RESUMO
In this paper, several approaches to assist employers in the accommodation process for disabled employees are discussed and a mathematical model is proposed to assist employers in predicting the accommodation level needed by an individual with a mobility-related disability. This study investigates the validity and reliability of this model in assessing the accommodation level needed by individuals utilizing data collected from twelve individuals with mobility-related disabilities. Based on the results of the statistical analyses, this proposed model produces a feasible preliminary measure for assessing the accommodation level needed for persons with mobility-related disabilities. Suggestions for practical application of this model in an industrial setting are addressed.
Assuntos
Inteligência Artificial , Sistemas de Apoio a Decisões Clínicas , Técnicas de Apoio para a Decisão , Avaliação da Deficiência , Pessoas com Deficiência/reabilitação , Transtornos dos Movimentos/reabilitação , Avaliação das Necessidades , Adulto , Feminino , Humanos , Masculino , Terapia Ocupacional/métodos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Inquéritos e Questionários , Terapia Assistida por Computador/métodosRESUMO
The University of Central Florida (UCF) was contracted by the Florida Center for Solid and Hazardous Waste Management (FCSHWM) to develop a well-defined methodology for conducting municipal solid waste composition studies. This methodology must account for the statistical variations in waste composition, be economical and practical in implementation, and build on a consensus of waste management professionals. This paper identifies possible sources of bias in waste composition study results and provides guidance for future planning of local waste stream composition analysis. To accomplish this objective, a composition study was designed and implemented for Marion County, FL, in fall 1996. The potential sources of concern investigated in detail were sample weight and contamination. The methodology developed by UCF is statistically valid and if widely implemented would provide a better representation of the waste stream. Lack of contamination adjustment is a major contributor to error in the waste stream analysis and should be accounted for in the methodology. For sample sorts using a large number of categories, sample size may be a contributor to bias. This likelihood for bias can be reduced by increasing the sample weight to at least200 kg, particularly when sorting commercial loads or reducing the number of categories.
