WorldWideScience

Sample records for factor analysis model

  1. Human Modeling for Ground Processing Human Factors Engineering Analysis

    Science.gov (United States)

    Stambolian, Damon B.; Lawrence, Brad A.; Stelges, Katrine S.; Steady, Marie-Jeanne O.; Ridgwell, Lora C.; Mills, Robert E.; Henderson, Gena; Tran, Donald; Barth, Tim

    2011-01-01

    There have been many advancements and accomplishments over the last few years using human modeling for human factors engineering analysis for design of spacecraft. The key methods used for this are motion capture and computer generated human models. The focus of this paper is to explain the human modeling currently used at Kennedy Space Center (KSC), and to explain the future plans for human modeling for future spacecraft designs

  2. Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

    Directory of Open Access Journals (Sweden)

    Hong Xue

    2018-01-01

    Full Text Available High capital cost is a significant hindrance to the promotion of prefabrication. In order to optimize cost management and reduce capital cost, this study aims to explore the latent factors and factor analysis evaluation model. Semi-structured interviews were conducted to explore potential variables and then questionnaire survey was employed to collect professionals’ views on their effects. After data collection, exploratory factor analysis was adopted to explore the latent factors. Seven latent factors were identified, including “Management Index”, “Construction Dissipation Index”, “Productivity Index”, “Design Efficiency Index”, “Transport Dissipation Index”, “Material increment Index” and “Depreciation amortization Index”. With these latent factors, a factor analysis evaluation model (FAEM, divided into factor analysis model (FAM and comprehensive evaluation model (CEM, was established. The FAM was used to explore the effect of observed variables on the high capital cost of prefabrication, while the CEM was used to evaluate comprehensive cost management level on prefabrication projects. Case studies were conducted to verify the models. The results revealed that collaborative management had a positive effect on capital cost of prefabrication. Material increment costs and labor costs had significant impacts on production cost. This study demonstrated the potential of on-site management and standardization design to reduce capital cost. Hence, collaborative management is necessary for cost management of prefabrication. Innovation and detailed design were needed to improve cost performance. The new form of precast component factories can be explored to reduce transportation cost. Meanwhile, targeted strategies can be adopted for different prefabrication projects. The findings optimized the capital cost and improved the cost performance through providing an evaluation and optimization model, which helps managers to

  3. Container Throughput Forecasting Using Dynamic Factor Analysis and ARIMAX Model

    Directory of Open Access Journals (Sweden)

    Marko Intihar

    2017-11-01

    Full Text Available The paper examines the impact of integration of macroeconomic indicators on the accuracy of container throughput time series forecasting model. For this purpose, a Dynamic factor analysis and AutoRegressive Integrated Moving-Average model with eXogenous inputs (ARIMAX are used. Both methodologies are integrated into a novel four-stage heuristic procedure. Firstly, dynamic factors are extracted from external macroeconomic indicators influencing the observed throughput. Secondly, the family of ARIMAX models of different orders is generated based on the derived factors. In the third stage, the diagnostic and goodness-of-fit testing is applied, which includes statistical criteria such as fit performance, information criteria, and parsimony. Finally, the best model is heuristically selected and tested on the real data of the Port of Koper. The results show that by applying macroeconomic indicators into the forecasting model, more accurate future throughput forecasts can be achieved. The model is also used to produce future forecasts for the next four years indicating a more oscillatory behaviour in (2018-2020. Hence, care must be taken concerning any bigger investment decisions initiated from the management side. It is believed that the proposed model might be a useful reinforcement of the existing forecasting module in the observed port.

  4. Replica Analysis for Portfolio Optimization with Single-Factor Model

    Science.gov (United States)

    Shinzato, Takashi

    2017-06-01

    In this paper, we use replica analysis to investigate the influence of correlation among the return rates of assets on the solution of the portfolio optimization problem. We consider the behavior of an optimal solution for the case where the return rate is described with a single-factor model and compare the findings obtained from our proposed methods with correlated return rates with those obtained with independent return rates. We then analytically assess the increase in the investment risk when correlation is included. Furthermore, we also compare our approach with analytical procedures for minimizing the investment risk from operations research.

  5. Dimensional Model for Estimating Factors influencing Childhood Obesity: Path Analysis Based Modeling

    Directory of Open Access Journals (Sweden)

    Maryam Kheirollahpour

    2014-01-01

    Full Text Available The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA was applied to reveal the hidden (secondary effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model.

  6. Factor Analysis of Drawings: Application to College Student Models of the Greenhouse Effect

    Science.gov (United States)

    Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

    2015-01-01

    Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance,…

  7. Foundations of factor analysis

    CERN Document Server

    Mulaik, Stanley A

    2009-01-01

    Introduction Factor Analysis and Structural Theories Brief History of Factor Analysis as a Linear Model Example of Factor AnalysisMathematical Foundations for Factor Analysis Introduction Scalar AlgebraVectorsMatrix AlgebraDeterminants Treatment of Variables as Vectors Maxima and Minima of FunctionsComposite Variables and Linear Transformations Introduction Composite Variables Unweighted Composite VariablesDifferentially Weighted Composites Matrix EquationsMulti

  8. Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

    Science.gov (United States)

    Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

    2017-01-01

    The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

  9. Factor analysis

    CERN Document Server

    Gorsuch, Richard L

    2013-01-01

    Comprehensive and comprehensible, this classic covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and sufficient discussion of applications for effective use. This includes not only theory but also the empirical evaluations of the importance of mathematical distinctions for applied scientific analysis.

  10. DETERMINANTS OF SOVEREIGN RATING: FACTOR BASED ORDERED PROBIT MODELS FOR PANEL DATA ANALYSIS MODELING FRAMEWORK

    Directory of Open Access Journals (Sweden)

    Dilek Teker

    2013-01-01

    Full Text Available The aim of this research is to compose a new rating methodology and provide credit notches to 23 countries which of 13 are developed and 10 are emerging. There are various literature that explains the determinants of credit ratings. Following the literature, we select 11 variables for our model which of 5 are eliminated by the factor analysis. We use specific dummies to investigate the structural breaks in time and cross section such as pre crises, post crises, BRIC membership, EU membership, OPEC membership, shipbuilder country and platinum reserved country. Then we run an ordered probit model and give credit notches to the countries. We use FITCH ratings as benchmark. Thus, at the end we compare the notches of FITCH with the ones we derive out of our estimated model.

  11. Critical Factors Analysis for Offshore Software Development Success by Structural Equation Modeling

    Science.gov (United States)

    Wada, Yoshihisa; Tsuji, Hiroshi

    In order to analyze the success/failure factors in offshore software development service by the structural equation modeling, this paper proposes to follow two approaches together; domain knowledge based heuristic analysis and factor analysis based rational analysis. The former works for generating and verifying of hypothesis to find factors and causalities. The latter works for verifying factors introduced by theory to build the model without heuristics. Following the proposed combined approaches for the responses from skilled project managers of the questionnaire, this paper found that the vendor property has high causality for the success compared to software property and project property.

  12. Verification of the model of predisposition in triathlon – structural model of confirmative factor analysis

    Directory of Open Access Journals (Sweden)

    Lenka Kovářová

    2012-09-01

    Full Text Available BACKGROUND: The triathlon is a combination of three different types of sport – swimming, cycling, and running. Each of these requires different top level predispositions and complex approach to talent selection is a rather difficult process. Attempts to identify assumptions in the triathlon have so far been specific and focused only on some groups of predispositions (physiology, motor tests, and psychology. The latest studies missed the structural approach and were based on determinants of sport performance, theory of sports training and expert assessment. OBJECTIVE: The aim of our study was to verify the model of predisposition in the short triathlon for talent assessment of young male athletes age 17–20 years. METHODS: The research sample consisted of 55 top level triathletes – men, who were included in the Government supported sports talent programme in the Czech Republic at the age of 17–20 years. We used a confirmative factor analysis (FA and Path diagram to verify the model, which allow us to explain mutual relationships among observed variables. For statistical data processing we used a structure equating modeling (SEM by software Lisrel L88. RESULTS: The study confirms best structural model for talent selection in triathlon at the age of 17–20 years old men, which composed seventeen indicators (tests and explained 91% of all cross-correlations (Goodness of Fit Index /GFI/ 0.91, Root Mean Square Residual /RMSR/ 0.13. Tests for predispositions in triathlons were grouped into five items, three motor predispositions (swimming, cycling and running skills, aerobic and psychological predispositions. Aerobic predispositions showed the highest importance to the assumptions to the general factor (1.00; 0. Running predispositions were measured as a very significant factor (–0.85; 0.28 which confirms importance of this critical stage of the race. Lower factor weight showed clusters of swimming (–0.61; 0.63 and cycling (0.53; 0

  13. Dynamic factor analysis in the frequency domain: causal modeling of multivariate psychophysiological time series

    NARCIS (Netherlands)

    Molenaar, P.C.M.

    1987-01-01

    Outlines a frequency domain analysis of the dynamic factor model and proposes a solution to the problem of constructing a causal filter of lagged factor loadings. The method is illustrated with applications to simulated and real multivariate time series. The latter applications involve topographic

  14. A receptor model for urban aerosols based on oblique factor analysis

    DEFF Research Database (Denmark)

    Keiding, Kristian; Sørensen, Morten S.; Pind, Niels

    1987-01-01

    A procedure is outlined for the construction of receptor models of urban aerosols, based on factor analysis. The advantage of the procedure is that the covariation of source impacts is included in the construction of the models. The results are compared with results obtained by other receptor......-modelling procedures. It was found that procedures based on correlating sources were physically sound as well as in mutual agreement. Procedures based on non-correlating sources were found to generate physically obscure models....

  15. Bayesian Sensitivity Analysis of a Nonlinear Dynamic Factor Analysis Model with Nonparametric Prior and Possible Nonignorable Missingness.

    Science.gov (United States)

    Tang, Niansheng; Chow, Sy-Miin; Ibrahim, Joseph G; Zhu, Hongtu

    2017-12-01

    Many psychological concepts are unobserved and usually represented as latent factors apprehended through multiple observed indicators. When multiple-subject multivariate time series data are available, dynamic factor analysis models with random effects offer one way of modeling patterns of within- and between-person variations by combining factor analysis and time series analysis at the factor level. Using the Dirichlet process (DP) as a nonparametric prior for individual-specific time series parameters further allows the distributional forms of these parameters to deviate from commonly imposed (e.g., normal or other symmetric) functional forms, arising as a result of these parameters' restricted ranges. Given the complexity of such models, a thorough sensitivity analysis is critical but computationally prohibitive. We propose a Bayesian local influence method that allows for simultaneous sensitivity analysis of multiple modeling components within a single fitting of the model of choice. Five illustrations and an empirical example are provided to demonstrate the utility of the proposed approach in facilitating the detection of outlying cases and common sources of misspecification in dynamic factor analysis models, as well as identification of modeling components that are sensitive to changes in the DP prior specification.

  16. Analysis on trust influencing factors and trust model from multiple perspectives of online Auction

    Science.gov (United States)

    Yu, Wang

    2017-10-01

    Current reputation models lack the research on online auction trading completely so they cannot entirely reflect the reputation status of users and may cause problems on operability. To evaluate the user trust in online auction correctly, a trust computing model based on multiple influencing factors is established. It aims at overcoming the efficiency of current trust computing methods and the limitations of traditional theoretical trust models. The improved model comprehensively considers the trust degree evaluation factors of three types of participants according to different participation modes of online auctioneers, to improve the accuracy, effectiveness and robustness of the trust degree. The experiments test the efficiency and the performance of our model under different scale of malicious user, under environment like eBay and Sporas model. The experimental results analysis show the model proposed in this paper makes up the deficiency of existing model and it also has better feasibility.

  17. Factor Analysis of Drawings: Application to college student models of the greenhouse effect

    Science.gov (United States)

    Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

    2015-09-01

    Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance, suggesting that 4 archetype models of the greenhouse effect dominate thinking within this population. Factor scores, indicating the extent to which each student's drawing aligned with representative models, were compared to performance on conceptual understanding and attitudes measures, demographics, and non-cognitive features of drawings. Student drawings were also compared to drawings made by scientists to ascertain the extent to which models reflect more sophisticated and accurate models. Results indicate that student and scientist drawings share some similarities, most notably the presence of some features of the most sophisticated non-scientific model held among the study population. Prior knowledge, prior attitudes, gender, and non-cognitive components are also predictive of an individual student's model. This work presents a new technique for analyzing drawings, with general implications for the use of drawings in investigating student conceptions.

  18. Modeling Indicator Systems for Evaluating Environmental Sustainable Development Based on Factor Analysis

    Institute of Scientific and Technical Information of China (English)

    WU Hao; CHEN Xiaoling; HE Ying; HE Xiaorong; CAI Xiaobin; XU Keyan

    2006-01-01

    Indicator systems of environmental sustainable development in the Poyang Lake Basin are established from 51 elementary indexes by factor analysis, which is composed of four steps such as the factor model, the parameter estimation, the factor rotation and the factor score. Under the condition that the cumulative proportion is greater than 85%, 5 explicit factors of environmental sustainable development as well as its factor score by region are carried out. The result indicates some impact factors to the basin environmental in descending sort order are volume of water, volume of waste gas discharge, volume of solid wastes, the degree to comprehensive utilization of waste gas, waste water and solid wastes, the emission volume of waste gas, waste water and solid wastes. It is helpful and important to provide decision support for constituting sustainable development strategies and evaluate the sustainable development status of each city.

  19. Decision making model design for antivirus software selection using Factor Analysis and Analytical Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Nurhayati Ai

    2018-01-01

    Full Text Available Virus spread increase significantly through the internet in 2017. One of the protection method is using antivirus software. The wide variety of antivirus software in the market tends to creating confusion among consumer. Selecting the right antivirus according to their needs has become difficult. This is the reason we conduct our research. We formulate a decision making model for antivirus software consumer. The model is constructed by using factor analysis and AHP method. First we spread questionnaires to consumer, then from those questionnaires we identified 16 variables that needs to be considered on selecting antivirus software. This 16 variables then divided into 5 factors by using factor analysis method in SPSS software. These five factors are security, performance, internal, time and capacity. To rank those factors we spread questionnaires to 6 IT expert then the data is analyzed using AHP method. The result is that performance factors gained the highest rank from all of the other factors. Thus, consumer can select antivirus software by judging the variables in the performance factors. Those variables are software loading speed, user friendly, no excessive memory use, thorough scanning, and scanning virus fast and accurately.

  20. Decision making model design for antivirus software selection using Factor Analysis and Analytical Hierarchy Process

    OpenAIRE

    Nurhayati Ai; Gautama Aditya; Naseer Muchammad

    2018-01-01

    Virus spread increase significantly through the internet in 2017. One of the protection method is using antivirus software. The wide variety of antivirus software in the market tends to creating confusion among consumer. Selecting the right antivirus according to their needs has become difficult. This is the reason we conduct our research. We formulate a decision making model for antivirus software consumer. The model is constructed by using factor analysis and AHP method. First we spread que...

  1. Assessing Heterogeneity for Factor Analysis Model with Continuous and Ordinal Outcomes

    Directory of Open Access Journals (Sweden)

    Ye-Mao Xia

    2016-01-01

    Full Text Available Factor analysis models with continuous and ordinal responses are a useful tool for assessing relations between the latent variables and mixed observed responses. These models have been successfully applied to many different fields, including behavioral, educational, and social-psychological sciences. However, within the Bayesian analysis framework, most developments are constrained within parametric families, of which the particular distributions are specified for the parameters of interest. This leads to difficulty in dealing with outliers and/or distribution deviations. In this paper, we propose a Bayesian semiparametric modeling for factor analysis model with continuous and ordinal variables. A truncated stick-breaking prior is used to model the distributions of the intercept and/or covariance structural parameters. Bayesian posterior analysis is carried out through the simulation-based method. Blocked Gibbs sampler is implemented to draw observations from the complicated posterior. For model selection, the logarithm of pseudomarginal likelihood is developed to compare the competing models. Empirical results are presented to illustrate the application of the methodology.

  2. Model endophenotype for bipolar disorder: Qualitative Analysis, etiological factors, and research areas

    Directory of Open Access Journals (Sweden)

    Naraiana de Oliveira Tavares

    2014-12-01

    Full Text Available The aim of this study is to present an updated view of the writings on the endophenotype model for bipolar disorder using analytical methodologies. A review and analysis of networks was performed through descriptors and keywords that characterize the composition of the endophenotype model as a model of health. Information was collected from between 1992 and 2014, and the main thematic areas covered in the articles were identified. We discuss the results and question their cohesion, emphasizing the need to strengthen and identify the points of connection between etiological factors and characteristics that make up the model of endophenotypes for bipolar disorder.

  3. Confirmatory Factor Analysis of the Structure of Statistics Anxiety Measure: An Examination of Four Alternative Models

    Directory of Open Access Journals (Sweden)

    Hossein Bevrani, PhD

    2011-09-01

    Full Text Available Objective: The aim of this study is to explore the confirmatory factor analysis results of the Persian adaptation of Statistics Anxiety Measure (SAM, proposed by Earp.Method: The validity and reliability assessments of the scale were performed on 298 college students chosen randomly from Tabriz University in Iran. Confirmatory factor analysis (CFA was carried out to determine the factor structures of the Persian adaptation of SAM.Results: As expected, the second order model provided a better fit to the data than the three alternative models. Conclusions: Hence, SAM provides an equally valid measure for use among college students. The study both expands and adds support to the existing body of math anxiety literature.

  4. An integrated factor analysis model for product eco-design based on full life cycle assessment

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Z.; Xiao, T.; Li, D.

    2016-07-01

    Among the methods of comprehensive analysis for a product or an enterprise, there exist defects and deficiencies in traditional standard cost analyses and life cycle assessment methods. For example, some methods only emphasize one dimension (such as economic or environmental factors) while neglecting other relevant dimensions. This paper builds a factor analysis model of resource value flow, based on full life cycle assessment and eco-design theory, in order to expose the relevant internal logic between these two factors. The model considers the efficient multiplication of resources, economic efficiency, and environmental efficiency as its core objectives. The model studies the status of resource value flow during the entire life cycle of a product, and gives an in-depth analysis on the mutual logical relationship of product performance, value, resource consumption, and environmental load to reveal the symptoms and potentials in different dimensions. This provides comprehensive, accurate and timely decision-making information for enterprise managers regarding product eco-design, as well as production and management activities. To conclude, it verifies the availability of this evaluation and analysis model using a Chinese SUV manufacturer as an example. (Author)

  5. Structural equation modeling analysis of factors influencing architects' trust in project design teams

    Institute of Scientific and Technical Information of China (English)

    DING Zhi-kun; NG Fung-fai; WANG Jia-yuan

    2009-01-01

    This paper describes a structural equation modeling (SEM) analysis of factors influencing architects' trust in project design teams. We undertook a survey of architects, during which we distributed 193 questionnaires in 29 A-level architectural We used Amos 6.0 for SEM to identify significant personal construct based factors affecting interpersonal trust. The results show that only social interaction between architects significantly affects their interpersonal trust. The explained variance of trust is not very high in the model. Therefore, future research should add more factors into the current model. The practical implication is that team managers should promote the social interactions between team members such that the interpersonal trust level between team members can be improved.

  6. Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

    Science.gov (United States)

    Clark, D Angus; Bowles, Ryan P

    2018-04-23

    In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.

  7. Analysis of automotive rolling lobe air spring under alternative factors with finite element model

    International Nuclear Information System (INIS)

    Wong, Pak Kin; Xie, Zhengchao; Zhao, Jing; Xu, Tao; He, Feng

    2014-01-01

    Air springs are widely used in automotive suspensions for their superior performance in terms of low friction motion, adjustable load carrying capacity and user-friendly ride height control. However, it has posed great difficulties in constructing an accurate model as well as the analysis of the influence of alternative factors, such as cord angle, cord diameter and initial pressure. In this paper, a numerical model of the rolling lobe air spring (RLAS) is built by using finite element method and compared with an existing analytical model. An experiment with respect to the vertical stiffness of the RLAS is carried out to validate the accuracy of the proposed model. Evaluation result reveals that the existing analytical model cannot represent the performance of the RLAS very well, whereas the accuracy of the numerical model is very good. With the verified numerical model, the impacts of many alternative factors on the characteristics of the RLAS are analyzed. Numerical results show that the newly proposed model is reliable to determine the vertical characteristic and physical dimensions of the RLAS under the alternative factors.

  8. Factor Analysis and Modelling for Rapid Quality Assessment of Croatian Wheat Cultivars with Different Gluten Characteristics

    Directory of Open Access Journals (Sweden)

    Želimir Kurtanjek

    2008-01-01

    Full Text Available Factor analysis and multivariate chemometric modelling for rapid assessment of baking quality of wheat cultivars from Slavonia region, Croatia, have been applied. The cultivars Žitarka, Kata, Monika, Ana, Demetra, Divana and Sana were grown under controlled conditions at the experimental field of Agricultural Institute Osijek during three years (2000–2002. Their quality properties were evaluated by 45 different chemical, physical and biochemical variables. The measured variables were grouped as: indirect quality parameters (6, farinographic parameters (7, extensographic parameters (5, baking test parameters (2 and reversed phase-high performance liquid chromatography (RP-HPLC of gluten proteins (25. The aim of this study is to establish minimal number (three, i.e. principal factors, among the 45 variables and to derive multivariate linear regression models for their use in simple and fast prediction of wheat properties. Selection of the principal factors based on the principal component analysis (PCA has been applied. The first three main factors of the analysis include: total glutenins (TGT, total ω-gliadins (Tω- and the ratio of dough resistance/extensibility (R/Ext. These factors account for 76.45 % of the total variance. Linear regression models gave average regression coefficients (R evaluated for the parameter groups: indirect quality R=0.91, baking test R=0.63, farinographic R=0.78, extensographic R=0.95 and RP-HPLC of gluten data R=0.90. Errors in the model predictions were evaluated by the 95 % significance intervals of the calibration lines. Practical applications of the models for rapid quality assessment and laboratory experiment planning were emphasized.

  9. Delineation of geochemical anomalies based on stream sediment data utilizing fractal modeling and staged factor analysis

    Science.gov (United States)

    Afzal, Peyman; Mirzaei, Misagh; Yousefi, Mahyar; Adib, Ahmad; Khalajmasoumi, Masoumeh; Zarifi, Afshar Zia; Foster, Patrick; Yasrebi, Amir Bijan

    2016-07-01

    Recognition of significant geochemical signatures and separation of geochemical anomalies from background are critical issues in interpretation of stream sediment data to define exploration targets. In this paper, we used staged factor analysis in conjunction with the concentration-number (C-N) fractal model to generate exploration targets for prospecting Cr and Fe mineralization in Balvard area, SE Iran. The results show coexistence of derived multi-element geochemical signatures of the deposit-type sought and ultramafic-mafic rocks in the NE and northern parts of the study area indicating significant chromite and iron ore prospects. In this regard, application of staged factor analysis and fractal modeling resulted in recognition of significant multi-element signatures that have a high spatial association with host lithological units of the deposit-type sought, and therefore, the generated targets are reliable for further prospecting of the deposit in the study area.

  10. Multiple Statistical Models Based Analysis of Causative Factors and Loess Landslides in Tianshui City, China

    Science.gov (United States)

    Su, Xing; Meng, Xingmin; Ye, Weilin; Wu, Weijiang; Liu, Xingrong; Wei, Wanhong

    2018-03-01

    Tianshui City is one of the mountainous cities that are threatened by severe geo-hazards in Gansu Province, China. Statistical probability models have been widely used in analyzing and evaluating geo-hazards such as landslide. In this research, three approaches (Certainty Factor Method, Weight of Evidence Method and Information Quantity Method) were adopted to quantitively analyze the relationship between the causative factors and the landslides, respectively. The source data used in this study are including the SRTM DEM and local geological maps in the scale of 1:200,000. 12 causative factors (i.e., altitude, slope, aspect, curvature, plan curvature, profile curvature, roughness, relief amplitude, and distance to rivers, distance to faults, distance to roads, and the stratum lithology) were selected to do correlation analysis after thorough investigation of geological conditions and historical landslides. The results indicate that the outcomes of the three models are fairly consistent.

  11. Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models

    International Nuclear Information System (INIS)

    Lamboni, Matieyendou; Monod, Herve; Makowski, David

    2011-01-01

    Many dynamic models are used for risk assessment and decision support in ecology and crop science. Such models generate time-dependent model predictions, with time either discretised or continuous. Their global sensitivity analysis is usually applied separately on each time output, but Campbell et al. (2006 ) advocated global sensitivity analyses on the expansion of the dynamics in a well-chosen functional basis. This paper focuses on the particular case when principal components analysis is combined with analysis of variance. In addition to the indices associated with the principal components, generalised sensitivity indices are proposed to synthesize the influence of each parameter on the whole time series output. Index definitions are given when the uncertainty on the input factors is either discrete or continuous and when the dynamic model is either discrete or functional. A general estimation algorithm is proposed, based on classical methods of global sensitivity analysis. The method is applied to a dynamic wheat crop model with 13 uncertain parameters. Three methods of global sensitivity analysis are compared: the Sobol'-Saltelli method, the extended FAST method, and the fractional factorial design of resolution 6.

  12. Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models

    Energy Technology Data Exchange (ETDEWEB)

    Lamboni, Matieyendou [INRA, Unite MIA (UR341), F78352 Jouy en Josas Cedex (France); Monod, Herve, E-mail: herve.monod@jouy.inra.f [INRA, Unite MIA (UR341), F78352 Jouy en Josas Cedex (France); Makowski, David [INRA, UMR Agronomie INRA/AgroParisTech (UMR 211), BP 01, F78850 Thiverval-Grignon (France)

    2011-04-15

    Many dynamic models are used for risk assessment and decision support in ecology and crop science. Such models generate time-dependent model predictions, with time either discretised or continuous. Their global sensitivity analysis is usually applied separately on each time output, but Campbell et al. (2006) advocated global sensitivity analyses on the expansion of the dynamics in a well-chosen functional basis. This paper focuses on the particular case when principal components analysis is combined with analysis of variance. In addition to the indices associated with the principal components, generalised sensitivity indices are proposed to synthesize the influence of each parameter on the whole time series output. Index definitions are given when the uncertainty on the input factors is either discrete or continuous and when the dynamic model is either discrete or functional. A general estimation algorithm is proposed, based on classical methods of global sensitivity analysis. The method is applied to a dynamic wheat crop model with 13 uncertain parameters. Three methods of global sensitivity analysis are compared: the Sobol'-Saltelli method, the extended FAST method, and the fractional factorial design of resolution 6.

  13. Rotordynamic analysis for stepped-labyrinth gas seals using moody's friction-factor model

    International Nuclear Information System (INIS)

    Ha, Tae Woong

    2001-01-01

    The governing equations are derived for the analysis of a stepped labyrinth gas seal generally used in high performance compressors, gas turbines, and steam turbines. The bulk-flow is assumed for a single cavity control volume set up in a stepped labyrinth cavity and the flow is assumed to be completely turbulent in the circumferential direction. The Moody's wall-friction-factor model is used for the calculation of wall shear stresses in the single cavity control volume. For the reaction force developed by the stepped labyrinth gas seal, linearized zeroth-order and first-order perturbation equations are developed for small motion about a centered position. Integration of the resultant first-order pressure distribution along and around the seal defines the rotordynamic coefficients of the stepped labyrinth gas seal. The resulting leakage and rotordynamic characteristics of the stepped labyrinth gas seal are presented and compared with Scharrer's theoretical analysis using Blasius' wall-friction-factor model. The present analysis shows a good qualitative agreement of leakage characteristics with Scharrer's analysis, but underpredicts by about 20 %. For the rotordynamic coefficients, the present analysis generally yields smaller predicted values compared with Scharrer's analysis

  14. Cross-Cultural Validation of the Modified Practice Attitudes Scale: Initial Factor Analysis and a New Factor Model.

    Science.gov (United States)

    Park, Heehoon; Ebesutani, Chad K; Chung, Kyong-Mee; Stanick, Cameo

    2018-01-01

    The objective of this study was to create the Korean version of the Modified Practice Attitudes Scale (K-MPAS) to measure clinicians' attitudes toward evidence-based treatments (EBTs) in the Korean mental health system. Using 189 U.S. therapists and 283 members from the Korean mental health system, we examined the reliability and validity of the MPAS scores. We also conducted the first exploratory and confirmatory factor analysis on the MPAS and compared EBT attitudes across U.S. and Korean therapists. Results revealed that the inclusion of both "reversed-worded" and "non-reversed-worded" items introduced significant method effects that compromised the integrity of the one-factor MPAS model. Problems with the one-factor structure were resolved by eliminating the "non-reversed-worded" items. Reliability and validity were adequate among both Korean and U.S. therapists. Korean therapists also reported significantly more negative attitudes toward EBTs on the MPAS than U.S. therapists. The K-MPAS is the first questionnaire designed to measure Korean service providers' attitudes toward EBTs to help advance the dissemination of EBTs in Korea. The current study also demonstrated the negative impacts that can be introduced by incorporating oppositely worded items into a scale, particularly with respect to factor structure and detecting significant group differences.

  15. Uncertainty Evaluation of the SFR Subchannel Thermal-Hydraulic Modeling Using a Hot Channel Factors Analysis

    International Nuclear Information System (INIS)

    Choi, Sun Rock; Cho, Chung Ho; Kim, Sang Ji

    2011-01-01

    In an SFR core analysis, a hot channel factors (HCF) method is most commonly used to evaluate uncertainty. It was employed to the early design such as the CRBRP and IFR. In other ways, the improved thermal design procedure (ITDP) is able to calculate the overall uncertainty based on the Root Sum Square technique and sensitivity analyses of each design parameters. The Monte Carlo method (MCM) is also employed to estimate the uncertainties. In this method, all the input uncertainties are randomly sampled according to their probability density functions and the resulting distribution for the output quantity is analyzed. Since an uncertainty analysis is basically calculated from the temperature distribution in a subassembly, the core thermal-hydraulic modeling greatly affects the resulting uncertainty. At KAERI, the SLTHEN and MATRA-LMR codes have been utilized to analyze the SFR core thermal-hydraulics. The SLTHEN (steady-state LMR core thermal hydraulics analysis code based on the ENERGY model) code is a modified version of the SUPERENERGY2 code, which conducts a multi-assembly, steady state calculation based on a simplified ENERGY model. The detailed subchannel analysis code MATRA-LMR (Multichannel Analyzer for Steady-State and Transients in Rod Arrays for Liquid Metal Reactors), an LMR version of MATRA, was also developed specifically for the SFR core thermal-hydraulic analysis. This paper describes comparative studies for core thermal-hydraulic models. The subchannel analysis and a hot channel factors based uncertainty evaluation system is established to estimate the core thermofluidic uncertainties using the MATRA-LMR code and the results are compared to those of the SLTHEN code

  16. Analysis on influence factors of China's CO2 emissions based on Path-STIRPAT model

    International Nuclear Information System (INIS)

    Li Huanan; Mu Hailin; Zhang Ming; Li Nan

    2011-01-01

    With the intensification of global warming and continued growth in energy consumption, China is facing increasing pressure to cut its CO 2 (carbon dioxide) emissions down. This paper discusses the driving forces influencing China's CO 2 emissions based on Path-STIRPAT model-a method combining Path analysis with STIRPAT (stochastic impacts by regression on population, affluence and technology) model. The analysis shows that GDP per capita (A), industrial structure (IS), population (P), urbanization level (R) and technology level (T) are the main factors influencing China's CO 2 emissions, which exert an influence interactively and collaboratively. The sequence of the size of factors' direct influence on China's CO 2 emission is A>T>P>R>IS, while that of factors' total influence is A>R>P>T>IS. One percent increase in A, IS, P, R and T leads to 0.44, 1.58, 1.31, 1.12 and -1.09 percentage change in CO 2 emission totally, where their direct contribution is 0.45, 0.07, 0.63, 0.08, 0.92, respectively. Improving T is the most important way for CO 2 reduction in China. - Highlights: → We analyze the driving forces influencing China's CO 2 emissions. → Five macro factors like per capita GDP are the main influencing factors. → These factors exert an influence interactively and collaboratively. → Different factors' direct and total influence on China's CO 2 emission is different. → Improving technology level is the most important way for CO 2 reduction in China.

  17. Testing of technology readiness index model based on exploratory factor analysis approach

    Science.gov (United States)

    Ariani, AF; Napitupulu, D.; Jati, RK; Kadar, JA; Syafrullah, M.

    2018-04-01

    SMEs readiness in using ICT will determine the adoption of ICT in the future. This study aims to evaluate the model of technology readiness in order to apply the technology on SMEs. The model is tested to find if TRI model is relevant to measure ICT adoption, especially for SMEs in Indonesia. The research method used in this paper is survey to a group of SMEs in South Tangerang. The survey measures the readiness to adopt ICT based on four variables which is Optimism, Innovativeness, Discomfort, and Insecurity. Each variable contains several indicators to make sure the variable is measured thoroughly. The data collected through survey is analysed using factor analysis methodwith the help of SPSS software. The result of this study shows that TRI model gives more descendants on some indicators and variables. This result can be caused by SMEs owners’ knowledge is not homogeneous about either the technology that they are used, knowledge or the type of their business.

  18. Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

    2018-03-01

    Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

  19. Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

    2017-01-01

    Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

  20. Analysis of operational events by ATHEANA framework for human factor modelling

    International Nuclear Information System (INIS)

    Bedreaga, Luminita; Constntinescu, Cristina; Doca, Cezar; Guzun, Basarab

    2007-01-01

    In the area of human reliability assessment, the experts recognise the fact that the current methods have not represented correctly the role of human in prevention, initiating and mitigating the accidents in nuclear power plants. The nature of this deficiency appears because the current methods used in modelling of human factor have not taken into account the human performance and reliability such as it has been observed in the operational events. ATHEANA - A Technique for Human Error ANAlysis - is a new methodology for human analysis that has included the specific data of operational events and also psychological models for human behaviour. This method has included new elements such as the unsafe action and error mechanisms. In this paper we present the application of ATHEANA framework in the analysis of operational events that appeared in different nuclear power plants during 1979-2002. The analysis of operational events has consisted of: - identification of the unsafe actions; - including the unsafe actions into a category, omission ar commission; - establishing the type of error corresponding to the unsafe action: slip, lapse, mistake and circumvention; - establishing the influence of performance by shaping the factors and some corrective actions. (authors)

  1. Risk factors of chronic periodontitis on healing response: a multilevel modelling analysis.

    Science.gov (United States)

    Song, J; Zhao, H; Pan, C; Li, C; Liu, J; Pan, Y

    2017-09-15

    Chronic periodontitis is a multifactorial polygenetic disease with an increasing number of associated factors that have been identified over recent decades. Longitudinal epidemiologic studies have demonstrated that the risk factors were related to the progression of the disease. A traditional multivariate regression model was used to find risk factors associated with chronic periodontitis. However, the approach requirement of standard statistical procedures demands individual independence. Multilevel modelling (MLM) data analysis has widely been used in recent years, regarding thorough hierarchical structuring of the data, decomposing the error terms into different levels, and providing a new analytic method and framework for solving this problem. The purpose of our study is to investigate the relationship of clinical periodontal index and the risk factors in chronic periodontitis through MLM analysis and to identify high-risk individuals in the clinical setting. Fifty-four patients with moderate to severe periodontitis were included. They were treated by means of non-surgical periodontal therapy, and then made follow-up visits regularly at 3, 6, and 12 months after therapy. Each patient answered a questionnaire survey and underwent measurement of clinical periodontal parameters. Compared with baseline, probing depth (PD) and clinical attachment loss (CAL) improved significantly after non-surgical periodontal therapy with regular follow-up visits at 3, 6, and 12 months after therapy. The null model and variance component models with no independent variables included were initially obtained to investigate the variance of the PD and CAL reductions across all three levels, and they showed a statistically significant difference (P periodontal therapy with regular follow-up visits had a remarkable curative effect. All three levels had a substantial influence on the reduction of PD and CAL. Site-level had the largest effect on PD and CAL reductions.

  2. Confirmatory Factor Analysis of WAIS-IV in a Clinical Sample: Examining a Bi-Factor Model

    Directory of Open Access Journals (Sweden)

    Rachel Collinson

    2016-12-01

    Full Text Available There have been a number of studies that have examined the factor structure of the Wechsler Adult Intelligence Scale IV (WAIS-IV using the standardization sample. In this study, we investigate its factor structure on a clinical neuropsychology sample of mixed aetiology. Correlated factor, higher-order and bi-factor models are all tested. Overall, the results suggest that the WAIS-IV will be suitable for use with this population.

  3. Confirmatory factor analysis of the neck disability index in a whiplash population indicates a one-factor model is viable

    OpenAIRE

    Gabel, Charles P.; Cuesta-Vargas, Antonio I.; Barr, Sebastian; Winkeljohn Black, Stephanie; Osborne, Jason W.; Melloh, Markus

    2016-01-01

    Purpose The neck disability index (NDI) as a 10-item patient reported outcome (PRO) measure is the most commonly used whiplash associated disorders (WAD) assessment tool. However, statistical rigor and factor structure are not definitive. To date, confirmatory factor analysis (CFA) has not examined whether the factor structure generalizes across different groups (e.g., WAD versus non-WAD). This study aimed to determine the psychometric properties of the NDI in these population groups.

  4. The Five-Factor Model personality traits in schizophrenia: A meta-analysis.

    Science.gov (United States)

    Ohi, Kazutaka; Shimada, Takamitsu; Nitta, Yusuke; Kihara, Hiroaki; Okubo, Hiroaki; Uehara, Takashi; Kawasaki, Yasuhiro

    2016-06-30

    Personality is one of important factors in the pathogenesis of schizophrenia because it affects patients' symptoms, cognition and social functioning. Several studies have reported specific personality traits in patients with schizophrenia compared with healthy subjects. However, the results were inconsistent among studies. The NEO Five-Factor Inventory (NEO-FFI) measures five personality traits: Neuroticism (N), Extraversion (E), Openness (O), Agreeableness (A) and Conscientiousness (C). Here, we performed a meta-analysis of these personality traits assessed by the NEO-FFI in 460 patients with schizophrenia and 486 healthy subjects from the published literature and investigated possible associations between schizophrenia and these traits. There was no publication bias for any traits. Because we found evidence of significant heterogeneity in all traits among the studies, we applied a random-effect model to perform the meta-analysis. Patients with schizophrenia showed a higher score for N and lower scores for E, O, A and C compared with healthy subjects. The effect sizes of these personality traits ranged from moderate to large. These differences were not affected by possible moderator factors, such as gender distribution and mean age in each study, expect for gender effect for A. These findings suggest that patients with schizophrenia have a different personality profile compared with healthy subjects. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  5. Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model

    OpenAIRE

    Gomez, Rapson; Watson, Shaun D.

    2017-01-01

    For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants (N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher o...

  6. Analysis of Factors that Influence Infiltration Rates using the HELP Model

    International Nuclear Information System (INIS)

    Dyer, J.; Shipmon, J.

    2017-01-01

    The Hydrologic Evaluation of Landfill Performance (HELP) model is used by Savannah River National Laboratory (SRNL) in conjunction with PORFLOW groundwater flow simulation software to make longterm predictions of the fate and transport of radionuclides in the environment at radiological waste sites. The work summarized in this report supports preparation of the planned 2018 Performance Assessment for the E-Area Low-Level Waste Facility (LLWF) at the Savannah River Site (SRS). More specifically, this project focused on conducting a sensitivity analysis of infiltration (i.e., the rate at which water travels vertically in soil) through the proposed E-Area LLWF closure cap. A sensitivity analysis was completed using HELP v3.95D to identify the cap design and material property parameters that most impact infiltration rates through the proposed closure cap for a 10,000-year simulation period. The results of the sensitivity analysis indicate that saturated hydraulic conductivity (Ksat) for select cap layers, precipitation rate, surface vegetation type, and geomembrane layer defect density are dominant factors limiting infiltration rate. Interestingly, calculated infiltration rates were substantially influenced by changes in the saturated hydraulic conductivity of the Upper Foundation and Lateral Drainage layers. For example, an order-of-magnitude decrease in Ksat for the Upper Foundation layer lowered the maximum infiltration rate from a base-case 11 inches per year to only two inches per year. Conversely, an order-of-magnitude increase in Ksat led to an increase in infiltration rate from 11 to 15 inches per year. This work and its results provide a framework for quantifying uncertainty in the radionuclide transport and dose models for the planned 2018 E-Area Performance Assessment. Future work will focus on the development of a nonlinear regression model for infiltration rate using Minitab 17® to facilitate execution of probabilistic simulations in the GoldSim® overall

  7. Analysis of Factors that Influence Infiltration Rates using the HELP Model

    Energy Technology Data Exchange (ETDEWEB)

    Dyer, J. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Shipmon, J. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2017-09-28

    The Hydrologic Evaluation of Landfill Performance (HELP) model is used by Savannah River National Laboratory (SRNL) in conjunction with PORFLOW groundwater flow simulation software to make longterm predictions of the fate and transport of radionuclides in the environment at radiological waste sites. The work summarized in this report supports preparation of the planned 2018 Performance Assessment for the E-Area Low-Level Waste Facility (LLWF) at the Savannah River Site (SRS). More specifically, this project focused on conducting a sensitivity analysis of infiltration (i.e., the rate at which water travels vertically in soil) through the proposed E-Area LLWF closure cap. A sensitivity analysis was completed using HELP v3.95D to identify the cap design and material property parameters that most impact infiltration rates through the proposed closure cap for a 10,000-year simulation period. The results of the sensitivity analysis indicate that saturated hydraulic conductivity (Ksat) for select cap layers, precipitation rate, surface vegetation type, and geomembrane layer defect density are dominant factors limiting infiltration rate. Interestingly, calculated infiltration rates were substantially influenced by changes in the saturated hydraulic conductivity of the Upper Foundation and Lateral Drainage layers. For example, an order-of-magnitude decrease in Ksat for the Upper Foundation layer lowered the maximum infiltration rate from a base-case 11 inches per year to only two inches per year. Conversely, an order-of-magnitude increase in Ksat led to an increase in infiltration rate from 11 to 15 inches per year. This work and its results provide a framework for quantifying uncertainty in the radionuclide transport and dose models for the planned 2018 E-Area Performance Assessment. Future work will focus on the development of a nonlinear regression model for infiltration rate using Minitab 17® to facilitate execution of probabilistic simulations in the GoldSim® overall

  8. Loneliness and solitude in adolescence: A confirmatory factor analysis of alternative models

    DEFF Research Database (Denmark)

    Goossens, Luc; Lasgaard, Mathias; Luyckx, Koen

    2009-01-01

    completed by a sample of mid-adolescents (N = 534) from Grades 10 through 12 (aged 15-18 years) in the Dutch-speaking part of Belgium. As expected, the four-factor solution provided a better fit to the data than did alternative models that comprised just a single factor, or two and three factors. Use...

  9. Understanding influential factors on implementing green supply chain management practices: An interpretive structural modelling analysis.

    Science.gov (United States)

    Agi, Maher A N; Nishant, Rohit

    2017-03-01

    In this study, we establish a set of 19 influential factors on the implementation of Green Supply Chain Management (GSCM) practices and analyse the interaction between these factors and their effect on the implementation of GSCM practices using the Interpretive Structural Modelling (ISM) method and the "Matrice d'Impacts Croisés Multiplication Appliquée à un Classement" (MICMAC) analysis on data compiled from interviews with supply chain (SC) executives based in the Gulf countries (Middle East region). The study reveals a strong influence and driving power of the nature of the relationships between SC partners on the implementation of GSCM practices. We especially found that dependence, trust, and durability of the relationship with SC partners have a very high influence. In addition, the size of the company, the top management commitment, the implementation of quality management and the employees training and education exert a critical influence on the implementation of GSCM practices. Contextual elements such as the industry sector and region and their effect on the prominence of specific factors are also highlighted through our study. Finally, implications for research and practice are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Analysis of Influence Factors of PM2.5 in Chengdu Based on VAR Model

    Science.gov (United States)

    Mingzhi, Luo

    2017-05-01

    Air pollution and smog are the serious harms to public health and has attracted public attention. Based on the vector auto-regressive (VAR) model, we analysed the influence factors of PM2.5 in Chengdu, investigated the effect of other kinds of air pollutants and meteorological factors onthe PM2.5 by using the methods of generalized impulse response function, variance decomposition analysis, Granger causality test and therelated daily data from December 1, 2013 to November 14, 2016 in Chengdu city to the empirical study. The resultsshow that the influence factors of PM2.5 were stable;the increase of nitrogen dioxide, ozone,precipitation and temperature difference led to the increase of PM2.5 concentration while the increase ofthe wind speed, PM10, sulphur dioxide and carbon monoxide resulted in the decrease of PM2.5 concentration.Climate conditions,nitrogen dioxide and ozone are Granger causes for PM2.5.It is suggestedthat the key for the control of PM2.5 must be based on the cause and formation rules of PM2.5.A further study on nitrogen dioxide and ozone may play an important role in finding out the real source and formation reasons of PM2.5.

  11. Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model

    Science.gov (United States)

    Gomez, Rapson; Watson, Shaun D.

    2017-01-01

    For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants (N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher on the general factor than the specific factors. The three positively worded items had negligible loadings on the general factor. The general factor explained most of the common variance in the SPS and SIAS, and demonstrated good model-based internal consistency reliability (omega hierarchical) and a strong association with fear of negative evaluation and extraversion. The practical implications of the findings for the utilization of the SPS and SIAS, and the theoretical and clinical implications for social anxiety are discussed. PMID:28210232

  12. Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model.

    Science.gov (United States)

    Gomez, Rapson; Watson, Shaun D

    2017-01-01

    For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants ( N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher on the general factor than the specific factors. The three positively worded items had negligible loadings on the general factor. The general factor explained most of the common variance in the SPS and SIAS, and demonstrated good model-based internal consistency reliability (omega hierarchical) and a strong association with fear of negative evaluation and extraversion. The practical implications of the findings for the utilization of the SPS and SIAS, and the theoretical and clinical implications for social anxiety are discussed.

  13. A Solution to Modeling Multilevel Confirmatory Factor Analysis with Data Obtained from Complex Survey Sampling to Avoid Conflated Parameter Estimates

    Directory of Open Access Journals (Sweden)

    Jiun-Yu Wu

    2017-09-01

    Full Text Available The issue of equality in the between-and within-level structures in Multilevel Confirmatory Factor Analysis (MCFA models has been influential for obtaining unbiased parameter estimates and statistical inferences. A commonly seen condition is the inequality of factor loadings under equal level-varying structures. With mathematical investigation and Monte Carlo simulation, this study compared the robustness of five statistical models including two model-based (a true and a mis-specified models, one design-based, and two maximum models (two models where the full rank of variance-covariance matrix is estimated in between level and within level, respectively in analyzing complex survey measurement data with level-varying factor loadings. The empirical data of 120 3rd graders' (from 40 classrooms perceived Harter competence scale were modeled using MCFA and the parameter estimates were used as true parameters to perform the Monte Carlo simulation study. Results showed maximum models was robust to unequal factor loadings while the design-based and the miss-specified model-based approaches produced conflated results and spurious statistical inferences. We recommend the use of maximum models if researchers have limited information about the pattern of factor loadings and measurement structures. Measurement models are key components of Structural Equation Modeling (SEM; therefore, the findings can be generalized to multilevel SEM and CFA models. Mplus codes are provided for maximum models and other analytical models.

  14. The Five-Factor Model of Personality and Borderline Personality Disorder: A Genetic Analysis of Comorbidity

    NARCIS (Netherlands)

    Distel, M.A.; Trull, T.J.; Willemsen, G.; Vink, J.M.; Derom, C.A.; Lynskey, M.; Martin, N.G.; Boomsma, D.I.

    2009-01-01

    Background: Recently, the nature of personality disorders and their relationship with normal personality traits has received extensive attention. The five-factor model (FFM) of personality, consisting of the personality traits neuroticism, extraversion, openness to experience, agreeableness, and

  15. Global combustion sources of organic aerosols: model comparison with 84 AMS factor-analysis data sets

    Science.gov (United States)

    Tsimpidi, Alexandra P.; Karydis, Vlassis A.; Pandis, Spyros N.; Lelieveld, Jos

    2016-07-01

    Emissions of organic compounds from biomass, biofuel, and fossil fuel combustion strongly influence the global atmospheric aerosol load. Some of the organics are directly released as primary organic aerosol (POA). Most are emitted in the gas phase and undergo chemical transformations (i.e., oxidation by hydroxyl radical) and form secondary organic aerosol (SOA). In this work we use the global chemistry climate model ECHAM/MESSy Atmospheric Chemistry (EMAC) with a computationally efficient module for the description of organic aerosol (OA) composition and evolution in the atmosphere (ORACLE). The tropospheric burden of open biomass and anthropogenic (fossil and biofuel) combustion particles is estimated to be 0.59 and 0.63 Tg, respectively, accounting for about 30 and 32 % of the total tropospheric OA load. About 30 % of the open biomass burning and 10 % of the anthropogenic combustion aerosols originate from direct particle emissions, whereas the rest is formed in the atmosphere. A comprehensive data set of aerosol mass spectrometer (AMS) measurements along with factor-analysis results from 84 field campaigns across the Northern Hemisphere are used to evaluate the model results. Both the AMS observations and the model results suggest that over urban areas both POA (25-40 %) and SOA (60-75 %) contribute substantially to the overall OA mass, whereas further downwind and in rural areas the POA concentrations decrease substantially and SOA dominates (80-85 %). EMAC does a reasonable job in reproducing POA and SOA levels during most of the year. However, it tends to underpredict POA and SOA concentrations during winter indicating that the model misses wintertime sources of OA (e.g., residential biofuel use) and SOA formation pathways (e.g., multiphase oxidation).

  16. Modeling of Iranian Cheetah Habitat using Ecological Niche Factor Analysis (Case Study: Dare Anjir Wildlife Refuge

    Directory of Open Access Journals (Sweden)

    N. Zamani

    2016-03-01

    Full Text Available Evaluation of habitat sustainability indexes is essential in wildlife management and conservation of rare species. Suitable habitats are required in wildlife managements and conservation also, they increase reproduction and survival rate of species. In this study in order to mapping habitat sustainability and recognizing habitat requirements of Iranian Cheetah (Acinonyx jubatus venaticus, field data from Dare Anjir  wildlife refuge were collected since autumn 2009 until summer 2011. Ecological Niche Factor Analysis approach has been used to develop habitat suitability model. In this method primary maps of  habitat variables including elevation, slope, aspect, vegetation cover, distance from water sources and environmental monitoring stations have been produced by Idrisi and Biomapper software and imported in Biomapper. The output scores obtained from the analysis showed that Iranian cheetah tends to mountain areas where has more topographical features for camouflage in order to hunting, and northern aspects which have more humidity, denser vegetation cover and more preys . Our result showed that the Iranian cheetah has medium niche width and prefer marginal habitats.

  17. Improved Dynamic Modeling of the Cascade Distillation Subsystem and Analysis of Factors Affecting Its Performance

    Science.gov (United States)

    Perry, Bruce A.; Anderson, Molly S.

    2015-01-01

    The Cascade Distillation Subsystem (CDS) is a rotary multistage distiller being developed to serve as the primary processor for wastewater recovery during long-duration space missions. The CDS could be integrated with a system similar to the International Space Station Water Processor Assembly to form a complete water recovery system for future missions. A preliminary chemical process simulation was previously developed using Aspen Custom Modeler® (ACM), but it could not simulate thermal startup and lacked detailed analysis of several key internal processes, including heat transfer between stages. This paper describes modifications to the ACM simulation of the CDS that improve its capabilities and the accuracy of its predictions. Notably, the modified version can be used to model thermal startup and predicts the total energy consumption of the CDS. The simulation has been validated for both NaC1 solution and pretreated urine feeds and no longer requires retuning when operating parameters change. The simulation was also used to predict how internal processes and operating conditions of the CDS affect its performance. In particular, it is shown that the coefficient of performance of the thermoelectric heat pump used to provide heating and cooling for the CDS is the largest factor in determining CDS efficiency. Intrastage heat transfer affects CDS performance indirectly through effects on the coefficient of performance.

  18. Moderating Factors of Video-Modeling with Other as Model: A Meta-Analysis of Single-Case Studies

    Science.gov (United States)

    Mason, Rose A.; Ganz, Jennifer B.; Parker, Richard I.; Burke, Mack D.; Camargo, Siglia P.

    2012-01-01

    Video modeling with other as model (VMO) is a more practical method for implementing video-based modeling techniques, such as video self-modeling, which requires significantly more editing. Despite this, identification of contextual factors such as participant characteristics and targeted outcomes that moderate the effectiveness of VMO has not…

  19. Confirmatory Factor Analysis of the Bases of Leader Power: First-Order Factor Model and Its Invariance Across Groups.

    Science.gov (United States)

    Rahim, M A; Magner, N R

    1996-10-01

    Confirmatory factor analyses of data (from five samples: N = 308 accountants and finance professionals, N = 578 management and non-management employees, and N = 588 employed management students in the U.S.; N = 728 management and non-management employees in S. Korea, N = 250 management and non-management bank employees in Bangladesh) on the 29 items of the Rahim Leader Power Inventory were performed with LISREL 7. The results provided support for the convergent and discriminant validities of the subscales measuring the five bases of leader power (coercive, reward, legitimate, expert, and referent), and the invariance of factor pattern and factor loadings across organizational levels and the three American samples. Additional analysis indicated that leader power profiles differed across the three national cultures represented in the study.

  20. Confirmatory factory analysis of the Neck Disability Index in a general problematic neck population indicates a one-factor model.

    Science.gov (United States)

    Gabel, Charles Philip; Cuesta-Vargas, Antonio I; Osborne, Jason W; Burkett, Brendan; Melloh, Markus

    2014-08-01

    The Neck Disability Index frequently is used to measure outcomes of the neck. The statistical rigor of the Neck Disability Index has been assessed with conflicting outcomes. To date, Confirmatory Factor Analysis of the Neck Disability Index has not been reported for a suitably large population study. Because the Neck Disability Index is not a condition-specific measure of neck function, initial Confirmatory Factor Analysis should consider problematic neck patients as a homogenous group. We sought to analyze the factor structure of the Neck Disability Index through Confirmatory Factor Analysis in a symptomatic, homogeneous, neck population, with respect to pooled populations and gender subgroups. This was a secondary analysis of pooled data. A total of 1,278 symptomatic neck patients (67.5% female, median age 41 years), 803 nonspecific and 475 with whiplash-associated disorder. The Neck Disability Index was used to measure outcomes. We analyzed pooled baseline data from six independent studies of patients with neck problems who completed Neck Disability Index questionnaires at baseline. The Confirmatory Factor Analysis was considered in three scenarios: the full sample and separate sexes. Models were compared empirically for best fit. Two-factor models have good psychometric properties across both the pooled and sex subgroups. However, according to these analyses, the one-factor solution is preferable from both a statistical perspective and parsimony. The two-factor model was close to significant for the male subgroup (pfactor structure when analyzed by Confirmatory Factor Analysis in a pooled, homogenous sample of neck problem patients. However, a two-factor model did approach significance for male subjects where questions separated into constructs of mental and physical function. Further investigations in different conditions, subgroup and sex-specific populations are warranted. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Reliability Analysis of a Composite Wind Turbine Blade Section Using the Model Correction Factor Method: Numerical Study and Validation

    DEFF Research Database (Denmark)

    Dimitrov, Nikolay Krasimirov; Friis-Hansen, Peter; Berggreen, Christian

    2013-01-01

    by the composite failure criteria. Each failure mode has been considered in a separate component reliability analysis, followed by a system analysis which gives the total probability of failure of the structure. The Model Correction Factor method used in connection with FORM (First-Order Reliability Method) proved...

