This work addresses the design, analysis, and validation of a transtibial custom prosthesis. The methodology consists of the usage of videometry to analyze angular relationships between joints, moments, and reaction forces in the human gait cycle. The customized geometric model of the proposed prosthesis was defined by considering healthy feet for the initial design. The prosthesis model was developed by considering the Flex-Foot^® Variflex^® architecture on a design basis. By means of the analytical method, the size and material of the final model were calculated. The behavior of the prosthesis was evaluated analytically by a curved elements analysis and the Castigliano theorem, and numerically by the Finite Element Method (FEM). The outcome shows the differences between the analytical and numerical methods for the final prosthesis design, with an error rate no greater than 6.5%.

Equalization Control of Nonlinear Systems by Discrete Models of the Volterra Operators

Marine species photo-identification and location for tracking are crucial for understanding the characteristics and patterns that distinguish each marine species. However, challenges in camera data acquisition and the unpredictability of animal movements have restricted progress in this field. To address these challenges, we present a novel algorithm for the first stage of marine species photo-identification and location methods. For marine species photo-identification applications, a color index-based thresholding segmentation method is proposed. This method is based on the characteristics of the GMR (Green Minus Red) color index and the proposed empirical BMG (Blue Minus Green) color index. These color indexes are modified to provide better information about the color of regions, such as marine animals, the sky, and land found in the scientific sightings images, allowing an optimal thresholding segmentation method. In the case of marine species location, a SURFs (Speeded-Up Robust Features)-based supervised classifier is used to obtain the location of the marine animal in the sighting image; with this, its tracking could be obtained. The tests were performed with the Kaggle happywhale public database; the results obtained in precision shown range from 0.77 up to 0.98 using the proposed indexes. Finally, the proposed method could be used in real-time marine species tracking with a processing time of 0.33 s for images of 645 × 376 pixels using a standard PC.