• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.599-610
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• 2021

Early detection of small concrete crack or reinforcement corrosion is necessary for Structural Health Monitoring (SHM). Global vibration based methods are advantageous over local methods because of simple equipment installation and cost efficiency. Among vibration based techniques, FRF based methods are preferred over modal based methods. In this study, a new coupled method using frequency response function (FRF) and proper orthogonal modes (POM) is proposed by using the dynamic characteristic of a damaged beam. For the numerical simulation, wave finite element (WFE), coupled with traditional finite element (FE) method is used for effectively incorporating the damage related information and faster computation. As reported in literature, hybrid combination of wave function based wave finite element method and shape function based finite element method can addresses the mid frequency modelling difficulty as it utilises the advantages of both the methods. It also reduces the dynamic matrix dimension. The algorithms are implemented on a three-dimensional reinforced concrete beam. Damage is modelled and studied for two scenarios, i.e., crack in concrete and rebar corrosion. Single and multiple damage locations with different damage length are also considered. The proposed methodology is found to be very sensitive to both single- and multiple- damage while being computationally efficient at the same time. It is observed that the detection of damage due to corrosion is more challenging than that of concrete crack. The similarity index obtained from the damage parameters shows that it can be a very effective indicator for appropriately indicating initiation of damage in concrete structure in the form of spread corrosion or invisible crack.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.25-44
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• 2010

With the increasing popularity of mobile devices, it has become necessary to protect private information and content in these devices. Face recognition has been favored over conventional passwords or security keys, because it can be easily implemented using a built-in camera, while providing user convenience. However, because mobile devices can be used both indoors and outdoors, there can be many illumination changes, which can reduce the accuracy of face recognition. Therefore, we propose a new face recognition method on a mobile device robust to illumination variations. This research makes the following four original contributions. First, we compared the performance of face recognition with illumination variations on mobile devices for several illumination normalization procedures suitable for mobile devices with low processing power. These include the Retinex filter, histogram equalization and histogram stretching. Second, we compared the performance for global and local methods of face recognition such as PCA (Principal Component Analysis), LNMF (Local Non-negative Matrix Factorization) and LBP (Local Binary Pattern) using an integer-based kernel suitable for mobile devices having low processing power. Third, the characteristics of each method according to the illumination va iations are analyzed. Fourth, we use two matching scores for several methods of illumination normalization, Retinex and histogram stretching, which show the best and $2^{nd}$ best performances, respectively. These are used as the inputs of an SVM (Support Vector Machine) classifier, which can increase the accuracy of face recognition. Experimental results with two databases (data collected by a mobile device and the AR database) showed that the accuracy of face recognition achieved by the proposed method was superior to that of other methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.2
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• pp.121-131
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• 1986

The stiffness matrix of circularly curved frame elements including the warping effects is formulated by the solutions of vlasov's differential equations, and the procedure for the elastic static analysis of curved girder systems by the displacement method is presented. The validity of this method has been demonstrated by comparing the analysis results with other solutions. And if the tangential lines of the two frame element axes connected at any nodal point coincide, the transformation to the global coordinate system can be omitted when we analyze the structures consisting of circularly curved elements. The theory introduced in this thesis can be applied with sufficient accuracy to the structures built up with horizontally circular curved frame elements which have closed or open cross sections and are symmetric to the axis perpendicular to the plane of the curvature, such as prestressed concrete box girder bridges.

