• Radiation Oncology Journal
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• v.20 no.2
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• pp.186-192
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• 2002

Purpose : Measurement of transmission dose is useful for in vivo dosimetry. In this study, previous algorithm for estimation of transmission dose was modified for use in cases with tissue deficit. Materials and Methods : The beam data was measured with flat solid phantom in various conditions of tissue deficit. New algorithm for correction of transmission dose for tissue deficit was developed by physical reasoning. The algorithm was tested in experimental settings with irregular contours mimicking breast cancer patients using multiple sheets of solid phantoms. Results : The correction algorithm for tissue deficit could accurately reflect the effect of tissue deficit with errors within ${\pm}1.0\%$ in most situations and within ${\pm}3.0\%$ in experimental settings with irregular contours mimicking breast cancer treatment set-up. Conclusion : Developed algorithm could accurately reflect the effect of tissue deficit and irregularly shaped body contour on transmission dosimetry.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Korean Journal of Ecology and Environment
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• v.40 no.1
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• pp.14-30
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• 2007

The purpose of this study was to evaluate trophic conditions of various Korean reservoirs using Trophic State Index (TSI) and predict the reservoir conditions by empirical models. The water quality dataset (2000, 2001) used here were obtained from the Ministry of Environment, Korea. The water quality, based on multi-parameters of dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), total phosphorus (TP), total nitrogen (TN), suspended solid (SS), Secchi depth (SD), chlorophyll-${\alpha}$ (CHL), and conductivity largely varied depending on the sampling watersheds and seasons. In general, trophic conditions declined along the longitudinal axis of headwater-to-the dam and the largest seasonal variations occurred during the summer monsoon of July-August. Major inputs of TP occurred during the monsoon (r=0.656, p=0.002) and this pattern was similar to solid dynamics of SS (r=0.678, p<0.001). Trophic parameters including CHL, TP, SD, and TN were employed to evaluate how the water systems varies with season. Trophic State Index (TSI, Carlson, 1977), based on TSI (CHL), TSI (TP), and TSI (SD), ranged from mesotrophic to eutrophic. However, the trophic state, based on TSI (TN), indicated eutrophic-hypereutrophic conditions in the entire reservoirs, regardless of the seasons, indicating a N-rich system. Overall, nutrient data showed that phosphorus was a primary factor regulating the trophic state. The relationships between CHL (eutrophication index) vs. trophic parameters (TN, TP, and SD) were analysed to develop empirical models which can predict the trophic status. Regression analyses of log-transformed seasonal CHL against TP showed that the value of $R^2$ was 0.31 (p=0.017) in the premonsoon but was 0.69 (p<0.001) during the postmonsoon, indicating a greater algal response to the phosphorus during the postmonsoon. In contrast, SD had reverse relation with TP, CHL during all season. TN had weak relations with CHL during all seasons. Overall, data suggest that TP seems to be a good predictor for algal biomass, estimated by CHL, as shown in the empirical models.

• Journal of Food Hygiene and Safety
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• v.28 no.3
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• pp.217-221
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• 2013

This study developed predictive models for the kinetic behavior of Staphylococcus aureus on processed cheeses. Mozzarella slice cheese and cheddar slice cheese were inoculated with 0.1 ml of a S. aureus strain mixture (ATCC13565, ATCC14458, ATCC23235, ATCC27664, and NCCP10826). The inoculated samples were then stored at $4^{\circ}C$ (1440 h), $15^{\circ}C$ (288 h), $25^{\circ}C$ (72 h), and $30^{\circ}C$ (48 h), and the growth of all bacteria and of S. aureus were enumerated on tryptic soy agar and mannitol salt agar, respectively. The Baranyi model was fitted to the growth data of S. aureus to calculate growth rate (${\mu}_{max}$; ${\log}CFU{\cdot}g^{-1}{\cdot}h^{-1}$), lag phase duration (LPD; h), lower asymptote (log CFU/g), and upper asymptote (log CFU/g). The growth parameters were further analyzed using the square root model as a function of temperature. The model performance was validated with observed data, and the root mean square error (RMSE) was calculated. At $4^{\circ}C$, S. aureus cell growth was not observed on either processed cheese, but S. aureus growth on the mozzarella and cheddar cheeses was observed at $15^{\circ}C$, $25^{\circ}C$, and $30^{\circ}C$. The ${\mu}_{max}$ values increased, but LPD values decreased as storage temperature increased. In addition, the developed models showed acceptable performance (RMSE = 0.3500-0.5344). This result indicates that the developed kinetic model should be useful in describing the growth pattern of S. aureus in processed cheeses.

