• The Journal of the Acoustical Society of Korea
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• v.21 no.8
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• pp.719-726
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• 2002

In this paper, we present a layered watermarking technique for digital audio data that is capable of detecting timing change and adapting complexity in detection. The proposed watermarking uses echo hiding as the first layer, which enables the detector to estimate linear speed change. The spread spectrum watermark is then inserted in the second layer which includes additional information like copyright data. We use two kinds of sequences in the second layer, one of which is for synchronization and the other is for data. The results of previous layer are used to make estimate of timing change in the next layer. The detector in the presented method can select detecting range form the first layer to the first layer, second pre-layer, or second main-layer due to the required system specification. Experimental results show that the proposed watermarking technique is robust to several processing attacks including timing change.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.201-207
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• 2018

There is no known polynomial time algorithm for random-type quadratic assignment problem(RQAP) that is a NP-complete problem. Therefore the heuristic or meta-heuristic approach are solve the approximated solution for the RQAP within polynomial time. This paper suggests polynomial time algorithm for random type quadratic assignment problem (QAP) with time complexity of $O(n^2)$. The proposed algorithm applies one-to-one matching strategy between ascending order of sum of distance for each location and descending order of sum of quantity for each facility. Then, swap the facilities for reflect the correlation of distances of locations and quantities of facilities. For the experimental data, this algorithm, in spite of $O(n^2)$ polynomial time algorithm, can be improve the solution than genetic algorithm a kind of metaheuristic method.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.107-113
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• 2015

This paper presents a polynomial time algorithm to the minimum cardinality feedback edge set and minimum weight feedback edge set problems. The algorithm makes use of the property wherein the sum of the minimum spanning tree edge set and the minimum feedback edge set equals a given graph's edge set. In other words, the minimum feedback edge set is inherently a complementary set of the former. The proposed algorithm, in pursuit of the optimal solution, modifies the minimum spanning tree finding Kruskal's algorithm so as to arrange the weight of edges in a descending order and to assign cycle-deficient edges to the maximum spanning tree edge set MXST and cycle-containing edges to the feedback edge set FES. This algorithm runs with linear time complexity, whose execution time corresponds to the number of edges of the graph. When extensively tested on various undirected graphs both with and without the weighed edge, the proposed algorithm has obtained the optimal solutions with 100% success and accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2595-2618
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• 2018

In this paper, we investigate secure communication with the presence of multiple eavesdroppers (Eves) in a two-tier downlink dense heterogeneous network, wherein there is a macrocell base station (MBS) and multiple femtocell base stations (FBSs). Each base station (BS) has multiple users. And Eves attempt to wiretap a macrocell user (MU). To keep Eves ignorant of the confidential message, we propose a physical-layer security scheme based on cross-layer cooperation to exploit interference in the considered network. Under the constraints on the quality of service (QoS) of other legitimate users and transmit power, the secrecy rate of system can be maximized through jointly optimizing the beamforming vectors of MBS and cooperative FBSs. We explore the problem of maximizing secrecy rate in both non-colluding and colluding Eves scenarios, respectively. Firstly, in non-colluding Eves scenario, we approximate the original non-convex problem into a few semi-definite programs (SDPs) by employing the semi-definite relaxation (SDR) technique and conservative convex approximation under perfect channel state information (CSI) case. Furthermore, we extend the frame to imperfect CSI case and use the Lagrangian dual theory to cope with uncertain constraints on CSI. Secondly, in colluding Eves scenario, we transform the original problem into a two-tier optimization problem equivalently. Among them, the outer layer problem is a single variable optimization problem and can be solved by one-dimensional linear search. While the inner-layer optimization problem is transformed into a convex SDP problem with SDR technique and Charnes-Cooper transformation. In the perfect CSI case of both non-colluding and colluding Eves scenarios, we prove that the relaxation of SDR is tight and analyze the complexity of proposed algorithms. Finally, simulation results validate the effectiveness and robustness of proposed scheme.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.20-26
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• 1994

In this paper, we propose an algorithm on partitioning a network into several subsets where the cost of a net which connects nodes in k subsets is given as k(k-1)/2 indicating the typical pattern of complete graphs. This problem is one of generalizations for multiple-way partitioning proposed by Sanchis. $^{[5]}$ Its solution can be applied to resource allocation problem in distributed systems. The proposed algorithm expanded the algorithm of Fiduccia and Mattheyses$^{[3]}$ to handle the multiple-way partitioning simultaneously. It has time and space complexity linear to the size of the network. To evaluate the performance of the proposed algorithm, we implemented also a traditional cluster growth method which groups connected nodes for nets, and compared experimental results with those of the proposed algorithm. The proposed algorithm shows some enhancement made.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.8
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• pp.14-25
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• 2002

