• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.239-241
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• 2009

This paper gives the activities and trend analysis handled in the ITU-T study group 5 meeting. In the meeting, the title of SG(Study Group)5 was changed into 'Environment and climate change' since the role of the former Focus Group 'ICT and Climate Change' was moved to SG5. SG5 consists of 3 WP(Working Part) and have total 20 Questions. The Recommendations to be established or revised were discussed and new Recommendations, K.79 and K.80, were consented. The agenda for the human exposure to electromagnetic fields due to radio systems and mobile equipment was focused and discussed in detail. Also, related to ICT and climate change, new questions to be studied in this study period were discussed and defined.

• Journal of Hydrogen and New Energy
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• v.29 no.1
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• pp.117-123
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• 2018

The long-term perception investigation of environment is needed for the persistence of each country's policy on climate change, which is greatly influenced by external factors. Long term data on perception and attitudes of people's thought can be a big data point for climate change and consistent policies can be implemented with the need for public demand. Information on the perception of the general public regarding the environment should be carried out as a basis for the national environmental policy.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.17-24
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• 2017

Using a sample of 180 managers in small and medium sized organizations in Chungcheong and Southern Gyeonggi Province, we proposed that official communication channel on safety issue will influence managers' safety climate, empathy (safety climate), and eventually occupational accidents. The results supported our hypotheses, showing managers concern about their employees' safety issue when the organization officially emphasize on safety issue. At the same time, it also tells that managers are emphatic on their employees regarding occupational accidents when it comes to safety climate.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.157-157
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• 2018

A reliable and accurate downscaling model which can provide climate change information, obtained from global climate models (GCMs), at finer resolution has been always of great interest to researchers. In order to achieve this model, linear methods widely have been studied in the past decades. However, nonlinear methods also can be potentially beneficial to solve downscaling problem. Therefore, this study explored the applicability of some nonlinear machine learning techniques such as neural network (NN), extreme learning machine (ELM), and ELM autoencoder (ELM-AE) as well as a linear method, least absolute shrinkage and selection operator (LASSO), to build a reliable temperature downscaling model. ELM is an efficient learning algorithm for generalized single layer feed-forward neural networks (SLFNs). Its excellent training speed and good generalization capability make ELM an efficient solution for SLFNs compared to traditional time-consuming learning methods like back propagation (BP). However, due to its shallow architecture, ELM may not capture all of nonlinear relationships between input features. To address this issue, ELM-AE was tested in the current study for temperature downscaling.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.6
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• pp.19-30
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• 2016

The projection of climate-related range shift is critical information for conservation planning of Korean fir (Abies koreana E. H. Wilson). We first modeled the distribution of Korean fir under current climate condition using five single-model species distribution models (SDMs) and the pre-evaluation weighted ensemble method and then predicted the distributions under future climate conditions projected with HadGEM2-AO under four $CO_2$ emission scenarios, the Representative Concentration Pathways (RCP) 2.6, 4.5, 6.0 and 8.5. We also investigated the predictive uncertainty stemming from five individual algorithms and four $CO_2$ emission scenarios for better interpretation of SDM projections. Five individual algorithms were Generalized linear model (GLM), Generalized additive model (GAM), Multivariate adaptive regression splines (MARS), Generalized boosted model (GBM) and Random forest (RF). The results showed high variations of model performances among individual SDMs and the wide range of diverging predictions of future distributions of Korean fir in response to RCPs. The ensemble model presented the highest predictive accuracy (TSS = 0.97, AUC = 0.99) and predicted that the climate habitat suitability of Korean fir would increase under climate changes. Accordingly, the fir distribution could expand under future climate conditions. Increasing precipitation may account for increases in the distribution of Korean fir. Increasing precipitation compensates the negative effects of increasing temperature. However, the future distribution of Korean fir is also affected by other ecological processes, such as interactions with co-existing species, adaptation and dispersal limitation, and other environmental factors, such as extreme weather events and land-use changes. Therefore, we need further ecological research and to develop mechanistic and process-based distribution models for improving the predictive accuracy.

• Journal of Environmental Health Sciences
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• v.43 no.3
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• pp.240-246
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• 2017

Objectives: This study was conducted to evaluate the vulnerability of the human health sector to $PM_{10}$ due to climate change in Incheon over the period of 2005-2014. Methods: Vulnerability to $PM_{10}$ consists of the three categories of climate exposure, sensitivity, and adaptive capacity. The indexes for climate exposure and sensitivity indicate positive effects, while adaptive capacity shows a negative effect on vulnerability to $PM_{10}$. The variables in each category were standardized by the rescaling method, and respective relative regional vulnerability was analyzed through the vulnerability index calculation formula of the Intergovernmental Panel on Climate Change. Results: Regions with a high exposure index were the western and northern urban areas with industrial complexes adjacent to a highway, including Bupyong-gu and Seo-gu. Major factors determining the climate exposure index were the $PM_{10}$ concentration, days of $PM_{10}$ >= $100{\mu}g/m^3$, and $PM_{10}$ emissions. The regions showing a high sensitivity index were urban regions with high populations; these commonly had a high mortality rate for related diseases and vulnerable populations. Conclusions: This study is able to support regionally adjusted adaptation policies and the quantitative background of policy priority since it provides information on the regional health vulnerability to $PM_{10}$ due to climate change in Incheon.

