• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.97-109
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• 2017

Green tides that developed along the coast of China in 2015 were detected and tracked using vegetation indices from GOCI and Landsat images. Green tides first appeared near the Jiangsu Province on May 14 before increasing in size and number and moving northward to the Shandong Peninsula in mid-June. Typhoon Cham-hom passed through the Yellow Sea on July 12, significantly decreasing the algal population. An algae patch moved east toward Korea and on June 18 and July 4, several masses were found between the southwestern shores of Korea and Jeju Island. The floating masses found in Korean waters were concentrated at the boundary of the open sea and the Jindo cold pool, a phenomenon also observed at the boundary of coastal and offshore waters in China. Sea surface temperatures, derived from NOAA SST data, were found to play a role in generation of the green tides.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.64-64
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• 2019

Screening and identification of genetic resources based on their phytoconstituents and morphological characters potentially provide baseline data for researchers, breeders, and nutraceutical companies who wish to formulate a nutrient-dense diet and health beneficial supplement. Thus, we evaluated the amount of total phenolic content and major phenolic compounds; examined if phenolic compounds could be used as distinguishing factors for perilla genetic resources; and investigated the relation between some quantitative and qualitative morphological characters with the contents of phenolic compounds in 360 accessions obtained from National Agrobiodiversity Center gene bank, Jeonju, Korea. Total phenolic content (TPC) was estimated using Folin-Ciocalteu colorimetric assay. Individual phenolic compounds were determined using an Ultra-High Performance Liquid Chromatography system equipped with Photodiode Array detector. Considerable variations were observed in TPC (7.99 to 117.47 mg GAE/g DE), rosmarinic acid (RA) (ND to 19.19 mg/g DE), caffeic acid (CA) (ND to 0.72 mg/g DE), apigenin-7-O-diglucuronide (ADG) (ND to 1.24 mg luteolin equivalent (LUE)/g DE), scutellarein-7-O-glucuronide (SG) (ND to 4.32 mg LUE/g DE), and apigenin-7-O-glucuronide (AG) (ND to 1.60 mg LUE/g DE). RA was the most dominant phenolic compound in most accessions (95.3%) followed by SG. The adaxial leaf color was light green, green and dark green in 13.8%, 65.0%, and 21.1 % of the accessions, respectively. 78.8% of the accessions had light green color at the abaxial side with the remaining being described as green. Most of the accessions (96.9%) were cordate shape, the remaining being eclipse. Intensities of green pigment at abaxial and adaxial leaf surfaces were correlated with contents of individual phenolic compounds and TPC whereas leaf length and width had no correlation with TPC, CA and RA, and negatively correlated with ADG, AG, and SG. Leaf shape was not related with content of phenolic compounds, color of leaves, or the length or width of leaves. Accessions IT57426, IT157434, IT267710, and IT267712 which contained relatively high contents of TPC and major phenolic compounds (RA and SG) could be used for further research in breeding and bioassay test. Our study result showed the contents of total phenolics and individual phenolic compounds along with the morphological characters could be useful distinguishing factors for perilla genetic resources.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.293-307
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• 2020

Every year, the floating macroalgae, green and golden tide, are massively detected at the Yellow Sea and East China Sea. After influx of them to the aquaculture facility or beach, it occurs enormous economic losses to remove them. Currently, remote sensing is used effectively to detect the floating macroalgae flowed into the coast. But it has difficulties to detect the floating macroalgae exactly because of the wavelength overlapped with other targets in the ocean. Also, it is difficult to distinguish between green and golden tide because they have similar spectral characteristics. Therefore, we tried to distinguish between green and golden tide applying the Deep learning method to the satellite images. To determine the network, the optimal training conditions were searched to train the AlexNet. Also, Gaofen-1 WFV images were used as a dataset to train and validate the network. Under these conditions, the network was determined after training, and used to confirm the test data. As a result, the accuracy of test data is 88.89%, and it can be possible to distinguish between green and golden tide with precision of 66.67% and 100%, respectively. It is interpreted that the AlexNet can be pick up on the subtle differences between green and golden tide. Through this study, it is expected that the green and golden tide can be effectively classified from various objects in the ocean and distinguished each other.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.9 no.3
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• pp.107-111
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• 2010

This paper is concerned with data center remote management service for demanding forecasting and reduction of energy usage. More particularly, intelligent server rack, mounted on inside of the data center, collects information about energy usage and temperature per server. Using this information, management platform forecasts energy demand in the future and automatically makes report according green environment raw. By providing the remote management service through remote terminals, users are not tied to a time and place to control device inside the data center. In this way, the data center remote management service enhances operability of the facility.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.985-996
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• 2021

While green packaging related concerns are mainly studied in developed countries, there is a lack of knowledge to observe purchase behavior toward green packaging in developing countries, especially in Vietnam. Buying green packaged products in FMCG is not required to trade-off between sustainability and product performance. Hence, this present research aims to understand the gap attitude - behavior existing on FMCG green packaged products among Vietnamese young consumers with psychosocial factors (environmental concern, environmental knowledge of green packaging and green trust) and contextual factors (availability of desired green packaging and product attributes). With a sample size of 396 respondents, data was collected by convenient sampling method and then was analyzed using structural equation modeling. The results reveal that all psychosocial factors are positive related to attitudes while purchase behavior is positively influenced. The findings also report that contextual factors have positive impacts on purchase behavior, which proves the important role of contextual factors in influencing consumer choices. It suggests that green packaging is receptive to Vietnamese young consumers but it should be considered within product-related context to enhance the difference in sustainability among similar FMCG products. Practical implications for marketers and future researches have also been discussed at the end of study.

