• 대한약침학회지
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• 제6권3호
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• pp.15-21
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• 2003

Background : This study focuses on the new acupuncture method of embedding method which inserts a substance on the acupuncture points for continuous stimulation. Clinical applications and cautions were examined through literary investigations. Results : Based on the literary consideration of embedding method, the following results were obtained : 1. Embedding method is a combination of traditional and embedding technique to provide longer duration of stimulation on the acupuncture points. 2. To administer the embedding method, one needs to utilize a embedding thread besides acupuncture apparatus. Sheep gut is commonly used in China and the surgical thread is the choice in Korea. 3. Embedding method may vary from the patient to patient, depending on the nature and location of the illness. Piercing, embedding, and tying are some of the possibilities. 4. Embedding method may have different arrangement of threads based on the choice of usage. 5. Embedding method is effective for various chronic illnesses such as aches, functional diseases, and the diseases of internal organs. 6. When using the embedding methods, cautions against infection and side effects due to strong stimulation are mandatory.

• 대한한의학원전학회지
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• 제32권1호
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• pp.61-74
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• 2019

Objectives : The purpose of this study is to help select an appropriate word embedding method when analyzing East Asian traditional medicine texts as data. Methods : Based on prescription data that imply traditional methods in traditional East Asian medicine, we have examined 4 count-based word embedding and 2 prediction-based word embedding methods. In order to intuitively compare these word embedding methods, we proposed a "prescription generating game" and compared its results with those from the application of the 6 methods. Results : When the adjacent vectors are extracted, the count-based word embedding method derives the main herbs that are frequently used in conjunction with each other. On the other hand, in the prediction-based word embedding method, the synonyms of the herbs were derived. Conclusions : Counting based word embedding methods seems to be more effective than prediction-based word embedding methods in analyzing the use of domesticated herbs. Among count-based word embedding methods, the TF-vector method tends to exaggerate the frequency effect, and hence the TF-IDF vector or co-word vector may be a more reasonable choice. Also, the t-score vector may be recommended in search for unusual information that could not be found in frequency. On the other hand, prediction-based embedding seems to be effective when deriving the bases of similar meanings in context.

• 지식경영연구
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• 제21권1호
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• pp.99-116
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• 2020

Text is the most widely used means of exchanging or expressing knowledge and information in the real world. Recently, researches on structuring unstructured text data for text analysis have been actively performed. One of the most representative document embedding method (i.e. doc2Vec) generates a single vector for each document using the whole corpus included in the document. This causes a limitation that the document vector is affected by not only core words but also other miscellaneous words. Additionally, the traditional document embedding algorithms map each document into only one vector. Therefore, it is not easy to represent a complex document with interdisciplinary subjects into a single vector properly by the traditional approach. In this paper, we introduce a multi-vector document embedding method to overcome these limitations of the traditional document embedding methods. After introducing the previous study on multi-vector document embedding, we visually analyze the effects of the multi-vector document embedding method. Firstly, the new method vectorizes the document using only predefined keywords instead of the entire words. Secondly, the new method decomposes various subjects included in the document and generates multiple vectors for each document. The experiments for about three thousands of academic papers revealed that the single vector-based traditional approach cannot properly map complex documents because of interference among subjects in each vector. With the multi-vector based method, we ascertained that the information and knowledge in complex documents can be represented more accurately by eliminating the interference among subjects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권5호
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• pp.2723-2740
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• 2017

Steganographic schemes which are based on minimizing an additive distortion function defined the overall impacts after embedding as the sum of embedding costs for individual image element. However, mutual impacts during embedding are often ignored. In this paper, an adaptive JPEG steganographic method based on weight distribution for embedding costs is proposed. The method takes mutual impacts during embedding in consideration. Firstly, an analysis is made about the factors that affect embedding fluctuations among JPEG coefficients. Then the Distortion Update Strategy (DUS) of updating the distortion costs is proposed, enabling to dynamically update the embedding costs group by group. At last, a kind of adaptive JPEG steganographic algorithm is designed combining with the update strategy and well-known additive distortion function. The experimental result illustrates that the proposed algorithm gains a superior performance in the fight against the current state-of-the-art steganalyzers with high-dimensional features.

