univ., Ibaraki (Japan). Research Center for Nuclear Physics; Ohsumi, H; Komori, M

    1997-03-01

    A compact accelerator with high current ion source, low energy beam transport elements and windowless gas target was designed to investigate the thermonuclear reaction cross section. The idea of this project focused on the cross section measurement of the fusion reaction data {sup 3}He+{sup 3}He-{sup 4}He+p+p at 25keV. The system will be installed in Otoh Cosmo Observatory (1270m.w.e.) to get rid of the huge cosmic and environmental background. It consists of NANOGUN ECR ion source, focusing elements made of permanent magnets window less {sup 3}He gas target and/or He{sup 3} plasma target and detector telescopes with low noise and low background. Requirements for these were discussed technically and various ideas were proposed. (author)

  8. Protein Secondary Structure Prediction Using AutoEncoder Network and Bayes Classifier

    Science.gov (United States)

    Wang, Leilei; Cheng, Jinyong

    2018-03-01

    Protein secondary structure prediction is belong to bioinformatics,and it's important in research area. In this paper, we propose a new prediction way of protein using bayes classifier and autoEncoder network. Our experiments show some algorithms including the construction of the model, the classification of parameters and so on. The data set is a typical CB513 data set for protein. In terms of accuracy, the method is the cross validation based on the 3-fold. Then we can get the Q3 accuracy. Paper results illustrate that the autoencoder network improved the prediction accuracy of protein secondary structure.

  9. A new modelling of the multigroup scattering cross section in deterministic codes for neutron transport

    International Nuclear Information System (INIS)

    Calloo, A.A.

    2012-01-01

    In reactor physics, calculation schemes with deterministic codes are validated with respect to a reference Monte Carlo code. The remaining biases are attributed to the approximations and models induced by the multigroup theory (self-shielding models and expansion of the scattering law using Legendre polynomials) to represent physical phenomena (resonant absorption and scattering anisotropy respectively). This work focuses on the relevance of a polynomial expansion to model the scattering law. Since the outset of reactor physics, the latter has been expanded on a truncated Legendre polynomial basis. However, the transfer cross sections are highly anisotropic, with non-zero values for a very small range of the cosine of the scattering angle. Besides, the finer the energy mesh and the lighter the scattering nucleus, the more exacerbated is the peaked shape of this cross section. As such, the Legendre expansion is less suited to represent the scattering law. Furthermore, this model induces negative values which are non-physical. In this work, various scattering laws are briefly described and the limitations of the existing model are pointed out. Hence, piecewise-constant functions have been used to represent the multigroup scattering cross section. This representation requires a different model for the diffusion source. The discrete ordinates method which is widely employed to solve the transport equation has been adapted. Thus, the finite volume method for angular discretization has been developed and implemented in Paris environment which hosts the S n solver, Snatch. The angular finite volume method has been compared to the collocation method with Legendre moments to ensure its proper performance. Moreover, unlike the latter, this method is adapted for both the Legendre moments and the piecewise-constant functions representations of the scattering cross section. This hybrid-source method has been validated for different cases: fuel cell in infinite lattice

  10. Highway-Rail Crossings Inventory Data

    Data.gov (United States)

    Department of Transportation — The entire National Highway-Rail Crossing Inventory is available in three separate downloadble files. There is a file of all current Public-at-Grade crossings. There...

  11. Transportation Energy Data Book, Edition 18

    Energy Technology Data Exchange (ETDEWEB)

    Davis, Stacy C.

    1998-09-01

    The Transportation Energy Data Book: Edition 18 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the Office of Transportation Technologies in the Department of Energy (DOE). Designed for use as a desk-top reference, the data book represents an assembly and display of statistics and information that characterize transportation activity, and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. This edition of the Data Book has 11 chapters which focus on various aspects of the transportation industry. Chapter 1 focuses on petroleum; Chapter 2 - energy Chapter 3 - emissions; Chapter 4 - transportation and the economy; Chapter 5 - highway vehicles; Chapter 6 - Light vehicles; Chapter 7 - heavy vehicles; Chapter 8 - alternative fuel vehicles; Chapter 9 - fleet vehicles; Chapter 10 - household vehicles; and Chapter 11 - nonhighway modes. The sources used represent the latest available data.

  12. Large-eddy simulation in a mixing tee junction: High-order turbulent statistics analysis

    International Nuclear Information System (INIS)

    Howard, Richard J.A.; Serre, Eric

    2015-01-01

    Highlights: • Mixing and thermal fluctuations in a junction are studied using large eddy simulation. • Adiabatic and conducting steel wall boundaries are tested. • Wall thermal fluctuations are not the same between the flow and the solid. • Solid thermal fluctuations cannot be predicted from the fluid thermal fluctuations. • High-order turbulent statistics show that the turbulent transport term is important. - Abstract: This study analyses the mixing and thermal fluctuations induced in a mixing tee junction with circular cross-sections when cold water flowing in a pipe is joined by hot water from a branch pipe. This configuration is representative of industrial piping systems in which temperature fluctuations in the fluid may cause thermal fatigue damage on the walls. Implicit large-eddy simulations (LES) are performed for equal inflow rates corresponding to a bulk Reynolds number Re = 39,080. Two different thermal boundary conditions are studied for the pipe walls; an insulating adiabatic boundary and a conducting steel wall boundary. The predicted flow structures show a satisfactory agreement with the literature. The velocity and thermal fields (including high-order statistics) are not affected by the heat transfer with the steel walls. However, predicted thermal fluctuations at the boundary are not the same between the flow and the solid, showing that solid thermal fluctuations cannot be predicted by the knowledge of the fluid thermal fluctuations alone. The analysis of high-order turbulent statistics provides a better understanding of the turbulence features. In particular, the budgets of the turbulent kinetic energy and temperature variance allows a comparative analysis of dissipation, production and transport terms. It is found that the turbulent transport term is an important term that acts to balance the production. We therefore use a priori tests to evaluate three different models for the triple correlation

  13. Composite Classifiers for Automatic Target Recognition

    National Research Council Canada - National Science Library

    Wang, Lin-Cheng

    1998-01-01

    ...) using forward-looking infrared (FLIR) imagery. Two existing classifiers, one based on learning vector quantization and the other on modular neural networks, are used as the building blocks for our composite classifiers...

  14. Symmetry Analysis of Gait between Left and Right Limb Using Cross-Fuzzy Entropy

    Directory of Open Access Journals (Sweden)

    Yi Xia

    2016-01-01

    Full Text Available The purpose of this paper is the investigation of gait symmetry problem by using cross-fuzzy entropy (C-FuzzyEn, which is a recently proposed cross entropy that has many merits as compared to the frequently used cross sample entropy (C-SampleEn. First, we used several simulation signals to test its performance regarding the relative consistency and dependence on data length. Second, the gait time series of the left and right stride interval were used to calculate the C-FuzzyEn values for gait symmetry analysis. Besides the statistical analysis, we also realized a support vector machine (SVM classifier to perform the classification of normal and abnormal gaits. The gait dataset consists of 15 patients with Parkinson’s disease (PD and 16 control (CO subjects. The results show that the C-FuzzyEn values of the PD patients’ gait are significantly higher than that of the CO subjects with a p value of less than 10-5, and the best classification performance evaluated by a leave-one-out (LOO cross-validation method is an accuracy of 96.77%. Such encouraging results imply that the C-FuzzyEn-based gait symmetry measure appears as a suitable tool for analyzing abnormal gaits.

  15. Using point-set compression to classify folk songs

    DEFF Research Database (Denmark)

    Meredith, David

    2014-01-01

    -neighbour algorithm and leave-one-out cross-validation to classify the 360 melodies into tune families. The classifications produced by the algorithms were compared with a ground-truth classification prepared by expert musicologists. Twelve of the thirteen compressors used in the experiment were based...... compared. The highest classification success rate of 77–84% was achieved by COSIATEC, followed by 60–64% for Forth’s algorithm and then 52–58% for SIATECCompress. When the NCDs were calculated using bzip2, the success rate was only 12.5%. The results demonstrate that the effectiveness of NCD for measuring...... similarity between folk-songs for classification purposes is highly dependent upon the actual compressor chosen. Furthermore, it seems that compressors based on finding maximal repeated patterns in point-set representations of music show more promise for NCD-based music classification than general...

  16. Changes over time in population level transport satisfaction and mode of travel: A 13 year repeat cross-sectional study, UK.

