• The Journal of Advanced Prosthodontics
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• v.15 no.6
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• pp.281-289
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• 2023

PURPOSE. This study aimed to predict the positional coordinates of incisor points from the scan data of conventional complete dentures and verify their accuracy. MATERIALS AND METHODS. The standard triangulated language (STL) data of the scanned 100 pairs of complete upper and lower dentures were imported into the computer-aided design software from which the position coordinates of the points corresponding to each landmark of the jaw were obtained. The x, y, and z coordinates of the incisor point (X_P, Y_P, and Z_P) were obtained from the maxillary and mandibular landmark coordinates using regression or calculation formulas, and the accuracy was verified to determine the deviation between the measured and predicted coordinate values. Y_P was obtained in two ways using the hamularincisive-papilla plane (HIP) and facial measurements. Multiple regression analysis was used to predict Z_P. The root mean squared error (RMSE) values were used to verify the accuracy of the X_P and Y_P. The RMSE value was obtained after crossvalidation using the remaining 30 cases of denture STL data to verify the accuracy of Z_P. RESULTS. The RMSE was 2.22 for predicting X_P. When predicting Y_P, the RMSE of the method using the HIP plane and facial measurements was 3.18 and 0.73, respectively. Cross-validation revealed the RMSE to be 1.53. CONCLUSION. Y_P and Z_P could be predicted from anatomical landmarks of the maxillary and mandibular edentulous jaw, suggesting that Y_P could be predicted with better accuracy with the addition of the position of the lower border of the upper lip.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3543-3548
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• 2023

Shutdown chemistry evolution is performed in nuclear power plants at each refueling outage (RFO) to establish safe conditions to open system and minimize inventory of corrosion products in the reactor coolant system (RCS). After hydrogen peroxide is added to RCS during shutdown chemistry evolution, corrosion products are released and are removed by filters and ion exchange resins in the chemical volume control system (CVCS). Shutdown chemistry evolution including RCS clean-up time to remove released corrosion products impacts the critical path schedule during RFOs. The estimation of clean-up time prior to RFO can provide more reliable actions for RCS clean-up operations and transients to operators during shutdown chemistry. Electric Power Research Institute (EPRI) shutdown calculator (SDC) enables to provide clean-up time by Co-58 peak activity through operational data from nuclear power plants (NPPs). In this study, we have investigated the results of EPRI SDC by shutdown chemistry data of Co-58 activity using NPP data from previous cycles and modeled the estimated clean-up time by EPRI SDC using average Co-58 activity of the NPP. We selected two RFO data from the NPP to evaluate EPRI SDC results using the purification time to reach to 1.3 mCi/cc of Co-58 after hydrogen peroxide addition. Comparing two RFO data, the similar purification time between actual and computed data by EPRI SDC, 0.92 and 1.74 h respectively, was observed with the deviation of 3.7-7.2%. As the modeling the estimated clean-up time, we calculated average Co-58 peak concentration for normal cycles after cycle 10 and applied two-sigma (2σ, 95.4%) for predicted Co-58 peak concentration as upper and lower values compared to the average data. For the verification of modeling, shutdown chemistry data for RFO 17 was used. Predicted RCS clean-up time with lower and upper values was between 21.05 and 27.58 h, and clean-up time for RFO 17 was 24.75 h, within the predicted time band. Therefore, our calculated modeling band was validated. This approach can be identified that the advantage of the modeling for clean-up time with SDC is that the primary prediction of shutdown chemistry plans can be performed more reliably during shutdown chemistry. This research can contribute to improving the efficiency and safety of shutdown chemistry evolution in nuclear power plants.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.18 no.2
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• pp.75-84
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• 2014

Objectives Eyes, one of visual inspection regions, present important clues to pathological patterns including deficiency and excess patterns to the clinicians. The purpose of this study was to develop Eyes Inspection Questionnaire (EIQ) and to examine which items among the EIQ were more predictive of clinicians' determination for the deficiency and excess patterns. Methods Nine questionnaire items for Visual Inspection of Eyes were extracted through the literature review. These items were presented to the 4 Korean medical doctors who are specialized in visual inspection to conduct the Delphi method. The Korean medical doctors were asked to rate the importance of each items for the corresponding Visual Inspection of Eyes, using a Likert 5-point scale(the 3 points of importance as a cut-off point). Then, out of 75 photographs submitted to the Society of HyungSang Medicine in 2009, 30 portrait pictures were selected as samples. The samples were copied to make 60 sample pictures, and then randomly assigned to 4 clinicians. The 4 clinicians evaluated the 60 samples for excess and deficiency of the eyes and were asked to check the 6 questionnaire items. The results were recorded as 5-points-scale, and their average and standard deviations were calculated. Intra- class reliability test and multi regression test were performed using SPSS 13. Results Intra-class correlation coefficient (ICC) was between 0.750 to 0.841 (P<0.05). Indices for visual inspection of the eyes were: endowment of the bone structure around the eyes; brightness of the eyes; upward deviation of the eyes; eye shapes; and definition of iris. 76.92% of deficiency symptom patterns and 86.42% of the excess symptom patterns matched the patterns predicted by the visual inspection of the eyes, according to the frequency analysis. According to the multiple regression analysis, were significantly related to the excessive symptoms, and to the deficiency symptoms. Conclusion This study is the first attempt of development for checklist of excess and deficiency of Visual Inspection of Eyes and quantitative measurement of excess and deficiency using the Visual Inspection of Eyes by the visual inspection experts. Still, additional studies are needed regarding the relationship visual inspection methods have with existing standards of diagnosis.

