• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.459-466
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• 2006

The objective of this study is to improve the accuracy of damage detection using natural frequency and modal strain energy. The following approaches are used to achieve the goal. First, modal strain energy is introduced and newly GA-based damage detection technique using natural frequency and modal strain energy is proposed. Next, to verify efficiency of the proposed technique, damage scenarios for free-free beams are designed and the vibration modal tests as damage cases are conducted. Finally, feasibility of proposed technique is verified in comparison with a GA-based damage detection technique using natural frequency and mode shape.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.110-114
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• 2015

This paper reports a novel object-detection technique in video sequences. The proposed algorithm consists of detection of objects in illuminated and occluded videos by using object features and a neural network technique. It consists of two functional modules: region-based object feature extraction and continuous detection of objects in video sequences with region features. This scheme is proposed as an enhancement of the Lowe's scale-invariant feature transform (SIFT) object detection method. This technique solved the high computation time problem of feature generation in the SIFT method. The improvement is achieved by region-based feature classification in the objects to be detected; optimal neural network-based feature reduction is presented in order to reduce the object region feature dataset with winner pixel estimation between the video frames of the video sequence. Simulation results show that the proposed scheme achieves better overall performance than other object detection techniques, and region-based feature detection is faster in comparison to other recent techniques.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.89-96
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• 2014

MANET has been applied to a wide variety of areas because it has advantages which can build a network quickly in a difficult situation to build a network. However, it is become a victim of malicious nodes because of characteristics such as mobility of nodes consisting MANET, limited resources, and the wireless network. Therefore, it is required to lightweight attack detection technique which can accurately detect attack without causing a large burden to the mobile node. In this paper, we propose a multistage attack detection techniques that attack detection takes place in routing phase and data transfer phase in order to increase the accuracy of attack detection. The proposed attack detection technique is composed of four modules at each stage in order to perform accurate attack detection. Flooding attack and packet discard or modify attacks is detected in the routing phase, and whether the attack by modification of data is detected in the data transfer phase. We assume that nodes have a public key and a private key in pairs in this paper.

• BMB Reports
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• v.39 no.3
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• pp.247-252
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• 2006

A rapid method for the detection of Hepatitis E Virus (HEV) was developed by utilizing nano-gold labeled oligonucleotide probes, silver stain enhancement and the microarray technique. The 5'-end -$NH_2$ modified oligonucleotide probes were immobilized on the surface of the chip base as the capture probe. The detection probe was made of the 3'-end -SH modified oligonucleotide probe and nano-gold colloid. The optimal concentrations of these two probes were determined. To test the detection sensitivity and specificity of this technique, a conservative fragment of the virus RNA was amplified by the RT-PCR/PCR one step amplification. The cDNA was hybridized with the capture probes and the detection probes on microarray. The detection signal was amplified by silver stain enhancement and could be identified by naked eyes. 100 fM of amplicon could be detected out on the microarray. As the results, preparation of nano-gold was improved and faster. Development time also was shortened to 2 min. Thus, considering high efficiency, low cost, good specificity and high sensitivity, this technique is alternative for the detection of HEV.

• Journal of Marine Bioscience and Biotechnology
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• v.6 no.1
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• pp.1-7
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• 2014

Marine-derived pathogens threat health and life of human and animals. Therefore, rapid and specific detection methods need to be developed. Here, we summarized various groups of detection methods, including conventional method, flow cytometry, nucleic acid-based method, and protein-based method. In addition, perspective of detection technique was discussed as a unified detection system for pathogens.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.85-94
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• 2014

This paper studied the detection technique using file DNA-based behavior pattern analysis in order to minimize damage to user system by malicious programs before signature or security patch is released. The file DNA-based detection technique was applied to defend against zero day attack and to minimize false detection, by remedying weaknesses of the conventional network-based packet detection technique and process-based detection technique. For the file DNA-based detection technique, abnormal behaviors of malware were splitted into network-related behaviors and process-related behaviors. This technique was employed to check and block crucial behaviors of process and network behaviors operating in user system, according to the fixed conditions, to analyze the similarity of behavior patterns of malware, based on the file DNA which process behaviors and network behaviors are mixed, and to deal with it rapidly through hazard warning and cut-off.

• Journal of Aerospace System Engineering
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• v.18 no.3
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• pp.41-47
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• 2024

Recently, as the practical application and commercialization of unmanned aerial vehicles (UAVs) is pursued, interest in ensuring the safety of the UAV is increasing. Because UAV accidents can result in property damage and loss of life, it is important to develop technology to prevent accidents. For this reason, a technique to detect the abnormal flight state of UAVs has been developed based on the AutoEncoder model. However, the existing detection technique is limited in terms of performance and real-time processing. In this paper, we propose a U-Net based abnormal flight detection technique. In the proposed technique, abnormal flight is detected based on the increasing rate of Mahalanobis distance for the reconstruction error obtained from the U-Net model. Through simulation experiments, it can be shown that the proposed detection technique has superior detection performance compared to the existing detection technique, and can operate in real-time in an on-board environment.

• Convergence Security Journal
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• v.14 no.7
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• pp.53-58
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• 2014

MANET can quickly build a network because it is configured with only the mobile node and it is very popular today due to its various application range. However, MANET should solve vulnerable security problem that dynamic topology, limited resources of each nodes, and wireless communication by the frequent movement of nodes have. In this paper, we propose a domain-based distributed cooperative intrusion detection techniques that can perform accurate intrusion detection by reducing overhead. In the proposed intrusion detection techniques, the local detection and global detection is performed after network is divided into certain size. The local detection performs on all the nodes to detect abnormal behavior of the nodes and the global detection performs signature-based attack detection on gateway node. Signature DB managed by the gateway node accomplishes periodic update by configuring neighboring gateway node and honeynet and maintains the reliability of nodes in the domain by the trust management module. The excellent performance is confirmed through comparative experiments of a multi-layer cluster technique and proposed technique in order to confirm intrusion detection performance of the proposed technique.

• ETRI Journal
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• v.35 no.3
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• pp.371-377
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• 2013

An effective signal detection algorithm with low complexity is presented for multiple-input multiple-output orthogonal frequency division multiplexing systems. The proposed technique, QR-MLD, combines the conventional maximum likelihood detection (MLD) algorithm and the QR algorithm, resulting in much lower complexity compared to MLD. The proposed technique is compared with a similar algorithm, showing that the complexity of the proposed technique with T=1 is a 95% improvement over that of MLD, at the expense of about a 2-dB signal-to-noise-ratio (SNR) degradation for a bit error rate (BER) of $10^{-3}$. Additionally, with T=2, the proposed technique reduces the complexity by 73% for multiplications and 80% for additions and enhances the SNR performance about 1 dB for a BER of $10^{-3}$.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.5
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• pp.612-619
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• 2013

This paper proposes an early diagnosis technique for the stator-turn fault (STF) in an interior permanent magnet (IPM)-type brushless DC (BLDC) motor using the impedance parameter. We have analyzed the varying characteristics owing to the STF through various experiments and the finite element method (FEM). As a result, we have presented a simple method for fault detection. This technique can be applied without requiring a fast Fourier transform (FFT) and the calculation of the negative-sequence impedance. The fault detection system works on the basis of the comparison the measured impedance with the database impedance. The variations in the characteristics owing to the STF as well as the proposed technique have been verified through the simulation and experiment.