• 전력전자학회:학술대회논문집
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• 전력전자학회 2000년도 전력전자학술대회 논문집
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• pp.111-114
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• 2000

Harmonics and fundamental reactive power of nonlinear loads in serious unbalanced power condition are compensated by current synchronous detection(CSD) theory which is also acceptable for single phase power system, but the CSD theory is not suitable any more in case of controlled independently harmonics and reactive component. Therefore a new algorithm the extended current synchronous detection (ECSD)theory for a three phase active power filter based on decomposition of fundamental reactive distorted components is proposed in this paper. The proposed ECSD theory is simulated and tested comparison with a few power theories under asymmtrical condition in power system.

• 제어로봇시스템학회논문지
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• 제22권9호
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• pp.699-704
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• 2016

In this paper, we propose a development method for a drowsiness detection system using retinex theory and edge information for vehicle safety. Detection of a drowsy state of a driver is very important because the drowsiness of driver is often the main cause of many car accidents. After acquiring an image of the entire face, we executed the pre-process step using the retinex theory. We then applied a technique for the detection of the white pixels using edge information. Experimental results showed that the proposed method improved the accuracy of detecting drowsiness to nearly 98%, and can be used to prevent a car accident caused by the driver's drowsiness.

• 전자공학회논문지CI
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• 제40권1호
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• pp.39-49
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• 2003

멀티미디어에 삽입된 워터마크의 검출은 저작권 보호 및 인증 분야에서 매우 중요한 역할을 한다. 최근 워터마크의 검출에 많이 사용되는 유사도 기반 알고리즘은 상가성 방법을 제외한 워터마크 삽입 방법에 대해서는 효과적이지 못한 단점을 가진다. 따라서 본 논문에서는 웨이블릿 변환 영역에서 상승적 방법에 의하여 삽입된 워터마크에 대한 효율적인 검출 알고리즘을 제안하였다. 제안한 워터마크 검출 알고리즘은 통계적 판단 이론에 따라 Bayes 판단 이론, Neyman-Pearson 정의, 및 웨이블릿 계수들의 확률 분포 모델을 기반으로 도출되어서, 주어진 오류 검출 확률에 대하여 간과 검출 확률을 최소화할 수 있다. 제안한 검출 알고리즘의 성능 평가는 견고성 측면에서 수행되었고, 실험 결과로부터 제안한 알고리즘이 유사도 기반 알고리즘에 비하여 우수한 성능을 나타냄을 확인하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.823-826
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• 2000

Motion detection is an important step in computer vision and image processing. Traditional motion detection systems are classified into two categories, namely, feature based and gradient based. In feature based motion detection, features in consecutive frames are detected and matched. Gradient based methods assume that the intensity varies linearly and locally. The method, which we propose, is neither feature nor gradient based but uses the electric field theory. The pixels in an image are modeled as point charges and motion is detected by using the variations between the two electric fields produced by the charges corresponding to the two images.

• 전력전자학회논문지
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• 제6권4호
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• pp.341-347
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• 2001

전류 동기 검출법은 3상이 불평형된 전원 시스템 하에서도 전원전류를 평형된 정현파로 보상해 줄 뿐 만 아니라 순시전력이론에 비해서 단상에도 적용가능한 이론이다. 그러나 종전의 전류 동기 검출법은 능동전력필터가 고조파 성분과 기본파 무효성분을 독립 제어하는 하이브리드형 능동전력필터 시스템 등에는 적용하기 곤란하다. 따라서 본 연구에서는 불평형 전원 시스템 하에서도 비선형 부하전류를 유효성분, 기본파 무효성분 그리고 왜형성분으로 분해하여 독립제어 가능한 확장된 전류 동기 검출법을 제시하였다. 본 연구에서 제시한 방법의 타당성을 입증하기 위해, 불평형 교류 전원 하에서 평균전력이론, 동기 전류 검출법 그리고 제안된 방법을 실험에 의하여 비교검토하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권10호
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• pp.3965-3982
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• 2015

Event detection is one of the key issues in many wireless sensor network (WSN) applications. The uncertainties that are derived from the instability of sensor node, measurement noise and incomplete sampling would influence the performance of event detection to a large degree. Many of the present researches described the sensor readings with crisp values, which cannot adequately handle the uncertainties inhered in the imprecise sensor readings. In this paper, a fault-tolerant event detection algorithm is proposed based on Dempster-Shafer (D-S) theory (also called evidence theory). Instead of crisp values, all possible states of the event are represented by the Basic Probability Assignment (BPA) functions, with which the output of each sensor node are characterized as weighted evidences. The combination rule was subsequently applied on each sensor node to fuse the evidences gathered from the neighboring nodes to make the final decision on whether the event occurs. Simulation results show that even 20% nodes are faulty, the accuracy of the proposed algorithm is around 80% for event region detection. Moreover, 97% of the error readings have been corrected, and an improved detection capability at the boundary of the event region is gained by 75%. The proposed algorithm can enhance the detection accuracy of the event region even in high error-rate environment, which reflects good reliability and robustness. The proposed algorithm is also applicable to boundary detection as it performs well at the boundary of the event.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2732-2753
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• 2019

