• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.503-514
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• 2020

Climate change leads to changes in phenological response and movement of plant habitats. Korea's evergreen broad-leaved forest has widened its distribution area compared for the past 20 years, and the range of its native habitats is moving northward. We analyzed climate indices such as the warmth index, the cold index, the lowest temperature in the coldest month, and the annual average temperature, which are closely related to vegetation distribution, to predict the change in the native habitat of Lauraceae evergreen broad-leaved trees. We also analyzed the change and spatial distribution to identify the habitat climate characteristics of 8 species of Lauraceae evergreen broad-leaved trees distributed in the warm temperate zone in Korea. Moreover, we predicted the natural habitat change in the 21st century according to the climate change scenario (RCP 4.5/8.5), applying the MaxEnt species distribution model. The monthly average climate index of the 8 species of Lauraceae evergreen broad-leaved trees was 116.9±10.8℃ for the temperate index, the cold index 3.9±3.8℃, 1495.7±455.4mm for the annual precipitation, 11.7±3.5 for the humidity index, 14.4±1.1℃ for the annual average temperature, and 1.0±2.1℃ for the lowest temperature of winter. Based on the climate change scenario RCP 4.5, the distribution of the Lauraceae evergreen broad-leaved trees was analyzed to expand to islands of Jeollanam-do and Gyeongsangnam-do, adjacent areas of the west and south coasts, and Goseong, Gangwon-do on the east coast. In the case of the distribution based on the climate change scenario RCP 8.5, it was analyzed that the distribution would expand to all of Jeollanam-do and Gyeongsangnam-do, and most regions except for some parts of Jeollabuk-do, Chungcheongnam-do, Gyeongsangbuk-do, and the capital region. For the conservation of Lauraceae evergreen broad-leaved trees to prepare for climate change, it is necessary to establish standards for conservation plans such as in-situ and ex-situ conservation and analyze various physical and chemical characteristics of native habitats. Moreover, it is necessary to preemptively detect changes such as distribution, migration, and decline of Lauraceae evergreen broad-leaved trees following climate change based on phenological response data based on climate indicators and establish conservation management plans.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.161-173
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• 2021

The shipping industry plummeted and was depressed due to the global economic crisis caused by the bankruptcy of Lehman Brothers in the US in 2008. In 2020, the shipping market also suffered from a collapse in the unstable global economic situation due to the COVID-19 pandemic, but unexpectedly, it changed to an upward trend from the end of 2020, and in 2021, it exceeded the market of the boom period of 2008. According to the Clarksons report published in May 2021, the decrease in cargo volume due to the COVID-19 pandemic in 2020 has returned to the pre-corona level by the end of 2020, and the tramper bulk carrier capacity of 103~104% of the Panamax has been in the ports due to congestion. Earnings across the bulker segments have risen to ten-year highs in recent months. In this study, as factors affecting BDI, the capacity and congestion ratio of Cape and Panamax ships on the supply side, iron ore and coal seaborne tonnge on the demand side and Granger causality test, IRF(Impulse Response Function) and FEVD(Forecast Error Variance Decomposition) were performed using VAR model to analyze the impact on BDI by congestion caused by strengthen quarantine at the port due to the COVID-19 pandemic and the loading and discharging operation delay due to the infection of the stevedore, etc and to predict the shipping market after the pandemic. As a result of the Granger causality test of variables and BDI using time series data from January 2016 to July 2021, causality was found in the Fleet and Congestion variables, and as a result of the Impulse Response Function, Congestion variable was found to have significant at both upper and lower limit of the confidence interval. As a result of the Forecast Error Variance Decomposition, Congestion variable showed an explanatory power upto 25% for the change in BDI. If the congestion in ports decreases after With Corona, it is expected that there is down-risk in the shipping market. The COVID-19 pandemic occurred not from economic factors but from an ecological factor by the pandemic is different from the past economic crisis. It is necessary to analyze from a different point of view than the past economic crisis. This study has meaningful to analyze the causality and explanatory power of Congestion factor by pandemic.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.461-472
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• 2022

Natural and anthropogenic factors cause forest types to continuously change. Since the ratio of forest area by forest type is important information for identifying the characteristics of national forest resources, an accurate understanding of the prospect of forest type change is required. The study aim was to use National Forest Inventory (NFI) time-series data to understand the characteristics of forest type change and to estimate future prospects of nationwide forest type change. We used forest type change information from the fifth and seventh NFI datasets, climate, topography, forest stand, and disturbance variables related to forest type change to analyze trends and characteristics of forest type change. The results showed that the forests in Korea are changing in the direction of decreasing coniferous forests and increasing mixed and broadleaf forests. The forest sites that were changing from coniferous to mixed forests or from mixed to broadleaf forests were mainly located in wet topographic environments and climatic conditions. The forest type changes occurred more frequently in sites with high disturbance potential (high temperature, young or sparse forest stands, and non-forest areas). We used a climate change scenario (RCP 8.5) to establish a forest type change model (SVM) to predict future changes. During the 40-year period from 2015 to 2055, the SVM predicted that coniferous forests will decrease from 38.1% to 28.5%, broadleaf forests will increase from 34.2% to 38.8%, and mixed forests will increase from 27.7% to 32.7%. These results can be used as basic data for establishing future forest management strategies.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.327-339
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• 2022

