Contrast Gain Control Model Fits Masking Data
NASA Technical Reports Server (NTRS)
Watson, Andrew B.; Solomon, Joshua A.; Null, Cynthia H. (Technical Monitor)
1994-01-01
We studied the fit of a contrast gain control model to data of Foley (JOSA 1994), consisting of thresholds for a Gabor patch masked by gratings of various orientations, or by compounds of two orientations. Our general model includes models of Foley and Teo & Heeger (IEEE 1994). Our specific model used a bank of Gabor filters with octave bandwidths at 8 orientations. Excitatory and inhibitory nonlinearities were power functions with exponents of 2.4 and 2. Inhibitory pooling was broad in orientation, but narrow in spatial frequency and space. Minkowski pooling used an exponent of 4. All of the data for observer KMF were well fit by the model. We have developed a contrast gain control model that fits masking data. Unlike Foley's, our model accepts images as inputs. Unlike Teo & Heeger's, our model did not require multiple channels for different dynamic ranges.
76 FR 49751 - Perfect Fitness, Provisional Acceptance of a Settlement Agreement and Order
Federal Register 2010, 2011, 2012, 2013, 2014
2011-08-11
... CONSUMER PRODUCT SAFETY COMMISSION [CPSC Docket No. 11-C0009] Perfect Fitness, Provisional...(e). Published below is a provisionally-accepted Settlement Agreement with Perfect Fitness... accordance with 16 CFR 1118.20, Perfect Fitness and staff (``Staff'') of the United States Consumer Product...
Is the Nintendo Wii Fit really acceptable to older people?: a discrete choice experiment
2011-01-01
Background Interactive video games such as the Nintendo Wii Fit are increasingly used as a therapeutic tool in health and aged care settings however, their acceptability to older people is unclear. The aim of this study was to determine the acceptability of the Nintendo Wii Fit as a therapy tool for hospitalised older people using a discrete choice experiment (DCE) before and after exposure to the intervention. Methods A DCE was administered to 21 participants in an interview style format prior to, and following several sessions of using the Wii Fit in physiotherapy. The physiotherapist prescribed the Wii Fit activities, supervised and supported the patient during the therapy sessions. Attributes included in the DCE were: mode of therapy (traditional or using the Wii Fit), amount of therapy, cost of therapy program and percentage of recovery made. Data was analysed using conditional (fixed-effects) logistic regression. Results Prior to commencing the therapy program participants were most concerned about therapy time (avoiding programs that were too intensive), and the amount of recovery they would make. Following the therapy program, participants were more concerned with the mode of therapy and preferred traditional therapy programs over programs using the Wii Fit. Conclusions The usefulness of the Wii Fit as a therapy tool with hospitalised older people is limited not only by the small proportion of older people who are able to use it, but by older people's preferences for traditional approaches to therapy. Mainstream media portrayals of the popularity of the Wii Fit with older people may not reflect the true acceptability in the older hospitalised population. PMID:22011360
Critical elements on fitting the Bayesian multivariate Poisson Lognormal model
NASA Astrophysics Data System (ADS)
Zamzuri, Zamira Hasanah binti
2015-10-01
Motivated by a problem on fitting multivariate models to traffic accident data, a detailed discussion of the Multivariate Poisson Lognormal (MPL) model is presented. This paper reveals three critical elements on fitting the MPL model: the setting of initial estimates, hyperparameters and tuning parameters. These issues have not been highlighted in the literature. Based on simulation studies conducted, we have shown that to use the Univariate Poisson Model (UPM) estimates as starting values, at least 20,000 iterations are needed to obtain reliable final estimates. We also illustrated the sensitivity of the specific hyperparameter, which if it is not given extra attention, may affect the final estimates. The last issue is regarding the tuning parameters where they depend on the acceptance rate. Finally, a heuristic algorithm to fit the MPL model is presented. This acts as a guide to ensure that the model works satisfactorily given any data set.
Elizur, Y; Ziv, M
2001-01-01
While heterosexist family undermining has been demonstrated to be a developmental risk factor in the life of persons with same-gender orientation, the issue of protective family factors is both controversial and relatively neglected. In this study of Israeli gay males (N = 114), we focused on the interrelations of family support, family acceptance and family knowledge of gay orientation, and gay male identity formation, and their effects on mental health and self-esteem. A path model was proposed based on the hypotheses that family support, family acceptance, family knowledge, and gay identity formation have an impact on psychological adjustment, and that family support has an effect on gay identity formation that is mediated by family acceptance. The assessment of gay identity formation was based on an established stage model that was streamlined for cross-cultural practice by defining three basic processes of same-gender identity formation: self-definition, self-acceptance, and disclosure (Elizur & Mintzer, 2001). The testing of our conceptual path model demonstrated an excellent fit with the data. An alternative model that hypothesized effects of gay male identity on family acceptance and family knowledge did not fit the data. Interpreting these results, we propose that the main effect of family support/acceptance on gay identity is related to the process of disclosure, and that both general family support and family acceptance of same-gender orientation play a significant role in the psychological adjustment of gay men.
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.
Model fit evaluation in multilevel structural equation models
Ryu, Ehri
2014-01-01
Assessing goodness of model fit is one of the key questions in structural equation modeling (SEM). Goodness of fit is the extent to which the hypothesized model reproduces the multivariate structure underlying the set of variables. During the earlier development of multilevel structural equation models, the “standard” approach was to evaluate the goodness of fit for the entire model across all levels simultaneously. The model fit statistics produced by the standard approach have a potential problem in detecting lack of fit in the higher-level model for which the effective sample size is much smaller. Also when the standard approach results in poor model fit, it is not clear at which level the model does not fit well. This article reviews two alternative approaches that have been proposed to overcome the limitations of the standard approach. One is a two-step procedure which first produces estimates of saturated covariance matrices at each level and then performs single-level analysis at each level with the estimated covariance matrices as input (Yuan and Bentler, 2007). The other level-specific approach utilizes partially saturated models to obtain test statistics and fit indices for each level separately (Ryu and West, 2009). Simulation studies (e.g., Yuan and Bentler, 2007; Ryu and West, 2009) have consistently shown that both alternative approaches performed well in detecting lack of fit at any level, whereas the standard approach failed to detect lack of fit at the higher level. It is recommended that the alternative approaches are used to assess the model fit in multilevel structural equation model. Advantages and disadvantages of the two alternative approaches are discussed. The alternative approaches are demonstrated in an empirical example. PMID:24550882
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),…
Mechanisms of complex network growth: Synthesis of the preferential attachment and fitness models
NASA Astrophysics Data System (ADS)
Golosovsky, Michael
2018-06-01
We analyze growth mechanisms of complex networks and focus on their validation by measurements. To this end we consider the equation Δ K =A (t ) (K +K0) Δ t , where K is the node's degree, Δ K is its increment, A (t ) is the aging constant, and K0 is the initial attractivity. This equation has been commonly used to validate the preferential attachment mechanism. We show that this equation is undiscriminating and holds for the fitness model [Caldarelli et al., Phys. Rev. Lett. 89, 258702 (2002), 10.1103/PhysRevLett.89.258702] as well. In other words, accepted method of the validation of the microscopic mechanism of network growth does not discriminate between "rich-gets-richer" and "good-gets-richer" scenarios. This means that the growth mechanism of many natural complex networks can be based on the fitness model rather than on the preferential attachment, as it was believed so far. The fitness model yields the long-sought explanation for the initial attractivity K0, an elusive parameter which was left unexplained within the framework of the preferential attachment model. We show that the initial attractivity is determined by the width of the fitness distribution. We also present the network growth model based on recursive search with memory and show that this model contains both the preferential attachment and the fitness models as extreme cases.
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.
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…
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…
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.
Level-Specific Evaluation of Model Fit in Multilevel Structural Equation Modeling
ERIC Educational Resources Information Center
Ryu, Ehri; West, Stephen G.
2009-01-01
In multilevel structural equation modeling, the "standard" approach to evaluating the goodness of model fit has a potential limitation in detecting the lack of fit at the higher level. Level-specific model fit evaluation can address this limitation and is more informative in locating the source of lack of model fit. We proposed level-specific test…
Klijn, Sven L; Weijenberg, Matty P; Lemmens, Paul; van den Brandt, Piet A; Lima Passos, Valéria
2017-10-01
Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.
Yuan, Shupei; Ma, Wenjuan; Kanthawala, Shaheen; Peng, Wei
2015-09-01
Health and fitness applications (apps) are one of the major app categories in the current mobile app market. Few studies have examined this area from the users' perspective. This study adopted the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) Model to examine the predictors of the users' intention to adopt health and fitness apps. A survey (n=317) was conducted with college-aged smartphone users at a Midwestern university in the United States. Performance expectancy, hedonic motivations, price value, and habit were significant predictors of users' intention of continued usage of health and fitness apps. However, effort expectancy, social influence, and facilitating conditions were not found to predict users' intention of continued usage of health and fitness apps. This study extends the UTATU2 Model to the mobile apps domain and provides health professions, app designers, and marketers with the insights of user experience in terms of continuously using health and fitness apps.
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.
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. PMID:23112804
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.
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
Induced subgraph searching for geometric model fitting
NASA Astrophysics Data System (ADS)
Xiao, Fan; Xiao, Guobao; Yan, Yan; Wang, Xing; Wang, Hanzi
2017-11-01
In this paper, we propose a novel model fitting method based on graphs to fit and segment multiple-structure data. In the graph constructed on data, each model instance is represented as an induced subgraph. Following the idea of pursuing the maximum consensus, the multiple geometric model fitting problem is formulated as searching for a set of induced subgraphs including the maximum union set of vertices. After the generation and refinement of the induced subgraphs that represent the model hypotheses, the searching process is conducted on the "qualified" subgraphs. Multiple model instances can be simultaneously estimated by solving a converted problem. Then, we introduce the energy evaluation function to determine the number of model instances in data. The proposed method is able to effectively estimate the number and the parameters of model instances in data severely corrupted by outliers and noises. Experimental results on synthetic data and real images validate the favorable performance of the proposed method compared with several state-of-the-art fitting methods.
Williams, Marie A; Soiza, Roy L; Jenkinson, Alison McE; Stewart, Alison
2010-09-13
Falls management programmes have been instituted to attempt to reduce falls. This pilot study was undertaken to determine whether the Nintendo® WiiFit was a feasible and acceptable intervention in community-dwelling older fallers. Community-dwelling fallers over 70 years were recruited and attended for computer-based exercises (n = 15) or standard care (n = 6). Balance and fear of falling were assessed at weeks 0, 4 and 12. Participants were interviewed on completion of the study to determine whether the intervention was acceptable.Eighty percent of participants attended 75% or more of the exercise sessions. An improvement in Berg Score was seen at four weeks (p = 0.02) and in Wii Age at 12 weeks (p = 0.03) in the intervention group. There was no improvement in balance scores in the standard care group. WiiFit exercise is acceptable in self-referred older people with a history of falls. The WiiFit has the potential to improve balance but further work is required. ClinicalTrials.gov - NCT01082042.
Analytical fitting model for rough-surface BRDF.
Renhorn, Ingmar G E; Boreman, Glenn D
2008-08-18
A physics-based model is developed for rough surface BRDF, taking into account angles of incidence and scattering, effective index, surface autocovariance, and correlation length. Shadowing is introduced on surface correlation length and reflectance. Separate terms are included for surface scatter, bulk scatter and retroreflection. Using the FindFit function in Mathematica, the functional form is fitted to BRDF measurements over a wide range of incident angles. The model has fourteen fitting parameters; once these are fixed, the model accurately describes scattering data over two orders of magnitude in BRDF without further adjustment. The resulting analytical model is convenient for numerical computations.
Kim, Jeongeun; Park, Hyeoun-Ae
2012-10-01
For effective health promotion using health information technology (HIT), it is mandatory that health consumers have the behavioral intention to measure, store, and manage their own health data. Understanding health consumers' intention and behavior is needed to develop and implement effective and efficient strategies. To develop and verify the extended Technology Acceptance Model (TAM) in health care by describing health consumers' behavioral intention of using HIT. This study used a cross-sectional descriptive correlational design. We extended TAM by adding more antecedents and mediating variables to enhance the model's explanatory power and to make it more applicable to health consumers' behavioral intention. Additional antecedents and mediating variables were added to the hypothetical model, based on their theoretical relevance, from the Health Belief Model and theory of planned behavior, along with the TAM. We undertook structural equation analysis to examine the specific nature of the relationship involved in understanding consumers' use of HIT. Study participants were 728 members recruited from three Internet health portals in Korea. Data were collected by a Web-based survey using a structured self-administered questionnaire. The overall fitness indices for the model developed in this study indicated an acceptable fit of the model. All path coefficients were statistically significant. This study showed that perceived threat, perceived usefulness, and perceived ease of use significantly affected health consumers' attitude and behavioral intention. Health consumers' health status, health belief and concerns, subjective norm, HIT characteristics, and HIT self-efficacy had a strong indirect impact on attitude and behavioral intention through the mediators of perceived threat, perceived usefulness, and perceived ease of use. An extended TAM in the HIT arena was found to be valid to describe health consumers' behavioral intention. We categorized the concepts in
Curve fitting methods for solar radiation data modeling
NASA Astrophysics Data System (ADS)
Karim, Samsul Ariffin Abdul; Singh, Balbir Singh Mahinder
2014-10-01
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 R2. 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.
Curve fitting methods for solar radiation data modeling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Karim, Samsul Ariffin Abdul, E-mail: samsul-ariffin@petronas.com.my, E-mail: balbir@petronas.com.my; Singh, Balbir Singh Mahinder, E-mail: samsul-ariffin@petronas.com.my, 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 withmore » two terms) gives better results as compare with the other fitting methods.« less
Modeling Evolution on Nearly Neutral Network Fitness Landscapes
NASA Astrophysics Data System (ADS)
Yakushkina, Tatiana; Saakian, David B.
2017-08-01
To describe virus evolution, it is necessary to define a fitness landscape. In this article, we consider the microscopic models with the advanced version of neutral network fitness landscapes. In this problem setting, we suppose a fitness difference between one-point mutation neighbors to be small. We construct a modification of the Wright-Fisher model, which is related to ordinary infinite population models with nearly neutral network fitness landscape at the large population limit. From the microscopic models in the realistic sequence space, we derive two versions of nearly neutral network models: with sinks and without sinks. We claim that the suggested model describes the evolutionary dynamics of RNA viruses better than the traditional Wright-Fisher model with few sequences.
Lee, Daniel Joseph; Veneri, Diana A
2018-05-01
The most common complaint lower limb prosthesis users report is inadequacy of a proper socket fit. Adjustments to the residual limb-socket interface can be made by the prosthesis user without consultation of a clinician in many scenarios through skilled self-management. Decision trees guide prosthesis wearers through the self-management process, empowering them to rectify fit issues, or referring them to a clinician when necessary. This study examines the development and acceptability testing of patient-centered decision trees for lower limb prosthesis users. Decision trees underwent a four-stage process: literature review and expert consultation, designing, two-rounds of expert panel review and revisions, and target audience testing. Fifteen lower limb prosthesis users (average age 61 years) reviewed the decision trees and completed an acceptability questionnaire. Participants reported agreement of 80% or above in five of the eight questions related to acceptability of the decision trees. Disagreement was related to the level of experience of the respondent. Decision trees were found to be easy to use, illustrate correct solutions to common issues, and have terminology consistent with that of a new prosthesis user. Some users with greater than 1.5 years of experience would not use the decision trees based on their own self-management skills. Implications for Rehabilitation Discomfort of the residual limb-prosthetic socket interface is the most common reason for clinician visits. Prosthesis users can use decision trees to guide them through the process of obtaining a proper socket fit independently. Newer users may benefit from using the decision trees more than experienced users.
Random-growth urban model with geographical fitness
NASA Astrophysics Data System (ADS)
Kii, Masanobu; Akimoto, Keigo; Doi, Kenji
2012-12-01
This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.
Multivariate prediction of upper limb prosthesis acceptance or rejection.
Biddiss, Elaine A; Chau, Tom T
2008-07-01
To develop a model for prediction of upper limb prosthesis use or rejection. A questionnaire exploring factors in prosthesis acceptance was distributed internationally to individuals with upper limb absence through community-based support groups and rehabilitation hospitals. A total of 191 participants (59 prosthesis rejecters and 132 prosthesis wearers) were included in this study. A logistic regression model, a C5.0 decision tree, and a radial basis function neural network were developed and compared in terms of sensitivity (prediction of prosthesis rejecters), specificity (prediction of prosthesis wearers), and overall cross-validation accuracy. The logistic regression and neural network provided comparable overall accuracies of approximately 84 +/- 3%, specificity of 93%, and sensitivity of 61%. Fitting time-frame emerged as the predominant predictor. Individuals fitted within two years of birth (congenital) or six months of amputation (acquired) were 16 times more likely to continue prosthesis use. To increase rates of prosthesis acceptance, clinical directives should focus on timely, client-centred fitting strategies and the development of improved prostheses and healthcare for individuals with high-level or bilateral limb absence. Multivariate analyses are useful in determining the relative importance of the many factors involved in prosthesis acceptance and rejection.
2012-01-01
Background For effective health promotion using health information technology (HIT), it is mandatory that health consumers have the behavioral intention to measure, store, and manage their own health data. Understanding health consumers’ intention and behavior is needed to develop and implement effective and efficient strategies. Objective To develop and verify the extended Technology Acceptance Model (TAM) in health care by describing health consumers’ behavioral intention of using HIT. Methods This study used a cross-sectional descriptive correlational design. We extended TAM by adding more antecedents and mediating variables to enhance the model’s explanatory power and to make it more applicable to health consumers’ behavioral intention. Additional antecedents and mediating variables were added to the hypothetical model, based on their theoretical relevance, from the Health Belief Model and theory of planned behavior, along with the TAM. We undertook structural equation analysis to examine the specific nature of the relationship involved in understanding consumers’ use of HIT. Study participants were 728 members recruited from three Internet health portals in Korea. Data were collected by a Web-based survey using a structured self-administered questionnaire. Results The overall fitness indices for the model developed in this study indicated an acceptable fit of the model. All path coefficients were statistically significant. This study showed that perceived threat, perceived usefulness, and perceived ease of use significantly affected health consumers’ attitude and behavioral intention. Health consumers’ health status, health belief and concerns, subjective norm, HIT characteristics, and HIT self-efficacy had a strong indirect impact on attitude and behavioral intention through the mediators of perceived threat, perceived usefulness, and perceived ease of use. Conclusions An extended TAM in the HIT arena was found to be valid to describe health
Modeling patients' acceptance of provider-delivered e-health.
Wilson, E Vance; Lankton, Nancy K
2004-01-01
Health care providers are beginning to deliver a range of Internet-based services to patients; however, it is not clear which of these e-health services patients need or desire. The authors propose that patients' acceptance of provider-delivered e-health can be modeled in advance of application development by measuring the effects of several key antecedents to e-health use and applying models of acceptance developed in the information technology (IT) field. This study tested three theoretical models of IT acceptance among patients who had recently registered for access to provider-delivered e-health. An online questionnaire administered items measuring perceptual constructs from the IT acceptance models (intrinsic motivation, perceived ease of use, perceived usefulness/extrinsic motivation, and behavioral intention to use e-health) and five hypothesized antecedents (satisfaction with medical care, health care knowledge, Internet dependence, information-seeking preference, and health care need). Responses were collected and stored in a central database. All tested IT acceptance models performed well in predicting patients' behavioral intention to use e-health. Antecedent factors of satisfaction with provider, information-seeking preference, and Internet dependence uniquely predicted constructs in the models. Information technology acceptance models provide a means to understand which aspects of e-health are valued by patients and how this may affect future use. In addition, antecedents to the models can be used to predict e-health acceptance in advance of system development.
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
Video Game Acceptance: A Meta-Analysis of the Extended Technology Acceptance Model.
Wang, Xiaohui; Goh, Dion Hoe-Lian
2017-11-01
The current study systematically reviews and summarizes the existing literature of game acceptance, identifies the core determinants, and evaluates the strength of the relationships in the extended technology acceptance model. Moreover, this study segments video games into two categories: hedonic and utilitarian and examines player acceptance of these two types separately. Through a meta-analysis of 50 articles, we find that perceived ease of use (PEOU), perceived usefulness (PU), and perceived enjoyment (PE) significantly associate with attitude and behavioral intention. PE is the dominant predictor of hedonic game acceptance, while PEOU and PU are the main determinants of utilitarian game acceptance. Furthermore, we find that respondent type and game platform are significant moderators. Findings of this study provide critical insights into the phenomenon of game acceptance and suggest directions for future research.
Zhuang, Ziqing; Bergman, Michael; Lei, Zhipeng; Niezgoda, George; Shaffer, Ronald
2017-01-01
This study assessed key test parameters and pass/fail criteria options for developing a respirator fit capability (RFC) test for half-mask air-purifying particulate respirators. Using a 25-subject test panel, benchmark RFC data were collected for 101 National Institute for Occupational Safety and Health-certified respirator models. These models were further grouped into 61 one-, two-, or three-size families. Fit testing was done using a PortaCount® Plus with N95-Companion accessory and an Occupational Safety and Health Administration-accepted quantitative fit test protocol. Three repeated tests (donnings) per subject/respirator model combination were performed. The panel passing rate (PPR) (number or percentage of the 25-subject panel achieving acceptable fit) was determined for each model using five different alternative criteria for determining acceptable fit. When the 101 models are evaluated individually (i.e., not grouped by families), the percentages of models capable of fitting >75% (19/25 subjects) of the panel were 29% and 32% for subjects achieving a fit factor ≥100 for at least one of the first two donnings and at least one of three donnings, respectively. When the models are evaluated grouped into families and using >75% of panel subjects achieving a fit factor ≥100 for at least one of two donnings as the PPR pass/fail criterion, 48% of all models can pass. When >50% (13/25 subjects) of panel subjects was the PPR criterion, the percentage of passing models increased to 70%. Testing respirators grouped into families and evaluating the first two donnings for each of two respirator sizes provided the best balance between meeting end user expectations and creating a performance bar for manufacturers. Specifying the test criterion for a subject obtaining acceptable fit as achieving a fit factor ≥100 on at least one out of the two donnings is reasonable because a majority of existing respirator families can achieve an PPR of >50% using this criterion
Zhuang, Ziqing; Bergman, Michael; Lei, Zhipeng; Niezgoda, George; Shaffer, Ronald
2017-06-01
This study assessed key test parameters and pass/fail criteria options for developing a respirator fit capability (RFC) test for half-mask air-purifying particulate respirators. Using a 25-subject test panel, benchmark RFC data were collected for 101 National Institute for Occupational Safety and Health-certified respirator models. These models were further grouped into 61 one-, two-, or three-size families. Fit testing was done using a PortaCount® Plus with N95-Companion accessory and an Occupational Safety and Health Administration-accepted quantitative fit test protocol. Three repeated tests (donnings) per subject/respirator model combination were performed. The panel passing rate (PPR) (number or percentage of the 25-subject panel achieving acceptable fit) was determined for each model using five different alternative criteria for determining acceptable fit. When the 101 models are evaluated individually (i.e., not grouped by families), the percentages of models capable of fitting >75% (19/25 subjects) of the panel were 29% and 32% for subjects achieving a fit factor ≥100 for at least one of the first two donnings and at least one of three donnings, respectively. When the models are evaluated grouped into families and using >75% of panel subjects achieving a fit factor ≥100 for at least one of two donnings as the PPR pass/fail criterion, 48% of all models can pass. When >50% (13/25 subjects) of panel subjects was the PPR criterion, the percentage of passing models increased to 70%. Testing respirators grouped into families and evaluating the first two donnings for each of two respirator sizes provided the best balance between meeting end user expectations and creating a performance bar for manufacturers. Specifying the test criterion for a subject obtaining acceptable fit as achieving a fit factor ≥100 on at least one out of the two donnings is reasonable because a majority of existing respirator families can achieve an PPR of >50% using this criterion
Model-Free CUSUM Methods for Person Fit
ERIC Educational Resources Information Center
Armstrong, Ronald D.; Shi, Min
2009-01-01
This article demonstrates the use of a new class of model-free cumulative sum (CUSUM) statistics to detect person fit given the responses to a linear test. The fundamental statistic being accumulated is the likelihood ratio of two probabilities. The detection performance of this CUSUM scheme is compared to other model-free person-fit statistics…
A Distributive Model of Treatment Acceptability
ERIC Educational Resources Information Center
Carter, Stacy L.
2008-01-01
A model of treatment acceptability is proposed that distributes overall treatment acceptability into three separate categories of influence. The categories are comprised of societal influences, consultant influences, and influences associated with consumers of treatments. Each of these categories are defined and their inter-relationships within…
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. Copyright © 2015 Elsevier Ltd. All rights reserved.
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 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.
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.…
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…
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.
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).
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).
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.…
Fitting milk production curves through nonlinear mixed models.
Piccardi, Monica; Macchiavelli, Raúl; Funes, Ariel Capitaine; Bó, Gabriel A; Balzarini, Mónica
2017-05-01
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.
Goodness-of-Fit Assessment of Item Response Theory Models
ERIC Educational Resources Information Center
Maydeu-Olivares, Alberto
2013-01-01
The article provides an overview of goodness-of-fit assessment methods for item response theory (IRT) models. It is now possible to obtain accurate "p"-values of the overall fit of the model if bivariate information statistics are used. Several alternative approaches are described. As the validity of inferences drawn on the fitted model…
A global goodness-of-fit statistic for Cox regression models.
Parzen, M; Lipsitz, S R
1999-06-01
In this paper, a global goodness-of-fit test statistic for a Cox regression model, which has an approximate chi-squared distribution when the model has been correctly specified, is proposed. Our goodness-of-fit statistic is global and has power to detect if interactions or higher order powers of covariates in the model are needed. The proposed statistic is similar to the Hosmer and Lemeshow (1980, Communications in Statistics A10, 1043-1069) goodness-of-fit statistic for binary data as well as Schoenfeld's (1980, Biometrika 67, 145-153) statistic for the Cox model. The methods are illustrated using data from a Mayo Clinic trial in primary billiary cirrhosis of the liver (Fleming and Harrington, 1991, Counting Processes and Survival Analysis), in which the outcome is the time until liver transplantation or death. The are 17 possible covariates. Two Cox proportional hazards models are fit to the data, and the proposed goodness-of-fit statistic is applied to the fitted models.
Automatic Fitting of Spiking Neuron Models to Electrophysiological Recordings
Rossant, Cyrille; Goodman, Dan F. M.; Platkiewicz, Jonathan; Brette, Romain
2010-01-01
Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains) that can run in parallel on graphics processing units (GPUs). The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models. PMID:20224819
The FITS model office ergonomics program: a model for best practice.
Chim, Justine M Y
2014-01-01
An effective office ergonomics program can predict positive results in reducing musculoskeletal injury rates, enhancing productivity, and improving staff well-being and job satisfaction. Its objective is to provide a systematic solution to manage the potential risk of musculoskeletal disorders among computer users in an office setting. A FITS Model office ergonomics program is developed. The FITS Model Office Ergonomics Program has been developed which draws on the legislative requirements for promoting the health and safety of workers using computers for extended periods as well as previous research findings. The Model is developed according to the practical industrial knowledge in ergonomics, occupational health and safety management, and human resources management in Hong Kong and overseas. This paper proposes a comprehensive office ergonomics program, the FITS Model, which considers (1) Furniture Evaluation and Selection; (2) Individual Workstation Assessment; (3) Training and Education; (4) Stretching Exercises and Rest Break as elements of an effective program. An experienced ergonomics practitioner should be included in the program design and implementation. Through the FITS Model Office Ergonomics Program, the risk of musculoskeletal disorders among computer users can be eliminated or minimized, and workplace health and safety and employees' wellness enhanced.
ERIC Educational Resources Information Center
Stanley, Leanne M.; Edwards, Michael C.
2016-01-01
The purpose of this article is to highlight the distinction between the reliability of test scores and the fit of psychometric measurement models, reminding readers why it is important to consider both when evaluating whether test scores are valid for a proposed interpretation and/or use. It is often the case that an investigator judges both the…
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…
ERIC Educational Resources Information Center
Song, Yanjie; Kong, Siu-Cheung
2017-01-01
The study aims at investigating university students' acceptance of a statistics learning platform to support the learning of statistics in a blended learning context. Three kinds of digital resources, which are simulations, online videos, and online quizzes, were provided on the platform. Premised on the technology acceptance model, we adopted a…
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).
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
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.
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.
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…
Tsai, Tsai-Hsuan; Wong, Alice May-Kuen; Hsu, Chien-Lung; Tseng, Kevin C.
2013-01-01
This study aims to assess the acceptability of a fitness testing platform (iFit) for installation in an assisted living community with the aim of promoting fitness and slowing the onset of frailty. The iFit platform develops a means of testing Bureau of Health Promotion mandated health assessment items for the elderly (including flexibility tests, grip strength tests, balance tests, and reaction time tests) and integrates wireless remote sensors in a game-like environment to capture and store subject response data, thus providing individuals in elderly care contexts with a greater awareness of their own physical condition. In this study, we specifically evaluated the users’ intention of using the iFit using a technology acceptance model (TAM). A total of 101 elderly subjects (27 males and 74 females) were recruited. A survey was conducted to measure technology acceptance, to verify that the platform could be used as intended to promote fitness among the elderly. Results indicate that perceived usefulness, perceived ease of use and usage attitude positively impact behavioral intention to use the platform. The iFit platform can offer user-friendly solutions for a community-based fitness care and monitoring of elderly subjects. In summary, iFit was determined by three key drivers and discussed as follows: risk factors among the frail elderly, mechanism for slowing the advance frailty, and technology acceptance and support for promoting physical fitness. PMID:23460859
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
2016-01-01
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
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.
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…
Groenesteijn, L; Commissaris, D A C M; Van den Berg-Zwetsloot, M; Hiemstra-Van Mastrigt, S
2016-07-19
Working in an office environment is characterised by physical inactivity and sedentary behaviour. This behaviour contributes to several health risks in the long run. Dynamic workstations which allow people to combine desk activities with physical activity, may contribute to prevention of these health risks. A dynamic workstation, called Oxidesk, was evaluated to determine the possible contribution to healthy behaviour and the impact on perceived work performance. A field test was conducted with 22 office workers, employed at a health insurance company in the Netherlands. The Oxidesk was well accepted, positively perceived for fitness and the participants maintained their work performance. Physical activity was lower than the activity level required in the Dutch guidelines for sufficient physical activity. Although there was a slight increase in physical activity, the Oxidesk may be helpful in the reducing health risks involved and seems applicable for introduction to office environments.
Comparison of three commercially available fit-test methods.
Janssen, Larry L; Luinenburg, D Michael; Mullins, Haskell E; Nelson, Thomas J
2002-01-01
American National Standards Institute (ANSI) standard Z88.10, Respirator Fit Testing Methods, includes criteria to evaluate new fit-tests. The standard allows generated aerosol, particle counting, or controlled negative pressure quantitative fit-tests to be used as the reference method to determine acceptability of a new test. This study examined (1) comparability of three Occupational Safety and Health Administration-accepted fit-test methods, all of which were validated using generated aerosol as the reference method; and (2) the effect of the reference method on the apparent performance of a fit-test method under evaluation. Sequential fit-tests were performed using the controlled negative pressure and particle counting quantitative fit-tests and the bitter aerosol qualitative fit-test. Of 75 fit-tests conducted with each method, the controlled negative pressure method identified 24 failures; bitter aerosol identified 22 failures; and the particle counting method identified 15 failures. The sensitivity of each method, that is, agreement with the reference method in identifying unacceptable fits, was calculated using each of the other two methods as the reference. None of the test methods met the ANSI sensitivity criterion of 0.95 or greater when compared with either of the other two methods. These results demonstrate that (1) the apparent performance of any fit-test depends on the reference method used, and (2) the fit-tests evaluated use different criteria to identify inadequately fitting respirators. Although "acceptable fit" cannot be defined in absolute terms at this time, the ability of existing fit-test methods to reject poor fits can be inferred from workplace protection factor studies.
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.
NASA Astrophysics Data System (ADS)
Chu, Hsing-Hui; Lu, Ta-Jung; Wann, Jong-Wen
The purpose of this research is to explore enterprises' acceptance of Audience Response System (ARS) using Technology Acceptance Model (TAM). The findings show that (1) IT characteristics and facilitating conditions could be external variables of TAM. (2) The degree of E-business has positive significant correlation with behavioral intention of employees. (3) TAM is a good model to predict and explain IT acceptance. (4) Demographic variables, industry and firm characteristics have no significant correlation with ARS acceptance. The results provide useful information to managers and ARS providers that (1) ARS providers should focus more on creating different usages to enhance interactivity and employees' using intention. (2) Managers should pay attention to build sound internal facilitating conditions for introducing IT. (3) According to the degree of E-business, managers should set up strategic stages of introducing IT. (4) Providers should increase product promotion and also leverage academic and government to promote ARS.
Mantzicopoulos, Panayota; French, Brian F; Maller, Susan J
2004-01-01
Competing models of the factorial structure of the Pictorial Scale of Perceived Competence and Social Acceptance (PSPCSA) were tested for fit using multisample confirmatory factor analysis. The best fitting model was tested for invariance (a) across samples of middle-class (n = 251) and economically disadvantaged (Head Start, n = 117) kindergarten children (whose ages ranged from 67 to 86 months), and (b) over time (at the end of preschool and kindergarten) for the Head Start sample. For kindergarten children, regardless of socioeconomic status, the factor structure of the PSPCSA was consistent with the 2-factor model of Competence and Acceptance. This model also fit reasonably well for Head Start children at the end of their preschool year. However, in addition to providing broad support for the dimensionality of the measure, our findings highlight important concerns about the PSPCSA. Copyright 2004 Society for Research in Child Development, Inc.
Using Structural Equation Modeling To Fit Models Incorporating Principal Components.
ERIC Educational Resources Information Center
Dolan, Conor; Bechger, Timo; Molenaar, Peter
1999-01-01
Considers models incorporating principal components from the perspectives of structural-equation modeling. These models include the following: (1) the principal-component analysis of patterned matrices; (2) multiple analysis of variance based on principal components; and (3) multigroup principal-components analysis. Discusses fitting these models…
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…
Major psychological factors affecting acceptance of gene-recombination technology.
Tanaka, Yutaka
2004-12-01
The purpose of this study was to verify the validity of a causal model that was made to predict the acceptance of gene-recombination technology. A structural equation model was used as a causal model. First of all, based on preceding studies, the factors of perceived risk, perceived benefit, and trust were set up as important psychological factors determining acceptance of gene-recombination technology in the structural equation model. An additional factor, "sense of bioethics," which I consider to be important for acceptance of biotechnology, was added to the model. Based on previous studies, trust was set up to have an indirect influence on the acceptance of gene-recombination technology through perceived risk and perceived benefit in the model. Participants were 231 undergraduate students in Japan who answered a questionnaire with a 5-point bipolar scale. The results indicated that the proposed model fits the data well, and showed that acceptance of gene-recombination technology is explained largely by four factors, that is, perceived risk, perceived benefit, trust, and sense of bioethics, whether the technology is applied to plants, animals, or human beings. However, the relative importance of the four factors was found to vary depending on whether the gene-recombination technology was applied to plants, animals, or human beings. Specifically, the factor of sense of bioethics is the most important factor in acceptance of plant gene-recombination technology and animal gene-recombination technology, and the factors of trust and perceived risk are the most important factors in acceptance of human being gene-recombination technology.
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.
A comparison of methods of fitting several models to nutritional response data.
Vedenov, D; Pesti, G M
2008-02-01
A variety of models have been proposed to fit nutritional input-output response data. The models are typically nonlinear; therefore, fitting the models usually requires sophisticated statistical software and training to use it. An alternative tool for fitting nutritional response models was developed by using widely available and easier-to-use Microsoft Excel software. The tool, implemented as an Excel workbook (NRM.xls), allows simultaneous fitting and side-by-side comparisons of several popular models. This study compared the results produced by the tool we developed and PROC NLIN of SAS. The models compared were the broken line (ascending linear and quadratic segments), saturation kinetics, 4-parameter logistics, sigmoidal, and exponential models. The NRM.xls workbook provided results nearly identical to those of PROC NLIN. Furthermore, the workbook successfully fit several models that failed to converge in PROC NLIN. Two data sets were used as examples to compare fits by the different models. The results suggest that no particular nonlinear model is necessarily best for all nutritional response data.
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
A Model Fit Statistic for Generalized Partial Credit Model
ERIC Educational Resources Information Center
Liang, Tie; Wells, Craig S.
2009-01-01
Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…
In defence of inclusive fitness theory.
Herre, Edward Allen; Wcislo, William T
2011-03-24
Arising from M. A. Nowak, C. E. Tarnita & E. O. Wilson 466, 1057-1062 (2010); Nowak et al. reply. Arguably the defining characteristic of the scientific process is its capacity for self-criticism and correction. Nowak et al. challenge proposed connections between relatedness and the evolution of eusociality, suggest instead that defensible nests and "spring-loaded" traits are key, and present alternative modelling approaches. They then dismiss the utility of Hamilton's insight that relatedness has a profound evolutionary effect, formalized in his widely accepted inclusive fitness theory as Hamilton's rule ("Rise and fall of inclusive fitness theory"). However, we believe that Nowak et al. fail to make their case for logical, theoretical and empirical reasons.
Goodness-Of-Fit Test for Nonparametric Regression Models: Smoothing Spline ANOVA Models as Example.
Teran Hidalgo, Sebastian J; Wu, Michael C; Engel, Stephanie M; Kosorok, Michael R
2018-06-01
Nonparametric regression models do not require the specification of the functional form between the outcome and the covariates. Despite their popularity, the amount of diagnostic statistics, in comparison to their parametric counter-parts, is small. We propose a goodness-of-fit test for nonparametric regression models with linear smoother form. In particular, we apply this testing framework to smoothing spline ANOVA models. The test can consider two sources of lack-of-fit: whether covariates that are not currently in the model need to be included, and whether the current model fits the data well. The proposed method derives estimated residuals from the model. Then, statistical dependence is assessed between the estimated residuals and the covariates using the HSIC. If dependence exists, the model does not capture all the variability in the outcome associated with the covariates, otherwise the model fits the data well. The bootstrap is used to obtain p-values. Application of the method is demonstrated with a neonatal mental development data analysis. We demonstrate correct type I error as well as power performance through simulations.
Fitting Item Response Theory Models to Two Personality Inventories: Issues and Insights.
Chernyshenko, O S; Stark, S; Chan, K Y; Drasgow, F; Williams, B
2001-10-01
The present study compared the fit of several IRT models to two personality assessment instruments. Data from 13,059 individuals responding to the US-English version of the Fifth Edition of the Sixteen Personality Factor Questionnaire (16PF) and 1,770 individuals responding to Goldberg's 50 item Big Five Personality measure were analyzed. Various issues pertaining to the fit of the IRT models to personality data were considered. We examined two of the most popular parametric models designed for dichotomously scored items (i.e., the two- and three-parameter logistic models) and a parametric model for polytomous items (Samejima's graded response model). Also examined were Levine's nonparametric maximum likelihood formula scoring models for dichotomous and polytomous data, which were previously found to provide good fits to several cognitive ability tests (Drasgow, Levine, Tsien, Williams, & Mead, 1995). The two- and three-parameter logistic models fit some scales reasonably well but not others; the graded response model generally did not fit well. The nonparametric formula scoring models provided the best fit of the models considered. Several implications of these findings for personality measurement and personnel selection were described.
Unifying distance-based goodness-of-fit indicators for hydrologic model assessment
NASA Astrophysics Data System (ADS)
Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim
2014-05-01
The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on
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…
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…
Sensitivity of Fit Indices to Misspecification in Growth Curve Models
ERIC Educational Resources Information Center
Wu, Wei; West, Stephen G.
2010-01-01
This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…
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.
Models incorporate knowledge, assumptions and data. The trick is to know which model to use and when. Rough exposure assessments may be potentially useful if the uncertainty can be quantified and is acceptable (i.e., “fit for purpose”).
P-Care BPJS Acceptance Model in Primary Health Centers.
Markam, Hosizah
2017-01-01
Electronic Medical Records (EMR) are increasingly adopted in healthcare facilities. Recently, implementation failure of electronic information systems is known to be caused by not only the quality of technical aspects, but also the user's behavior. It is known as applying the Technology Acceptance Model (TAM). This research aimed to analyze the acceptance model of p-care BPJS in the primary health centers. A total sample of 30 p-care BPJS users was drawn by multistage random sampling in which of these 30 primary health centers participated. Data analysis used both descriptive and inferential statistics. In the phase of structural model, it indicated that p-care BPJS acceptance model in the primary health centers was formed by Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) through Attitude towards use of p-care BPJS and Behavioral Intention to use p-care BPJS.
The Routine Fitting of Kinetic Data to Models
Berman, Mones; Shahn, Ezra; Weiss, Marjory F.