    Science.gov (United States)

    Olsen, Jonathan R; Macdonald, Laura; Ellaway, Anne

    2017-09-01

    The aim of the study was to examine changes over time in satisfaction with usual transport mode, explore individual and area level characteristics as mediators in the likelihood of transport satisfaction, and whether any changes in transport satisfaction varied by these factors over time. Adults from West Central Scotland, United Kingdom, who participated at both waves of the repeat cross-sectional 'Transport, Health and Well-being Study' conducted in 1997 (n=2735) and 2010 (n=2024) were assessed. Individuals completed a detailed postal questionnaire at both time points including self-rated satisfaction with usual transport mode (using a seven point scale subsequently dichotomised to a binary outcome of satisfied (1-2) and other (3-7)). Participants reported usual transport mode for travel to various destinations. A multilevel logistic regression model was used and individuals were nested within areas (c. 4000 population). At the 2010 sweep, two thirds (n=1345) of individuals were satisfied with their transport choice. Those with fair/poor health were less satisfied with their usual transport compared to those in better health (Odds Ratio (OR) 0.49, ptravelled by public transport (OR 2.39, p=0.005) and using multiple modes (OR 2.19, ptravelled by car. The proportion of those who travelled using public transport, active modes or by multiple mode increased journey satisfaction over time at a greater rate than those who travelled by car, highlighting that continued efforts should be made to promote these more active transport modes which have potential to impact on health.

  17. Nuclear transport

    International Nuclear Information System (INIS)

    Anon.

    2002-01-01

    During September and October 2001, 1 event has been reported and classified at the first level of the INES scale. This incident concerns the violation of the European regulation that imposes to any driver of radioactive matter of being the holder of a certificate asserting that he attended a special training. During this period, 13 in-site inspections have been made in places related to nuclear transport. (A.C.)

  18. Intramolecular cross-linking in a bacterial homolog of mammalian SLC6 neurotransmitter transporters suggests an evolutionary conserved role of transmembrane segments 7 and 8

    DEFF Research Database (Denmark)

    Kniazeff, Julie; Loland, Claus Juul; Goldberg, Naomi

    2005-01-01

    The extracellular concentration of the neurotransmitters dopamine, serotonin, norepinephrine, GABA and glycine is tightly controlled by plasma membrane transporters belonging to the SLC6 gene family. A very large number of putative transport proteins with a remarkable homology to the SLC6...... proximity between TM 7 and 8 in the tertiary structure of TnaT as previously suggested for the mammalian counterparts. Furthermore, the inhibition of uptake upon cross-linking the two cysteines provides indirect support for a conserved conformational role of these transmembrane domains in the transport...

  19. Statistical mechanics

    CERN Document Server

    Jana, Madhusudan

    2015-01-01

    Statistical mechanics is self sufficient, written in a lucid manner, keeping in mind the exam system of the universities. Need of study this subject and its relation to Thermodynamics is discussed in detail. Starting from Liouville theorem gradually, the Statistical Mechanics is developed thoroughly. All three types of Statistical distribution functions are derived separately with their periphery of applications and limitations. Non-interacting ideal Bose gas and Fermi gas are discussed thoroughly. Properties of Liquid He-II and the corresponding models have been depicted. White dwarfs and condensed matter physics, transport phenomenon - thermal and electrical conductivity, Hall effect, Magneto resistance, viscosity, diffusion, etc. are discussed. Basic understanding of Ising model is given to explain the phase transition. The book ends with a detailed coverage to the method of ensembles (namely Microcanonical, canonical and grand canonical) and their applications. Various numerical and conceptual problems ar...

  20. Air Carrier Traffic Statistics.

    Science.gov (United States)

    2013-11-01

    This report contains airline operating statistics for large certificated air carriers based on data reported to U.S. Department of Transportation (DOT) by carriers that hold a certificate issued under Section 401 of the Federal Aviation Act of 1958 a...

  1. Air Carrier Traffic Statistics.

    Science.gov (United States)

    2012-07-01

    This report contains airline operating statistics for large certificated air carriers based on data reported to U.S. Department of Transportation (DOT) by carriers that hold a certificate issued under Section 401 of the Federal Aviation Act of 1958 a...

  2. Mesoscale modeling of smoke transport over Central Africa: influences of trade winds, subtropical high, ITCZ and vertical statistics

    Science.gov (United States)

    Yang, Z.; Wang, J.; Hyer, E. J.; Ichoku, C. M.

    2012-12-01

    A fully-coupled meteorology-chemistry-aerosol model, Weather Research and Forecasting model with Chemistry (WRF-Chem), is used to simulate the transport of smoke aerosol over the Central Africa during February 2008. Smoke emission used in this study is specified from the Fire Locating and Modeling of Burning Emissions (FLAMBE) database derived from Moderate Resolution Imaging Spectroradiometer (MODIS) fire products. Model performance is evaluated using MODIS true color images, measured Aerosol Optical Depth (AOD) from space-borne MODIS (550 nm) and ground-based AERONET (500 nm), and Cloud-Aerosol Lidar data with Orthogonal Polarization (CALIOP) level 1 and 2 products. The simulated smoke transport is in good agreement with the validation data. Analyzing from three smoke events, smoke is constrained in a narrow belt between the Equator and 10°N near the surface, with the interplay of trade winds, subtropical high, and ITCZ. At the 700 hpa level, smoke expands farther meridionally. Topography blocks the smoke transport to the southeast of study area, because of high mountains located near the Great Rift Valley region. The simulation with injection height of 650 m is consistent with CALIOP measurements. The particular phenomenon, aerosol above cloud, is studied statistically from CALIOP observations. The total percentage of aerosol above cloud is about 5%.

  3. Assessment of fractures classified as non-mineralised in the Sicada database

    International Nuclear Information System (INIS)

    Claesson Liljedahl, Lillemor; Munier, Raymond; Sandstroem, Bjoern; Drake, Henrik; Tullborg, Eva-Lena

    2011-03-01

    The general objective of this report was to describe the results of the investigation of fractures classified as non-mineralised in Sicada. Such fractures exist at Forsmark and at Laxemar. The main aims of the investigation of these fractures were to: - Quantify the number of non-mineralised fractures (i.e. fractures lacking mineral coating) in Sicada (table: p f ract c ore e shi). - Closely examine a selection of fractures recorded as non-mineralised in Sicada. - Outline possible reasons for the existence of non-mineralised fractures. The work has involved extraction of fracture data from Sicada and subsequent statistical analysis. Since several thousand fractures are classified as non-mineralised in Sicada, it was not a practical possibility to include all these in this study, we examined one fracture sub-set from each site. We investigated a sample of 204 of these fractures in detail (see Sections 1.1 and 2.4). Rock mechanical differences between Forsmark and Laxemar and kinematic analysis of fracture surfaces is not discussed in this report

  4. Level crossing statistics for optical beam wander in a turbulent atmosphere with applications to ground-to-space laser communications.

    Science.gov (United States)

    Yura, Harold T; Fields, Renny A

    2011-06-20

    Level crossing statistics is applied to the complex problem of atmospheric turbulence-induced beam wander for laser propagation from ground to space. A comprehensive estimate of the single-axis wander angle temporal autocorrelation function and the corresponding power spectrum is used to develop, for the first time to our knowledge, analytic expressions for the mean angular level crossing rate and the mean duration of such crossings. These results are based on an extension and generalization of a previous seminal analysis of the beam wander variance by Klyatskin and Kon. In the geometrical optics limit, we obtain an expression for the beam wander variance that is valid for both an arbitrarily shaped initial beam profile and transmitting aperture. It is shown that beam wander can disrupt bidirectional ground-to-space laser communication systems whose small apertures do not require adaptive optics to deliver uniform beams at their intended target receivers in space. The magnitude and rate of beam wander is estimated for turbulence profiles enveloping some practical laser communication deployment options and suggesting what level of beam wander effects must be mitigated to demonstrate effective bidirectional laser communication systems.

  5. Transportation Energy Data Book, Edition 19; TOPICAL

    International Nuclear Information System (INIS)

    Davis, S.C.

    1999-01-01

    The Transportation Energy Data Book: Edition 19 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the Office of Transportation Technologies in the Department of Energy (DOE). Designed for use as a desk-top reference, the data book represents an assembly and display of statistics and information that characterize transportation activity, and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. The latest editions of the Data Book are available to a larger audience via the Internet (http://www-cta.ornl.gov/data/tedb.htm)

  6. Kinetic phenomena in charged particle transport in gases, swarm parameters and cross section data

    International Nuclear Information System (INIS)

    Petrovic, Z Lj; Suvakov, M; Nikitovic, Z; Dujko, S; Sasic, O; Jovanovic, J; Malovic, G; Stojanovic, V

    2007-01-01

    In this review we discuss the current status of the physics of charged particle swarms, mainly electrons. The whole field is analysed mainly through its relationship to plasma modelling and illustrated by some recent examples developed mainly by our group. The measurements of the swarm coefficients and the availability of the data are briefly discussed. More time is devoted to the development of complete electron-molecule cross section sets along with recent examples such as NO, CF 4 and HBr. We extend the discussion to the availability of ion and fast neutral data and how swarm experiments may serve to provide new data. As a point where new insight into the kinetics of charge particle transport is provided, the role of kinetic phenomena is discussed and recent examples are listed. We focus here on giving two examples on how non-conservative processes make dramatic effects in transport, the negative absolute mobility and the negative differential conductivity for positrons in argon. Finally we discuss the applicability of swarm data in plasma modelling and the relationship to other fields where swarm experiments and analysis make significant contributions. (topical review)

  7. Hybrid Neuro-Fuzzy Classifier Based On Nefclass Model

    Directory of Open Access Journals (Sweden)

    Bogdan Gliwa

    2011-01-01

    Full Text Available The paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which wasmodified. The presented classifier was compared to popular classifiers – neural networks andk-nearest neighbours. Efficiency of modifications in classifier was compared with methodsused in original model NEFCLASS (learning methods. Accuracy of classifier was testedusing 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wisconsin.Moreover, influence of ensemble classification methods on classification accuracy waspresented.

