Objectives: In response to increased interest in the safety of children's products, a risk management system is being prepared through exposure assessment of hazardous chemicals. To estimate exposure levels, risk assessors are using deterministic and probabilistic approaches to statistical methodology and a commercialized Monte Carlo simulation based on tools (MCTool) to efficiently support calculation of the probability density functions. This study was conducted to analyze and discuss the usage patterns and problems associated with the results of these two approaches and MCTools used in the case of probabilistic approaches by reviewing research reports related to exposure assessment for children's products. Methods: We collected six research reports on exposure and risk assessment of children's products and summarized the deterministic results and corresponding underlying distributions for exposure dose and concentration results estimated through deterministic and probabilistic approaches. We focused on mechanisms and differences in the MCTools used for decision making with probabilistic distributions to validate the simulation adequacy in detail. Results: The estimation results of exposure dose and concentration from the deterministic approaches were 0.19-3.98 times higher than the results from the probabilistic approach. For the probabilistic approach, the use of lognormal, Student's T, and Weibull distributions had the highest frequency as underlying distributions of the input parameters. However, we could not examine the reasons for the selection of each distribution because of the absence of test-statistics. In addition, there were some cases estimating the discrete probability distribution model as the underlying distribution for continuous variables, such as weight. To find the cause of abnormal simulations, we applied two MCTools used for all reports and described the improper usage routes of MCTools. Conclusions: For transparent and realistic exposure assessment, it is necessary to 1) establish standardized guidelines for the proper use of the two statistical approaches, including notes by MCTool and 2) consider the development of a new software tool with proper configurations and features specialized for risk assessment. Such guidelines and software will make exposure assessment more user-friendly, consistent, and rapid in the future.
Proceedings of the Korean Institute Of Construction Engineering and Management
/
2004.11a
/
pp.504-509
/
2004
Safety assessment of construction projects may be affected by various factors such as types and scale of projects, construction methods, procedure, climactic, and site conditions etc. Presently, in planning and design phases, designers are still often uncertain of their responsibilities, l3i]I information and training of safety. Therefore, designers are still failing to exploit the potential that have to eliminate and reduce risks on site. In this study, the concepts of safety impact assessment is introduced in order to derive the performing design for safety in design phase. For this purpose, a framework for safety impact assessment model using risk-based approach for construction projects is suggested. The suggested model includes of information survey and scenarios, classification of safety impact factors occurred by design and construction, and quantitative estimation of magnitude and frequency. Moreover, the checklist which is enable to identify relationship between safety impact factors and design factors is developed and the methodology of safety impact assessment model using risk-based approach is also proposed.
Korean Journal of Construction Engineering and Management
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v.12
no.6
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pp.79-92
/
2011
Quantity take-off is one of the critical tasks that determine the cost of a construction project, and its result should be accurate and reliable. BIM-based quantity take-off is a very attractive process for practitioners since the quantity take-off can be done automatically in a fast and accurate way. However, the result of BIM-based quantity take-off can be varied depending on how BIM was modeled. As a project progresses, more detailed design information is getting available, and it can be expected that the degree of completeness and accuracy for the BIMbased quantity take-off is going to be improved as well. However, when estimation is performed at each stage of a project life-cycle, there is no way to measure or forecast how accurate of the quantity take-off result from the BIM data given at the current stage. Therefore, this research derived factors that affect the BIM-based quantity takeoff and developed a methodology and framework to measure and forecast the completeness of BIM-based quantity take-off. The measurement framework and index that are proposed by this research was verified and validated for their consistency and feasibility through six pilot projects.
Marine Spatial Planning is an emerging strategy that promoting sustainable development at coastal and marine areas based on the concept of ecosystem services. Regarding its methodology, usage rate of resources and its impact should be considered in the process of spatial planning. Particularly, considering the rapid increase of coastal tourism, visitation pattern is required to be identified across coastal areas. However, actions to quantify visitation pattern have been limited due to its required high cost and labor for conducting extensive field-study. In this regard, this study aimed to pose the usage of social big data in Marine Spatial Planning to identify spatial visitation density and critical management zone throughout coastal areas. We suggested the usage of GPS information from Flickr and Twitter, and evaluated the critical management zone by applying spatial statistics and density analysis. This study's results clearly showed the coastal areas having relatively high visitors in the southern sea of South Korea. Applied Flickr and Twitter information showed high correlation with field data, when proxy excluding over-estimation was applied and appropriate grid-scale was identified in assessment approach. Overall, this study offers insights to use social big data in Marine Spatial Planning for reflecting size and usage rate of coastal tourism, which can be used to designate conservation area and critical zones forintensive management to promote constant supply of cultural services.
