• Title/Summary/Keyword: Event detection

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A Study on Possibility of Red Tide Detection Using MODIS Data (MODIS Data를 이용한 GOCI의 적조 탐지 가능성에 대한 연구)

  • Kim, Yong-Min;Byun, Young-Gi;Song, Woo-Seok;Yu, Ki-Yun
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2007.04a
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    • pp.131-134
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    • 2007
  • In this paper, we evaluate a red tide detection possibility of GOCI(Geostationary Ocean Color Imager) which will be launched in 2008. To detect red tide, we use a similar wavelength range of MODIS normalized water-leaving radiance data instead of GOCI data. Supposed to GOCI, red tide detection algorithm is based on MRI(MODIS Red tide Index) and use 667nm band to filter turbid water. The algorithm's effectiveness is verified by detecting large Cochlodinium polykrikoides red tide event that was appeared in Korean coastal waters. The evaluation was done by comparing the result with the update data provided by the NFRDI.

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DWT-based Denoising and Power Quality Disturbance Detection

  • Ramzan, Muhammad;Choe, Sangho
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.5
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    • pp.330-339
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    • 2015
  • Power quality (PQ) problems are becoming a big issue, since delicate complex electronic devices are widely used. We present a new denoising technique using discrete wavelet transform (DWT), where a modified correlation thresholding is used in order to reliably detect the PQ disturbances. We consider various PQ disturbances on the basis of IEEE-1159 standard over noisy environments, including voltage swell, voltage sag, transient, harmonics, interrupt, and their combinations. These event signals are decomposed using DWT for the detection of disturbances. We then evaluate the PQ disturbance detection ratio of the proposed denoising scheme over Gaussian noise channels. Simulation results also show that the proposed scheme has an improved signal-to-noise ratio (SNR) over existing scheme.

Damage assessment of frame structure using quadratic time-frequency distributions

  • Chandra, Sabyasachi;Barai, S.V.
    • Structural Engineering and Mechanics
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    • v.49 no.3
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    • pp.411-425
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    • 2014
  • This paper presents the processing of nonlinear features associated with a damage event by quadratic time-frequency distributions for damage identification in a frame structure. A time-frequency distribution is a function which distributes the total energy of a signal at a particular time and frequency point. As the occurrence of damage often gives rise to non-stationary, nonlinear structural behavior, simultaneous representation of the dynamic response in the time-frequency plane offers valuable insight for damage detection. The applicability of the bilinear time-frequency distributions of the Cohen class is examined for the damage assessment of a frame structure from the simulated acceleration data. It is shown that the changes in instantaneous energy of the dynamic response could be a good damage indicator. Presence and location of damage can be identified using Choi-Williams distribution when damping is ignored. However, in the presence of damping the Page distribution is more effective and offers better readability for structural damage detection.

The Fault Diagnosis Method of Diesel Engines Using a Statistical Analysis Method (통계적 분석기법을 이용한 디젤기관의 고장진단 방법에 관한 연구)

  • Kim, Young-Il;Oh, Hyun-Kyung;Yu, Yung-Ho
    • Journal of Advanced Marine Engineering and Technology
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    • v.30 no.2
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    • pp.247-252
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    • 2006
  • Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn until signal is growing to abnormal state that the signal is over or under the set point. therefore cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without any additional sensors. By analyzing the data with high correlation coefficient(CC), correlation level of interactive data can be defined. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC. FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

Soft Fault Detection Using an Improved Mechanism in Wireless Sensor Networks

  • Montazeri, Mojtaba;Kiani, Rasoul
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.10
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    • pp.4774-4796
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    • 2018
  • Wireless sensor networks are composed of a large number of inexpensive and tiny sensors used in different areas including military, industry, agriculture, space, and environment. Fault tolerance, which is considered a challenging task in these networks, is defined as the ability of the system to offer an appropriate level of functionality in the event of failures. The present study proposed an intelligent throughput descent and distributed energy-efficient mechanism in order to improve fault tolerance of the system against soft and permanent faults. This mechanism includes determining the intelligent neighborhood radius threshold, the intelligent neighborhood nodes number threshold, customizing the base paper algorithm for distributed systems, redefining the base paper scenarios for failure detection procedure to predict network behavior when running into soft and permanent faults, and some cases have been described for handling failure exception procedures. The experimental results from simulation indicate that the proposed mechanism was able to improve network throughput, fault detection accuracy, reliability, and network lifetime with respect to the base paper.