  8. Spread-sheet application to classify radioactive material for shipment

    International Nuclear Information System (INIS)

    Brown, A.N.

    1998-01-01

    A spread-sheet application has been developed at the Idaho National Engineering and Environmental Laboratory to aid the shipper when classifying nuclide mixtures of normal form, radioactive materials. The results generated by this spread-sheet are used to confirm the proper US DOT classification when offering radioactive material packages for transport. The user must input to the spread-sheet the mass of the material being classified, the physical form (liquid or not) and the activity of each regulated nuclide. The spread-sheet uses these inputs to calculate two general values: 1)the specific activity of the material and a summation calculation of the nuclide content. The specific activity is used to determine if the material exceeds the DOT minimal threshold for a radioactive material. If the material is calculated to be radioactive, the specific activity is also used to determine if the material meets the activity requirement for one of the three low specific activity designations (LSA-I, LSA-II, LSA-III, or not LSA). Again, if the material is calculated to be radioactive, the summation calculation is then used to determine which activity category the material will meet (Limited Quantity, Type A, Type B, or Highway Route Controlled Quantity). This spread-sheet has proven to be an invaluable aid for shippers of radioactive materials at the Idaho National Engineering and Environmental Laboratory. (authors)

  9. Modern applied U-statistics

    CERN Document Server

    Kowalski, Jeanne

    2008-01-01

    A timely and applied approach to the newly discovered methods and applications of U-statisticsBuilt on years of collaborative research and academic experience, Modern Applied U-Statistics successfully presents a thorough introduction to the theory of U-statistics using in-depth examples and applications that address contemporary areas of study including biomedical and psychosocial research. Utilizing a "learn by example" approach, this book provides an accessible, yet in-depth, treatment of U-statistics, as well as addresses key concepts in asymptotic theory by integrating translational and cross-disciplinary research.The authors begin with an introduction of the essential and theoretical foundations of U-statistics such as the notion of convergence in probability and distribution, basic convergence results, stochastic Os, inference theory, generalized estimating equations, as well as the definition and asymptotic properties of U-statistics. With an emphasis on nonparametric applications when and where applic...

  10. Vehicle routing with cross-docking

    DEFF Research Database (Denmark)

    Wen, Min; Larsen, Jesper; Clausen, Jens

    2009-01-01

    a set of homogeneous vehicles are used to transport orders from the suppliers to the corresponding customers via a cross-dock. The orders can be consolidated at the cross-dock but cannot be stored for very long because the cross-dock does not have long-term inventory-holding capabilities. The objective...... of the VRPCD is to minimize the total travel time while respecting time window constraints at the nodes and a time horizon for the whole transportation operation. In this paper, a mixed integer programming formulation for the VRPCD is proposed. A tabu search heuristic is embedded within an adaptive memory...... values) within very short computational time....

  11. Sistem Klasifikasi Kualitas Kopra Berdasarkan Warna dan Tekstur Menggunakan Metode Nearest Mean Classifier (NMC

    Directory of Open Access Journals (Sweden)

    Abdullah Abdullah

    2017-12-01

    The classification of copra quality with the help of computer by using image processing can help to speed up human work. Data mining techniques can be utilized for copra quality classification based on RGB color (red, green, blue and texture (energy, contrast, correlation, homogeneity. The problem is the difficulty in predicting the quality of copra in grade of A (80-85%, grade of B (70-75% and grade of C (60-65%. The purpose of this study is to develope an application for the classification of copra quality based on color and texture. The method used is the nearest mean classifier (NMC. Preprocessing is done before the classification process for background subtraction by using pixel subtraction method to separate the image of object against the background. The benefits of this research are it can save time in classifying the quality of copra and can facilitate the determination of copra price. Based on the evaluation result by using cross validation method obtained the average accuracy is 80.67% with standard deviation is 1.17%.  Keywords: classification,  image, copra, nearest mean classifier, pixel subtraction, RGB color, texture

  12. SVM Classifier - a comprehensive java interface for support vector machine classification of microarray data.

    Science.gov (United States)

    Pirooznia, Mehdi; Deng, Youping

    2006-12-12

    Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction. The GUI provides user-friendly access to state-of-the-art SVM methods embodied in the LIBSVM implementation of Support Vector Machine. We implemented the java interface using standard swing libraries. We used a sample data from a breast cancer study for testing classification accuracy. We achieved 100% accuracy in classification among the BRCA1-BRCA2 samples with RBF kernel of SVM. We have developed a java GUI application that allows SVM users to perform SVM training, classification and prediction. We have demonstrated that support vector machines can accurately classify genes into functional categories based upon expression data from DNA microarray hybridization experiments. Among the different kernel functions that we examined, the SVM that uses a radial basis kernel function provides the best performance. The SVM Classifier is available at http://mfgn.usm.edu/ebl/svm/.

  13. Transport of nuclear materials

    International Nuclear Information System (INIS)

    Anon.

    2002-01-01

    During november and december 2001, 2 events concerning nuclear transport were reported and classified on the first grade (grade 1) of the INES scale. The first event concerns a hole in a transport cask of contaminated tools. The hole seems to have been made by the fork of a handling equipment. The second event concerns the loss of a parcel containing a technetium generator, this generator represented an activity of about 141 G Becquerel of 99 Mo the day it left the premises of CIS-bio in Saclay. (A.C.)

  14. 36 CFR 1256.46 - National security-classified information.

    Science.gov (United States)

    2010-07-01

    ... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false National security-classified... Restrictions § 1256.46 National security-classified information. In accordance with 5 U.S.C. 552(b)(1), NARA... properly classified under the provisions of the pertinent Executive Order on Classified National Security...

  15. Pocket Guide to Transportation 2012

    Science.gov (United States)

    2012-01-01

    The Bureau of Transportation Statistics (BTS) of the Research and Innovative Technology Administration produces the Pocket Guide to Transportation as a compact resource that provides snapshots of the U.S. transportation system and highlights major tr...

  16. Class-specific Error Bounds for Ensemble Classifiers

    Energy Technology Data Exchange (ETDEWEB)

    Prenger, R; Lemmond, T; Varshney, K; Chen, B; Hanley, W

    2009-10-06

    The generalization error, or probability of misclassification, of ensemble classifiers has been shown to be bounded above by a function of the mean correlation between the constituent (i.e., base) classifiers and their average strength. This bound suggests that increasing the strength and/or decreasing the correlation of an ensemble's base classifiers may yield improved performance under the assumption of equal error costs. However, this and other existing bounds do not directly address application spaces in which error costs are inherently unequal. For applications involving binary classification, Receiver Operating Characteristic (ROC) curves, performance curves that explicitly trade off false alarms and missed detections, are often utilized to support decision making. To address performance optimization in this context, we have developed a lower bound for the entire ROC curve that can be expressed in terms of the class-specific strength and correlation of the base classifiers. We present empirical analyses demonstrating the efficacy of these bounds in predicting relative classifier performance. In addition, we specify performance regions of the ROC curve that are naturally delineated by the class-specific strengths of the base classifiers and show that each of these regions can be associated with a unique set of guidelines for performance optimization of binary classifiers within unequal error cost regimes.

  17. Just-in-time classifiers for recurrent concepts.

    Science.gov (United States)

    Alippi, Cesare; Boracchi, Giacomo; Roveri, Manuel

    2013-04-01

    Just-in-time (JIT) classifiers operate in evolving environments by classifying instances and reacting to concept drift. In stationary conditions, a JIT classifier improves its accuracy over time by exploiting additional supervised information coming from the field. In nonstationary conditions, however, the classifier reacts as soon as concept drift is detected; the current classification setup is discarded and a suitable one activated to keep the accuracy high. We present a novel generation of JIT classifiers able to deal with recurrent concept drift by means of a practical formalization of the concept representation and the definition of a set of operators working on such representations. The concept-drift detection activity, which is crucial in promptly reacting to changes exactly when needed, is advanced by considering change-detection tests monitoring both inputs and classes distributions.

  18. Spectral and cross-spectral analysis of uneven time series with the smoothed Lomb-Scargle periodogram and Monte Carlo evaluation of statistical significance

    Science.gov (United States)

    Pardo-Igúzquiza, Eulogio; Rodríguez-Tovar, Francisco J.

