• Journal of the Korean Society of School Health
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• v.29 no.3
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• pp.256-266
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• 2016

Purpose: This study was to compare and to examine the factors related to risk behaviors of adolescents living in small and medium-sized cities and in rural areas. Methods: The subjects were 545 adolescents (295 from small and medium-sized cities and 250 from rural areas). The data was analyzed by descriptive statistics, Pearson corelation coefficients, and multiple regression with IBM SPSS 19.0 program. Results: The factors influencing the risk behaviors of adolescents in small- medium cities were school, peer risk factors and community risk factors, self- control among protective factors, positive communication with parents, positive peer associations, these variables explained 42.0%. The most important variable explaining the risk behaviors of adolescents in small- medium cities was positive communication with parents, followed by community risk factors, peer risk factors, positive peer relationships, school and self-control. The factors affecting the risk behaviors of rural adolescents were school, personal risk factor, peer risk factor, self- control factor, which explained 38.5% of the risk behaviors of adolescents in rural areas. Among them, the most important variable explaining risk behaviors was personal risk factors, followed by peer risk factors, school, and self-control. Conclusion: These finding suggest a need to develop a strategy to improve positive communication with parents for adolescents living in small- medium cities and a strategy to reduce personal risk factors and peer risk factors for rural adolescents.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.57-75
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• 2024

This study aimed to investigate the current state and educational needs of risk education related to science and technology as perceived by secondary science teachers. A survey was conducted with a total of 366 secondary science teachers. The results are as follows. First, There were more teachers who had not provided education on risks arising from science and technology in terms of risk perception, risk assessment, and risk management than those who had not. Global warming was the most common risk taught by teachers, followed by earthquakes, artificial intelligence, and traffic accidents. Second, teachers recognized that they lacked understanding that the achievement standards of the 2022 revised science curriculum include risks that may occur due to science and technology, but they thought they were prepared to teach. Third, teachers recognized that their understanding of risk perception was higher than that of risk management and risk assessment. Fourth, the experience of teachers in training on risk was very limited, with fewer having training in risk assessment and risk management compared to risk perception. The most common training experienced was in laboratory safety. Fifth, teachers recognized that their capabilities for the 10 goals of risk education were not high. Middle school teachers or teachers majoring in integrated science education evaluated their capabilities relatively highly. Sixth, many teachers thought it was important to address risks in school science education. They prioritized 'information use', 'decision-making skills', and 'influence of mass media', in that order, for importance and called for urgent education in 'action skills', 'information use', and 'influence of risk perception'. Seventh, as a result of deriving the priorities of education needs for each of the 10 goals of risk education, 'action skills', 'influence of risk perception', and 'evaluate risk assessment' were ranked 1st, 2nd, and 3rd, respectively.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.401-409
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• 2006

We consider a generalized partly-parametric additive risk model which generalizes the partly parametric additive risk model suggested by McKeague and Sasieni (1994). As an estimation method of this model, we propose to use the weighted least square estimation, suggested by Huffer and McKeague (1991), for Aalen's additive risk model by a piecewise constant risk. We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least squares method.

• Journal of the Korea Safety Management & Science
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• v.6 no.2
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• pp.91-101
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• 2004

Consumers require various quality characteristics including safety. The reduction of risk concerned on product safety becomes an urgent issue in leading companies. The strategy for customer satisfaction by choosing attractive quality characteristic is not enough for risk reduction in view of producer. This paper presents a method for choosing quality characteristics and risk characteristics by integrating QFD based on quality requirements and AHP based on safety requirements, also shows its application for complex equipment.

• Fire Science and Engineering
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• v.10 no.2
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• pp.20-27
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• 1996

This paper discussed the limit of existing safety controls where the use of land around hazardous industry. There is a gap between engineering evaluation of acceptable criteria for loss reduction and risk exposure to the areas of high risk outside plants from the aspects of risk perception. The paper performed how land use safety could be designed between the density of uses with the duration of risk exposure by type of land use. It concluded the needs of multi-dimensional presentation for an appropriate risk controls on existing and future land use safety.

