• The KIPS Transactions:PartA
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• v.13A no.7 s.104
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• pp.607-614
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• 2006

The checkpointing schemes should reduce the process delay through managing the checkpoints of each node to fit the network load to enhance the performance of the process running on the cluster system that write the checkpoints into its global stable storage. For this reason, a cluster system with single IO space on a distributed RAID chooses a suitable checkpointng scheme to get the maximum IO performance and the best rollback recovery efficiency. In this paper, we improved the striped checkpointing scheme with dynamic stripe group size by adapting to the network bandwidth variation at the point of checkpointing. To analyze the performance of the multi striped checkpointing scheme, we applied Linpack HPC benchmark with MPI on our own cluster system with maximum 512 virtual nodes. The benchmark results showed that the multistriped checkpointing scheme has better performance than the striped checkpointing scheme on the checkpoint writing efficiency and rollback recovery at heavy system load.

• The Journal of Engineering Geology
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• v.18 no.4
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• pp.501-509
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• 2008

It is very important in designing civil engineering structures that the quantification of geological informations must be carried out in terms of importance. In this study, the geological informations are quantified and evaluated using analytic hierarchy process (AHP). A professional group was organized with 30 people in the field of civil engineering, transport, and geology. On the assumption that the civil engineering structure is linear such as highway or railroad, a survey of the group in terms of geological and hydro-geological elements has found that the hierarchy structure is composed of four levels. And fault structure is a primary factor which causes the stability of a linear civil engineering structure. The importance of geological items are arranged with fault (0.456), foliation/bedding plane(0.l65), lineation(0.144), ground water(0.124), and rock type(0.111).

• Smart Media Journal
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• v.4 no.3
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• pp.16-23
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• 2015

As the IT technology advances, data processing system is required to handle and process large amounts of data. However, the existing On-Disk system has limit to process data which increase rapidly. For that reason, the In-Memory system is being used which saves and manages data on the fast memory not saving data into hard disk. Although it has fast processing capability, it is necessary to use the fault tolerance techniques in the In-Memory system because it has a risk of data loss due to volatility which is one of the memory characteristics. These fault tolerance techniques lead to performance degradation of In-Memory system. In this paper, we classify the data into Hot and Cold data in consideration of the data usage characteristics in the In-Memory system and propose compound backup technique to ensure data persistence. The proposed technique increases the persistence and improves performance degradation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.216-223
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• 2019

Fault detection during production processes is one of the required operational tasks to run production processes both safely and consistently. Unexpected operational events or undetected process faults can have a serious impact on the production systems and subsequently on the final products' quality. In addition, such situations may lead to malfunctions or breakdowns of production processes. To reliably detect such abnormalities, a new one-class classification-based detection scheme has recently been developed The proposed method consists of four steps:1) noise filtering, 2) feature selection, 3) nonlinear representation and 4) outlier detection. The performance of the proposed scheme was demonstrated using the multivariate data obtained from a simulation process. The results have shown that the proposed method produced reliable monitoring results and outperforms any existing methods with an average improvement of 25.4%. The use of proper feature selection in the proposed framework yielded better detection performance.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.4
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• pp.160-167
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• 2021

Seabed deformation due to the fault failure have both a spatial variation and temporal history. When the faulting process initiates at a certain point beneath seabed, the failure spreads out to neighboring points, resulting in temporal changes of deformation. In particular, such a process induces tsunami waves from the vertical motion of seabed. The uprising speed of seabed affects the formation of initial surface profile, eventually altering the arrival time and runup of tsunamis at the coast. In this work, we developed a numerical model that can simulate the generation and propagation of tsunami waves by considering the horizontal and vertical changes of seabed in an active and dynamic manner. For the verification of the model, it was applied to the 2011 Tohoku-oki earthquake in Japan and the results confirmed that the accuracy was improved compared to the existing passive and static model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.111-116
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• 2022