• Economic and Environmental Geology
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• v.44 no.2
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• pp.135-152
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• 2011

Nitrate concentrations in springs at the southern slope of Jeju Island were predicted using multiple linear regression (MLR) of spatial variables including hydrogeological parameters and land use characteristics. Springs showed wide range of nitrate concentrations from <0.02 to 86 mg/L with a mean of 20 mg/L. Spatial variables were generated for the circular buffer when the optimal buffer radius was assigned as 400 m. Selected regression models were tested using the p values and Durbin-Watson statistics. Explanatory variables were selected using the adjusted $R^2$, Cp (total squared error) and AIC (Akaike's Information Criterion), and significance. In addition, mutual linear relations between variables were also considered. Small portion of springs, usually <10% of total samples, were identified as outliers indicating limitations of MLR using circular buffers. Adjusted $R^2$ of the proposed models was improved from 0.75 to 0.87 when outliers were eliminated. In particular, the areal proportion of natural area had the greatest influence on the nitrate concentrations in springs. Among anthropogenic land uses, the influence of nitrate contamination is diminishing in the following order of orchard, residential area, and dry farmland. It is apparent quality of springs in the study area is likely to be controlled by land uses instead of hydrogeological parameters. Most of all, it is worth highlighting that the contamination susceptibility of springs is highly sensitive to nearby land uses, in particular, orchard.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.361-369
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• 2017

Hemodynamic information in the carotid artery bifurcation is very important for understanding the development and progression mechanisms of cerebrovascular disease and for its early diagnosis and prediction of the progress. In this paper, we constructed a mock pulsatile blood circulation system using an anthropomorphic elastic vessel of the carotid artery bifurcation and ex vivo pig blood to acquire ultrasound images from blood and vessels synchronized with internal pressure while controlling the blood flow. Echogenicity, blood flow velocity, and blood vessel wall motion from the ultrasound images, and internal blood pressure were extracted over a cycle averaged from five cycles when the pulsatile pump rates are 20 r/min, 40 r/min, and 60 r/min. As a result, respectively, the peak systolic blood flow velocities were 20 cm/s, 25 cm/s, and 40 cm/s, the blood pressure differences were 30 mmHg, 70 mmHg, and 85 mmHg, the arterial walls were expanded to 0.05 mm, 0.15 mm, and 0.25 mm. Time-delayed cyclic variation of echogenicity compared to blood flow and pressure was observed, but the variation was minimal at 20 r/min. Time-synchronized cyclic variations of these parameters are important information for accurate input parameters and validation of the computational hemodynamic experiments which will provide useful information for the development and progress mechanisms of carotid artery stenosis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.66-76
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• 2016

Determination of type of a vehicle is being used in various areas such as collecting tolls, collecting statistical traffic data and traffic prognosis. Because most of the vehicle type classification systems depend on vehicle length indirectly or directly, highly reliable automatic vehicle length measurement system is crucial for them. This study makes use of a pencil beam laser rangemeter and devises a mechanical device which rotates the laser rangemeter. The implemented system measures the range between a point and the laser rangemeter then indicates it as a spherical coordinate. We obtain several silhouettes of cross section of the vehicle, the rate of change of the silhouettes, signs of the rates then squares the rates to apply cell averaging constant false alarm rate (CA-CFAR) technique to find out where the border is between the vehicle and the background. Using the border and trigonometry, we calculated the length of the vehicle and confirmed that the calculated vehicle length is about 94% of actual length.

