• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2062-2066
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• 2022

Nuclear energy sources are indispensable in cost effectively achieving carbon neutral economy, where public opinion is critical to adoption as the consequences of nuclear accident can be catastrophic. In this context, discussion on spent nuclear fuel is a prerequisite to expanding nuclear energy, as it leads to the issue of radioactive waste disposal. Given the dearth of study on spent nuclear fuel public acceptance, we use text mining and big data analysis on the news article and public comments data on Naver news portal to identify the Korean public opinion on spent nuclear fuel. We identify that the Korean public is more interested in the nuclear energy policy than spent nuclear fuel itself and that the alternative energy sources affect the position towards spent nuclear fuel. We recommend relating spent nuclear fuel issue with nuclear energy policy and environmental issues of alternative energy sources to further promote spent nuclear fuel.

• Journal of Soil and Groundwater Environment
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• v.15 no.6
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• pp.9-16
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• 2010

Groundwater sampling was performed at 38 wells where they are located in the areas with high uranium and radon (marked as A and B, respectively) concentrations, which were based on the previous research results. In-situ parameters (temperature, pH, EC, Eh, DO) and natural radionuclides (uranium and radon) were analyzed to figure out the characteristics of groundwater environments. In-situ data did not show any relations to natural radionuclide data, which could be caused by groundwater mixing, depths of wells, and geological settings, etc. But the highest radon well presented relatively low temperature value and the highest uranium well presented relatively low pH values The highest uranium concentration ranging $1.14{\sim}188.19{\mu}g/L$ showed in the area of A region consisted of Jurassic two-mica granite. The areas of Jurassic biotite granite and Cretaceous granite in the A region have the uranium concentrations ranging $0.10{\sim}49.78{\mu}g/L$ and $0.36{\sim}3.01{\mu}g/L$, respectively. The uranium values from between wells of community water systems (CWSs) penetrating fractured bed-rock aquifers and personal boreholes settled in shallow aquifers near the wells of CWSs show big differences. It implies that the groundwaters of the two areas have evolved from different water-rock interaction paths that may caused by various types of wells having different aquifers. High radon activities in the area of B region composed of Precambrian gneiss showed ranging from 6,770 to 64,688 pCi/L. Even though the wells are located in the same geological settings, their rodon concentration presented different according to depth and distance.

• Economic and Environmental Geology
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• v.41 no.5
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• pp.625-633
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• 2008

Uses of nickel have been widened in 20th century thanks to development of steel industry and munitions industry and also the demand from each uses on nickel has grown rapidly. In recent 5 years, the market price of nickel has been in bull market, so the security of supply became a big issue for each nickel user. However the entire material flow of nickel is not completed yet in Korea and not even in advanced countries, so recycling rate of nickel from raw materials to finished goods is not sufficient. Although statistical data and report systems about nickel are unprepared in domestic market, this study is carried out with limited market data for the completed material flow of nickel in domestic market and establishing recycling policies of nickel.

• Journal of Environmental Science International
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• v.23 no.4
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• pp.595-603
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• 2014

Jeju Island, a volcanic island, is the region that shows the biggest rainfall and has a big elevation-specific deviation of precipitation, but Jeju Island River Maintenance Plan doesn't reflect the characteristics of Jeju Island as it only calculates probable precipitation from four weather stations with elevation less than 100m. Therefore, this study uses AWS observational data in four Jeju Island weather stations and other regions to calculate location-specific probable precipitation, review the elevation-probable precipitation correlation in southern and northern regions, and create a probable precipitation map for all regions of Jeju Island, in order to produce better outcomes. This study is expected to be the most basic data to establish a safe Jeju island from flood disaster in preparation for the future climate changes and widely used for Jejudo Basin Dimension Planning, River Maintenance Plan, Pre-Disaster Impact Review, etc.

• Transactions of the Korean hydrogen and new energy society
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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.

• Korean Security Journal
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• no.13
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• pp.487-505
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• 2007

This study is to examine relations between the number of occurrence of big five critical crimes that consist of homicide, robbery, rape, theft, violence and the number of the security companies and the security guards, and between the number of the security companies, the security guards and the number of arrests from the big five critical crimes. To achieve this objective, this research selects a subject of study, the number of the security companies and security guards, and the number of occurrences of the big five critical crimes and arrests of the big five crimes from 1990 to 2005. The selected data are then analyzed according to the variables using SPSS 12.0. Each hypothesis is verified with the level of significance ${\alpha}$=.05 using the statistical techniques such as Correlation Analysis, Regression Analysis, etc. The following is the result of the study: First, the number of occurrences of the big five critical crimes affects the number of the security companies at a significant level. Second, the number of the security companies affects the number of arrests of the big five crime at a significant level.

