• Journal of Sasang Constitutional Medicine
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• v.20 no.1
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• pp.42-47
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• 2008

1. Objectives The Body Shape and Feature is one of the important standard for classification of Sasang Constitutions. In order to evaluate one's Body Shape and Feature objectively we have been developing the Body Measuring Machine. Now we develop the 3D Automatic Body Measuring Machine(3D-ABMM). So we make an analysis of the 3D-ABMM's Accuracy. 2. Methods By using the 3D-ABMM and Vivid 9i(3D laser scanner, Konica Minolta) we have a surface scan of the three objects which are the upper body of the female and male Manikin and a male model. We overlap each scan data using the RapidForm2006 (3D scan data solution, INUS Technology) and calculate the average distance and standard deviation between the same point of each scan data. 3. Results and Conclusions In the female Manikin, the average distance is 0.84mm and the standard deviation is 1.16mm and the maximum distance is 10.68mm. In the male Manikin, the average distance is 1.12mm and the standard deviation is 1.19mm and the maximum distance is 12.00mm. In the male model, the average distance is 3.26mm and the standard deviation is 2.59mm and the maximum distance is 12.75mm. From the results, 3D-ABMM has good accuracy for scanning body and will be a usable hardware of the 3D Automatic Body Analysis Machine.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.288-297
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• 1994

The sewing machine is one of the oldest machine that has ever used, which is related with clothes' life. Modern sewing machines are divided into three groups by the sititch character, which are the lock stitch sewing machine group, the over lock sewing machine group and the specical sewing machine group. The lock stitch sewing machine have being used more than any others, which is also good model to study. This work is part of the improvement of an industrial lock stitch(ILS) sewing machine's design. The research objectives are the kinematic analysis and evaluations of stitch performance. The feed dog and the needle extreme's motion, which are important two part's motion in the sewing machine, are characterized by the stitch process and the needle trace. The needle trace is formulated as the stitch spacing, the stitch spacing's ratio(the static characteristic), and the stitch's phase difference(the dynamic characteristic). The tested ILS sewing machine is evaluated as a good static characteristic and a bad dynamic characteristic. Namely, a stitch spacing's ratio is 0.01~0.063(mm/mm) and a stitch's phase difference ratio is 0.06~0.13(mm/mm).

• Journal of the Korean Society of Safety
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• v.38 no.4
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• pp.1-7
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• 2023

The steel wheels of urban railway vehicles gather a lot of data through regular measurements during maintenance. However, limited research has been carried out utilizing this data, resulting in difficulties predicting the maintenance period. This paper studied a machine learning model suitable for mileage prediction by studying the characteristics of mileage change according to diameter and flange thickness changes. The results of this study indicate that the larger the diameter, the longer the travel distance, and the longest flange thickness is at 30 mm, which gradually shortened at other times. As a result of research on the machine learning prediction model, it was confirmed that the random forest model is the optimal model with a high coefficient of determination and a low root mean square error.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.1
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• pp.34-41
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• 1993

SUS304 is wellknown as difficult-to-machine materials. It is easy to appear workhardened, and workhardening is one of the causes of groove wear on the tool. In this paper, the author would like to compare the width of flank wear with that of groove wear, and to find whether the groove wear can be used as a criterion of a tool life. The design of the twelve tests provides three levels for each variable (speed: 200m/min, 118m/min, 70m/min; feed: 0.3mm/rev, 0.17mm/rev, 0.1mm/rev; depth of cut: 0.4mm, 0.28mm, 0.2mm). The study of tool-life testing by statistical technique follows usual most scientific sequence. So the tool-life predicting equation is calculated by the method of least squares. The overall adequacy of the model can be verified by the analysis of variance. The results obtained are as follows : 1) When SUS304 is cut in 200(m/min), the width of flank wear is much larger than that of groove wear. 2) In cutting speed 118m/min, flank wear is a little larger than groove wear and in the cutting speed 70m/min, the latter is a little larger so that it is reasonable to determine the tool life according the crierion by groove wear in the low cutting speed (less than 70m/min). 3) Owing to the burr the depth of engagement along the cutting edge is extended toward the shank.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.12
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• pp.105-112
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• 2009

In this paper, we investigated abnormal ESD failure on guard-rings in the smart power IC fabricated with $0.35{\mu}m$ Bipolar-CMOS-DMOS (BCD) technology. Initially, ESD failure occurred below 200 V in the Machine Model (MM) test due to current crowding in the parasitic diode associated with the guard-rings which are generally adopted to prevent latch-up in high voltage devices. Optical Beam Induced Resistance Charge (OBIRCH) and Scanning Electronic Microscope (SEM) were used to find the failure spot and 3-D TCAD was used to verify cause of failure. According to the simulation results, excessive current flows at the comer of the guard-ring isolated by Local Oxidation of Silicon (LOCOS) in the ESD event. Eventually, the ESD failure occurs at that comer of the guard-ring. The modified comer design of the guard-ring is proposed to resolve such ESD failure. The test chips designed by the proposed modification passed MM test over 200 V. Analyzing the test chips statistically, ESD immunity was increased over 20 % in MM mode test. In order to avoid such ESD failure, the automatic method to check the weak point in the guard-ring is also proposed by modifying the Design Rule Check (DRC) used in BCD technology. This DRC was used to check other similar products and 24 errors were found. After correcting the errors, the measured ESD level fulfilled the general industry specification such as HBM 2000 V and MM 200V.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.6
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• pp.189-194
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• 2012

The purpose of this study is to predict the performance of a cyclone drying machine and air ejector used in drying applications. This paper deals with optimization of the geometry of the ejector for sludge drying using computational fluid dynamics. To facilitate the design of a jet ejector for air drying machines, a numerical model of simultaneous mass and heat transfers between the liquid(sludge) and gas(air) phases in the jet ejector was developed. The steady-state model was based on unidimensional balance equations of mass, energy and momentum for the liquid and gas phases. It was shown that the optimum condition to minimize pressure and momentum loss of air in the ejector was d=220mm. It was found that sludge particles inside the cyclone was smoothly discharged by the conical wedge installed on the bottom of the cyclone.

