Confidence driven TGV fusion

We introduce a novel model for spatially varying variational data fusion, driven by point-wise confidence values. The proposed model allows for the joint estimation of the data and the confidence values based on the spatial coherence of the data. We discuss the main properties of the introduced model as well as suitable algorithms for estimating the solution of the corresponding biconvex minimization problem and their convergence. The performance of the proposed model is evaluated considering the problem of depth image fusion by using both synthetic and real data from publicly available datasets

A Hybrid Approach for Trajectory Control Design

This work presents a methodology to design trajectory tracking feedback control laws, which embed non-parametric statistical models, such as Gaussian Processes (GPs). The aim is to minimize unmodeled dynamics such as undesired slippages. The proposed approach has the benefit of avoiding complex terramechanics analysis to directly estimate from data the robot dynamics on a wide class of trajectories. Experiments in both real and simulated environments prove that the proposed methodology is promising.Comment: 9 pages, 11 figure

Discovery and recognition of motion primitives in human activities

We present a novel framework for the automatic discovery and recognition of motion primitives in videos of human activities. Given the 3D pose of a human in a video, human motion primitives are discovered by optimizing the `motion flux', a quantity which captures the motion variation of a group of skeletal joints. A normalization of the primitives is proposed in order to make them invariant with respect to a subject anatomical variations and data sampling rate. The discovered primitives are unknown and unlabeled and are unsupervisedly collected into classes via a hierarchical non-parametric Bayes mixture model. Once classes are determined and labeled they are further analyzed for establishing models for recognizing discovered primitives. Each primitive model is defined by a set of learned parameters. Given new video data and given the estimated pose of the subject appearing on the video, the motion is segmented into primitives, which are recognized with a probability given according to the parameters of the learned models. Using our framework we build a publicly available dataset of human motion primitives, using sequences taken from well-known motion capture datasets. We expect that our framework, by providing an objective way for discovering and categorizing human motion, will be a useful tool in numerous research fields including video analysis, human inspired motion generation, learning by demonstration, intuitive human-robot interaction, and human behavior analysis

Functionalization of glass surfaces with SAMs: the effect of synthesis conditions and the application to pharmaceutical crystallization

Surfaces can alter the outcome of crystallization processes occurring via heterogenous nucleation. In a pharmaceutical scenario, the promotion of specific polymorphs or crystalline habits, as well as the alteration of nucleation kinetics, are compelling issues. Surfaces with controlled physico-chemical features represent a valuable tool for the study of drug crystallization by heterogeneous nucleation. For this purpose, the functionalization of glass with Self-Assembled Monolayers (SAMs) via silane chemistry was investigated. SAMs carrying thiol, amino, glycidyloxy and methacrylate end-groups will be presented. Different sets of synthesis conditions strongly affected the quality of SAMs. In this perspective, the reaction medium and the reaction time were identified as key parameters for getting controlled surface functionalization. Typical surface roughness was approx. 130 pm and SAM thickness was below 1 nm. SAM chemistry was investigated with XPS to confirm the presence of characteristic groups on the surface of glass. Finally, the application of SAMs to the crystallization of aspirin will be presented, discussing the impact of several surface chemistries on the nucleation kinetics

The new fiction view of models

How do models represent reality? There are two conditions that scientific models must satisfy to be representations of real systems, the aboutness condition and the epistemic condition. In this article, I critically assess the two main fictionalist theories of models as representations, the indirect fiction view and the direct fiction view, with respect to these conditions. And I develop a novel proposal, what I call ‘the new fiction view of models’. On this view, models are akin to fictional stories; they represent real-world phenomena if they stand in a denotation relation with reality; and they enable knowledge of reality via the generation of theoretical hypotheses, model–world comparisons and direct attributions

Fictionalism

In this entry I will offer a survey of the contemporary debate on fic- tionalism, which is a distinctive anti-realist view about certain regions of discourse that are valued for their usefulness rather than their truth

The Nature of Model-World Comparisons

Upholders of fictionalism about scientific models have not yet successfully explained how scientists can learn about the real world by making comparisons between models and the real phenomena they stand for. In this paper I develop an account of model-world comparisons in terms of what I take to be the best antirealist analyses of comparative claims that emerge from the current debate on fiction

The Problem of Satisfaction Conditions and the Dispensability of I-Desire

The problem of satisfaction conditions arises from the apparent difficulties of explaining the nature of the mental states involved in our emotional responses to tragic fictions. Greg Currie has recently proposed to solve the problem by arguing for the recognition of a class of imaginative counterparts of desires - what he and others call i-desires. In this paper I will articulate and rebut Currie's argument in favour of i-desires and I will put forward a new solution in terms of genuine desires. To this aim I will show that the same sort of puzzling phenomenon involved in our responses to tragic fictions arises also in a non-fictional case, and I will offer a solution to the problem of satisfaction conditions that dispenses with i-desires. The key to the explanation is in the notion of condition-dependent desires triggered by fictions