• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.501-504
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• 2003

This paper presents a new fractal coding scheme to find more optimal transformation by estimation of the optimal attractor. The conventional fractal coding schemes based on the collage theorem obtain the transformation to minimize the distance between an original image and its collage image. Heavy computation is why the schemes widely adopt the theorem. In other words, the optimal transformation can be obtained after the attractors of all the possible transformations are generated and then compared with an original image. It is clear that this process is not practical. Therefore, we introduce a sub-optimal scheme that provides better transformation than the conventional scheme, relieving the complexity problem in the optimal transformation. In a simple case, the optimal transformation can be obtained considering all the attractors and then our scheme is compared with the optimal. In general cases not to be able to find the optimal, our scheme is also evaluated and compared with the conventional schemes.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1747-1750
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• 2003

This paper proposes a multilevel vector error diffusion for fast and accurate color reproduction. Proposed method considered both hue angle and Euclidean distance during the multilevel vector error diffusion procedure to improve time complexity and output image quality In the error diffusion process, it can be determined whether error is diffused or not by comparing the vector norm and lightness value between original vector and error corrected vector of neighborhood pixels. For adaptive selection of output patch, this paper computes chroma value of error corrected vector and compares the hue angle between error corrected input vector and 64 primary color vectors.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.292-294
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• 2007

Recently, for satisfying many application demands such as coding delay, computing power, transporting channel characteristic, etc, many profiles are supported in video coding standards. Therefore, in transcoding between same standards or between other standards, the functional difference of profiles supported by application occur many problems. In this paper, transcoding MPEG-2 main profile to H.264/AVC baseline profile which has restriction in the number of reference frame is focused. In this case, the bidirectional prediction supported in MPEG-2 main profile is not supported in H.264/AVC baseline profile. Also, in the restriction of reference frame, motion vectors in the MPEG-2 decoder as predictor should be adjusted. In this paper, the proposed algorithm is based on the characteristic of which motion. vector is uniform according to the distance from reference frame. The adaptive search techniques through the determination of the uniformity extremely reduce the computational complexity.

• Journal of information and communication convergence engineering
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• v.14 no.4
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• pp.215-221
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• 2016

We consider a design of a combined quantizer and estimator for distributed systems wherein each node quantizes its measurement without any communication among the nodes and transmits it to a fusion node for estimation. Noting that the quantization partitions minimizing the estimation error are not independently encoded at nodes, we focus on the parameter regions created by the partitions and propose a cluster-based quantization algorithm that iteratively finds a given number of clusters of parameter regions with each region being closer to the corresponding codeword than to the other codewords. We introduce a new metric to determine the distance between codewords and parameter regions. We also discuss that the fusion node can perform an efficient estimation by finding the intersection of the clusters sent from the nodes. We demonstrate through experiments that the proposed design achieves a significant performance gain with a low complexity as compared to the previous designs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2191-2201
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• 2012

Traffic classification seeks to assign packet flows to an appropriate quality of service (QoS) class based on flow statistics without the need to examine packet payloads. Classification proceeds in two steps. Classification rules are first built by analyzing traffic traces, and then the classification rules are evaluated using test data. In this paper, we use self-organizing map and K-means clustering as unsupervised machine learning methods to identify the inherent classes in traffic traces. Three clusters were discovered, corresponding to transactional, bulk data transfer, and interactive applications. The K-nearest neighbor classifier was found to be highly accurate for the traffic data and significantly better compared to a minimum mean distance classifier.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1105-1112
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• 2020

Gait recognition, as a promising biometric, can be used in video-based surveillance and other security systems. However, due to the complexity of leg movement and the difference of external sampling conditions, gait recognition still faces many problems to be addressed. In this paper, an improved convolutional neural network (CNN) based on Gabor filter is therefore proposed to achieve gait recognition. Firstly, a gait feature extraction layer based on Gabor filter is inserted into the traditional CNNs, which is used to extract gait features from gait silhouette images. Then, in the process of gait classification, using the output of CNN as input, we utilize metric learning techniques to calculate distance between two gaits and achieve gait classification by k-nearest neighbors classifiers. Finally, several experiments are conducted on two open-accessed gait datasets and demonstrate that our method reaches state-of-the-art performances in terms of correct recognition rate on the OULP and CASIA-B datasets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1733-1751
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• 2015

The IEEE 802.15.4 standard not only provides a maximum of seven guaranteed time slots (GTSs) for allocation within a superframe to support time-critical traffic, but also achieves ultralow complexity, cost, and power in low-rate and short-distance wireless personal area networks (WPANs). Real-time wireless body area sensor networks (WBASNs), as a special purpose WPAN, can perfectly use the IEEE 802. 15. 4 standard for its wireless connection. In this paper, we propose an adaptive GTS allocation scheme for real-time WBASN data transmissions with different priorities in consideration of low latency, fairness, and bandwidth utilization. The proposed GTS allocation scheme combines a weight-based priority assignment algorithm with an innovative starvation avoidance scheme. Simulation results show that the proposed method significantly outperforms the existing GTS implementation for the traditional IEEE 802.15.4 in terms of average delay, contention free period bandwidth utilization, and fairness.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.8-14
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• 2002

This article presents a new algorithm for the K Shortest Paths Problem which develops initial K shortest paths, and repeal to expose hidden shortest paths with dual approach and to replace the longest path in the present K paths. The initial solution which comprises K shortest paths among shortest paths to traverse each arc is made from bidirectional Dijkstra algorithm. When a crossing node that have two or more inward arcs is found at least three time by turns in this K shortest paths, one inward arc of this crossing node, which has minimum detouring distance, is chosen, and a new path is exposed with joining a detouring subpath from source to this inward arc and a spur of a feasible path from this crossing node to sink. This algorithm, requires worst case time complexity of $O(Kn^2),\;and\;O(n^2)$ in the case $K{\leq}3$.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1503-1516
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• 2019

In this paper, to improve the accuracy of long sentence similarity calculation, we proposed a sentence similarity calculation method based on a system similarity function. The algorithm uses word2vector as the system elements to calculate the sentence similarity. The higher accuracy of our algorithm is derived from two characteristics: one is the negative effect of penalty item, and the other is that sentence similar function (SSF) based on word2vector similar elements doesn't satisfy the exchange rule. In later studies, we found the time complexity of our algorithm depends on the process of calculating similar elements, so we build an index of potentially similar elements when training the word vector process. Finally, the experimental results show that our algorithm has higher accuracy than the word mover's distance (WMD), and has the least query time of three calculation methods of SSF.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.5
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• pp.598-605
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• 2016

One of the effective methods for angular deception against monopulse radar is a cross eye technique. The typical cross eye technique can cause significant angular errors to monopulse radar by using two transceivers which transmit the signals with opposite phases. However, typical cross eye systems have high complexity of implementation because two transceivers should be installed with enough distance on the platform. In this paper, we propose a new cross eye technique with single transceiver based on the multipath effect. Then, angular deception performance of the proposed technique is analyzed.