• Journal of Soil and Groundwater Environment
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• v.18 no.1
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• pp.1-5
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• 2013

Global climate changes affect the local hydrologic cycle, and subsequently, require changes in water resource management strategies of Korea. Variations in precipitation and urbanization have adverse effects on the reasonable and efficient utilization of groundwater resources. Groundwater management strategies of Korea have been implemented based on the evaluation of "sustainable yield", which is calculated from the amount of annual recharge. However, this sustainable yield has no consideration of natural discharge and dynamic equilibrium of the groundwater system. Therefore, for the effective groundwater management strategies of the following decades, we need representative and reliable observations, and have to develop methods for the systematic analysis and interpretations of the data to draw valid information in linkage of natural and societal environmental changes.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1286-1295
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• 2020

It has been increasingly difficult to predict the amounts of Acer mono sap to be collected due to droughts and cold waves caused by recent climate changes with few studies conducted on the prediction of its collection volume. This study thus set out to propose a Big Data prediction system based on meteorological information for the collection of Acer mono sap. The proposed system would analyze collected data and provide managers with a statistical chart of prediction values regarding climate factors to affect the amounts of Acer mono sap to be collected, thus enabling efficient work. It was designed based on Hadoop for data collection, treatment and analysis. The study also analyzed and proposed an optimal prediction model for climate conditions to influence the volume of Acer mono sap to be collected by applying a multiple regression analysis model based on Hadoop and Mahout.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.225-229
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• 2005

The objective of this study is to evaluate snowmelt impact on watershed hydrology using climate change scenarios on Soyanggang-dam and Chungju-dam watershed. SLURP model was used for analyzing hydrological changes based on climate changes. The results (in years 2050 and 2100) of climate changes scenarios was CCCma CGCM2 of SRES suggested by IPCC and the snow cover map and snow depth was derived from NOAA/AVHRR images. The model was calibrated and verified for dam inflow data from 1998 to 2001.

• Atmosphere
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• v.18 no.3
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• pp.199-206
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• 2008

This study employs a structural time series method in order to model and estimate stochastic trend of surface temperatures of the globe, Northern Hemisphere, and Northeast Asia ($20^{\circ}N{\sim}60^{\circ}N$, $100^{\circ}E{\sim}150^{\circ}E$). For this study the reanalysis data CRUTEM3 (CRU/Hadley Centre gridded land-surface air temperature Version 3) is used. The results show that in these three regions range from $0.268^{\circ}C$ to $0.336^{\circ}C$ in 1997, whereas these vary from $0.423^{\circ}C$ to $0.583^{\circ}C$ in 2007. The annual mean temperature over Northeast Asia has increased by $0.031^{\circ}C$ in 2007 compared to 1997. The climate change in surface temperatures over Northeast Asia is slightly higher than that over the Northern Hemisphere.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.104-109
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• 2021

In the aftermath of the global pandemic that started in 2019, there have been many changes in the import/export and supply/demand process of agricultural products in each country. Amid these changes, the necessity and importance of each country's food self-sufficiency rate is increasing. There are several conditions that must accompany efficient agricultural activities, but among them, temperature is by far one of the most important conditions. For this reason, the need for high-accuracy climate data for stable agricultural activities is increasing, and various studies on climate prediction are being conducted in Korea, but data that can visually confirm climate prediction data for farmers are insufficient. Therefore, in this paper, we propose an artificial intelligence-based temperature prediction algorithm that can predict future temperature information by collecting and analyzing temperature data of farms in Gyeonggi-do in Korea for the last 10 years. If this algorithm is used, it is expected that it can be used as an auxiliary data for agricultural activities.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.91-102
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• 2018

The Korean government submitted the Intended Nationally Determined Contributions (INDC) to UNFCCC which aims to reduce 37% greenhouse gas emission for the opportunity of developing new energy industry and industry innovation by 2030 compared with Business-As-Usual scenario taking into account its international responsibilities and hosting headquarters of Green Climate Fund (GCF) secretariat. The 37% reduction is composed of 25.7% in the domestic markets and 11.3% in the international carbon markets. To achieve the reduction target in the international carbon market mechanisms, it must use the linkage of international carbon markets and develop new renewable energy technology for CDM and ODA. Finally, it must improve carbon capture storage (CCS) technology and establish domestic CCS institutional systems as soon as possible. And, it must activate CCS information exchange for the international cooperation on UNFCCC movement.