In this paper, we propose a modified AFC algorithm which is suitable for the implementation of WCDMA reverse link receiver modem. To reduce the complexity, the modified CP-FDD algorithm named 'Normalized CP-FDD' is applied to the AFC loop. The proposed FDD algorithm overcomes the conventional CP-FDD's sensitivity to the variance of input signal amplitude and increases the linear range of S -curve. Therefore, offset frequency estimation using the proposed scheme can be more stable than the conventional method. Unlike IS-95, since pilot symbol in WCDMA is not transmitted continuously, we introduce a moving average filter at the FDD input to increase the number of cross-product. So, tracking speed and stability are improved. For more rapid frequency acquisition and tracking, we adopt a multi-stage tracking mode. Using NCO having ROM table structure, the frequency offset is compensated. We applied the proposed algorithm in the implementation of WCDMA base station modem successfully.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.82-92
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• 2007

This paper describes a novel global shape (GS) feature based on radial basis function network (RBFN) and the extraction method of the proposed feature for 3D face recognition. RBFN is the weighted sum of RBfs, it well present the non-linearity of a facial shape using the linear combination of RBFs. It is the proposed facial feature that the weights of RBFN learned by the horizontal profiles of a face. RBFN based feature expresses the locality of the facial shape even if it is GS feature, and it reduces the feature complexity like existing global methods. And it also get the smoothing effect of the facial shape. Through the experiments, we get 94.7% using the proposed feature and hidden markov model (HMM) to match the features for 100 gallery set with those for 300 test set.

• Journal of the Korea Computer Graphics Society
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• v.17 no.4
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• pp.31-40
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• 2011

Projector-based visual systems are widely used for VR and experience display applications. But the illumination irregularity on the screen surface due to the screen material and its light reflection properties sometimes deteriorates the user experience. This phenomenon is particularly troublesome when the participants of the head tracking VR system such as CAVE or the motion generation experience system continually move around the system. One of reason to illumination irregularity is projector-screen specular reflection component to participant's eye's position and it's analysis needs high computation complexity. Similar to calculate specular lighting term using GPU's programmable shader, Our research adjusts every pixel's brightness in runtime with given 3D screen space model to reduce illumination irregularity. For doing that, Angle-based brightness compensate function are considered for specific screen installation and modified it for GPU-friendly compute and access. Two aspects are implemented, One is function access transformation from angular form to product and the other is piecewise linear interpolate approximation.

• Journal of Broadcast Engineering
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• v.14 no.5
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• pp.543-550
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• 2009

The most widely used block convolution method is the overlap save algorithm (OSA), where a block of M data to be convolved with a filter is concatenated with the previous block and 2M-point FFT and multiplications are performed for this overlapped block. By discarding half of the results, we obtain linear convolution results from the circular convolution. This paper proposes a new transform which reduces the block size to only M for the block convolution. The proposed transform can be implemented as the M multiplications followed by M-point FFT Hence, existing efficient FFT libraries and hardware can be exploited for the implementation of proposed method. Since the required transform size is half that of the conventional method, the overall computational complexity is reduced. Also the reduced transform size results in the reduction of data access time and cash miss-hit ratio, and thus the overall CPU time is reduced. Experiments show that the proposed method requires less computation time than the conventional OSA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.6
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• pp.1231-1243
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• 1997

Digital satellite communication channels have nonlinearities with memory due to saturation characteristics of traveling wave tube amplifier in the satellite and transmitter/receiver linear filters. In this paper, we propose a network structure and a learning algorithm for complex pi-sigma network (CPSK) and exploit CPSN in the problem of equalization of nonlinear satellite channels. The proposed CPSN is a complex-valued extension of real-valued pi-sigma network that is a higher-order feedforward network with fast learning while greatly reducing network complexity by utilizing efficient form of polynomials for many input variables. The performance of the proposed CPSN is demonstrated by computer simulations on the equalization of complex-valued QPSK input symbols distorted by a nonlinear channel modeled as a Volterra series and additive noise. The results indicate that the CPSN shows good equalization performance, fast convergence, and less computations as compared to conventional higher-order models such as Volterra filters.