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...
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)
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.
Identifying the important factors in simulation models with many factors
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
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...
Sparse and Robust Factor Modelling
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
Skewed factor models using selection mechanisms
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.
Skewed factor models using selection mechanisms
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.
Modeling Ability Differentiation in the Second-Order Factor Model
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,…
Comparison of Transcription Factor Binding Site Models
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.
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.
Linear factor copula models and their properties
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.
Linear factor copula models and their properties
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.
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...
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...
The asset pricing model of musharakah factors
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.
Factor Copula Models for Replicated Spatial Data
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.
Factor Copula Models for Replicated Spatial Data
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.
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...
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
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
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)
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
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
Model of a ternary complex between activated factor VII, tissue factor and factor IX.
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.
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%.
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.
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...
Cloud Computing Adoption Business Model Factors: Does Enterprise Size Matter?
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...
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
Modelling of Supercapacitors: Factors Influencing Performance
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....
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.
Hierarchical and coupling model of factors influencing vessel traffic flow.
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.
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.
Modeling global scene factors in attention
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
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....
[Lake eutrophication modeling in considering climatic factors change: a review].
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.
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
An alternative method for centrifugal compressor loading factor modelling
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.
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.
Functional dynamic factor models with application to yield curve forecasting
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
Human Modeling for Ground Processing Human Factors Engineering Analysis
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
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.
Quantifying credit portfolio losses under multi-factor models
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
Rethinking "Harmonious Parenting" Using a Three-Factor Discipline Model
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…
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
Is There Really a Global Business Cycle? : A Dynamic Factor Model with Stochastic Factor Selection
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
Testing alternative factor models of PTSD and the robustness of the dysphoria factor.
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
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...
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 ...
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.
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
Factor copula models for data with spatio-temporal dependence
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.
Factor copula models for data with spatio-temporal dependence
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.
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....
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.
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.
Supplementary Material for: Factor Copula Models for Replicated Spatial Data
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.
A 3-factor model for the FACIT-Sp.
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
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
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.
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.
The five-factor model in schizotypal personality disorder
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...
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.
Consumer's Online Shopping Influence Factors and Decision-Making Model
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.
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
Functional dynamic factor models with application to yield curve forecasting
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.
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.
Probabilistic Multi-Factor Interaction Model for Complex Material Behavior
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
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
The structure of musical preferences: a five-factor model.
Rentfrow, Peter J; Goldberg, Lewis R; Levitin, Daniel J
2011-06-01
Music is a cross-cultural universal, a ubiquitous activity found in every known human culture. Individuals demonstrate manifestly different preferences in music, and yet relatively little is known about the underlying structure of those preferences. Here, we introduce a model of musical preferences based on listeners' affective reactions to excerpts of music from a wide variety of musical genres. The findings from 3 independent studies converged to suggest that there exists a latent 5-factor structure underlying music preferences that is genre free and reflects primarily emotional/affective responses to music. We have interpreted and labeled these factors as (a) a Mellow factor comprising smooth and relaxing styles; (b) an Unpretentious factor comprising a variety of different styles of sincere and rootsy music such as is often found in country and singer-songwriter genres; (c) a Sophisticated factor that includes classical, operatic, world, and jazz; (d) an Intense factor defined by loud, forceful, and energetic music; and (e) a Contemporary factor defined largely by rhythmic and percussive music, such as is found in rap, funk, and acid jazz. The findings from a fourth study suggest that preferences for the MUSIC factors are affected by both the social and the auditory characteristics of the music. 2011 APA, all rights reserved
Modeling wind adjustment factor and midflame wind speed for Rothermel's surface fire spread model
Patricia L. Andrews
2012-01-01
Rothermel's surface fire spread model was developed to use a value for the wind speed that affects surface fire, called midflame wind speed. Models have been developed to adjust 20-ft wind speed to midflame wind speed for sheltered and unsheltered surface fuel. In this report, Wind Adjustment Factor (WAF) model equations are given, and the BehavePlus fire modeling...
Type D Personality : a five-factor model perspective
de Fruyt, F.; Denollet, J.K.L.
2002-01-01
This study investigated the position of Type D (high Negative Affectivity and high Social Inhibition) within the Five-Factor Model (FFM) of personality. A sample of 155 healthy subjects were administered the Type D Scale and the NEO-FFI, assessing the FFM traits. Subjects also filled out the General
The Five-Factor Model of Personality and Career Success.
Seibert, Scott E.; Kraimer, Maria L.
2001-01-01
Measures of career success and an inventory of the Five-Factor Model of Personality were completed by 496 workers. Extraversion was related positively to salary, promotion, and career satisfaction; neuroticism was related negatively to satisfaction. A significant negative relationship between agreeableness and salary was found for workers in…
A temperature dependent slip factor based thermal model for friction ...
Indian Academy of Sciences (India)
thermal modelling of FSW process by assuming the slip factor as a function of any one of the parameters such as ... Normal load, Fn. 31138 N .... source was moved in discrete steps of 1 mm to simulate the linear motion of the tool. At each load.
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 ...
The Five-Factor Model and Self-Determination Theory
DEFF Research Database (Denmark)
Olesen, Martin Hammershøj; Thomsen, Dorthe Kirkegaard; Schnieber, Anette
This study investigates conceptual overlap vs. distinction between individual differences in personality traits, i.e. the Five-Factor Model; and Self-determination Theory, i.e. general causality orientations. Twelve-hundred-and-eighty-seven freshmen (mean age 21.71; 64% women) completed electronic...
Reproductive Behavior and Personality Traits of the Five Factor Model
Jokela, Markus; Alvergne, Alexandra; Pollet, Thomas V.; Lummaa, Virpi
2011-01-01
We examined associations between Five Factor Model personality traits and various outcomes of reproductive behavior in a sample of 15 729 women and men from the Wisconsin Longitudinal Study (WLS) and Midlife Development in the United States (MIDUS) survey. Personality and reproductive history was
Risk factors and prognostic models for perinatal asphyxia at term
Ensing, S.
2015-01-01
This thesis will focus on the risk factors and prognostic models for adverse perinatal outcome at term, with a special focus on perinatal asphyxia and obstetric interventions during labor to reduce adverse pregnancy outcomes. For the majority of the studies in this thesis we were allowed to use data
Bayes Factor Covariance Testing in Item Response Models.
Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip
2017-12-01
Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.
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
Free-free Gaunt factors: comparison of various models
International Nuclear Information System (INIS)
Collins, L.A.; Merts, A.L.
1986-01-01
We develop the general theory of free-free absorption processes in terms of basic quantum mechanical principles. We perform calculations of the free-free Gaunt factor for several models of the electron-atom (ion) interaction in a variety of systems including rare gases, alkali, and aluminum. In addition, we investigate plasma-screening effects in such models as the Yukawa potential. Our calculations compare well with those of other authors, and our comparative study of various models allows a more thorough understanding of their range of validity. 38 refs., 2 figs., 14 tabs
Occam factors and model independent Bayesian learning of continuous distributions
International Nuclear Information System (INIS)
Nemenman, Ilya; Bialek, William
2002-01-01
Learning of a smooth but nonparametric probability density can be regularized using methods of quantum field theory. We implement a field theoretic prior numerically, test its efficacy, and show that the data and the phase space factors arising from the integration over the model space determine the free parameter of the theory ('smoothness scale') self-consistently. This persists even for distributions that are atypical in the prior and is a step towards a model independent theory for learning continuous distributions. Finally, we point out that a wrong parametrization of a model family may sometimes be advantageous for small data sets
Hadron form factors in the constituent quark model
International Nuclear Information System (INIS)
Cardarelli, F.; Salme', G.; Simula, S.; Pace, E.
1998-01-01
Hadron electromagnetic form factors are evaluated in a light-front constituent quark model based on the eigenfunctions of a mass operator, including in the q-q interaction a confining term and a one-gluon-exchange term (OGE). The spin-dependent part of the interaction plays an essential role for obtaining both a proper fit of the experimental nucleon electromagnetic form factors and the faster than dipole decrease of the magnetic N-P 33 (1232) transition form factor. The effects of the D wave, produced by the tensor part of the OGE interaction, on the quadrupole and Coulomb N-P 33 (1232) transition form factors have been found to be negligible. (author)
Form factors in the projected linear chiral sigma model
International Nuclear Information System (INIS)
Alberto, P.; Coimbra Univ.; Bochum Univ.; Ruiz Arriola, E.; Fiolhais, M.; Urbano, J.N.; Coimbra Univ.; Goeke, K.; Gruemmer, F.; Bochum Univ.
1990-01-01
Several nucleon form factors are computed within the framework of the linear chiral soliton model. To this end variational means and projection techniques applied to generalized hedgehog quark-boson Fock states are used. In this procedure the Goldberger-Treiman relation and a virial theorem for the pion-nucleon form factor are well fulfilled demonstrating the consistency of the treatment. Both proton and neutron charge form factors are correctly reproduced, as well as the proton magnetic one. The shapes of the neutron magnetic and of the axial form factors are good but their absolute values at the origin are too large. The slopes of all the form factors at zero momentum transfer are in good agreement with the experimental data. The pion-nucleon form factor exhibits to great extent a monopole shape with a cut-off mass of Λ=690 MeV. Electromagnetic form factors for the vertex γNΔ and the nucleon spin distribution are also evaluated and discussed. (orig.)
The Barrett–Crane model: asymptotic measure factor
International Nuclear Information System (INIS)
Kamiński, Wojciech; Steinhaus, Sebastian
2014-01-01
The original spin foam model construction for 4D gravity by Barrett and Crane suffers from a few troubling issues. In the simple examples of the vertex amplitude they can be summarized as the existence of contributions to the asymptotics from non-geometric configurations. Even restricted to geometric contributions the amplitude is not completely worked out. While the phase is known to be the Regge action, the so-called measure factor has remained mysterious for a decade. In the toy model case of the 6j symbol this measure factor has a nice geometric interpretation of V −1/2 leading to speculations that a similar interpretation should be possible also in the 4D case. In this paper we provide the first geometric interpretation of the geometric part of the asymptotic for the spin foam consisting of two glued 4-simplices (decomposition of the 4-sphere) in the Barrett–Crane model in the large internal spin regime. (paper)
The Barrett-Crane model: asymptotic measure factor
Kamiński, Wojciech; Steinhaus, Sebastian
2014-04-01
The original spin foam model construction for 4D gravity by Barrett and Crane suffers from a few troubling issues. In the simple examples of the vertex amplitude they can be summarized as the existence of contributions to the asymptotics from non-geometric configurations. Even restricted to geometric contributions the amplitude is not completely worked out. While the phase is known to be the Regge action, the so-called measure factor has remained mysterious for a decade. In the toy model case of the 6j symbol this measure factor has a nice geometric interpretation of V-1/2 leading to speculations that a similar interpretation should be possible also in the 4D case. In this paper we provide the first geometric interpretation of the geometric part of the asymptotic for the spin foam consisting of two glued 4-simplices (decomposition of the 4-sphere) in the Barrett-Crane model in the large internal spin regime.
Multi-factor energy price models and exotic derivatives pricing
Hikspoors, Samuel
The high pace at which many of the world's energy markets have gradually been opened to competition have generated a significant amount of new financial activity. Both academicians and practitioners alike recently started to develop the tools of energy derivatives pricing/hedging as a quantitative topic of its own. The energy contract structures as well as their underlying asset properties set the energy risk management industry apart from its more standard equity and fixed income counterparts. This thesis naturally contributes to these broad market developments in participating to the advances of the mathematical tools aiming at a better theory of energy contingent claim pricing/hedging. We propose many realistic two-factor and three-factor models for spot and forward price processes that generalize some well known and standard modeling assumptions. We develop the associated pricing methodologies and propose stable calibration algorithms that motivate the application of the relevant modeling schemes.
A test of resuspension factor models against Chernobyl data
International Nuclear Information System (INIS)
Garger, E.K.; Hoffman, F.O.
1995-04-01
After the accident at Unit 4 of the Chernobyl nuclear power plant (NPP), stationary air samplers were operated at Chernobyl and Baryshevka, cities which are 16 km and 150 km, respectively, from the NPP. Other air samplers were operated simultaneously, but intermittently, at locations within the 30 km zone at distances of 4-25 km from the NPP. These data were used to check the validity of time dependent models of the resuspension factor K (m -1 ). Seven different models were examined, three of which are discussed in the paper. Data from the stationary air samplers were averaged over one day or one month; dam from the intermittent air samplers were averaged over three days in 1986 and over four hours in 1991. The concentrations of eight radionuclides were measured at ten points during the same time period (14-17 September 1986). The calculated resuspension factors range from 6 x 10 -9 m -1 to 3 x 10 -6 m -1 . Data for the spatial means of K are given for certain time periods in 1986 and 1991; also presented are the calculated values according to the models. The experimental data and the calculated values differ by up to more than one order of magnitude. Also analysed was the temporal change in experimental values of K and these values were compared with model predictions. The annual means of the resuspension factor as determined experimentally and as calculated with the models are presented. The model derived from empirical data measured in Neuherberg after the Chernobyl accident agrees best with the data. The Garland model systematically gives results lower than the experimental values, and the calculated values of K from the Linsley model are consistently conservative. Also considered were the uncertainty of K due to fluctuations in air concentrations and possible biological effects of episodic exposures
A test of resuspension factor models against Chernobyl data
Energy Technology Data Exchange (ETDEWEB)
Garger, E.K. [Ukrainian Academy of Agricultural Sciences, Kiev (Ukraine). Inst. of Radioecology; Anspaugh, L.R.; Shinn, J.H. [Lawrence Livermore National Lab., CA (United States); Hoffman, F.O. [Senes Oak Ridge, Inc., TN (United States)
1995-04-01
After the accident at Unit 4 of the Chernobyl nuclear power plant (NPP), stationary air samplers were operated at Chernobyl and Baryshevka, cities which are 16 km and 150 km, respectively, from the NPP. Other air samplers were operated simultaneously, but intermittently, at locations within the 30 km zone at distances of 4-25 km from the NPP. These data were used to check the validity of time dependent models of the resuspension factor K (m{sup -1}). Seven different models were examined, three of which are discussed in the paper. Data from the stationary air samplers were averaged over one day or one month; dam from the intermittent air samplers were averaged over three days in 1986 and over four hours in 1991. The concentrations of eight radionuclides were measured at ten points during the same time period (14-17 September 1986). The calculated resuspension factors range from 6 x 10{sup -9} m{sup -1} to 3 x 10{sup -6} m{sup -1}. Data for the spatial means of K are given for certain time periods in 1986 and 1991; also presented are the calculated values according to the models. The experimental data and the calculated values differ by up to more than one order of magnitude. Also analysed was the temporal change in experimental values of K and these values were compared with model predictions. The annual means of the resuspension factor as determined experimentally and as calculated with the models are presented. The model derived from empirical data measured in Neuherberg after the Chernobyl accident agrees best with the data. The Garland model systematically gives results lower than the experimental values, and the calculated values of K from the Linsley model are consistently conservative. Also considered were the uncertainty of K due to fluctuations in air concentrations and possible biological effects of episodic exposures.
Human Factor Modelling in the Risk Assessment of Port Manoeuvers
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Teresa Abramowicz-Gerigk
2015-09-01
Full Text Available The documentation of human factor influence on the scenario development in maritime accidents compared with expert methods is commonly used as a basis in the process of setting up safety regulations and instructions. The new accidents and near misses show the necessity for further studies in determining the human factor influence on both risk acceptance criteria and development of risk control options for the manoeuvers in restricted waters. The paper presents the model of human error probability proposed for the assessment of ship masters and marine pilots' error decision and its influence on the risk of port manoeuvres.
SHMF: Interest Prediction Model with Social Hub Matrix Factorization
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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.
Modeling Factors with Influence on Sustainable University Management
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Oana Dumitrascu
2015-01-01
Full Text Available The main objective of this paper is to present the factors with influence on the sustainable university management and the relationships between them. In the scientific approach we begin from a graphical model, according to which the extracurricular activities together with internal environmental factors influence students’ involvement in such activities, the university attractiveness, their academic performance and their integration into the socially-economic and natural environment (components related with sustainable development. The model emphasizes that individual performances, related to students’ participation in extracurricular activities, have a positive influence on the sustainability of university management. The results of the study have shown that the university sustainability may be influenced by a number of factors, such as students’ performance, students’ involvement in extracurricular activities or university’s attractiveness and can in turn influence implicitly also the sustainability of university management. The originality of the paper consists in the relationships study using the modeling method in general and informatics tools of modeling in particular, as well as through graphical visualization of some influences, on the sustainability university management.
Condensation in models with factorized and pair-factorized stationary states
International Nuclear Information System (INIS)
Evans, M R; Waclaw, B
2015-01-01
Non-equilibrium real-space condensation is a phenomenon in which a finite fraction of some conserved quantity (mass, particles, etc) becomes spatially localized. We review two popular stochastic models of hopping particles that lead to condensation and whose stationary states assume a factorized form: the zero-range process and the misanthrope process, and their various generalizations. We also introduce a new model—a misanthrope process with parallel dynamics—that exhibits condensation and has a pair-factorized stationary state
The Factors of Forming the National HR-Management Model
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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.
Factors affecting strategic plan implementation using interpretive structural modeling (ISM).
Bahadori, Mohammadkarim; Teymourzadeh, Ehsan; Tajik, Hamidreza; Ravangard, Ramin; Raadabadi, Mehdi; Hosseini, Seyed Mojtaba
2018-06-11
Purpose Strategic planning is the best tool for managers seeking an informed presence and participation in the market without surrendering to changes. Strategic planning enables managers to achieve their organizational goals and objectives. Hospital goals, such as improving service quality and increasing patient satisfaction cannot be achieved if agreed strategies are not implemented. The purpose of this paper is to investigate the factors affecting strategic plan implementation in one teaching hospital using interpretive structural modeling (ISM). Design/methodology/approach The authors used a descriptive study involving experts and senior managers; 16 were selected as the study sample using a purposive sampling method. Data were collected using a questionnaire designed and prepared based on previous studies. Data were analyzed using ISM. Findings Five main factors affected strategic plan implementation. Although all five variables and factors are top level, "senior manager awareness and participation in the strategic planning process" and "creating and maintaining team participation in the strategic planning process" had maximum drive power. "Organizational structure effects on the strategic planning process" and "Organizational culture effects on the strategic planning process" had maximum dependence power. Practical implications Identifying factors affecting strategic plan implementation is a basis for healthcare quality improvement by analyzing the relationship among factors and overcoming the barriers. Originality/value The authors used ISM to analyze the relationship between factors affecting strategic plan implementation.
Finite-lattice form factors in free-fermion models
International Nuclear Information System (INIS)
Iorgov, N; Lisovyy, O
2011-01-01
We consider the general Z 2 -symmetric free-fermion model on the finite periodic lattice, which includes as special cases the Ising model on the square and triangular lattices and the Z n -symmetric BBS τ (2) -model with n = 2. Translating Kaufman's fermionic approach to diagonalization of Ising-like transfer matrices into the language of Grassmann integrals, we determine the transfer matrix eigenvectors and observe that they coincide with the eigenvectors of a square lattice Ising transfer matrix. This allows us to find exact finite-lattice form factors of spin operators for the statistical model and the associated finite-length quantum chains, of which the most general is equivalent to the XY chain in a transverse field
Object recognition in images via a factor graph model
He, Yong; Wang, Long; Wu, Zhaolin; Zhang, Haisu
2018-04-01
Object recognition in images suffered from huge search space and uncertain object profile. Recently, the Bag-of- Words methods are utilized to solve these problems, especially the 2-dimension CRF(Conditional Random Field) model. In this paper we suggest the method based on a general and flexible fact graph model, which can catch the long-range correlation in Bag-of-Words by constructing a network learning framework contrasted from lattice in CRF. Furthermore, we explore a parameter learning algorithm based on the gradient descent and Loopy Sum-Product algorithms for the factor graph model. Experimental results on Graz 02 dataset show that, the recognition performance of our method in precision and recall is better than a state-of-art method and the original CRF model, demonstrating the effectiveness of the proposed method.
Proposition Factor Model of World Class Manufacturing in Brazilian Enterprises
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Paulo Sergio Gonçalves de Oliveira
2016-05-01
Full Text Available The present paper aims to develop a model of World Class Manufacturing, to achieve this goal was elaborated a questionnaire with 35 assertive divided in 7 areas suggested by literature review. This questionnaire was send to manufacture specialists, product developers and technician through LinkedIn the participants was select by researchers in discussion groups taking in consideration their experience using the professional profile. About 1000 invite was send to professional from metal-mechanic sector which returned 180 valid questionnaires. The data was analyzed through factor analyses and was obtained 7 constructs, which explained 67% of data variance. The KMO was 0,84, which is considered good for, analyzes purpose. The seventh factor was eliminated because it Cranach’s Alpha was below 0,6 and the remained factor was nominated as: Lean Manufacturing, Human Resources Management to achieve flexibility, Marketing Integration, Costs Reduction and Flexibility.
Baryon octet electromagnetic form factors in a confining NJL model
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Manuel E. Carrillo-Serrano
2016-08-01
Full Text Available Electromagnetic form factors of the baryon octet are studied using a Nambu–Jona-Lasinio model which utilizes the proper-time regularization scheme to simulate aspects of colour confinement. In addition, the model also incorporates corrections to the dressed quarks from vector meson correlations in the t-channel and the pion cloud. Comparison with recent chiral extrapolations of lattice QCD results shows a remarkable level of consistency. For the charge radii we find the surprising result that rEp
Modeling impact of environmental factors on photovoltaic array performance
Energy Technology Data Exchange (ETDEWEB)
Yang, Jie; Sun, Yize; Xu, Yang [College of Mechanical Engineering, Donghua University NO.2999, North Renmin Road, Shanghai (China)
2013-07-01
It is represented in this paper that a methodology to model and quantify the impact of the three environmental factors, the ambient temperature, the incident irradiance and the wind speed, upon the performance of photovoltaic array operating under outdoor conditions. First, A simple correlation correlating operating temperature with the three environmental variables is validated for a range of wind speed studied, 2-8, and for irradiance values between 200 and 1000. Root mean square error (RMSE) between modeled operating temperature and measured values is 1.19% and the mean bias error (MBE) is -0.09%. The environmental factors studied influence I-V curves, P-V curves, and maximum-power outputs of photovoltaic array. The cell-to-module-to-array mathematical model for photovoltaic panels is established in this paper and the method defined as segmented iteration is adopted to solve the I-V curve expression to relate model I-V curves. The model I-V curves and P-V curves are concluded to coincide well with measured data points. The RMSE between numerically calculated maximum-power outputs and experimentally measured ones is 0.2307%, while the MBE is 0.0183%. In addition, a multivariable non-linear regression equation is proposed to eliminate the difference between numerically calculated values and measured ones of maximum power outputs over the range of high ambient temperature and irradiance at noon and in the early afternoon. In conclusion, the proposed method is reasonably simple and accurate.
The animal model determines the results of Aeromonas virulence factors
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Alejandro Romero
2016-10-01
Full Text Available The selection of an experimental animal model is of great importance in the study of bacterial virulence factors. Here, a bath infection of zebrafish larvae is proposed as an alternative model to study the virulence factors of A. hydrophila. Intraperitoneal infections in mice and trout were compared with bath infections in zebrafish larvae using specific mutants. The great advantage of this model is that bath immersion mimics the natural route of infection, and injury to the tail also provides a natural portal of entry for the bacteria. The implication of T3SS in the virulence of A. hydrophila was analysed using the AH-1::aopB mutant. This mutant was less virulent than the wild-type strain when inoculated into zebrafish larvae, as described in other vertebrates. However, the zebrafish model exhibited slight differences in mortality kinetics only observed using invertebrate models. Infections using the mutant AH-1∆vapA lacking the gene coding for the surface S-layer suggested that this protein was not totally necessary to the bacteria once it was inside the host, but it contributed to the inflammatory response. Only when healthy zebrafish larvae were infected did the mutant produce less mortality than the wild type. Variations between models were evidenced using the AH-1∆rmlB, which lacks the O-antigen lipopolysaccharide (LPS, and the AH-1∆wahD, which lacks the O-antigen LPS and part of the LPS outer-core. Both mutants showed decreased mortality in all of the animal models, but the differences between them were only observed in injured zebrafish larvae, suggesting that residues from the LPS outer core must be important for virulence. The greatest differences were observed using the AH-1ΔFlaB-J (lacking polar flagella and unable to swim and the AH-1::motX (non-motile but producing flagella. They were as pathogenic as the wild-type strain when injected into mice and trout, but no mortalities were registered in zebrafish larvae. This study
Parallelized preconditioned model building algorithm for matrix factorization
Kaya, Kamer; Birbil, İlker; Birbil, Ilker; Öztürk, Mehmet Kaan; Ozturk, Mehmet Kaan; Gohari, Amir
2017-01-01
Matrix factorization is a common task underlying several machine learning applications such as recommender systems, topic modeling, or compressed sensing. Given a large and possibly sparse matrix A, we seek two smaller matrices W and H such that their product is as close to A as possible. The objective is minimizing the sum of square errors in the approximation. Typically such problems involve hundreds of thousands of unknowns, so an optimizer must be exceptionally efficient. In this study, a...
INNOVATIVE PRACTICES IN TOURISM. APOSSIBLE MODEL BY FOSTERING SHADOW FACTORS
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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
Change management in Iranian hospitals: social factors model
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B. Delgoshaei
2012-02-01
Full Text Available Background: Continuous change in the complex health care environments is a major challenge for administrative managers. This study aimed to design a change model to facilitate change implementation in the Iranian hospitals. Methods: This is a descriptive and comparative study. The data were collected through library search and in-depth interview with 15 hospital managers. Nine well-established change theories developed by Lewin, Action Research, Kotter, Ackerman- Anderson and Anderson, Prosci , Kilman, Beer, Continuum, and Gelicher were compared. Common denominators of the theories were identified and tabulated. Experienced hospital managers’ suggestions about social factors were acquired. The initial model was designed and validated using the Delphi Technique. Results: The majority of the selected change models emphasize the significance of social factors in change implementation such as effective communication, organizational climate and culture, and leadership. The results from the interviews indicate that low readiness to change, lack of confidence (or trust for change, and autocratic leadership style ,and poor communication could hinder the change process. Conclusion: Based on the model developed in the study, effective communication, readiness of employees, and a contingency leadership/management combined could lead to successful implementation of change in the hospital.
Modeling soft factors in computer-based wargames
Alexander, Steven M.; Ross, David O.; Vinarskai, Jonathan S.; Farr, Steven D.
2002-07-01
Computer-based wargames have seen much improvement in recent years due to rapid increases in computing power. Because these games have been developed for the entertainment industry, most of these advances have centered on the graphics, sound, and user interfaces integrated into these wargames with less attention paid to the game's fidelity. However, for a wargame to be useful to the military, it must closely approximate as many of the elements of war as possible. Among the elements that are typically not modeled or are poorly modeled in nearly all military computer-based wargames are systematic effects, command and control, intelligence, morale, training, and other human and political factors. These aspects of war, with the possible exception of systematic effects, are individually modeled quite well in many board-based commercial wargames. The work described in this paper focuses on incorporating these elements from the board-based games into a computer-based wargame. This paper will also address the modeling and simulation of the systemic paralysis of an adversary that is implied by the concept of Effects Based Operations (EBO). Combining the fidelity of current commercial board wargames with the speed, ease of use, and advanced visualization of the computer can significantly improve the effectiveness of military decision making and education. Once in place, the process of converting board wargames concepts to computer wargames will allow the infusion of soft factors into military training and planning.
Clinical application of the five-factor model.
Widiger, Thomas A; Presnall, Jennifer Ruth
2013-12-01
The Five-Factor Model (FFM) has become the predominant dimensional model of general personality structure. The purpose of this paper is to suggest a clinical application. A substantial body of research indicates that the personality disorders included within the American Psychiatric Association's (APA) Diagnostic and Statistical Manual of Mental Disorders (DSM) can be understood as extreme and/or maladaptive variants of the FFM (the acronym "DSM" refers to any particular edition of the APA DSM). In addition, the current proposal for the forthcoming fifth edition of the DSM (i.e., DSM-5) is shifting closely toward an FFM dimensional trait model of personality disorder. Advantages of this shifting conceptualization are discussed, including treatment planning. © 2012 Wiley Periodicals, Inc.
Modeling of human factor Va inactivation by activated protein C
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Bravo Maria
2012-05-01
Full Text Available Abstract Background Because understanding of the inventory, connectivity and dynamics of the components characterizing the process of coagulation is relatively mature, it has become an attractive target for physiochemical modeling. Such models can potentially improve the design of therapeutics. The prothrombinase complex (composed of the protease factor (FXa and its cofactor FVa plays a central role in this network as the main producer of thrombin, which catalyses both the activation of platelets and the conversion of fibrinogen to fibrin, the main substances of a clot. A key negative feedback loop that prevents clot propagation beyond the site of injury is the thrombin-dependent generation of activated protein C (APC, an enzyme that inactivates FVa, thus neutralizing the prothrombinase complex. APC inactivation of FVa is complex, involving the production of partially active intermediates and “protection” of FVa from APC by both FXa and prothrombin. An empirically validated mathematical model of this process would be useful in advancing the predictive capacity of comprehensive models of coagulation. Results A model of human APC inactivation of prothrombinase was constructed in a stepwise fashion by analyzing time courses of FVa inactivation in empirical reaction systems with increasing number of interacting components and generating corresponding model constructs of each reaction system. Reaction mechanisms, rate constants and equilibrium constants informing these model constructs were initially derived from various research groups reporting on APC inactivation of FVa in isolation, or in the presence of FXa or prothrombin. Model predictions were assessed against empirical data measuring the appearance and disappearance of multiple FVa degradation intermediates as well as prothrombinase activity changes, with plasma proteins derived from multiple preparations. Our work integrates previously published findings and through the cooperative
Computer modeling the boron compound factor in normal brain tissue
International Nuclear Information System (INIS)
Gavin, P.R.; Huiskamp, R.; Wheeler, F.J.; Griebenow, M.L.
1993-01-01
The macroscopic distribution of borocaptate sodium (Na 2 B 12 H 11 SH or BSH) in normal tissues has been determined and can be accurately predicted from the blood concentration. The compound para-borono-phenylalanine (p-BPA) has also been studied in dogs and normal tissue distribution has been determined. The total physical dose required to reach a biological isoeffect appears to increase directly as the proportion of boron capture dose increases. This effect, together with knowledge of the macrodistribution, led to estimates of the influence of the microdistribution of the BSH compound. This paper reports a computer model that was used to predict the compound factor for BSH and p-BPA and, hence, the equivalent radiation in normal tissues. The compound factor would need to be calculated for other compounds with different distributions. This information is needed to design appropriate normal tissue tolerance studies for different organ systems and/or different boron compounds
Positive Orientation and the Five-Factor Model
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Miciuk Łukasz Roland
2016-04-01
Full Text Available The aim of the present study was to investigate the relationship between positive orientation (PO defined as a basic predisposition to perceive and evaluate positive aspects of life, the future and oneself and the Five-Factor Model of personality (FFM. Hypotheses postulated positive correlations between PO and extraversion, conscientiousness, agreeableness and openness; a negative correlation was predicted between PO and neuroticism. Two hundred Polish students completed the following measures: SES (Self-Esteem Scale, Rosenberg, SWLS (The Satisfaction with Life Scale; Diener, Emmons, Larson & Griffin, LOT-R (The Life Orientation Test - Revised; Scheier, Carver & Bridges and NEOFFI (NEO Five Factor Inventory, Costa & McCrae. The results confirmed correlations between PO and extraversion, conscientiousness, and neuroticism; correlations with openness and agreeableness were not supported. According to canonical correlations, PO shows a clear affinity to the FFM.
Workforce scheduling: A new model incorporating human factors
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Mohammed Othman
2012-12-01
Full Text Available Purpose: The majority of a company’s improvement comes when the right workers with the right skills, behaviors and capacities are deployed appropriately throughout a company. This paper considers a workforce scheduling model including human aspects such as skills, training, workers’ personalities, workers’ breaks and workers’ fatigue and recovery levels. This model helps to minimize the hiring, firing, training and overtime costs, minimize the number of fired workers with high performance, minimize the break time and minimize the average worker’s fatigue level.Design/methodology/approach: To achieve this objective, a multi objective mixed integer programming model is developed to determine the amount of hiring, firing, training and overtime for each worker type.Findings: The results indicate that the worker differences should be considered in workforce scheduling to generate realistic plans with minimum costs. This paper also investigates the effects of human fatigue and recovery on the performance of the production systems.Research limitations/implications: In this research, there are some assumptions that might affect the accuracy of the model such as the assumption of certainty of the demand in each period, and the linearity function of Fatigue accumulation and recovery curves. These assumptions can be relaxed in future work.Originality/value: In this research, a new model for integrating workers’ differences with workforce scheduling is proposed. To the authors' knowledge, it is the first time to study the effects of different important human factors such as human personality, skills and fatigue and recovery in the workforce scheduling process. This research shows that considering both technical and human factors together can reduce the costs in manufacturing systems and ensure the safety of the workers.
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.
Modeling Shear Induced Von Willebrand Factor Binding to Collagen
Dong, Chuqiao; Wei, Wei; Morabito, Michael; Webb, Edmund; Oztekin, Alparslan; Zhang, Xiaohui; Cheng, Xuanhong
2017-11-01
Von Willebrand factor (vWF) is a blood glycoprotein that binds with platelets and collagen on injured vessel surfaces to form clots. VWF bioactivity is shear flow induced: at low shear, binding between VWF and other biological entities is suppressed; for high shear rate conditions - as are found near arterial injury sites - VWF elongates, activating its binding with platelets and collagen. Based on parameters derived from single molecule force spectroscopy experiments, we developed a coarse-grain molecular model to simulate bond formation probability as a function of shear rate. By introducing a binding criterion that depends on the conformation of a sub-monomer molecular feature of our model, the model predicts shear-induced binding, even for conditions where binding is highly energetically favorable. We further investigate the influence of various model parameters on the ability to predict shear-induced binding (vWF length, collagen site density and distribution, binding energy landscape, and slip/catch bond length) and demonstrate parameter ranges where the model provides good agreement with existing experimental data. Our results may be important for understanding vWF activity and also for achieving targeted drug therapy via biomimetic synthetic molecules. National Science Foundation (NSF),Division of Mathematical Sciences (DMS).
Assessment of the five-factor model of personality.
Widiger, T A; Trull, T J
1997-04-01
The five-factor model (FFM) of personality is obtaining construct validation, recognition, and practical consideration across a broad domain of fields, including clinical psychology, industrial-organizational psychology, and health psychology. As a result, an array of instruments have been developed and existing instruments are being modified to assess the FFM. In this article, we present an overview and critique of five such instruments (the Goldberg Big Five Markers, the revised NEO Personality Inventory, the Interpersonal Adjective Scales-Big Five, the Personality Psychopathology-Five, and the Hogan Personality Inventory), focusing in particular on their representation of the lexical FFM and their practical application.
Replica Analysis for Portfolio Optimization with Single-Factor Model
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.
Liberal bias and the five-factor model.
Charney, Evan
2015-01-01
Duarte et al. draw attention to the "embedding of liberal values and methods" in social psychological research. They note how these biases are often invisible to the researchers themselves. The authors themselves fall prey to these "invisible biases" by utilizing the five-factor model of personality and the trait of openness to experience as one possible explanation for the under-representation of political conservatives in social psychology. I show that the manner in which the trait of openness to experience is conceptualized and measured is a particularly blatant example of the very liberal bias the authors decry.
Human Factors Engineering Review Model for advanced nuclear power reactors
International Nuclear Information System (INIS)
O'Hara, J.; Higgins, J.; Goodman, C.; Galletti, G.: Eckenrode, R.
1993-01-01
One of the major issues to emerge from the initial design reviews under the certification process was that detailed human-systems interface (HSI) design information was not available for staff review. To address the lack of design detail issue. The Nuclear Regulatory Commission (NRC) is performing the design certification reviews based on a design process plan which describes the human factors engineering (HFE) program elements that are necessary and sufficient to develop an acceptable detailed design specification. Since the review of a design process is unprecedented in the nuclear industry. The criteria for review are not addressed by current regulations or guidance documents and. therefore, had to be developed. Thus, an HFE Program Review Model was developed. This paper will describe the model's rationale, scope, objectives, development, general characteristics. and application
Influencing Factors and Simplified Model of Film Hole Irrigation
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Yi-Bo Li
2017-07-01
Full Text Available Film hole irrigation is an advanced low-cost and high-efficiency irrigation method, which can improve water conservation and water use efficiency. Given its various advantages and potential applications, we conducted a laboratory study to investigate the effects of soil texture, bulk density, initial soil moisture, irrigation depth, opening ratio (ρ, film hole diameter (D, and spacing on cumulative infiltration using SWMS-2D. We then proposed a simplified model based on the Kostiakov model for infiltration estimation. Error analyses indicated SWMS-2D to be suitable for infiltration simulation of film hole irrigation. Additional SWMS-2D-based investigations indicated that, for a certain soil, initial soil moisture and irrigation depth had the weakest effects on cumulative infiltration, whereas ρ and D had the strongest effects on cumulative infiltration. A simplified model with ρ and D was further established, and its use was then expanded to different soils. Verification based on seven soil types indicated that the established simplified double-factor model effectively estimates cumulative infiltration for film hole irrigation, with a small mean average error of 0.141–2.299 mm, a root mean square error of 0.177–2.722 mm, a percent bias of −2.131–1.479%, and a large Nash–Sutcliffe coefficient that is close to 1.0.
Talent identification model for sprinter using discriminant factor
Kusnanik, N. W.; Hariyanto, A.; Herdyanto, Y.; Satia, A.
2018-01-01
The main purpose of this study was to identify young talented sprinter using discriminant factor. The research was conducted in 3 steps including item pool, screening of item pool, and trial of instruments at the small and big size of samples. 315 male elementary school students participated in this study with mean age of 11-13 years old. Data were collected by measuring anthropometry (standing height, sitting height, body mass, and leg length); testing physical fitness (40m sprint for speed, shuttle run for agility, standing broad jump for power, multistage fitness test for endurance). Data were analyzed using discriminant factor. The result of this study found that there were 5 items that selected as an instrument to identify young talented sprinter: sitting height, body mass, leg length, sprint 40m, and multistage fitness test. Model of Discriminant for talent identification in sprinter was D = -24,497 + (0,155 sitting height) + (0,080 body mass) + (0,148 leg length) + (-1,225 Sprint 40m) + (0,563 MFT). The conclusion of this study: instrument tests that have been selected and discriminant model that have been found can be applied to identify young talented as a sprinter.
Dimensional models of personality: the five-factor model and the DSM-5
Trull, Timothy J.; Widiger, Thomas A.
2013-01-01
It is evident that the classification of personality disorder is shifting toward a dimensional trait model and, more specifically, the five-factor model (FFM). The purpose of this paper is to provide an overview of the FFM of personality disorder. It will begin with a description of this dimensional model of normal and abnormal personality functioning, followed by a comparison with a proposal for future revisions to DSM-5 and a discussion of its potential advantages as an integrative hierarchical model of normal and abnormal personality structure. PMID:24174888
Motivation Factors for Adopting Building Information Modeling (BIM in Iraq
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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.
Latent Fundamentals Arbitrage with a Mixed Effects Factor Model
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Andrei Salem Gonçalves
2012-09-01
Full Text Available We propose a single-factor mixed effects panel data model to create an arbitrage portfolio that identifies differences in firm-level latent fundamentals. Furthermore, we show that even though the characteristics that affect returns are unknown variables, it is possible to identify the strength of the combination of these latent fundamentals for each stock by following a simple approach using historical data. As a result, a trading strategy that bought the stocks with the best fundamentals (strong fundamentals portfolio and sold the stocks with the worst ones (weak fundamentals portfolio realized significant risk-adjusted returns in the U.S. market for the period between July 1986 and June 2008. To ensure robustness, we performed sub period and seasonal analyses and adjusted for trading costs and we found further empirical evidence that using a simple investment rule, that identified these latent fundamentals from the structure of past returns, can lead to profit.
Albarracin, Dolores; Tannenbaum, Melanie B.; Glasman, Laura R.; Rothman, Alexander J.
2010-01-01
Changing HIV-related behaviors requires addressing the individual, dyadic, and structural influences that shape them. This supplement of AIDS & Behavior presents frameworks that integrate these three influences on behavior. Concepts from these frameworks were selected to model the processes by which structural factors affect individual HIV-related behavior. In the Inclusion/Exclusion Model, material and symbolic inclusions and exclusions (sharing versus denying resources) regulate individuals...
mathematical models for prediction of safety factors for a simply
African Journals Online (AJOL)
HOD
Keywords: reliability, code calibration, load factor, safety factor, design, steel beam. 1. INTRODUCTION ... safety factors for the design of a simply supported steel beam using regression .... 5 design criteria for a solid timber portal frame.
Five-Factor Model personality profiles of drug users
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Crum Rosa M
2008-04-01
Full Text Available Abstract Background Personality traits are considered risk factors for drug use, and, in turn, the psychoactive substances impact individuals' traits. Furthermore, there is increasing interest in developing treatment approaches that match an individual's personality profile. To advance our knowledge of the role of individual differences in drug use, the present study compares the personality profile of tobacco, marijuana, cocaine, and heroin users and non-users using the wide spectrum Five-Factor Model (FFM of personality in a diverse community sample. Method Participants (N = 1,102; mean age = 57 were part of the Epidemiologic Catchment Area (ECA program in Baltimore, MD, USA. The sample was drawn from a community with a wide range of socio-economic conditions. Personality traits were assessed with the Revised NEO Personality Inventory (NEO-PI-R, and psychoactive substance use was assessed with systematic interview. Results Compared to never smokers, current cigarette smokers score lower on Conscientiousness and higher on Neuroticism. Similar, but more extreme, is the profile of cocaine/heroin users, which score very high on Neuroticism, especially Vulnerability, and very low on Conscientiousness, particularly Competence, Achievement-Striving, and Deliberation. By contrast, marijuana users score high on Openness to Experience, average on Neuroticism, but low on Agreeableness and Conscientiousness. Conclusion In addition to confirming high levels of negative affect and impulsive traits, this study highlights the links between drug use and low Conscientiousness. These links provide insight into the etiology of drug use and have implications for public health interventions.
The pion form factor within the hidden local symmetry model
International Nuclear Information System (INIS)
Benayoun, M.; David, P.; DelBuono, L.; Leruste, P.; O'Connell, H.B.
2003-01-01
We analyze a pion form factor formulation which fulfills the Analyticity requirement within the Hidden Local Symmetry (HLS) Model. This implies an s-dependent dressing of the ρ-γ VMD coupling and an account of several coupled channels. The corresponding function F π (s) provides nice fits of the pion form factor data from s=-0.25 to s=1 GeV 2 . It is shown that the coupling to KK has little effect, while ωπ 0 improves significantly the fit probability below the φ mass. No need for additional states like ρ(1450) shows up in this invariant-mass range. All parameters, except for the subtraction polynomial coefficients, are fixed from the rest of the HLS phenomenology. The fits show consistency with the expected behaviour of F π (s) at s=0 up to O(s 2 ) and with the phase shift data on δ 1 1 (s) from threshold to somewhat above the φ mass. The ω sector is also examined in relation with recent data from CMD-2. (orig.)
Logistic regression for risk factor modelling in stuttering research.
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.
Confirmatory Factor Analysis of WAIS-IV in a Clinical Sample: Examining a Bi-Factor Model
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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.
Some factors that will affect the next generation of forest growth models
International Nuclear Information System (INIS)
Leary, R.A.
1988-01-01
This paper discusses several types of factors that affect the form and referents of future growth models. These include philosophical, scientific, technological, educational, and organizational factors. Each factor is presented individually
A comparison of the VAR model and the PC factor model in forecasting inflation in Montenegro
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Lipovina-Božović Milena
2013-01-01
Full Text Available Montenegro started using the euro in 2002 and regained independence in 2006. Its main economic partners are European countries, yet inflation movements in Montenegro do not coincide with consumer price fluctuations in the eurozone. Trying to develop a useful forecasting model for Montenegrin inflation, we compare the results of a three-variable vector autoregression (VAR model, and a principle component (PC factor model starting with twelve variables. The estimation period is January 2001 to December 2012, and the control months are the first six months of 2013. The results show that in forecasting inflation, despite a high level of Montenegrin economic dependence on international developments, more reliable forecasts are achieved with the use of additional information on a larger number of factors, which includes domestic economic activity.
Microscopic models for hadronic form factors and vertex functions
International Nuclear Information System (INIS)
Santhanam, I.; Bhatnagar, S.; Mitra, A.N.
1990-01-01
We review the status of nucleon (N) and few-nucleon form factors (f.f.'s) from the view-point of a gradual unfolding of successively inner degrees of freedom (d.o.f.) with increase in q 2 . To this end we focus attention on the problem of a microscopic formulation of hadronic vertex functions (v.f.) from the point of view of their key role in understanding the physics of a large variety of few-hadron reactions on the one hand, and their practical usefulness in articulating the internal dynamics of hadron and few-hadron systems on the other hand. The criterion of an integrated view from low-energy spectroscopy to high-q 2 amplitudes is employed to emphasize the desirability of formulations in terms of relativistic dynamical equations based on Lorentz and gauge invariance in preference to phenomenological models, which often require additional assumptions beyond their original premises to extend their applicability domains. In this respect, the practical possibilities of the Bethe-Salpeter equation (BSE) in articulating the necessary dynamical ingredients are emphasized on a two-tier basis, the basis constants (3) being pre-determined from the mass spectral data (1 st stage) in preparation for the construction of the hadron-quark vertex functions (2 nd stage). An explicit construction is outlined for meson-quark and baryon-quark vertex functions as well as of meson-nucleon vertex functions in a stepwise fashion. The role of the latter as basic parameter-free ingredients is discussed for possible use in the more serious treatment in the current literature of quark-meson level (α) and meson-isobar (β) d.o.f. in 2-N and 3-N form factor studies. Since most of these studies are characterized by the use of RGM techniques at the six-quark level, a comparative discussion is also given of several contemporary RGM based models. Finally, the concrete prospects for employing such hardon-quark vertex functions for evaluating pp-bar annihilation amplitudes are briefly indicated
The capital asset pricing model versus the three factor model: A United Kingdom Perspective
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Chandra Shekhar Bhatnagar
2013-07-01
Full Text Available The Sharpe (1964, Lintner (1965 and Black (1972 Capital Asset Pricing Model (CAPM postulates that the equilibrium rates of return on all risky assets are a linear function of their covariance with the market portfolio. Recent work by Fama and French (1996, 2006 introduce a Three Factor Model that questions the “real world application” of the CAPM Theorem and its ability to explain stock returns as well as value premium effects in the United States market. This paper provides an out-of-sample perspective to the work of Fama and French (1996, 2006. Multiple regression is used to compare the performance of the CAPM, a split sample CAPM and the Three Factor Model in explaining observed stock returns and value premium effects in the United Kingdom market. The methodology of Fama and French (2006 was used as the framework for this study. The findings show that the Three Factor Model holds for the United Kingdom Market and is superior to the CAPM and the split sample CAPM in explaining both stock returns and value premium effects. The “real world application” of the CAPM is therefore not supported by the United Kingdom data.
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)
Electrical tortuosity, Kozeny’s factor and cementation factor modelled for chalk
DEFF Research Database (Denmark)
Katika, Konstantina; Fabricius, Ida Lykke
2015-01-01
saturated core plugs to determine the cementation factor, m. This value differs from the one Archie used to describe his equation and best describes the formation factor based on experimental data. Based on this m, we determine the formation factor, F, and the tortuosity, τ. We use this value of τ...
Physiological factors into plant uptake models for pollutant
International Nuclear Information System (INIS)
Goncharova, N.; Kalinkevich, E.; Pytyrskaya, V.; Lopareva, E.; Suvorov, D.
2002-01-01
The main principles of biological control of the intensity of pollutant flow into system soil-plant have been analysed. It demonstrated that functional state of plants is so far significant factor in determination of rate of pollutant turn on trophic chains as physical-chemical property of mineral elements Most biosphere and contamination assessment models are based on uniform soil conditions,since single coefficients are used to describe the transfer of contaminants to the plant. The main pathway of the functional control intensity of pollutant flow such as possibility of plant to increase mobility of mineral elements into soil and change of ion's exchange characteristics of plant tissues, which determine the degree of attraction and capacity of accumulation of non biogenic elements by a plant have been considered. It is known that there are two groups of factors which determine the level of pollutant accumulation by plant. The first group is connected with determination of the level of biological availability of pollutants for a plant in soil, the second group of factors determine attractive of the higher plants and capacity of radionuclides and heavy metals accumulation in biomass. At the same time in accordance with modern eco physiological data, different alive organisms can play active part in processes of the mineral elements migration. Metabolites of the coil microorganisms and especially root excretion of higher plants. Our investigations carried out earlier demonstrated that there is high correlation between the level of Cs, Cu, Zn and Co accumulation and cation exchange capacity of the intact plant tissues and on the other hand similar changes of these characteristics in condition of the experimental modification of radionuclide and heavy metals accumulation by different environmental factors. These data suggest that namely cation exchange capacity may be one of the main 'driving force' and physiological characteristics in absorption of non biogenic
Feng, Yongjiu; Tong, Xiaohua
2017-09-22
Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.
Integrated traffic conflict model for estimating crash modification factors.
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.
Directory of Open Access Journals (Sweden)
Grant B. Morgan
2015-02-01
Full Text Available Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds.
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.
E-Learning and Social Media Motivation Factor Model
Rosli, Mohd Shafie; Saleh, Nor Shela; Aris, Baharuddin; Ahmad, Maizah Hura; Sejzi, Abbas Abjoli; Shamsudin, Nur Amalina
2016-01-01
The aims of this study are to probe into the motivational factors toward the usage of e-learning and social media among educational technology postgraduate students in the Faculty of Education, Universiti Teknologi Malaysia. This study had involved 70 respondents via the means of a questionnaire. Four factors have been studied, named, the factor…
g-Factors in the (sdg) boson model
Morrison, I.
1986-07-01
The role of the g-boson in producing first-order variations in the g-factors of states in rotational nuclei is investigated. It is shown that the g-boson is unlikely to contribute directly to any observed g-factor variations in the ground-state band.
G-factors in the (sdg) boson model
Energy Technology Data Exchange (ETDEWEB)
Morrison, I.
1986-07-24
The role of the g-boson in producing first-order variations in the g-factors of states in rotational nuclei is investigated. It is shown that the g-boson is unlikely to contribute directly to any observed g-factor variations in the ground-state band.
Analytic properties of form factors in strictly confining models
International Nuclear Information System (INIS)
Csikor, F.
1979-12-01
An argument is presented showing that strict confinement implies the possible existence of an (unwanted) branch point at q 2 =0 in the form factors. In case of a bag extended to infinity in the relative time, the branch point is certainly there (provided that the form factor is non zero at q 2 =0). (author)
Critical Success Factors for E-Learning Acceptance: Confirmatory Factor Models
Selim, Hassan M.
2007-01-01
E-learning, one of the tools emerged from information technology, has been integrated in many university programs. There are several factors that need to be considered while developing or implementing university curriculums that offer e-learning based courses. This paper is intended to specify e-learning critical success factors (CSFs) as…
John Carroll’s Views on Intelligence: Bi-Factor vs. Higher-Order Models
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A. Alexander Beaujean
2015-10-01
Full Text Available The development of factor models is inextricably tied to the history of intelligence research. One of the most commonly-cited scholars in the field is John Carroll, whose three-stratum theory of cognitive ability has been one of the most influential models of cognitive ability in the past 20 years. Nonetheless, there is disagreement about how Carroll conceptualized the factors in his model. Some argue that his model is best represented through a higher-order model, while others argue that a bi-factor model is a better representation. Carroll was explicit about what he perceived the best way to represent his model, but his writings are not always easy to understand. In this article, I clarify his position by first describing the details and implications of bi-factor and higher-order models then show that Carroll’s published views are better represented by a bi-factor model.
A Dynamic Multi-Level Factor Model with Long-Range Dependence
DEFF Research Database (Denmark)
Ergemen, Yunus Emre; Rodríguez-Caballero, Carlos Vladimir
A dynamic multi-level factor model with stationary or nonstationary global and regional factors is proposed. In the model, persistence in global and regional common factors as well as innovations allows for the study of fractional cointegrating relationships. Estimation of global and regional...
Patrick, Renee B.; Gibbs, John C.
2007-01-01
The authors addressed whether parental expression of disappointment should be included as a distinct factor in M. L. Hoffman's (2000) well-established typology of parenting styles (induction, love withdrawal, power assertion). Hoffman's 3-factor model, along with a more inclusive 4-factor model (induction, love withdrawal, power assertion, and…
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
Modelling impulsive factors for electronics and restaurant coupons’ e-store display
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.
Spatial aspects affecting acidification factors in European acidification modelling
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
Bayes factor covariance testing in item response models
Fox, J.P.; Mulder, J.; Sinharay, Sandip
2017-01-01
Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning
Bayes Factor Covariance Testing in Item Response Models
Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip
2017-01-01
Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning
The Meaning of Higher-Order Factors in Reflective-Measurement Models
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…
Cultural factors in a mobile phone adoption and usage model
CSIR Research Space (South Africa)
Van Biljon, J
2008-01-01
Full Text Available . Although the feature driven and usability focus carry value, it is not the full picture. There is also an alternative or wider perspective: mobile phone use is influenced by demographic, social, cultural, and contextual factors that complicate...
Cholesterol, Triglycerides, and the Five-Factor Model of Personality
Sutin, Angelina R.; Terracciano, Antonio; Deiana, Barbara; Uda, Manuela; Schlessinger, David; Lakatta, Edward G.; Costa, Paul T.
2010-01-01
Unhealthy lipid levels are among the leading controllable risk factors for coronary heart disease. To identify the psychological factors associated with dyslipidemia, this study investigates the personality correlates of cholesterol (total, LDL, and HDL) and triglycerides. A community-based sample (N=5,532) from Sardinia, Italy, had their cholesterol and triglyceride levels assessed and completed a comprehensive personality questionnaire, the NEO-PI-R. All analyses controlled for age, sex, BM...
Viederytė, Rasa; Didžiokas, Rimantas
2014-01-01
Paper analyses several cluster models on the basis of competitiveness: Nine-factor model, Double diamond model, Funnel model of cluster determinants, Destination Competitiveness and sustainability models, which are related to Porter’s Diamond model and concentrate to the classical one - adopt M. Porter’s Diamond model methodology to the evaluation of Lithuanian Maritime sector’s clustering on the basis of competitiveness. Despite the advances in cluster research, this model remains a complex ...
Factors accounting for youth suicide attempt in Hong Kong: a model building.
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.
Maximum Likelihood Dynamic Factor Modeling for Arbitrary "N" and "T" Using SEM
Voelkle, Manuel C.; Oud, Johan H. L.; von Oertzen, Timo; Lindenberger, Ulman
2012-01-01
This article has 3 objectives that build on each other. First, we demonstrate how to obtain maximum likelihood estimates for dynamic factor models (the direct autoregressive factor score model) with arbitrary "T" and "N" by means of structural equation modeling (SEM) and compare the approach to existing methods. Second, we go beyond standard time…
Albarracin, Dolores; Tannenbaum, Melanie B; Glasman, Laura R; Rothman, Alexander J
2010-12-01
Changing HIV-related behaviors requires addressing the individual, dyadic, and structural influences that shape them. This supplement of AIDS & Behavior presents frameworks that integrate these three influences on behavior. Concepts from these frameworks were selected to model the processes by which structural factors affect individual HIV-related behavior. In the Inclusion/Exclusion Model, material and symbolic inclusions and exclusions (sharing versus denying resources) regulate individuals' ability and motivation to detect, prevent, and treat HIV. Structural interventions create inclusions that increase one's ability or motivation to perform these behaviors or exclusions that hinder one's ability or motivation to execute counterproductive behaviors. The need to expand research regarding multilevel influences on HIV-related behavior is also discussed, particularly concerning further understanding of sustained behavior change and effective dissemination of evidence-based intervention strategies.
Copula Based Factorization in Bayesian Multivariate Infinite Mixture Models
Martin Burda; Artem Prokhorov
2012-01-01
Bayesian nonparametric models based on infinite mixtures of density kernels have been recently gaining in popularity due to their flexibility and feasibility of implementation even in complicated modeling scenarios. In economics, they have been particularly useful in estimating nonparametric distributions of latent variables. However, these models have been rarely applied in more than one dimension. Indeed, the multivariate case suffers from the curse of dimensionality, with a rapidly increas...
Stochastic factor model for electricity spot price-the case of the Nordic market
International Nuclear Information System (INIS)
Vehvilaeinen, Iivo; Pyykkoenen, Tuomas
2005-01-01
This paper presents a stochastic factor based approach to mid-term modeling of spot prices in deregulated electricity markets. The fundamentals affecting the spot price are modeled independently and a market equilibrium model combines them to form spot price. Main advantage of the model is the transparency of the generated prices because each underlying factor and the dynamics between factors can be modeled and studied in detail. Paper shows realistic numerical examples on the forerunner Scandinavian electricity market. The model is used to price an exotic electricity derivative
Stochastic factor model for electricity spot price - the case of the Nordic market
International Nuclear Information System (INIS)
Vehvilainen, I.; Pyykkoenen, T.
2005-01-01
This paper presents a stochastic factor based approach to mid-term modeling of spot prices in deregulated electricity markets. The fundamentals affecting the spot price are modeled independently and a market equilibrium model combines them to form spot price. Main advantage of the model is the transparency of the generated prices because each underlying factor and the dynamics between factors can be modeled and studied in detail. Paper shows realistic numerical examples on the forerunner Scandinavian electricity market. The model is used to price an exotic electricity derivative. (author)
Exploring key factors in online shopping with a hybrid model.
Chen, Hsiao-Ming; Wu, Chia-Huei; Tsai, Sang-Bing; Yu, Jian; Wang, Jiangtao; Zheng, Yuxiang
2016-01-01
Nowadays, the web increasingly influences retail sales. An in-depth analysis of consumer decision-making in the context of e-business has become an important issue for internet vendors. However, factors affecting e-business are complicated and intertwined. To stimulate online sales, understanding key influential factors and causal relationships among the factors is important. To gain more insights into this issue, this paper introduces a hybrid method, which combines the Decision Making Trial and Evaluation Laboratory (DEMATEL) with the analytic network process, called DANP method, to find out the driving factors that influence the online business mostly. By DEMATEL approach the causal graph showed that "online service" dimension has the highest degree of direct impact on other dimensions; thus, the internet vendor is suggested to made strong efforts on service quality throughout the online shopping process. In addition, the study adopted DANP to measure the importance of key factors, among which "transaction security" proves to be the most important criterion. Hence, transaction security should be treated with top priority to boost the online businesses. From our study with DANP approach, the comprehensive information can be visually detected so that the decision makers can spotlight on the root causes to develop effectual actions.
Moderating Factors of Video-Modeling with Other as Model: A Meta-Analysis of Single-Case Studies
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…
Factorization of standard model cross sections at ultrahigh energy
Chien, Yang-Ting; Li, Hsiang-nan
2018-03-01
The factorization theorem for organizing multiple electroweak boson emissions at future colliders with energy far above the electroweak scale is formulated. Taking the inclusive muon-pair production in electron-positron collisions as an example, we argue that the summation over isospins is demanded for constructing the universal distributions of leptons and gauge bosons in an electron. These parton distributions are shown to have the same infrared structure in the phases of broken and unbroken electroweak symmetry, an observation consistent with the Goldstone equivalence theorem. The electroweak factorization of processes involving protons is sketched, with an emphasis on the subtlety of the scalar distributions. This formalism, in which electroweak shower effects are handled from the viewpoint of factorization theorem for the first time, is an adequate framework for collider physics at ultra high energy.
Adolescent Girls' Self-Concept and Its Related Factors Based on Roy Adaptation Model
M. Basiri Moghadam; SH. Khosravan; L. Sadeghmoghadam; N. Ebrahimi Senoo
2017-01-01
Aims: One of the most important factors of individual health in the adolescents is the self-concept. As a nursing model, the Roy adaptation model mainly investigates the factor. The aim of the study was to investigate the self-concept and its related factors in the adolescent girls in Gonabad Township, based on the Roy adaptation model. Instrument & Methods: In the descriptive cross-sectional study, 270 adolescent girls were studied in Gonabad Township, Iran, in 2015. The subjects were s...
Form factors and structure functions of hadrons in parton model
International Nuclear Information System (INIS)
Volkonskij, N.Yu.
1979-01-01
The hadron charge form factors and their relation to the deep-inelastic lepton-production structure functions in the regions of asymptotically high and small momentum transfer Q 2 are studied. The nucleon and pion charge radii are calculated. The results of calculations are in good agreement with the experimental data. The K- and D-meson charge radii are estimated. In the region of asymptotically high Q 2 the possibility of Drell-Yan-West relation violation is analyzed. It is shown, that for pseudoscalar mesons this relation is violated. The relation between the proton and neutron form factor asymptotics is obtained
The Conceptual Framework of Factors Affecting Shared Mental Model
Lee, Miyoung; Johnson, Tristan; Lee, Youngmin; O'Connor, Debra; Khalil, Mohammed
2004-01-01
Many researchers have paid attention to the potentiality and possibility of the shared mental model because it enables teammates to perform their job better by sharing team knowledge, skills, attitudes, dynamics and environments. Even though theoretical and experimental evidences provide a close relationship between the shared mental model and…
First International Workshop on Human Factors in Modeling (HuFaMo 2015)
DEFF Research Database (Denmark)
Störrle, Harald; Chaudron, Michel R. V.; Amaral, Vasco
2015-01-01
human factors in modeling. Our goal is to improve the state of the science and professionalism in empirical research in the Model Based Engineering community. Typical examples of research questions might consider the usability of a certain approach, such as a method or language, or the emotional states......Modeling is a human-intensive enterprise. As such, many research questions related to modeling can only be answered by empirical studies employing human factors. The International Workshop Series on Human Factors in Modeling (HuFaMo) is dedicated to the discussion of empirical research involving...... or personal judgements of modelers. While concerned with foundations and framework support for modeling, the community has been somehow neglecting the issue of human factors in this context. There is a growing need from the community concerned with quality factors to understand the best practices...
International Nuclear Information System (INIS)
Jiang Jianjun; Zhang Li; Wang Yiqun; Zhang Kun; Peng Yuyuan; Zhou Cheng
2012-01-01
Facing the shortcomings of the traditional cognitive factors and cognitive model, this paper presents a Bayesian networks cognitive reliability model by taking the main control room as a reference background and human factors as the key points. The model mainly analyzes the cognitive reliability affected by the human factors, and for the cognitive node and influence factors corresponding to cognitive node, a series of methods and function formulas to compute the node cognitive reliability is proposed. The model and corresponding methods can be applied to the evaluation of cognitive process for the nuclear power plant operators and have a certain significance for the prevention of safety accidents in nuclear power plants. (authors)
Pion form factor within QCD instanton vacuum model
International Nuclear Information System (INIS)
Dorokhov, A.E.
1997-01-01
Instanton induced pion wave function is constructed. It provides an intrinsic k 1 dependence which suppress soft virtual one-gluon exchanges and thus legitimate the perturbative QCD (pQCD) calculations of the pion electromagnetic form factor in the region of momentum transfers above the scale. (author)
The Modeling of Factors That Influence Coast Guard Manpower Requirements
2014-12-01
applications, and common data warehouses needed to fully develop an effective and efficient manpower requirements engineering and management program. The... manpower requirements determination ensures a ready force, and safe and effective mission execution. Shortage or excess of manpower is the catalyst...FACTORS THAT INFLUENCE COAST GUARD MANPOWER REQUIREMENTS by Kara M. Lavin December 2014 Thesis Advisor: Ronald E. Giachetti Co-Advisor
On Modeling and Analyzing Cost Factors in Information Systems Engineering
Mutschler, B.B.; Reichert, M.U.
Introducing enterprise information systems (EIS) is usually associated with high costs. It is therefore crucial to understand those factors that determine or influence these costs. Though software cost estimation has received considerable attention during the last decades, it is difficult to apply
A MATHEMATICAL MODEL FOR ASSESSING THE FACTORING ACTIVITY
Directory of Open Access Journals (Sweden)
Madalina Radoi
2013-11-01
Full Text Available Originally–being over 4,000 years old–factoring was first used in the fertile territory of old Mesopotamia at a time when the famous Code of Hammurabi was drawn up. However, many years passed until the British colonists started to use it on a large scale at a time when the metropolis would pay them sums of money for the merchandise that colonists sent to the old continent until they collected the invoices.In Romania factoring started to play a major role in financial operations for it led to the increase of liquidities on the market.According to the Romanian legislation, factoring is a contract concluded between a party known as “the client”, which supplies merchandise or provides services, and a banking institution or specialized financial institution known as “the factor”, whereby the latter ensures the financing source, collects the receivables and protects credit risks, while the client assigns to the factor the receivables resulting from the sale of goods or the provision of services to third parties.
Meaningful Causal Model among Psycho-sociological Factors on ...
African Journals Online (AJOL)
Intervention programmes should be designed on the aforementioned factors so as to enhance the psychological well-being of the hearing impaired adolescents in southwest Nigeria. Keywords: Psychological well-being,, Age, Self-concept, Hearing impairment, Self-efficacy. Gender & Behaviour, 10(2), December 2012 ...
Defense of single-factor models of population regulation
International Nuclear Information System (INIS)
Tamarin, R.H.
1978-01-01
I reject a multifactorial approach to the study of the regulation of animal populations for two reasons. First, a mechanism suggested by Chitty, that has natural selection at its base, has not been adequately tested. Second, the multifactorial model suggested by Lidicker is untestable because of its vagueness. As a middle ground, I suggest a model that has natural selection as its mechanism, but is multifacturial because it allows many parameters to be the selective agents. I particularly emphasize prediction and selective dispersal. Methods to test this model are suggested
The Influence Factor Model for the Popularity of Mobile Phone without Considering the Price Factor
Long, Hongming; Peng, Diefei; Wu, Hailin; Yang, Zihui
2018-01-01
Based on the statistical data like economic development, social development, population indicator and so on, this paper establishes the linear regression model which influences the popularity rate of mobile phone users.
Partial-factor Energy Efficiency Model of Indonesia
Nugroho Fathul; Syaifudin Noor
2018-01-01
This study employs the partial-factor energy efficiency to reveal the relationships between energy efficiency and the consumption of both, the renewable energy and non-renewable energy in Indonesia. The findings confirm that consumption of non-renewable energy will increase the inefficiency in energy consumption. On the other side, the use of renewable energy will increase the energy efficiency in Indonesia. As the result, the Government of Indonesia may address this issue by providing more s...
Model of key success factors for Business Intelligence implementation
Peter Mesaros; Tomas Mandicak; Daniela Mackova; Stefan Carnicky; Martina Habinakova; Marcela Spisakova
2016-01-01
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 a...
A New European Slope Length and Steepness Factor (LS-Factor for Modeling Soil Erosion by Water
Directory of Open Access Journals (Sweden)
Panos Panagos
2015-04-01
Full Text Available The Universal Soil Loss Equation (USLE model is the most frequently used model for soil erosion risk estimation. Among the six input layers, the combined slope length and slope angle (LS-factor has the greatest influence on soil loss at the European scale. The S-factor measures the effect of slope steepness, and the L-factor defines the impact of slope length. The combined LS-factor describes the effect of topography on soil erosion. The European Soil Data Centre (ESDAC developed a new pan-European high-resolution soil erosion assessment to achieve a better understanding of the spatial and temporal patterns of soil erosion in Europe. The LS-calculation was performed using the original equation proposed by Desmet and Govers (1996 and implemented using the System for Automated Geoscientific Analyses (SAGA, which incorporates a multiple flow algorithm and contributes to a precise estimation of flow accumulation. The LS-factor dataset was calculated using a high-resolution (25 m Digital Elevation Model (DEM for the whole European Union, resulting in an improved delineation of areas at risk of soil erosion as compared to lower-resolution datasets. This combined approach of using GIS software tools with high-resolution DEMs has been successfully applied in regional assessments in the past, and is now being applied for first time at the European scale.
Factor Structure and Market Integration under Two-Factor Monopolistic Competition Model
Directory of Open Access Journals (Sweden)
Evgeny Vladimirovich Zhelobodko
2013-09-01
Full Text Available The authors study the impact of trade liberalization on the market of a differentiated good and consumers’ welfare. The economy involves two factors of production: labor and capital. The researchers find that consumers always gain from trade liberalization. The article also establishes that the behavior of equilibrium price is independent of factor endowments’ structure in the countries involved into trade. The equilibrium price decreases (increases, remains unchanged under trade liberalization if and only if the inverse demand elasticity is increasing (decreasing, constant with respect to the individual consumption level. Furthermore, firms’ size which are measured as output increases (decreases when autarky changes to free trade if and only if the country is relatively richer (poorer in capital than its trading partner, regardless of the demand-side properties of the economy. Finally, the behavior of capital price (which equals firms’ profits in equilibrium is more complicated in the general case, but can be fully characterized for two limiting cases: (i when the structure of factor endowments in both countries is the same, and (ii when the Foreign country is a periphery country, i.e. it has zero endowment of capital
Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors
DEFF Research Database (Denmark)
Halbleib, Roxana; Voev, Valeri
2011-01-01
This paper analyzes the forecast accuracy of the multivariate realized volatility model introduced by Chiriac and Voev (2010), subject to different degrees of model parametrization and economic evaluation criteria. Bymodelling the Cholesky factors of the covariancematrices, the model generates......, regardless of the type of utility function or return distribution, would be better-off from using this model than from using some standard approaches....
Modeling lichen communities : ecological key factors in a changing environment
Lopes, Pedro António Pinho, 1976-
2010-01-01
Tese de doutoramento, Biologia (Ecologia), Universidade de Lisboa, Faculdade de Ciências, 2010 O fenómeno das alterações globais influencia o funcionamento de muitos dos sistemas planetários. Embora os factores ambientais associados a esse fenómeno funcionem numa escala global, os seus efeitos nos ecossistemas têm de ser estudados localmente. Este estudo é complexo não só pela necessidade de obter informação com uma elevada resolução espacial, mas também pela dificuldade de estarmos a trab...
Factors affecting GEBV accuracy with single-step Bayesian models.
Zhou, Lei; Mrode, Raphael; Zhang, Shengli; Zhang, Qin; Li, Bugao; Liu, Jian-Feng
2018-01-01
A single-step approach to obtain genomic prediction was first proposed in 2009. Many studies have investigated the components of GEBV accuracy in genomic selection. However, it is still unclear how the population structure and the relationships between training and validation populations influence GEBV accuracy in terms of single-step analysis. Here, we explored the components of GEBV accuracy in single-step Bayesian analysis with a simulation study. Three scenarios with various numbers of QTL (5, 50, and 500) were simulated. Three models were implemented to analyze the simulated data: single-step genomic best linear unbiased prediction (GBLUP; SSGBLUP), single-step BayesA (SS-BayesA), and single-step BayesB (SS-BayesB). According to our results, GEBV accuracy was influenced by the relationships between the training and validation populations more significantly for ungenotyped animals than for genotyped animals. SS-BayesA/BayesB showed an obvious advantage over SSGBLUP with the scenarios of 5 and 50 QTL. SS-BayesB model obtained the lowest accuracy with the 500 QTL in the simulation. SS-BayesA model was the most efficient and robust considering all QTL scenarios. Generally, both the relationships between training and validation populations and LD between markers and QTL contributed to GEBV accuracy in the single-step analysis, and the advantages of single-step Bayesian models were more apparent when the trait is controlled by fewer QTL.
EcoWellness: The Missing Factor in Holistic Wellness Models
Reese, Ryan F.; Myers, Jane E.
2012-01-01
A growing body of multidisciplinary literature has delineated the benefits that natural environments have on physical and mental health. Current wellness models in counseling do not specifically address the impact of nature on wellness or how the natural world can be integrated into counseling. The concept of EcoWellness is presented as the…
Factor Analysis of Drawings: Application to College Student Models of the Greenhouse Effect
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,…
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...
Using a knowledge elicitation method to specify the business model of a human factors organization
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
Using a knowledge elicitation method to specify the business model of a human factors organization.
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
The effects of motivational factors on car use : a multidisciplinary modelling approach
Steg, L; Geurs, K; Ras, M
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
Generalized Efficient Inference on Factor Models with Long-Range Dependence
DEFF Research Database (Denmark)
Ergemen, Yunus Emre
. Short-memory dynamics are allowed in the common factor structure and possibly heteroskedastic error term. In the estimation, a generalized version of the principal components (PC) approach is proposed to achieve efficiency. Asymptotics for efficient common factor and factor loading as well as long......A dynamic factor model is considered that contains stochastic time trends allowing for stationary and nonstationary long-range dependence. The model nests standard I(0) and I(1) behaviour smoothly in common factors and residuals, removing the necessity of a priori unit-root and stationarity testing...
Cholesterol, Triglycerides, and the Five-Factor Model of Personality
Sutin, Angelina R.; Terracciano, Antonio; Deiana, Barbara; Uda, Manuela; Schlessinger, David; Lakatta, Edward G.; Costa, Paul T.
2010-01-01
Unhealthy lipid levels are among the leading controllable risk factors for coronary heart disease. To identify the psychological factors associated with dyslipidemia, this study investigates the personality correlates of cholesterol (total, LDL, and HDL) and triglycerides. A community-based sample (N=5,532) from Sardinia, Italy, had their cholesterol and triglyceride levels assessed and completed a comprehensive personality questionnaire, the NEO-PI-R. All analyses controlled for age, sex, BMI, smoking, drinking, hypertension, and diabetes. Low Conscientiousness and traits related to impulsivity were associated with lower HDL cholesterol and higher triglycerides. Compared to the lowest 10%, those who scored in top 10% on Impulsivity had a 2.5 times greater risk of exceeding the clinical threshold for elevated triglycerides (OR=2.51, CI=1.56–4.07). In addition, sex moderated the association between trait depression (a component of Neuroticism) and HDL cholesterol, such that trait depression was associated with lower levels of HDL cholesterol in women but not men. When considering the connection between personality and health, unhealthy lipid profiles may be one intermediate biomarker between personality and morbidity and mortality. PMID:20109519
Separating form factor and nuclear model effects in quasielastic neutrino-nucleus scattering
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.
A Two-Factor Autoregressive Moving Average Model Based on Fuzzy Fluctuation Logical Relationships
Directory of Open Access Journals (Sweden)
Shuang Guan
2017-10-01
Full Text Available Many of the existing autoregressive moving average (ARMA forecast models are based on one main factor. In this paper, we proposed a new two-factor first-order ARMA forecast model based on fuzzy fluctuation logical relationships of both a main factor and a secondary factor of a historical training time series. Firstly, we generated a fluctuation time series (FTS for two factors by calculating the difference of each data point with its previous day, then finding the absolute means of the two FTSs. We then constructed a fuzzy fluctuation time series (FFTS according to the defined linguistic sets. The next step was establishing fuzzy fluctuation logical relation groups (FFLRGs for a two-factor first-order autoregressive (AR(1 model and forecasting the training data with the AR(1 model. Then we built FFLRGs for a two-factor first-order autoregressive moving average (ARMA(1,m model. Lastly, we forecasted test data with the ARMA(1,m model. To illustrate the performance of our model, we used real Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX and Dow Jones datasets as a secondary factor to forecast TAIEX. The experiment results indicate that the proposed two-factor fluctuation ARMA method outperformed the one-factor method based on real historic data. The secondary factor may have some effects on the main factor and thereby impact the forecasting results. Using fuzzified fluctuations rather than fuzzified real data could avoid the influence of extreme values in historic data, which performs negatively while forecasting. To verify the accuracy and effectiveness of the model, we also employed our method to forecast the Shanghai Stock Exchange Composite Index (SHSECI from 2001 to 2015 and the international gold price from 2000 to 2010.
Scrub Typhus Incidence Modeling with Meteorological Factors in South Korea.
Kwak, Jaewon; Kim, Soojun; Kim, Gilho; Singh, Vijay P; Hong, Seungjin; Kim, Hung Soo
2015-06-29
Since its recurrence in 1986, scrub typhus has been occurring annually and it is considered as one of the most prevalent diseases in Korea. Scrub typhus is a 3rd grade nationally notifiable disease that has greatly increased in Korea since 2000. The objective of this study is to construct a disease incidence model for prediction and quantification of the incidences of scrub typhus. Using data from 2001 to 2010, the incidence Artificial Neural Network (ANN) model, which considers the time-lag between scrub typhus and minimum temperature, precipitation and average wind speed based on the Granger causality and spectral analysis, is constructed and tested for 2011 to 2012. Results show reliable simulation of scrub typhus incidences with selected predictors, and indicate that the seasonality in meteorological data should be considered.
Scrub Typhus Incidence Modeling with Meteorological Factors in South Korea
Directory of Open Access Journals (Sweden)
Jaewon Kwak
2015-06-01
Full Text Available Since its recurrence in 1986, scrub typhus has been occurring annually and it is considered as one of the most prevalent diseases in Korea. Scrub typhus is a 3rd grade nationally notifiable disease that has greatly increased in Korea since 2000. The objective of this study is to construct a disease incidence model for prediction and quantification of the incidences of scrub typhus. Using data from 2001 to 2010, the incidence Artificial Neural Network (ANN model, which considers the time-lag between scrub typhus and minimum temperature, precipitation and average wind speed based on the Granger causality and spectral analysis, is constructed and tested for 2011 to 2012. Results show reliable simulation of scrub typhus incidences with selected predictors, and indicate that the seasonality in meteorological data should be considered.
Factoring variations in natural images with deep Gaussian mixture models
van den Oord, Aäron; Schrauwen, Benjamin
2014-01-01
Generative models can be seen as the swiss army knives of machine learning, as many problems can be written probabilistically in terms of the distribution of the data, including prediction, reconstruction, imputation and simulation. One of the most promising directions for unsupervised learning may lie in Deep Learning methods, given their success in supervised learning. However, one of the cur- rent problems with deep unsupervised learning methods, is that they often are harder to scale. As ...
Scale Factor Study for 1:30 Local Scour Model
2016-08-01
establishes the worst- case scour depth for the current bridge configuration and the proposed pier nose extension. INTRODUCTION : Extensive research has been...used in the general physical model. A flat test section, approximately 32 ft long and 34–45 ft wide, was molded to a uniform elevation . Stilling...discharge calculation from the flow uniformity checks. The water surface elevation was controlled with the adjustable lift gate at the downstream
Dynamic structure factor for liquid He4 and quantum lattice model
International Nuclear Information System (INIS)
Lee, M.H.
1975-01-01
It has been realized for some time now that the quantum lattice model (or the anisotropic Heisenberg antiferromagnetic model) is a useful model for studying the properties of quantum liquids especially near the lambda transition. The static critical values calculated from the quantum lattice model are in good agreement with the observed values. Furthermore, it was shown recently that there are collective modes in the quantum lattice model which are equivalent to the plasmons. Hence, it would seem to be interesting to study the dynamic structure factor for the quantum lattice model and to make a comparison with experiment. Work on the dynamic structure factor is reported here. (Auth.)
Reciprocal burnout model: Interconnectedness of interpersonal and intrapersonal factors
Directory of Open Access Journals (Sweden)
Andreja Pšeničny
2007-01-01
Full Text Available Burnout can be described as chronic state of extreme psychophysical and emotional exhaustion. Burning out is a stage process consisting of: the stage of exhaustion, the stage of captivity and the final stage – adrenal burnout. Adrenal burnout syndrome (ABS is the final stage of burning out process, resulting in a functional blocade of hypothalamic-pituitary-adrenal axis which causes secondary cortisol insufficiency. Even though they share similar symptoms, burnout and depression are two different types of disorder. They differ mainly in basic cortisol levels and self-esteem. Researchers tend to link the burnout syndrome and environmental stress (interpersonal causes. Recently, some of them found connection between burnout syndrome and personality traits (intrapersonal causes. Reciprocal burnout model links both causes. It shows that in the same circumstances only a few people suffer from adrenal burnout syndrome. It states that personal characteristics are one of the main causes why people suffering from burnout syndrome enroll in nonreciprocal personal and professional relations. Socialization process plays an important role in development of personality traits. The core of the reciprocal burnout model consists of one's attitude towards his or her basic needs' fulfillment, personal system of values, and correlation between fulfillment of basic needs (energy accumulation and burning out process (energy consumption. Reciprocal burnout model is opening a series of questions, concerning the connection between personality traits, life satisfaction and personal values, and burnout syndrome risk behavior, as well as the influence of whole life circumstances on burning out process.
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...
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.
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.
Factoring vs linear modeling in rate estimation: a simulation study of relative accuracy.
Maldonado, G; Greenland, S
1998-07-01
A common strategy for modeling dose-response in epidemiology is to transform ordered exposures and covariates into sets of dichotomous indicator variables (that is, to factor the variables). Factoring tends to increase estimation variance, but it also tends to decrease bias and thus may increase or decrease total accuracy. We conducted a simulation study to examine the impact of factoring on the accuracy of rate estimation. Factored and unfactored Poisson regression models were fit to follow-up study datasets that were randomly generated from 37,500 population model forms that ranged from subadditive to supramultiplicative. In the situations we examined, factoring sometimes substantially improved accuracy relative to fitting the corresponding unfactored model, sometimes substantially decreased accuracy, and sometimes made little difference. The difference in accuracy between factored and unfactored models depended in a complicated fashion on the difference between the true and fitted model forms, the strength of exposure and covariate effects in the population, and the study size. It may be difficult in practice to predict when factoring is increasing or decreasing accuracy. We recommend, therefore, that the strategy of factoring variables be supplemented with other strategies for modeling dose-response.
Predisposing, precipitating and perpetuating factors and the common sense model of illness
DEFF Research Database (Denmark)
Carstensen, Tina; Kasch, Helge; Frostholm, Lisbeth
2017-01-01
Background: Various predisposing, precipitating and perpetuating factors are found to be associated with development of persistent symptoms and disability after whiplash trauma. According to the commonsense model of illness, people use commonsense knowledge to develop individual illness models when...... facing health threat. Question: Can we use the common-sense model as a unifying model to encompass the impact of predisposing, precipitating, and perpetuating factors in the development of chronic whiplash? Looking into specific factors and their interaction: Do illness perceptions mediate the effect...... of precollision sick leave on chronic whiplash? Methods: This presentation will integrate findings from research on predisposing, precipitating, perpetuating factors that are associated with poor outcome after whiplash trauma and propose the common-sense model as a unifying model. Data from a study including 740...
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.
A Key Factor of the DCF Model Coherency
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Piotr Adamczyk
2017-04-01
Full Text Available Aim/purpose - The aim of this paper is to provide economically justified evidence that the business value calculated by income valuation methods is the same, regardless of the type of cash flow used in the valuation algorithm. Design/methodology/approach - The evidence was arrived at using free cash flow to equity (FCFE, debt (FCFD and firm (FCFF. The article draws attention to the FCFF method's particular popularity in income valuation, based on analysts' practice. It shows an overview of various approaches to determine the capital structure in the formula for WACC, both in practice and theory. Finally, it examines an empirical example with the authors' own derivations and postulates. Findings - The conclusion drawn from the conducted analysis is that the key to the reconciliation process, and thus DCF model coherency, is to apply the appropriate method of capital structure estimation during the calculation of the weighted average cost of capital (WACC. This capital structure will henceforth be referred to as 'income weights'. Research implications/limitations - It should be noted that the obtained compliance of valuation results does not imply that the income valuation becomes an objective way of determining business value. It still remains subjective. Originality/value/contribution - According to the presented approach, the DCF model's subjectivism is limited to the forecasts. The rest is the algorithm which, based on the principles of mathematics, should be used in the same way in every situation.
DEFF Research Database (Denmark)
Larsen, Malte Selch; Juul, Rasmus Vestergaard; Groth, Andreas Velsing
2018-01-01
activated factor VII (rFVIIa) and recombinant factor VIII (rFVIII) in several experimental animal models using population PK modelling, and apply a simulation-based approach to evaluate how well the developed animal population PK models predict human PK. PK models were developed for rFVIIa and r...
Aspect-Aware Latent Factor Model: Rating Prediction with Ratings and Reviews
Cheng, Zhiyong; Ding, Ying; Zhu, Lei; Kankanhalli, Mohan
2018-01-01
Although latent factor models (e.g., matrix factorization) achieve good accuracy in rating prediction, they suffer from several problems including cold-start, non-transparency, and suboptimal recommendation for local users or items. In this paper, we employ textual review information with ratings to tackle these limitations. Firstly, we apply a proposed aspect-aware topic model (ATM) on the review text to model user preferences and item features from different aspects, and estimate the aspect...
Trichotillomania and personality traits from the five-factor model
Directory of Open Access Journals (Sweden)
Nancy J. Keuthen
2015-01-01
Full Text Available Objective:To examine whether personality traits have predictive validity for trichotillomania (TTM diagnosis, pulling severity and control, and hair pulling style.Methods:In study 1, logistic regression was used with TTM cases (n=54 and controls (n=25 to determine if NEO Five-Factor Inventory (NEO-FFI personality domains predicted TTM case vs. control classification. In study 2, hierarchical multiple regression was used with TTM cases (n=164 to determine whether NEO-FFI personality domains predicted hair pulling severity and control as well as focused and automatic pulling styles.Results:TTM case vs. control status was predicted by NEO-FFI neuroticism. Every 1-point increase in neuroticism scores resulted in a 10% greater chance of TTM diagnosis. Higher neuroticism, higher openness, and lower agreeableness were associated with greater pulling severity. Higher neuroticism was also associated with less control over hair pulling. Higher neuroticism and lower openness were associated with greater focused pulling. None of the personality domains predicted automatic hair pulling.Conclusions:Personality traits, especially neuroticism, can predict TTM diagnosis, hair pulling severity and control, and the focused style of pulling. None of the personality traits predicted automatic pulling. Longitudinal studies are needed to determine whether personality variables predispose to TTM onset, impact disorder course, and/or result from hair pulling behavior.
New JLS-Factor Model versus the Standard JLS Model: A Case Study on Chinese Stock Bubbles
Directory of Open Access Journals (Sweden)
Zongyi Hu
2017-01-01
Full Text Available In this paper, we extend the Johansen-Ledoit-Sornette (JLS model by introducing fundamental economic factors in China (including the interest rate and deposit reserve rate and the historical volatilities of targeted and US equity indices into the original model, which is a flexible tool to detect bubbles and predict regime changes in financial markets. We then derive a general method to incorporate these selected factors in addition to the log-periodic power law signature of herding and compare the prediction accuracy of the critical time between the original and the new JLS models (termed the JLS-factor model by applying these two models to fit two well-known Chinese stock indices in three bubble periods. The results show that the JLS-factor model with Chinese characteristics successfully depicts the evolutions of bubbles and “antibubbles” and constructs efficient end-of-bubble signals for all bubbles in Chinese stock markets. In addition, the results of standard statistical tests demonstrate the excellent explanatory power of these additive factors and confirm that the new JLS model provides useful improvements over the standard JLS model.
Modeling the Factors Impacting Pesticide Concentrations in Groundwater Wells
DEFF Research Database (Denmark)
Aisopou, Angeliki; Binning, Philip John; Albrechtsen, Hans-Jørgen
2015-01-01
This study examines the effect of pumping, hydrogeology, and pesticide characteristics on pesticide concentrations in production wells using a reactive transport model in two conceptual hydrogeologic systems; a layered aquifer with and without a stream present. The pumping rate can significantly...... affect the pesticide breakthrough time and maximum concentration at the well. The effect of the pumping rate on the pesticide concentration depends on the hydrogeology of the aquifer; in a layered aquifer, a high pumping rate resulted in a considerably different breakthrough than a low pumping rate......, while in an aquifer with a stream the effect of the pumping rate was insignificant. Pesticide application history and properties have also a great impact on the effect of the pumping rate on the concentration at the well. The findings of the study show that variable pumping rates can generate temporal...
A Study on Influencing Factors of Knowledge Management Systems Adoption: Models Comparison Approach
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...
Skyrme-model πNN form factor and nucleon-nucleon interaction
International Nuclear Information System (INIS)
Holzwarth, G.; Machleidt, R.
1997-01-01
We apply the strong πNN form factor, which emerges from the Skyrme model, in the two-nucleon system using a one-boson-exchange (OBE) model for the nucleon-nucleon (NN) interaction. Deuteron properties and phase parameters of NN scattering are reproduced well. In contrast to the form factor of monopole shape that is traditionally used in OBE models, the Skyrme form factor leaves low-momentum transfers essentially unaffected while it suppresses the high-momentum region strongly. It turns out that this behavior is very appropriate for models of the NN interaction and makes it possible to use a soft pion form factor in the NN system. As a consequence, the πN and the NN systems can be described using the same πNN form factor, which is impossible with the monopole. copyright 1997 The American Physical Society
Hida, Hirotake; Mouri, Akihiro; Noda, Yukihiro
2013-01-01
Schizophrenia is a multifactorial psychiatric disorder in which both genetic and environmental factors play a role. Genetic [e.g., Disrupted-in-schizophrenia 1 (DISC1), Neuregulin-1 (NRG1)] and environmental factors (e.g., maternal viral infection, obstetric complications, social stress) may act during the developmental period to increase the incidence of schizophrenia. In animal models, interactions between susceptibility genes and the environment can be controlled in ways not possible in humans; therefore, such models are useful for investigating interactions between or within factors in the pathogenesis and pathophysiology of schizophrenia. We provide an overview of schizophrenic animal models investigating interactions between or within factors. First, we reviewed gene-environment interaction animal models, in which schizophrenic candidate gene mutant mice were subjected to perinatal immune activation or adolescent stress. Next, environment-environment interaction animal models, in which mice were subjected to a combination of perinatal immune activation and adolescent administration of drugs, were described. These animal models showed interaction between or within factors; behavioral changes, which were obscured by each factor, were marked by interaction of factors and vice versa. Appropriate behavioral approaches with such models will be invaluable for translational research on novel compounds, and also for providing insight into the pathogenesis and pathophysiology of schizophrenia.
Kleinlogel, E. P.; Dietz, J.
2015-01-01
Gender inequalities remain an issue in our society and particularly in the workplace. Several factors can explain this gender difference in top-level managerial positions such as career ambitions but also biases against women. In our chapter, we propose a model explaining why gender inequalities and particularly discrimination against women is still present in our societies despite social norms and existing legislation on gender equality. To this purpose, we review research on discrimination ...
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)
Khosravi, Yahya; Asilian-Mahabadi, Hassan; Hajizadeh, Ebrahim; Hassanzadeh-Rangi, Narmin; Bastani, Hamid; Khavanin, Ali; Mortazavi, Seyed Bagher
2014-01-01
There can be little doubt that the construction is the most hazardous industry in the worldwide. This study was designed to modeling the factors affecting unsafe behavior from the perspective of safety supervisors. The qualitative research was conducted to extract a conceptual model. A structural model was then developed based on a questionnaire survey (n=266) by two stage Structural Equation Model (SEM) approach. An excellent confirmed 12-factors structure explained about 62% of variances unsafe behavior in the construction industry. A good fit structural model indicated that safety climate factors were positively correlated with safety individual factors (Pconstruction workers' engagement in safe or unsafe behavior. In order to improve construction safety performance, more focus on the workplace condition is required.
Factors Models of Scrum Adoption in the Software Development Process: A Systematic Literature Review
Directory of Open Access Journals (Sweden)
Marilyn Sihuay
2018-05-01
Full Text Available (Background The adoption of Agile Software Development (ASD, in particular Scrum, has grown significantly since its introduction in 2001. However, in Lima, many ASDs implementations have been not suitable (uncompleted or inconsistent, thus losing benefits obtainable by this approach and the critical success factors in this context are unknown. (Objective To analyze factors models used in the evaluation of the adoption of ASDs, as these factors models can contribute to explaining the success or failure of these adoptions. (Method In this study we used a systematic literature review. (Result Ten models have been identified; their similarities and differences are presented. (Conclusion Each model identified consider different factors, however some of them are shared by five of these models, such as team member attributes, engaging customer, customer collaboration, experience and work environment.
Particle size - An important factor in environmental consequence modeling
International Nuclear Information System (INIS)
Yuan, Y.C.; MacFarlane, D.
1991-01-01
Most available environmental transport and dosimetry codes for radiological consequence analysis are designed primarily for estimating dose and health consequences to specific off-site individuals as well as the population as a whole from nuclear facilities operating under either normal or accident conditions. Models developed for these types of analyses are generally based on assumptions that the receptors are at great distances (several kilometers), and the releases are prolonged and filtered. This allows the use of simplified approaches such as averaged meteorological conditions and the use of a single (small) particle size for atmospheric transport and dosimetry analysis. Source depletion from particle settling, settle-out, and deposition is often ignored. This paper estimates the effects of large particles on the resulting dose consequences from an atmospheric release. The computer program AI-RISK has been developed to perform multiparticle-sized atmospheric transport, dose, and pathway analyses for estimating potential human health consequences from the accidental release of radioactive materials. The program was originally developed to facilitate comprehensive analyses of health consequences, ground contamination, and cleanup associated with possible energetic chemical reactions in high-level radioactive waste (HLW) tanks at a US Department of Energy site
The HEXACO and Five-Factor Models of Personality in Relation to RIASEC Vocational Interests
McKay, Derek A.; Tokar, David M.
2012-01-01
The current study extended the empirical research on the overlap of vocational interests and personality by (a) testing hypothesized relations between RIASEC interests and the personality dimensions of the HEXACO model, and (b) exploring the HEXACO personality model's predictive advantage over the five-factor model (FFM) in capturing RIASEC…
The Multi-state Latent Factor Intensity Model for Credit Rating Transitions
Koopman, S.J.; Lucas, A.; Monteiro, A.
2008-01-01
A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic factors. The model has a generalized semi-Markov structure designed to accommodate many of the
WALS estimation and forecasting in factor-based dynamic models with an application to Armenia
Poghosyan, K.; Magnus, J.R.
2012-01-01
Two model averaging approaches are used and compared in estimating and forecasting dynamic factor models, the well-known Bayesian model averaging (BMA) and the recently developed weighted average least squares (WALS). Both methods propose to combine frequentist estimators using Bayesian weights. We
Critical Factors Analysis for Offshore Software Development Success by Structural Equation Modeling
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.
Modelling of Safety Factors in the Design of GRP Composite Products
DEFF Research Database (Denmark)
Babu, B.J.C.; Prabhakaran, R.T. Durai; Lystrup, Aage
2010-01-01
as independent, while in real applications these factors may interact/influence each other. Following the concept developed by the authors, a simple graph theoretic model has been used to determine overall factor of safety. This is described with the help of an example and it has been demonstrated......An attempt has been made in this paper to arrive at the safety factor design of glass fibre reinforced polymer (GRP) composite products using graph theoretic model. In the conventional design and recommendations of the standards, these design factors affecting properties have been considered...
Niedhammer, I; Siegrist, J
1998-11-01
The effect of psychosocial factors at work on health, especially cardiovascular health, has given rise to growing concern in occupational epidemiology over the last few years. Two theoretical models, Karasek's model and the Effort-Reward Imbalance model, have been developed to evaluate psychosocial factors at work within specific conceptual frameworks in an attempt to take into account the serious methodological difficulties inherent in the evaluation of such factors. Karasek's model, the most widely used model, measures three factors: psychological demands, decision latitude and social support at work. Many studies have shown the predictive effects of these factors on cardiovascular diseases independently of well-known cardiovascular risk factors. More recently, the Effort-Reward Imbalance model takes into account the role of individual coping characteristics which was neglected in the Karasek model. The effort-reward imbalance model focuses on the reciprocity of exchange in occupational life where high-cost/low-gain conditions are considered particularly stressful. Three dimensions of rewards are distinguished: money, esteem and gratifications in terms of promotion prospects and job security. Some studies already support that high-effort/low reward-conditions are predictive of cardiovascular diseases.
On form factors of the conjugated field in the non-linear Schroedinger model
Energy Technology Data Exchange (ETDEWEB)
Kozlowski, K.K.
2011-05-15
Izergin-Korepin's lattice discretization of the non-linear Schroedinger model along with Oota's inverse problem provides one with determinant representations for the form factors of the lattice discretized conjugated field operator. We prove that these form factors converge, in the zero lattice spacing limit, to those of the conjugated field operator in the continuous model. We also compute the large-volume asymptotic behavior of such form factors in the continuous model. These are in particular characterized by Fredholm determinants of operators acting on closed contours. We provide a way of defining these Fredholm determinants in the case of generic paramaters. (orig.)
TEST OF THE FAMA-FRENCH THREE-FACTOR MODEL IN CROATIA
Directory of Open Access Journals (Sweden)
Denis Dolinar
2013-06-01
Full Text Available This paper empirically examines the Fama-French three-factor model of stock returns for Croatia. In contrast to the results of Fama and French (1993 for the U.S. stock market, their three-factor model did not show so successful when describing risk-return relation of Croatian stocks. This paper shows that the Fama-French three-factor model is a valid pricing model, since it explains cross-section of average returns on stocks in Croatia, and that has a greater explanatory power in comparison to the CAPM. In the case of Croatian stock market, size and B/M factors are not always significant, but on average they individually have certain marginal explanatory power. Namely, they capture small common variation in returns that is missed by the market factor. Moreover, B/M factor has shown as a stronger common risk proxy in relation to size factor. Finally, there is still a large portion of common variation in stock return that may be explained by other factors. Because emerging capital markets bear their own specificity, special care needs to be taken when applying existing or developing new pricing models.
The Research on Influencing Factors of Medical Logistics Cost Based on ISM Model
Directory of Open Access Journals (Sweden)
Zhai Yunkai
2017-01-01
Full Text Available The reason why medical logistics cost remains high is a system problem, this paper analyzes the system through the ISM model. The result presents that medical logistics cost factors have four levels of relationship, primary factor is the national policies, secondary factors are the talent construction and pharmaceutical enterprise scale, Intermediate factors are medical information management system and inventory cost, the key factors are transportation cost and distribution center location. Finally, according to the four levels of relationship, this paper put forward specific suggestions to reduce logistics cost.
Macroeconomic factors and oil futures prices. A data-rich model
International Nuclear Information System (INIS)
Zagaglia, Paolo
2010-01-01
I study the dynamics of oil futures prices in the NYMEX using a large panel dataset that includes global macroeconomic indicators, financial market indices, quantities and prices of energy products. I extract common factors from the panel data series and estimate a Factor-Augmented Vector Autoregression for the maturity structure of oil futures prices. I find that latent factors generate information that, once combined with that of the yields, improves the forecasting performance for oil prices. Furthermore, I show that a factor correlated to purely financial developments contributes to the model performance, in addition to factors related to energy quantities and prices. (author)
Analysis on trust influencing factors and trust model from multiple perspectives of online Auction
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.
These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.
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
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.
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....
Extracting the Evaluations of Stereotypes: Bi-factor Model of the Stereotype Content Structure
Directory of Open Access Journals (Sweden)
Pablo Sayans-Jiménez
2017-10-01
Full Text Available Stereotype dimensions—competence, morality and sociability—are fundamental to studying the perception of other groups. These dimensions have shown moderate/high positive correlations with each other that do not reflect the theoretical expectations. The explanation for this (e.g., halo effect undervalues the utility of the shared variance identified. In contrast, in this work we propose that this common variance could represent the global evaluation of the perceived group. Bi-factor models are proposed to improve the internal structure and to take advantage of the information representing the shared variance among dimensions. Bi-factor models were compared with first order models and other alternative models in three large samples (300–309 participants. The relationships among the global and specific bi-factor dimensions with a global evaluation dimension (measured through a semantic differential were estimated. The results support the use of bi-factor models rather than first order models (and other alternative models. Bi-factor models also show a greater utility to directly and more easily explore the stereotype content including its evaluative content.
Extracting the Evaluations of Stereotypes: Bi-factor Model of the Stereotype Content Structure.
Sayans-Jiménez, Pablo; Cuadrado, Isabel; Rojas, Antonio J; Barrada, Juan R
2017-01-01
Stereotype dimensions-competence, morality and sociability-are fundamental to studying the perception of other groups. These dimensions have shown moderate/high positive correlations with each other that do not reflect the theoretical expectations. The explanation for this (e.g., halo effect) undervalues the utility of the shared variance identified. In contrast, in this work we propose that this common variance could represent the global evaluation of the perceived group. Bi-factor models are proposed to improve the internal structure and to take advantage of the information representing the shared variance among dimensions. Bi-factor models were compared with first order models and other alternative models in three large samples (300-309 participants). The relationships among the global and specific bi-factor dimensions with a global evaluation dimension (measured through a semantic differential) were estimated. The results support the use of bi-factor models rather than first order models (and other alternative models). Bi-factor models also show a greater utility to directly and more easily explore the stereotype content including its evaluative content.
Risk management under a two-factor model of the term structure of interest rates
Manuel Moreno
1997-01-01
This paper presents several applications to interest rate risk management based on a two-factor continuous-time model of the term structure of interest rates previously presented in Moreno (1996). This model assumes that default free discount bond prices are determined by the time to maturity and two factors, the long-term interest rate and the spread (difference between the long-term rate and the short-term (instantaneous) riskless rate). Several new measures of ``generalized duration" are p...
Mohsen Shafiei Nikabadi; Laya Olfat; Ahmad Jafarian; Hassan Alibabaei Khamene
2013-01-01
The main goal of this article is to survey effects of necessary factors for deploying e-business models on business performance in automotive industry. Today, application of information technology and internet in business is turned to a critical tool to gain competitive advantages in business. The impact of e-businesses is so that changed competitive approach between companies from traditional to modern models. In this study, first, necessary key factors of implementing e-business in automoti...
Testing multi-factor asset pricing models in the Visegrad countries
Czech Academy of Sciences Publication Activity Database
Morgese Borys, Magdalena
2011-01-01
Roč. 61, č. 2 (2011), s. 118-139 ISSN 0015-1920 R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:AV0Z70850503 Keywords : capital asset pricing model * macroeconomic factor models * asset pricing Subject RIV: AH - Economics Impact factor: 0.346, year: 2011 http://journal.fsv.cuni.cz/mag/article/show/id/1208
Olga Klinkowska
2009-01-01
In this paper I develop the asset pricing model in which the wealth portfolio is enriched with human capital and housing capital. These two types of capital account for a significant portion of the total wealth. Additionally I introduce dynamics into the model and represent conditioning information by common factors estimated with dynamic factor methodology. In this way I can use more accurate representative of the unobservable information set of the investors. Obtained results prove that ind...
MacCann, Carolyn; Joseph, Dana L; Newman, Daniel A; Roberts, Richard D
2014-04-01
This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.
Rotation in the Dynamic Factor Modeling of Multivariate Stationary Time Series.
Molenaar, Peter C. M.; Nesselroade, John R.
2001-01-01
Proposes a special rotation procedure for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average.…
Form factors in quantum integrable models with GL(3)-invariant R-matrix
Energy Technology Data Exchange (ETDEWEB)
Pakuliak, S., E-mail: pakuliak@theor.jinr.ru [Laboratory of Theoretical Physics, JINR, 141980 Dubna, Moscow Reg. (Russian Federation); Moscow Institute of Physics and Technology, 141700 Dolgoprudny, Moscow Reg. (Russian Federation); Institute of Theoretical and Experimental Physics, 117259 Moscow (Russian Federation); Ragoucy, E., E-mail: eric.ragoucy@lapth.cnrs.fr [Laboratoire de Physique Théorique LAPTH, CNRS and Université de Savoie, BP 110, 74941 Annecy-le-Vieux Cedex (France); Slavnov, N.A., E-mail: nslavnov@mi.ras.ru [Steklov Mathematical Institute, Moscow (Russian Federation)
2014-04-15
We study integrable models solvable by the nested algebraic Bethe ansatz and possessing GL(3)-invariant R-matrix. We obtain determinant representations for form factors of off-diagonal entries of the monodromy matrix. These representations can be used for the calculation of form factors and correlation functions of the XXX SU(3)-invariant Heisenberg chain.
Modeling of the symmetry factor of electrochemical proton discharge via the Volmer reaction
DEFF Research Database (Denmark)
Björketun, Mårten E.; Tripkovic, Vladimir; Skúlason, Egill
2013-01-01
A scheme for evaluating symmetry factors of elementary electrode reactions using a density functional theory (DFT) based model of the electrochemical double layer is presented. As an illustration, the symmetry factor is determined for hydrogen adsorption via the electrochemical Volmer reaction...
The Hierarchical Factor Model of ADHD: Invariant across Age and National Groupings?
Toplak, Maggie E.; Sorge, Geoff B.; Flora, David B.; Chen, Wai; Banaschewski, Tobias; Buitelaar, Jan; Ebstein, Richard; Eisenberg, Jacques; Franke, Barbara; Gill, Michael; Miranda, Ana; Oades, Robert D.; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph; Sonuga-Barke, Edmund; Steinhausen, Hans-Christoph; Thompson, Margaret; Tannock, Rosemary; Asherson, Philip; Faraone, Stephen V.
2012-01-01
Objective: To examine the factor structure of attention-deficit/hyperactivity disorder (ADHD) in a clinical sample of 1,373 children and adolescents with ADHD and their 1,772 unselected siblings recruited from different countries across a large age range. Hierarchical and correlated factor analytic models were compared separately in the ADHD and…
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
Rotation in the dynamic factor modeling of multivariate stationary time series.
Molenaar, P.C.M.; Nesselroade, J.R.
2001-01-01
A special rotation procedure is proposed for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white
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.
Evaluation factors for verification and validation of low-level waste disposal site models
International Nuclear Information System (INIS)
Moran, M.S.; Mezga, L.J.
1982-01-01
The purpose of this paper is to identify general evaluation factors to be used to verify and validate LLW disposal site performance models in order to assess their site-specific applicability and to determine their accuracy and sensitivity. It is intended that the information contained in this paper be employed by model users involved with LLW site performance model verification and validation. It should not be construed as providing protocols, but rather as providing a framework for the preparation of specific protocols or procedures. A brief description of each evaluation factor is provided. The factors have been categorized according to recommended use during either the model verification or the model validation process. The general responsibilities of the developer and user are provided. In many cases it is difficult to separate the responsibilities of the developer and user, but the user is ultimately accountable for both verification and validation processes. 4 refs
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.
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.
System Dynamics Modeling of interactive cost factors for small modular reactors
International Nuclear Information System (INIS)
Ahn, Nam Sung; Lee, Keun Dae; Yoon, Suk Ho
2011-01-01
As a part of the Study on Economic Efficiency and Marketability of small modular reactors project, we at Nemo partners NEC consulting corporation were studying the various cost factors on small modular reactors (SMRs). To have a better knowledge of the interaction between the cost factors, System Dynamics Modeling has been developed. This model will contribute to our understanding of the interaction on the major factors effecting on the unit cost of SMRs to the SMRs' market share in the market economics as competition
Hill, Briony; Skouteris, Helen; McCabe, Marita; Milgrom, Jeannette; Kent, Bridie; Herring, Sharon J; Hartley-Clark, Linda; Gale, Janette
2013-02-01
nearly half of all women exceed the guideline recommended pregnancy weight gain for their Body Mass Index (BMI) category. Excessive gestational weight gain (GWG) is correlated positively with postpartum weight retention and is a predictor of long-term, higher BMI in mothers and their children. Psychosocial factors are generally not targeted in GWG behaviour change interventions, however, multifactorial, conceptual models that include these factors, may be useful in determining the pathways that contribute to excessive GWG. We propose a conceptual model, underpinned by health behaviour change theory, which outlines the psychosocial determinants of GWG, including the role of motivation and self-efficacy towards healthy behaviours. This model is based on a review of the existing literature in this area. there is increasing evidence to show that psychosocial factors, such as increased depressive symptoms, anxiety, lower self-esteem and body image dissatisfaction, are associated with excessive GWG. What is less known is how these factors might lead to excessive GWG. Our conceptual model proposes a pathway of factors that affect GWG, and may be useful for understanding the mechanisms by which interventions impact on weight management during pregnancy. This involves tracking the relationships among maternal psychosocial factors, including body image concerns, motivation to adopt healthy lifestyle behaviours, confidence in adopting healthy lifestyle behaviours for the purposes of weight management, and actual behaviour changes. health-care providers may improve weight gain outcomes in pregnancy if they assess and address psychosocial factors in pregnancy. Copyright © 2011 Elsevier Ltd. All rights reserved.