1962-01-01
A mathematical formalism is presented for use with digital computers to permit the routine fitting of data to physical and mathematical models. Given a set of data, the mathematical equations describing a model, initial conditions for an experiment, and initial estimates for the values of model parameters, the computer program automatically proceeds to obtain a least squares fit of the data by an iterative adjustment of the values of the parameters. When the experimental measures are linear combinations of functions, the linear coefficients for a least squares fit may also be calculated. The values of both the parameters of the model and the coefficients for the sum of functions may be unknown independent variables, unknown dependent variables, or known constants. In the case of dependence, only linear dependencies are provided for in routine use. The computer program includes a number of subroutines, each one of which performs a special task. This permits flexibility in choosing various types of solutions and procedures. One subroutine, for example, handles linear differential equations, another, special non-linear functions, etc. The use of analytic or numerical solutions of equations is possible. PMID:13867975
Technological Diffusion within Educational Institutions: Applying the Technology Acceptance Model.
ERIC Educational Resources Information Center
Wolski, Stacy; Jackson, Sally
Expectancy models of behavior such as the Theory of Reasoned Action (TRA) and the Technology Acceptance Model (TAM) offer guidelines that aid efforts to facilitate use of new technology. These models remind us that both acceptance of and resistance to technology use are grounded in beliefs and norms regarding the technology. Although TAM is widely…
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…
Dynamical modeling and multi-experiment fitting with PottersWheel
Maiwald, Thomas; Timmer, Jens
2008-01-01
Motivation: Modelers in Systems Biology need a flexible framework that allows them to easily create new dynamic models, investigate their properties and fit several experimental datasets simultaneously. Multi-experiment-fitting is a powerful approach to estimate parameter values, to check the validity of a given model, and to discriminate competing model hypotheses. It requires high-performance integration of ordinary differential equations and robust optimization. Results: We here present the comprehensive modeling framework Potters-Wheel (PW) including novel functionalities to satisfy these requirements with strong emphasis on the inverse problem, i.e. data-based modeling of partially observed and noisy systems like signal transduction pathways and metabolic networks. PW is designed as a MATLAB toolbox and includes numerous user interfaces. Deterministic and stochastic optimization routines are combined by fitting in logarithmic parameter space allowing for robust parameter calibration. Model investigation includes statistical tests for model-data-compliance, model discrimination, identifiability analysis and calculation of Hessian- and Monte-Carlo-based parameter confidence limits. A rich application programming interface is available for customization within own MATLAB code. Within an extensive performance analysis, we identified and significantly improved an integrator–optimizer pair which decreases the fitting duration for a realistic benchmark model by a factor over 3000 compared to MATLAB with optimization toolbox. Availability: PottersWheel is freely available for academic usage at http://www.PottersWheel.de/. The website contains a detailed documentation and introductory videos. The program has been intensively used since 2005 on Windows, Linux and Macintosh computers and does not require special MATLAB toolboxes. Contact: maiwald@fdm.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:18614583
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.
One-point fitting of the flux density produced by a heliostat
DOE Office of Scientific and Technical Information (OSTI.GOV)
Collado, Francisco J.
Accurate and simple models for the flux density reflected by an isolated heliostat should be one of the basic tools for the design and optimization of solar power tower systems. In this work, the ability and the accuracy of the Universidad de Zaragoza (UNIZAR) and the DLR (HFCAL) flux density models to fit actual energetic spots are checked against heliostat energetic images measured at Plataforma Solar de Almeria (PSA). Both the fully analytic models are able to acceptably fit the spot with only one-point fitting, i.e., the measured maximum flux. As a practical validation of this one-point fitting, the interceptmore » percentage of the measured images, i.e., the percentage of the energetic spot sent by the heliostat that gets the receiver surface, is compared with the intercept calculated through the UNIZAR and HFCAL models. As main conclusions, the UNIZAR and the HFCAL models could be quite appropriate tools for the design and optimization, provided the energetic images from the heliostats to be used in the collector field were previously analyzed. Also note that the HFCAL model is much simpler and slightly more accurate than the UNIZAR model. (author)« less
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
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. © 2015 by the Society for Personality and Social Psychology, Inc.
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…
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.
Fitting and Modeling in the ASC Data Analysis Environment
NASA Astrophysics Data System (ADS)
Doe, S.; Siemiginowska, A.; Joye, W.; McDowell, J.
As part of the AXAF Science Center (ASC) Data Analysis Environment, we will provide to the astronomical community a Fitting Application. We present a design of the application in this paper. Our design goal is to give the user the flexibility to use a variety of optimization techniques (Levenberg-Marquardt, maximum entropy, Monte Carlo, Powell, downhill simplex, CERN-Minuit, and simulated annealing) and fit statistics (chi (2) , Cash, variance, and maximum likelihood); our modular design allows the user easily to add their own optimization techniques and/or fit statistics. We also present a comparison of the optimization techniques to be provided by the Application. The high spatial and spectral resolutions that will be obtained with AXAF instruments require a sophisticated data modeling capability. We will provide not only a suite of astronomical spatial and spectral source models, but also the capability of combining these models into source models of up to four data dimensions (i.e., into source functions f(E,x,y,t)). We will also provide tools to create instrument response models appropriate for each observation.
A Note on Recurring Misconceptions When Fitting Nonlinear Mixed Models.
Harring, Jeffrey R; Blozis, Shelley A
2016-01-01
Nonlinear mixed-effects (NLME) models are used when analyzing continuous repeated measures data taken on each of a number of individuals where the focus is on characteristics of complex, nonlinear individual change. Challenges with fitting NLME models and interpreting analytic results have been well documented in the statistical literature. However, parameter estimates as well as fitted functions from NLME analyses in recent articles have been misinterpreted, suggesting the need for clarification of these issues before these misconceptions become fact. These misconceptions arise from the choice of popular estimation algorithms, namely, the first-order linearization method (FO) and Gaussian-Hermite quadrature (GHQ) methods, and how these choices necessarily lead to population-average (PA) or subject-specific (SS) interpretations of model parameters, respectively. These estimation approaches also affect the fitted function for the typical individual, the lack-of-fit of individuals' predicted trajectories, and vice versa.
Technology Acceptance Model for Wireless Internet.
ERIC Educational Resources Information Center
Lu, June; Yu, Chun-Sheng; Liu, Chang; Yao, James E.
2003-01-01
Develops a technology acceptance model (TAM) for wireless Internet via mobile devices (WIMD) and proposes that constructs, such as individual differences, technology complexity, facilitating conditions, social influences, and wireless trust environment determine user-perceived short and long-term usefulness, and ease of using WIMD. Twelve…
Person-Fit Statistics for Joint Models for Accuracy and Speed
ERIC Educational Resources Information Center
Fox, Jean-Paul; Marianti, Sukaesi
2017-01-01
Response accuracy and response time data can be analyzed with a joint model to measure ability and speed of working, while accounting for relationships between item and person characteristics. In this study, person-fit statistics are proposed for joint models to detect aberrant response accuracy and/or response time patterns. The person-fit tests…
Model fitting data from syllogistic reasoning experiments.
Hattori, Masasi
2016-12-01
The data presented in this article are related to the research article entitled "Probabilistic representation in syllogistic reasoning: A theory to integrate mental models and heuristics" (M. Hattori, 2016) [1]. This article presents predicted data by three signature probabilistic models of syllogistic reasoning and model fitting results for each of a total of 12 experiments ( N =404) in the literature. Models are implemented in R, and their source code is also provided.
Fitting ARMA Time Series by Structural Equation Models.
ERIC Educational Resources Information Center
van Buuren, Stef
1997-01-01
This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)
Fast auto-focus scheme based on optical defocus fitting model
NASA Astrophysics Data System (ADS)
Wang, Yeru; Feng, Huajun; Xu, Zhihai; Li, Qi; Chen, Yueting; Cen, Min
2018-04-01
An optical defocus fitting model-based (ODFM) auto-focus scheme is proposed. Considering the basic optical defocus principle, the optical defocus fitting model is derived to approximate the potential-focus position. By this accurate modelling, the proposed auto-focus scheme can make the stepping motor approach the focal plane more accurately and rapidly. Two fitting positions are first determined for an arbitrary initial stepping motor position. Three images (initial image and two fitting images) at these positions are then collected to estimate the potential-focus position based on the proposed ODFM method. Around the estimated potential-focus position, two reference images are recorded. The auto-focus procedure is then completed by processing these two reference images and the potential-focus image to confirm the in-focus position using a contrast based method. Experimental results prove that the proposed scheme can complete auto-focus within only 5 to 7 steps with good performance even under low-light condition.
Kor, Elham Movahed; Rashidian, Arash; Hosseini, Mostafa; Azar, Farbod Ebadi Fard; Arab, Mohammad
2016-10-01
It is essential to organize private physicians in urban areas by developing urban family medicine in Iran. Acceptance of this project is currently low among physicians. The present research determined the factors affecting acceptability of the Urban Family Medicine Project among physicians working in the private sector of Mazandaran and Fars provinces in Iran. This descriptive-analytical and cross-sectional study was conducted in Mazandaran and Fars provinces. The target population was all physicians working in private offices in these regions. The sample size was calculated to be 860. The instrument contained 70 items that were modified in accordance with feedback from eight healthcare managers and a pilot sample of 50 physicians. Data was analyzed using the LISREL 8.80. The response rate was 82.21% and acceptability was almost 50% for all domains. The fit indices of the structural model were the chi-square to degree-of-freedom (2.79), normalized fit index (0.98), non-normalized fit index (0.99), comparative fit index (0.99), and root mean square error of approximation (0.05). Training facilities had no significant direct effect on acceptability; however, workload had a direct negative effect on acceptability. Other factors had direct positive effects on acceptability. Specification of the factors relating to acceptance of the project among private physicians is required to develop the project in urban areas. It is essential to upgrade the payment system, remedy cultural barriers, decrease the workload, improve the scope of practice and working conditions, and improve collaboration between healthcare professionals.
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…
Identifying best-fitting inputs in health-economic model calibration: a Pareto frontier approach.
Enns, Eva A; Cipriano, Lauren E; Simons, Cyrena T; Kong, Chung Yin
2015-02-01
To identify best-fitting input sets using model calibration, individual calibration target fits are often combined into a single goodness-of-fit (GOF) measure using a set of weights. Decisions in the calibration process, such as which weights to use, influence which sets of model inputs are identified as best-fitting, potentially leading to different health economic conclusions. We present an alternative approach to identifying best-fitting input sets based on the concept of Pareto-optimality. A set of model inputs is on the Pareto frontier if no other input set simultaneously fits all calibration targets as well or better. We demonstrate the Pareto frontier approach in the calibration of 2 models: a simple, illustrative Markov model and a previously published cost-effectiveness model of transcatheter aortic valve replacement (TAVR). For each model, we compare the input sets on the Pareto frontier to an equal number of best-fitting input sets according to 2 possible weighted-sum GOF scoring systems, and we compare the health economic conclusions arising from these different definitions of best-fitting. For the simple model, outcomes evaluated over the best-fitting input sets according to the 2 weighted-sum GOF schemes were virtually nonoverlapping on the cost-effectiveness plane and resulted in very different incremental cost-effectiveness ratios ($79,300 [95% CI 72,500-87,600] v. $139,700 [95% CI 79,900-182,800] per quality-adjusted life-year [QALY] gained). Input sets on the Pareto frontier spanned both regions ($79,000 [95% CI 64,900-156,200] per QALY gained). The TAVR model yielded similar results. Choices in generating a summary GOF score may result in different health economic conclusions. The Pareto frontier approach eliminates the need to make these choices by using an intuitive and transparent notion of optimality as the basis for identifying best-fitting input sets. © The Author(s) 2014.
SPSS macros to compare any two fitted values from a regression model.
Weaver, Bruce; Dubois, Sacha
2012-12-01
In regression models with first-order terms only, the coefficient for a given variable is typically interpreted as the change in the fitted value of Y for a one-unit increase in that variable, with all other variables held constant. Therefore, each regression coefficient represents the difference between two fitted values of Y. But the coefficients represent only a fraction of the possible fitted value comparisons that might be of interest to researchers. For many fitted value comparisons that are not captured by any of the regression coefficients, common statistical software packages do not provide the standard errors needed to compute confidence intervals or carry out statistical tests-particularly in more complex models that include interactions, polynomial terms, or regression splines. We describe two SPSS macros that implement a matrix algebra method for comparing any two fitted values from a regression model. The !OLScomp and !MLEcomp macros are for use with models fitted via ordinary least squares and maximum likelihood estimation, respectively. The output from the macros includes the standard error of the difference between the two fitted values, a 95% confidence interval for the difference, and a corresponding statistical test with its p-value.
An approximation method for improving dynamic network model fitting.
Carnegie, Nicole Bohme; Krivitsky, Pavel N; Hunter, David R; Goodreau, Steven M
There has been a great deal of interest recently in the modeling and simulation of dynamic networks, i.e., networks that change over time. One promising model is the separable temporal exponential-family random graph model (ERGM) of Krivitsky and Handcock, which treats the formation and dissolution of ties in parallel at each time step as independent ERGMs. However, the computational cost of fitting these models can be substantial, particularly for large, sparse networks. Fitting cross-sectional models for observations of a network at a single point in time, while still a non-negligible computational burden, is much easier. This paper examines model fitting when the available data consist of independent measures of cross-sectional network structure and the duration of relationships under the assumption of stationarity. We introduce a simple approximation to the dynamic parameters for sparse networks with relationships of moderate or long duration and show that the approximation method works best in precisely those cases where parameter estimation is most likely to fail-networks with very little change at each time step. We consider a variety of cases: Bernoulli formation and dissolution of ties, independent-tie formation and Bernoulli dissolution, independent-tie formation and dissolution, and dependent-tie formation models.
Performance of Transit Model Fitting in Processing Four Years of Kepler Science Data
NASA Astrophysics Data System (ADS)
Li, Jie; Burke, Christopher J.; Jenkins, Jon Michael; Quintana, Elisa V.; Rowe, Jason; Seader, Shawn; Tenenbaum, Peter; Twicken, Joseph D.
2014-06-01
We present transit model fitting performance of the Kepler Science Operations Center (SOC) Pipeline in processing four years of science data, which were collected by the Kepler spacecraft from May 13, 2009 to May 12, 2013. Threshold Crossing Events (TCEs), which represent transiting planet detections, are generated by the Transiting Planet Search (TPS) component of the pipeline and subsequently processed in the Data Validation (DV) component. The transit model is used in DV to fit TCEs and derive parameters that are used in various diagnostic tests to validate planetary candidates. The standard transit model includes five fit parameters: transit epoch time (i.e. central time of first transit), orbital period, impact parameter, ratio of planet radius to star radius and ratio of semi-major axis to star radius. In the latest Kepler SOC pipeline codebase, the light curve of the target for which a TCE is generated is initially fitted by a trapezoidal model with four parameters: transit epoch time, depth, duration and ingress time. The trapezoidal model fit, implemented with repeated Levenberg-Marquardt minimization, provides a quick and high fidelity assessment of the transit signal. The fit parameters of the trapezoidal model with the minimum chi-square metric are converted to set initial values of the fit parameters of the standard transit model. Additional parameters, such as the equilibrium temperature and effective stellar flux of the planet candidate, are derived from the fit parameters of the standard transit model to characterize pipeline candidates for the search of Earth-size planets in the Habitable Zone. The uncertainties of all derived parameters are updated in the latest codebase to take into account for the propagated errors of the fit parameters as well as the uncertainties in stellar parameters. The results of the transit model fitting of the TCEs identified by the Kepler SOC Pipeline, including fitted and derived parameters, fit goodness metrics and
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.
Identifying best-fitting inputs in health-economic model calibration: a Pareto frontier approach
Enns, Eva A.; Cipriano, Lauren E.; Simons, Cyrena T.; Kong, Chung Yin
2014-01-01
Background To identify best-fitting input sets using model calibration, individual calibration target fits are often combined into a single “goodness-of-fit” (GOF) measure using a set of weights. Decisions in the calibration process, such as which weights to use, influence which sets of model inputs are identified as best-fitting, potentially leading to different health economic conclusions. We present an alternative approach to identifying best-fitting input sets based on the concept of Pareto-optimality. A set of model inputs is on the Pareto frontier if no other input set simultaneously fits all calibration targets as well or better. Methods We demonstrate the Pareto frontier approach in the calibration of two models: a simple, illustrative Markov model and a previously-published cost-effectiveness model of transcatheter aortic valve replacement (TAVR). For each model, we compare the input sets on the Pareto frontier to an equal number of best-fitting input sets according to two possible weighted-sum GOF scoring systems, and compare the health economic conclusions arising from these different definitions of best-fitting. Results For the simple model, outcomes evaluated over the best-fitting input sets according to the two weighted-sum GOF schemes were virtually non-overlapping on the cost-effectiveness plane and resulted in very different incremental cost-effectiveness ratios ($79,300 [95%CI: 72,500 – 87,600] vs. $139,700 [95%CI: 79,900 - 182,800] per QALY gained). Input sets on the Pareto frontier spanned both regions ($79,000 [95%CI: 64,900 – 156,200] per QALY gained). The TAVR model yielded similar results. Conclusions Choices in generating a summary GOF score may result in different health economic conclusions. The Pareto frontier approach eliminates the need to make these choices by using an intuitive and transparent notion of optimality as the basis for identifying best-fitting input sets. PMID:24799456
DOE Office of Scientific and Technical Information (OSTI.GOV)
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-Gaussianmore » 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
Fitness Testing: The Pleasure and Pain of It
ERIC Educational Resources Information Center
Garrett, Robyne; Wrench, Alison
2008-01-01
The obesity crisis is a discourse that has established common-sense understandings that all young people are less active and fit than previous generations. Unquestioning acceptance of the links between fitness and obesity in turn leads to unproblematic fitness testing of young people. This research investigated the personal and embodied…
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.
Considering a complemental model of health and fitness.
Neville, Ross D
2013-03-01
This article examines the concept of fitness, which, in spite of its much avowed cultural significance, has become the subject of much critical attention. In particular, it considers the now contested relation of fitness to health; the fact that, although there appears to be a clear consensus on a simple causal relation between the two, this has been deemed illusory outside the medico-scientific context of its production. In response to the problems with both of these positions, this article examines the potential for reconfiguring the relation between fitness and health on new terms. A complemental model of health and fitness is proposed; one that strives to account for the body's objective and subjective dimensions and for those intermediary varieties of experience that lie in between. © 2012 The Authors. Sociology of Health & Illness © 2012 Foundation for the Sociology of Health & Illness/Blackwell Publishing Ltd.
Using a modified technology acceptance model in hospitals.
Aggelidis, Vassilios P; Chatzoglou, Prodromos D
2009-02-01
The use of information technology in the health care sector and especially in hospitals offers great potential for improving the quality of services provided and the efficiency and effectiveness of the personnel, but also for reducing the organizational expenses. However, the main question that arises according to the literature is whether hospital personnel are willing to use state of the art information technology while performing their tasks. This study attempts to address this issue by developing and testing a modified technology acceptance model taking into consideration other relevant models found in the literature. The original TAM has been extended to include some exogenous variables in order to examine HIS acceptance by Greek hospital personnel. Correlation, explanatory and confirmation factor analysis was performed to test the reliability and validity of the measurement model. The structural equation modeling technique has also been used to evaluate the causal model. The results indicate that perceived usefulness, ease of use, social influence, attitude, facilitating conditions and self-efficacy significantly affect hospital personnel behavioral intention. Training has a strong indirect impact on behavioral intention through the mediators of facilitating condition and ease of use. Furthermore, the existence of significant positive effects between self-efficacy and social influence, perceived usefulness and anxiety, and facilitating conditions and social influence is also supported. The proposed model can explain 87% of the variance of behavioral intention indicating that the core constructs of the technology acceptance models have a strong and statistically significant influence on hospital personnel usage intention.
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...
Fitness level and body composition indices: cross-sectional study among Malaysian adolescent
2014-01-01
Background The importance of fitness level on the well-being of children and adolescent has long been recognised. The aim of this study was to investigate the fitness level of school-going Malaysian adolescent, and its association with body composition indices. Methods 1071 healthy secondary school students participated in the fitness assessment for the Malaysian Health and Adolescents Longitudinal Research Team (MyHEART) study. Body composition indices such as body mass index for age, waist circumference and waist height ratio were measured. Fitness level was assessed with Modified Harvard Step Test. Physical Fitness Score was calculated using total time of step test exercise and resting heart rates. Fitness levels were divided into 3 categories - unacceptable, marginally acceptable, and acceptable. Partial correlation analysis was used to determine the association between fitness score and body composition, by controlling age, gender, locality, ethnicity, smoking status and sexual maturation. Multiple regression analysis was conducted to determine which body composition was the strongest predictor for fitness. Results 43.3% of the participants were categorised into the unacceptable fitness group, 47.1% were considered marginally acceptable, and 9.6% were acceptable. There was a significant moderate inverse association (p < 0.001) between body composition with fitness score (r = -0.360, -0.413 and -0.403 for body mass index for age, waist circumference and waist height ratio, respectively). Waist circumference was the strongest and significant predictor for fitness (ß = -0.318, p = 0.002). Conclusion Only 9.6% of the students were fit. There was also an inverse association between body composition and fitness score among apparently healthy adolescents, with waist circumference indicated as the strongest predictor. The low fitness level among the Malaysian adolescent should necessitate the value of healthy lifestyle starting at a young age. PMID:25436933
Fitness level and body composition indices: cross-sectional study among Malaysian adolescent.
Hanifah, Redzal Abu; Majid, Hazreen Abdul; Jalaludin, Muhammad Yazid; Al-Sadat, Nabilla; Murray, Liam J; Cantwell, Marie; Su, Tin Tin; Nahar, Azmi Mohamed
2014-01-01
The importance of fitness level on the well-being of children and adolescent has long been recognised. The aim of this study was to investigate the fitness level of school-going Malaysian adolescent, and its association with body composition indices. 1071 healthy secondary school students participated in the fitness assessment for the Malaysian Health and Adolescents Longitudinal Research Team (MyHEART) study. Body composition indices such as body mass index for age, waist circumference and waist height ratio were measured. Fitness level was assessed with Modified Harvard Step Test. Physical Fitness Score was calculated using total time of step test exercise and resting heart rates. Fitness levels were divided into 3 categories - unacceptable, marginally acceptable, and acceptable. Partial correlation analysis was used to determine the association between fitness score and body composition, by controlling age, gender, locality, ethnicity, smoking status and sexual maturation. Multiple regression analysis was conducted to determine which body composition was the strongest predictor for fitness. 43.3% of the participants were categorised into the unacceptable fitness group, 47.1% were considered marginally acceptable, and 9.6% were acceptable. There was a significant moderate inverse association (p < 0.001) between body composition with fitness score (r = -0.360, -0.413 and -0.403 for body mass index for age, waist circumference and waist height ratio, respectively). Waist circumference was the strongest and significant predictor for fitness (ß = -0.318, p = 0.002). Only 9.6% of the students were fit. There was also an inverse association between body composition and fitness score among apparently healthy adolescents, with waist circumference indicated as the strongest predictor. The low fitness level among the Malaysian adolescent should necessitate the value of healthy lifestyle starting at a young age.
Acceptance model of a Hospital Information System.
Handayani, P W; Hidayanto, A N; Pinem, A A; Hapsari, I C; Sandhyaduhita, P I; Budi, I
2017-03-01
The purpose of this study is to develop a model of Hospital Information System (HIS) user acceptance focusing on human, technological, and organizational characteristics for supporting government eHealth programs. This model was then tested to see which hospital type in Indonesia would benefit from the model to resolve problems related to HIS user acceptance. This study used qualitative and quantitative approaches with case studies at four privately owned hospitals and three government-owned hospitals, which are general hospitals in Indonesia. The respondents involved in this study are low-level and mid-level hospital management officers, doctors, nurses, and administrative staff who work at medical record, inpatient, outpatient, emergency, pharmacy, and information technology units. Data was processed using Structural Equation Modeling (SEM) and AMOS 21.0. The study concludes that non-technological factors, such as human characteristics (i.e. compatibility, information security expectancy, and self-efficacy), and organizational characteristics (i.e. management support, facilitating conditions, and user involvement) which have level of significance of p<0.05, significantly influenced users' opinions of both the ease of use and the benefits of the HIS. This study found that different factors may affect the acceptance of each user in each type of hospital regarding the use of HIS. Finally, this model is best suited for government-owned hospitals. Based on the results of this study, hospital management and IT developers should have more understanding on the non-technological factors to better plan for HIS implementation. Support from management is critical to the sustainability of HIS implementation to ensure HIS is easy to use and provides benefits to the users as well as hospitals. Finally, this study could assist hospital management and IT developers, as well as researchers, to understand the obstacles faced by hospitals in implementing HIS. Copyright © 2016
Using evolutionary algorithms for fitting high-dimensional models to neuronal data.
Svensson, Carl-Magnus; Coombes, Stephen; Peirce, Jonathan Westley
2012-04-01
In the study of neurosciences, and of complex biological systems in general, there is frequently a need to fit mathematical models with large numbers of parameters to highly complex datasets. Here we consider algorithms of two different classes, gradient following (GF) methods and evolutionary algorithms (EA) and examine their performance in fitting a 9-parameter model of a filter-based visual neuron to real data recorded from a sample of 107 neurons in macaque primary visual cortex (V1). Although the GF method converged very rapidly on a solution, it was highly susceptible to the effects of local minima in the error surface and produced relatively poor fits unless the initial estimates of the parameters were already very good. Conversely, although the EA required many more iterations of evaluating the model neuron's response to a series of stimuli, it ultimately found better solutions in nearly all cases and its performance was independent of the starting parameters of the model. Thus, although the fitting process was lengthy in terms of processing time, the relative lack of human intervention in the evolutionary algorithm, and its ability ultimately to generate model fits that could be trusted as being close to optimal, made it far superior in this particular application than the gradient following methods. This is likely to be the case in many further complex systems, as are often found in neuroscience.
Clark, D Angus; Bowles, Ryan P
2018-04-23
In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.
Pham, Robyn; Cross, Suzanne; Fernandez, Bianca; Corson, Kathryn; Dillon, Kristen; Yackley, Coco; Davis, Melinda M
2017-01-01
Colorectal cancer (CRC) is the third leading cause of cancer death in the United States, yet 1 in 3 Americans have never been screened for CRC. Annual screening using fecal immunochemical tests (FITs) is often a preferred modality in populations experiencing CRC screening disparities. Although multiple studies evaluate the clinical effectiveness of FITs, few studies assess patient preferences toward kit characteristics. We conducted this community-led study to assess patient preferences for FIT characteristics and to use study findings in concert with clinical effectiveness data to inform regional FIT selection. We collaborated with local health system leaders to identify FITs and recruit age eligible (50 to 75 years), English or Spanish speaking community members. Participants completed up to 6 FITs and associated questionnaires and were invited to participate in a follow-up focus group. We used a sequential explanatory mixed-methods design to assess participant preferences and rank FIT kits. First, we used quantitative data from user testing to measure acceptability, ease of completion, and specimen adequacy through a descriptive analysis of 1) fixed response questionnaire items on participant attitudes toward and experiences with FIT kits, and 2) a clinical assessment of adherence to directions regarding collection, packaging, and return of specimens. Second, we analyzed qualitative data from focus groups to refine FIT rankings and gain deeper insight into the pros and cons associated with each tested kit. Seventy-six FITs were completed by 18 participants (Range, 3 to 6 kits per participant). Over half (56%, n = 10) of the participants were Hispanic and 50% were female (n = 9). Thirteen participants attended 1 of 3 focus groups. Participants preferred FITs that were single sample, used a probe and vial for sample collection, and had simple, large-font instructions with colorful pictures. Participants reported challenges using paper to catch samples, had
Limitations of inclusive fitness.
Allen, Benjamin; Nowak, Martin A; Wilson, Edward O
2013-12-10
Until recently, inclusive fitness has been widely accepted as a general method to explain the evolution of social behavior. Affirming and expanding earlier criticism, we demonstrate that inclusive fitness is instead a limited concept, which exists only for a small subset of evolutionary processes. Inclusive fitness assumes that personal fitness is the sum of additive components caused by individual actions. This assumption does not hold for the majority of evolutionary processes or scenarios. To sidestep this limitation, inclusive fitness theorists have proposed a method using linear regression. On the basis of this method, it is claimed that inclusive fitness theory (i) predicts the direction of allele frequency changes, (ii) reveals the reasons for these changes, (iii) is as general as natural selection, and (iv) provides a universal design principle for evolution. In this paper we evaluate these claims, and show that all of them are unfounded. If the objective is to analyze whether mutations that modify social behavior are favored or opposed by natural selection, then no aspect of inclusive fitness theory is needed.
ERIC Educational Resources Information Center
Akman, Ibrahim; Turhan, Cigdem
2017-01-01
This study aims to explore the users' behaviour and acceptance of social media for learning in higher educational institutions with the help of the extended Technology Acceptance Model (TAM). TAM has been extended to investigate how ethical and security awareness of users affect the actual usage of social learning applications. For this purpose, a…
[How to fit and interpret multilevel models using SPSS].
Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael
2007-05-01
Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.
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…
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…
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.
An application of model-fitting procedures for marginal structural models.
Mortimer, Kathleen M; Neugebauer, Romain; van der Laan, Mark; Tager, Ira B
2005-08-15
Marginal structural models (MSMs) are being used more frequently to obtain causal effect estimates in observational studies. Although the principal estimator of MSM coefficients has been the inverse probability of treatment weight (IPTW) estimator, there are few published examples that illustrate how to apply IPTW or discuss the impact of model selection on effect estimates. The authors applied IPTW estimation of an MSM to observational data from the Fresno Asthmatic Children's Environment Study (2000-2002) to evaluate the effect of asthma rescue medication use on pulmonary function and compared their results with those obtained through traditional regression methods. Akaike's Information Criterion and cross-validation methods were used to fit the MSM. In this paper, the influence of model selection and evaluation of key assumptions such as the experimental treatment assignment assumption are discussed in detail. Traditional analyses suggested that medication use was not associated with an improvement in pulmonary function--a finding that is counterintuitive and probably due to confounding by symptoms and asthma severity. The final MSM estimated that medication use was causally related to a 7% improvement in pulmonary function. The authors present examples that should encourage investigators who use IPTW estimation to undertake and discuss the impact of model-fitting procedures to justify the choice of the final weights.
Martin, Guillaume; Roques, Lionel
2016-01-01
Various models describe asexual evolution by mutation, selection, and drift. Some focus directly on fitness, typically modeling drift but ignoring or simplifying both epistasis and the distribution of mutation effects (traveling wave models). Others follow the dynamics of quantitative traits determining fitness (Fisher’s geometric model), imposing a complex but fixed form of mutation effects and epistasis, and often ignoring drift. In all cases, predictions are typically obtained in high or low mutation rate limits and for long-term stationary regimes, thus losing information on transient behaviors and the effect of initial conditions. Here, we connect fitness-based and trait-based models into a single framework, and seek explicit solutions even away from stationarity. The expected fitness distribution is followed over time via its cumulant generating function, using a deterministic approximation that neglects drift. In several cases, explicit trajectories for the full fitness distribution are obtained for arbitrary mutation rates and standing variance. For nonepistatic mutations, especially with beneficial mutations, this approximation fails over the long term but captures the early dynamics, thus complementing stationary stochastic predictions. The approximation also handles several diminishing returns epistasis models (e.g., with an optimal genotype); it can be applied at and away from equilibrium. General results arise at equilibrium, where fitness distributions display a “phase transition” with mutation rate. Beyond this phase transition, in Fisher’s geometric model, the full trajectory of fitness and trait distributions takes a simple form; robust to the details of the mutant phenotype distribution. Analytical arguments are explored regarding why and when the deterministic approximation applies. PMID:27770037
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…
The l z ( p ) * Person-Fit Statistic in an Unfolding Model Context.
Tendeiro, Jorge N
2017-01-01
Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded unfolding model is used. Results from a simulation study indicate that the person-fit statistic performed relatively well in detecting midpoint response style patterns and not so well in detecting extreme response style patterns.
Improved Model Fitting for the Empirical Green's Function Approach Using Hierarchical Models
NASA Astrophysics Data System (ADS)
Van Houtte, Chris; Denolle, Marine
2018-04-01
Stress drops calculated from source spectral studies currently show larger variability than what is implied by empirical ground motion models. One of the potential origins of the inflated variability is the simplified model-fitting techniques used in most source spectral studies. This study examines a variety of model-fitting methods and shows that the choice of method can explain some of the discrepancy. The preferred method is Bayesian hierarchical modeling, which can reduce bias, better quantify uncertainties, and allow additional effects to be resolved. Two case study earthquakes are examined, the 2016 MW7.1 Kumamoto, Japan earthquake and a MW5.3 aftershock of the 2016 MW7.8 Kaikōura earthquake. By using hierarchical models, the variation of the corner frequency, fc, and the falloff rate, n, across the focal sphere can be retrieved without overfitting the data. Other methods commonly used to calculate corner frequencies may give substantial biases. In particular, if fc was calculated for the Kumamoto earthquake using an ω-square model, the obtained fc could be twice as large as a realistic value.
On the accuracy of models for predicting sound propagation in fitted rooms.
Hodgson, M
1990-08-01
The objective of this article is to make a contribution to the evaluation of the accuracy and applicability of models for predicting the sound propagation in fitted rooms such as factories, classrooms, and offices. The models studied are 1:50 scale models; the method-of-image models of Jovicic, Lindqvist, Hodgson, Kurze, and of Lemire and Nicolas; the emprical formula of Friberg; and Ondet and Barbry's ray-tracing model. Sound propagation predictions by the analytic models are compared with the results of sound propagation measurements in a 1:50 scale model and in a warehouse, both containing various densities of approximately isotropically distributed, rectangular-parallelepipedic fittings. The results indicate that the models of Friberg and of Lemire and Nicolas are fundamentally incorrect. While more generally applicable versions exist, the versions of the models of Jovicic and Kurze studied here are found to be of limited applicability since they ignore vertical-wall reflections. The Hodgson and Lindqvist models appear to be accurate in certain limited cases. This preliminary study found the ray-tracing model of Ondet and Barbry to be the most accurate of all the cases studied. Furthermore, it has the necessary flexibility with respect to room geometry, surface-absorption distribution, and fitting distribution. It appears to be the model with the greatest applicability to fitted-room sound propagation prediction.
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.
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…
Assessing Model Fitting of Megamaser Disks with Simulated Observations
NASA Astrophysics Data System (ADS)
Han, Jiwon; Braatz, James; Pesce, Dominic
2018-01-01
The Megamaser Cosmology Project (MCP) measures the Hubble Constant by determining distances to galaxies with observations of 22 GHz H20 megamasers. The megamasers arise in the circumnuclear accretion disks of active galaxies. In this research, we aim to improve the estimation of systematic errors in MCP measurements. Currently, the MCP fits a disk model to the observed maser data with a Markov Chain Monte Carlo (MCMC) code. The disk model is described by up to 14 global parameters, including up to 6 that describe the disk warping. We first assess the model by generating synthetic datasets in which the locations and dynamics of the maser spots are exactly known, and fitting the model to these data. By doing so, we can also test the effects of unmodeled substructure on the estimated uncertainties. Furthermore, in order to gain better understanding of the physics behind accretion disk warping, we develop a physics-driven model for the warp and test it with the MCMC approach.
Cross-National Comparisons of College Students' Attitudes toward Diet/Fitness Apps on Smartphones
ERIC Educational Resources Information Center
Cho, Jaehee; Lee, H. Erin; Quinlan, Margaret
2017-01-01
Objective: Based on the technology acceptance model (TAM), we explored the nationally-bounded roles of four predictors (subjective norms, entertainment, recordability, and networkability) in determining the TAM variables of perceived usefulness (PU), perceived ease of use (PEOU), and behavioral intention (BI) to use diet/fitness apps on…
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'…
Lee, Chien-Ching; Lin, Shih-Pin; Yang, Shu-Ling; Tsou, Mei-Yung; Chang, Kuang-Yi
2013-03-01
Medical institutions are eager to introduce new information technology to improve patient safety and clinical efficiency. However, the acceptance of new information technology by medical personnel plays a key role in its adoption and application. This study aims to investigate whether perceived organizational learning capability (OLC) is associated with user acceptance of information technology among operating room nurse staff. Nurse anesthetists and operating room nurses were recruited in this questionnaire survey. A pilot study was performed to ensure the reliability and validity of the translated questionnaire, which consisted of 14 items from the four dimensions of OLC, and 16 items from the four constructs of user acceptance of information technology, including performance expectancy, effort expectancy, social influence, and behavioral intention. Confirmatory factor analysis was applied in the main survey to evaluate the construct validity of the questionnaire. Structural equation modeling was used to test the hypothetical relationships between the four dimensions of user acceptance of information technology and the second-ordered OLC. Goodness of fit of the hypothetic model was also assessed. Performance expectancy, effort expectancy, and social influence positively influenced behavioral intention of users of the clinical information system (all p < 0.001) and accounted for 75% of its variation. The second-ordered OLC was positively associated with performance expectancy, effort expectancy, and social influence (all p < 0.001). However, the hypothetic relationship between perceived OLC and behavioral intention was not significant (p = 0.87). The fit statistical analysis indicated reasonable model fit to data (root mean square error of approximation = 0.07 and comparative fit index = 0.91). Perceived OLC indirectly affects user behavioral intention through the mediation of performance expectancy, effort expectancy, and social influence in the operating room
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 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.« less
Goodness of fit of probability distributions for sightings as species approach extinction.
Vogel, Richard M; Hosking, Jonathan R M; Elphick, Chris S; Roberts, David L; Reed, J Michael
2009-04-01
Estimating the probability that a species is extinct and the timing of extinctions is useful in biological fields ranging from paleoecology to conservation biology. Various statistical methods have been introduced to infer the time of extinction and extinction probability from a series of individual sightings. There is little evidence, however, as to which of these models provide adequate fit to actual sighting records. We use L-moment diagrams and probability plot correlation coefficient (PPCC) hypothesis tests to evaluate the goodness of fit of various probabilistic models to sighting data collected for a set of North American and Hawaiian bird populations that have either gone extinct, or are suspected of having gone extinct, during the past 150 years. For our data, the uniform, truncated exponential, and generalized Pareto models performed moderately well, but the Weibull model performed poorly. Of the acceptable models, the uniform distribution performed best based on PPCC goodness of fit comparisons and sequential Bonferroni-type tests. Further analyses using field significance tests suggest that although the uniform distribution is the best of those considered, additional work remains to evaluate the truncated exponential model more fully. The methods we present here provide a framework for evaluating subsequent models.
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.
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.
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
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.
Correcting Model Fit Criteria for Small Sample Latent Growth Models with Incomplete Data
ERIC Educational Resources Information Center
McNeish, Daniel; Harring, Jeffrey R.
2017-01-01
To date, small sample problems with latent growth models (LGMs) have not received the amount of attention in the literature as related mixed-effect models (MEMs). Although many models can be interchangeably framed as a LGM or a MEM, LGMs uniquely provide criteria to assess global data-model fit. However, previous studies have demonstrated poor…
Consumers' acceptance of medicinal herbs: An application of the technology acceptance model (TAM).
Jokar, Nargesh Khatun; Noorhosseini, Seyyed Ali; Allahyari, Mohammad Sadegh; Damalas, Christos A
2017-07-31
The shift in consumers' preferences from synthetic to 'natural' products has led to a resurgence of interest in medicinal plants, particularly in developing countries. However, research data about consumers' preferences for particular products is hard to find. The main objective of this study was to contribute to the general understanding of consumers' intention for selecting medicinal herbs for consumption. Factors underpinning consumers' acceptance of medicinal herbs were studied with the technology acceptance model (TAM) in Rasht City of Iran using a structured questionnaire. Most respondents had low to moderate familiarity with consumption of medicinal herbs. However, about half of the respondents (47.5%) showed a high level of acceptance of medicinal herbs. Herbs like spearmint (Mentha spicata L.), spinach (Spinacia oleracea L.), basil (Ocimum basilicum L.), Damask rose (Rosa × damascena Herrm.), saffron (Crocus sativus L.), cinnamon (Cinnamomum verum J.Presl), flixweed [Descurainia sophia (L.) Webb ex Prantl], red feathers (Echium amoenum Fisch. & C.A.Mey.), and green tea [Camellia sinensis (L.) Kuntze] had the highest consumption rate among the majority (over 75%) of citizens of Rasht. The highest rate of perceived usefulness of medicinal herbs was related to their perceived role in healing diseases. The variable of importance of use of medicinal herbs had the strongest direct effect and the variables of perceived usefulness and attitude towards use had the second and third strongest direct effect on the acceptance of medicinal herbs' use at p < 0.01. Findings provide a useful evaluation of the acceptance of medicinal herbs and may serve as a benchmark for future research and evaluation concerning the use of medicinal herbs over time. For plant producers, more effective and targeted crop development should be encouraged, whereas for retailers better marketing and delivery strategies should be sought. Copyright © 2017 Elsevier Ireland Ltd. All rights
Modeling chromatic instrumental effects for a better model fitting of optical interferometric data
NASA Astrophysics Data System (ADS)
Tallon, M.; Tallon-Bosc, I.; Chesneau, O.; Dessart, L.
