• Clinical and Experimental Pediatrics
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• v.53 no.12
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• pp.979-984
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• 2010

Recent progress in neonatal medicine has enabled survival of many extremely low-birth-weight infants. Prenatal steroids, surfactants, and non-invasive ventilation have helped reduce the incidence of the classical form of bronchopulmonary dysplasia characterized by marked fibrosis and emphysema. However, a new form of bronchopulmonary dysplasia marked by arrest of alveolarization remains a complication in the postnatal course of extremely low-birth-weight infants. To better understand this challenging complication, detailed alveolarization mechanisms should be delineated. Proper alveolarization involves the temporal and spatial coordination of a number of cells, mediators, and genes. Cross-talk between the mesenchyme and the epithelium through soluble and diffusible factors are key processes of alveolarization. Lung interstitial cells derived from the mesenchyme play a crucial role in alveolarization. Peak alveolar formation coincides with intense lung interstitial cell proliferation. Myofibroblasts are essential for secondary septation, a critical process of alveolarization, and localize to the front lines of alveologenesis. The differentiation and migration of myofibroblasts are strictly controlled by various mediators and genes. Disruption of this finely controlled mechanism leads to abnormal alveolarization. Since arrest in alveolarization is a hallmark of a new form of bronchopulmonary dysplasia, knowledge regarding the role of lung interstitial cells during alveolarization and their control mechanism will enable us to find more specific therapeutic strategies for bronchopulmonary dysplasia. In this review, the role of lung interstitial cells during alveolarization and control mechanisms of their differentiation and migration will be discussed.

• Journal of the Korean Applied Science and Technology
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• v.12 no.2
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• pp.29-39
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• 1995

The phase separated structure and the electro-optical properties of the (polymer/liquid) crystal : LC) composite film strongly depended on the weight fraction of LC in it. The continuous LC phase was formed in a three-dimensional polymer network when the LC weight fraction was above 40wt%. The aggregation structure of the composite film could be controlled by controlling the solvent evaporation velocity during the film preparation process. The smaller LC domains or channels were formed in the case of the faster solvent evaporation velocity. The composite film exhibited reversible light scattering-light transmission switching upon electric field -OFF and -ON states, respectiverly. The light scattering properties of the composite film strongly depended on the spatial distortion of the nematic directors as well as the mismatch in refractive indices between matrix polymer and LC.

• Journal of environmental and Sanitary engineering
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• v.12 no.3
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• pp.31-39
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• 1997

The seasonal and spatial changes in dissolved organic carbon(DOC) in Lake Kasumigaura, a shallow and eutrophic lake, were analyzed from October 1992 to October 1995. The proportion of T-DOC was classified by labile(L-DOC) and refractory DOC(R-DOC) on the basis of long-term incubation, fractionated the molecular weight of T-DOC by ultrafiltration. The porewater DOC were measured at sedimental surface of the central basin in order to evaluate the DOC released from the sediment. The proportion of L-DOC and R-DOC were accounted for about 15% and 85% of T-DOC in the central basin, respectively. The molecular weight(MW) distribution occupied some 60% of the low and medium MW. The horizontal variation of T-DOC concentrations trended to higher in the central basin than in the inlet of influent rivers, because of contribution by autochthonous organic carbon loading. The seasonal variation of T-DOC showed to higher summer than winter in the inlet of influent, but at the central basin it fluctuated little seasonally. During the high increase of porewater DOC in 1994 evaluated the high release possibility from the sediment surface (10cm). The present study suggests that autochthonous organic carbon loading must be controlled for improving the water quality of the eutrophic lakes.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.37-46
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• 2016

The difference between definition time of GPS (Global Positioning System) position data and actual display time of car positions on a map could reduce the accuracy of car positions displayed in PND (Portable Navigation Device)-type CNS (Car Navigation System). Due to the time difference, the position of the car displayed on the map is not its current position, so an improved method to fix these problems is required. It is expected that a method that uses predicted future positionsto compensate for the delay caused by processing and display of the received GPS signals could mitigate these problems. Therefore, in this study an analysis was conducted to correct late processing problems of map positions by mapmatching using a Kalman filter with only GPS position data and a RRF (Road Reduction Filter) technique in a light-weight CNS. The effects on routing services are examined by analyzing differences that are decomposed into along and across the road elements relative to the direction of advancing car. The results indicate that it is possible to improve the positional accuracy in the along-the-road direction of a light-weight CNS device that uses only GPS position data, by applying a Kalman filter and RRF.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.293-302
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• 2019

In mountain accident events, it is important for the search team commander to determine the search area in order to secure the Golden Time. Within this period, assistance and treatment to the concerned individual will most likely prevent further injuries and harm. This paper proposes a method to determine the search priority area based on missing persons behavior and missing persons incidents statistics. GIS (Geographic Information System) and MCDM (Multi Criteria Decision Making) are integrated by applying WLC (Weighted Linear Combination) techniques. Missing persons were classified into five types, and their behavioral characteristics were analyzed to extract seven geographic analysis factors. Next, index values were set up for each missing person and element according to the behavioral characteristics, and the raster data generated by multiplying the weight of each element are superimposed to define models to select search priority areas, where each weight is calculated from the AHP (Analytical Hierarchy Process) through a pairwise comparison method obtained from search operation experts. Finally, the model generated in this study was applied to a missing person case through a virtual missing scenario, the priority area was selected, and the behavioral characteristics and topographical characteristics of the missing persons were compared with the selected area. The resulting analysis results were verified by mountain rescue experts as 'appropriate' in terms of the behavior analysis, analysis factor extraction, experimental process, and results for the missing persons.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.305-326
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• 2019

