• Journal of Korean Society of Steel Construction
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• v.11 no.4 s.41
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• pp.329-338
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• 1999

A systematic procedure to evaluate fatigue damages and to predict remaining fatigue lives is introduced for a steel railway bridge. Fatigue damages are evaluated by using the currently available fatigue damage theory. Fatigue lives with the condition of fatigue crack initiation are estimated by the probabilistic approach based on the reliability theory as well as the simplified procedure. A equivalent deterministic procedure is also suggested to assess the remaining fatigue life under various traffic conditions. Numerical simulations are used to assess dynamic stress histories with correction factors. Loading models are obtained from the passenger volume data. Train coincidences are also considered. Based on the results, the fatigue life is found to be underestimated by without considering the coincidence of trains on the bridge. The simplified method proposed in this study are found to yield approximately the same results as the systematic procedure.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.69-87
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• 2014

This paper suggests a conditional simulation framework based on multiple data transformations for geostatistical simulation of compositional data. First, log-ratio transformation is applied to original compositional data in order to apply conventional statistical methodologies. As for the next transformations that follow, minimum/maximum autocorrelation factors (MAF) and indicator transformations are sequentially applied. MAF transformation is applied to generate independent new variables and as a result, an independent simulation of individual variables can be applied. Indicator transformation is also applied to non-parametric conditional cumulative distribution function modeling of variables that do not follow multi-Gaussian random function models. Finally, inverse transformations are applied in the reverse order of those transformations that are applied. A case study with surface sediment compositions in tidal flats is carried out to illustrate the applicability of the presented simulation framework. All simulation results satisfied the constraints of compositional data and reproduced well the statistical characteristics of the sample data. Through surface sediment classification based on multiple simulation results of compositions, the probabilistic evaluation of classification results was possible, an evaluation unavailable in a conventional kriging approach. Therefore, it is expected that the presented simulation framework can be effectively applied to geostatistical simulation of various compositional data.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.87-94
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• 2008

In this paper, we propose a new vision-based fire detection method for a real-life application. Most previous vision-based methods using color information and temporal variation of pixel produce frequent false alarms because they used a lot of heuristic features. Furthermore there is also computation delay for accurate fire detection. To overcome these problems, we first detected candidated fire regions by using background modeling and color model of fire. Then we made probabilistic models of fire by using a fact that fire pixel values of consecutive frames are changed constantly and applied them to a Bayesian Network. In this paper we used two level Bayesian network, which contains the intermediate nodes and uses four skewnesses for evidence at each node. Skewness of R normalized with intensity and skewnesses of three high frequency components obtained through wavelet transform. The proposed system has been successfully applied to many fire detection tasks in real world environment and distinguishes fire from moving objects having fire color.

• Journal of KIISE:Software and Applications
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• v.34 no.2
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• pp.140-149
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• 2007

This paper presents a statistical model for Korean dependency-based parsing. Although Korean is one of free word order languages, it has the feature of which some word order is preferred to local contexts. Earlier works proposed parsing models using modification lengths due to this property. Our model uses headible path contexts for modification length probabilities. Using a headible path of a dependent it is effective for long distance relation because the large surface context for a dependent are abbreviated as its headible path. By combined with lexical bigram dependency, our probabilistic model achieves 86.9% accuracy in eojoel analysis for KAIST corpus, more improvement especially for long distance dependencies.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.157-166
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• 2008

This study proposed a model to estimate traffic accident likelihood using real-time traffic data obtained from freeway traffic surveillance systems. Traffic variables representing spatio-temporal variations of traffic conditions were utilized as independent variables in the proposed models. Binary logistics regression modelings were conducted to correlate traffic variables and accident data that were collected from the Seohaean freeway during recent three years, from 2004 to 2006. To apply more reliable traffic variables, outlier filtering and data imputation were also performed. The outcomes of the model that are actually probabilistic measures of accident occurrence would be effectively utilized not only in designing warning information systems but also in evaluating the effectiveness of various traffic operations strategies in terms of traffic safety.

