• 제목/요약/키워드: parameter detection

검색결과 823건 처리시간 0.026초

심전도 자동진단을 위한 P파 검출기법의 연구 (A Study on Detection of P-wave for Automated Electrocardiogram Interpreter)

  • 석정욱;권혁제;공인욱;이명호
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1995년도 추계학술대회
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    • pp.201-204
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    • 1995
  • In this study, we proposed an algorithm for P-wave detection. It is essential to decide the existence of P-wave and to extract some parameter about P-wave in automated ECG interpreter. Especially this paper describes the detection and estimation of three case, artrial flutter, coupled and non-coupled, which are very crucial things in ECG diagnosis. The performance of algorithm is showed by applying it to CSE(Common Standards for Quantative Electrocardiography) database.

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예인형 수동소나에 적합한 전방위 표적 자동탐지 및 추적기법 성능 분석 (Performance Analysis of Omni-Directional Automatic Target Detection and Tracking for a Towed Array Passive Sonar System)

  • 서익수
    • 한국군사과학기술학회지
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    • 제9권3호
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    • pp.33-40
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    • 2006
  • In towed array passive sonar system, sonar operators cannot detect and track the all targets simultaneously in the omni-directional area by just Operator Initiated Tracking(OIT). In this paper, omni-directional automatic target detection and tracking algorithm is described and optimize the parameters through ocean data to overcome the drawbacks of OITs. The algorithm is verified through sea trials with submarines.

무한원점을 이용한 주행방향 추정과 장애물 검출 (The course estimation of vehicle using vanishing point and obstacle detection)

  • 정준익;최성구;노도환
    • 전자공학회논문지S
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    • 제34S권11호
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    • pp.126-137
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    • 1997
  • This paper describes the algorithm which can estimate road following direction and deetect obstacle using a monocular vision system. This algorithm can estimate the course of vehicle using the vanishing point properties and detect obstacle by statistical method. The proposed algorithm is composed of four steps, which are lane prediction, lane extraction, road following parameter estimation and obstacle detection. It is designed for high processing speed and high accuracy. The former is achieved by a small area named sub-windown in lane existence area, the later is realized by using connected edge points of lane. We would like to present that the new mehod can detect obstacle using the simple statistical method. The paracticalities of the processing speed, the accuracy of the algorithm and proposing obstacle detection method, have been justified through the experiment applied VTR image of the real road to the algorithm.

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Bidirectional Artificial Neural Networks for Mobile-Phone Fraud Detection

  • Krenker, Andrej;Volk, Mojca;Sedlar, Urban;Bester, Janez;Kos, Andrej
    • ETRI Journal
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    • 제31권1호
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    • pp.92-94
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    • 2009
  • We propose a system for mobile-phone fraud detection based on a bidirectional artificial neural network (bi-ANN). The key advantage of such a system is the ability to detect fraud not only by offline processing of call detail records (CDR), but also in real time. The core of the system is a bi-ANN that predicts the behavior of individual mobile-phone users. We determined that the bi-ANN is capable of predicting complex time series (Call_Duration parameter) that are stored in the CDR.

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BB-BC optimization algorithm for structural damage detection using measured acceleration responses

  • Huang, J.L.;Lu, Z.R.
    • Structural Engineering and Mechanics
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    • 제64권3호
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    • pp.353-360
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    • 2017
  • This study presents the Big Bang and Big Crunch (BB-BC) optimization algorithm for detection of structure damage in large severity. Local damage is represented by a perturbation in the elemental stiffness parameter of the structural finite element model. A nonlinear objective function is established by minimizing the discrepancies between the measured and calculated acceleration responses (AR) of the structure. The BB-BC algorithm is utilized to solve the objective function, which can localize the damage position and obtain the severity of the damage efficiently. Numerical simulations have been conducted to identify both single and multiple structural damages for beam, plate and European Space Agency Structures. The present approach gives accurate identification results with artificial measurement noise.

Fault Detection in the Semiconductor Etch Process Using the Seasonal Autoregressive Integrated Moving Average Modeling

  • Arshad, Muhammad Zeeshan;Nawaz, Javeria Muhammad;Hong, Sang Jeen
    • Journal of Information Processing Systems
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    • 제10권3호
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    • pp.429-442
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    • 2014
  • In this paper, we investigated the use of seasonal autoregressive integrated moving average (SARIMA) time series models for fault detection in semiconductor etch equipment data. The derivative dynamic time warping algorithm was employed for the synchronization of data. The models were generated using a set of data from healthy runs, and the established models were compared with the experimental runs to find the faulty runs. It has been shown that the SARIMA modeling for this data can detect faults in the etch tool data from the semiconductor industry with an accuracy of 80% and 90% using the parameter-wise error computation and the step-wise error computation, respectively. We found that SARIMA is useful to detect incipient faults in semiconductor fabrication.

