• 스마트미디어저널
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• 제6권3호
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• pp.95-102
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• 2017

A large volume of research has been devoted to the development of security tools for protecting the Smart Grid systems, however the most of them have not taken the Availability, Integrity, Confidentiality (AIC) security triad model, not like CIA triad model in traditional Information Technology (IT) systems, into account the security measures for the electricity control systems. Thus, this study would propose a novel security framework, an abnormal behavior detection system, to maximize the availability of the control systems by considering a unique set of characteristics of the systems.

• 융합신호처리학회논문지
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• 제12권3호
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• pp.212-216
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• 2011

태양광 발전 시스템의 고장검출은 고장으로 인해 발생되는 기술적 및 경제적 손실을 최대한 줄이기 위한 첨단 기술로 각광을 받고 있다. 본 논문은 푸리에 신경회로망과 확률론적 의사결정법을 이용한 태양광 발전 시스템의 새로운 고장진단 알고리즘을 제안한다. 우선 태양광 시스템의 동적 모델링을 위하여 최급강하 기반 최적화 기법을 통해 신경회로망 모델을 구성하며 GLRT 알고리즘을 이용하여 태양광 시스템의 확률론적 고장검출 기법을 제안한다. 제안한 고장검출 알고리즘의 타당성 검증을 위하여 태양광 고장검출 테스트베드를 제작하여 실시간 실험을 실시하였으며 이 때 태양광으로부터의 신호는 직류 전력선 통신을 이용하였다.

• 전력전자학회논문지
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• 제27권2호
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• pp.100-105
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• 2022

This paper applies the arc detection algorithm to prevent the false detection in photo voltaic series arc detection circuit, which is required not only to detect the series arc quickly, but also not falsely detect the arc for the non-arc noise. For this purpose, this study proposes a rapid and preventive false detection method of single peak noise and short noise signals. First, to prevent false detection by single peak noise, Discrete wavelet transform (DWT)-based characteristic parameters are applied to determine the shape and the amplitude of the noise. In addition, arc fault detection within a few milliseconds is performed with the DWT iterative algorithm to quickly prevent false detection for short noise signals, considering the continuity of serial arc noise. Thus, the method operates not only to detect series arc, but also to avoid false arc detection for peak and short noises. The proposed algorithm is applied to real-time serial arc detection circuit based on the TMS320F28335 DSP. The serial arc detection and peak noise filtering performances are verified in the built simulated arc test facility. Furthermore, the filtering performance of short noise generated through DC switch operation is confirmed.

• 한국전자통신학회논문지
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• 제8권2호
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• pp.339-344
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• 2013

공항 경비보안은 공항의 시설 및 자산을 도난, 범죄 등으로부터 예방하기 위하여 살피고 지키는 활동이다. 이러한 활동을 효율적으로 할 수 있도록 지원하는 시스템을 보안시스템이라 할 수 있다. 보안시스템은 보안센터시스템, CCTV시스템, 출입통제 시스템, 침입감지시스템, 경비통신시스템, 경고방송시스템, 보안네트워크시스템, 외곽침입감지시스템, 검색시스템 및 정보보안시스템이 있으며 이에 대하여 살펴보고자 한다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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• pp.666-669
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• 2008

A number of intrusion detection systems have been developed to detect intrusive activity on individual hosts and networks. The systems developed rely almost exclusively on a software approach to intrusion detection analysis and response. In addition, the network systems developed apply a centralized approach to the detection of intrusive activity. The problems introduced by this approach are twofold. First the centralization of these functions becomes untenable as the size of the network increases.

• 정보와 통신
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• 제24권11호
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• pp.25-36
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• 2007

Deep packet inspection is widely recognized as a powerful way which is used for intrusion detection systems for inspecting, deterring and deflecting malicious attacks over the network. Fundamentally, almost intrusion detection systems have the ability to search through packets and identify contents that match with known attach. In this paper we survey the deep packet inspection implementations techniques, research challenges and algorithm. Finally, we provide a comparison between the different applied system.