    2012-12-01

    Many spectral analysis techniques have been designed assuming sequences taken with a constant sampling interval. However, there are empirical time series in the geosciences (sediment cores, fossil abundance data, isotope analysis, …) that do not follow regular sampling because of missing data, gapped data, random sampling or incomplete sequences, among other reasons. In general, interpolating an uneven series in order to obtain a succession with a constant sampling interval alters the spectral content of the series. In such cases it is preferable to follow an approach that works with the uneven data directly, avoiding the need for an explicit interpolation step. The Lomb-Scargle periodogram is a popular choice in such circumstances, as there are programs available in the public domain for its computation. One new computer program for spectral analysis improves the standard Lomb-Scargle periodogram approach in two ways: (1) It explicitly adjusts the statistical significance to any bias introduced by variance reduction smoothing, and (2) it uses a permutation test to evaluate confidence levels, which is better suited than parametric methods when neighbouring frequencies are highly correlated. Another novel program for cross-spectral analysis offers the advantage of estimating the Lomb-Scargle cross-periodogram of two uneven time series defined on the same interval, and it evaluates the confidence levels of the estimated cross-spectra by a non-parametric computer intensive permutation test. Thus, the cross-spectrum, the squared coherence spectrum, the phase spectrum, and the Monte Carlo statistical significance of the cross-spectrum and the squared-coherence spectrum can be obtained. Both of the programs are written in ANSI Fortran 77, in view of its simplicity and compatibility. The program code is of public domain, provided on the website of the journal (http://www.iamg.org/index.php/publisher/articleview/frmArticleID/112/). Different examples (with simulated and

  19. Cross-impact method

    Directory of Open Access Journals (Sweden)

    Suzić Nenad

    2014-01-01

    Full Text Available The paper displays the application of the Cross-Impact method in pedagogy, namely a methodological approach which crosses variables in a novel, but statistically justified manner. The method is an innovation in pedagogy as well as in research methodology of social and psychological phenomena. Specifically, events and processes are crossed, that is, experts' predictions of about future interaction of events and processes. Therefore, this methodology is futuristic; it concerns predicting future, which is of key importance for pedagogic objectives. The paper presents two instances of the cross-impact approach: the longer, displayed in fourteen steps, and the shorter, in four steps. They are both accompanied with mathematic and statistical formulae allowing for quantification, that is, a numerical expression of the probability of a certain event happening in the future. The advantage of this approach is that it facilitates planning in education which so far has been solely based on lay estimates and assumptions.

  20. Azimuthal anisotropy in heavy-ion collisions using non-extensive statistics in Boltzmann transport equation

    International Nuclear Information System (INIS)

    Tripathy, S.; Tiwari, S.K.; Younus, M.; Sahoo, R.

    2017-01-01

    One of the major goals in heavy-ion physics is to understand the properties of Quark Gluon Plasma (QGP), a deconfined hot and dense state of quarks and gluons existed shortly after the Big Bang. In the present scenario, the high-energy particle accelerators are able to reach energies where this extremely dense nuclear matter can be probed for a short time. Here, we follow our earlier works which use non-extensive statistics in Boltzmann Transport Equation (BTE). We represent the initial distribution of particles with the help of Tsallis power law distribution parameterized by the nonextensive parameter q and the Tsallis temperature T, remembering the fact that their origin is due to hard scatterings. We use the initial distribution (f in ) with Relaxation Time Approximation (RTA) of the BTE and calculate the final distribution (f fin ). Then we calculate ν 2 of the system using the final distribution in the definition of ν2

  1. 14 CFR 234.6 - Baggage-handling statistics.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Baggage-handling statistics. 234.6 Section 234.6 Aeronautics and Space OFFICE OF THE SECRETARY, DEPARTMENT OF TRANSPORTATION (AVIATION... statistics. Each reporting carrier shall report monthly to the Department on a domestic system basis...

  2. A Novel HMM Distributed Classifier for the Detection of Gait Phases by Means of a Wearable Inertial Sensor Network

    Directory of Open Access Journals (Sweden)

    Juri Taborri

    2014-09-01

    Full Text Available In this work, we decided to apply a hierarchical weighted decision, proposed and used in other research fields, for the recognition of gait phases. The developed and validated novel distributed classifier is based on hierarchical weighted decision from outputs of scalar Hidden Markov Models (HMM applied to angular velocities of foot, shank, and thigh. The angular velocities of ten healthy subjects were acquired via three uni-axial gyroscopes embedded in inertial measurement units (IMUs during one walking task, repeated three times, on a treadmill. After validating the novel distributed classifier and scalar and vectorial classifiers-already proposed in the literature, with a cross-validation, classifiers were compared for sensitivity, specificity, and computational load for all combinations of the three targeted anatomical segments. Moreover, the performance of the novel distributed classifier in the estimation of gait variability in terms of mean time and coefficient of variation was evaluated. The highest values of specificity and sensitivity (>0.98 for the three classifiers examined here were obtained when the angular velocity of the foot was processed. Distributed and vectorial classifiers reached acceptable values (>0.95 when the angular velocity of shank and thigh were analyzed. Distributed and scalar classifiers showed values of computational load about 100 times lower than the one obtained with the vectorial classifier. In addition, distributed classifiers showed an excellent reliability for the evaluation of mean time and a good/excellent reliability for the coefficient of variation. In conclusion, due to the better performance and the small value of computational load, the here proposed novel distributed classifier can be implemented in the real-time application of gait phases recognition, such as to evaluate gait variability in patients or to control active orthoses for the recovery of mobility of lower limb joints.

  3. Transport Coefficients of Fluids

    CERN Document Server

    Eu, Byung Chan

    2006-01-01

    Until recently the formal statistical mechanical approach offered no practicable method for computing the transport coefficients of liquids, and so most practitioners had to resort to empirical fitting formulas. This has now changed, as demonstrated in this innovative monograph. The author presents and applies new methods based on statistical mechanics for calculating the transport coefficients of simple and complex liquids over wide ranges of density and temperature. These molecular theories enable the transport coefficients to be calculated in terms of equilibrium thermodynamic properties, and the results are shown to account satisfactorily for experimental observations, including even the non-Newtonian behavior of fluids far from equilibrium.

  4. Pocket Guide to Transportation 2018

    Science.gov (United States)

    2018-01-01

    The 2018 BTS Pocket Guide to Transportation is a quick reference guide that provides transportation statistics at your fingertips. It provides key information and highlights major trends on the U.S. transportation system. This year features a new and...

  5. Comparing classifiers for pronunciation error detection

    NARCIS (Netherlands)

    Strik, H.; Truong, K.; Wet, F. de; Cucchiarini, C.

    2007-01-01

    Providing feedback on pronunciation errors in computer assisted language learning systems requires that pronunciation errors be detected automatically. In the present study we compare four types of classifiers that can be used for this purpose: two acoustic-phonetic classifiers (one of which employs

  6. Transportation energy data book: Edition 15

    Energy Technology Data Exchange (ETDEWEB)

    Davis, S.C.

    1995-05-01

    The Transportation Energy Data Book: Edition 15 is a statistical compendium. Designed for use as a desk-top reference, the data book represents an assembly and display of statistics and information that characterize transportation activity, and presents data on other factors that influence transportation energy use. Purpose of this document is to present relevant statistical data in the form of tables and graphs. Each of the major transportation modes is treated in separate chapters or sections. Chapter I compares US transportation data with data from other countries. Aggregate energy use and energy supply data for all modes are presented in Chapter 2. The highway mode, which accounts for over three-fourths of total transportation energy consumption, is dealt with in Chapter 3. Topics in this chapter include automobiles, trucks, buses, fleet vehicles, federal standards, fuel economies, and high-occupancy vehicle lane data. Household travel behavior characteristics are displayed in Chapter 4. Chapter 5 contains information on alternative fuels and alternative fuel vehicles. Chapter 6 covers the major nonhighway modes: air, water, and rail. The last chapter, Chapter 7, presents data environmental issues relating to transportation.

  7. Classifier Fusion With Contextual Reliability Evaluation.

    Science.gov (United States)

    Liu, Zhunga; Pan, Quan; Dezert, Jean; Han, Jun-Wei; He, You

    2018-05-01

    Classifier fusion is an efficient strategy to improve the classification performance for the complex pattern recognition problem. In practice, the multiple classifiers to combine can have different reliabilities and the proper reliability evaluation plays an important role in the fusion process for getting the best classification performance. We propose a new method for classifier fusion with contextual reliability evaluation (CF-CRE) based on inner reliability and relative reliability concepts. The inner reliability, represented by a matrix, characterizes the probability of the object belonging to one class when it is classified to another class. The elements of this matrix are estimated from the -nearest neighbors of the object. A cautious discounting rule is developed under belief functions framework to revise the classification result according to the inner reliability. The relative reliability is evaluated based on a new incompatibility measure which allows to reduce the level of conflict between the classifiers by applying the classical evidence discounting rule to each classifier before their combination. The inner reliability and relative reliability capture different aspects of the classification reliability. The discounted classification results are combined with Dempster-Shafer's rule for the final class decision making support. The performance of CF-CRE have been evaluated and compared with those of main classical fusion methods using real data sets. The experimental results show that CF-CRE can produce substantially higher accuracy than other fusion methods in general. Moreover, CF-CRE is robust to the changes of the number of nearest neighbors chosen for estimating the reliability matrix, which is appealing for the applications.

