• The Journal of Korea Robotics Society
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• 제19권1호
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• pp.16-22
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• 2024

Robotic grasping in unstructured environments poses a significant challenge, demanding precise estimation of gripping positions for diverse and unknown objects. Generative Grasping Convolution Neural Network (GG-CNN) can estimate the position and direction that can be gripped by a robot gripper for an unknown object based on a three-dimensional depth map. Since GG-CNN uses only a depth map as an input, the precision of the depth map is the most critical factor affecting the result. To address the challenge of depth map precision, we integrate the Segment Anything Model renowned for its robust zero-shot performance across various segmentation tasks. We adjust the components corresponding to the segmented areas in the depth map aligned through external calibration. The proposed method was validated on the Cornell dataset and SurgicalKit dataset. Quantitative analysis compared to existing methods showed a 49.8% improvement with the dataset including surgical instruments. The results highlight the practical importance of our approach, especially in scenarios involving thin and metallic objects.

• Journal of Trauma and Injury
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• 제18권2호
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• pp.141-147
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• 2005

Purpose: Recently, The new Injury Severity Score (NISS) has become a more accurate predictor of mortality than the traditional Injury Severity Score (ISS) in the trauma population. Trauma Score Injury Severity Score (TRISS) method, regarded as the gold standard for mortality prediction in trauma patients, still contains the ISS as an essential factor within its formula. The purpose of this study was to determine whether a simple modification of the TRISS by replacing the ISS with the NISS would improve the prediction of in-hospital mortality in a trauma population with blunt head and neck trauma. Objects and Methods: The study population consisted of 641 patients from a regional emergency medical center in Kyoungsangnam-do. Demographic data, clinical information, the final diagnosis, and the outcome for each patient were collected in a retrospective manner. the ISS, NISS, TRISS, and modified TRISS were calculated for each patients. The discrimination and the calibration of the ISS, NISS, modified TRISS and conventional TRISS models were compared using receiver operator characteristic (ROC) curves, areas under the ROC curve (AUC) and Hosmer-Lemeshow statistics. Results: The AUC of the ISS, NISS, modified TRISS, and conventional TRISS were 0.885, 0.941, 0.971, and 0.918 respectively. Statistical differences were found between the ISS and the NISS (p=0.008) and between the modified TRISS and the conventional TRISS (p=0.009). Hosmer-Lemeshow chi square values were 13.2, 2.3, 50.1, and 13.8, respectively; only the conventional TRISS failed to achieve the level of and an excellent calibration model (p<0.001). Conclusion: The modified TRISS is a more accurate predictor of in-hospital mortality than the conventional TRISS in a trauma population of blunt head and neck trauma.

• Journal of Wetlands Research
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• 제13권3호
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• pp.471-479
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• 2011

Evapotranspiration (ET) including evaporation from a land surface and transpiration from photosynthesis of vegetation is a hydrological factor that has an important role in water cycle. However, there is a limitation to understand it due to heterogeneity of land cover and vegetation. In this study, Mapping EvapoTRanspiration with Internalized Calibration (METRIC) model, one of the energy balance models, and MODerate resolution Imaging Spectroradiometer (MODIS) satellite based well-known Penman-Monteith algorithm were compared. Two ET maps were categorized and compared by land cover classification. The results represented overall applicability of the two models with the highest correlation coefficients in needleleaf and broadleaf forests. This study will be useful to estimate remote sensing based ET maps with high resolution and to figure out spatio-temporal variability and seasonal changes.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1248-1248
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• 2001

Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and considerable compositional changes in milk, reducing milk quality. The potential of near infrared (NIR) spectroscopy in the region from 1100 to 2500nm and chemometric method for classification to detect milk from mastitic cows was investigated. A total of 189 milk samples from 7 Holstein cows were collected for 27 days, consecutively, and analyzed for somatic cells (SCC). Three of the cows were healthy, and the rest had mastitis periods during the experiment. NIR transflectance milk spectra were obtained by the InfraAlyzer 500 spectrophotometer in the spectral range from 1100 to 2500nm. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. The classification of the samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two concentration of SCC - 200 000 cells/ml and 300 000 cells/ml, respectively, were used as thresholds fer separation of healthy and mastitis cows. The best detection accuracy was found for models, obtained using 200 000 cells/ml as threshold and smoothed absorbance data - 98.41% from samples in the calibration set and 87.30% from the samples in the independent test set were correctly classified. SIMCA results for classes, based on 300 000 cells/ml threshold, showed a little lower accuracy of classification. The analysis of changes in the loading of first PC factor for group of healthy milk and group of mastitic milk showed, that separation between classes was indirect and based on influence of mastitis on the milk components. The accuracy of mastitis detection by SIMCA method, based on NIR spectra of milk would allow health screening of cows and differentiation between healthy and mastitic milk samples. Having SIMCA models, mastitis detection would be possible by using only DIR spectra of milk, without any other analyses.

