Extending the Technology Acceptance Model: Policy Acceptance Model (PAM)
NASA Astrophysics Data System (ADS)
Pierce, Tamra
There has been extensive research on how new ideas and technologies are accepted in society. This has resulted in the creation of many models that are used to discover and assess the contributing factors. The Technology Acceptance Model (TAM) is one that is a widely accepted model. This model examines people's acceptance of new technologies based on variables that directly correlate to how the end user views the product. This paper introduces the Policy Acceptance Model (PAM), an expansion of TAM, which is designed for the analysis and evaluation of acceptance of new policy implementation. PAM includes the traditional constructs of TAM and adds the variables of age, ethnicity, and family. The model is demonstrated using a survey of people's attitude toward the upcoming healthcare reform in the United States (US) from 72 survey respondents. The aim is that the theory behind this model can be used as a framework that will be applicable to studies looking at the introduction of any new or modified policies.
Axelrod model: accepting or discussing
NASA Astrophysics Data System (ADS)
Dybiec, Bartlomiej; Mitarai, Namiko; Sneppen, Kim
2012-10-01
Agents building social systems are characterized by complex states, and interactions among individuals can align their opinions. The Axelrod model describes how local interactions can result in emergence of cultural domains. We propose two variants of the Axelrod model where local consensus is reached either by listening and accepting one of neighbors' opinion or two agents discuss their opinion and achieve an agreement with mixed opinions. We show that the local agreement rule affects the character of the transition between the single culture and the multiculture regimes.
Measured, modeled, and causal conceptions of fitness.
Abrams, Marshall
2012-01-01
THIS PAPER PROPOSES PARTIAL ANSWERS TO THE FOLLOWING QUESTIONS: in what senses can fitness differences plausibly be considered causes of evolution?What relationships are there between fitness concepts used in empirical research, modeling, and abstract theoretical proposals? How does the relevance of different fitness concepts depend on research questions and methodological constraints? The paper develops a novel taxonomy of fitness concepts, beginning with type fitness (a property of a genotype or phenotype), token fitness (a property of a particular individual), and purely mathematical fitness. Type fitness includes statistical type fitness, which can be measured from population data, and parametric type fitness, which is an underlying property estimated by statistical type fitnesses. Token fitness includes measurable token fitness, which can be measured on an individual, and tendential token fitness, which is assumed to be an underlying property of the individual in its environmental circumstances. Some of the paper's conclusions can be outlined as follows: claims that fitness differences do not cause evolution are reasonable when fitness is treated as statistical type fitness, measurable token fitness, or purely mathematical fitness. Some of the ways in which statistical methods are used in population genetics suggest that what natural selection involves are differences in parametric type fitnesses. Further, it's reasonable to think that differences in parametric type fitness can cause evolution. Tendential token fitnesses, however, are not themselves sufficient for natural selection. Though parametric type fitnesses are typically not directly measurable, they can be modeled with purely mathematical fitnesses and estimated by statistical type fitnesses, which in turn are defined in terms of measurable token fitnesses. The paper clarifies the ways in which fitnesses depend on pragmatic choices made by researchers.
Total force fitness: the military family fitness model.
Bowles, Stephen V; Pollock, Liz Davenport; Moore, Monique; Wadsworth, Shelley MacDermid; Cato, Colanda; Dekle, Judith Ward; Meyer, Sonia Wei; Shriver, Amber; Mueller, Bill; Stephens, Mark; Seidler, Dustin A; Sheldon, Joseph; Picano, James; Finch, Wanda; Morales, Ricardo; Blochberger, Sean; Kleiman, Matthew E; Thompson, Daniel; Bates, Mark J
2015-03-01
The military lifestyle can create formidable challenges for military families. This article describes the Military Family Fitness Model (MFFM), a comprehensive model aimed at enhancing family fitness and resilience across the life span. This model is intended for use by Service members, their families, leaders, and health care providers but also has broader applications for all families. The MFFM has three core components: (1) family demands, (2) resources (including individual resources, family resources, and external resources), and (3) family outcomes (including related metrics). The MFFM proposes that resources from the individual, family, and external areas promote fitness, bolster resilience, and foster well-being for the family. The MFFM highlights each resource level for the purpose of improving family fitness and resilience over time. The MFFM both builds on existing family strengths and encourages the development of new family strengths through resource-acquiring behaviors. The purpose of this article is to (1) expand the military's Total Force Fitness (TFF) intent as it relates to families and (2) offer a family fitness model. This article will summarize relevant evidence, provide supportive theory, describe the model, and proffer metrics that support the dimensions of this model.
Integrated Model for E-Learning Acceptance
NASA Astrophysics Data System (ADS)
Ramadiani; Rodziah, A.; Hasan, S. M.; Rusli, A.; Noraini, C.
2016-01-01
E-learning is not going to work if the system is not used in accordance with user needs. User Interface is very important to encourage using the application. Many theories had discuss about user interface usability evaluation and technology acceptance separately, actually why we do not make it correlation between interface usability evaluation and user acceptance to enhance e-learning process. Therefore, the evaluation model for e-learning interface acceptance is considered important to investigate. The aim of this study is to propose the integrated e-learning user interface acceptance evaluation model. This model was combined some theories of e-learning interface measurement such as, user learning style, usability evaluation, and the user benefit. We formulated in constructive questionnaires which were shared at 125 English Language School (ELS) students. This research statistics used Structural Equation Model using LISREL v8.80 and MANOVA analysis.
Model of aircraft passenger acceptance
NASA Technical Reports Server (NTRS)
Jacobson, I. D.
1978-01-01
A technique developed to evaluate the passenger response to a transportation system environment is described. Reactions to motion, noise, temperature, seating, ventilation, sudden jolts and descents are modeled. Statistics are presented for the age, sex, occupation, and income distributions of the candidates analyzed. Values are noted for the relative importance of system variables such as time savings, on-time arrival, convenience, comfort, safety, the ability to read and write, and onboard services.
Coaches as Fitness Role Models
ERIC Educational Resources Information Center
Nichols, Randall; Zillifro, Traci D.; Nichols, Ronald; Hull, Ethan E.
2012-01-01
The lack of physical activity, low fitness levels, and elevated obesity rates as high as 32% of today's youth are well documented. Many strategies and grants have been developed at the national, regional, and local levels to help counteract these current trends. Strategies have been developed and implemented for schools, households (parents), and…
Sensitivity of Fit Indices to Model Misspecification and Model Types
ERIC Educational Resources Information Center
Fan, Xitao; Sivo, Stephen A.
2007-01-01
The search for cut-off criteria of fit indices for model fit evaluation (e.g., Hu & Bentler, 1999) assumes that these fit indices are sensitive to model misspecification, but not to different types of models. If fit indices were sensitive to different types of models that are misspecified to the same degree, it would be very difficult to establish…
Evaluation of Model Fit in Cognitive Diagnosis Models
ERIC Educational Resources Information Center
Hu, Jinxiang; Miller, M. David; Huggins-Manley, Anne Corinne; Chen, Yi-Hsin
2016-01-01
Cognitive diagnosis models (CDMs) estimate student ability profiles using latent attributes. Model fit to the data needs to be ascertained in order to determine whether inferences from CDMs are valid. This study investigated the usefulness of some popular model fit statistics to detect CDM fit including relative fit indices (AIC, BIC, and CAIC),…
Biomedical model fitting and error analysis.
Costa, Kevin D; Kleinstein, Steven H; Hershberg, Uri
2011-09-20
This Teaching Resource introduces students to curve fitting and error analysis; it is the second of two lectures on developing mathematical models of biomedical systems. The first focused on identifying, extracting, and converting required constants--such as kinetic rate constants--from experimental literature. To understand how such constants are determined from experimental data, this lecture introduces the principles and practice of fitting a mathematical model to a series of measurements. We emphasize using nonlinear models for fitting nonlinear data, avoiding problems associated with linearization schemes that can distort and misrepresent the data. To help ensure proper interpretation of model parameters estimated by inverse modeling, we describe a rigorous six-step process: (i) selecting an appropriate mathematical model; (ii) defining a "figure-of-merit" function that quantifies the error between the model and data; (iii) adjusting model parameters to get a "best fit" to the data; (iv) examining the "goodness of fit" to the data; (v) determining whether a much better fit is possible; and (vi) evaluating the accuracy of the best-fit parameter values. Implementation of the computational methods is based on MATLAB, with example programs provided that can be modified for particular applications. The problem set allows students to use these programs to develop practical experience with the inverse-modeling process in the context of determining the rates of cell proliferation and death for B lymphocytes using data from BrdU-labeling experiments.
Evaluating Model Fit for Growth Curve Models: Integration of Fit Indices from SEM and MLM Frameworks
ERIC Educational Resources Information Center
Wu, Wei; West, Stephen G.; Taylor, Aaron B.
2009-01-01
Evaluating overall model fit for growth curve models involves 3 challenging issues. (a) Three types of longitudinal data with different implications for model fit may be distinguished: balanced on time with complete data, balanced on time with data missing at random, and unbalanced on time. (b) Traditional work on fit from the structural equation…
Are Physical Education Majors Models for Fitness?
ERIC Educational Resources Information Center
Kamla, James; Snyder, Ben; Tanner, Lori; Wash, Pamela
2012-01-01
The National Association of Sport and Physical Education (NASPE) (2002) has taken a firm stance on the importance of adequate fitness levels of physical education teachers stating that they have the responsibility to model an active lifestyle and to promote fitness behaviors. Since the NASPE declaration, national initiatives like Let's Move…
Fitting Neuron Models to Spike Trains
Rossant, Cyrille; Goodman, Dan F. M.; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K.; Brette, Romain
2011-01-01
Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input–output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model. PMID:21415925
Acceptance criteria for urban dispersion model evaluation
NASA Astrophysics Data System (ADS)
Hanna, Steven; Chang, Joseph
2012-05-01
The authors suggested acceptance criteria for rural dispersion models' performance measures in this journal in 2004. The current paper suggests modified values of acceptance criteria for urban applications and tests them with tracer data from four urban field experiments. For the arc-maximum concentrations, the fractional bias should have a magnitude <0.67 (i.e., the relative mean bias is less than a factor of 2); the normalized mean-square error should be <6 (i.e., the random scatter is less than about 2.4 times the mean); and the fraction of predictions that are within a factor of two of the observations (FAC2) should be >0.3. For all data paired in space, for which a threshold concentration must always be defined, the normalized absolute difference should be <0.50, when the threshold is three times the instrument's limit of quantification (LOQ). An overall criterion is then applied that the total set of acceptance criteria should be satisfied in at least half of the field experiments. These acceptance criteria are applied to evaluations of the US Department of Defense's Joint Effects Model (JEM) with tracer data from US urban field experiments in Salt Lake City (U2000), Oklahoma City (JU2003), and Manhattan (MSG05 and MID05). JEM includes the SCIPUFF dispersion model with the urban canopy option and the urban dispersion model (UDM) option. In each set of evaluations, three or four likely options are tested for meteorological inputs (e.g., a local building top wind speed, the closest National Weather Service airport observations, or outputs from numerical weather prediction models). It is found that, due to large natural variability in the urban data, there is not a large difference between the performance measures for the two model options and the three or four meteorological input options. The more detailed UDM and the state-of-the-art numerical weather models do provide a slight improvement over the other options. The proposed urban dispersion model acceptance
Students' Models of Curve Fitting: A Models and Modeling Perspective
ERIC Educational Resources Information Center
Gupta, Shweta
2010-01-01
The Models and Modeling Perspectives (MMP) has evolved out of research that began 26 years ago. MMP researchers use Model Eliciting Activities (MEAs) to elicit students' mental models. In this study MMP was used as the conceptual framework to investigate the nature of students' models of curve fitting in a problem-solving environment consisting of…
Evolution in random fitness landscapes: the infinite sites model
NASA Astrophysics Data System (ADS)
Park, Su-Chan; Krug, Joachim
2008-04-01
We consider the evolution of an asexually reproducing population in an uncorrelated random fitness landscape in the limit of infinite genome size, which implies that each mutation generates a new fitness value drawn from a probability distribution g(w). This is the finite population version of Kingman's house of cards model (Kingman 1978 J. Appl. Probab. 15 1). In contrast to Kingman's work, the focus here is on unbounded distributions g(w) which lead to an indefinite growth of the population fitness. The model is solved analytically in the limit of infinite population size N \\to \\infty and simulated numerically for finite N. When the genome-wide mutation probability U is small, the long-time behavior of the model reduces to a point process of fixation events, which is referred to as a diluted record process (DRP). The DRP is similar to the standard record process except that a new record candidate (a number that exceeds all previous entries in the sequence) is accepted only with a certain probability that depends on the values of the current record and the candidate. We develop a systematic analytic approximation scheme for the DRP. At finite U the fitness frequency distribution of the population decomposes into a stationary part due to mutations and a traveling wave component due to selection, which is shown to imply a reduction of the mean fitness by a factor of 1-U compared to the U \\to 0 limit.
A Stepwise Fitting Procedure for automated fitting of Ecopath with Ecosim models
NASA Astrophysics Data System (ADS)
Scott, Erin; Serpetti, Natalia; Steenbeek, Jeroen; Heymans, Johanna Jacomina
The Stepwise Fitting Procedure automates testing of alternative hypotheses used for fitting Ecopath with Ecosim (EwE) models to observation reference data (Mackinson et al. 2009). The calibration of EwE model predictions to observed data is important to evaluate any model that will be used for ecosystem based management. Thus far, the model fitting procedure in EwE has been carried out manually: a repetitive task involving setting > 1000 specific individual searches to find the statistically 'best fit' model. The novel fitting procedure automates the manual procedure therefore producing accurate results and lets the modeller concentrate on investigating the 'best fit' model for ecological accuracy.
A predictive fitness model for influenza
NASA Astrophysics Data System (ADS)
Łuksza, Marta; Lässig, Michael
2014-03-01
The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.
A predictive fitness model for influenza.
Luksza, Marta; Lässig, Michael
2014-03-06
The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.
Fitting models to correlated data (large samples)
NASA Astrophysics Data System (ADS)
Féménias, Jean-Louis
2004-03-01
The study of the ordered series of residuals of a fit proved to be useful in evaluating separately the pure experimental error and the model bias leading to a possible improvement of the modeling [J. Mol. Spectrosc. 217 (2003) 32]. In the present work this procedure is extended to homogeneous correlated data. This new method allows a separate estimation of pure experimental error, model bias, and data correlation; furthermore, it brings a new insight into the difference between goodness of fit and model relevance. It can be considered either as a study of 'random systematic errors' or as an extended approach of the Durbin-Watson problem [Biometrika 37 (1950) 409] taking into account the model error. In the present work an empirical approach is proposed for large samples ( n⩾500) where numerical tests are done showing the accuracy and the limits of the method.
Modeling and Fitting Exoplanet Transit Light Curves
NASA Astrophysics Data System (ADS)
Millholland, Sarah; Ruch, G. T.
2013-01-01
We present a numerical model along with an original fitting routine for the analysis of transiting extra-solar planet light curves. Our light curve model is unique in several ways from other available transit models, such as the analytic eclipse formulae of Mandel & Agol (2002) and Giménez (2006), the modified Eclipsing Binary Orbit Program (EBOP) model implemented in Southworth’s JKTEBOP code (Popper & Etzel 1981; Southworth et al. 2004), or the transit model developed as a part of the EXOFAST fitting suite (Eastman et al. in prep.). Our model employs Keplerian orbital dynamics about the system’s center of mass to properly account for stellar wobble and orbital eccentricity, uses a unique analytic solution derived from Kepler’s Second Law to calculate the projected distance between the centers of the star and planet, and calculates the effect of limb darkening using a simple technique that is different from the commonly used eclipse formulae. We have also devised a unique Monte Carlo style optimization routine for fitting the light curve model to observed transits. We demonstrate that, while the effect of stellar wobble on transit light curves is generally small, it becomes significant as the planet to stellar mass ratio increases and the semi-major axes of the orbits decrease. We also illustrate the appreciable effects of orbital ellipticity on the light curve and the necessity of accounting for its impacts for accurate modeling. We show that our simple limb darkening calculations are as accurate as the analytic equations of Mandel & Agol (2002). Although our Monte Carlo fitting algorithm is not as mathematically rigorous as the Markov Chain Monte Carlo based algorithms most often used to determine exoplanetary system parameters, we show that it is straightforward and returns reliable results. Finally, we show that analyses performed with our model and optimization routine compare favorably with exoplanet characterizations published by groups such as the
Chinese Nurses' Acceptance of PDA: A Cross-Sectional Survey Using a Technology Acceptance Model.
Wang, Yanling; Xiao, Qian; Sun, Liu; Wu, Ying
2016-01-01
This study explores Chinese nurses' acceptance of PDA, using a questionnaire based on the framework of Technology Acceptance Model (TAM). 357 nurses were involved in the study. The results reveal the scores of the nurses' acceptance of PDA were means 3.18~3.36 in four dimensions. The younger of nurses, the higher nurses' title, the longer previous usage time, the more experienced using PDA, and the more acceptance of PDA. Therefore, the hospital administrators may change strategies to enhance nurses' acceptance of PDA, and promote the wide application of PDA.
ERIC Educational Resources Information Center
Kirmizi, Özkan
2014-01-01
The aim of this study is to investigate technology acceptance of prospective English teachers by using Technology Acceptance Model (TAM) in Turkish context. The study is based on Structural Equation Model (SEM). The participants of the study from English Language Teaching Departments of Hacettepe, Gazi and Baskent Universities. The participants…
A neutrino model fit to the CMB power spectrum
NASA Astrophysics Data System (ADS)
Shanks, T.; Johnson, R. W. F.; Schewtschenko, J. A.; Whitbourn, J. R.
2014-12-01
The standard cosmological model, Λ cold dark matter (ΛCDM), provides an excellent fit to cosmic microwave background (CMB) data. However, the model has well-known problems. For example, the cosmological constant, Λ, is fine-tuned to 1 part in 10100 and the CDM particle is not yet detected in the laboratory. Shanks previously investigated a model which assumed neither exotic particles nor a cosmological constant but instead postulated a low Hubble constant (H0) to allow a baryon density compatible with inflation and zero spatial curvature. However, recent Planck results make it more difficult to reconcile such a model with CMB power spectra. Here, we relax the previous assumptions to assess the effects of assuming three active neutrinos of mass ≈5 eV. If we assume a low H0 ≈ 45 km s-1 Mpc-1 then, compared to the previous purely baryonic model, we find a significantly improved fit to the first three peaks of the Planck power spectrum. Nevertheless, the goodness of fit is still significantly worse than for ΛCDM and would require appeal to unknown systematic effects for the fit ever to be considered acceptable. A further serious problem is that the amplitude of fluctuations is low (σ8 ≈ 0.2), making it difficult to form galaxies by the present day. This might then require seeds, perhaps from a primordial magnetic field, to be invoked for galaxy formation. These and other problems demonstrate the difficulties faced by models other than ΛCDM in fitting ever more precise cosmological data.
ERIC Educational Resources Information Center
Tarhini, Ali; Elyas, Tariq; Akour, Mohammad Ali; Al-Salti, Zahran
2016-01-01
The main aim of this paper is to develop an amalgamated conceptual model of technology acceptance that explains how individual, social, cultural and organizational factors affect the students' acceptance and usage behaviour of the Web-based learning systems. More specifically, the proposed model extends the Technology Acceptance Model (TAM) to…
Model-based estimation of individual fitness
Link, W.A.; Cooch, E.G.; Cam, E.
2002-01-01
Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes (Rissa tridactyla) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw and Caswell, 1996).
Model-based estimation of individual fitness
Link, W.A.; Cooch, E.G.; Cam, E.
2002-01-01
Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes (Rissa tridactyla ) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw & Caswell, 1996).
Assessing the fit of parametric cure models.
Wileyto, E Paul; Li, Yimei; Chen, Jinbo; Heitjan, Daniel F
2013-04-01
Survival data can contain an unknown fraction of subjects who are "cured" in the sense of not being at risk of failure. We describe such data with cure-mixture models, which separately model cure status and the hazard of failure among non-cured subjects. No diagnostic currently exists for evaluating the fit of such models; the popular Schoenfeld residual (Schoenfeld, 1982. Partial residuals for the proportional hazards regression-model. Biometrika 69, 239-241) is not applicable to data with cures. In this article, we propose a pseudo-residual, modeled on Schoenfeld's, to assess the fit of the survival regression in the non-cured fraction. Unlike Schoenfeld's approach, which tests the validity of the proportional hazards (PH) assumption, our method uses the full hazard and is thus also applicable to non-PH models. We derive the asymptotic distribution of the residuals and evaluate their performance by simulation in a range of parametric models. We apply our approach to data from a smoking cessation drug trial.
ERIC Educational Resources Information Center
Hayduk, Leslie
2014-01-01
Researchers using factor analysis tend to dismiss the significant ill fit of factor models by presuming that if their factor model is close-to-fitting, it is probably close to being properly causally specified. Close fit may indeed result from a model being close to properly causally specified, but close-fitting factor models can also be seriously…
An Investigation of Item Fit Statistics for Mixed IRT Models
ERIC Educational Resources Information Center
Chon, Kyong Hee
2009-01-01
The purpose of this study was to investigate procedures for assessing model fit of IRT models for mixed format data. In this study, various IRT model combinations were fitted to data containing both dichotomous and polytomous item responses, and the suitability of the chosen model mixtures was evaluated based on a number of model fit procedures.…
An Investigation of Goodness of Model Data Fit
ERIC Educational Resources Information Center
Onder, Ismail
2007-01-01
IRT models' advantages can only be realized when the model fits the data set of interest. Therefore, this study aimed to investigate which IRT model will provide the best fit to the data obtained from OZDEBYR OSS 2004 D-II Exam Science Test. In goodness-of-fit analysis, first the model assumptions and then the expected model features were checked.…
76 FR 49751 - Perfect Fitness, Provisional Acceptance of a Settlement Agreement and Order
Federal Register 2010, 2011, 2012, 2013, 2014
2011-08-11
... Product Safety Commission. ACTION: Notice. SUMMARY: It is the policy of the Commission to publish settlements which it provisionally accepts under the Consumer Product Safety Act in the Federal Register in... death, and denies that it knowingly violated the reporting requirements of Section 15(b) of the CPSA,...
49 CFR 41.120 - Acceptable model codes.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 49 Transportation 1 2010-10-01 2010-10-01 false Acceptable model codes. 41.120 Section 41.120 Transportation Office of the Secretary of Transportation SEISMIC SAFETY § 41.120 Acceptable model codes. (a) This... of this part. (b)(1) The following are model codes which have been found to provide a level...
Chen, Ke; Chan, Alan Hoi Shou
2014-01-01
The purpose of this study was to develop and test a senior technology acceptance model (STAM) aimed at understanding the acceptance of gerontechnology by older Hong Kong Chinese people. The proposed STAM extended previous technology acceptance models and theories by adding age-related health and ability characteristics of older people. The proposed STAM was empirically tested using a cross-sectional questionnaire survey with a sample of 1012 seniors aged 55 and over in Hong Kong. The result showed that STAM was strongly supported and could explain 68% of the variance in the use of gerontechnology. For older Hong Kong Chinese, individual attributes, which include age, gender, education, gerontechnology self-efficacy and anxiety, and health and ability characteristics, as well as facilitating conditions explicitly and directly affected technology acceptance. These were better predictors of gerontechnology usage behaviour (UB) than the conventionally used attitudinal factors (usefulness and ease of use).
Modeling eBook acceptance: A study on mathematics teachers
NASA Astrophysics Data System (ADS)
Jalal, Azlin Abd; Ayub, Ahmad Fauzi Mohd; Tarmizi, Rohani Ahmad
2014-12-01
The integration and effectiveness of eBook utilization in Mathematics teaching and learning greatly relied upon the teachers, hence the need to understand their perceptions and beliefs. The eBook, an individual laptop completed with digitized textbook sofwares, were provided for each students in line with the concept of 1 student:1 laptop. This study focuses on predicting a model on the acceptance of the eBook among Mathematics teachers. Data was collected from 304 mathematics teachers in selected schools using a survey questionnaire. The selection were based on the proportionate stratified sampling. Structural Equation Modeling (SEM) were employed where the model was tested and evaluated and was found to have a good fit. The variance explained for the teachers' attitude towards eBook is approximately 69.1% where perceived usefulness appeared to be a stronger determinant compared to perceived ease of use. This study concluded that the attitude of mathematics teachers towards eBook depends largely on the perception of how useful the eBook is on improving their teaching performance, implying that teachers should be kept updated with the latest mathematical application and sofwares to use with the eBook to ensure positive attitude towards using it in class.
Lawson, Karen L; Bayly, Melanie; Cey, Emma
2013-01-01
This study examines the societal perceptions and judgements made towards HIV-positive pregnant women when compared with those targeting pregnant women with other medical conditions. One hundred and sixty participants (124 female) were randomly assigned to one of four experimental conditions defined by specific medical condition of the pregnant woman in the vignette (HIV/AIDS, obesity, lung cancer or diabetes). Participants were asked to respond to a variety of items gauging their reaction to the woman and her pregnancy subsequent to reading the scenario. As expected, participants were least approving of the pregnancy of the woman with HIV/AIDS, and they rated her as a less fit parent than the women with the other medical conditions. Subsequent analyses revealed that concern for the health of the child and attributions of responsibility/blame for the medical condition did not account for the differential reactions to the pregnant woman with HIV/AIDS. These findings corroborate the felt stigma and prejudicial attitudes reported by HIV-positive mothers.
ERIC Educational Resources Information Center
Yousif, Wael K.
2010-01-01
This causal and correlational study was designed to extend the Technology Acceptance Model (TAM) and to test its applicability to Valencia Community College (VCC) Engineering and Technology students as the target user group when investigating the factors influencing their decision to adopt and to utilize VMware as the target technology. In…
User Acceptance of YouTube for Procedural Learning: An Extension of the Technology Acceptance Model
ERIC Educational Resources Information Center
Lee, Doo Young; Lehto, Mark R.
2013-01-01
The present study was framed using the Technology Acceptance Model (TAM) to identify determinants affecting behavioral intention to use YouTube. Most importantly, this research emphasizes the motives for using YouTube, which is notable given its extrinsic task goal of being used for procedural learning tasks. Our conceptual framework included two…
ERIC Educational Resources Information Center
Park, Eunil; Kim, Ki Joon
2013-01-01
Purpose: The aim of this paper is to propose an integrated path model in order to explore user acceptance of long-term evolution (LTE) services by examining potential causal relationships between key psychological factors and user intention to use the services. Design/methodology/approach: Online survey data collected from 1,344 users are analysed…
ERIC Educational Resources Information Center
Pritchard, Tony; Hansen, Andrew; Scarboro, Shot; Melnic, Irina
2015-01-01
The purpose of this study was to investigate changes in fitness levels, content knowledge, physical activity levels, and participants' perceptions following the implementation of the sport education fitness model (SEFM) at a high school. Thirty-two high school students participated in 20 lessons using the SEFM. Aerobic capacity, muscular…
Blanquart, François; Bataillon, Thomas
2016-06-01
The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher's model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher's model was able to explain several statistical properties of the landscapes-including the mean and SD of selection and epistasis coefficients-it was often unable to explain the full structure of fitness landscapes.
Hyper-Fit: Fitting Linear Models to Multidimensional Data with Multivariate Gaussian Uncertainties
NASA Astrophysics Data System (ADS)
Robotham, A. S. G.; Obreschkow, D.
2015-09-01
Astronomical data is often uncertain with errors that are heteroscedastic (different for each data point) and covariant between different dimensions. Assuming that a set of D-dimensional data points can be described by a (D - 1)-dimensional plane with intrinsic scatter, we derive the general likelihood function to be maximised to recover the best fitting model. Alongside the mathematical description, we also release the hyper-fit package for the R statistical language (http://github.com/asgr/hyper.fit) and a user-friendly web interface for online fitting (http://hyperfit.icrar.org). The hyper-fit package offers access to a large number of fitting routines, includes visualisation tools, and is fully documented in an extensive user manual. Most of the hyper-fit functionality is accessible via the web interface. In this paper, we include applications to toy examples and to real astronomical data from the literature: the mass-size, Tully-Fisher, Fundamental Plane, and mass-spin-morphology relations. In most cases, the hyper-fit solutions are in good agreement with published values, but uncover more information regarding the fitted model.
Test of the technology acceptance model for the internet in pediatrics.
Chismar, William G.; Wiley-Patton, Sonja
2002-01-01
There is growing recognition of the importance of the Internet and, more generally, information technology to pediatric care. However, acceptance of these technologies has been low. Attitudes of physicians can play a pivotal role in the adoption session. This study tests the extension to a widely used model in the information systems literature: the Technology Acceptance Model (TAM). Data were collected in a survey of pediatricians to see how well the extended model, TAM2, fits in the medical arena. Our results partially confirm the model; significant parts of the model were not confirmed. The primary factors in pediatricians' acceptance of technology applications relate to their usefulness and job relevance. Little weight is given to ease of use and social factors. We discuss possible explanations for the discrepancies and suggest future research. PMID:12463806
Test of the technology acceptance model for the internet in pediatrics.
Chismar, William G; Wiley-Patton, Sonja
2002-01-01
There is growing recognition of the importance of the Internet and, more generally, information technology to pediatric care. However, acceptance of these technologies has been low. Attitudes of physicians can play a pivotal role in the adoption session. This study tests the extension to a widely used model in the information systems literature: the Technology Acceptance Model (TAM). Data were collected in a survey of pediatricians to see how well the extended model, TAM2, fits in the medical arena. Our results partially confirm the model; significant parts of the model were not confirmed. The primary factors in pediatricians' acceptance of technology applications relate to their usefulness and job relevance. Little weight is given to ease of use and social factors. We discuss possible explanations for the discrepancies and suggest future research.
Curve fitting methods for solar radiation data modeling
Karim, Samsul Ariffin Abdul E-mail: balbir@petronas.com.my; Singh, Balbir Singh Mahinder E-mail: balbir@petronas.com.my
2014-10-24
This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R{sup 2}. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.
The FIT Model - Fuel-cycle Integration and Tradeoffs
Steven J. Piet; Nick R. Soelberg; Samuel E. Bays; Candido Pereira; Layne F. Pincock; Eric L. Shaber; Meliisa C Teague; Gregory M Teske; Kurt G Vedros
2010-09-01
All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010] are an initial step by the FCR&D program toward a global analysis that accounts for the requirements and capabilities of each component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. The question originally posed to the “system losses study” was the cost of separation, fuel fabrication, waste management, etc. versus the separation efficiency. In other words, are the costs associated with marginal reductions in separations losses (or improvements in product recovery) justified by the gains in the performance of other systems? We have learned that that is the wrong question. The right question is: how does one adjust the compositions and quantities of all mass streams, given uncertain product criteria, to balance competing objectives including cost? FIT is a method to analyze different fuel cycles using common bases to determine how chemical performance changes in one part of a fuel cycle (say used fuel cooling times or separation efficiencies) affect other parts of the fuel cycle. FIT estimates impurities in fuel and waste via a rough estimate of physics and mass balance for a set of technologies. If feasibility is an issue for a set, as it is for “minimum fuel treatment” approaches such as melt refining and AIROX, it can help to make an estimate of how performances would have to change to achieve feasibility.
Goodness of Model-Data Fit and Invariant Measurement
ERIC Educational Resources Information Center
Engelhard, George, Jr.; Perkins, Aminah
2013-01-01
In this commentary, Englehard and Perkins remark that Maydeu-Olivares has presented a framework for evaluating the goodness of model-data fit for item response theory (IRT) models and correctly points out that overall goodness-of-fit evaluations of IRT models and data are not generally explored within most applications in educational and…
A Comparison of Item Fit Statistics for Mixed IRT Models
ERIC Educational Resources Information Center
Chon, Kyong Hee; Lee, Won-Chan; Dunbar, Stephen B.
2010-01-01
In this study we examined procedures for assessing model-data fit of item response theory (IRT) models for mixed format data. The model fit indices used in this study include PARSCALE's G[superscript 2], Orlando and Thissen's S-X[superscript 2] and S-G[superscript 2], and Stone's chi[superscript 2*] and G[superscript 2*]. To investigate the…
Power, sex, and rape myth acceptance: testing two models of rape proclivity.
Chapleau, Kristine M; Oswald, Debra L
2010-01-01
Power and sex are thought to be important factors associated with sexual aggression. The goal of this study was to offer a dual-process model to determine how both an implicit power-sex association and explicit power-sex beliefs contribute to rape myth acceptance and rape proclivity. In Study 1, an explicit measure of power-sex beliefs was developed using a participant sample of 131 college students (54% female; age: M = 20.2 years, SD = 3.5 years). In Study 2, 108 male college students (age: M = 19.1 years, SD = 1.3 years) completed a power-sex implicit association test and three explicit measures assessing power-sex beliefs, rape myth acceptance, and rape proclivity. Two models of rape proclivity were compared. The best-fitting model showed that rape myth acceptance mediated the relationships between rape proclivity and an implicit power-sex association, as well as explicit power-sex beliefs.
Development and application of an acceptance testing model
NASA Technical Reports Server (NTRS)
Pendley, Rex D.; Noonan, Caroline H.; Hall, Kenneth R.
1992-01-01
The process of acceptance testing large software systems for NASA has been analyzed, and an empirical planning model of the process constructed. This model gives managers accurate predictions of the staffing needed, the productivity of a test team, and the rate at which the system will pass. Applying the model to a new system shows a high level of agreement between the model and actual performance. The model also gives managers an objective measure of process improvement.
Resampling methods for model fitting and model selection.
Babu, G Jogesh
2011-11-01
Resampling procedures for fitting models and model selection are considered in this article. Nonparametric goodness-of-fit statistics are generally based on the empirical distribution function. The distribution-free property of these statistics does not hold in the multivariate case or when some of the parameters are estimated. Bootstrap methods to estimate the underlying distributions are discussed in such cases. The results hold not only in the case of one-dimensional parameter space, but also for the vector parameters. Bootstrap methods for inference, when the data is from an unknown distribution that may or may not belong to a specified family of distributions, are also considered. Most of the information criteria-based model selection procedures such as the Akaike information criterion, Bayesian information criterion, and minimum description length use estimation of bias. The bias, which is inevitable in model selection problems, arises mainly from estimating the distance between the "true" model and an estimated model. A jackknife type procedure for model selection is discussed, which instead of bias estimation is based on bias reduction.
A Causal Model of Teacher Acceptance of Technology
ERIC Educational Resources Information Center
Chang, Jui-Ling; Lieu, Pang-Tien; Liang, Jung-Hui; Liu, Hsiang-Te; Wong, Seng-lee
2012-01-01
This study proposes a causal model for investigating teacher acceptance of technology. We received 258 effective replies from teachers at public and private universities in Taiwan. A questionnaire survey was utilized to test the proposed model. The Lisrel was applied to test the proposed hypotheses. The result shows that computer self-efficacy has…
An, Ji-Young
2006-01-01
The purpose of this web-based study was to explain and predict consumers' acceptance and usage behavior of Internet health information and services. Toward this goal, the Information and Communication Technology Acceptance Model (ICTAM) was developed and tested. Individuals who received a flyer through the LISTSERV of HealthGuide were eligible to participate. The study population was eighteen years old and older who had used Internet health information and services for a minimum of 6 months. For the analyses, SPSS (version 13.0) and AMOS (version 5.0) were employed. More than half of the respondents were women (n = 110, 55%). The average age of the respondents was 35.16 years (S.D. = 10.07). A majority reported at least some college education (n = 126, 63%). All of the observed factors accounted for 75.53% of the total variance explained. The fit indices of the structural model were within an acceptable range: chi2/df = 2.38 (chi2 = 1786.31, df = 752); GFI = .71; RMSEA = .08; CFI = .86; NFI = .78. The results of this study provide empirical support for the continued development of ICTAM in the area of health consumers' information and communication technology acceptance.
HDFITS: Porting the FITS data model to HDF5
NASA Astrophysics Data System (ADS)
Price, D. C.; Barsdell, B. R.; Greenhill, L. J.
2015-09-01
The FITS (Flexible Image Transport System) data format has been the de facto data format for astronomy-related data products since its inception in the late 1970s. While the FITS file format is widely supported, it lacks many of the features of more modern data serialization, such as the Hierarchical Data Format (HDF5). The HDF5 file format offers considerable advantages over FITS, such as improved I/O speed and compression, but has yet to gain widespread adoption within astronomy. One of the major holdbacks is that HDF5 is not well supported by data reduction software packages and image viewers. Here, we present a comparison of FITS and HDF5 as a format for storage of astronomy datasets. We show that the underlying data model of FITS can be ported to HDF5 in a straightforward manner, and that by doing so the advantages of the HDF5 file format can be leveraged immediately. In addition, we present a software tool, fits2hdf, for converting between FITS and a new 'HDFITS' format, where data are stored in HDF5 in a FITS-like manner. We show that HDFITS allows faster reading of data (up to 100x of FITS in some use cases), and improved compression (higher compression ratios and higher throughput). Finally, we show that by only changing the import lines in Python-based FITS utilities, HDFITS formatted data can be presented transparently as an in-memory FITS equivalent.
Consequences of Fitting Nonidentified Latent Class Models
ERIC Educational Resources Information Center
Abar, Beau; Loken, Eric
2012-01-01
Latent class models are becoming more popular in behavioral research. When models with a large number of latent classes relative to the number of manifest indicators are estimated, researchers must consider the possibility that the model is not identified. It is not enough to determine that the model has positive degrees of freedom. A well-known…
Evaluating Item Fit for Multidimensional Item Response Models
ERIC Educational Resources Information Center
Zhang, Bo; Stone, Clement A.
2008-01-01
This research examines the utility of the s-x[superscript 2] statistic proposed by Orlando and Thissen (2000) in evaluating item fit for multidimensional item response models. Monte Carlo simulation was conducted to investigate both the Type I error and statistical power of this fit statistic in analyzing two kinds of multidimensional test…
Assessing Fit of Unidimensional Graded Response Models Using Bayesian Methods
ERIC Educational Resources Information Center
Zhu, Xiaowen; Stone, Clement A.
2011-01-01
The posterior predictive model checking method is a flexible Bayesian model-checking tool and has recently been used to assess fit of dichotomous IRT models. This paper extended previous research to polytomous IRT models. A simulation study was conducted to explore the performance of posterior predictive model checking in evaluating different…
Basak, Ecem; Gumussoy, Cigdem Altin; Calisir, Fethi
2015-01-01
This study aims at identifying the factors affecting the intention to use personal digital assistant (PDA) technology among physicians in Turkey using an extended Technology Acceptance Model (TAM). A structural equation-modeling approach was used to identify the variables that significantly affect the intention to use PDA technology. The data were collected from 339 physicians in Turkey. Results indicated that 71% of the physicians' intention to use PDA technology is explained by perceived usefulness and perceived ease of use. On comparing both, the perceived ease of use has the strongest effect, whereas the effect of perceived enjoyment on behavioral intention to use is found to be insignificant. This study concludes with the recommendations for managers and possible future research.
49 CFR 41.120 - Acceptable model codes.
Code of Federal Regulations, 2011 CFR
2011-10-01
... Transportation Office of the Secretary of Transportation SEISMIC SAFETY § 41.120 Acceptable model codes. (a) This section describes the standards that must be used to meet the seismic design and construction requirements... seismic safety substantially equivalent to that provided by use of the 1988 National Earthquake...
49 CFR 41.120 - Acceptable model codes.
Code of Federal Regulations, 2014 CFR
2014-10-01
... Transportation Office of the Secretary of Transportation SEISMIC SAFETY § 41.120 Acceptable model codes. (a) This section describes the standards that must be used to meet the seismic design and construction requirements... seismic safety substantially equivalent to that provided by use of the 1988 National Earthquake...
49 CFR 41.120 - Acceptable model codes.
Code of Federal Regulations, 2012 CFR
2012-10-01
... Transportation Office of the Secretary of Transportation SEISMIC SAFETY § 41.120 Acceptable model codes. (a) This section describes the standards that must be used to meet the seismic design and construction requirements... seismic safety substantially equivalent to that provided by use of the 1988 National Earthquake...
ERIC Educational Resources Information Center
Cheung, Ronnie; Vogel, Doug
2013-01-01
Collaborative technologies support group work in project-based environments. In this study, we enhance the technology acceptance model to explain the factors that influence the acceptance of Google Applications for collaborative learning. The enhanced model was empirically evaluated using survey data collected from 136 students enrolled in a…
Ketikidis, Panayiotis; Dimitrovski, Tomislav; Lazuras, Lambros; Bath, Peter A
2012-06-01
The response of health professionals to the use of health information technology (HIT) is an important research topic that can partly explain the success or failure of any HIT application. The present study applied a modified version of the revised technology acceptance model (TAM) to assess the relevant beliefs and acceptance of HIT systems in a sample of health professionals (n = 133). Structured anonymous questionnaires were used and a cross-sectional design was employed. The main outcome measure was the intention to use HIT systems. ANOVA was employed to examine differences in TAM-related variables between nurses and medical doctors, and no significant differences were found. Multiple linear regression analysis was used to assess the predictors of HIT usage intentions. The findings showed that perceived ease of use, but not usefulness, relevance and subjective norms directly predicted HIT usage intentions. The present findings suggest that a modification of the original TAM approach is needed to better understand health professionals' support and endorsement of HIT. Perceived ease of use, relevance of HIT to the medical and nursing professions, as well as social influences, should be tapped by information campaigns aiming to enhance support for HIT in healthcare settings.
Dynamic model for simulating the acceptance problem of nuclear energy
Seifritz, W.; Mennig, J.
1987-01-01
Nonlinear dynamics are attaining greater interest in different fields of application. Since the early 1980s, these methods have been applied intensively to a variety of very different general problems, such as the description of political and economic processes as well as the symbiotic behavior in the flora and fauna. The authors have tried to apply these mathematical methods to the dynamic behavior inherent in the problem of the acceptance of nuclear energy. The model, which simplifies the real situation, is two-dimensional and describes the symbiosis of two individuals: the capacity of nuclear power plants P and their acceptance A by the public. It is clear that in reality the acceptance problem depends on a series of other variables as well. However, it is believed that our investigations reveal some universal properties inherent to our socioeconomic system: nonlinearity and dissipative processes.
How Good Are Statistical Models at Approximating Complex Fitness Landscapes?
du Plessis, Louis; Leventhal, Gabriel E; Bonhoeffer, Sebastian
2016-09-01
Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations.
MAPCLUS: A Mathematical Programming Approach to Fitting the ADCLUS Model.
ERIC Educational Resources Information Center
Arabie, Phipps
1980-01-01
A new computing algorithm, MAPCLUS (Mathematical Programming Clustering), for fitting the Shephard-Arabie ADCLUS (Additive Clustering) model is presented. Details and benefits of the algorithm are discussed. (Author/JKS)
Fitting population models from field data
Emlen, J.M.; Freeman, D.C.; Kirchhoff, M.D.; Alados, C.L.; Escos, J.; Duda, J.J.
2003-01-01
The application of population and community ecology to solving real-world problems requires population and community dynamics models that reflect the myriad patterns of interaction among organisms and between the biotic and physical environments. Appropriate models are not hard to construct, but the experimental manipulations needed to evaluate their defining coefficients are often both time consuming and costly, and sometimes environmentally destructive, as well. In this paper we present an empirical approach for finding the coefficients of broadly inclusive models without the need for environmental manipulation, demonstrate the approach with both an animal and a plant example, and suggest possible applications. Software has been developed, and is available from the senior author, with a manual describing both field and analytic procedures.
Vowles, Kevin E; Sowden, Gail; Ashworth, Julie
2014-05-01
The therapeutic model underlying Acceptance and Commitment Therapy (ACT) is reasonably well-established as it applies to chronic pain. Several studies have examined measures of single ACT processes, or subsets of processes, and have almost uniformly indicated reliable relations with patient functioning. To date, however, no study has performed a comprehensive examination of the entire ACT model, including all of its component processes, as it relates to functioning. The present study performed this examination in 274 individuals with chronic pain presenting for an assessment appointment. Participants completed a battery of self-report questionnaires, assessing multiple aspects of the ACT model, as well as pain intensity, disability, and emotional distress. Initial exploratory factor analyses examined measures of the ACT model and measures of patient functioning separately with each analysis identifying three factors. Next, the fit of a model including ACT processes on the one hand and patient functioning on the other was examined using Structural Equation Modeling. Overall model fit was acceptable and indicated moderate correlations among the ACT processes themselves, as well as significant relations with pain intensity, emotional distress, and disability. These analyses build on the existing literature by providing, to our knowledge, the most comprehensive evaluation of the ACT theoretical model in chronic pain to date.
Relative and Absolute Fit Evaluation in Cognitive Diagnosis Modeling
ERIC Educational Resources Information Center
Chen, Jinsong; de la Torre, Jimmy; Zhang, Zao
2013-01-01
As with any psychometric models, the validity of inferences from cognitive diagnosis models (CDMs) determines the extent to which these models can be useful. For inferences from CDMs to be valid, it is crucial that the fit of the model to the data is ascertained. Based on a simulation study, this study investigated the sensitivity of various fit…
The technology acceptance model: predicting nurses' intention to use telemedicine technology (eICU).
Kowitlawakul, Yanika
2011-07-01
The purposes of this study were to determine factors and predictors that influence nurses' intention to use the eICU technology, to examine the applicability of the Technology Acceptance Model in explaining nurses' intention to use the eICU technology in healthcare settings, and to provide psychometric evidence of the measurement scales used in the study. The study involved 117 participants from two healthcare systems. The Telemedicine Technology Acceptance Model was developed based on the original Technology Acceptance Model that was initially developed by Fred Davis in 1986. The eICU Acceptance Survey was used as an instrument for the study. Content validity was examined, and the reliability of the instrument was tested. The results show that perceived usefulness is the most influential factor that influences nurses' intention to use the eICU technology. The principal factors that influence perceived usefulness are perceived ease of use, support from physicians, and years working in the hospital. The model fit was reasonably adequate and able to explain 58% of the variance (R = 0.58) in intention to use the eICU technology with the nursing sample.
Assessing the goodness of fit of personal risk models.
Gong, Gail; Quante, Anne S; Terry, Mary Beth; Whittemore, Alice S
2014-08-15
We describe a flexible family of tests for evaluating the goodness of fit (calibration) of a pre-specified personal risk model to the outcomes observed in a longitudinal cohort. Such evaluation involves using the risk model to assign each subject an absolute risk of developing the outcome within a given time from cohort entry and comparing subjects' assigned risks with their observed outcomes. This comparison involves several issues. For example, subjects followed only for part of the risk period have unknown outcomes. Moreover, existing tests do not reveal the reasons for poor model fit when it occurs, which can reflect misspecification of the model's hazards for the competing risks of outcome development and death. To address these issues, we extend the model-specified hazards for outcome and death, and use score statistics to test the null hypothesis that the extensions are unnecessary. Simulated cohort data applied to risk models whose outcome and mortality hazards agreed and disagreed with those generating the data show that the tests are sensitive to poor model fit, provide insight into the reasons for poor fit, and accommodate a wide range of model misspecification. We illustrate the methods by examining the calibration of two breast cancer risk models as applied to a cohort of participants in the Breast Cancer Family Registry. The methods can be implemented using the Risk Model Assessment Program, an R package freely available at http://stanford.edu/~ggong/rmap/.
Modeling of the charge acceptance of lead-acid batteries
NASA Astrophysics Data System (ADS)
Thele, M.; Schiffer, J.; Karden, E.; Surewaard, E.; Sauer, D. U.
This paper presents a model for flooded and VRLA batteries that is parameterized by impedance spectroscopy and includes the overcharging effects to allow charge-acceptance simulations (e.g. for regenerative-braking drive-cycle profiles). The full dynamic behavior and the short-term charge/discharge history is taken into account. This is achieved by a detailed modeling of the sulfate crystal growth and modeling of the internal gas recombination cycle. The model is applicable in the full realistic temperature and current range of automotive applications. For model validation, several load profiles (covering the dynamics and the current range appearing in electrically assisted or hybrid cars) are examined and the charge-acceptance limiting effects are elaborately discussed. The validation measurements have been performed for different types of lead-acid batteries (flooded and VRLA). The model is therefore an important tool for the development of automotive power nets, but it also allows to analyze different charging strategies and energy gains which can be achieved during regenerative-braking.
Eigen model with general fitness functions and degradation rates
NASA Astrophysics Data System (ADS)
Hu, Chin-Kun; Saakian, David B.
2006-03-01
We present an exact solution of Eigen's quasispecies model with a general degradation rate and fitness functions, including a square root decrease of fitness with increasing Hamming distance from the wild type. The found behavior of the model with a degradation rate is analogous to a viral quasi-species under attack by the immune system of the host. Our exact solutions also revise the known results of neutral networks in quasispecies theory. To explain the existence of mutants with large Hamming distances from the wild type, we propose three different modifications of the Eigen model: mutation landscape, multiple adjacent mutations, and frequency-dependent fitness in which the steady state solution shows a multi-center behavior.
Fitting milk production curves through nonlinear mixed models.