2014-07-01
Current interferometers often collect data simultaneously in many spectral channels by using dispersed fringes. Such polychromatic data provide powerful insights in various physical properties, where the observed objects show particular spectral features. Furthermore, one can measure spectral differential visibilities that do not directly depend on any calibration by a reference star. But such observations may be sensitive to instrumental artifacts that must be taken into account in order to fully exploit the polychromatic information of interferometric data. As a specimen, we consider here an observation of P Cygni with the VEGA visible combiner on CHARA interferometer. Indeed, although P Cygni is particularly well modeled by the radiative transfer code CMFGEN, we observe questionable discrepancies between expected and actual interferometric data. The problem is to determine their origin and disentangle possible instrumental effects from the astrophysical information. By using an expanded model fitting, which includes several instrumental features, we show that the differential visibilities are well explained by instrumental effects that could be otherwise attributed to the object. Although this approach leads to more reliable results, it assumes a fit specific to a particular instrument, and makes it more difficult to develop a generic model fitting independent of any instrument.
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
2017-01-04
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 (T opt ) for maximum photosynthetic rate (P max ). 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
Dawson, Carolyn H; Mackrill, Jamie B; Cain, Rebecca
2017-12-01
Hand hygiene (HH) prevents harmful contaminants spreading in settings including domestic, health care and food handling. Strategies to improve HH range from behavioural techniques through to automated sinks that ensure hand surface cleaning. This study aimed to assess user experience and acceptance towards a new automated sink, compared to a normal sink. An adapted version of the technology acceptance model (TAM) assessed each mode of handwashing. A within-subjects design enabled N = 46 participants to evaluate both sinks. Perceived Ease of Use and Satisfaction of Use were significantly lower for the automated sink, compared to the conventional sink (p < 0.005). Across the remaining TAM factors, there was no significant difference. Participants suggested design features including jet strength, water temperature and device affordance may improve HH technology. We provide recommendations for future HH technology development to contribute a positive user experience, relevant to technology developers, ergonomists and those involved in HH across all sectors. Practitioner Summary: The need to facilitate timely, effective hand hygiene to prevent illness has led to a rise in automated handwashing systems across different contexts. User acceptance is a key factor in system uptake. This paper applies the technology acceptance model as a means to explore and optimise the design of such systems.
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…
Xu, Wei; Zhou, Yuyang; Fu, Zhongfang; Rodriguez, Marcus
2017-12-01
Previous studies have shown that dispositional mindfulness is associated with less psychological symptoms in cancer patients. The present study investigated how dispositional mindfulness is related to psychological symptoms in advanced gastrointestinal cancer patients by considering the roles of self-acceptance and perceived stress. A total of 176 patients with advanced gastrointestinal cancer were recruited to complete a series of questionnaires including Mindfulness Attention Awareness Scale, Self-acceptance Questionnaire, Chinese Perceived Stress Scale, and General Health Questionnaire. Results showed that the proposed model fitted the data very well (χ 2 = 7.564, df = 7, P = .364, χ 2 /df = 1.094, Goodness of Fit Index (GFI) = 0.986, Comparative Fit Index (CFI) = 0.998, Tucker Lewis Index (TLI) = 0.995, Root Mean Square Error of Approximation (RMSEA) = 0.023). Further analyses revealed that, self-acceptance and perceived stress mediated the relation between dispositional mindfulness and psychological symptoms (indirect effect = -0.052, 95% confidence interval = -0.087 ~ -0.024), while self-acceptance also mediated the relation between dispositional mindfulness and perceived stress (indirect effect = -0.154, 95% confidence interval = -0.261 ~ -0.079). Self-acceptance and perceived stress played critical roles in the relation between dispositional mindfulness and psychological symptoms. Limitations, clinical implications, and directions for future research were discussed. Copyright © 2017 John Wiley & Sons, Ltd.
Commisso, Maria S; Martínez-Reina, Javier; Mayo, Juana; Domínguez, Jaime
2013-02-01
The main objectives of this work are: (a) to introduce an algorithm for adjusting the quasi-linear viscoelastic model to fit a material using a stress relaxation test and (b) to validate a protocol for performing such tests in temporomandibular joint discs. This algorithm is intended for fitting the Prony series coefficients and the hyperelastic constants of the quasi-linear viscoelastic model by considering that the relaxation test is performed with an initial ramp loading at a certain rate. This algorithm was validated before being applied to achieve the second objective. Generally, the complete three-dimensional formulation of the quasi-linear viscoelastic model is very complex. Therefore, it is necessary to design an experimental test to ensure a simple stress state, such as uniaxial compression to facilitate obtaining the viscoelastic properties. This work provides some recommendations about the experimental setup, which are important to follow, as an inadequate setup could produce a stress state far from uniaxial, thus, distorting the material constants determined from the experiment. The test considered is a stress relaxation test using unconfined compression performed in cylindrical specimens extracted from temporomandibular joint discs. To validate the experimental protocol, the test was numerically simulated using finite-element modelling. The disc was arbitrarily assigned a set of quasi-linear viscoelastic constants (c1) in the finite-element model. Another set of constants (c2) was obtained by fitting the results of the simulated test with the proposed algorithm. The deviation of constants c2 from constants c1 measures how far the stresses are from the uniaxial state. The effects of the following features of the experimental setup on this deviation have been analysed: (a) the friction coefficient between the compression plates and the specimen (which should be as low as possible); (b) the portion of the specimen glued to the compression plates (smaller
How Good Are Statistical Models at Approximating Complex Fitness Landscapes?
du Plessis, Louis; Leventhal, Gabriel E.; Bonhoeffer, Sebastian
2016-01-01
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. PMID:27189564
Liou, Jing-Yang; Ting, Chien-Kun; Mandell, M Susan; Chang, Kuang-Yi; Teng, Wei-Nung; Huang, Yu-Yin; Tsou, Mei-Yung
2016-08-01
Selecting an effective dose of sedative drugs in combined upper and lower gastrointestinal endoscopy is complicated by varying degrees of pain stimulation. We tested the ability of 5 response surface models to predict depth of sedation after administration of midazolam and alfentanil in this complex model. The procedure was divided into 3 phases: esophagogastroduodenoscopy (EGD), colonoscopy, and the time interval between the 2 (intersession). The depth of sedation in 33 adult patients was monitored by Observer Assessment of Alertness/Scores. A total of 218 combinations of midazolam and alfentanil effect-site concentrations derived from pharmacokinetic models were used to test 5 response surface models in each of the 3 phases of endoscopy. Model fit was evaluated with objective function value, corrected Akaike Information Criterion (AICc), and Spearman ranked correlation. A model was arbitrarily defined as accurate if the predicted probability is <0.5 from the observed response. The effect-site concentrations tested ranged from 1 to 76 ng/mL and from 5 to 80 ng/mL for midazolam and alfentanil, respectively. Midazolam and alfentanil had synergistic effects in colonoscopy and EGD, but additivity was observed in the intersession group. Adequate prediction rates were 84% to 85% in the intersession group, 84% to 88% during colonoscopy, and 82% to 87% during EGD. The reduced Greco and Fixed alfentanil concentration required for 50% of the patients to achieve targeted response Hierarchy models performed better with comparable predictive strength. The reduced Greco model had the lowest AICc with strong correlation in all 3 phases of endoscopy. Dynamic, rather than fixed, γ and γalf in the Hierarchy model improved model fit. The reduced Greco model had the lowest objective function value and AICc and thus the best fit. This model was reliable with acceptable predictive ability based on adequate clinical correlation. We suggest that this model has practical clinical value
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…
Comparison of 1-step and 2-step methods of fitting microbiological models.
Jewell, Keith
2012-11-15
Previous conclusions that a 1-step fitting method gives more precise coefficients than the traditional 2-step method are confirmed by application to three different data sets. It is also shown that, in comparison to 2-step fits, the 1-step method gives better fits to the data (often substantially) with directly interpretable regression diagnostics and standard errors. The improvement is greatest at extremes of environmental conditions and it is shown that 1-step fits can indicate inappropriate functional forms when 2-step fits do not. 1-step fits are better at estimating primary parameters (e.g. lag, growth rate) as well as concentrations, and are much more data efficient, allowing the construction of more robust models on smaller data sets. The 1-step method can be straightforwardly applied to any data set for which the 2-step method can be used and additionally to some data sets where the 2-step method fails. A 2-step approach is appropriate for visual assessment in the early stages of model development, and may be a convenient way to generate starting values for a 1-step fit, but the 1-step approach should be used for any quantitative assessment. Copyright © 2012 Elsevier B.V. All rights reserved.
Broadband distortion modeling in Lyman-α forest BAO fitting
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blomqvist, Michael; Kirkby, David; Margala, Daniel, E-mail: cblomqvi@uci.edu, E-mail: dkirkby@uci.edu, E-mail: dmargala@uci.edu
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 amore » 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.« less
Mobile computing acceptance factors in the healthcare industry: a structural equation model.
Wu, Jen-Her; Wang, Shu-Ching; Lin, Li-Min
2007-01-01
This paper presents a revised technology acceptance model to examine what determines mobile healthcare systems (MHS) acceptance by healthcare professionals. Conformation factor analysis was performed to test the reliability and validity of the measurement model. The structural equation modeling technique was used to evaluate the causal model. The results indicated that compatibility, perceived usefulness and perceived ease of use significantly affected healthcare professional behavioral intent. MHS self-efficacy had strong indirect impact on healthcare professional behavioral intent through the mediators of perceived usefulness and perceived ease of use. Yet, the hypotheses for technical support and training effects on the perceived usefulness and perceived ease of use were not supported. This paper provides initial insights into factors that are likely to be significant antecedents of planning and implementing mobile healthcare to enhance professionals' MHS acceptance. The proposed model variables explained 70% of the variance in behavioral intention to use MHS; further study is needed to explore extra significant antecedents of new IT/IS acceptance for mobile healthcare. Such as privacy and security issue, system and information quality, limitations of mobile devices; the above may be other interesting factors for implementing mobile healthcare and could be conducted by qualitative research.
Pines, Heather A; Gorbach, Pamina M; Weiss, Robert E; Hess, Kristen; Murphy, Ryan; Saunders, Terry; Brown, Joelle; Anton, Peter A; Cranston, Ross D
2013-03-01
We assessed the acceptability of three of over-the-counter products representative of potential rectal microbicide (RM) delivery systems. From 2009 to 2010, 117 HIV-uninfected males (79 %) and females (21 %) who engage in receptive anal intercourse participated in a 6-week randomized crossover acceptability trial. Participants received each of three products (enema, lubricant-filled applicator, suppository) every 2 weeks in a randomized sequence. CASI and T-ACASI scales assessed product acceptability via Likert responses. Factor analysis was used to identify underlying factors measured by each scale. Random effects models were fit to examine age and gender effects on product acceptability. Three underlying factors were identified: Satisfaction with Product Use, Sexual Pleasure, and Ease of Product Use. For acceptability, the applicator ranked highest; however, differences between product acceptability scores were greatest among females and younger participants. These findings indicate that RM delivery systems impact their acceptability and should be considered early in RM development to enhance potential use.
Gorbach, Pamina M.; Weiss, Robert E.; Hess, Kristen; Murphy, Ryan; Saunders, Terry; Brown, Joelle; Anton, Peter A.; Cranston, Ross D.
2012-01-01
We assessed the acceptability of three of over-the-counter products representative of potential rectal microbicide (RM) delivery systems. From 2009 to 2010, 117 HIV-uninfected males (79 %) and females (21 %) who engage in receptive anal intercourse participated in a 6-week randomized crossover acceptability trial. Participants received each of three products (enema, lubricant-filled applicator, suppository) every 2 weeks in a randomized sequence. CASI and T-ACASI scales assessed product acceptability via Likert responses. Factor analysis was used to identify underlying factors measured by each scale. Random effects models were fit to examine age and gender effects on product acceptability. Three underlying factors were identified: Satisfaction with Product Use, Sexual Pleasure, and Ease of Product Use. For acceptability, the applicator ranked highest; however, differences between product acceptability scores were greatest among females and younger participants. These findings indicate that RM delivery systems impact their acceptability and should be considered early in RM development to enhance potential use. PMID:23114512
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.
More Sophisticated Fits of the Oribts of Haumea's Interacting Moons
NASA Astrophysics Data System (ADS)
Oldroyd, William Jared; Ragozzine, Darin; Porter, Simon
2018-04-01
Since the discovery of Haumea's moons, it has been a challenge to model the orbits of its moons, Hi’iaka and Namaka. With many precision HST observations, Ragozzine & Brown 2009 succeeded in calculating a three-point mass model which was essential because Keplerian orbits were not a statistically acceptable fit. New data obtained in 2010 could be fit by adding a J2 and spin pole to Haumea, but new data from 2015 was far from the predicted locations, even after an extensive exploration using Bayesian Markov Chain Monte Carlo methods (using emcee). Here we report on continued investigations as to why our model cannot fit the full 10-year baseline of data. We note that by ignoring Haumea and instead examining the relative motion of the two moons in the Hi’iaka centered frame leads to adequate fits for the data. This suggests there are additional parameters connected to Haumea that will be required in a full model. These parameters are potentially related to photocenter-barycenter shifts which could be significant enough to affect the fitting process; these are unlikely to be caused by the newly discovered ring (Ortiz et al. 2017) or by unknown satellites (Burkhart et al. 2016). Additionally, we have developed a new SPIN+N-bodY integrator called SPINNY that self-consistently calculates the interactions between n-quadrupoles and is designed to test the importance of other possible effects (Haumea C22, satellite torques on the spin-pole, Sun, etc.) on our astrometric fits. By correctly determining the orbit of Haumea’s satellites we develop a better understanding of the physical properties of each of the objects with implications for the formation of Haumea, its moons, and its collisional family.
Jason B. Fellman; Mathew P. Miller; Rose M. Cory; David V. D' Amore; Dan White
2009-01-01
We evaluated whether fitting fluorescence excitation-emission matrices (EEMs) to a previously validated PARAFAC model is an acceptable alternative to building an original model. To do this, we built a l0-component model using 307 EEMscollected from southeast Alaskan soil and streamwater. All 307 EEMs were then fit to the existing model (CM) presented in Cory and...
A Person Fit Test for IRT Models for Polytomous Items
ERIC Educational Resources Information Center
Glas, C. A. W.; Dagohoy, Anna Villa T.
2007-01-01
A person fit test based on the Lagrange multiplier test is presented for three item response theory models for polytomous items: the generalized partial credit model, the sequential model, and the graded response model. The test can also be used in the framework of multidimensional ability parameters. It is shown that the Lagrange multiplier…
Limited-information goodness-of-fit testing of diagnostic classification item response models.
Hansen, Mark; Cai, Li; Monroe, Scott; Li, Zhen
2016-11-01
Despite the growing popularity of diagnostic classification models (e.g., Rupp et al., 2010, Diagnostic measurement: theory, methods, and applications, Guilford Press, New York, NY) in educational and psychological measurement, methods for testing their absolute goodness of fit to real data remain relatively underdeveloped. For tests of reasonable length and for realistic sample size, full-information test statistics such as Pearson's X 2 and the likelihood ratio statistic G 2 suffer from sparseness in the underlying contingency table from which they are computed. Recently, limited-information fit statistics such as Maydeu-Olivares and Joe's (2006, Psychometrika, 71, 713) M 2 have been found to be quite useful in testing the overall goodness of fit of item response theory models. In this study, we applied Maydeu-Olivares and Joe's (2006, Psychometrika, 71, 713) M 2 statistic to diagnostic classification models. Through a series of simulation studies, we found that M 2 is well calibrated across a wide range of diagnostic model structures and was sensitive to certain misspecifications of the item model (e.g., fitting disjunctive models to data generated according to a conjunctive model), errors in the Q-matrix (adding or omitting paths, omitting a latent variable), and violations of local item independence due to unmodelled testlet effects. On the other hand, M 2 was largely insensitive to misspecifications in the distribution of higher-order latent dimensions and to the specification of an extraneous attribute. To complement the analyses of the overall model goodness of fit using M 2 , we investigated the utility of the Chen and Thissen (1997, J. Educ. Behav. Stat., 22, 265) local dependence statistic XLD2 for characterizing sources of misfit, an important aspect of model appraisal often overlooked in favour of overall statements. The XLD2 statistic was found to be slightly conservative (with Type I error rates consistently below the nominal level) but still useful
An acceptance model for smart glasses based tourism augmented reality
NASA Astrophysics Data System (ADS)
Obeidy, Waqas Khalid; Arshad, Haslina; Huang, Jiung Yao
2017-10-01
Recent mobile technologies have revolutionized the way people experience their environment. Although, there is only limited research on users' acceptance of AR in the cultural tourism context, previous researchers have explored the opportunities of using augmented reality (AR) in order to enhance user experience. Recent AR research lack works that integrates dimensions which are specific to cultural tourism and smart glass specific context. Hence, this work proposes an AR acceptance model in the context of cultural heritage tourism and smart glasses capable of performing augmented reality. Therefore, in this paper we aim to present an AR acceptance model to understand the AR usage behavior and visiting intention for tourists who use Smart Glass based AR at UNESCO cultural heritage destinations in Malaysia. Furthermore, this paper identifies information quality, technology readiness, visual appeal, and facilitating conditions as external variables and key factors influencing visitors' beliefs, attitudes and usage intention.
TransFit: Finite element analysis data fitting software
NASA Technical Reports Server (NTRS)
Freeman, Mark
1993-01-01
The Advanced X-Ray Astrophysics Facility (AXAF) mission support team has made extensive use of geometric ray tracing to analyze the performance of AXAF developmental and flight optics. One important aspect of this performance modeling is the incorporation of finite element analysis (FEA) data into the surface deformations of the optical elements. TransFit is software designed for the fitting of FEA data of Wolter I optical surface distortions with a continuous surface description which can then be used by SAO's analytic ray tracing software, currently OSAC (Optical Surface Analysis Code). The improved capabilities of Transfit over previous methods include bicubic spline fitting of FEA data to accommodate higher spatial frequency distortions, fitted data visualization for assessing the quality of fit, the ability to accommodate input data from three FEA codes plus other standard formats, and options for alignment of the model coordinate system with the ray trace coordinate system. TransFit uses the AnswerGarden graphical user interface (GUI) to edit input parameters and then access routines written in PV-WAVE, C, and FORTRAN to allow the user to interactively create, evaluate, and modify the fit. The topics covered include an introduction to TransFit: requirements, designs philosophy, and implementation; design specifics: modules, parameters, fitting algorithms, and data displays; a procedural example; verification of performance; future work; and appendices on online help and ray trace results of the verification section.
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.
Using the Flipchem Photochemistry Model When Fitting Incoherent Scatter Radar Data
NASA Astrophysics Data System (ADS)
Reimer, A. S.; Varney, R. H.
2017-12-01
The North face Resolute Bay Incoherent Scatter Radar (RISR-N) routinely images the dynamics of the polar ionosphere, providing measurements of the plasma density, electron temperature, ion temperature, and line of sight velocity with seconds to minutes time resolution. RISR-N does not directly measure ionospheric parameters, but backscattered signals, recording them as voltage samples. Using signal processing techniques, radar autocorrelation functions (ACF) are estimated from the voltage samples. A model of the signal ACF is then fitted to the ACF using non-linear least-squares techniques to obtain the best-fit ionospheric parameters. The signal model, and therefore the fitted parameters, depend on the ionospheric ion composition that is used [e.g. Zettergren et. al. (2010), Zou et. al. (2017)].The software used to process RISR-N ACF data includes the "flipchem" model, which is an ion photochemistry model developed by Richards [2011] that was adapted from the Field LineInterhemispheric Plasma (FLIP) model. Flipchem requires neutral densities, neutral temperatures, electron density, ion temperature, electron temperature, solar zenith angle, and F10.7 as inputs to compute ion densities, which are input to the signal model. A description of how the flipchem model is used in RISR-N fitting software will be presented. Additionally, a statistical comparison of the fitted electron density, ion temperature, electron temperature, and velocity obtained using a flipchem ionosphere, a pure O+ ionosphere, and a Chapman O+ ionosphere will be presented. The comparison covers nearly two years of RISR-N data (April 2015 - December 2016). Richards, P. G. (2011), Reexamination of ionospheric photochemistry, J. Geophys. Res., 116, A08307, doi:10.1029/2011JA016613.Zettergren, M., Semeter, J., Burnett, B., Oliver, W., Heinselman, C., Blelly, P.-L., and Diaz, M.: Dynamic variability in F-region ionospheric composition at auroral arc boundaries, Ann. Geophys., 28, 651-664, https
A Case-Based Exploration of Task/Technology Fit in a Knowledge Management Context
2008-03-01
have a difficult time articulating to others. Researchers who subscribe to the constructionist perspective view knowledge as an inherently social ...Acceptance Model With Task-Technology Fit Constructs. Information & Management, 36, 9-21. Dooley, D. (2001). Social Research Methods (4th ed.). Upper...L. (2006). Social Research Methods : Qualitative and Quantitative Approaches (6 ed.). Boston: Pearson Education, Inc. Nonaka, I. (1994). A Dynamic
Twitter classification model: the ABC of two million fitness tweets.
Vickey, Theodore A; Ginis, Kathleen Martin; Dabrowski, Maciej
2013-09-01
The purpose of this project was to design and test data collection and management tools that can be used to study the use of mobile fitness applications and social networking within the context of physical activity. This project was conducted over a 6-month period and involved collecting publically shared Twitter data from five mobile fitness apps (Nike+, RunKeeper, MyFitnessPal, Endomondo, and dailymile). During that time, over 2.8 million tweets were collected, processed, and categorized using an online tweet collection application and a customized JavaScript. Using the grounded theory, a classification model was developed to categorize and understand the types of information being shared by application users. Our data show that by tracking mobile fitness app hashtags, a wealth of information can be gathered to include but not limited to daily use patterns, exercise frequency, location-based workouts, and overall workout sentiment.
Is High-Intensity Functional Training (HIFT)/CrossFit Safe for Military Fitness Training?
Poston, Walker S C; Haddock, Christopher K; Heinrich, Katie M; Jahnke, Sara A; Jitnarin, Nattinee; Batchelor, David B
2016-07-01
High-intensity functional training (HIFT) is a promising fitness paradigm that gained popularity among military populations. Rather than biasing workouts toward maximizing fitness domains such as aerobic endurance, HIFT workouts are designed to promote general physical preparedness. HIFT programs have proliferated as a result of concerns about the relevance of traditional physical training (PT), which historically focused on aerobic condition via running. Other concerns about traditional PT include: (1) the relevance of service fitness tests given current combat demands, (2) the perception that military PT is geared toward passing service fitness tests, and (3) that training for combat requires more than just aerobic endurance. Despite its' popularity in the military, concerns have been raised about HIFT's injury potential, leading to some approaches being labeled as "extreme conditioning programs" by several military and civilian experts. Given HIFT programs' popularity in the military and concerns about injury, a review of data on HIFT injury potential is needed to inform military policy. The purpose of this review is to: (1) provide an overview of scientific methods used to appropriately compare injury rates among fitness activities and (2) evaluate scientific data regarding HIFT injury risk compared to traditional military PT and other accepted fitness activities. Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.
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…
NASA Astrophysics Data System (ADS)
Siswanto, T.; Shofiati, R.; Hartini, H.
2018-01-01
www.mitigasi-bencana.com as a knowledge management website created based on survey results in April-July 2014 in East Java and Central Java provinces, indicates a gap between the expectations and reality that exist in the services provided by the regional disaster management agency. Based on condition analysis, the gaps that occur can be reduced if the community has the understanding and knowledge of adequate disaster mitigation. The problem that arises later is whether the chosen technology solution is appropriate and acceptable to the public? The methodology used in this study using the Technology Acceptance Model development is the Unified Theory of Acceptance and Utilization of Technology (UTAUT). Feedback obtained from respondents KarangTaruna youth SelogedongBantul, www.mitigasi-bencana.com can be accepted by the respondents, but from processed data is obtained only UTAUT hypotheses on the relationship dimension eligible for Social Expectancy on the Attitude toward technology, which means the higher the perception of the Social Expectancy, the higher the perception of the Attitude toward technology. Because www.mitigasi-bencana.com is new socialized so that society still need time to explore content information and knowledge contained therein. To be accepted by user, a knowledge management application must prepare various aspects of Performance Expectancy, Effort Expectancy, Social Factors, Facilitating Conditions and Attitude.
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…
Robustness of fit indices to outliers and leverage observations in structural equation modeling.
Yuan, Ke-Hai; Zhong, Xiaoling
2013-06-01
Normal-distribution-based maximum likelihood (NML) is the most widely used method in structural equation modeling (SEM), although practical data tend to be nonnormally distributed. The effect of nonnormally distributed data or data contamination on the normal-distribution-based likelihood ratio (LR) statistic is well understood due to many analytical and empirical studies. In SEM, fit indices are used as widely as the LR statistic. In addition to NML, robust procedures have been developed for more efficient and less biased parameter estimates with practical data. This article studies the effect of outliers and leverage observations on fit indices following NML and two robust methods. Analysis and empirical results indicate that good leverage observations following NML and one of the robust methods lead most fit indices to give more support to the substantive model. While outliers tend to make a good model superficially bad according to many fit indices following NML, they have little effect on those following the two robust procedures. Implications of the results to data analysis are discussed, and recommendations are provided regarding the use of estimation methods and interpretation of fit indices. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
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…
Electronic health record acceptance by physicians: testing an integrated theoretical model.
Gagnon, Marie-Pierre; Ghandour, El Kebir; Talla, Pascaline Kengne; Simonyan, David; Godin, Gaston; Labrecque, Michel; Ouimet, Mathieu; Rousseau, Michel
2014-04-01
Several countries are in the process of implementing an Electronic Health Record (EHR), but limited physicians' acceptance of this technology presents a serious threat to its successful implementation. The aim of this study was to identify the main determinants of physician acceptance of EHR in a sample of general practitioners and specialists of the Province of Quebec (Canada). We sent an electronic questionnaire to physician members of the Quebec Medical Association. We tested four theoretical models (Technology acceptance model (TAM), Extended TAM, Psychosocial Model, and Integrated Model) using path analysis and multiple linear regression analysis in order to identify the main determinants of physicians' intention to use the EHR. We evaluated the modifying effect of sociodemographic characteristics using multi-group analysis of structural weights invariance. A total of 157 questionnaires were returned. The four models performed well and explained between 44% and 55% of the variance in physicians' intention to use the EHR. The Integrated model performed the best and showed that perceived ease of use, professional norm, social norm, and demonstrability of the results are the strongest predictors of physicians' intention to use the EHR. Age, gender, previous experience and specialty modified the association between those determinants and intention. The proposed integrated theoretical model is useful in identifying which factors could motivate physicians from different backgrounds to use the EHR. Physicians who perceive the EHR to be easy to use, coherent with their professional norms, supported by their peers and patients, and able to demonstrate tangible results are more likely to accept this technology. Age, gender, specialty and experience should also be taken into account when developing EHR implementation strategies targeting physicians. Copyright © 2013 Elsevier Inc. All rights reserved.
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…
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.
Irvine, Michael A; Hollingsworth, T Déirdre
2018-05-26
Fitting complex models to epidemiological data is a challenging problem: methodologies can be inaccessible to all but specialists, there may be challenges in adequately describing uncertainty in model fitting, the complex models may take a long time to run, and it can be difficult to fully capture the heterogeneity in the data. We develop an adaptive approximate Bayesian computation scheme to fit a variety of epidemiologically relevant data with minimal hyper-parameter tuning by using an adaptive tolerance scheme. We implement a novel kernel density estimation scheme to capture both dispersed and multi-dimensional data, and directly compare this technique to standard Bayesian approaches. We then apply the procedure to a complex individual-based simulation of lymphatic filariasis, a human parasitic disease. The procedure and examples are released alongside this article as an open access library, with examples to aid researchers to rapidly fit models to data. This demonstrates that an adaptive ABC scheme with a general summary and distance metric is capable of performing model fitting for a variety of epidemiological data. It also does not require significant theoretical background to use and can be made accessible to the diverse epidemiological research community. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
The best-fit universe. [cosmological models
NASA Technical Reports Server (NTRS)
Turner, Michael S.
1991-01-01
Inflation provides very strong motivation for a flat Universe, Harrison-Zel'dovich (constant-curvature) perturbations, and cold dark matter. However, there are a number of cosmological observations that conflict with the predictions of the simplest such model: one with zero cosmological constant. They include the age of the Universe, dynamical determinations of Omega, galaxy-number counts, and the apparent abundance of large-scale structure in the Universe. While the discrepancies are not yet serious enough to rule out the simplest and most well motivated model, the current data point to a best-fit model with the following parameters: Omega(sub B) approximately equal to 0.03, Omega(sub CDM) approximately equal to 0.17, Omega(sub Lambda) approximately equal to 0.8, and H(sub 0) approximately equal to 70 km/(sec x Mpc) which improves significantly the concordance with observations. While there is no good reason to expect such a value for the cosmological constant, there is no physical principle that would rule out such.
Model-independent partial wave analysis using a massively-parallel fitting framework
NASA Astrophysics Data System (ADS)
Sun, L.; Aoude, R.; dos Reis, A. C.; Sokoloff, M.
2017-10-01
The functionality of GooFit, a GPU-friendly framework for doing maximum-likelihood fits, has been extended to extract model-independent {\\mathscr{S}}-wave amplitudes in three-body decays such as D + → h + h + h -. A full amplitude analysis is done where the magnitudes and phases of the {\\mathscr{S}}-wave amplitudes are anchored at a finite number of m 2(h + h -) control points, and a cubic spline is used to interpolate between these points. The amplitudes for {\\mathscr{P}}-wave and {\\mathscr{D}}-wave intermediate states are modeled as spin-dependent Breit-Wigner resonances. GooFit uses the Thrust library, with a CUDA backend for NVIDIA GPUs and an OpenMP backend for threads with conventional CPUs. Performance on a variety of platforms is compared. Executing on systems with GPUs is typically a few hundred times faster than executing the same algorithm on a single CPU.
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.
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.
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
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):…
[Study on the effect of different impression methods on the marginal fit of all-ceramic crowns].
Zhan, Lilin; Zeng, Liwei; Chen, Ping; Liao, Lan; Li, Shiyue; Liu, Renying
2015-08-01
To investigate the effect of three different impression methods on the marginal fit of all-ceramic crowns. The three methods include scanning silicone rubber impression, cast models, and direct optical impression. The polymethyl methacrylate (PMMA) material of a mandibular first molar in standard model was prepared with 16 models duplicated. The all-ceramic crowns were prepared using three different impression methods. Accurate impressions were made using silicone rubber, and the cast models were obtained. The PMMA models, silicone rubber impressions, and cast models were scanned, and digital models of three groups were obtained to produce 48 zirconia all-ceramic crowns with computer aided design/computer aided manufacture. The marginal fit of these groups was measured by silicone rubber gap impression. Statistical analysis was performed with SPSS 17.0 software. The marginal fit of direct optical impression groups, silicone rubber impression groups, cast model groups was (69.18±9.47), (81.04±10.88), (84.42±9.96) µm. A significant difference was observed in the marginal fit of the direct optical impression groups and the other groups (P<0.05). No statistically significant difference was observed in the marginal fit of the silicone rubber impression groups and the cast model groups (P>0.05). All marginal measurement sites are clinically acceptable by the three different impression scanning methods. The silicone rubber impression scanning method can be used for all-ceramic restorations.
Fitting direct covariance structures by the MSTRUCT modeling language of the CALIS procedure.
Yung, Yiu-Fai; Browne, Michael W; Zhang, Wei
2015-02-01
This paper demonstrates the usefulness and flexibility of the general structural equation modelling (SEM) approach to fitting direct covariance patterns or structures (as opposed to fitting implied covariance structures from functional relationships among variables). In particular, the MSTRUCT modelling language (or syntax) of the CALIS procedure (SAS/STAT version 9.22 or later: SAS Institute, 2010) is used to illustrate the SEM approach. The MSTRUCT modelling language supports a direct covariance pattern specification of each covariance element. It also supports the input of additional independent and dependent parameters. Model tests, fit statistics, estimates, and their standard errors are then produced under the general SEM framework. By using numerical and computational examples, the following tests of basic covariance patterns are illustrated: sphericity, compound symmetry, and multiple-group covariance patterns. Specification and testing of two complex correlation structures, the circumplex pattern and the composite direct product models with or without composite errors and scales, are also illustrated by the MSTRUCT syntax. It is concluded that the SEM approach offers a general and flexible modelling of direct covariance and correlation patterns. In conjunction with the use of SAS macros, the MSTRUCT syntax provides an easy-to-use interface for specifying and fitting complex covariance and correlation structures, even when the number of variables or parameters becomes large. © 2014 The British Psychological Society.
Is High Intensity Functional Training (HIFT)/CrossFit® Safe for Military Fitness Training?
Poston, Walker S.C.; Haddock, Christopher K.; Heinrich, Katie M.; Jahnke, Sara A.; Jitnarin, Nattinee; Batchelor, David B.
2016-01-01
High-intensity functional training (HIFT) is a promising fitness paradigm that gained popularity among military populations. Rather than biasing workouts toward maximizing fitness domains such as aerobic endurance, HIFT workouts are designed to promote general physical preparedness. HIFT programs have proliferated due to concerns about the relevance of traditional physical training (PT), which historically focused on aerobic condition via running. Other concerns about traditional PT include: 1) the relevance of service fitness tests given current combat demands; 2) the perception that military PT is geared toward passing service fitness tests; and 3) that training for combat requires more than just aerobic endurance. Despite its’ popularity in the military, concerns have been raised about HIFT’s injury potential, leading to some approaches being labeled as “extreme conditioning programs” by several military and civilian experts. Given HIFT programs’ popularity in the military and concerns about injury, a review of data on HIFT injury potential is needed to inform military policy. The purpose of this review is to: 1) provide an overview of scientific methods used to appropriately compare injury rates among fitness activities; and 2) evaluate scientific data regarding HIFT injury risk compared to traditional military PT and other accepted fitness activities PMID:27391615
Estimation of retinal vessel caliber using model fitting and random forests
NASA Astrophysics Data System (ADS)
Araújo, Teresa; Mendonça, Ana Maria; Campilho, Aurélio
2017-03-01
Retinal vessel caliber changes are associated with several major diseases, such as diabetes and hypertension. These caliber changes can be evaluated using eye fundus images. However, the clinical assessment is tiresome and prone to errors, motivating the development of automatic methods. An automatic method based on vessel crosssection intensity profile model fitting for the estimation of vessel caliber in retinal images is herein proposed. First, vessels are segmented from the image, vessel centerlines are detected and individual segments are extracted and smoothed. Intensity profiles are extracted perpendicularly to the vessel, and the profile lengths are determined. Then, model fitting is applied to the smoothed profiles. A novel parametric model (DoG-L7) is used, consisting on a Difference-of-Gaussians multiplied by a line which is able to describe profile asymmetry. Finally, the parameters of the best-fit model are used for determining the vessel width through regression using ensembles of bagged regression trees with random sampling of the predictors (random forests). The method is evaluated on the REVIEW public dataset. A precision close to the observers is achieved, outperforming other state-of-the-art methods. The method is robust and reliable for width estimation in images with pathologies and artifacts, with performance independent of the range of diameters.
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
Person-Fit and the Rasch Model, with an Application to Knowledge of Logical Quantors.
ERIC Educational Resources Information Center
Molenaar, Ivo W.; Hoijtink, Herbert
1996-01-01
Some specific person-fit results for the Rasch model are presented, followed by an application to a test measuring knowledge of reasoning with logical quantors. Some issues are relevant to all attempts to use person-fit statistics in research, but the special role of the Rasch model is highlighted. (SLD)
Some Statistics for Assessing Person-Fit Based on Continuous-Response Models
ERIC Educational Resources Information Center
Ferrando, Pere Joan
2010-01-01
This article proposes several statistics for assessing individual fit based on two unidimensional models for continuous responses: linear factor analysis and Samejima's continuous response model. Both models are approached using a common framework based on underlying response variables and are formulated at the individual level as fixed regression…
46 CFR 56.15-1 - Pipe joining fittings.
Code of Federal Regulations, 2013 CFR
2013-10-01
... subpart 50.25 of this subchapter are acceptable for use in piping systems. (b) Threaded, flanged, socket-welding, buttwelding, and socket-brazing pipe joining fittings, made in accordance with the applicable...
46 CFR 56.15-1 - Pipe joining fittings.
Code of Federal Regulations, 2011 CFR
2011-10-01
... subpart 50.25 of this subchapter are acceptable for use in piping systems. (b) Threaded, flanged, socket-welding, buttwelding, and socket-brazing pipe joining fittings, made in accordance with the applicable...
46 CFR 56.15-1 - Pipe joining fittings.
Code of Federal Regulations, 2014 CFR
2014-10-01
... subpart 50.25 of this subchapter are acceptable for use in piping systems. (b) Threaded, flanged, socket-welding, buttwelding, and socket-brazing pipe joining fittings, made in accordance with the applicable...
46 CFR 56.15-1 - Pipe joining fittings.
Code of Federal Regulations, 2012 CFR
2012-10-01
... subpart 50.25 of this subchapter are acceptable for use in piping systems. (b) Threaded, flanged, socket-welding, buttwelding, and socket-brazing pipe joining fittings, made in accordance with the applicable...
Calabrò, Paolo S; Orsi, Sirio; Gentili, Emiliano; Carlo, Meoni
2011-12-01
This paper presents the results of the modelling of the biogas extraction in a full-scale Italian landfill by the USEPA LandGEM model and the Andreottola-Cossu approach. The landfill chosen for this research ('Il Fossetto' plant, Monsummano Terme, Italy) had accepted mixed municipal raw waste for about 15 years. In the year 2003 a mechanical biological treatment (MBT) was implemented and starting from the end of the year 2006, the recirculation in the landfill of the concentrated leachate coming from the internal membrane leachate treatment plant was put into practice. The USEPA LandGEM model and the Andreottola-Cossu approach were chosen since they require only input data routinely acquired during landfill management (waste amount and composition) and allow a simplified calibration, therefore they are potentially useful for practical purposes such as landfill gas management. The results given by the models are compared with measured data and analysed in order to verify the impact of MBT on biogas production; moreover, the possible effects of the recirculation of the concentrated leachate are discussed. The results clearly show how both models can adequately fit measured data even after MBT implementation. Model performance was significantly reduced for the period after the beginning of recirculation of concentrated leachate when the probable inhibition of methane production, due to the competition between methanogens and sulfate-reducing bacteria, significantly influenced the biogas production and composition.
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.
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. PMID:24723812
van Baalen, Sophie; Leemans, Alexander; Dik, Pieter; Lilien, Marc R; Ten Haken, Bennie; Froeling, Martijn
2017-07-01
To evaluate if a three-component model correctly describes the diffusion signal in the kidney and whether it can provide complementary anatomical or physiological information about the underlying tissue. Ten healthy volunteers were examined at 3T, with T 2 -weighted imaging, diffusion tensor imaging (DTI), and intravoxel incoherent motion (IVIM). Diffusion tensor parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squares fitting of the DTI data and mono-, bi-, and triexponential fit parameters (D 1 , D 2 , D 3 , f fast2 , f fast3 , and f interm ) using a nonlinear fit of the IVIM data. Average parameters were calculated for three regions of interest (ROIs) (cortex, medulla, and rest) and from fiber tractography. Goodness of fit was assessed with adjusted R 2 ( Radj2) and the Shapiro-Wilk test was used to test residuals for normality. Maps of diffusion parameters were also visually compared. Fitting the diffusion signal was feasible for all models. The three-component model was best able to describe fast signal decay at low b values (b < 50), which was most apparent in Radj2 of the ROI containing high diffusion signals (ROI rest ), which was 0.42 ± 0.14, 0.61 ± 0.11, 0.77 ± 0.09, and 0.81 ± 0.08 for DTI, one-, two-, and three-component models, respectively, and in visual comparison of the fitted and measured S 0 . None of the models showed significant differences (P > 0.05) between the diffusion constant of the medulla and cortex, whereas the f fast component of the two and three-component models were significantly different (P < 0.001). Triexponential fitting is feasible for the diffusion signal in the kidney, and provides additional information. 2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:228-239. © 2016 The Authors Journal of Magnetic Resonance Imaging published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
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.
