• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1954-1961
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• 2009

This paper describes the development of a three-phase line-interactive dynamic voltage restorer with hybrid detection method, which is composed of three H-bridge inverter modules and super-capacitors. The operational feasibility was verified through computer simulations with PSCAD/EMTDC software, and experimental works with a 3kVA prototype. The developed system can compensate the input voltage sag and interruption within 2ms. The maximum allowable duration of voltage interruption is about 4 seconds. The developed system can be effectively used to compensate the voltage interruption in the sensitive load, such as computer, communication devices, and automation devices, and medical equipment. The developed system has a simple structure to be easily implemented with commercially available components, and to be highly reliable in operation.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.370-373
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• 2005

We have developed Hybrid algorithm for yellow sand detection. Hybrid algorithm is composed of three methods using infrared bands. The first method used the differential absorption in brightness temperature difference between $11\mu m\;and\;12\mu m$ (BID _1), through which help distinguish the yellow sand from various meteorological clouds. The second method uses the brightness temperature difference between $3.7\mu m\;and\;11\mu m$ (BID_2). The technique would be most sensitive to dust loading during the day when the BID _2 is enhanced by reflection of $3.7\mu m$ solar radiation. The third one is a newly developed algorithm from our research, the so-called surface temperature variation method (STY). We have applied the three methods to MODIS for derivation of the yellow sand dust and in conjunction with the Principle Component Analysis (PCA), a form of eigenvector statistical analysis. PCI shows better results for yellow sand detection in comparison with the results from individual method. The comparison between PCI and MODIS aerosols optical depth (AOD) shows remarkable good correlations during daytime and relatively good correlations over the land.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.11
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• pp.27-36
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• 2013

Islanding in a gird connected inverter of wind power generation system may influence a bad effect on equipments or yield safety hazards on grid so it should be detected rapidly and exactly. A passive method to detect islanding is comparatively simpler than an active method but suffers from non detection zone (NDZ). On the other hand, the active method can significantly reduce NDZ by injecting a disturbance into inverter output. To improve the reliability of islanding detection, this paper proposes a hybrid anti-islanding detection method combining the conventional passive method as well as the active method based on novel harmonic injection method using fourier transform. The proposed scheme is fast to detect islanding when NDZ does not exist because it has the nature of passive method. Under NDZ, the active method can detect occurrence of islanding reliably. The effectiveness and validity of the proposed scheme is proved through comparative simulations.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.4
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• pp.303-310
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• 2004

In this paper, for compensating dynamic voltage sag and harmonic current, 3-phase hybrid series active power filter based on the space vector detection is proposed. The Space vector algorithm for detecting the voltage sag and the harmonic current in compared with conventional theory is a simple method for calculating the compensating reference without any coordinated transformation. The effectiveness of the proposed system is verified by the PSIM simulation in the steady state and the transient state, which the proposed system is able to simultaneously compensate harmonics and source voltage unbalance / sag.

• Advances in robotics research
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• v.2 no.1
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• pp.33-44
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• 2018

This paper presents a novel feature detection algorithm called depth-hybrid speeded-up robust features (DH-SURF) augmented by depth information in the speeded-up robust features (SURF) algorithm. In the keypoint detection part of classical SURF, the standard deviation of the Gaussian kernel is varied for its scale-invariance property, resulting in increased computational complexity. We propose a keypoint detection method with less variation of the standard deviation by using depth data from a red-green-blue depth (RGB-D) sensor. Our approach maintains a scale-invariance property while reducing computation time. An RGB-D simultaneous localization and mapping (SLAM) system uses a feature extraction method and depth data concurrently; thus, the system is well-suited for showing the performance of the DH-SURF method. DH-SURF was implemented on a central processing unit (CPU) and a graphics processing unit (GPU), respectively, and was validated through the real-time RGB-D SLAM.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.348-358
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• 2022