• Ocean and Polar Research
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• v.44 no.1
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• pp.83-97
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• 2022

The Amundsen Sea in West Antarctica is one of the most affected regions by climate change, but it is one of the least studied realms due to difficulties in access. Korea Polar Research Institute (KOPRI) launched a research project in the Amundsen Sea in 2010 using the icebreaker research vessel (IBRV) Araon and has been conducting various research initiatives. In this paper, previous researches derived from the Amundsen Sea Embayment by Korean researchers are introduced. Through previous studies, researchers have been able to interpret the environmental and biogeochemical changes according to the inflow Circumpolar Deep Water (CDW) and provide information for climate models. In particular, researches using radiocarbon isotopes (¹⁴C) were introduced to understand the physical and biogeochemical mechanisms of the carbon cycle in the Amundsen Sea. Opportunely, with the construction of a second icebreaker research vessel, the direction for systematic and long-term polar data acquisition can be presented.

• Journal of Sensor Science and Technology
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• v.32 no.3
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• pp.164-168
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• 2023

Accurate and reliable weather forecasts for temperature, relative humidity, and precipitation using advanced transformer models and IoT are essential in various fields related to global climate change. We propose a novel weather prediction device that integrates state-of-the-art transformer models and IoT techniques to improve prediction accuracy and real-time processing. The proposed system demonstrated high reliability and performance, offering valuable insights for industries and sectors that rely on accurate weather information, including agriculture, transportation, and emergency response planning. The integration of transformer models with the IoT signifies a substantial advancement in weather and climate modeling.

• Ocean and Polar Research
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• v.33 no.spc3
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• pp.397-407
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• 2011

To understand the vertical structure of ocean currents from raw data observed by lowered-ADCP (LADCP), these data require post-processing. Data were processed using Krahman's version 10.8 processing software based on Matlab. It is estimated the influence of auxiliary data affecting the processed current structure. The bottom-tracked velocities and the GPS information significantly contribute the offset on reference velocities in the bottom layer and barotropic ones in the middle layer, respectively. Good quality data can be obtained when LADCP is least tilted in pitch and roll during observation. In situ application of LADCP to the (northward) volume transports of Kuroshio in the East China Sea proved to be 24.8. Sv (= $1{\times}10^6m^3s^{-1}$) in October 2007, and 28.2 Sv in June 2008, respectively. The volume transport is relatively large over the continental slope when compared to the shelf or the deep sea.

• Knowledge Management Research
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• v.18 no.4
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• pp.31-62
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• 2017

It found that employee silence negatively impacts both organizations and their employees as shown in findings from many studies and recently there has been a growing interest in it. Silence is described as intentionally withholding job-related ideas, information, concerns, and opinions. Employee silence may decrease organizational change and innovation and reduce employee learning motivation and knowledge sharing engagement as well. The purpose of this study is to examine the relationships among silence motivations, perceived silence climate, and employee silence; the relationships among employee silence, learning inertia and knowledge sharing disengagement; the mediating role of employee silence between antecedents of employee silence and consequences additionally. The results that analyzed using data from 225 employees in 42 organizations are as follows. First, the impact of silence motivation and perceived silence climate on employee silence are positively significant. Second, the influence of defensive silence motivation on the acquiescent and relational silence motivation is positively significant. Third, the influence of employee silence on learning inertia and knowledge sharing disengagement is positively significant. Forth, employee silence mediates the relationship between silence motivation and perceived silence climate and learning inertia and knowledge sharing disengagement. These results suggest that employee silence is another strong expression and message for organizations to try to establish a learning organization from the perspective of knowledge management.