• Journal of Korea Multimedia Society
• /
• v.10 no.10
• /
• pp.1260-1270
• /
• 2007

Testing and diagnosis of analog circuits(or mixed-signal circuits) continue to be a hard task for test engineers and efficient test methodologies to solve these problems are needed. This paper proposes a novel analog circuits test technique using time slot specification (TSS) based built-in current sensors (BICS). A technique for location of a fault site and separation of fault type based on TSS is also presented. The proposed built-in current sensors and TSS technique has high testability, fault coverage and a capability to diagnose catastrophic faults and parametric faults in analog circuits. In order to reduce time complexity of test point insertion procedure, external output and power nodes are used for test points and the current sensors are implemented in the automatic test equipment(ATE). The digital output of BICS can be easily combined with built-in digital test modules for analog IC test.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.901-904
• /
• 2005

Testing of mixed-signal circuit has become a difficult task for test engineers and efficient test solution to these problems are needed. In this paper a new specification-based mixed-signal test method called TSS(Time Slot Specification) using high performance current sensors and a novel test point selection technique without heavy computational overhead are proposed. External output and power nodes are used for test points and accessed by the current sensors in the ATE.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.11a
• /
• pp.1343-1346
• /
• 2013

본 연구에서는 기존의 Viola-Jones 물체 검출 프레임워크를 개선하여 하나의 특징 당 더 높은 효율을 가지며 검출대상이 아닌 서브 윈도우들을 더 빠르게 제거하는 학습 알고리즘을 제안한다. 학습의 결과로 생성된 물체 검출기는 서브윈도우를 특정 임계값까지 빠르게 제거하기 때문에 서브윈도우당 계산수가 줄어든다. 기존의 Viola-Jones 물체 검출기와 동일한 프레임워크이므로 인식성능에는 영향을 주지 않는다. MIT-CMU 테스트 집합에 대해서 서브윈도우당 특징 계산 횟수를 측정하였으며 기존 계산 횟수의 57%로 줄어들어 검출 속도가 약 71% 향상됨을 확인하였다.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.1
• /
• pp.9-18
• /
• 2015

Software Reliability Growth Models (SRGMs) are useful for determining the software release date or additional testing efforts by using software failure data. It is not appropriate for a SRGM to apply to all software. And besides a large number of SRGMs have already been proposed to estimate software reliability measures. Therefore selection of an optimal SRGM for use in a particular case has been an important issue. The existing methods for selecting a SRGM use the entire collected failure data. However, initial failure data may not affect the future failure occurrence and, in some cases, it results in the distorted result when evaluating the future failure. In this paper, we suggest a method for selecting a SRGM based on the evaluation goodness-of-fit using partial data. Our approach uses partial data except for inordinately unstable failure data in the entire failure data. We will find a portion of data used to select a SRGM through the comparison between the entire failure data and the partial failure data excluded the initial failure data with respect to the predictive ability of future failures. To justify our approach this paper shows that the predictive ability of future failures using partial data is more accurate than using the entire failure data with the real collected failure data.

• KIPS Transactions on Software and Data Engineering
• /
• v.9 no.12
• /
• pp.431-438
• /
• 2020

In this paper, the method to extract lip contour by multiple threshold is proposed. Spyridonos et. el. proposed a method to extract lip contour. First step is get Q image from transform of RGB into YIQ. Second step is to find lip corner points by change point detection and split Q image into upper and lower part by corner points. The candidate lip contour can be obtained by apply threshold to Q image. From the candidate contour, feature variance is calculated and the contour with maximum variance is adopted as final contour. The feature variance 'D' is based on the absolute difference near the contour points. The conventional method has 3 problems. The first one is related to lip corner point. Calculation of variance depends on much skin pixels and therefore the accuracy decreases and have effect on the split for Q image. Second, there is no analysis for color systems except YIQ. YIQ is a good however, other color systems such as HVS, CIELUV, YCrCb would be considered. Final problem is related to selection of optimal contour. In selection process, they used maximum of average feature variance for the pixels near the contour points. The maximum of variance causes reduction of extracted contour compared to ground contours. To solve the first problem, the proposed method excludes some of skin pixels and got 30% performance increase. For the second problem, HSV, CIELUV, YCrCb coordinate systems are tested and found there is no relation between the conventional method and dependency to color systems. For the final problem, maximum of total sum for the feature variance is adopted rather than the maximum of average feature variance and got 46% performance increase. By combine all the solutions, the proposed method gives 2 times in accuracy and stability than conventional method.