  2. The structure of PTSD symptoms: a test of alternative models using confirmatory factor analysis.

    Science.gov (United States)

    Elklit, Ask; Shevlin, Mark

    2007-09-01

    This study aimed to examine the structure of self-reported post-traumatic stress disorder (PTSD) symptoms. Based on previous factor analytic findings and the DSM-IV formulation, six confirmatory factor models were specified and estimated that reflected different symptom clusters. The analyses were based on responses from 1116 participants who had suffered whiplash injuries and screened for full or subclinical PTSD using the Harvard Trauma Questionnaire. A correlated four-factor model with re-experiencing, avoidance, dysphoria and arousal factors fitted the data very well. Correlations with criteria measures showed that these factors were associated with other trauma related variables in a theoretically predictable way and showed evidence of unique predictive utility. These results concur with previous research findings using different trauma populations but do not reflect the current DSM-IV symptom groupings.

  3. Job Stress and Related Factors Among Iranian Male Staff Using a Path Analysis Model.

    Science.gov (United States)

    Azad-Marzabadi, Esfandiar; Gholami Fesharaki, Mohammad

    2016-06-01

    In recent years, job stress has been cited as a risk factor for some diseases. Given the importance of this subject, we established a new model for classifying job stress among Iranian male staff using path analysis. This cross-sectional study was done on male staff in Tehran, Iran, 2013. The participants in the study were selected using a proportional stratum sampling method. The tools used included nine questionnaires (1- HSE questionnaire; 2- GHQ questionnaire; 3- Beck depression inventory; 4- Framingham personality type; 5- Azad-Fesharaki's physical activity questionnaire; 6- Adult attachment style questionnaire; 7- Azad socioeconomic questionnaire; 8- Job satisfaction survey; and 9- demographic questionnaire). A total of 575 individuals (all male) were recruited for the study. Their mean (±SD) age was 33.49 (±8.9) and their mean job experience was 12.79 (±8.98) years. The pathway of job stress among Iranian male staff showed an adequate model fit (RMSEA=0.021, GFI=0.99, AGFI=0.97, P=0.136). In addition, the total effect of variables like personality type (β=0.283), job satisfaction (β=0.287), and age (β=0.108) showed a positive relationship with job stress, while variables like general health (β=-0.151) and depression (β=-0.242) showed the reverse effect on job stress. According to the results of this study, we can conclude that our suggested model is suited to explaining the pathways of stress among Iranian male staff.

  4. A review of the models for evaluating organizational factors in human reliability analysis

    International Nuclear Information System (INIS)

    Alvarenga, Marco Antonio Bayout; Fonseca, Renato Alves da; Melo, Paulo Fernando Ferreira Frutuoso e

    2009-01-01

    Human factors should be evaluated in three hierarchical levels. The first level should concern the cognitive behavior of human beings during the control of processes that occur through the man-machine interface. Here, one evaluates human errors through human reliability models of first and second generation, like THERP, ASEP and HCR (first generation) and ATHEANA and CREAM (second generation). In the second level, the focus is in the cognitive behavior of human beings when they work in groups, as in nuclear power plants. The focus here is in the anthropological aspects that govern the interaction among human beings. In the third level, one is interested in the influence that the organizational culture exerts on human beings as well as on the tasks being performed. Here, one adds to the factors of the second level the economical and political aspects that shape the company organizational culture. Nowadays, the methodologies of HRA incorporate organizational factors in the group and organization levels through performance shaping factors. This work makes a critical evaluation of the deficiencies concerning human factors and evaluates the potential of quantitative techniques that have been proposed in the last decade to model organizational factors, including the interaction among groups, with the intention of eliminating this chronic deficiency of HRA models. Two important techniques will be discussed in this context: STAMP, based on system theory and FRAM, which aims at modeling the nonlinearities of socio-technical systems. (author)

  5. A review of the models for evaluating organizational factors in human reliability analysis

    Energy Technology Data Exchange (ETDEWEB)

    Alvarenga, Marco Antonio Bayout; Fonseca, Renato Alves da [Comissao Nacional de Energia Nuclear (CNEN), Rio de Janeiro, RJ (Brazil)], e-mail: bayout@cnen.gov.br, e-mail: rfonseca@cnen.gov.br; Melo, Paulo Fernando Ferreira Frutuoso e [Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear], e-mail: frutuoso@con.ufrj.br

    2009-07-01

    Human factors should be evaluated in three hierarchical levels. The first level should concern the cognitive behavior of human beings during the control of processes that occur through the man-machine interface. Here, one evaluates human errors through human reliability models of first and second generation, like THERP, ASEP and HCR (first generation) and ATHEANA and CREAM (second generation). In the second level, the focus is in the cognitive behavior of human beings when they work in groups, as in nuclear power plants. The focus here is in the anthropological aspects that govern the interaction among human beings. In the third level, one is interested in the influence that the organizational culture exerts on human beings as well as on the tasks being performed. Here, one adds to the factors of the second level the economical and political aspects that shape the company organizational culture. Nowadays, the methodologies of HRA incorporate organizational factors in the group and organization levels through performance shaping factors. This work makes a critical evaluation of the deficiencies concerning human factors and evaluates the potential of quantitative techniques that have been proposed in the last decade to model organizational factors, including the interaction among groups, with the intention of eliminating this chronic deficiency of HRA models. Two important techniques will be discussed in this context: STAMP, based on system theory and FRAM, which aims at modeling the nonlinearities of socio-technical systems. (author)

  6. Analysis on influencing factors of clinical teachers’ job satisfaction by structural equation model

    Directory of Open Access Journals (Sweden)

    Haiyi Jia

    2017-02-01

    Full Text Available [Research objective] Analyze the influencing factors of clinical teachers’ job satisfaction. [Research method] The ERG theory was used as the framework to design the questionnaires. Data were analyzed by structural equation model for investigating the influencing factors. [Research result] The modified model shows that factors of existence needs and growth needs have direct influence on the job satisfaction of clinical teachers, the influence coefficients are 0.540 and 0.380. The three influencing factors have positive effects on each other, and the correlation coefficients are 0.620, 0.400 and 0.330 respectively. [Research conclusion] Relevant departments should take active measures to improve job satisfaction of clinical teachers from two aspects: existence needs and growth needs, and to improve their work enthusiasm and teaching quality.

  7. The five-factor model of personality traits and organizational citizenship behaviors: a meta-analysis.

    Science.gov (United States)

    Chiaburu, Dan S; Oh, In-Sue; Berry, Christopher M; Li, Ning; Gardner, Richard G

    2011-11-01

    Using meta-analytic tests based on 87 statistically independent samples, we investigated the relationships between the five-factor model (FFM) of personality traits and organizational citizenship behaviors in both the aggregate and specific forms, including individual-directed, organization-directed, and change-oriented citizenship. We found that Emotional Stability, Extraversion, and Openness/Intellect have incremental validity for citizenship over and above Conscientiousness and Agreeableness, 2 well-established FFM predictors of citizenship. In addition, FFM personality traits predict citizenship over and above job satisfaction. Finally, we compared the effect sizes obtained in the current meta-analysis with the comparable effect sizes predicting task performance from previous meta-analyses. As a result, we found that Conscientiousness, Emotional Stability, and Extraversion have similar magnitudes of relationships with citizenship and task performance, whereas Openness and Agreeableness have stronger relationships with citizenship than with task performance. This lends some support to the idea that personality traits are (slightly) more important determinants of citizenship than of task performance. We conclude with proposed directions for future research on the relationships between FFM personality traits and specific forms of citizenship, based on the current findings. (c) 2011 APA, all rights reserved.

  8. Derivation and application of mathematical model for well test analysis with variable skin factor in hydrocarbon reservoirs

    Directory of Open Access Journals (Sweden)

    Pengcheng Liu

    2016-06-01

    Full Text Available Skin factor is often regarded as a constant in most of the mathematical model for well test analysis in oilfields, but this is only a kind of simplified treatment with the actual skin factor changeable. This paper defined the average permeability of a damaged area as a function of time by using the definition of skin factor. Therefore a relationship between a variable skin factor and time was established. The variable skin factor derived was introduced into existing traditional models rather than using a constant skin factor, then, this newly derived mathematical model for well test analysis considering variable skin factor was solved by Laplace transform. The dimensionless wellbore pressure and its derivative changed with dimensionless time were plotted with double logarithm and these plots can be used for type curve fitting. The effects of all the parameters in the expression of variable skin factor were analyzed based on the dimensionless wellbore pressure and its derivative. Finally, actual well testing data were used to fit the type curves developed which validates the applicability of the mathematical model from Sheng-2 Block, Shengli Oilfield, China.

  9. Sparse Probabilistic Parallel Factor Analysis for the Modeling of PET and Task-fMRI Data

    DEFF Research Database (Denmark)

    Beliveau, Vincent; Papoutsakis, Georgios; Hinrich, Jesper Løve

    2017-01-01

    Modern datasets are often multiway in nature and can contain patterns common to a mode of the data (e.g. space, time, and subjects). Multiway decomposition such as parallel factor analysis (PARAFAC) take into account the intrinsic structure of the data, and sparse versions of these methods improv...

  10. Detection and analysis of unusual features in the structural model and structure-factor data of a birch pollen allergen

    International Nuclear Information System (INIS)

    Rupp, Bernhard

    2012-01-01

    The structure factors deposited with PDB entry 3k78 show properties inconsistent with experimentally observed diffraction data, and without uncertainty represent calculated structure factors. The refinement of the model against these structure factors leads to an isomorphous structure different from the deposited model with an implausibly small R value (0.019). Physically improbable features in the model of the birch pollen structure Bet v 1d are faithfully reproduced in electron density generated with the deposited structure factors, but these structure factors themselves exhibit properties that are characteristic of data calculated from a simple model and are inconsistent with the data and error model obtained through experimental measurements. The refinement of the model against these structure factors leads to an isomorphous structure different from the deposited model with an implausibly small R value (0.019). The abnormal refinement is compared with normal refinement of an isomorphous variant structure of Bet v 1l. A variety of analytical tools, including the application of Diederichs plots, Rσ plots and bulk-solvent analysis are discussed as promising aids in validation. The examination of the Bet v 1d structure also cautions against the practice of indicating poorly defined protein chain residues through zero occupancies. The recommendation to preserve diffraction images is amplified

  11. Analysis of factors affecting satisfaction level on problem based learning approach using structural equation modeling

    Science.gov (United States)

    Hussain, Nur Farahin Mee; Zahid, Zalina

    2014-12-01

    Nowadays, in the job market demand, graduates are expected not only to have higher performance in academic but they must also be excellent in soft skill. Problem-Based Learning (PBL) has a number of distinct advantages as a learning method as it can deliver graduates that will be highly prized by industry. This study attempts to determine the satisfaction level of engineering students on the PBL Approach and to evaluate their determinant factors. The Structural Equation Modeling (SEM) was used to investigate how the factors of Good Teaching Scale, Clear Goals, Student Assessment and Levels of Workload affected the student satisfaction towards PBL approach.

  12. Analysis on the influence factors of Bitcoin's price based on VEC model

    OpenAIRE

    Zhu, Yechen; Dickinson, David; Li, Jianjun

    2017-01-01

    Background: Bitcoin, the most innovate digital currency as of now, created since 2008, even through experienced its ups and downs, still keeps drawing attentions to all parts of society. It relies on peer-to-peer network, achieved decentralization, anonymous and transparent. As the most representative digital currency, people curious to study how Bitcoin' price changes in the past. Methods: In this paper, we use monthly data from 2011 to 2016 to build a VEC model to exam how economic factors ...

  13. Linear model analysis of the influencing factors of boar longevity in Southern China.

    Science.gov (United States)

    Wang, Chao; Li, Jia-Lian; Wei, Hong-Kui; Zhou, Yuan-Fei; Jiang, Si-Wen; Peng, Jian

    2017-04-15

    This study aimed to investigate the factors influencing the boar herd life month (BHLM) in Southern China. A total of 1630 records of culling boars from nine artificial insemination centers were collected from January 2013 to May 2016. A logistic regression model and two linear models were used to analyze the effects of breed, housing type, age at herd entry, and seed stock herd on boar removal reason and BHLM, respectively. Boar breed and the age at herd entry had significant effects on the removal reasons (P linear models (with or without removal reason including) showed boars raised individually in stalls exhibited shorter BHLM than those raised in pens (P introduction. Copyright © 2017. Published by Elsevier Inc.

  14. Sensitivity Analysis of b-factor in Microwave Emission Model for Soil Moisture Retrieval: A Case Study for SMAP Mission

    Directory of Open Access Journals (Sweden)

    Dugwon Seo

    2010-05-01

    Full Text Available Sensitivity analysis is critically needed to better understand the microwave emission model for soil moisture retrieval using passive microwave remote sensing data. The vegetation b-factor along with vegetation water content and surface characteristics has significant impact in model prediction. This study evaluates the sensitivity of the b-factor, which is function of vegetation type. The analysis is carried out using Passive and Active L and S-band airborne sensor (PALS and measured field soil moisture from Southern Great Plains experiment (SGP99. The results show that the relative sensitivity of the b-factor is 86% in wet soil condition and 88% in high vegetated condition compared to the sensitivity of the soil moisture. Apparently, the b-factor is found to be more sensitive than the vegetation water content, surface roughness and surface temperature; therefore, the effect of the b-factor is fairly large to the microwave emission in certain conditions. Understanding the dependence of the b-factor on the soil and vegetation is important in studying the soil moisture retrieval algorithm, which can lead to potential improvements in model development for the Soil Moisture Active-Passive (SMAP mission.

  15. Analysis of significance of environmental factors in landslide susceptibility modeling: Case study Jemma drainage network, Ethiopia

    Directory of Open Access Journals (Sweden)

    Vít Maca

    2017-06-01

    Full Text Available Aim of the paper is to describe methodology for calculating significance of environmental factors in landslide susceptibility modeling and present result of selected one. As a study area part of a Jemma basin in Ethiopian Highland is used. This locality is highly affected by mass movement processes. In the first part all major factors and their influence are described briefly. Majority of the work focuses on research of other methodologies used in susceptibility models and design of own methodology. This method is unlike most of the methods used completely objective, therefore it is not possible to intervene in the results. In article all inputs and outputs of the method are described as well as all stages of calculations. Results are illustrated on specific examples. In study area most important factor for landslide susceptibility is slope, on the other hand least important is land cover. At the end of article landslide susceptibility map is created. Part of the article is discussion of results and possible improvements of the methodology.

  16. An analysis of a three-factor model proposed by the Danish Society of Actuaries for forecasting and risk analysis

    DEFF Research Database (Denmark)

    Jørgensen, Peter Løchte; Slipsager, Søren Kærgaard

    2016-01-01

    This paper provides the explicit solution to the three-factor diffusion model recently proposed by the Danish Society of Actuaries to the Danish industry of life insurance and pensions. The solution is obtained by use of the known general solution to multidimensional linear stochastic differential...

  17. A discriminant analysis prediction model of non-syndromic cleft lip with or without cleft palate based on risk factors.

    Science.gov (United States)

    Li, Huixia; Luo, Miyang; Luo, Jiayou; Zheng, Jianfei; Zeng, Rong; Du, Qiyun; Fang, Junqun; Ouyang, Na

    2016-11-23

    A risk prediction model of non-syndromic cleft lip with or without cleft palate (NSCL/P) was established by a discriminant analysis to predict the individual risk of NSCL/P in pregnant women. A hospital-based case-control study was conducted with 113 cases of NSCL/P and 226 controls without NSCL/P. The cases and the controls were obtained from 52 birth defects' surveillance hospitals in Hunan Province, China. A questionnaire was administered in person to collect the variables relevant to NSCL/P by face to face interviews. Logistic regression models were used to analyze the influencing factors of NSCL/P, and a stepwise Fisher discriminant analysis was subsequently used to construct the prediction model. In the univariate analysis, 13 influencing factors were related to NSCL/P, of which the following 8 influencing factors as predictors determined the discriminant prediction model: family income, maternal occupational hazards exposure, premarital medical examination, housing renovation, milk/soymilk intake in the first trimester of pregnancy, paternal occupational hazards exposure, paternal strong tea drinking, and family history of NSCL/P. The model had statistical significance (lambda = 0.772, chi-square = 86.044, df = 8, P Self-verification showed that 83.8 % of the participants were correctly predicted to be NSCL/P cases or controls with a sensitivity of 74.3 % and a specificity of 88.5 %. The area under the receiver operating characteristic curve (AUC) was 0.846. The prediction model that was established using the risk factors of NSCL/P can be useful for predicting the risk of NSCL/P. Further research is needed to improve the model, and confirm the validity and reliability of the model.

  18. [Analysis of dietary pattern and diabetes mellitus influencing factors identified by classification tree model in adults of Fujian].

    Science.gov (United States)

    Yu, F L; Ye, Y; Yan, Y S

    2017-05-10

    Objective: To find out the dietary patterns and explore the relationship between environmental factors (especially dietary patterns) and diabetes mellitus in the adults of Fujian. Methods: Multi-stage sampling method were used to survey residents aged ≥18 years by questionnaire, physical examination and laboratory detection in 10 disease surveillance points in Fujian. Factor analysis was used to identify the dietary patterns, while logistic regression model was applied to analyze relationship between dietary patterns and diabetes mellitus, and classification tree model was adopted to identify the influencing factors for diabetes mellitus. Results: There were four dietary patterns in the population, including meat, plant, high-quality protein, and fried food and beverages patterns. The result of logistic analysis showed that plant pattern, which has higher factor loading of fresh fruit-vegetables and cereal-tubers, was a protective factor for non-diabetes mellitus. The risk of diabetes mellitus in the population at T2 and T3 levels of factor score were 0.727 (95 %CI: 0.561-0.943) times and 0.736 (95 %CI : 0.573-0.944) times higher, respectively, than those whose factor score was in lowest quartile. Thirteen influencing factors and eleven group at high-risk for diabetes mellitus were identified by classification tree model. The influencing factors were dyslipidemia, age, family history of diabetes, hypertension, physical activity, career, sex, sedentary time, abdominal adiposity, BMI, marital status, sleep time and high-quality protein pattern. Conclusion: There is a close association between dietary patterns and diabetes mellitus. It is necessary to promote healthy and reasonable diet, strengthen the monitoring and control of blood lipids, blood pressure and body weight, and have good lifestyle for the prevention and control of diabetes mellitus.

  19. Model analysis of the world data on the pion transition form factor

    International Nuclear Information System (INIS)

    Noguera, S.; Vento, V.

    2012-01-01

    We discuss the impact of recent Belle data on our description of the pion transition form factor based on the assumption that a perturbative formalism and a nonperturbative one can be matched in a physically acceptable manner at a certain hadronic scale Q 0 . We discuss the implications of the different parameters of the model in comparing with world data and conclude that within experimental errors our description remains valid. Thus we can assert that the low Q 2 nonperturbative description together with an additional 1/Q 2 term at the matching scale have a strong influence on the Q 2 behavior up to very high values of Q 2 . (orig.)

  20. Factor Analysis for Clustered Observations.

    Science.gov (United States)

    Longford, N. T.; Muthen, B. O.

    1992-01-01

    A two-level model for factor analysis is defined, and formulas for a scoring algorithm for this model are derived. A simple noniterative method based on decomposition of total sums of the squares and cross-products is discussed and illustrated with simulated data and data from the Second International Mathematics Study. (SLD)

  1. Schistosoma mansoni reinfection: Analysis of risk factors by classification and regression tree (CART modeling.

    Directory of Open Access Journals (Sweden)

    Andréa Gazzinelli

    Full Text Available Praziquantel (PZQ is an effective chemotherapy for schistosomiasis mansoni and a mainstay for its control and potential elimination. However, it does not prevent against reinfection, which can occur rapidly in areas with active transmission. A guide to ranking the risk factors for Schistosoma mansoni reinfection would greatly contribute to prioritizing resources and focusing prevention and control measures to prevent rapid reinfection. The objective of the current study was to explore the relationship among the socioeconomic, demographic, and epidemiological factors that can influence reinfection by S. mansoni one year after successful treatment with PZQ in school-aged children in Northeastern Minas Gerais state Brazil. Parasitological, socioeconomic, demographic, and water contact information were surveyed in 506 S. mansoni-infected individuals, aged 6 to 15 years, resident in these endemic areas. Eligible individuals were treated with PZQ until they were determined to be negative by the absence of S. mansoni eggs in the feces on two consecutive days of Kato-Katz fecal thick smear. These individuals were surveyed again 12 months from the date of successful treatment with PZQ. A classification and regression tree modeling (CART was then used to explore the relationship between socioeconomic, demographic, and epidemiological variables and their reinfection status. The most important risk factor identified for S. mansoni reinfection was their "heavy" infection at baseline. Additional analyses, excluding heavy infection status, showed that lower socioeconomic status and a lower level of education of the household head were also most important risk factors for S. mansoni reinfection. Our results provide an important contribution toward the control and possible elimination of schistosomiasis by identifying three major risk factors that can be used for targeted treatment and monitoring of reinfection. We suggest that control measures that target

  2. Quantification of source impact to PM using three-dimensional weighted factor model analysis on multi-site data

    Science.gov (United States)

    Shi, Guoliang; Peng, Xing; Huangfu, Yanqi; Wang, Wei; Xu, Jiao; Tian, Yingze; Feng, Yinchang; Ivey, Cesunica E.; Russell, Armistead G.

    2017-07-01

    Source apportionment technologies are used to understand the impacts of important sources of particulate matter (PM) air quality, and are widely used for both scientific studies and air quality management. Generally, receptor models apportion speciated PM data from a single sampling site. With the development of large scale monitoring networks, PM speciation are observed at multiple sites in an urban area. For these situations, the models should account for three factors, or dimensions, of the PM, including the chemical species concentrations, sampling periods and sampling site information, suggesting the potential power of a three-dimensional source apportionment approach. However, the principle of three-dimensional Parallel Factor Analysis (Ordinary PARAFAC) model does not always work well in real environmental situations for multi-site receptor datasets. In this work, a new three-way receptor model, called "multi-site three way factor analysis" model is proposed to deal with the multi-site receptor datasets. Synthetic datasets were developed and introduced into the new model to test its performance. Average absolute error (AAE, between estimated and true contributions) for extracted sources were all less than 50%. Additionally, three-dimensional ambient datasets from a Chinese mega-city, Chengdu, were analyzed using this new model to assess the application. Four factors are extracted by the multi-site WFA3 model: secondary source have the highest contributions (64.73 and 56.24 μg/m3), followed by vehicular exhaust (30.13 and 33.60 μg/m3), crustal dust (26.12 and 29.99 μg/m3) and coal combustion (10.73 and 14.83 μg/m3). The model was also compared to PMF, with general agreement, though PMF suggested a lower crustal contribution.

  3. Numerical modeling of polymorphic transformation of oleic acid via near-infrared spectroscopy and factor analysis

    Science.gov (United States)

    Liu, Ling; Cheng, Yuliang; Sun, Xiulan; Pi, Fuwei

    2018-05-01

    Near-infrared (NIR) spectroscopy as a tool for direct and quantitatively screening the minute polymorphic transitions of bioactive fatty acids was assessed basing on a thermal heating process of oleic acid. Temperature-dependent NIR spectral profiles indicate that dynamical variances of COOH group dominate its γ → α phase transition, while the transition from active α to β phase mainly relates to the conformational transfer of acyl chain. Through operating multivariate curve resolution-alternating least squares with factor analysis, instantaneous contribution of each active polymorph during the transition process was illustrated for displaying the progressive evolutions of functional groups. Calculated contributions reveal that the α phase of oleic acid initially is present at around -18 °C, but sharply grows up around -2.2 °C from the transformation of γ phase and finally disappears at the melting point. On the other hand, the β phase of oleic acid is sole self-generation after melt even it embryonically appears at -2.2 °C. Such mathematical approach based on NIR spectroscopy and factor analysis calculation provides a volatile strategy in quantitatively exploring the transition processes of bioactive fatty acids; meanwhile, it maintains promising possibility for instantaneous quantifying each active polymorph of lipid materials.

  4. Factor analysis and scintigraphy

    International Nuclear Information System (INIS)

    Di Paola, R.; Penel, C.; Bazin, J.P.; Berche, C.

    1976-01-01

    The goal of factor analysis is usually to achieve reduction of a large set of data, extracting essential features without previous hypothesis. Due to the development of computerized systems, the use of largest sampling, the possibility of sequential data acquisition and the increase of dynamic studies, the problem of data compression can be encountered now in routine. Thus, results obtained for compression of scintigraphic images were first presented. Then possibilities given by factor analysis for scan processing were discussed. At last, use of this analysis for multidimensional studies and specially dynamic studies were considered for compression and processing [fr

  5. Analysis and modelling of the factors controlling seed oil concentration in sunflower: a review

    Directory of Open Access Journals (Sweden)

    Andrianasolo Fety Nambinina

    2016-03-01

    Full Text Available Sunflower appears as a potentially highly competitive crop, thanks to the diversification of its market and the richness of its oil. However, seed oil concentration (OC – a commercial criterion for crushing industry – is subjected to genotypic and environmental effects that make it sometimes hardly predictable. It is assumed that more understanding of oil physiology combined with the use of crop models should permit to improve prediction and management of grain quality for various end-users. Main effects of temperature, water, nitrogen, plant density and fungal diseases were reviewed in this paper. Current generic and specific crop models which simulate oil concentration were found to be empirical and to lack of proper evaluation processes. Recently two modeling approaches integrating ecophysiological knowledge were developed by Andrianasolo (2014, Statistical and dynamic modelling of sunflower (Helianthus annuus L. grain composition as a function of agronomic and environmental factors, Ph.D. Thesis, INP Toulouse: (i a statistical approach relating OC to a range of explanatory variables (potential OC, temperature, water and nitrogen stress indices, intercepted radiation, plant density which resulted in prediction quality from 1.9 to 2.5 oil points depending on the nature of the models; (ii a dynamic approach, based on “source-sink” relationships involving leaves, stems, receptacles (as sources and hulls, proteins and oil (as sinks and using priority rules for carbon and nitrogen allocation. The latter model reproduced dynamic patterns of all source and sink components faithfully, but tended to overestimate OC. A better description of photosynthesis and nitrogen uptake, as well as genotypic parameters is expected to improve its performance.

  6. The five-factor model of personality and borderline personality disorder: a genetic analysis of comorbidity.

    Science.gov (United States)

    Distel, Marijn A; Trull, Timothy J; Willemsen, Gonneke; Vink, Jacqueline M; Derom, Catherine A; Lynskey, Michael; Martin, Nicholas G; Boomsma, Dorret I

    2009-12-15

    Recently, the nature of personality disorders and their relationship with normal personality traits has received extensive attention. The five-factor model (FFM) of personality, consisting of the personality traits neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness, is one of the proposed models to conceptualize personality disorders as maladaptive variants of continuously distributed personality traits. The present study examined the phenotypic and genetic association between borderline personality and FFM personality traits. Data were available for 4403 monozygotic twins, 4425 dizygotic twins, and 1661 siblings from 6140 Dutch, Belgian, and Australian families. Broad-sense heritability estimates for neuroticism, agreeableness, conscientiousness, extraversion, openness to experience, and borderline personality were 43%, 36%, 43%, 47%, 54%, and 45%, respectively. Phenotypic correlations between borderline personality and the FFM personality traits ranged from .06 for openness to experience to .68 for neuroticism. Multiple regression analyses showed that a combination of high neuroticism and low agreeableness best predicted borderline personality. Multivariate genetic analyses showed the genetic factors that influence individual differences in neuroticism, agreeableness, conscientiousness, and extraversion account for all genetic liability to borderline personality. Unique environmental effects on borderline personality, however, were not completely shared with those for the FFM traits (33% is unique to borderline personality). Borderline personality shares all genetic variation with neuroticism, agreeableness, conscientiousness, and extraversion. The unique environmental influences specific to borderline personality may cause individuals with a specific pattern of personality traits to cross a threshold and develop borderline personality.

  7. An analysis of a three-factor model proposed by the Danish Society of Actuaries for forecasting and risk analysis

    OpenAIRE

    Jørgensen, Peter Løchte; Slipsager, Søren Kærgaard

    2016-01-01

    This paper provides the explicit solution to the three-factor diffusion model recently proposed by the Danish Society of Actuaries to the Danish industry of life insurance and pensions. The solution is obtained by use of the known general solution to multidimensional linear stochastic differential equation systems. With offset in the explicit solution, we establish the conditional distribution of the future state variables which allows for exact simulation. Using exact simulation, we illustra...

  8. A fractal model of effective stress of porous media and the analysis of influence factors

    Science.gov (United States)

    Li, Wei; Zhao, Huan; Li, Siqi; Sun, Wenfeng; Wang, Lei; Li, Bing

    2018-03-01

    The basic concept of effective stress describes the characteristics of fluid and solid interaction in porous media. In this paper, based on the theory of fractal geometry, a fractal model was built to analyze the relationship between the microstructure and the effective stress of porous media. From the microscopic point of view, the influence of effective stress on pore structure of porous media was demonstrated. Theoretical analysis and experimental results show that: (i) the fractal model of effective stress can be used to describe the relationship between effective stress and the microstructure of porous media; (ii) a linear increase in the effective stress leads to exponential increases in fractal dimension, porosity and pore number of the porous media, and causes a decreasing trend in the average pore radius.

  9. First course in factor analysis

    CERN Document Server

    Comrey, Andrew L

    2013-01-01

    The goal of this book is to foster a basic understanding of factor analytic techniques so that readers can use them in their own research and critically evaluate their use by other researchers. Both the underlying theory and correct application are emphasized. The theory is presented through the mathematical basis of the most common factor analytic models and several methods used in factor analysis. On the application side, considerable attention is given to the extraction problem, the rotation problem, and the interpretation of factor analytic results. Hence, readers are given a background of

  10. Model Correction Factor Method

    DEFF Research Database (Denmark)

    Christensen, Claus; Randrup-Thomsen, Søren; Morsing Johannesen, Johannes

    1997-01-01

    The model correction factor method is proposed as an alternative to traditional polynomial based response surface techniques in structural reliability considering a computationally time consuming limit state procedure as a 'black box'. The class of polynomial functions is replaced by a limit...... of the model correction factor method, is that in simpler form not using gradient information on the original limit state function or only using this information once, a drastic reduction of the number of limit state evaluation is obtained together with good approximations on the reliability. Methods...

  11. Higher Education End-of-Course Evaluations: Assessing the Psychometric Properties Utilizing Exploratory Factor Analysis and Rasch Modeling Approaches

    Directory of Open Access Journals (Sweden)

    Kelly D. Bradley

    2016-07-01

    Full Text Available This paper offers a critical assessment of the psychometric properties of a standard higher education end-of-course evaluation. Using both exploratory factor analysis (EFA and Rasch modeling, the authors investigate the (a an overall assessment of dimensionality using EFA, (b a secondary assessment of dimensionality using a principal components analysis (PCA of the residuals when the items are fit to the Rasch model, and (c an assessment of item-level properties using item-level statistics provided when the items are fit to the Rasch model. The results support the usage of the scale as a supplement to high-stakes decision making such as tenure. However, the lack of precise targeting of item difficulty to person ability combined with the low person separation index renders rank-ordering professors according to minuscule differences in overall subscale scores a highly questionable practice.

  12. Topographic factor analysis: a Bayesian model for inferring brain networks from neural data.

    Directory of Open Access Journals (Sweden)

    Jeremy R Manning

    Full Text Available The neural patterns recorded during a neuroscientific experiment reflect complex interactions between many brain regions, each comprising millions of neurons. However, the measurements themselves are typically abstracted from that underlying structure. For example, functional magnetic resonance imaging (fMRI datasets comprise a time series of three-dimensional images, where each voxel in an image (roughly reflects the activity of the brain structure(s-located at the corresponding point in space-at the time the image was collected. FMRI data often exhibit strong spatial correlations, whereby nearby voxels behave similarly over time as the underlying brain structure modulates its activity. Here we develop topographic factor analysis (TFA, a technique that exploits spatial correlations in fMRI data to recover the underlying structure that the images reflect. Specifically, TFA casts each brain image as a weighted sum of spatial functions. The parameters of those spatial functions, which may be learned by applying TFA to an fMRI dataset, reveal the locations and sizes of the brain structures activated while the data were collected, as well as the interactions between those structures.

  13. Examining the Competition for Forest Resources in Sweden Using Factor Substitution Analysis and Partial Equilibrium Modelling

    Energy Technology Data Exchange (ETDEWEB)

    Olsson, Anna

    2011-07-01

    The overall objective of the thesis is to analyse the procurement competition for forest resources in Sweden. The thesis consists of an introductory part and two self-contained papers. In paper I a translog cost function approach is used to analyse the factor substitution in the sawmill industry, the pulp and paper industry and the heating industry in Sweden over the period 1970 to 2008. The estimated parameters are used to calculate the Allen and Morishima elasticities of substitution as well as the price elasticities of input demand. The utilisation of forest resources in the energy sector has been increasing and this increase is believed to continue. The increase is, to a large extent, caused by economic policies introduced to reduce the emission of greenhouse gases. Such policies could lead to an increase in the procurement competition between the forest industries and the energy sector. The calculated substitution elasticities indicate that it is easier for the heating industry to substitutes between by-products and logging residues than it is for the pulp and paper industry to substitute between by-products and roundwood. This suggests that the pulp and paper industry could suffer from an increase in the procurement competition. However, overall the substitutions elasticities estimated in our study are relatively low. This indicates that substitution possibilities could be rather limited due to rigidities in input prices. This result suggests that competition of forest resources also might be relatively limited. In paper II a partial equilibrium model is constructed in order to asses the effects an increasing utilisation of forest resources in the energy sector. The increasing utilisation of forest fuel is, to a large extent, caused by economic policies introduced to reduce the emission of greenhouse gases. In countries where forests already are highly utilised such policies will lead to an increase in the procurement competition between the forest sector and

  14. An Exploratory Analysis of Economic Factors in the Navy Total Force Strength Model (NTFSM)

    Science.gov (United States)

    2015-12-01

    the model incorporates (in the personnel calculations) econometric effects to Losses by Expiration of Active Obligated Service, Attrition, and Length...Incorporate econometric effects of losses by LOS and paygrade using parameters generated by the Navy Econometric Modeling System (NEMS) to the greatest...community- level models . (CAP9) • Model architecture will support hosting of model , scenarios, (inputs, user comments, etc.) and outputs in a secure

  15. A factor analysis of Functional Independence and Functional Assessment Measure scores among focal and diffuse brain injury patients: The importance of bi-factor models.

    Science.gov (United States)

    Gunn, Sarah; Burgess, Gerald H; Maltby, John

    2018-04-28

    To explore the factor structure of the UK Functional Independence Measure and Functional Assessment Measure (FIM+FAM) among focal and diffuse acquired brain injury patients. Criterion standard. An NHS acute acquired brain injury inpatient rehabilitation hospital. Referred sample of 447 adults (835 cases after exclusions) admitted for inpatient treatment following an acquired brain injury significant enough to justify intensive inpatient neurorehabilitation. Not applicable. Functional Independence Measure and Functional Assessment Measure. Exploratory Factor Analysis suggested a two-factor structure to FIM+FAM scores, among both focal-proximate and diffuse-proximate acquired brain injury aetiologies. Confirmatory Factor Analysis suggested a three-factor bi-factor structure presented the best fit of the FIM+FAM score data across both aetiologies. However, across both analyses, a convergence was found towards a general factor, demonstrated by high correlations between factors in the Exploratory Factor Analysis, and by a general factor explaining the majority of the variance in scores on Confirmatory Factor Analysis. Our findings suggested that although factors describing specific functional domains can be derived from FIM+FAM item scores, there is a convergence towards a single factor describing overall functioning. This single factor informs the specific group factors (e.g. motor, psychosocial and communication function) following brain injury. Further research into the comparative value of the general and group factors as evaluative/prognostic measures is indicated. Copyright © 2018. Published by Elsevier Inc.

  16. Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

    Science.gov (United States)

    Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

    2017-09-27

    Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (pregression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. Creative Commons Attribution License

  17. A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation

    International Nuclear Information System (INIS)

    Trucco, P.; Cagno, E.; Ruggeri, F.; Grande, O.

    2008-01-01

    The paper presents an innovative approach to integrate Human and Organisational Factors (HOF) into risk analysis. The approach has been developed and applied to a case study in the maritime industry, but it can also be utilised in other sectors. A Bayesian Belief Network (BBN) has been developed to model the Maritime Transport System (MTS), by taking into account its different actors (i.e., ship-owner, shipyard, port and regulator) and their mutual influences. The latter have been modelled by means of a set of dependent variables whose combinations express the relevant functions performed by each actor. The BBN model of the MTS has been used in a case study for the quantification of HOF in the risk analysis carried out at the preliminary design stage of High Speed Craft (HSC). The study has focused on a collision in open sea hazard carried out by means of an original method of integration of a Fault Tree Analysis (FTA) of technical elements with a BBN model of the influences of organisational functions and regulations, as suggested by the International Maritime Organisation's (IMO) Guidelines for Formal Safety Assessment (FSA). The approach has allowed the identification of probabilistic correlations between the basic events of a collision accident and the BBN model of the operational and organisational conditions. The linkage can be exploited in different ways, especially to support identification and evaluation of risk control options also at the organisational level. Conditional probabilities for the BBN have been estimated by means of experts' judgments, collected from an international panel of different European countries. Finally, a sensitivity analysis has been carried out over the model to identify configurations of the MTS leading to a significant reduction of accident probability during the operation of the HSC

  18. Latent variable models an introduction to factor, path, and structural equation analysis

    CERN Document Server

    Loehlin, John C

    2004-01-01

    This fourth edition introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. The book is intended for advanced students and researchers in the areas of social, educational, clinical, ind

  19. Dynamics Modelling of Transmission Gear Rattle and Analysis on Influence Factors

    Science.gov (United States)

    He, Xiaona; Zhang, Honghui

    2018-02-01

    Based on the vibration dynamics modeling for the single stage gear of transmission system, this paper is to understand the mechanism of transmission rattle. The dynamic model response using MATLAB and Runge-Kutta algorithm is analyzed, and the ways for reducing the rattle noise of the automotive transmission is summarized.

  20. Building a Model of Employee Training through Holistic Analysis of Biological, Psychological, and Sociocultural Factors

    Science.gov (United States)

    Schenck, Andrew

    2015-01-01

    While theories of adult learning and motivation are often framed as being either biological, psychological, or sociocultural, they represent a more complex, integral process. To gain a more holistic perspective of this process, a study was designed to concurrently investigate relationships between a biological factor (age), psychological factors…

  1. Factors Associated with Increased Pain in Primary Dysmenorrhea: Analysis Using a Multivariate Ordered Logistic Regression Model.

    Science.gov (United States)

    Tomás-Rodríguez, María I; Palazón-Bru, Antonio; Martínez-St John, Damian R J; Navarro-Cremades, Felipe; Toledo-Marhuenda, José V; Gil-Guillén, Vicente F

    2017-04-01

    In the literature about primary dysmenorrhea (PD), either a pain gradient has been studied just in women with PD or pain was assessed as a binary variable (presence or absence). Accordingly, we decided to carry out a study in young women to determine possible factors associated with intense pain. A cross-sectional observational study. A Spanish University in 2016. A total of 306 women, aged 18-30 years. A questionnaire was filled in by the participants to assess associated factors with dysmenorrhoea. Our outcome measure was the Andersch and Milsom scale (grade from 0 to 3). grade 0 (menstruation is not painful and daily activity is unaffected), grade 1 (menstruation is painful but seldom inhibits normal activity, analgesics are seldom required, and mild pain), grade 2 (daily activity affected, analgesics required and give relief so that absence from work or school is unusual, and moderate pain), and grade 3 (activity clearly inhibited, poor effect of analgesics, vegetative symptoms and severe pain). Factors significantly associated with more extreme pain: a higher menstrual flow (odds ratio [OR], 2.11; P < .001), a worse quality of life (OR, 0.97; P < .001) and use of medication for PD (OR, 8.22; P < .001). We determined factors associated with extreme pain in PD in a novel way. Further studies are required to corroborate our results. Copyright © 2016 North American Society for Pediatric and Adolescent Gynecology. Published by Elsevier Inc. All rights reserved.

  2. "Factor Analysis Using ""R"""

    Directory of Open Access Journals (Sweden)

    A. Alexander Beaujean

    2013-02-01

    Full Text Available R (R Development Core Team, 2011 is a very powerful tool to analyze data, that is gaining in popularity due to its costs (its free and flexibility (its open-source. This article gives a general introduction to using R (i.e., loading the program, using functions, importing data. Then, using data from Canivez, Konold, Collins, and Wilson (2009, this article walks the user through how to use the program to conduct factor analysis, from both an exploratory and confirmatory approach.

  3. Identification and analysis of explanatory variables for a multi-factor productivity model of passenger airlines

    Directory of Open Access Journals (Sweden)

    Antonio Henriques de Araújo Jr

    2011-05-01

    Full Text Available The paper aimed to identify and analyze the explanatory variables for airlines productivity during 2000 2005, by testing the Pearson correlation between the single factor productivity capital, energy and labor of a sample of 45 selected international airlines (4 Brazilian carriers among them and their productivity explanatory variables like medium stage length, aircraft load factor, hours flown and cruise speed for selected routes besides aircraft seat configuration and airlines number of employees. The research demonstrated, that a set of variables can explain differences in productivity for passenger airlines, such as: investment in personnel training processes, automation, airplane seat density, occupation of aircraft, average flight stage length, density and extension of routes, among others.

  4. Tertiary Students ’ Entrepreneurship Learning Socialization : Factor Analysis and Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Chun- Mei Chou

    2015-09-01

    Full Text Available This study examines 728 tertiary students’ entrepreneurship learning socialization and its influencing factors to serve as a school reference for the development of internship and entrepreneurship education. The results show that students’ internship experience has a significant direct effect on entrepreneurship learning socialization, and entrepreneurship intention has a significant effect on entrepreneurship learning socialization through internship experience. The influence pattern and empirical data of entrepreneurship intention and internship experience on entrepreneurship learning socialization has a good fit. This paper gives an insight from Taiwan tertiary institutions about entrepreneurial learning socialization of students and contributions to them. We describe the development of the influencing factors, discuss its implications for entrepreneurship and internship education, and finally offer suggestions for further entrepreneurship education development.

  5. Modeling of the corium cooling and loading factor analysis for containment during severe accidents

    International Nuclear Information System (INIS)

    Konoval, A.V.; Kalvand, Ali.; Kazachkov, I.V.

    2013-01-01

    The paper is devoted to the development and study of the mathematical model for corium melt interaction with low-temperature melting blocks in the passive protection systems (PPS) against severe accidents at the NPP, and learning the peculiarities of construction and operation of the PPS. The configurations of cooling blocks' distributions considered and the results of their work in the corium cooling pool are compared to the data of other PPS's conceptions. The conclusion is made that the models developed and the results obtained may be useful for constructing the PPS against severe accidents

  6. Modeling of the corium cooling and loading factor analysis for containment during severe accidents

    Directory of Open Access Journals (Sweden)

    O. V. Konoval

    2013-09-01

    Full Text Available The paper is devoted to the development and study of the mathematical model for corium melt interaction with low-temperature melting blocks in the passive protection systems (PPS against severe accidents at the NPP, and learning the peculiarities of construction and operation of the PPS. The configurations of cooling blocks’ distributions considered and the results of their work in the corium cooling pool are compared to the data of oth-er PPS’s conceptions. The conclusion is made that the models developed and the results obtained may be useful for constructing the PPS against severe accidents.

  7. The Two- and Three-Dimensional Models of the HK-WISC: A Confirmatory Factor Analysis.

    Science.gov (United States)

    Chan, David W.; Lin, Wen-Ying

    1996-01-01

    Confirmatory analyses on the Hong Kong Wechsler Intelligence Scale for Children (HK-WISC) provided support for composite score interpretation based on the two- and three-dimensional models across age levels. Test sample was comprised of 1,100 children, ranging in age from 5 to 15 years at all 11 age levels specified by the HK-WISC. (KW)

  8. Factor Analysis of the HEW National Strategy for Youth Development Model's Community Program Impact Scales.

    Science.gov (United States)

    Truckenmiller, James L.

    The former HEW (Health, Education, and Welfare) National Strategy for Youth Development Model proposed a community-based program to promote positive youth development and to prevent delinquency through a sequence of youth needs assessments, needs-targeted programs, and program impact evaluation. HEW Community Program Impact Scales data obtained…

  9. Cross-Cultural Validation of Models of Approaches to Learning: An Application of Confirmatory Factor Analysis.

    Science.gov (United States)

    Wong, Ngai-Ying; Lin, Wen-Ying; Watkins, David

    1996-01-01

    Analyzes responses to a questionnaire from 10 samples of primary and secondary school students from Nigeria, Zimbabwe, Malaysia, Beijing, Hong Kong, and Canada. The questionnaire covered learning strategies, approaches, and motivation. These data were then analyzed using six different structural equation models. Includes discussion of the models…

  10. The analysis of factors of management of safety of critical information infrastructure with use of dynamic models

    Science.gov (United States)

    Trostyansky, S. N.; Kalach, A. V.; Lavlinsky, V. V.; Lankin, O. V.

    2018-03-01

    Based on the analysis of the dynamic model of panel data by region, including fire statistics for surveillance sites and statistics of a set of regional socio-economic indicators, as well as the time of rapid response of the state fire service to fires, the probability of fires in the surveillance sites and the risk of human death in The result of such fires from the values of the corresponding indicators for the previous year, a set of regional social-economics factors, as well as regional indicators time rapid response of the state fire service in the fire. The results obtained are consistent with the results of the application to the fire risks of the model of a rational offender. Estimation of the economic equivalent of human life from data on surveillance objects for Russia, calculated on the basis of the analysis of the presented dynamic model of fire risks, correctly agrees with the known literary data. The results obtained on the basis of the econometric approach to fire risks allow us to forecast fire risks at the supervisory sites in the regions of Russia and to develop management solutions to minimize such risks.

  11. Modeling and Finite Element Analysis of Load-Carrying Performance of a Wind Turbine Considering the Influence of Assembly Factors

    Directory of Open Access Journals (Sweden)

    Jianmei Wang

    2017-03-01

    Full Text Available In this work, a wind turbine shrink disk is used as the research object to investigate load-carrying performance of a multi-layer interference fit, and the theoretical model and finite element model are constructed. According to those models, a MW-level turbine shrink disk is designed, and a test device is developed to apply torque to this turbine shrink disk by hydraulic jack. Then, the circumferential slip between the contact surfaces is monitored and the slip of all contact surfaces is zero. This conclusion verifies the reasonability of the proposed models. The effect of the key influencing factors, such as machining deviation, assembly clearance and propel stroke, were analyzed. The contact pressure and load torque of the mating surfaces were obtained by building typical models with different parameters using finite element analysis (FEA. The results show that the minimum assembly clearance and the machining deviation within the machining range have little influence on load-carrying performance of multi-layer interference fit, while having a greater influence on the maximum assembly clearance and the propel stroke. The results also show that the load-carrying performance of a multiple-layer interference fit can be ensured only if the key factors are set within a reasonable design range. To avoid the abnormal operation of equipment caused by insufficient load torque, the propel stroke during practical assembly should be at least 0.95 times the designed propel stroke, which is significant in guiding the design and assembly of the multi-layer interference fit.

  12. Computational Modelling Approaches on Epigenetic Factors in Neurodegenerative and Autoimmune Diseases and Their Mechanistic Analysis

    Directory of Open Access Journals (Sweden)

    Afroza Khanam Irin

    2015-01-01

    Full Text Available Neurodegenerative as well as autoimmune diseases have unclear aetiologies, but an increasing number of evidences report for a combination of genetic and epigenetic alterations that predispose for the development of disease. This review examines the major milestones in epigenetics research in the context of diseases and various computational approaches developed in the last decades to unravel new epigenetic modifications. However, there are limited studies that systematically link genetic and epigenetic alterations of DNA to the aetiology of diseases. In this work, we demonstrate how disease-related epigenetic knowledge can be systematically captured and integrated with heterogeneous information into a functional context using Biological Expression Language (BEL. This novel methodology, based on BEL, enables us to integrate epigenetic modifications such as DNA methylation or acetylation of histones into a specific disease network. As an example, we depict the integration of epigenetic and genetic factors in a functional context specific to Parkinson’s disease (PD and Multiple Sclerosis (MS.

  13. Assessing the discriminating power of item and test scores in the linear factor-analysis model

    Directory of Open Access Journals (Sweden)

    Pere J. Ferrando

    2012-01-01

    Full Text Available Las propuestas rigurosas y basadas en un modelo psicométrico para estudiar el impreciso concepto de "capacidad discriminativa" son escasas y generalmente limitadas a los modelos no-lineales para items binarios. En este artículo se propone un marco general para evaluar la capacidad discriminativa de las puntuaciones en ítems y tests que son calibrados mediante el modelo de un factor común. La propuesta se organiza en torno a tres criterios: (a tipo de puntuación, (b rango de discriminación y (c aspecto específico que se evalúa. Dentro del marco propuesto: (a se discuten las relaciones entre 16 medidas, de las cuales 6 parecen ser nuevas, y (b se estudian las relaciones entre ellas. La utilidad de la propuesta en las aplicaciones psicométricas que usan el modelo factorial se ilustra mediante un ejemplo empírico.

  14. A general psychopathology factor (P factor) in children: Structural model analysis and external validation through familial risk and child global executive function.

    Science.gov (United States)

    Martel, Michelle M; Pan, Pedro M; Hoffmann, Maurício S; Gadelha, Ary; do Rosário, Maria C; Mari, Jair J; Manfro, Gisele G; Miguel, Eurípedes C; Paus, Tomás; Bressan, Rodrigo A; Rohde, Luis A; Salum, Giovanni A

    2017-01-01

    High rates of comorbidities and poor validity of disorder diagnostic criteria for mental disorders hamper advances in mental health research. Recent work has suggested the utility of continuous cross-cutting dimensions, including general psychopathology and specific factors of externalizing and internalizing (e.g., distress and fear) syndromes. The current study evaluated the reliability of competing structural models of psychopathology and examined external validity of the best fitting model on the basis of family risk and child global executive function (EF). A community sample of 8,012 families from Brazil with children ages 6-12 years completed structured interviews about the child and parental psychiatric syndromes, and a subsample of 2,395 children completed tasks assessing EF (i.e., working memory, inhibitory control, and time processing). Confirmatory factor analyses tested a series of structural models of psychopathology in both parents and children. The model with a general psychopathology factor ("P factor") with 3 specific factors (fear, distress, and externalizing) exhibited the best fit. The general P factor accounted for most of the variance in all models, with little residual variance explained by each of the 3 specific factors. In addition, associations between child and parental factors were mainly significant for the P factors and nonsignificant for the specific factors from the respective models. Likewise, the child P factor-but not the specific factors-was significantly associated with global child EF. Overall, our results provide support for a latent overarching P factor characterizing child psychopathology, supported by familial associations and child EF. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  15. Climatic factors controlling the productivity of pine stands. A model-based analysis

    International Nuclear Information System (INIS)

    McMurtrie, R.E.; Gholz, H.L.; Linder, S.; Gower, S.T.

    1994-01-01

    A process-based forest growth model, BIOMASS, is applied to stands of four pine species (Pinus elliottii, P. radiata, P. resinosa, and P. sylvestris) growing in five sub-tropical, temperate and boreal environments (in Australia, New Zealand, Florida, Sweden and Wisconsin). Measured annual above-ground net primary production (ANPP) at these sites ranges from 0.2 to 1.6 kg C m -2 . After establishing that simulated ANPP closely matches biomass production measured for the various stands, we analyse model runs to relate simulated productivity to absorbed photosynthetically-active radiation (APAR). Annual photosynthetic productivity (or gross primary production, GPP) simulated for the five stands is linearly related to utilizable APAR, derived by estimating the extent to which photosynthesis is limited by soil water deficit, high air saturation vapor deficit or low temperature. The reduction of GPP due to incomplete radiation interception is 10 to 25% for stands with high leaf area index (LAI) in Australia, New Zealand and Wisconsin and 50 to 60% for low LAI stands in Florida and Sweden. Gross carbon gain is reduced by a further 50 to 70% at sites experiencing cold winters (Sweden and Wisconsin), summer drought (Australia) or high summer humidity deficits (Australia and Wisconsin). Simulated carbon losses due to above-ground respiration average 50% of GPP, but are highly variable among the sites due to large differences in live biomass and tissue nitrogen concentrations. This results in a weaker relationship between simulated NPP and APAR. (au) 93 refs

  16. Model of T-Type Fracture in Coal Fracturing and Analysis of Influence Factors of Fracture Morphology

    Directory of Open Access Journals (Sweden)

    Yuwei Li

    2018-05-01

    Full Text Available Special T-type fractures can be formed when coal is hydraulically fractured and there is currently no relevant theoretical model to calculate and describe them. This paper first establishes the height calculation model of vertical fractures in multi-layered formations and deduces the stress intensity factor (SIF at the upper and lower sides of the fracture in the process of vertical fracture extension. Combined with the fracture tip stress analysis method of fracture mechanics theory, the horizontal bedding is taken into account for tensile and shear failure, and the critical mechanical conditions for the formation of horizontal fracture in coal are obtained. Finally, the model of T-type fracture in coal fracturing is established, and it is verified by fracturing simulation experiments. The model calculation result shows that the increase of vertical fracture height facilitates the increase of horizontal fracture length. The fracture toughness of coal has a significant influence on the length of horizontal fracture and there is a threshold. When the fracture toughness is less than the threshold, the length of horizontal fracture remains unchanged, otherwise, the length of horizontal fracture increases rapidly with the increase of fracture toughness. When the shear strength of the interface between the coalbed and the interlayer increases, the length of the horizontal fracture of the T-type fracture rapidly decreases.

  17. Confirmatory factor analysis of Post-Occupancy Evaluation Model (POEM) for sustainable neighborhood development

    Science.gov (United States)

    Yaman, R.; Thadaniti, S.; Abdullah, J.; Ahmad, N.; Ishak, N. M.

    2018-02-01

    The sustainable urban development growth in the ASEAN region has accelerated tremendously. More demand on the sustainable development has led to bigger market driven certified green neighborhood and buildings. However, there is a lack of post-occupancy evaluation study conducted in assessing the end-users perspective on the certified sustainable neighborhood development. This paper aims to investigate the end-users point of view on sustainable dimension pillar (SDP) adaptation based on environment dimension, social dimension and economic dimension using Post-Occupancy Evaluation Model (POEM) framework. The research methodology employed stakeholders-Inclusion Approach survey questionnaires in order to obtained the sustainable dimensional adaptation score. The results show that there is sustainable dimension gap in POEM evaluation, hence, suggested the pre- occupancy criteria did not fulfill the SDP adaptation and pre-occupancy criteria and variables if differ from post-occupancy criteria and variables.

