How well do computer-generated faces tap face expertise?

The use of computer-generated (CG) stimuli in face processing research is proliferating due to the ease with which faces can be generated, standardised and manipulated. However there has been surprisingly little research into whether CG faces are processed in the same way as photographs of real faces. The present study assessed how well CG faces tap face identity expertise by investigating whether two indicators of face expertise are reduced for CG faces when compared to face photographs. These indicators were accuracy for identification of own-race faces and the other-race effect (ORE)-the well-established finding that own-race faces are recognised more accurately than other-race faces. In Experiment 1 Caucasian and Asian participants completed a recognition memory task for own- and other-race real and CG faces. Overall accuracy for own-race faces was dramatically reduced for CG compared to real faces and the ORE was significantly and substantially attenuated for CG faces. Experiment 2 investigated perceptual discrimination for own- and other-race real and CG faces with Caucasian and Asian participants. Here again, accuracy for own-race faces was significantly reduced for CG compared to real faces. However the ORE was not affected by format. Together these results signal that CG faces of the type tested here do not fully tap face expertise. Technological advancement may, in the future, produce CG faces that are equivalent to real photographs. Until then caution is advised when interpreting results obtained using CG faces

Effectiveness of an evidence-based chiropractic continuing education workshop on participant knowledge of evidence-based health care

BACKGROUND: Chiropractors must continue to learn, develop themselves professionally throughout their careers, and become self-directed and lifelong learners. Using an evidence-based approach increases the probability of optimal patient outcomes. But most chiropractors lack knowledge and interest in evidence-based approaches. The purpose of this study was to develop and measure the effectiveness of evidence-based training for chiropractic practitioners in a continuing education setting. METHODS: We developed and evaluated a continuing education workshop on evidence-based principles and methods for chiropractic practitioners. Forty-seven chiropractors participated in the training and testing. The course consisted of 12.5 hours of training in which practitioners learned to develop focused questions, search electronic data bases, critically review articles and apply information from the literature to specific clinical questions. Following the workshop, we assessed the program performance through the use of knowledge testing and anonymous presentation quality surveys. RESULTS: Eighty-five percent of the participants completed all of the test, survey and data collection items. Pretest knowledge scores (15-item test) were low (47%). Post intervention scores (15-item test) improved with an effect size of 2.0. A 59-item knowledge posttest yielded very good results (mean score 88%). The quality of presentation was rated very good, and most participants (90%) would "definitely recommend" or "recommend" the workshop to a colleague. CONCLUSION: The results of the study suggest that the continuing education course was effective in enhancing knowledge in the evidence-based approach and that the presentation was well accepted

Predicting implementation from organizational readiness for change: a study protocol

<p>Abstract</p> <p>Background</p> <p>There is widespread interest in measuring organizational readiness to implement evidence-based practices in clinical care. However, there are a number of challenges to validating organizational measures, including inferential bias arising from the halo effect and method bias - two threats to validity that, while well-documented by organizational scholars, are often ignored in health services research. We describe a protocol to comprehensively assess the psychometric properties of a previously developed survey, the Organizational Readiness to Change Assessment.</p> <p>Objectives</p> <p>Our objective is to conduct a comprehensive assessment of the psychometric properties of the Organizational Readiness to Change Assessment incorporating methods specifically to address threats from halo effect and method bias.</p> <p>Methods and Design</p> <p>We will conduct three sets of analyses using longitudinal, secondary data from four partner projects, each testing interventions to improve the implementation of an evidence-based clinical practice. Partner projects field the Organizational Readiness to Change Assessment at baseline (n = 208 respondents; 53 facilities), and prospectively assesses the degree to which the evidence-based practice is implemented. We will conduct predictive and concurrent validities using hierarchical linear modeling and multivariate regression, respectively. For predictive validity, the outcome is the change from baseline to follow-up in the use of the evidence-based practice. We will use intra-class correlations derived from hierarchical linear models to assess inter-rater reliability. Two partner projects will also field measures of job satisfaction for convergent and discriminant validity analyses, and will field Organizational Readiness to Change Assessment measures at follow-up for concurrent validity (n = 158 respondents; 33 facilities). Convergent and discriminant validities will test associations between organizational readiness and different aspects of job satisfaction: satisfaction with leadership, which should be highly correlated with readiness, versus satisfaction with salary, which should be less correlated with readiness. Content validity will be assessed using an expert panel and modified Delphi technique.</p> <p>Discussion</p> <p>We propose a comprehensive protocol for validating a survey instrument for assessing organizational readiness to change that specifically addresses key threats of bias related to halo effect, method bias and questions of construct validity that often go unexplored in research using measures of organizational constructs.</p