• The korean journal of orthodontics
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• v.39 no.2
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• pp.112-119
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• 2009

Objective: To develop a mixed dentition analysis method in consideration of the normal variation of tooth sizes. Methods: According to the tooth-size of the maxillary central incisor, maxillary 1st molar, mandibular central incisor, mandibular lateral incisor, and mandibular 1st molar, 307 normal occlusion subjects were clustered into the smaller and larger tooth-size groups. Multiple regression analyses were then performed to predict the sizes of the canine and premolars for the 2 groups and both genders separately. For a cross validation dataset, 504 malocclusion patients were assigned into the 2 groups. Then multiple regression equations were applied. Results: Our results show that the maximum errors of the predicted space for the canine, 1st and 2nd premolars were 0.71 and 0.82 mm residual standard deviation for the normal occlusion and malocclusion groups, respectively. For malocclusion patients, the prediction errors did not imply a statistically significant difference depending on the types of malocclusion nor the types of tooth-size groups. The frequency of prediction error more than 1 mm and 2 mm were 17.3% and 1.8%, respectively. The overall prediction accuracy was dramatically improved in this study compared to that of previous studies. Conclusions: The computer aided calculation method used in this study appeared to be more efficient.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.9
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• pp.1215-1221
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• 2016

The prediction of carcass composition in Hanwoo steers is very important for value-based marketing, and the improvement of prediction accuracy and precision can be achieved through the analyses of independent variables using a prediction equation with a sufficient dataset. The present study was conducted to develop a prediction equation for Hanwoo carcass composition for which data was collected from 7,907 Hanwoo steers raised at a private farm in Gangwon Province, South Korea, and slaughtered in the period between January 2009 and September 2014. Carcass traits such as carcass weight (CWT), back fat thickness (BFT), eye-muscle area (EMA), and marbling score (MAR) were used as independent variables for the development of a prediction equation for carcass composition, such as retail cut weight and percentage (RC, and %RC, respectively), trimmed fat weight and percentage (FAT, and %FAT, respectively), and separated bone weight and percentage (BONE, and %BONE), and its feasibility for practical use was evaluated using the estimated retail yield percentage (ELP) currently used in Korea. The equations were functions of all the variables, and the significance was estimated via stepwise regression analyses. Further, the model equations were verified by means of the residual standard deviation and the coefficient of determination ($R^2$) between the predicted and observed values. As the results of stepwise analyses, CWT was the most important single variable in the equation for RC and FAT, and BFT was the most important variable for the equation of %RC and %FAT. The precision and accuracy of three variable equation consisting CWT, BFT, and EMA were very similar to those of four variable equation that included all for independent variables (CWT, BFT, EMA, and MAR) in RC and FAT, while the three variable equations provided a more accurate prediction for %RC. Consequently, the three-variable equation might be more appropriate for practical use than the four-variable equation based on its easy and cost-effective measurement. However, a relatively high average difference for the ELP in absolute value implies a revision of the official equation may be required, although the current official equation for predicting RC with three variables is still valid.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.4
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.

• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.161-170
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• 2023

We attempted to estimate the carbon accumulation of Hibiscus hamabo and Paliurus ramosissimus, semimangroves native to Jeju Island, by remote sensing and to build an artificial intelligence model that predicts its spatial variation with climatic factors. The aboveground carbon accumulation of semi-mangroves was estimated from the aboveground biomass density (AGBD) provided by the Global Ecosystem Dynamics Investigation (GEDI) lidar upscaled using the normalized difference vegetation index (NDVI) extracted from Sentinel-2 images. In Jeju Island, carbon accumulation per unit area was 16.6 t C/ha for H. hamabo and 21.1 t C/ha for P. ramosissimus. Total carbon accumulation of semi-mangroves was estimated at 11.5 t C on the entire coast of Jeju Island. Random forest analysis was applied to predict carbon accumulation in semi-mangroves according to environmental factors. The deviation of aboveground biomass compared to the distribution area of semi-mangrove forests in Jeju Island was calculated to analyze spatial variation of biomass. The main environmental factors affecting this deviation were the precipitation of the wettest month, the maximum temperature of the warmest month, isothermality, and the mean temperature of the wettest quarter. The carbon accumulation of semi-mangroves predicted by random forest analysis in Jeju Island showed spatial variation in the range of 12.0 t C/ha - 27.6 t C/ha. The remote sensing estimation method and the artificial intelligence prediction method of carbon accumulation in this study can be used as basic data and techniques needed for the conservation and creation of mangroves as carbon sink on the Korean Peninsula.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.50-57
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• 2011