  8. Status of radioactive material transport

    International Nuclear Information System (INIS)

    Kueny, Laurent

    2012-01-01

    As about 900.000 parcels containing radioactive materials are transported every year in France, the author recalls the main risks and safety principles associated with such transport. He indicates the different types of parcels defined by the regulation: excepted parcels, industrial non fissile parcels (type A), type B and fissile parcels, and highly radioactive type C parcels. He briefly presents the Q-system which is used to classify the parcels. He describes the role of the ASN in the control of transport safety, and indicates the different contracts existing between France or Areva and different countries (Germany, Japan, Netherlands, etc.) for the processing of used fuels in La Hague

  9. Classifying images using restricted Boltzmann machines and convolutional neural networks

    Science.gov (United States)

    Zhao, Zhijun; Xu, Tongde; Dai, Chenyu

    2017-07-01

    To improve the feature recognition ability of deep model transfer learning, we propose a hybrid deep transfer learning method for image classification based on restricted Boltzmann machines (RBM) and convolutional neural networks (CNNs). It integrates learning abilities of two models, which conducts subject classification by exacting structural higher-order statistics features of images. While the method transfers the trained convolutional neural networks to the target datasets, fully-connected layers can be replaced by restricted Boltzmann machine layers; then the restricted Boltzmann machine layers and Softmax classifier are retrained, and BP neural network can be used to fine-tuned the hybrid model. The restricted Boltzmann machine layers has not only fully integrated the whole feature maps, but also learns the statistical features of target datasets in the view of the biggest logarithmic likelihood, thus removing the effects caused by the content differences between datasets. The experimental results show that the proposed method has improved the accuracy of image classification, outperforming other methods on Pascal VOC2007 and Caltech101 datasets.

  10. Hierarchical mixtures of naive Bayes classifiers

    NARCIS (Netherlands)

    Wiering, M.A.

    2002-01-01

    Naive Bayes classifiers tend to perform very well on a large number of problem domains, although their representation power is quite limited compared to more sophisticated machine learning algorithms. In this pa- per we study combining multiple naive Bayes classifiers by using the hierar- chical

  11. Word2Vec inversion and traditional text classifiers for phenotyping lupus.

    Science.gov (United States)

    Turner, Clayton A; Jacobs, Alexander D; Marques, Cassios K; Oates, James C; Kamen, Diane L; Anderson, Paul E; Obeid, Jihad S

    2017-08-22

    Identifying patients with certain clinical criteria based on manual chart review of doctors' notes is a daunting task given the massive amounts of text notes in the electronic health records (EHR). This task can be automated using text classifiers based on Natural Language Processing (NLP) techniques along with pattern recognition machine learning (ML) algorithms. The aim of this research is to evaluate the performance of traditional classifiers for identifying patients with Systemic Lupus Erythematosus (SLE) in comparison with a newer Bayesian word vector method. We obtained clinical notes for patients with SLE diagnosis along with controls from the Rheumatology Clinic (662 total patients). Sparse bag-of-words (BOWs) and Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs) matrices were produced using NLP pipelines. These matrices were subjected to several different NLP classifiers: neural networks, random forests, naïve Bayes, support vector machines, and Word2Vec inversion, a Bayesian inversion method. Performance was measured by calculating accuracy and area under the Receiver Operating Characteristic (ROC) curve (AUC) of a cross-validated (CV) set and a separate testing set. We calculated the accuracy of the ICD-9 billing codes as a baseline to be 90.00% with an AUC of 0.900, the shallow neural network with CUIs to be 92.10% with an AUC of 0.970, the random forest with BOWs to be 95.25% with an AUC of 0.994, the random forest with CUIs to be 95.00% with an AUC of 0.979, and the Word2Vec inversion to be 90.03% with an AUC of 0.905. Our results suggest that a shallow neural network with CUIs and random forests with both CUIs and BOWs are the best classifiers for this lupus phenotyping task. The Word2Vec inversion method failed to significantly beat the ICD-9 code classification, but yielded promising results. This method does not require explicit features and is more adaptable to non-binary classification tasks. The Word2Vec inversion is

  12. The human dopamine transporter forms a tetramer in the plasma membrane: cross-linking of a cysteine in the fourth transmembrane segment is sensitive to cocaine analogs.

    Science.gov (United States)

    Hastrup, Hanne; Sen, Namita; Javitch, Jonathan A

    2003-11-14

    Using cysteine cross-linking, we demonstrated previously that the dopamine transporter (DAT) is at least a homodimer, with the extracellular end of transmembrane segment (TM) 6 at a symmetrical dimer interface. We have now explored the possibility that DAT exists as a higher order oligomer in the plasma membrane. Cysteine cross-linking of wild type DAT resulted in bands on SDS-PAGE consistent with dimer, trimer, and tetramer, suggesting that DAT forms a tetramer in the plasma membrane. A cysteine-depleted DAT (CD-DAT) into which only Cys243 or Cys306 was reintroduced was cross-linked to dimer, suggesting that these endogenous cysteines in TM4 and TM6, respectively, were cross-linked at a symmetrical dimer interface. Reintroduction of both Cys243 and Cys306 into CD-DAT led to a pattern of cross-linking indistinguishable from that of wild type, with dimer, trimer, and tetramer bands. This indicated that the TM4 interface and the TM6 interface are distinct and further suggested that DAT may exist in the plasma membrane as a dimer of dimers, with two symmetrical homodimer interfaces. The cocaine analog MFZ 2-12 and other DAT inhibitors, including benztropine and mazindol, protected Cys243 against cross-linking. In contrast, two substrates of DAT, dopamine and tyramine, did not significantly impact cross-linking. We propose that the impairment of cross-linking produced by the inhibitors results from a conformational change at the TM4 interface, further demonstrating that these compounds are not neutral blockers but by themselves have effects on the structure of the transporter.

  13. Transportation energy data book: edition 16

    Energy Technology Data Exchange (ETDEWEB)

    Davis, S.C. [Lockheed Martin Energy Systems, Inc., Oak Ridge, TN (United States); McFarlin, D.N. [Tennessee Univ., Knoxville, TN (United States)

    1996-07-01

    The Transportation Energy Data Book: Edition 16 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the Office of Transportation Technologies in the Department of Energy (DOE). Designed for use as a desk-top reference, the data book represents an assembly and display of statistics and information that characterize transportation activity, and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. Each of the major transportation modes is treated in separate chapters or sections. Chapter 1 compares U.S. transportation data with data from other countries. Aggregate energy use and energy supply data for all modes are presented in Chapter 2. The highway mode, which accounts for over three-fourths of total transportation energy consumption, is dealt with in Chapter 3. Topics in this chapter include automobiles, trucks, buses, fleet vehicles, federal standards, fuel economies, and high- occupancy vehicle lane data. Household travel behavior characteristics are displayed in Chapter 4. Chapter 5 contains information on alternative fuels and alternative fuel vehicles. Chapter 6 covers the major nonhighway modes: air, water, and rail. The last chapter, Chapter 7, presents data on environmental issues relating to transportation.

  14. Elastic and transport properties in polycrystals of crackedgrains: Cross-property relations and microstructure

    Energy Technology Data Exchange (ETDEWEB)

    Berryman, J.G.

    2007-10-02

    Some arguments of Bristow (1960) concerning the effects of cracks on elastic and transport (i.e., electrical or thermal conduction) properties of cold-worked metals are reexamined. The discussion is posed in terms of a modern understanding of bounds and estimates for physical properties of polycrystals--in contrast to Bristow's approach using simple mixture theory. One type of specialized result emphasized here is the cross-property estimates and bounds that can be obtained using the methods presented. Our results ultimately agree with those of Bristow, i.e., confirming that microcracking is not likely to be the main cause of the observed elastic behavior of cold-worked metals. However, it also becomes clear that the mixture theory approach to the analysis is too simple and that crack-crack interactions are necessary for proper quantitative study of Bristow's problem.

  15. Boron transport in plants: co-ordinated regulation of transporters

    Science.gov (United States)

    Miwa, Kyoko; Fujiwara, Toru

    2010-01-01

    Background The essentiality of boron (B) for plant growth was established >85 years ago. In the last decade, it has been revealed that one of the physiological roles of B is cross-linking the pectic polysaccharide rhamnogalacturonan II in primary cell walls. Borate cross-linking of pectic networks serves both for physical strength of cell walls and for cell adhesion. On the other hand, high concentrations of B are toxic to plant growth. To avoid deficiency and toxicity problems, it is important for plants to maintain their tissue B concentrations within an optimum range by regulating transport processes. Boron transport was long believed to be a passive, unregulated process, but the identification of B transporters has suggested that plants sense and respond to the B conditions and regulate transporters to maintain B homeostasis. Scope Transporters responsible for efficient B uptake by roots, xylem loading and B distribution among leaves have been described. These transporters are required under B limitation for efficient acquisition and utilization of B. Transporters important for tolerating high B levels in the environment have also been identified, and these transporters export B from roots back to the soil. Two types of transporters are involved in these processes: NIPs (nodulin-26-like intrinsic proteins), boric acid channels, and BORs, B exporters. It is demonstrated that the expression of genes encoding these transporters is finely regulated in response to B availability in the environment to ensure tissue B homeostasis. Furthermore, plants tolerant to stress produced by low B or high B in the environment can be generated through altered expression of these transporters. Conclusions The identification of the first B transporter led to the discovery that B transport was a process mediated not only by passive diffusion but also by transporters whose activity was regulated in response to B conditions. Now it is evident that plants sense internal and external B

  16. Transportation energy conservation data book

    Energy Technology Data Exchange (ETDEWEB)

    Loebl, A. S.; Bjornstad, D. J.; Burch, D. F.; Howard, E. B.; Hull, J. F.; Madewell, D. G.; Malthouse, N. S.; Ogle, M. C.