  18. Factors influencing adoption of farm management practices in three agrobiodiversity hotspots in India: an analysis using the Count Data Model

    Directory of Open Access Journals (Sweden)

    Prabhakaran T. Raghu

    2014-07-01

    Full Text Available Sustainable agricultural practices require, among other factors, adoption of improved nutrient management techniques, pest mitigation technology and soil conservation measures. Such improved management practices can be tools for enhancing crop productivity. Data on micro-level farm management practices from developing countries is either scarce or unavailable, despite the importance of their policy implications with regard to resource allocation. The present study investigates adoption of some farm management practices and factors influencing the adoption behavior of farm households in three agrobiodiversity hotspots in India: Kundra block in the Koraput district of Odisha, Meenangadi panchayat in the Wayanad district of Kerala and Kolli Hills in the Namakkal district of Tamil Nadu. Information on farm management practices was collected from November 2011 to February 2012 from 3845 households, of which the data from 2726 farm households was used for analysis. The three most popular farm management practices adopted by farmers include: application of chemical fertilizers, farm yard manure and green manure for managing nutrients; application of chemical pesticides, inter-cropping and mixed cropping for mitigating pests; and contour bunds, grass bunds and trenches for soil conservation. A Negative Binomial count data regression model was used to estimate factors influencing decision-making by farmers on farm management practices. The regression results indicate that farmers who received information from agricultural extension are statistically significant and positively related to the adoption of farm management practices. Another key finding shows the negative relationship between cultivation of local varieties and adoption of farm management practices.

  19. Analysis of the Factors Affecting the Interval between Blood Donations Using Log-Normal Hazard Model with Gamma Correlated Frailties.

    Science.gov (United States)

    Tavakol, Najmeh; Kheiri, Soleiman; Sedehi, Morteza

    2016-01-01

    Time to donating blood plays a major role in a regular donor to becoming continues one. The aim of this study was to determine the effective factors on the interval between the blood donations. In a longitudinal study in 2008, 864 samples of first-time donors in Shahrekord Blood Transfusion Center,  capital city of Chaharmahal and Bakhtiari Province, Iran were selected by a systematic sampling and were followed up for five years. Among these samples, a subset of 424 donors who had at least two successful blood donations were chosen for this study and the time intervals between their donations were measured as response variable. Sex, body weight, age, marital status, education, stay and job were recorded as independent variables. Data analysis was performed based on log-normal hazard model with gamma correlated frailty. In this model, the frailties are sum of two independent components assumed a gamma distribution. The analysis was done via Bayesian approach using Markov Chain Monte Carlo algorithm by OpenBUGS. Convergence was checked via Gelman-Rubin criteria using BOA program in R. Age, job and education were significant on chance to donate blood (Pdonation for the higher-aged donors, clericals, workers, free job, students and educated donors were higher and in return, time intervals between their blood donations were shorter. Due to the significance effect of some variables in the log-normal correlated frailty model, it is necessary to plan educational and cultural program to encourage the people with longer inter-donation intervals to donate more frequently.

  20. Water Use Efficiency and Its Influencing Factors in China: Based on the Data Envelopment Analysis (DEA—Tobit Model

    Directory of Open Access Journals (Sweden)

    Shuqiao Wang

    2018-06-01

    Full Text Available Water resources are important and irreplaceable natural and economic resources. Achieving a balance between economic prosperity and protection of water resource environments is a major issue in China. This article develops a data envelopment analysis (DEA approach with undesirable outputs by using Seiford’s linear converting method to estimate water use efficiencies for 30 provinces in China, from 2008–2016,and then analyzes the influencing factors while using a DEA-Tobit model. The findings show that the overall water use efficiency of the measured Chinese provinces, when considering sewage emissions as the undesirable output, is 0.582. Thus, most regions still need improvement. Provinces with the highest water efficiency are located in economically developed Eastern China. The spatial pattern of water use efficiency in China is consistent with the general pattern of regional economic development. This study implies that factors like export dependence, technical progress, and educational value have a positive influence on water use efficiency. Further, while industrial structure has had a negative impact, government intervention has had little impact on water use efficiency. These research results will provide a scientific basis for the government to make plans for water resource development, and it may be helpful in improving regional sustainable development.

  1. Factors affecting construction performance: exploratory factor analysis

    Science.gov (United States)

    Soewin, E.; Chinda, T.

    2018-04-01

    The present work attempts to develop a multidimensional performance evaluation framework for a construction company by considering all relevant measures of performance. Based on the previous studies, this study hypothesizes nine key factors, with a total of 57 associated items. The hypothesized factors, with their associated items, are then used to develop questionnaire survey to gather data. The exploratory factor analysis (EFA) was applied to the collected data which gave rise 10 factors with 57 items affecting construction performance. The findings further reveal that the items constituting ten key performance factors (KPIs) namely; 1) Time, 2) Cost, 3) Quality, 4) Safety & Health, 5) Internal Stakeholder, 6) External Stakeholder, 7) Client Satisfaction, 8) Financial Performance, 9) Environment, and 10) Information, Technology & Innovation. The analysis helps to develop multi-dimensional performance evaluation framework for an effective measurement of the construction performance. The 10 key performance factors can be broadly categorized into economic aspect, social aspect, environmental aspect, and technology aspects. It is important to understand a multi-dimension performance evaluation framework by including all key factors affecting the construction performance of a company, so that the management level can effectively plan to implement an effective performance development plan to match with the mission and vision of the company.

  2. Study of Factors Preventing Children from Enrolment in Primary School in the Republic of Honduras: Analysis Using Structural Equation Modelling

    Science.gov (United States)

    Ashida, Akemi

    2015-01-01

    Studies have investigated factors that impede enrolment in Honduras. However, they have not analysed individual factors as a whole or identified the relationships among them. This study used longitudinal data for 1971 children who entered primary schools from 1986 to 2000, and employed structural equation modelling to examine the factors…

  3. Reliability Analysis of Offshore Jacket Structures with Wave Load on Deck using the Model Correction Factor Method

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Friis-Hansen, P.; Nielsen, J.S.

    2006-01-01

    failure/collapse of jacket type platforms with wave in deck loads using the so-called Model Correction Factor Method (MCFM). A simple representative model for the RSR measure is developed and used in the MCFM technique. A realistic example is evaluated and it is seen that it is possible to perform...

  4. Three-dimensional flow analysis and improvement of slip factor model for forward-curved blades centrifugal fan

    International Nuclear Information System (INIS)

    Guo, En Min; Kim, Kwang Yong

    2004-01-01

    This work developed improved slip factor model and correction method to predict flow through impeller in forward-curved centrifugal fan. Both steady and unsteady three-dimensional CFD analyses were performed to validate the slip factor model and the correction method. The results show that the improved slip factor model presented in this paper could provide more accurate predictions for forward-curved centrifugal impeller than the other slip factor models since the present model takes into account the effect of blade curvature. The correction method is provided to predict mass-averaged absolute circumferential velocity at the exit of impeller by taking account of blockage effects induced by the large-scale backflow near the front plate and flow separation within blade passage. The comparison with CFD results also shows that the improved slip factor model coupled with the present correction method provides accurate predictions for mass-averaged absolute circumferential velocity at the exit of impeller near and above the flow rate of peak total pressure coefficient

  5. The joint return period analysis of natural disasters based on monitoring and statistical modeling of multidimensional hazard factors

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Xueqin [State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875 (China); National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023 (China); School of Social Development and Public Policy, Beijing Normal University, Beijing 100875 (China); Li, Ning [State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875 (China); Yuan, Shuai, E-mail: syuan@nmemc.org.cn [National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023 (China); Xu, Ning; Shi, Wenqin; Chen, Weibin [National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023 (China)

    2015-12-15

    As a random event, a natural disaster has the complex occurrence mechanism. The comprehensive analysis of multiple hazard factors is important in disaster risk assessment. In order to improve the accuracy of risk analysis and forecasting, the formation mechanism of a disaster should be considered in the analysis and calculation of multi-factors. Based on the consideration of the importance and deficiencies of multivariate analysis of dust storm disasters, 91 severe dust storm disasters in Inner Mongolia from 1990 to 2013 were selected as study cases in the paper. Main hazard factors from 500-hPa atmospheric circulation system, near-surface meteorological system, and underlying surface conditions were selected to simulate and calculate the multidimensional joint return periods. After comparing the simulation results with actual dust storm events in 54 years, we found that the two-dimensional Frank Copula function showed the better fitting results at the lower tail of hazard factors and that three-dimensional Frank Copula function displayed the better fitting results at the middle and upper tails of hazard factors. However, for dust storm disasters with the short return period, three-dimensional joint return period simulation shows no obvious advantage. If the return period is longer than 10 years, it shows significant advantages in extreme value fitting. Therefore, we suggest the multivariate analysis method may be adopted in forecasting and risk analysis of serious disasters with the longer return period, such as earthquake and tsunami. Furthermore, the exploration of this method laid the foundation for the prediction and warning of other nature disasters. - Highlights: • A method to estimate the multidimensional joint return periods is presented. • 2D function allows better fitting results at the lower tail of hazard factors. • Three-dimensional simulation has obvious advantages in extreme value fitting. • Joint return periods are closer to the reality

  6. The joint return period analysis of natural disasters based on monitoring and statistical modeling of multidimensional hazard factors

    International Nuclear Information System (INIS)

    Liu, Xueqin; Li, Ning; Yuan, Shuai; Xu, Ning; Shi, Wenqin; Chen, Weibin

    2015-01-01

    As a random event, a natural disaster has the complex occurrence mechanism. The comprehensive analysis of multiple hazard factors is important in disaster risk assessment. In order to improve the accuracy of risk analysis and forecasting, the formation mechanism of a disaster should be considered in the analysis and calculation of multi-factors. Based on the consideration of the importance and deficiencies of multivariate analysis of dust storm disasters, 91 severe dust storm disasters in Inner Mongolia from 1990 to 2013 were selected as study cases in the paper. Main hazard factors from 500-hPa atmospheric circulation system, near-surface meteorological system, and underlying surface conditions were selected to simulate and calculate the multidimensional joint return periods. After comparing the simulation results with actual dust storm events in 54 years, we found that the two-dimensional Frank Copula function showed the better fitting results at the lower tail of hazard factors and that three-dimensional Frank Copula function displayed the better fitting results at the middle and upper tails of hazard factors. However, for dust storm disasters with the short return period, three-dimensional joint return period simulation shows no obvious advantage. If the return period is longer than 10 years, it shows significant advantages in extreme value fitting. Therefore, we suggest the multivariate analysis method may be adopted in forecasting and risk analysis of serious disasters with the longer return period, such as earthquake and tsunami. Furthermore, the exploration of this method laid the foundation for the prediction and warning of other nature disasters. - Highlights: • A method to estimate the multidimensional joint return periods is presented. • 2D function allows better fitting results at the lower tail of hazard factors. • Three-dimensional simulation has obvious advantages in extreme value fitting. • Joint return periods are closer to the reality

  7. Using Structured Additive Regression Models to Estimate Risk Factors of Malaria: Analysis of 2010 Malawi Malaria Indicator Survey Data

    Science.gov (United States)

    Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

    2014-01-01

    Background After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. Methods We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Results Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. Conclusions The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities. PMID:24991915

  8. Confirmatory Factor Analysis of U.S. Merit Systems Protection Board's Survey of Sexual Harassment: The Fit of a Three-Factor Model.

    Science.gov (United States)

    Stockdale, Margaret S.; Hope, Kathryn G.

    1997-01-01

    Factor analysis of data from 1,070 federal employees, 575 undergraduates and 575 graduate students, faculty, and staff uncovered some weaknesses in the Merit Systems Protection Board's sexual harassment survey instrument. This type of survey does not adequately measure sexual coercion or quid pro quo forms of harassment. (SK)

  9. Validity of observer ratings of the five-factor model of personality traits: a meta-analysis.

    Science.gov (United States)

    Oh, In-Sue; Wang, Gang; Mount, Michael K

    2011-07-01

    Conclusions reached in previous research about the magnitude and nature of personality-performance linkages have been based almost exclusively on self-report measures of personality. The purpose of this study is to address this void in the literature by conducting a meta-analysis of the relationship between observer ratings of the five-factor model (FFM) personality traits and overall job performance. Our results show that the operational validities of FFM traits based on observer ratings are higher than those based on self-report ratings. In addition, the results show that when based on observer ratings, all FFM traits are significant predictors of overall performance. Further, observer ratings of FFM traits show meaningful incremental validity over self-reports of corresponding FFM traits in predicting overall performance, but the reverse is not true. We conclude that the validity of FFM traits in predicting overall performance is higher than previously believed, and our results underscore the importance of disentangling the validity of personality traits from the method of measurement of the traits.

  10. Quantitative Analysis of Mixtures of Monoprotic Acids Applying Modified Model-Based Rank Annihilation Factor Analysis on Variation Matrices of Spectrophotometric Acid-Base Titrations

    Directory of Open Access Journals (Sweden)

    Ebrahim Ghorbani-Kalhor

    2015-04-01

    Full Text Available In the current work, a new version of rank annihilation factor analysis was developedto circumvent the rank deficiency problem in multivariate data measurements.Simultaneous determination of dissociation constant and concentration of monoprotic acids was performed by applying model-based rank annihilation factor analysis on variation matrices of spectrophotometric acid-base titrations data. Variation matrices can be obtained by subtracting first row of data matrix from all rows of the main data matrix. This method uses variation matrices instead of multivariate spectrophotometric acid-base titrations matrices to circumvent the rank deficiency problem in the rank quantitation step. The applicability of this approach was evaluated by simulated data at first stage, then the binary mixtures of ascorbic and sorbic acids as model compounds were investigated by the proposed method. At the end, the proposed method was successfully applied for resolving the ascorbic and sorbic acid in an orange juice real sample. Therefore, unique results were achieved by applying rank annihilation factor analysis on variation matrix and using hard soft model combination advantage without any problem and difficulty in rank determination. Normal 0 false false false EN-US X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi; mso-bidi-language:AR-SA;}    

  11. Factor analysis of multivariate data

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Mahadevan, R.

    A brief introduction to factor analysis is presented. A FORTRAN program, which can perform the Q-mode and R-mode factor analysis and the singular value decomposition of a given data matrix is presented in Appendix B. This computer program, uses...

  12. Choice Model and Influencing Factor Analysis of Travel Mode for Migrant Workers: Case Study in Xi’an, China

    OpenAIRE

    Hong Chen; Zuo-xian Gan; Yu-ting He

    2015-01-01

    Based on the basic theory and methods of disaggregate choice model, the influencing factors in travel mode choice for migrant workers are analyzed, according to 1366 data samples of Xi’an migrant workers. Walking, bus, subway, and taxi are taken as the alternative parts of travel modes for migrant workers, and a multinomial logit (MNL) model of travel mode for migrant workers is set up. The validity of the model is verified by the hit rate, and the hit rates of four travel modes are all great...

  13. Attenuation Factors for B(E2) in the Microscopic Description of Multiphonon States ---A Simple Model Analysis---

    Science.gov (United States)

    Matsuyanagi, K.

    1982-05-01

    With an exactly solvable O(4) model of Piepenbring, Silvestre-Brac and Szymanski, we demonstrate that the attenuation factor for the B(E2) values, derived by the lowest-order approximation of the multiphonon method, takes excellent care of the kinematical anharmonicity effects, if multiphonon states are defined in the intrinsic subspace orthogonal to the pairing rotation. It is also shown that the other attenuation effect characterizing the interacting boson model is not a dominant effect in the model analysed here.

  14. Shell model and spectroscopic factors

    International Nuclear Information System (INIS)

    Poves, P.

    2007-01-01

    In these lectures, I introduce the notion of spectroscopic factor in the shell model context. A brief review is given of the present status of the large scale applications of the Interacting Shell Model. The spectroscopic factors and the spectroscopic strength are discussed for nuclei in the vicinity of magic closures and for deformed nuclei. (author)

  15. Tracking senescence-induced patterns in leaf litter leachate using parallel factor analysis (PARAFAC) modeling and self-organizing maps

    Science.gov (United States)

    Wheeler, K. I.; Levia, D. F.; Hudson, J. E.

    2017-09-01

    In autumn, the dissolved organic matter (DOM) contribution of leaf litter leachate to streams in forested watersheds changes as trees undergo resorption, senescence, and leaf abscission. Despite its biogeochemical importance, little work has investigated how leaf litter leachate DOM changes throughout autumn and how any changes might differ interspecifically and intraspecifically. Since climate change is expected to cause vegetation migration, it is necessary to learn how changes in forest composition could affect DOM inputs via leaf litter leachate. We examined changes in leaf litter leachate fluorescent DOM (FDOM) from American beech (Fagus grandifolia Ehrh.) leaves in Maryland, Rhode Island, Vermont, and North Carolina and from yellow poplar (Liriodendron tulipifera L.) leaves from Maryland. FDOM in leachate samples was characterized by excitation-emission matrices (EEMs). A six-component parallel factor analysis (PARAFAC) model was created to identify components that accounted for the majority of the variation in the data set. Self-organizing maps (SOM) compared the PARAFAC component proportions of leachate samples. Phenophase and species exerted much stronger influence on the determination of a sample's SOM placement than geographic origin. As expected, FDOM from all trees transitioned from more protein-like components to more humic-like components with senescence. Percent greenness of sampled leaves and the proportion of tyrosine-like component 1 were found to be significantly different between the two genetic beech clusters, suggesting differences in photosynthesis and resorption. Our results highlight the need to account for interspecific and intraspecific variations in leaf litter leachate FDOM throughout autumn when examining the influence of allochthonous inputs to streams.

  16. Inclusion of climatic and touristic factors in the analysis and modelling of the municipal water demand in a Mediterranean region

    Science.gov (United States)

    Toth, Elena; Bragalli, Cristiana; Neri, Mattia

    2017-04-01

    In Mediterranean regions, inherently affected by water scarcity conditions, the gap between water availability and demand may further increase in the near future due to both climatic and anthropogenic drivers. In particular, the high degree of urbanization and the concentration of population and activities in coastal areas is often severely impacting the water availability also for the residential sector. It is therefore crucial analysing the importance of both climatic and touristic factors as drivers for the water demand in such areas, to better understand and model the expected consumption in order to improve the water management policies and practices. The study presents an analysis referred to a large number of municipalities, covering almost the whole Romagna region, in Northern Italy, representing one of the most economically developed areas in Europe and characterized by an extremely profitable tourist industry, especially in the coastal cities. For this region it is therefore extremely important to assess the significance of the drivers that may influence the demand in the different periods of the year, that is climatic factors (rainfall depths and occurrence, temperature averages and extremes), but also the presence of tourists, in both official tourist accommodation structures and in holidays homes (and the latter are very difficult to estimate). Analyses on the Italian water industry at seasonal or monthly time scale has been so far, extremely limited in the literature by the scarce availability of data on the water demands, that are made public only as annual volumes. All the study municipalities are supplied by the same water company, who provided monthly consumption volumes data at the main inlet points of the entire distribution network for a period of 7 years (2009-2015). For the same period, precipitation and temperature data have been collected and summarised in indexes representing monthly averages, days of occurrence and over threshold values

  17. Risk factors and visual fatigue of baggage X-ray security screeners: a structural equation modelling analysis.

    Science.gov (United States)

    Yu, Rui-Feng; Yang, Lin-Dong; Wu, Xin

    2017-05-01

    This study identified the risk factors influencing visual fatigue in baggage X-ray security screeners and estimated the strength of correlations between those factors and visual fatigue using structural equation modelling approach. Two hundred and five X-ray security screeners participated in a questionnaire survey. The result showed that satisfaction with the VDT's physical features and the work environment conditions were negatively correlated with the intensity of visual fatigue, whereas job stress and job burnout had direct positive influences. The path coefficient between the image quality of VDT and visual fatigue was not significant. The total effects of job burnout, job stress, the VDT's physical features and the work environment conditions on visual fatigue were 0.471, 0.469, -0.268 and -0.251 respectively. These findings indicated that both extrinsic factors relating to VDT and workplace environment and psychological factors including job burnout and job stress should be considered in the workplace design and work organisation of security screening tasks to reduce screeners' visual fatigue. Practitioner Summary: This study identified the risk factors influencing visual fatigue in baggage X-ray security screeners and estimated the strength of correlations between those factors and visual fatigue. The findings were of great importance to the workplace design and the work organisation of security screening tasks to reduce screeners' visual fatigue.

  18. Analysis of Influencing Factors of Water Footprint Based on the STIRPAT Model: Evidence from the Beijing Agricultural Sector

    Directory of Open Access Journals (Sweden)

    Chen Jin

    2016-11-01

    Full Text Available Beijing suffers from a severe water shortage. To find the key factors that impact the agricultural water footprint (WF within Beijing to relieve the pressure on water resources, this study quantifies the agricultural WF within Beijing from 1980 to 2012 and examines the factors of population, urbanization level, GDP per capita, Engel coefficient, and total rural power using an extended stochastic impact by regression on population, affluence and technology (STIRPAT model. Ridge regression is employed to fit the extended STIRPAT model. The empirical results reveal that the Engel coefficient, which is defined as the total amount of food expenses accounted for the proportion of total personal consumption expenditures, has the largest positive impact on the increase in the agricultural WF, followed by urbanization. In contrast, total rural power, population, and GDP per capita can decrease the agricultural WF. Finally, policy recommendations from technological development, agriculture plantation structure adjustment, and virtual water imports are provided to cope with water shortages.

  19. A Path Analysis Model Pertinent to Undergraduates' Academic Success: Examining Academic Confidence, Psychological Capital and Academic Coping Factors

    Science.gov (United States)

    Kirikkanat, Berke; Soyer, Makbule Kali

    2018-01-01

    The major purpose of this study was to create a path analysis model of academic success in a group of university students, which included the variables of academic confidence and psychological capital with a mediator variable--academic coping. 400 undergraduates from Marmara University and Istanbul Commerce University who were in sophomore, junior…

  20. Analysis of risk factors and the establishment of a risk model for peripherally inserted central catheter thrombosis

    OpenAIRE

    Fang Hu; Ruo-Nan Hao; Jie Zhang; Zhi-Cheng Ma

    2016-01-01

    Objective: To investigate the main risk factors of peripherally inserted central catheter (PICC) related upper extremity deep venous thrombosis and establish the risk predictive model of PICC-related upper extremity deep venous thrombosis. Methods: Patients with PICC who were hospitalized between January 2014 and July 2015 were studied retrospectively; they were divided into a thrombosis group (n = 52), with patients who had a venous thrombosis complication after PICC, and a no-thrombosis ...

  1. Exploratory Bi-Factor Analysis: The Oblique Case

    Science.gov (United States)

    Jennrich, Robert I.; Bentler, Peter M.

    2012-01-01

    Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford ("Psychometrika" 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler ("Psychometrika" 76:537-549, 2011) introduced an exploratory form of bi-factor…

  2. Nominal Performance Biosphere Dose Conversion Factor Analysis

    International Nuclear Information System (INIS)

    M. Wasiolek

    2004-01-01

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs for the groundwater exposure scenario for the three climate states considered in the TSPA-LA as well as conversion factors for evaluating compliance with the groundwater protection standard. The BDCFs will be used in performance assessment for calculating all-pathway annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle activity in groundwater and the annual dose

  3. Influencing Factors and Development Trend Analysis of China Electric Grid Investment Demand Based on a Panel Co-Integration Model

    Directory of Open Access Journals (Sweden)

    Jinchao Li

    2018-01-01

    Full Text Available Electric grid investment demand analysis is significant to reasonably arranging construction funds for the electric grid and reduce costs. This paper used the panel data of electric grid investment from 23 provinces of China between 2004 and 2016 as samples to analyze the influence between electric grid investment demand and GDP, population scale, social electricity consumption, installed electrical capacity, and peak load based on co-integration tests. We find that GDP and peak load have positive influences on electric grid investment demand, but the impact of population scale, social electricity consumption, and installed electrical capacity on electric grid investment is not remarkable. We divide different regions in China into the eastern region, central region, and western region to analyze influence factors of electric grid investment, finally obtaining key factors in the eastern, central, and western regions. In the end, according to the analysis of key factors, we make a prediction about China’s electric grid investment for 2020 in different scenarios. The results offer a certain understanding for the development trend of China’s electric grid investment and contribute to the future development of electric grid investment.

  4. Analysis of the fibroblast growth factor system reveals alterations in a mouse model of spinal muscular atrophy.

    Science.gov (United States)

    Hensel, Niko; Ratzka, Andreas; Brinkmann, Hella; Klimaschewski, Lars; Grothe, Claudia; Claus, Peter

    2012-01-01

    The monogenetic disease Spinal Muscular Atrophy (SMA) is characterized by a progressive loss of motoneurons leading to muscle weakness and atrophy due to severe reduction of the Survival of Motoneuron (SMN) protein. Several models of SMA show deficits in neurite outgrowth and maintenance of neuromuscular junction (NMJ) structure. Survival of motoneurons, axonal outgrowth and formation of NMJ is controlled by neurotrophic factors such as the Fibroblast Growth Factor (FGF) system. Besides their classical role as extracellular ligands, some FGFs exert also intracellular functions controlling neuronal differentiation. We have previously shown that intracellular FGF-2 binds to SMN and regulates the number of a subtype of nuclear bodies which are reduced in SMA patients. In the light of these findings, we systematically analyzed the FGF-system comprising five canonical receptors and 22 ligands in a severe mouse model of SMA. In this study, we demonstrate widespread alterations of the FGF-system in both muscle and spinal cord. Importantly, FGF-receptor 1 is upregulated in spinal cord at a pre-symptomatic stage as well as in a mouse motoneuron-like cell-line NSC34 based model of SMA. Consistent with that, phosphorylations of FGFR-downstream targets Akt and ERK are increased. Moreover, ERK hyper-phosphorylation is functionally linked to FGFR-1 as revealed by receptor inhibition experiments. Our study shows that the FGF system is dysregulated at an early stage in SMA and may contribute to the SMA pathogenesis.

  5. Experimental analysis and theoretical model for anomalously high ideality factors in ZnO/diamond p-n junction diode

    International Nuclear Information System (INIS)

    Wang Chengxin; Yang Guowei; Liu Hongwu; Han Yonghao; Luo Jifeng; Gao Chunxiao; Zou Guangtian

    2004-01-01

    High-quality heterojunctions between p-type diamond single-crystalline films and highly oriented n-type ZnO films were fabricated by depositing the p-type diamond single-crystal films on the I o -type diamond single crystal using a hot filament chemical vapor deposition, and later growing a highly oriented n-type ZnO film on the p-type diamond single-crystal film by magnetron sputtering. Interestingly, anomalously high ideality factors (n>>2.0) in the prepared ZnO/diamond p-n junction diode in the interim bias voltage range were measured. For this, detailed electronic characterizations of the fabricated p-n junction were conducted, and a theoretical model was proposed to clarify the much higher ideality factors of the special heterojunction diode

  6. Longitudinal analysis of osteogenic and angiogenic signaling factors in healing models mimicking atrophic and hypertrophic non-unions in rats.

    Directory of Open Access Journals (Sweden)

    Susann Minkwitz

    Full Text Available Impaired bone healing can have devastating consequences for the patient. Clinically relevant animal models are necessary to understand the pathology of impaired bone healing. In this study, two impaired healing models, a hypertrophic and an atrophic non-union, were compared to physiological bone healing in rats. The aim was to provide detailed information about differences in gene expression, vascularization and histology during the healing process. The change from a closed fracture (healing control group to an open osteotomy (hypertrophy group led to prolonged healing with reduced mineralized bridging after 42 days. RT-PCR data revealed higher gene expression of most tested osteogenic and angiogenic factors in the hypertrophy group at day 14. After 42 days a significant reduction of gene expression was seen for Bmp4 and Bambi in this group. The inhibition of angiogenesis by Fumagillin (atrophy group decreased the formation of new blood vessels and led to a non-healing situation with diminished chondrogenesis. RT-PCR results showed an attempt towards overcoming the early perturbance by significant up regulation of the angiogenic regulators Vegfa, Angiopoietin 2 and Fgf1 at day 7 and a further continuous increase of Fgf1, -2 and Angiopoietin 2 over time. However µCT angiograms showed incomplete recovery after 42 days. Furthermore, lower expression values were detected for the Bmps at day 14 and 21. The Bmp antagonists Dan and Twsg1 tended to be higher expressed in the atrophy group at day 42. In conclusion, the investigated animal models are suitable models to mimic human fracture healing complications and can be used for longitudinal studies. Analyzing osteogenic and angiogenic signaling patterns, clear changes in expression were identified between these three healing models, revealing the importance of a coordinated interplay of different factors to allow successful bone healing.

  7. A Confirmatory Factor Analysis Model of Servant Leader of School Director Under the Office of the Vocational Education Commission in Thailand

    Directory of Open Access Journals (Sweden)

    Boonchan Sisan

    2017-11-01

    Full Text Available This research aims to develop and examine the Goodness-of-Fit Index of Confirmatory Factor Analysis (CFA in servant leader of school director under the Office of the Vocational Education Commission (OVEC. The result is based on the empirical data. The sample group consisted of 247 school directors under the OVEC. The samples were taken using Multi - Stage Sampling randomized technique. Research instrument was questionnaire which had 0.80 - 1.00 for item objective congruence, discriminative power with 0.46 - .80 , and reliability of .95. The data analysed by Confirmatory Factor Analysis (CFA. The study shows the servant leader of school director under the OVEC consists of six factors: Appreciating of Others, Developing Others, Developing Community, moral Expressions, Supporting Leadership, and Using Leadership Together. The results of examination of the Goodness-of-Fit Index of Confirmatory Factor Analysis (CFA found the model fit indexes based on the empirical data were =280.89; df=252; P-value=0.10204; Relative =1.11; RMSEA=0.022; NFI=0.98; RMR=0.016; SRMR=0.041; GFI=0.92; AGFI=0.89; NIF=0.98; IFI=1.00; CFI=1.00; CN=252.56. The factor loadings of six factors were from 0.73 – 0.94 and factor loadings of indicators were from -0.39 – 0.57.

  8. Nominal Performance Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M.A. Wasiolek

    2003-07-25

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports (BSC 2003 [DIRS 160964]; BSC 2003 [DIRS 160965]; BSC 2003 [DIRS 160976]; BSC 2003 [DIRS 161239]; BSC 2003 [DIRS 161241]) contain detailed description of the model input parameters. This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs and conversion factors for the TSPA. The BDCFs will be used in performance assessment for calculating annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle activity in groundwater and the annual dose from beta- and photon-emitting radionuclides.

  9. Exploring the core factors and its dynamic effects on oil price: An application on path analysis and BVAR-TVP model

    International Nuclear Information System (INIS)

    Chai Jian; Guo, Ju-E.; Meng Lei; Wang Shouyang

    2011-01-01

    As the uncertainty of oil price increases, impacts of the influential factors on oil price vary over time. It is of great importance to explore the core factors and its time-varying influence on oil price. In view of this, based on the PATH-ANALYSIS model, this paper obtains the core factors, builds an oil price system VAR model, which uses demand, supply, price, and inventory as endogenous variables, and China's net imports as well as dollar index as exogenous variables. Then we set up a BVAR-TVP (Time varying parameter) model to analyze dynamic impacts of core factors on oil price. The results show that: (1) oil prices became more sensitive to oil supply changes, and the influence delays became shorter; (2) the impact of oil inventories on oil prices with a time lag of two quarters but has a downward trend; (3) the impact of oil consumption on oil prices with a time lag of two quarters, and this effect is increasingly greater; (4) the US dollar index is always the important factor of oil price and its control power increases gradually, and the financial crisis (occurred in 2008) further strengthens the influence of US dollar. - Highlights: ► We build an oil price VAR model based on the PATH-ANALYSIS results. ► The dynamic effects of core factors on oil price was studied by BVAR-TVP model. ► Oil prices became more sensitive to oil supply changes. ► The effect of oil consumption on oil prices is increasingly greater. ► Financial crisis further strengthens the influence of US dollar on oil price.

  10. Lithuanian Population Aging Factors Analysis

    Directory of Open Access Journals (Sweden)

    Agnė Garlauskaitė

    2015-05-01

    Full Text Available The aim of this article is to identify the factors that determine aging of Lithuania’s population and to assess the influence of these factors. The article shows Lithuanian population aging factors analysis, which consists of two main parts: the first describes the aging of the population and its characteristics in theoretical terms. Second part is dedicated to the assessment of trends that influence the aging population and demographic factors and also to analyse the determinants of the aging of the population of Lithuania. After analysis it is concluded in the article that the decline in the birth rate and increase in the number of emigrants compared to immigrants have the greatest impact on aging of the population, so in order to show the aging of the population, a lot of attention should be paid to management of these demographic processes.

  11. Exploratory Bi-factor Analysis: The Oblique Case

    OpenAIRE

    Jennrich, Robert L.; Bentler, Peter M.

    2011-01-01

    Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bi-factor rotation criterion designed to produce a rotated loading mat...

  12. DISRUPTIVE EVENT BIOSPHERE DOSE CONVERSION FACTOR ANALYSIS

    International Nuclear Information System (INIS)

    M.A. Wasiolek

    2005-01-01

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The Biosphere Model Report (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis'' (Figure 1-1). The objective of this analysis was to develop the BDCFs for the volcanic

  13. Models of Economic Analysis

    OpenAIRE

    Adrian Ioana; Tiberiu Socaciu

    2013-01-01

    The article presents specific aspects of management and models for economic analysis. Thus, we present the main types of economic analysis: statistical analysis, dynamic analysis, static analysis, mathematical analysis, psychological analysis. Also we present the main object of the analysis: the technological activity analysis of a company, the analysis of the production costs, the economic activity analysis of a company, the analysis of equipment, the analysis of labor productivity, the anal...

  14. Nominal Performance Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M.A. Wasiolek

    2005-04-28

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standards. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis

  15. Nominal Performance Biosphere Dose Conversion Factor Analysis

    International Nuclear Information System (INIS)

    M.A. Wasiolek

    2005-01-01

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standards. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis'' (Figure 1-1). The objectives of this analysis are to develop BDCFs for the

  16. An innovation resistance factor model

    Directory of Open Access Journals (Sweden)

    Siti Salwa Mohd Ishak

    2016-09-01

    Full Text Available The process and implementation strategy of information technology in construction is generally considered through the limiting prism of theoretical contexts generated from innovation diffusion and acceptance. This research argues that more attention should be given to understanding the positive effects of resistance. The study develops a theoretical framing for the Integrated Resistance Factor Model (IRFM. The framing uses a combination of diffusion of innovation theory, technology acceptance model and social network perspective. The model is tested to identify the most significant resistance factors using Partial Least Square (PLS technique. All constructs proposed in the model are found to be significant, valid and consistent with the theoretical framework. IRFM is shown to be an effective and appropriate model of user resistance factors. The most critical factors to influence technology resistance in the online project information management system (OPIMS context are: support from leaders and peers, complexity of the technology, compatibility with key work practices; and pre-trial of the technology before it is actually deployed. The study provides a new model for further research in technology innovation specific to the construction industry.

  17. Analysis of the flood extent extraction model and the natural flood influencing factors: A GIS-based and remote sensing analysis

    International Nuclear Information System (INIS)

    Lawal, D U; Matori, A N; Yusuf, K W; Hashim, A M; Balogun, A L

    2014-01-01

    Serious floods have hit the State of Perlis in 2005, 2010, as well as 2011. Perlis is situated in the northern part of Peninsula Malaysia. The floods caused great damage to properties and human lives. There are various methods used in an attempt to provide the most reliable ways to reduce the flood risk and damage to the optimum level by identifying the flood vulnerable zones. The purpose of this paper is to develop a flood extent extraction model based on Minimum Distance Algorithm and to overlay with the natural flood influencing factors considered herein in order to examine the effect of each factor in flood generation. GIS spatial database was created from a geological map, SPOT satellite image, and the topographical map. An attribute database was equally created from field investigations and historical flood areas reports of the study area. The results show a great correlation between the flood extent extraction model and the flood factors

  18. Evaluation of chemical transport model predictions of primary organic aerosol for air masses classified by particle-component-based factor analysis

    OpenAIRE

    C. A. Stroud; M. D. Moran; P. A. Makar; S. Gong; W. Gong; J. Zhang; J. G. Slowik; J. P. D. Abbatt; G. Lu; J. R. Brook; C. Mihele; Q. Li; D. Sills; K. B. Strawbridge; M. L. McGuire

    2012-01-01

    Observations from the 2007 Border Air Quality and Meteorology Study (BAQS-Met 2007) in Southern Ontario, Canada, were used to evaluate predictions of primary organic aerosol (POA) and two other carbonaceous species, black carbon (BC) and carbon monoxide (CO), made for this summertime period by Environment Canada's AURAMS regional chemical transport model. Particle component-based factor analysis was applied to aerosol mass spectrometer measurements made at one urban site (Windsor, ON) and two...

  19. Analysis and modeling of delamination factor in drilling of woven kenaf fiber reinforced epoxy using Box Behnken experimental design

    Science.gov (United States)

    Suhaily, M.; Che Hassan, C. H.; Jaharah, A. G.; Afifah, M. A.; Nor Khairusshima, M. K.

    2018-01-01

    In this research study, it presents a comprehensive mathematical model for correlating the influences of drilling parameters on the delamination factor during the drilling of woven kenaf fiber reinforced epoxy composite laminates using the Box Behnken experimental design. The purpose of this study is to investigate the influence of drilling parameters such as cutting speed, feed rate and drill sizes on the delamination produced when drilling woven kenaf reinforced epoxy composite using the non-coated HSS drill bits. The damage generated on the woven kenaf reinforced epoxy composite laminates were observed both at the entrance and exit surface during the drilling operation. The experiments were conducted according to the Box Behnken experimental designs.

  20. Disruptive Event Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. A. Wasiolek

    2003-07-21

    This analysis report, ''Disruptive Event Biosphere Dose Conversion Factor Analysis'', is one of the technical reports containing documentation of the ERMYN (Environmental Radiation Model for Yucca Mountain Nevada) biosphere model for the geologic repository at Yucca Mountain, its input parameters, and the application of the model to perform the dose assessment for the repository. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of the two reports that develop biosphere dose conversion factors (BDCFs), which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the conceptual model as well as the mathematical model and lists its input parameters. Model input parameters are developed and described in detail in five analysis report (BSC 2003 [DIRS 160964], BSC 2003 [DIRS 160965], BSC 2003 [DIRS 160976], BSC 2003 [DIRS 161239], and BSC 2003 [DIRS 161241]). The objective of this analysis was to develop the BDCFs for the volcanic ash exposure scenario and the dose factors (DFs) for calculating inhalation doses during volcanic eruption (eruption phase of the volcanic event). The volcanic ash exposure scenario is hereafter referred to as the volcanic ash scenario. For the volcanic ash scenario, the mode of radionuclide release into the biosphere is a volcanic eruption through the repository with the resulting entrainment of contaminated waste in the tephra and the subsequent atmospheric transport and dispersion of contaminated material in

  1. Disruptive Event Biosphere Dose Conversion Factor Analysis

    International Nuclear Information System (INIS)

    M. A. Wasiolek

    2003-01-01

    This analysis report, ''Disruptive Event Biosphere Dose Conversion Factor Analysis'', is one of the technical reports containing documentation of the ERMYN (Environmental Radiation Model for Yucca Mountain Nevada) biosphere model for the geologic repository at Yucca Mountain, its input parameters, and the application of the model to perform the dose assessment for the repository. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of the two reports that develop biosphere dose conversion factors (BDCFs), which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the conceptual model as well as the mathematical model and lists its input parameters. Model input parameters are developed and described in detail in five analysis report (BSC 2003 [DIRS 160964], BSC 2003 [DIRS 160965], BSC 2003 [DIRS 160976], BSC 2003 [DIRS 161239], and BSC 2003 [DIRS 161241]). The objective of this analysis was to develop the BDCFs for the volcanic ash exposure scenario and the dose factors (DFs) for calculating inhalation doses during volcanic eruption (eruption phase of the volcanic event). The volcanic ash exposure scenario is hereafter referred to as the volcanic ash scenario. For the volcanic ash scenario, the mode of radionuclide release into the biosphere is a volcanic eruption through the repository with the resulting entrainment of contaminated waste in the tephra and the subsequent atmospheric transport and dispersion of contaminated material in the biosphere. The biosphere process

  2. [Multivariate and multilevel model analysis on factors that influencing the literacy of health among high school students in Guangdong province].

    Science.gov (United States)

    Ye, Xiao-hua; Xu, Ya; Zhou, Shu-dong; Gao, Yan-hui; Li, Yan-fen

    2011-09-01

    To analyze the awareness on health among high school students and its influencing factors in Guangdong. Multi-stage sampling and questionnaire "2009 health awareness survey of the Chinese citizens" developed by our Department of Health, were used. Data were analyzed by multivariate multilevel model under MLwinN 2.19 software. The mean scores on knowledge and ideas, behaviors and related skills among 1606 high school students of Guangdong province, were 69.08 ± 14.81, 60.05 ± 16.85 and 74.99 ± 21.17 respectively. Three items on health showed that they all related to each other and relations between grades (0.972, 0.715 and 0.855) were greater than the individuals (0.565, 0.426 and 0.438). Factors as students from outside the Pearl River Delta region or from the rural areas, being male, at general secondary schools, at grade one, with poor academic performance and more pocket money etc., had lower levels on those related information of health.

  3. Stability analysis of type 2 diabetes mellitus prognosis model with obesity as a trigger factor and metabolic syndrome as a risk factor

    Science.gov (United States)

    Jaya, A. I.; Lestari, A. D.; Ratianingsih, R.; Puspitasari, J. W.

    2018-03-01

    Obesity is found in 90% of the world's patients with a type 2 diabetes mellitus (DM) diagnosis. If it is not being treatment, the disease advances to a metabolic syndrome related to some atherosclerotic cardiovascular diseases. In this study, a mathematical model was constructed that represent the prognosis of type 2 DM. The prognosis is started from the transition of vulnerable people to overweight and obese. The advanced prognosis makes the type 2 DM sufferer become a metabolic syndrome. The model has no disease-free critical point, while the implicit endemic critical point is guaranteed for some requirements. The analysis of the critical point stability, by Jacobian matrix and Routh Hurwitz criteria, requires a parameter interval that identified from the characteristic polynomial. The requirements show that we have to pay attention to the transition rate of overweight to obese, more over the transition rate of obese to type 2 DM. The simulations show that the unstable condition of type 2 DM is easier to achieve because of the tightness of the parameter stability interval.

  4. Transforming Rubrics Using Factor Analysis

    Science.gov (United States)

    Baryla, Ed; Shelley, Gary; Trainor, William

    2012-01-01

    Student learning and program effectiveness is often assessed using rubrics. While much time and effort may go into their creation, it is equally important to assess how effective and efficient the rubrics actually are in terms of measuring competencies over a number of criteria. This study demonstrates the use of common factor analysis to identify…

  5. Evaluating WAIS-IV structure through a different psychometric lens: structural causal model discovery as an alternative to confirmatory factor analysis.

    Science.gov (United States)

    van Dijk, Marjolein J A M; Claassen, Tom; Suwartono, Christiany; van der Veld, William M; van der Heijden, Paul T; Hendriks, Marc P H

    Since the publication of the WAIS-IV in the U.S. in 2008, efforts have been made to explore the structural validity by applying factor analysis to various samples. This study aims to achieve a more fine-grained understanding of the structure of the Dutch language version of the WAIS-IV (WAIS-IV-NL) by applying an alternative analysis based on causal modeling in addition to confirmatory factor analysis (CFA). The Bayesian Constraint-based Causal Discovery (BCCD) algorithm learns underlying network structures directly from data and assesses more complex structures than is possible with factor analysis. WAIS-IV-NL profiles of two clinical samples of 202 patients (i.e. patients with temporal lobe epilepsy and a mixed psychiatric outpatient group) were analyzed and contrasted with a matched control group (N = 202) selected from the Dutch standardization sample of the WAIS-IV-NL to investigate internal structure by means of CFA and BCCD. With CFA, the four-factor structure as proposed by Wechsler demonstrates acceptable fit in all three subsamples. However, BCCD revealed three consistent clusters (verbal comprehension, visual processing, and processing speed) in all three subsamples. The combination of Arithmetic and Digit Span as a coherent working memory factor could not be verified, and Matrix Reasoning appeared to be isolated. With BCCD, some discrepancies from the proposed four-factor structure are exemplified. Furthermore, these results fit CHC theory of intelligence more clearly. Consistent clustering patterns indicate these results are robust. The structural causal discovery approach may be helpful in better interpreting existing tests, the development of new tests, and aid in diagnostic instruments.

  6. Analysis of Transforming Growth Factor- β1 Expression in Resorptive Lacunae following Orthodontic Tooth Movement in An Animal Model

    Science.gov (United States)

    Seifi, Massoud; Kazemi, Bahram; Kabiri, Sattar; Badiee, Mohammadreza

    2017-01-01

    Objective Root resorption is a complication of orthodontic treatment and till date, there is a dearth of information regarding this issue. The aim of this study was to determine whether the expression of transforming growth factor-β1 (TGF-β1, an inflammatory cytokine) is related to orthodontic force. Moreover, if associated, the expression level may be helpful in differential diagnosis, control and ultimate treatment of the disease. Materials and Methods In this experimental study, a total of 24 eight-week-old male Wistar rats were selected randomly. On day 0, an orthodontic appliance, which consisted of a closed coil spring, was ligated to the upper right first molar and incisor. The upper left first molar in these animals was not placed under orthodontic force, thus serving as the control group. On day 21, after anesthesia, the animals were sacrificed. The rats were then divided into two equal groups where the first group was subjected to histological evaluation and the second group to reverse transcriptase-polymerase chain reaction (RT-PCR). Orthodontic tooth movement was measured in both groups to determine the influence of the applied force. Results Statistical analysis of data showed a significant root resorption between the experimental group and control group (Porthodontic force and orthodontic induced inflammatory root resorption. In addition, no relationship is likely to exist between root resorption and TGF-β1 expression in the resorptive lacunae. PMID:28670520

  7. A Comparison of Pseudo-Maximum Likelihood and Asymptotically Distribution-Free Dynamic Factor Analysis Parameter Estimation in Fitting Covariance-Structure Models to Block-Toeplitz Representing Single-Subject Multivariate Time-Series

    NARCIS (Netherlands)

    Molenaar, P.C.M.; Nesselroade, J.R.

    1998-01-01

    The study of intraindividual variability pervades empirical inquiry in virtually all subdisciplines of psychology. The statistical analysis of multivariate time-series data - a central product of intraindividual investigations - requires special modeling techniques. The dynamic factor model (DFM),

  8. Structural modeling and DNA binding autoinhibition analysis of Ergp55, a critical transcription factor in prostate cancer.

    Directory of Open Access Journals (Sweden)

    Shanti P Gangwar

    Full Text Available BACKGROUND: The Ergp55 protein belongs to Ets family of transcription factor. The Ets proteins are highly conserved in their DNA binding domain and involved in various development processes and regulation of cancer metabolism. To study the structure and DNA binding autoinhibition mechanism of Ergp55 protein, we have produced full length and smaller polypeptides of Ergp55 protein in E. coli and characterized using various biophysical techniques. RESULTS: The Ergp55 polypeptides contain large amount of α-helix and random coil structures as measured by circular dichorism spectroscopy. The full length Ergp55 forms a flexible and elongated molecule as revealed by molecular modeling, dynamics simulation and structural prediction algorithms. The binding analyses of Ergp55 polypeptides with target DNA sequences of E74 and cfos promoters indicate that longer fragments of Ergp55 (beyond the Ets domain showed the evidence of auto-inhibition. This study also revealed the parts of Ergp55 protein that mediate auto-inhibition. SIGNIFICANCE: The current study will aid in designing the compounds that stabilize the inhibited form of Ergp55 and inhibit its binding to promoter DNA. It will contribute in the development of drugs targeting Ergp55 for the prostate cancer treatment.

  9. Development of a generalized stochastic model for the analysis of monoenergetic space-time nuclear factor Kinetics

    International Nuclear Information System (INIS)

    Pham, Nhu Viet Ha

    2011-02-01

    To predict the space-time dependent behavior of a nuclear reactor, the conventional space-dependent kinetics equations are widely used for treating the spatial variables. However, the solutions of such deterministic space-dependent kinetics equations, which give only the mean values of the neutron population and the delayed neutron precursor concentrations, do not offer sufficient insight into the actual dynamic processes within a reactor, where the interacting populations vary randomly with space and time. It is also noted that at high power levels, the random behavior of a reactor is negligible but at low power levels, such as at start-up, random fluctuations in population dynamics can be significant. To mathematically describe the evolution of the state of a nuclear reactor using a set of stochastic kinetics equations, the forward stochastic model (FSM) in stochastic kinetics theory is devised through the concept of reactor transition probability and its probability generating function as the spatial domain of a reactor is partitioned into a number of space cells. Nevertheless, the FSM equations for the mean value of neutron and precursor distribution are deterministic-like. Furthermore, the numerical treatment of the FSM equations for the means, variances, and covariances is quite complicated and time-consuming. In the present study, a generalized stochastic model (called the stochastic space-dependent kinetics model or SSKM) based on the FSM and the Its stochastic differential equations was newly developed for the analysis of monoenergetic spacetime nuclear reactor kinetics in one dimension. First, the FSM equations for determining the mean values of neutron and delayed-neutron precursor populations were considered as the deterministic ones without taking into account their variances and covariances. Second, the system of interest was randomized again in the light of the Its stochastic differential equations in order to derive the SSKM. The proposed model

  10. Nominal Performance Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2004-09-08

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs for the groundwater exposure scenario for the three climate states considered in the TSPA-LA as well as conversion factors for evaluating compliance with the groundwater protection standard. The BDCFs will be used in performance assessment for calculating all-pathway annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle

  11. Time Series Factor Analysis with an Application to Measuring Money

    NARCIS (Netherlands)

    Gilbert, Paul D.; Meijer, Erik

    2005-01-01

    Time series factor analysis (TSFA) and its associated statistical theory is developed. Unlike dynamic factor analysis (DFA), TSFA obviates the need for explicitly modeling the process dynamics of the underlying phenomena. It also differs from standard factor analysis (FA) in important respects: the

  12. Energy-Water Modeling and Analysis | Energy Analysis | NREL

    Science.gov (United States)

    Generation (ReEDS Model Analysis) U.S. Energy Sector Vulnerabilities to Climate Change and Extreme Weather Modeling and Analysis Energy-Water Modeling and Analysis NREL's energy-water modeling and analysis vulnerabilities from various factors, including water. Example Projects Renewable Electricity Futures Study

  13. The ATLAS Analysis Model

    CERN Multimedia

    Amir Farbin

    The ATLAS Analysis Model is a continually developing vision of how to reconcile physics analysis requirements with the ATLAS offline software and computing model constraints. In the past year this vision has influenced the evolution of the ATLAS Event Data Model, the Athena software framework, and physics analysis tools. These developments, along with the October Analysis Model Workshop and the planning for CSC analyses have led to a rapid refinement of the ATLAS Analysis Model in the past few months. This article introduces some of the relevant issues and presents the current vision of the future ATLAS Analysis Model. Event Data Model The ATLAS Event Data Model (EDM) consists of several levels of details, each targeted for a specific set of tasks. For example the Event Summary Data (ESD) stores calorimeter cells and tracking system hits thereby permitting many calibration and alignment tasks, but will be only accessible at particular computing sites with potentially large latency. In contrast, the Analysis...

  14. Disruptive Event Biosphere Dose Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2004-09-08

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2004 [DIRS 169671]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis''. The objective of this

  15. Disruptive Event Biosphere Dose Conversion Factor Analysis

    International Nuclear Information System (INIS)

    M. Wasiolek

    2004-01-01

    This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2004 [DIRS 169671]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis''. The objective of this analysis was to develop the BDCFs for the volcanic ash

  16. Analysis of Factors Affecting Patients’ Compliance to Topical Antiglaucoma Medications in Egypt as a Developing Country Model

    Directory of Open Access Journals (Sweden)

    Nahla B. Abu Hussein

    2015-01-01

    Full Text Available Purpose. To study factors affecting patients’ compliance to antiglaucoma medications in Egypt where there are unique factors as a developing country. Patients and Methods. A cross-sectional descriptive study on 440 Egyptian patients with open angle glaucoma (OAG recruited for over two years. The patients were thoroughly interviewed about their age, education level, duration of glaucoma, difficulty in instilling the drops, medication regimens, a family history of glaucoma, knowledge of the disease, and the presence of medical insurance. Results. 236 (53.6% were noncompliant compared to 204 (46.4% who were compliant. Females had a tendency for higher compliance (p=0.061. Patient age above 50 years and low level of education and negative family history of glaucoma were factors significantly associated with poor compliance (p<0.0001. Polytherapy and lack of medical insurance could be contributing factors. Conclusion. Egyptian patients have a high rate of noncompliance compared to the average in literature. Great effort is needed in educating patients about the importance of medications and the risk and the prognosis of this disease. Economic factors must also be taken into consideration in developing countries with large number of poor patients. We recommend simplifying drug regimens, incorporating electronic dose monitors, and creating reminders for follow-up visits of glaucoma patients.

  17. Empirical Study on Total Factor Productive Energy Efficiency in Beijing-Tianjin-Hebei Region-Analysis based on Malmquist Index and Window Model

    Science.gov (United States)

    Xu, Qiang; Ding, Shuai; An, Jingwen

    2017-12-01

    This paper studies the energy efficiency of Beijing-Tianjin-Hebei region and to finds out the trend of energy efficiency in order to improve the economic development quality of Beijing-Tianjin-Hebei region. Based on Malmquist index and window analysis model, this paper estimates the total factor energy efficiency in Beijing-Tianjin-Hebei region empirically by using panel data in this region from 1991 to 2014, and provides the corresponding political recommendations. The empirical result shows that, the total factor energy efficiency in Beijing-Tianjin-Hebei region increased from 1991 to 2014, mainly relies on advances in energy technology or innovation, and obvious regional differences in energy efficiency to exist. Throughout the window period of 24 years, the regional differences of energy efficiency in Beijing-Tianjin-Hebei region shrank. There has been significant convergent trend in energy efficiency after 2000, mainly depends on the diffusion and spillover of energy technologies.

  18. Analysis of Driving Factors for Extended Producer Responsibility by Using Interpretative Structure Modelling (ISM and Analytic Network Process (ANP

    Directory of Open Access Journals (Sweden)

    Xiong Zheng

    2017-03-01

    Full Text Available The establishment of an efficient reverse supply chain is important, especially in the electronics industry, considering the environmental and resource pressures worldwide. Extended Producer Responsibility (EPR, an important environmental policy approach, has been adopted extensively in various countries, and the effectiveness of its implementation has been proven through practical application. However, the establishment and development of EPR are lacking in most developing countries where collection and recycling systems are underdeveloped. This study addresses this problem by exploring the hierarchical relationship among the driving factors of EPR in the electronics industry in China and by identifying and ranking the factors that are critical in EPR implementation. As important managerial conclusions, research results show that EPR-related laws and regulations, the consciousness of senior executives, and corporate image are the three most important driving factors of EPR implementation.