The purpose of this study is to present the effective smoke control flow rate and mode for securing safety through quantitative risk assessment according to the smoke control flow rate and mode (supply or exhaust) of the platform when a train fire occurs at the subway platform. To this end, a fire outbreak scenario was created using a side platform with a central staircase as a model and fire analysis was performed for each scenario to compare and analyze fire propagation characteristics and ASET, evacuation analysis was performed to predict the number of deaths. In addition, a fire accident rate (F)/number of deaths (N) diagram (F/N diagram) was prepared for each scenario to compare and evaluate the risk according to the smoke control flow rate and mode. In the ASET analysis of harmful factors, carbon monoxide, temperature, and visible distance determined by performance-oriented design methods and standards for firefighting facilities, the effect of visible distance is the largest, In the case where the delay in entering the platform of the fire train was not taken into account, the ASET was analyzed to be about 800 seconds when the air flow rate was 4 × 833 m³/min. The estimated number of deaths varies greatly depending on the location of the vehicle of fire train, In the case of a fire occurring in a vehicle adjacent to the stairs, it is shown that the increase is up to three times that of the vehicle in the lead. In addition, when the smoke control flow rate increases, the number of fatalities decreases, and the reduction rate of the air supply method rather than the exhaust method increases. When the supply flow rate is 4 × 833 m³/min, the expected number of deaths is reduced to 13% compared to the case where ventilation is not performed. As a result of the risk assessment, it is found that the current social risk assessment criteria are satisfied when smoke control is performed, and the number of deaths is the flow rate 4 × 833 m³/min when smoke control is performed at 29.9 people in 10,000 year, It was analyzed that it decreased to 4.36 people.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4C
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• pp.247-254
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• 2006

Online testing method is one of the numerical experiment methods using experimental information for a numerical analysis directly. The method has an advantage in that analysis can be conducted without using an idealized mechanical model, because mechanical properties are updated from element test for a numerical analysis in real time. The online testing method has mainly been used for the geotechnical seismic engineering, whose major target is sand. A testing method that may be applied to a consolidation problem has recently been developed and laboratory and field verifications have been tried. Although related research thus far has mainly used a method to update average reaction for a numerical analysis by positioning an element tests at the center of a consolidation layer, a weakness that accuracy of the analysis can be impaired as the thickness of the consolidation layer becomes more thicker has been pointed out regarding the method. To clarify the effectiveness and possible analysis scope of the online testing method in relation to the consolidation problem, we need to review the results by applying experiment conditions that may completely exclude such a factor. This research reviewed the results of the online consolidation test in terms of reproduction of the consolidation settlement and the dissipation of excess pore water pressure of a clay specimen by comparing the results of an online consolidation test and a separated-type consolidation test carried out under the same conditions. As a result, the online consolidation test reproduced the change of compressibility according effective stress of clay without a huge contradiction. In terms of the dissipation rate of excess pore water pressure, however, the online consolidation test was a little faster. In conclusion, experiment procedure needs to improve in a direction that hydraulic conductivity can be updated in real time so as to more precisely predict the dissipation of excess pore water pressure. Further research or improvement should be carried out with regard to the consolidation settlement after the end of the dissipation of excess pore water pressure.

• Journal of Nutrition and Health
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• v.56 no.3
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• pp.300-314
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• 2023

Purpose: This study sought to predict the reasons for skipping breakfast by adolescents aged 13-18 years using the 7^th Korea National Health and Nutrition Examination Survey (KNHANES). Methods: The participants included 1,024 adolescents. The data were analyzed using a complex-sample t-test, the Rao Scott χ²-test, and the classification and regression tree (CART) algorithm for decision tree analysis with SPSS v. 27.0. The participants were divided into two groups, one regularly eating breakfast and the other skipping it. Results: A total of 579 and 445 study participants were found to be breakfast consumers and breakfast skippers respectively. Breakfast consumers were significantly younger than those who skipped breakfast. In addition, breakfast consumers had a significantly higher frequency of eating dinner, had been taught about nutrition, and had a lower frequency of eating out. The breakfast skippers did so to lose weight. Children who skipped breakfast consumed less energy, carbohydrates, proteins, fats, fiber, cholesterol, vitamin C, vitamin A, calcium, vitamin B1, vitamin B2, phosphorus, sodium, iron, potassium, and niacin than those who consumed breakfast. The best predictor of skipping breakfast was identifying adolescents who sought to control their weight by not eating meals. Other participants who had low and middle-low household incomes, ate dinner 3-4 times a week, were more than 14.5 years old, and ate out once a day showed a higher frequency of skipping breakfast. Conclusion: Based on these results, nutrition education targeted at losing weight correctly and emphasizing the importance of breakfast, especially for adolescents, is required. Moreover, nutrition educators should consider designing and implementing specific action plans to encourage adolescents to improve their breakfast-eating practices by also eating dinner regularly and reducing eating out.