• Journal of Animal Science and Technology
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• 제64권5호
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• pp.813-829
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• 2022

Internal and external defects of eggs should be detected to prevent cross-contamination of intact eggs by abnormal eggs during storage. Emerging detection technologies for abnormal eggs were introduced as an alternative to human inspection. The advanced technologies could rapidly detect abnormal eggs. Abnormal egg detection technologies using acoustic response, machine vision, and spectroscopy have been commercialized in the poultry industry. Non-destructive egg quality assessment methods meanwhile could preserve the value of eggs and improve detection efficiency. In order to improve detection efficiency, it is essential to select a proper algorithm for classifying the types of abnormal eggs. This review deals with the performance of the detection technologies for various types of abnormal eggs in recently published resources. In addition, the discriminant methods and detection algorithms of abnormal eggs reported in the published literature were investigated. Although the majority of the studies were conducted on a laboratory scale, the developed detection technologies for internal and external defects in eggs were technically feasible to obtain the excellent detection accuracy. To apply the developed detection technologies to the poultry industry, it is necessary to achieve the detection rates required from the industry.

• International journal of advanced smart convergence
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• 제9권3호
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• pp.232-238
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• 2020

In this paper, we study on aerial objects detection and position estimation algorithm for the safety of UAV that flight in BVLOS. We use the vision sensor and LiDAR to detect objects. We use YOLOv2 architecture based on CNN to detect objects on a 2D image. Additionally we use a clustering method to detect objects on point cloud data acquired from LiDAR. When a single sensor used, detection rate can be degraded in a specific situation depending on the characteristics of sensor. If the result of the detection algorithm using a single sensor is absent or false, we need to complement the detection accuracy. In order to complement the accuracy of detection algorithm based on a single sensor, we use the Kalman filter. And we fused the results of a single sensor to improve detection accuracy. We estimate the 3D position of the object using the pixel position of the object and distance measured to LiDAR. We verified the performance of proposed fusion algorithm by performing the simulation using the Gazebo simulator.

• 한국통신학회논문지
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• 제35권2C호
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• pp.229-237
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• 2010

기존 SM MIMO 시스템을 위한 신호검출 기법인 OSIC 계열의 기법과 준최적 신호검출 기법인 QRD-M 기법을 협력적 공간다중화 기반 상향링크 다중사용자 시스템에 적용할 경우 사용자별 신호의 검출성능에 차이가 발생한다. 본 논문에서는 협력적 공간다중화 기반 상향링크 다중사용자 시스템을 위한 사용자간별 검출성능 차이가 발생하지 않으면서 최적 신호검출 기법과 유사한 성능을 보이는 신호검출 기법을 제안한다. 제안된 신호검출 기법의 연산복잡도는 QPSK 변조에서는 QRD-M과 유사하지만, 16-QAM, 64-QAM과 같이 높은 차수의 변조방식의 시스템에서는 QRD-M에 비해 매우 낮은 연산복잡도를 가진다.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.603-622
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• 2023

Human error (HE) is an important concern in safety-critical systems such as nuclear power plants (NPPs). HE has played a role in many accidents and outage incidents in NPPs. Despite the increased automation in NPPs, HE remains unavoidable. Hence, the need for HE detection is as important as HE prevention efforts. In NPPs, HE is rather rare. Hence, anomaly detection, a widely used machine learning technique for detecting rare anomalous instances, can be repurposed to detect potential HE. In this study, we develop an unsupervised anomaly detection technique based on generative adversarial networks (GANs) to detect anomalies in manually collected surveillance data in NPPs. More specifically, our GAN is trained to detect mismatches between automatically recorded sensor data and manually collected surveillance data, and hence, identify anomalous instances that can be attributed to HE. We test our GAN on both a real-world dataset and an external dataset obtained from a testbed, and we benchmark our results against state-of-the-art unsupervised anomaly detection algorithms, including one-class support vector machine and isolation forest. Our results show that the proposed GAN provides improved anomaly detection performance. Our study is promising for the future development of artificial intelligence based HE detection systems.