• Journal of the Korean Applied Science and Technology
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• v.34 no.4
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• pp.1094-1103
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• 2017

The purpose of this study was to measure the bioactivity and antioxidant activity of seed from Gardenia jasminoides Ellis fructus (GJE). We determined tannin content ($1.517{\pm}0.003mg\;CE/g$, mg of catechin equivalents). The extraction yields of the GJE seed solvent were distilled water (DW) 36.61%, 70% methanol 30.10% and ethyl acetate (EA) 20.40%. The antioxidant activities of the extracts were significantly increased (0.2, 0.4, 0.6 mg/mL). Flavonoid contents (mg QE/g, mg of quercetin equivalents) were observed in the order of 70% methanol (0.799), DW (0.565) and EA (0.117). Antioxidant activities (DPPH, OH, ferrous ion-chelating capacity) were similar to the flavonoid content of each solvent. But ABTS scavenging activity and SOD like ability of DW extract were higher than 70% methanol extract. Comparing the yield and the antioxidant activity of each solvent of GJE seed, it seems to be preferable to use DW and 70% methanol solvent for extraction. As a result of this experiment, it has high antioxidant activity and physiological activity, which is expected to be highly valuable as a functional food and a natural antioxidant.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.363-368
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• 2021

Ship engine rooms have improved automation systems owing to the advancement of technology. However, there are many variables at sea, such as wind, waves, vibration, and equipment aging, which cause loosening, cutting, and leakage, which are not measured by automated systems. There are cases in which only one engineer is available for patrolling. This entails many risk factors in the engine room, where rotating equipment is operating at high temperature and high pressure. When the engineer patrols, he uses his five senses, with particular high dependence on vision. We hereby present a preliminary study to implement an engine-room patrol robot that detects and informs the machine room while a robot patrols the engine room. Images of ship engine-room equipment were classified using a convolutional neural network (CNN). After constructing the image dataset of the ship engine room, the network was trained with a pre-trained CNN model. Classification performance of the trained model showed high reproducibility. Images were visualized with a class activation map. Although it cannot be generalized because the amount of data was limited, it is thought that if the data of each ship were learned through transfer learning, a model suitable for the characteristics of each ship could be constructed with little time and cost expenditure.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5A
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• pp.887-899
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• 2006

The aim of this study is to investigate a correlation between fundamental data on aerodynamic characteristics of bridge girder cross-sections, such as aerodynamic force coefficients and flutter derivatives, and their aerodynamic behaviour. The section model tests were carried out in three stages. In the first stage, seven deck configurations were studied, namely; Six 2-edge girders and one box girder. In this stage, changes in aerodynamic force coefficients due to geometrical shape of girders, incidence angle of flow, wind directions and turbulence intensities were studied by static section model tests. In the second stage, the dynamic section model tests were carried out to investigate the relativity of static coefficients to dynamic responses. And finally, the two-dimensional (lift-torsion) aerodynamic derivatives of three bridge deck configurations were investigated by dynamic section model tests. The aerodynamic derivatives can be best described as a representation of the aerodynamic damping and the aerodynamic stiffness provided by the wind for a given deck geometry. The method employed here to extract these unsteady aerodynamic properties is known as the initial displacement technique. It involves the measurement of the decay in amplitude with time of an initial displacement of the deck in heave and torsion, for various wind speeds, in smooth flow. It is suggested that the proposed aerodynamic force coefficients and flutter derivatives of bridge girder sections will be potentially useful for the aeroelastic analysis and buffeting analysis.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.480-493
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• 2007

Many railway-advanced countries are using the various types of track to reduce the track maintenance and repair cost according to the improvement of velocity. It spends on much maintenance and repair cost for ballast track due to abrasion of ballast, track irregularity and unisotropical ballast-support stiffness. The ballast track on railway bridge is accelerating the deterioration of ballast according to interaction of railway bridge and track. As continuing the deterioration, it is caused dynamic loads. Due to these effects, it increases negative loads of track and bridge. However, when designing the railway bridge, the effect of ballast track was applicate only dead load, so elastic behavior effect of ballast track is not influenced. Therefore, this paper presumes the stiffness of ballast track on railway bridge considering dynamic behavior of railway bridge, it was evaluated that effect on dynamic behaviors of railway bridge according to ballast track stiffness.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.903-913
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• 2021

In the flood season, the measurement of the river discharge has many restrictions due to reasons such as budget, manpower, safety, convenience in measurement and so on. In particular, when heavy rain events occur due to typhoons, etc., it is difficult to measure the amount of flood due to the above problems. In order to improve this problem, in this study, a method was developed that can measure the river discharge in a flood season simply and safely in a short time with minimal manpower by combining the functions of a drone and a surface velocity doppler radar. To overcome the mechanical limitations of drones caused by weather issues such as wind and rainfall derived from the measurement of the river discharge using the conventional drone, we developed a drone with P56 grade dustproof and waterproof performance, stable flight capability at a wind speed of up to 36 km/h, and a payload weight of up to 10 kg. Further, to eliminate vibration which is the most important constraint factor in the measurement with a surface velocity doppler radar, a damper plate was developed as a device that combines a drone and a surface velocity Doppler radar. The velocity meter DSVM (Dron and Surface Veloctity Meter using doppler radar) that combines the flight equipment with the velocity meter was produced. The error of ±3.5% occurred as a result of measuring the river discharge using DSVM at the point of Geumsan-gun (Hwangpunggyo) located at Bonghwang stream (the first tributary stream of the Geum River). In addition, when calculating the mean velocity from the measured surface velocity, the measurement was performed using ADCP simultaneously to improve accuracy, and the mean velocity conversion factor (0.92) was calculated by comparing the mean velocity. In this study, the discharge measured by combining a drone and a surface velocity meter was compared with the discharge measured using ADCP and floats, so that the application and utility of DSVM was confirmed.