• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.16 no.1
• /
• pp.115-122
• /
• 2006

The most methods for intrusion detection are based on the misuse detection which accumulates hewn intrusion information and makes a decision of an attack against any behavior data. However it is very difficult to detect a new or modified aoack with only the collected patterns of attack behaviors. Therefore, if considering that the method of anomaly behavior detection actually has a high false detection rate, a new approach is required for very huge intrusion patterns based on sequence. The approach can improve a possibility for intrusion detection of known attacks as well as modified and unknown attacks in addition to the similarity measurement of intrusion patterns. This paper proposes a method which applies the multiple sequence alignments technique to the similarity matching of the sequence based intrusion patterns. It enables the statistical analysis of sequence patterns and can be implemented easily. Also, the method reduces the number of detection alerts and false detection for attacks according to the changes of a sequence size.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.9
• /
• pp.1315-1322
• /
• 2015

This paper proposes an active islanding detection method for the BESS (Battery Energy Storage System) with 3-phase inverter which is connected to the AC grid. The proposed method adopts the DDSRF (Decoupled Double Synchronous Reference Frame) PLL (Phase Locked-Loop) so that the independent control of positive-sequence and negative-sequence current is successfully carried out using the detected phase angle information. The islanding state can be detected by sensing the variation of negative-sequence voltage at the PCC (Point of Common Connection) due to the injection of 2-3% negative-sequence current from the BESS. The proposed method provides a secure and rapid detection under the variation of negative-sequence voltage due to the sag and swell. The feasibility of proposed method was verified by computer simulations with PSCAD/EMTDC and experimental analyses with 5kW hardware prototype for the benchmark circuit of islanding detection suggested by IEEE 1547 and UL1741. The proposed method would be applicable for the secure detection of islanding state in the grid-tied Microgrid.

• Interdisciplinary Bio Central
• /
• v.3 no.4
• /
• pp.14.1-14.9
• /
• 2011

Protein homology detection is an important issue in comparative genomics. Because of the exponential growth of sequence databases, fast and efficient homology detection tools are urgently needed. Currently, for homology detection, sequence comparison methods using local alignment such as BLAST are generally used as they give a reasonable measure for sequence similarity. However, these methods have drawbacks in offering overall sequence similarity, especially in dealing with eukaryotic genomes that often contain many insertions and duplications on sequences. Also these methods do not provide the explicit models for speciation, thus it is difficult to interpret their similarity measure into homology detection. Here, we present a novel method based on Word Conservation Score (WCS) to address the current limitations of homology detection. Instead of counting each amino acid, we adopted the concept of 'Word' to compare sequences. WCS measures overall sequence similarity by comparing word contents, which is much faster than BLAST comparisons. Furthermore, evolutionary distance between homologous sequences could be measured by WCS. Therefore, we expect that sequence comparison with WCS is useful for the multiple-species-comparisons of large genomes. In the performance comparisons on protein structural classifications, our method showed a considerable improvement over BLAST. Our method found bigger micro-syntenic blocks which consist of orthologs with conserved gene order. By testing on various datasets, we showed that WCS gives faster and better overall similarity measure compared to BLAST.

• Journal of Communications and Networks
• /
• v.8 no.2
• /
• pp.205-211
• /
• 2006

This paper considers the maximum likelihood (ML) detection of 16-ary differential amplitude and phase shift keying (DAPSK) in Rayleigh fading channels. Based on the conditional likelihood function, two new receiver structures, namely ML symbol-by-symbol receiver and ML sequence receiver, are proposed. For the symbol-by-symbol detection, the conventional DAPSK detector is shown to be sub-optimum due to the complete separation in the phase and amplitude detection, but it results in very close performance to the ML detector provided that its circular amplitude decision thresholds are optimized. For the sequence detection, a simple Viterbi algorithm with only two states are adopted to provide an SNR gain around 1 dB on the amplitude bit detection compared with the conventional detector.

