• The Journal of Korean Academy of Prosthodontics
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• v.50 no.2
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• pp.85-91
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• 2012

Purpose: The object of this study was to determine if the low-priced alloy and metal UCLA abutment could be available for manufacturing bar-retained framework of implant prosthesis. Materials and methods: Bar structure was classified into 4 groups, The specimen of group 1 and 2 were based on casting high noble metal alloys and noble metal alloys with gold UCLA abutment. The specimen of group 3 and 4 were based on casting noble metal alloys and base metal alloys with metal UCLA abutment. Cast bar structure was installed in an acrylic resin model and only the screw on the hexed abutment side was tightened to 20 Ncm. On the opposite side, vertical discrepancy was measured with stereo microscope from front, back, and lateral side of the implant-abutment interface. One-way ANOVA was performed to analyze the marginal fit discrepancy. Results: One-way ANOVA test showed significant differences among all groups ($P$<.05) except for Group 1 and 3. Among them, difference between Group 1 and 2 was noticeable. Measured vertical discrepancies were all below $70{\mu}m$ except to Group 2. Conclusion: Base metal alloy and metal UCLA abutment could be used as an alternative to high-priced gold alloy for implant bar-retained framework.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.125-130
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• 2011

Since conventional optimization that is classified as a deterministic method does not consider the uncertainty involved in a modeling or manufacturing process, an optimum design is often determined to be on the boundaries of the feasible region of constraints. Reliability-based design optimization is a method for obtaining a solution by minimizing the objective function while satisfying the reliability constraints. This method includes an optimization process and a reliability analysis that facilitates the quantization of the uncertainties related to design variables. Moment-based reliability analysis is a method for calculating the reliability of a system on the basis of statistical moments. In general, on the basis of these statistical moments, the Pearson system estimates seven types of distributions and determines the reliability of the system. However, it is technically difficult to practically consider the Pearson Type IV distribution. In this study, we propose an enhanced Pearson Type IV distribution based on a kriging model and validate the accuracy of the enhanced Pearson Type IV distribution by comparing it with a Monte Carlo simulation. Finally, reliability-based design optimization is performed for a system with type IV distribution by using the proposed method.

• Composites Research
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• v.34 no.5
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• pp.296-304
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• 2021

This study presented the evaluation of the stamp forming process for L-shape CF/PEKK thermoplastic composite using the finite element model. The formability of three different trimming allowances has been examined for representative product geometry. The results showed that those manufactured by high trimming allowance showed more excellent formability in those areas. Moreover, the effects of the trimming allowances on the stress, thickness, wrinkle distributions of thermoplastic composites fabricated with the stamp forming process were evaluated. The comparison of the simulation and experimental results for the thickness and wrinkle distributions proved the accuracy of the stamp forming model. The crystallinity of the composite was performed by differential scanning calorimetry (DSC). The void content of the composite was evaluated by matrix digestion. Then, the fabricated structure was characterized and achieved high quality in crystallinity and void content. Consequently, the presented FEM modeling shows excellent potential for application in the aircraft product design process. This pragmatic approach could efficiently offer a valuable solution for the thermoplastic composite manufacturing field.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.6
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• pp.255-266
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• 2022

The quality control of coarse aggregate among aggregates, which are the main ingredients of concrete, is currently carried out by SPC(Statistical Process Control) method through sampling. We construct a smart factory for manufacturing innovation by changing the quality control of coarse aggregates to inspect the coarse aggregates based on this image by acquired images through the camera instead of the current sieve analysis. First, obtained images were preprocessed, and HED(Hollistically-nested Edge Detection) which is the filter learned by deep learning segment each object. After analyzing each aggregate by image processing the segmentation result, fineness modulus and the aggregate shape rate are determined by analyzing result. The quality of aggregate obtained through the video was examined by calculate fineness modulus and aggregate shape rate and the accuracy of the algorithm was more than 90% accurate compared to that of aggregates through the sieve analysis. Furthermore, the aggregate shape rate could not be examined by conventional methods, but the content of this paper also allowed the measurement of the aggregate shape rate. For the aggregate shape rate, it was verified with the length of models, which showed a difference of ±4.5%. In the case of measuring the length of the aggregate, the algorithm result and actual length of the aggregate showed a ±6% difference. Analyzing the actual three-dimensional data in a two-dimensional video made a difference from the actual data, which requires further research.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.8
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• pp.975-981
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• 2013

