• Title/Summary/Keyword: Detection probability

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Modeling and Design of a Distributed Detection System Based on Active Sonar Sensor Networks (능동 소나망 분산탐지 체계의 모델링 및 설계)

  • Choi, Won-Yong;Kim, Song-Geun;Hong, Sun-Mog
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.1
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    • pp.123-131
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    • 2011
  • In this paper, modeling and design of a distributed detection system are considered for an active sonar sensor network. The sensor network has a parallel configuration and it consists of a fusion center and a set of receiver nodes. A system with two receiver nodes is considered to investigate a theoretical aspect of design. To be specific, AND rule and OR rule are considered as the fusion rules of the sensor network. For the fusion rules, it is shown that a threshold rule of each sensor node has uniformly most powerful properties. Optimum threshold for each sensor is obtained that maximizes the probability of detection given probability of false alarm. Numerical experiments were also performed to investigate the detection characteristics of a distributed detection system with multiple sensor nodes. The experimental results show how signal strength, false alarm probability, and the distance between nodes in a sensor field affect the system detection performances.

Probabilistic structural damage detection approaches based on structural dynamic response moments

  • Lei, Ying;Yang, Ning;Xia, Dandan
    • Smart Structures and Systems
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    • v.20 no.2
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    • pp.207-217
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    • 2017
  • Because of the inevitable uncertainties such as structural parameters, external excitations and measurement noises, the effects of uncertainties should be taken into consideration in structural damage detection. In this paper, two probabilistic structural damage detection approaches are proposed to account for the underlying uncertainties in structural parameters and external excitation. The first approach adopts the statistical moment-based structural damage detection (SMBDD) algorithm together with the sensitivity analysis of the damage vector to the uncertain parameters. The approach takes the advantage of the strength SMBDD, so it is robust to measurement noise. However, it requests the number of measured responses is not less than that of unknown structural parameters. To reduce the number of measurements requested by the SMBDD algorithm, another probabilistic structural damage detection approach is proposed. It is based on the integration of structural damage detection using temporal moments in each time segment of measured response time history with the sensitivity analysis of the damage vector to the uncertain parameters. In both approaches, probability distribution of damage vector is estimated from those of uncertain parameters based on stochastic finite element model updating and probabilistic propagation. By comparing the two probability distribution characteristics for the undamaged and damaged models, probability of damage existence and damage extent at structural element level can be detected. Some numerical examples are used to demonstrate the performances of the two proposed approaches, respectively.

Fault Detection and Diagnosis Systems of Induction Machines using Real-Time Stochastic Modeling Approach (실시간 확률 모델링 기법을 이용한 유도기기의 고장검출 및 진단시스템)

  • Lee, Jin-Woo;Kim, Kwang-Soo;Cho, Hyun-Cheol;Lee, Young-Jin;Lee, Kwon-Soon
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.58 no.3
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    • pp.241-248
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    • 2009
  • This paper presents stochastic methodology based fault detection algorithm for induction motor systems. We measure current of healthy induction motors by means of hall sensor systems and then establish its probability distribution. We propose online probability density estimation which is effective in real-time implementation due to its simplicity and low computational burden. In addition, we accomplish theoretical analysis of the proposed estimation to demonstrate its convergence property by using statistical convergence and system stability theories. We apply our fault detection approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.

Detection of Changes of Mean Nonconformities per Unit in the u Control Chart (u 관리도에서 단위당결점수 변화 탐지)

  • Chang, Kyung;Yang, Moon-Hee
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.20 no.43
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    • pp.205-209
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    • 1997
  • One objective of the u control chart is to detect changes of mean nonconformities per unit occurred owing to various causes. This paper shows the detection probability using the Poisson distribution for various parameters, that is, subsample size n, mean nonconformities per unit $u_o$, and $u_o's$ change ratio k. We find that (1) as $u_o$ increases the smaller n is required for the same detection probability and the same change ratio; (2) as k gets away from 1 the smaller n is required; (3) the bigger n is required for the bigger detection probability. Several tables are given from our findings and are hoped to be used as guidelines for u chart users.

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Optimal Numbers of Repeat Inspections with Decreasing Detection Probability

  • Kim, S.B.;Bai, D.S.
    • Journal of Korean Institute of Industrial Engineers
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    • v.11 no.2
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    • pp.19-27
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    • 1985
  • Optimal numbers of repeat inspections are obtained for a single inspector who has a fixed probability of detecting a nonconforming item on each inspection and will continue to inspect until further inspection is not warranted when comparing the expected increase of total gain with the inspection cost. It is assumed that the detection probability decreases as the number of repeat inspections increases, and that the lot to be inspected contains an unknown but Poisson distributed number of nonconforming items.

