• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.41-48
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• 2020

The sensor nodes in underwater IoT networks have practical limitations in power supply. Thus, the reduction of power consumption is one of the most important issues in underwater environments. In this regard, AMC(Adaptive Modulation and Coding) techniques are used by using the relation between SNR and BER. However, according to our hands-on experience, we observed that the relation between SNR and BER is not that tight in underwater environments. Therefore, we propose a deep learning based MLP classification model to reflect multiple underwater channel parameters at the same time. It correctly predicts BER with a high accuracy of 85.2%. The proposed model can choose the best parameters to have the highest throughput. Simulation results show that the throughput can be enhanced by 4.4 times higher than the conventionally measured results.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.274-292
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• 2011

This paper proposes an efficient coding method of the depth-map which is different from the natural images. The depth-map are so smooth in both inner parts of the objects and background, but it has sharp edges on the object-boundaries like a cliff. In addition, when a depth-map block is decomposed into bit planes, the characteristic of perfect matching or inverted matching between bit planes often occurs on the object-boundaries. Therefore, the proposed depth-map coding scheme is designed to have the bit-plane unit coding method using the adaptive XOR method for efficiently coding the depth-map images on the object-boundary areas, as well as the conventional DCT-based coding scheme (for example, H.264/AVC) for efficiently coding the inside area images of the objects or the background depth-map images. The experimental results show that the proposed algorithm improves the average bit-rate savings as 11.8 % ~ 20.8% and the average PSNR (Peak Signal-to-Noise Ratio) gains as 0.9 dB ~ 1.5 dB in comparison with the H.264/AVC coding scheme. And the proposed algorithm improves the average bit-rate savings as 7.7 % ~ 12.2 % and the average PSNR gains as 0.5 dB ~ 0.8 dB in comparison with the adaptive block-based depth-map coding scheme. It can be confirmed that the proposed method improves the subjective quality of synthesized image using the decoded depth-map in comparison with the H.264/AVC coding scheme. And the subjective quality of the proposed method was similar to the subjective quality of the adaptive block-based depth-map coding scheme.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.732-743
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• 2008

In H.264/AVC, 4$\times$4 block transform is used for intra and inter prediction instead of 8$\times$8 block transform. Using small block size coding, H.264/AVC obtains high temporal prediction efficiency, however, it has limitation in utilizing spatial redundancy. Motivated on these points, we propose a multi-dimensional transform which achieves both the accuracy of temporal prediction as well as effective use of spatial redundancy. From preliminary experiments, the proposed multi-dimensional transform achieves higher energy compaction than 2-D DCT used in H.264. We designed an integer-based transform and quantization coder for multi-dimensional coder. Moreover, several additional methods for multi-dimensional coder are proposed, which are cube forming, scan order, mode decision and updating parameters. The Context-based Adaptive Variable-Length Coding (CAVLC) used in H.264 was employed for the entropy coder. Simulation results show that the performance of the multi-dimensional codec appears similar to that of H.264 in lower bit rates although the rate-distortion curves of the multi-dimensional DCT measured by entropy and the number of non-zero coefficients show remarkably higher performance than those of H.264/AVC. This implies that more efficient entropy coder optimized to the statistics of multi-dimensional DCT coefficients and rate-distortion operation are needed to take full advantage of the multi-dimensional DCT. There remains many issues and future works about multi-dimensional coder to improve coding efficiency over H.264/AVC.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.5
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• pp.765-776
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• 1995

This paper describes a speaker adaptation method to improve the recognition performance of MLP(multiLayer Perceptron) based HMM(Hidden Markov Model) speech recognizer. In this method, we use lst-order linear transformation network to fit data of a new speaker to the MLP. Transformation parameters are adjusted by back-propagating classification error to the transformation network while leaving the MLP classifier fixed. The recognition system is based on semicontinuous HMM's which use the MLP as a fuzzy vector quantizer. The experimental results show that rapid speaker adaptation resulting in high recognition performance can be accomplished by this method. Namely, for supervised adaptation, the error rate is signifecantly reduced from 9.2% for the baseline system to 5.6% after speaker adaptation. And for unsupervised adaptation, the error rate is reduced to 5.1%, without any information from new speakers.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.398-406
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• 2013

