• Journal of Environmental Science International
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• v.7 no.3
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• pp.311-320
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• 1998

The volume transport and turnover time of the Deukryang Bay. located at the southern area of Korea, were calculated based on the current meter(RCM-7,ACM 16M) data observed at the three gateways of the tegrating observed data and then averaging on time. dangdo and Kogumdo. The total water volume transports through three entrances of the bay in May and October were $3.9{\times}10-2Sv, 3.4{\times}10^{-2}Sv(1Sv=10^6m^3s^{-1}$) and turnover time were 0.97day, 1.12day, respectively. Semidiurnal tides were predominant (70~85%). The water volume transports by residual currents were 2~4% of total water volume transports . The average fraction of fresh water calculated by tidal prism method using salinity difference between inflow current and outflow current through three entrances In Deukryang Bay was about 0.06% of total volume and the flushing time of fresh water was estimated as 0.97day.

• Journal of the Korea Computer Graphics Society
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• v.11 no.1
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• pp.40-49
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• 2005

Several optimization techniques have been proposed for volume ray casting, but these cannot achieve real-time frame rates. In addition, it is difficult to apply them to some applications that require perspective projection. Recently, hardware-based methods using 3D texture mapping are being used for real-time volume rendering. Although rendering speed approaches real time, the larger volumes require more swapping of volume bricks for the limited texture memory. Also, image quality deteriorates compared with that of conventional volume ray casting. In this paper, we propose a data structure for real-time volume ray casting named PERM (Precomputed dEnsity and gRadient Map). The PERM stores interpolated density and gradient vector for quantized cells. Since the information requiring time-consuming computations is stored in the PERM, our method can ensure interactive frame rates on a consumer PC platform. Our method normally produces high-quality images because it is based on conventional volume ray casting.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.3-6
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• 2003

In this study, we analyze the historical data of postal matter amount in korea, various social indexes concerning mail volume and postal data in developed countries. After correlation analysis between some variables, we suggest a new logistic model for forecasting the future mail volume. Finally, we forecast the mail volume in korea about 20 years hereafter.

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.265-274
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• 1994

This paper proposes a method of noninvasive reflectance light to measure the blood fractional volume (Vb) and oxygen saturation ($SO_2$) of biological tissue. We chose the red light of 660nm and infrared light of 880nm. In Vivo reflectance data were obtained by the physiological changes front the surface of the skin over the calf in human subject. The reflected light intensity from different layers within a biological tissue was measured by specially designed reflectometer to apply photon path diffusion model. The collected data represent the changes of blood (ractional volume and oxygen saturation at each reflected light wavelengths. The data evaluation was assessed by examining the slopes of the plotted indices for the changes in oxygen saturation and blood (ractional volume. The results presented in this paper claim that light reflectance can separately discriminate the change of blood volume and that of oxygenation in muscle and also in skin.

• Journal of Biomedical Engineering Research
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• v.31 no.4
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• pp.285-291
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• 2010

Recently, advance on various modalities of diagnosing, prostate volume estimation became possible not only by the existing two-dimension medical images data but also by the three-dimensional medical images data. In this study, magnetic resonance image (MRI), computer tomography (CT) and ultrasound (US) were employed to evaluate prostate phantom volume measurements for estimation, comparison and analysis. For the prostate phantoms aimed at estimating the volume, total of 17 models were developed by using devils-tongue jelly and changing each of the 5ml of capacity from 20ml to 100ml. For the volume estimation through 2D US, the calculation of the diameter with C9-5Mhz transducer was conducted by ellipsoid formula. For the volume estimation through 3D US, the Qlab software (Philips Medical) was used to calculate the volume data estimated by 3D9-3Mhz transducer. Moreover, the images by 16 channels CT and 1.5 Tesla MRI were added by the method of continuous cross-section addition and each of imaginary prostate model's volume was yielded. In the statistical analysis for comparing the availability of volume estimation, the correlation coefficient (r) was more than 0.9 for all indicating that there were highly correlated, and there were not statistically significant difference between each of the correlation coefficient (p=0.001). Therefore, the estimation of prostate phantom volume using three-dimensional modalities of diagnosing was quite closed to the actual estimation.