• Journal of the Korean Society of Earth Science Education
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• v.12 no.1
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• pp.1-17
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• 2019

The importance of education in formulating and complementing climate change response has been widely recognized by international and national frameworks, agendas, strategies and action plans. Climate change education has the potential to meet the needs of communities to access updated information and knowledge on climate change, supporting policy development and the enhancing effectiveness of climate change response. This study develops an innovative model of Integrated Urban Climate Education (IUCE) as one suitable method for teaching and learning climate change and urbanization. This paper presents approaches, methodology and key lessons learned from the case study of IUCE in Cam Le District of Da Nang City. Findings from the study identify a number of important characteristics about the development and implementation of IUCE in a way that effectively contributes to urban resilience building. These characteristics include (1) multidimensional approaches, (2) teacher - centered base, (3) school-family-community connection, and (4) symbiosis principle.

• Journal of Climate Change Research
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• v.6 no.2
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• pp.61-72
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• 2015

In this study, we have investigated monthly changes in temperature extremes in South Korea for the past (1921~2010) and the future (2011~2100). We used seven stations' (Gangneung, Seoul, Incheon, Daegu, Jeonju, Busan, Mokpo) data from KMA (Korea Meteorological Administration) for the past. For the future we used the closest grid point values to observations from the RCP8.5 scenario of 1 km resolution. The Expert Team on Climate Change Detection and Indices (ETCCDI)'s climate extreme indices were employed to quantify the characteristics of temperature extremes change. Temperature extreme indices in summer have increased while those in winter have decreased in the past. The extreme indices are expected to change more rapidly in the future than in the past. The number of frost days (FD) is projected to decrease in the future, and the occurrence period will be shortened by two months at the end of the $21^{st}$ century (2071~2100) compared to the present (1981~2010). The number of hot days (HD) is projected to increase in the future, and the occurrence period is projected to lengthen by two months at the end of the $21^{st}$ century compared to the present. The annual highest temperature and its fluctuation is expected to increase. Accordingly, the heat damage is also expected to increase. The result of this study can be used as an information on damage prevention measures due to temperature extreme events.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.1-15
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• 2024

In recent years, climate change has been responsible for unusual weather patterns on a global scale. Droughts, natural disasters triggered by insufficient rainfall, can inflict significant social and economic consequences on the entire agricultural sector due to their widespread occurrence and the challenge in accurately predicting their onset. The frequency of drought occurrences in South Korea has been rapidly increasing since 2000, with notably severe droughts hitting regions such as Incheon, Gyeonggi, Gangwon, Chungbuk, and Gyeongbuk in 2015, resulting in significant agricultural and social damage. To prepare for future drought occurrences resulting from climate change, it is essential to develop long-term drought predictions and implement corresponding measures for areas prone to drought. The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report outlines a climate change scenario under the Shared Socioeconomic Pathways (SSPs), which integrates projected future socio-economic changes and climate change mitigation efforts derived from the Coupled Model Intercomparison Project 6 (CMIP6). SSPs encompass a range of factors including demographics, economic development, ecosystems, institutions, technological advancements, and policy frameworks. In this study, various drought indices were calculated using SSP scenarios derived from 18 CMIP6 global climate models. The SSP5-8.5 scenario was employed as the climate change scenario, and meteorological drought indices such as the Standardized Precipitation Index (SPI), Self-Calibrating Effective Drought Index (scEDI), and Standardized Precipitation Evapotranspiration Index (SPEI) were utilized to analyze the prediction and variability of future drought occurrences in South Korea.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.5
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• pp.15-27
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• 2024

Agriculture is recognized as an important anthropogenic cause of non-point source loads. Improved understanding of non-point source loads according to fertilization practices can promote climate change and eutrophication mitigation. Thus, this study evaluated the impact of conventional and standard fertilization practices on non-point pollution (NPP) loads in a dual-cropping system, utilizing the Agricultural Policy/Environmental eXtender (APEX) model. Our research objectives were twofold: firstly, to calibrate and validate the APEX model with observed data through experiments from 2018 to 2023; and secondly, to compare the NPP loads under conventional and standard fertilization practices. The model calibration and validation showed satisfactory performance in simulating nitrogen (N) and phosphorus (P) loads, illustrating the model's applicability in a Korean agricultural setting. The simulation results under conventional fertilization practices revealed significantly higher NPP loads compared to the standard fertilization, with P loads under conventional practices being notably higher. Our findings emphasize the crucial role of recommended fertilization practices in reducing non-point source pollution. By providing a quantitative assessment of NPP loads under different fertilization practices, this study contributes valuable information to sustainable nutrient management in agricultural systems facing the dual challenges of climate change and environmental conservation.