Objective: The shape of the current physical and computational surrogates of children used for restraint system assessments is based largely on standard anthropometric dimensions. These scalar dimensions provide valuable information on the overall size of the individual but do not provide good guidance on shape or posture. This study introduced the development of a parametric model that statistically predicts individual child body shapes in seated postures with a few given parameters.
Methods: Surface geometry data from a laser scanner of children ages 3 to 11 (n = 135) were standardized by a 2-level fitting method using intermediate templates. The standardized data were analyzed by principal component analysis (PCA) to efficiently describe the body shape variance. Parameters such as stature, body mass index, erect sitting height, and 2 posture variables related to torso recline and lumbar spine flexion were associated with the PCA model using regression.
Results: When the original scan data were compared with the predictions of the model using the given subject dimensions, the average root mean square error for the torso was 9.5 mm, and the 95th percentile error was 17.35 mm.
Conclusions: For the first time, a statistical model of child body shapes in seated postures is available. This parametric model allows the generation of an infinite number of virtual children spanning a wide range of body sizes and postures. The results have broad applicability in product design and safety analysis. Future work is needed to improve the representation of hands and feet and to extend the age range of the model. The model presented in this article is publicly available online through HumanShape.org. 相似文献
In this study, Hydroelectric Power Plants, which have been built and integrated with irrigation schemes by the State Hydraulic Works which is a government agency and private companies in Turkey, have been examined. Technical, environmental, structural and social problems encountered during their operation have been analyzed, and appropriate solution proposals have been presented in the study for a sustainable irrigation and Hydroelectric Power Plant operation. Consequently, Hydroelectric Power Plants which have been integrated with irrigation schemes should be operated efficiently and they should be operated in attenuation with the environment. However, when hydroelectric projects are developed without preparing their necessary integrated basin management plans, then this will cause environmental, operation and maintenance, administrative, monitoring and evaluation problems. In order to ensure sustainability of hydroelectricity production and also in order to use water resources more efficiently for irrigation; it is very important to find permanent solutions to these problems. 相似文献
Difficulties in determining the standard time justify the need to develop alternative methods to direct measurement procedures. The indirect methods which are comparison and prediction, standard data and formulation, predefined movement-time systems have several deficiencies in time measurement procedures. In this study, an alternative indirect work measurement method based on artificial neural networks (ANNs) is presented which is simple and inexpensive. For the application of the proposed method, the products that have similar production processes are selected among the whole product family produced in a manufacturing company. The standard times of the sampled products that are previously measured are used and the standard times of the remaining several products and semi-products are predicted by the proposed method. The model results show that the proposed method can be applied accurately in companies which produce similar products. 相似文献