ERIC Educational Resources Information Center
Tarhini, Ali; Hone, Kate; Liu, Xiaohui; Tarhini, Takwa
2017-01-01
In this study, we examine the effects of individual-level culture on the adoption and acceptance of e-learning tools by students in Lebanon using a theoretical framework based on the Technology Acceptance Model (TAM). To overcome possible limitations of using TAM in developing countries, we extend TAM to include "subjective norms" (SN)…
Haslinger, Robert; Pipa, Gordon; Brown, Emery
2010-10-01
One approach for understanding the encoding of information by spike trains is to fit statistical models and then test their goodness of fit. The time-rescaling theorem provides a goodness-of-fit test consistent with the point process nature of spike trains. The interspike intervals (ISIs) are rescaled (as a function of the model's spike probability) to be independent and exponentially distributed if the model is accurate. A Kolmogorov-Smirnov (KS) test between the rescaled ISIs and the exponential distribution is then used to check goodness of fit. This rescaling relies on assumptions of continuously defined time and instantaneous events. However, spikes have finite width, and statistical models of spike trains almost always discretize time into bins. Here we demonstrate that finite temporal resolution of discrete time models prevents their rescaled ISIs from being exponentially distributed. Poor goodness of fit may be erroneously indicated even if the model is exactly correct. We present two adaptations of the time-rescaling theorem to discrete time models. In the first we propose that instead of assuming the rescaled times to be exponential, the reference distribution be estimated through direct simulation by the fitted model. In the second, we prove a discrete time version of the time-rescaling theorem that analytically corrects for the effects of finite resolution. This allows us to define a rescaled time that is exponentially distributed, even at arbitrary temporal discretizations. We demonstrate the efficacy of both techniques by fitting generalized linear models to both simulated spike trains and spike trains recorded experimentally in monkey V1 cortex. Both techniques give nearly identical results, reducing the false-positive rate of the KS test and greatly increasing the reliability of model evaluation based on the time-rescaling theorem.
Cross-national comparisons of college students' attitudes toward diet/fitness apps on smartphones.
Cho, Jaehee; Lee, H Erin; Quinlan, Margaret
2017-10-01
Based on the technology acceptance model (TAM), we explored the nationally-bounded roles of four predictors (subjective norms, entertainment, recordability, and networkability) in determining the TAM variables of perceived usefulness (PU), perceived ease of use (PEOU), and behavioral intention (BI) to use diet/fitness apps on smartphones. College students in the US and South Korea were invited to participate in a survey. We obtained 508 questionnaires (304 from the US and 204 from Korea). Data were analyzed mainly through path analysis. The four factors positively predicted the PU and PEOU of diet/fitness apps. While the effects of the predictors on the three TAM components were generally stronger among the US students than Korean students, the effect of subjective norms on the BI of diet/fitness apps was weaker among Korean students. Findings from the cross-national comparisons were helpful for thoroughly understanding the contextualized mechanisms involved in the adoption of diet/fitness apps.
Obtaining Predictions from Models Fit to Multiply Imputed Data
ERIC Educational Resources Information Center
Miles, Andrew
2016-01-01
Obtaining predictions from regression models fit to multiply imputed data can be challenging because treatments of multiple imputation seldom give clear guidance on how predictions can be calculated, and because available software often does not have built-in routines for performing the necessary calculations. This research note reviews how…
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…
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.…
Evaluation of marginal fit of two all-ceramic copings with two finish lines
Subasi, Gulce; Ozturk, Nilgun; Inan, Ozgur; Bozogullari, Nalan
2012-01-01
Objectives: This in-vitro study investigated the marginal fit of two all-ceramic copings with 2 finish line designs. Methods: Forty machined stainless steel molar die models with two different margin designs (chamfer and rounded shoulder) were prepared. A total of 40 standardized copings were fabricated and divided into 4 groups (n=10 for each finish line-coping material). Coping materials tested were IPS e.max Press and Zirkonzahn; luting agent was Variolink II. Marginal fit was evaluated after cementation with a stereomicroscope (Leica MZ16). Two-way analysis of variance and Tukey-HSD test were performed to assess the influence of each finish line design and ceramic type on the marginal fit of 2 all-ceramic copings (α =.05). Results: Two-way analysis of variance revealed no statistically significant differences for marginal fit relative to finish lines (P=.362) and ceramic types (P=.065). Conclusion: Within the limitations of this study, both types of all-ceramic copings demonstrated that the mean marginal fit was considered acceptable for clinical application (⩽120 μm). PMID:22509119
Acceptance and relationship context: a model of substance use disorder treatment outcome.
Gifford, Elizabeth V; Ritsher, Jennifer B; McKellar, John D; Moos, Rudolf H
2006-08-01
This study presented and tested a model of behavior change in long-term substance use disorder recovery, the acceptance and relationship context (ARC) model. The model specifies that acceptance-based behavior and constructive social relationships lead to recovery, and that treatment programs with supportive, involved relationships facilitate the development of these factors. This study used a prospective longitudinal naturalistic design and controlled for baseline levels of study variables. The model was tested on a sample of 2549 patients in 15 residential substance use disorder treatment programs. Acceptance-based responding (ABR), social relationship quality (SRQ), treatment program alliance (TPA) and substance use-related impairment were assessed using interviews and self-report questionnaires. TPA predicted ABR and SRQ and, in turn, ABR predicted better 2-year and 5-year treatment outcomes. The baseline-controlled model accounted for 41% of the variance in outcome at 2-year follow-up and 28% of the variance in outcome at 5-year follow-up. CONCLUSIONS Patients from treatment programs with an affiliative relationship network are more likely to respond adaptively to internal states associated previously with substance use, develop constructive social relationships and achieve long-term treatment benefits.
Fitting rainfall interception models to forest ecosystems of Mexico
NASA Astrophysics Data System (ADS)
Návar, José
2017-05-01
Models that accurately predict forest interception are essential both for water balance studies and for assessing watershed responses to changes in land use and the long-term climate variability. This paper compares the performance of four rainfall interception models-the sparse Gash (1995), Rutter et al. (1975), Liu (1997) and two new models (NvMxa and NvMxb)-using data from four spatially extensive, structurally diverse forest ecosystems in Mexico. Ninety-eight case studies measuring interception in tropical dry (25), arid/semi-arid (29), temperate (26), and tropical montane cloud forests (18) were compiled and analyzed. Coefficients derived from raw data or published statistical relationships were used as model input to evaluate multi-storm forest interception at the case study scale. On average empirical data showed that, tropical montane cloud, temperate, arid/semi-arid and tropical dry forests intercepted 14%, 18%, 22% and 26% of total precipitation, respectively. The models performed well in predicting interception, with mean deviations between measured and modeled interception as a function of total precipitation (ME) generally <5.8% and Nash-Sutcliffe efficiency E estimators >0.66. Model fitting precision was dependent on the forest ecosystem. Arid/semi-arid forests exhibited the smallest, while tropical montane cloud forest displayed the largest ME deviations. Improved agreement between measured and modeled data requires modification of in-storm evaporation rate in the Liu; the canopy storage in the sparse Gash model; and the throughfall coefficient in the Rutter and the NvMx models. This research concludes on recommending the wide application of rainfall interception models with some caution as they provide mixed results. The extensive forest interception data source, the fitting and testing of four models, the introduction of a new model, and the availability of coefficient values for all four forest ecosystems are an important source of information and
Zhu, Xiang; Zhang, Dianwen
2013-01-01
We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance of GPU-LMFit for the applications in superresolution localization microscopy and fluorescence lifetime imaging microscopy. PMID:24130785
Haslinger, Robert; Pipa, Gordon; Brown, Emery
2010-01-01
One approach for understanding the encoding of information by spike trains is to fit statistical models and then test their goodness of fit. The time rescaling theorem provides a goodness of fit test consistent with the point process nature of spike trains. The interspike intervals (ISIs) are rescaled (as a function of the model’s spike probability) to be independent and exponentially distributed if the model is accurate. A Kolmogorov Smirnov (KS) test between the rescaled ISIs and the exponential distribution is then used to check goodness of fit. This rescaling relies upon assumptions of continuously defined time and instantaneous events. However spikes have finite width and statistical models of spike trains almost always discretize time into bins. Here we demonstrate that finite temporal resolution of discrete time models prevents their rescaled ISIs from being exponentially distributed. Poor goodness of fit may be erroneously indicated even if the model is exactly correct. We present two adaptations of the time rescaling theorem to discrete time models. In the first we propose that instead of assuming the rescaled times to be exponential, the reference distribution be estimated through direct simulation by the fitted model. In the second, we prove a discrete time version of the time rescaling theorem which analytically corrects for the effects of finite resolution. This allows us to define a rescaled time which is exponentially distributed, even at arbitrary temporal discretizations. We demonstrate the efficacy of both techniques by fitting Generalized Linear Models (GLMs) to both simulated spike trains and spike trains recorded experimentally in monkey V1 cortex. Both techniques give nearly identical results, reducing the false positive rate of the KS test and greatly increasing the reliability of model evaluation based upon the time rescaling theorem. PMID:20608868
24 CFR 200.926c - Model code provisions for use in partially accepted code jurisdictions.
Code of Federal Regulations, 2010 CFR
2010-04-01
... Minimum Property Standards § 200.926c Model code provisions for use in partially accepted code... partially accepted, then the properties eligible for HUD benefits in that jurisdiction shall be constructed..., those portions of one of the model codes with which the property must comply. Schedule for Model Code...
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... partially accepted, then the properties eligible for HUD benefits in that jurisdiction shall be constructed..., those portions of one of the model codes with which the property must comply. Schedule for Model Code...
Fundamental Parameters Line Profile Fitting in Laboratory Diffractometers
Cheary, R. W.; Coelho, A. A.; Cline, J. P.
2004-01-01
The fundamental parameters approach to line profile fitting uses physically based models to generate the line profile shapes. Fundamental parameters profile fitting (FPPF) has been used to synthesize and fit data from both parallel beam and divergent beam diffractometers. The refined parameters are determined by the diffractometer configuration. In a divergent beam diffractometer these include the angular aperture of the divergence slit, the width and axial length of the receiving slit, the angular apertures of the axial Soller slits, the length and projected width of the x-ray source, the absorption coefficient and axial length of the sample. In a parallel beam system the principal parameters are the angular aperture of the equatorial analyser/Soller slits and the angular apertures of the axial Soller slits. The presence of a monochromator in the beam path is normally accommodated by modifying the wavelength spectrum and/or by changing one or more of the axial divergence parameters. Flat analyzer crystals have been incorporated into FPPF as a Lorentzian shaped angular acceptance function. One of the intrinsic benefits of the fundamental parameters approach is its adaptability any laboratory diffractometer. Good fits can normally be obtained over the whole 20 range without refinement using the known properties of the diffractometer, such as the slit sizes and diffractometer radius, and emission profile. PMID:27366594
2014-01-01
Background Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. Results The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input–output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard
10 CFR 26.111 - Checking the acceptability of the urine specimen.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 10 Energy 1 2010-01-01 2010-01-01 false Checking the acceptability of the urine specimen. 26.111 Section 26.111 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Collecting Specimens for Testing § 26.111 Checking the acceptability of the urine specimen. (a) Immediately after the donor...
10 CFR 26.111 - Checking the acceptability of the urine specimen.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 10 Energy 1 2011-01-01 2011-01-01 false Checking the acceptability of the urine specimen. 26.111 Section 26.111 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Collecting Specimens for Testing § 26.111 Checking the acceptability of the urine specimen. (a) Immediately after the donor...
Beglaryan, Mher; Petrosyan, Varduhi; Bunker, Edward
2017-06-01
In health care, information technologies (IT) hold a promise to harness an ever-increasing flow of health related information and bring significant benefits including improved quality of care, efficiency, and cost containment. One of the main tools for collecting and utilizing health data is the Electronic Health Record (EHR). EHRs implementation can face numerous barriers to acceptance including attitudes and perceptions of potential users, required effort attributed to their implementation and usage, and resistance to change. Various theories explicate different aspects of technology deployment, implementation, and acceptance. One of the common theories is the Technology Acceptance Model (TAM), which helps to study the implementation of different healthcare IT applications. The objectives of this study are: to understand the barriers of EHR implementation from the perspective of physicians; to identify major determinants of physicians' acceptance of technology; and develop a model that explains better how EHRs (and technologies in general) are accepted by physicians. The proposed model derives from a cross-sectional survey of physicians selected through multi-stage cluster sampling from the hospitals of Yerevan, Armenia. The study team designed the survey instrument based on a literature review on barriers of EHR implementation. The analysis employed exploratory structural equation modeling (ESEM) with a robust weighted least squares (WLSMV) estimator for categorical indicators. The analysis progressed in two steps: appraisal of the measurement model and testing of the structural model. The derived model identifies the following factors as direct determinants of behavioral intention to use a novel technology: projected collective usefulness; personal innovativeness; patient influence; and resistance to change. Other factors (e.g., organizational change, professional relationships, administrative monitoring, organizational support and computer anxiety) exert their
Wernke, Matthew M; Schroeder, Ryan M; Haynes, Michael L; Nolt, Lonnie L; Albury, Alexander W; Colvin, James M
2017-07-01
Objective: Prosthetic sockets are custom made for each amputee, yet there are no quantitative tools to determine the appropriateness of socket fit. Ensuring a proper socket fit can have significant effects on the health of residual limb soft tissues and overall function and acceptance of the prosthetic limb. Previous work found that elevated vacuum pressure data can detect movement between the residual limb and the prosthetic socket; however, the correlation between the two was specific to each user. The overall objective of this work is to determine the relationship between elevated vacuum pressure deviations and prosthetic socket fit. Approach: A tension compression machine was used to apply repeated controlled forces onto a residual limb model with sockets of different internal volume. Results: The vacuum pressure-displacement relationship was dependent on socket fit. The vacuum pressure data were sensitive enough to detect differences of 1.5% global volume and can likely detect differences even smaller. Limb motion was reduced as surface area of contact between the limb model and socket was maximized. Innovation: The results suggest that elevated vacuum pressure data provide information to quantify socket fit. Conclusions: This study provides evidence that the use of elevated vacuum pressure data may provide a method for prosthetists to quantify and monitor socket fit. Future studies should investigate the relationship between socket fit, limb motion, and limb health to define optimal socket fit parameters.
Cha, Jae Myung; Lee, Joung Il; Joo, Kwang Ro; Shin, Hyun Phil; Park, Jae Jun
2011-11-01
Colorectal cancer (CRC) screening with a fecal immunochemical test (FIT) reduces CRC mortality; however, the acceptance rate of a colonoscopy in patients with a positive FIT was not high. The aim of this study was therefore to determine whether a telephone reminder call could increase the acceptance rate of colonoscopy in patients with a positive FIT. We performed FITs for asymptomatic participants aged 50 years or older. For patients with a positive FIT, a colonoscopy was recommended via mailing notification only (control group) or via a telephone reminder call after mailing notification (intervention group). The calls informed patients about the significance of a positive FIT and encouraged a colonoscopy following positive FITs. The FIT results were positive in 90 of 8,318 patients who received FITs. Fifty patients were advised to receive colonoscopy via mailing notification only, and 40 patients were advised via both a telephone reminder call and a mailing notification. The acceptance rate of colonoscopy was significantly higher in the intervention group than in the control group (p = 0.038). The lesion-detection rate for an advanced neoplasia was also significantly higher in the intervention group than in the control group (p = 0.046). According to multivariate logistic regression analysis, a telephone reminder was a significant determinant of colonoscopy acceptance in patients with a positive FIT (OR 4.33; 95% CI, 1.19-15.75; p = 0.026). Telephone reminder calls in addition to mailing notification improved the acceptance rate of colonoscopy in patients with a positive FIT.
Finite element modelling of primary hip stem stability: the effect of interference fit.
Abdul-Kadir, Mohammed Rafiq; Hansen, Ulrich; Klabunde, Ralf; Lucas, Duncan; Amis, Andrew
2008-01-01
The most commonly reported complications related to cementless hip stems are loosening and thigh pain; both of these have been attributed to high levels of relative micromotion at the bone-implant interface due to insufficient primary fixation. Primary fixation is believed by many to rely on achieving a sufficient interference fit between the implant and the bone. However, attempting to achieve a high interference fit not infrequently leads to femoral canal fracture either intra-operatively or soon after. The appropriate range of diametrical interference fit that ensures primary stability without risking femoral fracture is not well understood. In this study, a finite element model was constructed to predict micromotion and, therefore, instability of femoral stems. The model was correlated with an in vitro micromotion experiment carried out on four cadaver femurs. It was confirmed that interference fit has a very significant effect on micromotion and ignoring this parameter in an analysis of primary stability is likely to underestimate the stability of the stem. Furthermore, it was predicted that the optimal level of interference fit is around 50 microm as this is sufficient to achieve good primary fixation while having a safety factor of 2 against femoral canal fracture. This result is of clinical relevance as it indicates a recommendation for the surgeon to err on the side of a low interference fit rather than risking femoral fracture.
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…
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…
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…
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
Pekkarinen, Saara; Lappi, Minna; Väisänen, Jere; Juntunen, Jouni; Pikkarainen, Minna
2017-01-01
Background Constantly increasing health care costs have led countries and health care providers to the point where health care systems must be reinvented. Consequently, electronic health (eHealth) has recently received a great deal of attention in social sciences in the domain of Internet studies. However, only a fraction of these studies focuses on the acceptability of eHealth, making consumers’ subjective evaluation an understudied field. This study will address this gap by focusing on the acceptance of MyData-based preventive eHealth services from the consumer point of view. We are adopting the term "MyData", which according to a White Paper of the Finnish Ministry of Transport and Communication refers to "1) a new approach, a paradigm shift in personal data management and processing that seeks to transform the current organization centric system to a human centric system, 2) to personal data as a resource that the individual can access and control." Objective The aim of this study was to investigate what factors influence consumers’ intentions to use a MyData-based preventive eHealth service before use. Methods We applied a new adoption model combining Venkatesh’s unified theory of acceptance and use of technology 2 (UTAUT2) in a consumer context and three constructs from health behavior theories, namely threat appraisals, self-efficacy, and perceived barriers. To test the research model, we applied structural equation modeling (SEM) with Mplus software, version 7.4. A Web-based survey was administered. We collected 855 responses. Results We first applied traditional SEM for the research model, which was not statistically significant. We then tested for possible heterogeneity in the data by running a mixture analysis. We found that heterogeneity was not the cause for the poor performance of the research model. Thus, we moved on to model-generating SEM and ended up with a statistically significant empirical model (root mean square error of approximation
Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.
DeCarlo, Lawrence T
2003-02-01
The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.
Metz, Thomas; Walewski, Joachim; Kaminski, Clemens F
2003-03-20
Evaluation schemes, e.g., least-squares fitting, are not generally applicable to any types of experiments. If the evaluation schemes were not derived from a measurement model that properly described the experiment to be evaluated, poorer precision or accuracy than attainable from the measured data could result. We outline ways in which statistical data evaluation schemes should be derived for all types of experiment, and we demonstrate them for laser-spectroscopic experiments, in which pulse-to-pulse fluctuations of the laser power cause correlated variations of laser intensity and generated signal intensity. The method of maximum likelihood is demonstrated in the derivation of an appropriate fitting scheme for this type of experiment. Statistical data evaluation contains the following steps. First, one has to provide a measurement model that considers statistical variation of all enclosed variables. Second, an evaluation scheme applicable to this particular model has to be derived or provided. Third, the scheme has to be characterized in terms of accuracy and precision. A criterion for accepting an evaluation scheme is that it have accuracy and precision as close as possible to the theoretical limit. The fitting scheme derived for experiments with pulsed lasers is compared to well-established schemes in terms of fitting power and rational functions. The precision is found to be as much as three timesbetter than for simple least-squares fitting. Our scheme also suppresses the bias on the estimated model parameters that other methods may exhibit if they are applied in an uncritical fashion. We focus on experiments in nonlinear spectroscopy, but the fitting scheme derived is applicable in many scientific disciplines.
Lenski, Richard E.; Wiser, Michael J.; Ribeck, Noah; Blount, Zachary D.; Nahum, Joshua R.; Morris, J. Jeffrey; Zaman, Luis; Turner, Caroline B.; Wade, Brian D.; Maddamsetti, Rohan; Burmeister, Alita R.; Baird, Elizabeth J.; Bundy, Jay; Grant, Nkrumah A.; Card, Kyle J.; Rowles, Maia; Weatherspoon, Kiyana; Papoulis, Spiridon E.; Sullivan, Rachel; Clark, Colleen; Mulka, Joseph S.; Hajela, Neerja
2015-01-01
Many populations live in environments subject to frequent biotic and abiotic changes. Nonetheless, it is interesting to ask whether an evolving population's mean fitness can increase indefinitely, and potentially without any limit, even in a constant environment. A recent study showed that fitness trajectories of Escherichia coli populations over 50 000 generations were better described by a power-law model than by a hyperbolic model. According to the power-law model, the rate of fitness gain declines over time but fitness has no upper limit, whereas the hyperbolic model implies a hard limit. Here, we examine whether the previously estimated power-law model predicts the fitness trajectory for an additional 10 000 generations. To that end, we conducted more than 1100 new competitive fitness assays. Consistent with the previous study, the power-law model fits the new data better than the hyperbolic model. We also analysed the variability in fitness among populations, finding subtle, but significant, heterogeneity in mean fitness. Some, but not all, of this variation reflects differences in mutation rate that evolved over time. Taken together, our results imply that both adaptation and divergence can continue indefinitely—or at least for a long time—even in a constant environment. PMID:26674951
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.
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
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
Potential fitting biases resulting from grouping data into variable width bins
NASA Astrophysics Data System (ADS)
Towers, S.
2014-07-01
When reading peer-reviewed scientific literature describing any analysis of empirical data, it is natural and correct to proceed with the underlying assumption that experiments have made good faith efforts to ensure that their analyses yield unbiased results. However, particle physics experiments are expensive and time consuming to carry out, thus if an analysis has inherent bias (even if unintentional), much money and effort can be wasted trying to replicate or understand the results, particularly if the analysis is fundamental to our understanding of the universe. In this note we discuss the significant biases that can result from data binning schemes. As we will show, if data are binned such that they provide the best comparison to a particular (but incorrect) model, the resulting model parameter estimates when fitting to the binned data can be significantly biased, leading us to too often accept the model hypothesis when it is not in fact true. When using binned likelihood or least squares methods there is of course no a priori requirement that data bin sizes need to be constant, but we show that fitting to data grouped into variable width bins is particularly prone to produce biased results if the bin boundaries are chosen to optimize the comparison of the binned data to a wrong model. The degree of bias that can be achieved simply with variable binning can be surprisingly large. Fitting the data with an unbinned likelihood method, when possible to do so, is the best way for researchers to show that their analyses are not biased by binning effects. Failing that, equal bin widths should be employed as a cross-check of the fitting analysis whenever possible.
Ranger, Jochen; Kuhn, Jörg-Tobias; Szardenings, Carsten
2017-05-01
Cognitive psychometric models embed cognitive process models into a latent trait framework in order to allow for individual differences. Due to their close relationship to the response process the models allow for profound conclusions about the test takers. However, before such a model can be used its fit has to be checked carefully. In this manuscript we give an overview over existing tests of model fit and show their relation to the generalized moment test of Newey (Econometrica, 53, 1985, 1047) and Tauchen (J. Econometrics, 30, 1985, 415). We also present a new test, the Hausman test of misspecification (Hausman, Econometrica, 46, 1978, 1251). The Hausman test consists of a comparison of two estimates of the same item parameters which should be similar if the model holds. The performance of the Hausman test is evaluated in a simulation study. In this study we illustrate its application to two popular models in cognitive psychometrics, the Q-diffusion model and the D-diffusion model (van der Maas, Molenaar, Maris, Kievit, & Boorsboom, Psychol Rev., 118, 2011, 339; Molenaar, Tuerlinckx, & van der Maas, J. Stat. Softw., 66, 2015, 1). We also compare the performance of the test to four alternative tests of model fit, namely the M 2 test (Molenaar et al., J. Stat. Softw., 66, 2015, 1), the moment test (Ranger et al., Br. J. Math. Stat. Psychol., 2016) and the test for binned time (Ranger & Kuhn, Psychol. Test. Asess. , 56, 2014b, 370). The simulation study indicates that the Hausman test is superior to the latter tests. The test closely adheres to the nominal Type I error rate and has higher power in most simulation conditions. © 2017 The British Psychological Society.
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)
Dou, Kaili; Yu, Ping; Liu, Fang; Guan, YingPing; Li, Zhenye; Ji, Yumeng; Du, Ningkai; Lu, Xudong; Duan, Huilong
2017-01-01
Background Chronic disease patients often face multiple challenges from difficult comorbidities. Smartphone health technology can be used to help them manage their conditions only if they accept and use the technology. Objective The aim of this study was to develop and test a theoretical model to predict and explain the factors influencing patients’ acceptance of smartphone health technology for chronic disease management. Methods Multiple theories and factors that may influence patients’ acceptance of smartphone health technology have been reviewed. A hybrid theoretical model was built based on the technology acceptance model, dual-factor model, health belief model, and the factors identified from interviews that might influence patients’ acceptance of smartphone health technology for chronic disease management. Data were collected from patient questionnaire surveys and computer log records about 157 hypertensive patients’ actual use of a smartphone health app. The partial least square method was used to test the theoretical model. Results The model accounted for .412 of the variance in patients’ intention to adopt the smartphone health technology. Intention to use accounted for .111 of the variance in actual use and had a significant weak relationship with the latter. Perceived ease of use was affected by patients’ smartphone usage experience, relationship with doctor, and self-efficacy. Although without a significant effect on intention to use, perceived ease of use had a significant positive influence on perceived usefulness. Relationship with doctor and perceived health threat had significant positive effects on perceived usefulness, countering the negative influence of resistance to change. Perceived usefulness, perceived health threat, and resistance to change significantly predicted patients’ intentions to use the technology. Age and gender had no significant influence on patients’ acceptance of smartphone technology. The study also
Model Fit to Experimental Data for Foam-Assisted Deep Vadose Zone Remediation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Roostapour, A.; Lee, G.; Zhong, Lirong
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 matchingmore » 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.« less
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.
Kinetic modeling and fitting software for interconnected reaction schemes: VisKin.
Zhang, Xuan; Andrews, Jared N; Pedersen, Steen E
2007-02-15
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. To determine rate constants from experimental data, fitting algorithms that adjust rate constants to fit the model to imported data were implemented using the Levenberg-Marquardt algorithm or using Broyden-Fletcher-Goldfarb-Shanno methods. 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.
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…
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…
MISFITS: evaluating the goodness of fit between a phylogenetic model and an alignment.
Nguyen, Minh Anh Thi; Klaere, Steffen; von Haeseler, Arndt
2011-01-01
As models of sequence evolution become more and more complicated, many criteria for model selection have been proposed, and tools are available to select the best model for an alignment under a particular criterion. However, in many instances the selected model fails to explain the data adequately as reflected by large deviations between observed pattern frequencies and the corresponding expectation. We present MISFITS, an approach to evaluate the goodness of fit (http://www.cibiv.at/software/misfits). MISFITS introduces a minimum number of "extra substitutions" on the inferred tree to provide a biologically motivated explanation why the alignment may deviate from expectation. These extra substitutions plus the evolutionary model then fully explain the alignment. We illustrate the method on several examples and then give a survey about the goodness of fit of the selected models to the alignments in the PANDIT database.
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…
Wernke, Matthew M.; Schroeder, Ryan M.; Haynes, Michael L.; Nolt, Lonnie L.; Albury, Alexander W.; Colvin, James M.
2017-01-01
Objective: Prosthetic sockets are custom made for each amputee, yet there are no quantitative tools to determine the appropriateness of socket fit. Ensuring a proper socket fit can have significant effects on the health of residual limb soft tissues and overall function and acceptance of the prosthetic limb. Previous work found that elevated vacuum pressure data can detect movement between the residual limb and the prosthetic socket; however, the correlation between the two was specific to each user. The overall objective of this work is to determine the relationship between elevated vacuum pressure deviations and prosthetic socket fit. Approach: A tension compression machine was used to apply repeated controlled forces onto a residual limb model with sockets of different internal volume. Results: The vacuum pressure–displacement relationship was dependent on socket fit. The vacuum pressure data were sensitive enough to detect differences of 1.5% global volume and can likely detect differences even smaller. Limb motion was reduced as surface area of contact between the limb model and socket was maximized. Innovation: The results suggest that elevated vacuum pressure data provide information to quantify socket fit. Conclusions: This study provides evidence that the use of elevated vacuum pressure data may provide a method for prosthetists to quantify and monitor socket fit. Future studies should investigate the relationship between socket fit, limb motion, and limb health to define optimal socket fit parameters. PMID:28736683
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
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…
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.
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.
Analysis and fit of stellar spectra using a mega-database of CMFGEN models
NASA Astrophysics Data System (ADS)
Fierro-Santillán, Celia; Zsargó, Janos; Klapp, Jaime; Díaz-Azuara, Santiago Alfredo; Arrieta, Anabel; Arias, Lorena
2017-11-01
We present a tool for analysis and fit of stellar spectra using a mega database of 15,000 atmosphere models for OB stars. We have developed software tools, which allow us to find the model that best fits to an observed spectrum, comparing equivalent widths and line ratios in the observed spectrum with all models of the database. We use the Hα, Hβ, Hγ, and Hδ lines as criterion of stellar gravity and ratios of He II λ4541/He I λ4471, He II λ4200/(He I+He II λ4026), He II λ4541/He I λ4387, and He II λ4200/He I λ4144 as criterion of T eff.
Galambos, Colleen; Rantz, Marilyn; Back, Jessie; Jun, Jung Sim; Skubic, Marjorie; Miller, Steven J
2017-07-01
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.
The complete set of Cassini's UVIS occultation observations of Enceladus plume: model fits
NASA Astrophysics Data System (ADS)
Portyankina, G.; Esposito, L. W.; Hansen, C. J.
2017-12-01
Since the discovery in 2005, plume of Enceladus was observed by most of the instruments onboard Cassini spacecraft. Ultraviolet Imaging Spectrograph (UVIS) have observed Enceladus plume and collimated jets embedded in it in occultational geometry on 6 different occasions. We have constructed a 3D direct simulation Monte Carlo (DSMC) model for Enceladus jets and apply it to the analysis of the full set of UVIS occultation observations conducted during Cassini's mission from 2005 to 2017. The Monte Carlo model tracks test particles from their source at the surface into space. The initial positions of all test particles for a single jet are fixed to one of 100 jets sources identified by Porco et al. (2014). The initial three-dimensional velocity of each particle contains two components: a velocity Vz which is perpendicular to the surface, and a thermal velocity which is isotropic in the upward hemisphere. The direction and speed of the thermal velocity of each particle is chosen randomly but the ensemble moves isotropically at a speed which satisfies a Boltzmann distribution for a given temperature Tth. A range for reasonable Vz is then determined by requiring that modeled jet widths match the observed ones. Each model run results in a set of coordinates and velocities of a given set of test particles. These are converted to the test particle number densities and then integrated along LoS for each time step of the occultation observation. The geometry of the observation is calculated using SPICE. The overarching result of the simulation run is a test particle number density along LoS for each time point during the occultation observation for each of the jets separately. To fit the model to the data, we integrate all jets that are crossed by the LoS at each point during an observation. The relative strength of the jets must be determined to fit the observed UVIS curves. The results of the fits are sets of active jets for each occultation. Each UVIS occultation
Dou, Kaili; Yu, Ping; Deng, Ning; Liu, Fang; Guan, YingPing; Li, Zhenye; Ji, Yumeng; Du, Ningkai; Lu, Xudong; Duan, Huilong
2017-12-06
Chronic disease patients often face multiple challenges from difficult comorbidities. Smartphone health technology can be used to help them manage their conditions only if they accept and use the technology. The aim of this study was to develop and test a theoretical model to predict and explain the factors influencing patients' acceptance of smartphone health technology for chronic disease management. Multiple theories and factors that may influence patients' acceptance of smartphone health technology have been reviewed. A hybrid theoretical model was built based on the technology acceptance model, dual-factor model, health belief model, and the factors identified from interviews that might influence patients' acceptance of smartphone health technology for chronic disease management. Data were collected from patient questionnaire surveys and computer log records about 157 hypertensive patients' actual use of a smartphone health app. The partial least square method was used to test the theoretical model. The model accounted for .412 of the variance in patients' intention to adopt the smartphone health technology. Intention to use accounted for .111 of the variance in actual use and had a significant weak relationship with the latter. Perceived ease of use was affected by patients' smartphone usage experience, relationship with doctor, and self-efficacy. Although without a significant effect on intention to use, perceived ease of use had a significant positive influence on perceived usefulness. Relationship with doctor and perceived health threat had significant positive effects on perceived usefulness, countering the negative influence of resistance to change. Perceived usefulness, perceived health threat, and resistance to change significantly predicted patients' intentions to use the technology. Age and gender had no significant influence on patients' acceptance of smartphone technology. The study also confirmed the positive relationship between intention to use
The Gold Medal Fitness Program: A Model for Teacher Change
ERIC Educational Resources Information Center
Wright, Jan; Konza, Deslea; Hearne, Doug; Okely, Tony
2008-01-01
Background: Following the 2000 Sydney Olympics, the NSW Premier, Mr Bob Carr, launched a school-based initiative in NSW government primary schools called the "Gold Medal Fitness Program" to encourage children to be fitter and more active. The Program was introduced into schools through a model of professional development, "Quality…
Describing the Process of Adopting Nutrition and Fitness Apps: Behavior Stage Model Approach
Sproesser, Gudrun; Schupp, Harald T; Renner, Britta
2018-01-01
Background Although mobile technologies such as smartphone apps are promising means for motivating people to adopt a healthier lifestyle (mHealth apps), previous studies have shown low adoption and continued use rates. Developing the means to address this issue requires further understanding of mHealth app nonusers and adoption processes. This study utilized a stage model approach based on the Precaution Adoption Process Model (PAPM), which proposes that people pass through qualitatively different motivational stages when adopting a behavior. Objective To establish a better understanding of between-stage transitions during app adoption, this study aimed to investigate the adoption process of nutrition and fitness app usage, and the sociodemographic and behavioral characteristics and decision-making style preferences of people at different adoption stages. Methods Participants (N=1236) were recruited onsite within the cohort study Konstanz Life Study. Use of mobile devices and nutrition and fitness apps, 5 behavior adoption stages of using nutrition and fitness apps, preference for intuition and deliberation in eating decision-making (E-PID), healthy eating style, sociodemographic variables, and body mass index (BMI) were assessed. Results Analysis of the 5 behavior adoption stages showed that stage 1 (“unengaged”) was the most prevalent motivational stage for both nutrition and fitness app use, with half of the participants stating that they had never thought about using a nutrition app (52.41%, 533/1017), whereas less than one-third stated they had never thought about using a fitness app (29.25%, 301/1029). “Unengaged” nonusers (stage 1) showed a higher preference for an intuitive decision-making style when making eating decisions, whereas those who were already “acting” (stage 4) showed a greater preference for a deliberative decision-making style (F4,1012=21.83, P<.001). Furthermore, participants differed widely in their readiness to adopt nutrition
Nonlinear Curve-Fitting Program
NASA Technical Reports Server (NTRS)
Everhart, Joel L.; Badavi, Forooz F.
1989-01-01
Nonlinear optimization algorithm helps in finding best-fit curve. Nonlinear Curve Fitting Program, NLINEAR, interactive curve-fitting routine based on description of quadratic expansion of X(sup 2) statistic. Utilizes nonlinear optimization algorithm calculating best statistically weighted values of parameters of fitting function and X(sup 2) minimized. Provides user with such statistical information as goodness of fit and estimated values of parameters producing highest degree of correlation between experimental data and mathematical model. Written in FORTRAN 77.
Weiss, Michael
2017-06-01
Appropriate model selection is important in fitting oral concentration-time data due to the complex character of the absorption process. When IV reference data are available, the problem is the selection of an empirical input function (absorption model). In the present examples a weighted sum of inverse Gaussian density functions (IG) was found most useful. It is shown that alternative models (gamma and Weibull density) are only valid if the input function is log-concave. Furthermore, it is demonstrated for the first time that the sum of IGs model can be also applied to fit oral data directly (without IV data). In the present examples, a weighted sum of two or three IGs was sufficient. From the parameters of this function, the model-independent measures AUC and mean residence time can be calculated. It turned out that a good fit of the data in the terminal phase is essential to avoid parameter biased estimates. The time course of fractional elimination rate and the concept of log-concavity have proved as useful tools in model selection.
Koivumäki, Timo; Pekkarinen, Saara; Lappi, Minna; Väisänen, Jere; Juntunen, Jouni; Pikkarainen, Minna
2017-12-22
Constantly increasing health care costs have led countries and health care providers to the point where health care systems must be reinvented. Consequently, electronic health (eHealth) has recently received a great deal of attention in social sciences in the domain of Internet studies. However, only a fraction of these studies focuses on the acceptability of eHealth, making consumers' subjective evaluation an understudied field. This study will address this gap by focusing on the acceptance of MyData-based preventive eHealth services from the consumer point of view. We are adopting the term "MyData", which according to a White Paper of the Finnish Ministry of Transport and Communication refers to "1) a new approach, a paradigm shift in personal data management and processing that seeks to transform the current organization centric system to a human centric system, 2) to personal data as a resource that the individual can access and control." The aim of this study was to investigate what factors influence consumers' intentions to use a MyData-based preventive eHealth service before use. We applied a new adoption model combining Venkatesh's unified theory of acceptance and use of technology 2 (UTAUT2) in a consumer context and three constructs from health behavior theories, namely threat appraisals, self-efficacy, and perceived barriers. To test the research model, we applied structural equation modeling (SEM) with Mplus software, version 7.4. A Web-based survey was administered. We collected 855 responses. We first applied traditional SEM for the research model, which was not statistically significant. We then tested for possible heterogeneity in the data by running a mixture analysis. We found that heterogeneity was not the cause for the poor performance of the research model. Thus, we moved on to model-generating SEM and ended up with a statistically significant empirical model (root mean square error of approximation [RMSEA] 0.051, Tucker-Lewis index [TLI] 0
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.
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.
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…
NASA Astrophysics Data System (ADS)
De Geyter, G.; Baes, M.; Fritz, J.; Camps, P.
2013-02-01
We present FitSKIRT, a method to efficiently fit radiative transfer models to UV/optical images of dusty galaxies. These images have the advantage that they have better spatial resolution compared to FIR/submm data. FitSKIRT uses the GAlib genetic algorithm library to optimize the output of the SKIRT Monte Carlo radiative transfer code. Genetic algorithms prove to be a valuable tool in handling the multi- dimensional search space as well as the noise induced by the random nature of the Monte Carlo radiative transfer code. FitSKIRT is tested on artificial images of a simulated edge-on spiral galaxy, where we gradually increase the number of fitted parameters. We find that we can recover all model parameters, even if all 11 model parameters are left unconstrained. Finally, we apply the FitSKIRT code to a V-band image of the edge-on spiral galaxy NGC 4013. This galaxy has been modeled previously by other authors using different combinations of radiative transfer codes and optimization methods. Given the different models and techniques and the complexity and degeneracies in the parameter space, we find reasonable agreement between the different models. We conclude that the FitSKIRT method allows comparison between different models and geometries in a quantitative manner and minimizes the need of human intervention and biasing. The high level of automation makes it an ideal tool to use on larger sets of observed data.
Fitting contraceptive diaphragms: can laywomen provide quality training for doctors?
Pickard, S; Baraitser, P; Herns, M; Massil, H
2001-07-01
To test the feasibility of training laywomen as professional patients to teach doctors to fit the contraceptive diaphragm. Semi-structured interviews with instructing doctors and questionnaires to DFFP trainees. These documented current teaching practice and the acceptability of professional patients. The Delphi technique was used to establish a curriculum for the professional patients' training programme. The results show that there is currently a lack of standardisation in teaching methods and content with respect to diaphragm fitting. All instructing doctors and DFFP trainees involved had experienced difficulties in recruiting women for training, and the majority would be happy to work with professional patients. After three rounds of the Delphi procedure, consensus was reached and a curriculum developed. Five women were recruited on to a training programme, and four successfully completed it. Lack of standardisation and difficulty recruiting patients are current problems when training doctors to fit diaphragms. Our study shows that the use of professional patients would be acceptable to both DFFP trainees and instructing doctors, and that it is possible to recruit and train women for this purpose.
