• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.123-132
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• 2011

Recently, DVC (Distributed Video Coding) is receiving a lot of attention as one of the low complexity video encoding techniques suitable for various applications with computation-limited and/or power-limited environment, and is being actively studied for improving the coding efficiency. This paper proposes a rate-distortion based selective block encoding scheme. First, the motion information is obtained in the process of generating side information at decoder and received through the feedback channel, and then, based on this information, the proposed method performs a selective block encoding based on rate-distortion optimization. Experimental results show that the performance of the proposed scheme reaches up to 2.2 dB PSNR gain over the existing scheme. Moreover, it is shown that the complexity can be reduced by encoding parts of region considering rate-distortion cost.

• Journal of Broadcast Engineering
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• v.15 no.5
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• pp.642-652
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• 2010

Recently, DVC (Distributed Video Coding) techniques are drawing a lot of interests as one of the future research works to achieve low complexity encoding in various applications. But, due to the limited computational complexity, the performances of DVC algorithms are inferior to those of conventional international standard video coders, which use zig-zag scan, run length code, entropy code and skipped macroblock. In this paper, in order to overcome the performance limit of the DVC system, the distortion for every block is estimated when side information is found at the decoder and then we propose a new selective block encoding scheme which provides the encoder side with the motion information for the highly distorted blocks and then allows the sender to encode the motion compensated frame difference signal. Through computer simulations, it is shown that the coding efficiency of the proposed scheme reaches almost that of the conventional inter-frame coding scheme.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.820-831
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• 2020

Extractive document summarization aims to select a few sentences while preserving its main information on a given document, but the current extractive methods do not consider the sentence-information repeat problem especially for news document summarization. In view of the importance and redundancy of news text information, in this paper, we propose a neural extractive summarization approach with joint sentence semantic clipping and selection, which can effectively solve the problem of news text summary sentence repetition. Specifically, a hierarchical selective encoding network is constructed for both sentence-level and document-level document representations, and data containing important information is extracted on news text; a sentence extractor strategy is then adopted for joint scoring and redundant information clipping. This way, our model strikes a balance between important information extraction and redundant information filtering. Experimental results on both CNN/Daily Mail dataset and Court Public Opinion News dataset we built are presented to show the effectiveness of our proposed approach in terms of ROUGE metrics, especially for redundant information filtering.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.397-400
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• 2002

In this paper, a novel noncoherent multiuser detector with diversity reception for a differentially encoded DS/CDMA signal in a frequency-selective Rayleigh fading channel is proposed. The proposed receiver employs multipath decorrelator and decision feedback differential detector (DFDD) with diversity reception. DFDD performs differential encoding and diversity combining. The performance is obtained by analysis and simulation and it is sown that the proposed receiver outperforms conventional differential receiver with slight increase of complexity.

• The Journal of Korea Robotics Society
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• v.8 no.1
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• pp.1-7
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• 2013

Body gesture Recognition has been one of the interested research field for Human-Robot Interaction(HRI). Most of the conventional body gesture recognition algorithms used Hidden Markov Model(HMM) for modeling gestures which have spatio-temporal variabilities. However, HMM-based algorithms have difficulties excluding meaningless gestures. Besides, it is necessary for conventional body gesture recognition algorithms to perform gesture segmentation first, then sends the extracted gesture to the HMM for gesture recognition. This separated system causes time delay between two continuing gestures to be recognized, and it makes the system inappropriate for continuous gesture recognition. To overcome these two limitations, this paper suggests primitive body model encoding, which performs spatio/temporal quantization of motions from human body model and encodes them into predefined primitive codes for each link of a body model, and Selective/Asynchronous Input-Parallel State machine(SAI-PSM) for multiple-simultaneous gesture recognition. The experimental results showed that the proposed gesture recognition system using primitive body model encoding and SAI-PSM can exclude meaningless gestures well from the continuous body model data, while performing multiple-simultaneous gesture recognition without losing recognition rates compared to the previous HMM-based work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4275-4291
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• 2021