The causes of motor burnout include overload, phase loss, restraint, interlayer short circuit, winding ground fault, instantaneous overvoltage, and the rotor contacting the stator, leading to insulation breakdown, leading to breakdown or electrical accidents. Therefore, equipment failure causes not only loss due to cost required for equipment maintenance/repair, but also huge economic loss due to productivity decrease due to process stop because the process itself including the motor is stopped. The current level of technology for diagnosing motor failures uses vibration, heat, and power analysis methods, but there is a limit to analyzing the problems only after a considerable amount of time has passed according to the failure. Therefore, in this paper, a device and algorithm for measuring insulation resistance using DC AMP signal was applied to an industrial motor to solve this problem. And by following the insulation resistance state value, we propose a diagnosis of deterioration and failure of the motor that cannot be solved by the existing method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.36-42
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• 2021

With recent developments in the Fourth Industrial Revolution, the manufacturing industry has changed rapidly. Through key aspects of Fourth Industrial Revolution super-connections and super-intelligence, machine learning will be able to make fault predictions during the foam-making process. Polyol and isocyanate are components in polyurethane foam. There has been a lot of research that could affect the characteristics of the products, depending on the specific mixture ratio and temperature. Based on these characteristics, this study collects data from each factor during the foam-making process and applies them to machine learning in order to predict faults. The algorithms used in machine learning are the decision tree, kNN, and an ensemble algorithm, and these algorithms learn from 5,147 cases. Based on 1,000 pieces of data for validation, the learning results show up to 98.5% accuracy using the ensemble algorithm. Therefore, the results confirm the faults of currently produced parts by collecting real-time data from each factor during the foam-making process. Furthermore, control of each of the factors may improve the fault rate.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.84.1-84.1
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• 2010

Currently, new and renewable energy come into the spotlight, such as solar energy, wind power, fuel cell, hybrid car etc., due to the energy resource is being depleted. Especially, in order to solve like this problem, the study of solar cell manufacturing systems are being extensively researched such as vacuum process. But the major fault of the vacuum process are its expensive production price. On the order hand, Roll-to-roll printing system, the new technology of solar cell manufacturing, has low production price compare with the vacuum process. Also roll-to-roll printing system can decrease the 95% of waste water and 99.9% of harmful gasses than the vacuum process. So we addressed the roll to roll printing system for the flexible solar cell by using printing technology. This roll-to-roll printing system is comprised of various modules, such as web handling module, fine pattern printing module, dry/curing module, uniform coating module and laminating module etc.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.132-132
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• 2015

Virtual metrology (VM) model based on plasma information (PI) parameter for C4F8 plasma-assisted oxide etching processes is developed to predict and monitor the process results such as an etching rate with improved performance. To apply fault detection and classification (FDC) or advanced process control (APC) models on to the real mass production lines efficiently, high performance VM model is certainly required and principal component regression (PCR) is preferred technique for VM modeling despite this method requires many number of data set to obtain statistically guaranteed accuracy. In this study, as an effective method to include the 'good information' representing parameter into the VM model, PI parameters are introduced and applied for the etch rate prediction. By the adoption of PI parameters of b-, q-factors and surface passivation parameters as PCs into the PCR based VM model, information about the reactions in the plasma volume, surface, and sheath regions can be efficiently included into the VM model; thus, the performance of VM is secured even for insufficient data set provided cases. For mass production data of 350 wafers, developed PI based VM (PI-VM) model was satisfied required prediction accuracy of industry in C4F8 plasma-assisted oxide etching process.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.37-41
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• 2018

Process safety technology has developed from qualitative methods such as HAZOP (hazard and operability study) to semi-quantitative methods such as LOPA (layer of protection analysis), and quantitative methods are actively studied these days. Quantitative risk assessment (QRA) is often based on fault tree analysis (FTA). FTA is efficient, but difficult to apply when failure events are not independent of each other. This problem can be avoided using a Markov process (MP). MP requires definition of all possible states, and thus, generally, is more complicated than FTA. A method is proposed in this work that uses an MP model and a Weibull distribution model in order to construct a reliability model for multiple dependent failures. As a case study, a pressure safety valve (PSV) is considered, for which there are three kinds of failure, i.e. open failure, close failure, and gas tight failure. According to recently reported inspection results, open failure and close failure are dependent on each other. A reliability model for a PSV group is proposed in this work that is to reproduce these results. It is expected that the application of the proposed method can be expanded to QRA of various systems that have partially dependent multiple failure states.