• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.669-670
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• 2008

In this paper, we present a real-time system to detect abnormal events on gas pipes, based on the signals which are observed through the audio sensors attached on them. First, features are extracted from these signals so that they are robust to noise and invariant to the distance between a sensor and a spot at which an abnormal event like an attack on the gas pipes occurs. Then, a classifier is constructed to detect abnormal events using neural networks. It is a combination of two neural network models, a Gaussian mixture model and a multi-layer perceptron, for the reduction of miss and false alarms. The former works for miss alarm prevention and the latter for false alarm prevention. The experimental result with real data from the actual gas system shows that the proposed system is effective in detecting the dangerous events in real-time with an accuracy of 92.9%.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.160.2-160
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• 2001

This paper presents an individual cylinder spark advance control strategy based upon the location of peak pressure (LPP) in spark ignition engines using artificial neural networks. The LPP is estimated using a feedforward multi-layer perceptron network (MLPN), which needs only five samples of output voltage from the cylinder pressure sensor. The cyclic variation of LPP restricts the gain of the feedback controller, and results in poor regulation performance during the transient operation of the engine. The transient performance of the spark advance controller is improved by adding a feedforward controller which reflects the abrupt changes of the engine operating conditions such as engine speed and manifold absolute pressure (MAP)...

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.41-48
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• 2007

Latest advances in network sensor technology and state of the art of mobile robot, and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. In this study, as the preliminary step for developing a multi-purpose "Intelligent Space" platform to implement advanced technologies easily to realize smart services to human. We will give an explanation for the ISpace system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. Instead we will focus on the main results with relevance to the DIND data fusion with CI of Intelligent Space. We will conclude by discussing some possible future extensions of ISpace. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions tracking multiple objects, human detection and motion assessment, with the results from the simulations run.

• Journal of Sensor Science and Technology
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• v.11 no.4
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• pp.239-246
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• 2002

In this paper a new design of multi-layer perceptron(MLP) for camera calibration is proposed. Most existing techniques determine a transformation from 3D spatial points to their image points and camera parameters are tried to be estimated from the transformation. The technique proposed here, on the other hand, determines rays of sight uniquely from image points and parameters are estimated from the relationship using an MLP. By this approach projection and back-projection can be done more straightforwardly. Being based on a geometric model, a network design process becomes less ambiguous, which is a clear merit compared to other neural net based techniques. An MLP designed according to the technique proposed showed fast and stable learning in tests under various conditions.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.510-513
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• 2007

무선 센서 네트워크의 표준인 IEEE 802.15.4는 전력소모를 줄이기 위해 비컨을 사용하는 슈퍼프레임 구조를 지원하는데 이를 멀티 홈 네트워크 환경에 적용시킬 경우 비컨의 충돌이 발생한다. 네트워크의 정보를 담은 비컨이 충돌되면 노드간의 통신에 장애가 발생하고 새로 네트워크에 참여하고자하는 노드도 수용할 수 없게 된다. 이와 같은 문제를 개선하고자 본 논문에서는 현재 제안되어있는 비컨 충돌 회피 방법들을 분석하고 이를 바탕으로 이웃 노드의 정보를 이용하여 다수의 센서 노드가 중복된 시간에 비컨을 전송할 수 있도록 하여 전체 네트워크에 비컨이 전송되는 시간을 줄이는 방법을 제시한다.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1999.05a
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• pp.169-172
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• 1999

Recently, the wavelet transform has been a new and powerful tool for signal processing. It is more suitable specially for the feature extraction and detection of non-stationary signals than traditional methods such as, the Fourier Transform(FT), the Fast Fourier Transform(FFT) and the Least Square Method etc. because of the characteristic of the multi-scale analysis and time-frequency domain localization. The wavelet transform has been developed for the analysis of PD pulse signal to raise in the progress of insulation degradation. In this paper, the wavelet transform was applied to one foundational method for feature extraction. For the obtain experimental data, a computer-aided partial discharge measurement system with a single acoustic sensor was used. If we are applying to the neural network method the accumulated data through the extracted feature, it is expected that we can detect the PD pulse signal in the insulation materials on the on-line.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.1
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• pp.54-59
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• 2006

The smart space is composed of the wire and/or wireless network, multi-sensor-based environment, and many various controllers. For the smart space, this paper presents a new design method of multirate digital decentralized controller using the intelligent digital redesign technique. In specific, the proposed method is based on the delta-operator and the multirate sampling and takes the form of the LMIs. To shows the feasibility of the suggested method, the computer simulations for Heating, ventilating, and ai. conditioning (HVAC) system are provided.

• Transactions of the Korean Society of Automotive Engineers
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• v.1 no.2
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• pp.49-59
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• 1993

A new signal processing technique is applied to four-cylinder spark and compression ignition engines for the diagnosis of power faults inside the cylinders. This technique utilizes two-sided directional power spectra(예S) of complex vibration signals measured from engine blocks as the patterns for engine cylinder power faults. The dPSs feature that they give not only the frequency contents but also the directivity of the engine block motion. For the automatic detection/diagnosis of cylinder power faults, pattern recognition method using multi-layer neural networks is employed. Experimental results show that the sucess rate for diagnosis of cylinder power faults using dPSs is higher than that using the conventional one-sided power spectra. The proposed technique is also tested to check the robustness to the sensor position and the engine rotational speed.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06b
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• pp.223-227
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• 2007

무선 센서 네트워크는 유비쿼터스 컴퓨팅에서 생활환경과 컴퓨터 사이의 중계자 역할을 하는 매우 중요한 연구 분야이다. 매우 제약적인 자원 환경에서 동작하여야 하는 센서 노드의 특성 때문에 제한된 자원을 효율적으로 관리할 수 있는 센서 노드용 운영체제가 요구된다. 또한 센서 네트워크는 외부 물리 환경의 변화에 반응하여 동작하는 시스템이기 때문에 여러 이벤트를 동시에 재빠르게 처리 할 수 있는 기능을 제공해야 하며, 센서네트워크 어플리케이션 프로그래머에게 이러한 반응형 어플리케이션 개발이 용의하도록 하는 프레임워크를 제공해야 한다. 이를 위해 본 논문에서는 반응형 시스템에 적합한 상태머신 프레임 워크를 멀티쓰레드 기반의 Nano-Qplus 운영체제 상에서 센서 네트워크의 자원적 제약을 준수하면서 효율적으로 이벤트를 처리 할 수 있는 프레임워크를 지원하는 센서네트워크용 운영체제의 구조를 제안한다.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.500-501
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• 2007

Automation systems for higher performance and efficiency in railway electrification systems are driving ever more demanding needs for new condition monitering systems which can consist of sensors connected to the substation and catenary systems. This paper reviews the recently developed condition monitering system, based on a IP network-based multi-agent system, wireless communications and sensor networks for railway electrification system. A new concept for information management, condition monitoring and control of power transmission are considered as railway automation in electrification system.