Context. In astronomy, new approaches to process and analyze the exponentially increasing amount of data are inevitable. For spectra, such as in the Sloan Digital Sky Survey spectral database, usually templates of well-known classes are used for classification. In case the fitting of a template fails, wrong spectral properties (e.g. redshift) are derived. Validation of the derived properties is the key to understand the caveats of the template-based method. Aims. In this paper we present a method for statistically computing the redshift z based on a similarity approach. This allows us to determine redshifts in spectra for emission and absorption features without using any predefined model. Additionally, we show how to determine the redshift based on single features. As a consequence we are, for example, able to filter objects that show multiple redshift components. Methods. The redshift calculation is performed by comparing predefined regions in the spectra and individually applying a nearest neighbor regression model to each predefined emission and absorption region. Results. The choice of the model parameters controls the quality and the completeness of the redshifts. For ≈90% of the analyzed 16 000 spectra of our reference and test sample, a certain redshift can be computed that is comparable to the completeness of SDSS (96%). The redshift calculation yields a precision for every individually tested feature that is comparable to the overall precision of the redshifts of SDSS. Using the new method to compute redshifts, we could also identify 14 spectra with a significant shift between emission and absorption or between emission and emission lines. The results already show the immense power of this simple machine-learning approach for investigating huge databases such as the SDSS.
We describe a web service providing a complete stereoscopic 3D video multi-stream cloud application to serve a potentially very large number of clients over the Internet. The system architecture consists of a stream provider that leverages highly scalable and reliable cloud computing and storage services, with automatic load balancing capability for live and content streaming. By use of a suiting flash media plugin the content is displayed on a wide variety of 3D capable devices like for example 3D workstations or smart TV sets. Videos are made available by an on-line stream provider for live broadcasting or by cloud storage services. Compared to conventional 3D video streaming over satellite channels there are considerable savings in cost as well as a wider range of applicability and functional improvements. Possible areas of application are medical surgery, live concerts, and sports events.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.