Gomes, Gisele Cristine Vieira; Bacha, Jéssica Maria Ribeiro; do Socorro Simões, Maria; Lin, Sumika Mori; Viveiro, Larissa Alamino Pereira; Varise, Eliana Maria; Filho, Wilson Jacob; Pompeu, José Eduardo
2017-01-01
Frailty can be defined as a medical syndrome with multiple causes and contributors, characterized by diminished strength and endurance and reduced physiological function that increases the vulnerability to develop functional dependency and/or death. Studies have shown that the most commonly studied exercise protocol for frail older adults is the multimodal training. Interactive video games (IVGs) involve tasks in virtual environments that combine physical and cognitive demands in an attractive and challenging way. The aim of this study will be to evaluate the feasibility, safety, acceptability, and functional outcomes of playing Nintendo Wii Fit Plus TM (NWFP) for frail older adults. The study is a randomized controlled, parallel group, feasibility trial. Participants will be randomly assigned to the experimental group (EG) and control group (CG). The EG will participate in 14 training sessions, each lasting 50 min, twice a week. In each training session, the participants will play five games, with three attempts at each game. The first attempt will be performed with the assistance of a physical therapist to correct the movements and posture of the patients and subsequent attempts will be performed independently. Scores achieved in the games will be recorded. The participants will be evaluated by a blinded physical therapist at three moments: before and after intervention and 30 days after the end of the intervention (follow-up). We will assess the feasibility, acceptability, safety, and clinical outcomes (postural control, gait, cognition, quality of life, mood, and fear of falling). Due to the deficiencies in multiple systems, studies have shown that multimodal interventions including motor-cognitive stimulation can improve the mobility of frail elderly adults. IVGs, among them the NWFP, are considered as a multimodal motor-cognitive intervention that can potentially improve motor and cognitive functions in the frail elderly. However, there is still no evidence
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'…
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.
AXAF FITS standard for ray trace interchange
NASA Technical Reports Server (NTRS)
Hsieh, Paul F.
1993-01-01
A standard data format for the archival and transport of x-ray events generated by ray trace models is described. Upon review and acceptance by the Advanced X-ray Astrophysics Facility (AXAF) Software Systems Working Group (SSWG), this standard shall become the official AXAF data format for ray trace events. The Flexible Image Transport System (FITS) is well suited for the purposes of the standard and was selected to be the basis of the standard. FITS is both flexible and efficient and is also widely used within the astronomical community for storage and transfer of data. In addition, software to read and write FITS format files are widely available. In selecting quantities to be included within the ray trace standard, the AXAF Mission Support team, Science Instruments team, and the other contractor teams were surveyed. From the results of this survey, the following requirements were established: (1) for the scientific needs, each photon should have associated with it: position, direction, energy, and statistical weight; the standard must also accommodate path length (relative phase), and polarization. (2) a unique photon identifier is necessary for bookkeeping purposes; (3) a log of individuals, organizations, and software packages that have modified the data must be maintained in order to create an audit trail; (4) a mechanism for extensions to the basic kernel should be provided; and (5) the ray trace standard should integrate with future AXAF data product standards.
AXAF FITS standard for ray trace interchange
NASA Astrophysics Data System (ADS)
Hsieh, Paul F.
1993-07-01
A standard data format for the archival and transport of x-ray events generated by ray trace models is described. Upon review and acceptance by the Advanced X-ray Astrophysics Facility (AXAF) Software Systems Working Group (SSWG), this standard shall become the official AXAF data format for ray trace events. The Flexible Image Transport System (FITS) is well suited for the purposes of the standard and was selected to be the basis of the standard. FITS is both flexible and efficient and is also widely used within the astronomical community for storage and transfer of data. In addition, software to read and write FITS format files are widely available. In selecting quantities to be included within the ray trace standard, the AXAF Mission Support team, Science Instruments team, and the other contractor teams were surveyed. From the results of this survey, the following requirements were established: (1) for the scientific needs, each photon should have associated with it: position, direction, energy, and statistical weight; the standard must also accommodate path length (relative phase), and polarization. (2) a unique photon identifier is necessary for bookkeeping purposes; (3) a log of individuals, organizations, and software packages that have modified the data must be maintained in order to create an audit trail; (4) a mechanism for extensions to the basic kernel should be provided; and (5) the ray trace standard should integrate with future AXAF data product standards.
NASA Astrophysics Data System (ADS)
Franzetti, Paolo; Scodeggio, Marco
2012-10-01
GOSSIP fits the electro-magnetic emission of an object (the SED, Spectral Energy Distribution) against synthetic models to find the simulated one that best reproduces the observed data. It builds-up the observed SED of an object (or a large sample of objects) combining magnitudes in different bands and eventually a spectrum; then it performs a chi-square minimization fitting procedure versus a set of synthetic models. The fitting results are used to estimate a number of physical parameters like the Star Formation History, absolute magnitudes, stellar mass and their Probability Distribution Functions.
Sabry, A H; W Hasan, W Z; Ab Kadir, M Z A; Radzi, M A M; Shafie, S
2018-01-01
The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.
W. Hasan, W. Z.
2018-01-01
The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model. PMID:29351554
Describing the Process of Adopting Nutrition and Fitness Apps: Behavior Stage Model Approach.
König, Laura M; Sproesser, Gudrun; Schupp, Harald T; Renner, Britta
2018-03-13
Although mobile technologies such as smartphone apps are promising means for motivating people to adopt a healthier lifestyle (mHealth apps), previous studies have shown low adoption and continued use rates. Developing the means to address this issue requires further understanding of mHealth app nonusers and adoption processes. This study utilized a stage model approach based on the Precaution Adoption Process Model (PAPM), which proposes that people pass through qualitatively different motivational stages when adopting a behavior. To establish a better understanding of between-stage transitions during app adoption, this study aimed to investigate the adoption process of nutrition and fitness app usage, and the sociodemographic and behavioral characteristics and decision-making style preferences of people at different adoption stages. Participants (N=1236) were recruited onsite within the cohort study Konstanz Life Study. Use of mobile devices and nutrition and fitness apps, 5 behavior adoption stages of using nutrition and fitness apps, preference for intuition and deliberation in eating decision-making (E-PID), healthy eating style, sociodemographic variables, and body mass index (BMI) were assessed. Analysis of the 5 behavior adoption stages showed that stage 1 ("unengaged") was the most prevalent motivational stage for both nutrition and fitness app use, with half of the participants stating that they had never thought about using a nutrition app (52.41%, 533/1017), whereas less than one-third stated they had never thought about using a fitness app (29.25%, 301/1029). "Unengaged" nonusers (stage 1) showed a higher preference for an intuitive decision-making style when making eating decisions, whereas those who were already "acting" (stage 4) showed a greater preference for a deliberative decision-making style (F 4,1012 =21.83, P<.001). Furthermore, participants differed widely in their readiness to adopt nutrition and fitness apps, ranging from having "decided
Ehteshami, Asghar
2017-03-01
Nowdays, due to the increasing importance of quality care, organizations focuse on the improving provision, management and distribution of health. On one hand, incremental costs of the new technologies and on the other hand, increased knowledge of health care recipients and their expectations for high quality services have doubled the need to make changes in order to respond to resource constraints (financial, human, material). For this purpose, several technologies, such as barcode, have been used in hospitals to improve services and staff productivity; but various factors effect on the adoption of new technologies and despite good implementation of a technology and its benefits, sometimes personnel don't accept and don't use it. This is an applied descriptive cross-sectional study in which all the barcode users in health information management department of the three academic hospitals (Feiz, Al-Zahra, Ayatollah Kashani) affiliated to Isfahan University of Medical Sciences were surveyed by the barcode technology acceptance questionnaire, in six areas as following: barcode ease of learning, capabilities, perception of its usefulness and its ease of use, users attitudes towards its using, and users intention. The finding showed that barcode technology total acceptance was relatively desirable (%76.9); the most compliance with TAM model was related to the user perceptions about the ease of use of barcode technology and the least compliance was related to the ease of learning barcode technology (respectively %83.7 and %71.5). Ease of learning and barcode capability effect of usefulness and perceived ease of barcode technology. Users perceptions effect their attitudes toward greater use of technology and their attitudes have an effect on their intention to use the technology and finally, their intention makes actual use of the technology (acceptance). Therefore, considering the six elements related to technology implementation can be important in the barcode
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.
Holden, Richard J; Asan, Onur; Wozniak, Erica M; Flynn, Kathryn E; Scanlon, Matthew C
2016-11-15
The value of health information technology (IT) ultimately depends on end users accepting and appropriately using it for patient care. This study examined pediatric intensive care unit nurses' perceptions, acceptance, and use of a novel health IT, the Large Customizable Interactive Monitor. An expanded technology acceptance model was tested by applying stepwise linear regression to data from a standardized survey of 167 nurses. Nurses reported low-moderate ratings of the novel IT's ease of use and low to very low ratings of usefulness, social influence, and training. Perceived ease of use, usefulness for patient/family involvement, and usefulness for care delivery were associated with system satisfaction (R 2 = 70%). Perceived usefulness for care delivery and patient/family social influence were associated with intention to use the system (R 2 = 65%). Satisfaction and intention were associated with actual system use (R 2 = 51%). The findings have implications for research, design, implementation, and policies for nursing informatics, particularly novel nursing IT. Several changes are recommended to improve the design and implementation of the studied IT.
46 CFR 56.15-10 - Special purpose fittings.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 46 Shipping 2 2010-10-01 2010-10-01 false Special purpose fittings. 56.15-10 Section 56.15-10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING PIPING SYSTEMS AND... with subpart 50.25 of this subchapter are acceptable for use in piping systems. (b) Special purpose...
Hagell, Peter; Westergren, Albert
Sample size is a major factor in statistical null hypothesis testing, which is the basis for many approaches to testing Rasch model fit. Few sample size recommendations for testing fit to the Rasch model concern the Rasch Unidimensional Measurement Models (RUMM) software, which features chi-square and ANOVA/F-ratio based fit statistics, including Bonferroni and algebraic sample size adjustments. This paper explores the occurrence of Type I errors with RUMM fit statistics, and the effects of algebraic sample size adjustments. Data with simulated Rasch model fitting 25-item dichotomous scales and sample sizes ranging from N = 50 to N = 2500 were analysed with and without algebraically adjusted sample sizes. Results suggest the occurrence of Type I errors with N less then or equal to 500, and that Bonferroni correction as well as downward algebraic sample size adjustment are useful to avoid such errors, whereas upward adjustment of smaller samples falsely signal misfit. Our observations suggest that sample sizes around N = 250 to N = 500 may provide a good balance for the statistical interpretation of the RUMM fit statistics studied here with respect to Type I errors and under the assumption of Rasch model fit within the examined frame of reference (i.e., about 25 item parameters well targeted to the sample).
Fitting measurement models to vocational interest data: are dominance models ideal?
Tay, Louis; Drasgow, Fritz; Rounds, James; Williams, Bruce A
2009-09-01
In this study, the authors examined the item response process underlying 3 vocational interest inventories: the Occupational Preference Inventory (C.-P. Deng, P. I. Armstrong, & J. Rounds, 2007), the Interest Profiler (J. Rounds, T. Smith, L. Hubert, P. Lewis, & D. Rivkin, 1999; J. Rounds, C. M. Walker, et al., 1999), and the Interest Finder (J. E. Wall & H. E. Baker, 1997; J. E. Wall, L. L. Wise, & H. E. Baker, 1996). Item response theory (IRT) dominance models, such as the 2-parameter and 3-parameter logistic models, assume that item response functions (IRFs) are monotonically increasing as the latent trait increases. In contrast, IRT ideal point models, such as the generalized graded unfolding model, have IRFs that peak where the latent trait matches the item. Ideal point models are expected to fit better because vocational interest inventories ask about typical behavior, as opposed to requiring maximal performance. Results show that across all 3 interest inventories, the ideal point model provided better descriptions of the response process. The importance of specifying the correct item response model for precise measurement is discussed. In particular, scores computed by a dominance model were shown to be sometimes illogical: individuals endorsing mostly realistic or mostly social items were given similar scores, whereas scores based on an ideal point model were sensitive to which type of items respondents endorsed.
Tan, Fa-Bing; Wang, Lu; Fu, Gang; Wu, Shu-Hong; Jin, Ping
2010-02-01
To study the effect of different optical impression methods in Cerec 3D/Inlab MC XL system on marginal and internal fit of all-ceramic crowns. A right mandibular first molar in the standard model was used to prepare full crown and replicated into thirty-two plaster casts. Sixteen of them were selected randomly for bonding crown and the others were used for taking optical impression, in half of which the direct optical impression taking method were used and the others were used for the indirect method, and then eight Cerec Blocs all-ceramic crowns were manufactured respectively. The fit of all-ceramic crowns were evaluated by modified United States Public Health Service (USPHS) criteria and scanning electron microscope (SEM) imaging, and the data were statistically analyzed with SAS 9.1 software. The clinically acceptable rate for all marginal measurement sites was 87.5% according to USPHS criteria. There was no statistically significant difference in marginal fit between direct and indirect method group (P > 0.05). With SEM imaging, all marginal measurement sites were less than 120 microm and no statistically significant difference was found between direct and indirect method group in terms of marginal or internal fit (P > 0.05). But the direct method group showed better fit than indirect method group in terms of mesial surface, lingual surface, buccal surface and occlusal surface (P < 0.05). The distal surface's fit was worse and the obvious difference was observed between mesial surface and distal surface in direct method group (P < 0.01). Under the conditions of this study, the optical impression method had no significant effect on marginal fit of Cerec Blocs crowns, but it had certain effect on internal fit. Overall all-ceramic crowns appeared to have clinically acceptable marginal fit.
Forslin, Mia; Kottorp, Anders; Kierkegaard, Marie; Johansson, Sverker
2016-11-11
To translate and culturally adapt the Acceptance of Chronic Health Conditions (ACHC) Scale for people with multiple sclerosis into Swedish, and to analyse the psychometric properties of the Swedish version. Ten people with multiple sclerosis participated in translation and cultural adaptation of the ACHC Scale; 148 people with multiple sclerosis were included in evaluation of the psychometric properties of the scale. Translation and cultural adaptation were carried out through translation and back-translation, by expert committee evaluation and pre-test with cognitive interviews in people with multiple sclerosis. The psychometric properties of the Swedish version were evaluated using Rasch analysis. The Swedish version of the ACHC Scale was an acceptable equivalent to the original version. Seven of the original 10 items fitted the Rasch model and demonstrated ability to separate between groups. A 5-item version, including 2 items and 3 super-items, demonstrated better psychometric properties, but lower ability to separate between groups. The Swedish version of the ACHC Scale with the original 10 items did not fit the Rasch model. Two solutions, either with 7 items (ACHC-7) or with 2 items and 3 super-items (ACHC-5), demonstrated acceptable psychometric properties. Use of the ACHC-5 Scale with super-items is recommended, since this solution adjusts for local dependency among items.
When accepting a gift can be professional misconduct and theft.
Griffith, Richard
2016-07-01
Gifts are often given as tokens of gratitude by grateful patients to district nurses. However, there are circumstances where the Nursing and Midwifery Council (NMC), as the professional regulator, and the courts, have held that accepting gifts, large or small, from vulnerable adults is dishonest and amounts to professional misconduct and even theft. Richard Griffith discusses the circumstances where a district nurse who accepts a gift can face a fitness-to-practise investigation and an allegation of theft.
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.
76 FR 5494 - Pipeline Safety: Mechanical Fitting Failure Reporting Requirements
Federal Register 2010, 2011, 2012, 2013, 2014
2011-02-01
... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration 49 CFR Part... Safety: Mechanical Fitting Failure Reporting Requirements AGENCY: Pipeline and Hazardous Materials Safety... tightening. A widely accepted industry guidance document, Gas Pipeline Technical Committee (GPTC) Guide, does...
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…
Analysis of the Best-Fit Sky Model Produced Through Redundant Calibration of Interferometers
NASA Astrophysics Data System (ADS)
Storer, Dara; Pober, Jonathan
2018-01-01
21 cm cosmology provides unique insights into the formation of stars and galaxies in the early universe, and particularly the Epoch of Reionization. Detection of the 21 cm line is challenging because it is generally 4-5 magnitudes weaker than the emission from foreground sources, and therefore the instruments used for detection must be carefully designed and calibrated. 21 cm cosmology is primarily conducted using interferometers, which are difficult to calibrate because of their complex structure. Here I explore the relationship between sky-based calibration, which relies on an accurate and comprehensive sky model, and redundancy-based calibration, which makes use of redundancies in the orientation of the interferometer's dishes. In addition to producing calibration parameters, redundant calibration also produces a best fit model of the sky. In this work I examine that sky model and explore the possibility of using that best fit model as an additional input to improve on sky-based calibration.
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.
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. PMID:24651252
A Multivariate Model for the Study of Parental Acceptance-Rejection and Child Abuse.
ERIC Educational Resources Information Center
Rohner, Ronald P.; Rohner, Evelyn C.
This paper proposes a multivariate strategy for the study of parental acceptance-rejection and child abuse and describes a research study on parental rejection and child abuse which illustrates the advantages of using a multivariate, (rather than a simple-model) approach. The multivariate model is a combination of three simple models used to study…
Muir, W M; Howard, R D
2001-07-01
Any release of transgenic organisms into nature is a concern because ecological relationships between genetically engineered organisms and other organisms (including their wild-type conspecifics) are unknown. To address this concern, we developed a method to evaluate risk in which we input estimates of fitness parameters from a founder population into a recurrence model to predict changes in transgene frequency after a simulated transgenic release. With this method, we grouped various aspects of an organism's life cycle into six net fitness components: juvenile viability, adult viability, age at sexual maturity, female fecundity, male fertility, and mating advantage. We estimated these components for wild-type and transgenic individuals using the fish, Japanese medaka (Oryzias latipes). We generalized our model's predictions using various combinations of fitness component values in addition to our experimentally derived estimates. Our model predicted that, for a wide range of parameter values, transgenes could spread in populations despite high juvenile viability costs if transgenes also have sufficiently high positive effects on other fitness components. Sensitivity analyses indicated that transgene effects on age at sexual maturity should have the greatest impact on transgene frequency, followed by juvenile viability, mating advantage, female fecundity, and male fertility, with changes in adult viability, resulting in the least impact.
33 CFR 157.122 - Piping, valves, and fittings.
Code of Federal Regulations, 2010 CFR
2010-07-01
... OIL IN BULK Crude Oil Washing (COW) System on Tank Vessels Design, Equipment, and Installation § 157..., valves, and fittings of each COW system must: (1) Meet 46 CFR part 56; and (2) Be of steel or an equivalent material accepted by the Commandant. (b) The piping of each COW system must be permanently...
A best-fit model for concept vectors in biomedical research grants.
Johnson, Calvin; Lau, William; Bhandari, Archna; Hays, Timothy
2008-11-06
The Research, Condition, and Disease Categorization (RCDC) project was created to standardize budget reporting by research topic. Text mining techniques have been implemented to classify NIH grant applications into proper research and disease categories. A best-fit model is shown to achieve classification performance rivaling that of concept vectors produced by human experts.
FragFit: a web-application for interactive modeling of protein segments into cryo-EM density maps.
Tiemann, Johanna K S; Rose, Alexander S; Ismer, Jochen; Darvish, Mitra D; Hilal, Tarek; Spahn, Christian M T; Hildebrand, Peter W
2018-05-21
Cryo-electron microscopy (cryo-EM) is a standard method to determine the three-dimensional structures of molecular complexes. However, easy to use tools for modeling of protein segments into cryo-EM maps are sparse. Here, we present the FragFit web-application, a web server for interactive modeling of segments of up to 35 amino acids length into cryo-EM density maps. The fragments are provided by a regularly updated database containing at the moment about 1 billion entries extracted from PDB structures and can be readily integrated into a protein structure. Fragments are selected based on geometric criteria, sequence similarity and fit into a given cryo-EM density map. Web-based molecular visualization with the NGL Viewer allows interactive selection of fragments. The FragFit web-application, accessible at http://proteinformatics.de/FragFit, is free and open to all users, without any login requirements.
NASA Astrophysics Data System (ADS)
Takahashi, Takuya; Sugiura, Junnnosuke; Nagayama, Kuniaki
2002-05-01
To investigate the role hydration plays in the electrostatic interactions of proteins, the time-averaged electrostatic potential of the B1 domain of protein G in an aqueous solution was calculated with full atomic molecular dynamics simulations that explicitly considers every atom (i.e., an all atom model). This all atom calculated potential was compared with the potential obtained from an electrostatic continuum model calculation. In both cases, the charge-screening effect was fairly well formulated with an effective relative dielectric constant which increased linearly with increasing charge-charge distance. This simulated linear dependence agrees with the experimentally determined linear relation proposed by Pickersgill. Cut-off approximations for Coulomb interactions failed to reproduce this linear relation. Correlation between the all atom model and the continuum models was found to be better than the respective correlation calculated for linear fitting to the two models. This confirms that the continuum model is better at treating the complicated shapes of protein conformations than the simple linear fitting empirical model. We have tried a sigmoid fitting empirical model in addition to the linear one. When weights of all data were treated equally, the sigmoid model, which requires two fitting parameters, fits results of both the all atom and the continuum models less accurately than the linear model which requires only one fitting parameter. When potential values are chosen as weighting factors, the fitting error of the sigmoid model became smaller, and the slope of both linear fitting curves became smaller. This suggests the screening effect of an aqueous medium within a short range, where potential values are relatively large, is smaller than that expected from the linear fitting curve whose slope is almost 4. To investigate the linear increase of the effective relative dielectric constant, the Poisson equation of a low-dielectric sphere in a high
Ehteshami, Asghar
2017-01-01
Nowdays, due to the increasing importance of quality care, organizations focuse on the improving provision, management and distribution of health. On one hand, incremental costs of the new technologies and on the other hand, increased knowledge of health care recipients and their expectations for high quality services have doubled the need to make changes in order to respond to resource constraints (financial, human, material). For this purpose, several technologies, such as barcode, have been used in hospitals to improve services and staff productivity; but various factors effect on the adoption of new technologies and despite good implementation of a technology and its benefits, sometimes personnel don’t accept and don’t use it. Methods: This is an applied descriptive cross-sectional study in which all the barcode users in health information management department of the three academic hospitals (Feiz, Al-Zahra, Ayatollah Kashani) affiliated to Isfahan University of Medical Sciences were surveyed by the barcode technology acceptance questionnaire, in six areas as following: barcode ease of learning, capabilities, perception of its usefulness and its ease of use, users attitudes towards its using, and users intention. Results: The finding showed that barcode technology total acceptance was relatively desirable (%76.9); the most compliance with TAM model was related to the user perceptions about the ease of use of barcode technology and the least compliance was related to the ease of learning barcode technology (respectively %83.7 and %71.5). Conclusion: Ease of learning and barcode capability effect of usefulness and perceived ease of barcode technology. Users perceptions effect their attitudes toward greater use of technology and their attitudes have an effect on their intention to use the technology and finally, their intention makes actual use of the technology (acceptance). Therefore, considering the six elements related to technology implementation can be
Development of an Advanced Respirator Fit-Test Headform
Bergman, Michael S.; Zhuang, Ziqing; Hanson, David; Heimbuch, Brian K.; McDonald, Michael J.; Palmiero, Andrew J.; Shaffer, Ronald E.; Harnish, Delbert; Husband, Michael; Wander, Joseph D.
2015-01-01
Improved respirator test headforms are needed to measure the fit of N95 filtering facepiece respirators (FFRs) for protection studies against viable airborne particles. A Static (i.e., non-moving, non-speaking) Advanced Headform (StAH) was developed for evaluating the fit of N95 FFRs. The StAH was developed based on the anthropometric dimensions of a digital headform reported by the National Institute for Occupational Safety and Health (NIOSH) and has a silicone polymer skin with defined local tissue thicknesses. Quantitative fit factor evaluations were performed on seven N95 FFR models of various sizes and designs. Donnings were performed with and without a pre-test leak checking method. For each method, four replicate FFR samples of each of the seven models were tested with two donnings per replicate, resulting in a total of 56 tests per donning method. Each fit factor evaluation was comprised of three 86-sec exercises: “Normal Breathing” (NB, 11.2 liters per min (lpm)), “Deep Breathing” (DB, 20.4 lpm), then NB again. A fit factor for each exercise and an overall test fit factor were obtained. Analysis of variance methods were used to identify statistical differences among fit factors (analyzed as logarithms) for different FFR models, exercises, and testing methods. For each FFR model and for each testing method, the NB and DB fit factor data were not significantly different (P > 0.05). Significant differences were seen in the overall exercise fit factor data for the two donning methods among all FFR models (pooled data) and in the overall exercise fit factor data for the two testing methods within certain models. Utilization of the leak checking method improved the rate of obtaining overall exercise fit factors ≥100. The FFR models, which are expected to achieve overall fit factors ≥ 100 on human subjects, achieved overall exercise fit factors ≥ 100 on the StAH. Further research is needed to evaluate the correlation of FFRs fitted on the StAH to
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,…
The relationship between motor competence, physical fitness and self-perception in children.
Vedul-Kjelsås, V; Sigmundsson, H; Stensdotter, A-K; Haga, M
2012-05-01
The aim of the current research was to explore the relationship between motor competence, physical fitness and self-perception, and to study to which extent this relationship may vary by gender. A sample of 67 children (mean age 11.46 years, SD 0.27) completed Harter's Self-Perception Profile for Children (SPPC), the Movement Assessment Battery for Children (MABC) and the Test of Physical Fitness (TPF) to assess self-perception, motor competence and physical fitness. The SPPC was stronger related to total score on TPF than to total score on MABC. However, when looking at boys and girls separately, this result was found for the boys only. In the group in general, total scores on both TPF and MABC correlated significantly with three of the domains of SPPC (social acceptance, athletic competence and physical appearance) and general self-worth. This relationship varied by gender. Interestingly, TPF was highest correlated with perception of athletic competence in boys but with perception of social acceptance in girls. A high and significant correlation was found between physical fitness and motor competence for both genders. The results indicated a strong relationship between physical fitness, motor competence and self-perception in children that varied by gender. This implies that all these factors are essential contributions in order to facilitate participation in physical activity in children. © 2011 Blackwell Publishing Ltd.
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…
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.
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. © The Author(s) 2014.
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.
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.
Handzel, Ophir; Wang, Haobing; Fiering, Jason; Borenstein, Jeffrey T.; Mescher, Mark J.; Leary Swan, Erin E.; Murphy, Brian A.; Chen, Zhiqiang; Peppi, Marcello; Sewell, William F.; Kujawa, Sharon G.; McKenna, Michael J.
2009-01-01
Temporal bone implants can be used to electrically stimulate the auditory nerve, to amplify sound, to deliver drugs to the inner ear and potentially for other future applications. The implants require storage space and access to the middle or inner ears. The most acceptable space is the cavity created by a canal wall up mastoidectomy. Detailed knowledge of the available space for implantation and pathways to access the middle and inner ears is necessary for the design of implants and successful implantation. Based on temporal bone CT scans a method for three-dimensional reconstruction of a virtual canal wall up mastoidectomy space is described. Using Amira® software the area to be removed during such surgery is marked on axial CT slices, and a three-dimensional model of that space is created. The average volume of 31 reconstructed models is 12.6 cm3 with standard deviation of 3.69 cm3, ranging from 7.97 to 23.25 cm3. Critical distances were measured directly from the model and their averages were calculated: height 3.69 cm, depth 2.43 cm, length above the external auditory canal (EAC) 4.45 cm and length posterior to EAC 3.16 cm. These linear measurements did not correlate well with volume measurements. The shape of the models was variable to a significant extent making the prediction of successful implantation for a given design based on linear and volumetric measurement unreliable. Hence, to assure successful implantation, preoperative assessment should include a virtual fitting of an implant into the intended storage space. The above-mentioned three-dimensional models were exported from Amira to a Solidworks application where virtual fitting was performed. Our results are compared to other temporal bone implant virtual fitting studies. Virtual fitting has been suggested for other human applications. PMID:19372649
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…
Searching for New Answers: The Application of Task-Technology Fit to E-Textbook Usage
ERIC Educational Resources Information Center
Gerhart, Natalie; Peak, Daniel A.; Prybutok, Victor R.
2015-01-01
Students have been slow to adopt e-textbooks even though they are often less expensive than traditional textbooks. Prior e-textbook research has focused on adoption behavior, with little research to date on how students perceive e-textbooks fitting their needs. This work builds upon Task-Technology Fit (TTF) and Consumer Acceptance and Use of…
NASA Astrophysics Data System (ADS)
Nättilä, J.; Miller, M. C.; Steiner, A. W.; Kajava, J. J. E.; Suleimanov, V. F.; Poutanen, J.
2017-12-01
Observations of thermonuclear X-ray bursts from accreting neutron stars (NSs) in low-mass X-ray binary systems can be used to constrain NS masses and radii. Most previous work of this type has set these constraints using Planck function fits as a proxy: the models and the data are both fit with diluted blackbody functions to yield normalizations and temperatures that are then compared with each other. For the first time, we here fit atmosphere models of X-ray bursting NSs directly to the observed spectra. We present a hierarchical Bayesian fitting framework that uses current X-ray bursting NS atmosphere models with realistic opacities and relativistic exact Compton scattering kernels as a model for the surface emission. We test our approach against synthetic data and find that for data that are well described by our model, we can obtain robust radius, mass, distance, and composition measurements. We then apply our technique to Rossi X-ray Timing Explorer observations of five hard-state X-ray bursts from 4U 1702-429. Our joint fit to all five bursts shows that the theoretical atmosphere models describe the data well, but there are still some unmodeled features in the spectrum corresponding to a relative error of 1-5% of the energy flux. After marginalizing over this intrinsic scatter, we find that at 68% credibility, the circumferential radius of the NS in 4U 1702-429 is R = 12.4±0.4 km, the gravitational mass is M = 1.9±0.3 M⊙, the distance is 5.1 < D/ kpc < 6.2, and the hydrogen mass fraction is X < 0.09.
Log-normal frailty models fitted as Poisson generalized linear mixed models.
Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver
2016-12-01
The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Snug as a Bug: Goodness of Fit and Quality of Models.
Jupiter, Daniel C
In elucidating risk factors, or attempting to make predictions about the behavior of subjects in our biomedical studies, we often build statistical models. These models are meant to capture some aspect of reality, or some real-world process underlying the phenomena we are examining. However, no model is perfect, and it is thus important to have tools to assess how accurate models are. In this commentary, we delve into the various roles that our models can play. Then we introduce the notion of the goodness of fit of models and lay the ground work for further study of diagnostic tests for assessing both the fidelity of our models and the statistical assumptions underlying them. Copyright © 2017 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.
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.
Correlated parameter fit of arrhenius model for thermal denaturation of proteins and cells.
Qin, Zhenpeng; Balasubramanian, Saravana Kumar; Wolkers, Willem F; Pearce, John A; Bischof, John C
2014-12-01
Thermal denaturation of proteins is critical to cell injury, food science and other biomaterial processing. For example protein denaturation correlates strongly with cell death by heating, and is increasingly of interest in focal thermal therapies of cancer and other diseases at temperatures which often exceed 50 °C. The Arrhenius model is a simple yet widely used model for both protein denaturation and cell injury. To establish the utility of the Arrhenius model for protein denaturation at 50 °C and above its sensitivities to the kinetic parameters (activation energy E a and frequency factor A) were carefully examined. We propose a simplified correlated parameter fit to the Arrhenius model by treating E a, as an independent fitting parameter and allowing A to follow dependently. The utility of the correlated parameter fit is demonstrated on thermal denaturation of proteins and cells from the literature as a validation, and new experimental measurements in our lab using FTIR spectroscopy to demonstrate broad applicability of this method. Finally, we demonstrate that the end-temperature within which the denaturation is measured is important and changes the kinetics. Specifically, higher E a and A parameters were found at low end-temperature (50 °C) and reduce as end-temperatures increase to 70 °C. This trend is consistent with Arrhenius parameters for cell injury in the literature that are significantly higher for clonogenics (45-50 °C) vs. membrane dye assays (60-70 °C). Future opportunities to monitor cell injury by spectroscopic measurement of protein denaturation are discussed.
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
Correlated Parameter Fit of Arrhenius Model for Thermal Denaturation of Proteins and Cells
Qin, Zhenpeng; Balasubramanian, Saravana Kumar; Wolkers, Willem F.; Pearce, John A.; Bischof, John C.
2014-01-01
Thermal denaturation of proteins is critical to cell injury, food science and other biomaterial processing. For example protein denaturation correlates strongly with cell death by heating, and is increasingly of interest in focal thermal therapies of cancer and other diseases at temperatures which often exceed 50 °C. The Arrhenius model is a simple yet widely used model for both protein denaturation and cell injury. To establish the utility of the Arrhenius model for protein denaturation at 50 °C and above its sensitivities to the kinetic parameters (activation energy Ea and frequency factor A) were carefully examined. We propose a simplified correlated parameter fit to the Arrhenius model by treating Ea, as an independent fitting parameter and allowing A to follow dependently. The utility of the correlated parameter fit is demonstrated on thermal denaturation of proteins and cells from the literature as a validation, and new experimental measurements in our lab using FTIR spectroscopy to demonstrate broad applicability of this method. Finally, we demonstrate that the end-temperature within which the denaturation is measured is important and changes the kinetics. Specifically, higher Ea and A parameters were found at low end-temperature (50°C) and reduce as end-temperatures increase to 70 °C. This trend is consistent with Arrhenius parameters for cell injury in the literature that are significantly higher for clonogenics (45 – 50 °C) vs. membrane dye assays (60 –70 °C). Future opportunities to monitor cell injury by spectroscopic measurement of protein denaturation are discussed. PMID:25205396
NASA Astrophysics Data System (ADS)
Yang, Wen; Fung, Richard Y. K.
2014-06-01
This article considers an order acceptance problem in a make-to-stock manufacturing system with multiple demand classes in a finite time horizon. Demands in different periods are random variables and are independent of one another, and replenishments of inventory deviate from the scheduled quantities. The objective of this work is to maximize the expected net profit over the planning horizon by deciding the fraction of the demand that is going to be fulfilled. This article presents a stochastic order acceptance optimization model and analyses the existence of the optimal promising policies. An example of a discrete problem is used to illustrate the policies by applying the dynamic programming method. In order to solve the continuous problems, a heuristic algorithm based on stochastic approximation (HASA) is developed. Finally, the computational results of a case example illustrate the effectiveness and efficiency of the HASA approach, and make the application of the proposed model readily acceptable.
Coutu, Marie-France; Légaré, France; Durand, Marie-José; Stacey, Dawn; Labrecque, Marie-Elise; Corbière, Marc; Bainbridge, Lesley
2018-04-16
Purpose To establish the acceptability and feasibility of implementing a shared decision-making (SDM) model in work rehabilitation. Methods We used a sequential mixed-methods design with diverse stakeholder groups (representatives of private and public employers, insurers, and unions, as well as workers having participated in a work rehabilitation program). First, a survey using a self-administered questionnaire enabled stakeholders to rate their level of agreement with the model's acceptability and feasibility and propose modifications, if necessary. Second, eight focus groups representing key stakeholders (n = 34) and four one-on-one interviews with workers were conducted, based on the questionnaire results. For each stakeholder group, we computed the percentage of agreement with the model's acceptability and feasibility and performed thematic analyses of the transcripts. Results Less than 50% of each stakeholder group initially agreed with the overall acceptability and feasibility of the model. Stakeholders proposed 37 modifications to the objectives, 17 to the activities, and 39 to improve the model's feasibility. Based on in-depth analysis of the transcripts, indicators were added to one objective, an interview guide was added as proposed by insurers to ensure compliance of the SDM process with insurance contract requirements, and one objective was reformulated. Conclusion Despite initially low agreement with the model's acceptability on the survey, subsequent discussions led to three minor changes and contributed to the model's ultimate acceptability and feasibility. Later steps will involve assessing the extent of implementation of the model in real rehabilitation settings to see if other modifications are necessary before assessing its impact.
Multiple organ definition in CT using a Bayesian approach for 3D model fitting
NASA Astrophysics Data System (ADS)
Boes, Jennifer L.; Weymouth, Terry E.; Meyer, Charles R.
1995-08-01
Organ definition in computed tomography (CT) is of interest for treatment planning and response monitoring. We present a method for organ definition using a priori information about shape encoded in a set of biometric organ models--specifically for the liver and kidney-- that accurately represents patient population shape information. Each model is generated by averaging surfaces from a learning set of organ shapes previously registered into a standard space defined by a small set of landmarks. The model is placed in a specific patient's data set by identifying these landmarks and using them as the basis for model deformation; this preliminary representation is then iteratively fit to the patient's data based on a Bayesian formulation of the model's priors and CT edge information, yielding a complete organ surface. We demonstrate this technique using a set of fifteen abdominal CT data sets for liver surface definition both before and after the addition of a kidney model to the fitting; we demonstrate the effectiveness of this tool for organ surface definition in this low-contrast domain.
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
Multidisciplinary Teamwork in Autism: Can One Size Fit All?
ERIC Educational Resources Information Center
Dillenburger, Karola; Röttgers, Hanns-Rüdiger; Dounavi, Katerina; Sparkman, Coleen; Keenan, Mickey; Thyer, Bruce; Nikopoulos, Christos
2014-01-01
Multidisciplinary practice has become an accepted approach in many education and social and health care fields. In fact, the right to a multidisciplinary assessment is enshrined in the United Nations Convention of the Rights for Persons with Disabilities (United Nations, 2007). In order to avert a "one size fits all" response to…
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
Acceptance threshold theory can explain occurrence of homosexual behaviour.
Engel, Katharina C; Männer, Lisa; Ayasse, Manfred; Steiger, Sandra
2015-01-01
Same-sex sexual behaviour (SSB) has been documented in a wide range of animals, but its evolutionary causes are not well understood. Here, we investigated SSB in the light of Reeve's acceptance threshold theory. When recognition is not error-proof, the acceptance threshold used by males to recognize potential mating partners should be flexibly adjusted to maximize the fitness pay-off between the costs of erroneously accepting males and the benefits of accepting females. By manipulating male burying beetles' search time for females and their reproductive potential, we influenced their perceived costs of making an acceptance or rejection error. As predicted, when the costs of rejecting females increased, males exhibited more permissive discrimination decisions and showed high levels of SSB; when the costs of accepting males increased, males were more restrictive and showed low levels of SSB. Our results support the idea that in animal species, in which the recognition cues of females and males overlap to a certain degree, SSB is a consequence of an adaptive discrimination strategy to avoid the costs of making rejection errors. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Crespo, José E; Castelo, Marcela K
2009-11-01
The robber fly Mallophora ruficauda is one of the principal pests of apiculture in the Pampas region of Argentina. As adults they prey on honey bees and other insects, while as larvae they are solitary ectoparasitoids of third instar scarab beetle larvae. Females of M. ruficauda lay eggs away from the host in tall grasses. After being dispersed by the wind, larvae drop to the ground, where they dig in search of their hosts. It is known that second instar larvae of M. ruficauda exhibit active host searching behaviour towards its preferred host, third instar larva of Cyclocephala signaticollis. Although the means by which host location occurs has been studied and since superparasitism is a frequent scenario in the field, no information about host discrimination and host acceptance is available. We carried out studies in the field and behavioural experiments in the laboratory to determine if M. ruficauda is capable of quality host discrimination. We also studied if this parasitoid is capable of conspecific detection in order to avoid superparasitism. Finally, we analyzed the conditions under which superparasitism occurs in the field. We report here that the second instar larva of M. ruficauda is able to discriminate the parasitism status of the host by means of chemical cues, but is not capable of detecting conspecifics prior to attacking a host. We also found that the host cannot detect the presence of the parasitoid by means of chemical cues, so that no counter-defense against parasitism occurs. Furthermore, we determined that superparasitism occurs on the heavier hosts, i.e. those with more abundant resources which could harbor several parasitoid individuals. Finally, we discuss the possible implications of larval host location and host discrimination decisions on the fitness of this parasitoid.
Fitting of dynamic recurrent neural network models to sensory stimulus-response data.
Doruk, R Ozgur; Zhang, Kechen
2018-06-02
We present a theoretical study aiming at model fitting for sensory neurons. Conventional neural network training approaches are not applicable to this problem due to lack of continuous data. Although the stimulus can be considered as a smooth time-dependent variable, the associated response will be a set of neural spike timings (roughly the instants of successive action potential peaks) that have no amplitude information. A recurrent neural network model can be fitted to such a stimulus-response data pair by using the maximum likelihood estimation method where the likelihood function is derived from Poisson statistics of neural spiking. The universal approximation feature of the recurrent dynamical neuron network models allows us to describe excitatory-inhibitory characteristics of an actual sensory neural network with any desired number of neurons. The stimulus data are generated by a phased cosine Fourier series having a fixed amplitude and frequency but a randomly shot phase. Various values of amplitude, stimulus component size, and sample size are applied in order to examine the effect of the stimulus to the identification process. Results are presented in tabular and graphical forms at the end of this text. In addition, to demonstrate the success of this research, a study involving the same model, nominal parameters and stimulus structure, and another study that works on different models are compared to that of this research.
