• Structural Engineering and Mechanics
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• v.30 no.6
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• pp.713-732
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• 2008

Serviceability and durability of the concrete members can be seriously affected by the corrosion of steel rebar. Carbonation front and or chloride ingress can destroy the passive film on rebar and may set the corrosion (oxidation process). Depending on the level of oxidation (expansive corrosion products/rust) damage to the cover concrete takes place in the form of expansion, cracking and spalling or delamination. This makes the concrete unable to develop forces through bond and also become unprotected against further degradation from corrosion; and thus marks the end of service life for corrosion-affected structures. This paper presents an analytical model that predicts the weight loss of steel rebar and the corresponding time from onset of corrosion for the known corrosion rate and thus can be used for the determination of time to cover cracking in corrosion affected RC member. This model uses fully the thick-walled cylinder approach. The gradual crack propagation in radial directions (from inside) is considered when the circumferential tensile stresses at the inner surface of intact concrete have reached the tensile strength of concrete. The analysis is done separately with and without considering the stiffness of reinforcing steel and rust combine along with the assumption of zero residual strength of cracked concrete. The model accounts for the time required for corrosion products to fill a porous zone before they start inducing expansive pressure on the concrete surrounding the steel rebar. The capability of the model to produce the experimental trends is demonstrated by comparing the model's predictions with the results of experimental data published in the literature. The effect of considering the corroded reinforcing steel bar stiffness is demonstrated. A sensitivity analysis has also been carried out to show the influence of the various parameters. It has been found that material properties and their inter-relations significantly influence weight loss of rebar. Time to cover cracking from onset of corrosion for the same weight loss is influenced by corrosion rate and state of oxidation of corrosion product formed. Time to cover cracking from onset of corrosion is useful in making certain decisions pertaining to inspection, repair, rehabilitation, replacement and demolition of RC member/structure in corrosive environment.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.3
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• pp.193-202
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• 2014

This paper presents a new method of sampling the climatic data for infrared signature analysis. Historical hourly data from a stationary marine buoy of KMA(Korean Meteorological Administration) are used to select a small number of sample points (N=100) to adequately cover the range of statistics(PDF, CDF) displayed by the original data set (S=56,670). The method uses a coarse bin to subdivide the variable space ($3^5$=243 bins) to make sample points cover the original data range, and a single-point ranking system to select individual points so that uniform coverage (1/N = 0.01) is obtained for each variable. The principal component analysis is used to calculate a joint probability of the coupled climatic variables. The selected sample data show good agreement to the original data set in statistical distribution and they will be used for statistical analysis of infrared signature and susceptibility of naval ships.

• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.109-117
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• 2014

This paper revises the Quine-McCluskey Algorithm to circuit minimization problems. Quine-McCluskey method repeatedly finds the prime implicant and employs additional procedures such as trial-and-error, branch-and-bound, and Petrick's method as a means of circuit minimization. The proposed algorithm, on the contrary, produces an implicant chart beforehand to simplify the search for the prime implicant. In addition, it determines a set cover to streamline the search for $1^{st}$ and $2^{nd}$ essential prime implicants. When applied to 3-variable and 4-variable experimental data, the proposed algorithm has indeed proved to obtain the optimal solutions much more simply and accurately than the Quine-McCluskey method.

• The Korean Journal of Ecology
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• v.9 no.3
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• pp.135-147
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• 1986

The simplification and the searching trends of complex data which assumed relationship between predictor variables and object variables are one of primary objective of ecological research. This study was aimed to apply cononical analysis consisting of canonical correlation analysis and canonical variate analysis related to lichen vegetation and several environmental variables which are elevation, height on grond, exposure side and cover values. Data collected from the Duckyoo National Park in August 1985. Lichen species was ranked by eqivocation information theory with cover values. Canonical correlation analysis was applied to one data set both set both environmental variables and lichem family. In order to make two sets of data matrix the scale of position vector ordination was calculated from the vector scalar product for lichen species. Canonical variate analysis was applied to rearranged data which was made by interval class code for environmental variables. The sharpness values was calculated in frequency of cotingency tables and the dispersion profiles of each species in classes of environmental variables was designed to extract component values based on the decomposition of expected frequencies in contingency table. The results of canonical correlation analysis revealed canonical first correlation value 0.815(89%), and second correlation value 0.083(11%). Significance test showed that the hypothesis of joint mutuallity of canonical correlation is accepted (P>0.05). The relation between canonical score of vegetation variables and that of environmental variable indicated linear tendency.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.429-438
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• 2011

LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3 D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground to the sensor (Wehr & Lohr, 1999). Data from laser scanning can produce products such as digital elevation model (DEM), digital surface model (DSM) and the intensity data. In Vietnam, the LiDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.5
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• pp.799-808
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• 2018

This study develops triacetate-containing functional fabrics with a cool-touch and cool-absorbent. For this purpose we used composite yarns made using triacetate filament and PET High absorbance quick dry filament as well as the composite fabric woven. The fineness of the yarn and structure of fabric varied the cover factor varied. The blend ratio of triacetate was differently set. When the triacetate content was the same, the cool touch of the fabric having a large cover factor and small SMD increased. The surface became smooth and the contact area became large; in addition, both the Qmax value and the cool-touch became large. In the case of similar density, the cool-touch of the fabric having a large content of triacetate increased. The cool-absorbent of the fabric containing triacetate showed a similar level of the PET High absorbance quick dry filament fabric treated with and endothermic cooling agent. It was possible to develop a functional coolness fabric with a cool-touch and a cool-absorbent when the content of triacetate and cover factor were well combined.

• Honam Mathematical Journal
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• v.36 no.2
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• pp.253-261
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• 2014

In this paper, we first will show that for any space X and any Wallman sublattice $\mathcal{A}$ of $\mathcal{R}(X)$ with $Z(X)^{\sharp}{\subseteq}\mathcal{A}$, (${\Phi}^{-1}_{\mathcal{A}}(X)$, ${\Phi}_{\mathcal{A}}$) is the minimal quasi-F cover of X if and only if (${\Phi}^{-1}_{\mathcal{A}}(X)$, ${\Phi}_{\mathcal{A}}$) is a quasi-F cover of X and $\mathcal{A}{\subseteq}\mathcal{Q}_X$. Using this, if X is a locally weakly Lindel$\ddot{o}$f space, the set {$\mathcal{A}|\mathcal{A}$ is a Wallman sublattice of $\mathcal{R}(X)$ with $Z(X)^{\sharp}{\subseteq}\mathcal{A}$ and ${\Phi}^{-1}_{\mathcal{A}}(X)$ is the minimal quasi-F cover of X}, when partially ordered by inclusion, has the minimal element $Z(X)^{\sharp}$ and the maximal element $\mathcal{Q}_X$. Finally, we will show that any Wallman sublattice $\mathcal{A}$ of $\mathcal{R}(X)$ with $Z(X)^{\sharp}{\subseteq}\mathcal{A}{\subseteq}\mathcal{Q}_X$, ${\Phi}_{\mathcal{A}_X}:{\Phi}^{-1}_{\mathcal{A}}(X){\rightarrow}X$ is $z^{\sharp}$-irreducible if and only if $\mathcal{A}=\mathcal{Q}_X$.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.283-285
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• 2005

To account for the importance of variable in multi-sensor data fusion, random forests are applied to supervised land-cover classification. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. Its 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. Supervised classification with a multi-sensor remote sensing data set including optical and polarimetric SAR data was carried out to illustrate the applicability of random forests. From the experimental result, the random forests approach could extract important variables or bands for land-cover discrimination and showed good performance, as compared with other non-parametric data fusion algorithms.

• Journal of Multimedia Information System
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• v.1 no.1
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• pp.1-10
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• 2014

In this paper, we propose a new view synthesis technique for coding of multi-view color and depth data in arbitrary camera arrangements. We treat each camera position as a 3-D point in world coordinates and build clusters of those vertices. Color and depth data within a cluster are gathered into one camera position using a hierarchical representation based on the concept of layered depth image (LDI). Since one camera can cover only a limited viewing range, we set multiple reference cameras so that multiple LDIs are generated to cover the whole viewing range. Therefore, we can enhance the visual quality of the reconstructed views from multiple LDIs comparing with that from a single LDI. From experimental results, the proposed scheme shows better coding performance under arbitrary camera configurations in terms of PSNR and subjective visual quality.

• Proceedings of the KSRS Conference
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• v.2
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• pp.848-851
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• 2006

Green vegetation is one of the most critical factors for environment conditions thorough modulating evapotranspiration and absorption of solar radiation. Thus, fractional green vegetation cover (FVC) plays an important role in observing and managing environment. Remote sensing provides a seemingly obvious data source for quantifying FVC over large area. Therefore we compared a set of methods for estimating FVC using hyperspectral remote sensing data. For our study, we used Hyperion imagery acquired in April, 2002. In order to achieve our efforts, we analyzed simple NDVI-based method and spectral mixture analysis (SMA) models that were applied a variety of combinations of possible endmembers.