• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.33-40
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• 1994

Most software reliability models and other methods attempt to estimate some measures based on its fault history. There are several phases of the software life cycle including testing phase. We can propose it's stopping rule to decide when to stop the testing and pass it on to the next phase by considering the detailed structure of software and calculating the failure rate when each fault was detected. Downs (1985) proposed a method which was developed for estimating the failure rate applicable only to two-level profiles. In this paper, I extended to profiles involving more levels.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.44-51
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• 2002

The construction road and addition work are increasing now. Therefore, slope stability is important in construction slope on the fault and fractured zone. Rock bolt method, soil nailing method and anchor method are applied to reinforcement method of slope. This paper is the study for construction management on reinforcement method of slope.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.332-336
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• 1991

Network management is responsible for gathering information on the usage of the network media by the network devices, ensuring the correct operation of the network, and providing reports. MAP network management must provide the high reliability of the media and signaling method, even in very harsh environments, providing a very low bit error rate and minimum number of retransmission. In this paper, we analysed the framework of OSI management and MAP network management and discussed the implementation method of fault management and remote management mechanism in the Mini-MAP controller developed for IBM-PC.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.479-484
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• 2007

This paper explains the design and implementation of the FRA(Fault Recovery Agent). FRA is a system that is suitable for recovering software error for multimedia distance education based on home network environment. In terms of distributed multimedia systems, the most important catagories for quality of service are a timeless, volume, and reliability. In this paper, we discuss a method for increasing reliability through fault tolerance. This paper explains a performance analysis of an error recovery system running on distributed multimedia environment using rule-based DEVS modeling and simulation techniques. In DEVS, a system has a time base, inputs, states, outputs, and functions. The proposed method is more efficient than the other method in comparison with error ration and processing time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3779-3784
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• 2012

Real-time process monitoring and diagnosis of industrial processes is one of important operational tasks for quality and safety reasons. The objective of fault diagnosis or identification is to find process variables responsible for causing a specific fault in the process. This helps process operators to investigate root causes more effectively. This work assesses the applicability of combining a nonlinear statistical technique of kernel Fisher discriminant analysis with a preprocessing method as a tool of on-line fault identification. To compare its performance to existing linear principal component analysis (PCA) identification scheme, a case study on a benchmark process was performed to show that the fault identification scheme produced more reliable diagnosis results than linear method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.7
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• pp.508-516
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• 2008

Fault detection and diagnosis(FDD) system is beneficial in equipment management by providing the operator with tools which can help find out a failure of the system. An experimental study has been performed on fault detection and diagnosis method for a water chiller. Bayes classifier, which is one of classical pattern classifiers, is adopted in deciding whether fault occurred or not. Failure modes in this study include refrigerant leakage, decrease in mass flow rate of the chilled water and cooling water, and sensor error of the cooling water inlet temperature. It is possible to detect and diagnose faults in this study by adopting FDD algorithm using only four parameters(compressor outlet temperature, chilled water inlet temperature, cooling water outlet temperature and compressor power consumption). Refrigerant leakage failure is detected at 20% of refrigerant leakage. When mass flow rate of the chilled and cooling water decrease more than 8% or 12%, FDD algorithm can detect the faults. The deviation of temperature sensor over $0.6^{\circ}C$ can be detected as fault.

• Structural Engineering and Mechanics
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• v.92 no.2
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• pp.121-131
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• 2024

This paper proposes a fault detection method for blade pitch systems of floating wind turbines using transformer-based deep-learning models. Transformers leverage self-attention mechanisms, efficiently process time-series data, and capture long-term dependencies more effectively than traditional recurrent neural networks (RNNs). The model was trained using normal operational data to detect anomalies through high reconstruction losses when encountering abnormal data. In this study, various fault conditions in a blade pitch system, including environmental load cases, were simulated using a detailed model of a spar-type floating wind turbine, the data collected from these simulations were used to train and test the transformer models. The model demonstrated superior fault-detection capabilities with high accuracy, precision, recall, and F1 scores. The results show that the proposed method successfully identifies faults and achieves high-performance metrics, outperforming existing traditional multi-layer perceptron (MLP) models and long short-term memory-autoencoder (LSTM-AE) models. This study highlights the potential of transformer models for real-time fault detection in wind turbines, contributing to more advanced condition-monitoring systems with minimal human intervention.

• Journal of Korea Multimedia Society
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• v.20 no.12
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• pp.1970-1979
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• 2017

Computerization of educational administration following educational informatization of government has been steadily improved for the purpose of teachers' offload and job efficiency, finally resulting that NEIS(National Education Information System) has been completed. The NEIS consists of Nationwide service of NEIS, Business portal system of NEIS, Authentication management system and so on. Students, parents and civil petitioners handle civil affairs through Nationwide service of NEIS and teachers and persons of task conduct theirs business by accessing the Business portal system of NEIS. At this time, users have to obtain their certification from Authentication management system. Previous Studies were mainly focused on the evaluation about its performance according to the introduction of NEIS. But from now on there is a growing interest in security assessment and an efficient method for security improvement to check if NEIS works properly. Therefore, in this thesis, we'll propose an analytic framework in which security assessment is carried out after comprehending the fault structures through performing Fault Fishbone Analysis based on the Fault Tree Analysis. As a result of the system applied, the system had the highest rate of improvement to 47.7 percent.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9A
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• pp.868-877
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• 2006

Sensor network applications need synchronized time to the highest degree such as object tracking, consistent state updates, duplicate detection, and temporal order delivery. In addition, reliability issues and fault tolerance in sophisticated sensor networks have become a critical area of research today. In this paper, we proposed a fault tolerant clock management scheme in sensor networks considering two cases of fault model such as network faults and clock faults. The proposed scheme restricts the propagation of synchronization error when there are clock faults of nodes such as rapid fluctuation, severe changes in drift rate, and so on. In addition, it handles topology changes. Simulation results show that the proposed method has about $1.5{\sim}2.0$ times better performance than TPSN in the presence of faults.

• Ocean Systems Engineering
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• v.9 no.3
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• pp.261-285
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• 2019

Nowadays in offshore industry there are emerging hazards with vague property such as act of terrorism, act of war, unforeseen natural disasters such as tsunami, etc. Therefore industry professionals such as offshore energy insurers, safety engineers and risk managers in order to determine the failure rates and frequencies for the potential hazards where there is no data available, they need to use an appropriate method to overcome this difficulty. Furthermore in conventional risk based analysis models such as when using a fault tree analysis, hazards with vague properties are normally waived and ignored. In other word in previous situations only a traditional probability based fault tree analysis could be implemented. To overcome this shortcoming fuzzy set theory is applied to fault tree analysis to combine the known and unknown data in which the pre-combined result will be determined under a fuzzy environment. This has been fulfilled by integration of a generic bow-tie based risk analysis model into the risk assessment phase of the Risk Management (RM) cycles as a backbone of the phase. For this reason Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) are used to analyse one of the significant risk factors associated in offshore terminals. This process will eventually help the insurers and risk managers in marine and offshore industries to investigate the potential hazards more in detail if there is vagueness. For this purpose a case study of offshore terminal while coinciding with the nature of the Caspian Sea was decided to be examined.