Bayes factor between Student t and Gaussian mixed models within an animal breeding context
Directory of Open Access Journals (Sweden)
García-Cortés Luis
2008-07-01
Full Text Available Abstract The implementation of Student t mixed models in animal breeding has been suggested as a useful statistical tool to effectively mute the impact of preferential treatment or other sources of outliers in field data. Nevertheless, these additional sources of variation are undeclared and we do not know whether a Student t mixed model is required or if a standard, and less parameterized, Gaussian mixed model would be sufficient to serve the intended purpose. Within this context, our aim was to develop the Bayes factor between two nested models that only differed in a bounded variable in order to easily compare a Student t and a Gaussian mixed model. It is important to highlight that the Student t density converges to a Gaussian process when degrees of freedom tend to infinity. The twomodels can then be viewed as nested models that differ in terms of degrees of freedom. The Bayes factor can be easily calculated from the output of a Markov chain Monte Carlo sampling of the complex model (Student t mixed model. The performance of this Bayes factor was tested under simulation and on a real dataset, using the deviation information criterion (DIC as the standard reference criterion. The two statistical tools showed similar trends along the parameter space, although the Bayes factor appeared to be the more conservative. There was considerable evidence favoring the Student t mixed model for data sets simulated under Student t processes with limited degrees of freedom, and moderate advantages associated with using the Gaussian mixed model when working with datasets simulated with 50 or more degrees of freedom. For the analysis of real data (weight of Pietrain pigs at six months, both the Bayes factor and DIC slightly favored the Student t mixed model, with there being a reduced incidence of outlier individuals in this population.
Application of the Value Optimization Model of Key Factors Based on DSEM
Directory of Open Access Journals (Sweden)
Chao Su
2016-01-01
Full Text Available The key factors of the damping solvent extraction method (DSEM for the analysis of the unbounded medium are the size of bounded domain, the artificial damping ratio, and the finite element mesh density. To control the simulation accuracy and computational efficiency of the soil-structure interaction, this study establishes a value optimization model of key factors that is composed of the design variables, the objective function, and the constraint function system. Then the optimum solutions of key factors are obtained by the optimization model. According to some comparisons of the results provided by the different initial conditions, the value optimization model of key factors is feasible to govern the simulation accuracy and computational efficiency and to analyze the practical unbounded medium-structure interaction.
Latent factor modeling of four schizotypy dimensions with theory of mind and empathy.
Directory of Open Access Journals (Sweden)
Jeffrey S Bedwell
Full Text Available Preliminary evidence suggests that theory of mind and empathy relate differentially to factors of schizotypy. The current study assessed 686 undergraduate students and used structural equation modeling to examine links between a four-factor model of schizotypy with performance on measures of theory of mind (Reading the Mind in the Eyes Test [MIE] and empathy (Interpersonal Reactivity Index [IRI]. Schizotypy was assessed using three self-report measures which were simultaneously entered into the model. Results revealed that the Negative factor of schizotypy showed a negative relationship with the Empathy factor, which was primarily driven by the Empathic Concern subscale of the IRI and the No Close Friends and Constricted Affect subscales of the Schizotypal Personality Questionnaire. These findings are consistent with a growing body of literature suggesting a relatively specific relationship between negative schizotypy and empathy, and are consistent with several previous studies that found no relationship between MIE performance and schizotypy.
Meitinger, T; Meindl, A; Bork, P; Rost, B; Sander, C; Haasemann, M; Murken, J
1993-12-01
The X-lined gene for Norrie disease, which is characterized by blindness, deafness and mental retardation has been cloned recently. This gene has been thought to code for a putative extracellular factor; its predicted amino acid sequence is homologous to the C-terminal domain of diverse extracellular proteins. Sequence pattern searches and three-dimensional modelling now suggest that the Norrie disease protein (NDP) has a tertiary structure similar to that of transforming growth factor beta (TGF beta). Our model identifies NDP as a member of an emerging family of growth factors containing a cystine knot motif, with direct implications for the physiological role of NDP. The model also sheds light on sequence related domains such as the C-terminal domain of mucins and of von Willebrand factor.
The structure of PTSD symptoms: a test of alternative models using confirmatory factor analysis.
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.
Reply to comment on 'Model calculation of the scanned field enhancement factor of CNTs'
International Nuclear Information System (INIS)
Ahmad, Amir; Tripathi, V K
2010-01-01
In the paper (Ahmad and Tripathi 2006 Nanotechnology 17 3798), we derived an expression to compute the field enhancement factor of CNTs under any positional distribution of CNTs by using the 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 was used to compute the field enhancement factor of a CNT in an array (uniformly distributed CNTs). We used an approximation to calculate the field enhancement factor. Hence, our expressions are correct in that assumption only. Zhbanov et al (2010 Nanotechnology 21 358001) suggest a correction that can calculate the field enhancement factor without using the approximation. Hence, this correction can improve the applicability of this model. (reply)
The Dual-Factor Model of Mental Health: Further Study of the Determinants of Group Differences
Lyons, Michael D.; Huebner, E. Scott; Hills, Kimberly J.; Shinkareva, Svetlana V.
2012-01-01
Consistent with a positive psychology framework, this study examined the contributions of personality, environmental, and perceived social support variables in classifying adolescents using Greenspoon and Saklofske's Dual-Factor model of mental health. This model incorporates information about positive subjective well-being (SWB), along with…
A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities across Categories
Duvvuri, Sri Devi; Gruca, Thomas S.
2010-01-01
Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to…
Logistic regression models of factors influencing the location of bioenergy and biofuels plants
T.M. Young; R.L. Zaretzki; J.H. Perdue; F.M. Guess; X. Liu
2011-01-01
Logistic regression models were developed to identify significant factors that influence the location of existing wood-using bioenergy/biofuels plants and traditional wood-using facilities. Logistic models provided quantitative insight for variables influencing the location of woody biomass-using facilities. Availability of "thinnings to a basal area of 31.7m2/ha...
Determining factors influencing survival of breast cancer by fuzzy logistic regression model.
Nikbakht, Roya; Bahrampour, Abbas
2017-01-01
Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.
WALS estimation and forecasting in factor-based dynamic models with an application to Armenia
Poghosyan, K.; Magnus, J.R.
2011-01-01
Two model averaging approaches are used and compared in estimating and forecasting dynamic factor models, the well-known BMA and the recently developed WALS. Both methods propose to combine frequentist estimators using Bayesian weights. We apply our framework to the Armenian economy using quarterly
Testing multi-factor asset pricing models in the Visegrad countries
Czech Academy of Sciences Publication Activity Database
Morgese Borys, Magdalena
-, č. 323 (2007), s. 1-40 ISSN 1211-3298 R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:AV0Z70850503 Keywords : capital asset pricing model * macroeconomic factor models * cost of capital Subject RIV: AH - Economics http://www.cerge-ei.cz/pdf/wp/Wp323.pdf
Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance
M. Asai (Manabu); M.J. McAleer (Michael)
2014-01-01
markdownabstract__Abstract__ Modelling covariance structures is known to suffer from the curse of dimensionality. In order to avoid this problem for forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures that accommodates
The Earnings/Price Risk Factor in Capital Asset Pricing Models
Directory of Open Access Journals (Sweden)
Rafael Falcão Noda
2015-01-01
Full Text Available This article integrates the ideas from two major lines of research on cost of equity and asset pricing: multi-factor models and ex ante accounting models. The earnings/price ratio is used as a proxy for the ex ante cost of equity, in order to explain realized returns of Brazilian companies within the period from 1995 to 2013. The initial finding was that stocks with high (low earnings/price ratios have higher (lower risk-adjusted realized returns, already controlled by the capital asset pricing model's beta. The results show that selecting stocks based on high earnings/price ratios has led to significantly higher risk-adjusted returns in the Brazilian market, with average abnormal returns close to 1.3% per month. We design asset pricing models including an earnings/price risk factor, i.e. high earnings minus low earnings, based on the Fama and French three-factor model. We conclude that such a risk factor is significant to explain returns on portfolios, even when controlled by size and market/book ratios. Models including the high earnings minus low earnings risk factor were better to explain stock returns in Brazil when compared to the capital asset pricing model and to the Fama and French three-factor model, having the lowest number of significant intercepts. These findings may be due to the impact of historically high inflation rates, which reduce the information content of book values, thus making the models based on earnings/price ratios better than those based on market/book ratios. Such results are different from those obtained in more developed markets and the superiority of the earnings/price ratio for asset pricing may also exist in other emerging markets.
Studying Term Structure of SHIBOR with the Two-Factor Vasicek Model
Directory of Open Access Journals (Sweden)
Chaoqun Ma
2014-01-01
Full Text Available With the development of the Chinese interest rate market, SHIBOR is playing an increasingly important role. Based on principal component analysing SHIBOR, a two-factor Vasicek model is established to portray the change in SHIBOR with different terms. And parameters are estimated by using the Kalman filter. The model is also used to fit and forecast SHIBOR with different terms. The results show that two-factor Vasicek model fits SHIBOR well, especially for SHIBOR in terms of three months or more.
Directory of Open Access Journals (Sweden)
KADEK MIRA PITRIYANTI
2015-11-01
Full Text Available In 1996, Fama and French developed the CAPM in Three Factor Model Fama and French (TFMFF to analyze the relationship between risk with rate of return by adding firm size factor that is proxied by Small Minus Big (SMB and value factor at Book to Market Ratio that is proxied by High Minus Low (HML on the CAPM model. The aim of this research is to compare the ability of CAPM and TFMFF in estimating the returns on six types of portfolios which are formed based on firm size and BE/ME. Selected samples are stocks of LQ-45 in period of February 2014, which have passed the selection of firm profits and ROE Warren Buffett criteria. Simple linear regression and Multiple linear regression with t test and F test statistics are used to demonstrate the influence and significance level of each variable. The results showed that TFMFF was more superior than CAPM. Market risk factor consistently affected each portfolio. SMB and HML is not always significantly effect on each portfolio, such as portfolio B/H, only market risk factor has a significant effect. However, the addition of SMB factors and HML factors could increase the coefficient of determination in each formed portfolio.
Yu, Yan; Qiu, Robin G
2014-01-01
Microblog that provides us a new communication and information sharing platform has been growing exponentially since it emerged just a few years ago. To microblog users, recommending followees who can serve as high quality information sources is a competitive service. To address this problem, in this paper we propose a matrix factorization model with structural regularization to improve the accuracy of followee recommendation in microblog. More specifically, we adapt the matrix factorization model in traditional item recommender systems to followee recommendation in microblog and use structural regularization to exploit structure information of social network to constrain matrix factorization model. The experimental analysis on a real-world dataset shows that our proposed model is promising.
WALS Estimation and Forecasting in Factor-based Dynamic Models with an Application to Armenia
Poghosyan, Karen; Magnus, Jan R.
2012-01-01
Two model averaging approaches are used and compared in estimating and forecasting dynamic factor models, the well-known Bayesian model averaging (BMA) and the recently developed weighted average least squares (WALS). Both methods propose to combine frequentist estimators using Bayesian weights. We apply our framework to the Armenian economy using quarterly data from 20002010, and we estimate and forecast real GDP growth and inflation.
Can we replace CAPM and the Three-Factor model with Implied Cost of Capital?
Löthman, Robert; Pettersson, Eric
2014-01-01
Researchers criticize predominant expected return models for being imprecise and based on fundamentally flawed assumptions. This dissertation evaluates Implied Cost of Capital, CAPM and the Three-Factor model abilities to estimate returns. We study each models expected return association to realized return and test for abnormal returns. Our sample covers the period 2000 to 2012 and includes 2916 US firms. We find that Implied Cost of Capital has a stronger association with realized returns th...
Stienstra, Martin R.; Ruel, Hubertus Johannes Maria; Boerrigter, Thomas
2010-01-01
Especially for companies in the media sector such as publishers, the Internet has created new strategic and commercial opportunities. However, many companies in the media sector are struggling with how to adapt their business and revenue model for doing profitable business online. This exploratory study goes into the success factors and the level of adoption of online revenue models by media sector companies. We use Chaffey (2002) in determining online revenue models in which we included Oste...
Constructing a unique two-phase compressibility factor model for lean gas condensates
Energy Technology Data Exchange (ETDEWEB)
Moayyedi, Mahmood; Gharesheikhlou, Aliashghar [Research Institute of Petroleum Industry (RIPI), Tehran (Iran, Islamic Republic of); Azamifard, Arash; Mosaferi, Emadoddin [Amirkabir University of Technology (AUT), Tehran (Iran, Islamic Republic of)
2015-02-15
Generating a reliable experimental model for two-phase compressibility factor in lean gas condensate reservoirs has always been demanding, but it was neglected due to lack of required experimental data. This study presents the main results of constructing the first two-phase compressibility factor model that is completely valid for Iranian lean gas condensate reservoirs. Based on a wide range of experimental data bank for Iranian lean gas condensate reservoirs, a unique two-phase compressibility factor model was generated using design of experiments (DOE) method and neural network technique (ANN). Using DOE, a swift cubic response surface model was generated for two-phase compressibility factor as a function of some selected fluid parameters for lean gas condensate fluids. The proposed DOE and ANN models were finally validated using four new independent data series. The results showed that there is a good agreement between experimental data and the proposed models. In the end, a detailed comparison was made between the results of proposed models.
Factor Analysis of Drawings: Application to college student models of the greenhouse effect
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.
Constructing a unique two-phase compressibility factor model for lean gas condensates
International Nuclear Information System (INIS)
Moayyedi, Mahmood; Gharesheikhlou, Aliashghar; Azamifard, Arash; Mosaferi, Emadoddin
2015-01-01
Generating a reliable experimental model for two-phase compressibility factor in lean gas condensate reservoirs has always been demanding, but it was neglected due to lack of required experimental data. This study presents the main results of constructing the first two-phase compressibility factor model that is completely valid for Iranian lean gas condensate reservoirs. Based on a wide range of experimental data bank for Iranian lean gas condensate reservoirs, a unique two-phase compressibility factor model was generated using design of experiments (DOE) method and neural network technique (ANN). Using DOE, a swift cubic response surface model was generated for two-phase compressibility factor as a function of some selected fluid parameters for lean gas condensate fluids. The proposed DOE and ANN models were finally validated using four new independent data series. The results showed that there is a good agreement between experimental data and the proposed models. In the end, a detailed comparison was made between the results of proposed models
Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.
Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed
2013-01-01
In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.
Eicher, Bernhard
2016-10-01
Hospitals are responsible for a remarkable part of the annual increase in healthcare expenditure. This article examines one of the major cost drivers, the expenditure for investment in hospital assets. The study, conducted in Switzerland, identifies factors that influence hospitals' investment decisions. A suggestion on how to categorize asset investment models is presented based on the life cycle of an asset, and its influencing factors defined based on transaction cost economics. The influence of five factors (human asset specificity, physical asset specificity, uncertainty, bargaining power, and privacy of ownership) on the selection of an asset investment model is examined using a two-step fuzzy-set Qualitative Comparative Analysis. The research shows that outsourcing-oriented asset investment models are particularly favored in the presence of two combinations of influencing factors: First, if technological uncertainty is high and both human asset specificity and bargaining power of a hospital are low. Second, if assets are very specific, technological uncertainty is high and there is a private hospital with low bargaining power, outsourcing-oriented asset investment models are favored too. Using Qualitative Comparative Analysis, it can be demonstrated that investment decisions of hospitals do not depend on isolated influencing factors but on a combination of factors. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
A dynamic factor model of the evaluation of the financial crisis in Turkey.
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.
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)
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)
Directory of Open Access Journals (Sweden)
Pawlasova Pavlina
2015-12-01
Full Text Available Satisfaction is one of the key factors which influences customer loyalty. We assume that the satisfied customer will be willing to use the ssame service provider again. The overall passengers´ satisfaction with public city transport may be affected by the overall service quality. Frequency, punctuality, cleanliness in the vehicle, proximity, speed, fare, accessibility and safety of transport, information and other factors can influence passengers´ satisfaction. The aim of this paper is to quantify factors and identify the most important factors influencing customer satisfaction with public city transport within conditions of the Czech Republic. Two methods of analysis are applied in order to fulfil the aim. The method of factor analysis and the method Varimax were used in order to categorize variables according to their mutual relations. The method of structural equation modelling was used to evaluate the factors and validate the model. Then, the optimal model was found. The logistic parameters, including service continuity and frequency, and service, including information rate, station proximity and vehicle cleanliness, are the factors influencing passengers´ satisfaction on a large scale.
Directory of Open Access Journals (Sweden)
Sayali Shrikrishna Sandbhor
2014-03-01
Full Text Available Construction sector has always been dependent on manpower. Most of the activities carried out on any construction site are labour intensive. Since productivity of any project depends directly on productivity of labour, it is a prime responsibility of the employer to enhance labour productivity. Measures to improve the same depend on analysis of positive and negative factors affecting productivity. Major attention should be given to factors that decrease the productivity of labour. Factor analysis thus is an integral part of any study aiming to improve productivity. Interpretive structural modeling is a methodology for identifying and summarizing relationships among factors which define an issue or problem. It provides a means to arrange the factors in an order as per their complexity. This study attempts to use the latest version of interpretive structural modeling i.e. total interpretive structural modeling to analyze factors negatively affecting construction labour productivity. It establishes interpretive relationship among these factors facilitating improvement in the overall productivity of construction site.
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.
Learning a generative model of images by factoring appearance and shape.
Le Roux, Nicolas; Heess, Nicolas; Shotton, Jamie; Winn, John
2011-03-01
Computer vision has grown tremendously in the past two decades. Despite all efforts, existing attempts at matching parts of the human visual system's extraordinary ability to understand visual scenes lack either scope or power. By combining the advantages of general low-level generative models and powerful layer-based and hierarchical models, this work aims at being a first step toward richer, more flexible models of images. After comparing various types of restricted Boltzmann machines (RBMs) able to model continuous-valued data, we introduce our basic model, the masked RBM, which explicitly models occlusion boundaries in image patches by factoring the appearance of any patch region from its shape. We then propose a generative model of larger images using a field of such RBMs. Finally, we discuss how masked RBMs could be stacked to form a deep model able to generate more complicated structures and suitable for various tasks such as segmentation or object recognition.
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.
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.
Directory of Open Access Journals (Sweden)
Oscar Armando Esparza-Del Villar
2017-03-01
Full Text Available Abstract Background Mexico is one of the countries with the highest rates of overweight and obesity around the world, with 68.8% of men and 73% of women reporting both. This is a public health problem since there are several health related consequences of not exercising, like having cardiovascular diseases or some types of cancers. All of these problems can be prevented by promoting exercise, so it is important to evaluate models of health behaviors to achieve this goal. Among several models the Health Belief Model is one of the most studied models to promote health related behaviors. This study validates the first exercise scale based on the Health Belief Model (HBM in Mexicans with the objective of studying and analyzing this model in Mexico. Methods Items for the scale called the Exercise Health Belief Model Scale (EHBMS were developed by a health research team, then the items were applied to a sample of 746 participants, male and female, from five cities in Mexico. The factor structure of the items was analyzed with an exploratory factor analysis and the internal reliability with Cronbach’s alpha. Results The exploratory factor analysis reported the expected factor structure based in the HBM. The KMO index (0.92 and the Barlett’s sphericity test (p < 0.01 indicated an adequate and normally distributed sample. Items had adequate factor loadings, ranging from 0.31 to 0.92, and the internal consistencies of the factors were also acceptable, with alpha values ranging from 0.67 to 0.91. Conclusions The EHBMS is a validated scale that can be used to measure exercise based on the HBM in Mexican populations.
Theoretical Assessment of the Impact of Climatic Factors in a Vibrio Cholerae Model.
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.
Rough electricity: a new fractal multi-factor model of electricity spot prices
DEFF Research Database (Denmark)
Bennedsen, Mikkel
We introduce a new 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, fractality, and our approach...... explicitly incorporates this into the model of the prices. Our setup generalizes the popular Ornstein Uhlenbeck-based multi-factor framework of Benth et al. (2007) and allows us to perform statistical tests to distinguish between an Ornstein Uhlenbeck-based model and a fractal model. Further, through...... the multi-factor approach we account for seasonality and spikes before estimating - and making inference on - the degree of fractality. This is novel in the literature and we present simulation evidence showing that these precautions are crucial to accurate estimation. Lastly, we estimate our model...
System dynamics modeling of social/political factors in nuclear power plant operations
International Nuclear Information System (INIS)
Hansen, K.F.; Turek, M.G.; Eubanks, C.K.
1995-01-01
The safety and performance of nuclear power plants are a function of many technical factors such as initial design, service and maintenance programs, and utility investment in improvements. Safety and performance are also a function of the social/political influences that affect requirements on personnel, practices and procedures, and resource availability. This paper describes a process for constructing models of the social/political influences on plant operations using the system dynamics technique. The model incorporates representation of internal utility actions and decisions as affected by external factors such as public opinion, intervenor actions, safety and economic regulation, and the financial community. The feedback between external agents and plant performance is explicitly modeled. The resulting model can be used to simulate performance under a variety of different external and internal policy choices. In particular, the model can be used to study means of improving performance in response to externally imposed regulations
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.
Unidimensional factor models imply weaker partial correlations than zero-order correlations.
van Bork, Riet; Grasman, Raoul P P P; Waldorp, Lourens J
2018-06-01
In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.
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.
A model of real estate and psychological factors in decision-making to buy real estate
Directory of Open Access Journals (Sweden)
Bojan Grum
2015-06-01
Full Text Available This article explores the psychological characteristics of potential real estate buyers connected with their decision to buy. Through a review of research, it reveals that most studies of psychological factors in the decision to buy real estate have a partial and dispersed orientation, and examine individual factors independently. It appears that the research area is lacking clearly defined models of psychological factors in the decision to buy real estate that would integrally and relationally explain the role of psychological characteristics of real estate buyers and their expectations in relation to a decision to buy. The article identifies two sets of psychological factors, motivational and emotional, determines their interaction with potential buyers’ expectations when deciding to purchase real estate and offers starting points for forming a model.
Effects of source shape on the numerical aperture factor with a geometrical-optics model.
Wan, Der-Shen; Schmit, Joanna; Novak, Erik
2004-04-01
We study the effects of an extended light source on the calibration of an interference microscope, also referred to as an optical profiler. Theoretical and experimental numerical aperture (NA) factors for circular and linear light sources along with collimated laser illumination demonstrate that the shape of the light source or effective aperture cone is critical for a correct NA factor calculation. In practice, more-accurate results for the NA factor are obtained when a linear approximation to the filament light source shape is used in a geometric model. We show that previously measured and derived NA factors show some discrepancies because a circular rather than linear approximation to the filament source was used in the modeling.
Remarks on electromagnetic form factors of hadrons in the quark model
International Nuclear Information System (INIS)
Vainshtein, A.I.; Zakharov, V.I.
1977-01-01
Relations between the transversal and longitudinal parts of elastic and quasielastic form factors are studied within the quark model. It is shown that for an even number of the constituent quarks the longitudinal part dominates while for an odd number the transversal part is the largest one. Consequences form this result are considered for deuteron form factor and for matrix elements of the electromagnetic transitions between π, rho, A 1 mesons
Assessing Factors Related to Waist Circumference and Obesity: Application of a Latent Variable Model
Dalvand, Sahar; Koohpayehzadeh, Jalil; Karimlou, Masoud; Asgari, Fereshteh; Rafei, Ali; Seifi, Behjat; Niksima, Seyed Hassan; Bakhshi, Enayatollah
2015-01-01
Background. Because the use of BMI (Body Mass Index) alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome) and obesity (binary outcome) among Iranian adults. Methods. Data included 18,990 Iranian individuals aged 20–65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variabl...
Haftu Hailu; Abdelkadir Kedir; Getachew Bassa; Kassu Jilcha
2017-01-01
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 th...
The relationship between the Five-Factor Model and latent DSM-IV personality disorder dimensions
Nestadt, Gerald; Costa, Paul T.; Hsu, Fang-Chi; Samuels, Jack; Bienvenu, O. Joseph; Eaton, William W.
2007-01-01
This study compared the latent structure of the DSM-IV personality disorders to the Five-Factor Model (FFM) of general personality dimensions. The subjects in the study were 742 community-residing individuals who participated in the Hopkins Epidemiology of Personality Disorder Study. DSM-IV personality disorder traits were assessed by psychologists using the International Personality Disorder Examination, and personality disorder dimensions were derived previously using dichotomous factor ana...
Proton and neutron charge form factors in soliton model with dilaton-quarkonium fields
International Nuclear Information System (INIS)
Magar, E.N.; Nikolaev, V.A.; Tkachev, O.G.; Novozhilov, V.Yu.
1997-01-01
Nucleon electromagnetic form factors are considered in the framework of the generalized Skyrme model with dilaton-quarkonium fields. In our first publication we got big discrepancy between calculated form factors and dipole approximation formula. Here we have reasonably good accordance between them in finite impulse region after vector meson dominance has been taken into account. Omega- and rho-mesons have been included only into hadron structure of the photon
A Framework for Integrating Cultural Factors in Military Modeling and Simulation
2006-01-01
Symbolic Interactionism : Perspective and Method. Englewood Cliffs, New Jersey, Prentice-Hall. Bonner, J. T. (1980). The Evolution of Culture in...cultural factors. The framework includes the impacts of cultural perception of information-such as interpretation of signs, signals and symbols . This...for Cultural Factors in Organizational Model .................... 23 5.3 Signs, Signals, and Symbols : The Impacts on the Cultural Perception of
Murphy, Kelly E.
2012-01-13
Fibroblasts and their activated phenotype, myofibroblasts, are the primary cell types involved in the contraction associated with dermal wound healing. Recent experimental evidence indicates that the transformation from fibroblasts to myofibroblasts involves two distinct processes: The cells are stimulated to change phenotype by the combined actions of transforming growth factor β (TGFβ) and mechanical tension. This observation indicates a need for a detailed exploration of the effect of the strong interactions between the mechanical changes and growth factors in dermal wound healing. We review the experimental findings in detail and develop a model of dermal wound healing that incorporates these phenomena. Our model includes the interactions between TGFβ and collagenase, providing a more biologically realistic form for the growth factor kinetics than those included in previous mechanochemical descriptions. A comparison is made between the model predictions and experimental data on human dermal wound healing and all the essential features are well matched. © 2012 Society for Mathematical Biology.
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.
PWSCC Growth Assessment Model Considering Stress Triaxiality Factor for Primary Alloy 600 Components
Directory of Open Access Journals (Sweden)
Jong-Sung Kim
2016-08-01
Full Text Available We propose a primary water stress corrosion cracking (PWSCC initiation model of Alloy 600 that considers the stress triaxiality factor to apply to finite element analysis. We investigated the correlation between stress triaxiality effects and PWSCC growth behavior in cold-worked Alloy 600 stream generator tubes, and identified an additional stress triaxiality factor that can be added to Garud's PWSCC initiation model. By applying the proposed PWSCC initiation model considering the stress triaxiality factor, PWSCC growth simulations based on the macroscopic phenomenological damage mechanics approach were carried out on the PWSCC growth tests of various cold-worked Alloy 600 steam generator tubes and compact tension specimens. As a result, PWSCC growth behavior results from the finite element prediction are in good agreement with the experimental results.
Murphy, Kelly E.; Hall, Cameron L.; Maini, Philip K.; McCue, Scott W.; McElwain, D. L. Sean
2012-01-01
Fibroblasts and their activated phenotype, myofibroblasts, are the primary cell types involved in the contraction associated with dermal wound healing. Recent experimental evidence indicates that the transformation from fibroblasts to myofibroblasts involves two distinct processes: The cells are stimulated to change phenotype by the combined actions of transforming growth factor β (TGFβ) and mechanical tension. This observation indicates a need for a detailed exploration of the effect of the strong interactions between the mechanical changes and growth factors in dermal wound healing. We review the experimental findings in detail and develop a model of dermal wound healing that incorporates these phenomena. Our model includes the interactions between TGFβ and collagenase, providing a more biologically realistic form for the growth factor kinetics than those included in previous mechanochemical descriptions. A comparison is made between the model predictions and experimental data on human dermal wound healing and all the essential features are well matched. © 2012 Society for Mathematical Biology.
Jiang, Ximiao; Huang, Baoshan; Yan, Xuedong; Zaretzki, Russell L; Richards, Stephen
2013-01-01
The severity of traffic-related injuries has been studied by many researchers in recent decades. However, the evaluation of many factors is still in dispute and, until this point, few studies have taken into account pavement management factors as points of interest. The objective of this article is to evaluate the combined influences of pavement management factors and traditional traffic engineering factors on the injury severity of 2-vehicle crashes. This study examines 2-vehicle rear-end, sideswipe, and angle collisions that occurred on Tennessee state routes from 2004 to 2008. Both the traditional ordered probit (OP) model and Bayesian ordered probit (BOP) model with weak informative prior were fitted for each collision type. The performances of these models were evaluated based on the parameter estimates and deviances. The results indicated that pavement management factors played identical roles in all 3 collision types. Pavement serviceability produces significant positive effects on the severity of injuries. The pavement distress index (PDI), rutting depth (RD), and rutting depth difference between right and left wheels (RD_df) were not significant in any of these 3 collision types. The effects of traffic engineering factors varied across collision types, except that a few were consistently significant in all 3 collision types, such as annual average daily traffic (AADT), rural-urban location, speed limit, peaking hour, and light condition. The findings of this study indicated that improved pavement quality does not necessarily lessen the severity of injuries when a 2-vehicle crash occurs. The effects of traffic engineering factors are not universal but vary by the type of crash. The study also found that the BOP model with a weak informative prior can be used as an alternative but was not superior to the traditional OP model in terms of overall performance.
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.
Recommendations on dose buildup factors used in models for calculating gamma doses for a plume
International Nuclear Information System (INIS)
Hedemann Jensen, P.; Thykier-Nielsen, S.
1980-09-01
Calculations of external γ-doses from radioactivity released to the atmosphere have been made using different dose buildup factor formulas. Some of the dose buildup factor formulas are used by the Nordic countries in their respective γ-dose models. A comparison of calculated γ-doses using these dose buildup factors shows that the γ-doses can be significantly dependent on the buildup factor formula used in the calculation. Increasing differences occur for increasing plume height, crosswind distance, and atmospheric stability and also for decreasing downwind distance. It is concluded that the most accurate γ-dose can be calculated by use of Capo's polynomial buildup factor formula. Capo-coefficients have been calculated and shown in this report for γ-energies below the original lower limit given by Capo. (author)
Rogers, Mary E; Glendon, A Ian
2018-01-01
This research reports on the 4-phase development of the 25-item Five-Factor Model Adolescent Personality Questionnaire (FFM-APQ). The purpose was to develop and determine initial evidence for validity of a brief adolescent personality inventory using a vocabulary that could be understood by adolescents up to 18 years old. Phase 1 (N = 48) consisted of item generation and expert (N = 5) review of items; Phase 2 (N = 179) involved item analyses; in Phase 3 (N = 496) exploratory factor analysis assessed the underlying structure; in Phase 4 (N = 405) confirmatory factor analyses resulted in a 25-item inventory with 5 subscales.
A Primary Human Critical Success Factors Model for the ERP System Implementation
Directory of Open Access Journals (Sweden)
Jenko Aleksander
2016-08-01
Full Text Available Background and Purpose: Many researchers have investigated various Critical success factors (CSFs and the different causes of ERP implementation project failures. Despite a detailed literature preview, we were unable to find an appropriate research with a comprehensive overview of the true causes behind CSFs, observed from a human factors perspective. The objective of this research was therefore to develop and evaluate the Primary human factors (PHFs model and to confirm the significant impact of PHFs on traditional CSFs and on the project success.
Bozhalkina, Yana; Timofeeva, Galina
2016-12-01
Mathematical model of loan portfolio in the form of a controlled Markov chain with discrete time is considered. It is assumed that coefficients of migration matrix depend on corrective actions and external factors. Corrective actions include process of receiving applications, interaction with existing solvent and insolvent clients. External factors are macroeconomic indicators, such as inflation and unemployment rates, exchange rates, consumer price indices, etc. Changes in corrective actions adjust the intensity of transitions in the migration matrix. The mathematical model for forecasting the credit portfolio structure taking into account a cumulative impact of internal and external changes is obtained.
A quantitative assessment of organizational factors affecting safety using system dynamics model
Energy Technology Data Exchange (ETDEWEB)
Yu, Jae Kook; Ahn, Nam Sung [Korea Electric Power Research Institute, Taejon (Korea, Republic of); Jae, Moo Sung [Hanyang Univ., Seoul (Korea, Republic of)
2004-02-01
The purpose of this study is to develop a system dynamics model for the assessment of the organizational and human factors in a nuclear power plant which contribute to nuclear safety. Previous studies can be classified into two major approaches. One is the engineering approach using tools such as ergonomics and Probability Safety Assessment (PSA). The other is the socio-psychology approach. Both have contributed to find organizational and human factors and to present guidelines to lessen human error in plants. However, since these approaches assume that the relationship among factors is independent they do not explain the interactions among the factors or variables in nuclear power plants. To overcome these restrictions, a system dynamics model, which can show cause and effect relationships among factors and quantify the organizational and human factors, has been developed. Handling variables such as the degree of leadership, the number of employees, and workload in each department, users can simulate various situations in nuclear power plant organization. Through simulation, users can get insights to improve safety in plants and to find managerial tools in both organizational and human factors.
A quantitative assessment of organizational factors affecting safety using system dynamics model
International Nuclear Information System (INIS)
Yu, Jae Kook; Ahn, Nam Sung; Jae, Moo Sung
2004-01-01
The purpose of this study is to develop a system dynamics model for the assessment of the organizational and human factors in a nuclear power plant which contribute to nuclear safety. Previous studies can be classified into two major approaches. One is the engineering approach using tools such as ergonomics and Probability Safety Assessment (PSA). The other is the socio-psychology approach. Both have contributed to find organizational and human factors and to present guidelines to lessen human error in plants. However, since these approaches assume that the relationship among factors is independent they do not explain the interactions among the factors or variables in nuclear power plants. To overcome these restrictions, a system dynamics model, which can show cause and effect relationships among factors and quantify the organizational and human factors, has been developed. Handling variables such as the degree of leadership, the number of employees, and workload in each department, users can simulate various situations in nuclear power plant organization. Through simulation, users can get insights to improve safety in plants and to find managerial tools in both organizational and human factors
Beyond the first episode: candidate factors for a risk prediction model of schizophrenia.
Murphy, Brendan P
2010-01-01
Many early psychosis services are financially compromised and cannot offer a full tenure of care to all patients. To maintain viability of services it is important that those with schizophrenia are identified early to maximize long-term outcomes, as are those with better prognoses who can be discharged early. The duration of untreated psychosis remains the mainstay in determining those who will benefit from extended care, yet its ability to inform on prognosis is modest in both the short and medium term. There are a number of known or putative genetic and environmental risk factors that have the potential to improve prognostication, though a multivariate risk prediction model combining them with clinical characteristics has yet to be developed. Candidate risk factors for such a model are presented, with an emphasis on environmental risk factors. More work is needed to corroborate many putative factors and to determine which of the established factors are salient and which are merely proxy measures. Future research should help clarify how gene-environment and environment-environment interactions occur and whether risk factors are dose-dependent, or if they act additively or synergistically, or are redundant in the presence (or absence) of other factors.
HOCOMOCO: a comprehensive collection of human transcription factor binding sites models
Kulakovskiy, Ivan V.; Medvedeva, Yulia A.; Schaefer, Ulf; Kasianov, Artem S.; Vorontsov, Ilya E.; Bajic, Vladimir B.; Makeev, Vsevolod J.
