• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.561-563
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• 2019

This paper proposes a watermarking method for copyright protection of images used in VR. The Embedding method is that finds the point through the SIFT feature points, inserts the watermark by using DWT and QIM on the surrounding area. The objective image to extract the embedded watermark is the projected image and its method finds the SIFT feature points and extracts watermark data from its surrounding areas after correction by using inverse process of matching and projection in the VR image production process. By comparing the NCC and BER between the extracted watermark and the inserted watermark, the watermark is determined by accumulating the watermark having a threshold value or more. This is confirmed by comparing with a conventional method.

• Journal of Korea Multimedia Society
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• v.16 no.5
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• pp.577-590
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• 2013

Shamir's (k,n)-threshold secret sharing scheme is not secure against cheating by attacker because the signature of participants is omitted. To prevent cheating, many schemes have been proposed, and a proactive secret sharing is one of those. The proactive secret sharing is a method to update shares in the secret sharing scheme at irregular intervals. In this paper, a proactive image secret sharing scheme over $GF(2^8)$ is proposed for the first time. For the past 30 years, Galois field operation is widely used in order to perform the efficient and secure bit operation in cryptography, and the proposed scheme with update phase of shadow image over $GF(2^8)$) at irregular intervals provides the lossless and non-compromising of secret image. To evaluate security and efficiency of images (i.e. cover and shadow images) distortion between the proposed scheme and the previous schemes, embedding capacity and PSNR are compared in experiments. The experimental results show that the performances of the embedding capacity and image distortion ratio of the proposed scheme are superior to the previous schemes.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.1-14
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• 2019

Because of the characteristics of game software, it is important to quickly identify and reflect users' needs into game software after its launch. However, most sites such as the Google Play Store, where users can download games and post reviews, provide only very limited and ambiguous classification categories for game reviews. Therefore, in this paper, we develop an automatic classification system for game reviews that categorizes reviews into categories that are clearer and more useful for game providers. The developed system converts words in reviews into vectors using word2vec, which is a representative word embedding model, and classifies reviews into the most relevant categories by measuring the similarity between those vectors and each category. Especially, in order to choose the best similarity measure that directly affects the classification performance of the system, we have compared the performance of three representative similarity measures, the Euclidean similarity, cosine similarity, and the extended Jaccard similarity, in a real environment. Furthermore, to allow a review to be classified into multiple categories, we use a threshold-based multi-category classification method. Through experiments on real reviews collected from Google Play Store, we have confirmed that the system achieved up to 95% accuracy.

• Composites Research
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• v.18 no.5
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• pp.1-8
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• 2005

Among many fabrication methods of composite materials, filament winding is the most effective method for fabricating axis-symmetric structures such as pressure tanks and pipes. Filament wound pressure tanks are under high internal pressure during the operation and it has the complexity in damage mechanisms and failure modes. For this reason, it is necessary to monitor the tank through its operation as well as whole fabrication process. A large number of sensors must be embedded into multi points of the tank from its fabrication step for monitoring the whole tank. Fiber optic sensors, especially fiber Bragg grating(FBG) sensors are widely used for various applications because of good multiplexing capabilities. However, we need to develop the embedding technique of FBG sensors into harsh inner environment of the tank far the successful embedment. In this paper, we studied the embedding technique of a number of FBG sensors into filament wound pressure tanks considering multiplexing.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.103-123
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• 1999

Input filtering as a preprocessing method is so much crucial to get good performance in time series forecasting. There are a few preprocessing methods (i.e. ARMA outputs as time domain filters, and Fourier transform or wavelet transform as time-frequency domain filters) for handling time series. Specially, the time-frequency domain filters describe the fractal structure of financial markets better than the time domain filters due to theoretically additional frequency information. Therefore, we, first of all, try to describe and analyze specially some issues on the effectiveness of different filtering methods from viewpoint of the performance of a neural network based forecasting. And then we discuss about neural network model architecture issues, for example, what type of neural network learning architecture is selected for our time series forecasting, and what input size should be applied to a model. In this study an input selection problem is limited to a size selection of the lagged input variables. To solve this problem, we simulate on analyzing and comparing a few neural networks having different model architecture and also use an embedding dimension measure as chaotic time series analysis or nonlinear dynamic analysis to reduce the dimensionality (i.e. the size of time delayed input variables) of the models. Throughout our study, experiments for integration methods of joint time-frequency analysis and neural network techniques are applied to a case study of daily Korean won / U. S dollar exchange returns and finally we suggest an integration framework for future research from our experimental results.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.556-564
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• 2003

