• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.3
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• pp.99-103
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• 1998

The curved surface machined by plate end mill causes a excess non-cutting volume, in these cases ball end mill is used for the curved surfaces. This study is aimed to obtain the optimum cutting conditions of various cutting speed, table speed, tool diameter, radius of curvature roughness on the conditions of various cutting speed, tool diameter, radius of curvature when machining the curved surface using the ball end mill. After designing curve rates, obtaining NC data by CAD/CAM system through CC-Cartesian method and transferred the data through DNC system, we machined the specimens by the CNC machining center, The surface roughness of specimens was measured by surface roughness tester and CNC 3D coordinate measuring machine. The cutting condition were the same as follow velocity; 15, 20, 25 30m/min, feed rate;40, 60, 80, 100m/min and radius of curvature; 30,40,50,60mm, tool diameters; ø8, ø12, ø16, ø 20mm. Analizing the working results, we can acquire the optimum cutting condition of curved specimen at the cutting velocity of 20~25m/min and the feed rate of 80mm/min. As the same cutting condition the best surface roughness was showed at ø16mm of the tool diameter. But the tool diameter was smaller than ø8mm. we could improve for the surface roughness by controlling the cusp.

• Journal of Technologic Dentistry
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• v.42 no.3
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• pp.213-219
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• 2020

Purpose: This study aimed to identify the impact of physical surface roughing with a polishing tool onto the pre-sintering yttria-stabilized tetragonal zirconia polycrystals (TZP) core and liner treatment for chemical bonding on the bond strength of TZP core and veneering ceramic. Methods: Overall, 80 specimens were classified into two groups (non-liner, NL; and usingliner, UL ) depending on the use of liner, and these two groups were then subclassified into four groups depending on the polishing tool used. (1) Non-liner groups: NS, non-liner+stone point; NC, non-liner+carbide bur; NP, non-liner+paper cone point; NT, non-liner+silicon point. (2) Using-liner groups: US, using-liner+stone point; UC, using-liner+carbide bur; UP, usingliner+paper cone point; UT, using-liner+silicon point. The pre-sintering surface roughing values and shapes were observed, and after burning up the veneering ceramic, the shear bond strength was measured using a universal testing machine. For significance testing, a one-way analysis of variance and Tukey's multiple comparison test were conducted. An optical microscope was used to observe the fracture plane, and the following results were obtained. Results: Surface roughness NP (4.09±0.51 ㎛) represented a higher value than other groups (p<0.001). In shear bond strength, NS (35.21±1.44 MPa) of the NL group showed the highest bond strength (p<0.001). The UL group did not show a statistically significant difference between groups (p=0.612). Conclusion: Our study findings reveal that the bond strength of TZP core and veneering ceramic was improved by pre-sintering physical surface treatment than by chemical bonding with liner surface treatment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.105-122
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• 2022

According to the statistics about the fatal crashes that have occurred on the expressways for the last 5 years, those who died on the shoulders of the road has been as 3 times high as the others who died on the expressways. It suggests that the crashes on the shoulders of the road should be fatal, and that it would be important to prevent the traffic crashes by cracking down on the vehicles intruding the shoulders of the road. Therefore, this study proposed a method to detect a vehicle that violates the shoulder lane by using the Faster R-CNN. The vehicle was detected based on the Faster R-CNN, and an additional reading module was configured to determine whether there was a shoulder violation. For experiments and evaluations, GTAV, a simulation game that can reproduce situations similar to the real world, was used. 1,800 images of training data and 800 evaluation data were processed and generated, and the performance according to the change of the threshold value was measured in ZFNet and VGG16. As a result, the detection rate of ZFNet was 99.2% based on Threshold 0.8 and VGG16 93.9% based on Threshold 0.7, and the average detection speed for each model was 0.0468 seconds for ZFNet and 0.16 seconds for VGG16, so the detection rate of ZFNet was about 7% higher. The speed was also confirmed to be about 3.4 times faster. These results show that even in a relatively uncomplicated network, it is possible to detect a vehicle that violates the shoulder lane at a high speed without pre-processing the input image. It suggests that this algorithm can be used to detect violations of designated lanes if sufficient training datasets based on actual video data are obtained.