• Earthquakes and Structures
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• v.9 no.1
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• pp.49-71
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• 2015

The present paper aims at evaluating damage and collapse behavior of low-rise buildings with unidirectional mass irregularities in plan (torsional buildings). In previous earthquake events, such buildings have been exposed to extensive damages and even total collapse in some cases. To investigate the performance and collapse behavior of such buildings from probabilistic points of view, three-dimensional three and six-story reinforced concrete models with unidirectional mass eccentricities ranging from 0% to 30% and designed with modern seismic design code provisions specific to intermediate ductility class were subjected to nonlinear static as well as extensive nonlinear incremental dynamic analysis (IDA) under a set of far-field real ground motions containing 21 two-component records. Performance of each model was then examined by means of calculating conventional seismic design parameters including the response reduction (R), structural overstrength (${\Omega}$) and structural ductility (${\mu}$) factors, calculation of probability distribution of maximum inter-story drift responses in two orthogonal directions and calculation collapse margin ratio (CMR) as an indicator of performance. Results demonstrate that substantial differences exist between the behavior of regular and irregular buildings in terms of lateral load capacity and collapse margin ratio. Also, results indicate that current seismic design parameters could be non-conservative for buildings with high levels of plan eccentricity and such structures do not meet the target "life safety" performance level based on safety margin against collapse. The adverse effects of plan irregularity on collapse safety of structures are more pronounced as the number of stories increases.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.712-721
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• 2010

This paper proposes a new fire-flame detection method using probabilistic membership function of visual features and Fuzzy Finite Automata (FFA). First, moving regions are detected by analyzing the background subtraction and candidate flame regions then identified by applying flame color models. Since flame regions generally have continuous and an irregular pattern continuously, membership functions of variance of intensity, wavelet energy and motion orientation are generated and applied to FFA. Since FFA combines the capabilities of automata with fuzzy logic, it not only provides a systemic approach to handle uncertainty in computational systems, but also can handle continuous spaces. The proposed algorithm is successfully applied to various fire videos and shows a better detection performance when compared with other methods.

• Earthquakes and Structures
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• v.11 no.3
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• pp.517-538
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• 2016

This paper presents a probabilistic fragility analysis for two groups of bridges: simply supported and integral bridges. Comparisons are based on the seismic fragility of the bridges subjected to accelerograms of two seismic sources. Three-dimensional finite-element models of the bridges were created for each set of bridge samples, considering the nonlinear behaviour of critical bridge components. When the seismic hazard in the site is controlled by a few seismic sources, it is important to quantify separately the contribution of each fault to the structure vulnerability. In this study, seismic records come from earthquakes that originated in strike-slip and reverse faulting mechanisms. The influence of the earthquake mechanism on the seismic vulnerability of the bridges was analysed by considering the displacement ductility of the piers. An in-depth parametric study was conducted to evaluate the sensitivity of the bridges' seismic responses to variations of structural parameters. The analysis showed that uncertainties related to the presence of lap splices in columns and superstructure type in terms of integral or simply supported spans should be considered in the fragility analysis of the bridge system. Finally, the fragility curves determine the conditional probabilities that a specific structural demand will reach or exceed the structural capacity by considering peak ground acceleration (PGA) and acceleration spectrum intensity (ASI). The results also show that the simply supported bridges perform consistently better from a seismic perspective than integral bridges and focal mechanism of the earthquakes plays an important role in the seismic fragility analysis of highway bridges.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1491-1500
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• 2008

This paper proposes an intelligent surveillance system to recognize suspicious patterns of the human behavior by using the Hidden Markov Model. First, the method finds foot area of the human by motion detection algorithm from image sequence of the surveillance camera. Then, these foot locus form observation series of features to learn the HMM. The feature that is position of the human foot is changed to each code that corresponds to a specific label among 16 local partitions of image region. Therefore, specific moving patterns formed by the foot locus are the series of the label numbers. The Baum-Welch algorithm of the HMM learns each suspicious and specific pattern to classify the human behaviors. To recognize the inputted human behavior pattern in a test image, the probabilistic comparison between the learned pattern of the HMM and foot series to be tested decides the categorization of the test pattern. The experimental results show that the method can be applied to detect a suspicious person prowling in corridor.

• Journal of Korean Society on Water Environment
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• v.33 no.2
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• pp.140-148
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• 2017

An important factor in determining the design and treatment efficiency of wastewater treatment plants (WWTPs) is the quantity and quality of influent. These detailed and accurate information is essential for process control, diagnosis and operation, as well as the basis in designing the plant, selecting the process and determining the optimal capacity of each bioreactor. Probabilistic models are used to predict the wastewater quantity and quality of WWTPs, which are widely used to improve the design and operation of WWTPs. In this study, the optimal probability distribution of time series influent data was derived for predicting water quantity and quality, and wastewater influent data were generated using the Monte Carlo simulation analysis. In addition, we estimated various alternatives for the improvement of bioreactor operations based on present operation condition using the generated influent data and activated sludge model, and suggested the alternative that can operate the most effectively. Thus, the influent quantity and quality are highly correlated with the actual operation data, so that the actual WWTPs influent characteristics were well reproduced. Using this will improve the operating conditions of WWTPs, and a proposed improvement plan for the current TMS (Tele Monitoring System) effluent quality standards can be made.