Adapting robot behavior to user's capabilities: a dance instruction study.

The ALIZ-E1 projects goal is to design a robot companion able to maintain affective interactions with young users over a period of time. One of these interactions consists in teaching a dance to hospitalized children according to their capabilities. We propose a methodology for adapting both, the movements used in the dance based on the users cognitive and physical capabilities through a set of metrics, and the robots interaction based on the users personality traits

A Practical Method to Estimate Information Content in the Context of 4D-Var Data Assimilation. I: Methodology

Data assimilation obtains improved estimates of the state of a physical system by combining imperfect model results with sparse and noisy observations of reality. Not all observations used in data assimilation are equally valuable. The ability to characterize the usefulness of different data points is important for analyzing the effectiveness of the assimilation system, for data pruning, and for the design of future sensor systems. This paper focuses on the four dimensional variational (4D-Var) data assimilation framework. Metrics from information theory are used to quantify the contribution of observations to decreasing the uncertainty with which the system state is known. We establish an interesting relationship between different information-theoretic metrics and the variational cost function/gradient under Gaussian linear assumptions. Based on this insight we derive an ensemble-based computational procedure to estimate the information content of various observations in the context of 4D-Var. The approach is illustrated on linear and nonlinear test problems. In the companion paper [Singh et al.(2011)] the methodology is applied to a global chemical data assimilation problem

Assembly Time Modeling Through Connective Complexity Metrics

This paper presents an approach for the development of surrogate models predicting the assembly time of a system based on complexity metrics of the physical system architecture when detailed geometric information is unavailable. A convention for modelling physical architecture is presented, followed by a sample of 10 analysed systems used for training and three systems used for validation. These systems are evaluated on complexity metrics developed from graph theoretic measures. An example model is developed based on a series of regressions of trends observed within the sample data. This is validated against the systems that are not used to develop the model. The model developed uses average path length, part count and path length density to approximate assembly time within the standard deviation of the subjective variation possible in Boothroyd and Dewhurst design for assembly (DFA) analysis. While the specific example model developed is generalisable only to systems similar to those in the sample set, the capability to develop mappings between physical architecture and assembly time in early-stage design is demonstrated

Space-Based Cosmic-Ray and Gamma-Ray Detectors: a Review

Prepared for the 2014 ISAPP summer school, this review is focused on space-borne and balloon-borne cosmic-ray and gamma-ray detectors. It is meant to introduce the fundamental concepts necessary to understand the instrument performance metrics, how they tie to the design choices and how they can be effectively used in sensitivity studies. While the write-up does not aim at being complete or exhaustive, it is largely self-contained in that related topics such as the basic physical processes governing the interaction of radiation with matter and the near-Earth environment are briefly reviewed.Comment: 86 pages, 70 figures, prepared for the 2014 ISAPP summer school. Change log in the writeup, ancillary material at https://bitbucket.org/lbaldini/crdetector

Content in the Context of 4D-Var Data Assimilation. II: Application to Global Ozone Assimilation

Data assimilation obtains improved estimates of the state of a physical system by combining imperfect model results with sparse and noisy observations of reality. Not all observations used in data assimilation are equally valuable. The ability to characterize the usefulness of different data points is important for analyzing the effectiveness of the assimilation system, for data pruning, and for the design of future sensor systems. In the companion paper [Sandu et al.(2011)] we derived an ensemble-based computational procedure to estimate the information content of various observations in the context of 4D-Var. Here we apply this methodology to quantify two information metrics (the signal and degrees of freedom for signal) for satellite observations used in a global chemical data assimilation problem with the GEOS-Chem chemical transport model. The assimilation of a subset of data points characterized by the highest information content, gives analyses that are comparable in quality with the one obtained using the entire data set