• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.173-173
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• 2023

The Mekong River Basin (MRB) is a crucial watershed in Asia, impacting over 60 million people across six developing nations. Accurate satellite-based precipitation products (SPPs) are essential for effective hydrological and watershed management in this region. However, the performance of SPPs has been varied and limited. The APHRODITE product, a unique gauge-based dataset for MRB, is widely used but is only available until 2015. In this study, we present a novel framework for correcting SPPs in the MRB by employing a deep learning approach that combines convolutional neural networks and encoder-decoder architecture to address pixel-by-pixel bias and enhance accuracy. The DLF was applied to four widely used SPPs (TRMM, CMORPH, CHIRPS, and PERSIANN-CDR) in MRB. For the original SPPs, the TRMM product outperformed the other SPPs. Results revealed that the DLF effectively bridged the spatial-temporal gap between the SPPs and the gauge-based dataset (APHRODITE). Among the four corrected products, ADJ-TRMM demonstrated the best performance, followed by ADJ-CDR, ADJ-CHIRPS, and ADJ-CMORPH. The DLF offered a robust and adaptable solution for bias correction in the MRB and beyond, capable of detecting intricate patterns and learning from data to make appropriate adjustments. With the discontinuation of the APHRODITE product, DLF represents a promising solution for generating a more current and reliable dataset for MRB research. This research showcased the potential of deep learning-based methods for improving the accuracy of SPPs, particularly in regions like the MRB, where gauge-based datasets are limited or discontinued.

• 공업화학
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• 제10권5호
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• pp.666-671
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• 1999

본 연구에서 술폰화된 poly(phenylene sulfide)(SPPS)는 10%의 발연황산으로 PPST를 술폰화한 후 NaOH 수용액으로 demethylation하여 제조하였다. 유기용매에 용해되는 PPST는 methyl-(phenylthio)phenyl sulfoxide(MPPSO)의 자가축합 반응으로 합성되었다. SPPS는 $1200cm^{-1}$에서 $-SO_{3}H$의 비대칭 O=S=O 신축진동에 의한 흡수피크와 $621cm^{-1}$에서 S-O 신축진동에 의한 흡수피크가 관찰된 것으로 보아 술폰산기가 도입된 것을 알 수 있다. PPST의 술폰화를 $150^{\circ}C$에서 12시간 반응했을 때 반복단위당 1.48개의 술폰산기가 도입되었으며, 고온 GPC로 측정된 PPST와 SPPS의 중량평균분자량(Mw)은 각각 118323과 131204이었다. SPPS의 암모니아 가스 흡착능은 $9.67mmol\;NH_{3}/g$이었고, 활성탄, 실리카겔보다 월등히 높았다.

• Journal of the Optical Society of Korea
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• 제18권5호
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• pp.429-435
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• 2014

We examined the effective utilization of Particle Swarm Optimization (PSO) to enhance the light absorption performance in thin CuIn1-xGaxSe2 (CIGS) solar cells with dual (top and bottom) gratings. The PSO tuned structure was demonstrated to be capable of achieving high and ultra broadband absorption spectra due to well-spaced and well-defined absorption peaks, which were SPPs and photonic modes induced by the metal and dielectric gratings. For only TM polarization and both polarizations, the fully optimized net absorptions exhibit 85.6% and 78.1%, which correspond to ~35.4% and ~23.5% improvement compared to optimized flat structures, respectively.

• 한국식품조리과학회지
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• 제33권1호
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• pp.78-86
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• 2017

Purpose: To increase the availability of Korean sweet potato (SP), the quality characteristics of the sweet potato pastes (SPPs) and rice madeira cake (RMC) using them were investigated. Methods: Ten different SPPs, orange fleshed Sinwhangmi, Juwhangmi, purple fleshed Sinjami and Yeonjami, Cream fleshed Sinyulmi, Sinchunmi, and newly developed Geonwhangmi, Dahomi, Daeyumi, and Pongwonmi were used. Their pastes were prepared by washed, peeled, steamed, crushed, vacuum packed and stored in a freezer until use. Results: The SPPs and RMC with them were significant difference from different cultivars with color value, rheology and texture properties, and preference test. The SPP showed the highest lightness value in Sinchunmi (55.89) and the highest viscosity in Geonhwangmi (55.33 poise). The RMCs with SPPs had lower values in hardness and chewiness than the RMC without SPP. Overall quality of preference test showed the highest values in RMC with Sinyulmi and Sincheonmi. Conclusion: The best quality of sweet potato shaped rice madeira cake was made using Sinyulmi and Sinchunmi pastes. It is suggested that sweet potato paste is possible to use as the biomaterials for application of processed foods.

