Empirical guidelines for use of irregular wave model to estimate nearshore wave height /

"July 1982."

Examining alternative econometric specifications of the disequilibrium model : an empirical study with labor market data /

"October 1986."

The etiology of social phobia: Empirical evidence and an initial model

Research into the etiology of social phobia has lagged far behind that of descriptive and maintaining factors. The current paper reviews data from a variety of sources that have some bearing on questions of the origins of social fears. Areas examined include genetic factors, temperament, childrearing, negative life events, and adverse social experiences. Epidemiological data are examined in detail and factors associated with social phobia such as cognitive distortions and social skills are also covered. The paper concludes with an initial model that draws together some of the current findings and aims to provide a platform for future research directions. (C) 2004 Elsevier Ltd. All rights reserved.

How does your model grow? An empirical investigation of the effects of ontological clarity and application domain size on query performance

Semantic data models provide a map of the components of an information system. The characteristics of these models affect their usefulness for various tasks (e.g., information retrieval). The quality of information retrieval has obvious important consequences, both economic and otherwise. Traditionally, data base designers have produced parsimonious logical data models. In spite of their increased size, ontologically clearer conceptual models have been shown to facilitate better performance for both problem solving and information retrieval tasks in experimental settings. The experiments producing evidence of enhanced performance for ontologically clearer models have, however, used application domains of modest size. Data models in organizational settings are likely to be substantially larger than those used in these experiments. This research used an experiment to investigate whether the benefits of improved information retrieval performance associated with ontologically clearer models are robust as the size of the application domains increase. The experiment used an application domain of approximately twice the size as tested in prior experiments. The results indicate that, relative to the users of the parsimonious implementation, end users of the ontologically clearer implementation made significantly more semantic errors, took significantly more time to compose their queries, and were significantly less confident in the accuracy of their queries.

An empirical study of Hoelfding Racing for model selction in K-nearest neighbor classification

Racing algorithms have recently been proposed as a general-purpose method for performing model selection in machine teaming algorithms. In this paper, we present an empirical study of the Hoeffding racing algorithm for selecting the k parameter in a simple k-nearest neighbor classifier. Fifteen widely-used classification datasets from UCI are used and experiments conducted across different confidence levels for racing. The results reveal a significant amount of sensitivity of the k-nn classifier to its model parameter value. The Hoeffding racing algorithm also varies widely in its performance, in terms of the computational savings gained over an exhaustive evaluation. While in some cases the savings gained are quite small, the racing algorithm proved to be highly robust to the possibility of erroneously eliminating the optimal models. All results were strongly dependent on the datasets used.

Is there a global model of learning organizations? An empirical, cross-nation study

This paper develops and tests a learning organization model derived from HRM and dynamic capability literatures in order to ascertain the model's applicability across divergent global contexts. We define a learning organization as one capable of achieving on-going strategic renewal, arguing based on dynamic capability theory that the model has three necessary antecedents: HRM focus, developmental orientation and customer-facing remit. Drawing on a sample comprising nearly 6000 organizations across 15 countries, we show that learning organizations exhibit higher performance than their less learning-inclined counterparts. We also demonstrate that innovation fully mediates the relationship between our conceptualization of the learning organization and organizational performance in 11 of the 15 countries we examined. It is the first time in our knowledge that these questions have been tested in a major, cross-global study, and our work contributes to both HRM and dynamic capability literatures, especially where the focus is the applicability of best practice parameters across national boundaries.

