• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.12
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• pp.1753-1757
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• 2012

A new liquid chromatographic tandem mass spectrometric (LC-MS/MS) assay for the quantification of ginsenoside Rb1 in human plasma was developed and validated. The separation was performed on a Agilent C18 column ($4.6mm{\times}150mm$, particle size 5 ${\mu}m$) with a gradient elution of 0.1% formic acid in water and 0.1% formic acid in methanol and a flow rate of 0.9 mL/min. The analyte was determined using electrospray positive ionization mass spectrometry in the multiple reaction monitoring (MRM) mode (m/z 1131.714${\rightarrow}$365.303). Human plasma samples were extracted with acetone : water (50:50) by the liquid-liquid extraction method. The method was linear over the dynamic range of 10~500 ng/mL with a correlation coefficient of r=0.9995. The intra-and inter-day precision over the concentration range of ginsenoside Rb1 was lower than 5.8% (correlation of variance, CV), and the accuracy was between 96.0~104.6%. This LC-MS/MS assay of ginsenoside Rb1 in human plasma is applicable for quantification in a pharmacokinetic study.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.548-559
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• 2019

Purpose: Analysis method of V2I data driven motorway service area usage behavior to cope with manpower survey. Method: Segmentation of traveling state group and boundary using the distribution characteristics of traveling speed data of individual vehicles. Result: As a result of the verification, the use rate of resting places in lunchtime surged, and the boundary between the distribution status of the traffic speed data was clearly or unclear. Conclusion: The effect of the cost reduction is big because it can cope with the use of rest area survey by manpower and there is no limit in the time and space range of investigation. The dynamic utilization rate of each time sequence, such as a service area/drowsiness shelter/simple service area, with a V2I system, can be calculated. Identify illegal parking on highway section. Identify the unexpected situation in the road section. Identify the real-time service area utilization rate and congestion information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.300-309
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• 2016

Curved beams are increasingly used in buildings, vehicles, ships, and aircraft, which has resulted in considerable effort towards developing an accurate method for analyzing the dynamic behavior of such structures. The stability behavior of elastic curved beams has been the subject of many investigations. Solutions to the relevant differential equations have traditionally been obtained by the standard finite difference or finite element methods. However, these techniques require a great deal of computer time for a large number of discrete nodes with conditions of complex geometry and loading. One efficient procedure for the solution of partial differential equations is the differential quadrature method (DQM). This method has been applied to many cases to overcome the difficulties of complex algorithms and high storage requirements for complex geometry and loading conditions. Out-of-plane buckling of curved beams with rotatory inertia were analyzed using DQM under uniformly distributed radial loads. Critical loads were calculated for the member with various parameter ratios, boundary conditions, and opening angles. The results were compared with exact results from other methods for available cases. The DQM used only a limited number of grid points and shows very good agreement with the exact results (less than 0.3% error). New results according to diverse variation are also suggested, which show important roles in the buckling behavior of curved beams and can be used for comparisons with other numerical solutions or experimental test data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• Journal of the Korean Geotechnical Society
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• v.20 no.5
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• pp.145-159
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• 2004

The conventional method for assessment of liquefaction potential proposed by Seed and Idriss has been widely used in most countries because of simplicity of tests. Even though various data such as stress, strain, stress path, and excess pore water pressure can be obtained from the dynamic test, especially, two simple experimental data such as the maximum deviatoric stress and the number of cycles at liquefaction have been used in the conventional assessment. In this study, a new detailed assessment for liquefaction potential to reflect both characteristics of real earthquake motion and dynamic soil resistance is proposed and verified. In the assessment, the safety factor of the liquefaction potential at a given depth of a site can be obtained by the ratio of a resistible cumulative plastic shear strain determined through the performance of the conventional cyclic test and a driving cumulative plastic shear strain calculated from the shear strain time history through the ground response analysis. The last point to cumulate the driving plastic shear strain to initiate soil liquefaction is important for this assessment. From the result of cyclic triaxial test using real earthquake motions, it was concluded that liquefaction under the impact-type earthquake loads would initiate as soon as a peak loading signal was reached. The driving cumulative plastic shear strain, therefore, can be determined by adding all plastic shear strains obtained from the ground response analysis up to the peak point. Through the verification of the proposed assessment, it can be concluded that the proposed assessment for liquefaction potential can be a progressive method to reflect both characteristics of the unique soil resistance and earthquake parameters such as peak earthquake signal, significant duration time, earthquake loading type, and magnitude.

• 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.

