• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제55권3호
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• pp.111-115
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• 2006

We investigated accelerated soft error rate(ASER) in 8M static random access memory(SRAM) cells. The effects on ASER by well structure, operational voltage, and cell transistor threshold voltage are examined. The ASER decreased exponentially with respect to operational voltage. The chips with buried nwell1 layer showed lower ASER than those either with normal well structure or with buried nwell1 + buried pwell structure. The ASER decreased as the ion implantation energy onto buried nwell1 changed from 1.5 MeV to 1.0 MeV. The lower viscosity of the capping layer also revealed lower ASER value. The decrease in the threshold voltage of driver or load transistor in SRAM cells caused the increase in the transistor on-current, resulting in lower ASER value. We confirmed that in order to obtain low ASER SRAM cells, it is necessary to also the buried nwell1 structure scheme and to fabricate the cell transistors with low threshold voltage and high on-current.

• Journal of the Korean Physical Society
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• 제73권11호
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• pp.1644-1649
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• 2018

Aiming at infrared thermal images with different buried depth defects, we study a variety of image segmentation algorithms based on the threshold to develop global search ability and the ability to find the defect area accurately. Firstly, the iterative thresholding method, the maximum entropy method, the minimum error method, the Ostu method and the minimum skewness method are applied to image segmentation of the same infrared thermal image. The study shows that the maximum entropy method and the minimum error method have strong global search capability and can simultaneously extract defects at different depths. However none of these five methods can accurately calculate the defect area at different depths. In order to solve this problem, we put forward a strategy of "divide and conquer". The infrared thermal image is divided into several local thermal maps, with each map containing only one defect, and the defect area is calculated after local image processing of the different buried defects one by one. The results show that, under the "divide and conquer" strategy, the iterative threshold method and the Ostu method have the advantage of high precision and can accurately extract the area of different defects at different depths, with an error of less than 5%.

• 전자공학회논문지
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• 제51권1호
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• pp.161-171
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• 2014

허프변환은 이미지 영역에서 패러미터 영역으로의 변환을 통해 주어진 이미지에서 모델 인스턴스를 추출해내는 방식으로 허프변환된 결과는 패러미터 영역 좌표에 해당하는 Cell 카운터들의 히스토그램 형태가 된다. 다음 단계로 임계값을 정한 후 이를 상회하는 카운터 값에 해당하는 패러미터 값을 통해 모델 인스턴스를 추출하게 되는데 일반적으로 그 임계값은 최고 Cell 카운터 값의 일정 부분에 해당하는 값을 주로 선택하게 된다. 임계점이 너무 낮을 경우 잘못된 모델 인스턴스를 추출할 가능성이 있으며(false positives) 반대로 너무 높은 임계점을 선택할 경우 존재하는 모델 인스턴스를 추출해내지 못하는 오류(false negatives)를 초래하게 된다. 본 논문에서는 일반화된 허프변환(Generalized Hough Transform) 적용 시 패러미터 영역에서의 Cell 카운터 값의 임계점 선택을 위한 방법으로 확률적인 접근방식을 제시하며 이를 위해 Cell 카운터 분포에 해당하는 조건부 확률을 도출하여 과학적인 임계점 선택이 가능함을 입증한다.

• 한국안전학회지
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• 제15권3호
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• pp.1-6
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• 2000

In fatigue crack growth test, it is important not only to analyze characteristics of fatigue crack growth but also to determine the threshold stress intensity factor, ${\Delta}K_{th}$. which is the threshold value of fatigue crack growth. Linear regression analysis using fatigue test data near the threshold is suggested to determine the ${\Delta}K_{th}$ in the standard test method but the ${\Delta}K_{th}$ can be affected by a fitting method. And there are some limitations on the linear regression analysis in the case of small number of test data near the threshold. The objective of this study is to investigate differences of the ${\Delta}K_{th}$ due to regression analysis method and to evaluate the relative error range of the ${\Delta}K_{th}$ in same fatigue crack growth test data.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.123-126
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• 2000

