• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.21-31
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• 2002

This study applied each Neural Networks theory and Fuzzy Set theory to improve accuracy in remotely sensed images. Remotely sensed data have been used to map land cover. The accuracy is dependent on a range of factors related to the data set and methods used. Thus, the accuracy of maps derived from conventional supervised image classification techniques is a function of factors related to the training, allocation, and testing stages of the classification. Conventional image classification techniques assume that all the pixels within the image are pure. That is, that they represent an area of homogeneous cover of a single land-cover class. But, this assumption is often untenable with pixels of mixed land-cover composition abundant in an image. Mixed pixels are a major problem in land-cover mapping applications. For each pixel, the strengths of class membership derived in the classification may be related to its land-cover composition. Fuzzy classification techniques are the concept of a pixel having a degree of membership to all classes is fundamental to fuzzy-sets-based techniques. A major problem with the fuzzy-sets and probabilistic methods is that they are slow and computational demanding. For analyzing large data sets and rapid processing, alterative techniques are required. One particularly attractive approach is the use of artificial neural networks. These are non-parametric techniques which have been shown to generally be capable of classifying data as or more accurately than conventional classifiers. An artificial neural networks, once trained, may classify data extremely rapidly as the classification process may be reduced to the solution of a large number of extremely simple calculations which may be performed in parallel.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.3
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• pp.258-264
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• 2011

A MCS technique is represented to stochastically analyze the uncertainties of wave forces exerted on the upright sections of composite breakwaters. A stochastical models for horizontal and uplift wave forces can be straightforwardly formulated as a function of the probabilistic characteristics of maximum wave height. Under the assumption of wave forces followed by extreme distribution, the behaviors of relative wave forces to Goda's wave forces are studied by the MCS technique. Double-truncated normal distribution is applied to take the effects of uncertainties of scale and shape parameters of extreme distribution into account properly. Averages and variances of relative wave forces are quantitatively calculated with respect to the exceedance probabilities of maximum design wave height. It is found that the averages of relative wave forces may be decreased consistently with the increases of the exceedance probabilities. In particular, the averages on uplift wave force are evaluated slightly larger than those on horizontal wave force, but the variations of coefficient of the former are adversely smaller than those of the latter. It means that the uncertainties of uplift wave forces are smaller than those of horizontal wave forces in the same condition of the exceedance probabilities. Therefore, the present results could be useful to the reliability based-design method that require the statistical properties about the uncertainties of wave forces.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.254-260
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• 2017

The service life of civil infrastructure needs to be maintained or extended through appropriate inspections and maintenance planning, which results from the optimization process. A multi-objective optimization process can lead to more rational and flexible trade-off solutions rather than a single-objective optimization for the service life management of civil infrastructure. Recent investigations on the service life management of civil infrastructure were generally based on minimizing the life-cycle cost analysis and maximizing the structural performance. Various objectives for service life management have been developed using novel probabilistic concepts and methods over the last few decades. On the other hand, an increase in the number of objectives in a multi-objective optimization problem can lead to difficulties in computational efficiency, visualization, and decision making. These difficulties can be overcome using the objective reduction approach to identify the redundant and essential objectives. As a result, the efficiency in computational efforts, visualization, and decision making can be improved. In this paper, the multi-objective optimization using the objective reduction approach was applied to the service life management of concrete bridges. The results showed that four initial objectives can be reduced by two objectives for the optimal service life management.

• Journal of Korea Water Resources Association
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• v.50 no.8
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• pp.551-562
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• 2017

In order to utilize 6-month precipitation forecasts (6 months at maximum) of Global Seasonal Forecast System version 5 (GloSea5), which is being provided by KMA (Korea Meteorological Administration) since 2014, for water resources management as well as other applications, it is needed to correct the forecast model's quantitative bias against observations. This study evaluated applicability of bias-correction skill in GloSea5 and selected an optimal method among 11 techniques that include probabilistic distribution type based, parametric, and non-parametric bias-correction to fix GloSea5's bias in precipitation forecasts. Non-parametric bias-correction provided the most similar results with observed data compared to other techniques in hindcast for the past events, yet relatively generated some discrepancies in forecast. On the contrary, parametric bias-correction produced the most reliable results in both hindcast and forecast periods. The results of this study are expected to be applicable to various applications using seasonal forecast model such as water resources operation and management, hydropower, agriculture, etc.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.8
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• pp.721-728
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• 2017

High-grade gray cast iron (HCI350) was prepared by adding Cr, Mo and Cu to the gray cast iron (GC300). Their microstructure, mechanical properties and fatigue strength were studied. Cast iron was made from round bar and plate-type castings, and was cut and polished to measure the percentage of each microstructure. The size of flake graphite decreased due to additives, while the structure of high density pearlite increased in volume percentage improving the tensile strength and fatigue strength. Based on the fatigue life data obtained from the fatigue test results, the probability - stress - life (P-S-N) curve was calculated using the 2-parameter Weibull distribution to which the maximum likelihood method was applied. The P-S-N curve showed that the fatigue strength of HCI350 was significantly improved and the dispersion of life data was lower than that of GC300. However, the fatigue life according to fatigue stress alleviation increased further. Data for reliability life design was presented by quantitatively showing the allowable stress value for the required life cycle number using the calculated P-S-N curve.