  19. Ranking factors involved in product design using a hybrid model of Quality Function Deployment, Data Envelopment Analysis and TOPSIS technique

    Directory of Open Access Journals (Sweden)

    Davood Feiz

    2014-08-01

    Full Text Available Quality function deployment (QFD is one such extremely important quality management tool, which is useful in product design and development. Traditionally, QFD rates the design requirements (DRs with respect to customer requirements, and aggregates the rating to get relative importance score of DRs. An increasing number of studies emphasize on the need to incorporate additional factors, such as cost and environmental impact, while calculating the relative importance of DRs. However, there are different methodologies for driving the relative importance of DRs, when several additional factors are considered. TOPSIS (technique for order preferences by similarity to ideal solution is suggested for the purpose of the research. This research proposes new approach of TOPSIS for considering the rating of DRs with respect to CRs, and several additional factors, simultaneously. Proposed method is illustrated using by step-by-step procedure. The proposed methodology was applied for the Sanam Electronic Company in Iran.

  20. An environmental analysis of genes associated with schizophrenia: hypoxia and vascular factors as interacting elements in the neurodevelopmental model.

    Science.gov (United States)

    Schmidt-Kastner, R; van Os, J; Esquivel, G; Steinbusch, H W M; Rutten, B P F

    2012-12-01

    Investigating and understanding gene-environment interaction (G × E) in a neurodevelopmentally and biologically plausible manner is a major challenge for schizophrenia research. Hypoxia during neurodevelopment is one of several environmental factors related to the risk of schizophrenia, and links between schizophrenia candidate genes and hypoxia regulation or vascular expression have been proposed. Given the availability of a wealth of complex genetic information on schizophrenia in the literature without knowledge on the connections to environmental factors, we now systematically collected genes from candidate studies (using SzGene), genome-wide association studies (GWAS) and copy number variation (CNV) analyses, and then applied four criteria to test for a (theoretical) link to ischemia-hypoxia and/or vascular factors. In all, 55% of the schizophrenia candidate genes (n=42 genes) met the criteria for a link to ischemia-hypoxia and/or vascular factors. Genes associated with schizophrenia showed a significant, threefold enrichment among genes that were derived from microarray studies of the ischemia-hypoxia response (IHR) in the brain. Thus, the finding of a considerable match between genes associated with the risk of schizophrenia and IHR and/or vascular factors is reproducible. An additional survey of genes identified by GWAS and CNV analyses suggested novel genes that match the criteria. Findings for interactions between specific variants of genes proposed to be IHR and/or vascular factors with obstetric complications in patients with schizophrenia have been reported in the literature. Therefore, the extended gene set defined here may form a reasonable and evidence-based starting point for hypothesis-based testing of G × E interactions in clinical genetic and translational neuroscience studies.

  1. Generalised linear mixed models analysis of risk factors for contamination of Danish broiler flocks with Salmonella typhimurium

    DEFF Research Database (Denmark)

    Chriél, Mariann; Stryhn, H.; Dauphin, G.

    1999-01-01

    are the broiler flocks (about 4000 flocks) which are clustered within producers. Broiler flocks with ST-infected parent stocks show increased risk of salmonella infection, and also the hatchery affects the salmonella status significantly. Among the rearing factors, only the use of medicine as well as the time......We present a retrospective observational study of risk factors associated with the occurrence of Salmonella typhimurium (ST) in Danish broiler flocks. The study is based on recordings from 1994 in the ante-mortem database maintained by the Danish Poultry Council. The epidemiological units...

  2. DSM-5 alternative personality disorder model traits as maladaptive extreme variants of the five-factor model: An item-response theory analysis.

    Science.gov (United States)

    Suzuki, Takakuni; Samuel, Douglas B; Pahlen, Shandell; Krueger, Robert F

    2015-05-01

    Over the past two decades, evidence has suggested that personality disorders (PDs) can be conceptualized as extreme, maladaptive variants of general personality dimensions, rather than discrete categorical entities. Recognizing this literature, the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) alternative PD model in Section III defines PDs partially through 25 maladaptive traits that fall within 5 domains. Empirical evidence based on the self-report measure of these traits, the Personality Inventory for DSM-5 (PID-5), suggests that these five higher-order domains share a structure and correlate in meaningful ways with the five-factor model (FFM) of general personality. In the current study, item response theory was used to compare the DSM-5 alternative PD model traits to those from a normative FFM inventory (the International Personality Item Pool-NEO [IPIP-NEO]) in terms of their measurement precision along the latent dimensions. Within a combined sample of 3,517 participants, results strongly supported the conclusion that the DSM-5 alternative PD model traits and IPIP-NEO traits are complimentary measures of 4 of the 5 FFM domains (with perhaps the exception of openness to experience vs. psychoticism). Importantly, the two measures yield largely overlapping information curves on these four domains. Differences that did emerge suggested that the PID-5 scales generally have higher thresholds and provide more information at the upper levels, whereas the IPIP-NEO generally had an advantage at the lower levels. These results support the general conceptualization that 4 domains of the DSM-5 alternative PD model traits are maladaptive, extreme versions of the FFM. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  3. Identifying the important factors in simulation models with many factors

    NARCIS (Netherlands)

    Bettonvil, B.; Kleijnen, J.P.C.

    1994-01-01

    Simulation models may have many parameters and input variables (together called factors), while only a few factors are really important (parsimony principle). For such models this paper presents an effective and efficient screening technique to identify and estimate those important factors. The

  4. An easy guide to factor analysis

    CERN Document Server

    Kline, Paul

    2014-01-01

    Factor analysis is a statistical technique widely used in psychology and the social sciences. With the advent of powerful computers, factor analysis and other multivariate methods are now available to many more people. An Easy Guide to Factor Analysis presents and explains factor analysis as clearly and simply as possible. The author, Paul Kline, carefully defines all statistical terms and demonstrates step-by-step how to work out a simple example of principal components analysis and rotation. He further explains other methods of factor analysis, including confirmatory and path analysis, a

  5. Confirmatory factor analysis and structural equation modeling of socio-cultural constructs among chamorro and non-chamorro micronesian betel nut chewers.

    Science.gov (United States)

    Murphy, Kelle L; Liu, Min; Herzog, Thaddeus A

    2017-07-05

    Betel nut chewing is embedded within the cultures of South Asia, and Southeast Asia, and the Western Pacific. The determinants of betel nut consumption are complex. Ongoing consumption of betel nut is affected by cultural, social, and drug-specific effects (i.e. dependence). This study's first objective was to assess the psychometric properties (i.e. reliability and validity) of the socio-cultural constructs in a survey developed for betel nut chewers. The study's second objective was to investigate the influence of socio-cultural variables on betel nut chewing behaviors among Chamorro and non-Chamorro Micronesians in Guam. The current study was a secondary analysis of a larger study (N = 600; n = 375 chewers and n = 225 former chewers) that examined socio-cultural factors that influence why chewers chew betel nut, along with assessing chewing behaviors, perceptions of risks, probability of changing behaviors, and methods that could be used to reduce use or quit. The socio-cultural constructs of the survey were analyzed using confirmatory factor analysis and structural equation modeling. The socio-cultural factors were a sufficient fit with data and the instrument is reliable and valid, as indicated by various model fit indices (χ 2 (13) = 18.49 with p = .14, TLI = .99, CFI = 1.00, SRMR = .02, RMSEA = .03 with 90% CIs [.00,.07]). Cronbach's alpha, the sign and magnitude of the factor loadings, the inter-factor correlations, and the large proportion of variance extracted for each factor, all indicate that the instrument is reliable and valid. Additionally, multivariate analyses showed that socio-cultural reasons were important contributing or chewing betel nut. Participants cited chewing because their friends and family members chewed, the behavior is embedded within their culture, and it would be considered rude and disrespectful to not chew. Based on the findings, this study provides important implications pertaining to

  6. Evaluation of chemical transport model predictions of primary organic aerosol for air masses classified by particle component-based factor analysis

    Directory of Open Access Journals (Sweden)

    C. A. Stroud

    2012-09-01

    Full Text Available Observations from the 2007 Border Air Quality and Meteorology Study (BAQS-Met 2007 in Southern Ontario, Canada, were used to evaluate predictions of primary organic aerosol (POA and two other carbonaceous species, black carbon (BC and carbon monoxide (CO, made for this summertime period by Environment Canada's AURAMS regional chemical transport model. Particle component-based factor analysis was applied to aerosol mass spectrometer measurements made at one urban site (Windsor, ON and two rural sites (Harrow and Bear Creek, ON to derive hydrocarbon-like organic aerosol (HOA factors. A novel diagnostic model evaluation was performed by investigating model POA bias as a function of HOA mass concentration and indicator ratios (e.g. BC/HOA. Eight case studies were selected based on factor analysis and back trajectories to help classify model bias for certain POA source types. By considering model POA bias in relation to co-located BC and CO biases, a plausible story is developed that explains the model biases for all three species.

    At the rural sites, daytime mean PM1 POA mass concentrations were under-predicted compared to observed HOA concentrations. POA under-predictions were accentuated when the transport arriving at the rural sites was from the Detroit/Windsor urban complex and for short-term periods of biomass burning influence. Interestingly, the daytime CO concentrations were only slightly under-predicted at both rural sites, whereas CO was over-predicted at the urban Windsor site with a normalized mean bias of 134%, while good agreement was observed at Windsor for the comparison of daytime PM1 POA and HOA mean values, 1.1 μg m−3 and 1.2 μg m−3, respectively. Biases in model POA predictions also trended from positive to negative with increasing HOA values. Periods of POA over-prediction were most evident at the urban site on calm nights due to an overly-stable model surface layer

  7. Influencing Factors and Development Trend Analysis of China Electric Grid Investment Demand Based on a Panel Co-Integration Model

    OpenAIRE

    Jinchao Li; Lin Chen; Yuwei Xiang; Jinying Li; Dong Peng

    2018-01-01

    Electric grid investment demand analysis is significant to reasonably arranging construction funds for the electric grid and reduce costs. This paper used the panel data of electric grid investment from 23 provinces of China between 2004 and 2016 as samples to analyze the influence between electric grid investment demand and GDP, population scale, social electricity consumption, installed electrical capacity, and peak load based on co-integration tests. We find that GDP and peak load have pos...

  8. Scalable group level probabilistic sparse factor analysis

    DEFF Research Database (Denmark)

    Hinrich, Jesper Løve; Nielsen, Søren Føns Vind; Riis, Nicolai Andre Brogaard

    2017-01-01

    Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a scalable group level probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component...... pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling...... shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex...

  9. Model independent spectroscopic information from an analysis of peripheral direct radiative capture reaction and its application for an extrapolation of an astrophysical S-factor to stellar energies

    International Nuclear Information System (INIS)

    Igamov, S.B.; Tursunmuratov, T.M.; Yarmukhamedov, R.

    2003-01-01

    In this work, within the framework of the cluster potential approach we develop a method which can be used an independent source of getting information on the value of the nuclear vertex constant (NVC) (or respective asymptotical normalization coefficient (ANC)) from the analysis of the direct radiative capture cross section σ(E)(or the astrophysical S-factor S(E)) at extremely low energies by a model independent way as possible. The main idea of the proposed method is that at stellar energies peripheral direct radiative capture reaction of astrophysical interest proceeds mainly through the tail of the overlap integral, which is completely determined by the binding energy and the respective ANC (or NVC). The main advantage of the proposed method is that it allows us to determine both the absolute value of NVC (or ANC) and the astrophysical S-factor S(E) at solar energies (0-50 keV) by means of the analysis of the same experimental astrophysical S-factor S exp (E) in a correct self consistent way using the same potential both for the bound state and for scattering state. The method has been applied for an investigation of the direct radiative capture t(α, γ) 7 Li and 3 He(α, γ) 7 Be reactions at extremely low energies. At first, this method was used for analysis of the S exp (E) to determine values of the modulus squared of the NVC's (or the respective ANC's). The values of NVC's are presented. Then, the obtained NVC's are used by us for extrapolation of the S(E) of the reactions considered to stellar energies (E=0-50 keV) for the 3 He(α, γ) 7 Be reaction and for the t(α, γ) 7 Li reaction. The obtained results are compared with those other authors

  10. Analysis of Epidermal Growth Factor Receptor Related Gene Expression Changes in a Cellular and Animal Model of Parkinson’s Disease

    Directory of Open Access Journals (Sweden)

    In-Su Kim

    2017-02-01

    Full Text Available We employed transcriptome analysis of epidermal growth factor receptor related gene expression changes in cellular and animal models of Parkinson’s disease (PD. We used a well-known Parkinsonian toxin 1-methyl-4-phenylpyridine (MPP+ to induce neuronal apoptosis in the human neuroblastoma SH-SY5Y cell line. The MPP+-treatment of SH-SY5Y cells was capable of inducing neuro-apoptosis, but it remains unclear what kinds of transcriptional genes are affected by MPP+ toxicity. Therefore the pathways that were significantly perturbed in MPP+ treated human neuroblastoma SH-SY5Y cells were identified based on genome-wide gene expression data at two time points (24 and 48 h. We found that the Epidermal Growth Factor Receptor (EGFR pathway-related genes showed significantly differential expression at all time points. The EGFR pathway has been linked to diverse cellular events such as proliferation, differentiation, and apoptosis. Further, to evaluate the functional significance of the altered EGFR related gene expression observed in MPP+-treated SH-SY5Y cells, the EGFR related GJB2 (Cx26 gene expression was analyzed in an MPP+-intoxicated animal PD model. Our findings identify that the EGFR signaling pathway and its related genes, such as Cx26, might play a significant role in dopaminergic (DAergic neuronal cell death during the process of neuro-apoptosis and therefore can be focused on as potential targets for therapeutic intervention.

  11. Robust and Sparse Factor Modelling

    DEFF Research Database (Denmark)

    Croux, Christophe; Exterkate, Peter

    Factor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having relatively few...... nonzero factor loadings. Compared to the traditional factor construction method, we find that this procedure leads to a favorable forecasting performance in the presence of outliers and to better interpretable factors. We investigate the performance of the method in a Monte Carlo experiment...

  12. Analysis of CD45- [CD34+/KDR+] endothelial progenitor cells as juvenile protective factors in a rat model of ischemic-hemorrhagic stroke.

    Directory of Open Access Journals (Sweden)

    Julius L Decano

    Full Text Available Identification of juvenile protective factors (JPFs which are altered with age and contribute to adult-onset diseases could identify novel pathways for reversing the effects of age, an accepted non-modifiable risk factor to adult-onset diseases. Since endothelial progenitor cells (EPCs have been observed to be altered in stroke, hypertension and hypercholesterolemia, said EPCs are candidate JPFs for adult-onset stroke. A priori, if EPC aging plays a 'master-switch JPF-role' in stroke pathogenesis, juvenile EPC therapy alone should delay stroke-onset. Using a hypertensive, transgenic-hyperlipidemic rat model of spontaneous ischemic-hemorrhagic stroke, spTg25, we tested the hypothesis that freshly isolated juvenile EPCs are JPFs that can attenuate stroke progression and delay stroke onset.FACS analysis revealed that CD45- [CD34+/KDR+] EPCs decrease with progression to stroke in spTg25 rats, exhibit differential expression of the dual endodthelin-1/VEGFsp receptor (DEspR and undergo differential DEspR-subtype specific changes in number and in vitro angiogenic tube-incorporation. In vivo EPC infusion of male, juvenile non-expanded cd45-[CD34+/KDR+] EPCs into female stroke-prone rats prior to stroke attenuated progression and delayed stroke onset (P<0.003. Detection of Y-chromosome DNA in brain microvessels of EPC-treated female spTg25 rats indicates integration of male EPCs into female rat brain microvessels. Gradient-echo MRI showed delay of ischemic-hemorrhagic lesions in EPC-treated rats. Real-time RT-PCR pathway-specific array-analysis revealed age-associated gene expression changes in CD45-[CD34+/KDR]EPC subtypes, which were accelerated in stroke-prone rats. Pro-angiogenic genes implicated in intimal hyperplasia were increased in stroke-prone rat EPCs (P<0.0001, suggesting a maladaptive endothelial repair system which acts like a double-edged sword repairing while predisposing to age-associated intimal hyperplasia.Altogether, the data

  13. Sparse and Robust Factor Modelling

    NARCIS (Netherlands)

    C. Croux (Christophe); P. Exterkate (Peter)

    2011-01-01

    textabstractFactor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having

  14. A factor analysis to detect factors influencing building national brand

    Directory of Open Access Journals (Sweden)

    Naser Azad

    Full Text Available Developing a national brand is one of the most important issues for development of a brand. In this study, we present factor analysis to detect the most important factors in building a national brand. The proposed study uses factor analysis to extract the most influencing factors and the sample size has been chosen from two major auto makers in Iran called Iran Khodro and Saipa. The questionnaire was designed in Likert scale and distributed among 235 experts. Cronbach alpha is calculated as 84%, which is well above the minimum desirable limit of 0.70. The implementation of factor analysis provides six factors including “cultural image of customers”, “exciting characteristics”, “competitive pricing strategies”, “perception image” and “previous perceptions”.

  15. Quality of life in people aged 65+ in Europe: associated factors and models of social welfare-analysis of data from the SHARE project (Wave 5).

    Science.gov (United States)

    Conde-Sala, Josep L; Portellano-Ortiz, Cristina; Calvó-Perxas, Laia; Garre-Olmo, Josep

    2017-04-01

    To analyse the clinical, sociodemographic and socioeconomic factors that influence perceived quality of life (QoL) in a community sample of 33,241 people aged 65+ and to examine the relationship with models of social welfare in Europe. This was a cross-sectional study of data from Wave 5 (2013) of the Survey of Health, Ageing and Retirement in Europe (SHARE). The instruments used in the present study were as follows: sociodemographic data, CASP-12 (QoL), EURO-D (depression), indicators of life expectancy and suicide (WHO), and economic indicators (World Bank). Statistical analysis included bivariate and multilevel analyses. In the multilevel analysis, greater satisfaction in life, less depression, sufficient income, better subjective health, physical activity, an absence of functional impairment, younger age and participation in activities were associated with better QoL in all countries. More education was only associated with higher QoL in Eastern European and Mediterranean countries, and only in the latter was caring for grandchildren also related to better QoL. Socioeconomic indicators were better and QoL scores higher (mean = 38.5 ± 5.8) in countries that had a social democratic (Nordic cluster) or corporatist model (Continental cluster) of social welfare, as compared to Eastern European and Mediterranean countries, which were characterized by poorer socioeconomic conditions, more limited social welfare provision and lower QoL scores (mean = 33.5 ± 6.4). Perceived quality-of-life scores are consistent with the sociodemographic and clinical characteristics of participants, as well as with the socioeconomic indicators and models of social welfare of the countries in which they live.

  16. The Infinitesimal Jackknife with Exploratory Factor Analysis

    Science.gov (United States)

    Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I.

    2012-01-01

    The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…

  17. Socio-Economic Factors Affecting Adoption of Modern Information and Communication Technology by Farmers in India: Analysis Using Multivariate Probit Model

    Science.gov (United States)

    Mittal, Surabhi; Mehar, Mamta

    2016-01-01

    Purpose: The paper analyzes factors that affect the likelihood of adoption of different agriculture-related information sources by farmers. Design/Methodology/Approach: The paper links the theoretical understanding of the existing multiple sources of information that farmers use, with the empirical model to analyze the factors that affect the…

  18. Housing price forecastability: A factor analysis

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

    of the model stays high at longer horizons. The estimated factors are strongly statistically signi…cant according to a bootstrap resampling method which takes into account that the factors are estimated regressors. The simple three-factor model also contains substantial out-of-sample predictive power...

  19. [Lake eutrophication modeling in considering climatic factors change: a review].

    Science.gov (United States)

    Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

    2012-11-01

    Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

  20. An Analysis of Decision Factors on the Price of South Korea’s Certified Emission Reductions in Use of Vector Error Correction Model

    Directory of Open Access Journals (Sweden)

    Sumin Park

    2017-09-01

    Full Text Available This study analyzes factors affecting the price of South Korea’s Certified Emission Reduction (CER using statistical methods. CER refers to the transaction price for the amount of carbon emitted. Analysis of results found a co-integration relationship among the price of South Korea’s CER, oil price (WTI, and South Korea’s maximum electric power demand, which means that there is a long-term relationship among the three variables. Based on this result, VECM (vector error correction model analysis, impulse response function, and variance decomposition were performed. As the oil price (WTI increases, the demand for gas in power generation in Korea declines while the demand for coal increases. This leads to increased greenhouse gas (GHG; e.g., CO2 emissions and increased price of South Korea’s CERs. In addition, rising oil prices (WTI cause a decline in demand for oil products such as kerosene, which results in an increase in South Korea’s maximum power demand.

  1. Factors associated with Specific Hypertensive Gestation Syndrome (SHGS in postpartum adolescent and young adult mothers in the Northeast of Brazil: a multiple analysis of hierarchical models

    Directory of Open Access Journals (Sweden)

    Eloisa Barreto Bacelar

    Full Text Available Abstract Objectives: to analyze possible associations between Specific Hypertensive Gestation Syndrome (SHGS and sociodemographic, prenatal, and delivery characteristics of young adult and teenage mothers. Methods: a hospital-based cross-sectional study and regional level, gathered from 54 municipalities in the Northeast region of Brazil from 2011-2012, using records from the National Survey, "Born in Brazil". A theoretical conceptual model with three-level hierarchy was established, with SHGS being the outcome variable. A multivariate analysis was performed from the bivariate analysis and p-value, with a significance of < 0.2 by the Wald test. Results: of the 2,960 adolescents and young adults included in the study, 135 (4.6% developed HSP. The mothers without a partner had 50% (OR=1.53 greater chance of presenting this pathology; while those without adequate schooling for age presented 90% higher chance (OR = 1.86 and those with a prior clinical risk factor, the chance of presenting the outcome was 21 times the chance of those without this antecedent (OR = 21.72. Conclusions: significant associations were identified between SHGS and postpartum adolescents and young adults without a partner, with low schooling and prior clinical risk, signaling the importance of investments in the quality of prenatal care and labor of the most vulnerable groups.

  2. The Recoverability of P-Technique Factor Analysis

    Science.gov (United States)

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

    2009-01-01

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

  3. Likelihood-based Dynamic Factor Analysis for Measurement and Forecasting

    NARCIS (Netherlands)

    Jungbacker, B.M.J.P.; Koopman, S.J.

    2015-01-01

    We present new results for the likelihood-based analysis of the dynamic factor model. The latent factors are modelled by linear dynamic stochastic processes. The idiosyncratic disturbance series are specified as autoregressive processes with mutually correlated innovations. The new results lead to

  4. Differences in within- and between-person factor structure of positive and negative affect: analysis of two intensive measurement studies using multilevel structural equation modeling.

    Science.gov (United States)

    Rush, Jonathan; Hofer, Scott M

    2014-06-01

    The Positive and Negative Affect Schedule (PANAS) is a widely used measure of emotional experience. The factor structure of the PANAS has been examined predominantly with cross-sectional designs, which fails to disaggregate within-person variation from between-person differences. There is still uncertainty as to the factor structure of positive and negative affect and whether they constitute 2 distinct independent factors. The present study examined the within-person and between-person factor structure of the PANAS in 2 independent samples that reported daily affect over 7 and 14 occasions, respectively. Results from multilevel confirmatory factor analyses revealed that a 2-factor structure at both the within-person and between-person levels, with correlated specific factors for overlapping items, provided good model fit. The best-fitting solution was one where within-person factors of positive and negative affect were inversely correlated, but between-person factors were independent. The structure was further validated through multilevel structural equation modeling examining the effects of cognitive interference, daily stress, physical symptoms, and physical activity on positive and negative affect factors.

  5. EXPLORATORY FACTOR ANALYSIS (EFA IN CONSUMER BEHAVIOR AND MARKETING RESEARCH

    Directory of Open Access Journals (Sweden)

    Marcos Pascual Soler

    2012-06-01

    Full Text Available Exploratory Factor Analysis (EFA is one of the most widely used statistical procedures in social research. The main objective of this work is to describe the most common practices used by researchers in the consumer behavior and marketing area. Through a literature review methodology the practices of AFE in five consumer behavior and marketing journals(2000-2010 were analyzed. Then, the choices made by the researchers concerning factor model, retention criteria, rotation, factors interpretation and other relevant issues to factor analysis were analized. The results suggest that researchers routinely conduct analyses using such questionable methods. Suggestions for improving the use of factor analysis and the reporting of results are presented and a checklist (Exploratory Factor Analysis Checklist, EFAC is provided to help editors, reviewers, and authors improve reporting exploratory factor analysis.

  6. Modelling human factor with Petri nets

    International Nuclear Information System (INIS)

    Bedreaga, Luminita; Constantinescu, Cristina; Guzun, Basarab

    2007-01-01

    The human contribution to risk and safety of nuclear power plant operation can be best understood, assessed and quantified using tools to evaluate human reliability. Human reliability analysis becomes an important part of every probabilistic safety assessment and it is used to demonstrate that nuclear power plants designed with different safety levels are prepared to cope with severe accidents. Human reliability analysis in context of probabilistic safety assessment consists in: identifying human-system interactions important to safety; quantifying probabilities appropriate with these interactions. Nowadays, the complex system functions can be modelled using special techniques centred either on states space adequate to system or on events appropriate to the system. Knowing that complex system model consists in evaluating the likelihood of success, in other words, in evaluating the possible value for that system being in some state, the inductive methods which are based on the system states can be applied also for human reliability modelling. Thus, switching to the system states taking into account the human interactions, the underlying basis of the Petri nets can be successfully applied and the likelihoods appropriate to these states can also derived. The paper presents the manner to assess the human reliability quantification using Petri nets approach. The example processed in the paper is from human reliability documentation without a detailed human factor analysis (qualitative). The obtained results by these two kinds of methods are in good agreement. (authors)

  7. Skewed factor models using selection mechanisms

    KAUST Repository

    Kim, Hyoung-Moon

    2015-12-21

    Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

  8. Skewed factor models using selection mechanisms

    KAUST Repository

    Kim, Hyoung-Moon; Maadooliat, Mehdi; Arellano-Valle, Reinaldo B.; Genton, Marc G.

    2015-01-01

    Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

  9. Modeling Ability Differentiation in the Second-Order Factor Model

    Science.gov (United States)

    Molenaar, Dylan; Dolan, Conor V.; van der Maas, Han L. J.

    2011-01-01

    In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model differentiation by introducing heteroscedastic residuals,…

  10. Confirmatory factor analysis of the female sexual function index.

    Science.gov (United States)

    Opperman, Emily A; Benson, Lindsay E; Milhausen, Robin R

    2013-01-01

    The Female Sexual Functioning Index (Rosen et al., 2000 ) was designed to assess the key dimensions of female sexual functioning using six domains: desire, arousal, lubrication, orgasm, satisfaction, and pain. A full-scale score was proposed to represent women's overall sexual function. The fifth revision to the Diagnostic and Statistical Manual (DSM) is currently underway and includes a proposal to combine desire and arousal problems. The objective of this article was to evaluate and compare four models of the Female Sexual Functioning Index: (a) single-factor model, (b) six-factor model, (c) second-order factor model, and (4) five-factor model combining the desire and arousal subscales. Cross-sectional and observational data from 85 women were used to conduct a confirmatory factor analysis on the Female Sexual Functioning Index. Local and global goodness-of-fit measures, the chi-square test of differences, squared multiple correlations, and regression weights were used. The single-factor model fit was not acceptable. The original six-factor model was confirmed, and good model fit was found for the second-order and five-factor models. Delta chi-square tests of differences supported best fit for the six-factor model validating usage of the six domains. However, when revisions are made to the DSM-5, the Female Sexual Functioning Index can adapt to reflect these changes and remain a valid assessment tool for women's sexual functioning, as the five-factor structure was also supported.

  11. Analysis of Bernstein's factorization circuit

    NARCIS (Netherlands)

    Lenstra, A.K.; Shamir, A.; Tomlinson, J.; Tromer, E.; Zheng, Y.

    2002-01-01

    In [1], Bernstein proposed a circuit-based implementation of the matrix step of the number field sieve factorization algorithm. These circuits offer an asymptotic cost reduction under the measure "construction cost x run time". We evaluate the cost of these circuits, in agreement with [1], but argue

  12. Functional dynamic factor models with application to yield curve forecasting

    KAUST Repository

    Hays, Spencer; Shen, Haipeng; Huang, Jianhua Z.

    2012-01-01

    resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM

  13. Confirmatory factor analysis applied to the Force Concept Inventory

    Science.gov (United States)

    Eaton, Philip; Willoughby, Shannon D.

    2018-06-01

    In 1995, Huffman and Heller used exploratory factor analysis to draw into question the factors of the Force Concept Inventory (FCI). Since then several papers have been published examining the factors of the FCI on larger sets of student responses and understandable factors were extracted as a result. However, none of these proposed factor models have been verified to not be unique to their original sample through the use of independent sets of data. This paper seeks to confirm the factor models proposed by Scott et al. in 2012, and Hestenes et al. in 1992, as well as another expert model proposed within this study through the use of confirmatory factor analysis (CFA) and a sample of 20 822 postinstruction student responses to the FCI. Upon application of CFA using the full sample, all three models were found to fit the data with acceptable global fit statistics. However, when CFA was performed using these models on smaller sample sizes the models proposed by Scott et al. and Eaton and Willoughby were found to be far more stable than the model proposed by Hestenes et al. The goodness of fit of these models to the data suggests that the FCI can be scored on factors that are not unique to a single class. These scores could then be used to comment on how instruction methods effect the performance of students along a single factor and more in-depth analyses of curriculum changes may be possible as a result.

  14. Using parallel factor analysis modeling (PARAFAC) and self-organizing maps to track senescence-induced patterns in leaf litter leachate

    Science.gov (United States)

    Wheeler, K. I.; Levia, D. F., Jr.; Hudson, J. E.

    2017-12-01

    As trees undergo autumnal processes such as resorption, senescence, and leaf abscission, the dissolved organic matter (DOM) contribution of leaf litter leachate to streams changes. However, little research has investigated how the fluorescent DOM (FDOM) changes throughout the autumn and how this differs inter- and intraspecifically. Two of the major impacts of global climate change on forested ecosystems include altering phenology and causing forest community species and subspecies composition restructuring. We examined changes in FDOM in leachate from American beech (Fagus grandifolia Ehrh.) leaves in Maryland, Rhode Island, Vermont, and North Carolina and yellow poplar (Liriodendron tulipifera L.) leaves from Maryland throughout three different phenophases: green, senescing, and freshly abscissed. Beech leaves from Maryland and Rhode Island have previously been identified as belonging to the same distinct genetic cluster and beech trees from Vermont and the study site in North Carolina from the other. FDOM in samples was characterized using excitation-emission matrices (EEMs) and a six-component parallel factor analysis (PARAFAC) model was created to identify components. Self-organizing maps (SOMs) were used to visualize variation and patterns in the PARAFAC component proportions of the leachate samples. Phenophase and species had the greatest influence on determining where a sample mapped on the SOM when compared to genetic clusters and geographic origin. Throughout senescence, FDOM from all the trees transitioned from more protein-like components to more humic-like ones. Percent greenness of the sampled leaves and the proportion of the tyrosine-like component 1 were found to significantly differ between the two genetic beech clusters. This suggests possible differences in photosynthesis and resorption between the two genetic clusters of beech. The use of SOMs to visualize differences in patterns of senescence between the different species and genetic

  15. The role of intimate partner violence and other health-related social factors on postpartum common mental disorders: a survey-based structural equation modeling analysis.

    Science.gov (United States)

    Reichenheim, Michael Eduardo; Moraes, Claudia Leite; Lopes, Claudia Souza; Lobato, Gustavo

    2014-05-05

    Although studies suggest the relevance of intimate partner violence (IPV) and other health-related social characteristics as risk factors for postpartum mental health, literature lacks evidence about how these are effectively connected. This study thus aims to explore how socio-economic position, maternal age, household and marital arrangements, general stressors, alcohol misuse and illicit drug abuse, and especially psychological and physical IPV relate in a framework leading to postpartum common mental disorder (CMD). The study was carried out in five primary health care units of Rio de Janeiro, Brazil, and included 810 randomly selected mothers of children up to five postpartum months waiting for pediatric visits. The postulated pathways between exposures and outcome were based on literature evidence and were further examined using structural equation models. Direct pathways to postpartum CMD arose from a latent variable depicting socio-economic position, a general stressors score, and both IPV variables. Notably, the effect of psychological IPV on postpartum CMD ran partly through physical IPV. The effect of teenage pregnancy, conjugal instability and maternal burden apparently happens solely through substance use, be it alcohol misuse, illicit drug abuse or both in tandem. Moreover, the effect of the latter on CMD seems to be entirely mediated through both types of IPV. Although the theoretical model underlying the analysis still requires in-depth detailing, results of this study may have shed some light on the role of both psychological and physical IPV as part of an intricate network of events leading to postpartum CMD. Health initiatives may want to make use of this knowledge when designing preventive and intervention approaches.

  16. Evaluating WAIS-IV structure through a different psychometric lens: Structural causal model discovery as an alternative to confirmatory factor analysis

    NARCIS (Netherlands)

    Dijk, M.J.A.M. van; Claassen, T.; Suwartono, C.; Veld, W.M. van der; Heijden, P.T. van der; Hendriks, M.P.H.

    2017-01-01

    Objective: Since the publication of the WAIS-IV in the U.S. in 2008, efforts have been made to explore the structural validity by applying factor analysis to various samples. This study aims to achieve a more fine-grained understanding of the structure of the Dutch language version of the WAIS-IV

  17. The scientific use of factor analysis in behavioral and life sciences

    National Research Council Canada - National Science Library

    Cattell, Raymond Bernard

    1978-01-01

    ...; the choice of procedures in experimentation; factor interpretation; the relationship of factor analysis to broadened psychometric concepts such as scaling, validity, and reliability, and to higher- strata models...

  18. HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis

    KAUST Repository

    Kulakovskiy, Ivan V.; Vorontsov, Ilya E.; Yevshin, Ivan S.; Sharipov, Ruslan N.; Fedorova, Alla D.; Rumynskiy, Eugene I.; Medvedeva, Yulia A.; Magana-Mora, Arturo; Bajic, Vladimir B.; Papatsenko, Dmitry A.; Kolpakov, Fedor A.; Makeev, Vsevolod J.

    2017-01-01

    We present a major update of the HOCOMOCO collection that consists of patterns describing DNA binding specificities for human and mouse transcription factors. In this release, we profited from a nearly doubled volume of published in vivo experiments on transcription factor (TF) binding to expand the repertoire of binding models, replace low-quality models previously based on in vitro data only and cover more than a hundred TFs with previously unknown binding specificities. This was achieved by systematic motif discovery from more than five thousand ChIP-Seq experiments uniformly processed within the BioUML framework with several ChIP-Seq peak calling tools and aggregated in the GTRD database. HOCOMOCO v11 contains binding models for 453 mouse and 680 human transcription factors and includes 1302 mononucleotide and 576 dinucleotide position weight matrices, which describe primary binding preferences of each transcription factor and reliable alternative binding specificities. An interactive interface and bulk downloads are available on the web: http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco11. In this release, we complement HOCOMOCO by MoLoTool (Motif Location Toolbox, http://molotool.autosome.ru) that applies HOCOMOCO models for visualization of binding sites in short DNA sequences.

  19. HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis

    KAUST Repository

    Kulakovskiy, Ivan V.

    2017-10-31

    We present a major update of the HOCOMOCO collection that consists of patterns describing DNA binding specificities for human and mouse transcription factors. In this release, we profited from a nearly doubled volume of published in vivo experiments on transcription factor (TF) binding to expand the repertoire of binding models, replace low-quality models previously based on in vitro data only and cover more than a hundred TFs with previously unknown binding specificities. This was achieved by systematic motif discovery from more than five thousand ChIP-Seq experiments uniformly processed within the BioUML framework with several ChIP-Seq peak calling tools and aggregated in the GTRD database. HOCOMOCO v11 contains binding models for 453 mouse and 680 human transcription factors and includes 1302 mononucleotide and 576 dinucleotide position weight matrices, which describe primary binding preferences of each transcription factor and reliable alternative binding specificities. An interactive interface and bulk downloads are available on the web: http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco11. In this release, we complement HOCOMOCO by MoLoTool (Motif Location Toolbox, http://molotool.autosome.ru) that applies HOCOMOCO models for visualization of binding sites in short DNA sequences.

  20. Multiple factor analysis by example using R

    CERN Document Server

    Pagès, Jérôme

    2014-01-01

    Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The

  1. Comparison of Transcription Factor Binding Site Models

    KAUST Repository

    Bhuyan, Sharifulislam

    2012-05-01

    Modeling of transcription factor binding sites (TFBSs) and TFBS prediction on genomic sequences are important steps to elucidate transcription regulatory mechanism. Dependency of transcription regulation on a great number of factors such as chemical specificity, molecular structure, genomic and epigenetic characteristics, long distance interaction, makes this a challenging problem. Different experimental procedures generate evidence that DNA-binding domains of transcription factors show considerable DNA sequence specificity. Probabilistic modeling of TFBSs has been moderately successful in identifying patterns from a family of sequences. In this study, we compare performances of different probabilistic models and try to estimate their efficacy over experimental TFBSs data. We build a pipeline to calculate sensitivity and specificity from aligned TFBS sequences for several probabilistic models, such as Markov chains, hidden Markov models, Bayesian networks. Our work, containing relevant statistics and evaluation for the models, can help researchers to choose the most appropriate model for the problem at hand.

  2. Confirmatory Factor Analysis of the Procrastination Assessment Scale for Students

    Directory of Open Access Journals (Sweden)

    Ronald D. Yockey

    2015-10-01

    Full Text Available The relative fit of one- and two-factor models of the Procrastination Assessment Scale for Students (PASS was investigated using confirmatory factor analysis on an ethnically diverse sample of 345 participants. The results indicated that although the two-factor model provided better fit to the data than the one-factor model, neither model provided optimal fit. However, a two-factor model which accounted for common item theme pairs used by Solomon and Rothblum in the creation of the scale provided good fit to the data. In addition, a significant difference by ethnicity was also found on the fear of failure subscale of the PASS, with Whites having significantly lower scores than Asian Americans or Latino/as. Implications of the results are discussed and recommendations made for future work with the scale.

  3. The Five-Factor Model: General Overview

    Directory of Open Access Journals (Sweden)

    A A Vorobyeva

    2011-12-01

    Full Text Available The article describes the five-factor model (FFM, giving an overview of its history, basic dimensions, cross-cultural research conducted on the model and highlights some practical studies based on the FFM, including the studies on job performance, leader performance and daily social interactions. An overview of the recent five-factor theory is also provided. According to the theory, the five factors are encoded in human genes, therefore it is almost impossible to change the basic factors themselves, but a person's behavior might be changed due to characteristic adaptations which do not alter personality dimensions, only a person's behavior.

  4. Analysis of technological, institutional and socioeconomic factors ...

    African Journals Online (AJOL)

    Analysis of technological, institutional and socioeconomic factors that influences poor reading culture among secondary school students in Nigeria. ... Proliferation and availability of smart phones, chatting culture and social media were identified as technological factors influencing poor reading culture among secondary ...

  5. Text mining factor analysis (TFA) in green tea patent data

    Science.gov (United States)

    Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

    2017-03-01

    Factor analysis has become one of the most widely used multivariate statistical procedures in applied research endeavors across a multitude of domains. There are two main types of analyses based on factor analysis: Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Both EFA and CFA aim to observed relationships among a group of indicators with a latent variable, but they differ fundamentally, a priori and restrictions made to the factor model. This method will be applied to patent data technology sector green tea to determine the development technology of green tea in the world. Patent analysis is useful in identifying the future technological trends in a specific field of technology. Database patent are obtained from agency European Patent Organization (EPO). In this paper, CFA model will be applied to the nominal data, which obtain from the presence absence matrix. While doing processing, analysis CFA for nominal data analysis was based on Tetrachoric matrix. Meanwhile, EFA model will be applied on a title from sector technology dominant. Title will be pre-processing first using text mining analysis.

  6. Human factors engineering program review model

    International Nuclear Information System (INIS)

    1994-07-01

    The staff of the Nuclear Regulatory Commission is performing nuclear power plant design certification reviews based on a design process plan that describes the human factors engineering (HFE) program elements that are necessary and sufficient to develop an acceptable detailed design specification and an acceptable implemented design. There are two principal reasons for this approach. First, the initial design certification applications submitted for staff review did not include detailed design information. Second, since human performance literature and industry experiences have shown that many significant human factors issues arise early in the design process, review of the design process activities and results is important to the evaluation of an overall design. However, current regulations and guidance documents do not address the criteria for design process review. Therefore, the HFE Program Review Model (HFE PRM) was developed as a basis for performing design certification reviews that include design process evaluations as well as review of the final design. A central tenet of the HFE PRM is that the HFE aspects of the plant should be developed, designed, and evaluated on the basis of a structured top-down system analysis using accepted HFE principles. The HFE PRM consists of ten component elements. Each element in divided into four sections: Background, Objective, Applicant Submittals, and Review Criteria. This report describes the development of the HFE PRM and gives a detailed description of each HFE review element

  7. Analysis of regional total factor energy efficiency in China under environmental constraints: based on undesirable-minds and DEA window model

    Science.gov (United States)

    Zhang, Shuying; Li, Deshan; Li, Shuangqiang; Jiang, Hanyu; Shen, Yuqing

    2017-06-01

    With China’s entrance into the new economy, the improvement of energy efficiency has become an important indicator to measure the quality of ecological civilization construction and economic development. According to the panel data of Chinese regions in 1996-2014, the nearest distance to the efficient frontier of Undesirable-MinDS Xeon model and DEA window model have been used to calculate the total factor energy efficiency of China’s regions. Study found that: Under environmental constraints, China’s total factor energy efficiency has increased after the first drop in the overall 1996-2014, and then increases again. And the difference between the regions is very large, showing a characteristic of “the east is the highest, the west is lower, and lowest is in the central” finally, this paper puts forward relevant policy suggestions.

  8. A Bayesian Nonparametric Approach to Factor Analysis

    DEFF Research Database (Denmark)

    Piatek, Rémi; Papaspiliopoulos, Omiros

    2018-01-01

    This paper introduces a new approach for the inference of non-Gaussian factor models based on Bayesian nonparametric methods. It relaxes the usual normality assumption on the latent factors, widely used in practice, which is too restrictive in many settings. Our approach, on the contrary, does no...

  9. Identifying Some Risk Factors for the Time to Death of the Elderly Using the Semi-Parametric Blended Model of Survival Analysis With Competing Risks

    Directory of Open Access Journals (Sweden)

    Samane Hajiabbasi

    2018-01-01

    Conclusion In single-variable fitting, age, history of myocardial infarction, history of stroke, and kidney problems were identified to have significant effects on the time to death of the elderly. Based on one-variable semi-parametric competing risk mixture fitted models, more significant risk factors for the time to death of elderly was identified when compared with a fitted multivariate mode to the data. This implies that the role of some independent variables can be explained by other independent variables.

  10. Linear factor copula models and their properties

    KAUST Repository

    Krupskii, Pavel; Genton, Marc G.

    2018-01-01

    We consider a special case of factor copula models with additive common factors and independent components. These models are flexible and parsimonious with O(d) parameters where d is the dimension. The linear structure allows one to obtain closed form expressions for some copulas and their extreme‐value limits. These copulas can be used to model data with strong tail dependencies, such as extreme data. We study the dependence properties of these linear factor copula models and derive the corresponding limiting extreme‐value copulas with a factor structure. We show how parameter estimates can be obtained for these copulas and apply one of these copulas to analyse a financial data set.

  11. Linear factor copula models and their properties

    KAUST Repository

    Krupskii, Pavel

    2018-04-25

    We consider a special case of factor copula models with additive common factors and independent components. These models are flexible and parsimonious with O(d) parameters where d is the dimension. The linear structure allows one to obtain closed form expressions for some copulas and their extreme‐value limits. These copulas can be used to model data with strong tail dependencies, such as extreme data. We study the dependence properties of these linear factor copula models and derive the corresponding limiting extreme‐value copulas with a factor structure. We show how parameter estimates can be obtained for these copulas and apply one of these copulas to analyse a financial data set.

  12. Modular Open-Source Software for Item Factor Analysis

    Science.gov (United States)

    Pritikin, Joshua N.; Hunter, Micheal D.; Boker, Steven M.

    2015-01-01

    This article introduces an item factor analysis (IFA) module for "OpenMx," a free, open-source, and modular statistical modeling package that runs within the R programming environment on GNU/Linux, Mac OS X, and Microsoft Windows. The IFA module offers a novel model specification language that is well suited to programmatic generation…

  13. Hand function evaluation: a factor analysis study.

    Science.gov (United States)

    Jarus, T; Poremba, R

    1993-05-01

    The purpose of this study was to investigate hand function evaluations. Factor analysis with varimax rotation was used to assess the fundamental characteristics of the items included in the Jebsen Hand Function Test and the Smith Hand Function Evaluation. The study sample consisted of 144 subjects without disabilities and 22 subjects with Colles fracture. Results suggest a four factor solution: Factor I--pinch movement; Factor II--grasp; Factor III--target accuracy; and Factor IV--activities of daily living. These categories differentiated the subjects without Colles fracture from the subjects with Colles fracture. A hand function evaluation consisting of these four factors would be useful. Such an evaluation that can be used for current clinical purposes is provided.

  14. [Risk factor analysis of the patients with solitary pulmonary nodules and establishment of a prediction model for the probability of malignancy].

    Science.gov (United States)

    Wang, X; Xu, Y H; Du, Z Y; Qian, Y J; Xu, Z H; Chen, R; Shi, M H

    2018-02-23

    Objective: This study aims to analyze the relationship among the clinical features, radiologic characteristics and pathological diagnosis in patients with solitary pulmonary nodules, and establish a prediction model for the probability of malignancy. Methods: Clinical data of 372 patients with solitary pulmonary nodules who underwent surgical resection with definite postoperative pathological diagnosis were retrospectively analyzed. In these cases, we collected clinical and radiologic features including gender, age, smoking history, history of tumor, family history of cancer, the location of lesion, ground-glass opacity, maximum diameter, calcification, vessel convergence sign, vacuole sign, pleural indentation, speculation and lobulation. The cases were divided to modeling group (268 cases) and validation group (104 cases). A new prediction model was established by logistic regression analying the data from modeling group. Then the data of validation group was planned to validate the efficiency of the new model, and was compared with three classical models(Mayo model, VA model and LiYun model). With the calculated probability values for each model from validation group, SPSS 22.0 was used to draw the receiver operating characteristic curve, to assess the predictive value of this new model. Results: 112 benign SPNs and 156 malignant SPNs were included in modeling group. Multivariable logistic regression analysis showed that gender, age, history of tumor, ground -glass opacity, maximum diameter, and speculation were independent predictors of malignancy in patients with SPN( P prediction model for the probability of malignancy as follow: p =e(x)/(1+ e(x)), x=-4.8029-0.743×gender+ 0.057×age+ 1.306×history of tumor+ 1.305×ground-glass opacity+ 0.051×maximum diameter+ 1.043×speculation. When the data of validation group was added to the four-mathematical prediction model, The area under the curve of our mathematical prediction model was 0.742, which is greater

  15. The multi-factor energy input–output model

    International Nuclear Information System (INIS)

    Guevara, Zeus; Domingos, Tiago

    2017-01-01

    Energy input–output analysis (EIO analysis) is a noteworthy tool for the analysis of the role of energy in the economy. However, it has relied on models that provide a limited description of energy flows in the economic system and do not allow an adequate analysis of energy efficiency. This paper introduces a novel energy input–output model, the multi-factor energy input–output model (MF-EIO model), which is obtained from a partitioning of a hybrid-unit input–output system of the economy. This model improves on current models by describing the energy flows according to the processes of energy conversion and the levels of energy use in the economy. It characterizes the vector of total energy output as a function of seven factors: two energy efficiency indicators; two characteristics of end-use energy consumption; and three economic features of the rest of the economy. Moreover, it is consistent with the standard model for EIO analysis, i.e., the hybrid-unit model. This paper also introduces an approximate version of the MF-EIO model, which is equivalent to the former under equal energy prices for industries and final consumers, but requires less data processing. The latter is composed by two linked models: a model of the energy sector in physical units, and a model of the rest of the economy in monetary units. In conclusion, the proposed modelling framework improves EIO analysis and extends EIO applications to the accounting for energy efficiency of the economy. - Highlights: • A novel energy input–output model is introduced. • It allows a more adequate analysis of energy flows than current models. • It describes energy flows according to processes of energy conversion and use. • It can be used for other environmental applications (material use and emissions). • An approximate version of the model is introduced, simpler and less data intensive.

  16. Integrating human factors into process hazard analysis

    International Nuclear Information System (INIS)

    Kariuki, S.G.; Loewe, K.

    2007-01-01

    A comprehensive process hazard analysis (PHA) needs to address human factors. This paper describes an approach that systematically identifies human error in process design and the human factors that influence its production and propagation. It is deductive in nature and therefore considers human error as a top event. The combinations of different factors that may lead to this top event are analysed. It is qualitative in nature and is used in combination with other PHA methods. The method has an advantage because it does not look at the operator error as the sole contributor to the human failure within a system but a combination of all underlying factors

  17. A mixture theory model of fluid and solute transport in the microvasculature of normal and malignant tissues. II: Factor sensitivity analysis, calibration, and validation.

    Science.gov (United States)

    Schuff, M M; Gore, J P; Nauman, E A

    2013-12-01

    The treatment of cancerous tumors is dependent upon the delivery of therapeutics through the blood by means of the microcirculation. Differences in the vasculature of normal and malignant tissues have been recognized, but it is not fully understood how these differences affect transport and the applicability of existing mathematical models has been questioned at the microscale due to the complex rheology of blood and fluid exchange with the tissue. In addition to determining an appropriate set of governing equations it is necessary to specify appropriate model parameters based on physiological data. To this end, a two stage sensitivity analysis is described which makes it possible to determine the set of parameters most important to the model's calibration. In the first stage, the fluid flow equations are examined and a sensitivity analysis is used to evaluate the importance of 11 different model parameters. Of these, only four substantially influence the intravascular axial flow providing a tractable set that could be calibrated using red blood cell velocity data from the literature. The second stage also utilizes a sensitivity analysis to evaluate the importance of 14 model parameters on extravascular flux. Of these, six exhibit high sensitivity and are integrated into the model calibration using a response surface methodology and experimental intra- and extravascular accumulation data from the literature (Dreher et al. in J Natl Cancer Inst 98(5):335-344, 2006). The model exhibits good agreement with the experimental results for both the mean extravascular concentration and the penetration depth as a function of time for inert dextran over a wide range of molecular weights.

  18. Investigating product development strategy in beverage industry using factor analysis

    Directory of Open Access Journals (Sweden)

    Naser Azad

    2013-03-01

    Full Text Available Selecting a product development strategy that is associated with the company's current service or product innovation, based on customers’ needs and changing environment, plays an important role in increasing demand, increasing market share, increasing sales and profits. Therefore, it is important to extract effective variables associated with product development to improve performance measurement of firms. This paper investigates important factors influencing product development strategies using factor analysis. The proposed model of this paper investigates 36 factors and, using factor analysis, we extract six most influential factors including information sharing, intelligence information, exposure strategy, differentiation, research and development strategy and market survey. The first strategy, partnership, includes five sub-factor including product development partnership, partnership with foreign firms, customers’ perception from competitors’ products, Customer involvement in product development, inter-agency coordination, customer-oriented approach to innovation and transmission of product development change where inter-agency coordination has been considered the most important factor. Internal strengths are the most influential factors impacting the second strategy, intelligence information. The third factor, introducing strategy, introducing strategy, includes four sub criteria and consumer buying behavior is the most influencing factor. Differentiation is the next important factor with five components where knowledge and expertise in product innovation is the most important one. Research and development strategy with four sub-criteria where reducing product development cycle plays the most influential factor and finally, market survey strategy is the last important factor with three factors and finding new market plays the most important role.

  19. A hierarchical model for ordinal matrix factorization

    DEFF Research Database (Denmark)

    Paquet, Ulrich; Thomson, Blaise; Winther, Ole

    2012-01-01

    This paper proposes a hierarchical probabilistic model for ordinal matrix factorization. Unlike previous approaches, we model the ordinal nature of the data and take a principled approach to incorporating priors for the hidden variables. Two algorithms are presented for inference, one based...

  20. Dynamic Factor Models for the Volatility Surface

    DEFF Research Database (Denmark)

    van der Wel, Michel; Ozturk, Sait R.; Dijk, Dick van

    The implied volatility surface is the collection of volatilities implied by option contracts for different strike prices and time-to-maturity. We study factor models to capture the dynamics of this three-dimensional implied volatility surface. Three model types are considered to examine desirable...

  1. SDI CFD MODELING ANALYSIS

    Energy Technology Data Exchange (ETDEWEB)

    Lee, S.

    2011-05-05

    The Savannah River Remediation (SRR) Organization requested that Savannah River National Laboratory (SRNL) develop a Computational Fluid Dynamics (CFD) method to mix and blend the miscible contents of the blend tanks to ensure the contents are properly blended before they are transferred from the blend tank; such as, Tank 50H, to the Salt Waste Processing Facility (SWPF) feed tank. The work described here consists of two modeling areas. They are the mixing modeling analysis during miscible liquid blending operation, and the flow pattern analysis during transfer operation of the blended liquid. The transient CFD governing equations consisting of three momentum equations, one mass balance, two turbulence transport equations for kinetic energy and dissipation rate, and one species transport were solved by an iterative technique until the species concentrations of tank fluid were in equilibrium. The steady-state flow solutions for the entire tank fluid were used for flow pattern analysis, for velocity scaling analysis, and the initial conditions for transient blending calculations. A series of the modeling calculations were performed to estimate the blending times for various jet flow conditions, and to investigate the impact of the cooling coils on the blending time of the tank contents. The modeling results were benchmarked against the pilot scale test results. All of the flow and mixing models were performed with the nozzles installed at the mid-elevation, and parallel to the tank wall. From the CFD modeling calculations, the main results are summarized as follows: (1) The benchmark analyses for the CFD flow velocity and blending models demonstrate their consistency with Engineering Development Laboratory (EDL) and literature test results in terms of local velocity measurements and experimental observations. Thus, an application of the established criterion to SRS full scale tank will provide a better, physically-based estimate of the required mixing time, and

  2. Nominal Performance Biosphere Dose Conversion Factor Analysis

    International Nuclear Information System (INIS)

    Wasiolek, M.

