Kim, Na-eun;Han, Hee-sun;Arulmozhi, Elanchezhian;Moon, Byeong-eun;Choi, Yung-Woo;Kim, Hyeon-tae
Journal of Bio-Environment Control
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v.31
no.1
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pp.1-7
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2022
Strawberry is a stand-out cultivating fruit in Korea. The optimum production of strawberry is highly dependent on growing environment. Smart farm technology, and automatic monitoring and control system maintain a favorable environment for strawberry growth in greenhouses, as well as play an important role to improve production. Moreover, physiological parameters of strawberry plant and it is surrounding environment may allow to give an idea on production of strawberry. Therefore, this study intends to build a machine learning model to predict strawberry's yield, cultivated in greenhouse. The environmental parameter like as temperature, humidity and CO2 and physiological parameters such as length of leaves, number of flowers and fruits and chlorophyll content of 'Seolhyang' (widely growing strawberry cultivar in Korea) were collected from three strawberry greenhouses located in Sacheon of Gyeongsangnam-do during the period of 2019-2020. A predictive model, Lasso regression was designed and validated through 5-fold cross-validation. The current study found that performance of the Lasso regression model is good to predict the number of flowers and fruits, when the MAPE value are 0.511 and 0.488, respectively during the model validation. Overall, the present study demonstrates that using AI based regression model may be convenient for farms and agricultural companies to predict yield of crops with fewer input attributes.
Geologic sequestration technologies such as CCS (carbon capture and storage), EGS (enhanced geothermal systems), and EOR (enhanced oil recovery) have been widely implemented in recent years, prompting evaluation of the mechanical stability of storage sites. As fluid injection can stimulate mechanical instability in storage layers by perturbing the stress state and pore pressure, poroelastic models considering various injection scenarios are required. In this study, we calculate the pore pressure, stress distribution, and vertical displacement along a surface using commercial finite element software (COMSOL); fault slips are subsequently simulated using PyLith, an open-source finite element software. The displacement fields, are obtained from PyLith is transferred back to COMSOL to determine changes in coseismic stresses and surface displacements. Our sequential use of COMSOL-PyLith-COMSOL for poroelastic modeling of fluid-injection and induced-earthquakes reveals large variations of pore pressure, vertical displacement, and Coulomb failure stress change during injection periods. On the other hand, the residual stress diffuses into the remote field after injection stops. This flow pattern suggests the necessity of numerical modeling and long-term monitoring, even after injection has stopped. We found that the time at which the Coulomb failure stress reaches the critical point greatly varies with the hydraulic and poroelastic properties (e.g., permeability and Biot-Willis coefficient) of the fault and injection layer. We suggest that an understanding of the detailed physical properties of the surrounding layer is important in selecting the injection site. Our numerical results showing the surface displacement and deviatoric stress distribution with different amounts of fault slip highlight the need to test more variable fault slip scenarios.
As the impermeable area of soil increases due to urbanization, the water circulation system of the city is deteriorating. The existing guidelines for low impact development (LID) facilities installed to solve these water problems or in previous studies, engineering aspects are more prominent than landscaping aspects. This study attempted to present an engineering and landscaping model for reducing pollutants by identifying the effects of vegetation on rainfall outflows and pollutant reduction in bioretention and the economic aspects of planting. Based on the results of artificial rainfall monitoring at Jeonju Seogok Park and the literature on vegetation rainfall runoff and pollutant reduction performance, the best vegetation for reducing pollution compared to cost was Lythrum salicaria L and Salix gracilistyla Miq. was the best vegetation for carbon storage. If you insist to design plants with only these two plantation, there is no choice but to take risks such as biodiversity. Herbaceous plants such as Lythrum salicaria L can be replaced by death of the plants or pests if considered planting various plants. The initial planting cost could expensive, but it is also necessary to mix and plant Salix gracilistyla Miq, which are woody plants that are advantageous in terms of maintenance, according to the surrounding environment and conditions. Based on the conclusions drawn in this study, it can be a reference material when considering the reduction of pollution by species and carbon storage of vegetation in LID facilities.
