• Journal of the korean academy of Pediatric Dentistry
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• v.28 no.3
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• pp.464-470
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• 2001

The purpose of this study was to evaluate the tensile strength of light-cured restorative posterior resin-based composites. Five commercially available light-cured composites(Denfil : DF, P60 : PS, Unifil S : US, Z100 : ZH, Z250 : ZT) were used. Rectangular tension test specimens were fabricated in a teflon mold giving 5mm in gauge length and 2mm in thickness. Specimens were subjected to the 5,000 thermal cycles between $5^{\circ}C$ and $55^{\circ}C$ and the immersion time in each bath was 15 second per cycle. Tensile testing was carried out with Instron at a crosshead speed of 0.5mm/min and fractured surface were observed with scanning electron microscope. The obtained results were summarized as follows; 1. The tensile strength of PS was highest. PS was significantly higher than DF, US and ZH(p<0.05) but in the case of ZT was similar to PS(p>0.05). 2. The tensile strength DF was lowest. DF was significantly lower than PS, US, ZH and ZT(p<0.05). 3. The tensile strength of US and ZH were significantly lower than PS and ZT(p<0.05). but were significantly higher than DF(p<0.05). The tensile strength of US and ZH were similar(p>0.05).

• Progress in Medical Physics
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• v.21 no.4
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• pp.332-339
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• 2010

We aimed to setup an adaptive radiation therapy platform using cone-beam CT (CBCT) and multileaf collimator (MLC) log data and also intended to analyze a trend of dose calculation errors during the procedure based on a phantom study. We took CT and CBCT images of Catphan-600 (The Phantom Laboratory, USA) phantom, and made a simple step-and-shoot intensity-modulated radiation therapy (IMRT) plan based on the CT. Original plan doses were recalculated based on the CT ($CT_{plan}$) and the CBCT ($CBCT_{plan}$). Delivered monitor unit weights and leaves-positions during beam delivery for each MLC segment were extracted from the MLC log data then we reconstructed delivered doses based on the CT ($CT_{recon}$) and CBCT ($CBCT_{recon}$) respectively using the extracted information. Dose calculation errors were evaluated by two-dimensional dose discrepancies ($CT_{plan}$ was the benchmark), gamma index and dose-volume histograms (DVHs). From the dose differences and DVHs, it was estimated that the delivered dose was slightly greater than the planned dose; however, it was insignificant. Gamma index result showed that dose calculation error on CBCT using planned or reconstructed data were relatively greater than CT based calculation. In addition, there were significant discrepancies on the edge of each beam while those were less than errors due to inconsistency of CT and CBCT. $CBCT_{recon}$ showed coupled effects of above two kinds of errors; however, total error was decreased even though overall uncertainty for the evaluation of delivered dose on the CBCT was increased. Therefore, it is necessary to evaluate dose calculation errors separately as a setup error, dose calculation error due to CBCT image quality and reconstructed dose error which is actually what we want to know.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.449-459
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• 2015

The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.

• Journal of Chest Surgery
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• v.29 no.5
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• pp.542-547
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• 1996

All patients who underwent video-assisted thoracic surgery (VATS) for diagnostic purposes from Jan. 1992 to Aug. 1995 were reviewed. The total number of patients were 111 with 57 male and 54 female, and the mean age was 49 years (range 1 to 74). Multiple biopsies from more than one location were performed in 17 patients , pleural biopsies were performed In 49 patients, lung biopsies in 43 patients, mediastinal mass or Iymph node biopsies in 33 patients, and two pericardium biopsies and one dia- phragm biopsy, for a total of 128 biopsies. Seventeen pleural biopsy cases and one lung biopsy case underwent operation under local anesthesia , the rest were performed under general anesthesia. In patients who underwent lung biopsy, the mean age was 49.1 ye rs (range 22~ 73). The operating time was 40 to 170 minutes (mean 97), intravenous or intramuscular injection for pain control was required 0 to 22 times(mean 4.7), and chest tube was inserted from 1 to 26 days(mean 7). In all patients except two, a diagnosis was obtained from the biopsy and complication was encountered in one patient in whom intraoperative paroxysmal atrial tachycardia was detected. In 7 patients, a thorn- cotomy had to be done due to pleural adhesion or intraoperative bleeding, and 7 patients had postoperative complications associated with the chest tube. In the pleural biopsy group, the mean age was 49 years (range 17~ 74). The operating time was 25 to 80 minutes (mean 49), intravenous or intramuscular injection for pain control was needed 0 to 20 times (mean 3.6), and the chest tube was i.nserted for 0 to 67 days(mean 9.8). In all the patients, a diagnosis was possible. The chest tube was inserted for longer than 7 days in 11 patients. In the Iymph node biopsy roup, the mean age was 44.2 years (range 1 ~ 68). The operating time was )0 to 3)5 minutes(mean 105), pain control was required 0 to 15 times(mean 3.2), and a chest tube was kept in place for 1 to 36 days(mean 6.1). In one patient, a diagnosis was not possible and a chest tube was kept in place for longer than 7 days in 7 patients. In the multiple biopsy group, the mean age was 53.1 years(range 20~ 71). The operating time was 15 to 165 minutes(mean 85), and pain control was done from 0 to 17 times(mean 3.1). The chest tube was kept in place for 1 to 16 days (mean 7.9).

