• The Journal of Korean Academy of Prosthodontics
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• v.59 no.1
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• pp.79-87
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• 2021

The digital workflow of optical impressions by the intraoral scanner and CADCAM manufacture of dental prostheses is actively developing. The complex process of traditional impression taking, definite cast fabrication, wax pattern making, and casting has been shortened, and the number of patient's visits can also be reduced. Advances in intraoral scanner technology have increased the precision and accuracy of optical impression, and its indication is progressively widened toward the long span fixed dental prosthesis. This case report describes the long span implant case, and the operator fully utilized digital workflow such as computer-guided implant surgical template and CAD-CAM produced restoration after the digital impression. The provisional restoration and customized abutments were prepared with the optical impression taken on the same day of implant surgery. Moreover, the final prosthesis was fabricated with the digital scan while utilizing the same customized abutment from the provisional restoration. During the data acquisition step, stl data of customized abutments, previously scanned at the time of provisional restoration delivery, were imported and automatically aligned with digital impression data using an 'A.I. abutment matching algorithm' the intraoral scanner software. By using this algorithm, it was possible to obtain the subgingival margin without the gingival retraction or abutment removal. Using the digital intraoral scanner's advanced functions, the operator could shorten the total treatment time. So that both the patient and the clinician could experience convenient and effective treatment, and it was possible to manufacture a prosthesis with predictability.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.2
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• pp.123-130
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• 2016

With the development of fast construction mode in shipbuilding market, the demand on accuracy management of hull is becoming higher and higher in shipbuilding industry. In order to enhance production efficiency and reduce manufacturing cycle time in shipbuilding industry, it is important for shipyards to have the accuracy of ship components evaluated efficiently during the whole manufacturing cycle time. In accurate shipbuilding process, block accuracy is the key part, which has significant meaning in shortening the period of shipbuilding process, decreasing cost and improving the quality of ship. The key of block accuracy control is to create a integrate block accuracy controlling system, which makes great sense in implementing comprehensive accuracy controlling, increasing block accuracy, standardization of proceeding of accuracy controlling, realizing "zero-defect transferring" and advancing non-allowance shipbuilding. Generally, managers of accuracy control measure the vital points at section surface of block by using the heavy total station, which is inconvenient and time-consuming for measurement of vital points. In this paper, a new measurement method based on point clouds technique has been proposed. This method is to measure the 3D coordinates values of vital points at section surface of block by using 3D scanner, and then compare the measured point with design point based on ICP algorithm which has an allowable error check process that makes sure that whether or not the error between design point and measured point is within the margin of error.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.1
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• pp.25-32
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• 2019

K-BEMS System was introduced to reduce peak load and to save total energy of the 200 buildings that KEPCO headquarter and branch offices use. And K-BEMS system is composed of PV, battery, and hybrid PCS. KEPCO research institute has carried out this K-BEMS research project for 3 years since January 2016. In this paper, the results of the project are shown. 9 modes of test results of K-BEMS system and are operational problems were analyzed. And measures to cure the trouble are also suggested. Batteries are operated more than 20% of SOC, and less than 20% of SOC battery protection switches are automatically shutting down the system and the system no longer respond to EMS, ending the supply of PV, and so therefore to continue the PV power supply it was turn out to be necessary that the EMS should automatically change its policy to change PV only supply mode automatically when the Battery Switch automatically operated. To operate the system continuously and automatically, it is necessary to modify the minimum operational SOC value, and in addition to that the EMS computer must remember the last shut-down SOC and Voltage which interrupted the system and add some margin to reflect the measurement error in the system.

• Korean Journal of Radiology
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• v.25 no.1
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• pp.43-54
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• 2024

Objective: To evaluate the added value of diffusion-weighted imaging (DWI)-based quantitative parameters to distinguish uterine sarcomas from atypical leiomyomas on preoperative magnetic resonance imaging (MRI). Materials and Methods: A total of 138 patients (age, 43.7 ± 10.3 years) with uterine sarcoma (n = 44) and atypical leiomyoma (n = 94) were retrospectively collected from four institutions. The cohort was randomly divided into training (84/138, 60.0%) and validation (54/138, 40.0%) sets. Two independent readers evaluated six qualitative MRI features and two DWI-based quantitative parameters for each index tumor. Multivariable logistic regression was used to identify the relevant qualitative MRI features. Diagnostic classifiers based on qualitative MRI features alone and in combination with DWI-based quantitative parameters were developed using a logistic regression algorithm. The diagnostic performance of the classifiers was evaluated using a cross-table analysis and calculation of the area under the receiver operating characteristic curve (AUC). Results: Mean apparent diffusion coefficient value of uterine sarcoma was lower than that of atypical leiomyoma (mean ± standard deviation, 0.94 ± 0.30 10^-3 mm²/s vs. 1.23 ± 0.25 10^-3 mm²/s; P < 0.001), and the relative contrast ratio was higher in the uterine sarcoma (8.16 ± 2.94 vs. 4.19 ± 2.66; P < 0.001). Selected qualitative MRI features included ill-defined margin (adjusted odds ratio [aOR], 17.9; 95% confidence interval [CI], 1.41-503, P = 0.040), intratumoral hemorrhage (aOR, 27.3; 95% CI, 3.74-596, P = 0.006), and absence of T2 dark area (aOR, 83.5; 95% CI, 12.4-1916, P < 0.001). The classifier that combined qualitative MRI features and DWI-based quantitative parameters showed significantly better performance than without DWI-based parameters in the validation set (AUC, 0.92 vs. 0.78; P < 0.001). Conclusion: The addition of DWI-based quantitative parameters to qualitative MRI features improved the diagnostic performance of the logistic regression classifier in differentiating uterine sarcomas from atypical leiomyomas on preoperative MRI.