• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6043-6062
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• 2019

Low-rank matrix decomposition has shown its capability in many applications such as image in-painting, de-noising, background reconstruction and defect detection etc. In this paper, we consider the texture background of rail track images and the sparse foreground of the defects to construct a low-rank matrix decomposition model with block sparsity for defect inspection of rail tracks, which jointly minimizes the nuclear norm and the 2-1 norm. Similar to ADM, an alternative method is proposed in this study to solve the optimization problem. After image decomposition, the defect areas in the resulting low-rank image will form dark stripes that horizontally cross the entire image, indicating the preciselocations of the defects. Finally, a two-stage defect extraction method is proposed to locate the defect areas. The experimental results of the two datasets show that our algorithm achieved better performance compared with other methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2326-2345
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• 2016

For the compression of color images, a common bitmap usually is generated to replace the three individual bitmaps that originate from block truncation coding (BTC) of the R, G and B channels. However, common bitmaps generated by some traditional schemes are not the best possible because they do not consider the minimized distortion of the entire color image. In this paper, we propose a near-optimized common bitmap scheme for BTC using Binary Ant Colony Optimization (BACO), producing a BACO-BTC scheme. First, the color image is compressed by the BTC algorithm to get three individual bitmaps, and three pairs of quantization values for the R, G, and B channels. Second, a near-optimized common bitmap is generated with minimized distortion of the entire color image based on the idea of BACO. Finally, the color image is reconstructed easily by the corresponding quantization values according to the common bitmap. The experimental results confirmed that reconstructed image of the proposed scheme has better visual quality and less computational complexity than the referenced schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5643-5656
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• 2016

The detection accuracy of steganalysis depends on many factors, including the embedding algorithm, the payload size, the steganalysis feature space and the properties of the cover source. In practice, the cover source mismatch (CSM) problem has been recognized as the single most important factor negatively affecting the performance. To address this problem, we propose a new framework for blind, universal steganalysis which uses traditional steganalyst features. Firstly, cover images with the same statistical properties are searched from a reference image database as aided samples. The test image and its aided samples form a whole test set. Then, by assuming that most of the aided samples are innocent, we conduct outlier detection on the test set to judge the test image as cover or stego. In this way, the framework has removed the need for training. Hence, it does not suffer from cover source mismatch. Because it performs anomaly detection rather than classification, this method is totally unsupervised. The results in our study show that this framework works superior than one-class support vector machine and the outlier detector without considering the image retrieval process.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.637-644
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• 2006

Biomedical image is often complex. An applied image analysis system should deal with the images which are of quite low quality and are challenging to segment. This paper presents a framework for color cell image segmentation by learning and classification online. It is a robust two-stage scheme using kernel method and watershed transform. In first stage, a two-class SVM is employed to discriminate the pixels of object from background; where the SVM is trained on the data which has been analyzed using the mean shift procedure. A real-time training strategy is also developed for SVM. In second stage, as the post-processing, local watershed transform is used to separate clustering cells. Comparison with the SSF (Scale space filter) and classical watershed-based algorithm (those are often employed for cell image segmentation) is given. Experimental results demonstrate that the new method is more accurate and robust than compared methods.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.2
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• pp.44-51
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• 2008

In this paper, we propose a modified clipping scheme for iterative decoding of superposition coding system by losing less power than clipping scheme. Our proposed scheme in superposition coding system shows good performance in peak-to-average power ratio(PAPR) and system performance with the same Clipping Ratio especially in low Clipping Ratio case. Finally in order to alleviate the performance degradation due to clipping noises, we combine a soft compensation algorithm that is combined with soft-input-soft-output(SISO) decoding algorithms in an iterative manner proposed by [1][2]. Simulation results show that with the proposed scheme, most performance loss can be recovered.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.2
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• pp.97-102
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• 2008

In this paper, we address the OFDM based on DFT or DCT in Cognitive Radio system. An adaptive OFDM based on DFT or DCT in Cognitive Radio system has the capacity to nullify individual carriers to avoid interference to the licensed users. Therefore, there could be a considerably large number of zero-valued inputs/outputs for the IDFT/DFT or IDCT/DCT on the OFDM transceiver. Hence, the standard methods of DFT and DCT are no longer efficient due to the wasted operations on zero. Based on this observation, we present a transform decomposition on two dimensional(2-D) systolic array for IDFT/DFT and IDCT/DCT, this algorithm can achieve an efficient computation for OFDM in Cognitive Radio system

