Crowdsourcing has been used in the context of disaster response in multiple ways (Munro 2013): including crowd searching, microtasking (explained next), citizen science, rapid translation, data cleaning and verification, developing ML classifiers, and election monitoring (Boulos et al. 2011).
The analytical verifications developed and reviewed here allow critical assessment of the advantages and limitations of 2D and 3D-DDA, can be used as benchmark tests for attempted modifications to the original DDA code, for calibration of input numerical control parameters, and for quantitative and meaningful comparison with other numerical discrete element methods.
We give an overview of the latest on-the-fly verification techniques developed within the CADP protocol engineering toolbox.
State feedback controllers achieving such a generalized performance objective are synthesized based on verification results developed for the nonlinear L2-gain property.
In comparison with other analysis and verification methods developed for similar modeling formalisms (Barnat et al., 2009; Bernot et al., 2004; Corblin et al., 2009; Fromentin et al., 2007), our approach is original in two respects.
In this study, we showed by means of a defined analytical validation and verification process developed according to the CLSI guidelines that the RT-qPCR-based EndoPredict multianalyte gene expression test is a robust test that can be performed reproducibly and accurately.
The methodology of the HFT and its numerical verifications were developed and described in a previous paper.
The proposed method devises an image-based gradient prediction to accelerate the accumulation, introduces a boundary recorder to eliminate redundant analyses in the line verification, and develops an image-based line verification algorithm to detect line thickness and reduce false detections as well.
Various formal methods based verification tools are developed to check the status after modeling network behaviors using a binary logic.
3) The development should enhance the usage of closed loop control: because of the absence of data and expertise, the analysis should be combined with closed loop verification to develop and refine various types of models, principles, methods and standards. .
