• Journal of the Society of Cosmetic Scientists of Korea
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• v.49 no.3
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• pp.213-223
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• 2023

A total of 81 handmade soaps on sale on the market were collected from January to November 2022. To compare quality characteristics, all ingredients were referred to, and the pH, dry reduction, heavy metals (lead, arsenic, cadmium, antimony, and mercury), and contents of free alkali were measured. All soaps had a slightly alkaline pH of 7.9 to 11.2, average drying loss was 17.6%, and free alkali was hardly detected. The average values of all heavy metals were 0.104 ㎍/g for lead, 0.035 ㎍/g for arsenic, 0.002 ㎍/g for cadmium, 0.048 ㎍/g for antimony, and 0.0003 ㎍/g for mercury. The results of handmade soap were below the recommended in regulations on safety standards for cosmetics of Ministry of Food and Drug Safety.

• Journal of Marine Life Science
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• v.3 no.2
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• pp.74-80
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• 2018

Mercury (Hg) poses a threat to marine ecosystem due to continuous inflow from various industries and bioaccumulation to higher trophic level via food web. Mercury can adversely affect growth, development, reproduction and metabolism to aquatic organisms. In the present study, acute toxicity and oxidative stress markers (total glutathione content, and activities of GST, GR and GPx) were investigated in brackish water flea Disphanosoma celebensis exposed to HgCl₂ for 24 h. As results, Hg showed negative effect in survival of D. celebensis. 24 h-LC₅₀ value was determined as 0.589 mg/l (95% C.I. 0.521~0.655 mg/l). After exposure to Hg (0.08 and 0.4 mg/l) for 24 h, total glutathione content was significantly decreased, whereas GST, GPx and GR activities were enhanced. These findings indicate that Hg induced oxidative stress in D. celebensis, and oxidative stress markers may be involved in cellular defense against Hg - mediated toxicity. This study provides a better understanding of molecular mode of action of Hg toxicity in this specie and potent of molecular markers for heavy metal monitoring in marine ecosystem.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.183-192
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• 2023

The remotely sensed data, such as satellite imagery and aerial photos, can be used to extract and detect some objects in the image through image interpretation and processing techniques. Significantly, the possibility for utilizing digital map updating and land monitoring has been increased through automatic object detection since spatial resolution of remotely sensed data has improved and technologies about deep learning have been developed. In this paper, we tried to extract plastic greenhouses into aerial orthophotos by using fully convolutional densely connected convolutional network (FC-DenseNet), one of the representative deep learning models for semantic segmentation. Then, a quantitative analysis of extraction results had performed. Using the farm map of the Ministry of Agriculture, Food and Rural Affairsin Korea, training data was generated by labeling plastic greenhouses into Damyang and Miryang areas. And then, FC-DenseNet was trained through a training dataset. To apply the deep learning model in the remotely sensed imagery, instance norm, which can maintain the spectral characteristics of bands, was used as normalization. In addition, optimal weights for each band were determined by adding attention modules in the deep learning model. In the experiments, it was found that a deep learning model can extract plastic greenhouses. These results can be applied to digital map updating of Farm-map and landcover maps.

• Journal of Venture Innovation
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• v.5 no.2
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• pp.85-99
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• 2022

Dryers becoming commercially available for experimental and industrial use are classified to general drying oven, hot-air dryer, vacuum dryer, freezing dryer, etc. and kinds of them are various from the function, size and volume, etc. But the moisture measurement is not applied although it is important factor for the quality control and the performance improvement of products, and then now is very passive because the weight is weighed arbitrarily after dry-end. Generally the method for measuring moisture is divided by a direct measurement method and a indirect measurement method, and the former such as the change of weight or volume on the front and rear of separation of moisture, etc. is mainly used. Relatively a indirect measurement is very limited to apply due to utilize measurement apparatuses using temperature conductivity and micro-wave etc. In this research, we easily designed the moisture measurement system using the open-source based Arduino, and monitored moisture fluctuations and weight profiles in the real-time without the effect of external environment. Concretely the temperature-humidity and load cell sensors were packaged into a drying oven and the various change values were measured, and their sensors capable to operate 60℃ and 80℃ were selected to suitable for the moisture sensitive materials and the food dry. And also the performance safety using the organic samples of banana, pear, sawdust could be secured because the changes of evaporation rate as the dry time and temperature, and the measurement values of load cell appeared stable response characteristics through repeated experiments. Hereafter we judge that the reliability can be improved increasingly through the expansion of temperature-humidity range and the comparative analysis with CFD(Computational Fluid Dynamics) program.