Piccardi, Monica; Macchiavelli, Raúl; Funes, Ariel Capitaine; Bó, Gabriel A; Balzarini, Mónica
2017-03-28
The aim of this work was to fit and compare three non-linear models (Wood, Milkbot and diphasic) to model lactation curves from two approaches: with and without cow random effect. Knowing the behaviour of lactation curves is critical for decision-making in a dairy farm. Knowledge of the model of milk production progress along each lactation is necessary not only at the mean population level (dairy farm), but also at individual level (cow-lactation). The fits were made in a group of high production and reproduction dairy farms; in first and third lactations in cool seasons. A total of 2167 complete lactations were involved, of which 984 were first-lactations and the remaining ones, third lactations (19 382 milk yield tests). PROC NLMIXED in SAS was used to make the fits and estimate the model parameters. The diphasic model resulted to be computationally complex and barely practical. Regarding the classical Wood and MilkBot models, although the information criteria suggest the selection of MilkBot, the differences in the estimation of production indicators did not show a significant improvement. The Wood model was found to be a good option for fitting the expected value of lactation curves. Furthermore, the three models fitted better when the subject (cow) random effect was considered, which is related to magnitude of production. The random effect improved the predictive potential of the models, but it did not have a significant effect on the production indicators derived from the lactation curves, such as milk yield and days in milk to peak.
ERIC Educational Resources Information Center
Fan, Xitao; Wang, Lin; Thompson, Bruce
1999-01-01
A Monte Carlo simulation study investigated the effects on 10 structural equation modeling fit indexes of sample size, estimation method, and model specification. Some fit indexes did not appear to be comparable, and it was apparent that estimation method strongly influenced almost all fit indexes examined, especially for misspecified models. (SLD)
Time-domain fitting of battery electrochemical impedance models
NASA Astrophysics Data System (ADS)
Alavi, S. M. M.; Birkl, C. R.; Howey, D. A.
2015-08-01
Electrochemical impedance spectroscopy (EIS) is an effective technique for diagnosing the behaviour of electrochemical devices such as batteries and fuel cells, usually by fitting data to an equivalent circuit model (ECM). The common approach in the laboratory is to measure the impedance spectrum of a cell in the frequency domain using a single sine sweep signal, then fit the ECM parameters in the frequency domain. This paper focuses instead on estimation of the ECM parameters directly from time-domain data. This may be advantageous for parameter estimation in practical applications such as automotive systems including battery-powered vehicles, where the data may be heavily corrupted by noise. The proposed methodology is based on the simplified refined instrumental variable for continuous-time fractional systems method ('srivcf'), provided by the Crone toolbox [1,2], combined with gradient-based optimisation to estimate the order of the fractional term in the ECM. The approach was tested first on synthetic data and then on real data measured from a 26650 lithium-ion iron phosphate cell with low-cost equipment. The resulting Nyquist plots from the time-domain fitted models match the impedance spectrum closely (much more accurately than when a Randles model is assumed), and the fitted parameters as separately determined through a laboratory potentiostat with frequency domain fitting match to within 13%.
Genome-Wide Heterogeneity of Nucleotide Substitution Model Fit
Arbiza, Leonardo; Patricio, Mateus; Dopazo, Hernán; Posada, David
2011-01-01
At a genomic scale, the patterns that have shaped molecular evolution are believed to be largely heterogeneous. Consequently, comparative analyses should use appropriate probabilistic substitution models that capture the main features under which different genomic regions have evolved. While efforts have concentrated in the development and understanding of model selection techniques, no descriptions of overall relative substitution model fit at the genome level have been reported. Here, we provide a characterization of best-fit substitution models across three genomic data sets including coding regions from mammals, vertebrates, and Drosophila (24,000 alignments). According to the Akaike Information Criterion (AIC), 82 of 88 models considered were selected as best-fit models at least in one occasion, although with very different frequencies. Most parameter estimates also varied broadly among genes. Patterns found for vertebrates and Drosophila were quite similar and often more complex than those found in mammals. Phylogenetic trees derived from models in the 95% confidence interval set showed much less variance and were significantly closer to the tree estimated under the best-fit model than trees derived from models outside this interval. Although alternative criteria selected simpler models than the AIC, they suggested similar patterns. All together our results show that at a genomic scale, different gene alignments for the same set of taxa are best explained by a large variety of different substitution models and that model choice has implications on different parameter estimates including the inferred phylogenetic trees. After taking into account the differences related to sample size, our results suggest a noticeable diversity in the underlying evolutionary process. All together, we conclude that the use of model selection techniques is important to obtain consistent phylogenetic estimates from real data at a genomic scale. PMID:21824869
Can a first-order exponential decay model fit heart rate recovery after resistance exercise?
Bartels-Ferreira, Rhenan; de Sousa, Élder D; Trevizani, Gabriela A; Silva, Lilian P; Nakamura, Fábio Y; Forjaz, Cláudia L M; Lima, Jorge Roberto P; Peçanha, Tiago
2015-03-01
The time-constant of postexercise heart rate recovery (HRRτ ) obtained by fitting heart rate decay curve by a first-order exponential fitting has being used to assess cardiac autonomic recovery after endurance exercise. The feasibility of this model was not tested after resistance exercise (RE). The aim of this study was to test the goodness of fit of the first-order exponential decay model to fit heart rate recovery (HRR) after RE. Ten healthy subjects participated in the study. The experimental sessions occurred in two separated days and consisted of performance of 1 set of 10 repetitions at 50% or 80% of the load achieved on the one-repetition maximum test [low-intensity (LI) and high-intensity (HI) sessions, respectively]. Heart rate (HR) was continuously registered before and during exercise and also for 10 min of recovery. A monoexponential equation was used to fit the HRR curve during the postexercise period using different time windows (i.e. 30, 60, 90, … 600 s). For each time window, (i) HRRτ was calculated and (ii) variation of HR explained by the model (R(2) goodness of fit index) was assessed. The HRRτ showed stabilization from 360 and 420 s on LI and HI, respectively. Acceptable R(2) values were observed from the 360 s on LI (R(2) > 0.65) and at all tested time windows on HI (R(2) > 0.75). In conclusion, this study showed that using a minimum length of monitoring (~420 s) HRR after RE can be adequately modelled by a first-order exponential fitting.
Stop search with acceptable fine-tuning in Susy models
NASA Astrophysics Data System (ADS)
Ćiçi, Ali; Ün, Cem Salih; Kirca, Zerrin
2017-02-01
Supersymmetry (SUSY) is one of the forefront candidates for the models beyond the Standard Model (SM) in resolving the gauge hierarchy problem by proposing new supersymmetric partners for the SM fields. In SUSY, stop, the supersymmetric partner of top quark, is of a special importance, since it cancels the largest quadratic contributions to the Higgs boson mass from top quark loop. Despite heavy stop mass requirement from the Higgs boson searches and fine-tuning demands, it is still possible to find stops of mass about a few hundred GeV, even as light as top quark. In this study, we search for light stop solutions within the SUSY Grand Unified Theory (GUT) models in light of acceptable fine-tuning and current experimental constraints. Afterwards, we analyze the possible signals through which the implications can be tested at the Large Hadron Collider (LHC) experiments.
The FIT 2.0 Model - Fuel-cycle Integration and Tradeoffs
Steven J. Piet; Nick R. Soelberg; Layne F. Pincock; Eric L. Shaber; Gregory M Teske
2011-06-01
All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010b] are steps by the Fuel Cycle Technology program toward an analysis that accounts for the requirements and capabilities of each fuel cycle component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. This report describes FIT 2, an update of the original FIT model.[Piet2010c] FIT is a method to analyze different fuel cycles; in particular, to determine how changes in one part of a fuel cycle (say, fuel burnup, cooling, or separation efficiencies) chemically affect other parts of the fuel cycle. FIT provides the following: Rough estimate of physics and mass balance feasibility of combinations of technologies. If feasibility is an issue, it provides an estimate of how performance would have to change to achieve feasibility. Estimate of impurities in fuel and impurities in waste as function of separation performance, fuel fabrication, reactor, uranium source, etc.
Multidimensional Rasch Model Information-Based Fit Index Accuracy
ERIC Educational Resources Information Center
Harrell-Williams, Leigh M.; Wolfe, Edward W.
2013-01-01
Most research on confirmatory factor analysis using information-based fit indices (Akaike information criterion [AIC], Bayesian information criteria [BIC], bias-corrected AIC [AICc], and consistent AIC [CAIC]) has used a structural equation modeling framework. Minimal research has been done concerning application of these indices to item response…
ERIC Educational Resources Information Center
Hashim, Junaidah
2008-01-01
Companies in Malaysia are beginning to use web-based training to reduce the cost of training and to provide employees with greater access to instruction. However, some people are uncomfortable with technology and prefer person-to-person methods of training. This study examines the acceptance of web-based training among a convenience sample of 261…
Assessing the fit of site-occupancy models
MacKenzie, D.I.; Bailey, L.L.
2004-01-01
Few species are likely to be so evident that they will always be detected at a site when present. Recently a model has been developed that enables estimation of the proportion of area occupied, when the target species is not detected with certainty. Here we apply this modeling approach to data collected on terrestrial salamanders in the Plethodon glutinosus complex in the Great Smoky Mountains National Park, USA, and wish to address the question 'how accurately does the fitted model represent the data?' The goodness-of-fit of the model needs to be assessed in order to make accurate inferences. This article presents a method where a simple Pearson chi-square statistic is calculated and a parametric bootstrap procedure is used to determine whether the observed statistic is unusually large. We found evidence that the most global model considered provides a poor fit to the data, hence estimated an overdispersion factor to adjust model selection procedures and inflate standard errors. Two hypothetical datasets with known assumption violations are also analyzed, illustrating that the method may be used to guide researchers to making appropriate inferences. The results of a simulation study are presented to provide a broader view of the methods properties.
Survival model construction guided by fit and predictive strength.
Chauvel, Cécile; O'Quigley, John
2016-10-05
Survival model construction can be guided by goodness-of-fit techniques as well as measures of predictive strength. Here, we aim to bring together these distinct techniques within the context of a single framework. The goal is how to best characterize and code the effects of the variables, in particular time dependencies, when taken either singly or in combination with other related covariates. Simple graphical techniques can provide an immediate visual indication as to the goodness-of-fit but, in cases of departure from model assumptions, will point in the direction of a more involved and richer alternative model. These techniques appear to be intuitive. This intuition is backed up by formal theorems that underlie the process of building richer models from simpler ones. Measures of predictive strength are used in conjunction with these goodness-of-fit techniques and, again, formal theorems show that these measures can be used to help identify models closest to the unknown non-proportional hazards mechanism that we can suppose generates the observations. Illustrations from studies in breast cancer show how these tools can be of help in guiding the practical problem of efficient model construction for survival data.
ERIC Educational Resources Information Center
Wong, Kung-Teck; Teo, Timothy; Russo, Sharon
2012-01-01
The purpose of this study is to validate the technology acceptance model (TAM) in an educational context and explore the role of gender and computer teaching efficacy as external variables. From the literature, it appeared that only limited studies had developed models to explain statistically the chain of influence of computer teaching efficacy…
The History of UTAUT Model and Its Impact on ICT Acceptance and Usage by Academicians
ERIC Educational Resources Information Center
Oye, N. D.; Iahad, N. A.; Rahim, N. Ab.
2014-01-01
This paper started with the review of the history of technology acceptance model from TRA to UTAUT. The expected contribution is to bring to lime light the current development stage of the technology acceptance model. Based on this, the paper examined the impact of UTAUT model on ICT acceptance and usage in HEIs. The UTAUT model theory was…
Miao, Hongyu; Dykes, Carrie; Demeter, Lisa M; Wu, Hulin
2009-03-01
Many biological processes and systems can be described by a set of differential equation (DE) models. However, literature in statistical inference for DE models is very sparse. We propose statistical estimation, model selection, and multimodel averaging methods for HIV viral fitness experiments in vitro that can be described by a set of nonlinear ordinary differential equations (ODE). The parameter identifiability of the ODE models is also addressed. We apply the proposed methods and techniques to experimental data of viral fitness for HIV-1 mutant 103N. We expect that the proposed modeling and inference approaches for the DE models can be widely used for a variety of biomedical studies.
Limitations of model-fitting methods for lensing shear estimation
NASA Astrophysics Data System (ADS)
Voigt, L. M.; Bridle, S. L.
2010-05-01
Gravitational lensing shear has the potential to be the most powerful tool for constraining the nature of dark energy. However, accurate measurement of galaxy shear is crucial and has been shown to be non-trivial by the Shear TEsting Programme. Here, we demonstrate a fundamental limit to the accuracy achievable by model-fitting techniques, if oversimplistic models are used. We show that even if galaxies have elliptical isophotes, model-fitting methods which assume elliptical isophotes can have significant biases if they use the wrong profile. We use noise-free simulations to show that on allowing sufficient flexibility in the profile the biases can be made negligible. This is no longer the case if elliptical isophote models are used to fit galaxies made up of a bulge plus a disc, if these two components have different ellipticities. The limiting accuracy is dependent on the galaxy shape, but we find the most significant biases (~1 per cent of the shear) for simple spiral-like galaxies. The implications for a given cosmic shear survey will depend on the actual distribution of galaxy morphologies in the Universe, taking into account the survey selection function and the point spread function. However, our results suggest that the impact on cosmic shear results from current and near future surveys may be negligible. Meanwhile, these results should encourage the development of existing approaches which are less sensitive to morphology, as well as methods which use priors on galaxy shapes learnt from deep surveys.
Supersymmetry with prejudice: Fitting the wrong model to LHC data
NASA Astrophysics Data System (ADS)
Allanach, B. C.; Dolan, Matthew J.
2012-09-01
We critically examine interpretations of hypothetical supersymmetric LHC signals, fitting to alternative wrong models of supersymmetry breaking. The signals we consider are some of the most constraining on the sparticle spectrum: invariant mass distributions with edges and endpoints from the golden decay chain q˜→qχ20(→l˜±l∓q)→χ10l+l-q. We assume a constrained minimal supersymmetric standard model (CMSSM) point to be the ‘correct’ one, but fit the signals instead with minimal gauge mediated supersymmetry breaking models (mGMSB) with a neutralino quasistable lightest supersymmetric particle, minimal anomaly mediation and large volume string compactification models. Minimal anomaly mediation and large volume scenario can be unambiguously discriminated against the CMSSM for the assumed signal and 1fb-1 of LHC data at s=14TeV. However, mGMSB would not be discriminated on the basis of the kinematic endpoints alone. The best-fit point spectra of mGMSB and CMSSM look remarkably similar, making experimental discrimination at the LHC based on the edges or Higgs properties difficult. However, using rate information for the golden chain should provide the additional separation required.
ERIC Educational Resources Information Center
Afari-Kumah, Eben; Achampong, Akwasi Kyere
2010-01-01
This study aims to examine the computer usage intentions of Ghanaian Tertiary Students. The Technology Acceptance Model was adopted as the theoretical framework to ascertain whether it could help explain behavioral intentions of individuals to accept and use technology. Factor analysis was used to assess the construct validity of the initial…
Atmospheric Turbulence Modeling for Aerospace Vehicles: Fractional Order Fit
NASA Technical Reports Server (NTRS)
Kopasakis, George (Inventor)
2015-01-01
An improved model for simulating atmospheric disturbances is disclosed. A scale Kolmogorov spectral may be scaled to convert the Kolmogorov spectral into a finite energy von Karman spectral and a fractional order pole-zero transfer function (TF) may be derived from the von Karman spectral. Fractional order atmospheric turbulence may be approximated with an integer order pole-zero TF fit, and the approximation may be stored in memory.
ERIC Educational Resources Information Center
Gyamfi, Stephen Adu
2016-01-01
This study extends the technology acceptance model to identify factors that influence technology acceptance among pre-service teachers in Ghana. Data from 380 usable questionnaires were tested against the research model. Utilising the extended technology acceptance model (TAM) as a research framework, the study found that: pre-service teachers'…
Blanquart, François; Bataillon, Thomas
2016-01-01
The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher’s model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher’s model was able to explain several statistical properties of the landscapes—including the mean and SD of selection and epistasis coefficients—it was often unable to explain the full structure of fitness landscapes. PMID:27052568
ERIC Educational Resources Information Center
Thissen, David
2013-01-01
In this commentary, David Thissen states that "Goodness-of-fit assessment for IRT models is maturing; it has come a long way from zero." Thissen then references prior works on "goodness of fit" in the index of Lord and Novick's (1968) classic text; Yen (1984); Drasgow, Levine, Tsien, Williams, and Mead (1995); Chen and…
Bayesian Data-Model Fit Assessment for Structural Equation Modeling
ERIC Educational Resources Information Center
Levy, Roy
2011-01-01
Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes…
Broadband distortion modeling in Lyman-α forest BAO fitting
Blomqvist, Michael; Kirkby, David; Bautista, Julian E.; ...
2015-11-23
Recently, the Lyman-α absorption observed in the spectra of high-redshift quasars has been used as a tracer of large-scale structure by means of the three-dimensional Lyman-α forest auto-correlation function at redshift z≃ 2.3, but the need to fit the quasar continuum in every absorption spectrum introduces a broadband distortion that is difficult to correct and causes a systematic error for measuring any broadband properties. Here, we describe a k-space model for this broadband distortion based on a multiplicative correction to the power spectrum of the transmitted flux fraction that suppresses power on scales corresponding to the typical length of amore » Lyman-α forest spectrum. In implementing the distortion model in fits for the baryon acoustic oscillation (BAO) peak position in the Lyman-α forest auto-correlation, we find that the fitting method recovers the input values of the linear bias parameter bF and the redshift-space distortion parameter βF for mock data sets with a systematic error of less than 0.5%. Applied to the auto-correlation measured for BOSS Data Release 11, our method improves on the previous treatment of broadband distortions in BAO fitting by providing a better fit to the data using fewer parameters and reducing the statistical errors on βF and the combination bF(1+βF) by more than a factor of seven. The measured values at redshift z=2.3 are βF=1.39+0.11 +0.24 +0.38-0.10 -0.19 -0.28 and bF(1+βF)=-0.374+0.007 +0.013 +0.020-0.007 -0.014 -0.022 (1σ, 2σ and 3σ statistical errors). Our fitting software and the input files needed to reproduce our main results are publicly available.« less
Broadband distortion modeling in Lyman-α forest BAO fitting
Blomqvist, Michael; Kirkby, David; Margala, Daniel E-mail: dkirkby@uci.edu; and others
2015-11-01
In recent years, the Lyman-α absorption observed in the spectra of high-redshift quasars has been used as a tracer of large-scale structure by means of the three-dimensional Lyman-α forest auto-correlation function at redshift z≅ 2.3, but the need to fit the quasar continuum in every absorption spectrum introduces a broadband distortion that is difficult to correct and causes a systematic error for measuring any broadband properties. We describe a k-space model for this broadband distortion based on a multiplicative correction to the power spectrum of the transmitted flux fraction that suppresses power on scales corresponding to the typical length of a Lyman-α forest spectrum. Implementing the distortion model in fits for the baryon acoustic oscillation (BAO) peak position in the Lyman-α forest auto-correlation, we find that the fitting method recovers the input values of the linear bias parameter b{sub F} and the redshift-space distortion parameter β{sub F} for mock data sets with a systematic error of less than 0.5%. Applied to the auto-correlation measured for BOSS Data Release 11, our method improves on the previous treatment of broadband distortions in BAO fitting by providing a better fit to the data using fewer parameters and reducing the statistical errors on β{sub F} and the combination b{sub F}(1+β{sub F}) by more than a factor of seven. The measured values at redshift z=2.3 are β{sub F}=1.39{sup +0.11 +0.24 +0.38}{sub −0.10 −0.19 −0.28} and b{sub F}(1+β{sub F})=−0.374{sup +0.007 +0.013 +0.020}{sub −0.007 −0.014 −0.022} (1σ, 2σ and 3σ statistical errors). Our fitting software and the input files needed to reproduce our main results are publicly available.
Broadband distortion modeling in Lyman-α forest BAO fitting
Blomqvist, Michael; Kirkby, David; Bautista, Julian E.; Arinyo-i-Prats, Andreu; Busca, Nicolás G.; Miralda-Escudé, Jordi; Slosar, Anže; Font-Ribera, Andreu; Margala, Daniel; Schneider, Donald P.; Vazquez, Jose A.
2015-11-23
Recently, the Lyman-α absorption observed in the spectra of high-redshift quasars has been used as a tracer of large-scale structure by means of the three-dimensional Lyman-α forest auto-correlation function at redshift z≃ 2.3, but the need to fit the quasar continuum in every absorption spectrum introduces a broadband distortion that is difficult to correct and causes a systematic error for measuring any broadband properties. Here, we describe a k-space model for this broadband distortion based on a multiplicative correction to the power spectrum of the transmitted flux fraction that suppresses power on scales corresponding to the typical length of a Lyman-α forest spectrum. In implementing the distortion model in fits for the baryon acoustic oscillation (BAO) peak position in the Lyman-α forest auto-correlation, we find that the fitting method recovers the input values of the linear bias parameter b_{F} and the redshift-space distortion parameter β_{F} for mock data sets with a systematic error of less than 0.5%. Applied to the auto-correlation measured for BOSS Data Release 11, our method improves on the previous treatment of broadband distortions in BAO fitting by providing a better fit to the data using fewer parameters and reducing the statistical errors on βF and the combination b_{F}(1+β_{F}) by more than a factor of seven. The measured values at redshift z=2.3 are βF=1.39^{+0.11 +0.24 +0.38}_{-0.10 -0.19 -0.28} and bF(1+βF)=-0.374^{+0.007 +0.013 +0.020}_{-0.007 -0.014 -0.022} (1σ, 2σ and 3σ statistical errors). Our fitting software and the input files needed to reproduce our main results are publicly available.
Parental Acceptance-Rejection Theory and the Phylogenetic Model.
ERIC Educational Resources Information Center
Rohner, Ronald P.
Guided by specific theoretical and methodological points of view--the phylogenetic perspective and the universalistic approach respectively--this paper reports on a worldwide study of the antecedents and effects of parental acceptance and rejection. Parental acceptance-rejection theory postulates that rejected children throughout our species share…
Chempy: A flexible chemical evolution model for abundance fitting
NASA Astrophysics Data System (ADS)
Rybizki, J.; Just, A.; Rix, H.-W.; Fouesneau, M.
2017-02-01
Chempy models Galactic chemical evolution (GCE); it is a parametrized open one-zone model within a Bayesian framework. A Chempy model is specified by a set of 5-10 parameters that describe the effective galaxy evolution along with the stellar and star-formation physics: e.g. the star-formation history (SFH), the feedback efficiency, the stellar initial mass function (IMF) and the incidence of supernova of type Ia (SN Ia). Chempy can sample the posterior probability distribution in the full model parameter space and test data-model matches for different nucleosynthetic yield sets, performing essentially as a chemical evolution fitting tool. Chempy can be used to confront predictions from stellar nucleosynthesis with complex abundance data sets and to refine the physical processes governing the chemical evolution of stellar systems.
Equilibrium Distribution of Mutators in the Single Fitness Peak Model
NASA Astrophysics Data System (ADS)
Tannenbaum, Emmanuel; Deeds, Eric J.; Shakhnovich, Eugene I.
2003-09-01
This Letter develops an analytically tractable model for determining the equilibrium distribution of mismatch repair deficient strains in unicellular populations. The approach is based on the single fitness peak model, which has been used in Eigen’s quasispecies equations in order to understand various aspects of evolutionary dynamics. As with the quasispecies model, our model for mutator-nonmutator equilibrium undergoes a phase transition in the limit of infinite sequence length. This “repair catastrophe” occurs at a critical repair error probability of ɛr=Lvia/L, where Lvia denotes the length of the genome controlling viability, while L denotes the overall length of the genome. The repair catastrophe therefore occurs when the repair error probability exceeds the fraction of deleterious mutations. Our model also gives a quantitative estimate for the equilibrium fraction of mutators in Escherichia coli.
Bosone, Lucia; Martinez, Frédéric; Kalampalikis, Nikos
2015-04-01
In health-promotional campaigns, positive and negative role models can be deployed to illustrate the benefits or costs of certain behaviors. The main purpose of this article is to investigate why, how, and when exposure to role models strengthens the persuasiveness of a message, according to regulatory fit theory. We argue that exposure to a positive versus a negative model activates individuals' goals toward promotion rather than prevention. By means of two experiments, we demonstrate that high levels of persuasion occur when a message advertising healthy dietary habits offers a regulatory fit between its framing and the described role model. Our data also establish that the effects of such internal regulatory fit by vicarious experience depend on individuals' perceptions of response-efficacy and self-efficacy. Our findings constitute a significant theoretical complement to previous research on regulatory fit and contain valuable practical implications for health-promotional campaigns.
ERIC Educational Resources Information Center
Tay, Louis; Ali, Usama S.; Drasgow, Fritz; Williams, Bruce
2011-01-01
This study investigated the relative model-data fit of an ideal point item response theory (IRT) model (the generalized graded unfolding model [GGUM]) and dominance IRT models (e.g., the two-parameter logistic model [2PLM] and Samejima's graded response model [GRM]) to simulated dichotomous and polytomous data generated from each of these models.…
Do I Have to Learn Something New? Mental Models and the Acceptance of Replacement Technologies
ERIC Educational Resources Information Center
Zhang, Wei; Xu, Peng
2011-01-01
Few studies in technology acceptance have explicitly addressed the acceptance of replacement technologies, technologies that replace legacy ones that have been in use. This article explores this issue through the theoretical lens of mental models. We contend that accepting replacement technologies entails both mental model maintenance and mental…
Changes in Self-acceptance of College Students Associated with the Encounter Model Class
ERIC Educational Resources Information Center
King, Mark
1976-01-01
The major concern of this study is changes in self-acceptance as related to different college classroom models. The specific research hypothesis is that self-acceptance increases as a function of the encounter classroom model. This was confirmed. Increased self-acceptance also appeared stable over time. (NG)
Rapid world modeling: Fitting range data to geometric primitives
Feddema, J.; Little, C.
1996-12-31
For the past seven years, Sandia National Laboratories has been active in the development of robotic systems to help remediate DOE`s waste sites and decommissioned facilities. Some of these facilities have high levels of radioactivity which prevent manual clean-up. Tele-operated and autonomous robotic systems have been envisioned as the only suitable means of removing the radioactive elements. World modeling is defined as the process of creating a numerical geometric model of a real world environment or workspace. This model is often used in robotics to plan robot motions which perform a task while avoiding obstacles. In many applications where the world model does not exist ahead of time, structured lighting, laser range finders, and even acoustical sensors have been used to create three dimensional maps of the environment. These maps consist of thousands of range points which are difficult to handle and interpret. This paper presents a least squares technique for fitting range data to planar and quadric surfaces, including cylinders and ellipsoids. Once fit to these primitive surfaces, the amount of data associated with a surface is greatly reduced up to three orders of magnitude, thus allowing for more rapid handling and analysis of world data.
Generalized least-squares fit of multiequation models
NASA Astrophysics Data System (ADS)
Marshall, Simon L.; Blencoe, James G.
2005-01-01
A method for fitting multiequation models to data sets of finite precision is proposed. This is based on the Gauss-Newton algorithm devised by Britt and Luecke (1973); the inclusion of several equations of condition to be satisfied at each data point results in a block diagonal form for the effective weighting matrix. This method allows generalized nonlinear least-squares fitting of functions that are more easily represented in the parametric form (x(t),y(t)) than as an explicit functional relationship of the form y=f(x). The Aitken (1935) formulas appropriate to multiequation weighted nonlinear least squares are recovered in the limiting case where the variances and covariances of the independent variables are zero. Practical considerations relevant to the performance of such calculations, such as the evaluation of the required partial derivatives and matrix products, are discussed in detail, and the operation of the algorithm is illustrated by applying it to the fit of complex permittivity data to the Debye equation.
Issues in Evaluating Model Fit With Missing Data
ERIC Educational Resources Information Center
Davey, Adam
2005-01-01
Effects of incomplete data on fit indexes remain relatively unexplored. We evaluate a wide set of fit indexes (?[squared], root mean squared error of appproximation, Normed Fit Index [NFI], Tucker-Lewis Index, comparative fit index, gamma-hat, and McDonald's Centrality Index) varying conditions of sample size (100-1,000 in increments of 50),…
Effect of the Number of Variables on Measures of Fit in Structural Equation Modeling.
ERIC Educational Resources Information Center
Kenny, David A.; McCoach, D. Betsy
2003-01-01
Used three approaches to understand the effect of the number of variables in the model on model fit in structural equation modeling through computer simulation. Developed a simple formula for the theoretical value of the comparative fit index. (SLD)
Assessing Model Data Fit of Unidimensional Item Response Theory Models in Simulated Data
ERIC Educational Resources Information Center
Kose, Ibrahim Alper
2014-01-01
The purpose of this paper is to give an example of how to assess the model-data fit of unidimensional IRT models in simulated data. Also, the present research aims to explain the importance of fit and the consequences of misfit by using simulated data sets. Responses of 1000 examinees to a dichotomously scoring 20 item test were simulated with 25…
An NCME Instructional Module on Item-Fit Statistics for Item Response Theory Models
ERIC Educational Resources Information Center
Ames, Allison J.; Penfield, Randall D.
2015-01-01
Drawing valid inferences from item response theory (IRT) models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. This instructional module provides an overview of methods used for evaluating the fit of IRT models. Upon completing…
Empirical fitness models for hepatitis C virus immunogen design
NASA Astrophysics Data System (ADS)
Hart, Gregory R.; Ferguson, Andrew L.
2015-12-01
Hepatitis C virus (HCV) afflicts 170 million people worldwide, 2%-3% of the global population, and kills 350 000 each year. Prophylactic vaccination offers the most realistic and cost effective hope of controlling this epidemic in the developing world where expensive drug therapies are not available. Despite 20 years of research, the high mutability of the virus and lack of knowledge of what constitutes effective immune responses have impeded development of an effective vaccine. Coupling data mining of sequence databases with spin glass models from statistical physics, we have developed a computational approach to translate clinical sequence databases into empirical fitness landscapes quantifying the replicative capacity of the virus as a function of its amino acid sequence. These landscapes explicitly connect viral genotype to phenotypic fitness, and reveal vulnerable immunological targets within the viral proteome that can be exploited to rationally design vaccine immunogens. We have recovered the empirical fitness landscape for the HCV RNA-dependent RNA polymerase (protein NS5B) responsible for viral genome replication, and validated the predictions of our model by demonstrating excellent accord with experimental measurements and clinical observations. We have used our landscapes to perform exhaustive in silico screening of 16.8 million T-cell immunogen candidates to identify 86 optimal formulations. By reducing the search space of immunogen candidates by over five orders of magnitude, our approach can offer valuable savings in time, expense, and labor for experimental vaccine development and accelerate the search for a HCV vaccine. Abbreviations: HCV—hepatitis C virus, HLA—human leukocyte antigen, CTL—cytotoxic T lymphocyte, NS5B—nonstructural protein 5B, MSA—multiple sequence alignment, PEG-IFN—pegylated interferon.
Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS
Bolker, Benjamin M.; Gardner, Beth; Maunder, Mark; Berg, Casper W.; Brooks, Mollie; Comita, Liza; Crone, Elizabeth; Cubaynes, Sarah; Davies, Trevor; de Valpine, Perry; Ford, Jessica; Gimenez, Olivier; Kéry, Marc; Kim, Eun Jung; Lennert-Cody, Cleridy; Magunsson, Arni; Martell, Steve; Nash, John; Nielson, Anders; Regentz, Jim; Skaug, Hans; Zipkin, Elise
2013-01-01
1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.
ERIC Educational Resources Information Center
Elwood, Susan; Changchit, Chuleeporn; Cutshall, Robert
2006-01-01
Purpose: This study aims to examine students' perceptions and their acceptance towards implementing a laptop program. Design/methodology/approach: Extensive research has been carried out on the technology acceptance model (TAM) to better understand the behavioral intention of individuals to accept and use technology. Therefore, the TAM was adopted…
The Adult Roles Models Program: Feasibility, Acceptability, and Initial Outcomes
Silver, Ellen Johnson; Dean, Randa; Perez, Amanda; Rivera, Angelic
2014-01-01
We present the feasibility and acceptability of a parent sexuality education program led by peer educators in community settings. We also report the results of an outcome evaluation with 71 parents who were randomized to the intervention or a control group, and surveyed one month prior to and six months after the 4-week intervention. The program was highly feasible and acceptable to participants, and the curriculum was implemented with a high level of fidelity and facilitator quality. Pilot data show promising outcomes for increasing parental knowledge, communication, and monitoring of their adolescent children. PMID:24883051
Hybrid E-Learning Acceptance Model: Learner Perceptions
ERIC Educational Resources Information Center
Ahmed, Hassan M. Selim
2010-01-01
E-learning tools and technologies have been used to supplement conventional courses in higher education institutions creating a "hybrid" e-learning module that aims to enhance the learning experiences of students. Few studies have addressed the acceptance of hybrid e-learning by learners and the factors affecting the learners'…
Using R^2 to compare least-squares fit models: When it must fail
Technology Transfer Automated Retrieval System (TEKTRAN)
R^2 can be used correctly to select from among competing least-squares fit models when the data are fitted in common form and with common weighting. However, then R^2 comparisons become equivalent to comparisons of the estimated fit variance s^2 in unweighted fitting, or of the reduced chi-square in...
Assessing Fit of Latent Regression Models. Research Report. ETS RR-09-50
ERIC Educational Resources Information Center
Sinharay, Sandip; Guo, Zhumei; von Davier, Matthias; Veldkamp, Bernard P.
2009-01-01
The reporting methods used in large-scale educational assessments such as the National Assessment of Educational Progress (NAEP) rely on a "latent regression model". There is a lack of research on the assessment of fit of latent regression models. This paper suggests a simulation-based model-fit technique to assess the fit of such…
Parental Vaccine Acceptance: A Logistic Regression Model Using Previsit Decisions.
Lee, Sara; Riley-Behringer, Maureen; Rose, Jeanmarie C; Meropol, Sharon B; Lazebnik, Rina
2016-10-26
This study explores how parents' intentions regarding vaccination prior to their children's visit were associated with actual vaccine acceptance. A convenience sample of parents accompanying 6-week-old to 17-year-old children completed a written survey at 2 pediatric practices. Using hierarchical logistic regression, for hospital-based participants (n = 216), vaccine refusal history (P < .01) and vaccine decision made before the visit (P < .05) explained 87% of vaccine refusals. In community-based participants (n = 100), vaccine refusal history (P < .01) explained 81% of refusals. Over 1 in 5 parents changed their minds about vaccination during the visit. Thirty parents who were previous vaccine refusers accepted current vaccines, and 37 who had intended not to vaccinate choose vaccination. Twenty-nine parents without a refusal history declined vaccines, and 32 who did not intend to refuse before the visit declined vaccination. Future research should identify key factors to nudge parent decision making in favor of vaccination.
Methodical fitting for mathematical models of rubber-like materials
NASA Astrophysics Data System (ADS)
Destrade, Michel; Saccomandi, Giuseppe; Sgura, Ivonne
2017-02-01
A great variety of models can describe the nonlinear response of rubber to uniaxial tension. Yet an in-depth understanding of the successive stages of large extension is still lacking. We show that the response can be broken down in three steps, which we delineate by relying on a simple formatting of the data, the so-called Mooney plot transform. First, the small-to-moderate regime, where the polymeric chains unfold easily and the Mooney plot is almost linear. Second, the strain-hardening regime, where blobs of bundled chains unfold to stiffen the response in correspondence to the `upturn' of the Mooney plot. Third, the limiting-chain regime, with a sharp stiffening occurring as the chains extend towards their limit. We provide strain-energy functions with terms accounting for each stage that (i) give an accurate local and then global fitting of the data; (ii) are consistent with weak nonlinear elasticity theory and (iii) can be interpreted in the framework of statistical mechanics. We apply our method to Treloar's classical experimental data and also to some more recent data. Our method not only provides models that describe the experimental data with a very low quantitative relative error, but also shows that the theory of nonlinear elasticity is much more robust that seemed at first sight.
Shin, Dong-Hee; Kim, Won-Yong; Kim, Won-Young
2008-06-01
This study explores attitudinal and behavioral patterns when using Cyworld by adopting an expanded Technology Acceptance Model (TAM). A model for Cyworld acceptance is used to examine how various factors modified from the TAM influence acceptance and its antecedents. This model is examined through an empirical study involving Cyworld users using structural equation modeling techniques. The model shows reasonably good measurement properties and the constructs are validated. The results not only confirm the model but also reveal general factors applicable to Web2.0. A set of constructs in the model can be the Web2.0-specific factors, playing as enhancing factor to attitudes and intention.
Acceptance and Commitment Therapy as a Unified Model of Behavior Change
ERIC Educational Resources Information Center
Hayes, Steven C.; Pistorello, Jacqueline; Levin, Michael E.
2012-01-01
The present article summarizes the assumptions, model, techniques, evidence, and diversity/social justice commitments of Acceptance and Commitment Therapy (ACT). ACT focused on six processes (acceptance, defusion, self, now, values, and action) that bear on a single overall target (psychological flexibility). The ACT model of behavior change has…
24 CFR 200.926c - Model code provisions for use in partially accepted code jurisdictions.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 24 Housing and Urban Development 2 2010-04-01 2010-04-01 false Model code provisions for use in partially accepted code jurisdictions. 200.926c Section 200.926c Housing and Urban Development Regulations... Minimum Property Standards § 200.926c Model code provisions for use in partially accepted...
ERIC Educational Resources Information Center
Zhang, Wei
2008-01-01
A major issue in the utilization of covariance structure analysis is model fit evaluation. Recent years have witnessed increasing interest in various test statistics and so-called fit indexes, most of which are actually based on or closely related to F[subscript 0], a measure of model fit in the population. This study aims to provide a systematic…
Performance of the Generalized S-X[squared] Item Fit Index for the Graded Response Model
ERIC Educational Resources Information Center
Kang, Taehoon; Chen, Troy T.
2011-01-01
The utility of Orlando and Thissen's ("2000", "2003") S-X[squared] fit index was extended to the model-fit analysis of the graded response model (GRM). The performance of a modified S-X[squared] in assessing item-fit of the GRM was investigated in light of empirical Type I error rates and power with a simulation study having…
Model-independent fit to Planck and BICEP2 data
NASA Astrophysics Data System (ADS)
Barranco, Laura; Boubekeur, Lotfi; Mena, Olga
2014-09-01
Inflation is the leading theory to describe elegantly the initial conditions that led to structure formation in our Universe. In this paper, we present a novel phenomenological fit to the Planck, WMAP polarization (WP) and the BICEP2 data sets using an alternative parametrization. Instead of starting from inflationary potentials and computing the inflationary observables, we use a phenomenological parametrization due to Mukhanov, describing inflation by an effective equation of state, in terms of the number of e-folds and two phenomenological parameters α and β. Within such a parametrization, which captures the different inflationary models in a model-independent way, the values of the scalar spectral index ns, its running and the tensor-to-scalar ratio r are predicted, given a set of parameters (α ,β). We perform a Markov Chain Monte Carlo analysis of these parameters, and we show that the combined analysis of Planck and WP data favors the Starobinsky and Higgs inflation scenarios. Assuming that the BICEP2 signal is not entirely due to foregrounds, the addition of this last data set prefers instead the ϕ2 chaotic models. The constraint we get from Planck and WP data alone on the derived tensor-to-scalar ratio is r <0.18 at 95% C.L., value which is consistent with the one quoted from the BICEP2 Collaboration analysis, r =0.16-0.05+0-06, after foreground subtraction. This is not necessarily at odds with the 2σ tension found between Planck and BICEP2 measurements when analyzing data in terms of the usual ns and r parameters, given that the parametrization used here, for the preferred value ns≃0.96, allows only for a restricted parameter space in the usual (ns,r) plane.
Tylka, Tracy L; Homan, Kristin J
2015-09-01
The acceptance model of intuitive eating posits that body acceptance by others facilitates body appreciation and internal body orientation, which contribute to intuitive eating. Two domains of exercise motives (functional and appearance) may also be linked to these variables, and thus were integrated into the model. The model fit the data well for 406 physically active U.S. college students, although some pathways were stronger for women. Body acceptance by others directly contributed to higher functional exercise motives and indirectly contributed to lower appearance exercise motives through higher internal body orientation. Functional exercise motives positively, and appearance exercise motives inversely, contributed to body appreciation. Whereas body appreciation positively, and appearance exercise motives inversely, contributed to intuitive eating for women, only the latter association was evident for men. To benefit positive body image and intuitive eating, efforts should encourage body acceptance by others and emphasize functional and de-emphasize appearance exercise motives.
A Simulated Annealing based Optimization Algorithm for Automatic Variogram Model Fitting
NASA Astrophysics Data System (ADS)
Soltani-Mohammadi, Saeed; Safa, Mohammad
2016-09-01
Fitting a theoretical model to an experimental variogram is an important issue in geostatistical studies because if the variogram model parameters are tainted with uncertainty, the latter will spread in the results of estimations and simulations. Although the most popular fitting method is fitting by eye, in some cases use is made of the automatic fitting method on the basis of putting together the geostatistical principles and optimization techniques to: 1) provide a basic model to improve fitting by eye, 2) fit a model to a large number of experimental variograms in a short time, and 3) incorporate the variogram related uncertainty in the model fitting. Effort has been made in this paper to improve the quality of the fitted model by improving the popular objective function (weighted least squares) in the automatic fitting. Also, since the variogram model function (£) and number of structures (m) too affect the model quality, a program has been provided in the MATLAB software that can present optimum nested variogram models using the simulated annealing method. Finally, to select the most desirable model from among the single/multi-structured fitted models, use has been made of the cross-validation method, and the best model has been introduced to the user as the output. In order to check the capability of the proposed objective function and the procedure, 3 case studies have been presented.
A quantitative confidence signal detection model: 1. Fitting psychometric functions
Yi, Yongwoo
2016-01-01
Perceptual thresholds are commonly assayed in the laboratory and clinic. When precision and accuracy are required, thresholds are quantified by fitting a psychometric function to forced-choice data. The primary shortcoming of this approach is that it typically requires 100 trials or more to yield accurate (i.e., small bias) and precise (i.e., small variance) psychometric parameter estimates. We show that confidence probability judgments combined with a model of confidence can yield psychometric parameter estimates that are markedly more precise and/or markedly more efficient than conventional methods. Specifically, both human data and simulations show that including confidence probability judgments for just 20 trials can yield psychometric parameter estimates that match the precision of those obtained from 100 trials using conventional analyses. Such an efficiency advantage would be especially beneficial for tasks (e.g., taste, smell, and vestibular assays) that require more than a few seconds for each trial, but this potential benefit could accrue for many other tasks. PMID:26763777
Tsai, Chung-Hung
2014-05-07
Telehealth has become an increasingly applied solution to delivering health care to rural and underserved areas by remote health care professionals. This study integrated social capital theory, social cognitive theory, and the technology acceptance model (TAM) to develop a comprehensive behavioral model for analyzing the relationships among social capital factors (social capital theory), technological factors (TAM), and system self-efficacy (social cognitive theory) in telehealth. The proposed framework was validated with 365 respondents from Nantou County, located in Central Taiwan. Structural equation modeling (SEM) was used to assess the causal relationships that were hypothesized in the proposed model. The finding indicates that elderly residents generally reported positive perceptions toward the telehealth system. Generally, the findings show that social capital factors (social trust, institutional trust, and social participation) significantly positively affect the technological factors (perceived ease of use and perceived usefulness respectively), which influenced usage intention. This study also confirmed that system self-efficacy was the salient antecedent of perceived ease of use. In addition, regarding the samples, the proposed model fitted considerably well. The proposed integrative psychosocial-technological model may serve as a theoretical basis for future research and can also offer empirical foresight to practitioners and researchers in the health departments of governments, hospitals, and rural communities.
Tsai, Chung-Hung
2014-01-01
Telehealth has become an increasingly applied solution to delivering health care to rural and underserved areas by remote health care professionals. This study integrated social capital theory, social cognitive theory, and the technology acceptance model (TAM) to develop a comprehensive behavioral model for analyzing the relationships among social capital factors (social capital theory), technological factors (TAM), and system self-efficacy (social cognitive theory) in telehealth. The proposed framework was validated with 365 respondents from Nantou County, located in Central Taiwan. Structural equation modeling (SEM) was used to assess the causal relationships that were hypothesized in the proposed model. The finding indicates that elderly residents generally reported positive perceptions toward the telehealth system. Generally, the findings show that social capital factors (social trust, institutional trust, and social participation) significantly positively affect the technological factors (perceived ease of use and perceived usefulness respectively), which influenced usage intention. This study also confirmed that system self-efficacy was the salient antecedent of perceived ease of use. In addition, regarding the samples, the proposed model fitted considerably well. The proposed integrative psychosocial-technological model may serve as a theoretical basis for future research and can also offer empirical foresight to practitioners and researchers in the health departments of governments, hospitals, and rural communities. PMID:24810577
An Investigation of Employees' Use of E-Learning Systems: Applying the Technology Acceptance Model
ERIC Educational Resources Information Center
Lee, Yi-Hsuan; Hsieh, Yi-Chuan; Chen, Yen-Hsun
2013-01-01
The purpose of this study is to apply the technology acceptance model to examine the employees' attitudes and acceptance of electronic learning (e-learning) systems in organisations. This study examines four factors (organisational support, computer self-efficacy, prior experience and task equivocality) that are believed to influence employees'…
Comparing the Fit of Item Response Theory and Factor Analysis Models
ERIC Educational Resources Information Center
Maydeu-Olivares, Alberto; Cai, Li; Hernandez, Adolfo
2011-01-01
Linear factor analysis (FA) models can be reliably tested using test statistics based on residual covariances. We show that the same statistics can be used to reliably test the fit of item response theory (IRT) models for ordinal data (under some conditions). Hence, the fit of an FA model and of an IRT model to the same data set can now be…
Convergence, Admissibility, and Fit of Alternative Confirmatory Factor Analysis Models for MTMM Data
ERIC Educational Resources Information Center
Lance, Charles E.; Fan, Yi
2016-01-01
We compared six different analytic models for multitrait-multimethod (MTMM) data in terms of convergence, admissibility, and model fit to 258 samples of previously reported data. Two well-known models, the correlated trait-correlated method (CTCM) and the correlated trait-correlated uniqueness (CTCU) models, were fit for reference purposes in…
An Application of M[subscript 2] Statistic to Evaluate the Fit of Cognitive Diagnostic Models
ERIC Educational Resources Information Center
Liu, Yanlou; Tian, Wei; Xin, Tao
2016-01-01
The fit of cognitive diagnostic models (CDMs) to response data needs to be evaluated, since CDMs might yield misleading results when they do not fit the data well. Limited-information statistic M[subscript 2] and the associated root mean square error of approximation (RMSEA[subscript 2]) in item factor analysis were extended to evaluate the fit of…
Albanese, A; Urso, R; Bianciardi, L; Rigato, M; Battisti, E
2009-11-01
With reference to experimental data in the literature, we present a model consisting of two elastic elements, conceived to simulate resistance to stretching, at constant velocity of elongation, of corneal tissue affected by keratoconus, treated with riboflavin and ultraviolet irradiation to induce cross-linking. The function describing model behaviour adapted to stress and strain values. It was found that the Young's moduli of the two elastic elements increased in cross-linked tissues and that cross-linking treatment therefore increased corneal rigidity. It is recognized that this observation is substantially in line with the conclusion reported in the literature, obtained using an exponential fitting function. It is observed, however, that the latter function implies a condition of non-zero stresses without strain, and does not provide interpretative insights for lack of any biomechanical basis. Above all, the function fits a singular trend, inexplicably claimed to be viscoelastic, with surprising perfection. In any case, using the reported data, the study demonstrates that a fitting equation obtained by a modelling approach not only shows the evident efficacy of the treatment, but also provides orientations for studying modifications induced in cross-linked fibres.
ERIC Educational Resources Information Center
Finch, W. Holmes; Finch, Maria E. Hernandez
2016-01-01
Researchers and data analysts are sometimes faced with the problem of very small samples, where the number of variables approaches or exceeds the overall sample size; i.e. high dimensional data. In such cases, standard statistical models such as regression or analysis of variance cannot be used, either because the resulting parameter estimates…
Modelling acceptance of sunlight in high and low photovoltaic concentration
Leutz, Ralf
2014-09-26
A simple model incorporating linear radiation characteristics, along with the optical trains and geometrical concentration ratios of solar concentrators is presented with performance examples for optical trains of HCPV, LCPV and benchmark flat-plate PV.
Percentile Analysis for Goodness-of-Fit Comparisons of Models to Data
2014-07-01
Science, 1, 11-38. Roberts, S., & Pashler, H. (2000). How persuasive is a good fit ? A comment on theory testing . Psychological Review, 107, 358-367...Percentile analysis for goodness -of- fit comparisons of models to data Sangeet Khemlani and J. Gregory Trafton skhemlani@gmail.com, trafton...modeling, it is routine to report a goodness -of- fit index (e.g., R2 or RMSE) between a putative model’s predictions and an observed dataset
Geostatistical models are appropriate for spatially distributed data measured at irregularly spaced locations. We propose an efficient Markov chain Monte Carlo (MCMC) algorithm for fitting Bayesian geostatistical models with substantial numbers of unknown parameters to sizable...
The Acceptance of Exceptionality: A Three Dimensional Model.
ERIC Educational Resources Information Center
Martin, Larry L.; Nivens, Maryruth K.
A model extrapolates from E. Kubler-Ross' conception of the stages of grief to apply to parent and family reactions when an exceptionality is identified. A chart lists possible parent feelings and reactions, possible school reactions to the parent in grief, and the child's reactions during each of five stages: denial, rage and anger, bargaining,…
A fitted neoprene garment to cover dressings in swine models.