    2000-01-01

    The purpose of this report was to document the process leading to development of the Biosphere Dose Conversion Factors (BDCFs) for the postclosure nominal performance of the potential repository at Yucca Mountain. BDCF calculations concerned twenty-four radionuclides. This selection included sixteen radionuclides that may be significant nominal performance dose contributors during the compliance period of up to 10,000 years, five additional radionuclides of importance for up to 1 million years postclosure, and three relatively short-lived radionuclides important for the human intrusion scenario. Consideration of radionuclide buildup in soil caused by previous irrigation with contaminated groundwater was taken into account in the BDCF development. The effect of climate evolution, from the current arid conditions to a wetter and cooler climate, on the BDCF values was evaluated. The analysis included consideration of different exposure pathway's contribution to the BDCFs. Calculations of nominal performance BDCFs used the GENII-S computer code in a series of probabilistic realizations to propagate the uncertainties of input parameters into the output. BDCFs for the nominal performance, when combined with the concentrations of radionuclides in groundwater allow calculation of potential radiation doses to the receptor of interest. Calculated estimates of radionuclide concentration in groundwater result from the saturated zone modeling. The integration of the biosphere modeling results (BDCFs) with the outcomes of the other component models is accomplished in the Total System Performance Assessment (TSPA) to calculate doses to the receptor of interest from radionuclides postulated to be released to the environment from the potential repository at Yucca Mountain

  3. Effectiveness of enforcement levels of speed limit and drink driving laws and associated factors – Exploratory empirical analysis using a bivariate ordered probit model

    Directory of Open Access Journals (Sweden)

    Behram Wali

    2017-06-01

    Full Text Available The contemporary traffic safety research comprises little information on quantifying the simultaneous association between drink driving and speeding among fatally injured drivers. Potential correlation between driver's drink driving and speeding behavior poses a substantial methodological concern which needs investigation. This study therefore focused on investigating the simultaneous impact of socioeconomic factors, fatalities, vehicle ownership, health services and highway agency road safety policies on enforcement levels of speed limit and drink driving laws. The effectiveness of enforcement levels of speed limit and drink driving laws has been investigated through development of bivariate ordered probit model using data extricated from WHO's global status report on road safety in 2013. The consistent and intuitive parameter estimates along with statistically significant correlation between response outcomes validates the statistical supremacy of bivariate ordered probit model. The results revealed that fatalities per thousand registered vehicles, hospital beds per hundred thousand population and road safety policies are associated with a likely medium or high effectiveness of enforcement levels of speed limit and drink driving laws, respectively. Also, the model encapsulates the effect of several other agency related variables and socio-economic status on the response outcomes. Marginal effects are reported for analyzing the impact of such factors on intermediate categories of response outcomes. The results of this study are expected to provide necessary insights to elemental enforcement programs. Also, marginal effects of explanatory variables may provide useful directions for formulating effective policy countermeasures for overcoming driver's speeding and drink driving behavior.

  4. A methodology to incorporate organizational factors into human reliability analysis

    International Nuclear Information System (INIS)

    Li Pengcheng; Chen Guohua; Zhang Li; Xiao Dongsheng

    2010-01-01

    A new holistic methodology for Human Reliability Analysis (HRA) is proposed to model the effects of the organizational factors on the human reliability. Firstly, a conceptual framework is built, which is used to analyze the causal relationships between the organizational factors and human reliability. Then, the inference model for Human Reliability Analysis is built by combining the conceptual framework with Bayesian networks, which is used to execute the causal inference and diagnostic inference of human reliability. Finally, a case example is presented to demonstrate the specific application of the proposed methodology. The results show that the proposed methodology of combining the conceptual model with Bayesian Networks can not only easily model the causal relationship between organizational factors and human reliability, but in a given context, people can quantitatively measure the human operational reliability, and identify the most likely root causes or the prioritization of root causes caused human error. (authors)

  5. Dynamic analysis of an SDOF helicopter model featuring skid landing gear and an MR damper by considering the rotor lift factor and a Bingham number

    Science.gov (United States)

    Saleh, Muftah; Sedaghati, Ramin; Bhat, Rama

    2018-06-01

    The present study addresses the performance of a skid landing gear (SLG) system of a rotorcraft impacting the ground at a vertical sink rate of up to 4.5 ms‑1. The impact attitude is assumed to be level as per chapter 527 of the Airworthiness Manual of Transport Canada Civil Aviation and part 27 of the Federal Aviation Regulations of the US Federal Aviation Administration. A single degree of freedom helicopter model is investigated under different values of rotor lift factor, L. In this study, three SLG versions are evaluated: (a) standalone conventional SLG; (b) SLG equipped with a passive viscous damper; and (c) SLG incorporated a magnetorheological energy absorber (MREA). The non-dimensional solutions of the helicopter models show that the two former SLG systems suffer adaptability issues with variations in the impact velocity and the rotor lift factor. Therefore, the alternative successful choice is to employ the MREA. Two different optimum Bingham numbers for compression and rebound strokes are defined. A new chart, called the optimum Bingham number versus rotor lift factor ‘B{i}o-L’, is introduced in this study to correlate the optimum Bingham numbers to the variation in the rotor lift factor and to provide more accessibility from the perspective of control design. The chart shows that the optimum Bingham number for the compression stroke is inversely linearly proportional to the increase in the rotor lift factor. This alleviates the impact force on the system and reduces the amount of magnetorheological yield force that would be generated. On the contrary, the optimum Bingham number for the rebound stroke is found to be directly linearly proportional to the rotor lift factor. This ensures controllable attenuation of the restoring force of the linear spring element. This idea can be exploited to generate charts for different landing attitudes and sink rates. In this article, the response of the helicopter equipped with the conventional undamped, damped

  6. The asset pricing model of musharakah factors

    Science.gov (United States)

    Simon, Shahril; Omar, Mohd; Lazam, Norazliani Md

    2015-02-01

    The existing three-factor model developed by Fama and French for conventional investment was formulated based on risk-free rates element in which contradict with Shariah principles. We note that the underlying principles that govern Shariah investment were mutual risk and profit sharing between parties, the assurance of fairness for all and that transactions were based on an underlying asset. In addition, the three-factor model did not exclude stock that was not permissible by Shariah such as financial services based on riba (interest), gambling operator, manufacture or sale of non-halal products or related products and other activities deemed non-permissible according to Shariah. Our approach to construct the factor model for Shariah investment was based on the basic tenets of musharakah in tabulating the factors. We start by noting that Islamic stocks with similar characteristics should have similar returns and risks. This similarity between Islamic stocks was defined by the similarity of musharakah attributes such as business, management, profitability and capital. These attributes define factor exposures (or betas) to factors. The main takeaways were that musharakah attributes we chose had explain stock returns well in cross section and were significant in different market environments. The management factor seemed to be responsible for the general dynamics of the explanatory power.

  7. Analysis of Economic Factors Affecting Stock Market

    OpenAIRE

    Xie, Linyin

    2010-01-01

    This dissertation concentrates on analysis of economic factors affecting Chinese stock market through examining relationship between stock market index and economic factors. Six economic variables are examined: industrial production, money supply 1, money supply 2, exchange rate, long-term government bond yield and real estate total value. Stock market comprises fixed interest stocks and equities shares. In this dissertation, stock market is restricted to equity market. The stock price in thi...

  8. Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel

    2016-12-19

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  9. Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel; Huser, Raphaë l; Genton, Marc G.

    2016-01-01

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  10. Comparative factor analysis models for an empirical study of EEG data, II: A data-guided resolution of the rotation indeterminacy.

    Science.gov (United States)

    Rogers, L J; Douglas, R R

    1984-02-01

    In this paper (the second in a series), we consider a (generic) pair of datasets, which have been analyzed by the techniques of the previous paper. Thus, their "stable subspaces" have been established by comparative factor analysis. The pair of datasets must satisfy two confirmable conditions. The first is the "Inclusion Condition," which requires that the stable subspace of one of the datasets is nearly identical to a subspace of the other dataset's stable subspace. On the basis of that, we have assumed the pair to have similar generating signals, with stochastically independent generators. The second verifiable condition is that the (presumed same) generating signals have distinct ratios of variances for the two datasets. Under these conditions a small elaboration of some elementary linear algebra reduces the rotation problem to several eigenvalue-eigenvector problems. Finally, we emphasize that an analysis of each dataset by the method of Douglas and Rogers (1983) is an essential prerequisite for the useful application of the techniques in this paper. Nonempirical methods of estimating the number of factors simply will not suffice, as confirmed by simulations reported in the previous paper.

  11. Preoperative factors affecting cost and length of stay for isolated off-pump coronary artery bypass grafting: hierarchical linear model analysis.

    Science.gov (United States)

    Shinjo, Daisuke; Fushimi, Kiyohide

    2015-11-17

    To determine the effect of preoperative patient and hospital factors on resource use, cost and length of stay (LOS) among patients undergoing off-pump coronary artery bypass grafting (OPCAB). Observational retrospective study. Data from the Japanese Administrative Database. Patients who underwent isolated, elective OPCAB between April 2011 and March 2012. The primary outcomes of this study were inpatient cost and LOS associated with OPCAB. A two-level hierarchical linear model was used to examine the effects of patient and hospital characteristics on inpatient costs and LOS. The independent variables were patient and hospital factors. We identified 2491 patients who underwent OPCAB at 268 hospitals. The mean cost of OPCAB was $40 665 ±7774, and the mean LOS was 23.4±8.2 days. The study found that select patient factors and certain comorbidities were associated with a high cost and long LOS. A high hospital OPCAB volume was associated with a low cost (-6.6%; p=0.024) as well as a short LOS (-17.6%, pcost and LOS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  12. Disruptive Event Biosphere Doser Conversion Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2000-12-28

    The purpose of this report was to document the process leading to, and the results of, development of radionuclide-, exposure scenario-, and ash thickness-specific Biosphere Dose Conversion Factors (BDCFs) for the postulated postclosure extrusive igneous event (volcanic eruption) at Yucca Mountain. BDCF calculations were done for seventeen radionuclides. The selection of radionuclides included those that may be significant dose contributors during the compliance period of up to 10,000 years, as well as radionuclides of importance for up to 1 million years postclosure. The approach documented in this report takes into account human exposure during three different phases at the time of, and after, volcanic eruption. Calculations of disruptive event BDCFs used the GENII-S computer code in a series of probabilistic realizations to propagate the uncertainties of input parameters into the output. The pathway analysis included consideration of different exposure pathway's contribution to the BDCFs. BDCFs for volcanic eruption, when combined with the concentration of radioactivity deposited by eruption on the soil surface, allow calculation of potential radiation doses to the receptor of interest. Calculation of radioactivity deposition is outside the scope of this report and so is the transport of contaminated ash from the volcano to the location of the receptor. The integration of the biosphere modeling results (BDCFs) with the outcomes of the other component models is accomplished in the Total System Performance Assessment (TSPA), in which doses are calculated to the receptor of interest from radionuclides postulated to be released to the environment from the potential repository at Yucca Mountain.

  13. ANALYSIS MODEL FOR INVENTORY MANAGEMENT

    Directory of Open Access Journals (Sweden)

    CAMELIA BURJA

    2010-01-01

    Full Text Available The inventory represents an essential component for the assets of the enterprise and the economic analysis gives them special importance because their accurate management determines the achievement of the activity object and the financial results. The efficient management of inventory requires ensuring an optimum level for them, which will guarantee the normal functioning of the activity with minimum inventory expenses and funds which are immobilised. The paper presents an analysis model for inventory management based on their rotation speed and the correlation with the sales volume illustrated in an adequate study. The highlighting of the influence factors on the efficient inventory management ensures the useful information needed to justify managerial decisions, which will lead to a balancedfinancial position and to increased company performance.

  14. Study of the factors affecting the karst volume assessment in the Dead Sea sinkhole problem using microgravity field analysis and 3-D modeling

    Directory of Open Access Journals (Sweden)

    L. V. Eppelbaum

    2008-11-01

    Full Text Available Thousands of sinkholes have appeared in the Dead Sea (DS coastal area in Israel and Jordan during two last decades. The sinkhole development is recently associated with the buried evaporation karst at the depth of 25–50 m from earth's surface caused by the drop of the DS level at the rate of 0.8–1.0 m/yr. Drop in the Dead Sea level has changed hydrogeological conditions in the subsurface and caused surface to collapse. The pre-existing cavern was detected using microgravity mapping in the Nahal Hever South site where seven sinkholes of 1–2 m diameter had been opened. About 5000 gravity stations were observed in the area of 200×200 m2 by the use of Scintrex CG-3M AutoGrav gravimeter. Besides the conventional set of corrections applied in microgravity investigations, a correction for a strong gravity horizontal gradient (DS Transform Zone negative gravity anomaly influence was inserted. As a result, residual gravity anomaly of –(0.08÷0.14 mGal was revealed. The gravity field analysis was supported by resistivity measurements. We applied the Emigma 7.8 gravity software to create the 3-D physical-geological models of the sinkholes development area. The modeling was confirmed by application of the GSFC program developed especially for 3-D combined gravity-magnetic modeling in complicated environments. Computed numerous gravity models verified an effective applicability of the microgravity technology for detection of karst cavities and estimation of their physical-geological parameters. A volume of the karst was approximately estimated as 35 000 m3. The visual analysis of large sinkhole clusters have been forming at the microgravity anomaly site, confirmed the results of microgravity mapping and 3-D modeling.

  15. A Multinomial Probit Model with Latent Factors

    DEFF Research Database (Denmark)

    Piatek, Rémi; Gensowski, Miriam

    2017-01-01

    be meaningfully linked to an economic model. We provide sufficient conditions that make this structure identified and interpretable. For inference, we design a Markov chain Monte Carlo sampler based on marginal data augmentation. A simulation exercise shows the good numerical performance of our sampler......We develop a parametrization of the multinomial probit model that yields greater insight into the underlying decision-making process, by decomposing the error terms of the utilities into latent factors and noise. The latent factors are identified without a measurement system, and they can...

  16. Operations and Modeling Analysis

    Science.gov (United States)

    Ebeling, Charles

    2005-01-01

    The Reliability and Maintainability Analysis Tool (RMAT) provides NASA the capability to estimate reliability and maintainability (R&M) parameters and operational support requirements for proposed space vehicles based upon relationships established from both aircraft and Shuttle R&M data. RMAT has matured both in its underlying database and in its level of sophistication in extrapolating this historical data to satisfy proposed mission requirements, maintenance concepts and policies, and type of vehicle (i.e. ranging from aircraft like to shuttle like). However, a companion analyses tool, the Logistics Cost Model (LCM) has not reached the same level of maturity as RMAT due, in large part, to nonexistent or outdated cost estimating relationships and underlying cost databases, and it's almost exclusive dependence on Shuttle operations and logistics cost input parameters. As a result, the full capability of the RMAT/LCM suite of analysis tools to take a conceptual vehicle and derive its operations and support requirements along with the resulting operating and support costs has not been realized.

  17. Factor Economic Analysis at Forestry Enterprises

    Directory of Open Access Journals (Sweden)

    M.Yu. Chik

    2018-03-01

    Full Text Available The article studies the importance of economic analysis according to the results of research of scientific works of domestic and foreign scientists. The calculation of the influence of factors on the change in the cost of harvesting timber products by cost items has been performed. The results of the calculation of the influence of factors on the change of costs on 1 UAH are determined using the full cost of sold products. The variable and fixed costs and their distribution are allocated that influences the calculation of the impact of factors on cost changes on 1 UAH of sold products. The paper singles out the general results of calculating the influence of factors on cost changes on 1 UAH of sold products. According to the results of the analysis, the list of reserves for reducing the cost of production at forest enterprises was proposed. The main sources of reserves for reducing the prime cost of forest products at forest enterprises are investigated based on the conducted factor analysis.

  18. An SPSSR -Menu for Ordinal Factor Analysis

    Directory of Open Access Journals (Sweden)

    Mario Basto

    2012-01-01

    Full Text Available Exploratory factor analysis is a widely used statistical technique in the social sciences. It attempts to identify underlying factors that explain the pattern of correlations within a set of observed variables. A statistical software package is needed to perform the calculations. However, there are some limitations with popular statistical software packages, like SPSS. The R programming language is a free software package for statistical and graphical computing. It offers many packages written by contributors from all over the world and programming resources that allow it to overcome the dialog limitations of SPSS. This paper offers an SPSS dialog written in theR programming language with the help of some packages, so that researchers with little or no knowledge in programming, or those who are accustomed to making their calculations based on statistical dialogs, have more options when applying factor analysis to their data and hence can adopt a better approach when dealing with ordinal, Likert-type data.

  19. Analysis of Increased Information Technology Outsourcing Factors

    Directory of Open Access Journals (Sweden)

    Brcar Franc

    2013-01-01

    Full Text Available The study explores the field of IT outsourcing. The narrow field of research is to build a model of IT outsourcing based on influential factors. The purpose of this research is to determine the influential factors on IT outsourcing expansion. A survey was conducted with 141 large-sized Slovenian companies. Data were statistically analyzed using binary logistic regression. The final model contains five factors: (1 management’s support; (2 knowledge on IT outsourcing; (3 improvement of efficiency and effectiveness; (4 quality improvement of IT services; and (5 innovation improvement of IT. Managers immediately can use the results of this research in their decision-making. Increased performance of each individual organization is to the benefit of the entire society. The examination of IT outsourcing with the methods used is the first such research in Slovenia.

  20. ANALYSIS OF THE FACTORS AFFECTING THE AVERAGE

    Directory of Open Access Journals (Sweden)

    Carmen BOGHEAN

    2013-12-01

    Full Text Available Productivity in agriculture most relevantly and concisely expresses the economic efficiency of using the factors of production. Labour productivity is affected by a considerable number of variables (including the relationship system and interdependence between factors, which differ in each economic sector and influence it, giving rise to a series of technical, economic and organizational idiosyncrasies. The purpose of this paper is to analyse the underlying factors of the average work productivity in agriculture, forestry and fishing. The analysis will take into account the data concerning the economically active population and the gross added value in agriculture, forestry and fishing in Romania during 2008-2011. The distribution of the average work productivity per factors affecting it is conducted by means of the u-substitution method.

  1. DISTANCE AS KEY FACTOR IN MODELLING STUDENTS’ RECRUITMENT BY UNIVERSITIES

    Directory of Open Access Journals (Sweden)

    SIMONA MĂLĂESCU

    2015-10-01

    Full Text Available Distance as Key Factor in Modelling Students’ Recruitment by Universities. In a previous paper analysing the challenge of keeping up with the current methodologies in the analysis and modelling of students’ recruitment by universities in the case of some ECE countries which still don’t register or develop key data to take advantage from the state of the art knowledge on the domain, we have promised to approach the factor distance in a future work due to the extent of the topic. This paper fulfill that promise bringing a review of the literature especially dealing with modelling the geographical area of recruiting students of an university, where combining distance with the proximate key factors previously reviewed, complete the meta-analysis of existing literature we have started a year ago. Beyond the theoretical benefit from a practical perspective, the metaanalysis aimed at synthesizing elements of good practice that can be applied to the local university system.

  2. Housing price forecastability: A factor analysis

    DEFF Research Database (Denmark)

    Møller, Stig Vinther; Bork, Lasse

    2017-01-01

    We examine U.S. housing price forecastability using principal component analysis (PCA), partial least squares (PLS), and sparse PLS (SPLS). We incorporate information from a large panel of 128 economic time series and show that macroeconomic fundamentals have strong predictive power for future...... movements in housing prices. We find that (S)PLS models systematically dominate PCA models. (S)PLS models also generate significant out-of-sample predictive power over and above the predictive power contained by the price-rent ratio, autoregressive benchmarks, and regression models based on small datasets....

  3. Safety and efficacy analysis of liposomal insulin-like growth factor-1 in a fluid gel formulation for hair-loss treatment in a hamster model.

    Science.gov (United States)

    Castro, R F; Azzalis, L A; Feder, D; Perazzo, F F; Pereira, E C; Junqueira, V B C; Rocha, K C; Machado, C D'A; Paschoal, F C; Gnann, L A; Fonseca, F L A

    2012-12-01

    Insulin-like growth factor (IGF)-1 has shown some interesting results in studies examining its use as a hair-loss treatment. IGF-1 works by regulating cellular proliferation and migration during the development of hair follicles. Hepatotoxicity and myelotoxicity were evaluated in hamsters (Mesocricetus auratus) after topical application of the liquid gel vehicle (placebo), 1% IGF-1 or 3% IGF-1. No significant difference in the levels of aspartate aminotransferase or alanine aminotransferase was found between the control and treated groups. ELISA did not shown any increase in the plasma level of IGF-1. A haematopoietic niche was found, but it was not associated with myelotoxicity. Efficacy was determined by dermatoscopy analysis of hair density and microscopy analysis of hair diameter, with hair found to be thicker and with more rapid growth in the 3% group than in either the 1% group or the control group. These results strongly suggest that liposomal IGF-1 in a liquid gel formulation is a safe and efficient treatment for hair loss. © The Author(s). CED © 2012 British Association of Dermatologists.

  4. Identification and control of factors influencing flow-accelerated corrosion in HRSG units using computational fluid dynamics modeling, full-scale air flow testing, and risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Pietrowski, Ronald L. [The Consolidated Edison Company of New York, Inc., New York, NY (United States)

    2010-11-15

    In 2009, Consolidated Edison's East River heat recovery steam generator units 10 and 20 both experienced economizer tube failures which forced each unit offline. Extensive inspections indicated that the primary failure mechanism was flow-accelerated corrosion (FAC). The inspections revealed evidence of active FAC in all 7 of the economizer modules, with the most advanced stages of degradation being noted in center modules. Analysis determined that various factors were influencing and enabling this corrosion mechanism. Computational fluid dynamics and full-scale air flow testing showed very turbulent feedwater flow prevalent in areas of the modules corresponding with the pattern of FAC damage observed through inspection. It also identified preferential flow paths, with higher flow velocities, in certain tubes directly under the inlet nozzles. A FAC risk analysis identified more general susceptibility to FAC in the areas experiencing damage due to feedwater pH, operating temperatures, local shear fluid forces, and the chemical composition of the original materials of construction. These, in combination, were the primary root causes of the failures. Corrective actions were identified, analyzed, and implemented, resulting in equipment replacements and repairs. (orig.)

  5. Factor analysis for exercise stress radionuclide ventriculography

    International Nuclear Information System (INIS)

    Hirota, Kazuyoshi; Yasuda, Mitsutaka; Oku, Hisao; Ikuno, Yoshiyasu; Takeuchi, Kazuhide; Takeda, Tadanao; Ochi, Hironobu

    1987-01-01

    Using factor analysis, a new image processing in exercise stress radionuclide ventriculography, changes in factors associated with exercise were evaluated in 14 patients with angina pectoris or old myocardial infarction. The patients were imaged in the left anterior oblique projection, and three factor images were presented on a color coded scale. Abnormal factors (AF) were observed in 6 patients before exercise, 13 during exercise, and 4 after exercise. In 7 patients, the occurrence of AF was associated with exercise. Five of them became free from AF after exercise. Three patients showing AF before exercise had aggravation of AF during exercise. Overall, the occurrence or aggravation of AF was associated with exercise in ten (71 %) of the patients. The other three patients, however, had disappearance of AF during exercise. In the last patient, none of the AF was observed throughout the study. In view of a high incidence of AF associated with exercise, the factor analysis may have the potential in evaluating cardiac reverse from the viewpoint of left ventricular wall motion abnormality. (Namekawa, K.)

  6. An Evaluation on Factors Influencing Decision making for Malaysia Disaster Management: The Confirmatory Factor Analysis Approach

    Science.gov (United States)

    Zubir, S. N. A.; Thiruchelvam, S.; Mustapha, K. N. M.; Che Muda, Z.; Ghazali, A.; Hakimie, H.

    2017-12-01

    For the past few years, natural disaster has been the subject of debate in disaster management especially in flood disaster. Each year, natural disaster results in significant loss of life, destruction of homes and public infrastructure, and economic hardship. Hence, an effective and efficient flood disaster management would assure non-futile efforts for life saving. The aim of this article is to examine the relationship between approach, decision maker, influence factor, result, and ethic to decision making for flood disaster management in Malaysia. The key elements of decision making in the disaster management were studied based on the literature. Questionnaire surveys were administered among lead agencies at East Coast of Malaysia in the state of Kelantan and Pahang. A total of 307 valid responses had been obtained for further analysis. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were carried out to analyse the measurement model involved in the study. The CFA for second-order reflective and first-order reflective measurement model indicates that approach, decision maker, influence factor, result, and ethic have a significant and direct effect on decision making during disaster. The results from this study showed that decision- making during disaster is an important element for disaster management to necessitate a successful collaborative decision making. The measurement model is accepted to proceed with further analysis known as Structural Equation Modeling (SEM) and can be assessed for the future research.

  7. Matrix factorizations, minimal models and Massey products

    International Nuclear Information System (INIS)

    Knapp, Johanna; Omer, Harun

    2006-01-01

    We present a method to compute the full non-linear deformations of matrix factorizations for ADE minimal models. This method is based on the calculation of higher products in the cohomology, called Massey products. The algorithm yields a polynomial ring whose vanishing relations encode the obstructions of the deformations of the D-branes characterized by these matrix factorizations. This coincides with the critical locus of the effective superpotential which can be computed by integrating these relations. Our results for the effective superpotential are in agreement with those obtained from solving the A-infinity relations. We point out a relation to the superpotentials of Kazama-Suzuki models. We will illustrate our findings by various examples, putting emphasis on the E 6 minimal model

  8. Mathematical models for prediction of safety factors for a simply ...

    African Journals Online (AJOL)

    From the results obtained, mathematical prediction models were developed using a least square regression analysis for bending, shear and deflection modes of failure considered in the study. The results showed that the safety factors for material, dead and live load are not unique, but they are influenced by safety index ...

  9. Correction factor for hair analysis by PIXE

    International Nuclear Information System (INIS)

    Montenegro, E.C.; Baptista, G.B.; Castro Faria, L.V. de; Paschoa, A.S.

    1980-01-01

    The application of the Particle Induced X-ray Emission (PIXE) technique to analyse quantitatively the elemental composition of hair specimens brings about some difficulties in the interpretation of the data. The present paper proposes a correction factor to account for the effects of the energy loss of the incident particle with penetration depth, and X-ray self-absorption when a particular geometrical distribution of elements in hair is assumed for calculational purposes. The correction factor has been applied to the analysis of hair contents Zn, Cu and Ca as a function of the energy of the incident particle. (orig.)

  10. Boolean Factor Analysis by Attractor Neural Network

    Czech Academy of Sciences Publication Activity Database

    Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.

    2007-01-01

    Roč. 18, č. 3 (2007), s. 698-707 ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007

  11. Correction factor for hair analysis by PIXE

    International Nuclear Information System (INIS)

    Montenegro, E.C.; Baptista, G.B.; Castro Faria, L.V. de; Paschoa, A.S.

    1979-06-01

    The application of the Particle Induced X-ray Emission (PIXE) technique to analyse quantitatively the elemental composition of hair specimens brings about some difficulties in the interpretation of the data. The present paper proposes a correction factor to account for the effects of energy loss of the incident particle with penetration depth, and x-ray self-absorption when a particular geometrical distribution of elements in hair is assumed for calculational purposes. The correction factor has been applied to the analysis of hair contents Zn, Cu and Ca as a function of the energy of the incident particle.(Author) [pt

  12. Confirmatory factor analysis using Microsoft Excel.

    Science.gov (United States)

    Miles, Jeremy N V

    2005-11-01

    This article presents a method for using Microsoft (MS) Excel for confirmatory factor analysis (CFA). CFA is often seen as an impenetrable technique, and thus, when it is taught, there is frequently little explanation of the mechanisms or underlying calculations. The aim of this article is to demonstrate that this is not the case; it is relatively straightforward to produce a spreadsheet in MS Excel that can carry out simple CFA. It is possible, with few or no programming skills, to effectively program a CFA analysis and, thus, to gain insight into the workings of the procedure.

  13. A kernel version of spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

    . Schölkopf et al. introduce kernel PCA. Shawe-Taylor and Cristianini is an excellent reference for kernel methods in general. Bishop and Press et al. describe kernel methods among many other subjects. Nielsen and Canty use kernel PCA to detect change in univariate airborne digital camera images. The kernel...... version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...

  14. Two Expectation-Maximization Algorithms for Boolean Factor Analysis

    Czech Academy of Sciences Publication Activity Database

    Frolov, A. A.; Húsek, Dušan; Polyakov, P.Y.

    2014-01-01

    Roč. 130, 23 April (2014), s. 83-97 ISSN 0925-2312 R&D Projects: GA ČR GAP202/10/0262 Grant - others:GA MŠk(CZ) ED1.1.00/02.0070; GA MŠk(CZ) EE.2.3.20.0073 Program:ED Institutional research plan: CEZ:AV0Z10300504 Keywords : Boolean Factor analysis * Binary Matrix factorization * Neural networks * Binary data model * Dimension reduction * Bars problem Subject RIV: IN - Informatics, Computer Science Impact factor: 2.083, year: 2014

  15. Risk Factors Analysis and Death Prediction in Some Life-Threatening Ailments Using Chi-Square Case-Based Reasoning (χ2 CBR) Model.

    Science.gov (United States)

    Adeniyi, D A; Wei, Z; Yang, Y

    2018-01-30

    A wealth of data are available within the health care system, however, effective analysis tools for exploring the hidden patterns in these datasets are lacking. To alleviate this limitation, this paper proposes a simple but promising hybrid predictive model by suitably combining the Chi-square distance measurement with case-based reasoning technique. The study presents the realization of an automated risk calculator and death prediction in some life-threatening ailments using Chi-square case-based reasoning (χ 2 CBR) model. The proposed predictive engine is capable of reducing runtime and speeds up execution process through the use of critical χ 2 distribution value. This work also showcases the development of a novel feature selection method referred to as frequent item based rule (FIBR) method. This FIBR method is used for selecting the best feature for the proposed χ 2 CBR model at the preprocessing stage of the predictive procedures. The implementation of the proposed risk calculator is achieved through the use of an in-house developed PHP program experimented with XAMP/Apache HTTP server as hosting server. The process of data acquisition and case-based development is implemented using the MySQL application. Performance comparison between our system, the NBY, the ED-KNN, the ANN, the SVM, the Random Forest and the traditional CBR techniques shows that the quality of predictions produced by our system outperformed the baseline methods studied. The result of our experiment shows that the precision rate and predictive quality of our system in most cases are equal to or greater than 70%. Our result also shows that the proposed system executes faster than the baseline methods studied. Therefore, the proposed risk calculator is capable of providing useful, consistent, faster, accurate and efficient risk level prediction to both the patients and the physicians at any time, online and on a real-time basis.

  16. Confirmatory Factor Analysis of the WISC-III with Child Psychiatric Inpatients.

    Science.gov (United States)

    Tupa, David J.; Wright, Margaret O'Dougherty; Fristad, Mary A.

    1997-01-01

    Factor models of the Wechsler Intelligence Scale for Children-Third Edition (WISC-III) for one, two, three, and four factors were tested using confirmatory factor analysis with a sample of 177 child psychiatric inpatients. The four-factor model proposed in the WISC-III manual provided the best fit to the data. (SLD)

  17. Snow model analysis.

    Science.gov (United States)

    2014-01-01

    This study developed a new snow model and a database which warehouses geometric, weather and traffic : data on New Jersey highways. The complexity of the model development lies in considering variable road : width, different spreading/plowing pattern...

  18. Analysis of mineral phases in coal utilizing factor analysis

    International Nuclear Information System (INIS)

    Roscoe, B.A.; Hopke, P.K.

    1982-01-01

    The mineral phase inclusions of coal are discussed. The contribution of these to a coal sample are determined utilizing several techniques. Neutron activation analysis in conjunction with coal washability studies have produced some information on the general trends of elemental variation in the mineral phases. These results have been enhanced by the use of various statistical techniques. The target transformation factor analysis is specifically discussed and shown to be able to produce elemental profiles of the mineral phases in coal. A data set consisting of physically fractionated coal samples was generated. These samples were analyzed by neutron activation analysis and then their elemental concentrations examined using TTFA. Information concerning the mineral phases in coal can thus be acquired from factor analysis even with limited data. Additional data may permit the resolution of additional mineral phases as well as refinement of theose already identified

  19. A Beginner’s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis

    Directory of Open Access Journals (Sweden)

    An Gie Yong

    2013-10-01

    Full Text Available The following paper discusses exploratory factor analysis and gives an overview of the statistical technique and how it is used in various research designs and applications. A basic outline of how the technique works and its criteria, including its main assumptions are discussed as well as when it should be used. Mathematical theories are explored to enlighten students on how exploratory factor analysis works, an example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.

  20. Actor-Partner Interdependence Model Analysis of Sexual Communication and Relationship/Family Planning Factors Among Immigrant Latino Couples in the United States.

    Science.gov (United States)

    Matsuda, Yui

    2017-05-01

    The Latino population in the United States is quickly growing, and its unintended pregnancy rate is increasing. To decrease unintended pregnancies, couples must mutually agree on family planning. Communication between partners is one key factor identified in successful family planning for couples. Therefore, the purpose of this study was to examine sexual communication and its associations with sexual relationship power, general communication, and views on family planning. The Actor-Partner Interdependence Model was used to analyze dyadic influences of the chosen variables. Forty immigrant Latino couples were recruited from prenatal care clinics. The study results were grouped according to the three types of power structures: exhibition of men's traditional machismo values, exhibition of women's increased power in their relationships, and exhibition of men's and women's own empowerment with sexual communication. There was a negative association between men's views on family planning and women's sexual communication (exhibition of machismo values); a negative association between women's sexual relationship power and their partners' sexual communication (exhibition of women's increased power); and positive associations between men's and women's general communication and sexual communication (exhibition of men's and women's own empowerment). Dyadic influences of sexual communication and associated variables need to be incorporated into interventions to facilitate family planning for couples.

  1. Actor–Partner Interdependence Model Analysis of Sexual Communication and Relationship/Family Planning Factors Among Immigrant Latino Couples in the United States

    Science.gov (United States)

    Matsuda, Yui

    2017-01-01

    The Latino population in the United States is quickly growing, and its unintended pregnancy rate is increasing. To decrease unintended pregnancies, couples must mutually agree on family planning. Communication between partners is one key factor identified in successful family planning for couples. Therefore, the purpose of this study was to examine sexual communication and its associations with sexual relationship power, general communication, and views on family planning. The Actor–Partner Interdependence Model was used to analyze dyadic influences of the chosen variables. Forty immigrant Latino couples were recruited from prenatal care clinics. The study results were grouped according to the three types of power structures: exhibition of men’s traditional machismo values, exhibition of women’s increased power in their relationships, and exhibition of men’s and women’s own empowerment with sexual communication. There was a negative association between men’s views on family planning and women’s sexual communication (exhibition of machismo values); a negative association between women’s sexual relationship power and their partners’ sexual communication (exhibition of women’s increased power); and positive associations between men’s and women’s general communication and sexual communication (exhibition of men’s and women’s own empowerment). Dyadic influences of sexual communication and associated variables need to be incorporated into interventions to facilitate family planning for couples. PMID:27367797

  2. Biosphere dose conversion Factor Importance and Sensitivity Analysis

    International Nuclear Information System (INIS)

    M. Wasiolek

    2004-01-01

    This report presents importance and sensitivity analysis for the environmental radiation model for Yucca Mountain, Nevada (ERMYN). ERMYN is a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis concerns the output of the model, biosphere dose conversion factors (BDCFs) for the groundwater, and the volcanic ash exposure scenarios. It identifies important processes and parameters that influence the BDCF values and distributions, enhances understanding of the relative importance of the physical and environmental processes on the outcome of the biosphere model, includes a detailed pathway analysis for key radionuclides, and evaluates the appropriateness of selected parameter values that are not site-specific or have large uncertainty

  3. Determining the Number of Factors in P-Technique Factor Analysis

    Science.gov (United States)

    Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael

    2017-01-01

    Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…

  4. Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

    Science.gov (United States)

    Roberson, Richard B; Elliott, Timothy R; Chang, Jessica E; Hill, Jessica N

    2014-11-01

    Our objective was to examine the use and quality of exploratory factor analysis (EFA) in articles published in Rehabilitation Psychology. Trained raters examined 66 separate exploratory factor analyses in 47 articles published between 1999 and April 2014. The raters recorded the aim of the EFAs, the distributional statistics, sample size, factor retention method(s), extraction and rotation method(s), and whether the pattern coefficients, structure coefficients, and the matrix of association were reported. The primary use of the EFAs was scale development, but the most widely used extraction and rotation method was principle component analysis, with varimax rotation. When determining how many factors to retain, multiple methods (e.g., scree plot, parallel analysis) were used most often. Many articles did not report enough information to allow for the duplication of their results. EFA relies on authors' choices (e.g., factor retention rules extraction, rotation methods), and few articles adhered to all of the best practices. The current findings are compared to other empirical investigations into the use of EFA in published research. Recommendations for improving EFA reporting practices in rehabilitation psychology research are provided.

  5. Exploratory Factor Analysis With Small Samples and Missing Data.

    Science.gov (United States)

    McNeish, Daniel

    2017-01-01

    Exploratory factor analysis (EFA) is an extremely popular method for determining the underlying factor structure for a set of variables. Due to its exploratory nature, EFA is notorious for being conducted with small sample sizes, and recent reviews of psychological research have reported that between 40% and 60% of applied studies have 200 or fewer observations. Recent methodological studies have addressed small size requirements for EFA models; however, these models have only considered complete data, which are the exception rather than the rule in psychology. Furthermore, the extant literature on missing data techniques with small samples is scant, and nearly all existing studies focus on topics that are not of primary interest to EFA models. Therefore, this article presents a simulation to assess the performance of various missing data techniques for EFA models with both small samples and missing data. Results show that deletion methods do not extract the proper number of factors and estimate the factor loadings with severe bias, even when data are missing completely at random. Predictive mean matching is the best method overall when considering extracting the correct number of factors and estimating factor loadings without bias, although 2-stage estimation was a close second.

  6. Analysis of nanomechanical properties of Borrelia burgdorferi spirochetes under the influence of lytic factors in an in vitro model using atomic force microscopy

    Directory of Open Access Journals (Sweden)

    Małgorzata Tokarska-Rodak

    2015-11-01

    Full Text Available Background: Atomic force microscopy (AFM is an experimental technique which recently has been used in biology, microbiology, and medicine to investigate the topography of surfaces and in the evaluation of mechanical properties of cells. The aim of this study was to evaluate the influence of the complement system and specific anti-Borrelia antibodies in in vitro conditions on the modification of nanomechanical features of B. burgdorferi B31 cells. Material and methods: In order to assess the influence of the complement system and anti-Borrelia antibodies on B. burgdorferi s.s. B31 spirochetes, the bacteria were incubated together with plasma of identified status. The samples were applied on the surface of mica disks. Young’s modulus and adhesive forces were analyzed with a NanoScope V, MultiMode 8 AFM microscope (Bruker by the PeakForce QNM technique in air using NanoScope Analysis 1.40 software (Bruker.Results/Conclusion: The average value of flexibility of spirochetes’ surface expressed by Young’s modulus was 10185.32 MPa, whereas the adhesion force was 3.68 nN. AFM is a modern tool with a broad spectrum of observational and measurement abilities. Young’s modulus and the adhesion force can be treated as parameters in the evaluation of intensity and changes which take place in pathogenic microorganisms under the influence of various lytic factors. The visualization of the changes in association with nanomechanical features provides a realistic portrayal of the lytic abilities of the elements of the innate and adaptive human immune system.

  7. Warranty claim analysis considering human factors

    International Nuclear Information System (INIS)

    Wu Shaomin

    2011-01-01

    Warranty claims are not always due to product failures. They can also be caused by two types of human factors. On the one hand, consumers might claim warranty due to misuse and/or failures caused by various human factors. Such claims might account for more than 10% of all reported claims. On the other hand, consumers might not be bothered to claim warranty for failed items that are still under warranty, or they may claim warranty after they have experienced several intermittent failures. These two types of human factors can affect warranty claim costs. However, research in this area has received rather little attention. In this paper, we propose three models to estimate the expected warranty cost when the two types of human factors are included. We consider two types of failures: intermittent and fatal failures, which might result in different claim patterns. Consumers might report claims after a fatal failure has occurred, and upon intermittent failures they might report claims after a number of failures have occurred. Numerical examples are given to validate the results derived.

  8. Chiral analysis of baryon form factors

    Energy Technology Data Exchange (ETDEWEB)

    Gail, T.A.

    2007-11-08

    This work presents an extensive theoretical investigation of the structure of the nucleon within the standard model of elementary particle physics. In particular, the long range contributions to a number of various form factors parametrizing the interactions of the nucleon with an electromagnetic probe are calculated. The theoretical framework for those calculations is chiral perturbation theory, the exact low energy limit of Quantum Chromo Dynamics, which describes such long range contributions in terms of a pion-cloud. In this theory, a nonrelativistic leading one loop order calculation of the form factors parametrizing the vector transition of a nucleon to its lowest lying resonance, the {delta}, a covariant calculation of the isovector and isoscalar vector form factors of the nucleon at next to leading one loop order and a covariant calculation of the isoscalar and isovector generalized vector form factors of the nucleon at leading one loop order are performed. In order to perform consistent loop calculations in the covariant formulation of chiral perturbation theory an appropriate renormalization scheme is defined in this work. All theoretical predictions are compared to phenomenology and results from lattice QCD simulations. These comparisons allow for a determination of the low energy constants of the theory. Furthermore, the possibility of chiral extrapolation, i.e. the extrapolation of lattice data from simulations at large pion masses down to the small physical pion mass is studied in detail. Statistical as well as systematic uncertainties are estimated for all results throughout this work. (orig.)

  9. Five-Factor Model of Personality, Work Behavior Self-Efficacy, and Length of Prior Employment for Individuals with Disabilities: An Exploratory Analysis

    Science.gov (United States)

    O'Sullivan, Deirdre; Strauser, David R.; Wong, Alex W. K.

    2012-01-01

    With the continued lower employment rate for persons with disabilities, researchers are focusing more on barriers to employment that reach beyond functional impairment. Personality and self-efficacy have consistently been important factors when considering employment outcomes for persons without disability; less is known about these factors as…

  10. Kernel parameter dependence in spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    kernel PCA. Shawe-Taylor and Cristianini [4] is an excellent reference for kernel methods in general. Bishop [5] and Press et al. [6] describe kernel methods among many other subjects. The kernel version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional...... feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply a kernel version of maximum autocorrelation factor (MAF) [7, 8] analysis to irregularly sampled stream sediment geochemistry data from South Greenland and illustrate the dependence...... of the kernel width. The 2,097 samples each covering on average 5 km2 are analyzed chemically for the content of 41 elements....

  11. Factors influencing creep model equation selection

    International Nuclear Information System (INIS)

    Holdsworth, S.R.; Askins, M.; Baker, A.; Gariboldi, E.; Holmstroem, S.; Klenk, A.; Ringel, M.; Merckling, G.; Sandstrom, R.; Schwienheer, M.; Spigarelli, S.

    2008-01-01

    During the course of the EU-funded Advanced-Creep Thematic Network, ECCC-WG1 reviewed the applicability and effectiveness of a range of model equations to represent the accumulation of creep strain in various engineering alloys. In addition to considering the experience of network members, the ability of several models to describe the deformation characteristics of large single and multi-cast collations of ε(t,T,σ) creep curves have been evaluated in an intensive assessment inter-comparison activity involving three steels, 21/4 CrMo (P22), 9CrMoVNb (Steel-91) and 18Cr13NiMo (Type-316). The choice of the most appropriate creep model equation for a given application depends not only on the high-temperature deformation characteristics of the material under consideration, but also on the characteristics of the dataset, the number of casts for which creep curves are available and on the strain regime for which an analytical representation is required. The paper focuses on the factors which can influence creep model selection and model-fitting approach for multi-source, multi-cast datasets

  12. Survival analysis models and applications

    CERN Document Server

    Liu, Xian

    2012-01-01

    Survival analysis concerns sequential occurrences of events governed by probabilistic laws.  Recent decades have witnessed many applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed techniques. Readers will learn how to perform analysis of survival data by following numerous empirical illustrations in SAS. Survival Analysis: Models and Applications: Presents basic techniques before leading onto some of the most advanced topics in survival analysis.Assumes only a minimal knowledge of SAS whilst enablin

  13. Human factors review for Severe Accident Sequence Analysis (SASA)

    International Nuclear Information System (INIS)

    Krois, P.A.; Haas, P.M.; Manning, J.J.; Bovell, C.R.

    1984-01-01

    The paper will discuss work being conducted during this human factors review including: (1) support of the Severe Accident Sequence Analysis (SASA) Program based on an assessment of operator actions, and (2) development of a descriptive model of operator severe accident management. Research by SASA analysts on the Browns Ferry Unit One (BF1) anticipated transient without scram (ATWS) was supported through a concurrent assessment of operator performance to demonstrate contributions to SASA analyses from human factors data and methods. A descriptive model was developed called the Function Oriented Accident Management (FOAM) model, which serves as a structure for bridging human factors, operations, and engineering expertise and which is useful for identifying needs/deficiencies in the area of accident management. The assessment of human factors issues related to ATWS required extensive coordination with SASA analysts. The analysis was consolidated primarily to six operator actions identified in the Emergency Procedure Guidelines (EPGs) as being the most critical to the accident sequence. These actions were assessed through simulator exercises, qualitative reviews, and quantitative human reliability analyses. The FOAM descriptive model assumes as a starting point that multiple operator/system failures exceed the scope of procedures and necessitates a knowledge-based emergency response by the operators. The FOAM model provides a functionally-oriented structure for assembling human factors, operations, and engineering data and expertise into operator guidance for unconventional emergency responses to mitigate severe accident progression and avoid/minimize core degradation. Operators must also respond to potential radiological release beyond plant protective barriers. Research needs in accident management and potential uses of the FOAM model are described. 11 references, 1 figure

  14. Workplace Innovation: Exploratory and Confirmatory Factor Analysis for Construct Validation

    Directory of Open Access Journals (Sweden)

    Wipulanusat Warit

    2017-06-01

    Full Text Available Workplace innovation enables the development and improvement of products, processes and services leading simultaneously to improvement in organisational performance. This study has the purpose of examining the factor structure of workplace innovation. Survey data, extracted from the 2014 APS employee census, comprising 3,125 engineering professionals in the Commonwealth of Australia’s departments were analysed using exploratory factor analysis (EFA and confirmatory factor analysis (CFA. EFA returned a two-factor structure explaining 69.1% of the variance of the construct. CFA revealed that a two-factor structure was indicated as a validated model (GFI = 0.98, AGFI = 0.95, RMSEA = 0.08, RMR = 0.02, IFI = 0.98, NFI = 0.98, CFI = 0.98, and TLI = 0.96. Both factors showed good reliability of the scale (Individual creativity: α = 0.83, CR = 0.86, and AVE = 0.62; Team Innovation: α = 0.82, CR = 0.88, and AVE = 0.61. These results confirm that the two factors extracted for characterising workplace innovation included individual creativity and team innovation.

  15. CMS analysis school model

    International Nuclear Information System (INIS)

    Malik, S; Bloom, K; Shipsey, I; Cavanaugh, R; Klima, B; Chan, Kai-Feng; D'Hondt, J; Narain, M; Palla, F; Rolandi, G; Schörner-Sadenius, T

    2014-01-01

    To impart hands-on training in physics analysis, CMS experiment initiated the concept of CMS Data Analysis School (CMSDAS). It was born over three years ago at the LPC (LHC Physics Centre), Fermilab and is based on earlier workshops held at the LPC and CLEO Experiment. As CMS transitioned from construction to the data taking mode, the nature of earlier training also evolved to include more of analysis tools, software tutorials and physics analysis. This effort epitomized as CMSDAS has proven to be a key for the new and young physicists to jump start and contribute to the physics goals of CMS by looking for new physics with the collision data. With over 400 physicists trained in six CMSDAS around the globe, CMS is trying to engage the collaboration in its discovery potential and maximize physics output. As a bigger goal, CMS is striving to nurture and increase engagement of the myriad talents, in the development of physics, service, upgrade, education of those new to CMS and the career development of younger members. An extension of the concept to the dedicated software and hardware schools is also planned, keeping in mind the ensuing upgrade phase.

  16. CMS Analysis School Model

    Energy Technology Data Exchange (ETDEWEB)

    Malik, S. [Nebraska U.; Shipsey, I. [Purdue U.; Cavanaugh, R. [Illinois U., Chicago; Bloom, K. [Nebraska U.; Chan, Kai-Feng [Taiwan, Natl. Taiwan U.; D' Hondt, J. [Vrije U., Brussels; Klima, B. [Fermilab; Narain, M. [Brown U.; Palla, F. [INFN, Pisa; Rolandi, G. [CERN; Schörner-Sadenius, T. [DESY

    2014-01-01

    To impart hands-on training in physics analysis, CMS experiment initiated the concept of CMS Data Analysis School (CMSDAS). It was born over three years ago at the LPC (LHC Physics Centre), Fermilab and is based on earlier workshops held at the LPC and CLEO Experiment. As CMS transitioned from construction to the data taking mode, the nature of earlier training also evolved to include more of analysis tools, software tutorials and physics analysis. This effort epitomized as CMSDAS has proven to be a key for the new and young physicists to jump start and contribute to the physics goals of CMS by looking for new physics with the collision data. With over 400 physicists trained in six CMSDAS around the globe, CMS is trying to engage the collaboration in its discovery potential and maximize physics output. As a bigger goal, CMS is striving to nurture and increase engagement of the myriad talents, in the development of physics, service, upgrade, education of those new to CMS and the career development of younger members. An extension of the concept to the dedicated software and hardware schools is also planned, keeping in mind the ensuing upgrade phase.

  17. Analysis of transfer reactions: determination of spectroscopic factors

    Energy Technology Data Exchange (ETDEWEB)

    Keeley, N. [CEA Saclay, Dept. d' Astrophysique, de Physique des Particules de Physique Nucleaire et de l' Instrumentation Associee (DSM/DAPNIA/SPhN), 91- Gif sur Yvette (France); The Andrzej So an Institute for Nuclear Studies, Dept. of Nuclear Reactions, Warsaw (Poland)

    2007-07-01

    An overview of the most popular models used for the analysis of direct reaction data is given, concentrating on practical aspects. The 4 following models (in order of increasing sophistication): the distorted wave born approximation (DWBA), the adiabatic model, the coupled channels born approximation, and the coupled reaction channels are briefly described. As a concrete example, the C{sup 12}(d,p)C{sup 13} reaction at an incident deuteron energy of 30 MeV is analysed with progressively more physically sophisticated models. The effect of the choice of the reaction model on the spectroscopic information extracted from the data is investigated and other sources of uncertainty in the derived spectroscopic factors are discussed. We have showed that the choice of the reaction model can significantly influence the nuclear structure information, particularly the spectroscopic factors or amplitudes but occasionally also the spin-parity, that we wish to extract from direct reaction data. We have also demonstrated that the DWBA can fail to give a satisfactory description of transfer data but when the tenets of the theory are fulfilled DWBA can work very well and will yield the same results as most sophisticated models. The use of global rather than fitted optical potentials can also lead to important differences in the extracted spectroscopic factors.

  18. Sea level rise and the geoid: factor analysis approach

    Directory of Open Access Journals (Sweden)

    Alexey Sadovski

    2013-08-01

    Full Text Available Sea levels are rising around the world, and this is a particular concern along most of the coasts of the United States. A 1989 EPA report shows that sea levels rose 5-6 inches more than the global average along the Mid-Atlantic and Gulf Coasts in the last century. The main reason for this is coastal land subsidence. This sea level rise is considered more as relative sea level rise than global sea level rise. Thus, instead of studying sea level rise globally, this paper describes a statistical approach by using factor analysis of regional sea level rates of change. Unlike physical models and semi-empirical models that attempt to approach how much and how fast sea levels are changing, this methodology allows for a discussion of the factor(s that statistically affects sea level rates of change, and seeks patterns to explain spatial correlations.

  19. Functional dynamic factor models with application to yield curve forecasting

    KAUST Repository

    Hays, Spencer

    2012-09-01

    Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. Model estimation is achieved through an expectation- maximization algorithm, where the time series parameters and factor loading curves are simultaneously estimated in a single step. Efficient computing is implemented and a data-driven smoothing parameter is nicely incorporated. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting.

  20. ORGANISATIONAL CULTURE ANALYSIS MODEL

    OpenAIRE

    Mihaela Simona Maracine

    2012-01-01

    The studies and researches undertaken have demonstrated the importance of studying organisational culture because of the practical valences it presents and because it contributes to increasing the organisation’s performance. The analysis of the organisational culture’s dimensions allows observing human behaviour within the organisation and highlighting reality, identifying the strengths and also the weaknesses which have an impact on its functionality and development. In this paper, we try to...

  1. A 3-factor model for the FACIT-Sp.

    Science.gov (United States)

    Canada, Andrea L; Murphy, Patricia E; Fitchett, George; Peterman, Amy H; Schover, Leslie R

    2008-09-01

    The 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-being Scale (FACIT-Sp) is a popular measure of the religious/spiritual (R/S) components of quality of life (QoL) in patients with cancer. The original factor analyses of the FACIT-Sp supported two factors: Meaning/Peace and Faith. Because Meaning suggests a cognitive aspect of R/S and Peace an affective component, we hypothesized a 3-factor solution: Meaning, Peace, and Faith. Participants were 240 long-term female survivors of cancer who completed the FACIT-Sp, the SF-12, and the BSI 18. We used confirmatory factor analysis to compare the 2- and 3-factor models of the FACIT-Sp and subsequently assessed associations between the resulting solutions and QoL domains. Survivors averaged 44 years of age and 10 years post-diagnosis. A 3-factor solution of the FACIT-Sp significantly improved the fit of the model to the data over the original 2-factor structure (Delta chi(2)=72.36, df=2, p<0.001). Further adjustments to the 3-factor model resulted in a final solution with even better goodness-of-fit indices (chi(2)=59.11, df=1, p=0.13, CFI=1.00, SMRM=0.05).The original Meaning/Peace factor controlling for Faith was associated with mental (r=0.63, p<0.000) and physical (r=0.22, p<0.01) health on the SF-12, and the original Faith factor controlling for Meaning/Peace was negatively associated with mental health (r=-0.15, p<0.05). The 3-factor model was more informative. Specifically, using partial correlations, the Peace factor was only related to mental health (r=0.53, p<0.001); Meaning was related to both physical (r=0.18, p<0.01) and mental (r=0.17, p<0.01) health; and Faith was negatively associated with mental health (r=-0.17, p<0.05). The results of this study support a 3-factor solution of the FACIT-Sp. The new solution not only represents a psychometric improvement over the original, but also enables a more detailed examination of the contribution of different dimensions of R/S to QoL. (c

  2. Worry About Caregiving Performance: A Confirmatory Factor Analysis

    Directory of Open Access Journals (Sweden)

    Ruijie Li

    2018-03-01

    Full Text Available Recent studies on the Zarit Burden Interview (ZBI support the existence of a unique factor, worry about caregiving performance (WaP, beyond role and personal strain. Our current study aims to confirm the existence of WaP within the multidimensionality of ZBI and to determine if predictors of WaP differ from the role and personal strain. We performed confirmatory factor analysis (CFA on 466 caregiver-patient dyads to compare between one-factor (total score, two-factor (role/personal strain, three-factor (role/personal strain and WaP, and four-factor models (role strain split into two factors. We conducted linear regression analyses to explore the relationships between different ZBI factors with socio-demographic and disease characteristics, and investigated the stage-dependent differences between WaP with role and personal strain by dyadic relationship. The four-factor structure that incorporated WaP and split role strain into two factors yielded the best fit. Linear regression analyses reveal that different variables significantly predict WaP (adult child caregiver and Neuropsychiatric Inventory Questionnaire (NPI-Q severity from role/personal strain (adult child caregiver, instrumental activities of daily living, and NPI-Q distress. Unlike other factors, WaP was significantly endorsed in early cognitive impairment. Among spouses, WaP remained low across Clinical Dementia Rating (CDR stages until a sharp rise in CDR 3; adult child and sibling caregivers experience a gradual rise throughout the stages. Our results affirm the existence of WaP as a unique factor. Future research should explore the potential of WaP as a possible intervention target to improve self-efficacy in the milder stages of burden.