Some previous studies adopted a method statistically based on the observed traffic volumes and travel times to estimate the parameters. Others tried to find an optimal set of parameters to minimize the gap between the observed and estimated traffic volumes using, for instance, a combined optimization model with a traffic assignment model. The latter is frequently used in a large-scale network that has a capability to find a set of optimal parameter values, but its appropriateness has never been demonstrated. Thus, we developed a methodology to estimate a set of parameter values of BPR(Bureau of Public Road) function using Harmony Search (HS) method. HS was developed in early 2000, and is a global search method proven to be superior to other global search methods (e.g. Genetic Algorithm or Tabu search). However, it has rarely been adopted in transportation research arena yet. The HS based transportation network calibration algorithm developed in this study is tested using a grid network, and its outcomes are compared to those from incremental method (Incre) and Golden Section (GS) method. It is found that the HS algorithm outperforms Incre and GS for copying the given observed link traffic counts, and it is also pointed out that the popular optimal network calibration techniques based on an objective function of traffic volume replication are lacking the capability to find appropriate free flow travel speed and ${\alpha}$ value.
A group sequential design can end a clinical trial early if a confirmed efficacy or a futility of study medication is found during clinical trials. Adaptation can adjust the design of clinical trials based on accumulated data. The key to this methodology is considered to control the overall type 1 error rate while maintaining the integrity of clinical trials. The estimation would be more complex and the sample size calculation will be more difficult if the clinical trials have repeated measurement data. Lee et al. (2002) suggested a repeated observation case by using the independent increments properties of the interim test statistics and investigated the properties of the proposed confidence interval based on the stage-wise ordering. This study extend Lee et al. (2002) to adaptive group sequential design. We suggest test statistics for the adaptation as redesigning the second stage of clinical trials and induce the stage-wise confidence interval of parameter of interests. The simulation will help to confirm the suggested method.
The purpose of this paper is to estimate the environmental performance of 29 Chinese provinces by adopting the advanced measurements, integrated pollution intensity index, IPI, which can be computed using Data Envelopment Analysis(DEA) techniques. This index has the advantage of accounting for multiple resources used, good outputs produced and pollutants emitted simultaneously. The result obtained using the methodology shows the obvious evidence that provinces located around eastern area of China take relatively low levels and these phenomenons have been clearly observed throughout the sample period 1998~2007. The estimated index can be interpreted that the environmental burden in China has been steadily decreased as economic growth. This paper also tries to figure out the relationship among IPI, income levels, economic structures, the level of environmental regulations and FDI inflow. The estimated relationship between IPI and income per capita predicts improving environmental performance with increasing income levels. This explains the improvement in IPI which is simultaneously observed with income increases. According to the 'pollution haven hypothesis', many researches have been concerned the possibility that a large amount of foreign capital has been invested in China to avoid the strict environmental standards in advanced countries. However, the estimated coefficients in all model specifications take negative sign with IPI and highly statistical significant. This is a indication that there are positive impacts of foreign investments on IPI by adopting clean and high technologies from advanced countries.
