• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.533-536
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• 2003

In this paper we propose AODC(Adaptive Over Driving Circuit) to reduce motion blurring and compensate color accuracy on LCD monitor. The proposed method has been experimented on adaptive ODC by motion grade after detection of moving objects. Also, we discriminated motion grade by mean value's degree of differential value between current frame and previous frame to detect moving objects. It has been found that the proposed method provides better performance than the conventional one from the point of view on the blurring of movement objects through the experiment. Its results show that the proposed method is very suitable for a motion blurring reduction on LCD monitor.

• Journal of Industrial Technology
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• v.26 no.A
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• pp.89-93
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• 2006

Pulse oximetry, which monitors non-invasively the oxygen saturation in blood, is influenced by patient's respiration, movement or a factor of an environment. Specially, it's difficult to measure a PPG (Photoplethsmography) signal from the moving patient because of the motion artifact. Accordingly, it is required to extract the pure PPG signal from the PPG signal to measure oxygen saturation. In this paper, we propose an adaptive noise canceller to improve the performance of motion artifact removal. Then we design a hardware system for real time monitoring of the oxygen saturation. The proposed algorithm estimates the slope of transition rate between two different wavelength signals.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.437-444
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• 2012

In this paper, we propose a method for predicting a user's location based on their past movement patterns. There is no restriction on the length of past movement patterns when using this method to predict the current location. For this purpose, a modified search tree has been devised. The search tree is constructed in an effective manner while it additionally learns the movement patterns of a user one by one. In fact, the time complexity of the learning process for a movement pattern is linear. In this process, the search tree expands to take into consideration more details about the movement patterns when a pattern that conflicts with an existing trained pattern is found. In this manner, the search tree is trained to make an exact matching, as needed, for location prediction. In the experiments, the results showed that this method is highly accurate in comparison with more complex and sophisticated methods. Also, the accuracy deviation of users of this method is significantly lower than for any other methods. This means that this method is highly stable for the variations of behavioral patterns as compared to any other method. Finally, 1.47 locations were considered on average for making a prediction with this method. This shows that the prediction process is very efficient.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1963-1967
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• 2003

Communication device to use slight movement for serious disabled is proposed. This device is developed mainly for patients suffering from ALS or a cerebral infarction. They often have communication difficulty because of deterioration of muscular functions. Features of this device are that the device is wearable on the user’s body and that it detects the movement of eyebrow. Because of these features, it is quite easy to install the sensor on the patient’s body, not like the conventional sensors. Furthermore, an adaptive communication software is incorporated. A feature of this software is that the arrangement and size of the button and window on the display can be optimized depending on the user's physical ability. In the field test it is confirmed that the communication device developed in this study is successfully helped the people with disability for increasing their communication ability.

• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1767-1774
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• 2016

In this paper, we propose the adaptation filtering for correcting the movement path of the recognized object by the depth information. When we recognize the object by the depth information, the path error should be occurred because of the noises in the depth information. The path error is corrected by appling the lowpass filtering, but the lowpass filtering is not efficient when the changes of the object's movement are rapid. In this paper, we apply the adaptation filtering that it gives weights adaptively as the difference between the predicted location and the measured location. To apply the adaptation filtering, we can see that the proposed method can correct accurately the path error of the radical change from simulation results.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.162-172
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• 2015

In this paper, we propose an adaptive detection algorithm of footstep and a classification algorithm for activities of the detected footstep. The proposed algorithm can detect and classify whole movement as well as individual and irregular activities, since it does not use continuous footstep signals which are used by most previous research. For classifying movement, we use feature vectors obtained from frequency spectrum from FFT, CWT, AR model and image of AR spectrogram. With SVM classifier, we obtain classification accuracy of single footstep activities over 90% when feature vectors using AR spectrogram image are used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.6
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• pp.1166-1191
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• 2011

This paper presents an adaptive active tracking system with sector based scanning for a single PTZ camera. Dividing sectors on an image reduces the search space to shorten selection time so that the system can cover many targets. Upon the selection of a target, the system estimates the target trajectory to predict the zooming location with a finite amount of time for camera movement. Advanced estimation techniques using probabilistic reason suffer from the unknown object dynamics and the inaccurate estimation compromises the zooming level to prevent tracking failure. The proposed system uses the simple piecewise estimation with a few frames to cope with fast moving objects and/or slow camera movements. The target is tracked in multiple steps and the zooming time for each step is determined by maximizing the zooming level within the expected variation of object velocity and detection. The number of zooming steps is adaptively determined according to target speed. In addition, the iterative estimation of a zooming location with camera movement time compensates for the target prediction error due to the difference between speeds of a target and a camera. The effectiveness of the proposed method is validated by simulations and real time experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1152-1168
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• 2010

Recently, due to the prevalence of various mobile devices and wireless broadband networks, there has been a significant increase in interest and demand for multimedia streaming services such as the mobile IPTV. In such a wireless broadband network, transmitting a continuous stream of multimedia data is difficult to achieve due to mobile stations (MSs) movement. Providing Quality of Service (QoS) for multimedia video streaming applications requires the server and/or client to be network-aware and adaptive. Therefore, in order to deploy a mobile IPTV service in wireless broadband networks, offering users efficient wireless resource utilization and seamlessly offering user perceived QoS are important issues. In this paper, we propose a new adaptive streaming scheme, called MARC (Mobile-aware Adaptive Rate Control), which adjusts the quality of bit-stream and transmission rate of video streaming based on the wireless channel status and network status. The proposed scheme can control the rate of multimedia streaming to be suitable for the wireless channel status by using awareness information of the wireless channel quality and the mobile station location. The proposed scheme can provide a seamless multimedia playback service in wireless broadband networks in addition to improving the QoS of multimedia streaming services. The proposed MARC scheme alleviates the discontinuity of multimedia playback and allocates a suitable client buffer to the wireless broadband network. The simulation results demonstrate the effectiveness of our proposed scheme.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.45-51
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• 2018

As data utilization and importance becomes important, data-related accidents and damages are gradually increasing. Especially, insider threats are the most harmful threats. And these insider threats are difficult to detect by traditional security systems, so rule-based abnormal behavior detection method has been widely used. However, it has a lack of adapting flexibly to changes in new attacks and new environments. Therefore, in this paper, we propose an adaptive anomaly movement detection framework based on a statistical Markov model to detect insider threats in advance. This is designed to minimize false positive rate and false negative rate by adopting environment factors that directly influence the behavior, and learning data based on statistical Markov model. In the experimentation, the framework shows good performance with a high F2-score of 0.92 and suspicious behavior detection, which seen as a normal behavior usually. It is also extendable to detect various types of suspicious activities by applying multiple modeling algorithms based on statistical learning and environment factors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.852-860
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• 2019

In this paper, we proposed a new trilateration technique based on exponential moving average (EMA) filter with adaptive signal model which enhances accuracy of positioning system even if the RSSI changes randomly due to movement of obstacles or blind node in indoor environment. In the proposed scheme, three fixed transmitters sent out the signal to blind node. The transmitter decides the location of the blind node based on RSSI and it estimates the cause of RSSI fluctuation which is interference of obstacle or movement of blind node. When the path between blind node and transmitter has become NLOS path because of obstacles, the transmitter ignores the measured RSSI in NLOS path and replace estimated RSSI in LOS environment. In the other case, the transmitter updated the new RSSI to represent of movement of blind node. The proposed scheme has been verified on a ZigBee testbed and we proved the improved positioning accuracy compared to the existing indoor position system.