With the application of wireless sensor networks in the fields of ecological observation, defense military, architecture and urban management etc., the security problem is becoming more and more serious. Characteristics and constraint conditions of wireless sensor networks such as computing power, storage space and battery have brought huge challenges to protection research. Inspired by the danger theory in biological immune system, this paper proposes an intrusion detection model for wireless sensor networks. The model abstracts expressions of antigens and antibodies in wireless sensor networks, defines meanings and functions of danger signals and danger areas, and expounds the process of intrusion detection based on the danger theory. The model realizes the distributed deployment, and there is no need to arrange an instance at each sensor node. In addition, sensor nodes trigger danger signals according to their own environmental information, and do not need to communicate with other nodes, which saves resources. When danger is perceived, the model acquires the global knowledge through node cooperation, and can perform more accurate real-time intrusion detection. In this paper, the performance of the model is analyzed including complexity and efficiency, and experimental results show that the model has good detection performance and reduces energy consumption.

• Journal of Power Electronics
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• 제14권6호
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• pp.1303-1313
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• 2014

Dynamic behavior of the harmonic detection part of an active power filter (APF) has an essential role in filter compensation performances during transient conditions. Instantaneous power (p-q) theory is extensively used to design harmonic detectors for active filters. Large overshoot of p-q theory method deteriorates filter response at a large and rapid load change. In this study the harmonic estimation of an APF during transient conditions for balanced three-phase nonlinear loads is conducted. A novel fuzzy instantaneous power (FIP) theory is proposed to improve conventional p-q theory dynamic performances during transient conditions to adapt automatically to any random and rapid nonlinear load change. Adding fuzzy rules in p-q theory improves the decomposition of the alternating current components of active and reactive power signals and develops correct reference during rapid and random current variation. Modifying p-q theory internal high-pass filter performance using fuzzy rules without any drawback is a prospect. In the simulated system using MATLAB/SIMULINK, the shunt active filter is connected to a rapidly time-varying nonlinear load. The harmonic detection parts of the shunt active filter are developed for FIP theory-based and p-q theory-based algorithms. The harmonic detector hardware is also developed using the TMS320F28335 digital signal processor and connected to a laboratory nonlinear load. The software is developed for FIP theory-based and p-q theory-based algorithms. The simulation and experimental tests results verify the ability of the new technique in harmonic detection of rapid changing nonlinear loads.

• Computers and Concrete
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• 제2권6호
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• pp.481-498
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• 2005

A wavelet based approach is proposed for structural damage detection in beams, plate and delamination of composite plates. Wavelet theory is applied here for crack identification of a beam element with a transverse on edge non-propagating open crack. Finite difference method was used for generating a general displacement equation for the cracked beam in the first example. In the second and third example, damage is detected from the deformed shape of a loaded simply supported plate applying the wavelet theory. Delamination in composite plate is identified using wavelet theory in the fourth example. The main concept used is the breaking down of the dynamic signal of a structural response into a series of local basis function called wavelets, so as to detect the special characteristics of the structure by scaling and transformation property of wavelets. In the light of the results obtained, limitations of the proposed method as well as suggestions for future work are presented. Results show great promise of wavelet approach for damage detection and structural health monitoring.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권8호
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• pp.4043-4060
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• 2017

Network Intrusion Detection (NID), an important topic in the field of information security, can be viewed as a pattern recognition problem. The existing pattern recognition methods can achieve a good performance when the number of training samples is large enough. However, modern network attacks are diverse and constantly updated, and the training samples have much smaller size. Furthermore, to improve the learning ability of SVM, the research of kernel functions mainly focus on the selection, construction and improvement of kernel functions. Nonetheless, in practice, there are no theories to solve the problem of the construction of kernel functions perfectly. In this paper, we effectively integrate the advantages of the radial basis function kernel and the polynomial kernel on the notion of the game theory and propose a novel kernel SVM algorithm with game theory for NID, called GTNID-SVM. The basic idea is to exploit the game theory in NID to get a SVM classifier with better learning ability and generalization performance. To the best of our knowledge, GTNID-SVM is the first algorithm that studies ensemble kernel function with game theory in NID. We conduct empirical studies on the DARPA dataset, and the results demonstrate that the proposed approach is feasible and more effective.