The images received from the polka dot patterns in black and white colors were analyzed by the factor analysis. 25 kinds of polka dot patterns which were different from one another in size of polka dots and in interval between polka dots were made. Then the colors of polka dots and ground of each pattern were inverted each other to make a total of 50kinds of polka dot patterns.
The image factors of these 50 kinds of polka dots patterns are identified by three factors, i, e, , clearness, simplicity and profoundness.
The factor of clearness is related to the size of polka dots. The factor of simplicity is related to the interval among polka dots. The factor of profoundness is related to the black and white color of ground texture.

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A new method is developed to measure the moisture transmission resistance (MTR) of fabrics. Hitherto the apparent MTR, whose physical meaning is indefinite, has reluctantly been introduced under the cup method, because the humidity inside the cup covered by fabrics is assumed to be constant. In order to investigate the spatial variation of humidity, the diffusion equation is numerically solved in the case of the cup uncovered by fabrics. The humidity changes rapidly and regularly inside the cup, while its variation is quite small outside the cup. The reciprocal of the evaporation rate is also found to be linearly dependent on the thickness of the air layer inside the cup. This relation suggests that the MTR can be correctly evaluated by using the difference between the evaporation rates for the cups covered and uncovered by fabrics. It has been confirmed by experiment that this simple method works quite well.

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The influence of selection of measurement items in several cases of principal component analysis has been discussed by using foot and leg data for footwear planning. The results are as follows:
(1) In the case of the analysis of both foot and leg data, the first and second principal components represent the specific characters concerning both foot and leg and this effect causes the decrease of information concerning the specific character of foot only. Therefore, it is effective to analyze foot and leg separately.
(2) In the analysis, the inclusion of the indices which represent the foot form to analysis items is effective to confirm shape factor of foot under careful examination of index's quality, because it can help the analysis of factor's meaning and increases the contribution rates of the third and fourth principal component.
(3) The exclusion of both items of stature and body weight causes the loss of informations concerning total body mass and decreases the eigenvalues and contribution rates in the first and second principal component of the foot and leg group or in the first principal component of the foot group only. Meanwhile, the exclusion increases the contribution rates of components on foot. Therefore the elimination of both stature and weight is effective to emphasize the shape factor of foot.

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