• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.600-612
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• 2013

In 2006, Zhang and Wang proposed a data hiding scheme based on Exploiting Modification Direction (EMD) to increase data hiding capacity. The major benefit of EMD is providing embedding capacity greater than 1 bit per pixel. Since then, many EMD-type data hiding schemes have been proposed. However, a serious disadvantage common to these approaches is that the embedded data is compromised when the embedding function is disclosed. Our proposed secure data hiding scheme remedies this disclosure shortcoming by employing an additional modulus function. The provided security analysis of our scheme demonstrates that attackers cannot get the secret information from the stegoimage even if the embedding function is made public. Furthermore, our proposed scheme also gives a simple solution to the overflow/underflow problem and maintains high embedding capacity and good stegoimage quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.945-958
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• 2017

This paper proposes a novel method of reversible data hiding in JPEG images. After analyzing the JPEG features, we provide a new algorithm of selecting appropriate blocks and coefficients to carry secret messages. Instead of embedding data into the histogram of all coefficients, we propose a strategy of ordered embedding to hide data by histogram shifts in several rounds. On the recipient end, secret messages can be exactly extracted, and the original JPEG image can be losslessly recovered. Experimental results show that high embedding rate can be achieved with limited distortions. Most importantly, the marked JPEG file generated by the proposed method requires less storage size than state-of-the-art works.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.347-353
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• 2022

In this paper, we propose a method that performs a text-video retrieval model by replacing video properties using captions. In general, the exisiting embedding-based models consist of both joint embedding space construction and the CNN-based video encoding process, which requires a lot of computation in the training as well as the inference process. To overcome this problem, we introduce a video-captioning module to replace the visual property of video with captions generated by the video-captioning module. To be specific, we adopt the caption generator that converts candidate videos into captions in the inference process, thereby enabling direct comparison between the text given as a query and candidate videos without joint embedding space. Through the experiment, the proposed model successfully reduces the amount of computation and inference time by skipping the visual processing process and joint embedding space construction on two benchmark dataset, MSR-VTT and VATEX.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.8
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• pp.1964-1981
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• 2012

In this paper a reversible data hiding scheme based on histogram shifting of host image blocks is presented. This method attempts to use full available capacity for data embedding by dividing the image into non-overlapping blocks. Applying histogram shifting to each block requires that extra information to be saved as overhead data for each block. This extra information (overhead or bookkeeping information) is used in order to extract payload and recover the block to its original state. A method to eliminate the need for this extra information is also introduced. This method uses maximum gap that exists between histogram bins for finding the value of pixels that was used for embedding in sender side. Experimental results show that the proposed method provides higher embedding capacity than the original reversible data hiding based on histogram shifting method and its improved versions in the current literature while it maintains the quality of marked image at an acceptable level.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.28 no.1
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• pp.119-133
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• 2015

Objective : Thread embedding acupuncture has become popular as a minimally invasive treatment for facial wrinkles and laxity. However, there is little published clinical practice guidelines. This study is to developing a specific procedure of thread embedding acupuncture for facial wrinkles and laxity. Method : We reviewed and summarized 6 studies on thread embedding acupuncture for facial wrinkles and laxity. And, four practitioners who have more than four year of clinical experience and one hundred of cases were participated in developing a thread embedding acupuncture procedure for facial wrinkles and laxity. Result and conclusion : We developed a thread embedding acupuncture procedure for facial wrinkles and laxity which consists of correction of lower jaw, facial laxity, nasolabial fold and eye wrinkles.

• 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.

• 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 KIISE:Computing Practices and Letters
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• v.9 no.1
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• pp.70-76
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• 2003

Digital watermarking is a technique embedding hidden information into multimedia data imperceptibly such as images and sounds. Generally an original image is transformed and coded watermark data is embedded in frequency domain watermarking models. In this paper, We propose a new data embedding method using Fresnel transform. A watermark image is fresnel-transformed and the intensity of transformed pattern is embedded into original image. Our watermarking model has the flexibility In data embedding. It is possible to get many embedding patterns from a single watermark image by using various distance parameters with Fresnel transform. All kinds of image models such af shape, letter and photo ran be used as a watermark data. The watermarking experiments were conducted to show the validity of the proposed method, and the results show that our method has the robustness against lossy compression, filtering and geometric transformation.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.389-399
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• 2021

In recent years, word embedding has been a popular field of natural language processing research and a skip-gram has become one successful word embedding method. It assigns a word embedding vector to each word using contexts, which provides an effective way to analyze text data. However, due to the limitation of vector space model, primary word embedding methods assume that every word only have a single meaning. As one faces multi-sense words, that is, words with more than one meaning, in reality, Neelakantan (2014) proposed a multi-sense skip-gram (MSSG) to find embedding vectors corresponding to the each senses of a multi-sense word using a clustering method. In this paper, we propose a modified method of the MSSG to improve statistical accuracy. Moreover, we propose a data-adaptive choice of the number of clusters, that is, the number of meanings for a multi-sense word. Some numerical evidence is given by conducting real data-based simulations.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1668-1669
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• 2011

본 논문에서는 Pogo Pin의 신호 전달 특성을 Ansys사의 Full wave simulation tool(HFSS)를 사용하여 분석하였고, 측정을 위해서 필요한 interface(Guide PCB)의 특성은 2-port de-embedding 방법을 이용하여 제거하였다. Guide PCB의 특성이 제거된 Pogo Pin만의 시뮬레이션 결과와 circuit simulator인 Agilent사의 ADS를 사용하여 Guide PCB의 특성을 de-embedding한 결과를 비교 검증하였고, Pogo Pin의 시뮬레이션 결과와 PCB의 특성을 de-embedding한 결과가 0~8 GHz까지 일치하는 것을 확인하였다.