• Korean Journal of Environment and Ecology
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• v.37 no.5
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• pp.337-346
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• 2023

Although wildlife bridge are built as a way to reduce habitat fragmentation caused by road construction, there is still a lot of debate about their effectiveness. Monitoring methods such as footprint traps and camera traps are used evaluate the effectiveness of wildlife bridge, but there is a limit to evaluate of effectiveness. In this study, the degree of use the wildlfe bridge was surveyed by striped field mouse that is likely use the wildlife bridge and surrounding as a habitat with capture-mark-recapture method.(Apodemus agraius). The distance and route of movement were identified by connecting the capture points, and the environmental factors on the use of the wildlife bridge implemented a generalized linear model(GLM) with the capture number of captured as a dependent variable. Consequently of capture, no individuals crossing the wildlife bridge, striped field mouse use the wildlife bridge as a habitat.The environmental factors affecting the use of mice were vegetation cover(1~2m, 2~8m, over 8m), vegetation construction, maximum diameter at breast height were positively correlated and slope was nagatively correlated. In conclusion, it is expected that the effectiveness of the wildlife bridge will be further improved by planting shrubs and trees and preventing high slope and cut slope increasing the utilization of the rat, such as being used as a food source in the ecosystem.

• Korean Journal of Environmental Biology
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• v.41 no.3
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• pp.283-290
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• 2023

The Republic of Korea reclaimed land to increase its food self-sufficiency rate, but the yield was reduced due to abnormal climate. In this study, it was hypothesized that rapid and continuous monitoring technology could help improve yield. Using the vegetation index (VI) analysis, the drought stress index was calculated and the drought stress for corn grown in Hwaong, Saemangeum, and Yeongsan River reclaimed tidal land was predicted according to drying treatment. The vegetation index of corn did not decrease during the last 20 days of irrigation when soil moisture rapidly decreased, but decreased rapidly during the 20 days after irrigation. The reduction rate of the vegetation index according to the drying treatment was in the order of Saemangeum>Yeongsan River>Hwaong reclaimed tidal land, and normalized difference vegetation index(NDVI) decreased by approximately 50% in all reclaimed tidal lands, confirming that drought stress occurred due to the decrease in moisture content of the leaves. In addition, structure pigment chlorophyll index (SIPI) and photochemical reflectance index (PRI), which are calculated based on changes in light use efficiency and carotenoids, were reduced; drought stress caused a decrease in light use efficiency and an increase in carotenoid content. Therefore, vegetation index analysis was confirmed to be effective in evaluating and predicting drought stress in corn growing on reclaimed tidal land corn.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.182-196
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• 2023

Accurate and timely estimation of crop yields is crucial for various purposes, including global food security planning and agricultural policy development. Remote sensing techniques, particularly using vegetation indices (VIs), have show n promise in monitoring and predicting crop conditions. However, traditional VIs such as the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) have limitations in capturing rapid changes in vegetation photosynthesis and may not accurately represent crop productivity. An alternative vegetation index, the near-infrared reflectance of vegetation (NIRv), has been proposed as a better predictor of crop yield due to its strong correlation with gross primary productivity (GPP) and its ability to untangle confounding effects in canopies. In this study, we investigated the potential of NIRv in estimating crop yield, specifically for corn and soybean crops in major crop-producing regions in 14 states of the United States. Our results demonstrated a significant correlation between the peak value of NIRv and crop yield/area for both corn and soybean. The correlation w as slightly stronger for soybean than for corn. Moreover, most of the target states exhibited a notable relationship between NIRv peak and yield, with consistent slopes across different states. Furthermore, we observed a distinct pattern in the yearly data, where most values were closely clustered together. However, the year 2012 stood out as an outlier in several states, suggesting unique crop conditions during that period. Based on the established relationships between NIRv peak and yield, we predicted crop yield data for 2022 and evaluated the accuracy of the predictions using the Root Mean Square Percentage Error (RMSPE). Our findings indicate the potential of NIRv peak in estimating crop yield at the county level, with varying accuracy across different counties.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.2
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• pp.101-115
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• 2024

The ocean heatwave is emerging as a major issue due to global warming, posing a direct threat to marine ecosystems and humanity through decreased food resources and reduced carbon absorption capacity of the oceans. Consequently, the prediction of ocean heatwaves in the vicinity of the Korean Peninsula is becoming increasingly important for marine environmental monitoring and management. In this study, an LSTM model was developed to improve the underestimated prediction of ocean heatwaves caused by the coarse vertical grid system of the Korean Peninsula Ocean Prediction System. Based on the results of ocean heatwave predictions for the Korean Peninsula conducted in 2023, as well as those generated by the LSTM model, the performance of heatwave predictions in the East Sea, Yellow Sea, and South Sea areas surrounding the Korean Peninsula was evaluated. The LSTM model developed in this study significantly improved the prediction performance of sea surface temperatures during periods of temperature increase in all three regions. However, its effectiveness in improving prediction performance during periods of temperature decrease or before temperature rise initiation was limited. This demonstrates the potential of the LSTM model to address the underestimated prediction of ocean heatwaves caused by the coarse vertical grid system during periods of enhanced stratification. It is anticipated that the utility of data-driven artificial intelligence models will expand in the future to improve the prediction performance of dynamical models or even replace them.

