• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.975-978
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• 2010

This paper presents a Kalman filter based modeling algorithm for autonomous robots. State of the robot systems is measured by using embedded sensors and then carried to a host computer via ubiquitous sensor network (USN). We settle a linear state space motion equation for unknown system dynamics and modify a popular Kalman filter algorithm in deriving suitable parameter estimation mechanism. We conduct real-time experiment to test our proposed modeling algorithm where velocity state of the constructed robot is used as system observation.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.1
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• pp.59-67
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• 2009

In this paper, we have proposed the structure of the IMADF(improved modified multiplication-free adaptive filter) to cancel the adaptive noise in biomedical signals. The IMADF structure use the one-step predicted filter in the multiplication-free adaptive digital filter(MADF) structure using the DPCM and Sign algorithm. And then we use the heart phantom model based on the magnetocardiographic (MCG) to test the biomedical signals and analyze the signal of it. Their functions of the heart phantom occur from the multidipole current source. This can play role the same in the real function of the human heart to study it. In the experimental results, the IMADF algorithm has reduced the computational complexity by use of only the addition operation without a multiplier. Also, under the condition of identical stationary-state error, it could obtain the stabled convergence characteristics that the IMADF algorithm is almost same as the sign algorithm, but is better than the MADF algorithm. Here, this algorithm has effective characteristics when the correlation of the input signal is highly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.428-451
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• 2010

Traffic matrix-based anomaly detection and DDoS attacks detection in networks are research focus in the network security and traffic measurement community. In this paper, firstly, a new type of unidirectional flow called IF flow is proposed. Merits and features of IF flows are analyzed in detail and then two efficient methods are introduced in our DDoS attacks detection and evaluation scheme. The first method uses residual variance ratio to detect DDoS attacks after Recursive Least Square (RLS) filter is applied to predict IF flows. The second method uses generalized likelihood ratio (GLR) statistical test to detect DDoS attacks after a Kalman filter is applied to estimate IF flows. Based on the two complementary methods, an evaluation formula is proposed to assess the seriousness of current DDoS attacks on router ports. Furthermore, the sensitivity of three types of traffic (IF flow, input link and output link) to DDoS attacks is analyzed and compared. Experiments show that IF flow has more power to expose anomaly than the other two types of traffic. Finally, two proposed methods are compared in terms of detection rate, processing speed, etc., and also compared in detail with Principal Component Analysis (PCA) and Cumulative Sum (CUSUM) methods. The results demonstrate that adaptive filter methods have higher detection rate, lower false alarm rate and smaller detection lag time.

• Journal of Broadcast Engineering
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• v.14 no.1
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• pp.3-14
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• 2009

Currently, H.264/AVC is used in many multimedia applications. Also, The MPEG-2 main profile which supports B pictures for bi-directional motion prediction is widely used in applications such as HDTV and DVD’s. Therefore, transcoding the MPEG-2 main profile to the H.264/AVC baseline is necessary for universal multimedia access. In this transcoding architecture including the GOP structure conversion, the proposed algorithms adopt the adaptive search range selection through the linearity test of a predictive motion vector and adaptive mode selection using the reference region complexity information. The proposed algorithms extremely reduce the computational complexity while maintaining the video quality.

• Current Optics and Photonics
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• v.1 no.2
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• pp.107-112
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• 2017