• 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.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제10권11호
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• pp.483-490
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• 2021

인공신경망을 이용해서 기존 곡을 학습시키고 새로운 곡을 생성하기 위해서는 전처리 과정으로 곡을 신경망이 인식할 수 있는 숫자로 변환해야 하며, 지금까지는 원-핫 인코딩이 사용되어 왔다. 본 논문에서는 음표 임베딩과 마디 임베딩을 제안하고 기존의 원-핫 인코딩과 성능을 비교하였다. 성능비교는 어떤 방식이 작곡가가 작곡한 곡과 유사한 곡을 생성하는지를 정량적 평가에 근거해서 수행하였으며, 평가방법으로는 자연어 처리 분야에서 사용되는 정량적 평가 방법들을 이용하였다. 평가결과 마디 임베딩으로 생성한 곡이 가장 좋았으며 그 다음으로 음표 임베딩이 좋았다. 이는 본 논문에서 제안한 음표 임베딩과 마디 임베딩이 원-핫 인코딩보다 작곡가가 작곡한 곡과 유사한 곡을 생성한 것으로서 의의가 있다.

• 한국멀티미디어학회논문지
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• 제13권1호
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• pp.76-82
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• 2010

리버서블 워터마킹은 디지털 영상에 정보를 은닉하고 인증된 상대에게만 은닉된 정보를 복호화하고 원래의 상태로 영상을 복구하는 방법이다. 본 논문에서는 히스토그램 이동을 이용한 고용량 리버서블 워터마킹을 제안한다. 본 논문에서는 높은 삽입량을 위하여 영상을 $2{\times}2$ 블록으로 분할하고, 각 블록에 수평, 수직, 대각에 대한 화소쌍을 이용하여 가장 빈도가 높은 최대 삽입공간을 찾는다. 최대 삽입공간을 포함하는 위치맵을 이용하여 오버플로우와 언더플로우를 제거하여, 반복적인 워터마크 삽입을 통해 삽입량을 증가시킨다. 실험을 통하여 제안한 방법이 기존의 리버서블 워터마킹 방법과 비교하여 좋은 화질과 높은 삽입량을 나타냄을 확인하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2003년도 춘계종합학술대회
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• pp.505-508
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• 2003

본 논문에서는 SC-CNN의 특성을 이용한 임베딩 구동 카오스 동기화 방법을 소개한다. SC-CNN은 Chua 회로의 미분방정식에서의 세가지 상태변수중 전류성분과 같이 동기화와 신호 합성에 어려운 상태변수를 전압성분으로 분리하여 다룰 수 있는 방법을 제공하고 있다. 여기서 지금까지 이용되오던 결합 동기나 구동동기화의 방법에 새로운 임베딩 구동 동기방식을 제안한다. 제안하는 Embedding Drive Synchronization(임베딩 구동동기)은 구동동기에서 미분상태변수를 완전히 대체하는 것이 아닌 한 성분만을 대체하여 구성되며 그 타당성을 검증하였다.

• 방송공학회논문지
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• 제12권2호
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• pp.112-119
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• 2007

Reversible data embedding theory has marked a new epoch for data hiding and information security. Being reversible, the original data and the embedded data as well should be completely restored. Difference expansion transform is a remarkable breakthrough in reversible data hiding scheme. The difference expansion method achieves high embedding capacity and keeps the distortion low. This paper shows that the difference expansion method with simplified location map, and new expandability and changeability can achieve more embedding capacity while keeping the distortion almost the same as the original expansion method.

• 대한기계학회논문집B
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• 제22권7호
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• pp.1030-1040
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• 1998

One of the main unresolved issues in large-eddy simulation(LES) of wall-bounded turbulent flows is the requirement of high spatial resolution in the near-wall region, especially in the spanwise direction. Such high resolution required in the near-wall region is generally used throughout the computational domain, making simulations of high Reynolds number, complex-geometry flows prohibitive. A grid-embedding strategy using a nonconforming spectral domain-decomposition method is proposed to address this limitation. This method provides an efficient way of clustering grid points in the near-wall region with spectral accuracy. LES of transitional and turbulent channel flow has been performed to evaluate the proposed grid-embedding technique. The computational domain is divided into three subdomains to resolve the near-wall regions in the spanwise direction. Spectral patching collocation methods are used for the grid-embedding and appropriate conditions are suggested for the interface matching. Results of LES using the grid-embedding strategy are promising compared to LES of global spectral method and direct numerical simulation. Overall, the results show that the spectral domain-decomposition grid-embedding technique provides an efficient method for resolving the near-wall region in LES of complex flows of engineering interest, allowing significant savings in the computational CPU and memory.