In this paper, we investigate two types of in-phase and quadrature-phase (IQ) data transfer methods for cloud multiple-input multiple-output (MIMO) network operation. They are termed "after-precoding" and "before-precoding". We formulate a cloud massive MIMO operation problem that aims at selecting the best IQ data transfer method and transmission strategy (beamforming technique, the number of concurrently receiving users, the number of used antennas for transmission) to maximize the ergodic sum-rate under a limited capacity of the digital unit-radio unit link. Based on our proposed solution, the optimal numbers of users and antennas are simultaneously chosen. Numerical results confirm that the sum-rate gain is greater when adaptive "after/before-precoding" method is available than when only conventional "after-precoding" IQ-data transfer is available.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.5
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• pp.435-446
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• 2014

Even if it is important to transmit high rate multimedia information without any transmission errors for surveillance systems, it is difficult to achieve error-free transmission due to infra-less adhoc networks. In order to reduce the transmission errors furthermore, additional signal overheads or retransmission of signals should be required, but they may lead to transmission delay. This paper represents a study on low delay and adaptive video transmission for the unmanned surveillance systems by developing system protocols. In addition, we introduce an efficient and adaptive control algorithm using system parameters for exploiting unmanned surveillance system properly over multi-channels.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.361-368
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• 2014

The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.26-35
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• 2009

In this paper, we investigate how to do resource allocation to guarantee a minimum user data rate at low signaling overhead in multi-cell orthogonal frequency division multiple access (OFDMA) wireless systems. We devise dynamic resource allocation (DRA) algorithms that can minimize the QoS violation ratio (i.e., the ratio of the number of users who fail to get the requested data rate to the total number of users in the overall network). We assume an OFDMA system that allows dynamic control of frequency reuse factor (FRF) of each sub-carrier. The proposed DRA algorithms determine the FRFs of the sub-carriers and allocate them to the users adaptively based on inter-cell interference and load distribution. In order to reduce the signaling overhead, we adopt a hierarchical resource allocation architecture which divides the resource allocation decision into the inter-cell coordinator (ICC) and the base station (BS) levels. We limit the information available at the ICC only to the load of each cell, that is, the total number of sub-carriers required for supporting the data rate requirement of all the users. We then present the DRA with limited coordination (DRA-LC) algorithm where the ICC performs load-adaptive inter-cell resource allocation with the limited information while the BS performs intra-cell resource allocation with full information about its own cell. For performance comparison, we design a centralized algorithm called DRA with full coordination (DRA-FC). Simulation results reveal that the DRA-LC algorithm can perform close to the DRA-FC algorithm at very low signaling overhead. In addition, it turns out to improve the QoS performance of the cell-boundary users, and achieve a better fairness among neighboring cells under non-uniform load distribution.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.165-175
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• 2007

The mobile agent executes a given task by which the agent code moves to the server directly. Therefore, node migration method becomes an important factor which impact on the whole performance of distributed system. In this paper, we propose an adaptive migration path technique of mobile agent using the metadata of naming agent. In this proposed technique, node selection for migration depends on the content of referenced metadata, and the reliability of migrated information is determined by the metadata updating method and cooperative operations of individual agents in multi-agents system. For these, we design the metadata using by the number of hit documents, hit ratio, node processing time and network delay time, and describe the methods for creating, using and updating metadata for which determine the adaptive node migration path of mobile agent according to the cooperation of individual agents and number of hit documents using by designed metadata. And results of evaluated performance for proposed adaptive migration path technique through the proper experiment and analysis gain rate of high effective information earning, because of high hit ratio(72%) about of fathered documents by case of applying metadata move to the 13 nodes. But, in case of non-applying metadata is hit ratio(46%) of gathered documents and rate of effective information earning about of 26 nodes is 36.8%.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.137-145
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• 2004

In this paper, a new algorithm for the segmentation of the multi moving objects at the 3 dimension space and the method of measuring the distance from the camera to the moving object by using stereo video monitoring system is proposed. It get the input image of left and right from the stereo video monitoring system, and the area of the multi moving objects segmented by using adaptive threshold and PRA(pixel recursive algorithm). Each of the object segmented by window mask, then each coordinate value and stereo disparity of the multi moving objects obtained from the window masks. The distance of the multi moving objects can be calculated by this disparity, the feature of the stereo vision system and the trigonometric function. From the experimental results, the error rate of a distance measurement be existed within 7.28％, therefore, in case of implementation the proposed algorithm, the stereo security system, the automatic moving robot system and the stereo remote control system will be applied practical application.