Mino, Matthew J; Mauskar, Neil A; Matt, Sara E; Pavlovich, Anna R; Prindeze, Nicholas J; Moffatt, Lauren T; Shupp, Jeffrey W
2012-12-17
Domesticated porcine species are commonly used in studies of wound healing, owing to similarities between porcine skin and human skin. Such studies often involve wound dressings, and keeping these dressings intact on the animal can be a challenge. The authors describe a novel and simple technique for constructing a fitted neoprene garment for pigs that covers dressings and maintains their integrity during experiments.
24 CFR 200.926c - Model code provisions for use in partially accepted code jurisdictions.
Code of Federal Regulations, 2011 CFR
2011-04-01
... Minimum Property Standards § 200.926c Model code provisions for use in partially accepted code... Chapter 3. (e) Materials standards Chapter 26. (f) Construction components Part III. (g) Glass Chapter 2... dwellings (NFPA 70A-1990)....
ERIC Educational Resources Information Center
Dyehouse, Melissa A.
2009-01-01
This study compared the model-data fit of a parametric item response theory (PIRT) model to a nonparametric item response theory (NIRT) model to determine the best-fitting model for use with ordinal-level alternate assessment ratings. The PIRT Generalized Graded Unfolding Model (GGUM) was compared to the NIRT Mokken model. Chi-square statistics…
The Search for "Optimal" Cutoff Properties: Fit Index Criteria in Structural Equation Modeling
ERIC Educational Resources Information Center
Sivo, Stephen A.; Xitao, Fan; Witta, E. Lea; Willse, John T.
2006-01-01
This study is a partial replication of L. Hu and P. M. Bentler's (1999) fit criteria work. The purpose of this study was twofold: (a) to determine whether cut-off values vary according to which model is the true population model for a dataset and (b) to identify which of 13 fit indexes behave optimally by retaining all of the correct models while…
Strudwick, Gillian
2015-05-01
The benefits of healthcare technologies can only be attained if nurses accept and intend to fully use them. One of the most common models utilized to understand user acceptance of technology is the Technology Acceptance Model. This model and modified versions of it have only recently been applied in the healthcare literature among nurse participants. An integrative literature review was conducted on this topic. Ovid/MEDLINE, PubMed, Google Scholar, and CINAHL were searched yielding a total of 982 references. Upon eliminating duplicates and applying the inclusion and exclusion criteria, the review included a total of four dissertations, three symposium proceedings, and 13 peer-reviewed journal articles. These documents were appraised and reviewed. The results show that a modified Technology Acceptance Model with added variables could provide a better explanation of nurses' acceptance of healthcare technology. These added variables to modified versions of the Technology Acceptance Model are discussed, and the studies' methodologies are critiqued. Limitations of the studies included in the integrative review are also examined.
Model Fitting for Predicted Precipitation in Darwin: Some Issues with Model Choice
ERIC Educational Resources Information Center
Farmer, Jim
2010-01-01
In Volume 23(2) of the "Australian Senior Mathematics Journal," Boncek and Harden present an exercise in fitting a Markov chain model to rainfall data for Darwin Airport (Boncek & Harden, 2009). Days are subdivided into those with precipitation and precipitation-free days. The author abbreviates these labels to wet days and dry days.…
A proposed model of factors influencing hydrogen fuel cell vehicle acceptance
NASA Astrophysics Data System (ADS)
Imanina, N. H. Noor; Kwe Lu, Tan; Fadhilah, A. R.
2016-03-01
Issues such as environmental problem and energy insecurity keep worsening as a result of energy use from household to huge industries including automotive industry. Recently, a new type of zero emission vehicle, hydrogen fuel cell vehicle (HFCV) has received attention. Although there are argues on the feasibility of hydrogen as the future fuel, there is another important issue, which is the acceptance of HFCV. The study of technology acceptance in the early stage is a vital key for a successful introduction and penetration of a technology. This paper proposes a model of factors influencing green vehicle acceptance, specifically HFCV. This model is built base on two technology acceptance theories and other empirical studies of vehicle acceptance. It aims to provide a base for finding the key factors influencing new sustainable energy fuelled vehicle, HFCV acceptance which is achieved by explaining intention to accept HFCV. Intention is influenced by attitude, subjective norm and perceived behavioural control from Theory of Planned Behaviour and personal norm from Norm Activation Theory. In the framework, attitude is influenced by perceptions of benefits and risks, and social trust. Perceived behavioural control is influenced by government interventions. Personal norm is influenced by outcome efficacy and problem awareness.
A Cautionary Note on the Use of Information Fit Indexes in Covariance Structure Modeling with Means
ERIC Educational Resources Information Center
Wicherts, Jelte M.; Dolan, Conor V.
2004-01-01
Information fit indexes such as Akaike Information Criterion, Consistent Akaike Information Criterion, Bayesian Information Criterion, and the expected cross validation index can be valuable in assessing the relative fit of structural equation models that differ regarding restrictiveness. In cases in which models without mean restrictions (i.e.,…
Performance of the Generalized S-X[Superscript 2] Item Fit Index for Polytomous IRT Models
ERIC Educational Resources Information Center
Kang, Taehoon; Chen, Troy T.
2008-01-01
Orlando and Thissen's S-X[superscript 2] item fit index has performed better than traditional item fit statistics such as Yen' s Q[subscript 1] and McKinley and Mill' s G[superscript 2] for dichotomous item response theory (IRT) models. This study extends the utility of S-X[superscript 2] to polytomous IRT models, including the generalized partial…
Why Should We Assess the Goodness-of-Fit of IRT Models?
ERIC Educational Resources Information Center
Maydeu-Olivares, Alberto
2013-01-01
In this rejoinder, Maydeu-Olivares states that, in item response theory (IRT) measurement applications, the application of goodness-of-fit (GOF) methods informs researchers of the discrepancy between the model and the data being fitted (the room for improvement). By routinely reporting the GOF of IRT models, together with the substantive results…
Residuals and the Residual-Based Statistic for Testing Goodness of Fit of Structural Equation Models
ERIC Educational Resources Information Center
Foldnes, Njal; Foss, Tron; Olsson, Ulf Henning
2012-01-01
The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion of the residuals, obtaining a geometrical interpretation by recognizing the residuals as the result of oblique projections. This sheds light on the…
A Model-Based Approach to Goodness-of-Fit Evaluation in Item Response Theory
ERIC Educational Resources Information Center
Oberski, Daniel L.; Vermunt, Jeroen K.
2013-01-01
These authors congratulate Albert Maydeu-Olivares on his lucid and timely overview of goodness-of-fit assessment in IRT models, a field to which he himself has contributed considerably in the form of limited information statistics. In this commentary, Oberski and Vermunt focus on two aspects of model fit: (1) what causes there may be of misfit;…
Approximations to the Distributions of Fit Indexes for Misspecified Structural Equation Models.
ERIC Educational Resources Information Center
Ogasawara, Haruhiko
2001-01-01
Derives approximations to the distributions of goodness-of-fit indexes in structural equation modeling with the assumption of multivariate normality and slight misspecification of models. Also derives an approximation to the asymptotic covariance matrix for the fit indexes by using the delta method and develops approximations to the densities of…
ERIC Educational Resources Information Center
Bauer, Daniel J.; Sterba, Sonya K.
2011-01-01
Previous research has compared methods of estimation for fitting multilevel models to binary data, but there are reasons to believe that the results will not always generalize to the ordinal case. This article thus evaluates (a) whether and when fitting multilevel linear models to ordinal outcome data is justified and (b) which estimator to employ…
Fitting the Rasch Model to Account for Variation in Item Discrimination
ERIC Educational Resources Information Center
Weitzman, R. A.
2009-01-01
Building on the Kelley and Gulliksen versions of classical test theory, this article shows that a logistic model having only a single item parameter can account for varying item discrimination, as well as difficulty, by using item-test correlations to adjust incorrect-correct (0-1) item responses prior to an initial model fit. The fit occurs…
Schaper, Louise K; Pervan, Graham P
2007-06-01
There is evidence to suggest that health professionals are reluctant to accept and utilise information and communication technologies (ICT) and concern is growing within health informatics research that this is contributing to the lag in adoption and utilisation of ICT across the health sector. Technology acceptance research within the field of information systems has been limited in its application to health and there is a concurrent need to develop and gain empirical support for models of technology acceptance within health and to examine acceptance and utilisation issues amongst health professionals to improve the success of information system implementation in this arena. This paper outlines a project that examines ICT acceptance and utilisation by Australian occupational therapists. It describes the theoretical basis behind the development of a research model and the methodology being employed to empirically validate the model using substantial quantitative, qualitative and longitudinal data. Preliminary results from Phase II of the study are presented. The theoretical significance of this work is that it uses a thoroughly constructed research model, with potentially the largest sample size ever tested, to extend technology acceptance research into the health sector.
Brown, Roger L; Scanlon, Matthew C; Karsh, Ben-Tzion
2012-01-01
Objective To identify predictors of nurses' acceptance of bar coded medication administration (BCMA). Design Cross-sectional survey of registered nurses (N=83) at an academic pediatric hospital that recently implemented BCMA. Methods Surveys assessed seven BCMA-related perceptions: ease of use; usefulness for the job; social influence from non-specific others to use BCMA; training; technical support; usefulness for patient care; and social influence from patients/families. An all possible subset regression procedure with five goodness-of-fit indicators was used to identify which set of perceptions best predicted BCMA acceptance (intention to use, satisfaction). Results Nurses reported a moderate perceived ease of use and low perceived usefulness of BCMA. Nurses perceived moderate-or-higher social influence to use BCMA and had moderately positive perceptions of BCMA-related training and technical support. Behavioral intention to use BCMA was high, but satisfaction was low. Behavioral intention to use was best predicted by perceived ease of use, perceived social influence from non-specific others, and perceived usefulness for patient care (56% of variance explained). Satisfaction was best predicted by perceived ease of use, perceived usefulness for patient care, and perceived social influence from patients/families (76% of variance explained). Discussion Variation in and low scores on ease of use and usefulness are concerning, especially as these variables often correlate with acceptance, as found in this study. Predicting acceptance benefited from using a broad set of perceptions and adapting variables to the healthcare context. Conclusion Success with BCMA and other technologies can benefit from assessing end-user acceptance and elucidating the factors promoting acceptance and use. PMID:22661559
NASA Astrophysics Data System (ADS)
Mead, A. J.; Peacock, J. A.; Heymans, C.; Joudaki, S.; Heavens, A. F.
2015-12-01
We present an optimized variant of the halo model, designed to produce accurate matter power spectra well into the non-linear regime for a wide range of cosmological models. To do this, we introduce physically motivated free parameters into the halo-model formalism and fit these to data from high-resolution N-body simulations. For a variety of Λ cold dark matter (ΛCDM) and wCDM models, the halo-model power is accurate to ≃ 5 per cent for k ≤ 10h Mpc-1 and z ≤ 2. An advantage of our new halo model is that it can be adapted to account for the effects of baryonic feedback on the power spectrum. We demonstrate this by fitting the halo model to power spectra from the OWLS (OverWhelmingly Large Simulations) hydrodynamical simulation suite via parameters that govern halo internal structure. We are able to fit all feedback models investigated at the 5 per cent level using only two free parameters, and we place limits on the range of these halo parameters for feedback models investigated by the OWLS simulations. Accurate predictions to high k are vital for weak-lensing surveys, and these halo parameters could be considered nuisance parameters to marginalize over in future analyses to mitigate uncertainty regarding the details of feedback. Finally, we investigate how lensing observables predicted by our model compare to those from simulations and from HALOFIT for a range of k-cuts and feedback models and quantify the angular scales at which these effects become important. Code to calculate power spectra from the model presented in this paper can be found at https://github.com/alexander-mead/hmcode.
THE TECHNOLOGY ACCEPTANCE MODEL: ITS PAST AND ITS FUTURE IN HEALTH CARE
HOLDEN, RICHARD J.; KARSH, BEN-TZION
2009-01-01
Increasing interest in end users’ reactions to health information technology (IT) has elevated the importance of theories that predict and explain health IT acceptance and use. This paper reviews the application of one such theory, the Technology Acceptance Model (TAM), to health care. We reviewed 16 data sets analyzed in over 20 studies of clinicians using health IT for patient care. Studies differed greatly in samples and settings, health ITs studied, research models, relationships tested, and construct operationalization. Certain TAM relationships were consistently found to be significant, whereas others were inconsistent. Several key relationships were infrequently assessed. Findings show that TAM predicts a substantial portion of the use or acceptance of health IT, but that the theory may benefit from several additions and modifications. Aside from improved study quality, standardization, and theoretically motivated additions to the model, an important future direction for TAM is to adapt the model specifically to the health care context, using beliefs elicitation methods. PMID:19615467
The technology acceptance model: its past and its future in health care.
Holden, Richard J; Karsh, Ben-Tzion
2010-02-01
Increasing interest in end users' reactions to health information technology (IT) has elevated the importance of theories that predict and explain health IT acceptance and use. This paper reviews the application of one such theory, the Technology Acceptance Model (TAM), to health care. We reviewed 16 data sets analyzed in over 20 studies of clinicians using health IT for patient care. Studies differed greatly in samples and settings, health ITs studied, research models, relationships tested, and construct operationalization. Certain TAM relationships were consistently found to be significant, whereas others were inconsistent. Several key relationships were infrequently assessed. Findings show that TAM predicts a substantial portion of the use or acceptance of health IT, but that the theory may benefit from several additions and modifications. Aside from improved study quality, standardization, and theoretically motivated additions to the model, an important future direction for TAM is to adapt the model specifically to the health care context, using beliefs elicitation methods.
NASA Astrophysics Data System (ADS)
Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O’Brien, Katherine R.
2017-01-01
When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.
Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O’Brien, Katherine R.
2017-01-01
When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike. PMID:28051123
Assessing Fit of Cognitive Diagnostic Models: A Case Study
ERIC Educational Resources Information Center
Sinharay, Sandip; Almond, Russell G.
2007-01-01
A cognitive diagnostic model uses information from educational experts to describe the relationships between item performances and posited proficiencies. When the cognitive relationships can be described using a fully Bayesian model, Bayesian model checking procedures become available. Checking models tied to cognitive theory of the domains…
Moment-Based Probability Modeling and Extreme Response Estimation, The FITS Routine Version 1.2
MANUEL,LANCE; KASHEF,TINA; WINTERSTEIN,STEVEN R.
1999-11-01
This report documents the use of the FITS routine, which provides automated fits of various analytical, commonly used probability models from input data. It is intended to complement the previously distributed FITTING routine documented in RMS Report 14 (Winterstein et al., 1994), which implements relatively complex four-moment distribution models whose parameters are fit with numerical optimization routines. Although these four-moment fits can be quite useful and faithful to the observed data, their complexity can make them difficult to automate within standard fitting algorithms. In contrast, FITS provides more robust (lower moment) fits of simpler, more conventional distribution forms. For each database of interest, the routine estimates the distribution of annual maximum response based on the data values and the duration, T, over which they were recorded. To focus on the upper tails of interest, the user can also supply an arbitrary lower-bound threshold, {chi}{sub low}, above which a shifted distribution model--exponential or Weibull--is fit.
24 CFR 200.926c - Model code provisions for use in partially accepted code jurisdictions.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 24 Housing and Urban Development 2 2014-04-01 2014-04-01 false Model code provisions for use in... Minimum Property Standards § 200.926c Model code provisions for use in partially accepted code jurisdictions. If a lender or other interested party is notified that a State or local building code has...
Faculty's Acceptance of Computer Based Technology: Cross-Validation of an Extended Model
ERIC Educational Resources Information Center
Ahmad, Tunku Badariah Tunku; Madarsha, Kamal Basha; Zainuddin, Ahmad Marzuki; Ismail, Nik Ahmad Hisham; Nordin, Mohamad Sahari
2010-01-01
The first aim of the present study is to validate an extended technology acceptance model (TAME) on the data derived from the faculty members of a university in an ongoing, computer mediated work setting. The study extended the original TAM model by including an intrinsic motivation component--computer self efficacy. In so doing, the study…
ERIC Educational Resources Information Center
Chow, Meyrick; Herold, David Kurt; Choo, Tat-Ming; Chan, Kitty
2012-01-01
Learners need to have good reasons to engage and accept e-learning. They need to understand that unless they do, the outcomes will be less favourable. The technology acceptance model (TAM) is the most widely recognized model addressing why users accept or reject technology. This study describes the development and evaluation of a virtual…
Melas, Christos D; Zampetakis, Leonidas A; Dimopoulou, Anastasia; Moustakis, Vassilis
2011-08-01
Recent empirical research has utilized the Technology Acceptance Model (TAM) to advance the understanding of doctors' and nurses' technology acceptance in the workplace. However, the majority of the reported studies are either qualitative in nature or use small convenience samples of medical staff. Additionally, in very few studies moderators are either used or assessed despite their importance in TAM based research. The present study focuses on the application of TAM in order to explain the intention to use clinical information systems, in a random sample of 604 medical staff (534 physicians) working in 14 hospitals in Greece. We introduce physicians' specialty as a moderator in TAM and test medical staff's information and communication technology (ICT) knowledge and ICT feature demands, as external variables. The results show that TAM predicts a substantial proportion of the intention to use clinical information systems. Findings make a contribution to the literature by replicating, explaining and advancing the TAM, whereas theory is benefited by the addition of external variables and medical specialty as a moderator. Recommendations for further research are discussed.
ERIC Educational Resources Information Center
Lee, Young-Sun; Wollack, James A.; Douglas, Jeffrey
2009-01-01
The purpose of this study was to assess the model fit of a 2PL through comparison with the nonparametric item characteristic curve (ICC) estimation procedures. Results indicate that three nonparametric procedures implemented produced ICCs that are similar to that of the 2PL for items simulated to fit the 2PL. However for misfitting items,…
Goodness of Fit Confirmatory Factor Analysis: The Effects of Sample Size and Model Parsimony.
ERIC Educational Resources Information Center
Marsh, Herbert W.; Balla, John
The influence of sample size (N) and model parsimony on a set of 22 goodness of fit indices was investigated, including those typically used in confirmatory factor analysis and some recently developed indices. For sample data simulated from 2 known population data structures, values for 6 of 22 fit indices were reasonably independent of N and were…
Exact Person Fit Indexes for the Rasch Model for Arbitrary Alternatives.
ERIC Educational Resources Information Center
Ponocny, Ivo
2000-01-01
Introduces a new algorithm for obtaining exact person fit indexes for the Rasch model. The algorithm realizes most tests for a general family of alternative hypotheses, including tests concerning differential item functioning. The method is also used as a goodness-of-fit test in some circumstances. Simulated examples and an empirical investigation…
ERIC Educational Resources Information Center
Cai, Li; Lee, Taehun
2009-01-01
We apply the Supplemented EM algorithm (Meng & Rubin, 1991) to address a chronic problem with the "two-stage" fitting of covariance structure models in the presence of ignorable missing data: the lack of an asymptotically chi-square distributed goodness-of-fit statistic. We show that the Supplemented EM algorithm provides a…
An experimentally determined evolutionary model dramatically improves phylogenetic fit.
Bloom, Jesse D
2014-08-01
All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here, I demonstrate an alternative: Experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses.
Acceptance of tinnitus: validation of the tinnitus acceptance questionnaire.
Weise, Cornelia; Kleinstäuber, Maria; Hesser, Hugo; Westin, Vendela Zetterqvist; Andersson, Gerhard
2013-01-01
The concept of acceptance has recently received growing attention within tinnitus research due to the fact that tinnitus acceptance is one of the major targets of psychotherapeutic treatments. Accordingly, acceptance-based treatments will most likely be increasingly offered to tinnitus patients and assessments of acceptance-related behaviours will thus be needed. The current study investigated the factorial structure of the Tinnitus Acceptance Questionnaire (TAQ) and the role of tinnitus acceptance as mediating link between sound perception (i.e. subjective loudness of tinnitus) and tinnitus distress. In total, 424 patients with chronic tinnitus completed the TAQ and validated measures of tinnitus distress, anxiety, and depression online. Confirmatory factor analysis provided support to a good fit of the data to the hypothesised bifactor model (root-mean-square-error of approximation = .065; Comparative Fit Index = .974; Tucker-Lewis Index = .958; standardised root mean square residual = .032). In addition, mediation analysis, using a non-parametric joint coefficient approach, revealed that tinnitus-specific acceptance partially mediated the relation between subjective tinnitus loudness and tinnitus distress (path ab = 5.96; 95% CI: 4.49, 7.69). In a multiple mediator model, tinnitus acceptance had a significantly stronger indirect effect than anxiety. The results confirm the factorial structure of the TAQ and suggest the importance of a general acceptance factor that contributes important unique variance beyond that of the first-order factors activity engagement and tinnitus suppression. Tinnitus acceptance as measured with the TAQ is proposed to be a key construct in tinnitus research and should be further implemented into treatment concepts to reduce tinnitus distress.
Fitting and Testing Conditional Multinormal Partial Credit Models
ERIC Educational Resources Information Center
Hessen, David J.
2012-01-01
A multinormal partial credit model for factor analysis of polytomously scored items with ordered response categories is derived using an extension of the Dutch Identity (Holland in "Psychometrika" 55:5-18, 1990). In the model, latent variables are assumed to have a multivariate normal distribution conditional on unweighted sums of item…
Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits
NASA Technical Reports Server (NTRS)
Kopasakis, George
2010-01-01
Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.
Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits
NASA Technical Reports Server (NTRS)
Kopasakis, George
2015-01-01
Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.
Revisiting the global electroweak fit of the Standard Model and beyond with Gfitter
NASA Astrophysics Data System (ADS)
Flächer, H.; Goebel, M.; Haller, J.; Hoecker, A.; Mönig, K.; Stelzer, J.
2009-04-01
The global fit of the Standard Model to electroweak precision data, routinely performed by the LEP electroweak working group and others, demonstrated impressively the predictive power of electroweak unification and quantum loop corrections. We have revisited this fit in view of (i) the development of the new generic fitting package, Gfitter, allowing for flexible and efficient model testing in high-energy physics, (ii) the insertion of constraints from direct Higgs searches at LEP and the Tevatron, and (iii) a more thorough statistical interpretation of the results. Gfitter is a modular fitting toolkit, which features predictive theoretical models as independent plug-ins, and a statistical analysis of the fit results using toy Monte Carlo techniques. The state-of-the-art electroweak Standard Model is fully implemented, as well as generic extensions to it. Theoretical uncertainties are explicitly included in the fit through scale parameters varying within given error ranges. This paper introduces the Gfitter project, and presents state-of-the-art results for the global electroweak fit in the Standard Model (SM), and for a model with an extended Higgs sector (2HDM). Numerical and graphical results for fits with and without including the constraints from the direct Higgs searches at LEP and Tevatron are given. Perspectives for future colliders are analysed and discussed. In the SM fit including the direct Higgs searches, we find M H =116.4{-1.3/+18.3} GeV, and the 2 σ and 3 σ allowed regions [114,145] GeV and [[113,168] and [180,225
Little, Mark P; Vineis, Paolo; Li, Guangquan
2008-09-21
A generalization of the two-mutation stochastic carcinogenesis model of Moolgavkar, Venzon and Knudson and certain models constructed by Little [Little, M.P. (1995). Are two mutations sufficient to cause cancer? Some generalizations of the two-mutation model of carcinogenesis of Moolgavkar, Venzon, and Knudson, and of the multistage model of Armitage and Doll. Biometrics 51, 1278-1291] and Little and Wright [Little, M.P., Wright, E.G. (2003). A stochastic carcinogenesis model incorporating genomic instability fitted to colon cancer data. Math. Biosci. 183, 111-134] is developed; the model incorporates multiple types of progressive genomic instability and an arbitrary number of mutational stages. The model is fitted to US Caucasian colon cancer incidence data. On the basis of the comparison of fits to the population-based data, there is little evidence to support the hypothesis that the model with more than one type of genomic instability fits better than models with a single type of genomic instability. Given the good fit of the model to this large dataset, it is unlikely that further information on presence of genomic instability or of types of genomic instability can be extracted from age-incidence data by extensions of this model.
Fitness model for the Italian interbank money market
NASA Astrophysics Data System (ADS)
de Masi, G.; Iori, G.; Caldarelli, G.
2006-12-01
We use the theory of complex networks in order to quantitatively characterize the formation of communities in a particular financial market. The system is composed by different banks exchanging on a daily basis loans and debts of liquidity. Through topological analysis and by means of a model of network growth we can determine the formation of different group of banks characterized by different business strategy. The model based on Pareto’s law makes no use of growth or preferential attachment and it reproduces correctly all the various statistical properties of the system. We believe that this network modeling of the market could be an efficient way to evaluate the impact of different policies in the market of liquidity.
Fitness model for the Italian interbank money market.
De Masi, G; Iori, G; Caldarelli, G
2006-12-01
We use the theory of complex networks in order to quantitatively characterize the formation of communities in a particular financial market. The system is composed by different banks exchanging on a daily basis loans and debts of liquidity. Through topological analysis and by means of a model of network growth we can determine the formation of different group of banks characterized by different business strategy. The model based on Pareto's law makes no use of growth or preferential attachment and it reproduces correctly all the various statistical properties of the system. We believe that this network modeling of the market could be an efficient way to evaluate the impact of different policies in the market of liquidity.
A no-scale inflationary model to fit them all
Ellis, John; García, Marcos A.G.; Olive, Keith A.; Nanopoulos, Dimitri V. E-mail: garciagarcia@physics.umn.edu E-mail: olive@physics.umn.edu
2014-08-01
The magnitude of B-mode polarization in the cosmic microwave background as measured by BICEP2 favours models of chaotic inflation with a quadratic m{sup 2} φ{sup 2}/2 potential, whereas data from the Planck satellite favour a small value of the tensor-to-scalar perturbation ratio r that is highly consistent with the Starobinsky R +R{sup 2} model. Reality may lie somewhere between these two scenarios. In this paper we propose a minimal two-field no-scale supergravity model that interpolates between quadratic and Starobinsky-like inflation as limiting cases, while retaining the successful prediction n{sub s} ≅ 0.96.
Using proper regression methods for fitting the Langmuir model to sorption data
Technology Transfer Automated Retrieval System (TEKTRAN)
The Langmuir model, originally developed for the study of gas sorption to surfaces, is one of the most commonly used models for fitting phosphorus sorption data. There are good theoretical reasons, however, against applying this model to describe P sorption to soils. Nevertheless, the Langmuir model...
24 CFR 200.926c - Model code provisions for use in partially accepted code jurisdictions.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 24 Housing and Urban Development 2 2012-04-01 2012-04-01 false Model code provisions for use in partially accepted code jurisdictions. 200.926c Section 200.926c Housing and Urban Development Regulations Relating to Housing and Urban Development (Continued) OFFICE OF ASSISTANT SECRETARY FOR...
ERIC Educational Resources Information Center
Wong, Kung-Teck; Osman, Rosma bt; Goh, Pauline Swee Choo; Rahmat, Mohd Khairezan
2013-01-01
This study sets out to validate and test the Technology Acceptance Model (TAM) in the context of Malaysian student teachers' integration of their technology in teaching and learning. To establish factorial validity, data collected from 302 respondents were tested against the TAM using confirmatory factor analysis (CFA), and structural equation…
Extended TAM Model: Impacts of Convenience on Acceptance and Use of Moodle
ERIC Educational Resources Information Center
Hsu, Hsiao-hui; Chang, Yu-ying
2013-01-01
The increasing online access to courses, programs, and information has shifted the control and responsibility of learning process from instructors to learners. Learners' perceptions of and attitudes toward e-learning constitute a critical factor to the success of such system. The purpose of this study is to take TAM (technology acceptance model)…
ERIC Educational Resources Information Center
Chang, Chi-Cheng; Yan, Chi-Fang; Tseng, Ju-Shih
2012-01-01
Since convenience is one of the features for mobile learning, does it affect attitude and intention of using mobile technology? The technology acceptance model (TAM), proposed by David (1989), was extended with perceived convenience in the present study. With regard to English language mobile learning, the variables in the extended TAM and its…
ERIC Educational Resources Information Center
Fusilier, Marcelline; Durlabhji, Subhash; Cucchi, Alain
2008-01-01
National background of users may influence the process of technology acceptance. The present study explored this issue with the new, integrated technology use model proposed by Sun and Zhang (2006). Data were collected from samples of college students in India, Mauritius, Reunion Island, and United States. Questionnaire methodology and…
Improving sleep with mindfulness and acceptance: a metacognitive model of insomnia.
Ong, Jason C; Ulmer, Christi S; Manber, Rachel
2012-11-01
While there is an accumulating evidence to suggest that therapies using mindfulness and acceptance-based approaches have benefits for improving the symptoms of insomnia, it is unclear how these treatments work. The goal of this paper is to present a conceptual framework for the cognitive mechanisms of insomnia based upon mindfulness and acceptance approaches. The existing cognitive and behavioral models of insomnia are first reviewed and a two-level model of cognitive (primary) and metacognitive (secondary) arousal is presented in the context of insomnia. We then focus on the role of metacognition in mindfulness and acceptance-based therapies, followed by a review of these therapies in the treatment of insomnia. A conceptual framework is presented detailing the mechanisms of metacognition in the context of insomnia treatments. This model proposes that increasing awareness of the mental and physical states that are present when experiencing insomnia symptoms and then learning how to shift mental processes can promote an adaptive stance to one's response to these symptoms. These metacognitive processes are characterized by balanced appraisals, cognitive flexibility, equanimity, and commitment to values and are posited to reduce sleep-related arousal, leading to remission from insomnia. We hope that this model will further the understanding and impact of mindfulness and acceptance-based approaches to insomnia.
ERIC Educational Resources Information Center
Nworji, Alexander O.
2013-01-01
Most organizations spend millions of dollars due to the impact of improperly implemented database application systems as evidenced by poor data quality problems. The purpose of this quantitative study was to use, and extend, the technology acceptance model (TAM) to assess the impact of information quality and technical quality factors on database…
Invariance of an Extended Technology Acceptance Model Across Gender and Age Group
ERIC Educational Resources Information Center
Ahmad, Tunku Badariah Tunku; Madarsha, Kamal Basha; Zainuddin, Ahmad Marzuki; Ismail, Nik Ahmad Hisham; Khairani, Ahmad Zamri; Nordin, Mohamad Sahari
2011-01-01
In this study, we examined the likelihood of a TAME (extended technology acceptance model), in which the interrelationships among computer self-efficacy, perceived usefulness, intention to use and self-reported use of computer-mediated technology were tested. In addition, the gender- and age-invariant of its causal structure were evaluated. The…
Design of spatial experiments: Model fitting and prediction
Fedorov, V.V.
1996-03-01
The main objective of the paper is to describe and develop model oriented methods and algorithms for the design of spatial experiments. Unlike many other publications in this area, the approach proposed here is essentially based on the ideas of convex design theory.
Fitting Meta-Analytic Structural Equation Models with Complex Datasets
ERIC Educational Resources Information Center
Wilson, Sandra Jo; Polanin, Joshua R.; Lipsey, Mark W.
2016-01-01
A modification of the first stage of the standard procedure for two-stage meta-analytic structural equation modeling for use with large complex datasets is presented. This modification addresses two common problems that arise in such meta-analyses: (a) primary studies that provide multiple measures of the same construct and (b) the correlation…
Fitting the Balding-Nichols model to forensic databases.
Rohlfs, Rori V; Aguiar, Vitor R C; Lohmueller, Kirk E; Castro, Amanda M; Ferreira, Alessandro C S; Almeida, Vanessa C O; Louro, Iuri D; Nielsen, Rasmus
2015-11-01
Large forensic databases provide an opportunity to compare observed empirical rates of genotype matching with those expected under forensic genetic models. A number of researchers have taken advantage of this opportunity to validate some forensic genetic approaches, particularly to ensure that estimated rates of genotype matching between unrelated individuals are indeed slight overestimates of those observed. However, these studies have also revealed systematic error trends in genotype probability estimates. In this analysis, we investigate these error trends and show how they result from inappropriate implementation of the Balding-Nichols model in the context of database-wide matching. Specifically, we show that in addition to accounting for increased allelic matching between individuals with recent shared ancestry, studies must account for relatively decreased allelic matching between individuals with more ancient shared ancestry.
Mechanical Response of Polycarbonate with Strength Model Fits
2012-02-01
Proceedings of the Seventh International Symposium on Ballistics. The Hague (Netherlands), 1983, 541–547. 4. Zerilli, F .; Armstrong, R . A...Constitutive Model Equation for the Dynamic Deformation Behavior of Polymers. J. Material Sci. 2007, 42 (12), 4562–4574. 5. Zerilli, F .; Armstrong, R ...Polyvinylidene Diflouride. J. Polymer. 2005, 46, 12546–12555. 19. Richeton, J.; Ahzi, S.; Vecchio, K. S.; Jiang, F . C.; Adharapurapu, R . R . Influence of
Parameter fitting for piano sound synthesis by physical modeling
NASA Astrophysics Data System (ADS)
Bensa, Julien; Gipouloux, Olivier; Kronland-Martinet, Richard
2005-07-01
A difficult issue in the synthesis of piano tones by physical models is to choose the values of the parameters governing the hammer-string model. In fact, these parameters are hard to estimate from static measurements, causing the synthesis sounds to be unrealistic. An original approach that estimates the parameters of a piano model, from the measurement of the string vibration, by minimizing a perceptual criterion is proposed. The minimization process that was used is a combination of a gradient method and a simulated annealing algorithm, in order to avoid convergence problems in case of multiple local minima. The criterion, based on the tristimulus concept, takes into account the spectral energy density in three bands, each allowing particular parameters to be estimated. The optimization process has been run on signals measured on an experimental setup. The parameters thus estimated provided a better sound quality than the one obtained using a global energetic criterion. Both the sound's attack and its brightness were better preserved. This quality gain was obtained for parameter values very close to the initial ones, showing that only slight deviations are necessary to make synthetic sounds closer to the real ones.
On assessing model fit for distribution-free longitudinal models under missing data.
Wu, P; Tu, X M; Kowalski, J
2014-01-15
The generalized estimating equation (GEE), a distribution-free, or semi-parametric, approach for modeling longitudinal data, is used in a wide range of behavioral, psychotherapy, pharmaceutical drug safety, and healthcare-related research studies. Most popular methods for assessing model fit are based on the likelihood function for parametric models, rendering them inappropriate for distribution-free GEE. One rare exception is a score statistic initially proposed by Tsiatis for logistic regression (1980) and later extended by Barnhart and Willamson to GEE (1998). Because GEE only provides valid inference under the missing completely at random assumption and missing values arising in most longitudinal studies do not follow such a restricted mechanism, this GEE-based score test has very limited applications in practice. We propose extensions of this goodness-of-fit test to address missing data under the missing at random assumption, a more realistic model that applies to most studies in practice. We examine the performance of the proposed tests using simulated data and demonstrate the utilities of such tests with data from a real study on geriatric depression and associated medical comorbidities.
An opinion diffusion model with decision-making groups: The influence of the opinion's acceptability
NASA Astrophysics Data System (ADS)
Cheng, Zhichao; Xiong, Yang; Xu, Yiwen
2016-11-01
An opinion dynamic model with decision-making groups was proposed to study the process of adopting new opinions or ideas by individuals. The opinion's acceptability is introduced to distinguish the general character of different opinions. The simulation results on a free-scale network demonstrate that when two opinions have similar acceptability, the opinion supported by more decision-making groups in the beginning will eventually win the support of more agents, whereas an opinion supported by fewer decision-making groups in the beginning may be supported by the majority at the end only if it has better acceptability, and if the tolerance threshold of the society is higher than a specific value.
Genetic algorithm with an improved fitness function for (N)ARX modelling
NASA Astrophysics Data System (ADS)
Chen, Q.; Worden, K.; Peng, P.; Leung, A. Y. T.
2007-02-01
In this article a new fitness function is introduced in an attempt to improve the quality of the auto-regressive with exogenous inputs (ARX) model using a genetic algorithm (GA). The GA is employed to identify the coefficients and the number of time lags of the models of dynamic systems with the new fitness function which is based on the prediction error and the correlation functions between the prediction error and the input and output signals. The new fitness function provides the GA with a better performance in the evolution process. Two examples of the ARX modelling of a linear and a non-linear (NARX) simulated dynamic system are examined using the proposed fitness function.
Network growth models: A behavioural basis for attachment proportional to fitness
NASA Astrophysics Data System (ADS)
Bell, Michael; Perera, Supun; Piraveenan, Mahendrarajah; Bliemer, Michiel; Latty, Tanya; Reid, Chris
2017-02-01
Several growth models have been proposed in the literature for scale-free complex networks, with a range of fitness-based attachment models gaining prominence recently. However, the processes by which such fitness-based attachment behaviour can arise are less well understood, making it difficult to compare the relative merits of such models. This paper analyses an evolutionary mechanism that would give rise to a fitness-based attachment process. In particular, it is proven by analytical and numerical methods that in homogeneous networks, the minimisation of maximum exposure to node unfitness leads to attachment probabilities that are proportional to node fitness. This result is then extended to heterogeneous networks, with supply chain networks being used as an example.
Network growth models: A behavioural basis for attachment proportional to fitness
Bell, Michael; Perera, Supun; Piraveenan, Mahendrarajah; Bliemer, Michiel; Latty, Tanya; Reid, Chris
2017-01-01
Several growth models have been proposed in the literature for scale-free complex networks, with a range of fitness-based attachment models gaining prominence recently. However, the processes by which such fitness-based attachment behaviour can arise are less well understood, making it difficult to compare the relative merits of such models. This paper analyses an evolutionary mechanism that would give rise to a fitness-based attachment process. In particular, it is proven by analytical and numerical methods that in homogeneous networks, the minimisation of maximum exposure to node unfitness leads to attachment probabilities that are proportional to node fitness. This result is then extended to heterogeneous networks, with supply chain networks being used as an example. PMID:28205599
Culture and Parenting: Family Models Are Not One-Size-Fits-All. FPG Snapshot #67
ERIC Educational Resources Information Center
FPG Child Development Institute, 2012
2012-01-01
Family process models guide theories and research about family functioning and child development outcomes. Theory and research, in turn, inform policies and services aimed at families. But are widely accepted models valid across cultural groups? To address these gaps, FPG researchers examined the utility of two family process models for families…
Variable Transformation in Nonlinear Least Squares model Fitting
1981-07-01
Chemistry, Vol. 10, pp. 91-104, 1973. 11. H.J. Britt and R.H. Luecke , "The Estimation of Parameters in Nonlinear, Implicit Models", Technometrics, Vol...respect to the unknown C, 6, and K. This yields the following set of normal equations. 11 H.J, Britt and H.H. Lueake, "The Estimation of...Carbide Corporation Chemicals and Plastics ATTN: H.J. Britt P.O. Box 8361 Charleston, WV 25303 California Institute of Tech Guggenheim Aeronautical
CPOPT : optimization for fitting CANDECOMP/PARAFAC models.
Dunlavy, Daniel M.; Kolda, Tamara Gibson; Acar, Evrim
2008-10-01
Tensor decompositions (e.g., higher-order analogues of matrix decompositions) are powerful tools for data analysis. In particular, the CANDECOMP/PARAFAC (CP) model has proved useful in many applications such chemometrics, signal processing, and web analysis; see for details. The problem of computing the CP decomposition is typically solved using an alternating least squares (ALS) approach. We discuss the use of optimization-based algorithms for CP, including how to efficiently compute the derivatives necessary for the optimization methods. Numerical studies highlight the positive features of our CPOPT algorithms, as compared with ALS and Gauss-Newton approaches.
Fitting meta-analytic structural equation models with complex datasets.
Wilson, Sandra Jo; Polanin, Joshua R; Lipsey, Mark W
2016-06-01
A modification of the first stage of the standard procedure for two-stage meta-analytic structural equation modeling for use with large complex datasets is presented. This modification addresses two common problems that arise in such meta-analyses: (a) primary studies that provide multiple measures of the same construct and (b) the correlation coefficients that exhibit substantial heterogeneity, some of which obscures the relationships between the constructs of interest or undermines the comparability of the correlations across the cells. One component of this approach is a three-level random effects model capable of synthesizing a pooled correlation matrix with dependent correlation coefficients. Another component is a meta-regression that can be used to generate covariate-adjusted correlation coefficients that reduce the influence of selected unevenly distributed moderator variables. A non-technical presentation of these techniques is given, along with an illustration of the procedures with a meta-analytic dataset. Copyright © 2016 John Wiley & Sons, Ltd.
Adaptation in Tunably Rugged Fitness Landscapes: The Rough Mount Fuji Model
Neidhart, Johannes; Szendro, Ivan G.; Krug, Joachim
2014-01-01
Much of the current theory of adaptation is based on Gillespie’s mutational landscape model (MLM), which assumes that the fitness values of genotypes linked by single mutational steps are independent random variables. On the other hand, a growing body of empirical evidence shows that real fitness landscapes, while possessing a considerable amount of ruggedness, are smoother than predicted by the MLM. In the present article we propose and analyze a simple fitness landscape model with tunable ruggedness based on the rough Mount Fuji (RMF) model originally introduced by Aita et al. in the context of protein evolution. We provide a comprehensive collection of results pertaining to the topographical structure of RMF landscapes, including explicit formulas for the expected number of local fitness maxima, the location of the global peak, and the fitness correlation function. The statistics of single and multiple adaptive steps on the RMF landscape are explored mainly through simulations, and the results are compared to the known behavior in the MLM model. Finally, we show that the RMF model can explain the large number of second-step mutations observed on a highly fit first-step background in a recent evolution experiment with a microvirid bacteriophage. PMID:25123507
Modeling of a Parabolic Trough Solar Field for Acceptance Testing: A Case Study
Wagner, M. J.; Mehos, M. S.; Kearney, D. W.; McMahan, A. C.
2011-01-01
As deployment of parabolic trough concentrating solar power (CSP) systems ramps up, the need for reliable and robust performance acceptance test guidelines for the solar field is also amplified. Project owners and/or EPC contractors often require extensive solar field performance testing as part of the plant commissioning process in order to ensure that actual solar field performance satisfies both technical specifications and performance guaranties between the involved parties. Performance test code work is currently underway at the National Renewable Energy Laboratory (NREL) in collaboration with the SolarPACES Task-I activity, and within the ASME PTC-52 committee. One important aspect of acceptance testing is the selection of a robust technology performance model. NREL1 has developed a detailed parabolic trough performance model within the SAM software tool. This model is capable of predicting solar field, sub-system, and component performance. It has further been modified for this work to support calculation at subhourly time steps. This paper presents the methodology and results of a case study comparing actual performance data for a parabolic trough solar field to the predicted results using the modified SAM trough model. Due to data limitations, the methodology is applied to a single collector loop, though it applies to larger subfields and entire solar fields. Special consideration is provided for the model formulation, improvements to the model formulation based on comparison with the collected data, and uncertainty associated with the measured data. Additionally, this paper identifies modeling considerations that are of particular importance in the solar field acceptance testing process and uses the model to provide preliminary recommendations regarding acceptable steady-state testing conditions at the single-loop level.
Marsh, Rebeccah E; Riauka, Terence A; McQuarrie, Steve A
2007-01-01
Increasingly, fractals are being incorporated into pharmacokinetic models to describe transport and chemical kinetic processes occurring in confined and heterogeneous spaces. However, fractal compartmental models lead to differential equations with power-law time-dependent kinetic rate coefficients that currently are not accommodated by common commercial software programs. This paper describes a parameter optimization method for fitting individual pharmacokinetic curves based on a simulated annealing (SA) algorithm, which always converged towards the global minimum and was independent of the initial parameter values and parameter bounds. In a comparison using a classical compartmental model, similar fits by the Gauss-Newton and Nelder-Mead simplex algorithms required stringent initial estimates and ranges for the model parameters. The SA algorithm is ideal for fitting a wide variety of pharmacokinetic models to clinical data, especially those for which there is weak prior knowledge of the parameter values, such as the fractal models.
Modified Likelihood-Based Item Fit Statistics for the Generalized Graded Unfolding Model
ERIC Educational Resources Information Center
Roberts, James S.
2008-01-01
Orlando and Thissen (2000) developed an item fit statistic for binary item response theory (IRT) models known as S-X[superscript 2]. This article generalizes their statistic to polytomous unfolding models. Four alternative formulations of S-X[superscript 2] are developed for the generalized graded unfolding model (GGUM). The GGUM is a…
Hydrothermal germination models: comparison of two data-fitting approaches with probit optimization
Technology Transfer Automated Retrieval System (TEKTRAN)
Probit models for estimating hydrothermal germination rate yield model parameters that have been associated with specific physiological processes. The desirability of linking germination response to seed physiology must be weighed against expectations of model fit and the relative accuracy of predi...
Revisiting a Statistical Shortcoming When Fitting the Langmuir Model to Sorption Data
Technology Transfer Automated Retrieval System (TEKTRAN)
The Langmuir model is commonly used for describing sorption behavior of reactive solutes to surfaces. Fitting the Langmuir model to sorption data requires either the use of nonlinear regression or, alternatively, linear regression using one of the linearized versions of the model. Statistical limit...
Development of a program to fit data to a new logistic model for microbial growth.
Fujikawa, Hiroshi; Kano, Yoshihiro
2009-06-01
Recently we developed a mathematical model for microbial growth in food. The model successfully predicted microbial growth at various patterns of temperature. In this study, we developed a program to fit data to the model with a spread sheet program, Microsoft Excel. Users can instantly get curves fitted to the model by inputting growth data and choosing the slope portion of a curve. The program also could estimate growth parameters including the rate constant of growth and the lag period. This program would be a useful tool for analyzing growth data and further predicting microbial growth.
Ross, Victoria L; Fielding, Kelly S; Louis, Winnifred R
2014-05-01
Faced with a severe drought, the residents of the regional city of Toowoomba, in South East Queensland, Australia were asked to consider a potable wastewater reuse scheme to supplement drinking water supplies. As public risk perceptions and trust have been shown to be key factors in acceptance of potable reuse projects, this research developed and tested a social-psychological model of trust, risk perceptions and acceptance. Participants (N = 380) were surveyed a few weeks before a referendum was held in which residents voted against the controversial scheme. Analysis using structural equation modelling showed that the more community members perceived that the water authority used fair procedures (e.g., consulting with the community and providing accurate information), the greater their sense of shared identity with the water authority. Shared social identity in turn influenced trust via increased source credibility, that is, perceptions that the water authority is competent and has the community's interest at heart. The findings also support past research showing that higher levels of trust in the water authority were associated with lower perceptions of risk, which in turn were associated with higher levels of acceptance, and vice versa. The findings have a practical application for improving public acceptance of potable recycled water schemes.
Tao, Donghua
2008-11-06
This study extended the Technology Acceptance Model (TAM) by examining the roles of two aspects of e-resource characteristics, namely, information quality and system quality, in predicting public health students' intention to use e-resources for completing research paper assignments. Both focus groups and a questionnaire were used to collect data. Descriptive analysis, data screening, and Structural Equation Modeling (SEM) techniques were used for data analysis. The study found that perceived usefulness played a major role in determining students' intention to use e-resources. Perceived usefulness and perceived ease of use fully mediated the impact that information quality and system quality had on behavior intention. The research model enriches the existing technology acceptance literature by extending TAM. Representing two aspects of e-resource characteristics provides greater explanatory information for diagnosing problems of system design, development, and implementation.
NASA Astrophysics Data System (ADS)
Shekhar, Karthik; Ruberman, Claire F.; Ferguson, Andrew L.; Barton, John P.; Kardar, Mehran; Chakraborty, Arup K.
2013-12-01
Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses.
The acceptance of in silico models for REACH: Requirements, barriers, and perspectives
2011-01-01
In silico models have prompted considerable interest and debate because of their potential value in predicting the properties of chemical substances for regulatory purposes. The European REACH legislation promotes innovation and encourages the use of alternative methods, but in practice the use of in silico models is still very limited. There are many stakeholders influencing the regulatory trajectory of quantitative structure-activity relationships (QSAR) models, including regulators, industry, model developers and consultants. Here we outline some of the issues and challenges involved in the acceptance of these methods for regulatory purposes. PMID:21982269
ERIC Educational Resources Information Center
Lee, Yi-Hsuan; Hsieh, Yi-Chuan; Hsu, Chia-Ning
2011-01-01
This study intends to investigate factors affecting business employees' behavioral intentions to use the e-learning system. Combining the innovation diffusion theory (IDT) with the technology acceptance model (TAM), the present study proposes an extended technology acceptance model. The proposed model was tested with data collected from 552…
Atmospheric Properties Of T Dwarfs Inferred From Model Fits At Low Spectral Resolution
NASA Astrophysics Data System (ADS)
Giorla Godfrey, Paige A.; Rice, Emily L.; Filippazzo, Joseph C.; Douglas, Stephanie E.
