• Journal of Power Electronics
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• v.11 no.6
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• pp.801-810
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• 2011

An open circuit fault diagnostic method in IGBTs for the ac to dc converters used in microgrid applications is developed in this paper. An ac to dc converter is a key technology for microgrids in order to interface both distributed generation (DG) and renewable energy resources (RES). Also, highly reliable ac to dc converters are necessary to keep converters in continuous operation as long as possible during power switch fault conditions. Therefore, the proposed fault diagnostic method is developed to reduce the fault detection time and to avoid any other fault alarms because continuous operation is desired. The proposed diagnostic method is a combination of the absolute normalized dc current technique and the false alarm suppression algorithm to overcome the long fault detection time and fault alarm problems. The simulation and experimental results show that the developed fault diagnostic method can perform fault detection within about one cycle. The results illustrate that the reliability of an ac to dc converter interfaced with a microgrid can be improved by using the proposed fault diagnostic method.

• Journal of the Korean Solar Energy Society
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• v.35 no.2
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• pp.11-19
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• 2015

Islanding is a phenomenon that EPS(Electric Power System) is continuously energized by PV PCS(Photovoltaic Power Conditioning System) even when EPS is isolated from the grid. Unintentional islanding will result in safety hazard, power quality degradation and many other issues. So, islanding protection of grid-connected PV PCS is a key function for standards compliance. Nowadays, many anti-islanding schemes are researched. But existing anti-islanding schemes used in PV PCS have power quality degradation and non-detection zone issues. This paper analyses not only detection performance of existed anti-islanding schemes using active frequency drift but also THD of PCS output current according to each value disturbance for anti-islanding. In addition, the lowest value of disturbance in each scheme was tabulated under guarantee of anti-islanding condition.

• Journal of the Korea Society of Computer and Information
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• v.4 no.3
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• pp.8-12
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• 1999

Edge detection is a key component for many modern computer vision applications. While it is certainly not the only way to identify an object, or track a feature, it can be one of the most convenient if it is done quickly and consistently. Many algorithms proposed is applied to gray level images. But. there are limits in method using only intensity information, so, many researchers has try to done research about using color information. In this paper, we propose the new edge detection method usign color information, implement the widely used algorithms and compared with them in performance. In result of experiment, we show that the proposed algorithm have better result in fine detail and shaded region of image.

• Annual Conference of KIPS
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• 2004.11a
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• pp.883-886
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• 2004

Many of facial feature extracting applications and systems have been developed in the field of face recognition systems and its application, and most of them use the eyes as a key-feature of human face. In this paper we show a simple and fast eye detection algorithm for embedded systems. The eyes are very important facial features because of the attribution they have. For example, we know the darkest regions in a face are the pair of pupils, and the eyes are always a pair and parallel. Using such attributors, our algorithm works well under various light conditions, size of face in image, and various pose such as panning and tilting. The main keys to develop this algorithm are the eyes' attribution that we can usually contemplate and easily find when we think about what is the attribution that the eyes have. With some constraints of the eyes and knowledge of the anthropometric human face, we detect human eye in an image, and the experimental results demonstrate successful eye detection.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1287-1294
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• 2004

Recently relationships between reliability measures and the coverage have been developed for evaluation of software reliability. Particularly the mean value function of the coverage-based software reliability growth model is important because of its key role in rep-resenting the software reliability growth. In this paper, we first review the problems of the existing mean value functions with respect to the assumptions on which they are based. Then a new mean value function is proposed. The new mean value function is developed for a general testing environment in which imperfect fault detection and repeated construct execution are allowed. Finally performance of the proposed model is empirically evaluated by applying it to a real data set.

