• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.23-31
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• 2010

The increasing demands on low-power, and low-complexity video encoder have been motivating extensive research activities on distributed video coding (DVC) in which the encoder compresses frames without utilizing inter-frame statistical correlation. In DVC encoder, contrary to the conventional video encoder, an error control code compresses the video frames by representing the frames in the form of syndrome bits. In the meantime, the DVC decoder generates side information which is modeled as a noisy version of the original video frames, and a decoder of the error-control code corrects the errors in the side information with the syndrome bits. The noisy observation, i.e., the side information can be understood as the output of a virtual channel corresponding to the orignal video frames, and the conditional probability of the virtual channel model is assumed to follow a Laplacian distribution. Thus, performance improvement of DVC systems depends on performances of the error-control code and the optimal reconstruction step in the DVC decoder. In turn, the performances of two constituent blocks are directly related to a better estimation of the parameter of the correlation channel. In this paper, we propose an algorithm to estimate the parameter of the correlation channel and also a low-complexity version of the proposed algorithm. In particular, the proposed algorithm minimizes squared-error of the Laplacian probability distribution and the empirical observations. Finally, we show that the conventional algorithm can be improved by adopting a confidential window. The proposed algorithm results in PSNR gain up to 1.8 dB and 1.1 dB on Mother and Foreman video sequences, respectively.

• Communications of Mathematical Education
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• v.33 no.3
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• pp.163-180
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• 2019

This study introduces a development of calculus contents which makes to understand the main concepts of calculus in a short period of time and to enhance problem solving and computational thinking for complex problems encountered in the real world for college freshmen with diverse backgrounds. As a concrete measure, we developed 'Teaching and Learning' contents and Python-based code for Calculus I and II which was used in actual classroom. In other words, the entire process of teaching and learning, action plan, and evaluation method for calculus class with Python based coding are reported and shared. In anytime and anywhere, our students were able to freely practice and effectively exercise calculus problems. By using the given code, students could gain meaningful understanding of calculus contents and were able to expand their computational thinking skills. In addition, we share a way that it motivated student activities, and evaluated students fairly based on data which they generated, but still instructor's work load is less than before. Therefore, it can be a teaching and learning model for college mathematics which shows a possibility to cover calculus concepts and computational thinking at once in a innovative way for the 21st century.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.931-936
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• 2006

This paper presents different issues of the real-time compression algorithms without compromising the video quality in the distributed environment. The theme of this research is to manage the critical processing stages (speed, information lost, redundancy, distortion) having better encoded ratio, without the fluctuation of quantization scale by using IP configuration. In this paper, different techniques such as distortion measure with searching method cover the block phenomenon with motion estimation process while passing technique and floating measurement is configured by discrete cosine transform (DCT) to reduce computational complexity which is implemented in this video codec. While delay of bits in encoded buffer side especially in real-time state is being controlled to produce the video with high quality and maintenance a low buffering delay. Our results show the performance accuracy gain with better achievement in all the above processes in an encouraging mode.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.210-219
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• 2017

This paper proposes a modified min-max algorithm (MMMA) for nonbinary quasi-cyclic low-density parity-check (NB-QC-LDPC) codes and an efficient parallel block-layered decoder architecture corresponding to the algorithm on a graphics processing unit (GPU) platform. The algorithm removes multiplications over the Galois field (GF) in the merger step to reduce decoding latency without any performance loss. The decoding implementation on a GPU for NB-QC-LDPC codes achieves improvements in both flexibility and scalability. To perform the decoding on the GPU, data and memory structures suitable for parallel computing are designed. The implementation results for NB-QC-LDPC codes over GF(32) and GF(64) demonstrate that the parallel block-layered decoding on a GPU accelerates the decoding process to provide a faster decoding runtime, and obtains a higher coding gain under a low $10^{-10}$ bit error rate and low $10^{-7}$ frame error rate, compared to existing methods.

