• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.197-204
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• 2015

In this paper, we present an algorithm for the detection of illegally parked vehicles based on a combination of some image processing algorithms. A digital camera is fixed in the illegal parking region to capture the video frames. An adaptive Gaussian mixture model (GMM) is used for background subtraction in a complex environment to identify the regions of moving objects in our test video. Stationary objects are detected by using the pixel-level features in time sequences. A stationary vehicle is detected by using the local features of the object, and thus, information about illegally parked vehicles is successfully obtained. An automatic alarm system can be utilized according to the different regulations of different illegal parking regions. The results of this study obtained using a test video sequence of a real-time traffic scene show that the proposed method is effective.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.181-184
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• 2000

This paper presents an experimental system, where an object extracted from an image sequence is embedded into the desired position in a scene. First, a moving object is detected and the 3-D structure is obtained by SFM analysis of comer trajectories. We constrained the motion to translational motion only. Extracted objects are classified by matching with 3-D models and then the structure of the occluded part is restored. Camera calibration is performed for the background scene which will embed the object. Finally, the object is embedded into the scene. In the experiments, we used synthetic image sequences generated with OpenGL library for easy evaluation of the 3-D structure estimation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.40-45
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• 1999

The demands for robotic and automatic system are continually increasing in manufacturing fields. There have been many studies to monitor and predict the system, but they have mainly focused upon measuring cutting force, and current of motor spindle, and upon using acoustic sensor, etc.In this study, time series sequence of cutting force was acquired by taking advantage of piezoelectric type tool dynamometer. Radial cutting force was obtained from it and was available for useful observation data. The parameter was estimated using PAA (parameter adaptation algorithm) from observation data. ARMA(auto regressive moving average) model was selected for system model and second order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1570-1578
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• 2000

Object motion is an important feature of content in video sequences. By now, various methods to exact feature about the object motion have been reported[1,2]. However they are not suitable to index video using the motion, since a lot of bits and complex indexing parameters are needed for the indexing [3,4] In this paper, we propose object motion map which could provide efficient indexing method for object motion. The proposed object motion map has both global and local motion information during an object is moving. Furthermore, it requires small bit of memory for the indexing. to evaluate performance of proposed indexing technique, experiments are performed with video database consisting of MPEG-1 video sequence in MPEG-7 test set.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.310-318
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• 2012

Detecting intrusion attacks accurately and rapidly in wireless networks is one of the most challenging security problems. Intrusion attacks of various types can be detected by the change in traffic flow that they induce. Wireless industrial networks based on the wireless networks for industrial automation-process automation (WIA-PA) standard use a superframe to schedule network communications. We propose an intrusion detection system for WIA-PA networks. After modeling and analyzing traffic flow data by time-sequence techniques, we propose a data traffic prediction model based on autoregressive moving average (ARMA) using the time series data. The model can quickly and precisely predict network traffic. We initialized the model with data traffic measurements taken by a 16-channel analyzer. Test results show that our scheme can effectively detect intrusion attacks, improve the overall network performance, and prolong the network lifetime.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.77-77
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• 2000

The shape of small or curved object is usually reconstructed using a single camera by moving its lens position to find a sequence of the focused images. Most conventional methods have used a window with fixed shape to test the focus measure, which resulted in a deterioration of accuracy. To solve this problem, this paper proposes a new approach of using a shape adaptive window. It estimates the shape of the object at every step and applies the same shape of window to calculate the focus measure. Focus measure is based on the variance of the pixels inside the window. This paper includes the experimental results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.877-884
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• 2002

This paper deals with a multi-stage TSK fuzzy modeling method by using Genetic Programming (GP). Based on the time sequence of sampling data the best structural change points of complex systems are detemined by using GP, and also the moving window is simultaneously introduced to overcome the excessive amount of calculation during the generating procedure of GP tree. Therefore, a multi-stage TSK fuzzy model that attempts to represent a complex problem by decomposing it into multi-stage sub-problems is addressed and its learning algorithm is proposed based on the Radial Basis Function (RBF) network. This approach allows us to determine the model structure and parameters by stages so that the problems ran be simplified.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.87-98
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• 1994

Object-oriented analysis-synthesis coding subdivides each image of a sequence into moving objects and compensates the motion of each object. Thus it can reconstruct real motion better than conventional motion-compensated coding techniques at very-low-bit-rates. It uses a mapping parameter technique for estimating motion information of each object. Since a mapping parameter technique uses gradient operators it is sensitive to redundant details and noise. To accurately determine mapping parameters, we propose a new analysis method using integral projections for estimation of gradient values. Also to reconstruct correctly the local motion the proposed algorithm divides an image into segmented objects each of which having uniform motion information while the conventional one assumes a large object having the same motion information. Computer simulation results with several test sequences show that the proposed image analysis method in object-oriented analysis-synthesis coding shows better performance than the conventional one.

• Journal of the Ergonomics Society of Korea
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• v.29 no.6
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• pp.959-964
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• 2010

Seat belt is an important means to protect drivers and passengers from the damages by car accidents. Many ways to increase the seat belt wearing rate have been proposed through human factors researches. The primary ways to increase seat belt use rate have emphasized the intention-behavior cycle. This study focused on the gap between intention and behavior. The gap may be bridged by the habit for seat belt use behavior. Divers following a desirable car starting sequence, from sitting on the chair, fastening seat belt, starting engine to moving a car, reported that higher belt wearing rate and unconscious behavior (automated response). That is, the habitualized procedure knowledge prevented drivers from forgetting to fasten their seat belt. The reminder systems such as warning light and warning sound could not significantly give an influence in remembering to fasten seat belt. In order to increase the seat belt use rate, the desirable car starting procedure should be included in the driving education program.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.5
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• pp.505-511
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• 2014

The functional role of warehouses in modern industry is changing from an established concept of storage to a concept of circulation. The target of this study is to improve the stacker crane's efficiency for the internal operations of the Automated Storage and Retrieval System (AS/RS). Eight operating schemes are proposed under the combination of three conditions, namely, the storing method, the layout type, and the sequence of command execution. The moving distance of the stacker crane is calculated using the same gateway data through a simulation based on a C# program. The optimal operating scheme is proposed based on the analyzed simulation results. In conclusion, the combination of conditions of random storage, two-way type warehouse, and dual command execution elicits optimum results in travel efficiency for the stacker crane.