Consistent Partial Matching of Shape Collections via Sparse Modeling

Recent efforts in the area of joint object matching approach the problem by taking as input a set of pairwise maps, which are then jointly optimized across the whole collection so that certain accuracy and consistency criteria are satisfied. One natural requirement is cycle‐consistency—namely the fact that map composition should give the same result regardless of the path taken in the shape collection. In this paper, we introduce a novel approach to obtain consistent matches without requiring initial pairwise solutions to be given as input. We do so by optimizing a joint measure of metric distortion directly over the space of cycle‐consistent maps; in order to allow for partially similar and extra‐class shapes, we formulate the problem as a series of quadratic programs with sparsity‐inducing constraints, making our technique a natural candidate for analysing collections with a large presence of outliers. The particular form of the problem allows us to leverage results and tools from the field of evolutionary game theory. This enables a highly efficient optimization procedure which assures accurate and provably consistent solutions in a matter of minutes in collections with hundreds of shapes.     

A Numerical Approximation‐Based Controller for Mobile Robots with Velocity Limitation

In this paper the problem of trajectory tracking considers that the values of the control actions do not exceed a maximum allowable value and the zero convergence of tracking errors is demonstrated. The control law is based on a linear algebra approach. First, the desired trajectories of some state variables are determined by analyzing the conditions for a system of linear equations to have an exact solution. Therefore, the control signals are obtained by solving the system of linear equations. The optimal controller parameters are selected through nonlinear programming so as to prevent the saturation of the control actions. Experimental results are presented and discussed, demonstrating the controller's good performance. Finally, the performance of the proposed controller is compared with a fuzzy controller, and all the results are validated through experimental laboratory tests.     

How do instream flow increase and gravel augmentation impact biological communities in large rivers: A case study on the Upper Rhine River

Actions are being developed to address the adverse consequences of engineering works on large European rivers by developing and implementing restoration activities in order to enhance the functionality and biodiversity of fluvial hydrosystems. However, as has frequently been mentioned in the scientific literature, quantitative and qualitative evaluation of the project benefits, if any, and their sustainability are hindered by the difficulty in assessing the responses of aquatic and riparian communities to the methods employed. A case study was conducted on a by‐passed section of the Upper Rhine River (France and Germany) to investigate the effects of instream flow increase and gravel augmentation on selected aquatic and riparian communities (macroinvertebrates, macrophytes, and riparian plants). This paper presents the results of a 6‐year interdisciplinary, before‐after control‐impact design monitoring study. The complexity of the study lies in carrying out a separate assessment of the cumulative effects on a site‐based, project‐specific basis. The results showed that (a) the instream flow increase resulted in greater richness of macrophyte species in the newly created backwaters, (b) the artificial gravel bar favoured the recruitment of pioneer species, including invasive species, although gravel redistribution by floods prevented their development, and (c) gravel augmentation tended to promote the taxonomic richness of macroinvertebrate communities with the appearance of species adapted to the new substrate areas. These findings should help to fill the knowledge gaps in large‐scale restoration and contribute key responses to the most frequently arising issues in this area, especially those concerning the efficiency and sustainability of river restoration projects.     

A New Approach for Nonlinear Multivariable Fed-Batch Bioprocess Trajectory Tracking Control

This paper proposes a new control law based on linear algebra. This technique allows nonlinear path tracking in multivariable and complex systems. This new methodology consists in finding the control action to make the system follow predefined concentration profiles solving a system of linear equations. The controller parameters are selected with a Monte Carlo algorithm so as to minimize a previously defined cost index. The control scheme is applied to a fed-batch penicillin production process. Different tests are shown to prove the controller effectiveness, such as adding parametric uncertainty, perturbations in the control action and in the initial conditions. Moreover, a comparison with other controllers from the literature is made, showing the better performance of the present approach.     

Gromov-Hausdorff Stable Signatures for Shapes using Persistence

We introduce a family of signatures for finite metric spaces, possibly endowed with real valued functions, based on the persistence diagrams of suitable filtrations built on top of these spaces. We prove the stability of our signatures under Gromov-Hausdorff perturbations of the spaces. We also extend these results to metric spaces equipped with measures. Our signatures are well-suited for the study of unstructured point cloud data, which we illustrate through an application in shape classification.