• Journal of the Korea Computer Graphics Society
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• v.27 no.2
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• pp.1-11
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• 2021

In a virtual environment, a 3D workspace and 3D interaction are possible, but most virtual reality applications use a 2D color picker. This paper implements a 3D color picker based on 3D color space in a virtual environment, and compares color selection performance with the existing 2D color picker. The 3D color picker is intuitive by using the 3D color space as it is, and it can position the 3D pointer at a specific point in the color space using a controller, which is a virtual reality device, so a user can select a color in one step. On the other hand, the 2D color picker has the advantage of being familiar with existing users who work with colors in a computer environment, but has a disadvantage that requires several steps of user interaction since it has to set color properties through 2D interfaces. Based on user experiments, we confirmed the usefulness of a 3D color picker in addition to a 2D color picker in a virtual environment, and it was possible to perform natural 3D work in a virtual environment using the 3D color picker.

• Journal of Biosystems Engineering
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• v.25 no.5
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• pp.399-408
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• 2000

This study is final focused on developing fruit harvesting robot can distinguish fruit type and status accurately. Multi-joint robot is able to discriminate tree shape and select mature fruit by image processing. The multi-joint robot consists of (a) rotating base, (b)turning first joint-arm, (c)rotating and turning second joint-arm, (d)rotating and turning third joint-arm, (e)rotating and turning last joint and (f)picker hand. The operational ranges of the robot are: horizontal 860~2,220mm, vertical 1,440~2,260mm, 270 degrees’rotation angle, 90 or 270 degrees’turning angle. The robot weighs 330kg. The multi-joint robot was designed in high accuracy and efficiency by getting as close as the movements of human arms and waist.

• Tunnel and Underground Space
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• v.21 no.5
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• pp.349-358
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• 2011

This paper introduces a new P wave arrival time determination algorithm of acoustic emission (AE) suitable to identify P waves with low signal-to-noise ratio generated in rock masses around the high-level radioactive waste disposal repositories. The algorithms adopted for this paper were amplitude threshold picker, Akaike Information Criterion (AIC), two step AIC, and Hinkley criterion. The elastic waves were generated by Pencil Lead Break test on a granite sample, then mixed with white noise to make it difficult to distinguish P wave artificially. The results obtained from amplitude threshold picker, AIC, and Hinkley criterion produced relatively large error due to the low signal-to-noise ratio. On the other hand, two step AIC algorithm provided the correct results regardless of white noise so that the accuracy of source localization was more improved and could be satisfied with the error range.