    1976-10-01

    Statistics which characterize the major transportation modes are assembled and displayed, and data on other factors which influence the transportation sector in the nation are presented. Statistical data on energy use in the transportation sector are presented in the form of tables, graphs, and charts. The following topics are covered in six chapters: Characteristics of Transportation Modes; Energy Characteristics, including energy consumption by source and by sector and energy intensiveness; Conservation Alternatives; Government Impacts, including expenditures, regulations and research, development, and demonstration spending; Energy Supply, including domestic petroleum production, prices, and projections; and Transportation Demand, including population characteristics and economic determinants. A bibliography of data sources is provided at the end of each chapter. A more general bibliography glossary, and subject index are included at the end of the book.

  17. The ability of current statistical classifications to separate services and manufacturing

    DEFF Research Database (Denmark)

    Christensen, Jesper Lindgaard

    2013-01-01

    This paper explores the performance of current statistical classification systems in classifying firms and, in particular, their ability to distinguish between firms that provide services and firms that provide manufacturing. We find that a large share of firms, almost 20%, are not classified...... as expected based on a comparison of their statements of activities with the assigned industry codes. This result is robust to analyses on different levels of aggregation and is validated in an additional survey. It is well known from earlier literature that industry classification systems are not perfect....... This paper provides a quantification of the flaws in classifications of firms. Moreover, it is explained why the classifications of firms are imprecise. The increasing complexity of production, inertia in changes to statistical systems and the increasing integration of manufacturing products and services...

  18. Zubarev's Nonequilibrium Statistical Operator Method in the Generalized Statistics of Multiparticle Systems

    Science.gov (United States)

    Glushak, P. A.; Markiv, B. B.; Tokarchuk, M. V.

    2018-01-01

    We present a generalization of Zubarev's nonequilibrium statistical operator method based on the principle of maximum Renyi entropy. In the framework of this approach, we obtain transport equations for the basic set of parameters of the reduced description of nonequilibrium processes in a classical system of interacting particles using Liouville equations with fractional derivatives. For a classical systems of particles in a medium with a fractal structure, we obtain a non-Markovian diffusion equation with fractional spatial derivatives. For a concrete model of the frequency dependence of a memory function, we obtain generalized Kettano-type diffusion equation with the spatial and temporal fractality taken into account. We present a generalization of nonequilibrium thermofield dynamics in Zubarev's nonequilibrium statistical operator method in the framework of Renyi statistics.

  19. On Perturbation Components Correspondence between Diffusion and Transport

    Energy Technology Data Exchange (ETDEWEB)

    G. Palmiotti

    2012-11-01

    We have established a correspondence between perturbation components in diffusion and transport theory. In particular we have established the correspondence between the leakage perturbation component of the diffusion theory to that of the group self scattering in transport theory. This has been confirmed by practical applications on sodium void reactivity calculations of fast reactors. Why this is important for current investigations? Recently, there has been a renewed interest in designing fast reactors where the sodium void reactivity coefficient is minimized. In particular the ASTRID8,9 reactor concept has been optimized with this goal in mind. The correspondence on the leakage term that has been established here has a twofold implication for the design of this kind of reactors. First, this type of reactor has a radial reflector; therefore, as shown before, the sodium void reactivity coefficient calculation requires the use of transport theory. The minimization of the sodium reactivity coefficient is normally done by increasing the leakage component that has a negative sign. The correspondence established in this paper allows to directly look at this component in transport theory. The second implication is related to the uncertainty evaluation on sodium void reactivity. As it has shown before, the total sodium void reactivity effect is the result of a large compensation (opposite sign) between the scattering (called often spectral) component and the leakage one. Consequently, one has to evaluate separately the uncertainty on each separate component and then combine them statistically. If one wants to compute the cross section sensitivity coefficients of the two different components, the formulation established in this paper allows to achieve this goal by playing on the contribution to the sodium void reactivity coming from the group self scattering of the sodium cross section.

  20. Logarithmic learning for generalized classifier neural network.

    Science.gov (United States)

    Ozyildirim, Buse Melis; Avci, Mutlu

    2014-12-01

    Generalized classifier neural network is introduced as an efficient classifier among the others. Unless the initial smoothing parameter value is close to the optimal one, generalized classifier neural network suffers from convergence problem and requires quite a long time to converge. In this work, to overcome this problem, a logarithmic learning approach is proposed. The proposed method uses logarithmic cost function instead of squared error. Minimization of this cost function reduces the number of iterations used for reaching the minima. The proposed method is tested on 15 different data sets and performance of logarithmic learning generalized classifier neural network is compared with that of standard one. Thanks to operation range of radial basis function included by generalized classifier neural network, proposed logarithmic approach and its derivative has continuous values. This makes it possible to adopt the advantage of logarithmic fast convergence by the proposed learning method. Due to fast convergence ability of logarithmic cost function, training time is maximally decreased to 99.2%. In addition to decrease in training time, classification performance may also be improved till 60%. According to the test results, while the proposed method provides a solution for time requirement problem of generalized classifier neural network, it may also improve the classification accuracy. The proposed method can be considered as an efficient way for reducing the time requirement problem of generalized classifier neural network. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Pre-transport factors affecting the welfare of cattle during road transport for slaughter – a review

    Directory of Open Access Journals (Sweden)

    Veronika Šímová

    2016-01-01

    Full Text Available In terms of animal welfare, transport per se is very important in the course of the transportation process and transport duration is considered as one of the determining factors, however, the phase that precedes the actual transport is also of great importance (and often even more important as to stress induction. This pre-transport phase includes many aspects, such as on-farm handling, rearing conditions, assembly of animals, classifying, weighing, repenning in a new environment, re-grouping, mixing with unfamiliar animals, and handling at loading, which is regarded as the most significant factor affecting animal welfare. Therefore, the present work focuses on the factors that play a role during this phase. Those factors are naturally interconnected and their adverse consecutive effects on animal welfare can hardly be separated.

  2. Quantum statistical effects in the mass transport of interstitial solutes in a crystalline solid

    Science.gov (United States)

    Woo, C. H.; Wen, Haohua

    2017-09-01

    The impact of quantum statistics on the many-body dynamics of a crystalline solid at finite temperatures containing an interstitial solute atom (ISA) is investigated. The Mori-Zwanzig theory allows the many-body dynamics of the crystal to be formulated and solved analytically within a pseudo-one-particle approach using the Langevin equation with a quantum fluctuation-dissipation relation (FDR) based on the Debye model. At the same time, the many-body dynamics is also directly solved numerically via the molecular dynamics approach with a Langevin heat bath based on the quantum FDR. Both the analytical and numerical results consistently show that below the Debye temperature of the host lattice, quantum statistics significantly impacts the ISA transport properties, resulting in major departures from both the Arrhenius law of diffusion and the Einstein-Smoluchowski relation between the mobility and diffusivity. Indeed, we found that below one-third of the Debye temperature, effects of vibrations on the quantum mobility and diffusivity are both orders-of-magnitude larger and practically temperature independent. We have shown that both effects have their physical origin in the athermal lattice vibrations derived from the phonon ground state. The foregoing theory is tested in quantum molecular dynamics calculation of mobility and diffusivity of interstitial helium in bcc W. In this case, the Arrhenius law is only valid in a narrow range between ˜300 and ˜700 K. The diffusivity becomes temperature independent on the low-temperature side while increasing linearly with temperature on the high-temperature side.

  3. Transport Coefficients from Large Deviation Functions

    Directory of Open Access Journals (Sweden)

    Chloe Ya Gao

    2017-10-01

    Full Text Available We describe a method for computing transport coefficients from the direct evaluation of large deviation functions. This method is general, relying on only equilibrium fluctuations, and is statistically efficient, employing trajectory based importance sampling. Equilibrium fluctuations of molecular currents are characterized by their large deviation functions, which are scaled cumulant generating functions analogous to the free energies. A diffusion Monte Carlo algorithm is used to evaluate the large deviation functions, from which arbitrary transport coefficients are derivable. We find significant statistical improvement over traditional Green–Kubo based calculations. The systematic and statistical errors of this method are analyzed in the context of specific transport coefficient calculations, including the shear viscosity, interfacial friction coefficient, and thermal conductivity.

