• Journal of the Korean Institute of Gas
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• v.12 no.3
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• pp.56-63
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• 2008

We have garnered 3,593 data of gas [Natural Gas (NG) and Liquefied Petroleum Gas (LPG)] accidents reported for 16 years from 1991, and then analyzed the accidents according to their types and causes based on the classified database. According to the results the gas leak has been the most common accident followed by the explosion and then fire accidents. The most frequent accident-occurring locations for fire, explosion and leak are recognized around the valve, hose and pipeline, respectively. In addition, we have applied the Poisson analysis to predict the most-likely probabilities of fire, explosion and release in the upcoming 5 years. From this research we have assured the successive database updating will highly improve the anticipating-probability accuracy and thus it will play a key role as a significant safety-securing guideline against the gas disasters.

• International Journal of Highway Engineering
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• v.8 no.3 s.29
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• pp.29-37
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• 2006

The primary objective of this study is to characterize traffic axle loadings that consider Korea specific traffic conditions for developing mechanistic-based pavement design method as a part of Korea Pavement Research Program(KPRP). Although the concept of equivalent single axle load(ESAL) has been generally used since the 1960s for the pavement design, the mechanistic-based pavement design procedure requires more accurate axle loading data on the specific pavement. In this study, axle loading data were collected according to vehicle type and highway functional classification. Axle-load spectrum was then standardized by cumulative density function(cdf), because the axle load spectrum could vary from the observed site, truck traffic volume, and truck type, Finally, this study presented the procedure and S-shaped exponential models for characterizing axle load spectra according to vehicle type and highway functional classification.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.107-120
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• 2017

There are many wildfire risk indices worldwide, but objective comparisons between such various wildfire risk indices and surface dryness indices have not been conducted for the wildfire cases in Korea. This paper describes a sensitivity analysis on the wildfire risk indices and surface dryness indices for Korea using LDAPS(Local Analysis and Prediction System) meteorological dataset on a 1.5-km grid and MODIS(Moderate-resolution Imaging Spectroradiometer) satellite images on a 1-km grid. We analyzed the meteorology-based wildfire risk indices such as the Australian FFDI(forest fire danger index), the Canadian FFMC(fine fuel moisture code), the American HI(Haines index), and the academically presented MNI(modified Nesterov index). Also we examined the satellite-based surface dryness indices such as NDDI(normalized difference drought index) and TVDI(temperature vegetation dryness index). As a result of the comparisons between the six indices regarding 120 wildfire cases with the area damaged over 1ha during the period between January 2013 and May 2017, we found that the FFDI and FFMC showed a good predictability for most wildfire cases but the MNI and TVDI were not suitable for Korea. The NDDI can be used as a proxy parameter for wildfire risk because its average CDF(cumulative distribution function) scores were stably high irrespective of fire size. The indices tested in this paper should be carefully chosen and used in an integrated way so that they can contribute to wildfire forecasting in Korea.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• The KIPS Transactions:PartB
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• v.14B no.3 s.113
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• pp.145-152
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• 2007

In this paper, we propose an automatic extraction model for unknown translations and implement an unknown translation extraction system using the proposed model. The proposed model as a phrase-alignment model is incorporated with three models: a phrase-boundary model, a language model, and a translation model. Using the proposed model we implement the system for extracting unknown translations, which consists of three parts: construction of parallel corpora, alignment of Korean and English words, extraction of unknown translations. To evaluate the performance of the proposed system, we have established the reference corpus for extracting unknown translation, which comprises of 2,220 parallel sentences including about 1,500 unknown translations. Through several experiments, we have observed that the proposed model is very useful for extracting unknown translations. In the future, researches on objective evaluation and establishment of parallel corpora with good quality should be performed and studies on improving the performance of unknown translation extraction should be kept up.

• 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.