• Korean Journal of Ecology and Environment
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• v.46 no.1
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• pp.33-40
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• 2013

From March 2012 to January 2013, this study was conducted as a part of the project for making a precise electronic ecological zoning map of vegetation on a highly reduced scale of 1 to 5,000 with a view to improving management efficiency of national parks and enlarging the availability of the data produced from the basic research monitoring the resources of national parks. For the research accuracy and rapidity, a vegetation map was specially created for the on-the-site-vegetation research. To make the map more meticulous, we categorized the vegetation database into five groups: broadleaved forest, coniferous forest, mixed forest, rock vegetation and miscellaneous one. After comparing the results of the data built for the vegetation research and the actual research findings, it was made clear that vegetation of both categories was almost the same in case of broad-leaved forest with 72.20% and 78.45% respectively, and also equivalent in other groups like, for example, coniferous forest (16.70%, 13.41%), mixed forest (9.50%, 7.49%) and rock vegetation (0.60%, 0.15%). According to the precise vegetation map produced from the research, the deciduous broad-leaved forest was the most widely prevalent type in the correlated hierarchical classification of vegetation, occupying 65.78% of the overall vegetation. It was followed by mountain valley forest (15.17%), coniferous forest (10.90%), and plantation forest (7.00%) in order. It is particularly noteworthy that Mt. Deogyusan national park has retained a very stable and versatile forest vegetation in the outstanding state since approximately 20% of the mountain turns out to belong to the I grade vegetation conservation classification which contains climax forests, unique vegetation, subalpine vegetation, matured stands which are older than 50 years and etc.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.281-286
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• 2003

A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.665-679
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• 2019

Mesoscale soil moisture measurement from the promising Cosmic-Ray Neutron Probe (CRNP) is expected to bridge the gap between large scale microwave remote sensing and point-based in-situ soil moisture observations. Traditional calibration based on $N_0$ method is used to convert neutron intensity measured at the CRNP to field scale soil moisture. However, the static calibration parameter $N_0$ used in traditional technique is insufficient to quantify long term soil moisture variation and easily influenced by different time-variant factors, contributing to the high uncertainties in CRNP soil moisture product. Consequently, in this study, we proposed a modified traditional calibration method, so-called Dynamic-$N_0$ method, which take into account the temporal variation of $N_0$ to improve the CRNP based soil moisture estimation. In particular, a nonlinear regression method has been developed to directly estimate the time series of $N_0$ data from the corrected neutron intensity. The $N_0$ time series were then reapplied to generate the soil moisture. We evaluated the performance of Dynamic-$N_0$ method for soil moisture estimation compared with the traditional one by using a weighted in-situ soil moisture product. The results indicated that Dynamic-$N_0$ method outperformed the traditional calibration technique, where correlation coefficient increased from 0.70 to 0.72 and RMSE and bias reduced from 0.036 to 0.026 and -0.006 to $-0.001m^3m^{-3}$. Superior performance of the Dynamic-$N_0$ calibration method revealed that the temporal variability of $N_0$ was caused by hydrogen pools surrounding the CRNP. Although several uncertainty sources contributed to the variation of $N_0$ were not fully identified, this proposed calibration method gave a new insight to improve field scale soil moisture estimation from the CRNP.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.5
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• pp.61-78
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• 2019

