• Membrane and Water Treatment
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• v.10 no.1
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• pp.1-11
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• 2019

The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) predicted that recent extreme hydrological events would affect water quality and aggravate various forms of water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed and sunlight) were established using the Representative Concentration Pathways (RCP) 8.5 climate change scenario suggested by the AR5 and calculated the future runoff for each target period (Reference:1989-2015; I: 2016-2040; II: 2041-2070; and III: 2071-2099) using the semi-distributed land use-based runoff processes (SLURP) model. Meteorological factors that affect water quality (precipitation, temperature and runoff) were inputted into the multiple linear regression analysis (MLRA) and artificial neural network (ANN) models to analyze water quality data, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), total nitrogen (T-N) and total phosphorus (T-P). Future water quality prediction of the Anseongcheon River basin shows that DO at Gongdo station in the river will drop by 35% in autumn by the end of the $21^{st}$ century and that BOD, COD and SS will increase by 36%, 20% and 42%, respectively. Analysis revealed that the oxygen demand at Dongyeongyo station will decrease by 17% in summer and BOD, COD and SS will increase by 30%, 12% and 17%, respectively. This study suggests that there is a need to continuously monitor the water quality of the Anseongcheon River basin for long-term management. A more reliable prediction of future water quality will be achieved if various social scenarios and climate data are taken into consideration.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.516-516
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• 2016

기후변화는 농업생산량 감소와 식량 안보 문제와 같이 농업에 심각한 영향을 미칠 수 있다. 또한 기존의 농업수리 및 관개배수 시설 운영에 영향을 줄 수 있다. 따라서 지속가능한 농업 수자원 관리를 위해서는 기후변화의 영향을 고려한 장기적인 계획 수립이 필요하다. 따라서 본 연구에서는 논벼 지역의 설계용수량의 확률론적 분석을 통한 논벼 필요수량 및 설계용수량에 대한 기후변화영향 평가를 실시하였다. 이를 위해서 본 연구에서는 23개 GCM의 36개 산출물을 활용하여 Multi-model ensemble 구축하였다. 먼저 GCM별 증발산량과 유효우량을 산정한 결과 중부지역에서는 IPSL-CM5A 모델의 기후변화자료를 활용할 경우 증발산량과 유효우량이 타 GCM 모델들과 비하여 크게 산정되었다. 남부지역에서는 CanESM2 모델을 적용할 경우 가장 많은 증발산량과 유효우량이 모의되는 것으로 나타났다. 이처럼 GCM별로 다양한 결과가 모의되기 때문에 농업시설 설계에 적용되는 설계용수량의 경우 안전성을 위하여 Multi-GCM models을 활용할 필요가 있다. Multi-model ensemble의 RCP 4.5와 RCP 8.5 시나리오를 적용한 결과, 모든 경우에서 1995s(1981-2014)에 비해 설계용수량은 점차적으로 증가하는 것으로 나타났다. 평균 증가율은 RCP 4.5에서 중부지역이 9.4%, 남부지역이 6.0% 증가하는 것으로 나타난 반면, RCP 8.5에서는 중부지역이 11.1%, 남부지역이 8.2% 증가하는 것으로 나타났다. 또한 여러 GCM 산출물간의 불확실성은 RCP 4.5보다는 RCP 8.5 시나리오가, 중부 지역보다는 남부 지역이, 논벼 증발산량 보다는 유효우량이 더 큰 것으로 분석되었다. 본 연구는 향후 미래 가뭄 위험성을 최소화하기 위한 농업 수자원관리 전략수립에 활용될 수 있을 것이다. 또한 본 연구결과는 기후변화 영향 평가에 있어서 적합한 GCM 자료를 선택하는데 있어, 불확실성을 가늠할 수 있는 유용한 척도로 이용될 수 있을 것으로 기대된다.

• Korean Journal of Medicinal Crop Science
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• v.28 no.6
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• pp.428-434
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• 2020

Background: This study aimed to investigate the quality characteristics of Astragalus membranaceus Bunge leaf (AMBL) fermented with lactic acid bacteria and the applicability of its biologically active compounds. Methods and Results: An assessment of physicochemical properties such as pH, total acidity, free sugars, and isoflavonoid (calycosin-7-o-β-d-glucoside, ononin, calycosin, and formononetin) was conducted. Furthermore, the levels of antioxidant compounds, including polyphenols and flavonoids, and radical scavenging activities of the extracts using 2,2-Diphenyl-1-picryl-hydrazyl-hydrate and 2,2-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) were investigated. The calycosin content in the water extract of AMBL fermented with Leuconostoc mesenteroides increased by approximately twice as much as the control. Conclusions: These results indicate that L. mesenteroides can be used to improve biological activity through fermentation, and that AMBL can be used as a functional materials and edible resource in industrial areas.

