• International Journal of Quality Innovation
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• v.7 no.2
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• pp.97-124
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• 2006

The purpose of this research is to create an expert risk-based piping system inspection model. The proposed system includes a risk-based piping inspection system and a piping inspection guideline system. The research procedure consists of three parts: the risk-based inspection model, the risk-based piping inspection model, and the piping inspection guideline system model. In this research procedure, a field plant visit is conducted to collect the related domestic information (Taiwan) and foreign standards and regulations for creating a strategic risk-based piping inspection and analysis system in accordance with the piping damage characteristics in the petrochemical industry. In accordance with various piping damage models and damage positions, petrochemical plants provide the optimal piping inspection planning tool for efficient piping risk prediction for enhancing plant operation safety.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.103-110
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• 2022

In the era of the 4th Industrial Revolution, smart technology being considered to improve productivity breakthroughs is in the spotlight as a means to replace traditional construction technology in the construction industry. However, various problems are occurring in construction sites using smart technology and causing negative impacts on construction projects. Therefore, the objective of this study is to identify risk factors that occur when smart technologies are used in construction projects. To achieve this purpose, this study investigated the difficulties at construction projects using smart technology, and risk factors were derived based on site surveys and literature. The risk factors were measured by experts, and then a total of 19 risk factors was derived by exploratory factor analysis. As a result, risks were classified as 5 factors, the institutional factor is the most difficult response, and the government needs anticipative system improvement and a long-term plan. The research findings provide practical implications for construction experts trying to apply smart technology in construction sites and construction policy-makers to revitalize smart technology.

• Corrosion Science and Technology
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• v.11 no.5
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• pp.179-183
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• 2012

As one of promising solutions to overcome high oil price and energy crisis, the construction market of high value-added LNG plants is spotlighted world widely. The purpose of this study is to introduce LNG-RBI system to develop risk assessment technology with RAM(Reliability, Availability, Maintainability) modules against overseas monopolization. After analyzing relevant specific features and their technical levels, risk assessment program, non-destructive reliability evaluation strategy and safety criteria unification class are derived as core technologies. These IT-based convergence technologies can be used for enhancement of LNG plant efficiency, in which the modular parts are related to a system with artificial optimized algorithms as well as diverse databases of facility inspection and diagnosis fields.

• International Journal of Contents
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• v.13 no.1
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• pp.22-30
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• 2017

The diffusion of advanced mobile technology has introduced new types of personal information or 'location data'. These new data mean new opportunities for businesses, such as location-based services (LBS), but have resulted in new consumer anxieties regarding disclosure of personal information. This study examines the effects of the consumers' perceived control over "time-andplace" information in location-aware services on their perceived privacy risk. A total of 270 respondents participated in this study. Conditions of perceived privacy control were operationalized over time-and-place information, in a $2{\times}2$ factorial design. Results indicate that the perceived control over time-and-place personal information is a significant predictor of perceived risk, and control assurances over time-and-place information enhances the perception of control, thus alleviating the perceived risk. In addition, the effect is much more significant when time and place were combined.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10539-10542
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• 2015

A method to predict the risk of lung cancer is proposed, based on two feature selection algorithms: Fisher and ReliefF, and BP Neural Networks. An appropriate quantity of risk factors was chosen for lung cancer risk prediction. The process featured two steps, firstly choosing the risk factors by combining two feature selection algorithms, then providing the predictive value by neural network. Based on the method framework, an algorithm LCRP (lung cancer risk prediction) is presented, to reduce the amount of risk factors collected in practical applications. The proposed method is suitable for health monitoring and self-testing. Experiments showed it can actually provide satisfactory accuracy under low dimensions of risk factors.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.394-398
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• 2016

In this paper, a fire detection system based on quantitative risk estimation is presented. Multiple sensors are used to build a comprehensive indicator that represents the risk of fire quantitatively. The proposed fire risk estimation method consists of two stages which determines the occurrence of fire and estimates the toxicity of the surveillance area. In the first stage, fire is reliably detected under diverse fire scenarios. The risk of fire is estimated in the second stage. Applying Purser's Fractional Effective Dose (FED) model which quantitates harmfulness of toxic gases, the risk of the surveillance area and evacuation time are calculated. A fire experiment conducted using four different types of combustion materials for the verification of the system resulted in a maximum error rate of 12.5%. By using FED calculation and risk estimation methods, the proposed system can detect various signs of fire faster than conventional systems.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.103-110
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• 2021