• Geotechnical Engineering
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• v.14 no.3
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• pp.73-94
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• 1998

In the present study, a method of the three-dimensional limit equilibrium stability analysis of shape of the potential failure wedge for the concave-shaped excavation corner is assumed on the basis of the results of the FLACSU program analysis. Estimation of the three-dimensional seepage forces expected to act on the failure wedge is made by solving the three-dimensional continuity equation of flow with appropriate boundary conditions. By using the proposed method of three-dimensional stability analysis of the concave-shaped excavation corner, a parametric study is performed to examine the reinforcement effect of skew soil nailing system, range of the efficient skew angles and seepage effect on the overall stability. Also examined is the effect of an existence of the right-angled excavation corner on three-dimensional deflection behaviors of the convex-shaped skew soil nailing walls. The results of analyses of the convexshaped excavation corner with skew soil nailing system is further included to illustrate the effects of various design parameters for typical patterns of skew nails reinforcement system.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2008.04a
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• pp.69-75
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• 2008

기포반응도는 월성발전소를 비롯한 CANDU형 원자로의 주된 안전성 쟁점사안으로 끊임없이 논의되어 왔다. 이는 설계기준사고가 노심에서 열에너지 불균형이 원인이 되어 기준이상의 핵연료 파손과 방사성물질 누출로 발전할 위험이 있는 사건들로 정의될 때, 사건 진행 과정에 기포반응도 증가는 조기에 운전중단을 실패할 경우 출력폭주로 이어지므로 사건의 결말이 중대사고로 전환될 위험이 크기 때문이다. 본 연구는 공개된 최신 핵자료인 ENDF/B-VII.0를 NJOY.99로 처리한 연속에너지 반응단면적 라이브러리를 구축하고 MCNP-4C에 접속하여 37봉 천연우라늄 핵연료다발의 표준노심격자에 대한 기포반응도를 시뮬레이션하여, 지금까지 각종문헌에 제시된 값들과 비교, 종합하므로 내제된 불확실성을 추정하는 내용이다. ENDF/B-VII.0 기반 MCNP-4C의 CANDU 노심격자 모델은 동일한 핵자료와 핵종농도를 사용한 WIMS-IAEA 모델과 비교할 때, 초기 노심의 임계도 오차 약 3.51mk가 연소 진행에 따라 $7.5\times10^{-4}mk$/MWD/teU의 비율로 감소하는 것으로 나타났다. 또한 MCNP-4C 예측기포반응도는 초기노심에서 기포율 50% 및 100%에 대해 각각 8.38 및 15.96mk, 평형노심에서 7.68 및 14.72mk로 계산된다. 이는 월성 2, 3, 4 FSAR의 초기노심 및 평형노심에서 100% 기포상태에 대한 값, 약15.0 및 10.6mk와 비교할 때, 초기노심은 약 1.0mk 평형노심은 약4, 1mk 보수적이지만, 다른 연구결과들과는 최대오차 ${\pm}1{\sim}2mk$ 이내에서 잘 일치하는 것으로 평가되었다. 본 연구는 CANDU 노심의 기포반응도 불확실성 요인의 규명 및 영향평가를 위한 노력의 일부로서 앞으로 감속재의 붕산농도 변화, 감속재 및 냉각재의 중수 순도 변화, 기기노화에 의한 격자 구조 및 물성 변화, 중성자속 및 출력 분포 불균형, 반응도조절장치의 위치, 등 주요 설계변수의 변화에 대한 반응도영향 분석연구를 계속할 계획이다.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1000-1015
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• 2010

In this paper, we propose a novel algorithm for hand gesture recognition. The hand detection method is based on human skin color, and we use the boundary energy information to locate the hand region accurately, then the moment method will be employed to locate the hand palm center. Hand gesture recognition can be separated into 2 step: firstly, the hand posture recognition: we employ the parallel NNs to deal with problem of hand posture recognition, pattern of a hand posture can be extracted by utilize the fitting ellipses method, which separates the detected hand region by 12 ellipses and calculates the white pixels rate in ellipse line. the pattern will be input to the NNs with 12 input nodes, the NNs contains 4 output nodes, each output node out a value within 0~1, the posture is then represented by composed of the 4 output codes. Secondly, the hand gesture tracking and recognition: we employed the Kalman filter to predict the position information of gesture to create the position sequence, distance relationship between positions will be used to confirm the gesture. The simulation have been performed on Windows XP to evaluate the efficiency of the algorithm, for recognizing the hand posture, we used 300 training images to train the recognizing machine and used 200 images to test the machine, the correct number is up to 194. And for testing the hand tracking recognition part, we make 1200 times gesture (each gesture 400 times), the total correct number is 1002 times. These results shows that the proposed gesture recognition algorithm can achieve an endurable job for detecting the hand and its' gesture.