• Journal of Korea Multimedia Society
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• v.5 no.5
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• pp.494-504
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• 2002

Volume rendering is a method of displaying volumetric data as a sequence two-dimensional image. Because this algorithm has an advantage of visualizing structures within objects, it has recently been used to analyze medical images i.e, MRI, PET, and SPECT. In this paper. we suggested a method for creating images easily from sampled volumetric data and applied the interpolation method to medical images. Additionally, we implemented and applied two kinds of interpolation methods to improve the image quality, linear interpolation and cubic interpolation at the sampling stage. Subsequently, we compared the results of volume rendered data using a transfer function. We anticipate a significant contribution to diagnosis through image reconstruction using a volumetric data set, because volume rendering techniques of medical images are the result of 3-dimensional data.

• The KIPS Transactions:PartA
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• v.10A no.2
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• pp.157-164
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• 2003

Volume graphics have received a lot of attention as a medical image analysis tool nowadays. In the visualization based on volume graphics, there is a process called voxelization which transforms the geometrically defined objects into the volumetric objects. It enables us to volume render the geometrically defined data with sampling data. This paper suggests a voxeliration method using the cutting surfaces of cubes, implements the method on a PC, and evaluates it with simple geometric modeling data to explore propriety of the method. This method features the ability of calculating the exact normal vector from a voxel, having no hole among voxels, having multi-resolution representation.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.300-307
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• 2010

According to growth of web, data processing technology is developing. In the Web of next generation, high-speed or high-volume data processing technologies for various wire-wireless users, USN and RFID are developing too. In this paper, we propose a high-volume data processing technology using Complex Event Processing(CEP) engine. CEP is the technology to process complex events. CEP Engine is the following characteristics. First it collects a high-volume event(data). Secondly it analyses events. Finally it lets event connect to new actions. In other words, CEP engine collects, analyses, filters high-volume events. Also it extracts events using pattern-matching for registered events and new events. As the results extracted. We use it by an input event of other work, real-time response for demanded event and can trigger to database for only valid data.

• The KIPS Transactions:PartA
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• v.13A no.7 s.104
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• pp.639-646
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• 2006

Data compression technologies enable us to store and transfer large amount of data efficiently, and become more and more important due to increasing data size and the network traffic. Moreover, as a result of the increase of computing power, volumetric data produced from various applied science and engineering fields has been getting much larger. In this Paper, we present a volume compression scheme which exploits Daubeches wavelet transform. The proposed scheme basically supports lossy compression for 3D volume data, and provides unit-wise random accessibility. Since our scheme shows far lower error rates than the previous compression methods based on Haar filter, it could be used well for interactive visualization applications as well as large volume data compression requiring image fidelity.

• Journal of Preventive Medicine and Public Health
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• v.39 no.1
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• pp.13-20
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• 2006

Objectives: To propose a risk-adjustment model with using insurance claims data and to analyze whether or not the outcomes of non-emergent and isolated coronary artery bypass graft surgery (CABG) differed between the low- and high-volume hospitals for the patients who are at different levels of surgical risk. Methods: This is a cross-sectional study that used the 2002 data of the national health insurance claims. The study data set included the patient level data as well as all the ICD-10 diagnosis and procedure codes that were recorded in the claims. The patient's biological, admission and comorbidity information were used in the risk-adjustment model. The risk factors were adjusted with the logistic regression model. The subjects were classified into five groups based on the predicted surgical risk: minimal (<0.5%), low (0.5% to 2%), moderate (2% to 5%), high (5% to 20%), and severe (=20%). The differences between the low- and high-volume hospitals were assessed in each of the five risk groups. Results: The final risk-adjustment model consisted of ten risk factors and these factors were found to have statistically significant effects on patient mortality. The C-statistic (0.83) and Hosmer-Lemeshow test ($x^2=6.92$, p=0.55) showed that the model's performance was good. A total of 30 low-volume hospitals (971 patients) and 4 high-volume hospitals (1,087 patients) were identified. Significant differences for the in-hospital mortality were found between the low- and high-volume hospitals for the high (21.6% vs. 7.2%, p=0.00) and severe (44.4% vs. 11.8%, p=0.00) risk patient groups. Conclusions: Good model performance showed that insurance claims data can be used for comparing hospital mortality after adjusting for the patients' risk. Negative correlation was existed between surgery volume and in-hospital mortality. However, only patients in high and severe risk groups had such a relationship.