This study is about the effect of the founder's self-efficacy on the sales of the founding company by focusing on the factors that are currently emphasized in the founding education. In particular, this paper starts from the consciousness of the problem that the education that is being implemented to achieve the purpose of successful start-up among various government-based start-up support projects is failing to produce many start-up failures. Entrepreneurs cannot be assessed by objective financial data, but there is a high degree of uncertainty that should be determined based on their personal and learning abilities. In addition, many previous studies, which are likely to be successful when there is a high self-efficacy in a specific field due to the influence of factors such as personal experience or learning, will answer the direction of support for start-up companies. This study focuses on the impact of the founder's self-efficacy on the sales of the founding firms, especially the sales that are the key to the survival of the founding firms. This study has six major studies. First, to analyze whether the self-efficacy of entrepreneurs with respect to entrepreneurship affects the sales of entrepreneurs. Second, to analyze whether the self-efficacy of entrepreneurs with respect to market orientation affects the sales of entrepreneurs. Analysis of whether the founder's self-efficacy affects the sales of the founding firms. Fourth, analysis of whether the founder's self-efficiency affects the sales of the founding firms' understanding of management environment changes. An analysis of whether efficacy affects the sales of a start-up company, and sixth, an analysis of whether the founder's self-efficacy of business model building ability affects the sales of a start-up company. As a result of the empirical analysis, this study found that the self-efficacy of entrepreneurs on product differentiation capability and business model building capacity had a positive influence on the sales of entrepreneurs. The self-efficacy had a positive effect on self-efficacy, and the customer orientation had a positive effect on self-efficacy on business model building capacity. Also, it was confirmed that a path exists between the components of self-efficacy and that self-efficacy through the path has a positive effect on the sales of the start-up company. Therefore, the results of this study suggest the implications of establishing such a path and strengthening self-efficacy to create the survival and start-up performance of a start-up company if the goal of the start-up company is to survive when implementing various support projects for the start-up company.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1243-1254
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• 2021

For water resources operation or agricultural water management, it is important to accurately predict evapotranspiration for a long-term future over a seasonal or monthly basis. In this study, reference evapotranspiration forecast (up to 12 months in advance) was performed using statistically predicted monthly temperatures and temperature-based Hamon method for the Han River basin. First, the daily maximum and minimum temperature data for 15 meterological stations in the basin were derived by spatial-temporal downscaling the monthly temperature forecasts. The results of goodness-of-fit test for the downscaled temperature data at each site showed that the percent bias (PBIAS) ranged from 1.3 to 6.9%, the ratio of the root mean square error to the standard deviation of the observations (RSR) ranged from 0.22 to 0.27, the Nash-Sutcliffe efficiency (NSE) ranged from 0.93 to 0.95, and the Pearson correlation coefficient (r) ranged from 0.97 to 0.98 for the monthly average daily maximum temperature. And for the monthly average daily minimum temperature, PBIAS was 7.8 to 44.7%, RSR was 0.21 to 0.25, NSE was 0.94 to 0.96, and r was 0.98 to 0.99. The difference by site was not large, and the downscaled results were similar to the observations. In the results of comparing the forecasted reference evapotranspiration calculated using the downscaled data with the observed values for the entire region, PBIAS was 2.2 to 5.4%, RSR was 0.21 to 0.28, NSE was 0.92 to 0.96, and r was 0.96 to 0.98, indicating a very high fit. Due to the characteristics of the statistical models and uncertainty in the downscaling process, the predicted reference evapotranspiration may slightly deviate from the observed value in some periods when temperatures completely different from the past are observed. However, considering that it is a forecast result for the future period, it will be sufficiently useful as information for the evaluation or operation of water resources in the future.

• Journal of the Korean Orthopaedic Association
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• v.53 no.6
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• pp.505-512
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• 2018

Purpose: Many reconstruction methods have been attempted after an en-bloc resection of the proximal humerus. In particular, the introduction of reverse shoulder arthroplasty (RSA) has made a breakthrough in the functional recovery of the shoulder. Nevertheless, RSA has limitations when the humeral bone stock loss is significant. In addition, it is unclear if RSA is effective in patients showing failure with non-operative treatment of a proximal humeral tumor. Materials and Methods: A reconstruction was performed using an overlapping allograft-RSA composite for 11 patients with a failed proximal humeral construct. Delayed RSA was performed on 6 patients with failed non-operative treatment. The pre- and postoperative Musculoskeletal Tumor Society (MSTS) score and the complications were addressed. Results: Overlapping allograft-RSA composite afforded a stable construct in 11 failed proximal humeral reconstructions and the patient's chief complaints were resolved. The mean time to the union of overlapped allograft-host junction was 5.5 months. Average preoperative MSTS score of 20.3 point increased to 25.7 point, postoperatively. Four of the six patients who had RSA within 4 years from the index operation showed arm elevation of more than $90^{\circ}$ whereas the remaining 5 patients showed some disability. The complications include one case each of dislocation and aseptic infection, which were resolved by changing the polyethylene liner and scar revision, respectively. None of the 6 patients who underwent delayed RSA after the failure of non-operative treatment showed arm elevation more than $90^{\circ}$. Conclusion: An overlapping allograft-RSA composite is a simple and reliable reconstructive modality in patients with massive bone loss. In patients with metastatic cancer necessitating a surgical resection at presentation, early conversion to RSA is recommended to secure functional recovery.