2016-09-01
Brown dwarf spectral types (M, L, T, Y) correlate with spectral morphology, and generally appear to correspond with decreasing mass and effective temperature (Teff). Model fits to observed spectra suggest, however, that spectral subclasses do not share this monotonic temperature correlation, indicating that secondary parameters (gravity, metallicity, dust) significantly influence spectral morphology. We seekto disentangle the fundamental parameters that underlie the spectral type sequence of the coolest fully populated spectral class of brown dwarfs using atmosphere models. We investigate the relationship between spectral type and best fit model parameters for a sample of over 150 T dwarfs with low resolution (R 75-100) near-infrared ( 0.8-2.5 micron) SpeX Prism spectra. We use synthetic spectra from four model grids (Saumon & Marley 2008, Morley+ 2012, Saumon+ 2012, BT Settl 2013) and a Markov-Chain Monte Carlo (MCMC) analysis to determine robust best fit parameters and their uncertainties. We compare the consistency of each model grid by performing our analysis on the full spectrum and also on individual wavelength bands (Y,J,H,K). We find more consistent results between the J band and full spectrum fits and that our best fit spectral type-Teff results agree with the polynomial relationships of Stephens+2009 and Filippazzo+ 2015 using bolometric luminosities. Our analysis consists of the most extensive low resolution T dwarf model comparison to date, and lays the foundation for interpretation of cool brown dwarf and exoplanet spectra.
2015-01-01
Background Today, people use the Internet to satisfy health-related information and communication needs. In Malaysia, Internet use for health management has become increasingly significant due to the increase in the incidence of chronic diseases, in particular among urban women and their desire to stay healthy. Past studies adopted the Technology Acceptance Model (TAM) and Health Belief Model (HBM) independently to explain Internet use for health-related purposes. Although both the TAM and HBM have their own merits, independently they lack the ability to explain the cognition and the related mechanism in which individuals use the Internet for health purposes. Objective This study aimed to examine the influence of perceived health risk and health consciousness on health-related Internet use based on the HBM. Drawing on the TAM, it also tested the mediating effects of perceived usefulness of the Internet for health information and attitude toward Internet use for health purposes for the relationship between health-related factors, namely perceived health risk and health consciousness on health-related Internet use. Methods Data obtained for the current study were collected using purposive sampling; the sample consisted of women in Malaysia who had Internet access. The partial least squares structural equation modeling method was used to test the research hypotheses developed. Results Perceived health risk (β=.135, t 1999=2.676) and health consciousness (β=.447, t 1999=9.168) had a positive influence on health-related Internet use. Moreover, perceived usefulness of the Internet and attitude toward Internet use for health-related purposes partially mediated the influence of health consciousness on health-related Internet use (β=.025, t 1999=3.234), whereas the effect of perceived health risk on health-related Internet use was fully mediated by perceived usefulness of the Internet and attitude (β=.029, t 1999=3.609). These results suggest the central role of
Soft X-ray spectral fits of Geminga with model neutron star atmospheres
NASA Technical Reports Server (NTRS)
Meyer, R. D.; Pavlov, G. G.; Meszaros, P.
1994-01-01
The spectrum of the soft X-ray pulsar Geminga consists of two components, a softer one which can be interpreted as thermal-like radiation from the surface of the neutron star, and a harder one interpreted as radiation from a polar cap heated by relativistic particles. We have fitted the soft spectrum using a detailed magnetized hydrogen atmosphere model. The fitting parameters are the hydrogen column density, the effective temperature T(sub eff), the gravitational redshift z, and the distance to radius ratio, for different values of the magnetic field B. The best fits for this model are obtained when B less than or approximately 1 x 10(exp 12) G and z lies on the upper boundary of the explored range (z = 0.45). The values of T(sub eff) approximately = (2-3) x 10(exp 5) K are a factor of 2-3 times lower than the value of T(sub eff) obtained for blackbody fits with the same z. The lower T(sub eff) increases the compatibility with some proposed schemes for fast neutrino cooling of neutron stars (NSs) by the direct Urca process or by exotic matter, but conventional cooling cannot be excluded. The hydrogen atmosphere fits also imply a smaller distance to Geminga than that inferred from a blackbody fit. An accurate evaluation of the distance would require a better knowledge of the ROSAT Position Sensitive Proportional Counter (PSPC) response to the low-energy region of the incident spectrum. Our modeling of the soft component with a cooler magnetized atmosphere also implies that the hard-component fit requires a characteristic temperature which is higher (by a factor of approximately 2-3) and a surface area which is smaller (by a factor of 10(exp 3), compared to previous blackbody fits.
Finite population size effects in quasispecies models with single-peak fitness landscape
NASA Astrophysics Data System (ADS)
Saakian, David B.; Deem, Michael W.; Hu, Chin-Kun
2012-04-01
We consider finite population size effects for Crow-Kimura and Eigen quasispecies models with single-peak fitness landscape. We formulate accurately the iteration procedure for the finite population models, then derive the Hamilton-Jacobi equation (HJE) to describe the dynamic of the probability distribution. The steady-state solution of HJE gives the variance of the mean fitness. Our results are useful for understanding the population sizes of viruses in which the infinite population models can give reliable results for biological evolution problems.
An Empirical Assessment of a Technology Acceptance Model for Apps in Medical Education.
Briz-Ponce, Laura; García-Peñalvo, Francisco José
2015-11-01
The evolution and the growth of mobile applications ("apps") in our society is a reality. This general trend is still upward and the app use has also penetrated the medical education community. However, there is a lot of unawareness of the students' and professionals' point of view about introducing "apps" within Medical School curriculum. The aim of this research is to design, implement and verify that the Technology Acceptance Model (TAM) can be employed to measure and explain the acceptance of mobile technology and "apps" within Medical Education. The methodology was based on a survey distributed to students and medical professionals from University of Salamanca. This model explains 46.7% of behavioral intention to use mobile devise or "apps" for learning and will help us to justify and understand the current situation of introducing "apps" into the Medical School curriculum.
Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses
ERIC Educational Resources Information Center
Huang, Guan-Hua; Wang, Su-Mei; Hsu, Chung-Chu
2011-01-01
Statisticians typically estimate the parameters of latent class and latent profile models using the Expectation-Maximization algorithm. This paper proposes an alternative two-stage approach to model fitting. The first stage uses the modified k-means and hierarchical clustering algorithms to identify the latent classes that best satisfy the…
Status Characteristics and Expectation States: Fitting and Testing a Recent Model.
ERIC Educational Resources Information Center
Fox, John; Moore, James C., Jr.
1979-01-01
Fourteen experimental studies were reviewed using linear model of Berger et al. The model fits the data from these experiments remarkably well. These results demonstrate the utility and apparent validity of this theory of status-organizing processes. (Author/RD)
Genetic Model Fitting in IQ, Assortative Mating & Components of IQ Variance.
ERIC Educational Resources Information Center
Capron, Christiane; Vetta, Adrian R.; Vetta, Atam
1998-01-01
The biometrical school of scientists who fit models to IQ data traces their intellectual ancestry to R. Fisher (1918), but their genetic models have no predictive value. Fisher himself was critical of the concept of heritability, because assortative mating, such as for IQ, introduces complexities into the study of a genetic trait. (SLD)
Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes
ERIC Educational Resources Information Center
Leite, Walter L.; Stapleton, Laura M.
2011-01-01
In this study, the authors compared the likelihood ratio test and fit indexes for detection of misspecifications of growth shape in latent growth models through a simulation study and a graphical analysis. They found that the likelihood ratio test, MFI, and root mean square error of approximation performed best for detecting model misspecification…
An Assessment of the Nonparametric Approach for Evaluating the Fit of Item Response Models
ERIC Educational Resources Information Center
Liang, Tie; Wells, Craig S.; Hambleton, Ronald K.
2014-01-01
As item response theory has been more widely applied, investigating the fit of a parametric model becomes an important part of the measurement process. There is a lack of promising solutions to the detection of model misfit in IRT. Douglas and Cohen introduced a general nonparametric approach, RISE (Root Integrated Squared Error), for detecting…
Amarathunga, Jayani P; Schuetz, Michael A; Yarlagadda, Prasad Kvd; Schmutz, Beat
2014-12-01
Intramedullary nailing is the standard fixation method for displaced diaphyseal fractures of the tibia. An optimal nail design should both facilitate insertion and anatomically fit the bone geometry at its final position in order to reduce the risk of stress fractures and malalignments. Due to the nonexistence of suitable commercial software, we developed a software tool for the automated fit assessment of nail designs. Furthermore, we demonstrated that an optimised nail, which fits better at the final position, is also easier to insert. Three-dimensional models of two nail designs and 20 tibiae were used. The fitting was quantified in terms of surface area, maximum distance, sum of surface areas and sum of maximum distances by which the nail was protruding into the cortex. The software was programmed to insert the nail into the bone model and to quantify the fit at defined increment levels. On average, the misfit during the insertion in terms of the four fitting parameters was smaller for the Expert Tibial Nail Proximal bend (476.3 mm(2), 1.5 mm, 2029.8 mm(2), 6.5 mm) than the Expert Tibial Nail (736.7 mm(2), 2.2 mm, 2491.4 mm(2), 8.0 mm). The differences were statistically significant (p ≤ 0.05). The software could be used by nail implant manufacturers for the purpose of implant design validation.
Development and design of a late-model fitness test instrument based on LabView
NASA Astrophysics Data System (ADS)
Xie, Ying; Wu, Feiqing
2010-12-01
Undergraduates are pioneers of China's modernization program and undertake the historic mission of rejuvenating our nation in the 21st century, whose physical fitness is vital. A smart fitness test system can well help them understand their fitness and health conditions, thus they can choose more suitable approaches and make practical plans for exercising according to their own situation. following the future trends, a Late-model fitness test Instrument based on LabView has been designed to remedy defects of today's instruments. The system hardware consists of fives types of sensors with their peripheral circuits, an acquisition card of NI USB-6251 and a computer, while the system software, on the basis of LabView, includes modules of user register, data acquisition, data process and display, and data storage. The system, featured by modularization and an open structure, is able to be revised according to actual needs. Tests results have verified the system's stability and reliability.
Space charge modeling in electron-beam irradiated polyethylene: Fitting model and experiments
Le Roy, S.; Laurent, C.; Teyssedre, G.; Baudoin, F.; Griseri, V.
2012-07-15
A numerical model for describing charge accumulation in electron-beam irradiated low density polyethylene has been put forward recently. It encompasses the generation of positive and negative charges due to impinging electrons and their transport in the insulation. However, the model was not optimized to fit all the data available regarding space charge dynamics obtained using up-to-date pulsed electro-acoustic techniques. In the present approach, model outputs are compared with experimental space charge distribution obtained during irradiation and post-irradiation, the irradiated samples being in short circuit conditions or with the irradiated surface at a floating potential. A unique set of parameters have been used for all the simulations, and it encompasses the transport parameters already optimized for charge transport in polyethylene under an external electric field. The model evolution in itself consists in describing the recombination between positive and negative charges according to the Langevin formula, which is physically more accurate than the previous description and has the advantage of reducing the number of adjustable parameters of the model. This also provides a better description of the experimental behavior underlining the importance of recombination processes in irradiated materials.
Space charge modeling in electron-beam irradiated polyethylene: Fitting model and experiments
NASA Astrophysics Data System (ADS)
Le Roy, S.; Baudoin, F.; Griseri, V.; Laurent, C.; Teyssèdre, G.
2012-07-01
A numerical model for describing charge accumulation in electron-beam irradiated low density polyethylene has been put forward recently. It encompasses the generation of positive and negative charges due to impinging electrons and their transport in the insulation. However, the model was not optimized to fit all the data available regarding space charge dynamics obtained using up-to-date pulsed electro-acoustic techniques. In the present approach, model outputs are compared with experimental space charge distribution obtained during irradiation and post-irradiation, the irradiated samples being in short circuit conditions or with the irradiated surface at a floating potential. A unique set of parameters have been used for all the simulations, and it encompasses the transport parameters already optimized for charge transport in polyethylene under an external electric field. The model evolution in itself consists in describing the recombination between positive and negative charges according to the Langevin formula, which is physically more accurate than the previous description and has the advantage of reducing the number of adjustable parameters of the model. This also provides a better description of the experimental behavior underlining the importance of recombination processes in irradiated materials.
Fast and exact Newton and Bidirectional fitting of Active Appearance Models.
Kossaifi, Jean; Tzimiropoulos, Yorgos; Pantic, Maja
2016-12-21
Active Appearance Models (AAMs) are generative models of shape and appearance that have proven very attractive for their ability to handle wide changes in illumination, pose and occlusion when trained in the wild, while not requiring large training dataset like regression-based or deep learning methods. The problem of fitting an AAM is usually formulated as a non-linear least squares one and the main way of solving it is a standard Gauss-Newton algorithm. In this paper we extend Active Appearance Models in two ways: we first extend the Gauss-Newton framework by formulating a bidirectional fitting method that deforms both the image and the template to fit a new instance. We then formulate a second order method by deriving an efficient Newton method for AAMs fitting. We derive both methods in a unified framework for two types of Active Appearance Models, holistic and part-based, and additionally show how to exploit the structure in the problem to derive fast yet exact solutions. We perform a thorough evaluation of all algorithms on three challenging and recently annotated inthe- wild datasets, and investigate fitting accuracy, convergence properties and the influence of noise in the initialisation. We compare our proposed methods to other algorithms and show that they yield state-of-the-art results, out-performing other methods while having superior convergence properties.
Shot model parameters for Cygnus X-1 through phase portrait fitting
NASA Technical Reports Server (NTRS)
Lochner, James C.; Swank, J. H.; Szymkowiak, A. E.
1991-01-01
Shot models for systems having about 1/f power density spectrum are developed by utilizing a distribution of shot durations. Parameters of the distribution are determined by fitting the power spectrum either with analytic forms for the spectrum of a shot model with a given shot profile, or with the spectrum derived from numerical realizations of trial shot models. The shot fraction is specified by fitting the phase portrait, which is a plot of intensity at a given time versus intensity at a delayed time and in principle is sensitive to different shot profiles. These techniques have been extensively applied to the X-ray variability of Cygnus X-1, using HEAO 1 A-2 and an Exosat ME observation. The power spectra suggest models having characteristic shot durations lasting from milliseconds to a few seconds, while the phase portrait fits give shot fractions of about 50 percent. Best fits to the portraits are obtained if the amplitude of the shot is a power-law function of the duration of the shot. These fits prefer shots having a symmetric exponential rise and decay. Results are interpreted in terms of a distribution of magnetic flares in the accretion disk.
NASA Astrophysics Data System (ADS)
Shan, Bonan; Wang, Jiang; Zhang, Lvxia; Deng, Bin; Wei, Xile
2017-02-01
In order to fit neural model’s spiking features to electrophysiological recordings, in this paper, a fitting framework based on particle swarm optimization (PSO) algorithm is proposed to estimate the model parameters in an augmented multi-timescale adaptive threshold (AugMAT) model. PSO algorithm is an advanced evolutionary calculation method based on iteration. Selecting a reasonable criterion function will ensure the effectiveness of PSO algorithm. In this work, firing rate information is used as the main spiking feature and the estimation error of firing rate is selected as the criterion for fitting. A series of simulations are presented to verify the performance of the framework. The first step is model validation; an artificial training data is introduced to test the fitting procedure. Then we talk about the suitable PSO parameters, which exhibit adequate compromise between speediness and accuracy. Lastly, this framework is used to fit the electrophysiological recordings, after three adjustment steps, the features of experimental data are translated into realistic spiking neuron model.
The Predicting Model of E-commerce Site Based on the Ideas of Curve Fitting
NASA Astrophysics Data System (ADS)
Tao, Zhang; Li, Zhang; Dingjun, Chen
On the basis of the idea of the second multiplication curve fitting, the number and scale of Chinese E-commerce site is analyzed. A preventing increase model is introduced in this paper, and the model parameters are solved by the software of Matlab. The validity of the preventing increase model is confirmed though the numerical experiment. The experimental results show that the precision of preventing increase model is ideal.
Curve fitting toxicity test data: Which comes first, the dose response or the model?
Gully, J.; Baird, R.; Bottomley, J.
1995-12-31
The probit model frequently does not fit the concentration-response curve of NPDES toxicity test data and non-parametric models must be used instead. The non-parametric models, trimmed Spearman-Karber, IC{sub p}, and linear interpolation, all require a monotonic concentration-response. Any deviation from a monotonic response is smoothed to obtain the desired concentration-response characteristics. Inaccurate point estimates may result from such procedures and can contribute to imprecision in replicate tests. The following study analyzed reference toxicant and effluent data from giant kelp (Macrocystis pyrifera), purple sea urchin (Strongylocentrotus purpuratus), red abalone (Haliotis rufescens), and fathead minnow (Pimephales promelas) bioassays using commercially available curve fitting software. The purpose was to search for alternative parametric models which would reduce the use of non-parametric models for point estimate analysis of toxicity data. Two non-linear models, power and logistic dose-response, were selected as possible alternatives to the probit model based upon their toxicological plausibility and ability to model most data sets examined. Unlike non-parametric procedures, these and all parametric models can be statistically evaluated for fit and significance. The use of the power or logistic dose response models increased the percentage of parametric model fits for each protocol and toxicant combination examined. The precision of the selected non-linear models was also compared with the EPA recommended point estimation models at several effect.levels. In general, precision of the alternative models was equal to or better than the traditional methods. Finally, use of the alternative models usually produced more plausible point estimates in data sets where the effects of smoothing and non-parametric modeling made the point estimate results suspect.
Model fit to experimental data for foam-assisted deep vadose zone remediation.
Roostapour, A; Lee, G; Zhong, L; Kam, S I
2014-01-15
This study investigates how a foam model, developed in Roostapour and Kam [1], can be applied to make a fit to a set of existing laboratory flow experiments in an application relevant to deep vadose zone remediation. This study reveals a few important insights regarding foam-assisted deep vadose zone remediation: (i) the mathematical framework established for foam modeling can fit typical flow experiments matching wave velocities, saturation history, and pressure responses; (ii) the set of input parameters may not be unique for the fit, and therefore conducting experiments to measure basic model parameters related to relative permeability, initial and residual saturations, surfactant adsorption and so on should not be overlooked; and (iii) gas compressibility plays an important role for data analysis, thus should be handled carefully in laboratory flow experiments. Foam kinetics, causing foam texture to reach its steady-state value slowly, may impose additional complications.
Anshel, Mark H; Brinthaupt, Thomas M; Kang, Minsoo
2010-01-01
This study examined the effect of a 10-week wellness program on changes in physical fitness and mental well-being. The conceptual framework for this study was the Disconnected Values Model (DVM). According to the DVM, detecting the inconsistencies between negative habits and values (e.g., health, family, faith, character) and concluding that these "disconnects" are unacceptable promotes the need for health behavior change. Participants were 164 full-time employees at a university in the southeastern U.S. The program included fitness coaching and a 90-minute orientation based on the DVM. Multivariate Mixed Model analyses indicated significantly improved scores from pre- to post-intervention on selected measures of physical fitness and mental well-being. The results suggest that the Disconnected Values Model provides an effective cognitive-behavioral approach to generating health behavior change in a 10-week workplace wellness program.
ERIC Educational Resources Information Center
Wu, Xiaoyu; Gao, Yuan
2011-01-01
This paper applies the extended technology acceptance model (exTAM) in information systems research to the use of clickers in student learning. The technology acceptance model (TAM) posits that perceived ease of use and perceived usefulness of technology influence users' attitudes toward using and intention to use technology. Research subsequent…
Optimization of Active Muscle Force-Length Models Using Least Squares Curve Fitting.
Mohammed, Goran Abdulrahman; Hou, Ming
2016-03-01
The objective of this paper is to propose an asymmetric Gaussian function as an alternative to the existing active force-length models, and to optimize this model along with several other existing models by using the least squares curve fitting method. The minimal set of coefficients is identified for each of these models to facilitate the least squares curve fitting. Sarcomere simulated data and one set of rabbits extensor digitorum II experimental data are used to illustrate optimal curve fitting of the selected force-length functions. The results shows that all the curves fit reasonably well with the simulated and experimental data, while the Gordon-Huxley-Julian model and asymmetric Gaussian function are better than other functions in terms of statistical test scores root mean squared error and R-squared. However, the differences in RMSE scores are insignificant (0.3-6%) for simulated data and (0.2-5%) for experimental data. The proposed asymmetric Gaussian model and the method of parametrization of this and the other force-length models mentioned above can be used in the studies on active force-length relationships of skeletal muscles that generate forces to cause movements of human and animal bodies.
A goodness-of-fit test for occupancy models with correlated within-season revisits
Wright, Wilson; Irvine, Kathryn M.; Rodhouse, Thomas J.
2016-01-01
Occupancy modeling is important for exploring species distribution patterns and for conservation monitoring. Within this framework, explicit attention is given to species detection probabilities estimated from replicate surveys to sample units. A central assumption is that replicate surveys are independent Bernoulli trials, but this assumption becomes untenable when ecologists serially deploy remote cameras and acoustic recording devices over days and weeks to survey rare and elusive animals. Proposed solutions involve modifying the detection-level component of the model (e.g., first-order Markov covariate). Evaluating whether a model sufficiently accounts for correlation is imperative, but clear guidance for practitioners is lacking. Currently, an omnibus goodnessof- fit test using a chi-square discrepancy measure on unique detection histories is available for occupancy models (MacKenzie and Bailey, Journal of Agricultural, Biological, and Environmental Statistics, 9, 2004, 300; hereafter, MacKenzie– Bailey test). We propose a join count summary measure adapted from spatial statistics to directly assess correlation after fitting a model. We motivate our work with a dataset of multinight bat call recordings from a pilot study for the North American Bat Monitoring Program. We found in simulations that our join count test was more reliable than the MacKenzie–Bailey test for detecting inadequacy of a model that assumed independence, particularly when serial correlation was low to moderate. A model that included a Markov-structured detection-level covariate produced unbiased occupancy estimates except in the presence of strong serial correlation and a revisit design consisting only of temporal replicates. When applied to two common bat species, our approach illustrates that sophisticated models do not guarantee adequate fit to real data, underscoring the importance of model assessment. Our join count test provides a widely applicable goodness-of-fit test and
Mathematical Modeling of Allelopathy. III. A Model for Curve-Fitting Allelochemical Dose Responses
Liu, De Li; An, Min; Johnson, Ian R.; Lovett, John V.
2003-01-01
Bioassay techniques are often used to study the effects of allelochemicals on plant processes, and it is generally observed that the processes are stimulated at low allelochemical concentrations and inhibited as the concentrations increase. A simple empirical model is presented to analyze this type of response. The stimulation-inhibition properties of allelochemical-dose responses can be described by the parameters in the model. The indices, p% reductions, are calculated to assess the allelochemical effects. The model is compared with experimental data for the response of lettuce seedling growth to Centaurepensin, the olfactory response of weevil larvae to α-terpineol, and the responses of annual ryegrass (Lolium multiflorum Lam.), creeping red fescue (Festuca rubra L., cv. Ensylva), Kentucky bluegrass (Poa pratensis L., cv. Kenblue), perennial ryegrass (L. perenne L., cv. Manhattan), and Rebel tall fescue (F. arundinacea Schreb) seedling growth to leachates of Rebel and Kentucky 31 tall fescue. The results show that the model gives a good description to observations and can be used to fit a wide range of dose responses. Assessments of the effects of leachates of Rebel and Kentucky 31 tall fescue clearly differentiate the properties of the allelopathic sources and the relative sensitivities of indicators such as the length of root and leaf. PMID:19330111
Mathematical Modeling of Allelopathy. III. A Model for Curve-Fitting Allelochemical Dose Responses.
Liu, De Li; An, Min; Johnson, Ian R; Lovett, John V
2003-01-01
Bioassay techniques are often used to study the effects of allelochemicals on plant processes, and it is generally observed that the processes are stimulated at low allelochemical concentrations and inhibited as the concentrations increase. A simple empirical model is presented to analyze this type of response. The stimulation-inhibition properties of allelochemical-dose responses can be described by the parameters in the model. The indices, p% reductions, are calculated to assess the allelochemical effects. The model is compared with experimental data for the response of lettuce seedling growth to Centaurepensin, the olfactory response of weevil larvae to alpha-terpineol, and the responses of annual ryegrass (Lolium multiflorum Lam.), creeping red fescue (Festuca rubra L., cv. Ensylva), Kentucky bluegrass (Poa pratensis L., cv. Kenblue), perennial ryegrass (L. perenne L., cv. Manhattan), and Rebel tall fescue (F. arundinacea Schreb) seedling growth to leachates of Rebel and Kentucky 31 tall fescue. The results show that the model gives a good description to observations and can be used to fit a wide range of dose responses. Assessments of the effects of leachates of Rebel and Kentucky 31 tall fescue clearly differentiate the properties of the allelopathic sources and the relative sensitivities of indicators such as the length of root and leaf.
An, Ji-Young; Hayman, Laura L; Panniers, Teresa; Carty, Barbara
2007-01-01
About 110 million American adults are looking for health information and services on the Internet. Identification of the factors influencing healthcare consumers' technology acceptance is requisite to understanding their acceptance and usage behavior of online health information and related services. The purpose of this article is to describe the development of the Information and Communication Technology Acceptance Model (ICTAM). From the literature reviewed, ICTAM was developed with emphasis on integrating multidisciplinary perspectives from divergent frameworks and empirical findings into a unified model with regard to healthcare consumers' acceptance and usage behavior of information and services on the Internet.
Efficient occupancy model-fitting for extensive citizen-science data.
Dennis, Emily B; Morgan, Byron J T; Freeman, Stephen N; Ridout, Martin S; Brereton, Tom M; Fox, Richard; Powney, Gary D; Roy, David B
2017-01-01
Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved using standard computers. This is especially important when models need to be fitted each year, typically for many different species, as with British butterflies for example. Using both real and simulated data we demonstrate that the two approaches, with and without random effects, can result in similar conclusions regarding trends. There are many advantages to classical model-fitting, including the ability to compare a range of alternative models, identify appropriate covariates and assess model fit, using standard tools of maximum likelihood. In addition, modelling in terms of covariates provides opportunities for understanding the ecological processes that are in operation. We show that there is even greater potential; the classical approach allows us to construct regional indices simply, which indicate how changes in occupancy typically vary over a species' range. In addition we are also able to construct dynamic occupancy maps, which provide a novel, modern tool for examining temporal changes in species distribution. These new developments may be applied to a wide range of taxa, and are valuable at a time of climate change. They also have the potential to motivate citizen
Efficient occupancy model-fitting for extensive citizen-science data
Morgan, Byron J. T.; Freeman, Stephen N.; Ridout, Martin S.; Brereton, Tom M.; Fox, Richard; Powney, Gary D.; Roy, David B.
2017-01-01
Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved using standard computers. This is especially important when models need to be fitted each year, typically for many different species, as with British butterflies for example. Using both real and simulated data we demonstrate that the two approaches, with and without random effects, can result in similar conclusions regarding trends. There are many advantages to classical model-fitting, including the ability to compare a range of alternative models, identify appropriate covariates and assess model fit, using standard tools of maximum likelihood. In addition, modelling in terms of covariates provides opportunities for understanding the ecological processes that are in operation. We show that there is even greater potential; the classical approach allows us to construct regional indices simply, which indicate how changes in occupancy typically vary over a species’ range. In addition we are also able to construct dynamic occupancy maps, which provide a novel, modern tool for examining temporal changes in species distribution. These new developments may be applied to a wide range of taxa, and are valuable at a time of climate change. They also have the potential to motivate citizen
ERIC Educational Resources Information Center
Tarhini, Ali; Hone, Kate; Liu, Xiaohui
2014-01-01
The success of an e-learning intervention depends to a considerable extent on student acceptance and use of the technology. Therefore, it has become imperative for practitioners and policymakers to understand the factors affecting the user acceptance of e-learning systems in order to enhance the students' learning experience. Based on an extended…
Estimating the pi* goodness of fit index for finite mixtures of item response models.
Revuelta, Javier
2008-05-01
Testing the fit of finite mixture models is a difficult task, since asymptotic results on the distribution of likelihood ratio statistics do not hold; for this reason, alternative statistics are needed. This paper applies the pi* goodness of fit statistic to finite mixture item response models. The pi* statistic assumes that the population is composed of two subpopulations - those that follow a parametric model and a residual group outside the model; pi* is defined as the proportion of population in the residual group. The population was divided into two or more groups, or classes. Several groups followed an item response model and there was also a residual group. The paper presents maximum likelihood algorithms for estimating item parameters, the probabilities of the groups and pi*. The paper also includes a simulation study on goodness of recovery for the two- and three-parameter logistic models and an example with real data from a multiple choice test.
ERIC Educational Resources Information Center
Teo, Timothy
2016-01-01
The aim of this study is to examine the factors that influenced the use of Facebook among university students. Using an extended technology acceptance model (TAM) with emotional attachment (EA) as an external variable, a sample of 498 students from a public-funded Thailand university were surveyed on their responses to five variables hypothesized…
Comparing PyMorph and SDSS photometry. I. Background sky and model fitting effects
NASA Astrophysics Data System (ADS)
Fischer, J.-L.; Bernardi, M.; Meert, A.
2017-01-01
A number of recent estimates of the total luminosities of galaxies in the SDSS are significantly larger than those reported by the SDSS pipeline. This is because of a combination of three effects: one is simply a matter of defining the scale out to which one integrates the fit when defining the total luminosity, and amounts on average to ≤0.1 mags even for the most luminous galaxies. The other two are less trivial and tend to be larger; they are due to differences in how the background sky is estimated and what model is fit to the surface brightness profile. We show that PyMorph sky estimates are fainter than those of the SDSS DR7 or DR9 pipelines, but are in excellent agreement with the estimates of Blanton et al. (2011). Using the SDSS sky biases luminosities by more than a few tenths of a magnitude for objects with half-light radii ≥7 arcseconds. In the SDSS main galaxy sample these are typically luminous galaxies, so they are not necessarily nearby. This bias becomes worse when allowing the model more freedom to fit the surface brightness profile. When PyMorph sky values are used, then two component Sersic-Exponential fits to E+S0s return more light than single component deVaucouleurs fits (up to ˜0.2 mag), but less light than single Sersic fits (0.1 mag). Finally, we show that PyMorph fits of Meert et al. (2015) to DR7 data remain valid for DR9 images. Our findings show that, especially at large luminosities, these PyMorph estimates should be preferred to the SDSS pipeline values.
Clavijo-Baque, Sabrina; Bozinovic, Francisco
2012-01-01
The origin of endothermy is a puzzling phenomenon in the evolution of vertebrates. To address this issue several explicative models have been proposed. The main models proposed for the origin of endothermy are the aerobic capacity, the thermoregulatory and the parental care models. Our main proposal is that to compare the alternative models, a critical aspect is to determine how strongly natural selection was influenced by body temperature, and basal and maximum metabolic rates during the evolution of endothermy. We evaluate these relationships in the context of three main hypotheses aimed at explaining the evolution of endothermy, namely the parental care hypothesis and two hypotheses related to the thermoregulatory model (thermogenic capacity and higher body temperature models). We used data on basal and maximum metabolic rates and body temperature from 17 rodent populations, and used intrinsic population growth rate (Rmax) as a global proxy of fitness. We found greater support for the thermogenic capacity model of the thermoregulatory model. In other words, greater thermogenic capacity is associated with increased fitness in rodent populations. To our knowledge, this is the first test of the fitness consequences of the thermoregulatory and parental care models for the origin of endothermy. PMID:22606328
Montes, Richard O
2012-03-01
Pharmaceutical manufacturing processes consist of a series of stages (e.g., reaction, workup, isolation) to generate the active pharmaceutical ingredient (API). Outputs at intermediate stages (in-process control) and API need to be controlled within acceptance criteria to assure final drug product quality. In this paper, two methods based on tolerance interval to derive such acceptance criteria will be evaluated. The first method is serial worst case (SWC), an industry risk minimization strategy, wherein input materials and process parameters of a stage are fixed at their worst-case settings to calculate the maximum level expected from the stage. This maximum output then becomes input to the next stage wherein process parameters are again fixed at worst-case setting. The procedure is serially repeated throughout the process until the final stage. The calculated limits using SWC can be artificially high and may not reflect the actual process performance. The second method is the variation transmission (VT) using autoregressive model, wherein variation transmitted up to a stage is estimated by accounting for the recursive structure of the errors at each stage. Computer simulations at varying extent of variation transmission and process stage variability are performed. For the scenarios tested, VT method is demonstrated to better maintain the simulated confidence level and more precisely estimate the true proportion parameter than SWC. Real data examples are also presented that corroborate the findings from the simulation. Overall, VT is recommended for setting acceptance criteria in a multi-staged pharmaceutical manufacturing process.
Kloeckner, Frederik; Farkas, Robert; Franken, Tobias; Schmitz-Rode, Thomas
2014-04-01
Documentation of research data plays a key role in the biomedical engineering innovation processes. It makes an important contribution to the protection of intellectual property, the traceability of results and fulfilling the regulatory requirement. Because of the increasing digitalization in laboratories, an electronic alternative to the commonly-used paper-bound notebooks could contribute to the production of sophisticated documentation. However, compared to in an industrial environment, the use of electronic laboratory notebooks is not widespread in academic laboratories. Little is known about the acceptance of an electronic documentation system and the underlying reasons for this. Thus, this paper aims to establish a prediction model on the potential preference and acceptance of scientists either for paper-based or electronic documentation. The underlying data for the analysis originate from an online survey of 101 scientists in industrial, academic and clinical environments. Various parameters were analyzed to identify crucial factors for the system preference using binary logistic regression. The analysis showed significant dependency between the documentation system preference and the supposed workload associated with the documentation system (p<0.006; odds ratio=58.543) and an additional personal component. Because of the dependency of system choice on specific parameters it is possible to predict the acceptance of an electronic laboratory notebook before implementation.
Velasco, Jose; Pizarro, Daniel; Macias-Guarasa, Javier
2012-10-15
This paper presents a novel approach for indoor acoustic source localization using sensor arrays. The proposed solution starts by defining a generative model, designed to explain the acoustic power maps obtained by Steered Response Power (SRP) strategies. An optimization approach is then proposed to fit the model to real input SRP data and estimate the position of the acoustic source. Adequately fitting the model to real SRP data, where noise and other unmodelled effects distort the ideal signal, is the core contribution of the paper. Two basic strategies in the optimization are proposed. First, sparse constraints in the parameters of the model are included, enforcing the number of simultaneous active sources to be limited. Second, subspace analysis is used to filter out portions of the input signal that cannot be explained by the model. Experimental results on a realistic speech database show statistically significant localization error reductions of up to 30% when compared with the SRP-PHAT strategies.
Aeroelastic modeling for the FIT team F/A-18 simulation
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Wieseman, Carol D.
1989-01-01
Some details of the aeroelastic modeling of the F/A-18 aircraft done for the Functional Integration Technology (FIT) team's research in integrated dynamics modeling and how these are combined with the FIT team's integrated dynamics model are described. Also described are mean axis corrections to elastic modes, the addition of nonlinear inertial coupling terms into the equations of motion, and the calculation of internal loads time histories using the integrated dynamics model in a batch simulation program. A video tape made of a loads time history animation was included as a part of the oral presentation. Also discussed is work done in one of the areas of unsteady aerodynamic modeling identified as needing improvement, specifically, in correction factor methodologies for improving the accuracy of stability derivatives calculated with a doublet lattice code.
Velasco, Jose; Pizarro, Daniel; Macias-Guarasa, Javier
2012-01-01
This paper presents a novel approach for indoor acoustic source localization using sensor arrays. The proposed solution starts by defining a generative model, designed to explain the acoustic power maps obtained by Steered Response Power (SRP) strategies. An optimization approach is then proposed to fit the model to real input SRP data and estimate the position of the acoustic source. Adequately fitting the model to real SRP data, where noise and other unmodelled effects distort the ideal signal, is the core contribution of the paper. Two basic strategies in the optimization are proposed. First, sparse constraints in the parameters of the model are included, enforcing the number of simultaneous active sources to be limited. Second, subspace analysis is used to filter out portions of the input signal that cannot be explained by the model. Experimental results on a realistic speech database show statistically significant localization error reductions of up to 30% when compared with the SRP-PHAT strategies. PMID:23202021
Orruño, Estibalitz; Gagnon, Marie Pierre; Asua, José; Ben Abdeljelil, Anis
2011-01-01
We examined the main factors affecting the intention of physicians to use teledermatology using a modified Technology Acceptance Model (TAM). The investigation was carried out during a teledermatology pilot study conducted in Spain. A total of 276 questionnaires were sent to physicians by email and 171 responded (62%). Cronbach's alpha was acceptably high for all constructs. Theoretical variables were well correlated with each other and with the dependent variable (Intention to Use). Logistic regression indicated that the original TAM model was good at predicting physicians' intention to use teledermatology and that the variables Perceived Usefulness and Perceived Ease of Use were both significant (odds ratios of 8.4 and 7.4, respectively). When other theoretical variables were added, the model was still significant and it also became more powerful. However, the only significant predictor in the modified model was Facilitators with an odds ratio of 9.9. Thus the TAM was good at predicting physicians' intention to use teledermatology. However, the most important variable was the perception of Facilitators to using the technology (e.g. infrastructure, training and support).
McDonald, Eileen; Lamb, Amanda; Grillo, Barbara; Lucas, Lee; Miesfeldt, Susan
2014-04-01
This work examined acceptability of cancer genetic counseling models of service delivery among Maine residents at risk for hereditary cancer susceptibility disorders. Pre-counseling, participants ranked characteristics reflecting models of care from most to least important including: mode-of-communication (in-person versus telegenetics), provider level of training (genetic specialty versus some training/experience), delivery format (one-on-one versus group counseling), and location (local versus tertiary service requiring travel). Associations between models of care characteristic rankings and patient characteristics, including rural residence, perceived cancer risk, and perceived risk for a hereditary cancer risk susceptibility disorder were examined. A total of 149/300 (49.7% response rate) individuals from 11/16 Maine counties responded; 30.8% were from rural counties; 92.2% indicated that an important/the most important model of care characteristic is provider professional qualifications. Among other characteristics, 65.1% ranked one-on-one counseling as important/the most important. In-person and local counseling were ranked the two least important characteristics (51.8% and 52.1% important/the most important, respectively). Responses did not vary by patient characteristics with the exception of greater acceptance of group counseling among those at perceived high personal cancer risk. Cancer telegenetic services hold promise for access to expert providers in a one-on-one format for rurally remote clients.
Computational model of collective nest selection by ants with heterogeneous acceptance thresholds.
Masuda, Naoki; O'shea-Wheller, Thomas A; Doran, Carolina; Franks, Nigel R
2015-06-01
Collective decision-making is a characteristic of societies ranging from ants to humans. The ant Temnothorax albipennis is known to use quorum sensing to collectively decide on a new home; emigration to a new nest site occurs when the number of ants favouring the new site becomes quorate. There are several possible mechanisms by which ant colonies can select the best nest site among alternatives based on a quorum mechanism. In this study, we use computational models to examine the implications of heterogeneous acceptance thresholds across individual ants in collective nest choice behaviour. We take a minimalist approach to develop a differential equation model and a corresponding non-spatial agent-based model. We show, consistent with existing empirical evidence, that heterogeneity in acceptance thresholds is a viable mechanism for efficient nest choice behaviour. In particular, we show that the proposed models show speed-accuracy trade-offs and speed-cohesion trade-offs when we vary the number of scouts or the quorum threshold.
Model fitting of the kinematics of ten superluminal components in blazar 3C 279
NASA Astrophysics Data System (ADS)
Qian, Shan-Jie
2013-07-01
The kinematics of ten superluminal components (C11- C16, C18, C20, C21 and C24) of blazar 3C 279 are studied from VLBI observations. It is shown that their initial trajectory, distance from the core and apparent speed can be well fitted by the precession model proposed by Qian. Combined with the results of the model fit for the six superluminal components (C3, C4, C7a, C8, C9 and C10) already published, the kinematics of sixteen superluminal components can now be consistently interpreted in the precession scenario with their ejection times spanning more than 25 yr (or more than one precession period). The results from model fitting show the possible existence of a common precessing trajectory for these knots within a projected core distance of ~0.2-0.4 mas. In the framework of the jet-precession scenario, we can, for the first time, identify three classes of trajectories which are characterized by their collimation parameters. These different trajectories could be related to the helical structure of magnetic fields in the jet. Through fitting the model, the bulk Lorentz factor, Doppler factor and viewing angle of these knots are derived. It is found that there is no evidence for any correlation between the bulk Lorentz factor of the components and their precession phase (or ejection time). In a companion paper, the kinematics of another seven components (C5a, C6, C7, C17, C19, C22 and C23) have been derived from model fitting, and a binary black-hole/jet scenario was envisaged. The precession model proposed by Qian would be useful for understanding the kinematics of superluminal components in blazar 3C 279 derived from VLBI observations, by disentangling different mechanisms and ingredients. More generally, it might also be helpful for studying the mechanism of jet swing (wobbling) in other blazars.
ERIC Educational Resources Information Center
McCluskey, Ken W.
2010-01-01
This article presents the author's comments on Hisham B. Ghassib's "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?" Ghassib's article focuses on the transformation of science from pre-modern times to the present. Ghassib (2010) notes that, unlike in an earlier era when the economy depended on static…
ERIC Educational Resources Information Center
Harris, Carole Ruth
2010-01-01
This article presents the author's comments on Hisham Ghassib's article entitled "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?" In his article, Ghassib (2010) provides an overview of the philosophical foundations that led to exact science, its role in what was later to become a driving force in the modern…
Universal Screening for Emotional and Behavioral Problems: Fitting a Population-Based Model
ERIC Educational Resources Information Center
Schanding, G. Thomas, Jr.; Nowell, Kerri P.
2013-01-01
Schools have begun to adopt a population-based method to conceptualizing assessment and intervention of students; however, little empirical evidence has been gathered to support this shift in service delivery. The present study examined the fit of a population-based model in identifying students' behavioral and emotional functioning using a…
Super Kids--Superfit. A Comprehensive Fitness Intervention Model for Elementary Schools.
ERIC Educational Resources Information Center
Virgilio, Stephen J.; Berenson, Gerald S.
1988-01-01
Objectives and activities of the cardiovascular (CV) fitness program Super Kids--Superfit are related in this article. This exercise program is one component of the Heart Smart Program, a CV health intervention model for elementary school students. Program evaluation, parent education, and school and community intervention strategies are…
A Bayesian Approach to Person Fit Analysis in Item Response Theory Models. Research Report.
ERIC Educational Resources Information Center
Glas, Cees A. W.; Meijer, Rob R.
A Bayesian approach to the evaluation of person fit in item response theory (IRT) models is presented. In a posterior predictive check, the observed value on a discrepancy variable is positioned in its posterior distribution. In a Bayesian framework, a Markov Chain Monte Carlo procedure can be used to generate samples of the posterior distribution…
Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee
2013-07-01
Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.
ERIC Educational Resources Information Center
Wang, Chee Keng John; Pyun, Do Young; Liu, Woon Chia; Lim, Boon San Coral; Li, Fuzhong
2013-01-01
Using a multilevel latent growth curve modeling (LGCM) approach, this study examined longitudinal change in levels of physical fitness performance over time (i.e. four years) in young adolescents aged from 12-13 years. The sample consisted of 6622 students from 138 secondary schools in Singapore. Initial analyses found between-school variation on…
ERIC Educational Resources Information Center
Rounds, James B., Jr.; And Others
Using a multidimensional scaling procedure, this study examined the fit of Holland's RIASEC hexagon model to the internal relationships among the Strong-Campbell Interest Inventory (SCII) General Occupational Theme scales. SCII intercorrelation matrices for both sexes as reported in the SCII Manual were submitted, separately for each sex, to…
Impact of Missing Data on Person-Model Fit and Person Trait Estimation
ERIC Educational Resources Information Center
Zhang, Bo; Walker, Cindy M.
2008-01-01
The purpose of this research was to examine the effects of missing data on person-model fit and person trait estimation in tests with dichotomous items. Under the missing-completely-at-random framework, four missing data treatment techniques were investigated including pairwise deletion, coding missing responses as incorrect, hotdeck imputation,…
Fitting Item Response Models to the Maryland Functional Reading Test Results.
ERIC Educational Resources Information Center
Hambleton, Ronald K.; And Others
The potential of item response theory (IRT) for solving a number of testing problems in the Maryland Functional Reading Program would appear to be substantial in view of the many other promising applications of the theory. But, it is well-known that the advantages derived from an IRT model cannot be achieved when the fit between an item response…
Bauer, Daniel J.; Sterba, Sonya K.
2011-01-01
Previous research has compared methods of estimation for multilevel models fit to binary data but there are reasons to believe that the results will not always generalize to the ordinal case. This paper thus evaluates (a) whether and when fitting multilevel linear models to ordinal outcome data is justified and (b) which estimator to employ when instead fitting multilevel cumulative logit models to ordinal data, Maximum Likelihood (ML) or Penalized Quasi-Likelihood (PQL). ML and PQL are compared across variations in sample size, magnitude of variance components, number of outcome categories, and distribution shape. Fitting a multilevel linear model to ordinal outcomes is shown to be inferior in virtually all circumstances. PQL performance improves markedly with the number of ordinal categories, regardless of distribution shape. In contrast to binary data, PQL often performs as well as ML when used with ordinal data. Further, the performance of PQL is typically superior to ML when the data includes a small to moderate number of clusters (i.e., ≤ 50 clusters). PMID:22040372
A Nonparametric Approach for Assessing Goodness-of-Fit of IRT Models in a Mixed Format Test
ERIC Educational Resources Information Center
Liang, Tie; Wells, Craig S.
2015-01-01
Investigating the fit of a parametric model plays a vital role in validating an item response theory (IRT) model. An area that has received little attention is the assessment of multiple IRT models used in a mixed-format test. The present study extends the nonparametric approach, proposed by Douglas and Cohen (2001), to assess model fit of three…
Polynomial fitting model for phase reconstruction: interferograms with high fringe density
NASA Astrophysics Data System (ADS)
Téllez-Quiñones, Alejandro; Malacara-Doblado, Daniel; García-Márquez, Jorge
2012-09-01
A data fitting model is proposed to estimate phases from its cosine and sine. The a priori assumption is that the phases to be reconstructed should be expressed by polynomials. The cosine and sine of the phases are obtained from interferograms with high fringe density by generalized phase-shifting techniques The proposed method is employed for phase reconstrution by line integration of the phase gradient or any other phase-unwrapping technique and the fit is achieved by a least-squares minimization.
Wadehn, Federico; Carnal, David; Loeliger, Hans-Andrea
2015-08-01
Heart rate variability is one of the key parameters for assessing the health status of a subject's cardiovascular system. This paper presents a local model fitting algorithm used for finding single heart beats in photoplethysmogram recordings. The local fit of exponentially decaying cosines of frequencies within the physiological range is used to detect the presence of a heart beat. Using 42 subjects from the CapnoBase database, the average heart rate error was 0.16 BPM and the standard deviation of the absolute estimation error was 0.24 BPM.
Modeling of pharmaceuticals mixtures toxicity with deviation ratio and best-fit functions models.
Wieczerzak, Monika; Kudłak, Błażej; Yotova, Galina; Nedyalkova, Miroslava; Tsakovski, Stefan; Simeonov, Vasil; Namieśnik, Jacek
2016-11-15
The present study deals with assessment of ecotoxicological parameters of 9 drugs (diclofenac (sodium salt), oxytetracycline hydrochloride, fluoxetine hydrochloride, chloramphenicol, ketoprofen, progesterone, estrone, androstenedione and gemfibrozil), present in the environmental compartments at specific concentration levels, and their mutual combinations by couples against Microtox® and XenoScreen YES/YAS® bioassays. As the quantitative assessment of ecotoxicity of drug mixtures is an complex and sophisticated topic in the present study we have used two major approaches to gain specific information on the mutual impact of two separate drugs present in a mixture. The first approach is well documented in many toxicological studies and follows the procedure for assessing three types of models, namely concentration addition (CA), independent action (IA) and simple interaction (SI) by calculation of a model deviation ratio (MDR) for each one of the experiments carried out. The second approach used was based on the assumption that the mutual impact in each mixture of two drugs could be described by a best-fit model function with calculation of weight (regression coefficient or other model parameter) for each of the participants in the mixture or by correlation analysis. It was shown that the sign and the absolute value of the weight or the correlation coefficient could be a reliable measure for the impact of either drug A on drug B or, vice versa, of B on A. Results of studies justify the statement, that both of the approaches show similar assessment of the mode of mutual interaction of the drugs studied. It was found that most of the drug mixtures exhibit independent action and quite few of the mixtures show synergic or dependent action.
ERIC Educational Resources Information Center
Fusilier, Marcelline; Durlabhji, Subhash
2005-01-01
Purpose: The purpose of this paper is to explore behavioral processes involved in internet technology acceptance and use with a sample in India, a developing country that can potentially benefit from greater participation in the web economy. Design/methodology/approach - User experience was incorporated into the technology acceptance model (TAM)…
ERIC Educational Resources Information Center
Lee, Woong-Kyu
2012-01-01
The principal objective of this study was to gain insight into attitude changes occurring during IT acceptance from the perspective of elaboration likelihood model (ELM). In particular, the primary target of this study was the process of IT acceptance through an education program. Although the Internet and computers are now quite ubiquitous, and…
ERIC Educational Resources Information Center
Mahdi, Hasan Rebhi
2014-01-01
The study aimed at investigating the influence of E-learning Self-Efficacy (ELSE) on the acceptance of e-learning by using the Technology Acceptance Model (TAM). According to the TAM which used as the theoretical basis, both of the Perceived Usefulness (PU) and the Perceived Ease of Use (PEOU) influence directly the end user's Behavioral Intention…
Grievink, Liat Shavit; Penny, David; Hendy, Michael D.; Holland, Barbara R.