  4. Transport Coefficients from Large Deviation Functions

    Science.gov (United States)

    Gao, Chloe; Limmer, David

    2017-10-01

    We describe a method for computing transport coefficients from the direct evaluation of large deviation function. This method is general, relying on only equilibrium fluctuations, and is statistically efficient, employing trajectory based importance sampling. Equilibrium fluctuations of molecular currents are characterized by their large deviation functions, which is a scaled cumulant generating function analogous to the free energy. A diffusion Monte Carlo algorithm is used to evaluate the large deviation functions, from which arbitrary transport coefficients are derivable. We find significant statistical improvement over traditional Green-Kubo based calculations. The systematic and statistical errors of this method are analyzed in the context of specific transport coefficient calculations, including the shear viscosity, interfacial friction coefficient, and thermal conductivity.

  5. DECISION TREE CLASSIFIERS FOR STAR/GALAXY SEPARATION

    International Nuclear Information System (INIS)

    Vasconcellos, E. C.; Ruiz, R. S. R.; De Carvalho, R. R.; Capelato, H. V.; Gal, R. R.; LaBarbera, F. L.; Frago Campos Velho, H.; Trevisan, M.

    2011-01-01

    We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: 14 ≤ r ≤ 21 (85.2%) and r ≥ 19 (82.1%). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT, and Ball et al. We find that our FT classifier is comparable to or better in completeness over the full magnitude range 15 ≤ r ≤ 21, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes (r > 19), our classifier is the only one that maintains high completeness (>80%) while simultaneously achieving low contamination (∼2.5%). We also examine the SDSS parametric classifier (psfMag - modelMag) to see if the dividing line between stars and galaxies can be adjusted to improve the classifier. We find that currently stars in close pairs are often misclassified as galaxies, and suggest a new cut to improve the classifier. Finally, we apply our FT classifier to separate stars from galaxies in the full set of 69,545,326 SDSS photometric objects in the magnitude range 14 ≤ r ≤ 21.

  6. Quantum formalism for classical statistics

    Science.gov (United States)

    Wetterich, C.

    2018-06-01

    In static classical statistical systems the problem of information transport from a boundary to the bulk finds a simple description in terms of wave functions or density matrices. While the transfer matrix formalism is a type of Heisenberg picture for this problem, we develop here the associated Schrödinger picture that keeps track of the local probabilistic information. The transport of the probabilistic information between neighboring hypersurfaces obeys a linear evolution equation, and therefore the superposition principle for the possible solutions. Operators are associated to local observables, with rules for the computation of expectation values similar to quantum mechanics. We discuss how non-commutativity naturally arises in this setting. Also other features characteristic of quantum mechanics, such as complex structure, change of basis or symmetry transformations, can be found in classical statistics once formulated in terms of wave functions or density matrices. We construct for every quantum system an equivalent classical statistical system, such that time in quantum mechanics corresponds to the location of hypersurfaces in the classical probabilistic ensemble. For suitable choices of local observables in the classical statistical system one can, in principle, compute all expectation values and correlations of observables in the quantum system from the local probabilistic information of the associated classical statistical system. Realizing a static memory material as a quantum simulator for a given quantum system is not a matter of principle, but rather of practical simplicity.

  7. Natural gas encasement for highway crossings.

    Science.gov (United States)

    2015-03-01

    The University Transportation Center for Alabama researchers examined the Alabama Department of : Transportations current policy regarding the encasement of natural gas and hazardous liquid pipelines at roadway : crossings. The group collected inf...

  8. Cross-field blob transport in tokamak scrape-off-layer plasmas

    International Nuclear Information System (INIS)

    D'Ippolito, D.A.; Myra, J.R.; Krasheninnikov, S.I.

    2002-01-01

    Recent measurements show that nondiffusive, intermittent transport of particles can play a major role in the scrape-off-layer (SOL) of fusion experiments. A possible mechanism for fast convective plasma transport is related to the plasma filaments or 'blobs' observed in the SOL with fast cameras and probes. In this paper, physical arguments suggesting the importance of blob transport [S. I. Krasheninnikov, Phys. Lett. A 283, 368 (2001)] have been extended by calculations using a three-field fluid model, treating the blobs as coherent propagating structures. The properties of density, temperature and vorticity blobs, and methods of averaging over ensembles of blobs to get the average SOL profiles, are illustrated. The role of ionization of background neutrals in sustaining the density blob transport is also discussed. Many qualitative features of the experiments, such as relatively flat density profiles and transport coefficients increasing toward the wall, are shown to emerge naturally from the blob transport paradigm

  9. Membrane porters of ATP-binding cassette transport systems are polyphyletic.

    Science.gov (United States)

    Wang, Bin; Dukarevich, Maxim; Sun, Eric I; Yen, Ming Ren; Saier, Milton H

    2009-09-01

    The ATP-binding cassette (ABC) superfamily consists of both importers and exporters. These transporters have, by tradition, been classified according to the ATP hydrolyzing constituents, which are monophyletic. The evolutionary origins of the transmembrane porter proteins/domains are not known. Using five distinct computer programs, we here provide convincing statistical data suggesting that the transmembrane domains of ABC exporters are polyphyletic, having arisen at least three times independently. ABC1 porters arose by intragenic triplication of a primordial two-transmembrane segment (TMS)-encoding genetic element, yielding six TMS proteins. ABC2 porters arose by intragenic duplication of a dissimilar primordial three-TMS-encoding genetic element, yielding a distinctive protein family, nonhomologous to the ABC1 proteins. ABC3 porters arose by duplication of a primordial four-TMS-encoding genetic element, yielding either eight- or 10-TMS proteins. We assign each of 48 of the 50 currently recognized families of ABC exporters to one of the three evolutionarily distinct ABC types. Currently available high-resolution structural data for ABC porters are fully consistent with our findings. These results provide guides for future structural and mechanistic studies of these important transport systems.

  10. SVM Classifier – a comprehensive java interface for support vector machine classification of microarray data

    Science.gov (United States)

    Pirooznia, Mehdi; Deng, Youping

    2006-01-01

    Motivation Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction. Results The GUI provides user-friendly access to state-of-the-art SVM methods embodied in the LIBSVM implementation of Support Vector Machine. We implemented the java interface using standard swing libraries. We used a sample data from a breast cancer study for testing classification accuracy. We achieved 100% accuracy in classification among the BRCA1–BRCA2 samples with RBF kernel of SVM. Conclusion We have developed a java GUI application that allows SVM users to perform SVM training, classification and prediction. We have demonstrated that support vector machines can accurately classify genes into functional categories based upon expression data from DNA microarray hybridization experiments. Among the different kernel functions that we examined, the SVM that uses a radial basis kernel function provides the best performance. The SVM Classifier is available at . PMID:17217518

  11. Sediment transport patterns in the San Francisco Bay Coastal System from cross-validation of bedform asymmetry and modeled residual flux

    Science.gov (United States)

    Barnard, Patrick L.; Erikson, Li H.; Elias, Edwin P.L.; Dartnell, Peter; Barnard, P.L.; Jaffee, B.E.; Schoellhamer, D.H.

    2013-01-01

    The morphology of ~ 45,000 bedforms from 13 multibeam bathymetry surveys was used as a proxy for identifying net bedload sediment transport directions and pathways throughout the San Francisco Bay estuary and adjacent outer coast. The spatially-averaged shape asymmetry of the bedforms reveals distinct pathways of ebb and flood transport. Additionally, the region-wide, ebb-oriented asymmetry of 5% suggests net seaward-directed transport within the estuarine-coastal system, with significant seaward asymmetry at the mouth of San Francisco Bay (11%), through the northern reaches of the Bay (7–8%), and among the largest bedforms (21% for λ > 50 m). This general indication for the net transport of sand to the open coast strongly suggests that anthropogenic removal of sediment from the estuary, particularly along clearly defined seaward transport pathways, will limit the supply of sand to chronically eroding, open-coast beaches. The bedform asymmetry measurements significantly agree (up to ~ 76%) with modeled annual residual transport directions derived from a hydrodynamically-calibrated numerical model, and the orientation of adjacent, flow-sculpted seafloor features such as mega-flute structures, providing a comprehensive validation of the technique. The methods described in this paper to determine well-defined, cross-validated sediment transport pathways can be applied to estuarine-coastal systems globally where bedforms are present. The results can inform and improve regional sediment management practices to more efficiently utilize often limited sediment resources and mitigate current and future sediment supply-related impacts.

  12. Statistical description of turbulent transport for flux driven toroidal plasmas

    Science.gov (United States)

    Anderson, J.; Imadera, K.; Kishimoto, Y.; Li, J. Q.; Nordman, H.

    2017-06-01

    A novel methodology to analyze non-Gaussian probability distribution functions (PDFs) of intermittent turbulent transport in global full-f gyrokinetic simulations is presented. In this work, the auto-regressive integrated moving average (ARIMA) model is applied to time series data of intermittent turbulent heat transport to separate noise and oscillatory trends, allowing for the extraction of non-Gaussian features of the PDFs. It was shown that non-Gaussian tails of the PDFs from first principles based gyrokinetic simulations agree with an analytical estimation based on a two fluid model.