• Atmosphere
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• v.24 no.2
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• pp.245-251
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• 2014

Statistical trajectory analysis has been widely used to identify potential source regions for chemically and radiatively important chemical species in the atmosphere. The most widely used method is a statistical source-receptor model developed by Stohl (1996), of which the underlying principle is that elevated concentrations at an observation site are proportionally related to both the average concentrations on a specific grid cell where the observed air mass has been passing over and the residence time staying over that grid cell. Thus, the method can compute a residence-time-weighted mean concentration for each grid cell by superimposing the back trajectory domain on the grid matrix. The concentration on a grid cell could be used as a proxy for potential source strength of corresponding species. This technical note describes the statistical trajectory approach and introduces its application to estimate potential source regions of $CO_2$ enhancements observed at Korean Global Atmosphere Watch Observatory in Anmyeon-do. Back trajectories are calculated using HYSPLIT 4 model based on wind fields provided by NCEP GDAS. The identified $CO_2$ potential source regions responsible for the pollution events observed at Anmyeon-do in 2010 were mainly Beijing area and the Northern China where Haerbin, Shenyang and Changchun mega cities are located. This is consistent with bottom-up emission information. In spite of inherent uncertainties of this method in estimating sharp spatial gradients within the vicinity of the emission hot spots, this study suggests that the statistical trajectory analysis can be a useful tool for identifying anthropogenic potential source regions for major GHGs.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.5
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• pp.873-882
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• 1992

The study is concerned with the rigid-plastic element analysis for axisymmetric hydromechanical deep drawing in which the fluid flow influences the metal deformation. Due to the fluid pressure acting on the sheet material hydromechanical deep drawing is distinguished from the conventional deep drawing processes. In considering the pressure effect, the governing equation for fluid pressure is solved and the result is reflected on the global stiffness matrix. The solution procedure consists of two stages ; i.e., initial bulging of the sheet surface before the initiation of steady fluid flow in the flange and fluid-lubricated stage. The problem is decoupled between fluid analysis and analysis of solid deformation by deformation by iterative feedback of mutual computed results. The corresponding experiments are carried out for axisymmetric hydro-mechanical deep drawing of annealled aluminium sheet as well as for deep drawing. It has been shown from the experiments that the limit drawing ratio for hydro-mechanical deep drawing is improved as compared with deep drawing. The computed results are in good agreement with the experiment for variation of punch head and chamber pressure with respect to the punch travel and for distribution of thicknees strain. It is thus shown that the present method of analysis can be effectively applied to the analysis of axisymmetric hydro-mechanical deep drawing processes.

• Investigative Magnetic Resonance Imaging
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• v.15 no.2
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• pp.110-122
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• 2011

Purpose : The purpose of this study is to establish the method generating human brain anatomical connectivity from Korean children and evaluating the network topological properties using small-world network analysis. Materials and Methods : Using diffusion tensor images (DTI) and parcellation maps of structural MRIs acquired from twelve healthy Korean children, we generated a brain structural connectivity matrix for individual. We applied one sample t-test to the connectivity maps to derive a representative anatomical connectivity for the group. By spatially normalizing the white matter bundles of participants into a template standard space, we obtained the anatomical brain network model. Network properties including clustering coefficient, characteristic path length, and global/local efficiency were also calculated. Results : We found that the structural connectivity of Korean children group preserves the small-world properties. The anatomical connectivity map obtained in this study showed that children group had higher intra-hemispheric connectivity than inter-hemispheric connectivity. We also observed that the neural connectivity of the group is high between brain stem and motorsensory areas. Conclusion : We suggested a method to examine the anatomical brain network of Korean children group. The proposed method can be used to evaluate the efficiency of anatomical brain networks in people with disease.

• Applied Microscopy
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• v.21 no.1
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• pp.1-20
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• 1991