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.2
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• pp.426-434
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• 2015

In this paper we proposed a dada-aided Doppler estimation method for underwater acoustic communication. The training sequence is non-dedicate, hence it can be designed for Doppler estimation as well as channel equalization. We assume the channel has been equalized and consider only flat-fading channel. First, based on the training symbols the theoretical received sequence is composed. Next the least square principle is applied to build the objective function, which minimizes the error between the composed and the actual received signal. Then an iterative approach is applied to solve the least square problem. The proposed approach involves an outer loop and inner loop, which resolve the channel gain and Doppler coefficient, respectively. The theoretical performance bound, i.e. the Cramer-Rao Lower Bound (CRLB) of estimation is also derived. Computer simulations results show that the proposed algorithm achieves the CRLB in medium to high SNR cases.

• ETRI Journal
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• v.32 no.4
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• pp.512-519
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• 2010

A cooperative model is presented to enable sharing of the spectrum with secondary users. Compared with the optimal model and competitive model, the cooperative model could reach the maximum total profit for secondary users with better fairness. The cooperative model is built based on the Nash equilibrium. Then a conceding factor is introduced so that the total spectrum required from secondary users will decrease. It also results in a decrease in cost which the primary user charges to the secondary users. The optimum solution, which is the maximum total profit for the secondary users, is called the collusion state. It is possible that secondary users may leave the collusion state to pursue the maximum of individual profit. The stability of the algorithm is discussed by introducing a vindictive factor to inhabit the motive of deviation. In practice, the number of secondary users may change. Adaptive methods have been used to deal with the changing number of secondary users. Both the total profit and fairness are considered in the spectrum allocating. The shared spectrum is 11.3893 with a total profit of 65.2378 in the competitive model. In the cooperative model, the shared spectrum is 8.5856 with the total profit of 73.4963. The numerical results reveal the effectiveness of the cooperative model.

• Smart Structures and Systems
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• v.21 no.3
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• pp.373-387
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• 2018

Semi-active isolation systems based on leverage-type stiffness control strategies have been widely studied. The main concept behind this type of system is to adjust the stiffness in the isolator to match the fundamental period of the isolated system by using a simple leverage mechanism. Although this system achieves high performance under far-field earthquakes, it is unsuitable for near-fault strong ground motion. To overcome this problem, this study considers the potential energy effect in the control law of the semi-active isolation system. The minimal energy weighting (MEW) between the potential energy and kinetic energy was first optimized through a series of numerical simulations. Two MEW algorithms, namely generic and near-fault MEW control, were then developed to efficiently reduce the structural displacement responses. To demonstrate the performance of the proposed method, a two-degree-of-freedom structure was employed as a benchmark. Numerical results indicate that the dynamic response of the structure can be effectively dampened by the proposed MEW control under both far-field and near-fault earthquakes, whereas the structural responses resulting from conventional control methods may be greater than those for the purely passive control method. Moreover, according to experimental verifications, both the generic and near-fault MEW control modes yielded promising results under impulse-like earthquakes. The practicability of the proposed control algorithm was verified.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.523-530
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• 2016

We use both theoretical analysis and simulations to study the impact of crosspoint-queued (CQ) buffer size on CQ switch throughput and delay performance under different traffic models, input loads, and scheduling algorithms. In this paper, we present the following. 1) We prove the stability of CQ switch using any work-conserving scheduling algorithm. 2) We present an exact closed-form formula for the CQ switch throughput and a non-closed-form but convergent formula for its delay using static non-work-conserving random scheduling algorithms with any given buffer size under independent Bernoulli traffic. 3) We show that the above results can serve as a conservative guide on deciding the required buffer size in pure CQ switches using work-conserving algorithms such as the random scheduling, under independent Bernoulli traffic. 4) Furthermore, our simulation results under real-trace traffic show that simple round-robin and random work-conserving algorithms can achieve quite good throughput and delay performance with a feasible crosspoint buffer size. Our work reveals the impact of buffer size on the CQ switch performance and provides a theoretical guide on designing the buffer size in pure CQ switch, which is an important step toward building ultra-high-speed switch fabrics.