• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.190-199
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• 2014

In the last years, fault problem in power electronics has been more and more investigated both from theoretical and practical point of view. The fault problem can cause equipment failure, data and economical losses. And the analyze system require to ensure fault problem and also rectify failures. The current errors on these faults are applied for identified type of faults. This paper presents technique to detection and identification faults in three-phase voltage source inverter (VSI) by using time-frequency distribution (TFD). TFD capable represent time frequency representation (TFR) in temporal and spectral information. Based on TFR, signal parameters are calculated such as instantaneous average current, instantaneous root mean square current, instantaneous fundamental root mean square current and, instantaneous total current waveform distortion. From on results, the detection of VSI faults could be determined based on characteristic of parameter estimation. And also concluded that the fault detection is capable of identifying the type of inverter fault and can reduce cost maintenance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1119-1143
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• 2014

Lightweight trust mechanism with lightweight cryptographic primitives has emerged as an important mechanism in resource constraint wireless sensor based mobile devices. In this work, outlier detection in lightweight Mobile Ad-hoc NETworks (MANETs) is extended to create the space of reliable trust cycle with anomaly detection mechanism and minimum energy losses [1]. Further, system is tested against outliers through detection ratios and anomaly scores before incorporating virtual programmable nodes to increase the efficiency. Security in proposed system is verified through ProVerif automated toolkit and mathematical analysis shows that it is strong against bad mouthing and on-off attacks. Performance of proposed technique is analyzed over different MANET routing protocols with variations in number of nodes and it is observed that system provide good amount of throughput with maximum of 20% increase in delay on increase of maximum of 100 nodes. System is reflecting good amount of scalability, optimization of resources and security. Lightweight modeling and policy analysis with lightweight cryptographic primitives shows that the intruders can be detection in few milliseconds without any conflicts in access rights.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1243-1248
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• 2014

In General, LPI radar's detection probability by ES equipments is lower than that of conventional pulsed radar because of very low transmitting power and high antenna gain etc. LPI radar is a kind of RF stealth technique such as RCS reduction design. Therefore the ultimate goal of LPI radar is detection probability reduction by opponent. If one of the two, RCS value or LPI radar performance is not sufficient, own platform will be found first by opponent. In this paper, some considerations are suggested for detection probability reduction.

• ETRI Journal
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• v.32 no.6
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• pp.871-880
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• 2010

Many applications dealing with image management need a technique for removing duplicate images or for grouping related (near-duplicate) images in a database. This paper proposes a concentric circle-based image signature which makes it possible to detect near-duplicates rapidly and accurately. An image is partitioned by radius and angle levels from the center of the image. Feature values are calculated using the average or variation between the partitioned sub-regions. The feature values distributed in sequence are formed into an image signature by hash generation. The hashing facilitates storage space reduction and fast matching. The performance was evaluated through discriminability and robustness tests. Using these tests, the particularity among the different images and the invariability among the modified images are verified, respectively. In addition, we also measured the discriminability and robustness by the distribution analysis of the hashed bits. The proposed method is robust to various modifications, as shown by its average detection rate of 98.99%. The experimental results showed that the proposed method is suitable for near-duplicate detection in large databases.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.862-866
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• 2004

Non-intrusive methods based on active remote IR illumination for eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. Based on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• Smart Structures and Systems
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• v.15 no.2
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• pp.315-334
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• 2015

A main goal of this study is to propose a damage detection technique to detect and localize damages of a top-tensioned riser. In this paper, the top-tensioned finite element (FE) model is considered as an analytical model of the riser, and a vibration-based damage detection method is proposed. The present method consists of a FE model updating and damage index method. In order to accomplish the goal of this study, first, a sensitivity-based FE model updating method using natural frequencies and zero frequencies is introduced. Second, natural frequencies and zero frequencies of the axial mode on the top-tensioned riser are estimated by eigenvalue analysis. Finally, the locations and severities of the damages are estimated from the damage index method. Three numerical examples are considered to verify the performance of the proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.1-7
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• 2016

As new information and communication technologies evolve, security threats are also becoming increasingly intelligent and advanced. In this paper, we analyze the time series data continuously entered through a series of periods from the network device or lightweight IoT (Internet of Things) devices by using the statistical technique and propose a system to detect abnormal behaviors of the device or abnormality based on the analysis results. The proposed system performs the first level abnormal detection by using previously entered data set, thereafter performs the second level anomaly detection according to the trust bound configured by using stored time series data based on time attribute or group attribute. Multi-level analysis is able to improve reliability and to reduce false positives as well through a variety of decision data set.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.174-177
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• 2008

In 3D gaming environment, it is important to simulate the physically plausible behaviors of gaming objects in real time. In particular, rigid body dynamics consists in the heart of most game physics. In this paper, we present a constraint-based rigid body simulation method using continuous collision detection as a collision detection method, and LCP formulation as a collision response method. The continuous collision detection method never misses any collisions and thus is able to accurately report the first time of collision as well as its associated colliding features. Moreover, since the number of colliding features is typically low, it also reduces the complexity in the LCP formulation.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.5
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• pp.662-673
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• 2012

This study introduces a condition diagnosis technique for a turbine governor system. The governor system is an important control system to handle turbine speed in a nuclear power plant. The turbine governor system includes turbine valves and stop valves which have their own functions in the system. Because a turbine governor system is operated by high oil pressure, it is very difficult to maintain under stable operating conditions. Turbine valves supply oil pressure to the governor system for proper operation. Using the pressure variation of turbine and governor valves, operating conditions of the turbine governor control system are detected and identified. To achieve automatic detection of valve status, time-based and frequency-based analysis is employed. In this study, a new approach, wavelet decomposition, was used to extract specific features from the pressure signals of the governor and stop valves. The extracted features, which represent the operating conditions of the turbine governor system, include important information to control and diagnose the valves. After extracting the specific features, decision rules were used to classify the valve conditions. The rules were generated by a decision tree algorithm (a typical simple method for data-based rule generation). The results given by the wavelet-based analysis were compared to detection results using time- and frequency-based approaches. Compared with the several related studies, the wavelet transform-based analysis, the proposed in this study has the advantage of easier application without auxiliary features.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4240-4258
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• 2016

A practical iterative channel estimation technique is proposed for the multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in the high-speed mobile environment, such as high speed railway scenario. In the iterative algorithm, the Kalman filter and data detection are jointed to estimate the time-varying channel, where the detection error is considered as part of the noise in the Kalman recursion in each iteration to reduce the effect of the detection error propagation. Moreover, the employed Kalman filter is from the canonical state space model, which does not include the parameters of the autoregressive (AR) model, so the proposed method does not need to estimate the parameters of AR model, whose accuracy affects the convergence speed. Simulation results show that the proposed method is robust to the fast time-varying channel, and it can obtain more gains compared with the available methods.