2013-01-01
Transcription factor (TF) binding site (TFBS) models are crucial for computational reconstruction of transcription regulatory networks. In existing repositories, a TF often has several models (also called binding profiles or motifs), obtained from different experimental data. Having a single TFBS model for a TF is more pragmatic for practical applications. We show that integration of TFBS data from various types of experiments into a single model typically results in the improved model quality probably due to partial correction of source specific technique bias. We present the Homo sapiens comprehensive model collection (HOCOMOCO, http://autosome.ru/HOCOMOCO/, http://cbrc.kaust.edu.sa/hocomoco/) containing carefully hand-curated TFBS models constructed by integration of binding sequences obtained by both low- and high-throughput methods. To construct position weight matrices to represent these TFBS models, we used ChIPMunk software in four computational modes, including newly developed periodic positional prior mode associated with DNA helix pitch. We selected only one TFBS model per TF, unless there was a clear experimental evidence for two rather distinct TFBS models. We assigned a quality rating to each model. HOCOMOCO contains 426 systematically curated TFBS models for 401 human TFs, where 172 models are based on more than one data source. PMID:23175603
HOCOMOCO: A comprehensive collection of human transcription factor binding sites models
Kulakovskiy, Ivan V.; Medvedeva, Yulia A.; Schaefer, Ulf; Kasianov, Artem S.; Vorontsov, Ilya E.; Bajic, Vladimir B.; Makeev, Vsevolod J.
2012-01-01
Transcription factor (TF) binding site (TFBS) models are crucial for computational reconstruction of transcription regulatory networks. In existing repositories, a TF often has several models (also called binding profiles or motifs), obtained from different experimental data. Having a single TFBS model for a TF is more pragmatic for practical applications. We show that integration of TFBS data from various types of experiments into a single model typically results in the improved model quality probably due to partial correction of source specific technique bias. We present the Homo sapiens comprehensive model collection (HOCOMOCO, http://autosome.ru/HOCOMOCO/, http://cbrc.kaust.edu.sa/ hocomoco/) containing carefully hand-curated TFBS models constructed by integration of binding sequences obtained by both low- and high-throughput methods. To construct position weight matrices to represent these TFBS models, we used ChIPMunk software in four computational modes, including newly developed periodic positional prior mode associated with DNA helix pitch. We selected only one TFBS model per TF, unless there was a clear experimental evidence for two rather distinct TFBS models. We assigned a quality rating to each model. HOCOMOCO contains 426 systematically curated TFBS models for 401 human TFs, where 172 models are based on more than one data source. The Author(s) 2012.
HOCOMOCO: A comprehensive collection of human transcription factor binding sites models
Kulakovskiy, Ivan V.
2012-11-21
Transcription factor (TF) binding site (TFBS) models are crucial for computational reconstruction of transcription regulatory networks. In existing repositories, a TF often has several models (also called binding profiles or motifs), obtained from different experimental data. Having a single TFBS model for a TF is more pragmatic for practical applications. We show that integration of TFBS data from various types of experiments into a single model typically results in the improved model quality probably due to partial correction of source specific technique bias. We present the Homo sapiens comprehensive model collection (HOCOMOCO, http://autosome.ru/HOCOMOCO/, http://cbrc.kaust.edu.sa/ hocomoco/) containing carefully hand-curated TFBS models constructed by integration of binding sequences obtained by both low- and high-throughput methods. To construct position weight matrices to represent these TFBS models, we used ChIPMunk software in four computational modes, including newly developed periodic positional prior mode associated with DNA helix pitch. We selected only one TFBS model per TF, unless there was a clear experimental evidence for two rather distinct TFBS models. We assigned a quality rating to each model. HOCOMOCO contains 426 systematically curated TFBS models for 401 human TFs, where 172 models are based on more than one data source. The Author(s) 2012.
Estimating safety effects of pavement management factors utilizing Bayesian random effect models.
Jiang, Ximiao; Huang, Baoshan; Zaretzki, Russell L; Richards, Stephen; Yan, Xuedong
2013-01-01
Previous studies of pavement management factors that relate to the occurrence of traffic-related crashes are rare. Traditional research has mostly employed summary statistics of bidirectional pavement quality measurements in extended longitudinal road segments over a long time period, which may cause a loss of important information and result in biased parameter estimates. The research presented in this article focuses on crash risk of roadways with overall fair to good pavement quality. Real-time and location-specific data were employed to estimate the effects of pavement management factors on the occurrence of crashes. This research is based on the crash data and corresponding pavement quality data for the Tennessee state route highways from 2004 to 2009. The potential temporal and spatial correlations among observations caused by unobserved factors were considered. Overall 6 models were built accounting for no correlation, temporal correlation only, and both the temporal and spatial correlations. These models included Poisson, negative binomial (NB), one random effect Poisson and negative binomial (OREP, ORENB), and two random effect Poisson and negative binomial (TREP, TRENB) models. The Bayesian method was employed to construct these models. The inference is based on the posterior distribution from the Markov chain Monte Carlo (MCMC) simulation. These models were compared using the deviance information criterion. Analysis of the posterior distribution of parameter coefficients indicates that the pavement management factors indexed by Present Serviceability Index (PSI) and Pavement Distress Index (PDI) had significant impacts on the occurrence of crashes, whereas the variable rutting depth was not significant. Among other factors, lane width, median width, type of terrain, and posted speed limit were significant in affecting crash frequency. The findings of this study indicate that a reduction in pavement roughness would reduce the likelihood of traffic
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).
International Nuclear Information System (INIS)
Yan Guanghua; Liu, Chihray; Lu Bo; Palta, Jatinder R; Li, Jonathan G
2008-01-01
The purpose of this study was to choose an appropriate head scatter source model for the fast and accurate independent planar dose calculation for intensity-modulated radiation therapy (IMRT) with MLC. The performance of three different head scatter source models regarding their ability to model head scatter and facilitate planar dose calculation was evaluated. A three-source model, a two-source model and a single-source model were compared in this study. In the planar dose calculation algorithm, in-air fluence distribution was derived from each of the head scatter source models while considering the combination of Jaw and MLC opening. Fluence perturbations due to tongue-and-groove effect, rounded leaf end and leaf transmission were taken into account explicitly. The dose distribution was calculated by convolving the in-air fluence distribution with an experimentally determined pencil-beam kernel. The results were compared with measurements using a diode array and passing rates with 2%/2 mm and 3%/3 mm criteria were reported. It was found that the two-source model achieved the best agreement on head scatter factor calculation. The three-source model and single-source model underestimated head scatter factors for certain symmetric rectangular fields and asymmetric fields, but similar good agreement could be achieved when monitor back scatter effect was incorporated explicitly. All the three source models resulted in comparable average passing rates (>97%) when the 3%/3 mm criterion was selected. The calculation with the single-source model and two-source model was slightly faster than the three-source model due to their simplicity
Energy Technology Data Exchange (ETDEWEB)
Yan Guanghua [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Liu, Chihray; Lu Bo; Palta, Jatinder R; Li, Jonathan G [Department of Radiation Oncology, University of Florida, Gainesville, FL 32610-0385 (United States)
2008-04-21
The purpose of this study was to choose an appropriate head scatter source model for the fast and accurate independent planar dose calculation for intensity-modulated radiation therapy (IMRT) with MLC. The performance of three different head scatter source models regarding their ability to model head scatter and facilitate planar dose calculation was evaluated. A three-source model, a two-source model and a single-source model were compared in this study. In the planar dose calculation algorithm, in-air fluence distribution was derived from each of the head scatter source models while considering the combination of Jaw and MLC opening. Fluence perturbations due to tongue-and-groove effect, rounded leaf end and leaf transmission were taken into account explicitly. The dose distribution was calculated by convolving the in-air fluence distribution with an experimentally determined pencil-beam kernel. The results were compared with measurements using a diode array and passing rates with 2%/2 mm and 3%/3 mm criteria were reported. It was found that the two-source model achieved the best agreement on head scatter factor calculation. The three-source model and single-source model underestimated head scatter factors for certain symmetric rectangular fields and asymmetric fields, but similar good agreement could be achieved when monitor back scatter effect was incorporated explicitly. All the three source models resulted in comparable average passing rates (>97%) when the 3%/3 mm criterion was selected. The calculation with the single-source model and two-source model was slightly faster than the three-source model due to their simplicity.
How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?
Bassu, Simona; Brisson, Nadine; Grassini, Patricio; Durand, Jean-Louis; Boote, Kenneth; Lizaso, Jon; Jones, James W.; Rosenzweig, Cynthia; Ruane, Alex C.; Adam, Myriam;
2014-01-01
Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(sup 1) per degC. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.
A pedestal temperature model with self-consistent calculation of safety factor and magnetic shear
International Nuclear Information System (INIS)
Onjun, T; Siriburanon, T; Onjun, O
2008-01-01
A pedestal model based on theory-motivated models for the pedestal width and the pedestal pressure gradient is developed for the temperature at the top of the H-mode pedestal. The pedestal width model based on magnetic shear and flow shear stabilization is used in this study, where the pedestal pressure gradient is assumed to be limited by first stability of infinite n ballooning mode instability. This pedestal model is implemented in the 1.5D BALDUR integrated predictive modeling code, where the safety factor and magnetic shear are solved self-consistently in both core and pedestal regions. With the self-consistently approach for calculating safety factor and magnetic shear, the effect of bootstrap current can be correctly included in the pedestal model. The pedestal model is used to provide the boundary conditions in the simulations and the Multi-mode core transport model is used to describe the core transport. This new integrated modeling procedure of the BALDUR code is used to predict the temperature and density profiles of 26 H-mode discharges. Simulations are carried out for 13 discharges in the Joint European Torus and 13 discharges in the DIII-D tokamak. The average root-mean-square deviation between experimental data and the predicted profiles of the temperature and the density, normalized by their central values, is found to be about 14%
Stochastic Optimization of Wind Turbine Power Factor Using Stochastic Model of Wind Power
DEFF Research Database (Denmark)
Chen, Peiyuan; Siano, Pierluigi; Bak-Jensen, Birgitte
2010-01-01
This paper proposes a stochastic optimization algorithm that aims to minimize the expectation of the system power losses by controlling wind turbine (WT) power factors. This objective of the optimization is subject to the probability constraints of bus voltage and line current requirements....... The optimization algorithm utilizes the stochastic models of wind power generation (WPG) and load demand to take into account their stochastic variation. The stochastic model of WPG is developed on the basis of a limited autoregressive integrated moving average (LARIMA) model by introducing a crosscorrelation...... structure to the LARIMA model. The proposed stochastic optimization is carried out on a 69-bus distribution system. Simulation results confirm that, under various combinations of WPG and load demand, the system power losses are considerably reduced with the optimal setting of WT power factor as compared...
ARMA Cholesky Factor Models for the Covariance Matrix of Linear Models.
Lee, Keunbaik; Baek, Changryong; Daniels, Michael J
2017-11-01
In longitudinal studies, serial dependence of repeated outcomes must be taken into account to make correct inferences on covariate effects. As such, care must be taken in modeling the covariance matrix. However, estimation of the covariance matrix is challenging because there are many parameters in the matrix and the estimated covariance matrix should be positive definite. To overcomes these limitations, two Cholesky decomposition approaches have been proposed: modified Cholesky decomposition for autoregressive (AR) structure and moving average Cholesky decomposition for moving average (MA) structure, respectively. However, the correlations of repeated outcomes are often not captured parsimoniously using either approach separately. In this paper, we propose a class of flexible, nonstationary, heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the covariance matrix that we denote as ARMACD. We analyze a recent lung cancer study to illustrate the power of our proposed methods.
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...
Cusack, Lynette; Smith, Morgan; Hegney, Desley; Rees, Clare S.; Breen, Lauren J.; Witt, Regina R.; Rogers, Cath; Williams, Allison; Cross, Wendy; Cheung, Kin
2016-01-01
Building nurses' resilience to complex and stressful practice environments is necessary to keep skilled nurses in the workplace and ensuring safe patient care. A unified theoretical framework titled Health Services Workplace Environmental Resilience Model (HSWERM), is presented to explain the environmental factors in the workplace that promote nurses' resilience. The framework builds on a previously-published theoretical model of individual resilience, which identified the key constructs of p...
Modeling Child Development Factors for the Early Introduction of ICTs in Schools
K. E. Oyetade; S. D. Eyono Obono
2015-01-01
One of the fundamental characteristics of Information and Communication Technology (ICT) has been the ever-changing nature of continuous release and models of ICTs with its impact on the academic, social, and psychological benefits of its introduction in schools. However, there seems to be a growing concern about its negative impact on students when introduced early in schools for teaching and learning. This study aims to design a model of child development factors affect...
Analytical expressions for two-nucleon transfer spectroscopic factors in sdg interacting boson model
International Nuclear Information System (INIS)
Devi, Y.D.; Kota, V.K.B.
1991-01-01
Analytical expressions for two-nucleon (l = 0,2 and 4) transfer spectroscopic factors are derived in the SU sdg (3) limit of the sdg interacting boson model. In addition, large N (boson number) limit expressions for the ratio of summed l = 0 transfer strength to excited 0 + states to that of ground state are derived in all the symmetry limits of the sdg model. Some comparisons with data are made. (author)
Analytical expressions for two-nucleon transfer spectroscopic factors in sdg interacting boson model
Energy Technology Data Exchange (ETDEWEB)
Devi, Y.D.; Kota, V.K.B. (Physical Research Lab., Ahmedabad (India))
1991-11-01
Analytical expressions for two-nucleon (l = 0,2 and 4) transfer spectroscopic factors are derived in the SU{sub sdg}(3) limit of the sdg interacting boson model. In addition, large N (boson number) limit expressions for the ratio of summed l = 0 transfer strength to excited 0{sup +} states to that of ground state are derived in all the symmetry limits of the sdg model. Some comparisons with data are made. (author).
Antecedents Factors that Influence Soy Consumption: A Structural Equation Modeling Approach
Balasubramanian, Siva K.; Moon, Wanki; Rimal, Arbindra; Coker, Kesha
2009-01-01
We propose a structural model of antecedent factors that affect the frequency of soy consumption. This model, suggests that soy-general knowledge influences perceptions about nutrition concern, health benefits of soy, soy related personal beliefs and personal attitudes toward soy. Health benefits of soy, in turn, impacts soy-related personal beliefs and personal attitudes toward soy. Additionally, soy-related personal beliefs influence personal attitudes toward soy. Finally, both nutrition co...
Lepton Flavor Violation in the Two Higgs Doublet Model using g-2 muon factor
International Nuclear Information System (INIS)
Diaz, Rodolfo A.; Martinez, R.; Rodriguez, J.-Alexis; Tuiran, E.
2002-01-01
Current experimental data from the g-2 muon factor, seems to show the necessity of physics beyond the Standard Model (SM), since the difference between SM and experimental predictions is approximately 2.6σ. In the framework of the General Two Higgs Doublet Model (2HDM), we calculate the muon anomalous magnetic moment to get lower and upper bounds for the Flavour Changing (FC) Yukawa couplings in the leptonic sector
Forming Factors And Builder Indicators Of Brand Personality Models In Traditional Retail Traders
Directory of Open Access Journals (Sweden)
Yunelly Asra
2017-12-01
Full Text Available This study aims to find the factors forming and indicator builder model of brand personality of traditional retail traders through measuring the influence of retail mix and culture. The formation of brand personality uses Aaker brand personality dimension to 250 consumers in Bengkalis Regency. The type of research is causal research design. The research variables are brand personality Retail Mix and Brand Personality. Data collection is done by probability sampling with purposive method. Data analysis was done by perception analysis frequency distribution and multiple regression using SPSS version 21.0. The results of this study are The factor of retail mix partially has a positive and significant impact on the brand personality of traditional retail traders in Bengkalis Regency. Factor cultural partially does not affect the brand personality of traditional retail traders in Bengkalis Regency. Simultaneously retail mix and cultural have positive and significant influence on traditional brand traders brand personality in Bengkalis Regency. Initial forming factor of brand personality model of traditional retail traders in Bengkalis Regency is Retail Mix Factor. Indicator of the model of traditional traders brand personality builder in Bengkalis are sincerity excitement competence sophistication competence ruggedness.
A survey of the influencing factors and models for resident's household waste management behavior
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The problem of household solid waste has been concerned and researched on by municipalities and researchers.At present, household solid waste has been changed to management problem from technical one. From the point view of management, the research on household solid waste is to study the factors which influence resident's behavior of managtng their waste. Based on the literature review, firstly, this paper summarizes those factors which have already been identified to have impact on resident's behavior of managing their waste. They are social-demographic variables,knowledge, environmental values, psychological factors, publicity and system design. Secondly, three typical models of the relationship between factors and behavior, which are factors determining task performance in waste management,conceptualization of waste management behavior and the theoretical model of repeated behavior on household waste management, are analyzed and the deficiencies of these models are also analyzed. Finally, according to the current situation in household waste management and the culture and resident's habits in China, this paper puts forward a research focus and suggestions about resident 's behavior of household solid waste management.
Modeling the thermal absorption factor of photovoltaic/thermal combi-panels
International Nuclear Information System (INIS)
Santbergen, R.; Zolingen, R.J.Ch. van
2006-01-01
In a photovoltaic/thermal combi-panel solar cells generate electricity while residual heat is extracted to be used for tap water heating or room heating. In such a panel the entire solar spectrum can be used in principle. Unfortunately long wavelength solar irradiance is poorly absorbed by the semiconductor material in standard solar cells. A computer model was developed to determine the thermal absorption factor of crystalline silicon solar cells. It was found that for a standard untextured solar cell with a silver back contact a relatively large amount of long wavelength irradiance is lost by reflection resulting in an absorption factor of only 74%. The model was then used to investigate ways to increase this absorption factor. One way is absorbing long wavelength irradiance in a second absorber behind a semi-transparent solar cell. According to the model this will increase the total absorption factor to 87%. The second way is to absorb irradiance in the back contact of the solar cell by using rough interfaces in combination with a non-standard metal as back contact. Theoretically the absorption factor can then be increased to 85%
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.
A quantitative assessment of organizational factors affecting safety using a system dynamics model
Energy Technology Data Exchange (ETDEWEB)
Yoo, J. K. [Systemix Company, Seoul (Korea, Republic of); Yoon, T. S. [Korea Electric Power Research Institute (Korea, Republic of)
2003-07-01
The purpose of this study is to develop a system dynamics model for the assessment of organizational and human factors in the nuclear power plant safety. Previous studies are classified into two major approaches. One is the engineering approach such as ergonomics and Probabilistic Safety Assessment (PSA). The other is socio-psychology one. Both have contributed to find organizational and human factors and increased nuclear safety However, since these approaches assume that the relationship among factors is independent they do not explain the interactions between factors or variables in NPP's. To overcome these restrictions, a system dynamics model, which can show causal relations between factors and quantify organizational and human factors, has been developed. Operating variables such as degree of leadership, adjustment of number of employee, and workload in each department, users can simulate various situations in nuclear power plants in the organization side. Through simulation, user can get an insight to improve safety in plants and to find managerial tools in the organization and human side.
A quantitative assessment of organizational factors affecting safety using a system dynamics model
International Nuclear Information System (INIS)
Yoo, J. K.; Yoon, T. S.
2003-01-01
The purpose of this study is to develop a system dynamics model for the assessment of organizational and human factors in the nuclear power plant safety. Previous studies are classified into two major approaches. One is the engineering approach such as ergonomics and Probabilistic Safety Assessment (PSA). The other is socio-psychology one. Both have contributed to find organizational and human factors and increased nuclear safety However, since these approaches assume that the relationship among factors is independent they do not explain the interactions between factors or variables in NPP's. To overcome these restrictions, a system dynamics model, which can show causal relations between factors and quantify organizational and human factors, has been developed. Operating variables such as degree of leadership, adjustment of number of employee, and workload in each department, users can simulate various situations in nuclear power plants in the organization side. Through simulation, user can get an insight to improve safety in plants and to find managerial tools in the organization and human side
Creemers, Bert; Kyriakides, Leonidas
2010-01-01
The dynamic model of educational effectiveness defines school level factors associated with student outcomes. Emphasis is given to the two main aspects of policy, evaluation, and improvement in schools which affect quality of teaching and learning at both the level of teachers and students: a)
Savolainen, Reijo
2015-01-01
Introduction: The article contributes to the conceptual studies of affective factors in information seeking by examining Kuhlthau's information search process model. Method: This random-digit dial telephone survey of 253 people (75% female) living in a rural, medically under-serviced area of Ontario, Canada, follows-up a previous interview study…
Vascular risk factors and Alzheimer’s disease. Therapeutic approaches in mouse models
Wiesmann, M.
2017-01-01
The first aim of this thesis was to elucidate the impact of major vascular risk factors like hypertension, apoE4 and stroke during the very early phase of Alzheimer’s disease (AD) using several mice models. Hypertension has proven to be associated with cerebrovascular impairment already at young age
Nucleon electromagnetic form factors in a relativistic quark model with chiral symmetry
International Nuclear Information System (INIS)
Barik, N.
1987-01-01
The nucleon electromagnetic form factors are computed in an independent quark model based on the Dirac equation. Corrections for centre-of-mass motion and pion-cloud effects are incorporated. Results for static quantities are in reasonable agreement with the experimental data. (author)
Nucleon electromagnetic form factors in a relativistic quark model with chiral symmetry
Energy Technology Data Exchange (ETDEWEB)
Barik, N; Das, M
1987-05-01
The nucleon electromagnetic form factors are computed in an independent quark model based on the Dirac equation. Corrections for centre-of-mass motion and pion-cloud effects are incorporated. Results for static quantities are in reasonable agreement with the experimental data.
The Predictive Effect of Big Five Factor Model on Social Reactivity ...
African Journals Online (AJOL)
The study tested a model of providing a predictive explanation of Big Five Factor on social reactivity among secondary school adolescents of Cross River State, Nigeria. A sample of 200 students randomly selected across 12 public secondary schools in the State participated in the study (120 male and 80 female). Data ...
A two-factor, stochastic programming model of Danish mortgage-backed securities
DEFF Research Database (Denmark)
Nielsen, Søren S.; Poulsen, Rolf
2004-01-01
-trivial, both in terms of deciding on an initial mortgage, and in terms of managing (rebalancing) it optimally.We propose a two-factor, arbitrage-free interest-rate model, calibrated to observable security prices, and implement on top of it a multi-stage, stochastic optimization program with the purpose...
Verification of Overall Safety Factors In Deterministic Design Of Model Tested Breakwaters
DEFF Research Database (Denmark)
Burcharth, H. F.
2001-01-01
The paper deals with concepts of safety implementation in design. An overall safety factor concept is evaluated on the basis of a reliability analysis of a model tested rubble mound breakwater with monolithic super structure. Also discussed are design load identification and failure mode limit...
Directory of Open Access Journals (Sweden)
Susanne Eva Tanner
2015-10-01
Full Text Available Connectivity is a critical property of marine fish populations as it drives population replenishment, determines colonization patterns and the resilience of populations to harvest. Understanding connectivity patterns is particularly important in species that present ontogenetic migrations and segregated habitat use during their life history, such as marine species with estuarine nursery areas. Albeit challenging, fish movement can be estimated and quantified using different methodologies depending on the life history stages of interest (e.g. biophysical modelling, otolith chemistry, genetic markers. Relative contributions from estuarine nursery areas to the adult coastal populations were determined using otolith elemental composition and maximum likelihood estimation for four commercially important species (Dicentrarchus labrax, Plathichtys flesus, Solea senegalensis and Solea solea and showed high interannual variability. Here, the effects of abiotic and biotic factors on the observed variability in connectivity rates and extent between estuarine juvenile and coastal adult subpopulations are investigated using generalized linear models (GLM and generalized mixed models (GMM. Abiotic factors impacting both larval and juvenile life history stages are included in the models (e.g. wind force and direction, NAO, water temperature while biotic factors relative to the estuarine residency of juvenile fish are evaluated (e.g. juvenile density, food availability. Factors contributing most to the observed variability in connectivity rates are singled out and compared among species. General trends are identified and results area discussed in the general context of identifying potential management frameworks applicable to different life stages and which may prove useful for ontogenetically migrating species.
Conceptualizations of Personality Disorders with the Five Factor Model-Count and Empathy Traits
Kajonius, Petri J.; Dåderman, Anna M.
2017-01-01
Previous research has long advocated that emotional and behavioral disorders are related to general personality traits, such as the Five Factor Model (FFM). The addition of section III in the latest "Diagnostic and Statistical Manual of Mental Disorders" (DSM) recommends that extremity in personality traits together with maladaptive…
Meson form factors and covariant three-dimensional formulation of the composite model
International Nuclear Information System (INIS)
Skachkov, N.B.; Solovtsov, I.L.
1979-01-01
An apparatus is developed which allows within the relativistic quark model, to find explicit expressions for meson form factors in terms of the wave functions of two-quark system that obey the covariant two-particle quasipotential equation. The exact form of wave functions is obtained by passing to the relativistic configurational representation. As an example, the quark Coulomb interaction is considered
Raynor, Douglas A.; Levine, Heidi
2009-01-01
Objective: In fall 2006, the authors examined associations between the five-factor model of personality and several key health behaviors. Methods: College students (N = 583) completed the American College Health Association-National College Health Assessment and the International Personality Item Pool Big Five short-form questionnaire. Results:…
Integrals of random fields treated by the model correction factor method
DEFF Research Database (Denmark)
Franchin, P.; Ditlevsen, Ove Dalager; Kiureghian, Armen Der
2002-01-01
The model correction factor method (MCFM) is used in conjunction with the first-order reliability method (FORM) to solve structural reliability problems involving integrals of non-Gaussian random fields. The approach replaces the limit-state function with an idealized one, in which the integrals ...
DEFF Research Database (Denmark)
Franchin, P.; Ditlevsen, Ove Dalager; Kiureghian, Armen Der
2002-01-01
The model correction factor method (MCFM) is used in conjunction with the first-order reliability method (FORM) to solve structural reliability problems involving integrals of non-Gaussian random fields. The approach replaces the limit-state function with an idealized one, in which the integrals ...
The performance of multi-factor term structure models for pricing and hedging caps and swaptions
Driessen, J.J.A.G.; Klaassen, P.; Melenberg, B.
2000-01-01
In this paper we empirically compare a wide range of different term structure models when it comes to the pricing and, in particular, hedging of caps and swaptions. We analyze the influence of the number of factors on the hedging and pricing results, and investigate which type of data "interest rate
The Performance of Multi-Factor Term Structure Models for Pricing and Hedging Caps and Swaptions
Driessen, J.J.A.G.; Klaassen, P.; Melenberg, B.
2000-01-01
In this paper we empirically compare different term structure models when it comes to the pricing and hedging of caps and swaptions.We analyze the influence of the number of factors on the pricing and hedging results, and investigate which type of data -interest rate data or derivative price data-
A Four- and Five-Factor Structural Model for Wechsler Tests: Does It Really Matter Clinically?
Schwartz, David M.
2013-01-01
The purpose of this commentary is to focus on the clinical utility of the four- and five-factor structural models for the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) and Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). It provides a discussion of important considerations when evaluating the clinical utility of the…
Fung, Karen; ElAtia, Samira
2015-01-01
Using Hierarchical Linear Modelling (HLM), this study aimed to identify factors such as ESL/ELL/EAL status that would predict students' reading performance in an English language arts exam taken across Canada. Using data from the 2007 administration of the Pan-Canadian Assessment Program (PCAP) along with the accompanying surveys for students and…
Humphrey, Neil; Wigelsworth, Michael
2012-01-01
The current study explores some of the factors associated with children's mental health difficulties in primary school. Multilevel modeling with data from 628 children from 36 schools was used to determine how much variation in mental health difficulties exists between and within schools, and to identify characteristics at the school and…
Omar, Zoharah; Ahmad, Aminah
2014-01-01
Following the classic systems model of inputs, processes, and outputs, this study examined the influence of three input factors, team climate, work overload, and team leadership, on research project team effectiveness as measured by publication productivity, team member satisfaction, and job frustration. This study also examined the mediating…
Czech Academy of Sciences Publication Activity Database
Horáček, Jaromír; Laukkanen, A. M.; Šidlof, Petr; Murphy, P.; Švec, J. G.
2009-01-01
Roč. 61, č. 3 (2009), s. 137-145 ISSN 1021-7762 R&D Projects: GA ČR(CZ) GA101/08/1155 Institutional research plan: CEZ:AV0Z20760514 Keywords : biomechanics of voice modeling * fundamental frequency * phoniation type * gender differences in voice Subject RIV: BI - Acoustics Impact factor: 1.439, year: 2007
Karanikas, Nektarios; Schwarz, M; Harfmann, J
2017-01-01
A symbiotic relationship between human factors and safety scientists is needed to ensure the provision of holistic solutions for problems emerging in modern socio-technical systems. System Theoretic Accident Model and Processes (STAMP) tackles both interactions and individual failures of human and
Situational effects of the school factors included in the dynamic model of educational effectiveness
Creerners, Bert; Kyriakides, Leonidas
We present results of a longitudinal study in which 50 schools, 113 classes and 2,542 Cypriot primary students participated. We tested the validity of the dynamic model of educational effectiveness and especially its assumption that the impact of school factors depends on the current situation of
1/M corrections to baryonic form factors in the quark model
International Nuclear Information System (INIS)
Cheng, H.; Tseng, B.
1996-01-01
Weak current-induced baryonic form factors at zero recoil are evaluated in the rest frame of the heavy parent baryon using the nonrelativistic quark model. Contrary to previous similar work in the literature, our quark model results do satisfy the constraints imposed by heavy quark symmetry for heavy-heavy baryon transitions at the symmetric point v·v'=1 and are in agreement with the predictions of the heavy quark effective theory for antitriplet-antitriplet heavy baryon form factors at zero recoil evaluated to order 1/m Q . Furthermore, the quark model approach has the merit that it is applicable to any heavy-heavy and heavy-light baryonic transitions at maximum q 2 . Assuming a dipole q 2 behavior, we have applied the quark model form factors to nonleptonic, semileptonic, and weak radiative decays of the heavy baryons. It is emphasized that the flavor suppression factor occurring in many heavy-light baryonic transitions, which is unfortunately overlooked in most literature, is very crucial towards an agreement between theory and experiment for the semileptonic decay Λ c →Λe + ν e . Predictions for the decay modes Λ b →J/ψΛ, Λ c →pφ, Λ b →Λγ, Ξ b →Ξγ, and for the semileptonic decays of Λ b , Ξ b, c, and Ω b are presented. copyright 1996 The American Physical Society
Job Satisfaction and Personality: The Utility of the Five-Factor Model of Personality
1999-03-01
represented by E, symbolizes the focus on the P-E interaction (Dawis, 1992). Even prior to Lewin, Parsons (1909) emphasized this same concept in the...Personality structure: Emergence of the five-factor model. Annual Review of Psychology. 41. 417-440. Ekehammar, B. (1974). Interactionism in personality
Factors Predicting Sustainability of the Schoolwide Positive Behavior Intervention Support Model
Chitiyo, Jonathan; May, Michael E.
2018-01-01
The Schoolwide Positive Behavior Intervention Support model (SWPBIS) continues to gain widespread use across schools in the United States and abroad. Despite its widespread implementation, little research has examined factors that influence its sustainability. Informed by Rogers's diffusion theory, this study examined school personnel's…
Pohlmeyer, J. V.; Waters, S. L.; Cummings, L. J.
2013-01-01
nutrient-rich culture medium is perfused through a 2D porous scaffold impregnated with growth factor and seeded with cells. We model these processes on the timescale of cell proliferation, which typically is of the order of days. While a quantitative
[Risk factors of eating disorders in the narratives of fashion models].
Bogár, Nikolett; Túry, Ferenc
2017-01-01
The risk of eating disorders is high in populations who are exposed to slimness ideal, so among fashion models. The present qualitative study evaluates the risk factors of eating disorders in a group of fashion models with semistructured interview. Moreover, the aim of the study was to examine the impact of professional requirements on the health of models. The study group was internationally heterogeneous. The models were involved by personal professional relationship. A semistructured questionnaire was used by e-mail containing anthropometric data and different aspects of the model profession. 29 female and three male models, three agents, two designers, three fotographers, one personal trainer and one stylist answered the questionnaire. Transient bulimic symptoms were reported by six female models (21%). Moreover, five female models fulfilled the DSM-5 criteria of anorexia nervosa or bulimia nervosa. Four of them were anorexic (body mass index: 13.9-15.3), one was bulimic. The symptoms of three persons began before the model career, those of two models after it. 17 models reported that the model profession intensively increased the bodily preoccupations. The study corroborates the effect of the model profession on the increase of the risk for eating disorders. In the case of the models, whose eating disorder began after stepping into the model profession, the role of the representants of the fashion industry can be suggested as a form of psychological abuse. As the models or in the case of underages their parents accepted the strong requirement of slimness, an unconscious collusion is probable. Our date highlight the health impact of cultural ideals, and call the attention to prevention strategies.
Pohlmeyer, J. V.
2013-01-29
Motivated by experimental work (Miller et al. in Biomaterials 27(10):2213-2221, 2006, 32(11):2775-2785, 2011) we investigate the effect of growth factor driven haptotaxis and proliferation in a perfusion tissue engineering bioreactor, in which nutrient-rich culture medium is perfused through a 2D porous scaffold impregnated with growth factor and seeded with cells. We model these processes on the timescale of cell proliferation, which typically is of the order of days. While a quantitative representation of these phenomena requires more experimental data than is yet available, qualitative agreement with preliminary experimental studies (Miller et al. in Biomaterials 27(10):2213-2221, 2006) is obtained, and appears promising. The ultimate goal of such modeling is to ascertain initial conditions (growth factor distribution, initial cell seeding, etc.) that will lead to a final desired outcome. © 2013 Society for Mathematical Biology.
Electromagnetic and Scalar Pion form factor in the Kroll-Lee-Zumino model
International Nuclear Information System (INIS)
Dominguez, C.A.; Jottar, J.I.; Loewe, M.; Willers, B.
2009-01-01
The renormalizable Abelian quantum field theory model of Kroll, Lee, and Zumino is used at the one loop level to compute vertex corrections to the tree-level, Vector Meson Dominance (VMD) electromagnetic pion form factor. These corrections, together with the one-loop vacuum polarization contribution, imply a resulting electromagnetic pion form factor in excellent agreement with data in the whole range of accessible momentum transfers in the space-like region. The time-like form factor, which reproduces the Gounaris-Sakurai formula at and near the rho-meson peak, is unaffected by the vertex correction at order O(g 2 ). The KLZ model is also used to compute the scalar radius of the pion at the one loop level, finding π 2 > S =0.40fm 2 . This value implies for the low energy constant of chiral perturbation theory l-bar 4 =3.4
Modification of transition's factor in the compact surface-potential-based MOSFET model
Directory of Open Access Journals (Sweden)
Kevkić Tijana
2016-01-01
Full Text Available The modification of an important transition's factor which enables continual behavior of the surface potential in entire useful range of MOSFET operation is presented. The various modifications have been made in order to obtain an accurate and computationally efficient compact MOSFET model. The best results have been achieved by introducing the generalized logistic function (GL in fitting of considered factor. The smoothness and speed of the transition of the surface potential from the depletion to the strong inversion region can be controlled in this way. The results of the explicit model with this GL functional form for transition's factor have been verified extensively with the numerical data. A great agreement was found for a wide range of substrate doping and oxide thickness. Moreover, the proposed approach can be also applied on the case where quantum mechanical effects play important role in inversion mode.
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.
Bethe Ansatz and exact form factors of the O(N) Gross Neveu-model
International Nuclear Information System (INIS)
Babujian, Hrachya M.; Foerster, Angela; Karowski, Michael
2016-01-01
We apply previous results on the O(N) Bethe Ansatz http://dx.doi.org/10.1088/1751-8113/45/5/055207, http://arxiv.org/abs/1204.3479, http://dx.doi.org/10.1007/JHEP11(2013)089 to construct a general form factor formula for the O(N) Gross-Neveu model. We examine this formula for several operators, such as the energy momentum, the spin-field and the current. We also compare these results with the 1/N expansion of this model and obtain full agreement. We discuss bound state form factors, in particular for the three particle form factor of the field. In addition for the two particle case we prove a recursion relation for the K-functions of the higher level Bethe Ansatz.
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.
