• Korean Journal of Radiology
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• v.25 no.3
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• pp.224-242
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• 2024

The emergence of Chat Generative Pre-trained Transformer (ChatGPT), a chatbot developed by OpenAI, has garnered interest in the application of generative artificial intelligence (AI) models in the medical field. This review summarizes different generative AI models and their potential applications in the field of medicine and explores the evolving landscape of Generative Adversarial Networks and diffusion models since the introduction of generative AI models. These models have made valuable contributions to the field of radiology. Furthermore, this review also explores the significance of synthetic data in addressing privacy concerns and augmenting data diversity and quality within the medical domain, in addition to emphasizing the role of inversion in the investigation of generative models and outlining an approach to replicate this process. We provide an overview of Large Language Models, such as GPTs and bidirectional encoder representations (BERTs), that focus on prominent representatives and discuss recent initiatives involving language-vision models in radiology, including innovative large language and vision assistant for biomedicine (LLaVa-Med), to illustrate their practical application. This comprehensive review offers insights into the wide-ranging applications of generative AI models in clinical research and emphasizes their transformative potential.

• Journal of Integrative Natural Science
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• v.17 no.3
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• pp.93-103
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• 2024

Mongolia's diverse geographical landscape and harsh climate make it particularly susceptible to various natural disasters, including forest fires, heavy rains, dust storms, and heavy snow. This study aims to explore the relationships between key climatic variables and the frequency of these disasters. We collected monthly data from January 2022 to April 2024, encompassing average temperature, temperature variability (absolute temperature difference), average humidity, and precipitation across the capitals of Mongolia's 21 provinces and the capital city Ulaanbaatar. The data were analyzed using multiple statistical models: Linear Regression, Poisson Regression, and Negative Binomial Regression. Descriptive statistics provided initial insights into the variability and distribution of the climatic variables and disaster occurrences. The models aimed to identify significant predictors and quantify their impact on disaster frequencies. Our approach involved standardizing the predictor variables to ensure comparability and interpretability of the regression coefficients. Our findings indicate that climatic variables significantly affect the frequency of natural disasters. The Negative Binomial Regression model was particularly suitable for our data, which exhibited overdispersion common characteristic in count data such as disaster occurrences. Understanding these relationships is crucial for developing targeted disaster management strategies and policies to mitigate the adverse effects of climate change on Mongolian communities. This research provides valuable insights into how climatic changes impact disaster occurrences, offering a foundation for informed decision-making and policy development to enhance community resilience.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.146-157
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• 2019

One of the most distinctive features of the South Korean rural environment is that the variation of weather or climate is large even within a small area due to complex terrains. The Geospatial Schemes based on Topo-Climatology (GSTP) was developed to simulate such variations effectively. In the present study, we reviewed the progress of the geospatial schemes for production of farm-scale agricultural weather data. Efforts have been made to improve the GSTP since 2000s. The schemes were used to provide climate information based on the current normal year and future climate scenarios at a landscape scale. The digital climate maps for the normal year include the maps of the monthly minimum temperature, maximum temperature, precipitation, and solar radiation in the past 30 years at 30 m or 270 m spatial resolution. Based on these digital climate maps, future climate change scenario maps were also produced at the high spatial resolution. These maps have been used for climate change impact assessment at the field scale by reprocessing them and transforming them into various forms. In the 2010s, the GSTP model was used to produce information for farm-specific weather conditions and weather forecast data on a landscape scale. The microclimate models of which the GSTP model consists have been improved to provide detailed weather condition data based on daily weather observation data in recent development. Using such daily data, the Early warning service for agrometeorological hazard has been developed to provide weather forecasts in real-time by processing a digital forecast and mid-term weather forecast data (KMA) at 30 m spatial resolution. Currently, daily minimum temperature, maximum temperature, precipitation, solar radiation quantity, and the duration of sunshine are forecasted as detailed weather conditions and forecast information. Moreover, based on farm-specific past-current-future weather information, growth information for various crops and agrometeorological disaster forecasts have been produced.