With the unprecedented growth of textual information on the Internet, an efficient automatic summarization system has become an urgent need. Recently, the neural network models based on the encoder-decoder with an attention mechanism have demonstrated powerful capabilities in the sentence summarization task. However, for paragraphs or longer document summarization, these models fail to mine the core information in the input text, which leads to information loss and repetitions. In this paper, we propose an abstractive document summarization method by applying guidance signals of key sentences to the encoder based on the hierarchical encoder-decoder architecture, denoted as KI-HABS. Specifically, we first train an extractor to extract key sentences in the input document by the hierarchical bidirectional GRU. Then, we encode the key sentences to the key information representation in the sentence level. Finally, we adopt key information representation guided selective encoding strategies to filter source information, which establishes a connection between the key sentences and the document. We use the CNN/Daily Mail and Gigaword datasets to evaluate our model. The experimental results demonstrate that our method generates more informative and concise summaries, achieving better performance than the competitive models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10A
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• pp.1473-1479
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• 2000

This paper presents the performance evaluation of an adaptive QAM scheme under flat and frequency selective fading channels for indoor wireless communication systems. The QAM modulation is combined with differential encoding and the demodulation process is carried out noncoherently. The adaptation is performed by varying the modulation level of QAM, depending upon received signal strength. The adaptation mechanism allows a 2- or 3-bit increase or decrease at a time, if the channel condition is considered to be significantly good or bad. Simulation results show that the average number of bits per symbol (ABPS) for each symbol block transmitted over a flat fading channel is higher than 5.0 and the BER performance is better than 10^-4 for a SNR value higher than 30 dB. For frequency selective fading channels, an oversampling technique in the receiver was employed. The BER performance obtained for frequency selective fading channels is better than 10^-4 with a SNR value of 40 dB and ABPS is found to be approximately 5.5. Therefore, this scheme is very useful in that it provides both very high bandwidth efficiency and acceptable performance with moderate SNR values over flat and frequency selective fading channels. In addition, this scheme provides reduced receiver complexity by way of noncoherent detection.

• Journal of IKEEE
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• v.22 no.4
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• pp.1163-1167
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• 2018

The selective encryption scheme for canonical Huffman codes using the inversion of bit values is proposed. The symbols are divided into blocks of a certain size, and each symbol in the block is compressed by canonical Huffman coding. Blocks are determined to be sent in the original code or encrypted form. The encryption block inverts the values of the whole bits, and bits of block that do not encrypt are not inverted. Those compressed data are transmitted with the encryption information. It is possible to decrypt the compressed data on the receiving side using the encryption information and compressed data.

• Journal of Broadcast Engineering
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• v.11 no.3 s.32
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• pp.326-335
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• 2006

Design criteria far a block code which guarantees minimized PAPR of the OFDM signals are proposed in this paper. Encoding procedure of the minimum PAPR codes (MPC) is composed of searching a seed codeword, circular shifting the register elements, and determining codeword inversion. It is shown that the PEP is invariant to the circular shift of register elements and codeword inversion. Based on such properties, systematic encoding rule for MPC is proposed. In addition proposed encoding rule can reduced greatly the size of look up table for MPC.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2056-2059
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• 2003

The rate control is very important to solve the difficulties arising from bit-rate on transmission through channel and to improve video quality. It is very important to point out that the amount of output bit obtained the encoding process using rate controller brings many problems on the transmission of channels and furthermore output bitstream decoded affects directly on the visual quality of displayed subject. In this paper, the effective rate control algorithm by rate-distortion modeling using MPEG-4 encoder is proposed. The proposed rate control has applied different weighting by VOP prediction type and even in the same VOP prediction type, the predicted reference allocates more bit. Through these bit allocation the minimization of distortion can be achieved preventing propagation of quantization error The amount of saved bitstream obtained by the proposed algorithm in this thesis is allocated to I-VOP using region of interest(ROI) selective enhancement on the next GOV encoding process and this process brought the improvement of visual quality.