• Journal of Biomedical Engineering Research
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• v.42 no.3
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• pp.80-85
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• 2021

We developed a model to classify the absence of cervical cancer using deep learning from the cervical image to which the histogram equalization algorithm was applied, and to compare the performance of each model. A total of 4259 images were used for this study, of which 1852 images were normal and 2407 were abnormal. And this paper applied Image Sharpening(IS), Histogram Equalization(HE), and Contrast Limited Adaptive Histogram Equalization(CLAHE) to the original image. Peak Signal-to-Noise Ratio(PSNR) and Structural Similarity index for Measuring image quality(SSIM) were used to assess the quality of images objectively. As a result of assessment, IS showed 81.75dB of PSNR and 0.96 of SSIM, showing the best image quality. CLAHE and HE showed the PSNR of 62.67dB and 62.60dB respectively, while SSIM of CLAHE was shown as 0.86, which is closer to 1 than HE of 0.75. Using ResNet-50 model with transfer learning, digital image-processed images are classified into normal and abnormal each. In conclusion, the classification accuracy of each model is as follows. 90.77% for IS, which shows the highest, 90.26% for CLAHE and 87.60% for HE. As this study shows, applying proper digital image processing which is for cervical images to Computer Aided Diagnosis(CAD) can help both screening and diagnosing.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.1-10
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• 2021

Agricultural reservoirs have a great influence on the water circulation in the watershed. It is necessary to evaluate the impact on water circulation by the agricultural reservoir. Therefore, in this study, we simulated the agricultural watershed through linkage of Hydrological Simulation Program Fortran (HSPF) and Module-based hydrologic Analysis for Agricultural watershed (MASA) and evaluated the contribution of the agricultural reservoir to water circulation by watershed water circulation index. As a result of simulating the Idong reservoir watershed through the HSPF-MASA linkage model, the model performance during the validation period was R2 0.74 upstream, 0.78 downstream, and 0.76 reservoir water level, respectively. To evaluate the contribution of agricultural reservoirs, three scenarios (baseline, present state, and present state without reservoir) were simulated, and the water balance differences for each scenario were analyzed. In the evaluation through the agricultural water circulation rate in the watershed, it was found that the water circulation rate increased by 1.1%, and the direct flow rate decreased by 13.6 mm due to the agricultural reservoir. In the evaluation through the Budyko curve, the evaporation index increased by 0.01. Agricultural reservoirs reduce direct runoff and increase evapotranspiration, which has a positive effect on the water circulation.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.2
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• pp.194-207
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• 2021

It is necessary to assess and manage the different elements of the marine ecosystem, such as climate change, habitat, primary and secondary production, energy flow, food web, potential yield, and fishing, to maintain the health of the ecosystem as well as support sustainable development of fishery. We set up an ecosystem model around the Korean peninsula to produce scientific predictions necessary for the assessment and management of marine ecosystems and presented the usability of the model with scenario experiments. We used the Atlantis ecosystem model based on the marine food web; Atlantis is a three-dimensional end-to-end model that includes the information and processes within an entire system, from an abiotic environment to human activity. We input the ecological and biological parameters, such as growth, mortality, spawning, recruitment, and migration, to the Atlantis model via functional groups using existing research and local measurements. During the simulation period (2018-2019), we confirmed that the model reproduced the observed data reasonably and reflected the actual ecosystem characteristics appropriately. We thus identified the usability of a marine ecosystem model with experiments on different environmental change scenarios.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.187-195
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• 2021

In order to assess the cell toxicity of 10 instruments made of polymers, the MTT assay which utilizes the L-929 cell was selected. Specimens were eluted at a temperature of 37℃ for 24 hours at a rate of 4g per 20mL, RPMI 1640, and then was positively and negatively contrasted with a control test solution, in accordance with the Notification No. 2020-12 Protocols of Medical Apparatus Biological Safety from the Ministry of Drug and Food Safety. As a result of 24 hours of incubation in 37℃, 5% CO₂ Incubator and assessment using an ELISA reader, the results of Intraoral camera indiciated a cellular viability of more than 70% at a 50% eluate. But, the Plastic impression tray, 3D printing tweezer, Impression disposable syringe, Dental floss holder, Hand implant scaler, Surgical retractor, Oral scanner tip, Dental mirror, and the Water pick tip all reported a cellular viability of more than 70% at a 100% eluate, which indicates that do not exhibit cytotoxicity, thus allowing it to be used in contact with the mucous membrane of the oral cavity.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.443-451
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• 2021