Cimperman, Miha; Makovec Brenčič, Maja; Trkman, Peter
2016-06-01
Although telehealth offers an improved approach to providing healthcare services, its adoption by end users remains slow. With an older population as the main target, these traditionally conservative users pose a big challenge to the successful implementation of innovative telehealth services. The objective of this study was to develop and empirically test a model for predicting the factors affecting older users' acceptance of Home Telehealth Services (HTS). A survey instrument was administered to 400 participants aged 50 years and above from both rural and urban environments in Slovenia. Structural equation modeling was applied to analyze the causal effect of seven hypothesized predicting factors. HTS were introduced as a bundle of functionalities, representing future services that currently do not exist. This enabled users' perceptions to be measured on the conceptual level, rather than attitudes to a specific technical solution. Six relevant predictors were confirmed in older users' HTS acceptance behavior, with Performance Expectancy (r=0.30), Effort Expectancy (r=0.49), Facilitating Conditions (r=0.12), and Perceived Security (r=0.16) having a direct impact on behavioral intention to use HTS. In addition, Computer Anxiety is positioned as an antecedent of Effort Expectancy with a strong negative influence (r=-0.61), and Doctor's Opinion influence showed a strong impact on Performance Expectancy (r=0.31). The results also indicate Social Influence as an irrelevant predictor of acceptance behavior. The model of six predictors yielded 77% of the total variance explained in the final measured Behavioral Intention to Use HTS by older adults. The level at which HTS are perceived as easy to use and manage is the leading acceptance predictor in older users' HTS acceptance. Together with Perceived Usefulness and Perceived Security, these three factors represent the key influence on older people's HTS acceptance behavior. When promoting HTS, interventions should focus
Hossain, Nazmul; Yokota, Fumihiko; Sultana, Nazneen; Ahmed, Ashir
2018-04-17
Existing studies regarding e-health are mostly focused on information technology design and implementation, system architecture and infrastructure, and its importance in public health with ancillaries and barriers to mass adoption. However, not enough studies have been conducted to assess the end-users' reaction and acceptance behavior toward e-health, especially from the perspective of rural communities in developing countries. The objective of this study is to explore the factors that influence rural end users' acceptance of e-health in Bangladesh. Data were collected between June and July 2016 through a field survey with structured questionnaire form 292 randomly selected rural respondents from Bheramara subdistrict, Bangladesh. Technology Acceptance Model was adopted as the research framework. Logistic regression analysis was performed to test the theoretical model. The study found social reference as the most significantly influential variable (Coef. = 2.28, odds ratio [OR] = 9.73, p < 0.01) followed by advertisement (Coef. = 1.94, OR = 6.94, p < 0.01); attitude toward the system (Coef. = 1.52, OR = 4.56, p < 0.01); access to cellphone (Coef. = 1.37, OR = 3.92, p < 0.05), and perceived system effectiveness (Coef. = 0.74, OR = 2.10, p < 0.01). Among demographic variables, age, gender, and education were found significant while we did not find any significant impact of respondents' monthly family expenditure on their e-health acceptance behavior. The model explains 54.70% deviance (R 2 = 0.5470) in the response variable with its constructs. The "Hosmer-Lemeshow" goodness-of-fit score (0.539) is also above the standard threshold (0.05), which indicates that the data fit well with the model. The study provides guidelines for the successful adoption of e-health among rural communities in developing countries. This also creates an opportunity for e-health technology developers and service providers to have a better
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…
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.
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.
Molitor, John
2012-03-01
Bayesian methods have seen an increase in popularity in a wide variety of scientific fields, including epidemiology. One of the main reasons for their widespread application is the power of the Markov chain Monte Carlo (MCMC) techniques generally used to fit these models. As a result, researchers often implicitly associate Bayesian models with MCMC estimation procedures. However, Bayesian models do not always require Markov-chain-based methods for parameter estimation. This is important, as MCMC estimation methods, while generally quite powerful, are complex and computationally expensive and suffer from convergence problems related to the manner in which they generate correlated samples used to estimate probability distributions for parameters of interest. In this issue of the Journal, Cole et al. (Am J Epidemiol. 2012;175(5):368-375) present an interesting paper that discusses non-Markov-chain-based approaches to fitting Bayesian models. These methods, though limited, can overcome some of the problems associated with MCMC techniques and promise to provide simpler approaches to fitting Bayesian models. Applied researchers will find these estimation approaches intuitively appealing and will gain a deeper understanding of Bayesian models through their use. However, readers should be aware that other non-Markov-chain-based methods are currently in active development and have been widely published in other fields.
ERIC Educational Resources Information Center
Augustus-Horvath, Casey L.; Tylka, Tracy L.
2011-01-01
The acceptance model of intuitive eating (Avalos & Tylka, 2006) posits that body acceptance by others helps women appreciate their body and resist adopting an observer's perspective of their body, which contribute to their eating intuitively/adaptively. We extended this model by integrating body mass index (BMI) into its structure and…
Duarte, Adam; Adams, Michael J.; Peterson, James T.
2018-01-01
Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic assumptions are violated. Moreover, diagnostics to identify when bias in parameter estimates from N-mixture models is likely is largely unexplored. We simulated count data sets using 837 combinations of detection probability, number of sample units, number of survey occasions, and type and extent of heterogeneity in abundance or detectability. We fit Poisson N-mixture models to these data, quantified the bias associated with each combination, and evaluated if the parametric bootstrap goodness-of-fit (GOF) test can be used to indicate bias in parameter estimates. We also explored if assumption violations can be diagnosed prior to fitting N-mixture models. In doing so, we propose a new model diagnostic, which we term the quasi-coefficient of variation (QCV). N-mixture models performed well when assumptions were met and detection probabilities were moderate (i.e., ≥0.3), and the performance of the estimator improved with increasing survey occasions and sample units. However, the magnitude of bias in estimated mean abundance with even slight amounts of unmodeled heterogeneity was substantial. The parametric bootstrap GOF test did not perform well as a diagnostic for bias in parameter estimates when detectability and sample sizes were low. The results indicate the QCV is useful to diagnose potential bias and that potential bias associated with unidirectional trends in abundance or detectability can be diagnosed using Poisson regression. This study represents the most thorough assessment to date of assumption violations and diagnostics when fitting N-mixture models using the most commonly implemented error distribution. Unbiased estimates of population state variables are needed to properly inform management decision
Decision making on fitness landscapes
NASA Astrophysics Data System (ADS)
Arthur, R.; Sibani, P.
2017-04-01
We discuss fitness landscapes and how they can be modified to account for co-evolution. We are interested in using the landscape as a way to model rational decision making in a toy economic system. We develop a model very similar to the Tangled Nature Model of Christensen et al. that we call the Tangled Decision Model. This is a natural setting for our discussion of co-evolutionary fitness landscapes. We use a Monte Carlo step to simulate decision making and investigate two different decision making procedures.
Asteroid orbit fitting with radar and angular observations
NASA Astrophysics Data System (ADS)
Baturin, A. P.
2013-12-01
The asteroid orbit fitting problem using their radar and angular observations has been considered. The problem was solved in a standanrd way by means of minimization of weighted sum of squares of residuals. In the orbit fitting both kinds of radar observa-tions have been used: the observations of time delays and of Doppler frequency shifts. The weight for angular observations has been set the same for all of them and has been determined as inverse mean-square residual obtained in the orbit fitting using just angular observations. The weights of radar observations have been set as inverse squared errors of these observations published together with them in the Minor Planet Center electronical circulars (MPECs). For the orbit fitting some five asteroids have been taken from these circulars. The asteroids have been chosen fulfilling the requirement of more than six radar observations of them to be available. The asteroids are 1950 DA, 1999 RQ36, 2002 NY40, 2004 DC and 2005 EU2. Several orbit fittings for these aster-oids have been done: with just angular observations; with just radar observations; with both angular and radar observations. The obtained results are quite acceptable because in the last case the mean-square angular residuals are approximately equal to the same ones obtained in the fitting with just angular observations. As to radar observations mean-square residuals, the time delay residuals for three asteroids do not exceed 1 μs, for two others ˜ 10 μs and the Doppler shift residuals for three asteroids do not exceed 1 Hz, for two others ˜ 10 Hz. The motion equations included perturbations from 9 planets and the Moon using their ephemerides DE422. The numerical integration has been performed with Everhart 27-order method with variable step. All calculations have been exe-cuted to a 34-digit decimal precision (i.e. using 128-bit floating-point numbers). Further, the sizes of confidence ellipsoids of im-proved orbit parameters have been compared. It
Zhang, Z; Jewett, D L
1994-01-01
Due to model misspecification, currently-used Dipole Source Localization (DSL) methods may contain Multiple-Generator Errors (MulGenErrs) when fitting simultaneously-active dipoles. The size of the MulGenErr is a function of both the model used, and the dipole parameters, including the dipoles' waveforms (time-varying magnitudes). For a given fitting model, by examining the variation of the MulGenErrs (or the fit parameters) under different waveforms for the same generating-dipoles, the accuracy of the fitting model for this set of dipoles can be determined. This method of testing model misspecification can be applied to evoked potential maps even when the parameters of the generating-dipoles are unknown. The dipole parameters fitted in a model should only be accepted if the model can be shown to be sufficiently accurate.
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…
FIT: statistical modeling tool for transcriptome dynamics under fluctuating field conditions
Iwayama, Koji; Aisaka, Yuri; Kutsuna, Natsumaro
2017-01-01
Abstract Motivation: Considerable attention has been given to the quantification of environmental effects on organisms. In natural conditions, environmental factors are continuously changing in a complex manner. To reveal the effects of such environmental variations on organisms, transcriptome data in field environments have been collected and analyzed. Nagano et al. proposed a model that describes the relationship between transcriptomic variation and environmental conditions and demonstrated the capability to predict transcriptome variation in rice plants. However, the computational cost of parameter optimization has prevented its wide application. Results: We propose a new statistical model and efficient parameter optimization based on the previous study. We developed and released FIT, an R package that offers functions for parameter optimization and transcriptome prediction. The proposed method achieves comparable or better prediction performance within a shorter computational time than the previous method. The package will facilitate the study of the environmental effects on transcriptomic variation in field conditions. Availability and Implementation: Freely available from CRAN (https://cran.r-project.org/web/packages/FIT/). Contact: anagano@agr.ryukoku.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online PMID:28158396
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,…
ERIC Educational Resources Information Center
Seiverling, Laura; Harclerode, Whitney; Williams, Keith
2014-01-01
The purpose of this study was to examine if sequential presentation with feeder modeling would lead to an increase in bites accepted of new foods compared to sequential presentation without feeder modeling in a typically developing 4-year-old boy with food selectivity. The participant's acceptance of novel foods increased both in the modeling and…
Using SAS PROC CALIS to fit Level-1 error covariance structures of latent growth models.
Ding, Cherng G; Jane, Ten-Der
2012-09-01
In the present article, we demonstrates the use of SAS PROC CALIS to fit various types of Level-1 error covariance structures of latent growth models (LGM). Advantages of the SEM approach, on which PROC CALIS is based, include the capabilities of modeling the change over time for latent constructs, measured by multiple indicators; embedding LGM into a larger latent variable model; incorporating measurement models for latent predictors; and better assessing model fit and the flexibility in specifying error covariance structures. The strength of PROC CALIS is always accompanied with technical coding work, which needs to be specifically addressed. We provide a tutorial on the SAS syntax for modeling the growth of a manifest variable and the growth of a latent construct, focusing the documentation on the specification of Level-1 error covariance structures. Illustrations are conducted with the data generated from two given latent growth models. The coding provided is helpful when the growth model has been well determined and the Level-1 error covariance structure is to be identified.
Mavroidis, Panayiotis; Pearlstein, Kevin A; Dooley, John; Sun, Jasmine; Saripalli, Srinivas; Das, Shiva K; Wang, Andrew Z; Chen, Ronald C
2018-02-02
To estimate the radiobiological parameters of three popular normal tissue complication probability (NTCP) models, which describe the dose-response relations of bladder regarding different acute urinary symptoms during post-prostatectomy radiotherapy (RT). To evaluate the goodness-of-fit and the correlation of those models with those symptoms. Ninety-three consecutive patients treated from 2010 to 2015 with post-prostatectomy image-guided intensity modulated radiotherapy (IMRT) were included in this study. Patient-reported urinary symptoms were collected pre-RT and weekly during treatment using the validated Prostate Cancer Symptom Indices (PCSI). The assessed symptoms were flow, dysuria, urgency, incontinence, frequency and nocturia using a Likert scale of 1 to 4 or 5. For this analysis, an increase by ≥2 levels in a symptom at any time during treatment compared to baseline was considered clinically significant. The dose volume histograms of the bladder were calculated. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS) and Logit NTCP models were used to fit the clinical data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC), Akaike information criterion (AIC) and Odds Ratio methods. For the symptoms of urinary urgency, leakage, frequency and nocturia, the derived LKB model parameters were: 1) D 50 = 64.2Gy, m = 0.50, n = 1.0; 2) D 50 = 95.0Gy, m = 0.45, n = 0.50; 3) D 50 = 83.1Gy, m = 0.56, n = 1.00; and 4) D 50 = 85.4Gy, m = 0.60, n = 1.00, respectively. The AUC values for those symptoms were 0.66, 0.58, 0.64 and 0.64, respectively. The differences in AIC between the different models were less than 2 and ranged within 0.1 and 1.3. Different dose metrics were correlated with the symptoms of urgency, incontinence, frequency and nocturia. The symptoms of urinary flow and dysuria were poorly associated with dose. The values of the
Measuring fit of sequence data to phylogenetic model: gain of power using marginal tests.
Waddell, Peter J; Ota, Rissa; Penny, David
2009-10-01
Testing fit of data to model is fundamentally important to any science, but publications in the field of phylogenetics rarely do this. Such analyses discard fundamental aspects of science as prescribed by Karl Popper. Indeed, not without cause, Popper (Unended quest: an intellectual autobiography. Fontana, London, 1976) once argued that evolutionary biology was unscientific as its hypotheses were untestable. Here we trace developments in assessing fit from Penny et al. (Nature 297:197-200, 1982) to the present. We compare the general log-likelihood ratio (the G or G (2) statistic) statistic between the evolutionary tree model and the multinomial model with that of marginalized tests applied to an alignment (using placental mammal coding sequence data). It is seen that the most general test does not reject the fit of data to model (P approximately 0.5), but the marginalized tests do. Tests on pairwise frequency (F) matrices, strongly (P < 0.001) reject the most general phylogenetic (GTR) models commonly in use. It is also clear (P < 0.01) that the sequences are not stationary in their nucleotide composition. Deviations from stationarity and homogeneity seem to be unevenly distributed amongst taxa; not necessarily those expected from examining other regions of the genome. By marginalizing the 4( t ) patterns of the i.i.d. model to observed and expected parsimony counts, that is, from constant sites, to singletons, to parsimony informative characters of a minimum possible length, then the likelihood ratio test regains power, and it too rejects the evolutionary model with P < 0.001. Given such behavior over relatively recent evolutionary time, readers in general should maintain a healthy skepticism of results, as the scale of the systematic errors in published trees may really be far larger than the analytical methods (e.g., bootstrap) report.
The Role of Psychopathy and Exposure to Violence in Rape Myth Acceptance.
Debowska, Agata; Boduszek, Daniel; Dhingra, Katie; Kola, Susanna; Meller-Prunska, Aleksandra
2015-09-01
The main aim of the present study was to specify and test a structural model to examine the relationships between four psychopathy dimensions (Interpersonal Manipulation, Callous Affect, Erratic Lifestyle, and Antisocial Behavior), childhood exposure to violence, and rape myth acceptance while controlling for gender, age, sample type (prisoner vs. non-prisoner), and relationship status. Participants were a sample of non-offending adults (n = 319) recruited from the University of Security in Poznan, and a sample of prisoners (n = 129) incarcerated in Stargard Szczecinski Prison. Results indicated that the model provided a good fit for the data, and that Callous Affect and childhood exposure to violence had a significant positive effect on attitudes toward rape and rape victims. Theoretical and practical implications of our findings are discussed. © The Author(s) 2014.
Stojek, Monika M K; Montoya, Amanda K; Drescher, Christopher F; Newberry, Andrew; Sultan, Zain; Williams, Celestine F; Pollock, Norman K; Davis, Catherine L
We used mediation models to examine the mechanisms underlying the relationships among physical fitness, sleep-disordered breathing (SDB), symptoms of depression, and cognitive functioning. We conducted a cross-sectional secondary analysis of the cohorts involved in the 2003-2006 project PLAY (a trial of the effects of aerobic exercise on health and cognition) and the 2008-2011 SMART study (a trial of the effects of exercise on cognition). A total of 397 inactive overweight children aged 7-11 received a fitness test, standardized cognitive test (Cognitive Assessment System, yielding Planning, Attention, Simultaneous, Successive, and Full Scale scores), and depression questionnaire. Parents completed a Pediatric Sleep Questionnaire. We used bootstrapped mediation analyses to test whether SDB mediated the relationship between fitness and depression and whether SDB and depression mediated the relationship between fitness and cognition. Fitness was negatively associated with depression ( B = -0.041; 95% CI, -0.06 to -0.02) and SDB ( B = -0.005; 95% CI, -0.01 to -0.001). SDB was positively associated with depression ( B = 0.99; 95% CI, 0.32 to 1.67) after controlling for fitness. The relationship between fitness and depression was mediated by SDB (indirect effect = -0.005; 95% CI, -0.01 to -0.0004). The relationship between fitness and the attention component of cognition was independently mediated by SDB (indirect effect = 0.058; 95% CI, 0.004 to 0.13) and depression (indirect effect = -0.071; 95% CI, -0.01 to -0.17). SDB mediates the relationship between fitness and depression, and SDB and depression separately mediate the relationship between fitness and the attention component of cognition.
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.
From Passive Acceptance to Active Commitment: A Model of Feminist Identity Development for Women.
ERIC Educational Resources Information Center
Downing, Nancy E.; Roush, Kristin L.
1985-01-01
Presents a model of feminist identity development for women, derived, in part, from Cross's (1971) theory of Black identity development. The stages in this process include passive acceptance, revelation, embeddedness-emanation, synthesis, and active commitment. Implications of the model are outlined for women, nonsexist and feminist…
Calibrating White Dwarf Asteroseismic Fitting Techniques
NASA Astrophysics Data System (ADS)
Castanheira, B. G.; Romero, A. D.; Bischoff-Kim, A.
2017-03-01
The main goal of looking for intrinsic variability in stars is the unique opportunity to study their internal structure. Once we have extracted independent modes from the data, it appears to be a simple matter of comparing the period spectrum with those from theoretical model grids to learn the inner structure of that star. However, asteroseismology is much more complicated than this simple description. We must account not only for observational uncertainties in period determination, but most importantly for the limitations of the model grids, coming from the uncertainties in the constitutive physics, and of the fitting techniques. In this work, we will discuss results of numerical experiments where we used different independently calculated model grids (white dwarf cooling models WDEC and fully evolutionary LPCODE-PUL) and fitting techniques to fit synthetic stars. The advantage of using synthetic stars is that we know the details of their interior structure so we can assess how well our models and fitting techniques are able to the recover the interior structure, as well as the stellar parameters.
Cortical bone viscoelasticity and fixation strength of press-fit femoral stems: an in-vitro model.
Norman, T L; Ackerman, E S; Smith, T S; Gruen, T A; Yates, A J; Blaha, J D; Kish, V L
2006-02-01
Cementless total hip femoral components rely on press-fit for initial stability and bone healing and remodeling for secondary fixation. However, the determinants of satisfactory press-fit are not well understood. In previous studies, human cortical bone loaded circumferentially to simulate press-fit exhibited viscoelastic, or time dependent, behavior. The effect of bone viscoelastic behavior on the initial stability of press-fit stems is not known. Therefore, in the current study, push-out loads of cylindrical stems press-fit into reamed cadaver diaphyseal femoral specimens were measured immediately after assembly and 24 h with stem-bone diametral interference and stem surface treatment as independent variables. It was hypothesized that stem-bone interference would result in a viscoelastic response of bone that would decrease push-out load thereby impairing initial press-fit stability. Results showed that push-out load significantly decreased over a 24 h period due to bone viscoelasticity. It was also found that high and low push-out loads occurred at relatively small amounts of stem-bone interference, but a relationship between stem-bone interference and push-out load could not be determined due to variability among specimens. On the basis of this model, it was concluded that press-fit fixation can occur at relatively low levels of diametral interference and that stem-bone interference elicits viscoelastic response that reduces stem stability over time. From a clinical perspective, these results suggest that there could be large variations in initial press-fit fixation among patients.
Hsu, Hsien-Yuan; Lin, Jr-Hung; Kwok, Oi-Man; Acosta, Sandra; Willson, Victor
2016-01-01
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 fit indices. Our study proposed to fill this gap in the methodological literature. A Monte Carlo study was conducted to investigate the performance of (a) level-specific fit indices derived by a partially saturated model method (e.g., CFIPS_B and CFIPS_W) and (b) SRMRW and SRMRB in terms of their performance in multilevel structural equation models across varying ICCs. The design factors included intraclass correlation (ICC: ICC1 = 0.091 to ICC6 = 0.500), numbers of groups in between-level models (NG: 50, 100, 200, and 1,000), group size (GS: 30, 50, and 100), and type of misspecification (no misspecification, between-level misspecification, and within-level misspecification). Our simulation findings raise a concern regarding the performance of between-level-specific partial saturated fit indices in low ICC conditions: the performances of both TLIPS_B and RMSEAPS_B were more influenced by ICC compared with CFIPS_B and SRMRB. However, when traditional cutoff values (RMSEA≤ 0.06; CFI, TLI≥ 0.95; SRMR≤ 0.08) were applied, CFIPS_B and TLIPS_B were still able to detect misspecified between-level models even when ICC was as low as 0.091 (ICC1). On the other hand, both RMSEAPS_B and SRMRB were not recommended under low ICC conditions. PMID:29795901
ERIC Educational Resources Information Center
Chan, Wai
2007-01-01
In social science research, an indirect effect occurs when the influence of an antecedent variable on the effect variable is mediated by an intervening variable. To compare indirect effects within a sample or across different samples, structural equation modeling (SEM) can be used if the computer program supports model fitting with nonlinear…
Gunsoy, S; Ulusoy, M
2016-01-01
The purpose of this study was to evaluate the internal and marginal fit of chrome cobalt (Co-Cr) crowns were fabricated with laser sintering, computer-aided design (CAD) and computer-aided manufacturing, and conventional methods. Polyamide master and working models were designed and fabricated. The models were initially designed with a software application for three-dimensional (3D) CAD (Maya, Autodesk Inc.). All models were fabricated models were produced by a 3D printer (EOSINT P380 SLS, EOS). 128 1-unit Co-Cr fixed dental prostheses were fabricated with four different techniques: Conventional lost wax method, milled wax with lost-wax method (MWLW), direct laser metal sintering (DLMS), and milled Co-Cr (MCo-Cr). The cement film thickness of the marginal and internal gaps was measured by an observer using a stereomicroscope after taking digital photos in ×24. Best fit rates according to mean and standard deviations of all measurements was in DLMS both in premolar (65.84) and molar (58.38) models in μm. A significant difference was found DLMS and the rest of fabrication techniques (P < 0.05). No significant difference was found between MCo-CR and MWLW in all fabrication techniques both in premolar and molar models (P > 0.05). DMLS was best fitting fabrication techniques for single crown based on the results.The best fit was found in marginal; the larger gap was found in occlusal.All groups were within the clinically acceptable misfit range.
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
Cowin, Leanne S; Moroney, Robyn
2018-01-01
Sessional academic staff are an important part of nursing education. Increases in casualisation of the academic workforce continue and satisfaction with the job role is an important bench mark for quality curricula delivery and influences recruitment and retention. This study examined relations between four job constructs - organisation fit, organisation support, staff role and job satisfaction for Sessional Academic Staff at a School of Nursing by creating two path analysis models. A cross-sectional correlational survey design was utilised. Participants who were currently working as sessional or casual teaching staff members were invited to complete an online anonymous survey. The data represents a convenience sample of Sessional Academic Staff in 2016 at a large school of Nursing and Midwifery in Australia. After psychometric evaluation of each of the job construct measures in this study we utilised Structural Equation Modelling to better understand the relations of the variables. The measures used in this study were found to be both valid and reliable for this sample. Job support and job fit are positively linked to job satisfaction. Although the hypothesised model did not meet model fit standards, a new 'nested' model made substantive sense. This small study explored a new scale for measuring academic job role, and demonstrated how it promotes the constructs of job fit and job supports. All four job constructs are important in providing job satisfaction - an outcome that in turn supports staffing stability, retention, and motivation.
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).
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.
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. Copyright © 2015 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ding, Tao; Li, Cheng; Huang, Can
Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less
Permutation tests for goodness-of-fit testing of mathematical models to experimental data.
Fişek, M Hamit; Barlas, Zeynep
2013-03-01
This paper presents statistical procedures for improving the goodness-of-fit testing of theoretical models to data obtained from laboratory experiments. We use an experimental study in the expectation states research tradition which has been carried out in the "standardized experimental situation" associated with the program to illustrate the application of our procedures. We briefly review the expectation states research program and the fundamentals of resampling statistics as we develop our procedures in the resampling context. The first procedure we develop is a modification of the chi-square test which has been the primary statistical tool for assessing goodness of fit in the EST research program, but has problems associated with its use. We discuss these problems and suggest a procedure to overcome them. The second procedure we present, the "Average Absolute Deviation" test, is a new test and is proposed as an alternative to the chi square test, as being simpler and more informative. The third and fourth procedures are permutation versions of Jonckheere's test for ordered alternatives, and Kendall's tau(b), a rank order correlation coefficient. The fifth procedure is a new rank order goodness-of-fit test, which we call the "Deviation from Ideal Ranking" index, which we believe may be more useful than other rank order tests for assessing goodness-of-fit of models to experimental data. The application of these procedures to the sample data is illustrated in detail. We then present another laboratory study from an experimental paradigm different from the expectation states paradigm - the "network exchange" paradigm, and describe how our procedures may be applied to this data set. Copyright © 2012 Elsevier Inc. All rights reserved.
Ding, Tao; Li, Cheng; Huang, Can; ...
2017-01-09
Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less
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…
Yusof, Maryati Mohd; Kuljis, Jasna; Papazafeiropoulou, Anastasia; Stergioulas, Lampros K
2008-06-01
The realization of Health Information Systems (HIS) requires rigorous evaluation that addresses technology, human and organization issues. Our review indicates that current evaluation methods evaluate different aspects of HIS and they can be improved upon. A new evaluation framework, human, organization and technology-fit (HOT-fit) was developed after having conducted a critical appraisal of the findings of existing HIS evaluation studies. HOT-fit builds on previous models of IS evaluation--in particular, the IS Success Model and the IT-Organization Fit Model. This paper introduces the new framework for HIS evaluation that incorporates comprehensive dimensions and measures of HIS and provides a technological, human and organizational fit. Literature review on HIS and IS evaluation studies and pilot testing of developed framework. The framework was used to evaluate a Fundus Imaging System (FIS) of a primary care organization in the UK. The case study was conducted through observation, interview and document analysis. The main findings show that having the right user attitude and skills base together with good leadership, IT-friendly environment and good communication can have positive influence on the system adoption. Comprehensive, specific evaluation factors, dimensions and measures in the new framework (HOT-fit) are applicable in HIS evaluation. The use of such a framework is argued to be useful not only for comprehensive evaluation of the particular FIS system under investigation, but potentially also for any Health Information System in general.
10 CFR 26.111 - Checking the acceptability of the urine specimen.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 10 Energy 1 2013-01-01 2013-01-01 false Checking the acceptability of the urine specimen. 26.111 Section 26.111 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Collecting Specimens for..., the collector shall measure the temperature of the specimen. The temperature-measuring device used...
10 CFR 26.111 - Checking the acceptability of the urine specimen.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 10 Energy 1 2012-01-01 2012-01-01 false Checking the acceptability of the urine specimen. 26.111 Section 26.111 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Collecting Specimens for..., the collector shall measure the temperature of the specimen. The temperature-measuring device used...
10 CFR 26.111 - Checking the acceptability of the urine specimen.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 10 Energy 1 2014-01-01 2014-01-01 false Checking the acceptability of the urine specimen. 26.111 Section 26.111 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Collecting Specimens for..., the collector shall measure the temperature of the specimen. The temperature-measuring device used...
Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy
NASA Astrophysics Data System (ADS)
Nabizadeh, Nooshin; John, Nigel
2014-03-01
Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.
Knies, Jennifer L.; Kingsolver, Joel G.
2013-01-01
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 reaction(s) over some physiological temperature range for which all the rate-limiting enzymes are in 100% active conformation. We test this assumption using datasets 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 is 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. PMID:20528477
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.
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…
Anticipating mismatches of HIT investments: Developing a viability-fit model for e-health services.
Mettler, Tobias
2016-01-01
Albeit massive investments in the recent years, the impact of health information technology (HIT) has been controversial and strongly disputed by both research and practice. While many studies are concerned with the development of new or the refinement of existing measurement models for assessing the impact of HIT adoption (ex post), this study presents an initial attempt to better understand the factors affecting viability and fit of HIT and thereby underscores the importance of also having instruments for managing expectations (ex ante). We extend prior research by undertaking a more granular investigation into the theoretical assumptions of viability and fit constructs. In doing so, we use a mixed-methods approach, conducting qualitative focus group discussions and a quantitative field study to improve and validate a viability-fit measurement instrument. Our findings suggest two issues for research and practice. First, the results indicate that different stakeholders perceive HIT viability and fit of the same e-health services very unequally. Second, the analysis also demonstrates that there can be a great discrepancy between the organizational viability and individual fit of a particular e-health service. The findings of this study have a number of important implications such as for health policy making, HIT portfolios, and stakeholder communication. Copyright © 2015. Published by Elsevier Ireland Ltd.
BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments
Thomas, Brandon R.; Chylek, Lily A.; Colvin, Joshua; ...
2015-11-09
Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here in this paper, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive.
Hwang, Ji Young; Kim, Ki Young; Lee, Kang Hyun
2014-12-01
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. 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. 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. Factors that influence the use of telemetry by EMTs in ambulances included patients' clinical factors, as well as complex organizational and environmental factors surrounding the EMTs' occupational environments. This suggests
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
Amino acids intake and physical fitness among adolescents.
Gracia-Marco, Luis; Bel-Serrat, Silvia; Cuenca-Garcia, Magdalena; Gonzalez-Gross, Marcela; Pedrero-Chamizo, Raquel; Manios, Yannis; Marcos, Ascensión; Molnar, Denes; Widhalm, Kurt; Polito, Angela; Vanhelst, Jeremy; Hagströmer, Maria; Sjöström, Michael; Kafatos, Anthony; de Henauw, Stefaan; Gutierrez, Ángel; Castillo, Manuel J; Moreno, Luis A
2017-06-01
The aim was to investigate whether there was an association between amino acid (AA) intake and physical fitness and if so, to assess whether this association was independent of carbohydrates intake. European adolescents (n = 1481, 12.5-17.5 years) were measured. Intake was assessed via two non-consecutive 24-h dietary recalls. Lower and upper limbs muscular fitness was assessed by standing long jump and handgrip strength tests, respectively. Cardiorespiratory fitness was assessed by the 20-m shuttle run test. Physical activity was objectively measured. Socioeconomic status was obtained via questionnaires. Lower limbs muscular fitness seems to be positively associated with tryptophan, histidine and methionine intake in boys, regardless of centre, age, socioeconomic status, physical activity and total energy intake (model 1). However, these associations disappeared once carbohydrates intake was controlled for (model 2). In girls, only proline intake seems to be positively associated with lower limbs muscular fitness (model 2) while cardiorespiratory fitness seems to be positively associated with leucine (model 1) and proline intake (models 1 and 2). None of the observed significant associations remained significant once multiple testing was controlled for. In conclusion, we failed to detect any associations between any of the evaluated AAs and physical fitness after taking into account the effect of multiple testing.
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)…
Ogunleye, Ayodele A; Sandercock, Gavin R; Voss, Christine; Eisenmann, Joey C; Reed, Katharine
2013-11-01
Cardiorespiratory fitness is known to be cardioprotective and its association with the components of the metabolic syndrome in children is becoming clearer. The aim of the present study was to examine the extent to which cardiorespiratory fitness may offset the weight-related association with mean arterial pressure (MAP) in schoolchildren. Cross-sectional study. Schoolchildren from the East of England, U.K. A total of 5983 (48% females) schoolchildren, 10 to 16 years of age, had height, weight and blood pressure measured by standard procedures and cardiorespiratory fitness assessed by the 20 m shuttle-run test. Participants were classified as fit or unfit using internationally accepted fitness cut-off points; and as normal weight, overweight or obese based on BMI, again using international cut-off points. Age-adjusted ANCOVA was used to determine the main effects and interaction of fitness and BMI on MAP Z-score. Logistic regression models were used to estimate odds ratios of elevated MAP. Prevalence of elevated MAP in schoolchildren was 14.8% overall and 35.7% in those who were obese-unfit. Approximately 21% of participants were overweight and 5% obese, while 23% were classified as unfit. MAP generally increased across BMI categories and was higher in the aerobically unfit participants. Obese-fit males had lower MAP compared with obese-unfit males (P < 0.001); this trend was similar in females (P = 0.05). Increasing fitness level may have a positive impact on the weight-related elevations of MAP seen in obese and overweight schoolchildren.
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. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.
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…
FIREFLY (Fitting IteRativEly For Likelihood analYsis): a full spectral fitting code
NASA Astrophysics Data System (ADS)
Wilkinson, David M.; Maraston, Claudia; Goddard, Daniel; Thomas, Daniel; Parikh, Taniya
2017-12-01
We present a new spectral fitting code, FIREFLY, for deriving the stellar population properties of stellar systems. FIREFLY is a chi-squared minimization fitting code that fits combinations of single-burst stellar population models to spectroscopic data, following an iterative best-fitting process controlled by the Bayesian information criterion. No priors are applied, rather all solutions within a statistical cut are retained with their weight. Moreover, no additive or multiplicative polynomials are employed to adjust the spectral shape. This fitting freedom is envisaged in order to map out the effect of intrinsic spectral energy distribution degeneracies, such as age, metallicity, dust reddening on galaxy properties, and to quantify the effect of varying input model components on such properties. Dust attenuation is included using a new procedure, which was tested on Integral Field Spectroscopic data in a previous paper. The fitting method is extensively tested with a comprehensive suite of mock galaxies, real galaxies from the Sloan Digital Sky Survey and Milky Way globular clusters. We also assess the robustness of the derived properties as a function of signal-to-noise ratio (S/N) and adopted wavelength range. We show that FIREFLY is able to recover age, metallicity, stellar mass, and even the star formation history remarkably well down to an S/N ∼ 5, for moderately dusty systems. Code and results are publicly available.1
Van Drunen, Wendy E; van Kleunen, Mark; Dorken, Marcel E
2015-07-21
Clonality is a pervasive feature of sessile organisms, but this form of asexual reproduction is thought to interfere with sexual fitness via the movement of gametes among the modules that comprise the clone. This within-clone movement of gametes is expected to reduce sexual fitness via mate limitation of male reproductive success and, in some cases, via the production of highly inbred (i.e., self-fertilized) offspring. However, clonality also results in the spatial expansion of the genetic individual (i.e., genet), and this should decrease distances gametes and sexually produced offspring must travel to avoid competing with other gametes and offspring from the same clone. The extent to which any negative effects of clonality on mating success might be offset by the positive effects of spatial expansion is poorly understood. Here, we develop spatially explicit models in which fitness was determined by the success of genets through their male and female sex functions. Our results indicate that clonality serves to increase sexual fitness when it is associated with the outward expansion of the genet. Our models further reveal that the main fitness benefit of clonal expansion might occur through the dispersal of offspring over a wider area compared with nonclonal phenotypes. We conclude that, instead of interfering with sexual reproduction, clonal expansion should often serve to enhance sexual fitness.
A critique of Rasch residual fit statistics.
Karabatsos, G
2000-01-01
In test analysis involving the Rasch model, a large degree of importance is placed on the "objective" measurement of individual abilities and item difficulties. The degree to which the objectivity properties are attained, of course, depends on the degree to which the data fit the Rasch model. It is therefore important to utilize fit statistics that accurately and reliably detect the person-item response inconsistencies that threaten the measurement objectivity of persons and items. Given this argument, it is somewhat surprising that there is far more emphasis placed in the objective measurement of person and items than there is in the measurement quality of Rasch fit statistics. This paper provides a critical analysis of the residual fit statistics of the Rasch model, arguably the most often used fit statistics, in an effort to illustrate that the task of Rasch fit analysis is not as simple and straightforward as it appears to be. The faulty statistical properties of the residual fit statistics do not allow either a convenient or a straightforward approach to Rasch fit analysis. For instance, given a residual fit statistic, the use of a single minimum critical value for misfit diagnosis across different testing situations, where the situations vary in sample and test properties, leads to both the overdetection and underdetection of misfit. To improve this situation, it is argued that psychometricians need to implement residual-free Rasch fit statistics that are based on the number of Guttman response errors, or use indices that are statistically optimal in detecting measurement disturbances.
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. Copyright © 2014 Elsevier Ltd. All rights reserved.
Using geometry to improve model fitting and experiment design for glacial isostasy
NASA Astrophysics Data System (ADS)
Kachuck, S. B.; Cathles, L. M.
2017-12-01
As scientists we routinely deal with models, which are geometric objects at their core - the manifestation of a set of parameters as predictions for comparison with observations. When the number of observations exceeds the number of parameters, the model is a hypersurface (the model manifold) in the space of all possible predictions. The object of parameter fitting is to find the parameters corresponding to the point on the model manifold as close to the vector of observations as possible. But the geometry of the model manifold can make this difficult. By curving, ending abruptly (where, for instance, parameters go to zero or infinity), and by stretching and compressing the parameters together in unexpected directions, it can be difficult to design algorithms that efficiently adjust the parameters. Even at the optimal point on the model manifold, parameters might not be individually resolved well enough to be applied to new contexts. In our context of glacial isostatic adjustment, models of sparse surface observations have a broad spread of sensitivity to mixtures of the earth's viscous structure and the surface distribution of ice over the last glacial cycle. This impedes precise statements about crucial geophysical processes, such as the planet's thermal history or the climates that controlled the ice age. We employ geometric methods developed in the field of systems biology to improve the efficiency of fitting (geodesic accelerated Levenberg-Marquardt) and to identify the maximally informative sources of additional data to make better predictions of sea levels and ice configurations (optimal experiment design). We demonstrate this in particular in reconstructions of the Barents Sea Ice Sheet, where we show that only certain kinds of data from the central Barents have the power to distinguish between proposed models.
User acceptance of a touchless sterile system to control virtual orthodontic study models.
Wan Hassan, Wan Nurazreena; Abu Kassim, Noor Lide; Jhawar, Abhishek; Shurkri, Norsyafiqah Mohd; Kamarul Baharin, Nur Azreen; Chan, Chee Seng
2016-04-01
In this article, we present an evaluation of user acceptance of our innovative hand-gesture-based touchless sterile system for interaction with and control of a set of 3-dimensional digitized orthodontic study models using the Kinect motion-capture sensor (Microsoft, Redmond, Wash). The system was tested on a cohort of 201 participants. Using our validated questionnaire, the participants evaluated 7 hand-gesture-based commands that allowed the user to adjust the model in size, position, and aspect and to switch the image on the screen to view the maxillary arch, the mandibular arch, or models in occlusion. Participants' responses were assessed using Rasch analysis so that their perceptions of the usefulness of the hand gestures for the commands could be directly referenced against their acceptance of the gestures. Their perceptions of the potential value of this system for cross-infection control were also evaluated. Most participants endorsed these commands as accurate. Our designated hand gestures for these commands were generally accepted. We also found a positive and significant correlation between our participants' level of awareness of cross infection and their endorsement to use this system in clinical practice. This study supports the adoption of this promising development for a sterile touch-free patient record-management system. Copyright © 2016 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.
vFitness: a web-based computing tool for improving estimation of in vitro HIV-1 fitness experiments
2010-01-01
Background The replication rate (or fitness) between viral variants has been investigated in vivo and in vitro for human immunodeficiency virus (HIV). HIV fitness plays an important role in the development and persistence of drug resistance. The accurate estimation of viral fitness relies on complicated computations based on statistical methods. This calls for tools that are easy to access and intuitive to use for various experiments of viral fitness. Results Based on a mathematical model and several statistical methods (least-squares approach and measurement error models), a Web-based computing tool has been developed for improving estimation of virus fitness in growth competition assays of human immunodeficiency virus type 1 (HIV-1). Conclusions Unlike the two-point calculation used in previous studies, the estimation here uses linear regression methods with all observed data in the competition experiment to more accurately estimate relative viral fitness parameters. The dilution factor is introduced for making the computational tool more flexible to accommodate various experimental conditions. This Web-based tool is implemented in C# language with Microsoft ASP.NET, and is publicly available on the Web at http://bis.urmc.rochester.edu/vFitness/. PMID:20482791
vFitness: a web-based computing tool for improving estimation of in vitro HIV-1 fitness experiments.