2010-01-01
Commonly used phylogenetic models assume a homogeneous process through time in all parts of the tree. However, it is known that these models can be too simplistic as they do not account for nonhomogeneous lineage-specific properties. In particular, it is now widely recognized that as constraints on sequences evolve, the proportion and positions of variable sites can vary between lineages causing heterotachy. The extent to which this model misspecification affects tree reconstruction is still unknown. Here, we evaluate the effect of changes in the proportions and positions of variable sites on model fit and tree estimation. We consider 5 current models of nucleotide sequence evolution in a Bayesian Markov chain Monte Carlo framework as well as maximum parsimony (MP). We show that for a tree with 4 lineages where 2 nonsister taxa undergo a change in the proportion of variable sites tree reconstruction under the best-fitting model, which is chosen using a relative test, often results in the wrong tree. In this case, we found that an absolute test of model fit is a better predictor of tree estimation accuracy. We also found further evidence that MP is not immune to heterotachy. In addition, we show that increased sampling of taxa that have undergone a change in proportion and positions of variable sites is critical for accurate tree reconstruction. PMID:20525636
Zhang, Huiying; Cocosila, Mihail; Archer, Norm
2010-01-01
Pervasive healthcare support through mobile information technology solutions is playing an increasing role in the attempt to improve healthcare and reduce costs. Despite the apparent attractiveness, many mobile applications have failed or have not been implemented as predicted. Among factors possibly leading to such outcomes, technology adoption is a key problem. This must be investigated early in the development process because healthcare is a particularly sensitive area with vital social implications. Moreover, it is important to investigate technology acceptance using the support of scientific tools validated for relevant information systems research. This article presents an empirical study based on the Technology Acceptance Model 2 in mobile homecare nursing. The study elicited the perceptions of 91 Canadian nurses who used personal digital assistants for 1 month in their daily activities. A partial least squares modeling data analysis revealed that nurse's perception of usefulness is the main factor in the adoption of mobile technology, having subjective norm and image within the organization as significant antecedents. Overall, this study was the first attempt at investigating scientifically, through a pertinent information systems research model, user adoption of mobile systems by homecare nursing personnel.
Goodness-of-fit methods for additive-risk models in tumorigenicity experiments.
Ghosh, Debashis
2003-09-01
In tumorigenicity experiments, a complication is that the time to event is generally not observed, so that the time to tumor is subject to interval censoring. One of the goals in these studies is to properly model the effect of dose on risk. Thus, it is important to have goodness of fit procedures available for assessing the model fit. While several estimation procedures have been developed for current-status data, relatively little work has been done on model-checking techniques. In this article, we propose numerical and graphical methods for the analysis of current-status data using the additive-risk model, primarily focusing on the situation where the monitoring times are dependent. The finite-sample properties of the proposed methodology are examined through numerical studies. The methods are then illustrated with data from a tumorigenicity experiment.
NASA Astrophysics Data System (ADS)
Lee, Min Jin; Hong, Helen; Chung, Jin Wook
2014-03-01
We propose an automatic vessel segmentation method of vertebral arteries in CT angiography using combined circular and cylindrical model fitting. First, to generate multi-segmented volumes, whole volume is automatically divided into four segments by anatomical properties of bone structures along z-axis of head and neck. To define an optimal volume circumscribing vertebral arteries, anterior-posterior bounding and side boundaries are defined as initial extracted vessel region. Second, the initial vessel candidates are tracked using circular model fitting. Since boundaries of the vertebral arteries are ambiguous in case the arteries pass through the transverse foramen in the cervical vertebra, the circle model is extended along z-axis to cylinder model for considering additional vessel information of neighboring slices. Finally, the boundaries of the vertebral arteries are detected using graph-cut optimization. From the experiments, the proposed method provides accurate results without bone artifacts and eroded vessels in the cervical vertebra.
Knies, Jennifer L; Kingsolver, Joel G
2010-08-01
The initial rise of fitness that occurs with increasing temperature is attributed to Arrhenius kinetics, in which rates of reaction increase exponentially with increasing temperature. Models based on Arrhenius typically assume single rate-limiting reactions over some physiological temperature range for which all the rate-limiting enzymes are in 100% active conformation. We test this assumption using data sets for microbes that have measurements of fitness (intrinsic rate of population growth) at many temperatures and over a broad temperature range and for diverse ectotherms that have measurements at fewer temperatures. When measurements are available at many temperatures, strictly Arrhenius kinetics are rejected over the physiological temperature range. However, over a narrower temperature range, we cannot reject strictly Arrhenius kinetics. The temperature range also affects estimates of the temperature dependence of fitness. These results indicate that Arrhenius kinetics only apply over a narrow range of temperatures for ectotherms, complicating attempts to identify general patterns of temperature dependence.
2011-09-30
2011 to 00-00-2011 4 . TITLE AND SUBTITLE Fitting Models of the Population Consequences of Acoustic Disturbance to Data from Marine Mammal...and 4 ) initialize each of the MCMC chains. The Gibbs sampler allows us to factor the above high dimensional model into a series of lower dimension 4 ...at NEAq, and an example time series for one animal highlights both body fat code, and entanglement episodes (Figure 4 ). Individual health is a
Trinkoff, A.M.; Storr, C.L.; Wilson, M.L.; Gurses, A.P.
2015-01-01
Summary Background To our knowledge, no evidence is available on health care professionals’ use of electronic personal health records (ePHRs) for their health management. We therefore focused on nurses’ personal use of ePHRs using a modified technology acceptance model. Objectives To examine (1) the psychometric properties of the ePHR acceptance model, (2) the associations of perceived usefulness, ease of use, data privacy and security protection, and perception of self as health-promoting role models to nurses’ own ePHR use, and (3) the moderating influences of age, chronic illness and medication use, and providers’ use of electronic health record (EHRs) on the associations between the ePHR acceptance constructs and ePHR use. Methods A convenience sample of registered nurses, those working in one of 12 hospitals in the Maryland and Washington, DC areas and members of the nursing informatics community (AMIA and HIMSS), were invited to respond to an anonymous online survey; 847 responded. Multiple logistic regression identified associations between the model constructs and ePHR use, and the moderating effect. Results Overall, ePHRs were used by 47%. Sufficient reliability for all scales was found. Three constructs were significantly related to nurses’ own ePHR use after adjusting for covariates: usefulness, data privacy and security protection, and health-promoting role model. Nurses with providers that used EHRs who perceived a higher level of data privacy and security protection had greater odds of ePHR use than those whose providers did not use EHRs. Older nurses with a higher self-perception as health-promoting role models had greater odds of ePHR use than younger nurses. Conclusions Nurses who use ePHRs for their personal health might promote adoption by the general public by serving as health-promoting role models. They can contribute to improvements in patient education and ePHR design, and serve as crucial resources when working with their
Fitting complex population models by combining particle filters with Markov chain Monte Carlo.
Knape, Jonas; de Valpine, Perry
2012-02-01
We show how a recent framework combining Markov chain Monte Carlo (MCMC) with particle filters (PFMCMC) may be used to estimate population state-space models. With the purpose of utilizing the strengths of each method, PFMCMC explores hidden states by particle filters, while process and observation parameters are estimated using an MCMC algorithm. PFMCMC is exemplified by analyzing time series data on a red kangaroo (Macropus rufus) population in New South Wales, Australia, using MCMC over model parameters based on an adaptive Metropolis-Hastings algorithm. We fit three population models to these data; a density-dependent logistic diffusion model with environmental variance, an unregulated stochastic exponential growth model, and a random-walk model. Bayes factors and posterior model probabilities show that there is little support for density dependence and that the random-walk model is the most parsimonious model. The particle filter Metropolis-Hastings algorithm is a brute-force method that may be used to fit a range of complex population models. Implementation is straightforward and less involved than standard MCMC for many models, and marginal densities for model selection can be obtained with little additional effort. The cost is mainly computational, resulting in long running times that may be improved by parallelizing the algorithm.
Improved cosmological model fitting of Planck data with a dark energy spike
NASA Astrophysics Data System (ADS)
Park, Chan-Gyung
2015-06-01
The Λ cold dark matter (Λ CDM ) model is currently known as the simplest cosmology model that best describes observations with a minimal number of parameters. Here we introduce a cosmology model that is preferred over the conventional Λ CDM one by constructing dark energy as the sum of the cosmological constant Λ and an additional fluid that is designed to have an extremely short transient spike in energy density during the radiation-matter equality era and an early scaling behavior with radiation and matter densities. The density parameter of the additional fluid is defined as a Gaussian function plus a constant in logarithmic scale-factor space. Searching for the best-fit cosmological parameters in the presence of such a dark energy spike gives a far smaller chi-square value by about 5 times the number of additional parameters introduced and narrower constraints on the matter density and Hubble constant compared with the best-fit Λ CDM model. The significant improvement in reducing the chi square mainly comes from the better fitting of the Planck temperature power spectrum around the third (ℓ≈800 ) and sixth (ℓ≈1800 ) acoustic peaks. The likelihood ratio test and the Akaike information criterion suggest that the model of a dark energy spike is strongly favored by the current cosmological observations over the conventional Λ CDM model. However, based on the Bayesian information criterion which penalizes models with more parameters, the strong evidence supporting the presence of a dark energy spike disappears. Our result emphasizes that the alternative cosmological parameter estimation with even better fitting of the same observational data is allowed in Einstein's gravity.
A flexible, interactive software tool for fitting the parameters of neuronal models
Friedrich, Péter; Vella, Michael; Gulyás, Attila I.; Freund, Tamás F.; Káli, Szabolcs
2014-01-01
The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool. PMID
A flexible, interactive software tool for fitting the parameters of neuronal models.
Friedrich, Péter; Vella, Michael; Gulyás, Attila I; Freund, Tamás F; Káli, Szabolcs
2014-01-01
The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool.
Fitting a mixture model by expectation maximization to discover motifs in biopolymers
Bailey, T.L.; Elkan, C.
1994-12-31
The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expectation maximization to fit a two-component finite mixture model to the set of sequences. Multiple motifs are found by fitting a mixture model to the data, probabilistically erasing the occurrences of the motif thus found, and repeating the process to find successive motifs. The algorithm requires only a set of unaligned sequences and a number specifying the width of the motifs as input. It returns a model of each motif and a threshold which together can be used as a Bayes-optimal classifier for searching for occurrences of the motif in other databases. The algorithm estimates how many times each motif occurs in each sequence in the dataset and outputs an alignment of the occurrences of the motif. The algorithm is capable of discovering several different motifs with differing numbers of occurrences in a single dataset.
2010-09-30
unlimited. Fitting Models of the Population Consequences of Acoustic Disturbance to Data from Marine Mammal Populations James S. Clark H.L... model that provides daily estimates of lipid status, as lipid status of the mother is directly linked to pup survival. This model will use the drift...assess the feasibility of #2. WORK COMPLETED We have completed the following tasks: 1. Built the statistical model to estimate at-sea lipid status 2
The Blazar 3C 66A in 2003-2004: hadronic versus leptonic model fits
Reimer, A.
2008-12-24
The low-frequency peaked BL Lac object 3C 66A was the subject of an extensive multi-wavelength campaign from July 2003 till April 2004, which included quasi-simultaneous observations at optical, X-rays and very high energy gamma-rays. Here we apply the hadronic Synchrotron-Proton Blazar (SPB) model to the observed spectral energy distribution time-averaged over a flaring state, and compare the resulting model fits to those obtained from the application of the leptonic Synchrotron-Self-Compton (SSC) model. The results are used to identify diagnostic key predictions of the two blazar models for future multi-wavelength observations.
2016-01-01
Background The future of health care delivery is becoming more citizen centered, as today’s user is more active, better informed, and more demanding. Worldwide governments are promoting online health services, such as electronic health record (EHR) patient portals and, as a result, the deployment and use of these services. Overall, this makes the adoption of patient-accessible EHR portals an important field to study and understand. Objective The aim of this study is to understand the factors that drive individuals to adopt EHR portals. Methods We applied a new adoption model using, as a starting point, Ventkatesh's Unified Theory of Acceptance and Use of Technology in a consumer context (UTAUT2) by integrating a new construct specific to health care, a new moderator, and new relationships. To test the research model, we used the partial least squares (PLS) causal modelling approach. An online questionnaire was administrated. We collected 360 valid responses. Results The statistically significant drivers of behavioral intention are performance expectancy (beta=.200; t=3.619), effort expectancy (beta=.185; t=2.907), habit (beta=.388; t=7.320), and self-perception (beta=.098; t=2.285). The predictors of use behavior are habit (beta=0.206; t=2.752) and behavioral intention (beta=0.258; t=4.036). The model explained 49.7% of the variance in behavioral intention and 26.8% of the variance in use behavior. Conclusions Our research helps to understand the desired technology characteristics of EHR portals. By testing an information technology acceptance model, we are able to determine what is more valued by patients when it comes to deciding whether to adopt EHR portals or not. The inclusion of specific constructs and relationships related to the health care consumer area also had a significant impact on understanding the adoption of EHR portals. PMID:26935646
Shekhar, Karthik; Ruberman, Claire F.; Ferguson, Andrew L.; Barton, John P.; Kardar, Mehran; Chakraborty, Arup K.
2017-01-01
Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus’ fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses. PMID:24483484
ERIC Educational Resources Information Center
Kunina-Habenicht, Olga; Rupp, Andre A.; Wilhelm, Oliver
2012-01-01
Using a complex simulation study we investigated parameter recovery, classification accuracy, and performance of two item-fit statistics for correct and misspecified diagnostic classification models within a log-linear modeling framework. The basic manipulated test design factors included the number of respondents (1,000 vs. 10,000), attributes (3…
unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance
Fiske, Ian J.; Chandler, Richard B.
2011-01-01
Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientific questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mechanisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unified modeling interface. The R package unmarked provides such a unified modeling framework, including tools for data exploration, model fitting, model criticism, post-hoc analysis, and model comparison.
Double-sigmoid model for fitting fatigue profiles in mouse fast- and slow-twitch muscle.
Cairns, S P; Robinson, D M; Loiselle, D S
2008-07-01
We present a curve-fitting approach that permits quantitative comparisons of fatigue profiles obtained with different stimulation protocols in isolated slow-twitch soleus and fast-twitch extensor digitorum longus (EDL) muscles of mice. Profiles from our usual stimulation protocol (125 Hz for 500 ms, evoked once every second for 100-300 s) could be fitted by single-term functions (sigmoids or exponentials) but not by a double exponential. A clearly superior fit, as confirmed by the Akaiki Information Criterion, was achieved using a double-sigmoid function. Fitting accuracy was exceptional; mean square errors were typically <1% and r(2) > 0.9995. The first sigmoid (early fatigue) involved approximately 10% decline of isometric force to an intermediate plateau in both muscle types; the second sigmoid (late fatigue) involved a reduction of force to a final plateau, the decline being 83% of initial force in EDL and 63% of initial force in soleus. The maximal slope of each sigmoid was seven- to eightfold greater in EDL than in soleus. The general applicability of the model was tested by fitting profiles with a severe force loss arising from repeated tetanic stimulation evoked at different frequencies or rest periods, or with excitation via nerve terminals in soleus. Late fatigue, which was absent at 30 Hz, occurred earlier and to a greater extent at 125 than 50 Hz. The model captured small changes in rate of late fatigue for nerve terminal versus sarcolemmal stimulation. We conclude that a double-sigmoid expression is a useful and accurate model to characterize fatigue in isolated muscle preparations.
Scholey, J. E.; Lin, L.; Ainsley, C. G.
2015-06-15
Purpose: To evaluate the accuracy and limitations of a commercially-available treatment planning system’s (TPS’s) dose calculation algorithm for proton pencil-beam scanning (PBS) and present a novel technique to efficiently derive a clinically-acceptable beam model. Methods: In-air fluence profiles of PBS spots were modeled in the TPS alternately as single-(SG) and double-Gaussian (DG) functions, based on fits to commissioning data. Uniform-fluence, single-energy-layer square fields of various sizes and energies were calculated with both beam models and delivered to water. Dose was measured at several depths. Motivated by observed discrepancies in measured-versus-calculated dose comparisons, a third model was constructed based on double-Gaussian parameters contrived through a novel technique developed to minimize these differences (DGC). Eleven cuboid-dose-distribution-shaped fields with varying range/modulation and field size were subsequently generated in the TPS, using each of the three beam models described, and delivered to water. Dose was measured at the middle of each spread-out Bragg peak. Results: For energies <160 MeV, the DG model fit square-field measurements to <2% at all depths, while the SG model could disagree by >6%. For energies >160 MeV, both SG and DG models fit square-field measurements to <1% at <4 cm depth, but could exceed 6% deeper. By comparison, disagreement with the DGC model was always <3%. For the cuboid plans, calculation-versus-measured percent dose differences exceeded 7% for the SG model, being larger for smaller fields. The DG model showed <3% disagreement for all field sizes in shorter-range beams, although >5% differences for smaller fields persisted in longer-range beams. In contrast, the DGC model predicted measurements to <2% for all beams. Conclusion: Neither the TPS’s SG nor DG models, employed as intended, are ideally suited for routine clinical use. However, via a novel technique to be presented, its DG model can be
Tao, Donghua
2009-11-14
Following up a previous study that examined public health students' intention to use e-resources for completing research paper assignments, the present study proposed two models to investigate whether or not public health students actually used the e-resources they intended to use and whether or not the determinants of intention to use predict actual use of e-resources. Focus groups and pre- and post-questionnaires were used to collect data. Descriptive analysis, data screening, and Structural Equation Modeling (SEM) techniques were used for data analysis. The study found that the determinants of intention-to-use significantly predict actual use behavior. Direct impact of perceived usefulness and indirect impact of perceived ease of use to both behavior intention and actual behavior indicated the importance of ease of use at the early stage of technology acceptance. Non-significant intention-behavior relationship prompted thoughts on the measurement of actual behavior and multidimensional characteristics of the intention construct.
NASA Astrophysics Data System (ADS)
Furlan, E.; Fischer, W. J.; Ali, B.; Stutz, A. M.; Stanke, T.; Tobin, J. J.; Megeath, S. T.; Osorio, M.; Hartmann, L.; Calvet, N.; Poteet, C. A.; Booker, J.; Manoj, P.; Watson, D. M.; Allen, L.
2016-05-01
We present key results from the Herschel Orion Protostar Survey: spectral energy distributions (SEDs) and model fits of 330 young stellar objects, predominantly protostars, in the Orion molecular clouds. This is the largest sample of protostars studied in a single, nearby star formation complex. With near-infrared photometry from 2MASS, mid- and far-infrared data from Spitzer and Herschel, and submillimeter photometry from APEX, our SEDs cover 1.2-870 μm and sample the peak of the protostellar envelope emission at ˜100 μm. Using mid-IR spectral indices and bolometric temperatures, we classify our sample into 92 Class 0 protostars, 125 Class I protostars, 102 flat-spectrum sources, and 11 Class II pre-main-sequence stars. We implement a simple protostellar model (including a disk in an infalling envelope with outflow cavities) to generate a grid of 30,400 model SEDs and use it to determine the best-fit model parameters for each protostar. We argue that far-IR data are essential for accurate constraints on protostellar envelope properties. We find that most protostars, and in particular the flat-spectrum sources, are well fit. The median envelope density and median inclination angle decrease from Class 0 to Class I to flat-spectrum protostars, despite the broad range in best-fit parameters in each of the three categories. We also discuss degeneracies in our model parameters. Our results confirm that the different protostellar classes generally correspond to an evolutionary sequence with a decreasing envelope infall rate, but the inclination angle also plays a role in the appearance, and thus interpretation, of the SEDs.
Kinetic modelling of RDF pyrolysis: Model-fitting and model-free approaches.
Çepelioğullar, Özge; Haykırı-Açma, Hanzade; Yaman, Serdar
2016-02-01
In this study, refuse derived fuel (RDF) was selected as solid fuel and it was pyrolyzed in a thermal analyzer from room temperature to 900°C at heating rates of 5, 10, 20, and 50°C/min in N2 atmosphere. The obtained thermal data was used to calculate the kinetic parameters using Coats-Redfern, Friedman, Flylnn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) methods. As a result of Coats-Redfern model, decomposition process was assumed to be four independent reactions with different reaction orders. On the other hand, model free methods demonstrated that activation energy trend had similarities for the reaction progresses of 0.1, 0.2-0.7 and 0.8-0.9. The average activation energies were found between 73-161kJ/mol and it is possible to say that FWO and KAS models produced closer results to the average activation energies compared to Friedman model. Experimental studies showed that RDF may be a sustainable and promising feedstock for alternative processes in terms of waste management strategies.
Ruiz, Francisco J; Odriozola-González, Paula
2015-06-16
This study analyzed the interrelationships between key constructs of cognitive therapy (CT; depressogenic schemas), metacognitive therapy (MCT; dysfunctional metacognitive beliefs), and acceptance and commitment therapy (ACT; psychological inflexibility) in the prediction of depressive symptoms. With a lapse of nine months, 106 nonclinical participants responded twice to an anonymous online survey containing the following questionnaires: the Depression subscale of the Depression Anxiety and Stress Scales (DASS), the Dysfunctional Attitude Scale Revised (DAS-R), the Positive beliefs, Negative beliefs and Need to control subscales of the Metacognitions Questionnaire-30 (MCQ-30), and the Acceptance and Action Questionnaire - II (AAQ-II). Results showed that when controlling for baseline levels of depressive symptoms and demographic variables, psychological inflexibility longitudinally mediated the effect of depressogenic schemas (path ab = .023, SE = .010; 95% BC CI [.008, .048]) and dysfunctional metacognitive beliefs on depressive symptoms (positive metacognitive beliefs: path ab = .052, SE = .031; 95% BC CI [.005, .134]; negative metacognitive beliefs: path ab = .087, SE = .049; 95% BC CI [.016, .214]; need to control: path ab = .087, SE = .051; 95% BC CI [.013, .220]). Results are discussed emphasizing the role of psychological inflexibility in the CT and MCT models of depression.
Aeroelastic modeling for the FIT (Functional Integration Technology) team F/A-18 simulation
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Wieseman, Carol D.
1989-01-01
As part of Langley Research Center's commitment to developing multidisciplinary integration methods to improve aerospace systems, the Functional Integration Technology (FIT) team was established to perform dynamics integration research using an existing aircraft configuration, the F/A-18. An essential part of this effort has been the development of a comprehensive simulation modeling capability that includes structural, control, and propulsion dynamics as well as steady and unsteady aerodynamics. The structural and unsteady aerodynamics contributions come from an aeroelastic mode. Some details of the aeroelastic modeling done for the Functional Integration Technology (FIT) team research are presented. Particular attention is given to work done in the area of correction factors to unsteady aerodynamics data.
Balbuena Ortega, A; Arroyo Carrasco, M L; Méndez Otero, M M; Gayou, V L; Delgado Macuil, R; Martínez Gutiérrez, H; Iturbe Castillo, M D
2014-12-12
In this paper, the nonlinear refractive index of colloidal gold nanoparticles under continuous wave illumination is investigated with the z-scan technique. Gold nanoparticles were synthesized using ascorbic acid as reductant, phosphates as stabilizer and cetyltrimethylammonium chloride (CTAC) as surfactant agent. The nanoparticle size was controlled with the CTAC concentration. Experiments changing incident power and sample concentration were done. The experimental z-scan results were fitted with three models: thermal lens, aberrant thermal lens and the nonlocal model. It is shown that the nonlocal model reproduces with exceptionally good agreement; the obtained experimental behaviour.
NASA Technical Reports Server (NTRS)
Wu, L.; Chow, D. S-L.; Tam, V.; Putcha, L.
2015-01-01
An intranasal gel formulation of scopolamine (INSCOP) was developed for the treatment of Motion Sickness. Bioavailability and pharmacokinetics (PK) were determined per Investigative New Drug (IND) evaluation guidance by the Food and Drug Administration. Earlier, we reported the development of a PK model that can predict the relationship between plasma, saliva and urinary scopolamine (SCOP) concentrations using data collected from an IND clinical trial with INSCOP. This data analysis project is designed to validate the reported best fit PK model for SCOP by comparing observed and model predicted SCOP concentration-time profiles after administration of INSCOP.
Balbuena Ortega, A.; Arroyo Carrasco, M.L.; Méndez Otero, M.M.; Gayou, V.L.; Delgado Macuil, R.; Martínez Gutiérrez, H.; Iturbe Castillo, M.D.
2014-01-01
In this paper, the nonlinear refractive index of colloidal gold nanoparticles under continuous wave illumination is investigated with the z-scan technique. Gold nanoparticles were synthesized using ascorbic acid as reductant, phosphates as stabilizer and cetyltrimethylammonium chloride (CTAC) as surfactant agent. The nanoparticle size was controlled with the CTAC concentration. Experiments changing incident power and sample concentration were done. The experimental z-scan results were fitted with three models: thermal lens, aberrant thermal lens and the nonlocal model. It is shown that the nonlocal model reproduces with exceptionally good agreement; the obtained experimental behaviour. PMID:25705090
Modeling canopy-level productivity: is the "big-leaf" simplification acceptable?
NASA Astrophysics Data System (ADS)
Sprintsin, M.; Chen, J. M.
2009-05-01
The "big-leaf" approach to calculating the carbon balance of plant canopies assumes that canopy carbon fluxes have the same relative responses to the environment as any single unshaded leaf in the upper canopy. Widely used light use efficiency models are essentially simplified versions of the big-leaf model. Despite its wide acceptance, subsequent developments in the modeling of leaf photosynthesis and measurements of canopy physiology have brought into question the assumptions behind this approach showing that big leaf approximation is inadequate for simulating canopy photosynthesis because of the additional leaf internal control on carbon assimilation and because of the non-linear response of photosynthesis on leaf nitrogen and absorbed light, and changes in leaf microenvironment with canopy depth. To avoid this problem a sunlit/shaded leaf separation approach, within which the vegetation is treated as two big leaves under different illumination conditions, is gradually replacing the "big-leaf" strategy, for applications at local and regional scales. Such separation is now widely accepted as a more accurate and physiologically based approach for modeling canopy photosynthesis. Here we compare both strategies for Gross Primary Production (GPP) modeling using the Boreal Ecosystem Productivity Simulator (BEPS) at local (tower footprint) scale for different land cover types spread over North America: two broadleaf forests (Harvard, Massachusetts and Missouri Ozark, Missouri); two coniferous forests (Howland, Maine and Old Black Spruce, Saskatchewan); Lost Creek shrubland site (Wisconsin) and Mer Bleue petland (Ontario). BEPS calculates carbon fixation by scaling Farquhar's leaf biochemical model up to canopy level with stomatal conductance estimated by a modified version of the Ball-Woodrow-Berry model. The "big-leaf" approach was parameterized using derived leaf level parameters scaled up to canopy level by means of Leaf Area Index. The influence of sunlit
Effects of new mutations on fitness: insights from models and data.
Bataillon, Thomas; Bailey, Susan F
2014-07-01
The rates and properties of new mutations affecting fitness have implications for a number of outstanding questions in evolutionary biology. Obtaining estimates of mutation rates and effects has historically been challenging, and little theory has been available for predicting the distribution of fitness effects (DFE); however, there have been recent advances on both fronts. Extreme-value theory predicts the DFE of beneficial mutations in well-adapted populations, while phenotypic fitness landscape models make predictions for the DFE of all mutations as a function of the initial level of adaptation and the strength of stabilizing selection on traits underlying fitness. Direct experimental evidence confirms predictions on the DFE of beneficial mutations and favors distributions that are roughly exponential but bounded on the right. A growing number of studies infer the DFE using genomic patterns of polymorphism and divergence, recovering a wide range of DFE. Future work should be aimed at identifying factors driving the observed variation in the DFE. We emphasize the need for further theory explicitly incorporating the effects of partial pleiotropy and heterogeneity in the environment on the expected DFE.
Model for the overall phase-space acceptance in a Zeeman decelerator
NASA Astrophysics Data System (ADS)
Dulitz, Katrin; Vanhaecke, Nicolas; Softley, Timothy P.
2015-01-01
We present a formalism to calculate phase-space acceptance in a Zeeman decelerator. Using parameters closely mimicking previous Zeeman deceleration experiments, this approach reveals a velocity dependence of the phase stability which we ascribe to the finite rise and fall times of the current pulses that generate the magnetic fields inside the deceleration coils. It is shown that changing the current switch-off times (characterized by the reduced position of the synchronous particle κ0) as the sequence progresses, so as to maintain a constant mean acceleration per pulse, can lead to a constant phase stability and hence a beam with well-defined characteristics. We also find that the time overlap between fields of adjacent coils has an influence on the phase-space acceptance. Previous theoretical and experimental results [A. W. Wiederkehr et al., Phys. Rev. A 82, 043428 (2010), 10.1103/PhysRevA.82.043428; J. Chem. Phys. 135, 214202 (2011)., 10.1063/1.3662141] suggested unfilled regions in phase space that influence particle transmission through the decelerator. Our model provides a means to directly identify the origin of these effects due to coupling between longitudinal and transverse dynamics. Since optimum phase stability is restricted to a rather small parameter range in terms of the reduced position of the synchronous particle κ0, only a limited range of final velocities can be attained using a given number of coils. We evaluate phase stability for different Zeeman deceleration sequences, and by comparison with numerical three-dimensional particle-trajectory simulations, we demonstrate that our model provides a valuable tool to find optimum parameter sets for improved Zeeman deceleration schemes. An acceleration-deceleration scheme is shown to be a useful approach to generating beams with well-defined properties for variable-energy collision experiments. More generally, the model provides significant physical insights that are applicable to other types of
Schaper, Louise; Pervan, Graham
2007-01-01
The research reported in this paper describes the development, empirical validation and analysis of a model of technology acceptance by Australian occupational therapists. The study described involved the collection of quantitative data through a national survey. The theoretical significance of this work is that it uses a thoroughly constructed research model, with one of the largest sample sizes ever tested (n=1605), to extend technology acceptance research into the health sector. Results provide strong support for the model. This work reveals the complexity of the constructs and relationships that influence technology acceptance and highlights the need to include sociotechnical and system issues in studies of technology acceptance in healthcare to improve information system implementation success in this arena. The results of this study have practical and theoretical implications for health informaticians and researchers in the field of health informatics and information systems, tertiary educators, Commonwealth and State Governments and the allied health professions.
Model Fit to Experimental Data for Foam-Assisted Deep Vadose Zone Remediation
Roostapour, A.; Lee, G.; Zhong, Lirong; Kam, Seung I.
2014-01-15
Foam has been regarded as a promising means of remeidal amendment delivery to overcome subsurface heterogeneity in subsurface remediation processes. This study investigates how a foam model, developed by Method of Characteristics and fractional flow analysis in the companion paper of Roostapour and Kam (2012), can be applied to make a fit to a set of existing laboratory flow experiments (Zhong et al., 2009) in an application relevant to deep vadose zone remediation. This study reveals a few important insights regarding foam-assisted deep vadose zone remediation: (i) the mathematical framework established for foam modeling can fit typical flow experiments matching wave velocities, saturation history , and pressure responses; (ii) the set of input parameters may not be unique for the fit, and therefore conducting experiments to measure basic model parameters related to relative permeability, initial and residual saturations, surfactant adsorption and so on should not be overlooked; and (iii) gas compressibility plays an important role for data analysis, thus should be handled carefully in laboratory flow experiments. Foam kinetics, causing foam texture to reach its steady-state value slowly, may impose additional complications.
NASA Astrophysics Data System (ADS)
Cheng, Yuan-Chieh; Chen, Jia-Hong; Chang, Rong-Jie; Wang, Chung-Yen; Hsu, Wei-Yao; Wang, Pei-Jen
2015-09-01
Contact lenses are typically measured by the wet-box method because of the high optical power resulting from the anterior central curvature of cornea, even though the back vertex power of the lenses are small. In this study, an optical measurement system based on the Shack-Hartmann wavefront principle was established to investigate the aberrations of soft contact lenses. Fitting conditions were micmicked to study the optical design of an eye model with various topographical shapes in the anterior cornea. Initially, the contact lenses were measured by the wet-box method, and then by fitting the various topographical shapes of cornea to the eye model. In addition, an optics simulation program was employed to determine the sources of errors and assess the accuracy of the system. Finally, samples of soft contact lenses with various Diopters were measured; and, both simulations and experimental results were compared for resolving the controversies of fitting contact lenses to an eye model for optical measurements. More importantly, the results show that the proposed system can be employed for study of primary aberrations in contact lenses.
Fitting a Two-Component Scattering Model to Polarimetric SAR Data
NASA Technical Reports Server (NTRS)
Freeman, A.
1998-01-01
Classification, decomposition and modeling of polarimetric SAR data has received a great deal of attention in the recent literature. The objective behind these efforts is to better understand the scattering mechanisms which give rise to the polarimetric signatures seen in SAR image data. In this Paper an approach is described, which involves the fit of a combination of two simple scattering mechanisms to polarimetric SAR observations. The mechanisms am canopy scatter from a cloud of randomly oriented oblate spheroids, and a ground scatter term, which can represent double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants or Bragg scatter from a moderately rough surface, seen through a layer of vertically oriented scatterers. An advantage of this model fit approach is that the scattering contributions from the two basic scattering mechanisms can be estimated for clusters of pixels in polarimetric SAR images. The solution involves the estimation of four parameters from four separate equations. The model fit can be applied to polarimetric AIRSAR data at C-, L- and P-Band.
Efficient parallel implementation of active appearance model fitting algorithm on GPU.
Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou
2014-01-01
The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.
Detection of implausible phylogenetic inferences using posterior predictive assessment of model fit.
Brown, Jeremy M
2014-05-01
Systematic phylogenetic error caused by the simplifying assumptions made in models of molecular evolution may be impossible to avoid entirely when attempting to model evolution across massive, diverse data sets. However, not all deficiencies of inference models result in unreliable phylogenetic estimates. The field of phylogenetics lacks a direct method to identify cases where model specification adversely affects inferences. Posterior predictive simulation is a flexible and intuitive approach for assessing goodness-of-fit of the assumed model and priors in a Bayesian phylogenetic analysis. Here, I propose new test statistics for use in posterior predictive assessment of model fit. These test statistics compare phylogenetic inferences from posterior predictive data sets to inferences from the original data. A simulation study demonstrates the utility of these new statistics. The new tests reject the plausibility of inferred tree lengths or topologies more often when data/model combinations produce biased inferences. I also apply this approach to exemplar empirical data sets, highlighting the value of the novel assessments.
Deng, Bai-Chuan; Yun, Yong-Huan; Liang, Yi-Zeng; Cao, Dong-Sheng; Xu, Qing-Song; Yi, Lun-Zhao; Huang, Xin
2015-06-23
Partial least squares (PLS) is one of the most widely used methods for chemical modeling. However, like many other parameter tunable methods, it has strong tendency of over-fitting. Thus, a crucial step in PLS model building is to select the optimal number of latent variables (nLVs). Cross-validation (CV) is the most popular method for PLS model selection because it selects a model from the perspective of prediction ability. However, a clear minimum of prediction errors may not be obtained in CV which makes the model selection difficult. To solve the problem, we proposed a new strategy for PLS model selection which combines the cross-validated coefficient of determination (Qcv(2)) and model stability (S). S is defined as the stability of PLS regression vectors which is obtained using model population analysis (MPA). The results show that, when a clear maximum of Qcv(2) is not obtained, S can provide additional information of over-fitting and it helps in finding the optimal nLVs. Compared with other regression vector based indictors such as the Euclidean 2-norm (B2), the Durbin Watson statistic (DW) and the jaggedness (J), S is more sensitive to over-fitting. The model selected by our method has both good prediction ability and stability.
Fitting a Two-Component Scattering Model to Polarimetric SAR Data from Forests
NASA Technical Reports Server (NTRS)
Freeman, Anthony
2007-01-01
Two simple scattering mechanisms are fitted to polarimetric synthetic aperture radar (SAR) observations of forests. The mechanisms are canopy scatter from a reciprocal medium with azimuthal symmetry and a ground scatter term that can represent double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants or Bragg scatter from a moderately rough surface, which is seen through a layer of vertically oriented scatterers. The model is shown to represent the behavior of polarimetric backscatter from a tropical forest and two temperate forest sites by applying it to data from the National Aeronautic and Space Agency/Jet Propulsion Laboratory's Airborne SAR (AIRSAR) system. Scattering contributions from the two basic scattering mechanisms are estimated for clusters of pixels in polarimetric SAR images. The solution involves the estimation of four parameters from four separate equations. This model fit approach is justified as a simplification of more complicated scattering models, which require many inputs to solve the forward scattering problem. The model is used to develop an understanding of the ground-trunk double-bounce scattering that is present in the data, which is seen to vary considerably as a function of incidence angle. Two parameters in the model fit appear to exhibit sensitivity to vegetation canopy structure, which is worth further exploration. Results from the model fit for the ground scattering term are compared with estimates from a forward model and shown to be in good agreement. The behavior of the scattering from the ground-trunk interaction is consistent with the presence of a pseudo-Brewster angle effect for the air-trunk scattering interface. If the Brewster angle is known, it is possible to directly estimate the real part of the dielectric constant of the trunks, a key variable in forward modeling of backscatter from forests. It is also shown how, with a priori knowledge of the forest height, an estimate for the
Löscher, Wolfgang
2016-10-01
Animal seizure and epilepsy models continue to play an important role in the early discovery of new therapies for the symptomatic treatment of epilepsy. Since 1937, with the discovery of phenytoin, almost all anti-seizure drugs (ASDs) have been identified by their effects in animal models, and millions of patients world-wide have benefited from the successful translation of animal data into the clinic. However, several unmet clinical needs remain, including resistance to ASDs in about 30% of patients with epilepsy, adverse effects of ASDs that can reduce quality of life, and the lack of treatments that can prevent development of epilepsy in patients at risk following brain injury. The aim of this review is to critically discuss the translational value of currently used animal models of seizures and epilepsy, particularly what animal models can tell us about epilepsy therapies in patients and which limitations exist. Principles of translational medicine will be used for this discussion. An essential requirement for translational medicine to improve success in drug development is the availability of animal models with high predictive validity for a therapeutic drug response. For this requirement, the model, by definition, does not need to be a perfect replication of the clinical condition, but it is important that the validation provided for a given model is fit for purpose. The present review should guide researchers in both academia and industry what can and cannot be expected from animal models in preclinical development of epilepsy therapies, which models are best suited for which purpose, and for which aspects suitable models are as yet not available. Overall further development is needed to improve and validate animal models for the diverse areas in epilepsy research where suitable fit for purpose models are urgently needed in the search for more effective treatments.
Computational Software for Fitting Seismic Data to Epidemic-Type Aftershock Sequence Models
NASA Astrophysics Data System (ADS)
Chu, A.
2014-12-01
Modern earthquake catalogs are often analyzed using spatial-temporal point process models such as the epidemic-type aftershock sequence (ETAS) models of Ogata (1998). My work introduces software to implement two of ETAS models described in Ogata (1998). To find the Maximum-Likelihood Estimates (MLEs), my software provides estimates of the homogeneous background rate parameter and the temporal and spatial parameters that govern triggering effects by applying the Expectation-Maximization (EM) algorithm introduced in Veen and Schoenberg (2008). Despite other computer programs exist for similar data modeling purpose, using EM-algorithm has the benefits of stability and robustness (Veen and Schoenberg, 2008). Spatial shapes that are very long and narrow cause difficulties in optimization convergence and problems with flat or multi-modal log-likelihood functions encounter similar issues. My program uses a robust method to preset a parameter to overcome the non-convergence computational issue. In addition to model fitting, the software is equipped with useful tools for examining modeling fitting results, for example, visualization of estimated conditional intensity, and estimation of expected number of triggered aftershocks. A simulation generator is also given with flexible spatial shapes that may be defined by the user. This open-source software has a very simple user interface. The user may execute it on a local computer, and the program also has potential to be hosted online. Java language is used for the software's core computing part and an optional interface to the statistical package R is provided.
Kinetic Modeling and Fitting Software for Inter-connected Reaction Schemes: VisKin
Zhang, Xuan; Andrews, Jared N.; Pedersen, Steen E.
2007-01-01
Reaction kinetics for complex, highly-interconnected kinetic schemes are modeled using analytical solutions to a system of ordinary differential equations. The algorithm employs standard linear algebra methods that are implemented using MatLab functions in a Visual Basic interface. A graphical user interface for simple entry of reaction schemes facilitates comparison of a variety of reaction schemes. To ensure microscopic balance, graph theory algorithms are used to determine violations of thermodynamic cycle constraints. Analytical solutions based on linear differential equations result in fast comparisons of first order kinetic rates and amplitudes as a function of changing ligand concentrations. For analysis of higher order kinetics, we also implemented a solution using numerical integration. In order to determine rate constants from experimental data, fitting algorithms using the Levenberg-Marquardt algorithm or using Broyden-Fletcher-Goldfarb-Shanno (BFGS) methods were implemented that adjust rate constants to fit the model to imported data. We have included the ability to carry out global fitting of data sets obtained at varying ligand concentrations. These tools are combined in a single package, which we have dubbed VisKin, to guide and analyze kinetic experiments. The software is available online for use on PCs. PMID:17207764
Fitting of different models for water vapour sorption on potato starch granules
NASA Astrophysics Data System (ADS)
Czepirski, L.; Komorowska-Czepirska, E.; Szymońska, J.
2002-08-01
Water vapour adsorption isotherms for native and modified potato starch were investigated. To obtain the best fit for the experimental data several models based on the BET approach were evaluated. The hypothesis that water is adsorbed on the starch granules at the primary and secondary adsorption sites as well as a concept considering the adsorbent fractality were also tested. It was found, that the equilibrium adsorption points in the examined range of relative humidity (0.03-0.90) were most accurately predicted by using a three-parameter model proposed by Kats and Kutarov.
Goodness-of-fit tests for open capture-recapture models
Pollock, K.H.; Hines, J.E.; Nichols, J.D.
1985-01-01
General goodness-of-fit tests for the Jolly-Seber model are proposed. These tests are based on conditional arguments using minimal sufficient statistics. The tests are shown to be of simple hypergeometric form so that a series of independent contingency table chi-square tests can be performed. The relationship of these tests to other proposed tests is discussed. This is followed by a simulation study of the power of the tests to detect departures from the assumptions of the Jolly-Seber model. Some meadow vole capture-recapture data are used to illustrate the testing procedure which has been implemented in a computer program available from the authors.
Practical Person-Fit Assessment with the Linear FA Model: New Developments and a Comparative Study.
Ferrando, Pere J; Vigil-Colet, Andreu; Lorenzo-Seva, Urbano
2016-01-01
Linear factor analysis (FA) is, possibly, the most widely used model in psychometric applications based on graded-response or more continuous items. However, in these applications consistency at the individual level (person fit) is virtually never assessed. The aim of the present study is to propose a simple and workable approach to routinely assess person fit in FA-based studies. To do so, we first consider five potentially appropriate indices, of which one is a new proposal and the other is a modification of an existing index. Next, the effectiveness of these indices is assessed by using (a) a thorough simulation study that attempts to mimic realistic conditions, and (b) an illustrative example based on real data. Results suggest that the mean-squared lico index and the personal correlation work well in conjunction and can function effectively for detecting different types of inconsistency. Finally future directions and lines of research are discussed.
Practical Person-Fit Assessment with the Linear FA Model: New Developments and a Comparative Study
Ferrando, Pere J.; Vigil-Colet, Andreu; Lorenzo-Seva, Urbano
2016-01-01
Linear factor analysis (FA) is, possibly, the most widely used model in psychometric applications based on graded-response or more continuous items. However, in these applications consistency at the individual level (person fit) is virtually never assessed. The aim of the present study is to propose a simple and workable approach to routinely assess person fit in FA-based studies. To do so, we first consider five potentially appropriate indices, of which one is a new proposal and the other is a modification of an existing index. Next, the effectiveness of these indices is assessed by using (a) a thorough simulation study that attempts to mimic realistic conditions, and (b) an illustrative example based on real data. Results suggest that the mean-squared lico index and the personal correlation work well in conjunction and can function effectively for detecting different types of inconsistency. Finally future directions and lines of research are discussed. PMID:28082929
NASA Technical Reports Server (NTRS)
Kuhlthau, A. R.; Jacobson, I. D.
1977-01-01
Meaningful criteria and methodology for assessing, particularly in the area of ride quality, the potential acceptability to the traveling public of present and future transportation systems were investigated. Ride quality was found to be one of the important variables affecting the decision of users of air transportation, and to be influenced by several environmental factors, especially motion, noise, pressure, temperature, and seating. Models were developed to quantify the relationship of subjective comfort to all of these parameters and then were exercised for a variety of situations. Passenger satisfaction was found to be strongly related to ride quality and was so modeled. A computer program was developed to assess the comfort and satisfaction levels of passengers on aircraft subjected to arbitrary flight profiles over arbitrary terrain. A model was deduced of the manner in which passengers integrate isolated segments of a flight to obtain an overall trip comfort rating. A method was established for assessing the influence of other links (e.g., access, terminal conditions) in the overall passenger trip.
Hwang, Ji Young; Kim, Ki Young
2014-01-01
Abstract Objective: The aim of the study was to verify the effects of patient factors perceived by emergency medical technicians (EMTs) as well as their social and organizational factors on prehospital telemetry use intention based on the technology use intention and elaboration likelihood models. Materials and Methods: This is a retrospective empirical study. Questionnaires were developed on the basis of clinical factors of 72,907 patients assessed by prehospital telemetry from January 1, 2009 to April 30, 2012 by reviewing their prehospital medical care records and in-hospital medical records. Questionnaires regarding the social and organizational factors of EMTs were created on the basis of a literature review. To verify which factors affect the utilization of telemetry, we developed a partial least-squares route model on the basis of each characteristic. In total, 136 EMTs who had experience in using prehospital telemetry were surveyed from April 1 to April 7, 2013. Reliability, validity, hypotheses, and the model goodness of fit of the study tools were tested. Results: The clinical factors of the patients (path coefficient=−0.12; t=2.38), subjective norm (path coefficient=0.18; t=2.63), and job fit (path coefficient=0.45; t=5.29) positively affected the perceived usefulness (p<0.010). Meanwhile, the clinical factors of the patients (path coefficients=−0.19; t=4.46), subjective norm (path coefficient=0.08; t=1.97), loyalty incentives (path coefficient=−0.17; t=3.83), job fit (path coefficient=−0.32; t=7.06), organizational facilitations (path coefficient=0.08; t=1.99), and technical factors (i.e., usefulness and ease of use) positively affected attitudes (path coefficient=0.10, 0.58; t=2.62, 5.81; p<0.010). Attitudes and perceived usefulness significantly positively affected use intention. Conclusions: Factors that influence the use of telemetry by EMTs in ambulances included patients' clinical factors, as well as complex organizational and
Fitted Hanbury-Brown-Twiss radii versus space-time variances in flow-dominated models
Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan
2006-04-15
The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown-Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simple Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data.
Fitted Hanbury-Brown Twiss radii versus space-time variances in flow-dominated models
NASA Astrophysics Data System (ADS)
Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan
2006-04-01
The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simple Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data.
Dufour, C.; Le-Huy, H.; El Hakimi, A.; Soumagne, J.C.
1996-01-01
Real-time simulation of a small power network containing a Marti modeled transmission line is made using 2 parallel DSP`s. A new fitting method is used in the modeling of the Marti line which is optimized with regards to the fitting error curve. Results are presented which show the time costs of the Marti line modeling versus constant-parameter line modeling and the time savings by using two parallel DSP`s.
Model fitting of kink waves in the solar atmosphere: Gaussian damping and time-dependence
NASA Astrophysics Data System (ADS)
Morton, R. J.; Mooroogen, K.
2016-09-01
Aims: Observations of the solar atmosphere have shown that magnetohydrodynamic waves are ubiquitous throughout. Improvements in instrumentation and the techniques used for measurement of the waves now enables subtleties of competing theoretical models to be compared with the observed waves behaviour. Some studies have already begun to undertake this process. However, the techniques employed for model comparison have generally been unsuitable and can lead to erroneous conclusions about the best model. The aim here is to introduce some robust statistical techniques for model comparison to the solar waves community, drawing on the experiences from other areas of astrophysics. In the process, we also aim to investigate the physics of coronal loop oscillations. Methods: The methodology exploits least-squares fitting to compare models to observational data. We demonstrate that the residuals between the model and observations contain significant information about the ability for the model to describe the observations, and show how they can be assessed using various statistical tests. In particular we discuss the Kolmogorov-Smirnoff one and two sample tests, as well as the runs test. We also highlight the importance of including any observational trend line in the model-fitting process. Results: To demonstrate the methodology, an observation of an oscillating coronal loop undergoing standing kink motion is used. The model comparison techniques provide evidence that a Gaussian damping profile provides a better description of the observed wave attenuation than the often used exponential profile. This supports previous analysis from Pascoe et al. (2016, A&A, 585, L6). Further, we use the model comparison to provide evidence of time-dependent wave properties of a kink oscillation, attributing the behaviour to the thermodynamic evolution of the local plasma.
Model Flexibility Analysis Does Not Measure the Persuasiveness of a Fit.