• Bulletin of the Korean Chemical Society
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• 제22권1호
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• pp.53-58
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• 2001

Sulfonated poly(phenylene sulfide) (SPPS) polymers were prepared by sulfonation of poly[methyl[4-(phenylthio) phenyl]sulfonium trifluoromethanesulfonate] (PPST) with fumic sulfonic acid (10% $SO_3-H_2SO_4$) and demethylation with aqueous NaOH solution. The equilibrium constants of ion exchange reactions between alkali metal cations ($Li^+,\;Na^+,\;and\;K^+$) and SPPS ion exchanger in organic solvents such as tetrahydrofuran (THF) and dioxane were measured. The equilibrium constants of ion exchange reactions increased as the polarity of the solvent increased, and the reaction temperature decreased. The equilibrium constants of the ion exchange reaction ($K_{eq}$) also increased in the order of $Li^+,\;Na^+,\;and\;K^+$. To elucidate the spontaneity of the exchange reaction in organic solvents, the enthalpy, entropy, and Gibbs free energy were calculated. The enthalpy of reaction ranged from -0.88 to -1.33 kcal/mol, entropy ranged from 1.42 to 4.41 cal/Kmol, and Gibbs free energy ranged from -1.03 to -2.55 kcal/mol. Therefore, the exchange reactions were spontaneous because the Gibbs free energies were negative. The SPPS ion exchanger and alkali metal ion bounding each other produced good ion exchange capability in organic solvents.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.159-159
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• 2023

The Amazon River basin is one of the largest basins in the world, and its ecosystem is vital for biodiversity, hydrology, and climate regulation. Thus, understanding the hydrometeorological process is essential to the maintenance of the Amazon River basin. However, it is still tricky to monitor the Amazon River basin because of its size and the low density of the monitoring gauge network. To solve those issues, remote sensing products have been largely used. Yet, those products have some limitations. Therefore, this study aims to do bias corrections to improve the accuracy of Satellite Precipitation Products (SPPs) in the Amazon River basin. We use 331 rainfall stations for the observed data and two daily satellite precipitation gridded datasets (CHIRPS, TRMM). Due to the limitation of the observed data, the period of analysis was set from 1st January 1990 to 31st December 2010. The observed data were interpolated to have the same resolution as the SPPs data using the IDW method. For bias correction, we use convolution neural networks (CNN) combined with an autoencoder architecture (ConvAE). To evaluate the bias correction performance, we used some statistical indicators such as NSE, RMSE, and MAD. Hence, those results can increase the quality of precipitation data in the Amazon River basin, improving its monitoring and management.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.148-148
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• 2022

Spatiotemporal precipitation data is one of the primary quantities in hydrological as well as climatological studies. Despite the fact that the estimation of these data has made considerable progress owing to advances in remote sensing, the discrepancy between satellite-derived precipitation product (SPP) data and observed data is still remarkable. This study aims to propose an effective deep learning model (DLM) for bias correction of SPPs. In which TRMM (The Tropical Rainfall Measuring Mission), CMORPH (CPC Morphing technique), and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) are three SPPs with a spatial resolution of 0.25o exploited for bias correction, and APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) data is used as a benchmark to evaluate the effectiveness of DLM. We selected the Mekong River Basin as a case study area because it is one of the largest watersheds in the world and spans many countries. The adjusted dataset has demonstrated an impressive performance of DLM in bias correction of SPPs in terms of both spatial and temporal evaluation. The findings of this study indicate that DLM can generate reliable estimates for the gridded satellite-based precipitation bias correction.

• 통합자연과학논문집
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• 제9권2호
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• pp.86-93
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• 2016

The peptide sequences, GHK(Gly-His-Lys) and KTTKS(Lys-Thr-Thr-Lys-Ser), using a collagen stimulator recently were manipulated at N-terminal as a multifunctional peptide derivative with PEG(polyethyleneglycol) linker connected to gallic acid which presents anti-inflammatory activity. The multifunctional peptide derivatives were obtained in a normal peptide preparation method through SPPS(solid phase peptide synthesis) using Fmoc chemistry and a carboxyl group insertion reaction of PEG-3,4,5-triacetoxy benzoate by using potassium tert-butoxide and ethyl bromoacetate, which was separated by Sephadex DEAE. It gave a good compromise to a cosmetic application for cell cytotoxicity, anti-wrinkle, and anti-inflammation.

• ETRI Journal
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• 제29권6호
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• pp.808-810
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• 2007

We demonstrate 10 Gbps optical signal transmission via long-range surface plasmon polaritons (LR-SPPs) in a very thin metal strip-guided geometry. The LR-SPP waveguide was fabricated as a 14 nm thick, 2.5 ${\mu}m$ wide, and 4 cm long gold strip embedded in a polymer and pigtailed with single-mode fibers. The total insertion loss of 16 dB was achieved at a wavelength of 1.55 ${\mu}m$ as a carrier wave. In a 10 Gbps optical signal transmission experiment, the LR-SPP waveguide exhibits an excellent eye opening and a 2.2 dB power penalty at $10^{-12}$ bit error rate. We confirm, for the first time, that LR-SPPs can efficiently transfer data signals as well as the carrier light.