• The Journal of Korean Physical Therapy
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• v.20 no.4
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• pp.71-78
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• 2008

Purpose: This study standardizes the position and direction of devices based on general user expectations and stereotypes. Population stereotypes are cognitive structures that contain the perceiver's knowledge, beliefs, and expectations about human groups. In this paper, the stereotypes that people typically expect when manipulating 'cylindrical key-in-knob locks' and 'lever-type water faucet handles' were investigated and data regarding their expectations were collected. Methods: Two sets of 600 participants, between 13 and over 60 years old, were recruited for the experiment. Each group was evenly subdivided into six age groups. Each participant was presented with cylindrical door locks mounted on a miniature door and actual lever-type water faucet handles mounted on a mockup sink. Results: If the cylindrical lock was positioned 'vertically,' 59.2% of the participants expected the device to be locked, and if the lever type faucet handle was positioned 'up,' 63.0% of the participants expected the device to be turned on. Thus, daily-use devices should be designed consistent with user expectations of operation. There was a significant difference between genders for manipulating the faucet handle between up and down. Conclusion: A more general stereotype may be defined by repetitive measurements under the same test conditions with fixed time intervals, as well as accounting for people with cognitive problems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.73-82
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• 2010

Door is an important object to understand given environment and it could be used to distinguish with corridors and rooms. Doors are widely used natural landmark in mobile robotics for localization and navigation. However, almost algorithm for door recognition with camera is difficult real-time application because feature extraction and matching have heavy computation complexity. This paper proposes a method to recognize a door in corridor. First, we extract distinguished lines which have high possibility to comprise of door using Hough transformation. Then, we detect candidate of door region by applying previously extracted lines to first-stage visual fuzzy system. Finally, door regions are determined by verifying knob region in candidate of door region suing second-stage visual fuzzy system.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.54-60
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• 2018

In this paper, we propose an efficient automatic control method for the collision avoidance of drones. In general, the drones are controlled by transmitting to the flight control (FC) module the received PWM signals transmitted from a RC controller which transduce movements of the knob into PWM signal. We implemented the collision avoidance module in-between receiver and FC module to monitor and change the throttle, pitch and roll control signals to avoid drone collision. In order to avoid the collision, a LiDAR distance sensor and a servo-motor are installed and periodically measure the obstacle distance within -45 degrees from 45 degrees in flight direction. If the collision is predicted, the received PWM signal is changed and transmitted to the FC module to prevent the collision. We applied our proposed method to a hexacopter and the experimental results show that the safety is improved because it can prevent the collision caused by the inadvertency or inexperienced maneuver.