• 한국전자파학회:학술대회논문집
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• 한국전자파학회 2003년도 종합학술발표회 논문집 Vol.13 No.1
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• pp.163-167
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• 2003

In this paper, an air-suspension type RF MEMS inductor is fabricated, and an appropriate de-embedding scheme for 3-dimenstional MEMS structure is applied and verified with inductance calculation algorithm. With the presented de-embedding method, parasitics from contanct pads and feeding lines are effectively and accurately de-embedded using open and short calibration procedure, and only spiral and posts can be characterized as a high-Q inductor structure. The validity of the de-embedding method is verified by the comparison of the measured and calculated inductances of two 1.5 and 2.5 turn square spiral inductors. The open-short de-embedded inductance error is below 5% each case in comparison with the calculated value based on H.M. Greenhouse's algorithm.

• 한국지능시스템학회논문지
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• 제13권3호
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• pp.310-315
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• 2003

본 논문에서는 SC-CNN의 특성을 이용한 임베딩 구동 카오스 동기화(Embedding Drive Synchronization) 방법을 소개하고 이 동기화 방법을 통한 비밀통신을 제안한다. 새로 제안한 임베딩 구동동기는 일반적인 구동동기 방법에서 모든 상태 변수를 구동시키는 방법과 달리 상태 변수 중 한 성분만을 구동시키는 방법이다. 본 논문에서는 SC＿CNN에서 임베딩 구동 동기화를 먼저 이룬 후 비밀통신에 적용하였다.

• 한방비만학회지
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• 제12권2호
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• pp.1-7
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• 2012

Objectives: The purpose of this report was to review the clinical trials of the catgut embedding for obesity treatment. Methods: We searched the clinical trial papers with key words of obesity and catgut embedding via searching Pubmed, Scopus and KISS etc. Results: We reviewed 8 searched articles, 7 articles were conducted in China and only 1 article was published in Korea. Most of Chinese articles used acupuncture as a control group and revealed the equality or superiority of catgut embedding in body weight loss. The only Korean article, which was uncontrolled, implanted catgut in localized fat area, it had changes partially in fat thick, body size. Conclusions: The acupoint catgut embedding has the efficacy of body weight loss, but to confirm the efficacy of localized fat loss, more randomized controlled trials are needed.

• Journal of Acupuncture Research
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• 제36권1호
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• pp.55-58
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• 2019

The aim of this study was to investigate the efficacy of treatment with thread-embedding therapy for 24 patients with hemifacial spasm (HFS). The muscle spasm of these patients was treated with thread-embedding therapy. Patients with nuchal pain were treated with tendino-musculature acupuncture in the sternocleidomastoid, splenius, and trapezius muscles. We evaluated the treatment effect using the Scott's scale, where 20, 3, 1, and 0 patients presented Scott's grade 0, grade 1, grade 2, and grade 3, respectively. The grade of the spasm intensity decreased noticeably after treatment. The results revealed that the Scott's grade changed to 0 in 83.3% of HFS patients, and 91.7% patients felt satisfied with thread-embedding therapy. These findings suggested that thread-embedding therapy was effective and can be used widely for HFS.

• Journal of Multimedia Information System
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• 제9권2호
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• pp.93-102
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• 2022

Dependency parsing is a decision problem of the syntactic relation between words in a sentence. Recently, deep learning models are used for dependency parsing based on the word representations in a continuous vector space. However, it causes a mislabeled tagging problem for the proper nouns that rarely appear in the training corpus because it is difficult to express out-of-vocabulary (OOV) words in a continuous vector space. To solve the OOV problem in dependency parsing, we explored the proper noun embedding method according to the embedding unit. Before representing words in a continuous vector space, we replace the proper nouns with a special token and train them for the contextual features by using the multi-layer bidirectional LSTM. Two models of the syllable-based and morpheme-based unit are proposed for proper noun embedding and the performance of the dependency parsing is more improved in the ensemble model than each syllable and morpheme embedding model. The experimental results showed that our ensemble model improved 1.69%p in UAS and 2.17%p in LAS than the same arc-eager approach-based Malt parser.

• ETRI Journal
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• 제44권4호
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• pp.599-612
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• 2022

This study focuses on improving a word embedding model to enhance the performance of downstream tasks, such as those of dialog systems. To improve traditional word embedding models, such as skip-gram, it is critical to refine the word features and expand the context model. In this paper, we approach the word model from the perspective of subword embedding and attempt to extend the context model by integrating various sentence models. Our proposed sentence model is a subword-based skip-thought model that integrates self-attention and relative position encoding techniques. We also propose a clustering-based dialog model for downstream task verification and evaluate its relationship with the sentence-model-based subword embedding technique. The proposed subword embedding method produces better results than previous methods in evaluating word and sentence similarity. In addition, the downstream task verification, a clustering-based dialog system, demonstrates an improvement of up to 4.86% over the results of FastText in previous research.

