• Proceedings of the KSR Conference
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• 2009.05a
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• pp.483-494
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• 2009

Since the embedded system is more intelligent, the importance of the reliability in the embedded system is a lot more visible. Especially the reliability of the embedded system in the train control system is even better important. As the special quality of the embedded system, the hardware of the system is directly controlled by the software in the embedded system. As the expansion of complexity, the expense amd the time for verification is required more and more. This paper is presented the verification of the reliability as the method with background of failure Embedded system is gradually, the importance of 'A built-in on the system embedded system's reliability is focused. In particular, in the train control system built-in of the embedded system, reliability is even more important. The embedded system of the system controls over hardware, software with built-in directly. The more complex system is, the more increasable of depending on the reliability of the time verification and expensive is. This paper is about he characteristics of the reliability and verification of embedded system under the failure mechanisms, based on the verification methodology suggested by in the train control system.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

• Journal of Platform Technology
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• v.9 no.1
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• pp.32-39
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• 2021

Existing environmental measuring devices mainly focus on electromagnetic wave and eco-friendly product certification and durability test, and sensor reliability verification and verification of measurement data are conducted mainly through sensor performance evaluation through type approval and registration, acceptance test, initial calibration, and periodic test. This platform has established an ICT-based environmental monitoring sensor reliability verification system that supports not only performance evaluation for each target sensor, but also a verification system for sensor data reliability. A sensor board to collect sensor data for environmental information was produced, and a sensor and data reliability evaluation and verification service system was standardized. In addition, to evaluate and verify the reliability of sensor data based on ICT, a sensor data platform monitoring prototype using LoRa communication was produced, and the test was conducted in smart cities. To analyze the data received through the system, an optimization algorithm was developed using machine learning. Through this, a sensor big data analysis system is established for reliability verification, and the foundation for an integrated evaluation and verification system is provide.

• Journal of Korea Game Society
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• v.11 no.6
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• pp.53-60
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• 2011

Since the importance of software reliability for game service increases continuously, the reliability evaluation becomes very important. This research performed an experiment which was intended to analyze the effect of software verification and validation, a representative activity of the software development process, on the software reliability. The results from the experiments provided the reliability evaluation based on the development process (e.g., Bayesian Belief Network based reliability estimation) with very useful bases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1360-1388
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• 2021

Shipbuilding and repairing enterprise has the characteristics of many hazards and accidents. Therefore, the safety management ability of shipbuilding and repairing MIS (management information system) must be effectively guaranteed. The verification on safety management is the necessary measure to ensure and improve the safety management ability of MIS. Safety verification can not only increase the safety of MIS, but also make early warning of potential risks in management to avoid the accidents. Based on the authoritative standards in the field of safety in shipbuilding and repairing enterprise, this paper applied modeling and verification method based on ontology to safety verification of MIS, extracted the concepts and associations from related safety standards to construct axiom set to support safety verification on MIS of shipbuilding and repairing enterprise. Then, this paper developed the corresponding safety ontology modeling and verification tool-SOMVT. By the application and comparison of two examples, this paper effectively verified the safety of MIS to prove the modeling method and the SOMVT can improve the safety of MIS in a much more effective and stable way to traditional manual analysis.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.59-65
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• 2021

In this paper, we propose the AI certification standardization activities for systematic research and planning for the standardization of trustworthy artificial intelligence (AI). The activities will be in two-fold. In the stage 1, we investigate the scope and possibility of standardization through AI reliability technology research targeting international standards organizations. And we establish the AI reliability technology standard and AI reliability verification for the feasibility of the AI reliability technology/certification standards. In the stage 2, based on the standard technical specifications established in the previous stage, we establish AI reliability certification program for verification of products, systems and services. Along with the establishment of the AI reliability certification system, a global InterOp (Interoperability test) event, an AI reliability certification international standard meetings and seminars are to be held for the spread of AI reliability certification. Finally, TAIPP (Trustworthy AI Partnership Project) will be established through the participation of relevant standards organizations and industries to overall maintain and develop standards and certification programs to ensure the governance of AI reliability certification standards.

• Journal of IKEEE
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• v.15 no.4
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• pp.267-273
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• 2011

In hardware design, its stability and reliability are important, because a hardware error can cause serious damages or disaster. To improve stability and reliability, this paper presents the implementation of the hardware verification system using the fault injection method in PC environment. This paper presents a verification platform that can verify hardware system reliably and effectively, through a process to generate faults as well as insert input signals into the actual running system environment. The verification system is configured to connect a PC with a digital I/O card, and it can transmit or receive signals from the target system, as a verifier's intention. In addition, it can generate faults and inject them into the target system. And it can be monitored by displaying the received signals from the target system to the graphical wave signals. We can evaluate its reliability by analyzing the graphical wave signals. In this paper, the proposed verification system has been applied to the FPGA firmware of a nuclear power plant control system. As a result, we found its usefulness and reliability.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1425-1429
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• 2003

In this study, when structure which is combined by welding is receiving internal pressure, finite element analysis to confirm stability of structure and reliability of welding part is achieved. And we analyze the results. Also, if stability of the structure and reliability of the welding part are not defined, research that look for method to change design to receive stability and reliability is achieved.

• Bulletin of the Korean Mathematical Society
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• v.56 no.6
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• pp.1435-1445
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• 2019

We consider a checkpointing model for silent errors, where a checkpoint is taken every fixed number of verifications. Assuming generally distributed i.i.d. inter-occurrence times of errors, we derive the reliability of the model as a function of the number of verifications between two checkpoints and the duration of work interval between two verifications.

• International Journal of Reliability and Applications
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• v.10 no.2
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• pp.109-118
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• 2009

Crankshaft, the core element of the engine of a vehicle, transforms the translational motion generated by combustion to rotational motion. Its failure will cause serious damage to the engine so its reliability verification must be performed. In this study, the S-N data of the bending and torsion fatigue limits of a crankshaft are derived. To evaluate the reliability of the crankshaft, reliability verification and analysis are performed. For the purpose of further evaluation, the bending and torsion tests of the original crankshaft are carried out, and failure mode analysis is made. The appropriate number of samples, the applied load, and the test time are computed. On the basis of the test results, Weibull analysis for the shape and scale parameters of the crankshaft is estimated. Likewise, the $B_{10}$ life under 50% of the confidence level and the MTTF are exactly calculated, and the groundwork for improving the reliability of the crankshaft is laid.