• Environmental and Resource Economics Review
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• v.20 no.3
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• pp.489-529
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• 2011

When greenhouse gas mitigation policies are implemented, energy intensive manufacturing industries are influenced much due to an increase in cost. However, industries that have price setting power are damaged less by the policies. Therefore, this paper analyzes vulnerability of energy intensive manufacturing industries to the policies by measuring price setting power of the industries. We analyzed price setting power model through ECM, employing the import prices and wages as independent variables. The industries that their prices react to import prices are price takers, which their prices are determined by rival's ones. On the other hand, the industry that their prices react to wages that mean domestic cost are price setters, and they will be less vulnerable to the policies. In addition, fluctuation of energy prices would be reflected in import prices because it influences other countries than my one. Thus, we employed energy prices as control variable to measure the net effects of import prices. As empirical results, petroleum products, chemical products, non-metallic mineral products, textiles, and motor vehicles sector have price setting power, so the industries have competitiveness on greenhouse gas mitigation policies.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.10
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• pp.1881-1891
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• 2000

Cenosphere particles of different fly ash formed at the pulverized coal power plant were hollow sphere or filled with small particles inside solid particles. And size was relatively larger than other fly ash particles as well as specific gravity was small to suspend in the water. In this paper, it was demonstrated to contain a variety of morphological particle type, and the physical and chemical properties related to the cenosphere and fly ash particles. Furthermore it was estimated the possibility to reuse the cenosphere particles on the base of cenosphere properties. Cenosphere formation resulted from melting of mineral inclusion in coal, and then gas generation inside the molten droplet. As the aluminosilicate particle was progressively heated, a molten surface layer developed around the solid core. Further heating leaded to cause the formation of fine particles at the core. The mass median diameter(MMD) of cenosphere particles was $123.11{\mu}m$ and the range of size distribution was $100{\sim}200{\mu}m$ with single modal. It was represented that specific density was $0.67g/cm^3$ fineness was $1135g/cm^3$. The chemical components of cenosphere were similar to other fly ash including $SiO_2$, $Al_2O_3$, but the amount of the chemical component was different respectively. In the case of fly ash, $SiO_2$ concentration was 54.75%, and $Al_2O_3$ concentration was 21.96%, so this two components was found in 76.71% of the total concentration. But in the case of cenosphere, it was represented that $SiO_2$ concentration was 59.17% and $Al_2O_3$ concentration was 30.16%, so this two components was found in 89.33% of the total concentration. Glassy component formed by the aluminosilicate was high in the cenosphere, so that it was suitable to use insulating heat material.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.1
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• pp.79-84
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• 2008

This paper describes the application of bioluminescence stimulating agents on a genetically engineered microorganism, Pseudomonas putida mt-2 KG1206, to monitor toluene analogs using in groundwater samples from petroleum hydrocarbon contaminated sites. The maximum bioluminescent response with pure chemicals followed in the order: m-methyl benzyl alchohol > m-toluate > toluene > m-xylene > benzoate > p-xylene > o-xylene. Generally, the bioluminescence production of strain mixed with groundwater samples was dependent on the contaminated total inducer concentrations. However, few samples showed opposite results, where these phenomena may be caused by the complexicity of environmental samples. Two chemicals, SL(sodium lactate) and KNO$_3$, were tested to determine a better bioluminescence stimulant. Both chemicals stimulate the bioluminescence activity of strain KG1206, however, a slightly high bioluminescence was observed with nitrogen chemical. This selected stimulant was then tested on samples collected from contaminated groundwater samples. The bioluminescence activity of all samples mixed with the strain was stimulated with KNO$_3$ amendment. This suggests that the low bioluminescence activity exhibited by the environmental groundwater samples can be stimulated by amending the culture with a proper agent, such as nitrogen compound. These findings would be useful, especially, when strain was used to monitor the groundwater samples contaminated with low inducer contaminants. Overall, the results of this study found the ability of bioluminescence producing bacteria to biosensor a specific group of environmental contaminants, and suggest the potential for more efficient preliminary application of this engineered strain in a field-ready bioassay.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.101-111
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• 2014

Spatial events are predictable using data mining classification algorithms. Decision trees have been used as one of representative classification algorithms. And they were normally used in the classification tasks that have label class values. However since using rule ranking methods, spatial prediction have been applied in the spatial prediction problems. This paper compared rule ranking methods for the spatial prediction application using a decision tree. For the comparison experiment, C4.5 decision tree algorithm, and rule ranking methods such as Laplace, M-estimate and m-branch were implemented. As a spatial prediction case study, landslide which is one of representative spatial event occurs in the natural environment was applied. Among the rule ranking methods, in the results of accuracy evaluation, m-branch showed the better accuracy than other methods. However in case of m-brach and M-estimate required additional time-consuming procedure for searching optimal parameter values. Thus according to the application areas, the methods can be selectively used. The spatial prediction using a decision tree can be used not only for spatial predictions, but also for causal analysis in the specific event occurrence location.

• Journal of the Korean Ceramic Society
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• v.39 no.5
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• pp.452-459
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• 2002

This paper addresses the hydrothermal reactivity of blast furnace slag and fly ash with lime, respectively. The test conditions were CaO-to-$SiO_2$ ratio (C/S), autoclaving temperature ($140{\circ}C$ and $180{\circ}C$) and time (20 to 60h). The study was carried out in terms of the hydrothermal reactivity between $SiO_2$ contained in each hydraulic material and (pure) lime and the compressive strength of autoclaved specimens. Porosity measurement and the XRD analysis were also made in order to ascertain the hydraulicity of the siliceous materials. Compressive strength of the specimens was interpreted in terms of porosity and the reactivity of CaO and $SiO_2$. And the XRD analysis showed the C/S change of the hydrates in the course of autoclaving process. $SiO_2$ in the blast furnace slag was more reactive with CaO than that in the fly ash and consequently the blast furnace slag specimens resulted in much higher compressive strength. A maximum compressive strength of $807kg/cm^2$ was obtained for the blast furnace slag at the autoclaving condition of $180{\circ}C$ and 40 h, while only $397kg/cm^2$ was maximally to achieve with fly ash.