태양전지 실리콘 웨이퍼에서의 레일리기준 기반 레이저산란 패턴 분석 및 결함 검출 (Investigation of Laser Scattering Pattern and Defect Detection Based on Rayleigh Criterion for Crystalline Silicon Wafer Used in Solar Cell)

  • 연정승;김경범
    • 한국정밀공학회지
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    • 제28권5호
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    • pp.606-613
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    • 2011
  • In this paper, patterns of laser scattering and detection of micro defects have been investigated based on Rayleigh criterion for silicon wafer in solar cell. Also, a new laser scattering mechanism is designed using characteristics of light scattering against silicon wafer surfaces. Its parameters are to be optimally selected to obtain effective and featured patterns of laser scattering. The optimal parametric ranges of laser scattering are determined using the mean intensity of laser scattering. Scattering patterns of micro defects are investigated at the extracted parameter region. Among a lot of pattern features, both maximum connected area and number of connected component in patterns of laser scattering are regarded as the important information for detecting micro defects. Their usefulness is verified in the experiment.

차선변이 함수 기반의 선행차량 인식 알고리즘 (Stereo Image Processing Algorithm to Preceding Vehicle Detection Based on DLI)

  • 황희정;백광렬;이운근
    • 대한전기학회논문지:시스템및제어부문D
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    • 제53권7호
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    • pp.509-516
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    • 2004
  • This paper proposes an image processing algorithm for detecting obstacles on road using DLI(disparity of lane-related information) that is generated by stereo images acquired from dual cameras mounted on a moving vehicle. The DLI is a disparity that is acquired using a single lane information from road lane detection. For the purpose to reduce processing time, we use small block of edge-histogram based blocking logic. This algorithm detects moving objects such as preceding vehicles and obstacles. The proposed algorithm has been implemented in a personal computer with the road image data of a typical highway. We successfully performed experiments under a wide variety of road conditions without changing parameter values or adding human intervention. Experimental results also showed that the proposed DLI is quite successful.

비등방 확산 필터의 최적조건 선정을 통한 태양전지 실리콘 웨이퍼의 마이크로 크랙 검출 (Micro-crack Detection in Silicon Solar Wafer through Optimal Parameter Selection in Anisotropic Diffusion Filter)

  • 서형준;김경범
    • 반도체디스플레이기술학회지
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    • 제13권3호
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    • pp.61-67
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    • 2014
  • Micro-cracks in crystalline silicon wafer often result in wafer breakage in solar wafer manufacturing, and also their existence may lead to electrical failure in post fabrication inspection. Therefore, the reliable detection of micro-cracks is of importance in the photovoltaic industry. In this paper, an experimental method to select optimal parameters in anisotropic diffusion filter is proposed. It can reliably detect micro-cracks by the distinct extension of boundary as well as noise reduction in near-infrared image patterns of micro-cracks. Its performance is verified by experiments of several type cracks machined.

웨이블렛 패킷 변환과 Teager 에너지를 이용한 잡음 환경에서의 단일 채널 음성 판별 (A Single Channel Voice Activity Detection for Noisy Environments Using Wavelet Packet Decomposition and Teager Energy)

  • 구본응
    • 한국음향학회지
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    • 제33권2호
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    • pp.139-145
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    • 2014
  • 본 논문에서는 WPD (Wavelet Packet Decomposition) 계수에 Teager 에너지를 적용한 특징 계수를 임계값 알고리듬에 적용하여 잡음에 강인한 VAD 알고리듬을 제안하였다. 임계값은 비음성 구간의 평균과 표준편차를 추산하여 설정하였다. TIMIT 음성과 NOISEX 잡음 데이터베이스를 사용한 실험 결과, 제안된 알고리듬이 기존의 대표적인 비교 대상 알고리듬보다 우수함을 보였다. 정확도는 SNR 10 dB부터 -10 dB까지 ROC (Receiver Operating Characteristics) 곡선을 사용하여 비교하였다.