  13. Metropolitan transportation management center concepts of operation : a cross-cutting study : improving transportation network efficiency

    Science.gov (United States)

    1999-10-01

    The implementor and operator of a regional transportation management center (TMC) face a challenging task. Operators of TMCsthe primary point of coordination for managing transportation resourcestypically control millions of dollars of intellig...

  14. 32 CFR 2400.28 - Dissemination of classified information.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Dissemination of classified information. 2400.28... SECURITY PROGRAM Safeguarding § 2400.28 Dissemination of classified information. Heads of OSTP offices... originating official may prescribe specific restrictions on dissemination of classified information when...

  15. Pain and Joy of a Panel Survey on Transport Studies

    Energy Technology Data Exchange (ETDEWEB)

    Comendador Arquero, María Eugenia López-Lambas

    2016-07-01

    Over ten years ago, it was established that the most frequent reason that motivates a panel survey on transport studies is the evaluation of a change in the transportation system, or a specific transportation-planning project, especially when the project involves novel elements. From a statistical viewpoint, a panel survey has the definite advantage to offer more accurate estimatesof changes than cross-sectional surveys for the same sample size. Observing travel patterns of individuals and households overseveral consecutive days, has offered insights into activity scheduling and travel planning. Variability in travel patterns has important policy implications as well, but how much effort is worth to design a panel survey? To evaluate the effects of the transport policies introduced in Madrid during the last five years, a ‘short-long’ panel survey wasbuilt, based on a sample of a Madrid-worker subpopulation most affected by those recent changes in transport policy. The paper describes both the design and construction of the panel based on GPS technology, and presents some results based on an analysis of its two waves; for example, it registered an increment of public transport use and walking trips in 10%. The panel overcomes the known attrition problem thanks to providing incentives, maintaining contact, using the same interviewer for the same respondents, and conducting face-to-face interviews. (Author)

  16. Detection of serum antibodies cross-reacting with Mycobacterium avium subspecies paratuberculosis and beta-cell antigen zinc transporter 8 homologous peptides in patients with high-risk proliferative diabetic retinopathy.

    Science.gov (United States)

    Pinna, Antonio; Masala, Speranza; Blasetti, Francesco; Maiore, Irene; Cossu, Davide; Paccagnini, Daniela; Mameli, Giuseppe; Sechi, Leonardo A

    2014-01-01

    MAP3865c, a Mycobacterium avium subspecies paratuberculosis (MAP) cell membrane protein, has a relevant sequence homology with zinc transporter 8 (ZnT8), a beta-cell membrane protein involved in Zn++ transportation. Recently, antibodies recognizing MAP3865c epitopes have been shown to cross-react with ZnT8 in type 1 diabetes patients. The purpose of this study was to detect antibodies against MAP3865c peptides in patients with high-risk proliferative diabetic retinopathy and speculate on whether they may somehow be involved in the pathogenesis of this severe retinal disorder. Blood samples were obtained from 62 type 1 and 80 type 2 diabetes patients with high-risk proliferative diabetic retinopathy and 81 healthy controls. Antibodies against 6 highly immunogenic MAP3865c peptides were detected by indirect ELISA. Type 1 diabetes patients had significantly higher rates of positive antibodies than controls. Conversely, no statistically significant differences were found between type 2 diabetes patients and controls. After categorization of type 1 diabetes patients into two groups, one with positive, the other with negative antibodies, we found that they had similar mean visual acuity (∼ 0.6) and identical rates of vitreous hemorrhage (28.6%). Conversely, Hashimoto's thyroiditis prevalence was 4/13 (30.7%) in the positive antibody group and 1/49 (2%) in the negative antibody group, a statistically significant difference (P = 0.016). This study confirmed that type 1 diabetes patients have significantly higher rates of positive antibodies against MAP/ZnT8 peptides, but failed to find a correlation between the presence of these antibodies and the severity degree of high-risk proliferative diabetic retinopathy. The significantly higher prevalence of Hashimoto's disease among type 1 diabetes patients with positive antibodies might suggest a possible common environmental trigger for these conditions.

  17. Influence of Signal and Noise on Statistical Fluctuation of Single-Mode Laser System

    International Nuclear Information System (INIS)

    Xu Dahai; Cheng Qinghua; Cao Li; Wu Dajin

    2006-01-01

    On the basis of calculating the steady-state mean normalized intensity fluctuation of a signal-mode laser system driven by both colored pump noise with signal modulation and the quantum noise with cross-correlation between its real and imaginary parts, we analyze the influence of modulation signal, noise, and its correlation form on the statistical fluctuation of the laser system. We have found that when the amplitude of modulation signal weakens and its frequency quickens, the statistical fluctuation will reduce rapidly. The statistical fluctuation of the laser system can be restrained by reducing the intensity of pump noise and quantum noise. Moreover, with prolonging of colored cross-correlation time, the statistical fluctuation of laser system experiences a repeated changing process, that is, from decreasing to augmenting, then to decreasing, and finally to augmenting again. With the decreasing of the value of cross-correlation coefficient, the statistical fluctuation will decrease too. When the cross-correlation form between the real part and imaginary part of quantum noise is zero correlation, the statistical fluctuation of laser system has a minimum. Compared with the influence of intensity of pump noise, the influence of intensity of quantum noise on the statistical fluctuation is smaller.

  18. AUS, Neutron Transport and Gamma Transport System for Fission Reactors and Fusion Reactors

    International Nuclear Information System (INIS)

    1990-01-01

    1 - Description of program or function: AUS is a neutronics code system which may be used for calculations of a wide range of fission reactors, fusion blankets and other neutron applications. The present version, AUS98, has a nuclear cross section library based on ENDF/B-VI and includes modules which provide for reactor lattice calculations, one-dimensional transport calculations, multi-dimensional diffusion calculations, cell and whole reactor burnup calculations, and flexible editing of results. Calculations of multi-region resonance shielding, coupled neutron and photon transport, energy deposition, fission product inventory and neutron diffusion are combined within the one code system. The major changes from the previous release, AUS87, are the inclusion of a cross-section library based on ENDF/B-VI, the addition of the POW3D multi-dimensional diffusion module, the addition of the MICBURN module for controlling whole reactor burnup calculations, and changes to the system as a consequence of moving from IBM mainframe computers to UNIX workstations. 2 - Method of solution: AUS98 is a modular system in which the modules are complete programs linked by a path given in the input stream. A simple path is simply a sequence of modules, but the path is actually pre-processed and compiled using the Fortran 77 compiler. This provides for complex module linking if required. Some of the modules included in AUS98 are: MIRANDA Cross-section generation in a multi-region resonance subgroup calculation and preliminary group condensation. ANAUSN One-dimensional discrete ordinates calculation. ICPP Isotropic collision probability calculation in one dimension and for rod clusters. POW3D Multi-dimensional neutron diffusion calculation including feedback-free kinetics. AUSIDD One-dimensional diffusion calculation. EDITAR Reaction-rate editing and group collapsing following a transport calculation. CHAR Lattice and global burnup calculation. MICBURN Control of global burnup

  19. Transportation energy data book: Edition 13

    Energy Technology Data Exchange (ETDEWEB)

    Davis, S.C.; Strang, S.G.

    1993-03-01

    The Transportation Energy Data Book: Edition 13 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the Office of Transportation Technologies in the Department of Energy (DOE). Designed for use as a desk-top reference, the data book represents an assembly and display of statistics and information that characterize transportation activity, and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. Each of the major transportation modes -- highway, air, water, rail, pipeline -- is treated in separate chapters or sections. Chapter 1 compares US transportation data with data from seven other countries. Aggregate energy use and energy supply data for all modes are presented in Chapter 2. The highway mode, which accounts for over three-fourths of total transportation energy consumption, is dealt with in Chapter 3. Topics in this chapter include automobiles, trucks, buses, fleet automobiles, federal standards, fuel economies, and vehicle emission data. Household travel behavior characteristics are displayed in Chapter 4. Chapter 5 contains information on alternative fuels and alternatively-fueled vehicles. The last chapter, Chapter 6, covers each of the nonhighway modes: air, water, pipeline, and rail, respectively.

  20. Transportation energy data book: Edition 13

    Energy Technology Data Exchange (ETDEWEB)

    Davis, S.C.; Strang, S.G.

    1993-03-01

    The Transportation Energy Data Book: Edition 13 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the Office of Transportation Technologies in the Department of Energy (DOE). Designed for use as a desk-top reference, the data book represents an assembly and display of statistics and information that characterize transportation activity, and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. Each of the major transportation modes - highway, air, water, rail, pipeline - is treated in separate chapters or sections. Chapter 1 compares US transportation data with data from seven other countries. Aggregate energy use and energy supply data for all modes are presented in Chapter 2. The highway mode, which accounts for over three-fourths of total transportation energy consumption, is dealt with in Chapter 3. Topics in this chapter include automobiles, trucks, buses, fleet automobiles, federal standards, fuel economies, and vehicle emission data. Household travel behavior characteristics are displayed in Chapter 4. Chapter 5 contains information on alternative fuels and alternatively-fueled vehicles. The last chapter, Chapter 6, covers each of the nonhighway modes: air, water, pipeline, and rail, respectively.