An Adaptive Design Methodology for Reduction of Product Development Risk

Embedded systems interaction with environment inherently complicates understanding of requirements and their correct implementation. However, product uncertainty is highest during early stages of development. Design verification is an essential step in the development of any system, especially for Embedded System. This paper introduces a novel adaptive design methodology, which incorporates step-wise prototyping and verification. With each adaptive step product-realization level is enhanced while decreasing the level of product uncertainty, thereby reducing the overall costs. The back-bone of this frame-work is the development of Domain Specific Operational (DOP) Model and the associated Verification Instrumentation for Test and Evaluation, developed based on the DOP model. Together they generate functionally valid test-sequence for carrying out prototype evaluation. With the help of a case study 'Multimode Detection Subsystem' the application of this method is sketched. The design methodologies can be compared by defining and computing a generic performance criterion like Average design-cycle Risk. For the case study, by computing Average design-cycle Risk, it is shown that the adaptive method reduces the product development risk for a small increase in the total design cycle time.Comment: 21 pages, 9 figure

A Multi-Code Analysis Toolkit for Astrophysical Simulation Data

The analysis of complex multiphysics astrophysical simulations presents a unique and rapidly growing set of challenges: reproducibility, parallelization, and vast increases in data size and complexity chief among them. In order to meet these challenges, and in order to open up new avenues for collaboration between users of multiple simulation platforms, we present yt (available at http://yt.enzotools.org/), an open source, community-developed astrophysical analysis and visualization toolkit. Analysis and visualization with yt are oriented around physically relevant quantities rather than quantities native to astrophysical simulation codes. While originally designed for handling Enzo's structure adaptive mesh refinement (AMR) data, yt has been extended to work with several different simulation methods and simulation codes including Orion, RAMSES, and FLASH. We report on its methods for reading, handling, and visualizing data, including projections, multivariate volume rendering, multi-dimensional histograms, halo finding, light cone generation and topologically-connected isocontour identification. Furthermore, we discuss the underlying algorithms yt uses for processing and visualizing data, and its mechanisms for parallelization of analysis tasks.Comment: 18 pages, 6 figures, emulateapj format. Resubmitted to Astrophysical Journal Supplement Series with revisions from referee. yt can be found at http://yt.enzotools.org