Finger millet (Eleusine coracana) is widely cultivated in tropical regions worldwide owing to its high nutritional value. Finger millet is more tolerant against biotic and abiotic stresses such as pests, drought, and salt than other millet crops; therefore, it was proposed as a candidate crop to adapt to climate change in Korea. In 2019, we used expressed sequence tag simple sequence repeat (EST-SSR) markers to evaluate the genetic diversity and structure of 102 finger millet accessions from two geographical regions (Africa and South Asia) to identify appropriate accessions and enhance crop diversity in Korea. In total, 40 primers produced 116 alleles, ranging in size from 135 to 457 bp, with a mean polymorphism information content (PIC) of 0.18225. Polymorphism was detected among the 40 primers, and 13 primers were found to have PIC values > 0.3. Principal coordinate and phylogenetic analyses, based on the combined data of both markers, grouped the finger millet accessions according to their respective collection areas.Therefore, the 102 accessions were classified into two groups, one from Asia and the other from Africa. We have conducted an in-depth study on the finger millet landrace pedigree. By sorting out and using the molecular characteristics of each pedigree, it will be useful for the management and accession identification of the plant resource. The novel SSR markers developed in this study will aid in future genetic analyses of E. coracana.

• Journal of Biomedical Engineering Research
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• v.43 no.1
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• pp.27-34
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• 2022

Drunk driving defines a driver as unable to drive a vehicle safely due to drinking. To crack down on drunk driving, alcohol concentration evaluates through breathing and crack down on drinking using S-shaped courses. A method for assessing drunk driving without using BAC or BrAC is measurement via biosignal. Depending on the individual specificity of drinking, alcohol evaluation studies through various biosignals need to be conducted. In this study, we measure biosignals that are related to alcohol concentration, predict BrAC through SVM, and verify the effectiveness of the S-shaped course. Participants were 8 men who have a driving license. Subjects conducted a d2 test and a scenario evaluation of driving an S-shaped course when they attained BrAC's certain criteria. We utilized SVR to predict BrAC via biosignals. Statistical analysis used a one-way Anova test. Depending on the amount of drinking, there was a tendency to increase pupil size, HR, normLF, skin conductivity, body temperature, SE, and speed, while normHF tended to decrease. There was no apparent change in the respiratory rate and TN-E. The result of the D2 test tended to increase from 0.03% and decrease from 0.08%. Measured biosignals have enabled BrAC predictions using SVR models to obtain high Figs in primary and secondary cross-validations. In this study, we were able to predict BrAC through changes in biosignals and SVMs depending on alcohol concentration and verified the effectiveness of the S-shaped course drinking control method.

• Journal of Biomedical Engineering Research
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• v.42 no.6
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• pp.268-276
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• 2021

Functional near-infrared spectroscopy-based brain-computer interface (fNIRS-based BCI) has been receiving much attention. However, we are practically constrained to obtain a lot of fNIRS data by inherent hemodynamic delay. For this reason, when employing machine learning techniques, a problem due to the high-dimensional feature vector may be encountered, such as deteriorated classification accuracy. In this study, we employ an elastic net-based feature selection which is one of the embedded methods and demonstrate the utility of which by analyzing the results. Using the fNIRS dataset obtained from 18 participants for classifying brain activation induced by mental arithmetic and idle state, we calculated classification accuracies after performing feature selection while changing the parameter α (weight of lasso vs. ridge regularization). Grand averages of classification accuracy are 80.0 ± 9.4%, 79.3 ± 9.6%, 79.0 ± 9.2%, 79.7 ± 10.1%, 77.6 ± 10.3%, 79.2 ± 8.9%, and 80.0 ± 7.8% for the various values of α = 0.001, 0.005, 0.01, 0.05, 0.1, 0.2, and 0.5, respectively, and are not statistically different from the grand average of classification accuracy estimated with all features (80.1 ± 9.5%). As a result, no difference in classification accuracy is revealed for all considered parameter α values. Especially for α = 0.5, we are able to achieve the statistically same level of classification accuracy with even 16.4% features of the total features. Since elastic net-based feature selection can be easily applied to other cases without complicated initialization and parameter fine-tuning, we can be looking forward to seeing that the elastic-based feature selection can be actively applied to fNIRS data.