For effective and accurate prediction of overpressure in the Efomeh field, located in the Niger delta basin of Nigeria, integrated seismic and borehole analyses were undertaken. Normal and abnormal pore pressure zones were delineated based on the principle of normal and deviation from normal velocity trends. The transition between the two trends signifies the top of overpressure. The overpressure tops were picked at regular intervals from seismic data using interval velocities obtained by applying Dix's approximation. The accuracy of the predicted overpressure zone was confirmed from the sonic velocity data of the Efomeh 01 well. The variation to the depth of overpressure between the predicted and observed values was less than 10mat the Efomeh 01 well location, with confidence of over 99 per cent. The depth map generated shows that the depth distribution to the top of the overpressure zone of the Efomeh field falls within the sub-sea depth range of 2655${\pm}$2m (2550 ms) to 3720${\pm}$2m (2900 ms). This depth conforms to thick marine shales using the Efomeh 01 composite log. The lower part of the Agbada Formation within the Efomeh field is overpressured and the depth of the top of the overpressure does not follow any time-stratigraphic boundary across the field. Prediction of the top of the overpressure zone within the Efomeh field for potential wells that will total depth beyond 2440m sub-sea is very important for safer drilling practice as well as the prevention of lost circulation.

• The Korean Journal of Pain
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• v.29 no.4
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• pp.249-254
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• 2016

Background: This study aimed to investigate the effect of strenuous exercise on ${\beta}$-endorphine (${\beta}$-END) level in fibromyalgia (FM) patients compared to healthy subjects. Methods: We enrolled 30 FM patients and 15 healthy individuals. All study participants underwent a treadmill exercise test using modified Bruce protocol (M.Bruce). The goal of the test was achieving at least 70% of the predicted maximal heart rate (HRMax). The serum levels of ${\beta}$-END were measured before and after the exercise program. Measurements were done while heart rate was at least 70% of its predicted maximum. Results: The mean ${\pm}$ the standard deviation (SD) of exercise duration in the FM and control groups were $24.26{\pm}5.29$ and $29.06{\pm}3.26$ minutes, respectively, indicating a shorter time to achieve the goal heart rate in FM patients (P < 0.003). Most FM patients attained 70% HRMax at lower stages (stage 2 and 3) of M.Bruce compared to the control group (70% versus 6.6%, respectively; P < 0.0001). Compared to healthy subjects, FM patients had lower serum ${\beta}$-END levels both in baseline and post-exercise status ($Mean{\pm}SD$: $122.07{\pm}28.56{\mu}g/ml$ and $246.55{\pm}29.57{\mu}g/ml$ in the control group versus $90.12{\pm}20.91{\mu}g/ml$ and $179.80{\pm}28.57{\mu}g/ml$ in FM patients, respectively; P < 0.001). Conclusions: We found that FM patients had lower levels of ${\beta}$-END in both basal and post-exercise status. Exercise increased serum the ${\beta}$-END level in both groups but the average increase in ${\beta}$-END in FM patients was significantly lower than in the control group.

• Korean Journal of Optics and Photonics
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• v.29 no.4
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• pp.166-172
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• 2018

In this paper, we propose a new method to predict a mirror's surface deformation due to the stress of moisture release by a coating in the environment of outer space. We measured the surface deformation of circular samples 50 mm in diameter and 1.03 mm thick, using an interferometer. The results were analyzed using Zernike fringe polynomials. The coating stress caused by moisture release was calculated to be 152.7 MPa. This value was applied to an analytic model of a 1.25 mm thickness sample mirror, confirming that the change of surface deformation could be predicted within the standard deviation of the measurement result ($78.9{\pm}5.9nm$). Using this methodology, we predicted the surface deformation of 600 mm hyperbolic mirror for the Compact Advanced Satellite, which will be launched in 2019. The result is only $2.005{\mu}m$ of focal shift, leading to 2.3% degradation of modulation transfer function (MTF) at the Nyquist frequency, which satisfies the requirement.