Evans, Nathan J; Howard, Zachary L; Heathcote, Andrew; Brown, Scott D
2017-02-02
Recently, Veksler, Myers, and Gluck (2015) proposed model flexibility analysis as a method that "aids model evaluation by providing a metric for gauging the persuasiveness of a given fit" (p. 755) Model flexibility analysis measures the complexity of a model in terms of the proportion of all possible data patterns it can predict. We show that this measure does not provide a reliable way to gauge complexity, which prevents model flexibility analysis from fulfilling either of the 2 aims outlined by Veksler et al. (2015): absolute and relative model evaluation. We also show that model flexibility analysis can even fail to correctly quantify complexity in the most clear cut case, with nested models. We advocate for the use of well-established techniques with these characteristics, such as Bayes factors, normalized maximum likelihood, or cross-validation, and against the use of model flexibility analysis. In the discussion, we explore 2 issues relevant to the area of model evaluation: the completeness of current model selection methods and the philosophical debate of absolute versus relative model evaluation. (PsycINFO Database Record
Atmospheric Properties of T Dwarfs Inferred from Model Fits at Low Spectral Resolution
NASA Astrophysics Data System (ADS)
Godfrey, Paige A.; Rice, Emily L.; Filippazzo, Joe; Douglas, Stephanie; BDNYC
2016-01-01
Brown dwarfs are substellar objects that cool over time because they are not massive enough to sustain hydrogen fusion at their cores. While spectral types (M, L, T, Y) generally correlate with decreasing temperature, spectral subclasses (T0, T1, T2, etc.) do not, suggesting that secondary parameters (gravity, metallicity, dust) play a role in the spectral type-temperature relationship. We investigate this relationship for T dwarfs, which make up the coolest fully-populated spectral class of substellar objects. Our sample consists of 154 T dwarfs with low resolution (R~75-100) near-infrared (~0.8-2.5 micron) spectra from the SpeX Prism Library and the literature. We compare each observed spectrum to synthetic spectra from four model grids using a Markov-Chain Monte Carlo analysis to determine robust best-fit parameters and uncertainties. We evaluate the best fit parameters from each model grid per object to constrain how spectral type relates to decreasing temperature and increasing surface gravity and to compare the consistency of each model grid. To test for discrepant results when fitting to relatively narrow wavelength ranges, this analysis is performed on the full spectrum of the Y, J, H, and K bands and on each band separately. New detections of cooler objects extending into the Y dwarf and exoplanet regimes motivate our model comparisons and search for trends with spectral type and other observational properties across the decreasing temperatures in order to better understand the atmospheres of substellar objects, including cool gas giant exoplanets.
Blowout Jets: Hinode X-Ray Jets that Don't Fit the Standard Model
NASA Technical Reports Server (NTRS)
Moore, Ronald L.; Cirtain, Jonathan W.; Sterling, Alphonse C.; Falconer, David A.
2010-01-01
Nearly half of all H-alpha macrospicules in polar coronal holes appear to be miniature filament eruptions. This suggests that there is a large class of X-ray jets in which the jet-base magnetic arcade undergoes a blowout eruption as in a CME, instead of remaining static as in most solar X-ray jets, the standard jets that fit the model advocated by Shibata. Along with a cartoon depicting the standard model, we present a cartoon depicting the signatures expected of blowout jets in coronal X-ray images. From Hinode/XRT movies and STEREO/EUVI snapshots in polar coronal holes, we present examples of (1) X-ray jets that fit the standard model, and (2) X-ray jets that do not fit the standard model but do have features appropriate for blowout jets. These features are (1) a flare arcade inside the jet-base arcade in addition to the small flare arcade (bright point) outside that standard jets have, (2) a filament of cool (T is approximately 80,000K) plasma that erupts from the core of the jetbase arcade, and (3) an extra jet strand that should not be made by the reconnection for standard jets but could be made by reconnection between the ambient unipolar open field and the opposite-polarity leg of the filament-carrying flux-rope core field of the erupting jet-base arcade. We therefore infer that these non-standard jets are blowout jets, jets made by miniature versions of the sheared-core-arcade eruptions that make CMEs
Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J
2016-05-01
Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) .
A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit
NASA Technical Reports Server (NTRS)
Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.
2016-01-01
Shoulder injury is one of the most severe risks that have the potential to impair crewmembers' performance and health in long duration space flight. Overall, 64% of crewmembers experience shoulder pain after extra-vehicular training in a space suit, and 14% of symptomatic crewmembers require surgical repair (Williams & Johnson, 2003). Suboptimal suit fit, in particular at the shoulder region, has been identified as one of the predominant risk factors. However, traditional suit fit assessments and laser scans represent only a single person's data, and thus may not be generalized across wide variations of body shapes and poses. The aim of this work is to develop a software tool based on a statistical analysis of a large dataset of crewmember body shapes. This tool can accurately predict the skin deformation and shape variations for any body size and shoulder pose for a target population, from which the geometry can be exported and evaluated against suit models in commercial CAD software. A preliminary software tool was developed by statistically analyzing 150 body shapes matched with body dimension ranges specified in the Human-Systems Integration Requirements of NASA ("baseline model"). Further, the baseline model was incorporated with shoulder joint articulation ("articulation model"), using additional subjects scanned in a variety of shoulder poses across a pre-specified range of motion. Scan data was cleaned and aligned using body landmarks. The skin deformation patterns were dimensionally reduced and the co-variation with shoulder angles was analyzed. A software tool is currently in development and will be presented in the final proceeding. This tool would allow suit engineers to parametrically generate body shapes in strategically targeted anthropometry dimensions and shoulder poses. This would also enable virtual fit assessments, with which the contact volume and clearance between the suit and body surface can be predictively quantified at reduced time and
Ashby, Nathaniel J S; Jekel, Marc; Dickert, Stephan; Glöckner, Andreas
2016-12-01
Recent research makes increasing use of eye-tracking methodologies to generate and test process models. Overall, such research suggests that attention, generally indexed by fixations (gaze duration), plays a critical role in the construction of preference, although the methods used to support this supposition differ substantially. In 2 studies we empirically test prototypical versions of prominent processing assumptions against 1 another and several base models. We find that general evidence accumulation processes provide a good fit to the data. An accumulation process that assumes leakage and temporal variability in evidence weighting (i.e., a primacy effect) fits the aggregate data, both in terms of choices and decision times, and does so across varying types of choices (e.g., charitable giving and hedonic consumption) and numbers of options well. However, when comparing models on the level of the individual, for a majority of participants simpler models capture choice data better. The theoretical and practical implications of these findings are discussed. (PsycINFO Database Record
NASA Astrophysics Data System (ADS)
Arsenault, Richard; Brissette, François P.; Poulin, Annie; Côté, Pascal; Martel, Jean-Luc
2014-05-01
The process of hydrological model parameter calibration is routinely performed with the help of stochastic optimization algorithms. Many such algorithms have been created and they sometimes provide varying levels of performance (as measured by an efficiency metric such as Nash-Sutcliffe). This is because each algorithm is better suited for one type of optimization problem rather than another. This research project's aim was twofold. First, it was sought upon to find various features in the calibration problem fitness landscapes to map the encountered problem types to the best possible optimization algorithm. Second, the optimal number of model evaluations in order to minimize resources usage and maximize overall model quality was investigated. A total of five stochastic optimization algorithms (SCE-UA, CMAES, DDS, PSO and ASA) were used to calibrate four lumped hydrological models (GR4J, HSAMI, HMETS and MOHYSE) on 421 basins from the US MOPEX database. Each of these combinations was performed using three objective functions (Log(RMSE), NSE, and a metric combining NSE, RMSE and BIAS) to add sufficient diversity to the fitness landscapes. Each run was performed 30 times for statistical analysis. With every parameter set tested during the calibration process, the validation value was taken on a separate period. It was then possible to outline the calibration skill versus the validation skill for the different algorithms. Fitness landscapes were characterized by various metrics, such as the dispersion metric, the mean distance between random points and their respective local minima (found through simple hill-climbing algorithms) and the mean distance between the local minima and the best local optimum found. These metrics were then compared to the calibration score of the various optimization algorithms. Preliminary results tend to show that fitness landscapes presenting a globally convergent structure are more prevalent than other types of landscapes in this
Determinants of Intention to Use eLearning Based on the Technology Acceptance Model
ERIC Educational Resources Information Center
Punnoose, Alfie Chacko
2012-01-01
The purpose of this study was to find some of the predominant factors that determine the intention of students to use eLearning in the future. Since eLearning is not just a technology acceptance decision but also involves cognition, this study extended its search beyond the normal technology acceptance variables into variables that could affect…
Preservice Teachers' Acceptance of ICT Integration in the Classroom: Applying the UTAUT Model
ERIC Educational Resources Information Center
Birch, A.; Irvine, V.
2009-01-01
In this study, the researchers explore the factors that influence preservice teachers' acceptance of information and communication technology (ICT) integration in the classroom. The Unified Theory of Acceptance and Use of Technology (UTAUT) was developed by Venkatesh et al. ["MIS Quarterly, 27"(3), 425-478] in 2003 and shown to…
ERIC Educational Resources Information Center
Butler, Rory
2013-01-01
Internet-enabled mobile devices have increased the accessibility of learning content for students. Given the ubiquitous nature of mobile computing technology, a thorough understanding of the acceptance factors that impact a learner's intention to use mobile technology as an augment to their studies is warranted. Student acceptance of mobile…
Bajzer, Željko; Gibbons, Simon J.; Coleman, Heidi D.; Linden, David R.
2015-01-01
Noninvasive breath tests for gastric emptying are important techniques for understanding the changes in gastric motility that occur in disease or in response to drugs. Mice are often used as an animal model; however, the gamma variate model currently used for data analysis does not always fit the data appropriately. The aim of this study was to determine appropriate mathematical models to better fit mouse gastric emptying data including when two peaks are present in the gastric emptying curve. We fitted 175 gastric emptying data sets with two standard models (gamma variate and power exponential), with a gamma variate model that includes stretched exponential and with a proposed two-component model. The appropriateness of the fit was assessed by the Akaike Information Criterion. We found that extension of the gamma variate model to include a stretched exponential improves the fit, which allows for a better estimation of T1/2 and Tlag. When two distinct peaks in gastric emptying are present, a two-component model is required for the most appropriate fit. We conclude that use of a stretched exponential gamma variate model and when appropriate a two-component model will result in a better estimate of physiologically relevant parameters when analyzing mouse gastric emptying data. PMID:26045615
ERIC Educational Resources Information Center
Liu, Xun
2010-01-01
This study extended the technology acceptance model and empirically tested the new model with wikis, a new type of educational technology. Based on social cognitive theory and the theory of planned behavior, three new variables, wiki self-efficacy, online posting anxiety, and perceived behavioral control, were added to the original technology…
ERIC Educational Resources Information Center
Kilic, Eylem; Güler, Çetin; Çelik, H. Eray; Tatli, Cemal
2015-01-01
Purpose: The purpose of this study is to investigate the factors which might affect the intention to use interactive whiteboards (IWBs) by university students, using Technology Acceptance Model by the structural equation modeling approach. The following hypothesis guided the current study: H1. There is a positive relationship between IWB…
Crystallographic observation of 'induced fit' in a cryptophane host–guest model system
Taratula, Olena; Hill, P. Aru; Khan, Najat S.; Carroll, Patrick J.; Dmochowski, Ivan J.
2010-01-01
Cryptophane-A, comprised of two cyclotriguaiacylenes joined by three ethylene linkers, is a prototypal organic host molecule that binds reversibly to neutral small molecules via London forces. Of note are trifunctionalized, water-soluble cryptophane-A derivatives, which exhibit exceptional affinity for xenon in aqueous solution. In this paper, we report high-resolution X-ray structures of cryptophane-A and trifunctionalized derivatives in crown–crown and crown–saddle conformations, as well as in complexes with water, methanol, xenon or chloroform. Cryptophane internal volume varied by more than 20% across this series, which exemplifies 'induced fit' in a model host–guest system. PMID:21266998
Understanding Systematics in ZZ Ceti Model Fitting to Enable Differential Seismology
NASA Astrophysics Data System (ADS)
Fuchs, J. T.; Dunlap, B. H.; Clemens, J. C.; Meza, J. A.; Dennihy, E.; Koester, D.
2017-03-01
We are conducting a large spectroscopic survey of over 130 Southern ZZ Cetis with the Goodman Spectrograph on the SOAR Telescope. Because it employs a single instrument with high UV throughput, this survey will both improve the signal-to-noise of the sample of SDSS ZZ Cetis and provide a uniform dataset for model comparison. We are paying special attention to systematics in the spectral fitting and quantify three of those systematics here. We show that relative positions in the log g -Teff plane are consistent for these three systematics.
SSC Model Fits to Simultaneous Fermi and CAO observations of Bl Lac's
NASA Astrophysics Data System (ADS)
Gordon, Tyler; Macomb, Daryl J.; Hand, Jared; Norris, Jay P.; Long, Min
2016-01-01
The Challis Astronomical Observatory (CAO) has been surveying a sample of blazar-type AGN since 2010.Â The CAO blazar sample includes4 3 sources - comprising 30 FSRQs, 15 BL Lacs, one radio galaxy and four unclassified sources - covering a redshift range 0.02 < z < 2. Observations are carried out in BVRI filters. Here we describe photometric results on a small sample emphasizing BL Lacs.Â We combine the CAO data with Fermi/LAT data and explore the suitability of fits to the data using the uniform conical jet model of Potter and Cotter (MNRAS, 2012, 423, 756-765).
Fitting models to correlated data III: A comparison between residual analysis and other methods
NASA Astrophysics Data System (ADS)
Féménias, Jean-Louis
2005-07-01
Applications of the χ2 test, the F test, the Durbin-Watson d test, and the f (or Sign) test, to examples of correlated data treatment, show important drawbacks with the d test and (apparently) with the f test. An analytical approach based on residual analysis suggests an improvement in their use that leads to better results at lowest order; it also points out a distinction between goodness-of-fit tests, as the f test, and goodness-of-modeling tests, as the χ2 and F tests. The residual analysis method is applied to the same examples; it looks faster, simpler, and often more accurate than the classical ones.
Trajectory fitting in function space with application to analytic modeling of surfaces
NASA Technical Reports Server (NTRS)
Barger, Raymond L.
1992-01-01
A theory for representing a parameter-dependent function as a function trajectory is described. Additionally, a theory for determining a piecewise analytic fit to the trajectory is described. An example is given that illustrates the application of the theory to generating a smooth surface through a discrete set of input cross-section shapes. A simple procedure for smoothing in the parameter direction is discussed, and a computed example is given. Application of the theory to aerodynamic surface modeling is demonstrated by applying it to a blended wing-fuselage surface.
Chang, Chi-Ping
2015-06-01
Many technology developments hold the potential to improve the quality of life of people and make life easier and more comfortable. New technologies have been well accepted by most people. Information sharing in particular is a major catalyst of change in our current technology-based society. Technology has widely innovated life and drastically changed lifestyles. The Technology Acceptance Model (TAM), a model developed to address the rapid advances in computer technology, is used to explain and predict user acceptance of new information technology. In the past, businesses have used the TAM as an assessment tool to predict user acceptance when introducing new technology products. They have also used external factors in the model to influence user perceptions and beliefs and to ensure the successful spread of new technologies. Informatization plays a critical role in healthcare services. Due to the rapid aging of populations and upward trends in the incidence of chronic illness, requirements for long-term care have increased in both quality and quantity. Therefore, there has been an increased emphasis on integrating healthcare and information technology. However, most elderly are significantly less adept at technology use than the general population. Therefore, we reexamined the effect that the essential concepts in a TAM exerted on technology acceptance. In the present study, the technology acceptance experience with regard to telehealth of the elderly was used as an example to explain how the revised technology acceptance model (TAM 2) may be effectively applied to enhance the understanding of technology care among nurses. The results may serve as a reference for future research on healthcare-technology use in long-term care or in elderly populations.
SpectrRelax: An application for Mössbauer spectra modeling and fitting
NASA Astrophysics Data System (ADS)
Matsnev, M. E.; Rusakov, V. S.
2012-10-01
The SpectrRelax application was created for analysis and fitting of absorption and emission Mossbauer spectra of isotopes with 1/2 ↔ 3/2 transitions. Available models include a single Pseudo-Voigt line, doublet, and a sextet, a number of relaxation models, and a distribution of hyperfine/relaxation parameters of any model. SpectRelax can evaluate user supplied analytical expressions of model parameters and their error estimates. Complex parameter constraints or even new models can be implemented by setting parameter values to analytical expressions. Optimal model parameters search is performed using a maximum likelihood criterion in a Levenberg-Marquardt (L-M) algorithm. In the search process, a matrix of linear correlation coefficients between model parameters is calculated along with the error estimates, which allows better understanding of the optimized results. Partial derivatives of the model functions are evaluated using a "dual numbers" algorithm, which provides exact derivatives values at any point and improves the L-M method convergence. SpectrRelax runs under Windows operating systems by Microsoft. The application has a modern graphical user interface with extensive model editing and preview capabilities.
A Pearson-type goodness-of-fit test for stationary and time-continuous Markov regression models.
Aguirre-Hernández, R; Farewell, V T
2002-07-15
Markov regression models describe the way in which a categorical response variable changes over time for subjects with different explanatory variables. Frequently it is difficult to measure the response variable on equally spaced discrete time intervals. Here we propose a Pearson-type goodness-of-fit test for stationary Markov regression models fitted to panel data. A parametric bootstrap algorithm is used to study the distribution of the test statistic. The proposed technique is applied to examine the fit of a Markov regression model used to identify markers for disease progression in psoriatic arthritis.
Fitting mathematical models to describe the rheological behaviour of chocolate pastes
NASA Astrophysics Data System (ADS)
Barbosa, Carla; Diogo, Filipa; Alves, M. Rui
2016-06-01
The flow behavior is of utmost importance for the chocolate industry. The objective of this work was to study two mathematical models, Casson and Windhab models that can be used to fit chocolate rheological data and evaluate which better infers or previews the rheological behaviour of different chocolate pastes. Rheological properties (viscosity, shear stress and shear rates) were obtained with a rotational viscometer equipped with a concentric cylinder. The chocolate samples were white chocolate and chocolate with varying percentages in cacao (55%, 70% and 83%). The results showed that the Windhab model was the best to describe the flow behaviour of all the studied samples with higher determination coefficients (r2 > 0.9).
NASA Astrophysics Data System (ADS)
González-Oreja, José Antonio; Saiz-Salinas, José Ignacio
1999-07-01
Models of the macrozoobenthic community responses to abiotic variables measured in the polluted Bilbao estuary were obtained by multiple linear regression analyses. Total, Oligochaeta and Nematoda abundance and biomass were considered as dependent variables. Intertidal level, dissolved oxygen at the bottom of the water column (DOXB) and organic content of the sediment were selected by the analyses as the three principal explanatory variables. Goodness-of-fit of the models was high ( overlinex=71.3% ). Total abundance and biomass increased as a linear function of DOXB. The principal outcome of the vast sewage scheme currently in progress in the study area is an important contributor of increasing DOXB levels. The models exposed in this paper will serve as a tool to evaluate the expected changes in the near future.
A goodness-of-fit test for capture-recapture model M(t) under closure
Stanley, T.R.; Burnham, K.P.
1999-01-01
A new, fully efficient goodness-of-fit test for the time-specific closed-population capture-recapture model M(t) is presented. This test is based on the residual distribution of the capture history data given the maximum likelihood parameter estimates under model M(t), is partitioned into informative components, and is based on chi-square statistics. Comparison of this test with Leslie's test (Leslie, 1958, Journal of Animal Ecology 27, 84- 86) for model M(t), using Monte Carlo simulations, shows the new test generally outperforms Leslie's test. The new test is frequently computable when Leslie's test is not, has Type I error rates that are closer to nominal error rates than Leslie's test, and is sensitive to behavioral variation and heterogeneity in capture probabilities. Leslie's test is not sensitive to behavioral variation in capture probabilities but, when computable, has greater power to detect heterogeneity than the new test.
GRace: a MATLAB-based application for fitting the discrimination-association model.
Stefanutti, Luca; Vianello, Michelangelo; Anselmi, Pasquale; Robusto, Egidio
2014-10-28
The Implicit Association Test (IAT) is a computerized two-choice discrimination task in which stimuli have to be categorized as belonging to target categories or attribute categories by pressing, as quickly and accurately as possible, one of two response keys. The discrimination association model has been recently proposed for the analysis of reaction time and accuracy of an individual respondent to the IAT. The model disentangles the influences of three qualitatively different components on the responses to the IAT: stimuli discrimination, automatic association, and termination criterion. The article presents General Race (GRace), a MATLAB-based application for fitting the discrimination association model to IAT data. GRace has been developed for Windows as a standalone application. It is user-friendly and does not require any programming experience. The use of GRace is illustrated on the data of a Coca Cola-Pepsi Cola IAT, and the results of the analysis are interpreted and discussed.
Wenseleers, Tom; Helanterä, Heikki; Alves, Denise A; Dueñez-Guzmán, Edgar; Pamilo, Pekka
2013-01-01
The conflicts over sex allocation and male production in insect societies have long served as an important test bed for Hamilton's theory of inclusive fitness, but have for the most part been considered separately. Here, we develop new coevolutionary models to examine the interaction between these two conflicts and demonstrate that sex ratio and colony productivity costs of worker reproduction can lead to vastly different outcomes even in species that show no variation in their relatedness structure. Empirical data on worker-produced males in eight species of Melipona bees support the predictions from a model that takes into account the demographic details of colony growth and reproduction. Overall, these models contribute significantly to explaining behavioural variation that previous theories could not account for.
A fungal growth model fitted to carbon-limited dynamics of Rhizoctonia solani.
Jeger, M J; Lamour, A; Gilligan, C A; Otten, W
2008-01-01
Here, a quasi-steady-state approximation was used to simplify a mathematical model for fungal growth in carbon-limiting systems, and this was fitted to growth dynamics of the soil-borne plant pathogen and saprotroph Rhizoctonia solani. The model identified a criterion for invasion into carbon-limited environments with two characteristics driving fungal growth, namely the carbon decomposition rate and a measure of carbon use efficiency. The dynamics of fungal spread through a population of sites with either low (0.0074 mg) or high (0.016 mg) carbon content were well described by the simplified model with faster colonization for the carbon-rich environment. Rhizoctonia solani responded to a lower carbon availability by increasing the carbon use efficiency and the carbon decomposition rate following colonization. The results are discussed in relation to fungal invasion thresholds in terms of carbon nutrition.
Goodness-of-fit measures for individual-level models of infectious disease in a Bayesian framework.
Gardner, A; Deardon, R; Darlington, G
2011-12-01
In simple models there are a variety of tried and tested ways to assess goodness-of-fit. However, in complex non-linear models, such as spatio-temporal individual-level models, less research has been done on how best to ascertain goodness-of-fit. Often such models are fitted within a Bayesian statistical framework, since such a framework is ideally placed to account for the many areas of data uncertainty. Within a Bayesian context, a major tool for assessing goodness-of-fit is the posterior predictive distribution. That is, a distribution for a test statistic is found through simulation from the posterior distribution and then compared with the observed test statistic for the data. Here, we examine different test statistics and ascertain how well they can detect model misspecification via a simulation study.
Hsu, Hung-Hsiou; Wu, Ya-Hui
2016-11-09
The purposes of this study are to investigate the effectiveness of implementing a nursing information system and to discuss several issues affecting its successful deployment from the perspectives of nurses, the major users of the system. The methodology was based on the theory of the technology acceptance model. This study adopted a cross-sectional study method to survey and collect data. In total, 167 questionnaires were distributed to subjects. Approximately 94.6%, or 158 valid questionnaires, were collected. The data were analyzed using SPSS and PLS software.The data analysis indicated that the factors that most significantly influenced the willingness of nurses to use the nursing information system were their degrees of satisfaction with the system and their perceptions of its usefulness. A nursing information system that can provide functions that are useful and convenient and that facilitate the avoidance of tedious repetitive writing and improve the quality of provided care can encourage nurse satisfaction with the system and thus stimulate their interest in using it for their work. The ease of use of the system can also affect the willingness of nurses to use it.
Goodness-of-fit tests and model diagnostics for negative binomial regression of RNA sequencing data.
Mi, Gu; Di, Yanming; Schafer, Daniel W
2015-01-01
This work is about assessing model adequacy for negative binomial (NB) regression, particularly (1) assessing the adequacy of the NB assumption, and (2) assessing the appropriateness of models for NB dispersion parameters. Tools for the first are appropriate for NB regression generally; those for the second are primarily intended for RNA sequencing (RNA-Seq) data analysis. The typically small number of biological samples and large number of genes in RNA-Seq analysis motivate us to address the trade-offs between robustness and statistical power using NB regression models. One widely-used power-saving strategy, for example, is to assume some commonalities of NB dispersion parameters across genes via simple models relating them to mean expression rates, and many such models have been proposed. As RNA-Seq analysis is becoming ever more popular, it is appropriate to make more thorough investigations into power and robustness of the resulting methods, and into practical tools for model assessment. In this article, we propose simulation-based statistical tests and diagnostic graphics to address model adequacy. We provide simulated and real data examples to illustrate that our proposed methods are effective for detecting the misspecification of the NB mean-variance relationship as well as judging the adequacy of fit of several NB dispersion models.
Bloom, Jesse D
2014-10-01
Phylogenetic analyses of molecular data require a quantitative model for how sequences evolve. Traditionally, the details of the site-specific selection that governs sequence evolution are not known a priori, making it challenging to create evolutionary models that adequately capture the heterogeneity of selection at different sites. However, recent advances in high-throughput experiments have made it possible to quantify the effects of all single mutations on gene function. I have previously shown that such high-throughput experiments can be combined with knowledge of underlying mutation rates to create a parameter-free evolutionary model that describes the phylogeny of influenza nucleoprotein far better than commonly used existing models. Here, I extend this work by showing that published experimental data on TEM-1 beta-lactamase (Firnberg E, Labonte JW, Gray JJ, Ostermeier M. 2014. A comprehensive, high-resolution map of a gene's fitness landscape. Mol Biol Evol. 31:1581-1592) can be combined with a few mutation rate parameters to create an evolutionary model that describes beta-lactamase phylogenies much better than most common existing models. This experimentally informed evolutionary model is superior even for homologs that are substantially diverged (about 35% divergence at the protein level) from the TEM-1 parent that was the subject of the experimental study. These results suggest that experimental measurements can inform phylogenetic evolutionary models that are applicable to homologs that span a substantial range of sequence divergence.
A History of Regression and Related Model-Fitting in the Earth Sciences (1636?-2000)
Howarth, Richard J.
2001-12-15
The (statistical) modeling of the behavior of a dependent variate as a function of one or more predictors provides examples of model-fitting which span the development of the earth sciences from the 17th Century to the present. The historical development of these methods and their subsequent application is reviewed. Bond's predictions (c. 1636 and 1668) of change in the magnetic declination at London may be the earliest attempt to fit such models to geophysical data. Following publication of Newton's theory of gravitation in 1726, analysis of data on the length of a 1{sup o} meridian arc, and the length of a pendulum beating seconds, as a function of sin{sup 2}(latitude), was used to determine the ellipticity of the oblate spheroid defining the Figure of the Earth. The pioneering computational methods of Mayer in 1750, Boscovich in 1755, and Lambert in 1765, and the subsequent independent discoveries of the principle of least squares by Gauss in 1799, Legendre in 1805, and Adrain in 1808, and its later substantiation on the basis of probability theory by Gauss in 1809 were all applied to the analysis of such geodetic and geophysical data. Notable later applications include: the geomagnetic survey of Ireland by Lloyd, Sabine, and Ross in 1836, Gauss's model of the terrestrial magnetic field in 1838, and Airy's 1845 analysis of the residuals from a fit to pendulum lengths, from which he recognized the anomalous character of measurements of gravitational force which had been made on islands. In the early 20th Century applications to geological topics proliferated, but the computational burden effectively held back applications of multivariate analysis. Following World War II, the arrival of digital computers in universities in the 1950s facilitated computation, and fitting linear or polynomial models as a function of geographic coordinates, trend surface analysis, became popular during the 1950-60s. The inception of geostatistics in France at this time by Matheron had
NASA Astrophysics Data System (ADS)
Ehrlich, R.
2016-12-01
Evidence is presented in support of an unconventional 3 + 3 model of the neutrino mass eigenstates with specific m2 > 0 and m2 < 0 masses. The two large m2 > 0 masses of the model were originally suggested based on a SN 1987A analysis, and they were further supported by several dark matter fits. The new evidence for one of the m2 > 0 mass values comes from an analysis of published data from the three most precise tritium β - decay experiments. The KATRIN experiment by virtue of a unique 3-part signature should either confirm or reject the model in its entirety.
Lévy Flights and Self-Similar Exploratory Behaviour of Termite Workers: Beyond Model Fitting
Miramontes, Octavio; DeSouza, Og; Paiva, Leticia Ribeiro; Marins, Alessandra; Orozco, Sirio
2014-01-01
Animal movements have been related to optimal foraging strategies where self-similar trajectories are central. Most of the experimental studies done so far have focused mainly on fitting statistical models to data in order to test for movement patterns described by power-laws. Here we show by analyzing over half a million movement displacements that isolated termite workers actually exhibit a range of very interesting dynamical properties –including Lévy flights– in their exploratory behaviour. Going beyond the current trend of statistical model fitting alone, our study analyses anomalous diffusion and structure functions to estimate values of the scaling exponents describing displacement statistics. We evince the fractal nature of the movement patterns and show how the scaling exponents describing termite space exploration intriguingly comply with mathematical relations found in the physics of transport phenomena. By doing this, we rescue a rich variety of physical and biological phenomenology that can be potentially important and meaningful for the study of complex animal behavior and, in particular, for the study of how patterns of exploratory behaviour of individual social insects may impact not only their feeding demands but also nestmate encounter patterns and, hence, their dynamics at the social scale. PMID:25353958
Total Force Fitness in units part 1: military demand-resource model.
Bates, Mark J; Fallesen, Jon J; Huey, Wesley S; Packard, Gary A; Ryan, Diane M; Burke, C Shawn; Smith, David G; Watola, Daniel J; Pinder, Evette D; Yosick, Todd M; Estrada, Armando X; Crepeau, Loring; Bowles, Stephen V
2013-11-01
The military unit is a critical center of gravity in the military's efforts to enhance resilience and the health of the force. The purpose of this article is to augment the military's Total Force Fitness (TFF) guidance with a framework of TFF in units. The framework is based on a Military Demand-Resource model that highlights the dynamic interactions across demands, resources, and outcomes. A joint team of subject-matter experts identified key variables representing unit fitness demands, resources, and outcomes. The resulting framework informs and supports leaders, support agencies, and enterprise efforts to strengthen TFF in units by (1) identifying TFF unit variables aligned with current evidence and operational practices, (2) standardizing communication about TFF in units across the Department of Defense enterprise in a variety of military organizational contexts, (3) improving current resources including evidence-based actions for leaders, (4) identifying and addressing of gaps, and (5) directing future research for enhancing TFF in units. These goals are intended to inform and enhance Service efforts to develop Service-specific TFF models, as well as provide the conceptual foundation for a follow-on article about TFF metrics for units.
Lifting a veil on diversity: a Bayesian approach to fitting relative-abundance models.
Golicher, Duncan J; O'Hara, Robert B; Ruíz-Montoya, Lorena; Cayuela, Luis
2006-02-01
Bayesian methods incorporate prior knowledge into a statistical analysis. This prior knowledge is usually restricted to assumptions regarding the form of probability distributions of the parameters of interest, leaving their values to be determined mainly through the data. Here we show how a Bayesian approach can be applied to the problem of drawing inference regarding species abundance distributions and comparing diversity indices between sites. The classic log series and the lognormal models of relative- abundance distribution are apparently quite different in form. The first is a sampling distribution while the other is a model of abundance of the underlying population. Bayesian methods help unite these two models in a common framework. Markov chain Monte Carlo simulation can be used to fit both distributions as small hierarchical models with shared common assumptions. Sampling error can be assumed to follow a Poisson distribution. Species not found in a sample, but suspected to be present in the region or community of interest, can be given zero abundance. This not only simplifies the process of model fitting, but also provides a convenient way of calculating confidence intervals for diversity indices. The method is especially useful when a comparison of species diversity between sites with different sample sizes is the key motivation behind the research. We illustrate the potential of the approach using data on fruit-feeding butterflies in southern Mexico. We conclude that, once all assumptions have been made transparent, a single data set may provide support for the belief that diversity is negatively affected by anthropogenic forest disturbance. Bayesian methods help to apply theory regarding the distribution of abundance in ecological communities to applied conservation.
Estimation of high-resolution dust column density maps. Empirical model fits
NASA Astrophysics Data System (ADS)
Juvela, M.; Montillaud, J.
2013-09-01
Context. Sub-millimetre dust emission is an important tracer of column density N of dense interstellar clouds. One has to combine surface brightness information at different spatial resolutions, and specific methods are needed to derive N at a resolution higher than the lowest resolution of the observations. Some methods have been discussed in the literature, including a method (in the following, method B) that constructs the N estimate in stages, where the smallest spatial scales being derived only use the shortest wavelength maps. Aims: We propose simple model fitting as a flexible way to estimate high-resolution column density maps. Our goal is to evaluate the accuracy of this procedure and to determine whether it is a viable alternative for making these maps. Methods: The new method consists of model maps of column density (or intensity at a reference wavelength) and colour temperature. The model is fitted using Markov chain Monte Carlo methods, comparing model predictions with observations at their native resolution. We analyse simulated surface brightness maps and compare its accuracy with method B and the results that would be obtained using high-resolution observations without noise. Results: The new method is able to produce reliable column density estimates at a resolution significantly higher than the lowest resolution of the input maps. Compared to method B, it is relatively resilient against the effects of noise. The method is computationally more demanding, but is feasible even in the analysis of large Herschel maps. Conclusions: The proposed empirical modelling method E is demonstrated to be a good alternative for calculating high-resolution column density maps, even with considerable super-resolution. Both methods E and B include the potential for further improvements, e.g., in the form of better a priori constraints.
Nassar, Matthew R; Gold, Joshua I
2013-04-01
Fitting models to behavior is commonly used to infer the latent computational factors responsible for generating behavior. However, the complexity of many behaviors can handicap the interpretation of such models. Here we provide perspectives on problems that can arise when interpreting parameter fits from models that provide incomplete descriptions of behavior. We illustrate these problems by fitting commonly used and neurophysiologically motivated reinforcement-learning models to simulated behavioral data sets from learning tasks. These model fits can pass a host of standard goodness-of-fit tests and other model-selection diagnostics even when the models do not provide a complete description of the behavioral data. We show that such incomplete models can be misleading by yielding biased estimates of the parameters explicitly included in the models. This problem is particularly pernicious when the neglected factors are unknown and therefore not easily identified by model comparisons and similar methods. An obvious conclusion is that a parsimonious description of behavioral data does not necessarily imply an accurate description of the underlying computations. Moreover, general goodness-of-fit measures are not a strong basis to support claims that a particular model can provide a generalized understanding of the computations that govern behavior. To help overcome these challenges, we advocate the design of tasks that provide direct reports of the computational variables of interest. Such direct reports complement model-fitting approaches by providing a more complete, albeit possibly more task-specific, representation of the factors that drive behavior. Computational models then provide a means to connect such task-specific results to a more general algorithmic understanding of the brain.
Fitting a 3-D analytic model of the coronal mass ejection to observations
NASA Technical Reports Server (NTRS)
Gibson, S. E.; Biesecker, D.; Fisher, R.; Howard, R. A.; Thompson, B. J.
1997-01-01
The application of an analytic magnetohydrodynamic model is presented to observations of the time-dependent explusion of 3D coronal mass ejections (CMEs) out of the solar corona. This model relates the white-light appearance of the CME to its internal magnetic field, which takes the form of a closed bubble, filled with a partly anchored, twisted magnetic flux rope and embedded in an otherwise open background field. The density distribution frozen into the expanding CME expanding field is fully 3D, and can be integrated along the line of sight to reproduce observations of scattered white light. The model is able to reproduce the three conspicuous features often associated with CMEs as observed with white-light coronagraphs: a surrounding high-density region, an internal low-density cavity, and a high-density core. The model also describes the self-similar radial expansion of these structures. By varying the model parameters, the model can be fitted directly to observations of CMEs. It is shown how the model can quantitatively match the polarized brightness contrast of a dark cavity emerging through the lower corona as observed by the HAO Mauna Loa K-coronameter to within the noise level of the data.
Basch, Corey H; Hillyer, Grace Clarke; Ethan, Danna; Berdnik, Alyssa; Basch, Charles E
2015-07-01
Tanned skin has been associated with perceptions of fitness and social desirability. Portrayal of models in magazines may reflect and perpetuate these perceptions. Limited research has investigated tanning shade gradations of models in men's versus women's fitness and muscle enthusiast magazines. Such findings are relevant in light of increased incidence and prevalence of melanoma in the United States. This study evaluated and compared tanning shade gradations of adult Caucasian male and female model images in mainstream fitness and muscle enthusiast magazines. Sixty-nine U.S. magazine issues (spring and summer, 2013) were utilized. Two independent reviewers rated tanning shade gradations of adult Caucasian male and female model images on magazines' covers, advertisements, and feature articles. Shade gradations were assessed using stock photographs of Caucasian models with varying levels of tanned skin on an 8-shade scale. A total of 4,683 images were evaluated. Darkest tanning shades were found among males in muscle enthusiast magazines and lightest among females in women's mainstream fitness magazines. By gender, male model images were 54% more likely to portray a darker tanning shade. In this study, images in men's (vs. women's) fitness and muscle enthusiast magazines portrayed Caucasian models with darker skin shades. Despite these magazines' fitness-related messages, pro-tanning images may promote attitudes and behaviors associated with higher skin cancer risk. To date, this is the first study to explore tanning shades in men's magazines of these genres. Further research is necessary to identify effects of exposure to these images among male readers.
Alipoor, Mohammad; Maier, Stephan E; Gu, Irene Yu-Hua; Mehnert, Andrew; Kahl, Fredrik
2015-01-01
The monoexponential model is widely used in quantitative biomedical imaging. Notable applications include apparent diffusion coefficient (ADC) imaging and pharmacokinetics. The application of ADC imaging to the detection of malignant tissue has in turn prompted several studies concerning optimal experiment design for monoexponential model fitting. In this paper, we propose a new experiment design method that is based on minimizing the determinant of the covariance matrix of the estimated parameters (D-optimal design). In contrast to previous methods, D-optimal design is independent of the imaged quantities. Applying this method to ADC imaging, we demonstrate its steady performance for the whole range of input variables (imaged parameters, number of measurements, and range of b-values). Using Monte Carlo simulations we show that the D-optimal design outperforms existing experiment design methods in terms of accuracy and precision of the estimated parameters.
NASA Astrophysics Data System (ADS)
Saakian, David B.; Hu, Chin-Kun; Khachatryan, H.
2004-10-01
In a recent paper [Phys. Rev. E 69, 046121 (2004)], we used the Suzuki-Trottere formalism to study a quasispecies biological evolution model in a parallel mutation-selection scheme with a single-peak fitness function and a point mutation. In the present paper, we extend such a study to evolution models with more general fitness functions or multiple mutations in the parallel mutation-selection scheme. We give some analytical equations to define the error thresholds for some general cases of mean-field-like or symmetric mutation schemes and fitness functions. We derive some equations for the dynamics in the case of a point mutation and polynomial fitness functions. We derive exact dynamics for two-point mutations, asymmetric mutations, and the four-value spin model with a single-peak fitness function. The same method is applied for the model with a royal road fitness function. We derive the steady-state distribution for the single-peak fitness function.
Galambos, Colleen; Rantz, Marilyn; Back, Jessie; Jun, Jung Sim; Skubic, Marjorie; Miller, Steven J
2017-02-09
Aging in place is a preferred and cost-effective living option for older adults. Research indicates that technology can assist with this goal. Information on consumer preferences will help in technology development to assist older adults to age in place. The study aim was to explore the perceptions and preferences of older adults and their family members about a fall risk assessment system. Using a qualitative approach, this study examined the perceptions, attitudes, and preferences of 13 older adults and five family members about their experience living with the fall risk assessment system during five points in time. Themes emerged in relation to preferences and expectations about the technology and how it fits into daily routines. We were able to capture changes that occurred over time for older adult participants. Results indicated that there was acceptance of the technology as participants adapted to it. Two themes were present across the five points in time-safety and usefulness. Five stages of acceptance emerged from the data from preinstallation to 2 years postinstallation. Identified themes, stages of acceptance, and design and development considerations are discussed.
Rodrigue, Nicolas; Philippe, Hervé; Lartillot, Nicolas
2010-01-01
Modeling the interplay between mutation and selection at the molecular level is key to evolutionary studies. To this end, codon-based evolutionary models have been proposed as pertinent means of studying long-range evolutionary patterns and are widely used. However, these approaches have not yet consolidated results from amino acid level phylogenetic studies showing that selection acting on proteins displays strong site-specific effects, which translate into heterogeneous amino acid propensities across the columns of alignments; related codon-level studies have instead focused on either modeling a single selective context for all codon columns, or a separate selective context for each codon column, with the former strategy deemed too simplistic and the latter deemed overparameterized. Here, we integrate recent developments in nonparametric statistical approaches to propose a probabilistic model that accounts for the heterogeneity of amino acid fitness profiles across the coding positions of a gene. We apply the model to a dozen real protein-coding gene alignments and find it to produce biologically plausible inferences, for instance, as pertaining to site-specific amino acid constraints, as well as distributions of scaled selection coefficients. In their account of mutational features as well as the heterogeneous regimes of selection at the amino acid level, the modeling approaches studied here can form a backdrop for several extensions, accounting for other selective features, for variable population size, or for subtleties of mutational features, all with parameterizations couched within population-genetic theory. PMID:20176949
Explicit finite element modelling of the impaction of metal press-fit acetabular components.
Hothi, H S; Busfield, J J C; Shelton, J C
2011-03-01
Metal press-fit cups and shells are widely used in hip resurfacing and total hip replacement procedures. These acetabular components are inserted into a reamed acetabula cavity by either impacting their inner polar surface (shells) or outer rim (cups). Two-dimensional explicit dynamics axisymmetric finite element models were developed to simulate these impaction methods. Greater impact velocities were needed to insert the components when the interference fit was increased; a minimum velocity of 2 m/s was required to fully seat a component with a 2 mm interference between the bone and outer diameter. Changing the component material from cobalt-chromium to titanium alloy resulted in a reduction in the number of impacts on the pole to seat it from 14 to nine. Of greatest significance, it was found that locking a rigid cap to the cup or shell rim resulted in up to nine fewer impactions being necessary to seat it than impacting directly on the polar surface or using a cap free from the rim of the component, as is the case with many commercial resurfacing cup impaction devices currently used. This is important to impactor design and could make insertion easier and also reduce acetabula bone damage.
ERIC Educational Resources Information Center
Aquino, Cesar A.
2014-01-01
This study represents a research validating the efficacy of Davis' Technology Acceptance Model (TAM) by pairing it with the Organizational Change Readiness Theory (OCRT) to develop another extension to the TAM, using the medical Laboratory Information Systems (LIS)--Electronic Health Records (EHR) interface as the medium. The TAM posits that it is…
ERIC Educational Resources Information Center
Wolusky, G. Anthony
2016-01-01
This quantitative study used a web-based questionnaire to assess the attitudes and perceptions of online and hybrid faculty towards student-centered asynchronous virtual teamwork (AVT) using the technology acceptance model (TAM) of Davis (1989). AVT is online student participation in a team approach to problem-solving culminating in a written…
ERIC Educational Resources Information Center
Teo, Timothy; Tan, Lynde
2012-01-01
This study applies the theory of planned behavior (TPB), a theory that is commonly used in commercial settings, to the educational context to explain pre-service teachers' technology acceptance. It is also interested in examining its validity when used for this purpose. It has found evidence that the TPB is a valid model to explain pre-service…
ERIC Educational Resources Information Center
Teo, Timothy; Ursavas, Omer Faruk; Bahcekapili, Ekrem
2011-01-01
Purpose: The purpose of this study is to assess the efficiency of the technology acceptance model (TAM) to explain pre-service teachers' intention to use technology in Turkey. Design/methodology/approach: A total of 197 pre-service teachers from a Turkish university completed a survey questionnaire measuring their responses to four constructs…
ERIC Educational Resources Information Center
Ndubisi, Nelson
2006-01-01
Organisational investments in information technologies have increased significantly in the past few decades. All around the globe and in Malaysia particularly, a number of educational institutions are experimenting with e-learning. Adopting the theory of planned behaviour (TPB) and the technology acceptance model (TAM) this article tries to…
Spectral observations of Ellerman bombs and fitting with a two-cloud model
Hong, Jie; Ding, M. D.; Li, Ying; Fang, Cheng; Cao, Wenda
2014-09-01
We study the Hα and Ca II 8542 Å line spectra of four typical Ellerman bombs (EBs) in the active region NOAA 11765 on 2013 June 6, observed with the Fast Imaging Solar Spectrograph installed at the 1.6 m New Solar Telescope at Big Bear Solar Observatory. Considering that EBs may occur in a restricted region in the lower atmosphere, and that their spectral lines show particular features, we propose a two-cloud model to fit the observed line profiles. The lower cloud can account for the wing emission, and the upper cloud is mainly responsible for the absorption at line center. After choosing carefully the free parameters, we get satisfactory fitting results. As expected, the lower cloud shows an increase of the source function, corresponding to a temperature increase of 400-1000 K in EBs relative to the quiet Sun. This is consistent with previous results deduced from semi-empirical models and confirms that local heating occurs in the lower atmosphere during the appearance of EBs. We also find that the optical depths can increase to some extent in both the lower and upper clouds, which may result from either direct heating in the lower cloud, or illumination by an enhanced radiation on the upper cloud. The velocities derived from this method, however, are different from those obtained using the traditional bisector method, implying that one should be cautious when interpreting this parameter. The two-cloud model can thus be used as an efficient method to deduce the basic physical parameters of EBs.
Fitting Data to Model: Structural Equation Modeling Diagnosis Using Two Scatter Plots
ERIC Educational Resources Information Center
Yuan, Ke-Hai; Hayashi, Kentaro
2010-01-01
This article introduces two simple scatter plots for model diagnosis in structural equation modeling. One plot contrasts a residual-based M-distance of the structural model with the M-distance for the factor score. It contains information on outliers, good leverage observations, bad leverage observations, and normal cases. The other plot contrasts…
NASA Technical Reports Server (NTRS)
Kuhlman, J. M.
1979-01-01
The aerodynamic design of a wind-tunnel model of a wing representative of that of a subsonic jet transport aircraft, fitted with winglets, was performed using two recently developed optimal wing-design computer programs. Both potential flow codes use a vortex lattice representation of the near-field of the aerodynamic surfaces for determination of the required mean camber surfaces for minimum induced drag, and both codes use far-field induced drag minimization procedures to obtain the required spanloads. One code uses a discrete vortex wake model for this far-field drag computation, while the second uses a 2-D advanced panel wake model. Wing camber shapes for the two codes are very similar, but the resulting winglet camber shapes differ widely. Design techniques and considerations for these two wind-tunnel models are detailed, including a description of the necessary modifications of the design geometry to format it for use by a numerically controlled machine for the actual model construction.
Electrically detected magnetic resonance modeling and fitting: An equivalent circuit approach
Leite, D. M. G.; Batagin-Neto, A.; Nunes-Neto, O.; Gómez, J. A.; Graeff, C. F. O.
2014-01-21
The physics of electrically detected magnetic resonance (EDMR) quadrature spectra is investigated. An equivalent circuit model is proposed in order to retrieve crucial information in a variety of different situations. This model allows the discrimination and determination of spectroscopic parameters associated to distinct resonant spin lines responsible for the total signal. The model considers not just the electrical response of the sample but also features of the measuring circuit and their influence on the resulting spectral lines. As a consequence, from our model, it is possible to separate different regimes, which depend basically on the modulation frequency and the RC constant of the circuit. In what is called the high frequency regime, it is shown that the sign of the signal can be determined. Recent EDMR spectra from Alq{sub 3} based organic light emitting diodes, as well as from a-Si:H reported in the literature, were successfully fitted by the model. Accurate values of g-factor and linewidth of the resonant lines were obtained.
Statistics of dark matter substructure - I. Model and universal fitting functions
NASA Astrophysics Data System (ADS)
Jiang, Fangzhou; van den Bosch, Frank C.
2016-05-01
We present a new, semi-analytical model describing the evolution of dark matter subhaloes. The model uses merger trees constructed using the method of Parkinson et al. to describe the masses and redshifts of subhaloes at accretion, which are subsequently evolved using a simple model for the orbit-averaged mass-loss rates. The model is extremely fast, treats subhaloes of all orders, accounts for scatter in orbital properties and halo concentrations, uses a simple recipe to convert subhalo mass to maximum circular velocity, and considers subhalo disruption. The model is calibrated to accurately reproduce the average subhalo mass and velocity functions in numerical simulations. We demonstrate that, on average, the mass fraction in subhaloes is tightly correlated with the `dynamical age' of the host halo, defined as the number of halo dynamical times that have elapsed since its formation. Using this relation, we present universal fitting functions for the evolved and unevolved subhalo mass and velocity functions that are valid for a broad range in host halo mass, redshift and Λ cold dark matter cosmology.
The shape of dark matter haloes - II. The GALACTUS H I modelling & fitting tool
NASA Astrophysics Data System (ADS)
Peters, S. P. C.; van der Kruit, P. C.; Allen, R. J.; Freeman, K. C.