• Journal of Technologic Dentistry
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• v.38 no.4
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• pp.291-298
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• 2016

Purpose: This study was to evaluate the effect of coloring liquids on the shear bond strength between zirconia and veneering ceramic. Methods: Zirconia(15 mm in diameter, 2.5 mm in thickness; n=40) used in the experiment were divided into 5 groups depending on the coloring liquid. Each specimen were polished using a polishing machine(LaboPol-2, Struers, UK). A cylinder of veneering porcelain(6 mm in diameter, 3 mm in thickness) was fabricated and fired on zirconia surfaces. The shear bond strength was measured using a universal testing machine(Model 4302, Instron, USA). All data were analyzed statistically using a one-way ANOVA and Tukey's multiple comparisons test. After the shear bond test, fracture surfaces were examined by SEM. Results: Colored zirconia showed a higher shear bonding strength than that of uncolored zirconia except for colored zirconia immersed in Zirkonzahn coloring liquid. In particular, colored zirconia immersed in Kuwotech coloring liquid showed the highest shear bond strength. After the shear bond test, mixed failure patterns were mainly observed in the failure between zirconia and veneering ceramic. Conclusion: Coloring liquid enhanced the shear bond strength zirconia and veneering ceramic than uncolored zirconia.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.255-262
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• 2018

Purpose: To obtain the dynamic characteristics (spring stiffness and damping coefficient) of a rubber mount supporting a tractor cabin in order to develop a simulation model of an agricultural tractor. Methods: The KS M 6604 rubber mount test method was used to test the dynamic characteristics of the rubber mount. Of the methods proposed in the standard, the resonance method was used. To perform the test according to the standard, a base excitation test device was constructed and the accelerations were measured. Results: Displacement transmissibility was measured by varying the frequency from 3-30 Hz. The vibration transmissibility at resonance was confirmed, and the dynamic stiffness and damping coefficient of the rubber mount were obtained. The front rubber mount has a spring constant of 1247 N/mm and damping ratio of 3.27 Ns/mm, and the rear rubber mount has a spring constant of 702 N/mm and damping ratio of 1.92 Ns/mm. Conclusions: The parameters in the z-direction were obtained in this study. In future studies, we will develop a more complete tractor simulation model if the parameters for the x- and y-directions can be obtained.

• Archives of Craniofacial Surgery
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• v.12 no.1
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• pp.12-16
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• 2011

Purpose: This study examined the biomechanical stability of four different plating techniques in the experimental model of mandibular subcondyle fracture. Methods: Twenty standardized bovine tibia bone samples ($7{\times}1.5{\times}1.0cm$) were used for this study. Each of the four sets of tibia bone was cut to mimic a perpendicular subcondyle fracture in the center area. The osteotomized tibia bone was fixed using one of four different fixation groups (A,B,C,D). The fixation systems included single 2.0 mm 4 hole mini adaption plate (A), single 2.0 mm 4 hole dynamic compression miniplate (B), double fixation with 2.0 mm 4 hole mini adaption plate (C), double fixation with a 2.0 mm 4 hole mini adaption plate and 2.0 mm 4 hole dynamic compression miniplate (D). A bending force was applied to the experimental model using a pressure machine (858 table top system, $MTS^{(R)}$) until failure occurred. The load for permanent deformation, maximum load of failure were measured in the load displacement curve with the chart recorder. Results: Double fixation with a 2.0 mm 4 hole mini adaption plate and a 2.0 mm 4 hole dynamic compression miniplate (D) applied to the anterior and posterior regions of the subcondyle experimental model showed the highest load to failure. Conclusion: From this study, double fixation with an adaption plate and dynamic compression miniplate fixation technique produced the greatest biomechanical stability. This technique may be considered a useful means of fixation to reduce the postoperative internal maxillary fixation period and achieve early mobility of the jaw.

• Imaging Science in Dentistry
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• v.51 no.3
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• pp.299-306
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• 2021

Purpose: This study aimed to propose a fully automatic landmark identification model based on a deep learning algorithm using real clinical data and to verify its accuracy considering inter-examiner variability. Materials and Methods: In total, 950 lateral cephalometric images from Yonsei Dental Hospital were used. Two calibrated examiners manually identified the 13 most important landmarks to set as references. The proposed deep learning model has a 2-step structure-a region of interest machine and a detection machine-each consisting of 8 convolution layers, 5 pooling layers, and 2 fully connected layers. The distance errors of detection between 2 examiners were used as a clinically acceptable range for performance evaluation. Results: The 13 landmarks were automatically detected using the proposed model. Inter-examiner agreement for all landmarks indicated excellent reliability based on the 95% confidence interval. The average clinically acceptable range for all 13 landmarks was 1.24 mm. The mean radial error between the reference values assigned by 1 expert and the proposed model was 1.84 mm, exhibiting a successful detection rate of 36.1%. The A-point, the incisal tip of the maxillary and mandibular incisors, and ANS showed lower mean radial error than the calibrated expert variability. Conclusion: This experiment demonstrated that the proposed deep learning model can perform fully automatic identification of cephalometric landmarks and achieve better results than examiners for some landmarks. It is meaningful to consider between-examiner variability for clinical applicability when evaluating the performance of deep learning methods in cephalometric landmark identification.