• Journal of Food Hygiene and Safety
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• v.35 no.1
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• pp.37-44
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• 2020

This study investigated the probability of foodborne illness caused by raw oyster consumption contaminated with high risk Vibrio species such as V. vulnificus and V. cholerae. Eighty-eight raw oyster samples were collected from the south coast, west coast and Seoul areas, and examined for the prevalence of high risk Vibrio species. The growth patterns of V. vulnificus and V. cholerae in raw oysters were evaluated, and consumption frequency and amounts for raw oyster were investigated from a Korean National Health and Nutrition Examination Survey. With the collected data, a risk assessment simulation was conducted to estimate the probability of foodborne illness caused by intake of raw oysters, using @RISK. Of 88 raw oysters, there were no V. vulnificus- or V. cholerae-positive samples. Thus, initial contamination levels of Vibrio species in raw oysters were estimated by the statistical methods developed by Vose and Sanaa, and the estimated value for the both Vibrio spp. was -3.6 Log CFU/g. In raw oyster, cell counts of V. vulnificus and V. cholerae remained unchanged. The incidence of raw oyster consumers was 0.35%, and the appropriate probabilistic distribution for the consumption amounts was the exponential distribution. A risk assessment simulation model was developed with the collected data, and the probability of the foodborne illness caused by the consumption of raw oyster was 9.08×10^-15 for V. vulnificus and 8.16×10^-13 for V. cholerae. Consumption frequency was the first factor, influencing the probability of foodborne illness.

• Journal of Food Hygiene and Safety
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• v.35 no.1
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• pp.51-59
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• 2020

This study evalutated the risk of foodborne illness from Vibrio spp. (Vibrio vulnificus and Vibrio cholerae) through sea squirt consumption. The prevalence of V. vulnificus and V. cholerae in sea squirt was evaluated, and the predictive models to describe the kinetic behavior of the Vibrio in sea squirt were developed. Distribution temperatures and times were collected, and they were fitted to probabilistic distributions to determine the appropriate distributions. The raw data from the Korea National Health and Nutrition Examination Survey 2016 were used to estimate the consumption rates and amount of sea squirt. In the hazard characterization, the Beta-Poisson model for V. vulnificus and V. cholerae infection was used. With the collected data, a simulation model was prepared and it was run with @RISK to estimate probabilities of foodborne illness by pathogenic Vibrio spp. through sea squirt consumption. Among 101 sea squirt samples, there were no V. vulnificus positive samples, but V. cholerae was detected in one sample. The developed predictive models described the fates of Vibrio spp. in sea squirt during distribution and storage, appropriately shown as 0.815-0.907 of R² and 0.28 of RMSE. The consumption rate of sea squirt was 0.26%, and the daily consumption amount was 68.84 g per person. The Beta-Poisson model [P=1-(1+Dose/β)^-α] was selected as a dose-response model. With these data, a simulation model was developed, and the risks of V. vulnificus and V. cholerae foodborne illness from sea squirt consumption were 2.66×10^-15, and 1.02×10^-12, respectively. These results suggest that the risk of pathogenic Vibrio spp. in sea squirt could be considered low in Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.72-85
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• 2019

The goal of this study is to predict sexual violence crimes, which is an routine risk. The study used to the Weight of Evidence on sexual violence crimes that occurred in partly Cheongju-si for five years from 2011 to 2015. The results are as follows. First, application and analysis of the Weight of Evidence that considers the weight of evidence characteristics showed 8 out of total 26 evidences that are used for a sexual violence crimes risk prediction. The evidences were residential area, date of use permission for building, individual housing price, floor area ratio, number of basement floor, lot area, security light and recreational facility; which satisfied credibility in the process of calculating weight. Second, The weight calculated 8 evidences were combined to create the prediction map in the end. The map showed that 16.5% of sexual violence crimes probability occurs in 0.3㎢, which is 3.3% of the map. The area of probability of 34.5% is 1.8㎢, which is 19.0% of the map and the area of probability of 75.5% is 2.0㎢, which is 20.7% of the map. This study derived the probability of occurrence of sexual violence crime risk and environmental factors or conditions that could reduce it. Such results could be used as basic data for devising preemptive measures to minimize sexual violence, such as police activities to prevent crimes.

• Journal of Radiation Protection and Research
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• v.38 no.2
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• pp.60-67
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• 2013

A diffusion coefficient is an important parameter in the prediction of atmospheric dispersion using a Gaussian plume model, and its modelling approach varies. In this study, dispersion coefficients recommended by the U. S. Nuclear Regulatory Commission's (U. S. NRC's) regulatory guide and the Canadian Nuclear Safety Commission's (CNSC's) regulatory guide, and used in probabilistic accident consequence analysis codes MACCS and MACCS2 have been investigated. Based on the atmospheric dispersion model for a hypothetical accidental release recommended by the U. S. NRC, its influence to atmospheric dispersion factor was discussed. It was found that diffusion coefficients are basically predicted from a Pasquill- Gifford curve, but various curve fitting equations are recommended or used. A lateral dispersion coefficient is corrected with consideration for the additional spread due to plume meandering in all models, however its modelling approach showed a distinctive difference. Moreover, a vertical dispersion coefficient is corrected with consideration for the additional plume spread due to surface roughness in all models, except for the U. S. NRC's recommendation. For a specified surface roughness, the atmospheric dispersion factors showed differences up to approximately 4 times depending on the modelling approach of a dispersion coefficient. For the same model, the atmospheric dispersion factors showed differences by 2 to 3 times depending on surface roughness.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.1 no.1
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• pp.21-32
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• 1981

Recent trends in design standards development in some European countries and U.S.A. have encouraged the use of probabilistic limit sate design concepts. Reliability based design criteria such as LSD, LRFD, PBLSD, adopted in those advanced countries have the potentials that they afford for symplifying the design process and placing it on a consistent reliability bases for various construction materials. A reliability based design criteria for RC flexural members are proposed in this study. Lind-Hasofer's invariant second-moment reliability theory is used in the derivation of an algorithmic reliability analysis method as well as an iterative determination of load and resistance factors. In addition, Cornell's Mean First-Order Second Moment Method is employed as a practical tool for the approximate reliability analysis and the derivation of design criteria. Uncertainty measures for flexural resistance and load effects are based on the Ellingwood's approach for the evaluation of uncertainties of loads and resistances. The implied relative safety levels of RC flexural members designed by the strength design provisions of the current standard code were evaluated using the second moment reliability analysis method proposed in this study. And then, resistance and load factors corresponding to the target reliability index(${\beta}=4$) which is considered to be appropriate level of reliability considering our practices are calculated by using the proposed methods. These reliability based factors were compared to those specified by our current ultimate strength design provisions. It was found that the reliability levels of flexural members designed by current code are not appropriate, and the code specified resistance and load factors were considerably different from the reliability based resistance and load factors proposed in this study.

• Asia Marketing Journal
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• v.14 no.2
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• pp.157-176
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• 2012

Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.