A robust optimization is only one of the ways to minimize the effects of variances in design variables on the objective functions at the preliminary design stage. To predict the variances and to formulate the probabilistic constraints are the most important procedures for the robust optimization formulation. Though several methods such as the process capability index and the six sigma technique were proposed for the prediction and formulation of the variances and probabilistic constraints, respectively, there are few attempts using a percent defective which has been widely applied in the quality control of the manufacturing process for probabilistic constraints. In this study, the robust optimization for a lower control arm of automobile vehicle was carried out, in which the design space showing the mean and variance sensitivity of weight and stress was explored before robust optimization for a lower control arm. The 2nd order Taylor expansion for calculating the standard deviation was used to improve the numerical accuracy for predicting the variances. Simplex algorithm which does not use the gradient information in optimization was used to convert constrained optimization into unconstrained one in robust optimization.

• Progress in Medical Physics
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• v.29 no.1
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• pp.8-15
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• 2018

This work reports the acceptance testing and commissioning experience of the Robotic Intensity-Modulated Radiation Therapy (IMRT) M6 system with a newly released $InCise^{TM}2$ Multileaf Collimator (MLC) installed at the Yonsei Cancer Center. Acceptance testing included a mechanical interdigitation test, leaf positional accuracy, leakage check, and End-to-End (E2E) tests. Beam data measurements included tissue-phantom ratios (TPRs), off-center ratios (OCRs), output factors collected at 11 field sizes (the smallest field size was $7.6mm{\times}7.7mm$ and largest field size was $115.0mm{\times}100.1mm$ at 800 mm source-to-axis distance), and open beam profiles. The beam model was verified by checking patient-specific quality assurance (QA) in four fiducial-inserted phantoms, using 10 intracranial and extracranial patient plans. All measurements for acceptance testing satisfied manufacturing specifications. Mean leaf position offsets using the Garden Fence test were found to be $0.01{\pm}0.06mm$ and $0.07{\pm}0.05mm$ for X1 and X2 leaf banks, respectively. Maximum and average leaf leakages were 0.20% and 0.18%, respectively. E2E tests for five tracking modes showed 0.26 mm (6D Skull), 0.3 mm (Fiducial), 0.26 mm (Xsight Spine), 0.62 mm (Xsight Lung), and 0.6 mm (Synchrony). TPRs, OCRs, output factors, and open beams measured under various conditions agreed with composite data provided from the manufacturer to within 2%. Patient-specific QA results were evaluated in two ways. Point dose measurements with an ion chamber were all within the 5% absolute-dose agreement, and relative-dose measurements using an array ion chamber detector all satisfied the 3%/3 mm gamma criterion for more than 90% of the measurement points. The Robotic IMRT M6 system equipped with the $InCise^{TM}2$ MLC was proven to be accurate and reliable.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.648-654
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• 2004

The Mass Flow Controller(MFC) has become crucial in semiconductor manufacturing equipments. It is an important element because the quality and the yield of a semiconductor process are decided by the accurate flow control of gas. Therefore, the demand for implementing the high speed and the highly accurate control of MFCs has been increasing. It is hard to find an article of the control algorithm applied to MFCs. But, it is known that commercially available MFCs adopt PID control algorithms. Particularly, when the system detects the flow by way of heat transfer, the MFC control problem includes the slow response and the nonlinearity. In this paper, MFC control algorithm with a superior performance to the conventional PID algorithm is discussed and the superiority is demonstrated through the experiment. A fuzzy controller was utilized in order to compensate the nonlinearity and the slow response, and the performance is compared with that of an MFC currently available in the market. The control system, in this paper, consists of a personal computer, the data acquisition board and the control algorithm carried out by LabWindows/CVI program on the PC. In addition, a method of estimating the actual flow from the sensor output with the slow response is presented. In conclusion, according to the result of the experiment, the proposed algorithm shows better accuracy and is faster than the conventional controller.

