• IE interfaces
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• v.22 no.2
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• pp.185-191
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• 2009

In this study, we propose an improved group location tracking scheme (GLS) called integrated GLS (IGLS) which, in addition to the group location registration of the GLS, sends an integrated group registration message to a virtual visitor location register (VVLR) instead of sending an individual group registration message. This integrated procedure of proposed scheme leads registration cost of group registration and group location registration to be reduced significantly. Numerical results demonstrate that our proposed IGLS outperforms conventional GLS and delayed GLS (dGLS). The IGLS can be applied effectively on public transportation systems such as subway, train and bus.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.211-217
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• 1998

Many practical control problems for the complex, uncertain or large-scale plants, need to simultaneously achieve a number of objectives, which may conflict or compete with each other. If the conventional optimization methods are applied to solve these control problems, the solution process may be time-consuming and the resulting solution would ofter lose its original meaning of optimality. Nevertheless, the human operators usually performs satisfactory results based on their qualitative and heuristic knowledge. In this paper, we investigate the control strategies of the human operators, and propose a fuzzy model-based multi-objective satisfactory controller. We also apply it to the automatic train operation(ATO) system for the magnetically levitated vehicles(MAGLEV). One of the human operator's strategies is to predict the control result in order to find the meaningful solution. In this paper, Takagi-Sugeno fuzzy model is used to simulated the prediction procedure. Another str tegy is to evaluate the multiple objectives with respect to their own standards. To realize this strategy, we propose the concept of a satisfactory solution and a satisfactory control scheme. The MAGLEV train is a typical example of the uncertain, complex and large-scale plants. Moreover, the ATO system has to satisfy multiple objectives, such as seed pattern tracking, stop gap accuracy, safety and riding comfort. In this paper, the speed pattern tracking controller and the automatic stop controller of the ATO system is designed based on the proposed control scheme. The effectiveness of the ATO system based on the proposed scheme is shown by the experiments with a rotary test bed and a real MAGLEV train.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.2
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• pp.129-138
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• 2017

This paper has been shown for the extraction of Doppler signature from the radar signal for an air-breathing targets tracked in the ground radar. For the extractions, a Doppler resolution is confirmed from mathematical modeling of PT(pulse train) waveform. Doppler signatures of air-breathing target are varied to radar aspect angle of engine and are determined from physical parameter of jet engine. To confirm such Doppler signatures, the radar signal reflected from the air-breathing target is obtained by our radar signal storage. After this extraction, radar aspect angle of engine has estimated from tracking information. Relative differences of Doppler signatures to radar aspect angle of engine is verified from these results and Doppler profiles for radar target identification appliance are presented.

• Journal of Veterinary Science
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• v.23 no.1
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• pp.17.1-17.10
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• 2022

Background: Inspection of livestock farms using surveillance cameras is emerging as a means of early detection of transboundary animal disease such as African swine fever (ASF). Object tracking, a developing technology derived from object detection aims to the consistent identification of individual objects in farms. Objectives: This study was conducted as a preliminary investigation for practical application to livestock farms. With the use of a high-performance artificial intelligence (AI)-based 3D depth camera, the aim is to establish a pathway for utilizing AI models to perform advanced object tracking. Methods: Multiple crossovers by two humans will be simulated to investigate the potential of object tracking. Inspection of consistent identification will be the evidence of object tracking after crossing over. Two AI models, a fast model and an accurate model, were tested and compared with regard to their object tracking performance in 3D. Finally, the recording of pig pen was also processed with aforementioned AI model to test the possibility of 3D object detection. Results: Both AI successfully processed and provided a 3D bounding box, identification number, and distance away from camera for each individual human. The accurate detection model had better evidence than the fast detection model on 3D object tracking and showed the potential application onto pigs as a livestock. Conclusions: Preparing a custom dataset to train AI models in an appropriate farm is required for proper 3D object detection to operate object tracking for pigs at an ideal level. This will allow the farm to smoothly transit traditional methods to ASF-preventing precision livestock farming.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.274-286
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• 2022

Multi-object tracking has been studied for a long time under computer vision and plays a critical role in applications such as autonomous driving and driving assistance. Multi-object tracking techniques generally consist of a detector that detects objects and a tracker that tracks the detected objects. Various publicly available datasets allow us to train a detector model without much effort. However, there are relatively few publicly available datasets for training a tracker model, and configuring own tracker datasets takes a long time compared to configuring detector datasets. Hence, the detector is often developed separately with a tracker module. However, the separated tracker should be adjusted whenever the former detector model is changed. This study proposes a system that can train a model that performs detection and tracking simultaneously using only the detector training datasets. In particular, a Siam network with augmentation is used to compose the detector and tracker. Experiments are conducted on public datasets to verify that the proposed algorithm can formulate a real-time multi-object tracker comparable to the state-of-the-art tracker models.

