• Smart Media Journal
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• v.10 no.1
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• pp.16-24
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• 2021

The exiting word embedding methodology such as word2vec represents words, which only occur in the raw training corpus, as a fixed-length vector into a continuous vector space, so when mapping the words incorporated in the raw training corpus into a fixed-length vector in morphologically rich language, out-of-vocabulary (OOV) problem often happens. Even for sentence embedding, when representing the meaning of a sentence as a fixed-length vector by synthesizing word vectors constituting a sentence, OOV words make it challenging to meaningfully represent a sentence into a fixed-length vector. In particular, since the agglutinative language, the Korean has a morphological characteristic to integrate lexical morpheme and grammatical morpheme, handling OOV words is an important factor in improving performance. In this paper, we propose parallel Tri-LSTM sentence embedding that is robust to the OOV problem by extending utilizing the morphological information of words into sentence-level. As a result of the sentiment analysis task with corpus in Korean, we empirically found that the character unit is better than the morpheme unit as an embedding unit for Korean sentence embedding. We achieved 86.17% accuracy on the sentiment analysis task with the parallel bidirectional Tri-LSTM sentence encoder.

• Journal of Korea Multimedia Society
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• v.17 no.1
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• pp.34-42
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• 2014

In this paper an embedding algorithm based on commute time is implemented by organizing patches according to the graph-based metric, and its performance is analyzed by comparing with the results of principal component analysis embedding. It is usual that the dimensionality reduction be done within some acceptable approximation error. However this paper shows the proposed manifold embedding method generates the intrinsic geometry corresponding to the signal despite severe approximation error, so that it can be applied to the areas such as pattern classification or machine learning.

• Journal of Acupuncture Research
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• v.31 no.4
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• pp.195-204
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• 2014

Objectives : The purpose of this study is to report the improvement in patients with knee pain by the instrumentality of needle-embedding therapy. Methods : We treated 5 patients who have a disease related with osteoarthitis of the knee by needle-embedding therapy combined with Korean medical treatment. We checked numeric rating scale(NRS) and Western Ontario and McMaster Universities index(WOMAC index). Results : NRS and WOMAC index were decreased at all cases. Conclusions : This study shows needle-embedding therapy has a medical effect when applied on osteoarthritis of the knee.

• Journal of the Korea Furniture Society
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• v.10 no.2
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• pp.1-8
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• 1999

The use of structural wood based panels like plywood, OSB in many applications involves the use of nails, and data on the performance of panel-nail connection are needed for design and comparative purpose. This study was carried out to develop basic information on nail performance(withdrawal, embedding, nailhead push through) with water absorption in plywood and OSB. In withdrawal resistance test, initial stiffness of plywood performed better than OSB in 24hr soaked condition. The soaked condition reduced average nail withdrawal resistance value about 46% (12d mail), 53%(8d nail) in OSB, 17%(12d mail), 24%(8d mail) in plywood. The nail embedding strength of plywood also performed better than that of OSB and retention value(wet strength/dry strength) yielded similar in each nail types. The nail head push through capacity of OSB was higher than that of plywood in dry condition, but equal or lower in soaked condition. Therefore, critical consideration about structural panels is required in moist applications. The average values of nail withdrawal, nail embedding strength and nail head push through resistance of tested materials meet the minimum requirement of various specification and standards.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.891-902
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• 2012

Reversible data hiding scheme is a form of steganography in which the secret embedding data can be retrieved from a stego image for the purpose of identification, copyright protection and making a covert channel. The reversible data hiding should satisfy that not only are the distortions due to artifacts against the cover image invisible but also it has large embedding capacity as far as possible. In this paper, we propose a robust reversible data hiding scheme by exploiting the differences between a center pixel and its neighboring pixels in each sub-block of the image to embed secret data into extra space. Moreover, our scheme enhances the embedding capacity and can recover the embedded data from the stego image without causing any perceptible distortions to the cover image. Simulation results show that our proposed scheme has lower visible distortions in the stego image and provides robustness to geometrical image manipulations, such as rotation and cropping operations.