• Fire Science and Engineering
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• v.26 no.4
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• pp.31-41
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• 2012

This study collected 5,100 cases of gas accident occurred in Korea for 14 years from 1995 to 2008, established Database and based on it, analyzed them by detailed forms and reasons. As the result of analyzing the whole city gas accidents with Poisson analysis, the item of "Careless work-Explosion-Pipeline' showed the highest rate of accidents for the next 5 years. And, "Joint Losening and corrosion-Release-Pipeline" showed the lowest rate of accident. In addition, for the result of analyzing only accidents related to LPG vaporizer, "LPG-Vaporizer-Fire" showed the highest rate of accident and "LPG-Vaporizer-Products Faults" showed the lowest rate of accident. Also, as the result of comparing and analyzing foreign LPG accident accompanied by Jet fire, facility's defect which is liquid outflow cut-off device and heat exchanger's defect were analyzed as the main reason causing jet fire, like the case of Korea, but the number of accidents for the next 5 years was the highest in "LPG-Mechanical-Jet fire" and "LPG-Mechanical-Vapor Cloud" showed the highest rate of accidents. By grafting Poisson distribution theory onto gas accident expecting program of the future, it's expected to suggest consistent standard and be used as the scale which can be used in actual field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.724-731
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• 2016

As the structural damage caused by earthquakes has been gradually increasing, estimating the seismic fragility of structures has become essential for earthquake preparation. Seismic fragility curves are widely used as a probabilistic indicator of structural safety against earthquakes, and many researchers have made efforts to develop them in a more accurate and effective manner. However, most of the previous research studies used simplified 2D analytical models when deriving fragility curves, mainly to reduce the numerical simulation time; however, in many cases 2D models are inadequate to accurately evaluate the seismic behavior of a structure and its seismic vulnerability. Thus, this study provides a way to derive more accurate, but still effective, seismic fragility curves by using 3D analytical models. In this method, the reliability analysis software, FERUM, is integrated with the structural analysis software, ZEUS-NL, enabling the automatic exchange of data between these two software packages, and the first order reliability method (FORM), which is not a sampling-based method, is utilized to calculate the structural failure probabilities. These tools make it possible to conduct structural reliability analyses effectively even with 3D models. By using the proposed method, this study conducted a seismic vulnerability assessment of RC frame structures with their 3D analytical models.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.747-754
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• 2021

Purpose: Seismic safety evaluation of a curved bridge must be performed since the curved bridges exhibit the complex behavior rather than the straight bridges, due to geometrical characteristics. In order to conduct the probabilistic seismic assessment of the curved bridge, Seismic fragility evaluation was performed using the uncertainty of the steel material properties of a curved bridge girde, in this study. Method: The finite element (FE) model using ABAQUS platform of the curved bridge girder was constructed, and the statistical parameters of steel materials presented in previous studies were used. 100 steel material models were sampled using the Latin Hypercube Sampling method. As an input ground motion in this study, seismic fragility evaluation was performed by the normalized scale of the Gyeongju earthquake to 0.2g, 0.5g, 0.8g, 1.2g, and 1.5g. Result: As a result of the seismic fragility evaluation of the curved girder, it was found that there was no failure up to 0.03g corresponding to the limit state of allowable stress design, but the failure was started from 0.11g associated with using limit state design. Conclusion: In this study, seismic fragility evaluation was performed considering steel materials uncertainties. Further it must be considered the seismic fragility of the curved bridge using both the uncertainties of input motions and material properties.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1869-1880
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• 2021

Korean Journal of Remote Sensing (KJRS), leading the field of remote sensing and GIS in South Korea for over 37 years, has published interdisciplinary research papers. In this study, we performed the topic modeling based on Latent Dirichlet Allocation (LDA), a probabilistic generative model, to identify the research topics and trends using 1) the whole articles, and 2) specific articles related to natural and environmental disasters published in KJRS by analyzing titles, keywords, and abstracts. The results of LDA showed that 4 topics('Polar', 'Hydrosphere', 'Geosphere', and 'Atmosphere') were identified in the whole articles and the topic of 'Polar' was dominant among them (linear slope=3.51 × 10^-3, p<0.05) over time. For the specific articles related to natural and environmental disasters, the optimal number of topics were 7 ('Marine pollution', 'Air pollution', 'Volcano', 'Wildfire', 'Flood', 'Drought', and 'Heavy rain') and the topic of 'Air pollution' was dominant (linear slope=2.61 × 10^-3, p<0.05) over time. The results from this study provide the history and insight into natural and environmental disasters in KRJS with multidisciplinary researchers.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.141-151
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• 2019

A network of graph data structure is used in many applications to represent interactions between entities. Recently, as the size of the network to be processed due to the development of the big data technology is getting larger, it becomes more difficult to handle it in one server, and thus the necessity of distributed processing is also increasing. In this paper, we propose a distributed processing system for efficiently performing subgraph and stores. To reduce unnecessary searches, we use statistical information of the data to determine the search order through probabilistic scoring. Since the relationship between the vertex and the degree of the graph network may show different characteristics depending on the type of data, the search order is determined by calculating a score to reduce unnecessary search through a different scoring method for a graph having various distribution characteristics. The graph is sequentially searched in the distributed servers according to the determined order. In order to demonstrate the superiority of the proposed method, performance comparison with the existing method was performed. As a result, the search time is improved by about 3 ~ 10% compared with the existing method.