• Safety and Health at Work
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• 제3권2호
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• pp.92-100
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• 2012

Objectives: The French National Occupational Diseases Surveillance and Prevention Network (RNV3P) is a French network of occupational disease specialists, which collects, in standardised coded reports, all cases where a physician of any specialty, referred a patient to a university occupational disease centre, to establish the relation between the disease observed and occupational exposures, independently of statutory considerations related to compensation. The objective is to compare the relevance of disproportionality measures, widely used in pharmacovigilance, for the detection of potentially new disease ${\times}$ exposure associations in RNV3P database (by analogy with the detection of potentially new health event ${\times}$ drug associations in the spontaneous reporting databases from pharmacovigilance). Methods: 2001-2009 data from RNV3P are used (81,132 observations leading to 11,627 disease ${\times}$ exposure associations). The structure of RNV3P database is compared with the ones of pharmacovigilance databases. Seven disproportionality metrics are tested and their results, notably in terms of ranking the disease ${\times}$ exposure associations, are compared. Results: RNV3P and pharmacovigilance databases showed similar structure. Frequentist methods (proportional reporting ratio [PRR], reporting odds ratio [ROR]) and a Bayesian one (known as BCPNN for "Bayesian Confidence Propagation Neural Network") show a rather similar behaviour on our data, conversely to other methods (as Poisson). Finally the PRR method was chosen, because more complex methods did not show a greater value with the RNV3P data. Accordingly, a procedure for detecting signals with PRR method, automatic triage for exclusion of associations already known, and then investigating these signals is suggested. Conclusion: This procedure may be seen as a first step of hypothesis generation before launching epidemiological and/or experimental studies.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2004년도 추계 학술대회 논문집
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• pp.13-18
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• 2004

In this study, a new method is proposed generating 3D wire-frames of building using the lowest level topology, points, which are input by human operators. Through the procedure, it is possible to make prediction occlusion points and generate the topology automatically among points, lines, surfaces from buildings. In order to adjust the error of initial values which are input manually, the least squares adjustment for model-image fitting is carried out using the edge information of aerial imagery. And also, model fitting procedure is done making all surfaces plane of buildings by the least squares adjustment. As a result of those procedure, 3D building models are refined similar to real figures of buildings.

• 한국자동차공학회논문집
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• 제11권5호
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• pp.29-36
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• 2003

Exhaust manifolds suffer from serious temperature variation during the thermal fatigue test. The spatial distribution of temperature changes at each moment. Because transient flow can not be simulated during the long period of temperature change, the simulation can not be performed by conjugate heat transfer analysis. In this study, a new procedure for transient thermal analysis is established by decoupling fluid-solid analysis. The procedure consists of (1) transient CFD calculation (2 cycles), (2) mapping heat transfer coefficient to the inner surface of solid mesh as a boundary condition of heat conduction analysis and (3) transient heat conduction analysis in the long period (30 min). The realistic temperature change can be predicted by this procedure.

• 산업기술연구
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• 제28권B호
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• pp.101-109
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• 2008

In general, non-stationary or chaos time series forecasting is very difficult since there exists a drift and/or nonlinearities in them. To overcome this situation, we suggest a new prediction method based on multiple model TS fuzzy predictors combined with preprocessing of time series data, where, instead of time series data, the differences of them are applied to predictors as input. In preprocessing procedure, the candidates of optimal difference interval are determined by using con-elation analysis and corresponding difference data are generated. And then, for each of them, TS fuzzy predictor is constructed by using k-means clustering algorithm and least squares method. Finally, the best predictor which minimizes the performance index is selected and it works on hereafter for prediction. Computer simulation is performed to show the effectiveness and usefulness of our method.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 1999년도 제3회 압연심포지엄 논문집 압연기술의 미래개척 (Exploitation of Future Rolling Technologies)
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• pp.438-446
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• 1999

Crop minimization of the top and bottom ends of hot rolled plate, in a plate, in a plate mill, has been investigated. The existing model to determine the edging pattern at the finishing rolling pass was not reasonable to get high width accuracy and rolling yields. New models including width prediction have been formulated by using neural network model of back propagation learning algorithm and statistical analysis based on the actual production rolling data to give the optimal pattern for minimizing trimming loss. Using these models, at a given rolling condition of broadside pass and finishing pass and the permissible condition of width variation, it was possible to minimize crip at the top and bottom ends according to optimum procedure in plate mill. An application to improve the plan view pattern reduced width variation by 23% and crop length by 30% on average with an effective fishtail crop shape.

