• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.8
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• pp.495-497
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• 2005

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a neural network used for identification of the process dynamics of s signal input and signal output system and it was shown that this method offered superior capability over the conventional back propagation algorithm. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal estimate input signal about controller using neural networks.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.6
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• pp.165-173
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• 1999

HILS system consists of hardwares which are engine and dynamometer and softwares which is vehicle model without the engine. It is well-known that because of engines's nonlinearity it is difficult to describe an engine exactly and not to lose it reality coincidently. But HILS system is the high technology that can compensate this weakness by using a real engine instead of model. The various experiments regarding the ACC which are not normally available for real vehicle tests have been performed by the HILS system. From the results , the HILS system is expected to decrease the experimental accident rate and save costs and time. Compared with simulation, HILS experimental results show similarities and expected to increase road capacity.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.18-20
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• 2005

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a neural network used for identification of the process dynamics of s signal input and signal output system and it was shown that this method offered superior capability over the conventional back propagation algorithm. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal estimate input signal about controller using neural networks.

• Proceedings of the KSR Conference
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• 2003.10b
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• pp.417-422
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• 2003

Rockfall mitigation methods have been widely constructed along railway lines but aren't estimated with any economic analysis methods up to now. Therefore, this study applied a benefit-cost analysis to rockfall mitigation method to determine whether it is indeed an economically efficient construction. The Benefits were estimated based on data collected from disaster history, and included three types of benefits that are originated by reduction of train accident, train delay and rockfall removing cost. The costs included both construction cost and the maintenance cost of the selected method. This analysis could clarify the investment effect of rockfall mitigation method that would be built at rockfall prone slope.

• 한국가스학회:학술대회논문집
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• 2005.10a
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• pp.49-58
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• 2005

A Cost-Benefit Analysis which would help us to make optical decisions among safety investment alternatives, calculating and comparing costs and benefits for facilities in chemical plants. As well as offering the related information in the decision makings for safety improvement, it promotes on-site safety activities and the efficiency of safety investments The developed Cost-Benefit Analysis will eventually contribute to our efforts in economically justifying the safety investments in chemical plants.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.29
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• pp.47-61
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• 1994

Today, we can see the more serious industrial accidents than in the past according to the high growth rate of industrial society. Therefore, from the corporate as well as the human viewpoint it pays to have workers adequately trained and safety - oriented. The cost of accidents is high in terms of medical insurance costs lost time on the job, legal fees for court cases, workers' compensation, disability insurance, and unemployment compensation. The cost of preventing occupational accidents or illnesses is much less then the cost of treatment or workers' compensation. In this study, we investigate the situations of industrial accidents and safety control of 277 coporates in Busan, analyze the causes of accidents and propose the countermeasures to each of causes.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.19-24
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• 2014

This study, the exchange value of the car after the repair, which affects the valuation elements and repair characteristics factors were investigated. Based on this specific accident damaged condition of the car, repair range, repair methods, repair costs, market transactions, taking into account the vehicle's depreciation appraisal method is proposed.

• Health Policy and Management
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• v.28 no.3
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• pp.308-314
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• 2018

Injury is a serious problem that not only causes death but also significantly degrades the quality of life of the people and causes loss of socioeconomic opportunities and costs. Damage occurs as a result of an accident. Among them, natural disasters and artificial disasters take lives of many people in a short time and threaten their physical and mental health. The United States has responded to the disaster by establishing relevant laws and regulations and a response system with the recognition that health is recognised soon to be as national security in the wake of the 9/11 terrorist attacks and the Katrina disaster. It is necessary to build a knowledge infrastructure to train disaster response experts in public health area and to have health competence to cope with disasters.

• Nuclear Engineering and Technology
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• v.39 no.6
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• pp.703-716
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• 2007

As digital and computer technologies have grown, human-machine interfaces (HMIs) have evolved. In safety-critical systems, especially in nuclear power plants (NPPs), HMIs are important for reducing operational costs, the number of necessary operators, and the probability of accident occurrence. Efforts have been made to improve main control room (MCR) interface design and to develop automated or decision support systems to ensure convenient operation and maintenance. In this paper, an integrated decision support system to aid operator cognitive processes is proposed for advanced MCRs of future NPPs. This work suggests the design concept of a decision support system which accounts for an operator's cognitive processes. The proposed system supports not only a particular task, but also the entire operation process based on a human cognitive process model. In this paper, the operator's operation processes are analyzed according to a human cognitive process model and appropriate support systems that support each cognitive process activity are suggested.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.717-719
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• 2003

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult to the PID gains suitably lots of researches have been reported with respect to turning schemes of PID gains. A Neural Network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident.