• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.99-132
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• 2022

The purpose of this study is to propose AET (Augmented and Extended Topics), a novel method of synthesizing both LDA and BERTopic results, and to analyze the recently published LIS articles as an experimental approach. To achieve the purpose of this study, 55,442 abstracts from 85 LIS journals within the WoS database, which spans from January 2001 to October 2021, were analyzed. AET first constructs a WORD2VEC-based cosine similarity matrix between LDA and BERTopic results, extracts AT (Augmented Topics) by repeating the matrix reordering and segmentation procedures as long as their semantic relations are still valid, and finally determines ET (Extended Topics) by removing any LDA related residual subtopics from the matrix and ordering the rest of them by F₁ (BERTopic topic size rank, Inverse cosine similarity rank). AET, by comparing with the baseline LDA result, shows that AT has effectively concretized the original LDA topic model and ET has discovered new meaningful topics that LDA didn't. When it comes to the qualitative performance evaluation, AT performs better than LDA while ET shows similar performances except in a few cases.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.18-36
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• 2024

As interest in ESG has been increased, it is easy to find papers that empirically study that a company's ESG activities have a positive impact on the company's performance. However, research on what ESG activities companies should actually engage in is relatively lacking. Accordingly, this study systematically classifies ESG activities of companies and seeks to provide insight to companies seeking to plan new ESG activities. This study analyzes how Chinese manufacturing companies perform ESG activities based on their dynamic capabilities in the global economy and how they differ in their activities. This study used the ESG annual reports of 151 Chinese manufacturing listed companies on the Shanghai & Shenzhen Stock Exchange and ESG indicators of China Securities Index Company (CSI) as data. This study focused on the following three research questions. The first is to determine whether there are any differences in ESG activities between companies with high ESG scores (TOP-25) and companies with low ESG scores (BOT-25), and the second is to determine whether there are any changes in ESG activities over a 10-year period (2010-2019), focusing only on companies with high ESG scores. The results showed that there was a significant difference in ESG activities between high and low ESG scorers, while tracking the year-to-year change in activities of the top-25 companies did not show any difference in ESG activities. In the third study, social network analysis was conducted on the keywords of E/S/G. Through the co-concurrence matrix technique, we visualized the ESG activities of companies in a four-quadrant graph and set the direction for ESG activities based on this.

• 프린팅코리아
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• s.54
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• pp.112-115
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• 2006

한국옥외광고협회와 코엑스가 주최한 제15회 한국국제사인.디자인전(KORSIGN 2006, 이하 코사인전)이 지난 11월 2일부터 5일까지 서울 코엑스 태평양홀과 인도양홀에서 개최됐다. 역대 최대 규모로 열린 이번 행사는 전시장 면적이 기존의 태평양홀에서 인도양홀까지 확대외었으며, 참여업체 규모도 180개사 650부스로 대폭 늘어나고 행사기간동안 국내외 바이어 참관객 1만5천여명이 다녀가는 등 국내를 대표하는 사인전시회로서의 면모를 유갑없이 보여주었다.

• Distribution Business Review
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• no.2
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• pp.125-129
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• 2002

"대규모 할인점 하나가 들어서면 반경 5킬로미터 이내의 중소유통점포는 파리를 날린다." 한국수퍼마켓협동조합연합회에서 자회사인 (주)바로코사의 설립을 통해 신 유통혁신을 이루고자 할 당시의 시대상을 극명히 들어내는 말이다. 고객을 더 이상 단순한 구매행위에 만족하지 않았다. 쇼핑의 편리성, 다양성, 경제성, 오락성을 동시에 구가하길 바랬다.(중략)길 바랬다.(중략)

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.629-634
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• 2000

In this paper, we describe the structure of the DWMT (discrete wavelet multitone) transceiver for VDSL system. The DWMT transceiver consists of the transmultiplexer using cosine modulation filter bank (CMFB), time domain equalizer (TEQ) and frequency domain equalizer (FEQ) minimizing the effects of the transmission channel. For FEQ, we have expanded the conventional l-D linear transversal equalizer into 2-dimensions, i.e. time and subchannel axes and we have implemented it using the 2-dimensional LMS methods. In order to qualify the performance of FEQ, we have applied it to the DWMT based VDSL transceiver and the equalizer's performance is verified by simulation using the VDSL line test model specified by the ANSI T1E1.4 requirements.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.29-35
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• 2010