Discriminative correlation filter (DCF) based tracking algorithms have recently shown impressive performance on benchmark datasets. However, amount of recent researches are vulnerable to heavy occlusions, irregular deformations and so on. In this paper, we intend to solve these problems and handle the contradiction between accuracy and real-time in the framework of tracking-by-detection. Firstly, we propose an innovative strategy to combine the template and color-based models instead of a simple linear superposition and rely on the strengths of both to promote the accuracy. Secondly, to enhance the discriminative power of the learned template model, the spatial regularization is introduced in the learning stage to penalize the objective boundary information corresponding to features in the background. Thirdly, we utilize a discriminative multi-scale estimate method to solve the problem of scale variations. Finally, we research strategies to limit the computational complexity of our tracker. Abundant experiments demonstrate that our tracker performs superiorly against several advanced algorithms on both the OTB2013 and OTB2015 datasets while maintaining the high frame rates.

• Journal of The Geomorphological Association of Korea
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• v.20 no.1
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• pp.21-33
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• 2013

Weight of evidence model was applied for potential mapping of mountainous wetland to reduce the range of the field survey and to increase the efficiency of operations because the surveys of mountainous wetland need a lot of time and money owing to inaccessibility and extensiveness. The relationship between mountainous wetland location and related factors is expressed as a probability by Weight of evidence model. For this, the spatial database consist of slope map, curvature map, vegetation index map, wetness index map, soil drainage rating map was constructed in Yeongnam area, Korea, and weights of evidence based on the relationship between mountainous wetland location and each factor rating were calculated. As a result of correlation analysis between mountainous wetland location and each factors rating using likelihood ratio values, the probability of mountainous wetlands were increased at condition of lower slope, lower curvature, lower vegetation index value, lower wetness value, moderate soil drainage rating. Mountainous Wetland Potential Index(MWPI) was calculated by summation of the likelihood ratio and mountainous wetland potential map was constucted from GIS integration. The mountain wetland potential map was verified by comparison with the known mountainous wetland locations. The result showed the 75.48% in prediction accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1633-1649
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• 2017

In remote sensing image processing, the traditional fusion algorithm is based on the Intensity-Hue-Saturation (IHS) transformation. This method does not take into account the texture or spectrum information, spatial resolution and statistical information of the photos adequately, which leads to spectrum distortion of the image. Although traditional solutions in such application combine manifold methods, the fusion procedure is rather complicated and not suitable for practical operation. In this paper, an improved IHS transformation fusion algorithm based on the local variance weighting scheme is proposed for remote sensing images. In our proposal, firstly, the local variance of the SPOT (which comes from French "Systeme Probatoire d'Observation dela Tarre" and means "earth observing system") image is calculated by using different sliding windows. The optimal window size is then selected with the images being normalized with the optimal window local variance. Secondly, the power exponent is chosen as the mapping function, and the local variance is used to obtain the weight of the I component and match SPOT images. Then we obtain the I' component with the weight, the I component and the matched SPOT images. Finally, the final fusion image is obtained by the inverse Intensity-Hue-Saturation transformation of the I', H and S components. The proposed algorithm has been tested and compared with some other image fusion methods well known in the literature. Simulation result indicates that the proposed algorithm could obtain a superior fused image based on quantitative fusion evaluation indices.

• Journal of Environmental Impact Assessment
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• v.26 no.3
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• pp.171-180
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• 2017

The vulnerability analysis of climate change driven disaster has been used as institutional framework for the urban policies of disaster prevention since 2012. However, some problems have occurred due to the structure of vulnerability analysis, such as overweighted variables and duplicated application of variables of similar meaning. The goal of this study is to examine the differences of results between the method of current guideline and the method of weight equalization. For this, we examines the current structural framework of the vulnerability analysis, and performs empirical analysis. As a result, the extent and magnitude of vulnerability showed different spatial patterns depending on the weighting methods. Standardized weighting method relatively represented wider vulnerable areas compared to the pre-existing method which follows the current instruction manual. To apply the results of vulnerability analysis to urban planning process for disaster prevention, this study suggests that the reliability of the results should be ensured by improving analytical framework and detailed review of the results.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.47-57
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• 2010

The aim of this study is to detect landslide using digital aerial photography and apply the landslide to landslide susceptibility mapping by artificial neural network (ANN) and geographic information system (GIS) at Jinbu area where many landslides have occurred in 2006 by typhoon Ewiniar, Bilis and Kaemi. Landslide locations were identified by visual interpretation of aerial photography taken before and after landslide occurrence, and checked in field. For landslide susceptibility mapping, maps of the topography, geology, soil, forest, lineament, and landuse were constructed from the spatial data sets. Using the factors and landslide location and artificial neural network, the relative weight for the each factors was determinated by back-propagation algorithm. As the result, the aspect and slope factor showed higher weight in 1.2-1.5 times than other factors. Then, landslide susceptibility map was drawn using the weights and finally, the map was validated by comparing with landslide locations that were not used directly in the analysis. As the validation result, the prediction accuracy showed 81.44%.