• Journal of Korean Society on Water Environment
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• 제25권1호
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• pp.7-17
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• 2009

Soil and Water Assessment Tool (SWAT) was used to assess the impact of potential future climate change on the water cycle and soil loss of the Daecheong reservoir watershed. A sensitivity analysis using influence coefficient method was conducted for two selected hydrological input parameters and three selected sediment input parameters to identify the most to the least sensitive parameters. A further detailed sensitivity analysis was performed for the parameters: Manning coefficient for channel (Cn), evaporation (ESCO), and sediment concentration in lateral (LAT_SED), support practice factor (USLA_P). Calibration and verification of SWAT were performed on monthly basis for 1993~2006 and 1977~1991, respectively. The model efficiency index (EI) and coefficient of determination ($R^2$) computed for the monthly comparisons of runoffs were 0.78 and 0.76 for the calibration period, and 0.58 and 0.65 for the verification period. The results showed that the hydrological cycle in the watershed is very sensitive to climate factors. A doubling of atmospheric $CO_2$ concentrations was predicted to result in an average annual flow increase of 27.9% and annual sediment yield increase of 23.3%. Essentially linear impacts were predicted between two precipitation change scenarios of -20, and 20%, which resulted in average annual flow and sediment yield changes at Okcheon of -53.8%, 63.0% and -55.3%, 65.8%, respectively. An average annual flow increase of 46.3% and annual sediment yield increase of 36.4% was estimated for a constant humidity increase 5%. An average annual flow decrease of 9.6% and annual sediment yield increase of 216.4% was estimated for a constant temperature increase $4^{\circ}C$.

• Proceedings of the Korean Geotechical Society Conference
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• 한국지반공학회 2008년도 춘계 학술발표회 초청강연 및 논문집
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• pp.1431-1437
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• 2008

The small-strain shear modulus ($G_{max}$) of uncemented sand is affected by the the mean principal stress and void ratio, and it has been known that the cementation and aging also affect to $G_{max}$ of sand. For extensive understanding about the effect of cementation on the $G_{max}$ of sand, a series of bender element tests was conducted on the cemented specimens prepared in a large calibration chamber by pluviation of the sand-gypsum mixture. It was observed from the experimental results that the $G_{max}$ of cemented sand is higher above 10 times than value of uncemented one, and it increases exponentially with the gypsum content increases. Whereas, the increase of the vertical stress from 50kPa to 200kPa and the relative density from 40% to 80% result in 20~30% and 2 times increase of $G_{max}$, respectively. It means that the gypsum content, that is cementation level, is the most influential factor on the $G_{max}$ of cemented sand. In addition, the effect of relative density on $G_{max}$ was more apparent on cemented sand than uncemented one.

• The Korean Journal of Applied Statistics
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• 제33권5호
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• pp.555-567
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• 2020

Hypertension has a steadily increasing incidence rate as well as represents a risk factors for secondary diseases such as cardiovascular disease. Therefore, it is important to predict the incidence rate of the disease. In this study, we constructed nomograms that can predict the incidence rate of hypertension. We use data from the Korean National Health and Nutrition Examination Survey (KNHANES) for 2013-2016. The complex sampling data required the use of a Rao-Scott chi-squared test to identify 10 risk factors for hypertension. Smoking and exercise variables were not statistically significant in the Logistic regression; therefore, eight effects were selected as risk factors for hypertension. Logistic and Bayesian nomograms constructed from the selected risk factors were proposed and compared. The constructed nomograms were then verified using a receiver operating characteristics curve and calibration plot.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• 제24권1호
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• pp.47-54
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• 2013

This paper introduces a W-band millimeter-wave power standard transfer system using the direct comparison method. The transfer system was developed to evaluate the effective efficiency and calibration factor of a W-band waveguide power sensor. The evaluation method and the measured results of the directional coupler that characterizes the calibration system are studied. The uncertainties of the standard transfer system are investigated, and the major uncertainty contributors are discussed as well. The performance of the realized W-band power standard transfer system was verified by comparing results with reference values.

• Journal of Periodontal and Implant Science
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• 제47권1호
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• pp.13-19
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• 2017

Purpose: The purpose of this study was to examine whether periodontal pocket could be satisfactorily visualized by optical coherence tomography (OCT) and to suggest quantitative methods for measuring periodontal pocket depth. Methods: We acquired OCT images of periodontal pockets in a porcine model and determined the actual axial resolution for measuring the exact periodontal pocket depth using a calibration method. Quantitative measurements of periodontal pockets were performed by real axial resolution and compared with the results from manual periodontal probing. Results: The average periodontal pocket depth measured by OCT was $3.10{\pm}0.15mm$, $4.11{\pm}0.17mm$, $5.09{\pm}0.17mm$, and $6.05{\pm}0.21mm$ for each periodontal pocket model, respectively. These values were similar to those obtained by manual periodontal probing. Conclusions: OCT was able to visualize periodontal pockets and show attachment loss. By calculating the calibration factor to determine the accurate axial resolution, quantitative standards for measuring periodontal pocket depth can be established regardless of the position of periodontal pocket in the OCT image.

• Journal of the Computational Structural Engineering Institute of Korea
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• 제24권4호
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• pp.383-389
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• 2011

In this paper, a statistical calibration method is proposed in order to identify the variability of complex modulus for a rubber material due to operational temperature and experimental/model errors. To describe temperature- and frequency-dependent material properties, a fractional derivative model and a shift factor relationship are used. A likelihood function is defined as a product of the probability density functions where experimental values lie on the model. The variation of the fractional derivative model parameters is obtained by maximizing the likelihood function. Using the proposed method, the variability of a synthetic rubber material is estimated and applied to a rubber mount problem. The dynamic characteristics of the rubber mount are calculated using a finite element model of which material properties are sampled from Monte Carlo simulation. The calculated dynamic stiffnesses show very large variation.