• Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.253-260
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• 2015

Feature-based NC machining, which requires high quality of 3D CAD model, is widely used in machining aircraft structural part. However, there has been little research on how to automatically detect the CAD model errors. As a result, the user has to manually check the errors with great effort before NC programming. This paper proposes an automatic CAD model errors detection approach for aircraft structural part. First, the base faces are identified based on the reference directions corresponding to machining coordinate systems. Then, the CAD models are partitioned into multiple local regions based on the base faces. Finally, the CAD model error types are evaluated based on the heuristic rules. A prototype system based on CATIA has been developed to verify the effectiveness of the proposed approach.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.4
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• pp.402-409
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• 2013

An innovative application of voltage-contrast (VC) inspection allowed inline detection of NMOS leakage in dense SRAM cells is presented. Cell sizes of SRAM are continual to do the shrinkage with bit density promotion as semiconductor technology advanced, but the resulting challenges include not only development of smaller-scale devices, but also intra-devices isolation. The NMOS leakage caused by the underneath n+/P-well shorted to the adjacent PMOS/N-well was inspected by the proposed electron-beam (e-beam) scan in which VC images were compared during the in-line process step of post contact tungsten (W) CMP (Chemical Mechanical Planarization) instead of end-of-line electrical test, which has a long response time. A series of experiments based on the mechanism for improving the intra-well isolation was performed and verified by the inline VC inspection. An optimal process-integration condition involved to the tradeoff between the implant dosage and photo CD was carried out.

• Bulletin of the Korean Chemical Society
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• v.31 no.11
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• pp.3259-3264
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• 2010

A label-free amperometric immunosensor has been proposed for the detection of myeloperoxidase (MPO) in human serum. To fabricate such an immunosensor, a composite film consisting of N,N-dimethylformamide (DMF), multiwall carbon nanotubes (MWCNTs) and 1-ethyl-3-methyl imidazolium tetrafluoroborate ($EMIMBF_4$) suspension was initially formed on a glassy carbon electrode (GCE). Then cerium dioxide ($CeO_2$) dispersed by chitosan was coated on the GCE. After that, MPO antibodies (anti-MPO) were attached onto the nano$CeO_2$ surface. With a noncompetitive immunoassay format, the antibody-antigen complex formed between the immobilized anti-MPO and MPO in sample solution. The immunosensor was characterized by cyclic voltammetry, transmission electron microscopy (TEM) and scanning electron microscopy (SEM). The factors influencing the performance of the immunosensor were studied in detail. Under optimal conditions, the current change before and after the immunoreaction was proportional to MPO concentration in the range of 5 to $300\;ng\;mL^{-1}$ with a detection limit of $0.2\;ng\;mL^{-1}$.

• Bulletin of the Korean Chemical Society
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• v.35 no.1
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• pp.204-210
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• 2014

The nitrogen doped porous carbon nanopolyhedrons (N-PCNPs)-multi-walled carbon nanotubes (MWCNTs) hybrid materials were prepared for the first time. Combining the excellent catalytic activities, good electrical conductivities and high surface areas of N-PCNPs and MWCNTs, the simultaneous determination of hydroquinone (HQ), catechol (CC) and resorcinol (RE) with good analytical performance was achieved at the N-PCNPs-MWCNTs modified electrode. The linear response ranges for HQ, CC and RE are 0.2-455 ${\mu}M$, 0.7-440 ${\mu}M$ and 3.0-365 ${\mu}M$, respectively, and the detection limits (S/N = 3) are $0.03{\mu}M$, $0.11{\mu}M$ and $0.38{\mu}M$, respectively. These results are much better than that obtained on some graphene or CNTs-based materials modified electrodes. Furthermore, the developed sensor was successfully applied to simultaneously detect HQ, CC and RE in the local river water samples.

