• Korean Journal of Optics and Photonics
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• v.21 no.2
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• pp.82-88
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• 2010

Photopolymer is a material for recording three dimensional holograms containing photo information. Photopolymer has been found to be a proper material due to many advantages such as high DE value, easy processing, and low price. Compositions of PVA, monomer, initiater and photosensitizer were determined by previous experiments and the compositions of $SeO_2$ and $TiO_2$ were considered as variable to find out the effects of $TiO_2$ on DE. The DE values were constant for the varying compositions of $TiO_2$ (0.1 mg~1.0 mg). In other words, $TiO_2$ is not directly effective on the DE values. Composition change experiments from $SeO_2$ 0.1 mg, $TiO_2$ 0.9 mg to $SeO_2$ 0.9 mg, $TiO_2$ 0.1 showed a maximum DE value of 73.75% at a component of $SeO_2$ 0.8 mg, $TiO_2$ 0.2 mg. It seemed that regardless of the amount of $TiO_2$, increasing the amount of $SeO_2$ gently increases DE`s. If nano particles are heavily added, transparent films could not be made due to the separation of particles by the solubility decrease. Photopolymer films could be made with high DE values for an extensive angle range if $TiO_2$ additions were kept minimum and $SeO_2$ additions were kept maximum.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.603-614
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• 2021

Recently, the surface temperature in the seas around Korea has been continuously rising. This temperature rise causes changes in fishery resources and affects leisure activities such as fishing. In particular, high temperatures lead to the occurrence of red tides, causing severe damage to ocean industries such as aquaculture. Meanwhile, changes in sea temperature are closely related to military operation to detect submarines. This is because the degree of diffraction, refraction, or reflection of sound waves used to detect submarines varies depending on the ocean mixed layer. Currently, research on the prediction of changes in sea water temperature is being actively conducted. However, existing research is focused on predicting only the surface temperature of the ocean, so it is difficult to identify fishery resources according to depth and apply them to military operations such as submarine detection. Therefore, in this study, we predicted the temperature of the ocean mixed layer at a depth of 38m by using temperature data for each water depth in the upper mixed layer and meteorological data such as temperature, atmospheric pressure, and sunlight that are related to the surface temperature. The data used are meteorological data and sea temperature data by water depth observed from 2016 to 2020 at the IEODO Ocean Research Station. In order to increase the accuracy and efficiency of prediction, LSTM (Long Short-Term Memory), which is known to be suitable for time series data among deep learning techniques, was used. As a result of the experiment, in the daily prediction, the RMSE (Root Mean Square Error) of the model using temperature, atmospheric pressure, and sunlight data together was 0.473. On the other hand, the RMSE of the model using only the surface temperature was 0.631. These results confirm that the model using meteorological data together shows better performance in predicting the temperature of the upper ocean mixed layer.

• Korean Journal of Environmental Biology
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• v.40 no.3
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• pp.267-274
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• 2022

Excess nitrogen (N) flowing from livestock manure to water systems poses a serious threat to the natural environment. Thus, livestock wastewater management has recently drawn attention to this related field. This study first attempted to obtain the optimal conditions for the further volatilization of NH₃ gas generated from pig wastewater by adjusting the amount of injected magnesia (MgO). At 0.8 wt.% of MgO (by pig wastewater weight), the volatility rate of NH₃ increased to 75.5% after a day of aeration compared to untreated samples (pig wastewater itself). This phenomenon was attributed to increases in the pH of pig wastewater as MgO dissolved in it, increasing the volatilization efficiency of NH₃. The initial pH of pig wastewater was 8.4, and the pH was 9.2 when MgO was added up to 0.8 wt.%. Second, the residual ammonia nitrogen (NH₄⁺-N) in pig wastewater was removed by precipitation in the form of struvite (NH₄MgPO₄·6H₂O) by adjusting the pH after adding MgO and H₃PO₄. Struvite produced in the pig wastewater was identified by field emission scanning electron microscopy (FE-SEM) and X-ray diffraction (XRD) analysis. White precipitates began to form at pH 6, and the higher the pH, the lower the concentration of NH₄⁺-N in pig wastewater. Of the total 86.1% of NH₄⁺-N removed, 62.4% was achieved at pH 6, which was the highest removal rate. Furthermore, how struvite changes with pH was investigated. Under conditions of pH 11 or higher, the synthesized struvite was completely decomposed. The yield of struvite in the precipitate was determined to be between 68% and 84% through a variety of analyses.