• Journal of the Korean earth science society
• /
• v.25 no.1
• /
• pp.10-21
• /
• 2004

Recently, spatial data integration for geoscientific application has been regarded as an important task of various geoscientific applications of GIS. Although much research has been reported in the literature, quantitative assessment of the spatial interrelationship between input data layers and an integrated layer has not been considered fully and is in the development stage. Regarding this matter, we propose here, methodologies that account for the spatial interrelationship and spatial patterns in the spatial integration task, namely a multi-buffer zone analysis and a statistical analysis based on a contingency table. The main part of our work, the multi-buffer zone analysis, was addressed and applied to reveal the spatial pattern around geological source primitives and statistical analysis was performed to extract information for the assessment of an integrated layer. Mineral potential mapping using multi-source geoscience data sets from Ogdong in Korea was applied to illustrate application of this methodology.

• Proceedings of the Korean Ceranic Society Conference
• /
• 2007.07a
• /
• pp.129-137
• /
• 2007

This paper presents a numerical model which can predict degree of hydration of cement mineral component, such as $C_{3}S$, $C_{2}S$, $C_{3}A$, $C_{4}AF$ and microstructure of hydrating cement as a function of water to cement ratio, cement particle size distribution, cement mineral components and temperature. In this model cement particles are parked randomly in cell space and hydration process is described using a multi-component integrated kinetic model. The simulation result of degree of hydration of cement mineral component agrees well with experiment result. The content of cement hydration product, such as CSH and CH can be obtained as an accompanied result during hydration process. By introducing of equal-area projection method, water withdrawl mechanism and contact area among cement particles can be considered in detail. By using proposed method, pore size distribution of hydrating cement is predicted.

• Cement Symposium
• /
• s.34
• /
• pp.129-137
• /
• 2007

This paper presents a numerical model which can predict degree of cement mineral component, such as $C_3S$, $C_2S$, $C_3A$, $C_4AF$ and microstructure of hydrating cement as a function of water to cement ratio, cement particle size distribution, cement mineral components and temperature. In this model cement particles are parked randomly in cell space and hydration process is described using a multi-component intergrated kinetic model. The simulation result of degree of hydration of cement mineral component agrees well with experiment result. The content of cement hydration product, such as CSH and CH can be obtained as an accompanied result during hydration process. By introducing of equal-area projection method, water withdrawl mechanism and contact area among cement particles can be considered in detail. By using proposed method, pore size distribution of hydrating cement is predicted.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2000.11a
• /
• pp.421-424
• /
• 2000

This paper investigates the characteristics of analytical models in prediction of sound transmission loss for the multi-layered panels with high density mineral wools. The results show that the sandwich model is more adequate to account for sound insulation performance of those panels than the poro-elastic model. In order to improve STC(Sound Transmission Class), the effect of fiber directions of mineral wools is examined, analytically and experimentally. From the comparison of the measurements with the predictions, it is evident that the vertical fiber directions of mineral wools enhance STC value up to 6 dB, compared to that of the horizontal fiber directions.

• Proceedings of the Materials Research Society of Korea Conference
• /
• 2007.11a
• /
• pp.153.1-153.1
• /
• 2007

• Korean Journal of Remote Sensing
• /
• v.22 no.3
• /
• pp.211-219
• /
• 2006

A random forests classifier is applied to multi-sensor data fusion for supervised land-cover classification in order to account for the importance of variable. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. The distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Two different multi-sensor data sets for supervised classification were used to illustrate the applicability of random forests: one with optical and polarimetric SAR data and the other with multi-temporal Radarsat-l and ENVISAT ASAR data sets. From the experimental results, the random forests approach could extract important variables or bands for land-cover discrimination and showed reasonably good performance in terms of classification accuracy.

• Resources Recycling
• /
• v.14 no.5 s.67
• /
• pp.32-39
• /
• 2005

Leaching behavior of nickel contained in waste Multi-Layer Ceramic Capacitor (MLCC) was investigated using a batch reactor. The effects of acid type, acid concentration, leaching temperature, particle size, and reaction time on the extraction of nickel metal from waste MLCC were examined. As a result, 97% of nickel contained in waste MLCC was leached out in 30 min at the temperature of $90^{\circ}C$ under the condition of $HNO_3$ concentration 1N, solid/liquid ratio 5 g/L and particle size $-300/+180{\mu}m$. It was also found that a Jander equation was useful to fit well the leaching rate data. The rate of nickel leaching is controlled by pore diffusion in $BaTiO_3$ layer and has an activation energy of 37.6 kJ/mol (9.0 kcal/mol).

• Tribology and Lubricants
• /
• v.28 no.2
• /
• pp.47-55
• /
• 2012

Generally, to product multi-grade oil like engine oil, a sort of mineral base oil is mixed with a fundamental additive package liquid and a polymer liquid as viscosity index improver in order to improve the lubricating property of base oil. That is, engine oil is the mixture of more than two fluids. Specially, a polymeric type liquid cannot be seen as the linear viscosity like Newtonian fluids. In this research, by using the governing equation describing non-Newtonian hydrodynamic lubrication related with the mixture of incompressible fluids based on the principle of continuum mechanics, it will be compared the bearing performance between the mixture of each liquid to be blended and multi-grade engine oil as a single fluid in a high speed hydrodynamic journal bearing. Further, it is to be found the way estimating the performance of the blended multi-grade engine lubricant in a journal bearing in advance before blending by using the physical properties of mineral base oil, fundamental additive liquid and polymer liquid of viscosity index improver. So, it can be reduced the number of trial and error to get the wanted lubricant by selecting the proper volume fraction of each liquid to satisfy the expected performance and estimating in advance the performance of various multi-grade oils before blending. Therefore, it can be shorten the developing time and saved the developing cost.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.690-690
• /
• 2003

The purpose of this study is to analyze the geological environment changes of tidal flat in the Hampyeong Bay. Especially, it centers on the changes in the sedimentary environment using remote sensing data. Multi-temporal Landsat data were used in this study. Remote sensing methods can be effectively applied for quantitative analysis of geological environment changes in tidal flat.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.359-362
• /
• 2004

In multi-dimensional image, ICA-based feature extraction algorithm, which is proposed in this paper, is for the purpose of detecting target feature about pixel assumed as a linear mixed spectrum sphere, which is consisted of each different type of material object (target feature and background feature) in spectrum sphere of reflectance of each pixel. Landsat ETM+ satellite image is consisted of multi-dimensional data structure and, there is target feature, which is purposed to extract and various background image is mixed. In this paper, in order to eliminate background features (tidal flat, seawater and etc) around target feature (laver farm) effectively, pixel spectrum sphere of target feature is projected onto the orthogonal spectrum sphere of background feature. The rest amount of spectrum sphere of target feature in the pixel can be presumed to remove spectrum sphere of background feature. In order to make sure the excellence of feature extraction method based on ICA, which is proposed in this paper, laver farm feature extraction from Landsat ETM+ satellite image is applied. Also, In the side of feature extraction accuracy and the noise level, which is still remaining not to remove after feature extraction, we have conducted a comparing test with traditionally most popular method, maximum-likelihood. As a consequence, the proposed method from this paper can effectively eliminate background features around mixed spectrum sphere to extract target feature. So, we found that it had excellent detection efficiency.