• Korean Management Science Review
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• v.28 no.2
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• pp.1-16
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• 2011

In this study we suggested two optimization models to answer a question from an investor standpoint : how many convertible bonds should one convert, and how many keep? One model minimizes certain risk to the minimum required expected return, the other maximizes the expected return subject to the maximum acceptable risk. In comparison with Markowitz portfolio models, which use the variance of return, our models used Conditional Value-at-Risk(CVaR) for risk measurement. As a coherent measurement, CVaR overcomes the shortcomings of Value-at-Risk(VaR). But there are still difficulties in solving CVaR including optimization models. For this reason, we adopted Rockafellar and Uryasev's[18, 19] approach. Then we could approximate the models as linear programming problems with scenarios. We also suggested to extend the models with credit risk, and applied examples of our models to Hynix 207CB, a convertible bond issued by the global semiconductor company Hynix.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.456-463
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• 2002

Nowadays. risk management in the enterprise is considered as the important activity. Risk management ran be defined as the activity which is the analysis of risk factors related to damages, the estimation of the magnitude of risk, and the determination of investment to protect damage in a company. Initially, risk management was originated in financial areas. But the concept of risk has been expanded in the enterprise. Most companies have extended their activities in various areas. In this tendency, most activities must be considered in supply chain So, risk management must be ronsidered as the concept in the viewpoint of supply chain. The framework of risk management in supply chain and the related mathematical model are represented in this paper. Risk management in supply chain ran provide a positive opportunity not only to protect various damages, but also to improve the relationship between partners.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.61-82
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• 2020

The security risk management used by some service providers is not appropriate for effective security enhancement. The reason is that the security risk management methods did not take into account the opinions of security experts, types of service, and security vulnerability-based risk assessment. Moreover, the security risk assessment method, which has a great influence on the risk treatment method in an information security risk assessment model, should be security risk assessment for fine-grained risk assessment, considering security vulnerability rather than security threat. Therefore, we proposed an improved information security risk management model and methods that consider vulnerability-based risk assessment and mitigation to enhance security controls considering limited security budget. Moreover, we can evaluate the security cost allocation strategies based on security vulnerability measurement that consider the security weight.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.73-78
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• 2024

COVID-19 pandemic outbreak increased the use of Internet of Medical Things (IoMT), but the existing IoMT solutions are not free from attacks. This paper proposes a secure and resilient framework for IoMT, it computes the risk using Risk Impact Parameters (RIP) and Risk is also calculated based upon the Threat Events in the Internet of Medical Things (IoMT). UICC (Universal Integrated Circuit Card) and TPM (Trusted Platform Module) are used to ensure security in IoMT. PILAR Risk Management Tool is used to perform qualitative and quantitative risk analysis. It is designed to support the risk management process along long periods, providing incremental analysis as the safeguards improve.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.6
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• pp.434-444
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• 2013

In order to evaluate drought risk at upland according to climate change scenario (RCP8.5), we have carried out the simulation using agricultural water balance estimation model, called AFKAE0.5, at 66 weather station sites in 2020, 2046, 2050, 2084, and 2090. Total Drought Risk Index between the first month (f) and last month (l) (TDRI(f/l)) and maximum continuous drought risk index (MCDRI(f/l)) were defined as the index for analyzing pattern and strength of drought simulated by the model. Based on distribution maps of MCDRI (1/12), drought strength was predicted to be most severe in 2084 for all regions. Some regions showed severe risk of drought meaning over 20 days of MCDRI (1/12) in the other years, while MCDRI (1/12) in other regions did not reach 5 days. Even though maximum value of TDRI (1/12) in 2090 was greater than in 2050, more severe drought risk in 2050 than in 2090 was predicted based on MCDRI (4/6). It implies that drought risk should be assessed for each crop with its own growing season.