• Title/Summary/Keyword: Detection Systems

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Preemptive Failure Detection using Contamination-Based Stacking Ensemble in Missiles

  • Seong-Mok Kim;Ye-Eun Jeong;Yong Soo Kim;Youn-Ho Lee;Seung Young Lee
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.5
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    • pp.1301-1316
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    • 2024
  • In modern warfare, missiles play a pivotal role but typically spend the majority of their lifecycle in long-term storage or standby mode, making it difficult to detect failures. Preemptive detection of missiles that will fail is crucial to preventing severe consequences, including safety hazards and mission failures. This study proposes a contamination-based stacking ensemble model, employing the local outlier factor (LOF), to detect such missiles. The proposed model creates multiple base LOF models with different contamination values and combines their anomaly scores to achieve a robust anomaly detection. A comparative performance analysis was conducted between the proposed model and the traditional single LOF model, using production-related inspection data from missiles deployed in the military. The experimental results showed that, with the contamination parameter set to 0.1, the proposed model exhibited an increase of approximately 22 percentage points in accuracy and 71 percentage points in F1-score compared to the single LOF model. This approach enables the preemptive identification of potential failures, undetectable through traditional statistical quality control methods. Consequently, it contributes to lower missile failure rates in real battlefield scenarios, leading to significant time and cost savings in the military industry.

An Architecture Design of Distributed Internet Worm Detection System for Fast Response

  • Lim, Jung-Muk;Han, Young-Ju;Chung, Tai-Myoung
    • Proceedings of the Korea Society of Information Technology Applications Conference
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    • 2005.11a
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    • pp.161-164
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    • 2005
  • As the power of influence of the Internet grows steadily, attacks against the Internet can cause enormous monetary damages nowadays. A worm can not only replicate itself like a virus but also propagate itself across the Internet. So it infects vulnerable hosts in the Internet and then downgrades the overall performance of the Internet or makes the Internet not to work. To response this, worm detection and prevention technologies are developed. The worm detection technologies are classified into two categories, host based detection and network based detection. Host based detection methods are a method which checks the files that worms make, a method which checks the integrity of the file systems and so on. Network based detection methods are a misuse detection method which compares traffic payloads with worm signatures and anomaly detection methods which check inbound/outbound scan rates, ICMP host/port unreachable message rates, and TCP RST packet rates. However, single detection methods like the aforementioned can't response worms' attacks effectively because worms attack the Internet in the distributed fashion. In this paper, we propose a design of distributed worm detection system to overcome the inefficiency. Existing distributed network intrusion detection systems cooperate with each other only with their own information. Unlike this, in our proposed system, a worm detection system on a network in which worms select targets and a worm detection system on a network in which worms propagate themselves cooperate with each other with the direction-aware information in terms of worm's lifecycle. The direction-aware information includes the moving direction of worms and the service port attacked by worms. In this way, we can not only reduce false positive rate of the system but also prevent worms from propagating themselves across the Internet through dispersing the confirmed worm signature.

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The quench detection technique of the superconducting magnet using an AE sensor (AE센서를 이용한 초전도자석의 퀜치 검출기법)

  • Kim, Ho-Min;Lee, Bang-Woo;Oh, Il-Sung;Lee, Hai-Gun;Iwasa, Yukikazu
    • Proceedings of the KIEE Conference
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    • 2004.07c
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    • pp.1748-1750
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    • 2004
  • This paper deals with the detection method of the Quench phenomenon for superconducting magnet using the Acoustic Emission (AE) sensor. AE sensor is the elements, which is used to change the Acoustic signal to the voltage value. This signal may be used to detect whether the superconducting magnet has been at the Quench state or not. Recently, the development of the Quench detection technique, which is the using voltage and current signals, fiber-optic sensor, and so on, for the superconducting applications is widely studying. This method for the Quench detection of the superconducting magnet is also studying at some kinds of institute in Japan and the united state. Because of the large-scale superconducting magnet like International Thermonuclear Experimental Reactor(ITER) is charged a lot of energy, when the Quench phenomenon is being at the superconducting magnet it is happen to the problem of the protection for the applications. In this paper, we concluded that the Quench detection was possible when the mechanical stress by means of the local heat is generated at the part of inside superconducting magnets.