An adaptive optics system can be simulated or analyzed to predict its closed-loop performance. However, this type of prediction based on various assumptions can occasionally produce outcomes which are far from actual experience. Thus, every adaptive optics system is desired to be tested in a closed loop on an optical test bench before its application to a telescope. In the close-loop test bench, we need an atmospheric simulator that simulates atmospheric disturbances, mostly in phase, in terms of spatial and temporal behavior. We report the development of an atmospheric turbulence simulator consisting of two point sources, a commercially available deformable mirror with a $12{\times}12$ actuator array, and two random phase plates. The simulator generates an atmospherically distorted single or binary star with varying stellar magnitudes and angular separations. We conduct a simulation of a binary star by optically combining two point sources mounted on independent precision stages. The light intensity of each source (an LED with a pin hole) is adjustable to the corresponding stellar magnitude, while its angular separation is precisely adjusted by moving the corresponding stage. First, the atmospheric phase disturbance at a single instance, i.e., a phase screen, is generated via a computer simulation based on the thin-layer Kolmogorov atmospheric model and its temporal evolution is predicted based on the frozen flow hypothesis. The deformable mirror is then continuously best-fitted to the time-sequenced phase screens based on the least square method. Similarly, we also implement another simulation by rotating two random phase plates which were manufactured to have atmospheric-disturbance-like residual aberrations. This later method is limited in its ability to simulate atmospheric disturbances, but it is easy and inexpensive to implement. With these two methods, individually or in unison, we can simulate typical atmospheric disturbances observed at the Bohyun Observatory in South Korea, which corresponds to an area from 7 to 15 cm with regard to the Fried parameter at a telescope pupil plane of 500 nm.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.818-827
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• 2008

In this paper, we propose a new noise estimation and reduction algorithm for stationary and nonstationary noisy environments. This approach uses an algorithm that classifies the speech and noise signal contributions in time-frequency bins. It relies on the ratio of the normalized standard deviation of the noisy power spectrum in time-frequency bins to its average. If the ratio is greater than an adaptive estimator, speech is considered to be present. The propose method uses an auto control parameter for an adaptive estimator to work well in highly nonstationary noisy environments. The auto control parameter is controlled by a linear function using a posteriori signal to noise ratio(SNR) according to the increase or the decrease of the noise level. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of much more simplicity and light computational load for estimating the stationary and nonstationary noise environments. The proposed algorithm is superior to conventional methods. To evaluate the algorithm's performance, we test it using the NOIZEUS database, and use the segment signal-to-noise ratio(SNR) and ITU-T P.835 as evaluation criteria.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1721-1736
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• 2013

Black and gray hole attack is one kind of routing disturbing attacks and can bring great damage to the network. As a result, an efficient algorithm to detect black and gray attack is important. This paper demonstrate an adaptive approach to detecting black and gray hole attacks in ad hoc network based on a cross layer design. In network layer, we proposed a path-based method to overhear the next hop's action. This scheme does not send out extra control packets and saves the system resources of the detecting node. In MAC layer, a collision rate reporting system is established to estimate dynamic detecting threshold so as to lower the false positive rate under high network overload. We choose DSR protocol to test our algorithm and ns-2 as our simulation tool. Our experiment result verifies our theory: the average detection rate is above 90% and the false positive rate is below 10%. Moreover, the adaptive threshold strategy contributes to decrease the false positive rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1161-1168
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• 2003

In this paper, we propose an improved statistical model-based voice activity detection algorithm and threshold update method. We first improve signal-to-noise ratio by using speech enhancement preprocessing algorithm combined power subtraction method and matched filter, then apply it to LLR test optimum decision rule for improving the performance even in low SNR conditions. And we propose an adaptive threshold update method that was not concerned in any papers. We also perform extensive computer simulations to demonstrate the performance improvement of the proposed VAD algorithm employing the proposed speech enhancement preprocessing algorithm and adaptive threshold update method under various background noise environments. Finally we verify our results by comparing ITU-T G.729 Annex B.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1243-1248
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• 2006

Object tracking in a real time image is one of interesting subjects in computer vision and many practical application fields past couple of years. But sometimes existing systems cannot find object by recognize background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which does not influenced by illumination and remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up MBR(minimum bounding rectangle) using the internal point of detected object, the system tracks object through this MBR. In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• Journal of The Korean Association of Information Education
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• v.11 no.2
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• pp.243-249
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• 2007

Most homepages of schools are available to publicize activities of education, to load educational materials efficiently. But we can't use current homepages of schools in making characteristic information or sharing educational resources. In this study, this I-CUBE system with RSS was designed and embodied for sharing characteristic educational activities and works in schools. Currently, I-CUBE is being under experimental test for sharing education activities and making community in elementry schools,.