• Genomics & Informatics
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• v.15 no.4
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• pp.170-177
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• 2017

HOTAIR is an lncRNA that has been known to have an oncogenic role in different cancers. There is limited knowledge of genetic and epigenetic elements and their interactions for the gene encoding HOTAIR. Therefore, understanding the molecular mechanism and its regulation remains to be challenging. We used different in silico analyses to find genetic and epigenetic elements of HOTAIR gene to gain insight into its regulation. We reported different regulatory elements including canonical promoters, transcription start sites, CpGIs as well as epigenetic marks that are potentially involved in the regulation of HOTAIR gene expression. We identified repeat sequences and single nucleotide polymorphisms that are located within or next to the CpGIs of HOTAIR. Our analyses may help to find potential interactions between genetic and epigenetic elements of HOTAIR gene in the human tissues and show opportunities and limitations for researches on HOTAIR gene in future studies.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.2
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• pp.17-22
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• 2004

In this paper, a concatenated RS and Turbo code is proposed for OFDM system over burst error channel. The concatenated code used in this study is a RS(255,202) code and a rate 1/2 turbo code. The turbo code uses 2 recursive systematic convolutional (RSC) code as the constituent codes and the parity bit are punctured to get the desired code rate. It is shown by simulation that the conventional OFDM system fails when there exists burst noise. The concatenated RS and turbo code obtains at least 5dB gain over the turbo code at the bit error probability of 10/sup -3/.

• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.102-107
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• 2010

This paper presented a rate-distortion estimation method for effective mode decision in H.264/AVC. In this approach, in order to decide a mode, laplacian distribution modeling of DCT coefficients is utilized, which do not need to such process as quantization, entropy coding. From the simulation results, proposed a method showed that rate-distortion between proposed scheme and practical value was almost the same and performed 0.02dB of PSNR gain.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.211-214
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• 1998

TCM(Trellis-Coded Modulation)은 대역폭과 전력이 제한된 채널환경에서 채널부호화 기술과 변조기술을 결합시켜 대역폭의 증가없이 에러정정능력을 개선시키는 통신 기술이다. 본 논문에서는 TCM 신호의 복호시 사용되는 Viterbi decoder에서 traceback depth의 감소에 따른 BER(Bit Error Rate)의 증가를 개선하기 위해 수신부에서 설정하는 traceback depth를 주기로 blocking하여 TCM encoder의 입력시퀀스에 zero padding bits를 추가시키는 새로운 알고리듬을 제안한다. 모의실험결과, traceback depth가 50인 hard decision의 경우 약 2~2.5dB, 4-level soft decision과 8-level soft decision의 경우 약 0.3~2dB의 coding gain을 얻을 수 있었다.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2714-2716
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• 2005

In this paper, we designed the adaptive fuzzy logic controller for crane system using neural network and real-coding genetic algorithm. The proposed algorithm show a good performance on convergence velocity and diversity of population among evolutionary computations. The weights of neural network is adaptively changed to tune the input/output gain of fuzzy logic controller. And the genetic algorithm was used to leam the feedforward neural network. As a result of computer simulation, the proposed adaptive fuzzy logic controller is superior to conventional controllers in moving and modifying the destination point.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.49-58
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• 2020

Non-orthogonal multiple access (NOMA) has been recognized as a significant technology in the fifth generation (5G) and beyond mobile communication, which encompasses the advanced smart convergence of the artificial intelligence (AI) and the internet of things (IoT). In NOMA, since the channel resources are shared by many users, it is essential to establish the user fairness. Such fairness is achieved by the power allocation among the users, and in turn, the less power is allocated to the stronger channel users. Especially, the first and second strong channel users have to share the extremely small amount of power. In this paper, we consider the power optimization for the two users with the small power. First, the closed-form expression for the power allocation is derived and then the results are validated by the numerical results. Furthermore, with the derived analytical expression, for the various channel environments, the optimal power allocation is investigated and the impact of the channel gain difference on the power allocation is analyzed.