• Korean Journal of Environment and Ecology
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• v.36 no.1
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• pp.102-111
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• 2022

Among protected areas, National Parks are rich in biodiversity, and the benefits of ecosystem services provided to human are higher than the others. Ecosystem service evaluation is being used to manage the value of national parks based on objective and scientific data. Ecosystem services are classified into four services: supporting, provisioning, regulating and cultural. The purpose of this study is to evaluate habitat quality among supporting services. Habitat Quality Model of InVEST was used to analyze. The coefficients of sensitivity and habitat initial value were reset by reflecting prior studies and the actual conditions of protected areas. Habitat quality of 21 national parks except Hallasan National Park was analyzed and mapped. The value of habitat quality was evaluated to be between 0 and 1, and the closer it is to 1, the more natural it is. As a result of habitat quality analysis, Seoraksan and Taebaeksan National Parks (0.90), Jirisan and Odaesan National Parks (0.89), and Sobaeksan National Park (0.88) were found to be the highest in the order. As a result of comparing the area and habitat quality of 18 national parks except for coastal-marine national parks, the larger the area, the higher the overall habitat quality. Comparing the value of habitat quality of each zone, the value of habitat quality was high in the order of the park nature preservation zone, the park nature environmental zone, the park cultural heritage zone, and the park village zone. Considering both the analysis of habitat quality and the legal regulations for each zone of use, it is judged that the more artificial acts are restricted, the higher the habitat quality. This study is meaningful in analyzing habitat quality of 21 National Parks by readjusting the parameters according to the situation of protected areas in Korea. It is expected to be easy to intuitively understand through accurate data and mapping, and will be useful in making policy decisions regarding the development and preservation of protected areas in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.156-172
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• 2014

This research measures and compares on-site net radiation energy, air temperature, wind speed, and surface temperature considering various spatial characteristics with a focus on land use types in urban areas in Changwon, Southern Gyeongsangnam-do, to analyze the accuracy of an ENVI-met model, which is an analysis program of microclimate. The on-site measurement was performed for three days in a mobile measurement: two days during the daytime and one day during the nighttime. The analysis using the ENVI-met model was also performed in the same time zone as the on-site measurement. The results indicated that the ENVI-met model showed higher net radiation than the on-site measurement by approximately $300Wm^{-2}$ during the daytime whereas the latter showed higher net radiation energy by approximately $200Wm^{-2}$ during the nighttime. The temperature was found to be much higher by approximately $2-6^{\circ}C$ in the on-site measurement during both the daytime and nighttime. The on-site measurement also showed higher surface temperature than the ENVI-met by approximately $7-13^{\circ}C$. In terms of the wind speed, there was a significant difference between the results of the ENVI-met model and on-site measurement. As for the correlation between the results of the ENVI-met model and on-site measurement, the temperature showed significantly high correlation whereas the correlations for the net radiation energy, surface temperature, and wind speed were very low. These results appear to be affected by excessive or under estimation of solar and terrestrial radiation and climatic conditions of the surrounding areas and characteristics of land cover. Hence, these factors should be considered when applying these findings in urban and environment planning for improving the microclimate in urban areas.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.1
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• pp.29-36
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• 2007

This study was carried out to develop a water quality simulation model for the evaluation of an ungauged watershed. For this purpose, the WASP5 model was selected and modified. The model consists of three sub-models, LOAD-M, DYN-M, and EUT-M. LOAD-M, an empirical model, estimates runoff loadings using point and non-point source data of villages. The Geum River Estuary watershed was selected to calibrate and verify the Modified-WASP5. The LOAD-M model was established using field data of water quality and quantity at the gauging stations of the watershed and was applied to the ungauged watersheds, taking the watershed properties into consideration. The result of water quality simulation using Modified-WASP5 shows that the observed average BOD data from Gongju and Ganggyeong were 2.6 mg/L and 2.8 mg/L, and the simulated data were 2.5 mg/L and 2.4 mg/L, respectively. Generally, simulation results were in good agreement with the observed data. This study focused on formulating an integrated model for evaluating ungauged watersheds. Even though simulation results varied slightly due to limited availability of data, the model developed in this study would be a useful tool for the assessment and management of ungauged watersheds.

• Journal of The Korean Association For Science Education
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• v.44 no.4
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• pp.325-341
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• 2024

