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John G. Kreifeldt

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Publication statistics

Pub. period:1987-1995
Pub. count:5
Number of co-authors:7

Co-authors

Number of publications with 3 favourite co-authors:

Rungtai Lin:1
Keoun Nah:1
Colin G. Drury:1

Productive colleagues

John G. Kreifeldt's 3 most productive colleagues in number of publications:

Colin G. Drury:32
Stephan Konz:15
Rungtai Lin:9

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May 20

CTS 2013 - The 2013 Intl. Conf. on Collaboration Techn. and Systems

May 22

Knowing (by) Designing 2013

May 27

13th Intl. Conf. on New Interfaces for Musical Expression

May 18

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John G. Kreifeldt

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Publications by John G. Kreifeldt (bibliography)

1995

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Kreifeldt, John G. and Nah, Keoun (1995): Adding and Subtracting Percentiles -- How Bad Can It Be?. In: Proceedings of the Human Factors and Ergonomics Society 39th Annual Meeting 1995. pp. 301-305.

“When performing anthropometric analysis or design, it frequently happens that some particular anthropometric value is not tabulated although it would appear to be derivable by adding or subtracting two relevant and tabulated dimensions. Because percentile values are usually required, there is the temptation to add or subtract the relevant percentile values of the two tabulated dimensions. In some cases, this will produce minimal or no error between the actual percentile value and the result of adding/subtracting the tabulated values, while in other cases, the resulting percentile will be very seriously in error. The magnitude of the errors depends on the percentiles, correlation coefficient and ratio of the standard deviations of the two variates. This paper details the combinations of these three factors for which adding/subtracting two identical percentile values produces acceptable as well as grossly misleading results. Several tables, charts and equations are provided to aid in this common problem. The results may be particularly useful when only the ratio of standard deviations may be known or approximated rather than their individual values. In general, subtracting percentiles leads to greater errors than adding them.”

1992

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Lin, Rungtai and Kreifeldt, John G. (1992): Understanding the Image Functions for Icon Design. In: Proceedings of the Human Factors Society 36th Annual Meeting 1992. pp. 341-345.

“Because icons vary from very representational to extremely abstract symbols in a user interface, an important issue faced by designers when designing an icon is how to select an appropriate design style for the image. There are no simple rules that can be followed by designers to determine the design style. The present study is intended to help designers to choose a proper design style for the icon at an early design stage. First, a classification of icons is summarized and the levels of stylization are discussed and demonstrated with examples. Then, thirty icons from several drawing packages and generally used symbols are selected, and a matching test is conducted to obtain the correct matching rates. The results are presented with some explanations for icon recognition and confusion, and finally how to select the right image function for icon design is discussed.”

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Kreifeldt, John G. (1992): Warnings and Expert Opinions: An Evaluation Methodology Based on Fuzzy Probabilities. In: Proceedings of the Human Factors Society 36th Annual Meeting 1992. pp. 940-944.

“A number of mandated and voluntary standards and guidelines expressed as good practice have been set out for the design of warnings. However, the question always arises as to whether or not a given warning will accomplish (or would have accomplished) its purpose of preventing injury whether or not it follows such guidelines. The answer to this question must be phrased in probabilities and sometimes only in qualitative form such as "low probability", "high probability", "more probable than not", etc. In order to obtain such answers, experts are often consulted for their opinions. A methodology is presented which can be used as a basis for checking the consistency of the final conclusions or opinions using the concept of "fuzzy probabilities" and conceptually simple computations. The methodology is also of use to the expert in formulating his opinion rationally and deducing its implications clearly. This methodology is presented here in the context of the opined probability of effectiveness of warnings and instructions although it may be used in any context in which the total proposition can be phrased as a set of interrelated sub propositions as is common in reliability theory, decision theory, etc.”

1991

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Buck, James R., Leamon, Tom B., Kreifeldt, John G., Konz, Stephan and Drury, Colin G. (1991): Human Factors Design. In: Proceedings of the Human Factors Society 35th Annual Meeting 1991. pp. 534-535.

1987

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Kreifeldt, John G. and Chuang, Ming C. (1987): Towards a New Approach to Vision: Applications to Robots and Humans. In: Proceedings of the Human Factors Society 31st Annual Meeting 1987. pp. 1281-1285.

“A description of a novel and very speculative approach to new research directions for human vision with application to robotic vision is described. The goal of the approach is to propose a plausible, implementable, spatial perception model for human vision and apply this model to a stereo robot vision system. The model is based on computer algorithms variously called "Multidimensional Scaling", well known is psychology and sociology but relatively unknown in engineering. These algorithms can reconstruct a spatially accurate model to a high level of metric precision of a "configuration of points" from low quality, error prone non-metric data about the configuration. ALSCAL -- a general purpose computer package adaptable for this purpose is being presently evaluated. This is a departure from typical engineering approaches which are directed toward gathering a low volume of highly precise referenced data about the positions of selected points in the visual scene and substitutes instead an approach of gathering a high volume of very low precision relative data about the interpoint spacings. It would seem that the latter approach is the one actually used by the human vision system. The results are highly encouraging in that the agreement between test configurations of two and three dimensional configurations of points are very faithfully reconstructed from as low as 10 points in a configuration using only rank ordered (i.e. non-metric) information about interpoint spacings. The reconstructions are remarkably robust even under human-like "fuzzy" imprecision in visual measurements.”

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