• International Journal of Safety
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• v.11 no.1
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• pp.6-10
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• 2012

This paper presents a study on the analysis for reducing the number of false alarms in fire detection system. In order to intelligent algorithm fuzzy logic is adopted in developing fire detection system to reduce false alarm. The intelligent fire detection algorithm compared and analyzed the fire and non-fire signatures measured in circuits simulating flame fire and smoldering fire. The algorithm has input variables obtained by fire experiment with K-type thermocouple and optical smoke sensor. Also triangular membership function is used for inference rules. And the antecedent part of inference rules consists of temperature and smoke density, and the consequent part consists of fire probability. A fire-experiment is conducted with paper, plastic, and n-heptane to simulate actual fire situation. The results show that the intelligent fire detection algorithm suggested in this study can more effectively discriminate signatures between fire and similar fire.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.46-51
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• 2005

Intelligent Space(ISpace) is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Simulations are carried out to evaluate the proposed performance. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.147-150
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• 2009

최근 새롭게 등장한 무선 센서 네트워크는 기존의 네트워크와는 다르게 통신 인프라가 없는 환경에서도 동작이 가능한 저전력 소출력의 무선 센서간의 네트워크를 형성하고 이들간의 정보 유통이 이루어진다. 무선 센서 네트워크는 열린 환경에서 배치되기 때문에 물리적 공격에 취약하다. 공격자는 손쉽게 노드들을 포획할 수 있으며 포획된 노드를 통해 허위 보고서를 네트워크에 주입할 수 있다. 허위 보고서 삽입 공격은 허위 경보를 유발할 뿐만 아니라 네트워크의 제한된 에너지를 고갈시킨다. 이러한 허위 보고서를 조기에 탐지 및 폐기하기 위하여 Yu와 Guan은 동적 여과 프로토골(dynamic on-route filtering scheme)를 제안하였다. 그러나 무선 센서 노드는 오직 제한된 진력자원으로 이루어져 있기 때문에 전력보존과 전력관리가 중요시 여겨진다. 본 논문에서는 동적 여과 프로토콜에서 허위 보고서 주입 공격에 대한 충분한 보안 강도 제공과 에너지 효율성을 위한 기법을 제안한다.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.525-527
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• 1999

In this paper, we propose the target tracking system using fuzzy basis function expansion (FBFN) based on genetic algorithm (GA). In general, the objective of target tracking is to predict the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical method, the parameter uncertainty and the environmental noise may deteriorate the performance of the system. To resolve these problems, we apply artificial intelligent technique to the tracking control of moving targets. The proposed method combines the advantages of both traditional and intelligent technique. The result of numerical simulation shows the effectiveness of the proposed method.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.780-785
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• 2003

Maintaining track tension in tracked vehicles minimizes the excessive load on the tracks and prevents the peal-off of tracks from the road-wheel, and adequately guarantees the stable and improved driving of the tracked vehicles. However, the track tension cannot be easily measured due to the limitation in the sensor technology, harsh environment, etc. In this study, the track tension is estimated in real-time from the measurable signals of tracked vehicles and controlled based on a fuzzy logic controller. The proposed control system is implemented on tracked vehicles and its performance is evaluated under various driving conditions.

• Journal of Sensor Science and Technology
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• v.20 no.3
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• pp.151-155
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• 2011

A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.133-139
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• 2013

This paper proposes a vision-based indoor localization method for autonomous vehicles. A single upward-facing digital camera was mounted on an autonomous vehicle and used as a vision sensor to identify artificial landmarks and any natural corner features. An interest point detector was used to find the natural features. Using an optical flow detection algorithm, information related to the direction and vehicle translation was defined. This information was used to track the vehicle movements. Random noise related to uneven light disrupted the calculation of the vehicle translation. Thus, to estimate the vehicle translation, a Kalman filter was used to calculate the vehicle position. These algorithms were tested on a vehicle in a real environment. The image processing method could recognize the landmarks precisely, while the Kalman filter algorithm could estimate the vehicle's position accurately. The experimental results confirmed that the proposed approaches can be implemented in practical situations.

• Proceedings of the KIPE Conference
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• 2003.11a
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• pp.186-189
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• 2003

This paper is proposed to position and speed control of interior permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. A gopinath observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of IPMSM, that employs a d-q rotating reference frame attached to the rotor, A gopinath observer is implemented to compute the speed and position feedback signal. The validity of the proposed scheme is confirmed by various response characteristics.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.438-439
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• 2011

Magnetic levitation control system of a metal ball was designed using combined PID and fuzzy logic, in which two electromagnets are used to control the vertical and horizontal position of the ball. Single synchronization coil sensor was used to detect the vertical position. Electric power is differentially supplied to two electromagnets so that the ball can move horizontally. In the experiment 25 cm diameter metal ball was levitated and successfully controlled to move horizontally.