Ma, Jingming; Dykes, Carrie; Wu, Tao; Huang, Yangxin; Demeter, Lisa; Wu, Hulin
2010-05-18
The replication rate (or fitness) between viral variants has been investigated in vivo and in vitro for human immunodeficiency virus (HIV). HIV fitness plays an important role in the development and persistence of drug resistance. The accurate estimation of viral fitness relies on complicated computations based on statistical methods. This calls for tools that are easy to access and intuitive to use for various experiments of viral fitness. Based on a mathematical model and several statistical methods (least-squares approach and measurement error models), a Web-based computing tool has been developed for improving estimation of virus fitness in growth competition assays of human immunodeficiency virus type 1 (HIV-1). Unlike the two-point calculation used in previous studies, the estimation here uses linear regression methods with all observed data in the competition experiment to more accurately estimate relative viral fitness parameters. The dilution factor is introduced for making the computational tool more flexible to accommodate various experimental conditions. This Web-based tool is implemented in C# language with Microsoft ASP.NET, and is publicly available on the Web at http://bis.urmc.rochester.edu/vFitness/.
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.
Fitted Hanbury-Brown-Twiss radii versus space-time variances in flow-dominated models
DOE Office of Scientific and Technical Information (OSTI.GOV)
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 simplemore » 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.« less
Gender Differences in Teacher Computer Acceptance
ERIC Educational Resources Information Center
Yuen, Allan H. K.; Ma, Will W. K.
2002-01-01
Teachers' computer acceptance is an important factor to the successful use of computers in education. This article explores the gender differences in teacher computer acceptance. The Technology Acceptance Model (TAM) was used as the framework to determine if such differences are present. Survey questionnaires were administered to 186 preservice…
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).
Physical fitness assessment: an update.
Wilder, Robert P; Greene, Jill Amanda; Winters, Kathryne L; Long, William B; Gubler, K; Edlich, Richard F
2006-01-01
The American College of Sports Medicine (ACSM) gives the following definition of health-related physical fitness: Physical fitness is defined as a set of attributes that people have or achieve that relates to the ability to perform physical activity. It is also characterized by (1) an ability to perform daily activities with vigor, and (2) a demonstration of traits and capacities that are associated with a low risk of premature development of hypokinetic diseases (e.g., those associated with physical inactivity). Information from an individual's health and medical records can be combined with information from physical fitness assessment to meet the specific health goals and rehabilitative needs of that individual. Attaining adequate informed consent from participants prior to exercise testing is mandatory because of ethical and legal considerations.A physical fitness assessment includes measures of body composition, cardiorespiratory endurance, muscular fitness, and musculoskeletal flexibility. The three common techniques for assessing body composition are hydrostatic weighing, and skinfold measurements, and anthropometric measurements. Cardiorespiratory endurance is a crucial component of physical fitness assessment because of its strong correlation with health and health risks. Maximal oxygen uptake (VO2max) is the traditionally accepted criterion for measuring cardiorespiratory endurance. Although maximal-effort tests must be used to measure VO2max, submaximal exercise can be used to estimate this value. Muscular fitness has historically been used to describe an individual's integrated status of muscular strength and muscular endurance. An individual's muscular strength is specific to a particular muscle or muscle group and refers to the maximal force (N or kg) that the muscle or muscle group can generate. Dynamic strength can be assessed by measuring the movement of an individual's body against an external load. Isokinetic testing may be performed by assessing
Makri-Botsari, Evi
2015-08-01
The purpose of this study was to detect gender specific patterns in the network of relations between unconditionality of parental and teacher acceptance in the form of unconditional positive regard and a range of educational outcomes, as indexed by academic self-perception, academic intrinsic motivation, and academic achievement. To test the role of gender as a moderator, a multi-group analysis was employed within the framework of structural equation modelling with increasing restrictions placed on the structural paths across genders. The results on a sample of 427 adolescents in grades 7-9 showed that conditionality of acceptance undermined level of perceived acceptance for both social agents. Moreover, unconditionality of teacher acceptance exerted stronger influences on students' educational outcomes than unconditionality of parental acceptance, with effect sizes being larger for girls than for boys. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Frenken, Koen
2001-06-01
The biological evolution of complex organisms, in which the functioning of genes is interdependent, has been analyzed as "hill-climbing" on NK fitness landscapes through random mutation and natural selection. In evolutionary economics, NK fitness landscapes have been used to simulate the evolution of complex technological systems containing elements that are interdependent in their functioning. In these models, economic agents randomly search for new technological design by trial-and-error and run the risk of ending up in sub-optimal solutions due to interdependencies between the elements in a complex system. These models of random search are legitimate for reasons of modeling simplicity, but remain limited as these models ignore the fact that agents can apply heuristics. A specific heuristic is one that sequentially optimises functions according to their ranking by users of the system. To model this heuristic, a generalized NK-model is developed. In this model, core elements that influence many functions can be distinguished from peripheral elements that affect few functions. The concept of paradigmatic search can then be analytically defined as search that leaves core elements in tact while concentrating on improving functions by mutation of peripheral elements.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhao, Gong-Bo, E-mail: gongbo@icosmology.info; Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth PO1 3FX
2014-04-01
Based on a suite of N-body simulations of the Hu-Sawicki model of f(R) gravity with different sets of model and cosmological parameters, we develop a new fitting formula with a numeric code, MGHalofit, to calculate the nonlinear matter power spectrum P(k) for the Hu-Sawicki model. We compare the MGHalofit predictions at various redshifts (z ≤ 1) to the f(R) simulations and find that the relative error of the MGHalofit fitting formula of P(k) is no larger than 6% at k ≤ 1 h Mpc{sup –1} and 12% at k in (1, 10] h Mpc{sup –1}, respectively. Based on a sensitivitymore » study of an ongoing and a future spectroscopic survey, we estimate the detectability of a signal of modified gravity described by the Hu-Sawicki model using the power spectrum up to quasi-nonlinear scales.« less
Bustamante, Carlos D.; Valero-Cuevas, Francisco J.
2010-01-01
The field of complex biomechanical modeling has begun to rely on Monte Carlo techniques to investigate the effects of parameter variability and measurement uncertainty on model outputs, search for optimal parameter combinations, and define model limitations. However, advanced stochastic methods to perform data-driven explorations, such as Markov chain Monte Carlo (MCMC), become necessary as the number of model parameters increases. Here, we demonstrate the feasibility and, what to our knowledge is, the first use of an MCMC approach to improve the fitness of realistically large biomechanical models. We used a Metropolis–Hastings algorithm to search increasingly complex parameter landscapes (3, 8, 24, and 36 dimensions) to uncover underlying distributions of anatomical parameters of a “truth model” of the human thumb on the basis of simulated kinematic data (thumbnail location, orientation, and linear and angular velocities) polluted by zero-mean, uncorrelated multivariate Gaussian “measurement noise.” Driven by these data, ten Markov chains searched each model parameter space for the subspace that best fit the data (posterior distribution). As expected, the convergence time increased, more local minima were found, and marginal distributions broadened as the parameter space complexity increased. In the 36-D scenario, some chains found local minima but the majority of chains converged to the true posterior distribution (confirmed using a cross-validation dataset), thus demonstrating the feasibility and utility of these methods for realistically large biomechanical problems. PMID:19272906
Mitchell, Tarah; White, Edward D; Ritschel, Daniel
2014-06-01
The primary objective in this research involves determining the Air Force Physical Fitness Test's (AFPFT) predictability of combat fitness and whether measures within the AFPFT require modification to increase this predictability further. We recruited 60 female volunteers and compared their performance on the AFPFT to the Marine Combat Fitness Test, the proxy for combat fitness. We discovered little association between the two (R(2) of 0.35), however, this association significantly increased (adjusted R(2) of 0.56) when utilizing the raw scores of the AFPFT instead of using the gender/age scoring tables. Improving on these associations, we develop and propose a simple ordinary least squares regression model that minimally impacts the AFPFT testing routine. This two-event model for predicting combat fitness incorporates the 1.5-mile run along with the number of repetitions of a 30-lb dumbbell from chest height to overhead with arms extended during a 2-minute time span. These two events predicted combat fitness as assessed by the Marine Combat Fitness Test with an adjusted R(2) of 0.82. By adopting this model, we greatly improve the Air Force's ability to assess combat fitness for women. Reprint & Copyright © 2014 Association of Military Surgeons of the U.S.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 10 Energy 1 2011-01-01 2011-01-01 false Acceptable devices for conducting initial and confirmatory tests for alcohol and methods of use. 26.91 Section 26.91 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Collecting Specimens for Testing § 26.91 Acceptable devices for conducting initial...
Code of Federal Regulations, 2010 CFR
2010-01-01
... 10 Energy 1 2010-01-01 2010-01-01 false Acceptable devices for conducting initial and confirmatory tests for alcohol and methods of use. 26.91 Section 26.91 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Collecting Specimens for Testing § 26.91 Acceptable devices for conducting initial...
Code of Federal Regulations, 2013 CFR
2013-01-01
... 10 Energy 1 2013-01-01 2013-01-01 false Acceptable devices for conducting initial and confirmatory tests for alcohol and methods of use. 26.91 Section 26.91 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Collecting Specimens for Testing § 26.91 Acceptable devices for conducting initial...
Code of Federal Regulations, 2014 CFR
2014-01-01
... 10 Energy 1 2014-01-01 2014-01-01 false Acceptable devices for conducting initial and confirmatory tests for alcohol and methods of use. 26.91 Section 26.91 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Collecting Specimens for Testing § 26.91 Acceptable devices for conducting initial...
Code of Federal Regulations, 2012 CFR
2012-01-01
... 10 Energy 1 2012-01-01 2012-01-01 false Acceptable devices for conducting initial and confirmatory tests for alcohol and methods of use. 26.91 Section 26.91 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Collecting Specimens for Testing § 26.91 Acceptable devices for conducting initial...
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) . © 2015 John Wiley & Sons Ltd/London School of Economics.
Measuring Quasar Spin via X-ray Continuum Fitting
NASA Astrophysics Data System (ADS)
Jenkins, Matthew; Pooley, David; Rappaport, Saul; Steiner, Jack
2018-01-01
We have identified several quasars whose X-ray spectra appear very soft. When fit with power-law models, the best-fit indices are greater than 3. This is very suggestive of thermal disk emission, indicating that the X-ray spectrum is dominated by the disk component. Galactic black hole binaries in such states have been successfully fit with disk-blackbody models to constrain the inner radius, which also constrains the spin of the black hole. We have fit those models to XMM-Newton spectra of several of our identified soft X-ray quasars to place constraints on the spins of the supermassive black holes.
RATES OF FITNESS DECLINE AND REBOUND SUGGEST PERVASIVE EPISTASIS
Perfeito, L; Sousa, A; Bataillon, T; Gordo, I
2014-01-01
Unraveling the factors that determine the rate of adaptation is a major question in evolutionary biology. One key parameter is the effect of a new mutation on fitness, which invariably depends on the environment and genetic background. The fate of a mutation also depends on population size, which determines the amount of drift it will experience. Here, we manipulate both population size and genotype composition and follow adaptation of 23 distinct Escherichia coli genotypes. These have previously accumulated mutations under intense genetic drift and encompass a substantial fitness variation. A simple rule is uncovered: the net fitness change is negatively correlated with the fitness of the genotype in which new mutations appear—a signature of epistasis. We find that Fisher's geometrical model can account for the observed patterns of fitness change and infer the parameters of this model that best fit the data, using Approximate Bayesian Computation. We estimate a genomic mutation rate of 0.01 per generation for fitness altering mutations, albeit with a large confidence interval, a mean fitness effect of mutations of −0.01, and an effective number of traits nine in mutS− E. coli. This framework can be extended to confront a broader range of models with data and test different classes of fitness landscape models. PMID:24372601
ERIC Educational Resources Information Center
Sotelo, Benjamin Eladio
2015-01-01
The Technology Acceptance Model (TAM) has been an important model for the understanding of end user acceptance regarding technology and a framework used in thousands of researched scenarios since publication in 1986. Similarly, the Kubler-Ross model of death and dying has also been used as a model for the study of acceptance within the medical…
Ong, Kevin L; Rundell, Steve; Liepins, Imants; Laurent, Ryan; Markel, David; Kurtz, Steven M
2009-11-01
Press-fit implantation may result in acetabular component deformation between the ischial-ilial columns ("pinching"). The biomechanical and clinical consequences of liner pinching due to press-fit implantation have not been well studied. We compared the effects of pinching on the polyethylene fracture risk, potential wear rate, and stresses for two different thickness liners using computational methods. Line-to-line ("no pinch") reaming and 2 mm underreaming press fit ("pinch") conditions were examined for Trident cups with X3 polyethylene liner wall thicknesses of 5.9 mm (36E) and 3.8 mm (40E). Press-fit cup deformations were measured from a foam block configuration. A hybrid material model, calibrated to experimentally determined stress-strain behavior of sequentially annealed polyethylene, was applied to the computational model. Molecular chain stretch did not exceed the fracture threshold in any cases. Nominal shell pinch of 0.28 mm was estimated to increase the volumetric wear rate by 70% for both cups and peak contact stresses by 140 and 170% for the 5.9 and 3.8 mm-thick liners, respectively. Although pinching increases liner stresses, polyethylene fracture is highly unlikely, and the volumetric wear rates are likely to be low compared to conventional polyethylene. (c) 2009 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.
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.
A comparison of wearable fitness devices.
Kaewkannate, Kanitthika; Kim, Soochan
2016-05-24
Wearable trackers can help motivate you during workouts and provide information about your daily routine or fitness in combination with your smartphone without requiring potentially disruptive manual calculations or records. This paper summarizes and compares wearable fitness devices, also called "fitness trackers" or "activity trackers." These devices are becoming increasingly popular in personal healthcare, motivating people to exercise more throughout the day without the need for lifestyle changes. The various choices in the market for wearable devices are also increasing, with customers searching for products that best suit their personal needs. Further, using a wearable device or fitness tracker can help people reach a fitness goal or finish line. Generally, companies display advertising for these kinds of products and depict them as beneficial, user friendly, and accurate. However, there are no objective research results to prove the veracity of their words. This research features subjective and objective experimental results, which reveal that some devices perform better than others. The four most popular wristband style wearable devices currently on the market (Withings Pulse, Misfit Shine, Jawbone Up24, and Fitbit Flex) are selected and compared. The accuracy of fitness tracking is one of the key components for fitness tracking, and some devices perform better than others. This research shows subjective and objective experimental results that are used to compare the accuracy of four wearable devices in conjunction with user friendliness and satisfaction of 7 real users. In addition, this research matches the opinions between reviewers on an Internet site and those of subjects when using the device. Withings Pulse is the most friendly and satisfactory from the users' viewpoint. It is the most accurate and repeatable for step and distance tracking, which is the most important measurement of fitness tracking, followed by Fitbit Flex, Jawbone Up24, and Misfit
ERIC Educational Resources Information Center
Thompson, James R.; Wehmeyer, Michael L.; Hughes, Carolyn
2010-01-01
A person-environment fit conceptualization of intellectual disability (ID) requires educators to focus on the gap between a student's competencies and the demands of activities and settings in schools. In this article the implications of the person-environment fit conceptual model are considered in regard to instructional benefits, special…
An Introduction to Goodness of Fit for PMU Parameter Estimation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Riepnieks, Artis; Kirkham, Harold
2017-10-01
New results of measurements of phasor-like signals are presented based on our previous work on the topic. In this document an improved estimation method is described. The algorithm (which is realized in MATLAB software) is discussed. We examine the effect of noisy and distorted signals on the Goodness of Fit metric. The estimation method is shown to be performing very well with clean data and with a measurement window as short as a half a cycle and as few as 5 samples per cycle. The Goodness of Fit decreases predictably with added phase noise, and seems to be acceptable evenmore » with visible distortion in the signal. While the exact results we obtain are specific to our method of estimation, the Goodness of Fit method could be implemented in any phasor measurement unit.« less
Direito, Artur; Jiang, Yannan; Whittaker, Robyn; Maddison, Ralph
2015-07-11
Physical activity is a modifiable behavior related to many preventable non-communicable diseases. There is an age-related decline in physical activity levels in young people, which tracks into adulthood. Common interactive technologies such as smartphones, particularly employing immersive features, may enhance the appeal and delivery of interventions to increase levels of physical activity in young people. The primary aim of the Apps for IMproving FITness (AIMFIT) trial is to evaluate the effectiveness of two popular "off-the-shelf" smartphone apps for improving cardiorespiratory fitness in young people. A three-arm, parallel, randomized controlled trial will be conducted in Auckland, New Zealand. Fifty-one eligible young people aged 14-17 years will be randomized to one of three conditions: 1) use of an immersive smartphone app, 2) use of a non-immersive app, or 3) usual behavior (control). Both smartphone apps consist of an eight-week training program designed to improve fitness and ability to run 5 km, however, the immersive app features a game-themed design and adds a narrative. Data are collected at baseline and 8 weeks. The primary outcome is cardiorespiratory fitness, assessed as time to complete the one mile run/walk test at 8 weeks. Secondary outcomes are physical activity levels, self-efficacy, enjoyment, psychological need satisfaction, and acceptability and usability of the apps. Analysis using intention to treat principles will be performed using regression models. Despite the proliferation of commercially available smartphone applications, there is a dearth of empirical evidence to support their effectiveness on the targeted health behavior. This pragmatic study will determine the effectiveness of two popular "off-the-shelf" apps as a stand-alone instrument for improving fitness and physical activity among young people. Adherence to app use will not be closely controlled; however, random allocation of participants, a heterogeneous group, and data
Usability and acceptability of balance exergames in older adults: A scoping review.
Nawaz, Ather; Skjæret, Nina; Helbostad, Jorunn Lægdheim; Vereijken, Beatrix; Boulton, Elisabeth; Svanaes, Dag
2016-12-01
Serious games (exergames) have the potential to be effective for postural balance and increasing muscle strength. Several games have been developed to increase physical fitness and balance among older adults. However, it is unclear to which degree usability and acceptability of exergames for older adults have been evaluated. The aim of this study was to summarize usability evaluation and acceptability of studies in older adults. We conducted a scoping review on studies focusing on usability of exergames for older adults. The result shows that older adults consider usability and acceptability of exercise video games good. The review shows that longitudinal studies mainly use off-the-shelf exergame and evaluated game effectiveness and acceptability, whereas cross-sectional studies focus on interactional experience. Studies varied in their approaches to measure usability and acceptability of exergames for older adults. There is a need for a systematic developmental approach to involve older adults in development of exergames for longitudinal studies. © The Author(s) 2015.
Acceptability of GM foods among Pakistani consumers.
Ali, Akhter; Rahut, Dil Bahadur; Imtiaz, Muhammad
2016-04-02
In Pakistan majority of the consumers do not have information about genetically modified (GM) foods. In developing countries particularly in Pakistan few studies have focused on consumers' acceptability about GM foods. Using comprehensive primary dataset collected from 320 consumers in 2013 from Pakistan, this study analyzes the determinants of consumers' acceptability of GM foods. The data was analyzed by employing the bivariate probit model and censored least absolute deviation (CLAD) models. The empirical results indicated that urban consumers are more aware of GM foods compared to rural consumers. The acceptance of GM foods was more among females' consumers as compared to male consumers. In addition, the older consumers were more willing to accept GM food compared to young consumers. The acceptability of GM foods was also higher among wealthier households. Low price is the key factor leading to the acceptability of GM foods. The acceptability of the GM foods also reduces the risks among Pakistani consumers.
Acceptability of GM foods among Pakistani consumers
Ali, Akhter; Rahut, Dil Bahadur; Imtiaz, Muhammad
2016-01-01
ABSTRACT In Pakistan majority of the consumers do not have information about genetically modified (GM) foods. In developing countries particularly in Pakistan few studies have focused on consumers' acceptability about GM foods. Using comprehensive primary dataset collected from 320 consumers in 2013 from Pakistan, this study analyzes the determinants of consumers' acceptability of GM foods. The data was analyzed by employing the bivariate probit model and censored least absolute deviation (CLAD) models. The empirical results indicated that urban consumers are more aware of GM foods compared to rural consumers. The acceptance of GM foods was more among females' consumers as compared to male consumers. In addition, the older consumers were more willing to accept GM food compared to young consumers. The acceptability of GM foods was also higher among wealthier households. Low price is the key factor leading to the acceptability of GM foods. The acceptability of the GM foods also reduces the risks among Pakistani consumers. PMID:27494790
OTM Machine Acceptance: In the Arab Culture
NASA Astrophysics Data System (ADS)
Rashed, Abdullah; Santos, Henrique
Basically, neglecting the human factor is one of the main reasons for system failures or for technology rejection, even when important technologies are considered. Biometrics mostly have the characteristics needed for effortless acceptance, such as easiness and usefulness, that are essential pillars of acceptance models such as TAM (technology acceptance model). However, it should be investigated. Many studies have been carried out to research the issues of technology acceptance in different cultures, especially the western culture. Arabic culture lacks these types of studies with few publications in this field. This paper introduces a new biometric interface for ATM machines. This interface depends on a promising biometrics which is odour. To discover the acceptance of this biometrics, we distributed a questionnaire via a web site and called for participation in the Arab Area and found that most respondents would accept to use odour.
ERIC Educational Resources Information Center
Fenton, Ray
The Concerns Based Acceptance Model (CBAM) has been a key element in developing and assessing the implementation of science and mathematics programs over the past 20 years. CBAM provides an organized approach to assessing where people stand as they learn about, and accept, changes in organizations. This study examined the status of the adoption of…
BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments
Thomas, Brandon R.; Chylek, Lily A.; Colvin, Joshua; Sirimulla, Suman; Clayton, Andrew H.A.; Hlavacek, William S.; Posner, Richard G.
2016-01-01
Summary: Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive. Availability and implementation: BioNetFit can be used on stand-alone Mac, Windows/Cygwin, and Linux platforms and on Linux-based clusters running SLURM, Torque/PBS, or SGE. The BioNetFit source code (Perl) is freely available (http://bionetfit.nau.edu). Supplementary information: Supplementary data are available at Bioinformatics online. Contact: bionetgen.help@gmail.com PMID:26556387
Webb, Haley J; Zimmer-Gembeck, Melanie J; Mastro, Shawna
2016-09-01
This study examined the bidirectional (conjoint) longitudinal pathways linking adolescents' body dysmorphic disorder (BDD) symptoms with self- and peer-reported social functioning. Participants were 367 Australian students (45.5% boys, mean age=12.01 years) who participated in two waves of a longitudinal study with a 12-month lag between assessments. Participants self-reported their symptoms characteristic of BDD, and perception of peer acceptance. Classmates reported who was popular and victimized in their grade, and rated their liking (acceptance) of their classmates. In support of both stress exposure and stress generation models, T1 victimization was significantly associated with more symptoms characteristic of BDD at T2 relative to T1, and higher symptom level at T1 was associated with lower perceptions of peer acceptance at T2 relative to T1. These results support the hypothesized bidirectional model, whereby adverse social experiences negatively impact symptoms characteristic of BDD over time, and symptoms also exacerbate low perceptions of peer-acceptance. Copyright © 2016 Elsevier Ltd. All rights reserved.
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.
A fuzzy inventory model with acceptable shortage using graded mean integration value method
NASA Astrophysics Data System (ADS)
Saranya, R.; Varadarajan, R.
2018-04-01
In many inventory models uncertainty is due to fuzziness and fuzziness is the closed possible approach to reality. In this paper, we proposed a fuzzy inventory model with acceptable shortage which is completely backlogged. We fuzzily the carrying cost, backorder cost and ordering cost using Triangular and Trapezoidal fuzzy numbers to obtain the fuzzy total cost. The purpose of our study is to defuzzify the total profit function by Graded Mean Integration Value Method. Further a numerical example is also given to demonstrate the developed crisp and fuzzy models.
Schmader, Toni; Sedikides, Constantine
2017-10-01
People seek out situations that "fit," but the concept of fit is not well understood. We introduce State Authenticity as Fit to the Environment (SAFE), a conceptual framework for understanding how social identities motivate the situations that people approach or avoid. Drawing from but expanding the authenticity literature, we first outline three types of person-environment fit: self-concept fit, goal fit, and social fit. Each type of fit, we argue, facilitates cognitive fluency, motivational fluency, and social fluency that promote state authenticity and drive approach or avoidance behaviors. Using this model, we assert that contexts subtly signal social identities in ways that implicate each type of fit, eliciting state authenticity for advantaged groups but state inauthenticity for disadvantaged groups. Given that people strive to be authentic, these processes cascade down to self-segregation among social groups, reinforcing social inequalities. We conclude by mapping out directions for research on relevant mechanisms and boundary conditions.
Local Minima Free Parameterized Appearance Models
Nguyen, Minh Hoai; De la Torre, Fernando
2010-01-01
Parameterized Appearance Models (PAMs) (e.g. Eigentracking, Active Appearance Models, Morphable Models) are commonly used to model the appearance and shape variation of objects in images. While PAMs have numerous advantages relative to alternate approaches, they have at least two drawbacks. First, they are especially prone to local minima in the fitting process. Second, often few if any of the local minima of the cost function correspond to acceptable solutions. To solve these problems, this paper proposes a method to learn a cost function by explicitly optimizing that the local minima occur at and only at the places corresponding to the correct fitting parameters. To the best of our knowledge, this is the first paper to address the problem of learning a cost function to explicitly model local properties of the error surface to fit PAMs. Synthetic and real examples show improvement in alignment performance in comparison with traditional approaches. PMID:21804750
Aguirre-Gutiérrez, Jesús; Carvalheiro, Luísa G; Polce, Chiara; van Loon, E Emiel; Raes, Niels; Reemer, Menno; Biesmeijer, Jacobus C
2013-01-01
Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species' data
Bethea, Terrence C; Berry, Diane; Maloney, Ann E; Sikich, Linmarie
2012-02-01
The aim of our feasibility study was to examine the acceptability and utility of "Dance Dance Revolution" (DDR) (Konami of America, Redwood City, CA)) to increase physical fitness in 8-11-year-old black and Hispanic youth. Twenty-eight 4(th) and 5(th) grade children attending an afterschool program participated. Outcomes included physical activity, physical fitness, use of home DDR, survey of safety and acceptability, anthropometrics, and fasting metabolic profile measured at baseline, 12 weeks, and 30 weeks. At 12 weeks, physical fitness (maximum O2 uptake [VO2max]) increased by 4.9±9.9 percent and was sustained through 30 weeks, when the VO2max was 105.0±9.9 percent (range, 93.0-133.9 percent) of baseline values. Absolute VO2max increased by 2.97±4.99 mL/kg/minute (95% confidence interval 0.75-5.19, P=0.013). Participants maintained an average of 1.12 hours/day of increased movement to music. Trends suggested increased total moderate-vigorous physical activity, decreased light activity, and a modest increase in sedentary screen time. There were no significant changes in body mass index, fasting lipids, or glucose. Participants and parents approved of the activity. DDR appears feasible and acceptable to minority youth. DDR may increase moderate-vigorous physical activity and improve physical fitness in at-risk populations.
Complex growing networks with intrinsic vertex fitness
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bedogne, C.; Rodgers, G. J.
2006-10-15
One of the major questions in complex network research is to identify the range of mechanisms by which a complex network can self organize into a scale-free state. In this paper we investigate the interplay between a fitness linking mechanism and both random and preferential attachment. In our models, each vertex is assigned a fitness x, drawn from a probability distribution {rho}(x). In Model A, at each time step a vertex is added and joined to an existing vertex, selected at random, with probability p and an edge is introduced between vertices with fitnesses x and y, with a ratemore » f(x,y), with probability 1-p. Model B differs from Model A in that, with probability p, edges are added with preferential attachment rather than randomly. The analysis of Model A shows that, for every fixed fitness x, the network's degree distribution decays exponentially. In Model B we recover instead a power-law degree distribution whose exponent depends only on p, and we show how this result can be generalized. The properties of a number of particular networks are examined.« less
Integrating the Levels of Person-Environment Fit: The Roles of Vocational Fit and Group Fit
ERIC Educational Resources Information Center
Vogel, Ryan M.; Feldman, Daniel C.
2009-01-01
Previous research on fit has largely focused on person-organization (P-O) fit and person-job (P-J) fit. However, little research has examined the interplay of person-vocation (P-V) fit and person-group (P-G) fit with P-O fit and P-J fit in the same study. This article advances the fit literature by examining these relationships with data collected…
NASA Astrophysics Data System (ADS)
Mandal, S.; Choudhury, B. U.
2015-07-01
Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.
The lunar libration: comparisons between various models - a model fitted to LLR observations
NASA Astrophysics Data System (ADS)
Chapront, J.; Francou, G.
2005-09-01
We consider 4 libration models: 3 numerical models built by JPL (ephemerides for the libration in DE245, DE403 and DE405) and an analytical model improved with numerical complements fitted to recent LLR observations. The analytical solution uses 3 angular variables (ρ1, ρ2, τ) which represent the deviations with respect to Cassini's laws. After having referred the models to a unique reference frame, we study the differences between the models which depend on gravitational and tidal parameters of the Moon, as well as amplitudes and frequencies of the free librations. It appears that the differences vary widely depending of the above quantities. They correspond to a few meters displacement on the lunar surface, reminding that LLR distances are precise to the centimeter level. Taking advantage of the lunar libration theory built by Moons (1984) and improved by Chapront et al. (1999) we are able to establish 4 solutions and to represent their differences by Fourier series after a numerical substitution of the gravitational constants and free libration parameters. The results are confirmed by frequency analyses performed separately. Using DE245 as a basic reference ephemeris, we approximate the differences between the analytical and numerical models with Poisson series. The analytical solution - improved with numerical complements under the form of Poisson series - is valid over several centuries with an internal precision better than 5 centimeters.
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…
ERIC Educational Resources Information Center
Nagy, Judit T.
2018-01-01
The aim of the study was to examine the determining factors of students' video usage and their learning satisfaction relating to the supplementary application of educational videos, accessible in a Moodle environment in a Business Mathematics Course. The research model is based on the extension of "Technology Acceptance Model" (TAM), in…
Zhai, Xuetong; Chakraborty, Dev P
2017-06-01
The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics
Sánchez-Jiménez, Pedro E; Pérez-Maqueda, Luis A; Perejón, Antonio; Criado, José M
2013-02-05
This paper provides some clarifications regarding the use of model-fitting methods of kinetic analysis for estimating the activation energy of a process, in response to some results recently published in Chemistry Central journal. The model fitting methods of Arrhenius and Savata are used to determine the activation energy of a single simulated curve. It is shown that most kinetic models correctly fit the data, each providing a different value for the activation energy. Therefore it is not really possible to determine the correct activation energy from a single non-isothermal curve. On the other hand, when a set of curves are recorded under different heating schedules are used, the correct kinetic parameters can be clearly discerned. Here, it is shown that the activation energy and the kinetic model cannot be unambiguously determined from a single experimental curve recorded under non isothermal conditions. Thus, the use of a set of curves recorded under different heating schedules is mandatory if model-fitting methods are employed.
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.
Regulatory Fit and Equal Opportunity/Diversity: Implications for DEOMI
2013-01-01
than demographic diversity ( Ivancevich & Gilbert, 2000); the goal of equality is to create and manage a heterogeneous mix of abilities, skills, ideas...accepted. Recruiting of minorities and women are not seen as violations of EO laws (Kravitz, 2008; Newman & Lyon , 2009; Pyburn, et al., 2008). Similarly...209-213. REGULATORY FIT AND EQUAL OPPORTUNITY/DIVERSITY 23 Ivancevich , J. M. & Gilbert, J. A. (2000). Diversity management: Time for a new approach
Understanding Host-Switching by Ecological Fitting
Araujo, Sabrina B. L.; Braga, Mariana Pires; Brooks, Daniel R.; Agosta, Salvatore J.; Hoberg, Eric P.; von Hartenthal, Francisco W.; Boeger, Walter A.
2015-01-01
Despite the fact that parasites are highly specialized with respect to their hosts, empirical evidence demonstrates that host switching rather than co-speciation is the dominant factor influencing the diversification of host-parasite associations. Ecological fitting in sloppy fitness space has been proposed as a mechanism allowing ecological specialists to host-switch readily. That proposal is tested herein using an individual-based model of host switching. The model considers a parasite species exposed to multiple host resources. Through time host range expansion can occur readily without the prior evolution of novel genetic capacities. It also produces non-linear variation in the size of the fitness space. The capacity for host colonization is strongly influenced by propagule pressure early in the process and by the size of the fitness space later. The simulations suggest that co-adaptation may be initiated by the temporary loss of less fit phenotypes. Further, parasites can persist for extended periods in sub-optimal hosts, and thus may colonize distantly related hosts by a "stepping-stone" process. PMID:26431199
Evaluating Suit Fit Using Performance Degradation
NASA Technical Reports Server (NTRS)
Margerum, Sarah E.; Cowley, Matthew; Harvill, Lauren; Benson, Elizabeth; Rajulu, Sudhakar
2012-01-01
The Mark III planetary technology demonstrator space suit can be tailored to an individual by swapping the modular components of the suit, such as the arms, legs, and gloves, as well as adding or removing sizing inserts in key areas. A method was sought to identify the transition from an ideal suit fit to a bad fit and how to quantify this breakdown using a metric of mobility-based human performance data. To this end, the degradation of the range of motion of the elbow and wrist of the suit as a function of suit sizing modifications was investigated to attempt to improve suit fit. The sizing range tested spanned optimal and poor fit and was adjusted incrementally in order to compare each joint angle across five different sizing configurations. Suited range of motion data were collected using a motion capture system for nine isolated and functional tasks utilizing the elbow and wrist joints. A total of four subjects were tested with motions involving both arms simultaneously as well as the right arm by itself. Findings indicated that no single joint drives the performance of the arm as a function of suit size; instead it is based on the interaction of multiple joints along a limb. To determine a size adjustment range where an individual can operate the suit at an acceptable level, a performance detriment limit was set. This user-selected limit reveals the task-dependent tolerance of the suit fit around optimal size. For example, the isolated joint motion indicated that the suit can deviate from optimal by as little as -0.6 in to -2.6 in before experiencing a 10% performance drop in the wrist or elbow joint. The study identified a preliminary method to quantify the impact of size on performance and developed a new way to gauge tolerances around optimal size.
Isochrone Fitting of Hubble Photometry in UV-Vis Bands
NASA Astrophysics Data System (ADS)
Barker, Hallie; Paust, Nathaniel
2017-01-01
We present the results of isochrone fitting of color-magnitude diagrams from Hubble Space Telescope Wide Field Camera 3 (WFC3) and Advanced Camera for Surveys (ACS) photometry of the globular clusters M13 and M80 in five bands from the ultraviolet to near infrared. Fits from both the Dartmouth Stellar Evolution Program (DSEP) and the PAdova and TRieste Stellar Evolution Code (PARSEC) are examined. Ages, extinctions, and distances are found from the isochrone fitting, and metallicities are confirmed. We conduct careful qualitative analysis on the inconsistencies of the fits across all of the color combinations possible with the five observed bands, and find that the (F606W-F814W) color generally produces very good fits, but that there are large discrepancies when the data is fit using colors including UV bands for both models. Finally, we directly compare the two models by performing isochrone-isochrone fitting, and find that the age in PARSEC is on average 1.5 Gyr younger than DSEP for similar-appearing models at the same metallicity, and that the two models become less discrepant at lower metallicities.
A Comparison of the Fit of Empirical Data to Two Latent Trait Models. Report No. 92.
ERIC Educational Resources Information Center
Hutten, Leah R.
Goodness of fit of raw test score data were compared, using two latent trait models: the Rasch model and the Birnbaum three-parameter logistic model. Data were taken from various achievement tests and the Scholastic Aptitude Test (Verbal). A minimum sample size of 1,000 was required, and the minimum test length was 40 items. Results indicated that…
Greguras, Gary J; Diefendorff, James M
2009-03-01
Integrating and expanding upon the person-environment fit (PE fit) and the self-determination theory literatures, the authors hypothesized and tested a model in which the satisfaction of the psychological needs for autonomy, relatedness, and competence partially mediated the relations between different types of perceived PE fit (i.e., person-organization fit, person-group fit, and job demands-abilities fit) with employee affective organizational commitment and overall job performance. Data from 163 full-time working employees and their supervisors were collected across 3 time periods. Results indicate that different types of PE fit predicted different types of psychological need satisfaction and that psychological need satisfaction predicted affective commitment and performance. Further, person-organization fit and demands-abilities fit also evidenced direct effects on employee affective commitment. These results begin to explicate the processes through which different types of PE fit relate to employee attitudes and behaviors. (c) 2009 APA, all rights reserved.
Payne, Velma L; Hysong, Sylvia J
2016-07-13
Audit and feedback (A&F) is a strategy that has been used in various disciplines for performance and quality improvement. There is limited research regarding medical professionals' acceptance of clinical-performance feedback and whether feedback impacts clinical practice. The objectives of our research were to (1) investigate aspects of A&F that impact physicians' acceptance of performance feedback; (2) determine actions physicians take when receiving feedback; and (3) determine if feedback impacts physicians' patient-management behavior. In this qualitative study, we employed grounded theory methods to perform a secondary analysis of semi-structured interviews with 12 VA primary care physicians. We analyzed a subset of interview questions from the primary study, which aimed to determine how providers of high, low and moderately performing VA medical centers use performance feedback to maintain and improve quality of care, and determine perceived utility of performance feedback. Based on the themes emergent from our analysis and their observed relationships, we developed a model depicting aspects of the A&F process that impact feedback acceptance and physicians' patient-management behavior. The model is comprised of three core components - Reaction, Action and Impact - and depicts elements associated with feedback recipients' reaction to feedback, action taken when feedback is received, and physicians modifying their patient-management behavior. Feedback characteristics, the environment, external locus-of-control components, core values, emotion and the assessment process induce or deter reaction, action and impact. Feedback characteristics (content and timeliness), and the procedural justice of the assessment process (unjust penalties) impact feedback acceptance. External locus-of-control elements (financial incentives, competition), the environment (patient volume, time constraints) and emotion impact patient-management behavior. Receiving feedback generated
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.
Fit reduced GUTS models online: From theory to practice.
Baudrot, Virgile; Veber, Philippe; Gence, Guillaume; Charles, Sandrine
2018-05-20
Mechanistic modeling approaches, such as the toxicokinetic-toxicodynamic (TKTD) framework, are promoted by international institutions such as the European Food Safety Authority and the Organization for Economic Cooperation and Development to assess the environmental risk of chemical products generated by human activities. TKTD models can encompass a large set of mechanisms describing the kinetics of compounds inside organisms (e.g., uptake and elimination) and their effect at the level of individuals (e.g., damage accrual, recovery, and death mechanism). Compared to classical dose-response models, TKTD approaches have many advantages, including accounting for temporal aspects of exposure and toxicity, considering data points all along the experiment and not only at the end, and making predictions for untested situations as realistic exposure scenarios. Among TKTD models, the general unified threshold model of survival (GUTS) is within the most recent and innovative framework but is still underused in practice, especially by risk assessors, because specialist programming and statistical skills are necessary to run it. Making GUTS models easier to use through a new module freely available from the web platform MOSAIC (standing for MOdeling and StAtistical tools for ecotoxIClogy) should promote GUTS operability in support of the daily work of environmental risk assessors. This paper presents the main features of MOSAIC_GUTS: uploading of the experimental data, GUTS fitting analysis, and LCx estimates with their uncertainty. These features will be exemplified from literature data. Integr Environ Assess Manag 2018;00:000-000. © 2018 SETAC. © 2018 SETAC.
Viral fitness: definitions, measurement, and current insights
Wargo, Andrew R.; Kurath, Gael
2012-01-01
Viral fitness is an active area of research, with recent work involving an expanded number of human, non-human vertebrate, invertebrate, plant, and bacterial viruses. Many publications deal with RNA viruses associated with major disease emergence events, such as HIV-1, influenza virus, and Dengue virus. Study topics include drug resistance, immune escape, viral emergence, host jumps, mutation effects, quasispecies diversity, and mathematical models of viral fitness. Important recent trends include increasing use of in vivo systems to assess vertebrate virus fitness, and a broadening of research beyond replicative fitness to also investigate transmission fitness and epidemiologic fitness. This is essential for a more integrated understanding of overall viral fitness, with implications for disease management in the future.
NASA Astrophysics Data System (ADS)
Hollaway, M. J.; Beven, K. J.; Benskin, C. McW. H.; Collins, A. L.; Evans, R.; Falloon, P. D.; Forber, K. J.; Hiscock, K. M.; Kahana, R.; Macleod, C. J. A.; Ockenden, M. C.; Villamizar, M. L.; Wearing, C.; Withers, P. J. A.; Zhou, J. G.; Barber, N. J.; Haygarth, P. M.
