• Journal of dental hygiene science
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• v.15 no.1
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• pp.54-59
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• 2015

The present study investigated the influences of various abutment teeth shapes (maxillary right canine, pre-molar, molar) on the marginal adaptation of computer aided design/computer aided manufacturing-fabricated zirconia core. In vitro adaptation of zirconia cores manufactured by three different abutments were evaluated. Thirty zirconia cores were made per each models and the adaptation was evaluated through a silicone replica technique. The measurement of the adaptation was carried out using digital microscope. The mean and standard deviation of each reference point were analyzed using the one-way (ANOVA) and Tukey's honestly significant difference tests (${\alpha}=0.05$). The overall marginal fits of the zirconia cores were as follows: canine: $47.59{\mu}m$, pre-molar: $43.74{\mu}m$, molar: $40.36{\mu}m$. They were no statistically significant differences between groups for adaptation (p>0.05). This confirmed that the type of abutment teeth used does not determine the precision of fit of zirconia core.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.587-597
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• 2010

When a car accident occurs, people who had an accident are not free from civil and criminal issues so that the accident investigator should reenact and analyze the accident situation accurately. In addition, the obtained documents through the analysis of such car accident occurrence and related factors have to be used to carry out the improvement of the areas that has numerous car accidents and complementary actions. The vehicle speed, accelerating force, braking power are currently known as the most affecting factors in accordance with many car accidents, traffic facilities, road design, etc. The vehicle's performance and rode friction coefficient road surface friction coefficient are affecting the most closely in this field. Especially, once the estimate of the speed of the accident moment relating to main eleven articles of Traffic Accident Exemption Law is very important and accuracy is required. However, currently the researches of these matters have not made exclusively yet in Korea. In this study by reflecting this current situation, until the sudden braking history is found from the car's sudden braking, it estimates accurately the transient brake time and rode friction coefficient by measuring a time of transient brake time through the precision speed detector (Vericom VC2000PC). The analysis of the experimental results calculated the transient brake time and friction coefficient to fit into the purpose of this study in the basis of different kind of various special purpose asphalt pavement and slip-prevention pavement and provided the fundamental data.

• Journal of Ecology and Environment
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• v.48 no.2
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• pp.196-206
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• 2024

Background: Most of the biomass equations were developed using sample trees collected mainly from pan-tropical and tropical regions that may over- or underestimate biomass. Site-specific models would improve the accuracy of the biomass estimates and enhance the country's measurement, reporting, and verification activities. The aim of the study is to develop site-specific biomass estimation models and validate and evaluate the existing generic models developed for pan-tropical forest and newly developed allometric models. Total of 140 trees was harvested from each diameter class biomass model development. Data was analyzed using SAS procedures. All relevant statistical tests (normality, multicollinearity, and heteroscedasticity) were performed. Data was transformed to logarithmic functions and multiple linear regression techniques were used to develop model to estimate aboveground biomass (AGB). The root mean square error (RMSE) was used for measuring model bias, precision, and accuracy. The coefficient of determination (R² and adjusted [adj]-R²), the Akaike Information Criterion (AIC) and the Schwarz Bayesian information Criterion was employed to select most appropriate models. Results: For the general total AGB models, adj-R² ranged from 0.71 to 0.85, and model 9 with diameter at stump height at 10 cm (DSH₁₀), ρ and crown width (CW) as predictor variables, performed best according to RMSE and AIC. For the merchantable stem models, adj-R² varied from 0.73 to 0.82, and model 8) with combination of ρ, diameter at breast height and height (H), CW and DSH₁₀ as predictor variables, was best in terms of RMSE and AIC. The results showed that a best-fit model for above-ground biomass of tree components was developed. AGB_Stem = exp {-1.8296 + 0.4814 natural logarithm (Ln) (ρD²H) + 0.1751 Ln (CW) + 0.4059 Ln (DSH₃₀)} AGB_Branch = exp {-131.6 + 15.0013 Ln (ρD²H) + 13.176 Ln (CW) + 21.8506 Ln (DSH₃₀)} AGB_Foliage = exp {-0.9496 + 0.5282 Ln (DSH₃₀) + 2.3492 Ln (ρ) + 0.4286 Ln (CW)} AGB_Total = exp {-1.8245 + 1.4358 Ln (DSH₃₀) + 1.9921 Ln (ρ) + 0.6154 Ln (CW)} Conclusions: The results demonstrated that the development of local models derived from an appropriate sample of representative species can greatly improve the estimation of total AGB.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.1
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• pp.85-91
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• 2011

RV-GIUH must be applied at an outlet or a junction of highest order stream of a subbasin because the model was derived for basins following Horton's ordering system. However hydrograph is calculated at various locations which does not fit to the desirable points. Therefore, some guideline is required for RV-GIUH application in practice. This study would like to suggest the outlet location criteria for appling RV-GIUH at un-gauged basin. Locations were selected by moving to upstream from outlet of Sanganmi basin and unit hydrograph using derived and simple RV-GIUH were estimated at each location. As the results, the peaks of RV-GIUH in upstream were exaggerated because of distortion of length ratio and total stream length. To avoid this error, the location must be selected at 60% downstream of highest stream length. To apply RV-GIUH at various places, equations correcting distortion of total stream length were suggested. With the correcting equations, it can be possible that RV-GIUH is applied at 20% downstream of highest stream length. Application and precision of RV-GIUH will be improved through this research.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.677-692
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• 2018