A Star and Pancake graph also have such a good property of a hypercube and have a low network cost than the hypercube. A Macro-star graph which has the star graph as a basic module has the node symmetry, the maximum fault tolerance, and the hierarchical decomposition property. And, it is an interconnection network which improves the network cost against the Star graph. In this paper, we propose a method to embed between Star graph, Pancake graph, and Macro-star graph using the edge definition of graphs. We prove that the Star graph $S_n$ can be embedded into Pancake graph $P_n$ with dilation 4, and Macro-star graph MS(2,n) can be embedded into Pancake graph $P_{2n＋1}$ with dilation 4. Also, we have a result that the embedding cost, a Pancake graph can be embedded into Star and Macro-star graph, is O(n).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.62-71
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• 2006

Development of an artificial reverberation algorithm with low memory requirements has been an issue of importance in applications such as mobile multimedia devices. One possible solution to this problem is to embed a time-varying all-pass filter to the feedback loop of the comb filter. In this paper, theoretical and perceptual analyses of reverberators embedding time-varying all-pass filters are presented. The analyses are to iud a perceptually acceptable degree of phase variation by the all-pass filter. Based on the analyses, we propose a new methodology of designing reverberators embedding time-varying all-pass filters. Through the subjective tests, we showed that, even with smaller memory, the proposed method is capable of providing perceptually comparable sound quality to the conventional methods involving time-invariant parameters.

• The Journal of the Acoustical Society of Korea
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• v.30 no.6
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• pp.303-307
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• 2011

This paper describes an audio watermarking using Quantization Index Modulation (QIM) on significant peaks in frequency domain. The audio signal is broken up into L samples length frames with non-overlapping and rectangular window. The zero-crossing rate of each frame is calculated for decision whether it is proper to be watermarked or not. If the frame is legitimate, frequency magnitude response is computed by discrete Fourier transform. For the QIM, we set the quantization step size based on maximum value of frequency magnitude response and select n significant peaks with w samples around them in frequency domain, totally $n{\times}(w+1)$ samples. Finally, watermark embedding is performed. Decoder extract watermarks based on Euclidean distance, that is a blind detection. The proposed method is robust against many attacks of watermark benchmark.

• Journal of Korea Multimedia Society
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• v.9 no.9
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• pp.1173-1183
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• 2006

Matrix-star, Pancake, and RFM graphs have such a good property of Star graph and a lower network cost than Hypercube. Matrix-star graph has Star graph as a basic module and the node symmetry, the maximum fault tolerance, and the hierarchical decomposition property. Also it is an interconnection network that improves the network cost against Star graph. In this paper, we propose a method to embed among Matrix-star Pancake, and RFM graphs using the edge definition of graphs. We prove that Matrix-star $MS_{2,n}$ can be embedded into Pancake $P_{2n}$ with dilation 4, expansion 1, and $RFM_{n}$ graphs can be embedded into Pancake $P_{n}$ with dilation 2. Also, we show that Matrix-star $MS_{2,n}$ can be embedded into the $RFM_{2n}$ with average dilation 3.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.54-60
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• 1996

In most pattern recognition and image understanding applications, images are degraded by noise and other distortions. Therefore, it is more relevant to decide how similar two objects are rather than to decide whether the two are exactly the same. In this paper, we propose a method for recognizing degraded symbols using a distance measure between two graphs representing the symbols. a symbol is represented as a graph consisting of nodes and edges based on the run graph concept. The graph is then transformed into a reference model graph with production rule containing the embedding transform. The symbols are recognized by using the distance measure which is estimated by using the number of production rules used and the structural homomorphism between a transformed graph and a model graph. the proposed approach is applies to the recognition of non-note musical symbols and the result are given.