This study examined how specific aspects of epistemic cognition are developed in elementary students during modeling activities, using the Apt-AIR framework. The study focused on a class unit titled 'Shall We Find Out What the Landscape of a Riverside Looks Like?' which is part of the land chapter in the third-grade Korean elementary science curriculum. Ambitious Science Teaching (AST) was applied as a teaching strategy to enhance students' model construction. Seven science classes were conducted in line with the core practices of AST, with 29 elementary school students participating in the study. The classes were organized into four stages: initial model composition, inquiry activity, group model composition-sharing, and final model construction. The class activities at each stage were analyzed using both the AIR model, i.e., epistemic aim and value (A), epistemic ideals (I), and reliable epistemic processes (R), and the multi-faceted framework for epistemic thinking from the Apt-AIR framework. The results of the study revealed that in science classes emphasizing modeling activities based on the core practices of AST, the elementary students progressively developed more sophisticated explanatory models that included causal relationships explaining the topographic differences between the upstream and downstream sections of a river. This result was due to their engagement in constructing initial models to describe phenomena, supplementing the initial models using data collected in the model experiment, and participating in discussions to share and evaluate group models. Additionally, from the perspective of the Apt-AIR framework, the aspects of epistemic cognition demonstrated by the elementary students in their modeling activities were appropriate for engaging with cognitive processes related to epistemic aims and values, epistemic ideals, and reliable processes. The other four aspects of the Apt-AIR framework, however, were not performed as effectively. In particular, the application of reliable epistemic processes for knowledge construction required more improvement.

• Journal of Korea Water Resources Association
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• v.45 no.9
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• pp.929-941
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• 2012

In recent years, interest in river environment such as riparian landscape, water quality and ecological conservation has been growing with increasing recreation on agricultural river watershed. That caused the increase of necessity of water resources development, one of solutions for the diversification of agricultural water demand and shortages. In this respects, heightening irrigation dam, as a part of the 4-major river restoration project, is necessary to secure not only additional agricultural water but also instream flow for water quality improvement. However, operation plan of irrigation dam still not be clear. In this study, additional storage which secured through heightening irrigation dam was estimated using SWAT model. And instream flow effects on water quality of downstream were evaluated. The findings show that the additional water supply will contribute positively to water quantity and quality of downstream. The results show a 2~10% water quality improvement effect on nutrients, as well as an 1~8% water quantity increasing effect. In particular, additional storage can be effectively supplied from February to April by the reservoir operation. However, maintaining better water quality in irrigation reservoirs is important because the water quality of irrigation reservoirs can be negatively impacts the water quality in downstream of reservoirs.

• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.542-549
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• 2020

Purpose: As nitrate nitrogen produced during fermentation of liquid fertilizer is a pollution indicator of water, in this study, four research areas where liquid fertilizer was sprayed were selected, and a model was designed to estimate the concentration of nitrate nitrogen pollution. Method: Prior to shooting on site, a spectrum library was constructed by dividing the ratio of liquid fertilizer into 5 groups: 0%, 25%, 50%, 75%, and 100%. PLSR (Partial least squares regression) method was applied to hyperspectral images acquired in the study area based on the aspect of spectrum. Result: The behavior of nitrate nitrogen was confirmed by 1st and 2nd differentiation of the spectrum of the constructed liquid fertilizer. PLSR concentration estimation modeling was implemented using images from field experiments and compared with actual concentration of nitrate nitrogen. Conclusion: When comparing the PLSR concentration estimation model with the actual concentration of nitrate nitrogen, it was measured that the detection is possible in high concentration areas where the concentration of nitrate nitrogen is 70mg/kg or more.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.242-249
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• 2006

Potential impacts of the future climate change on crop production can be inferred by crop simulations at a landscape scale, if the climate data may be provided at appropriate spatial scales. Northern Gyunggi Province is one of the few prospective regions in South Korea for growing quality soybeans. Any geographical shift of production areas under the changing climate may influence the current land planning policy in this region. A soybean growth simulation was performed at 342 land units in northern Gyunggi province to test the potential geographical shift of the current production areas for quality soybeans in the near future (form 2011 to 2100). The land units for soybean cultivation were selected by the land use, the soil characteristics, and the minimum arable land area. Daily maximum and minimum temperature, precipitation, the number of rain days and solar radiation were extracted for each land unit from the future digital climate models (DCM, 2011-2040, 2041-2070, 2071-2100). Daily weather data for 30 years were randomly generated for each land unit for each normal year by using a well-known statistical method. They were used to run CROPGRO-Soybean model to simulate the growth, phonology, and yields of 3 cultivars representing different maturity groups grown at 342 land units. According to the model calculations, the warming trend in this region will accelerate the flowering and physiological maturity of all cultivars, resulting in a 7 to 9 days reduction in overall growing season and a 1 to 15% reduction in grain yield of early to medium maturity cultivars. There was a slight increase in grain yield of the late maturing cultivar under the projected climate by 2070, but a decreasing tend was dominant by the year 2100.