Security Simulation with Collaboration of Intrusion Detection System and Firewall (침입 탐지 시스템과 침입 차단 시스템의 연동을 통한 보안 시뮬레이션)

  • 서희석;조대호
    • Journal of the Korea Society for Simulation
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    • v.10 no.1
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    • pp.83-92
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    • 2001
  • For the prevention of the network intrusion from damaging the system, both IDS (Intrusion Detection System) and Firewall are frequently applied. The collaboration of IDS and Firewall efficiently protects the network because of making up for the weak points in the each demerit. A model has been constructed based on the DEVS (Discrete Event system Specification) formalism for the simulation of the system that consists of IDS and Firewall. With this model we can simulation whether the intrusion detection, which is a core function of IDS, is effectively done under various different conditions. As intrusions become more sophisticated, it is beyond the scope of any one IDS to deal with them. Thus we placed multiple IDS agents in the network where the information helpful for detecting the intrusions is shared among these agents to cope effectively with attackers. If an agent detects intrusions, it transfers attacker's information to a Firewall. Using this mechanism attacker's packets detected by IDS can be prevented from damaging the network.

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The Fault Diagnosis Method of Diesel Engines Using a Statistical Analysis Method (통계적분석기법을 이용한 디젤기관의 고장진단 방법에 관한 연구)

  • Kim, Young-Il;Oh, Hyun-Gyeong;Cheon, Hang-Chun;Yu, Yung-Ho
    • Proceedings of the Korean Society of Marine Engineers Conference
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    • 2005.06a
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    • pp.281-286
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    • 2005
  • Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn while signal is growing to abnormal state until the signal is over or under the set point and cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without additional sensors. By analyzing this data having high correlation coefficient(CC), correlation level of interactive data can be understood. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC, FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

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Motion Tracking Algorithm for A CCTV System (CCTV 시스템을 위한 움직임 추적 기법)

  • Kang, Seoung-Il;Hong, Sung-Hoon
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.295-296
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    • 2006
  • This paper implements a method that tracking the moving objects that detected by the motion detection function of the digital CCTV system. We simply implement the motion detection function of the digital CCTV system that use frame difference and thresholding. When motion is detected, the motion detection function generates two outputs. One output is the event that the motion is arised in input image frame. The other output is coordinate that motion is exists. Then, do the block matching algorithm[2] using coordinate, that motion is exists, as initial coordinate of the block matching algorithm. The best matched coordinate is new initial coordinate of the block matching algorithm for the next image frame. We simply use the block matching algorithm that implements tracking the moving objects. It is simple, but useful the actual digital CCTV system.

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The detection and diagnosis model for small scale MSLB accident

  • Wang, Meng;Chen, Wenzhen
    • Nuclear Engineering and Technology
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    • v.53 no.10
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    • pp.3256-3263
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    • 2021
  • The main steam line break accident is an essential initiating event of the pressurized water reactor. In present work, the fuzzy set theory and the signal-based fault detection method has been used to detect the occurrence and diagnosis of the location and break area for the small scale MSLB. The models are validated by the AP1000 accident simulator based on MAAP5. From the test results it can be seen that the proposed approach has a rapid and proper response on accident detection and location diagnosis. The method proposed to evaluate the break area shows good performances for small scale MSLB with the relative deviation within ±3%.

A Kidnapping Detection Using Human Pose Estimation in Intelligent Video Surveillance Systems

  • Park, Ju Hyun;Song, KwangHo;Kim, Yoo-Sung
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.8
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    • pp.9-16
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    • 2018
  • In this paper, a kidnapping detection scheme in which human pose estimation is used to classify accurately between kidnapping cases and normal ones is proposed. To estimate human poses from input video, human's 10 joint information is extracted by OpenPose library. In addition to the features which are used in the previous study to represent the size change rates and the regularities of human activities, the human pose estimation features which are computed from the location of detected human's joints are used as the features to distinguish kidnapping situations from the normal accompanying ones. A frame-based kidnapping detection scheme is generated according to the selection of J48 decision tree model from the comparison of several representative classification models. When a video has more frames of kidnapping situation than the threshold ratio after two people meet in the video, the proposed scheme detects and notifies the occurrence of kidnapping event. To check the feasibility of the proposed scheme, the detection accuracy of our newly proposed scheme is compared with that of the previous scheme. According to the experiment results, the proposed scheme could detect kidnapping situations more 4.73% correctly than the previous scheme.