• The Korean Journal of Quaternary Research
• /
• v.13 no.1
• /
• pp.53-65
• /
• 1999

It is only possible by Physical based Water Balance Models such as $BROOK_{TOP}$ developed by me to estimate regional water balances caused by changes of regional ecosystem, which result in climate change, change of vegetation due to climate change, artificial landuse change, etc. This study estimates regional water balances of mid-north agricultural and forest regions in Germany using $BROOK_{TOP}$-Water Balance Model with climate change scenarios developed by PIK in Germany and GCM Scenarios developed by Praha University in Czech. Developing Water Resource Change Estimation System such as this study for global warming with considering climate, surface and underground conditions provides the basis of system development for surface-, groundwater-, cultivation-, ecosystem-, natural emergency-management, landuse and regional planing.

• KIEAE Journal
• /
• v.13 no.5
• /
• pp.43-50
• /
• 2013

Recent researches on plant factory system deal with the convergence of lighting technology, agricultural technology inclusive to the high-tech industries worldwide in order to respond to the decreasing crop harvest due to global warming and abnormal weather phenomena. However, the fundamental performance standard is not currently being introduced in the case of plants factory and its commercialization is not activated because of high initial investment and operating cost. Large portion of the initial investment and operating cost of a plant factory is ascribed to artificial light sources and thermal control facilities, therefore, innovation should be provided in order to improve the economics of the plant factory. As an alternative, new plant factory could harness solar thermal and geothermal systems for heating, cooling and ventilation. In this study, a natural light dependent multi-layer plant factory's thermal environment was analyzed with two-dimensional numerical methods to elicit efficient operation conditions for optimized internal physical environment. Depending on the supply air temperature and airflow rate introduced in the facility, the temperature changes around the crops was interpreted. Since the air supplied into the plant factory does not stay long enough, the ambient temperature predicted around the plating trays was not significantly different from that of the supplied air. However, the changes of airflow rate and air flow pattern could cause difference to the temperature around the planting trays. Increasing the amount of time of air staying around the planting trays could improve energy performance in case the thermal environment of a natural light based multi-layer plant factory is considered.

• Journal of Korea Water Resources Association
• /
• v.47 no.2
• /
• pp.207-221
• /
• 2014

Recently, due to global warming, climate change has affected short time concentrated local rain and unexpected heavy rain which is increasingly causing life and property damage. Therefore, this paper studies the characteristic of localized heavy rain and flash flood in Nakdong basin study area by applying Data Mining method to predict flood and constructing water level predicting model. For the verification neural network from Data Mining method and hydraulic flood routing was used for flood from July 1989 to September 1999 in Nakdong point and Iseon point was used to compare flood level change between observed water level and SAM (Slope Area Method). In this research, the study area was divided into three cases in which each point's flood discharge, water level was considered to construct the model for hydraulic flood routing and neural network based on artificial intelligence which can be made from simple input data used for comparison analysis and comparison evaluation according to actual water level and from the model.

• International Journal of Advanced Culture Technology
• /
• v.7 no.4
• /
• pp.125-136
• /
• 2019

The radish skin and radish greens are an edible part of the radish. But they are removed before eating the radish and used as a byproduct or an animal feed material because of their tough and rough texture. Melanin is a pigment that gives colour to our skin. But increased production of melanin can turn into benign or malignant tumours. These days due to global warming, the amount of Ultra violet (UVB) rays has been extensively increased with sunlight. Due to this, a phenomenon called exogenous photo aging is widely observed for all skin colour and types. As a result of this phenomenon, a set of enzymes called matrix metalloproteinases (MMP's) that serves as degradation enzymes for extracellular matrix proteins mainly collagen is increased, causing depletion in collagen and resulting in early wrinkles formation. Therefore in our study we used the murine melanoma cell line B16/F10 to study the melanogenesis inhibition by Heated radish extract (HRE) in vitro and we used HRM-2 hair less mice exposed to artificial UVB for checking the efficacy of Heated radish extract in vivo. Furthermore, we prepared a 3% Heated radish extract (HRE) cream and checked its effects on human skin. Our results have clearly demonstrated that Heated radish extract (HRE) have potently suppressed the tyrosinase activity and melanin production in B16/F10 cells. It had also reduced the expression of components involved in melanin production pathway both transcriptionally and transitionally. In in vivo studies, HRE had potently suppressed the expression of MMP's and reduced the wrinkle formation and inhibited collagen degradation. Moreover, on human skin, ginseng cream increased the resilience, skin moisture and enhanced the skin tone. Therefore in light of these findings, we conclude that HRE is an excellent skin whitening and antiaging product.

• Journal of Internet of Things and Convergence
• /
• v.10 no.2
• /
• pp.43-50
• /
• 2024

This manuscript proposes an artificial intelligence-based(AI) energy platform system that efficiently use existing energy than creating new energy than creating new energy sources. To this end, it collects public information data portal and statistics data portal and data emissions, including energy usage and greenhouse gas emissions, including energy consumption and greenhouse gas emissions.In addition, it provides strong security and personal information protection functions to overcome the limit of existing energy platform. Through the built energy platform, improving power supply and user convenience of users and users to contribute to global warming issues.In this paper, the contents to implement the contents of the system, and improvement direction from the future completion and improvement direction.