• Structural Engineering and Mechanics
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• v.41 no.5
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• pp.663-673
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• 2012

A number of mode shape-based structure damage identification methods have been verified by numerical simulations or experiments for on-line structure health monitoring (SHM). However, many of them need a baseline mode shape generated by the healthy structure serving as a reference to identify damages. Otherwise these methods can hardly perform well when multiple cracks conditions occur. So it is important to solve the problems above. By aid of the fractal dimension method (FD), Qiao and Wang proposed a generalized fractal dimension (GFD) to detect the delamination damage. As a modification of GFD, Qiao and Cao proposed the approximate waveform capacity dimension (AWCD) technique to simplify the calculation of fractal and overcome the false peak appearing in the high mode shapes. Based on their valued work, this paper combined and applied the AWCD method and curvature mode shape data to detect multiple damages in beam. In the end, the identification properties of the AWCD for multiple damages have been verified by groups of Monte Carlo simulations and experiments.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1016-1026
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• 2017

An adaptive extended Kalman filter based on the maximum likelihood (EKF-ML) is proposed for detecting voltage sag in this paper. Considering that the choice of the process and measurement error covariance matrices affects seriously the performance of the extended Kalman filter (EKF), the EKF-ML method uses the maximum likelihood method to adaptively optimize the error covariance matrices and the initial conditions. This can ensure that the EKF has better accuracy and faster convergence for estimating the voltage amplitude (states). Moreover, without more complexity, the EKF-ML algorithm is almost as simple as the conventional EKF, but it has better anti-disturbance performance and more accuracy in detection of the voltage sag. More importantly, the EKF-ML algorithm is capable of accurately estimating the noise parameters and is robust against various noise levels. Simulation results show that the proposed method performs with a fast dynamic and tracking response, when voltage signals contain harmonics or a pulse and are jointly embedded in an unknown measurement noise.

• Journal of the Korean Physical Society
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• v.73 no.11
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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%.

• Animal Bioscience
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• v.34 no.9
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• pp.1532-1543
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• 2021

Objective: This study was aimed to establish a quantitative detection method for meat contamination based on specific polypeptides. Methods: Thermally stable peptides with good responses were screened by high resolution liquid chromatography tandem mass spectrometry. Standard curves of specific polypeptide were established by triple quadrupole mass spectrometry. Finally, the adulteration of commercial samples was detected according to the standard curve. Results: Fifteen thermally stable peptides with good responses were screened. The selected specific peptides can be detected stably in raw meat and deep processed meat with the detection limit up to 1% and have a good linear relationship with the corresponding muscle composition. Conclusion: This method can be effectively used for quantitative analysis of commercial samples.

• Annual Conference of KIPS
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• 2008.05a
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• pp.1116-1119
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• 2008

무선 센서 네트워크는 주변 정보를 감지할 수 있는 다수의 센서들로 구성된 네트워크로 다양한 분야에서 활용되고 있다. 과거에는 무선 센서 네트워크 환경에서 각 센서들 간의 비밀통신이 중요한 이슈였으며, 특히 이를 위한 키 관리 기법들이 주요 연구방향이었다. 하지만 잘 분배되고 관리된 키라 할지라도, 공격자에 의해 특정한 센서 노드(node)가 수집되면, 노출된 노드(compromised node)가 가지고 있는 키가 공격자에게 들어나게 된다. 노출된 공유키(shared key)를 통해 노출되지 않은 정상 노드(non-compromised node) 사이의 대칭키(pairwise key)를 얻을 수 있으며 결국 공격자는 네트워크에 심각한 영향을 줄 수 있는 메시지 삽입 및 수정 공격을 감행할 수 있다. 본 논문에서는 이와 같은 공격을 탐지하고 오용된 키(misused key)를 폐기하기 위한 방법으로 DAC(detection at cluster header) 기법을 제안한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.675-686
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• 2005

In this paper, we propose an efficient face region detection technique for the content-based video summarization. To segment video, shot changes are detected from a video sequence and key frames are selected from the shots. We select one frame that has the least difference between neighboring frames in each shot. The proposed face detection algorithm detects face region from selected key frames. And then, we provide user with summarized frames included face region that has an important meaning in dramas or movies. Using Bayes classification rule and statistical characteristic of the skin pixels, face regions are detected in the frames. After skin detection, we adopt the projection method to segment an image(frame) into face region and non-face region. The segmented regions are candidates of the face object and they include many false detected regions. So, we design a classifier to minimize false lesion using CART. From SGLD matrices, we extract the textual feature values such as Inertial, Inverse Difference, and Correlation. As a result of our experiment, proposed face detection algorithm shows a good performance for the key frames with a complex and variant background. And our system provides key frames included the face region for user as video summarized information.