• 제어로봇시스템학회:학술대회논문집
• /
• 1994.10a
• /
• pp.7-12
• /
• 1994

This paper describes an outline of pseudorandom M-sequence and its applications to measurement and control engineering. At first, generation and properties of M-sequence is briefly described and then its applications to delay time measurement, information transmission by use of M-array, two dimensional positioning, fault detection of logical circuit, fault detection of RAM, linear and nonlinear system identification.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.6
• /
• pp.15-20
• /
• 2016

In this paper, we consider selective mapping (SLM) based OFDM systems without side information, where SLM is one of the promising peak-to-average power ratio (PAPR) reduction techniques due to its simplicity and no distortion in the transmitted signal. First, we construct a new phase sequence where a part of phase sequence is replaced by an orthogonal sequence. Based on the proposed phase sequence, we propose a new scheme for detecting coherently the index of the phase sequence used in transmitter without side information. Computer simulation shows that the proposed detection scheme performs well in SLM-based OFDM systems, and specifically outperforms the existing ones when channel variation is relatively small between sub-carriers used in phase sequence detection.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.17 no.6
• /
• pp.546-552
• /
• 2012

This paper presents an active anti-islanding detection method using negative sequence voltage injection to the grid through a three-phase photovoltaic inverters. Because islanding operation mode can cause a variety of problems, the islanding detection of grid-connected photovoltaic inverter is the mandatory feature. The islanding mode is detected by measuring the magnitude of negative sequence impedance calculated by the negative sequence voltage and current at the point of common coupling. Simulation and experimental test are performed to verify the effectiveness of the proposed method which can detect the islanding mode in the specified time. The test has been done in accordance with the condition on IEEE Std 929-2000.

• Journal of electromagnetic engineering and science
• /
• v.5 no.1
• /
• pp.26-30
• /
• 2005

It is important to know phase offsets of PN(Pseudo Noise) sequences in spread spectrum communications since the acquisition is equivalent to making a phase offset between a receiving PN sequence and a PN sequence of local PN generator be identical. In this paper, a phase offset enumeration method for PN sequences with error detection, and its application to the synchronization are proposed. The phase offset enumeration for an n-tuple PN sequence and its error detection are performed when one period of the sequence is received. Once the phase offset of the receiving sequence is calculated, we can easily accomplish the synchronization by initializing shift registers of a local PN generator according to the phase offset value. The mean acquisition time performance of the proposed scheme was derived analytically. Since this synchronization scheme can be realized by using simple circuit and acquires very rapid acquisition in high SNR but shows performance degradation in low SNR, it can be especially useful in indoor and office environments.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.62 no.4
• /
• pp.198-203
• /
• 2013

There are conditions that can be unbalanced three phase currents in a large generator by untransposed lines, unbalanced loads, unsymmetrical faults, and open phases. The unbalanced conditions can producing negative sequence components of current that induce two times frequence current in the surface of the rotor, the retaining rings, the slot wedges in the field windings. These rotor currents make the rotor rapidly overheat, so the rotor can cause substantial damage in a very short time. This paper presents the digital negative sequence relay algorithm for unbalanced protection in a generator. The proposed algorithm was tested by using collected current signals on PSCAD/EMTDC considering a hydro turbine based generator control system. It can be seen that the proposed relaying by negative sequence current is useful for detection of unbalanced state of large generator.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.05a
• /
• pp.2-4
• /
• 2023

Sequence data plays an important role in the field of intelligence, especially for industrial control, traffic control and other aspects. Finding abnormal parts in sequence data has long been an application field of AI technology. In this paper, we propose an anomaly detection method for sequence data using a diffusion model. The diffusion model has two major advantages: interpretability derived from rigorous mathematical derivation and unrestricted selection of backbone models. This method uses the diffusion model to predict and reconstruct the sequence data, and then detects the abnormal part by comparing with the real data. This paper successfully verifies the feasibility of the diffusion model in the field of anomaly detection. We use the combination of MLP and diffusion model to generate data and compare the generated data with real data to detect anomalous points.