• Asian Journal of Atmospheric Environment
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• v.7 no.1
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• pp.56-63
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• 2013

Children are particularly vulnerable to adverse health effects associated with heavy metal exposure. The goal of this study was to investigate the relationship between proximity to an industry complex and blood lead and urinary cadmium levels for children aged 7-13 who lived in Ulsan where a big petrochemical complex is located. We conducted a questionnaire survey to collect data including sociodemographics, daily habits, residential environment, etc. We also analyzed blood lead and urinary cadmium levels using Atomic Absorption Spectrometry (AAS). Data were analyzed using regression analysis. All statistical analyses were conducted with SAS software version 9.2. We calculated distance by using a Geographic Information System (ArcGIS version 10.0). The geometric mean blood lead level was 1.55 ${\mu}g/dL$ (boys: 1.59 ${\mu}g/dL$, girls: 1.51 ${\mu}g/dL$), and the geometric mean urinary cadmium level was 0.51 ${\mu}g/g$ creatinine (boys: 0.45 ${\mu}g/g$ creatinine, girls: 0.58 ${\mu}g/g$ creatinine). In the results of regression analyses, we found that urinary cadmium levels significantly decreased as distance between residence and industrial complex increased after adjusting for age, gender, income, passive smoking and the length of residence. This result was opposite to that for lead levels. Our observations support the hypothesis that urinary cadmium levels in children are related to their proximity to an industrial complex.

• Journal of Environmental Science International
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• v.25 no.7
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• pp.1007-1016
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• 2016

Environmental policy implementation has been strengthened to protect the source waters in Korea and to improve their water quality. Increasing of non-point source caused water quality problem continuously. Research on runoff from forests, which occupy over 65% of the land in korea, is insufficient, and studies on the characteristics and influences of storm runoff are necessary. In this study, we chose to compare the effects of land use in the form of two types of forest distribution and then gathered data on storm characteristics and runoff properties during rainfall events in these areas. Furthermore, the significance and influences of the discharges were analyzed through correlation analysis, and multilateral runoff characteristics were examined by deducing a formula through $COD_{Mn}$ and TOC regression analysis. At two forest points, for which the basin areas differed from each other, flow changed according to storm quantity and intensity. The peak discharge at point A, where the basin area was big, was high, whereas water-quality fundamental items (BOD, $COD_{Mn}$, and SS) and TOC density were high at point B where the slope and storm intensity were high. Effects of dissolved organic matter were determined through correlation analysis, and the regression formulas for $COD_{Mn}$ and TOC were deduced by regression analysis. It is expected that the data from this study could be useful as basic information in establishing forest management measures.

• Journal of Environmental Science International
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• v.17 no.4
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• pp.423-437
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• 2008

Until comparatively lately, the annual time series of the $SO_2$ concentration had been shown in a decreasing trend in Ulsan as well as other Korean cities. However, the high concentration of $SO_2$ was frequently found in the specific countermeasure region including the national industrial complex such as Mipo and Onsan in the Ulsan city for the period of $2001{\sim}2004$. There are many conditions that can influence the high concentration of $SO_2$ at monitoring sites in Ulsan, such as: First, annual usage of the fuel including sulfur increased in comparison with the year before in spite of the fuel conversion policy which wants to use low sulfur oil less than 3% and LNG. Second, point source, such as the power plants and the petroleum and chemistry stacks, was the biggest contributor in $SO_2$ emission, as a analyzed result of both the air quality modeling and the stack tole-monitoring system (TMS) data. And third, the air pollutants that occurred in processes of homing and manufacturing of the fuel including sulfur were transported slow into a special monitoring site by accumulating along the frontal area of see-breeze. It was concluded that Ulsan's current environmental policy together with control methods should be changed into the regulation on total amount of emission, including a market-based emission trading with calculating of atmospheric environmental critical loads, for the $SO_2$ reduction like the specific countermeasure for the $O_3$ and PM10 reduction in the Seoul metropolitan area. And this change should be started in the big point sources of $1{\sim}3$ species because they are big contributors of Ulsan's $SO_2$ pollution. Especially it is necessary to revitalize of the self-regulation environmental management. Other control methods for sustaining the $SO_2$ reduction are as follows: maintenance of the fuel conversion policy, reinforcement of the regional stationary source emission standard, and enlargement of the stack TMS.

• Journal of Ocean Engineering and Technology
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• v.33 no.5
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• pp.427-434
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• 2019

Artificial intelligence (AI)-aided research currently enjoys active use in a wide array of fields thanks to the rapid development of computing capability and the use of Big Data. Until now, forecasting methods were primarily based on physics models and statistical studies. Today, AI is utilized in disaster prevention forecasts by studying the relationships between physical factors and their characteristics. Current studies also involve combining AI and physics models to supplement the strengths and weaknesses of each aspect. However, prior to these studies, an optimization algorithm for the AI model should be developed and its applicability should be studied. This study aimed to improve the forecast performance by constructing a model for neural network optimization. An artificial neural network (ANN) followed the ever-changing path of a typhoon to produce similar typhoon predictions, while the optimization achieved by the neural network algorithm was examined by evaluating the activation function, hidden layer composition, and dropouts. A learning and test dataset was constructed from the available digital data of one typhoon that affected Korea throughout the record period (1951-2018). As a result of neural network optimization, assessments showed a higher degree of forecast accuracy.