• Journal of Ocean Engineering and Technology
• /
• v.33 no.6
• /
• pp.590-596
• /
• 2019

Numerous deaths and substantial property damage have occurred recently due to frequent disasters of the highest intensity according to the abnormal climate, which is caused by various problems, such as global warming, all over the world. Such large-scale disasters have become an international issue and have made people aware of the disasters so they can implement disaster-prevention measures. Extensive information on disaster prevention actively has been announced publicly to support the natural disaster reduction measures throughout the world. In Japan, diverse developmental studies on disaster prevention systems, which support hazard map development and flood control activity, have been conducted vigorously to estimate external forces according to design frequencies as well as expected maximum frequencies from a variety of areas, such as rivers, coasts, and ports based on broad disaster prevention data obtained from several huge disasters. However, the current reduction measures alone are not sufficiently effective due to the change of the paradigms of the current disasters. Therefore, in order to obtain the synergy effect of reduction measures, a study of the establishment of an integrated system is required to improve the various disaster prevention technologies and the current disaster prevention system. In order to develop a similar typhoon search system and establish a disaster prevention infrastructure, in this study, techniques will be developed that can be used to forecast typhoons before they strike by using artificial intelligence (AI) technology and offer primary disaster prevention information according to the direction of the typhoon. The main function of this model is to predict the most similar typhoon among the existing typhoons by utilizing the major typhoon information, such as course, central pressure, and speed, before the typhoon directly impacts South Korea. This model is equipped with a combination of AI and DNN forecasts of typhoons that change from moment to moment in order to efficiently forecast a current typhoon based on similar typhoons in the past. Thus, the result of a similar typhoon search showed that the quality of prediction was higher with the grid size of one degree rather than two degrees in latitude and longitude.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2011.05a
• /
• pp.18-18
• /
• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• Journal of Korean Society for Geospatial Information Science
• /
• v.17 no.3
• /
• pp.23-31
• /
• 2009

The border of the shorelines in a nation is an important factor in determining the border of a national territory, but Korea's shorelines are rapidly changing due to the recent rise in sea level from global warming and growth-centered economic policy over the decades of years. This research was done centering on the areas having well-preserved shorelines as they naturally are and other areas having damaged shorelines in their vicinities due to artificial structures at the two beaches located at the neighboring areas and having mutually homogeneous ocean conditions with each other. First, this research derived the shorelines using the aerial photographies taken from 1947 until 2007 and revised the tidal levels sounding data obtained from a hydrographical survey automation system consisting of Echosounder[Echotrac 3100] and Differential Global Positioning System[Beacon]by using topographical data and ships on land obtained by applying post-processing Kinematic GPS measuring method. In addition, this research evaluated the changes and dimensional variations for the last 60 years by dividing these determined shorelines into 5 sections. As a result, the Haewundae Beach showed a total of 29% decrease rate in dimension as of the year 2007 in comparison with the year 1947 due to a rapid dimensional decline centering on its west areas, while the dimension of the Gwanganri Beach showed an increase in its dimension amounting to a total of 69% due to the decrease in flow velocity by artificial structures built on both ends of the beach-forming accumulation; thus, it was found that there existed a big difference in deposition & accumulation tendency depending on neighboring environment in spite of the homogeneous ocean conditions.

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

• Korean Journal of Remote Sensing
• /
• v.25 no.5
• /
• pp.423-434
• /
• 2009

The Arctic environment is sensitive to change of sea-ice distribution. The increase and decrease of sea ice work to an index of globe warming progress. In order to predict the progress of hereafter earth global warming, continuous monitoring regarding a change of the sea ice area in the Arctic should be performed. The remote sensing based on an artificial satellite is most effective on the North Pole. The sea ice observation using a passive microwave sensor has been continued from 1970's. The determination of sea ice extent and ice type is one of the great successes of the passive microwave imagers. In this paper, to investigate the seasonal and inter-annual variation of sea-ice distribution we used here the sea ice data from July 2002 to May 2009 around the Arctic within $60^{\circ}N$ for the AMSR-E 12.5km sea-ice concentration, a passive microwave sensor. From an early analysis of these data, the arctic sea-ice extent has been steadily decreasing at a rate of about 3.1%, accounting for about $2{\times}10^5\;km^2$, which was calculated for the sea-ice cover reaching its minimum extent at the end of each summer. It is also revealed that this trend corresponds to a decline in the multi-year ice that is affected mainly by summer sea surface and air temperature increases. The extent of younger and thinner (first-year) ice decreased to the 2007 minimum, but rapidly recovered in 2008 and 2009 due to the dramatic loss in 2007. Seasonal variations of the sea-ice extent show significant year-to-year variation in the seasons of January-March in the Barents and Labrador seas and August-October in the region from the East Siberian and Chukchi seas to the North Pole. The spatial distribution of multi-year ice (7-year old) indicates that the perennial ice fraction has rapidly shrunk recently out of the East Siberian, Laptev, and Kara seas to the high region of the Arctic within the last seven years and the Northeast Passage could become open year-round in near future.