Jang, Seon-Kyeong; Choi, Hye-Im; Park, Soohyun; Jaekal, Eunju; Lee, Ga-Young; Cho, Young Il; Choi, Kee-Hong
2016-01-01
Acknowledging separable factors underlying negative symptoms may lead to better understanding and treatment of negative symptoms in individuals with schizophrenia. The current study aimed to test whether the negative symptoms factor (NSF) of the Positive and Negative Syndrome Scale (PANSS) would be better represented by expressive and experiential deficit factors, rather than by a single factor model, using confirmatory factor analysis (CFA). Two hundred and twenty individuals with schizophrenia spectrum disorders completed the PANSS; subsamples additionally completed the Brief Negative Symptom Scale (BNSS) and the Motivation and Pleasure Scale-Self-Report (MAP-SR). CFA results indicated that the two-factor model fit the data better than the one-factor model; however, latent variables were closely correlated. The two-factor model's fit was significantly improved by accounting for correlated residuals between N2 (emotional withdrawal) and N6 (lack of spontaneity and flow of conversation), and between N4 (passive social withdrawal) and G16 (active social avoidance), possibly reflecting common method variance. The two NSF factors exhibited differential patterns of correlation with subdomains of the BNSS and MAP-SR. These results suggest that the PANSS NSF would be better represented by a two-factor model than by a single-factor one, and support the two-factor model's adequate criterion-related validity. Common method variance among several items may be a potential source of measurement error under a two-factor model of the PANSS NSF.
Xu, Lihua; Wubbena, Zane; Stewart, Trae
2016-01-01
Purpose: The purpose of this paper is to investigate the factor structure and the measurement invariance of the Multifactor Leadership Questionnaire (MLQ) across gender of K-12 school principals (n=6,317) in the USA. Design/methodology/approach: Nine first-order factor models and four second-order factor models were tested using confirmatory…
Panagos, P.; Borrelli, P.; Meusburger, K.; van der Zanden, E.H.; Poesen, J.; Alewell, C.
2015-01-01
The USLE/RUSLE support practice factor (P-factor) is rarely taken into account in soil erosion risk modelling at sub-continental scale, as it is difficult to estimate for large areas. This study attempts to model the P-factor in the European Union. For this, it considers the latest policy
DEFF Research Database (Denmark)
Callot, Laurent; Kristensen, Johannes Tang
This paper shows that the parsimoniously time-varying methodology of Callot and Kristensen (2015) can be applied to factor models.We apply this method to study macroeconomic instability in the US from 1959:1 to 2006:4 with a particular focus on the Great Moderation. Models with parsimoniously time...... that the parameters of both models exhibit a higher degree of instability in the period from 1970:1 to 1984:4 relative to the following 15 years. In our setting the Great Moderation appears as the gradual ending of a period of high structural instability that took place in the 1970s and early 1980s....
Model for next-to-leading order threshold resummed form factors
International Nuclear Information System (INIS)
Aglietti, Ugo; Ricciardi, Giulia
2004-01-01
We present a model for next-to-leading order resummed threshold form factors based on a timelike coupling recently introduced in the framework of small x physics. Improved expressions for the form factors in N-space are obtained which are not plagued by Landau-pole singularities, as the included absorptive effects - usually neglected - act as regulators. The physical reason is that, because of faster decay of gluon jets, there is not enough resolution time to observe the Landau pole. Our form factors reduce to the standard ones when the absorptive parts related to the coupling are neglected. The inverse transform from N-space to x-space can be done directly without any prescription and we obtain analytical expressions for the form factors, which are well defined in all x-space
Directory of Open Access Journals (Sweden)
Rina Wu
2016-02-01
Full Text Available Studying the influencing factors of carbon dioxide emissions is not only practically but also theoretically crucial for establishing regional carbon-reduction policies, developing low-carbon economy and solving the climate problems. Therefore, we used a geographical detector model which is consists of four parts, i.e., risk detector, factor detector, ecological detector and interaction detector to analyze the effect of these social economic factors, i.e., GDP, industrial structure, urbanization rate, economic growth rate, population and road density on the increase of energy consumption carbon dioxide emissions in industrial sector in Inner Mongolia northeast of China. Thus, combining with the result of four detectors, we found that GDP and population more influence than economic growth rate, industrial structure, urbanization rate and road density. The interactive effect of any two influencing factors enhances the increase of the carbon dioxide emissions. The findings of this research have significant policy implications for regions like Inner Mongolia.
Overview of Building Information Modelling (BIM) adoption factors for construction organisations
Mohammad, W. N. S. Wan; Abdullah, M. R.; Ismail, S.; Takim, R.
2018-04-01
Improvement and innovation in building visualization, project coordination and communication are the major benefits generated by Building Information Modelling (BIM) for construction organisations. Thus, as many firms across the world would adopt BIM, however they do not know the clear direction in which path they are moving as there is no specific reference available for them to refer to. Hence, the paper seeks to identify the factors of BIM adoption from previous research. The methodology used in this paper is based on literature review from various sources such as conference articles and journals. Then, the findings were analysed using content analysis. The findings show that there are 24 factors found from literature that influence the adoption of BIM and four (4) factors such as vendor, organisational vision, knowledge, and implementation plan are among the least factors mentioned by previous researchers.
Modelling the critical success factors of agile software development projects in South Africa
Directory of Open Access Journals (Sweden)
Tawanda B. Chiyangwa
2017-10-01
Full Text Available Background: The continued in failure of agile and traditional software development projects have led to the consideration, attention and dispute to critical success factors that are the aspects which are most vital to make a software engineering methodology fruitful. Although there is an increasing variety of critical success factors and methodologies, the conceptual frameworks which have causal relationship are limited. Objective: The objective of this study was to identify and provide insights into the critical success factors that influence the success of software development projects using agile methodologies in South Africa. Method: Quantitative method of collecting data was used. Data were collected in South Africa through a Web-based survey using structured questionnaires. Results: These results show that organisational factors have a great influence on performance expectancy characteristics. Conclusion: The results of this study discovered a comprehensive model that could provide guidelines to the agile community and to the agile professionals.
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.
Application of Delphi method for determining the affecting factors upon audit risk model
Directory of Open Access Journals (Sweden)
Zohreh Hajiha
2012-01-01
Full Text Available The assessment of risks in an audit work could directly influence the costs, timing, and strategies as well as audit quality. The purpose of this paper is to identify the critical affecting factors on risks proposed in Audit Risk Model (ARM, in Iranian audit environment of Iran. In the present, the Delphi Method consists of 60 audit partners and managers is employed. The panel consists of two equally divided groups, one from audit organization, a governmental organization, and the other from private audit firms. We employ two rounds of Delphi and 58 critical risk factors extracted from auditing literature and Iranian auditing standards and present them to the experts. There are 43 factors categorized as important factors to assess the risks in ARM. The results are considerable in an Iranian audit environment, findings show the most important factors are in inherent risk factors. Finally, we made a comparison with a similar study in Taiwan. Differences indicate that in professional judgment issues like risk assessment, the consideration of particular culture and environment could help enhance the precision of assessments, especially in assessing control risk factors.
Analyzing Factors Influencing Teaching as a Career Choice Using Structural Equation Modeling
Directory of Open Access Journals (Sweden)
Budhinath Padhy
2015-02-01
Full Text Available The purpose of the study is to analyze factors influencing students’ perceptions of teaching as a career choice using structural equation modeling with the goal of shaping a teacher education recruitment program. In this study, 458 students from a Midwestern university in the United States responded to an online survey about career-related factors they value, their expectation that teaching would offer those factors, and any social-influence factors that might encourage them to choose a teaching career. The effect of 10 exogenous motivation variables (value-environment, value-intrinsic, value-extrinsic, value-altruistic, expectancy-environment, expectancy-intrinsic, expectancy-extrinsic, social-media-education, social-prior-experience, and social-suggestions on choosing a teaching career was examined. Results of our analysis showed that the factors related to expectancy-environment, expectancy-intrinsic, social-media-education, social-prior-experience, and social-suggestions were found to be significant, whereas value-related factors and expectancy-extrinsic factors were found to be insignificant.
Alboni, Paolo; Alboni, Marco
2006-11-01
Conventional risk factors (abnormal lipids, hypertension, etc.) are independent predictors of atherosclerosis and cardiovascular events; however, these factors are not specific since about half patients with acute myocardial infarction paradoxically result at low cardiovascular risk. Recent prospective studies provide convincing evidence that some psychosocial factors are independent predictors of atherosclerosis and cardiovascular events, as well. Psychosocial factors that promote atherosclerosis can be divided into two general categories: chronic stressors, including social isolation/low social support and work stress (subordination without job control) and emotional factors, including affective disorders such as depression, severe anxiety and hostility/anger. The emotional factors, such as the chronic stressors, activate the biological mechanisms of chronic stress: increased activity of the hypothalamic-pituitary-adrenal axis, sympathetic system and inflammation processes, which have atherogenic effects, and an increase in blood coagulation. In spite of the amount of published data, psychosocial factors receive little attention in the medical setting. About 30 years ago, Kuller defined the criteria for a causal relation between a risk factor and atherosclerosis and cardiac events. The first of these criteria states that experimental research should demonstrate that any new factor would increase the extent of atherosclerosis or its complications in suitable animal models. We carried out a bibliographic research in order to investigate whether the results of the studies dealing with animal examination and experimentation support the psychosocial factors as predictors of atherosclerosis. Contributions related to some of the psychosocial factors such as social isolation, subordination and hostility/anger have been found. In these studies atherosclerotic extension has been evaluated at necroscopy; however, the incidence of cardiovascular events has not been
Granularity as a Cognitive Factor in the Effectiveness of Business Process Model Reuse
Holschke, Oliver; Rake, Jannis; Levina, Olga
Reusing design models is an attractive approach in business process modeling as modeling efficiency and quality of design outcomes may be significantly improved. However, reusing conceptual models is not a cost-free effort, but has to be carefully designed. While factors such as psychological anchoring and task-adequacy in reuse-based modeling tasks have been investigated, information granularity as a cognitive concept has not been at the center of empirical research yet. We hypothesize that business process granularity as a factor in design tasks under reuse has a significant impact on the effectiveness of resulting business process models. We test our hypothesis in a comparative study employing high and low granularities. The reusable processes provided were taken from widely accessible reference models for the telecommunication industry (enhanced Telecom Operations Map). First experimental results show that Recall in tasks involving coarser granularity is lower than in cases of finer granularity. These findings suggest that decision makers in business process management should be considerate with regard to the implementation of reuse mechanisms of different granularities. We realize that due to our small sample size results are not statistically significant, but this preliminary run shows that it is ready for running on a larger scale.
HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models
Kulakovskiy, Ivan V.
2015-11-19
Models of transcription factor (TF) binding sites provide a basis for a wide spectrum of studies in regulatory genomics, from reconstruction of regulatory networks to functional annotation of transcripts and sequence variants. While TFs may recognize different sequence patterns in different conditions, it is pragmatic to have a single generic model for each particular TF as a baseline for practical applications. Here we present the expanded and enhanced version of HOCOMOCO (http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco10), the collection of models of DNA patterns, recognized by transcription factors. HOCOMOCO now provides position weight matrix (PWM) models for binding sites of 601 human TFs and, in addition, PWMs for 396 mouse TFs. Furthermore, we introduce the largest up to date collection of dinucleotide PWM models for 86 (52) human (mouse) TFs. The update is based on the analysis of massive ChIP-Seq and HT-SELEX datasets, with the validation of the resulting models on in vivo data. To facilitate a practical application, all HOCOMOCO models are linked to gene and protein databases (Entrez Gene, HGNC, UniProt) and accompanied by precomputed score thresholds. Finally, we provide command-line tools for PWM and diPWM threshold estimation and motif finding in nucleotide sequences.
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.
Projects Delay Factors of Saudi Arabia Construction Industry Using PLS-SEM Path Modelling Approach
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Abdul Rahman Ismail
2016-01-01
Full Text Available This paper presents the development of PLS-SEM Path Model of delay factors of Saudi Arabia construction industry focussing on Mecca City. The model was developed and assessed using SmartPLS v3.0 software and it consists of 37 factors/manifests in 7 groups/independent variables and one dependent variable which is delay of the construction projects. The model was rigorously assessed at measurement and structural components and the outcomes found that the model has achieved the required threshold values. At structural level of the model, among the seven groups, the client and consultant group has the highest impact on construction delay with path coefficient β-value of 0.452 and the project management and contract administration group is having the least impact to the construction delay with β-value of 0.016. The overall model has moderate explaining power ability with R2 value of 0.197 for Saudi Arabia construction industry representation. This model will able to assist practitioners in Mecca city to pay more attention in risk analysis for potential construction delay.
Casey, F P; Baird, D; Feng, Q; Gutenkunst, R N; Waterfall, J J; Myers, C R; Brown, K S; Cerione, R A; Sethna, J P
2007-05-01
We apply the methods of optimal experimental design to a differential equation model for epidermal growth factor receptor signalling, trafficking and down-regulation. The model incorporates the role of a recently discovered protein complex made up of the E3 ubiquitin ligase, Cbl, the guanine exchange factor (GEF), Cool-1 (beta -Pix) and the Rho family G protein Cdc42. The complex has been suggested to be important in disrupting receptor down-regulation. We demonstrate that the model interactions can accurately reproduce the experimental observations, that they can be used to make predictions with accompanying uncertainties, and that we can apply ideas of optimal experimental design to suggest new experiments that reduce the uncertainty on unmeasurable components of the system.
An Explanatory Model of Dating Violence Risk Factors in Spanish Adolescents.
Aizpitarte, Alazne; Alonso-Arbiol, Itziar; Van de Vijver, Fons J R
2017-12-01
Dating violence is a serious public health issue that needs further understanding in terms of risk factors that may be involved in it. The main goal of this study was to test a mediational model of dating violence risk factors. The sample was composed of 477 secondary and college students from Spain (59% females). A dynamic developmental explanatory model considering aggressiveness, insecure attachment, interparental conflict, and peer dating violence was tested using a multigroup structural equation model. Aggressiveness partially mediated the relation between anxious attachment and dating violence and fully mediated the association between interparental conflict resolution and dating violence. Furthermore, perceived peer dating violence was a direct predictor of dating violence. Implications for prevention and intervention plans are discussed. © 2017 The Authors. Journal of Research on Adolescence © 2017 Society for Research on Adolescence.
International Nuclear Information System (INIS)
Zhou Zhongbao; Zhou Jinglun; Sun Quan
2007-01-01
Effect of Human factors on system safety is increasingly serious, which is often ignored in traditional probabilistic safety assessment methods however. A new probabilistic safety assessment model based on object-oriented Bayesian networks is proposed in this paper. Human factors are integrated into the existed event sequence diagrams. Then the classes of the object-oriented Bayesian networks are constructed which are converted to latent Bayesian networks for inference. Finally, the inference results are integrated into event sequence diagrams for probabilistic safety assessment. The new method is applied to the accident of loss of coolant in a nuclear power plant. the results show that the model is not only applicable to real-time situation assessment, but also applicable to situation assessment based certain amount of information. The modeling complexity is kept down and the new method is appropriate to large complex systems due to the thoughts of object-oriented. (authors)
Directory of Open Access Journals (Sweden)
Daniel Jorge Caetano
2017-12-01
Full Text Available The problem of airline flight network optimization can be split into subproblems such as Schedule Generation (SG and Fleet Assignment (FA, solved in consecutive steps or in an integrated way, usually based on monetary costs and revenue forecasts. A linear programming model to solve SG and FA in an integrated way is presented, but with an alternative approach based on transport momentum and aircraft load factor. This alternative approach relies on demand forecast and allows obtaining solutions considering minimum average load factors. Results of the proposed model applications to instances of a regional Brazilian airline are presented. The comparison of the schedules generated by the proposed approach against those obtained by applying a model based on monetary costs and revenue forecasts demonstrates the validity of this alternative approach for airlines network planning.
Identification and synthetic modeling of factors affecting American black duck populations
Conroy, Michael J.; Miller, Mark W.; Hines, James E.
2002-01-01
We reviewed the literature on factors potentially affecting the population status of American black ducks (Anas rupribes). Our review suggests that there is some support for the influence of 4 major, continental-scope factors in limiting or regulating black duck populations: 1) loss in the quantity or quality of breeding habitats; 2) loss in the quantity or quality of wintering habitats; 3) harvest, and 4) interactions (competition, hybridization) with mallards (Anas platyrhychos) during the breeding and/or wintering periods. These factors were used as the basis of an annual life cycle model in which reproduction rates and survival rates were modeled as functions of the above factors, with parameters of the model describing the strength of these relationships. Variation in the model parameter values allows for consideration of scientific uncertainty as to the degree each of these factors may be contributing to declines in black duck populations, and thus allows for the investigation of the possible effects of management (e.g., habitat improvement, harvest reductions) under different assumptions. We then used available, historical data on black duck populations (abundance, annual reproduction rates, and survival rates) and possible driving factors (trends in breeding and wintering habitats, harvest rates, and abundance of mallards) to estimate model parameters. Our estimated reproduction submodel included parameters describing negative density feedback of black ducks, positive influence of breeding habitat, and negative influence of mallard densities; our survival submodel included terms for positive influence of winter habitat on reproduction rates, and negative influences of black duck density (i.e., compensation to harvest mortality). Individual models within each group (reproduction, survival) involved various combinations of these factors, and each was given an information theoretic weight for use in subsequent prediction. The reproduction model with highest
Significance of categorization and the modeling of age related factors for radiation protection
International Nuclear Information System (INIS)
Matsuoka, Osamu
1987-01-01
It is proposed that the categorization and modelling are necessary with regard to age related factors of radionuclide metabolism for the radiation protection of the public. In order to utilize the age related information as a model for life time risk estimate of public, it is necessary to generalize and simplify it according to the categorized model patterns. Since the patterns of age related changes in various parameters of radionuclide metabolism seem to be rather simple, it is possible to categorize them into eleven types of model patterns. Among these models, five are selected as positively significant models to be considered. Examples are shown as to the fitting of representative parameters of both physiological and metabolic parameter of radionuclides into the proposed model. The range of deviation from adult standard value is also analyzed for each model. The fitting of each parameter to categorized models, and its comparative consideration provide the effective information as to the physiological basis of radionuclide metabolism. Discussions are made on the problems encountered in the application of available age related information to radiation protection of the public, i.e. distribution of categorized parameter, period of life covered, range of deviation from adult value, implication to other dosimetric and pathological models and to the final estimation. 5 refs.; 3 figs.; 4 tabs
Predictive model of thrombospondin-1 and vascular endothelial growth factor in breast tumor tissue.
Rohrs, Jennifer A; Sulistio, Christopher D; Finley, Stacey D
2016-01-01
Angiogenesis, the formation of new blood capillaries from pre-existing vessels, is a hallmark of cancer. Thus far, strategies for reducing tumor angiogenesis have focused on inhibiting pro-angiogenic factors, while less is known about the therapeutic effects of mimicking the actions of angiogenesis inhibitors. Thrombospondin-1 (TSP1) is an important endogenous inhibitor of angiogenesis that has been investigated as an anti-angiogenic agent. TSP1 impedes the growth of new blood vessels in many ways, including crosstalk with pro-angiogenic factors. Due to the complexity of TSP1 signaling, a predictive systems biology model would provide quantitative understanding of the angiogenic balance in tumor tissue. Therefore, we have developed a molecular-detailed, mechanistic model of TSP1 and vascular endothelial growth factor (VEGF), a promoter of angiogenesis, in breast tumor tissue. The model predicts the distribution of the angiogenic factors in tumor tissue, revealing that TSP1 is primarily in an inactive, cleaved form due to the action of proteases, rather than bound to its cellular receptors or to VEGF. The model also predicts the effects of enhancing TSP1's interactions with its receptors and with VEGF. To provide additional predictions that can guide the development of new anti-angiogenic drugs, we simulate administration of exogenous TSP1 mimetics that bind specific targets. The model predicts that the CD47-binding TSP1 mimetic dramatically decreases the ratio of receptor-bound VEGF to receptor-bound TSP1, in favor of anti-angiogenesis. Thus, we have established a model that provides a quantitative framework to study the response to TSP1 mimetics.
Can stochastic consumer phase models in QMRA be simplified to a single factor?
DEFF Research Database (Denmark)
Neves, Maria Ines; Mungai, Sylvester N.; Nauta, Maarten J.
2018-01-01
, and a consumer phase model (CPM) needs to be included in a QMRA to allow an evaluation of the effectiveness of intervention measures in food production and processing in terms of human health risk. However, the development of a CPM is complex because consumer practices can be highly variable and data are scarce......In quantitative microbiological risk assessment (QMRA), the consumer phase covers the part of the food chain following production and retail, where the consumer transports, stores, prepares and consumes the food products considered. These consumer practices have a crucial impact on exposure......-implemented and their equivalent surrogate models were derived, basing the value of the constant surrogate model factor on the absolute risk estimate from the stochastic model. The performances of the models were evaluated by comparing the effects of hypothetical intervention measures that reduce the mean or the standard...
Molenaar, Dylan; Tuerlinckx, Francis; van der Maas, Han L J
2015-05-01
We show how the hierarchical model for responses and response times as developed by van der Linden (2007), Fox, Klein Entink, and van der Linden (2007), Klein Entink, Fox, and van der Linden (2009), and Glas and van der Linden (2010) can be simplified to a generalized linear factor model with only the mild restriction that there is no hierarchical model at the item side. This result is valuable as it enables all well-developed modelling tools and extensions that come with these methods. We show that the restriction we impose on the hierarchical model does not influence parameter recovery under realistic circumstances. In addition, we present two illustrative real data analyses to demonstrate the practical benefits of our approach. © 2014 The British Psychological Society.
Bagby, R Michael; Widiger, Thomas A
2018-01-01
The Five-Factor Model (FFM) is a dimensional model of general personality structure, consisting of the domains of neuroticism (or emotional instability), extraversion versus introversion, openness (or unconventionality), agreeableness versus antagonism, and conscientiousness (or constraint). The FFM is arguably the most commonly researched dimensional model of general personality structure. However, a notable limitation of existing measures of the FFM has been a lack of coverage of its maladaptive variants. A series of self-report inventories has been developed to assess for the maladaptive personality traits that define Diagnostic and Statistical Manual of Mental Disorders (fifth edition; DSM-5) Section II personality disorders (American Psychiatric Association [APA], 2013) from the perspective of the FFM. In this paper, we provide an introduction to this Special Section, presenting the rationale and empirical support for these measures and placing them in the historical context of the recent revision to the APA diagnostic manual. This introduction is followed by 5 papers that provide further empirical support for these measures and address current issues within the personality assessment literature. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Hofmann, Rich; Sherman, Larry
Using data from 135 sixth-, seventh-, and eighth-graders between 11 and 15 years old attending a middle school in a suburban Southwest Ohio school district, two hypothesized models of the factor structures for the Coopersmith Self-Esteem Inventory were tested. One model represents the original Coopersmith factor structure, and the other model is…
Huang, Weihui; Li, Yadan; Lin, Yufeng; Ye, Xue; Zang, Dawei
2012-07-05
The present study established a mouse model of cerebral infarction by middle cerebral artery occlusion, and monitored the effect of 25 μg/kg leukemia inhibitory factor and (or) basic fibroblast growth factor administration 2 hours after model establishment. Results showed that following administration, the number of endogenous neural stem cells in the infarct area significantly increased, malondialdehyde content in brain tissue homogenates significantly decreased, nitric oxide content, glutathione peroxidase and superoxide dismutase activity significantly elevated, and mouse motor function significantly improved as confirmed by the rotarod and bar grab tests. In particular, the effect of leukemia inhibitory factor in combination with basic fibroblast growth factor was the most significant. Results indicate that leukemia inhibitory factor and basic fibroblast growth factor can improve the microenvironment after cerebral infarction by altering free radical levels, improving the quantity of endogenous neural stem cells, and promoting neurological function of mice with cerebral infarction.
Modeling of dengue occurrences early warning involving temperature and rainfall factors
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Prama Setia Putra
2017-07-01
Full Text Available Objective: To understand dengue transmission process and its vector dynamics and to develop early warning model of dengue occurrences based on mosquito population and host-vector threshold values considering temperature and rainfall. Methods: To obtain the early warning model, mosquito population and host-vector models are developed initially. Both are developed using differential equations. Basic offspring number (R0m and basic reproductive ratio (R0d which are the threshold values are derived from the models under constant parameters assumption. Temperature and rainfall effects on mosquito and dengue are performed in entomological and disease transmission parameters. Some of parameters are set as functions of temperature or rainfall while other parameters are set to be constant. Hereafter, both threshold values are computed using those parameters. Monthly dengue occurrences data are categorized as zero and one values which one means the outbreak does occur in that month. Logistics regression is chosen to bridge the threshold values and categorized data. Threshold values are considered as the input of early warning model. Semarang city is selected as the sample to develop this early waning model. Results: The derived threshold values which are R 0 m and R 0 d show to have relation that mosquito as dengue vector affects transmission of the disease. Result of the early warning model will be a value between zero and one. It is categorized as outbreak does occur when the value is larger than 0.5 while other is categorized as outbreak does not occur. By using single predictor, the model can perform 68% accuracy approximately. Conclusions: The extinction of mosquitoes will be followed by disease disappearance while mosquitoes existence can lead to disease free or endemic states. Model simulations show that mosquito population are more affected by weather factors than human. Involving weather factors implicitly in the threshold value and linking them
Kruse, Clemens Scott; DeShazo, Jonathan; Kim, Forest; Fulton, Lawrence
2014-05-23
The Health Information Technology for Economic and Clinical Health Act (HITECH) allocated $19.2 billion to incentivize adoption of the electronic health record (EHR). Since 2009, Meaningful Use Criteria have dominated information technology (IT) strategy. Health care organizations have struggled to meet expectations and avoid penalties to reimbursements from the Center for Medicare and Medicaid Services (CMS). Organizational theories attempt to explain factors that influence organizational change, and many theories address changes in organizational strategy. However, due to the complexities of the health care industry, existing organizational theories fall short of demonstrating association with significant health care IT implementations. There is no organizational theory for health care that identifies, groups, and analyzes both internal and external factors of influence for large health care IT implementations like adoption of the EHR. The purpose of this systematic review is to identify a full-spectrum of both internal organizational and external environmental factors associated with the adoption of health information technology (HIT), specifically the EHR. The result is a conceptual model that is commensurate with the complexity of with the health care sector. We performed a systematic literature search in PubMed (restricted to English), EBSCO Host, and Google Scholar for both empirical studies and theory-based writing from 1993-2013 that demonstrated association between influential factors and three modes of HIT: EHR, electronic medical record (EMR), and computerized provider order entry (CPOE). We also looked at published books on organizational theories. We made notes and noted trends on adoption factors. These factors were grouped as adoption factors associated with various versions of EHR adoption. The resulting conceptual model summarizes the diversity of independent variables (IVs) and dependent variables (DVs) used in articles, editorials, books, as
The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).
Modeling the factors associating with health-related habits among Japanese students.
Mato, Mie; Tsukasaki, Keiko
2017-11-23
The aim of the present study was to clarify the structural relationship between health-related habits and psychosocial factors during adolescence/early adulthood. An anonymous, self-administered questionnaire was provided to 1141 third- and fourth-year students at eight academic departments from six universities in regional Japanese cities. Surveys included items addressing participants' demographic characteristics, psychosocial factors (individual-level social capital, self-efficacy, mental health (from health-related quality of life SF-36v2), and sense of coherence (SOC)), and health-related habits. A multiple indicator analysis based on structural equation modeling was conducted to examine the structural relationship between health-related habits and these factors. Valid responses were obtained from 952 participants. The final model demonstrated a high level of goodness of fit. While the path from SOC to health-related habits was significant, those from self-efficacy to health-related habits and from mental health to health-related habits were not significant. The path coefficient from SOC to health-related habits was greater than the path coefficient from background characteristics. In the multiple population comparison that considered gender, a nearly identical model was supported for men and women. Psychosocial factors related to health-related habits were social capital, self-efficacy, mental health, and SOC. Furthermore, it was suggested that SOC functions as an intervening factor for maintaining a healthy lifestyle. It was observed that individual psychosocial factors influence health-related habits more than their background characteristics. Findings highlight that supporting the building of social relationships and social environments is essential to promote a healthy lifestyle among university students. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Model-based identification and use of task complexity factors of human integrated systems
International Nuclear Information System (INIS)
Ham, Dong-Han; Park, Jinkyun; Jung, Wondea
2012-01-01
Task complexity is one of the conceptual constructs that are critical to explain and predict human performance in human integrated systems. A basic approach to evaluating the complexity of tasks is to identify task complexity factors and measure them. Although a great deal of task complexity factors have been studied, there is still a lack of conceptual frameworks for identifying and organizing them analytically, which can be generally used irrespective of the types of domains and tasks. This study proposes a model-based approach to identifying and using task complexity factors, which has two facets—the design aspects of a task and complexity dimensions. Three levels of design abstraction, which are functional, behavioral, and structural aspects of a task, characterize the design aspect of a task. The behavioral aspect is further classified into five cognitive processing activity types. The complexity dimensions explain a task complexity from different perspectives, which are size, variety, and order/organization. Twenty-one task complexity factors are identified by the combination of the attributes of each facet. Identification and evaluation of task complexity factors based on this model is believed to give insights for improving the design quality of tasks. This model for complexity factors can also be used as a referential framework for allocating tasks and designing information aids. The proposed approach is applied to procedure-based tasks of nuclear power plants (NPPs) as a case study to demonstrate its use. Last, we compare the proposed approach with other studies and then suggest some future research directions.
Structural Equation Model for Evaluating Factors Affecting Quality of Social Infrastructure Projects
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Shahid Hussain
2018-05-01
Full Text Available The quality of the constructed social infrastructure project has been considered a necessary measure for the sustainability of projects. Studies on factors affecting project quality have used various techniques and methods to explain the relationships between particular variables. Unexpectedly, Structural Equation Modeling (SEM has acquired very little concern in factors affecting project quality studies. To address this limitation in the body of knowledge, the objective of this study was to apply the SEM approach and build a model that explained and identified the critical factors affecting quality in social infrastructure projects. The authors developed a quantitative approach using smart-PLS version 3.2.7. This study shed light on the views of different experts based on their experience in public construction projects in Pakistan. Particularly, the authors aimed to find out the relationships between construction, stakeholders, materials, design, and external factors, and how these relate to project quality. The findings of this study revealed that the R2 value of the model was scored at 0.749, which meant that the five exogenous latent constructs collectively explained 74.9% of the variance in project quality. The Goodness-of-Fit of the model was 0.458. The construction related factor was the most important out of the five constructs. This study determined that better planning and monitoring and evaluation should be developed to better address and control the quality defects by decision-makers, project managers as well as contractors. These findings might support practitioners and decision makers to focus on quality related problems that might occur in their current or future projects.
Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models
Ting, Chee-Ming
2017-12-06
We consider the challenges in estimating state-related changes in brain connectivity networks with a large number of nodes. Existing studies use sliding-window analysis or time-varying coefficient models which are unable to capture both smooth and abrupt changes simultaneously, and rely on ad-hoc approaches to the high-dimensional estimation. To overcome these limitations, we propose a Markov-switching dynamic factor model which allows the dynamic connectivity states in functional magnetic resonance imaging (fMRI) data to be driven by lower-dimensional latent factors. We specify a regime-switching vector autoregressive (SVAR) factor process to quantity the time-varying directed connectivity. The model enables a reliable, data-adaptive estimation of change-points of connectivity regimes and the massive dependencies associated with each regime. We develop a three-step estimation procedure: 1) extracting the factors using principal component analysis, 2) identifying connectivity regimes in a low-dimensional subspace based on the factor-based SVAR model, 3) constructing high-dimensional state connectivity metrics based on the subspace estimates. Simulation results show that our estimator outperforms K-means clustering of time-windowed coefficients, providing more accurate estimate of time-evolving connectivity. It achieves percentage of reduction in mean squared error by 60% when the network dimension is comparable to the sample size. When applied to resting-state fMRI data, our method successfully identifies modular organization in resting-state networks in consistency with other studies. It further reveals changes in brain states with variations across subjects and distinct large-scale directed connectivity patterns across states.
Factors Affecting the Choice of Professors as a Role Model from the Viewpoint of Medical Students
Directory of Open Access Journals (Sweden)
Masome Rahimi
2018-01-01
Full Text Available The role of professors as a model can have a beneficial impact on the mental, psychological and educational conditions of medical students. This also plays an important role in improving professionalism and academic achievements among medical students. Therefore, the present study was aimed at evaluating the standpoint of students on factors influencing the selection of professors as a role model. This descriptive cross-sectional study was conducted on the students of different disciplines studying in Jahrom University of Medical Sciences in 2016. A randomized sampling method was conducted on 217 students. Their viewpoints were collected using a 30- question researcher-made questionnaire. The questionnaire consisted of three parts, each containing ten items. In addition, this questionnaire was distributed among 20 people (as a pilot survey, the alpha coefficient of which was equal to 0.88; and its measurement was based on Likert scale "from very low to very high". Data were analyzed using SPSS 18 and descriptive statistics. Most respondents were nursing students and the highest influence of professors as a role model was associated with their role as a research leader (future specialized courses in the clinical choices and selection of future specialized fields. The factors influencing the selection of professors as a role model included their respectful attitude toward students, and the high level of their knowledge and skills. On the other hand, the most important factors that caused professors not to be regarded as a role model included their inappropriate relationship with the students and refusing to listen to them. Role model professors can have a beneficial impact on the future of students and scientific communities, as far as the science and education is concerned. Therefore, it is necessary for professors to pay particular attention to strengthening their role as a model at universities.
A protective factors model for alcohol abuse and suicide prevention among Alaska Native youth.
Allen, James; Mohatt, Gerald V; Fok, Carlotta Ching Ting; Henry, David; Burkett, Rebekah
2014-09-01
This study provides an empirical test of a culturally grounded theoretical model for prevention of alcohol abuse and suicide risk with Alaska Native youth, using a promising set of culturally appropriate measures for the study of the process of change and outcome. This model is derived from qualitative work that generated an heuristic model of protective factors from alcohol (Allen et al. in J Prev Interv Commun 32:41-59, 2006; Mohatt et al. in Am J Commun Psychol 33:263-273, 2004a; Harm Reduct 1, 2004b). Participants included 413 rural Alaska Native youth ages 12-18 who assisted in testing a predictive model of Reasons for Life and Reflective Processes about alcohol abuse consequences as co-occurring outcomes. Specific individual, family, peer, and community level protective factor variables predicted these outcomes. Results suggest prominent roles for these predictor variables as intermediate prevention strategy target variables in a theoretical model for a multilevel intervention. The model guides understanding of underlying change processes in an intervention to increase the ultimate outcome variables of Reasons for Life and Reflective Processes regarding the consequences of alcohol abuse.
Meeting Human Reliability Requirements through Human Factors Design, Testing, and Modeling
Energy Technology Data Exchange (ETDEWEB)
R. L. Boring
2007-06-01
In the design of novel systems, it is important for the human factors engineer to work in parallel with the human reliability analyst to arrive at the safest achievable design that meets design team safety goals and certification or regulatory requirements. This paper introduces the System Development Safety Triptych, a checklist of considerations for the interplay of human factors and human reliability through design, testing, and modeling in product development. This paper also explores three phases of safe system development, corresponding to the conception, design, and implementation of a system.
Global warming factors modelled for 40 generic municipal waste management scenarios
DEFF Research Database (Denmark)
Christensen, Thomas Højlund; Simion, F.; Tonini, Davide
2009-01-01
Global warming factors (kg CO2-eq.-tonne—1 of waste) have been modelled for 40 different municipal waste management scenarios involving a variety of recycling systems (paper, glass, plastic and organics) and residual waste management by landfilling, incineration or mechanical—biological waste...... treatment. For average European waste composition most waste management scenarios provided negative global warming factors and hence overall savings in greenhouse gas emissions: Scenarios with landfilling saved 0—400, scenarios with incineration saved 200—700, and scenarios with mechanical...
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.
EFFECTIVE FACTORS AND MODEL SYSTEMS IN THE INDUSTRIAL PRODUCTION OF NISIN
Directory of Open Access Journals (Sweden)
Ömer ŞİMŞEK
2007-01-01
Full Text Available Nisin is the first bacteriocin identified in Lactococcus lactis and belongs to type 1 lanthibiotic group. High nisin production in cultured media is related with the composition of fermentation medium, pH, produced nisin concentration and most importantly growth amount of cell. For industrial purpose, batch, fed-batch and continue fermentation systems were developed by regarding these factors. Maintaining efficient production of nisin having important potential at preservation of foods is important for both industrial production and using as starter culture. In this review the fermentation factors at nisin production were outlined and constructed model systems were compared.