An empirical study of Kirkpatrick's evaluation model in the hospitality industry

This study examined Kirkpatrick’s training evaluation model (Kirkpatrick & Kirkpatrick, 2006) by assessing a sales training program conducted at an organization in the hospitality industry. The study assessed the employees’ training outcomes of knowledge and skills, job performance, and the impact of the training upon the organization. By assessing these training outcomes and their relationships, the study demonstrated whether Kirkpatrick’s theories are supported and the lower evaluation levels can be used to predict organizational impact. The population for this study was a group of reservations sales agents from a leading luxury hotel chain’s reservations center. During the study period from January 2005 to May 2007, there were 335 reservations sales agents employed in this Global Reservations Center (GRC). The number of reservations sales agents who had completed a sales training program/intervention during this period and had data available for at least two months pre and post training composed the sample for this study. The number of agents was 69 ( N = 69). Four hypotheses were tested through paired-samples t tests, correlation, and hierarchical regression analytic procedures. Results from the analyses supported the hypotheses in this study. The significant improvement in the call score supported hypothesis one that the reservations sales agents who completed the training improved their knowledge of content and required skills in handling calls (Level 2). Hypothesis two was accepted in part as there was significant improvement in call conversion, but there was no significant improvement of time usage. The significant improvement in the sales per call supported hypothesis three that the reservations agents who completed the training contributed to increased organizational impact (Level 4), i.e., made significantly more sales. Last, findings supported hypothesis four that Level 2 and Level 3 variables can be used for predicting Level 4 organizational impact. The findings supported the theory of Kirkpatrick’s evaluation model that in order to expect organizational results, a positive change in behavior (job performance) and learning must occur. The examinations of Levels 2 and 3 helped to partially explain and predict Level 4 results.

The transducer model for contrast detection and discrimination: formal relations, implications, and an empirical test.

The transducer function mu for contrast perception describes the nonlinear mapping of stimulus contrast onto an internal response. Under a signal detection theory approach, the transducer model of contrast perception states that the internal response elicited by a stimulus of contrast c is a random variable with mean mu(c). Using this approach, we derive the formal relations between the transducer function, the threshold-versus-contrast (TvC) function, and the psychometric functions for contrast detection and discrimination in 2AFC tasks. We show that the mathematical form of the TvC function is determined only by mu, and that the psychometric functions for detection and discrimination have a common mathematical form with common parameters emanating from, and only from, the transducer function mu and the form of the distribution of the internal responses. We discuss the theoretical and practical implications of these relations, which have bearings on the tenability of certain mathematical forms for the psychometric function and on the suitability of empirical approaches to model validation. We also present the results of a comprehensive test of these relations using two alternative forms of the transducer model: a three-parameter version that renders logistic psychometric functions and a five-parameter version using Foley's variant of the Naka-Rushton equation as transducer function. Our results support the validity of the formal relations implied by the general transducer model, and the two versions that were contrasted account for our data equally well.

Model reduction for nonlinear aerodynamics and aeroelasticity using a Discrete Empirical Interpolation Method

A novel surrogate model is proposed in lieu of Computational Fluid Dynamics (CFD) solvers, for fast nonlinear aerodynamic and aeroelastic modeling. A nonlinear function is identified on selected interpolation points by
a discrete empirical interpolation method (DEIM). The flow field is then reconstructed using a least square approximation of the flow modes extracted
by proper orthogonal decomposition (POD). The aeroelastic reduce order
model (ROM) is completed by introducing a nonlinear mapping function
between displacements and the DEIM points. The proposed model is investigated to predict the aerodynamic forces due to forced motions using
a N ACA 0012 airfoil undergoing a prescribed pitching oscillation. To investigate aeroelastic problems at transonic conditions, a pitch/plunge airfoil
and a cropped delta wing aeroelastic models are built using linear structural models. The presence of shock-waves triggers the appearance of limit
cycle oscillations (LCO), which the model is able to predict. For all cases
tested, the new ROM shows the ability to replicate the nonlinear aerodynamic forces, structural displacements and reconstruct the complete flow
field with sufficient accuracy at a fraction of the cost of full order CFD
model.

Model reduction for nonlinear aeroelasticity using the Discrete Empirical Interpolation Method

A novel surrogate model is proposed in lieu of computational fluid dynamic (CFD) code for fast nonlinear aerodynamic modeling. First, a nonlinear function is identified on selected interpolation points defined by discrete empirical interpolation method (DEIM). The flow field is then reconstructed by a least square approximation of flow modes extracted by proper orthogonal decomposition (POD). The proposed model is applied in the prediction of limit cycle oscillation for a plunge/pitch airfoil and a delta wing with linear structural model, results are validate against a time accurate CFD-FEM code. The results show the model is able to replicate the aerodynamic forces and flow fields with sufficient accuracy while requiring a fraction of CFD cost.