• 제목/요약/키워드: detection theory

검색결과 507건 처리시간 0.028초

압전 수정 결정 미량 천평[PZ QCM] 바이오센서의 원리와 응용 (The Theory and Application or Piezoelectric Quartz Crystal Microbalance[PZ QCM] for Biosensor)

  • 김의락
    • KSBB Journal
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    • 제18권2호
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    • pp.79-89
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    • 2003
  • This article contains an overview of acoustic wave devices, the theory and application of piezoelectric quartz crystal microbalances(PZ QCM), clinical analysis, gas phase detection, DNA biosensors, drug analysis, food microbial analysis and environmental analysis.

Transfer matrix formulations and single variable shear deformation theory for crack detection in beam-like structures

  • Bozyigit, Baran;Yesilce, Yusuf;Wahab, Magd Abdel
    • Structural Engineering and Mechanics
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    • 제73권2호
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    • pp.109-121
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    • 2020
  • This study aims to estimate crack location and crack length in damaged beam structures using transfer matrix formulations, which are based on analytical solutions of governing equations of motion. A single variable shear deformation theory (SVSDT) that considers parabolic shear stress distribution along beam cross-section is used, as well as, Timoshenko beam theory (TBT). The cracks are modelled using massless rotational springs that divide beams into segments. In the forward problem, natural frequencies of intact and cracked beam models are calculated for different crack length and location combinations. In the inverse approach, which is the main concern of this paper, the natural frequency values obtained from experimental studies, finite element simulations and analytical solutions are used for crack identification via plots of rotational spring flexibilities against crack location. The estimated crack length and crack location values are tabulated with actual data. Three different beam models that have free-free, fixed-free and simple-simple boundary conditions are considered in the numerical analyses.

환경방사능 측정에서의 검출한계치의 정량적 고찰 및 최소검출방사능 농도 계산 (Determination of Minimum Detectable Activity in Environmental Samples)

  • 이명호;신현상;홍광희;조영현;이창우
    • Journal of Radiation Protection and Research
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    • 제24권3호
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    • pp.171-184
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    • 1999
  • 본 논문에서는 저준위 환경방사능 측정시 이용되는 검출한계에 대한 기본개념 및 수식을 통계학적 이론을 기초로 서술하였다. 방사능을 정확하게 검출할 신뢰도를 95%로 설정하여 알파 베타 및 감마선 측정기에 대한 검출한계치값을 계산하였다. 또한 환경 방사능 계측에 많이 사용되는 방사능 핵종에 대해 최소 검출 방사능 농도값을 검출한계치 개념을 근거로 계산하여 저준위 환경 방사능 분석시 환경방사능 측정결과에 대한 신뢰도 평가에 활용 가능 하도록 하였다.

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저수준 시각적 특질이 위협 탐지에 미치는 효과: 뱀 탐지 이론의 검증 (Effects of Low-Level Visual Attributes on Threat Detection: Testing the Snake Detection Theory)

  • 김태훈;권다솜;이도준
    • 감성과학
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    • 제23권3호
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    • pp.47-62
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    • 2020
  • 뱀 탐지 이론은 영장류가 천적인 뱀과 경쟁하면서 뱀을 효과적으로 탐지할 수 있는 시각 체계를 갖추게 되었다고 설명한다. 구체적인 가설 중 하나는 먼지세포 중심의 피질하 시각 경로가 사람으로 하여금 심적 자원을 사용하지 않고서도 자동적으로 뱀의 위협을 탐지할 수 있게 한다는 것이다. 이에 본 연구는 뱀 영상에 대한 인간 참가자의 반응을 공포 표정의 얼굴 및 꽃에 대한 반응과 비교함으로써 뱀 탐지 이론의 가정들을 검토하였다. 참가자들은 원본 영상을 관찰하거나, 원본 영상에서 색상, 밝기와 대비, 공간주파수 에너지 차이를 제거한 변환 영상을 관찰하였다. 실험 1의 참가자들은 각 영상에 대한 정서가와 각성 유발 정도를 평정하였고, 실험 2의 참가자들은 연속점멸억제 절차에서 표적 자극을 탐지하였다. 그 결과, 뱀에 대한 반응은 시각 요인의 영향을 가장 크게 받았다. 영상들의 시각적 차이를 제거했을 때, 뱀 영상은 덜 부정적이고 각성을 덜 유발하며 연속점멸억제에서 느리게 탈출하였다. 그에 비해, 다른 범주에 대한 반응은 영상 변환의 영향을 덜 받았다. 특히, 공포 표정의 얼굴은 일관적으로 영상 조건에 상관없이 위협적인 대상으로 평정되었으며 빠르게 탐지되었다. 또한, 실험 1에서 측정한 각성 평정의 변화량과 실험 2에서 측정한 연속점멸억제 탈출 시간의 변화량이 부적 상관을 보였다. 영상 변환 후 각성 평정 점수가 많이 감소한 뱀 영상일수록 탐지반응시간이 증가하였다. 이러한 결과는 뱀이 인간 관찰자의 위협 탐지 반응에 미치는 영향이 공포 표정의 얼굴에 비해 제한적이며, 연속점멸억제 탈출 반응과 의식적 평정 반응이 처리 기제를 공유할 가능성을 시사한다. 결론적으로 본 연구는 인간의 뱀 탐지가 무의식적 피질하 시각 경로의 산물이라는 가정에 의문을 제기한다.

