• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.179-180
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• 2006

The real time monitoring of the power systems covering wide area are essential for the stable operation and control of the power system. Synchronized phasor measurement is a key for the precise monitoring and control of the power systems. In this paper, to suggest an appropriate network topology of Power Infrastructure Defense System(PIDS) and to estimate the maximum network bandwidth with using the network analyzer, we simulate a PIDS and analyze the network traffic.

• 산업경영시스템학회지
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• 제12권20호
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• pp.71-76
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• 1989

In this paper, GERT network in modeled to improve the network of manufacturing process with feedback loop. A lot of Information on the GERT network can be derived from the equivalent W-function and MGF(moment generating function) using Mason's rule. These equations are used in calculating the variations of the performance measure and in improving the system performance. System improvement in manufacturing process is achieved by increasing the equivalent probabilities of each branches and by decreasing the expected equivalent time.

• 융합보안논문지
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• 제9권2호
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• pp.33-39
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• 2009

네트워크 보안시스템을 단일 요소로 구분하여 점검하고 있는 현실의 문제점을 개선하기 위해 본 논문은 네트워크 보안시스템 점검은 취약성을 찾는 것이 아니라, 네트워크 보안시스템을 이루는 각 보안장비가 유기적으로 잘 작동하는지 종합적으로 점검하는 것임에 착안 네트워크 보안시스템을 점검하는 자동화 방법을 제안하고 이를 구현하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.42.2-42
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• 2002

We discuss a neural network solver for the inverse optimization problem. The problem is that find functional relations between input and output data, which are include defects. Finding the relations, predictions of the defect parts are also required. The part of finding the defects in the input data is an inverse problem . We consider the meanings to solve the problem on the neural network system at first. Next, we consider the network structure of the system, the learning scheme of the network, and at last, examine the precision on the numerical calculations. In the paper, we proposed the high-precision learning method for plural three-layer neural network system that is series-connect...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.436-439
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• 1995

In this paper we present a method to construct fuzzy model with multi-dimension input membership function, which can construct fuzzy inference system on one node of the network directly. This method comes from a common framework called Universal Learning Network (ULN). The fuzzy model under the framework of ULN is called Universal Learning Network-based Fuzzy Inference System (ULNFIS), which possesses certain advantages over other networks such as neural network. We also introduce how to imitate a real system with ULN and a control scheme using ULNFIS.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.193-194
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• 2006

In this paper, the SPINS, a sensor network security mechanism, was researched to design a system to be applied to home network structure and check the security of which degree was ensured by a virtual network of home networking middleware. Sensor Network security mechanism SPINS provides data confidentiality and authentication by SNEP, and provides authenticated broadcast by ${\mu}TESLA$. We designed the system that applied SPINS to home networking middleware basic structure.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2007년도 하계종합학술대회 논문집
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• pp.131-132
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• 2007

In this paper, we designed and implemented bio-signals transmission and storage system using wireless sensor network based on ZigBee. Wireless sensor network is organized with routing protocol based on tree structure. The data is transmitted to monitoring system based on SIP. ZigBee will be used as various combinations with other wireless network technologies for application purposes.

• 대한전기학회논문지
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• 제37권9호
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• pp.663-670
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• 1988

Advances in VLSI technology have made it possible to have a larger number of processing elements to be included in highly parallel processor system. A system with a large number of processing elements and memory requires a complex data path. Multistage Interconnection networks(MINS) are useful in providing programmable data path between processing elements and memory modules in multiprocessor system. In this thesis, the performance of MINS for the star network has been analyzed and compared with other networks, such as generalized shuffle network, delta network, and referenced crossbar network.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2009년도 정보통신설비 학술대회
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• pp.136-137
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• 2009

In this paper, we introduce UFSN(Underground Facility Sensor Network) in order to build the intelligent management system for the underground facility and drainage in convergence with ubiquitous technologies and propose the energy harvesting system for UFSN.

• 한국컴퓨터정보학회논문지
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• 제24권5호
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• pp.149-156
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• 2019

The existing subtract image based intrusion detection system for CCTV digital images has a problem that it can not distinguish intruders from moving backgrounds that exist in the natural environment. In this paper, we tried to solve the problems of existing system by designing real - time intrusion detection system for CCTV digital image by combining subtract image based intrusion detection method and background learning artificial neural network technology. Our proposed system consists of three steps: subtract image based intrusion detection, background artificial neural network learning stage, and background artificial neural network evaluation stage. The final intrusion detection result is a combination of result of the subtract image based intrusion detection and the final intrusion detection result of the background artificial neural network. The step of subtract image based intrusion detection is a step of determining the occurrence of intrusion by obtaining a difference image between the background cumulative average image and the current frame image. In the background artificial neural network learning, the background is learned in a situation in which no intrusion occurs, and it is learned by dividing into a detection window unit set by the user. In the background artificial neural network evaluation, the learned background artificial neural network is used to produce background recognition or intrusion detection in the detection window unit. The proposed background learning intrusion detection system is able to detect intrusion more precisely than existing subtract image based intrusion detection system and adaptively execute machine learning on the background so that it can be operated as highly practical intrusion detection system.