• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.294-300
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• 2008

This study was conducted to investigate what to consider for active response in the intrusion detection system, how to implement active response, and 6-phase response models to respond actively, including the active response scheme to detect unknown attacks by using a traffic measuring engine and an anomaly detection engine.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.2
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• pp.118-129
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• 2013

Since the obstacles and mines are of the risk factors for operating ships and submarines, the active sonar system is inevitably used to avoid the hazards in ocean environment. In this paper, modeling and simulation algorithm is used for active sonar systemto quantify the measure of mission achievability, which is known as Measure of Effectiveness(MOE), specifically for detection in this study. MOE for detection is directly formulated as a Cumulative Detection Probability(CDP) calculated from Probability of Detection(PD) in range and azimuth. The detection probability is calculated from Transmission Loss(TL) and the sonar parameters such asDirectivity Index (DI) calculated from the shape of transmitted and received array, steered beam patterns, and Reverberation Level (RL). The developed code is applied to demonstrating its applicability.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.122-128
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• 2013

This paper presents a detection algorithm that accurately finds the active area of a video player on monitors or smart TVs. Unlike the previous approaches, temporal difference-based detection algorithms or hooking programs, the proposed detection algorithm can locate the active video player by using the spatial and temporal correlation and a corner detection filter. First, an initial location of the video player is found using conventional temporal difference-based detection. Then, starting from the initial location, the four corners of the active video player are detected by the spatial edge information and the corner detection filter. The experimental results show that proposed algorithm provides fast detection speed and high accuracy.

• Journal of Ocean Engineering and Technology
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• v.8 no.1
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• pp.62-70
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• 1994

In order to estimate the detection range of a active SONAR system, the SONAR equation is commonly used. In this paper, an algorithm to calculate detection range in active SONAR system as function of SONAR depth and target depth is presented. For given SONAR parameters and environment, the transmission loss and background level are found, signal excess is computed. Using log-normal distribution, signal excess is converted to detection probability at each range. Then, the detection range is obtained by integrating the detection probability as function of range for each depth. The proposed algorithm have been applied to the case of omni-directional source with center frequency 30Hz for summer and winter sound profiles. It is found that the optimal search depth is the source depth since the detection range increase at source depth where the signal excess is maximized.

• Journal of Power Electronics
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• v.16 no.2
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• pp.760-768
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• 2016

Three-phase grid-connected inverters are widely applied in the fields of new energy power generation, electric vehicles and so on. Islanding detection is necessary to ensure the stability and safety of such systems. In this paper, feature recognition technology is applied and a novel islanding detection method is proposed. It can identify the features of inverter systems. The theoretical values of these features are defined as codebooks. The difference between the actual value of a feature and the codebook is defined as the quantizing distortion. When islanding happens, the sum of the quantizing distortions exceeds the threshold value. Thus, islanding can be detected. The non-detection zone can be avoided by choosing reasonable features. To accelerate the speed of detection and to avoid miscalculation, an active islanding detection method based on feature recognition technology is given. Compared to the active frequency or phase drift methods, the proposed active method can reduce the distortion of grid-current when the inverter works normally. The principles of the islanding detection method based on the feature recognition technology and the improved active method are both analyzed in detail. An 18 kVA DSP-based three-phase inverter with the SVPWM control strategy has been established and tested. Simulation and experimental results verify the theoretical analysis.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1577-1580
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• 2005

With remarkable growth of using Internet, attempts to try intrusions on network are now increasing. Intrusion Detection System is a security system which detects and copes illegal intrusions. Especially with increasing dispersive attacks through network, concerns for this Distributed Intrusion Detection are also rising. The previous Intrusion Detection System has difficulty in coping cause it detects intrusions only on particular network and only same segment. About same attacks, system lacks capacity of combining information and related data. Also it lacks cooperations against intrusions. Systematic and general security controls can make it possible to detect intrusions and deal with intrusions and predict. This paper considers Distributed Intrusion Detection preventing attacks and suggests the way sending active packets between nodes safely and performing in corresponding active node certainly. This study suggested improved E-IDS system which prevents service attacks and also studied sending messages safely by encoding. Encoding decreases security attacks in active network. Also described effective ways of dealing intrusions when misuses happens thorough case study. Previous network nodes can't deal with hacking and misuses happened in the middle nodes at all, cause it just encodes ends. With above suggested ideas, problems caused by security services can be improved.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.151-159
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• 2006

This paper studied active response policy generation scheme in intrusion detection system. We considered seven requirements of intrusion detection system for active response with components as the preceding study We presented the scheme which I can generate signature with a base with integrate one model with NIDS and ADS. We studied detection of the Unknown Attack which was active, and studied scheme for generated to be able to do signature automatically through Unknown Attack detection.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.35-41
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• 2012

This paper proposes a moving object detection algorithm for active camera system that can be applied to mobile robot and intelligent surveillance system. Most of moving object detection algorithms based on a stationary camera system. These algorithms used fixed surveillance system that does not consider the motion of the background or robot tracking system that track pre-learned object. Unlike the stationary camera system, the active camera system has a problem that is difficult to extract the moving object due to the error occurred by the movement of camera. In order to overcome this problem, the motion of the camera was compensated by using SURF and Pseudo Perspective model, and then the moving object is extracted efficiently using stochastic Label Cluster transport model. This method is possible to detect moving object because that minimizes effect of the background movement. Our approach proves robust and effective in terms of moving object detection in active camera system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.22-27
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• 2012

Correct and fast detection of a micro-grid (MG) islanding is essential to the MG since operation, control and protection of the MG depend on an operating mode i.e., an interconnected mode or an islanding mode. When islanding occurs, the frequency of the point of common coupling (PCC) is not the nominal frequency during the transient state owing to the frequency rise or drop of generators in the MG. Thus, the active and reactive power calculated by the frequency domain based method such as Fourier Transform might contain some errors. This paper proposes an islanding detection algorithm for the MG based on the instantaneous active and reactive powers delivered to the dedicated line in the time domain. During the islanding mode, the instantaneous active and reactive powers delivered to the dedicated line are constants, which depend on the voltage of the PCC and the impedance of the dedicated line. In this paper, the instantaneous active and reactive powers are calculated in the time domain and used to detect islanding. The performance of the proposed algorithm is verified under various scenarios including islanding conditions, fault conditions and load variation using the PSCAD/EMTDC simulator. The results indicate that the algorithm successfully detects islanding for the MG.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.51-56
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• 2022

In space based constellation network, users are allowed to enter or leave the network arbitrarily. Hence, the number, identities and transmitted data of active users vary with time and have considerable impacts on the receiver's performance. The so-called problem of multiuser detection means identifying the identity of each active user and detecting the data transmitted by each active user. Traditional methods assume that the number of active users is equal to the maximum number of users that the network can hold. The model of traditional methods are simple and the performance are suboptimal. In this paper a Maximum A Posteriori Probability (MAP) based multiuser detection method is proposed. The proposed method models the activity state of users as Markov chain and transforms multiuser detection into searching optimal path in grid map with BCJR algorithm. Simulation results indicate that the proposed method obtains 2.6dB and 1dB E_b/N₀ gains respectively when activity detection error rate and symbol error rate reach 10^-3, comparing with reference methods.