• Exercise Science
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• v.23 no.1
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• pp.1-11
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• 2014

The purpose of this study was to develop and validate regression models to estimate maximal oxygen uptake (VO₂max) from the 20 m Progressive Shuttle Run Test (20 m PSRT) in Korean middle-school girls aged 13-15 years. The 20 m PSRT and VO₂max were assessed in a sample of 194 participants. The sample was randomly split into validation (n=127) and test-retest reliability (n=99, 32 out of 127 participants also performed validity test) groups. 127 participants performed a graded exercise test (GXT, stationary gas analyser) and the 20 m PSRT (portable gas analyser) once to develop a VO₂max prediction model and to analyze the validity of the modified 20 m PSRT protocol (starting at 7.5 km/h and increasing by 0.5 km/h every 1 min). 99 participants performed the 20 m PSRT twice for test-retest reliability purpose. Mean measured VO₂max (39.2±5.1 ml/kg/min) from the potable gas analyzer was significantly increased from that measured during the GXT from stationary gas analyzer (37.7±5.7 ml/kg/min, p=.001) using the modified 20 m PSRT protocol. But it was a narrow range (1.5 ml/kg/min). The measured VO₂max from the potable and stationary gas analyzers correlated at r=.88(p<.001). Test-retest of the 20 m PSRT yielded comparable results (Laps r=.88 & final speed r=.85). New regression equations were developed from present data to predict VO₂max for middle-school girls: y=.231×Laps-.311×weight(in kg)+46.201 (r=.74, SEE=4.29 ml/kg/min). It is concluded that (a) the modified 20 m PSRT protocol is a valid and reliable test and (b) this equation developed in this study provides valid estimates of VO₂max of Korean middle-school girl aged 13-15 years.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.802-811
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• 2023

Marine spatial planning (MSP) is a crucial element for rational allocation and sustainable use of marine areas. Particularly, Fishing Activity Protected Areas constitute essential zones accounting for 45.6% designated for sustainable fishing activities. However, the current assessment of these zones does not adequately consider future demands and potential values, necessitating appropriate evaluation methods and predictive tools for long-term planning. In this study, we selected key fish species (Scomber japonicus, Trichiurus lepturus, Engraulis japonicus, and Larimichthys polyactis) within the Fishing Activity Protected Area to predict their distribution and compare it with the current designated zones for evaluating the ability of the prediction tool. Employing the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report scenarios (SSP1-2.6 and SSP5-8.5), we used species distribution models (such as MaxEnt) to assess the movement and distribution changes of these species owing to future variations. The results indicated a 30-50% increase in the distribution area of S. japonicus, T. lepturus, and L. polyactis, whereas the distribution area of E. japonicus decreased by approximately 6-11%. Based on these results, a species richness map for the four key species was created. Within the marine spatial planning boundaries, the overlap between areas rated "high" in species richness and the Fishing Activity Protected Area was approximately 15%, increasing to 21% under the RCP 2.6 scenario and 34% under the RCP 8.5 scenario. These findings can serve as scientific evidence for future evaluations of use zones or changes in reserve areas. The current and predicted distributions of species owing to climate change can address the limitations of current use zone evaluations and contribute to the development of plans for sustainable and beneficial use of marine resources.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.229-256
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• 2023

The increase in telecommuting and household electricity demand due to the pandemic has led to significant changes in electricity demand patterns. This has led to difficulties in identifying KEPCO's PPA (power purchase agreements) and residential solar power generation and has added to the challenges of electricity demand forecasting and grid operation for power exchanges. Unlike other energy resources, electricity is difficult to store, so it is essential to maintain a balance between energy production and consumption. A shortage or overproduction of electricity can cause significant instability in the energy system, so it is necessary to manage the supply and demand of electricity effectively. Especially in the Fourth Industrial Revolution, the importance of data has increased, and problems such as large-scale fires and power outages can have a severe impact. Therefore, in the field of electricity, it is crucial to accurately predict the amount of power generation, such as renewable energy, along with the exact demand for electricity, for proper power generation management, which helps to reduce unnecessary power production and efficiently utilize energy resources. In this study, we reviewed the renewable energy generation forecasting system, its objectives, and practical applications to construct optimal aggregated power resources using data from 169 power plants provided by the Ministry of Trade, Industry, and Energy, developed an aggregation algorithm considering the settlement of the forecasting system, and applied it to the analytical logic to synthesize and interpret the results. This study developed an optimal aggregation algorithm and derived an aggregation configuration (Result_Number 546) that reached 80.66% of the maximum settlement amount and identified plants that increase the settlement amount (B1783, B1729, N6002, S5044, B1782, N6006) and plants that decrease the settlement amount (S5034, S5023, S5031) when aggregating plants. This study is significant as the first study to develop an optimal aggregation algorithm using aggregated power resources as a research unit, and we expect that the results of this study can be used to improve the stability of the power system and efficiently utilize energy resources.