• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.240-247
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• 2006

Piezoelectric sensor-based health monitoring technique using a two-step support vector machine (SYM) classifier is discussed for damage identification of a railroad track. An active sensing system composed of two PZT patches was investigated in conjunction with both impedance and guided wave propagation methods to detect two kinds of damage of the railroad track (one is a hole damage of 0.5cm in diameter at web section and the other is a transverse cut damage of 7.5cm in length and 0.5cm in depth at head section). Two damage-sensitive features were extracted one by one from each method; a) feature I: root mean square deviations (RMSD) of impedance signatures and b) feature II: wavelet coefficients for $A_0$ mode of guided waves. By defining damage indices from those damage-sensitive features, a two-dimensional damage feature (2-D DF) space was made. In order to minimize a false-positive indication of the current active sensing system, a two-step SYM classifier was applied to the 2-D DF space. As a result, optimal separable hyper-planes were successfully established by the two-step SYM classifier: Damage detection was accomplished by the first step-SYM, and damage classification was also carried out by the second step-SYM. Finally, the applicability of the proposed two-step SYM classifier has been verified by thirty test patterns.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1147-1154
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• 2016

In this paper, we numerically compare two penalized least square methods, the ${\ell}_0$-penalized method and the fused lasso regression (FLR, ${\ell}_1$ penalization), in finding multiple change points of a signal. We find that the ${\ell}_0$-penalized method performs better than the FLR, which produces many false detections in some cases as the theory tells. In addition, the computation of ${\ell}_0$-penalized method relies on dynamic programming and is as efficient as the FLR.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.12
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• pp.1702-1705
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• 2006

A simulation study was conducted to evaluate a fine-mapping method exploiting population-wide linkage disequilibrium. Data were simulated according to the pedigree structure based on a large paternal half-sib family population with a total of 1,034 or 2,068 progeny. Twenty autosomes of 100 cM were generated with 5 cM or 1 cM marker intervals for all founder individuals in the pedigree, and marker alleles and a number of quantitative trait loci (QTL) explaining a total of 70% phenotypic variance were generated and randomly assigned across the whole chromosomes, assuming linkage equilibrium between the markers. The founder chromosomes were then descended through the pedigree to the current offspring generation, including recombinants that were generated by recombination between adjacent markers. Power to detect QTL was high for the QTL with at least moderate size, which was more pronounced with larger sample size and denser marker map. However, sample size contributed much more significantly to power to detect QTL than map density to the precise estimate of QTL position. No QTL was detected on the test chromosomes in which QTL was not assigned, which did not allow detection of false positive QTL. For the multiple QTL that were closely located, the estimates of the QTL positions were biased, except when the QTL were located on the right marker positions. Our fine mapping simulation results indicate that construction of dense maps and large sample size is needed to increase power to detect QTL and mapping precision for QTL position.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.119-126
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• 1999

We proposed an algorithm which detects scene changes in video with speediness and accuracy. It is a two-step approach. In the first step, we decide potential scene change segments using the compressed domain data extracted by temporal sampling of MPEG compressed video. In the second step, we determine the exact scene change positions using the pixel values of each frame in those segments by means of combining the intensity and edge changes. In addition we discuss the method to remove false detection generated from camera flash. Integrating the above methods, we introduce a structure that can detect scene changes speedily and accurately.

• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.33-43
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• 2006

This paper proposes a method to extract coronary arteries effectively in the angiography, In general. DSA(Digital Subtraction Angiography) is a well-established technique for the visualization of coronary arteries, DSA involves the subtraction of a mask image, an image of a heart before the injection of contrast medium, from a live image, However, this technique is sensitive to the movement of background and can cause wrong detection due to the variance of background intensity between two images. Therefore, this paper solves the structural problem resulted from background movement by selecting an image which has the least difference of movement through the similarity analysis of background texture, and it extracts only the blood vessels effectively through local intensity correction of the selected images, Experimental results show that the proposed method has the lower false-detection rate and higher accuracy rate than existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1532-1553
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• 2014

