An agent-based approach for the application of nature's forms to product conceptual design.

Given current high market competitiveness, it is necessary to differentiate between products that perform the same function. For this objective, designer can recur to various sources of inspiration in the searching of the more attractive form during the conceptual design stage. One of these sources can be nature, which offers a large number of geometries and textures that can be used from a shape point of view to help the designer in the creative process. This work presents an agent-based approach for a design-aided tool to provide users with some ideas, beginning with simple parts/concepts, and then increasing the complexity level according to the answers offered by designer. The proposed paradigm was implemented using the JADE agent-based platform. In order to validate the platform, several product categories were offered to fifteen different users and a total of sixty design proposals were obtained with the aid of the platform. After evaluating all the proposals, twelve of the sixty designs were finally selected and modelled by a Computer-Aided Design software. The obtained results demonstrate the feasibility of using an agent-based approach to obtain an adaptive intelligent solution to the product conceptual design problem.

Geometrical custom modeling of human cornea in vivo and its use for the diagnosis of corneal ectasia.

AIM: To establish a new procedure for 3D geometric reconstruction of the human cornea to obtain a solid model that represents a personalized and in vivo morphology of both the anterior and posterior corneal surfaces. This model is later analyzed to obtain geometric variables enabling the characterization of the corneal geometry and establishing a new clinical diagnostic criterion in order to distinguish between healthy corneas and corneas with keratoconus. METHOD: The method for the geometric reconstruction of the cornea consists of the following steps: capture and preprocessing of the spatial point clouds provided by the Sirius topographer that represent both anterior and posterior corneal surfaces, reconstruction of the corneal geometric surfaces and generation of the solid model. Later, geometric variables are extracted from the model obtained and statistically analyzed to detect deformations of the cornea. RESULTS: The variables that achieved the best results in the diagnosis of keratoconus were anterior corneal surface area (ROC area: 0.847, p<0.000, std. error: 0.038, 95% CI: 0.777 to 0.925), posterior corneal surface area (ROC area: 0.807, p<0.000, std. error: 0.042, 95% CI: 0,726 to 0,889), anterior apex deviation (ROC area: 0.735, p<0.000, std. error: 0.053, 95% CI: 0.630 to 0.840) and posterior apex deviation (ROC area: 0.891, p<0.000, std. error: 0.039, 95% CI: 0.8146 to 0.9672). CONCLUSION: Geometric modeling enables accurate characterization of the human cornea. Also, from a clinical point of view, the procedure described has established a new approach for the study of eye-related diseases.