In the development of a Risk Monitor probabilistic safety assessment (PSA) model from the basic PSA model of a nuclear power plant, the modeling of common-cause failure (CCF) is very important. At present, some approximate modeling methods are widely used, but there lacks criterion of modeling accuracy and error analysis. In this paper, aiming at ensuring the accuracy of risk assessment and minimizing the Risk Monitor PSA models size, we present three basic issues of CCF model resulted from the changes of a nuclear power plant configuration, put forward corresponding modeling methods, and derive accuracy criteria of CCF modeling based on minimum cut sets and risk indicators according to the requirements of risk monitoring. Finally, a nuclear power plant Risk Monitor PSA model is taken as an example to demonstrate the effectiveness of the proposed modeling method and accuracy criteria, and the application scope of the idea of this paper is also discussed.

• Korean Journal of Veterinary Service
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• v.46 no.4
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• pp.255-262
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• 2023

Caseous lymphadenitis (CLA) is an endemic but not well-studied disease of Korean native goats (KNG) in Korea. Corynebacterium pseudotuberculosis is the causative agent of the contagious and chronic CLA found in goats. This study aimed to validate the potential risk factors associated with CLA and assess its seasonal prevalence to mitigate this disease in KNG. Data were collected through a questionnaire from four high- and four low-prevalence farms randomly selected based on a prior investigation. The monthly assessments of CLA were conducted in a goat abattoir located in Jeonnam Province, Korea, to evaluate its seasonal prevalence. The associated risk factors for CLA in KNG herds imply that herd size, scratching against pillars, pipes, or walls in the herd, and disinfection of goat herds are potential risk factors for CLA (P<0.05). The type of floor and entry of new goats into the herd, which are potential risk factors, affected CLA prevalence in the KNG herd (P<0.2). The prevalence of CLA in KNG was significantly higher in spring (29.34%) than in autumn (14.61%), summer (15.31%), and winter (19.48%) (P<0.05). Based on the risk factor assessment, attention should be to establishing accurate preventive measures by avoiding these identified potential risk factors.

• Journal of the Korean Society of Safety
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• v.37 no.1
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• pp.78-87
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• 2022

In the risk assessment of urban railway systems, a hazard log is created by identifying hazards from accident and failure data. Then, based on a risk matrix, evaluators analyze the frequency and severity of the occurrence of the hazards, conduct the risk assessment, and then establish safety measures for the risk factors prior to risk control. However, because subjective judgments based on the evaluators' experiences affect the risk assessment results, a more objective and automated risk assessment system must be established. In this study, we propose a risk assessment model in which an adaptive neuro-fuzzy inference system (ANFIS), which is combined in artificial neural networks (ANN) and fuzzy inference system (FIS), is applied to the risk assessment of urban railway systems. The newly proposed model is more objective and automated, alleviating the limitations of risk assessments that use a risk matrix. In addition, the reliability of the model was verified by comparing the risk assessment results and risk control priorities between the newly proposed ANFIS-based risk assessment model and the risk assessment using a risk matrix. Results of the comparison indicate that a high level of accuracy was demonstrated in the risk assessment results of the proposed model, and uncertainty and subjectivity were mitigated in the risk control priority.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.340-350
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• 2021

This paper proposes a decision support model for USVs to improve the accuracy of collision avoidance decision-making. It is formed by Navigation Safety Domain (NSD) and domain-based Collision Risk Index (CRI), capable of determining the collision stage and risk between multiple ships. The NSD is composed of a warning domain and a forbidden domain, which is constructed under the constraints of COLREGs (International Regulations for Preventing Collisions at Sea). The proposed domain based CRI takes the radius of NSD in various encounter situations as threshold parameters. It is found that the value of collision risk in any directions can be calculated, including actual value and risk threshold. A catamaran USV and 6 given vessels are taken as study objects to validate the proposed model. It is found that the judgment of collision stage is accurate and the azimuth range of risk exists can be detected, hence the ships can take direct and effective collision avoidance measures. According to the relation between the actual value of CRI and risk threshold, the decision support rules are summarized, and the specific terms of COLREGs to be followed in each encounter situation are given.