2018-03-01
There is a need to model and predict the transfer of phosphorus (P) from land to water, but this is challenging because of the large number of complex physical and biogeochemical processes involved. This study presents, for the first time, a 'limits of acceptability' approach of the Generalized Likelihood Uncertainty Estimation (GLUE) framework to the Soil and Water Assessment Tool (SWAT), in an application to a water quality problem in the Newby Beck catchment (12.5 km2), Cumbria, United Kingdom (UK). Using high frequency outlet data (discharge and P), individual evaluation criteria (limits of acceptability) were assigned to observed discharge and P loads for all evaluation time steps, identifying where the model was performing well/poorly and to infer which processes required improvement in the model structure. Initial limits of acceptability were required to be relaxed by a substantial amount (by factors of between 5.3 and 6.7 on a normalized scale depending on the evaluation criteria used) in order to gain a set of behavioral simulations (1001 and 1016, respectively out of 5,000,000). Of the 39 model parameters tested, the representation of subsurface processes and associated parameters, were consistently shown as critical to the model not meeting the evaluation criteria, irrespective of the chosen evaluation metric. It is therefore concluded that SWAT is not an appropriate model to guide P management in this catchment. This approach highlights the importance of high frequency monitoring data for setting robust model evaluation criteria. It also raises the question as to whether it is possible to have sufficient input data available to drive such models so that we can have confidence in their predictions and their ability to inform catchment management strategies to tackle the problem of diffuse pollution from agriculture.
Parental influences on 7-9 year olds' physical activity: a conceptual model.
Leary, Janie M; Lilly, Christa L; Dino, Geri; Loprinzi, Paul D; Cottrell, Lesley
2013-05-01
Models characterizing parental influence on child and adolescent physical activity (PA) over time are limited. Preschool and Adolescent Models (PM and AM) of PA are available leaving the need to focus on elementary-aged children. We tested current models (PM and AM) with a sample of 7-9 year-olds, and then developed a model appropriate to this specific target population. Parent-child dyads completed questionnaires in 2010-2011. All models were assessed using path analysis and model fit indices. For adequate power, 90 families were needed, with 174 dyads participating. PM and AM exhibited poor fit when applied to the study population. A gender-specific model was developed and demonstrated acceptable fit. To develop an acceptable model for this population, constructs from both the PM (i.e. parental perception of child competency) and AM (i.e., child-reported self-efficacy) were used. For boys, self-efficacy was a strong predictor of PA, which was influenced by various parental variables. For girls, parental PA demonstrated the greatest strength of association with child PA. This new model can be used to promote PA and guide future research/interventions. Future studies, particularly longitudinal designs, are needed to confirm the utility of this model as a bridge between currently available models. Copyright © 2013 Elsevier Inc. All rights reserved.
Manimaran, S; Lakshmi, K Bhagya
2013-01-01
HMIS will incorporate a paradigm shift in health such as removing manual records and transformation of data through the complex structure of health departments in Tamilnadu. Thus developing a model of technology acceptance in HMIS contest is important and necessary in order to promote usage of the HMIS in rural health care system. The papers purpose is to formulate a model of technology acceptance of Health Management Information System (HMIS) by generating and validating a research model that best describes rural health care workers usage behavior and behavior intention. This research proposes a theoretical framework which is comprised of key determinants that influence usage behavior of HMIS together with moderator. It has been tested through different parametric test and confirmatory factor analysis. Data analysis shows that health workers innovativeness and voluntariness have a direct and positive influence on Technology Acceptance level and that the basic TAM hypotheses are fulfilled. HMIS usage behavior and behavior intention can be increased with factors that are effecting the successful implementation of HMIS when it remains high. This research enables health departments to know which aspects of their HMIS components and variables to improve. This shows that HMIS usage and health workers/staffs acceptance level are key tools in the success of HMIS. This research has seemed to be done at the right time and in the right place to the best of its kind.
NASA Astrophysics Data System (ADS)
Maghsoudi, Mastoureh; Bakar, Shaiful Anuar Abu
2017-05-01
In this paper, a recent novel approach is applied to estimate the threshold parameter of a composite model. Several composite models from Transformed Gamma and Inverse Transformed Gamma families are constructed based on this approach and their parameters are estimated by the maximum likelihood method. These composite models are fitted to allocated loss adjustment expenses (ALAE). In comparison to all composite models studied, the composite Weibull-Inverse Transformed Gamma model is proved to be a competitor candidate as it best fit the loss data. The final part considers the backtesting method to verify the validation of VaR and CTE risk measures.
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. Copyright © 2014 Elsevier Inc. All rights reserved.
A mathematical description of the inclusive fitness theory.
Wakano, Joe Yuichiro; Ohtsuki, Hisashi; Kobayashi, Yutaka
2013-03-01
Recent developments in the inclusive fitness theory have revealed that the direction of evolution can be analytically predicted in a wider class of models than previously thought, such as those models dealing with network structure. This paper aims to provide a mathematical description of the inclusive fitness theory. Specifically, we provide a general framework based on a Markov chain that can implement basic models of inclusive fitness. Our framework is based on the probability distribution of "offspring-to-parent map", from which the key concepts of the theory, such as fitness function, relatedness and inclusive fitness, are derived in a straightforward manner. We prove theorems showing that inclusive fitness always provides a correct prediction on which of two competing genes more frequently appears in the long run in the Markov chain. As an application of the theorems, we prove a general formula of the optimal dispersal rate in the Wright's island model with recurrent mutations. We also show the existence of the critical mutation rate, which does not depend on the number of islands and below which a positive dispersal rate evolves. Our framework can also be applied to lattice or network structured populations. Copyright © 2012 Elsevier Inc. All rights reserved.
Work, family and life-course fit
Moen, Phyllis; Kelly, Erin; Huang, Qinlei
2008-01-01
This study moves from “work-family” to a multi-dimensional “life-course fit” construct (employees’ cognitive assessments of resources, resource deficits, and resource demands), using a combined work-family, demands-control and ecology of the life course framing. It examined (1) impacts of job and home ecological systems on fit dimensions, and (2) whether control over work time predicted and mediated life-course fit outcomes. Using cluster analysis of survey data on a sample of 917 white-collar employees from Best Buy headquarters, we identified four job ecologies (corresponding to the job demands-job control model) and five home ecologies (theorizing an analogous home demands-home control model). Job and home ecologies predicted fit dimensions in an additive, not interactive, fashion. Employees’ work-time control predicted every life-course fit dimension and partially mediated effects of job ecologies, organizational tenure, and job category. PMID:19430546
Fitness consequences of sex-specific selection.
Connallon, Tim; Cox, Robert M; Calsbeek, Ryan
2010-06-01
Theory suggests that sex-specific selection can facilitate adaptation in sexually reproducing populations. However, sexual conflict theory and recent experiments indicate that sex-specific selection is potentially costly due to sexual antagonism: alleles harmful to one sex can accumulate within a population because they are favored in the other sex. Whether sex-specific selection provides a net fitness benefit or cost depends, in part, on the relative frequency and strength of sexually concordant versus sexually antagonistic selection throughout a species' genome. Here, we model the net fitness consequences of sex-specific selection while explicitly considering both sexually concordant and sexually antagonistic selection. The model shows that, even when sexual antagonism is rare, the fitness costs that it imposes will generally overwhelm fitness benefits of sexually concordant selection. Furthermore, the cost of sexual antagonism is, at best, only partially resolved by the evolution of sex-limited gene expression. To evaluate the key parameters of the model, we analyze an extensive dataset of sex-specific selection gradients from wild populations, along with data from the experimental evolution literature. The model and data imply that sex-specific selection may likely impose a net cost on sexually reproducing species, although additional research will be required to confirm this conclusion.
ERIC Educational Resources Information Center
Gentry, Marcia
2010-01-01
This article presents the author's brief comment on Hisham B. Ghassib's "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?" Ghassib (2010) takes the reader through an interesting history of human innovation and processes and situates his theory within a productivist model. The deliberate attention to…
NASA Astrophysics Data System (ADS)
Balázs, Csaba; Li, Tong
2016-05-01
In this work we perform a comprehensive statistical analysis of the AMS-02 electron, positron fluxes and the antiproton-to-proton ratio in the context of a simplified dark matter model. We include known, standard astrophysical sources and a dark matter component in the cosmic ray injection spectra. To predict the AMS-02 observables we use propagation parameters extracted from observed fluxes of heavier nuclei and the low energy part of the AMS-02 data. We assume that the dark matter particle is a Majorana fermion coupling to third generation fermions via a spin-0 mediator, and annihilating to multiple channels at once. The simultaneous presence of various annihilation channels provides the dark matter model with additional flexibility, and this enables us to simultaneously fit all cosmic ray spectra using a simple particle physics model and coherent astrophysical assumptions. Our results indicate that AMS-02 observations are not only consistent with the dark matter hypothesis within the uncertainties, but adding a dark matter contribution improves the fit to the data. Assuming, however, that dark matter is solely responsible for this improvement of the fit, it is difficult to evade the latest CMB limits in this model.
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
Ward, Jeffery Kurt; Hastie, Peter A; Wadsworth, Danielle D; Foote, Shelby; Brock, Sheri J; Hollett, Nikki
2017-09-01
The purpose of this study was to determine the extent to which a sport education season of fitness could provide students with recommended levels of in-class moderate-to-vigorous physical activity (MVPA) while also increasing students' fitness knowledge and fitness achievement. One hundred and sixty-six 5th-grade students (76 boys, 90 girls) participated in a 20-lesson season called "CrossFit Challenge" during a 4-week period. The Progressive Aerobic Cardiovascular Endurance Run, push-ups, and curl-ups tests of the FITNESSGRAM® were used to assess fitness at pretest and posttest, while fitness knowledge was assessed through a validated, grade-appropriate test of health-related fitness knowledge (HRF). Physical activity was measured with Actigraph GT3X triaxial accelerometers. Results indicated a significant time effect for all fitness tests and the knowledge test. Across the entire season, the students spent an average of 54.5% of lesson time engaged in MVPA, irrespective of the type of lesson (instruction, free practice, or competition). The results suggest that configuring the key principles of sport education within a unit of fitness is an efficient model for providing students with the opportunity to improve fitness skill and HRF knowledge while attaining recommended levels of MVPA.
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)…
Percolation on fitness landscapes: effects of correlation, phenotype, and incompatibilities
Gravner, Janko; Pitman, Damien; Gavrilets, Sergey
2009-01-01
We study how correlations in the random fitness assignment may affect the structure of fitness landscapes, in three classes of fitness models. The first is a phenotype space in which individuals are characterized by a large number n of continuously varying traits. In a simple model of random fitness assignment, viable phenotypes are likely to form a giant connected cluster percolating throughout the phenotype space provided the viability probability is larger than 1/2n. The second model explicitly describes genotype-to-phenotype and phenotype-to-fitness maps, allows for neutrality at both phenotype and fitness levels, and results in a fitness landscape with tunable correlation length. Here, phenotypic neutrality and correlation between fitnesses can reduce the percolation threshold, and correlations at the point of phase transition between local and global are most conducive to the formation of the giant cluster. In the third class of models, particular combinations of alleles or values of phenotypic characters are “incompatible” in the sense that the resulting genotypes or phenotypes have zero fitness. This setting can be viewed as a generalization of the canonical Bateson-Dobzhansky-Muller model of speciation and is related to K- SAT problems, prominent in computer science. We analyze the conditions for the existence of viable genotypes, their number, as well as the structure and the number of connected clusters of viable genotypes. We show that analysis based on expected values can easily lead to wrong conclusions, especially when fitness correlations are strong. We focus on pairwise incompatibilities between diallelic loci, but we also address multiple alleles, complex incompatibilities, and continuous phenotype spaces. In the case of diallelic loci, the number of clusters is stochastically bounded and each cluster contains a very large sub-cube. Finally, we demonstrate that the discrete NK model shares some signature properties of models with high
Stiglbauer, Barbara; Kovacs, Carrie
2017-12-28
In organizational psychology research, autonomy is generally seen as a job resource with a monotone positive relationship with desired occupational outcomes such as well-being. However, both Warr's vitamin model and person-environment (PE) fit theory suggest that negative outcomes may result from excesses of some job resources, including autonomy. Thus, the current studies used survey methodology to explore cross-sectional relationships between environmental autonomy, person-environment autonomy (mis)fit, and well-being. We found that autonomy and autonomy (mis)fit explained between 6% and 22% of variance in well-being, depending on type of autonomy (scheduling, method, or decision-making) and type of (mis)fit operationalization (atomistic operationalization through the separate assessment of actual and ideal autonomy levels vs. molecular operationalization through the direct assessment of perceived autonomy (mis)fit). Autonomy (mis)fit (PE-fit perspective) explained more unique variance in well-being than environmental autonomy itself (vitamin model perspective). Detrimental effects of autonomy excess on well-being were most evident for method autonomy and least consistent for decision-making autonomy. We argue that too-much-of-a-good-thing effects of job autonomy on well-being exist, but suggest that these may be dependent upon sample characteristics (range of autonomy levels), type of operationalization (molecular vs. atomistic fit), autonomy facet (method, scheduling, or decision-making), as well as individual and organizational moderators. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Global fits of GUT-scale SUSY models with GAMBIT
NASA Astrophysics Data System (ADS)
Athron, Peter; Balázs, Csaba; Bringmann, Torsten; Buckley, Andy; Chrząszcz, Marcin; Conrad, Jan; Cornell, Jonathan M.; Dal, Lars A.; Edsjö, Joakim; Farmer, Ben; Jackson, Paul; Krislock, Abram; Kvellestad, Anders; Mahmoudi, Farvah; Martinez, Gregory D.; Putze, Antje; Raklev, Are; Rogan, Christopher; de Austri, Roberto Ruiz; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Serra, Nicola; Weniger, Christoph; White, Martin
2017-12-01
We present the most comprehensive global fits to date of three supersymmetric models motivated by grand unification: the constrained minimal supersymmetric standard model (CMSSM), and its Non-Universal Higgs Mass generalisations NUHM1 and NUHM2. We include likelihoods from a number of direct and indirect dark matter searches, a large collection of electroweak precision and flavour observables, direct searches for supersymmetry at LEP and Runs I and II of the LHC, and constraints from Higgs observables. Our analysis improves on existing results not only in terms of the number of included observables, but also in the level of detail with which we treat them, our sampling techniques for scanning the parameter space, and our treatment of nuisance parameters. We show that stau co-annihilation is now ruled out in the CMSSM at more than 95% confidence. Stop co-annihilation turns out to be one of the most promising mechanisms for achieving an appropriate relic density of dark matter in all three models, whilst avoiding all other constraints. We find high-likelihood regions of parameter space featuring light stops and charginos, making them potentially detectable in the near future at the LHC. We also show that tonne-scale direct detection will play a largely complementary role, probing large parts of the remaining viable parameter space, including essentially all models with multi-TeV neutralinos.
BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments.
Thomas, Brandon R; Chylek, Lily A; Colvin, Joshua; Sirimulla, Suman; Clayton, Andrew H A; Hlavacek, William S; Posner, Richard G
2016-03-01
Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive. BioNetFit can be used on stand-alone Mac, Windows/Cygwin, and Linux platforms and on Linux-based clusters running SLURM, Torque/PBS, or SGE. The BioNetFit source code (Perl) is freely available (http://bionetfit.nau.edu). Supplementary data are available at Bioinformatics online. bionetgen.help@gmail.com. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Hu, Yu; Wang, Ying; Liang, Hui; Chen, Yaping
2017-12-11
Background: Reasons for acceptance of seasonal influenza vaccine (SIV) vaccination among pregnant women in China are poorly understood. We assessed the intention to accept SIV among pregnant women in Zhejiang province, by using a self-administrated structured questionnaire developed on the basis of health belief model (HBM). Methods: From 1 January to 31 March 2014, pregnant women with ≥12 gestational weeks who attended antenatal clinics (ANCs) at public hospitals in 6 out of 90 districts were surveyed using a self-administered questionnaire that covered knowledge, attitudes, and beliefs related to SIV vaccination and influenza infection. We examined the associations between the acceptance of SIV vaccination and the demographic factors and HBM constructs using the logistic regression model, calculating the adjusted odds ratio (AOR). Results: Of the 1252 participants, 76.28% were willing to receive the SIV vaccination during their current pregnancy. High levels of perceived susceptibility of influenza (AOR = 1.75 (95%CI: 1.36-2.08)), high levels of perceived severity of influenza (AOR = 1.62 (95%CI: 1.25-1.95)), high level of perceived benefits of vaccination (AOR = 1.97 (95%CI: 1.76-2.21)), and high levels of cues to action were positively associated with the acceptance of SIV vaccination among pregnant women (AOR = 2.03 (95%CI: 1.70-2.69)), while high level of perceived barriers of vaccination was a negative determinant (AOR = 0.76 (95%CI: 0.62-0.94)). Conclusions: Poor knowledge and negative attitude towards SIV were associated with the poor acceptance of SIV. Health providers' recommendations were important to pregnant women's acceptance of SIV. Health education and direct communication strategies on SIV vaccination and influenza infection are necessary to improve the acceptance of SIV vaccination among pregnant women.
NASA Astrophysics Data System (ADS)
Bowers, Peter; Rosowski, John J.
2018-05-01
An air-conduction circuit model that will serve as the basis for a model of bone-conduction hearing is developed for chinchilla. The lumped-element model is based on the classic Zwislocki model of the human middle ear. Model parameters are fit to various measurements of chinchilla middle-ear transfer functions and impedances. The model is in agreement with studies of the effects of middle-ear cavity holes in experiments that require access to the middle-ear air space.
Saunders, Christina T; Blume, Jeffrey D
2017-10-26
Mediation analysis explores the degree to which an exposure's effect on an outcome is diverted through a mediating variable. We describe a classical regression framework for conducting mediation analyses in which estimates of causal mediation effects and their variance are obtained from the fit of a single regression model. The vector of changes in exposure pathway coefficients, which we named the essential mediation components (EMCs), is used to estimate standard causal mediation effects. Because these effects are often simple functions of the EMCs, an analytical expression for their model-based variance follows directly. Given this formula, it is instructive to revisit the performance of routinely used variance approximations (e.g., delta method and resampling methods). Requiring the fit of only one model reduces the computation time required for complex mediation analyses and permits the use of a rich suite of regression tools that are not easily implemented on a system of three equations, as would be required in the Baron-Kenny framework. Using data from the BRAIN-ICU study, we provide examples to illustrate the advantages of this framework and compare it with the existing approaches. © The Author 2017. Published by Oxford University Press.
Muntaner, C; Schoenbach, C
1994-01-01
The authors use confirmatory factor analysis to investigate the psychosocial dimensions of work environments relevant to health outcomes, in a representative sample of five U.S. metropolitan areas. Through an aggregated inference system, scales from Schwartz and associates' job scoring system and from the Dictionary of Occupational Titles (DOT) were employed to examine two alternative models: the demand-control model of Karasek and Theorell and Johnson's demand-control-support model. Confirmatory factor analysis was used to test the two models. The two multidimensional models yielded better fits than an unstructured model. After allowing for the measurement error variance due to the method of assessment (Schwartz and associates' system or DOT), both models yielded acceptable goodness-of-fit indices, but the fit of the demand-control-support model was significantly better. Overall these results indicate that the dimensions of Control (substantive complexity of work, skill discretion, decision authority), Demands (physical exertion, physical demands and hazards), and Social Support (coworker and supervisor social supports) provide an acceptable account of the psychosocial dimensions of work associated with health outcomes.
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.
The Blazar 3C 66A in 2003-2004: hadronic versus leptonic model fits
DOE Office of Scientific and Technical Information (OSTI.GOV)
Reimer, A.; Joshi, M.; Boettcher, M.
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.
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.
Tao, Donghua
2008-01-01
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. PMID:18999300
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.
Berry, Diane; Maloney, Ann E.; Sikich, Linmarie
2012-01-01
Abstract Objective The aim of our feasibility study was to examine the acceptability and utility of “Dance Dance Revolution” (DDR) (Konami of America, Redwood City, CA)) to increase physical fitness in 8–11-year-old black and Hispanic youth. Subjects and Methods Twenty-eight 4th and 5th grade children attending an afterschool program participated. Outcomes included physical activity, physical fitness, use of home DDR, survey of safety and acceptability, anthropometrics, and fasting metabolic profile measured at baseline, 12 weeks, and 30 weeks. Results At 12 weeks, physical fitness (maximum O2 uptake [VO2max]) increased by 4.9±9.9 percent and was sustained through 30 weeks, when the VO2max was 105.0±9.9 percent (range, 93.0–133.9 percent) of baseline values. Absolute VO2max increased by 2.97±4.99 mL/kg/minute (95% confidence interval 0.75–5.19, P=0.013). Participants maintained an average of 1.12 hours/day of increased movement to music. Trends suggested increased total moderate–vigorous physical activity, decreased light activity, and a modest increase in sedentary screen time. There were no significant changes in body mass index, fasting lipids, or glucose. Participants and parents approved of the activity. Conclusion DDR appears feasible and acceptable to minority youth. DDR may increase moderate–vigorous physical activity and improve physical fitness in at-risk populations. PMID:26196430
DeWall, C Nathan; Baumeister, Roy F; Vohs, Kathleen D
2008-12-01
Seven experiments showed that the effects of social acceptance and social exclusion on self-regulatory performance depend on the prospect of future acceptance. Excluded participants showed decrements in self-regulation, but these decrements were eliminated if the self-regulation task was ostensibly a diagnostic indicator of the ability to get along with others. No such improvement was found when the task was presented as diagnostic of good health. Accepted participants, in contrast, performed relatively poorly when the task was framed as a diagnostic indicator of interpersonally attractive traits. Furthermore, poor performance among accepted participants was not due to self-handicapping or overconfidence. Offering accepted participants a cash incentive for self-regulating eliminated the self-regulation deficits. These findings provide evidence that the need to belong fits standard motivational patterns: Thwarting the drive intensifies it, whereas satiating it leads to temporary reduction in drive. Accepted people are normally good at self-regulation but are unwilling to exert the effort to self-regulate if self-regulation means gaining the social acceptance they have already obtained.
DeWall, C. Nathan; Baumeister, Roy F.; Vohs, Kathleen D.
2008-01-01
Seven experiments showed that the effects of social acceptance and social exclusion on self-regulatory performance depend on the prospect of future acceptance. Excluded participants showed decrements in self-regulation, but these decrements were eliminated if the self-regulation task was ostensibly a diagnostic indicator of the ability to get along with others. No such improvement was found when the task was presented as diagnostic of good health. Accepted participants, in contrast, performed relatively poorly when the task was framed as a diagnostic indicator of interpersonally attractive traits. Furthermore, poor performance among accepted participants was not due to self-handicapping or overconfidence. Offering accepted participants a cash incentive for self-regulating eliminated the self-regulation deficits. These findings provide evidence that the need to belong fits standard motivational patterns: thwarting the drive intensifies it, whereas satiating it leads to temporary reduction in drive. Accepted people are normally good at self-regulation but are unwilling to exert the effort to self-regulate if self-regulation means gaining the social acceptance they have already obtained. PMID:19025289
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
Consumer acceptance and stability of spray dried betanin in model juices.
Kaimainen, Mika; Laaksonen, Oskar; Järvenpää, Eila; Sandell, Mari; Huopalahti, Rainer
2015-11-15
Spray dried beetroot powder was used to colour model juices, and the consumer acceptance of the juices and stability of the colour during storage at 60 °C, 20 °C, 4 °C, and -20 °C were studied. The majority of the consumers preferred the model juices coloured with anthocyanins or beetroot extract over model juices coloured with spray dried beetroot powder. The consumers preferred more intensely coloured samples over lighter samples. Spray dried betanin samples were described as 'unnatural' and 'artificial' whereas the colour of beetroot extract was described more 'natural' and 'real juice'. No beetroot-derived off-odours or off-flavours were perceived in the model juices coloured with beetroot powder. Colour stability in model juices was greatly dependent on storage temperature with better stability at lower temperatures. Colour stability in the spray dried powder was very good at 20 °C. Betacyanins from beetroot could be a potential colourant for food products that are stored cold. Copyright © 2015 Elsevier Ltd. All rights reserved.
Universality Classes of Interaction Structures for NK Fitness Landscapes
NASA Astrophysics Data System (ADS)
Hwang, Sungmin; Schmiegelt, Benjamin; Ferretti, Luca; Krug, Joachim
2018-02-01
Kauffman's NK-model is a paradigmatic example of a class of stochastic models of genotypic fitness landscapes that aim to capture generic features of epistatic interactions in multilocus systems. Genotypes are represented as sequences of L binary loci. The fitness assigned to a genotype is a sum of contributions, each of which is a random function defined on a subset of k ≤ L loci. These subsets or neighborhoods determine the genetic interactions of the model. Whereas earlier work on the NK model suggested that most of its properties are robust with regard to the choice of neighborhoods, recent work has revealed an important and sometimes counter-intuitive influence of the interaction structure on the properties of NK fitness landscapes. Here we review these developments and present new results concerning the number of local fitness maxima and the statistics of selectively accessible (that is, fitness-monotonic) mutational pathways. In particular, we develop a unified framework for computing the exponential growth rate of the expected number of local fitness maxima as a function of L, and identify two different universality classes of interaction structures that display different asymptotics of this quantity for large k. Moreover, we show that the probability that the fitness landscape can be traversed along an accessible path decreases exponentially in L for a large class of interaction structures that we characterize as locally bounded. Finally, we discuss the impact of the NK interaction structures on the dynamics of evolution using adaptive walk models.
Universality Classes of Interaction Structures for NK Fitness Landscapes
NASA Astrophysics Data System (ADS)
Hwang, Sungmin; Schmiegelt, Benjamin; Ferretti, Luca; Krug, Joachim
2018-07-01
Kauffman's NK-model is a paradigmatic example of a class of stochastic models of genotypic fitness landscapes that aim to capture generic features of epistatic interactions in multilocus systems. Genotypes are represented as sequences of L binary loci. The fitness assigned to a genotype is a sum of contributions, each of which is a random function defined on a subset of k ≤ L loci. These subsets or neighborhoods determine the genetic interactions of the model. Whereas earlier work on the NK model suggested that most of its properties are robust with regard to the choice of neighborhoods, recent work has revealed an important and sometimes counter-intuitive influence of the interaction structure on the properties of NK fitness landscapes. Here we review these developments and present new results concerning the number of local fitness maxima and the statistics of selectively accessible (that is, fitness-monotonic) mutational pathways. In particular, we develop a unified framework for computing the exponential growth rate of the expected number of local fitness maxima as a function of L, and identify two different universality classes of interaction structures that display different asymptotics of this quantity for large k. Moreover, we show that the probability that the fitness landscape can be traversed along an accessible path decreases exponentially in L for a large class of interaction structures that we characterize as locally bounded. Finally, we discuss the impact of the NK interaction structures on the dynamics of evolution using adaptive walk models.
Acceptability and validity of older driver screening with the DrivingHealth Inventory.
Edwards, Jerri D; Leonard, Kathleen M; Lunsman, Melissa; Dodson, Joan; Bradley, Stacy; Myers, Charlsie A; Hubble, Bridgette
2008-05-01
Research has indicated that technology can be effectively used to identify high-risk older drivers. However, adaptation of such technology has been limited. Researchers debate whether older drivers represent a safety problem as well as whether they should be screened for driving fitness. The present study examined how drivers feel regarding technological screening and mandatory state testing. The validity and acceptability of a new technological screening battery for identifying high-risk drivers, the DrivingHealth Inventory (DHI), was also evaluated. In a sample of 258 Alabama drivers aged 18-87, older drivers performed significantly worse than younger drivers on sensory, cognitive, and physical subtests of the DHI, and older drivers with a crash history performed worse than older drivers without crashes. Regardless of age, 90% of participants supported states requiring screening for older drivers' license renewal. The majority of the participants (72%) supported use of technological screening batteries such as the DHI as a driver screening tool. Considering the acceptability and potential efficacy of the DHI, it may be a useful tool in evaluating driving fitness among older adults.
NLINEAR - NONLINEAR CURVE FITTING PROGRAM
NASA Technical Reports Server (NTRS)
Everhart, J. L.
1994-01-01
A common method for fitting data is a least-squares fit. In the least-squares method, a user-specified fitting function is utilized in such a way as to minimize the sum of the squares of distances between the data points and the fitting curve. The Nonlinear Curve Fitting Program, NLINEAR, is an interactive curve fitting routine based on a description of the quadratic expansion of the chi-squared statistic. NLINEAR utilizes a nonlinear optimization algorithm that calculates the best statistically weighted values of the parameters of the fitting function and the chi-square that is to be minimized. The inputs to the program are the mathematical form of the fitting function and the initial values of the parameters to be estimated. This approach provides the user with statistical information such as goodness of fit and estimated values of parameters that produce the highest degree of correlation between the experimental data and the mathematical model. In the mathematical formulation of the algorithm, the Taylor expansion of chi-square is first introduced, and justification for retaining only the first term are presented. From the expansion, a set of n simultaneous linear equations are derived, which are solved by matrix algebra. To achieve convergence, the algorithm requires meaningful initial estimates for the parameters of the fitting function. NLINEAR is written in Fortran 77 for execution on a CDC Cyber 750 under NOS 2.3. It has a central memory requirement of 5K 60 bit words. Optionally, graphical output of the fitting function can be plotted. Tektronix PLOT-10 routines are required for graphics. NLINEAR was developed in 1987.
Modeling the Etiology of Adolescent Substance Use: A Test of the Social Development Model
Catalano, Richard F.; Kosterman, Rick; Hawkins, J. David; Newcomb, Michael D.; Abbott, Robert D.
2007-01-01
The social development model is a general theory of human behavior that seeks to explain antisocial behaviors through specification of predictive developmental relationships. It incorporates the effects of empirical predictors (“risk factors” and “protective factors”) for antisocial behavior and attempts to synthesize the most strongly supported propositions of control theory, social learning theory, and differential association theory. This article examines the power of social development model constructs measured at ages 9 to 10 and 13 to 14 to predict drug use at ages 17 to 18. The sample of 590 is from the longitudinal panel of the Seattle Social Development Project, which in 1985 sampled fifth grade students from high crime neighborhoods in Seattle, Washington. Structural equation modeling techniques were used to examine the fit of the model to the data. Although all but one path coefficient were significant and in the expected direction, the model did not fit the data as well as expected (CFI=.87). We next specified second-order factors for each path to capture the substantial common variance in the constructs' opportunities, involvement, and rewards. This model fit the data well (CFI=.90). We conclude that the social development model provides an acceptable fit to predict drug use at ages 17 to 18. Implications for the temporal nature of key constructs and for prevention are discussed. PMID:17848978
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
Yang, Hui-Ju; Chen, Kuei-Min; Chen, Ming-De; Wu, Hui-Chuan; Chang, Wen-Jane; Wang, Yueh-Chin; Huang, Hsin-Ting
2015-10-01
The transtheoretical model was applied to promote behavioural change and test the effects of a group senior elastic band exercise programme on the functional fitness of community older adults in the contemplation and preparation stages of behavioural change. Forming regular exercise habits is challenging for older adults. The transtheoretical model emphasizes using different strategies in various stages to facilitate behavioural changes. Quasi-experimental design with pre-test and post-tests on two groups. Six senior activity centres were randomly assigned to either the experimental or control group. The data were collected during 2011. A total of 199 participants were recruited and 169 participants completed the study (experimental group n = 84, control group n = 85). The elastic band exercises were performed for 40 minutes, three times per week for 6 months. The functional fitness of the participants was evaluated at baseline and at the third and sixth month of the intervention. Statistical analyses included a two-way mixed design analysis of variance, one-way repeated measures analysis of variance and an analysis of covariance. All of the functional fitness indicators had significant changes at post-tests from pre-test in the experimental group. The experimental group had better performances than the control group in all of the functional fitness indicators after three months and 6 months of the senior elastic band exercises. The exercise programme provided older adults with appropriate strategies for maintaining functional fitness, which improved significantly after the participants exercising regularly for 6 months. © 2015 John Wiley & Sons Ltd.
Helgesson, P; Sjöstrand, H
2017-11-01
Fitting a parametrized function to data is important for many researchers and scientists. If the model is non-linear and/or defect, it is not trivial to do correctly and to include an adequate uncertainty analysis. This work presents how the Levenberg-Marquardt algorithm for non-linear generalized least squares fitting can be used with a prior distribution for the parameters and how it can be combined with Gaussian processes to treat model defects. An example, where three peaks in a histogram are to be distinguished, is carefully studied. In particular, the probability r 1 for a nuclear reaction to end up in one out of two overlapping peaks is studied. Synthetic data are used to investigate effects of linearizations and other assumptions. For perfect Gaussian peaks, it is seen that the estimated parameters are distributed close to the truth with good covariance estimates. This assumes that the method is applied correctly; for example, prior knowledge should be implemented using a prior distribution and not by assuming that some parameters are perfectly known (if they are not). It is also important to update the data covariance matrix using the fit if the uncertainties depend on the expected value of the data (e.g., for Poisson counting statistics or relative uncertainties). If a model defect is added to the peaks, such that their shape is unknown, a fit which assumes perfect Gaussian peaks becomes unable to reproduce the data, and the results for r 1 become biased. It is, however, seen that it is possible to treat the model defect with a Gaussian process with a covariance function tailored for the situation, with hyper-parameters determined by leave-one-out cross validation. The resulting estimates for r 1 are virtually unbiased, and the uncertainty estimates agree very well with the underlying uncertainty.
NASA Astrophysics Data System (ADS)
Helgesson, P.; Sjöstrand, H.
2017-11-01
Fitting a parametrized function to data is important for many researchers and scientists. If the model is non-linear and/or defect, it is not trivial to do correctly and to include an adequate uncertainty analysis. This work presents how the Levenberg-Marquardt algorithm for non-linear generalized least squares fitting can be used with a prior distribution for the parameters and how it can be combined with Gaussian processes to treat model defects. An example, where three peaks in a histogram are to be distinguished, is carefully studied. In particular, the probability r1 for a nuclear reaction to end up in one out of two overlapping peaks is studied. Synthetic data are used to investigate effects of linearizations and other assumptions. For perfect Gaussian peaks, it is seen that the estimated parameters are distributed close to the truth with good covariance estimates. This assumes that the method is applied correctly; for example, prior knowledge should be implemented using a prior distribution and not by assuming that some parameters are perfectly known (if they are not). It is also important to update the data covariance matrix using the fit if the uncertainties depend on the expected value of the data (e.g., for Poisson counting statistics or relative uncertainties). If a model defect is added to the peaks, such that their shape is unknown, a fit which assumes perfect Gaussian peaks becomes unable to reproduce the data, and the results for r1 become biased. It is, however, seen that it is possible to treat the model defect with a Gaussian process with a covariance function tailored for the situation, with hyper-parameters determined by leave-one-out cross validation. The resulting estimates for r1 are virtually unbiased, and the uncertainty estimates agree very well with the underlying uncertainty.
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.
Testing goodness of fit in regression: a general approach for specified alternatives.
Solari, Aldo; le Cessie, Saskia; Goeman, Jelle J
2012-12-10
When fitting generalized linear models or the Cox proportional hazards model, it is important to have tools to test for lack of fit. Because lack of fit comes in all shapes and sizes, distinguishing among different types of lack of fit is of practical importance. We argue that an adequate diagnosis of lack of fit requires a specified alternative model. Such specification identifies the type of lack of fit the test is directed against so that if we reject the null hypothesis, we know the direction of the departure from the model. The goodness-of-fit approach of this paper allows to treat different types of lack of fit within a unified general framework and to consider many existing tests as special cases. Connections with penalized likelihood and random effects are discussed, and the application of the proposed approach is illustrated with medical examples. Tailored functions for goodness-of-fit testing have been implemented in the R package global test. Copyright © 2012 John Wiley & Sons, Ltd.
Definitions: Health, Fitness, and Physical Activity.
ERIC Educational Resources Information Center
Corbin, Charles B.; Pangrazi, Robert P.; Franks, B. Don
2000-01-01
This paper defines a variety of fitness components, using a simple multidimensional hierarchical model that is consistent with recent definitions in the literature. It groups the definitions into two broad categories: product and process. Products refer to states of being such as physical fitness, health, and wellness. They are commonly referred…
Chakrapani, Venkatesan; Newman, Peter A; Shunmugam, Murali; Mengle, Shruta; Nelson, Ruban; Rubincam, Clara; Kumar, Pushpesh
2017-07-01
Topical rectal microbicides (RMs) are a new prevention technology in development that aims to reduce the risk of HIV acquisition from anal sex. We examined RM acceptability among men who have sex with men (MSM) in India. We conducted a qualitative exploratory study guided by a modified Technology Acceptance Model, with 10 focus groups ( n = 61) of MSM and 10 key informant interviews. Data were explored using framework analysis. RM acceptability was influenced by technological contexts: perceived usefulness of RMs, perceived ease of use of RM and applicator, and habits around condom and lubricant use; individual and interpersonal contexts: perceived relevance and preferences for product formulation and dosing frequency; and MSM community/social contexts: perceived social approval, RM-related stigma, social support. Implementation of RMs for MSM in India may be supported by multi-level interventions that engage community-based organizations in destigmatizing and distributing RMs, ideally gel-based products that enable on-demand use before sex.
Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution
NASA Astrophysics Data System (ADS)
Yunus, R. M.; Hasan, M. M.; Zubairi, Y. Z.
2017-09-01
In this study, the Tweedie distribution was used to fit the monthly rainfall data from 24 monitoring stations of Peninsula Malaysia for the period from January, 2008 to April, 2015. The aim of the study is to determine whether the distributions within the Tweedie family fit well the monthly Malaysian rainfall data. Within the Tweedie family, the gamma distribution is generally used for fitting the rainfall totals, however the Poisson-gamma distribution is more useful to describe two important features of rainfall pattern, which are the occurrences (dry months) and the amount (wet months). First, the appropriate distribution of the monthly rainfall was identified within the Tweedie family for each station. Then, the Tweedie Generalised Linear Model (GLM) with no explanatory variable was used to model the monthly rainfall data. Graphical representation was used to assess model appropriateness. The QQ plots of quantile residuals show that the Tweedie models fit the monthly rainfall data better for majority of the stations in the west coast and mid land than those in the east coast of Peninsula. This significant finding suggests that the best fitted distribution depends on the geographical location of the monitoring station. In this paper, a simple model is developed for generating synthetic rainfall data for use in various areas, including agriculture and irrigation. We have showed that the data that were simulated using the Tweedie distribution have fairly similar frequency histogram to that of the actual data. Both the mean number of rainfall events and mean amount of rain for a month were estimated simultaneously for the case that the Poisson gamma distribution fits the data reasonably well. Thus, this work complements previous studies that fit the rainfall amount and the occurrence of rainfall events separately, each to a different distribution.
Molecular mechanisms of protein aggregation from global fitting of kinetic models.
Meisl, Georg; Kirkegaard, Julius B; Arosio, Paolo; Michaels, Thomas C T; Vendruscolo, Michele; Dobson, Christopher M; Linse, Sara; Knowles, Tuomas P J
2016-02-01
The elucidation of the molecular mechanisms by which soluble proteins convert into their amyloid forms is a fundamental prerequisite for understanding and controlling disorders that are linked to protein aggregation, such as Alzheimer's and Parkinson's diseases. However, because of the complexity associated with aggregation reaction networks, the analysis of kinetic data of protein aggregation to obtain the underlying mechanisms represents a complex task. Here we describe a framework, using quantitative kinetic assays and global fitting, to determine and to verify a molecular mechanism for aggregation reactions that is compatible with experimental kinetic data. We implement this approach in a web-based software, AmyloFit. Our procedure starts from the results of kinetic experiments that measure the concentration of aggregate mass as a function of time. We illustrate the approach with results from the aggregation of the β-amyloid (Aβ) peptides measured using thioflavin T, but the method is suitable for data from any similar kinetic experiment measuring the accumulation of aggregate mass as a function of time; the input data are in the form of a tab-separated text file. We also outline general experimental strategies and practical considerations for obtaining kinetic data of sufficient quality to draw detailed mechanistic conclusions, and the procedure starts with instructions for extensive data quality control. For the core part of the analysis, we provide an online platform (http://www.amylofit.ch.cam.ac.uk) that enables robust global analysis of kinetic data without the need for extensive programming or detailed mathematical knowledge. The software automates repetitive tasks and guides users through the key steps of kinetic analysis: determination of constraints to be placed on the aggregation mechanism based on the concentration dependence of the aggregation reaction, choosing from several fundamental models describing assembly into linear aggregates and
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…
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…
NASA Astrophysics Data System (ADS)
Kabir, Muhammad Auwal; Saidin, Siti Zabedah; Ahmi, Aidi
2017-10-01
The aim of this paper is to develop a conceptual framework that would be used in determining the factors that influence the behavioral intention to use electronic collection system in federal government owned hospitals in Nigeria. The framework is supported by Technology Acceptance Model (TAM) as the underlying theory of the study. Past literature on individual user intention were thoroughly reviewed and found that TAM is fit appropriate in explaining the phenomenon under study. Based on the reviewed literature, it is expected that perceived usefulness and perceived ease of use will influence the intention of users (employees) to use e-collection system in the performance of their job tasks in Nigerian federal hospitals. In other words, users with higher perception on the system's usefulness and its ease of use are more likely to express their interest and willingness to use the system. In addition, the study has extended TAM with facilitating conditions construct and the research is expected to discover the level of its influence on behavioral intention to use e-collection system.
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.