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Fault Detection and Diagnosis System for a Three-Phase Inverter Using a DWT-Based Artificial Neural Network

  • Rohan, Ali;Kim, Sung Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.4
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    • pp.238-245
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    • 2016
  • Inverters are considered the basic building blocks of industrial electrical drive systems that are widely used for various applications; however, the failure of electronic switches mainly affects the constancy of these inverters. For safe and reliable operation of an electrical drive system, faults in power electronic switches must be detected by an efficient system that is capable of identifying the type of faults. In this paper, an open switch fault identification technique for a three-phase inverter is presented. Single, double, and triple switching faults can be diagnosed using this method. The detection mechanism is based on stator current analysis. Discrete wavelet transform (DWT) using Daubechies is performed on the Clarke transformed (-) stator current and features are extracted from the wavelets. An artificial neural network is then used for the detection and identification of faults. To prove the feasibility of this method, a Simulink model of the DWT-based feature extraction scheme using a neural network for the proposed fault detection system in a three-phase inverter with an induction motor is briefly discussed with simulation results. The simulation results show that the designed system can detect faults quite efficiently, with the ability to differentiate between single and multiple switching faults.

Improved Decoupled Control and Islanding Detection of Inverter-Based Distribution in Multibus Microgrid Systems

  • Pinto, Smitha Joyce;Panda, Gayadhar
    • Journal of Power Electronics
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    • v.16 no.4
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    • pp.1526-1540
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    • 2016
  • This work mainly discusses an accurate and fast islanding detection based on fractional wavelet packet transform (FRWPT)for multibus microgrid systems. The proposed protection scheme uses combined desirable features retrieved from discrete fractional Fourier transform (FRFT) and wavelet packet transform (WPT) techniques, which provides precise time-frequency information on minute perturbation signals introduced in the system. Moreover, this study focuses on the design of decoupling control with a distributed controller based on state feedback for the efficient operation of microgrid systems that are transitioning from the grid-connected mode to the islanded mode. An IEEE 9-bus test system with inverter based distributed generation (DG) units is considered for islanding assessment and smooth operation. Finally, tracking errors are greatly reduced with stability improvement based on the proposed controller. FRWPT based islanding detection is demonstrated via a time domain simulation of the system. Simulated results show an improvement in system stability with the application of the proposed controller and accurate islanding detection based on the FRWPT technique in comparison with the results obtained by applying the wavelet transform (WT) and WPT.

Soft-Input Soft-Output Multiple Symbol Detection for Ultra-Wideband Systems

  • Wang, Chanfei;Gao, Hui;Lv, Tiejun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.7
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    • pp.2614-2632
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    • 2015
  • A multiple symbol detection (MSD) algorithm is proposed relying on soft information for ultra-wideband systems, where differential space-time block code is employed. The proposed algorithm aims to calculate a posteriori probabilities (APP) of information symbols, where a forward and backward message passing mechanism is implemented based on the BCJR algorithm. Specifically, an MSD metric is analyzed and performed for serving the APP model. Furthermore, an autocorrelation sampling is employed to exploit signals dependencies among different symbols, where the observation window slides one symbol each time. With the aid of the bidirectional message passing mechanism and the proposed sampling approach, the proposed MSD algorithm achieves a better detection performance as compared with the existing MSD. In addition, when the proposed MSD is exploited in conjunction with channel decoding, an iterative soft-input soft-output MSD approach is obtained. Finally, simulations demonstrate that the proposed approaches improve detection performance significantly.