• 한방재활의학과학회지
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• 제33권3호
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• pp.129-134
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• 2023

Objectives The purpose of this study was to review the studies of catgut embedding related to obesity treatment. Methods We searched the papers with key words of obesity and catgut embedding via searching Research Information Sharing Service, DBpia, Koreanstudies Information Service System, Oriental Medicine Advanced Searching Integrated System, Scopus, PubMed. Additional data including study design, study topics, characteristics of participants and treatment, outcomes was extracted from full text of each study. Results There were nine studies about the catgut embedding related to obesity treatment. Five articles were conducted in China, two articles were conducted in Mexico, and two articles was published in Korea. Analysis of seven experimental studies and two observational studies were conducted to describe each research subject, method, and research results. Conclusions More interest and further research will be needed on catgut embedding related to obesity treatment in the Korean medicine to achieve clinical application and to develop treatment protocols for the obesity disease.

• 동의생리병리학회지
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• 제31권1호
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• pp.25-35
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• 2017

About 60% to 90% of a total population experience low back pain at least once of life, and about 35% to 79% among them experience a recurrent and chronic low back pain. thread-embedding therapy is mainly used to improve appearance or treat obesity in early stage, but recently it is also used to treat musculoskeletal pain. This study aimed to search Chinese study using thread-embedding therapy on low back pain and to analyse their methodology. Three Chinese database(CNKI(www.cnki.net), WANFANG(www.wanfangdata.com), WEIPU(www.cqvip.com)) were searched for clinical study of thread-embedding therapy up to March 2016. The characteristics of included studies and regimen of thread-embedding in those studies were analyzed. The total 21 studies (4 case studies, 16 non-randomized controlled trials, 1 randomized controlled trial) were included. All studies on thread embedding treatment of low back pain reported that its effectiveness was very good. The most frequently used acupoints was Ashi acupoints and acupoints on bladder meridian(BL) or governor vessel(GV). Thread-embedding therapy is considered very useful for low back pain in Traditional Chinese medicine. Further studies are needed to investigate the effect of thread-embedding therapy and to expand its application. This study is limited in that the literature search in the Chinese database were restricted.

• 방송공학회논문지
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• 제16권5호
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• pp.801-810
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• 2011

본 논문에서는 디지털 영상을 위한 공간 영역에서의 무손실 데이터 삽입 방법을 제안한다. 제안하는 방법은 데이터 삽입 및 추출을 위해 위치 지도 등의 부가 정보를 삽입하는 대신에 단 한 개의 파라미터 만을 필요로 한다. 삽입 과정에서는 $3{\times}3$ 크기의 창이 대상 영상 위를 한 화소 단위로 움직이며 각 위치에서 한 비트의 데이터를 삽입 할 수 있다. 따라서, 이상적인 삽입 용량은 영상의 화소수와 동일하다. 또한, 추가적인 실제 삽입 용량의 증가를 위해, 삽입 대상 화소의 예측을 위한 새로운 계수를 적용하였다. 그 결과 기존의 방법에 비해 삽입 용량이 매우 큰 폭으로 증가하고, 고용량 데이터 삽입 시의 영상 화질 또한 향상되었다. 제안 방법은 컴퓨터 시뮬레이션을 통해 검증하였다.

• 한국융합학회논문지
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• 제9권10호
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• pp.45-53
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• 2018

최근 이중 언어 임베딩(bilingual word embedding) 관련 연구들이 각광을 받고 있다. 그러나 한국어와 특정 언어로 구성된 병렬(parallel-aligned) 말뭉치로 이중 언어 워드 임베딩을 하는 연구는 질이 높은 많은 양의 말뭉치를 구하기 어려우므로 활발히 이루어지지 않고 있다. 특히, 특정 영역에 사용할 수 있는 로컬 이중 언어 워드 임베딩(local bilingual word embedding)의 경우는 상대적으로 더 희소하다. 또한 이중 언어 워드 임베딩을 하는 경우 번역 쌍이 단어의 개수에서 일대일 대응을 이루지 못하는 경우가 많다. 본 논문에서는 로컬 워드 임베딩을 위해 한국어-영어로 구성된 한국 법률 단락 868,163개를 크롤링(crawling)하여 임베딩을 하였고 3가지 연결 전략을 제안하였다. 본 전략은 앞서 언급한 불규칙적 대응 문제를 해결하고 단락 정렬 말뭉치에서 번역 쌍의 질을 향상시켰으며 베이스라인인 글로벌 워드 임베딩(global bilingual word embedding)과 비교하였을 때 2배의 성능을 확인하였다.