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Lips Detection by Probability Map Based Genetic Algorithm (확률맵 기반 유전자 알고리즘에 의한 입술영역 검출)

  • Hwang Dong-Guk;Kim Tae-Ick;Park Cheon-Joo;Jun Byung-Min;Park Hee-Jung
    • The Journal of the Korea Contents Association
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    • v.4 no.4
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    • pp.79-87
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    • 2004
  • In this paper, we propose a probability map based genetic algorithm to detect lips from portrait image. The existing genetic algorithm used to get an optimal solution is modified in order to get multiple optimal solutions for lips detection. Each individual consists of two chromosomes to represent coordinates x, y in space. Also the algorithm introduce a preserving zone in the population, a modified uniform crossover, a selection without individual duplication. Using probability map of H, 5 components, the proposed algorithm has adaptability in the segmentation of objects with similar colors. In experiments, we analyzed relationships of primary parameters and found that the algorithm can apply to the detection of other ROIs easily

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Hybrid Iterative Detection Algorithm for MIMO Systems (다중 안테나 시스템을 위한 Hybrid Iterative 검출 기법)

  • Kim, Sang-Heon;Shin, Myeong-Cheol;Kim, Kyeong-Yeon;Lee, Chung-Yong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.4 s.316
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    • pp.117-122
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    • 2007
  • For multiple antenna systems, we consider the hybrid iterative detection of the maximum a posteriori probability(MAP) detection and the linear detection such as the minimum-mean-square-error(MMSE) filtering with soft cancelation. We devise methods to obtain both the lower complexity of the linear detection and the superior performance of the MAP detection. Using the a prior probability of the coded bit which is extrinsic of the outer decoder, we compute the threshold of grouping and determine the detection scheme symbol by symbol. Through the simulation results, it is shown that the proposed receiver obtains the superior performance to the MMSE detector and the lower complexity than the MAP detector.

SPRT-based Collaboration Construction for Malware Detection in IoT

  • Jun-Won Ho
    • International journal of advanced smart convergence
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    • v.12 no.1
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    • pp.64-69
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    • 2023
  • We devise a collaboration construction method based on the SPRT (Sequential Probability Ratio Test) for malware detection in IoT. In our method, high-end IoT nodes having capable of detecting malware and generating malware signatures harness the SPRT to give a reward of malware signatures to low-end IoT nodes providing useful data for malware detection in IoT. We evaluate our proposed method through simulation. Our simulation results indicate that the number of malware signatures provided for collaboration is varied in accordance with the threshold for fraction of useful data.

The Human Performance Degradation in Vigilance due to Prolonged and Monotonous Tasks (경계(警戒) 임무(任務) 담당자(擔當者)의 시간지연(時間遲延)에 따르는 인간(人間) 성능(性能)의 변화(變化)에 대(對)한 연구(硏究) 및 개선방안(改善方案))

  • Myun-Woo,Lee
    • Bulletin of the Society of Naval Architects of Korea
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    • v.11 no.1
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    • pp.27-34
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    • 1974
  • This study is aimed at a validation of the vigilance simulation model which was proposed earlier (2). The model estimates a perceived danger value, an alertness level and the probability of detection at a given elapsed time of vigilance. Twenty-nine male and seven female subjects were given a simple task. They were asked to detect a number(four numbers out of six digits in the telephone directory which have the probability of occurrence in the range of 0.0010-0.0018) in six different experimental conditions, for periods of two to three hours. Analysis of the experiments showed that although the mean detection rate varied slightly in two hours, the within-subject variance and the number of cyclic performance fluctuations increased significantly. A primal factor that affects the performance seems to be the frequency of target occurrence. By curve fitting, the relation between the probability of detection and the percentages of danger event occurrence was derived; $y=0.50(1-{\varepsilon}^{-50x^2})+0.39$. Assuming the equation represents the normal detection rate(100% performance), the Relative Vigilance Performance Rating was calculated. This rating method could be a useful criterion in selecting and training of the vigilance personnel. The results show that the simulation model is a good estimator of human a performance when the probability of danger occurrence is greater than 0.0015; it gives a good reference for improving the vigilance system. Suggestions are made that (1) the validity of proposed functional equations over the extended range of danger probability be studied, (2) an analysis of the cyclic fluctuations of the alertness level be accomplished, and (3) the cost functions of detection reliability be included in any future model.

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Research on an Engagement Level Underwater Weapon System Model with Neyman-Pearson Detector (Neyman-Pearson 표적 탐지기를 적용한 수중 무기체계 교전수준 모델 개발 연구)

  • Cho, Hyunjin;Kim, Wan-Jin;Kim, Sanghun;Yang, Hocheol;Lee, Hee Kwang
    • Journal of the Korea Society for Simulation
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    • v.28 no.2
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    • pp.89-95
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    • 2019
  • This paper introduces the simulation concepts and technical approach of underwater weapon system performance analysis simulator, especially focused on probabilistic target detection concepts. We calculated the signal excess (SE) value using SONAR equation, then derived the probability density function(PDF) for target presence($H_1$) or absence($H_0$) cases, respectively. With the Neyman-Pearson detector criterion, we got the probability of detection($P_D$) while satisfying the given probability of false alarm($P_{FA}$). At every instance of simulation, target detection is decided in the probabilistic perspective. With the proposed detection implementation, we improved the model fidelity so that it could support the tactical decision during the operation.