• Journal of Preventive Medicine and Public Health
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• v.35 no.4
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• pp.282-286
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• 2002

Objectives : The level of 4-hydroxyproline (4-Hyp) in human urine was measured using high performance liquid chromatography (HPLC) with a fluorescence detector. This method is useful for medical examinations and investigating the radicals induced by physical, chemical, mental stresses. This method is superior to many published several methods in terms of its low cost and ability to analyze many samples. Methods : The urine from workers in a tire manufacturing company (22 male pre- and post-shift workers) and 18 office-workers as controls were analyzed. Data concerning age, the cumulative drinking amount and the cumulative smoking amount was collected with a questionnaire. The optimum applied amount of dansyl-Cl, the optimum reaction temperature and time, the recoveries and the optimum pH of the eluent and buffer were determined.4-Hyp from human urine was derivatized with dansyl-Cl (dimethylamino-naphthalene-1-sulfonyl chloride) after removing the a-amino acid by a treatment with phthalic dicarboxaldehyde (OPA) and cleaned with Bond Elut C18 column. The 4-Hyp derivatives were separated on a reversed phase column by gradient elution with a phosphate buffer (5 mmol, pH 8.0) and acetonitrile, and detected by fluorescence measurements at 340 nm (excitation) and 538 nm (emission). Results : The detection limit for the urinary free 4-Hyp was $0.364{\mu}mol/l$. The recovery rate of 4-Hyp was 99.7%, and the effective pH of the phosphate buffer and borate buffer were 3.0 and 8.0, respectively. From statistical analysis, age, drinking and smoking did not affect the urinary free 4-Hyp in both the controls and workers. The range of urinary 4-Hyp in the controls, pre-shift, and post-shift workers were 0.33-16.44, N.D-49.06, and $0.32-56.27{\mu}mol/l$. From the pared-sample t-test, the urinary 4-Hyp levels in post-shift workers ($11.82{\pm}6.73\;nmmol/mg\;Cre$) were 2-fold higher than in pre-shift workers ($5.36{\pm}5.53\;nmol;/mg\;Cre$) and controls ($4.91{\pm}4.89\;nmol;/mg\;Cre$). Conclusions : This method was developed with high sensitivity, accuracy, and precision. The present method was effectively applied to analyze the urinary free 4-Hyp in both controls and workers.

• Korean Journal of Optics and Photonics
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• v.33 no.4
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• pp.137-145
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• 2022

A directional coupler device, one of the fundamental components of photonic integrated circuits, distributes optical power by evanescent field coupling between two adjacent optical waveguides. In this paper, the design process for manufacturing a directional coupler device is reviewed, and the accuracy of the design results, as seen from the characteristics of the actual fabricated device, is confirmed. When designing a directional coupler device through a two-dimensional (2D) beam-propagation-method (BPM) simulation, an optical structure is converted to a two-dimensional planar structure through the effective index method. After fabricating the directional coupler device array, the characteristics are measured. To supplement the 2D-BPM results that are different from the experimental results, a 3D-BPM simulation is performed. Although 3D-BPM simulation requires more computational resources, the simulation result is closer to the experimental results. Furthermore, the waveguide core refractive index used in 3D-BPM is adjusted to produce a simulation result consistent with the experimental results. The proposed design procedure enables accurate design of directional coupler devices, predicting the experimental results based on 3D-BPM.