In this paper, we propose new watermarking technique using weighting factor decision method in the watermark embedding step and adaptive threshold decision method in the watermark extracting step. In our method, we are determined weighting factor in simple by calculating distance between pixel coefficient and neighborhood pixel coefficients and threshold is adaptively determined by searching the minimized extract error value using histogram of difference value.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.1155-1158
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• 1999

In this paper, we consider the optimal control of detection threshold to minimize the conditional mean-square state estimation error for the probabilistic data association (PDA) filter. Earlier works on this problem involved the cumbersome graphical optimization algorithm or time-consuming numerical optimization algorithm. Using the numerical approximation of information reduction factor, we obtained the closed-form optimal detection threshold. This results are very useful for real-time implemenation.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2004년도 춘계 학술대회논문집
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• pp.77-82
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• 2004

A new anisotropic mesh refinement method is proposed. The new method is based on a simple second order interpolation error indicator. Therefore, it is methodologically direct and intuitive as compared with traditional anisotropic refinement strategies. Moreover, it does not depend on the mesh type. The error indicator is face-wisely calculated for all faces in a mesh and the cell refinement type is determined by the configuration of face markings with a given threshold. For the sake of simplicity, an application for a poisson equation on a triangle mesh is considered. The error field and resultant mesh refinement pattern are compared and effects of the threshold selection are discussed. Applying anisotropic refinement with various thresholds, we observed higher convergence rates than those in the uniform refinement cases.

• 한국가스학회지
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• 제25권5호
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• pp.63-69
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• 2021

본 연구에서는 오토인코더의 재구성 오류의 임계값을 이용하여 가스 시설에서의 작업이 정상 작업인지 비정상 작업인지를 판단하는 알고리즘을 구축하였다. 이 알고리즘은 정상 작업의 시계열 데이터만으로 오토인코더를 학습하여 최적화된 정상 작업의 재구성 오류의 임계값을 도출한다. 이 알고리즘을 새로운 작업의 시계열 데이터에 적용하여 재구성 오류를 구한 다음 이것을 정상 작업의 재구성 오류 임계값과 비교하여 정상작업인지 비정상 작업인지를 판별한다. 이 알고리즘을 학습하고 검증하기 위해서 가상의 가스 시설에서의 작업을 규정하고 정상 작업 데이터로만 이루어진 학습 데이터 세트와 정상 작업과 비정상 작업 데이터를 모두 포함한 검증 데이터 세트를 구축하였다.

• 대한전자공학회논문지
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• 제21권4호
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• pp.58-64
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• 1984

이온주입형 E-IGFET에서 이온주입층내 불순물 profile을 임의의 형태로 가정하였으며, 가정한 불순물 profile을 이용하여 threshold 전압에 대한 간단한 model을 유도하였다. 유도한 model을 이용하여 Gaus-sian-profile일 때의 threshold 전압치를 구하였고, 실제의 측정 data와 비교하였을 때 일치함을 확인할 수 있었다. 더불어, box-profile일 때의 threshold 전압치의 오차를 계산해 보았다. 또한, substrate-bias에 의한 threshold 전압의 변화를 simulation하였으며. 계산과정에서 이온주입층의 깊이 D를 구하는 새로운 방법을 제시하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1519-1522
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• 2002

In this paper, we propose a new adaptive dissolve detection method based on the analysis of a dissolve modeling error that is the difference between an ideally modeled dissolve curve without any correlation and an actual variance curve with a correlation. The dissolve modeling error is determined based on a correlation between two scenes and variances for each scene. First, Candidate regions are extracted by using the characteristics of a parabola that is downward convex, then the candidate region will be verified based on a dissolve modeling error. If a dissolve modeling error on a candidate region is less than a threshold that is defined by a dissolve modeling error with a target correlation, the candidate region should be a dissolve region with a correlation less than the target correlation. The threshold is adaptively determined based on the variances between the candidate regions and the target correlation. By considering the correlation between neighbor scenes, the proposed method is able to be a semantic scene-change detector. The proposed algorithm was tested on various types of data and its performance proved to be more accurate and reliable when compared with other commonly used methods