• 제목/요약/키워드: Detection characteristics

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1.55 ${\mu}$m파장의 저광량을 검출을 위한 APD의 자이거 모드 특성 (Geiger-mode characteristics of avalanche photodiodes for low-light-level detection at 1.55 ${\mu}$m)

  • 장현주;황인각;최용석;이용희
    • 한국광학회:학술대회논문집
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    • 한국광학회 2004년도 제15회 정기총회 및 동계학술발표회
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    • pp.288-289
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    • 2004
  • The performance of the InGaAs/InP avalanche photodidodes operated in Geiger-mode was investigated for 1550nm wavelengths at room temperature. We find the optimal operating points where the high quantum detection efficiency and low dark current are achieved. For the optical pulse detection, the gated-mode is used to reduce the dark current.

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Language- Independent Sentence Boundary Detection with Automatic Feature Selection

  • Lee, Do-Gil
    • Journal of the Korean Data and Information Science Society
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    • 제19권4호
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    • pp.1297-1304
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    • 2008
  • This paper proposes a machine learning approach for language-independent sentence boundary detection. The proposed method requires no heuristic rules and language-specific features, such as part-of-speech information, a list of abbreviations or proper names. With only the language-independent features, we perform experiments on not only an inflectional language but also an agglutinative language, having fairly different characteristics (in this paper, English and Korean, respectively). In addition, we obtain good performances in both languages. We have also experimented with the methods under a wide range of experimental conditions, especially for the selection of useful features.

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Comparative Analysis of Detection Algorithms for Corner and Blob Features in Image Processing

  • Xiong, Xing;Choi, Byung-Jae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제13권4호
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    • pp.284-290
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    • 2013
  • Feature detection is very important to image processing area. In this paper we compare and analyze some characteristics of image processing algorithms for corner and blob feature detection. We also analyze the simulation results through image matching process. We show that how these algorithms work and how fast they execute. The simulation results are shown for helping us to select an algorithm or several algorithms extracting corner and blob feature.

대수수신계통의 탐색특성개선 (An Improvement in Detection Performance of Logarithmic Receiver)

  • 윤현보;장태무;조광래
    • 한국통신학회논문지
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    • 제9권1호
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    • pp.45-48
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    • 1984
  • A serious degradation of blocking of the detection performance in a cell aeraging-logarithmic detector/constant false alarm rate(CA-LOG/CFAR) is known to be caused by the presence of a large interfering noise in the set of sample mean. A technique consisting of the logarithmic circuit and inverter has been proposed to alleviate this problem, by modifying the conventional CA-LOG/CFAR receiver. The detection performance of the proposed technique is linearly improbed over the normal output level and the blocking characteristics of the CA-LOG/CFAR can be changed to finite output level.

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A Novel Abnormal Behavior Detection Framework to Maximize the Availability in Smart Grid

  • Shin, Incheol
    • 스마트미디어저널
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    • 제6권3호
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    • pp.95-102
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    • 2017
  • A large volume of research has been devoted to the development of security tools for protecting the Smart Grid systems, however the most of them have not taken the Availability, Integrity, Confidentiality (AIC) security triad model, not like CIA triad model in traditional Information Technology (IT) systems, into account the security measures for the electricity control systems. Thus, this study would propose a novel security framework, an abnormal behavior detection system, to maximize the availability of the control systems by considering a unique set of characteristics of the systems.

모바일 기기 진동의 인지적 특성 (Perceptual Characteristics of Mobile Device Vibrations)

  • 최승문
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2008년도 학술대회 3부
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    • pp.30-35
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    • 2008
  • 본 논문은 2008 한국 HCI 학회 중 개최되는 햅틱스 관련 연구 워크샵에 "모바일 기기 진동의 인지적 특성" 이라는 제목으로 발표하기 위하여, 포항공과대학교 햅틱스 및 가상현실 연구실에서 수행된 모바일 기기 진동 관련 연구를 주요 결과 중심으로 요약한 것이다. 모바일 기기에서 발생하는 진동의 물리적 특성, 절대 인지 역치, 인식 강도, 인지적으로 정확한 진동 효과를 유발하기 위한 렌더링 방법 등에 대해서 간략하게 서술한다.

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Damage detection using finite element model updating with an improved optimization algorithm

  • Xu, Yalan;Qian, Yu;Song, Gangbing;Guo, Kongming
    • Steel and Composite Structures
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    • 제19권1호
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    • pp.191-208
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    • 2015
  • The sensitivity-based finite element model updating method has received increasing attention in damage detection of structures based on measured modal parameters. Finding an optimization technique with high efficiency and fast convergence is one of the key issues for model updating-based damage detection. A new simple and computationally efficient optimization algorithm is proposed and applied to damage detection by using finite element model updating. The proposed method combines the Gauss-Newton method with region truncation of each iterative step, in which not only the constraints are introduced instead of penalty functions, but also the searching steps are restricted in a controlled region. The developed algorithm is illustrated by a numerically simulated 25-bar truss structure, and the results have been compared and verified with those obtained from the trust region method. In order to investigate the reliability of the proposed method in damage detection of structures, the influence of the uncertainties coming from measured modal parameters on the statistical characteristics of detection result is investigated by Monte-Carlo simulation, and the probability of damage detection is estimated using the probabilistic method.

Small Target Detection with Clutter Rejection using Stochastic Hypothesis Testing

  • Kang, Suk-Jong;Kim, Do-Jong;Ko, Jung-Ho;Bae, Hyeon-Deok
    • 한국멀티미디어학회논문지
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    • 제10권12호
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    • pp.1559-1565
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    • 2007
  • The many target-detection methods that use forward-looking infrared (FUR) images can deal with large targets measuring $70{\times}40$ pixels, utilizing their shape features. However, detection small targets is difficult because they are more obscure and there are many target-like objects. Therefore, few studies have examined how to detect small targets consisting of fewer than $30{\times}10$ pixels. This paper presents a small target detection method using clutter rejection with stochastic hypothesis testing for FLIR imagery. The proposed algorithm consists of two stages; detection and clutter rejection. In the detection stage, the mean of the input FLIR image is first removed and then the image is segmented using Otsu's method. A closing operation is also applied during the detection stage in order to merge any single targets detected separately. Then, the residual of the clutters is eliminated using statistical hypothesis testing based on the t-test. Several FLIR images are used to prove the performance of the proposed algorithm. The experimental results show that the proposed algorithm accurately detects small targets (Jess than $30{\times}10$ pixels) with a low false alarm rate compared to the center-surround difference method using the receiver operating characteristics (ROC) curve.

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