• Journal of Sensor Science and Technology
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• v.21 no.2
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• pp.103-108
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• 2012

Radiofrequency(RF) signal is a key medium to the most of the present wireless communication devices including RF identification devices(RFID) and smart sensors. However, the most critical barrier to overcome in RFID application is in the failure rate in detection. The most notable improvement in the detection was from the introduction of EPC Class1 Gen2 protocol, but the fundamental problems in the physical properties of the RF signal drew less attention. In this work, we focused on the physical properties of the RF signal in order to understand the failure rate by noting the existence of the ground planes and noise sources in the real environment. By using the mathematical computation software, Maple, we simulated the distribution of the electromagnetic field from a dipole antenna when ground planes exist. Calculations showed that the dark area can be formed by interference. We also constructed a test system to measure the failure rate in the detection of a RFID transponder. The test system was composed of a fixed RFID reader and an EPC Class1 Gen2 transponder which was attached to a scanner to sweep in the x-y plane. Labview software was used to control the x-y scanner and to acquire data. Tests in the laboratory environment showed that the dark area can be as much as 43 %. One who wants to use RFID and smart sensors should carefully consider the extent of the dark area.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5238-5244
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• 2011

Recently, wireless sensor networks have become increasingly interesting areas over extensive application fields such as military, ecological, and health-related areas. Almost sensor networks have mission-critical tasks that requires very high security. Therefore, extensive work has been done for securing sensor networks from outside attackers, efficient cryptographic systems, secure key management and authorization, but little work has yet been done to protect these networks from inside threats. This paper proposed an method to select which nodes should activate their idle nodes as detectors to be able to watch all packets in the sensor network. Suggested method is modeled as optimization equation, and heuristic Greedy algorithm based simulation results are presented to verify my approach.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.6
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• pp.3-13
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• 2004

Kvarnstrom et al. ${in}^{[10]}$ proposed a rule protection scheme by using one-way hash function to protect rules in security systems over ubiquitous environment. Son et at. ${in}^{[5-6]}$ also prooposed a rule protection scheme for Snort, which is one of the most common IDS. These schemes provide security only for the header information but not for its contents. To solve this problem, this paper presents a scheme based on the symmetric cryptosystem over Snort not only for the header information but also contents. This paper uses the key management based on PCMCIA security module proposed ${by}^{[12]}$ for the symmetric cryptosystem. Our scheme could be adjusted to other security systems, which use the rule based detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1674-1688
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• 2023

The remarkable advancement of quantum steganography offers enhanced security for quantum communications. However, there is a significant concern regarding the potential misuse of this technology. Moreover, the current research on identifying malicious quantum steganography is insufficient. To address this gap in steganalysis research, this paper proposes a specialized quantum steganalysis algorithm. This algorithm utilizes quantum machine learning techniques to detect steganography in general quantum secure communication schemes that are based on pure states. The algorithm presented in this paper consists of two main steps: data preprocessing and automatic discrimination. The data preprocessing step involves extracting and amplifying abnormal signals, followed by the automatic detection of suspicious quantum carriers through training on steganographic and non-steganographic data. The numerical results demonstrate that a larger disparity between the probability distributions of steganographic and non-steganographic data leads to a higher steganographic detection indicator, making the presence of steganography easier to detect. By selecting an appropriate threshold value, the steganography detection rate can exceed 90%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2895-2921
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• 2018

Security has become one of the major concerns in mobile adhoc networks (MANETs). Data and voice communication amongst roaming battlefield entities (such as platoon of soldiers, inter-battlefield tanks and military aircrafts) served by MANETs throw several challenges. It requires complex securing strategy to address threats such as unauthorized network access, man in the middle attacks, denial of service etc., to provide highly reliable communication amongst the nodes. Intrusion Detection and Prevention System (IDPS) undoubtedly is a crucial ingredient to address these threats. IDPS in MANET is managed by Command Control Communication and Intelligence (C3I) system. It consists of networked computers in the tactical battle area that facilitates comprehensive situation awareness by the commanders for timely and optimum decision-making. Key issue in such IDPS mechanism is lack of Smart Learning Engine. We propose a novel behavioral based "Smart Multi-Instance Multi-Label Intrusion Detection and Prevention System (MIML-IDPS)" that follows a distributed and centralized architecture to support a Robust C3I System. This protocol is deployed in a virtually clustered non-uniform network topology with dynamic election of several virtual head nodes acting as a client Intrusion Detection agent connected to a centralized server IDPS located at Command and Control Center. Distributed virtual client nodes serve as the intelligent decision processing unit and centralized IDPS server act as a Smart MIML decision making unit. Simulation and experimental analysis shows the proposed protocol exhibits computational intelligence with counter attacks, efficient memory utilization, classification accuracy and decision convergence in securing C3I System in a Tactical Battlefield environment.