• The Korean Journal of Pesticide Science
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• v.15 no.1
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• pp.8-14
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• 2011

Methoxyfenozide and novaluron was sprayed on Aster scaber during cultivation period. Samples were collected 7 times in 0-10 days after spraying. Both methoxyfenozide and novaluron were extracted with methanol, partitioned with dichloromethane and analyzed by HPLC. At the fortified level of 0.4 and $2\;mg{\cdot}kg^{-1}$, average recovery of methoxyfenozide were $102.5{\pm}3.03$ and $84.4{\pm}2.82%$, and novaluron were $88.7{\pm}2.32$ and $90.6{\pm}4.50%$, respectively. Biological half-life of methoxyfenozide was 3.99 days and novaluron which was 3.16 days at recommended spray level on cultivation period of the plant. The major reducing factor of novaluron was the increased weight of the plant. In case of application of methoxyfenozide and novaluron following pesticide guide line for safe use, the final residue level was calculated to lower than maximum residue level (MRL).

• Journal of Aerospace System Engineering
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• v.12 no.1
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• pp.57-67
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• 2018

The APD (Antenna Pointing Driver) is an electronic equipment tool that is used to drive the two-axis gimbal-type antenna for the image data transmission of CAS (Compact Advanced Satellite). In this study, a heat dissipation of EEE (Electrical, Electronic and Electromechanical) is reviewed, to identify the parts that directly affected its efficiency, lifetime as well as the reliability of the structure. This event eventually incurs a failure of the EEE part itself, or even the entire satellite system as noted in experiments in this case. To guarantee reliability of electronic equipment during the mission, the junction temperature of EEE parts is considered a significant and important design factor, and subsequently must be secured within the allowable range. Therefore, the notation of the thermal analysis considering the derating is indispensable, and a proper thermal mathematical model should be constructed for this case. In this study, the thermal design and thermal analysis are performed to confirm the temperature requirement of the APD. In addition, we noted that the validity of the thermal model, according to each of the identified modeling methods, was therefore compared through the thermal analysis utilized in this case.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.575-586
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• 2020

In this study, a two-dimensional hydraulic model test was conducted to examine the hydraulic phenomena that occur around the seawall when wave and wind coexist. Based on recent seawall repair and reinforcement examples, the experimental section was constructed under the condition of installing wave dissipation blocks on the safety surface of four different representative seawalls. Water level fluctuation, reflection, overtopping and wave pressure characteristics according to external force change were reviewed. It was confirmed that the top concrete shape of the seawall is the most important factor of the hydraulic characteristics that appear in front of the seawall, and the tendency is more pronounced when wind acts. Even in the case of vertical type seawall, when wind of 3 m/s~5 m/s occurs, the amount of overtopping increases to about 5%~12%. In the case of wave pressure, it was confirmed from the experimental results that the value increased from about 1.5 to 2.2 times in front of the top of concrete block. In addition, it was confirmed that when the shape of the seawall was different, the range of change in the hydraulic characteristics appeared larger. Therefore, when designing a seawall of a new shape, a more detailed review of the hydraulic characteristics should be accompanied based on these experimental results.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.543-551
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• 2023

As climate change continues to prompt an increasing demand for advancements in disaster and safety management technologies to address abnormal high water temperatures, typhoons, floods, and droughts, sea surface temperature has emerged as a pivotal factor for swiftly assessing the impacts of summer harmful algal blooms in the seas surrounding Korean Peninsula and the formation and dissipation of cold water along the East Coast of Korea. Therefore, this study sought to gauge predictive performance by leveraging statistical methods and deep learning algorithms to harness sea surface temperature data effectively for marine anomaly research. The sea surface temperature data employed in the predictions spans from 2018 to 2022 and originates from the Heuksando Tidal Observatory. Both traditional statistical ARIMA methods and advanced deep learning models, including long short-term memory (LSTM) and gated recurrent unit (GRU), were employed. Furthermore, prediction performance was evaluated using the attention LSTM technique. The technique integrated an attention mechanism into the sequence-to-sequence (s2s), further augmenting the performance of LSTM. The results showed that the attention LSTM model outperformed the other models, signifying its superior predictive performance. Additionally, fine-tuning hyperparameters can improve sea surface temperature performance.