• 한국안전학회지
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• 제16권3호
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• pp.117-124
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• 2001

This paper introduces m analysis framework and procedure for the support of the cognitive error analysis of emergency tasks in nuclear poler plants. The framework provides a new perspective in the utilization of influencing factors into error prediction. The framework can be characterized by two features. First, influencing factors that affect the occurrence of human error me classified into three groups, i.e., task characteristic factors(TCF), situation factors(SF), and performance assisting factors(PAF). This classification aims to support error prediction from the viewpoint of assessing the adequacy of PAF under given TCF and SF. Second, the assessment of influencing factors is made by each cognitive function. Through this, influencing factors assessment and error prediction can be made in an integrative way according to each cognitive function. In addition, it helps analysts identify vulnerable cognitive functions and error factors, and obtain specific nor reduction strategies. The proposed framework was applied to the error analysis of the bleed and feed operation of nuclear emergency tasks.

• 소성∙가공
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• 제28권2호
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• pp.89-97
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• 2019

In this paper, we examine the application of a new concept - on-line FE model in various metal rolling processes. This technology allows for completion of process simulation within a tiny fraction of a second without losing the high level of prediction accuracy inherent to FEM. The procedure is systematically demonstrated through the design of actual on-line models for the prediction of the width spread in horizontal rolling of the slab using a dog bone profile and horizontal rolling of the strip with a strip profile. The validity and the prediction accuracy of the on-line FE models were analyzed and discussed.

• Earthquakes and Structures
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• 제7권1호
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• pp.17-38
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• 2014

As the desire for high performance buildings increases, it is increasingly evident that engineers require reliable methods for the estimation of seismic demands on both structural and non-structural components. To this extent, improved tools for the prediction of floor spectra would assist in the assessment of acceleration sensitive non-structural and secondary components. Recently, a new procedure was successfully developed and tested for the simplified construction of floor spectra, at various levels of elastic damping, atop single-degree-of-freedom structures. This paper extends the methodology to multi-degree-of-freedom (MDOF) supporting systems responding in the elastic range, proposing a simplified modal combination approach for floor spectra over upper storeys and accounting for the limited filtering of the ground motion input that occurs over lower storeys. The procedure is tested numerically by comparing predictions with floor spectra obtained from time-history analyses of RC wall structures of 2- to 20-storeys in height. Results demonstrate that the method performs well for MDOF systems responding in the elastic range. Future research should further develop the approach to permit the prediction of floor spectra in MDOF systems that respond in the inelastic range.

• 한국구조물진단유지관리공학회 논문집
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• 제14권5호
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• pp.119-127
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• 2010

본 논문에서는 탄산화 콘크리트 구조물의 내구성을 예측하기 위한 새로운 접근 방법을 제시하였다. 제시된 예측 방법은, 새로운 계측 데이터가 있을 때 베이스 이론에 근거하여 지속적인 업데이팅이 가능하며 모델 매개변수의 확률론적인 특성이 고려된다. 탄산화 내구성 해석 모델의 절차는 라틴 하이퍼큐브 샘플 추출법(LHS)으로 간단하게 정리되고, 이를 통해 얻는 표본으로 결정된다. 이 방법은 콘크리트 구조물의 설계에 유용하게 사용될 수 있으며, 모니터링을 통한 콘크리트 구조물의 잔존수명을 예측할 수 있다. 본 논문에서 사전예측치는 탄산화에 노출된 국내 콘크리트 구조물 데이터(3700개 시편)를 이용하여 콘크리트 탄산계수의 확률 특성을 고려하여 나타내었으며, 우도함수는 현장 모니터링 데이터를 이용하였으며 사후예측치는 사전예측치와 우도함수를 조합하여 나타내었다. 또한, 몬테 카를로 시뮬레이션(MCS)과 LHS의 비교를 통하여 본 논문에서 수행된 LHS를 이용한 샘플링기법이 보다 효율적인 시뮬레이션 수행이 가능함을 확인하였다.

• 제어로봇시스템학회논문지
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• 제6권1호
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• pp.104-111
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• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.