1991
DOI: 10.1147/rd.351.0227
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Picturing randomness on a graphics supercomputer

Abstract: This paper provides a light introduction to a simple graphics technique which can be used to represent random data on a graphics supercomputer. The representation, called a "noise-sphere," can be used to detect "bad" random-number generators with little training on the part of the observer. The system uses lighting and shading facilities of 3D extensions to the X-Windows or the PHIGS+ standard. To encourage reader involvement, computational recipes and suggestions for future experiments are included.

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Cited by 7 publications
(2 citation statements)
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“…The proposed improved method is, in our modest opinion, a novelty in producing strong passwords that was not seen for years, maybe ever since the invention of graphical passwords in 1990s [73,74]. "The idea of PsychoPass is that a password can be created, memorized and recalled by just thinking of an action sequence instead of a word or string of characters" [72].…”
Section: A Psychopass Methodsmentioning
confidence: 99%
“…The proposed improved method is, in our modest opinion, a novelty in producing strong passwords that was not seen for years, maybe ever since the invention of graphical passwords in 1990s [73,74]. "The idea of PsychoPass is that a password can be created, memorized and recalled by just thinking of an action sequence instead of a word or string of characters" [72].…”
Section: A Psychopass Methodsmentioning
confidence: 99%
“…Today it is widely acknowledged that certified randomness can be a valuable resource (e.g., for testing primality [13,14]), and that under various circumstances a lack of randomness may have negative consequences (e.g., erroneous numerical calculations [15]). The pitfalls of software-generated pseudo-randomness [16] are well-known [15,[17][18][19]. In John von Neumann's words [20]: "Anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin."…”
Section: Introductionmentioning
confidence: 99%