2017-01-01
We present a new H I modelling tool called GALACTUS. The program has been designed to perform automated fits of disc-galaxy models to observations. It includes a treatment for the self-absorption of gas. The software has been released into the public domain. We describe the design philosophy and inner workings of the program. After this, we model the face-on galaxy NGC 2403 using both self-absorption and optically thin models, showing that self-absorption occurs even in face-on galaxies. These results are then used to model an edge-on galaxy. It is shown that the maximum surface brightness plateaus seen in Paper I of this series are indeed signs of self-absorption. The apparent H I mass of an edge-on galaxy can be drastically lower compared with that same galaxy seen face-on. The Tully-Fisher relation is found to be relatively free from self-absorption issues.
Body-Fitted Detonation Shock Dynamics and the Pseudo-Reaction-Zone Energy Release Model
NASA Astrophysics Data System (ADS)
Meyer, Chad; Quirk, James; Short, Mark; Chqiuete, Carlos
2016-11-01
Programmed-burn methods are a class of models used to propagate a detonation wave, without the high resolution cost associated with a direct numerical simulation. They separate the detonation evolution calculation into two components: timing and energy release. The timing component is usually calculated with a Detonation Shock Dynamics model, a surface evolution representation that relates the normal velocity of the surface (Dn) to its local curvature. The energy release component must appropriately capture the degree of energy change associated with chemical reaction while simultaneously remaining synchronized with the timing component. The Pseudo-Reaction-Zone (PRZ) model is a reactive burn like energy release model, converting reactants into products, but with a conversion rate that is a function of the DSD surface Dn field. As such, it requires the DSD calculation produce smooth Dn fields, a challenge in complex geometries. We describe a new body-fitted approach to the Detonation Shock Dynamics calculation which produces the required smooth Dn fields, and a method for calibrating the PRZ model such that the rate of energy release remains as synced as possible with the timing component. We show results for slab, rate-stick and arc geometries.
A new fit-for-purpose model testing framework: Decision Crash Tests
NASA Astrophysics Data System (ADS)
Tolson, Bryan; Craig, James
2016-04-01
Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building
Bousbahi, Fatiha; Alrazgan, Muna Saleh
2015-01-01
To enhance instruction in higher education, many universities in the Middle East have chosen to introduce learning management systems (LMS) to their institutions. However, this new educational technology is not being used at its full potential and faces resistance from faculty members. To investigate this phenomenon, we conducted an empirical research study to uncover factors influencing faculty members' acceptance of LMS. Thus, in the Fall semester of 2014, Information Technology faculty members were surveyed to better understand their perceptions of the incorporation of LMS into their courses. The results showed that personal factors such as motivation, load anxiety, and organizational support play important roles in the perception of the usefulness of LMS among IT faculty members. These findings suggest adding these constructs in order to extend the Technology acceptance model (TAM) for LMS acceptance, which can help stakeholders of the university to implement the use of this system. This may assist in planning and evaluating the use of e-learning. PMID:26491712
Bousbahi, Fatiha; Alrazgan, Muna Saleh
2015-01-01
To enhance instruction in higher education, many universities in the Middle East have chosen to introduce learning management systems (LMS) to their institutions. However, this new educational technology is not being used at its full potential and faces resistance from faculty members. To investigate this phenomenon, we conducted an empirical research study to uncover factors influencing faculty members' acceptance of LMS. Thus, in the Fall semester of 2014, Information Technology faculty members were surveyed to better understand their perceptions of the incorporation of LMS into their courses. The results showed that personal factors such as motivation, load anxiety, and organizational support play important roles in the perception of the usefulness of LMS among IT faculty members. These findings suggest adding these constructs in order to extend the Technology acceptance model (TAM) for LMS acceptance, which can help stakeholders of the university to implement the use of this system. This may assist in planning and evaluating the use of e-learning.
SCAN-based hybrid and double-hybrid density functionals from models without fitted parameters
NASA Astrophysics Data System (ADS)
Hui, Kerwin; Chai, Jeng-Da
2016-01-01
By incorporating the nonempirical strongly constrained and appropriately normed (SCAN) semilocal density functional [J. Sun, A. Ruzsinszky, and J. P. Perdew, Phys. Rev. Lett. 115, 036402 (2015)] in the underlying expression of four existing hybrid and double-hybrid models, we propose one hybrid (SCAN0) and three double-hybrid (SCAN0-DH, SCAN-QIDH, and SCAN0-2) density functionals, which are free from any fitted parameters. The SCAN-based double-hybrid functionals consistently outperform their parent SCAN semilocal functional for self-interaction problems and noncovalent interactions. In particular, SCAN0-2, which includes about 79% of Hartree-Fock exchange and 50% of second-order Møller-Plesset correlation, is shown to be reliably accurate for a very diverse range of applications, such as thermochemistry, kinetics, noncovalent interactions, and self-interaction problems.
Corneal modeling using conic section fits of PAR corneal topography system measurements
NASA Astrophysics Data System (ADS)
Zipper, Stanley; Manns, Fabrice; Fernandez, Viviana; Sandadi, Samith; Ho, Arthur; Parel, Jean-Marie A.
2001-06-01
The purpose of this study was to measure the average shape and variability of human corneas and to develop a tool for analyzing, height, curvature, and aberrations based on a conic section model. Fresh Eye Bank Eyes were placed in Dextran until the corneal thickness reached a physiological value. The eyes were placed in a custom made holder and measured using an intraoperative PAR Corneal Topography System (CTS) mounted on an operation microscope. Topography was measured before and after removal of the epithelium. A series of MATLAB functions were written to analyze the raw-z (height) data in polar coordinates. The functions fit conic sections to the PAR CTS data along hemi-meridians at 5 degree(s) intervals. The conic shape factor and apical radius were used to calculate and display the curvature. The dependence of these parameters with meridional position was examined.
Strain estimation in 3D by fitting linear and planar data to the March model
NASA Astrophysics Data System (ADS)
Mulchrone, Kieran F.; Talbot, Christopher J.
2016-08-01
The probability density function associated with the March model is derived and used in a maximum likelihood method to estimate the best fit distribution and 3D strain parameters for a given set of linear or planar data. Typically it is assumed that in the initial state (pre-strain) linear or planar data are uniformly distributed on the sphere which means the number of strain parameters estimated needs to be reduced so that the numerical technique succeeds. Essentially this requires that the data are rotated into a suitable reference frame prior to analysis. The method has been applied to a suitable example from the Dalradian of SW Scotland and results obtained are consistent with those from an independent method of strain analysis. Despite March theory having been incorporated deep into the fabric of geological strain analysis, its full potential as a simple direct 3D strain analytical tool has not been achieved. The method developed here may help remedy this situation.
Students' Acceptance of Tablet PCs and Implications for Educational Institutions
ERIC Educational Resources Information Center
El-Gayar, Omar; Moran, Mark; Hawkes, Mark
2011-01-01
This research develops and empirically tests a factor model for understanding college students' acceptance of Tablet PC (TPC) as a means to forecast, explain, and improve their usage pattern in education. The analysis involved more than 230 students from a regional Midwestern institution. Overall, our model exhibited a good fit with the data and…
ERIC Educational Resources Information Center
Wang, Wen-Chung; Chen, Cheng-Te
2005-01-01
This study investigates item parameter recovery, standard error estimates, and fit statistics yielded by the WINSTEPS program under the Rasch model and the rating scale model through Monte Carlo simulations. The independent variables were item response model, test length, and sample size. WINSTEPS yielded practically unbiased estimates for the…
On the Model-Based Bootstrap with Missing Data: Obtaining a "P"-Value for a Test of Exact Fit
ERIC Educational Resources Information Center
Savalei, Victoria; Yuan, Ke-Hai
2009-01-01
Evaluating the fit of a structural equation model via bootstrap requires a transformation of the data so that the null hypothesis holds exactly in the sample. For complete data, such a transformation was proposed by Beran and Srivastava (1985) for general covariance structure models and applied to structural equation modeling by Bollen and Stine…
ERIC Educational Resources Information Center
Enders, Craig K.
2002-01-01
Proposed a method for extending the Bollen-Stine bootstrap model (K. Bollen and R. Stine, 1992) fit to structural equation models with missing data. Developed a Statistical Analysis System macro program to implement this procedure, and assessed its usefulness in a simulation. The new method yielded model rejection rates close to the nominal 5%…
A simple algorithm for optimization and model fitting: AGA (asexual genetic algorithm)
NASA Astrophysics Data System (ADS)
Cantó, J.; Curiel, S.; Martínez-Gómez, E.
2009-07-01
Context: Mathematical optimization can be used as a computational tool to obtain the optimal solution to a given problem in a systematic and efficient way. For example, in twice-differentiable functions and problems with no constraints, the optimization consists of finding the points where the gradient of the objective function is zero and using the Hessian matrix to classify the type of each point. Sometimes, however it is impossible to compute these derivatives and other type of techniques must be employed such as the steepest descent/ascent method and more sophisticated methods such as those based on the evolutionary algorithms. Aims: We present a simple algorithm based on the idea of genetic algorithms (GA) for optimization. We refer to this algorithm as AGA (asexual genetic algorithm) and apply it to two kinds of problems: the maximization of a function where classical methods fail and model fitting in astronomy. For the latter case, we minimize the chi-square function to estimate the parameters in two examples: the orbits of exoplanets by taking a set of radial velocity data, and the spectral energy distribution (SED) observed towards a YSO (Young Stellar Object). Methods: The algorithm AGA may also be called genetic, although it differs from standard genetic algorithms in two main aspects: a) the initial population is not encoded; and b) the new generations are constructed by asexual reproduction. Results: Applying our algorithm in optimizing some complicated functions, we find the global maxima within a few iterations. For model fitting to the orbits of exoplanets and the SED of a YSO, we estimate the parameters and their associated errors.
The Kunming CalFit study: modeling dietary behavioral patterns using smartphone data.
Seto, Edmund; Hua, Jenna; Wu, Lemuel; Bestick, Aaron; Shia, Victor; Eom, Sue; Han, Jay; Wang, May; Li, Yan
2014-01-01
Human behavioral interventions aimed at improving health can benefit from objective wearable sensor data and mathematical models. Smartphone-based sensing is particularly practical for monitoring behavioral patterns because smartphones are fairly common, are carried by individuals throughout their daily lives, offer a variety of sensing modalities, and can facilitate various forms of user feedback for intervention studies. We describe our findings from a smartphone-based study, in which an Android-based application we developed called CalFit was used to collect information related to young adults' dietary behaviors. In addition to monitoring dietary patterns, we were interested in understanding contextual factors related to when and where an individual eats, as well as how their dietary intake relates to physical activity (which creates energy demand) and psychosocial stress. 12 participants were asked to use CalFit to record videos of their meals over two 1-week periods, which were translated into nutrient intake by trained dietitians. During this same period, triaxial accelerometry was used to assess each subject's energy expenditure, and GPS was used to record time-location patterns. Ecological momentary assessment was also used to prompt subjects to respond to questions on their phone about their psychological state. The GPS data were processed through a web service we developed called Foodscoremap that is based on the Google Places API to characterize food environments that subjects were exposed to, which may explain and influence dietary patterns. Furthermore, we describe a modeling framework that incorporates all of these information to dynamically infer behavioral patterns that may be used for future intervention studies.
NASA Astrophysics Data System (ADS)
Hajigeorgiou, Photos G.
2016-12-01
An analytical model for the diatomic potential energy function that was recently tested as a universal function (Hajigeorgiou, 2010) has been further modified and tested as a suitable model for direct-potential-fit analysis. Applications are presented for the ground electronic states of three diatomic molecules: oxygen, carbon monoxide, and hydrogen fluoride. The adjustable parameters of the extended Lennard-Jones potential model are determined through nonlinear regression by fits to calculated rovibrational energy term values or experimental spectroscopic line positions. The model is shown to lead to reliable, compact and simple representations for the potential energy functions of these systems and could therefore be classified as a suitable and attractive model for direct-potential-fit analysis.
Adult Role Models: Feasibility, Acceptability, and Initial Outcomes for Sex Education
ERIC Educational Resources Information Center
Colarossi, Lisa; Silver, Ellen Johnson; Dean, Randa; Perez, Amanda; Rivera, Angelic
2014-01-01
The authors present the feasibility and acceptability of a parent sexuality education program led by peer educators in community settings. They also report the results of an outcome evaluation with 71 parents who were randomized to the intervention or a control group and surveyed one month prior to and six months after the four-week intervention.…
ERIC Educational Resources Information Center
Yallah, Ali
2014-01-01
The implementation of Telemedicine in behavioral health centers can be expensive if proactive steps were not taken to minimize user perceptions towards the new technology. Despite the significant capital investments on new Telemedicine, no consensus identified and explained what factors determined the acceptance, or rejection, of the technology.…
Exploring Students' Intention to Use LINE for Academic Purposes Based on Technology Acceptance Model
ERIC Educational Resources Information Center
Van De Bogart, Willard; Wichadee, Saovapa
2015-01-01
The LINE application is often conceived as purely social space; however, the authors of this paper wanted to determine if it could be used for academic purposes. In this study, we examined how undergraduate students accepted LINE in terms of using it for classroom-related activities (e.g., submit homework, follow up course information queries,…
ERIC Educational Resources Information Center
Sanchez-Franco, Manuel J.
2010-01-01
Perceived affective quality is an attractive area of research in Information System. Specifically, understanding the intrinsic and extrinsic individual factors and interaction effects that influence Information and Communications Technology (ICT) acceptance and adoption--in higher education--continues to be a focal interest in learning research.…
ERIC Educational Resources Information Center
Liu, Yi Chun; Huang, Yong-Ming
2015-01-01
The teaching of translation has received considerable attention in recent years. Research on translation in collaborative learning contexts, however, has been less studied. In this study, we use a tool of synchronous collaboration to assist students in experiencing a peer translation process. Afterward, the unified theory of acceptance and use of…
ERIC Educational Resources Information Center
Iqbal, Shakeel; Bhatti, Zeeshan Ahmed
2015-01-01
M-learning is learning delivered via mobile devices and mobile technology. The research indicates that this medium of learning has potential to enhance formal as well as informal learning. However, acceptance of m-learning greatly depends upon the personal attitude of students towards this medium; therefore this study focuses only on the…
ERIC Educational Resources Information Center
Padilla-Melendez, Antonio; del Aguila-Obra, Ana Rosa; Garrido-Moreno, Aurora
2013-01-01
The importance of technology for education is increasing year-by-year at all educational levels and particularly for Universities. This paper reexamines one important determinant of technology acceptance and use, such as perceived playfulness in the context of a blended learning setting and reveals existing gender differences. After a literature…
Inventory Responding as a Model of People's Acceptance of Personality Interpretations.
ERIC Educational Resources Information Center
Layne, Christopher; Michels, Philip J.
1979-01-01
A Barnum group rated the personal accuracies of a list of personality inventory items and then an equivalent list of bogus feedback. The correlation between their inventory and feedback ratings was highly significant. Variables influencing inventory responding exerted an equal influence upon feedback acceptance. (Author/GDC)
ERIC Educational Resources Information Center
Davis, Theresa M.
2013-01-01
Background: There is little evidence that technology acceptance is well understood in healthcare. The hospital environment is complex and dynamic creating a challenge when new technology is introduced because it impacts current processes and workflows which can significantly affect patient care delivery and outcomes. This study tested the effect…
Effects of body image on college students' attitudes toward diet/fitness apps on smartphones.
Cho, Jaehee; Lee, H Erin; Kim, Sun Jin; Park, Dongjin
2015-01-01
Considering the increasing use of diet/fitness apps, this study aimed to investigate how four factors related to body image--evaluations of and orientations toward both appearance and fitness--impact college students' perception of the usefulness of such apps. Based on the Technology Acceptance Model, this study tested a path model examining the relationships among the four body-image-oriented factors, perceived usefulness (PU) of diet/fitness apps, and behavioral intention to use such apps. Results from a path analysis revealed that while college students' evaluation of appearance and fitness decreased the PU of diet/fitness apps, their orientation toward fitness increased the same outcome variable.
Silva, Mónica A; Jonsen, Ian; Russell, Deborah J F; Prieto, Rui; Thompson, Dave; Baumgartner, Mark F
2014-01-01
Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF). The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS) algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs) fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina) tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to "true" GPS locations. Data on 6 fin whales (Balaenoptera physalus) were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM) fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6 ± 5.6 km) was nearly half that of LS estimates (11.6 ± 8.4 km). Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales' behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates.
Fitting data to model: structural equation modeling diagnosis using two scatter plots.
Yuan, Ke-Hai; Hayashi, Kentaro
2010-12-01
This article introduces two simple scatter plots for model diagnosis in structural equation modeling. One plot contrasts a residual-based M-distance of the structural model with the M-distance for the factor score. It contains information on outliers, good leverage observations, bad leverage observations, and normal cases. The other plot contrasts the residual-based M-distance with the quantile of a chi distribution. It allows the researcher to visually identify clusters of potential outliers. The article further studies the effect of the potential outliers on the overall model evaluation when they are removed according to the order of the clusters exhibited in the plot. Suggestions are provided on determining the outlier status of outstanding cases in real data analysis. Recommendations are also made on the choice of robust methods and maximum likelihood following outlier removal.
Simulating topological domains in human chromosomes with a fitting-free model.
Brackley, C A; Michieletto, D; Mouvet, F; Johnson, J; Kelly, S; Cook, P R; Marenduzzo, D
2016-09-02
We discuss a polymer model for the 3D organization of human chromosomes. A chromosome is represented by a string of beads, with each bead being "colored" according to 1D bioinformatic data (e.g., chromatin state, histone modification, GC content). Individual spheres (representing bi- and multi-valent transcription factors) can bind reversibly and selectively to beads with the appropriate color. During molecular dynamics simulations, the factors bind, and the string spontaneously folds into loops, rosettes, and topologically-associating domains (TADs). This organization occurs in the absence of any specified interactions between distant DNA segments, or between transcription factors. A comparison with Hi-C data shows that simulations predict the location of most boundaries between TADs correctly. The model is "fitting-free" in the sense that it does not use Hi-C data as an input; consequently, one of its strengths is that it can - in principle - be used to predict the 3D organization of any region of interest, or whole chromosome, in a given organism, or cell line, in the absence of existing Hi-C data. We discuss how this simple model might be refined to include more transcription factors and binding sites, and to correctly predict contacts between convergent CTCF binding sites.
Supersymmetric fits after the Higgs discovery and implications for model building.
Ellis, John
The data from the first run of the LHC at 7 and 8 TeV, together with the information provided by other experiments such as precision electroweak measurements, flavour measurements, the cosmological density of cold dark matter and the direct search for the scattering of dark matter particles in the LUX experiment, provide important constraints on supersymmetric models. Important information is provided by the ATLAS and CMS measurements of the mass of the Higgs boson, as well as the negative results of searches at the LHC for events with [Formula: see text] accompanied by jets, and the LHCb and CMS measurements of [Formula: see text]. Results are presented from frequentist analyses of the parameter spaces of the CMSSM and NUHM1. The global [Formula: see text] functions for the supersymmetric models vary slowly over most of the parameter spaces allowed by the Higgs mass and the [Formula: see text] search, with best-fit values that are comparable to the [Formula: see text] for the standard model. The 95 % CL lower limits on the masses of gluinos and squarks allow significant prospects for observing them during the LHC runs at higher energies.
Slater, Graham J; Harmon, Luke J; Wegmann, Daniel; Joyce, Paul; Revell, Liam J; Alfaro, Michael E
2012-03-01
In recent years, a suite of methods has been developed to fit multiple rate models to phylogenetic comparative data. However, most methods have limited utility at broad phylogenetic scales because they typically require complete sampling of both the tree and the associated phenotypic data. Here, we develop and implement a new, tree-based method called MECCA (Modeling Evolution of Continuous Characters using ABC) that uses a hybrid likelihood/approximate Bayesian computation (ABC)-Markov-Chain Monte Carlo approach to simultaneously infer rates of diversification and trait evolution from incompletely sampled phylogenies and trait data. We demonstrate via simulation that MECCA has considerable power to choose among single versus multiple evolutionary rate models, and thus can be used to test hypotheses about changes in the rate of trait evolution across an incomplete tree of life. We finally apply MECCA to an empirical example of body size evolution in carnivores, and show that there is no evidence for an elevated rate of body size evolution in the pinnipeds relative to terrestrial carnivores. ABC approaches can provide a useful alternative set of tools for future macroevolutionary studies where likelihood-dependent approaches are lacking.
Cheung, Emily Yee Man; Sachs, John
2006-12-01
The modified technology acceptance model was used to predict actual Blackboard usage (a web-based information system) in a sample of 57 Hong Kong student teachers whose mean age was 27.8 yr. (SD = 6.9). While the general form of the model was supported, Application-specific Self-efficacy was a more powerful predictor of system use than Behavioural Intention as predicted by the theory of reasoned action. Thus in this cultural and educational context, it has been shown that the model does not fully mediate the effect of Self-efficacy on System Use. Also, users' Enjoyment exerted considerable influence on the component variables of Usefulness and Ease of Use and on Application-specific Self-efficacy, thus indirectly influencing system usage. Consequently, efforts to gain students' acceptance and, therefore, use of information systems such as Blackboard must pay adequate attention to users' Self-efficacy and motivational variables such as Enjoyment.
Fitting host-parasitoid models with CV2 > 1 using hierarchical generalized linear models.
Perry, J N; Noh, M S; Lee, Y; Alston, R D; Norowi, H M; Powell, W; Rennolls, K
2000-01-01
The powerful general Pacala-Hassell host-parasitoid model for a patchy environment, which allows host density-dependent heterogeneity (HDD) to be distinguished from between-patch, host density-independent heterogeneity (HDI), is reformulated within the class of the generalized linear model (GLM) family. This improves accessibility through the provision of general software within well-known statistical systems, and allows a rich variety of models to be formulated. Covariates such as age class, host density and abiotic factors may be included easily. For the case where there is no HDI, the formulation is a simple GLM. When there is HDI in addition to HDD, the formulation is a hierarchical generalized linear model. Two forms of HDI model are considered, both with between-patch variability: one has binomial variation within patches and one has extra-binomial, overdispersed variation within patches. Examples are given demonstrating parameter estimation with standard errors, and hypothesis testing. For one example given, the extra-binomial component of the HDI heterogeneity in parasitism is itself shown to be strongly density dependent. PMID:11416907
Hertäg, Loreen; Hass, Joachim; Golovko, Tatiana; Durstewitz, Daniel
2012-01-01
For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which neurons may operate in vivo. Here we present an approach to parameter estimation for a simple spiking neuron model mainly based on standard f–I curves obtained from in vitro recordings. Such recordings are routinely obtained in standard protocols and assess a neuron’s response under a wide range of mean-input currents. Our fitting procedure makes use of closed-form expressions for the firing rate derived from an approximation to the adaptive exponential integrate-and-fire (AdEx) model. The resulting fitting process is simple and about two orders of magnitude faster compared to methods based on numerical integration of the differential equations. We probe this method on different cell types recorded from rodent prefrontal cortex. After fitting to the f–I current-clamp data, the model cells are tested on completely different sets of recordings obtained by fluctuating (“in vivo-like”) input currents. For a wide range of different input regimes, cell types, and cortical layers, the model could predict spike times on these test traces quite accurately within the bounds of physiological reliability, although no information from these distinct test sets was used for model fitting. Further analyses delineated some of the empirical factors constraining model fitting and the model’s generalization performance. An even simpler adaptive LIF neuron was also examined in this context. Hence, we have developed a “high-throughput” model fitting procedure which is simple and fast, with good prediction performance, and which relies only on firing rate information and standard physiological data widely and easily available. PMID:22973220
NASA Astrophysics Data System (ADS)
Dumedah, Gift; Walker, Jeffrey P.
2017-03-01
The sources of uncertainty in land surface models are numerous and varied, from inaccuracies in forcing data to uncertainties in model structure and parameterizations. Majority of these uncertainties are strongly tied to the overall makeup of the model, but the input forcing data set is independent with its accuracy usually defined by the monitoring or the observation system. The impact of input forcing data on model estimation accuracy has been collectively acknowledged to be significant, yet its quantification and the level of uncertainty that is acceptable in the context of the land surface model to obtain a competitive estimation remain mostly unknown. A better understanding is needed about how models respond to input forcing data and what changes in these forcing variables can be accommodated without deteriorating optimal estimation of the model. As a result, this study determines the level of forcing data uncertainty that is acceptable in the Joint UK Land Environment Simulator (JULES) to competitively estimate soil moisture in the Yanco area in south eastern Australia. The study employs hydro genomic mapping to examine the temporal evolution of model decision variables from an archive of values obtained from soil moisture data assimilation. The data assimilation (DA) was undertaken using the advanced Evolutionary Data Assimilation. Our findings show that the input forcing data have significant impact on model output, 35% in root mean square error (RMSE) for 5cm depth of soil moisture and 15% in RMSE for 15cm depth of soil moisture. This specific quantification is crucial to illustrate the significance of input forcing data spread. The acceptable uncertainty determined based on dominant pathway has been validated and shown to be reliable for all forcing variables, so as to provide optimal soil moisture. These findings are crucial for DA in order to account for uncertainties that are meaningful from the model standpoint. Moreover, our results point to a proper
Zhou, Liming; Yang, Yuxing; Yuan, Shiying
2006-02-01
A new algorithm, the coordinates transform iterative optimizing method based on the least square curve fitting model, is presented. This arithmetic is used for extracting the bio-impedance model parameters. It is superior to other methods, for example, its speed of the convergence is quicker, and its calculating precision is higher. The objective to extract the model parameters, such as Ri, Re, Cm and alpha, has been realized rapidly and accurately. With the aim at lowering the power consumption, decreasing the price and improving the price-to-performance ratio, a practical bio-impedance measure system with double CPUs has been built. It can be drawn from the preliminary results that the intracellular resistance Ri increased largely with an increase in working load during sitting, which reflects the ischemic change of lower limbs.
Semenov, Yuri S; Novozhilov, Artem S
2016-05-01
A two-valued fitness landscape is introduced for the classical Eigen's quasispecies model. This fitness landscape can be considered as a direct generalization of the so-called single- or sharply peaked landscape. A general, non-permutation invariant quasispecies model is studied, and therefore the dimension of the problem is [Formula: see text], where N is the sequence length. It is shown that if the fitness function is equal to [Formula: see text] on a G-orbit A and is equal to w elsewhere, then the mean population fitness can be found as the largest root of an algebraic equation of degree at most [Formula: see text]. Here G is an arbitrary isometry group acting on the metric space of sequences of zeroes and ones of the length N with the Hamming distance. An explicit form of this exact algebraic equation is given in terms of the spherical growth function of the G-orbit A. Motivated by the analysis of the two-valued fitness landscapes, an abstract generalization of Eigen's model is introduced such that the sequences are identified with the points of a finite metric space X together with a group of isometries acting transitively on X. In particular, a simplicial analog of the original quasispecies model is discussed, which can be considered as a mathematical model of the switching of the antigenic variants for some bacteria.
Evapotranspiration measurement and modeling without fitting parameters in high-altitude grasslands
NASA Astrophysics Data System (ADS)
Ferraris, Stefano; Previati, Maurizio; Canone, Davide; Dematteis, Niccolò; Boetti, Marco; Balocco, Jacopo; Bechis, Stefano
2016-04-01
Mountain grasslands are important, also because one sixth of the world population lives inside watershed dominated by snowmelt. Also, grasslands provide food to both domestic and selvatic animals. The global warming will probably accelerate the hydrological cycle and increase the drought risk. The combination of measurements, modeling and remote sensing can furnish knowledge in such faraway areas (e.g.: Brocca et al., 2013). A better knowledge of water balance can also allow to optimize the irrigation (e.g.: Canone et al., 2015). This work is meant to build a model of water balance in mountain grasslands, ranging between 1500 and 2300 meters asl. The main input is the Digital Terrain Model, which is more reliable in grasslands than both in the woods and in the built environment. It drives the spatial variability of shortwave solar radiation. The other atmospheric forcings are more problematic to estimate, namely air temperature, wind and longwave radiation. Ad hoc routines have been written, in order to interpolate in space the meteorological hourly time variability. The soil hydraulic properties are less variable than in the plains, but the soil depth estimation is still an open issue. The soil vertical variability has been modeled taking into account the main processes: soil evaporation, root uptake, and fractured bedrock percolation. The time variability latent heat flux and soil moisture results have been compared with the data measured in an eddy covariance station. The results are very good, given the fact that the model has no fitting parameters. The space variability results have been compared with the results of a model based on Landsat 7 and 8 data, applied over an area of about 200 square kilometers. The spatial correlation is quite in agreement between the two models. Brocca et al. (2013). "Soil moisture estimation in alpine catchments through modelling and satellite observations". Vadose Zone Journal, 12(3), 10 pp. Canone et al. (2015). "Field
Fitting Cox Models with Doubly Censored Data Using Spline-Based Sieve Marginal Likelihood.
Li, Zhiguo; Owzar, Kouros
2016-06-01
In some applications, the failure time of interest is the time from an originating event to a failure event, while both event times are interval censored. We propose fitting Cox proportional hazards models to this type of data using a spline-based sieve maximum marginal likelihood, where the time to the originating event is integrated out in the empirical likelihood function of the failure time of interest. This greatly reduces the complexity of the objective function compared with the fully semiparametric likelihood. The dependence of the time of interest on time to the originating event is induced by including the latter as a covariate in the proportional hazards model for the failure time of interest. The use of splines results in a higher rate of convergence of the estimator of the baseline hazard function compared with the usual nonparametric estimator. The computation of the estimator is facilitated by a multiple imputation approach. Asymptotic theory is established and a simulation study is conducted to assess its finite sample performance. It is also applied to analyzing a real data set on AIDS incubation time.
Equilibrium Reconstructions with V3FIT and Current Evolution Modeling for 3-D Stellarator Plasmas
NASA Astrophysics Data System (ADS)
Schmitt, J. C.; Cianciosa, M.; Geiger, J.; Lazerson, S.
2016-10-01
V3FIT is a powerful equilibrium reconstruction tool for magnetic confinement fusion experiments which are inherently 3-D in nature (i.e. stellarators) or have 3-D components (tokamaks with 3-D shaping, reversed field pinches with helical states, etc). Here, we present details of the diagnostic modeling, constraints and the user interface for reconstructions of W7-X plasmas. For typical discharges during the OP1.1 run campaign of W7-X, the net toroidal current and current density profile do not reach steady-state. When modeling the current evolution in 3-D plasmas, both poloidal and toroidal currents are linked with both poloidal and toroidal fluxes. In contrast, in toroidally axisymmetric plasmas, the poloidal flux is linked only with the toroidal current and the toroidal current is linked only with the poloidal flux. Compared to an equivalently-sized axisymmetric configuration, the current diffusion in 3-D plasmas is enhanced, leading to a faster relaxation of the current profile to its steady-state. Implications for the time-evolution of the current and rotational transform profiles in stellarator plasmas are discussed. This work is supported by DoE Grant DE-SC00014529.
Improved Spectral Fitting Models for the B-Stark Diagnostic at DIII-D
NASA Astrophysics Data System (ADS)
Pablant, N. A.; Grierson, B. A.; Burrell, K. H.; Groebner, R. J.; Kaplan, D. H.; Holcomb, C. T.
2010-11-01
Recent results are presented from the B-Stark diagnostic installed on the DIII-D tokamak. This diagnostic provides measurements of the magnitude and direction of the internal magnetic field. The B-Stark system is a version of a motional Stark effect (MSE) diagnostic based on the relative line intensities and spacing of the Stark split Dα emission from injected neutral beams. Improvements to the spectral fitting model are presented, including the addition of an analytical model for Dα emission from the fast-ion distribution. We discuss the accuracy of using in-situ beam-into-gas calibrations to find the beam emission line profiles, the viewing direction and the transmission properties of the collection optics. We also present results of efforts to improve the determination of the beam emission line profiles. Finally, the magnetic field measured with the B-Stark system is compared to values found from plasma equilibrium reconstructions (EFIT) and the MSE polarimetry system on DIII-D.
Model Order Selection for Short Data: An Exponential Fitting Test (EFT)
NASA Astrophysics Data System (ADS)
Quinlan, Angela; Barbot, Jean-Pierre; Larzabal, Pascal; Haardt, Martin
2006-12-01
High-resolution methods for estimating signal processing parameters such as bearing angles in array processing or frequencies in spectral analysis may be hampered by the model order if poorly selected. As classical model order selection methods fail when the number of snapshots available is small, this paper proposes a method for noncoherent sources, which continues to work under such conditions, while maintaining low computational complexity. For white Gaussian noise and short data we show that the profile of the ordered noise eigenvalues is seen to approximately fit an exponential law. This fact is used to provide a recursive algorithm which detects a mismatch between the observed eigenvalue profile and the theoretical noise-only eigenvalue profile, as such a mismatch indicates the presence of a source. Moreover this proposed method allows the probability of false alarm to be controlled and predefined, which is a crucial point for systems such as RADARs. Results of simulations are provided in order to show the capabilities of the algorithm.
Kügler, Philipp
2012-01-01
The inference of reaction rate parameters in biochemical network models from time series concentration data is a central task in computational systems biology. Under the assumption of well mixed conditions the network dynamics are typically described by the chemical master equation, the Fokker Planck equation, the linear noise approximation or the macroscopic rate equation. The inverse problem of estimating the parameters of the underlying network model can be approached in deterministic and stochastic ways, and available methods often compare individual or mean concentration traces obtained from experiments with theoretical model predictions when maximizing likelihoods, minimizing regularized least squares functionals, approximating posterior distributions or sequentially processing the data. In this article we assume that the biological reaction network can be observed at least partially and repeatedly over time such that sample moments of species molecule numbers for various time points can be calculated from the data. Based on the chemical master equation we furthermore derive closed systems of parameter dependent nonlinear ordinary differential equations that predict the time evolution of the statistical moments. For inferring the reaction rate parameters we suggest to not only compare the sample mean with the theoretical mean prediction but also to take the residual of higher order moments explicitly into account. Cost functions that involve residuals of higher order moments may form landscapes in the parameter space that have more pronounced curvatures at the minimizer and hence may weaken or even overcome parameter sloppiness and uncertainty. As a consequence both deterministic and stochastic parameter inference algorithms may be improved with respect to accuracy and efficiency. We demonstrate the potential of moment fitting for parameter inference by means of illustrative stochastic biological models from the literature and address topics for future
ERIC Educational Resources Information Center
Fan, Xitao; And Others
A Monte Carlo study was conducted to assess the effects of some potential confounding factors on structural equation modeling (SEM) fit indices and parameter estimates for both true and misspecified models. The factors investigated were data nonnormality, SEM estimation method, and sample size. Based on the fully crossed and balanced 3x3x4x2…
Schlemm, Eckhard
2015-09-01
The Bak-Sneppen model is an abstract representation of a biological system that evolves according to the Darwinian principles of random mutation and selection. The species in the system are characterized by a numerical fitness value between zero and one. We show that in the case of five species the steady-state fitness distribution can be obtained as a solution to a linear differential equation of order five with hypergeometric coefficients. Similar representations for the asymptotic fitness distribution in larger systems may help pave the way towards a resolution of the question of whether or not, in the limit of infinitely many species, the fitness is asymptotically uniformly distributed on the interval [fc, 1] with fc ≳ 2/3.
Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting
Ross, James C.; Kindlmann, Gordon L.; Okajima, Yuka; Hatabu, Hiroto; Díaz, Alejandro A.; Silverman, Edwin K.; Washko, George R.; Dy, Jennifer; Estépar, Raúl San José
2013-01-01
Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The proposed
Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting
Ross, James C.; Kindlmann, Gordon L.; Okajima, Yuka; Hatabu, Hiroto; Díaz, Alejandro A.; Silverman, Edwin K.; Washko, George R.; Dy, Jennifer; Estépar, Raúl San José
2013-12-15
Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The proposed
ProFit: Bayesian galaxy fitting tool
NASA Astrophysics Data System (ADS)
Robotham, A. S. G.; Taranu, D.; Tobar, R.
2016-12-01
ProFit is a Bayesian galaxy fitting tool that uses the fast C++ image generation library libprofit (ascl:1612.003) and a flexible R interface to a large number of likelihood samplers. It offers a fully featured Bayesian interface to galaxy model fitting (also called profiling), using mostly the same standard inputs as other popular codes (e.g. GALFIT ascl:1104.010), but it is also able to use complex priors and a number of likelihoods.
2015-11-01
n=19,769; 7,692 [28- day reservists course]; 12,077 [80- day standard]. The 28- day incurred 17.6% injury rate, 1 stress fracture, 5.2% attrition, 30.0...fitness test failure. The 80- day : 34.3% injury rate, 44 stress fractures, 5.0% attrition, 12.1% fitness test failure. Separate models were derived to...accuracy was poor, accuracy was improved in models that included course length (28 vs. 80 day ) as a predictor; suggesting the potential for using duration
Wasylkiw, L; Emms, A A; Meuse, R; Poirier, K F
2009-03-01
The current study is a content analysis of women appearing in advertisements in two types of magazines: fitness/health versus fashion/beauty chosen because of their large and predominantly female readerships. Women appearing in advertisements of the June 2007 issue of five fitness/health magazines were compared to women appearing in advertisements of the June 2007 issue of five beauty/fashion magazines. Female models appearing in advertisements of both types of magazines were primarily young, thin Caucasians; however, images of models were more likely to emphasize appearance over performance when they appeared in fashion magazines. This difference in emphasis has implications for future research.
Jones, Simon R.
2010-01-01
The causes of auditory verbal hallucinations (AVHs) are still unclear. The evidence for 2 prominent cognitive models of AVHs, one based on inner speech, the other on intrusions from memory, is briefly reviewed. The fit of these models, as well as neurological models, to the phenomenology of AVHs is then critically examined. It is argued that only a minority of AVHs, such as those with content clearly relating to verbalizations experienced surrounding previous trauma, are consistent with cognitive AVHs-as-memories models. Similarly, it is argued that current neurological models are only phenomenologically consistent with a limited subset of AVHs. In contrast, the phenomenology of the majority of AVHs, which involve voices attempting to regulate the ongoing actions of the voice hearer, are argued to be more consistent with inner speech–based models. It is concluded that subcategorizations of AVHs may be necessary, with each underpinned by different neurocognitive mechanisms. The need to study what is termed the dynamic developmental progression of AVHs is also highlighted. Future empirical research is suggested in this area. PMID:18820262
Murine animal models for preclinical islet transplantation: No model fits all (research purposes).
Cantarelli, Elisa; Citro, Antonio; Marzorati, Simona; Melzi, Raffaella; Scavini, Marina; Piemonti, Lorenzo
2013-01-01
Advances in islet transplantation research have led to remarkable improvements in the outcome in humans with type 1 diabetes. However, pitfalls, mainly linked both to early liver-specific inflammatory events and to pre-existing and transplant-induced auto- and allo-specific adaptive immune responses, still remain. In this scenario research into pancreatic islet transplantation, essential to investigate new strategies to overcome open issues, needs very well-designed preclinical studies to obtain consistent and reliable results and select only promising strategies that may be translated into the clinical practice. This review discusses the main shortcomings of the mouse models currently used in islet transplantation research, outlining the main factors and variables to take into account for the design of new preclinical studies. Since several parameters concerning both the graft (i.e., islets) and the recipient (i.e., diabetic mice) may influence transplant outcome, we recommend considering several critical points in designing future bench-to-bedside islet transplantation research.
Madsen, Jonas S; Lin, Yu-Cheng; Squyres, Georgia R; Price-Whelan, Alexa; de Santiago Torio, Ana; Song, Angela; Cornell, William C; Sørensen, Søren J; Xavier, Joao B; Dietrich, Lars E P
2015-12-01
As biofilms grow, resident cells inevitably face the challenge of resource limitation. In the opportunistic pathogen Pseudomonas aeruginosa PA14, electron acceptor availability affects matrix production and, as a result, biofilm morphogenesis. The secreted matrix polysaccharide Pel is required for pellicle formation and for colony wrinkling, two activities that promote access to O2. We examined the exploitability and evolvability of Pel production at the air-liquid interface (during pellicle formation) and on solid surfaces (during colony formation). Although Pel contributes to the developmental response to electron acceptor limitation in both biofilm formation regimes, we found variation in the exploitability of its production and necessity for competitive fitness between the two systems. The wild type showed a competitive advantage against a non-Pel-producing mutant in pellicles but no advantage in colonies. Adaptation to the pellicle environment selected for mutants with a competitive advantage against the wild type in pellicles but also caused a severe disadvantage in colonies, even in wrinkled colony centers. Evolution in the colony center produced divergent phenotypes, while adaptation to the colony edge produced mutants with clear competitive advantages against the wild type in this O2-replete niche. In general, the structurally heterogeneous colony environment promoted more diversification than the more homogeneous pellicle. These results suggest that the role of Pel in community structure formation in response to electron acceptor limitation is unique to specific biofilm models and that the facultative control of Pel production is required for PA14 to maintain optimum benefit in different types of communities.
Demetrius, Lloyd; Ziehe, Martin
2007-11-01
The term Darwinian fitness refers to the capacity of a variant type to invade and displace the resident population in competition for available resources. Classical models of this dynamical process claim that competitive outcome is a deterministic event which is regulated by the population growth rate, called the Malthusian parameter. Recent analytic studies of the dynamics of competition in terms of diffusion processes show that growth rate predicts invasion success only in populations of infinite size. In populations of finite size, competitive outcome is a stochastic process--contingent on resource constraints--which is determined by the rate at which a population returns to its steady state condition after a random perturbation in the individual birth and death rates. This return rate, a measure of robustness or population stability, is analytically characterized by the demographic parameter, evolutionary entropy, a measure of the uncertainty in the age of the mother of a randomly chosen newborn. This article appeals to computational and numerical methods to contrast the predictive power of the Malthusian and the entropic principles. The computational analysis rejects the Malthusian model and is consistent with of the entropic principle. These studies thus provide support for the general claim that entropy is the appropriate measure of Darwinian fitness and constitutes an evolutionary parameter with broad predictive and explanatory powers.
Genetic analysis of survival and fitness in turkeys with multiple-trait animal models.
Quinton, C D; Wood, B J; Miller, S P
2011-11-01
Genetic parameters for production, survival, and structural fitness traits recorded in pedigreed turkey sire and dam parental lines from a nucleus breeding program were estimated with multiple-trait animal models. Survival and conformation traits were scored in binary terms of health, where 0 = died or affected, and 1 = survived or healthy. Walking ability at 20 wk was subjectively scored from 1 (poor) to 6 (excellent). Body weights and egg production displayed moderate heritability (h(2) = 0.18 to 0.35). Early survival (to 3 wk) displayed low heritability (h(2) = 0.02 and 0.04 for the dam and sire lines, respectively). Late survival (3 to 23 wk) and longevity (age at death or cull) had low to moderate heritability (h(2) = 0.12 to 0.14). Walking ability had moderate heritability (h(2) = 0.26, 0.25). Leg structure health displayed low heritability (h(2) = 0.08), as did hip structure, foot, and skin health (h(2) ≤ 0.02). Crop health displayed moderate heritability (h(2) = 0.12). Walking ability, hip and leg structures, footpad, and breast skin health had negative genetic correlations with BW (r(G) = -0.50 to -0.23). Egg production had moderate positive genetic correlation with late survival (r(G) = 0.61). Genetic correlations between early and late survival were close to zero (r(G) = 0.10 and 0.03 for the dam and sire lines, respectively). Walking ability had high positive genetic correlations with late survival, longevity, hip structure, and leg structure in both lines (r(G) = 0.51 to 0.91). These genetic parameters indicate that unchecked selection for growth could decrease survival, walking ability, and hip, leg, footpad, and skin health in turkeys. However, index selection should be effective at improving fitness, survival, and growth simultaneously in commercial turkey lines. Walking ability should be a good indicator trait for selection to improve overall late survival and hip and leg health in turkeys.
A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit
NASA Technical Reports Server (NTRS)
Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.
2016-01-01
Suboptimal suit fit is a known risk factor for crewmember shoulder injury. Suit fit assessment is however prohibitively time consuming and cannot be generalized across wide variations of body shapes and poses. In this work, we have developed a new design tool based on the statistical analysis of body shape scans. This tool is aimed at predicting the skin deformation and shape variations for any body size and shoulder pose for a target population. This new process, when incorporated with CAD software, will enable virtual suit fit assessments, predictively quantifying the contact volume, and clearance between the suit and body surface at reduced time and cost.
The fitting of general force-of-infection models to wildlife disease prevalence data
Heisey, D.M.; Joly, D.O.; Messier, F.
2006-01-01
Researchers and wildlife managers increasingly find themselves in situations where they must deal with infectious wildlife diseases such as chronic wasting disease, brucellosis, tuberculosis, and West Nile virus. Managers are often charged with designing and implementing control strategies, and researchers often seek to determine factors that influence and control the disease process. All of these activities require the ability to measure some indication of a disease's foothold in a population and evaluate factors affecting that foothold. The most common type of data available to managers and researchers is apparent prevalence data. Apparent disease prevalence, the proportion of animals in a sample that are positive for the disease, might seem like a natural measure of disease's foothold, but several properties, in particular, its dependency on age structure and the biasing effects of disease-associated mortality, make it less than ideal. In quantitative epidemiology, the a??force of infection,a?? or infection hazard, is generally the preferred parameter for measuring a disease's foothold, and it can be viewed as the most appropriate way to a??adjusta?? apparent prevalence for age structure. The typical ecology curriculum includes little exposure to quantitative epidemiological concepts such as cumulative incidence, apparent prevalence, and the force of infection. The goal of this paper is to present these basic epidemiological concepts and resulting models in an ecological context and to illustrate how they can be applied to understand and address basic epidemiological questions. We demonstrate a practical approach to solving the heretofore intractable problem of fitting general force-of-infection models to wildlife prevalence data using a generalized regression approach. We apply the procedures to Mycobacterium bovis (bovine tuberculosis) prevalence in bison (Bison bison) in Wood Buffalo National Park, Canada, and demonstrate strong age dependency in the force of
Development of a Stellar Model-Fitting Pipeline for Asteroseismic Data from the TESS Mission
NASA Astrophysics Data System (ADS)
Metcalfe, Travis
The launch of NASA's Kepler space telescope in 2009 revolutionized the quality and quantity of observational data available for asteroseismic analysis. Prior to the Kepler mission, solar-like oscillations were extremely difficult to observe, and data only existed for a handful of the brightest stars in the sky. With the necessity of studying one star at a time, the traditional approach to extracting the physical properties of the star from the observations was an uncomfortably subjective process. A variety of experts could use similar tools but come up with significantly different answers. Not only did this subjectivity have the potential to undermine the credibility of the technique, it also hindered the compilation of a uniform sample that could be used to draw broader physical conclusions from the ensemble of results. During a previous award from NASA, we addressed these issues by developing an automated and objective stellar model-fitting pipeline for Kepler data, and making it available through the Asteroseismic Modeling Portal (AMP). This community modeling tool has allowed us to derive reliable asteroseismic radii, masses and ages for large samples of stars (Metcalfe et al. 2014), but the most recent observations are so precise that we are now limited by systematic uncertainties associated with our stellar models. With a huge archive of Kepler data available for model validation, and the next planet-hunting satellite already approved for an expected launch in 2017, now is the time to incorporate what we have learned into the next generation of AMP. We propose to improve the reliability of our estimates of stellar properties over the next 4 years by collaborating with two open-source development projects that will augment and ultimately replace the stellar evolution and pulsation models that we now use in AMP. Our current treatment of the oscillations does not include the effects of radiative or convective heat-exchange, nor does it account for the influence
Zhang, Chuanwei; Liu, Shiyuan; Shi, Tielin; Tang, Zirong
2011-02-01
The success of the model-based infrared reflectrometry (MBIR) technique relies heavily on accurate modeling and fast calculation of the infrared metrology process, which continues to be a challenge, especially for three-dimensional (3D) trench structures. In this paper, we present a simplified formulation for effective medium approximation (EMA), determined by a fitting-based method for the modeling of 3D trench structures. Intensive investigations have been performed with an emphasis on the generality of the fitting-determined (FD)-EMA formulation in terms of trench depth, trench pitch, and incidence angle so that its application is not limited to a particular configuration. Simulations conducted on a taper trench structure have further verified the proposed FD-EMA and demonstrated that the MBIR metrology with the FD-EMA-based model achieves an accuracy one order higher than that of the conventional zeroth-order EMA-based model.
Stress physiology in marine mammals: how well do they fit the terrestrial model?
Atkinson, Shannon; Crocker, Daniel; Houser, Dorian; Mashburn, Kendall
2015-07-01
Stressors are commonly accepted as the causal factors, either internal or external, that evoke physiological responses to mediate the impact of the stressor. The majority of research on the physiological stress response, and costs incurred to an animal, has focused on terrestrial species. This review presents current knowledge on the physiology of the stress response in a lesser studied group of mammals, the marine mammals. Marine mammals are an artificial or pseudo grouping from a taxonomical perspective, as this group represents several distinct and diverse orders of mammals. However, they all are fully or semi-aquatic animals and have experienced selective pressures that have shaped their physiology in a manner that differs from terrestrial relatives. What these differences are and how they relate to the stress response is an efflorescent topic of study. The identification of the many facets of the stress response is critical to marine mammal management and conservation efforts. Anthropogenic stressors in marine ecosystems, including ocean noise, pollution, and fisheries interactions, are increasing and the dramatic responses of some marine mammals to these stressors have elevated concerns over the impact of human-related activities on a diverse group of animals that are difficult to monitor. This review covers the physiology of the stress response in marine mammals and places it in context of what is known from research on terrestrial mammals, particularly with respect to mediator activity that diverges from generalized terrestrial models. Challenges in conducting research on stress physiology in marine mammals are discussed and ways to overcome these challenges in the future are suggested.
