• Journal of Radiation Protection and Research
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• v.41 no.2
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• pp.93-99
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• 2016

Background: Industrial X-ray CT system is normally applied to non-destructive testing (NDT) for industrial product made from metal. Furthermore there are some special CT systems, which have an ability to inspect nuclear fuel assemblies or rocket motors, using high power and high energy (more than 6 MeV) pulsed X-ray source. In these case, pulsed X-ray are produced by the electron linear accelerator, and a huge number of photons with a wide energy spectrum are produced within a very short period. Consequently, it is difficult to measure the X-ray energy spectrum for such accelerator-based X-ray sources using simple spectrometry. Due to this difficulty, unexpected images and artifacts which lead to incorrect density information and dimensions of specimens cannot be avoided in CT images. For getting highly precise CT images, it is important to know the precise energy spectrum of emitted X-rays. Materials and Methods: In order to realize it we investigated a new approach utilizing the Bayesian estimation method combined with an attenuation curve measurement using step shaped attenuation material. This method was validated by precise measurement of energy spectrum from a 1 MeV electron accelerator. In this study, to extend the applicable X-ray energy range we tried to measure energy spectra of X-ray sources from 6 and 9 MeV linear accelerators by using the recently developed method. Results and Discussion: In this study, an attenuation curves are measured by using a step-shaped attenuation materials of aluminum and steel individually, and the each X-ray spectrum is reconstructed from the measured attenuation curve by the spectrum type Bayesian estimation method. Conclusion: The obtained result shows good agreement with simulated spectra, and the presently developed technique is adaptable for high energy X-ray source more than 6 MeV.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.355-362
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• 2012

Remaining useful life(RUL) prediction of a system is important in the prognostics field since it is directly linked with safety and maintenance scheduling. In the physics-based prognostics, accurately estimated model parameters can predict the remaining useful life exactly. It, however, is not a simple task to estimate the model parameters because most real system have multivariate model parameters, also they are correlated each other. This paper presents representative methods to estimate model parameters in the physics-based prognostics and discusses the difference between three methods; the particle filter method(PF), the overall Bayesian method(OBM), and the sequential Bayesian method(SBM). The three methods are based on the same theoretical background, the Bayesian estimation technique, but the methods are distinguished from each other in the sampling methods or uncertainty analysis process. Therefore, a simple physical model as an easy task and the Paris model for crack growth problem are used to discuss the difference between the three methods, and the performance of each method evaluated by using established prognostics metrics is compared.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.237-250
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• 2022

In this study, we propose a method to estimate the biomass of invertebrate grazers from the videos with underwater drones by using a multi-object tracking model based on deep learning. In order to detect invertebrate grazers by classes, we used YOLOv5 (You Only Look Once version 5). For biomass estimation we used DeepSORT (Deep Simple Online and real-time tracking). The performance of each model was evaluated on a workstation with a GPU accelerator. YOLOv5 averaged 0.9 or more mean Average Precision (mAP), and we confirmed it shows about 59 fps at 4 k resolution when using YOLOv5s model and DeepSORT algorithm. Applying the proposed method in the field, there was a tendency to be overestimated by about 28%, but it was confirmed that the level of error was low compared to the biomass estimation using object detection model only. A follow-up study is needed to improve the accuracy for the cases where frame images go out of focus continuously or underwater drones turn rapidly. However,should these issues be improved, it can be utilized in the production of decision support data in the field of invertebrate grazers control and monitoring in the future.

• Archives of Plastic Surgery
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• v.38 no.1
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• pp.35-42
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• 2011

Purpose: Blow-out fractures can be reduced using various methods. The orbital reconstruction technique using a balloon under endoscopic control has advantages over other methods. However, this method has some problems too, such as postoperative follow-up, management of the balloon catheter, and reduction of the posterior orbital floor. Thus, we developed a simple, effective method for orbital floor reduction that involves molding and shaping the antral balloon catheter. Methods: A 0, 30, or $70^{\circ}$, 4-mm endoscope was placed though a two-point, 5-mm maxillary antrostomy. The balloon catheter is placed directly at the orbital apex to reconstruct the anterior shelf (spherical shape), while it is turned in a U-shape towards the anterior maxilla for the posterior shelf (elliptical shape). Orbital floor defects, compound or comminuted fractures are reconstructed with alloplastic materials through an open lid incision under the endoscopic control. Results: This technique was applied to ten patients with orbital floor fractures: five anterior shelf and five posterior shelf fracture, respectively. Four of the patients had zygomatico-orbital fractures, while the rest had isolated orbital floor fractures. Two patients were given porous polyethylene implants Synpor$^{(R)}$) and three underwent reconstruction with a resorbable mesh plate. No complication associated with this technique was identified. Conclusion: The freestyle placement and selection of a urinary balloon catheter under endoscopic control and the preoperative estimation of the volume enhanced the stabilization of the orbital contour. This method improves the adaptation of the orbital floor without the risk of injuring the surrounding orbital contents, dissecting blindly, or using sharp traction. One drawback of this method is the patient's discomfort from the catheter during treatment.