Radio spectrum is a precious resource and characterized by fixed allocation policy. However, a large portion of the allocated radio spectrum is underutilized. Conversely, the rapid development of ubiquitous wireless technologies increases the demand for radio spectrum. Cognitive Radio (CR) methodologies have been introduced as a promising approach in detecting the white spaces, allowing the unlicensed users to use the licensed spectrum thus realizing Dynamic Spectrum Access (DSA) in an effective manner. This paper proposes a generalized framework for DSA between the licensed (primary) and unlicensed (secondary) users based on Continuous Time Markov Chain (CTMC) model. We present a spectrum access scheme in the presence of sensing errors based on CTMC which aims to attain optimum spectrum access probabilities for the secondary users. The primary user occupancy is identified by spectrum sensing algorithms and the sensing errors are captured in the form of false alarm and mis-detection. Simulation results show the effectiveness of the proposed spectrum access scheme in terms of the throughput attained by the secondary users, throughput optimization using optimum access probabilities, probability of interference with increasing number of secondary users. The efficacy of the algorithm is analyzed for both imperfect spectrum sensing and perfect spectrum sensing.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.37-43
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• 2012

In this paper, we analysis wideband spectrum sensing with distance based weight combining for Cognitive Radio (CR) systems. CR systems is implemented the spectrum of the Primary User(PU) by using a energy detection method. Threshold is determined in accordance with the constant false alarm rate (CFAR) algorithm for energy detection. The signal of PU is BPSK signal and the wireless channel between a PU and CR systems is modeled as Gaussian channel. From the simulation results, the wideband sensing with distance based and Distance based weight Combing (DWC) methods shows higher spectrum sensing performance than single CR user spectrum sensing.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2814-2818
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• 2000

This paper describes an image processing algorithm capable of recognizing the road lane using a CDF (Cumulative Distribution Function). which is designed for the model function of the road lane. The CDF has distinctive peak points at the vicinity of the lane direction because of the directional and positional continuities of the lane. We construct a scatter diagram by collecting the edge pixels with the direction corresponding to the peak point of the CDF and carry out the principal axis-based line fitting for the scatter diagram to obtain the lane information. As noises play the role of making a lot of similar features to the lane appear and disappear in the image we introduce a recursive estimator of the function to reduce the noise effect and a scene understanding index (SUI) formulated by statistical parameters of the CDF to prevent a false alarm or miss detection. The proposed algorithm has been implemented in a real time on the video data obtained from a test vehicle driven in a typical highway.

• Structural Engineering and Mechanics
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• v.41 no.5
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• pp.663-673
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• 2012

A number of mode shape-based structure damage identification methods have been verified by numerical simulations or experiments for on-line structure health monitoring (SHM). However, many of them need a baseline mode shape generated by the healthy structure serving as a reference to identify damages. Otherwise these methods can hardly perform well when multiple cracks conditions occur. So it is important to solve the problems above. By aid of the fractal dimension method (FD), Qiao and Wang proposed a generalized fractal dimension (GFD) to detect the delamination damage. As a modification of GFD, Qiao and Cao proposed the approximate waveform capacity dimension (AWCD) technique to simplify the calculation of fractal and overcome the false peak appearing in the high mode shapes. Based on their valued work, this paper combined and applied the AWCD method and curvature mode shape data to detect multiple damages in beam. In the end, the identification properties of the AWCD for multiple damages have been verified by groups of Monte Carlo simulations and experiments.

• Journal of KIEE
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• v.11 no.1
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• pp.69-77
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• 2001

This paper describes an image processing algorithm capable of recognizing road lanes by using a CDF(cumulative distribution function). The CDF is designed for the model function of road lanes. Based on the assumptions that there are no abrupt changes in the direction and location of road lanes and that the intensity of lane boundaries differs from that of the background, we formulated the CDF, which accumulates the edge magnitude for edge directions. The CDF has distinctive peak points at the vicinity of lane directions due to the directional and the positional continuities of a lane. To obtain lane-related information a scatter diagram was constructed by collecting edge pixels, of which the direction corresponds to the peak point of the CDF, then the principal axis-based line fitting was performed for the scatter diagram. Noises can cause many similar features to appear and to disappear in an image. Therefore, to reduce the noise effect a recursive estimator of the CDF was introduced, and also to prevent false alarms or miss detection a scene understanding index (DUI) was formulated by the statistical parameters of the CDF. The proposed algorithm has been implemented in real time on video data obtained from a test vehicle driven on a typical highway.