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Volume 8 (1972)
- Issue 6 Pages 247-
- Issue 5 Pages 207-
- Issue 4 Pages 155-
- Issue 3 Pages 115-
- Issue 2 Pages 65-
- Issue 1 Pages 1-
Volume 8, Issue 3
Displaying 1-6 of 6 articles from this issue
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T. Wake, [in Japanese]1972 Volume 8 Issue 3 Pages 115-120
Published: June 15, 1972
Released on J-STAGE: March 11, 2010
JOURNAL FREE ACCESSPupillary movements in left eye were measured at dark and light adaptation. A small illumination spot was exposed in right eye. If the illumination spot is low intensity, the contraction of the pupil slightly occurs at once, and then it recovers during the exposure of the spot. If the spot luminance is increased, the relationship of contracted-dilated pupil reveals light and dark adaptation curve. Furthermore, pupillary area decreases with the increase of the intensity of the spot, and it increases with the increase of separation between a fixed point and the spot, and with the decrease of size of the spot. The relation between contracted pupil and intensity of the spot is discussed.View full abstractDownload PDF (696K) -
S. Murai, K. Kuribara1972 Volume 8 Issue 3 Pages 121-127
Published: June 15, 1972
Released on J-STAGE: March 11, 2010
JOURNAL FREE ACCESSTo analyse precisely the cmplex configurations of human body is an indispensable theme to solve many problems in human engineering.
In this paper, firstly three dimensional coordinates of mesh points on human body were acquired so accurately by analytical photogrammetry, and secondly on the base of these data digital body model, composed of smoothly continued surfaces, were formed in computer.
An automatic processing system for digital body model developed by authors would provide so many significant procedure in human engineering, such as perspective and development diagram of human body by graphical processing, numerical integration of human body surfaces, and so on.View full abstractDownload PDF (3138K) -
M. Yabuuchi1972 Volume 8 Issue 3 Pages 128-134
Published: June 15, 1972
Released on J-STAGE: March 11, 2010
JOURNAL FREE ACCESSThe purpose of this paper is to examine an algorithm of the statististical pattern recognition processing, which can be considered as consisting of three processes: normalization, selection of feature measurements, and classification. The algorithm was applied to hand-drawn simple geometrical figure recognition. The pattern samples used for two experiments were obtained by asking subjects to draw figures in a 10cm-square (L-cond.) or in a 5cm-square (S-cond.). As to both conditions, a simple normalization technique was deviced and estimated by testing equality of mean vectors and covariance matrices. An idea of multivariate statistical control was utilized to detect abnormal input patterns. The good recognition accuracy was obtained in the results of two experiments.View full abstractDownload PDF (726K) -
In the 17th session of the Commission Internationale de l'EclairageH. Manabe1972 Volume 8 Issue 3 Pages 135-140
Published: June 15, 1972
Released on J-STAGE: March 11, 2010
JOURNAL FREE ACCESSDownload PDF (794K) -
K. Nakao, [in Japanese], [in Japanese]1972 Volume 8 Issue 3 Pages 141-146
Published: June 15, 1972
Released on J-STAGE: March 11, 2010
JOURNAL FREE ACCESSTo use the values of mesurement of human body effectively, we should know the maximum errors about each item of mesurement. Therefore the present authors carried out the mesurements of six mesured by 6-8 mesurers about 43 items. From these values 99% critical interval was calcurated and classified by the mean of mesured values. The 99% rate of confidence “Ck” was obtained as follows;
Ck=t0.01⋅Sk√Nk+1/Nk/Mk
Nk: Number of mesurers
Sk: Standard diviation (unbiased)
Mk: Mean of mesured values
The mean value and standard diviation of 99% rates of confidence of 6 mesured were obtained. These means and standard diviations were divided into 6 groups as seen on Table 3 and 4. The former is called as the Degree of Confidence and the latter is called as the Degree of Stability. From these data it can be concluded that the item with 4 figures of number of mesured value generally includes the maximum error of 3%, one with 3 figures does 15%, one with 2 does 25%.View full abstractDownload PDF (709K) -
J. Sato1972 Volume 8 Issue 3 Pages 147-152
Published: June 15, 1972
Released on J-STAGE: March 11, 2010
JOURNAL FREE ACCESSThe result I got about the errors of measured values in the operation of measurement was as follows.
When I divided the measured values I got by measuring length by micrometer into a true value, a working value and a perceived value, and examined the relations among these values, it was found that the working value is near to the true one, while the perceived one is far from the true one.
This is caused by incorrect reading of scale marks. And personal differences are comparatively little in the working values, but they are very remarkable in the perceived values.
This comes from the fact that the working value is measured by mechanical operation, while the perceived value depends upon perceptive recognition through vision.
I give the ways of incorrect reading: (1) counting the number of 1mm scale marks of sleeve, (2) not reading 0.5mm scale marks of sleeve at all, (3) unnecessary reading of 0.5mm scale marks of sleeve, (4) incorrect reading of thimble.
Among these (3) cases appear most remarkly. It is clear that these errors had relations with the thickness of 1 ines of scale marks.View full abstractDownload PDF (652K)
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