Redshift measurement and spectral classification for eBOSS galaxies with the redmonster software

We describe the redmonster automated redshift measurement and spectral classification software designed for the extended Baryon Oscillation Spectroscopic Survey (eBOSS) of the Sloan Digital Sky Survey IV (SDSS-IV). We describe the algorithms, the template standard and requirements, and the newly developed galaxy templates to be used on eBOSS spectra. We present results from testing on early data from eBOSS, where we have found a 90.5% automated redshift and spectral classification success rate for the luminous red galaxy sample (redshifts 0.6 ≲ z ≲ 1.0). The redmonster performance meets the eBOSS cosmology requirements for redshift classification and catastrophic failures and represents a significant improvement over the previous pipeline. We describe the empirical processes used to determine the optimum number of additive polynomial terms in our models and an acceptable ΔXr2 threshold for declaring statistical confidence. Statistical errors on redshift measurement due to photon shot noise are assessed, and we find typical values of a few tens of km s-1. An investigation of redshift differences in repeat observations scaled by error estimates yields a distribution with a Gaussian mean and standard deviation of μ ∼ 0.01 and σ ∼ 0.65, respectively, suggesting the reported statistical redshift uncertainties are over-estimated by ∼54%. We assess the effects of object magnitude, signal-to-noise ratio, fiber number, and fiber head location on the pipeline's redshift success rate. Finally, we describe directions of ongoing development.Publisher PDFPeer reviewe

REDSHIFT MEASUREMENT and SPECTRAL CLASSIFICATION for eBOSS GALAXIES with the REDMONSTER SOFTWARE

We describe the redmonster automated redshift measurement and spectral classification software designed for the extended Baryon Oscillation Spectroscopic Survey (eBOSS) of the Sloan Digital Sky Survey IV (SDSS-IV). We describe the algorithms, the template standard and requirements, and the newly developed galaxy templates to be used on eBOSS spectra. We present results from testing on early data from eBOSS, where we have found a 90.5% automated redshift and spectral classification success rate for the luminous red galaxy sample (redshifts 0.6 ≲ z ≲ 1.0). The redmonster performance meets the eBOSS cosmology requirements for redshift classification and catastrophic failures and represents a significant improvement over the previous pipeline. We describe the empirical processes used to determine the optimum number of additive polynomial terms in our models and an acceptable δX2rthreshold for declaring statistical confidence. Statistical errors on redshift measurement due to photon shot noise are assessed, and we find typical values of a few tens of km s-1. An investigation of redshift differences in repeat observations scaled by error estimates yields a distribution with a Gaussian mean and standard deviation of μ ∼ 0.01 and σ ∼ 0.65, respectively, suggesting the reported statistical redshift uncertainties are over-estimated by ∼54%. We assess the effects of object magnitude, signal-to-noise ratio, fiber number, and fiber head location on the pipeline's redshift success rate. Finally, we describe directions of ongoing development

ISO 26262 Compliant Automatic Requirements-Based Testing for TargetLink

International audienceThis paper presents an automatic method that has been developed in order to support international standards regarding functional safety, like ISO 26262 for automotive and DO178B for aeronautics. It describes a seamless and integrated method to formalise requirements based on pattern specification automatons and generated C-observer code. Based on such C-Observers then requirements based functional tests can be generated and formal verification can be automated as the generated C-code observers are integrated into a test and verification tool environment. The advantage of such approach includes the possibility to enable requirements-based test case generation, automatic test execution and analysis and test quality measurement by automatic generation of requirements coverage and traceability reports. The described method is in-line with the software quality standards as it is for example specified in the new automotive standard for functional safety ISO 26262. The approach has already been implemented in a first instance for the Matlab/Simulink models and production code generation with TargetLink from dSPACE

The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems

Scenario-based testing for the safety validation of highly automated vehicles is a promising approach that is being examined in research and industry. This approach heavily relies on data from real-world scenarios to derive the necessary scenario information for testing. Measurement data should be collected at a reasonable effort, contain naturalistic behavior of road users and include all data relevant for a description of the identified scenarios in sufficient quality. However, the current measurement methods fail to meet at least one of the requirements. Thus, we propose a novel method to measure data from an aerial perspective for scenario-based validation fulfilling the mentioned requirements. Furthermore, we provide a large-scale naturalistic vehicle trajectory dataset from German highways called highD. We evaluate the data in terms of quantity, variety and contained scenarios. Our dataset consists of 16.5 hours of measurements from six locations with 110 000 vehicles, a total driven distance of 45 000 km and 5600 recorded complete lane changes. The highD dataset is available online at: http://www.highD-dataset.comComment: IEEE International Conference on Intelligent Transportation Systems (ITSC) 201

Modeling the object-oriented software process: OPEN and the unified process

A short introduction to software process modeling is presented, particularly object-oriented modeling. Two major industrial process models are discussed: the OPEN model and the Unified Process model. In more detail, the quality assurance in the Unified Process tool (formally called Objectory) is reviewed

Software development: A paradigm for the future

A new paradigm for software development that treats software development as an experimental activity is presented. It provides built-in mechanisms for learning how to develop software better and reusing previous experience in the forms of knowledge, processes, and products. It uses models and measures to aid in the tasks of characterization, evaluation and motivation. An organization scheme is proposed for separating the project-specific focus from the organization's learning and reuse focuses of software development. The implications of this approach for corporations, research and education are discussed and some research activities currently underway at the University of Maryland that support this approach are presented