• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2275-2278
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• 2003

In this paper, we propose a visual inspection algorithm to detect can print-errors by using multi-camera and image valuing algorithm. The features of the algorithm are to use four cameras that are arranged with 90$^{\circ}$ between each other and to adopt a synthesized image model which represents whole surface of a can. Using the model, detection process is straight forward, namely it is comparing a partial region of the can to a specific region of the model where is previously marked.

• 대한전기학회논문지
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• 제33권1호
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• pp.17-20
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• 1984

The motivation in this paper is in constructing the controller with faster adapting speed than the one using the errors between the states of the plant and the model as the adaptive criterion. In the first part of this work, the adaptive law is found by using the state errors. In the later part, the adaptive law is obtained by introducing the companion model method. Finally the justification for the adaptive speed characteristics are compared.

• 대한수학회보
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• 제56권6호
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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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2009년도 추계학술대회 논문집
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• pp.579-580
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• 2009

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.258-258
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• 2018

In this study, a hydraulic flow model and an error correction model are combined to improve the flood simulation accuracy. First, the hydraulic flow model is calibrated by optimizing the Manning's roughness coefficient that considers spatial and temporal variability. Then, an error correction model were used to correct the systematic errors of the calibrated hydraulic model. The error correction model is developed using Artificial Neural Networks (ANNs) that can estimate the systematic simulation errors of the hydraulic model by considering some state variables as inputs. The input variables are selected using parital mutual information (PMI) technique. It was found that the calibrated hydraulic model can simulate flood water levels with good accuracy. Then, the accuracy of estimated flood levels is improved further by using the error correction model. The method proposed in this study can be used to the flood control and water resources management as it can provide accurate water level eatimation.

• 대기
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• 제25권1호
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• pp.1-18
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• 2015

The most objective way to overcome the limitation of numerical weather prediction model is to represent the uncertainty of prediction by introducing probabilistic forecast. The uncertainty of the numerical weather prediction system developed due to the parameterization of unresolved scale motions and the energy losses from the sub-scale physical processes. In this study, we focused on the growth of model errors. We performed ensemble forecast to represent model uncertainty. By employing the multi-physics scheme (PHYS) and the stochastic kinetic energy backscatter scheme (SKEBS) in simulating typhoon Rusa (2002), we assessed the performance level of the two schemes. The both schemes produced better results than the control run did in the ensemble mean forecast of the track. The results using PHYS improved by 28% and those based on SKEBS did by 7%. Both of the ensemble mean errors of the both schemes increased rapidly at the forecast time 84 hrs. The both ensemble spreads increased gradually during integration. The results based on SKEBS represented model errors very well during the forecast time of 96 hrs. After the period, it produced an under-dispersive pattern. The simulation based on PHYS overestimated the ensemble mean error during integration and represented the real situation well at the forecast time of 120 hrs. The displacement speed of the typhoon based on PHYS was closest to the best track, especially after landfall. In the sensitivity tests of the model uncertainty of SKEBS, ensemble mean forecast was sensitive to the physics parameterization. By adjusting the forcing parameter of SKEBS, the default experiment improved in the ensemble spread, ensemble mean errors, and moving speed.

• 정보교육학회논문지
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• 제2권1호
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• pp.35-51
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• 1998

Software reliability growth model is one of the evaluation methods, software quality which quantitatively calculates the software reliability based on the number of errors detected. For correct and precise evaluation of reliability of certain software, the reliability model, which is considered to fit dose to real data should be selected as well. In this paper, the optimal model for specific test data was selected one of among five software reliability growth models based on NHPP(Non Homogeneous Poission Process), and in result reliability estimating scales(total expected number of errors, error detection rate, expected number of errors remaining in the software, reliability etc) could obtained. According to reliability estimating scales obtained, Software development and predicting optimal release point and finally in conducting systematic project management.

• 대한인간공학회지
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• 제13권2호
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• pp.33-41
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• 1994

The paper presents a new scheme and a support system for the analysis sof hyman errors in nuclear power plants based on a cognitive model. We discusse the problems identified in current managerial analysis, and propose a new approach that frames the description of human activities according to a human decision making modle, so that it could provide a better reconstruction of a sequence of event suspected of involving human errors. This sophistcated approach becomes practical for the field application with the support of a computerized aiding system. The model-based event re-construction method is expected to enable the analysts to produce more informative reports, which in turn heop to derive appropriate counter- measures to reduce the possibility of the analyzed human errors.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.290-291
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• 2007

Barometers can provide height information steady but its accuracy becomes poor as the air data varies due to the vehicles's moving or time's elapsing. In order to keep the accuracy in spite of the air data changes, we propose a filter for the identification of baro-errors. The baro-errors mainly consist of bias and scale factor errors which gradually varies as the air data varies. With GPS height measurements, the scale factor and bias estimator is designed by applying the interacting multiple model (IMM) filtering technique to the baro-error random walk model. The resultant estimates are used to compensate current baro-measurement to supply accurate measurements steadily.

• 한국정밀공학회지
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• 제15권11호
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• pp.137-144
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• 1998

In this paper we present our research dealing with the problem of tool deflection during the milling. We try to compensate the errors by considering a new tool trajectory. In order to determine the compensated tool trajectory, the problem is divided in three steps : cutting forces model, tool deflection model and trajectory compensation. Starting from experimental data, we determine a cutting forces model., which allows us to anticipate the tool deflection along one nominal path. In order to determine the compensated tool trajectory, we propose in this paper a method of path compensation, called “mirror method”. This method of tool path optimization allows to minimize errors due to tool deflection. Several examples are processed in simulations and validated experimentally.