• Journal of Nutrition and Health
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• v.57 no.4
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• pp.435-450
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• 2024

Purpose: This study developed the evaluation components and criteria for the Korean Healthy Diet (KHD) and assessed the current compliance of Koreans. Methods: The study reviewed domestic and international dietary guidelines and literature and conducted an online survey of 514 Korean adults to understand their nutritional perceptions, specifically the perceived importance of health and incorporation into usual diet. Data from the Korea National Health and Nutrition Examination Survey (KNHANES) were used to investigate food and nutrient intake patterns and examine the relationship between intake and metabolic syndrome (MetS). Based on these data, the components and criteria for a KHD were established by sex and age, and adherence was assessed. Results: The KHD evaluation included 13 dietary components: carbohydrates, sugar, fiber, protein, total fat, saturated fat, sodium, calcium, mixed grains, meat·fish·eggs·beans, vegetables, fruits, and dairy products. Applying the selected components and criteria to data from the KNHANES (2019-2021), the average KHD adherence score for Korean adults was 5.465 ± 0.023 out of a maximum score of 13. The score significantly increased with age (4.766 ± 0.044 for 19-29 years; 5.276±0.032 for 30-49 years; 6.109 ± 0.033 for 50-64 years), and women (5.642 ± 0.028) had higher scores than men (5.284 ± 0.030) (p < 0.05). Furthermore, the total score significantly differed between those with MetS (5.518 ± 0.045) and those without (5.568 ± 0.026) after adjusted for sex and age (p < 0.05). When scoring the dietary components, sugar (0.852 ± 0.004) and proteins (0.881 ± 0.004) scored relatively higher in the association with MetS, whereas calcium (0.148 ± 0.004) and mixed grains (0.225 ± 0.005) scored relatively lower. Conclusions: The KHD evaluation criteria could be used as a tool for screening and monitoring the overall diet quality of Koreans.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.2
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• pp.109-117
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• 2013

The Global Framework on Climate Services (GFCS) will guide the development of climate services that link science-based climate information and predictions with climate-risk management and adaptation to climate change. GFCS structure is made up of 5 pillars; Observations/Monitoring (OBS), Research/ Modeling/ Prediction (RES), Climate Services Information System (CSIS) and User Interface Platform (UIP) which are all supplemented with Capacity Development (CD). Corresponding to each GFCS pillar, the Commission for Agricultural Meteorology (CAgM) has been proposing "Global Initiatives in AgroMeteorology" (GIAM) in order to facilitate GFCS implementation scheme from the perspective of AgroMeteorology - Global AgroMeteorological Outlook System (GAMOS) for OBS, Global AgroMeteorological Pilot Projects (GAMPP) for RES, Global Federation of AgroMeteorological Society (GFAMS) for UIP/RES, WAMIS next phase for CSIS/UIP, and Global Centers of Research and Excellence in AgroMeteorology (GCREAM) for CD, through which next generation experts will be brought up as virtuous cycle for human resource procurements. The World AgroMeteorological Information Service (WAMIS) is a dedicated web server in which agrometeorological bulletins and advisories from members are placed. CAgM is about to extend its service into a Grid portal to share computer resources, information and human resources with user communities as a part of GFCS. To facilitate ICT resources sharing, a specialized or dedicated Data Center or Production Center (DCPC) of WMO Information System for WAMIS is under implementation by Korea Meteorological Administration. CAgM will provide land surface information to support LDAS (Land Data Assimilation System) of next generation Earth System as an information provider. The International Society for Agricultural Meteorology (INSAM) is an Internet market place for agrometeorologists. In an effort to strengthen INSAM as UIP for research community in AgroMeteorology, it was proposed by CAgM to establish Global Federation of AgroMeteorological Society (GFAMS). CAgM will try to encourage the next generation agrometeorological experts through Global Center of Excellence in Research and Education in AgroMeteorology (GCREAM) including graduate programmes under the framework of GENRI as a governing hub of Global Initiatives in AgroMeteorology (GIAM of CAgM). It would be coordinated under the framework of GENRI as a governing hub for all global initiatives such as GFAMS, GAMPP, GAPON including WAMIS II, primarily targeting on GFCS implementations.