PhotoRaptor - Photometric Research Application To Redshifts

Due to the necessity to evaluate photo-z for a variety of huge sky survey data sets, it seemed important to provide the astronomical community with an instrument able to fill this gap. Besides the problem of moving massive data sets over the network, another critical point is that a great part of astronomical data is stored in private archives that are not fully accessible on line. So, in order to evaluate photo-z it is needed a desktop application that can be downloaded and used by everyone locally, i.e. on his own personal computer or more in general within the local intranet hosted by a data center. The name chosen for the application is PhotoRApToR, i.e. Photometric Research Application To Redshift (Cavuoti et al. 2015, 2014; Brescia 2014b). It embeds a machine learning algorithm and special tools dedicated to preand post-processing data. The ML model is the MLPQNA (Multi Layer Perceptron trained by the Quasi Newton Algorithm), which has been revealed particularly powerful for the photo-z calculation on the base of a spectroscopic sample (Cavuoti et al. 2012; Brescia et al. 2013, 2014a; Biviano et al. 2013). The PhotoRApToR program package is available, for different platforms, at the official website (http://dame.dsf.unina.it/dame_photoz.html#photoraptor).Comment: User Manual of the PhotoRaptor tool, 54 pages. arXiv admin note: substantial text overlap with arXiv:1501.0650

Photometric redshift estimation based on data mining with PhotoRApToR

Photometric redshifts (photo-z) are crucial to the scientific exploitation of modern panchromatic digital surveys. In this paper we present PhotoRApToR (Photometric Research Application To Redshift): a Java/C++ based desktop application capable to solve non-linear regression and multi-variate classification problems, in particular specialized for photo-z estimation. It embeds a machine learning algorithm, namely a multilayer neural network trained by the Quasi Newton learning rule, and special tools dedicated to pre- and postprocessing data. PhotoRApToR has been successfully tested on several scientific cases. The application is available for free download from the DAME Program web site.Comment: To appear on Experimental Astronomy, Springer, 20 pages, 15 figure

Clustering and Turbophoresis in a Shear Flow without Walls

We investigate the spatial distribution of inertial particles suspended in the bulk of a turbulent inhomogeneous flow. By means of direct numerical simulations of particle trajectories transported by the turbulent Kolmogorov flow, we study large and small scale mechanisms inducing inhomogeneities in the distribution of heavy particles. We discuss turbophoresis both for large and weak inertia, providing heuristic arguments for the functional form of the particle density profile. In particular, we argue and numerically confirm that the turbophoretic effect is maximal for particles of intermediate inertia. Our results indicate that small-scale fractal clustering and turbophoresis peak in different ranges in the particles' Stokes number and the separation of the two peaks increases with the flow's Reynolds number.Comment: 13 pages, 5 figure

Endoscopic Camera Control by Head Movements for Thoracic Surgery

In current video-assisted thoracic surgery, the endoscopic camera is operated by an assistant of the surgeon, which has several disadvantages. This paper describes a system which enables the surgeon to control the endoscopic camera without the help of an assistant. The system is controlled using head movements, so the surgeon can use his/her hands to oper- ate the instruments. The system is based on a flexible endoscope, which leaves more space for the surgeon to operate his/her instruments compared to a rigid endoscope. The endoscopic image is shown either on a monitor or by means of a head- mounted display. Several trial sessions were performed with an anatomical model. Results indicate that the developed concept may provide a solution to some of the problems currently encountered in video-assisted thoracic surgery. The use of a head-mounted display turned out to be a valuable addition since it ensures the image is always in front of the surgeon’s eyes

Coupling traffic models on networks and urban dispersion models for simulating sustainable mobility strategies

AbstractThe aim of the present paper is to investigate the viability of macroscopic traffic models for modeling and testing different traffic scenarios, in order to define the impact on air quality of different strategies for the reduction of traffic emissions. To this aim, we complement a well assessed traffic model on networks (Garavello and Piccoli (2006) [1]) with a strategy for estimating data needed from the model and we couple it with the urban dispersion model Sirane (Soulhac (2000) [2])

A Nonlinear Observer for Free-Floating Target Motion using only Pose Measurements

In this paper, we design a nonlinear observer to estimate the inertial pose and the velocity of a free-floating non-cooperative satellite (Target) using only relative pose measurements. In the context of control design for orbital robotic capture of such a non-cooperative Target, due to lack of navigational aids, only a relative pose estimate may be obtained from slow-sampled and noisy exteroceptive sensors. The velocity, however, cannot be measured directly. To address this problem, we develop a model-based observer which acts as an internal model for Target kinematics/dynamics and therefore, may act as a predictor during periods of no measurement. To this end, firstly, we formalize the estimation problem on the SE(3) Lie group with different state and measurement spaces. Secondly, we develop the kinematics and dynamics observer such that the overall observer error dynamics possesses a stability property. Finally, the proposed observer is validated through robust Monte-Carlo simulations and experiments on a robotic facility.Comment: 8 pages, 6 figure