  3. A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis

    Science.gov (United States)

    Edwards, Michael C.

    2010-01-01

    Item factor analysis has a rich tradition in both the structural equation modeling and item response theory frameworks. The goal of this paper is to demonstrate a novel combination of various Markov chain Monte Carlo (MCMC) estimation routines to estimate parameters of a wide variety of confirmatory item factor analysis models. Further, I show…

  4. An evaluation of energy-environment-economic efficiency for EU, APEC and ASEAN countries: Design of a Target-Oriented DFM model with fixed factors in Data Envelopment Analysis

    International Nuclear Information System (INIS)

    Suzuki, Soushi; Nijkamp, Peter

    2016-01-01

    This paper aims to offer an advanced assessment methodology for sustainable national energy-environment-economic efficiency strategies, based on an extended Data Envelopment Analysis (DEA). The use of novel efficiency-improving approaches based on DEA originates from the so-called Distance Friction Minimisation (DFM) method. To design a feasible improvement strategy for low-efficiency DMUs, we develop here a Target-Oriented (TO) DFM model. However, in many real-world cases input factors may not be flexibly adjusted in the short run. In this study, we integrate the TO-DFM model with a fixed (inflexible) factor (FF) approach to cope with such more realistic circumstances. Super-efficiency DEA is next used in our comparative study on the efficiency assessment of energy-environment-economic targets for the EU, APEC and ASEAN (A&A) countries, employing appropriate data sets from the years 2003 to 2012. We consider two inputs (primary energy consumption and population) and two outputs (CO 2 and GDP), including a fixed input factor (viz. population). On the basis of our DEA analysis results, EU countries appear to exhibit generally a higher efficiency than A&A countries. The above-mentioned TO-DFM-FF projection model is able to address realistic circumstances and requirements in an operational sustainability strategy for efficiency improvement in inefficient countries in the A&A region. - Highlights: • We examine energy-environment-economic efficiency in European and A&A countries. • We present an operational efficiency improvement strategy using DEA. • European countries tend to have higher energy efficiency than A&A countries. • The study provides efficiency-enhancing strategic paths for inefficient countries.

  5. Liquidity indicator for the Croatian economy – Factor analysis approach

    Directory of Open Access Journals (Sweden)

    Mirjana Čižmešija

    2014-12-01

    Full Text Available Croatian business surveys (BS are conducted in the manufacturing industry, retail trade and construction sector. In all of these sectors, manager´s assessments of liquidity are measured. The aim of the paper was to form a new composite liquidity indicator by including business survey liquidity measures from all three covered economic sectors in the Croatian economy mentioned above. In calculating the leading indicator, a factor analysis approach was used. However, this kind of indicator does not exist in a Croatia or in any other European economy. Furthermore, the issue of Croatian companies´ illiquidity is highly neglected in the literature. The empirical analysis consists of two parts. In the first part the new liquidity indicator was formed using factor analysis. One factor (representing the new liquidity indicator; LI was extracted out of the three liquidity variables in three economic sectors. This factor represents the new liquidity indicator. In the second part, econometric models were applied in order to investigate the forecasting properties of the new business survey liquidity indicator, when predicting the direction of changes in Croatian industrial production. The quarterly data used in the research covered the period from January 2000 to April 2013. Based on econometric analysis, it can be concluded that the LI is a leading indicator of Croatia’s industrial production with better forecasting properties then the standard liquidity indicators (formed in a manufacturing industry.

  6. ROCK PROPERTIES MODEL ANALYSIS MODEL REPORT

    International Nuclear Information System (INIS)

    Clinton Lum

    2002-01-01

    The purpose of this Analysis and Model Report (AMR) is to document Rock Properties Model (RPM) 3.1 with regard to input data, model methods, assumptions, uncertainties and limitations of model results, and qualification status of the model. The report also documents the differences between the current and previous versions and validation of the model. The rock properties models are intended principally for use as input to numerical physical-process modeling, such as of ground-water flow and/or radionuclide transport. The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. This work was conducted in accordance with the following planning documents: WA-0344, ''3-D Rock Properties Modeling for FY 1998'' (SNL 1997, WA-0358), ''3-D Rock Properties Modeling for FY 1999'' (SNL 1999), and the technical development plan, Rock Properties Model Version 3.1, (CRWMS MandO 1999c). The Interim Change Notice (ICNs), ICN 02 and ICN 03, of this AMR were prepared as part of activities being conducted under the Technical Work Plan, TWP-NBS-GS-000003, ''Technical Work Plan for the Integrated Site Model, Process Model Report, Revision 01'' (CRWMS MandO 2000b). The purpose of ICN 03 is to record changes in data input status due to data qualification and verification activities. These work plans describe the scope, objectives, tasks, methodology, and implementing procedures for model construction. The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. The work scope for this activity consists of the following: (1) Conversion of the input data (laboratory measured porosity data, x-ray diffraction mineralogy, petrophysical calculations of bound water, and petrophysical calculations of porosity) for each borehole into stratigraphic coordinates; (2) Re-sampling and merging of data sets; (3) Development of geostatistical simulations of porosity; (4

  7. Intercity Travel Demand Analysis Model

    OpenAIRE

    Ming Lu; Hai Zhu; Xia Luo; Lei Lei

    2014-01-01

    It is well known that intercity travel is an important component of travel demand which belongs to short distance corridor travel. The conventional four-step method is no longer suitable for short distance corridor travel demand analysis for the time spent on urban traffic has a great impact on traveler's main mode choice. To solve this problem, the author studied the existing intercity travel demand analysis model, then improved it based on the study, and finally established a combined model...

  8. Uncertainty analysis of environmental models

    International Nuclear Information System (INIS)

    Monte, L.

    1990-01-01

    In the present paper an evaluation of the output uncertainty of an environmental model for assessing the transfer of 137 Cs and 131 I in the human food chain are carried out on the basis of a statistical analysis of data reported by the literature. The uncertainty analysis offers the oppotunity of obtaining some remarkable information about the uncertainty of models predicting the migration of non radioactive substances in the environment mainly in relation to the dry and wet deposition

  9. Multiscale Signal Analysis and Modeling

    CERN Document Server

    Zayed, Ahmed

    2013-01-01

    Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image proce...

  10. [Cultural regionalization for Notopterygium incisum based on 3S technology platform. I. Evaluation for growth suitability for N. incisum based on ecological factors analysis by Maxent and ArcGIS model].

    Science.gov (United States)

    Sun, Hong-bing; Sun, Hui; Jiang, Shun-yuan; Zhou, Yi; Cao, Wen-long; Ji, Ming-chang; Zhy, Wen-tao; Yan, Han-jing

    2015-03-01

    Growth suitability as assessment indicators for medicinal plants cultivation was proposed based on chemical quality determination and ecological factors analysis by Maxent and ArcGIS model. Notopterygium incisum, an endangered Chinese medicinal plant, was analyzed as a case, its potential distribution areas at different suitability grade and regionalization map were formulated based on growth suitability theory. The results showed that the most suitable habitats is Sichuan province, and more than 60% of the most suitable areawas located in the western Sichuan such as Aba and Ganzi prefectures for N. incisum. The results indicated that habitat altitude, average air temperature in September, and vegetation types were the dominant factors contributing to the grade of plant growth, precipitation and slope were the major factors contributing to notopterol accumulation in its underground parts, while isoimperatorin in its underground parts was negatively corelated with precipitation and slope of its habitat. However, slope as a factor influencing chemical components seemed to be a pseudo corelationship. Therefore, there were distinguishing differences between growth suitability and quality suitability for medicinal plants, which was helpful to further research and practice of cultivation regionalization, wild resource monitoring and large-scale cultivation of traditional Chinese medicine plants.

  11. The Meaning of Higher-Order Factors in Reflective-Measurement Models

    Science.gov (United States)

    Eid, Michael; Koch, Tobias

    2014-01-01

    Higher-order factor analysis is a widely used approach for analyzing the structure of a multidimensional test. Whenever first-order factors are correlated researchers are tempted to apply a higher-order factor model. But is this reasonable? What do the higher-order factors measure? What is their meaning? Willoughby, Holochwost, Blanton, and Blair…

  12. Multivariate analysis: models and method

    International Nuclear Information System (INIS)

    Sanz Perucha, J.

    1990-01-01

    Data treatment techniques are increasingly used since computer methods result of wider access. Multivariate analysis consists of a group of statistic methods that are applied to study objects or samples characterized by multiple values. A final goal is decision making. The paper describes the models and methods of multivariate analysis

  13. Domain specific modeling and analysis

    NARCIS (Netherlands)

    Jacob, Joost Ferdinand

    2008-01-01

    It is desirable to model software systems in such a way that analysis of the systems, and tool development for such analysis, is readily possible and feasible in the context of large scientific research projects. This thesis emphasizes the methodology that serves as a basis for such developments.

  14. Sensitivity Analysis of Simulation Models

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    2009-01-01

    This contribution presents an overview of sensitivity analysis of simulation models, including the estimation of gradients. It covers classic designs and their corresponding (meta)models; namely, resolution-III designs including fractional-factorial two-level designs for first-order polynomial

  15. A multilevel analysis of the demands-control model: Is stress at work determined by factors at the group level or the individual level?

    NARCIS (Netherlands)

    Van Yperen, N.W.; Snijders, T.A.B.

    2000-01-01

    This study explored the extent to which negative health-related outcomes are associated with differences between work groups and with differences between individuals within work groups using R. A. Karasek's (1979) demands-control model. The sample consisted of 260 employees in 31 working groups of a

  16. Stochastic modeling analysis and simulation

    CERN Document Server

    Nelson, Barry L

    1995-01-01

    A coherent introduction to the techniques for modeling dynamic stochastic systems, this volume also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Suitable for advanced undergraduates and graduate-level industrial engineers and management science majors, it proposes modeling systems in terms of their simulation, regardless of whether simulation is employed for analysis. Beginning with a view of the conditions that permit a mathematical-numerical analysis, the text explores Poisson and renewal processes, Markov chains in discrete and continuous time, se

  17. Improved SVR Model for Multi-Layer Buildup Factor Calculation

    International Nuclear Information System (INIS)

    Trontl, K.; Pevec, D.; Smuc, T.

    2006-01-01

    The accuracy of point kernel method applied in gamma ray dose rate calculations in shielding design and radiation safety analysis is limited by the accuracy of buildup factors used in calculations. Although buildup factors for single-layer shields are well defined and understood, buildup factors for stratified shields represent a complex physical problem that is hard to express in mathematical terms. The traditional approach for expressing buildup factors of multi-layer shields is through semi-empirical formulas obtained by fitting the results of transport theory or Monte Carlo calculations. Such an approach requires an ad-hoc definition of the fitting function and often results with numerous and usually inadequately explained and defined correction factors added to the final empirical formula. Even more, finally obtained formulas are generally limited to a small number of predefined combinations of materials within relatively small range of gamma ray energies and shield thicknesses. Recently, a new approach has been suggested by the authors involving one of machine learning techniques called Support Vector Machines, i.e., Support Vector Regression (SVR). Preliminary investigations performed for double-layer shields revealed great potential of the method, but also pointed out some drawbacks of the developed model, mostly related to the selection of one of the parameters describing the problem (material atomic number), and the method in which the model was designed to evolve during the learning process. It is the aim of this paper to introduce a new parameter (single material buildup factor) that is to replace the existing material atomic number as an input parameter. The comparison of two models generated by different input parameters has been performed. The second goal is to improve the evolution process of learning, i.e., the experimental computational procedure that provides a framework for automated construction of complex regression models of predefined

  18. EMPLOYMENT LEVEL ANALYSIS FROM THE DETERMINANT FACTORS PERSPECTIVE

    Directory of Open Access Journals (Sweden)

    Elena Diana ŞERB

    2016-02-01

    Full Text Available Neglecting the human factor as part of the labor market causes losses for society as any activity that is initiated within it, has as a starting point, and also as a finishing point, the human intervention. The starting point of the article is represented by the projections made by the European    Commission in the Population Ageing Report in 2015 underlying assumptions and projections, and also by the projections of the United Nations report in 2015, and this resulted in many conclusions including the one that for the first time in Romania the average aging in 2015 exceeds the values measured by EU till present day, and this is reflected in the employment level (active aging population. The hypothesis behind the article is that the evolution of the population and migrants has repercussions on employment. Structured in three parts: knowledge status, the analysis of employment indicators and information about the intensity and direction of the link between a number of factors and employment level, this article aims to establish the determinant factors of employment through a research focused on the analysis of secondary sources, and also using the regression model. The most important lesson learned as a result of this research is that the labor market works with a variety of factors with a higher or lower influence, and in turn the labor market influences other factors.

  19. Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Stevens, Andrew J.; Pu, Yunchen; Sun, Yannan; Spell, Gregory; Carin, Lawrence

    2017-04-20

    We introduce new dictionary learning methods for tensor-variate data of any order. We represent each data item as a sum of Kruskal decomposed dictionary atoms within the framework of beta-process factor analysis (BPFA). Our model is nonparametric and can infer the tensor-rank of each dictionary atom. This Kruskal-Factor Analysis (KFA) is a natural generalization of BPFA. We also extend KFA to a deep convolutional setting and develop online learning methods. We test our approach on image processing and classification tasks achieving state of the art results for 2D & 3D inpainting and Caltech 101. The experiments also show that atom-rank impacts both overcompleteness and sparsity.

  20. Model of separated form factors for unilamellar vesicles

    International Nuclear Information System (INIS)

    Kiselev, M.A.; Aksenov, V.L.; Lesieur, P.; Lombardo, D.; Kiselev, A.M.

    2001-01-01

    A new model of separated form factors is proposed for the evaluation of small-angle neutron scattering curves from large unilamellar vesicles. The validity of the model was checked via comparison with the model of a hollow sphere. The model of separated form factors and the hollow sphere model give a reasonable agreement in the evaluation of vesicle parameters

  1. ANALYSIS OF FACTORS WHICH AFFECTING THE ECONOMIC GROWTH

    Directory of Open Access Journals (Sweden)

    Suparna Wijaya

    2017-03-01

    Full Text Available High economic growth and sustainable process are main conditions for sustainability of economic country development. They are also become measures of the success of the country's economy. Factors which tested in this study are economic and non-economic factors which impacting economic development. This study has a goal to explain the factors that influence on macroeconomic Indonesia. It used linear regression modeling approach. The analysis result showed that Tax Amnesty, Exchange Rate, Inflation, and interest rate, they jointly can bring effect which amounted to 77.6% on economic growth whereas the remaining 22.4% is the influenced by other variables which not observed in this study. Keywords: tax amnesty, exchange rates, inflation, SBI and economic growth

  2. Path analysis of risk factors leading to premature birth.

    Science.gov (United States)

    Fields, S J; Livshits, G; Sirotta, L; Merlob, P

    1996-01-01

    The present study tested whether various sociodemographic, anthropometric, behavioral, and medical/physiological factors act in a direct or indirect manner on the risk of prematurity using path analysis on a sample of Israeli births. The path model shows that medical complications, primarily toxemia, chorioammionitis, and a previous low birth weight delivery directly and significantly act on the risk of prematurity as do low maternal pregnancy weight gain and ethnicity. Other medical complications, including chronic hypertension, preclampsia, and placental abruption, although significantly correlated with prematurity, act indirectly on prematurity through toxemia. The model further shows that the commonly accepted sociodemographic, anthropometric, and behavioral risk factors act by modifying the development of medical complications that lead to prematurity as opposed to having a direct effect on premature delivery. © 1996 Wiley-Liss, Inc. Copyright © 1996 Wiley-Liss, Inc.

  3. How Do Executive Functions Fit with the Cattell-Horn-Carroll Model? Some Evidence from a Joint Factor Analysis of the Delis-Kaplan Executive Function System and the Woodcock-Johnson III Tests of Cognitive Abilities

    Science.gov (United States)

    Floyd, Randy G.; Bergeron, Renee; Hamilton, Gloria; Parra, Gilbert R.

    2010-01-01

    This study investigated the relations among executive functions and cognitive abilities through a joint exploratory factor analysis and joint confirmatory factor analysis of 25 test scores from the Delis-Kaplan Executive Function System and the Woodcock-Johnson III Tests of Cognitive Abilities. Participants were 100 children and adolescents…

  4. Analysis of influencing factors on public perception in contaminated site management: Simulation by structural equation modeling at four sites in China.

    Science.gov (United States)

    Li, Xiaonuo; Chen, Weiping; Cundy, Andrew B; Chang, Andrew C; Jiao, Wentao

    2018-03-15

    Public perception towards contaminated site management, a not readily quantifiable latent parameter, was linked through structural equation modeling in this paper to 22 measurable/observable manifest variables associated with the extent of information dissemination and public knowledge of soil pollution, attitude towards remediation policies, and participation in risk mitigation processes. Data obtained through a survey of 412 community residents at four remediation sites in China were employed in the model validation. The outcomes showed that public perception towards contaminated site management might be explained through selected measurable parameters in five categories, namely information disclosure, knowledge of soil pollution, expectations of remediation and redevelopment outcomes, public participation, and site policy, along with their interactions. Among these, information dissemination and attitude towards management policies exhibited significant influence in promoting positive public perception. Based on these examples, responsible agencies therefore should focus on public accessibility to reliable information, and encourage public inputs into policies for contaminated site management, in order to gain public confidence during remediation and regeneration projects. Copyright © 2018 Elsevier Ltd. All rights reserved.

  5. Factors influencing crime rates: an econometric analysis approach

    Science.gov (United States)

    Bothos, John M. A.; Thomopoulos, Stelios C. A.

    2016-05-01

    The scope of the present study is to research the dynamics that determine the commission of crimes in the US society. Our study is part of a model we are developing to understand urban crime dynamics and to enhance citizens' "perception of security" in large urban environments. The main targets of our research are to highlight dependence of crime rates on certain social and economic factors and basic elements of state anticrime policies. In conducting our research, we use as guides previous relevant studies on crime dependence, that have been performed with similar quantitative analyses in mind, regarding the dependence of crime on certain social and economic factors using statistics and econometric modelling. Our first approach consists of conceptual state space dynamic cross-sectional econometric models that incorporate a feedback loop that describes crime as a feedback process. In order to define dynamically the model variables, we use statistical analysis on crime records and on records about social and economic conditions and policing characteristics (like police force and policing results - crime arrests), to determine their influence as independent variables on crime, as the dependent variable of our model. The econometric models we apply in this first approach are an exponential log linear model and a logit model. In a second approach, we try to study the evolvement of violent crime through time in the US, independently as an autonomous social phenomenon, using autoregressive and moving average time-series econometric models. Our findings show that there are certain social and economic characteristics that affect the formation of crime rates in the US, either positively or negatively. Furthermore, the results of our time-series econometric modelling show that violent crime, viewed solely and independently as a social phenomenon, correlates with previous years crime rates and depends on the social and economic environment's conditions during previous years.

  6. Profile and Risk Factor Analysis of Unintentional Injuries in Children.

    Science.gov (United States)

    Bhamkar, Rahul; Seth, Bageshree; Setia, Maninder Singh

    2016-10-01

    To study the profile and various risk factors associated with unintentional injuries in children. The study is a cross sectional analysis of data collected from 351 children presenting with unintentional injury to a tertiary care hospital in Navi Mumbai, India. Data were collected about variables based on Haddon Phase Factor Matrix - host, environment and agent factors. Proportions for categorical variables across various groups were compared using Chi square test or Fisher's exact test. Logistic regression model was used to evaluate the factors. Falls (36 %) were the most common injuries followed by bites (23 %). Majority of children were school going children (38 %) followed by preschool children (29 %). Forty-seven percent were from lower socioeconomic class. Commonest place of injury was home (48 %) and the commonest time was evening (49 %). Though there was male predominance in injuries, the difference across gender did not vary significantly (p = 0.15). Poisonings were significantly more common in infants and toddlers and in rural population (p risk of bites compared to urban (p Profile of injuries varies widely as per the variations in agent, host and environmental factors. Socio-environmental, economic conditions and infancy-toddler age groups are predisposing risk factors for bites and poisoning. Although rural areas and lower socioeconomic class population are more vulnerable to serious types of injuries, they still lack essential basic medical care.

  7. SHMF: Interest Prediction Model with Social Hub Matrix Factorization

    Directory of Open Access Journals (Sweden)

    Chaoyuan Cui

    2017-01-01

    Full Text Available With the development of social networks, microblog has become the major social communication tool. There is a lot of valuable information such as personal preference, public opinion, and marketing in microblog. Consequently, research on user interest prediction in microblog has a positive practical significance. In fact, how to extract information associated with user interest orientation from the constantly updated blog posts is not so easy. Existing prediction approaches based on probabilistic factor analysis use blog posts published by user to predict user interest. However, these methods are not very effective for the users who post less but browse more. In this paper, we propose a new prediction model, which is called SHMF, using social hub matrix factorization. SHMF constructs the interest prediction model by combining the information of blogs posts published by both user and direct neighbors in user’s social hub. Our proposed model predicts user interest by integrating user’s historical behavior and temporal factor as well as user’s friendships, thus achieving accurate forecasts of user’s future interests. The experimental results on Sina Weibo show the efficiency and effectiveness of our proposed model.

  8. Erikson Psychosocial Stage Inventory: A Factor Analysis

    Science.gov (United States)

    Gray, Mary McPhail; And Others

    1986-01-01

    The 72-item Erikson Psychosocial Stage Inventory (EPSI) was factor analyzed for a group of 534 university freshmen and sophomore students. Seven factors emerged, which were labeled Initiative, Industry, Identity, Friendship, Dating, Goal Clarity, and Self-Confidence. Item's representing Erikson's factors, Trust and Autonomy, were dispersed across…

  9. Model of a ternary complex between activated factor VII, tissue factor and factor IX.

    Science.gov (United States)

    Chen, Shu-wen W; Pellequer, Jean-Luc; Schved, Jean-François; Giansily-Blaizot, Muriel

    2002-07-01

    Upon binding to tissue factor, FVIIa triggers coagulation by activating vitamin K-dependent zymogens, factor IX (FIX) and factor X (FX). To understand recognition mechanisms in the initiation step of the coagulation cascade, we present a three-dimensional model of the ternary complex between FVIIa:TF:FIX. This model was built using a full-space search algorithm in combination with computational graphics. With the known crystallographic complex FVIIa:TF kept fixed, the FIX docking was performed first with FIX Gla-EGF1 domains, followed by the FIX protease/EGF2 domains. Because the FIXa crystal structure lacks electron density for the Gla domain, we constructed a chimeric FIX molecule that contains the Gla-EGF1 domains of FVIIa and the EGF2-protease domains of FIXa. The FVIIa:TF:FIX complex has been extensively challenged against experimental data including site-directed mutagenesis, inhibitory peptide data, haemophilia B database mutations, inhibitor antibodies and a novel exosite binding inhibitor peptide. This FVIIa:TF:FIX complex provides a powerful tool to study the regulation of FVIIa production and presents new avenues for developing therapeutic inhibitory compounds of FVIIa:TF:substrate complex.

  10. Reformulation of Crop and Management Factor in ANSWERS Model

    Directory of Open Access Journals (Sweden)

    Yayat Hidayat

    2008-05-01

    Full Text Available Crop and management factor value is significantly corelated with outputs of ANSWERS model especially on soil erosion. Using daily crop and management factors (daily C factors, the ANSWERS model performs well in predicting soil erosion which is showed by determination coeffient (R2 = 0.89, model efficiency (0.86, and average of percentage model deviations (24.1%. Whereas using USLE C factor (2 cropping systems, predicted is much higher than measured soil erosion (over estimate. Output of the model is not statisfy; it is represented by model coefficient (0.40 and average of percentage model deviations (63.6%.

  11. A Comparative Analysis of Ability of Mimicking Portfolios in Representing the Background Factors

    OpenAIRE

    Asgharian, Hossein

    2004-01-01

    Our aim is to give a comparative analysis of ability of different factor mimicking portfolios in representing the background factors. Our analysis contains a cross-sectional regression approach, a time-series regression approach and a portfolio approach for constructing factor mimicking portfolios. The focus of the analysis is the power of mimicking portfolios in the asset pricing models. We conclude that the time series regression approach, with the book-to-market sorted portfolios as the ba...

  12. Reliability analysis and operator modelling

    International Nuclear Information System (INIS)

    Hollnagel, Erik

    1996-01-01

    The paper considers the state of operator modelling in reliability analysis. Operator models are needed in reliability analysis because operators are needed in process control systems. HRA methods must therefore be able to account both for human performance variability and for the dynamics of the interaction. A selected set of first generation HRA approaches is briefly described in terms of the operator model they use, their classification principle, and the actual method they propose. In addition, two examples of second generation methods are also considered. It is concluded that first generation HRA methods generally have very simplistic operator models, either referring to the time-reliability relationship or to elementary information processing concepts. It is argued that second generation HRA methods must recognise that cognition is embedded in a context, and be able to account for that in the way human reliability is analysed and assessed

  13. The Factors of Forming the National HR-Management Model

    Directory of Open Access Journals (Sweden)

    Elena P. Kostenko

    2017-12-01

    Full Text Available There are some factors considered in this article, which influence the forming of national HR-management model. The group-forming criterion is the nature of factors, that determine the system of HR-management as a system of corporate culture values, norms and rules of organizational behavior, ways of realization some important managing functions and dominating approaches to make decisions. This article shows that the plurality of combinations in different factors leads to forming the unique HR-management model. The geoclimatic factor influences the principles of the labor organization (orientation primarily on individual or collective forms of labor, attitude to the management experience of other countries, attitude to resources, etc., the distribution of labor resources, the level of labor mobility, and the psychosocial type of employee. Models of man's labor behavior are constituted In the process of historical development. Attention is focused on the formation of a national HR-model, such as the conducted socio-economic policy, the characteristics of the institutional environment, economic goals and priorities of the country's development, the level of development and the nature of the national productive forces and economic structures. Much attention was paid to the analysis of the historically formed value system and labor traditions, which influence the approaches to HR-management. As far as religion influences the model of person’s inclusion in labor, motives of labor behavior, management culture of a certain employee, preferred payment etc., we examined how the main traditional religions (Christianity, Islam, Judaism, Buddhism, Confucianism, Hinduism influence the HR-management system in different countries.

  14. Factoral analysis of the cost of preparing oil

    Energy Technology Data Exchange (ETDEWEB)

    Avdeyeva, L A; Kudoyarov, G Sh; Shmatova, M F

    1979-01-01

    Mathematical statistics methods (basically correlational and regression analysis) are used to study the factors which form the level of cost of preparing oil with consideration of the mutual influence of the factors. Selected as the claims for inclusion into a mathematical model was a group of five a priori justified factors: the water level of the oil being extracted (%); the specific expenditure of deemulsifiers; the volume of oil preparation; the quality of oil preparation (the salt content) and the level of use of the installations' capacities (%). To construct an economic and mathematical model of the cost of the technical preparation (SPP) of the oil, all the unions which make up the Ministry of the Oil Industry were divided into two comparable totalities. The first group included unions in which the oil SPP was lower than the branch average and the second, unions in which the SPP was higher than the branch wide cost. Using the coefficients of regression, special elasticity coefficients and the fluctuation indicators, the basic factors were finally identified which have the greatest influence on the formation of the oil SPP level separately for the first and second groups of unions.

  15. Phenotypic factor analysis of psychopathology reveals a new body-related transdiagnostic factor.

    Science.gov (United States)

    Pezzoli, Patrizia; Antfolk, Jan; Santtila, Pekka

    2017-01-01

    Comorbidity challenges the notion of mental disorders as discrete categories. An increasing body of literature shows that symptoms cut across traditional diagnostic boundaries and interact in shaping the latent structure of psychopathology. Using exploratory and confirmatory factor analysis, we reveal the latent sources of covariation among nine measures of psychopathological functioning in a population-based sample of 13024 Finnish twins and their siblings. By implementing unidimensional, multidimensional, second-order, and bifactor models, we illustrate the relationships between observed variables, specific, and general latent factors. We also provide the first investigation to date of measurement invariance of the bifactor model of psychopathology across gender and age groups. Our main result is the identification of a distinct "Body" factor, alongside the previously identified Internalizing and Externalizing factors. We also report relevant cross-disorder associations, especially between body-related psychopathology and trait anger, as well as substantial sex and age differences in observed and latent means. The findings expand the meta-structure of psychopathology, with implications for empirical and clinical practice, and demonstrate shared mechanisms underlying attitudes towards nutrition, self-image, sexuality and anger, with gender- and age-specific features.

  16. PENGUJIAN FAMA-FRENCH THREE-FACTOR MODEL DI INDONESIA

    Directory of Open Access Journals (Sweden)

    Damar Hardianto

    2017-03-01

    Full Text Available This study empirically examined the Fama-French three factor model of stock returnsfor Indonesia over the period 2000-2004. We found evidence for pervasive market, size, andbook-to-market factors in Indonesian stock returns. We found that cross-sectional mean returnswere explained by exposures to these three factors, and not by the market factor alone. Theempirical results were reasonably consistent with the Fama-French three factor model.

  17. Risk factor analysis of equine strongyle resistance to anthelmintics

    Directory of Open Access Journals (Sweden)

    G. Sallé

    2017-12-01

    Full Text Available Intestinal strongyles are the most problematic endoparasites of equids as a result of their wide distribution and the spread of resistant isolates throughout the world. While abundant literature can be found on the extent of anthelmintic resistance across continents, empirical knowledge about associated risk factors is missing. This study brought together results from anthelmintic efficacy testing and risk factor analysis to provide evidence-based guidelines in the field. It involved 688 horses from 39 French horse farms and riding schools to both estimate Faecal Egg Count Reduction (FECR after anthelmintic treatment and to interview farm and riding school managers about their practices. Risk factors associated with reduced anthelmintic efficacy in equine strongyles were estimated across drugs using a marginal modelling approach. Results demonstrated ivermectin efficacy (96.3% ± 14.5% FECR, the inefficacy of fenbendazole (42.8% ± 33.4% FECR and an intermediate profile for pyrantel (90.3% ± 19.6% FECR. Risk factor analysis provided support to advocate for FEC-based treatment regimens combined with individual anthelmintic dosage and the enforcement of tighter biosecurity around horse introduction. The combination of these measures resulted in a decreased risk of drug resistance (relative risk of 0.57, p = 0.02. Premises falling under this typology also relied more on their veterinarians suggesting practitionners play an important role in the sustainability of anthelmintic usage. Similarly, drug resistance risk was halved in premises with frequent pasture rotation and with stocking rate below five horses/ha (relative risk of 0.53, p < 0.01. This is the first empirical risk factor analysis for anthelmintic resistance in equids. Our findings should guide the implementation of more sustained strongyle management in the field. Keywords: Horse, Nematode, Anthelmintic resistance, Strongyle, Cyathostomin

  18. Intercity Travel Demand Analysis Model

    Directory of Open Access Journals (Sweden)

    Ming Lu

    2014-01-01

    Full Text Available It is well known that intercity travel is an important component of travel demand which belongs to short distance corridor travel. The conventional four-step method is no longer suitable for short distance corridor travel demand analysis for the time spent on urban traffic has a great impact on traveler's main mode choice. To solve this problem, the author studied the existing intercity travel demand analysis model, then improved it based on the study, and finally established a combined model of main mode choice and access mode choice. At last, an integrated multilevel nested logit model structure system was built. The model system includes trip generation, destination choice, and mode-route choice based on multinomial logit model, and it achieved linkage and feedback of each part through logsum variable. This model was applied in Shenzhen intercity railway passenger demand forecast in 2010 as a case study. As a result, the forecast results were consistent with the actuality. The model's correctness and feasibility were verified.

  19. Dispersion-theoretical analysis of the nucleon electromagnetic form factors

    Energy Technology Data Exchange (ETDEWEB)

    Belushkin, M.

    2007-09-29

    The structure of the proton and the neutron is of fundamental importance for the study of the strong interaction dynamics over a wide range of momentum transfers. The nucleon form factors encode information on the internal structure of the nucleon as probed by the electromagnetic interaction, and, to a certain extent, reflect the charge and magnetisation distributions within the proton and the neutron. In this thesis we report on our investigation of the electromagnetic form factors of the proton and the neutron with dispersion relation techniques, including known experimental input on the {pi}{pi}, K anti K and the {rho}{pi} continua and perturbative QCD constraints. We include new experimental data on the pion form factor and the nucleon form factors in our simultaneous analysis of all four form factors in both the space- and the timelike regions for all momentum transfers, and perform Monte- Carlo sampling in order to obtain theoretical uncertainty bands. Finally, we discuss the implications of our results on the pion cloud of the nucleon, the nucleon radii and the Okubo-Zweig-Iizuka rule, and present our results of a model-independent approach to estimating two-photon effects in elastic electron-proton scattering. (orig.)

  20. Dispersion-theoretical analysis of the nucleon electromagnetic form factors

    International Nuclear Information System (INIS)

    Belushkin, M.

    2007-01-01

    The structure of the proton and the neutron is of fundamental importance for the study of the strong interaction dynamics over a wide range of momentum transfers. The nucleon form factors encode information on the internal structure of the nucleon as probed by the electromagnetic interaction, and, to a certain extent, reflect the charge and magnetisation distributions within the proton and the neutron. In this thesis we report on our investigation of the electromagnetic form factors of the proton and the neutron with dispersion relation techniques, including known experimental input on the ππ, K anti K and the ρπ continua and perturbative QCD constraints. We include new experimental data on the pion form factor and the nucleon form factors in our simultaneous analysis of all four form factors in both the space- and the timelike regions for all momentum transfers, and perform Monte- Carlo sampling in order to obtain theoretical uncertainty bands. Finally, we discuss the implications of our results on the pion cloud of the nucleon, the nucleon radii and the Okubo-Zweig-Iizuka rule, and present our results of a model-independent approach to estimating two-photon effects in elastic electron-proton scattering. (orig.)

  1. Bayesian analysis of CCDM models

    Science.gov (United States)

    Jesus, J. F.; Valentim, R.; Andrade-Oliveira, F.

    2017-09-01

    Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, produces a negative pressure term which can be used to explain the accelerated expansion of the Universe. In this work we tested six different spatially flat models for matter creation using statistical criteria, in light of SNe Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Bayesian Evidence (BE). These criteria allow to compare models considering goodness of fit and number of free parameters, penalizing excess of complexity. We find that JO model is slightly favoured over LJO/ΛCDM model, however, neither of these, nor Γ = 3αH0 model can be discarded from the current analysis. Three other scenarios are discarded either because poor fitting or because of the excess of free parameters. A method of increasing Bayesian evidence through reparameterization in order to reducing parameter degeneracy is also developed.

  2. Bayesian analysis of CCDM models

    Energy Technology Data Exchange (ETDEWEB)

    Jesus, J.F. [Universidade Estadual Paulista (Unesp), Câmpus Experimental de Itapeva, Rua Geraldo Alckmin 519, Vila N. Sra. de Fátima, Itapeva, SP, 18409-010 Brazil (Brazil); Valentim, R. [Departamento de Física, Instituto de Ciências Ambientais, Químicas e Farmacêuticas—ICAQF, Universidade Federal de São Paulo (UNIFESP), Unidade José Alencar, Rua São Nicolau No. 210, Diadema, SP, 09913-030 Brazil (Brazil); Andrade-Oliveira, F., E-mail: jfjesus@itapeva.unesp.br, E-mail: valentim.rodolfo@unifesp.br, E-mail: felipe.oliveira@port.ac.uk [Institute of Cosmology and Gravitation—University of Portsmouth, Burnaby Road, Portsmouth, PO1 3FX United Kingdom (United Kingdom)

    2017-09-01

    Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, produces a negative pressure term which can be used to explain the accelerated expansion of the Universe. In this work we tested six different spatially flat models for matter creation using statistical criteria, in light of SNe Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Bayesian Evidence (BE). These criteria allow to compare models considering goodness of fit and number of free parameters, penalizing excess of complexity. We find that JO model is slightly favoured over LJO/ΛCDM model, however, neither of these, nor Γ = 3α H {sub 0} model can be discarded from the current analysis. Three other scenarios are discarded either because poor fitting or because of the excess of free parameters. A method of increasing Bayesian evidence through reparameterization in order to reducing parameter degeneracy is also developed.

  3. Classification analysis of organization factors related to system safety

    International Nuclear Information System (INIS)

    Liu Huizhen; Zhang Li; Zhang Yuling; Guan Shihua

    2009-01-01

    This paper analyzes the different types of organization factors which influence the system safety. The organization factor can be divided into the interior organization factor and exterior organization factor. The latter includes the factors of political, economical, technical, law, social culture and geographical, and the relationships among different interest groups. The former includes organization culture, communication, decision, training, process, supervision and management and organization structure. This paper focuses on the description of the organization factors. The classification analysis of the organization factors is the early work of quantitative analysis. (authors)

  4. INNOVATIVE PRACTICES IN TOURISM. APOSSIBLE MODEL BY FOSTERING SHADOW FACTORS

    Directory of Open Access Journals (Sweden)

    Ada Mirela TOMESCU

    2015-08-01

    Full Text Available The paper is the result of an empirical research, a study that includes a theoretical framework. The data used to test our hypotheses come from 60 small tourism firms from Bihor County, Romania. The research conducted has revealed that actions focusing on innovation must be based on a solid analysis, supported by the knowledge and the understanding of the contextual factors (environment, culture as a mental programming, values also based on the organizational factors (the management commitment, systemic perspective, learning and practice of experimentation, rapid transfer of knowledge within the organization. For the purpose of this work, the contextual factors that are exogenous represent the shadow factors. The studies performed in three European projects implemented in tourism SMEs of Bihor County have allowed us to advance the idea that contextual and organizational factors, that are identified as the source of innovation are based on rationality, which is enlarged by affectivity and imagination. The identified correlations may be considered, in our opinion an element of novelty and originality. Finally, the purpose of this paper is to provide a possible model, based on the idea of building an innovative firm, the one that has learned how to determine their own employees to be innovative. O03, L2, L26

  5. Dynamic Factor Analysis of Nonstationary Multivariate Time Series.

    Science.gov (United States)

    Molenaar, Peter C. M.; And Others

    1992-01-01

    The dynamic factor model proposed by P. C. Molenaar (1985) is exhibited, and a dynamic nonstationary factor model (DNFM) is constructed with latent factor series that have time-varying mean functions. The use of a DNFM is illustrated using data from a television viewing habits study. (SLD)

  6. A Confirmatory Factor Analysis of the Academic Motivation Scale with Black College Students

    Science.gov (United States)

    Cokley, Kevin

    2015-01-01

    The factor structure of the Academic Motivation Scale (AMS) was examined with a sample of 578 Black college students. A confirmatory factor analysis of the AMS was conducted. Results indicated that the hypothesized seven-factor model did not fit the data. Implications for future research with the AMS are discussed.

  7. Using BMDP and SPSS for a Q factor analysis.

    Science.gov (United States)

    Tanner, B A; Koning, S M

    1980-12-01

    While Euclidean distances and Q factor analysis may sometimes be preferred to correlation coefficients and cluster analysis for developing a typology, commercially available software does not always facilitate their use. Commands are provided for using BMDP and SPSS in a Q factor analysis with Euclidean distances.

  8. Using a knowledge elicitation method to specify the business model of a human factors organization

    NARCIS (Netherlands)

    Schraagen, J.M.C.; Ven, J. van de; Hoffman, R.R.; Moon, B.M.

    2009-01-01

    Concept Mapping was used to structure knowledge elicitation interviews with a group of human factors specialists whose goal was to describe the business model of their Department. This novel use of cognitive task analysis to describe the business model of a human factors organization resulted in a

  9. Using a knowledge elicitation method to specify the business model of a human factors organization.

    NARCIS (Netherlands)

    Schraagen, Johannes Martinus Cornelis; van de Ven, Josine; Hoffman, Robert R.; Moon, Brian M.

    2009-01-01

    Concept Mapping was used to structure knowledge elicitation interviews with a group of human factors specialists whose goal was to describe the business model of their Department. This novel use of cognitive task analysis to describe the business model of a human factors organization resulted in a

  10. Factor analysis of serogroups botanica and aurisina of Leptospira biflexa.

    Science.gov (United States)

    Cinco, M

    1977-11-01

    Factor analysis is performed on serovars of Botanica and Aurisina serogroup of Leptospira biflexa. The results show the arrangement of main factors serovar and serogroup specific, as well as the antigens common with serovars of heterologous serogroups.

  11. Human factors analysis of incident/accident report

    International Nuclear Information System (INIS)

    Kuroda, Isao

    1992-01-01

    Human factors analysis of accident/incident has different kinds of difficulties in not only technical, but also psychosocial background. This report introduces some experiments of 'Variation diagram method' which is able to extend to operational and managemental factors. (author)

  12. Nonparametric factor analysis of time series

    OpenAIRE

    Rodríguez-Poo, Juan M.; Linton, Oliver Bruce

    1998-01-01

    We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.

  13. Analysis of success factors in advertising

    OpenAIRE

    Fedorchak, Oleksiy; Kedebecz, Kristina

    2017-01-01

    The essence of factors of the success of advertising campaigns is investigated. The stages of conducting and stages of evaluation of the effectiveness of advertising campaigns are determined. Also defined goals and objectives of advertising campaigns.

  14. [Cultural regionalization for Coptis chinensis based on 3S technology platform Ⅰ. Study on growth suitability for Coptis chinensis based on ecological factors analysis by Maxent and ArcGIS model].

    Science.gov (United States)

    Liu, Xin; Yang, Yan-Fang; Song, Hong-Ping; Zhang, Xiao-Bo; Huang, Lu-Qi; Wu, He-Zhen

    2016-09-01

    At the urgent request of Coptis chinensis planting,growth suitability as assessment indicators for C. chinensis cultivation was proposed and analyzed in this paper , based on chemical quality determination and ecological fators analysis by Maxent and ArcGIS model. Its potential distribution areas at differernt suitability grade and regionalization map were formulated based on statistical theory and growth suitability theory. The results showed that the most suitable habitats is some parts of Chongqing and Hubei province, such as Shizhu, Lichuan, Wulong, Wuxi, Enshi. There are seven ecological factor is the main ecological factors affect the growth of Coptidis Rhizoma, including altitude, precipitation in February and September and the rise of precipitation and altitude is conducive to the accumulation of total alkaloid content in C. chinensis. Therefore, The results of the study not only illustrates the most suitable for the surroundings of Coptidis Rhizoma, also helpful to further research and practice of cultivation regionalization, wild resource monitoring and large-scale cultivation of traditional Chinese medicine plants. Copyright© by the Chinese Pharmaceutical Association.

  15. Holographic analysis of diffraction structure factors

    International Nuclear Information System (INIS)

    Marchesini, S.; Bucher, J.J.; Shuh, D.K.; Fabris, L.; Press, M.J.; West, M.W.; Hussain, Z.; Mannella, N.; Fadley, C.S.; Van Hove, M.A.; Stolte, W.C.

    2002-01-01

    We combine the theory of inside-source/inside-detector x-ray fluorescence holography and Kossel lines/ x ray standing waves in kinematic approximation to directly obtain the phases of the diffraction structure factors. The influence of Kossel lines and standing waves on holography is also discussed. We obtain partial phase determination from experimental data obtaining the sign of the real part of the structure factor for several reciprocal lattice vectors of a vanadium crystal

  16. Identification of noise in linear data sets by factor analysis

    International Nuclear Information System (INIS)

    Roscoe, B.A.; Hopke, Ph.K.

    1982-01-01

    A technique which has the ability to identify bad data points, after the data has been generated, is classical factor analysis. The ability of classical factor analysis to identify two different types of data errors make it ideally suited for scanning large data sets. Since the results yielded by factor analysis indicate correlations between parameters, one must know something about the nature of the data set and the analytical techniques used to obtain it to confidentially isolate errors. (author)

  17. Exploring Technostress: Results of a Large Sample Factor Analysis

    OpenAIRE

    Jonušauskas, Steponas; Raišienė, Agota Giedrė

    2016-01-01

    With reference to the results of a large sample factor analysis, the article aims to propose the frame examining technostress in a population. The survey and principal component analysis of the sample consisting of 1013 individuals who use ICT in their everyday work was implemented in the research. 13 factors combine 68 questions and explain 59.13 per cent of the answers dispersion. Based on the factor analysis, questionnaire was reframed and prepared to reasonably analyze the respondents’ an...

  18. Statictical Analysis Of The Conditioning Factors Of Urban Electric Consumption

    International Nuclear Information System (INIS)

    Segura D'Rouville, Juan Joel; Suárez Carreño, Franyelit María

    2017-01-01

    This research work presents the analysis of the most important factors that condition the urban residential electricity consumption. This study shows the quantitative parameters conditioning the electricity consumption. This sector of analysis has been chosen because there is disaggregated information of which are the main social and technological factors that determine its behavior, growth, with the objective of elaborating policies in the management of the electric consumption. The electrical demand considered as the sum of the powers of all the equipment that are used in each of the instants of a full day, is related to the electrical consumption, which is not but the value of the power demanded by a determined consumer Multiplied by the time in which said demand is maintained. In this report we propose the design of a probabilistic model of prediction of electricity consumption, taking into account mainly influential social and technological factors. The statistical process of this database is done through the Stat Graphics software version 4.1, for its extensive didactic in the accomplishment of calculations and associated methods. Finally, the correlation of the variables was performed to classify the determinants in a specific way and thus to determine the consumption of the dwellings. (author)

  19. Factors accounting for youth suicide attempt in Hong Kong: a model building.

    Science.gov (United States)

    Wan, Gloria W Y; Leung, Patrick W L

    2010-10-01

    This study aimed at proposing and testing a conceptual model of youth suicide attempt. We proposed a model that began with family factors such as a history of physical abuse and parental divorce/separation. Family relationship, presence of psychopathology, life stressors, and suicide ideation were postulated as mediators, leading to youth suicide attempt. The stepwise entry of the risk factors to a logistic regression model defined their proximity as related to suicide attempt. Path analysis further refined our proposed model of youth suicide attempt. Our originally proposed model was largely confirmed. The main revision was dropping parental divorce/separation as a risk factor in the model due to lack of significant contribution when examined alongside with other risk factors. This model was cross-validated by gender. This study moved research on youth suicide from identification of individual risk factors to model building, integrating separate findings of the past studies.

  20. Worldwide analysis of marine oil spill cleanup cost factors

    International Nuclear Information System (INIS)

    Etkin, D.S.

    2000-01-01

    The many factors that influence oil spill response costs were discussed with particular emphasis on how spill responses differ around the world because of differing cultural values, socio-economic factors and labor costs. This paper presented an analysis of marine oil spill cleanup costs based on the country, proximity to shoreline, spill size, oil type, degree of shoreline oiling and cleanup methodology. The objective was to determine how each factor impacts per-unit cleanup costs. Near-shore spills and in-port spills were found to be 4-5 times more expensive to clean than offshore spills. Responses to spills of heavy fuels also cost 10 times more than for lighter crudes and diesel. Spill responses for spills under 30 tonnes are 10 times more costly than on a per-unit basis, for spills of 300 tonnes. A newly developed modelling technique that can be used on different types of marine spills was described. It is based on updated cost data acquired from case studies of more than 300 spills in 40 countries. The model determines a per-unit cleanup cost estimation by taking into consideration oil type, location, spill size, cleanup methodology, and shoreline oiling. It was concluded that the actual spill costs are totally dependent on the actual circumstances of the spill. 13 refs., 10 tabs., 3 figs

  1. Ranking factors of an investment in cogeneration: sensitivity analysis ranking the technical and economical factors

    International Nuclear Information System (INIS)

    Sundberg, Gunnel

    2001-01-01

    A deregulation of the electricity market in Europe will result in increased competition among the power-producing companies. They will therefore carefully estimate the financial risk in an investment in new power-producing capability. One part of the risk assessment is to perform a sensitivity analysis. This paper presents a sensitivity analysis using factorial design, resulting in an assessment of the most important technical and economical factors affecting an investment in gas turbine combined cycle and a steam cycle fired by wood chips. The study is performed using a simulation model that optimises the operation of existing power plants and potential new investments to fulfil the desired heat demand. The local utility system analysed is a Swedish district heating system with 655 GWh y -1 heat demand. The conclusion is that to understand which of the technical and economical factors affect the investment, it is not sufficient to investigate the parameters of the studied plant, but also the parameters related to the competing plants. Both the individual effects of the factors and the effect of their interaction should be investigated. For the energy system studied the price of natural gas, price of wood chips and investment cost have the major influence on the profitability of the investment. (Author)

  2. A Parametric Factor Model of the Term Structure of Mortality

    DEFF Research Database (Denmark)

    Haldrup, Niels; Rosenskjold, Carsten Paysen T.

    The prototypical Lee-Carter mortality model is characterized by a single common time factor that loads differently across age groups. In this paper we propose a factor model for the term structure of mortality where multiple factors are designed to influence the age groups differently via...... on the loading functions, the factors are not designed to be orthogonal but can be dependent and can possibly cointegrate when the factors have unit roots. We suggest two estimation procedures similar to the estimation of the dynamic Nelson-Siegel term structure model. First, a two-step nonlinear least squares...... procedure based on cross-section regressions together with a separate model to estimate the dynamics of the factors. Second, we suggest a fully specified model estimated by maximum likelihood via the Kalman filter recursions after the model is put on state space form. We demonstrate the methodology for US...

  3. Analysis of Human Error Types and Performance Shaping Factors in the Next Generation Main Control Room

    International Nuclear Information System (INIS)

    Sin, Y. C.; Jung, Y. S.; Kim, K. H.; Kim, J. H.

    2008-04-01

    Main control room of nuclear power plants has been computerized and digitalized in new and modernized plants, as information and digital technologies make great progresses and become mature. Survey on human factors engineering issues in advanced MCRs: Model-based approach, Literature survey-based approach. Analysis of human error types and performance shaping factors is analysis of three human errors. The results of project can be used for task analysis, evaluation of human error probabilities, and analysis of performance shaping factors in the HRA analysis

  4. Conformational analysis of lignin models

    International Nuclear Information System (INIS)

    Santos, Helio F. dos

    2001-01-01

    The conformational equilibrium for two 5,5' biphenyl lignin models have been analyzed using a quantum mechanical semiempirical method. The gas phase and solution structures are discussed based on the NMR and X-ray experimental data. The results obtained showed that the observed conformations are solvent-dependent, being the geometries and the thermodynamic properties correlated with the experimental information. This study shows how a systematic theoretical conformational analysis can help to understand chemical processes at a molecular level. (author)

  5. Cloud Computing Adoption Business Model Factors: Does Enterprise Size Matter?

    OpenAIRE

    Bogataj Habjan, Kristina; Pucihar, Andreja

    2017-01-01

    This paper presents the results of research investigating the impact of business model factors on cloud computing adoption. The introduced research model consists of 40 cloud computing business model factors, grouped into eight factor groups. Their impact and importance for cloud computing adoption were investigated among enterpirses in Slovenia. Furthermore, differences in opinion according to enterprise size were investigated. Research results show no statistically significant impacts of in...

  6. The Butterfly Effect: Correlations Between Modeling in Nuclear-Particle Physics and Socioeconomic Factors

    CERN Document Server

    Pia, Maria Grazia; Bell, Zane W.; Dressendorfer, Paul V.

    2010-01-01

    A scientometric analysis has been performed on selected physics journals to estimate the presence of simulation and modeling in physics literature in the past fifty years. Correlations between the observed trends and several social and economical factors have been evaluated.

  7. Assessment of slip factor models at off-design condition

    International Nuclear Information System (INIS)

    Yoon, Sung Ho; Baek, Je Hyun

    2000-01-01

    Slip factor is defined as an empirical factor being multiplied to theoretical energy transfer for the estimation of real work input of a centrifugal compressor. Researchers have tried to develop a simple empirical model, for a century, to predict a slip factor. However most these models were developed on the condition of design point assuming inviscid flow. So these models often fail to predict a correct slip factor at off-design condition. In this study, we summarized various slip factor models and compared these models with experimental and numerical data at off-design condition. As a result of this study, Wiesner's and Paeng and Chung's models are applicable for radial impeller, but all the models are not suitable for backswept impeller. Finally, the essential avenues for future study is discussed

  8. Modelling impulsive factors for electronics and restaurant coupons’ e-store display

    Science.gov (United States)

    Ariningsih, P. K.; Nainggolan, M.; Sandy, I. A.

    2018-04-01

    In many times, the increment of e-store visitors does not followed by sales increment. Most purchases through e-commerce are impulsive buying, however only small amount of study is available to understand impulsive factors of e-store display. This paper suggests a preliminary concept on understanding the impulsive factors in Electronics and Restaurant Coupons e-store display, which are two among few popular group products sold through e-commerce. By conducting literature study and survey, 31 attributes were identified as impulsive factors in electronics e-store display and 20 attributes were identified as impulsive factors for restaurant coupon e-store. The attributes were then grouped into comprehensive impulsive factors by factor analysis. Each group of impulsive attributes were generated into 3 factors. Accessibility Factors and Trust Factors appeared for each group products. The other factors are Internal Factors for electronics e-store and Marketing factors for restaurant coupons e-store. Structural Equation Model of the impulsive factors was developed for each type of e-store, which stated the covariance between Trust Factors and Accessibility Factors. Based on preliminary model, Internal Factor and Trust Factor are influencing impulsive buying in electronics store. Special factor for electronics e-store is Internal Factor, while for restaurant coupons e-store is Marketing Factor.

  9. Distribution system modeling and analysis

    CERN Document Server

    Kersting, William H

    2001-01-01

    For decades, distribution engineers did not have the sophisticated tools developed for analyzing transmission systems-often they had only their instincts. Things have changed, and we now have computer programs that allow engineers to simulate, analyze, and optimize distribution systems. Powerful as these programs are, however, without a real understanding of the operating characteristics of a distribution system, engineers using the programs can easily make serious errors in their designs and operating procedures. Distribution System Modeling and Analysis helps prevent those errors. It gives readers a basic understanding of the modeling and operating characteristics of the major components of a distribution system. One by one, the author develops and analyzes each component as a stand-alone element, then puts them all together to analyze a distribution system comprising the various shunt and series devices for power-flow and short-circuit studies. He includes the derivation of all models and includes many num...

  10. Human Reliability Analysis for Design: Using Reliability Methods for Human Factors Issues

    Energy Technology Data Exchange (ETDEWEB)

    Ronald Laurids Boring

    2010-11-01

    This paper reviews the application of human reliability analysis methods to human factors design issues. An application framework is sketched in which aspects of modeling typically found in human reliability analysis are used in a complementary fashion to the existing human factors phases of design and testing. The paper provides best achievable practices for design, testing, and modeling. Such best achievable practices may be used to evaluate and human system interface in the context of design safety certifications.

  11. Human Reliability Analysis for Design: Using Reliability Methods for Human Factors Issues

    International Nuclear Information System (INIS)

    Boring, Ronald Laurids

    2010-01-01

    This paper reviews the application of human reliability analysis methods to human factors design issues. An application framework is sketched in which aspects of modeling typically found in human reliability analysis are used in a complementary fashion to the existing human factors phases of design and testing. The paper provides best achievable practices for design, testing, and modeling. Such best achievable practices may be used to evaluate and human system interface in the context of design safety certifications.

  12. Regression analysis of nuclear plant capacity factors

    International Nuclear Information System (INIS)

    Stocks, K.J.; Faulkner, J.I.

