• 대한기계학회논문집A
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• 제41권5호
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• pp.381-389
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• 2017

마르코프체인 시뮬레이션으로 추출한 점을 기반으로 커널 밀도함수를 구성하고 중요도 추출함수로 가정하였다. 크리깅 근사모델은 한계상태식 근방에서 상세히 구성되었다. 고장확률은 크리깅 근사모델에 대해 중요도 추출법을 수행하여 계산하였다. 커널 밀도함수가 한계상태식의 근방에서 더 많은 점을 추출할 수 있도록 기존의 방법을 개선하였다. 커널 밀도함수의 파라메터를 찾기 위한 안정적인 수치계산 방안이 제시된다. 크리깅 근사모델의 불확실성으로 인해 계산된 고장확률이 변경될 가능성을 계산하여, 크리깅 근사모델의 완성도를 평가하였다.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2005년도 봄학술 발표회 논문집(II)
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• pp.525-528
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• 2005

This study determines the best composite grade to minimize the void of aggregate mixture based on the maximum density theory in an attempt to suggest a mix proportion method design for asphalt mixtures. Study results show that the grading curve with the maximum mass per unit capacity of each aggregate mixture satisfied the KS standards and the optimum AP content to meet the optimal asphalt mixture void rate of 4$\%$ was 5.7$\%$, less than the optimum AP content of 6.5$\%$ suggested in the Marshal mix proportion method design. At the same time, the asphalt mixture produced based upon the suggested mix proportion method had a flow value 17$\%$ lower than that of asphalt mixture produced according to the Marshal method, while its density was greater by 0.06$\～$0.09. This suggests that the introduced mix proportion method design helps to improve the shape flexibility and crack-resistance of asphalt concrete.

• 품질경영학회지
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• 제49권2호
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• pp.201-211
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• 2021

Purpose: This paper proposes a density adaptive grid algorithm for the k-NN regression model to reduce the computation time for large datasets without significant prediction accuracy loss. Methods: The proposed method utilizes the concept of the grid with centroid to reduce the number of reference data points so that the required computation time is much reduced. Since the grid generation process in this paper is based on quantiles of original variables, the proposed method can fully reflect the density information of the original reference data set. Results: Using five real-life datasets, the proposed k-NN regression model is compared with the original k-NN regression model. The results show that the proposed density adaptive grid-based k-NN regression model is superior to the original k-NN regression in terms of data reduction ratio and time efficiency ratio, and provides a similar prediction error if the appropriate number of grids is selected. Conclusion: The proposed density adaptive grid algorithm for the k-NN regression model is a simple and effective model which can help avoid a large loss of prediction accuracy with faster execution speed and fewer memory requirements during the testing phase.

• Communications for Statistical Applications and Methods
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• 제19권4호
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• pp.517-526
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• 2012

In this paper a support vector method is proposed for use when the sample observations are contaminated by a normally distributed measurement error. The performance of deconvolution density estimators based on the support vector method is explored and compared with kernel density estimators by means of a simulation study. An interesting result was that for the estimation of kurtotic density, the support vector deconvolution estimator with a Gaussian kernel showed a better performance than the classical deconvolution kernel estimator.

• 반도체디스플레이기술학회지
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• 제6권2호
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• pp.45-48
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• 2007

The proposed method offers an improved DC/DC converter scheme to increase power density. It is based on half-bridge topology with newly introduced pulse-grouping control method, which helps to reduce the transformer size and the volume of semiconductor devices maintaining high efficiency. Test results with 85W(18.5V/4.6A) design shows that the measured efficiency is 93.5% with power density of $36W/in^3$.

• 전기학회논문지
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• 제56권1호
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• pp.197-205
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• 2007

We have proposed a novel line detection method based on the estimated probability density function of gradient directions of edges. By estimating peaks of the density function, we determine groups of edges that have the same gradient direction. For edges in the same groups, we detect lines that correspond to peaks of the connectivity weighted distribution of the distances from the origin. In the experiments using the Data Matrix barcode images and LCD images, the proposed method showed better performance than conventional Methods in terms of the processing speed and accuracy.

• Communications for Statistical Applications and Methods
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• 제23권1호
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• pp.71-83
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• 2016

In this paper we discuss a deconvolution density estimator obtained using the support vector machines (SVM) and Tikhonov's regularization method solving ill-posed problems in reproducing kernel Hilbert space (RKHS). A remarkable property of SVM is that the SVM leads to sparse solutions, but the support vector deconvolution density estimator does not preserve sparsity as well as we expected. Thus, in section 3, we propose another support vector deconvolution estimator (method II) which leads to a very sparse solution. The performance of the deconvolution density estimators based on the support vector method is compared with the classical kernel deconvolution density estimator for important cases of Gaussian and Laplacian measurement error by means of a simulation study. In the case of Gaussian error, the proposed support vector deconvolution estimator shows the same performance as the classical kernel deconvolution density estimator.

• 한국분말재료학회지
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• 제4권3호
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• pp.188-195
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• 1997

In most of sintered metal powder compacts, the sintered density distribution is controlled to be as high and uniform as possible to ensure the required mechanical properties. In general, the density distribution in the compacts is not uniform and not easy to measure. In the present study, a method for measuring the density distribution was developed, based on the indentation force equation by which the hardness and the relative density were related. The indentation force equation, expressed as a function of strength constant, workhardening coefficient and relative density, was obtained by finite element analysis of rigid-ball indentation on sintered powder metal compacts. The present method was verified by comparing the predicted density distribution in the sintered Fe-0.5%C-2%Cu compacts with that obtained by experiments, in which the density distribution was directly measured by machining the compacts from the outer surface progressively.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2007년도 하계학술대회 논문집
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• pp.286-288
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• 2007

The proposed method offers an improved control method for high power density AC/DC adapter by using more energy efficient electrical equipments. Power factor corrector (PFC) topology is based on boost topology with boundary conduction mode (BCM). DC/DC topology is based on half-bridge topology with newly introduced off-time control method, which helps to reduce size of the semiconductor and the magnetic devices. Test results with 85W AC/DC adapter (18.5V/4.6A) design shows that the measured efficiency is 90% with power density of $36W/in^3$. It also show low no load power consumption of about 0.5W.

• 반도체디스플레이기술학회지
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• 제23권2호
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• pp.38-44
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• 2024

This research proposed DBSCAN-D, which is a clustering technique for locating POI based on existing density-based clustering research, such as GPS data, generated by moving objects. This method is designed based on 'staying time' and 'directionality' extracted from the relationship between GPS data. The staying time can be extracted through the difference in the reception time between data using the time at which the GPS data is received. Directionality can be expressed by moving the area of data generated later in the direction of the position of the previously generated data by concentrating on the point where the GPS data is sequentially generated. Through these two properties, it is possible to perform clustering suitable for the data set generated by the moving object.