In this paper, we introduce a novel entropy coding method to improve the JPEG image compression standard. JPEG is one of the most widely used image compression methods due to its high visual quality for the compression ratio, and especially because of its high efficiency. Based on the observation that the blocks of data fed to the entropy coder usually contain consecutive sequences of numbers with small magnitudes including 0, 1, and -1, we separate those sequences from the data and encode them using a method dedicated to those values. We further improve the compression ratio based on the fact that this separation makes the lengths of blocks much shorter. In our experiment, we show that the proposed method can outperform the JPEG standard preserving its visual characteristics.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.11
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• pp.49-54
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• 2005

This paper proposes the low power MDCT algorithm for precise FV with minimum size of sub-window in mobile phone. Proposed algerian uses the coefficient at the middle of whole result process requiring the least number of calculations, since it has a good characteristic when used as standard of the FV and needs minimum amount of operation. In addition, using the DCT result related to the middle frequency makes the characteristic of FV more superior because it suppresses the impulsive noise and difference of focus values is larger than any others. The proposed algorithm is implemented using Verilog HDL and verified using Excalibur-ARM board.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2008.11a
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• pp.149-152
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• 2008

본 논문에서는 디지털화된 형태로 취득 및 저장된 홀로그램 신호를 압축하는 새로운 알고리즘을 제안한다. 제안한 알고리즘은 취득한 디지털 홀로그램을 일정한 영역으로 분리하여 다수의 세그먼트로 만든다. 광학적인 특성상 각각의 세그먼트들은 각각의 공간적인 위치에서 객체를 촬영한 것과 같은 성분을 포함한다. 다음으로, 이 세그먼트들에 대해서 Fresnel 변환의 기저함수와 유사한 코사인 변환(Discrete Cosine Transform)을 적용하면 원 객체와 유사한 정보를 얻게 된다. 시각적으로 유사한 특성을 갖는, 즉 상관성을 갖는 세그먼트들을 하나의 비디오 스트림으로 구성하고 MCTF(Motion Compensated Temporal Filtering)을 적용한다. MCTF를 통해 얻어진 두 개의 스트림은 MCTF 과정 동안 움직임 보상 과정을 거치면서 재구성되므로 상당히 높은 압축 효율을 보일 수 있다. 마지막으로 이러한 과정을 통해 얻어진 두 개의 스트림은 각각 H.264를 통해 압축된다. 실험결과를 살펴보면 기존의 연구에 비해서 약 11%의 압축 효율이 증가한 것을 확인할 수 있었다. 따라서 제안한 기술은 디지털 홀로그램의 부호화를 위한 좋은 연구 사례가 될 것으로 사료된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.18-28
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• 1997

This paper presents image data compression using a classified vector quantization (CVQ) which categories edge blocks according to the energy distribution of subimages in the discrete cosine transform domain. Classifying the edge blocks enhances visual quality of the compressed images while maintaining a high compression ratio. The proposed classification method categories subimages into eight lypes of edge features according to an energy distribution. A neural network, trained with the data generated from the proposed classification method, can successfully classify subimages to eight edge categories. Experimental results are given to show how the (1VQ method incorporatd with a neural network can produce faithful compressed image quality for high compression ratios.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.727-732
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• 2012

This paper presents an approach to classify normal and arrhythmia from the MIT-BIH Arrhythmia Database using Discrete Cosine Transform(DCT), Discrete Wavelet Transform(DWT) and neural network. In the first step, Discrete Cosine Transform is used to obtain the representative 15 coefficients for input features of neural network. In the second step, Discrete Wavelet Transform are used to extract maximum value, minimum value, mean value, variance, and standard deviation of detail coefficients. Neural network classifies normal and arrhythmia beats using 55 numbers of input features, and then the accuracy rate is 98.8%.