Systems Factorial Technology (SFT) comprises a set of powerful nonparametric models and measures, together with a theory-driven experiment methodology termed the Double Factorial Paradigm (DFP), for assessing the cognitive information processing mechanisms supporting the processing of multiple sources of information in a given task (Townsend & Nozawa, 1995). We provide an overview of the model-based measures of SFT together with a tutorial on designing a DFP experiment to take advantage of all SFT measures in a single experiment. Illustrative examples are given to highlight the breadth of applicability of these techniques across psychology. We further introduce and demonstrate a new package for performing SFT analyses using R for Statistical Computing.
Advances in autonomy have the potential to reshape the landscape of the modern world. Yet, research on human-machine interaction is needed to better understand the dynamic exchanges required between humans and machines in order to optimize human reliance on novel technologies. A key aspect of that exchange involves the notion of transparency as humans and machines require shared awareness and shared intent for optimal team work. Questions remain however, regarding how to represent information in order to generate shared awareness and intent in a human-machine context. The current paper will review a recent model of human-robot transparency and will propose a number of methods to foster transparency between humans and machines.
Recent work establishes that static and dynamic natural images have fractal-like l/falpha spatiotemporal spectra. Artifical textures, with randomized phase spectra, and 1/falpha amplitude spectra are also used in studies of texture and noise perception. Influenced by colorimetric principles and motivated by the ubiquity of 1/falpha spatial and temporal image spectra, we treat the spatial and temporal frequency exponents as the dimensions characterizing a dynamic texture space, and we characterize two key attributes of this space, the spatiotemporal appearance map and the spatiotemporal discrimination function (a map of MacAdam-like just-noticeable-difference contours).
Operators in dynamic environments, such as aircraft cockpits, ground vehicles, and command-and-control centers, could benefit greatly from 3-D auditory technology when searching their environments for visual targets or other time-critical information.
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