    1980-07-01

    Operating data on all commercial nuclear power plants of the PWR, HWR, BWR and GCR types in the Western World are analysed statistically to determine whether the explanatory variables size, year of operation, vintage and reactor supplier are significant in accounting for the variation in capacity factor. The results are compared with a number of previous studies which analysed only United States reactors. The possibility of specification errors affecting the results is also examined. Although, in general, the variables considered are statistically significant, they explain only a small portion of the variation in the capacity factor. The equations thus obtained should certainly not be used to predict the lifetime performance of future large reactors

  13. A structural dynamic factor model for the effects of monetary policy estimated by the EM algorithm

    DEFF Research Database (Denmark)

    Bork, Lasse

    This paper applies the maximum likelihood based EM algorithm to a large-dimensional factor analysis of US monetary policy. Specifically, economy-wide effects of shocks to the US federal funds rate are estimated in a structural dynamic factor model in which 100+ US macroeconomic and financial time...... series are driven by the joint dynamics of the federal funds rate and a few correlated dynamic factors. This paper contains a number of methodological contributions to the existing literature on data-rich monetary policy analysis. Firstly, the identification scheme allows for correlated factor dynamics...... as opposed to the orthogonal factors resulting from the popular principal component approach to structural factor models. Correlated factors are economically more sensible and important for a richer monetary policy transmission mechanism. Secondly, I consider both static factor loadings as well as dynamic...

  14. Parametric Analysis of Flexible Logic Control Model

    Directory of Open Access Journals (Sweden)

    Lihua Fu

    2013-01-01

    Full Text Available Based on deep analysis about the essential relation between two input variables of normal two-dimensional fuzzy controller, we used universal combinatorial operation model to describe the logic relationship and gave a flexible logic control method to realize the effective control for complex system. In practical control application, how to determine the general correlation coefficient of flexible logic control model is a problem for further studies. First, the conventional universal combinatorial operation model has been limited in the interval [0,1]. Consequently, this paper studies a kind of universal combinatorial operation model based on the interval [a,b]. And some important theorems are given and proved, which provide a foundation for the flexible logic control method. For dealing reasonably with the complex relations of every factor in complex system, a kind of universal combinatorial operation model with unequal weights is put forward. Then, this paper has carried out the parametric analysis of flexible logic control model. And some research results have been given, which have important directive to determine the values of the general correlation coefficients in practical control application.

  15. An Empirical Analysis of Job Satisfaction Factors.

    Science.gov (United States)

    1987-09-01

    have acknowledged the importance of factors which make the Air Force attractive to its members or conversely, make other employees consider...Maslow’s need hierarchy theory attempts to show that man has five basic categories of needs: physiological, safety, belongingness , esteem, and self...attained until lower-level basic needs are attained. This implies a sort of growth process where optional job environments for given employees are

  16. Modelling of Supercapacitors: Factors Influencing Performance

    OpenAIRE

    Kroupa, M; Offer, GJ; Kosek, J

    2016-01-01

    The utilizable capacitance of Electrochemical Double Layer Capacitors (EDLCs) is a function of the frequency at which they are operated and this is strongly dependent on the construction and physical parameters of the device. We simulate the dynamic behavior of an EDLC using a spatially resolved model based on the porous electrode theory. The model of Verbrugge and Liu (J. Electrochem. Soc. 152, D79 (2005)) was extended with a dimension describing the transport into the carbon particle pores....

  17. Modeling of human factor Va inactivation by activated protein C

    Directory of Open Access Journals (Sweden)

    Bravo Maria

    2012-05-01

    analysis of in vitro experiments and mathematical constructs we are able to produce a final validated model that includes 24 chemical reactions and interactions with 14 unique rate constants which describe the flux in concentrations of 24 species. Conclusion This study highlights the complexity of the inactivation process and provides a module of equations describing the Protein C pathway that can be integrated into existing comprehensive mathematical models describing tissue factor initiated coagulation.

  18. APPLICATION OF THE INFORMATION THEORY AND COGNITIVE TECHNOLOGIES FOR MODELING ECOLOGICAL AND SOCIOECONOMIC SYSTEMS (ASC-analysis of the impact of environmental and commercial factors on the health of the population)

    OpenAIRE

    Lutsenko Y. V.; Strelnikov V. V.

    2016-01-01

    A determination system of the population health is a big complex hierarchical system. The current level of management of such systems involves the use of mathematical models and corresponding software tools for the accumulation of baseline data (monitoring), identification, prediction and decision-making. However, when modeling such large complex systems, we face a number of problems. The main problem is that in one model it is necessary to process a very large number of factors in a proper a...

  19. A Factor Analysis of the BSRI and the PAQ.

    Science.gov (United States)

    Edwards, Teresa A.; And Others

    Factor analysis of the Bem Sex Role Inventory (BSRI) and the Personality Attributes Questionnaire (PAQ) was undertaken to study the independence of the masculine and feminine scales within each instrument. Both instruments were administered to undergraduate education majors. Analysis of primary first and second order factors of the BSRI indicated…

  20. Modeling human reliability analysis using MIDAS

    International Nuclear Information System (INIS)

    Boring, R. L.

    2006-01-01

    This paper documents current efforts to infuse human reliability analysis (HRA) into human performance simulation. The Idaho National Laboratory is teamed with NASA Ames Research Center to bridge the SPAR-H HRA method with NASA's Man-machine Integration Design and Analysis System (MIDAS) for use in simulating and modeling the human contribution to risk in nuclear power plant control room operations. It is anticipated that the union of MIDAS and SPAR-H will pave the path for cost-effective, timely, and valid simulated control room operators for studying current and next generation control room configurations. This paper highlights considerations for creating the dynamic HRA framework necessary for simulation, including event dependency and granularity. This paper also highlights how the SPAR-H performance shaping factors can be modeled in MIDAS across static, dynamic, and initiator conditions common to control room scenarios. This paper concludes with a discussion of the relationship of the workload factors currently in MIDAS and the performance shaping factors in SPAR-H. (authors)

  1. Sensitivity analysis of a modified energy model

    International Nuclear Information System (INIS)

    Suganthi, L.; Jagadeesan, T.R.

    1997-01-01

    Sensitivity analysis is carried out to validate model formulation. A modified model has been developed to predict the future energy requirement of coal, oil and electricity, considering price, income, technological and environmental factors. The impact and sensitivity of the independent variables on the dependent variable are analysed. The error distribution pattern in the modified model as compared to a conventional time series model indicated the absence of clusters. The residual plot of the modified model showed no distinct pattern of variation. The percentage variation of error in the conventional time series model for coal and oil ranges from -20% to +20%, while for electricity it ranges from -80% to +20%. However, in the case of the modified model the percentage variation in error is greatly reduced - for coal it ranges from -0.25% to +0.15%, for oil -0.6% to +0.6% and for electricity it ranges from -10% to +10%. The upper and lower limit consumption levels at 95% confidence is determined. The consumption at varying percentage changes in price and population are analysed. The gap between the modified model predictions at varying percentage changes in price and population over the years from 1990 to 2001 is found to be increasing. This is because of the increasing rate of energy consumption over the years and also the confidence level decreases as the projection is made far into the future. (author)

  2. Analysis and optimization of the TWINKLE factoring device

    NARCIS (Netherlands)

    Lenstra, A.K.; Shamir, A.; Preneel, B.

    2000-01-01

    We describe an enhanced version of the TWINKLE factoring device and analyse to what extent it can be expected to speed up the sieving step of the Quadratic Sieve and Number Field Sieve factoring al- gorithms. The bottom line of our analysis is that the TWINKLE-assisted factorization of 768-bit

  3. Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

    Science.gov (United States)

    Stankov, L

    1979-07-01

    The procedure for hierarchical factoring suggested by Schmid and Leiman (1957) is applied within the framework of image analysis and orthoblique rotational procedures. It is shown that this approach necessarily leads to correlated higher order factors. Also, one can obtain a smaller number of factors than produced by typical hierarchical procedures.

  4. Ventilation Model and Analysis Report

    International Nuclear Information System (INIS)

    Chipman, V.

    2003-01-01

    This model and analysis report develops, validates, and implements a conceptual model for heat transfer in and around a ventilated emplacement drift. This conceptual model includes thermal radiation between the waste package and the drift wall, convection from the waste package and drift wall surfaces into the flowing air, and conduction in the surrounding host rock. These heat transfer processes are coupled and vary both temporally and spatially, so numerical and analytical methods are used to implement the mathematical equations which describe the conceptual model. These numerical and analytical methods predict the transient response of the system, at the drift scale, in terms of spatially varying temperatures and ventilation efficiencies. The ventilation efficiency describes the effectiveness of the ventilation process in removing radionuclide decay heat from the drift environment. An alternative conceptual model is also developed which evaluates the influence of water and water vapor mass transport on the ventilation efficiency. These effects are described using analytical methods which bound the contribution of latent heat to the system, quantify the effects of varying degrees of host rock saturation (and hence host rock thermal conductivity) on the ventilation efficiency, and evaluate the effects of vapor and enhanced vapor diffusion on the host rock thermal conductivity

  5. Modification and analysis of engineering hot spot factor of HFETR

    International Nuclear Information System (INIS)

    Hu Yuechun; Deng Caiyu; Li Haitao; Xu Taozhong; Mo Zhengyu

    2014-01-01

    This paper presents the modification and analysis of engineering hot spot factors of HFETR. The new factors are applied in the fuel temperature analysis and the estimated value of the safety allowable operating power of HFETR. The result shows the maximum cladding temperature of the fuel is lower when the new factor are in utilization, and the safety allowable operating power of HFETR if higher, thus providing the economical efficiency of HFETR. (authors)

  6. A replication of a factor analysis of motivations for trapping

    Science.gov (United States)

    Schroeder, Susan; Fulton, David C.

    2015-01-01

    Using a 2013 sample of Minnesota trappers, we employed confirmatory factor analysis to replicate an exploratory factor analysis of trapping motivations conducted by Daigle, Muth, Zwick, and Glass (1998).  We employed the same 25 items used by Daigle et al. and tested the same five-factor structure using a recent sample of Minnesota trappers. We also compared motivations in our sample to those reported by Daigle et el.

  7. Factor analysis improves the selection of prescribing indicators

    DEFF Research Database (Denmark)

    Rasmussen, Hanne Marie Skyggedal; Søndergaard, Jens; Sokolowski, Ineta

    2006-01-01

    OBJECTIVE: To test a method for improving the selection of indicators of general practitioners' prescribing. METHODS: We conducted a prescription database study including all 180 general practices in the County of Funen, Denmark, approximately 472,000 inhabitants. Principal factor analysis was us...... appropriate and inappropriate prescribing, as revealed by the correlation of the indicators in the first factor. CONCLUSION: Correlation and factor analysis is a feasible method that assists the selection of indicators and gives better insight into prescribing patterns....

  8. Human factor analysis and preventive countermeasures in nuclear power plant

    International Nuclear Information System (INIS)

    Li Ye

    2010-01-01

    Based on the human error analysis theory and the characteristics of maintenance in a nuclear power plant, human factors of maintenance in NPP are divided into three different areas: human, technology, and organization. Which is defined as individual factors, including psychological factors, physiological characteristics, health status, level of knowledge and interpersonal skills; The technical factors including technology, equipment, tools, working order, etc.; The organizational factors including management, information exchange, education, working environment, team building and leadership management,etc The analysis found that organizational factors can directly or indirectly affect the behavior of staff and technical factors, is the most basic human error factor. Based on this nuclear power plant to reduce human error and measures the response. (authors)

  9. Applying Petri nets in modelling the human factor

    International Nuclear Information System (INIS)

    Bedreaga, Luminita; Constntinescu, Cristina; Guzun, Basarab

    2007-01-01

    Usually, in the reliability analysis performed for complex systems, we determine the success probability to work with other performance indices, i.e. the likelihood associated with a given state. The possible values assigned to system states can be derived using inductive methods. If one wants to calculate the probability to occur a particular event in the system, then deductive methods should be applied. In the particular case of the human reliability analysis, as part of probabilistic safety analysis, the international regulatory commission have developed specific guides and procedures to perform such assessments. The paper presents the modality to obtain the human reliability quantification using the Petri nets approach. This is an efficient means to assess reliability systems because of their specific features. The examples showed in the paper are from human reliability documentation without a detailed human factor analysis (qualitative). We present human action modelling using event trees and Petri nets approach. The obtained results by these two kinds of methods are in good concordance. (authors)

  10. Factor Analysis for Finding Invariant Neural Descriptors of Human Emotions

    Directory of Open Access Journals (Sweden)

    Vitor Pereira

    2018-01-01

    Full Text Available A major challenge in decoding human emotions from electroencephalogram (EEG data is finding representations that are invariant to inter- and intrasubject differences. Most of the previous studies are focused in building an individual discrimination model for every subject (subject dependent model. Building subject-independent models is a harder problem due to the high data variability between different subjects and different experiments with the same subject. This paper explores, for the first time, the Factor Analysis as an efficient technique to extract temporal and spatial EEG features suitable to build brain-computer interface for decoding human emotions across various subjects. Our findings show that early waves (temporal window of 200–400 ms after the stimulus onset carry more information about the valence of the emotion. Also, spatial location of features, with a stronger impact on the emotional valence, occurs in the parietal and occipital regions of the brain. All discrimination models (NN, SVM, kNN, and RF demonstrate better discrimination rate of the positive valence. These results match closely experimental psychology hypothesis that, during early periods after the stimulus presentation, the brain response—to images with highly positive valence—is stronger.

  11. Confirmatory Factor Analysis of the ISB - Burnout Syndrome Inventory

    Directory of Open Access Journals (Sweden)

    Ana Maria T. Benevides-Pereira

    2017-05-01

    Full Text Available AimBurnout is a dysfunctional reaction to chronic occupational stress. The present study analysis the psychometric qualities of the Burnout Syndrome Inventory (ISB through Confirmatory Factor Analysis (CFA.MethodEmpirical study in a multi-centre and multi-occupational sample (n = 701 using the ISB. The Part I assesses antecedent factors: Positive Organizational Conditions (PC and Negative Organizational Conditions (NC. The Part II assesses the syndrome: Emotional Exhaustion (EE, Dehumanization (DE, Emotional Distancing (ED and Personal Accomplishment (PA.ResultsThe highest means occurred in the positive scales CP (M = 23.29, SD = 5.89 and PA (M = 14.84, SD = 4.71. Negative conditions showed the greatest variability (SD = 6.03. Reliability indexes were reasonable, with the lowest rate at .77 for DE and the highest rate .91 for PA. The CFA revealed RMSEA = .057 and CFI = .90 with all scales regressions showing significant values (β = .73 until β = .92.ConclusionThe ISB showed a plausible instrument to evaluate burnout. The two sectors maintained the initial model and confirmed the theoretical presupposition. This instrument makes possible a more comprehensive idea of the labour context, and one or another part may be used separately according to the needs and the aims of the assessor.

  12. Hierarchical and coupling model of factors influencing vessel traffic flow.

    Directory of Open Access Journals (Sweden)

    Zhao Liu

    Full Text Available Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

  13. Hierarchical and coupling model of factors influencing vessel traffic flow.

    Science.gov (United States)

    Liu, Zhao; Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

    2017-01-01

    Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

  14. Confirmatory factor analysis of the Competitive State Anxiety Inventory-2.

    Science.gov (United States)

    Lane, A M; Sewell, D F; Terry, P C; Bartram, D; Nesti, M S

    1999-06-01

    The aim of this study was to evaluate the factor structure of the Competitive State Anxiety Inventory-2 (CSAI-2) using confirmatory factor analysis. Volunteer participants (n = 1213) completed the CSAI-2 approximately 1 h before competition and the data were analysed in two samples. The hypothesized model showed poor fit indices in both samples independently (Robust Comparative Fit Index: sample A = 0.82, sample B = 0.84) and simultaneously (Comparative Fit Index = 0.83), suggesting that the factor structure proposed by Martens et al. is flawed. Our findings suggest that a limitation of the Cognitive Anxiety scale derives from phrasing items around the word 'concerned' rather than 'worried'. We suggest that being concerned about an impending performance does not necessarily mean that an athlete is experiencing negative thoughts, but that the athlete is acknowledging the importance and difficulty of the challenge and is attempting to mobilize resources to cope. The present results question the use of the CSAI-2 as a valid measure of competitive state anxiety.

  15. Chou-Yang model and PHI form factor

    Energy Technology Data Exchange (ETDEWEB)

    Fazal-e-Aleem; Saleem, M.; Rafique, M.

    1988-03-01

    By using the deduced differential cross-section data for PHIp elastic scattering at 175 GeV/c in the Chou-Yang model, the PHI form factor has been computed and parametrized. Then in conjunction with the proton form factor this form factor is used in the pristine Chou-Yang model to obtain differential cross-section data at Fermilab energies. The theoretical results agree with the experimental measurements, endorsing the conjecture that the hadronic form factor of neutral particle is proportional to its magnetic form factor.

  16. [A factor analysis method for contingency table data with unlimited multiple choice questions].

    Science.gov (United States)

    Toyoda, Hideki; Haiden, Reina; Kubo, Saori; Ikehara, Kazuya; Isobe, Yurie

    2016-02-01

    The purpose of this study is to propose a method of factor analysis for analyzing contingency tables developed from the data of unlimited multiple-choice questions. This method assumes that the element of each cell of the contingency table has a binominal distribution and a factor analysis model is applied to the logit of the selection probability. Scree plot and WAIC are used to decide the number of factors, and the standardized residual, the standardized difference between the sample, and the proportion ratio, is used to select items. The proposed method was applied to real product impression research data on advertised chips and energy drinks. Since the results of the analysis showed that this method could be used in conjunction with conventional factor analysis model, and extracted factors were fully interpretable, and suggests the usefulness of the proposed method in the study of psychology using unlimited multiple-choice questions.

  17. Analysis of vector boson production within TMD factorization

    Energy Technology Data Exchange (ETDEWEB)

    Scimemi, Ignazio [Universidad Complutense de Madrid, Departamento de Fisica Teorica, Madrid (Spain); Vladimirov, Alexey [Universitaet Regensburg, Institut fuer Theoretische Physik, Regensburg (Germany)

    2018-02-15

    We present a comprehensive analysis and extraction of the unpolarized transverse momentum dependent (TMD) parton distribution functions, which are fundamental constituents of the TMD factorization theorem. We provide a general review of the theory of TMD distributions, and present a new scheme of scale fixation. This scheme, called the ζ-prescription, allows to minimize the impact of perturbative logarithms in a large range of scales and does not generate undesired power corrections. Within ζ-prescription we consistently include the perturbatively calculable parts up to next-to-next-to-leading order (NNLO), and perform the global fit of the Drell-Yan and Z-boson production, which include the data of E288, Tevatron and LHC experiments. The non-perturbative part of the TMDs are explored checking a variety of models. We support the obtained results by a study of theoretical uncertainties, perturbative convergence, and a dedicated study of the range of applicability of the TMD factorization theorem. The considered non-perturbative models present significant differences in the fitting behavior, which allow us to clearly disfavor most of them. The numerical evaluations are provided by the arTeMiDe code, which is introduced in this work and that can be used for current/future TMD phenomenology. (orig.)

  18. Analysis of vector boson production within TMD factorization

    International Nuclear Information System (INIS)

    Scimemi, Ignazio; Vladimirov, Alexey

    2018-01-01

    We present a comprehensive analysis and extraction of the unpolarized transverse momentum dependent (TMD) parton distribution functions, which are fundamental constituents of the TMD factorization theorem. We provide a general review of the theory of TMD distributions, and present a new scheme of scale fixation. This scheme, called the ζ-prescription, allows to minimize the impact of perturbative logarithms in a large range of scales and does not generate undesired power corrections. Within ζ-prescription we consistently include the perturbatively calculable parts up to next-to-next-to-leading order (NNLO), and perform the global fit of the Drell-Yan and Z-boson production, which include the data of E288, Tevatron and LHC experiments. The non-perturbative part of the TMDs are explored checking a variety of models. We support the obtained results by a study of theoretical uncertainties, perturbative convergence, and a dedicated study of the range of applicability of the TMD factorization theorem. The considered non-perturbative models present significant differences in the fitting behavior, which allow us to clearly disfavor most of them. The numerical evaluations are provided by the arTeMiDe code, which is introduced in this work and that can be used for current/future TMD phenomenology. (orig.)

  19. Simplified model for DNB analysis

    International Nuclear Information System (INIS)

    Silva Filho, E.

    1979-08-01

    In a pressurized water nuclear reactor (PWR), the power of operation is restricted by the possibility of the occurrence of the departure from nucleate boiling called DNB (Departure from Nucleate Boiling) in the hottest channel of the core. The present work proposes a simplified model that analyses the thermal-hydraulic conditions of the coolant in the hottest channel of PWRs with the objective to evaluate BNB in this channel. For this the coupling between the hot channel and typical nominal channels assumed imposing the existence of a cross flow between these channels in a way that a uniforme pressure axial distribution results along the channels. The model is applied for Angra-I reactor and the results are compared with those of Final Safety Analysis Report (FSAR) obtained by Westinghouse through the THINC program, beeing considered satisfactory (Author) [pt

  20. ANALYSIS OF RISK FACTORS ECTOPIC PREGNANCY

    Directory of Open Access Journals (Sweden)

    Budi Santoso

    2017-04-01

    Full Text Available Introduction: Ectopic pregnancy is a pregnancy with extrauterine implantation. This situation is gynecologic emergency that contributes to maternal mortality. Therefore, early recognition, based on identification of the causes of ectopic pregnancy risk factors, is needed. Methods: The design descriptive observational. The samples were pregnant women who had ectopic pregnancy at Maternity Room, Emergency Unit, Dr. Soetomo Hospital, Surabaya, from 1 July 2008 to 1 July 2010. Sampling technique was total sampling using medical records. Result: Patients with ectopic pregnancy were 99 individuals out of 2090 pregnant women who searched for treatment in Dr. Soetomo Hospital. However, only 29 patients were accompanied with traceable risk factors. Discussion:. Most ectopic pregnancies were in the age group of 26-30 years, comprising 32 patients (32.32%, then in age groups of 31–35 years as many as 25 patients (25.25%, 18 patients in age group 21–25 years (18.18%, 17 patients in age group 36–40 years (17.17%, 4 patients in age group 41 years and more (4.04%, and the least was in age group of 16–20 years with 3 patients (3.03%. A total of 12 patients with ectopic pregnancy (41.38% had experience of abortion and 6 patients (20.69% each in groups of patients with ectopic pregnancy who used family planning, in those who used family planning as well as ectopic pregnancy patients with history of surgery. There were 2 patients (6.90% of the group of patients ectopic pregnancy who had history of surgery and history of abortion. The incidence rate of ectopic pregnancy was 4.73%, mostly in the second gravidity (34.34%, whereas the nulliparous have the highest prevalence of 39.39%. Acquired risk factors, i.e. history of operations was 10.34%, patients with family planning 20.69%, patients with history of abortion 41.38%, patients with history of abortion and operation 6.90% patients with family and history of abortion was 20.69%.

  1. Analysis of an innovative business model

    OpenAIRE

    Picquendaele, Laetitia

    2016-01-01

    This master thesis will investigate the freemium business model, raising on the questions: “Why is the freemium business model innovative and what are its success factors?” The aim is to analyse this business model by confronting theory and practice. Therefore, the document begins with a description discussion of the freemium business model. The literature review concludes by determining the success factors of the business model innovation and of the freemium model. The theory in this first p...

  2. Logistic regression for risk factor modelling in stuttering research.

    Science.gov (United States)

    Reed, Phil; Wu, Yaqionq

    2013-06-01

    To outline the uses of logistic regression and other statistical methods for risk factor analysis in the context of research on stuttering. The principles underlying the application of a logistic regression are illustrated, and the types of questions to which such a technique has been applied in the stuttering field are outlined. The assumptions and limitations of the technique are discussed with respect to existing stuttering research, and with respect to formulating appropriate research strategies to accommodate these considerations. Finally, some alternatives to the approach are briefly discussed. The way the statistical procedures are employed are demonstrated with some hypothetical data. Research into several practical issues concerning stuttering could benefit if risk factor modelling were used. Important examples are early diagnosis, prognosis (whether a child will recover or persist) and assessment of treatment outcome. After reading this article you will: (a) Summarize the situations in which logistic regression can be applied to a range of issues about stuttering; (b) Follow the steps in performing a logistic regression analysis; (c) Describe the assumptions of the logistic regression technique and the precautions that need to be checked when it is employed; (d) Be able to summarize its advantages over other techniques like estimation of group differences and simple regression. Copyright © 2012 Elsevier Inc. All rights reserved.

  3. Modeling global scene factors in attention

    Science.gov (United States)

    Torralba, Antonio

    2003-07-01

    Models of visual attention have focused predominantly on bottom-up approaches that ignored structured contextual and scene information. I propose a model of contextual cueing for attention guidance based on the global scene configuration. It is shown that the statistics of low-level features across the whole image can be used to prime the presence or absence of objects in the scene and to predict their location, scale, and appearance before exploring the image. In this scheme, visual context information can become available early in the visual processing chain, which allows modulation of the saliency of image regions and provides an efficient shortcut for object detection and recognition. 2003 Optical Society of America

  4. Multivariate factor analysis of Girgentana goat milk composition

    Directory of Open Access Journals (Sweden)

    Pietro Giaccone

    2010-01-01

    Full Text Available The interpretation of the several variables that contribute to defining milk quality is difficult due to the high degree of  correlation among them. In this case, one of the best methods of statistical processing is factor analysis, which belongs  to the multivariate groups; for our study this particular statistical approach was employed.  A total of 1485 individual goat milk samples from 117 Girgentana goats, were collected fortnightly from January to July,  and analysed for physical and chemical composition, and clotting properties. Milk pH and tritable acidity were within the  normal range for fresh goat milk. Morning milk yield resulted 704 ± 323 g with 3.93 ± 1.23% and 3.48±0.38% for fat  and protein percentages, respectively. The milk urea content was 43.70 ± 8.28 mg/dl. The clotting ability of Girgentana  milk was quite good, with a renneting time equal to 16.96 ± 3.08 minutes, a rate of curd formation of 2.01 ± 1.63 min-  utes and a curd firmness of 25.08 ± 7.67 millimetres.  Factor analysis was performed by applying axis orthogonal rotation (rotation type VARIMAX; the analysis grouped the  milk components into three latent or common factors. The first, which explained 51.2% of the total covariance, was  defined as “slow milks”, because it was linked to r and pH. The second latent factor, which explained 36.2% of the total  covariance, was defined as “milk yield”, because it is positively correlated to the morning milk yield and to the urea con-  tent, whilst negatively correlated to the fat percentage. The third latent factor, which explained 12.6% of the total covari-  ance, was defined as “curd firmness,” because it is linked to protein percentage, a30 and titatrable acidity. With the aim  of evaluating the influence of environmental effects (stage of kidding, parity and type of kidding, factor scores were anal-  ysed with the mixed linear model. Results showed significant effects of the season of

  5. A Study on Influencing Factors of Knowledge Management Systems Adoption: Models Comparison Approach

    OpenAIRE

    Mei-Chun Yeh; Ming-Shu Yuan

    2007-01-01

    Using Linear Structural Relation model (LISREL model) as analysis method and technology acceptance model and decomposed theory of planned behavior as research foundation, this study approachesmainly from the angle of behavioral intention to examine the influential factors of 421 employees adopting knowledge management systems and in the meantime to compare the two method models mentioned on the top. According to the research, there is no, in comparison with technology acceptance model anddeco...

  6. Testing for time-varying loadings in dynamic factor models

    DEFF Research Database (Denmark)

    Mikkelsen, Jakob Guldbæk

    Abstract: In this paper we develop a test for time-varying factor loadings in factor models. The test is simple to compute and is constructed from estimated factors and residuals using the principal components estimator. The hypothesis is tested by regressing the squared residuals on the squared...... there is evidence of time-varying loadings on the risk factors underlying portfolio returns for around 80% of the portfolios....

  7. MATHEMATICAL RISK ANALYSIS: VIA NICHOLAS RISK MODEL AND BAYESIAN ANALYSIS

    Directory of Open Access Journals (Sweden)

    Anass BAYAGA

    2010-07-01

    Full Text Available The objective of this second part of a two-phased study was to explorethe predictive power of quantitative risk analysis (QRA method andprocess within Higher Education Institution (HEI. The method and process investigated the use impact analysis via Nicholas risk model and Bayesian analysis, with a sample of hundred (100 risk analysts in a historically black South African University in the greater Eastern Cape Province.The first findings supported and confirmed previous literature (KingIII report, 2009: Nicholas and Steyn, 2008: Stoney, 2007: COSA, 2004 that there was a direct relationship between risk factor, its likelihood and impact, certiris paribus. The second finding in relation to either controlling the likelihood or the impact of occurrence of risk (Nicholas risk model was that to have a brighter risk reward, it was important to control the likelihood ofoccurrence of risks as compared with its impact so to have a direct effect on entire University. On the Bayesian analysis, thus third finding, the impact of risk should be predicted along three aspects. These aspects included the human impact (decisions made, the property impact (students and infrastructural based and the business impact. Lastly, the study revealed that although in most business cases, where as business cycles considerably vary dependingon the industry and or the institution, this study revealed that, most impacts in HEI (University was within the period of one academic.The recommendation was that application of quantitative risk analysisshould be related to current legislative framework that affects HEI.

  8. Factoring handedness data: I. Item analysis.

    Science.gov (United States)

    Messinger, H B; Messinger, M I

    1995-12-01

    Recently in this journal Peters and Murphy challenged the validity of factor analyses done on bimodal handedness data, suggesting instead that right- and left-handers be studied separately. But bimodality may be avoidable if attention is paid to Oldfield's questionnaire format and instructions for the subjects. Two characteristics appear crucial: a two-column LEFT-RIGHT format for the body of the instrument and what we call Oldfield's Admonition: not to indicate strong preference for handedness item, such as write, unless "... the preference is so strong that you would never try to use the other hand unless absolutely forced to...". Attaining unimodality of an item distribution would seem to overcome the objections of Peters and Murphy. In a 1984 survey in Boston we used Oldfield's ten-item questionnaire exactly as published. This produced unimodal item distributions. With reflection of the five-point item scale and a logarithmic transformation, we achieved a degree of normalization for the items. Two surveys elsewhere based on Oldfield's 20-item list but with changes in the questionnaire format and the instructions, yielded markedly different item distributions with peaks at each extreme and sometimes in the middle as well.

  9. Sensitivity analysis approaches applied to systems biology models.

    Science.gov (United States)

    Zi, Z

    2011-11-01

    With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

  10. Motivation Factors for Adopting Building Information Modeling (BIM in Iraq

    Directory of Open Access Journals (Sweden)

    W. A. Hatem

    2018-04-01

    Full Text Available Building information modeling (BIM is an integrated and comprehensive system including whatever is related to a construction project and its stages. It represents a unified database for all project data through which project documents are available to all stakeholders. This paper evaluates the factors driving the adoption of BIM in Iraqi construction projects in different ministries and adopts quantitative approach to collect data by using a questionnaire survey specially prepared for this purpose which was distributed to experts in the ministries of the Iraqi construction sector. Returned data were subjected to proper statistical analysis. Results showed that the highest motivation for BIM application is to include it in the educational curricula, raise awareness through courses and workshops and contracting with international experts with experience in BIM field.

  11. Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling.

    Science.gov (United States)

    Golay, Philippe; Reverte, Isabelle; Rossier, Jérôme; Favez, Nicolas; Lecerf, Thierry

    2013-06-01

    The interpretation of the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all cross-loadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  12. Confirmatory factor analysis of posttraumatic stress symptoms in sexually harassed women.

    Science.gov (United States)

    Palmieri, Patrick A; Fitzgerald, Louise F

    2005-12-01

    Posttraumatic stress disorder (PTSD) factor analytic research to date has not provided a clear consensus on the structure of posttraumatic stress symptoms. Seven hypothesized factor structures were evaluated using confirmatory factor analysis of the Posttraumatic Stress Disorder Checklist, a paper-and-pencil measure of posttraumatic stress symptom severity, in a sample of 1,218 women who experienced a broad range of workplace sexual harassment. The model specifying correlated re-experiencing, effortful avoidance, emotional numbing, and hyperarousal factors provided the best fit to the data. Virtually no support was obtained for the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV; American Psychiatric Association, 1994) three-factor model of re-experiencing, avoidance, and hyperarousal factors. Different patterns of correlations with external variables were found for the avoidance and emotional numbing factors, providing further validation of the supported model.

  13. Geologic Framework Model Analysis Model Report

    Energy Technology Data Exchange (ETDEWEB)

    R. Clayton

    2000-12-19

    The purpose of this report is to document the Geologic Framework Model (GFM), Version 3.1 (GFM3.1) with regard to data input, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, qualification status of the model, and the differences between Version 3.1 and previous versions. The GFM represents a three-dimensional interpretation of the stratigraphy and structural features of the location of the potential Yucca Mountain radioactive waste repository. The GFM encompasses an area of 65 square miles (170 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the GFM were chosen to encompass the most widely distributed set of exploratory boreholes (the Water Table or WT series) and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The GFM was constructed from geologic map and borehole data. Additional information from measured stratigraphy sections, gravity profiles, and seismic profiles was also considered. This interim change notice (ICN) was prepared in accordance with the Technical Work Plan for the Integrated Site Model Process Model Report Revision 01 (CRWMS M&O 2000). The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. The GFM is one component of the Integrated Site Model (ISM) (Figure l), which has been developed to provide a consistent volumetric portrayal of the rock layers, rock properties, and mineralogy of the Yucca Mountain site. The ISM consists of three components: (1) Geologic Framework Model (GFM); (2) Rock Properties Model (RPM); and (3) Mineralogic Model (MM). The ISM merges the detailed project stratigraphy into model stratigraphic units that are most useful for the primary downstream models and the

  14. Geologic Framework Model Analysis Model Report

    International Nuclear Information System (INIS)

    Clayton, R.

    2000-01-01

    The purpose of this report is to document the Geologic Framework Model (GFM), Version 3.1 (GFM3.1) with regard to data input, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, qualification status of the model, and the differences between Version 3.1 and previous versions. The GFM represents a three-dimensional interpretation of the stratigraphy and structural features of the location of the potential Yucca Mountain radioactive waste repository. The GFM encompasses an area of 65 square miles (170 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the GFM were chosen to encompass the most widely distributed set of exploratory boreholes (the Water Table or WT series) and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The GFM was constructed from geologic map and borehole data. Additional information from measured stratigraphy sections, gravity profiles, and seismic profiles was also considered. This interim change notice (ICN) was prepared in accordance with the Technical Work Plan for the Integrated Site Model Process Model Report Revision 01 (CRWMS M and O 2000). The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. The GFM is one component of the Integrated Site Model (ISM) (Figure l), which has been developed to provide a consistent volumetric portrayal of the rock layers, rock properties, and mineralogy of the Yucca Mountain site. The ISM consists of three components: (1) Geologic Framework Model (GFM); (2) Rock Properties Model (RPM); and (3) Mineralogic Model (MM). The ISM merges the detailed project stratigraphy into model stratigraphic units that are most useful for the primary downstream models and

  15. The determinant factors of open business model

    Directory of Open Access Journals (Sweden)

    Juan Mejía-Trejo

    2017-01-01

    Full Text Available Intro ducción : Desde principios del siglo XXI, varios autores afirman que los modelos de negocio abiertos (OBM permiten a una organización ser más eficaz en la creación y la ca p tura de valor siendo un requisito previo para el éxito de las asociaciones de co - des arrollo. Como resultado de las tendencias de: crecientes costos de desarrollo y ciclos de vida de los produ c tos/servicios más cortos, las empresas encuentran cada vez más difícil justificar las inversi o nes en innovación. El OBM resuelve ambas tendencias, s ubrayando los términos: " ecosistema de la industria " y/o " modelo de negocio colaborativo ". No sólo cambia el pr o ceso de innovación, sino que también modifica a las propias organizaciones mediante la r e configuración de sus cadenas de valor y redes. Para las empresas, crea una lógica heurística basada en el actual modelo de negocio y tecnología para extenderlas, con estrategia, al desa r rollo de la innov a ción para crear valor y aumentar los ingresos y beneficios. Enfatiza tanto las relaciones exte r nas así como la gobernabilidad, como valiosos recursos con varios roles que promueven la competitividad corporativa. Por lo tanto, para un sector especializado de alta tecnología como lo es el de las tecnologías de la información de la zona metropolitana de Guadalajar a (IT S MZG, exponemos el siguiente problema de investigación: ¿Cuáles son los factores determinantes de la OBM como modelo empírico que se aplc a do en el ITSMZG? Método: Como se ve, esta investigación tiene como objetivo plantear, los factores determ i nantes de la OBM como un modelo empírico que sea aplicado en el ITSMZG.Se trata de un estudio documental para seleccionar las principales v a riables entre los especialistas de las ITSMZG que practican el proceso OBM mediante el proceso de j e rarquía analítica (AHP y el Panel de Delphi a fin de contrastar los términos académicos con la experiencia de los e s pecialistas. Es un

  16. Factor analysis for imperfect maintenance planning at nuclear power plants by cognitive task analysis

    International Nuclear Information System (INIS)

    Takagawa, Kenichi; Iida, Hiroyasu

    2011-01-01

    Imperfect maintenance planning was frequently identified in domestic nuclear power plants. To prevent such an event, we analyzed causal factors in maintenance planning stages and showed the directionality of countermeasures in this study. There is a pragmatic limit in finding the causal factors from the items based on report descriptions. Therefore, the idea of the systemic accident model, which is used to monitor the performance variability in normal circumstances, is taken as a new concept instead of investigating negative factors. As an actual method for analyzing usual activities, cognitive task analysis (CTA) was applied. Persons who experienced various maintenance activities at one electric power company were interviewed about sources related to decision making during maintenance planning, and then usual factors affecting planning were extracted as performance variability factors. The tendency of domestic events was analyzed using the classification item of those factors, and the directionality of countermeasures was shown. The following are critical for preventing imperfect maintenance planning: the persons in charge should fully understand the situation of the equipment for which they are responsible in the work planning and maintenance evaluation stages, and they should definitely understand, for example, the maintenance bases of that equipment. (author)

  17. Research on Human-Error Factors of Civil Aircraft Pilots Based On Grey Relational Analysis

    Directory of Open Access Journals (Sweden)

    Guo Yundong

    2018-01-01

    Full Text Available In consideration of the situation that civil aviation accidents involve many human-error factors and show the features of typical grey systems, an index system of civil aviation accident human-error factors is built using human factor analysis and classification system model. With the data of accidents happened worldwide between 2008 and 2011, the correlation between human-error factors can be analyzed quantitatively using the method of grey relational analysis. Research results show that the order of main factors affecting pilot human-error factors is preconditions for unsafe acts, unsafe supervision, organization and unsafe acts. The factor related most closely with second-level indexes and pilot human-error factors is the physical/mental limitations of pilots, followed by supervisory violations. The relevancy between the first-level indexes and the corresponding second-level indexes and the relevancy between second-level indexes can also be analyzed quantitatively.

  18. Separating form factor and nuclear model effects in quasielastic neutrino-nucleus scattering

    Science.gov (United States)

    Wieske, Joseph

    2017-09-01

    When studying neutrino oscillations an understanding of charged current quasielastic (CCQE) neutrino-nucleus scattering is imperative. This interaction depends on a nuclear model as well as knowledge of form factors. In the past, CCQE data from the MiniBooNE experiment was analyzed assuming the Relativistic Fermi Gas (RFG) nuclear model, an axial dipole form factor in, and using the the z-expansion for the axial form factor in. We present the first analysis that combines a non-RFG nuclear model, in particular the Correlated Fermi Gas nuclear model (CFG) of, and the z expansion for the axial form factor. This will allow us to separate form factor and nuclear model effects in CCQE scattering. This project was supported through the Wayne State University REU program under NSF Grant PHY-1460853 and by the DOE Grant DE-SC0007983.

  19. Exploring Technostress: Results of a Large Sample Factor Analysis

    Directory of Open Access Journals (Sweden)

    Steponas Jonušauskas

    2016-06-01

    Full Text Available With reference to the results of a large sample factor analysis, the article aims to propose the frame examining technostress in a population. The survey and principal component analysis of the sample consisting of 1013 individuals who use ICT in their everyday work was implemented in the research. 13 factors combine 68 questions and explain 59.13 per cent of the answers dispersion. Based on the factor analysis, questionnaire was reframed and prepared to reasonably analyze the respondents’ answers, revealing technostress causes and consequences as well as technostress prevalence in the population in a statistically validated pattern. A key elements of technostress based on factor analysis can serve for the construction of technostress measurement scales in further research.

  20. Economic Analysis of Factors Affecting Technical Efficiency of ...

    African Journals Online (AJOL)

    Economic Analysis of Factors Affecting Technical Efficiency of Smallholders ... socio-economic characteristics which influence technical efficiency in maize production. ... Ministry of Agriculture and livestock, records, books, reports and internet.

  1. An alternative method for centrifugal compressor loading factor modelling

    Science.gov (United States)

    Galerkin, Y.; Drozdov, A.; Rekstin, A.; Soldatova, K.

    2017-08-01

    The loading factor at design point is calculated by one or other empirical formula in classical design methods. Performance modelling as a whole is out of consideration. Test data of compressor stages demonstrates that loading factor versus flow coefficient at the impeller exit has a linear character independent of compressibility. Known Universal Modelling Method exploits this fact. Two points define the function - loading factor at design point and at zero flow rate. The proper formulae include empirical coefficients. A good modelling result is possible if the choice of coefficients is based on experience and close analogs. Earlier Y. Galerkin and K. Soldatova had proposed to define loading factor performance by the angle of its inclination to the ordinate axis and by the loading factor at zero flow rate. Simple and definite equations with four geometry parameters were proposed for loading factor performance calculated for inviscid flow. The authors of this publication have studied the test performance of thirteen stages of different types. The equations are proposed with universal empirical coefficients. The calculation error lies in the range of plus to minus 1,5%. The alternative model of a loading factor performance modelling is included in new versions of the Universal Modelling Method.

  2. Arc modeling for welding analysis

    International Nuclear Information System (INIS)

    Glickstein, S.S.

    1978-04-01

    A one-dimensional model of the welding arc that considers heat generation by the Joule effect and heat losses by radiation and conduction has been used to study the effects of various gases and gas mixtures currently employed for welding applications. Minor additions of low ionization potential impurities to these gases are shown to significantly perturb the electrical properties of the parent gas causing gross changes in the radial temperature distribution of the arc discharge. Such changes are reflected in the current density distribution and ultimately in the input energy distribution to the weldment. The result is observed as a variation in weld penetration. Recently published experiments and analyses of welding arcs are also evaluated and shown to contain erroneous data and results. Contrary to previous beliefs, the inclusion of a radiation loss term in the basic energy balance equation is important and cannot be considered as negligible in an argon arc at temperatures as low as 10,000 0 K. The one-dimensional analysis of the welding arc as well as the evaluation of these earlier published reports helps to explain the effects of various gases used for welding, improves our understanding of the physics of the welding arc, and provides a stepping stone for a more elaborate model which can be applied to help optimize welding parameters

  3. Structural and functional analysis of coral Hypoxia Inducible Factor.

    Science.gov (United States)

    Zoccola, Didier; Morain, Jonas; Pagès, Gilles; Caminiti-Segonds, Natacha; Giuliano, Sandy; Tambutté, Sylvie; Allemand, Denis

    2017-01-01

    Tissues of symbiotic Cnidarians are exposed to wide, rapid and daily variations of oxygen concentration. Indeed, during daytime, intracellular O2 concentration increases due to symbiont photosynthesis, while during night, respiration of both host cells and symbionts leads to intra-tissue hypoxia. The Hypoxia Inducible Factor 1 (HIF-1) is a heterodimeric transcription factor used for maintenance of oxygen homeostasis and adaptation to hypoxia. Here, we carried out a mechanistic study of the response to variations of O2 concentrations of the coral model Stylophora pistillata. In silico analysis showed that homologs of HIF-1 α (SpiHIF-1α) and HIF-1β (SpiHIF-1β) exist in coral. A specific SpiHIF-1 DNA binding on mammalian Hypoxia Response Element (HRE) sequences was shown in extracts from coral exposed to dark conditions. Then, we cloned the coral HIF-1α and β genes and determined their expression and transcriptional activity. Although HIF-1α has an incomplete Oxygen-dependent Degradation Domain (ODD) relative to its human homolog, its protein level is increased under hypoxia when tested in mammalian cells. Moreover, co-transfection of SpiHIF-1α and β in mammalian cells stimulated an artificial promoter containing HRE only in hypoxic conditions. This study shows the strong conservation of molecular mechanisms involved in adaptation to O2 concentration between Cnidarians and Mammals whose ancestors diverged about 1,200-1,500 million years ago.

  4. Structural and functional analysis of coral Hypoxia Inducible Factor.

    Directory of Open Access Journals (Sweden)

    Didier Zoccola

    Full Text Available Tissues of symbiotic Cnidarians are exposed to wide, rapid and daily variations of oxygen concentration. Indeed, during daytime, intracellular O2 concentration increases due to symbiont photosynthesis, while during night, respiration of both host cells and symbionts leads to intra-tissue hypoxia. The Hypoxia Inducible Factor 1 (HIF-1 is a heterodimeric transcription factor used for maintenance of oxygen homeostasis and adaptation to hypoxia. Here, we carried out a mechanistic study of the response to variations of O2 concentrations of the coral model Stylophora pistillata. In silico analysis showed that homologs of HIF-1 α (SpiHIF-1α and HIF-1β (SpiHIF-1β exist in coral. A specific SpiHIF-1 DNA binding on mammalian Hypoxia Response Element (HRE sequences was shown in extracts from coral exposed to dark conditions. Then, we cloned the coral HIF-1α and β genes and determined their expression and transcriptional activity. Although HIF-1α has an incomplete Oxygen-dependent Degradation Domain (ODD relative to its human homolog, its protein level is increased under hypoxia when tested in mammalian cells. Moreover, co-transfection of SpiHIF-1α and β in mammalian cells stimulated an artificial promoter containing HRE only in hypoxic conditions. This study shows the strong conservation of molecular mechanisms involved in adaptation to O2 concentration between Cnidarians and Mammals whose ancestors diverged about 1,200-1,500 million years ago.

  5. Sustainable Manufacturing Practices in Malaysian Automotive Industry: Confirmatory Factor Analysis

    OpenAIRE

    Habidin, Nurul Fadly; Zubir, Anis Fadzlin Mohd; Fuz, Nursyazwani Mohd; Latip, Nor Azrin Md; Azman, Mohamed Nor Azhari

    2015-01-01

    Sustainable manufacturing practices (SMPs) have received enormous attention in current years as an effective solution to support the continuous growth and expansion of the automotive manufacturing industry. This reported study was conducted to examine confirmatory factor analysis for SMP such as manufacturing process, supply chain management, social responsibility, and environmental management based on automotive manufacturing industry. The results of confirmatory factor analysis show that fo...

  6. An Analysis of Construction Accident Factors Based on Bayesian Network

    OpenAIRE

    Yunsheng Zhao; Jinyong Pei

    2013-01-01

    In this study, we have an analysis of construction accident factors based on bayesian network. Firstly, accidents cases are analyzed to build Fault Tree method, which is available to find all the factors causing the accidents, then qualitatively and quantitatively analyzes the factors with Bayesian network method, finally determines the safety management program to guide the safety operations. The results of this study show that bad condition of geological environment has the largest posterio...

  7. Model Performance Evaluation and Scenario Analysis (MPESA)

    Science.gov (United States)

    Model Performance Evaluation and Scenario Analysis (MPESA) assesses the performance with which models predict time series data. The tool was developed Hydrological Simulation Program-Fortran (HSPF) and the Stormwater Management Model (SWMM)

  8. Problems with the factor analysis of items: Solutions based on item response theory and item parcelling

    Directory of Open Access Journals (Sweden)

    Gideon P. De Bruin

    2004-10-01

    Full Text Available The factor analysis of items often produces spurious results in the sense that unidimensional scales appear multidimensional. This may be ascribed to failure in meeting the assumptions of linearity and normality on which factor analysis is based. Item response theory is explicitly designed for the modelling of the non-linear relations between ordinal variables and provides a strong alternative to the factor analysis of items. Items may also be combined in parcels that are more likely to satisfy the assumptions of factor analysis than do the items. The use of the Rasch rating scale model and the factor analysis of parcels is illustrated with data obtained with the Locus of Control Inventory. The results of these analyses are compared with the results obtained through the factor analysis of items. It is shown that the Rasch rating scale model and the factoring of parcels produce superior results to the factor analysis of items. Recommendations for the analysis of scales are made. Opsomming Die faktorontleding van items lewer dikwels misleidende resultate op, veral in die opsig dat eendimensionele skale as meerdimensioneel voorkom. Hierdie resultate kan dikwels daaraan toegeskryf word dat daar nie aan die aannames van lineariteit en normaliteit waarop faktorontleding berus, voldoen word nie. Itemresponsteorie, wat eksplisiet vir die modellering van die nie-liniêre verbande tussen ordinale items ontwerp is, bied ’n aantreklike alternatief vir die faktorontleding van items. Items kan ook in pakkies gegroepeer word wat meer waarskynlik aan die aannames van faktorontleding voldoen as individuele items. Die gebruik van die Rasch beoordelingskaalmodel en die faktorontleding van pakkies word aan die hand van data wat met die Lokus van Beheervraelys verkry is, gedemonstreer. Die resultate van hierdie ontledings word vergelyk met die resultate wat deur ‘n faktorontleding van die individuele items verkry is. Die resultate dui daarop dat die Rasch

  9. Model of key success factors for Business Intelligence implementation

    Directory of Open Access Journals (Sweden)

    Peter Mesaros

    2016-07-01

    Full Text Available New progressive technologies recorded growth in every area. Information-communication technologies facilitate the exchange of information and it facilitates management of everyday activities in enterprises. Specific modules (such as Business Intelligence facilitate decision-making. Several studies have demonstrated the positive impact of Business Intelligence to decision-making. The first step is to put in place the enterprise. The implementation process is influenced by many factors. This article discusses the issue of key success factors affecting to successful implementation of Business Intelligence. The article describes the key success factors for successful implementation and use of Business Intelligence based on multiple studies. The main objective of this study is to verify the effects and dependence of selected factors and proposes a model of key success factors for successful implementation of Business Intelligence. Key success factors and the proposed model are studied in Slovak enterprises.

  10. Final Technical Report: Advanced Measurement and Analysis of PV Derate Factors.

    Energy Technology Data Exchange (ETDEWEB)

    King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Burton, Patrick D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Christian Birk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-12-01

    The Advanced Measurement and Analysis of PV Derate Factors project focuses on improving the accuracy and reducing the uncertainty of PV performance model predictions by addressing a common element of all PV performance models referred to as “derates”. Widespread use of “rules of thumb”, combined with significant uncertainty regarding appropriate values for these factors contribute to uncertainty in projected energy production.

  11. Dependent defaults and losses with factor copula models

    Directory of Open Access Journals (Sweden)

    Ackerer Damien

    2017-12-01

    Full Text Available We present a class of flexible and tractable static factor models for the term structure of joint default probabilities, the factor copula models. These high-dimensional models remain parsimonious with paircopula constructions, and nest many standard models as special cases. The loss distribution of a portfolio of contingent claims can be exactly and efficiently computed when individual losses are discretely supported on a finite grid. Numerical examples study the key features affecting the loss distribution and multi-name credit derivatives prices. An empirical exercise illustrates the flexibility of our approach by fitting credit index tranche prices.

  12. Left ventricular wall motion abnormalities evaluated by factor analysis as compared with Fourier analysis

    International Nuclear Information System (INIS)

    Hirota, Kazuyoshi; Ikuno, Yoshiyasu; Nishikimi, Toshio

    1986-01-01

    Factor analysis was applied to multigated cardiac pool scintigraphy to evaluate its ability to detect left ventricular wall motion abnormalities in 35 patients with old myocardial infarction (MI), and in 12 control cases with normal left ventriculography. All cases were also evaluated by conventional Fourier analysis. In most cases with normal left ventriculography, the ventricular and atrial factors were extracted by factor analysis. In cases with MI, the third factor was obtained in the left ventricle corresponding to wall motion abnormality. Each case was scored according to the coincidence of findings of ventriculography and those of factor analysis or Fourier analysis. Scores were recorded for three items; the existence, location, and degree of asynergy. In cases of MI, the detection rate of asynergy was 94 % by factor analysis, 83 % by Fourier analysis, and the agreement in respect to location was 71 % and 66 %, respectively. Factor analysis had higher scores than Fourier analysis, but this was not significant. The interobserver error of factor analysis was less than that of Fourier analysis. Factor analysis can display locations and dynamic motion curves of asynergy, and it is regarded as a useful method for detecting and evaluating left ventricular wall motion abnormalities. (author)

  13. Multi-Scale Factor Analysis of High-Dimensional Brain Signals

    KAUST Repository

    Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain

    2017-01-01

    In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive

  14. Efficiency limit factor analysis for the Francis-99 hydraulic turbine

    Science.gov (United States)

    Zeng, Y.; Zhang, L. X.; Guo, J. P.; Guo, Y. K.; Pan, Q. L.; Qian, J.

    2017-01-01

    The energy loss in hydraulic turbine is the most direct factor that affects the efficiency of the hydraulic turbine. Based on the analysis theory of inner energy loss of hydraulic turbine, combining the measurement data of the Francis-99, this paper calculates characteristic parameters of inner energy loss of the hydraulic turbine, and establishes the calculation model of the hydraulic turbine power. Taken the start-up test conditions given by Francis-99 as case, characteristics of the inner energy of the hydraulic turbine in transient and transformation law are researched. Further, analyzing mechanical friction in hydraulic turbine, we think that main ingredients of mechanical friction loss is the rotation friction loss between rotating runner and water body, and defined as the inner mechanical friction loss. The calculation method of the inner mechanical friction loss is given roughly. Our purpose is that explore and research the method and way increasing transformation efficiency of water flow by means of analysis energy losses in hydraulic turbine.

  15. A dynamic factor model of the evaluation of the financial crisis in Turkey.

    Science.gov (United States)

    Sezgin, F; Kinay, B

    2010-01-01

    Factor analysis has been widely used in economics and finance in situations where a relatively large number of variables are believed to be driven by few common causes of variation. Dynamic factor analysis (DFA) which is a combination of factor and time series analysis, involves autocorrelation matrices calculated from multivariate time series. Dynamic factor models were traditionally used to construct economic indicators, macroeconomic analysis, business cycles and forecasting. In recent years, dynamic factor models have become more popular in empirical macroeconomics. They have more advantages than other methods in various respects. Factor models can for instance cope with many variables without running into scarce degrees of freedom problems often faced in regression-based analysis. In this study, a model which determines the effect of the global crisis on Turkey is proposed. The main aim of the paper is to analyze how several macroeconomic quantities show an alteration before the evolution of the crisis and to decide if a crisis can be forecasted or not.