Purpose: An implant-supported prosthesis consists of an implant fixture, an abutment, an internal screw that connects the abutment to the implant fixture, and the upper prosthesis. Numerous studies have investigated the microorganisms present on the implant surface, surrounding tissues, and the subgingival microflora associated with peri-implantitis. However, there is limited information regarding the microbiome within the internal screw space. In this study, microbial samples were collected from the supragingival surfaces of natural teeth, the peri-implant sulcus, and the implant-abutment screw hole, in order to characterize the microbiome of the internal screw space in healthy subjects. Methods: Samples were obtained from the supragingival region of natural teeth, the peri-implant sulcus, and the implant screw hole in 20 healthy subjects. DNA was extracted, and the V3-V4 region of the 16S ribosomal RNA was sequenced for microbiome analysis. Alpha diversity, beta diversity, linear discriminant analysis effect size (LEfSe), and network analysis were employed to compare the characteristics of the microbiomes. Results: We observed significant differences in beta diversity among the samples. Upon analyzing the significant taxa using LEfSe, the microbial composition of the implant-abutment screw hole's microbiome was found to be similar to that of the other sampling sites' microbiomes. Moreover, the microbiome network analysis revealed a unique network complexity in samples obtained from the implant screw hole compared to those from the other sampling sites. Conclusions: The bacterial composition of the biofilm collected from the implant-abutment screw hole exhibited significant differences compared to the supra-structure of the implant. Therefore, long-term monitoring and management of not only the peri-implant tissue but also the implant screw are necessary.
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.
NA KYOUNG IM;HYUNKEUN JIN;GYUNDO PAK;YOUNG-GYU PARK;KYEONG OK KIM;YONGHAN CHOI;YOUNG HO KIM
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.
The present study aims to identify the effect of land cover categories on particulate matter (PM) concentrations by analyzing the correlation between monthly PM concentrations in Seoul's air quality monitoring network and the percentages of land cover categories by buffers around air quality monitoring stations. According to a monthly correlation analysis between land cover categories and PM concentrations, in the buffer 3km, PM10 showed a better correlation than PM2.5, there was a clear negative correlation with the forest area, the grassland and the urbanized area had some positive correlation with PM10, and the barren land and the urbanized area had some positive correlation with PM2.5. According to a monthly correlation analysis of dominant land cover sub-categories and sub-sub-categories within the buffer 3km, PM10 showed a clear negative correlation with the broad-leaved forest, and some positive correlation with the road was dominant. PM2.5 showed partly negative correlation with the broad-leaved forest and partly positive correlation with the commercial area. There was a very low or no correlation with other grassland and bare land subcategories. A monthly stepwise regression analysis on noticeable land cover sub-categories and sub-sub-categories with positive or negative correlations revealed that an increasing percentage of the broad-leaved forest had a clear effect on reducing PM10 concentrations, and the road was excluded from the selected variables. Although an increasing percentage of the commercial area had some effect on increasing monthly PM2.5 concentrations and an increasing percentage of the broad-leaved forest had an effect on decreasing the PM2.5 concentrations, their effect size was smaller than that on PM10. The forest area around the city center had the largest and clearest effect on reducing PM concentrations. The urbanized area's sub-categories and sub-sub-categories were also confirmed to have some effect on increasing PM concentrations.