• Journal of Science and Technology Studies
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• v.11 no.1
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• pp.1-29
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• 2011

The purpose of this study is to develop a theoretical framework to analyze the social processes of embedding new technologies, among others, green technologies, in society, and based on this, to identify problems and challenges in introducing and assimilating biogas technologies in local communities in Korea. Chapter Two strives to develop a framework to analyze the social processes of embedding new technologies in society. A couple of key concepts such as technology community, technology learning and technology politics are introduced and discussed. Chapter Three and Four examine the problems arising from the social processes of embedding biogas plant technologies in local communities in Korea and tries to suggest policy options to tackle these problems.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.974-986
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• 2016

Reversible image watermarking, a type of digital data hiding, is capable of recovering the original image and extracting the hidden message with precision. A number of reversible algorithms have been proposed to achieve a high embedding capacity and a low distortion. While numerous algorithms for the achievement of a favorable performance regarding a small embedding capacity exist, the main goal of this paper is the achievement of a more favorable performance regarding a larger embedding capacity and a lower distortion. This paper therefore proposes a reversible data hiding algorithm for which a novel piecewise 2D auto-regression (P2AR) predictor that is based on a rhombus-embedding scheme is used. In addition, a minimum description length (MDL) approach is applied to remove the outlier pixels from a training set so that the effect of a multiple linear regression can be maximized. The experiment results demonstrate that the performance of the proposed method is superior to those of previous methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3286-3301
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• 2014

Jung and Yoo proposed the first image interpolation-based reversible data hiding algorithm. Although their algorithm achieved superior interpolation results, the embedding capacity was insufficient. Lee and Huang proposed an improved algorithm to enhance the embedding capacity and the interpolation results. However, these algorithms present limitations to magnify the original image to any resolution and pixels in the boundary region of the magnified image are poorly manipulated. Furthermore, the capacity and the image quality can be improved further. This study modifies the pixel mapping scheme and adopts a bilinear interpolation to solve boundary artifacts. The modified reference pixel determination and an optimal pixel adjustment process can effectively enhance the embedding capacity and the image quality. The experimental results show our proposed algorithm achieves a higher embedding capacity under acceptable visual distortions, and can be applied to a magnified image at any resolution. Our proposed technique is feasible in reversible data hiding.

• Smart Media Journal
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• v.7 no.4
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• pp.24-29
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• 2018

Text analysis technique for natural language processing in deep learning represents words in vector form through word embedding. In this paper, we propose a method of constructing a document vector and classifying it into spam and normal text message, using word embedding and deep learning method. Automatic spacing applied in the preprocessing process ensures that words with similar context are adjacently represented in vector space. Additionally, the intentional word formation errors with non-alphabetic or extraordinary characters are designed to avoid being blocked by spam message filter. Two embedding algorithms, CBOW and skip grams, are used to produce the sentence vector and the performance and the accuracy of deep learning based spam filter model are measured by comparing to those of SVM Light.

• Journal of Sasang Constitutional Medicine
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• v.34 no.4
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• pp.49-56
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• 2022

Objectives The purpose of this study is to compare the changes before and after constitutional acupuncture treatment in soyangin who received embedding therapy for wrinkle improvement. Methods A retrospective study reviewing medical records was conducted. The patient was classified as a Soyangin by a specialist based on K-PRISM, personality, appearance, voice and usual symptoms. Records on the degree of wrinkles, postoperative symptoms, and patient satisfaction were reviewed. Results The patient's wrinkles were improved after the embedding therapy. After therapy symptoms were fever, flushing, and burning sensation. After acupuncture, these symptoms were reduced. Patient satisfaction increased after constitutional acupuncture treatment. Conclusion As a result of embedding treatment in Soyangin patients, there was an effect of wrinkle improvement. As a result of constitutional acupuncture treatment, anxiety and stress were reduced before the procedure, and symptoms of heat, burning, and flushing were reduced after the procedure.