• Journal of the Ergonomics Society of Korea
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• v.29 no.4
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• pp.647-654
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• 2010

In a service environment, the spatial layout is an important factor that has a great impact on customers' behavioral characteristics including wayfinding and purchasing. Previous studies have shown a gap between marketing, focusing solely on profitability and satisfaction, and architecture, looking only into efficiency of pedestrian flow. To balance such disparity, this study suggests an integrated approach for assessing behavioral patterns in complex service environments. With the objective that complex service environments should aim to increase its profitability and efficiency while guaranteeing customer satisfaction, quantitative metrics was developed for evaluation. The metrics was defined to use data from behavior observation including path tracking, population counting, and gaze analysis, while previous studies have relied on abstract survey methods that were prone to sampling errors and loss of data. For validation of the metrics in a real world setting, a case study was conducted at 4 train stations in Korea. In the case study, experiments were conducted to gather the required data in all 4 train stations, while their physical layouts were also analyzed. With the results from the case study, comparative evaluation of the 4 train stations in terms of behavioral efficiency was possible, together with a discussion on the effect of their physical settings.

• International Journal of Railway
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• v.4 no.4
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• pp.93-96
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• 2011

The basic element of the EMS suspension is the electromagnet system, which suspends the vehicle without contact by attracting forces to the rails at the guideway. The suspension of a vehicle by attractive magnetic forces is inherently unstable and consequently it is continuously adjusted by the strength of the suspending electromagnet from rail irregularity and bending of the guideway. In order to improve reliable tracking, it needs to get feedback signals without measurement delay time. In this paper the concept of feedback control system with Kalman Filter in EMS is proposed. The input signals in the feedback control system are an air-gap and an acceleration signal. The air-gap signal with noise from the gap sensor is transformed to the filtered air-gap signal y without measurement delay time by using Kalman Filter. The filtered air-gap signal is transformed to a relative velocity and a relative acceleration signal. Then it multiplies these values by gain matrix in order to get the actuator's reference voltage value. The simulation results show that the dynamic responses of the suspension system can be improved by reducing the influence of measurement delay time of air-gap signals.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.42-45
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• 2010

This paper proposes an intelligent video surveillance system for human object tracking. The proposed system integrates the object extraction, human object recognition, face detection, and camera control. First, the object in the video signals is extracted using the background subtraction. Then, the object region is examined whether it is human or not. For this recognition, the region-based shape descriptor, angular radial transform (ART) in MPEG-7, is used to learn and train the shapes of human bodies. When it is decided that the object is human or something to be investigated, the face region is detected. Finally, the face or object region is tracked in the video, and the pan/tilt/zoom (PTZ) controllable camera tracks the moving object with the motion information of the object. This paper performs the simulation with the real CCTV cameras and their communication protocol. According to the experiments, the proposed system is able to track the moving object(human) automatically not only in the image domain but also in the real 3-D space. The proposed system reduces the human supervisors and improves the surveillance efficiency with the computer vision techniques.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.7
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• pp.155-162
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• 2003

We propose a new technique far real-tine controller design of a autonomous cruise mobile robot with three drive wheels. The proposed control scheme uses a Caussian function as a unit function in the fuzzy neural network. and a back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-foray. The control performance of the proposed controller is illustrated by performing the computer simulation for trajectory tracking of the speed and azimuth of a autonomous cruise mobile robot driven by three independent wheels.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1697-1700
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• 2003

We propose a new technique for real-time controller design of a autonomous cruise mobile robot with three drive wheels. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and a back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The control performance of the proposed controller is illustrated by performing the computer simulation for trajectory tracking of the speed and azimuth of a autonomous cruise mobile robot driven by three independent wheels.