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.
International Nuclear Information System (INIS)
Erisman, Jan Willem; Draaijers, Geert
2003-01-01
The influence of forest characteristics on deposition can be modelled reasonably well; forest edge effects and dynamical processes are still uncertain. - Dry deposition of gases and particles to forests is influenced by factors influencing the turbulent transport, such as wind speed, tree height, canopy closure, LAI, etc. as well as by factors influencing surface condition, such as precipitation, relative humidity, global radiation, etc. In this paper, an overview of these factors is given and it is shown which are the most important determining temporal and spatial variation of dry deposition of sodium and sulphur. Furthermore, it is evaluated how well current deposition models are able to describe the temporal and spatial variation in dry deposition. It is concluded that the temporal variation is not modelled well enough, because of limited surface-wetness exchange parameterisations. The influence of forest characteristics are modelled reasonably well, provided enough data describing the forests and the spatial variation in concentration is available. For Europe these data are not available. The means to decrease the atmospheric deposition through forest management is discussed
Cusack, Lynette; Smith, Morgan; Hegney, Desley; Rees, Clare S; Breen, Lauren J; Witt, Regina R; Rogers, Cath; Williams, Allison; Cross, Wendy; Cheung, Kin
2016-01-01
Building nurses' resilience to complex and stressful practice environments is necessary to keep skilled nurses in the workplace and ensuring safe patient care. A unified theoretical framework titled Health Services Workplace Environmental Resilience Model (HSWERM), is presented to explain the environmental factors in the workplace that promote nurses' resilience. The framework builds on a previously-published theoretical model of individual resilience, which identified the key constructs of psychological resilience as self-efficacy, coping and mindfulness, but did not examine environmental factors in the workplace that promote nurses' resilience. This unified theoretical framework was developed using a literary synthesis drawing on data from international studies and literature reviews on the nursing workforce in hospitals. The most frequent workplace environmental factors were identified, extracted and clustered in alignment with key constructs for psychological resilience. Six major organizational concepts emerged that related to a positive resilience-building workplace and formed the foundation of the theoretical model. Three concepts related to nursing staff support (professional, practice, personal) and three related to nursing staff development (professional, practice, personal) within the workplace environment. The unified theoretical model incorporates these concepts within the workplace context, linking to the nurse, and then impacting on personal resilience and workplace outcomes, and its use has the potential to increase staff retention and quality of patient care.
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)
Astrøm, Anne Nordrehaug; Ekbäck, Gunnar; Ordell, Sven
2010-04-01
No studies have tested oral health-related quality of life models in dentate older adults across different populations. To test the factor structure of oral health outcomes within Gilbert's conceptual model among 65-year olds in Sweden and Norway. It was hypothesized that responses to 14 observed indicators could be explained by three correlated factors, symptom status, functional limitations and oral disadvantages, that each observed oral health indicator would associate more strongly with the factor it is supposed to measure than with competing factors and that the proposed 3-factor structure would possess satisfactory cross-national stability with 65-year olds in Norway and Sweden. In 2007, 6078 Swedish- and 4062 Norwegian adults borne in 1942 completed mailed questionnaires including oral symptoms, functional limitations and the eight item Oral Impacts on Daily Performances inventory. Model generation analysis was restricted to the Norwegian study group and the model achieved was tested without modifications in Swedish 65-year olds. A modified 3-factor solution with cross-loadings, improved the fit to the data compared with a 2-factor- and the initially proposed 3-factor model among the Norwegian [comparative fit index (CFI) = 0.97] and Swedish (CFI = 0.98) participants. All factor loadings for the modified 3-factor model were in the expected direction and were statistically significant at CR > 1. Multiple group confirmatory factor analyses, with Norwegian and Swedish data simultaneously revealed acceptable fit for the unconstrained model (CFI = 0.97), whereas unconstrained and constrained models were statistically significant different in nested model comparison. Within construct validity of Gilbert's model was supported with Norwegian and Swedish 65-year olds, indicating that the 14-item questionnaire reflected three constructs; symptom status, functional limitation and oral disadvantage. Measurement invariance was confirmed at the level of factor structure
Continuous Release of Tumor-Derived Factors Improves the Modeling of Cachexia in Muscle Cell Culture
Directory of Open Access Journals (Sweden)
Robert W. Jackman
2017-09-01
Full Text Available Cachexia is strongly associated with a poor prognosis in cancer patients but the biological trigger is unknown and therefore no therapeutics exist. The loss of skeletal muscle is the most deleterious aspect of cachexia and it appears to depend on secretions from tumor cells. Models for studying wasting in cell culture consist of experiments where skeletal muscle cells are incubated with medium conditioned by tumor cells. This has led to candidates for cachectic factors but some of the features of cachexia in vivo are not yet well-modeled in cell culture experiments. Mouse myotube atrophy measured by myotube diameter in response to medium conditioned by mouse colon carcinoma cells (C26 is consistently less than what is seen in muscles of mice bearing C26 tumors with moderate to severe cachexia. One possible reason for this discrepancy is that in vivo the C26 tumor and skeletal muscle share a circulatory system exposing the muscle to tumor factors in a constant and increasing way. We have applied Transwell®-adapted cell culture conditions to more closely simulate conditions found in vivo where muscle is exposed to the ongoing kinetics of constant tumor secretion of active factors. C26 cells were incubated on a microporous membrane (a Transwell® insert that constitutes the upper compartment of wells containing plated myotubes. In this model, myotubes are exposed to a constant supply of cancer cell secretions in the medium but without direct contact with the cancer cells, analogous to a shared circulation of muscle and cancer cells in tumor-bearing animals. The results for myotube diameter support the idea that the use of Transwell® inserts serves as a more physiological model of the muscle wasting associated with cancer cachexia than the bolus addition of cancer cell conditioned medium. The Transwell® model supports the notion that the dose and kinetics of cachectic factor delivery to muscle play a significant role in the extent of pathology.
Kwon, Oh Young; Park, So Youn
2016-03-01
The purpose of this study was to determine the relationship between personality traits, using the Five-Factor Model, and characteristics and motivational factors affecting specialty choice in Korean medical students. A questionnaire survey of Year 4 medical students (n=110) in July 2015 was administered. We evaluated the personality traits of Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness by using the Korean version of Big Five Inventory. Questions about general characteristics, medical specialties most preferred as a career, motivational factors in determining specialty choice were included. Data between five personality traits and general characteristics and motivational factors affecting specialty choice were analyzed using Student t-test, Mann-Whitney test and analysis of variance. Of the 110 eligible medical students, 105 (95.4% response rate) completed the questionnaire. More Agreeableness students preferred clinical medicine to basic medicine (p=0.010) and more Openness students preferred medical departments to others (p=0.031). Personal interest was the significant motivational factors in more Openness students (p=0.003) and Conscientiousness students (p=0.003). Medical students with more Agreeableness were more likely to prefer clinical medicine and those with more Openness preferred medical departments. Personal interest was a significant influential factor determining specialty choice in more Openness and Conscientiousness students. These findings may be helpful to medical educators or career counselors in the specialty choice process.
Specialty choice preference of medical students according to personality traits by Five-Factor Model
Directory of Open Access Journals (Sweden)
Oh Young Kwon
2016-03-01
Full Text Available Purpose: The purpose of this study was to determine the relationship between personality traits, using the Five-Factor Model, and characteristics and motivational factors affecting specialty choice in Korean medical students. Methods: A questionnaire survey of Year 4 medical students (n=110 in July 2015 was administered. We evaluated the personality traits of Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness by using the Korean version of Big Five Inventory. Questions about general characteristics, medical specialties most preferred as a career, motivational factors in determining specialty choice were included. Data between five personality traits and general characteristics and motivational factors affecting specialty choice were analyzed using Student t-test, Mann-Whitney test and analysis of variance. Results: Of the 110 eligible medical students, 105 (95.4% response rate completed the questionnaire. More Agreeableness students preferred clinical medicine to basic medicine (p=0.010 and more Openness students preferred medical departments to others (p=0.031. Personal interest was the significant motivational factors in more Openness students (p=0.003 and Conscientiousness students (p=0.003. Conclusion: Medical students with more Agreeableness were more likely to prefer clinical medicine and those with more Openness preferred medical departments. Personal interest was a significant influential factor determining specialty choice in more Openness and Conscientiousness students. These findings may be helpful to medical educators or career counselors in the specialty choice process.
Specific count model for investing the related factors of cost of GERD and functional dyspepsia
Abadi, Alireza; Chaibakhsh, Samira; Safaee, Azadeh; Moghimi-Dehkordi, Bijan
2013-01-01
Aim The purpose of this study is to analyze the cost of GERD and functional dyspepsia for investing its related factors. Background Gastro-oesophageal reflux disease GERD and dyspepsia are the most common symptoms of gastrointestinal disorders. Recent studies showed high prevalence and variety of clinical presentation of these two symptoms imposed enormous economic burden to the society. Cost data that related to economics burden have specific characteristics. So this kind of data needs to specific models. Poisson regression (PR) and negative binomial regression (NB) are the models that were used for analyzing cost data in this paper. Patients and methods This study designed as a cross-sectional household survey from May 2006 to December 2007 on a random sample of individual in the Tehran province, Iran to find the prevalence of gastrointestinal symptoms and disorders and its related factors. The Cost in each item was counted. PR and NB were carried out to the data respectively. Likelihood ratio test was performed for comparison between models. Also Log likelihood, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to compare performance of the models. Results According to Likelihood ratio test and all three criterions that we used to compare performance of the models, NB was the best model for analyzing this cost data. Sex, age and insurance statues were being significant. Conclusion PR and NB models were carried out for this data and according the results improved fit of the NB model over PR, it clearly indicates that over-dispersion is involved due to unobserved heterogeneity and/or clustering. NB model in cost data more appropriate fit than PR. PMID:24834282
Suzuki, Takakuni; Griffin, Sarah A; Samuel, Douglas B
2017-04-01
Several studies have shown structural and statistical similarities between the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) alternative personality disorder model and the Five-Factor Model (FFM). However, no study to date has evaluated the nomological network similarities between the two models. The relations of the Revised NEO Personality Inventory (NEO PI-R) and the Personality Inventory for DSM-5 (PID-5) with relevant criterion variables were examined in a sample of 336 undergraduate students (M age = 19.4; 59.8% female). The resulting profiles for each instrument were statistically compared for similarity. Four of the five domains of the two models have highly similar nomological networks, with the exception being FFM Openness to Experience and PID-5 Psychoticism. Further probing of that pair suggested that the NEO PI-R domain scores obscured meaningful similarity between PID-5 Psychoticism and specific aspects and lower-order facets of Openness. The results support the notion that the DSM-5 alternative personality disorder model trait domains represent variants of the FFM domains. Similarities of Openness and Psychoticism domains were supported when the lower-order aspects and facets of Openness domain were considered. The findings support the view that the DSM-5 trait model represents an instantiation of the FFM. © 2015 Wiley Periodicals, Inc.
Linear and nonlinear models for predicting fish bioconcentration factors for pesticides.
Yuan, Jintao; Xie, Chun; Zhang, Ting; Sun, Jinfang; Yuan, Xuejie; Yu, Shuling; Zhang, Yingbiao; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu
2016-08-01
This work is devoted to the applications of the multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and projection pursuit regression (PPR) to quantitative structure-property relationship analysis of bioconcentration factors (BCFs) of pesticides tested on Bluegill (Lepomis macrochirus). Molecular descriptors of a total of 107 pesticides were calculated with the DRAGON Software and selected by inverse enhanced replacement method. Based on the selected DRAGON descriptors, a linear model was built by MLR, nonlinear models were developed using MLP NN and PPR. The robustness of the obtained models was assessed by cross-validation and external validation using test set. Outliers were also examined and deleted to improve predictive power. Comparative results revealed that PPR achieved the most accurate predictions. This study offers useful models and information for BCF prediction, risk assessment, and pesticide formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.
Optimization Scheduling Model for Wind-thermal Power System Considering the Dynamic penalty factor
PENG, Siyu; LUO, Jianchun; WANG, Yunyu; YANG, Jun; RAN, Hong; PENG, Xiaodong; HUANG, Ming; LIU, Wanyu
2018-03-01
In this paper, a new dynamic economic dispatch model for power system is presented.Objective function of the proposed model presents a major novelty in the dynamic economic dispatch including wind farm: introduced the “Dynamic penalty factor”, This factor could be computed by using fuzzy logic considering both the variable nature of active wind power and power demand, and it could change the wind curtailment cost according to the different state of the power system. Case studies were carried out on the IEEE30 system. Results show that the proposed optimization model could mitigate the wind curtailment and the total cost effectively, demonstrate the validity and effectiveness of the proposed model.
Testing of technology readiness index model based on exploratory factor analysis approach
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.
Energy Technology Data Exchange (ETDEWEB)
Brinkmann, Markus; Eichbaum, Kathrin [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Kammann, Ulrike [Thünen-Institute of Fisheries Ecology, Palmaille 9, 22767 Hamburg (Germany); Hudjetz, Sebastian [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Cofalla, Catrina [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Buchinger, Sebastian; Reifferscheid, Georg [Federal Institute of Hydrology (BFG), Department G3: Biochemistry, Ecotoxicology, Am Mainzer Tor 1, 56068 Koblenz (Germany); Schüttrumpf, Holger [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Preuss, Thomas [Department of Environmental Biology and Chemodynamics, Institute for Environmental Research,ABBt- Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); and others
2014-07-01
Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios.
International Nuclear Information System (INIS)
Brinkmann, Markus; Eichbaum, Kathrin; Kammann, Ulrike; Hudjetz, Sebastian; Cofalla, Catrina; Buchinger, Sebastian; Reifferscheid, Georg; Schüttrumpf, Holger; Preuss, Thomas
2014-01-01
Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios
External factors in hospital information system (HIS) adoption model: a case on Malaysia.
Lee, Heng Wei; Ramayah, Thurasamy; Zakaria, Nasriah
2012-08-01
Studies related to healthcare ICT integration in Malaysia are relatively little, thus this paper provide a literature review of the integration of information and communication technologies (ICT) in the healthcare sector in Malaysia through the hospital information system (HIS). Our study emphasized on secondary data to investigate the factors related to ICT integration in healthcare through HIS. Therefore this paper aimed to gather an in depth understanding of issues related to HIS adoption, and contributing in fostering HIS adoption in Malaysia and other countries. This paper provides a direction for future research to study the correlation of factors affecting HIS adoption. Finally a research model is proposed using current adoption theories and external factors from human, technology, and organization perspectives.
Sum rules for four-spinon dynamic structure factor in XXX model
International Nuclear Information System (INIS)
Si Lakhal, B.; Abada, A.
2005-01-01
In the context of the antiferromagnetic spin 12 Heisenberg quantum spin chain (XXX model), we estimate the contribution of the exact four-spinon dynamic structure factor S 4 by calculating a number of sum rules the total dynamic structure factor S is known to satisfy exactly. These sum rules are: the static susceptibility, the integrated intensity, the total integrated intensity, the first frequency moment and the nearest-neighbor correlation function. We find that the contribution of S 4 is between 1% and 2.5%, depending on the sum rule, whereas the contribution of the exact two-spinon dynamic structure factor S 2 is between 70% and 75%. The calculations are numerical and Monte Carlo based. Good statistics are obtained
Meson form factors and covariant three-dimensional formulation of composite model
International Nuclear Information System (INIS)
Skachkov, N.B.; Solovtsov, I.L.
1978-01-01
An approach is developed which is applied in the framework of the relativistic quark model to obtain explicit expressions for meson form factors in terms of covariant wave functions of the two-quark system. These wave functions obey the two-particle quasipotential equation in which the relative motion of quarks is singled out in a covariant way. The exact form of the wave functions is found using the transition to the relativistic configurational representation with the help of the harmonic analysis on the Lorentz group instead of the usual Fourier expansion and then solving the relativistic difference equation thus obtained. The expressions found for form factors are transformed into the three-dimensional covariant form which is a direct geometrical relativistic generalization of analogous expressions of the nonrelativistic quantum mechanics and provides the decrease of the meson form factor by the Fsub(π)(t) approximately t -1 law as -t infinity, in the Coulomb field
Modeling the assessment of the economic factors impact on the development of social entrepreneurship
Absalyamov, T.; Kundakchyan, R.; Zulfakarova, L.; Zapparova, Z.
2017-12-01
The article deals with the research of modern trends in the development of social entrepreneurship in Russia. The results of the research allow the authors to identify a system of factors that affect the development of entrepreneurship in the modern Russian economy. Moreover, the authors argue the regional specificity of the development of social entrepreneurship. The paper considers specific features and formulates the main limitations of the development of entrepreneurship and the competitive environment in the social sphere. The authors suggest an econometric model for assessing the influence of economic factors on the development of socially-oriented entrepreneurship and present an algorithm for calculating its components. The results of the econometric analysis identify the main factors of the change in the performance indicators of entrepreneurial activity and determine the degree of their impact on social entrepreneurship. The results and conclusions can serve as an estimation of the socioeconomic consequences of the sustainability disruption of the entrepreneurial potential realization in the social sphere.
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.
Factors associated with therapeutic inertia in hypertension: validation of a predictive model.
Redón, Josep; Coca, Antonio; Lázaro, Pablo; Aguilar, Ma Dolores; Cabañas, Mercedes; Gil, Natividad; Sánchez-Zamorano, Miguel Angel; Aranda, Pedro
2010-08-01
To study factors associated with therapeutic inertia in treating hypertension and to develop a predictive model to estimate the probability of therapeutic inertia in a given medical consultation, based on variables related to the consultation, patient, physician, clinical characteristics, and level of care. National, multicentre, observational, cross-sectional study in primary care and specialist (hospital) physicians who each completed a questionnaire on therapeutic inertia, provided professional data and collected clinical data on four patients. Therapeutic inertia was defined as a consultation in which treatment change was indicated (i.e., SBP >or= 140 or DBP >or= 90 mmHg in all patients; SBP >or= 130 or DBP >or= 80 in patients with diabetes or stroke), but did not occur. A predictive model was constructed and validated according to the factors associated with therapeutic inertia. Data were collected on 2595 patients and 13,792 visits. Therapeutic inertia occurred in 7546 (75%) of the 10,041 consultations in which treatment change was indicated. Factors associated with therapeutic inertia were primary care setting, male sex, older age, SPB and/or DBP values close to normal, treatment with more than one antihypertensive drug, treatment with an ARB II, and more than six visits/year. Physician characteristics did not weigh heavily in the association. The predictive model was valid internally and externally, with acceptable calibration, discrimination and reproducibility, and explained one-third of the variability in therapeutic inertia. Although therapeutic inertia is frequent in the management of hypertension, the factors explaining it are not completely clear. Whereas some aspects of the consultations were associated with therapeutic inertia, physician characteristics were not a decisive factor.
Chiral-model of weak-interaction form factors and magnetic moments of octet baryons
International Nuclear Information System (INIS)
Kubodera, K.; Kohyama, Y.; Tsushima, K.; Yamaguchi, T.
1989-01-01
For baryon spectroscopy, magnetic moments and weak interaction form factors provide valuable information, and the impressive amount of available experimental data on these quantities for the octet baryons invites detailed investigations. The authors of this paper have made extensive studies of the weak-interaction form factors and magnetic moments of the octet baryons within the framework of the volume-type cloudy-bag model (v-type CBM). The clouds of all octet mesons have been included. Furthermore, we have taken into account in a unified framework various effects that were so far only individually discussed in the literature. Thus, the gluonic effects, center-of-mass (CM0 corrections, and recoil corrections have been included). In this talk, after giving a brief summary of some salient features of the results, we discuss a very interesting application of our model to the problem of the spin content of nucleons
Zero-Inflated Poisson Modeling of Fall Risk Factors in Community-Dwelling Older Adults.
Jung, Dukyoo; Kang, Younhee; Kim, Mi Young; Ma, Rye-Won; Bhandari, Pratibha
2016-02-01
The aim of this study was to identify risk factors for falls among community-dwelling older adults. The study used a cross-sectional descriptive design. Self-report questionnaires were used to collect data from 658 community-dwelling older adults and were analyzed using logistic and zero-inflated Poisson (ZIP) regression. Perceived health status was a significant factor in the count model, and fall efficacy emerged as a significant predictor in the logistic models. The findings suggest that fall efficacy is important for predicting not only faller and nonfaller status but also fall counts in older adults who may or may not have experienced a previous fall. The fall predictors identified in this study--perceived health status and fall efficacy--indicate the need for fall-prevention programs tailored to address both the physical and psychological issues unique to older adults. © The Author(s) 2014.
The Importance of Business Model Factors for Cloud Computing Adoption: Role of Previous Experiences
Directory of Open Access Journals (Sweden)
Bogataj Habjan Kristina
2017-08-01
Full Text Available Background and Purpose: Bringing several opportunities for more effective and efficient IT governance and service exploitation, cloud computing is expected to impact the European and global economies significantly. Market data show that despite many advantages and promised benefits the adoption of cloud computing is not as fast and widespread as foreseen. This situation shows the need for further exploration of the potentials of cloud computing and its implementation on the market. The purpose of this research was to identify individual business model factors with the highest impact on cloud computing adoption. In addition, the aim was to identify the differences in opinion regarding the importance of business model factors on cloud computing adoption according to companies’ previous experiences with cloud computing services.
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.
Directory of Open Access Journals (Sweden)
Mohamd Hakkak
2013-11-01
Full Text Available The rapid diffusion of the Internet has radically changed the delivery channels applied by the financial services industry. The aim of this study is to identify the influencing factors that encourage customers to adopt online banking in Khorramabad. The research constructs are developed based on the technology acceptance model (TAM and incorporates some extra important control variables. The model is empirically verified to study the factors influencing the online banking adoption behavior of 210 customers of Tejarat Banks in Khorramabad. The findings of the study suggest that the quality of the internet connection, the awareness of online banking and its benefits, the social influence and computer self-efficacy have significant impacts on the perceived usefulness (PU and perceived ease of use (PEOU of online banking acceptance. Trust and resistance to change also have significant impact on the attitude towards the likelihood of adopting online banking.
Strange mesonic transition form factor in the chiral constituent quark model
International Nuclear Information System (INIS)
Ito, H.; Ramsey-Musolf, M.J.
1998-01-01
The form factor g ρπ (S) (Q 2 ) of the strange vector current transition matrix element left-angle ρ|bar sγ μ s|π right-angle is calculated within the chiral quark model. A strange vector current of the constituent U and D quarks is induced by kaon radiative corrections and this mechanism yields the nonvanishing values of g ρπ (S) (0). The numerical result at the photon point is consistent with the one given by the φ-meson dominance model, but the falloff in the Q 2 dependence is faster than the monopole form factor. Mesonic radiative corrections are also examined for the electromagnetic ρ-to-π and K * -to-K transition amplitudes. copyright 1998 The American Physical Society
Use of model plant hosts to identify Pseudomonas aeruginosa virulence factors
Rahme, Laurence G.; Tan, Man-Wah; Le, Long; Wong, Sandy M.; Tompkins, Ronald G.; Calderwood, Stephen B.; Ausubel, Frederick M.
1997-01-01
We used plants as an in vivo pathogenesis model for the identification of virulence factors of the human opportunistic pathogen Pseudomonas aeruginosa. Nine of nine TnphoA mutant derivatives of P. aeruginosa strain UCBPP-PA14 that were identified in a plant leaf assay for less pathogenic mutants also exhibited significantly reduced pathogenicity in a burned mouse pathogenicity model, suggesting that P. aeruginosa utilizes common strategies to infect both hosts. Seven of these nine mutants contain TnphoA insertions in previously unknown genes. These results demonstrate that an alternative nonvertebrate host of a human bacterial pathogen can be used in an in vivo high throughput screen to identify novel bacterial virulence factors involved in mammalian pathogenesis. PMID:9371831
A six-factor model of brand personality and its predictive validity
Directory of Open Access Journals (Sweden)
Živanović Marko
2017-01-01
Full Text Available The study examines applicability and usefulness of HEXACO-based model in the description of brand personality. Following contemporary theoretical developments in human personality research, Study 1 explored the latent personality structure of 120 brands using descriptors of six personality traits as defined in HEXACO model: Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness. The results of exploratory factor analyses have supported HEXACO personality six-factor structure to a large extent. In Study 2 we addressed the question of predictive validity of HEXACO-based brand personality. Brand personality traits, but predominantly Honesty-Humility, accounted for substantial amount of variance in prediction of important aspects of consumer-brand relationship: attitude toward brand, perceived quality of a brand, and brand loyalty. The implications of applying HEXACO-based brand personality in marketing research are discussed. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. 179018 and Grant no. 175012
Directory of Open Access Journals (Sweden)
Cai-Jun Wu
2015-01-01
Full Text Available Background: Animal models of asphyxiation cardiac arrest (ACA are frequently used in basic research to mirror the clinical course of cardiac arrest (CA. The rates of the return of spontaneous circulation (ROSC in ACA animal models are lower than those from studies that have utilized ventricular fibrillation (VF animal models. The purpose of this study was to characterize the factors associated with the ROSC in the ACA porcine model. Methods: Forty-eight healthy miniature pigs underwent endotracheal tube clamping to induce CA. Once induced, CA was maintained untreated for a period of 8 min. Two minutes following the initiation of cardiopulmonary resuscitation (CPR, defibrillation was attempted until ROSC was achieved or the animal died. To assess the factors associated with ROSC in this CA model, logistic regression analyses were performed to analyze gender, the time of preparation, the amplitude spectrum area (AMSA from the beginning of CPR and the pH at the beginning of CPR. A receiver-operating characteristic (ROC curve was used to evaluate the predictive value of AMSA for ROSC. Results: ROSC was only 52.1% successful in this ACA porcine model. The multivariate logistic regression analyses revealed that ROSC significantly depended on the time of preparation, AMSA at the beginning of CPR and pH at the beginning of CPR. The area under the ROC curve in for AMSA at the beginning of CPR was 0.878 successful in predicting ROSC (95% confidence intervals: 0.773∼0.983, and the optimum cut-off value was 15.62 (specificity 95.7% and sensitivity 80.0%. Conclusions: The time of preparation, AMSA and the pH at the beginning of CPR were associated with ROSC in this ACA porcine model. AMSA also predicted the likelihood of ROSC in this ACA animal model.
Testing the CAPM and Three Factors Model in China: Evidence from the Shanghai Stock Exchange
Wang, Weixi
2015-01-01
Since inception, China’s stock market has grown rapidly and has become one of the most important emerging markets in the world. However, many popular financial media depicts China’s stock market as irrational. Besides, empirical studies on asset pricing in China’s stock market do not provide a consistent conclusion for different periods. This study tests the Capital Asset Pricing Model (CAPM) and Fama-French Three Factors Model in Shanghai Stock Exchange, China. For validity test of the CAPM,...
A conceptual model of factors contributing to the development of muscle dysmorphia.
Grieve, Frederick G
2007-01-01
Muscle dysmorphia is a recently described subcategory of Body Dysmorphic Disorder. It is most prevalent in males and has a number of cognitive, behavioral, socioenviornmental, emotional, and psychological factors that influence its expression. An etiological model describing these influences is presented for evaluation. Nine variables (body mass, media influences, ideal body internalization, low self-esteem, body dissatisfaction, health locus of control, negative affect, perfectionism, and body distortion) were identified through the use of extant literature on muscle dysmorphia and through extrapolation from literature involving women and eating disorders. The functional relationships among these variables are described and implications of the model are discussed.
International Nuclear Information System (INIS)
Ng, Y.C.; Hoffman, F.O.
1983-01-01
A parameter value for a radioecological assessment model is not a single value but a distribution of values about a central value. The sources that contribute to the variability of transfer factors to predict foodchain transport of radionuclides are enumerated. Knowledge of these sources, judgement in interpreting the available data, consideration of collateral information, and established criteria that specify the desired level of conservatism in the resulting predictions are essential elements when selecting appropriate parameter values for radioecological assessment models and regulatory guides. 39 references, 4 figures, 5 tables
Cosmological models with a hybrid scale factor in an extended gravity theory
Mishra, B.; Tripathy, S. K.; Tarai, Sankarsan
2018-03-01
A general formalism to investigate Bianchi type V Ih universes is developed in an extended theory of gravity. A minimally coupled geometry and matter field is considered with a rescaled function of f(R,T) substituted in place of the Ricci scalar R in the geometrical action. Dynamical aspects of the models are discussed by using a hybrid scale factor (HSF) that behaves as power law in an initial epoch and as an exponential form at late epoch. The power law behavior and the exponential behavior appear as two extreme cases of the present model.
Directory of Open Access Journals (Sweden)
Nnadi Nnaemeka Emmanuel
2011-09-01
Full Text Available Landscape epidemiology describes how the temporal dynamics of host, vector, and pathogen populations interact spatially within a permissive environment to enable transmission. It also aims at understanding the vegetation and geologic conditions that are necessary for the maintenance and transmission of a particular pathogen. The current review describes the evolution of landscape epidemiology. As a science, it also highlights the various methods of mapping and modeling diseases and disease risk factors. The key tool to characterize landscape is satellite remote sensing and these data are used as inputs to drive spatial models of transmission risk.
Energy Technology Data Exchange (ETDEWEB)
Ng, Y.C.; Hoffman, F.O.
1983-01-01
A parameter value for a radioecological assessment model is not a single value but a distribution of values about a central value. The sources that contribute to the variability of transfer factors to predict foodchain transport of radionuclides are enumerated. Knowledge of these sources, judgement in interpreting the available data, consideration of collateral information, and established criteria that specify the desired level of conservatism in the resulting predictions are essential elements when selecting appropriate parameter values for radioecological assessment models and regulatory guides. 39 references, 4 figures, 5 tables.
Poet, Torka S; Timchalk, Charles; Bartels, Michael J; Smith, Jordan N; McDougal, Robin; Juberg, Daland R; Price, Paul S
2017-06-01
A physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model combined with Monte Carlo analysis of inter-individual variation was used to assess the effects of the insecticide, chlorpyrifos and its active metabolite, chlorpyrifos oxon in humans. The PBPK/PD model has previously been validated and used to describe physiological changes in typical individuals as they grow from birth to adulthood. This model was updated to include physiological and metabolic changes that occur with pregnancy. The model was then used to assess the impact of inter-individual variability in physiology and biochemistry on predictions of internal dose metrics and quantitatively assess the impact of major sources of parameter uncertainty and biological diversity on the pharmacodynamics of red blood cell acetylcholinesterase inhibition. These metrics were determined in potentially sensitive populations of infants, adult women, pregnant women, and a combined population of adult men and women. The parameters primarily responsible for inter-individual variation in RBC acetylcholinesterase inhibition were related to metabolic clearance of CPF and CPF-oxon. Data Derived Extrapolation Factors that address intra-species physiology and biochemistry to replace uncertainty factors with quantitative differences in metrics were developed in these same populations. The DDEFs were less than 4 for all populations. These data and modeling approach will be useful in ongoing and future human health risk assessments for CPF and could be used for other chemicals with potential human exposure. Copyright © 2017 Elsevier Inc. All rights reserved.
Tanaka, Yoichi; Nishi, Yuki; Nishi, Yuki; Osumi, Michihiro; Morioka, Shu
2017-01-01
Pain is a subjective emotional experience that is influenced by psychosociological factors such as social skills, which are defined as problem-solving abilities in social interactions. This study aimed to reveal the relationships among pain, social skills, and other psychosociological factors by using structural equation modeling. A total of 101 healthy volunteers (41 men and 60 women; mean age: 36.6±12.7 years) participated in this study. To evoke participants' sense of inner pain, we showed them images of painful scenes on a PC screen and asked them to evaluate the pain intensity by using the visual analog scale (VAS). We examined the correlation between social skills and VAS, constructed a hypothetical model based on results from previous studies and the current correlational analysis results, and verified the model's fit using structural equation modeling. We found significant positive correlations between VAS and total social skills values, as well as between VAS and the "start of relationships" subscales. Structural equation modeling revealed that the values for "start of relationships" had a direct effect on VAS values (path coefficient =0.32, p social support. The results indicated that extroverted people are more sensitive to inner pain and tend to get more social support and maintain a better psychological condition.
Model calculating annual mean atmospheric dispersion factor for coastal site of nuclear power plant
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
This paper describes an atmospheric dispersion field experiment performed on the coastal site of nuclear power plant in the east part of China during 1995 to 1996. The three-dimension joint frequency are obtained by hourly observation of wind and temperature on a 100m high tower; the frequency of the “event day of land and sea breezes” are given by observation of surface wind and land and sea breezes; the diffusion parameters are got from measurements of turbulent and wind tunnel simulation test.A new model calculating the annual mean atmospheric dispersion factor for coastal site of nuclear power plant is developed and established.This model considers not only the effect from mixing release and mixed layer but also the effect from the internal boundary layer and variation of diffusion parameters due to the distance from coast.The comparison between results obtained by the new model and current model shows that the ratio of annual mean atmospheric dispersion factor gained by the new model and the current one is about 2.0.
A Comparative Study of CAPM and Seven Factors Risk Adjusted Return Model
Directory of Open Access Journals (Sweden)
Madiha Riaz Bhatti
2014-12-01
Full Text Available This study is a comparison and contrast of the predictive powers of two asset pricing models: CAPM and seven factor risk-return adjusted model, to explain the cross section of stock rate of returns in the financial sector listed at Karachi Stock Exchange (KSE. To test the models daily returns from January 2013 to February 2014 have been taken and the excess returns of portfolios are regressed on explanatory variables. The results of the tested models indicate that the models are valid and applicable in the financial market of Pakistan during the period under study, as the intercepts are not significantly different from zero. It is consequently established from the findings that all the explanatory variables explain the stock returns in the financial sector of KSE. In addition, the results of this study show that addition of more explanatory variables to the single factor CAPM results in reasonably high values of R2. These results provide substantial support to fund managers, investors and financial analysts in making investment decisions.
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.
Risk factors of chronic periodontitis on healing response: a multilevel modelling analysis.
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.
Forming Factors And Builder Indicators Of Brand Personality Models In Traditional Retail Traders
Yunelly Asra; Teguh Widodo
2017-01-01
This study aims to find the factors forming and indicator builder model of brand personality of traditional retail traders through measuring the influence of retail mix and culture. The formation of brand personality uses Aaker brand personality dimension to 250 consumers in Bengkalis Regency. The type of research is causal research design. The research variables are brand personality Retail Mix and Brand Personality. Data collection is done by probability sampling with purposive method. Data...
Key factors regulating the mass delivery of macromolecules to model cell membranes
DEFF Research Database (Denmark)
Campbell, Richard A.; Watkins, Erik B.; Jagalski, Vivien
2014-01-01
We show that both gravity and electrostatics are key factors regulating interactions between model cell membranes and self-assembled liquid crystalline aggregates of dendrimers and phospholipids. The system is a proxy for the trafficking of reservoirs of therapeutic drugs to cell membranes for slow...... of the aggregates to activate endocytosis pathways on specific cell types is discussed in the context of targeted drug delivery applications....
Interpersonal success factors for strategy implementation: a case study using group model building
Rodney J Scott; Robert Y Cavana; Donald Cameron
2015-01-01
Strategy implementation has been identified as an area of system dynamics literature requiring greater attention. Most strategies fail to be implemented successfully, and processes for effectively implementing strategy are yet to be fully explained and explored. The reported interpersonal success factors for strategy implementation are reported outcomes for group model building, suggesting potential applicability. A case study using validated survey methods yielded promising results, and sugg...
The risk factors of laryngeal pathology in Korean adults using a decision tree model.