A sensitivity study for the second order reliability-based design model of rubble mound breakwaters

The reliability-based risk assessment and structural design model (REBAD) (Balas, 1998) introduced in this paper, is a worthwhile tool in the preliminary design of maritime structures which are portrayed by vast failure consequences and significant resource expenditures. REBAD model in which the Second-Order Reliability Method (SORM) is utilized together with a cost-optimization algorithm, is implemented to Mersin yacht harbor which is constructed near the city of Mersin located on the Turkish coast of Mediterranean Sea. SORM is established on a more correct approximation of the failure surface than the first-order method. The failure mode probability is predicted by approximating the failure surface by a quadratic surface with the identical curvature at the design point. First, REBAD is implemented to the main breakwater by utilising the Hudson failure function to determine the size of armor units, then failure mode response functions were obtained for the fixed exceedance probability of several damage levels. Combining with the hydraulic model study carried out by Ergin and Ozhan (1994) and REBAD outcome, the trunk section of main breakwater and design functions were determined. The second order reliability-based sensitivity study was also carried out to systematically compare limit state equations of Hudson and Van der Meer

Reliability-based risk assessment in coastal projects: Case study in Turkey

The risk of damage during the construction phase of a coastal structure was investigated by utilizing Level II and III reliability methods. Structural risks were incorporated in the planning phase of coastal projects by utilizing a practical risk management approach implemented in the Mezitli (Icel) Yacht Harbor project in Turkey. By specifying the exceedance probability of damage level at the design stage, the delay times of construction activities due to damage were obtained at the project-planning phase, which enabled the estimation of the project completion time. It is found that structural risk of damage in the construction period can be an important factor to be considered in the reliability-based project management. because coastal projects involve considerable damage risk during the construction phase. The application of Monte Carlo simulations (Level III), which is generally performed within a few minutes of CPU time in fast computers, has the advantage of robustness when compared with the second-order methods such as the Hasofer-Lind method, provided that the probability distribution of random variables and their correlation are described with an acceptable accuracy, which should be obtained from data accumulated over a sufficient number of years. In this study, by specifying the exceedance probability of "no damage level" at the design stage, the probability of construction completion times were estimated at the planning phase for the case study of Mezitli Yacht Harbor, where the probability distributions of random variables were obtained from the governmental archives

Failure mode response functions in reliability-based design of rubble-mound breakwaters

The reliability-based model applied in this paper, provides a valuable tool in the design of coastal structures which are characterized by large failure consequences and substantial capital expenditures. Therefore, the implementation of the model to the design of rubble-mound breakwaters has an utmost importance especially in countries such as Turkey, where the use of natural stone for breakwaters is very common due to its economy. The purpose of the present paper is to describe the model by implementing it to Mersin Yacht Harbor which will be constructed near the coastal city of Mersin located on the Mediterranean Sea, and compare the results of the reliability-based model which utilizes the failure functions of Hudson and Van der Meer, with the deterministic design. Mersin Yacht Harbor construction project is a public investment administrated by the Ministry of Transportation. This study is the first application of the reliability-based design for breakwaters in Turkey (Balas, 1996). In the reliability-based model, the hydraulic stability of the main armor layer which is the most important failure mode as dislocking of the armor units under the wave attack, is described to compare the effects of failure mode response functions derived from Hudson and Van der Meer equations

Marine litter prediction by artificial intelligence

Artificial intelligence techniques of neural network and fuzzy systems were applied as alternative methods to determine beach litter grading, based on litter surveys of the Antalya coastline (the Turkish Riviera). Litter measurements were categorized and assessed by artificial intelligence techniques, which lead to a new litter categorization system. The constructed neural network satisfactorily predicted the grading of the Antalya beaches and litter categories based on the number of litter items in the general litter category. It has been concluded that, neural networks could be used for high-speed predictions of litter items and beach grading, when the characteristics of the main litter category was determined by field studies. This can save on field effort when fast and reliable estimations of litter categories are required for management or research studies of beaches-especially those concerned with health and safety, and it has economic implications. The main advantages in using fuzzy systems are that they consider linguistic adjectival definitions, e.g. many/few, etc. As a result, additional information inherent in linguistic comments/refinements and judgments made during field studies can be incorporated in grading systems