• Ultrasonography
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• v.32 no.1
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• pp.59-65
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• 2013

Purpose: The purpose of this study is to establish the methodology regarding synthesis of ultrasound contrast agent imaging, and to evaluate the characteristics of the synthesized ultrasound contrast agents, including size or degradation interval and image quality. Materials and Methods: The ultrasound contrast agent, composed of liposome and SF6, was synthesized from the mixture solution of $21{\mu}mol$ DPPC (1, 2-Dihexadecanoyl-sn-glycero-3-phosphocholine, $C_{40}H_{80}NO_8P$), $9{\mu}mol$ cholesterol, $1.9{\mu}mol$ of DCP (Dihexadecylphosphate, $[CH_3(CH_2)_{15}O]_2P(O)OH$), and chloroform. After evaporation in a warm water bath and drying during a period of 12-24 hours, the contrast agent was synthesized by the sonication process by addition of buffer and SF6 gas. The size of the contrast agent was controlled by use of either extruder or sonication methods. After synthesis of contrast agents, analysis of the size distribution of the bubbles was performed using dynamic light scattering measurement methods. The degradation curve was also evaluated by changes in the number of contrast agents via light microscopy immediate, 12 hours, 24 hours, 36 hours, 48 hours, 60 hours, 72 hours, and 84 hours after synthesis. For evaluation of the role as an US contrast agent, the echogenicity of the synthesized microbubble was compared with commercially available microbubbles (SonoVue, Bracco, Milan, Italy) using a clinical ultrasound machine and phantom. Results: The contrast agents were synthesized successfully using an evaporation-drying-sonication method. The majority of bubbles showed a mean size of 154.2 nanometers, and they showed marked degradation 24 hours after synthesis. ANOVA test revealed a significant difference among SonoVue, synthesized contrast agent, and saline (p < 0.001). Although no significant difference was observed between SonoVue and the synthesized contrast agent, difference in echogenicity was observed between synthesized contrast agent and saline (p < 0.01). Conclusion: We could synthesize ultrasound contrast agents using an evaporation-drying-sonication method. On the basis of these results, many prospective types of research, such as anticancer drug delivery, gene delivery, including siRNA or microRNA, targeted molecular imaging, and targeted therapy can be performed.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.6
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• pp.305-314
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• 2017

Ocean wave energy harvesting is still too expensive despite developing a variety of wave energy converter (WEC) devices. For the cost-effective wave energy harvesting, it can be an effective measure to use existing breakwaters or newly installed breakwaters for both wave control and energy harvesting purposes. In this study, we investigated the functionality of both breakwater and wave-power generator for the oscillating water column (OWC)-type wave energy converter (WEC) installed in a pneumatic floating breakwater, which was originally developed as a floating breakwater. In order to verify the performance of the breakwater as a WEC, the air flow velocity from air-chamber to WEC has to be evaluated properly. Therefore, air flow velocity, wave transformation and motion of floating structure was numerically implemented based on BEM from linear velocity potential theory without considering the compressibility of air within the chamber. Air pressure, meanwhile, was assumed to be fluctuated by the motions of structure and the water level change within air-chamber. The validity of the obtained values can be determined by comparing the previous results from the numerical analysis for different shapes. Based on numerical model results, wave transformation characteristics around OWC system mounted on the fixed and floating breakwaters, and motions of the structure with air flow velocities are investigated. In summary, all numerical results are almost identical to the previous research considering air compressibility. Therefore, it can be concluded that this analysis not considering air compressibility in the air chamber is more efficient and practical method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.4
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• pp.393-399
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• 2017

In a reciprocating compressor, the piston and connecting rod are important parts. Excess mechanical stress on these parts may cause damage, and broken parts are expensive and difficult to replace. Therefore, it is necessary to analyze the mechanical stress affecting durability and longevity. The main purpose of this study was to identify locations of maximum stress on pistons and connecting rods. Based on dynamic calculation of the working process of a specific air compressor, an analysis of piston and connecting rod performance has been completed. A three-dimensional model for the air compressor's pistons and connecting rods was built separately, and FEM analysis of these components was carried out using a numerical method. The pistons were loaded by pressure which was changed according to crankshaft angle without thermal boundary conditions. The simulation results were used to predict and estimate stress concentration as well as the value of this stress on pistons and connecting rods. The maximum equivalent stress calculated are over 190 MPa on pistons and 123 MPa on connecting rods at crank angle $135^{\circ}$ and $225^{\circ}$ but these are under tensile yield strength. Besides, the calculated safety factors of connecting rods and pistons is higher than 1. Moreover, the results obtained can be used to provide manufacturers with references to optimize the design of pistons and connecting rods for reciprocating compressors.

• Journal of Korean Society of Steel Construction
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• v.29 no.1
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• pp.49-60
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• 2017

As well as the strength check, fatigue life check is also mainly required for designing mooring lines of the floating structures. In general, forces which induce dynamic structural response significantly affect to fatigue design of the mooring lines. So, waves are mainly considered as the governing loading for fatigue design of the mooring lines. In this study, characteristics of the fatigue damage of the mooring lines for submerged floating tunnels (SFT) under irregular waves are investigated. For this study time domain hydrodynamic analysis is used to obtain motion of the tunnel and tension and stresses of the mooring lines under the specific environmental conditions. Also, the Rainflow-counting method, the Palmgren-Miner's rule, and S-N curves for floating offshore structures presented by DNV recommendation is applied to calculate the fatigue damage due to the fluctuating stresses. Referring to the design plactice of the tendon pipes for TLP (tension-leg platform), which is very similar structural system to SFT, it is assumed that a 100 year return period wave attacks the SFT systems during 48 hours and the fatigue damages due to the environmental loading are calculated. Following the analysis sequence, the effects of the tunnel draft, spacing and initial inclination angle of the mooring lines on the fatigue damage under the specific environmental loadings are investigated.