• Journal of the korean academy of Pediatric Dentistry
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• v.30 no.1
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• pp.41-46
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• 2003

In order to evaluate the sufficient etching time for successful bonding and also minimizing unnecessary mineral loss, the enamel surface roughness analysis was performed using confocal laser scanning microscopy. Sixty extracted sound human molar teeth were imbedded in the center of acrylic cylinder using self-curing clear resin exposing buccal surface, and then polished with series of SiC paper(220, 500, 800, 1000, 2000, 4000 grit). Each specimen was randomly assigned to six groups(N=10). 37% phosphoric acid was applied to the polished tooth surface for 10, 20, 30, 40, 50, 60 seconds respectively and washed with copious water. After the surface roughness analysis, five roughness parameters(Sa, Sq, Sz, Sdr, Ra) were statistically analysed by ANOVA and Duncan post hoc test. We found that the all five parameters had higher roughness value in 30 seconds etching time, especially parameter Sz showed the lowest value in 10 seconds etching time and the highest value in 30 seconds etching time compared with the other etching times(p<0.05).

• Clean Technology
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• v.23 no.4
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• pp.345-356
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• 2017

The composting is a biological process that converts organic matter into useful resources such as fertilizers. It is a continuous transition of microbial communities to adapt changes in organic matter and environmental conditions (carbonation rate, temperature, humidity, oxygen supply, pH, etc.). Most of the composting plants are located in the proximity of the residential areas. It is a general scenario where government authorities receive complaints from the local residents due to release of odor from the composting, and has become a social problem in Korea. Identification of dominant microorganisms, understanding change in microbial communities and augmentation of specific microorganism for composting is vital to enhance the efficiency of composting, quality of the compost produced, and reduction of odor. In this paper, we suggest the optimum operation conditions and methods for compost depot to reduce odor generation. The selection of the appropriate microorganisms and their rapid increase in population are effective to promote composting. The optimal growth conditions of bacteria such as aeration (oxygen), temperature, and humidity were standardized to maximize composting through microbial degradation. The use of porous minerals and moisture control has significantly improved odor removal. Recent technologies to reduce odor from the composting environment and improved composting processes are also presented.

• The Journal of Engineering Geology
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• v.26 no.3
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• pp.307-314
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• 2016

Shear characteristics of soils can be investigated using various types of shear stress measuring apparatus. Ring shear tests are often applied for examining the residual shear strength under the unlimited deformation. This paper presents drainage-consolidation-shear velocity dependent undrained shear strengths measured in terms of water leakage. A series of ring shear tests were performed under the constant normal stress (50 kPa) and controled shear velocity ranging from 0.01~1 mm/sec under the undrained condition. As a result, undrained shear strengths are dependent on shear velocity. It exhibits that straining hardening behavior is observed for the shear velocity lower than 0.1 mm/sec; however, the strain softening behavior is observed for the shear velocity higher than 0.1 mm/sec. Water leakage can cause the increase in shear stress irrespective of shear velocity. Shear stress increases with increasing amount of water leakage. It is due to the fact that the small grains and water flow out through the rubble edge in the ring shear box. Repetitive saturation and consolidation processes may minimize the error.

• Journal of the Korean Geotechnical Society
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• v.20 no.8
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• pp.67-75
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• 2004

The landslide is one of the most significant natural disasters, which cause a lot of loss of human lives and properties. The landslides in natural slopes generally occur by complicated problems such as soil properties, topography, and geology. Artificial Neural Network (ANN) model is efficient computing technique that is widely used to solve complicated problems in many research fields. In this paper, the ANN model with application of error back propagation method was proposed for estimation of landslide hazard in natural slope. This model can evaluate the possibility of landslide hazard with two different approaches: one considering only soil properties; the other considering soil properties, topography, and geology. In order to evaluate reasonably the landslide hazard, the SlideEval (Ver, 1.0) program was developed using the ANN model. The evaluation of slope stability using the ANN model shows a high accuracy. Especially, the prediction of landslides using the ANN model gives more stable and accurate results in the case of considering such factors as soil, topographic and geological properties together. As a result of comparison with the statistical analysis(Korea Institute of Geosciences and Mineral Resources, 2003), the analysis using the ANN model is approximately equal to the statistical analysis. Therefore, the SlideEval (Ver. 1.0) program using ANN model can predict landslides hazard and estimate the slope stability.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.6
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• pp.791-798
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• 2014

Cirsium setidens Nakai, a wild perennial, is widely consumed as a food and traditional medicine in Korea. In addition, diverse functionalities of C. setidens Nakai, including anti-inflammatory and antioxidant effects, have been reported. However, whether or not C. setidens Nakai and its major compound, pectolinarin have high nutritional value and functional properties remains unknown. This paper investigated the proximate compositions, mineral contents, hepatoprotective activities, hepatic fat accumulation inhibitory activities, and anti-inflammatory and anti-oxidant activities of C. setidens Nakai and its component parts, including of pectolinarin. The result showed that C. setidens Nakai and its major compounds have potential as a functional food material with natural antioxidant and anti-inflammatory activities.