• Journal of the Ergonomics Society of Korea
• /
• v.29 no.5
• /
• pp.811-818
• /
• 2010

In this study, a self-administered checklist for evaluation of the musculoskeletal disorders risk factors in construction industry was developed, and its reliability and validity were studied. 10 items of the checklist were determined based on the literature review, and total 2,793 construction workers participated in the analysis of the checklist's applicability. The results from the reliability analysis showed high Cohen's kappa coefficient (0.50~0.77), and high validity was also obtained in terms of relative risk (RR 1.73~9.14). Positive predictability was relatively low (13.0~32.5%), while negative predictability was high (80.1~96.8%). It can be concluded that the checklist would be suitable as a quick filtering tool of the ergonomic risk factors.

• Journal of Korean Society for Quality Management
• /
• v.44 no.2
• /
• pp.373-388
• /
• 2016

Purpose: This paper suggests a hierarchical time delay model to evaluate failure risks in FMEA(failure modes and effects analysis). In place of the conventional RPN(risk priority number), a more reasonable and objective risk metric is proposed under hierarchical failure cause structure considering time delay between a failure mode and its causes. Methods: The structure of failure modes and their corresponding causes are analyzed together with the time gaps between occurrences of causes and failures. Assuming the severity of a failure depends on the length of the delayed time for corrective action, a severity model is developed. Using the expected severity, a risk priority metric is defined. Results: For linear and quadratic types of severity, nice forms of expected severity are derived and a meaningful metric for risk evaluation is defined. Conclusion: The suggested REM(risk evaluation metric) provides a more reasonable and objective risk measure than the conventional RPN for FMEA.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.635-637
• /
• 2021

Cybersecurity assessment is the process of assessing the risk level of a system through threat and vulnerability analysis to take appropriate security measures. Accurate security evaluation models are needed to prepare for the recent increase in cyberattacks and the ever-developing intelligent security threats. Therefore, we present a risk assessment model through a matrix-based security assessment model analysis that scores by assigning weights across security equipment, intervals, and vulnerabilities. The factors necessary for cybersecurity evaluation can be simplified and evaluated according to the corporate environment. It is expected that the evaluation will be more appropriate for the enterprise environment through evaluation by security equipment, which will help the cyber security evaluation research in the future.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.38 no.5
• /
• pp.690-704
• /
• 2014

This study examined the risk perception in internet shopping by Chinese and analyzed the effects of risk perception on internet word-of-mouth acceptance and transmission. This analysis was conducted with data collected from 373 Chinese individuals in their 20s. Data were analyzed with factorial analysis, cluster analysis, ANOVA, multiple regression analysis, Chi-square test, and Cronbach's ${\alpha}$ using SPSS 18.0. The results were: 1) The factor analysis of risk perception extracted four factors: fashion/social psychological risk, product risk, transaction risk, and economic risk. The cluster analysis classified them into: Group with low-risk, Group with high-risk, Group with economic risk, and Group with medium-risk. 2) Group with high-risk and Group with economic risk had a higher word-of-mouth acceptance than other groups. The Group with a high-risk had more word-of-mouth transmission than other groups. 3) It was found that when word-of-mouth was accepted, the factual information about fashion products (size and material) was most referred to, and that the overall evaluation of satisfaction and dissatisfaction was most conveyed when word-of-mouth was conveyed. 4) Internet word-of-mouth acceptance was affected by product risk, economic risk, and transaction risk. Internet word-of-mouth transmission was affected by economic risk, and fashion/social psychological risk, product risk, and transaction risk.

• Journal of the Korea Safety Management & Science
• /
• v.9 no.1
• /
• pp.23-35
• /
• 2007

Present time there are many risk analysis method in the world. A hazard is an exposure that has the potential to induce and adverse event. Risk is the probability of an adverse event given exposure to hazard. The evaluation of scientific information on the hazardous properties of environmental agents and the extent of exposure to these agents. But operation risk analysis method is not enough for manufacturing industry even if it is existence, it will be separated to improve Safety. In this paper, I will develop the AHP Weighted operation risk analysis method to improve Safety.

• Nuclear Engineering and Technology
• /
• v.49 no.2
• /
• pp.395-403
• /
• 2017

An efficient evaluation method for the probability of a tornado missile strike without using the Monte Carlo method is proposed in this paper. A major part of the proposed probability evaluation is based on numerical results computed using an in-house code, Tornado-borne missile analysis code, which enables us to evaluate the liftoff and flight behaviors of unconstrained objects on the ground driven by a tornado. Using the Tornado-borne missile analysis code, we can obtain a stochastic correlation between local wind speed and flight distance of each object, and this stochastic correlation is used to evaluate the conditional strike probability, $Q_V(r)$, of a missile located at position r, where the local wind speed is V. In contrast, the annual exceedance probability of local wind speed, which can be computed using a tornado hazard analysis code, is used to derive the probability density function, p(V). Then, we finally obtain the annual probability of tornado missile strike on a structure with the convolutional integration of product of $Q_V(r)$ and p(V) over V. The evaluation method is applied to a simple problem to qualitatively confirm the validity, and to quantitatively verify the results for two extreme cases in which an object is located just in the vicinity of or far away from the structure.