Analysis about supply chain structure was achieved in product unit that is not 'business' dimension that is existent discussion target in surrounding and supply chain structure as that this study analyzes positively how supply chain structure according to business surroundings of product changes. This can do that analysis of product unit in synthetic supply chain management is essential when recognize the importance that supply chain management must consist by product special quality according to corporation's each product. Sort product environment and studied relation with supply chain structure to achieve study purpose hereupon. Structure variable of supply chain drew through existent literature study here. Executed question investigation for supply chain by product for study that is actual proof enemy, and figure method used analysis of variance (ANOVA) mainly. If summarize result of study, result that analyze relation between business environment of product and supply chain structure, according to business environment of product, showed that supply chain structure changes. Certified that relation of two group (environment group of uncertain product and environment group of stable product) of business environment of product and structure variable (that is number of participant of supply chain, lead time of supply chain, about administration's independence, response points of supply chain) of supply chain is significant relation all from all structure variables except number of participant of supply chain. Variable that express length of supply chain from structure Variable of supply chain is number of participant of supply chain and lead time of supply chain, and variable that display monitoring or trust aspect for supply chain is administration's independence degree and response points of supply chain. As analysis result, product that environment is uncertain is appearing more shortly than product that length of supply chain stabilizes, and also, monitoring or trust aspect for supply chain was proved that is consisting abuzzer than product that stabilize. Therefore, showed that put essential point in administration of 'hierarchy'putting first than 'market' when business environment designs supply chain structure in case of uncertain product, and proved that the other side business environment is focusing in administration way of 'market' putting first in case of stable product.
Journal of the Korean Society of Environmental Restoration Technology
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v.3
no.1
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pp.10-19
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2000
Due to the urbanization, concentrated population, and limited land exploitation in the modern society, the environment surrounding that we live in is getting polluted more and more, and it has become hard even to let urban children experience the nature. This research was conducted to help people recognize the importance of our natural resources through the environmental education of elementary school and to use school's practical open-space for the Indigenous Plants education. The results of this study are as follows : First, the status of a plant utilization in our institutional education : There were 362 species totally of 124 species of Trees, 156 species of Herbs, 63 species of Crops, and 19 species of Hydrophytes which appear in the elementary school text book. Of all, the most frequently appearing species of tree were the Malus pumila var. dulcissima, Pinus densijlora, Citrus unshiu, Diospyros kaki. Second, the effect of plant education using the land around schools : The result of research on the open-space of the 19 elementary schools located in Mapo-gu showed that most of the species planted are the Juniperus chinensisrose, Hibiscus syriacus. Pelargonium inquinans in the order of size, and the plants appearing in text book were grown in the botanical garden organized in 7 schools. Especially most of the Indigenous Plants were being planted in botanical garden, and Pinus densijlora, Abeliophyllum distichum, Polygonatum var. plurijlorum, Liriope platyphylla and so on. Last, the result of this research on recognition of Environment, Planting education and Indigenous plants : It showed that educational necessity of students and teachers about environment and Indigenous Plants was more than 80%. The management of botanical garden was conducted by some teachers and managers. The results of this study suggested that we needed the reconstruction of curriculum, the efficient application of plant education for effectiveness of using school environment and monitoring continually and construction information sources for the better environment education in the elementary schools.
Characteristics of organophoshhorus pesticides (OPs) distribution were investigated in Shingu Reservoir, as a shallow eutrophic agriculture reservoir in Korea. In August 2006, IBP, DDVP and dyfonate were detected in the water column of Singu Reservoir, ranging from 1340.7 to 16030.1 ng $L^{-1}$, 58.7 to 127.6 ng $L^{-1}$ and N.D. to 20.3 ng $L^{-1}$, respectively, However, in September 2006, mevinfos, ethoprofos, phorate, chlorfenvinfos, and methidathion were also found in addition to IBP (202.5${\sim}$213.2 ng $L^{-1}$), DDVP (100.7${\sim}$340.6 ng $L^{-1}$) and dyfonate (N.D.${\sim}$25.0 ng $L^{-1})$. Maximum concentrations of OPs were observed at the middle depth in August, which might be related with photo-oxidation. On the other hand, IBP and DDVP among the OPs were detected in suspended particles, suggesting the relatively active adsorption reactivity. The composition of OPs varied temporally on account of the influence of inflow water from its surrounding areas. In the present study, the observed OPs concentrations seem to be not acute toBic levels to aquatic organisms in Shingu Reservoir, considering the standard monitoring levels of U.S. Environmental Protection Agency and Japan Ministry of Environment.
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