The total fertility rate of Korea was 1.05 in 2017, showing a return to the 1.08 level in the year 2005. 1.05 is a very low fertility level that is far from replacement level fertility or safety zone 1.5. The number may indicate a low fertility trap. It is therefore important to predict fertility than at any other time. In the meantime, we have predicted the age-specific fertility rate and total fertility rate by various statistical methods. When the data trend is disconnected or fluctuating, it applied a nonparametric method applying the smoothness and weight. In addition, the Bayesian method of using the pre-distribution of fertility rates in advanced countries with reference to the three-stage transition phenomenon have been applied. This paper examines which method is reasonable in terms of precision and feasibility by applying estimation, forecasting, and comparing the results of the recent variability of the Korean fertility rate with parametric, non-parametric and Bayesian methods. The results of the analysis showed that the total fertility rate was in the order of KOSTAT's total fertility rate, Bayesian, parametric and non-parametric method outcomes. Given the level of TFR 1.05 in 2017, the predicted total fertility rate derived from the parametric and nonparametric models is most reasonable. In addition, if a fertility rate data is highly complete and a quality is good, the parametric model approach is superior to other methods in terms of parameter estimation, calculation efficiency and goodness-of-fit.

• Journal of the Korean Society for Railway
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• v.18 no.3
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• pp.261-269
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• 2015

To overcome the weaknesses of viaduct bridges and the non-economic efficiency of underground LRT, the study of near-surface railway systems is in progress. To apply a box structure to the low depth transit, a connection joint to precast modules are very important when applying precast modular structures to replace temporary structures. In this study, wall to wall connections were applied in diverse cases such as rebar connections, guiding structures that were used to fit the verticality of precast walls during construction, and non-reinforcement structures used only for waterstop. Experimental performance verification was carried out for the bending, shear and splitting of the wall to wall connection. Precision of construction joints between wall to wall was identified as a factor that influenced the structural performance of the precast wall. A structure that can serve as a guide during the vertical insertion of a wall is confirmed for the most suitable case, but it will be necessary to modify this structure for detailed cases.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.543-559
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• 2019

Data often include missing values due to various reasons. If the missing data mechanism is not MCAR, analysis based on fully observed cases may an estimation cause bias and decrease the precision of the estimate since partially observed cases are excluded. Especially when data include many variables, missing values cause more serious problems. Many imputation techniques are suggested to overcome this difficulty. However, imputation methods using parametric models may not fit well with real data which do not satisfy model assumptions. In this study, we review imputation methods using nonlinear models such as kernel, resampling, and spline methods which are robust on model assumptions. In addition, we suggest utilizing imputation classes to improve imputation accuracy or adding random errors to correctly estimate the variance of the estimates in nonlinear imputation models. Performances of imputation methods using nonlinear models are compared under various simulated data settings. Simulation results indicate that the performances of imputation methods are different as data settings change. However, imputation based on the kernel regression or the penalized spline performs better in most situations. Utilizing imputation classes or adding random errors improves the performance of imputation methods using nonlinear models.

• Tunnel and Underground Space
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• v.31 no.5
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• pp.374-384
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• 2021

In this study, we propose a new approach for automatic fracture detection in CT scan images of rock specimens. This approach is built on top of two-stage object detection deep learning algorithm called Faster R-CNN with a major modification of using rotated bounding box. The use of rotated bounding box plays a key role in the future work to overcome several inherent difficulties of fracture segmentation relating to the heterogeneity of uninterested background (i.e., minerals) and the variation in size and shape of fracture. Comparing to the commonly used bounding box (i.e., axis-align bounding box), rotated bounding box shows a greater adaptability to fit with the elongated shape of fracture, such that minimizing the ratio of background within the bounding box. Besides, an additional benefit of rotated bounding box is that it can provide relative information on the orientation and length of fracture without the further segmentation and measurement step. To validate the applicability of the proposed approach, we train and test our approach with a number of CT image sets of fractured granite specimens with highly heterogeneous background and other rocks such as sandstone and shale. The result demonstrates that our approach can lead to the encouraging results on fracture detection with the mean average precision (mAP) up to 0.89 and also outperform the conventional approach in terms of background-to-object ratio within the bounding box.

• Journal of Animal Environmental Science
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• v.18 no.sup
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• pp.81-90
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• 2012

This study was evaluated high end research grade Near infrared spectrophotometer (NIRS) to low end popular field grade multiple Near infrared spectrophotometer (NIRS) for rapid analysis at forage quality at sight with 241 samples of Italian ryegrass silage during 3 years collected whole country for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with Unity Scientific Model 2500X (650 nm~2,500 nm) then trim and fit to low end popular field grade NIRS with Unity Scientific Model 1400 (1,400 nm~2,400 nm) then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.000%~0.343% differences, rapidly analysis for chemical constituents, NDF, ADF, and crude protein, crude ash and fermentation parameter such as moisture, pH and lactic acid, finally forage quality parameter, TDN, DMI, RFV within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless during 3 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of forage analysis with NIRS at sight. Especially the agriculture products such as forage will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods Global Distance (GD) and Neighbour Distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple popular field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.58 no.3
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• pp.301-307
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• 2013

This study was evaluated high end research grade Near Infrared Reflectance Spectrophotometer (NIRS) to field grade multiple Near Infrared Reflectance Spectrophotometer (NIRS) for rapid analysis at fresh rice leaf at sight with 238 samples of fresh rice leaf during year 2012, collected Jeollabuk-do for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with 400 nm ~ 2500 nm during from year 2003 to year 2009, seven years collected fresh rice leaf database then trim and fit to field grade NIRS with 1200 nm ~ 2400 nm then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.005% differences, rapidly analysis for chemical constituents, Total nitrogen in fresh rice leaf within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless last during more than 8 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of fresh rice leaf analysis with NIRS at sight. Especially the agriculture products such as rice will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods global distance (GD) and neighbour distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.