• Journal of Food Hygiene and Safety
• /
• v.27 no.4
• /
• pp.349-355
• /
• 2012

In this study, we configured a system which ranks hazardous chemicals to determine their management priorities based on experts' opinions and the existing CRS (chemical ranking and scoring). Aggregate exposure of food, health functional food, oriental/herbal medicine and cosmetics have been taken into account to determine management priority. In this study, 25 hazardous chemicals were selected, such as cadmium, lead, mercury, and arsenic, etc. These 25 materials were ranked according to their 1) risk (exposure or hazard) indexes, 2) exposure source-based weight, and 3) public interests, which were also formed based on the existing priority ranking system. Cadmium was scored the highest (178.5) and bisphenol A the lowest (56.8). Ten materials -- cadmium, lead, mercury, arsenic, tar, acrylamide, benzopyrene, aluminium, benzene, and PAHs -- scored higher than 100. Eight materials -- aflatoxin, manganese, phthalate, chromium, nitrate/nitrite, ethylcarbamate, formaldehyde, and copper -- recorded scores in the range from 70 to 100. Also evaluated as potential risks were 7 materials; sulfur dioxide, ochratoxin, dioxins, PCBs, fumonisin, methyl mercury, and bisphenol A, and these materials were scored above 50. Then we compared risk index and correlation coefficient of total scores to confirm the validity of the total scores; we analyzed correlation coefficient of parameter and indicator. We discovered that the total score and weight, which has incorporated public interests, were high and statistically significant. In conclusion, the result of this study contributes to strengthening risk assessment and risk management of hazardous chemicals.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.24 no.3
• /
• pp.302-310
• /
• 2018

Despite the accident rate for fishing vessels accounts for 70% of all maritime accidents, few studies on such accidents have been done and most of the them mainly focus on causes and mitigation policies to reduce that accident rate. Thus, this risk analysis on sea accidents is the first to be performed for the successful and efficient implementation of accident reducing measures. In risk analysis, risk is calculated based on the combination of frequency and the consequence of an accident, and is usually expressed as a single number. However, there exists uncertainty in the risk calculation process if one uses a limited number of data for analysis. Therefore, in the study we propose a probabilistic simulation method to forecast risk not as a single number, but in a range of possible risk values. For the capability of the proposed method, using the criteria with the ALARP region, we show the possible risk values spanning across the different risk regions, whereas the single risk value calculated from the existing method lies in one of the risk regions. Therefore, a decision maker could employ appropriate risk mitigation options to handle the risks lying in different regions. For this study, we used fishing vessel accident data from 1988 to 2016.

• Geomechanics and Engineering
• /
• v.18 no.5
• /
• pp.515-525
• /
• 2019

A karst collapse, as a natural hazard, is totally different to a normal collapse. In recent years, karst collapses have caused substantial economic losses and even threatened human safety. A risk assessment model for karst collapse was developed based on the fuzzy analytic hierarchy process (FAHP) and grey relational analysis (GRA), which is a simple and effective mathematical algorithm. An evaluation index played an important role in the process of completing the risk assessment model. In this study, the proposed model was applied to Jiaobai village in southwest China. First, the main controlling factors were summarized as an evaluation index of the model based on an investigation and statistical analysis of the natural formation law of karst collapse. Second, the FAHP was used to determine the relative weights and GRA was used to calculate the grey relational coefficient among the indices. Finally, the relational sequence of evaluation objects was established by calculating the grey weighted relational degree. According to the maximum relational rule, the greater the relational degree the better the relational degree with the hierarchy set. The results showed that the model accurately simulated the field condition. It is also demonstrated the contribution of various control factors to the process of karst collapse and the degree of collapse in the study area.

• Journal of Environmental Health Sciences
• /
• v.48 no.3
• /
• pp.159-166
• /
• 2022

Background: A quantitative structure-activity relationship (QSAR) model was adopted in the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH, EU) regulations as well as the Act on Registration, Evaluation, etc. of Chemicals (AREC, Republic of Korea). It has been previously used in the registration of chemicals. Objectives: In this study, we investigated the correlation between the predicted data provided by three prediction programs using a QSAR model and actual experimental results (acute fish, daphnia magna toxicity). Through this approach, we aimed to effectively conjecture on the performance and determine the most applicable programs when designating toxic substances through the AREC. Methods: Chemicals that had been registered and evaluated in the Toxic Chemicals Control Act (TCCA, Republic of Korea) were selected for this study. Two prediction programs developed and operated by the U.S. EPA - the Ecological Structure-Activity Relationship (ECOSAR) and Toxicity Estimation Software Tool (T.E.S.T.) models - were utilized along with the TOPKAT (Toxicity Prediction by Komputer Assisted Technology) commercial program. The applicability of these three programs was evaluated according to three parameters: accuracy, sensitivity, and specificity. Results: The prediction analysis on fish and daphnia magna in the three programs showed that the TOPKAT program had better sensitivity than the others. Conclusions: Although the predictive performance of the TOPKAT program when using a single predictive program was found to perform well in toxic substance designation, using a single program involves many restrictions. It is necessary to validate the reliability of predictions by utilizing multiple methods when applying the prediction program to the regulation of chemicals.