Software fault prediction is a method to compute fault in the software sections using software properties which helps to evaluate the quality of software in terms of cost and effort. Recently, several software fault detection techniques have been proposed to classifying faulty or non-faulty. However, for such a person, and most studies have shown the power of predictive errors in their own databases, the performance of the software is not consistent. In this paper, we propose a hybrid soft computing technique for SFP based on optimal feature extraction and classification (HST-SFP). First, we introduce the bat induced butterfly optimization (BBO) algorithm for optimal feature selection among multiple features which compute the most optimal features and remove unnecessary features. Second, we develop a layered recurrent neural network (L-RNN) based classifier for predict the software faults based on their features which enhance the detection accuracy. Finally, the proposed HST-SFP technique has the more effectiveness in some sophisticated technical terms that outperform databases of probability of detection, accuracy, probability of false alarms, precision, ROC, F measure and AUC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.704-719
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• 2024

Botnet pandemics are becoming more prevalent with the growing use of mobile phone technologies. Mobile phone technologies provide a wide range of applications, including entertainment, commerce, education, and finance. In addition, botnet refers to the collection of compromised devices managed by a botmaster and engaging with each other via a command server to initiate an attack including phishing email, ad-click fraud, blockchain, and much more. As the number of botnet attacks rises, detecting harmful activities is becoming more challenging in handheld devices. Therefore, it is crucial to evaluate mobile botnet assaults to find the security vulnerabilities that occur through coordinated command servers causing major financial and ethical harm. For this purpose, we propose a hybrid analysis approach that integrates permissions and API and experiments on the machine-learning classifiers to detect mobile botnet applications. In this paper, the experiment employed benign, botnet, and malware applications for validation of the performance and accuracy of classifiers. The results conclude that a classifier model based on a simple decision tree obtained 99% accuracy with a low 0.003 false-positive rate than other machine learning classifiers for botnet applications detection. As an outcome of this paper, a hybrid approach enhances the accuracy of mobile botnet detection as compared to static and dynamic features when both are taken separately.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.243.1-243.1
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• 2010

Devices based on nanomaterials platforms are emerging as a powerful tool for ultrasensitive sensors for the direct detection of biological and chemical species. In this talk, we will report the preparation and the full characterization of electrochemical polymerization of biopolymers platforms and nano-structure formation for electrochemical detection of enzymatic activity and toxic compound in electrolyte for biosensor applications. Formation of an electroactive polymer film of two different compounds has been quantified by observing new redox peak at higher potentials in cyclic voltammogram measurements. RCT value of at various biopolymer concentration based hybrid films has been obtained from electrochemical impedance spectroscopy analysis and possible mechanism for formation of complexes during electrochemical polymerization on conducting substrates has been investigated. Biosensors developed based on these hybrid biopolymers have very high sensitivity.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2006.06a
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• pp.649-653
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• 2006

In this paper, we propose a hybrid feature extraction method in which Principal Components Analysis is combined with optimized k-Means clustering technique. Our approach hierarchically reduces the redundancy of features with high explanation in principal components analysis for choosing a good subset of features critical to improve the performance of classifiers. Based on this result, we evaluate the performance of intrusion detection by using Support Vector Machine and a nonparametric approach based on k-Nearest Neighbor over data sets with reduced features. The Experiment results with KDD Cup 1999 dataset show several advantages in terms of computational complexity and our method achieves significant detection rate which shows possibility of detecting successfully attacks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1016-1030
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• 2018

In this paper, an error-detection-coding-aided iterative hard decision interference cancellation (EDC-IHIC) scheme for multiple-input multiple-output systems employing hybrid automatic repeat request (HARQ) for multi-packet transmission is developed and investigated. In the EDC-IHIC scheme, only packets identified as error-free by the EDC are submitted to the interference cancellation (IC) stage for cancellation from the received signals. Therefore, the possibility of error propagation, including inter-transmission error propagation, can be eliminated using EDC-IHIC. Because EDC must be implemented in systems that employ HARQ to determine packet retransmission, error propagation can be prevented without the need for additional redundancy. The results of simulations conducted herein verify that the EDC-IHIC scheme outperforms conventional hard decision IC schemes in terms of the packet error rate in various environments.