• 제목/요약/키워드: Electronic detection

검색결과 2,318건 처리시간 0.031초

A New Vehicle Detection Method based on Color Integral Histogram

  • Hwang, Jae-Pil;Ryu, Kyung-Jin;Park, Seong-Keun;Kim, Eun-Tai;Kang, Hyung-Jin
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제8권4호
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    • pp.248-253
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    • 2008
  • In this paper, a novel vehicle detection algorithm is proposed that utilizes the color histogram of the image. The color histogram is used to search the image for regions with shadow, block symmetry, and block non-homogeneity, thereby detecting the vehicle region. First, an integral histogram of the input image is computed to decrease the amount of required computation time for the block color histograms. Then, shadow detection is performed and the block symmetry and block non-homogeneity are checked in a cascade manner to detect the vehicle in the image. Finally, the proposed scheme is applied to both still images taken in a parking lot and an on-road video sequence to demonstrate its effectiveness.

Fault Detection in Semiconductor Manufacturing Using Statistical Method

  • Lim, Woo-Yup;Jeon, Sung-Ik;Han, Seung-Soo;Soh, Dae-Wha;Hong, Sang-Jeen
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2009년도 추계학술대회 논문집
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    • pp.44-44
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    • 2009
  • Fault detection is necessary for yield enhancement and cost reduction in semiconductor manufacturing. Sensory data acquired from the semiconductor processing tool is too large to analyze for the purpose of fault detection and classification(FDC). We studied the techniques of fault detection using statistical method. Multiple regression analysis smoothly detected faults and can be easy made a model. For real-time and fast computing time, the huge data was analyzed by each step. We also considered interaction and critical factors in tool parameters and process.

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Performance Comparison of Coherent and Non-Coherent Detection Schemes in LR-UWB System

  • Kwon, Soonkoo;Ji, Sinae;Kim, Jaeseok
    • Journal of Communications and Networks
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    • 제14권5호
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    • pp.518-523
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    • 2012
  • This paper presents new coherent and non-coherent detection methods for the IEEE 802.15.4a low-rate ultra-wideband physical layer with forward error correction (FEC) coding techniques. The coherent detection method involving channel estimation is based on the correlation characteristics of the preamble signal. A coherent receiver uses novel iterated selective-rake (IT-SRAKE) to detect 2-bit data in a non-line-of-sight channel. The non-coherent detection method that does not involve channel estimation employs a 2-bit data detection scheme using modified transmitted reference pulse cluster (M-TRPC) methods. To compare the two schemes, we have designed an IT-SRAKE receiver and a MTRPC receiver using an IEEE 802.15.4a physical layer. Simulation results show the performance of IT-SRAKE is better than that of the M-TRPC by 3-9 dB.

Using machine learning for anomaly detection on a system-on-chip under gamma radiation

  • Eduardo Weber Wachter ;Server Kasap ;Sefki Kolozali ;Xiaojun Zhai ;Shoaib Ehsan;Klaus D. McDonald-Maier
    • Nuclear Engineering and Technology
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    • 제54권11호
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    • pp.3985-3995
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    • 2022
  • The emergence of new nanoscale technologies has imposed significant challenges to designing reliable electronic systems in radiation environments. A few types of radiation like Total Ionizing Dose (TID) can cause permanent damages on such nanoscale electronic devices, and current state-of-the-art technologies to tackle TID make use of expensive radiation-hardened devices. This paper focuses on a novel and different approach: using machine learning algorithms on consumer electronic level Field Programmable Gate Arrays (FPGAs) to tackle TID effects and monitor them to replace before they stop working. This condition has a research challenge to anticipate when the board results in a total failure due to TID effects. We observed internal measurements of FPGA boards under gamma radiation and used three different anomaly detection machine learning (ML) algorithms to detect anomalies in the sensor measurements in a gamma-radiated environment. The statistical results show a highly significant relationship between the gamma radiation exposure levels and the board measurements. Moreover, our anomaly detection results have shown that a One-Class SVM with Radial Basis Function Kernel has an average recall score of 0.95. Also, all anomalies can be detected before the boards are entirely inoperative, i.e. voltages drop to zero and confirmed with a sanity check.