Simplified MMSE Detection with SoIC for Iterative Receivers in Multiple Antenna Systems (다중 안테나 시스템에서 연 간섭 제거를 이용한 저 복잡도 MMSE 신호 검출 방법)

  • Kim, Jong-Kyung;Seo, Jong-Soo
    • Journal of Advanced Navigation Technology
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    • v.13 no.3
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    • pp.385-392
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    • 2009
  • Simplified minimum mean square error (MMSE) detection technique combined with soft interference cancellation(SoIC) is proposed for iterative receivers in multiple antenna systems. To avoid repeated matrix inversions required to obtain the MMSE filter coefficients during the iteration between the soft detector and decoder, simplified matrix inversion techniques are applied to calculate the filter coefficient matrix. Simulation results show that the proposed MMSE detections with SoIC indicate a comparable or slightly degraded detection performance while achieving a significantly reduced complexity as compared to the conventional MMSE detection with SoIC.

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A Study on Partial Correlation based PSS Detection Schemes for Initial Cell Search in LTE Systems (LTE 시스템에서 초기 셀 탐색을 위한 부분 상관값 기반 PSS 검출 방식에 관한 고찰)

  • Joo, Jung Suk
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.9
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    • pp.3-10
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    • 2014
  • The synchronization signal in Long Term Evolution (LTE) systems contains the primary synchronization signal (PSS) and the secondary synchronization signal (SSS), and the overall synchronization performance is dominated by PSS detection. In this paper, we propose a PSS detection scheme employing three partial correlation based PSS detectors with different partial correlation lengths, in which calculated partial correlation values are reused in order to reduce computational complexity. A coherent selection scheme using tentative frequency offsets is also proposed to select one reliable result from outputs of partial correlation based PSS detectors. It is shown through computer simulation that the proposed scheme can have a robust detection performance in wide range of frequency offsets.

Performance Improvement for Tracking Small Targets (고기동 표적 추적 성능 개선을 위한 연구)

  • Jung, Yun-Sik;Kim, Kyung-Su;Song, Taek-Lyul
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.11
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    • pp.1044-1052
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    • 2010
  • In this paper, a new realtime algorithm called the RTPBTD-HPDAF (Recursive Temporal Profile Base Target Detection with Highest Probability Data Association Filter) is presented for tracking fast moving small targets with IIR (Imaging Infrared) sensor systems. Spatial filter algorithms are mainly used for target in IIR sensor system detection and tracking however they often generate high density clutter due to various shapes of cloud. The TPBTD (Temporal Profile Base Target Detection) algorithm based on the analysis of temporal behavior of individual pixels is known to have good performance for detection and tracking of fast moving target with suppressing clutter. However it is not suitable to detect stationary and abruptly maneuvering targets. Moreover its computational load may not be negligible. The PTPBTD-HPDAF algorithm proposed in this paper for real-time target detection and tracking is shown to be computationally cheap while it has benefit of tracking targets with abrupt maneuvers. The performance of the proposed RTPBTD-HPDAF algorithm is tested and compared with the spatial filter with HPDAF algorithm for run-time and track initiation at real IIR video.

Lattice-Reduction-Aided Detection based Extended Noise Variance Matrix using Semidefinite Relaxation in MIMO Systems (MIMO시스템에서 Semidefinite Relaxation을 이용한 잡음 분산 행렬 기반의 Lattice-Reduction-Aided 검출기)

  • Lee, Dong-Jin;Park, Su-Bin;Byun, Youn-Shik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.11C
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    • pp.932-939
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    • 2008
  • Recently lattice-reduction (LR) has been used in signal detection for multiple-input multiple-output (MIMO) systems. The conventional LR aided detection schemes are combinations of LR and signal detection methods such as zero-forcing (ZF) and minimum mean square error (MMSE) detection. In this paper, we propose the Lattice-Reduction-aided scheme based on extended noise variance matrix to search good candidate symbol set in quantization step. Then this scheme estimates transmitted symbol with Semidefinite Relaxation by candidate symbol set. Simulation results in a random MIMO system show that the proposed scheme exhibits improved performance and a slight increase in complexity.