Byeon, Haewon
2015-01-01
The purpose of this study was to identify risk factors affecting laryngeal pathology in the Korean population and to evaluate the derived prediction model. Cross-sectional study. Data were drawn from the 2008 Korea National Health and Nutritional Examination Survey. The subjects were 3135 persons (1508 male and 2114 female) aged 19 years and older living in the community. The independent variables were age, sex, occupation, smoking, alcohol drinking, and self-reported voice problems. A decision tree analysis was done to identify risk factors for predicting a model of laryngeal pathology. The significant risk factors of laryngeal pathology were age, gender, occupation, smoking, and self-reported voice problem in decision tree model. Four significant paths were identified in the decision tree model for the prediction of laryngeal pathology. Those identified as high risk groups for laryngeal pathology included those who self-reported a voice problem, those who were males in their 50s who did not recognize a voice problem, those who were not economically active males in their 40s, and male workers aged 19 and over and under 50 or 60 and over who currently smoked. The results of this study suggest that individual risk factors, such as age, sex, occupation, health behavior, and self-reported voice problem, affect the onset of laryngeal pathology in a complex manner. Based on the results of this study, early management of the high-risk groups is needed for the prevention of laryngeal pathology. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.
An Empirical Application of a Two-Factor Model of Stochastic Volatility
Czech Academy of Sciences Publication Activity Database
Kuchyňka, Alexandr
2008-01-01
Roč. 17, č. 3 (2008), s. 243-253 ISSN 1210-0455 R&D Projects: GA ČR GA402/07/1113; GA MŠk(CZ) LC06075 Institutional research plan: CEZ:AV0Z10750506 Keywords : stochastic volatility * Kalman filter Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2008/E/kuchynka-an empirical application of a two-factor model of stochastic volatility.pdf
Multi-Period Structural Model of a Mortgage Portfolio with Cointegrated Factors
Czech Academy of Sciences Publication Activity Database
Gapko, Petr; Šmíd, Martin
2016-01-01
Roč. 66, č. 6 (2016), s. 565-574 ISSN 0015-1920 R&D Projects: GA ČR GA15-10331S Institutional support: RVO:67985556 Keywords : credit risk * mortgage * loan portfolio * dynamic model * estimation Subject RIV: AH - Economics Impact factor: 0.604, year: 2016 http://library.utia.cas.cz/separaty/2016/E/smid-0467176.pdf
Analysis on the influence factors of Bitcoin's price based on VEC model
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 ...
MODELING POLLINATION FACTORS THAT INFLUENCE ALFALFA SEED YIELD IN NORTH-CENTRAL NEVADA
BREAZEALE, Don; FERNANDEZ, George; NARAYANAN, Rangesan
2008-01-01
The relative importance of both environmental and management factors on alfalfa seed yield was investigated on North–Central Nevada farms. Multiple linear regression models using 2002-2003 data revealed that cumulative tripped fl owers increased seed yield in both years. Field location does not appear to make a difference in the observed variation in tripped fl ower production. The results suggest that seed yield can be increased by (a) by placing bee shelters closer and (b) cultural practice...
Extracting the Evaluations of Stereotypes: Bi-factor Model of the Stereotype Content Structure
Sayans-Jiménez, Pablo; Cuadrado, Isabel; Rojas, Antonio J.; Barrada, Juan R.
2017-01-01
Stereotype dimensions—competence, morality and sociability—are fundamental to studying the perception of other groups. These dimensions have shown moderate/high positive correlations with each other that do not reflect the theoretical expectations. The explanation for this (e.g., halo effect) undervalues the utility of the shared variance identified. In contrast, in this work we propose that this common variance could represent the global evaluation of the perceived group. Bi-factor models ar...
Thermodynamic model for the elastic form factor in diffraction scattering of protons
International Nuclear Information System (INIS)
Grashin, A.F.; Evstratenko, A.S.; Lepeshkin, M.V.
1988-01-01
An explicit expression is obtained for the differential pp(p-bar)-scattering cross section in the diffraction-cone region by employing the thermodynamic model for the elastic form factor previously proposed in Ref. 4. Data for the energy region 16.3≤(s)/sup 1/2/ ≤546 GeV have been analyzed and significant deviations have been discovered from the commonly used approximations in the form of linear or quadratic exponentials
Models of Anaylzing the Influence of Factors on Forming Profit Rate
Directory of Open Access Journals (Sweden)
Klara S. Jakovčević
2014-04-01
Full Text Available The analysis in this paper is focused on identifying the impact of individual factors on the elements of the profit rate. The primary aim of this work is a methodological overview of solutions for understanding the full content of the profit rate as a cause of economic quality as well as indicators of the results of reproduction. Application of model analysis of profit rate factors was performed in an enterprise from Serbia that manufactures construction materials from baked clay. The aim is of application is to test the range in determining elements and factors of economic success of the enterprise, and quantification of changes in its assumptions. The results are useful guideline for the management to take organizational measures to increase the economic success of the enterprise. This means eliminating the negative, emphasizing the positive impact of objectively, and organizational factors to make higher economic success. Based on empirical research, it could be concluded that the proposed quantitative models of analyzing the dynamics of enterprise business quality could be applied in practice.
Dalvand, Sahar; Koohpayehzadeh, Jalil; Karimlou, Masoud; Asgari, Fereshteh; Rafei, Ali; Seifi, Behjat; Niksima, Seyed Hassan; Bakhshi, Enayatollah
2015-01-01
Because the use of BMI (Body Mass Index) alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome) and obesity (binary outcome) among Iranian adults. Data included 18,990 Iranian individuals aged 20-65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variable model, we estimated the relation of two correlated responses (waist circumference and obesity) with independent variables including age, gender, PR (Place of Residence), PA (physical activity), smoking status, SBP (Systolic Blood Pressure), DBP (Diastolic Blood Pressure), CHOL (cholesterol), FBG (Fasting Blood Glucose), diabetes, and FHD (family history of diabetes). All variables were related to both obesity and waist circumference (WC). Older age, female sex, being an urban resident, physical inactivity, nonsmoking, hypertension, hypercholesterolemia, hyperglycemia, diabetes, and having family history of diabetes were significant risk factors that increased WC and obesity. Findings from this study of Iranian adult settings offer more insights into factors associated with high WC and high prevalence of obesity in this population.
Assessing Factors Related to Waist Circumference and Obesity: Application of a Latent Variable Model
Directory of Open Access Journals (Sweden)
Sahar Dalvand
2015-01-01
Full Text Available Background. Because the use of BMI (Body Mass Index alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome and obesity (binary outcome among Iranian adults. Methods. Data included 18,990 Iranian individuals aged 20–65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variable model, we estimated the relation of two correlated responses (waist circumference and obesity with independent variables including age, gender, PR (Place of Residence, PA (physical activity, smoking status, SBP (Systolic Blood Pressure, DBP (Diastolic Blood Pressure, CHOL (cholesterol, FBG (Fasting Blood Glucose, diabetes, and FHD (family history of diabetes. Results. All variables were related to both obesity and waist circumference (WC. Older age, female sex, being an urban resident, physical inactivity, nonsmoking, hypertension, hypercholesterolemia, hyperglycemia, diabetes, and having family history of diabetes were significant risk factors that increased WC and obesity. Conclusions. Findings from this study of Iranian adult settings offer more insights into factors associated with high WC and high prevalence of obesity in this population.
Directory of Open Access Journals (Sweden)
Jianchang Lu
2015-04-01
Full Text Available Based on the international community’s analysis of the present CO2 emissions situation, a Log Mean Divisia Index (LMDI decomposition model is proposed in this paper, aiming to reflect the decomposition of carbon productivity. The model is designed by analyzing the factors that affect carbon productivity. China’s contribution to carbon productivity is analyzed from the dimensions of influencing factors, regional structure and industrial structure. It comes to the conclusions that: (a economic output, the provincial carbon productivity and energy structure are the most influential factors, which are consistent with China’s current actual policy; (b the distribution patterns of economic output, carbon productivity and energy structure in different regions have nothing to do with the Chinese traditional sense of the regional economic development patterns; (c considering the regional protectionism, regional actual situation need to be considered at the same time; (d in the study of the industrial structure, the contribution value of industry is the most prominent factor for China’s carbon productivity, while the industrial restructuring has not been done well enough.
Directory of Open Access Journals (Sweden)
Guillem Casanovas
2014-01-01
Full Text Available Systemic iron homeostasis involves a negative feedback circuit in which the expression level of the peptide hormone hepcidin depends on and controls the iron blood levels. Hepcidin expression is regulated by the BMP6/SMAD and IL6/STAT signaling cascades. Deregulation of either pathway causes iron-related diseases such as hemochromatosis or anemia of inflammation. We quantitatively analyzed how BMP6 and IL6 control hepcidin expression. Transcription factor (TF phosphorylation and reporter gene expression were measured under co-stimulation conditions, and the promoter was perturbed by mutagenesis. Using mathematical modeling, we systematically analyzed potential mechanisms of cooperative and competitive promoter regulation by the transcription factors, and experimentally validated the model predictions. Our results reveal that hepcidin cross-regulation primarily occurs by combinatorial transcription factor binding to the promoter, whereas signaling crosstalk is insignificant. We find that the presence of two BMP-responsive elements enhances the steepness of the promoter response towards the iron-sensing BMP signaling axis, which promotes iron homeostasis in vivo. IL6 co-stimulation reduces the promoter sensitivity towards the BMP signal, because the SMAD and STAT transcription factors compete for recruiting RNA polymerase to the transcription start site. This may explain why inflammatory signals disturb iron homeostasis in anemia of inflammation. Taken together, our results reveal why the iron homeostasis circuit is sensitive to perturbations implicated in disease.
A HUMAN FACTORS META MODEL FOR U.S. NUCLEAR POWER PLANT CONTROL ROOM MODERNIZATION
Energy Technology Data Exchange (ETDEWEB)
Joe, Jeffrey C.
2017-03-01
Over the last several years, the United States (U.S.) Department of Energy (DOE) has sponsored human factors research and development (R&D) and human factors engineering (HFE) activities through its Light Water Reactor Sustainability (LWRS) program to modernize the main control rooms (MCR) of commercial nuclear power plants (NPP). Idaho National Laboratory (INL), in partnership with numerous commercial nuclear utilities, has conducted some of this R&D to enable the life extension of NPPs (i.e., provide the technical basis for the long-term reliability, productivity, safety, and security of U.S. NPPs). From these activities performed to date, a human factors meta model for U.S. NPP control room modernization can now be formulated. This paper discusses this emergent HFE meta model for NPP control room modernization, with the goal of providing an integrated high level roadmap and guidance on how to perform human factors R&D and HFE for those in the U.S. nuclear industry that are engaging in the process of upgrading their MCRs.
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
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.
Chan, W. S.; Fuentes, J. D.; Lerdau, M.
2010-12-01
This presentation will provide research findings to evaluate the hypothesis that the loss of biogenic volatile organic compound (BVOC) within plant canopies is dynamic and depends on factors such as plant canopy architecture (height and leaf area distribution), atmospheric turbulence, concentration of oxidants (OH, O3, NO3), and the reactivity of BVOC species. Results will be presented from a new one dimensional, multilevel canopy model that couples algorithms for canopy microclimate, leaf physiology, BVOC emission, turbulent transport, and atmospheric chemistry to investigate the relative importance of factors that impact BVOC loss within a forest canopy. Model sensitivity tests will be presented and discussed to identify factors driving canopy loss. Results show isoprene and monoterpene canopy losses as high as 9 and 18%, respectively, for tall canopies during the daytime. We hypothesize that canopy height and wind speed (i.e. canopy residence time) may be the most important in dictating within-canopy loss. This work will reduce the error in bottom-up flux estimates of BVOCs and ultimately improve parameterizations of BVOC sources in air quality models by accounting for within canopy processes.
Antaramian, Susan P; Scott Huebner, E; Hills, Kimberly J; Valois, Robert F
2010-10-01
Traditional mental health models focus on psychological problems and distress; accordingly, health is viewed as the absence of illness or disability. In contrast, a dual-factor model of mental health incorporates both indicators of positive subjective well-being (SWB) and measures of psychopathological symptoms to comprehensively determine an individual's psychological adjustment. This study used such a dual-factor model to measure the mental health status of young adolescents. A total of 764 middle school students were classified into one of four distinct groups based on having high or low psychopathology and high or low SWB. Furthermore, group differences in student engagement, academic achievement, and environmental support for learning were investigated. Results demonstrated the existence of a traditionally neglected group of adolescents (low SWB and low psychopathology) who are nonetheless at risk for academic and behavior problems in school and who performed no better than the most troubled group of adolescents. Overall, both the presence of positive well-being and the absence of symptoms were necessary for ensuring the most advantageous school performance. These results highlight the importance of incorporating positive indicators of well-being along with traditional negative factors in more fully understanding relationships between individuals' mental health and educational outcomes. © 2010 American Orthopsychiatric Association.
Relativistic form factors for hadrons with quark-model wave functions
International Nuclear Information System (INIS)
Stanley, D.P.; Robson, D.
1982-01-01
The relationship between relativistic form factors and quark-potential-model wave functions is examined using an improved version of an approach by Licht and Pagnamenta. Lorentz-contraction effects are expressed in terms of an effective hadron mass which varies as the square root of the number of quark constituents. The effective mass is calculated using the rest-frame wave functions from the mean-square momentum along the direction of the momentum transfer. Applications with the parameter-free approach are made to the elastic form factors of the pion, proton, and neutron using a Hamiltonian which simultaneously describes mesons and baryons. A comparison of the calculated radii for pions and kaons suggests that the measured kaon radius should be slightly smaller than the corresponding pion radius. The large negative squared charge radius for the neutron is partially explained via the quark model but a full description requires the inclusion of a small component of a pion ''cloud'' configuration. The problematic connection between the sizes of hadrons deduced from form factors and the ''measured'' values of average transverse momenta is reconciled in the present model
International Nuclear Information System (INIS)
Nafidi, A.; Gutiérrez, R.; Gutiérrez-Sánchez, R.; Ramos-Ábalos, E.; El Hachimi, S.
2016-01-01
The aim of this study is to model electric power consumption during a period of economic crisis, characterised by declining gross domestic product. A novel aspect of this study is its use of a Gamma-type diffusion process for short and medium-term forecasting – other techniques that have been used to describe such consumption patterns are not valid in this situation. In this study, we consider a new extension of the stochastic Gamma diffusion process by introducing time functions (exogenous factors) that affect its trend. This extension is defined in terms of Kolmogorov backward and forward equations. After obtaining the transition probability density function and the moments (specifically, the trend function), the inference on the process parameters is obtained by discrete sampling of the sample paths. Finally, this stochastic process is applied to model total net electricity consumption in Spain, when affected by the following set of exogenous factors: Gross Domestic Product (GDP), Gross Fixed Capital Formation (GFCF) and Final Domestic Consumption (FDC). - Highlights: • The aim is modelling and predicting electricity consumption in Spain. • We propose a Gamma-type diffusion process for short and medium-term forecasting. • We compared the fit using diffusion processes with different exogenous factors.
Factors associated with leisure time physical inactivity in black individuals: hierarchical model
Directory of Open Access Journals (Sweden)
Francisco José Gondim Pitanga
2014-09-01
Full Text Available Background. A number of studies have shown that the black population exhibits higher levels of leisure-time physical inactivity (LTPI, but few have investigated the factors associated with this behavior.Objective. The aim of this study was to analyze associated factors and the explanatory model proposed for LTPI in black adults.Methods. The design was cross-sectional with a sample of 2,305 adults from 20–96 years of age, 902 (39.1% men, living in the city of Salvador, Brazil. LTPI was analyzed using the International Physical Activity Questionnaire (IPAQ. A hierarchical model was built with the possible factors associated with LTPI, distributed in distal (age and sex, intermediate 1 (socioeconomic status, educational level and marital status, intermediate 2 (perception of safety/violence in the neighborhood, racial discrimination in private settings and physical activity at work and proximal blocks (smoking and participation in Carnival block rehearsals. We estimated crude and adjusted odds ratio (OR using logistic regression.Results. The variables inversely associated with LTPI were male gender, socioeconomic status and secondary/university education, although the proposed model explains only 4.2% of LTPI.Conclusions. We conclude that male gender, higher education and socioeconomic status can reduce LTPI in black adults.
Li, Ronghui; Pan, Wei; Guo, Jinchuan; Pang, Yong; Wu, Jianqiang; Li, Yiping; Pan, Baozhu; Ji, Yong; Ding, Ling
2014-05-01
The basis for submerged plant restoration in surface water is to research the complicated dynamic mechanism of water transparency. In this paper, through the impact factor analysis of water transparency, the suspended sediment, dissolved organic matter, algae were determined as three main impactfactors for water transparency of Neijiang River in Eastern China. And the multiple regression equation of water transparency and sediment concentration, permanganate index, chlorophyll-a concentration was developed. Considering the complicated transport and transformation of suspended sediment, dissolved organic matter and algae, numerical model of them were developed respectively for simulating the dynamic process. Water transparency numerical model was finally developed by coupling the sediment, water quality, and algae model. These results showed that suspended sediment was a key factor influencing water transparency of Neijiang River, the influence of water quality indicated by chemical oxygen demand and algal concentration indicated by chlorophyll a were indeterminate when their concentrations were lower, the influence was more obvious when high concentrations are available, such three factors showed direct influence on water transparency.
Form factors of descendant operators: reduction to perturbed M(2,2s+1) models
International Nuclear Information System (INIS)
Lashkevich, Michael; Pugai, Yaroslav
2015-01-01
In the framework of the algebraic approach to form factors in two-dimensional integrable models of quantum field theory we consider the reduction of the sine-Gordon model to the Φ 13 -perturbation of minimal conformal models of the M(2,2s+1) series. We find in an algebraic form the condition of compatibility of local operators with the reduction. We propose a construction that make it possible to obtain reduction compatible local operators in terms of screening currents. As an application we obtain exact multiparticle form factors for the compatible with the reduction conserved currents T ±2k , Θ ±(2k−2) , which correspond to the spin ±(2k−1) integrals of motion, for any positive integer k. Furthermore, we obtain all form factors of the operators T 2k T −2l , which generalize the famous TT̄ operator. The construction is analytic in the s parameter and, therefore, makes sense in the sine-Gordon theory.
Modeling silicon diode energy response factors for use in therapeutic photon beams.
Eklund, Karin; Ahnesjö, Anders
2009-10-21
Silicon diodes have good spatial resolution, which makes them advantageous over ionization chambers for dosimetry in fields with high dose gradients. However, silicon diodes overrespond to low-energy photons, that are more abundant in scatter which increase with large fields and larger depths. We present a cavity-theory-based model for a general response function for silicon detectors at arbitrary positions within photon fields. The model uses photon and electron spectra calculated from fluence pencil kernels. The incident photons are treated according to their energy through a bipartition of the primary beam photon spectrum into low- and high-energy components. Primary electrons from the high-energy component are treated according to Spencer-Attix cavity theory. Low-energy primary photons together with all scattered photons are treated according to large cavity theory supplemented with an energy-dependent factor K(E) to compensate for energy variations in the electron equilibrium. The depth variation of the response for an unshielded silicon detector has been calculated for 5 x 5 cm(2), 10 x 10 cm(2) and 20 x 20 cm(2) fields in 6 and 15 MV beams and compared with measurements showing that our model calculates response factors with deviations less than 0.6%. An alternative method is also proposed, where we show that one can use a correlation with the scatter factor to determine the detector response of silicon diodes with an error of less than 3% in 6 MV and 15 MV photon beams.
Urbain, Jay
2015-12-01
We present the design, and analyze the performance of a multi-stage natural language processing system employing named entity recognition, Bayesian statistics, and rule logic to identify and characterize heart disease risk factor events in diabetic patients over time. The system was originally developed for the 2014 i2b2 Challenges in Natural Language in Clinical Data. The system's strengths included a high level of accuracy for identifying named entities associated with heart disease risk factor events. The system's primary weakness was due to inaccuracies when characterizing the attributes of some events. For example, determining the relative time of an event with respect to the record date, whether an event is attributable to the patient's history or the patient's family history, and differentiating between current and prior smoking status. We believe these inaccuracies were due in large part to the lack of an effective approach for integrating context into our event detection model. To address these inaccuracies, we explore the addition of a distributional semantic model for characterizing contextual evidence of heart disease risk factor events. Using this semantic model, we raise our initial 2014 i2b2 Challenges in Natural Language of Clinical data F1 score of 0.838 to 0.890 and increased precision by 10.3% without use of any lexicons that might bias our results. Copyright © 2015 Elsevier Inc. All rights reserved.
Modeling silicon diode energy response factors for use in therapeutic photon beams
International Nuclear Information System (INIS)
Eklund, Karin; Ahnesjoe, Anders
2009-01-01
Silicon diodes have good spatial resolution, which makes them advantageous over ionization chambers for dosimetry in fields with high dose gradients. However, silicon diodes overrespond to low-energy photons, that are more abundant in scatter which increase with large fields and larger depths. We present a cavity-theory-based model for a general response function for silicon detectors at arbitrary positions within photon fields. The model uses photon and electron spectra calculated from fluence pencil kernels. The incident photons are treated according to their energy through a bipartition of the primary beam photon spectrum into low- and high-energy components. Primary electrons from the high-energy component are treated according to Spencer-Attix cavity theory. Low-energy primary photons together with all scattered photons are treated according to large cavity theory supplemented with an energy-dependent factor K(E) to compensate for energy variations in the electron equilibrium. The depth variation of the response for an unshielded silicon detector has been calculated for 5 x 5 cm 2 , 10 x 10 cm 2 and 20 x 20 cm 2 fields in 6 and 15 MV beams and compared with measurements showing that our model calculates response factors with deviations less than 0.6%. An alternative method is also proposed, where we show that one can use a correlation with the scatter factor to determine the detector response of silicon diodes with an error of less than 3% in 6 MV and 15 MV photon beams.
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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.
Rajaprasad, Sunku Venkata Siva; Chalapathi, Pasupulati Venkata
2015-09-01
Construction activity has made considerable breakthroughs in the past two decades on the back of increases in development activities, government policies, and public demand. At the same time, occupational health and safety issues have become a major concern to construction organizations. The unsatisfactory safety performance of the construction industry has always been highlighted since the safety management system is neglected area and not implemented systematically in Indian construction organizations. Due to a lack of enforcement of the applicable legislation, most of the construction organizations are forced to opt for the implementation of Occupational Health Safety Assessment Series (OHSAS) 18001 to improve safety performance. In order to better understand factors influencing the implementation of OHSAS 18001, an interpretive structural modeling approach has been applied and the factors have been classified using matrice d'impacts croises-multiplication appliqué a un classement (MICMAC) analysis. The study proposes the underlying theoretical framework to identify factors and to help management of Indian construction organizations to understand the interaction among factors influencing in implementation of OHSAS 18001. Safety culture, continual improvement, morale of employees, and safety training have been identified as dependent variables. Safety performance, sustainable construction, and conducive working environment have been identified as linkage variables. Management commitment and safety policy have been identified as the driver variables. Management commitment has the maximum driving power and the most influential factor is safety policy, which states clearly the commitment of top management towards occupational safety and health.
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...
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Seonyoung Yun, PhD, RN
2018-03-01
Full Text Available Purpose: The purpose of this study was to build and test a model outlining the factors related to workplace bullying among nurses. The hypothesized model included authentic leadership and a relationship-oriented organizational culture as influencing factors, symptom experience and turnover intention as consequences, and positive psychological capital as a mediator of workplace bullying among nurses. Methods: We obtained structured questionnaire data from 301 nurses working at hospitals in South Korea. Based on these data, the developed model was verified via a structural equation modeling analysis using SPSS and AMOS program. Results: The fit indices of the hypothesized model satisfied recommended levels; χ2 = 397.58 (p < .001, normed χ2 (χ2/df = 1.82, RMR = .05, TLI = .93, CFI = .94, RMSEA = .05. A relationship-oriented organizational culture had a direct effect on workplace bullying (β = −.48, p < .001. Furthermore, workplace bullying had a direct effect on symptom experience (β = .36, p < .001, and this relationship was mediated by positive psychological capital (β = .15, p = .003. Workplace bullying also had an indirect effect on turnover intention (β = .20, p = .007. Finally, symptom experience had a direct effect on turnover intention (β = .31, p = .002. Conclusion: These results suggest that workplace bullying among nurses may be prevented by constructing a relationship-oriented organizational culture, as long as employees have sufficient positive psychological capital. In this regard, workplace bullying among nurses should be addressed using a comprehensive strategy that considers both individual and organizational factors. Keywords: bullying, leadership, nurses, organizational culture, personnel turnover
Spatial scale effects in environmental risk-factor modelling for diseases
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Ram K. Raghavan
2013-05-01
Full Text Available Studies attempting to identify environmental risk factors for diseases can be seen to extract candidate variables from remotely sensed datasets, using a single buffer-zone surrounding locations from where disease status are recorded. A retrospective case-control study using canine leptospirosis data was conducted to verify the effects of changing buffer-zones (spatial extents on the risk factors derived. The case-control study included 94 case dogs predominantly selected based on positive polymerase chain reaction (PCR test for leptospires in urine, and 185 control dogs based on negative PCR. Land cover features from National Land Cover Dataset (NLCD and Kansas Gap Analysis Program (KS GAP around geocoded addresses of cases/controls were extracted using multiple buffers at every 500 m up to 5,000 m, and multivariable logistic models were used to estimate the risk of different land cover variables to dogs. The types and statistical significance of risk factors identified changed with an increase in spatial extent in both datasets. Leptospirosis status in dogs was significantly associated with developed high-intensity areas in models that used variables extracted from spatial extents of 500-2000 m, developed medium-intensity areas beyond 2,000 m and up to 3,000 m, and evergreen forests beyond 3,500 m and up to 5,000 m in individual models in the NLCD. Significant associations were seen in urban areas in models that used variables extracted from spatial extents of 500-2,500 m and forest/woodland areas beyond 2,500 m and up to 5,000 m in individual models in Kansas gap analysis programme datasets. The use of ad hoc spatial extents can be misleading or wrong, and the determination of an appropriate spatial extent is critical when extracting environmental variables for studies. Potential work-arounds for this problem are discussed.
Off-critical statistical models: factorized scattering theories and bootstrap program
International Nuclear Information System (INIS)
Mussardo, G.
1992-01-01
We analyze those integrable statistical systems which originate from some relevant perturbations of the minimal models of conformal field theories. When only massive excitations are present, the systems can be efficiently characterized in terms of the relativistic scattering data. We review the general properties of the factorizable S-matrix in two dimensions with particular emphasis on the bootstrap principle. The classification program of the allowed spins of conserved currents and of the non-degenerate S-matrices is discussed and illustrated by means of some significant examples. The scattering theories of several massive perturbations of the minimal models are fully discussed. Among them are the Ising model, the tricritical Ising model, the Potts models, the series of the non-unitary minimal models M 2,2n+3 , the non-unitary model M 3,5 and the scaling limit of the polymer system. The ultraviolet limit of these massive integrable theories can be exploited by the thermodynamics Bethe ansatz, in particular the central charge of the original conformal theories can be recovered from the scattering data. We also consider the numerical method based on the so-called conformal space truncated approach which confirms the theoretical results and allows a direct measurement of the scattering data, i.e. the masses and the S-matrix of the particles in bootstrap interaction. The problem of computing the off-critical correlation functions is discussed in terms of the form-factor approach
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Subhas C. Misra
2018-06-01
Full Text Available Biomedical engineering has grown as a vast field of research that includes many areas of engineering and technology also. Personalized Medicine is an emerging approach in today’s medicare system. It bears a very strong potential to consolidate modern e-health systems fundamentally. Scientists have already discovered some of the personalized drugs that can shift the whole medicare system into a new dimension. However, bringing the change in the whole medicare system is not an easy task. There are several factors that can affect the successful adoption of Personalized Medicine systems in the healthcare management sector. This paper aims at identifying the critical factors with the help of an empirical study. A questionnaire was distributed amongst some clinicians, clinical researchers, practitioners in pharmaceutical industries, regulatory board members, and a larger section of patients. The response data collected thereby were analyzed by using appropriate statistical methods. Based on the statistical analysis, an attempt is made to prepare a list of critical success factors in the adoption of personalized medicine in healthcare management. The study indicates that eight of the thirteen hypothesized factors have statistical relationship with “Success”. The important success factors detected are: data management, team work and composition, privacy and confidentiality, mind-set, return on investment, sufficient time, R&D and alignment. To the best of our knowledge, this is the first academic paper in which an attempt has been made to model the vital critical factors for the successful implementation of Personalized Medicine in healthcare management. The study bears the promise of important applications in healthcare engineering and technology. Keywords: Healthcare management, Personalized medicine, E-health, Success factors, Medicare systems, Regression analysis
Christen, Andreas; Johnson, Mark; Molodovskaya, Marina; Ketler, Rick; Nesic, Zoran; Crawford, Ben; Giometto, Marco; van der Laan, Mike
2013-04-01
The most important long-lived greenhouse gas (LLGHG) emitted during combustion of fuels is carbon dioxide (CO2), however also traces of the LLGHGs methane (CH4) and nitrous oxide (N2O) are released, the quantities of which depend largely on the conditions of the combustion process. Emission factors determine the mass of LLGHGs emitted per energy used (or kilometre driven for cars) and are key inputs for bottom-up emission modelling. Emission factors for CH4 are typically determined in the laboratory or on a test stand for a given combustion system using a small number of samples (vehicles, furnaces), yet associated with larger uncertainties when scaled to entire fleets. We propose an alternative, different approach - Can integrated emission factors be independently determined using direct micrometeorological flux measurements over an urban surface? If so, do emission factors determined from flux measurements (top-down) agree with up-scaled emission factors of relevant combustion systems (heating, vehicles) in the source area of the flux measurement? Direct flux measurements of CH4 were carried out between February and May, 2012 over a relatively densely populated, urban surface in Vancouver, Canada by means of eddy covariance (EC). The EC-system consisted of an ultrasonic anemometer (CSAT-3, Campbell Scientific Inc.) and two open-path infrared gas analyzers (Li7500 and Li7700, Licor Inc.) on a tower at 30m above the surface. The source area of the EC system is characterised by a relative homogeneous morphometry (5.3m average building height), but spatially and temporally varying emission sources, including two major intersecting arterial roads (70.000 cars drive through the 50% source area per day) and seasonal heating in predominantly single-family houses (natural gas). An inverse dispersion model (turbulent source area model), validated against large eddy simulations (LES) of the urban roughness sublayer, allows the determination of the spatial area that
Dierks, Raphaela Marie Louisa; Bruyère, Olivier; Reginster, Jean-Yves; Richy, Florent-Frederic
2016-10-01
Technological innovations, new regulations, increasing costs of drug productions and new demands are only few key drivers of a projected alternation in the pharmaceutical industry. The purpose of this review is to understand the macro economic factors responsible for the business model revolution to possess a competitive advantage over market players. Areas covered: Existing literature on macro-economic factors changing the pharmaceutical landscape has been reviewed to present a clear image of the current market environment. Expert commentary: Literature shows that pharmaceutical companies are facing an architectural alteration, however the evidence on the rationale driving the transformation is outstanding. Merger & Acquisitions (M&A) deals and collaborations are headlining the papers. Q1 2016 did show a major slowdown in M&A deals by volume since 2013 (with deal cancellations of Pfizer and Allergan, or the downfall of Valeant), but pharmaceutical analysts remain confident that this shortfall was a consequence of the equity market volatility. It seems likely that the shift to an M&A model will become apparent during the remainder of 2016, with deal announcements of Abbott Laboratories, AbbVie and Sanofi worth USD 45billion showing the appetite of big pharma companies to shift from the fully vertical integrated business model to more horizontal business models.
Dai, Hanjun
2017-07-26
Motivation: An accurate characterization of transcription factor (TF)-DNA affinity landscape is crucial to a quantitative understanding of the molecular mechanisms underpinning endogenous gene regulation. While recent advances in biotechnology have brought the opportunity for building binding affinity prediction methods, the accurate characterization of TF-DNA binding affinity landscape still remains a challenging problem. Results: Here we propose a novel sequence embedding approach for modeling the transcription factor binding affinity landscape. Our method represents DNA binding sequences as a hidden Markov model (HMM) which captures both position specific information and long-range dependency in the sequence. A cornerstone of our method is a novel message passing-like embedding algorithm, called Sequence2Vec, which maps these HMMs into a common nonlinear feature space and uses these embedded features to build a predictive model. Our method is a novel combination of the strength of probabilistic graphical models, feature space embedding and deep learning. We conducted comprehensive experiments on over 90 large-scale TF-DNA data sets which were measured by different high-throughput experimental technologies. Sequence2Vec outperforms alternative machine learning methods as well as the state-of-the-art binding affinity prediction methods.
The effect of modifiable risk factors on geographic mortality differentials: a modelling study
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Stevenson Christopher E
2012-01-01
Full Text Available Abstract Background Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown. Methods We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy. Results Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas--accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men and 35.6% (women of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men-- accounting for 8.8% and 6.3% respectively-- and only smoking contributing to the difference in women--accounting for 12.3%. Conclusions These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas.
Gravitational form factors and angular momentum densities in light-front quark-diquark model
Energy Technology Data Exchange (ETDEWEB)
Kumar, Narinder [Indian Institute of Technology Kanpur, Department of Physics, Kanpur (India); Mondal, Chandan [Chinese Academy of Sciences, Institute of Modern Physics, Lanzhou (China); Sharma, Neetika [I K Gujral Punjab Technical University, Department of Physical Sciences, Jalandhar, Punjab (India); Panjab University, Department of Physics, Chandigarh (India)
2017-12-15
We investigate the gravitational form factors (GFFs) and the longitudinal momentum densities (p{sup +} densities) for proton in a light-front quark-diquark model. The light-front wave functions are constructed from the soft-wall AdS/QCD prediction. The contributions from both the scalar and the axial vector diquarks are considered here. The results are compared with the consequences of a parametrization of nucleon generalized parton distributions (GPDs) in the light of recent MRST measurements of parton distribution functions (PDFs) and a soft-wall AdS/QCD model. The spatial distribution of angular momentum for up and down quarks inside the nucleon has been presented. At the density level, we illustrate different definitions of angular momentum explicitly for an up and down quark in the light-front quark-diquark model inspired by AdS/QCD. (orig.)
Linear model analysis of the influencing factors of boar longevity in Southern China.
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.
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Tian-Syung Lan
2014-01-01
Full Text Available This study used system dynamics method to investigate the factors affecting elementary school students’ BMI values. The construction of the dynamic model is divided into the qualitative causal loop and the quantitative system dynamics modeling. According to the system dynamics modeling, this study consisted of research on the four dimensions: student’s personal life style, diet-relevant parenting behaviors, advocacy and implementation of school nutrition education, and students’ peer interaction. The results of this study showed that students with more adequate health concepts usually have better eating behaviors and consequently have less chance of becoming obese. In addition, this study also verified that educational attainment and socioeconomic status of parents have a positive correlation with students’ amounts of physical activity, and nutrition education has a prominent influence on changing students’ high-calorie diets.
Markovits, Henry; Benenson, Joyce F; Kramer, Donald L
2003-01-01
This study examined internal representations of food sharing in 589 children and adolescents (8-19 years of age). Questionnaires, depicting a variety of contexts in which one person was asked to share a resource with another, were used to examine participants' expectations of food-sharing behavior. Factors that were varied included the value of the resource, the relation between the two depicted actors, the quality of this relation, and gender. Results indicate that internal models of food-sharing behavior showed systematic patterns of variation, demonstrating that individuals have complex contextually based internal models at all ages, including the youngest. Examination of developmental changes in use of individual patterns is consistent with the idea that internal models reflect age-specific patterns of interactions while undergoing a process of progressive consolidation.
Empiric model for mean generation time adjustment factor for classic point kinetics equations
Energy Technology Data Exchange (ETDEWEB)
Goes, David A.B.V. de; Martinez, Aquilino S.; Goncalves, Alessandro da C., E-mail: david.goes@poli.ufrj.br, E-mail: aquilino@lmp.ufrj.br, E-mail: alessandro@con.ufrj.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Departamento de Engenharia Nuclear
2017-11-01
Point reactor kinetics equations are the easiest way to observe the neutron production time behavior in a nuclear reactor. These equations are derived from the neutron transport equation using an approximation called Fick's law leading to a set of first order differential equations. The main objective of this study is to review classic point kinetics equation in order to approximate its results to the case when it is considered the time variation of the neutron currents. The computational modeling used for the calculations is based on the finite difference method. The results obtained with this model are compared with the reference model and then it is determined an empirical adjustment factor that modifies the point reactor kinetics equation to the real scenario. (author)