ERIC Educational Resources Information Center
Tay, Louis; Drasgow, Fritz
2012-01-01
Two Monte Carlo simulation studies investigated the effectiveness of the mean adjusted X[superscript 2]/df statistic proposed by Drasgow and colleagues and, because of problems with the method, a new approach for assessing the goodness of fit of an item response theory model was developed. It has been previously recommended that mean adjusted…
ERIC Educational Resources Information Center
Hansen, Mark; Cai, Li; Monroe, Scott; Li, Zhen
2014-01-01
It is a well-known problem in testing the fit of models to multinomial data that the full underlying contingency table will inevitably be sparse for tests of reasonable length and for realistic sample sizes. Under such conditions, full-information test statistics such as Pearson's X[superscript 2]?? and the likelihood ratio statistic…
ERIC Educational Resources Information Center
O'Neill, James M.; Clark, Jeffrey K.; Jones, James A.
2016-01-01
Background: In elementary grades, comprehensive health education curricula have demonstrated effectiveness in addressing singular health issues. The Michigan Model for Health (MMH) was implemented and evaluated to determine its impact on nutrition, physical fitness, and safety knowledge and skills. Methods: Schools (N = 52) were randomly assigned…
ERIC Educational Resources Information Center
Gallini, Joan K., Mandeville, Garrett K.
1984-01-01
This Monte Carlo study examined the validity of the chi-square test for model evaluation in different instances of misspecification and sample size. The usefulness of the chi-square difference statistic to compare competing structures and improvement in fit is also addressed. (Author/BS)
Madsen, Jonas S.; Lin, Yu-Cheng; Squyres, Georgia R.; Price-Whelan, Alexa; de Santiago Torio, Ana; Song, Angela; Cornell, William C.; Sørensen, Søren J.
2015-01-01
As biofilms grow, resident cells inevitably face the challenge of resource limitation. In the opportunistic pathogen Pseudomonas aeruginosa PA14, electron acceptor availability affects matrix production and, as a result, biofilm morphogenesis. The secreted matrix polysaccharide Pel is required for pellicle formation and for colony wrinkling, two activities that promote access to O2. We examined the exploitability and evolvability of Pel production at the air-liquid interface (during pellicle formation) and on solid surfaces (during colony formation). Although Pel contributes to the developmental response to electron acceptor limitation in both biofilm formation regimes, we found variation in the exploitability of its production and necessity for competitive fitness between the two systems. The wild type showed a competitive advantage against a non-Pel-producing mutant in pellicles but no advantage in colonies. Adaptation to the pellicle environment selected for mutants with a competitive advantage against the wild type in pellicles but also caused a severe disadvantage in colonies, even in wrinkled colony centers. Evolution in the colony center produced divergent phenotypes, while adaptation to the colony edge produced mutants with clear competitive advantages against the wild type in this O2-replete niche. In general, the structurally heterogeneous colony environment promoted more diversification than the more homogeneous pellicle. These results suggest that the role of Pel in community structure formation in response to electron acceptor limitation is unique to specific biofilm models and that the facultative control of Pel production is required for PA14 to maintain optimum benefit in different types of communities. PMID:26431965
Linking the Fits, Fitting the Links: Connecting Different Types of PO Fit to Attitudinal Outcomes
ERIC Educational Resources Information Center
Leung, Aegean; Chaturvedi, Sankalp
2011-01-01
In this paper we explore the linkages among various types of person-organization (PO) fit and their effects on employee attitudinal outcomes. We propose and test a conceptual model which links various types of fits--objective fit, perceived fit and subjective fit--in a hierarchical order of cognitive information processing and relate them to…
ERIC Educational Resources Information Center
Awuah, Lawrence J.
2012-01-01
Understanding citizens' adoption of electronic-government (e-government) is an important topic, as the use of e-government has become an integral part of governance. Success of such initiatives depends largely on the efficient use of e-government services. The unified theory of acceptance and use of technology (UTAUT) model has provided a…
Brewer, Shannon K.; Worthington, Thomas A.; Zhang, Tianjioa; Logue, Daniel R.; Mittelstet, Aaron R.
2016-01-01
Truncated distributions of pelagophilic fishes have been observed across the Great Plains of North America, with water use and landscape fragmentation implicated as contributing factors. Developing conservation strategies for these species is hindered by the existence of multiple competing flow regime hypotheses related to species persistence. Our primary study objective was to compare the predicted distributions of one pelagophil, the Arkansas River Shiner Notropis girardi, constructed using different flow regime metrics. Further, we investigated different approaches for improving temporal transferability of the species distribution model (SDM). We compared four hypotheses: mean annual flow (a baseline), the 75th percentile of daily flow, the number of zero-flow days, and the number of days above 55th percentile flows, to examine the relative importance of flows during the spawning period. Building on an earlier SDM, we added covariates that quantified wells in each catchment, point source discharges, and non-native species presence to a structured variable framework. We assessed the effects on model transferability and fit by reducing multicollinearity using Spearman’s rank correlations, variance inflation factors, and principal component analysis, as well as altering the regularization coefficient (β) within MaxEnt. The 75th percentile of daily flow was the most important flow metric related to structuring the species distribution. The number of wells and point source discharges were also highly ranked. At the default level of β, model transferability was improved using all methods to reduce collinearity; however, at higher levels of β, the correlation method performed best. Using β = 5 provided the best model transferability, while retaining the majority of variables that contributed 95% to the model. This study provides a workflow for improving model transferability and also presents water-management options that may be considered to improve the
Rather, Manzoor A; Bhat, Bilal A; Qurishi, Mushtaq A
2013-12-15
Natural product based drugs constitute a substantial proportion of the pharmaceutical market particularly in the therapeutic areas of infectious diseases and oncology. The primary focus of any drug development program so far has been to design selective ligands (drugs) that act on single selective disease targets to obtain highly efficacious and safe drugs with minimal side effects. Although this approach has been successful for many diseases, yet there is a significant decline in the number of new drug candidates being introduced into clinical practice over the past few decades. This serious innovation deficit that the pharmaceutical industries are facing is due primarily to the post-marketing failures of blockbuster drugs. Many analysts believe that the current capital-intensive model-"the one drug to fit all" approach will be unsustainable in future and that a new "less investment, more drugs" model is necessary for further scientific growth. It is now well established that many diseases are multi-factorial in nature and that cellular pathways operate more like webs than highways. There are often multiple ways or alternate routes that may be switched on in response to the inhibition of a specific target. This gives rise to the resistant cells or resistant organisms under the specific pressure of a targeted agent, resulting in drug resistance and clinical failure of the drug. Drugs designed to act against individual molecular targets cannot usually combat multifactorial diseases like cancer, or diseases that affect multiple tissues or cell types such as diabetes and immunoinflammatory diseases. Combination drugs that affect multiple targets simultaneously are better at controlling complex disease systems and are less prone to drug resistance. This multicomponent therapy forms the basis of phytotherapy or phytomedicine where the holistic therapeutic effect arises as a result of complex positive (synergistic) or negative (antagonistic) interactions between
NASA Astrophysics Data System (ADS)
Sire, Clément; Majumdar, Satya N.; Dean, David S.
2006-07-01
A simplified form of the time-dependent evolutionary dynamics of a quasispecies model with a rugged fitness landscape is solved via a mapping onto a random flux model whose asymptotic behaviour can be described in terms of a random walk. The statistics of the number of changes of the dominant genotype from a finite set of genotypes are exactly obtained confirming existing conjectures based on numerics.
Developing a New Instrument for Assessing Acceptance of Change
Di Fabio, Annamaria; Gori, Alessio
2016-01-01
This article focuses on the usefulness of going beyond the concept of resistance to change and capitalizing on the use of a model that includes positivity and acceptance of change. We first discuss the theoretical background of this new construct in the work and organizational fields and then evaluate the psychometric properties of a new measure for assessing acceptance of change. The results of exploratory factor analysis indicated a factor structure with five principal dimensions; besides confirmatory factor analysis (CFA) goodness of fit indices indicated a good fit of the model to the data. All the dimensions showed good values of internal consistency. The results of the present study indicate that the Acceptance of Change Scale (ACS) is a brief and easily administered instrument with good psychometric properties that can promote the development of clients' strengths and the growth of a sense of Self, thereby helping them choose their own way without losing any opportunities in their lives and their work. PMID:27303356
Jbabdi, Saad; Sotiropoulos, Stamatios N; Savio, Alexander M; Graña, Manuel; Behrens, Timothy EJ
2012-01-01
In this article, we highlight an issue that arises when using multiple b-values in a model-based analysis of diffusion MR data for tractography. The non-mono-exponential decay, commonly observed in experimental data, is shown to induce over-fitting in the distribution of fibre orientations when not considered in the model. Extra fibre orientations perpendicular to the main orientation arise to compensate for the slower apparent signal decay at higher b-values. We propose a simple extension to the ball and stick model based on a continuous Gamma distribution of diffusivities, which significantly improves the fitting and reduces the over-fitting. Using in-vivo experimental data, we show that this model outperforms a simpler, noise floor model, especially at the interfaces between brain tissues, suggesting that partial volume effects are a major cause of the observed non-mono-exponential decay. This model may be helpful for future data acquisition strategies that may attempt to combine multiple shells to improve estimates of fibre orientations in white matter and near the cortex. PMID:22334356
Pleasure and Pain: Experiences of Fitness Testing
ERIC Educational Resources Information Center
Wrench, Alison; Garrett, Robyne
2008-01-01
The obesity crisis is a hegemonic discourse that has established common-sense understandings that young people are less active and fit than previous generations. Unquestioning acceptance of links between fitness and obesity in turn leads to unproblematic fitness testing of young people. Argument is made that fitness tests motivate and encourage…
Quasispecies on Fitness Landscapes.
Schuster, Peter
2016-01-01
Selection-mutation dynamics is studied as adaptation and neutral drift on abstract fitness landscapes. Various models of fitness landscapes are introduced and analyzed with respect to the stationary mutant distributions adopted by populations upon them. The concept of quasispecies is introduced, and the error threshold phenomenon is analyzed. Complex fitness landscapes with large scatter of fitness values are shown to sustain error thresholds. The phenomenological theory of the quasispecies introduced in 1971 by Eigen is compared to approximation-free numerical computations. The concept of strong quasispecies understood as mutant distributions, which are especially stable against changes in mutations rates, is presented. The role of fitness neutral genotypes in quasispecies is discussed.
Using Fit Indexes to Select a Covariance Model for Longitudinal Data
ERIC Educational Resources Information Center
Liu, Siwei; Rovine, Michael J.; Molenaar, Peter C. M.
2012-01-01
This study investigated the performance of fit indexes in selecting a covariance structure for longitudinal data. Data were simulated to follow a compound symmetry, first-order autoregressive, first-order moving average, or random-coefficients covariance structure. We examined the ability of the likelihood ratio test (LRT), root mean square error…
Testing the Youth Physical Activity Promotion Model: Fatness and Fitness as Enabling Factors
ERIC Educational Resources Information Center
Chen, Senlin; Welk, Gregory J.; Joens-Matre, Roxane R.
2014-01-01
As the prevalence of childhood obesity increases, it is important to examine possible differences in psychosocial correlates of physical activity between normal weight and overweight children. The study examined fatness (weight status) and (aerobic) fitness as Enabling factors related to youth physical activity within the Youth Physical Activity…
Work, Family, and Mental Health: Testing Different Models of Work-Family Fit.
ERIC Educational Resources Information Center
Grzywacz, Joseph G.; Bass, Brenda L.
2003-01-01
Using family resilience theory, this study examined the effects of work-family conflict and work-family facilitation on mental health among working adults to gain a better understanding of work-family fit. Results suggest that family to work facilitation is a family protective factor that offsets and buffers the deleterious effects of work-family…
Gray Matter Correlates of Fluid, Crystallized, and Spatial Intelligence: Testing the P-FIT Model
ERIC Educational Resources Information Center
Colom, Roberto; Haier, Richard J.; Head, Kevin; Alvarez-Linera, Juan; Quiroga, Maria Angeles; Shih, Pei Chun; Jung, Rex E.
2009-01-01
The parieto-frontal integration theory (P-FIT) nominates several areas distributed throughout the brain as relevant for intelligence. This theory was derived from previously published studies using a variety of both imaging methods and tests of cognitive ability. Here we test this theory in a new sample of young healthy adults (N = 100) using a…
Implementation of a Personal Fitness Unit Using the Personalized System of Instruction Model
ERIC Educational Resources Information Center
Prewitt, Steven; Hannon, James C.; Colquitt, Gavin; Brusseau, Timothy A.; Newton, Maria; Shaw, Janet
2015-01-01
Levels of physical activity and health-related fitness (HRF) are decreasing among adolescents in the United States. Several interventions have been implemented to reverse this downtrend. Traditionally, physical educators incorporate a direct instruction (DI) strategy, with teaching potentially leading students to disengage during class. An…
Mesler, Robert A.; Pihlstroem, Ylva M.
2013-09-01
We perform calorimetry on the bright gamma-ray burst GRB 030329 by fitting simultaneously the broadband radio afterglow and the observed afterglow image size to a semi-analytic MHD and afterglow emission model. Our semi-analytic method is valid in both the relativistic and non-relativistic regimes, and incorporates a model of the interstellar scintillation that substantially effects the broadband afterglow below 10 GHz. The model is fitted to archival measurements of the afterglow flux from 1 day to 8.3 yr after the burst. Values for the initial burst parameters are determined and the nature of the circumburst medium is explored. Additionally, direct measurements of the lateral expansion rate of the radio afterglow image size allow us to estimate the initial Lorentz factor of the jet.
Alcalá-Quintana, Rocío; García-Pérez, Miguel A
2013-12-01
Research on temporal-order perception uses temporal-order judgment (TOJ) tasks or synchrony judgment (SJ) tasks in their binary SJ2 or ternary SJ3 variants. In all cases, two stimuli are presented with some temporal delay, and observers judge the order of presentation. Arbitrary psychometric functions are typically fitted to obtain performance measures such as sensitivity or the point of subjective simultaneity, but the parameters of these functions are uninterpretable. We describe routines in MATLAB and R that fit model-based functions whose parameters are interpretable in terms of the processes underlying temporal-order and simultaneity judgments and responses. These functions arise from an independent-channels model assuming arrival latencies with exponential distributions and a trichotomous decision space. Different routines fit data separately for SJ2, SJ3, and TOJ tasks, jointly for any two tasks, or also jointly for the three tasks (for common cases in which two or even the three tasks were used with the same stimuli and participants). Additional routines provide bootstrap p-values and confidence intervals for estimated parameters. A further routine is included that obtains performance measures from the fitted functions. An R package for Windows and source code of the MATLAB and R routines are available as Supplementary Files.
Ferreira, Abílio G T; Henrique, Douglas S; Vieira, Ricardo A M; Maeda, Emilyn M; Valotto, Altair A
2015-03-01
The objective of this study was to evaluate four mathematical models with regards to their fit to lactation curves of Holstein cows from herds raised in the southwestern region of the state of Parana, Brazil. Initially, 42,281 milk production records from 2005 to 2011 were obtained from "Associação Paranaense de Criadores de Bovinos da Raça Holandesa (APCBRH)". Data lacking dates of drying and total milk production at 305 days of lactation were excluded, resulting in a remaining 15,142 records corresponding to 2,441 Holstein cows. Data were sorted according to the parity order (ranging from one to six), and within each parity order the animals were divided into quartiles (Q25%, Q50%, Q75% and Q100%) corresponding to 305-day lactation yield. Within each parity order, for each quartile, four mathematical models were adjusted, two of which were predominantly empirical (Brody and Wood) whereas the other two presented more mechanistic characteristics (models Dijkstra and Pollott). The quality of fit was evaluated by the corrected Akaike information criterion. The Wood model showed the best fit in almost all evaluated situations and, therefore, may be considered as the most suitable model to describe, at least empirically, the lactation curves of Holstein cows raised in Southwestern Parana.
Seasonality of Influenza A(H7N9) Virus in China—Fitting Simple Epidemic Models to Human Cases
Lin, Qianying; Lin, Zhigui; Chiu, Alice P. Y.; He, Daihai
2016-01-01
Background Three epidemic waves of influenza A(H7N9) (hereafter ‘H7N9’) human cases have occurred between March 2013 and July 2015 in China. However, the underlying transmission mechanism remains unclear. Our main objective is to use mathematical models to study how seasonality, secular changes and environmental transmission play a role in the spread of H7N9 in China. Methods Data on human cases and chicken cases of H7N9 infection were downloaded from the EMPRES-i Global Animal Disease Information System. We modelled on chicken-to-chicken transmission, assuming a constant ratio of 10−6 human case per chicken case, and compared the model fit with the observed human cases. We developed three different modified Susceptible-Exposed-Infectious-Recovered-Susceptible models: (i) a non-periodic transmission rate model with an environmental class, (ii) a non-periodic transmission rate model without an environmental class, and (iii) a periodic transmission rate model with an environmental class. We then estimated the key epidemiological parameters and compared the model fit using Akaike Information Criterion and Bayesian Information Criterion. Results Our results showed that a non-periodic transmission rate model with an environmental class provided the best model fit to the observed human cases in China during the study period. The estimated parameter values were within biologically plausible ranges. Conclusions This study highlighted the importance of considering secular changes and environmental transmission in the modelling of human H7N9 cases. Secular changes were most likely due to control measures such as Live Poultry Markets closures that were implemented during the initial phase of the outbreaks in China. Our results suggested that environmental transmission via viral shedding of infected chickens had contributed to the spread of H7N9 human cases in China. PMID:26963937
Implementation of the Iterative Proportion Fitting Algorithm for Geostatistical Facies Modeling
Li Yupeng Deutsch, Clayton V.
2012-06-15
In geostatistics, most stochastic algorithm for simulation of categorical variables such as facies or rock types require a conditional probability distribution. The multivariate probability distribution of all the grouped locations including the unsampled location permits calculation of the conditional probability directly based on its definition. In this article, the iterative proportion fitting (IPF) algorithm is implemented to infer this multivariate probability. Using the IPF algorithm, the multivariate probability is obtained by iterative modification to an initial estimated multivariate probability using lower order bivariate probabilities as constraints. The imposed bivariate marginal probabilities are inferred from profiles along drill holes or wells. In the IPF process, a sparse matrix is used to calculate the marginal probabilities from the multivariate probability, which makes the iterative fitting more tractable and practical. This algorithm can be extended to higher order marginal probability constraints as used in multiple point statistics. The theoretical framework is developed and illustrated with estimation and simulation example.
Strategy for Fitting Neuronal Models to Dual Patch Data under Multiple Stimulation Protocols
2007-11-02
intensity of ON shock was controlled at weak, median and strong level which caused weak, median and strong excitatory post-synaptic potential ( EPSP ...known from the experiment. The equations of the glutamatergic EPSP can be found in [5]. EPSP consisted of both α -amino-3-hydroxy- 5-methyl-4-isoxazole...the 43 parameters, there were two additional unknown parameters that needed to be fit for each EPSP stimulation protocol. All the unknown parameters
The Effects of Selected Death Education Curriculum Models on Death Anxiety and Death Acceptance.
ERIC Educational Resources Information Center
Combs, Don C.
1981-01-01
A comparison of the effects of didactic and experiential death education curriculums show no decrease in death anxiety from mid- to posttesting for any treatment group. Anxiety was increased from pre- to mid-testing for some students. Results may be due to model deficiencies. Further research is suggested. (JAC)
ERIC Educational Resources Information Center
Fletcher, Jordan L.
2013-01-01
Developing nations are poised to spend billions on information and communication technology (ICT) innovation in 2020. A study of the historical adoption of ICT in developing nations has indicated that their adoption patterns do not follow typical technology innovation adoption models. This study addressed the weaknesses found in existing…
Escobar-Rodríguez, Tomás; Romero-Alonso, María Mercedes
2013-05-01
This article analyzes the attitude of nurses toward the use of automated unit-based medication storage and distribution systems and identifies influencing factors. Understanding these factors provides an opportunity to explore actions that might be taken to boost adoption by potential users. The theoretical grounding for this research is the Technology Acceptance Model. The Technology Acceptance Model specifies the causal relationships between perceived usefulness, perceived ease of use, attitude toward using, and actual usage behavior. The research model has six constructs, and nine hypotheses were generated from connections between these six constructs. These constructs include perceived risks, experience level, and training. The findings indicate that these three external variables are related to the perceived ease of use and perceived usefulness of automated unit-based medication storage and distribution systems, and therefore, they have a significant influence on attitude toward the use of these systems.
Measures of relative fitness of social behaviors in finite structured population models.
Tarnita, Corina E; Taylor, Peter D
2014-10-01
How should we measure the relative selective advantage of different behavioral strategies? The various approaches to this question have fallen into one of the following categories: the fixation probability of a mutant allele in a wild type population, some measures of gene frequency and gene frequency change, and a formulation of the inclusive fitness effect. Countless theoretical studies have examined the relationship between these approaches, and it has generally been thought that, under standard simplifying assumptions, they yield equivalent results. Most of this theoretical work, however, has assumed homogeneity of the population interaction structure--that is, that all individuals are equivalent. We explore the question of selective advantage in a general (heterogeneous) population and show that, although appropriate measures of fixation probability and gene frequency change are equivalent, they are not, in general, equivalent to the inclusive fitness effect. The latter does not reflect effects of selection acting via mutation, which can arise on heterogeneous structures, even for low mutation. Our theoretical framework provides a transparent analysis of the different biological factors at work in the comparison of these fitness measures and suggests that their theoretical and empirical use needs to be revised and carefully grounded in a more general theory.
An Escherichia coli asr mutant has decreased fitness during colonization in a mouse model.
Armalyte, Julija; Seputiene, Vaida; Melefors, Ojar; Suziedeliene, Edita
2008-01-01
The Escherichia coli asr gene, like its homologues in other enterobacteria, is strongly induced by low external pH. The E. coli asr mutant shows weakened ability to adapt to acidic pH. This suggests that the asr gene product is important for enterobacterial species, both commensal and pathogenic, in overcoming acid stress in the stomach and subsequently colonizing the intestine. We examined the relative fitness of an E. coli asr mutant compared to a wild type, by feeding both strains simultaneously to mice and letting them colonize the intestine. Analysis of the bacteria after passage through the intestine showed up to five orders of magnitude less asr mutant than wild type. Transcomplementation of the asr gene on a plasmid partially restored the number of mutants. Similar competition in liquid media demonstrated that the asr mutant has reduced viability during long-term incubation in rich media, but is as fit as the wild type when bacteria are challenged in minimal medium. Competition carried out under different pH conditions proved that pH of the media was not the main determinant leading to the decreased fitness of the asr mutant. This suggests that the asr gene product is important for adaptation to stress conditions other than acidity, including long periods of starvation.
NASA Technical Reports Server (NTRS)
Johnson, T. J.; Harding, A. K.; Venter, C.
2012-01-01
Pulsed gamma rays have been detected with the Fermi Large Area Telescope (LAT) from more than 20 millisecond pulsars (MSPs), some of which were discovered in radio observations of bright, unassociated LAT sources. We have fit the radio and gamma-ray light curves of 19 LAT-detected MSPs in the context of geometric, outermagnetospheric emission models assuming the retarded vacuum dipole magnetic field using a Markov chain Monte Carlo maximum likelihood technique. We find that, in many cases, the models are able to reproduce the observed light curves well and provide constraints on the viewing geometries that are in agreement with those from radio polarization measurements. Additionally, for some MSPs we constrain the altitudes of both the gamma-ray and radio emission regions. The best-fit magnetic inclination angles are found to cover a broader range than those of non-recycled gamma-ray pulsars.
ERIC Educational Resources Information Center
Maydeu-Olivares, Alberto; Montano, Rosa
2013-01-01
We investigate the performance of three statistics, R [subscript 1], R [subscript 2] (Glas in "Psychometrika" 53:525-546, 1988), and M [subscript 2] (Maydeu-Olivares & Joe in "J. Am. Stat. Assoc." 100:1009-1020, 2005, "Psychometrika" 71:713-732, 2006) to assess the overall fit of a one-parameter logistic model…
Blissett, Jackie; Bennett, Carmel; Fogel, Anna; Harris, Gillian; Higgs, Suzanne
2016-02-14
Few children consume the recommended portions of fruit or vegetables. This study examined the effects of parental physical prompting and parental modelling in children's acceptance of a novel fruit (NF) and examined the role of children's food-approach and food-avoidance traits on NF engagement and consumption. A total of 120 caregiver-child dyads (fifty-four girls, sixty-six boys) participated in this study. Dyads were allocated to one of the following three conditions: physical prompting but no modelling, physical prompting and modelling or a modelling only control condition. Dyads ate a standardised meal containing a portion of a fruit new to the child. Parents completed measures of children's food approach and avoidance. Willingness to try the NF was observed, and the amount of the NF consumed was measured. Physical prompting but no modelling resulted in greater physical refusal of the NF. There were main effects of enjoyment of food and food fussiness on acceptance. Food responsiveness interacted with condition such that children who were more food responsive had greater NF acceptance in the prompting and modelling conditions in comparison with the modelling only condition. In contrast, children with low food responsiveness had greater acceptance in the modelling control condition than in the prompting but no modelling condition. Physical prompting in the absence of modelling is likely to be detrimental to NF acceptance. Parental use of physical prompting strategies, in combination with modelling of NF intake, may facilitate acceptance of NF, but only in food-responsive children. Modelling consumption best promotes acceptance in children with low food responsiveness.
White, J Wilson; Nickols, Kerry J; Malone, Daniel; Carr, Mark H; Starr, Richard M; Cordoleani, Flora; Baskett, Marissa L; Hastings, Alan; Botsford, Louis W
2016-12-01
Integral projection models (IPMs) have a number of advantages over matrix-model approaches for analyzing size-structured population dynamics, because the latter require parameter estimates for each age or stage transition. However, IPMs still require appropriate data. Typically they are parameterized using individual-scale relationships between body size and demographic rates, but these are not always available. We present an alternative approach for estimating demographic parameters from time series of size-structured survey data using a Bayesian state-space IPM (SSIPM). By fitting an IPM in a state-space framework, we estimate unknown parameters and explicitly account for process and measurement error in a dataset to estimate the underlying process model dynamics. We tested our method by fitting SSIPMs to simulated data; the model fit the simulated size distributions well and estimated unknown demographic parameters accurately. We then illustrated our method using nine years of annual surveys of the density and size distribution of two fish species (blue rockfish, Sebastes mystinus, and gopher rockfish, S. carnatus) at seven kelp forest sites in California. The SSIPM produced reasonable fits to the data, and estimated fishing rates for both species that were higher than our Bayesian prior estimates based on coast-wide stock assessment estimates of harvest. That improvement reinforces the value of being able to estimate demographic parameters from local-scale monitoring data. We highlight a number of key decision points in SSIPM development (e.g., open vs. closed demography, number of particles in the state-space filter) so that users can apply the method to their own datasets.
Yu, Lin; McCracken, Lance M
2016-02-01
Acceptance and commitment therapy (ACT) is one of the so called "third-wave" cognitive behavioral therapies. It has been increasingly applied to chronic pain, and there is accumulating evidence to support its effectiveness. ACT is based on a model of general human functioning called the psychological flexibility (PF) model. Most facets of the PF model have been examined in chronic pain. However, a potential key facet related to "self" appears underappreciated. Indeed, a positive or healthy sense of self seems essential to our well-being, and there have been numerous studies of the self in chronic pain. At the same time, these studies are not currently well organized or easy to summarize. This lack of clarity and integration creates barriers to progress in this area of research. PF with its explicit inclusion of self-related therapeutic processes within a broad, integrative, theoretical model may help. The current review summarizes the PF model in the context of chronic pain with a specific emphasis on the parts of the model that address self-related processes.
Fitting and Calibrating a Multilevel Mixed-Effects Stem Taper Model for Maritime Pine in NW Spain.
Arias-Rodil, Manuel; Castedo-Dorado, Fernando; Cámara-Obregón, Asunción; Diéguez-Aranda, Ulises
2015-01-01
Stem taper data are usually hierarchical (several measurements per tree, and several trees per plot), making application of a multilevel mixed-effects modelling approach essential. However, correlation between trees in the same plot/stand has often been ignored in previous studies. Fitting and calibration of a variable-exponent stem taper function were conducted using data from 420 trees felled in even-aged maritime pine (Pinus pinaster Ait.) stands in NW Spain. In the fitting step, the tree level explained much more variability than the plot level, and therefore calibration at plot level was omitted. Several stem heights were evaluated for measurement of the additional diameter needed for calibration at tree level. Calibration with an additional diameter measured at between 40 and 60% of total tree height showed the greatest improvement in volume and diameter predictions. If additional diameter measurement is not available, the fixed-effects model fitted by the ordinary least squares technique should be used. Finally, we also evaluated how the expansion of parameters with random effects affects the stem taper prediction, as we consider this a key question when applying the mixed-effects modelling approach to taper equations. The results showed that correlation between random effects should be taken into account when assessing the influence of random effects in stem taper prediction.
Fitting and Calibrating a Multilevel Mixed-Effects Stem Taper Model for Maritime Pine in NW Spain
Arias-Rodil, Manuel; Castedo-Dorado, Fernando; Cámara-Obregón, Asunción; Diéguez-Aranda, Ulises
2015-01-01
Stem taper data are usually hierarchical (several measurements per tree, and several trees per plot), making application of a multilevel mixed-effects modelling approach essential. However, correlation between trees in the same plot/stand has often been ignored in previous studies. Fitting and calibration of a variable-exponent stem taper function were conducted using data from 420 trees felled in even-aged maritime pine (Pinus pinaster Ait.) stands in NW Spain. In the fitting step, the tree level explained much more variability than the plot level, and therefore calibration at plot level was omitted. Several stem heights were evaluated for measurement of the additional diameter needed for calibration at tree level. Calibration with an additional diameter measured at between 40 and 60% of total tree height showed the greatest improvement in volume and diameter predictions. If additional diameter measurement is not available, the fixed-effects model fitted by the ordinary least squares technique should be used. Finally, we also evaluated how the expansion of parameters with random effects affects the stem taper prediction, as we consider this a key question when applying the mixed-effects modelling approach to taper equations. The results showed that correlation between random effects should be taken into account when assessing the influence of random effects in stem taper prediction. PMID:26630156
Using Geometry-Based Metrics as Part of Fitness-for-Purpose Evaluations of 3D City Models
NASA Astrophysics Data System (ADS)
Wong, K.; Ellul, C.
2016-10-01
Three-dimensional geospatial information is being increasingly used in a range of tasks beyond visualisation. 3D datasets, however, are often being produced without exact specifications and at mixed levels of geometric complexity. This leads to variations within the models' geometric and semantic complexity as well as the degree of deviation from the corresponding real world objects. Existing descriptors and measures of 3D data such as CityGML's level of detail are perhaps only partially sufficient in communicating data quality and fitness-for-purpose. This study investigates whether alternative, automated, geometry-based metrics describing the variation of complexity within 3D datasets could provide additional relevant information as part of a process of fitness-for-purpose evaluation. The metrics include: mean vertex/edge/face counts per building; vertex/face ratio; minimum 2D footprint area and; minimum feature length. Each metric was tested on six 3D city models from international locations. The results show that geometry-based metrics can provide additional information on 3D city models as part of fitness-for-purpose evaluations. The metrics, while they cannot be used in isolation, may provide a complement to enhance existing data descriptors if backed up with local knowledge, where possible.
Lin, Wen-Yen; Chou, Wen-Cheng; Tsai, Tsai-Hsuan; Lin, Chung-Chih; Lee, Ming-Yih
2016-01-01
Body posture and activity are important indices for assessing health and quality of life, especially for elderly people. Therefore, an easily wearable device or instrumented garment would be valuable for monitoring elderly people’s postures and activities to facilitate healthy aging. In particular, such devices should be accepted by elderly people so that they are willing to wear it all the time. This paper presents the design and development of a novel, textile-based, intelligent wearable vest for real-time posture monitoring and emergency warnings. The vest provides a highly portable and low-cost solution that can be used both indoors and outdoors in order to provide long-term care at home, including health promotion, healthy aging assessments, and health abnormality alerts. The usability of the system was verified using a technology acceptance model-based study of 50 elderly people. The results indicated that although elderly people are anxious about some newly developed wearable technologies, they look forward to wearing this instrumented posture-monitoring vest in the future. PMID:27999324
Lin, Wen-Yen; Chou, Wen-Cheng; Tsai, Tsai-Hsuan; Lin, Chung-Chih; Lee, Ming-Yih
2016-12-17
Body posture and activity are important indices for assessing health and quality of life, especially for elderly people. Therefore, an easily wearable device or instrumented garment would be valuable for monitoring elderly people's postures and activities to facilitate healthy aging. In particular, such devices should be accepted by elderly people so that they are willing to wear it all the time. This paper presents the design and development of a novel, textile-based, intelligent wearable vest for real-time posture monitoring and emergency warnings. The vest provides a highly portable and low-cost solution that can be used both indoors and outdoors in order to provide long-term care at home, including health promotion, healthy aging assessments, and health abnormality alerts. The usability of the system was verified using a technology acceptance model-based study of 50 elderly people. The results indicated that although elderly people are anxious about some newly developed wearable technologies, they look forward to wearing this instrumented posture-monitoring vest in the future.
Schiffelers, Marie-Jeanne W A; Blaauboer, Bas J; Bakker, Wieger E; Beken, Sonja; Hendriksen, Coenraad F M; Koëter, Herman B W M; Krul, Cyrille
2014-06-01
Pharmaceuticals and chemicals are subjected to regulatory safety testing accounting for approximately 25% of laboratory animal use in Europe. This testing meets various objections and has led to the development of a range of 3R models to Replace, Reduce or Refine the animal models. However, these models must overcome many barriers before being accepted for regulatory risk management purposes. This paper describes the barriers and drivers and options to optimize this acceptance process as identified by two expert panels, one on pharmaceuticals and one on chemicals. To untangle the complex acceptance process, the multilevel perspective on technology transitions is applied. This perspective defines influences at the micro-, meso- and macro level which need alignment to induce regulatory acceptance of a 3R model. This paper displays that there are many similar mechanisms within both sectors that prevent 3R models from becoming accepted for regulatory risk assessment and management. Shared barriers include the uncertainty about the value of the new 3R models (micro level), the lack of harmonization of regulatory requirements and acceptance criteria (meso level) and the high levels of risk aversion (macro level). In optimizing the process commitment, communication, cooperation and coordination are identified as critical drivers.
NASA Astrophysics Data System (ADS)
Milani, G.; Hanel, T.; Donetti, R.; Milani, F.
2016-06-01
The paper is aimed at studying the possible interaction between two different accelerators (DPG and TBBS) in the chemical kinetic of Natural Rubber (NR) vulcanized with sulphur. The same blend with several DPG and TBBS concentrations is deeply analyzed from an experimental point of view, varying the curing temperature in the range 150-180°C and obtaining rheometer curves with a step of 10°C. In order to study any possible interaction between the two accelerators -and eventually evaluating its engineering relevance-rheometer data are normalized by means of the well known Sun and Isayev normalization approach and two output parameters are assumed as meaningful to have an insight into the possible interaction, namely time at maximum torque and reversion percentage. Two different numerical meta-models, which belong to the family of the so-called response surfaces RS are compared. The first is linear against TBBS and DPG and therefore well reproduces no interaction between the accelerators, whereas the latter is a non-linear RS with bilinear term. Both RS are deduced from standard best fitting of experimental data available. It is found that, generally, there is a sort of interaction between TBBS and DPG, but that the error introduced making use of a linear model (no interaction) is generally lower than 10%, i.e. fully acceptable from an engineering standpoint.
Valero, Antonio; Pasquali, Frédérique; De Cesare, Alessandra; Manfreda, Gerardo
2014-08-01
Current sampling plans assume a random distribution of microorganisms in food. However, food-borne pathogens are estimated to be heterogeneously distributed in powdered foods. This spatial distribution together with very low level of contaminations raises concern of the efficiency of current sampling plans for the detection of food-borne pathogens like Cronobacter and Salmonella in powdered foods such as powdered infant formula or powdered eggs. An alternative approach based on a Poisson distribution of the contaminated part of the lot (Habraken approach) was used in order to evaluate the probability of falsely accepting a contaminated lot of powdered food when different sampling strategies were simulated considering variables such as lot size, sample size, microbial concentration in the contaminated part of the lot and proportion of contaminated lot. The simulated results suggest that a sample size of 100g or more corresponds to the lower number of samples to be tested in comparison with sample sizes of 10 or 1g. Moreover, the number of samples to be tested greatly decrease if the microbial concentration is 1CFU/g instead of 0.1CFU/g or if the proportion of contamination is 0.05 instead of 0.01. Mean contaminations higher than 1CFU/g or proportions higher than 0.05 did not impact on the number of samples. The Habraken approach represents a useful tool for risk management in order to design a fit-for-purpose sampling plan for the detection of low levels of food-borne pathogens in heterogeneously contaminated powdered food. However, it must be outlined that although effective in detecting pathogens, these sampling plans are difficult to be applied since the huge number of samples that needs to be tested. Sampling does not seem an effective measure to control pathogens in powdered food.
ERIC Educational Resources Information Center
Hsu, Hsien-Yuan; Lin, Jr-Hung; Kwok, Oi-Man; Acosta, Sandra; Willson, Victor
2017-01-01
Several researchers have recommended that level-specific fit indices should be applied to detect the lack of model fit at any level in multilevel structural equation models. Although we concur with their view, we note that these studies did not sufficiently consider the impact of intraclass correlation (ICC) on the performance of level-specific…
ERIC Educational Resources Information Center
Henson, James M.; Reise, Steven P.; Kim, Kevin H.
2007-01-01
The accuracy of structural model parameter estimates in latent variable mixture modeling was explored with a 3 (sample size) [times] 3 (exogenous latent mean difference) [times] 3 (endogenous latent mean difference) [times] 3 (correlation between factors) [times] 3 (mixture proportions) factorial design. In addition, the efficacy of several…
Elghafghuf, Adel; Dufour, Simon; Reyher, Kristen; Dohoo, Ian; Stryhn, Henrik
2014-12-01
Mastitis is a complex disease affecting dairy cows and is considered to be the most costly disease of dairy herds. The hazard of mastitis is a function of many factors, both managerial and environmental, making its control a difficult issue to milk producers. Observational studies of clinical mastitis (CM) often generate datasets with a number of characteristics which influence the analysis of those data: the outcome of interest may be the time to occurrence of a case of mastitis, predictors may change over time (time-dependent predictors), the effects of factors may change over time (time-dependent effects), there are usually multiple hierarchical levels, and datasets may be very large. Analysis of such data often requires expansion of the data into the counting-process format - leading to larger datasets - thus complicating the analysis and requiring excessive computing time. In this study, a nested frailty Cox model with time-dependent predictors and effects was applied to Canadian Bovine Mastitis Research Network data in which 10,831 lactations of 8035 cows from 69 herds were followed through lactation until the first occurrence of CM. The model was fit to the data as a Poisson model with nested normally distributed random effects at the cow and herd levels. Risk factors associated with the hazard of CM during the lactation were identified, such as parity, calving season, herd somatic cell score, pasture access, fore-stripping, and proportion of treated cases of CM in a herd. The analysis showed that most of the predictors had a strong effect early in lactation and also demonstrated substantial variation in the baseline hazard among cows and between herds. A small simulation study for a setting similar to the real data was conducted to evaluate the Poisson maximum likelihood estimation approach with both Gaussian quadrature method and Laplace approximation. Further, the performance of the two methods was compared with the performance of a widely used estimation
NASA Astrophysics Data System (ADS)
Wen, Mingjian; Li, Junhao; Brommer, Peter; Elliott, Ryan S.; Sethna, James P.; Tadmor, Ellad B.
2017-01-01
Fitted interatomic potentials are widely used in atomistic simulations thanks to their ability to compute the energy and forces on atoms quickly. However, the simulation results crucially depend on the quality of the potential being used. Force matching is a method aimed at constructing reliable and transferable interatomic potentials by matching the forces computed by the potential as closely as possible, with those obtained from first principles calculations. The potfit program is an implementation of the force-matching method that optimizes the potential parameters using a global minimization algorithm followed by a local minimization polish. We extended potfit in two ways. First, we adapted the code to be compliant with the KIM Application Programming Interface (API) standard (part of the Knowledgebase of Interatomic Models project). This makes it possible to use potfit to fit many KIM potential models, not just those prebuilt into the potfit code. Second, we incorporated the geodesic Levenberg-Marquardt (LM) minimization algorithm into potfit as a new local minimization algorithm. The extended potfit was tested by generating a training set using the KIM environment-dependent interatomic potential (EDIP) model for silicon and using potfit to recover the potential parameters from different initial guesses. The results show that EDIP is a ‘sloppy model’ in the sense that its predictions are insensitive to some of its parameters, which makes fitting more difficult. We find that the geodesic LM algorithm is particularly efficient for this case. The extended potfit code is the first step in developing a KIM-based fitting framework for interatomic potentials for bulk and two-dimensional materials. The code is available for download via https://www.potfit.net.
Falahati Marvast, Fatemeh; Arabalibeik, Hossein; Alipour, Fatemeh; Sheikhtaheri, Abbas; Nouri, Leila; Soozande, Mehdi; Yarmahmoodi, Masood
2016-01-01
Keratoconus is a progressive non-inflammatory disease of the cornea. Rigid gas permeable contact lenses (RGPs) are prescribed when the disease progresses. Contact lens fitting and assessment is very difficult in these patients and is a concern of ophthalmologists and optometrists. In this study, a hierarchical fuzzy system is used to capture the expertise of experienced ophthalmologists during the lens evaluation phase of prescription. The system is fine-tuned using genetic algorithms. Sensitivity, specificity and accuracy of the final system are 88.9%, 94.4% and 92.6% respectively.
Hilbe, Christian; Traulsen, Arne
2016-01-01
Brood parasites exploit their host in order to increase their own fitness. Typically, this results in an arms race between parasite trickery and host defence. Thus, it is puzzling to observe hosts that accept parasitism without any resistance. The ‘mafia’ hypothesis suggests that these hosts accept parasitism to avoid retaliation. Retaliation has been shown to evolve when the hosts condition their response to mafia parasites, who use depredation as a targeted response to rejection. However, it is unclear if acceptance would also emerge when ‘farming’ parasites are present in the population. Farming parasites use depredation to synchronize the timing with the host, destroying mature clutches to force the host to re-nest. Herein, we develop an evolutionary model to analyse the interaction between depredatory parasites and their hosts. We show that coevolutionary cycles between farmers and mafia can still induce host acceptance of brood parasites. However, this equilibrium is unstable and in the long-run the dynamics of this host–parasite interaction exhibits strong oscillations: when farmers are the majority, accepters conditional to mafia (the host will reject first and only accept after retaliation by the parasite) have a higher fitness than unconditional accepters (the host always accepts parasitism). This leads to an increase in mafia parasites’ fitness and in turn induce an optimal environment for accepter hosts. PMID:27293783
NASA Astrophysics Data System (ADS)
Brodie, E.; King, E.; Molins, S.; Karaoz, U.; Steefel, C. I.; Banfield, J. F.; Beller, H. R.; Anantharaman, K.; Ligocki, T. J.; Trebotich, D.
2015-12-01
Pore-scale processes mediated by microorganisms underlie a range of critical ecosystem services, regulating carbon stability, nutrient flux, and the purification of water. Advances in cultivation-independent approaches now provide us with the ability to reconstruct thousands of genomes from microbial populations from which functional roles may be assigned. With this capability to reveal microbial metabolic potential, the next step is to put these microbes back where they belong to interact with their natural environment, i.e. the pore scale. At this scale, microorganisms communicate, cooperate and compete across their fitness landscapes with communities emerging that feedback on the physical and chemical properties of their environment, ultimately altering the fitness landscape and selecting for new microbial communities with new properties and so on. We have developed a trait-based model of microbial activity that simulates coupled functional guilds that are parameterized with unique combinations of traits that govern fitness under dynamic conditions. Using a reactive transport framework, we simulate the thermodynamics of coupled electron donor-acceptor reactions to predict energy available for cellular maintenance, respiration, biomass development, and enzyme production. From metagenomics, we directly estimate some trait values related to growth and identify the linkage of key traits associated with respiration and fermentation, macromolecule depolymerizing enzymes, and other key functions such as nitrogen fixation. Our simulations were carried out to explore abiotic controls on community emergence such as seasonally fluctuating water table regimes across floodplain organic matter hotspots. Simulations and metagenomic/metatranscriptomic observations highlighted the many dependencies connecting the relative fitness of functional guilds and the importance of chemolithoautotrophic lifestyles. Using an X-Ray microCT-derived soil microaggregate physical model combined
Hurt, Aeron C; Nor'e, Siti Sarah; McCaw, James M; Fryer, Helen R; Mosse, Jennifer; McLean, Angela R; Barr, Ian G
2010-09-01
To determine the relative fitness of oseltamivir-resistant strains compared to susceptible wild-type viruses, we combined mathematical modeling and statistical techniques with a novel in vivo "competitive-mixtures" experimental model. Ferrets were coinfected with either pure populations (100% susceptible wild-type or 100% oseltamivir-resistant mutant virus) or mixed populations of wild-type and oseltamivir-resistant influenza viruses (80%:20%, 50%:50%, and 20%:80%) at equivalent infectivity titers, and the changes in the relative proportions of those two viruses were monitored over the course of the infection during within-host and over host-to-host transmission events in a ferret contact model. Coinfection of ferrets with mixtures of an oseltamivir-resistant R292K mutant A(H3N2) virus and a R292 oseltamivir-susceptible wild-type virus demonstrated that the R292K mutant virus was rapidly outgrown by the R292 wild-type virus in artificially infected donor ferrets and did not transmit to any of the recipient ferrets. The competitive-mixtures model was also used to investigate the fitness of the seasonal A(H1N1) oseltamivir-resistant H274Y mutant and showed that within infected ferrets the H274Y mutant virus was marginally outgrown by the wild-type strain but demonstrated equivalent transmissibility between ferrets. This novel in vivo experimental method and accompanying mathematical analysis provide greater insight into the relative fitness, both within the host and between hosts, of two different influenza virus strains compared to more traditional methods that infect ferrets with only pure populations of viruses. Our statistical inferences are essential for the development of the next generation of mathematical models of the emergence and spread of oseltamivir-resistant influenza in human populations.
Gutierrez, Eric; Quinn, Daniel B; Chin, Diana D; Lentink, David
2016-12-06
There are three common methods for calculating the lift generated by a flying animal based on the measured airflow in the wake. However, these methods might not be accurate according to computational and robot-based studies of flapping wings. Here we test this hypothesis for the first time for a slowly flying Pacific parrotlet in still air using stereo particle image velocimetry recorded at 1000 Hz. The bird was trained to fly between two perches through a laser sheet wearing laser safety goggles. We found that the wingtip vortices generated during mid-downstroke advected down and broke up quickly, contradicting the frozen turbulence hypothesis typically assumed in animal flight experiments. The quasi-steady lift at mid-downstroke was estimated based on the velocity field by applying the widely used Kutta-Joukowski theorem, vortex ring model, and actuator disk model. The calculated lift was found to be sensitive to the applied model and its different parameters, including vortex span and distance between the bird and laser sheet-rendering these three accepted ways of calculating weight support inconsistent. The three models predict different aerodynamic force values mid-downstroke compared to independent direct measurements with an aerodynamic force platform that we had available for the same species flying over a similar distance. Whereas the lift predictions of the Kutta-Joukowski theorem and the vortex ring model stayed relatively constant despite vortex breakdown, their values were too low. In contrast, the actuator disk model predicted lift reasonably accurately before vortex breakdown, but predicted almost no lift during and after vortex breakdown. Some of these limitations might be better understood, and partially reconciled, if future animal flight studies report lift calculations based on all three quasi-steady lift models instead. This would also enable much needed meta studies of animal flight to derive bioinspired design principles for quasi-steady lift
ERIC Educational Resources Information Center
Teo, Timothy
2012-01-01
This study examined pre-service teachers' self-reported intention to use technology. One hundred fifty-seven participants completed a survey questionnaire measuring their responses to six constructs from a research model that integrated the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB). Structural equation modeling was…
ERIC Educational Resources Information Center
Custer, Michael; Sharairi, Sid; Yamazaki, Kenji; Signatur, Diane; Swift, David; Frey, Sharon
2008-01-01
The present study compared item and ability invariance as well as model-data fit between the one-parameter (1PL) and three-parameter (3PL) Item Response Theory (IRT) models utilizing real data across five grades; second through sixth as well as simulated data at second, fourth and sixth grade. At each grade, the 1PL and 3PL IRT models were run…
Acceptance and Commitment Therapy: Introduction
ERIC Educational Resources Information Center
Twohig, Michael P.
2012-01-01
This is the introductory article to a special series in Cognitive and Behavioral Practice on Acceptance and Commitment Therapy (ACT). Instead of each article herein reviewing the basics of ACT, this article contains that review. This article provides a description of where ACT fits within the larger category of cognitive behavior therapy (CBT):…