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.421-430
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• 2003

The extraction technique for Doppler information(Doppler centroid frequency(f$_{dc}$) and it's rate(f$_{r}$) is very important to make an image from the radar echo signal data. Clutterlock and auto-focusing techniques have been widely used to extract accurate Doppler information. But both techniques are not easy to implement in SAR processor and need quite lots of time to calculate accurate f$_{dc}$ and f$_{r}$ because they are generally based on echo signal data only. In this paper we suggest hybrid method for Doppler extraction using both of echo signal data and orbital and attitude information of satellite. In this method CDE(Correlation Doppler Estimation) technique is only used to estimate exact modular f$_{dc}$ using received echo signal data and rest of other algorithms are based on simple mathematical model of geometry between satellite and ground targets as well as the Doppler frequency ambiguity resolving problem. The experimental results using Radarsat-1 signal data shows that the proposed method can be effectively used for the extraction of Doppler information.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.9-20
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• 2010

In order to visualize participating media in 3D space, they usually calculate the incoming radiance by subdividing the ray path into small subintervals, and accumulating their respective light energy due to direct illumination, scattering, absorption, and emission. Among these light phenomena, scattering behaves in very complicated manner in 3D space, often requiring a great deal of simulation efforts. To effectively simulate the light scattering effect, several approximation techniques have been proposed. Volume photon mapping takes a simple approach where the light scattering phenomenon is represented in volume photon map through a stochastic simulation, and the stored information is explored in the rendering stage. While effective, this method has a problem that the number of necessary photons increases very fast when a higher variance reduction is needed. In an attempt to resolve such problem, we propose a different approach for rendering particle-based volume data where kernel smoothing, one of several density estimation methods, is explored to represent and reconstruct the light in-scattering effect. The effectiveness of the presented technique is demonstrated with several examples of volume data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.129-134
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• 2018

Research on the technique for estimating the indoor position has been actively carried out. In particular, the WiFi fingerprint method, which does not require any additional infrastructure, is being partially used because of its high economic efficiency. The KNN method which estimates similar points to the corresponding points by comparing intensity information of the WLAN reception signal measured at various points in advance with intensity information measured at a specific point in the future is simple but has a good performance. However, in the conventional KNN scheme, since the number K of average candidate positions is constant, there is a problem that the position estimation error is not optimized according to a specific point. In this paper, we proposed an algorithm that adaptively changes the K value for each point and applied it to experimental data and evaluated its performance.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.567-576
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• 2005

This paper proposes an image-based modeling method which recovers 3D models using projected line segments in multiple images. Using the method, a user obtains accurate 3D model data via several steps of simple manual works. The embedded nonlinear minimization technique in the model parameter estimation stage is based on the distances between the user provided image line segments and the projected line segments of primitives. We define an error using a finite line segment and thus increase accuracy in the model parameter estimation. The error is defined as the sum of differences between the observed image line segments provided by the user and the predicted image line segments which are computed using the current model parameters and camera parameters. The method is robust in a sense that it recovers 3D structures even from partially occluded objects and it does not be seriously affected by small measurement errors in the reconstruction process. This paper also describesexperimental results from real images and difficulties and tricks that are found while implementing the image-based modeler.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.3 no.4
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• pp.228-233
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• 1998

This study presents a close-range photogrammetry that is applicable to beach profile estimation using a non-metric camera. Based on the analysis of oblique video image in which the video camera was installed on a horizontal plane and the field of view was fixed, a new equation to analyze a photograph was developed considering the following aspects: (1) camera is allowed to be rotated about its optical axis and (2) a simple error model is adopted to correct lens distortion and other systematic errors associated with the non-metric camera, which improves accuracy of non-metric imageries. To test the modified technique, photographs of the beach were taken near the Donghae City in February, 1998. In addition, beach profiles were surveyed with conventional dumpy level and surveying staff. RMS error between the estimated and measured beach profiles is less than 10 cm in elevation.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.309-315
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• 1998

Process Capability can be expressed with a process index which indicates the incapability of a process to meet its specifications. This index is regarded as a process capability index(PCI) or more precisely as a process incapability index(PII). It is obtained from a simple transformation of a PCI. Greenwich and Jahr-Schaffrath(1995) considered the PII $C_{pp}$ which could be obtained from the transformation to the PCI, $C_{pm}$, and they provided the asymptotic distribution for $C_{pp}$ which was useful unless the process characteristic was normally distributed. However, some statistical inferences based on the asymptotic distribution need a large sample size. There are some processes which process engineers could not help obtaining sufficiently a large sample size. Thus, we have derived its corresponding bootstrap asymptotic distribution since bootstrapping would be a helpful technique for the PII, $C_{pp}$ which was nonparametric or free from assumptions of the distribution of the characteristic X. Moreover, we have constructed six bootstrap confidence intervals used in reducing bias of estimations based on the bootstrap asymptotic distribution and simulated their performances for $C_{pp}$,