Appropriate speed limits at a reasonable level in urban roads are highly important factors for efficient and safe movement. Thus, it is greatly necessary to develop the objective models or methodology based on engineering study considering factors such as traffic accident rates, roadside development levels, and roadway geometry characteristics etc. The purpose of this study is to develop the estimate model of appropriate speed limits at each road sections in urban roads using traffic information big data and field specific data and to review the effects of accident decrease. In this study, the estimate method of appropriate speed limits in directional two or more lanes of urban roads is reflecting features of actual variables in a form of adjustment factor on the basis of the maximum statutory speed limits. As a result of investigating and testing influential variables, the main variables to affect the operating speed are the function of road, the existence of median, the width of lane, the number of traffic entrance/exit path and the number of traffic signal or nonsignal at intersection and crosswalk. As a result of testing this model, when the differences are bigger between the real operating speed and the recommended speed limits using model developed in this study, the accident rate generally turns out to be higher. In case of using the model proposed in this study, it means accident rate can be lower. When the result of this study is applied, the speed limits of directional two or more lane roads in Seoul appears about 11km/h lower than the current speed limits. The decrease of average operating speed caused by the decrease of speed limits is 2.8km/h, and the decrease effect of whole accidents according to the decrease of speed is 18% at research road. In case that accident severity is considered, the accident decrease effects are expected to 17~24% in fatalities, 11~17% in seriously injured road user, 6~9% in slightly injured road user, 5~6% in property damage only accidents.
Although the methodology and models to assess the economic value of technology assets such as patents are being presented in various ways, there does not exist a structured assessment model which enables to objectively assess a database property's value, and thus there is a need to enhance the application feasibility of practical purposes such as licensing of DB assets, commercialization transfer, security, etc., through the establishment of the valuation model and the life-cycle decision logic. In this study, during the valuation process of DB assets, the size of customer demand group expected and the amount of demand, the size and importance of data sets, the approximate degree of database' contribution to the sales performance of a company, the life-cycle of database assets, etc. will be analyzed whether they are appropriate as input variables or not. As for most of DB assets, due to irregular updates there are hardly cases their life-cycle expires, and thus software package's persisting period, ie. 5 years, is often considered the standard. We herein propose the life-cycle estimation logic and valuation models of DB assets based on the concept of half life for DB usage frequency under the condition that DB assets' value decays and there occurs no data update over time.
Genetic parameters for birth weights (BWT), calving ease scores observed from calves born by heifers (CEH), and calving ease scores observed from calves born by cows (CEC) were estimated using Bayesian methodology with Gibbs sampling in different threshold animal models. Data consisted of 77,458 records for calving ease scores and birth weights in Gelbvieh cattle. Gibbs samplers were used to obtain the parameters of interest for the categorical traits in two univariate threshold animal models, a bivariate threshold animal model, and a three-trait linear-threshold animal model. Samples of heritabilities and genetic correlations were calculated from the posterior means of dispersion parameters. In a univariate threshold animal model with CEH (model 1), the posterior means of heritabilities for calving ease was 0.35 for direct genetic effects and 0.18 for maternal genetic effects. In the other univariate threshold model with CEC (model 2), the posterior means of heritabilities of CEC was 0.28 for direct genetic effects and 0.18 for maternal genetic effects. In a bivariate threshold model with CEH and CEC (model 3), heritability estimates were similar to those in unvariate threshold models. In this model, genetic correlation between heifer calving ease and cow calving ease was 0.89 and 0.87 for direct genetic effect and maternal genetic effects, respectively. In a three-trait animal model, which contained two categorical traits (CEH and CEC) and one continuous trait (BWT) (model 4), heritability estimates of CEH and CEC for direct (maternal) genetic effects were 0.40 (0.23) and 0.23 (0.13), respectively. In this model, genetic correlation estimates between CEH and CEC were 0.89 and 0.66 for direct genetic effects and maternal effects, respectively. These estimates were greater than estimates between BWT and CEH (0.82 and 0.34) or BWT and CEC (0.85 and 0.26). This result indicates that CEH and CEC should be high correlated rather than estimates between calving ease and birth weight. Genetic correlation estimates between direct genetic effects and maternal effects were -0.29, -0.31 and 0.15 for BWT, CEH and CEC, respectively. Correlation for permanent environmental effects between BWT and CEC was -0.83 in model 4. This study can provide genetic evaluation for calving ease with other continuous traits jointly with assuming that calving ease from first calving was a same trait to calving ease from later parities calving. Further researches for reliability of dispersion parameters would be needed even if the more correlated traits would be concerned in the model, the higher reliability could be obtained, especially on threshold model with property that categorical traits have little information.
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