레이더 시스템에서 레이더 단면적에 따른 탐지 거리 추정을 위한 코히런트 집적과 비 코히런트 집적에 대한 비교 (A Comparison on Coherent Integration and Non-coherent Integration to Estimate Detection Range about Radar Cross Section in Radar System)

  • 함성민;가관우;이관형
    • 한국정보전자통신기술학회논문지
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    • 제7권2호
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    • pp.100-105
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    • 2014
  • 본 논문에서는 레이더 시스템에서 탐지 거리 추정에 영향을 미치는 레이더 단면적의 크기에 대한 집적 방식을 비교 분석한다. 본 논문에서는 레이더 단면적의 크기에 따라 크기가 작을 경우 스웰링 케이스 1, 클 경우에는 스웰링 케이스 3의 탐지 확률을 레이더 방정식에 적용하여 탐지 거리를 추정하였다. 모의실험을 통해서 스웰링 케이스의 차이에 따른 코히런트 집적과 비 코히런트 방식을 비교 분석하였다. 모의실험을 통해서, 비 코히런트 집적 방식이 추정 거리가 가장 우수하였고 코히런트 집적 방식은 스웰링 케이스를 적용한 탐지 거리 추정에 적합하지 않음을 알 수 있었다.

Low-Complexity MIMO Detection Algorithm with Adaptive Interference Mitigation in DL MU-MIMO Systems with Quantization Error

  • Park, Jangyong;Kim, Minjoon;Kim, Hyunsub;Jung, Yunho;Kim, Jaeseok
    • Journal of Communications and Networks
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    • 제18권2호
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    • pp.210-217
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    • 2016
  • In this paper, we propose a low complexity multiple-input multiple-output (MIMO) detection algorithm with adaptive interference mitigation in downlink multiuser MIMO (DL MU-MIMO) systems with quantization error of the channel state information (CSI) feedback. In DL MU-MIMO systems using the imperfect precoding matrix caused by quantization error of the CSI feedback, the station receives the desired signal as well as the residual interference signal. Therefore, a complexMIMO detection algorithm with interference mitigation is required for mitigating the residual interference. To reduce the computational complexity, we propose a MIMO detection algorithm with adaptive interference mitigation. The proposed algorithm adaptively mitigates the residual interference by using the maximum likelihood detection (MLD) error criterion (MEC). We derive a theoretical MEC by using the MLD error condition and a practical MEC by approximating the theoretical MEC. In conclusion, the proposed algorithm adaptively performs interference mitigation when satisfying the practical MEC. Simulation results show that the proposed algorithm reduces the computational complexity and has the same performance, compared to the generalized sphere decoder, which always performs interference mitigation.

A Biologically Inspired New Hardware Fault Detection: immunotronic and Genetic Algorithm-Based Approach

  • Lee, Sanghyung;Kim, Euntai;Park, Mignon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제4권1호
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    • pp.7-11
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    • 2004
  • This paper proposes a new immunotronic approach for the fault detection in hardware. The suggested method is, inspired by biology and its implementation is based on genetic algorithm. Tolerance conditions in the immunotronic system for fault detection correspond to the antibodies in the biological immune system. A novel algorithm of generating tolerance conditions is suggested based on the principle of the antibody diversity and GA optimization is employed to select mature tolerance conditions in immunotronic fault detection system. The suggested method is applied to the fault detection for MCNC benchmark FSMs (finite state machines) and its effectiveness is demonstrated by the computer simulation.

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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Frequency Domain DTV Pilot Detection Based on the Bussgang Theorem for Cognitive Radio

  • Hwang, Sung Sue;Park, Dong Chan;Kim, Suk Chan
    • ETRI Journal
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    • 제35권4호
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    • pp.644-654
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    • 2013
  • In this paper, a signal detection scheme for cognitive radio (CR) based on the Bussgang theorem is proposed. The proposed scheme calculates the statistical difference between Gaussian noise and the primary user signal by applying the Bussgang theorem to the received signal. Therefore, the proposed scheme overcomes the noise uncertainty and gives scalable complexity according to the zero-memory nonlinear function for a mobile device. We also present the theoretical analysis on the detection threshold and the detection performance in the additive white Gaussian noise channel. The proposed detection scheme is evaluated by computer simulations based on the IEEE 802.22 standard for the wireless regional area network. Our results show that the proposed scheme is robust to the noise uncertainty and works well in a very low signal-to-noise ratio.

LSTM Autoencoder를 활용한 전동기 이상 탐지 (Motor Anomaly Detection Using LSTM Autoencoder)

  • 박준석;하유진;유재천
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2023년도 제67차 동계학술대회논문집 31권1호
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    • pp.307-309
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    • 2023
  • 본 논문에서는 LSTM Autoencoder를 활용한 전동기의 Anomaly Detection을 제안한다. 전동기의 Anomaly Detection를 통해 전동킥보드의 고장을 예방하여 이용자의 안전을 보장한다. 전동기로부터 얻은 시계열 진동 데이터와 시계열 데이터 분석에 유의미한 LSTM을 활용한 Autoencoder를 통해 Anomaly Detection을 구현했다. 그 결과 99.9%의 정확도를 기록하였다.

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