Performance assessment of a vibro-finishing technology for additively manufactured components

Metal components produced by Additive Manufacturing (AM) technologies usually exhibit a rough surface, that in certain applications can result detrimental for the part’s functionality. Thus, it is of great interest to study the finishing processes that can be applied to the surfaces, both external and internal, of AM components. The aim of this work is the evaluation of the capabilities of a vibro-finishing process in the treatment of samples produced by Laser-Powder Bed Fusion (L-PBF) from AlSi10Mg powders. In this research, the abrasive media is identified, and the surface quality improvement is analysed in terms of surface roughness and modifications induced by the finishing treatment (i.e., edge rounding, material loss) against finishing duration. The cost of the treatment is also evaluated

On the Robustness of Random Forest Against Untargeted Data Poisoning: An Ensemble-Based Approach

Machine learning is becoming ubiquitous. From finance to medicine, machine learning models are boosting decision-making processes and even outperforming humans in some tasks. This huge progress in terms of prediction quality does not however find a counterpart in the security of such models and corresponding predictions, where perturbations of fractions of the training set (poisoning) can seriously undermine the model accuracy. Research on poisoning attacks and defenses received increasing attention in the last decade, leading to several promising solutions aiming to increase the robustness of machine learning. Among them, ensemble-based defenses, where different models are trained on portions of the training set and their predictions are then aggregated, provide strong theoretical guarantees at the price of a linear overhead. Surprisingly, ensemble-based defenses, which do not pose any restrictions on the base model, have not been applied to increase the robustness of random forest models. The work in this paper aims to fill in this gap by designing and implementing a novel hash-based ensemble approach that protects random forest against untargeted, random poisoning attacks. An extensive experimental evaluation measures the performance of our approach against a variety of attacks, as well as its sustainability in terms of resource consumption and performance, and compares it with a traditional monolithic model based on random forest. A final discussion presents our main findings and compares our approach with existing poisoning defenses targeting random forests.Comment: 15 pages, 8 figure

The effects of visual parabolic motion on the subjective vertical and on interception

Observers typically present a strong bias in estimating the orientation of a visual bar when their body is tilted >60° in the roll plane and in the absence of visual background information. Known as the A-effect, this phenomenon likely results from the under-compensation of body tilt. Static visual cues can reduce such bias in the perceived vertical. Yet, it is unknown whether dynamic visual cues would be also effective. Here we presented projectile motions of a visual target along parabolic trajectories with different orientations relative to physical gravity. The aim of the experiment was twofold: First, we assessed whether the projectile motions could bias the estimation of the perceived orientation of a visual bar, measured with a classical subjective visual vertical (SVV) task. Second, we evaluated whether the ability to estimate time-to-contact of the visual target in an interception task was influenced by the orientation of these parabolic trajectories. Two groups of participants performed the experiment, either with their head and body tilted 90° along the roll plane or in an upright position. We found that the perceived orientation of the visual bar in the SVV task was affected by the orientation of the parabolic trajectories. This result was present in the tilted but not in the upright participants. In the interception task, the timing error increased linearly as a function of the orientation of the parabola. These results support the hypothesis that a gravity vector estimated from dynamic visual stimuli contributes to the subjective visual vertical