Nonparaxial Imaging Theory for Differential Phase Contrast Imaging

  • Jeongmin Kim
    • Current Optics and Photonics
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    • 제7권5호
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    • pp.537-544
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    • 2023
  • Differential phase contrast (DPC) microscopy, a central quantitative phase imaging (QPI) technique in cell biology, facilitates label-free, real-time monitoring of intrinsic optical phase variations in biological samples. The existing DPC imaging theory, while important for QPI, is grounded in paraxial diffraction theory. However, this theory lacks accuracy when applied to high numerical aperture (NA) systems that are vital for high-resolution cellular studies. To tackle this limitation, we have, for the first time, formulated a nonparaxial DPC imaging equation with a transmission cross-coefficient (TCC) for high NA DPC microscopy. Our theoretical framework incorporates the apodization of the high NA objective lens, nonparaxial light propagation, and the angular distribution of source intensity or detector sensitivity. Thus, our TCC model deviates significantly from traditional paraxial TCCs, influenced by both NA and the angular variation of illumination or detection. Our nonparaxial imaging theory could enhance phase retrieval accuracy in QPI based on high NA DPC imaging.

Human Detection 을 위한 Bayesian Logistic Regression (Bayesian Logistic Regression for Human Detection)

  • ;;이칠우
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2008년도 학술대회 1부
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    • pp.569-572
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    • 2008
  • The possibility to extent the solution in human detection problem for plug-in on vision-based Human Computer Interaction domain is very attractive, since the successful of the machine leaning theory and computer vision marriage. Bayesian logistic regression is a powerful classifier performing sparseness and high accuracy. The difficulties of finding people in an image will be conquered by implementing this Bavesian model as classifier. The comparison with other massive classifier e.g. SVM and RVM will introduce acceptance of this method for human detection problem. Our experimental results show the good performance of Bavesian logistic regression in human detection problem, both in trade-off curves (ROC, DET) and real-implementation compare to SVM and RVM.

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태양광 발전 시스템을 위한 유비쿼터스 네트워킹 기반 지능형 모니터링 및 고장진단 기술 (Ubiquitous Networking based Intelligent Monitoring and Fault Diagnosis Approach for Photovoltaic Generator Systems)

  • 조현철;심광열
    • 전기학회논문지
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    • 제59권9호
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    • pp.1673-1679
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    • 2010
  • A photovoltaic (PV) generator is significantly regarded as one important alternative of renewable energy systems recently. Fault detection and diagnosis of engineering dynamic systems is a fundamental issue to timely prevent unexpected damages in industry fields. This paper presents an intelligent monitoring approach and fault detection technique for PV generator systems by means of artificial neural network and statistical signal detection theory. We devise a multi-Fourier neural network model for representing dynamics of PV systems and apply a general likelihood ratio test (GLRT) approach for investigating our decision making algorithm in fault detection and diagnosis. We make use of a test-bed of ubiquitous sensor network (USN) based PV monitoring systems for testing our proposed fault detection methodology. Lastly, a real-time experiment is accomplished for demonstrating its reliability and practicability.

Adaptive Watermark Detection Algorithm Using Perceptual Model and Statistical Decision Method Based on Multiwavelet Transform

  • Hwang Eui-Chang;Kim Dong Kyue;Moon Kwang-Seok;Kwon Ki-Ryong
    • 한국멀티미디어학회논문지
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    • 제8권6호
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    • pp.783-789
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    • 2005
  • This paper is proposed a watermarking technique for copyright protection of multimedia contents. We proposed adaptive watermark detection algorithm using stochastic perceptual model and statistical decision method in DMWT(discrete multi wavelet transform) domain. The stochastic perceptual model calculates NVF(noise visibility function) based on statistical characteristic in the DMWT. Watermark detection algorithm used the likelihood ratio depend on Bayes' decision theory by reliable detection measure and Neyman-Pearson criterion. To reduce visual artifact of image, in this paper, adaptively decide the embedding number of watermark based on DMWT, and then the watermark embedding strength differently at edge and texture region and flat region embedded when watermark embedding minimize distortion of image. In experiment results, the proposed statistical decision method based on multiwavelet domain could decide watermark detection.

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Robust Entropy Based Voice Activity Detection Using Parameter Reconstruction in Noisy Environment

  • Han, Hag-Yong;Lee, Kwang-Seok;Koh, Si-Young;Hur, Kang-In
    • Journal of information and communication convergence engineering
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    • 제1권4호
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    • pp.205-208
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    • 2003
  • Voice activity detection is a important problem in the speech recognition and speech communication. This paper introduces new feature parameter which are reconstructed by spectral entropy of information theory for robust voice activity detection in the noise environment, then analyzes and compares it with energy method of voice activity detection and performance. In experiments, we confirmed that spectral entropy and its reconstructed parameter are superior than the energy method for robust voice activity detection in the various noise environment.