• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.27-36
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• 2019

In this paper, we propose a method to find the most similar answer to the user's response from the question-answer database in order to avoid generating a redundant question in retrieval-based automatic question generation system. As a question of the most similar answer to user's response may already be known to the user, the question should be removed from a set of question candidates. A similarity detector calculates a similarity between two answers by utilizing the same words, paraphrases, and sentential meanings. Paraphrases can be acquired by building a phrase table used in a statistical machine translation. A sentential meaning's similarity of two answers is calculated by an attention-based convolutional neural network. We evaluate the accuracy of the similarity detector on an evaluation set with 100 answers, and can get the 71% Mean Reciprocal Rank (MRR) score.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.891-897
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• 2003

Partial response maxim likelihood (PRML) is a powerful and indispensable detection scheme for perpendicular magnetic recording channels. The performance of PRML can be improved by incorporating a noise prediction scheme into branch metric computations of Viterbi algorithm (VA). However, the systems constructed by VA have shortcomings in the form of high complexity and cost. In this connection, a new simple detection scheme is proposed by exploiting the minimum run-length parameter d=1 of RLL code. The proposed detection scheme have a slicer instead of Viterbi detector and a noise predictor as a feedback filter. Therefore, to improve BER performance, the proposed detection scheme is extended to dual detection scheme for improving the BER performance. Simulation results show that the proposed scheme has a comparable performance to noise-predictive maximum likelihood (NPML) detector with less complexity when the partial response (PR) target is (1,2,1).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9C
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• pp.840-845
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• 2006

This paper presents a partial response maximum likelihood (PRML) detection method using partial response signal-to-noise ratio (PRSNR) that evaluates the signal quality of asymmetric optical recording channel. It is confirmed that the equalizer maximizing the PRSNR value can be most properly adapted to the asymmetric optical recording channel. The proposed PRML detection using this result has 1.8dB SNR gain at $8.5{\times}10-5$ bit error rate compared to PRML detection using typical adaptive equalizer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.77-82
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• 2005

Partial response maximum likelihood (PRML) detection using the Viterbi algorithm involves the calculation of likelihood metrics that determine the most likely sequence of decoded data. In general, it is assumed that branches at each node in the trellis diagram have same probabilities. If modulation code with minimum and maximum run-length constraints is used, the occurrence ratio (Ro) of each particular pattern is different, and therefore the assumption is not true. We present a calculation scheme of the likelihood metrics for the PRML detection using the occurrence ratio. In simulation, we have tested the two (1,7) run-length-limited codes and calculated the occurrence ratios as the orders of PR targets are changed. We can identify that the PRML detections using the occurrence ratio provide more than about 0.5dB gain compared to conventional PRML detections at 10/sup -5/ BER in high-density magnetic recording and optical recording channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.927-932
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• 2006

We Propose a partial response maximum likelihood(PRML) detection method that improves the performance of the high-density optical storage system. It concurrently adjusts the coefficient of equalizer and reference values of branches in Viterbi detector. For the estimation of asymmetric channel characteristics by the tangential tilt, we exploit sync patterns in each data frame. The simulation result shows it improves the Performance up to 4dB at 10-6 BER compared to conventional adaptive PRML.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.871-876
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• 2005

In this paper, we propose an improved partial response maximum likelihood (PRML) detection scheme that has an adaptive equalizer and can be applied in the asymmetric optical recording system with high-density. We confirmed that the proposed PRML detector improves detection performance. In addition, we implemented the detector by Verilog HDL. The adaptive equalizer is composed of tap coefficient updating unit using LMS algorithn and FIR filter. FIR filter is implemented by the transposed direct form architecture for high speed operation. Viterbi detector is implemented by the register exchange method.

• Annual Conference on Human and Language Technology
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• 2019.10a
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• pp.465-469
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• 2019

자연어 처리를 위해서 두 문장의 의미 유사성을 분석하는 것은 아주 중요하다. 이 논문은 패러프레이즈 검출 태스크를 수행하기 위한 Paraphrase-BERT를 제안한다. 우선 구글이 제안한 사전 학습된 BERT를 그대로 이용해서 패러프레이즈 데이터 (MRPC)를 가지고 파인 튜닝하였고 추가적으로 최근에 구글에서 새로 발표한 Whole Word Masking 기술을 사용하여 사전 학습된 BERT 모델을 새롭게 파인 튜닝하였다. 그리고 마지막으로 다중 작업 학습을 수행하여 성능을 향상시켰다. 구체적으로 질의 응답 태스크와 패러프레이즈 검출 태스크를 동시에 학습하여 후자가 더 잘 수행될 수 있도록 하였다. 결과적으로 점점 더 성능이 개선되었고 (11.11%의 정확도 향상, 7.88%의 F1 점수 향상), 향후 작업으로 파인 튜닝하는 방법에 대해서 추가적으로 연구할 계획이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.767-770
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• 2018

인공지능의 발달로 사람이 사용하는 자연어 형태의 문장을 통해 정보를 주고받는 질의응답 시스템이 주목받고 있다. 이러한 질의응답 시스템은 자연어로 구성된 사용자의 질의문에서 의도를 정확하게 파악해야 한다. 단순히 질의어의 키워드에 의존한 검색은 단어의 중의성을 고려하지 않아 질의문의 의도를 정확히 파악하는 데 문제가 있다. 이런 문제점을 해결하기 위해 질의문의 의미와 맥락에 따른 연관성을 이용하여 유의어를 확장하는 방법이 연구되고 있다. 본 논문에서는 워드 임베딩을 통해 생성된 단어 유사도를 이용하여 질의문에서 추출된 키워드를 확장하는 방법을 제안한다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.6
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• pp.49-58
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• 2002

Based on electrophysiological retina mechanism, a retina model is proposed, which has similar response characteristics compared with the real primate retina. Photoreceptors, horizontal cells, and bipolar cells are modeled based on the previously studied retina models. And amacrine cells known to have relation to movements detection, and bipolar cell terminals are newly modeled using 3 NDP mechanism. The proposed model verified by analyzing the spatial response characteristics to stationary and moving stimuli, and characteristics for different speeds. Through this retina model, human vision system could be applied to computer vision systems for movement detection, and it could be the basic research for the implantable artificial retina.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.178-185
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• 2009

A signal processing algorithm is proposed for end point detection which is used commonly in accelerometers-based pattern recognition problem. In the conventional method, end points are detected by manual manipulation with an additive button or algorithm based on statistical computation and highpass filtering to cause critical time delay and difficulty for parameters optimization. As an solution, we propose a focused Time Lagged Feedforward Network(TLFN) with respect to a differential signal of acceleration, which is widely applied for time series forecasting. The simple experiment is conducted with handwriting and the detection performance and response characteristic of the proposed algorithm is tested and analyzed.