The effects of exogenous $Ca^{2+}$ stimulation on the post-ischemic myocardial cells were studied using isolated Langendorff-perfused guinea pig hearts. At the starting point of reperfusion, Tyrode solutions, each containing 2.0mM, 4.0mM and 8.0mM $CaCl_2$ respectively, were administered for 2 minutes apart by descending, ascending, or by combined sequences followed by standard Tyrode solution containing 1.0mM $CaCl_2$. The minutes of global ischemia produced reversible but moderate to severe degree of myocardial ultrastructrual changes including focal destruction of sarcolemma, loss of nuclear matrix, clumping and margination of chromatins, mitochondrial swelling, destruction of mitochondrial cristae, shortening of sarcomeres, focal loss of myofibrils, and separation of cell junctions. In spite of reperfusion, the ultrastructure was more severely damaged and irreversible changes such as intracellular fluid accumulation, contracted sarcomeres, mitochondrial destruction, disruption of sarcolemma, loss of nuclear matrix, and separation of cell junction were observed in a large number of cells. In contrast, Tyrode-perfused $Ca^{2+}$-stimulated myocardial cells showed relatively well preserved ultrastucture, except slight changes including focal mitochondrial swelling, widening of T-tubule, and widening of cell junctions, especially at fasciae adherentes. The post-ischemic $Ca^{2+}$-stimulated reperfused myocardial cells produced focal changes such as mitochondrial destruction, disintegration of sarcolemma, widening of T-tubule, and intracellular fluid accumulation with slight variation in degree of changes by the method of $Ca^{2+}$ administration sequence. However, in a large number of the myocardial cells, chromatins were redistributed relatively evenly in the nuclear matrix, mitochondrial cristae were tightly packed, and a considerable number of intramitochondrial granules and glycogen granules reap-pealed. These results indicate that exogenous $Ca^{2+}$ stimulation in the initial period of reperfusion may be beneficial to salvage or to reduce the post-ischemic myocardium from further deleterious changes, and that the beneficial effects may be derived from the reserves of the function of the intracellular $Ca^{2+}$ regulating organelles and/or from the responsiveness of contractile apparatus to $Ca^{2+}$ stimulation.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.1
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• pp.64-73
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• 2011

Oil price prediction is an important issue for the regulators of the government and the related industries. When employing the time series techniques for prediction, however, it becomes difficult and challenging since the behavior of the series of oil prices is dominated by quantitatively unexplained irregular external factors, e.g., supply- or demand-side shocks, political conflicts specific to events in the Middle East, and direct or indirect influences from other global economical indices, etc. Identifying and quantifying the relationship between oil price and those external factors may provide more relevant prediction than attempting to unclose the underlying structure of the series itself. Technically, this implies the prediction is to be based on the vectoral data on the degrees of the relationship rather than the series data. This paper proposes a novel method for time series prediction of using Semi-Supervised Learning that was originally designed only for the vector types of data. First, several time series of oil prices and other economical indices are transformed into the multiple dimensional vectors by the various types of technical indicators and the diverse combination of the indicator-specific hyper-parameters. Then, to avoid the curse of dimensionality and redundancy among the dimensions, the wellknown feature extraction techniques, PCA and NLPCA, are employed. With the extracted features, a timepointspecific similarity matrix of oil prices and other economical indices is built and finally, Semi-Supervised Learning generates one-timepoint-ahead prediction. The series of crude oil prices of West Texas Intermediate (WTI) was used to verify the proposed method, and the experiments showed promising results : 0.86 of the average AUC.

• KSBB Journal
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• v.31 no.4
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• pp.263-269
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• 2016

For decades, the microorganisms in arctic soils have been newly discovered according to the climate change and global warming. In this study, the chemical structure of a lipid A molecule from Pseudomonas sp. strain PAMC 28615 which was newly discovered from arctic soils was characterized by mass spectrometric approaches such as matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) and MALDI multi-stage tandem mass spectrometry (MS). First, lipopolysaccharide (LPS) from Pseudomonas sp. strain PAMC 28615 was extracted and subsequently hydrolyzed to obtain the lipid A. The parent ion peak at m/z 1632 was determined by MALDI-TOF MS, which also can validate our lipid A purification method. For detailed structural determination, we performed the multiple-stage tandem mass analysis ($MS^4$) of the parent ion, and subsequently the abundant fragment ions in each MS stage are tested. The fragment ions in each MS stage were produced from the loss of phosphate groups and fatty acyl groups, which could be used to confirm the composition or the position of the lipid A components. Consequently, the mass spectrometry-based lipid A profiling method could provide the detail chemical structure of lipid A from the Pseudomonas sp. strain PAMC 28615 as an arctic bacterium from the frozen arctic soil.