  16. Quantifying credit portfolio losses under multi-factor models

    NARCIS (Netherlands)

    G. Colldeforns-Papiol (Gemma); L. Ortiz Gracia (Luis); C.W. Oosterlee (Kees)

    2018-01-01

    textabstractIn this work, we investigate the challenging problem of estimating credit risk measures of portfolios with exposure concentration under the multi-factor Gaussian and multi-factor t-copula models. It is well-known that Monte Carlo (MC) methods are highly demanding from the computational

  17. Rethinking "Harmonious Parenting" Using a Three-Factor Discipline Model

    Science.gov (United States)

    Greenspan, Stephen

    2006-01-01

    Diana Baumrind's typology of parenting is based on a two-factor model of "control" and "warmth". Her recommended discipline style, labeled "authoritative parenting", was constructed by taking high scores on these two factors. A problem with authoritative parenting is that it does not allow for flexible and differentiated responses to discipline…

  18. Person-fit to the Five Factor Model of personality

    Czech Academy of Sciences Publication Activity Database

    Allik, J.; Realo, A.; Mõttus, R.; Borkenau, P.; Kuppens, P.; Hřebíčková, Martina

    2012-01-01

    Roč. 71, č. 1 (2012), s. 35-45 ISSN 1421-0185 R&D Projects: GA ČR GAP407/10/2394 Institutional research plan: CEZ:AV0Z70250504 Keywords : Five Factor Model * cross - cultural comparison * person-fit Subject RIV: AN - Psychology Impact factor: 0.638, year: 2012

  19. Is There Really a Global Business Cycle? : A Dynamic Factor Model with Stochastic Factor Selection

    NARCIS (Netherlands)

    T. Berger (Tino); L.C.G. Pozzi (Lorenzo)

    2016-01-01

    textabstractWe investigate the presence of international business cycles in macroeconomic aggregates (output, consumption, investment) using a panel of 60 countries over the period 1961-2014. The paper presents a Bayesian stochastic factor selection approach for dynamic factor models with

  20. Analysis of related risk factors for pancreatic fistula after pancreaticoduodenectomy

    Directory of Open Access Journals (Sweden)

    Qi-Song Yu

    2016-08-01

    Full Text Available Objective: To explore the related risk factors for pancreatic fistula after pancreaticoduodenectomy to provide a theoretical evidence for effectively preventing the occurrence of pancreatic fistula. Methods: A total of 100 patients who were admitted in our hospital from January, 2012 to January, 2015 and had performed pancreaticoduodenectomy were included in the study. The related risk factors for developing pancreatic fistula were collected for single factor and Logistic multi-factor analysis. Results: Among the included patients, 16 had pancreatic fistula, and the total occurrence rate was 16% (16/100. The single-factor analysis showed that the upper abdominal operation history, preoperative bilirubin, pancreatic texture, pancreatic duct diameter, intraoperative amount of bleeding, postoperative hemoglobin, and application of somatostatin after operation were the risk factors for developing pancreatic fistula (P<0.05. The multi-factor analysis showed that the upper abdominal operation history, the soft pancreatic texture, small pancreatic duct diameter, and low postoperative hemoglobin were the dependent risk factors for developing pancreatic fistula (OR=4.162, 6.104, 5.613, 4.034, P<0.05. Conclusions: The occurrence of pancreatic fistula after pancreaticoduodenectomy is closely associated with the upper abdominal operation history, the soft pancreatic texture, small pancreatic duct diameter, and low postoperative hemoglobin; therefore, effective measures should be taken to reduce the occurrence of pancreatic fistula according to the patients’ own conditions.

  1. Environmental Performance in Countries Worldwide: Determinant Factors and Multivariate Analysis

    Directory of Open Access Journals (Sweden)

    Isabel Gallego-Alvarez

    2014-11-01

    Full Text Available The aim of this study is to analyze the environmental performance of countries and the variables that can influence it. At the same time, we performed a multivariate analysis using the HJ-biplot, an exploratory method that looks for hidden patterns in the data, obtained from the usual singular value decomposition (SVD of the data matrix, to contextualize the countries grouped by geographical areas and the variables relating to environmental indicators included in the environmental performance index. The sample used comprises 149 countries of different geographic areas. The findings obtained from the empirical analysis emphasize that socioeconomic factors, such as economic wealth and education, as well as institutional factors represented by the style of public administration, in particular control of corruption, are determinant factors of environmental performance in the countries analyzed. In contrast, no effect on environmental performance was found for factors relating to the internal characteristics of a country or political factors.

  2. Comparing statistical and machine learning classifiers: alternatives for predictive modeling in human factors research.

    Science.gov (United States)

    Carnahan, Brian; Meyer, Gérard; Kuntz, Lois-Ann

    2003-01-01

    Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two machine learning approaches--genetic programming and decision tree induction--were used to construct classification models designed to predict whether or not a student truck driver would pass his or her commercial driver license (CDL) examination. The models were developed and validated using the curriculum scores and CDL exam performances of 37 student truck drivers who had completed a 320-hr driver training course. Results indicated that the machine learning classification models were superior to discriminant analysis and logistic regression in terms of predictive accuracy. Actual or potential applications of this research include the creation of models that more accurately predict human performance outcomes.

  3. Testing alternative factor models of PTSD and the robustness of the dysphoria factor.

    Science.gov (United States)

    Elklit, Ask; Armour, Cherie; Shevlin, Mark

    2010-01-01

    This study first aimed to examine the structure of self-reported posttraumatic stress disorder (PTSD) symptoms using three different samples. The second aim of the paper was to test the robustness of the factor analytic model when depression scores were controlled for. Based on previous factor analytic findings and the DSM-IV formulation, six confirmatory factor models were specified and estimated that reflected different symptom clusters. The best fitting model was subsequently re-fitted to the data after including a depression variable. The analyses were based on responses from 973 participants across three samples. Sample 1 consisted of 633 parents who were members of 'The National Association of Infant Death' and who had lost a child. Sample 2 consisted of 227 victims of rape, who completed a questionnaire within 4 weeks of the rape. Each respondent had been in contact with the Centre for Rape Victims (CRV) at the Aarhus University Hospital, Denmark. Sample 3 consisted of 113 refugees resident in Denmark. All participants had been referred to a treatment centre which focused on rehabilitating refugees through treatment for psychosocial integration problems (RRCF: Rehabliterings og Revliderings Centre for Flygtninge). In total 500 participants received a diagnosis of PTSD/sub-clinical PTSD (Sample 1, N=214; 2, N=176; 3, N=110). A correlated four-factor model with re-experiencing, avoidance, dysphoria, and arousal factors provided the best fit to the sample data. The average attenuation in the factor loadings was highest for the dysphoria factor (M=-.26, SD=.11) compared to the re-experiencing (M=-.14, SD=.18), avoidance (M=-.10, SD=.21), and arousal (M=-.09, SD=.13) factors. With regards to the best fitting factor model these results concur with previous research findings using different trauma populations but do not reflect the current DSM-IV symptom groupings. The attenuation of dysphoria factor loadings suggests that dysphoria is a non-specific component of

  4. Innovative supply chain optimization models with multiple uncertainty factors

    DEFF Research Database (Denmark)

    Choi, Tsan Ming; Govindan, Kannan; Li, Xiang

    2017-01-01

    Uncertainty is an inherent factor that affects all dimensions of supply chain activities. In today’s business environment, initiatives to deal with one specific type of uncertainty might not be effective since other types of uncertainty factors and disruptions may be present. These factors relate...... to supply chain competition and coordination. Thus, to achieve a more efficient and effective supply chain requires the deployment of innovative optimization models and novel methods. This preface provides a concise review of critical research issues regarding innovative supply chain optimization models...

  5. Spatial aspects affecting acidification factors in European acidification modelling

    NARCIS (Netherlands)

    Bellekom, S.; Hettelingh, J. -P.; Aben, J.

    Plain linear models have recently been used in methodologies to model fate and transport for assessing acidification in life cycle impact assessment (LCIA), or in support of air pollution abatement policies. These models originate from a statistical analysis of the relationship between inputs and

  6. The effects of motivational factors on car use: a multidisciplinary modelling approach

    Energy Technology Data Exchange (ETDEWEB)

    Steg, L.; Ras, M. [University of Groningen (Netherlands). Centre for Environmental and Traffic Psychology; Geurs, K. [National Institute of Public Health and Environment, Bilthoven (Netherlands)

    2001-11-01

    Current transport models usually do not take motivational factors into account, and if they do, it is only implicitly. This paper presents a modelling approach aimed at explicitly examining the effects of motivational factors on present and future car use in the Netherlands. A car-use forecasting model for the years 2010 and 2020 was constructed on the basis of (i) a multinominal regression analysis, which revealed the importance of a motivational variable (viz., problem awareness) in explaining current car-use behavior separate from socio-demographic and socio-economic variables, and (ii) a population model constructed to forecast the size and composition of the Dutch population. The results show that car use could be better explained by taking motivational factors explicitly into account, and that the level of car use forecast might change significantly if changes in motivations are assumed. The question on how motivational factors could be incorporated into current (Dutch) national transport models was also addressed. (author)

  7. A temperature dependent slip factor based thermal model for friction

    Indian Academy of Sciences (India)

    This paper proposes a new slip factor based three-dimensional thermal model to predict the temperature distribution during friction stir welding of 304L stainless steel plates. The proposed model employs temperature and radius dependent heat source to study the thermal cycle, temperature distribution, power required, the ...

  8. Study on visibility evaluation model which is considered field factors; Field factor wo koryoshita shininsei hyoka model ni kansuru kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    Nakanishi, M; Hagiwara, T [Hokkaido University, Sapporo (Japan)

    1997-10-01

    The present study proposes a model to evaluate visual performance of road traffic facilities required for drivers. Two factors were employed to obtain the suitable contrast for drivers under driving situation. One factor is a suitable luminance range, which is derived from minimum required luminance and glare luminance. Another is a field. The model showed capability of providing visibility range in some cases. 8 refs., 4 figs., 2 tabs.

  9. Hypersonic - Model Analysis as a Service

    DEFF Research Database (Denmark)

    Acretoaie, Vlad; Störrle, Harald

    2014-01-01

    Hypersonic is a Cloud-based tool that proposes a new approach to the deployment of model analysis facilities. It is implemented as a RESTful Web service API o_ering analysis features such as model clone detection. This approach allows the migration of resource intensive analysis algorithms from...

  10. Factor copula models for data with spatio-temporal dependence

    KAUST Repository

    Krupskii, Pavel

    2017-10-13

    We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

  11. Factor copula models for data with spatio-temporal dependence

    KAUST Repository

    Krupskii, Pavel; Genton, Marc G.

    2017-01-01

    We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

  12. A pragmatic approach to estimate alpha factors for common cause failure analysis

    International Nuclear Information System (INIS)

    Hassija, Varun; Senthil Kumar, C.; Velusamy, K.

    2014-01-01

    Highlights: • Estimation of coefficients in alpha factor model for common cause analysis. • A derivation of plant specific alpha factors is demonstrated. • We examine sensitivity of common cause contribution to total system failure. • We compare beta factor and alpha factor models for various redundant configurations. • The use of alpha factors is preferable, especially for large redundant systems. - Abstract: Most of the modern technological systems are deployed with high redundancy but still they fail mainly on account of common cause failures (CCF). Various models such as Beta Factor, Multiple Greek Letter, Binomial Failure Rate and Alpha Factor exists for estimation of risk from common cause failures. Amongst all, alpha factor model is considered most suitable for high redundant systems as it arrives at common cause failure probabilities from a set of ratios of failures and the total component failure probability Q T . In the present study, alpha factor model is applied for the assessment of CCF of safety systems deployed at two nuclear power plants. A method to overcome the difficulties in estimation of the coefficients viz., alpha factors in the model, importance of deriving plant specific alpha factors and sensitivity of common cause contribution to the total system failure probability with respect to hazard imposed by various CCF events is highlighted. An approach described in NUREG/CR-5500 is extended in this study to provide more explicit guidance for a statistical approach to derive plant specific coefficients for CCF analysis especially for high redundant systems. The procedure is expected to aid regulators for independent safety assessment

  13. Collapsing Factors in Multitrait-Multimethod Models: Examining Consequences of a Mismatch Between Measurement Design and Model

    Directory of Open Access Journals (Sweden)

    Christian eGeiser

    2015-08-01

    Full Text Available Models of confirmatory factor analysis (CFA are frequently applied to examine the convergent validity of scores obtained from multiple raters or methods in so-called multitrait-multimethod (MTMM investigations. Many applications of CFA-MTMM and similarly structured models result in solutions in which at least one method (or specific factor shows non-significant loading or variance estimates. Eid et al. (2008 distinguished between MTMM measurement designs with interchangeable (randomly selected versus structurally different (fixed methods and showed that each type of measurement design implies specific CFA-MTMM measurement models. In the current study, we hypothesized that some of the problems that are commonly seen in applications of CFA-MTMM models may be due to a mismatch between the underlying measurement design and fitted models. Using simulations, we found that models with M method factors (where M is the total number of methods and unconstrained loadings led to a higher proportion of solutions in which at least one method factor became empirically unstable when these models were fit to data generated from structurally different methods. The simulations also revealed that commonly used model goodness-of-fit criteria frequently failed to identify incorrectly specified CFA-MTMM models. We discuss implications of these findings for other complex CFA models in which similar issues occur, including nested (bifactor and latent state-trait models.

  14. Formal Analysis of Domain Models

    National Research Council Canada - National Science Library

    Bharadwaj, Ramesh

    2002-01-01

    Recently, there has been a great deal of interest in the application of formal methods, in particular, precise formal notations and automatic analysis tools for the creation and analysis of requirements specifications (i.e...

  15. Beyond factor analysis: Multidimensionality and the Parkinson's Disease Sleep Scale-Revised.

    Directory of Open Access Journals (Sweden)

    Maria E Pushpanathan

    Full Text Available Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson's disease (PD. The Parkinson's Disease Sleep Scale (PDSS and its variants (the Parkinson's disease Sleep Scale-Revised; PDSS-R, and the Parkinson's Disease Sleep Scale-2; PDSS-2 quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA and REM sleep behaviour disorder (RBD symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments.

  16. ModelMate - A graphical user interface for model analysis

    Science.gov (United States)

    Banta, Edward R.

    2011-01-01

    ModelMate is a graphical user interface designed to facilitate use of model-analysis programs with models. This initial version of ModelMate supports one model-analysis program, UCODE_2005, and one model software program, MODFLOW-2005. ModelMate can be used to prepare input files for UCODE_2005, run UCODE_2005, and display analysis results. A link to the GW_Chart graphing program facilitates visual interpretation of results. ModelMate includes capabilities for organizing directories used with the parallel-processing capabilities of UCODE_2005 and for maintaining files in those directories to be identical to a set of files in a master directory. ModelMate can be used on its own or in conjunction with ModelMuse, a graphical user interface for MODFLOW-2005 and PHAST.

  17. A confirmatory factor analysis of the Utrecht Work Engagement Scale for Students in a Chinese sample.

    Science.gov (United States)

    Meng, Lina; Jin, Yi

    2017-02-01

    Educational institutions play an important role in encouraging students' engagement with course work. Educators are finding instruments to measure students' engagement in order to develop strategies to improve it. Little is known about the factor structure of the Utrecht Work Engagement Scale for Students among Chinese nursing students. The aim of this research was to examine the factor structure of the Utrecht Work Engagement Scale for Students via confirmatory factor analysis. The study used a cross-sectional design. A sample of 480 students from a nursing school in one Chinese university completed the Utrecht Work Engagement Scale for Students. Factor analysis was used to analyze the resulting data. The overall results of internal consistency reliability and confirmatory factor analysis provided evidence supporting the reliability and three-factor structure of the Utrecht Work Engagement Scale for Students. The total internal consistency reliability coefficients were 0.91. Model comparison tests indicated that an oblique factors model that permitted correlations between pairs of error terms fitted the data better than other first-order models. In addition, due to the three strongly intercorrelated factors, a second-order model was found to fit the data well, providing support for the factorial structure of the Utrecht Work Engagement Scale for Students. The findings of confirmatory factor analysis provided evidence supporting the reliability and three-factor structure of the Utrecht Work Engagement Scale for Students when evaluated with a Chinese nursing student sample in this study. Thus, it is appropriate to use The Utrecht Work Engagement Scale for Students in for assessing the engagement among Chinese nursing students. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Constructing the Japanese version of the Maslach Burnout Inventory-Student Survey: Confirmatory factor analysis.

    Science.gov (United States)

    Tsubakita, Takashi; Shimazaki, Kazuyo

    2016-01-01

    To examine the factorial validity of the Maslach Burnout Inventory-Student Survey, using a sample of 2061 Japanese university students majoring in the medical and natural sciences (67.9% male, 31.8% female; Mage  = 19.6 years, standard deviation = 1.5). The back-translated scale used unreversed items to assess inefficacy. The inventory's descriptive properties and Cronbach's alphas were calculated using SPSS software. The present authors compared fit indices of the null, one factor, and default three factor models via confirmatory factor analysis with maximum-likelihood estimation using AMOS software, version 21.0. Intercorrelations between exhaustion, cynicism, and inefficacy were relatively higher than in prior studies. Cronbach's alphas were 0.76, 0.85, and 0.78, respectively. Although fit indices of the hypothesized three factor model did not meet the respective criteria, the model demonstrated better fit than did the null and one factor models. The present authors added four paths between error variables within items, but the modified model did not show satisfactory fit. Subsequent analysis revealed that a bi-factor model fit the data better than did the hypothesized or modified three factor models. The Japanese version of the Maslach Burnout Inventory-Student Survey needs minor changes to improve the fit of its three factor model, but the scale as a whole can be used to adequately assess overall academic burnout in Japanese university students. Although the scale was back-translated, two items measuring exhaustion whose expressions overlapped should be modified, and all items measuring inefficacy should be reversed in order to statistically clarify the factorial difference between the scale's three factors. © 2015 The Authors. Japan Journal of Nursing Science © 2015 Japan Academy of Nursing Science.

  19. ANALYSIS MODEL FOR RETURN ON CAPITAL EMPLOYED

    Directory of Open Access Journals (Sweden)

    BURJA CAMELIA

    2013-02-01

    Full Text Available At the microeconomic level, the appreciation of the capitals’ profitability is a very complex action which is ofinterest for stakeholders. This study has as main purpose to extend the traditional analysis model for the capitals’profitability, based on the ratio “Return on capital employed”. In line with it the objectives of this work aim theidentification of factors that exert an influence on the capital’s profitability utilized by a company and the measurementof their contribution in the manifestation of the phenomenon. The proposed analysis model is validated on the use caseof a representative company from the agricultural sector. The results obtained reveal that in a company there are somefactors which can act positively on the capitals’ profitability: capital turnover, sales efficiency, increase the share ofsales in the total revenues, improvement of the expenses’ efficiency. The findings are useful both for the decisionmakingfactors in substantiating the economic strategies and for the capital owners who are interested in efficiency oftheir investments.

  20. A hierarchical factor analysis of a safety culture survey.

    Science.gov (United States)

    Frazier, Christopher B; Ludwig, Timothy D; Whitaker, Brian; Roberts, D Steve

    2013-06-01

    Recent reviews of safety culture measures have revealed a host of potential factors that could make up a safety culture (Flin, Mearns, O'Connor, & Bryden, 2000; Guldenmund, 2000). However, there is still little consensus regarding what the core factors of safety culture are. The purpose of the current research was to determine the core factors, as well as the structure of those factors that make up a safety culture, and establish which factors add meaningful value by factor analyzing a widely used safety culture survey. A 92-item survey was constructed by subject matter experts and was administered to 25,574 workers across five multi-national organizations in five different industries. Exploratory and hierarchical confirmatory factor analyses were conducted revealing four second-order factors of a Safety Culture consisting of Management Concern, Personal Responsibility for Safety, Peer Support for Safety, and Safety Management Systems. Additionally, a total of 12 first-order factors were found: three on Management Concern, three on Personal Responsibility, two on Peer Support, and four on Safety Management Systems. The resulting safety culture model addresses gaps in the literature by indentifying the core constructs which make up a safety culture. This clarification of the major factors emerging in the measurement of safety cultures should impact the industry through a more accurate description, measurement, and tracking of safety cultures to reduce loss due to injury. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

  1. Confirmatory factor analysis reveals a latent cognitive structure common to bipolar disorder, schizophrenia, and normal controls.

    Science.gov (United States)

    Schretlen, David J; Peña, Javier; Aretouli, Eleni; Orue, Izaskun; Cascella, Nicola G; Pearlson, Godfrey D; Ojeda, Natalia

    2013-06-01

    We sought to determine whether a single hypothesized latent factor structure would characterize cognitive functioning in three distinct groups. We assessed 576 adults (340 community controls, 126 adults with bipolar disorder, and 110 adults with schizophrenia) using 15 measures derived from nine cognitive tests. Confirmatory factor analysis (CFA) was conducted to examine the fit of a hypothesized six-factor model. The hypothesized factors included attention, psychomotor speed, verbal memory, visual memory, ideational fluency, and executive functioning. The six-factor model provided an excellent fit for all three groups [for community controls, root mean square error of approximation (RMSEA) schizophrenia, RMSEA = 0.06 and CFI = 0.98]. Alternate models that combined fluency with processing speed or verbal and visual memory reduced the goodness of fit. Multi-group CFA results supported factor invariance across the three groups. Confirmatory factor analysis supported a single six-factor structure of cognitive functioning among patients with schizophrenia or bipolar disorder and community controls. While the three groups clearly differ in level of performance, they share a common underlying architecture of information processing abilities. These cognitive factors could provide useful targets for clinical trials of treatments that aim to enhance information processing in persons with neurological and neuropsychiatric disorders. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. Towards automatic analysis of dynamic radionuclide studies using principal-components factor analysis

    International Nuclear Information System (INIS)

    Nigran, K.S.; Barber, D.C.

    1985-01-01

    A method is proposed for automatic analysis of dynamic radionuclide studies using the mathematical technique of principal-components factor analysis. This method is considered as a possible alternative to the conventional manual regions-of-interest method widely used. The method emphasises the importance of introducing a priori information into the analysis about the physiology of at least one of the functional structures in a study. Information is added by using suitable mathematical models to describe the underlying physiological processes. A single physiological factor is extracted representing the particular dynamic structure of interest. Two spaces 'study space, S' and 'theory space, T' are defined in the formation of the concept of intersection of spaces. A one-dimensional intersection space is computed. An example from a dynamic 99 Tcsup(m) DTPA kidney study is used to demonstrate the principle inherent in the method proposed. The method requires no correction for the blood background activity, necessary when processing by the manual method. The careful isolation of the kidney by means of region of interest is not required. The method is therefore less prone to operator influence and can be automated. (author)

  3. Comprehensive Behavioral Analysis of Activating Transcription Factor 5-Deficient Mice

    Directory of Open Access Journals (Sweden)

    Mariko Umemura

    2017-07-01

    Full Text Available Activating transcription factor 5 (ATF5 is a member of the CREB/ATF family of basic leucine zipper transcription factors. We previously reported that ATF5-deficient (ATF5-/- mice demonstrated abnormal olfactory bulb development due to impaired interneuron supply. Furthermore, ATF5-/- mice were less aggressive than ATF5+/+ mice. Although ATF5 is widely expressed in the brain, and involved in the regulation of proliferation and development of neurons, the physiological role of ATF5 in the higher brain remains unknown. Our objective was to investigate the physiological role of ATF5 in the higher brain. We performed a comprehensive behavioral analysis using ATF5-/- mice and wild type littermates. ATF5-/- mice exhibited abnormal locomotor activity in the open field test. They also exhibited abnormal anxiety-like behavior in the light/dark transition test and open field test. Furthermore, ATF5-/- mice displayed reduced social interaction in the Crawley’s social interaction test and increased pain sensitivity in the hot plate test compared with wild type. Finally, behavioral flexibility was reduced in the T-maze test in ATF5-/- mice compared with wild type. In addition, we demonstrated that ATF5-/- mice display disturbances of monoamine neurotransmitter levels in several brain regions. These results indicate that ATF5 deficiency elicits abnormal behaviors and the disturbance of monoamine neurotransmitter levels in the brain. The behavioral abnormalities of ATF5-/- mice may be due to the disturbance of monoamine levels. Taken together, these findings suggest that ATF5-/- mice may be a unique animal model of some psychiatric disorders.

  4. Students' motivation to study dentistry in Malaysia: an analysis using confirmatory factor analysis.

    Science.gov (United States)

    Musa, Muhd Firdaus Che; Bernabé, Eduardo; Gallagher, Jennifer E

    2015-06-12

    Malaysia has experienced a significant expansion of dental schools over the past decade. Research into students' motivation may inform recruitment and retention of the future dental workforce. The objectives of this study were to explore students' motivation to study dentistry and whether that motivation varied by students' and school characteristics. All 530 final-year students in 11 dental schools (6 public and 5 private) in Malaysia were invited to participate at the end of 2013. The self-administered questionnaire, developed at King's College London, collected information on students' motivation to study dentistry and demographic background. Responses on students' motivation were collected using five-point ordinal scales. Confirmatory factor analysis (CFA) was used to evaluate the underlying structure of students' motivation to study dentistry. Multivariate analysis of variance (MANOVA) was used to compare factor scores for overall motivation and sub-domains by students' and school characteristics. Three hundred and fifty-six final-year students in eight schools (all public and two private) participated in the survey, representing an 83% response rate for these schools and 67% of all final-year students nationally. The majority of participants were 24 years old (47%), female (70%), Malay (56%) and from middle-income families (41%) and public schools (78%). CFA supported a model with five first-order factors (professional job, healthcare and people, academic, careers advising and family and friends) which were linked to a single second-order factor representing overall students' motivation. Academic factors and healthcare and people had the highest standardized factor loadings (0.90 and 0.71, respectively), suggesting they were the main motivation to study dentistry. MANOVA showed that students from private schools had higher scores for healthcare and people than those in public schools whereas Malay students had lower scores for family and friends than those

  5. Clinicopathological Analysis of Factors Related to Colorectal Tumor Perforation

    OpenAIRE

    Medina-Arana, Vicente; Martínez-Riera, Antonio; Delgado-Plasencia, Luciano; Rodríguez-González, Diana; Bravo-Gutiérrez, Alberto; Álvarez-Argüelles, Hugo; Alarcó-Hernández, Antonio; Salido-Ruiz, Eduardo; Fernández-Peralta, Antonia M.; González-Aguilera, Juan J.

    2015-01-01

    Abstract Colorectal tumor perforation is a life-threatening complication of this disease. However, little is known about the anatomopathological factors or pathophysiologic mechanisms involved. Pathological and immunohistochemical analysis of factors related with tumoral neo-angiogenesis, which could influence tumor perforation are assessed in this study. A retrospective study of patients with perforated colon tumors (Group P) and T4a nonperforated (controls) was conducted between 2001 and 20...

  6. Analysis of Key Factors Driving Japan’s Military Normalization

    Science.gov (United States)

    2017-09-01

    no change to our policy of not giving in to terrorism.”40 Though the prime minister was democratically supported, Koizumi’s leadership style took...of the key driving factors of Japan’s normalization. The areas of prime ministerial leadership , regional security threats, alliance issues, and...analysis of the key driving factors of Japan’s normalization. The areas of prime ministerial leadership , regional security threats, alliance issues, and

  7. Analysis of uncertainty in modeling perceived risks

    International Nuclear Information System (INIS)

    Melnyk, R.; Sandquist, G.M.

    2005-01-01

    Expanding on a mathematical model developed for quantifying and assessing perceived risks, the distribution functions, variances, and uncertainties associated with estimating the model parameters are quantified. The analytical model permits the identification and assignment of any number of quantifiable risk perception factors that can be incorporated within standard risk methodology. Those risk perception factors associated with major technical issues are modeled using lognormal probability density functions to span the potentially large uncertainty variations associated with these risk perceptions. The model quantifies the logic of public risk perception and provides an effective means for measuring and responding to perceived risks. (authors)

  8. Factor analysis of the contextual fine motor questionnaire in children.

    Science.gov (United States)

    Lin, Chin-Kai; Meng, Ling-Fu; Yu, Ya-Wen; Chen, Che-Kuo; Li, Kuan-Hua

    2014-02-01

    Most studies treat fine motor as one subscale in a developmental test, hence, further factor analysis of fine motor has not been conducted. In fact, fine motor has been treated as a multi-dimensional domain from both clinical and theoretical perspectives, and therefore to know its factors would be valuable. The aim of this study is to analyze the internal consistency and factor validity of the Contextual Fine Motor Questionnaire (CFMQ). Based on the ecological observation and literature, the Contextual Fine Motor Questionnaire (CFMQ) was developed and includes 5 subscales: Pen Control, Tool Use During Handicraft Activities, the Use of Dining Utensils, Connecting and Separating during Dressing and Undressing, and Opening Containers. The main purpose of this study is to establish the factorial validity of the CFMQ through conducting this factor analysis study. Among 1208 questionnaires, 904 were successfully completed. Data from the children's CFMQ submitted by primary care providers was analyzed, including 485 females (53.6%) and 419 males (46.4%) from grades 1 to 5, ranging in age from 82 to 167 months (M=113.9, SD=16.3). Cronbach's alpha was used to measure internal consistency and explorative factor analysis was applied to test the five factor structures within the CFMQ. Results showed that Cronbach's alpha coefficient of the CFMQ for 5 subscales ranged from .77 to .92 and all item-total correlations with corresponding subscales were larger than .4 except one item. The factor loading of almost all items classified to their factor was larger than .5 except 3 items. There were five factors, explaining a total of 62.59% variance for the CFMQ. In conclusion, the remaining 24 items in the 5 subscales of the CFMQ had appropriate internal consistency, test-retest reliability and construct validity. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. Evaluation of the Thermodynamic Models for the Thermal Diffusion Factor

    DEFF Research Database (Denmark)

    Gonzalez-Bagnoli, Mariana G.; Shapiro, Alexander; Stenby, Erling Halfdan

    2003-01-01

    Over the years, several thermodynamic models for the thermal diffusion factors for binary mixtures have been proposed. The goal of this paper is to test some of these models in combination with different equations of state. We tested the following models: those proposed by Rutherford and Drickamer...... we applied different thermodynamic models, such as the Soave-Redlich-Kwong and the Peng-Robinson equations of state. The necessity to try different thermo-dynamic models is caused by the high sensitivity of the thermal diffusion factors to the values of the partial molar properties. Two different...... corrections for the determination of the partial molar volumes have been implemented; the Peneloux correction and the correction based on the principle of corresponding states....

  10. Uncovering Transcriptional Regulatory Networks by Sparse Bayesian Factor Model

    Directory of Open Access Journals (Sweden)

    Qi Yuan(Alan

    2010-01-01

    Full Text Available Abstract The problem of uncovering transcriptional regulation by transcription factors (TFs based on microarray data is considered. A novel Bayesian sparse correlated rectified factor model (BSCRFM is proposed that models the unknown TF protein level activity, the correlated regulations between TFs, and the sparse nature of TF-regulated genes. The model admits prior knowledge from existing database regarding TF-regulated target genes based on a sparse prior and through a developed Gibbs sampling algorithm, a context-specific transcriptional regulatory network specific to the experimental condition of the microarray data can be obtained. The proposed model and the Gibbs sampling algorithm were evaluated on the simulated systems, and results demonstrated the validity and effectiveness of the proposed approach. The proposed model was then applied to the breast cancer microarray data of patients with Estrogen Receptor positive ( status and Estrogen Receptor negative ( status, respectively.

  11. Supplementary Material for: Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel; Huser, Raphaë l; Genton, Marc G.

    2016-01-01

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  12. Using Factor Analysis to Identify Topic Preferences Within MBA Courses

    Directory of Open Access Journals (Sweden)

    Earl Chrysler

    2003-02-01

    Full Text Available This study demonstrates the role of a principal components factor analysis in conducting a gap analysis as to the desired characteristics of business alumni. Typically, gap analyses merely compare the emphases that should be given to areas of inquiry with perceptions of actual emphases. As a result, the focus is upon depth of coverage. A neglected area in need of investigation is the breadth of topic dimensions and their differences between the normative (should offer and the descriptive (actually offer. The implications of factor structures, as well as traditional gap analyses, are developed and discussed in the context of outcomes assessment.

  13. An Analysis of the Factors Impacting Employee's Specific Investment

    Institute of Scientific and Technical Information of China (English)

    WU Ai-hua; GE Wen-lei

    2008-01-01

    The amount of specific investment from employees is limited, and the reasons of the under-investment from employees are analyzed in this paper. Based on the relationship of the specific investment and the employee demission, an empirical study has been conducted focusing on the factors influencing the employee turnover and the specific investment. A theoretical model of the factors influencing employee's specific investment is given.

  14. Analysis of IFR driver fuel hot channel factors

    International Nuclear Information System (INIS)

    Ku, J.Y.; Chang, L.K.; Mohr, D.

    1994-01-01

    Thermal-hydraulic uncertainty factors for Integral Fast Reactor (IFR) driver fuels have been determined based primarily on the database obtained from the predecessor fuels used in the IFR prototype, Experimental Breeder Reactor II. The uncertainty factors were applied to the channel factors (HCFs) analyses to obtain separate overall HCFs for fuel and cladding for steady-state analyses. A ''semistatistical horizontal method'' was used in the HCFs analyses. The uncertainty factor of the fuel thermal conductivity dominates the effects considered in the HCFs analysis; the uncertainty in fuel thermal conductivity will be reduced as more data are obtained to expand the currently limited database for the IFR ternary metal fuel (U-20Pu-10Zr). A set of uncertainty factors to be used for transient analyses has also been derived

  15. Interactive analysis of human error factors in NPP operation events

    International Nuclear Information System (INIS)

    Zhang Li; Zou Yanhua; Huang Weigang

    2010-01-01

    Interactive of human error factors in NPP operation events were introduced, and 645 WANO operation event reports from 1999 to 2008 were analyzed, among which 432 were found relative to human errors. After classifying these errors with the Root Causes or Causal Factors, and then applying SPSS for correlation analysis,we concluded: (1) Personnel work practices are restricted by many factors. Forming a good personnel work practices is a systematic work which need supports in many aspects. (2)Verbal communications,personnel work practices, man-machine interface and written procedures and documents play great roles. They are four interaction factors which often come in bundle. If some improvements need to be made on one of them,synchronous measures are also necessary for the others.(3) Management direction and decision process, which are related to management,have a significant interaction with personnel factors. (authors)

  16. Analysis of IFR driver fuel hot channel factors

    International Nuclear Information System (INIS)

    Ku, J.Y.; Chang, L.K.; Mohr, D.

    2004-01-01

    Thermal-hydraulic uncertainty factors for Integral Fast Reactor (IFR) driver fuels have been determined based primarily on the database obtained from the predecessor fuels used in the IFR prototype. Experimental Breeder Reactor II. The uncertainty factors were applied to the hot channel factors (HCFs) analyses to obtain separate overall HCFs for fuel and cladding for steady-state analyses. A 'semistatistical horizontal method' was used in the HCFs analyses. The uncertainty factor of the fuel thermal conductivity dominates the effects considered in the HCFs analysis; the uncertainty in fuel thermal conductivity will be reduced as more data are obtained to expand the currently limited database for the IFR ternary metal fuel (U-20Pu-10Zr). A set of uncertainty factors to be used for transient analyses has also been derived. (author)

  17. Model calculation of the scanned field enhancement factor of CNTs

    International Nuclear Information System (INIS)

    Ahmad, Amir; Tripathi, V K

    2006-01-01

    The field enhancement factor of a carbon nanotube (CNT) placed in a cluster of CNTs is smaller than an isolated CNT because the electric field on one tube is screened by neighbouring tubes. This screening depends on the length of the CNTs and the spacing between them. We have derived an expression to compute the field enhancement factor of CNTs under any positional distribution of CNTs using a model of a floating sphere between parallel anode and cathode plates. Using this expression we can compute the field enhancement factor of a CNT in a cluster (non-uniformly distributed CNTs). This expression is used to compute the field enhancement factor of a CNT in an array (uniformly distributed CNTs). Comparison has been shown with experimental results and existing models

  18. HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

    Science.gov (United States)

    Fan, Jianqing; Liao, Yuan; Mincheva, Martina

    2011-01-01

    The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.

  19. Ranking insurance firms using AHP and Factor Analysis

    Directory of Open Access Journals (Sweden)

    Mohammad Khodaei Valahzaghard

    2013-03-01

    Full Text Available Insurance industry includes a significant part of economy and it is important to learn more about the capabilities of different firms, which are active in this industry. In this paper, we present an empirical study to rank the insurance firms using analytical hierarchy process as well as factor analysis. The study considers four criteria including capital adequacy, quality of earning, quality of cash flow and quality of firms’ assets. The results of the implementation of factor analysis (FA have been verified using Kaiser-Meyer-Olkin (KMO=0.573 and Bartlett's Chi-Square (443.267 P-value=0.000 tests. According to the results FA, the first important factor, capital adequacy, represents 21.557% of total variance, the second factor, quality of income, represents 20.958% of total variance. In addition, the third factor, quality of cash flow, represents 19.417% of total variance and the last factor, quality of assets, represents 18.641% of total variance. The study has also used analytical hierarchy process (AHP to rank insurance firms. The results of our survey indicate that capital adequacy (0.559 is accounted as the most important factor followed by quality of income (0.235, quality of cash flow (0.144 and quality of assets (0.061. The results of AHP are consistent with the results of FA, which somewhat validates the overall study.

  20. A factor analysis to find critical success factors in retail brand

    Directory of Open Access Journals (Sweden)

    Naser Azad

    2013-03-01

    Full Text Available The present exploratory study aims to find critical components of retail brand among some retail stores. The study seeks to build a brand name in retail level and looks to find important factors affecting it. Customer behavior is largely influenced when the first retail customer experience is formed. These factors have direct impacts on customer experience and satisfaction in retail industry. The proposed study performs an empirical investigation on two well-known retain stores located in city of Tehran, Iran. Using a sample of 265 people from regular customers, the study uses factor analysis and extracts four main factors including related brand, product benefits, customer welfare strategy and corporate profits using the existing 31 factors in the literature.

  1. The five-factor model in schizotypal personality disorder

    OpenAIRE

    Gurrera, Ronald J.; Dickey, Chandlee C.; Niznikiewicz, Margaret A.; Voglmaier, Martina M.; Shenton, Martha E.; McCarley, Robert W.

    2005-01-01

    Studies of the five-factor model of personality in schizotypal personality disorder (SPD) have produced inconsistent results, particularly with respect to openness. In the present study, the NEO-FFI was used to measure five-factor personality dimensions in 28 community volunteers with SPD and 24 psychiatrically healthy individuals. Standard multivariate statistical analyses were used to evaluate personality differences as a function of diagnosis and gender. Individuals with SPD had significan...

  2. Consumer's Online Shopping Influence Factors and Decision-Making Model

    Science.gov (United States)

    Yan, Xiangbin; Dai, Shiliang

    Previous research on online consumer behavior has mostly been confined to the perceived risk which is used to explain those barriers for purchasing online. However, perceived benefit is another important factor which influences consumers’ decision when shopping online. As a result, an integrated consumer online shopping decision-making model is developed which contains three elements—Consumer, Product, and Web Site. This model proposed relative factors which influence the consumers’ intention during the online shopping progress, and divided them into two different dimensions—mentally level and material level. We tested those factors with surveys, from both online volunteers and offline paper surveys with more than 200 samples. With the help of SEM, the experimental results show that the proposed model and method can be used to analyze consumer’s online shopping decision-making process effectively.

  3. Integrated traffic conflict model for estimating crash modification factors.

    Science.gov (United States)

    Shahdah, Usama; Saccomanno, Frank; Persaud, Bhagwant

    2014-10-01

    Crash modification factors (CMFs) for road safety treatments are usually obtained through observational models based on reported crashes. Observational Bayesian before-and-after methods have been applied to obtain more precise estimates of CMFs by accounting for the regression-to-the-mean bias inherent in naive methods. However, sufficient crash data reported over an extended period of time are needed to provide reliable estimates of treatment effects, a requirement that can be a challenge for certain types of treatment. In addition, these studies require that sites analyzed actually receive the treatment to which the CMF pertains. Another key issue with observational approaches is that they are not causal in nature, and as such, cannot provide a sound "behavioral" rationale for the treatment effect. Surrogate safety measures based on high risk vehicle interactions and traffic conflicts have been proposed to address this issue by providing a more "causal perspective" on lack of safety for different road and traffic conditions. The traffic conflict approach has been criticized, however, for lacking a formal link to observed and verified crashes, a difficulty that this paper attempts to resolve by presenting and investigating an alternative approach for estimating CMFs using simulated conflicts that are linked formally to observed crashes. The integrated CMF estimates are compared to estimates from an empirical Bayes (EB) crash-based before-and-after analysis for the same sample of treatment sites. The treatment considered involves changing left turn signal priority at Toronto signalized intersections from permissive to protected-permissive. The results are promising in that the proposed integrated method yields CMFs that closely match those obtained from the crash-based EB before-and-after analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Personality disorders in substance abusers: Validation of the DIP-Q through principal components factor analysis and canonical correlation analysis

    Directory of Open Access Journals (Sweden)

    Hesse Morten

    2005-05-01

    Full Text Available Abstract Background Personality disorders are common in substance abusers. Self-report questionnaires that can aid in the assessment of personality disorders are commonly used in assessment, but are rarely validated. Methods The Danish DIP-Q as a measure of co-morbid personality disorders in substance abusers was validated through principal components factor analysis and canonical correlation analysis. A 4 components structure was constructed based on 238 protocols, representing antagonism, neuroticism, introversion and conscientiousness. The structure was compared with (a a 4-factor solution from the DIP-Q in a sample of Swedish drug and alcohol abusers (N = 133, and (b a consensus 4-components solution based on a meta-analysis of published correlation matrices of dimensional personality disorder scales. Results It was found that the 4-factor model of personality was congruent across the Danish and Swedish samples, and showed good congruence with the consensus model. A canonical correlation analysis was conducted on a subset of the Danish sample with staff ratings of pathology. Three factors that correlated highly between the two variable sets were found. These variables were highly similar to the three first factors from the principal components analysis, antagonism, neuroticism and introversion. Conclusion The findings support the validity of the DIP-Q as a measure of DSM-IV personality disorders in substance abusers.

  5. A rough multi-factor model of electricity spot prices

    International Nuclear Information System (INIS)

    Bennedsen, Mikkel

    2017-01-01

    We introduce a new continuous-time mathematical model of electricity spot prices which accounts for the most important stylized facts of these time series: seasonality, spikes, stochastic volatility, and mean reversion. Empirical studies have found a possible fifth stylized fact, roughness, and our approach explicitly incorporates this into the model of the prices. Our setup generalizes the popular Ornstein–Uhlenbeck-based multi-factor framework of and allows us to perform statistical tests to distinguish between an Ornstein–Uhlenbeck-based model and a rough model. Further, through the multi-factor approach we account for seasonality and spikes before estimating – and making inference on – the degree of roughness. This is novel in the literature and we present simulation evidence showing that these precautions are crucial for accurate estimation. Lastly, we estimate our model on recent data from six European energy exchanges and find statistical evidence of roughness in five out of six markets. As an application of our model, we show how, in these five markets, a rough component improves short term forecasting of the prices. - Highlights: • Statistical modeling of electricity spot prices • Multi-factor decomposition • Roughness • Electricity price forecasting

  6. Aircraft vulnerability analysis by modelling and simulation

    CSIR Research Space (South Africa)

    Willers, CJ

    2014-09-01

    Full Text Available attributable to misuse of the weapon or to missile performance restrictions. This paper analyses some of the factors affecting aircraft vulnerability and demonstrates a structured analysis of the risk and aircraft vulnerability problem. The aircraft...

  7. Multinomial Response Models, for Modeling and Determining Important Factors in Different Contraceptive Methods in Women

    Directory of Open Access Journals (Sweden)

    E Haji Nejad

    2001-06-01

    Full Text Available Difference aspects of multinomial statistical modelings and its classifications has been studied so far. In these type of problems Y is the qualitative random variable with T possible states which are considered as classifications. The goal is prediction of Y based on a random Vector X ? IR^m. Many methods for analyzing these problems were considered. One of the modern and general method of classification is Classification and Regression Trees (CART. Another method is recursive partitioning techniques which has a strange relationship with nonparametric regression. Classical discriminant analysis is a standard method for analyzing these type of data. Flexible discriminant analysis method which is a combination of nonparametric regression and discriminant analysis and classification using spline that includes least square regression and additive cubic splines. Neural network is an advanced statistical method for analyzing these types of data. In this paper properties of multinomial logistics regression were investigated and this method was used for modeling effective factors in selecting contraceptive methods in Ghom province for married women age 15-49. The response variable has a tetranomial distibution. The levels of this variable are: nothing, pills, traditional and a collection of other contraceptive methods. A collection of significant independent variables were: place, age of women, education, history of pregnancy and family size. Menstruation age and age at marriage were not statistically significant.

  8. Incorporation of human factors into ship collision risk models focusing on human centred design aspects

    International Nuclear Information System (INIS)

    Sotiralis, P.; Ventikos, N.P.; Hamann, R.; Golyshev, P.; Teixeira, A.P.

    2016-01-01

    This paper presents an approach that more adequately incorporates human factor considerations into quantitative risk analysis of ship operation. The focus is on the collision accident category, which is one of the main risk contributors in ship operation. The approach is based on the development of a Bayesian Network (BN) model that integrates elements from the Technique for Retrospective and Predictive Analysis of Cognitive Errors (TRACEr) and focuses on the calculation of the collision accident probability due to human error. The model takes into account the human performance in normal, abnormal and critical operational conditions and implements specific tasks derived from the analysis of the task errors leading to the collision accident category. A sensitivity analysis is performed to identify the most important contributors to human performance and ship collision. Finally, the model developed is applied to assess the collision risk of a feeder operating in Dover strait using the collision probability estimated by the developed BN model and an Event tree model for calculation of human, economic and environmental risks. - Highlights: • A collision risk model for the incorporation of human factors into quantitative risk analysis is proposed. • The model takes into account the human performance in different operational conditions leading to the collision. • The most important contributors to human performance and ship collision are identified. • The model developed is applied to assess the collision risk of a feeder operating in Dover strait.

  9. Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

    Science.gov (United States)

    Abumeri, Galib H.; Chamis, Christos C.

    2010-01-01

    Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required

  10. Dynamic Multi-Factor Credit Risk Model with Fat-Tailed Factors

    Czech Academy of Sciences Publication Activity Database

    Gapko, Petr; Šmíd, Martin

    2012-01-01

    Roč. 62, č. 2 (2012), s. 125-140 ISSN 0015-1920 R&D Projects: GA ČR GD402/09/H045; GA ČR GA402/09/0965 Grant - others:Univerzita Karlova(CZ) GAUK 46108 Institutional research plan: CEZ:AV0Z10750506 Keywords : credit risk * probability of default * loss given default * credit loss * credit loss distribution * Basel II Subject RIV: AH - Economics Impact factor: 0.340, year: 2012 http://library.utia.cas.cz/separaty/2012/E/smid-dynamic multi-factor credit risk model with fat-tailed factors.pdf

  11. Statistical Modelling of Wind Proles - Data Analysis and Modelling

    DEFF Research Database (Denmark)

    Jónsson, Tryggvi; Pinson, Pierre

    The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....

  12. Reception in Chile of the United Nations Commission on International Trade Law Model Law on Cross-Border Insolvency: Brief analysis of the center of main interests of the debtor as a new connecting factor

    Directory of Open Access Journals (Sweden)

    Jeremy Daniel Levy Morchio

    2015-12-01

    Full Text Available This article analyze the United Nations Commission on International Trade Law (UNCITRAL Model Law on Cross-border Insolvency and its incorporation into national law by means of the entry into force of the new Law of Insolvency and Re-entrepreneurship, paying special attention to the concept of center of main interests of the debtor, as a new factor of connection between jurisdictions. For this, we will begin with the situation of cross-border insolvency in Chile prior to the new law, will analyze the origin, structure and objectives of the model law and the way in which was introduced in Chile, to finally study the concept of center of main interests of the debtor.

  13. Cancer risk factors in Korean news media: a content analysis.

    Science.gov (United States)

    Kye, Su Yeon; Kwon, Jeong Hyun; Kim, Yong-Chan; Shim, Minsun; Kim, Jee Hyun; Cho, Hyunsoon; Jung, Kyu Won; Park, Keeho

    2015-01-01

    Little is known about the news coverage of cancer risk factors in Korea. This study aimed to examine how the news media encompasses a wide array of content regarding cancer risk factors and related cancer sites, and investigate whether news coverage of cancer risk factors is congruent with the actual prevalence of the disease. A content analysis was conducted on 1,138 news stories covered during a 5-year period between 2008 and 2012. The news stories were selected from nationally representative media in Korea. Information was collected about cancer risk factors and cancer sites. Of various cancer risk factors, occupational and environmental exposures appeared most frequently in the news. Breast cancer was mentioned the most in relation to cancer sites. Breast, cervical, prostate, and skin cancer were overrepresented in the media in comparison to incidence and mortality cases, whereas lung, thyroid, liver, and stomach cancer were underrepresented. To our knowledge, this research is the first investigation dealing with news coverage about cancer risk factors in Korea. The study findings show occupational and environmental exposures are emphasized more than personal lifestyle factors; further, more prevalent cancers in developed countries have greater media coverage, not reflecting the realities of the disease. The findings may help health journalists and other health storytellers to develop effective ways to communicate cancer risk factors.

  14. Landslides geotechnical analysis. Qualitative assessment by valuation factors

    Science.gov (United States)

    Cuanalo Oscar, Sc D.; Oliva Aldo, Sc D.; Polanco Gabriel, M. E.

    2012-04-01

    In general, a landslide can cause a disaster when it is combined a number of factors such as an extreme event related to a geological phenomenon, vulnerable elements exposed in a specific geographic area, and the probability of loss and damage evaluated in terms of lives and economic assets, in a certain period of time. This paper presents the qualitative evaluation of slope stability through of Valuation Factors, obtained from the characterization of the determinants and triggers factors that influence the instability; for the first the morphology and topography, geology, soil mechanics, hydrogeology and vegetation to the second, the rain, earthquakes, erosion and scour, human activity, and ultimately dependent factors of the stability analysis, and its influence ranges which greatly facilitate the selection of construction processes best suited to improve the behavior of a slope or hillside. The Valuation Factors are a set of parameters for assessing the influence of conditioning and triggering factors that influence the stability of slopes and hillsides. The characteristics of each factor must be properly categorized to involve its effect on behavior; a way to do this is by assigning a weighted value range indicating its effect on the stability of a slope. It is proposed to use Valuation Factors with weighted values between 0 and 1 (arbitrarily selected but common sense and logic), the first corresponds to no or minimal effect on stability (no effect or very little influence) and the second, the greatest impact on it (has a significant influence). The meddle effects are evaluated with intermediate values.

  15. Critical success factors model developing for sustainable Kaizen implementation in manufactur-ing industry in Ethiopia

    Directory of Open Access Journals (Sweden)

    Haftu Hailu

    2017-12-01

    Full Text Available The purpose of the research is to identify critical success factors and model developing for sustaining kaizen implementation. Peacock shoe is one of the manufacturing industries in Ethiopia facing challenges on sustaining. The methodology followed is factor analysis and empirically testing hypothesis. A database was designed using SPSS version 20. The survey was validated using statistical validation using the Cronbach alpha index; the result is 0.908. The KMO index value was obtained for the 32 items and had a value of 0.642 with Bartlett's Test of Sphericity Approx. Chi-Square 4503.007, degree of freedom 496 and significance value 0.000. A factor analysis by principal components and varimax rotation was applied for finding the critical success factors. Finding designates that 32 items were merged into eight critical success factors. All the eight factors together explain for 76.941 % of the variance. Multiple regression model analysis has indicated that some of the critical success factors had relationship with success indicators. Due to constraint of time, the researcher focused only at peacock shoe manufacturing industry. Other limitation also includes the absence of any local research that shows the critical success factors at the moment.

  16. Theoretical Assessment of the Impact of Climatic Factors in a Vibrio Cholerae Model.

    Science.gov (United States)

    Kolaye, G; Damakoa, I; Bowong, S; Houe, R; Békollè, D

    2018-05-04

    A mathematical model for Vibrio Cholerae (V. Cholerae) in a closed environment is considered, with the aim of investigating the impact of climatic factors which exerts a direct influence on the bacterial metabolism and on the bacterial reservoir capacity. We first propose a V. Cholerae mathematical model in a closed environment. A sensitivity analysis using the eFast method was performed to show the most important parameters of the model. After, we extend this V. cholerae model by taking account climatic factors that influence the bacterial reservoir capacity. We present the theoretical analysis of the model. More precisely, we compute equilibria and study their stabilities. The stability of equilibria was investigated using the theory of periodic cooperative systems with a concave nonlinearity. Theoretical results are supported by numerical simulations which further suggest the necessity to implement sanitation campaigns of aquatic environments by using suitable products against the bacteria during the periods of growth of aquatic reservoirs.

  17. Variance-based sensitivity analysis for wastewater treatment plant modelling.

    Science.gov (United States)

    Cosenza, Alida; Mannina, Giorgio; Vanrolleghem, Peter A; Neumann, Marc B

    2014-02-01

    Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes. © 2013.

  18. Development of interpretation models for PFN uranium log analysis

    International Nuclear Information System (INIS)

    Barnard, R.W.

    1980-11-01

    This report presents the models for interpretation of borehole logs for the PFN (Prompt Fission Neutron) uranium logging system. Two models have been developed, the counts-ratio model and the counts/dieaway model. Both are empirically developed, but can be related to the theoretical bases for PFN analysis. The models try to correct for the effects of external factors (such as probe or formation parameters) in the calculation of uranium grade. The theoretical bases and calculational techniques for estimating uranium concentration from raw PFN data and other parameters are discussed. Examples and discussions of borehole logs are included

  19. Salivary SPECT and factor analysis in Sjoegren's syndrome

    International Nuclear Information System (INIS)

    Nakamura, T.; Oshiumi, Y.; Yonetsu, K.; Muranaka, T.; Sakai, K.; Kanda, S.; National Fukuoka Central Hospital

    1991-01-01

    Salivary SPECT and factor analysis in Sjoegren's syndrome were performed in 17 patients and 6 volunteers as controls. The ability of SPECT to detect small differences in the level of uptake can be used to separate glands from background even when uptake is reduced as in the patients with Sjoegren's syndrome. In control and probable Sjoegren's syndrome groups the uptake ratio of the submandibular gland to parotid gland on salivary SPECT (S/P ratio) was less than 1.0. However, in the definite Sjoergren's syndrome group, the ratio was more than 1.0. Moreover, the ratio in all patients with sialectasia, which is characteristic of Sjoegren's syndrome, was more than 1.0. Salivary factor analysis of normal parotid glands showed slowly increasing patterns of uptake and normal submandibular glands had rapidly increasing patterns of uptake. However, in the definite Sjoegren's syndrome group, the factor analysis patterns were altered, with slowly increasing patterns dominating both in the parotid and submandibular glands. These results suggest that the S/P ratio in salivary SPECT and salivary factor analysis provide additional radiologic criteria in diagnosing Sjoegren's syndrome. (orig.)

  20. Genomewide analysis of TCP transcription factor gene family in ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Genetics; Volume 93; Issue 3. Genomewide ... Teosinte branched1/cycloidea/proliferating cell factor1 (TCP) proteins are a large family of transcriptional regulators in angiosperms. They are ... To the best of our knowledge, this is the first study of a genomewide analysis of apple TCP gene family.