• Journal of Plant Biotechnology
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• v.33 no.4
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• pp.277-281
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• 2006

Fourier transform - infrared spectroscopy (FT-IR) provides biochemical profiles containing overlapping signals from a majority of the compounds that are present when whole cell extracts are analyzed. We attempted to determine the ripeness of strawberry fruit flesh by FT-IR. Fruit ripeness was divided into four developmental stages based on fruit skin color: 'yellow-green', 'pink-green', 'pink', and 'red' stages. Principal component analysis of FT-IR data of inside fruit flesh extracts clustered samples of four different developmental stages into three discrete groups: (1) 'yellow-green' group, (2) 'pink-green' group, and (3) 'pink' and 'red' group. The most remarkable difference between four different developmental stages was found in the carbohydrate fingerprint region $(1,000-1,100cm^{-1})$ of the FT-IR spectrum, indicating that differences in carbohydrate compounds represented the ripeness of strawberry fruit. Overall results indicate that FT-IR in combination with PCA enables discrimination of the ripeness of strawberry fruit flesh.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.690-691
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• 2011

제주 스마트그리드 실증사업은 기기 설치, 시험운전 단계에서 실증운전 단계로 넘어가는 과정 중에 있다. 제주 가상전력시장기반 하에서 수요측 자원의 본격적인 Full-Scale 전력거래가 시작될 예정이며, 거래 수익 최대화를 위해서는 에너지저장장치의 적절한 운영이 필수적으로 요구된다. 당사에서는 에너지저장장치의 시간대별 운영 패턴 도출을 통해 가상전력시장에 참여할 수 있는 에너지저장장치 운영 프로그램을 개발하였다. 본 논문에서는 가상전력시장의 개요, 에너지저장장치 운영 프로그램의 개념과 실행 스케쥴, 그리고 입출력 데이터와 Flow Chart 등에 대하여 기술하였다. 향후 실증단계 진행 중에 신뢰할 만한 Raw Data와 거래 reference를 확보, 분석하고 적용하는 과정을 거치면서 운영 알고리즘을 조금 더 개선해야 할 필요가 있다.

• Advances in nano research
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• v.10 no.3
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• pp.253-261
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• 2021

Polydimethylsiloxane (PDMS) is one of the most widely adopted silicon-based organic polymeric elastomers. Elastomeric nanostructures are normally required to accomplish an explicit mechanical role and correspondingly their mechanical properties are crucial to affect device and material performance. Despite its wide application, the mechanical properties of PDMS are yet fully understood. In particular, the time dependent mechanical response of PDMS has not been fully elucidated. Here, utilizing state-of-the-art PeakForce Quantitative Nanomechanical Mapping (PFQNM) together with Force Volume (FV) and Fast Force Volume (FFV), the elastic moduli of PDMS samples were assessed in a time-dependent fashion. Specifically, the acquisition frequency was discretely changed four orders of magnitude from 0.1 Hz up to 2 kHz. Careful calibrations were done. Force data were fitted with a linearized DMT contact mechanics model considering surface adhesion force. Increased Young's modulus was discovered with increasing acquisition frequency. It was measured 878 ± 274 kPa at 0.1 Hz and increased to 4586 ± 758 kPa at 2 kHz. The robust local probing of mechanical measurement as well as unprecedented high-resolution topography imaging open new avenues for quantitative nanomechanical mapping of soft polymers, and can be extended to soft biological systems.

• ALGAE
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• v.20 no.3
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• pp.197-205
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• 2005

Temporal variability in lake phytoplankton is controlled by a complex between hydrological and chemical factors, and biological interactions. We explored annual change of phytoplankton in Lake Daecheong, using phytoplankton analysis data from 1997 to 2002 (except 2000). The standing crop of phytoplankton was ranged from 3.5 x 10 to 1.5 x 106 cells mL$^{-1}$ and the highest mean value was at site 1. The class composition ratios of phytoplankton standing crop were divided into three classes. From January to March, diatoms showed a dominance (68.1-77.7%). From April to June, diatoms were mixed with cryptomonad etc. or blue-green algae. From July to October, blue-green algae showed a dominance (54.7-84.0%). In the case of green algae, the class composition ratios were below 10%. But green algae appeared all the year round.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.201-206
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• 2021

The significance of high-quality development and green total factor productivity has attracted widespread attention and research, while few studies on green total factor productivity that considers the use of water resources have been conducted in the context of water shortages and water stress. In this study, the green total factor productivity of water use from 2005 to 2015 in mainland China is evaluated based on the global Malmquist-Luenberger productivity index. Results show that: (1) China's green total factor productivity of water use has been improving since 2005 with an annual global Malmquist-Luenberger productivity index of 1.0104. (2) At the regional level, the eastern zone in mainland China owns the highest green total factor productivity of water use, while that in the intermediate zone ranks last. (3) The green total factor productivity of water use in the southern region (1.0113) significantly higher than that in the northern region (1.0095), and also higher than the national average level in the same period. BPC index has been the most important incluencing factor of green total factor productivity of water use at both national level and regional level since 2011.