• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.5
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• pp.628-636
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• 2018

Because large buoys are mainly made of steel, they are heavy and vulnerable to corrosion by sea water. This makes buoy installation and maintenance difficult. Moreover, vessel collision accidents with buoys and damage to vessels due to the material of buoys (e.g., steel) are reported every year. Recently, light buoys adopting eco-friendly and lightweight materials have come into the spotlight in order to solve the previously-mentioned problems. In Korea, a new lightweight buoy with a 7-Nautical Mile lantern adopting expanded polypropylene (EPP) and aluminum to create a buoyant body and tower structure, respectively, was developed in 2017. When these light buoys are operated in the ocean, the visibility and angle of light from the lantern installed on the light buoys changes, which may cause them to function improperly. Therefore, research on the performance of light buoys is needed since the weight distribution and motion characteristics of these new buoys differ from conventional models. In this study, stability estimation and motion analyses for newly-developed buoys under various environmental conditions considering a mooring line were carried out using ANSYS AQWA. Numerical simulations for the estimation of wind and current loads were performed using commercial CFD software, Siemens STAR-CCM+, to increase the accuracy of motion analysis. By comparing the estimated maximum significant motions of the light buoys, it was found that waves and currents were more influential in the motion of the buoys. And, the estimated motions of the buoys became larger as the sea state became worser, which might be the reason that the peak frequencies of the wave spectra got closer to those of the buoys.

• The Korean Journal of Nuclear Medicine
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• v.37 no.5
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• pp.288-300
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• 2003

Purpose: To obtain regional blood flow and tissue-blood partition coefficient with time-activity curves from ${H_2}^{15}O$ PET, fitting of some parameters in the Kety model is conventionally accomplished by nonlinear least squares (NLS) analysis. However, NLS requires considerable compuation time then is impractical for pixel-by-pixel analysis to generate parametric images of these parameters. In this study, we investigated several fast parameter estimation methods for the parametric image generation and compared their statistical reliability and computational efficiency. Materials and Methods: These methods included linear least squres (LLS), linear weighted least squares (LWLS), linear generalized least squares (GLS), linear generalized weighted least squares (GWLS), weighted Integration (WI), and model-based clustering method (CAKS). ${H_2}^{15}O$ dynamic brain PET with Poisson noise component was simulated using numerical Zubal brain phantom. Error and bias in the estimation of rCBF and partition coefficient, and computation time in various noise environments was estimated and compared. In audition, parametric images from ${H_2}^{15}O$ dynamic brain PET data peformed on 16 healthy volunteers under various physiological conditions was compared to examine the utility of these methods for real human data. Results: These fast algorithms produced parametric images with similar image qualify and statistical reliability. When CAKS and LLS methods were used combinedly, computation time was significantly reduced and less than 30 seconds for $128{\times}128{\times}46$ images on Pentium III processor. Conclusion: Parametric images of rCBF and partition coefficient with good statistical properties can be generated with short computation time which is acceptable in clinical situation.